SIRIS-Lab/citation-parser-SPAN · Datasets at Hugging Face

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intent is grounded in the real world the speaker and listener inhabit together. Commu- nicative intents can also be about abstract worlds, e.g. bank accounts, computer ﬁle systems, or a purely hypothetical world in the speaker’s mind. Linguists distinguish communicative intent from conventional (orstanding ) meaning (Quine, 1960; Grice, 1968). The conventional meaning of an expression (word, phrase, sentence) is what is con- stant across all of its possible contexts of use. Con- ventional meaning is an abstract object that repre- sents the communicative potential of a form, given the linguistic system it is drawn from. Each lin- guistic system (say, English) provides a relation CES, which contains pairs (e; s)of expres- sions eand their conventional meanings s.6The ﬁeld of linguistic semantics provides many com- peting theories of what conventional meanings s look like. For our purposes, we don’t need to select among these theories; all we assume is that conven- tional meanings must have interpretations, such as a means of testing them for truth against a model of the world. Thus, like the meaning relation M,C connects language to objects outside of language. 5In spoken languages, the primary articulators are the com- ponents of the vocal tract. In signed languages, they are principally the hands and face. 6We abstract away here from the facts that linguistic sys- temsCchange over time and are only incompletely shared among different speakers. They are stable enough to function as rich signals to communicative intent.Returning to the meaning relation Mfrom above, it is best understood as mediated by the relation C of a linguistic system shared between two inter- locutors. The speaker has a certain communica- tive intent i, and chooses an expression ewith a standing meaning swhich is ﬁt to express iin the current communicative situation. Upon hearing e, the listener then reconstructs sand uses their own knowledge of the communicative situation and their hypotheses about the speaker’s state of mind and intention in an attempt to deduce i. This active participation of the listener is cru- cial to human communication (Reddy, 1979; Clark, 1996). For example, to make sense of (8) and (9) (from Clark, 1996, p.144), the listener has to calcu- late that Napoleon refers to a speciﬁc pose (hand inside coat ﬂap) or that China trip refers to a person who has recently traveled to China. (8) The photographer asked me to do a Napoleon for the camera. 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prose. (Gary Marcus) (5) Though BERT passed the lab’s common-sense test, ma- chines are still a long way from an artiﬁcial version of a human’s common sense. (Oren Etzioni) However, there are plenty of instances where the popular press gets it wrong, such as (6) from the B2C website,2apparently based on the Google Blog post about BERT and search, which includes numerous statements like (7).3 (6) BERT is a system by which Google’s algorithm uses pattern recognition to better understand how human beings communicate so that it can return more relevant results for users. (7) Here are some of the examples that showed up our evaluation process that demonstrate BERTs ability to understand the intent behind your search. In sum, it is not clear from our academic literature whether all authors are clear on the distinction be- tween form and meaning, but it is clear that the way we speak about what neural LMs are doing is misleading to the public. Part of the reason for this tendency to use impre- cise language may well be that we do not yet fully understand what exactly it is about language that the large LMs come to implicitly represent. Their success, however, has sparked a subﬁeld (‘BERTol- ogy’) that aims to answer this question. The methodology of probing tasks (e.g. Adi et al., 2017; Ettinger et al., 2018) has been used to show that 1https://www.nytimes.com/2018/11/18/technology/artific ial-intelligence-language.html, accessed 2019/12/04 2https://www.business2community.com/seo/what-t o-do-about-bert-googles-recent-local-algorithm-updat e-02259261, accessed 2019/12/04 3https://www.blog.google/products/search/search-langu age-understanding-bert/, accessed 2019/12/04large LMs learn at least some information about phenomena such as English subject-verb agreement (Goldberg, 2019; Jawahar et al., 2019), constituent types, dependency labels, NER, and (core) seman- tic role types (again, all in English) (Tenney et al., 2019).4Hewitt and Manning (2019) ﬁnd informa- tion analogous to unlabeled dependency structures in the word vectors provided by ELMo and BERT (trained on English). And of course it is well estab- lished that vector-space representations of words pick up word classes, both syntactic (POS, e.g. Lin et al., 2015) and semantic (lexical similarity, e.g. Rubenstein and Goodenough, 1965; Mikolov et al., 2013). Others have looked more closely at the success of the large LMs on apparently meaning sensitive tasks and found that in fact, far from doing the “rea- soning” ostensibly required to complete the tasks, they were instead simply more effective at leverag- ing artifacts in the data than previous approaches. 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frameworks and regulations. Only half of countries have standards for school principals that explicitly address collaboration. \| School principals are expected to fulfil various leadership roles .....................................25 \| \|-------------------------------------------------------------------------------------------------------------------------------------------------------\| \| The impact of school principals can be significant...............................................................31 \| \| Leadership standards can guide action and certification...................................................39 \| \| Conclusion ........................................................................................................................................42 \| S chool leadership involves steering educational institutions to achieve their goals, such as improving student learning and fostering a positive school environment (UNESCO, 2018). School principals bear responsibilities such as shaping an educational vision, aligning teaching practices with standards and student needs, encouraging professional development and collaboration, and ensuring student well-being and safety. Such responsibilities require them to both manage and lead under resource constraints and frequent education policy shifts. Principals have to address the needs of diverse student populations; respond to the exigencies of digital technology (UNESCO, 2023b); and deal with emergencies such as displacement (UNESCO, 2019), natural disasters and health crises like COVID-19 (Longmuir, 2023). They need to deal with community expectations and navigate accountability pressures (Lee, 2016). In some contexts, decentralized arrangements empower principals to take the action they deem appropriate to address problems. Principals also increasingly have access to better management tools, regulatory frameworks and communication channels. These resources can develop their capacity to build trust and effective collaborative relationships with staff, students, parents and community stakeholders for joint action (UNESCO, 2023a). This chapter examines principals' roles, with an emphasis on primary and secondary education. The term 'principal' refers to the individual responsible for leading a school, either independently or within an administrative organization like a board or council, overseeing its guidance, organization and operation ( Box 2.1 ). Their roles are generally described as expectations, which are outlined in various government texts. The chapter also examines the impact principals have on educational outcomes and how this is mediated by individual and governance characteristics. Finally, the chapter looks at how this understanding is being codified in leadership standards. ## SCHOOL PRINCIPALS ARE EXPECTED TO FULFIL VARIOUS LEADERSHIP ROLES Principals have historically been seen mainly as administrators focused on tasks like setting budgets and timetables. But they are increasingly expected to take on roles with broader impact. 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deviation of the distribution of the number of records in that domain. This facilitates the identification of niches where there is clear alignment with NACE codes between S&T domains (for relative frequencies close to and above 100%, such as Agrifood with NACE code 10 ‘Manufacture of food products’), in relation to mappings where S&T production is more evenly spread. As shown in Annex 1, the IPC to NACE v2 concordance table contains mappings 72 An IPC symbol is the specific full taxonomic classification associated with a patent record.at different granularity levels, namely two-digit and three-digit NACE codes. Thus, no proper con- cordance table-based mapping between the final two-digit summary results of Part 2, on one side, and the IPC patent classification, on the other, can be fully produced. The results of the S&T domains to NACE mapping carried out via patents is presented in Annex 8 for each EaP country. On expert assessment, the results of this mapping exercise as expressed by pairs of S&T domains and two-digit NACE codes seems satisfactory. The presence of multiple assignations, that is, the appearance of a given NACE code in several S&T specialisation domains, as well as some low rel- ative frequency figures, are an indication of the natural transversality of and/or overlap between some S&T domains, which have the potential to impact knowledge-based development in several sectors. Steps 3-5 – Quantified mapping of S&T domains to E&I domains, via scientific publications In the work presented in Part 3, EaP scientific publications were semantically analysed, togeth- er with patents and Horizon 2020 projects, and classified into a list of 14 S&T domains, which emerged directly from the textual content of the analysed records via topic modelling. Here, the taxonomic classification of publications (by far the largest data set analysed in this work) via ASJC subject fields (ASJC – All Science Journal Classification, the taxonomy adopted by Elsevi- er’s Scopus) is exploited to find a link between the S&T domains uncovered in Part 2 and the NACE sectors which underpin the E&I domains identified in Part 2. To do so, ASJC subject fields were first mapped to NABS and then official NABS to NACE concordance tables were exploited to achieve the ASJC to NACE proposed mapping. The NABS to NACE concordance table is presented in Annex 2. 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Official data on road traffic crashes capture only 56 percent of fatal-ities in low- and middle-income countries, on average. 1 Crash reports exist, yet they are buried in piles of paper or collected by private operators instead of being converted into useful data or disseminated to the people who need the information to make policy decisions. In Kenya, where official figures under - report the number of fatalities b y a factor of 4.5,2 the rapid expansion of mobile phones and social media provides an opportunity to leverage commuter reports on traffic conditions as a potential source of data on road traffic crashes. Big data mining, combined with digitization of official paper records, has demonstrated how dispa-rate data can be leveraged to inform urban spatial analysis, planning, and management. 3 Researchers worked in close collaboration with the National Police Service to digitize more than 10,000 situation reports spanning from 2013 to 2020 from the 14 police stations in Nairobi to create the first digital and geolocated administrative dataset of individual crashes in the city. They combined administrative data with data crowdsourced using a software appli-cation for mobile devices and short message service (SMS) traffic platform, Ma3Route, which has more than 1.1 million subscribers in Kenya. They analyzed 870,000 transport-related tweets submitted between 2012 and 2020 to identify and geolocate 36,428 crash reports by developing and improving natural lan-guage processing and geoparsing algorithms. 4 To verify the accuracy of crowdsourced reports and the efficiency of the algorithms, the team dis-patched a motorcycle delivery company to the site of the reported crash minutes after each new crash report was received for a subset of reports. In 92 per - cent of cases, a crash was verified to have occurred in the stated location or nearby. By combining these sources of data, researchers were able to identify the 5 percent of roads (crash black spots) where 50 percent of the road traffic deaths occur in the city (map S4.2.1). This exercise demonstrates that addressing data scarcity can transform an intractable problem into a more manageable one. In this case, investing in the safety of a 6,200-kilometer road network is intractable. Digitiz-ing and analyzing administrative data and variables on injuries and deaths can help to narrow down the locations and times of the day and week that are associated with the most severe crashes. 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this volume). Political activism - in Maasdorp's case, joining the Cambridge Socialist Society and the Cambridge Scientists' Anti- War Group - was not only a way to compensate for her invisibility and lack of recognition in professional science, but also an attempt to shape the political foundations of science. As Keeble explains, 'lateral thinking', that is, the practice of investigating alternative scientific roles ascribed to or assumed by women, as science educators, members of scientific organizations, and voluntary, unpaid scientific workers, is essential to recovering hidden historical figures like Maasdorp. This must, however, be coupled with a recognition of the fact that, as a member of the white colonial elite in South Africa and Rhodesia, Maasdorp was nevertheless able to acquire a certain degree of visibility that was systematically denied to Black women. Nuala Proinnseas Caomhánach's discussion of Lynn Margulis' scientific career as a 'rebel' evolutionary biologist further illuminates the struggles women faced inside and outside the laboratory and testifies to their willingness to challenge disciplinary and patriarchal boundaries. Combining insights from cell biology, ecology and geoscience, Margulis' much- maligned theory of evolution was as synthetic in its origin as the idea it propagated, namely that evolution had begun with microbes, not animals, and that symbiosis, not competition, had been its driving force. Although Margulis did manage to forge a relatively successful career in academia, her visibility was predicated on her ability to leverage the power of media and navigate all the risks such a process of exposure involved. As Caomhánach cogently points out, 'without the making of a persona, the scientist remains obscure and invisible'. In the case of women scientists - Rosalind Franklin being another xample - that invisibility was not only 'ascribed' by men, but it was also e sometimes 'curated' by them. The construction of a scientific persona in Margulis' case must also be seen against the background of American media's growing concern with science reporting in the 1960s- 1970s. As Caomhánach discusses, the process of becoming visible involved several layers of 'de- gendering' and 're- gendering'. Media reporting on Margulis replicated entrenched gender biases by attaching non- scientific attributes to her. Dismissed as a theorist because she was a woman, she eventually 'gain[ed] acceptance and … inclusion in the field' because of her image as a masculinized scientific rebel. The point then is that Margulis was able to control her image as an 'outsider' and	[ "this", "volume", ")", ".", "Political", "activism", "-", "in", "Maasdorp", "'s", "case", ",", "joining", "the", "Cambridge", "Socialist", "Society", "and", "the", "Cambridge", "Scientists", "'", "Anti-", " ", "War", "Group", "-", "was", "not", "only", "a", "way", "to", "compensate", "for", "her", "invisibility", "and", "lack", "of", "recognition", "in", "professional", "science", ",", "but", "also", "an", "attempt", "to", "shape", "the", "political", "foundations", "of", "science", ".", "As", "Keeble", "explains", ",", "'", "lateral", "thinking", "'", ",", "that", "is", ",", "the", "practice", "of", "investigating", "alternative", "scientific", "roles", "ascribed", "to", "or", "assumed", "by", "women", ",", "as", "science", "educators", ",", "members", "of", "scientific", "organizations", ",", "and", "voluntary", ",", "unpaid", "scientific", " ", "workers", ",", " ", "is", " ", "essential", " ", "to", " ", "recovering", " ", "hidden", " ", "historical", " ", "figures", " ", "like", "Maasdorp", ".", "This", "must", ",", "however", ",", "be", "coupled", "with", "a", "recognition", "of", "the", "fact", "that", ",", "as", "a", "member", "of", "the", "white", "colonial", "elite", "in", "South", "Africa", "and", "Rhodesia", ",", "Maasdorp", "was", "nevertheless", "able", "to", "acquire", "a", "certain", "degree", "of", "visibility", "that", "was", "systematically", "denied", "to", "Black", "women", ".", "\n\n", "Nuala", "Proinnseas", "Caomhánach", "'s", "discussion", "of", "Lynn", "Margulis", "'", "scientific", "career", "as", "a", "'", "rebel", "'", "evolutionary", "biologist", "further", "illuminates", "the", "struggles", "women", "faced", "inside", "and", "outside", "the", "laboratory", "and", "testifies", "to", "their", "willingness", " ", "to", " ", "challenge", " ", "disciplinary", " ", "and", " ", "patriarchal", " ", "boundaries", ".", " ", "Combining", "insights", "from", "cell", "biology", ",", "ecology", "and", "geoscience", ",", "Margulis", "'", "much-", " ", "maligned", "theory", "of", "evolution", "was", "as", "synthetic", "in", "its", "origin", "as", "the", "idea", "it", "propagated", ",", "namely", "that", "evolution", "had", "begun", "with", "microbes", ",", "not", "animals", ",", "and", "that", "symbiosis", ",", "not", "competition", ",", "had", "been", "its", "driving", "force", ".", "Although", "Margulis", "did", "manage", "to", "forge", "a", "relatively", "successful", "career", "in", "academia", ",", "her", "visibility", "was", "predicated", "on", "her", "ability", "to", "leverage", "the", "power", "of", "media", "and", "navigate", "all", "the", "risks", "such", "a", "process", "of", "exposure", "involved", ".", "As", "Caomhánach", "cogently", "points", "out", ",", "'", "without", "the", "making", "of", "a", "persona", ",", "the", "scientist", "remains", "obscure", "and", "invisible", "'", ".", "In", "the", "case", "of", "women", "scientists", "-", "Rosalind", "Franklin", "being", "another", "xample", "-", "that", "invisibility", "was", "not", "only", "'", "ascribed", "'", "by", "men", ",", "but", "it", "was", "also", "e", "sometimes", "'", "curated", "'", "by", "them", ".", "\n\n", "The", " ", "construction", " ", "of", " ", "a", " ", "scientific", " ", "persona", " ", "in", " ", "Margulis", "'", " ", "case", " ", "must", " ", "also", "be", " ", "seen", " ", "against", " ", "the", " ", "background", " ", "of", " ", "American", " ", "media", "'s", " ", "growing", " ", "concern", "\n\n", "with", " ", "science", " ", "reporting", " ", "in", " ", "the", " ", "1960s-", " ", "1970s", ".", " ", "As", " ", "Caomhánach", " ", "discusses", ",", "the", "process", "of", "becoming", "visible", "involved", "several", "layers", "of", "'", "de-", " ", "gendering", "'", "and", " ", "'", "re-", " ", "gendering", "'", ".", " ", "Media", " ", "reporting", " ", "on", " ", "Margulis", " ", "replicated", " ", "entrenched", "gender", "biases", " ", "by", " ", "attaching", " ", "non-", " ", "scientific", " ", "attributes", " ", "to", " ", "her", ".", " ", "Dismissed", " ", "as", "a", "theorist", "because", "she", "was", "a", "woman", ",", "she", "eventually", "'", "gain[ed", "]", "acceptance", "and", "…", "inclusion", "in", "the", "field", "'", "because", "of", "her", "image", "as", "a", "masculinized", "scientific", "rebel", ".", "The", "point", "then", "is", "that", "Margulis", "was", "able", "to", "control", "her", "image", "as", "an", "'", "outsider", "'", "and" ]	[]
Western notion of knowledge as abstract, objective and detached from the lived experiences of individuals. As argued by Solney Rolnik: The main operation of Western modernity culture, including colonialism, most important and most successful micro-political operation is the anaesthesia of the knowing body: the anaesthesia of this capacity to be affected by the world, as a field of forces, and this obstruction of our access to sensations, to tension, in order to affirm the ethical, political function of thought.² ⁵ ## Against this backdrop, Shahjahan argues that: Bringing awareness to our bodies helps us acknowledge and dismantle hegemonic knowledge systems that privilege the mind. Reconnecting to our bodies provides us a different locus of articulation for our theories and experiences. Furthermore, acknowledging our bodies helps us bridge theory and practice.² ⁶ The question that arose within Common Ground was thus: How do we restore the feeling body as the knowing body? How could we enact this idea of the body as a bridge between theory and practice? By developing activities and exercises within the Common Ground program, we tried to anchor the ideas and theories at the heart of our reflections in the body s ' experience in order to truly incarnate 24 Kimmerer (2013). 25 Guggenheim New York (2015). 26 Shahjahan (2014). Being ' lazy ' and slowing down: Toward decolonizing time, our body, and pedagogy (p. 489). other ways of relating to the living and to each other. In this way, we sought to propose activities that encouraged a different way of paying attention to the world and to others. Throughout the first, online phase of the program, participants were given embodied and creative exercises called ' instructions ' that were designed to prepare them for the session ahead. Based on the principle of instructions performed by artists such as Yoko Ono or Marina Abramovic, these exercises aimed to disrupt the normal order of things, question our ways of relating to our bodies and our environment, and invite the senses and the imagination into the learning process to explore the themes addressed during the sessions. During the second and third phases, which started with the CHC weekend, centering the body became a key aspect of the collective process. Common Ground s methodology ' therefore aimed to invite participants, in their own bodies and in the environment around them, to share moments of play as a means of creating	[ "Western", "notion", "of", "knowledge", "as", "abstract", ",", "objective", "and", "detached", "from", "the", "lived", "experiences", "of", "individuals", ".", "As", "argued", "by", "Solney", "Rolnik", ":", "\n\n", "The", "main", "operation", "of", "Western", "modernity", "culture", ",", "including", "colonialism", ",", "most", "important", "and", "most", "successful", "micro", "-", "political", "operation", "is", "the", "anaesthesia", "of", "the", "knowing", "body", ":", "the", "anaesthesia", "of", "this", "capacity", "to", "be", "affected", "by", "the", "world", ",", "as", "a", "field", "of", "forces", ",", "and", "this", "obstruction", "of", "our", "access", "to", "sensations", ",", "to", "tension", ",", "in", "order", "to", "affirm", "the", "ethical", ",", "political", "function", "of", "thought.²", "⁵", "\n\n", "#", "#", "Against", "this", "backdrop", ",", "Shahjahan", "argues", "that", ":", "\n\n", "Bringing", "awareness", "to", "our", "bodies", "helps", "us", "acknowledge", "and", "dismantle", "hegemonic", "knowledge", "systems", "that", "privilege", "the", "mind", ".", "Reconnecting", "to", "our", "bodies", "provides", "us", "a", "different", "locus", "of", "articulation", "for", "our", "theories", "and", "experiences", ".", "Furthermore", ",", "acknowledging", "our", "bodies", "helps", "us", "bridge", "theory", "and", "practice.²", "⁶", "\n\n", "The", "question", "that", "arose", "within", "Common", "Ground", "was", "thus", ":", "How", "do", "we", "restore", "the", "feeling", "body", "as", "the", "knowing", "body", "?", "How", "could", "we", "enact", "this", "idea", "of", "the", "body", "as", "a", "bridge", "between", "theory", "and", "practice", "?", "By", "developing", "activities", "and", "exercises", "within", "the", "Common", "Ground", "program", ",", "we", "tried", "to", "anchor", "the", "ideas", "and", "theories", "at", "the", "heart", "of", "our", "reflections", "in", "the", "body", "s", "'", "experience", "in", "order", "to", "truly", "incarnate", "\n\n", "24", "Kimmerer", "(", "2013", ")", ".", "\n\n", "25", "Guggenheim", "New", "York", "(", "2015", ")", ".", "\n\n", "26", "Shahjahan", "(", "2014", ")", ".", "Being", "'", "lazy", "'", "and", "slowing", "down", ":", "Toward", "decolonizing", "time", ",", "our", "body", ",", "and", "pedagogy", "(", "p.", "489", ")", ".", "\n\n", "other", "ways", "of", "relating", "to", "the", "living", "and", "to", "each", "other", ".", "In", "this", "way", ",", "we", "sought", "to", "propose", "activities", "that", "encouraged", "a", "different", "way", "of", "paying", "attention", "to", "the", "world", "and", "to", "others", ".", "\n\n", "Throughout", "the", "first", ",", "online", "phase", "of", "the", "program", ",", "participants", "were", "given", "embodied", "and", "creative", "exercises", "called", "'", "instructions", "'", "that", "were", "designed", "to", "prepare", "them", "for", "the", "session", "ahead", ".", "Based", "on", "the", "principle", "of", "instructions", "performed", "by", "artists", "such", "as", "Yoko", "Ono", "or", "Marina", "Abramovic", ",", "these", "exercises", "aimed", "to", "disrupt", "the", "normal", "order", "of", "things", ",", "question", "our", "ways", "of", "relating", "to", "our", "bodies", "and", "our", "environment", ",", "and", "invite", "the", "senses", "and", "the", "imagination", "into", "the", "learning", "process", "to", "explore", "the", "themes", "addressed", "during", "the", "sessions", ".", "During", "the", "second", "and", "third", "phases", ",", "which", "started", "with", "the", "CHC", "weekend", ",", "centering", "the", "body", "became", "a", "key", "aspect", "of", "the", "collective", "process", ".", "\n\n", "Common", "Ground", "s", "methodology", "'", "therefore", "aimed", "to", "invite", "participants", ",", "in", "their", "own", "bodies", "and", "in", "the", "environment", "around", "them", ",", "to", "share", "moments", "of", "play", "as", "a", "means", "of", "creating" ]	[ { "end": 1330, "label": "CITATION_ID", "start": 1328 }, { "end": 1440, "label": "CITATION_SPAN", "start": 1331 }, { "end": 1298, "label": "CITATION_ID", "start": 1296 }, { "end": 1277, "label": "CITATION_ID", "start": 1275 }, { "end": 1294, "label": "CITATION_SPAN", "start": 1278 }, { "end": 1327, "label": "CITATION_SPAN", "start": 1299 }, { "end": 877, "label": "CITATION_REF", "start": 874 } ]
rules were viewed as being restrictive to new investment, other factors-such as the lack of new major mineral discoveries, the decline in the global gold industry, and the political instability that preceded South Africa's independence-also might have encouraged disinvestment. ## PNG In 2002, when mineral prices were near record lows, PNG's mining fiscal regime was reviewed with the intention of attracting investment. The PNG Income Tax Act was amended to introduce relaxation rules for ring-fencing. Specifically, PNG allowed a tax deduction of up to 25% of allowable exploration expenditures undertaken outside the producing mine. 16 Other changes include more attractive accelerated depreciation arrangements and the elimination of loss carry forward time limits (Hogan & Goldsworthy, 2010). Neither South Africa nor PNG saw fit to suspend their ring-fencing rules. Instead, they modified them to rebalance the policy objectives of securing early revenues, protecting their tax base on the one hand, and attracting and maintaining mining investment on the other. 16 See, for example, Department of Petroleum and Energy, Petroleum Division (2005). 1.0 INTRODUCTION 2.0 THE FUNDAMENTALS OF RING-FENCING ## 3.0 THE BENEFITS AND RISKS OF RING-FENCING 4.0 DESIGNING RING-FENCING RULES 5.0 THE IMPLEMENTATION OF RING-FENCING RULES 6.0 CONCLUSION ## 3.2.2 Ring-Fencing May Make It Harder for an Investor to Attract Capital Mining is a highly capital-intensive industry. As such, significant upfront finance during the exploration and development phases and additional funding throughout the mine's life are required to maintain operations and fund expansions. Mining investors may look to raise funds through debt or equity, depending on the stage and risk profile of the project, as well as the creditworthiness of the taxpayer (IGF & OECD, 2017b). A good cashflow position and lower tax costs can enhance the after-tax profitability-and thus creditworthiness-of a specific project and can also make it more attractive for equity investment. Ring-fencing rules may have a negative impact on this fundraising capability since they may accelerate tax payments. ## 3.2.3 Under Ring-Fencing, Mining Investors May Register Permanent Losses Mining typically requires substantial upfront expenditures during the exploration and development phases, as well as additional investments throughout the mine's life to maintain operations and fund expansions (IGF & OECD, 2017a, p. 17). Exploration and development expenditures, including additional investments, can be costly. Only a small percentage of exploration projects are successful: 'It takes 500-1,000 grassroots exploration projects to identify 100 targets for advanced exploration, which in turn lead to	[ "rules", "were", "viewed", "as", "being", "restrictive", "to", "new", "investment", ",", "other", "factors", "-", "such", "as", "the", "lack", "of", "new", "major", "mineral", "discoveries", ",", "the", "decline", "in", "the", "global", "gold", "industry", ",", "and", "the", "political", "instability", "that", "preceded", "South", "Africa", "'s", "independence", "-", "also", "might", "have", "encouraged", "disinvestment", ".", "\n\n", "#", "#", "PNG", "\n\n", "In", "2002", ",", "when", "mineral", "prices", "were", "near", "record", "lows", ",", "PNG", "'s", "mining", "fiscal", "regime", "was", "reviewed", "with", "the", "intention", "of", "attracting", "investment", ".", "The", "PNG", "Income", "Tax", "Act", "was", "amended", "to", "introduce", "relaxation", "rules", "for", "ring", "-", "fencing", 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"Lan A, Kotler D, Kronfeld-Schor N, Stukalin Y, Einat H (Jan 2022; Online ahead of print) Changes in sleep patterns of college students in Israel during COVID-19 lockdown, a sleep diaries study. Sleep and Biological Rhythms Bilu C, Frolinger-Ashkenazy T, Einat H, Zimmet P, Bishko Y, Halperin D, Kronfeld-Schor N (Nov 2021; Online ahead of print) Effects of photoperiod and diet on BDNF daily rhythms in diurnal sand rats. Behavioural Brain Research 418 113666 Oved S, Mofaz M, Lan A, Einat H, Kronfeld-Schor N, Yamin D, Shmueli E (June 2021) Differential effects of COVID-19 lockdowns on well-being: interaction between age, gender and chronotype. Journal of the Royal Society Interface 18(179):20210078 Kazavchinsky L, Dahan S, Einat H (Nov 2020) Exploring test batteries for affective- and anxiety-like behaviors in female and male ICR and black Swiss mice. Acta Neuropsychiatrica. 32:293-302 *Stukalin Y, Lan A, Einat H (2020) Revisiting the validity of the mouse tail suspension test: Systematic review and meta-analysis of the effects of prototypic antidepressants. Neuroscience and Biobehavioral Reviews. 112:39-47 " "• Petrache, A.L., Khan, A.A., Nicholson, M.W., Monaco, A., Kuta-Siejkowska, M., Haider, S., ...Ali, A. (2020). Selective modulation of α5 GABAA receptors exacerbates aberrant inhibition at key hippocampal neuronal circuits in APP mouse model of Alzheimer’s disease. Front. Cell. Neurosci., https://doi.org/10.3389 • Petrache, A.L., Rajulawalla, A., Shi, A., Wetzel, A., Saito, T., Saido, T.C., ...Ali, A. (2019). Aberrant Excitatory-Inhibitory Synaptic Mechanisms in Entorhinal Cortex Microcircuits during the Pathogenesis of Alzheimer’s disease. Cerebral Cortex, doi:10.1093/cercor/bhz016 • Shi, A., Petrache, A.L., Shi, J., Ali, A. (2019). Preserved Calretinin interneurons in an app model of Alzheimer’s Disease disrupts hippocampal inhibition via up-regulated P2Y1 purinoreceptors. Cerebral Cortex, doi:10.1093/cercor/bhz165 • Khan, A., Shekh-Ahmad, T., Khalilova, A., Walker, M., Ali, A.B. (2018). Cannabidiol exerts antiepileptic effects by restoring hippocampal interneuron functions in a temporal lobe epilepsy model. British Journal of Pharmacology, • Nicholson, M.W., Sweeney, A., Pekle, E., Alam, S., Ali, A.B., Duchen, M., Jovanovic, J.N. (2018). Diazepam-induced loss of inhibitory synapses mediated by PLCδ/ Ca²⁺/calcineurin signalling downstream of GABAA receptors. Molecular Psychiatry, doi:10.1038/s41380-018-0100-y " "Craig, L., Hoo, Z. L., Yan, T. Z., Wardlaw, J. and Quinn, T. J. (2022) Prevalence of dementia in ischaemic or mixed stroke populations: systematic review and meta-analysis. Journal of Neurology, Neurosurgery and Psychiatry, 93(2), pp. 180-187. (doi: 10.1136/jnnp-2020-325796) (PMID:34782389) Burton, J. K. et al. (2021) Non-pharmacological interventions for preventing delirium in hospitalised non-ICU patients. Cochrane Database of Systematic Reviews, 2021(11), CD013307. 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Full text Bravo A.; Accuosto P.; Saggion H.. LaSTUS-TALN at IberLEF 2019 eHealth-KD challenge deep learning approaches to information extraction in biomedical texts . CEUR Workshop Proceedings 2019; 2421: 51-59. Chiruzzo L.; AbuRa''ed A.; Bravo A.; Saggion H.. LaSTUS-TALN+INCO @ CL-SciSumm 2019 . CEUR Workshop Proceedings 2019; 2414: 224-232. Goularte F.B.; Nassar S.M.; Fileto R.; Saggion H.. A text summarization method based on fuzzy rules and applicable to automated assessment . Expert Systems with Applications 2019; 115: 264-275. Publication link Porcaro L.; Saggion H.. Recognizing musical entities in user-generated content . Computacion y Sistemas 2019; 23(3): 1079-1088. Publication link Full text Other resources Štajner S.; Saggion H.; Ponzetto S.P.. Improving lexical coverage of text simplification systems for Spanish . Expert Systems with Applications 2019; 118: 80-91. Publication link Full text Abura¿ed A.; Bravo A.; Chiruzzo L.; Saggion H.. LaSTUS/TALN+INCO @ CL-SciSumm 2018 - Using regression and convolutions for cross-document semantic linking and summarization of scholarly literature . CEUR Workshop Proceedings 2018; (2132): 150-163. Full text Accuosto P.; Saggion H.. Improving the accessibility of biomedical texts by semantic enrichment and definition expansion . Procesamiento del Lenguaje Natural 2018; 61. Publication link Full text Agerri R.; Bel N.; Rigau G.; Saggion H.. TUNER: Multifaceted domain adaptation for advanced textual semantic processing. First results available . Procesamiento del Lenguaje Natural 2018; 61: 163-166. Publication link Full text Barbieri F.; Marujo L.s.; Karuturi P.; Brendel W.; Saggion H.. Exploring emoji usage and prediction through a temporal variation lens . CEUR Workshop Proceedings 2018; 2130. Hernández I, Tello J, Belda C, Ureña A, Salcedo I, Espinosa L, Saggion H Saggion. Savana: Re-using Electronic Health Records with Artificial Intelligence . International Journal of Interactive Multimedia and Artificial Intelligence 2018; 4(7): 8-12. Abura'ed A, Chiruzzo L, Saggion H, Accuosto P, Bravo A. LaSTUS/TALN @ CLSciSumm-17: Cross-document sentence matching and scientific text summarization systems . CEUR Workshop Proceedings 2017; 2002(0): 55-66. AbuRa'ed, Ahmed; Chiruzzo, Luis; Saggion, Horacio; Accuosto, Pablo; Bravo Serrano, Àlex. LaSTUS/TALN @ CLSciSumm-17: cross-document sentence matching and scientific text summarization systems . ACM SIGIR Forum 2017. Full text Codina-Filba J.; Bouayad-Agha N.; Burga A.; Casamayor G.; Mille S.; Muller A.; Saggion H.; Wanner L.. Using genre-specific features for patent summaries . Information processing & management 2017; 53(1): 151-174. Publication link Full text Espinosa-Anke L.; Oramas S.; Saggion H.; Serra X.. ELMDist: A Vector Space Model with Words and MusicBrainz Entities . Lecture Notes in Computer Science 2017; 10577 LNCS(0): 355-366.	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Fuest, C., Gros, D., Mengel, P.-L., Presidente, G., and Tirole, J., ‘ How to Escape the Middle Technology Trap: EU Innovation Policy ’, EconPol Policy Report, 2024. ix Myers, K. and Lanahan, L., ‘ Estimating Spillovers from Publicly Funded R&D: Evidence from the US Department of Energy ’, American Economic Review, Vol. 112, No. 7, July 2022. x Testa, G., Compano, R., Correia, A. and Rückert, E., ‘ In search of EU unicorns: What do we know about them ’, EUR 30978 EN, Publications Office of the European Union, Luxembourg, 2022. xi Bruegel, EU Digital Policy Overview , Bruegel Factsheet, 2024. xii Acemoglu, D., et al, ‘ Robot and automation: New insights from micro data: Advanced Technology Adoption: Selection or Causal Effects? ’, AEA Papers and Proceedings, 113: 210–214, 2023. xiii European Commission, Eurostat, Digitalisation in Europe – 2024 edition , Interactive Publication, 2024. xiv https:/ /epochai.org/blog/how-much-does- it-cost-to-train-frontier-ai-models 38THE FUTURE OF EUROPEAN COMPETITIVENESS — PART A \| CHAPTER 23. A joint decarbonisation and competitiveness plan High energy costs in Europe are an obstacle to growth, while lack of generation and grid capacity could impede the spread of digital tech and transport electrification . Commission estimates suggest that high energy prices in recent years have taken a toll on potential growth in Europei. Energy prices also continue to affect corporate investment sentiment much more than in other major economies. Around half of European companies see energy costs as a major impediment to investment – 30 percentage points higher than US companiesii. Energy-intensive industries (EIIs) have been hit hardest: production has fallen 10-15% since 2021 and the composition of European industry is changing, with increasing imports from countries with lower energy costs. Energy prices have also become more volatile, increasing the price of hedging and adding uncertainty to investment decisions. Without a significant increase in generation and grid capacity, Europe may also face limitations on making production more digital, as training and running AI models and maintaining data centres is highly energy-intensive. Data centres are currently responsible for 2.7% of the EU’s electricity demand, but by 2030 their consumption is expected to rise by 28%. FIGURE 1 Energy-intensive manufacturing challenges % change in industrial production (Apr. 24 vs Apr. 21) Source: Eurostat, OECD Trade value added (TiVA database) and ECB staff calculations. The EU’s decarbonisation goals are also more ambitious than its competitors’, creating additional short- term costs for European industry .	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13. Rapport d’Analyse Comparative – Études diagnostiques sur le livre jeunesse au service des apprentissages, 6 pays d’Afrique subsaharienne (2020-2021), Institut Français. 14. Kevane, Michael and Alain Joseph Sissao. ‘Habitudes de lecture au Burkina Faso.’ 2007. https://www.enssib.fr/bibliotheque-numerique/documents/38272-habitudes-de-lectureau-burkina-faso.pdf, 2007. Accessed 10 October 2024. 15. Ouagadougou International Book Fair: The Digital Opportunity in Question, 23 November 2023. Accessed 10 October 2024. 16. United Nations, UN Comtrade Database: Burkina Faso Imports of Printed Books, Brochures, Leaflets, and Similar Printed Matter (HS 490199). 2023. Accessed 24 February 2025. 17. Bureau International de l’Édition Française (BIEF), Le marché du livre en français en Afrique de l’Ouest (The French- language book market in West Africa), 2021. 74 THE AFRICAN BOOK INDUSTRY • Trends, Challenges and Opportunities for GrowthBURUNDI This mapping was carried out on the basis of documentary research and data collected during a consultation with government representatives and interviews with various stakeholders. Source: World Bank. HISTORICAL CONTEXT Publishing houses in Burundi began to emerge around the time of the country’s independence in 1962, within the framework of the educational activities of religious institutions. In 1961, Librairie Saint-Paul was created, selling books, periodicals and stationery. The University of Burundi, which was founded in 1964, did not have a dedicated publishing entity, but it did have a Presses et Publication department offering content focused primarily on academic news. In 1977 , the Ministry of Youth, Sports and Culture established the Centre of Burundian Civilization (Centre de Civilisation Burundaise), which published the magazine Culture et Société for over three decades. Following the civil war (1993–2005), publishing activities experienced a revival during the 2010s, marked by the emergence of publishing houses such as Bandima, Iwacu and Soma. INSTITUTIONAL AND LEGAL FRAMEWORK The Ministry of East African Community Affairs, Youth, Sports and Culture is responsible for coordinating policies and measures related to the book and publishing sector in Burundi. It operates through the Directorate of Culture and three specialised administrative bodies: 1 the Burundian Centre for Reading and Cultural Activities (Centre Burundais pour la Lecture et l’Animation Culturelle – CEBULAC), established in October 2007 , 2 which is responsible for formulating and implementing government policy on public reading, the promotion of literary creativity and the support of community libraries; the Burundian Copyright Office (Office Burundais des Droits d’Auteur – OBDA), set up in September 2011, 3 which contributes to the protection of copyright and oversees the registration of literary works;	[ "13", ".", "Rapport", "d’Analyse", "Comparative", "–", " ", "Études", "diagnostiques", "\n", "sur", "le", "livre", "jeunesse", "au", "service", "des", "apprentissages", ",", "6", " ", "pays", "\n", "d’Afrique", "subsaharienne", "(", "2020", "-", "2021", ")", ",", "Institut", "Français", ".", "\n", "14", ".", "Kevane", ",", "Michael", "and", "Alain", "Joseph", "Sissao", ".", "‘", "Habitudes", "\n", "de", "lecture", "au", "Burkina", "Faso", ".", "’", "2007", ".", "https://www.enssib.fr/bibliotheque-numerique/documents/38272-habitudes-de-lectureau-burkina-faso.pdf", ",", "2007", ".", "Accessed", "10", "October", "2024", ".", "\n", "15", ".", "Ouagadougou", "International", "Book", "Fair", ":", "The", "Digital", "\n", "Opportunity", "in", "Question", ",", "23", "November", "2023", ".", "Accessed", "10", "\n", "October", "2024", ".", "\n", "16", ".", "United", "Nations", ",", "UN", "Comtrade", "Database", ":", "Burkina", "Faso", "\n", "Imports", "of", "Printed", "Books", ",", "Brochures", ",", "Leaflets", ",", "and", "Similar", "Printed", "Matter", "(", "HS", " ", "490199", ")", ".", "2023", ".", "Accessed", "24", "February", "2025", ".", "\n", "17", ".", "Bureau", "International", "de", "l’Édition", "Française", "(", "BIEF", ")", ",", "Le", "\n", "marché", "du", "livre", "en", "français", "en", "Afrique", "de", "l’Ouest", "(", "The", "French-", "\n", "language", "book", "market", "in", "West", "Africa", ")", ",", "2021", ".", "\n", "74", "\n", "THE", "AFRICAN", "BOOK", "INDUSTRY", "•", "Trends", ",", "Challenges", "and", "Opportunities", "for", "GrowthBURUNDI", "\n", "This", "mapping", "was", "carried", "out", "on", "the", "basis", "\n", "of", "documentary", "research", "and", "data", "collected", "during", "a", "consultation", "with", "government", "representatives", "and", "interviews", "with", "various", "stakeholders", ".", "Source", ":", "World", "Bank", ".", "HISTORICAL", "CONTEXT", "\n", "Publishing", "houses", "in", "Burundi", "began", "to", "\n", "emerge", "around", "the", "time", "of", "the", "country", "’s", "independence", "in", "1962", ",", "within", "the", "framework", "of", "the", "educational", "activities", "of", "religious", "institutions", ".", "In", "1961", ",", "Librairie", "Saint", "-", "Paul", "was", "created", ",", "selling", "books", ",", "periodicals", "and", "stationery", ".", "The", "University", "of", "Burundi", ",", "which", "was", "founded", "in", "1964", ",", "did", "not", "have", "a", "dedicated", "publishing", "entity", ",", "but", "it", "did", "have", "a", "Presses", "et", "Publication", "department", "offering", "content", "focused", "primarily", "on", "academic", "news", ".", "\n", "In", "1977", ",", "the", "Ministry", "of", "Youth", ",", "Sports", "\n", "and", "Culture", "established", "the", "Centre", "of", "Burundian", "Civilization", "(", "Centre", "de", "Civilisation", "Burundaise", ")", ",", "which", "published", "the", "magazine", "Culture", "et", "Société", "for", "over", "three", "decades", ".", "Following", "the", "civil", "war", "(", "1993–2005", ")", ",", "publishing", "activities", "experienced", "a", "revival", "during", "the", "2010s", ",", "marked", "by", "the", "emergence", "of", "publishing", "houses", "such", "as", "Bandima", ",", "Iwacu", "and", "Soma", ".", "\n", "INSTITUTIONAL", "AND", "LEGAL", "\n", "FRAMEWORK", "\n", "The", "Ministry", "of", "East", "African", "Community", "\n", "Affairs", ",", "Youth", ",", "Sports", "and", "Culture", "is", "responsible", "for", "coordinating", "policies", "and", "measures", "related", "to", "the", "book", "and", "publishing", "sector", "in", "Burundi", ".", "It", "operates", "through", "the", "Directorate", "of", "Culture", "and", "three", "specialised", "administrative", "bodies", ":", "\n", "1", "\n", "the", "Burundian", "Centre", "for", "Reading", "and", "Cultural", "Activities", "(", "Centre", "Burundais", "pour", "la", "Lecture", "et", "l’Animation", "Culturelle", "–", "CEBULAC", ")", ",", "established", "in", "October", "2007", ",", "\n", "2", "\n", "which", "is", "responsible", "for", "formulating", "and", "implementing", "government", "policy", "on", "public", "reading", ",", "the", "promotion", "of", "literary", "creativity", "and", "the", "support", "of", "community", "libraries", ";", "the", "Burundian", "Copyright", "Office", "(", "Office", "Burundais", "des", "Droits", "d’Auteur", "–", "OBDA", ")", ",", "set", "up", "in", "September", "2011", ",", "\n", "3", "which", "\n", "contributes", "to", "the", "protection", "of", "copyright", "and", "oversees", "the", "registration", "of", "literary", "works", ";" ]	[ { "end": 2, "label": "CITATION_ID", "start": 0 }, { "end": 177, "label": "CITATION_ID", "start": 175 }, { "end": 403, "label": "CITATION_ID", "start": 401 }, { "end": 527, "label": "CITATION_ID", "start": 525 }, { "end": 703, "label": "CITATION_ID", "start": 701 }, { "end": 174, "label": "CITATION_SPAN", "start": 4 }, { "end": 400, "label": "CITATION_SPAN", "start": 179 }, { "end": 524, "label": "CITATION_SPAN", "start": 405 }, { "end": 700, "label": "CITATION_SPAN", "start": 529 }, { "end": 867, "label": "CITATION_SPAN", "start": 705 } ]
17 256 UA 876 35 673 872 17 7 500 PublicationsFigure 3.53. Number of publications and EC projects in collaboration between EaP actors in different countries, in the ‘Fundamental physics and mathematics’ domain Colour indicates the relative distribution of documents, computed row-wise. AM AZ BY GE MD UA Other 10 18 25 19 18 29 10 7 11 8 9 14 18 7 19 15 18 34 25 11 19 23 30 50 19 8 15 23 23 57 18 9 18 30 23 115 EC projectsAM AZ BY GE MD UA Other AM 22 22 45 17 44 351 AZ 22 15 23 9 27 222 BY 22 15 23 15 66 394 GE 45 23 23 20 62 370 MD 17 9 15 20 59 207 UA 44 27 66 62 59 2 388 PublicationsFigure 3.54. Number of publications and EC projects in collaboration between EaP actors in different countries, in the ‘Governance, culture, education and the economy’ domain Colour indicates the relative distribution of documents, computed row-wise. 214 Part 3 Analysis of scientific and technological potential Regional collaboration in Health and wellbeing In the case of Health and wellbeing publications, external collaborations again have a significant weight across all six EaP countries. Within the EaP, some of the highest-intensity collaborations are Armenia and Azerbaijan with Georgia and Ukraine, and Georgia and Moldova with Ukraine. The highest number of collaborations in EC pro- jects are between Georgia and Ukraine, with the intensity of external collaborations still significant.Regional collaboration in ICT and com- puter science In the case of ICT and computer science publi- cations, external collaborations again have a sig- nificant weight throughout all six EaP countries. Azerbaijan, not usually standing out in other do- mains, has the second-highest collaboration with Ukraine. Georgia and Armenia also collaborate in- tensively with each other. Collaborations in terms of EC projects are much less concentrated on external partners and very evenly distributed. Azerbaijan, however, has very few EC projects. AM AZ BY GE MD UA Other 4 1 2 2 1 1 3 1 3 10 2 1 3 40 EC projectsAM AZ BY GE MD UA Other AM 33 44 82 31 73 771 AZ 33 29 49 20 48 343 BY 44 29 59 33 195 1 364 GE 82 49 59 44 121 949 MD 31 20 33 44 62 444 UA 73 48 195 121 62 3	[ "17", "256", "\n", "UA", "876", "35", "673", "872", "17", "7", "500", "\n", "PublicationsFigure", "3.53", ".", "Number", "of", "publications", "and", "EC", "projects", "in", "collaboration", "between", "EaP", "actors", "in", "different", "countries", ",", "in", "the", "\n", "‘", "Fundamental", "physics", "and", "mathematics", "’", "domain", "\n", "Colour", "indicates", "the", "relative", "distribution", "of", "documents", ",", "computed", "row", "-", "wise", ".", "\n", "AM", "\n", "AZ", "\n", "BY", "\n", "GE", "\n", "MD", "\n", "UA", "\n", "Other", "\n", "10", "18", "25", "19", "18", "29", "\n", "10", "7", "11", "8", "9", "14", "\n", "18", "7", "19", "15", "18", "34", "\n", "25", "11", "19", "23", "30", "50", "\n", "19", "8", "15", "23", "23", "57", "\n", "18", "9", "18", "30", "23", "115", "\n", "EC", "projectsAM", "\n", "AZ", "\n", "BY", "\n", "GE", "\n", "MD", "\n", "UA", "\n", "Other", "\n", "AM", "22", "22", "45", "17", "44", "351", "\n", "AZ", "22", "15", "23", "9", "27", "222", "\n", "BY", "22", "15", "23", "15", "66", "394", "\n", "GE", "45", "23", "23", "20", "62", "370", "\n", "MD", "17", "9", "15", "20", "59", "207", "\n", "UA", "44", "27", "66", "62", "59", "2", "388", "\n", "PublicationsFigure", "3.54", ".", "Number", "of", "publications", "and", "EC", "projects", "in", "collaboration", "between", "EaP", "actors", "in", "different", "countries", ",", "in", "the", "\n", "‘", "Governance", ",", "culture", ",", "education", "and", "the", "economy", "’", "domain", "\n", "Colour", "indicates", "the", "relative", "distribution", "of", "documents", ",", "computed", "row", "-", "wise", ".", "\n", "214", "\n ", "Part", "3", "Analysis", "of", "scientific", "and", "technological", "potential", "\n", "Regional", "collaboration", "in", "Health", "and", "\n", "wellbeing", "\n", "In", "the", "case", "of", "Health", "and", "wellbeing", "publications", ",", "\n", "external", "collaborations", "again", "have", "a", "significant", "\n", "weight", "across", "all", "six", "EaP", "countries", ".", "Within", "the", "EaP", ",", "\n", "some", "of", "the", "highest", "-", "intensity", "collaborations", "are", "\n", "Armenia", "and", "Azerbaijan", "with", "Georgia", "and", "Ukraine", ",", "\n", "and", "Georgia", "and", "Moldova", "with", "Ukraine", ".", "\n", "The", "highest", "number", "of", "collaborations", "in", "EC", "pro-", "\n", "jects", "are", "between", "Georgia", "and", "Ukraine", ",", "with", "the", "\n", "intensity", "of", "external", "collaborations", "still", "significant", ".", "Regional", "collaboration", "in", "ICT", "and", "com-", "\n", "puter", "science", "\n", "In", "the", "case", "of", "ICT", "and", "computer", "science", "publi-", "\n", "cations", ",", "external", "collaborations", "again", "have", "a", "sig-", "\n", "nificant", "weight", "throughout", "all", "six", "EaP", "countries", ".", "\n", "Azerbaijan", ",", "not", "usually", "standing", "out", "in", "other", "do-", "\n", "mains", ",", "has", "the", "second", "-", "highest", "collaboration", "with", "\n", "Ukraine", ".", "Georgia", "and", "Armenia", "also", "collaborate", "in-", "\n", "tensively", "with", "each", "other", ".", "\n", "Collaborations", "in", "terms", "of", "EC", "projects", "are", "much", "\n", "less", "concentrated", "on", "external", "partners", "and", "very", "\n", "evenly", "distributed", ".", "Azerbaijan", ",", "however", ",", "has", "very", "\n", "few", "EC", "projects", ".", "\n", "AM", "\n", "AZ", "\n", "BY", "\n", "GE", "\n", "MD", "\n", "UA", "\n", "Other", "\n", "4", "\n", "1", "\n", "2", "2", "\n", "1", "1", "3", "\n", "1", "3", "10", "\n", "2", "1", "3", "40", "\n", "EC", "projectsAM", "\n", "AZ", "\n", "BY", "\n", "GE", "\n", "MD", "\n", "UA", "\n", "Other", "\n", "AM", "33", "44", "82", "31", "73", "771", "\n", "AZ", "33", "29", "49", "20", "48", "343", "\n", "BY", "44", "29", "59", "33", "195", "1", "364", "\n", "GE", "82", "49", "59", "44", "121", "949", "\n", "MD", "31", "20", "33", "44", "62", "444", "\n", "UA", "73", "48", "195", "121", "62", "3" ]	[]
statistically significant differences were seen between the responses from residents in Sanjay colony and Bhalswa on the NCI, four in 'sense of community' (SOC), and two in each of the themes 'neigbourliness' (NEI) and 'attraction to neighbourhood' (ATTR) as shown in Figure 2.1 . Regarding the sense of community (SOC), residents in Sanjay colony were 9.3 percentage points (pp) more likely to believe their neighbours would help them in an emergency (NCI 9, p<0.001) and 9.5 pp more likely to have a greater willing -ness to improve their neighbourhood than residents in Bhalswa (NCI 12, p<0.001). Residents of Sanjay colony were 10.2 pp more likely to feel a greater sense of community than those residents of Bhalswa (NCI 18, p<0.001). Sanjay colony resi -dents were 5.48 pp less likely to feel that their neighbours agree with them about what is important in life (NCI 8, p<0.05). In the subscale 'neighbouring' (NEI), residents in Sanjay colony were 4.76 pp less likely to invite neighbours to their home (NCI 15, p<0.01) and 9.7 pp less likely to feel that neighbourhood friendships meant a great deal to them (NCI 4, p<0.001). <!-- image --> Figure 2.1 Neighbourhood Cohesion Index Note: Neighbourhood Cohesion Index (NCI) estimated averaged marginal component effects for Sanjay colony with 95% CIs. The percentage points (pp) estimates for Sanjay colony (=1) with the base group being Bhalswa (=0). The marginal effect of each independent variable being averaged over the joint distribution of the remaining variables. The independent variables are in the vertical axis. The horizontal axis gives the prediction of change in the independent variable (points), and the associated 95% CIs (bars). Table 2.4 Neighbourhood Cohesion Index (NCI) \| Item description \| Sanjay colony with base Bhalswa \| \|-------------------------------------------------------------------------------------------------------------------------------------------\|-----------------------------------\| \| Sense of community (SOC) \| \| \| I agree with most of my neighbourhood about what's important in life (NCI 8) \| -0.055 (0.023) \| \| I believe my neighbours would help me in an emergency (NCI 9) \| 0.092 * (0.025) \| \| I feel loyal to people in my neighbourhood (NCI 10) \| -0.028 (0.035) \| \| I'd be willing to work with others to improve my neighbourhood (NCI 12) \| 0.095 *** (0.025) \| \| I think of myself as similar to people who live in this neighbourhood (NCI 14) \| -0.001 (0.033) \| \| A feeling of fellowship runs deep in this neighbourhood (NCI 16)	[ " ", "statistically", " ", "significant", " ", "differences", " ", "were", " ", "seen", " ", "between", " ", "the", " ", "responses", " ", "from", 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"greater", "sense", "of", "community", "than", "those", "residents", "of", "Bhalswa", "(", "NCI", "18", ",", "p<0.001", ")", ".", "Sanjay", "colony", "resi", "-dents", "were", "5.48", "pp", "less", "likely", "to", "feel", "that", "their", "neighbours", "agree", "with", "them", "about", "what", "is", "important", "in", "life", "(", "NCI", "8", ",", "p<0.05", ")", ".", "\n\n", "In", "the", "subscale", "'", "neighbouring", "'", "(", "NEI", ")", ",", "residents", "in", "Sanjay", "colony", "were", "4.76", "pp", "less", " ", "likely", " ", "to", " ", "invite", " ", "neighbours", " ", "to", " ", "their", " ", "home", " ", "(", "NCI", "15", ",", "p<0.01", ")", "and", "9.7", "pp", "less", "likely", "to", "feel", "that", "neighbourhood", "friendships", "meant", "a", "great", "deal", "to", "them", "(", "NCI", "4", ",", "p<0.001", ")", ".", "\n\n", "<", "!", "--", "image", "--", ">", "\n\n", "Figure", "2.1", "Neighbourhood", "Cohesion", "Index", "\n\n", "Note", ":", "Neighbourhood", "Cohesion", "Index", "(", "NCI", ")", "estimated", "averaged", "marginal", "component", "effects", "for", "Sanjay", "colony", "with", "95", "%", "CIs", ".", "The", "percentage", "points", "(", "pp", ")", "estimates", "for", "Sanjay", "colony", "(=", "1", ")", "with", "the", "base", "group", "being", "Bhalswa", "(=", "0", ")", ".", "The", "marginal", "effect", "of", "each", "independent", "variable", "being", "averaged", "over", "the", "joint", "distribution", "of", "the", "remaining", "variables", ".", "The", "independent", "variables", "are", "in", "the", "vertical", "axis", ".", "The", "horizontal", "axis", "gives", "the", "prediction", "of", "change", "in", "the", "independent", "variable", "(", "points", ")", ",", "and", "the", "associated", "95", "%", "CIs", "(", "bars", ")", ".", "\n\n", "Table", "2.4", "Neighbourhood", "Cohesion", "Index", "(", "NCI", ")", "\n\n", "\|", "Item", "description", " ", "\|", "Sanjay", "colony", "with", "base", "Bhalswa", " ", "\|", "\n", "\|-------------------------------------------------------------------------------------------------------------------------------------------\|-----------------------------------\|", "\n", "\|", "Sense", "of", "community", "(", "SOC", ")", " ", "\|", " ", "\|", "\n", "\|", "I", "agree", "with", "most", "of", "my", "neighbourhood", "about", "what", "'s", "important", "in", "life", "(", "NCI", "8)", " ", "\|", "-0.055", "", "", "(", "0.023", ")", " ", "\|", "\n", "\|", "I", "believe", "my", "neighbours", "would", "help", "me", "in", "an", "emergency", "(", "NCI", "9", ")", " ", "\|", "0.092", "", "", "", "(", "0.025", ")", " ", "\|", "\n", "\|", "I", "feel", "loyal", "to", "people", "in", "my", "neighbourhood", "(", "NCI", "10", ")", " ", "\|", "-0.028", "(", "0.035", ")", " ", "\|", "\n", "\|", "I", "'d", "be", "willing", "to", "work", "with", "others", "to", "improve", "my", "neighbourhood", "(", "NCI", "12", ")", " ", "\|", "0.095", "", "", "", "(", "0.025", ")", " ", "\|", "\n", "\|", "I", "think", "of", "myself", "as", "similar", "to", "people", "who", "live", "in", "this", "neighbourhood", "(", "NCI", "14", ")", " ", "\|", "-0.001", "(", "0.033", ")", " ", "\|", "\n", "\|", "A", "feeling", "of", "fellowship", "runs", "deep", "in", "this", "neighbourhood", "(", "NCI", "16", ")" ]	[]
be registered.16 Although similar regulations had been implemented locally before 1929, it was the first time that all Western- trained physicians had to register to be allowed to practice.17 This registration process generated an unprecedented mass of documents providing rather detailed information on virtually every Western- style physician in the country.18 These new documents provide a more comprehensive view on the profession of ‘Western- style physician’ compared to previous studies that have tended to focus on some individuals or specific institutions.19 This is particularly true for the provinces of inland China, some of which have remained poorly documented.20 Women as Western- style physicians The proportion of women among Chinese physicians was far from negligi - ble, especially in the case of Western medicine, which attracted proportion - ally more women than Chinese medicine. The link between missionary and philanthropic works, the circulation of Western scientific knowledge and the education of women resulted in the rapid feminization of the profession in the province, so much so that on the eve of World War II, the share of women among Sichuan’s Western- style physicians was comparable to that of the United States. Overall, among both Chinese- style and Western- style physicians, women made up a minority of Sichuanese practitioners. Out of more than 2,300 physicians whose registration files were archived by the provincial admin - istration between 1937 and 1947, only 60 (2.6 per cent) were women (Table 7.1 ). However, there is a stark difference concerning the propor - tion of women physicians practising Western and Chinese- style medicine. Chinese- style physicians constitute a large majority of the total number of physicians registered but of these only 1.5 per cent are women, compared to 11 per cent for Western- style physicians. This disparity indicates that Western medicine provided more professional opportunities for women than Chinese medicine. This was partly due to the situation of women within Chinese medicine. State- sanctioned registration of Chinese- style physicians favoured orthodox, literati medicine, based on the knowledge of the Chinese medical classics. In this regard, female healers 176 Negotiating in/visibility suffered from long- term marginalization from literati physicians.21 The modes of transmission of Chinese medicine – master to apprentice, father to son, uncle to nephew and so on – tended to exclude women from literati medicine, although there were some exceptions. This does not mean that there were no women healers. 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....................................................................................................................................................... 233 Table 4.2. Combined EIST specialisation domains in Armenia ............................................. 236 Table 4.3. Combined EIST specialisation domains in Azerbaijan ........................................ 238 Table 4.4. Combined EIST specialisation domains in Georgia .............................................. 240 Table 4.5. Combined EIST specialisation domains in Moldova ............................................. 241 Table 4.6. Combined EIST specialisation domains in Ukraine .............................................. 244 Table 4.7. Pairs of economic clusters and S&T domains that can be identified in at least two countries ............................................................................................................................................... 246 268 Annexes Annexes Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation269 270 Annexes Annex 1. Results of the full economic mapping analysis for Georgia, Moldova and UkraineAn ‘X’ in a yellow-coloured cell shows whether an industry passed an individual criterion, either for the number of employees (or employment) and turnover. An ‘X’ in a green-coloured cell shows whether an industry passed the criteria for both the number of employees (or employment) and turnover. GEORGIA MOLDOVA UKRAINEEmploy- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover NACE Industry name Current Current CurrentEmerg- ingEmerg- ingEmerg- ingCurrent Current CurrentEmerg- ingEmerg- ingEmerg- ingCurrent Current CurrentEmerg- ingEmerg- ingEmerg- ing 34 52 28 61 64 40 31 29 15 50 47 21 55 40 35 83 57 34 A AGRICULTURE, FORESTRY AND FISHING 1 Crop and animal production, hunting and related service activities 1.1 Growing of non-perennial crops X X X X X 1.2 Growing of perennial crops X X X X X X X 1.3 Plant propagation 1.4 Animal production X X X X X X 1.5 Mixed farming X X 1.6 Support activities to agriculture and post-harvest crop activities X X X X 1.7 Hunting, trapping and related service activities 2 Forestry and logging 2.1 Silviculture and other forestry 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Assistant principals can help with daily school operations. Teachers and support staff can exercise leadership when they participate in decision making and in designing approaches to teaching and learning. Student involvement in leadership can be empowering and promote critical thinking and responsibility for learning. Parents and community members can promote culturally responsive practices and strengthen the school’s connection with the community. As part of the 2018 Teaching and Learning International Survey (TALIS), in which 48 education systems participated, 89% of lower secondary schools had a school management team. On average, among schools with a management team, 8 in 10 had an assistant principal, 6 in 10 had teachers (department heads or other teachers), 5 in 10 had school governing board members, 4 in 10 had financial managers, and 3 in 10 had parent or student representatives ( Figure 4.1). While there is considerable difference between education systems, it is clear that almost all of them, depending on school size and other contextual factors, offer opportunities for participating in school decision making and the exercise of leadership and initiative. Despite this potential, school leadership often remains hierarchical and limits stakeholders’ engagement. Teachers need leadership training and autonomy. Student involvement is more established in high-income countries. Parents and communities face barriers to their participation. This chapter examines how principals share leadership with these actors, highlighting the importance of creating collaborative learning environments and achieving positive outcomes for students.SCHOOL PERSONNEL CAN LEAD IF GIVEN OPPORTUNITIES AND SUPPORT Assistant principals play an essential role in schools’ success by supporting school operations (Oleszewski et al., 2012). Teachers in leadership positions can promote teaching of high quality (Berg and Zoellick, 2019). Other school staff also take on leadership roles, contributing to decision making and school operations (Ansley et al., 2019). All these roles can be performed in an organized structure or through individual initiatives. ASSISTANT PRINCIPALS AND TEACHER LEADERS SUPPORT PRINCIPALS Various leadership roles exist to help the principal shape the school’s vision, develop teaching strategies, ensure smooth operations and form a collaborative leadership team. Deputy, vice, assistant or co-principals , usually seen as subordinate, mirror the principal’s role (Matthews and Crow, 2003). Their roles are shaped largely by principals’ discretion (Arar, 2014; Guihen, 2019) and involve managerial and leadership responsibilities, especially when schools are granted autonomy (Wong, 2009). 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chosen and how it is designed, it must be clearly defined in the law. Clear rules on how to implement ring-fencing in mining-including methods to apportion revenues and expenditures and how to deal with domestic transfer pricing scenariosare critical. Clear criteria must be developed to enable effective implementation by both companies and governments. ## Financial Support for the OECD Comes From the Following Donors: <!-- image --> <!-- image --> <!-- image --> <!-- image --> <!-- image --> <!-- image --> Schweizerische Eidgenossenschaft Confederation suisse Contederazione Svizzera Contederaziun svizra Swviss Conlederation Federal Department of Economic Affairs, Education and Research eaeR State Secretariat for Economic Affairs SECO <!-- image --> <!-- image --> <!-- image --> Ministry of Foreign Affairs <!-- image --> <!-- image --> <!-- image --> <!-- image --> ## Support for the IGF Comes From the Following: IGF Project Funders <!-- image --> <!-- image --> IGF Secretariat Funders <!-- image --> <!-- image --> IGF Secretariat Host <!-- image --> <!-- image --> ## References Australian Energy Regulator. (2023). Ring-fencing . https://www.aer.gov.au/industry/networks/ ring-fencing Benninger, T., Devlin, D., Godinez, E. 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World Bank. https://documents1.worldbank.org/curated/ en/222451496911224999/pdf/Oil-Gas-and-Mining-A-Sourcebook-for-Understandingthe-Extractive-Industries.pdf Daniel, P., Keen, M., & McPherson, C. (Eds.). (2010). The taxation of petroleum and minerals: Principles, problems and practice . Routledge. https://www.international-arbitrationattorney.com/wp-content/uploads/arbitrationlaw1394930.pdf Davis Tax Committee. (2014). First interim report on mining for the Minister of Finance . https://www.taxcom.org.za/docs/20151201%20DTC%20First%20Interim%20Report%20 on%20Mining%20(hard-rock).pdf Davis Tax Committee. (2016). Second and final report on hard-rock mining for the Minister of Finance . 20171113 Second and final hard-rock mining report on website.pdf Department of Petroleum and Energy, Petroleum Division. (2005). Petroleum policy handbook . Government of Papua New Guinea. Ernst & Young. (2019). Global oil and gas tax guide . https://globaltaxnews.ey.com/news/20195677-ey-global-oil-and-gas-tax-guide-2019 Ghana Revenue Authority. (n.d.). Mineral royalties tax. https://gra.gov.gh/portfolio/mineralroyalties-tax/ Hogan, L. & Goldsworthy, B. (2010). International mineral taxation: Experience and issues. In P. Daniel, M. Keen, & C. McPherson (Eds.), The taxation of petroleum and minerals . Routledge. https://www.international-arbitration-attorney.com/wp-content/uploads/ arbitrationlaw1394930.pdf Intergovernmental Forum on Mining, Minerals, Metals and Sustainable Development & Organisation for Economic Co-operation and Development. (2017b). 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acceleration circuitry ), which can include microprocessors, programmable processing devices (e.g., FPGAs, ASICs, PLDs, DSPs. and/or the like), and/or the like. The also includes non-transitory or transitory machine-readable media (also referred to as “computer readable medium ” or “ ”), which may be embodied as, or otherwise include , , and/or memory devices/elements of the . Additionally or alternatively, the can be embodied as any of the devices/technologies described for the and/or . The system memory (also referred to as “ ”) includes one or more hardware elements/devices for storing data and/or (and/or , ). Any number of memory devices may be used to provide for a given amount of . As examples, the can be embodied as processor cache or scratchpad memory, volatile memory, non-volatile memory (NVM), and/or any other machine readable media for storing data. Examples of volatile memory include random access memory (RAM), static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), thyristor RAM (T-RAM), content-addressable memory (CAM), and/or the like. Examples of NVM can include read-only memory (ROM) (e.g., including programmable ROM (PROM), erasable PROM (EPROM), electrically EPROM (EEPROM), flash memory (e.g., NAND flash memory, NOR flash memory, and the like), solid-state storage (SSS) or solid-state ROM, programmable metallization cell (PMC), and/or the like), non-volatile RAM (NVRAM), phase change memory (PCM) or phase change RAM (PRAM) (e.g., 3D XPoint™ memory, chalcogenide RAM (CRAM), Interfacial Phase-Change Memory (IPCM), and the like), memistor devices, resistive memory or resistive RAM (ReRAM) (e.g., memristor devices, metal oxide-based ReRAM, quantum dot resistive memory devices, and the like), conductive bridging RAM (or PMC), magnetoresistive RAM (MRAM), electrochemical RAM (ECRAM), ferroelectric RAM (FeRAM), anti-ferroelectric RAM (AFeRAM), ferroelectric field-effect transistor (FeFET) memory, and/or the like. Additionally or alternatively, the can include spintronic memory devices (e.g., domain wall memory (DWM), spin transfer torque (STT) memory (e.g., STT-RAM or STT-MRAM), magnetic tunneling junction memory devices, spin-orbit transfer memory devices, Spin-Hall memory devices, nanowire memory cells, and/or the like). In some implementations, the may be formed into any number of different package types, such as single die package (SDP), dual die package (DDP), quad die package (Q17P), memory modules (e.g., dual inline memory modules (DIMMs), microDIMMs, and/or MiniDIMMs), and/or the like. 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end of stool sampling, whereas 19 cases seroconverted earlier. All stool samples collected prior to the anti-TG2 negative plasma, and corresponding samples from the matched controls, were subjected to DNA virome analysis. The DNA virome metagenomes were characterised in 1,271 stool samples from the MIDIA nested case-control dataset. The starting material was a supernatant of faecal material. Shortly after the collection of faecal samples (during 2001 – 2010), samples were resuspended in phosphate-buffered saline with the addition of 2.5 μg/mL fungizone, 50 IU/mL penicillin, 0.5% bovine serum albumin, 50 μg/mL streptomycin, 50 IU/mL penicillin, 50 μg/mL streptomycin. The resuspended samples were vigorously vortexed and centrifuged at 4000×g for 30 min, and the supernatants were collected and biobanked at -80°C until further processing. In the present project, the biobanked supernatants were thawed, re-centrifuged to clarify the material, and subjected to RNA and DNA co-purification using the Qiagen Viral RNA extraction chemistry (Qiagen, Hilden, Germany) according to its protocol, with the exception of reducing the amount of carrier RNA added. In addition, for a smaller study on the early stages of T1D (islet autoimmunity), we generated 311 combined metagenomic libraries of DNA and RNA viromes; we have sequenced 2/3 of these libraries by December 2023. In this T1D study, we focused on early-onset islet autoimmunity cases, and selected fewer samples per subject. Cases were selected based on their very early onset of islet autoimmunity. They were eligible if the pre-seroconversion period was covered by stool sample collection (i.e. if stools were available at 12, 9, 6, 3 and 0 months before the first blood sample positive for any autoantibody marker of islet autoimmunity). Islet autoimmunity was defined on the basis of the results of tests for plasma autoantibodies against glutamic acid decarboxylase 65 (GADA), protein tyrosine phosphatase IA2 (IA2A) and insulin (IAA) as previously described in detail (Stene, Witso et al. 2007). The seroconversion window of islet autoimmunity was defined as the period between the last negative and first positive sample for any of the autoantibodies tested – there had to be at least two consecutive samples positive for at least two islet autoantibodies, or a strong positivity for one autoantibody leading to the development of T1D. Sample handling and nucleic acid extraction were performed according to our published protocol (Kramna and Cinek 2018). 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chosen and how it is designed, it must be clearly defined in the law. Clear rules on how to implement ring-fencing in mining-including methods to apportion revenues and expenditures and how to deal with domestic transfer pricing scenariosare critical. Clear criteria must be developed to enable effective implementation by both companies and governments. ## Financial Support for the OECD Comes From the Following Donors: <!-- image --> <!-- image --> <!-- image --> <!-- image --> <!-- image --> <!-- image --> Schweizerische Eidgenossenschaft Confederation suisse Contederazione Svizzera Contederaziun svizra Swviss Conlederation Federal Department of Economic Affairs, Education and Research eaeR State Secretariat for Economic Affairs SECO <!-- image --> <!-- image --> <!-- image --> Ministry of Foreign Affairs <!-- image --> <!-- image --> <!-- image --> <!-- image --> ## Support for the IGF Comes From the Following: IGF Project Funders <!-- image --> <!-- image --> IGF Secretariat Funders <!-- image --> <!-- image --> IGF Secretariat Host <!-- image --> <!-- image --> ## References Australian Energy Regulator. (2023). Ring-fencing . https://www.aer.gov.au/industry/networks/ ring-fencing Benninger, T., Devlin, D., Godinez, E. C., & Vernon-Lin, N. (2024). Cash flow analysis of fiscal regimes for extractive industries (Working paper WP/24/89). International Monetary Fund. https://www.imf.org/-/media/Files/Publications/WP/2024/English/wpiea2024089-printpdf.ashx Bindeman, K. (1999, October). Production-sharing agreements: An economic analysis . Oxford Institute for Energy Studies. https://www.oxfordenergy.org/wpcms/wp-content/ uploads/2010/11/WPM25-ProductionSharingAgreementsAnEconomicAnalysisKBindemann-1999.pdf Calder, J. (2014). Administering fiscal regimes for extractive industries: A handbook , International Monetary Fund. https://www.elibrary.imf.org/display/book/9781475575170/978 1475575170.xml Cameron, P. D., & Stanley, M. C. (2017). Oil, gas, and mining: A sourcebook for understanding the extractives industries . World Bank. https://documents1.worldbank.org/curated/ en/222451496911224999/pdf/Oil-Gas-and-Mining-A-Sourcebook-for-Understandingthe-Extractive-Industries.pdf Daniel, P., Keen, M., & McPherson, C. (Eds.). (2010). The taxation of petroleum and minerals: Principles, problems and practice . Routledge. https://www.international-arbitrationattorney.com/wp-content/uploads/arbitrationlaw1394930.pdf Davis Tax Committee. (2014). First interim report on mining for the Minister of Finance . https://www.taxcom.org.za/docs/20151201%20DTC%20First%20Interim%20Report%20 on%20Mining%20(hard-rock).pdf Davis Tax Committee. (2016). Second and final report on hard-rock mining for the Minister of Finance . 20171113 Second and final hard-rock mining report on website.pdf Department of Petroleum and Energy, Petroleum Division. (2005). Petroleum policy handbook . Government of Papua New Guinea. Ernst & Young. (2019). Global oil and gas tax guide . https://globaltaxnews.ey.com/news/20195677-ey-global-oil-and-gas-tax-guide-2019 Ghana Revenue Authority. (n.d.). Mineral royalties tax. https://gra.gov.gh/portfolio/mineralroyalties-tax/ Hogan, L. & Goldsworthy, B. (2010). International mineral taxation: Experience and issues. In P. Daniel, M. Keen, & C. McPherson (Eds.), The taxation of petroleum and minerals . Routledge. https://www.international-arbitration-attorney.com/wp-content/uploads/ arbitrationlaw1394930.pdf Intergovernmental Forum on Mining, Minerals, Metals and Sustainable Development & Organisation for Economic Co-operation and Development. (2017b). Limiting the impact of excessive interest deductions on mining revenue. https://www.oecd.org/content/dam/ oecd/en/about/programmes/beps-in-mining/limiting-the-impact-of-excessive-interestdeductions-on-mining-revenue.pdf	[ "chosen", "and", "how", "it", "is", "designed", ",", "it", "must", "be", "clearly", "defined", "in", "the", "law", ".", "Clear", "rules", "on", "how", "to", "implement", "ring", "-", "fencing", "in", "mining", "-", "including", "methods", "to", "apportion", "revenues", "and", "expenditures", "and", "how", "to", "deal", "with", "domestic", "transfer", "pricing", "scenariosare", "critical", ".", "Clear", "criteria", "must", "be", "developed", "to", "enable", "effective", "implementation", "by", "both", "companies", "and", "governments", ".", "\n\n", "#", "#", "Financial", "Support", "for", "the", "OECD", "Comes", "From", "the", "Following", "Donors", ":", "\n\n", "<", "!", "--", "image", "--", ">", "\n\n", "<", "!", "--", "image", "--", ">", "\n\n", "<", "!", "--", 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Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation193 Figure 3.37. Specialisation index and citation impact across domains of Ukraine’s S&T ecosystem against the EaP average, for publications Specialisation indexNo pubs. 100 500 1 000Normalised citation impact2 1.3 1 0.75 0.50.25 0.5 1 2 4 Agrifood Biotechnology Chemistry and chemical engineering Electric and electronic technologies Energy Environmental sciences and industries Fundamental physics and mathematics Governance, culture, education and the economy Health and wellbeing ICT and computer science Mechanical engineering and heavy machinery Nanotechnology and materials Optics and photonics Transportation Figure 3.38. Specialisation index across domains of Ukraine’s S&T ecosystem against the EaP average, for patents 0.8 0.6 0.4 1.0 2.0 Specialisation indexTransportation Energy Health and wellbeing Optics and photonics Biotechnology Electric and electronic technologies Environmental sciences and industries ICT and computer science Agrifood Nanotechnology and materials Mechanical engineering and heavy machinery Fundamental physics and mathematics Chemistry and chemical engineering Governance, culture, education and the economy 194 Part 3 Analysis of scientific and technological potential UkraineTemporal evolution of the domains Period over period change in the relative size of each domain, domain size and data source size independent (% change for 2015-2018, over previous period 2011-2014) Change in share of publicationsChange in share of patents Change, weighted average of publications and patents Agrifood 52.73% 2.65% 15.11% Biotechnology -15.47% 6.79% -6.79% Chemistry and chemical engineering -33.56% -3.20% -25.04% Electric and electronic technologies -8.23% -7.50% -7.82% Energy 8.66% -16.42% -5.00% Environmental sciences and industries 3.99% -13.16% -0.79% Fundamental physics and mathematics -19.92% -8.80% -18.72% Governance, culture, education and the economy43.97% -5.97% 42.48% Health and wellbeing 36.91% 2.67% 19.96% ICT and computer science 32.17% 19.32% 28.72% Mechanical engineering and heavy machinery15.33% 1.31% 4.41% Nanotechnology and materials -15.97% -7.24% -14.05% Optics and photonics -29.69% -7.14% -24.07% Transportation 64.95% 7.79% 37.53%Table 3.18. Temporal evolution of Ukraine’s S&T domains Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation195 5. Identification of the main actors and collaboration patterns within the S&T specialisation do- mains The use of all metadata information for each S&T record gathered offers the opportunity to identify local and international actors linked to specific documents produced by the EaP as a whole and by each EaP country. 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"engineering", "and", "heavy", "machinery", "\n", "Fundamental", "physics", "and", "mathematics", "\n", "Chemistry", "and", "chemical", "engineering", "\n", "Governance", ",", "culture", ",", "education", "and", "the", "economy", "\n", "194", "\n ", "Part", "3", "Analysis", "of", "scientific", "and", "technological", "potential", "\n", "UkraineTemporal", "evolution", "of", "the", "domains", "\n", "Period", "over", "period", "change", "in", "the", "relative", "size", "of", "each", "domain", ",", "\n", "domain", "size", "and", "data", "source", "size", "independent", "\n", "(", "%", "change", "for", "2015", "-", "2018", ",", "over", "previous", "period", "2011", "-", "2014", ")", "\n", "Change", "in", "\n", "share", "of", "\n", "publicationsChange", "in", "share", "\n", "of", "patents", "Change", ",", "weighted", "average", "of", "\n", "publications", "and", "patents", "\n", "Agrifood", "52.73", "%", "2.65", "%", "15.11", "%", "\n", "Biotechnology", "-15.47", "%", "6.79", "%", "-6.79", "%", "\n", "Chemistry", "and", "chemical", "engineering", "-33.56", "%", "-3.20", "%", "-25.04", "%", "\n", "Electric", "and", "electronic", "technologies", "-8.23", "%", "-7.50", "%", "-7.82", "%", "\n", "Energy", "8.66", "%", "-16.42", "%", "-5.00", "%", "\n", "Environmental", "sciences", "and", "industries", "3.99", "%", "-13.16", "%", "-0.79", "%", "\n", "Fundamental", "physics", "and", "mathematics", "-19.92", "%", "-8.80", "%", "-18.72", "%", "\n", "Governance", ",", "culture", ",", "education", "and", "the", "\n", "economy43.97", "%", "-5.97", "%", "42.48", "%", "\n", "Health", "and", "wellbeing", "36.91", "%", "2.67", "%", "19.96", "%", "\n", "ICT", "and", "computer", "science", "32.17", "%", "19.32", "%", "28.72", "%", "\n", "Mechanical", "engineering", "and", "heavy", "\n", "machinery15.33", "%", "1.31", "%", "4.41", "%", "\n", "Nanotechnology", "and", "materials", "-15.97", "%", "-7.24", "%", "-14.05", "%", "\n", "Optics", "and", "photonics", "-29.69", "%", "-7.14", "%", "-24.07", "%", "\n", "Transportation", "64.95", "%", "7.79", "%", "37.53%Table", "3.18", ".", "Temporal", "evolution", "of", "Ukraine", "’s", "S&T", "domains", "\n", "Smart", "Specialisation", "in", "the", "Eastern", "Partnership", "countries", "-", "Potential", "for", "knowledge", "-", "based", "economic", "cooperation195", "\n", "5", ".", "Identification", "of", "the", "main", "\n", "actors", "and", "collaboration", "patterns", "\n", "within", "the", "S&T", "specialisation", "do-", "\n", "mains", "\n", "The", "use", "of", "all", "metadata", "information", "for", "each", "S&T", "\n", "record", "gathered", "offers", "the", "opportunity", "to", "identify", "\n", "local", "and", "international", "actors", "linked", "to", "specific", "\n", "documents", "produced", "by", "the", "EaP", "as", "a", "whole", "and", "\n", "by", "each", "EaP", "country", ".", "This", "information", ",", "in", "turn", ",", "has", "\n", "allowed", "national", "and", "international", "collabora-", "\n", "tion", "networks", "in", "which", "the", "EaP", "countries", "’", "S&T", "\n", "ecosystems", "are", "active", "to", "be", "disentangled", ",", "in", "ag-", "\n", "gregate", "and", "by", "identified", "S&T" ]	[]
thermal budget through the following process. - the insulator 280 is provided over the conductor 242 with the insulator 244 positioned therebetween. - the insulator 280 preferably includes an excess-oxygen region. - silicon oxide, silicon oxynitride, silicon nitride oxide, silicon nitride, silicon oxide to which fluorine is added, silicon oxide to which carbon is added, silicon oxide to which carbon and nitrogen are added, porous silicon oxide, a resin, or the like is preferably included. - silicon oxide and silicon oxynitride, which have thermal stability, are preferable. - the insulator 280 When the insulator 244 is not provided, the insulator 280 is in contact with the side surfaces of the oxide 230 a and the oxide 230 b . In this case, oxygen contained in the insulator 280 is sometimes supplied to the channel formation region of the oxide 230 owing to heating. Note that the concentration of impurities such as water or hydrogen in the insulator 280 is preferably lowered. - the insulator 281 functioning as an interlayer film is preferably provided over the insulator 280 . - the concentration of impurities such as water or hydrogen in the insulator 281 is preferably lowered. - the capacitor 100 a is provided in a region overlapping with the transistor 200 a . - the capacitor 100 a includes the conductor 110 , the insulator 130 , and the conductor 120 over the insulator 130 . - a conductor that can be used for the conductor 205 , the conductor 260 , or the like can be used. - the capacitor 100 a is formed in an opening provided in the insulator 244 , the insulator 280 , and the insulator 281 . - the conductor 110 functioning as a lower electrode and the conductor 120 functioning as an upper electrode face each other with the insulator 130 as a dielectric positioned therebetween. - the conductor 110 of the capacitor 100 a is formed in contact with the conductor 242 a of the transistor 200 a. - the capacitor 100 a can have a larger capacitance without an increase in its projected area. Therefore, it is preferred that the capacitor 100 a be a cylindrical capacitor (have a side surface area larger than a bottom surface area). - the above structure can increase the capacitance per unit area of the capacitor 100 a and advance further miniaturization or higher integration of	[ "thermal", "budget", "through", "the", "following", "process", ".", "\n", "-", "the", "insulator", "280", "\n", "is", "provided", "over", "the", "conductor", "242", "with", "the", "insulator", "244", "positioned", "therebetween", ".", "\n", "-", "the", "insulator", "280", "\n", "preferably", "includes", "an", "excess", "-", "oxygen", "region", ".", "\n", "-", "silicon", "oxide", ",", "silicon", "oxynitride", ",", "silicon", "nitride", "oxide", ",", "silicon", "nitride", ",", "silicon", "oxide", "to", "which", "fluorine", "is", "added", ",", "silicon", "oxide", "to", "which", "carbon", "is", "added", ",", "silicon", "oxide", "to", "which", "carbon", "and", "nitrogen", "are", "added", ",", "porous", "silicon", "oxide", ",", "a", "resin", ",", "or", "the", "like", "\n", "is", "preferably", "included", ".", "\n", "-", "silicon", "oxide", "and", "silicon", "oxynitride", ",", "which", "have", "thermal", "stability", ",", "\n", "are", "preferable", ".", "\n", "-", "the", "insulator", "280", "\n", "When", "the", "insulator", "244", "is", "not", "provided", ",", "the", "insulator", "280", "is", "in", "contact", "with", "the", "side", "surfaces", "of", "the", "oxide", "230", "a", "and", "the", "oxide", "230", "b", ".", "In", "this", "case", ",", "oxygen", "contained", "in", "the", "insulator", "280", "is", "sometimes", "supplied", "to", "the", "channel", "formation", "region", "of", "the", "oxide", "230", "owing", "to", "heating", ".", "Note", "that", "the", "concentration", "of", "impurities", "such", "as", "water", "or", "hydrogen", "in", "the", "insulator", "280", "is", "preferably", "lowered", ".", "\n", "-", "the", "insulator", "281", "functioning", "as", "an", "interlayer", "film", "\n", "is", "preferably", "provided", "over", "the", "insulator", "280", ".", "\n", "-", "the", "concentration", "of", "impurities", "such", "as", "water", "or", "hydrogen", "in", "the", "insulator", "281", "\n", "is", "preferably", "lowered", ".", "\n", "-", "the", "capacitor", "100", "a", "\n", "is", "provided", "in", "a", "region", "overlapping", "with", "the", "transistor", "200", "a", ".", "\n", "-", "the", "capacitor", "100", "a", "\n", "includes", "the", "conductor", "110", ",", "the", "insulator", "130", ",", "and", "the", "conductor", "120", "over", "the", "insulator", "130", ".", "\n", "-", "a", "conductor", "that", "can", "be", "used", "for", "the", "conductor", "205", ",", "the", "conductor", "260", ",", "or", "the", "like", "\n", "can", "be", "used", ".", "\n", "-", "the", "capacitor", "100", "a", "\n", "is", "formed", "in", "an", "opening", "provided", "in", "the", "insulator", "244", ",", "the", "insulator", "280", ",", "and", "the", "insulator", "281", ".", "\n", "-", "the", "conductor", "110", "functioning", "as", "a", "lower", "electrode", "and", "the", "conductor", "120", "functioning", "as", "an", "upper", "electrode", "\n", "face", "each", "other", "with", "the", "insulator", "130", "as", "a", "dielectric", "positioned", "therebetween", ".", "\n", "-", "the", "conductor", "110", "of", "the", "capacitor", "100", "a", "\n", "is", "formed", "in", "contact", "with", "the", "conductor", "242", "a", "of", "the", "transistor", "200", "a.", "\n", "-", "the", "capacitor", "100", "a", "\n", "can", "have", "a", "larger", "capacitance", "without", "an", "increase", "in", "its", "projected", "area", ".", "Therefore", ",", "it", "is", "preferred", "that", "the", "capacitor", "100", "a", "be", "a", "cylindrical", "capacitor", "(", "have", "a", "side", "surface", "area", "larger", "than", "a", "bottom", "surface", "area", ")", ".", "\n", "-", "the", "above", "structure", "\n", "can", "increase", "the", "capacitance", "per", "unit", "area", "of", "the", "capacitor", "100", "a", "and", "advance", "further", "miniaturization", "or", "higher", "integration", "of" ]	[]
0.515 0.376 12 Manufacture of tobacco products 3.213 2.254 0.178 13 Manufacture of textiles 3.119 0.791 14 Manufacture of wearing apparel 2.291 2.066 15 Manufacture of leather and related products 4.075 1.112 16 Manufacture of wood and of products of wood and cork 2.215 2.886 0.899 17 Manufacture of paper and paper products 0.956 18.1 Printing and service activities related to printing 2.609 1.743 0.773 19 Manufacture of coke and refined petroleum products 2.930 0.466 1.322 0.412 0.788 20.1 Manufacture of basic chemicals 0.364 1.860 0.864 0.774 1.412 0.726 20.2 Manufacture of pesticides and other agrochemical products 0.617 0.597 0.497 3.324 0.965 20.3 Manufacture of paints 1.967 0.812 1.389 20.4 Manufacture of soap and detergents 0.699 1.765 0.608 1.174 0.944 0.809 20.5 Manufacture of other chemical products 2.254 0.597 0.742 1.338 1.017 20.6 Manufacture of man-made fibres 5.575 0.425 21 Manufacture of basic pharmaceutical products 1.156 1.305 0.596 0.996 1.126 0.822 22 Manufacture of rubber and plastic products 0.849 2.636 1.282 0.227 0.837 23 Manufacture of other non-metallic mineral products 0.906 1.766 1.836 0.467 23.1 Manufacture of glass and glass products 0.988 2.553 1.839 0.620 23.3 Manufacture of clay building materials 2.142 1.288 0.700 23.4 Manufacture of other porcelain and ceramic products 5.381 0.262 23.5 Manufacture of cement, lime and plaster 1.688 1.579 1.438 0.330 0.769 24 Manufacture of basic metals 0.366 1.366 1.924 0.617 1.679 25.1 Manufacture of structural metal products 1.867 1.561 25.2 Manufacture of tanks 1.412 2.630 1.304 25.3 Manufacture of steam generators 4.405 25.4 Manufacture of weapons and ammunition 0.584 2.015 1.610 1.317 25.5 Forging, pressing, stamping and roll-forming of metal 1.265 2.948 0.634 0.982 25.6 Treatment and coating of metals; machining 1.323 1.535 2.551 0.591Table 2.32. Specialised industries using data for patents issued Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation95 NACE Industry name Armenia Azerbaijan Belarus Georgia Moldova Ukraine 25.7 Manufacture of cutlery, tools and general hardware 0.866 1.330 1.880 0.959 0.609 25.9 Manufacture of other fabricated metal products 4.074 26.1 Manufacture of electronic components and boards 1.957 0.540 1.311 0.666 0.962 0.565 26.2 Manufacture of computers and peripheral equipment 2.220 0.390 1.635 0.618 0.280 0.856 26.3 Manufacture of communication equipment 1.010 0.682 1.158 1.505 0.825 0.820 26.4 Manufacture of consumer electronics 3.283 0.278 1.743 26.5 Manufacture of instruments and appliances for measuring 0.216 0.777 1.364 0.680 1.020 1.943 26.6 Manufacture of irradiation 1.696 1.774 0.509 0.635 1.295 26.7Manufacture	[ "0.515", "0.376", "\n", "12", "Manufacture", "of", "tobacco", "products", "3.213", "2.254", "0.178", "\n", "13", "Manufacture", "of", "textiles", "3.119", "0.791", "\n", "14", "Manufacture", "of", "wearing", "apparel", "2.291", "2.066", "\n", "15", "Manufacture", "of", "leather", "and", "related", "products", "4.075", "1.112", "\n", "16", "Manufacture", "of", "wood", "and", "of", "products", "of", "wood", "and", "cork", "2.215", "2.886", "0.899", "\n", "17", "Manufacture", "of", "paper", "and", "paper", "products", "0.956", "\n", "18.1", "Printing", "and", "service", "activities", "related", "to", "printing", "2.609", "1.743", "0.773", "\n", "19", "Manufacture", "of", "coke", "and", "refined", "petroleum", "products", "2.930", "0.466", "1.322", "0.412", "0.788", "\n", "20.1", "Manufacture", "of", "basic", "chemicals", "0.364", "1.860", "0.864", "0.774", "1.412", "0.726", "\n", "20.2", "Manufacture", "of", "pesticides", "and", "other", "agrochemical", "products", "0.617", "0.597", "0.497", "3.324", "0.965", "\n", "20.3", "Manufacture", "of", "paints", "1.967", "0.812", "1.389", "\n", "20.4", "Manufacture", "of", "soap", "and", "detergents", "0.699", "1.765", "0.608", "1.174", "0.944", "0.809", "\n", "20.5", "Manufacture", "of", "other", "chemical", "products", "2.254", "0.597", "0.742", "1.338", "1.017", "\n", "20.6", "Manufacture", "of", "man", "-", "made", "fibres", "5.575", "0.425", "\n", "21", "Manufacture", "of", "basic", "pharmaceutical", "products", "1.156", "1.305", "0.596", "0.996", "1.126", "0.822", "\n", "22", "Manufacture", "of", "rubber", "and", "plastic", "products", "0.849", "2.636", "1.282", "0.227", "0.837", "\n", "23", "Manufacture", "of", "other", "non", "-", "metallic", "mineral", "products", "0.906", "1.766", "1.836", "0.467", "\n", "23.1", "Manufacture", "of", "glass", "and", "glass", "products", "0.988", "2.553", "1.839", "0.620", "\n", "23.3", "Manufacture", "of", "clay", "building", "materials", "2.142", "1.288", "0.700", "\n", "23.4", "Manufacture", "of", "other", "porcelain", "and", "ceramic", "products", "5.381", "0.262", "\n", "23.5", "Manufacture", "of", "cement", ",", "lime", "and", "plaster", "1.688", "1.579", "1.438", "0.330", "0.769", "\n", "24", "Manufacture", "of", "basic", "metals", "0.366", "1.366", "1.924", "0.617", "1.679", "\n", "25.1", "Manufacture", "of", "structural", "metal", "products", "1.867", "1.561", "\n", "25.2", "Manufacture", "of", "tanks", "1.412", "2.630", "1.304", "\n", "25.3", "Manufacture", "of", "steam", "generators", "4.405", "\n", "25.4", "Manufacture", "of", "weapons", "and", "ammunition", "0.584", "2.015", "1.610", "1.317", "\n", "25.5", "Forging", ",", "pressing", ",", "stamping", "and", "roll", "-", "forming", "of", "metal", "1.265", "2.948", "0.634", "0.982", "\n", "25.6", "Treatment", "and", "coating", "of", "metals", ";", "machining", "1.323", "1.535", "2.551", "0.591Table", "2.32", ".", "Specialised", "industries", "using", "data", "for", "patents", "issued", "\n", "Smart", "Specialisation", "in", "the", "Eastern", "Partnership", "countries", "-", "Potential", "for", "knowledge", "-", "based", "economic", "cooperation95", "\n ", "NACE", " ", "Industry", "name", "\n", "Armenia", "\n", "Azerbaijan", "\n", "Belarus", "\n", "Georgia", "\n", "Moldova", "\n", "Ukraine", "\n", "25.7", "Manufacture", "of", "cutlery", ",", "tools", "and", "general", "hardware", "0.866", "1.330", "1.880", "0.959", "0.609", "\n", "25.9", "Manufacture", "of", "other", "fabricated", "metal", "products", "4.074", "\n", "26.1", "Manufacture", "of", "electronic", "components", "and", "boards", "1.957", "0.540", "1.311", "0.666", "0.962", "0.565", "\n", "26.2", "Manufacture", "of", "computers", "and", "peripheral", "equipment", "2.220", "0.390", "1.635", "0.618", "0.280", "0.856", "\n", "26.3", "Manufacture", "of", "communication", "equipment", "1.010", "0.682", "1.158", "1.505", "0.825", "0.820", "\n", "26.4", "Manufacture", "of", "consumer", "electronics", "3.283", "0.278", "1.743", "\n", "26.5", "Manufacture", "of", "instruments", "and", "appliances", "for", "measuring", "0.216", "0.777", "1.364", "0.680", "1.020", "1.943", "\n", "26.6", "Manufacture", "of", "irradiation", "1.696", "1.774", "0.509", "0.635", "1.295", "\n", "26.7Manufacture" ]	[]
digital twin requires replication of the factory, its robots, processes and the overlay of an AI algorithm. To facilitate this cooperation, EU companies should be encouraged to participate in an “AI Vertical Priorities Plan”. The aim of this plan would be to accelerate AI development across the ten strategic sectors where EU business models will benefit most from rapid AI introduction (automotives, advanced manufacturing and robotics, energy, telecoms, agriculture, aerospace, defence, environmental forecasting, pharma and healthcare). Companies that participate in the plan would benefit from EU funding for model development and a specific set of exemptions regarding competition and AI experimentation. In particular, to overcome the EU’s lack of large data sets, model training should be fed with data freely contributed by multiple EU companies within a certain sector. It should be supported within open-source frameworks, safeguarded from antitrust enforcement by competition authorities. Experimentation should be encouraged via the opening up, EU-wide coordination and harmonisation of national “AI Sandbox regimes” to companies participating in the plan. These experimental “sand - boxes” would enable regular assessments of regulatory hindrances deriving from EU or national legislation and provide feedback from private companies and research centres to regulators. Given the dominance of US providers, the EU must find a middle way between promoting its domestic cloud industry and ensuring access to the technologies it needs . It is too late for the EU to try and develop systematic challengers to the major US cloud providers: the investment needs involved are too large and would divert resources away from sectors and companies where the EU’s innovative prospects are better. However, for reasons of European sovereignty, the EU should ensure that it has a competitive domestic industry that can meet the demand for “sover - eign cloud” solutions. To achieve this goal, the report recommends adopting EU-wide data security policies for collaboration between EU and non-EU cloud providers, allowing access to US hyperscalers’ latest cloud technolo - gies while preserving encryption, security and ring-fenced services for trusted EU providers. At the same time, the EU should legislate mandatory standards for public sector procurement, thereby levelling the playing field for EU companies against larger non-EU players. Outside of “sovereign” market segments, it is recommended to negotiate a low barrier “digital transatlantic marketplace”, guaranteeing supply chain security and trade opportunities for EU and US tech companies on fair and equal conditions. To make these opportunities equally attractive	[ "digital", "twin", "requires", "replication", "of", "the", "factory", ",", "its", "robots", ",", "\n", "processes", "and", "the", "overlay", "of", "an", "AI", "algorithm", ".", "To", "facilitate", "this", "cooperation", ",", "EU", "companies", "should", "be", "encouraged", "to", "\n", "participate", "in", "an", "“", "AI", "Vertical", "Priorities", "Plan", "”", ".", "The", "aim", "of", "this", "plan", "would", "be", "to", "accelerate", "AI", "development", "across", "the", "\n", "ten", "strategic", "sectors", "where", "EU", "business", "models", "will", "benefit", "most", "from", "rapid", "AI", "introduction", "(", "automotives", ",", "advanced", "\n", "manufacturing", "and", "robotics", ",", "energy", ",", "telecoms", ",", "agriculture", ",", "aerospace", ",", "defence", ",", "environmental", "forecasting", ",", "pharma", "\n", "and", "healthcare", ")", ".", "Companies", "that", "participate", "in", "the", "plan", "would", "benefit", "from", "EU", "funding", "for", "model", "development", "\n", "and", "a", "specific", "set", "of", "exemptions", "regarding", "competition", "and", "AI", "experimentation", ".", "In", "particular", ",", "to", "overcome", "the", "EU", "’s", "\n", "lack", "of", "large", "data", "sets", ",", "model", "training", "should", "be", "fed", "with", "data", "freely", "contributed", "by", "multiple", "EU", "companies", "within", "\n", "a", "certain", "sector", ".", "It", "should", "be", "supported", "within", "open", "-", "source", "frameworks", ",", "safeguarded", "from", "antitrust", "enforcement", "\n", "by", "competition", "authorities", ".", "Experimentation", "should", "be", "encouraged", "via", "the", "opening", "up", ",", "EU", "-", "wide", "coordination", "and", "\n", "harmonisation", "of", "national", "“", "AI", "Sandbox", "regimes", "”", "to", "companies", "participating", "in", "the", "plan", ".", "These", "experimental", "“", "sand", "-", "\n", "boxes", "”", "would", "enable", "regular", "assessments", "of", "regulatory", "hindrances", "deriving", "from", "EU", "or", "national", "legislation", "and", "\n", "provide", "feedback", "from", "private", "companies", "and", "research", "centres", "to", "regulators", ".", "\n", "Given", "the", "dominance", "of", "US", "providers", ",", "the", "EU", "must", "find", "a", "middle", "way", "between", "promoting", "its", "domestic", "cloud", "\n", "industry", "and", "ensuring", "access", "to", "the", "technologies", "it", "needs", ".", "It", "is", "too", "late", "for", "the", "EU", "to", "try", "and", "develop", "systematic", "\n", "challengers", "to", "the", "major", "US", "cloud", "providers", ":", "the", "investment", "needs", "involved", "are", "too", "large", "and", "would", "divert", "resources", "\n", "away", "from", "sectors", "and", "companies", "where", "the", "EU", "’s", "innovative", "prospects", "are", "better", ".", "However", ",", "for", "reasons", "of", "European", "\n", "sovereignty", ",", "the", "EU", "should", "ensure", "that", "it", "has", "a", "competitive", "domestic", "industry", "that", "can", "meet", "the", "demand", "for", "“", "sover", "-", "\n", "eign", "cloud", "”", "solutions", ".", "To", "achieve", "this", "goal", ",", "the", "report", "recommends", "adopting", "EU", "-", "wide", "data", "security", "policies", "for", "\n", "collaboration", "between", "EU", "and", "non", "-", "EU", "cloud", "providers", ",", "allowing", "access", "to", "US", "hyperscalers", "’", "latest", "cloud", "technolo", "-", "\n", "gies", "while", "preserving", "encryption", ",", "security", "and", "ring", "-", "fenced", "services", "for", "trusted", "EU", "providers", ".", "At", "the", "same", "time", ",", "the", "\n", "EU", "should", "legislate", "mandatory", "standards", "for", "public", "sector", "procurement", ",", "thereby", "levelling", "the", "playing", "field", "for", "EU", "\n", "companies", "against", "larger", "non", "-", "EU", "players", ".", "Outside", "of", "“", "sovereign", "”", "market", "segments", ",", "it", "is", "recommended", "to", "negotiate", "\n", "a", "low", "barrier", "“", "digital", "transatlantic", "marketplace", "”", ",", "guaranteeing", "supply", "chain", "security", "and", "trade", "opportunities", "for", "EU", "\n", "and", "US", "tech", "companies", "on", "fair", "and", "equal", "conditions", ".", "To", "make", "these", "opportunities", "equally", "attractive" ]	[]
\| I \| \| J \| J \| J \| J \| \| \|-----------------\|-----------------\|-----------------\|---------------\|----------------------\|-------------------\|---------\| \| \| \| % female \| % female \| Number (000,000) \| Number (000,000) \| \| \| Youth \| Adults \| Youth \| Adults \| Youth \| Adults \| Country \| \| 4.6.2 \| \| \| \| \| \| \| \| 83 ₋₁ ᵢ \| 72 ₋₁ ᵢ \| 58 ₋₁ ᵢ \| 70 ₋₁ ᵢ \| 1,110 ₋₁ ᵢ \| 5,312 ₋₁ ᵢ \| AGO \| \| 66 ₋₁ \| \| \| \| 856 ₋₁ \| 4,009 ₋₁ \| BEN \| \| ᵢ \| 47 ₋₁ ᵢ \| 60 ₋₁ ᵢ \| 60 ₋₁ ᵢ \| ᵢ \| ᵢ \| \| \| … \| … \| … \| … \| … \| … \| BWA \| \| 54 ₋₁ \| 34 ₋₁ ᵢ \| 52 ₋₁ ᵢ \| 55 ₋₁ ᵢ \| 2,072 ₋₁ ᵢ \| 8,225 ₋₁ \| BFA \| \| ᵢ 94 \| \| \| \| 152 ₋₁ ᵢ \| ᵢ 1,678 ₋₁ ᵢ \| \| \| ₋₁ ᵢ 99 ₋₁ ᵢ \| 76 ₋₁ ᵢ 91 ₋₁ ᵢ \| 53 ₋₁ ᵢ 29 ₋₁ ᵢ \| 64 ₋₁ ᵢ \| 70 ₋₁ ᵢ 1 ₋₁ ᵢ \| 39 ₋₁ ᵢ \| CMR \| \| 86 ₋₃ ᵢ \| 78 ₋₃ ᵢ \| 59 ₋₃ ᵢ 57 ₋₃ \| 62 ₋₃ ᵢ 60 ₋₃ \| 703 ₋₃ ᵢ 706 ₋₃ ᵢ \| 3,262 ₋₃ ᵢ 1,699 \| CAF \| \| 38 ₋₃ ᵢ \| 37 ₋₃ ᵢ 27 ₋₁ ᵢ \| ᵢ 54 ₋₁ ᵢ \| ᵢ 56 ₋₁ ᵢ \| 2,186 ₋₁ ᵢ \| ₋₃ ᵢ 6,652 ₋₁ \| TCD \| \| 36 ₋₁ ᵢ \| 62 ₋₁ ᵢ \| 47 ₋₁ ᵢ \| 56 ₋₁ ᵢ \| 28 ₋₁ ᵢ \| ᵢ 196 ₋₁ ᵢ \| \| \| 82 ₋₁ ᵢ \| 81 ₋₂ ᵢ \| 58 ₋₂ ᵢ \| 64 ₋₂ ᵢ \| 187 ₋₂ ᵢ \| 654 ₋₂ ᵢ \| COM \| \| 82 ₋₂ ᵢ \| \| \| \| 804 ₋₄ \| 1,484 ₋₄ \| \| \| \| 50 ₋₂ ᵢ \| 76 ₋₄ \| 65 ₋₄ \| \| 10,137 ₋₁ \| COG CIV \| \| 67 ₋₂ 88 ₋₁ \| 81 ₋₁ ᵢ \| 61 ₋₁ ᵢ \| 74 ₋₁ ᵢ \| 2,202 ₋₁ ᵢ \| ᵢ \| \| \| ᵢ \| … \| … \| …	[ "\|", "I", " ", "\|", " ", "\|", "J", " ", "\|", "J", " ", "\|", "J", " ", "\|", "J", " ", "\|", " ", "\|", "\n", "\|-----------------\|-----------------\|-----------------\|---------------\|----------------------\|-------------------\|---------\|", "\n", "\|", " ", "\|", " ", "\|", "%", "female", " ", "\|", "%", "female", " ", "\|", "Number", "(", "000,000", ")", " ", "\|", "Number", "(", "000,000", ")", " ", "\|", " ", "\|", "\n", "\|", "Youth", " ", "\|", "Adults", " ", "\|", "Youth", " ", "\|", "Adults", " ", "\|", "Youth", " ", "\|", "Adults", " ", "\|", "Country", "\|", "\n", "\|", "4.6.2", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "\n", "\|", "83", "₋₁", "ᵢ", " ", "\|", "72", "₋₁", "ᵢ", " ", "\|", "58", "₋₁", "ᵢ", " ", "\|", "70", "₋₁", "ᵢ", " ", "\|", "1,110", "₋₁", "ᵢ", " ", "\|", "5,312", "₋₁", "ᵢ", " ", "\|", "AGO", " ", "\|", "\n", "\|", "66", "₋₁", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "856", "₋₁", " ", "\|", "4,009", "₋₁", " ", "\|", "BEN", " ", "\|", "\n", "\|", "ᵢ", " ", "\|", "47", "₋₁", "ᵢ", " ", "\|", "60", "₋₁", "ᵢ", " ", "\|", "60", "₋₁", "ᵢ", " ", "\|", "ᵢ", " ", "\|", "ᵢ", " ", "\|", " ", "\|", "\n", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "BWA", " ", "\|", "\n", "\|", "54", "₋₁", " ", "\|", "34", "₋₁", "ᵢ", " ", "\|", "52", "₋₁", "ᵢ", " ", "\|", "55", "₋₁", "ᵢ", " ", "\|", "2,072", "₋₁", "ᵢ", " ", "\|", "8,225", "₋₁", " ", "\|", "BFA", " ", "\|", "\n", "\|", "ᵢ", "94", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "152", "₋₁", "ᵢ", " ", "\|", "ᵢ", "1,678", "₋₁", "ᵢ", " ", "\|", " ", "\|", "\n", "\|", "₋₁", "ᵢ", "99", "₋₁", "ᵢ", " ", "\|", "76", "₋₁", "ᵢ", "91", "₋₁", "ᵢ", "\|", "53", "₋₁", "ᵢ", "29", "₋₁", "ᵢ", "\|", "64", "₋₁", "ᵢ", " ", "\|", "70", "₋₁", "ᵢ", "1", "₋₁", "ᵢ", " ", "\|", "39", "₋₁", "ᵢ", " ", "\|", "CMR", " ", "\|", "\n", "\|", "86", "₋₃", "ᵢ", " ", "\|", "78", "₋₃", "ᵢ", " ", "\|", "59", "₋₃", "ᵢ", "57", "₋₃", " ", "\|", "62", "₋₃", "ᵢ", "60", "₋₃", "\|", "703", "₋₃", "ᵢ", "706", "₋₃", "ᵢ", " ", "\|", "3,262", "₋₃", "ᵢ", "1,699", " ", "\|", "CAF", " ", "\|", "\n", "\|", "38", "₋₃", "ᵢ", " ", "\|", "37", "₋₃", "ᵢ", "27", "₋₁", "ᵢ", "\|", "ᵢ", "54", "₋₁", "ᵢ", " ", "\|", "ᵢ", "56", "₋₁", "ᵢ", " ", "\|", "2,186", "₋₁", "ᵢ", " ", "\|", "₋₃", "ᵢ", "6,652", "₋₁", " ", "\|", "TCD", " ", "\|", "\n", "\|", "36", "₋₁", "ᵢ", " ", "\|", "62", "₋₁", "ᵢ", " ", "\|", "47", "₋₁", "ᵢ", " ", "\|", "56", "₋₁", "ᵢ", " ", "\|", "28", "₋₁", "ᵢ", " ", "\|", "ᵢ", "196", "₋₁", "ᵢ", " ", "\|", " ", "\|", "\n", "\|", "82", "₋₁", "ᵢ", " ", "\|", "81", "₋₂", "ᵢ", " ", "\|", "58", "₋₂", "ᵢ", " ", "\|", "64", "₋₂", "ᵢ", " ", "\|", "187", "₋₂", "ᵢ", " ", "\|", "654", "₋₂", "ᵢ", " ", "\|", "COM", " ", "\|", "\n", "\|", "82", "₋₂", "ᵢ", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "804", "₋₄", " ", "\|", "1,484", "₋₄", " ", "\|", " ", "\|", "\n", "\|", " ", "\|", "50", "₋₂", "ᵢ", " ", "\|", "76", "₋₄", " ", "\|", "65", "₋₄", " ", "\|", " ", "\|", "10,137", "₋₁", " ", "\|", "COG", "CIV", "\|", "\n", "\|", "67", "₋₂", "88", "₋₁", " ", "\|", "81", "₋₁", "ᵢ", " ", "\|", "61", "₋₁", "ᵢ", " ", "\|", "74", "₋₁", "ᵢ", " ", "\|", "2,202", "₋₁", "ᵢ", " ", "\|", "ᵢ", " ", "\|", " ", "\|", "\n", "\|", "ᵢ", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " " ]	[]
education 1 CHAPTER 1. Introduction .................................................................................................................................................................................. 5 Expectations of leaders at the school and system level have been changing ........................................................................................... 10 Guide to the report ........................................................................................................................................................................................................ 13 Recommendations ......................................................................................................................................................................................................... 17 CHAPTER 2. School leadership: Roles, impact and standards ........................................................................................................... 23 School principals are expected to fulfil various leadership roles .................................................................................................................. 25 The impact of school principals can be significant .............................................................................................................................................. 31 Leadership standards can guide action and certification ................................................................................................................................ 39 Conclusion ....................................................................................................................................................................................................................... 42 CHAPTER 3. School leadership: Selection, training and conditions .................................................................................................. 45 Improving selection processes is needed to professionalize principals’ careers ..................................................................................... 47 Countries need to do more to prepare and train school leaders ................................................................................................................... 57 Countries try to make principalship an attractive career path ...................................................................................................................... 67 Conclusion ........................................................................................................................................................................................................................ 74 CHAPTER 4. Shared school leadership ...................................................................................................................................................... 77 School personnel can lead if given opportunities and support ...................................................................................................................... 79 Students can exercise leadership through formal channels and informally ............................................................................................. 87 Engaged parents and community members can steer schools towards their goals ............................................................................. 90 Conclusion ....................................................................................................................................................................................................................... 94 CHAPTER 5. System leadership .................................................................................................................................................................. 97 System leaders need to set expectations for quality and equity ................................................................................................................. 99 System leaders should be instructional leaders .............................................................................................................................................. 105 Civil servants are often not selected to serve as system leaders .............................................................................................................. 108 Conclusion ..................................................................................................................................................................................................................... 112 CHAPTER 6. Political leadership ............................................................................................................................................................... 115 Political motivations determine education system development .............................................................................................................. 117 The direction of education is influenced by many other actors ................................................................................................................... 127 Conclusion ..................................................................................................................................................................................................................... 137 xiv 2024/5 • GLOBAL EDUCATION MONITORING REPORTMonitoring education in the Sustainable Development Goals 139 CHAPTER 7. Introduction ............................................................................................................................................................................ 143 Conference on Education Data and Statistics ................................................................................................................................................... 145 SDG 4 Scorecard .......................................................................................................................................................................................................... 145 2025 Comprehensive Review ................................................................................................................................................................................. 147 CHAPTER 8. Primary and secondary education .................................................................................................................................. 150 Access and completion .............................................................................................................................................................................................. 152 Learning ......................................................................................................................................................................................................................... 157 Focus 8.1. Mathematics anxiety negatively affects mathematics performance ................................................................................... 164 CHAPTER 9. Early childhood education ................................................................................................................................................. 170 Focus 9.1. Preschool leadership needs attention ............................................................................................................................................. 177 Focus 9.2. Training for parents and caregivers can support early childhood development ............................................................... 179 CHAPTER 10. Technical, vocational, tertiary and adult education ................................................................................................. 182 Focus 10.1. Higher education leaders face major challenges ....................................................................................................................... 190 Focus 10.2. Women are under-represented in higher education leadership .......................................................................................... 194 CHAPTER 11. Skills for work ..................................................................................................................................................................... 196 Focus 11.1. Can leadership be taught? ................................................................................................................................................................. 201 CHAPTER 12. Equity .................................................................................................................................................................................... 206 Focus 12.1. Peers affect individual education outcomes ............................................................................................................................... 214 CHAPTER 13. Youth and adult literacy ................................................................................................................................................... 218 Focus 13.1. 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per labelled topic group (or ‘domain’) in the Eastern Partnership region. Nanotechnolo- gy and materials is the domain with the most re- cords (with a total of 35 742), followed by Health and wellbeing (29 643), Fundamental physics and mathematics (29 120), Mechanical engineering and heavy machinery (24 097) and ICT and com- puter science (16 529).Although very small in comparison to publications and patents, the number of EC projects is useful to gauge the activity of internationally-connected EaP research and innovation actors. In this con- text, there are a significant number of EC projects on Nanotechnology and materials (65 projects), Environmental sciences and industries (63), ITC and computer science (61), Health and wellbeing (56) and Energy (54). The highest concentration, however, is in the Governance domain (197), due to the nature of these projects. The number of publications in international jour- nals has been increasing considerably in recent years within the majority of domains and is ex- pected to continue to do so, as reflected by the CAGR (compound annual growth rate), except for Chemistry and chemical engineering and Optics and photonics, where the number of records has remained fairly consistent throughout the time range considered. Some of the domains present an especially high growth rate, such as Govern- ance, culture, education and the economy (24%), Transportation (20%) and Health (15%). Publications (critical mass \| CAGR)PatentsEC projectsTotal Nanotechnology and materials 29 067 3.7% 6 641 65 35 773 Health and wellbeing 17 874 14.5% 11 726 56 29 656 Fundamental physics and mathematics 26 852 1.9% 2 255 18 29 125 Mechanical engineering and heavy machinery5 582 9.9% 18 510 8 24 100 ICT and computer science 13 111 13.8% 4 044 61 17 216 Biotechnology 10 340 5.7% 5 837 29 16 206 Governance, culture, education and the economy14 895 24.3% 434 197 15 526 Environmental sciences and industries 10 735 10.6% 3 272 63 14 070 Electric and electronic technologies 5 874 5.8% 7 009 17 12 900 Energy 5 496 8.6% 5 828 54 11 378 Chemistry and chemical engineering 8 132 1.4% 2 380 14 10 526 Optics and photonics 8 043 -0.3% 1 896 19 9 958 Agrifood 2 949 12.5% 5 907 21 8 877 Transportation 2 355 20.4% 1 984 25 4 364Table 3.4. Number of records per labelled topic group (i.e. ‘domain’) in the Eastern Partnership region 154 Part 3 Analysis	[ "per", "labelled", "topic", "group", "(", "or", "‘", "domain", "’", ")", "\n", "in", "the", "Eastern", "Partnership", "region", ".", "Nanotechnolo-", "\n", "gy", "and", "materials", "is", "the", "domain", "with", "the", "most", "re-", "\n", "cords", "(", "with", "a", "total", "of", "35", "742", ")", ",", "followed", "by", "Health", "\n", "and", "wellbeing", "(", "29", "643", ")", ",", "Fundamental", "physics", "and", "\n", "mathematics", "(", "29", "120", ")", ",", "Mechanical", "engineering", "\n", "and", "heavy", "machinery", "(", "24", "097", ")", "and", "ICT", "and", "com-", "\n", "puter", "science", "(", "16", "529).Although", "very", "small", "in", "comparison", "to", "publications", "\n", "and", "patents", ",", "the", "number", "of", "EC", "projects", "is", "useful", "\n", "to", "gauge", "the", "activity", "of", "internationally", "-", "connected", "\n", "EaP", "research", "and", "innovation", "actors", ".", "In", "this", "con-", "\n", "text", ",", "there", "are", "a", "significant", "number", "of", "EC", "projects", "\n", "on", "Nanotechnology", "and", "materials", "(", "65", "projects", ")", ",", "\n", "Environmental", "sciences", "and", "industries", "(", "63", ")", ",", "ITC", "\n", "and", "computer", "science", "(", "61", ")", ",", "Health", "and", "wellbeing", "\n", "(", "56", ")", "and", "Energy", "(", "54", ")", ".", "The", "highest", "concentration", ",", "\n", "however", ",", "is", "in", "the", "Governance", "domain", "(", "197", ")", ",", "due", "\n", "to", "the", "nature", "of", "these", "projects", ".", "\n", "The", "number", "of", "publications", "in", "international", "jour-", "\n", "nals", "has", "been", "increasing", "considerably", "in", "recent", "\n", "years", "within", "the", "majority", "of", "domains", "and", "is", "ex-", "\n", "pected", "to", "continue", "to", "do", "so", ",", "as", "reflected", "by", "the", "\n", "CAGR", "(", "compound", "annual", "growth", "rate", ")", ",", "except", "for", "\n", "Chemistry", "and", "chemical", "engineering", "and", "Optics", "\n", "and", "photonics", ",", "where", "the", "number", "of", "records", "has", "\n", "remained", "fairly", "consistent", "throughout", "the", "time", "\n", "range", "considered", ".", "Some", "of", "the", "domains", "present", "\n", "an", "especially", "high", "growth", "rate", ",", "such", "as", "Govern-", "\n", "ance", ",", "culture", ",", "education", "and", "the", "economy", "(", "24", "%", ")", ",", "\n", "Transportation", "(", "20", "%", ")", "and", "Health", "(", "15", "%", ")", ".", "\n", "Publications", "\n", "(", "critical", "mass", "\|", "CAGR)PatentsEC", "\n", "projectsTotal", "\n", "Nanotechnology", "and", "materials", "29", "067", "3.7", "%", "6", "641", "65", "35", "773", "\n", "Health", "and", "wellbeing", "17", "874", "14.5", "%", "11", "726", "56", "29", "656", "\n", "Fundamental", "physics", "and", "mathematics", "26", "852", "1.9", "%", "2", "255", "18", "29", "125", "\n", "Mechanical", "engineering", "and", "heavy", "\n", "machinery5", "582", "9.9", "%", "18", "510", "8", "24", "100", "\n", "ICT", "and", "computer", "science", "13", "111", "13.8", "%", "4", "044", "61", "17", "216", "\n", "Biotechnology", "10", "340", "5.7", "%", "5", "837", "29", "16", "206", "\n", "Governance", ",", "culture", ",", "education", "and", "the", "\n", "economy14", "895", "24.3", "%", "434", "197", "15", "526", "\n", "Environmental", "sciences", "and", "industries", "10", "735", "10.6", "%", "3", "272", "63", "14", "070", "\n", "Electric", "and", "electronic", "technologies", "5", "874", "5.8", "%", "7", "009", "17", "12", "900", "\n", "Energy", "5", "496", "8.6", "%", "5", "828", "54", "11", "378", "\n", "Chemistry", "and", "chemical", "engineering", "8", "132", "1.4", "%", "2", "380", "14", "10", "526", "\n", "Optics", "and", "photonics", "8", "043", "-0.3", "%", "1", "896", "19", "9", "958", "\n", "Agrifood", "2", "949", "12.5", "%", "5", "907", "21", "8", "877", "\n", "Transportation", "2", "355", "20.4", "%", "1", "984", "25", "4", "364Table", "3.4", ".", "Number", "of", "records", "per", "labelled", "topic", "group", "(", "i.e.", "‘", "domain", "’", ")", "in", "the", "Eastern", "Partnership", "region", "\n", "154", "\n ", "Part", "3", "Analysis" ]	[]
devices (e.g., visible light cameras, thermographic camera and/or thermal imaging camera (TIC) systems, forward-looking infrared (FLIR) camera systems, radiometric thermal camera systems, active infrared (IR) camera systems, ultraviolet (UV) camera systems, and/or the like), light detection and ranging (LiDAR) sensors, proximity sensors (e.g., IR radiation detector and the like), depth sensors, ambient light sensors, optical light sensors, ultrasonic transceivers, microphones, inductive loops, force and/or load sensors, remote charge converters (RCC), rotor speed and position sensor(s), fiber optic gyro (FOG) inertial sensors, Attitude & Heading Reference Unit (AHRU), fibre Bragg grating (FBG) sensors and interrogators, tachometers, engine temperature gauges, pressure gauges, transformer sensors, airspeed-measurement meters, speed indicators, and/or the like. The IMUs, MEMS, and/or NEMS can include, for example, one or more 3-axis accelerometers, one or more 3-axis gyroscopes, one or more magnetometers, one or more compasses, one or more barometers, and/or the like. Additionally or alternatively, the can include sensors of various compute components such as, for example, digital thermal sensors (DTS) of respective processors/cores, thermal sensor on-die (TSOD) of respective dual inline memory modules (DIMMs), baseboard thermal sensors, and/or any other sensor(s), such as any of those discussed herein. The allow the to change its state, position, and/or orientation, or move or control a mechanism or system. The comprise electrical and/or mechanical devices for moving or controlling a mechanism or system, and converts energy (e.g., electric current or moving air and/or liquid) into some kind of motion. The is configured to operate one or based on one or more captured events, instructions, control signals, and/or configurations received from a , , and/or other components of the . As examples, the actuators can be or include any number and combination of the following: soft actuators (e.g., actuators that changes its shape in response to a stimuli such as, for example, mechanical, thermal, magnetic, and/or electrical stimuli), hydraulic actuators, pneumatic actuators, mechanical actuators, electromechanical actuators (EMAs), microelectromechanical actuators, electrohydraulic actuators, linear actuators, linear motors, rotary motors, DC motors, stepper motors, servomechanisms, electromechanical switches, electromechanical relays (EMRs), power switches, valve actuators, piezoelectric actuators and/or biomorphs, thermal biomorphs, solid state actuators, solid state relays (SSRs), shape-memory alloy-based actuators, electroactive polymer-based actuators, relay driver integrated circuits (ICs), solenoids, impactive actuators/mechanisms (e.g., jaws, claws, tweezers, clamps, hooks, mechanical fingers, humaniform dexterous robotic hands, and/or other gripper mechanisms that physically grasp by direct impact upon an object), propulsion actuators/mechanisms (e.g., wheels, axles, thrusters, propellers, engines, motors	[ "devices", "(", "e.g.", ",", "visible", "light", "cameras", ",", "thermographic", "camera", "and/or", "thermal", "imaging", "camera", "(", "TIC", ")", "systems", ",", "forward", "-", "looking", "infrared", "(", "FLIR", ")", "camera", "systems", ",", "radiometric", "thermal", "camera", "systems", ",", "active", "infrared", "(", "IR", ")", "camera", "systems", ",", "ultraviolet", "(", "UV", ")", "camera", "systems", ",", "and/or", "the", "like", ")", ",", "light", "detection", "and", "ranging", "(", "LiDAR", ")", "sensors", ",", "proximity", "sensors", "(", "e.g.", ",", "IR", "radiation", "detector", "and", "the", "like", ")", ",", "depth", "sensors", ",", "ambient", "light", "sensors", ",", "optical", "light", "sensors", ",", "ultrasonic", "transceivers", ",", "microphones", ",", "inductive", "loops", ",", "force", "and/or", "load", "sensors", ",", "remote", "charge", "converters", "(", "RCC", ")", ",", "rotor", "speed", "and", "position", "sensor(s", ")", ",", "fiber", "optic", "gyro", "(", "FOG", ")", "inertial", "sensors", ",", "Attitude", "&", "amp", ";", "Heading", "Reference", "Unit", "(", "AHRU", ")", ",", "fibre", "Bragg", "grating", "(", "FBG", ")", "sensors", "and", "interrogators", ",", "tachometers", ",", "engine", "temperature", "gauges", ",", "pressure", "gauges", ",", "transformer", "sensors", ",", "airspeed", "-", "measurement", "meters", ",", "speed", "indicators", ",", "and/or", "the", "like", ".", "The", "IMUs", ",", "MEMS", ",", "and/or", "NEMS", "can", "include", ",", "for", "example", ",", "one", "or", "more", "3", "-", "axis", "accelerometers", ",", "one", "or", "more", "3", "-", "axis", "gyroscopes", ",", "one", "or", "more", "magnetometers", ",", "one", "or", "more", "compasses", ",", "one", "or", "more", "barometers", ",", "and/or", "the", "like", ".", "Additionally", "or", "alternatively", ",", "the", " ", "can", "include", "sensors", "of", "various", "compute", "components", "such", "as", ",", "for", "example", ",", "digital", "thermal", "sensors", "(", "DTS", ")", "of", "respective", "processors", "/", "cores", ",", "thermal", "sensor", "on", "-", "die", "(", "TSOD", ")", "of", "respective", "dual", "inline", "memory", "modules", "(", "DIMMs", ")", ",", "baseboard", "thermal", "sensors", ",", "and/or", "any", "other", "sensor(s", ")", ",", "such", "as", "any", "of", "those", "discussed", "herein", ".", "\n\n", "The", " ", "allow", "the", " ", "to", "change", "its", "state", ",", "position", ",", "and/or", "orientation", ",", "or", "move", "or", "control", "a", "mechanism", "or", "system", ".", "The", " ", "comprise", "electrical", "and/or", "mechanical", "devices", "for", "moving", "or", "controlling", "a", "mechanism", "or", "system", ",", "and", "converts", "energy", "(", "e.g.", ",", "electric", "current", "or", "moving", "air", "and/or", "liquid", 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",", "linear", "actuators", ",", "linear", "motors", ",", "rotary", "motors", ",", "DC", "motors", ",", "stepper", "motors", ",", "servomechanisms", ",", "electromechanical", "switches", ",", "electromechanical", "relays", "(", "EMRs", ")", ",", "power", "switches", ",", "valve", "actuators", ",", "piezoelectric", "actuators", "and/or", "biomorphs", ",", "thermal", "biomorphs", ",", "solid", "state", "actuators", ",", "solid", "state", "relays", "(", "SSRs", ")", ",", "shape", "-", "memory", "alloy", "-", "based", "actuators", ",", "electroactive", "polymer", "-", "based", "actuators", ",", "relay", "driver", "integrated", "circuits", "(", "ICs", ")", ",", "solenoids", ",", "impactive", "actuators", "/", "mechanisms", "(", "e.g.", ",", "jaws", ",", "claws", ",", "tweezers", ",", "clamps", ",", "hooks", ",", "mechanical", "fingers", ",", "humaniform", "dexterous", "robotic", "hands", ",", "and/or", "other", "gripper", "mechanisms", "that", "physically", "grasp", "by", "direct", "impact", "upon", "an", "object", ")", ",", "propulsion", "actuators", "/", "mechanisms", "(", "e.g.", ",", "wheels", ",", "axles", ",", "thrusters", ",", "propellers", ",", "engines", ",", "motors" ]	[]
OECD Economics Department Working Papers No. 1839 Assessing the impact of global demographic change on the German economy By: Donal Smith, Robert Grundke, Marius Bickmann and Tony Huang OECD Economics Department Working Papers Assessing the impact of global demographic change on the German economy No.1839 P UBE 2 \| AS SESSING THE IMPACT OF GLOBAL DEMOGRAPHIC CHANGE ON THE GERMAN ECONOMY © OECD 2025 OECD Working Papers should not be reported as representing the official views of the OECD or of its member countries. The opinions expressed and arguments employed are those of the authors. Working Papers describe preliminary results or research in progress by the author(s) and are published to stimulate discussion on a broad range of issues on which the OECD works. Comments on Working Papers are welcomed, and may be sent to the OECD Economics Department . 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mous Boston crime family. \| \| BS \| Princess Margaret, Countess of Snowdon, (Margaret Rose 21 August 1930 - 9 February 2002) was the younger daughter of King George VI and Queen Elizabeth The Queen Mother and the only sibling of Queen Elizabeth II. Princess Margaret, Countess of Snowdon, (Margaret Rose 21 August 1930 - 9 February 2002) was the younger daughter of King George VI and Queen Elizabeth The Queen Mother and the only sibling of Queen Elizabeth II. Princess Margaret, Countess of Snowdon, (Margaret Rose 21 August 1930 - 9 February 2002) was the younger daughter of King George VI and Queen Elizabeth The Queen Mother and the only sibling of Queen Elizabeth II. ... \| Bulger was one of the FBI's most wanted fugitives for 16 years until he was captured in Santa Monica, California, in 2011. He was convicted in 2013 of a litany of crimes, including racketeering, extortion, money-laundering, and murder. He was sentenced to two consecutive life sentences plus five years. He died in federal prison in West Virginia on Tuesday at the age of 89. Bulger was one of the FBI's most wanted fugitives for 16 years until he was captured in Santa Monica, California, in 2011. \| \| DBS \| She married Antony Armstrong-Jones, a photographer, in 1960. It was the first marriage for the Queen and the first for Prince Philip, Duke of Edinburgh. After divorcing Armstrong-Jones in 1978, she married Group Captain Peter Townsend in June that same year. She died at the age of 71 on 9 February 2002. Why did Princess Margaret marry Antony Armstrong- Jones? \| He was one of the FBI's most wanted fugitives for 16 years until his capture in 2011. Born in Boston, Whitey Bulger was the son of Irish immi- grants. After serving in the U.S. Navy during World War II, Whitey Bulger joined the Irish-American mafia, the Winter Hill Gang, in the early 1950s. He quickly rose through the ranks of the gang, eventually becoming its leader. He was known as 'Whitey' because of his light brown hair and blue eyes. \| \| BS b \| Princess Margaret, Countess of Snowdon (Margaret Rose 21 August 1930 - 9 February 2002) was the eldest daugh- ter of King George VI and Queen Elizabeth The Queen Mother. 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me and meeting me at the river. I live in your legacy and you live in mine. Ubuntu! Dear Ancestors. What did you hope for when you went to the Americas. What were you running from? Where were you heading? Did you feel sorry for the people of the land you lived on? What were your dreams made of? These engagements with the themes of the CHC, through their materialization in artworks, reached a broader audience. By centering the past on the creation of the future, the hope is to disrupt the hierarchy of progress hidden beneath a linear perception of time -the idea that one can only exist at odds with the other. Embracing our ancestral roots and giving them space in our existence allows us to reunite past, present and future within ourselves, which is a crucial element not only of individual healing, but also of shaping the kinds of conversations across time and space that can foster a sustainable future. The shift from individual to collective memory can play a crucial role in reshaping our cultural and societal identities.²³ This process involves both remembering our ancestral experience and wisdom and imagining how they can be transposed into future scenarios. Allowing a continuous interaction between past, present and future experiences, and understanding time in a non-linear way, is a way of disrupting the narratives of linear progress embedded in Western thinking. Indeed, the idea of nonlinearity, or circularity, is echoed more broadly in Indigenous cultures ' approach 23 Bachleitner (2022). Collective memory and the social creation of identities: Linking the past with the present and future. to time, and particularly in the worldview of author Robin Wall Kimmerer, for whom time is often conceptualized as circular or cyclical. Kimmerer also puts forward the idea that the non-linearity of time is linked to a vision of the interconnection between all forms of life.² ⁴ The Common Ground program, beyond the CHC weekend, thus offers a space to explore these collaborative processes and alternative temporal frameworks through art, poetry, letters and other forms of entanglement. ## Bringing the Body into the Collective Healing Process A key aspect of the Common Ground residency and its application of the CHC methodology was the understanding that knowledge is not produced in a vacuum but is deeply connected to the bodily experiences of those involved. 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BASE DURING FINANCIAL DERIVATIVES ARRANGEMENTS Company A is a mining company in Country A. It has entered into a long-term financial derivative instrument arrangement with an overseas-based independent Investment Bank Z: • whereby if the market price of the commodity extracted by Company A falls below a set price of USD 100, Investment Bank Z will pay Company A the difference between the set price (USD 100) and the actual market price. • whereby if the market price of the commodity rises above the set price, Company A pays the difference to Investment Bank Z. Based on the facts of the case, the price was set at USD 100, while the market demand trends and longer-term prognosis indicated that the commodity price would be mostly rising in the coming 5 years to USD 120, USD 130, USD 150, USD 170, and USD 200, respectively, with a very low risk that the price drops below USD 100. As a result of this arrangement, most of the profits earned over the 5-year period are paid to the independent Investment Bank Z. During the audit, an exchange of information exercise was carried out, which identified that Investment Bank Z had entered into an identical but reverse arrangement with Company B, which is controlled by the beneficial owner of Company A. As a result of this arrangement, most of the profit—less the annual administration fee that stays with the bank— was paid to Company B. Investment Bank Z was thus acting as a mere intermediary, which was effectively a BEPS arrangement between related parties in Companies A and B. Ring-fencing rules could avoid this type of scenario by ring-fencing the outcomes of such derivative instrument arrangements into separate tax bases that would not allow Company A to offset such expenses resulting from derivatives unless the gain was made on such a derivative transaction. This way, even in the absence of detection of such a BEPS arrangement, the tax base is protected. Ring-fencing rules effectively disallow Company A from offsetting losses derived from these types of transactions from mining revenues. In case of legitimate derivative arrangements, the company will still be entitled to offset the derivative losses from derivative gains earned in subsequent periods. This feature of ring-fencing rules is particularly relevant for developing countries that may lack the tools and infrastructure to detect such abusive arrangements. 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\| \| … \| … \| … \| … \| … \| Belarus \| \| \| 0.95 \| 0.88 \| 0.8 \| 1 \| … \| Belgium \| \| Bermuda \| … \| … \| … \| … \| … \| \| \| Bosnia and Herzegovina \| 0.58 \| … \| … \| 0.5 \| … \| \| \| Bulgaria \| 0.56 \| 0.65 \| 0.73 \| 0.71 \| … \| \| \| \| 0.88 \| 0.78 \| 0.7 \| 0.83 \| … \| Canada \| \| Croatia \| … \| … \| … \| … \| … \| \| \| \| 0.84 \| \| 0.55 \| … \| … \| Czechia 0.47 \| \| \| … \| 0.68 \| 0.77 \| 0.83 \| … \| Denmark \| \| \| 0.88 \| 0.83 \| 0.95 \| 0.83 \| … \| Estonia \| \| Finland \| 0.88 \| 0.81 \| 0.85 \| … \| 100 ₋₂ \| \| \| France \| 1 \| 0.99 \| 1 \| 1 \| … \| \| \| \| 1 \| 0.9 \| 0.95 \| 0.92 \| … \| Germany \| \| Greece \| … \| … \| … \| … \| … \| \| \| \| 1 \| 0.86 \| 0.93 \| 0.79 \| … \| Hungary \| \| Iceland \| … \| … \| … \| … \| … \| \| \| \| 0.88 \| 0.81 \| 0.85 \| 0.83 \| … \| Ireland \| \| Italy \| 0.88 \| 0.88 \| 0.8 \| 0.83 \| … \| \| \| Latvia \| 1 \| \| \| \| \| 0.86 \| \| \| \| … \| 0.95 \| 1 … \| … … \| \| \| Lithuania \| 1 \| \| … 0.9 \| 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The analysis of endurance, measured in cycles, is performed using the method de- scribed by IEC 61951-2, clause 7.5.1.4. Figure 10 shows the cycling profiles of an AAA NiMH battery. The test procedure is as follows: 1. The battery is first discharged at a rate of 0.2 C until it reaches the cut-off voltage of 1 V . 2. The battery is then charged for 2 h at a 0.5 C rate. The charge termination criterion is either a ∆V of 5 mV to 10 mV (this criterion refers to a decline of voltage during charge after a certain time) or a maximum charge time of 132 min.Batteries 2025 ,11, 30 14 of 20 3. Immediately after charging, the battery is discharged at a 0.5 C rate until it reaches the cut-off voltage of 1 V . Batteries 2025, 11, x FOR PEER REVIEW 15 of 21 Furthermore, all portable NiMH batteries tested during the recovery experiment show a discharge duration longer than 4 h, and in terms of columbic eﬃciency, the highest observed value is 78% for the D size and the smallest value is 62% for the 9V battery. 6. Endurance of Portable NiMH Batteries The analysis of endurance, measured in cycles, is performed using the method de- scribed by IEC 61951-2, clause 7.5.1.4. Figure 10 shows the cycling proﬁles of an AAA NiMH battery. The test procedure is as follows: 1. The battery is ﬁrst discharged at a rate of 0.2 C until it reaches the cut-oﬀ voltage of 1 V. 2. The battery is then charged for 2 h at a 0.5 C rate. The charge termination criterion is either a ΔV of 5 mV to 10 mV (this criterion refers to a decline of voltage during charge after a certain time) or a maximum charge time of 132 min. 3. Immediately after charging, the battery is discharged at a 0.5 C rate until it reaches the cut-oﬀ voltage of 1 V. If the discharge duration is less than 72 min, the experiment is terminated. Figure 10. NiMH endurance in cycles analysis according to IEC 61951-2 for an AAA Energizer 700 mAh battery (a) voltage proﬁle, (b) current proﬁle, (c) capacity, and d) columbic eﬃciency vs. cycle number. The vertical red lines in (c,d) indicate checkup cycles. 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the high cost of complying with regulations that apply once companies reach a particular size. As a result, the EU has proportionally fewer small and medium-sized companies than the US and proportionally more micro companies [see Figure 7] . However, there is a close link between the size of companies and technology adoption. Evidence from the US show that adoption rises with firm size for all advanced technologiesxii. Likewise, while in 2023 30% of large businesses in the EU had adopted AI, only 7% of SMEs had done the samexiii. Size enables adoption because larger companies can spread the high fixed costs of AI investment over greater revenues, they can count on more skilled management to make the necessary organisational changes, and they can deploy AI more productively owing to larger data sets. In other words, a fragmented Single Market puts EU companies at a disadvantage in terms of the speed of adoption and diffusion of new AI applications. 04. Regulatory gold-plating refers to the practice where national governments or authorities go beyond the minimum requirements set by European Union legislation when implementing it into domestic law. 30THE FUTURE OF EUROPEAN COMPETITIVENESS — PART A \| CHAPTER 2FIGURE 7 Size distribution of firms in EU and US 2021 Note: Does not include the self-employed. EU data refer to the following sectors: industry, construction and market services (except public administration and defence; compulsory social security; activities of membership organizations). For the EU, to discount the self-employed, data on businesses with 0 employees has been used as a proxy.US data refers to the private sector, which includes agriculture but represents around 1% of the total firms. Data for the US is based on the 1st quarter of the year. Source: ECB calculations based on Eurostat and Bureau of Labour Statistics data Competition for computing power and lack of investment in connectivity could soon translate into digital bottlenecks [see the chapter on digitalisation and advanced technologies] . Training new foundation models and building vertically integrated AI applications requires massive increases in computing power, which is triggering an ongoing global “AI chip race” at huge expense. This is a race in which smaller and less well-funded EU companies may struggle to compete. 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\| \| Figure 6.2 \| Teacher hiring and firing is politically influenced in many countries ....................................................................................... \| 120 \| \| Figure 6.3 \| Within two years of their appointment, 51% of education ministers have left office........................................................ \| 123 \| \| Figure 7.1 \| A country-led process will be used to make decisions on education statistics................................................................... \| 146 \| \| Figure 7.2 \| Some SDG 4 indicators have been under scrutiny due to low data coverage....................................................................... \| 147 \| \| Figure 8.1 \| Since 2015, the out-of-school population has stagnated........................................................................................................... \| 152 \| \| Figure 8.2 \| Sub-Saharan Africa accounts for more than half of the total number out-of-school children and adolescents ........................................................................................................................................................................................ \| 154 \| \| Figure 8.3 \| COVID-19 does not appear to have had a negative impact on out-of-school rates ........................................................... \| 155 \|	[ "\|", "\n", "\|", "Figure", "6.2", " ", "\|", "Teacher", "hiring", "and", "firing", "is", "politically", "influenced", "in", "many", "countries", ".......................................................................................", " ", "\|", "120", "\|", "\n", "\|", "Figure", "6.3", " ", "\|", "Within", "two", "years", "of", "their", "appointment", ",", "51", "%", "of", "education", "ministers", "have", "left", "office", "........................................................", " ", "\|", "123", "\|", "\n", "\|", "Figure", "7.1", " ", "\|", "A", "country", "-", "led", "process", "will", "be", "used", "to", "make", "decisions", "on", "education", "statistics", "...................................................................", " ", "\|", "146", "\|", "\n", "\|", "Figure", "7.2", " ", "\|", "Some", "SDG", "4", "indicators", "have", "been", "under", "scrutiny", "due", "to", "low", "data", "coverage", ".......................................................................", " ", "\|", "147", "\|", "\n", "\|", "Figure", "8.1", " ", "\|", "Since", "2015", ",", "the", "out", "-", "of", "-", "school", "population", "has", "stagnated", "...........................................................................................................", " ", "\|", "152", "\|", "\n", "\|", "Figure", "8.2", " ", "\|", "Sub", "-", "Saharan", "Africa", "accounts", "for", "more", "than", "half", "of", "the", "total", "number", "out", "-", "of", "-", "school", "children", "and", "adolescents", "........................................................................................................................................................................................", " ", "\|", "154", "\|", "\n", "\|", "Figure", "8.3", " ", "\|", "COVID-19", "does", "not", "appear", "to", "have", "had", "a", "negative", "impact", "on", "out", "-", "of", "-", "school", "rates", "...........................................................", " ", "\|", "155", "\|" ]	[]
salaries of bogus/ghost employees in Delhi alone by the Municipal Corporation of Delhi (MCD). In 2004, over Rs. 32 lakhs (Rs. 3 million or £2.7 million) was released for salaries of 1,826 employees. Six MCD officials were arrested in con -nection with the embezzlement (Times of India, 2009). In summary, previous research demonstrates that government urban health care does not meet the needs of the poor. There seems to be at least four main reasons according to the literature - a shortage of government provision, the attitude of doctors in the government sector to the urban poor, corruption within the system and a lack of trust. Evidence suggests that some doctors and medical practitioners in government hospitals have a poor attitude towards patients from low-income households, offering a poor quality of care (National Family Health Survey, 2014 ; Peters and Muraleedharan, 2008 ; Ishwardat et al., 2016). This leads to issues around trust (Raha et al., 2010 ; Aneli et al., 2018). Large numbers of medical practitioners, as many as 40% in a typical day, are also absent from government facilities ( Pulla, 2015 ; Chaudhury et al., 2006). Corruption within the government system has implied a lack of structure and efficiency around provision ( Kumar, 2003 ; World Bank, 2008 ; Dash et al., 2009 ; Sengupta and Nandy, 2005). Reports around corruption have targeted the Municipal Corporation of Delhi, which is responsible for improvements and coordination of medical health facilities around the city ( Dash et al., 2009 ; Naher et al., 2020). � In our research of the healthcare providers surveyed, more than 50% have been practising for over 20 years in their slum community. Their ages ranged from 22 to 64 years ( x = 38.93, σ = 10.576). The majority (90.7%) reported that they had no other occupation and working in medicine was their only job. There was a split in residency, with 40.8% stating that they lived in the community and 59.2% indicat -ing that they lived outside the community where they practice medicine. This could have some bearing on the levels of trust and respect. However, we could conjecture that as stated by the practitioners themselves long term respect and trust is gained owing to effective and efficient diagnosis, medicine prescriptions and the curing of ailments. 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RING -FENCING 1.0 INTRODUCTION 34 Ring-Fencing Mining Income: A toolkit for tax administrators and policy-makersor incentives available in respect of the profits from downstream activities. On the other hand, taxpayers may prefer to accelerate their cash flows and benefit from tax deferral due to the special rules applicable for the extractive operations, such as the accelerated deduction of capital expenditure (e.g., immediate 100% deduction of such expenditure, rather than being subject to gradual depreciation). Countries will be able to collect taxes from upstream activities (i.e., mining) regardless of the costs (e.g., development costs of downstream infrastructure or losses incurred at the downstream stage, such as risks playing out during the processing, smelting, refining, or transport), or vice versa. As explained above, there may be a motivation to offset downstream expenses against upstream income if upstream is subject to a higher rate of tax. T anzania includes this type of ring-fence in its legislation (see Box 10). Countries with a highly integrated mining sector and differential tax rates may wish to consider this variation. BOX 10. TANZANIA • losses from the separate mining operations may be deducted only in calculating future income from that operation and not income from any other activity whethera mining operation under a different mineral right, processing, smelting, refining or a non-mining activity; • income from the separate mining operations may not be reduced by a loss from any other activity whether a mining operation under a different mineral rights, processing , smelting , refining or a non-mining activity.” Source: Section 65F (1)a, and 1(b) of Chapter 332, Income T ax Act (rev. 2019). Italics are authors’ emphasis. If resource-rich developing countries are seeking to encourage downstream activities, the existence of ring-fencing rules might be a relevant consideration for an investor in considering the economic viability and attractiveness of doing so. The fact that the profits from the downstream activities often result in lower rates of profitability is also reflected in the lower rate of CIT that is applicable to those profits. The investors may want to benefit from the deferral of tax on the upstream activities if they undertake such additional investment into downstream activities; this is why it may be more attractive for investors if there is no ring-fencing regime. Careful consideration should be given to what the costs are (e.g., timing difference of tax collection) and what the benefits are (e.g., attracting investment for	[ "RING", "-FENCING", "1.0", "INTRODUCTION", "\n", "34", "\n", "Ring", "-", "Fencing", "Mining", "Income", ":", "A", "toolkit", "for", "tax", "administrators", "and", "policy", "-", "makersor", "incentives", "available", "in", "respect", "of", "the", "profits", "from", "downstream", "activities", ".", "\n", "On", "the", "other", "hand", ",", "taxpayers", "may", "prefer", "to", "accelerate", "their", "cash", "flows", "and", "\n", "benefit", "from", "tax", "deferral", "due", "to", "the", "special", "rules", "applicable", "for", "the", "extractive", "\n", "operations", ",", "such", "as", "the", "accelerated", "deduction", "of", "capital", "expenditure", "(", "e.g.", ",", "\n", "immediate", "100", "%", "deduction", "of", "such", "expenditure", ",", "rather", "than", "being", "subject", "\n", "to", "gradual", "depreciation", ")", ".", "\n", "Countries", "will", "be", "able", "to", "collect", "taxes", "from", "upstream", "activities", "(", "i.e.", ",", "\n", "mining", ")", "regardless", "of", "the", "costs", "(", "e.g.", ",", "development", "costs", "of", "downstream", "\n", "infrastructure", "or", "losses", "incurred", "at", "the", "downstream", "stage", ",", "such", "as", "risks", "\n", "playing", "out", "during", "the", "processing", ",", "smelting", ",", "refining", ",", "or", "transport", ")", ",", "or", "vice", "\n", "versa", ".", "As", "explained", "above", ",", "there", "may", "be", "a", "motivation", "to", "offset", "downstream", "\n", "expenses", "against", "upstream", "income", "if", "upstream", "is", "subject", "to", "a", "higher", "rate", "of", "\n", "tax", ".", "T", "anzania", "includes", "this", "type", "of", "ring", "-", "fence", "in", "its", "legislation", "(", "see", "Box", "10", ")", ".", "\n", "Countries", "with", "a", "highly", "integrated", "mining", "sector", "and", "differential", "tax", "rates", "\n", "may", "wish", "to", "consider", "this", "variation", ".", "\n", "BOX", "10", ".", "TANZANIA", "\n", "•", "losses", "from", "the", "separate", "mining", "operations", "may", "be", "deducted", "only", "\n", "in", "calculating", "future", "income", "from", "that", "operation", "and", "not", "income", "\n", "from", "any", "other", "activity", "whethera", "mining", "operation", "under", "a", "different", "\n", "mineral", "right", ",", "processing", ",", "smelting", ",", "refining", "or", "a", "non", "-", "mining", "activity", ";", "\n", "•", "income", "from", "the", "separate", "mining", "operations", "may", "not", "be", "reduced", " \n", "by", "a", "loss", "from", "any", "other", "activity", "whether", "a", "mining", "operation", "under", "\n", "a", "different", "mineral", "rights", ",", "processing", ",", "smelting", ",", "refining", " ", "or", "a", " \n", "non", "-", "mining", "activity", ".", "”", "\n", "Source", ":", "Section", "65F", "(", "1)a", ",", "and", "1(b", ")", "of", "Chapter", "332", ",", "Income", "T", "ax", "Act", "(", "rev", ".", "2019", ")", ".", "\n", "Italics", "are", "authors", "’", "emphasis", ".", "\n", "If", "resource", "-", "rich", "developing", "countries", "are", "seeking", "to", "encourage", "downstream", "\n", "activities", ",", "the", "existence", "of", "ring", "-", "fencing", "rules", "might", "be", "a", "relevant", "\n", "consideration", "for", "an", "investor", "in", "considering", "the", "economic", "viability", "and", "\n", "attractiveness", "of", "doing", "so", ".", "The", "fact", "that", "the", "profits", "from", "the", "downstream", "\n", "activities", "often", "result", "in", "lower", "rates", "of", "profitability", "is", "also", "reflected", "in", "the", "\n", "lower", "rate", "of", "CIT", "that", "is", "applicable", "to", "those", "profits", ".", "The", "investors", "may", "want", "to", "\n", "benefit", "from", "the", "deferral", "of", "tax", "on", "the", "upstream", "activities", "if", "they", "undertake", "\n", "such", "additional", "investment", "into", "downstream", "activities", ";", "this", "is", "why", "it", "may", "\n", "be", "more", "attractive", "for", "investors", "if", "there", "is", "no", "ring", "-", "fencing", "regime", ".", "Careful", "\n", "consideration", "should", "be", "given", "to", "what", "the", "costs", "are", "(", "e.g.", ",", "timing", "difference", "\n", "of", "tax", "collection", ")", "and", "what", "the", "benefits", "are", "(", "e.g.", ",", "attracting", "investment", "for", "\n" ]	[]
a kind used for the extraction of ‘soft’ fixed vegetable oils (excluding flours and meals) X X X X 223Oil-seeds and oleaginous fruits, whole or broken, of a kind used for the extraction of other fixed vegetable oils (including flours and meals of oil-seeds or oleaginous fruit, n.e.s.) 231Natural rubber, balata, gutta-percha, guayule, chicle and similar natural gums, in primary forms (including latex) or in plates, sheets or strip 232 Synthetic rubber; reclaimed rubber; waste, parings and scrap of unhardened rubber 244 Cork, natural, raw and waste (including natural cork in blocks or sheets) 245 Fuel wood (excluding wood waste) and wood charcoal X 246 Wood in chips or particles and wood waste X 247 Wood in the rough, whether or not stripped of bark or sapwood, or roughly squared X X Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation305 306 Annexes ARMENIA AZERBAIJAN BELARUS GEORGIA MOLDOVA UKRAINE SITC Goods name Current Emerging Current Emerging Current Emerging Current Emerging Current Emerging Current Emerging 19 12 3 8 65 64 18 26 41 23 51 52 248 Wood, simply worked, and railway sleepers of wood X X X X 251 Pulp and waste paper 261 Silk 263 Cotton 264Jute and other textile bast fibres, n.e.s., raw or processed but not spun; tow and waste of these fibres (including yarn waste and garnetted stock) 265 Vegetable textile fibres (other than cotton and jute), raw or processed but not spun; waste of these fibres 266 Synthetic fibres suitable for spinning X 267 Other man-made fibres suitable for spinning; waste of man-made fibres 268 Wool and other animal hair (including wool tops) 269 Worn clothing and other worn textile articles; rags 271 Confidential trade of group 271 272 Fertilizers, crude, other than those of division 56 273 Stone, sand and gravel X X 274 Sulphur and unroasted iron pyrites 277 Natural abrasives, n.e.s. (including industrial diamonds) 278 Other crude minerals X X X 281 Iron ore and concentrates X X 282 Ferrous waste and scrap; remelting scrap ingots of iron or steel X 283 Copper ores and concentrates; copper mattes; cement copper X X X 284Nickel ores and concentrates; nickel mattes, nickel oxide sinters and other intermediate products of nickel metallurgy 285 Aluminium ores and concentrates (including alumina) X X 286 Uranium or thorium ores and concentrates 287 Ores and concentrates of base metals, n.e.s. X X 288 Non-ferrous	[ "a", "kind", "used", "for", "the", "extraction", "of", "‘", "soft", "’", "fixed", "vegetable", "oils", "(", "excluding", "flours", "and", "\n", "meals", ")", " ", "X", "X", "X", "X", "\n", "223Oil", "-", "seeds", "and", "oleaginous", "fruits", ",", "whole", "or", "broken", ",", "of", "a", "kind", "used", "for", "the", "extraction", "of", "other", "fixed", "vegetable", "oils", "\n", "(", "including", "flours", "and", "meals", "of", "oil", "-", "seeds", "or", "oleaginous", "fruit", ",", "n.e.s", ".", ")", " \n", "231Natural", "rubber", ",", "balata", ",", "gutta", "-", "percha", ",", "guayule", ",", "chicle", "and", "similar", "natural", "gums", ",", "in", "primary", "forms", "(", "including", "latex", ")", "or", "\n", "in", "plates", ",", "sheets", "or", "strip", " \n", "232", "Synthetic", "rubber", ";", "reclaimed", "rubber", ";", "waste", ",", "parings", "and", "scrap", "of", "unhardened", "rubber", " \n", "244", "Cork", ",", "natural", ",", "raw", "and", "waste", "(", "including", "natural", "cork", "in", "blocks", "or", "sheets", ")", " \n", "245", "Fuel", "wood", "(", "excluding", "wood", "waste", ")", "and", "wood", "charcoal", " ", "X", " \n", "246", "Wood", "in", "chips", "or", "particles", "and", "wood", "waste", " ", "X", " \n", "247", "Wood", "in", "the", "rough", ",", "whether", "or", "not", "stripped", "of", "bark", "or", "sapwood", ",", "or", "roughly", "squared", " ", "X", "X", " \n", "Smart", "Specialisation", "in", "the", "Eastern", "Partnership", "countries", "-", "Potential", "for", "knowledge", "-", "based", "economic", "cooperation305", "306", "\n", "Annexes", "\n", "ARMENIA", "AZERBAIJAN", "BELARUS", "GEORGIA", "MOLDOVA", "UKRAINE", "\n", "SITC", "Goods", "name", "Current", "Emerging", "Current", "Emerging", "Current", "Emerging", "Current", "Emerging", "Current", "Emerging", "Current", "Emerging", "\n", "19", "12", "3", "8", "65", "64", "18", "26", "41", "23", "51", "52", "\n", "248", "Wood", ",", "simply", "worked", ",", "and", "railway", "sleepers", "of", "wood", " ", "X", "X", " ", "X", "X", "\n", "251", "Pulp", "and", "waste", "paper", " \n", "261", "Silk", " \n", "263", "Cotton", " \n", "264Jute", "and", "other", "textile", "bast", "fibres", ",", "n.e.s", ".", ",", "raw", "or", "processed", "but", "not", "spun", ";", "tow", "and", "waste", "of", "these", "fibres", "(", "including", "\n", "yarn", "waste", "and", "garnetted", "stock", ")", " \n", "265", "Vegetable", "textile", "fibres", "(", "other", "than", "cotton", "and", "jute", ")", ",", "raw", "or", "processed", "but", "not", "spun", ";", "waste", "of", "these", "fibres", " \n", "266", "Synthetic", "fibres", "suitable", "for", "spinning", " ", "X", " \n", "267", "Other", "man", "-", "made", "fibres", "suitable", "for", "spinning", ";", "waste", "of", "man", "-", "made", "fibres", " \n", "268", "Wool", "and", "other", "animal", "hair", "(", "including", "wool", "tops", ")", " \n", "269", "Worn", "clothing", "and", "other", "worn", "textile", "articles", ";", "rags", " \n", "271", "Confidential", "trade", "of", "group", "271", " \n", "272", "Fertilizers", ",", "crude", ",", "other", "than", "those", "of", "division", "56", " \n", "273", "Stone", ",", "sand", "and", "gravel", " ", "X", "X", " \n", "274", "Sulphur", "and", "unroasted", "iron", "pyrites", " \n", "277", "Natural", "abrasives", ",", "n.e.s", ".", "(", "including", "industrial", "diamonds", ")", " \n", "278", "Other", "crude", "minerals", " ", "X", " ", "X", " ", "X", " \n", "281", "Iron", "ore", "and", "concentrates", " ", "X", "X", "\n", "282", "Ferrous", "waste", "and", "scrap", ";", "remelting", "scrap", "ingots", "of", "iron", "or", "steel", " ", "X", " \n", "283", "Copper", "ores", "and", "concentrates", ";", "copper", "mattes", ";", "cement", "copper", "X", " ", "X", "X", " \n", "284Nickel", "ores", "and", "concentrates", ";", "nickel", "mattes", ",", "nickel", "oxide", "sinters", "and", "other", "intermediate", "products", "of", "nickel", "\n", "metallurgy", " \n", "285", "Aluminium", "ores", "and", "concentrates", "(", "including", "alumina", ")", " ", "X", "X", "\n", "286", "Uranium", "or", "thorium", "ores", "and", "concentrates", " \n", "287", "Ores", "and", "concentrates", "of", "base", "metals", ",", "n.e.s", ".", "X", " ", "X", "\n", "288", "Non", "-", "ferrous" ]	[]
export specialisation for Azerbaijan \| SITC \| Goods name \| Current strength \| %share of exports \| Emerging strength \| %share of exports \| \|--------\|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------\|--------------------\|---------------------\|---------------------\|---------------------\| \| \| \| 3 \| 88.0% \| 8 \| 90.8% \| \| 0 \| Food and live animals \| \| \| \| \| \| 054 \| Vegetables, fresh, chilled, frozen or simply preserved (including dried leguminous vegetables); roots, tubers and other edible vegetable products, n.e.s., fresh or dried \| \| \| X \| 0.7% \| \| 057 \| Fruit and nuts (not including oil nuts), fresh or dried \| \| \| X \| 1.3% \| \| 1 \| Beverages and tobacco \| \| \| \| \| \| 2 \| Crude materials, inedible, except fuels \| \| \| \| \| \| 3 \| Mineral fuels, lubricants and related materials \| \| \| \| \| \| 333 \| Petroleum oils and oils obtained from bituminous minerals, crude \| X \| 82.1% \| X \| 82.1% \| \| 335 \| Residual petroleum products, n.e.s., and related materials \| \| \| X \| 0.2% \| \| 343 \| Natural gas, whether or not liquefied \| X \| 5.6% \| X \| 5.6% \| \| 351 \| Electric current \| \| \| X \| 0.2% \| \| 4 \| Animal and vegetable oils, fats and waxes \| \| \| \| \| \| 5 \| Chemicals and related products, n.e.s. \| \| \| \| \| \| 571 \| Polymers of ethylene, in primary forms \| X \| 0.4% \| \| \| \| 6 \| Manufactured goods classified chiefly by material \| \| \| \| \| \| 679 \| Tubes, pipes and hollow profiles, and tube or pipe fittings, of iron or steel \| \| \| X \| 0.2% \| \| 684 \| Aluminium \| \| \| X \| 0.5% \| \| 7 \| Machinery and transport equipment \| \| \| \| \| \| 8 \| Miscellaneous manufactured articles \| \| \| \| \| \| 9 \| Commodities and transactions not classified elsewhere in the SITC \| \| \| \| \| ## Mapping of goods export specialisations - results for Georgia Results of the export mapping for Georgia are shown in Table 2.18 . The 18 goods categories with current strength represent almost 61% of the total exports for 2012-2019. 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as experiences of searching for belonging. Despite coming from different cultures, religions and nationalities, participants found that power structures and oppressive narratives overlapped and converged in their stories. The group also explored how these legacies continue to shape their lives today. On the second day, activities focused on the third and fourth pillars of CHC: strengthening interconnection, and envisioning just and sustainable futures. After participating in outdoor activities, the group reconvened in a circle to share stories of resilience and survival from their families and communities. Building on the work of the first day, this activity invited participants to reflect on the strengths and coping strategies of their ancestors and to explore how their cultural heritage has equipped them with the resources to face contemporary challenges. It also invited participants to consider the more-than-human as a teacher of resilience and sustainable ways of relating to one another. The activity began with an extract from Robin Wall Kimmerer s book ' Braiding Sweetgrass , ²² which describes how the ' three sisters ' , bean, corn and pumpkin seeds, are planted together in a gardening method practised by Native American peoples. Based on a biological and scientific study of the interactions between these three species, Kimmerer teaches us how, planted together and thanks to the unique characteristics of each plant, they create an environment where they all benefit from each other s presence. This ecological lesson opened the day s sharing ' ' circle, presenting symbiosis as a metaphor for human and more-than-human healing. Throughout the sharing circles, the facilitators chose not to intervene too much in the powerful process of community building that was being woven before their eyes. Indeed, as the discussions progressed, a process of solidarity and mutual recognition emerged, weaving together distinct but interconnected experiences. After providing a theoretical framework, they mostly let the natural flow of the conversation take over, occasionally stepping in to restart the discussion, as the participants were very engaged and responding to each other. Very quickly, the group created a particularly deep and transformative space for sharing. One of the reasons for this is certainly the pre-existing connection among the participants forged during the first online phase of the program. After each workshop, at least one hour was dedicated to discussion and sharing of experiences among the participants. 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60% of the records. Alternatively, Figure 3.19 presents the distribu- tion of analysed records in the form of weighted percentages by type of record. This means that percentages are calculated within each domain relative to the total number of records per data source. This figure, complementing Figure 3.18, allows to better observe the distribution patterns of patents and EC projects, which are smaller, in volume terms, than publications. As presented in Figure 3.19, Governance, culture, education and the economy is primarily composed of EC R&I projects due to the nature of the Eu- ropean research and innovation framework pro- grammes, which support capacity building as well as transnational cooperation projects, typically oriented to research, education, economic devel- opment, education as well as some priority areas such as ICT, energy, transportation and the envi- ronment. Thus, although R&I projects are not the ideal source for identifying purely emerging spe- cialisations, they do allow relevant internationally connected actors in the EaP to be identified, espe- cially in the areas above, as well as, again, gaug- ing the strength of the hard sciences in the EaP. It also enables different relative specialisations to be explored throughout the EaP countries. 58 Noting that the total volume of analysed scientific publi- cations is higher than that of patents. Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation155 Agrifood Biotechnology Chemistry and chemical engineering Electric and electronic technologies Energy Environmental sciences and industries Fundamental physics and mathematics Governance, culture, education and the economy Health and wellbeing ICT and computer science Mechanical engineering and heavy machinery Nanotechnology and materials Optics and photonics Transportation Agrifood 964 315 65 149 1 347 138 196 722 133 615 236 45 52 Biotechnology 964 3 277 178 325 465 342 110 2 687 138 212 1 656 109 45 Chemistry and chemical engineering315 3 277 111 314 694 308 40 682 88 143 1 809 91 9 Electric and electronic technologies65 178 111 3 102 148 660 121 217 1 008 1 213 1 004 856 240 Energy 149 325 314 3 102 666 2 470 288 257 504 2 135 799 185 326 Environmental sciences and industries1 347 465 694 148 666 512 1 128 754 592 693 542 101 113 Fundamental physics and mathematics138 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rising to this challenge. Since the Great Financial Crisis (GFC), a sizeable and persistent gap has opened between private productive investment01 in the EU and the US. At the same time, the private investment gap across the two economies has not been offset by higher government investment, which also dropped after the GFC and has been persistently lower in the EU compared to the US as a share of GDP. EU households provide ample savings to finance higher investment, but at present these savings are not being channelled efficiently into productive investments. In 2022, EU household savings were EUR 1,390 billion compared with EUR 840 billion in the US. But, despite their higher savings, EU households have considerably lower wealth than their US counterparts, largely because of the lower returns they receive from financial markets on their asset holdings. The EU can meet these investment needs without overstretching the resources of the European economy, but the private sector will need public support to finance the plan . The European Commission and the IMF’s Research Department have simulated scenarios of a sustained EU investment push of around 5% of GDP, using their multi-country models. The results suggest that investment of this magnitude would increase output by around 6% within 15 years. Since supply adjusts more gradually than demand – as the build-up of additional capital takes time – the transition phase implies some inflationary pressures, but these pressures dissipate over time. Unlocking the investment will be challenging. Historically in Europe, around four-fifths of productive investment has been under - taken by the private sector, and the remaining one-fifth by the public sector. Delivering private investment of around 4% of GDP through market financing alone would require a reduction in the private cost of capital – by approximately 250 basis points in the European Commission model. Although improved capital market efficiency (e.g. through the completion of the Capital Markets Union) is expected to reduce private financing costs, the reduction will likely be substantially smaller. Fiscal incentives to unlock private investment therefore appear necessary to finance the investment plan, in addition to direct government investment. The required stimulus to private investment will have some impact on public finances, but productivity gains can reduce the fiscal costs . If the investment-related government spending is not compensated by budgetary savings elsewhere, primary fiscal balances may temporarily deteriorate before the investment plan fully exerts its positive	[ "rising", "to", "this", "challenge", ".", "Since", "the", "Great", "Financial", "Crisis", "(", "GFC", ")", ",", "a", "\n", "sizeable", "and", "persistent", "gap", "has", "opened", "between", "private", "productive", "investment01", "in", "the", "EU", "and", "the", "US", ".", "At", "the", "same", "\n", "time", ",", "the", "private", "investment", "gap", "across", "the", "two", "economies", "has", "not", "been", "offset", "by", "higher", "government", "investment", ",", "\n", "which", "also", "dropped", "after", "the", "GFC", "and", "has", "been", "persistently", "lower", "in", "the", "EU", "compared", "to", "the", "US", "as", "a", "share", "of", "GDP", ".", "\n", "EU", "households", "provide", "ample", "savings", "to", "finance", "higher", "investment", ",", "but", "at", "present", "these", "savings", "are", "not", "being", "\n", "channelled", "efficiently", "into", "productive", "investments", ".", "In", "2022", ",", "EU", "household", "savings", "were", "EUR", "1,390", "billion", "compared", "\n", "with", "EUR", "840", "billion", "in", "the", "US", ".", "But", ",", "despite", "their", "higher", "savings", ",", "EU", "households", "have", "considerably", "lower", "wealth", "than", "\n", "their", "US", "counterparts", ",", "largely", "because", "of", "the", "lower", "returns", "they", "receive", "from", "financial", "markets", "on", "their", "asset", "holdings", ".", "\n", "The", "EU", "can", "meet", "these", "investment", "needs", "without", "overstretching", "the", "resources", "of", "the", "European", "economy", ",", "\n", "but", "the", "private", "sector", "will", "need", "public", "support", "to", "finance", "the", "plan", ".", "The", "European", "Commission", "and", "the", "IMF", "’s", "\n", "Research", "Department", "have", "simulated", "scenarios", "of", "a", "sustained", "EU", "investment", "push", "of", "around", "5", "%", "of", "GDP", ",", "using", "their", "\n", "multi", "-", "country", "models", ".", "The", "results", "suggest", "that", "investment", "of", "this", "magnitude", "would", "increase", "output", "by", "around", "6", "%", "\n", "within", "15", "years", ".", "Since", "supply", "adjusts", "more", "gradually", "than", "demand", "–", "as", "the", "build", "-", "up", "of", "additional", "capital", "takes", "time", "\n", "–", "the", "transition", "phase", "implies", "some", "inflationary", "pressures", ",", "but", "these", "pressures", "dissipate", "over", "time", ".", "Unlocking", "the", "\n", "investment", "will", "be", "challenging", ".", "Historically", "in", "Europe", ",", "around", "four", "-", "fifths", "of", "productive", "investment", "has", "been", "under", "-", "\n", "taken", "by", "the", "private", "sector", ",", "and", "the", "remaining", "one", "-", "fifth", "by", "the", "public", "sector", ".", "Delivering", "private", "investment", "of", "around", "\n", "4", "%", "of", "GDP", "through", "market", "financing", "alone", "would", "require", "a", "reduction", "in", "the", "private", "cost", "of", "capital", "–", "by", "approximately", "\n", "250", "basis", "points", "in", "the", "European", "Commission", "model", ".", "Although", "improved", "capital", "market", "efficiency", "(", "e.g.", "through", "\n", "the", "completion", "of", "the", "Capital", "Markets", "Union", ")", "is", "expected", "to", "reduce", "private", "financing", "costs", ",", "the", "reduction", "will", "likely", "\n", "be", "substantially", "smaller", ".", "Fiscal", "incentives", "to", "unlock", "private", "investment", "therefore", "appear", "necessary", "to", "finance", "the", "\n", "investment", "plan", ",", "in", "addition", "to", "direct", "government", "investment", ".", "\n", "The", "required", "stimulus", "to", "private", "investment", "will", "have", "some", "impact", "on", "public", "finances", ",", "but", "productivity", "gains", "\n", "can", "reduce", "the", "fiscal", "costs", ".", "If", "the", "investment", "-", "related", "government", "spending", "is", "not", "compensated", "by", "budgetary", "\n", "savings", "elsewhere", ",", "primary", "fiscal", "balances", "may", "temporarily", "deteriorate", "before", "the", "investment", "plan", "fully", "exerts", "its", "\n", "positive" ]	[]
to their commercial attractiveness, and the tax deferral benefit plays a limited role in making such investment decisions. These considerations are relevant for designing special exceptions from the ring-fencing rules, such as for the purpose of attracting investment into the marginal ore projects, where the tax deferral advantage may play an important role. Some resource-rich countries have found it necessary to relax their ringfencing rules to attract further investment. Resource-rich countries such as PNG and South Africa have had ring-fencing rules for a long time. At some point, these governments considered the need to relax strict ring-fencing rules to attract further investment in the context of low commodity prices (see Box 7). On the other hand, countries such as Kenya, PNG, and the Cook Islands have introduced an exemption to ring-fencing rules in which ## 1.0 INTRODUCTION 2.0 THE FUNDAMENTALS OF RING-FENCING ## 3.0 THE BENEFITS AND RISKS OF RING-FENCING 4.0 DESIGNING RING-FENCING RULES 5.0 THE IMPLEMENTATION OF RING-FENCING RULES 6.0 CONCLUSION unsuccessful exploration expenditures are incurred by the mining investor who holds more than one mine. The policy objective behind the exception seems to be to try to balance different policy objectives: deliver early government revenues and attract exploration investments to their jurisdiction. See Section 4 for more details. ## BOX 7. THE RELAXATION OF RING-FENCING RULES IN PNG AND SOUTH AFRICA Photo: Raina Hattingh ## South Africa In the early 1980s, many mines were being developed in South Africa. If a company owned more than one mine, the unredeemed capital expenditure of one mine could be deducted from the mining income from another mine. Some major mergers and takeovers caused the government authorities to express concerns that vast new capital expenditures could substantially erode the mining tax base. Consequently, South Africa introduced ring-fencing rules mine by mine and distinguished mining from non-mining activities (Davis Tax Committee, 2016, p. 50). Following a steep decline in new mining investment, South Africa announced a partial relaxation of the ring-fencing rules for 'new mines' (a mine opened after March 14, 1990) (Leger & Nicol, 1992). This meant that the 'old mines' in the same entity may have access to the unredeemed capital expenditure of the 'new mine' but limited to 25% of the remaining taxable income of the 'old mines' after they have exhausted all their applicable capital expenditure in a given tax year' (Davis Tax Committee, 2014). Although the old ring-fencing	[ "to", "their", "commercial", "attractiveness", ",", "and", "the", "tax", "deferral", "benefit", "plays", "a", "limited", "role", "in", "making", "such", "investment", "decisions", ".", "These", "considerations", "are", "relevant", "for", "designing", "special", "exceptions", "from", "the", "ring", "-", "fencing", "rules", ",", "such", "as", "for", "the", "purpose", "of", "attracting", "investment", "into", "the", "marginal", "ore", "projects", ",", "where", "the", "tax", "deferral", "advantage", "may", "play", "an", "important", "role", ".", "\n\n", "Some", "resource", "-", "rich", "countries", "have", "found", "it", "necessary", "to", "relax", "their", "ringfencing", "rules", "to", "attract", "further", "investment", ".", "Resource", "-", "rich", "countries", "such", "as", "PNG", "and", "South", "Africa", "have", "had", "ring", "-", "fencing", "rules", "for", "a", "long", "time", ".", "At", "some", "point", ",", "these", "governments", "considered", "the", "need", "to", "relax", "strict", "ring", "-", "fencing", "rules", "to", "attract", "further", "investment", "in", "the", "context", "of", "low", "commodity", "prices", "(", "see", "Box", "7", ")", ".", "On", "the", "other", "hand", ",", "countries", "such", "as", "Kenya", ",", "PNG", ",", "and", "the", "Cook", "Islands", "have", "introduced", "an", "exemption", "to", "ring", "-", "fencing", "rules", "in", "which", "\n\n", "#", "#", "1.0", "INTRODUCTION", "\n\n", "2.0", "THE", "FUNDAMENTALS", "OF", "RING", "-", "FENCING", "\n\n", "#", "#", "3.0", "THE", "BENEFITS", "AND", "RISKS", "OF", "RING", "-", "FENCING", "\n\n", "4.0", "DESIGNING", "RING", "-", "FENCING", "RULES", "\n\n", "5.0", "THE", "IMPLEMENTATION", "OF", "RING", "-", "FENCING", "RULES", "\n\n", "6.0", "CONCLUSION", "\n\n", "unsuccessful", "exploration", "expenditures", "are", "incurred", "by", "the", "mining", "investor", "who", "holds", "more", "than", "one", "mine", ".", "The", "policy", "objective", "behind", "the", "exception", "seems", "to", "be", "to", "try", "to", "balance", "different", "policy", "objectives", ":", "deliver", "early", "government", "revenues", "and", "attract", "exploration", "investments", "to", "their", "jurisdiction", ".", "See", "Section", "4", "for", "more", "details", ".", "\n\n", "#", "#", "BOX", "7", ".", "THE", "RELAXATION", "OF", "RING", "-", "FENCING", "RULES", "IN", "PNG", "AND", "SOUTH", "AFRICA", "\n\n", "Photo", ":", "Raina", "Hattingh", "\n\n", "#", "#", "South", "Africa", "\n\n", "In", "the", "early", "1980s", ",", "many", "mines", "were", "being", "developed", "in", "South", "Africa", ".", "If", "a", "company", "owned", "more", "than", "one", "mine", ",", "the", "unredeemed", "capital", "expenditure", "of", "one", "mine", "could", "be", "deducted", "from", "the", "mining", "income", "from", "another", "mine", ".", "Some", "major", "mergers", "and", "takeovers", "caused", "the", "government", "authorities", "to", "express", "concerns", "that", "vast", "new", "capital", "expenditures", "could", "substantially", "erode", "the", "mining", "tax", "base", ".", "Consequently", ",", "South", "Africa", "introduced", "ring", "-", "fencing", "rules", "mine", "by", "mine", "and", "distinguished", "mining", "from", "non", "-", "mining", "activities", "(", "Davis", "Tax", "Committee", ",", "2016", ",", "p.", "50", ")", ".", "\n\n", "Following", "a", "steep", "decline", "in", "new", "mining", "investment", ",", "South", "Africa", "announced", "a", "partial", "relaxation", "of", "the", "ring", "-", "fencing", "rules", "for", "'", "new", "mines", "'", "(", "a", "mine", "opened", "after", "March", "14", ",", "1990", ")", "(", "Leger", "&", "amp", ";", "Nicol", ",", "1992", ")", ".", "\n\n", "This", "meant", "that", "the", "'", "old", "mines", "'", "in", "the", "same", "entity", "may", "have", "access", "to", "the", "unredeemed", "capital", "expenditure", "of", "the", "'", "new", "mine", "'", "but", "limited", "to", "25", "%", "of", "the", "remaining", "taxable", "income", "of", "the", "'", "old", "mines", "'", "after", "they", "have", "exhausted", "all", "their", "applicable", "capital", "expenditure", "in", "a", "given", "tax", "year", "'", "(", "Davis", "Tax", "Committee", ",", "2014", ")", ".", "Although", "the", "old", "ring", "-", "fencing" ]	[ { "end": 2265, "label": "CITATION_REF", "start": 2242 }, { "end": 2259, "label": "AUTHOR", "start": 2242 }, { "end": 2265, "label": "YEAR", "start": 2261 }, { "end": 2062, "label": "CITATION_REF", "start": 2030 }, { "end": 2049, "label": "AUTHOR", "start": 2030 }, { "end": 2055, "label": "YEAR", "start": 2051 } ]
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Available at: https;// ssrn .com /abstract =130 4823 (Accessed February 2025). Paniagua, V. (2022). When Clients Vote for Brokers: How Elections Improve Public Goods Provision in Urban Slums, World Development , 158, 105919. Perlman, J. (1976). The Myth of Marginality: Urban Poverty and Politics in Rio de Janeiro . Berkeley, CA: University of California Press. Ray, T. (1969). The Politics of the Barrios of Venezuela . Berkeley, CA: University of California Press. Raghavarao, D. , Wiley, J. B., and Chitturi, P. (2011). Choice-Based Conjoint Analysis: Models and Designs . 1st edition. Boca Raton, FL: CRC Press, Taylor and Francis Group. Rossi, P. H. , and Nock, S. L. (1982). Measuring Social Judgements. The Factorial Survey Approach . Beverly Hills, CA: Sage Publications. Stokes, S. (1995). Cultures in Conflict: Social Movements and the state in Peru . Berkeley, CA: University of California Press. Stokes, S. , Dunning, T., Nazareno, M., and Brusco, V. (2013). Brokers, Voters, and Clientelism . Cambridge: Cambridge University Press. Tourangeau, R. , Rasiniski, K. A., Bradburn, N., and D’Andrade, R. (1989). Carryover Effects in Attitude Surveys, Public Opinion Quarterly , 53(4), 495–524. Wagenaar, A. C. , Denk, C. E., Hannan, P. J., Chen, H., and Harwood, E. M. (2001). Liability of Commercial and Social Hosts for Alcohol-Related Injuries: A National Survey of Accountability Norms and Judgments, Public Opinion Quarterly , 65, 344–368. Wallander, L. (2009). 25 Years of Factorial Surveys in Sociology: A Review, Social Science Research , 38, 505–520. Wirtz, J. (1996). Controlling Halo in Attribute-Specific Customer Satisfaction Measures: Towards a Conceptual Framework, Asian Journal of Marketing , 5(1), 41–58.	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OF EUROPEAN COMPETITIVENESS — PART A \| CHAPTER 2BOX 2 A closer look at the role of the ICT sector in the EU-US labour productivity gap The EU’s aggregate gap in labour productivity growth compared with the US reflects differences in industry composition, sectoral innovation and technology diffusion. The EU economy has traditionally been strong in all mid-technology sectors that are not at the centre of radical technological advances. The EU has less activity in sectors in which much of the productivity growth has originated in recent years, notably the ICT sector and the exploitation of large-scale digital services. Due to slow technology diffusion within industries, the EU’s productivity growth gap compared to the US was particularly pronounced in these industries with very high productivity growth. Excluding the main ICT sectors (the manufacturing of computers and electronics and information and communication activities) from the analysis, EU productivity has been broadly at par with the US in the period 2000-2019. The remaining disadvantage in productivity growth versus the US is significantly reduced to 0.2 percentage points (0.8% productivity growth for the US versus 0.6% for the EU). The actual EU-US gap can be considered close to zero as EU 27 productivity growth is 0.2 to 0.3percentage points higher than the EU10 selection (for which EU KLEMS data is available). For 2013-2019 the role of ICT is even more striking, as the EU productivity growth excluding the main ICT sectors exceeded that of the US by some margin. This analysis may underestimate the total impact of ICT developments on the productivity gap. In addition to ICT sectors, the US also has high productivity growth in professional services and finance and insurance, reflecting strong ICT technology diffusion effects. These sectors are amongst the biggest contributors to intangible investment in the total economy in the US. Also, some part of fintech is in the sector Finance and Insurance. On the other hand, the EU outperforms the US in mid-technology sectors like manufacturing of transport equipment, agriculture and in the wholesale and retail sectors. The latter reflects catching up effects to key innovations that had been introduced in the US in the previous decade such as in e-commerce and online retail reaching larger customer bases, implementation of advanced inventory management systems, digital payment systems, data analytics and robotics, and automation. 27THE FUTURE OF EUROPEAN COMPETITIVENESS — PART A \| CHAPTER 2Key barriers to innovation in	[ "OF", "EUROPEAN", "COMPETITIVENESS", " ", "—", "PART", "A", "\|", "CHAPTER", "2BOX", "2", "\n", "A", "closer", "look", "at", "the", "role", "of", "the", "ICT", "sector", "in", "the", "EU", "-", "US", "labour", "\n", "productivity", "gap", "\n", "The", "EU", "’s", "aggregate", "gap", "in", "labour", "productivity", "growth", "compared", "with", "the", "US", "reflects", "differences", "in", "industry", "\n", "composition", ",", "sectoral", "innovation", "and", "technology", "diffusion", ".", "The", "EU", "economy", "has", "traditionally", "been", "strong", "\n", "in", "all", "mid", "-", "technology", "sectors", "that", "are", "not", "at", "the", "centre", "of", "radical", "technological", "advances", ".", "The", "EU", "has", "less", "\n", "activity", "in", "sectors", "in", "which", "much", "of", "the", "productivity", "growth", "has", "originated", "in", "recent", "years", ",", "notably", "the", "ICT", "\n", "sector", "and", "the", "exploitation", "of", "large", "-", "scale", "digital", "services", ".", "Due", "to", "slow", "technology", "diffusion", "within", "industries", ",", "\n", "the", "EU", "’s", "productivity", "growth", "gap", "compared", "to", "the", "US", "was", "particularly", "pronounced", "in", "these", "industries", "with", "\n", "very", "high", "productivity", "growth", ".", "\n", "Excluding", "the", "main", "ICT", "sectors", "(", "the", "manufacturing", "of", "computers", "and", "electronics", "and", "information", "and", "\n", "communication", "activities", ")", "from", "the", "analysis", ",", "EU", "productivity", "has", "been", "broadly", "at", "par", "with", "the", "US", "in", "the", "period", "\n", "2000", "-", "2019", ".", "The", "remaining", "disadvantage", "in", "productivity", "growth", "versus", "the", "US", "is", "significantly", "reduced", "to", "0.2", "\n", "percentage", "points", "(", "0.8", "%", "productivity", "growth", "for", "the", "US", "versus", "0.6", "%", "for", "the", "EU", ")", ".", "The", "actual", "EU", "-", "US", "gap", "can", "\n", "be", "considered", "close", "to", "zero", "as", "EU", "27", "productivity", "growth", "is", "0.2", "to", "0.3percentage", "points", "higher", "than", "the", "EU10", "\n", "selection", "(", "for", "which", "EU", "KLEMS", "data", "is", "available", ")", ".", "For", "2013", "-", "2019", "the", "role", "of", "ICT", "is", "even", "more", "striking", ",", "as", "the", "EU", "\n", "productivity", "growth", "excluding", "the", "main", "ICT", "sectors", "exceeded", "that", "of", "the", "US", "by", "some", "margin", ".", "\n", "This", "analysis", "may", "underestimate", "the", "total", "impact", "of", "ICT", "developments", "on", "the", "productivity", "gap", ".", "In", "addition", "\n", "to", "ICT", "sectors", ",", "the", "US", "also", "has", "high", "productivity", "growth", "in", "professional", "services", "and", "finance", "and", "insurance", ",", "\n", "reflecting", "strong", "ICT", "technology", "diffusion", "effects", ".", "These", "sectors", "are", "amongst", "the", "biggest", "contributors", "to", "\n", "intangible", "investment", "in", "the", "total", "economy", "in", "the", "US", ".", "Also", ",", "some", "part", "of", "fintech", "is", "in", "the", "sector", "Finance", "and", "\n", "Insurance", ".", "On", "the", "other", "hand", ",", "the", "EU", "outperforms", "the", "US", "in", "mid", "-", "technology", "sectors", "like", "manufacturing", "of", "\n", "transport", "equipment", ",", "agriculture", "and", "in", "the", "wholesale", "and", "retail", "sectors", ".", "The", "latter", "reflects", "catching", "up", "effects", "\n", "to", "key", "innovations", "that", "had", "been", "introduced", "in", "the", "US", "in", "the", "previous", "decade", "such", "as", "in", "e", "-", "commerce", "and", "\n", "online", "retail", "reaching", "larger", "customer", "bases", ",", "implementation", "of", "advanced", "inventory", "management", "systems", ",", "\n", "digital", "payment", "systems", ",", "data", "analytics", "and", "robotics", ",", "and", "automation", ".", "\n", "27THE", "FUTURE", "OF", "EUROPEAN", "COMPETITIVENESS", " ", "—", "PART", "A", "\|", "CHAPTER", "2Key", "barriers", "to", "innovation", "in" ]	[]
5.5 7.7₊₁ MSR Nicaragua … 81 9 9 7 12 18 36 71 76 45 50 34 38 9.1 11.5 15₋₂ … 3₋₂ … … … … … … 18₋₁ … 59 … … … … 4.1ᵢ 3.8₋₁ 22.3ᵢ 17.7 NIC Panama 79 73 8 8 13 16 31 29 94 95 74 78 59 63 11.5 12.7 21₋₂ … 4₋₂ … … 42₋₁ … 16₋₁ … 39 99 … 94 … 98₋₁ … 3.4 3.4₋₁ 15.2 11.9 PAN Paraguay 76₊₁ 77 15 19 16 26 33 37 91 94 73 81 61 67 5.7 8.2 16₋₂ … 6₋₂ … … 34₋₁ … 15₋₁ 28₊₁ … … … … … … … 3.3 3.4 18.2₊₁ 22.0 PRY Peru 98 100 3 1 4 1 16 6 95 98 85 93 77 86 -0.6 0.3 31₋₂ … 23₋₂ … … 50₋₁ … 34₋₁ 71₊₁ 80 … 13 … … … … 4.0 4.2 17.6 19.2₊₁ PER Saint Kitts and Nevis … … … … … … … … … … … … … … … … … … … … … … … … 100₊₁ 100₋₂ 72 68₋₂ … … … … 2.5 3.6₋₁ 8.8 10.2₊₁ KNA Saint Lucia 95 48 1 1 9 7 21 21 99 100 95 98 84 92 16.4 13.0 … … … … … … … … … 100 … 77 … 70 … 66 3.9 3.7₋₁ 16.5 16.3₋₁ LCA Saint Vincent/Grenadines 96 58₋₁ 0.4 0.3 4 3 23 19 … … … … … … … … … … … … … … … … 100₊₁ … 84 79 … … … … 5.0 7.2₋₁ 17.2 12.6₊₁ VCT Sint Maarten … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … 4.2₋₁ … 23.0 SXM Suriname 90 50 11 14 17 24 43 62 85 87 55 58 28 32 12.4 14.8 … … … … … … … … … … 98 100 84 82₋₂ 50 … 5.5 2.9 11.4 8.6₊₁ SUR Trinidad and Tobago … 32 6 16 7 20 18 33 97 98 93 95 84 84 9.5 11.0 80₊₁ … … … 58 … 48 … … … … 81 … … … … 4.5 2.9₋₁ 12.3 8.9₊₁ TTO Turks and Caicos Islands 91₋₁ 99 … … …	[ "5.5", "7.7₊₁", "MSR", "\n", "Nicaragua", "…", "81", "9", "9", "7", "12", "18", "36", "71", "76", "45", "50", "34", "38", "9.1", "11.5", "15₋₂", "…", "3₋₂", "…", "…", "…", "…", "…", "…", "18₋₁", "…", "59", "…", "…", "…", "…", "4.1ᵢ", "3.8₋₁", "22.3ᵢ", "17.7", "NIC", "\n", "Panama", "79", "73", "8", "8", "13", "16", "31", "29", "94", "95", "74", "78", "59", "63", "11.5", "12.7", "21₋₂", "…", "4₋₂", "…", "…", "42₋₁", "…", "16₋₁", "…", "39", "99", "…", "94", "…", "98₋₁", "…", "3.4", "3.4₋₁", "15.2", "11.9", "PAN", "\n", "Paraguay", "76₊₁", "77", "15", "19", "16", "26", "33", "37", "91", "94", "73", "81", "61", "67", "5.7", "8.2", "16₋₂", "…", "6₋₂", "…", "…", "34₋₁", "…", "15₋₁", "28₊₁", "…", "…", "…", "…", "…", "…", "…", "3.3", "3.4", "18.2₊₁", "22.0", "PRY", "\n", "Peru", "98", "100", "3", "1", "4", "1", "16", "6", "95", "98", "85", "93", "77", "86", "-0.6", "0.3", "31₋₂", "…", "23₋₂", "…", "…", "50₋₁", "…", "34₋₁", "71₊₁", "80", "…", "13", "…", "…", "…", "…", "4.0", "4.2", "17.6", "19.2₊₁", "PER", "\n", "Saint", "Kitts", "and", "Nevis", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "100₊₁", "100₋₂", "72", "68₋₂", "…", "…", "…", "…", "2.5", "3.6₋₁", "8.8", "10.2₊₁", "KNA", "\n", "Saint", "Lucia", "95", "48", "1", "1", "9", "7", "21", "21", "99", "100", "95", "98", "84", "92", "16.4", "13.0", "…", "…", "…", "…", "…", "…", "…", "…", "…", "100", "…", "77", "…", "70", "…", "66", "3.9", "3.7₋₁", "16.5", "16.3₋₁", "LCA", "\n", "Saint", "Vincent", "/", "Grenadines", "96", "58₋₁", "0.4", "0.3", "4", "3", "23", "19", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "100₊₁", "…", "84", "79", "…", "…", "…", "…", "5.0", "7.2₋₁", "17.2", "12.6₊₁", "VCT", "\n", "Sint", "Maarten", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "4.2₋₁", "…", "23.0", "SXM", "\n", "Suriname", "90", "50", "11", "14", "17", "24", "43", "62", "85", "87", "55", "58", "28", "32", "12.4", "14.8", "…", "…", "…", "…", "…", "…", "…", "…", "…", "…", "98", "100", "84", "82₋₂", "50", "…", "5.5", "2.9", "11.4", "8.6₊₁", "SUR", "\n", "Trinidad", "and", "Tobago", "…", "32", "6", "16", "7", "20", "18", "33", "97", "98", "93", "95", "84", "84", "9.5", "11.0", "80₊₁", "…", "…", "…", "58", "…", "48", "…", "…", "…", "…", "81", "…", "…", "…", "…", "4.5", "2.9₋₁", "12.3", "8.9₊₁", "TTO", "\n", "Turks", "and", "Caicos", "Islands", "91₋₁", "99", "…", "…", "…" ]	[]
and the Arkansas-White- Red regions. Generally, negative trends were obtained inthe South Atlantic-Gulf and to a lesser extent in the New England regions. Noteworthy is that most recently, from 1988 to 2007, in 29 out of 41 basins or in 71%, theobserved trends were negative; more than half of the exceptions, that is, the basins which persisted with positive trends during the past 20 years, tended to lie in the Ohioand Upper Mississippi regions; but the most significant positive trends during this recent period were observed in the Souris-Red-Rainy region in northern Minnesota. The present results on groundwater storage are fully consistent with previous studies dealing with changes of other measures of hydrologic cycle activity, namely with thetrends in precipitation, total surface runoff, and terrestrial evaporation. The consensus of these studies is that the water cycle has generally been accelerating during the past halfcentury over most of the United States east of the Rockies, the two major exceptions being the South Atlantic-Gulf region and possibly also a smaller area in New England. References Andreadis KM, Lettenmaier DP (2006) Trends in 20th century drought over the continental United States. Geophys Res Lett 33:L10403. doi: 10.1029/2006GL025711 Boussinesq J (1877) Essai sur la théorie des eaux courantes. Mém Acad Sci Inst France 23, footnote 252 –260 Brutsaert W (2005) Hydrology: an introduction. Cambridge Univ Press, Cambridge 605 pp Brutsaert W (2006) Indications of increasing land surface evaporation during the second half of the 20th century. Geophys Res Lett 33: L20403. doi: 10.1029/2006GL027532 Brutsaert W (2008) Long-term groundwater storage trends estimated from streamflow records: climatic perspective. Water Resour Res44:W02409. doi: 10.1029/2007WR006518 Brutsaert W, Lopez JP (1998) Basin-scale geohydrologic drought flow features of riparian aquifers in the southern Great Plains. WaterResour Res 34:233 –240 Brutsaert W, Parlange MB (1998) Hydrologic cycle explains the evaporation paradox. Nature 396:30 Brutsaert W, Sugita M (2008) Is Mongolia ’s groundwater increasing or decreasing? The case of the Kherlen River Basin. Hydrol Sci J 53:1221 –1229 Carlston CW (1963) Drainage density and streamflow. US Geol Survey Prof Paper 422-C:1 –8 Carlston CW (1966) The effect of climate on drainage density and streamflow. Bull Internat Assoc Scientif Hydrol 11:62 –69 Chapman MJ, Peck MF (1997) Ground-water resources of the upper Chattahoochee River basin in Georgia. US Geol Survey Open- File Rept 96 –363:43 Dery SJ, Wood EF (2005) Decreasing rive r discharge in Northern Canada. 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activities, or in the mining law. Some countries that negotiate project-specific fiscal terms negotiated ring-fencing rules that go beyond the primary law (see the example from Sierra Leone in Box 1). Guinea3 and Papua New Guinea4 (PNG) also include a specific ring-fence in their mining contracts. This practice may be especially relevant where the primary law contains no provisions on ring-fencing or only narrow ring-fencing provisions. It is also relevant if a particular project presents specific fiscal risks that could be addressed or managed by well-designed ring-fencing rules. BOX 1. RING -FENCING IN MINING CONTRACTS: THE CASE OF SIERRA LEONE Sierra Leone introduced ring-fencing rules for mining in 2009. The ring-fence is applied per mining licence: “the chargeable income for any year of assessment of a holder of a large-scale mining licence shall be calculated separately for each large-scale mining licence under which licence such holder shall maintain separate balance sheets, statements and books of accounts for each large-scale mining licence under which mining operations are carried on.”5 The country also negotiated ring-fencing rules in some mining contracts that go beyond the general rules. Under the SierraMin Bauxite Limited, Concession, 2017 and the T onguma Limited Concession, 2012, the government negotiated a further operational level of ring-fencing. Any activities carried out by the mining company that are separate from the mining operations contemplated in the contracts shall be considered “non-project activities.” Such non-mining activities will be accounted for separately, as if they were carried out by a separate corporate entity and shall be subject to the law of general application. 3 ResourceContracts.org - Winning Consortium Simandou SAU, Exploitation License, 2020 . 4 ResourceContracts.org - Ramu Nickel Limited, Orogen Minerals (Ramu) Limited, JVA, 2000 . 5 S.155 (1), Sierra Leone Mines and Minerals Act , 2009.3.0 THE BENEFITS AND RISKS OF RING -FENCING 4.0 DESIGNING RING -FENCING RULES 5.0 THE IMPLEMENTATION OF RING -FENCING RULES 6.0 CONCLUSION 2.0 THE FUNDAMENTALS OF RING -FENCING 1.0 INTRODUCTION 8 Ring-Fencing Mining Income: A toolkit for tax administrators and policy-makers2.2 The Prevalence of Ring-Fencing Rules in the Extractive Sectors Ring-fencing rules are widespread worldwide. They are particularly prevalent in the mining sector in developing countries. The findings in Box 2 are based on a survey of ring-fencing rules undertaken by the Intergovernmental Forum on Mining, Minerals, Metals and Sustainable Development (IGF). BOX 2. 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- Cummings, R.G., Taylor, L.O., 1999. Unbiased value estimates for environmental goods: ' a cheap talk design for the contingent valuation method. American Economic Review 89, 649 -665. - Di Comite, F., Thisse, J.F., Vandenbussche, H., 2014. Verti-zontal differentiation in export markets. Journal of International Economics 93 (1), 50 -66. - Di Marcantonio, F., Menapace, L., Barreiro-Hurle, J., Ciaian, P., Dessart, F., Colen, L., 2020. Empirical testing of the impact on consumer choice resulting from differences - Di Marcantonio, F., Nedelcu, B., Padiu, B., Rebedea, T., et al., 2024. Food-checker -A mobile-based crowdsourcing application for 'dual quality. of food, Publications Office of the European Union. https://data.europa.eu/doi/10.2760/242232. - Ding, M., Grewal, R., Liechty, J., 2005. Incentive-Aligned Conjoint Analysis. Journal of Marketing Research 42, 67 -82. - Dodds, W.B., Monroe, K.B., Grewal, D., 1991. Effects of Price, Brand, and Store Information on Buyers ' Product Evaluations. Journal of Marketing Research 28, 307 319. - - Dong, S., Ding, M., Huber, J., 2010. A simple mechanism to incentive-align conjoint experiments. International Journal of Research in Marketing 27, 25 -32. Duivenvoorde, B., 2019. The Upcoming Changes in the Unfair Commercial Practices Directive: A Better Deal for Consumers? Journal of European Consumer and Market Law 8 (6), 219 -228. - ECO (2021). Manual For Testing dual quality in food products. European project funded by the Consumer Programme of the DG Justice of the European Commission. https://www.fightdualfood.eu/files/uploads/2021/11/D3.1-ECO-Manual\_ compressed.pdf. Erdem, T., Swait, J., Valenzuela, A., 2006. Brands as Signals: A Cross-Country Validation Study. Journal of Marketing 70 (01/01), 34 -49. - Ettenson, R., 1993. Brand Name and Country of Origin Effects in the Emerging Market Economies of Russia, Poland and Hungary. International Marketing Review 10 (5). Focos (2019), Dual Quality: East vs West, or USA vs UK (accessed 27 April 2022), https://www.focos-food.com/dual-quality-east-west-usa-uk/. - Franke, N., Keinz, P., Steger, C.J., 2009. Testing the Value of Customization: When Do Customers Really Prefer Products Tailored to Their Preferences? Journal of Marketing 73 (5), 103 -121. - Franke, N., Schreier, M., Kaiser, U., 2010. The ''I designed ItMyself '' Effect in Mass Customization. Management Science 65, 125 -140. - Gao, S., Grebitus, C., DeLong, K.L., 2024. Explaining consumer willingess to pay for country-of-origin labeling with ethnocentrism, country image, and product image: Examples from China s beef market. Canadian Journal of Agricultural Economics. ' - Graham, D.J., Orquin, J.L., Visschers, V.H., 2012. Eye tracking and nutrition label use: A review of the literature and recommendations for label enhancement. Food Policy 37 (4), 378 -382.	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activity belt and the prospect of connecting the observed outflows from the solar surface at a variety of latitudes with those encountered at the spacecraft. These connections are key to many of the prime mission goals.” The best is yet to come These are just the first observations made by Solar Orbiter from its newly inclined orbit, and much of this first set of data still awaits further analysis. The complete dataset of Solar Orbiter's first full ‘pole-to-pole' flight past the Sun is expected to arrive on Earth by October 2025. All ten of Solar Orbiter’s scientific instruments will collect unprecedented data in the years to come. Dr Daniel Müller, ESA’s Solar Orbiter project scientist, said: “This is just the first step of Solar Orbiter’s ‘stairway to heaven’: in the coming years, the spacecraft will climb further out of the ecliptic plane for ever better views of the Sun’s polar regions. These data will transform our understanding of the Sun’s magnetic field, the solar wind, and solar activity.” The spacecraft, which launched in February 2020, began the ‘high latitude’ part of its journey five years later, in February 2025. Nearly all Sun-observing spacecraft have tilted from the ecliptic plane by no more than 7°.The exception to this is the ESA/NASA Ulysses mission (1990–2009), which flew over the Sun's poles but did not carry any imaging instruments and remained at much larger distances from the Sun itself. Solar Orbiter’s observations will complement Ulysses’ by observing the poles for the first time with telescopes, in addition to a full suite of in-situ sensors, while flying much closer to the Sun where the solar wind can be sampled in a more pristine state. Additionally, Solar Orbiter will monitor changes at the poles throughout the solar cycle. Solar Orbiter will continue to orbit around the Sun at this tilt angle until 24 December 2026, when its next flight past Venus will tilt its orbit to 24°. From 10 June 2029, the spacecraft will orbit the Sun at an angle of 33°. Solar Orbiter is a space mission of international collaboration between ESA and NASA, operated by ESA. ## Links - ESA's story - ESA Solar Orbiter - Dr Hamish Reid’s academic profile - Professor Lucie Green’s academic profile - Professor Chris Owen’s academic profile - UCL Mullard Space Science Laboratory - UCL Mathematical & Physical Sciences ## Images - Top: A screenshot from the	[ "activity", "belt", "and", "the", "prospect", "of", "connecting", "the", "observed", "outflows", "from", "the", "solar", "surface", "at", "a", "variety", "of", "latitudes", "with", "those", "encountered", "at", "the", "spacecraft", ".", " ", "These", "connections", "are", "key", "to", "many", "of", "the", "prime", "mission", "goals", ".", "”", "\n\n", "The", "best", "is", "yet", "to", "come", "\n", "These", "are", "just", "the", "first", "observations", "made", "by", "Solar", "Orbiter", "from", "its", "newly", "inclined", "orbit", ",", "and", "much", "of", "this", "first", "set", "of", "data", "still", "awaits", "further", "analysis", ".", "The", "complete", "dataset", "of", "Solar", "Orbiter", "'s", "first", "full", "‘", "pole", "-", "to", "-", "pole", "'", "flight", "past", "the", "Sun", "is", "expected", "to", "arrive", "on", "Earth", "by", "October", "2025", ".", "All", "ten", "of", "Solar", "Orbiter", "’s", "scientific", "instruments", "will", "collect", "unprecedented", "data", "in", "the", "years", "to", "come", ".", "\n\n", "Dr", "Daniel", "Müller", ",", "ESA", "’s", "Solar", "Orbiter", "project", "scientist", ",", "said", ":", "“", "This", "is", "just", "the", "first", "step", "of", "Solar", "Orbiter", "’s", "‘", "stairway", "to", "heaven", "’", ":", "in", "the", "coming", "years", ",", "the", "spacecraft", "will", "climb", "further", "out", "of", "the", "ecliptic", "plane", "for", "ever", "better", "views", "of", "the", "Sun", "’s", "polar", "regions", ".", "These", "data", "will", "transform", "our", "understanding", "of", "the", "Sun", "’s", "magnetic", "field", ",", "the", "solar", "wind", ",", "and", "solar", "activity", ".", "”", "\n\n", "The", "spacecraft", ",", "which", "launched", "in", "February", "2020", ",", "began", "the", "‘", "high", "latitude", "’", "part", "of", "its", "journey", "five", "years", "later", ",", "in", "February", "2025", ".", "\n\n", "Nearly", "all", "Sun", "-", "observing", "spacecraft", "have", "tilted", "from", "the", "ecliptic", "plane", "by", "no", "more", "than", "7", "°", ".The", "exception", "to", "this", "is", "the", "ESA", "/", "NASA", "Ulysses", "mission", "(", "1990–2009", ")", ",", "which", "flew", "over", "the", "Sun", "'s", "poles", "but", "did", "not", "carry", "any", "imaging", "instruments", "and", "remained", "at", "much", "larger", "distances", "from", "the", "Sun", "itself", ".", "\n\n", "Solar", "Orbiter", "’s", "observations", "will", "complement", "Ulysses", "’", "by", "observing", "the", "poles", "for", "the", "first", "time", "with", "telescopes", ",", "in", "addition", "to", "a", "full", "suite", "of", "in", "-", "situ", "sensors", ",", "while", "flying", "much", "closer", "to", "the", "Sun", "where", "the", "solar", "wind", "can", "be", "sampled", "in", "a", "more", "pristine", "state", ".", "Additionally", ",", "Solar", "Orbiter", "will", "monitor", "changes", "at", "the", "poles", "throughout", "the", "solar", "cycle", ".", "\n\n", "Solar", "Orbiter", "will", "continue", "to", "orbit", "around", "the", "Sun", "at", "this", "tilt", "angle", "until", "24", "December", "2026", ",", "when", "its", "next", "flight", "past", "Venus", "will", "tilt", "its", "orbit", "to", "24", "°", ".", "From", "10", "June", "2029", ",", "the", "spacecraft", "will", "orbit", "the", "Sun", "at", "an", "angle", "of", "33", "°", ".", "\n\n", "Solar", "Orbiter", "is", "a", "space", "mission", "of", "international", "collaboration", "between", "ESA", "and", "NASA", ",", "operated", "by", "ESA", ".", "\n\n", "#", "#", "Links", "\n\n", "-", "ESA", "'s", "story", "\n", "-", "ESA", "Solar", "Orbiter", "\n", "-", "Dr", "Hamish", "Reid", "’s", "academic", "profile", "\n", "-", "Professor", "Lucie", "Green", "’s", "academic", "profile", "\n", "-", "Professor", "Chris", "Owen", "’s", "academic", "profile", "\n", "-", "UCL", "Mullard", "Space", "Science", "Laboratory", "\n", "-", "UCL", "Mathematical", "&", "amp", ";", "Physical", "Sciences", "\n\n", "#", "#", "Images", "\n\n", "-", "Top", ":", "A", "screenshot", "from", "the" ]	[]
per second—meaning that digital data can, in princi-ple, circle the globe five times within a second. 6 Data traffic is growing rapidly around the world. Internet data usage rose from 4.6 to 13 gigabytes per person per month between 2012 and 2017. 7 Four trends are driving the explosion in data traffic. First, the number of internet users is growing. More than half of the world’s population is now online, up from less than one-third in 2010, and that share is forecast to reach two-thirds by 2023. Second, the number of con-nected devices on the IoT already exceeds the number of human users and is forecast to reach 25 billion by 2025 with the diffusion of 5G technology. 8 Third, internet speeds are continually increasing, which supports growing data volumes. By 2023 the speed of broadband service provided over fixed networks is expected to double from 2018 levels, 9 even as the speed of broadband service provided over fixed networks triples. Fourth, video accounts for three-fifths of inter - net traffic, and associated quality improvements are increasing video data traffic. 10 A two-hour movie in standard definition uses 1.4 gigabytes of data, whereas ultra-high definition uses 18 gigabytes. 11 Although most data traffic is still carried over fixed networks, data traffic carried over wireless networks is forecast to rise to more than 20 percent of the global total by 2022, up from only 3 percent in 2012. This shift is driven by the greater prevalence of mobile traffic in emerging nations, with China and India alone accounting for more than 40 percent of the world’s mobile data traffic as of 2018. Both poor people and poor countries face fundamen- tal inequities in their ability to access data infrastruc-ture. To participate in the data-driven economy, people require internet connectivity. It entails both access to last-mile internet infrastructure—increasingly provided through a wireless signal—and ownership of a data-enabled mobile handset (also known as a smart - phone)—or alternatively a full-blown fixed line con-nection. Such connectivity makes it possible for people to both have access to data about other people (and increasingly other things) and provide their own data to others. Large swathes of the population remain excluded from the internet, particularly the poor, the uneducated, the elderly, those living in rural areas, and—in some parts of the world—women. This com-plex situation reflects both the supply-side challenges entailed in rolling out coverage of the	[ "per", "second", "—", "meaning", "that", "digital", "data", "can", ",", "in", "princi", "-", "ple", ",", "circle", "the", "globe", "five", "times", "within", "a", "second", ".", "\n", "6", "\n", "Data", "traffic", "is", "growing", "rapidly", "around", "the", "world", ".", "\n", "Internet", "data", "usage", "rose", "from", "4.6", "to", "13", "gigabytes", "per", "person", "per", "month", "between", "2012", "and", "2017", ".", "\n", "7", "Four", "trends", "\n", "are", "driving", "the", "explosion", "in", "data", "traffic", ".", "First", ",", "the", "number", "of", "internet", "users", "is", "growing", ".", "More", "than", "half", "of", "the", "world", "’s", "population", "is", "now", "online", ",", "up", "from", "less", "than", "one", "-", "third", "in", "2010", ",", "and", "that", "share", "is", "forecast", "to", "reach", "two", "-", "thirds", "by", "2023", ".", "Second", ",", "the", "number", "of", "con", "-", "nected", "devices", "on", "the", "IoT", "already", "exceeds", "the", "number", "of", "human", "users", "and", "is", "forecast", "to", "reach", "25", "billion", "by", "2025", "with", "the", "diffusion", "of", "5", "G", "technology", ".", "\n", "8", "Third", ",", "\n", "internet", "speeds", "are", "continually", "increasing", ",", "which", "supports", "growing", "data", "volumes", ".", "By", "2023", "the", "speed", "of", "broadband", "service", "provided", "over", "fixed", "networks", "is", "expected", "to", "double", "from", "2018", "levels", ",", "\n", "9", "even", "as", "the", "speed", "\n", "of", "broadband", "service", "provided", "over", "fixed", "networks", "triples", ".", "Fourth", ",", "video", "accounts", "for", "three", "-", "fifths", "of", "inter", "-", "\n", "net", "traffic", ",", "and", "associated", "quality", "improvements", "are", "increasing", "video", "data", "traffic", ".", "\n", "10", "A", "two", "-", "hour", "movie", "in", "\n", "standard", "definition", "uses", "1.4", "gigabytes", "of", "data", ",", "whereas", "ultra", "-", "high", "definition", "uses", "18", "gigabytes", ".", "\n", "11", "\n", "Although", "most", "data", "traffic", "is", "still", "carried", "over", "\n", "fixed", "networks", ",", "data", "traffic", "carried", "over", "wireless", "networks", "is", "forecast", "to", "rise", "to", "more", "than", "20", "percent", "of", "the", "global", "total", "by", "2022", ",", "up", "from", "only", "3", "percent", "in", "2012", ".", "This", "shift", "is", "driven", "by", "the", "greater", "prevalence", "of", "mobile", "traffic", "in", "emerging", "nations", ",", "with", "China", "and", "India", "alone", "accounting", "for", "more", "than", "40", "percent", "of", "the", "world", "’s", "mobile", "data", "traffic", "as", "of", "2018", ".", "\n", "Both", "poor", "people", "and", "poor", "countries", "face", "fundamen-", "\n", "tal", "inequities", "in", "their", "ability", "to", "access", "data", "infrastruc", "-", "ture", ".", "To", "participate", "in", "the", "data", "-", "driven", "economy", ",", "people", " \n", "require", "internet", "connectivity", ".", "It", "entails", "both", "access", " \n", "to", "last", "-", "mile", "internet", "infrastructure", "—", "increasingly", "provided", "through", "a", "wireless", "signal", "—", "and", "ownership", "of", "a", "data", "-", "enabled", "mobile", "handset", "(", "also", "known", "as", "a", "smart", "-", "\n", "phone)—or", "alternatively", "a", "full", "-", "blown", "fixed", "line", "con", "-", "nection", ".", "Such", "connectivity", "makes", "it", "possible", "for", "people", "to", "both", "have", "access", "to", "data", "about", "other", "people", "(", "and", "increasingly", "other", "things", ")", "and", "provide", "their", "own", "data", "to", "others", ".", "Large", "swathes", "of", "the", "population", "remain", "excluded", "from", "the", "internet", ",", "particularly", "the", "poor", ",", "the", "uneducated", ",", "the", "elderly", ",", "those", "living", "in", "rural", "areas", ",", "and", "—", "in", "some", "parts", "of", "the", "world", "—", "women", ".", "This", "com", "-", "plex", "situation", "reflects", "both", "the", "supply", "-", "side", "challenges", "entailed", "in", "rolling", "out", "coverage", "of", "the" ]	[]
second case, only one (average) contact between each couple of ancestor (0-level) pinballs is retained. Therefore, the area A0of the ancestor pinball (and not that of the contacting descendant , A) should be used to compute the penalty force. In case of perfectly at and centered contact this approach ensures that the obtained penalty force is the same (for a given penetration p), irrespective of the the hierarchy level chosen for the pinballs. As concerns the penetration p, the problem is more complex and of geometric nature. A major issue is that the standard penetration measurement procedure is unable to detect penetrations larger than the pinball diameter , so that the maximum detectable penetration becomes smaller and smaller as the chosen hierarchy level increases. This translates into a practical limitation of the penalty force, which may lead to numerical disaster. In order to overcome this limitation, we need to modify the strategy to measure the penetration (for proper descendant pinballs) in such a way that it functions also for penetrations larger than the descendant pinball diameter, ideally up to the ancestor pinball diameter.	[ "second", "case", ",", "only", "one", "(", "average", ")", "contact", "between", "each", "couple", "of", "ancestor", "(", "0", "-", "level", ")", "pinballs", "\n", "is", "retained", ".", "Therefore", ",", "the", "area", "A0of", "the", "ancestor", "pinball", "(", "and", "not", "that", "of", "the", "contacting", "descendant", ",", "\n", "A", ")", "should", "be", "used", "to", "compute", "the", "penalty", "force", ".", "In", "case", "of", "perfectly", "\n", "at", "and", "centered", "contact", "this", "\n", "approach", "ensures", "that", "the", "obtained", "penalty", "force", "is", "the", "same", "(", "for", "a", "given", "penetration", "p", ")", ",", "irrespective", "\n", "of", "the", "the", "hierarchy", "level", "chosen", "for", "the", "pinballs", ".", "\n", "As", "concerns", "the", "penetration", "p", ",", "the", "problem", "is", "more", "complex", "and", "of", "geometric", "nature", ".", "A", "major", "\n", "issue", "is", "that", "the", "standard", "penetration", "measurement", "procedure", "is", "unable", "to", "detect", "penetrations", "larger", "\n", "than", "the", "pinball", "diameter", ",", "so", "that", "the", "maximum", "detectable", "penetration", "becomes", "smaller", "and", "smaller", "\n", "as", "the", "chosen", "hierarchy", "level", "increases", ".", "This", "translates", "into", "a", "practical", "limitation", "of", "the", "penalty", "force", ",", "\n", "which", "may", "lead", "to", "numerical", "disaster", ".", "\n", "In", "order", "to", "overcome", "this", "limitation", ",", "we", "need", "to", "modify", "the", "strategy", "to", "measure", "the", "penetration", "\n", "(", "for", "proper", "descendant", "pinballs", ")", "in", "such", "a", "way", "that", "it", "functions", "also", "for", "penetrations", "larger", "than", "\n", "the", "descendant", "pinball", "diameter", ",", "ideally", "up", "to", "the", "ancestor", "pinball", "diameter", "." ]	[]
… \| … … \| 1 ₋₁ … \| … … \| … … \| … … \| … … \| \| 17 … \| 56 \| 87 \| 96 ₋₁ 98 \| 22 \| … 15 … \| … \| 53 … 62 \| 0.4 3.6 \| \| 4.4 \| \| ᵢ \| 14.8 \| \| \| \| \| 0.3 ₋₁ 4.9 \| \| \| \| \| \| \| 2 ₋₁ … … \| … \| … \| … \| … \| … \| … … \| … \| … … 28 ᵢ \| 85 \| … \| … 68 \| … … … \| … 87 \| \| … \| 4.7 \| 12.5 ᵢ \| \| \| \| 18.3 \| 11.3 \| \| \| \| \| 94 \| \| NER NGA RWA STP \| \| \| \| … … 35 ₋₁ … \| … … \| … … 29 ₋₁ \| … \| … … … \| … … \| … … \| \| … … \| … 34 68 \| … \| … 74 80 \| 20 ₊₁ ᵢ … … 75 ₋₁ … \| … … … \| … … … 73 … \| 74 ₋₁ 71 ₋₁ 100 7 \| 5.5 4.9 2.7 ₋₁ … \| 23.8 12.6 15.1 ₋₁ \| 22.5 6.7 ₋₃ \| SLE SOM ZAF SSD TGO \| \| 29.4 ₋₁ \| \| \| SEN SYC \| \| 5.2 ₋₁ 6.0 ₋₁ 4.7 ₋₁ 6.8 \| … … \| … 18.9 \| \| \| \| \| 80 ₋₂ … 100 … … … … … … \| … … … \| 52 ₋₂ … … \| … \| … … … \| … \| … … … \| \| ₊₁ … … \| … \| \| 81 ₋₂ … \| … 69 … \| 84 54 … \| \| … … … \| \| \| \| \| \| \| \| \| 4.2 ₋₄ \| \| \| 66 … \| \| \| \| … \| ## PROGRESS SINCE 2015: SELECTED INDICATORS: Continued \| \| Participation/Completion \| Participation/Completion \| Participation/Completion \| Participation/Completion \| Participation/Completion \| Participation/Completion \| Participation/Completion \| Participation/Completion \| Participation/Completion \| Participation/Completion \| Participation/Completion \| Participation/Completion \| Participation/Completion \| Participation/Completion \| Gender \| Gender \| \|-----------------------------\|--------------------------------------------------\|----------------------------\|----------------------------\|----------------------------\|------------------------------------\|------------------------------------\|----------------------------\|----------------------------\|----------------------------\|----------------------------\|----------------------------\|----------------------------\|----------------------------\|----------------------------\|-----------------------------------\|-----------------------------------\| \| \| A \| A \| \| \| \| \| \| \| C (%) Completion rate \| C (%) Completion rate \| C (%) Completion rate	[ "…", " ", "\|", "…", "…", " ", "\|", "1", "₋₁", "…", " ", "\|", "…", "…", " ", "\|", "…", "…", " ", "\|", "…", "…", " ", "\|", "…", "…", " ", "\|", " ", "\|", "17", "…", " ", "\|", "56", " ", "\|", "87", " ", "\|", "96", "₋₁", "98", " ", "\|", "22", " ", "\|", "…", "15", "…", " ", "\|", "…", " ", "\|", "53", "…", "62", " ", "\|", "0.4", "3.6", " ", "\|", " ", "\|", "4.4", " ", "\|", " ", "\|", "ᵢ", " ", "\|", "14.8", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "0.3", "₋₁", "4.9", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "\n", "\|", "2", "₋₁", "…", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", "…", " ", "\|", "…", " ", "\|", "…", "…", "28", "ᵢ", " ", "\|", "85", " ", "\|", "…", " ", "\|", "…", "68", " ", "\|", "…", "…", "…", " ", "\|", "…", "87", " ", "\|", " ", "\|", "…", " ", "\|", "4.7", " ", "\|", "12.5", "ᵢ", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "18.3", " ", "\|", "11.3", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "94", " ", "\|", " ", "\|", "NER", "NGA", "RWA", "STP", "\|", " ", "\|", " ", "\|", "\n", "\|", "…", "…", "35", "₋₁", "…", " ", "\|", "…", "…", " ", "\|", "…", "…", "29", "₋₁", " ", "\|", "…", " ", "\|", "…", "…", "…", " ", "\|", "…", "…", " ", "\|", "…", "…", " ", "\|", " ", "\|", "…", "…", " ", "\|", "…", "34", "68", " ", "\|", "…", " ", "\|", "…", "74", "80", " ", "\|", "20", "₊₁", "ᵢ", "…", "…", "75", "₋₁", "…", "\|", "…", "…", "…", " ", "\|", "…", "…", "…", "73", "…", " ", "\|", "74", "₋₁", "71", "₋₁", "100", "7", "\|", "5.5", "4.9", "2.7", "₋₁", "…", " ", "\|", "23.8", "12.6", "15.1", "₋₁", " ", "\|", "22.5", "6.7", "₋₃", " ", "\|", "SLE", "SOM", "ZAF", "SSD", "TGO", "\|", " ", "\|", "29.4", "₋₁", " ", "\|", " ", "\|", " ", "\|", "SEN", "SYC", " ", "\|", " ", "\|", "5.2", "₋₁", "6.0", "₋₁", "4.7", "₋₁", "6.8", "\|", "…", "…", " ", "\|", "…", "18.9", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "\n", "\|", "80", "₋₂", "…", "100", "…", "…", "…", "…", "…", "…", "\|", "…", "…", "…", " ", "\|", "52", "₋₂", "…", "…", " ", "\|", "…", " ", "\|", "…", "…", "…", " ", "\|", "…", " ", "\|", "…", "…", "…", " ", "\|", " ", "\|", "₊₁", "…", "…", " ", "\|", "…", " ", "\|", " ", "\|", "81", "₋₂", "…", " ", "\|", "…", "69", "…", " ", "\|", "84", "54", "…", " ", "\|", " ", "\|", "…", "…", "…", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "4.2", "₋₄", " ", "\|", " ", "\|", " ", "\|", "66", "…", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "…", " ", "\|", "\n\n", "#", "#", "PROGRESS", "SINCE", "2015", ":", "SELECTED", "INDICATORS", ":", "Continued", "\n\n", "\|", " ", "\|", "Participation", "/", "Completion", " ", "\|", "Participation", "/", "Completion", " ", "\|", "Participation", "/", "Completion", " ", "\|", "Participation", "/", "Completion", " ", "\|", "Participation", "/", "Completion", " ", 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"\|-----------------------------\|--------------------------------------------------\|----------------------------\|----------------------------\|----------------------------\|------------------------------------\|------------------------------------\|----------------------------\|----------------------------\|----------------------------\|----------------------------\|----------------------------\|----------------------------\|----------------------------\|----------------------------\|-----------------------------------\|-----------------------------------\|", "\n", "\|", " ", "\|", "A", " ", "\|", "A", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "C", "(", "%", ")", "Completion", "rate", " ", "\|", "C", "(", "%", ")", "Completion", "rate", " ", "\|", "C", "(", "%", ")", "Completion", "rate", " " ]	[]
the internet at http:// dnb.d- nb.de. Library of Congress Cataloging-in-Publication Data A CIP catalog record for this book has been applied for at the Library of Congress. This book was published with the financial assistance of the Department of Modern Languages, Literatures and Cultures of the University of Bologna. The cover illustration was designed by the interns of CISR, Inter-University Centre for the Study of Romanticism (https://site.unibo.it/cisr/it): Giulia Manenti, Elisa Rosolani, Francesca Zanellato. ISSN 2504- 1924 • ISBN 978- 3- 0343- 4669- 6 (Print) ISBN 978- 3- 0343- 4866- 9 (E- PDF) • ISBN 978- 3- 0343- 4867- 6 (EPUB) DOI 10.3726/ b21636 Open Access: This work is licensed under a Creative Commons Attribution NonCommercial NoDerivatives 4.0 unported license. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/ © Lilla Maria Crisafulli / Serena Baiesi / Carlotta Farese (eds.), Elena Spandri / Fabio Liberto / Franca Dellarosa / Gioia Angeletti / Maria Schoina / Timothy Webb 2023. Published by Peter Lang Group AG, Lausanne, Suisse [email protected] http:// www.peterl ang.com/ newgenprepdf	[ "the", "internet", " \n", "at", "http://", " ", "dnb.d-", "nb.de", ".", "\n", "Library", "of", "Congress", "Cataloging", "-", "in", "-", "Publication", "Data", "\n", "A", "CIP", "catalog", "record", "for", "this", "book", "has", "been", "applied", "for", "at", "the", "\n", "Library", "of", "Congress", ".", "\n", "This", "book", "was", "published", "with", "the", "financial", "assistance", "of", "the", "Department", "of", "Modern", "\n", "Languages", ",", "Literatures", "and", "Cultures", "of", "the", "University", "of", "Bologna", ".", "\n", "The", "cover", "illustration", "was", "designed", "by", "the", "interns", "of", "CISR", ",", "Inter", "-", "University", "Centre", "for", "the", "\n", "Study", "of", "Romanticism", "(", "https://site.unibo.it/cisr/it", "):", " \n", "Giulia", "Manenti", ",", "Elisa", "Rosolani", ",", "Francesca", "Zanellato", ".", "\n", "ISSN", "2504-", "1924", "•", "ISBN", "978-", "3-", "0343-", "4669-", "6", "(", "Print", ")", "\n", "ISBN", "978-", "3-", "0343-", "4866-", "9", "(", "E-", "PDF", ")", "•", "ISBN", "978-", "3-", "0343-", "4867-", "6", "(", "EPUB", ")", "\n", "DOI", "10.3726/", "b21636", "\n", "Open", "Access", ":", "This", "work", "is", "licensed", "under", "a", "Creative", "Commons", "\n", "Attribution", "NonCommercial", "NoDerivatives", "4.0", "unported", "license", ".", "\n", "To", "view", "a", "copy", "of", "this", "license", ",", "visit", "\n", "https://creativecommons.org/licenses/by-nc-nd/4.0/", "\n", "©", "Lilla", "Maria", "Crisafulli", "/", "Serena", "Baiesi", "/", "Carlotta", "Farese", "(", "eds", ".", ")", ",", "\n", "Elena", "Spandri", "/", "Fabio", "Liberto", "/", "Franca", "Dellarosa", "/", "Gioia", "Angeletti", "/", " \n", "Maria", "Schoina", "/", "Timothy", "Webb", "2023", ".", "\n", "Published", "by", "Peter", "Lang", "Group", "AG", ",", "Lausanne", ",", "Suisse", "\n", "[email protected]", "http://", "www.peterl", "ang.com/", " ", "newgenprepdf" ]	[]
as organizations with extreme political aims such as white supremacists and neo-Nazis in the United States.¹¹ Members of such large groups exaggerate selected aspects of their childhood large-group identities by holding on to a restricted special nationalistic, religious or political belief. Sometimes they become believers in ideas that were not available in their childhood environments. In short, they give up sharing overall sentiments with people who had the same childhood large-group identity but who have not made such specific new selections. 10 In this paper I will not focus on large-group leaders and the psychological two-way street between them and their followers. Elsewhere I studied in depth the importance of the tent s ' pole in steadying the tent canvas -Volkan (1997); Volkan (2020). 11 Volkan (2020); Suistola & Volkan (2017). Religious knives: Historical and psychological dimensions of international terrorism. ## Initial Reactions to Massive Trauma at the Hand of the Other	[ "as", "organizations", "with", "extreme", "political", "aims", "such", "as", "white", "supremacists", "and", "neo", "-", "Nazis", "in", "the", "United", "States.¹¹", "Members", "of", "such", "large", "groups", "exaggerate", "selected", "aspects", "of", "their", "childhood", "large", "-", "group", "identities", "by", "holding", "on", "to", "a", "restricted", "special", "nationalistic", ",", "religious", "or", "political", "belief", ".", "Sometimes", "they", "become", "believers", "in", "ideas", "that", "were", "not", "available", "in", "their", "childhood", "environments", ".", "In", "short", ",", "they", "give", "up", "sharing", "overall", "sentiments", "with", "people", "who", "had", "the", "same", "childhood", "large", "-", "group", "identity", "but", "who", "have", "not", "made", "such", "specific", "new", "selections", ".", "\n\n", "10", "In", "this", "paper", "I", "will", "not", "focus", "on", "large", "-", "group", "leaders", "and", "the", "psychological", "two", "-", "way", "street", "between", "them", "and", "their", "followers", ".", "Elsewhere", "I", "studied", "in", "depth", "the", "importance", "of", "the", "tent", "s", "'", "pole", "in", "steadying", "the", "tent", "canvas", "-Volkan", "(", "1997", ")", ";", "Volkan", "(", "2020", ")", ".", "\n\n", "11", "Volkan", "(", "2020", ")", ";", "Suistola", "&", "amp", ";", "Volkan", "(", "2017", ")", ".", "Religious", "knives", ":", "Historical", "and", "psychological", "dimensions", "of", "international", "terrorism", ".", "\n\n", "#", "#", "Initial", "Reactions", "to", "Massive", "Trauma", "at", "the", "Hand", "of", "the", "Other" ]	[ { "end": 556, "label": "CITATION_ID", "start": 554 }, { "end": 810, "label": "CITATION_ID", "start": 808 }, { "end": 824, "label": "CITATION_REF", "start": 811 }, { "end": 817, "label": "AUTHOR", "start": 811 }, { "end": 823, "label": "YEAR", "start": 819 }, { "end": 854, "label": "CITATION_REF", "start": 841 }, { "end": 847, "label": "AUTHOR", "start": 841 }, { "end": 853, "label": "YEAR", "start": 849 } ]
0 NCI = Normalised citation impact EC projects = EU-funded R&I projectsTable V. Selected S&T specialisation domains in Azerbaijan 18 Overview of economic, innovation, scientific and technological specialisations Georgia – Summary of the strengths of the S&T specialisations Georgia’s most highlighted S&T domains are the following: ■Environmental sciences and industries scores highly on all S&T indicators – on crit- ical mass, specialisation and excellence – for publications, patents and projects. It is a very clear specialisation domain for Georgia, with particular relevance in Geology and Geotech- nical engineering, as well as Environmental engineering and Chemistry; ■Agrifood presents a high specialisation in patents and publications, as well as a critical mass in patents and a relevant number of EU-funded R&I projects, with science oriented towards Horticulture, Genetics and Plant sci- ence; ■Health and wellbeing presents a high crit- ical mass, specialisation and citation impact in publications, while no positive indicator emerges in relation to patents. It co-occurs frequently with the domain of Agrifood. Be- yond General medicine, research is related in particular to Infectious diseases and Immu- nology; and ■ICT and computer science presents a spe- cialisation in patents as well as highly cited publications and a relevant number of EC pro- jects. GEORGIA Critical mass Specialisation Excellence Summary S&T domain Pubs. Pat. Pubs. Pat. NCIEC projectsTotal Agrifood 4 Biotechnology 0 Chemistry and chemical engineering2 Electric and electronic technologies0 Environmental sciences and industries6 Fundamental physics and mathematics3 Governance, culture, education and the economy4 Health and wellbeing 3 ICT and computer science 3 Mechanical engineering and heavy machinery2 Nanotechnology and materials 2 Optics and photonics 1 NCI = Normalised citation impact EC projects = EU-funded R&I projectsTable VI. Selected S&T specialisation domains in Georgia Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation19 Moldova – Summary of the strengths of the S&T specialisations Moldova presents a rather diversified S&T pano- rama. Its most highlighted S&T specialisation do- mains are the following: ■Health and wellbeing presents a nota- ble critical mass, specialisation and citation impact in publications, as well as a relevant number of patents and EC projects. The ‘Nico- lae Testemitanu’ State University of Medicine and Pharmacy is the leading academic institu- tion in the domain, accounting for more than one third of the country’s total records pro- duced on this topic; ■Nanotechnology and materials presents a notable critical mass, specialisation and cita- tion impact in publications, as	[ "0", "\n", "", "NCI", "=", "Normalised", "citation", "impact", "", "EC", "projects", "=", "EU", "-", "funded", "R&I", "projectsTable", "V.", "Selected", "S&T", "specialisation", "domains", "in", "Azerbaijan", "\n", "18", "\n", "Overview", "of", "economic", ",", "innovation", ",", "scientific", "and", "technological", "specialisations", "\n", "Georgia", "–", "Summary", "of", "the", "strengths", "of", "\n", "the", "S&T", "specialisations", "\n", "Georgia", "’s", "most", "highlighted", "S&T", "domains", "are", "the", "\n", "following", ":", "\n ", "■", "Environmental", "sciences", "and", "industries", "\n", "scores", "highly", "on", "all", "S&T", 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"\n", "technologies0", "\n", "Environmental", "sciences", "and", "\n", "industries6", "\n", "Fundamental", "physics", "and", "\n", "mathematics3", "\n", "Governance", ",", "culture", ",", "education", "\n", "and", "the", "economy4", "\n", "Health", "and", "wellbeing", "3", "\n", "ICT", "and", "computer", "science", "3", "\n", "Mechanical", "engineering", "and", "\n", "heavy", "machinery2", "\n", "Nanotechnology", "and", "materials", "2", "\n", "Optics", "and", "photonics", "1", "\n", "", "NCI", "=", "Normalised", "citation", "impact", "", "EC", "projects", "=", "EU", "-", "funded", "R&I", "projectsTable", "VI", ".", "Selected", "S&T", "specialisation", "domains", "in", "Georgia", "\n", "Smart", "Specialisation", "in", "the", "Eastern", "Partnership", "countries", "-", "Potential", "for", "knowledge", "-", "based", "economic", "cooperation19", "\n", "Moldova", "–", "Summary", "of", "the", "strengths", "of", "\n", "the", "S&T", "specialisations", "\n", "Moldova", "presents", "a", 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that single women were finally allowed to be honoured in the 1980s. Their ages, in order, were eighty- one, seventy- seven, and seventy- one. Lise Meitner was unmarried and died at the age of ninety in 1968, just before the second wave of the feminist movement.21 In Figure 0.2 , the third generation is indicated by the oval located after the second wave of feminism on the timeline; it is difficult to deny the existence of a double standard in the twentieth century, especially before the second 1901M. Curie (1903/191 1) WW I 1919 1 MWIA 1 Sex Disqualification (R emov al) Act 1919; The Medical Women’ s Int ernational Associatio n 2 SJWS: The Society of Japanese Women Scientis ts (1958~ ) 3 ICWES: The In ternational Conf erence of Wo men Engineer s and Scientis ts (1964~ ) 4 CEDAW: Convention on Elimination of All Forms of Discrimination Ag ainst Wo men (1979)The fi rst woman Ox ford DPhil 19221958 SJWS 2 1979 CEDA W * 41999 ICWES 11 3 in Japa n1964 ICWES 1 3 in New YorkThe fi rst woman Cambridge PhD 1925WW III. Joliot-Curie (1935)G. R. Cori (1947)D. C. Hodgkin (1964)B. McClintock (1983) G. Elion (1988) C. Nüsslein- Volhard (1995)Levi-Montalcini (1986) M. G. Mayer (1963) R. S. Yalow (1977) 10 20 30 40 50 60 70 80 90 2000 404040 70 80 7 0 7 0 Second- wave feminism Figure 0.2 Nobel Prize women in science and international exchanges xxx Negotiating in/visibility wave of feminism, when even top scientists were assumed to be ‘good wives’ and ‘wise mothers’. Gerty and Carl Cori received the Nobel Prize in 1947. For thirty- five years, they formed a close scientific partnership. They started their careers at a medical school in Prague, in what is now the Czech Republic, and moved to the US in 1922 to avoid antisemitism.22 However, for a long time, they could not find jobs that allowed them to work together because of anti- nepotism rules. Maria Goeppert Mayer was another typical example of a trailing spouse. She married Joseph Mayer in Göttingen in Germany. Eventually, Joseph was hired by the Johns Hopkins University, which had strict anti- nepotism rules, prohibiting the employment of relatives. Maria had neither a job nor a salary, while Joseph gained a post at Columbia, following his term at Hopkins. In 1960, she was finally appointed a full professor of	[ "that", "single", "women", "were", "finally", "allowed", "to", "\n", "be", "honoured", "in", "the", "1980s", ".", "Their", "ages", ",", "in", "order", ",", "were", "eighty-", " ", "one", ",", "seventy-", " \n", "seven", ",", "and", "seventy-", " ", "one", ".", "Lise", "Meitner", "was", "unmarried", "and", "died", "at", "the", "age", "of", "\n", "ninety", "in", "1968", ",", "just", "before", "the", "second", "wave", "of", "the", "feminist", "movement.21", "In", "\n", "Figure", "0.2", ",", "the", "third", "generation", "is", "indicated", "by", "the", "oval", "located", "after", "the", "\n", "second", "wave", "of", "feminism", "on", "the", "timeline", ";", "it", "is", "difficult", "to", "deny", "the", "existence", "\n", "of", "a", "double", "standard", "in", "the", "twentieth", "century", ",", "especially", "before", "the", "second", " \n \n \n \n \n \n \n", "1901M.", "Curie", "(", "1903/191", "1", ")", "\n", "WW", "I", "\n", "1919", "", "1", "\n", "MWIA", "\n", "", "1", "Sex", "Disqualification", "(", "R", "emov", "al", ")", "Act", "1919", ";", "The", "Medical", "Women", "’", "s", "Int", "ernational", "Associatio", "n", "\n", "", "2", "SJWS", ":", "The", "Society", "of", "Japanese", "Women", "Scientis", "ts", "(", "1958~", " ", ")", "\n", "", "3", "ICWES", ":", "The", "In", "ternational", "Conf", "erence", "of", "Wo", "men", "Engineer", "s", "and", "Scientis", "ts", "(", "1964~", " ", ")", "\n", "", "4", "CEDAW", ":", "Convention", "on", "Elimination", "of", "All", "Forms", "of", "Discrimination", "Ag", "ainst", "Wo", "men", "(", "1979)The", "fi", "rst", "woman", "Ox", "ford", "DPhil", "19221958", "\n", "SJWS", "", "2", "\n", "1979", "\n", "CEDA", "W", "", "41999", "\n", "ICWES", "11", "", "3", "\n", "in", "Japa", "n1964", "\n", "ICWES", "1", "*", "3", "\n", "in", "New", "YorkThe", "fi", "rst", "woman", "Cambridge", "PhD", "1925WW", "III", ".", "Joliot", "-", "Curie", "(", "1935)G.", "R.", "Cori", "(", "1947)D.", "C.", "Hodgkin", "(", "1964)B.", "McClintock", "(", "1983", ")", "\n", "G.", "Elion", "(", "1988", ")", "\n", "C.", "Nüsslein-", "\n", "Volhard", "(", "1995)Levi", "-", "Montalcini", "\n ", "(", "1986", ")", "\n", "M.", "G.", "Mayer", "\n ", "(", "1963", ")", "R.", "S.", "Yalow", "\n ", "(", "1977", ")", "\n", "10", "20", "30", "40", "50", "60", "70", "80", "90", "2000", "404040", "70", "80", "7", "0", "7", "0", "\n", "Second-", "wave", "\n", "feminism", "\n", "Figure", "0.2", " ", "Nobel", "Prize", "women", "in", "science", "and", "international", "exchanges", "\n \n", "xxx", "\n ", "Negotiating", "in", "/", "visibility", "\n", "wave", "of", "feminism", ",", "when", "even", "top", "scientists", "were", "assumed", "to", "be", "‘", "good", "wives", "’", "\n", "and", "‘", "wise", "mothers", "’", ".", "\n", "Gerty", "and", "Carl", "Cori", "received", "the", "Nobel", "Prize", "in", "1947", ".", "For", "thirty-", " ", "five", "\n", "years", ",", "they", "formed", "a", "close", "scientific", "partnership", ".", "They", "started", "their", "careers", "at", "\n", "a", "medical", "school", "in", "Prague", ",", "in", "what", "is", "now", "the", "Czech", "Republic", ",", "and", "moved", "to", "\n", "the", "US", "in", "1922", "to", "avoid", "antisemitism.22", "However", ",", "for", "a", "long", "time", ",", "they", "could", "\n", "not", "find", "jobs", "that", "allowed", "them", "to", "work", "together", "because", "of", "anti-", " ", "nepotism", "\n", "rules", ".", "Maria", "Goeppert", "Mayer", "was", "another", "typical", "example", "of", "a", "trailing", "\n", "spouse", ".", "She", "married", "Joseph", "Mayer", "in", "Göttingen", "in", "Germany", ".", "Eventually", ",", "\n", "Joseph", "was", "hired", "by", "the", "Johns", "Hopkins", "University", ",", "which", "had", "strict", "anti-", " \n", "nepotism", "rules", ",", "prohibiting", "the", "employment", "of", "relatives", ".", "Maria", "had", "neither", "a", "\n", "job", "nor", "a", "salary", ",", "while", "Joseph", "gained", "a", "post", "at", "Columbia", ",", "following", "his", "term", "\n", "at", "Hopkins", ".", "In", "1960", ",", "she", "was", "finally", "appointed", "a", "full", "professor", "of" ]	[ { "end": 269, "label": "CITATION_REF", "start": 267 }, { "end": 1817, "label": "CITATION_REF", "start": 1815 } ]
to work after raising a family I took an Open University degree, gaining friends and lots of experience as well as a degree to update my professional qualifications – again, paid for by part-time work. I now have concerns for my eldest grandson, who wants, very sensibly, to take an apprenticeship, as I hear that companies are cutting back on employees and are not often looking at taking on apprentices. Jean Austin Crawley, West Sussex Have an opinion on anything you’ve read in the Guardian today? Please email us your letter and it will be considered for publication in our letters section. - Universities - Higher education - Student engagement - Students - letters ### Most viewed - CDC erupts in chaos after ousted chief Susan Monarez refuses to resign - Ostapenko and Townsend confront each other after US Open match: ‘She said I had no education’ - Glorious Grimsby humiliate Manchester United with shootout victory - The Burning Man Orgy Dome: welcome to the latest festival disaster - How hard will Trump’s 50% tariff hit India, and what is Delhi doing about it? ## Most viewed ## Most viewed - Education - Schools - Teachers - Universities - Students - News - Opinion - Sport - Culture - Lifestyle Original reporting and incisive analysis, direct from the Guardian every morning - Help - Complaints & corrections - SecureDrop - Work for us - Privacy policy - Cookie policy - Terms & conditions - Contact us - All topics - All writers - Digital newspaper archive - Tax strategy - Facebook - YouTube - Instagram - LinkedIn - Newsletters	[ "to", "work", "after", "raising", "a", "family", "I", "took", "an", "Open", "University", "degree", ",", "gaining", "friends", "and", "lots", "of", "experience", "as", "well", "as", "a", "degree", "to", "update", "my", "professional", "qualifications", "–", "again", ",", "paid", "for", "by", "part", "-", "time", "work", ".", "\n\n", "I", "now", "have", "concerns", "for", "my", "eldest", "grandson", ",", "who", "wants", ",", "very", "sensibly", ",", "to", "take", "an", "apprenticeship", ",", "as", "I", "hear", "that", "companies", "are", "cutting", "back", "on", "employees", "and", "are", "not", "often", "looking", "at", "taking", "on", "apprentices", ".", "\n", "Jean", "Austin", "\n", "Crawley", ",", "West", "Sussex", "\n\n", "Have", "an", "opinion", "on", "anything", "you", "’ve", "read", "in", "the", "Guardian", "today", "?", "Please", "email", "us", "your", "letter", "and", "it", "will", "be", "considered", "for", "publication", "in", "our", "letters", "section", ".", "\n\n", "-", "Universities", "\n", "-", "Higher", "education", "\n", "-", "Student", "engagement", "\n", "-", "Students", "\n", "-", "letters", "\n\n", "#", "#", "#", "Most", "viewed", "\n\n", "-", "CDC", "erupts", "in", "chaos", "after", "ousted", "chief", "Susan", "Monarez", "refuses", "to", "resign", "\n", "-", "Ostapenko", "and", "Townsend", "confront", "each", "other", "after", "US", "Open", "match", ":", "‘", "She", "said", "I", "had", "no", "education", "’", "\n", "-", "Glorious", "Grimsby", "humiliate", "Manchester", "United", "with", "shootout", "victory", "\n", "-", "The", "Burning", "Man", "Orgy", "Dome", ":", "welcome", "to", "the", "latest", "festival", "disaster", "\n", "-", "How", "hard", "will", "Trump", "’s", "50", "%", "tariff", "hit", "India", ",", "and", "what", "is", "Delhi", "doing", "about", "it", "?", "\n\n", "#", "#", "Most", "viewed", "\n\n", "#", "#", "Most", "viewed", "\n\n", "-", "Education", "\n", "-", "Schools", "\n", "-", "Teachers", "\n", "-", "Universities", "\n", "-", "Students", "\n\n", "-", "News", "\n", "-", "Opinion", "\n", "-", "Sport", "\n", "-", "Culture", "\n", "-", "Lifestyle", "\n\n", "Original", "reporting", "and", "incisive", "analysis", ",", "direct", "from", "the", "Guardian", "every", "morning", "\n\n", "-", "Help", "\n", "-", "Complaints", "&", "amp", ";", "corrections", "\n", "-", "SecureDrop", "\n", "-", "Work", "for", "us", "\n", "-", "Privacy", "policy", "\n", "-", "Cookie", "policy", "\n", "-", "Terms", "&", "amp", ";", "conditions", "\n", "-", "Contact", "us", "\n\n", "-", "All", "topics", "\n", "-", "All", "writers", "\n", "-", "Digital", "newspaper", "archive", "\n", "-", "Tax", "strategy", "\n", "-", "Facebook", "\n", "-", "YouTube", "\n", "-", "Instagram", "\n", "-", "LinkedIn", "\n", "-", "Newsletters" ]	[]
there- fore been decided to circumvent taxonomies and to use the textual content of each record to ob- tain fine-grained and homogeneous mapping of all S&T activities across the EaP countries. To do so, a series of topics have been extracted from the com- bined corpus of scientific publications, EU-funded research projects and patents by means of topic modelling – an algorithmic approach to extract condensed information from large textual corpora in the form of ‘topics’. Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation145 The result of topic modelling is a series of top- ics, each characterised by a list of the main words that tend to appear in them. This whole process is carried out iteratively and with human revision in order to identify and eliminate unrelated or irrel- evant terms: proper names, acronyms, words with little meaning or transversal words. Topics are extracted individually for each country, allowing for differences and nuances in national special- isations. The individual topics are then clustered together according to their semantic similarity, leading to 14 S&T specialisation domains defined across the EaP. This section presents and discuss- es these results. 2.1 S&T data availability Table 3.1 presents the data sources used in topic modelling. Publications account for 64.48% of the total number of records, while patents account for 32.36% and EC projects for only 0.16%. Additionally, Table 3.2 showcases the specific dis- tribution of records per type and per country. It is important to note the significantly low number of patents in comparison to the number of publica- tions, which is especially pronounced in the cases Scope Source Data extraction criteriaNo of records (2012-2019) Scientific publications in internationally indexed journalsScopus (Elsevier)Publications with at least one author with an EaP affiliation131 179 European Commission- funded research and innovation projectsCORDIS - Community Research and Development Information ServiceFP7 and H2020 projects with at least one EaP partner324 PatentsWorldwide bibliographic data (DOCDB) - European Patent OfficeAt least one EaP inventor or applicant for those patents filed through a patent office covered by the EPO DOCDB database261 997 (2011-2018)Table 3.1. Characterisation of the data sources used in topic modelling, including the name of the source, its scope, the data extraction criteria and the number of recordsof Armenia and Azerbaijan, where publications ac- count for 96%, 92% and 87% of the total num- ber of records in the country, respectively. This is partially	[ "there-", "\n", "fore", "been", "decided", "to", "circumvent", "taxonomies", "and", "\n", "to", "use", "the", "textual", "content", "of", "each", "record", "to", "ob-", "\n", "tain", "fine", "-", "grained", "and", "homogeneous", "mapping", "of", "all", "\n", "S&T", "activities", "across", "the", "EaP", "countries", ".", "To", "do", "so", ",", "a", "\n", "series", "of", "topics", "have", "been", "extracted", "from", "the", "com-", "\n", "bined", "corpus", "of", "scientific", "publications", ",", "EU", "-", "funded", "\n", "research", "projects", "and", "patents", "by", "means", "of", "topic", "\n", "modelling", "–", "an", "algorithmic", "approach", "to", "extract", "\n", "condensed", "information", "from", "large", "textual", "corpora", "\n", "in", "the", "form", "of", "‘", "topics", "’", ".", "\n", "Smart", "Specialisation", "in", "the", "Eastern", "Partnership", "countries", "-", "Potential", "for", "knowledge", "-", "based", "economic", "cooperation145", "\n", "The", "result", "of", "topic", "modelling", "is", "a", "series", "of", "top-", "\n", "ics", ",", "each", "characterised", "by", "a", "list", "of", "the", "main", "words", "\n", "that", "tend", "to", "appear", "in", "them", ".", "This", "whole", "process", "is", "\n", "carried", "out", "iteratively", "and", "with", "human", "revision", "in", "\n", "order", "to", "identify", "and", "eliminate", "unrelated", "or", "irrel-", "\n", "evant", "terms", ":", "proper", "names", ",", "acronyms", ",", "words", "with", "\n", "little", "meaning", "or", "transversal", "words", ".", "Topics", "are", "\n", "extracted", "individually", "for", "each", "country", ",", "allowing", "\n", "for", "differences", "and", "nuances", "in", "national", "special-", "\n", "isations", ".", "The", "individual", "topics", "are", "then", "clustered", "\n", "together", "according", "to", "their", "semantic", "similarity", ",", "\n", "leading", "to", "14", "S&T", "specialisation", "domains", "defined", "\n", "across", "the", "EaP.", "This", "section", "presents", "and", "discuss-", "\n", "es", "these", "results", ".", "\n", "2.1", "S&T", "data", "availability", "\n", "Table", "3.1", "presents", "the", "data", "sources", "used", "in", "topic", "\n", "modelling", ".", "Publications", "account", "for", "64.48", "%", "of", "the", "\n", "total", "number", "of", "records", ",", "while", "patents", "account", "for", "\n", "32.36", "%", "and", "EC", "projects", "for", "only", "0.16", "%", ".", "\n", "Additionally", ",", "Table", "3.2", "showcases", "the", "specific", "dis-", "\n", "tribution", "of", "records", "per", "type", "and", "per", "country", ".", "It", "is", "\n", "important", "to", "note", "the", "significantly", "low", "number", "of", "\n", "patents", "in", "comparison", "to", "the", "number", "of", "publica-", "\n", "tions", ",", "which", "is", "especially", "pronounced", "in", "the", "cases", "\n", "Scope", "Source", "Data", "extraction", "criteriaNo", "of", "records", " \n", "(", "2012", "-", "2019", ")", "\n", "Scientific", "publications", "\n", "in", "internationally", "indexed", "\n", "journalsScopus", "(", "Elsevier)Publications", "with", "at", "least", "\n", "one", "author", "with", "an", "EaP", "\n", "affiliation131", "179", "\n", "European", "Commission-", "\n", "funded", "research", "and", "\n", "innovation", "projectsCORDIS", "-", "Community", "\n", "Research", "and", "\n", "Development", "Information", "\n", "ServiceFP7", "and", "H2020", "projects", "\n", "with", "at", "least", "one", "EaP", "\n", "partner324", "\n", "PatentsWorldwide", "bibliographic", "\n", "data", "(", "DOCDB", ")", "-", "European", "\n", "Patent", "OfficeAt", "least", "one", "EaP", "inventor", "\n", "or", "applicant", "for", "those", "\n", "patents", "filed", "through", "a", "\n", "patent", "office", "covered", "by", "\n", "the", "EPO", "DOCDB", "database261", "997", "\n", "(", "2011", "-", "2018)Table", "3.1", ".", "Characterisation", "of", "the", "data", "sources", "used", "in", "topic", "modelling", ",", "including", "the", "name", "of", "the", "source", ",", "its", "scope", ",", "\n", "the", "data", "extraction", "criteria", "and", "the", "number", "of", "recordsof", "Armenia", "and", "Azerbaijan", ",", "where", "publications", "ac-", "\n", "count", "for", "96", "%", ",", "92", "%", "and", "87", "%", "of", "the", "total", "num-", "\n", "ber", "of", "records", "in", "the", "country", ",", "respectively", ".", "This", "is", "\n", "partially" ]	[]
and the second conductor, respectively, of the conductor 205 are used. - a conductive material that has a function of inhibiting the passage of impurities such as water and hydrogen is preferably used as the first conductor of the conductor 240 . - a conductive material that has a function of inhibiting the passage of impurities such as water and hydrogen is preferably used. - tantalum, tantalum nitride, titanium, titanium nitride, ruthenium, ruthenium oxide, or the like is preferably used. - the conductive material having a function of inhibiting the passage of impurities such as water and hydrogen may be used as a single layer or stacked layers. Using the conductive material for the first conductor of the conductor 240 can prevent impurities such as hydrogen and water from entering the oxide 230 through the conductor 240 from the layers above the insulator 281 . - the conductor 240 may be provided as a single layer or to have a stacked-layer structure of three or more layers. - the layers may be distinguished by ordinal numbers corresponding to the formation order. - the conductor 260 is covered with the insulator 270 and the insulator 273 functioning as an etching stopper, it is not necessary to provide an alignment margin for the conductor 260 and the conductor 240 . - the distance between the conductor 260 and the conductor 240 can be small. Accordingly, the area occupied by the cell 600 can be reduced, and the miniaturization and high integration of the semiconductor device can be achieved. - the conductor 242 b and the oxide 230 may be divided into the transistor 200 a side and the transistor 200 b side. Moreover, an opening may be formed in the conductor 242 b and the oxide 230 . - the opening is formed in the conductor 242 b and the oxide 230 , and the conductor 240 and the conductor 209 are in direct contact with each other; however, the present invention is not limited thereto. - a bottom surface of the conductor 240 may be in contact with the conductor 242 b - a top surface of the conductor 209 may be in contact with the region 243 b of the oxide 230 a . - FIG. 5 (A) is an enlarged view obtained by changing the shape of an area around the conductor 240 and the conductor 209 from that	[ "and", "the", "second", "conductor", ",", "respectively", ",", "of", "the", "conductor", "205", "\n", "are", "used", ".", "\n", "-", "a", "conductive", "material", "that", "has", "a", "function", "of", "inhibiting", "the", "passage", "of", "impurities", "such", "as", "water", "and", "hydrogen", "\n", "is", "preferably", "used", "as", "the", "first", "conductor", "of", "the", "conductor", "240", ".", "\n", "-", "a", "conductive", "material", "that", "has", "a", "function", "of", "inhibiting", "the", "passage", "of", "impurities", "such", "as", "water", "and", "hydrogen", "\n", "is", "preferably", "used", ".", "\n", "-", "tantalum", ",", "tantalum", "nitride", ",", "titanium", ",", "titanium", "nitride", ",", "ruthenium", ",", "ruthenium", "oxide", ",", "or", "the", "like", "\n", "is", "preferably", "used", ".", "\n", "-", "the", "conductive", "material", "having", "a", "function", "of", "inhibiting", "the", "passage", "of", "impurities", "such", "as", "water", "and", "hydrogen", "\n", "may", "be", "used", "as", "a", "single", "layer", "or", "stacked", "layers", ".", "Using", "the", "conductive", "material", "for", "the", "first", "conductor", "of", "the", "conductor", "240", "can", "prevent", "impurities", "such", "as", "hydrogen", "and", "water", "from", "entering", "the", "oxide", "230", "through", "the", "conductor", "240", "from", "the", "layers", "above", "the", "insulator", "281", ".", "\n", "-", "the", "conductor", "240", "\n", "may", "be", "provided", "as", "a", "single", "layer", "or", "to", "have", "a", "stacked", "-", "layer", "structure", "of", "three", "or", "more", "layers", ".", "\n", "-", "the", "layers", "\n", "may", "be", "distinguished", "by", "ordinal", "numbers", "corresponding", "to", "the", "formation", "order", ".", "\n", "-", "the", "conductor", "260", "\n", "is", "covered", "with", "the", "insulator", "270", "and", "the", "insulator", "273", "functioning", "as", "an", "etching", "stopper", ",", "it", "is", "not", "necessary", "to", "provide", "an", "alignment", "margin", "for", "the", "conductor", "260", "and", "the", "conductor", "240", ".", "\n", "-", "the", "distance", "between", "the", "conductor", "260", "and", "the", "conductor", "240", "\n", "can", "be", "small", ".", "Accordingly", ",", "the", "area", "occupied", "by", "the", "cell", "600", "can", "be", "reduced", ",", "and", "the", "miniaturization", "and", "high", "integration", "of", "the", "semiconductor", "device", "can", "be", "achieved", ".", "\n", "-", "the", "conductor", "242", "b", "and", "the", "oxide", "230", "\n", "may", "be", "divided", "into", "the", "transistor", "200", "a", "side", "and", "the", "transistor", "200", "b", "side", ".", "Moreover", ",", "an", "opening", "may", "be", "formed", "in", "the", "conductor", "242", "b", "and", "the", "oxide", "230", ".", "\n", "-", "the", "opening", "\n", "is", "formed", "in", "the", "conductor", "242", "b", "and", "the", "oxide", "230", ",", "and", "the", "conductor", "240", "and", "the", "conductor", "209", "are", "in", "direct", "contact", "with", "each", "other", ";", "however", ",", "the", "present", "invention", "is", "not", "limited", "thereto", ".", "\n", "-", "a", "bottom", "surface", "of", "the", "conductor", "240", "\n", "may", "be", "in", "contact", "with", "the", "conductor", "242", "b", "\n", "-", "a", "top", "surface", "of", "the", "conductor", "209", "\n", "may", "be", "in", "contact", "with", "the", "region", "243", "b", "of", "the", "oxide", "230", "a", ".", "\n", "-", "FIG", ".", "5", "(", "A", ")", "\n", "is", "an", "enlarged", "view", "obtained", "by", "changing", "the", "shape", "of", "an", "area", "around", "the", "conductor", "240", "and", "the", "conductor", "209", "from", "that" ]	[]
Y are functionally connected are disclosed in this specification and the like. Accordingly, without being limited to a predetermined connection relation, for example, a connection relation shown in drawings or texts, a connection relation other than one shown in drawings or texts is regarded as being described in the drawings or the texts. - X and Y denote an object (e.g., a device, an element, a circuit, a wiring, an electrode, a terminal, a conductive film, or a layer). - An example of the case where X and Y are directly connected is the case where an element that allows electrical connection between X and Y (e.g., a switch, a transistor, a capacitor, an inductor, a resistor, a diode, a display element, a light-emitting element, or a load) is not connected between X and Y, and is the case where X and Y are connected without an element that allows electrical connection between X and Y (e.g., a switch, a transistor, a capacitor, an inductor, a resistor, a diode, a display element, a light-emitting element, or a load) placed therebetween. - an element that allows electrical connection between X and Y e.g., a switch, a transistor, a capacitor, an inductor, a resistor, a diode, a display element, a light-emitting element, or a load - one or more elements that allow electrical connection between X and Y can be connected between X and Y. - a switch has a function of being controlled to be turned on or off. That is, a switch has a function of being in a conduction state (on state) or a non-conduction state (off state) to control whether or not current flows. - a switch has a function of selecting and changing a current path. Note that the case where X and Y are electrically connected includes the case where X and Y are directly connected. - X and Y are functionally connected is the case where one or more circuits that allow functional connection between X and Y (e.g., a logic circuit (an inverter, a NAND circuit, a NOR circuit, or the like), a signal converter circuit (a DA converter circuit, an AD converter circuit, a gamma correction circuit, or the like), a potential level converter circuit (a power supply circuit (e.g., a step-up circuit, a step-down circuit, or the like), a level shifter circuit for changing the potential level of a signal, or the	[ "Y", "are", "functionally", "connected", "are", "disclosed", "in", "this", "specification", "and", "the", "like", ".", "Accordingly", ",", "without", "being", "limited", "to", "a", "predetermined", "connection", "relation", ",", "for", "example", ",", "a", "connection", "relation", "shown", "in", "drawings", "or", "texts", ",", "a", "connection", "relation", "other", "than", "one", "shown", "in", "drawings", "or", "texts", "is", "regarded", "as", "being", "described", "in", "the", "drawings", "or", "the", "texts", ".", "\n", "-", "X", "and", "Y", "\n", "denote", "an", "object", "(", "e.g.", ",", "a", "device", ",", "an", "element", ",", "a", "circuit", ",", "a", "wiring", ",", "an", "electrode", ",", "a", "terminal", ",", "a", "conductive", "film", ",", "or", "a", "layer", ")", ".", "\n", "-", "An", "example", "of", "the", "case", "where", "X", "and", "Y", "are", "directly", "connected", "\n", "is", "the", "case", "where", "an", "element", "that", "allows", "electrical", "connection", "between", "X", "and", "Y", "(", "e.g.", ",", "a", "switch", ",", "a", "transistor", ",", "a", "capacitor", ",", "an", "inductor", ",", "a", "resistor", ",", "a", "diode", ",", "a", "display", "element", ",", "a", "light", "-", "emitting", "element", ",", "or", "a", "load", ")", "is", "not", "connected", "between", "X", "and", "Y", ",", "and", "is", "the", "case", "where", "X", "and", "Y", "are", "connected", "without", "an", "element", "that", "allows", "electrical", "connection", "between", "X", "and", "Y", "(", "e.g.", ",", "a", "switch", ",", "a", "transistor", ",", "a", "capacitor", ",", "an", "inductor", ",", "a", "resistor", ",", "a", "diode", ",", "a", "display", "element", ",", "a", "light", "-", "emitting", "element", ",", "or", "a", "load", ")", "placed", "therebetween", ".", "\n", "-", "an", "element", "that", "allows", "electrical", "connection", "between", "X", "and", "Y", "\n", "e.g.", ",", "a", "switch", ",", "a", "transistor", ",", "a", "capacitor", ",", "an", "inductor", ",", "a", "resistor", ",", "a", "diode", ",", "a", "display", "element", ",", "a", "light", "-", "emitting", "element", ",", "or", "a", "load", "\n", "-", "one", "or", "more", "elements", "that", "allow", "electrical", "connection", "between", "X", "and", "Y", "\n", "can", "be", "connected", "between", "X", "and", "Y.", "\n", "-", "a", "switch", "\n", "has", "a", "function", "of", "being", "controlled", "to", "be", "turned", "on", "or", "off", ".", "That", "is", ",", "a", "switch", "has", "a", "function", "of", "being", "in", "a", "conduction", "state", "(", "on", "state", ")", "or", "a", "non", "-", "conduction", "state", "(", "off", "state", ")", "to", "control", "whether", "or", "not", "current", "flows", ".", "\n", "-", "a", "switch", "\n", "has", "a", "function", "of", "selecting", "and", "changing", "a", "current", "path", ".", "Note", "that", "the", "case", "where", "X", "and", "Y", "are", "electrically", "connected", "includes", "the", "case", "where", "X", "and", "Y", "are", "directly", "connected", ".", "\n", "-", "X", "and", "Y", "\n", "are", "functionally", "connected", "is", "the", "case", "where", "one", "or", "more", "circuits", "that", "allow", "functional", "connection", "between", "X", "and", "Y", "(", "e.g.", ",", "a", "logic", "circuit", "(", "an", "inverter", ",", "a", "NAND", "circuit", ",", "a", "NOR", "circuit", ",", "or", "the", "like", ")", ",", "a", "signal", "converter", "circuit", "(", "a", "DA", "converter", "circuit", ",", "an", "AD", "converter", "circuit", ",", "a", "gamma", "correction", "circuit", ",", "or", "the", "like", ")", ",", "a", "potential", "level", "converter", "circuit", "(", "a", "power", "supply", "circuit", "(", "e.g.", ",", "a", "step", "-", "up", "circuit", ",", "a", "step", "-", "down", "circuit", ",", "or", "the", "like", ")", ",", "a", "level", "shifter", "circuit", "for", "changing", "the", "potential", "level", "of", "a", "signal", ",", "or", "the" ]	[]
an extranet, a PAN (Personal Area Network), a LAN (Local Area Network), a CAN (Campus Area Network), a MAN (Metropolitan Area Network), a WAN (Wide Area Network), or a GAN (Global Area Network). In the case of performing wireless communication, it is possible to use, as a communication protocol or a communication technology, a communications standard such as LTE (Long Term Evolution), GSM (Global System for Mobile Communication: registered trademark), EDGE (Enhanced Data Rates for GSM Evolution), CDMA2000 (Code Division Multiple Access 2000), or W-CDMA (registered trademark), or a communications standard developed by IEEE, such as Wi-Fi (registered trademark), Bluetooth (registered trademark), or ZigBee (registered trademark). With the structure in and , analog signals obtained with external sensors or the like can be processed by different AI systems. For example, analog signals containing biological information such as brain waves, a pulse, blood pressure, and body temperature obtained with a variety of sensors such as a brain wave sensor, a pulse wave sensor, a blood pressure sensor, and a temperature sensor can be processed by different AI systems. When signal processing or learning is performed by different AI systems, the amount of information processed by each AI system can be reduced. Accordingly, signal processing or learning can be performed with a smaller amount of arithmetic processing. As a result, recognition accuracy can be increased. The information obtained with each AI system is expected to enable instant and collective understanding of a complex change in biological information. The structure described in this embodiment can be used in appropriate combination with the structure described in the other embodiments. In this embodiment, an example of an IC incorporating the AI system described in the above embodiment will be described. In the AI system described in the above embodiment, a digital processing circuit formed of Si transistors, such as a CPU; an analog arithmetic circuit using OS transistors; an OS-FPGA; and an OS memory such as a DOSRAM or a NOSRAM can be integrated into one die. illustrates an example of an IC in which the AI system is incorporated. An illustrated in includes a and a . The is mounted on a printed , for example. A plurality of such IC chips are combined and electrically connected to each other on the printed ; thus, a board on which electronic components are mounted (a circuit board ) is completed. In the , the various	[ "an", "extranet", ",", "a", "PAN", "(", "Personal", "Area", "Network", ")", ",", "a", "LAN", "(", "Local", "Area", "Network", ")", ",", "a", "CAN", "(", "Campus", "Area", "Network", ")", ",", "a", "MAN", "(", "Metropolitan", "Area", "Network", ")", ",", "a", "WAN", "(", "Wide", "Area", "Network", ")", ",", "or", "a", "GAN", "(", "Global", "Area", "Network", ")", ".", "In", "the", "case", "of", "performing", "wireless", "communication", ",", "it", "is", "possible", "to", "use", ",", "as", "a", "communication", "protocol", "or", "a", "communication", "technology", ",", "a", "communications", "standard", "such", "as", "LTE", "(", "Long", "Term", "Evolution", ")", ",", "GSM", "(", "Global", "System", "for", "Mobile", "Communication", ":", "registered", "trademark", ")", ",", "EDGE", "(", "Enhanced", "Data", "Rates", "for", "GSM", "Evolution", ")", ",", "CDMA2000", "(", "Code", "Division", "Multiple", "Access", "2000", ")", ",", "or", "W", "-", "CDMA", "(", "registered", "trademark", ")", ",", "or", "a", "communications", "standard", "developed", "by", "IEEE", ",", "such", "as", "Wi", "-", "Fi", "(", "registered", "trademark", ")", ",", "Bluetooth", "(", "registered", "trademark", ")", ",", "or", "ZigBee", "(", "registered", "trademark", ")", ".", "\n\n", "With", "the", "structure", "in", " ", "and", ",", "analog", "signals", "obtained", "with", "external", "sensors", "or", "the", "like", "can", "be", "processed", "by", "different", "AI", "systems", ".", "For", "example", ",", "analog", "signals", "containing", "biological", "information", "such", "as", "brain", "waves", ",", "a", "pulse", ",", "blood", "pressure", ",", "and", "body", "temperature", "obtained", "with", "a", "variety", "of", "sensors", "such", "as", "a", "brain", "wave", "sensor", ",", "a", "pulse", "wave", "sensor", ",", "a", "blood", "pressure", "sensor", ",", "and", "a", "temperature", "sensor", "can", "be", "processed", "by", "different", "AI", "systems", ".", "When", "signal", "processing", "or", "learning", "is", "performed", "by", "different", "AI", "systems", ",", "the", "amount", "of", "information", "processed", "by", "each", "AI", "system", "can", "be", "reduced", ".", "Accordingly", ",", "signal", "processing", "or", "learning", "can", "be", "performed", "with", "a", "smaller", "amount", "of", "arithmetic", "processing", ".", "As", "a", "result", ",", "recognition", "accuracy", "can", "be", "increased", ".", "The", "information", "obtained", "with", "each", "AI", "system", "is", "expected", "to", "enable", "instant", "and", "collective", "understanding", "of", "a", "complex", "change", "in", "biological", "information", ".", "\n\n", "The", "structure", "described", "in", "this", "embodiment", "can", "be", "used", "in", "appropriate", "combination", "with", "the", "structure", "described", "in", "the", "other", "embodiments", ".", "\n\n", "In", "this", "embodiment", ",", "an", "example", "of", "an", "IC", "incorporating", "the", "AI", "system", "described", "in", "the", "above", "embodiment", "will", "be", "described", ".", "\n\n", "In", "the", "AI", "system", "described", "in", "the", "above", "embodiment", ",", "a", "digital", "processing", "circuit", "formed", "of", "Si", "transistors", ",", "such", "as", "a", "CPU", ";", "an", "analog", "arithmetic", "circuit", "using", "OS", "transistors", ";", "an", "OS", "-", "FPGA", ";", "and", "an", "OS", "memory", "such", "as", "a", "DOSRAM", "or", "a", "NOSRAM", "can", "be", "integrated", "into", "one", "die", ".", "\n\n", "illustrates", "an", "example", "of", "an", "IC", "in", "which", "the", "AI", "system", "is", "incorporated", ".", "An", " ", "illustrated", "in", " ", "includes", "a", " ", "and", "a", " ", ".", "The", " ", "is", "mounted", "on", "a", "printed", " ", ",", "for", "example", ".", "A", "plurality", "of", "such", "IC", "chips", "are", "combined", "and", "electrically", "connected", "to", "each", "other", "on", "the", "printed", " ", ";", "thus", ",", "a", "board", "on", "which", "electronic", "components", "are", "mounted", "(", "a", "circuit", "board", ")", "is", "completed", ".", "In", "the", " ", ",", "the", "various" ]	[]
Leather and imitations of leather; ani- mal skins, and hides; trunks and travelling luggage and carrying bags; umbrellas and parasols; walk- ing sticks; whips, harness and saddlery; collars, leashes and clothing for animals Class 19 – Building materials (non-metallic); non-metallic rigid pipes for building; asphalt, pitch and bitumen; non-metallic transportable buildings; monuments, not of metal Class 20 – Furniture, mirrors, picture frames; con- tainers, not of metal, for storage or transport; unworked or semi-worked bone, horn, ivory, whale- bone or mother-of-pearl; shells; meerschaum; yel- low amber Class 21 – Household or kitchen utensils and containers; combs and sponges; brushes, (except paintbrushes); brush-making materials; articles for cleaning purposes; steelwool; unworked or semi- worked glass, (except building glass used in build- ing); glassware, porcelain and earthenware Class 22 – Ropes and string; nets; tents, awnings, and tarpaulins; awnings of textile or synthetic ma- terials; sails; sacks for the transport and storage of materials in bulk; padding, cushioning and stuffing materials, (except of paper, cardboard, rubber or plastics); raw fibrous textile materials and substi- tutes therefor Class 23 – Yarns and threads, for textile use Class 24 – Textiles and substitutes for textiles; bed covers; table covers; household linen; curtains of textile or plastic Class 25 – Clothing, footwear, headgear Class 26 – Lace and embroidery, ribbons and braid; buttons, hooks and eyes, pins and needles; artificial flowers; hair decorations; false hair Class 27 – Carpets, rugs, mats and matting, li- noleum and other materials for covering existing floors; wall hangings (non-textile) Class 28 – Games, toys and playthings; video game apparatus; gymnastic and sporting articles; decorations for Christmas trees Class 29 – Meat, fish, poultry and game; meat ex- tracts; preserved, frozen, dried and cooked fruits and vegetables; jellies, jams, compotes; eggs; milk and milk products; edible oils and fats Class 30 – Coffee, tea, cocoa and artificial cof- fee; rice; tapioca and sago; flour and preparations made from cereals; bread, pastries and confec- tionery; edible ices; sugar, honey, treacle; yeast, baking-powder; salt; mustard; vinegar, sauces (condiments); spices; ice Class 31 – Raw and unprocessed agricultural, aq- uacultural, horticultural and forestry products; raw and unprocessed grains and seeds; fresh fruits and vegetables, fresh herbs; natural plants and flowers; bulbs, seedlings and seeds for planting; live animals; foodstuffs and beverages for ani- mals; malt Class 32 – Beers; mineral and aerated waters and other non-alcoholic beverages; fruit beverages and fruit juices; syrups and	[ "Leather", "and", "imitations", "of", "leather", ";", "ani-", "\n", "mal", "skins", ",", "and", "hides", ";", "trunks", "and", "travelling", "luggage", "\n", "and", "carrying", "bags", ";", "umbrellas", "and", "parasols", ";", "walk-", "\n", "ing", "sticks", ";", "whips", ",", "harness", "and", "saddlery", ";", "collars", ",", "\n", "leashes", "and", "clothing", "for", "animals", "\n", "Class", "19", "–", "Building", "materials", "(", "non", "-", "metallic", ")", ";", "\n", "non", "-", "metallic", "rigid", "pipes", "for", "building", ";", "asphalt", ",", "pitch", "\n", "and", "bitumen", ";", "non", "-", "metallic", "transportable", "buildings", ";", "\n", "monuments", ",", "not", "of", "metal", "\n", "Class", "20", "–", "Furniture", ",", "mirrors", ",", "picture", "frames", ";", "con-", "\n", "tainers", ",", "not", "of", "metal", ",", "for", "storage", "or", "transport", ";", "\n", "unworked", "or", "semi", "-", "worked", "bone", ",", "horn", ",", "ivory", ",", "whale-", "\n", "bone", "or", "mother", "-", "of", "-", "pearl", ";", "shells", ";", "meerschaum", ";", "yel-", "\n", "low", "amber", "\n", "Class", "21", "–", "Household", "or", "kitchen", "utensils", "and", "\n", "containers", ";", "combs", "and", "sponges", ";", "brushes", ",", "(", 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",", "horticultural", "and", "forestry", "products", ";", "raw", "\n", "and", "unprocessed", "grains", "and", "seeds", ";", "fresh", "fruits", "\n", "and", "vegetables", ",", "fresh", "herbs", ";", "natural", "plants", "and", "\n", "flowers", ";", "bulbs", ",", "seedlings", "and", "seeds", "for", "planting", ";", "\n", "live", "animals", ";", "foodstuffs", "and", "beverages", "for", "ani-", "\n", "mals", ";", "malt", "\n", "Class", "32", "–", "Beers", ";", "mineral", "and", "aerated", "waters", "and", "\n", "other", "non", "-", "alcoholic", "beverages", ";", "fruit", "beverages", "\n", "and", "fruit", "juices", ";", "syrups", "and" ]	[]
of ring-fencing rules is particularly relevant for developing countries that may lack the tools and infrastructure to detect such abusive arrangements. Note: Such a structure is also possible directly between the related Companies A and B in the absence of Investment Bank Z. ## 1.0 INTRODUCTION 2.0 THE FUNDAMENTALS OF RING-FENCING ## 3.0 THE BENEFITS AND RISKS OF RING-FENCING 4.0 DESIGNING RING-FENCING RULES 5.0 THE IMPLEMENTATION OF RING-FENCING RULES 6.0 CONCLUSION Such BEPS practices also result in permanent revenue losses for the host government. Where the costs or losses resulting from such BEPS practices are ring-fenced from the mining tax base, the ring-fencing rules can contribute to protecting the tax base from permanent revenue losses. While aggressive tax planning could be dealt with more effectively by (a) introducing general anti-avoidance measures, and/or (b) improving the capability of tax administrations to detect and mitigate BEPS practices generally, the reality is that these two conditions are not always in place in developing countries. Ring-fencing can be considered a temporary measure in such circumstances. ## 3.1.2.4 The Overstatement of Exploration and Development Expenditures The consolidation of revenues and expenditures between projects held by one mining investor can increase the risk of companies inflating their exploration and mine development expenditures, which may not be audited at all (due to limited capacities and statute of limitation rules) or are audited only once the mine starts production and often receive preferential tax treatment, such as accelerated depreciation or investment allowances/tax credits, to lower their overall tax burden on profit-making operations. 15 This is particularly common in jurisdictions with weak monitoring capacity. The overstatement of expenditures raises the need for additional financing and, thus, associated costs, such as interest deductions, where the investor uses debt to finance the additional 'overstated' costs. Such additional debt financing is often provided by related parties, which has a further negative effect on the tax base-in addition to the overstated costs-because there is an additional deduction of the financing costs in relation to the related-party debt financing. Ring-fencing may reduce this risk by limiting the consolidation of revenues with losses derived from exploration or development areas. BEPS practices may need to be resolved through the full suite of transfer pricing rules and other measures. However, the effect of ring-fencing may, to some extent, discourage such practices. This is especially true where both the overstated expenses and the financing costs are allocated to	[ "of", "ring", "-", "fencing", "rules", "is", "particularly", "relevant", "for", "developing", "countries", "that", "may", "lack", "the", "tools", "and", "infrastructure", "to", "detect", "such", "abusive", "arrangements", ".", "\n\n", "Note", ":", "Such", "a", "structure", "is", "also", "possible", "directly", "between", "the", "related", "Companies", "A", "and", "B", "in", "the", "absence", "of", "Investment", "Bank", "Z.", "\n\n", "#", "#", "1.0", "INTRODUCTION", "\n\n", "2.0", "THE", "FUNDAMENTALS", "OF", "RING", "-", "FENCING", "\n\n", "#", "#", "3.0", "THE", "BENEFITS", "AND", "RISKS", "OF", "RING", "-", "FENCING", "\n\n", "4.0", "DESIGNING", "RING", "-", "FENCING", "RULES", "\n\n", "5.0", "THE", "IMPLEMENTATION", "OF", "RING", "-", "FENCING", "RULES", "\n\n", "6.0", "CONCLUSION", "\n\n", "Such", "BEPS", "practices", "also", "result", "in", "permanent", "revenue", "losses", "for", "the", "host", "government", ".", "Where", "the", "costs", "or", "losses", "resulting", "from", "such", "BEPS", "practices", "are", "ring", "-", "fenced", "from", "the", "mining", "tax", "base", ",", "the", "ring", "-", "fencing", "rules", "can", "contribute", "to", "protecting", "the", "tax", "base", "from", "permanent", "revenue", "losses", ".", "\n\n", "While", "aggressive", "tax", "planning", "could", "be", "dealt", "with", "more", "effectively", "by", "(", "a", ")", "introducing", "general", "anti", "-", "avoidance", "measures", ",", "and/or", "(", "b", ")", "improving", "the", "capability", "of", "tax", "administrations", "to", "detect", "and", "mitigate", "BEPS", "practices", "generally", ",", "the", "reality", "is", "that", "these", "two", "conditions", "are", "not", "always", "in", "place", "in", "developing", "countries", ".", "Ring", "-", "fencing", "can", "be", "considered", "a", "temporary", "measure", "in", "such", "circumstances", ".", "\n\n", "#", "#", "3.1.2.4", "The", "Overstatement", "of", "Exploration", "and", "Development", "Expenditures", "\n\n", "The", "consolidation", "of", "revenues", "and", "expenditures", "between", "projects", "held", "by", "one", "mining", "investor", "can", "increase", "the", "risk", "of", "companies", "inflating", "their", "exploration", "and", "mine", "development", "expenditures", ",", "which", "may", "not", "be", "audited", "at", "all", "(", "due", "to", "limited", "capacities", "and", "statute", "of", "limitation", "rules", ")", "or", "are", "audited", "only", "once", "the", "mine", "starts", "production", "and", "often", "receive", "preferential", "tax", "treatment", ",", "such", "as", "accelerated", "depreciation", "or", "investment", "allowances", "/", "tax", "credits", ",", "to", "lower", "their", "overall", "tax", "burden", "on", "profit", "-", "making", "operations", ".", "15", " ", "This", "is", "particularly", "common", "in", "jurisdictions", "with", "weak", "monitoring", "capacity", ".", "\n\n", "The", "overstatement", "of", "expenditures", "raises", "the", "need", "for", "additional", "financing", "and", ",", "thus", ",", "associated", "costs", ",", "such", "as", "interest", "deductions", ",", "where", "the", "investor", "uses", "debt", "to", "finance", "the", "additional", "'", "overstated", "'", "costs", ".", "Such", "additional", "debt", "financing", "is", "often", "provided", "by", "related", "parties", ",", "which", "has", "a", "further", "negative", "effect", "on", "the", "tax", "base", "-", "in", "addition", "to", "the", "overstated", "costs", "-", "because", "there", "is", "an", "additional", "deduction", "of", "the", "financing", "costs", "in", "relation", "to", "the", "related", "-", "party", "debt", "financing", ".", "Ring", "-", "fencing", "may", "reduce", "this", "risk", "by", "limiting", "the", "consolidation", "of", "revenues", "with", "losses", "derived", "from", "exploration", "or", "development", "areas", ".", "\n\n", "BEPS", "practices", "may", "need", "to", "be", "resolved", "through", "the", "full", "suite", "of", "transfer", "pricing", "rules", "and", "other", "measures", ".", "However", ",", "the", "effect", "of", "ring", "-", "fencing", "may", ",", "to", "some", "extent", ",", "discourage", "such", "practices", ".", "This", "is", "especially", "true", "where", "both", "the", "overstated", "expenses", "and", "the", "financing", "costs", "are", "allocated", "to" ]	[]
the contribu - tions in this section show that the examination of personal and professional networks in science and their role in rendering women more visible cannot be separated from an examination of the broader political context in which their lives and careers unfolded. In/ visibilities in medicine and care: Treating, teaching, reforming As in the case of science and engineering, some of the chapters in this volume also provide an opportunity for comparative study between different areas 20 Negotiating in/visibility of medicine. Medicine and care have been among the most examined sites of science in relation to gender, education and women’s work, but the papers in this section suggest new avenues of investigation. They focus in particular on neglected arenas like women’s work as doctors and educators in second - ary schools in Romania, women physicians’ role in training midwives in Republican China and attempts made by female cadres, researchers, doctors and medical students to alleviate ‘women’s illnesses’ and promote ‘grassroot science’ in Maoist China. These chapters highlight often- overlooked insti - tutional contexts, ranging from secondary schools to rural health stations, and examine how political events, such as World War I and the Great Leap Famine,54 both expanded and constrained the range of opportunities avail - able to female physicians and scientists. Camelia Zavarache’s contribution addresses the importance of politi - cal change, border reconfiguration and state- building in the appointment of women as doctors in secondary- school education in interwar Romania, a time when the country significantly expanded its territory and minority population.55 Zavarache argues that the state’s agenda of providing hygiene education to secondary- school students was intertwined with the aim of producing a healthy ‘body’ for the Romanian nation. This played a crucial role in allowing women access to positions as school doctors, especially after the passing of the 1928 Law on Secondary Education which stipu - lated that female doctors should be employed to teach hygiene courses and conduct medical examinations in girls’ schools. Although the socio- political and economic circumstances that followed World War I created a situation that helped render women more visible both as health professionals and ‘modernising agents’ of the new, enlarged Romanian state, Zavarache dem - onstrates that women often had to fight for the school positions they were legally entitled to. Using archival documents which have been largely neglected in Romanian historiography, especially correspondence between women doctors and	[ "the", "contribu", "-", "\n", "tions", "in", "this", "section", "show", "that", "the", "examination", "of", "personal", "and", "professional", "\n", "networks", "in", "science", "and", "their", "role", "in", "rendering", "women", "more", "visible", "can", "not", "\n", "be", "separated", "from", "an", "examination", "of", "the", "broader", "political", "context", "in", "which", "\n", "their", "lives", "and", "careers", "unfolded", ".", "\n", "In/", "visibilities", "in", "medicine", "and", "care", ":", "Treating", ",", "teaching", ",", "reforming", "\n", "As", "in", "the", "case", "of", "science", "and", "engineering", ",", "some", "of", "the", "chapters", "in", "this", "volume", "\n", "also", "provide", "an", "opportunity", "for", "comparative", "study", "between", "different", "areas", " \n", "20", "\n ", "Negotiating", "in", "/", "visibility", "\n", "of", "medicine", ".", "Medicine", "and", "care", "have", "been", "among", "the", "most", "examined", "sites", "of", "\n", "science", "in", "relation", "to", "gender", ",", "education", "and", "women", "’s", "work", ",", "but", "the", "papers", "\n", "in", "this", "section", "suggest", "new", "avenues", "of", "investigation", ".", "They", "focus", "in", "particular", "\n", "on", "neglected", "arenas", "like", "women", "’s", "work", "as", "doctors", "and", "educators", "in", "second", "-", "\n", "ary", "schools", "in", "Romania", ",", "women", "physicians", "’", "role", "in", "training", "midwives", "in", "\n", "Republican", "China", "and", "attempts", "made", "by", "female", "cadres", ",", "researchers", ",", "doctors", "\n", "and", "medical", "students", "to", "alleviate", "‘", "women", "’s", "illnesses", "’", "and", "promote", "‘", "grassroot", "\n", "science", "’", "in", "Maoist", "China", ".", "These", "chapters", "highlight", "often-", " ", "overlooked", "insti", "-", "\n", "tutional", "contexts", ",", "ranging", "from", "secondary", "schools", "to", "rural", "health", "stations", ",", "\n", "and", "examine", "how", "political", "events", ",", "such", "as", "World", "War", "I", "and", "the", "Great", "Leap", "\n", "Famine,54", "both", "expanded", "and", "constrained", "the", "range", "of", "opportunities", "avail", "-", "\n", "able", "to", "female", "physicians", "and", "scientists", ".", "\n", "Camelia", "Zavarache", "’s", "contribution", "addresses", "the", "importance", "of", "politi", "-", "\n", "cal", "change", ",", "border", "reconfiguration", "and", "state-", " ", "building", "in", "the", "appointment", "\n", "of", "women", "as", "doctors", "in", "secondary-", " ", "school", "education", "in", "interwar", "Romania", ",", "\n", "a", "time", "when", "the", "country", "significantly", "expanded", "its", "territory", "and", "minority", "\n", "population.55", "Zavarache", "argues", "that", "the", "state", "’s", "agenda", "of", "providing", "hygiene", "\n", "education", "to", "secondary-", " ", "school", "students", "was", "intertwined", "with", "the", "aim", "of", "\n", "producing", "a", "healthy", "‘", "body", "’", "for", "the", "Romanian", "nation", ".", "This", "played", "a", "crucial", "\n", "role", "in", "allowing", "women", "access", "to", "positions", "as", "school", "doctors", ",", "especially", "\n", "after", "the", "passing", "of", "the", "1928", "Law", "on", "Secondary", "Education", "which", "stipu", "-", "\n", "lated", "that", "female", "doctors", "should", "be", "employed", "to", "teach", "hygiene", "courses", "and", "\n", "conduct", "medical", "examinations", "in", "girls", "’", "schools", ".", "Although", "the", "socio-", " ", "political", "\n", "and", "economic", "circumstances", "that", "followed", "World", "War", "I", "created", "a", "situation", "\n", "that", "helped", "render", "women", "more", "visible", "both", "as", "health", "professionals", "and", "\n", "‘", "modernising", "agents", "’", "of", "the", "new", ",", "enlarged", "Romanian", "state", ",", "Zavarache", "dem", "-", "\n", "onstrates", "that", "women", "often", "had", "to", "fight", "for", "the", "school", "positions", "they", "were", "\n", "legally", "entitled", "to", ".", "\n", "Using", "archival", "documents", "which", "have", "been", "largely", "neglected", "in", "Romanian", "\n", "historiography", ",", "especially", "correspondence", "between", "women", " ", "doctors", "and", "\n" ]	[ { "end": 1301, "label": "CITATION_REF", "start": 1299 }, { "end": 1717, "label": "CITATION_REF", "start": 1715 } ]
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Huygens, D., Foschi, J., Caro, D., Caldeira, C., Faraca, G., Foster, G., Solis, M., Marschinski, R., Napolano, L., Fruergaard Astrup, T. and Tonini, D., Techno -scientific assessment of the management options for used and waste textiles in the European Union . Publications Office of the European Union, Luxembourg, JRC134586, 2023. https://publications.jrc.ec.europa.eu/repository/handle/JRC134586 ISO (International Standard Organization), ISO 14040 - environmental management - life cycle assessment - principles and framework , 2006. ISO (International Standard Organization), ISO 14044 - environmental management - life cycle assessment - requirements and guidelines , 2006. Kawecki, D., and B. Nowack, Polymer -Specific Modeling of the Environmental Emissions of Seven Commodity Plastics As Macro - and Microplastics , Environmental Science and Technology, Vol. 53, No. 16, pp. 9664 –9676, 2019. https://pubs.acs.org/doi/abs/10.1021/acs.est.9b02900 Kaza, S ., Yao, L . C., Bhada -Tata, P., Van Woerden, F . What a Waste 2.0: A Global Snapshot of Solid Waste Management to 2050 . Urban Development . World Bank. 2018. http://hdl.handle.net/10986/30317 Kounina, A., Daystar, J., Chalumeau, S., Devine, J., Geyer, R., Pires, T.S., Uday Sonar, S., Venditti, R.A., and Boucher, J., The global apparel industry is a significant yet overlooked source of plastic leakage . nature communications, 15 -5022, 2024. https://doi.org/10.1038/s41467 -024-49441 -4 Lase , I. S., 2023. Modeling material flows through plastic recycling chains . Ghent University. https://biblio.ugent.be/publication/01HG0M47FPW1MXCKKWDAT8099Q (accessed June 2024). Linder, C., Schmitt, J., Fischer, E., Hein J., Stoffstrombild Kunststoffe in Deutschland 2021: Zahlen und Fakten zum Lebensweg von Kunststoffen , Conversio Market & Strategy GmbH, 2021. https://plasticseurope.org/de/wp - content/uploads/sites/3/2022/11/Kurzfassung_Stoffstrombild_2021.pdf (accessed January 2025) .	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about the health and well-being of present and future generations, the responsible thing will be not to settle for a worst-case scenario, but to provide Gavi with what it needs. “For us, Gavi is a game changer,” Kaseya says. Nature 643 , 880 (2025) doi: https://doi.org/10.1038/d41586-025-02270-x Reprints and permissions Related Articles Vaccines save lives. Leaders must champion them Will RFK Jr’s vaccine agenda make America contagious again? Vaccine sceptic RFK Jr is now a powerful force in US science: what will he do? 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Hangzhou, Zhejiang, China Westlake University Chemistry Faculty Positions at Westlake University Multiple positions are open at all ranks. Hangzhou, Zhejiang, China Westlake University Global Talent Recruitment-Hospital of Stomatology Xi’an Jiaotong University Leading Talent, Excellent Young Scholars (Overseas), Young Top Talents, Postdoctoral Fellow Xi'an, Shaanxi (CN) Hospital of Stomatology Xi’an Jiaotong University Principal Investigators in Population Health Data Science (2 positions) The Lunenfeld-Tanenbaum Research Institute, a leading research institute in Toronto, is seeking emerging leaders in Population Health Data Science. Toronto, Ontario, Canada Lunenfeld-Tanenbaum Research Institute Principal Investigators in Biomedical Discovery Research (2 positions) The Lunenfeld-Tanenbaum Research Institute is recruiting emerging leaders in Systems, Cellular, Chemical, Molecular and Musculoskeletal	[ "about", "the", "health", "and", "well", "-", "being", "of", "present", "and", "future", "generations", ",", "the", "responsible", "thing", "will", "be", "not", "to", "settle", "for", "a", "worst", "-", "case", "scenario", ",", "but", "to", "provide", "Gavi", "with", "what", "it", "needs", ".", "“", "For", "us", ",", "Gavi", "is", "a", "game", "changer", ",", "”", "Kaseya", "says", ".", "\n\n\n\n\n", "Nature", "\n \n", "643", "\n", ",", "880", "(", "2025", ")", "\n\n\n", "doi", ":", "https://doi.org/10.1038/d41586-025-02270-x", "\n\n\n\n\n\n\n\n\n", "Reprints", "and", "permissions", "\n\n\n\n\n", "Related", "Articles", "\n\n\n\n\n\n\n\n\n\n\n\n \n ", "Vaccines", "save", "lives", ".", "Leaders", "must", "champion", 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Guet-Mccreight, A., Skinner, F.K., and Topolnik, L. (2020). Common principles in functional organization of vip/calretinin cell-driven disinhibitory circuits across cortical areas. Front. Neural Circuits 14 . https://doi.org/10.3389/fncir. 2020.00032. Hangya, B., Ranade, S.P., Lorenc, M., and Kepecs, A. (2015). Central cholinergic neurons are rapidly recruited by reinforcement feedback. Cell 162 , 11551168. https://doi.org/10.1016/j.cell.2015.07.057. He, M., Tucciarone, J., Lee, S., Nigro, M.J., Kim, Y., Levine, J.M., Kelly, S.M., Krugikov, I., Wu, P., Chen, Y., et al. (2016). Strategies and tools for combinatorial targeting of gabaergic neurons in mouse cerebral cortex. Neuron 91 , 1228-1243. https://doi.org/10.1016/j.neuron.2016.08.021. <!-- image --> Henson, R.N., and Rugg, M.D. (2003). Neural response suppression, haemodynamic repetition effects, and behavioural priming. Neuropsychologia 41 , 263-270. https://doi.org/10.1016/s0028-3932(02)00159-8. Hersman, S., Allen, D., Hashimoto, M., Brito, S.I., and Anthony, T.E. (2020). Stimulus salience determines defensive behaviors elicited by aversively conditioned serial compound auditory stimuli. Elife 9 . https://doi.org/10.7554/elife. 53803. Holland, P.C. (1980). Influence of visual conditioned stimulus characteristics on the form of pavlovian appetitive conditioned responding in rats. J. Exp. Psychol. Anim. Behav. Process. 6 , 81-97. https://doi.org/10.1037/0097-7403.6.1. 81. Ishai, A., Pessoa, L., Bikle, P.C., and Ungerleider, L.G. (2004). Repetition suppression of faces is modulated by emotion. Proc. Natl. Acad. Sci. U S A 101 , 9827-9832. https://doi.org/10.1073/pnas.0403559101. Kapur, S. (2003). Psychosis as A state of aberrant salience: a framework linking biology, phenomenology, and pharmacology in schizophrenia. Am. J. Psychiatry 160 , 13-23. https://doi.org/10.1176/appi.ajp.160.1.13. Kastli, R., Vighagen, R., Van Der Bourg, A., Argunsah, A.O., Iqbal, A., Voigt, ¨ F.F., Kirschenbaum, D., Aguzzi, A., Helmchen, F., and Karayannis, T. (2020). Developmental divergence of sensory stimulus representation in cortical interneurons. Nat. Commun. 11 , 5729. https://doi.org/10.1038/s41467-02019427-z. Keller, A.J., Dipoppa, M., Roth, M.M., Caudill, M.S., Ingrosso, A., Miller, K.D., and Scanziani, M. (2020). A disinhibitory circuit for contextual modulation in primary visual cortex. Neuron 108 , 1181-1193.e8. https://doi.org/10.1016/j. neuron.2020.11.013. Kim, H., Ahrlund-Richter, S., Wang, X., Deisseroth, K., and Carle ´ n, M. (2016). ¨ Prefrontal parvalbumin neurons in control of attention. Cell 164 , 208-218. https://doi.org/10.1016/j.cell.2015.11.038. Kim, I.H., Kim, N., Kim, S., Toda, K., Catavero, C.M., Courtland, J.L., Yin, H.H., and Soderling, S.H. (2020). Dysregulation of the synaptic cytoskeleton in the pfc drives neural circuit pathology, leading to social dysfunction. Cell Rep. 32 , 107965. https://doi.org/10.1016/j.celrep.2020.107965. Krabbe, S., Grundemann, J., and Luthi, A. (2018). Amygdala inhibitory circuits € € regulate associative fear conditioning. Biol. Psychiatry 83 , 800-809. https:// doi.org/10.1016/j.biopsych.2017.10.006. Krabbe, S., Paradiso, E., D'aquin, S., Bitterman, Y., Courtin, J., Xu, C., Yonehara, K., Markovic, M., Muller, C., Eichlisberger, T., et al. (2019). Adaptive dis-€ inhibitory gating by vip interneurons permits associative learning. Nat. Neurosci. 22 , 1834-1843. https://doi.org/10.1038/s41593-019-0508-y.	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may be based on a device fingerprint of the and/or some other device or system in the MRF. Additionally or alternatively, the UID may be based on any other type of identifier and/or network address, such as any of those discussed herein. Any of the aforementioned examples may be combined. In any of the aforementioned examples, the AI/ML system(s) include one or more optimizers that perform the multi-objective optimization according. The optimizers are based on one or more objective functions or multi-objective function(s), which include an optimization problem involving more than one objective function to be either minimized or maximized. The optimizers may define a multi-objective optimization model that comprises one or more decision variables, objectives, and constraints. The decision variables are variables that represent decisions to be made, and the objectives are the measures to be optimized. The constraints define restrictions on feasible solutions (including all optimal solutions) that must be satisfied, and/or restrictions on the values the decision variables may hold. One example of the decision variables includes prioritized or otherwise desired materials to be recovered from the material stream. The objective functions indicate how much each of their decision variables contributes to the objectives to be optimized. The multi-objective optimization model may also define one or more coefficients corresponding to one or more of the decision variables. The coefficients indicate the contribution of the corresponding decision variable to the value of the objective function. The optimal solutions in multi-objective optimization can be defined from a mathematical concept of partial ordering. The term domination is used for this purpose in the parlance of multi-objective optimization. A first solution is said to dominate a second solution if both of the following conditions are true: (1) the first solution is no worse than the second solution in all objectives, and (2) the first solution is strictly better than the second solution in at least one objective. For a given set of solutions, a pair-wise comparison can be made using a graphical representation and a determination as to whether one point in the graph dominates the other can be established. All points that are not dominated by any other member of the set are called “non-dominated points” or “non-dominated solutions”. The Pareto frontier comprises a set of non-dominated points in such a graphical representation. Here, the AI/ML system(s) solves the multi-objective function(s) to optimize a number of objectives simultaneously, where the	[ "may", "be", "based", "on", "a", "device", "fingerprint", "of", "the", " ", "and/or", "some", "other", "device", "or", "system", "in", "the", "MRF", ".", "Additionally", "or", "alternatively", ",", "the", "UID", "may", "be", "based", "on", "any", "other", "type", "of", "identifier", "and/or", "network", "address", ",", "such", "as", "any", "of", "those", "discussed", "herein", ".", "Any", "of", "the", "aforementioned", "examples", "may", "be", "combined", ".", "\n\n", "In", "any", "of", "the", "aforementioned", "examples", ",", "the", "AI", "/", "ML", "system(s", ")", " ", "include", "one", "or", "more", "optimizers", "that", "perform", "the", "multi", "-", "objective", "optimization", "according", ".", "The", "optimizers", "are", "based", "on", "one", "or", "more", "objective", "functions", "or", "multi", "-", "objective", "function(s", ")", ",", "which", "include", "an", "optimization", "problem", "involving", "more", "than", "one", "objective", "function", "to", "be", "either", "minimized", "or", "maximized", ".", "The", "optimizers", "may", "define", "a", "multi", "-", "objective", "optimization", "model", "that", "comprises", "one", "or", "more", "decision", "variables", ",", "objectives", ",", "and", "constraints", ".", "The", "decision", "variables", "are", "variables", "that", "represent", "decisions", "to", "be", "made", ",", "and", "the", "objectives", "are", "the", "measures", "to", "be", "optimized", ".", "The", "constraints", "define", "restrictions", "on", "feasible", "solutions", "(", "including", "all", "optimal", "solutions", ")", "that", "must", "be", "satisfied", ",", "and/or", "restrictions", "on", "the", "values", "the", "decision", "variables", "may", "hold", ".", "One", "example", "of", "the", "decision", "variables", "includes", "prioritized", "or", "otherwise", "desired", "materials", "to", "be", "recovered", "from", "the", "material", "stream", ".", "The", "objective", "functions", "indicate", "how", "much", "each", "of", "their", "decision", "variables", "contributes", "to", "the", "objectives", "to", "be", "optimized", ".", "The", "multi", "-", "objective", "optimization", "model", "may", "also", "define", "one", "or", "more", "coefficients", "corresponding", "to", "one", "or", "more", "of", "the", "decision", "variables", ".", "The", "coefficients", "indicate", "the", "contribution", "of", "the", "corresponding", "decision", "variable", "to", "the", "value", "of", "the", "objective", "function", ".", "The", "optimal", "solutions", "in", "multi", "-", "objective", "optimization", "can", "be", "defined", "from", "a", "mathematical", "concept", "of", "partial", "ordering", ".", "The", "term", "domination", "is", "used", "for", "this", "purpose", "in", "the", "parlance", "of", "multi", "-", "objective", "optimization", ".", "A", "first", "solution", "is", "said", "to", "dominate", "a", "second", "solution", "if", "both", "of", "the", "following", "conditions", "are", "true", ":", "(", "1", ")", "the", "first", "solution", "is", "no", "worse", "than", "the", "second", "solution", "in", "all", "objectives", ",", "and", "(", "2", ")", "the", "first", "solution", "is", "strictly", "better", "than", "the", "second", "solution", "in", "at", "least", "one", "objective", ".", "For", "a", "given", "set", "of", "solutions", ",", "a", "pair", "-", "wise", "comparison", "can", "be", "made", "using", "a", "graphical", "representation", "and", "a", "determination", "as", "to", "whether", "one", "point", "in", "the", "graph", "dominates", "the", "other", "can", "be", "established", ".", "All", "points", "that", "are", "not", "dominated", "by", "any", "other", "member", "of", "the", "set", "are", "called", "“", "non", "-", "dominated", "points", "”", "or", "“", "non", "-", "dominated", "solutions", "”", ".", "The", "Pareto", "frontier", "comprises", "a", "set", "of", "non", "-", "dominated", "points", "in", "such", "a", "graphical", "representation", ".", "Here", ",", "the", "AI", "/", "ML", "system(s", ")", " ", "solves", "the", "multi", "-", "objective", "function(s", ")", "to", "optimize", "a", "number", "of", "objectives", "simultaneously", ",", "where", "the" ]	[]
objective function's decision variables are often changed or manipulated within the bounds of the constraints to improve the objective function's values. In general, the difficulty in solving an objective function increases as the number of decision variables included in that objective function increases. - the term “decision variable” refers to a variable that represents a decision to be made. - optimization at least in some examples refers to an act, process, or methodology of making something (e.g., a design, system, or decision) as fully perfect, functional, or effective as possible. Optimization usually includes mathematical procedures such as finding the maximum or minimum of a function. - the term “optimal” at least in some examples refers to a most desirable or satisfactory end, outcome, or output. - the term “optimum” at least in some examples refers to an amount or degree of something that is most favorable to some end. - opticalma at least in some examples refers to a condition, degree, amount, or compromise that produces a best possible result. Additionally or alternatively, the term “optima” at least in some examples refers to a most favorable or advantageous outcome or result. - probability at least in some examples refers to a numerical description of how likely an event is to occur and/or how likely it is that a proposition is true. - probability distribution at least in some examples refers to a mathematical function that gives the probabilities of occurrence of different possible outcomes for an experiment or event. Additionally or alternatively, the term “probability distribution” at least in some examples refers to a statistical function that describes all possible values and likelihoods that a random variable can take within a given range (e.g., a bound between minimum and maximum possible values). - a probability distribution may have one or more factors or attributes such as, for example, a mean or average, mode, support, tail, head, median, variance, standard deviation, quantile, symmetry, skewness, kurtosis, and the like. - a probability distribution may be a description of a random phenomenon in terms of a sample space and the probabilities of events (subsets of the sample space). - Example probability distributions include discrete distributions (e.g., Bernoulli distribution, discrete uniform, binomial, Dirac measure, Gauss-Kuzmin distribution, geometric, hypergeometric, negative binomial, negative hypergeometric, Poisson, Poisson binomial, Rademacher distribution, Yule-Simon distribution, zeta distribution, Zipf distribution, and the like), continuous distributions (e.g., Bates distribution, beta, continuous uniform,	[ "objective", "function", "'s", "decision", "variables", "\n", "are", "often", "changed", "or", "manipulated", "within", "the", "bounds", "of", "the", "constraints", "to", "improve", "the", "objective", "function", "'s", "values", ".", "In", "general", ",", "the", "difficulty", "in", "solving", "an", "objective", "function", "increases", "as", "the", "number", "of", "decision", "variables", "included", "in", "that", "objective", "function", "increases", ".", "\n", "-", "the", "term", "“", "decision", "variable", "”", "\n", "refers", "to", "a", "variable", "that", "represents", "a", "decision", "to", "be", "made", ".", "\n", "-", "optimization", "\n", "at", "least", "in", "some", "examples", "refers", "to", "an", "act", ",", "process", ",", "or", "methodology", "of", "making", "something", "(", "e.g.", ",", "a", "design", ",", "system", ",", 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George VI and Queen Elizabeth The Queen Mother. Princess Margaret, Countess of Snowdon. (Margaret Rose 21 August 1930 - 9 February 2002) was the eldest daughter of Queen Elizabeth The Queen Mother. (Margaret Rose 21 August 1930 - 9 February 2002) was the oldest child of King George VI and Queen Elizabeth \| Bulger was one of the FBI's most wanted fugitives for 16 years until he was captured in Santa Monica, California, in 2011. He was convicted in 2013 of a litany of crimes, including racketeering, extortion, money-laundering, and murder. He was sentenced to two consecutive life sentences plus five years. He died in federal prison in West Virginia on Tuesday at the age of 89. Bulger was one of the FBI's most wanted fugitives for 16 years before he was captured in Santa Monica, California, in 2011. \|	[ "George", "VI", "and", "Queen", "Elizabeth", "The", "Queen", "Mother", ".", "Princess", "Margaret", ",", "Countess", "of", "Snowdon", ".", "(", "Margaret", "Rose", "21", "August", "1930", "-", "9", "February", "2002", ")", "was", "the", "eldest", "daughter", "of", "Queen", "Elizabeth", "The", "Queen", "Mother", ".", "(", "Margaret", "Rose", "21", "August", "1930", "-", "9", "February", "2002", ")", "was", "the", "oldest", "child", "of", "King", "George", "VI", "and", "Queen", "Elizabeth", " ", "\|", "Bulger", "was", "one", "of", "the", "FBI", "'s", "most", "wanted", "fugitives", "for", "16", "years", "until", "he", "was", "captured", "in", "Santa", "Monica", ",", "California", ",", "in", "2011", ".", "He", "was", "convicted", "in", "2013", "of", "a", "litany", "of", "crimes", ",", "including", "racketeering", ",", "extortion", ",", "money", "-", "laundering", ",", "and", "murder", ".", "He", "was", "sentenced", "to", "two", "consecutive", "life", "sentences", "plus", "five", "years", ".", "He", "died", "in", "federal", "prison", "in", "West", "Virginia", "on", "Tuesday", "at", "the", "age", "of", "89", ".", "Bulger", "was", "one", "of", "the", "FBI", "'s", "most", "wanted", "fugitives", "for", "16", "years", "before", "he", "was", "captured", "in", "Santa", "Monica", ",", "California", ",", "in", "2011", ".", "\|" ]	[]
up from 20% in 2021. LNG prices are typically higher than pipeline gas on spot markets owing to liquification and transportation costs. Moreover, with the reduction of pipeline supply from Russia, more gas is being bought on LNG spot markets both in the EU and globally leading to stronger competition. Even gas bought in long-term contracts is largely indexed to spot markets, which are increasingly influenced by supply disruptions and demand patterns in Asia. Financial and behavioural aspects of gas derivative markets can exacerbate this volatility and amplify the impact of shocks . A few non-financial corporates undertake most trading activity in European gas markets. Recent evidence presented by the European Securities Markets Agency (ESMA) suggests that there is significant concen - tration both at position and trading venue level and that concentration increased in 2022 during largest spike in natural gas prices. The top 5 companies hold around 60% of positions in some trading venues and their short positions increased considerably by almost 200% between February and November 2022 [see Figure 4]vii. Super - vision of these companies’ activities could be improved. While regulated financial entities (for example, investment banks, investment funds and clearing market participants) are covered by conduct and prudential rules, many of the companies that trade commodity derivatives can rely on exemptions. In particular, when a commodity compa - ny’s main activities are not trading, they can be exempted from authorisation as a supervised investment company (so-called “ancillary” exemptions). The US has a stricter approach. Exemptions apply on some types of contracts, but commodity companies are not exempted from supervision, allowing for a more precise level of scrutiny. In addition, energy commodities are subject to position limits, including Henry Hub natural gas contracts. 01. AggregateEU is a first step in demand aggregation allowing the pooling of demand, the coordination of infrastructure use and negotiation with international partners, fostering more centralised EU joint purchasing to further leverage the EU’s market power. 43THE FUTURE OF EUROPEAN COMPETITIVENESS — PART A \| CHAPTER 3FIGURE 4 Market concentration in EU gas derivatives markets Europe’s market rules pass on this volatility to end users and may prevent the full benefits of decarbonising power generation from reaching them . Even as Europe reduces its dependence on natural gas and increases investment in clean energy generation, its market rules in the power sector do not fully decouple the price of renew - able	[ "up", "from", "20", "%", "in", "2021", ".", "LNG", "prices", "are", "typically", "higher", "than", "pipeline", "gas", "on", "spot", "markets", "owing", "\n", "to", "liquification", "and", "transportation", "costs", ".", "Moreover", ",", "with", "the", "reduction", "of", "pipeline", "supply", "from", "Russia", ",", "more", "gas", "is", "\n", "being", "bought", "on", "LNG", "spot", "markets", "both", "in", "the", "EU", "and", "globally", "leading", "to", "stronger", "competition", ".", "Even", "gas", "bought", "\n", "in", "long", "-", "term", "contracts", "is", "largely", "indexed", "to", "spot", "markets", ",", "which", "are", "increasingly", "influenced", "by", "supply", "disruptions", "\n", "and", "demand", "patterns", "in", "Asia", ".", "\n", "Financial", "and", "behavioural", "aspects", "of", "gas", "derivative", "markets", "can", "exacerbate", "this", "volatility", "and", "amplify", "the", "\n", "impact", "of", "shocks", ".", "A", "few", "non", "-", "financial", "corporates", "undertake", "most", "trading", "activity", "in", "European", "gas", "markets", ".", "Recent", "\n", "evidence", "presented", "by", "the", "European", "Securities", "Markets", "Agency", "(", "ESMA", ")", "suggests", "that", "there", "is", "significant", "concen", "-", "\n", "tration", "both", "at", "position", "and", "trading", "venue", "level", "and", "that", "concentration", "increased", "in", "2022", "during", "largest", "spike", "\n", "in", "natural", "gas", "prices", ".", "The", "top", "5", "companies", "hold", "around", "60", "%", "of", "positions", "in", "some", "trading", "venues", "and", "their", "short", "\n", "positions", "increased", "considerably", "by", "almost", "200", "%", "between", "February", "and", "November", "2022", "[", "see", "Figure", "4]vii", ".", "Super", "-", "\n", "vision", "of", "these", "companies", "’", "activities", "could", "be", "improved", ".", "While", "regulated", "financial", "entities", "(", "for", "example", ",", "investment", "\n", "banks", ",", "investment", "funds", "and", "clearing", "market", "participants", ")", "are", "covered", "by", "conduct", "and", "prudential", "rules", ",", "many", "of", "\n", "the", "companies", "that", "trade", "commodity", "derivatives", "can", "rely", "on", "exemptions", ".", "In", "particular", ",", "when", "a", "commodity", "compa", "-", "\n", "ny", "’s", "main", "activities", "are", "not", "trading", ",", "they", "can", "be", "exempted", "from", "authorisation", "as", "a", "supervised", "investment", "company", "\n", "(", "so", "-", "called", "“", "ancillary", "”", "exemptions", ")", ".", "The", "US", "has", "a", "stricter", "approach", ".", "Exemptions", "apply", "on", "some", "types", "of", "contracts", ",", "but", "\n", "commodity", "companies", "are", "not", "exempted", "from", "supervision", ",", "allowing", "for", "a", "more", "precise", "level", "of", "scrutiny", ".", " ", "In", "addition", ",", "\n", "energy", "commodities", "are", "subject", "to", "position", "limits", ",", "including", "Henry", "Hub", "natural", "gas", "contracts", ".", "\n", "01", ".", "AggregateEU", "is", "a", "first", "step", "in", "demand", "aggregation", "allowing", "the", "pooling", "of", "demand", ",", "the", "coordination", "of", "infrastructure", "use", "and", "\n", "negotiation", "with", "international", "partners", ",", "fostering", "more", "centralised", "EU", "joint", "purchasing", "to", "further", "leverage", "the", "EU", "’s", "market", "power", ".", "\n", "43THE", "FUTURE", "OF", "EUROPEAN", "COMPETITIVENESS", " ", "—", "PART", "A", "\|", "CHAPTER", "3FIGURE", "4", "\n", "Market", "concentration", "in", "EU", "gas", "derivatives", "markets", "\n", "Europe", "’s", "market", "rules", "pass", "on", "this", "volatility", "to", "end", "users", "and", "may", "prevent", "the", "full", "benefits", "of", "decarbonising", "\n", "power", "generation", "from", "reaching", "them", ".", "Even", "as", "Europe", "reduces", "its", "dependence", "on", "natural", "gas", "and", "increases", "\n", "investment", "in", "clean", "energy", "generation", ",", "its", "market", "rules", "in", "the", "power", "sector", "do", "not", "fully", "decouple", "the", "price", "of", "renew", "-", "\n", "able" ]	[ { "end": 1126, "label": "CITATION_REF", "start": 1123 } ]
and RIPL3-2023 database [ 15] (TRIPL3 1/2). The “main isomer” is marked with an asterisk() in each nucleus E∗(MeV) Texp. 1/2(ns) Tlit. 1/2(ns) Ref. TRIPL3 1/2(ns) 88Br 0.270 4500 (400) 5500 (100) [ 16] 5300 91Rb 1.134* 15 (4) 16 (1) [ 17] 16.6 92Rb 0.284* 54.4 (27) 54 (3) [ 18]5 4 0.142 0.82 (4) 0.75 (3) [ 19]0 . 7 5 93Rb 4.423* 97 (15) 111 (11) [ 17] 111 94Rb 2.075 65 (8) 107 (16) [ 20] 107 1.485* 42 (7) 18 (1) [ 20]1 8 0.328 1.6 (1) – – – 95Rb 0.835* 101 (24) 94 (7) [ 17]– 95Sr 0.556* 21.0 (5) 21.5 (3) [ 21] 21.9 97Sr 0.831* 530 (22) 504 (8) [ 16] 395 0.308 200 (10) 165 (4) [ 21] 169 98Y 1.181* 740 (30) 780 (30) [ 22] 780 0.496 6740 (140) 6900 (50) [ 22] 6900 0.375 37.8 (13) 35.2 (5) [ 22] 35.2 0.171 680 (30) 630 (20) [ 22] 630 97Zr 1.264* 106 (11) 102.8 (24) [ 23] 102.8 99Zr 1.039 29 (4) 54 (10) [ 24]5 4 0.252* 345 (12) 336 (5) [ 25] 293 0.122 1.01 (3) 1.08 (2) [ 26]1 . 0 7 101Zr 0.942* 18.2 (19) 16 (2) [ 27]1 6 108Tc 0.330(+ x)* 116 (3) 94 (10) [ 28]– 0.176(+ x)2 . 8 1 ( 4 ) – – – 0.106(+ x)0 . 9 4 ( 6 ) – – – ﬁssion of252Cf), and are used in evaluated data. Although an isomeric state was observed in Ref. [ 44], no absolute excita- tion energy was assigned. However, in Ref. [ 45], the author established a level scheme without ﬂoating level, based on common γ-ray transitions (86 keV and 106 keV) seen in both 108Moβdecay and252Cf(sf). The γ-γcoincidences from our data are in agreement with these three level schemes. Further-more, we observe a transition with E γ/similarequal58 keV that was also reported in Ref. [ 43]. We derived from our data that the level at E∗=330 keV is a consistent candidate for the 116 ns isomeric state, from all γ-γcoincidences reported in Fig. 9. For completeness, we report in the ﬁgure the γ-ray energies measured by our setup. Besides, we measured the half-life of two short-lived states below the main isomer for the ﬁrst time, at E∗=176.2 and 106.3 keV. 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With a global network of more than 170 scholars across twenty countries, Carnegie is renowned for its independent analysis of major global problems and understanding of regional contexts. Democracy, Conflict, and Governance Program The Democracy, Conflict, and Governance Program is a leading source of independent policy research, writing, and outreach on global democracy, conflict, and governance. It an - alyzes and seeks to improve international efforts to reduce democratic backsliding, mitigate conflict and violence, overcome political polarization, promote gender equality, and advance pro-democratic uses of new technologies.	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vs 14.85%; P-value = 0.007). They also presented higher rates of respiratory symptom than non-severe cases (79.55% vs 46.53%; P-value < 0.001). The biological comparison found significant differences for neutrophil count (median, 4.74 vs Figure 1 Receiver operating characteristic (ROC) curves of parameters of blood routine for the diagnosis (discriminating) of disease severity on admission. <!-- image --> 3.56; P-value < 0.001), lymphocyte count (median, 1.02 vs 1.73; P-value < 0.001), eosinophil count (median, 0.01 vs 0.04; P-value < 0.001), and CRP level (median, 86.4 vs 3.4; P-value < 0.001). According to ROC curves of hematologic parameters and CRP admission level, the AUCs of leucocyte count, neutrophil count, monocyte count, hemoglobin count, and CRP level were 0.594, 0.691, 0.523, 0.475, and 0.872, respectively ( Figure 1 ). The AUC for severity prediction of CRP was significantly higher than leucocyte count (P-value < 0.001), and neutrophil count (P-value < 0.001). As represented in Table III , CRP level was associated with COVID-19 severity in the univariate analysis (OR=1.22, 95% IC (1.13-1.33)). For the multivariate analysis, we found that CRP level was CRP , C-reactive protein. Table III Independent discriminators (predictors) of disease severity. \| \| Univariate OR (95% CI) \| Multivariate Model OR (95% CI) \| Multivariate Model (stepwise) OR (95% CI) \| \|--------------------------\|--------------------------\|----------------------------------\|---------------------------------------------\| \| Demographics \| Demographics \| Demographics \| Demographics \| \| Age, years \| 1.07 (1.04-1.10) \| 1.04 (1.00-1.08) \| 1.05 (1.02-1.09) \| \| Male \| 5.93 (2.58-13.66) \| 3.90 (1.24-12.33) \| 3.35 (1.20-9.36) \| \| Comorbidities \| Comorbidities \| Comorbidities \| Comorbidities \| \| Hypertension \| 3.76 (1.70-8.29) \| 0.88 (0.24-3.21) \| \| \| Diabetes \| 3.42 (1.25-9.38) \| 0.95 (0.21-4.27) \| \| \| Cardiovascular disease \| 6.40 (2.07-19.79) \| 3.74 (0.76-18.29) \| \| \| Respiratory disease \| 2.54 (0.83-7.74) \| \| \| \| Other disease \| 3.28 (1.44-7.46) \| 3.19 (0.96-10.55) \| \| \| Clinical symptoms \| Clinical symptoms \| Clinical symptoms \| Clinical symptoms \| \| Fever \| 1.99 (0.97-4.08) \| \| \| \| General symptom \| 1.72 (0.84-3.54) \| \| \| \| Respiratory symptom \| 4.47 (1.95-10.25) \| 4.26 (1.31-13.89) \| 3.11 (1.11-8.74) \| \| ENT symptom \| 0.63 (0.28-1.44) \| \| \| \| Digestive symptom \| 1.35 (0.60-3.04) \| \| \| \| Blood routine \| Blood routine \| Blood routine \| Blood routine \| \| Leucocyte (×10 9 per L) \| 1.15 (1.00-1.32) \| \| \| \| Neutrophil (×10 9 per L) \|	[ "vs", " ", "14.85", "%", ";", " ", "P", "-", "value", " ", "=", " ", "0.007", ")", ".", " ", "They", " ", "also", "presented", " ", "higher", " ", "rates", " ", "of", " ", "respiratory", " ", "symptom", " ", "than", "non", "-", "severe", " ", "cases", " ", "(", "79.55", "%", " ", "vs", " ", "46.53", "%", ";", " ", "P", "-", "value", " ", "&", "lt", ";", "0.001", ")", ".", "The", "biological", "comparison", "found", "significant", "differences", " ", "for", " ", "neutrophil", " ", "count", " ", "(", "median", ",", " ", "4.74", " ", "vs", "\n\n", "Figure", 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Suite 1001 Ottawa, Ontario Canada K1P 5G4 IGFMining.org X @IGFMining <!-- image --> ## OECD HEAD OFFICE 2, rue André Pascal 75775 Paris Cedex 16 France @ OECD.org X OECD <!-- image --> ## ACKNOWLEDGEMENTS The lead authors of this publication are Tomas Balco, Senior Advisor, BEPS Capacity Building Team of Global Relations and Development Division, OECD, and Jaqueline Taquiri, Senior Policy Advisor, Tax and Extractive Industries, IGF. The authors would like to recognize the contributions made by the governments of Kenya, Liberia, Papua New Guinea, South Africa, Tanzania, the United Kingdom, and Zambia as well as Thomas Baunsgaard from the International Monetary Fund, and the International Council on Mining and Metals. The authors were ably assisted in their research work by members of the IGF's Global Mining Tax Initiative, including Kudzai Mataba, Alexandra Readhead, and Ekpen Omonbude, and colleagues from the OECD, including Andrew Viola. 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The number of arbitrators shall be one. ## LIST OF ABBREVIATIONS APT additional profit tax BEPS	[ "Suite", "1001", "Ottawa", ",", "Ontario", "Canada", "K1P", "5G4", "\n\n", "IGFMining.org", "X", "@IGFMining", "\n\n", "<", "!", "--", "image", "--", ">", "\n\n", "#", "#", "OECD", "HEAD", "OFFICE", "\n\n", "2", ",", "rue", "André", "Pascal", "75775", "Paris", "Cedex", "16", "France", "\n\n", "@", "\n\n", "OECD.org", "X", "OECD", "\n\n", "<", "!", "--", "image", "--", ">", "\n\n", "#", "#", "ACKNOWLEDGEMENTS", "\n\n", "The", "lead", "authors", "of", "this", "publication", "are", "Tomas", "Balco", ",", "Senior", "Advisor", ",", "BEPS", "Capacity", "Building", "Team", "of", "Global", "Relations", "and", "Development", "Division", ",", "OECD", ",", "and", "Jaqueline", "Taquiri", ",", "Senior", "Policy", "Advisor", ",", "Tax", "and", "Extractive", "Industries", ",", "IGF", ".", "\n\n", "The", "authors", "would", "like", "to", "recognize", "the", "contributions", "made", "by", "the", "governments", "of", "Kenya", ",", "Liberia", ",", "Papua", "New", "Guinea", ",", "South", "Africa", ",", "Tanzania", ",", "the", "United", "Kingdom", ",", "and", "Zambia", "as", "well", "as", "Thomas", "Baunsgaard", "from", "the", "International", "Monetary", "Fund", ",", "and", "the", "International", "Council", "on", "Mining", "and", "Metals", ".", "The", "authors", "were", "ably", "assisted", "in", "their", "research", "work", "by", "members", "of", "the", "IGF", "'s", "Global", "Mining", "Tax", "Initiative", ",", "including", "Kudzai", "Mataba", ",", "Alexandra", "Readhead", ",", "and", "Ekpen", "Omonbude", ",", "and", "colleagues", "from", "the", "OECD", ",", "including", "Andrew", "Viola", ".", "\n\n", "OECD", ":", "http://www.oecd.org/en/about/programmes/beps-in-mining", "\n\n", "IGF", ":", "www.igfmining.org/financial-benefits/", "\n\n", "<", "!", "--", "image", "--", ">", "\n\n", "This", "work", "is", "made", "available", "under", "the", "Creative", "Commons", "Attribution", "4.0", "International", "licence", ".", "By", "using", "this", "work", ",", "you", "agree", "to", "be", "bound", "by", "the", "terms", "of", "this", "licence", "(", "https://", "creativecommons.org/licenses/by/4.0/", ")", ".", "\n\n", "Attribution", "-", "You", "must", "cite", "the", "work", ".", "\n\n", "Translations", "You", "must", "cite", "the", "original", "work", ",", "identify", "changes", "to", "the", "original", "and", "add", "the", "following", "text", ":", "In", "the", "event", "of", "any", "discrepancy", "between", "the", "original", "work", "and", "the", "translation", ",", "only", "the", "text", "of", "the", "original", "work", "should", "be", "considered", "valid", ".", "\n\n", "Adaptations", "You", "must", "cite", "the", "original", "work", "and", "add", "the", "following", "text", ":", "This", "is", "an", "adaptation", "of", "an", "original", "work", "by", "the", "OECD", ",", "the", "IISD", "and", "the", "IGF", ".", "The", "opinions", "expressed", "and", "arguments", "employed", "in", "this", "adaptation", "should", "not", "be", "reported", "as", "representing", "the", "official", "views", "of", "the", "OECD", ",", "the", "IGF", ",", "or", "their", "respective", "member", "countries", ".", "\n\n", "Third", "-", "party", "material", "The", "licence", "does", "not", "apply", "to", "third", "-", "party", "material", "in", "the", "work", ".", "If", "using", "such", "material", ",", "you", "are", "responsible", "for", "obtaining", "permission", "from", "the", "third", "party", "and", "for", "any", "claims", "of", "infringement", ".", "\n\n", "You", "must", "not", "use", "the", "OECD", "'s", ",", "the", "IISD", "'s", "or", "the", "IGF", "'s", "respective", "logo", ",", "visual", "identity", ",", "or", "cover", "image", "without", "express", "permission", "or", "suggest", "the", "OECD", "or", "IISD", "/", "IGF", "endorses", "your", "use", "of", "the", "work", ".", "Any", "dispute", "arising", "under", "this", "licence", "shall", "be", "settled", "by", "arbitration", "in", "accordance", "with", "the", "2012", "Rules", "of", "the", "Permanent", "Court", "of", "Arbitration", ".", "The", "seat", "of", "arbitration", "shall", "be", "Paris", "(", "France", ")", ".", "The", "number", "of", "arbitrators", "shall", "be", "one", ".", "\n\n", "#", "#", "LIST", "OF", "ABBREVIATIONS", "\n\n", "APT", "\n\n", "additional", "profit", "tax", "\n\n", "BEPS", "\n\n" ]	[]
Figure 3.66. Keyword cloud for Chemistry and chemical engineering in Azerbaijan Figure 3.68. Keyword cloud for Mechanical engineering and heavy machinery in Azerbaijan Figure 3.67. Keyword cloud for Energy in Azerbaijan Figure 3.69. Keyword cloud for Health and wellbeing in Azerbaijan 222 Part 3 Analysis of scientific and technological potential Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation223 6.4 Georgia – Summary of the strengths of the S&T specialisa- tions Georgia’s most highlighted S&T domains are the following: ■Environmental sciences and industries ticks all S&T indicators – on critical mass, spe- cialisation and excellence – for publications, patents and projects. It is a very clear spe- cialisation domain for Georgia, with particular relevance in Geology and Geotechnical engi- neering, as well as Environmental engineering and Chemistry; ■Agrifood presents a high specialisation in patents and publications, as well as a critical mass in patents and a relevant number of EU-funded R&I projects, with science orient- ed towards Horticulture, Genetics and Plant science; GEORGIA Critical mass Specialisation Excellence Summary S&T domain Pubs. Pat. Pubs. Pat. NCIEC projectsTotal Agrifood 4 Biotechnology 0 Chemistry and chemical engineering2 Electric and electronic technologies0 Environmental sciences and industries6 Fundamental physics and mathematics3 Governance, culture, education and the economy4 Health and wellbeing 3 ICT and computer science 3 Mechanical engineering and heavy machinery2 Nanotechnology and materials 2 Optics and photonics 1 NCI = Normalised citation impact EC projects = EU-funded R&I projectsTable 3.31. Selected S&T specialisation domains in Georgia ■Health and wellbeing presents a high crit- ical mass, specialisation and citation impact in publications, while no positive indicator emerges in relation to patents. It co-occurs frequently with the domain of Agrifood. Be- yond General medicine, research is related, in particular, to Infectious diseases and Immu- nology; and ■ICT and computer science presents a spe- cialisation in patents as well as highly cited publications and a relevant number of EC pro- jects. The following clouds present the most relevant keywords for these highlighted S&T domains. Figure 3.70. Keyword cloud for Environmental sciences and industries in Georgia Figure 3.72. Keyword cloud for Health and wellbeing in Georgia Figure 3.71. Keyword cloud for Agrifood in Georgia Figure 3.73. 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on the sensor data received from the sensing means to optimize the recovery of one or more desired materials from a waste stream. Example [0189] includes the method of example [0188] and/or some other example(s) herein, wherein the method includes: optimizing an arrangement of the material handling means based on the sensor data using optimization means. Example [0190] includes the method of examples [0188]-[0189] and/or some other example(s) herein, wherein the controlling includes: controlling material handling means to remove contaminants recognized by the sensing means from the waste stream. Example [0191] includes the method of examples [0188]-[0190] and/or some other example(s) herein, wherein the controlling includes: controlling material handling means to remove the one or more desired materials recognized by the sensing means from the waste stream. Example [0192] includes a method for material handling, comprising: receiving status information from the material handling means; and controlling the material handling means based on the sensor data received status information. Example [0193] includes the apparatus of examples [0188]-[0192] and/or some other example(s) herein, wherein the controlling includes: reconfiguring the material handling means in real time or near real time to remove varying types of the one or more desired materials. Example [0194] includes the apparatus of example [0193] and/or some other example(s) herein, wherein the material handling means includes a plurality material handling mechanisms, and the reconfiguring includes: reconfiguring each of the plurality of material handling mechanisms in real time or near real time to balance an amount of the one or more desired materials to be removed between each of the plurality of material handling mechanisms. Example [0195] includes the apparatus of examples [0188]-[0194] and/or some other example(s) herein, wherein the sensing means comprises a machine vision system. Example [0196] includes the method of examples [0188]-[0195] and/or some other example(s) herein, wherein the method includes: operating a machine learning model and/or artificial intelligence system to adaptively control the material handling means based on the sensor data. Example [0197] includes a method of operating a central controller of a material recovery facility (MRF), the method comprising: receiving data streams from respective sensors of a set of sensors; processing the one or more data streams to determine an MRF status of the MRF, wherein the MRF status is based on a composition of a material waste stream at one or more locations within the MRF and an operating condition of at least one	[ "on", "the", "sensor", "data", "received", "from", "the", "sensing", "means", "to", "optimize", "the", "recovery", "of", "one", "or", "more", "desired", "materials", "from", "a", "waste", "stream", ".", "\n\n", "Example", "[", "0189", "]", "includes", "the", "method", "of", "example", "[", "0188", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "the", "method", "includes", ":", "optimizing", "an", "arrangement", "of", "the", "material", "handling", "means", "based", "on", "the", "sensor", "data", "using", "optimization", "means", ".", "\n\n", "Example", "[", "0190", "]", "includes", "the", "method", "of", "examples", "[", "0188]-[0189", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "the", "controlling", "includes", ":", "controlling", "material", "handling", "means", "to", "remove", "contaminants", "recognized", "by", "the", "sensing", "means", "from", "the", "waste", "stream", ".", "\n\n", "Example", "[", "0191", "]", "includes", "the", "method", "of", "examples", "[", "0188]-[0190", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "the", "controlling", "includes", ":", "controlling", "material", "handling", "means", "to", "remove", "the", "one", "or", "more", "desired", "materials", "recognized", "by", "the", "sensing", "means", "from", "the", "waste", "stream", ".", "\n\n", "Example", "[", "0192", "]", "includes", "a", "method", "for", "material", "handling", ",", "comprising", ":", "receiving", "status", "information", "from", "the", "material", "handling", "means", ";", "and", "controlling", "the", "material", "handling", "means", "based", "on", "the", "sensor", "data", "received", "status", "information", ".", "\n\n", "Example", "[", "0193", "]", "includes", "the", "apparatus", "of", "examples", "[", "0188]-[0192", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "the", "controlling", "includes", ":", "reconfiguring", "the", "material", "handling", "means", "in", "real", "time", "or", "near", "real", "time", "to", "remove", "varying", "types", "of", "the", "one", "or", "more", "desired", "materials", ".", "\n\n", "Example", "[", "0194", "]", "includes", "the", "apparatus", "of", "example", "[", "0193", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "the", "material", "handling", "means", "includes", "a", "plurality", "material", "handling", "mechanisms", ",", "and", "the", "reconfiguring", "includes", ":", "reconfiguring", "each", "of", "the", "plurality", "of", "material", "handling", "mechanisms", "in", "real", "time", "or", "near", "real", "time", "to", "balance", "an", "amount", "of", "the", "one", "or", "more", "desired", "materials", "to", "be", "removed", "between", "each", "of", "the", "plurality", "of", "material", "handling", "mechanisms", ".", "\n\n", "Example", "[", "0195", "]", "includes", "the", "apparatus", "of", "examples", "[", "0188]-[0194", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "the", "sensing", "means", "comprises", "a", "machine", "vision", "system", ".", "\n\n", "Example", "[", "0196", "]", "includes", "the", "method", "of", "examples", "[", "0188]-[0195", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "the", "method", "includes", ":", "operating", "a", "machine", "learning", "model", "and/or", "artificial", "intelligence", "system", "to", "adaptively", "control", "the", "material", "handling", "means", "based", "on", "the", "sensor", "data", ".", "\n\n", "Example", "[", "0197", "]", "includes", "a", "method", "of", "operating", "a", "central", "controller", "of", "a", "material", "recovery", "facility", "(", "MRF", ")", ",", "the", "method", "comprising", ":", "receiving", "data", "streams", "from", "respective", "sensors", "of", "a", "set", "of", "sensors", ";", "processing", "the", "one", "or", "more", "data", "streams", "to", "determine", "an", "MRF", "status", "of", "the", "MRF", ",", "wherein", "the", "MRF", "status", "is", "based", "on", "a", "composition", "of", "a", "material", "waste", "stream", "at", "one", "or", "more", "locations", "within", "the", "MRF", "and", "an", "operating", "condition", "of", "at", "least", "one" ]	[]
specialisation is above 1.5 highlighted in dark green and industries where the degree of specialisation is above 1.25 but below 1.5 high- lighted in light green. Based on the results, for each EaP country we can identify those industries which have an innovation potential based on the relative share of product and/or process innova- tors, as follows. 40 Industry names are those used in the Enterprise Survey. NACE codes match the corresponding ISIC codes. Industry names therefore do not necessarily match NACE industry names. 86 Part 2 Analysis of economic and innovation potential ■Armenia • Paper (NACE 17) • Basic metals (NACE 24) • Construction (NACE F) • Transport (NACE H) ■Azerbaijan • Recycling (NACE 33) • Services of motor vehicles (NACE 45) • Wholesale (NACE 46) ■Georgia • Garments (NACE 14) • Publishing, printing and recorded media (NACE 18) • Chemicals (NACE 20+21) • Non-metallic mineral products (NACE 23) • Basic metals (NACE 24) • Fabricated metal products (NACE 25) • Furniture (NACE 31) • Retail (NACE 47) • Hotels and restaurants (NACE I) ■Moldova • Wood (NACE 16) • Paper (NACE 17) • Chemicals (NACE 20+21) • Plastics & rubber (NACE 22) • Precision instruments (NACE 26) • Machinery and equipment (NACE 28) • Information and communication (NACE J) ■Ukraine • Textiles (NACE 13) • Services of motor vehicles (NACE 45) The fact that only two industries emerge as spe- cialised for Ukraine is a direct result of the fact that the weighted number of enterprises is much higher in Ukraine than in the other countries, with a more equal distribution of enterprises across the different industries.Armenia Azerbaijan Belarus Georgia Moldova Ukraine EaP All industries 4 317 2 475 27 903 5 748 6 528 56 574 103 545Table 2.27. Weighted number of enterprises covered in the Enterprise Survey Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation87 88 Part 2 Analysis of economic and innovation potential Share of product innovators Share of process innovators Share of product and/or process innovators Name of industry Armenia Azerbaijan Belarus Georgia Moldova Ukraine EaP Armenia Azerbaijan Belarus Georgia Moldova Ukraine EaP Armenia Azerbaijan Belarus Georgia Moldova Ukraine EaP Food (10+11) 37.0 42.6 63.3 33.7 42.9 39.1 43.1 23.3 3.7 43.2 25.8 50.1 19.2 27.5 45.5 46.3 65.5 42.5 61.7 44.6 51.0 Tobacco (12) -- -- -- -- 0.0 -- -- -- -- -- -- 0.0 -- --	[ "specialisation", "is", "above", "1.5", "highlighted", "\n", "in", "dark", "green", "and", "industries", "where", "the", "degree", "of", "\n", "specialisation", "is", "above", "1.25", "but", "below", "1.5", "high-", "\n", "lighted", "in", "light", "green", ".", "Based", "on", "the", "results", ",", "for", "\n", "each", "EaP", "country", "we", "can", "identify", "those", "industries", "\n", "which", "have", "an", "innovation", "potential", "based", "on", "the", "\n", "relative", "share", "of", "product", "and/or", "process", "innova-", "\n", "tors", ",", "as", "follows", ".", "\n", "40", "Industry", "names", "are", "those", "used", "in", "the", "Enterprise", "Survey", ".", "\n", "NACE", "codes", "match", "the", "corresponding", "ISIC", "codes", ".", "Industry", "\n", "names", "therefore", "do", "not", "necessarily", "match", "NACE", "industry", "\n", "names", ".", "\n", "86", "\n ", "Part", "2", "Analysis", "of", "economic", "and", "innovation", "potential", "\n ", "■", "Armenia", "\n", "•", "Paper", "(", "NACE", "17", ")", "\n", "•", "Basic", "metals", "(", "NACE", "24", ")", "\n", "•", "Construction", "(", "NACE", "F", ")", "\n", "•", "Transport", "(", "NACE", "H", ")", "\n ", "■", "Azerbaijan", "\n", "•", "Recycling", "(", "NACE", "33", ")", "\n", "•", "Services", "of", "motor", "vehicles", "(", "NACE", "45", ")", "\n", "•", "Wholesale", "(", "NACE", "46", ")", "\n ", "■", "Georgia", "\n", "•", "Garments", "(", "NACE", "14", ")", "\n", "•", "Publishing", ",", "printing", "and", "recorded", "media", "\n", "(", "NACE", "18", ")", "\n", "•", "Chemicals", "(", "NACE", "20", "+", "21", ")", "\n", "•", "Non", "-", "metallic", "mineral", "products", "(", "NACE", "23", ")", "\n", "•", "Basic", "metals", "(", "NACE", "24", ")", "\n", "•", "Fabricated", "metal", "products", "(", "NACE", "25", ")", "\n", "•", "Furniture", "(", "NACE", "31", ")", "\n", "•", "Retail", "(", "NACE", "47", ")", "\n", "•", "Hotels", "and", "restaurants", "(", "NACE", "I", ")", "\n ", "■", "Moldova", "\n", "•", "Wood", "(", "NACE", "16", ")", "\n", "•", "Paper", "(", "NACE", "17", ")", "\n", "•", "Chemicals", "(", "NACE", "20", "+", "21", ")", "\n", "•", "Plastics", "&", "rubber", "(", "NACE", "22", ")", "\n", "•", "Precision", "instruments", "(", "NACE", "26", ")", "\n", "•", "Machinery", "and", "equipment", "(", "NACE", "28", ")", "\n", "•", "Information", "and", "communication", "(", "NACE", "J", ")", "■", "Ukraine", "\n", "•", "Textiles", "(", "NACE", "13", ")", "\n", "•", "Services", "of", "motor", "vehicles", "(", "NACE", "45", ")", "\n", "The", "fact", "that", "only", "two", "industries", "emerge", "as", "spe-", "\n", "cialised", "for", "Ukraine", "is", "a", "direct", "result", "of", "the", "fact", "\n", "that", "the", "weighted", "number", "of", "enterprises", "is", "much", "\n", "higher", "in", "Ukraine", "than", "in", "the", "other", "countries", ",", "with", "\n", "a", "more", "equal", "distribution", "of", "enterprises", "across", "the", "\n", "different", "industries", ".", "Armenia", "Azerbaijan", "Belarus", "Georgia", "Moldova", "Ukraine", "EaP", "\n", "All", "industries", "4", "317", "2", "475", "27", "903", "5", "748", "6", "528", "56", "574", "103", "545Table", "2.27", ".", "Weighted", "number", "of", "enterprises", "covered", "in", "the", "Enterprise", "Survey", "\n", "Smart", "Specialisation", "in", "the", "Eastern", "Partnership", "countries", "-", "Potential", "for", "knowledge", "-", "based", "economic", "cooperation87", "88", "\n ", "Part", "2", "Analysis", "of", "economic", "and", "innovation", "potential", "\n", "Share", "of", "product", "innovators", "Share", "of", "process", "innovators", "Share", "of", "product", "and/or", "process", "innovators", "\n", "Name", "of", "industry", "Armenia", "Azerbaijan", "Belarus", "Georgia", "Moldova", "Ukraine", "EaP", "Armenia", "Azerbaijan", "Belarus", "Georgia", "Moldova", "Ukraine", "EaP", "Armenia", "Azerbaijan", "Belarus", "Georgia", "Moldova", "Ukraine", "EaP", "\n", "Food", "(", "10", "+", "11", ")", "37.0", "42.6", "63.3", "33.7", "42.9", "39.1", "43.1", "23.3", "3.7", "43.2", "25.8", "50.1", "19.2", "27.5", "45.5", "46.3", "65.5", "42.5", "61.7", "44.6", "51.0", "\n", "Tobacco", "(", "12", ")", "--", "--", "--", "--", "0.0", "--", "--", "--", "--", "--", "--", "0.0", "--", "--" ]	[]
Spider uses trapped fireflies as glowing bait to attract more prey \| EurekAlert! Advanced Search Home News Releases Multimedia Meetings Login Register News Release 28-Aug-2025 Spider uses trapped fireflies as glowing bait to attract more prey Peer-Reviewed Publication British Ecological Society Facebook X LinkedIn WeChat Bluesky Message WhatsApp Email image: Sheet web spider with fireflies caught in web view more Credit: Tunghai University Spider Ecologists have observed a species of nocturnal spider attracting prey to its web using the bioluminescent beacons of already trapped fireflies. This rare example of a predator exploiting its prey’s mating signal for its own gain is documented in the British Ecological Society’s Journal of Animal Ecology . Researchers at Tunghai University, Taiwan have observed sheet web spiders Psechrus clavis capturing fireflies in their webs and leaving them there while they emitted bioluminescent light for up to an hour. The researchers even observed the spiders going to check on the captured fireflies from time to time. Intrigued by this unusual behaviour the researchers set up an experiment to test whether this was a strategy used by the spiders to increase their hunting success. In the experiment, they placed LEDs that resembled fireflies, in real sheet spider webs and left other webs clear as controls. They found three times the amount of prey was attracted to webs with the LEDs compared to the control webs. This increased to ten times more prey when they only looked at fireflies being captured. The findings confirm that captured fireflies left as bait increase the hunting success rate of the spiders. The researchers also noticed that the majority of captured fireflies were male, who were likely mistaking the glow for potential mates. Dr I-Min Tso, the lead author of the study said: “Our findings highlight a previously undocumented interaction where firefly signals, intended for sexual communication, are also beneficial to spiders. “This study sheds new light on the ways that nocturnal sit-and-wait predators can rise to the challenges of attracting prey and provides a unique perspective on the complexity of predator-prey interactions.” The researchers suggest that this behaviour could have developed in sheet web spiders to avoid costly investment in their own bioluminescence like other sit-and-wait predators, such as anglerfish. Instead, the spiders are able to outsource prey attraction to their prey’s own signals. 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cohesion meas -ures are different in two neighbourhood types - A comparison of Sanjay (slum/ JJ - illegal housing built on public land) and Ajit Vihar (unauthorised - illegal housing built on private land typically owned by the household). - 3. There is a causal link between trust, social capital and neighbourhood cohe -sion irrespective of neighbourhood type - A comparison of Sanjay, Bhalswa and Ajit Vihar. ## Neighbourhoods Research from around the world has shown that maintaining well-being is crucial for those living in difficult and challenging circumstances. Well-being helps people cope with stress, trauma and hardship, enhancing resilience and mental health, and is vital in areas affected by poverty, conflict and disasters. We examine the relation -ships between subjective well-being (SWB) and neighbourhood cohesion, taking into consideration the socio-economic background of the households as well as levels of trust within our three different settlement types. As neighbourhoods are bounded urban areas, they provide a valuable opportunity to understand the perceptions of individuals and communities within a specific, finite region. By investigating different neighbourhoods, we can explore and compare how these factors vary across regions, shedding light on patterns and differences in community well-being, social cohesion and quality of life. This comparative approach reveals important insights into how neighbourhood characteristics impact residents ( Puddifoot, 1995 ; Pinchak et al., 2021). We consider the association between neighbourhood social cohesion and well-being for residents living in our different colony types. In this chapter, we will first explore the attitudes of residents through the Neighbourhood Cohesion Index (NCI) and the subjective well-being scale (SWB). These residents live in Bhalswa (resettlement colony) and Sanjay (slum/JJ colony), allowing us to investigate the first hypothesis: Being able to choose your neighbourhood is beneficial to your well-being and contributes positively to attitudes around neighbourhood cohesion - A comparison of Sanjay (slum/JJ) and Bhalswa (resettlement). Second, we consider whether the type of neighbourhood you live in affects how you perceive your community and your involvement within it. Residents' preferences on social capital and neighbourhood cohesion measures are different in two neighbourhood types - A comparison of Sanjay (slum/JJ - illegal housing public land) and Ajit Vihar (unauthorised - illegal housing private owned land). Third, we investigate links between trust, social capital and neighbourhood cohesion in the three different neighbourhood types. 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London: Zed Books. - Wemheuer, F. Famine Politics in Maoist China and the Soviet Union . New Haven, CT: Yale University Press, 2014. - White, P. 'Darwin's emotions: The scientific self and the sentiment of objectivity.' Isis , 100 (2009), 811- 26. - Wilson, E. B. The Cell in Development and Heredity . New York: The Macmillan Company, 1925. - Wray, K. B. 'Scientific authorship in the age of collaborative research.' Studies in History and Philosophy of Science Part A , 37: 3 (2006), 505- 14. - Wu, Y.- L. Reproducing Women: Medicine, Metaphor, and Childbirth in Late Imperial China . Berkeley: University of California Press, 2010.	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Seen from such comparative perspectives, the near silence of post- 1989 historiography on the topic of women and science in the former communist bloc is even more striking, given that many women were not active on the peripheries of the scientific establishment, but at its very heart. Equally striking is the fact that the shadow of empire(s) lingers on - often unacknowledged - in discussions of science in South- Eastern and Central Europe, where it is not uncommon for public debates and even academic scholarship to take for granted the notion that 'modern' equals 'Western' and that 'Western' science is the yardstick by which all science is to be measured. 46 Although recent scholarship engages with the 'interimperial' legacies that have shaped Eastern European regions like Transylvania, 47 the domain of science has only occasionally been interrogated in the manner that scholarship on South Asia and other former colonial contexts has done, by moving away from George Basalla's influential diffusionist model of 'Western science' towards more sophisticated understandings of 'modern' science and empire as co- constituted, or a questioning of the moral and political underpinnings of 'Western science'. 48 Recent work that investigates how the implementation of a doctrine of 'self- management' - of scientific workers and their labour - by Yugoslavian socialist elites was linked to the creation of certain forms of scientific 'independence' from the 'West' represents a similar attempt in this direction. 49 In short, approaching the topic holistically, with a mind prepared to question well- established orthodoxies of geography, science, discipline, gender, race, labour and so on, is essential to considering the task at hand: piecing together histories of women in science from fragmentary, often silent archives. One is reminded here of Saidiya Hartman's wonderfully instructive work on Atlantic slavery: 'I had been looking for relatives whose only proof of existence was fragments of stories and names that repeated themselves across generations.' 50 Piecing together a story from such fragmentary archives should perhaps begin with the recognition of a salient, albeit rarely acknowledged truth - one amply demonstrated by Hartman's work - namely, that writing histories of erased, invisible or marginalized groups is difficult, time- consuming work. 51 Not infrequently, such work is rendered even more complicated by the entrenched power dynamics of academic research and translation in(to) the English language, which ensure, for example, that vibrant intellectual debates, often published in other languages, are only	[ "Seen", "from", "such", "comparative", "perspectives", ",", "the", "near", "silence", "of", "post-", " ", "1989", "historiography", "on", "the", "topic", "of", "women", "and", "science", 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region is developing, such as near zero-emissions processes for materials production. To enable these goals, the report recommends for the EU to establish industrial partnerships with third countries in the form of offtake agreements across the supply chain or co-investment in manufacturing projects. The EU’s Global Gateway could be leveraged for the necessary investment. However, in situations where otherwise productive EU companies are being threatened by state-sponsored competition, the EU should be prepared to apply trade measures in line with principles described above [see the Box in chapter 1 – the starting point] . As part of its decarbonisation strategy, the EU should develop an industrial action plan for the automo - tive sector [see the chapter on automotive] . In the short term, the main objective for the sector should be to avoid a radical delocalisation of production away from the EU or the rapid takeover of EU plants and companies by state-subsidised foreign producers, while continuing decarbonisation. The countervailing tariffs recently adopted by the Commission against Chinese automotive companies making battery EVs will help level the playing field in this regard while accommodating genuine productivity gains in China. Looking forward, the report recommends for the EU to develop an industrial roadmap that accounts for the horizontal convergence (i.e. electrification, digitalisation and circularity) and the vertical convergence (i.e. critical raw materials, batteries, transport and charging infrastruc - ture) of value chains in the automotive ecosystem. As part of this action plan, the EU should evaluate support for IPCEIs in the automotive sector. Scale, standardisation and collaboration will be crucial for EU manufacturers to become competitive in areas such as small and affordable European EVs, software-defined vehicle and autonomous driving solutions, and the circularity value chain. A coherent digital policy, encompassing the data ecosystem, should support these developments. In building such a roadmap, the EU should follow a technology-neutral approach in defining the path to CO2 and pollutant reductions and should take stock of market and technological developments. The wider EU strategy towards cross-border and modal integration and sustainable transport needs to plan for competitiveness and not only for cohesion [see the chapter on transport] . Transport should be based on a new unified approach to planning at the EU and national levels, focused on harmonisation and interoperability as well as cohesion. 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They were 7.5 pp (p<0.01) more likely to favour profiles with brokers having 12th grade education and a 11.4 pp (p<0.1) greater likelihood of preferring brokers with college education. In the unauthorised colony, Ajit Vihar, the longer residents had lived in the settlement, then this significantly decreased the likelihood of preferring a broker of the same partisanship from 17.9 pp to 2.8 pp (p<0.01). This is a sizable reduction of 15.1 pp. This was the most noticeable effect on choice. This could imply that for residents, the party of the broker is less important in Ajit Vihar in relation to ‘getting things done’ in their neighbourhood. In Ajit Vihar, residents were more likely to favour brokers from the parliamentary party BJP or AAP, municipal and state govern - ments. The data imply that this may not be how they would vote in an election. Robustness checks The analysis undertaken for each settlement rated slum leader profile observations, with respondents rating eight pairs of two slum leader and neighbour profiles per pairing. To obtain accurate variance estimates, standard errors are clustered by respondent, as observed choice outcomes are not independent across profiles rated by a single respondent. Due to multiple iterations, prior vignettes and their evalua - tions may frame subsequent vignettes and lead to carryover effects (Tourangeau et al., 1989 ; Wirtz, 1996 ). Conducting diagnostics around the variation in judgements gives interclass correlation for Sanjay colony ( ρ=0.274), Bhalswa ( ρ=0.269), Ajit Vihar ( ρ=0.252), hence, only 25–27% of the variation in judgements was attributed to the variation between respondents. This relatively moderate value indicates that the fairness of evaluations was rather homogeneous among respond - ents ( Auspurg and Hinz, 2015 ). The correlation between respondent value vari - ables and the error term for each settlement is close to zero (r<0.04), indicating a successful randomisation and that the model assumptions of independent vari - ables not being correlated with the error term is met. Standard randomised balance checks were also performed by regressing respondent attributes on indicator vari - ables for all of the broker profiles. We used again, as set out in the design effects section, binary indicators for duration of time in the settlement, education and gen - der. It was found that there was no change in our main findings when controlling for these demographic variables. 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sciences and industriesC02F Treatment of water, waste water, sewage, or sludge 523 414.14% Environmental sciences and industriesE21BEarth or rock drilling; obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells271 318.41% Environmental sciences and industriesB01D Separation 235 247.89% Environmental sciences and industriesE21C Mining or quarrying 214 199.07% Environmental sciences and industriesG01NInvestigating or analysing materials by determining their chemical or physical properties196 49.76% Fundamental physics and mathematicsG01NInvestigating or analysing materials by determining their chemical or physical properties153 38.85% Fundamental physics and mathematicsG06F Electric digital data processing 92 70.77% Fundamental physics and mathematicsF03D Wind motors 88 68.93% Fundamental physics and mathematicsB01D Separation 81 85.44% Fundamental physics and mathematicsH01LSemiconductor devices; electric solid state devices not otherwise provided for80 79.30% Governance, culture, education and the economyA61B Diagnosis; surgery; identification 83 14.35% Governance, culture, education and the economyG06F Electric digital data processing 70 53.85% 164 Part 3 Analysis of scientific and technological potential Domain IPC Description No recordsRelative freq. Governance, culture, education and the economyA63BApparatus for physical training, gymnastics, swimming, climbing, or fencing; ball games; training equipment28 104.67% Governance, culture, education and the economyG09BEducational or demonstration appliances; appliances for teaching, or communicating with, the blind, deaf or mute; models; planetaria; globes; maps; diagrams21 14.53% Governance, culture, education and the economyG06QData processing systems or methods, specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes; systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes, not otherwise provided for20 41.81% Health and wellbeingA61B Diagnosis; surgery; identification 5 506 952.05% Health and wellbeingA61K Preparations for medical, dental, or toilet purposes 2 540 556.80% Health and wellbeingG01NInvestigating or analysing materials by determining their chemical or physical properties2 247 570.51% Health and wellbeingA61PSpecific therapeutic activity of chemical compounds or medicinal preparations1 493 458.50% Health and wellbeingA61NElectrotherapy; magnetotherapy; radiation therapy; ultrasound therapy719 344.02% ICT and computer scienceG06F Electric digital data processing 693 533.08% ICT and computer scienceG06QData processing systems or methods, specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes; systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes, not otherwise provided for259 541.46% ICT and computer scienceH04LTransmission of digital information, e.g. telegraphic communication254 525.52% ICT and computer scienceA61B Diagnosis; surgery; identification 207 35.79% ICT and computer scienceH04N Pictorial communication, e.g. television 196 197.98% Mechanical engineering and heavy machineryA61B Diagnosis; surgery; identification 649 112.22% Mechanical engineering and heavy machineryG01NInvestigating or analysing materials by	[ "sciences", "and", "\n", "industriesC02F", "Treatment", "of", "water", ",", "waste", "water", ",", "sewage", ",", "or", "sludge", "523", "414.14", "%", "\n", "Environmental", "\n", "sciences", "and", "\n", "industriesE21BEarth", "or", "rock", "drilling", ";", "obtaining", "oil", ",", "gas", ",", "water", ",", "soluble", "or", "\n", "meltable", "materials", "or", "a", "slurry", "of", "minerals", "from", "wells271", "318.41", "%", "\n", "Environmental", "\n", "sciences", "and", "\n", "industriesB01D", "Separation", "235", "247.89", "%", "\n", "Environmental", "\n", "sciences", "and", "\n", "industriesE21C", "Mining", "or", "quarrying", "214", "199.07", "%", "\n", "Environmental", "\n", "sciences", "and", "\n", "industriesG01NInvestigating", "or", "analysing", "materials", "by", "determining", "their", "\n", "chemical", "or", "physical", "properties196", "49.76", "%", "\n", "Fundamental", "\n", "physics", "and", "\n", "mathematicsG01NInvestigating", "or", "analysing", "materials", "by", "determining", "their", "\n", "chemical", "or", "physical", "properties153", "38.85", "%", "\n", "Fundamental", "\n", "physics", "and", "\n", "mathematicsG06F", "Electric", "digital", "data", "processing", "92", "70.77", "%", "\n", "Fundamental", "\n", "physics", "and", "\n", "mathematicsF03D", "Wind", "motors", "88", "68.93", "%", "\n", "Fundamental", "\n", "physics", "and", "\n", "mathematicsB01D", "Separation", "81", "85.44", "%", "\n", "Fundamental", "\n", "physics", "and", "\n", "mathematicsH01LSemiconductor", "devices", ";", "electric", "solid", "state", "devices", "not", "\n", "otherwise", "provided", "for80", "79.30", "%", "\n", "Governance", ",", "\n", "culture", ",", "education", "\n", "and", "the", "economyA61B", "Diagnosis", ";", "surgery", ";", "identification", "83", "14.35", "%", "\n", "Governance", ",", "\n", "culture", ",", "education", "\n", "and", "the", "economyG06F", "Electric", "digital", "data", "processing", "70", "53.85", "%", "\n", "164", "\n ", "Part", "3", "Analysis", "of", "scientific", "and", "technological", "potential", "\n", "Domain", "IPC", "Description", "No", "recordsRelative", "\n", "freq", ".", "\n", "Governance", ",", "\n", "culture", ",", "education", "\n", "and", "the", "economyA63BApparatus", "for", "physical", "training", ",", "gymnastics", ",", "swimming", ",", "\n", "climbing", ",", "or", "fencing", ";", "ball", "games", ";", "training", "equipment28", "104.67", "%", "\n", "Governance", ",", "\n", "culture", ",", "education", "\n", "and", "the", "economyG09BEducational", "or", "demonstration", "appliances", ";", "appliances", "for", "\n", "teaching", ",", "or", "communicating", "with", ",", "the", "blind", ",", "deaf", "or", "mute", ";", "\n", "models", ";", "planetaria", ";", "globes", ";", "maps", ";", "diagrams21", "14.53", "%", "\n", "Governance", ",", "\n", "culture", ",", "education", "\n", "and", "the", "economyG06QData", "processing", "systems", "or", "methods", ",", "specially", "adapted", "\n", "for", "administrative", ",", "commercial", ",", "financial", ",", "managerial", ",", "\n", "supervisory", "or", "forecasting", "purposes", ";", "systems", "or", "methods", "\n", "specially", "adapted", "for", "administrative", ",", "commercial", ",", "\n", "financial", ",", "managerial", ",", "supervisory", "or", "forecasting", "\n", "purposes", ",", "not", "otherwise", "provided", "for20", "41.81", "%", "\n", "Health", "and", "\n", "wellbeingA61B", "Diagnosis", ";", "surgery", ";", "identification", "5", "506", "952.05", "%", "\n", "Health", "and", "\n", "wellbeingA61", "K", "Preparations", "for", "medical", ",", "dental", ",", "or", "toilet", "purposes", "2", "540", "556.80", "%", "\n", "Health", "and", "\n", "wellbeingG01NInvestigating", "or", "analysing", "materials", "by", "determining", "their", "\n", "chemical", "or", "physical", "properties2", "247", "570.51", "%", "\n", "Health", "and", "\n", "wellbeingA61PSpecific", "therapeutic", "activity", "of", "chemical", "compounds", "or", "\n", "medicinal", "preparations1", "493", "458.50", "%", "\n", "Health", "and", "\n", "wellbeingA61NElectrotherapy", ";", "magnetotherapy", ";", "radiation", "therapy", ";", "\n", "ultrasound", "therapy719", "344.02", "%", "\n", "ICT", "and", "computer", "\n", "scienceG06F", "Electric", "digital", "data", "processing", "693", "533.08", "%", "\n", "ICT", "and", "computer", "\n", "scienceG06QData", "processing", "systems", "or", "methods", ",", "specially", "adapted", "\n", "for", "administrative", ",", "commercial", ",", "financial", ",", "managerial", ",", "\n", "supervisory", "or", "forecasting", "purposes", ";", "systems", "or", "methods", "\n", "specially", "adapted", "for", "administrative", ",", "commercial", ",", "\n", "financial", ",", "managerial", ",", "supervisory", "or", "forecasting", "\n", "purposes", ",", "not", "otherwise", "provided", "for259", "541.46", "%", "\n", "ICT", "and", "computer", "\n", "scienceH04LTransmission", "of", "digital", "information", ",", "e.g.", "telegraphic", "\n", "communication254", "525.52", "%", "\n", "ICT", "and", "computer", "\n", "scienceA61B", "Diagnosis", ";", "surgery", ";", "identification", "207", "35.79", "%", "\n", "ICT", "and", "computer", "\n", "scienceH04N", "Pictorial", "communication", ",", "e.g.", "television", "196", "197.98", "%", "\n", "Mechanical", "\n", "engineering", "and", "\n", "heavy", "machineryA61B", "Diagnosis", ";", "surgery", ";", "identification", "649", "112.22", "%", "\n", "Mechanical", "\n", "engineering", "and", "\n", "heavy", "machineryG01NInvestigating", "or", "analysing", "materials", "by" ]	[]
of topics consisting of groups of relevant words, as previously explained. These topics generally have a much finer gran- ularity than the S&T priority domains we would typically define in the design of a Smart Speciali- sation Strategy. Therefore, for practical reasons, to best help in defining the different domains, topics whose semantic content was largely overlapping were grouped together. Additionally, some of the extracted topics were finally discarded because of a phenomenon commonly known as ‘topic drift’56, 56 Liu, Q., Huang, H. & Feng, C., ‘Micro-blog post topic drift detection based on LDA model’, Behavior and Social Com- puting, Springer, Cham., pp. 106-118, 2013.Figure 3.1. A graphical representation of the results produced by topic modelling via Latent Dirichlet Allocation Documents are linked to several topics, while topics are composed of words appearing in the various texts. The same words can appear in multiple topics, while the topics connected to some specific documents may feature some words which are not actually contained in some of the texts, but are semantically related 148 Part 3 Analysis of scientific and technological potential whereby the content of some topics is diverted by recurrent words which do not convey meaningful information (such as, for instance, terms related to methods and instruments transversally used in different scientific domains). Once topics were grouped, to achieve point 2. above, a series of domain names were chosen to label each of those groups. These domains are used as labels, transversely across EaP countries so that topics featuring similar semantic content from two different countries are eventually given the same label. The choice of label is carried out to facilitate use by stakeholders in a participatory co-design of R&D&I policies, particularly towards the EDP in the context of Smart Specialisation. Lastly, to have a clear understanding of the num- ber of records associated with each single do- main, the fractional document/topic weights were converted into a categorical association: docu- ments were eventually associated with a specific topic if the respective weight exceeded the aver- age weight of the topic across records plus one standard deviation. This allowed us to link docu- ments with a limited subset to topics and, in turn, domains. 2.3 Results Table 3.3a presents the 14 labelled topic groups obtained from the topic modelling process de- scribed in the previous sections. A second table includes the first 50 keywords linked to the topics within each group;	[ "of", "topics", "consisting", "of", "\n", "groups", "of", "relevant", "words", ",", "as", "previously", "explained", ".", "\n", "These", "topics", "generally", "have", "a", "much", "finer", "gran-", "\n", "ularity", "than", "the", "S&T", "priority", "domains", "we", "would", "\n", "typically", "define", "in", "the", "design", "of", "a", "Smart", "Speciali-", "\n", "sation", "Strategy", ".", "Therefore", ",", "for", "practical", "reasons", ",", "to", "\n", "best", "help", "in", "defining", "the", "different", "domains", ",", "topics", "\n", "whose", "semantic", "content", "was", "largely", "overlapping", "\n", "were", "grouped", "together", ".", "Additionally", ",", "some", "of", "the", "\n", "extracted", "topics", "were", "finally", "discarded", "because", "of", "\n", "a", "phenomenon", "commonly", "known", "as", "‘", "topic", "drift’56", ",", "\n", "56", "Liu", ",", "Q.", ",", "Huang", ",", "H.", "&", "Feng", ",", "C.", ",", "‘", "Micro", "-", "blog", "post", "topic", "drift", "\n", "detection", "based", "on", "LDA", "model", "’", ",", "Behavior", "and", "Social", "Com-", "\n", "puting", ",", "Springer", ",", "Cham", ".", ",", "pp", ".", "106", "-", "118", ",", "2013.Figure", "3.1", ".", "A", "graphical", "representation", "of", "the", "results", "produced", "by", "topic", "modelling", "via", "Latent", "Dirichlet", "Allocation", "\n", "Documents", "are", "linked", "to", "several", "topics", ",", "while", "topics", "are", "composed", "of", "words", "appearing", "in", "the", "various", "texts", ".", "The", "same", "\n", "words", "can", "appear", "in", "multiple", "topics", ",", "while", "the", "topics", "connected", "to", "some", "specific", "documents", "may", "feature", "some", "words", "\n", "which", "are", "not", "actually", "contained", "in", "some", "of", "the", "texts", ",", "but", "are", "semantically", "related", "\n", "148", "\n ", "Part", "3", "Analysis", "of", "scientific", "and", "technological", "potential", "\n", "whereby", "the", "content", "of", "some", "topics", "is", "diverted", "by", "\n", "recurrent", "words", "which", "do", "not", "convey", "meaningful", "\n", "information", "(", "such", "as", ",", "for", "instance", ",", "terms", "related", "\n", "to", "methods", "and", "instruments", "transversally", "used", "in", "\n", "different", "scientific", "domains", ")", ".", "\n", "Once", "topics", "were", "grouped", ",", "to", "achieve", "point", "2", ".", "\n", "above", ",", "a", "series", "of", "domain", "names", "were", "chosen", "to", "\n", "label", "each", "of", "those", "groups", ".", "These", "domains", "are", "\n", "used", "as", "labels", ",", "transversely", "across", "EaP", "countries", "\n", "so", "that", "topics", "featuring", "similar", "semantic", "content", "\n", "from", "two", "different", "countries", "are", "eventually", "given", "\n", "the", "same", "label", ".", "The", "choice", "of", "label", "is", "carried", "out", "\n", "to", "facilitate", "use", "by", "stakeholders", "in", "a", "participatory", "\n", "co", "-", "design", "of", "R&D&I", "policies", ",", "particularly", "towards", "\n", "the", "EDP", "in", "the", "context", "of", "Smart", "Specialisation", ".", "\n", "Lastly", ",", "to", "have", "a", "clear", "understanding", "of", "the", "num-", "\n", "ber", "of", "records", "associated", "with", "each", "single", "do-", "\n", "main", ",", "the", "fractional", "document", "/", "topic", "weights", "were", "\n", "converted", "into", "a", "categorical", "association", ":", "docu-", "\n", "ments", "were", "eventually", "associated", "with", "a", "specific", "\n", "topic", "if", "the", "respective", "weight", "exceeded", "the", "aver-", "\n", "age", "weight", "of", "the", "topic", "across", "records", "plus", "one", "\n", "standard", "deviation", ".", "This", "allowed", "us", "to", "link", "docu-", "\n", "ments", "with", "a", "limited", "subset", "to", "topics", "and", ",", "in", "turn", ",", "\n", "domains", ".", "\n", "2.3", "Results", "\n", "Table", "3.3a", "presents", "the", "14", "labelled", "topic", "groups", "\n", "obtained", "from", "the", "topic", "modelling", "process", "de-", "\n", "scribed", "in", "the", "previous", "sections", ".", "A", "second", "table", "\n", "includes", "the", "first", "50", "keywords", "linked", "to", "the", "topics", "\n", "within", "each", "group", ";" ]	[ { "end": 533, "label": "CITATION_ID", "start": 531 }, { "end": 693, "label": "CITATION_SPAN", "start": 534 }, { "end": 528, "label": "CITATION_REF", "start": 526 } ]
48 UA 5 5 22 13 1 238 PublicationsFigure 3.51. Number of publications and EC projects in collaboration between EaP actors in different countries, in the ‘Energy’ domain Colour indicates the relative distribution of documents, computed row-wise. AM AZ BY GE MD UA Other 1 1 1 3 2 5 1 3 6 8 3 3 15 1 2 6 3 41 EC projectsAM AZ BY GE MD UA Other AM 10 19 30 8 33 313 AZ 10 7 16 4 15 164 BY 19 7 13 9 83 497 GE 30 16 13 7 33 534 MD 8 4 9 7 36 151 UA 33 15 83 33 36 2 875 PublicationsFigure 3.52. Number of publications and EC projects in collaboration between EaP actors in different countries, in the ‘Environmental sciences and industries’ domain Colour indicates the relative distribution of documents, computed row-wise. Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation213 Regional collaboration in Fundamental physics and mathematics The domain of Fundamental physics and math- ematics accounts for the vast majority of co-pub- lications in the Eastern Partnership. Armenia and Georgia collaborate most intensively with one an- other, holding the highest number of publications in their bilateral collaborations. For Azerbaijan, Moldova and Ukraine, external partnerships ac- count for the vast majority of their collaborations. In terms of EC projects, the only intra-EaP collabo- ration is between Ukraine and Armenia. The inten- sity of collaborations with external partners is less significant in this case.Regional collaboration in Governance, culture, education and the economy In the case of Governance, culture education and the economy publications, external collabo- rations again have a significant weight across all six EaP countries. Within the EaP, the pattern of collaboration is very evenly distributed. Besides Ukraine, Armenia-Georgia and Moldova-Ukraine are the partnerships that stand out the most. Collaboration in terms of EC projects is higher than in other domains, and evenly distributed across the countries. Georgia’s collaboration with Ukraine and Armenia stands out. AM AZ BY GE MD UA Other 2 2 3 1 2 4 7 1 2 4 8 EC projectsAM AZ BY GE MD UA Other AM 94 1 412 1 663 6 876 3 162 AZ 94 6 9 3 35 648 BY 1 412 6 1 377 10 673 2 619 GE 1 663 9 1 377 9 872 2 500 MD 6 3 10 9	[ "48", "\n", "UA", "5", "5", "22", "13", "1", "238", "\n", "PublicationsFigure", "3.51", ".", "Number", "of", "publications", "and", "EC", "projects", "in", "collaboration", "between", "EaP", "actors", "in", "different", "countries", ",", "in", "the", "\n", "‘", "Energy", "’", "domain", "\n", "Colour", "indicates", "the", "relative", "distribution", "of", "documents", ",", "computed", "row", "-", "wise", ".", "\n", "AM", "\n", "AZ", "\n", "BY", "\n", "GE", "\n", "MD", "\n", "UA", "\n", "Other", "\n", "1", "1", "\n", "1", "3", "\n", "2", "5", "\n", "1", "3", "6", "8", "\n", "3", "3", "15", "\n", "1", "2", "6", "3", "41", "\n", "EC", "projectsAM", "\n", "AZ", "\n", "BY", "\n", "GE", "\n", "MD", "\n", "UA", "\n", "Other", "\n", "AM", "10", "19", "30", "8", "33", "313", "\n", "AZ", "10", "7", "16", "4", "15", "164", "\n", "BY", "19", "7", "13", "9", "83", "497", "\n", "GE", "30", "16", "13", "7", "33", "534", "\n", "MD", "8", "4", "9", "7", "36", "151", "\n", "UA", "33", "15", "83", "33", "36", "2", "875", "\n", "PublicationsFigure", "3.52", ".", "Number", "of", "publications", "and", "EC", "projects", "in", "collaboration", "between", "EaP", "actors", "in", "different", "countries", ",", "in", "the", "\n", "‘", "Environmental", "sciences", "and", "industries", "’", "domain", "\n", "Colour", "indicates", "the", "relative", "distribution", "of", "documents", ",", "computed", "row", "-", "wise", ".", "\n", "Smart", "Specialisation", "in", "the", "Eastern", "Partnership", "countries", "-", "Potential", "for", "knowledge", "-", "based", "economic", "cooperation213", "\n", "Regional", "collaboration", "in", "Fundamental", "\n", "physics", "and", "mathematics", "\n", "The", "domain", "of", "Fundamental", "physics", "and", "math-", "\n", "ematics", "accounts", "for", "the", "vast", "majority", "of", "co", "-", "pub-", "\n", "lications", "in", "the", "Eastern", "Partnership", ".", "Armenia", "and", "\n", "Georgia", "collaborate", "most", "intensively", "with", "one", "an-", "\n", "other", ",", "holding", "the", "highest", "number", "of", "publications", "\n", "in", "their", "bilateral", "collaborations", ".", "For", "Azerbaijan", ",", "\n", "Moldova", "and", "Ukraine", ",", "external", "partnerships", "ac-", "\n", "count", "for", "the", "vast", "majority", "of", "their", "collaborations", ".", "\n", "In", "terms", "of", "EC", "projects", ",", "the", "only", "intra", "-", "EaP", "collabo-", "\n", "ration", "is", "between", "Ukraine", "and", "Armenia", ".", "The", "inten-", "\n", "sity", "of", "collaborations", "with", "external", "partners", "is", "less", "\n", "significant", "in", "this", "case", ".", "Regional", "collaboration", "in", "Governance", ",", "\n", "culture", ",", "education", "and", "the", "economy", "\n", "In", "the", "case", "of", "Governance", ",", "culture", "education", "\n", "and", "the", "economy", "publications", ",", "external", "collabo-", "\n", "rations", "again", "have", "a", "significant", "weight", "across", "all", "\n", "six", "EaP", "countries", ".", "Within", "the", "EaP", ",", "the", "pattern", "of", "\n", "collaboration", "is", "very", "evenly", "distributed", ".", "Besides", "\n", "Ukraine", ",", "Armenia", "-", "Georgia", "and", "Moldova", "-", "Ukraine", "\n", "are", "the", "partnerships", "that", "stand", "out", "the", "most", ".", "\n", "Collaboration", "in", "terms", "of", "EC", "projects", "is", "higher", "than", "\n", "in", "other", "domains", ",", "and", "evenly", "distributed", "across", "\n", "the", "countries", ".", "Georgia", "’s", "collaboration", "with", "Ukraine", "\n", "and", "Armenia", "stands", "out", ".", "\n", "AM", "\n", "AZ", "\n", "BY", "\n", "GE", "\n", "MD", "\n", "UA", "\n", "Other", "\n", "2", "2", "3", "\n", "1", "\n", "2", "4", "7", "\n", "1", "\n", "2", "4", "8", "\n", "EC", "projectsAM", "\n", "AZ", "\n", "BY", "\n", "GE", "\n", "MD", "\n", "UA", "\n", "Other", "\n", "AM", "94", "1", "412", "1", "663", "6", "876", "3", "162", "\n", "AZ", "94", "6", "9", "3", "35", "648", "\n", "BY", "1", "412", "6", "1", "377", "10", "673", "2", "619", "\n", "GE", "1", "663", "9", "1", "377", "9", "872", "2", "500", "\n", "MD", "6", "3", "10", "9" ]	[]
age of 18 and his reading and writing are not perfect. The second informant, Mr. Norman (the driver henceforth), is from St. Mary in the north of Jamaica. He migrated to Britain when he was 17. Today he is 59 years old. He worked in two factories in Manchester, as a dry cleaner, and as a carpet fitter before he became a taxi-driver, which is his present job. He also studied for a while in Jamaica and took a course in reading and writing in Manchester. This means that he dealt, and is still dealing with different people. Accordingly, his language is expected to be influenced more than that of the first informant. ## 5. Data Collection Data gathering is based on three factors. Firstly, the author once lived with his informants for one year or so, which enabled him to observe a great deal of the properties of their speech. Secondly, he recorded their casual speech with their permission. Thirdly, in the process, he gave them separately a list of words and sentences to read, some of which are given below in table (1). In addition, examples will be citied in the analysis from the informants' casual speech when appropriate. It is important to mention that the Jamaican Creole transcriptions in this study are based on Cassidy (1961) and Cassidy and Le Page (1967), and the RP counterparts on Gimson (1980) and Roach (2000). Transcribing and codifying data were done by the researcher himself, then checked by trained transcribers and a phonologist at the University of Bangor, North Wales. Data was coded manually to categorize the pronunciation of the fricative in question in the spontaneous speech and list reading of the subjects. For reference regarding Jamaican talk of the subjects, Cassidy (1961), Cassidy and Le Page (1967), Bailey (1966), and Holm (2000) were consulted. As for the Arabic speakers, the author referred to Basalamah (1990) and to his intuition as a native speaker of the dialect spoken by the Arab subjects. The data displayed in (table 1) and (table 2) below contains information pertaining to the pronunciation of English voiced labio-dental fricative /v/. Table 1. Words pronounced by the barber and the driver in casual speech \| Gloss \| Driver \| Barber \| JC \| RP \| \|---------\|------------\|------------\|------------\|------------\| \| seven \| /se β ˌ m/ \| /se β ˌ m/ \| /se β ˌ m/ \| /seven/ \| \|	[ "age", "of", "18", "and", "his", "reading", "and", "writing", "are", "not", "perfect", ".", "\n\n", "The", " ", "second", " ", "informant", ",", " ", "Mr.", " ", "Norman", " ", "(", "the", " ", "driver", " ", "henceforth", ")", ",", " ", "is", " ", "from", " ", "St.", " ", "Mary", " ", "in", " ", "the", " ", "north", " ", "of", " ", "Jamaica", ".", " ", "He", "migrated", "to", "Britain", "when", "he", "was", "17", ".", "Today", "he", "is", "59", "years", "old", ".", "He", "worked", "in", "two", "factories", "in", "Manchester", ",", "as", "a", "dry", "cleaner", ",", "and", "as", "a", "carpet", "fitter", "before", "he", "became", "a", "taxi", "-", "driver", ",", "which", "is", "his", "present", "job", ".", "He", "also", "studied", "for", "a", 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"speech", "and", "list", "reading", "of", "the", "subjects", ".", "For", "reference", "regarding", "\n\n", "Jamaican", "talk", "of", "the", "subjects", ",", " ", "Cassidy", " ", "(", "1961", ")", ",", " ", "Cassidy", " ", "and", " ", "Le", " ", "Page", " ", "(", "1967", ")", ",", " ", "Bailey", " ", "(", "1966", ")", ",", " ", "and", " ", "Holm", " ", "(", "2000", ")", "were", "consulted", ".", "As", "for", "the", "Arabic", "speakers", ",", "the", "author", "referred", "to", "Basalamah", "(", "1990", ")", "and", "to", "his", "intuition", "as", "a", "native", "speaker", "of", "the", "dialect", "spoken", "by", "the", "Arab", "subjects", ".", "\n\n", "The", " ", "data", " ", "displayed", " ", "in", " ", "(", "table", " ", "1", ")", " ", "and", " ", "(", "table", " ", "2", ")", " ", "below", " ", "contains", " ", "information", " ", "pertaining", " ", "to", " ", "the", " ", "pronunciation", " ", "of", "English", "voiced", "labio", "-", "dental", "fricative", "/v/.", "\n\n", "Table", "1", 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come to the conclusion that many of the features found in Haitian French-lexifier creoles do occur in L2 French and other interlanguages, as a result of L1 transfer and other acquisition processes. The investigation includes word-order within the noun phrase, pronominal clitics, the absence of copula, grammatical gender, and verb movement. The major claim of the model of creole genesis advocated in the study which he calls gradualist/second language acquisition, is that creole genesis does not involve any specific mental processes or strategies other than those attested in ordinary second language acquisition. In Lefebvre et al. (2003), a number of second language researchers and creolists engage in dialogues which focus on the processes characterizing various stages of L2 acquisition and creole genesis, such as relexification and transfer from L1 and their role in the initial state. The dialogues also cover morphological, phonological, semantic and syntactic properties of interlanguage grammar and creole grammars. Their findings lend support to the view that the same processes are found to shape the initial stages of the two situations. ## 3. Current Study This study aims at investigating to what extent the linguistic processes exhibited in the creolization/decreolization parallel those manifested by Mousa's (1994) learners in particular and those of child language and second/foreign language in general. Furthermore, it is assumed that foreign/second language learning, de/creolization and historical change are significantly linked, in such a way that accounting for these learning situations is never precise without historical explanations. Thus, another aim of this study is to see to what extent the behaviour of the speakers of the Board Jamaican Creole and Mousa's learners exhibit facts of historical change. But before embarking on our investigation, introducing the Jamaican informants and the Saudi learners in Mousa's (1994) work is necessary. ## 4. Jamaican Informants The informants are two speakers of what is called the Broad Jamaican Creole (Baily, 1973) of nearly the same age. The first one Mr. Mike (the barber henceforth), is from Hanover in the west of Jamaica. He migrated to Britain when he was 18 years old. Today he is 61 years old. He is a barber in Moss Side, Manchester, England. Most of his customers are West Indies, old and young. He uses the same language (Broad Jamaican Creole) at work, home and everywhere. He is always in touch with the West Indies people. He has little education. 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IV. Selected S&T specialisation domains in ArmeniaIn Armenia, Agrifood correlates highly with the S&T domains Biotechnology and Health and wellbeing, notably in the healthy sweetener industry; ■owing to the country’s hard sciences strengths, the domain Nanotechnology and materials presents a notable critical mass and a rele- vant number of EC projects, with an orienta- tion to fundamental fields (such as Condensed matter, or Electronic, optical and magnetic materials); ■Health and wellbeing presents a large crit- ical mass and specialisation in publications, and important activity in EC projects. The sci- entific publications cluster in the subject field General medicine, followed at a distance by Genetics, Public Health and Biochemistry. Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation17 Azerbaijan – Summary of the strengths of the S&T specialisations Azerbaijan presents a rather diversified S&T pan- orama, but in several S&T domains it is oriented towards the oil and petrochemical industries from a variety of disciplines and technologies. Its most highlighted S&T domains are the following: ■Chemistry and chemical engineering presents a notable critical mass in publica- tions and patents, as well as a high scientif- ic specialisation and citation impact. Highly co-occurrent with Energy and Environmental sciences and industries, Azeri chemistry and chemical engineering is well-aligned with the petrochemical industry, with particular strengths in catalysis and synthesis processes in organic chemistry; ■Energy presents a notable scientific and technological specialisation, as well as a crit- ical mass in patents. In accordance with the country’s Chemistry and chemical engineering acumen, S&T activity in Energy is oriented to- wards the oil and petrochemical industry; ■Mechanical engineering and heavy ma- chinery presents a scientific and technologi- cal specialisation, critical mass in patents and a high scientific citation impact. This domain frequently overlaps with Energy; ■Health and wellbeing presents a high crit- ical mass and specialisation in both publica- tions and patents. The scientific publications cluster in the subject field ‘General medicine’, followed at a distance by ‘Cardiology and car- diovascular medicine’, and patents in the phar- maceutical and medical devices classes (A61). AZERBAIJAN Critical mass Specialisation Excellence Summary S&T domain Pubs. Pat. Pubs. Pat. NCIEC projectsTotal Agrifood 2 Biotechnology 2 Chemistry and chemical engineering4 Energy 4 Environmental sciences and industries1 Fundamental physics and mathematics2 Governance, culture, education and the economy3 Health and wellbeing 4 ICT and computer science 3 Mechanical engineering and heavy machinery4 Nanotechnology and materials 1 Optics and photonics	[ "IV", ".", "Selected", "S&T", "specialisation", "domains", "in", "ArmeniaIn", "Armenia", ",", "Agrifood", "correlates", "highly", "with", "the", "\n", "S&T", "domains", "Biotechnology", "and", "Health", "and", "\n", "wellbeing", ",", "notably", "in", "the", "healthy", "sweetener", "\n", "industry", ";", "\n ", "■", "owing", "to", "the", "country", "’s", "hard", "sciences", "strengths", ",", "\n", "the", "domain", "Nanotechnology", "and", "materials", "\n", "presents", "a", "notable", "critical", "mass", "and", "a", "rele-", "\n", "vant", "number", "of", "EC", "projects", ",", "with", "an", "orienta-", "\n", "tion", "to", "fundamental", "fields", "(", "such", "as", "Condensed", "\n", "matter", ",", "or", "Electronic", ",", "optical", "and", "magnetic", "\n", "materials", ")", ";", "\n ", "■", "Health", "and", "wellbeing", "presents", "a", "large", "crit-", "\n", "ical", "mass", "and", "specialisation", "in", "publications", ",", "\n", "and", "important", "activity", "in", "EC", "projects", ".", "The", "sci-", "\n", "entific", "publications", "cluster", "in", "the", "subject", "field", "\n", "General", "medicine", ",", "followed", "at", "a", "distance", "by", "\n", "Genetics", ",", "Public", "Health", "and", "Biochemistry", ".", "\n", "Smart", "Specialisation", "in", "the", "Eastern", "Partnership", "countries", "-", "Potential", "for", "knowledge", "-", "based", "economic", "cooperation17", "\n", "Azerbaijan", "–", "Summary", "of", "the", "strengths", "\n", "of", "the", "S&T", "specialisations", "\n", "Azerbaijan", "presents", "a", "rather", "diversified", "S&T", "pan-", "\n", "orama", ",", "but", "in", "several", "S&T", "domains", "it", "is", "oriented", "\n", "towards", "the", "oil", "and", "petrochemical", "industries", "from", "\n", "a", "variety", "of", "disciplines", "and", "technologies", ".", "Its", "most", "\n", "highlighted", "S&T", "domains", "are", "the", "following", ":", "\n ", "■", "Chemistry", "and", "chemical", "engineering", "\n", "presents", "a", "notable", "critical", "mass", "in", "publica-", "\n", "tions", "and", "patents", ",", "as", "well", "as", "a", "high", "scientif-", "\n", "ic", "specialisation", "and", "citation", "impact", ".", "Highly", "\n", "co", "-", "occurrent", "with", "Energy", "and", "Environmental", "\n", "sciences", "and", "industries", ",", "Azeri", "chemistry", "and", "\n", "chemical", "engineering", "is", "well", "-", "aligned", "with", "\n", "the", "petrochemical", "industry", ",", "with", "particular", "\n", "strengths", "in", "catalysis", "and", "synthesis", "processes", "\n", "in", "organic", "chemistry", ";", "\n ", "■", "Energy", "presents", "a", "notable", "scientific", "and", "\n", "technological", "specialisation", ",", "as", "well", "as", "a", "crit-", "\n", "ical", "mass", "in", "patents", ".", "In", "accordance", "with", "the", "country", "’s", "Chemistry", "and", "chemical", "engineering", "\n", "acumen", ",", "S&T", "activity", "in", "Energy", "is", "oriented", "to-", "\n", "wards", "the", "oil", "and", "petrochemical", "industry", ";", "\n ", "■", "Mechanical", "engineering", "and", "heavy", "ma-", "\n", "chinery", "presents", "a", "scientific", "and", "technologi-", "\n", "cal", "specialisation", ",", "critical", "mass", "in", "patents", "and", "\n", "a", "high", "scientific", "citation", "impact", ".", "This", "domain", "\n", "frequently", "overlaps", "with", "Energy", ";", "\n ", "■", "Health", "and", "wellbeing", "presents", "a", "high", "crit-", "\n", "ical", "mass", "and", "specialisation", "in", "both", "publica-", "\n", "tions", "and", "patents", ".", "The", "scientific", "publications", "\n", "cluster", "in", "the", "subject", "field", "‘", "General", "medicine", "’", ",", "\n", "followed", "at", "a", "distance", "by", "‘", "Cardiology", "and", "car-", "\n", "diovascular", "medicine", "’", ",", "and", "patents", "in", "the", "phar-", "\n", "maceutical", "and", "medical", "devices", "classes", "(", "A61", ")", ".", "\n ", "AZERBAIJAN", "Critical", "mass", "Specialisation", "Excellence", "Summary", "\n", "S&T", "domain", "Pubs", ".", "Pat", ".", "Pubs", ".", "Pat", ".", "NCIEC", "\n", "projectsTotal", "\n", "Agrifood", "2", "\n", "Biotechnology", "2", "\n", "Chemistry", "and", "chemical", "\n", "engineering4", "\n", "Energy", "4", "\n", "Environmental", "sciences", "and", "\n", "industries1", "\n", "Fundamental", "physics", "and", "\n", "mathematics2", "\n", "Governance", ",", "culture", ",", "education", "\n", "and", "the", "economy3", "\n", "Health", "and", "wellbeing", "4", "\n", "ICT", "and", "computer", "science", "3", "\n", "Mechanical", "engineering", "and", "\n", "heavy", "machinery4", "\n", "Nanotechnology", "and", "materials", "1", "\n", "Optics", "and", "photonics" ]	[]
on current policies, Chinese technology may represent the lowest-cost route to achieving some of these targets. Owing to a fast pace of innovation, low manufacturing costs and state subsidies four times higher than in other major econo - miesiv, the country is now dominating global exports of clean technologies. Significant overcapacity is expected: by 2030 at the latest, China’s annual manufacturing capacity for solar photovoltaic (PV) is expected to be double the level of global demand, and for battery cells it is expected to at least cover the level of global demand. Production of EVs is expanding at a similar pace. The EU is already seeing a sharp deterioration in its trade balance with China, reflecting in particular imports of EVs, batteries and solar PV products [see Figure 3] . While rising bankruptcies in China suggest that the economy is entering a phase of industrial consolidation, overcapacities are likely to persist, especially given ongoing weaknesses in household consumption and high saving rates. Moreover, in response to perceived unfair competition, an increasing number of countries are raising tariff and non-tariff barriers against China, which will re-direct Chinese overcapacity towards the EU market. In May, the US announced significant hikes in tariffs against a range of products. 40THE FUTURE OF EUROPEAN COMPETITIVENESS — PART A \| CHAPTER 3 FIGURE 3 EU trade balance by partner country EUR billion Source: Eurostat, 2024. Europe must confront some fundamental choices about how to pursue its decarbonisation path while preserving the competitive position of its industry . Black-and-white solutions are unlikely to be successful in the European context. Emulating the US approach of systematically shutting out Chinese technology would likely set back the energy transition and therefore impose higher costs on the EU economy. It would also be more costly for Europe to trigger reciprocal tariffs: more than a third of the EU’s manufacturing GDP is absorbed outside the EU, compared with only around a fifth for the USv. However, a laissez-faire approach is also unlikely to succeed in Europe given the threat it could pose to employment, productivity and economic security. According to ECB simulations, if the Chinese EV industry were to follow a similar trajectory of subsidies to that applied in the solar PV industry, EU domestic production of EVs would decline by 70% and EU producers’ global market share would fall by 30 percentage pointsvi. The automotive industry alone employs, directly and indirectly,	[ "on", "current", "\n", "policies", ",", "Chinese", "technology", "may", "represent", "the", "lowest", "-", "cost", "route", "to", "achieving", "some", "of", "these", "targets", ".", "Owing", "to", "a", "\n", "fast", "pace", "of", "innovation", ",", "low", "manufacturing", "costs", "and", "state", "subsidies", "four", "times", "higher", "than", "in", "other", "major", "econo", "-", "\n", "miesiv", ",", "the", "country", "is", "now", "dominating", "global", "exports", "of", "clean", "technologies", ".", "Significant", "overcapacity", "is", "expected", ":", "by", "\n", "2030", "at", "the", "latest", ",", "China", "’s", "annual", "manufacturing", "capacity", "for", "solar", "photovoltaic", "(", "PV", ")", "is", "expected", "to", "be", "double", "the", "\n", "level", "of", "global", "demand", ",", "and", "for", "battery", "cells", "it", "is", "expected", "to", "at", "least", "cover", "the", "level", "of", "global", "demand", ".", "Production", "\n", "of", "EVs", "is", "expanding", "at", "a", "similar", "pace", ".", "The", "EU", "is", "already", "seeing", "a", "sharp", "deterioration", "in", "its", "trade", "balance", "with", "China", ",", "\n", "reflecting", "in", "particular", "imports", "of", "EVs", ",", "batteries", "and", "solar", "PV", "products", "[", "see", "Figure", "3", "]", ".", "While", "rising", "bankruptcies", "in", "\n", "China", "suggest", "that", "the", "economy", "is", "entering", "a", "phase", "of", "industrial", "consolidation", ",", "overcapacities", "are", "likely", "to", "persist", ",", "\n", "especially", "given", "ongoing", "weaknesses", "in", "household", "consumption", "and", "high", "saving", "rates", ".", "Moreover", ",", "in", "response", "to", "\n", "perceived", "unfair", "competition", ",", "an", "increasing", "number", "of", "countries", "are", "raising", "tariff", "and", "non", "-", "tariff", "barriers", "against", "\n", "China", ",", "which", "will", "re", "-", "direct", "Chinese", "overcapacity", "towards", "the", "EU", "market", ".", "In", "May", ",", "the", "US", "announced", "significant", "hikes", "\n", "in", "tariffs", "against", "a", "range", "of", "products", ".", "\n", "40THE", "FUTURE", "OF", "EUROPEAN", "COMPETITIVENESS", " ", "—", "PART", "A", "\|", "CHAPTER", "3", "\n", "FIGURE", "3", "\n", "EU", "trade", "balance", "by", "partner", "country", " \n", "EUR", "billion", "\n", "Source", ":", "Eurostat", ",", "2024", ".", "\n", "Europe", "must", "confront", "some", "fundamental", "choices", "about", "how", "to", "pursue", "its", "decarbonisation", "path", "while", "\n", "preserving", "the", "competitive", "position", "of", "its", "industry", ".", "Black", "-", "and", "-", "white", "solutions", "are", "unlikely", "to", "be", "successful", "in", "\n", "the", "European", "context", ".", "Emulating", "the", "US", "approach", "of", "systematically", "shutting", "out", "Chinese", "technology", "would", "likely", "\n", "set", "back", "the", "energy", "transition", "and", "therefore", "impose", "higher", "costs", "on", "the", "EU", "economy", ".", "It", "would", "also", "be", "more", "costly", "\n", "for", "Europe", "to", "trigger", "reciprocal", "tariffs", ":", "more", "than", "a", "third", "of", "the", "EU", "’s", "manufacturing", "GDP", "is", "absorbed", "outside", "the", "\n", "EU", ",", "compared", "with", "only", "around", "a", "fifth", "for", "the", "USv", ".", "However", ",", "a", "laissez", "-", "faire", "approach", "is", "also", "unlikely", "to", "succeed", "\n", "in", "Europe", "given", "the", "threat", "it", "could", "pose", "to", "employment", ",", "productivity", "and", "economic", "security", ".", "According", "to", "ECB", "\n", "simulations", ",", "if", "the", "Chinese", "EV", "industry", "were", "to", "follow", "a", "similar", "trajectory", "of", "subsidies", "to", "that", "applied", "in", "the", "solar", "PV", "\n", "industry", ",", "EU", "domestic", "production", "of", "EVs", "would", "decline", "by", "70", "%", "and", "EU", "producers", "’", "global", "market", "share", "would", "fall", "\n", "by", "30", "percentage", "pointsvi", ".", "The", "automotive", "industry", "alone", "employs", ",", "directly", "and", "indirectly", "," ]	[ { "end": 246, "label": "CITATION_REF", "start": 244 }, { "end": 2082, "label": "CITATION_REF", "start": 2081 }, { "end": 2515, "label": "CITATION_REF", "start": 2513 }, { "end": 1478, "label": "CITATION_REF", "start": 1464 } ]
7 9 5 11 9 4 10.1 Processing/preserving of meat X X X X X X 10.2 Processing/preserving of fish, etc. X X X 10.3 Processing/preserving of fruit, vegetables X X X X 10.4 Vegetable and animal oils and fats X X X X X X 10.5 Dairy products X X X 10.6Grain mill products, starches and starch products X X X X X X X X X X 10.7 Other food products X X X 10.8 Prepared animal feeds X X X X 11 Beverages X X X X X X X X X X X X 12 Tobacco products X X X X X X 13 Manufacture of textiles X X X X X X X 14 Manufacture of wearing apparel X X X X X X X 15 Manufacture of leather and related products X X X X X X X 16Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials X X X X X X X 17 Manufacture of paper and paper products X X X X X X 18.1Printing and service activities related to printing X X X X X X 18.2 Reproduction of recorded media 19Manufacture of coke and refined petroleum products X X X X 20Manufacture of chemicals and chemical products X X X X X X X X X X 21 Pharmaceuticals, medicinal chemicals, etc. X X X X X X Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation299 300 Annexes ARMENIA AZERBAIJAN GEORGIA MOLDOVA UKRAINEEmploy- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover NACE Industry name Current Emerging Current Emerging Current Emerging Current Emerging Current Emerging 5 5 3 10 8 5 6 5 2 6 11 4 5 8 4 11 5 4 7 10 5 1 7 1 7 9 5 11 9 4 22 Manufacture of rubber and plastic products X X X X X 23Manufacture of other non-metallic mineral 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general revenues and expenditures \| \| Revenues \| Expenditures \| \|----------\|--------------------------------------------------------------------------------\|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\| \| Direct \| Mining revenues derived from the sale of minerals mined from a mining project. \| Prospecting, exploration, and development expenditures are clearly attributed to a specific mining project. For instance, the depreciation associated with a drill rig used only for a specific mining project. \| \| Indirect \| Income from the sale of a drilling rig previously used for more than one mine. \| Continuing the drilling example, assuming that the drilling rig is used during the taxable year for two or more licence areas, the costs will need to be allocated to more than one licence area where it was actually used. \| \| General \| Income earned from interest on current account bank deposit. \| Management and administration expenditures, human resource expenditures, expenses related to the operation of internal information technology systems, overhead costs. \| Source: Author's elaboration. ## 5.2.2 A Method for Apportioning All Indirect and General Expenditures and Revenues Direct revenues and expenditures should be attributed in full to the specific licence area or business activities to which they relate. Indirect and general revenues and expenditures, however, are not directly attributable to a specific licence area or may relate to different business activities carried out by the same enterprise, which creates apportionment challenges. For instance, it can be difficult to apportion - · revenues derived from ore from differing licence areas where these are mixed during the processing stage to produce one product, - · revenues from raw materials versus processed goods or revenues from mining versus manufacturing activities, - · expenditures related to staff involved in more than one licence area/ business activity, - · expenditures related to equipment used for different mines/business activities, and - · financing costs incurred while borrowing funds to expand different mining projects/business activities. ## 1.0 INTRODUCTION 2.0 THE FUNDAMENTALS OF RING-FENCING 3.0 THE BENEFITS AND RISKS OF RING-FENCING 4.0 DESIGNING RING-FENCING RULES 5.0 THE IMPLEMENTATION OF RING-FENCING RULES 6.0 CONCLUSION Different allocation methods are used to apportion general and indirect expenditures and revenues. Direct and indirect methods could be applied depending on the materiality of the revenues and expenditures. The significance and materiality of the relevant expenditure could be considered when setting up specific tracking or tracing requirements, rather than relying on simplification approaches based on a proxy allocation rule, such as the CapEx expenditure mentioned	[ "general", "revenues", "and", "expenditures", "\n\n", "\|", " ", "\|", "Revenues", " ", "\|", "Expenditures", " ", "\|", "\n", "\|----------\|--------------------------------------------------------------------------------\|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\|", "\n", "\|", "Direct", " ", "\|", "Mining", "revenues", "derived", "from", "the", "sale", "of", "minerals", "mined", "from", "a", "mining", "project", ".", "\|", "Prospecting", ",", "exploration", ",", "and", "development", "expenditures", "are", "clearly", "attributed", "to", "a", "specific", "mining", "project", ".", "For", "instance", ",", "the", "depreciation", "associated", "with", "a", "drill", "rig", "used", "only", "for", "a", "specific", "mining", "project", ".", " ", "\|", "\n", "\|", "Indirect", "\|", "Income", "from", "the", "sale", "of", "a", "drilling", "rig", "previously", "used", "for", "more", "than", "one", "mine", ".", "\|", "Continuing", "the", "drilling", "example", ",", "assuming", "that", "the", "drilling", "rig", "is", "used", "during", "the", "taxable", "year", "for", "two", "or", "more", "licence", "areas", ",", "the", "costs", "will", "need", "to", "be", "allocated", "to", "more", "than", "one", "licence", "area", "where", "it", "was", "actually", "used", ".", "\|", "\n", "\|", "General", " ", "\|", "Income", "earned", "from", "interest", "on", "current", "account", "bank", "deposit", ".", " ", "\|", "Management", "and", "administration", "expenditures", ",", "human", "resource", "expenditures", ",", "expenses", "related", "to", "the", "operation", "of", "internal", "information", "technology", "systems", ",", "overhead", "costs", ".", " ", "\|", "\n\n", "Source", ":", "Author", "'s", "elaboration", ".", "\n\n", "#", "#", "5.2.2", "A", "Method", "for", "Apportioning", "All", "Indirect", "and", "General", "Expenditures", "and", "Revenues", "\n\n", "Direct", "revenues", "and", "expenditures", "should", "be", "attributed", "in", "full", "to", "the", "specific", "licence", "area", "or", "business", "activities", "to", "which", "they", "relate", ".", "Indirect", "and", "general", "revenues", "and", "expenditures", ",", "however", ",", "are", "not", "directly", "attributable", "to", "a", "specific", "licence", "area", "or", "may", "relate", "to", "different", "business", "activities", "carried", "out", "by", "the", "same", "enterprise", ",", "which", "creates", "apportionment", "challenges", ".", "For", "instance", ",", "it", "can", "be", "difficult", "to", "apportion", "\n\n", "-", "·", "revenues", "derived", "from", "ore", "from", "differing", "licence", "areas", "where", "these", "are", "mixed", "during", "the", "processing", "stage", "to", "produce", "one", "product", ",", "\n", "-", "·", "revenues", "from", "raw", "materials", "versus", "processed", "goods", "or", "revenues", "from", "mining", "versus", "manufacturing", "activities", ",", "\n", "-", "·", "expenditures", "related", "to", "staff", "involved", "in", "more", "than", "one", "licence", "area/", "business", "activity", ",", "\n", "-", "·", "expenditures", "related", "to", "equipment", "used", "for", "different", "mines", "/", "business", "activities", ",", "and", "\n", "-", "·", "financing", "costs", "incurred", "while", "borrowing", "funds", "to", "expand", "different", "mining", "projects", "/", "business", "activities", ".", "\n\n", "#", "#", "1.0", "INTRODUCTION", "\n\n", "2.0", "THE", "FUNDAMENTALS", "OF", "RING", "-", "FENCING", "\n\n", "3.0", "THE", "BENEFITS", "AND", "RISKS", "OF", "RING", "-", "FENCING", "\n\n", "4.0", "DESIGNING", "RING", "-", "FENCING", "RULES", "\n\n", "5.0", "THE", "IMPLEMENTATION", "OF", "RING", "-", "FENCING", "RULES", "\n\n", "6.0", "CONCLUSION", "\n\n", "Different", "allocation", "methods", "are", "used", "to", "apportion", "general", "and", "indirect", "expenditures", "and", "revenues", ".", "Direct", "and", "indirect", "methods", "could", "be", "applied", "depending", "on", "the", "materiality", "of", "the", "revenues", "and", "expenditures", ".", "The", "significance", "and", "materiality", "of", "the", "relevant", "expenditure", "could", "be", "considered", "when", "setting", "up", "specific", "tracking", "or", "tracing", "requirements", ",", "rather", "than", "relying", "on", "simplification", "approaches", "based", "on", "a", "proxy", "allocation", "rule", ",", "such", "as", "the", "CapEx", "expenditure", "mentioned" ]	[]
The report also indicates the evidence-informed areas for knowledge-based economic cooperation to support bilateral and region-wide initiatives. 2 Executive summary covery, resilience and reform: post 2020 Eastern Partnership priorities’4. The S3 Framework was developed at the request of EU Enlargement and Neighbourhood economies that voluntarily took on the development of Smart Specialisation Strategies in different administra- tive, institutional and political contexts. It oper- ationalises the guidance offered to EU Member States into a set of practical steps, but also adapts and adjusts the approach to suit non-EU countries. Starting from the first phase of 1 institution- al capacity building (Decision to start S3 Pro- cess) to the second 2 institutional capacity building (Analysis of the Strategic mandates), it continues with the mapping phases through steps 3diagnosis (Quantitative mapping) and 4 diagnosis (Qualitative mapping). The next steps include engaging in 5 stakeholder dialogue, developing the 6 institutional capacity for implementation and, finally, 7 drafting the strategy (see the figure below). This study aims to offer a solid basis for the Smart Specialisation process by offering an extensive quantitative analysis of national-level potential in the economy, innovation, science and technology based on available international data. This effort, amongst others, is part of the targeted support 4 SWD(2021) 186 final, 2.7.2021.EXECUTIVE SUMMARY Most Eastern Partnership countries have com- mitted to developing their Smart Specialisa- tion Strategies based on the Smart Specialisation Framework for EU Enlargement and Neighbour- hood Region (S3 Framework)2, developed by the JRC in cooperation with partner countries, inter- national experts and policy directorates of the European Commission. The application of this EU- made innovation policy concept will allow Eastern Partners to promote knowledge-based economic development and targeted research and innova- tion policies building on territorial specificities, unique potentials and emerging niches. This ef- fort has been recognised in the 2020 European Commission’s Joint Communication: ‘Eastern Partnership policy beyond 2020: Reinforcing Re- silience – an Eastern Partnership that delivers for all’3 and the Joint Staff Working Document ‘Re- 2 Matusiak, M., Kleibrink, A. (ed.), Supporting an Inno- vation Agenda for the Western Balkans – Tools and Methodologies, Publications Office of the European Un- ion, Luxembourg, 2018, ISBN 978-92-79-81870-7, doi:10.2760/48162, JRC111430. 3 https://eeas.europa.eu/sites/default/files/1_en_act_ part1_v6.pdf. 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can also facilitate favorable capital market and invest - ment conditions and foster GDP growth.107 Finally, international cooperation can boost statistical inde-pendence and data transparency when adherence to standards of data quality and the independence of their producers is required for accession to interna-tional organizations or agreements. An example is Colombia’s successful bid to join the Organisation for Economic Co-operation and Development (OECD). 108 Civil society performs a vital function in demand- ing transparency and holding government account - able. Citizen-generated data can be used to challenge official statistics when their accuracy or impartiality are in question. A free and empowered press is a Figure 2.9 Greater NSO independence and freedom of the press are positively correlated with better statistical performance Sources: NSO independence score: Mo Ibrahim Foundation, Ibrahim Index of African Governance (database), http://mo.ibrahim.foundation/iiag/; World Press Freedom Index: Reporters Without Borders, 2020 World Press Freedom Index (database), https://rsf.org/en/ranking_table. Data at http://bit.do/WDR2021-Fig-2_9. Note: The x’s represent countries. Panel a shows only African countries, and panel b shows all countries with data available. The NSO independence score ranges from 0 to 100. The World Press Freedom Index ranges from 100 to 0—lower values imply greater press freedom.	[ "can", "also", "facilitate", "favorable", "capital", "market", "and", "invest", "-", "\n", "ment", "conditions", "and", "foster", "GDP", "growth.107", "Finally", ",", "\n", "international", "cooperation", "can", "boost", "statistical", "inde", "-", "pendence", "and", "data", "transparency", "when", "adherence", "to", "standards", "of", "data", "quality", "and", "the", "independence", "of", "their", "producers", "is", "required", "for", "accession", "to", "interna", "-", "tional", "organizations", "or", "agreements", ".", "An", "example", "is", "Colombia", "’s", "successful", "bid", "to", "join", "the", "Organisation", "for", "Economic", "Co", "-", "operation", "and", "Development", "(", "OECD", ")", ".", "\n", "108", "\n", "Civil", "society", "performs", "a", "vital", "function", "in", "demand-", "\n", "ing", "transparency", "and", "holding", "government", "account", "-", "\n", "able", ".", "Citizen", "-", "generated", "data", "can", "be", "used", "to", "challenge", "official", "statistics", "when", "their", "accuracy", "or", "impartiality", "are", "in", "question", ".", "A", "free", "and", "empowered", "press", "is", "a", "Figure", "2.9", " ", "Greater", "NSO", "independence", "and", "freedom", "of", "the", "press", "are", "positively", "correlated", "with", "\n", "better", "statistical", "performance", "\n", "Sources", ":", "NSO", "independence", "score", ":", "Mo", "Ibrahim", "Foundation", ",", "Ibrahim", "Index", "of", "African", "Governance", "(", "database", ")", ",", "http://mo.ibrahim.foundation/iiag/", ";", "World", "Press", "Freedom", "Index", ":", "Reporters", "\n", "Without", "Borders", ",", "2020", "World", "Press", "Freedom", "Index", "(", "database", ")", ",", "https://rsf.org/en/ranking_table", ".", "Data", "at", "http://bit.do/WDR2021-Fig-2_9", ".", "\n", "Note", ":", "The", "x", "’s", "represent", "countries", ".", "Panel", "a", "shows", "only", "African", "countries", ",", "and", "panel", "b", "shows", "all", "countries", "with", "data", "available", ".", "The", "NSO", "independence", "score", "ranges", "from", "0", "to", "100", ".", "The", "\n", "World", "Press", "Freedom", "Index", "ranges", "from", "100", "to", "0", "—", "lower", "values", "imply", "greater", "press", "freedom", "." ]	[ { "end": 1164, "label": "CITATION_SPAN", "start": 863 } ]
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intent is grounded in the real world the speaker and listener inhabit together. Commu- nicative intents can also be about abstract worlds, e.g. bank accounts, computer ﬁle systems, or a purely hypothetical world in the speaker’s mind. Linguists distinguish communicative intent from conventional (orstanding ) meaning (Quine, 1960; Grice, 1968). The conventional meaning of an expression (word, phrase, sentence) is what is con- stant across all of its possible contexts of use. Con- ventional meaning is an abstract object that repre- sents the communicative potential of a form, given the linguistic system it is drawn from. Each lin- guistic system (say, English) provides a relation CES, which contains pairs (e; s)of expres- sions eand their conventional meanings s.6The ﬁeld of linguistic semantics provides many com- peting theories of what conventional meanings s look like. For our purposes, we don’t need to select among these theories; all we assume is that conven- tional meanings must have interpretations, such as a means of testing them for truth against a model of the world. Thus, like the meaning relation M,C connects language to objects outside of language. 5In spoken languages, the primary articulators are the com- ponents of the vocal tract. In signed languages, they are principally the hands and face. 6We abstract away here from the facts that linguistic sys- temsCchange over time and are only incompletely shared among different speakers. They are stable enough to function as rich signals to communicative intent.Returning to the meaning relation Mfrom above, it is best understood as mediated by the relation C of a linguistic system shared between two inter- locutors. The speaker has a certain communica- tive intent i, and chooses an expression ewith a standing meaning swhich is ﬁt to express iin the current communicative situation. Upon hearing e, the listener then reconstructs sand uses their own knowledge of the communicative situation and their hypotheses about the speaker’s state of mind and intention in an attempt to deduce i. This active participation of the listener is cru- cial to human communication (Reddy, 1979; Clark, 1996). For example, to make sense of (8) and (9) (from Clark, 1996, p.144), the listener has to calcu- late that Napoleon refers to a speciﬁc pose (hand inside coat ﬂap) or that China trip refers to a person who has recently traveled to China. (8) The photographer asked me to do a Napoleon for the camera. (9) Never

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prose. (Gary Marcus) (5) Though BERT passed the lab’s common-sense test, ma- chines are still a long way from an artiﬁcial version of a human’s common sense. (Oren Etzioni) However, there are plenty of instances where the popular press gets it wrong, such as (6) from the B2C website,2apparently based on the Google Blog post about BERT and search, which includes numerous statements like (7).3 (6) BERT is a system by which Google’s algorithm uses pattern recognition to better understand how human beings communicate so that it can return more relevant results for users. (7) Here are some of the examples that showed up our evaluation process that demonstrate BERTs ability to understand the intent behind your search. In sum, it is not clear from our academic literature whether all authors are clear on the distinction be- tween form and meaning, but it is clear that the way we speak about what neural LMs are doing is misleading to the public. Part of the reason for this tendency to use impre- cise language may well be that we do not yet fully understand what exactly it is about language that the large LMs come to implicitly represent. Their success, however, has sparked a subﬁeld (‘BERTol- ogy’) that aims to answer this question. The methodology of probing tasks (e.g. Adi et al., 2017; Ettinger et al., 2018) has been used to show that 1https://www.nytimes.com/2018/11/18/technology/artific ial-intelligence-language.html, accessed 2019/12/04 2https://www.business2community.com/seo/what-t o-do-about-bert-googles-recent-local-algorithm-updat e-02259261, accessed 2019/12/04 3https://www.blog.google/products/search/search-langu age-understanding-bert/, accessed 2019/12/04large LMs learn at least some information about phenomena such as English subject-verb agreement (Goldberg, 2019; Jawahar et al., 2019), constituent types, dependency labels, NER, and (core) seman- tic role types (again, all in English) (Tenney et al., 2019).4Hewitt and Manning (2019) ﬁnd informa- tion analogous to unlabeled dependency structures in the word vectors provided by ELMo and BERT (trained on English). And of course it is well estab- lished that vector-space representations of words pick up word classes, both syntactic (POS, e.g. Lin et al., 2015) and semantic (lexical similarity, e.g. Rubenstein and Goodenough, 1965; Mikolov et al., 2013). Others have looked more closely at the success of the large LMs on apparently meaning sensitive tasks and found that in fact, far from doing the “rea- soning” ostensibly required to complete the tasks, they were instead simply more effective at leverag- ing artifacts in the data than previous approaches. Niven and Kao (2019) ﬁnd that

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frameworks and regulations. Only half of countries have standards for school principals that explicitly address collaboration. | School principals are expected to fulfil various leadership roles .....................................25 | |-------------------------------------------------------------------------------------------------------------------------------------------------------| | The impact of school principals can be significant...............................................................31 | | Leadership standards can guide action and certification...................................................39 | | Conclusion ........................................................................................................................................42 | S chool leadership involves steering educational institutions to achieve their goals, such as improving student learning and fostering a positive school environment (UNESCO, 2018). School principals bear responsibilities such as shaping an educational vision, aligning teaching practices with standards and student needs, encouraging professional development and collaboration, and ensuring student well-being and safety. Such responsibilities require them to both manage and lead under resource constraints and frequent education policy shifts. Principals have to address the needs of diverse student populations; respond to the exigencies of digital technology (UNESCO, 2023b); and deal with emergencies such as displacement (UNESCO, 2019), natural disasters and health crises like COVID-19 (Longmuir, 2023). They need to deal with community expectations and navigate accountability pressures (Lee, 2016). In some contexts, decentralized arrangements empower principals to take the action they deem appropriate to address problems. Principals also increasingly have access to better management tools, regulatory frameworks and communication channels. These resources can develop their capacity to build trust and effective collaborative relationships with staff, students, parents and community stakeholders for joint action (UNESCO, 2023a). This chapter examines principals' roles, with an emphasis on primary and secondary education. The term 'principal' refers to the individual responsible for leading a school, either independently or within an administrative organization like a board or council, overseeing its guidance, organization and operation ( Box 2.1 ). Their roles are generally described as expectations, which are outlined in various government texts. The chapter also examines the impact principals have on educational outcomes and how this is mediated by individual and governance characteristics. Finally, the chapter looks at how this understanding is being codified in leadership standards. ## SCHOOL PRINCIPALS ARE EXPECTED TO FULFIL VARIOUS LEADERSHIP ROLES Principals have historically been seen mainly as administrators focused on tasks like setting budgets and timetables. But they are increasingly expected to take on roles with broader impact. This section focuses on four key roles: set a vision, lead instruction, foster collaboration and support teachers to improve school outcomes (Bush, 2008; Hallinger and Kovačević, 2019).  School principals are increasingly expected to take on

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deviation of the distribution of the number of records in that domain. This facilitates the identification of niches where there is clear alignment with NACE codes between S&T domains (for relative frequencies close to and above 100%, such as Agrifood with NACE code 10 ‘Manufacture of food products’), in relation to mappings where S&T production is more evenly spread. As shown in Annex 1, the IPC to NACE v2 concordance table contains mappings 72 An IPC symbol is the specific full taxonomic classification associated with a patent record.at different granularity levels, namely two-digit and three-digit NACE codes. Thus, no proper con- cordance table-based mapping between the final two-digit summary results of Part 2, on one side, and the IPC patent classification, on the other, can be fully produced. The results of the S&T domains to NACE mapping carried out via patents is presented in Annex 8 for each EaP country. On expert assessment, the results of this mapping exercise as expressed by pairs of S&T domains and two-digit NACE codes seems satisfactory. The presence of multiple assignations, that is, the appearance of a given NACE code in several S&T specialisation domains, as well as some low rel- ative frequency figures, are an indication of the natural transversality of and/or overlap between some S&T domains, which have the potential to impact knowledge-based development in several sectors. Steps 3-5 – Quantified mapping of S&T domains to E&I domains, via scientific publications In the work presented in Part 3, EaP scientific publications were semantically analysed, togeth- er with patents and Horizon 2020 projects, and classified into a list of 14 S&T domains, which emerged directly from the textual content of the analysed records via topic modelling. Here, the taxonomic classification of publications (by far the largest data set analysed in this work) via ASJC subject fields (ASJC – All Science Journal Classification, the taxonomy adopted by Elsevi- er’s Scopus) is exploited to find a link between the S&T domains uncovered in Part 2 and the NACE sectors which underpin the E&I domains identified in Part 2. To do so, ASJC subject fields were first mapped to NABS and then official NABS to NACE concordance tables were exploited to achieve the ASJC to NACE proposed mapping. The NABS to NACE concordance table is presented in Annex 2. As only first-level NABS are mapped to NACE sectors – while Scopus ASJC fields are mapped to

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Official data on road traffic crashes capture only 56 percent of fatal-ities in low- and middle-income countries, on average. 1 Crash reports exist, yet they are buried in piles of paper or collected by private operators instead of being converted into useful data or disseminated to the people who need the information to make policy decisions. In Kenya, where official figures under - report the number of fatalities b y a factor of 4.5,2 the rapid expansion of mobile phones and social media provides an opportunity to leverage commuter reports on traffic conditions as a potential source of data on road traffic crashes. Big data mining, combined with digitization of official paper records, has demonstrated how dispa-rate data can be leveraged to inform urban spatial analysis, planning, and management. 3 Researchers worked in close collaboration with the National Police Service to digitize more than 10,000 situation reports spanning from 2013 to 2020 from the 14 police stations in Nairobi to create the first digital and geolocated administrative dataset of individual crashes in the city. They combined administrative data with data crowdsourced using a software appli-cation for mobile devices and short message service (SMS) traffic platform, Ma3Route, which has more than 1.1 million subscribers in Kenya. They analyzed 870,000 transport-related tweets submitted between 2012 and 2020 to identify and geolocate 36,428 crash reports by developing and improving natural lan-guage processing and geoparsing algorithms. 4 To verify the accuracy of crowdsourced reports and the efficiency of the algorithms, the team dis-patched a motorcycle delivery company to the site of the reported crash minutes after each new crash report was received for a subset of reports. In 92 per - cent of cases, a crash was verified to have occurred in the stated location or nearby. By combining these sources of data, researchers were able to identify the 5 percent of roads (crash black spots) where 50 percent of the road traffic deaths occur in the city (map S4.2.1). This exercise demonstrates that addressing data scarcity can transform an intractable problem into a more manageable one. In this case, investing in the safety of a 6,200-kilometer road network is intractable. Digitiz-ing and analyzing administrative data and variables on injuries and deaths can help to narrow down the locations and times of the day and week that are associated with the most severe crashes. The analysis offers an invaluable road map for future regulation,

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this volume). Political activism - in Maasdorp's case, joining the Cambridge Socialist Society and the Cambridge Scientists' Anti- War Group - was not only a way to compensate for her invisibility and lack of recognition in professional science, but also an attempt to shape the political foundations of science. As Keeble explains, 'lateral thinking', that is, the practice of investigating alternative scientific roles ascribed to or assumed by women, as science educators, members of scientific organizations, and voluntary, unpaid scientific workers, is essential to recovering hidden historical figures like Maasdorp. This must, however, be coupled with a recognition of the fact that, as a member of the white colonial elite in South Africa and Rhodesia, Maasdorp was nevertheless able to acquire a certain degree of visibility that was systematically denied to Black women. Nuala Proinnseas Caomhánach's discussion of Lynn Margulis' scientific career as a 'rebel' evolutionary biologist further illuminates the struggles women faced inside and outside the laboratory and testifies to their willingness to challenge disciplinary and patriarchal boundaries. Combining insights from cell biology, ecology and geoscience, Margulis' much- maligned theory of evolution was as synthetic in its origin as the idea it propagated, namely that evolution had begun with microbes, not animals, and that symbiosis, not competition, had been its driving force. Although Margulis did manage to forge a relatively successful career in academia, her visibility was predicated on her ability to leverage the power of media and navigate all the risks such a process of exposure involved. As Caomhánach cogently points out, 'without the making of a persona, the scientist remains obscure and invisible'. In the case of women scientists - Rosalind Franklin being another xample - that invisibility was not only 'ascribed' by men, but it was also e sometimes 'curated' by them. The construction of a scientific persona in Margulis' case must also be seen against the background of American media's growing concern with science reporting in the 1960s- 1970s. As Caomhánach discusses, the process of becoming visible involved several layers of 'de- gendering' and 're- gendering'. Media reporting on Margulis replicated entrenched gender biases by attaching non- scientific attributes to her. Dismissed as a theorist because she was a woman, she eventually 'gain[ed] acceptance and … inclusion in the field' because of her image as a masculinized scientific rebel. The point then is that Margulis was able to control her image as an 'outsider' and

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[]

Western notion of knowledge as abstract, objective and detached from the lived experiences of individuals. As argued by Solney Rolnik: The main operation of Western modernity culture, including colonialism, most important and most successful micro-political operation is the anaesthesia of the knowing body: the anaesthesia of this capacity to be affected by the world, as a field of forces, and this obstruction of our access to sensations, to tension, in order to affirm the ethical, political function of thought.² ⁵ ## Against this backdrop, Shahjahan argues that: Bringing awareness to our bodies helps us acknowledge and dismantle hegemonic knowledge systems that privilege the mind. Reconnecting to our bodies provides us a different locus of articulation for our theories and experiences. Furthermore, acknowledging our bodies helps us bridge theory and practice.² ⁶ The question that arose within Common Ground was thus: How do we restore the feeling body as the knowing body? How could we enact this idea of the body as a bridge between theory and practice? By developing activities and exercises within the Common Ground program, we tried to anchor the ideas and theories at the heart of our reflections in the body s ' experience in order to truly incarnate 24 Kimmerer (2013). 25 Guggenheim New York (2015). 26 Shahjahan (2014). Being ' lazy ' and slowing down: Toward decolonizing time, our body, and pedagogy (p. 489). other ways of relating to the living and to each other. In this way, we sought to propose activities that encouraged a different way of paying attention to the world and to others. Throughout the first, online phase of the program, participants were given embodied and creative exercises called ' instructions ' that were designed to prepare them for the session ahead. Based on the principle of instructions performed by artists such as Yoko Ono or Marina Abramovic, these exercises aimed to disrupt the normal order of things, question our ways of relating to our bodies and our environment, and invite the senses and the imagination into the learning process to explore the themes addressed during the sessions. During the second and third phases, which started with the CHC weekend, centering the body became a key aspect of the collective process. Common Ground s methodology ' therefore aimed to invite participants, in their own bodies and in the environment around them, to share moments of play as a means of creating

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rules were viewed as being restrictive to new investment, other factors-such as the lack of new major mineral discoveries, the decline in the global gold industry, and the political instability that preceded South Africa's independence-also might have encouraged disinvestment. ## PNG In 2002, when mineral prices were near record lows, PNG's mining fiscal regime was reviewed with the intention of attracting investment. The PNG Income Tax Act was amended to introduce relaxation rules for ring-fencing. Specifically, PNG allowed a tax deduction of up to 25% of allowable exploration expenditures undertaken outside the producing mine. 16 Other changes include more attractive accelerated depreciation arrangements and the elimination of loss carry forward time limits (Hogan & Goldsworthy, 2010). Neither South Africa nor PNG saw fit to suspend their ring-fencing rules. Instead, they modified them to rebalance the policy objectives of securing early revenues, protecting their tax base on the one hand, and attracting and maintaining mining investment on the other. 16 See, for example, Department of Petroleum and Energy, Petroleum Division (2005). 1.0 INTRODUCTION 2.0 THE FUNDAMENTALS OF RING-FENCING ## 3.0 THE BENEFITS AND RISKS OF RING-FENCING 4.0 DESIGNING RING-FENCING RULES 5.0 THE IMPLEMENTATION OF RING-FENCING RULES 6.0 CONCLUSION ## 3.2.2 Ring-Fencing May Make It Harder for an Investor to Attract Capital Mining is a highly capital-intensive industry. As such, significant upfront finance during the exploration and development phases and additional funding throughout the mine's life are required to maintain operations and fund expansions. Mining investors may look to raise funds through debt or equity, depending on the stage and risk profile of the project, as well as the creditworthiness of the taxpayer (IGF & OECD, 2017b). A good cashflow position and lower tax costs can enhance the after-tax profitability-and thus creditworthiness-of a specific project and can also make it more attractive for equity investment. Ring-fencing rules may have a negative impact on this fundraising capability since they may accelerate tax payments. ## 3.2.3 Under Ring-Fencing, Mining Investors May Register Permanent Losses Mining typically requires substantial upfront expenditures during the exploration and development phases, as well as additional investments throughout the mine's life to maintain operations and fund expansions (IGF & OECD, 2017a, p. 17). Exploration and development expenditures, including additional investments, can be costly. Only a small percentage of exploration projects are successful: 'It takes 500-1,000 grassroots exploration projects to identify 100 targets for advanced exploration, which in turn lead to

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"*Lan A, Kotler D, Kronfeld-Schor N, Stukalin Y, Einat H (Jan 2022; Online ahead of print) Changes in sleep patterns of college students in Israel during COVID-19 lockdown, a sleep diaries study. Sleep and Biological Rhythms *Bilu C, Frolinger-Ashkenazy T, Einat H, Zimmet P, Bishko Y, Halperin D, Kronfeld-Schor N (Nov 2021; Online ahead of print) Effects of photoperiod and diet on BDNF daily rhythms in diurnal sand rats. Behavioural Brain Research 418 113666 *Oved S, Mofaz M, Lan A, Einat H, Kronfeld-Schor N, Yamin D, Shmueli E (June 2021) Differential effects of COVID-19 lockdowns on well-being: interaction between age, gender and chronotype. Journal of the Royal Society Interface 18(179):20210078 *Kazavchinsky L, Dahan S, Einat H (Nov 2020) Exploring test batteries for affective- and anxiety-like behaviors in female and male ICR and black Swiss mice. Acta Neuropsychiatrica. 32:293-302 *Stukalin Y, Lan A, Einat H (2020) Revisiting the validity of the mouse tail suspension test: Systematic review and meta-analysis of the effects of prototypic antidepressants. Neuroscience and Biobehavioral Reviews. 112:39-47 " "• Petrache, A.L., Khan, A.A., Nicholson, M.W., Monaco, A., Kuta-Siejkowska, M., Haider, S., ...Ali, A. (2020). Selective modulation of α5 GABAA receptors exacerbates aberrant inhibition at key hippocampal neuronal circuits in APP mouse model of Alzheimer’s disease. Front. Cell. Neurosci., https://doi.org/10.3389 • Petrache, A.L., Rajulawalla, A., Shi, A., Wetzel, A., Saito, T., Saido, T.C., ...Ali, A. (2019). Aberrant Excitatory-Inhibitory Synaptic Mechanisms in Entorhinal Cortex Microcircuits during the Pathogenesis of Alzheimer’s disease. Cerebral Cortex, doi:10.1093/cercor/bhz016 • Shi, A., Petrache, A.L., Shi, J., Ali, A. (2019). Preserved Calretinin interneurons in an app model of Alzheimer’s Disease disrupts hippocampal inhibition via up-regulated P2Y1 purinoreceptors. Cerebral Cortex, doi:10.1093/cercor/bhz165 • Khan, A., Shekh-Ahmad, T., Khalilova, A., Walker, M., Ali, A.B. (2018). Cannabidiol exerts antiepileptic effects by restoring hippocampal interneuron functions in a temporal lobe epilepsy model. British Journal of Pharmacology, • Nicholson, M.W., Sweeney, A., Pekle, E., Alam, S., Ali, A.B., Duchen, M., Jovanovic, J.N. (2018). Diazepam-induced loss of inhibitory synapses mediated by PLCδ/ Ca²⁺/calcineurin signalling downstream of GABAA receptors. Molecular Psychiatry, doi:10.1038/s41380-018-0100-y " "Craig, L., Hoo, Z. L., Yan, T. Z., Wardlaw, J. and Quinn, T. J. (2022) Prevalence of dementia in ischaemic or mixed stroke populations: systematic review and meta-analysis. Journal of Neurology, Neurosurgery and Psychiatry, 93(2), pp. 180-187. (doi: 10.1136/jnnp-2020-325796) (PMID:34782389) Burton, J. K. et al. (2021) Non-pharmacological interventions for preventing delirium in hospitalised non-ICU patients. Cochrane Database of Systematic Reviews, 2021(11), CD013307. (doi: 10.1002/14651858.CD013307.pub3) (PMID:34826144)

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Full text Bravo A.; Accuosto P.; Saggion H.. LaSTUS-TALN at IberLEF 2019 eHealth-KD challenge deep learning approaches to information extraction in biomedical texts . CEUR Workshop Proceedings 2019; 2421: 51-59. Chiruzzo L.; AbuRa''ed A.; Bravo A.; Saggion H.. LaSTUS-TALN+INCO @ CL-SciSumm 2019 . CEUR Workshop Proceedings 2019; 2414: 224-232. Goularte F.B.; Nassar S.M.; Fileto R.; Saggion H.. A text summarization method based on fuzzy rules and applicable to automated assessment . Expert Systems with Applications 2019; 115: 264-275. Publication link Porcaro L.; Saggion H.. Recognizing musical entities in user-generated content . Computacion y Sistemas 2019; 23(3): 1079-1088. Publication link Full text Other resources Štajner S.; Saggion H.; Ponzetto S.P.. Improving lexical coverage of text simplification systems for Spanish . Expert Systems with Applications 2019; 118: 80-91. Publication link Full text Abura¿ed A.; Bravo A.; Chiruzzo L.; Saggion H.. LaSTUS/TALN+INCO @ CL-SciSumm 2018 - Using regression and convolutions for cross-document semantic linking and summarization of scholarly literature . CEUR Workshop Proceedings 2018; (2132): 150-163. Full text Accuosto P.; Saggion H.. Improving the accessibility of biomedical texts by semantic enrichment and definition expansion . Procesamiento del Lenguaje Natural 2018; 61. Publication link Full text Agerri R.; Bel N.; Rigau G.; Saggion H.. TUNER: Multifaceted domain adaptation for advanced textual semantic processing. First results available . Procesamiento del Lenguaje Natural 2018; 61: 163-166. Publication link Full text Barbieri F.; Marujo L.s.; Karuturi P.; Brendel W.; Saggion H.. Exploring emoji usage and prediction through a temporal variation lens . CEUR Workshop Proceedings 2018; 2130. Hernández I, Tello J, Belda C, Ureña A, Salcedo I, Espinosa L, Saggion H Saggion. Savana: Re-using Electronic Health Records with Artificial Intelligence . International Journal of Interactive Multimedia and Artificial Intelligence 2018; 4(7): 8-12. Abura'ed A, Chiruzzo L, Saggion H, Accuosto P, Bravo A. LaSTUS/TALN @ CLSciSumm-17: Cross-document sentence matching and scientific text summarization systems . CEUR Workshop Proceedings 2017; 2002(0): 55-66. AbuRa'ed, Ahmed; Chiruzzo, Luis; Saggion, Horacio; Accuosto, Pablo; Bravo Serrano, Àlex. LaSTUS/TALN @ CLSciSumm-17: cross-document sentence matching and scientific text summarization systems . ACM SIGIR Forum 2017. Full text Codina-Filba J.; Bouayad-Agha N.; Burga A.; Casamayor G.; Mille S.; Muller A.; Saggion H.; Wanner L.. Using genre-specific features for patent summaries . Information processing & management 2017; 53(1): 151-174. Publication link Full text Espinosa-Anke L.; Oramas S.; Saggion H.; Serra X.. ELMDist: A Vector Space Model with Words and MusicBrainz Entities . Lecture Notes in Computer Science 2017; 10577 LNCS(0): 355-366.

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Fuest, C., Gros, D., Mengel, P.-L., Presidente, G., and Tirole, J., ‘ How to Escape the Middle Technology Trap: EU Innovation Policy ’, EconPol Policy Report, 2024. ix Myers, K. and Lanahan, L., ‘ Estimating Spillovers from Publicly Funded R&D: Evidence from the US Department of Energy ’, American Economic Review, Vol. 112, No. 7, July 2022. x Testa, G., Compano, R., Correia, A. and Rückert, E., ‘ In search of EU unicorns: What do we know about them ’, EUR 30978 EN, Publications Office of the European Union, Luxembourg, 2022. xi Bruegel, EU Digital Policy Overview , Bruegel Factsheet, 2024. xii Acemoglu, D., et al, ‘ Robot and automation: New insights from micro data: Advanced Technology Adoption: Selection or Causal Effects? ’, AEA Papers and Proceedings, 113: 210–214, 2023. xiii European Commission, Eurostat, Digitalisation in Europe – 2024 edition , Interactive Publication, 2024. xiv https:/ /epochai.org/blog/how-much-does- it-cost-to-train-frontier-ai-models 38THE FUTURE OF EUROPEAN COMPETITIVENESS — PART A | CHAPTER 23. A joint decarbonisation and competitiveness plan High energy costs in Europe are an obstacle to growth, while lack of generation and grid capacity could impede the spread of digital tech and transport electrification . Commission estimates suggest that high energy prices in recent years have taken a toll on potential growth in Europei. Energy prices also continue to affect corporate investment sentiment much more than in other major economies. Around half of European companies see energy costs as a major impediment to investment – 30 percentage points higher than US companiesii. Energy-intensive industries (EIIs) have been hit hardest: production has fallen 10-15% since 2021 and the composition of European industry is changing, with increasing imports from countries with lower energy costs. Energy prices have also become more volatile, increasing the price of hedging and adding uncertainty to investment decisions. Without a significant increase in generation and grid capacity, Europe may also face limitations on making production more digital, as training and running AI models and maintaining data centres is highly energy-intensive. Data centres are currently responsible for 2.7% of the EU’s electricity demand, but by 2030 their consumption is expected to rise by 28%. FIGURE 1 Energy-intensive manufacturing challenges % change in industrial production (Apr. 24 vs Apr. 21) Source: Eurostat, OECD Trade value added (TiVA database) and ECB staff calculations. The EU’s decarbonisation goals are also more ambitious than its competitors’, creating additional short- term costs for European industry .

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13. Rapport d’Analyse Comparative – Études diagnostiques sur le livre jeunesse au service des apprentissages, 6 pays d’Afrique subsaharienne (2020-2021), Institut Français. 14. Kevane, Michael and Alain Joseph Sissao. ‘Habitudes de lecture au Burkina Faso.’ 2007. https://www.enssib.fr/bibliotheque-numerique/documents/38272-habitudes-de-lectureau-burkina-faso.pdf, 2007. Accessed 10 October 2024. 15. Ouagadougou International Book Fair: The Digital Opportunity in Question, 23 November 2023. Accessed 10 October 2024. 16. United Nations, UN Comtrade Database: Burkina Faso Imports of Printed Books, Brochures, Leaflets, and Similar Printed Matter (HS 490199). 2023. Accessed 24 February 2025. 17. Bureau International de l’Édition Française (BIEF), Le marché du livre en français en Afrique de l’Ouest (The French- language book market in West Africa), 2021. 74 THE AFRICAN BOOK INDUSTRY • Trends, Challenges and Opportunities for GrowthBURUNDI This mapping was carried out on the basis of documentary research and data collected during a consultation with government representatives and interviews with various stakeholders. Source: World Bank. HISTORICAL CONTEXT Publishing houses in Burundi began to emerge around the time of the country’s independence in 1962, within the framework of the educational activities of religious institutions. In 1961, Librairie Saint-Paul was created, selling books, periodicals and stationery. The University of Burundi, which was founded in 1964, did not have a dedicated publishing entity, but it did have a Presses et Publication department offering content focused primarily on academic news. In 1977 , the Ministry of Youth, Sports and Culture established the Centre of Burundian Civilization (Centre de Civilisation Burundaise), which published the magazine Culture et Société for over three decades. Following the civil war (1993–2005), publishing activities experienced a revival during the 2010s, marked by the emergence of publishing houses such as Bandima, Iwacu and Soma. INSTITUTIONAL AND LEGAL FRAMEWORK The Ministry of East African Community Affairs, Youth, Sports and Culture is responsible for coordinating policies and measures related to the book and publishing sector in Burundi. It operates through the Directorate of Culture and three specialised administrative bodies: 1 the Burundian Centre for Reading and Cultural Activities (Centre Burundais pour la Lecture et l’Animation Culturelle – CEBULAC), established in October 2007 , 2 which is responsible for formulating and implementing government policy on public reading, the promotion of literary creativity and the support of community libraries; the Burundian Copyright Office (Office Burundais des Droits d’Auteur – OBDA), set up in September 2011, 3 which contributes to the protection of copyright and oversees the registration of literary works;

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17 256 UA 876 35 673 872 17 7 500 PublicationsFigure 3.53. Number of publications and EC projects in collaboration between EaP actors in different countries, in the ‘Fundamental physics and mathematics’ domain Colour indicates the relative distribution of documents, computed row-wise. AM AZ BY GE MD UA Other 10 18 25 19 18 29 10 7 11 8 9 14 18 7 19 15 18 34 25 11 19 23 30 50 19 8 15 23 23 57 18 9 18 30 23 115 EC projectsAM AZ BY GE MD UA Other AM 22 22 45 17 44 351 AZ 22 15 23 9 27 222 BY 22 15 23 15 66 394 GE 45 23 23 20 62 370 MD 17 9 15 20 59 207 UA 44 27 66 62 59 2 388 PublicationsFigure 3.54. Number of publications and EC projects in collaboration between EaP actors in different countries, in the ‘Governance, culture, education and the economy’ domain Colour indicates the relative distribution of documents, computed row-wise. 214 Part 3 Analysis of scientific and technological potential Regional collaboration in Health and wellbeing In the case of Health and wellbeing publications, external collaborations again have a significant weight across all six EaP countries. Within the EaP, some of the highest-intensity collaborations are Armenia and Azerbaijan with Georgia and Ukraine, and Georgia and Moldova with Ukraine. The highest number of collaborations in EC pro- jects are between Georgia and Ukraine, with the intensity of external collaborations still significant.Regional collaboration in ICT and com- puter science In the case of ICT and computer science publi- cations, external collaborations again have a sig- nificant weight throughout all six EaP countries. Azerbaijan, not usually standing out in other do- mains, has the second-highest collaboration with Ukraine. Georgia and Armenia also collaborate in- tensively with each other. Collaborations in terms of EC projects are much less concentrated on external partners and very evenly distributed. Azerbaijan, however, has very few EC projects. AM AZ BY GE MD UA Other 4 1 2 2 1 1 3 1 3 10 2 1 3 40 EC projectsAM AZ BY GE MD UA Other AM 33 44 82 31 73 771 AZ 33 29 49 20 48 343 BY 44 29 59 33 195 1 364 GE 82 49 59 44 121 949 MD 31 20 33 44 62 444 UA 73 48 195 121 62 3

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[]

statistically significant differences were seen between the responses from residents in Sanjay colony and Bhalswa on the NCI, four in 'sense of community' (SOC), and two in each of the themes 'neigbourliness' (NEI) and 'attraction to neighbourhood' (ATTR) as shown in Figure 2.1 . Regarding the sense of community (SOC), residents in Sanjay colony were 9.3 percentage points (pp) more likely to believe their neighbours would help them in an emergency (NCI 9, p<0.001) and 9.5 pp more likely to have a greater willing -ness to improve their neighbourhood than residents in Bhalswa (NCI 12, p<0.001). Residents of Sanjay colony were 10.2 pp more likely to feel a greater sense of community than those residents of Bhalswa (NCI 18, p<0.001). Sanjay colony resi -dents were 5.48 pp less likely to feel that their neighbours agree with them about what is important in life (NCI 8, p<0.05). In the subscale 'neighbouring' (NEI), residents in Sanjay colony were 4.76 pp less likely to invite neighbours to their home (NCI 15, p<0.01) and 9.7 pp less likely to feel that neighbourhood friendships meant a great deal to them (NCI 4, p<0.001).  Figure 2.1 Neighbourhood Cohesion Index Note: Neighbourhood Cohesion Index (NCI) estimated averaged marginal component effects for Sanjay colony with 95% CIs. The percentage points (pp) estimates for Sanjay colony (=1) with the base group being Bhalswa (=0). The marginal effect of each independent variable being averaged over the joint distribution of the remaining variables. The independent variables are in the vertical axis. The horizontal axis gives the prediction of change in the independent variable (points), and the associated 95% CIs (bars). Table 2.4 Neighbourhood Cohesion Index (NCI) | Item description | Sanjay colony with base Bhalswa | |-------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------| | Sense of community (SOC) | | | I agree with most of my neighbourhood about what's important in life (NCI 8) | -0.055 ** (0.023) | | I believe my neighbours would help me in an emergency (NCI 9) | 0.092 *** (0.025) | | I feel loyal to people in my neighbourhood (NCI 10) | -0.028 (0.035) | | I'd be willing to work with others to improve my neighbourhood (NCI 12) | 0.095 *** (0.025) | | I think of myself as similar to people who live in this neighbourhood (NCI 14) | -0.001 (0.033) | | A feeling of fellowship runs deep in this neighbourhood (NCI 16)

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[]

be registered.16 Although similar regulations had been implemented locally before 1929, it was the first time that all Western- trained physicians had to register to be allowed to practice.17 This registration process generated an unprecedented mass of documents providing rather detailed information on virtually every Western- style physician in the country.18 These new documents provide a more comprehensive view on the profession of ‘Western- style physician’ compared to previous studies that have tended to focus on some individuals or specific institutions.19 This is particularly true for the provinces of inland China, some of which have remained poorly documented.20 Women as Western- style physicians The proportion of women among Chinese physicians was far from negligi - ble, especially in the case of Western medicine, which attracted proportion - ally more women than Chinese medicine. The link between missionary and philanthropic works, the circulation of Western scientific knowledge and the education of women resulted in the rapid feminization of the profession in the province, so much so that on the eve of World War II, the share of women among Sichuan’s Western- style physicians was comparable to that of the United States. Overall, among both Chinese- style and Western- style physicians, women made up a minority of Sichuanese practitioners. Out of more than 2,300 physicians whose registration files were archived by the provincial admin - istration between 1937 and 1947, only 60 (2.6 per cent) were women (Table 7.1 ). However, there is a stark difference concerning the propor - tion of women physicians practising Western and Chinese- style medicine. Chinese- style physicians constitute a large majority of the total number of physicians registered but of these only 1.5 per cent are women, compared to 11 per cent for Western- style physicians. This disparity indicates that Western medicine provided more professional opportunities for women than Chinese medicine. This was partly due to the situation of women within Chinese medicine. State- sanctioned registration of Chinese- style physicians favoured orthodox, literati medicine, based on the knowledge of the Chinese medical classics. In this regard, female healers 176 Negotiating in/visibility suffered from long- term marginalization from literati physicians.21 The modes of transmission of Chinese medicine – master to apprentice, father to son, uncle to nephew and so on – tended to exclude women from literati medicine, although there were some exceptions. This does not mean that there were no women healers. They were rather involved

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....................................................................................................................................................... 233 Table 4.2. Combined EIST specialisation domains in Armenia ............................................. 236 Table 4.3. Combined EIST specialisation domains in Azerbaijan ........................................ 238 Table 4.4. Combined EIST specialisation domains in Georgia .............................................. 240 Table 4.5. Combined EIST specialisation domains in Moldova ............................................. 241 Table 4.6. Combined EIST specialisation domains in Ukraine .............................................. 244 Table 4.7. Pairs of economic clusters and S&T domains that can be identified in at least two countries ............................................................................................................................................... 246 268 Annexes Annexes Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation269 270 Annexes Annex 1. Results of the full economic mapping analysis for Georgia, Moldova and UkraineAn ‘X’ in a yellow-coloured cell shows whether an industry passed an individual criterion, either for the number of employees (or employment) and turnover. An ‘X’ in a green-coloured cell shows whether an industry passed the criteria for both the number of employees (or employment) and turnover. GEORGIA MOLDOVA UKRAINEEmploy- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover NACE Industry name Current Current CurrentEmerg- ingEmerg- ingEmerg- ingCurrent Current CurrentEmerg- ingEmerg- ingEmerg- ingCurrent Current CurrentEmerg- ingEmerg- ingEmerg- ing 34 52 28 61 64 40 31 29 15 50 47 21 55 40 35 83 57 34 A AGRICULTURE, FORESTRY AND FISHING 1 Crop and animal production, hunting and related service activities 1.1 Growing of non-perennial crops X X X X X 1.2 Growing of perennial crops X X X X X X X 1.3 Plant propagation 1.4 Animal production X X X X X X 1.5 Mixed farming X X 1.6 Support activities to agriculture and post-harvest crop activities X X X X 1.7 Hunting, trapping and related service activities 2 Forestry and logging 2.1 Silviculture and other forestry activities X X X X 2.2 Logging X X 2.3 Gathering of wild growing non-wood products 2.4 Support services to forestry X X 3 Fishing and aquaculture 3.1 Fishing 3.2 Aquaculture B MINING AND QUARRYING 5 Mining of coal and lignite 5.1 Mining of hard coal X X X 5.2 Mining of lignite 6 Extraction of crude petroleum and natural gas 6.1 Extraction of crude petroleum X X X X 6.2 Extraction of natural gas X X X Smart Specialisation in the Eastern Partnership countries -

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[]

Assistant principals can help with daily school operations. Teachers and support staff can exercise leadership when they participate in decision making and in designing approaches to teaching and learning. Student involvement in leadership can be empowering and promote critical thinking and responsibility for learning. Parents and community members can promote culturally responsive practices and strengthen the school’s connection with the community. As part of the 2018 Teaching and Learning International Survey (TALIS), in which 48 education systems participated, 89% of lower secondary schools had a school management team. On average, among schools with a management team, 8 in 10 had an assistant principal, 6 in 10 had teachers (department heads or other teachers), 5 in 10 had school governing board members, 4 in 10 had financial managers, and 3 in 10 had parent or student representatives ( Figure 4.1). While there is considerable difference between education systems, it is clear that almost all of them, depending on school size and other contextual factors, offer opportunities for participating in school decision making and the exercise of leadership and initiative. Despite this potential, school leadership often remains hierarchical and limits stakeholders’ engagement. Teachers need leadership training and autonomy. Student involvement is more established in high-income countries. Parents and communities face barriers to their participation. This chapter examines how principals share leadership with these actors, highlighting the importance of creating collaborative learning environments and achieving positive outcomes for students.SCHOOL PERSONNEL CAN LEAD IF GIVEN OPPORTUNITIES AND SUPPORT Assistant principals play an essential role in schools’ success by supporting school operations (Oleszewski et al., 2012). Teachers in leadership positions can promote teaching of high quality (Berg and Zoellick, 2019). Other school staff also take on leadership roles, contributing to decision making and school operations (Ansley et al., 2019). All these roles can be performed in an organized structure or through individual initiatives. ASSISTANT PRINCIPALS AND TEACHER LEADERS SUPPORT PRINCIPALS Various leadership roles exist to help the principal shape the school’s vision, develop teaching strategies, ensure smooth operations and form a collaborative leadership team. Deputy, vice, assistant or co-principals , usually seen as subordinate, mirror the principal’s role (Matthews and Crow, 2003). Their roles are shaped largely by principals’ discretion (Arar, 2014; Guihen, 2019) and involve managerial and leadership responsibilities, especially when schools are granted autonomy (Wong, 2009). Principals can first empower assistant principals by providing clear authority and guidance, as lack of support can

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chosen and how it is designed, it must be clearly defined in the law. Clear rules on how to implement ring-fencing in mining-including methods to apportion revenues and expenditures and how to deal with domestic transfer pricing scenariosare critical. Clear criteria must be developed to enable effective implementation by both companies and governments. ## Financial Support for the OECD Comes From the Following Donors:       Schweizerische Eidgenossenschaft Confederation suisse Contederazione Svizzera Contederaziun svizra Swviss Conlederation Federal Department of Economic Affairs, Education and Research eaeR State Secretariat for Economic Affairs SECO    Ministry of Foreign Affairs     ## Support for the IGF Comes From the Following: IGF Project Funders   IGF Secretariat Funders   IGF Secretariat Host   ## References Australian Energy Regulator. (2023). Ring-fencing . https://www.aer.gov.au/industry/networks/ ring-fencing Benninger, T., Devlin, D., Godinez, E. C., & Vernon-Lin, N. (2024). Cash flow analysis of fiscal regimes for extractive industries (Working paper WP/24/89). International Monetary Fund. https://www.imf.org/-/media/Files/Publications/WP/2024/English/wpiea2024089-printpdf.ashx Bindeman, K. (1999, October). Production-sharing agreements: An economic analysis . Oxford Institute for Energy Studies. https://www.oxfordenergy.org/wpcms/wp-content/ uploads/2010/11/WPM25-ProductionSharingAgreementsAnEconomicAnalysisKBindemann-1999.pdf Calder, J. (2014). Administering fiscal regimes for extractive industries: A handbook , International Monetary Fund. https://www.elibrary.imf.org/display/book/9781475575170/978 1475575170.xml Cameron, P. D., & Stanley, M. C. (2017). Oil, gas, and mining: A sourcebook for understanding the extractives industries . World Bank. https://documents1.worldbank.org/curated/ en/222451496911224999/pdf/Oil-Gas-and-Mining-A-Sourcebook-for-Understandingthe-Extractive-Industries.pdf Daniel, P., Keen, M., & McPherson, C. (Eds.). (2010). The taxation of petroleum and minerals: Principles, problems and practice . Routledge. https://www.international-arbitrationattorney.com/wp-content/uploads/arbitrationlaw1394930.pdf Davis Tax Committee. (2014). First interim report on mining for the Minister of Finance . https://www.taxcom.org.za/docs/20151201%20DTC%20First%20Interim%20Report%20 on%20Mining%20(hard-rock).pdf Davis Tax Committee. (2016). Second and final report on hard-rock mining for the Minister of Finance . 20171113 Second and final hard-rock mining report on website.pdf Department of Petroleum and Energy, Petroleum Division. (2005). Petroleum policy handbook . Government of Papua New Guinea. Ernst & Young. (2019). Global oil and gas tax guide . https://globaltaxnews.ey.com/news/20195677-ey-global-oil-and-gas-tax-guide-2019 Ghana Revenue Authority. (n.d.). Mineral royalties tax. https://gra.gov.gh/portfolio/mineralroyalties-tax/ Hogan, L. & Goldsworthy, B. (2010). International mineral taxation: Experience and issues. In P. Daniel, M. Keen, & C. McPherson (Eds.), The taxation of petroleum and minerals . Routledge. https://www.international-arbitration-attorney.com/wp-content/uploads/ arbitrationlaw1394930.pdf Intergovernmental Forum on Mining, Minerals, Metals and Sustainable Development & Organisation for Economic Co-operation and Development. (2017b). Limiting the impact of excessive interest deductions on mining revenue. https://www.oecd.org/content/dam/ oecd/en/about/programmes/beps-in-mining/limiting-the-impact-of-excessive-interestdeductions-on-mining-revenue.pdf

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acceleration circuitry ), which can include microprocessors, programmable processing devices (e.g., FPGAs, ASICs, PLDs, DSPs. and/or the like), and/or the like. The also includes non-transitory or transitory machine-readable media (also referred to as “computer readable medium ” or “ ”), which may be embodied as, or otherwise include , , and/or memory devices/elements of the . Additionally or alternatively, the can be embodied as any of the devices/technologies described for the and/or . The system memory (also referred to as “ ”) includes one or more hardware elements/devices for storing data and/or (and/or , ). Any number of memory devices may be used to provide for a given amount of . As examples, the can be embodied as processor cache or scratchpad memory, volatile memory, non-volatile memory (NVM), and/or any other machine readable media for storing data. Examples of volatile memory include random access memory (RAM), static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), thyristor RAM (T-RAM), content-addressable memory (CAM), and/or the like. Examples of NVM can include read-only memory (ROM) (e.g., including programmable ROM (PROM), erasable PROM (EPROM), electrically EPROM (EEPROM), flash memory (e.g., NAND flash memory, NOR flash memory, and the like), solid-state storage (SSS) or solid-state ROM, programmable metallization cell (PMC), and/or the like), non-volatile RAM (NVRAM), phase change memory (PCM) or phase change RAM (PRAM) (e.g., 3D XPoint™ memory, chalcogenide RAM (CRAM), Interfacial Phase-Change Memory (IPCM), and the like), memistor devices, resistive memory or resistive RAM (ReRAM) (e.g., memristor devices, metal oxide-based ReRAM, quantum dot resistive memory devices, and the like), conductive bridging RAM (or PMC), magnetoresistive RAM (MRAM), electrochemical RAM (ECRAM), ferroelectric RAM (FeRAM), anti-ferroelectric RAM (AFeRAM), ferroelectric field-effect transistor (FeFET) memory, and/or the like. Additionally or alternatively, the can include spintronic memory devices (e.g., domain wall memory (DWM), spin transfer torque (STT) memory (e.g., STT-RAM or STT-MRAM), magnetic tunneling junction memory devices, spin-orbit transfer memory devices, Spin-Hall memory devices, nanowire memory cells, and/or the like). In some implementations, the may be formed into any number of different package types, such as single die package (SDP), dual die package (DDP), quad die package (Q17P), memory modules (e.g., dual inline memory modules (DIMMs), microDIMMs, and/or MiniDIMMs), and/or the like. Additionally or alternatively, the is or includes block addressable memory device(s), such as those based on NAND or NOR flash memory technologies (e.g., single-level cell (“SLC”), multi-level cell (“MLC”), quad-level cell (“QLC”), tri-level cell (“TLC”), or

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[]

end of stool sampling, whereas 19 cases seroconverted earlier. All stool samples collected prior to the anti-TG2 negative plasma, and corresponding samples from the matched controls, were subjected to DNA virome analysis. The DNA virome metagenomes were characterised in 1,271 stool samples from the MIDIA nested case-control dataset. The starting material was a supernatant of faecal material. Shortly after the collection of faecal samples (during 2001 – 2010), samples were resuspended in phosphate-buffered saline with the addition of 2.5 μg/mL fungizone, 50 IU/mL penicillin, 0.5% bovine serum albumin, 50 μg/mL streptomycin, 50 IU/mL penicillin, 50 μg/mL streptomycin. The resuspended samples were vigorously vortexed and centrifuged at 4000×g for 30 min, and the supernatants were collected and biobanked at -80°C until further processing. In the present project, the biobanked supernatants were thawed, re-centrifuged to clarify the material, and subjected to RNA and DNA co-purification using the Qiagen Viral RNA extraction chemistry (Qiagen, Hilden, Germany) according to its protocol, with the exception of reducing the amount of carrier RNA added. In addition, for a smaller study on the early stages of T1D (islet autoimmunity), we generated 311 combined metagenomic libraries of DNA and RNA viromes; we have sequenced 2/3 of these libraries by December 2023. In this T1D study, we focused on early-onset islet autoimmunity cases, and selected fewer samples per subject. Cases were selected based on their very early onset of islet autoimmunity. They were eligible if the pre-seroconversion period was covered by stool sample collection (i.e. if stools were available at 12, 9, 6, 3 and 0 months before the first blood sample positive for any autoantibody marker of islet autoimmunity). Islet autoimmunity was defined on the basis of the results of tests for plasma autoantibodies against glutamic acid decarboxylase 65 (GADA), protein tyrosine phosphatase IA2 (IA2A) and insulin (IAA) as previously described in detail (Stene, Witso et al. 2007). The seroconversion window of islet autoimmunity was defined as the period between the last negative and first positive sample for any of the autoantibodies tested – there had to be at least two consecutive samples positive for at least two islet autoantibodies, or a strong positivity for one autoantibody leading to the development of T1D. Sample handling and nucleic acid extraction were performed according to our published protocol (Kramna and Cinek 2018). The DIPP cohort The DIPP (Diabetes Prediction and Prevention study) birth cohort started newborn screening in the general

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chosen and how it is designed, it must be clearly defined in the law. Clear rules on how to implement ring-fencing in mining-including methods to apportion revenues and expenditures and how to deal with domestic transfer pricing scenariosare critical. Clear criteria must be developed to enable effective implementation by both companies and governments. ## Financial Support for the OECD Comes From the Following Donors:       Schweizerische Eidgenossenschaft Confederation suisse Contederazione Svizzera Contederaziun svizra Swviss Conlederation Federal Department of Economic Affairs, Education and Research eaeR State Secretariat for Economic Affairs SECO    Ministry of Foreign Affairs     ## Support for the IGF Comes From the Following: IGF Project Funders   IGF Secretariat Funders   IGF Secretariat Host   ## References Australian Energy Regulator. (2023). Ring-fencing . https://www.aer.gov.au/industry/networks/ ring-fencing Benninger, T., Devlin, D., Godinez, E. C., & Vernon-Lin, N. (2024). Cash flow analysis of fiscal regimes for extractive industries (Working paper WP/24/89). International Monetary Fund. https://www.imf.org/-/media/Files/Publications/WP/2024/English/wpiea2024089-printpdf.ashx Bindeman, K. (1999, October). Production-sharing agreements: An economic analysis . Oxford Institute for Energy Studies. https://www.oxfordenergy.org/wpcms/wp-content/ uploads/2010/11/WPM25-ProductionSharingAgreementsAnEconomicAnalysisKBindemann-1999.pdf Calder, J. (2014). Administering fiscal regimes for extractive industries: A handbook , International Monetary Fund. https://www.elibrary.imf.org/display/book/9781475575170/978 1475575170.xml Cameron, P. D., & Stanley, M. C. (2017). Oil, gas, and mining: A sourcebook for understanding the extractives industries . World Bank. https://documents1.worldbank.org/curated/ en/222451496911224999/pdf/Oil-Gas-and-Mining-A-Sourcebook-for-Understandingthe-Extractive-Industries.pdf Daniel, P., Keen, M., & McPherson, C. (Eds.). (2010). The taxation of petroleum and minerals: Principles, problems and practice . Routledge. https://www.international-arbitrationattorney.com/wp-content/uploads/arbitrationlaw1394930.pdf Davis Tax Committee. (2014). First interim report on mining for the Minister of Finance . https://www.taxcom.org.za/docs/20151201%20DTC%20First%20Interim%20Report%20 on%20Mining%20(hard-rock).pdf Davis Tax Committee. (2016). Second and final report on hard-rock mining for the Minister of Finance . 20171113 Second and final hard-rock mining report on website.pdf Department of Petroleum and Energy, Petroleum Division. (2005). Petroleum policy handbook . Government of Papua New Guinea. Ernst & Young. (2019). Global oil and gas tax guide . https://globaltaxnews.ey.com/news/20195677-ey-global-oil-and-gas-tax-guide-2019 Ghana Revenue Authority. (n.d.). Mineral royalties tax. https://gra.gov.gh/portfolio/mineralroyalties-tax/ Hogan, L. & Goldsworthy, B. (2010). International mineral taxation: Experience and issues. In P. Daniel, M. Keen, & C. McPherson (Eds.), The taxation of petroleum and minerals . Routledge. https://www.international-arbitration-attorney.com/wp-content/uploads/ arbitrationlaw1394930.pdf Intergovernmental Forum on Mining, Minerals, Metals and Sustainable Development & Organisation for Economic Co-operation and Development. (2017b). Limiting the impact of excessive interest deductions on mining revenue. https://www.oecd.org/content/dam/ oecd/en/about/programmes/beps-in-mining/limiting-the-impact-of-excessive-interestdeductions-on-mining-revenue.pdf

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Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation193 Figure 3.37. Specialisation index and citation impact across domains of Ukraine’s S&T ecosystem against the EaP average, for publications Specialisation indexNo pubs. 100 500 1 000Normalised citation impact2 1.3 1 0.75 0.50.25 0.5 1 2 4 Agrifood Biotechnology Chemistry and chemical engineering Electric and electronic technologies Energy Environmental sciences and industries Fundamental physics and mathematics Governance, culture, education and the economy Health and wellbeing ICT and computer science Mechanical engineering and heavy machinery Nanotechnology and materials Optics and photonics Transportation Figure 3.38. Specialisation index across domains of Ukraine’s S&T ecosystem against the EaP average, for patents 0.8 0.6 0.4 1.0 2.0 Specialisation indexTransportation Energy Health and wellbeing Optics and photonics Biotechnology Electric and electronic technologies Environmental sciences and industries ICT and computer science Agrifood Nanotechnology and materials Mechanical engineering and heavy machinery Fundamental physics and mathematics Chemistry and chemical engineering Governance, culture, education and the economy 194 Part 3 Analysis of scientific and technological potential UkraineTemporal evolution of the domains Period over period change in the relative size of each domain, domain size and data source size independent (% change for 2015-2018, over previous period 2011-2014) Change in share of publicationsChange in share of patents Change, weighted average of publications and patents Agrifood 52.73% 2.65% 15.11% Biotechnology -15.47% 6.79% -6.79% Chemistry and chemical engineering -33.56% -3.20% -25.04% Electric and electronic technologies -8.23% -7.50% -7.82% Energy 8.66% -16.42% -5.00% Environmental sciences and industries 3.99% -13.16% -0.79% Fundamental physics and mathematics -19.92% -8.80% -18.72% Governance, culture, education and the economy43.97% -5.97% 42.48% Health and wellbeing 36.91% 2.67% 19.96% ICT and computer science 32.17% 19.32% 28.72% Mechanical engineering and heavy machinery15.33% 1.31% 4.41% Nanotechnology and materials -15.97% -7.24% -14.05% Optics and photonics -29.69% -7.14% -24.07% Transportation 64.95% 7.79% 37.53%Table 3.18. Temporal evolution of Ukraine’s S&T domains Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation195 5. Identification of the main actors and collaboration patterns within the S&T specialisation do- mains The use of all metadata information for each S&T record gathered offers the opportunity to identify local and international actors linked to specific documents produced by the EaP as a whole and by each EaP country. This information, in turn, has allowed national and international collabora- tion networks in which the EaP countries’ S&T ecosystems are active to be disentangled, in ag- gregate and by identified S&T

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[]

thermal budget through the following process. - the insulator 280 is provided over the conductor 242 with the insulator 244 positioned therebetween. - the insulator 280 preferably includes an excess-oxygen region. - silicon oxide, silicon oxynitride, silicon nitride oxide, silicon nitride, silicon oxide to which fluorine is added, silicon oxide to which carbon is added, silicon oxide to which carbon and nitrogen are added, porous silicon oxide, a resin, or the like is preferably included. - silicon oxide and silicon oxynitride, which have thermal stability, are preferable. - the insulator 280 When the insulator 244 is not provided, the insulator 280 is in contact with the side surfaces of the oxide 230 a and the oxide 230 b . In this case, oxygen contained in the insulator 280 is sometimes supplied to the channel formation region of the oxide 230 owing to heating. Note that the concentration of impurities such as water or hydrogen in the insulator 280 is preferably lowered. - the insulator 281 functioning as an interlayer film is preferably provided over the insulator 280 . - the concentration of impurities such as water or hydrogen in the insulator 281 is preferably lowered. - the capacitor 100 a is provided in a region overlapping with the transistor 200 a . - the capacitor 100 a includes the conductor 110 , the insulator 130 , and the conductor 120 over the insulator 130 . - a conductor that can be used for the conductor 205 , the conductor 260 , or the like can be used. - the capacitor 100 a is formed in an opening provided in the insulator 244 , the insulator 280 , and the insulator 281 . - the conductor 110 functioning as a lower electrode and the conductor 120 functioning as an upper electrode face each other with the insulator 130 as a dielectric positioned therebetween. - the conductor 110 of the capacitor 100 a is formed in contact with the conductor 242 a of the transistor 200 a. - the capacitor 100 a can have a larger capacitance without an increase in its projected area. Therefore, it is preferred that the capacitor 100 a be a cylindrical capacitor (have a side surface area larger than a bottom surface area). - the above structure can increase the capacitance per unit area of the capacitor 100 a and advance further miniaturization or higher integration of

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[]

0.515 0.376 12 Manufacture of tobacco products 3.213 2.254 0.178 13 Manufacture of textiles 3.119 0.791 14 Manufacture of wearing apparel 2.291 2.066 15 Manufacture of leather and related products 4.075 1.112 16 Manufacture of wood and of products of wood and cork 2.215 2.886 0.899 17 Manufacture of paper and paper products 0.956 18.1 Printing and service activities related to printing 2.609 1.743 0.773 19 Manufacture of coke and refined petroleum products 2.930 0.466 1.322 0.412 0.788 20.1 Manufacture of basic chemicals 0.364 1.860 0.864 0.774 1.412 0.726 20.2 Manufacture of pesticides and other agrochemical products 0.617 0.597 0.497 3.324 0.965 20.3 Manufacture of paints 1.967 0.812 1.389 20.4 Manufacture of soap and detergents 0.699 1.765 0.608 1.174 0.944 0.809 20.5 Manufacture of other chemical products 2.254 0.597 0.742 1.338 1.017 20.6 Manufacture of man-made fibres 5.575 0.425 21 Manufacture of basic pharmaceutical products 1.156 1.305 0.596 0.996 1.126 0.822 22 Manufacture of rubber and plastic products 0.849 2.636 1.282 0.227 0.837 23 Manufacture of other non-metallic mineral products 0.906 1.766 1.836 0.467 23.1 Manufacture of glass and glass products 0.988 2.553 1.839 0.620 23.3 Manufacture of clay building materials 2.142 1.288 0.700 23.4 Manufacture of other porcelain and ceramic products 5.381 0.262 23.5 Manufacture of cement, lime and plaster 1.688 1.579 1.438 0.330 0.769 24 Manufacture of basic metals 0.366 1.366 1.924 0.617 1.679 25.1 Manufacture of structural metal products 1.867 1.561 25.2 Manufacture of tanks 1.412 2.630 1.304 25.3 Manufacture of steam generators 4.405 25.4 Manufacture of weapons and ammunition 0.584 2.015 1.610 1.317 25.5 Forging, pressing, stamping and roll-forming of metal 1.265 2.948 0.634 0.982 25.6 Treatment and coating of metals; machining 1.323 1.535 2.551 0.591Table 2.32. Specialised industries using data for patents issued Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation95 NACE Industry name Armenia Azerbaijan Belarus Georgia Moldova Ukraine 25.7 Manufacture of cutlery, tools and general hardware 0.866 1.330 1.880 0.959 0.609 25.9 Manufacture of other fabricated metal products 4.074 26.1 Manufacture of electronic components and boards 1.957 0.540 1.311 0.666 0.962 0.565 26.2 Manufacture of computers and peripheral equipment 2.220 0.390 1.635 0.618 0.280 0.856 26.3 Manufacture of communication equipment 1.010 0.682 1.158 1.505 0.825 0.820 26.4 Manufacture of consumer electronics 3.283 0.278 1.743 26.5 Manufacture of instruments and appliances for measuring 0.216 0.777 1.364 0.680 1.020 1.943 26.6 Manufacture of irradiation 1.696 1.774 0.509 0.635 1.295 26.7Manufacture

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[]

digital twin requires replication of the factory, its robots, processes and the overlay of an AI algorithm. To facilitate this cooperation, EU companies should be encouraged to participate in an “AI Vertical Priorities Plan”. The aim of this plan would be to accelerate AI development across the ten strategic sectors where EU business models will benefit most from rapid AI introduction (automotives, advanced manufacturing and robotics, energy, telecoms, agriculture, aerospace, defence, environmental forecasting, pharma and healthcare). Companies that participate in the plan would benefit from EU funding for model development and a specific set of exemptions regarding competition and AI experimentation. In particular, to overcome the EU’s lack of large data sets, model training should be fed with data freely contributed by multiple EU companies within a certain sector. It should be supported within open-source frameworks, safeguarded from antitrust enforcement by competition authorities. Experimentation should be encouraged via the opening up, EU-wide coordination and harmonisation of national “AI Sandbox regimes” to companies participating in the plan. These experimental “sand - boxes” would enable regular assessments of regulatory hindrances deriving from EU or national legislation and provide feedback from private companies and research centres to regulators. Given the dominance of US providers, the EU must find a middle way between promoting its domestic cloud industry and ensuring access to the technologies it needs . It is too late for the EU to try and develop systematic challengers to the major US cloud providers: the investment needs involved are too large and would divert resources away from sectors and companies where the EU’s innovative prospects are better. However, for reasons of European sovereignty, the EU should ensure that it has a competitive domestic industry that can meet the demand for “sover - eign cloud” solutions. To achieve this goal, the report recommends adopting EU-wide data security policies for collaboration between EU and non-EU cloud providers, allowing access to US hyperscalers’ latest cloud technolo - gies while preserving encryption, security and ring-fenced services for trusted EU providers. At the same time, the EU should legislate mandatory standards for public sector procurement, thereby levelling the playing field for EU companies against larger non-EU players. Outside of “sovereign” market segments, it is recommended to negotiate a low barrier “digital transatlantic marketplace”, guaranteeing supply chain security and trade opportunities for EU and US tech companies on fair and equal conditions. To make these opportunities equally attractive

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[]

| I | | J | J | J | J | | |-----------------|-----------------|-----------------|---------------|----------------------|-------------------|---------| | | | % female | % female | Number (000,000) | Number (000,000) | | | Youth | Adults | Youth | Adults | Youth | Adults | Country | | 4.6.2 | | | | | | | | 83 ₋₁ ᵢ | 72 ₋₁ ᵢ | 58 ₋₁ ᵢ | 70 ₋₁ ᵢ | 1,110 ₋₁ ᵢ | 5,312 ₋₁ ᵢ | AGO | | 66 ₋₁ | | | | 856 ₋₁ | 4,009 ₋₁ | BEN | | ᵢ | 47 ₋₁ ᵢ | 60 ₋₁ ᵢ | 60 ₋₁ ᵢ | ᵢ | ᵢ | | | … | … | … | … | … | … | BWA | | 54 ₋₁ | 34 ₋₁ ᵢ | 52 ₋₁ ᵢ | 55 ₋₁ ᵢ | 2,072 ₋₁ ᵢ | 8,225 ₋₁ | BFA | | ᵢ 94 | | | | 152 ₋₁ ᵢ | ᵢ 1,678 ₋₁ ᵢ | | | ₋₁ ᵢ 99 ₋₁ ᵢ | 76 ₋₁ ᵢ 91 ₋₁ ᵢ | 53 ₋₁ ᵢ 29 ₋₁ ᵢ | 64 ₋₁ ᵢ | 70 ₋₁ ᵢ 1 ₋₁ ᵢ | 39 ₋₁ ᵢ | CMR | | 86 ₋₃ ᵢ | 78 ₋₃ ᵢ | 59 ₋₃ ᵢ 57 ₋₃ | 62 ₋₃ ᵢ 60 ₋₃ | 703 ₋₃ ᵢ 706 ₋₃ ᵢ | 3,262 ₋₃ ᵢ 1,699 | CAF | | 38 ₋₃ ᵢ | 37 ₋₃ ᵢ 27 ₋₁ ᵢ | ᵢ 54 ₋₁ ᵢ | ᵢ 56 ₋₁ ᵢ | 2,186 ₋₁ ᵢ | ₋₃ ᵢ 6,652 ₋₁ | TCD | | 36 ₋₁ ᵢ | 62 ₋₁ ᵢ | 47 ₋₁ ᵢ | 56 ₋₁ ᵢ | 28 ₋₁ ᵢ | ᵢ 196 ₋₁ ᵢ | | | 82 ₋₁ ᵢ | 81 ₋₂ ᵢ | 58 ₋₂ ᵢ | 64 ₋₂ ᵢ | 187 ₋₂ ᵢ | 654 ₋₂ ᵢ | COM | | 82 ₋₂ ᵢ | | | | 804 ₋₄ | 1,484 ₋₄ | | | | 50 ₋₂ ᵢ | 76 ₋₄ | 65 ₋₄ | | 10,137 ₋₁ | COG CIV | | 67 ₋₂ 88 ₋₁ | 81 ₋₁ ᵢ | 61 ₋₁ ᵢ | 74 ₋₁ ᵢ | 2,202 ₋₁ ᵢ | ᵢ | | | ᵢ | … | … | …

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education 1 CHAPTER 1. Introduction .................................................................................................................................................................................. 5 Expectations of leaders at the school and system level have been changing ........................................................................................... 10 Guide to the report ........................................................................................................................................................................................................ 13 Recommendations ......................................................................................................................................................................................................... 17 CHAPTER 2. School leadership: Roles, impact and standards ........................................................................................................... 23 School principals are expected to fulfil various leadership roles .................................................................................................................. 25 The impact of school principals can be significant .............................................................................................................................................. 31 Leadership standards can guide action and certification ................................................................................................................................ 39 Conclusion ....................................................................................................................................................................................................................... 42 CHAPTER 3. School leadership: Selection, training and conditions .................................................................................................. 45 Improving selection processes is needed to professionalize principals’ careers ..................................................................................... 47 Countries need to do more to prepare and train school leaders ................................................................................................................... 57 Countries try to make principalship an attractive career path ...................................................................................................................... 67 Conclusion ........................................................................................................................................................................................................................ 74 CHAPTER 4. Shared school leadership ...................................................................................................................................................... 77 School personnel can lead if given opportunities and support ...................................................................................................................... 79 Students can exercise leadership through formal channels and informally ............................................................................................. 87 Engaged parents and community members can steer schools towards their goals ............................................................................. 90 Conclusion ....................................................................................................................................................................................................................... 94 CHAPTER 5. System leadership .................................................................................................................................................................. 97 System leaders need to set expectations for quality and equity ................................................................................................................. 99 System leaders should be instructional leaders .............................................................................................................................................. 105 Civil servants are often not selected to serve as system leaders .............................................................................................................. 108 Conclusion ..................................................................................................................................................................................................................... 112 CHAPTER 6. Political leadership ............................................................................................................................................................... 115 Political motivations determine education system development .............................................................................................................. 117 The direction of education is influenced by many other actors ................................................................................................................... 127 Conclusion ..................................................................................................................................................................................................................... 137 xiv 2024/5 • GLOBAL EDUCATION MONITORING REPORTMonitoring education in the Sustainable Development Goals 139 CHAPTER 7. Introduction ............................................................................................................................................................................ 143 Conference on Education Data and Statistics ................................................................................................................................................... 145 SDG 4 Scorecard .......................................................................................................................................................................................................... 145 2025 Comprehensive Review ................................................................................................................................................................................. 147 CHAPTER 8. Primary and secondary education .................................................................................................................................. 150 Access and completion .............................................................................................................................................................................................. 152 Learning ......................................................................................................................................................................................................................... 157 Focus 8.1. Mathematics anxiety negatively affects mathematics performance ................................................................................... 164 CHAPTER 9. Early childhood education ................................................................................................................................................. 170 Focus 9.1. Preschool leadership needs attention ............................................................................................................................................. 177 Focus 9.2. Training for parents and caregivers can support early childhood development ............................................................... 179 CHAPTER 10. Technical, vocational, tertiary and adult education ................................................................................................. 182 Focus 10.1. Higher education leaders face major challenges ....................................................................................................................... 190 Focus 10.2. Women are under-represented in higher education leadership .......................................................................................... 194 CHAPTER 11. Skills for work ..................................................................................................................................................................... 196 Focus 11.1. Can leadership be taught? ................................................................................................................................................................. 201 CHAPTER 12. Equity .................................................................................................................................................................................... 206 Focus 12.1. Peers affect individual education outcomes ............................................................................................................................... 214 CHAPTER 13. Youth and adult literacy ................................................................................................................................................... 218 Focus 13.1. Family

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per labelled topic group (or ‘domain’) in the Eastern Partnership region. Nanotechnolo- gy and materials is the domain with the most re- cords (with a total of 35 742), followed by Health and wellbeing (29 643), Fundamental physics and mathematics (29 120), Mechanical engineering and heavy machinery (24 097) and ICT and com- puter science (16 529).Although very small in comparison to publications and patents, the number of EC projects is useful to gauge the activity of internationally-connected EaP research and innovation actors. In this con- text, there are a significant number of EC projects on Nanotechnology and materials (65 projects), Environmental sciences and industries (63), ITC and computer science (61), Health and wellbeing (56) and Energy (54). The highest concentration, however, is in the Governance domain (197), due to the nature of these projects. The number of publications in international jour- nals has been increasing considerably in recent years within the majority of domains and is ex- pected to continue to do so, as reflected by the CAGR (compound annual growth rate), except for Chemistry and chemical engineering and Optics and photonics, where the number of records has remained fairly consistent throughout the time range considered. Some of the domains present an especially high growth rate, such as Govern- ance, culture, education and the economy (24%), Transportation (20%) and Health (15%). Publications (critical mass | CAGR)PatentsEC projectsTotal Nanotechnology and materials 29 067 3.7% 6 641 65 35 773 Health and wellbeing 17 874 14.5% 11 726 56 29 656 Fundamental physics and mathematics 26 852 1.9% 2 255 18 29 125 Mechanical engineering and heavy machinery5 582 9.9% 18 510 8 24 100 ICT and computer science 13 111 13.8% 4 044 61 17 216 Biotechnology 10 340 5.7% 5 837 29 16 206 Governance, culture, education and the economy14 895 24.3% 434 197 15 526 Environmental sciences and industries 10 735 10.6% 3 272 63 14 070 Electric and electronic technologies 5 874 5.8% 7 009 17 12 900 Energy 5 496 8.6% 5 828 54 11 378 Chemistry and chemical engineering 8 132 1.4% 2 380 14 10 526 Optics and photonics 8 043 -0.3% 1 896 19 9 958 Agrifood 2 949 12.5% 5 907 21 8 877 Transportation 2 355 20.4% 1 984 25 4 364Table 3.4. Number of records per labelled topic group (i.e. ‘domain’) in the Eastern Partnership region 154 Part 3 Analysis

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devices (e.g., visible light cameras, thermographic camera and/or thermal imaging camera (TIC) systems, forward-looking infrared (FLIR) camera systems, radiometric thermal camera systems, active infrared (IR) camera systems, ultraviolet (UV) camera systems, and/or the like), light detection and ranging (LiDAR) sensors, proximity sensors (e.g., IR radiation detector and the like), depth sensors, ambient light sensors, optical light sensors, ultrasonic transceivers, microphones, inductive loops, force and/or load sensors, remote charge converters (RCC), rotor speed and position sensor(s), fiber optic gyro (FOG) inertial sensors, Attitude & Heading Reference Unit (AHRU), fibre Bragg grating (FBG) sensors and interrogators, tachometers, engine temperature gauges, pressure gauges, transformer sensors, airspeed-measurement meters, speed indicators, and/or the like. The IMUs, MEMS, and/or NEMS can include, for example, one or more 3-axis accelerometers, one or more 3-axis gyroscopes, one or more magnetometers, one or more compasses, one or more barometers, and/or the like. Additionally or alternatively, the can include sensors of various compute components such as, for example, digital thermal sensors (DTS) of respective processors/cores, thermal sensor on-die (TSOD) of respective dual inline memory modules (DIMMs), baseboard thermal sensors, and/or any other sensor(s), such as any of those discussed herein. The allow the to change its state, position, and/or orientation, or move or control a mechanism or system. The comprise electrical and/or mechanical devices for moving or controlling a mechanism or system, and converts energy (e.g., electric current or moving air and/or liquid) into some kind of motion. The is configured to operate one or based on one or more captured events, instructions, control signals, and/or configurations received from a , , and/or other components of the . As examples, the actuators can be or include any number and combination of the following: soft actuators (e.g., actuators that changes its shape in response to a stimuli such as, for example, mechanical, thermal, magnetic, and/or electrical stimuli), hydraulic actuators, pneumatic actuators, mechanical actuators, electromechanical actuators (EMAs), microelectromechanical actuators, electrohydraulic actuators, linear actuators, linear motors, rotary motors, DC motors, stepper motors, servomechanisms, electromechanical switches, electromechanical relays (EMRs), power switches, valve actuators, piezoelectric actuators and/or biomorphs, thermal biomorphs, solid state actuators, solid state relays (SSRs), shape-memory alloy-based actuators, electroactive polymer-based actuators, relay driver integrated circuits (ICs), solenoids, impactive actuators/mechanisms (e.g., jaws, claws, tweezers, clamps, hooks, mechanical fingers, humaniform dexterous robotic hands, and/or other gripper mechanisms that physically grasp by direct impact upon an object), propulsion actuators/mechanisms (e.g., wheels, axles, thrusters, propellers, engines, motors

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OECD Economics Department Working Papers No. 1839 Assessing the impact of global demographic change on the German economy By: Donal Smith, Robert Grundke, Marius Bickmann and Tony Huang OECD Economics Department Working Papers Assessing the impact of global demographic change on the German economy No.1839 P UBE 2 | AS SESSING THE IMPACT OF GLOBAL DEMOGRAPHIC CHANGE ON THE GERMAN ECONOMY © OECD 2025 OECD Working Papers should not be reported as representing the official views of the OECD or of its member countries. The opinions expressed and arguments employed are those of the authors. Working Papers describe preliminary results or research in progress by the author(s) and are published to stimulate discussion on a broad range of issues on which the OECD works. Comments on Working Papers are welcomed, and may be sent to the OECD Economics Department . This document and any map included herein are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. A ttribution 4.0 International (CC BY 4.0) This work is made available under the Creative Commons Attribution 4.0 International licence. By using this work, you accept to be bound by the terms of this licence (https://creativecommons.org/licenses/by/4.0/). Attribution – you must cite the work. Translations – you must cite the original work, identify changes to the original and add the following text: In the event of any discrepancy between the original work and the translation, only the text of original work should be considered valid. Adaptations – you must cite the original work and add the following text: This is an adaptation of an original work by the OECD. The opinions expressed and arguments employed in this adaptation should not be reported as representing the official views of the OECD or of its Member countries. Third -party material – the licence does not apply to third- party material in the work. If using such material, you are responsible for obtaining permission from the third party and for any claims of infringement. You must not use the OECD logo, visual identity or cover image without express permission or suggest the OECD endorses your use of the work. Any dispute arising under this licence shall be settled by arbitration in accordance with the Permanent Court of Arbitration (PCA) Arbitration Rules 2012. The seat of arbitration shall

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mous Boston crime family. | | BS | Princess Margaret, Countess of Snowdon, (Margaret Rose 21 August 1930 - 9 February 2002) was the younger daughter of King George VI and Queen Elizabeth The Queen Mother and the only sibling of Queen Elizabeth II. Princess Margaret, Countess of Snowdon, (Margaret Rose 21 August 1930 - 9 February 2002) was the younger daughter of King George VI and Queen Elizabeth The Queen Mother and the only sibling of Queen Elizabeth II. Princess Margaret, Countess of Snowdon, (Margaret Rose 21 August 1930 - 9 February 2002) was the younger daughter of King George VI and Queen Elizabeth The Queen Mother and the only sibling of Queen Elizabeth II. ... | Bulger was one of the FBI's most wanted fugitives for 16 years until he was captured in Santa Monica, California, in 2011. He was convicted in 2013 of a litany of crimes, including racketeering, extortion, money-laundering, and murder. He was sentenced to two consecutive life sentences plus five years. He died in federal prison in West Virginia on Tuesday at the age of 89. Bulger was one of the FBI's most wanted fugitives for 16 years until he was captured in Santa Monica, California, in 2011. | | DBS | She married Antony Armstrong-Jones, a photographer, in 1960. It was the first marriage for the Queen and the first for Prince Philip, Duke of Edinburgh. After divorcing Armstrong-Jones in 1978, she married Group Captain Peter Townsend in June that same year. She died at the age of 71 on 9 February 2002. Why did Princess Margaret marry Antony Armstrong- Jones? | He was one of the FBI's most wanted fugitives for 16 years until his capture in 2011. Born in Boston, Whitey Bulger was the son of Irish immi- grants. After serving in the U.S. Navy during World War II, Whitey Bulger joined the Irish-American mafia, the Winter Hill Gang, in the early 1950s. He quickly rose through the ranks of the gang, eventually becoming its leader. He was known as 'Whitey' because of his light brown hair and blue eyes. | | BS b | Princess Margaret, Countess of Snowdon (Margaret Rose 21 August 1930 - 9 February 2002) was the eldest daugh- ter of King George VI and Queen Elizabeth The Queen Mother. Princess Margaret (Margaret Rose 21 August 1930 - 9 February 2002) was the eldest child of King

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me and meeting me at the river. I live in your legacy and you live in mine. Ubuntu! Dear Ancestors. What did you hope for when you went to the Americas. What were you running from? Where were you heading? Did you feel sorry for the people of the land you lived on? What were your dreams made of? These engagements with the themes of the CHC, through their materialization in artworks, reached a broader audience. By centering the past on the creation of the future, the hope is to disrupt the hierarchy of progress hidden beneath a linear perception of time -the idea that one can only exist at odds with the other. Embracing our ancestral roots and giving them space in our existence allows us to reunite past, present and future within ourselves, which is a crucial element not only of individual healing, but also of shaping the kinds of conversations across time and space that can foster a sustainable future. The shift from individual to collective memory can play a crucial role in reshaping our cultural and societal identities.²³ This process involves both remembering our ancestral experience and wisdom and imagining how they can be transposed into future scenarios. Allowing a continuous interaction between past, present and future experiences, and understanding time in a non-linear way, is a way of disrupting the narratives of linear progress embedded in Western thinking. Indeed, the idea of nonlinearity, or circularity, is echoed more broadly in Indigenous cultures ' approach 23 Bachleitner (2022). Collective memory and the social creation of identities: Linking the past with the present and future. to time, and particularly in the worldview of author Robin Wall Kimmerer, for whom time is often conceptualized as circular or cyclical. Kimmerer also puts forward the idea that the non-linearity of time is linked to a vision of the interconnection between all forms of life.² ⁴ The Common Ground program, beyond the CHC weekend, thus offers a space to explore these collaborative processes and alternative temporal frameworks through art, poetry, letters and other forms of entanglement. ## Bringing the Body into the Collective Healing Process A key aspect of the Common Ground residency and its application of the CHC methodology was the understanding that knowledge is not produced in a vacuum but is deeply connected to the bodily experiences of those involved. As anchored in decolonial theory, this perspective challenges the

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BASE DURING FINANCIAL DERIVATIVES ARRANGEMENTS Company A is a mining company in Country A. It has entered into a long-term financial derivative instrument arrangement with an overseas-based independent Investment Bank Z: • whereby if the market price of the commodity extracted by Company A falls below a set price of USD 100, Investment Bank Z will pay Company A the difference between the set price (USD 100) and the actual market price. • whereby if the market price of the commodity rises above the set price, Company A pays the difference to Investment Bank Z. Based on the facts of the case, the price was set at USD 100, while the market demand trends and longer-term prognosis indicated that the commodity price would be mostly rising in the coming 5 years to USD 120, USD 130, USD 150, USD 170, and USD 200, respectively, with a very low risk that the price drops below USD 100. As a result of this arrangement, most of the profits earned over the 5-year period are paid to the independent Investment Bank Z. During the audit, an exchange of information exercise was carried out, which identified that Investment Bank Z had entered into an identical but reverse arrangement with Company B, which is controlled by the beneficial owner of Company A. As a result of this arrangement, most of the profit—less the annual administration fee that stays with the bank— was paid to Company B. Investment Bank Z was thus acting as a mere intermediary, which was effectively a BEPS arrangement between related parties in Companies A and B. Ring-fencing rules could avoid this type of scenario by ring-fencing the outcomes of such derivative instrument arrangements into separate tax bases that would not allow Company A to offset such expenses resulting from derivatives unless the gain was made on such a derivative transaction. This way, even in the absence of detection of such a BEPS arrangement, the tax base is protected. Ring-fencing rules effectively disallow Company A from offsetting losses derived from these types of transactions from mining revenues. In case of legitimate derivative arrangements, the company will still be entitled to offset the derivative losses from derivative gains earned in subsequent periods. This feature of ring-fencing rules is particularly relevant for developing countries that may lack the tools and infrastructure to detect such abusive arrangements. Note: Such a structure is also possible directly

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| | … | … | … | … | … | Belarus | | | 0.95 | 0.88 | 0.8 | 1 | … | Belgium | | Bermuda | … | … | … | … | … | | | Bosnia and Herzegovina | 0.58 | … | … | 0.5 | … | | | Bulgaria | 0.56 | 0.65 | 0.73 | 0.71 | … | | | | 0.88 | 0.78 | 0.7 | 0.83 | … | Canada | | Croatia | … | … | … | … | … | | | | 0.84 | | 0.55 | … | … | Czechia 0.47 | | | … | 0.68 | 0.77 | 0.83 | … | Denmark | | | 0.88 | 0.83 | 0.95 | 0.83 | … | Estonia | | Finland | 0.88 | 0.81 | 0.85 | … | 100 ₋₂ | | | France | 1 | 0.99 | 1 | 1 | … | | | | 1 | 0.9 | 0.95 | 0.92 | … | Germany | | Greece | … | … | … | … | … | | | | 1 | 0.86 | 0.93 | 0.79 | … | Hungary | | Iceland | … | … | … | … | … | | | | 0.88 | 0.81 | 0.85 | 0.83 | … | Ireland | | Italy | 0.88 | 0.88 | 0.8 | 0.83 | … | | | Latvia | 1 | | | | | 0.86 | | | | … | 0.95 | 1 … | … … | | | Lithuania | 1 | | … 0.9 | 1 | … | Liechtenstein … 0.85 | | | … | … | … | … | … | Luxembourg | | Malta | | | 0.9 | 0.92 | … | 0.84 0.72 | | | 0.88 | 0.79 | 0.85 | 0.67 | 100 | Monaco | | | … | | … | … | … | Montenegro … | | Netherlands (Kingdom of | … | … | … | … | … | the) | | North | … | … | … | … | … | Macedonia | | Norway | … | … | … | … | … | | |

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The analysis of endurance, measured in cycles, is performed using the method de- scribed by IEC 61951-2, clause 7.5.1.4. Figure 10 shows the cycling profiles of an AAA NiMH battery. The test procedure is as follows: 1. The battery is first discharged at a rate of 0.2 C until it reaches the cut-off voltage of 1 V . 2. The battery is then charged for 2 h at a 0.5 C rate. The charge termination criterion is either a ∆V of 5 mV to 10 mV (this criterion refers to a decline of voltage during charge after a certain time) or a maximum charge time of 132 min.Batteries 2025 ,11, 30 14 of 20 3. Immediately after charging, the battery is discharged at a 0.5 C rate until it reaches the cut-off voltage of 1 V . Batteries 2025, 11, x FOR PEER REVIEW 15 of 21 Furthermore, all portable NiMH batteries tested during the recovery experiment show a discharge duration longer than 4 h, and in terms of columbic eﬃciency, the highest observed value is 78% for the D size and the smallest value is 62% for the 9V battery. 6. Endurance of Portable NiMH Batteries The analysis of endurance, measured in cycles, is performed using the method de- scribed by IEC 61951-2, clause 7.5.1.4. Figure 10 shows the cycling proﬁles of an AAA NiMH battery. The test procedure is as follows: 1. The battery is ﬁrst discharged at a rate of 0.2 C until it reaches the cut-oﬀ voltage of 1 V. 2. The battery is then charged for 2 h at a 0.5 C rate. The charge termination criterion is either a ΔV of 5 mV to 10 mV (this criterion refers to a decline of voltage during charge after a certain time) or a maximum charge time of 132 min. 3. Immediately after charging, the battery is discharged at a 0.5 C rate until it reaches the cut-oﬀ voltage of 1 V. If the discharge duration is less than 72 min, the experiment is terminated. Figure 10. NiMH endurance in cycles analysis according to IEC 61951-2 for an AAA Energizer 700 mAh battery (a) voltage proﬁle, (b) current proﬁle, (c) capacity, and d) columbic eﬃciency vs. cycle number. The vertical red lines in (c,d) indicate checkup cycles. Moreover, every 50 cycles a checkup cycle is performed using the standard condi- tions for capacity rate calculation (charge

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the high cost of complying with regulations that apply once companies reach a particular size. As a result, the EU has proportionally fewer small and medium-sized companies than the US and proportionally more micro companies [see Figure 7] . However, there is a close link between the size of companies and technology adoption. Evidence from the US show that adoption rises with firm size for all advanced technologiesxii. Likewise, while in 2023 30% of large businesses in the EU had adopted AI, only 7% of SMEs had done the samexiii. Size enables adoption because larger companies can spread the high fixed costs of AI investment over greater revenues, they can count on more skilled management to make the necessary organisational changes, and they can deploy AI more productively owing to larger data sets. In other words, a fragmented Single Market puts EU companies at a disadvantage in terms of the speed of adoption and diffusion of new AI applications. 04. Regulatory gold-plating refers to the practice where national governments or authorities go beyond the minimum requirements set by European Union legislation when implementing it into domestic law. 30THE FUTURE OF EUROPEAN COMPETITIVENESS — PART A | CHAPTER 2FIGURE 7 Size distribution of firms in EU and US 2021 Note: Does not include the self-employed. EU data refer to the following sectors: industry, construction and market services (except public administration and defence; compulsory social security; activities of membership organizations). For the EU, to discount the self-employed, data on businesses with 0 employees has been used as a proxy.US data refers to the private sector, which includes agriculture but represents around 1% of the total firms. Data for the US is based on the 1st quarter of the year. Source: ECB calculations based on Eurostat and Bureau of Labour Statistics data Competition for computing power and lack of investment in connectivity could soon translate into digital bottlenecks [see the chapter on digitalisation and advanced technologies] . Training new foundation models and building vertically integrated AI applications requires massive increases in computing power, which is triggering an ongoing global “AI chip race” at huge expense. This is a race in which smaller and less well-funded EU companies may struggle to compete. Mainly due to the computational power required, the cost of training frontier AI models is estimated to have grown by a factor of 2 to 3 per year for the past eight

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| | Figure 6.2 | Teacher hiring and firing is politically influenced in many countries ....................................................................................... | 120 | | Figure 6.3 | Within two years of their appointment, 51% of education ministers have left office........................................................ | 123 | | Figure 7.1 | A country-led process will be used to make decisions on education statistics................................................................... | 146 | | Figure 7.2 | Some SDG 4 indicators have been under scrutiny due to low data coverage....................................................................... | 147 | | Figure 8.1 | Since 2015, the out-of-school population has stagnated........................................................................................................... | 152 | | Figure 8.2 | Sub-Saharan Africa accounts for more than half of the total number out-of-school children and adolescents ........................................................................................................................................................................................ | 154 | | Figure 8.3 | COVID-19 does not appear to have had a negative impact on out-of-school rates ........................................................... | 155 |

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salaries of bogus/ghost employees in Delhi alone by the Municipal Corporation of Delhi (MCD). In 2004, over Rs. 32 lakhs (Rs. 3 million or £2.7 million) was released for salaries of 1,826 employees. Six MCD officials were arrested in con -nection with the embezzlement (Times of India, 2009). In summary, previous research demonstrates that government urban health care does not meet the needs of the poor. There seems to be at least four main reasons according to the literature - a shortage of government provision, the attitude of doctors in the government sector to the urban poor, corruption within the system and a lack of trust. Evidence suggests that some doctors and medical practitioners in government hospitals have a poor attitude towards patients from low-income households, offering a poor quality of care (National Family Health Survey, 2014 ; Peters and Muraleedharan, 2008 ; Ishwardat et al., 2016). This leads to issues around trust (Raha et al., 2010 ; Aneli et al., 2018). Large numbers of medical practitioners, as many as 40% in a typical day, are also absent from government facilities ( Pulla, 2015 ; Chaudhury et al., 2006). Corruption within the government system has implied a lack of structure and efficiency around provision ( Kumar, 2003 ; World Bank, 2008 ; Dash et al., 2009 ; Sengupta and Nandy, 2005). Reports around corruption have targeted the Municipal Corporation of Delhi, which is responsible for improvements and coordination of medical health facilities around the city ( Dash et al., 2009 ; Naher et al., 2020). � In our research of the healthcare providers surveyed, more than 50% have been practising for over 20 years in their slum community. Their ages ranged from 22 to 64 years ( x = 38.93, σ = 10.576). The majority (90.7%) reported that they had no other occupation and working in medicine was their only job. There was a split in residency, with 40.8% stating that they lived in the community and 59.2% indicat -ing that they lived outside the community where they practice medicine. This could have some bearing on the levels of trust and respect. However, we could conjecture that as stated by the practitioners themselves long term respect and trust is gained owing to effective and efficient diagnosis, medicine prescriptions and the curing of ailments. According to Dr Dwivedi trust from the community comes with time and reliability: 'The patients from this

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RING -FENCING 1.0 INTRODUCTION 34 Ring-Fencing Mining Income: A toolkit for tax administrators and policy-makersor incentives available in respect of the profits from downstream activities. On the other hand, taxpayers may prefer to accelerate their cash flows and benefit from tax deferral due to the special rules applicable for the extractive operations, such as the accelerated deduction of capital expenditure (e.g., immediate 100% deduction of such expenditure, rather than being subject to gradual depreciation). Countries will be able to collect taxes from upstream activities (i.e., mining) regardless of the costs (e.g., development costs of downstream infrastructure or losses incurred at the downstream stage, such as risks playing out during the processing, smelting, refining, or transport), or vice versa. As explained above, there may be a motivation to offset downstream expenses against upstream income if upstream is subject to a higher rate of tax. T anzania includes this type of ring-fence in its legislation (see Box 10). Countries with a highly integrated mining sector and differential tax rates may wish to consider this variation. BOX 10. TANZANIA • losses from the separate mining operations may be deducted only in calculating future income from that operation and not income from any other activity whethera mining operation under a different mineral right, processing, smelting, refining or a non-mining activity; • income from the separate mining operations may not be reduced by a loss from any other activity whether a mining operation under a different mineral rights, processing , smelting , refining or a non-mining activity.” Source: Section 65F (1)a, and 1(b) of Chapter 332, Income T ax Act (rev. 2019). Italics are authors’ emphasis. If resource-rich developing countries are seeking to encourage downstream activities, the existence of ring-fencing rules might be a relevant consideration for an investor in considering the economic viability and attractiveness of doing so. The fact that the profits from the downstream activities often result in lower rates of profitability is also reflected in the lower rate of CIT that is applicable to those profits. The investors may want to benefit from the deferral of tax on the upstream activities if they undertake such additional investment into downstream activities; this is why it may be more attractive for investors if there is no ring-fencing regime. Careful consideration should be given to what the costs are (e.g., timing difference of tax collection) and what the benefits are (e.g., attracting investment for

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a kind used for the extraction of ‘soft’ fixed vegetable oils (excluding flours and meals) X X X X 223Oil-seeds and oleaginous fruits, whole or broken, of a kind used for the extraction of other fixed vegetable oils (including flours and meals of oil-seeds or oleaginous fruit, n.e.s.) 231Natural rubber, balata, gutta-percha, guayule, chicle and similar natural gums, in primary forms (including latex) or in plates, sheets or strip 232 Synthetic rubber; reclaimed rubber; waste, parings and scrap of unhardened rubber 244 Cork, natural, raw and waste (including natural cork in blocks or sheets) 245 Fuel wood (excluding wood waste) and wood charcoal X 246 Wood in chips or particles and wood waste X 247 Wood in the rough, whether or not stripped of bark or sapwood, or roughly squared X X Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation305 306 Annexes ARMENIA AZERBAIJAN BELARUS GEORGIA MOLDOVA UKRAINE SITC Goods name Current Emerging Current Emerging Current Emerging Current Emerging Current Emerging Current Emerging 19 12 3 8 65 64 18 26 41 23 51 52 248 Wood, simply worked, and railway sleepers of wood X X X X 251 Pulp and waste paper 261 Silk 263 Cotton 264Jute and other textile bast fibres, n.e.s., raw or processed but not spun; tow and waste of these fibres (including yarn waste and garnetted stock) 265 Vegetable textile fibres (other than cotton and jute), raw or processed but not spun; waste of these fibres 266 Synthetic fibres suitable for spinning X 267 Other man-made fibres suitable for spinning; waste of man-made fibres 268 Wool and other animal hair (including wool tops) 269 Worn clothing and other worn textile articles; rags 271 Confidential trade of group 271 272 Fertilizers, crude, other than those of division 56 273 Stone, sand and gravel X X 274 Sulphur and unroasted iron pyrites 277 Natural abrasives, n.e.s. (including industrial diamonds) 278 Other crude minerals X X X 281 Iron ore and concentrates X X 282 Ferrous waste and scrap; remelting scrap ingots of iron or steel X 283 Copper ores and concentrates; copper mattes; cement copper X X X 284Nickel ores and concentrates; nickel mattes, nickel oxide sinters and other intermediate products of nickel metallurgy 285 Aluminium ores and concentrates (including alumina) X X 286 Uranium or thorium ores and concentrates 287 Ores and concentrates of base metals, n.e.s. X X 288 Non-ferrous

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[]

export specialisation for Azerbaijan | SITC | Goods name | Current strength | %share of exports | Emerging strength | %share of exports | |--------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------|---------------------|---------------------|---------------------| | | | 3 | 88.0% | 8 | 90.8% | | 0 | Food and live animals | | | | | | 054 | Vegetables, fresh, chilled, frozen or simply preserved (including dried leguminous vegetables); roots, tubers and other edible vegetable products, n.e.s., fresh or dried | | | X | 0.7% | | 057 | Fruit and nuts (not including oil nuts), fresh or dried | | | X | 1.3% | | 1 | Beverages and tobacco | | | | | | 2 | Crude materials, inedible, except fuels | | | | | | 3 | Mineral fuels, lubricants and related materials | | | | | | 333 | Petroleum oils and oils obtained from bituminous minerals, crude | X | 82.1% | X | 82.1% | | 335 | Residual petroleum products, n.e.s., and related materials | | | X | 0.2% | | 343 | Natural gas, whether or not liquefied | X | 5.6% | X | 5.6% | | 351 | Electric current | | | X | 0.2% | | 4 | Animal and vegetable oils, fats and waxes | | | | | | 5 | Chemicals and related products, n.e.s. | | | | | | 571 | Polymers of ethylene, in primary forms | X | 0.4% | | | | 6 | Manufactured goods classified chiefly by material | | | | | | 679 | Tubes, pipes and hollow profiles, and tube or pipe fittings, of iron or steel | | | X | 0.2% | | 684 | Aluminium | | | X | 0.5% | | 7 | Machinery and transport equipment | | | | | | 8 | Miscellaneous manufactured articles | | | | | | 9 | Commodities and transactions not classified elsewhere in the SITC | | | | | ## Mapping of goods export specialisations - results for Georgia Results of the export mapping for Georgia are shown in Table 2.18 . The 18 goods categories with current strength represent almost 61% of the total exports for 2012-2019. Specialised exports in Beverages and tobacco (SITC 1) account for more than 13% of the total exports, those in Crude materials, inedible,

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[]

as experiences of searching for belonging. Despite coming from different cultures, religions and nationalities, participants found that power structures and oppressive narratives overlapped and converged in their stories. The group also explored how these legacies continue to shape their lives today. On the second day, activities focused on the third and fourth pillars of CHC: strengthening interconnection, and envisioning just and sustainable futures. After participating in outdoor activities, the group reconvened in a circle to share stories of resilience and survival from their families and communities. Building on the work of the first day, this activity invited participants to reflect on the strengths and coping strategies of their ancestors and to explore how their cultural heritage has equipped them with the resources to face contemporary challenges. It also invited participants to consider the more-than-human as a teacher of resilience and sustainable ways of relating to one another. The activity began with an extract from Robin Wall Kimmerer s book ' Braiding Sweetgrass , ²² which describes how the ' three sisters ' , bean, corn and pumpkin seeds, are planted together in a gardening method practised by Native American peoples. Based on a biological and scientific study of the interactions between these three species, Kimmerer teaches us how, planted together and thanks to the unique characteristics of each plant, they create an environment where they all benefit from each other s presence. This ecological lesson opened the day s sharing ' ' circle, presenting symbiosis as a metaphor for human and more-than-human healing. Throughout the sharing circles, the facilitators chose not to intervene too much in the powerful process of community building that was being woven before their eyes. Indeed, as the discussions progressed, a process of solidarity and mutual recognition emerged, weaving together distinct but interconnected experiences. After providing a theoretical framework, they mostly let the natural flow of the conversation take over, occasionally stepping in to restart the discussion, as the participants were very engaged and responding to each other. Very quickly, the group created a particularly deep and transformative space for sharing. One of the reasons for this is certainly the pre-existing connection among the participants forged during the first online phase of the program. After each workshop, at least one hour was dedicated to discussion and sharing of experiences among the participants. This process of connecting individual experiences and sharing personal/intimate aspects of one s life

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60% of the records. Alternatively, Figure 3.19 presents the distribu- tion of analysed records in the form of weighted percentages by type of record. This means that percentages are calculated within each domain relative to the total number of records per data source. This figure, complementing Figure 3.18, allows to better observe the distribution patterns of patents and EC projects, which are smaller, in volume terms, than publications. As presented in Figure 3.19, Governance, culture, education and the economy is primarily composed of EC R&I projects due to the nature of the Eu- ropean research and innovation framework pro- grammes, which support capacity building as well as transnational cooperation projects, typically oriented to research, education, economic devel- opment, education as well as some priority areas such as ICT, energy, transportation and the envi- ronment. Thus, although R&I projects are not the ideal source for identifying purely emerging spe- cialisations, they do allow relevant internationally connected actors in the EaP to be identified, espe- cially in the areas above, as well as, again, gaug- ing the strength of the hard sciences in the EaP. It also enables different relative specialisations to be explored throughout the EaP countries. 58 Noting that the total volume of analysed scientific publi- cations is higher than that of patents. Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation155 Agrifood Biotechnology Chemistry and chemical engineering Electric and electronic technologies Energy Environmental sciences and industries Fundamental physics and mathematics Governance, culture, education and the economy Health and wellbeing ICT and computer science Mechanical engineering and heavy machinery Nanotechnology and materials Optics and photonics Transportation Agrifood 964 315 65 149 1 347 138 196 722 133 615 236 45 52 Biotechnology 964 3 277 178 325 465 342 110 2 687 138 212 1 656 109 45 Chemistry and chemical engineering315 3 277 111 314 694 308 40 682 88 143 1 809 91 9 Electric and electronic technologies65 178 111 3 102 148 660 121 217 1 008 1 213 1 004 856 240 Energy 149 325 314 3 102 666 2 470 288 257 504 2 135 799 185 326 Environmental sciences and industries1 347 465 694 148 666 512 1 128 754 592 693 542 101 113 Fundamental physics and mathematics138 342 308 660 2 470 512 520 414 1 164 1 139 2 115 930 258 Governance, culture, education and the

[ "60", "%", "of", "the", "\n", "records", ".", "\n", "Alternatively", ",", "Figure", "3.19", "presents", "the", "distribu-", "\n", "tion", "of", "analysed", "records", "in", "the", "form", "of", "weighted", "\n", "percentages", "by", "type", "of", "record", ".", "This", "means", "that", "\n", "percentages", "are", "calculated", "within", "each", "domain", "\n", "relative", "to", "the", "total", "number", "of", "records", "per", "data", "\n", "source", ".", "This", "figure", ",", "complementing", "Figure", "3.18", ",", "\n", "allows", "to", "better", "observe", "the", "distribution", "patterns", "\n", "of", "patents", "and", "EC", "projects", ",", "which", "are", "smaller", ",", "in", "\n", "volume", "terms", ",", "than", "publications", ".", "\n", "As", "presented", "in", "Figure", "3.19", ",", "Governance", ",", "culture", ",", "\n", "education", "and", "the", "economy", "is", "primarily", "composed", "\n", "of", "EC", "R&I", "projects", "due", "to", "the", "nature", "of", "the", "Eu-", "\n", "ropean", "research", "and", "innovation", "framework", "pro-", "\n", "grammes", ",", "which", "support", "capacity", "building", "as", "well", "\n", "as", "transnational", "cooperation", "projects", ",", "typically", "\n", "oriented", "to", "research", ",", "education", ",", "economic", "devel-", "\n", "opment", ",", "education", "as", "well", "as", "some", "priority", "areas", "\n", "such", "as", "ICT", ",", "energy", ",", "transportation", "and", "the", "envi-", "\n", "ronment", ".", "Thus", ",", "although", "R&I", "projects", "are", "not", "the", "\n", "ideal", "source", "for", "identifying", "purely", "emerging", "spe-", "\n", "cialisations", ",", "they", "do", "allow", "relevant", "internationally", "\n", "connected", "actors", "in", "the", "EaP", "to", "be", "identified", ",", "espe-", "\n", "cially", "in", "the", "areas", "above", ",", "as", "well", "as", ",", "again", ",", "gaug-", "\n", "ing", "the", "strength", "of", "the", "hard", "sciences", "in", "the", "EaP.", "\n", "It", "also", "enables", "different", "relative", "specialisations", "to", "\n", "be", "explored", "throughout", "the", "EaP", "countries", ".", "\n", "58", "Noting", "that", "the", "total", "volume", "of", "analysed", "scientific", "publi-", "\n", "cations", "is", "higher", "than", "that", "of", "patents", ".", "\n", "Smart", "Specialisation", "in", "the", "Eastern", "Partnership", "countries", "-", "Potential", "for", "knowledge", "-", "based", "economic", "cooperation155", "\n", "Agrifood", "\n", "Biotechnology", "\n", "Chemistry", "and", "chemical", "\n", "engineering", "\n", "Electric", "and", "electronic", "\n", "technologies", "\n", "Energy", "\n", "Environmental", "sciences", "and", "\n", "industries", "\n", "Fundamental", "physics", "and", "\n", "mathematics", "\n", "Governance", ",", "culture", ",", "\n", "education", "and", "the", "economy", "\n", "Health", "and", "wellbeing", "\n", "ICT", "and", "computer", "science", "\n", "Mechanical", "engineering", "and", "\n", "heavy", "machinery", "\n", "Nanotechnology", "and", "\n", "materials", "\n", "Optics", "and", "photonics", "\n", "Transportation", "\n", "Agrifood", "964", "315", "65", "149", "1", "347", "138", "196", "722", "133", "615", "236", "45", "52", "\n", "Biotechnology", "964", "3", "277", "178", "325", "465", "342", "110", "2", "687", "138", "212", "1", "656", "109", "45", "\n", "Chemistry", "and", "chemical", "\n", "engineering315", "3", "277", "111", "314", "694", "308", "40", "682", "88", "143", "1", "809", "91", "9", "\n", "Electric", "and", "electronic", "\n", "technologies65", "178", "111", "3", "102", "148", "660", "121", "217", "1", "008", "1", "213", "1", "004", "856", "240", "\n", "Energy", "149", "325", "314", "3", "102", "666", "2", "470", "288", "257", "504", "2", "135", "799", "185", "326", "\n", "Environmental", "sciences", "and", "\n", "industries1", "347", "465", "694", "148", "666", "512", "1", "128", "754", "592", "693", "542", "101", "113", "\n", "Fundamental", "physics", "and", "\n", "mathematics138", "342", "308", "660", "2", "470", "512", "520", "414", "1", "164", "1", "139", "2", "115", "930", "258", "\n", "Governance", ",", "culture", ",", "\n", "education", "and", "the" ]

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rising to this challenge. Since the Great Financial Crisis (GFC), a sizeable and persistent gap has opened between private productive investment01 in the EU and the US. At the same time, the private investment gap across the two economies has not been offset by higher government investment, which also dropped after the GFC and has been persistently lower in the EU compared to the US as a share of GDP. EU households provide ample savings to finance higher investment, but at present these savings are not being channelled efficiently into productive investments. In 2022, EU household savings were EUR 1,390 billion compared with EUR 840 billion in the US. But, despite their higher savings, EU households have considerably lower wealth than their US counterparts, largely because of the lower returns they receive from financial markets on their asset holdings. The EU can meet these investment needs without overstretching the resources of the European economy, but the private sector will need public support to finance the plan . The European Commission and the IMF’s Research Department have simulated scenarios of a sustained EU investment push of around 5% of GDP, using their multi-country models. The results suggest that investment of this magnitude would increase output by around 6% within 15 years. Since supply adjusts more gradually than demand – as the build-up of additional capital takes time – the transition phase implies some inflationary pressures, but these pressures dissipate over time. Unlocking the investment will be challenging. Historically in Europe, around four-fifths of productive investment has been under - taken by the private sector, and the remaining one-fifth by the public sector. Delivering private investment of around 4% of GDP through market financing alone would require a reduction in the private cost of capital – by approximately 250 basis points in the European Commission model. Although improved capital market efficiency (e.g. through the completion of the Capital Markets Union) is expected to reduce private financing costs, the reduction will likely be substantially smaller. Fiscal incentives to unlock private investment therefore appear necessary to finance the investment plan, in addition to direct government investment. The required stimulus to private investment will have some impact on public finances, but productivity gains can reduce the fiscal costs . If the investment-related government spending is not compensated by budgetary savings elsewhere, primary fiscal balances may temporarily deteriorate before the investment plan fully exerts its positive

[ "rising", "to", "this", "challenge", ".", "Since", "the", "Great", "Financial", "Crisis", "(", "GFC", ")", ",", "a", "\n", "sizeable", "and", "persistent", "gap", "has", "opened", "between", "private", "productive", "investment01", "in", "the", "EU", "and", "the", "US", ".", "At", "the", "same", "\n", "time", ",", "the", "private", "investment", "gap", "across", "the", "two", "economies", "has", "not", "been", "offset", "by", "higher", "government", "investment", ",", "\n", "which", "also", "dropped", "after", "the", "GFC", "and", "has", "been", "persistently", "lower", "in", "the", "EU", "compared", "to", "the", "US", "as", "a", "share", "of", "GDP", ".", "\n", "EU", "households", "provide", "ample", "savings", "to", "finance", "higher", "investment", ",", "but", "at", "present", "these", "savings", "are", "not", "being", "\n", "channelled", "efficiently", "into", "productive", "investments", ".", "In", "2022", ",", "EU", "household", "savings", "were", "EUR", "1,390", "billion", "compared", "\n", "with", "EUR", "840", "billion", "in", "the", "US", ".", "But", ",", "despite", "their", "higher", "savings", ",", "EU", "households", "have", "considerably", "lower", "wealth", "than", "\n", "their", "US", "counterparts", ",", "largely", "because", "of", "the", "lower", "returns", "they", "receive", "from", "financial", "markets", "on", "their", "asset", "holdings", ".", "\n", "The", "EU", "can", "meet", "these", "investment", "needs", "without", "overstretching", "the", "resources", "of", "the", "European", "economy", ",", "\n", "but", "the", "private", "sector", "will", "need", "public", "support", "to", "finance", "the", "plan", ".", "The", "European", "Commission", "and", "the", "IMF", "’s", "\n", "Research", "Department", "have", "simulated", "scenarios", "of", "a", "sustained", "EU", "investment", "push", "of", "around", "5", "%", "of", "GDP", ",", "using", "their", "\n", "multi", "-", "country", "models", ".", "The", "results", "suggest", "that", "investment", "of", "this", "magnitude", "would", "increase", "output", "by", "around", "6", "%", "\n", "within", "15", "years", ".", "Since", "supply", "adjusts", "more", "gradually", "than", "demand", "–", "as", "the", "build", "-", "up", "of", "additional", "capital", "takes", "time", "\n", "–", "the", "transition", "phase", "implies", "some", "inflationary", "pressures", ",", "but", "these", "pressures", "dissipate", "over", "time", ".", "Unlocking", "the", "\n", "investment", "will", "be", "challenging", ".", "Historically", "in", "Europe", ",", "around", "four", "-", "fifths", "of", "productive", "investment", "has", "been", "under", "-", "\n", "taken", "by", "the", "private", "sector", ",", "and", "the", "remaining", "one", "-", "fifth", "by", "the", "public", "sector", ".", "Delivering", "private", "investment", "of", "around", "\n", "4", "%", "of", "GDP", "through", "market", "financing", "alone", "would", "require", "a", "reduction", "in", "the", "private", "cost", "of", "capital", "–", "by", "approximately", "\n", "250", "basis", "points", "in", "the", "European", "Commission", "model", ".", "Although", "improved", "capital", "market", "efficiency", "(", "e.g.", "through", "\n", "the", "completion", "of", "the", "Capital", "Markets", "Union", ")", "is", "expected", "to", "reduce", "private", "financing", "costs", ",", "the", "reduction", "will", "likely", "\n", "be", "substantially", "smaller", ".", "Fiscal", "incentives", "to", "unlock", "private", "investment", "therefore", "appear", "necessary", "to", "finance", "the", "\n", "investment", "plan", ",", "in", "addition", "to", "direct", "government", "investment", ".", "\n", "The", "required", "stimulus", "to", "private", "investment", "will", "have", "some", "impact", "on", "public", "finances", ",", "but", "productivity", "gains", "\n", "can", "reduce", "the", "fiscal", "costs", ".", "If", "the", "investment", "-", "related", "government", "spending", "is", "not", "compensated", "by", "budgetary", "\n", "savings", "elsewhere", ",", "primary", "fiscal", "balances", "may", "temporarily", "deteriorate", "before", "the", "investment", "plan", "fully", "exerts", "its", "\n", "positive" ]

[]

to their commercial attractiveness, and the tax deferral benefit plays a limited role in making such investment decisions. These considerations are relevant for designing special exceptions from the ring-fencing rules, such as for the purpose of attracting investment into the marginal ore projects, where the tax deferral advantage may play an important role. Some resource-rich countries have found it necessary to relax their ringfencing rules to attract further investment. Resource-rich countries such as PNG and South Africa have had ring-fencing rules for a long time. At some point, these governments considered the need to relax strict ring-fencing rules to attract further investment in the context of low commodity prices (see Box 7). On the other hand, countries such as Kenya, PNG, and the Cook Islands have introduced an exemption to ring-fencing rules in which ## 1.0 INTRODUCTION 2.0 THE FUNDAMENTALS OF RING-FENCING ## 3.0 THE BENEFITS AND RISKS OF RING-FENCING 4.0 DESIGNING RING-FENCING RULES 5.0 THE IMPLEMENTATION OF RING-FENCING RULES 6.0 CONCLUSION unsuccessful exploration expenditures are incurred by the mining investor who holds more than one mine. The policy objective behind the exception seems to be to try to balance different policy objectives: deliver early government revenues and attract exploration investments to their jurisdiction. See Section 4 for more details. ## BOX 7. THE RELAXATION OF RING-FENCING RULES IN PNG AND SOUTH AFRICA Photo: Raina Hattingh ## South Africa In the early 1980s, many mines were being developed in South Africa. If a company owned more than one mine, the unredeemed capital expenditure of one mine could be deducted from the mining income from another mine. Some major mergers and takeovers caused the government authorities to express concerns that vast new capital expenditures could substantially erode the mining tax base. Consequently, South Africa introduced ring-fencing rules mine by mine and distinguished mining from non-mining activities (Davis Tax Committee, 2016, p. 50). Following a steep decline in new mining investment, South Africa announced a partial relaxation of the ring-fencing rules for 'new mines' (a mine opened after March 14, 1990) (Leger & Nicol, 1992). This meant that the 'old mines' in the same entity may have access to the unredeemed capital expenditure of the 'new mine' but limited to 25% of the remaining taxable income of the 'old mines' after they have exhausted all their applicable capital expenditure in a given tax year' (Davis Tax Committee, 2014). Although the old ring-fencing

[ "to", "their", "commercial", "attractiveness", ",", "and", "the", "tax", "deferral", "benefit", "plays", "a", "limited", "role", "in", "making", "such", "investment", "decisions", ".", "These", "considerations", "are", "relevant", "for", "designing", "special", "exceptions", "from", "the", "ring", "-", "fencing", "rules", ",", "such", "as", "for", "the", "purpose", "of", "attracting", "investment", "into", "the", "marginal", "ore", "projects", ",", "where", "the", "tax", "deferral", "advantage", "may", "play", "an", "important", "role", ".", "\n\n", "Some", "resource", "-", "rich", "countries", "have", "found", "it", "necessary", "to", "relax", "their", "ringfencing", "rules", "to", "attract", "further", "investment", ".", "Resource", "-", "rich", "countries", "such", "as", "PNG", "and", "South", "Africa", "have", "had", "ring", "-", "fencing", "rules", "for", "a", "long", "time", ".", "At", "some", "point", ",", "these", "governments", "considered", "the", "need", "to", "relax", "strict", "ring", "-", "fencing", "rules", "to", "attract", "further", "investment", "in", "the", "context", "of", "low", "commodity", "prices", "(", "see", "Box", "7", ")", ".", "On", "the", "other", "hand", ",", "countries", "such", "as", "Kenya", ",", "PNG", ",", "and", "the", "Cook", "Islands", "have", "introduced", "an", "exemption", "to", "ring", "-", "fencing", "rules", "in", "which", "\n\n", "#", "#", "1.0", "INTRODUCTION", "\n\n", "2.0", "THE", "FUNDAMENTALS", "OF", "RING", "-", "FENCING", "\n\n", "#", "#", "3.0", "THE", "BENEFITS", "AND", "RISKS", "OF", "RING", "-", "FENCING", "\n\n", "4.0", "DESIGNING", "RING", "-", "FENCING", "RULES", "\n\n", "5.0", "THE", "IMPLEMENTATION", "OF", "RING", "-", "FENCING", "RULES", "\n\n", "6.0", "CONCLUSION", "\n\n", "unsuccessful", "exploration", "expenditures", "are", "incurred", "by", "the", "mining", "investor", "who", "holds", "more", "than", "one", "mine", ".", "The", "policy", "objective", "behind", "the", "exception", "seems", "to", "be", "to", "try", "to", "balance", "different", "policy", "objectives", ":", "deliver", "early", "government", "revenues", "and", "attract", "exploration", "investments", "to", "their", "jurisdiction", ".", "See", "Section", "4", "for", "more", "details", ".", "\n\n", "#", "#", "BOX", "7", ".", "THE", "RELAXATION", "OF", "RING", "-", "FENCING", "RULES", "IN", "PNG", "AND", "SOUTH", "AFRICA", "\n\n", "Photo", ":", "Raina", "Hattingh", "\n\n", "#", "#", "South", "Africa", "\n\n", "In", "the", "early", "1980s", ",", "many", "mines", "were", "being", "developed", "in", "South", "Africa", ".", "If", "a", "company", "owned", "more", "than", "one", "mine", ",", "the", "unredeemed", "capital", "expenditure", "of", "one", "mine", "could", "be", "deducted", "from", "the", "mining", "income", "from", "another", "mine", ".", "Some", "major", "mergers", "and", "takeovers", "caused", "the", "government", "authorities", "to", "express", "concerns", "that", "vast", "new", "capital", "expenditures", "could", "substantially", "erode", "the", "mining", "tax", "base", ".", "Consequently", ",", "South", "Africa", "introduced", "ring", "-", "fencing", "rules", "mine", "by", "mine", "and", "distinguished", "mining", "from", "non", "-", "mining", "activities", "(", "Davis", "Tax", "Committee", ",", "2016", ",", "p.", "50", ")", ".", "\n\n", "Following", "a", "steep", "decline", "in", "new", "mining", "investment", ",", "South", "Africa", "announced", "a", "partial", "relaxation", "of", "the", "ring", "-", "fencing", "rules", "for", "'", "new", "mines", "'", "(", "a", "mine", "opened", "after", "March", "14", ",", "1990", ")", "(", "Leger", "&", "amp", ";", "Nicol", ",", "1992", ")", ".", "\n\n", "This", "meant", "that", "the", "'", "old", "mines", "'", "in", "the", "same", "entity", "may", "have", "access", "to", "the", "unredeemed", "capital", "expenditure", "of", "the", "'", "new", "mine", "'", "but", "limited", "to", "25", "%", "of", "the", "remaining", "taxable", "income", "of", "the", "'", "old", "mines", "'", "after", "they", "have", "exhausted", "all", "their", "applicable", "capital", "expenditure", "in", "a", "given", "tax", "year", "'", "(", "Davis", "Tax", "Committee", ",", "2014", ")", ".", "Although", "the", "old", "ring", "-", "fencing" ]

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OF EUROPEAN COMPETITIVENESS — PART A | CHAPTER 2BOX 2 A closer look at the role of the ICT sector in the EU-US labour productivity gap The EU’s aggregate gap in labour productivity growth compared with the US reflects differences in industry composition, sectoral innovation and technology diffusion. The EU economy has traditionally been strong in all mid-technology sectors that are not at the centre of radical technological advances. The EU has less activity in sectors in which much of the productivity growth has originated in recent years, notably the ICT sector and the exploitation of large-scale digital services. Due to slow technology diffusion within industries, the EU’s productivity growth gap compared to the US was particularly pronounced in these industries with very high productivity growth. Excluding the main ICT sectors (the manufacturing of computers and electronics and information and communication activities) from the analysis, EU productivity has been broadly at par with the US in the period 2000-2019. The remaining disadvantage in productivity growth versus the US is significantly reduced to 0.2 percentage points (0.8% productivity growth for the US versus 0.6% for the EU). The actual EU-US gap can be considered close to zero as EU 27 productivity growth is 0.2 to 0.3percentage points higher than the EU10 selection (for which EU KLEMS data is available). For 2013-2019 the role of ICT is even more striking, as the EU productivity growth excluding the main ICT sectors exceeded that of the US by some margin. This analysis may underestimate the total impact of ICT developments on the productivity gap. In addition to ICT sectors, the US also has high productivity growth in professional services and finance and insurance, reflecting strong ICT technology diffusion effects. These sectors are amongst the biggest contributors to intangible investment in the total economy in the US. Also, some part of fintech is in the sector Finance and Insurance. On the other hand, the EU outperforms the US in mid-technology sectors like manufacturing of transport equipment, agriculture and in the wholesale and retail sectors. The latter reflects catching up effects to key innovations that had been introduced in the US in the previous decade such as in e-commerce and online retail reaching larger customer bases, implementation of advanced inventory management systems, digital payment systems, data analytics and robotics, and automation. 27THE FUTURE OF EUROPEAN COMPETITIVENESS — PART A | CHAPTER 2Key barriers to innovation in

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[]

5.5 7.7₊₁ MSR Nicaragua … 81 9 9 7 12 18 36 71 76 45 50 34 38 9.1 11.5 15₋₂ … 3₋₂ … … … … … … 18₋₁ … 59 … … … … 4.1ᵢ 3.8₋₁ 22.3ᵢ 17.7 NIC Panama 79 73 8 8 13 16 31 29 94 95 74 78 59 63 11.5 12.7 21₋₂ … 4₋₂ … … 42₋₁ … 16₋₁ … 39 99 … 94 … 98₋₁ … 3.4 3.4₋₁ 15.2 11.9 PAN Paraguay 76₊₁ 77 15 19 16 26 33 37 91 94 73 81 61 67 5.7 8.2 16₋₂ … 6₋₂ … … 34₋₁ … 15₋₁ 28₊₁ … … … … … … … 3.3 3.4 18.2₊₁ 22.0 PRY Peru 98 100 3 1 4 1 16 6 95 98 85 93 77 86 -0.6 0.3 31₋₂ … 23₋₂ … … 50₋₁ … 34₋₁ 71₊₁ 80 … 13 … … … … 4.0 4.2 17.6 19.2₊₁ PER Saint Kitts and Nevis … … … … … … … … … … … … … … … … … … … … … … … … 100₊₁ 100₋₂ 72 68₋₂ … … … … 2.5 3.6₋₁ 8.8 10.2₊₁ KNA Saint Lucia 95 48 1 1 9 7 21 21 99 100 95 98 84 92 16.4 13.0 … … … … … … … … … 100 … 77 … 70 … 66 3.9 3.7₋₁ 16.5 16.3₋₁ LCA Saint Vincent/Grenadines 96 58₋₁ 0.4 0.3 4 3 23 19 … … … … … … … … … … … … … … … … 100₊₁ … 84 79 … … … … 5.0 7.2₋₁ 17.2 12.6₊₁ VCT Sint Maarten … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … 4.2₋₁ … 23.0 SXM Suriname 90 50 11 14 17 24 43 62 85 87 55 58 28 32 12.4 14.8 … … … … … … … … … … 98 100 84 82₋₂ 50 … 5.5 2.9 11.4 8.6₊₁ SUR Trinidad and Tobago … 32 6 16 7 20 18 33 97 98 93 95 84 84 9.5 11.0 80₊₁ … … … 58 … 48 … … … … 81 … … … … 4.5 2.9₋₁ 12.3 8.9₊₁ TTO Turks and Caicos Islands 91₋₁ 99 … … …

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[]

and the Arkansas-White- Red regions. Generally, negative trends were obtained inthe South Atlantic-Gulf and to a lesser extent in the New England regions. Noteworthy is that most recently, from 1988 to 2007, in 29 out of 41 basins or in 71%, theobserved trends were negative; more than half of the exceptions, that is, the basins which persisted with positive trends during the past 20 years, tended to lie in the Ohioand Upper Mississippi regions; but the most significant positive trends during this recent period were observed in the Souris-Red-Rainy region in northern Minnesota. The present results on groundwater storage are fully consistent with previous studies dealing with changes of other measures of hydrologic cycle activity, namely with thetrends in precipitation, total surface runoff, and terrestrial evaporation. The consensus of these studies is that the water cycle has generally been accelerating during the past halfcentury over most of the United States east of the Rockies, the two major exceptions being the South Atlantic-Gulf region and possibly also a smaller area in New England. References Andreadis KM, Lettenmaier DP (2006) Trends in 20th century drought over the continental United States. Geophys Res Lett 33:L10403. doi: 10.1029/2006GL025711 Boussinesq J (1877) Essai sur la théorie des eaux courantes. Mém Acad Sci Inst France 23, footnote 252 –260 Brutsaert W (2005) Hydrology: an introduction. Cambridge Univ Press, Cambridge 605 pp Brutsaert W (2006) Indications of increasing land surface evaporation during the second half of the 20th century. Geophys Res Lett 33: L20403. doi: 10.1029/2006GL027532 Brutsaert W (2008) Long-term groundwater storage trends estimated from streamflow records: climatic perspective. Water Resour Res44:W02409. doi: 10.1029/2007WR006518 Brutsaert W, Lopez JP (1998) Basin-scale geohydrologic drought flow features of riparian aquifers in the southern Great Plains. WaterResour Res 34:233 –240 Brutsaert W, Parlange MB (1998) Hydrologic cycle explains the evaporation paradox. Nature 396:30 Brutsaert W, Sugita M (2008) Is Mongolia ’s groundwater increasing or decreasing? The case of the Kherlen River Basin. Hydrol Sci J 53:1221 –1229 Carlston CW (1963) Drainage density and streamflow. US Geol Survey Prof Paper 422-C:1 –8 Carlston CW (1966) The effect of climate on drainage density and streamflow. Bull Internat Assoc Scientif Hydrol 11:62 –69 Chapman MJ, Peck MF (1997) Ground-water resources of the upper Chattahoochee River basin in Georgia. US Geol Survey Open- File Rept 96 –363:43 Dery SJ, Wood EF (2005) Decreasing rive r discharge in Northern Canada. Geophys Res Lett 32:L10401. doi: 10.1029/2005GL022845

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activities, or in the mining law. Some countries that negotiate project-specific fiscal terms negotiated ring-fencing rules that go beyond the primary law (see the example from Sierra Leone in Box 1). Guinea3 and Papua New Guinea4 (PNG) also include a specific ring-fence in their mining contracts. This practice may be especially relevant where the primary law contains no provisions on ring-fencing or only narrow ring-fencing provisions. It is also relevant if a particular project presents specific fiscal risks that could be addressed or managed by well-designed ring-fencing rules. BOX 1. RING -FENCING IN MINING CONTRACTS: THE CASE OF SIERRA LEONE Sierra Leone introduced ring-fencing rules for mining in 2009. The ring-fence is applied per mining licence: “the chargeable income for any year of assessment of a holder of a large-scale mining licence shall be calculated separately for each large-scale mining licence under which licence such holder shall maintain separate balance sheets, statements and books of accounts for each large-scale mining licence under which mining operations are carried on.”5 The country also negotiated ring-fencing rules in some mining contracts that go beyond the general rules. Under the SierraMin Bauxite Limited, Concession, 2017 and the T onguma Limited Concession, 2012, the government negotiated a further operational level of ring-fencing. Any activities carried out by the mining company that are separate from the mining operations contemplated in the contracts shall be considered “non-project activities.” Such non-mining activities will be accounted for separately, as if they were carried out by a separate corporate entity and shall be subject to the law of general application. 3 ResourceContracts.org - Winning Consortium Simandou SAU, Exploitation License, 2020 . 4 ResourceContracts.org - Ramu Nickel Limited, Orogen Minerals (Ramu) Limited, JVA, 2000 . 5 S.155 (1), Sierra Leone Mines and Minerals Act , 2009.3.0 THE BENEFITS AND RISKS OF RING -FENCING 4.0 DESIGNING RING -FENCING RULES 5.0 THE IMPLEMENTATION OF RING -FENCING RULES 6.0 CONCLUSION 2.0 THE FUNDAMENTALS OF RING -FENCING 1.0 INTRODUCTION 8 Ring-Fencing Mining Income: A toolkit for tax administrators and policy-makers2.2 The Prevalence of Ring-Fencing Rules in the Extractive Sectors Ring-fencing rules are widespread worldwide. They are particularly prevalent in the mining sector in developing countries. The findings in Box 2 are based on a survey of ring-fencing rules undertaken by the Intergovernmental Forum on Mining, Minerals, Metals and Sustainable Development (IGF). BOX 2. IGF’S ANALYSIS OF RING -FENCING RULES IN MINING: DETERMINING RING -FENCING PRACTICE

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[]

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activity belt and the prospect of connecting the observed outflows from the solar surface at a variety of latitudes with those encountered at the spacecraft. These connections are key to many of the prime mission goals.” The best is yet to come These are just the first observations made by Solar Orbiter from its newly inclined orbit, and much of this first set of data still awaits further analysis. The complete dataset of Solar Orbiter's first full ‘pole-to-pole' flight past the Sun is expected to arrive on Earth by October 2025. All ten of Solar Orbiter’s scientific instruments will collect unprecedented data in the years to come. Dr Daniel Müller, ESA’s Solar Orbiter project scientist, said: “This is just the first step of Solar Orbiter’s ‘stairway to heaven’: in the coming years, the spacecraft will climb further out of the ecliptic plane for ever better views of the Sun’s polar regions. These data will transform our understanding of the Sun’s magnetic field, the solar wind, and solar activity.” The spacecraft, which launched in February 2020, began the ‘high latitude’ part of its journey five years later, in February 2025. Nearly all Sun-observing spacecraft have tilted from the ecliptic plane by no more than 7°.The exception to this is the ESA/NASA Ulysses mission (1990–2009), which flew over the Sun's poles but did not carry any imaging instruments and remained at much larger distances from the Sun itself. Solar Orbiter’s observations will complement Ulysses’ by observing the poles for the first time with telescopes, in addition to a full suite of in-situ sensors, while flying much closer to the Sun where the solar wind can be sampled in a more pristine state. Additionally, Solar Orbiter will monitor changes at the poles throughout the solar cycle. Solar Orbiter will continue to orbit around the Sun at this tilt angle until 24 December 2026, when its next flight past Venus will tilt its orbit to 24°. From 10 June 2029, the spacecraft will orbit the Sun at an angle of 33°. Solar Orbiter is a space mission of international collaboration between ESA and NASA, operated by ESA. ## Links - ESA's story - ESA Solar Orbiter - Dr Hamish Reid’s academic profile - Professor Lucie Green’s academic profile - Professor Chris Owen’s academic profile - UCL Mullard Space Science Laboratory - UCL Mathematical & Physical Sciences ## Images - Top: A screenshot from the

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per second—meaning that digital data can, in princi-ple, circle the globe five times within a second. 6 Data traffic is growing rapidly around the world. Internet data usage rose from 4.6 to 13 gigabytes per person per month between 2012 and 2017. 7 Four trends are driving the explosion in data traffic. First, the number of internet users is growing. More than half of the world’s population is now online, up from less than one-third in 2010, and that share is forecast to reach two-thirds by 2023. Second, the number of con-nected devices on the IoT already exceeds the number of human users and is forecast to reach 25 billion by 2025 with the diffusion of 5G technology. 8 Third, internet speeds are continually increasing, which supports growing data volumes. By 2023 the speed of broadband service provided over fixed networks is expected to double from 2018 levels, 9 even as the speed of broadband service provided over fixed networks triples. Fourth, video accounts for three-fifths of inter - net traffic, and associated quality improvements are increasing video data traffic. 10 A two-hour movie in standard definition uses 1.4 gigabytes of data, whereas ultra-high definition uses 18 gigabytes. 11 Although most data traffic is still carried over fixed networks, data traffic carried over wireless networks is forecast to rise to more than 20 percent of the global total by 2022, up from only 3 percent in 2012. This shift is driven by the greater prevalence of mobile traffic in emerging nations, with China and India alone accounting for more than 40 percent of the world’s mobile data traffic as of 2018. Both poor people and poor countries face fundamen- tal inequities in their ability to access data infrastruc-ture. To participate in the data-driven economy, people require internet connectivity. It entails both access to last-mile internet infrastructure—increasingly provided through a wireless signal—and ownership of a data-enabled mobile handset (also known as a smart - phone)—or alternatively a full-blown fixed line con-nection. Such connectivity makes it possible for people to both have access to data about other people (and increasingly other things) and provide their own data to others. Large swathes of the population remain excluded from the internet, particularly the poor, the uneducated, the elderly, those living in rural areas, and—in some parts of the world—women. This com-plex situation reflects both the supply-side challenges entailed in rolling out coverage of the

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second case, only one (average) contact between each couple of ancestor (0-level) pinballs is retained. Therefore, the area A0of the ancestor pinball (and not that of the contacting descendant , A) should be used to compute the penalty force. In case of perfectly at and centered contact this approach ensures that the obtained penalty force is the same (for a given penetration p), irrespective of the the hierarchy level chosen for the pinballs. As concerns the penetration p, the problem is more complex and of geometric nature. A major issue is that the standard penetration measurement procedure is unable to detect penetrations larger than the pinball diameter , so that the maximum detectable penetration becomes smaller and smaller as the chosen hierarchy level increases. This translates into a practical limitation of the penalty force, which may lead to numerical disaster. In order to overcome this limitation, we need to modify the strategy to measure the penetration (for proper descendant pinballs) in such a way that it functions also for penetrations larger than the descendant pinball diameter, ideally up to the ancestor pinball diameter.

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… | … … | 1 ₋₁ … | … … | … … | … … | … … | | 17 … | 56 | 87 | 96 ₋₁ 98 | 22 | … 15 … | … | 53 … 62 | 0.4 3.6 | | 4.4 | | ᵢ | 14.8 | | | | | 0.3 ₋₁ 4.9 | | | | | | | 2 ₋₁ … … | … | … | … | … | … | … … | … | … … 28 ᵢ | 85 | … | … 68 | … … … | … 87 | | … | 4.7 | 12.5 ᵢ | | | | 18.3 | 11.3 | | | | | 94 | | NER NGA RWA STP | | | | … … 35 ₋₁ … | … … | … … 29 ₋₁ | … | … … … | … … | … … | | … … | … 34 68 | … | … 74 80 | 20 ₊₁ ᵢ … … 75 ₋₁ … | … … … | … … … 73 … | 74 ₋₁ 71 ₋₁ 100 7 | 5.5 4.9 2.7 ₋₁ … | 23.8 12.6 15.1 ₋₁ | 22.5 6.7 ₋₃ | SLE SOM ZAF SSD TGO | | 29.4 ₋₁ | | | SEN SYC | | 5.2 ₋₁ 6.0 ₋₁ 4.7 ₋₁ 6.8 | … … | … 18.9 | | | | | 80 ₋₂ … 100 … … … … … … | … … … | 52 ₋₂ … … | … | … … … | … | … … … | | ₊₁ … … | … | | 81 ₋₂ … | … 69 … | 84 54 … | | … … … | | | | | | | | | 4.2 ₋₄ | | | 66 … | | | | … | ## PROGRESS SINCE 2015: SELECTED INDICATORS: Continued | | Participation/Completion | Participation/Completion | Participation/Completion | Participation/Completion | Participation/Completion | Participation/Completion | Participation/Completion | Participation/Completion | Participation/Completion | Participation/Completion | Participation/Completion | Participation/Completion | Participation/Completion | Participation/Completion | Gender | Gender | |-----------------------------|--------------------------------------------------|----------------------------|----------------------------|----------------------------|------------------------------------|------------------------------------|----------------------------|----------------------------|----------------------------|----------------------------|----------------------------|----------------------------|----------------------------|----------------------------|-----------------------------------|-----------------------------------| | | A | A | | | | | | | C (%) Completion rate | C (%) Completion rate | C (%) Completion rate

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the internet at http:// dnb.d- nb.de. Library of Congress Cataloging-in-Publication Data A CIP catalog record for this book has been applied for at the Library of Congress. This book was published with the financial assistance of the Department of Modern Languages, Literatures and Cultures of the University of Bologna. The cover illustration was designed by the interns of CISR, Inter-University Centre for the Study of Romanticism (https://site.unibo.it/cisr/it): Giulia Manenti, Elisa Rosolani, Francesca Zanellato. ISSN 2504- 1924 • ISBN 978- 3- 0343- 4669- 6 (Print) ISBN 978- 3- 0343- 4866- 9 (E- PDF) • ISBN 978- 3- 0343- 4867- 6 (EPUB) DOI 10.3726/ b21636 Open Access: This work is licensed under a Creative Commons Attribution NonCommercial NoDerivatives 4.0 unported license. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/ © Lilla Maria Crisafulli / Serena Baiesi / Carlotta Farese (eds.), Elena Spandri / Fabio Liberto / Franca Dellarosa / Gioia Angeletti / Maria Schoina / Timothy Webb 2023. Published by Peter Lang Group AG, Lausanne, Suisse [email protected] http:// www.peterl ang.com/ newgenprepdf

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as organizations with extreme political aims such as white supremacists and neo-Nazis in the United States.¹¹ Members of such large groups exaggerate selected aspects of their childhood large-group identities by holding on to a restricted special nationalistic, religious or political belief. Sometimes they become believers in ideas that were not available in their childhood environments. In short, they give up sharing overall sentiments with people who had the same childhood large-group identity but who have not made such specific new selections. 10 In this paper I will not focus on large-group leaders and the psychological two-way street between them and their followers. Elsewhere I studied in depth the importance of the tent s ' pole in steadying the tent canvas -Volkan (1997); Volkan (2020). 11 Volkan (2020); Suistola & Volkan (2017). Religious knives: Historical and psychological dimensions of international terrorism. ## Initial Reactions to Massive Trauma at the Hand of the Other

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0 *NCI = Normalised citation impact *EC projects = EU-funded R&I projectsTable V. Selected S&T specialisation domains in Azerbaijan 18 Overview of economic, innovation, scientific and technological specialisations Georgia – Summary of the strengths of the S&T specialisations Georgia’s most highlighted S&T domains are the following: ■Environmental sciences and industries scores highly on all S&T indicators – on crit- ical mass, specialisation and excellence – for publications, patents and projects. It is a very clear specialisation domain for Georgia, with particular relevance in Geology and Geotech- nical engineering, as well as Environmental engineering and Chemistry; ■Agrifood presents a high specialisation in patents and publications, as well as a critical mass in patents and a relevant number of EU-funded R&I projects, with science oriented towards Horticulture, Genetics and Plant sci- ence; ■Health and wellbeing presents a high crit- ical mass, specialisation and citation impact in publications, while no positive indicator emerges in relation to patents. It co-occurs frequently with the domain of Agrifood. Be- yond General medicine, research is related in particular to Infectious diseases and Immu- nology; and ■ICT and computer science presents a spe- cialisation in patents as well as highly cited publications and a relevant number of EC pro- jects. GEORGIA Critical mass Specialisation Excellence Summary S&T domain Pubs. Pat. Pubs. Pat. NCI*EC projects*Total Agrifood 4 Biotechnology 0 Chemistry and chemical engineering2 Electric and electronic technologies0 Environmental sciences and industries6 Fundamental physics and mathematics3 Governance, culture, education and the economy4 Health and wellbeing 3 ICT and computer science 3 Mechanical engineering and heavy machinery2 Nanotechnology and materials 2 Optics and photonics 1 *NCI = Normalised citation impact *EC projects = EU-funded R&I projectsTable VI. Selected S&T specialisation domains in Georgia Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation19 Moldova – Summary of the strengths of the S&T specialisations Moldova presents a rather diversified S&T pano- rama. Its most highlighted S&T specialisation do- mains are the following: ■Health and wellbeing presents a nota- ble critical mass, specialisation and citation impact in publications, as well as a relevant number of patents and EC projects. The ‘Nico- lae Testemitanu’ State University of Medicine and Pharmacy is the leading academic institu- tion in the domain, accounting for more than one third of the country’s total records pro- duced on this topic; ■Nanotechnology and materials presents a notable critical mass, specialisation and cita- tion impact in publications, as

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[]

that single women were finally allowed to be honoured in the 1980s. Their ages, in order, were eighty- one, seventy- seven, and seventy- one. Lise Meitner was unmarried and died at the age of ninety in 1968, just before the second wave of the feminist movement.21 In Figure 0.2 , the third generation is indicated by the oval located after the second wave of feminism on the timeline; it is difficult to deny the existence of a double standard in the twentieth century, especially before the second 1901M. Curie (1903/191 1) WW I 1919 *1 MWIA *1 Sex Disqualification (R emov al) Act 1919; The Medical Women’ s Int ernational Associatio n *2 SJWS: The Society of Japanese Women Scientis ts (1958~ ) *3 ICWES: The In ternational Conf erence of Wo men Engineer s and Scientis ts (1964~ ) *4 CEDAW: Convention on Elimination of All Forms of Discrimination Ag ainst Wo men (1979)The fi rst woman Ox ford DPhil 19221958 SJWS *2 1979 CEDA W * 41999 ICWES 11 *3 in Japa n1964 ICWES 1 *3 in New YorkThe fi rst woman Cambridge PhD 1925WW III. Joliot-Curie (1935)G. R. Cori (1947)D. C. Hodgkin (1964)B. McClintock (1983) G. Elion (1988) C. Nüsslein- Volhard (1995)Levi-Montalcini (1986) M. G. Mayer (1963) R. S. Yalow (1977) 10 20 30 40 50 60 70 80 90 2000 404040 70 80 7 0 7 0 Second- wave feminism Figure 0.2 Nobel Prize women in science and international exchanges xxx Negotiating in/visibility wave of feminism, when even top scientists were assumed to be ‘good wives’ and ‘wise mothers’. Gerty and Carl Cori received the Nobel Prize in 1947. For thirty- five years, they formed a close scientific partnership. They started their careers at a medical school in Prague, in what is now the Czech Republic, and moved to the US in 1922 to avoid antisemitism.22 However, for a long time, they could not find jobs that allowed them to work together because of anti- nepotism rules. Maria Goeppert Mayer was another typical example of a trailing spouse. She married Joseph Mayer in Göttingen in Germany. Eventually, Joseph was hired by the Johns Hopkins University, which had strict anti- nepotism rules, prohibiting the employment of relatives. Maria had neither a job nor a salary, while Joseph gained a post at Columbia, following his term at Hopkins. In 1960, she was finally appointed a full professor of

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to work after raising a family I took an Open University degree, gaining friends and lots of experience as well as a degree to update my professional qualifications – again, paid for by part-time work. I now have concerns for my eldest grandson, who wants, very sensibly, to take an apprenticeship, as I hear that companies are cutting back on employees and are not often looking at taking on apprentices. Jean Austin Crawley, West Sussex Have an opinion on anything you’ve read in the Guardian today? Please email us your letter and it will be considered for publication in our letters section. - Universities - Higher education - Student engagement - Students - letters ### Most viewed - CDC erupts in chaos after ousted chief Susan Monarez refuses to resign - Ostapenko and Townsend confront each other after US Open match: ‘She said I had no education’ - Glorious Grimsby humiliate Manchester United with shootout victory - The Burning Man Orgy Dome: welcome to the latest festival disaster - How hard will Trump’s 50% tariff hit India, and what is Delhi doing about it? ## Most viewed ## Most viewed - Education - Schools - Teachers - Universities - Students - News - Opinion - Sport - Culture - Lifestyle Original reporting and incisive analysis, direct from the Guardian every morning - Help - Complaints & corrections - SecureDrop - Work for us - Privacy policy - Cookie policy - Terms & conditions - Contact us - All topics - All writers - Digital newspaper archive - Tax strategy - Facebook - YouTube - Instagram - LinkedIn - Newsletters

[ "to", "work", "after", "raising", "a", "family", "I", "took", "an", "Open", "University", "degree", ",", "gaining", "friends", "and", "lots", "of", "experience", "as", "well", "as", "a", "degree", "to", "update", "my", "professional", "qualifications", "–", "again", ",", "paid", "for", "by", "part", "-", "time", "work", ".", "\n\n", "I", "now", "have", "concerns", "for", "my", "eldest", "grandson", ",", "who", "wants", ",", "very", "sensibly", ",", "to", "take", "an", "apprenticeship", ",", "as", "I", "hear", "that", "companies", "are", "cutting", "back", "on", "employees", "and", "are", "not", "often", "looking", "at", "taking", "on", "apprentices", ".", "\n", "Jean", "Austin", "\n", "Crawley", ",", "West", "Sussex", "\n\n", "Have", "an", "opinion", "on", "anything", "you", "’ve", "read", "in", "the", "Guardian", "today", "?", "Please", "email", "us", "your", "letter", "and", "it", "will", "be", "considered", "for", "publication", "in", "our", "letters", "section", ".", "\n\n", "-", "Universities", "\n", "-", "Higher", "education", "\n", "-", "Student", "engagement", "\n", "-", "Students", "\n", "-", "letters", "\n\n", "#", "#", "#", "Most", "viewed", "\n\n", "-", "CDC", "erupts", "in", "chaos", "after", "ousted", "chief", "Susan", "Monarez", "refuses", "to", "resign", "\n", "-", "Ostapenko", "and", "Townsend", "confront", "each", "other", "after", "US", "Open", "match", ":", "‘", "She", "said", "I", "had", "no", "education", "’", "\n", "-", "Glorious", "Grimsby", "humiliate", "Manchester", "United", "with", "shootout", "victory", "\n", "-", "The", "Burning", "Man", "Orgy", "Dome", ":", "welcome", "to", "the", "latest", "festival", "disaster", "\n", "-", "How", "hard", "will", "Trump", "’s", "50", "%", "tariff", "hit", "India", ",", "and", "what", "is", "Delhi", "doing", "about", "it", "?", "\n\n", "#", "#", "Most", "viewed", "\n\n", "#", "#", "Most", "viewed", "\n\n", "-", "Education", "\n", "-", "Schools", "\n", "-", "Teachers", "\n", "-", "Universities", "\n", "-", "Students", "\n\n", "-", "News", "\n", "-", "Opinion", "\n", "-", "Sport", "\n", "-", "Culture", "\n", "-", "Lifestyle", "\n\n", "Original", "reporting", "and", "incisive", "analysis", ",", "direct", "from", "the", "Guardian", "every", "morning", "\n\n", "-", "Help", "\n", "-", "Complaints", "&", "amp", ";", "corrections", "\n", "-", "SecureDrop", "\n", "-", "Work", "for", "us", "\n", "-", "Privacy", "policy", "\n", "-", "Cookie", "policy", "\n", "-", "Terms", "&", "amp", ";", "conditions", "\n", "-", "Contact", "us", "\n\n", "-", "All", "topics", "\n", "-", "All", "writers", "\n", "-", "Digital", "newspaper", "archive", "\n", "-", "Tax", "strategy", "\n", "-", "Facebook", "\n", "-", "YouTube", "\n", "-", "Instagram", "\n", "-", "LinkedIn", "\n", "-", "Newsletters" ]

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there- fore been decided to circumvent taxonomies and to use the textual content of each record to ob- tain fine-grained and homogeneous mapping of all S&T activities across the EaP countries. To do so, a series of topics have been extracted from the com- bined corpus of scientific publications, EU-funded research projects and patents by means of topic modelling – an algorithmic approach to extract condensed information from large textual corpora in the form of ‘topics’. Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation145 The result of topic modelling is a series of top- ics, each characterised by a list of the main words that tend to appear in them. This whole process is carried out iteratively and with human revision in order to identify and eliminate unrelated or irrel- evant terms: proper names, acronyms, words with little meaning or transversal words. Topics are extracted individually for each country, allowing for differences and nuances in national special- isations. The individual topics are then clustered together according to their semantic similarity, leading to 14 S&T specialisation domains defined across the EaP. This section presents and discuss- es these results. 2.1 S&T data availability Table 3.1 presents the data sources used in topic modelling. Publications account for 64.48% of the total number of records, while patents account for 32.36% and EC projects for only 0.16%. Additionally, Table 3.2 showcases the specific dis- tribution of records per type and per country. It is important to note the significantly low number of patents in comparison to the number of publica- tions, which is especially pronounced in the cases Scope Source Data extraction criteriaNo of records (2012-2019) Scientific publications in internationally indexed journalsScopus (Elsevier)Publications with at least one author with an EaP affiliation131 179 European Commission- funded research and innovation projectsCORDIS - Community Research and Development Information ServiceFP7 and H2020 projects with at least one EaP partner324 PatentsWorldwide bibliographic data (DOCDB) - European Patent OfficeAt least one EaP inventor or applicant for those patents filed through a patent office covered by the EPO DOCDB database261 997 (2011-2018)Table 3.1. Characterisation of the data sources used in topic modelling, including the name of the source, its scope, the data extraction criteria and the number of recordsof Armenia and Azerbaijan, where publications ac- count for 96%, 92% and 87% of the total num- ber of records in the country, respectively. This is partially

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[]

and the second conductor, respectively, of the conductor 205 are used. - a conductive material that has a function of inhibiting the passage of impurities such as water and hydrogen is preferably used as the first conductor of the conductor 240 . - a conductive material that has a function of inhibiting the passage of impurities such as water and hydrogen is preferably used. - tantalum, tantalum nitride, titanium, titanium nitride, ruthenium, ruthenium oxide, or the like is preferably used. - the conductive material having a function of inhibiting the passage of impurities such as water and hydrogen may be used as a single layer or stacked layers. Using the conductive material for the first conductor of the conductor 240 can prevent impurities such as hydrogen and water from entering the oxide 230 through the conductor 240 from the layers above the insulator 281 . - the conductor 240 may be provided as a single layer or to have a stacked-layer structure of three or more layers. - the layers may be distinguished by ordinal numbers corresponding to the formation order. - the conductor 260 is covered with the insulator 270 and the insulator 273 functioning as an etching stopper, it is not necessary to provide an alignment margin for the conductor 260 and the conductor 240 . - the distance between the conductor 260 and the conductor 240 can be small. Accordingly, the area occupied by the cell 600 can be reduced, and the miniaturization and high integration of the semiconductor device can be achieved. - the conductor 242 b and the oxide 230 may be divided into the transistor 200 a side and the transistor 200 b side. Moreover, an opening may be formed in the conductor 242 b and the oxide 230 . - the opening is formed in the conductor 242 b and the oxide 230 , and the conductor 240 and the conductor 209 are in direct contact with each other; however, the present invention is not limited thereto. - a bottom surface of the conductor 240 may be in contact with the conductor 242 b - a top surface of the conductor 209 may be in contact with the region 243 b of the oxide 230 a . - FIG. 5 (A) is an enlarged view obtained by changing the shape of an area around the conductor 240 and the conductor 209 from that

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Y are functionally connected are disclosed in this specification and the like. Accordingly, without being limited to a predetermined connection relation, for example, a connection relation shown in drawings or texts, a connection relation other than one shown in drawings or texts is regarded as being described in the drawings or the texts. - X and Y denote an object (e.g., a device, an element, a circuit, a wiring, an electrode, a terminal, a conductive film, or a layer). - An example of the case where X and Y are directly connected is the case where an element that allows electrical connection between X and Y (e.g., a switch, a transistor, a capacitor, an inductor, a resistor, a diode, a display element, a light-emitting element, or a load) is not connected between X and Y, and is the case where X and Y are connected without an element that allows electrical connection between X and Y (e.g., a switch, a transistor, a capacitor, an inductor, a resistor, a diode, a display element, a light-emitting element, or a load) placed therebetween. - an element that allows electrical connection between X and Y e.g., a switch, a transistor, a capacitor, an inductor, a resistor, a diode, a display element, a light-emitting element, or a load - one or more elements that allow electrical connection between X and Y can be connected between X and Y. - a switch has a function of being controlled to be turned on or off. That is, a switch has a function of being in a conduction state (on state) or a non-conduction state (off state) to control whether or not current flows. - a switch has a function of selecting and changing a current path. Note that the case where X and Y are electrically connected includes the case where X and Y are directly connected. - X and Y are functionally connected is the case where one or more circuits that allow functional connection between X and Y (e.g., a logic circuit (an inverter, a NAND circuit, a NOR circuit, or the like), a signal converter circuit (a DA converter circuit, an AD converter circuit, a gamma correction circuit, or the like), a potential level converter circuit (a power supply circuit (e.g., a step-up circuit, a step-down circuit, or the like), a level shifter circuit for changing the potential level of a signal, or the

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an extranet, a PAN (Personal Area Network), a LAN (Local Area Network), a CAN (Campus Area Network), a MAN (Metropolitan Area Network), a WAN (Wide Area Network), or a GAN (Global Area Network). In the case of performing wireless communication, it is possible to use, as a communication protocol or a communication technology, a communications standard such as LTE (Long Term Evolution), GSM (Global System for Mobile Communication: registered trademark), EDGE (Enhanced Data Rates for GSM Evolution), CDMA2000 (Code Division Multiple Access 2000), or W-CDMA (registered trademark), or a communications standard developed by IEEE, such as Wi-Fi (registered trademark), Bluetooth (registered trademark), or ZigBee (registered trademark). With the structure in and , analog signals obtained with external sensors or the like can be processed by different AI systems. For example, analog signals containing biological information such as brain waves, a pulse, blood pressure, and body temperature obtained with a variety of sensors such as a brain wave sensor, a pulse wave sensor, a blood pressure sensor, and a temperature sensor can be processed by different AI systems. When signal processing or learning is performed by different AI systems, the amount of information processed by each AI system can be reduced. Accordingly, signal processing or learning can be performed with a smaller amount of arithmetic processing. As a result, recognition accuracy can be increased. The information obtained with each AI system is expected to enable instant and collective understanding of a complex change in biological information. The structure described in this embodiment can be used in appropriate combination with the structure described in the other embodiments. In this embodiment, an example of an IC incorporating the AI system described in the above embodiment will be described. In the AI system described in the above embodiment, a digital processing circuit formed of Si transistors, such as a CPU; an analog arithmetic circuit using OS transistors; an OS-FPGA; and an OS memory such as a DOSRAM or a NOSRAM can be integrated into one die. illustrates an example of an IC in which the AI system is incorporated. An illustrated in includes a and a . The is mounted on a printed , for example. A plurality of such IC chips are combined and electrically connected to each other on the printed ; thus, a board on which electronic components are mounted (a circuit board ) is completed. In the , the various

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Leather and imitations of leather; ani- mal skins, and hides; trunks and travelling luggage and carrying bags; umbrellas and parasols; walk- ing sticks; whips, harness and saddlery; collars, leashes and clothing for animals Class 19 – Building materials (non-metallic); non-metallic rigid pipes for building; asphalt, pitch and bitumen; non-metallic transportable buildings; monuments, not of metal Class 20 – Furniture, mirrors, picture frames; con- tainers, not of metal, for storage or transport; unworked or semi-worked bone, horn, ivory, whale- bone or mother-of-pearl; shells; meerschaum; yel- low amber Class 21 – Household or kitchen utensils and containers; combs and sponges; brushes, (except paintbrushes); brush-making materials; articles for cleaning purposes; steelwool; unworked or semi- worked glass, (except building glass used in build- ing); glassware, porcelain and earthenware Class 22 – Ropes and string; nets; tents, awnings, and tarpaulins; awnings of textile or synthetic ma- terials; sails; sacks for the transport and storage of materials in bulk; padding, cushioning and stuffing materials, (except of paper, cardboard, rubber or plastics); raw fibrous textile materials and substi- tutes therefor Class 23 – Yarns and threads, for textile use Class 24 – Textiles and substitutes for textiles; bed covers; table covers; household linen; curtains of textile or plastic Class 25 – Clothing, footwear, headgear Class 26 – Lace and embroidery, ribbons and braid; buttons, hooks and eyes, pins and needles; artificial flowers; hair decorations; false hair Class 27 – Carpets, rugs, mats and matting, li- noleum and other materials for covering existing floors; wall hangings (non-textile) Class 28 – Games, toys and playthings; video game apparatus; gymnastic and sporting articles; decorations for Christmas trees Class 29 – Meat, fish, poultry and game; meat ex- tracts; preserved, frozen, dried and cooked fruits and vegetables; jellies, jams, compotes; eggs; milk and milk products; edible oils and fats Class 30 – Coffee, tea, cocoa and artificial cof- fee; rice; tapioca and sago; flour and preparations made from cereals; bread, pastries and confec- tionery; edible ices; sugar, honey, treacle; yeast, baking-powder; salt; mustard; vinegar, sauces (condiments); spices; ice Class 31 – Raw and unprocessed agricultural, aq- uacultural, horticultural and forestry products; raw and unprocessed grains and seeds; fresh fruits and vegetables, fresh herbs; natural plants and flowers; bulbs, seedlings and seeds for planting; live animals; foodstuffs and beverages for ani- mals; malt Class 32 – Beers; mineral and aerated waters and other non-alcoholic beverages; fruit beverages and fruit juices; syrups and

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of ring-fencing rules is particularly relevant for developing countries that may lack the tools and infrastructure to detect such abusive arrangements. Note: Such a structure is also possible directly between the related Companies A and B in the absence of Investment Bank Z. ## 1.0 INTRODUCTION 2.0 THE FUNDAMENTALS OF RING-FENCING ## 3.0 THE BENEFITS AND RISKS OF RING-FENCING 4.0 DESIGNING RING-FENCING RULES 5.0 THE IMPLEMENTATION OF RING-FENCING RULES 6.0 CONCLUSION Such BEPS practices also result in permanent revenue losses for the host government. Where the costs or losses resulting from such BEPS practices are ring-fenced from the mining tax base, the ring-fencing rules can contribute to protecting the tax base from permanent revenue losses. While aggressive tax planning could be dealt with more effectively by (a) introducing general anti-avoidance measures, and/or (b) improving the capability of tax administrations to detect and mitigate BEPS practices generally, the reality is that these two conditions are not always in place in developing countries. Ring-fencing can be considered a temporary measure in such circumstances. ## 3.1.2.4 The Overstatement of Exploration and Development Expenditures The consolidation of revenues and expenditures between projects held by one mining investor can increase the risk of companies inflating their exploration and mine development expenditures, which may not be audited at all (due to limited capacities and statute of limitation rules) or are audited only once the mine starts production and often receive preferential tax treatment, such as accelerated depreciation or investment allowances/tax credits, to lower their overall tax burden on profit-making operations. 15 This is particularly common in jurisdictions with weak monitoring capacity. The overstatement of expenditures raises the need for additional financing and, thus, associated costs, such as interest deductions, where the investor uses debt to finance the additional 'overstated' costs. Such additional debt financing is often provided by related parties, which has a further negative effect on the tax base-in addition to the overstated costs-because there is an additional deduction of the financing costs in relation to the related-party debt financing. Ring-fencing may reduce this risk by limiting the consolidation of revenues with losses derived from exploration or development areas. BEPS practices may need to be resolved through the full suite of transfer pricing rules and other measures. However, the effect of ring-fencing may, to some extent, discourage such practices. This is especially true where both the overstated expenses and the financing costs are allocated to

[ "of", "ring", "-", "fencing", "rules", "is", "particularly", "relevant", "for", "developing", "countries", "that", "may", "lack", "the", "tools", "and", "infrastructure", "to", "detect", "such", "abusive", "arrangements", ".", "\n\n", "Note", ":", "Such", "a", "structure", "is", "also", "possible", "directly", "between", "the", "related", "Companies", "A", "and", "B", "in", "the", "absence", "of", "Investment", "Bank", "Z.", "\n\n", "#", "#", "1.0", "INTRODUCTION", "\n\n", "2.0", "THE", "FUNDAMENTALS", "OF", "RING", "-", "FENCING", "\n\n", "#", "#", "3.0", "THE", "BENEFITS", "AND", "RISKS", "OF", "RING", "-", "FENCING", "\n\n", "4.0", "DESIGNING", "RING", "-", "FENCING", "RULES", "\n\n", "5.0", "THE", "IMPLEMENTATION", "OF", "RING", "-", "FENCING", "RULES", "\n\n", "6.0", "CONCLUSION", "\n\n", "Such", "BEPS", "practices", "also", "result", "in", "permanent", "revenue", "losses", "for", "the", "host", "government", ".", "Where", "the", "costs", "or", "losses", "resulting", "from", "such", "BEPS", "practices", "are", "ring", "-", "fenced", "from", "the", "mining", "tax", "base", ",", "the", "ring", "-", "fencing", "rules", "can", "contribute", "to", "protecting", "the", "tax", "base", "from", "permanent", "revenue", "losses", ".", "\n\n", "While", "aggressive", "tax", "planning", "could", "be", "dealt", "with", "more", "effectively", "by", "(", "a", ")", "introducing", "general", "anti", "-", "avoidance", "measures", ",", "and/or", "(", "b", ")", "improving", "the", "capability", "of", "tax", "administrations", "to", "detect", "and", "mitigate", "BEPS", "practices", "generally", ",", "the", "reality", "is", "that", "these", "two", "conditions", "are", "not", "always", "in", "place", "in", "developing", "countries", ".", "Ring", "-", "fencing", "can", "be", "considered", "a", "temporary", "measure", "in", "such", "circumstances", ".", "\n\n", "#", "#", "3.1.2.4", "The", "Overstatement", "of", "Exploration", "and", "Development", "Expenditures", "\n\n", "The", "consolidation", "of", "revenues", "and", "expenditures", "between", "projects", "held", "by", "one", "mining", "investor", "can", "increase", "the", "risk", "of", "companies", "inflating", "their", "exploration", "and", "mine", "development", "expenditures", ",", "which", "may", "not", "be", "audited", "at", "all", "(", "due", "to", "limited", "capacities", "and", "statute", "of", "limitation", "rules", ")", "or", "are", "audited", "only", "once", "the", "mine", "starts", "production", "and", "often", "receive", "preferential", "tax", "treatment", ",", "such", "as", "accelerated", "depreciation", "or", "investment", "allowances", "/", "tax", "credits", ",", "to", "lower", "their", "overall", "tax", "burden", "on", "profit", "-", "making", "operations", ".", "15", " ", "This", "is", "particularly", "common", "in", "jurisdictions", "with", "weak", "monitoring", "capacity", ".", "\n\n", "The", "overstatement", "of", "expenditures", "raises", "the", "need", "for", "additional", "financing", "and", ",", "thus", ",", "associated", "costs", ",", "such", "as", "interest", "deductions", ",", "where", "the", "investor", "uses", "debt", "to", "finance", "the", "additional", "'", "overstated", "'", "costs", ".", "Such", "additional", "debt", "financing", "is", "often", "provided", "by", "related", "parties", ",", "which", "has", "a", "further", "negative", "effect", "on", "the", "tax", "base", "-", "in", "addition", "to", "the", "overstated", "costs", "-", "because", "there", "is", "an", "additional", "deduction", "of", "the", "financing", "costs", "in", "relation", "to", "the", "related", "-", "party", "debt", "financing", ".", "Ring", "-", "fencing", "may", "reduce", "this", "risk", "by", "limiting", "the", "consolidation", "of", "revenues", "with", "losses", "derived", "from", "exploration", "or", "development", "areas", ".", "\n\n", "BEPS", "practices", "may", "need", "to", "be", "resolved", "through", "the", "full", "suite", "of", "transfer", "pricing", "rules", "and", "other", "measures", ".", "However", ",", "the", "effect", "of", "ring", "-", "fencing", "may", ",", "to", "some", "extent", ",", "discourage", "such", "practices", ".", "This", "is", "especially", "true", "where", "both", "the", "overstated", "expenses", "and", "the", "financing", "costs", "are", "allocated", "to" ]

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the contribu - tions in this section show that the examination of personal and professional networks in science and their role in rendering women more visible cannot be separated from an examination of the broader political context in which their lives and careers unfolded. In/ visibilities in medicine and care: Treating, teaching, reforming As in the case of science and engineering, some of the chapters in this volume also provide an opportunity for comparative study between different areas 20 Negotiating in/visibility of medicine. Medicine and care have been among the most examined sites of science in relation to gender, education and women’s work, but the papers in this section suggest new avenues of investigation. They focus in particular on neglected arenas like women’s work as doctors and educators in second - ary schools in Romania, women physicians’ role in training midwives in Republican China and attempts made by female cadres, researchers, doctors and medical students to alleviate ‘women’s illnesses’ and promote ‘grassroot science’ in Maoist China. These chapters highlight often- overlooked insti - tutional contexts, ranging from secondary schools to rural health stations, and examine how political events, such as World War I and the Great Leap Famine,54 both expanded and constrained the range of opportunities avail - able to female physicians and scientists. Camelia Zavarache’s contribution addresses the importance of politi - cal change, border reconfiguration and state- building in the appointment of women as doctors in secondary- school education in interwar Romania, a time when the country significantly expanded its territory and minority population.55 Zavarache argues that the state’s agenda of providing hygiene education to secondary- school students was intertwined with the aim of producing a healthy ‘body’ for the Romanian nation. This played a crucial role in allowing women access to positions as school doctors, especially after the passing of the 1928 Law on Secondary Education which stipu - lated that female doctors should be employed to teach hygiene courses and conduct medical examinations in girls’ schools. Although the socio- political and economic circumstances that followed World War I created a situation that helped render women more visible both as health professionals and ‘modernising agents’ of the new, enlarged Romanian state, Zavarache dem - onstrates that women often had to fight for the school positions they were legally entitled to. Using archival documents which have been largely neglected in Romanian historiography, especially correspondence between women doctors and

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Eunomia, PET market in Europe state of play 2022. 2023. https://www.plasticsrecyclers.eu/wp - content/uploads/2023/06/PET_REPORT2022_June2023.pdf (accessed January 2025). Euromines, The Electronics Value Chain and Its Raw Materials. 2020. https://www.euromines.org/files/key_value_chain_electronics_euromines_final_0.pdf (accessed January 2025). Eurostat, PRODCOM. Statistics by products . Overview, 2022 . https://ec.europa.eu/eurostat/web/prodcom (accessed March 2024). Garcia -Gutierrez, P., Amadei, A.M., Klenert, D., Nessi, S., Tonini, D., Tosches, D., Ardente, F. and Saveyn, H., Environmental and economic assessment of plastic waste recycling , EUR 31423 EN, Publications Office of the European Union, Luxembourg, JRC132067, 2023, ISBN 978 -92-76-99528 -9. https://publications.jrc.ec.europa.eu/repository/handle/JRC132067 41 Huisman, J., Botezatu I., Herreras, L., Liddane M., Hintsa J., Luda di Cortemiglia V., Leroy P., Vermeersch, E., Mohanty, S., van den Brink, S., Ghenciu, B., Dimitrova, D., Nash, E., Shryane, T., Wieting, M., Kehoe, J., Baldé, C.P., Magalini, F., Zanasi, A ., Ruini, F., Männistö, T., and Bonzio, A., Countering WEEE Illegal Trade (CWIT) Summary Report , 2015. https://weee -forum.org/projects - campaigns/cwit/ (accessed May 2024). Huygens, D., Foschi, J., Caro, D., Caldeira, C., Faraca, G., Foster, G., Solis, M., Marschinski, R., Napolano, L., Fruergaard Astrup, T. and Tonini, D., Techno -scientific assessment of the management options for used and waste textiles in the European Union . Publications Office of the European Union, Luxembourg, JRC134586, 2023. https://publications.jrc.ec.europa.eu/repository/handle/JRC134586 ISO (International Standard Organization), ISO 14040 - environmental management - life cycle assessment - principles and framework , 2006. ISO (International Standard Organization), ISO 14044 - environmental management - life cycle assessment - requirements and guidelines , 2006. Kawecki, D., and B. Nowack, Polymer -Specific Modeling of the Environmental Emissions of Seven Commodity Plastics As Macro - and Microplastics , Environmental Science and Technology, Vol. 53, No. 16, pp. 9664 –9676, 2019. https://pubs.acs.org/doi/abs/10.1021/acs.est.9b02900 Kaza, S ., Yao, L . C., Bhada -Tata, P., Van Woerden, F . What a Waste 2.0: A Global Snapshot of Solid Waste Management to 2050 . Urban Development . World Bank. 2018. http://hdl.handle.net/10986/30317 Kounina, A., Daystar, J., Chalumeau, S., Devine, J., Geyer, R., Pires, T.S., Uday Sonar, S., Venditti, R.A., and Boucher, J., The global apparel industry is a significant yet overlooked source of plastic leakage . nature communications, 15 -5022, 2024. https://doi.org/10.1038/s41467 -024-49441 -4 Lase , I. S., 2023. Modeling material flows through plastic recycling chains . Ghent University. https://biblio.ugent.be/publication/01HG0M47FPW1MXCKKWDAT8099Q (accessed June 2024). Linder, C., Schmitt, J., Fischer, E., Hein J., Stoffstrombild Kunststoffe in Deutschland 2021: Zahlen und Fakten zum Lebensweg von Kunststoffen , Conversio Market & Strategy GmbH, 2021. https://plasticseurope.org/de/wp - content/uploads/sites/3/2022/11/Kurzfassung_Stoffstrombild_2021.pdf (accessed January 2025) .

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about the health and well-being of present and future generations, the responsible thing will be not to settle for a worst-case scenario, but to provide Gavi with what it needs. “For us, Gavi is a game changer,” Kaseya says. Nature 643 , 880 (2025) doi: https://doi.org/10.1038/d41586-025-02270-x Reprints and permissions Related Articles Vaccines save lives. Leaders must champion them Will RFK Jr’s vaccine agenda make America contagious again? Vaccine sceptic RFK Jr is now a powerful force in US science: what will he do? Scientists hail historic malaria vaccine approval — but point to challenges ahead Subjects Vaccines Public health Infection Epidemiology Latest on: Vaccines Acne vaccines could offer robust defence Outlook 27 AUG 25 RFK Jr demanded a vaccine study be retracted — the journal said no News 22 AUG 25 Cancelling mRNA studies is the highest irresponsibility Editorial 15 AUG 25 Public health AI versus skin cancer: the future of dermatology diagnosis Outlook 27 AUG 25 An abiding mystery of the French Revolution is solved — by epidemiology News 27 AUG 25 Emotional AI is here — let’s shape it, not shun it Correspondence 26 AUG 25 Infection Pig lung transplanted into a person in world first News 26 AUG 25 Protection from biological hazards at work arrives at last Correspondence 05 AUG 25 mRNA vaccines for HIV trigger strong immune response in people News 01 AUG 25 Acne vaccines could offer robust defence Outlook 27 AUG 25 RFK Jr demanded a vaccine study be retracted — the journal said no News 22 AUG 25 Cancelling mRNA studies is the highest irresponsibility Editorial 15 AUG 25 Jobs Faculty Recruitment, Westlake University School of Medicine Faculty positions are open at four distinct ranks: Assistant Professor, Associate Professor, Full Professor, and Chair Professor. Hangzhou, Zhejiang, China Westlake University Chemistry Faculty Positions at Westlake University Multiple positions are open at all ranks. Hangzhou, Zhejiang, China Westlake University Global Talent Recruitment-Hospital of Stomatology Xi’an Jiaotong University Leading Talent, Excellent Young Scholars (Overseas), Young Top Talents, Postdoctoral Fellow Xi'an, Shaanxi (CN) Hospital of Stomatology Xi’an Jiaotong University Principal Investigators in Population Health Data Science (2 positions) The Lunenfeld-Tanenbaum Research Institute, a leading research institute in Toronto, is seeking emerging leaders in Population Health Data Science. Toronto, Ontario, Canada Lunenfeld-Tanenbaum Research Institute Principal Investigators in Biomedical Discovery Research (2 positions) The Lunenfeld-Tanenbaum Research Institute is recruiting emerging leaders in Systems, Cellular, Chemical, Molecular and Musculoskeletal

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Guet-Mccreight, A., Skinner, F.K., and Topolnik, L. (2020). Common principles in functional organization of vip/calretinin cell-driven disinhibitory circuits across cortical areas. Front. Neural Circuits 14 . https://doi.org/10.3389/fncir. 2020.00032. Hangya, B., Ranade, S.P., Lorenc, M., and Kepecs, A. (2015). Central cholinergic neurons are rapidly recruited by reinforcement feedback. Cell 162 , 11551168. https://doi.org/10.1016/j.cell.2015.07.057. He, M., Tucciarone, J., Lee, S., Nigro, M.J., Kim, Y., Levine, J.M., Kelly, S.M., Krugikov, I., Wu, P., Chen, Y., et al. (2016). Strategies and tools for combinatorial targeting of gabaergic neurons in mouse cerebral cortex. Neuron 91 , 1228-1243. https://doi.org/10.1016/j.neuron.2016.08.021.  Henson, R.N., and Rugg, M.D. (2003). Neural response suppression, haemodynamic repetition effects, and behavioural priming. Neuropsychologia 41 , 263-270. https://doi.org/10.1016/s0028-3932(02)00159-8. Hersman, S., Allen, D., Hashimoto, M., Brito, S.I., and Anthony, T.E. (2020). Stimulus salience determines defensive behaviors elicited by aversively conditioned serial compound auditory stimuli. Elife 9 . https://doi.org/10.7554/elife. 53803. Holland, P.C. (1980). Influence of visual conditioned stimulus characteristics on the form of pavlovian appetitive conditioned responding in rats. J. Exp. Psychol. Anim. Behav. Process. 6 , 81-97. https://doi.org/10.1037/0097-7403.6.1. 81. Ishai, A., Pessoa, L., Bikle, P.C., and Ungerleider, L.G. (2004). Repetition suppression of faces is modulated by emotion. Proc. Natl. Acad. Sci. U S A 101 , 9827-9832. https://doi.org/10.1073/pnas.0403559101. Kapur, S. (2003). Psychosis as A state of aberrant salience: a framework linking biology, phenomenology, and pharmacology in schizophrenia. Am. J. Psychiatry 160 , 13-23. https://doi.org/10.1176/appi.ajp.160.1.13. Kastli, R., Vighagen, R., Van Der Bourg, A., Argunsah, A.O., Iqbal, A., Voigt, ¨ F.F., Kirschenbaum, D., Aguzzi, A., Helmchen, F., and Karayannis, T. (2020). Developmental divergence of sensory stimulus representation in cortical interneurons. Nat. Commun. 11 , 5729. https://doi.org/10.1038/s41467-02019427-z. Keller, A.J., Dipoppa, M., Roth, M.M., Caudill, M.S., Ingrosso, A., Miller, K.D., and Scanziani, M. (2020). A disinhibitory circuit for contextual modulation in primary visual cortex. Neuron 108 , 1181-1193.e8. https://doi.org/10.1016/j. neuron.2020.11.013. Kim, H., Ahrlund-Richter, S., Wang, X., Deisseroth, K., and Carle ´ n, M. (2016). ¨ Prefrontal parvalbumin neurons in control of attention. Cell 164 , 208-218. https://doi.org/10.1016/j.cell.2015.11.038. Kim, I.H., Kim, N., Kim, S., Toda, K., Catavero, C.M., Courtland, J.L., Yin, H.H., and Soderling, S.H. (2020). Dysregulation of the synaptic cytoskeleton in the pfc drives neural circuit pathology, leading to social dysfunction. Cell Rep. 32 , 107965. https://doi.org/10.1016/j.celrep.2020.107965. Krabbe, S., Grundemann, J., and Luthi, A. (2018). Amygdala inhibitory circuits € € regulate associative fear conditioning. Biol. Psychiatry 83 , 800-809. https:// doi.org/10.1016/j.biopsych.2017.10.006. Krabbe, S., Paradiso, E., D'aquin, S., Bitterman, Y., Courtin, J., Xu, C., Yonehara, K., Markovic, M., Muller, C., Eichlisberger, T., et al. (2019). Adaptive dis-€ inhibitory gating by vip interneurons permits associative learning. Nat. Neurosci. 22 , 1834-1843. https://doi.org/10.1038/s41593-019-0508-y.

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may be based on a device fingerprint of the and/or some other device or system in the MRF. Additionally or alternatively, the UID may be based on any other type of identifier and/or network address, such as any of those discussed herein. Any of the aforementioned examples may be combined. In any of the aforementioned examples, the AI/ML system(s) include one or more optimizers that perform the multi-objective optimization according. The optimizers are based on one or more objective functions or multi-objective function(s), which include an optimization problem involving more than one objective function to be either minimized or maximized. The optimizers may define a multi-objective optimization model that comprises one or more decision variables, objectives, and constraints. The decision variables are variables that represent decisions to be made, and the objectives are the measures to be optimized. The constraints define restrictions on feasible solutions (including all optimal solutions) that must be satisfied, and/or restrictions on the values the decision variables may hold. One example of the decision variables includes prioritized or otherwise desired materials to be recovered from the material stream. The objective functions indicate how much each of their decision variables contributes to the objectives to be optimized. The multi-objective optimization model may also define one or more coefficients corresponding to one or more of the decision variables. The coefficients indicate the contribution of the corresponding decision variable to the value of the objective function. The optimal solutions in multi-objective optimization can be defined from a mathematical concept of partial ordering. The term domination is used for this purpose in the parlance of multi-objective optimization. A first solution is said to dominate a second solution if both of the following conditions are true: (1) the first solution is no worse than the second solution in all objectives, and (2) the first solution is strictly better than the second solution in at least one objective. For a given set of solutions, a pair-wise comparison can be made using a graphical representation and a determination as to whether one point in the graph dominates the other can be established. All points that are not dominated by any other member of the set are called “non-dominated points” or “non-dominated solutions”. The Pareto frontier comprises a set of non-dominated points in such a graphical representation. Here, the AI/ML system(s) solves the multi-objective function(s) to optimize a number of objectives simultaneously, where the

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[]

objective function's decision variables are often changed or manipulated within the bounds of the constraints to improve the objective function's values. In general, the difficulty in solving an objective function increases as the number of decision variables included in that objective function increases. - the term “decision variable” refers to a variable that represents a decision to be made. - optimization at least in some examples refers to an act, process, or methodology of making something (e.g., a design, system, or decision) as fully perfect, functional, or effective as possible. Optimization usually includes mathematical procedures such as finding the maximum or minimum of a function. - the term “optimal” at least in some examples refers to a most desirable or satisfactory end, outcome, or output. - the term “optimum” at least in some examples refers to an amount or degree of something that is most favorable to some end. - opticalma at least in some examples refers to a condition, degree, amount, or compromise that produces a best possible result. Additionally or alternatively, the term “optima” at least in some examples refers to a most favorable or advantageous outcome or result. - probability at least in some examples refers to a numerical description of how likely an event is to occur and/or how likely it is that a proposition is true. - probability distribution at least in some examples refers to a mathematical function that gives the probabilities of occurrence of different possible outcomes for an experiment or event. Additionally or alternatively, the term “probability distribution” at least in some examples refers to a statistical function that describes all possible values and likelihoods that a random variable can take within a given range (e.g., a bound between minimum and maximum possible values). - a probability distribution may have one or more factors or attributes such as, for example, a mean or average, mode, support, tail, head, median, variance, standard deviation, quantile, symmetry, skewness, kurtosis, and the like. - a probability distribution may be a description of a random phenomenon in terms of a sample space and the probabilities of events (subsets of the sample space). - Example probability distributions include discrete distributions (e.g., Bernoulli distribution, discrete uniform, binomial, Dirac measure, Gauss-Kuzmin distribution, geometric, hypergeometric, negative binomial, negative hypergeometric, Poisson, Poisson binomial, Rademacher distribution, Yule-Simon distribution, zeta distribution, Zipf distribution, and the like), continuous distributions (e.g., Bates distribution, beta, continuous uniform,

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[]

George VI and Queen Elizabeth The Queen Mother. Princess Margaret, Countess of Snowdon. (Margaret Rose 21 August 1930 - 9 February 2002) was the eldest daughter of Queen Elizabeth The Queen Mother. (Margaret Rose 21 August 1930 - 9 February 2002) was the oldest child of King George VI and Queen Elizabeth | Bulger was one of the FBI's most wanted fugitives for 16 years until he was captured in Santa Monica, California, in 2011. He was convicted in 2013 of a litany of crimes, including racketeering, extortion, money-laundering, and murder. He was sentenced to two consecutive life sentences plus five years. He died in federal prison in West Virginia on Tuesday at the age of 89. Bulger was one of the FBI's most wanted fugitives for 16 years before he was captured in Santa Monica, California, in 2011. |

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[]

up from 20% in 2021. LNG prices are typically higher than pipeline gas on spot markets owing to liquification and transportation costs. Moreover, with the reduction of pipeline supply from Russia, more gas is being bought on LNG spot markets both in the EU and globally leading to stronger competition. Even gas bought in long-term contracts is largely indexed to spot markets, which are increasingly influenced by supply disruptions and demand patterns in Asia. Financial and behavioural aspects of gas derivative markets can exacerbate this volatility and amplify the impact of shocks . A few non-financial corporates undertake most trading activity in European gas markets. Recent evidence presented by the European Securities Markets Agency (ESMA) suggests that there is significant concen - tration both at position and trading venue level and that concentration increased in 2022 during largest spike in natural gas prices. The top 5 companies hold around 60% of positions in some trading venues and their short positions increased considerably by almost 200% between February and November 2022 [see Figure 4]vii. Super - vision of these companies’ activities could be improved. While regulated financial entities (for example, investment banks, investment funds and clearing market participants) are covered by conduct and prudential rules, many of the companies that trade commodity derivatives can rely on exemptions. In particular, when a commodity compa - ny’s main activities are not trading, they can be exempted from authorisation as a supervised investment company (so-called “ancillary” exemptions). The US has a stricter approach. Exemptions apply on some types of contracts, but commodity companies are not exempted from supervision, allowing for a more precise level of scrutiny. In addition, energy commodities are subject to position limits, including Henry Hub natural gas contracts. 01. AggregateEU is a first step in demand aggregation allowing the pooling of demand, the coordination of infrastructure use and negotiation with international partners, fostering more centralised EU joint purchasing to further leverage the EU’s market power. 43THE FUTURE OF EUROPEAN COMPETITIVENESS — PART A | CHAPTER 3FIGURE 4 Market concentration in EU gas derivatives markets Europe’s market rules pass on this volatility to end users and may prevent the full benefits of decarbonising power generation from reaching them . Even as Europe reduces its dependence on natural gas and increases investment in clean energy generation, its market rules in the power sector do not fully decouple the price of renew - able

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and RIPL3-2023 database [ 15] (TRIPL3 1/2). The “main isomer” is marked with an asterisk(*) in each nucleus E∗(MeV) Texp. 1/2(ns) Tlit. 1/2(ns) Ref. TRIPL3 1/2(ns) 88Br 0.270* 4500 (400) 5500 (100) [ 16] 5300 91Rb 1.134* 15 (4) 16 (1) [ 17] 16.6 92Rb 0.284* 54.4 (27) 54 (3) [ 18]5 4 0.142 0.82 (4) 0.75 (3) [ 19]0 . 7 5 93Rb 4.423* 97 (15) 111 (11) [ 17] 111 94Rb 2.075 65 (8) 107 (16) [ 20] 107 1.485* 42 (7) 18 (1) [ 20]1 8 0.328 1.6 (1) – – – 95Rb 0.835* 101 (24) 94 (7) [ 17]– 95Sr 0.556* 21.0 (5) 21.5 (3) [ 21] 21.9 97Sr 0.831* 530 (22) 504 (8) [ 16] 395 0.308 200 (10) 165 (4) [ 21] 169 98Y 1.181* 740 (30) 780 (30) [ 22] 780 0.496 6740 (140) 6900 (50) [ 22] 6900 0.375 37.8 (13) 35.2 (5) [ 22] 35.2 0.171 680 (30) 630 (20) [ 22] 630 97Zr 1.264* 106 (11) 102.8 (24) [ 23] 102.8 99Zr 1.039 29 (4) 54 (10) [ 24]5 4 0.252* 345 (12) 336 (5) [ 25] 293 0.122 1.01 (3) 1.08 (2) [ 26]1 . 0 7 101Zr 0.942* 18.2 (19) 16 (2) [ 27]1 6 108Tc 0.330(+ x)* 116 (3) 94 (10) [ 28]– 0.176(+ x)2 . 8 1 ( 4 ) – – – 0.106(+ x)0 . 9 4 ( 6 ) – – – ﬁssion of252Cf), and are used in evaluated data. Although an isomeric state was observed in Ref. [ 44], no absolute excita- tion energy was assigned. However, in Ref. [ 45], the author established a level scheme without ﬂoating level, based on common γ-ray transitions (86 keV and 106 keV) seen in both 108Moβdecay and252Cf(sf). The γ-γcoincidences from our data are in agreement with these three level schemes. Further-more, we observe a transition with E γ/similarequal58 keV that was also reported in Ref. [ 43]. We derived from our data that the level at E∗=330 keV is a consistent candidate for the 116 ns isomeric state, from all γ-γcoincidences reported in Fig. 9. For completeness, we report in the ﬁgure the γ-ray energies measured by our setup. Besides, we measured the half-life of two short-lived states below the main isomer for the ﬁrst time, at E∗=176.2 and 106.3 keV. From the multiple isomers analysis, we undoubt-edly concluded that the 176.2 keV state, populated

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281 Manoj Harjani, “O-RAN is overhyped as avoiding Chinese 5G influence,” ASPI, May 29, 2024, https:// www.aspistrategist.org.au/o-ran-is-overhyped-as-avoiding- chinese-5g-influence/ . 282 Emil Björnson, “Open RAN: Success or Failure?” Wireless Future, October 23, 2024, https://ma-mimo. ellintech .se/2024/10/23/open-ran-success-or-failure/ . 283 Ramsha Jahangir and Justin Hendrix, “With US Commitment to Internet Freedom in Jeopardy, China and Russia Set to Gain,” Tech Policy Press, February 6, 2025, https://www.techpolicy.press/with-us- commit - ment-to-internet-freedom-in-jeopardy-china-and-russia-set- to-gain/ ; Arun Sukumar and Arindrajit Basu, “Back to the territorial state: China and Russia’s use of UN cybercrime negotiations to challenge the liberal cyber order,” Journal of Cyber Policy 9, no.2 (2024): 256-287, https://www.tandfonline.com/ doi/full/10.1080 /23738871.2024.2436591 . 284 Emma Klein and Stewart Patrick, “Envisioning a Global Regime Complex to Govern Artificial Intelligence,” Carnegie Endowment for International Peace, March 21, 2024, https://carnegieendowment.org/ research /2024/03/envisioning-a-global-regime-complex-to-govern-artificial-intelligence ?lang=en . 285 Vibhu Mishra, “General Assembly adopts landmark resolution on artificial intelligence,” United Nations, March 21, 2024, https:// news.un.org/en/story/2024/03/1147831 . 286 Raj Bhala, “The New Age of Global T rade: Aggressive Neo-Mercantilism,” The Diplomat , March 1, 2025, https://thediplomat.com/2025/03/the-new-age -of-global-trade-aggressive-neo-mercantilism/ . 287 “#KeepItOn,” Access Now, accessed May 2025, https://www.accessnow.org/campaign/keepiton/ . 288 “Global statement: Stop facial recognition surveillance now!” joint letter, European Digital Rights and Big Brother Watch, et al., September 2023, https://edri.org/wp-content/uploads/2023/09/Global-statement- Stop-facial-recognition-now.pdf . 80 | Digital Democracy in a Divided Global LandscapeIn a complex, changing, and increasingly contested world, the Carnegie Endowment generates strategic ideas, supports diplomacy, and trains the next generation of international scholar-practitioners to help countries and institutions take on the most difficult global problems and advance peace. With a global network of more than 170 scholars across twenty countries, Carnegie is renowned for its independent analysis of major global problems and understanding of regional contexts. Democracy, Conflict, and Governance Program The Democracy, Conflict, and Governance Program is a leading source of independent policy research, writing, and outreach on global democracy, conflict, and governance. It an - alyzes and seeks to improve international efforts to reduce democratic backsliding, mitigate conflict and violence, overcome political polarization, promote gender equality, and advance pro-democratic uses of new technologies.

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vs 14.85%; P-value = 0.007). They also presented higher rates of respiratory symptom than non-severe cases (79.55% vs 46.53%; P-value < 0.001). The biological comparison found significant differences for neutrophil count (median, 4.74 vs Figure 1 Receiver operating characteristic (ROC) curves of parameters of blood routine for the diagnosis (discriminating) of disease severity on admission.  3.56; P-value < 0.001), lymphocyte count (median, 1.02 vs 1.73; P-value < 0.001), eosinophil count (median, 0.01 vs 0.04; P-value < 0.001), and CRP level (median, 86.4 vs 3.4; P-value < 0.001). According to ROC curves of hematologic parameters and CRP admission level, the AUCs of leucocyte count, neutrophil count, monocyte count, hemoglobin count, and CRP level were 0.594, 0.691, 0.523, 0.475, and 0.872, respectively ( Figure 1 ). The AUC for severity prediction of CRP was significantly higher than leucocyte count (P-value < 0.001), and neutrophil count (P-value < 0.001). As represented in Table III , CRP level was associated with COVID-19 severity in the univariate analysis (OR=1.22, 95% IC (1.13-1.33)). For the multivariate analysis, we found that CRP level was CRP , C-reactive protein. Table III Independent discriminators (predictors) of disease severity. | | Univariate OR (95% CI) | Multivariate Model OR (95% CI) | Multivariate Model (stepwise) OR (95% CI) | |--------------------------|--------------------------|----------------------------------|---------------------------------------------| | Demographics | Demographics | Demographics | Demographics | | Age, years | 1.07 (1.04-1.10) | 1.04 (1.00-1.08) | 1.05 (1.02-1.09) | | Male | 5.93 (2.58-13.66) | 3.90 (1.24-12.33) | 3.35 (1.20-9.36) | | Comorbidities | Comorbidities | Comorbidities | Comorbidities | | Hypertension | 3.76 (1.70-8.29) | 0.88 (0.24-3.21) | | | Diabetes | 3.42 (1.25-9.38) | 0.95 (0.21-4.27) | | | Cardiovascular disease | 6.40 (2.07-19.79) | 3.74 (0.76-18.29) | | | Respiratory disease | 2.54 (0.83-7.74) | | | | Other disease | 3.28 (1.44-7.46) | 3.19 (0.96-10.55) | | | Clinical symptoms | Clinical symptoms | Clinical symptoms | Clinical symptoms | | Fever | 1.99 (0.97-4.08) | | | | General symptom | 1.72 (0.84-3.54) | | | | Respiratory symptom | 4.47 (1.95-10.25) | 4.26 (1.31-13.89) | 3.11 (1.11-8.74) | | ENT symptom | 0.63 (0.28-1.44) | | | | Digestive symptom | 1.35 (0.60-3.04) | | | | Blood routine | Blood routine | Blood routine | Blood routine | | Leucocyte (×10 9 per L) | 1.15 (1.00-1.32) | | | | Neutrophil (×10 9 per L) |

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[]

Suite 1001 Ottawa, Ontario Canada K1P 5G4 IGFMining.org X @IGFMining  ## OECD HEAD OFFICE 2, rue André Pascal 75775 Paris Cedex 16 France @ OECD.org X OECD  ## ACKNOWLEDGEMENTS The lead authors of this publication are Tomas Balco, Senior Advisor, BEPS Capacity Building Team of Global Relations and Development Division, OECD, and Jaqueline Taquiri, Senior Policy Advisor, Tax and Extractive Industries, IGF. The authors would like to recognize the contributions made by the governments of Kenya, Liberia, Papua New Guinea, South Africa, Tanzania, the United Kingdom, and Zambia as well as Thomas Baunsgaard from the International Monetary Fund, and the International Council on Mining and Metals. The authors were ably assisted in their research work by members of the IGF's Global Mining Tax Initiative, including Kudzai Mataba, Alexandra Readhead, and Ekpen Omonbude, and colleagues from the OECD, including Andrew Viola. OECD: http://www.oecd.org/en/about/programmes/beps-in-mining IGF: www.igfmining.org/financial-benefits/  This work is made available under the Creative Commons Attribution 4.0 International licence. By using this work, you agree to be bound by the terms of this licence (https:// creativecommons.org/licenses/by/4.0/). Attribution - You must cite the work. Translations You must cite the original work, identify changes to the original and add the following text: In the event of any discrepancy between the original work and the translation, only the text of the original work should be considered valid. Adaptations You must cite the original work and add the following text: This is an adaptation of an original work by the OECD, the IISD and the IGF. The opinions expressed and arguments employed in this adaptation should not be reported as representing the official views of the OECD, the IGF, or their respective member countries. Third-party material The licence does not apply to third-party material in the work. If using such material, you are responsible for obtaining permission from the third party and for any claims of infringement. You must not use the OECD's, the IISD's or the IGF's respective logo, visual identity, or cover image without express permission or suggest the OECD or IISD/IGF endorses your use of the work. Any dispute arising under this licence shall be settled by arbitration in accordance with the 2012 Rules of the Permanent Court of Arbitration. The seat of arbitration shall be Paris (France). The number of arbitrators shall be one. ## LIST OF ABBREVIATIONS APT additional profit tax BEPS

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Figure 3.66. Keyword cloud for Chemistry and chemical engineering in Azerbaijan Figure 3.68. Keyword cloud for Mechanical engineering and heavy machinery in Azerbaijan Figure 3.67. Keyword cloud for Energy in Azerbaijan Figure 3.69. Keyword cloud for Health and wellbeing in Azerbaijan 222 Part 3 Analysis of scientific and technological potential Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation223 6.4 Georgia – Summary of the strengths of the S&T specialisa- tions Georgia’s most highlighted S&T domains are the following: ■Environmental sciences and industries ticks all S&T indicators – on critical mass, spe- cialisation and excellence – for publications, patents and projects. It is a very clear spe- cialisation domain for Georgia, with particular relevance in Geology and Geotechnical engi- neering, as well as Environmental engineering and Chemistry; ■Agrifood presents a high specialisation in patents and publications, as well as a critical mass in patents and a relevant number of EU-funded R&I projects, with science orient- ed towards Horticulture, Genetics and Plant science; GEORGIA Critical mass Specialisation Excellence Summary S&T domain Pubs. Pat. Pubs. Pat. NCI*EC projects*Total Agrifood 4 Biotechnology 0 Chemistry and chemical engineering2 Electric and electronic technologies0 Environmental sciences and industries6 Fundamental physics and mathematics3 Governance, culture, education and the economy4 Health and wellbeing 3 ICT and computer science 3 Mechanical engineering and heavy machinery2 Nanotechnology and materials 2 Optics and photonics 1 *NCI = Normalised citation impact *EC projects = EU-funded R&I projectsTable 3.31. Selected S&T specialisation domains in Georgia ■Health and wellbeing presents a high crit- ical mass, specialisation and citation impact in publications, while no positive indicator emerges in relation to patents. It co-occurs frequently with the domain of Agrifood. Be- yond General medicine, research is related, in particular, to Infectious diseases and Immu- nology; and ■ICT and computer science presents a spe- cialisation in patents as well as highly cited publications and a relevant number of EC pro- jects. The following clouds present the most relevant keywords for these highlighted S&T domains. Figure 3.70. Keyword cloud for Environmental sciences and industries in Georgia Figure 3.72. Keyword cloud for Health and wellbeing in Georgia Figure 3.71. Keyword cloud for Agrifood in Georgia Figure 3.73. Keyword cloud for ICT and computer science in Georgia 224 Part 3 Analysis of scientific and technological potential Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation225 6.5 Moldova – Summary of the strengths

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on the sensor data received from the sensing means to optimize the recovery of one or more desired materials from a waste stream. Example [0189] includes the method of example [0188] and/or some other example(s) herein, wherein the method includes: optimizing an arrangement of the material handling means based on the sensor data using optimization means. Example [0190] includes the method of examples [0188]-[0189] and/or some other example(s) herein, wherein the controlling includes: controlling material handling means to remove contaminants recognized by the sensing means from the waste stream. Example [0191] includes the method of examples [0188]-[0190] and/or some other example(s) herein, wherein the controlling includes: controlling material handling means to remove the one or more desired materials recognized by the sensing means from the waste stream. Example [0192] includes a method for material handling, comprising: receiving status information from the material handling means; and controlling the material handling means based on the sensor data received status information. Example [0193] includes the apparatus of examples [0188]-[0192] and/or some other example(s) herein, wherein the controlling includes: reconfiguring the material handling means in real time or near real time to remove varying types of the one or more desired materials. Example [0194] includes the apparatus of example [0193] and/or some other example(s) herein, wherein the material handling means includes a plurality material handling mechanisms, and the reconfiguring includes: reconfiguring each of the plurality of material handling mechanisms in real time or near real time to balance an amount of the one or more desired materials to be removed between each of the plurality of material handling mechanisms. Example [0195] includes the apparatus of examples [0188]-[0194] and/or some other example(s) herein, wherein the sensing means comprises a machine vision system. Example [0196] includes the method of examples [0188]-[0195] and/or some other example(s) herein, wherein the method includes: operating a machine learning model and/or artificial intelligence system to adaptively control the material handling means based on the sensor data. Example [0197] includes a method of operating a central controller of a material recovery facility (MRF), the method comprising: receiving data streams from respective sensors of a set of sensors; processing the one or more data streams to determine an MRF status of the MRF, wherein the MRF status is based on a composition of a material waste stream at one or more locations within the MRF and an operating condition of at least one

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specialisation is above 1.5 highlighted in dark green and industries where the degree of specialisation is above 1.25 but below 1.5 high- lighted in light green. Based on the results, for each EaP country we can identify those industries which have an innovation potential based on the relative share of product and/or process innova- tors, as follows. 40 Industry names are those used in the Enterprise Survey. NACE codes match the corresponding ISIC codes. Industry names therefore do not necessarily match NACE industry names. 86 Part 2 Analysis of economic and innovation potential ■Armenia • Paper (NACE 17) • Basic metals (NACE 24) • Construction (NACE F) • Transport (NACE H) ■Azerbaijan • Recycling (NACE 33) • Services of motor vehicles (NACE 45) • Wholesale (NACE 46) ■Georgia • Garments (NACE 14) • Publishing, printing and recorded media (NACE 18) • Chemicals (NACE 20+21) • Non-metallic mineral products (NACE 23) • Basic metals (NACE 24) • Fabricated metal products (NACE 25) • Furniture (NACE 31) • Retail (NACE 47) • Hotels and restaurants (NACE I) ■Moldova • Wood (NACE 16) • Paper (NACE 17) • Chemicals (NACE 20+21) • Plastics & rubber (NACE 22) • Precision instruments (NACE 26) • Machinery and equipment (NACE 28) • Information and communication (NACE J) ■Ukraine • Textiles (NACE 13) • Services of motor vehicles (NACE 45) The fact that only two industries emerge as spe- cialised for Ukraine is a direct result of the fact that the weighted number of enterprises is much higher in Ukraine than in the other countries, with a more equal distribution of enterprises across the different industries.Armenia Azerbaijan Belarus Georgia Moldova Ukraine EaP All industries 4 317 2 475 27 903 5 748 6 528 56 574 103 545Table 2.27. Weighted number of enterprises covered in the Enterprise Survey Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation87 88 Part 2 Analysis of economic and innovation potential Share of product innovators Share of process innovators Share of product and/or process innovators Name of industry Armenia Azerbaijan Belarus Georgia Moldova Ukraine EaP Armenia Azerbaijan Belarus Georgia Moldova Ukraine EaP Armenia Azerbaijan Belarus Georgia Moldova Ukraine EaP Food (10+11) 37.0 42.6 63.3 33.7 42.9 39.1 43.1 23.3 3.7 43.2 25.8 50.1 19.2 27.5 45.5 46.3 65.5 42.5 61.7 44.6 51.0 Tobacco (12) -- -- -- -- 0.0 -- -- -- -- -- -- 0.0 -- --

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Spider uses trapped fireflies as glowing bait to attract more prey | EurekAlert! Advanced Search Home News Releases Multimedia Meetings Login Register News Release 28-Aug-2025 Spider uses trapped fireflies as glowing bait to attract more prey Peer-Reviewed Publication British Ecological Society Facebook X LinkedIn WeChat Bluesky Message WhatsApp Email image: Sheet web spider with fireflies caught in web view more Credit: Tunghai University Spider Ecologists have observed a species of nocturnal spider attracting prey to its web using the bioluminescent beacons of already trapped fireflies. This rare example of a predator exploiting its prey’s mating signal for its own gain is documented in the British Ecological Society’s Journal of Animal Ecology . Researchers at Tunghai University, Taiwan have observed sheet web spiders Psechrus clavis capturing fireflies in their webs and leaving them there while they emitted bioluminescent light for up to an hour. The researchers even observed the spiders going to check on the captured fireflies from time to time. Intrigued by this unusual behaviour the researchers set up an experiment to test whether this was a strategy used by the spiders to increase their hunting success. In the experiment, they placed LEDs that resembled fireflies, in real sheet spider webs and left other webs clear as controls. They found three times the amount of prey was attracted to webs with the LEDs compared to the control webs. This increased to ten times more prey when they only looked at fireflies being captured. The findings confirm that captured fireflies left as bait increase the hunting success rate of the spiders. The researchers also noticed that the majority of captured fireflies were male, who were likely mistaking the glow for potential mates. Dr I-Min Tso, the lead author of the study said: “Our findings highlight a previously undocumented interaction where firefly signals, intended for sexual communication, are also beneficial to spiders. “This study sheds new light on the ways that nocturnal sit-and-wait predators can rise to the challenges of attracting prey and provides a unique perspective on the complexity of predator-prey interactions.” The researchers suggest that this behaviour could have developed in sheet web spiders to avoid costly investment in their own bioluminescence like other sit-and-wait predators, such as anglerfish. Instead, the spiders are able to outsource prey attraction to their prey’s own signals. The sheet web spider Psechrus clavis is a nocturnal sit and wait predator found in subtropical forests

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[]

| 1 | | 0.9 | 1 | … | Poland 0.8 | | Portugal | … | … | … | … | … | | | Republic of | | | 0.75 | 0.83 | 100 ₋₄ | Moldova 0.86 0.76 | | Romania | 1 | 0.97 | 1 | 1 | … | | | | | | 0.9 | … | … | | | San | 1 | 0.94 | 0.9 | 1 | | Russian Federation 1 … | | | | | | | 100 | Marino | | | | | … | … | … | Serbia … … | | | 0.51 | 0.64 | … | 0.25 | … … | Slovakia | | Spain | | 0.93 | 0.85 | 1 | … | Slovenia 1 | | Sweden | 1 | | 0.95 | 1 | | 1 0.91 | | | | 0.8 | … | 0.83 | … | | | Switzerland | … | … | … | … | … | | | Ukraine United Kingdom | 1 | 0.92 | 0.95 | 1 | … | | | | 0.41 | 0.59 | … | 0.83 … | … … | United States … … … |

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[]

cohesion meas -ures are different in two neighbourhood types - A comparison of Sanjay (slum/ JJ - illegal housing built on public land) and Ajit Vihar (unauthorised - illegal housing built on private land typically owned by the household). - 3. There is a causal link between trust, social capital and neighbourhood cohe -sion irrespective of neighbourhood type - A comparison of Sanjay, Bhalswa and Ajit Vihar. ## Neighbourhoods Research from around the world has shown that maintaining well-being is crucial for those living in difficult and challenging circumstances. Well-being helps people cope with stress, trauma and hardship, enhancing resilience and mental health, and is vital in areas affected by poverty, conflict and disasters. We examine the relation -ships between subjective well-being (SWB) and neighbourhood cohesion, taking into consideration the socio-economic background of the households as well as levels of trust within our three different settlement types. As neighbourhoods are bounded urban areas, they provide a valuable opportunity to understand the perceptions of individuals and communities within a specific, finite region. By investigating different neighbourhoods, we can explore and compare how these factors vary across regions, shedding light on patterns and differences in community well-being, social cohesion and quality of life. This comparative approach reveals important insights into how neighbourhood characteristics impact residents ( Puddifoot, 1995 ; Pinchak et al., 2021). We consider the association between neighbourhood social cohesion and well-being for residents living in our different colony types. In this chapter, we will first explore the attitudes of residents through the Neighbourhood Cohesion Index (NCI) and the subjective well-being scale (SWB). These residents live in Bhalswa (resettlement colony) and Sanjay (slum/JJ colony), allowing us to investigate the first hypothesis: Being able to choose your neighbourhood is beneficial to your well-being and contributes positively to attitudes around neighbourhood cohesion - A comparison of Sanjay (slum/JJ) and Bhalswa (resettlement). Second, we consider whether the type of neighbourhood you live in affects how you perceive your community and your involvement within it. Residents' preferences on social capital and neighbourhood cohesion measures are different in two neighbourhood types - A comparison of Sanjay (slum/JJ - illegal housing public land) and Ajit Vihar (unauthorised - illegal housing private owned land). Third, we investigate links between trust, social capital and neighbourhood cohesion in the three different neighbourhood types. There is a causal link between trust, social capital and neighbourhood cohesion irrespective of neighbourhood type -

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Seen from such comparative perspectives, the near silence of post- 1989 historiography on the topic of women and science in the former communist bloc is even more striking, given that many women were not active on the peripheries of the scientific establishment, but at its very heart. Equally striking is the fact that the shadow of empire(s) lingers on - often unacknowledged - in discussions of science in South- Eastern and Central Europe, where it is not uncommon for public debates and even academic scholarship to take for granted the notion that 'modern' equals 'Western' and that 'Western' science is the yardstick by which all science is to be measured. 46 Although recent scholarship engages with the 'interimperial' legacies that have shaped Eastern European regions like Transylvania, 47 the domain of science has only occasionally been interrogated in the manner that scholarship on South Asia and other former colonial contexts has done, by moving away from George Basalla's influential diffusionist model of 'Western science' towards more sophisticated understandings of 'modern' science and empire as co- constituted, or a questioning of the moral and political underpinnings of 'Western science'. 48 Recent work that investigates how the implementation of a doctrine of 'self- management' - of scientific workers and their labour - by Yugoslavian socialist elites was linked to the creation of certain forms of scientific 'independence' from the 'West' represents a similar attempt in this direction. 49 In short, approaching the topic holistically, with a mind prepared to question well- established orthodoxies of geography, science, discipline, gender, race, labour and so on, is essential to considering the task at hand: piecing together histories of women in science from fragmentary, often silent archives. One is reminded here of Saidiya Hartman's wonderfully instructive work on Atlantic slavery: 'I had been looking for relatives whose only proof of existence was fragments of stories and names that repeated themselves across generations.' 50 Piecing together a story from such fragmentary archives should perhaps begin with the recognition of a salient, albeit rarely acknowledged truth - one amply demonstrated by Hartman's work - namely, that writing histories of erased, invisible or marginalized groups is difficult, time- consuming work. 51 Not infrequently, such work is rendered even more complicated by the entrenched power dynamics of academic research and translation in(to) the English language, which ensure, for example, that vibrant intellectual debates, often published in other languages, are only

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region is developing, such as near zero-emissions processes for materials production. To enable these goals, the report recommends for the EU to establish industrial partnerships with third countries in the form of offtake agreements across the supply chain or co-investment in manufacturing projects. The EU’s Global Gateway could be leveraged for the necessary investment. However, in situations where otherwise productive EU companies are being threatened by state-sponsored competition, the EU should be prepared to apply trade measures in line with principles described above [see the Box in chapter 1 – the starting point] . As part of its decarbonisation strategy, the EU should develop an industrial action plan for the automo - tive sector [see the chapter on automotive] . In the short term, the main objective for the sector should be to avoid a radical delocalisation of production away from the EU or the rapid takeover of EU plants and companies by state-subsidised foreign producers, while continuing decarbonisation. The countervailing tariffs recently adopted by the Commission against Chinese automotive companies making battery EVs will help level the playing field in this regard while accommodating genuine productivity gains in China. Looking forward, the report recommends for the EU to develop an industrial roadmap that accounts for the horizontal convergence (i.e. electrification, digitalisation and circularity) and the vertical convergence (i.e. critical raw materials, batteries, transport and charging infrastruc - ture) of value chains in the automotive ecosystem. As part of this action plan, the EU should evaluate support for IPCEIs in the automotive sector. Scale, standardisation and collaboration will be crucial for EU manufacturers to become competitive in areas such as small and affordable European EVs, software-defined vehicle and autonomous driving solutions, and the circularity value chain. A coherent digital policy, encompassing the data ecosystem, should support these developments. In building such a roadmap, the EU should follow a technology-neutral approach in defining the path to CO2 and pollutant reductions and should take stock of market and technological developments. The wider EU strategy towards cross-border and modal integration and sustainable transport needs to plan for competitiveness and not only for cohesion [see the chapter on transport] . Transport should be based on a new unified approach to planning at the EU and national levels, focused on harmonisation and interoperability as well as cohesion. This approach should be matched by deeper coordination with adjacent network industries (energy and telecoms) and new incentives

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[]

They were 7.5 pp (p<0.01) more likely to favour profiles with brokers having 12th grade education and a 11.4 pp (p<0.1) greater likelihood of preferring brokers with college education. In the unauthorised colony, Ajit Vihar, the longer residents had lived in the settlement, then this significantly decreased the likelihood of preferring a broker of the same partisanship from 17.9 pp to 2.8 pp (p<0.01). This is a sizable reduction of 15.1 pp. This was the most noticeable effect on choice. This could imply that for residents, the party of the broker is less important in Ajit Vihar in relation to ‘getting things done’ in their neighbourhood. In Ajit Vihar, residents were more likely to favour brokers from the parliamentary party BJP or AAP, municipal and state govern - ments. The data imply that this may not be how they would vote in an election. Robustness checks The analysis undertaken for each settlement rated slum leader profile observations, with respondents rating eight pairs of two slum leader and neighbour profiles per pairing. To obtain accurate variance estimates, standard errors are clustered by respondent, as observed choice outcomes are not independent across profiles rated by a single respondent. Due to multiple iterations, prior vignettes and their evalua - tions may frame subsequent vignettes and lead to carryover effects (Tourangeau et al., 1989 ; Wirtz, 1996 ). Conducting diagnostics around the variation in judgements gives interclass correlation for Sanjay colony ( ρ=0.274), Bhalswa ( ρ=0.269), Ajit Vihar ( ρ=0.252), hence, only 25–27% of the variation in judgements was attributed to the variation between respondents. This relatively moderate value indicates that the fairness of evaluations was rather homogeneous among respond - ents ( Auspurg and Hinz, 2015 ). The correlation between respondent value vari - ables and the error term for each settlement is close to zero (r<0.04), indicating a successful randomisation and that the model assumptions of independent vari - ables not being correlated with the error term is met. Standard randomised balance checks were also performed by regressing respondent attributes on indicator vari - ables for all of the broker profiles. We used again, as set out in the design effects section, binary indicators for duration of time in the settlement, education and gen - der. It was found that there was no change in our main findings when controlling for these demographic variables. Finally, we took great care at the design

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[]

sciences and industriesC02F Treatment of water, waste water, sewage, or sludge 523 414.14% Environmental sciences and industriesE21BEarth or rock drilling; obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells271 318.41% Environmental sciences and industriesB01D Separation 235 247.89% Environmental sciences and industriesE21C Mining or quarrying 214 199.07% Environmental sciences and industriesG01NInvestigating or analysing materials by determining their chemical or physical properties196 49.76% Fundamental physics and mathematicsG01NInvestigating or analysing materials by determining their chemical or physical properties153 38.85% Fundamental physics and mathematicsG06F Electric digital data processing 92 70.77% Fundamental physics and mathematicsF03D Wind motors 88 68.93% Fundamental physics and mathematicsB01D Separation 81 85.44% Fundamental physics and mathematicsH01LSemiconductor devices; electric solid state devices not otherwise provided for80 79.30% Governance, culture, education and the economyA61B Diagnosis; surgery; identification 83 14.35% Governance, culture, education and the economyG06F Electric digital data processing 70 53.85% 164 Part 3 Analysis of scientific and technological potential Domain IPC Description No recordsRelative freq. Governance, culture, education and the economyA63BApparatus for physical training, gymnastics, swimming, climbing, or fencing; ball games; training equipment28 104.67% Governance, culture, education and the economyG09BEducational or demonstration appliances; appliances for teaching, or communicating with, the blind, deaf or mute; models; planetaria; globes; maps; diagrams21 14.53% Governance, culture, education and the economyG06QData processing systems or methods, specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes; systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes, not otherwise provided for20 41.81% Health and wellbeingA61B Diagnosis; surgery; identification 5 506 952.05% Health and wellbeingA61K Preparations for medical, dental, or toilet purposes 2 540 556.80% Health and wellbeingG01NInvestigating or analysing materials by determining their chemical or physical properties2 247 570.51% Health and wellbeingA61PSpecific therapeutic activity of chemical compounds or medicinal preparations1 493 458.50% Health and wellbeingA61NElectrotherapy; magnetotherapy; radiation therapy; ultrasound therapy719 344.02% ICT and computer scienceG06F Electric digital data processing 693 533.08% ICT and computer scienceG06QData processing systems or methods, specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes; systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes, not otherwise provided for259 541.46% ICT and computer scienceH04LTransmission of digital information, e.g. telegraphic communication254 525.52% ICT and computer scienceA61B Diagnosis; surgery; identification 207 35.79% ICT and computer scienceH04N Pictorial communication, e.g. television 196 197.98% Mechanical engineering and heavy machineryA61B Diagnosis; surgery; identification 649 112.22% Mechanical engineering and heavy machineryG01NInvestigating or analysing materials by

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"determining", "their", "\n", "chemical", "or", "physical", "properties153", "38.85", "%", "\n", "Fundamental", "\n", "physics", "and", "\n", "mathematicsG06F", "Electric", "digital", "data", "processing", "92", "70.77", "%", "\n", "Fundamental", "\n", "physics", "and", "\n", "mathematicsF03D", "Wind", "motors", "88", "68.93", "%", "\n", "Fundamental", "\n", "physics", "and", "\n", "mathematicsB01D", "Separation", "81", "85.44", "%", "\n", "Fundamental", "\n", "physics", "and", "\n", "mathematicsH01LSemiconductor", "devices", ";", "electric", "solid", "state", "devices", "not", "\n", "otherwise", "provided", "for80", "79.30", "%", "\n", "Governance", ",", "\n", "culture", ",", "education", "\n", "and", "the", "economyA61B", "Diagnosis", ";", "surgery", ";", "identification", "83", "14.35", "%", "\n", "Governance", ",", "\n", "culture", ",", "education", "\n", "and", "the", "economyG06F", "Electric", "digital", "data", "processing", "70", "53.85", "%", "\n", "164", "\n ", "Part", "3", "Analysis", "of", "scientific", "and", "technological", "potential", "\n", "Domain", "IPC", "Description", "No", "recordsRelative", "\n", "freq", ".", "\n", "Governance", ",", "\n", "culture", ",", "education", "\n", "and", "the", "economyA63BApparatus", "for", "physical", "training", ",", "gymnastics", ",", "swimming", ",", "\n", "climbing", ",", "or", "fencing", ";", "ball", "games", ";", "training", "equipment28", "104.67", "%", "\n", "Governance", ",", "\n", "culture", ",", "education", "\n", "and", "the", "economyG09BEducational", "or", "demonstration", "appliances", ";", "appliances", "for", "\n", "teaching", ",", "or", "communicating", "with", ",", "the", "blind", ",", "deaf", "or", "mute", ";", "\n", "models", ";", "planetaria", ";", "globes", ";", "maps", ";", "diagrams21", "14.53", "%", "\n", "Governance", ",", "\n", "culture", ",", "education", "\n", "and", "the", "economyG06QData", "processing", "systems", "or", "methods", ",", "specially", "adapted", "\n", "for", "administrative", ",", "commercial", ",", "financial", ",", "managerial", ",", "\n", "supervisory", "or", "forecasting", "purposes", ";", "systems", "or", "methods", "\n", "specially", "adapted", "for", "administrative", ",", "commercial", ",", "\n", "financial", ",", "managerial", ",", "supervisory", "or", "forecasting", "\n", "purposes", ",", "not", "otherwise", "provided", "for20", "41.81", "%", "\n", "Health", "and", "\n", "wellbeingA61B", "Diagnosis", ";", "surgery", ";", "identification", "5", "506", "952.05", "%", "\n", "Health", "and", "\n", "wellbeingA61", "K", "Preparations", "for", "medical", ",", "dental", ",", "or", "toilet", "purposes", "2", "540", "556.80", "%", "\n", "Health", "and", "\n", "wellbeingG01NInvestigating", "or", "analysing", "materials", "by", "determining", "their", "\n", "chemical", "or", "physical", "properties2", "247", "570.51", "%", "\n", "Health", "and", "\n", "wellbeingA61PSpecific", "therapeutic", "activity", "of", "chemical", "compounds", "or", "\n", "medicinal", "preparations1", "493", "458.50", "%", "\n", "Health", "and", "\n", "wellbeingA61NElectrotherapy", ";", "magnetotherapy", ";", "radiation", "therapy", ";", "\n", "ultrasound", "therapy719", "344.02", "%", "\n", "ICT", "and", "computer", "\n", "scienceG06F", "Electric", "digital", "data", "processing", "693", "533.08", "%", "\n", "ICT", "and", "computer", "\n", "scienceG06QData", "processing", "systems", "or", "methods", ",", "specially", "adapted", "\n", "for", "administrative", ",", "commercial", ",", "financial", ",", "managerial", ",", "\n", "supervisory", "or", "forecasting", "purposes", ";", "systems", "or", "methods", "\n", "specially", "adapted", "for", "administrative", ",", "commercial", ",", "\n", "financial", ",", "managerial", ",", "supervisory", "or", "forecasting", "\n", "purposes", ",", "not", "otherwise", "provided", "for259", "541.46", "%", "\n", "ICT", "and", "computer", "\n", "scienceH04LTransmission", "of", "digital", "information", ",", "e.g.", "telegraphic", "\n", "communication254", "525.52", "%", "\n", "ICT", "and", "computer", "\n", "scienceA61B", "Diagnosis", ";", "surgery", ";", "identification", "207", "35.79", "%", "\n", "ICT", "and", "computer", "\n", "scienceH04N", "Pictorial", "communication", ",", "e.g.", "television", "196", "197.98", "%", "\n", "Mechanical", "\n", "engineering", "and", "\n", "heavy", "machineryA61B", "Diagnosis", ";", "surgery", ";", "identification", "649", "112.22", "%", "\n", "Mechanical", "\n", "engineering", "and", "\n", "heavy", "machineryG01NInvestigating", "or", "analysing", "materials", "by" ]

[]

of topics consisting of groups of relevant words, as previously explained. These topics generally have a much finer gran- ularity than the S&T priority domains we would typically define in the design of a Smart Speciali- sation Strategy. Therefore, for practical reasons, to best help in defining the different domains, topics whose semantic content was largely overlapping were grouped together. Additionally, some of the extracted topics were finally discarded because of a phenomenon commonly known as ‘topic drift’56, 56 Liu, Q., Huang, H. & Feng, C., ‘Micro-blog post topic drift detection based on LDA model’, Behavior and Social Com- puting, Springer, Cham., pp. 106-118, 2013.Figure 3.1. A graphical representation of the results produced by topic modelling via Latent Dirichlet Allocation Documents are linked to several topics, while topics are composed of words appearing in the various texts. The same words can appear in multiple topics, while the topics connected to some specific documents may feature some words which are not actually contained in some of the texts, but are semantically related 148 Part 3 Analysis of scientific and technological potential whereby the content of some topics is diverted by recurrent words which do not convey meaningful information (such as, for instance, terms related to methods and instruments transversally used in different scientific domains). Once topics were grouped, to achieve point 2. above, a series of domain names were chosen to label each of those groups. These domains are used as labels, transversely across EaP countries so that topics featuring similar semantic content from two different countries are eventually given the same label. The choice of label is carried out to facilitate use by stakeholders in a participatory co-design of R&D&I policies, particularly towards the EDP in the context of Smart Specialisation. Lastly, to have a clear understanding of the num- ber of records associated with each single do- main, the fractional document/topic weights were converted into a categorical association: docu- ments were eventually associated with a specific topic if the respective weight exceeded the aver- age weight of the topic across records plus one standard deviation. This allowed us to link docu- ments with a limited subset to topics and, in turn, domains. 2.3 Results Table 3.3a presents the 14 labelled topic groups obtained from the topic modelling process de- scribed in the previous sections. A second table includes the first 50 keywords linked to the topics within each group;

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48 UA 5 5 22 13 1 238 PublicationsFigure 3.51. Number of publications and EC projects in collaboration between EaP actors in different countries, in the ‘Energy’ domain Colour indicates the relative distribution of documents, computed row-wise. AM AZ BY GE MD UA Other 1 1 1 3 2 5 1 3 6 8 3 3 15 1 2 6 3 41 EC projectsAM AZ BY GE MD UA Other AM 10 19 30 8 33 313 AZ 10 7 16 4 15 164 BY 19 7 13 9 83 497 GE 30 16 13 7 33 534 MD 8 4 9 7 36 151 UA 33 15 83 33 36 2 875 PublicationsFigure 3.52. Number of publications and EC projects in collaboration between EaP actors in different countries, in the ‘Environmental sciences and industries’ domain Colour indicates the relative distribution of documents, computed row-wise. Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation213 Regional collaboration in Fundamental physics and mathematics The domain of Fundamental physics and math- ematics accounts for the vast majority of co-pub- lications in the Eastern Partnership. Armenia and Georgia collaborate most intensively with one an- other, holding the highest number of publications in their bilateral collaborations. For Azerbaijan, Moldova and Ukraine, external partnerships ac- count for the vast majority of their collaborations. In terms of EC projects, the only intra-EaP collabo- ration is between Ukraine and Armenia. The inten- sity of collaborations with external partners is less significant in this case.Regional collaboration in Governance, culture, education and the economy In the case of Governance, culture education and the economy publications, external collabo- rations again have a significant weight across all six EaP countries. Within the EaP, the pattern of collaboration is very evenly distributed. Besides Ukraine, Armenia-Georgia and Moldova-Ukraine are the partnerships that stand out the most. Collaboration in terms of EC projects is higher than in other domains, and evenly distributed across the countries. Georgia’s collaboration with Ukraine and Armenia stands out. AM AZ BY GE MD UA Other 2 2 3 1 2 4 7 1 2 4 8 EC projectsAM AZ BY GE MD UA Other AM 94 1 412 1 663 6 876 3 162 AZ 94 6 9 3 35 648 BY 1 412 6 1 377 10 673 2 619 GE 1 663 9 1 377 9 872 2 500 MD 6 3 10 9

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[]

age of 18 and his reading and writing are not perfect. The second informant, Mr. Norman (the driver henceforth), is from St. Mary in the north of Jamaica. He migrated to Britain when he was 17. Today he is 59 years old. He worked in two factories in Manchester, as a dry cleaner, and as a carpet fitter before he became a taxi-driver, which is his present job. He also studied for a while in Jamaica and took a course in reading and writing in Manchester. This means that he dealt, and is still dealing with different people. Accordingly, his language is expected to be influenced more than that of the first informant. ## 5. Data Collection Data gathering is based on three factors. Firstly, the author once lived with his informants for one year or so, which enabled him to observe a great deal of the properties of their speech. Secondly, he recorded their casual speech with their permission. Thirdly, in the process, he gave them separately a list of words and sentences to read, some of which are given below in table (1). In addition, examples will be citied in the analysis from the informants' casual speech when appropriate. It is important to mention that the Jamaican Creole transcriptions in this study are based on Cassidy (1961) and Cassidy and Le Page (1967), and the RP counterparts on Gimson (1980) and Roach (2000). Transcribing and codifying data were done by the researcher himself, then checked by trained transcribers and a phonologist at the University of Bangor, North Wales. Data was coded manually to categorize the pronunciation of the fricative in question in the spontaneous speech and list reading of the subjects. For reference regarding Jamaican talk of the subjects, Cassidy (1961), Cassidy and Le Page (1967), Bailey (1966), and Holm (2000) were consulted. As for the Arabic speakers, the author referred to Basalamah (1990) and to his intuition as a native speaker of the dialect spoken by the Arab subjects. The data displayed in (table 1) and (table 2) below contains information pertaining to the pronunciation of English voiced labio-dental fricative /v/. Table 1. Words pronounced by the barber and the driver in casual speech | Gloss | Driver | Barber | JC | RP | |---------|------------|------------|------------|------------| | seven | /se β ˌ m/ | /se β ˌ m/ | /se β ˌ m/ | /seven/ | |

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come to the conclusion that many of the features found in Haitian French-lexifier creoles do occur in L2 French and other interlanguages, as a result of L1 transfer and other acquisition processes. The investigation includes word-order within the noun phrase, pronominal clitics, the absence of copula, grammatical gender, and verb movement. The major claim of the model of creole genesis advocated in the study which he calls gradualist/second language acquisition, is that creole genesis does not involve any specific mental processes or strategies other than those attested in ordinary second language acquisition. In Lefebvre et al. (2003), a number of second language researchers and creolists engage in dialogues which focus on the processes characterizing various stages of L2 acquisition and creole genesis, such as relexification and transfer from L1 and their role in the initial state. The dialogues also cover morphological, phonological, semantic and syntactic properties of interlanguage grammar and creole grammars. Their findings lend support to the view that the same processes are found to shape the initial stages of the two situations. ## 3. Current Study This study aims at investigating to what extent the linguistic processes exhibited in the creolization/decreolization parallel those manifested by Mousa's (1994) learners in particular and those of child language and second/foreign language in general. Furthermore, it is assumed that foreign/second language learning, de/creolization and historical change are significantly linked, in such a way that accounting for these learning situations is never precise without historical explanations. Thus, another aim of this study is to see to what extent the behaviour of the speakers of the Board Jamaican Creole and Mousa's learners exhibit facts of historical change. But before embarking on our investigation, introducing the Jamaican informants and the Saudi learners in Mousa's (1994) work is necessary. ## 4. Jamaican Informants The informants are two speakers of what is called the Broad Jamaican Creole (Baily, 1973) of nearly the same age. The first one Mr. Mike (the barber henceforth), is from Hanover in the west of Jamaica. He migrated to Britain when he was 18 years old. Today he is 61 years old. He is a barber in Moss Side, Manchester, England. Most of his customers are West Indies, old and young. He uses the same language (Broad Jamaican Creole) at work, home and everywhere. He is always in touch with the West Indies people. He has little education. He left school before the

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IV. Selected S&T specialisation domains in ArmeniaIn Armenia, Agrifood correlates highly with the S&T domains Biotechnology and Health and wellbeing, notably in the healthy sweetener industry; ■owing to the country’s hard sciences strengths, the domain Nanotechnology and materials presents a notable critical mass and a rele- vant number of EC projects, with an orienta- tion to fundamental fields (such as Condensed matter, or Electronic, optical and magnetic materials); ■Health and wellbeing presents a large crit- ical mass and specialisation in publications, and important activity in EC projects. The sci- entific publications cluster in the subject field General medicine, followed at a distance by Genetics, Public Health and Biochemistry. Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation17 Azerbaijan – Summary of the strengths of the S&T specialisations Azerbaijan presents a rather diversified S&T pan- orama, but in several S&T domains it is oriented towards the oil and petrochemical industries from a variety of disciplines and technologies. Its most highlighted S&T domains are the following: ■Chemistry and chemical engineering presents a notable critical mass in publica- tions and patents, as well as a high scientif- ic specialisation and citation impact. Highly co-occurrent with Energy and Environmental sciences and industries, Azeri chemistry and chemical engineering is well-aligned with the petrochemical industry, with particular strengths in catalysis and synthesis processes in organic chemistry; ■Energy presents a notable scientific and technological specialisation, as well as a crit- ical mass in patents. In accordance with the country’s Chemistry and chemical engineering acumen, S&T activity in Energy is oriented to- wards the oil and petrochemical industry; ■Mechanical engineering and heavy ma- chinery presents a scientific and technologi- cal specialisation, critical mass in patents and a high scientific citation impact. This domain frequently overlaps with Energy; ■Health and wellbeing presents a high crit- ical mass and specialisation in both publica- tions and patents. The scientific publications cluster in the subject field ‘General medicine’, followed at a distance by ‘Cardiology and car- diovascular medicine’, and patents in the phar- maceutical and medical devices classes (A61). AZERBAIJAN Critical mass Specialisation Excellence Summary S&T domain Pubs. Pat. Pubs. Pat. NCI*EC projects*Total Agrifood 2 Biotechnology 2 Chemistry and chemical engineering4 Energy 4 Environmental sciences and industries1 Fundamental physics and mathematics2 Governance, culture, education and the economy3 Health and wellbeing 4 ICT and computer science 3 Mechanical engineering and heavy machinery4 Nanotechnology and materials 1 Optics and photonics

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[]

on current policies, Chinese technology may represent the lowest-cost route to achieving some of these targets. Owing to a fast pace of innovation, low manufacturing costs and state subsidies four times higher than in other major econo - miesiv, the country is now dominating global exports of clean technologies. Significant overcapacity is expected: by 2030 at the latest, China’s annual manufacturing capacity for solar photovoltaic (PV) is expected to be double the level of global demand, and for battery cells it is expected to at least cover the level of global demand. Production of EVs is expanding at a similar pace. The EU is already seeing a sharp deterioration in its trade balance with China, reflecting in particular imports of EVs, batteries and solar PV products [see Figure 3] . While rising bankruptcies in China suggest that the economy is entering a phase of industrial consolidation, overcapacities are likely to persist, especially given ongoing weaknesses in household consumption and high saving rates. Moreover, in response to perceived unfair competition, an increasing number of countries are raising tariff and non-tariff barriers against China, which will re-direct Chinese overcapacity towards the EU market. In May, the US announced significant hikes in tariffs against a range of products. 40THE FUTURE OF EUROPEAN COMPETITIVENESS — PART A | CHAPTER 3 FIGURE 3 EU trade balance by partner country EUR billion Source: Eurostat, 2024. Europe must confront some fundamental choices about how to pursue its decarbonisation path while preserving the competitive position of its industry . Black-and-white solutions are unlikely to be successful in the European context. Emulating the US approach of systematically shutting out Chinese technology would likely set back the energy transition and therefore impose higher costs on the EU economy. It would also be more costly for Europe to trigger reciprocal tariffs: more than a third of the EU’s manufacturing GDP is absorbed outside the EU, compared with only around a fifth for the USv. However, a laissez-faire approach is also unlikely to succeed in Europe given the threat it could pose to employment, productivity and economic security. According to ECB simulations, if the Chinese EV industry were to follow a similar trajectory of subsidies to that applied in the solar PV industry, EU domestic production of EVs would decline by 70% and EU producers’ global market share would fall by 30 percentage pointsvi. The automotive industry alone employs, directly and indirectly,

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7 9 5 11 9 4 10.1 Processing/preserving of meat X X X X X X 10.2 Processing/preserving of fish, etc. X X X 10.3 Processing/preserving of fruit, vegetables X X X X 10.4 Vegetable and animal oils and fats X X X X X X 10.5 Dairy products X X X 10.6Grain mill products, starches and starch products X X X X X X X X X X 10.7 Other food products X X X 10.8 Prepared animal feeds X X X X 11 Beverages X X X X X X X X X X X X 12 Tobacco products X X X X X X 13 Manufacture of textiles X X X X X X X 14 Manufacture of wearing apparel X X X X X X X 15 Manufacture of leather and related products X X X X X X X 16Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials X X X X X X X 17 Manufacture of paper and paper products X X X X X X 18.1Printing and service activities related to printing X X X X X X 18.2 Reproduction of recorded media 19Manufacture of coke and refined petroleum products X X X X 20Manufacture of chemicals and chemical products X X X X X X X X X X 21 Pharmaceuticals, medicinal chemicals, etc. X X X X X X Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation299 300 Annexes ARMENIA AZERBAIJAN GEORGIA MOLDOVA UKRAINEEmploy- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover Employ- ment Turnover Employ- ment & turnover NACE Industry name Current Emerging Current Emerging Current Emerging Current Emerging Current Emerging 5 5 3 10 8 5 6 5 2 6 11 4 5 8 4 11 5 4 7 10 5 1 7 1 7 9 5 11 9 4 22 Manufacture of rubber and plastic products X X X X X 23Manufacture of other non-metallic mineral products X X X X 24 Manufacture of basic metals X

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general revenues and expenditures | | Revenues | Expenditures | |----------|--------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | Direct | Mining revenues derived from the sale of minerals mined from a mining project. | Prospecting, exploration, and development expenditures are clearly attributed to a specific mining project. For instance, the depreciation associated with a drill rig used only for a specific mining project. | | Indirect | Income from the sale of a drilling rig previously used for more than one mine. | Continuing the drilling example, assuming that the drilling rig is used during the taxable year for two or more licence areas, the costs will need to be allocated to more than one licence area where it was actually used. | | General | Income earned from interest on current account bank deposit. | Management and administration expenditures, human resource expenditures, expenses related to the operation of internal information technology systems, overhead costs. | Source: Author's elaboration. ## 5.2.2 A Method for Apportioning All Indirect and General Expenditures and Revenues Direct revenues and expenditures should be attributed in full to the specific licence area or business activities to which they relate. Indirect and general revenues and expenditures, however, are not directly attributable to a specific licence area or may relate to different business activities carried out by the same enterprise, which creates apportionment challenges. For instance, it can be difficult to apportion - · revenues derived from ore from differing licence areas where these are mixed during the processing stage to produce one product, - · revenues from raw materials versus processed goods or revenues from mining versus manufacturing activities, - · expenditures related to staff involved in more than one licence area/ business activity, - · expenditures related to equipment used for different mines/business activities, and - · financing costs incurred while borrowing funds to expand different mining projects/business activities. ## 1.0 INTRODUCTION 2.0 THE FUNDAMENTALS OF RING-FENCING 3.0 THE BENEFITS AND RISKS OF RING-FENCING 4.0 DESIGNING RING-FENCING RULES 5.0 THE IMPLEMENTATION OF RING-FENCING RULES 6.0 CONCLUSION Different allocation methods are used to apportion general and indirect expenditures and revenues. Direct and indirect methods could be applied depending on the materiality of the revenues and expenditures. The significance and materiality of the relevant expenditure could be considered when setting up specific tracking or tracing requirements, rather than relying on simplification approaches based on a proxy allocation rule, such as the CapEx expenditure mentioned

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The report also indicates the evidence-informed areas for knowledge-based economic cooperation to support bilateral and region-wide initiatives. 2 Executive summary covery, resilience and reform: post 2020 Eastern Partnership priorities’4. The S3 Framework was developed at the request of EU Enlargement and Neighbourhood economies that voluntarily took on the development of Smart Specialisation Strategies in different administra- tive, institutional and political contexts. It oper- ationalises the guidance offered to EU Member States into a set of practical steps, but also adapts and adjusts the approach to suit non-EU countries. Starting from the first phase of 1 institution- al capacity building (Decision to start S3 Pro- cess) to the second 2 institutional capacity building (Analysis of the Strategic mandates), it continues with the mapping phases through steps 3diagnosis (Quantitative mapping) and 4 diagnosis (Qualitative mapping). The next steps include engaging in 5 stakeholder dialogue, developing the 6 institutional capacity for implementation and, finally, 7 drafting the strategy (see the figure below). This study aims to offer a solid basis for the Smart Specialisation process by offering an extensive quantitative analysis of national-level potential in the economy, innovation, science and technology based on available international data. This effort, amongst others, is part of the targeted support 4 SWD(2021) 186 final, 2.7.2021.EXECUTIVE SUMMARY Most Eastern Partnership countries have com- mitted to developing their Smart Specialisa- tion Strategies based on the Smart Specialisation Framework for EU Enlargement and Neighbour- hood Region (S3 Framework)2, developed by the JRC in cooperation with partner countries, inter- national experts and policy directorates of the European Commission. The application of this EU- made innovation policy concept will allow Eastern Partners to promote knowledge-based economic development and targeted research and innova- tion policies building on territorial specificities, unique potentials and emerging niches. This ef- fort has been recognised in the 2020 European Commission’s Joint Communication: ‘Eastern Partnership policy beyond 2020: Reinforcing Re- silience – an Eastern Partnership that delivers for all’3 and the Joint Staff Working Document ‘Re- 2 Matusiak, M., Kleibrink, A. (ed.), Supporting an Inno- vation Agenda for the Western Balkans – Tools and Methodologies, Publications Office of the European Un- ion, Luxembourg, 2018, ISBN 978-92-79-81870-7, doi:10.2760/48162, JRC111430. 3 https://eeas.europa.eu/sites/default/files/1_en_act_ part1_v6.pdf. INSTITUTIONAL CAPACITY FOR IMPLEMENTATIONFINAL S3 STRATEGYINSTITUTIONAL CAPACITY BUILDING (Decision to Start S3 Process)INSTITUTIONAL CAPACITY BUILDING (Analysis of Strategic Mandates)DIAGNOSIS (Quantitative mapping)DIAGNOSIS (Qualitative mapping) STAKEHOLDER DIALOGUE Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation3

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can also facilitate favorable capital market and invest - ment conditions and foster GDP growth.107 Finally, international cooperation can boost statistical inde-pendence and data transparency when adherence to standards of data quality and the independence of their producers is required for accession to interna-tional organizations or agreements. An example is Colombia’s successful bid to join the Organisation for Economic Co-operation and Development (OECD). 108 Civil society performs a vital function in demand- ing transparency and holding government account - able. Citizen-generated data can be used to challenge official statistics when their accuracy or impartiality are in question. A free and empowered press is a Figure 2.9 Greater NSO independence and freedom of the press are positively correlated with better statistical performance Sources: NSO independence score: Mo Ibrahim Foundation, Ibrahim Index of African Governance (database), http://mo.ibrahim.foundation/iiag/; World Press Freedom Index: Reporters Without Borders, 2020 World Press Freedom Index (database), https://rsf.org/en/ranking_table. Data at http://bit.do/WDR2021-Fig-2_9. Note: The x’s represent countries. Panel a shows only African countries, and panel b shows all countries with data available. The NSO independence score ranges from 0 to 100. The World Press Freedom Index ranges from 100 to 0—lower values imply greater press freedom.

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