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

text stringlengths 29 12.2k	tokens listlengths 5 1.47k	label listlengths 0 64
Vam k D. Volkan ı is an Emeritus Professor of Psychiatry at the University of Virginia and an Emeritus Training and Supervising Analyst at the Washington-Baltimore Psychoanalytic Institute. He is the Emeritus President of the International Dialogue Initiative. healing such traumas. This chapter explores psychopolitical concepts that have proven helpful in attempts to enable collective healing. ## Types of Massive Traumas Massive traumas vary in type. Some spring from natural causes, such as earthquakes, tropical storms, tsunamis, floods, forest fires or volcanic eruptions. Some are due to man-made but accidental disasters, such as the 1986 Chernobyl accident that contaminated the atmosphere with tons of radioactive dust. Society may also respond with trauma to the murder or sudden death of a person who functioned as a symbol that unconsciously stood for a parent figure and/or was perceived as a representative of a large-group identity. Assassinations of John F. Kennedy¹ and Martin Luther King, Jr. in the United States, Yitzhak Rabin in Israel,² Prime Minister Olof Palme in Sweden, the National Democratic Party leader Giorgi Chanturia in the Republic of Georgia, former Prime Minister Rafik Hariri in Lebanon, or the deaths of the American astronauts, especially teacher Christa McAuliffe, in the 1986 space shuttle Challenger explosion,³ and the death of Diana, Princess of Wales, in a car accident in 1997, ⁴ all led to responses that were experienced as shared trauma. Other massive traumas such as terrorist attacks, wars and even genocide can be ascribed to the deliberate actions of an enemy, an outsider. They might spring from a territorial conflict between two neighbouring countries that results in mass atrocities, such as the territorial conflict between India and Pakistan in Kashmir that has led to the disappearance of more than 8,000 persons since 1989, and thousands of extra-judicial killings, torture and rape, with Kashmiri Muslims fearing that they will lose their culture. Such deliberate catastrophes can also occur within a national boundary when there is chronic mistreatment or oppression of a smaller racial or ethnic group by the dominant Other. One of the best-known examples of this is the history of slavery in the United States and the discrimination towards black Americans 1 Wolfenstein & Kliman (Eds.) (1965). Children and the death of a president: Multi-disciplinary studies. 2 Erlich (1998). Adolescents ' reactions to Rabin s assassination: A case of patricide? ' Raviv et al. (2000). Young Israelis ' reactions to national	[ "Vam", "k", "D.", "Volkan", "ı", "is", "an", "Emeritus", "Professor", "of", "Psychiatry", "at", "the", "University", "of", "Virginia", "and", "an", "Emeritus", "Training", "and", "Supervising", "Analyst", "at", "the", "Washington", "-", "Baltimore", "Psychoanalytic", "Institute", ".", "He", "is", "the", "Emeritus", "President", "of", "the", "International", "Dialogue", "Initiative", ".", "\n\n", "healing", "such", "traumas", ".", "This", "chapter", "explores", "psychopolitical", "concepts", "that", "have", "proven", "helpful", "in", "attempts", "to", "enable", "collective", "healing", ".", "\n\n", "#", "#", "Types", "of", "Massive", "Traumas", "\n\n", "Massive", "traumas", "vary", "in", "type", ".", "Some", "spring", "from", "natural", "causes", ",", "such", "as", "earthquakes", ",", "tropical", "storms", ",", "tsunamis", ",", "floods", ",", "forest", "fires", "or", "volcanic", "eruptions", ".", "Some", "are", "due", "to", "man", "-", "made", "but", "accidental", "disasters", ",", "such", "as", "the", "1986", "Chernobyl", "accident", "that", "contaminated", "the", "atmosphere", "with", "tons", "of", "radioactive", "dust", ".", "Society", "may", "also", "respond", "with", "trauma", "to", "the", "murder", "or", "sudden", "death", "of", "a", "person", "who", "functioned", "as", "a", "symbol", "that", "unconsciously", "stood", "for", "a", "parent", "figure", "and/or", "was", "perceived", "as", "a", "representative", "of", "a", "large", "-", "group", "identity", ".", "Assassinations", "of", "John", "F.", "Kennedy¹", "and", "Martin", "Luther", "King", ",", "Jr.", "in", "the", "United", "States", ",", "Yitzhak", "Rabin", "in", "Israel,²", "Prime", "Minister", "Olof", "Palme", "in", "Sweden", ",", "the", "National", "Democratic", "Party", "leader", "Giorgi", "Chanturia", "in", "the", "Republic", "of", "Georgia", ",", "former", "Prime", "Minister", "Rafik", "Hariri", "in", "Lebanon", ",", "or", "the", "deaths", "of", "the", "American", "astronauts", ",", "especially", "teacher", "Christa", "McAuliffe", ",", "in", "the", "1986", "space", "shuttle", "Challenger", "explosion,³", "and", "the", "death", "of", "Diana", ",", "Princess", "of", "Wales", ",", "in", "a", "car", "accident", "in", "1997", ",", "⁴", "all", "led", "to", "responses", "that", "were", "experienced", "as", "shared", "trauma", ".", "\n\n", "Other", "massive", "traumas", "such", "as", "terrorist", "attacks", ",", "wars", "and", "even", "genocide", "can", "be", "ascribed", "to", "the", "deliberate", "actions", "of", "an", "enemy", ",", "an", "outsider", ".", "They", "might", "spring", "from", "a", "territorial", "conflict", "between", "two", "neighbouring", "countries", "that", "results", "in", "mass", "atrocities", ",", "such", "as", "the", "territorial", "conflict", "between", "India", "and", "Pakistan", "in", "Kashmir", "that", "has", "led", "to", "the", "disappearance", "of", "more", "than", "8,000", "persons", "since", "1989", ",", "and", "thousands", "of", "extra", "-", "judicial", "killings", ",", "torture", "and", "rape", ",", "with", "Kashmiri", "Muslims", "fearing", "that", "they", "will", "lose", "their", "culture", ".", "\n\n", "Such", "deliberate", "catastrophes", "can", "also", "occur", "within", "a", "national", "boundary", "when", "there", "is", "chronic", "mistreatment", "or", "oppression", "of", "a", "smaller", "racial", "or", "ethnic", "group", "by", "the", "dominant", "Other", ".", "One", "of", "the", "best", "-", "known", "examples", "of", "this", "is", "the", "history", "of", "slavery", "in", "the", "United", "States", "and", "the", "discrimination", "towards", "black", "Americans", "\n\n", "1", "Wolfenstein", "&", "amp", ";", "Kliman", "(", "Eds", ".", ")", "(", "1965", ")", ".", "Children", "and", "the", "death", "of", "a", "president", ":", "Multi", "-", "disciplinary", "studies", ".", "\n\n", "2", "Erlich", "(", "1998", ")", ".", "Adolescents", "'", "reactions", "to", "Rabin", "s", "assassination", ":", "A", "case", "of", "patricide", "?", "'", "Raviv", "et", "al", ".", "(", "2000", ")", ".", "Young", "Israelis", "'", "reactions", "to", "national" ]	[ { "end": 2331, "label": "CITATION_ID", "start": 2330 }, { "end": 2441, "label": "CITATION_ID", "start": 2440 }, { "end": 2455, "label": "CITATION_REF", "start": 2442 }, { "end": 2448, "label": "AUTHOR", "start": 2442 }, { "end": 2454, "label": "YEAR", "start": 2450 }, { "end": 2370, "label": "CITATION_REF", "start": 2332 }, { "end": 2363, "label": "AUTHOR", "start": 2332 }, { "end": 2369, "label": "YEAR", "start": 2365 }, { "end": 987, "label": "CITATION_REF", "start": 986 }, { "end": 1430, "label": "CITATION_REF", "start": 1429 }, { "end": 1358, "label": "CITATION_REF", "start": 1357 }, { "end": 1063, "label": "CITATION_REF", "start": 1062 } ]
, , functions/ , , , , , , , , , conveyors , , and/or any other device or system discussed herein. The includes one or more processors (also referred to as “ ”). The includes circuitry capable of sequentially and/or automatically carrying out a sequence of arithmetic or logical operations, and recording, storing, and/or transferring digital data. Additionally or alternatively, the includes any device capable of executing or otherwise operating computer-executable instructions, such as program code, software modules, and/or functional processes. The includes various hardware elements or components such as, for example, a set of processor cores and one or more of on-chip or on-die memory or registers, cache and/or scratchpad memory, low drop-out voltage regulators (LDOs), interrupt controllers, serial interfaces such as SPI, I2C or universal programmable serial interface circuit, real time clock (RTC), timer-counters including interval and watchdog timers, general purpose I/O, memory card controllers such as secure digital/multi-media card (SD/MMC) or similar, interfaces, mobile industry processor interface (MIPI) interfaces and Joint Test Access Group (JTAG) test access ports. Some of these components, such as the on-chip or on-die memory or registers, cache and/or scratchpad memory, may be implemented using the same or similar devices as the discussed infra. The is also coupled with and , and is configured to execute instructions stored in the memory/storage to enable various apps, OSs, or other software elements to run on the . In particular, the is configured to operate app software (e.g., , , ) to provide one or more services to a user of the and/or user(s) of remote systems/devices. As examples, the can be embodied as, or otherwise include one or multiple central processing units (CPUs), application processors, graphics processing units (GPUs), RISC processors, Acorn RISC Machine (ARM) processors, complex instruction set computer (CISC) processors, DSPs, FPGAs, programmable logic devices (PLDs), ASICs, baseband processors, radio-frequency integrated circuits (RFICs), microprocessors or controllers, multi-core processors, multithreaded processors, ultra-low voltage processors, embedded processors, a specialized x-processing units (xPUs) or a data processing unit (DPUs) (e.g., Infrastructure Processing Unit (IPU), network processing unit (NPU), and the like), and/or any other processing devices or elements, or any combination thereof. In some implementations, the is embodied as one or more special-purpose processor(s)/controller(s) configured (or configurable) to operate according to the various implementations and other aspects discussed herein. Additionally or alternatively, the includes one or more hardware accelerators (e.g., same or similar to	[ ",", ",", "functions/", ",", ",", ",", ",", ",", ",", " ", ",", ",", ",", "conveyors", ",", ",", "and/or", "any", "other", "device", "or", "system", "discussed", "herein", ".", "\n\n", "The", " ", "includes", "one", "or", "more", "processors", " ", "(", "also", "referred", "to", "as", "“", "”", ")", ".", "The", " ", "includes", "circuitry", "capable", "of", "sequentially", "and/or", "automatically", "carrying", "out", "a", "sequence", "of", "arithmetic", "or", "logical", "operations", ",", "and", "recording", ",", "storing", ",", "and/or", "transferring", "digital", "data", ".", "Additionally", "or", "alternatively", ",", "the", " ", "includes", "any", "device", "capable", "of", "executing", "or", "otherwise", "operating", "computer", "-", "executable", "instructions", ",", "such", "as", "program", "code", ",", "software", "modules", ",", "and/or", "functional", "processes", ".", "The", " ", "includes", "various", "hardware", "elements", "or", "components", "such", "as", ",", "for", "example", ",", "a", "set", "of", "processor", "cores", "and", "one", "or", "more", "of", "on", "-", "chip", "or", "on", "-", "die", "memory", "or", "registers", ",", "cache", "and/or", "scratchpad", "memory", ",", "low", "drop", "-", "out", "voltage", "regulators", "(", "LDOs", ")", ",", "interrupt", "controllers", ",", "serial", "interfaces", "such", "as", "SPI", ",", "I2C", "or", "universal", "programmable", "serial", "interface", "circuit", ",", "real", "time", "clock", "(", "RTC", ")", ",", "timer", "-", "counters", "including", "interval", "and", "watchdog", "timers", ",", "general", "purpose", "I", "/", "O", ",", "memory", "card", "controllers", "such", "as", "secure", "digital", "/", "multi", "-", "media", "card", "(", "SD", "/", "MMC", ")", "or", "similar", ",", "interfaces", ",", "mobile", "industry", "processor", "interface", "(", "MIPI", ")", "interfaces", "and", "Joint", "Test", "Access", "Group", "(", "JTAG", ")", "test", "access", "ports", ".", "Some", "of", "these", "components", ",", "such", "as", "the", "on", "-", "chip", "or", "on", "-", "die", "memory", "or", "registers", ",", "cache", "and/or", "scratchpad", "memory", ",", "may", "be", "implemented", "using", "the", "same", "or", "similar", "devices", "as", "the", " ", "discussed", "infra", ".", "The", " ", "is", "also", "coupled", "with", " ", "and", " ", ",", "and", "is", "configured", "to", "execute", "instructions", "stored", "in", "the", "memory", "/", "storage", "to", "enable", "various", "apps", ",", "OSs", ",", "or", "other", "software", "elements", "to", "run", "on", "the", " ", ".", "In", "particular", ",", "the", " ", "is", "configured", "to", "operate", "app", "software", "(", "e.g.", ",", " ", ",", " ", ",", " ", ")", "to", "provide", "one", "or", "more", "services", "to", "a", "user", "of", "the", " ", "and/or", "user(s", ")", "of", "remote", "systems", "/", "devices", ".", "\n\n", "As", "examples", ",", "the", " ", "can", "be", "embodied", "as", ",", "or", "otherwise", "include", "one", "or", "multiple", "central", "processing", "units", "(", "CPUs", ")", ",", "application", "processors", ",", "graphics", "processing", "units", "(", "GPUs", ")", ",", "RISC", "processors", ",", "Acorn", "RISC", "Machine", "(", "ARM", ")", "processors", ",", "complex", "instruction", "set", "computer", "(", "CISC", ")", "processors", ",", "DSPs", ",", "FPGAs", ",", "programmable", "logic", "devices", "(", "PLDs", ")", ",", "ASICs", ",", "baseband", "processors", ",", "radio", "-", "frequency", "integrated", "circuits", "(", "RFICs", ")", ",", "microprocessors", "or", "controllers", ",", "multi", "-", "core", "processors", ",", "multithreaded", "processors", ",", "ultra", "-", "low", "voltage", "processors", ",", "embedded", "processors", ",", "a", "specialized", "x", "-", "processing", "units", "(", "xPUs", ")", "or", "a", "data", "processing", "unit", "(", "DPUs", ")", "(", "e.g.", ",", "Infrastructure", "Processing", "Unit", "(", "IPU", ")", ",", "network", "processing", "unit", "(", "NPU", ")", ",", "and", "the", "like", ")", ",", "and/or", "any", "other", "processing", "devices", "or", "elements", ",", "or", "any", "combination", "thereof", ".", "In", "some", "implementations", ",", "the", " ", "is", "embodied", "as", "one", "or", "more", "special", "-", "purpose", "processor(s)/controller(s", ")", "configured", "(", "or", "configurable", ")", "to", "operate", "according", "to", "the", "various", "implementations", "and", "other", "aspects", "discussed", "herein", ".", "Additionally", "or", "alternatively", ",", "the", " ", "includes", "one", "or", "more", "hardware", "accelerators", "(", "e.g.", ",", "same", "or", "similar", "to" ]	[]
into a form that allows analysis. The statistical analysis allows us to understand the fine-grain choice structure of the individual characteristics by estimating the average marginal component effect. Through analysis, the relative statistical importance of each characteristic can be assessed by using the marginal effect of the attribute averaged over the joint distribution of the remaining attributes. This analysis will show the likelihood of how individual characteristics vary in importance in differ -ent informal settlements that have different levels of institutions in place. We pro -vide a greater understanding of the mechanisms at work in these broker and client choice relationships. We explore the emergence of brokers in different community types in Delhi, India, and how the broker builds a following from local residents. We seek to investigate the origins of hierarchy in clientelist spaces and study the processes through which informal leaders emerge within our different slum types. Now, let us look at each of the parts of the research in turn. First, we set out some of the discussions carried out with community members and brokers, allowing for Figure 4.2 Screenshot illustrating Qualtrics data collection software <!-- image --> voices from the grassroots to inform our research. Second, we describe how we set up the conjoint experiment. Third, these quantitative findings are presented to allow us to investigate the overarching themes of governance, politics and brokers in different slum types in Delhi. ## Voices from brokers and residents ## Capability When talking with the brokers, they expressed their desire to support their communities to gain popularity and a larger following. This support, they suggested, helps them climb the party ranks and enhances their value to their political party. As these neighbourhoods aren't electoral constituencies, the goal for brokers and political parties isn't to secure a majority but to enable as many resident votes as possible. Political parties in India are constantly seeking brokers who can deliver a significant voter base. Ambitious brokers aim to work in multiple neighbourhoods to maximise the number of voters they can influence for politicians. These brokers are often entrepreneurial, aspiring for political careers and promotions within the party by its leaders. Our data from the household survey shows that in each of our neighbourhoods, around 80% of residents say they voted in the last round of Delhi elections, both at the municipal and state levels. To do so, these residents must have a	[ "into", "a", "form", "that", "allows", "analysis", ".", "The", "statistical", "analysis", "allows", "us", "to", "understand", "the", "fine", "-", "grain", "choice", "structure", "of", "the", "individual", "characteristics", "by", "estimating", "the", "average", "marginal", " ", "component", " ", "effect", ".", " ", "Through", " ", "analysis", ",", " ", "the", " ", "relative", " ", "statistical", " ", "importance", " ", "of", "each", "characteristic", "can", "be", "assessed", "by", "using", "the", "marginal", "effect", "of", "the", "attribute", "averaged", "over", "the", "joint", "distribution", "of", "the", "remaining", "attributes", ".", "This", "analysis", "will", "show", "the", "likelihood", "of", "how", "individual", "characteristics", "vary", "in", "importance", "in", "differ", "-ent", "informal", "settlements", "that", "have", "different", "levels", "of", "institutions", "in", "place", ".", "We", "pro", "-vide", "a", "greater", "understanding", "of", "the", "mechanisms", "at", "work", "in", "these", "broker", "and", "client", "choice", "relationships", ".", "We", "explore", "the", "emergence", "of", "brokers", "in", "different", "community", "types", "in", "Delhi", ",", "India", ",", "and", "how", "the", "broker", "builds", "a", "following", "from", "local", "residents", ".", "We", "seek", "to", "investigate", "the", "origins", "of", "hierarchy", "in", "clientelist", "spaces", "and", "study", "the", "processes", "through", "which", "informal", "leaders", "emerge", "within", "our", "different", "slum", "types", ".", "Now", ",", "let", "us", "look", "at", "each", "of", "the", "parts", "of", "the", "research", "in", "turn", ".", "First", ",", "we", "set", "out", "some", "of", "the", "discussions", "carried", "out", "with", "community", "members", "and", "brokers", ",", "allowing", "for", "\n\n", "Figure", "4.2", "Screenshot", "illustrating", "Qualtrics", "data", "collection", "software", "\n\n", "<", "!", "--", "image", "--", ">", "\n\n", "voices", "from", "the", "grassroots", "to", "inform", "our", "research", ".", "Second", ",", "we", "describe", "how", "we", "set", "up", "the", "conjoint", "experiment", ".", "Third", ",", "these", "quantitative", "findings", "are", "presented", "to", "allow", "us", "to", "investigate", "the", "overarching", "themes", "of", "governance", ",", "politics", "and", "brokers", "in", "different", "slum", "types", "in", "Delhi", ".", "\n\n", "#", "#", "Voices", "from", "brokers", "and", "residents", "\n\n", "#", "#", "Capability", "\n\n", "When", "talking", "with", "the", "brokers", ",", "they", "expressed", "their", "desire", "to", "support", "their", "communities", "to", "gain", "popularity", "and", "a", "larger", "following", ".", "This", "support", ",", "they", "suggested", ",", "helps", "them", "climb", "the", "party", "ranks", "and", "enhances", "their", "value", "to", "their", "political", "party", ".", "As", "these", "neighbourhoods", "are", "n't", "electoral", "constituencies", ",", "the", "goal", "for", "brokers", "and", "political", "parties", "is", "n't", "to", "secure", "a", "majority", "but", "to", "enable", "as", "many", "resident", "votes", "as", "possible", ".", "Political", "parties", "in", "India", "are", "constantly", "seeking", "brokers", "who", "can", "deliver", "a", "significant", "voter", "base", ".", "Ambitious", "brokers", "aim", "to", "work", "in", "multiple", "neighbourhoods", "to", "maximise", "the", "number", "of", "voters", "they", "can", "influence", "for", "politicians", ".", "These", "brokers", "are", "often", "entrepreneurial", ",", "aspiring", "for", "political", "careers", "and", "promotions", "within", "the", "party", "by", "its", "leaders", ".", "Our", "data", "from", "the", "household", "survey", "shows", "that", "in", "each", "of", "our", "neighbourhoods", ",", "around", "80", "%", "of", "residents", "say", "they", "voted", "in", "the", "last", "round", "of", "Delhi", "elections", ",", "both", "at", "the", "municipal", "and", "state", "levels", ".", "To", "do", "so", ",", "these", "residents", "must", "have", "a" ]	[]
limited to cells that are hormone receptor positive, including most breast cancers. For these diseases, cell type -specific epigenetic clocks that mirror the cells at risk may be of use ( i.e., hormone -sensitive epithelial cells ), but these cells are lacking from blood or saliva samples. Conversely, cervical samples, routinely obtained from women aged 25 -64 years , are a source of hormone -sensitive epithelial and immune cells that could help to define epigenetic clocks indicating disease risk. Whether specific epigenetic clocks in cervical samples or a discordance in tick rates between general and cell type -specific epigenetic c locks could predict disease remained unknown. As part of Deliverable D8.2 we aimed to define: • an optimi sed “general epigenetic clock” – i.e., a list of CpGs – which collectively change with age in cervical samples . • cell type -specific epigenetic clocks for epithelial and immune cells within cervical samples. We analysed cervical liquid -based cytology samples and describe novel epigenetic clocks, the WID (W omen’s cancer risk IDentification clocks), which can indicate cancer risk and are altered upon hormone exposure . HEAP – D8.2 Ageing DNAme signatures page 6/15 Project No. 874662 HORIZON 2020 2 Methods 2.1 Samples Samples used for development of the general and cell type -specific clocks were collected as part of the FORECEE Programme, a European research project aimed at developing new strategies for female cancer prediction (Table 1) . Cervical screening was performed for women aged >18 years across five different European locations, including the Czech Republic, Germany, Italy, Norway, and the UK. FORECEE has received ethical approval from the UK Health Research Authority (R EC 14/LO/1633) and other contributing centres. Women with either breast, ovarian, or endometrial cancer as well as age -matched controls were included. Table 1. Samples in the FORECEE Study used for training and validation. SET TYPE NUMBER OF SAMPLES TRAINING Control 869 VALIDATION Control 225 Breast cancer 442 Ovarian cancer 289 Cervical smears were collected with a Rovers cervical brush and stored in PreservCyt solution (ThinPrep ). DNA was extracted from cervical samples on a Hamilton Star liquid handling platform using the Nucleo -Mag Blood 200 µL kit (Macherey Nagel, cat #744501.4) with prior modifications for optimal lysis of cervical cell pellets. Concentration and quality abso rbance ratios were measured using a Nanodrop- 8000 (Thermo Scientific) and extracted DNA was stored at -80°C until further analysis. 2.2	[ "limited", "to", "cells", "that", "are", "hormone", "receptor", "positive", ",", "including", "most", "breast", "cancers", ".", "For", "these", "diseases", ",", "cell", "type", "-specific", "\n", "epigenetic", "clocks", "that", "mirror", "the", "cells", "at", "risk", "may", "be", "of", "use", "(", "i.e.", ",", "\n", "hormone", "-sensitive", "epithelial", "cells", ")", ",", "but", "these", "cells", "are", "lacking", "from", "blood", "\n", "or", "saliva", "samples", ".", "Conversely", ",", "cervical", "samples", ",", "routinely", "obtained", "from", " \n", "women", "aged", "25", "-64", "years", ",", "are", "a", "source", " ", "of", "hormone", "-sensitive", "epithelial", "\n", "and", "immune", "cells", "that", "could", "help", "to", "define", "epigenetic", "clocks", "indicating", "disease", "risk", ".", " ", "Whether", "specific", "epigenetic", "clocks", "in", "cervical", "samples", "or", "a", "\n", "discordance", "in", "tick", "rates", "between", "general", "and", "cell", "type", "-specific", "\n", "epigenetic", "c", "locks", "could", "predict", "disease", "remained", "unknown", ".", " \n \n", "As", "part", "of", "Deliverable", "D8.2", "we", "aimed", "to", "define", ":", " \n", "•", "an", "optimi", "sed", "“", "general", "epigenetic", "clock", "”", "–", "i.e.", ",", "a", "list", "of", "CpGs", "–", " ", "which", "\n", "collectively", "change", "with", "age", "in", "cervical", "samples", ".", "\n", "•", "cell", "type", "-specific", "epigenetic", "clocks", "for", " ", "epithelial", "and", "immune", "cells", "\n", "within", "cervical", "samples", ".", " \n \n", "We", "analysed", "cervical", "liquid", "-based", "cytology", "samples", "and", "describe", "novel", "\n", "epigenetic", "clocks", ",", "the", "WID", "(", "W", "omen", "’s", "cancer", "risk", "IDentification", "clocks", ")", ",", " \n", "which", "can", "indicate", "cancer", "risk", " ", "and", "are", "altered", "upon", "hormone", " ", "exposure", ".", "\n \n \n \n \n", "HEAP", " ", "–", "D8.2", "Ageing", "DNAme", "signatures", " ", "page", "6/15", "\n \n", "Project", "No", ".", "874662", " \n \n \n", "HORIZON", "2020", " \n", "2", "Methods", " \n", "2.1", "Samples", " \n", "Samples", "used", "for", "development", "of", "the", "general", "and", "cell", "type", "-specific", "clocks", "\n", "were", "collected", "as", "part", "of", "the", "FORECEE", "Programme", ",", "a", "European", "research", "\n", "project", "aimed", "at", "developing", "new", "strategies", "for", "female", "cancer", "prediction", " \n", "(", "Table", "1", ")", ".", "Cervical", "screening", "was", "performed", "for", "women", "aged", ">", "18", "years", "\n", "across", "five", "different", "European", "locations", ",", "including", "the", "Czech", "Republic", ",", "\n", "Germany", ",", "Italy", ",", "Norway", ",", "and", "the", "UK", ".", "FORECEE", "has", "received", "ethical", "\n", "approval", "from", "the", "UK", "Health", "Research", "Authority", "(", "R", "EC", "14", "/", "LO/1633", ")", "and", "\n", "other", "contributing", "centres", ".", "Women", "with", "either", "breast", ",", "ovarian", ",", "or", "endometrial", "cancer", "as", "well", "as", "age", "-matched", "controls", "were", "included", ".", " \n \n", "Table", "1", ".", "Samples", "in", "the", "FORECEE", "Study", "used", "for", "training", "and", "validation", ".", " \n \n", "SET", "TYPE", " ", "NUMBER", "OF", "SAMPLES", " \n", "TRAINING", " ", "Control", " ", "869", "\n", "VALIDATION", " ", "Control", " ", "225", " \n", "Breast", "cancer", " ", "442", " \n", "Ovarian", "cancer", " ", "289", "\n ", "Cervical", "smears", "were", "collected", "with", "a", "Rovers", "cervical", "brush", "and", "stored", "in", "\n", "PreservCyt", "solution", "(", "ThinPrep", ")", ".", "DNA", "was", "extracted", "from", "cervical", "samples", "\n", "on", "a", "Hamilton", "Star", "liquid", "handling", "platform", "using", "the", "Nucleo", "-Mag", "Blood", "200", "\n", "µL", "kit", "(", "Macherey", "Nagel", ",", "cat", "#", "744501.4", ")", "with", "prior", "modifications", "for", "optimal", "\n", "lysis", "of", "cervical", "cell", "pellets", ".", "Concentration", "and", "quality", "abso", "rbance", "ratios", "\n", "were", "measured", "using", "a", "Nanodrop-", "8000", "(", "Thermo", "Scientific", ")", "and", "extracted", "\n", "DNA", "was", "stored", "at", "-80", "°", "C", "until", "further", "analysis", ".", " \n", "2.2" ]	[]
referred to as consolidation of the tax base of a taxpayer. In mining, a company may carry on multiple projects and/or undertake several activities along the mining value chain or be involved in non-mining activities, such as transport, manufacturing, or even sophisticated financial investment activities. In these cases, where consolidation rules are in place, the company may use costs incurred in one project (e.g., during exploration) and/or activity (e.g., when undertaking manufacturing activities) to offset profits earned in another. Such consolidation is fiscally attractive for mining taxpayers because it allows tax savings resulting from the deduction of costs related to one project/activity against the income generated by another project/activity. These tax savings reduce the after-tax costs of investments. They can, in turn, encourage mining companies to invest in exploration and continue other mining and non-mining activities because they can recover their costs sooner, which may improve their cash flows. For governments, attracting investments is an important policy objective, and these considerations related to consolidation play an important role in the decisions of investors. However, such consolidation can postpone government tax revenues. By offsetting costs or losses against the income of producing mines, companies can defer the payment of CITs—sometimes for very long periods or indefinitely. Consolidation can also result in revenue loss if exploration projects are unsuccessful or when a mining investor undertakes non-mining activities, such as speculative and high-risk financial investment activities. Furthermore, where mining investors engage in base erosion and profit shifting (BEPS) practices, consolidation might accelerate those effects and may result in permanent losses of tax revenues for the host jurisdiction. Balancing these potentially conflicting objectives through careful tax policy design is essential to ensure that investors do not lose the deductibility of legitimate expenses incurred, and governments ensure the collection of economic rents.1 1 Economic or resource rent has been defined as “the excess of the total project lifetime value arising from the exploitation of a deposit over the sum of all costs of exploitation including the compensation to all factors of production.” See Land (2008, p. 5).Ring-Fencing Mining Income: A toolkit for tax administrators and policy-makers 3 Ring-Fencing Mining Income: A toolkit for tax administrators and policy-makers1.0 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 In developing countries, a delay in tax payments or	[ "referred", "to", "as", "consolidation", "of", "the", "tax", "base", "of", "a", "taxpayer", ".", "\n", "In", "mining", ",", "a", "company", "may", "carry", "on", "multiple", "projects", "and/or", "undertake", "\n", "several", "activities", "along", "the", "mining", "value", "chain", "or", "be", "involved", "in", "non", "-", "mining", "\n", "activities", ",", "such", "as", "transport", ",", "manufacturing", ",", "or", "even", "sophisticated", "financial", "\n", "investment", "activities", ".", "In", "these", "cases", ",", "where", "consolidation", "rules", "are", "in", "place", ",", "\n", "the", "company", "may", "use", "costs", "incurred", "in", "one", "project", "(", "e.g.", ",", "during", "exploration", ")", "\n", "and/or", "activity", "(", "e.g.", ",", "when", "undertaking", "manufacturing", "activities", ")", "to", "offset", "\n", "profits", "earned", "in", "another", ".", "\n", "Such", "consolidation", "is", "fiscally", "attractive", "for", "mining", "taxpayers", "because", "it", "\n", "allows", "tax", "savings", "resulting", "from", "the", "deduction", "of", "costs", "related", "to", "one", "\n", "project", "/", "activity", "against", "the", "income", "generated", "by", "another", "project", "/", "activity", ".", "\n", "These", "tax", "savings", "reduce", "the", "after", "-", "tax", "costs", "of", "investments", ".", "They", "can", ",", "in", "\n", "turn", ",", "encourage", "mining", "companies", "to", "invest", "in", "exploration", "and", "continue", "\n", "other", "mining", "and", "non", "-", "mining", "activities", "because", "they", "can", "recover", "their", "costs", "\n", "sooner", ",", "which", "may", "improve", "their", "cash", "flows", ".", "\n", "For", "governments", ",", "attracting", "investments", "is", "an", "important", "policy", "objective", ",", "\n", "and", "these", "considerations", "related", "to", "consolidation", "play", "an", "important", "role", "\n", "in", "the", "decisions", "of", "investors", ".", "However", ",", "such", "consolidation", "can", "postpone", "\n", "government", "tax", "revenues", ".", "By", "offsetting", "costs", "or", "losses", "against", "the", "income", "of", "\n", "producing", "mines", ",", "companies", "can", "defer", "the", "payment", "of", "CITs", "—", "sometimes", "for", "\n", "very", "long", "periods", "or", "indefinitely", ".", "Consolidation", "can", "also", "result", "in", "revenue", "loss", "\n", "if", "exploration", "projects", "are", "unsuccessful", "or", "when", "a", "mining", "investor", "undertakes", "\n", "non", "-", "mining", "activities", ",", "such", "as", "speculative", "and", "high", "-", "risk", "financial", "investment", "\n", "activities", ".", "Furthermore", ",", "where", "mining", "investors", "engage", "in", "base", "erosion", "and", "\n", "profit", "shifting", "(", "BEPS", ")", "practices", ",", "consolidation", "might", "accelerate", "those", "effects", "\n", "and", "may", "result", "in", "permanent", "losses", "of", "tax", "revenues", "for", "the", "host", "jurisdiction", ".", "\n", "Balancing", "these", "potentially", "conflicting", "objectives", "through", "careful", "tax", "policy", "\n", "design", "is", "essential", "to", "ensure", "that", "investors", "do", "not", "lose", "the", "deductibility", "of", "\n", "legitimate", "expenses", "incurred", ",", "and", "governments", "ensure", "the", "collection", " \n", "of", "economic", "rents.1", "\n", "1", "Economic", "or", "resource", "rent", "has", "been", "defined", "as", "“", "the", "excess", "of", "the", "total", "project", "\n", "lifetime", "value", "arising", "from", "the", "exploitation", "of", "a", "deposit", "over", "the", "sum", "of", "all", "costs", " \n", "of", "exploitation", "including", "the", "compensation", "to", "all", "factors", "of", "production", ".", "”", "See", "Land", "\n", "(", "2008", ",", "p.", "5).Ring", "-", "Fencing", "Mining", "Income", ":", "A", "toolkit", "for", "tax", "administrators", "and", "policy", "-", "makers", "\n", "3", "\n", "Ring", "-", "Fencing", "Mining", "Income", ":", "A", "toolkit", "for", "tax", "administrators", "and", "policy", "-", "makers1.0", "INTRODUCTION", "\n", "2.0", "THE", "\n", "FUNDAMENTALS", " \n", "OF", "RING", "-FENCING", "\n", "3.0", "THE", "BENEFITS", "\n", "AND", "RISKS", "OF", " \n", "RING", "-FENCING", "\n", "4.0", "DESIGNING", "\n", "RING", "-FENCING", "\n", "RULES", "\n", "5.0", "THE", "\n", "IMPLEMENTATION", "\n", "OF", "RING", "-FENCING", "\n", "RULES", "\n", "6.0", "CONCLUSION", "In", "developing", "countries", ",", "a", "delay", "in", "tax", "payments", "or" ]	[ { "end": 2137, "label": "CITATION_REF", "start": 2136 }, { "end": 2402, "label": "CITATION_REF", "start": 2384 }, { "end": 2388, "label": "AUTHOR", "start": 2384 }, { "end": 2395, "label": "YEAR", "start": 2391 } ]
blocks that were not fully covered by water and do not intersect with GISCO country data for 2020 and 2024 at 1:1 ,000,000 or 1:100 ,000. The colour indicates if one or a combination of several GISCO datasets missed a block. Th e size of the blocks is exaggerated to make them visible at global level. The number after the hyphen indicates the amount of unique processing blocks for this category ( dataset combination ); in total there are 5 ,194 unique blocks identified by any of the three datasets. The high number of only GISCO 2020 at 1:1,000,000 scale (green) confirms the assumption that improved in the 2024 data release; high number of GISCO at 1:1 ,000,000 compared to data or combinations that include 1:100 ,000 indicates the before mentioned relationship to mapping scale. 21 Figure 7. LCFM processing blocks that were not fully covered by water and do not intersect with GISCO country data for 2020 or 2024 at 1:1,000,000 or 1:100,000. Source: JRC based on data from VITO – Flemish Institute for Technological Research (LCFM processing blocks) and Eurostat /GISCO (country boundaries) . Note: The size of the blocks is exaggerated to make them visible at global lev el. The number after the hyphen in the legend indicates the amount of unique processing blocks for this category (dataset combination) . Figure 7 indicates that all identified blocks are located along continental outlines either coastlines or shorelines for interior water bodies like the Caspian Sea that GISCO does not allocate to a specific country. The figure also indicates some geographic patterns with regards to individual GISCO datasets. — Africa, which the exception is the Red Sea, depicts only a few lo cations with identified blocks. This result is likely linked to 1) steeper coasts with little ambiguity to identify the water/land boundary 2) a relatively low complexity of the coastline i.e. elongated shorelines with few bends and small radius, and 3) fe w small coastal islands. — Asia indicates blocks predominantly identified for GISCO 2020 at 1:1 ,000,000 (green). This suggests that the country boundaries improved in terms of completeness for GISCO 2024. — Complex shorelines show a dominance of blocks for GIS CO data at 1:1 ,000,000 for both 2020 and 2024 (purple). Shorelines are characterized by a high fragmentation and low compactness. Reasons for shoreline complexity may be due to former presence of fjords in formerly	[ "blocks", "that", "were", "not", "fully", "covered", "by", "water", "and", "do", "not", "intersect", "\n", "with", "GISCO", "country", "data", "for", "2020", "and", "2024", "at", "1:1", ",", "000,000", " ", "or", "1:100", ",", "000", ".", "The", "colour", "indicates", "if", "\n", "one", "or", "a", "combination", "of", "several", "GISCO", "datasets", "missed", "a", "block", ".", "Th", "e", "size", "of", "the", "blocks", "is", "\n", "exaggerated", "to", "make", "them", "visible", "at", "global", "level", ".", "The", "number", "after", "the", "hyphen", "indicates", "the", "\n", "amount", "of", "unique", "processing", "blocks", "for", "this", "category", "(", "dataset", "combination", ")", ";", "in", "total", "there", "are", "5", ",", "194", "\n", "unique", "blocks", "identified", "by", "any", "of", "the", "three", "datasets", ".", "The", "high", "number", "of", "only", "GISCO", "2020", "at", "\n", "1:1,000,000", "scale", "(", "green", ")", "confirms", "the", "assumption", "that", "improved", "in", "the", "2024", "data", "release", ";", "high", "\n", "number", "of", "GISCO", "at", "1:1", ",", "000,000", " ", "compared", "to", "data", "or", "combinations", "that", "include", "1:100", ",", "000", "\n", "indicates", "the", "before", "mentioned", "relationship", "to", "mapping", "scale", ".", " \n\n", "21", "Figure", "7", ".", "LCFM", "processing", "blocks", "that", "were", "not", "fully", "covered", "by", "water", "and", "do", "not", "intersect", "with", "GISCO", "\n", "country", "data", "for", "2020", "or", "2024", "at", "1:1,000,000", "or", "1:100,000", ".", " \n", "Source", ":", "JRC", "based", "on", "data", "from", "VITO", "–", "Flemish", "Institute", "for", "Technological", "Research", "(", "LCFM", "processing", "blocks", ")", "and", "\n", "Eurostat", "/GISCO", " ", "(", "country", "boundaries", ")", ".", "Note", ":", "The", "size", "of", "the", "blocks", "is", "exaggerated", "to", "make", "them", "visible", "at", "global", "lev", "el", ".", "The", "\n", "number", "after", "the", "hyphen", "in", "the", "legend", "indicates", "the", "amount", "of", "unique", "processing", "blocks", "for", "this", "category", "(", "dataset", "\n", "combination", ")", ".", "\n", "Figure", "7", "indicates", " ", "that", "all", "identified", "blocks", "are", "located", "along", "continental", "outlines", "either", "coastlines", "\n", "or", "shorelines", "for", " ", "interior", "water", "bodies", "like", "the", "Caspian", "Sea", "that", "GISCO", "does", "not", "allocate", "to", "a", "\n", "specific", "country", ".", "The", "figure", "also", "indicates", "some", "geographic", "patterns", "with", "regards", "to", "individual", "\n", "GISCO", "datasets", ".", " \n", "—", "Africa", ",", "which", "the", "exception", "is", "the", "Red", "Sea", ",", "depicts", "only", "a", "few", "lo", "cations", "with", "identified", "blocks", ".", "\n", "This", "result", "is", "likely", "linked", "to", "1", ")", "steeper", "coasts", "with", "little", "ambiguity", "to", "identify", "the", "water", "/", "land", "\n", "boundary", "2", ")", "a", "relatively", "low", "complexity", "of", "the", "coastline", "i.e.", "elongated", "shorelines", "with", "few", "bends", "\n", "and", "small", "radius", ",", "and", "3", ")", "fe", "w", "small", "coastal", "islands", ".", " \n", "—", "Asia", "indicates", "blocks", "predominantly", "identified", "for", "GISCO", "2020", "at", "1:1", ",", "000,000", " ", "(", "green", ")", ".", "This", "\n", "suggests", "that", "the", "country", "boundaries", "improved", "in", "terms", "of", "completeness", "for", "GISCO", "2024", ".", " \n", "—", "Complex", "shorelines", "show", "a", "dominance", "of", "blocks", "for", "GIS", "CO", "data", "at", "1:1", ",", "000,000", " ", "for", "both", "2020", "\n", "and", "2024", "(", "purple", ")", ".", "Shorelines", "are", "characterized", "by", "a", "high", "fragmentation", "and", "low", "compactness", ".", "\n", "Reasons", "for", "shoreline", "complexity", "may", "be", "due", "to", "former", "presence", "of", "fjords", "in", "formerly" ]	[]
second capacitor, a first conductor, a second conductor, a third conductor, and a fourth conductor. - the first transistor includes a first gate, a first source, and a first drain. - the second transistor includes a second gate, a third gate over the second gate, a first low-resistance region, a second low-resistance region, and an oxide sandwiched between the second gate and the third gate. - the third transistor includes a fourth gate, a second source, and a second drain. - the fourth transistor includes a fifth gate, a sixth gate over the fifth gate, the second low-resistance region, a third low-resistance region, and the oxide sandwiched between the fifth gate and the sixth gate. - the first capacitor includes a first electrode, a second electrode over the first electrode, and a first insulator sandwiched between the first electrode and the second electrode. - the second capacitor includes a third electrode, a fourth electrode over the third electrode, and a second insulator sandwiched between the third electrode and the fourth electrode. - the first low-resistance region overlaps with the first gate. - the first conductor is electrically connected to the first gate. - the first conductor is connected to a bottom surface of the first low-resistance region. - the first capacitor overlaps with the first low-resistance region. - the first electrode is electrically connected to the first low-resistance region. - the third low-resistance region overlaps with the fourth gate. - the fourth conductor is electrically connected to the fourth gate. - the fourth conductor is connected to a bottom surface of the third low-resistance region. - the second capacitor overlaps with the third low-resistance region. - the third electrode is electrically connected to the third low-resistance region. - the second conductor is electrically connected to the first drain and the second drain. - the third conductor overlaps with the second conductor. - the third conductor is connected to the second conductor and a side surface of the second low-resistance region. - the first drain and the second drain are preferably provided in a fourth low-resistance region. - a distance between the second gate and the first gate be less than or equal to half the width of the first gate. - a distance between the second gate and the second conductor be less than or equal to half the width of the first gate. - the semiconductor device further include	[ "second", "capacitor", ",", "a", "first", "conductor", ",", "a", "second", "conductor", ",", "a", "third", "conductor", ",", "and", "a", "fourth", "conductor", ".", "\n", "-", "the", "first", "transistor", "\n", "includes", "a", "first", "gate", ",", "a", "first", "source", ",", "and", "a", "first", "drain", ".", "\n", "-", "the", "second", "transistor", "\n", "includes", "a", "second", "gate", ",", "a", "third", "gate", "over", "the", "second", "gate", ",", "a", "first", "low", "-", "resistance", "region", ",", "a", "second", "low", "-", "resistance", "region", ",", "and", "an", "oxide", "sandwiched", "between", "the", "second", "gate", "and", "the", "third", "gate", ".", "\n", "-", "the", "third", "transistor", "\n", "includes", "a", "fourth", "gate", ",", "a", "second", "source", ",", "and", "a", "second", "drain", ".", "\n", "-", "the", "fourth", "transistor", "\n", "includes", "a", "fifth", "gate", ",", "a", "sixth", "gate", "over", "the", "fifth", "gate", ",", "the", "second", "low", "-", "resistance", "region", ",", "a", "third", "low", "-", "resistance", "region", ",", "and", "the", "oxide", "sandwiched", "between", "the", "fifth", "gate", "and", "the", "sixth", "gate", ".", "\n", "-", "the", "first", "capacitor", "\n", "includes", "a", "first", "electrode", ",", "a", "second", "electrode", "over", "the", "first", "electrode", ",", "and", "a", "first", "insulator", "sandwiched", "between", "the", "first", "electrode", "and", "the", "second", "electrode", ".", "\n", "-", "the", "second", "capacitor", "\n", "includes", "a", "third", "electrode", ",", "a", "fourth", "electrode", "over", "the", "third", "electrode", ",", "and", "a", "second", "insulator", "sandwiched", "between", "the", "third", "electrode", "and", "the", "fourth", "electrode", ".", "\n", "-", "the", "first", "low", "-", "resistance", "region", "\n", "overlaps", "with", "the", "first", "gate", ".", "\n", "-", "the", "first", "conductor", "\n", "is", "electrically", "connected", "to", "the", "first", "gate", ".", "\n", "-", "the", "first", "conductor", "\n", "is", "connected", "to", "a", "bottom", "surface", "of", "the", "first", "low", "-", "resistance", "region", ".", "\n", "-", "the", "first", "capacitor", "\n", "overlaps", "with", "the", "first", "low", "-", "resistance", "region", ".", "\n", "-", "the", "first", "electrode", "\n", "is", "electrically", "connected", "to", "the", "first", "low", "-", "resistance", "region", ".", "\n", "-", "the", "third", "low", "-", "resistance", "region", "\n", "overlaps", "with", "the", "fourth", "gate", ".", "\n", "-", "the", "fourth", "conductor", "\n", "is", "electrically", "connected", "to", "the", "fourth", "gate", ".", "\n", "-", "the", "fourth", "conductor", "\n", "is", "connected", "to", "a", "bottom", "surface", "of", "the", "third", "low", "-", "resistance", "region", ".", "\n", "-", "the", "second", "capacitor", "\n", "overlaps", "with", "the", "third", "low", "-", "resistance", "region", ".", "\n", "-", "the", "third", "electrode", "\n", "is", "electrically", "connected", "to", "the", "third", "low", "-", "resistance", "region", ".", "\n", "-", "the", "second", "conductor", "\n", "is", "electrically", "connected", "to", "the", "first", "drain", "and", "the", "second", "drain", ".", "\n", "-", "the", "third", "conductor", "\n", "overlaps", "with", "the", "second", "conductor", ".", "\n", "-", "the", "third", "conductor", "\n", "is", "connected", "to", "the", "second", "conductor", "and", "a", "side", "surface", "of", "the", "second", "low", "-", "resistance", "region", ".", "\n", "-", "the", "first", "drain", "and", "the", "second", "drain", "\n", "are", "preferably", "provided", "in", "a", "fourth", "low", "-", "resistance", "region", ".", "\n", "-", "a", "distance", "between", "the", "second", "gate", "and", "the", "first", "gate", "\n", "be", "less", "than", "or", "equal", "to", "half", "the", "width", "of", "the", "first", "gate", ".", "\n", "-", "a", "distance", "between", "the", "second", "gate", "and", "the", "second", "conductor", "\n", "be", "less", "than", "or", "equal", "to", "half", "the", "width", "of", "the", "first", "gate", ".", "\n", "-", "the", "semiconductor", "device", "\n", "further", "include" ]	[]
PART III Entrepreneurship Source: Flooded Cellar Productions10.4324/9781003467342-7 55 Stories from the street An intricate sidewalk ballet This chapter has been made available under a CC-BY-NC-ND 4.0 license. The stretch of Hudson Street where I live is each day the scene of an intricate sidewalk ballet. I make my own first entrance into it a little after eight when I put out the garbage can, surely a prosaic occupation, but I enjoy my part, my little clang, as the droves of junior high school students walk by the centre of the stage dropping candy wrappers. (How do they eat so much candy so early in the morning?) While I sweep up the wrappers I watch the other rituals of morning: Mr Halpert unlocking the laundry’s handcart from its mooring to a cellar door, Joe Cornacchia’s son-in-law stacking out the empty crates from the delicatessen, the barber bringing out his sidewalk folding chair, Mr Goldstein arranging the coils of wire which proclaim the hardware store is open, the wife of the tenement’s superintendent depositing her chunky three-year-old with a toy mandolin on the stoop, the vantage point from which he is learning the English his mother cannot speak. (Jacobs 1961 , p. 61) DOI: 10.4324/9781003467342-810.4324/9781003467342-8 114 Urban life in Delhi slumsStories from the street Introduction As in the quote by Jane Jacobs, setting out the morning routine she encountered on Hudson Street, New York, in her 1961 book Death and Life in Great American Cities , we highlight the voices of the entrepreneurs we encountered during this research in our Delhi neighbourhoods. Stories of the street scenes where goods are being hawked and haggled over in shops and markets will be told alongside the voices of entrepre - neurs – the street vendors, textile workers, carpenters, painters, recyclers, beauticians, barbers and cooks. The atmosphere in these settlements is buoyant, friendly, exuding community cohesion and trust. The slums provide examples of organic growth where the poor are agents of change. Place attachment provides a feeling of community uniqueness and irreplaceability. With a sense of belonging, feelings of loyalty, trust and a life with value and dignity, there follows a desire for bottom-up approaches to alleviating poverty. It is an ‘infectious’ atmosphere, with the poor focused on their family, neighbourhoods and the next generation. According to Jane Jacobs A good way to see the problem of the city is to take a bus or	[ "PART", " ", "III", "\n", "Entrepreneurship", "\n", "Source", ":", "Flooded", "Cellar", "Productions10.4324/9781003467342", "-", "7", "\n", "55", "\n", "Stories", "from", "the", "street", "\n", "An", "intricate", "sidewalk", "ballet", "\n", "This", "chapter", "has", "been", "made", "available", "under", "a", "CC", "-", "BY", "-", "NC", "-", "ND", "4.0", "license", ".", "\n", "The", "stretch", "of", "Hudson", "Street", "where", "I", "live", "is", "each", "day", "the", "scene", "of", "an", "intricate", "\n", "sidewalk", "ballet", ".", "I", "make", "my", "own", "first", "entrance", "into", "it", "a", "little", "after", "eight", "when", "I", "\n", "put", "out", "the", "garbage", "can", ",", "surely", "a", "prosaic", "occupation", ",", "but", "I", "enjoy", "my", "part", ",", "my", "\n", "little", "clang", ",", "as", "the", "droves", "of", "junior", "high", "school", "students", "walk", "by", "the", "centre", "of", "the", "\n", "stage", "dropping", "candy", "wrappers", ".", "(", "How", "do", "they", "eat", "so", "much", "candy", "so", "early", "in", "the", "\n", "morning", "?", ")", "While", "I", "sweep", "up", "the", "wrappers", "I", "watch", "the", "other", "rituals", "of", "morning", ":", "\n", "Mr", "Halpert", "unlocking", "the", "laundry", "’s", "handcart", "from", "its", "mooring", "to", "a", "cellar", "door", ",", "\n", "Joe", "Cornacchia", "’s", "son", "-", "in", "-", "law", "stacking", "out", "the", "empty", "crates", "from", "the", "delicatessen", ",", "\n", "the", "barber", "bringing", "out", "his", "sidewalk", "folding", "chair", ",", "Mr", "Goldstein", "arranging", "the", "\n", "coils", "of", "wire", "which", "proclaim", "the", "hardware", "store", "is", "open", ",", "the", "wife", "of", "the", "tenement", "’s", "\n", "superintendent", "depositing", "her", "chunky", "three", "-", "year", "-", "old", "with", "a", "toy", "mandolin", "on", "the", "\n", "stoop", ",", "the", "vantage", "point", "from", "which", "he", "is", "learning", "the", "English", "his", "mother", "can", "not", "\n", "speak", ".", "(", "Jacobs", "1961", ",", "p.", "61", ")", "\n", "DOI", ":", "10.4324/9781003467342", "-", "810.4324/9781003467342", "-", "8", "\n", "114", "Urban", "life", "in", "Delhi", "slumsStories", "from", "the", "street", "\n", "Introduction", "\n", "As", "in", "the", "quote", "by", "Jane", "Jacobs", ",", "setting", "out", "the", "morning", "routine", "she", "encountered", "on", "\n", "Hudson", "Street", ",", "New", "York", ",", "in", "her", "1961", "book", "Death", "and", "Life", "in", "Great", "American", "Cities", ",", "\n", "we", "highlight", "the", "voices", "of", "the", "entrepreneurs", "we", "encountered", "during", "this", "research", "in", "\n", "our", "Delhi", "neighbourhoods", ".", "Stories", "of", "the", "street", "scenes", "where", "goods", "are", "being", "hawked", "\n", "and", "haggled", "over", "in", "shops", "and", "markets", "will", "be", "told", "alongside", "the", "voices", "of", "entrepre", "-", "\n", "neurs", "–", "the", "street", "vendors", ",", "textile", "workers", ",", "carpenters", ",", "painters", ",", "recyclers", ",", "beauticians", ",", "\n", "barbers", "and", "cooks", ".", "The", "atmosphere", "in", "these", "settlements", "is", "buoyant", ",", "friendly", ",", "exuding", "\n", "community", "cohesion", "and", "trust", ".", "The", "slums", "provide", "examples", "of", "organic", "growth", "where", "\n", "the", "poor", "are", "agents", "of", "change", ".", "Place", "attachment", "provides", "a", "feeling", "of", "community", "\n", "uniqueness", "and", "irreplaceability", ".", "With", "a", "sense", "of", "belonging", ",", "feelings", "of", "loyalty", ",", "trust", "\n", "and", "a", "life", "with", "value", "and", "dignity", ",", "there", "follows", "a", "desire", "for", "bottom", "-", "up", "approaches", "to", "\n", "alleviating", "poverty", ".", "It", "is", "an", "‘", "infectious", "’", "atmosphere", ",", "with", "the", "poor", "focused", "on", "their", "\n", "family", ",", "neighbourhoods", "and", "the", "next", "generation", ".", "\n", "According", "to", "Jane", "Jacobs", "\n", "A", "good", "way", "to", "see", "the", "problem", "of", "the", "city", "is", "to", "take", "a", "bus", "or" ]	[ { "end": 1214, "label": "CITATION_REF", "start": 1195 }, { "end": 1201, "label": "AUTHOR", "start": 1195 }, { "end": 1206, "label": "YEAR", "start": 1202 }, { "end": 1267, "label": "CITATION_SPAN", "start": 1216 } ]
4 4 2 2 7.107E-03 7.107E-03 1.000E+00 1.000E+00 4 4.00000E-01 3 3 3 3 2 2 1.071E-01 1.071E-01 1.000E+00 1.000E+00 5 5.00000E-01 6 6 6 6 3 2 1.381E-01 1.381E-01 1.000E+00 1.000E+00 In conclusion, the numerical tests performed so far seem to conrm that the REDP procedure performs correctly, and can be safely combined with REDU andASN. 94 Tuesday 12thAugust, 2025 @ 13:38 6.5 Penetration variation with lateral sliding The scope of this Section is to investigate the in uence of lateral sliding on the measurement of penetration between two contacting bodies using the pinball contact algorithm. In particular, we want to verify if and how the amount of penetration varies when two contacting bodies slide with respect to each other along two parallel lines. A certain variation of the penetration is expected, since pinballs may not exactly represent a at surface and they protrude from the elements in which they are embedded. The tests assume two continuum blocks meshed by quadrangles in 2D. The tests performed are summarized in Table 14 and are described in the following. Test Mesh Description Displacement Sub-cases step [m] MEPE41 2 Q42L Parent pinballs ( MLEV 0 ) 0 :1 10 MEPE42 2 Q42L Idem 41 but MLEV 1 0:1 10 MEPE43 2 Q42L Idem 42 but add REDP 0:1 10 MEPE44 2 Q42L Idem 42 but MLEV 2 0:1 10 Table 14: Tests to measure the penetration between two parallel sliding bodies. 95 Tuesday 12thAugust, 2025 @ 13:38 6.5.1 Case MEPE41 This test is geometrically similar to case MEPE01 of Section 6.1. Two unit quadrangles touch them- selves in the initial conguration so that there is penetration already at step 0. A vertical initial velocity is assigned to the projectile (upper body) so that the contact is not discarded by the a priori rebound algorithm. However, unlike in case MEPE01 and the following ones presented previously, we do not prescribe any constraints besides those stemming from contact. This ensures that the system is not fully- constrained due to the prescribed dofs (and it does not become over-constrained when contact is detected). Consequently, there is no need to add extra dummy elements. Furthermore, we only perform the initialization step (step 0) and immediately stop the simulation thereafter. In fact, the scope here is just that of measuring the penetration. The test is subdivided into several distinct sub-tests, which are obtained by using	[ "4", "4", "2", "2", "7.107E-03", "7.107E-03", "1.000E+00", "1.000E+00", "\n", "4", "4.00000E-01", "3", "3", "3", "3", "2", "2", "1.071E-01", "1.071E-01", "1.000E+00", "1.000E+00", "\n", "5", "5.00000E-01", "6", "6", "6", "6", "3", "2", "1.381E-01", "1.381E-01", "1.000E+00", "1.000E+00", "\n", "In", "conclusion", ",", "the", "numerical", "tests", "performed", "so", "far", "seem", "to", "con", "\f", "rm", "that", "the", "REDP", "procedure", "\n", "performs", "correctly", ",", "and", "can", "be", "safely", "combined", "with", "REDU", "andASN", ".", "\n", "94", "\n", "Tuesday", "12thAugust", ",", "2025", "@", "13:38", "\n", "6.5", "Penetration", "variation", "with", "lateral", "sliding", "\n", "The", "scope", "of", "this", "Section", "is", "to", "investigate", "the", "in", "\n", "uence", "of", "lateral", "sliding", "on", "the", "measurement", "of", "\n", "penetration", "between", "two", "contacting", "bodies", "using", "the", "pinball", "contact", "algorithm", ".", "\n", "In", "particular", ",", "we", "want", "to", "verify", "if", "and", "how", "the", "amount", "of", "penetration", "varies", "when", "two", "contacting", "\n", "bodies", "slide", "with", "respect", "to", "each", "other", "along", "two", "parallel", "lines", ".", "A", "certain", "variation", "of", "the", "penetration", "\n", "is", "expected", ",", "since", "pinballs", "may", "not", "exactly", "represent", "a", "\n", "at", "surface", "and", "they", "protrude", "from", "the", "elements", "\n", "in", "which", "they", "are", "embedded", ".", "\n", "The", "tests", "assume", "two", "continuum", "blocks", "meshed", "by", "quadrangles", "in", "2D.", "The", "tests", "performed", "are", "\n", "summarized", "in", "Table", "14", "and", "are", "described", "in", "the", "following", ".", "\n", "Test", "Mesh", "Description", "Displacement", "Sub", "-", "cases", "\n", "step", "[", "m", "]", "\n", "MEPE41", "2", "Q42L", "Parent", "pinballs", "(", "MLEV", "0", ")", "0", ":1", "10", "\n", "MEPE42", "2", "Q42L", "Idem", "41", "but", "MLEV", "1", "0:1", "10", "\n", "MEPE43", "2", "Q42L", "Idem", "42", "but", "add", "REDP", "0:1", "10", "\n", "MEPE44", "2", "Q42L", "Idem", "42", "but", "MLEV", "2", "0:1", "10", "\n", "Table", "14", ":", "Tests", "to", "measure", "the", "penetration", "between", "two", "parallel", "sliding", "bodies", ".", "\n", "95", "\n", "Tuesday", "12thAugust", ",", "2025", "@", "13:38", "\n", "6.5.1", "Case", "MEPE41", "\n", "This", "test", "is", "geometrically", "similar", "to", "case", "MEPE01", "of", "Section", "6.1", ".", "Two", "unit", "quadrangles", "touch", "them-", "\n", "selves", "in", "the", "initial", "con", "\f", "guration", "so", "that", "there", "is", "penetration", "already", "at", "step", "0", ".", "A", "vertical", "initial", "\n", "velocity", "is", "assigned", "to", "the", "projectile", "(", "upper", "body", ")", "so", "that", "the", "contact", "is", "not", "discarded", "by", "the", "a", "priori", "\n", "rebound", "algorithm", ".", "\n", "However", ",", "unlike", "in", "case", "MEPE01", "and", "the", "following", "ones", "presented", "previously", ",", "we", "do", "not", "prescribe", "\n", "any", "constraints", "besides", "those", "stemming", "from", "contact", ".", "This", "ensures", "that", "the", "system", "is", "not", "fully-", "\n", "constrained", "due", "to", "the", "prescribed", "dofs", "(", "and", "it", "does", "not", "become", "over", "-", "constrained", "when", "contact", "is", "\n", "detected", ")", ".", "Consequently", ",", "there", "is", "no", "need", "to", "add", "extra", "dummy", "elements", ".", "Furthermore", ",", "we", "only", "\n", "perform", "the", "initialization", "step", "(", "step", "0", ")", "and", "immediately", "stop", "the", "simulation", "thereafter", ".", "In", "fact", ",", "the", "\n", "scope", "here", "is", "just", "that", "of", "measuring", "the", "penetration", ".", "\n", "The", "test", "is", "subdivided", "into", "several", "distinct", "sub", "-", "tests", ",", "which", "are", "obtained", "by", "using" ]	[]
base erosion and profit shifting CAPEX capital expenditure CIT corporate income tax EPZ export processing zone IGF Intergovernmental Forum on Mining, Minerals, Metals and Sustainable Development IMF International Monetary Fund IRR internal rate of return MNE multinational enterprise OECD Organisation for Economic Co-operation and Development OPEX operating expenditure PNG Papua New Guinea PSA production-sharing agreement RRT resource rent tax SCA Supreme Court of Appeal ## TABLE OF CONTENTS \| 1.0 Introduction..................................................................................................................................................1 \| 1.0 Introduction..................................................................................................................................................1 \| \|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------\|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\| \| \| 1.1 About This Practice Note................................................................................................................................................................................ 4 \| \| \| 1.2 Who Is This Practice Note For?................................................................................................................................................................ 4 \| \| \| 1.3 What Gap DoesThis Practice Note Fill? ..................................................................................................................................... 4 \| \| 2.0 The Fundamentals of Ring-Fencing................................................................................................ 5 \| 2.0 The Fundamentals of Ring-Fencing................................................................................................ 5 \| \| \| 2.1 The Source of Ring-Fencing Rules........................................................................................................................................................ 7 \| \| \| 2.2 The Prevalence of Ring-Fencing Rules in the Extractive Sectors.................................................................. 8 \| \| 3.0 The Benefits and Risks of Ring-Fencing .................................................................................... 12 \| 3.0 The Benefits and Risks of Ring-Fencing .................................................................................... 12 \| \| \| 3.1 The Benefits.................................................................................................................................................................................................................. 13 \| \| \| 3.2 The Risks ......................................................................................................................................................................................................................... 19 \| \| 4.0 Designing Ring-Fencing Rules......................................................................................................... 23 \| 4.0 Designing Ring-Fencing Rules......................................................................................................... 23 \| \| \| 4.1 When Ring-Fencing Is an Appropriate Policy Response....................................................................................... 24 \| \| \| 4.2 Designing Ring-Fencing Rules..............................................................................................................................................................26 \| \| \| 4.3 What Aspects of Mining Operations Should Be Ring-Fenced? .................................................................28 \| \| \| 4.4 WhichTaxes Should Be Ring-Fenced?.......................................................................................................................................39 \| \| \| 4.5 Who Ring-Fencing Rules Should ApplyTo............................................................................................................................. 41 \| \| \| 4.6 Is It Reasonable to Consider Some Exceptions to Ring-Fencing Rules?.........................................43 \| \| \| 4.7 How to Deal With Permanent Losses Where Ring-Fencing Rules Exist............................................ 46 \| \| 5.0 The Implementation of Ring-Fencing Rules.............................................................................. 51 \| 5.0 The Implementation of Ring-Fencing Rules.............................................................................. 51 \| \| \| 5.1 Introducing Ring-Fencing Rules Into the Applicable Legal Framework.............................................. 52 \| \| \| 5.2 How Should the Apportionment of Revenues and Expenditures Work?............................................56 \| \| 5.3 How of Ring-Fencing \| ...............................................................................................................................................................................................................62 \| \| \| 5.4 How to Design Taxpayers' Compliance Obligations...................................................................................................63 \| \| 6.0 Conclusion.................................................................................................................................................. 67 \| 6.0 Conclusion.................................................................................................................................................. 67 \| \| \| Financial Support for the OECD Comes From the Following Donors:............................................................70 \| \| \| Support for the IGF Comes From the Following:........................................................................................................................71 \| \| \| References................................................................................................................................................................................................................................72 \| 1.0 Introduction ## 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	[ "base", "erosion", "and", "profit", "shifting", "\n\n", "CAPEX", "\n\n", "capital", "expenditure", "\n\n", "CIT", "\n\n", "corporate", "income", "tax", "\n\n", "EPZ", "\n\n", "export", "processing", "zone", "\n\n", "IGF", "\n\n", "Intergovernmental", "Forum", "on", "Mining", ",", "Minerals", ",", "Metals", "\n\n", "and", "Sustainable", "Development", "\n\n", "IMF", "\n\n", "International", "Monetary", "Fund", "\n\n", "IRR", "\n\n", "internal", "rate", "of", "return", "\n\n", "MNE", "\n\n", "multinational", "enterprise", "\n\n", "OECD", "\n\n", "Organisation", "for", "Economic", "Co", "-", "operation", "and", "Development", "\n\n", "OPEX", "\n\n", "operating", "expenditure", "\n\n", "PNG", "\n\n", "Papua", "New", "Guinea", "\n\n", "PSA", "\n\n", "production", "-", "sharing", "agreement", "\n\n", "RRT", "\n\n", "resource", "rent", "tax", "\n\n", "SCA", "\n\n", "Supreme", "Court", "of", "Appeal", "\n\n", "#", "#", "TABLE", "OF", "CONTENTS", "\n\n", "\|", "1.0", "Introduction", "..................................................................................................................................................", "1", " ", "\|", "1.0", "Introduction", "..................................................................................................................................................", "1", " ", "\|", "\n", "\|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------\|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\|", "\n", "\|", " ", "\|", "1.1", "About", "This", "Practice", "Note", "................................................................................................................................................................................", "4", " ", "\|", "\n", "\|", " ", "\|", "1.2", "Who", "Is", "This", "Practice", "Note", "For", "?", "................................................................................................................................................................", "4", " ", "\|", "\n", "\|", " ", "\|", "1.3", "What", "Gap", "DoesThis", "Practice", "Note", "Fill", "?", ".....................................................................................................................................", "4", " ", "\|", "\n", "\|", "2.0", "The", "Fundamentals", "of", "Ring", "-", "Fencing", "................................................................................................", "5", " ", "\|", "2.0", "The", "Fundamentals", "of", "Ring", "-", "Fencing", "................................................................................................", "5", " ", "\|", "\n", "\|", " ", "\|", "2.1", "The", "Source", "of", "Ring", "-", "Fencing", "Rules", "........................................................................................................................................................", "7", " ", "\|", "\n", "\|", " ", "\|", "2.2", "The", "Prevalence", "of", "Ring", "-", "Fencing", "Rules", "in", "the", "Extractive", "Sectors", "..................................................................", "8", " ", "\|", "\n", "\|", "3.0", "The", "Benefits", "and", "Risks", "of", "Ring", "-", "Fencing", "....................................................................................", "12", " ", "\|", "3.0", "The", "Benefits", "and", "Risks", "of", "Ring", "-", "Fencing", "....................................................................................", "12", " ", "\|", "\n", "\|", " ", "\|", "3.1", "The", "Benefits", "..................................................................................................................................................................................................................", "13", " ", "\|", "\n", "\|", " ", "\|", "3.2", "The", "Risks", ".........................................................................................................................................................................................................................", "19", " ", "\|", "\n", "\|", "4.0", "Designing", "Ring", "-", "Fencing", "Rules", ".........................................................................................................", "23", " ", "\|", "4.0", "Designing", "Ring", "-", "Fencing", "Rules", ".........................................................................................................", "23", " ", "\|", "\n", "\|", " ", "\|", "4.1", "When", "Ring", "-", "Fencing", "Is", "an", "Appropriate", "Policy", "Response", ".......................................................................................", "24", " ", "\|", "\n", "\|", " ", "\|", "4.2", "Designing", "Ring", "-", "Fencing", "Rules", "..............................................................................................................................................................", "26", " ", "\|", "\n", "\|", " ", "\|", "4.3", "What", "Aspects", "of", "Mining", "Operations", "Should", "Be", "Ring", "-", "Fenced", "?", ".................................................................", "28", " ", "\|", "\n", "\|", " ", "\|", "4.4", "WhichTaxes", "Should", "Be", "Ring", "-", "Fenced?", ".......................................................................................................................................", "39", " ", "\|", "\n", "\|", " ", "\|", "4.5", "Who", "Ring", "-", "Fencing", "Rules", "Should", "ApplyTo", ".............................................................................................................................", "41", " ", "\|", "\n", "\|", " ", "\|", "4.6", "Is", "It", "Reasonable", "to", "Consider", "Some", "Exceptions", "to", "Ring", "-", "Fencing", "Rules?", ".........................................", "43", " ", "\|", "\n", "\|", " ", "\|", "4.7", "How", "to", "Deal", "With", "Permanent", "Losses", "Where", "Ring", "-", "Fencing", "Rules", "Exist", "............................................", "46", " ", "\|", "\n", "\|", "5.0", "The", "Implementation", "of", "Ring", "-", "Fencing", "Rules", "..............................................................................", "51", " ", "\|", "5.0", "The", "Implementation", "of", "Ring", "-", "Fencing", "Rules", "..............................................................................", "51", " ", "\|", "\n", "\|", " ", "\|", "5.1", "Introducing", "Ring", "-", "Fencing", "Rules", "Into", "the", "Applicable", "Legal", "Framework", "..............................................", "52", " ", "\|", "\n", "\|", " ", "\|", "5.2", "How", "Should", "the", "Apportionment", "of", "Revenues", "and", "Expenditures", "Work?", "............................................", "56", " ", "\|", "\n", "\|", "5.3", "How", "of", "Ring", "-", "Fencing", " ", "\|", "...............................................................................................................................................................................................................", "62", " ", "\|", "\n", "\|", " ", "\|", "5.4", "How", "to", "Design", "Taxpayers", "'", "Compliance", "Obligations", "...................................................................................................", "63", " ", "\|", "\n", "\|", "6.0", "Conclusion", "..................................................................................................................................................", "67", " ", "\|", "6.0", "Conclusion", "..................................................................................................................................................", "67", " ", "\|", "\n", "\|", " ", "\|", "Financial", "Support", "for", "the", "OECD", "Comes", "From", "the", "Following", "Donors:", "............................................................", "70", " ", "\|", "\n", "\|", " ", "\|", "Support", "for", "the", "IGF", "Comes", "From", "the", "Following:", "........................................................................................................................", "71", " ", "\|", "\n", "\|", " ", "\|", "References", "................................................................................................................................................................................................................................", "72", "\|", "\n\n", "1.0", "Introduction", "\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" ]	[]
spent the past four years studying the manuscripts, said the volumes were “four versions of Thornton’s life as her circumstances changed and she looked back over the years trying to make sense of what happened”. Thornton was “particularly keen to restate her identity as a chaste wife and to lay the blame for the family’s downturn in fortune on various male family members, including her late husband”, she said. “Her writings show that, alongside domestic and familial responsibilities, early modern women were fully engaged with the political events of their day.” Thornton was born in Yorkshire in 1626. The family moved to Ireland seven years later, where her father became lord deputy shortly before he died. Amid the turmoil of the Irish Rebellion, the family returned to northern England, where they were caught up in the civil war. As royalists, their estates were confiscated, and parliamentarian and Scottish soldiers were billeted on their land. Thornton agreed to marry a parliamentarian to secure her family’s financial future. She gave birth to nine babies, later describing both the dangers of childbirth and the deaths of six of her infant children. Her husband, William, died in 1668 without a will and leaving her heavily in debt. Pages from Alice Thornton’s Book of Remembrances. Photograph: Durham Cathedral Library <!-- image --> Her financial woes are detailed in her books, but they show her to be financially shrewd and capable of negotiating complex legal matters. “She was quite switched on and adept at managing finances,” said Beattie. In Book One, Thornton defends herself against rumours that she was conducting a clandestine affair with the local curate, Thomas Comber, who was not only nearly 20 years her junior but was also engaged to her 14-year-old daughter. “She really struggles with this because she thinks of herself as a godly woman, a chaste wife. I think she does have a good relationship with Comber, but the fact that people think she might be cheating on her husband really worried her,” said Beattie. Comber is later appointed dean of Durham Cathedral. “He does well for himself. But people wonder why she married off her daughter at the age of 14, and the rumour is that it’s about Alice trying to get Comber for herself.” Thornton also writes about two attempted rapes. One of her attackers was a captain in the Scottish army “who did swear to ravish me	[ "spent", "the", "past", "four", "years", "studying", "the", "manuscripts", ",", "said", "the", "volumes", "were", "“", "four", "versions", "of", "Thornton", "’s", "life", "as", "her", "circumstances", "changed", "and", "she", "looked", "back", "over", "the", "years", "trying", "to", "make", "sense", "of", "what", "happened", "”", ".", "\n\n", "Thornton", "was", "“", "particularly", "keen", "to", "restate", "her", "identity", "as", "a", "chaste", "wife", "and", "to", "lay", "the", "blame", "for", "the", "family", "’s", "downturn", "in", "fortune", "on", "various", "male", "family", "members", ",", "including", "her", "late", "husband", "”", ",", "she", "said", ".", "\n\n", "“", "Her", "writings", "show", "that", ",", "alongside", "domestic", "and", "familial", "responsibilities", ",", "early", "modern", "women", "were", "fully", "engaged", "with", "the", "political", "events", "of", "their", "day", ".", "”", "\n\n", "Thornton", "was", "born", "in", "Yorkshire", "in", "1626", ".", "The", "family", "moved", "to", "Ireland", "seven", "years", "later", ",", "where", "her", "father", "became", "lord", "deputy", "shortly", "before", "he", "died", ".", "Amid", "the", "turmoil", "of", "the", "Irish", "Rebellion", ",", "the", "family", "returned", "to", "northern", "England", ",", "where", "they", "were", "caught", "up", "in", "the", "civil", "war", ".", "As", "royalists", ",", "their", "estates", "were", "confiscated", ",", "and", "parliamentarian", "and", "Scottish", "soldiers", "were", "billeted", "on", "their", "land", ".", "\n\n", "Thornton", "agreed", "to", "marry", "a", "parliamentarian", "to", "secure", "her", "family", "’s", "financial", "future", ".", "She", "gave", "birth", "to", "nine", "babies", ",", "later", "describing", "both", "the", "dangers", "of", "childbirth", "and", "the", "deaths", "of", "six", "of", "her", "infant", "children", ".", "Her", "husband", ",", "William", ",", "died", "in", "1668", "without", "a", "will", "and", "leaving", "her", "heavily", "in", "debt", ".", "\n\n", "Pages", "from", "Alice", "Thornton", "’s", "Book", "of", "Remembrances", ".", "Photograph", ":", "Durham", "Cathedral", "Library", "\n\n", "<", "!", "--", "image", "--", ">", "\n\n", "Her", "financial", "woes", "are", "detailed", "in", "her", "books", ",", "but", "they", "show", "her", "to", "be", "financially", "shrewd", "and", "capable", "of", "negotiating", "complex", "legal", "matters", ".", "“", "She", "was", "quite", "switched", "on", "and", "adept", "at", "managing", "finances", ",", "”", "said", "Beattie", ".", "\n\n", "In", "Book", "One", ",", "Thornton", "defends", "herself", "against", "rumours", "that", "she", "was", "conducting", "a", "clandestine", "affair", "with", "the", "local", "curate", ",", "Thomas", "Comber", ",", "who", "was", "not", "only", "nearly", "20", "years", "her", "junior", "but", "was", "also", "engaged", "to", "her", "14", "-", "year", "-", "old", "daughter", ".", "\n\n", "“", "She", "really", "struggles", "with", "this", "because", "she", "thinks", "of", "herself", "as", "a", "godly", "woman", ",", "a", "chaste", "wife", ".", "I", "think", "she", "does", "have", "a", "good", "relationship", "with", "Comber", ",", "but", "the", "fact", "that", "people", "think", "she", "might", "be", "cheating", "on", "her", "husband", "really", "worried", "her", ",", "”", "said", "Beattie", ".", "\n\n", "Comber", "is", "later", "appointed", "dean", "of", "Durham", "Cathedral", ".", "“", "He", "does", "well", "for", "himself", ".", "But", "people", "wonder", "why", "she", "married", "off", "her", "daughter", "at", "the", "age", "of", "14", ",", "and", "the", "rumour", "is", "that", "it", "’s", "about", "Alice", "trying", "to", "get", "Comber", "for", "herself", ".", "”", "\n\n", "Thornton", "also", "writes", "about", "two", "attempted", "rapes", ".", "One", "of", "her", "attackers", "was", "a", "captain", "in", "the", "Scottish", "army", "“", "who", "did", "swear", "to", "ravish", "me" ]	[]
23.39 \| 1.22 \| 77.23 \| 401.76 \| \| \| 10-6-1 \| 3.95 \| 3.04 \| 23.95 \| 1.23 \| 77 \| 406.03 \| \| \| 100-6-1 \| 4.22 \| 3.04 \| 24.1 \| 1.22 \| 76.36 \| 399.91 \| \| \| 1000-6-1 \| 4.3 \| 3.03 \| 24.62 \| 1.21 \| 76.27 \| 397.27 \| Table 4: Analysis of the generated text among different dimensions. We used the prefix in the validation set and the small transformer model trained on CCNEWS to generate the text. Under the column params we report hyper parameters for the decoding strategy considered. For DELAYEDBS we we have varied only the parameter for top-k sampling and we used beam size equal to 6 and delay length of 1 . \| prefix \| Princess Margaret, Countess of Snowdon . Princess Margaret, Countess of Snowdon, (Margaret Rose 21 Au- gust 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. \| Whitey Bulger . James Joseph Whitey Bulger Jr. ( Septem- ber 3, 1929 - October 30, 2018) was an Irish-American or- ganized crime boss and FBI informant who led the Winter Hill Gang in the Winter Hill neighborhood of Somerville, Massachusetts, a city directly northwest of Boston. \| \|----------\|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\| \| top-k \| She is the only surviving member from the Royal Family who was born in the same year as the Queen Mother. Princess Margaret, Countess of Snowdon, (Margaret Rose 21 August 1930 - 9 February 2002) was a British princess who married into the British Royal Family in 1939. She is a cousin to the Queen, Prince Philip, Prince Charles, Prince William, Prince Harry and Prince Edward. Princess Margaret, Countess of Snowdon, (Margaret Rose 21 August 1930 - 9 February 2002) is the younger daugh- ter of King George VI and Queen Elizabeth. She is the only survivor from the Royal Family who was born in the same year as Queen Elizabeth. \| He was a fugitive for 16 years before his arrest in 2011. He was sentenced in 2013 to two life terms plus five years for his role in 11 murders and was released in 2014. Bulger was found dead in his cell at the U.S. penitentiary in West Virginia. He was 89. He was serving the life sentences for his role in the infa-	[ "23.39", "\|", " ", "1.22", "\|", " ", "77.23", "\|", " ", "401.76", "\|", "\n", "\|", " ", "\|", "10", "-", "6", "-", "1", " ", "\|", " ", "3.95", "\|", " ", "3.04", "\|", " ", "23.95", "\|", " ", "1.23", "\|", " ", "77", " ", "\|", " ", "406.03", "\|", "\n", "\|", " ", "\|", "100", "-", "6", "-", "1", " ", "\|", " ", "4.22", "\|", " ", "3.04", "\|", " ", "24.1", " ", "\|", " ", "1.22", "\|", " ", "76.36", "\|", " ", "399.91", "\|", "\n", "\|", " ", "\|", "1000", "-", "6", "-", "1", "\|", " ", "4.3", " ", "\|", " ", "3.03", "\|", " ", "24.62", "\|", " ", "1.21", "\|", " ", "76.27", "\|", " ", "397.27", "\|", "\n\n", "Table", "4", ":", "Analysis", "of", "the", "generated", "text", "among", "different", "dimensions", ".", "We", "used", "the", "prefix", "in", "the", "validation", "set", "and", "the", "small", "transformer", "model", "trained", "on", "CCNEWS", "to", "generate", "the", "text", ".", "Under", "the", "column", "params", "we", "report", "hyper", "parameters", "for", "the", "decoding", "strategy", "considered", ".", "For", "DELAYEDBS", "we", "we", "have", "varied", "only", "the", "parameter", "for", "top", "-", "k", "sampling", "and", "we", "used", "beam", "size", "equal", "to", "6", "and", "delay", "length", "of", "1", ".", "\n\n", "\|", "prefix", " ", "\|", "Princess", "Margaret", ",", "Countess", "of", "Snowdon", ".", "Princess", "Margaret", ",", "Countess", "of", "Snowdon", ",", "(", "Margaret", "Rose", "21", "Au-", "gust", "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", ".", " ", "\|", "Whitey", "Bulger", ".", "James", "Joseph", "Whitey", "Bulger", "Jr.", "(", "Septem-", "ber", "3", ",", "1929", "-", "October", "30", ",", "2018", ")", "was", "an", "Irish", "-", "American", "or-", "ganized", "crime", "boss", "and", "FBI", "informant", "who", "led", "the", "Winter", "Hill", "Gang", "in", "the", "Winter", "Hill", "neighborhood", "of", "Somerville", ",", "Massachusetts", ",", "a", "city", "directly", "northwest", "of", "Boston", ".", " ", "\|", "\n", "\|----------\|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\|", "\n", "\|", "top", "-", "k", " ", "\|", "She", "is", "the", "only", "surviving", "member", "from", "the", "Royal", "Family", "who", "was", "born", "in", "the", "same", "year", "as", "the", "Queen", "Mother", ".", "Princess", "Margaret", ",", "Countess", "of", "Snowdon", ",", "(", "Margaret", "Rose", "21", "August", "1930", "-", "9", "February", "2002", ")", "was", "a", "British", "princess", "who", "married", "into", "the", "British", "Royal", "Family", "in", "1939", ".", "She", "is", "a", "cousin", "to", "the", "Queen", ",", "Prince", "Philip", ",", "Prince", "Charles", ",", "Prince", "William", ",", "Prince", "Harry", "and", "Prince", "Edward", ".", "Princess", "Margaret", ",", "Countess", "of", "Snowdon", ",", "(", "Margaret", "Rose", "21", "August", "1930", "-", "9", "February", "2002", ")", "is", "the", "younger", "daugh-", "ter", "of", "King", "George", "VI", "and", "Queen", "Elizabeth", ".", "She", "is", "the", "only", "survivor", "from", "the", "Royal", "Family", "who", "was", "born", "in", "the", "same", "year", "as", "Queen", "Elizabeth", ".", " ", "\|", "He", "was", "a", "fugitive", "for", "16", "years", "before", "his", "arrest", "in", "2011", ".", "He", "was", "sentenced", "in", "2013", "to", "two", "life", "terms", "plus", "five", "years", "for", "his", "role", "in", "11", "murders", "and", "was", "released", "in", "2014", ".", "Bulger", "was", "found", "dead", "in", "his", "cell", "at", "the", "U.S.", "penitentiary", "in", "West", "Virginia", ".", "He", "was", "89", ".", "He", "was", "serving", "the", "life", "sentences", "for", "his", "role", "in", "the", "infa-" ]	[]
outputs to produce badges and indicators wh ich can highlight easy-to-reproduce or well-reproduced research outputs. Finally, SciLake has initiated 4 pilots, encompassing a diverse array of scientiﬁc domains (Neuroscience, Cancer, Transport, and Energy), to showcase and assess the value of the SciLake services and their capability to address needs of diverse research communities. During RP1, SciLake partners have conducted a broad range of activities which lay the groundwork for the rest of the project. The most important achievements we re: - The collection and initial analysis of the SciLake pilot needs and requirements regarding the SciLake ecosystem (partly reported in D1.1)Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far⌄ 2 of 4 - The design and implementation of the initial version of the SciLake ecosystem architecture (reported in D1.2) - The design and implementation of the initial versions of the Scientiﬁc Lake service (D2.1) the Smart Impact-driven Knowledge Discovery service (D3.1) and the Smart Reproducibility Assistance service (D4.1) - The groundwork for the creation of the domain-speciﬁc SKGs that will be used by the SciLake pilots - The engagement of partners in various dissemination activities As a RIA project, SciLake naturally focuses on innovation, striving to advance the current state of the art. Its main innovations are expected to be centered around the key technologies used for the creation of the Scientiﬁc Lake, the Smart Impact-driven Knowledge Discovery, and the Smart Reproducibility Assistance service. Regarding the Scientiﬁc Lake service, the main contribution is expected to be in the ﬁeld of the eﬃcient Knowledge Graph mining and querying techniques. Notably, the AvantGraph component already incorporates innovative approaches that oﬀer performance on par with, or superior to, state- of-the-art systems, under speciﬁc conditions. By testing scenarios within the SciLake pilot projects, the AvantGraph team aims to address cases of particular interest and develop advanced solutions that push the boundaries of the current technologies. Regarding the Smart Impact-Driven Knowledge Discovery service, the primary contribution is expected to lie in the development of improved impact indicators for research outputs. Currently, no adequate impact indicators exist for research datasets or software hence, we aim to provide meaningful solutions for that. Additionally, we investigate variations of indicators for papers, incorporating additional factors (e.g. citation intent, topics) to oﬀer a more nuanced impact assessment. Finally, we are experimenting on meaningful approaches to	[ "outputs", "to", "produce", "badges", "and", "indicators", "wh", "ich", "can", "highlight", "easy", "-", "to", "-", "reproduce", "or", "well", "-", "reproduced", "\n", "research", "outputs", ".", "\n", "Finally", ",", "SciLake", "has", "initiated", "4", "pilots", ",", "encompassing", "a", "diverse", "array", "of", "scientiﬁc", "domains", "\n", "(", "Neuroscience", ",", "Cancer", ",", "Transport", ",", "and", "Energy", ")", ",", "to", "showcase", "and", "assess", "the", "value", "of", "the", "SciLake", "\n", "services", "and", "their", "capability", "to", "address", "needs", "of", "diverse", "research", "communities", ".", "\n", "During", "RP1", ",", "SciLake", "partners", "have", "conducted", "a", "broad", "range", "of", "activities", "which", "lay", "the", "groundwork", "\n", "for", "the", "rest", "of", "the", "project", ".", "The", "most", "important", "achievements", "we", "re", ":", "\n", "-", "The", "collection", "and", "initial", "analysis", "of", "the", "SciLake", "pilot", "needs", "and", "requirements", "regarding", "the", "SciLake", "\n", "ecosystem", "(", "partly", "reported", "in", "D1.1)Work", "performed", "from", "the", "beginning", "of", "the", "project", "to", "the", "end", "of", "the", "\n", "period", "covered", "by", "the", "report", "and", "main", "results", "achieved", "so", "far", "⌄", "\n", "2", "of", "4", "\n", "-", "The", "design", "and", "implementation", "of", "the", "initial", "version", "of", "the", "SciLake", "ecosystem", "architecture", "(", "reported", "\n", "in", "D1.2", ")", "\n", "-", "The", "design", "and", "implementation", "of", "the", "initial", "versions", "of", "the", "Scientiﬁc", "Lake", "service", "(", "D2.1", ")", "the", "Smart", "\n", "Impact", "-", "driven", "Knowledge", "Discovery", "service", "(", "D3.1", ")", "and", "the", "Smart", "Reproducibility", "Assistance", "service", "\n", "(", "D4.1", ")", "\n", "-", "The", "groundwork", "for", "the", "creation", "of", "the", "domain", "-", "speciﬁc", "SKGs", "that", "will", "be", "used", "by", "the", "SciLake", "pilots", "\n", "-", "The", "engagement", "of", "partners", "in", "various", "dissemination", "activities", "\n", "As", "a", "RIA", "project", ",", "SciLake", "naturally", "focuses", "on", "innovation", ",", "striving", "to", "advance", "the", "current", "state", "of", "the", "\n", "art", ".", "Its", "main", "innovations", "are", "expected", "to", "be", "centered", "around", "the", "key", "technologies", "used", "for", "the", "\n", "creation", "of", "the", "Scientiﬁc", "Lake", ",", "the", "Smart", "Impact", "-", "driven", "Knowledge", "Discovery", ",", "and", "the", "Smart", "\n", "Reproducibility", "Assistance", "service", ".", "\n", "Regarding", "the", "Scientiﬁc", "Lake", "service", ",", "the", "main", "contribution", "is", "expected", "to", "be", "in", "the", "ﬁeld", "of", "the", "\n", "eﬃcient", "Knowledge", "Graph", "mining", "and", "querying", "techniques", ".", "Notably", ",", "the", "AvantGraph", "component", "\n", "already", "incorporates", "innovative", "approaches", "that", "oﬀer", "performance", "on", "par", "with", ",", "or", "superior", "to", ",", "state-", "\n", "of", "-", "the", "-", "art", "systems", ",", "under", "speciﬁc", "conditions", ".", "By", "testing", "scenarios", "within", "the", "SciLake", "pilot", "projects", ",", "\n", "the", "AvantGraph", "team", "aims", "to", "address", "cases", "of", "particular", "interest", "and", "develop", "advanced", "solutions", "\n", "that", "push", "the", "boundaries", "of", "the", "current", "technologies", ".", "\n", "Regarding", "the", "Smart", "Impact", "-", "Driven", "Knowledge", "Discovery", "service", ",", "the", "primary", "contribution", "is", "\n", "expected", "to", "lie", "in", "the", "development", "of", "improved", "impact", "indicators", "for", "research", "outputs", ".", "Currently", ",", "no", "\n", "adequate", "impact", "indicators", "exist", "for", "research", "datasets", "or", "software", "hence", ",", "we", "aim", "to", "provide", "\n", "meaningful", "solutions", "for", "that", ".", "Additionally", ",", "we", "investigate", "variations", "of", "indicators", "for", "papers", ",", "\n", "incorporating", "additional", "factors", "(", "e.g.", "citation", "intent", ",", "topics", ")", "to", "oﬀer", "a", "more", "nuanced", "impact", "\n", "assessment", ".", "Finally", ",", "we", "are", "experimenting", "on", "meaningful", "approaches", "to" ]	[]
emphasis on instructional leadership and quality assurance. <!-- image --> <!-- image --> <!-- image -->	[ "emphasis", "on", "instructional", "leadership", "and", "quality", "assurance", ".", "\n\n", "<", "!", "--", "image", "--", ">", "\n\n", "<", "!", "--", "image", "--", ">", "\n\n", "<", "!", "--", "image", "--", ">" ]	[]
from millions to trillions. However, the origin of bacteria dates back to 3.5 billion years ago, and so the overall diversification rate among them is actually quite low. "If actual bacterial richness really is much higher than described richness for other groups, then a clade with low diversification rates [namely bacteria] would contain the majority of species across life - this would be in stark contrast to our results. Therefore, we caution that our results apply primarily to known species diversity," wrote the authors. RELATED TOPICS Plants & Animals New Species Ecology Research Birds Trees Earth & Climate Ecology Rainforests Exotic Species Environmental Awareness RELATED TERMS Adult stem cell Stem cell Evolution Earth Sociobiology Convergent evolution Biodiversity Biodiversity hotspot Story Source: Materials provided by Frontiers . Note: Content may be edited for style and length. Journal Reference : John J. Wiens, Daniel S. Moen. Rapid radiations underlie most of the known diversity of life . Frontiers in Ecology and Evolution , 2025; 13 DOI: 10.3389/fevo.2025.1596591 Cite This Page : MLA APA Chicago Frontiers. "Most of Earth’s species came from explosive bursts of evolution." ScienceDaily. ScienceDaily, 23 August 2025. <www.sciencedaily.com / releases / 2025 / 08 / 250822073805.htm>. Frontiers. (2025, August 23). Most of Earth’s species came from explosive bursts of evolution. ScienceDaily . Retrieved August 27, 2025 from www.sciencedaily.com / releases / 2025 / 08 / 250822073805.htm Frontiers. "Most of Earth’s species came from explosive bursts of evolution." ScienceDaily. www.sciencedaily.com / releases / 2025 / 08 / 250822073805.htm (accessed August 27, 2025). Explore More from ScienceDaily RELATED STORIES Violent Supernovae 'Triggered at Least Two Earth Extinctions' Mar. 13, 2025 — At least two mass extinction events in Earth's history were likely caused by the 'devastating' effects of nearby supernova explosions, a new study suggests. Researchers say these ... No Increase in Grain Dust Explosion Incidents Last Year, Decrease in Injuries Feb. 18, 2025 — Nine U.S. grain dust explosions in 2024 caused two injuries and no fatalities, according to a nationwide annual summary. These numbers are similar to last year's (nine explosions, 12 injuries ... Most Species Are Rare, but Not Very Rare Sep. 4, 2023 — More than 100 years of observations in nature have revealed a universal pattern of species abundances: Most species are rare but not very rare, and only a few species are very common. These so-called ... Biodiversity Engine for Fishes: Shifting Water Depth Feb.	[ "from", "millions", "to", "trillions", ".", "However", ",", "the", "origin", "of", "bacteria", "dates", "back", "to", "3.5", "billion", "years", "ago", ",", "and", "so", "the", "overall", "diversification", "rate", "among", "them", "is", "actually", "quite", "low", ".", "\n\n\n", "\"", "If", "actual", "bacterial", "richness", "really", "is", "much", "higher", "than", "described", "richness", "for", "other", "groups", ",", "then", "a", "clade", "with", "low", "diversification", "rates", "[", "namely", "bacteria", "]", "would", "contain", "the", "majority", "of", "species", "across", "life", "-", "this", "would", "be", "in", "stark", "contrast", "to", "our", "results", ".", "Therefore", ",", "we", "caution", "that", "our", "results", "apply", "primarily", "to", "known", "species", "diversity", ",", "\"", "wrote", "the", "authors", ".", "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n", "RELATED", "TOPICS", "\n\n\n\n\n\n\n", "Plants", "&", "Animals", "\n\n\n\n\n\n\n", "New", "Species", "\n\n\n\n\n\n\n", "Ecology", "Research", "\n\n\n\n\n\n\n", "Birds", "\n\n\n\n\n\n\n", "Trees", "\n\n\n\n\n\n\n\n\n\n\n", "Earth", "&", "Climate", "\n\n\n\n\n\n\n", "Ecology", "\n\n\n\n\n\n\n", "Rainforests", "\n\n\n\n\n\n\n", "Exotic", "Species", "\n\n\n\n\n\n\n", "Environmental", "Awareness", "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n", "RELATED", "TERMS", "\n\n\n\n\n\n\n", "Adult", "stem", "cell", "\n\n\n\n\n\n\n", "Stem", "cell", "\n\n\n\n\n\n\n", "Evolution", "\n\n\n\n\n\n\n", "Earth", "\n\n\n\n\n\n\n", "Sociobiology", "\n\n\n\n\n\n\n", "Convergent", "evolution", "\n\n\n\n\n\n\n", "Biodiversity", "\n\n\n\n\n\n\n", "Biodiversity", "hotspot", "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n", "Story", "Source", ":", "\n\n\n", "Materials", "provided", "by", "\n", "Frontiers", "\n", ".", "\n", "Note", ":", "Content", "may", "be", "edited", "for", "style", "and", "length", ".", "\n\n\n\n\n\n\n\n\n\n\n", "Journal", "Reference", "\n", ":", "\n\n\n\n\n", "John", "J.", "Wiens", ",", "Daniel", "S.", "Moen", ".", "\n", "Rapid", "radiations", "underlie", "most", "of", "the", "known", "diversity", "of", "life", "\n", ".", "\n", "Frontiers", "in", "Ecology", "and", "Evolution", "\n", ",", "2025", ";", "13", "DOI", ":", "\n", "10.3389", "/", "fevo.2025.1596591", "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n", "Cite", "This", "Page", "\n", ":", "\n\n\n\n\n\n\n", "MLA", "\n\n\n", "APA", "\n\n\n", "Chicago", "\n\n\n\n\n\n\n\n\n", "Frontiers", ".", "\"", "Most", "of", "Earth", "’s", "species", "came", "from", "explosive", "bursts", "of", "evolution", ".", "\"", "ScienceDaily", ".", "ScienceDaily", ",", "23", "August", "2025", ".", "<", "www.sciencedaily.com", "\n", "/", "\n", "releases", "\n", "/", "\n", "2025", "\n", "/", "\n", "08", "\n", "/", "\n", "250822073805.htm", ">", ".", "\n\n\n", "Frontiers", ".", "(", "2025", ",", "August", "23", ")", ".", "Most", "of", "Earth", "’s", "species", "came", "from", "explosive", "bursts", "of", "evolution", ".", "\n", "ScienceDaily", "\n", ".", "Retrieved", "August", "27", ",", "2025", "from", "www.sciencedaily.com", "\n", "/", "\n", "releases", "\n", "/", "\n", "2025", "\n", "/", "\n", "08", "\n", "/", "\n", "250822073805.htm", "\n\n\n", "Frontiers", ".", "\"", "Most", "of", "Earth", "’s", "species", "came", "from", "explosive", "bursts", "of", "evolution", ".", "\"", "ScienceDaily", ".", "www.sciencedaily.com", "\n", "/", "\n", "releases", "\n", "/", "\n", "2025", "\n", "/", "\n", "08", "\n", "/", "\n", "250822073805.htm", "(", "accessed", "August", "27", ",", "2025", ")", ".", "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n", "Explore", "More", "\n\n\n", "from", "ScienceDaily", "\n\n\n\n\n\n\n\n\n", "RELATED", "STORIES", "\n\n\n\n\n \n", "Violent", "Supernovae", "'", "Triggered", "at", "Least", "Two", "Earth", "Extinctions", "'", "\n\n\n\n\n", "Mar.", "13", ",", "2025", "—", "\n ", "At", "least", "two", "mass", "extinction", "events", "in", "Earth", "'s", "history", "were", "likely", "caused", "by", "the", "'", "devastating", "'", "effects", "of", "nearby", "supernova", "explosions", ",", "a", "new", "study", "suggests", ".", "Researchers", "say", "these", "...", "\n \n", "No", "Increase", "in", "Grain", "Dust", "Explosion", "Incidents", "Last", "Year", ",", "Decrease", "in", "Injuries", "\n\n\n\n\n", "Feb.", "18", ",", "2025", "—", "\n ", "Nine", "U.S.", "grain", "dust", "explosions", "in", "2024", "caused", "two", "injuries", "and", "no", "fatalities", ",", "according", "to", "a", "nationwide", "annual", "summary", ".", "These", "numbers", "are", "similar", "to", "last", "year", "'s", "(", "nine", "explosions", ",", "12", "injuries", "...", "\n \n", "Most", "Species", "Are", "Rare", ",", "but", "Not", "Very", "Rare", "\n\n\n\n\n", "Sep.", "4", ",", "2023", "—", "\n ", "More", "than", "100", "years", "of", "observations", "in", "nature", "have", "revealed", "a", "universal", "pattern", "of", "species", "abundances", ":", "Most", "species", "are", "rare", "but", "not", "very", "rare", ",", "and", "only", "a", "few", "species", "are", "very", "common", ".", "These", "so", "-", "called", "...", "\n \n", "Biodiversity", "Engine", "for", "Fishes", ":", "Shifting", "Water", "Depth", "\n\n\n\n\n", "Feb." ]	[ { "end": 1312, "label": "CITATION_SPAN", "start": 1138 } ]
898 774 973 Proportion of viral reads median (IQR)54% (40% - 68%)29% (18% - 54%)48% (27% - 65%) Proportion of reads assigned to newly described viruses median (IQR) mean (range)44% (29% - 60%) 45% (1% - 92%)22% (12% - 47%) 32% (2% - 93%)37% (19% - 58%) 40% (1% - 93%) IQR, interquartile range 102.3.2 Human viruses The identification of human viruses against established databases revealed an expected repertoire of childhood gut viruses. These were namely Human mastadenovirus A, B, C and F, Mamastrovirus ,Human bocaparvovirus, Rotavirus A, Norwalk virus, Human herpesvirus 5 (cytomegalovirus), Human herpesvirus 6 (roseolovirus), Human parechovirus, Enterovirus A, Cardiovirus, sequences of human endogenous retroviruses, and most importantly, various anelloviridae (Alpha-, Beta and Gammatorquevirus of various species). Anelloviruses were partly covered by specific PCR testing in one of our previous studies on CD (Tapia, Chuda et al. 2020) - therein published exploration using a single real-time PCR reaction did not however cover the whole spectrum of anelloviruses known today. Notably, although our metagenomic protocol was primarily designed to find DNA viruses, the signal included many known RNA viruses that commonly infect children. These included rotavirus, enterovirus and parechovirus. It is well known that DNA polymerases also have some RNA-dependent DNA polymerase activity, which is inconsistently reflected in these signals. Signals from human viruses, except Anelloviridae, did not meet the criteria for association testing (too few positive samples or too few positive individuals would preclude meaningful testing). The human virus data will be reported in a paper together with the bacteriophage data. 2.3.3 Known bacteriophages and novel viruses from the dark matter The DNA virome was dominated by bacteriophage genomes, but a large fraction of the viromes was unidentifiable prior to the novel virus extraction process. This unidentified fraction is commonly referred to as the dark matter . For example, the mean unidentified fraction in samples from the Finnish DIPP study was 95.5% against a collection of full-length and near-full-length viral sequences from NCBI GenBank, 70.0% against (Camarillo-Guerrero, Almeida et al. 2021); 88.9% against (Gregory, Zablocki et al. 2020); 70.7% against (Shah, Deng et al. 2023). As the authors of the latter publications are Partner 20 in this project, and because of the exceptionally high quality of their annotated non-redundant database, we decided to use their protocols and experience to construct a novel viral database of the dark matter observed in both MIDIA and DIPP studies. Using methods	[ "898", "774", "973", "\n", "Proportion", "of", "viral", "reads", "\n", "median", "(", "IQR)54", "%", "\n", "(", "40", "%", "-", "68%)29", "%", "\n", "(", "18", "%", "-", "54%)48", "%", "\n", "(", "27", "%", "-", "65", "%", ")", "\n", "Proportion", "of", "reads", "assigned", "to", "\n", "newly", "described", "viruses", "\n", "median", "(", "IQR", ")", "\n", "mean", "(", "range)44", "%", "(", "29", "%", "-", "60", "%", ")", "\n", "45", "%", "(", "1", "%", "-", "92%)22", "%", "(", "12", "%", "-", "47", "%", ")", "\n", "32", "%", "(", "2", "%", "-", "93%)37", "%", "(", "19", "%", "-", "58", "%", ")", "\n", "40", "%", "(", "1", "%", "-", "93", "%", ")", "\n", "IQR", ",", "interquartile", "range", "\n", "102.3.2", "Human", "viruses", "\n", "The", "identification", "of", "human", "viruses", "against", "established", "databases", "revealed", "an", "expected", "repertoire", "of", "childhood", "gut", "\n", "viruses", ".", "These", "were", "namely", "Human", "mastadenovirus", " ", "A", ",", "B", ",", "C", "and", "F", ",", "Mamastrovirus", ",", "Human", "bocaparvovirus", ",", "Rotavirus", "A", ",", "\n", "Norwalk", "virus", ",", "Human", "herpesvirus", "5", "(", "cytomegalovirus", ")", ",", "Human", "herpesvirus", "6", "(", "roseolovirus", ")", ",", "Human", "parechovirus", ",", "\n", "Enterovirus", "A", ",", "Cardiovirus", ",", "sequences", "of", "human", "endogenous", "retroviruses", ",", "and", "most", "importantly", ",", "various", "anelloviridae", "\n", "(", "Alpha-", ",", "Beta", "and", "Gammatorquevirus", "of", "various", "species", ")", ".", "Anelloviruses", "were", "partly", "covered", "by", "specific", "PCR", "testing", "in", "\n", "one", "of", "our", "previous", "studies", "on", "CD", "(", "Tapia", ",", "Chuda", "et", "al", ".", "2020", ")", "-", "therein", "published", "exploration", "using", "a", "single", "real", "-", "time", "PCR", "\n", "reaction", "did", "not", "however", "cover", "the", "whole", "spectrum", "of", "anelloviruses", "known", "today", ".", "\n", "Notably", ",", "although", "our", "metagenomic", "protocol", "was", "primarily", "designed", "to", "find", "DNA", "viruses", ",", "the", "signal", "included", "many", "\n", "known", "RNA", "viruses", "that", "commonly", "infect", "children", ".", "These", "included", "rotavirus", ",", "enterovirus", "and", "parechovirus", ".", "It", "is", "well", "\n", "known", "that", "DNA", "polymerases", "also", "have", "some", "RNA", "-", "dependent", "DNA", "polymerase", "activity", ",", "which", "is", "inconsistently", "reflected", "\n", "in", "these", "signals", ".", "\n", "Signals", "from", "human", "viruses", ",", "except", "Anelloviridae", ",", "did", "not", "meet", "the", "criteria", "for", "association", "testing", "(", "too", "few", "positive", "\n", "samples", "or", "too", "few", "positive", "individuals", "would", "preclude", "meaningful", "testing", ")", ".", "The", "human", "virus", "data", "will", "be", "reported", "in", "a", "\n", "paper", "together", "with", "the", "bacteriophage", "data", ".", "\n", "2.3.3", "Known", "bacteriophages", "and", "novel", "viruses", "from", "the", "dark", "matter", "\n", "The", "DNA", "virome", "was", "dominated", "by", "bacteriophage", "genomes", ",", "but", "a", "large", "fraction", "of", "the", "viromes", "was", "unidentifiable", "prior", "\n", "to", "the", "novel", "virus", "extraction", "process", ".", "This", "unidentified", "fraction", "is", "commonly", "referred", "to", "as", "the", "dark", "matter", ".", "For", "example", ",", "\n", "the", "mean", "unidentified", "fraction", "in", "samples", "from", "the", "Finnish", "DIPP", "study", "was", "95.5", "%", "against", "a", "collection", "of", "full", "-", "length", "and", "\n", "near", "-", "full", "-", "length", "viral", "sequences", "from", "NCBI", "GenBank", ",", "70.0", "%", "against", "(", "Camarillo", "-", "Guerrero", ",", "Almeida", "et", "al", ".", "2021", ")", ";", "88.9", "%", "\n", "against", "(", "Gregory", ",", "Zablocki", "et", "al", ".", "2020", ")", ";", "70.7", "%", "against", "(", "Shah", ",", "Deng", "et", "al", ".", "2023", ")", ".", "\n", "As", "the", "authors", "of", "the", "latter", "publications", "are", "Partner", "20", "in", "this", "project", ",", "and", "because", "of", "the", "exceptionally", "high", "quality", "of", "\n", "their", "annotated", "non", "-", "redundant", "database", ",", "we", "decided", "to", "use", "their", "protocols", "and", "experience", "to", "construct", "a", "novel", "viral", "\n", "database", "of", "the", "dark", "matter", "observed", "in", "both", "MIDIA", "and", "DIPP", "studies", ".", "\n", "Using", "methods" ]	[ { "end": 946, "label": "CITATION_REF", "start": 922 }, { "end": 941, "label": "AUTHOR", "start": 922 }, { "end": 946, "label": "YEAR", "start": 942 }, { "end": 2263, "label": "CITATION_REF", "start": 2224 }, { "end": 2258, "label": "AUTHOR", "start": 2224 }, { "end": 2263, "label": "YEAR", "start": 2259 }, { "end": 2310, "label": "CITATION_REF", "start": 2281 }, { "end": 2305, "label": "AUTHOR", "start": 2281 }, { "end": 2310, "label": "YEAR", "start": 2306 }, { "end": 2350, "label": "CITATION_REF", "start": 2328 }, { "end": 2350, "label": "YEAR", "start": 2346 }, { "end": 2345, "label": "AUTHOR", "start": 2328 } ]
880 PublicationsFigure 3.55. Number of publications and EC projects in collaboration between EaP actors in different countries, in the ‘Health and wellbeing’ domain Colour indicates the relative distribution of documents, computed row-wise. AM AZ BY GE MD UA Other 2 9 10 10 9 14 2 2 2 2 2 2 9 2 9 8 8 16 10 2 9 10 10 17 10 2 8 10 8 18 9 2 8 10 8 32 EC projectsAM AZ BY GE MD UA Other AM 4 19 21 5 18 189 AZ 4 4 5 4 51 157 BY 19 4 18 13 71 787 GE 21 5 18 6 24 238 MD 5 4 13 6 14 72 UA 18 51 71 24 14 2 730 PublicationsFigure 3.56. Number of publications and EC projects in collaboration between EaP actors in different countries, in the ‘ICT and computer science’ domain Colour indicates the relative distribution of documents, computed row-wise. Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation215 Regional collaboration in Mechanical en- gineering and heavy machinery In terms of publications, there are very few collab- orations in the domain of Mechanical engineer- ing and heavy machinery. Most collaborations are with external partners. There are very few collaborations on EC projects.Regional collaboration in Nanotechnolo- gy and materials In the case of Nanotechnology and materials publications, external collaborations again have a significant weight throughout all six EaP countries. Within the EaP, some of the highest-intensity col- laborations are Armenia and Georgia. For all coun- tries, Ukraine is one of the most relevant partners. The number of EC project collaborations is again very low, with Ukraine having the highest number of collaborations with one another and across the EaP. AM AZ BY GE MD UA Other 1 1 1 1 4 EC projectsAM AZ BY GE MD UA Other AM 1 2 1 38 AZ 1 2 97 BY 2 2 1 18 189 GE 1 2 1 4 23 MD 1 1 4 61 UA 2 18 4 4 1 154 PublicationsFigure 3.57. Number of publications and EC projects in collaboration between EaP actors in different countries, in the ‘Mechanical engineering and heavy machinery’ domain Colour indicates the relative distribution of documents, computed row-wise. AM AZ BY GE MD UA Other 3 2 3 5 1 1 1 3 1 2 2 13 28 2 2 3 4	[ "880", "\n", "PublicationsFigure", "3.55", ".", "Number", "of", "publications", "and", "EC", "projects", "in", "collaboration", "between", "EaP", "actors", "in", "different", "countries", ",", "in", "the", "\n", "‘", "Health", "and", "wellbeing", "’", "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", "2", "9", "10", "10", "9", "14", "\n", "2", "2", "2", "2", "2", "2", "\n", "9", "2", "9", "8", "8", "16", "\n", "10", "2", "9", "10", "10", "17", "\n", "10", "2", "8", "10", "8", "18", "\n", "9", "2", "8", "10", "8", "32", "\n", "EC", "projectsAM", "\n", "AZ", "\n", "BY", "\n", "GE", "\n", "MD", "\n", "UA", "\n", "Other", "\n", "AM", "4", "19", "21", "5", "18", "189", "\n", "AZ", "4", "4", "5", "4", "51", "157", "\n", "BY", "19", "4", "18", "13", "71", "787", "\n", "GE", "21", "5", "18", "6", "24", "238", "\n", "MD", "5", "4", "13", "6", "14", "72", "\n", "UA", "18", "51", "71", "24", "14", "2", "730", "\n", "PublicationsFigure", "3.56", ".", "Number", "of", "publications", "and", "EC", "projects", "in", "collaboration", "between", "EaP", "actors", "in", "different", "countries", ",", "in", "the", "\n", "‘", "ICT", "and", "computer", "science", "’", "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", "cooperation215", "\n", "Regional", "collaboration", "in", "Mechanical", "en-", "\n", "gineering", "and", "heavy", "machinery", "\n", "In", "terms", "of", "publications", ",", "there", "are", "very", "few", "collab-", "\n", "orations", "in", "the", "domain", "of", "Mechanical", "engineer-", "\n", "ing", "and", "heavy", "machinery", ".", "Most", "collaborations", "\n", "are", "with", "external", "partners", ".", "\n", "There", "are", "very", "few", "collaborations", "on", "EC", "projects", ".", "Regional", "collaboration", "in", "Nanotechnolo-", "\n", "gy", "and", "materials", "\n", "In", "the", "case", "of", "Nanotechnology", "and", "materials", "\n", "publications", ",", "external", "collaborations", "again", "have", "a", "\n", "significant", "weight", "throughout", "all", "six", "EaP", "countries", ".", "\n", "Within", "the", "EaP", ",", "some", "of", "the", "highest", "-", "intensity", "col-", "\n", "laborations", "are", "Armenia", "and", "Georgia", ".", "For", "all", "coun-", "\n", "tries", ",", "Ukraine", "is", "one", "of", "the", "most", "relevant", "partners", ".", "\n", "The", "number", "of", "EC", "project", "collaborations", "is", "again", "\n", "very", "low", ",", "with", "Ukraine", "having", "the", "highest", "number", "of", "\n", "collaborations", "with", "one", "another", "and", "across", "the", "EaP.", "\n", "AM", "\n", "AZ", "\n", "BY", "\n", "GE", "\n", "MD", "\n", "UA", "\n", "Other", "\n", "1", "1", "\n", "1", "\n", "1", "4", "\n", "EC", "projectsAM", "\n", "AZ", "\n", "BY", "\n", "GE", "\n", "MD", "\n", "UA", "\n", "Other", "\n", "AM", "1", "2", "1", "38", "\n", "AZ", "1", "2", "97", "\n", "BY", "2", "2", "1", "18", "189", "\n", "GE", "1", "2", "1", "4", "23", "\n", "MD", "1", "1", "4", "61", "\n", "UA", "2", "18", "4", "4", "1", "154", "\n", "PublicationsFigure", "3.57", ".", "Number", "of", "publications", "and", "EC", "projects", "in", "collaboration", "between", "EaP", "actors", "in", "different", "countries", ",", "in", "the", "\n", "‘", "Mechanical", "engineering", "and", "heavy", "machinery", "’", "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", "3", "2", "3", "5", "\n", "1", "1", "1", "\n", "3", "1", "2", "2", "13", "28", "\n", "2", "2", "3", "4", "\n" ]	[]
oversaw the chemical 110 Negotiating in/visibility department of Baghdad’s largest department store, granted my request and ordered medicines from several Czechoslovak pharmaceutical factories. The surgery was not even finished yet, and already patients were coming in. Or their family members with requests for medical consultation.44 It is obvious that after the opening of the clinic in the spring of 1925, Vlasta Kálalová was quite busy with various arrangements for her apartment and office, so that she did not have much time to write letters, but the letters that have been preserved are an important source to understand her life there: ‘I just want to keep busy now. There’s not that much work yet. The average daily income just covers the expenses (which are quite considerable here, at least CZK150 a day), only the operations are a welcome plus.’45 In July 1925, the necessary surgical equipment arrived from Prague and in September, Ruth Tobolářová arrived in Baghdad. In October 1925, when Masaryk received a further report on the development of the Czech ‘enclave’, Vlasta already had her regular patients and an important assistant in the person of nurse Ruth Tobolářová and could therefore afford to rent a larger house in a better area of the town. She found a suitable house that was larger than the previous one and could also accommodate rooms for post- operative patients. The house was situated in the centre of the city and was easily accessible for her patients: I rented a spacious house (10 rooms on the first floor with a kitchen, cool rooms for summer and servants’ quarters on the ground floor) for Rs. 3000 per year. My house is still being repaired and we will be able to move in about a week. It will have, besides the consulting room, rooms for diathermy and a waiting room, quite a nice operating theatre and two large rooms for patients, which can accommodate 8– 10 beds, and a third room can be added later!46 The new house, known as the Burazanli House, was repaired during the autumn (she moved in on 7 November 1925) and adapted to the needs of a small clinic. On 15 December, by a decree of the Baghdad director of health, the activity of the ‘Czekoslovak Mustausaf’47 was authorized. ‘Mustausaf’ indicated, according to Kálalová, a dispensary or small private clinic, and was a general term used for a medical facility with	[ "oversaw", "the", "chemical", " \n \n \n \n \n \n \n", "110", "\n ", "Negotiating", "in", "/", "visibility", "\n", "department", "of", "Baghdad", "’s", "largest", "department", "store", ",", "granted", "my", "request", "and", "\n", "ordered", "medicines", "from", "several", "Czechoslovak", "pharmaceutical", "factories", ".", "The", "\n", "surgery", "was", "not", "even", "finished", "yet", ",", "and", "already", "patients", "were", "coming", "in", ".", "Or", "\n", "their", "family", "members", "with", "requests", "for", "medical", "consultation.44", "\n", "It", "is", "obvious", "that", "after", "the", "opening", "of", "the", "clinic", "in", "the", "spring", "of", "1925", ",", "Vlasta", "\n", "Kálalová", "was", "quite", "busy", "with", "various", "arrangements", "for", "her", "apartment", "and", "\n", "office", ",", "so", "that", "she", "did", "not", "have", "much", "time", "to", "write", "letters", ",", "but", "the", "letters", "that", "\n", "have", "been", "preserved", "are", "an", "important", "source", "to", "understand", "her", "life", "there", ":", "‘", "I", "\n", "just", "want", "to", "keep", "busy", "now", ".", "There", "’s", "not", "that", "much", "work", "yet", ".", "The", "average", "\n", "daily", "income", "just", "covers", "the", "expenses", "(", "which", "are", "quite", "considerable", "here", ",", "at", "\n", "least", "CZK150", "a", "day", ")", ",", "only", "the", "operations", "are", "a", "welcome", "plus", ".", "’45", "\n", "In", "July", "1925", ",", "the", "necessary", "surgical", "equipment", "arrived", "from", "Prague", "\n", "and", "in", "September", ",", "Ruth", "Tobolářová", "arrived", "in", "Baghdad", ".", "In", "October", "1925", ",", "\n", "when", "Masaryk", "received", "a", "further", "report", "on", "the", "development", "of", "the", "Czech", "\n", "‘", "enclave", "’", ",", "Vlasta", "already", "had", "her", "regular", "patients", "and", "an", "important", "assistant", "\n", "in", "the", "person", "of", "nurse", "Ruth", "Tobolářová", "and", "could", "therefore", "afford", "to", "rent", "\n", "a", "larger", "house", "in", "a", "better", "area", "of", "the", "town", ".", "She", "found", "a", "suitable", "house", "that", "\n", "was", "larger", "than", "the", "previous", "one", "and", "could", "also", "accommodate", "rooms", "for", "\n", "post-", " ", "operative", "patients", ".", "The", "house", "was", "situated", "in", "the", "centre", "of", "the", "city", "and", "\n", "was", "easily", "accessible", "for", "her", "patients", ":", "\n", "I", "rented", "a", "spacious", "house", "(", "10", "rooms", "on", "the", "first", "floor", "with", "a", "kitchen", ",", "cool", "\n", "rooms", "for", "summer", "and", "servants", "’", "quarters", "on", "the", "ground", "floor", ")", "for", "Rs", ".", "3000", "\n", "per", "year", ".", "My", "house", "is", "still", "being", "repaired", "and", "we", "will", "be", "able", "to", "move", "in", "about", "\n", "a", "week", ".", "It", "will", "have", ",", "besides", "the", "consulting", "room", ",", "rooms", "for", "diathermy", "and", "a", "\n", "waiting", "room", ",", "quite", "a", "nice", "operating", "theatre", "and", "two", "large", "rooms", "for", "patients", ",", "\n", "which", "can", "accommodate", "8", "–", " ", "10", "beds", ",", "and", "a", "third", "room", "can", "be", "added", "later!46", "\n", "The", "new", "house", ",", "known", "as", "the", "Burazanli", "House", ",", "was", "repaired", "during", "the", "\n", "autumn", "(", "she", "moved", "in", "on", "7", "November", "1925", ")", "and", "adapted", "to", "the", "needs", "\n", "of", "a", "small", "clinic", ".", "On", "15", "December", ",", "by", "a", "decree", "of", "the", "Baghdad", "director", "\n", "of", "health", ",", "the", "activity", "of", "the", "‘", "Czekoslovak", "Mustausaf’47", "was", "authorized", ".", "\n", "‘", "Mustausaf", "’", "indicated", ",", "according", "to", "Kálalová", ",", "a", "dispensary", "or", "small", "private", "\n", "clinic", ",", "and", "was", "a", "general", "term", "used", "for", "a", "medical", "facility", "with" ]	[ { "end": 354, "label": "CITATION_REF", "start": 352 }, { "end": 885, "label": "CITATION_REF", "start": 883 }, { "end": 1986, "label": "CITATION_REF", "start": 1984 }, { "end": 2252, "label": "CITATION_REF", "start": 2250 } ]
44 19 Environmental sciences and industries 1 331 614 710 623 368 383 263 253 172 188 Fundamental physics and mathematics 5 398 4 606 3 907 4 495 3 734 3 438 3 608 3 123 3 028 2 832 Governance, culture, education and the economy 903 438 687 675 279 453 240 211 146 155 Health and wellbeing 1 731 1 414 1 249 2 126 986 1 465 925 707 366 599 ICT and computer science 678 496 823 466 383 201 189 137 281 121 Mechanical engineering and heavy machinery 388 182 319 96 67 60 55 30 55 23 Nanotechnology and materials 4 197 2 452 2 526 1 568 1 202 649 435 461 523 283 Optics and photonics 1 054 573 372 483 300 200 147 182 211 57 Transportation 70 67 104 42 15 24 8 9 23 2 PublicationsGermany France United Kingdom Spain Italy Belgium Greece Netherlands Poland Romania Agrifood 12 14 7 14 14 11 9 13 5 8 Biotechnology 12 10 13 9 7 5 5 6 10 4 Chemistry and chemical engineering 9 5 5 4 4 4 3 3 3 3 Electric and electronic technologies 6 4 5 3 5 4 4 1 Energy 40 23 22 24 25 28 17 14 15 19 Environmental sciences and industries 51 42 36 42 41 36 26 31 23 28 Fundamental physics and mathematics 7 6 6 5 5 2 2 2 4 3 Governance, culture, education and the economy 138 115 99 106 109 93 83 76 77 71 Health and wellbeing 34 26 29 27 21 16 12 17 14 10 ICT and computer science 37 33 37 39 34 29 29 24 22 22 Mechanical engineering and heavy machinery 3 1 4 1 2 2 1 2 2 Nanotechnology and materials 33 23 29 18 20 13 12 5 11 3 Optics and photonics 10 8 7 3 6 2 4 Transportation 17 10 13 11 13 11 8 7 8 5 EC projectsFigure 3.61. Number of publications and EC projects in collaboration between EaP actors and partners outside of the EaP Colour indicates the relative distribution, computed row-wise. 218 Part 3 Analysis of scientific and technological potential Extra-EaP international collaboration This last section of the chapter presents indicators of collaboration activity between EaP countries and external international partners. The Russian Federation was so far the	[ "44", "19", "\n", "Environmental", "sciences", "and", "industries", "1", "331", "614", "710", "623", "368", "383", "263", "253", "172", "188", "\n", "Fundamental", "physics", "and", "mathematics", "5", "398", "4", "606", "3", "907", "4", "495", "3", "734", "3", "438", "3", "608", "3", "123", "3", "028", "2", "832", "\n", "Governance", ",", "culture", ",", "education", "and", "the", "economy", "903", "438", "687", "675", "279", "453", "240", "211", "146", "155", "\n", "Health", "and", "wellbeing", "1", "731", "1", "414", "1", "249", "2", "126", "986", "1", "465", "925", "707", "366", "599", "\n", "ICT", "and", "computer", "science", "678", "496", "823", "466", "383", "201", "189", "137", "281", "121", "\n", "Mechanical", "engineering", "and", "heavy", "machinery", "388", "182", "319", "96", "67", "60", "55", "30", "55", "23", "\n", "Nanotechnology", "and", "materials", "4", "197", "2", "452", "2", "526", "1", "568", "1", "202", "649", "435", "461", "523", "283", "\n", "Optics", "and", "photonics", "1", "054", "573", "372", "483", "300", "200", "147", "182", "211", "57", "\n", "Transportation", "70", "67", "104", "42", "15", "24", "8", "9", "23", "2", "\n", "PublicationsGermany", "\n", "France", "\n", "United", "\n", "Kingdom", "\n", "Spain", "\n", "Italy", "\n", "Belgium", "\n", "Greece", "\n", "Netherlands", "\n", "Poland", "\n", "Romania", "\n", "Agrifood", "12", "14", "7", "14", "14", "11", "9", "13", "5", "8", "\n", "Biotechnology", "12", "10", "13", "9", "7", "5", "5", "6", "10", "4", "\n", "Chemistry", "and", "chemical", "engineering", "9", "5", "5", "4", "4", "4", "3", "3", "3", "3", "\n", "Electric", "and", "electronic", "technologies", "6", "4", "5", "3", "5", "4", "4", "1", "\n", "Energy", "40", "23", "22", "24", "25", "28", "17", "14", "15", "19", "\n", "Environmental", "sciences", "and", "industries", "51", "42", "36", "42", "41", "36", "26", "31", "23", "28", "\n", "Fundamental", "physics", "and", "mathematics", "7", "6", "6", "5", "5", "2", "2", "2", "4", "3", "\n", "Governance", ",", "culture", ",", "education", "and", "the", "economy", "138", "115", "99", "106", "109", "93", "83", "76", "77", "71", "\n", "Health", "and", "wellbeing", "34", "26", "29", "27", "21", "16", "12", "17", "14", "10", "\n", "ICT", "and", "computer", "science", "37", "33", "37", "39", "34", "29", "29", "24", "22", "22", "\n", "Mechanical", "engineering", "and", "heavy", "machinery", "3", "1", "4", "1", "2", "2", "1", "2", "2", "\n", "Nanotechnology", "and", "materials", "33", "23", "29", "18", "20", "13", "12", "5", "11", "3", "\n", "Optics", "and", "photonics", "10", "8", "7", "3", "6", "2", "4", "\n", "Transportation", "17", "10", "13", "11", "13", "11", "8", "7", "8", "5", "\n", "EC", "projectsFigure", "3.61", ".", "Number", "of", "publications", "and", "EC", "projects", "in", "collaboration", "between", "EaP", "actors", "and", "partners", "outside", "of", "the", "\n", "EaP", "\n", "Colour", "indicates", "the", "relative", "distribution", ",", "computed", "row", "-", "wise", ".", "\n", "218", "\n ", "Part", "3", "Analysis", "of", "scientific", "and", "technological", "potential", "\n", "Extra", "-", "EaP", "international", "collaboration", "\n", "This", "last", "section", "of", "the", "chapter", "presents", "indicators", "\n", "of", "collaboration", "activity", "between", "EaP", "countries", "\n", "and", "external", "international", "partners", ".", "\n", "The", "Russian", "Federation", "was", "so", "far", "the" ]	[]
be used interchangeably. Additionally, although the term “ML algorithm” may refer to different concepts than the term “ML model,” these terms may be used interchangeably for the purposes of the present disclosure. The term “machine learning application” or “ML application” at least in some examples refers to an application, program, process, algorithm, and/or function that contains some AI/ML model(s) and application-level descriptions. Additionally or alternatively, the term “machine learning application” or “ML application” at least in some examples refers to a complete and deployable application and/or package that includes at least one ML model and/or other data capable of achieving a certain function and/or performing a set of actions or tasks in an operational environment. For purposes of the present disclosure, the terms “ML application”, “AI application”, “AI/ML application”, and the like may be used interchangeably. The term “matrix” at least in some examples refers to a rectangular array of numbers, symbols, or expressions, arranged in rows and columns, which may be used to represent an object or a property of such an object. The terms “model parameter” and/or “parameter” in the context of ML, at least in some examples refer to values, characteristics, and/or properties that are learnt during training. Additionally or alternatively, “model parameter” and/or “parameter” in the context of ML, at least in some examples refer to a configuration variable that is internal to the model and whose value can be estimated from the given data. Model parameters are usually required by a model when making predictions, and their values define the skill of the model on a particular problem. Examples of such model parameters/parameters include weights (e.g., in an ANN); constraints; support vectors in a support vector machine (SVM); coefficients in a linear regression and/or logistic regression; word frequency, sentence length, noun or verb distribution per sentence, the number of specific character n-grams per word, lexical diversity, and the like, for natural language processing (NLP) and/or natural language understanding (NLU); and/or the like. The term “objective function” at least in some examples refers to a function to be maximized or minimized for a specific optimization problem. In some cases, an objective function is defined by its decision variables and an objective. The objective is the value, target, or goal to be optimized, such as maximizing profit or minimizing usage of a particular resource. The specific objective function chosen depends on the specific problem to be solved	[ "be", "used", "interchangeably", ".", "Additionally", ",", "although", "the", "term", "“", "ML", "algorithm", "”", "may", "refer", "to", "different", "concepts", "than", "the", "term", "“", "ML", "model", ",", "”", "these", "terms", "may", "be", "used", "interchangeably", "for", "the", "purposes", "of", "the", "present", "disclosure", ".", "\n\n", "The", "term", "“", "machine", "learning", "application", "”", "or", "“", "ML", "application", "”", "at", "least", "in", "some", "examples", "refers", "to", "an", "application", ",", "program", ",", "process", ",", "algorithm", ",", "and/or", "function", "that", "contains", "some", "AI", "/", "ML", "model(s", ")", "and", "application", "-", "level", "descriptions", ".", "Additionally", "or", "alternatively", ",", "the", "term", "“", "machine", "learning", "application", "”", "or", "“", "ML", "application", "”", "at", "least", "in", "some", "examples", "refers", "to", "a", "complete", "and", "deployable", "application", "and/or", "package", "that", "includes", "at", "least", "one", "ML", "model", "and/or", "other", "data", "capable", "of", "achieving", "a", "certain", "function", "and/or", "performing", "a", "set", "of", "actions", "or", "tasks", "in", "an", "operational", "environment", ".", "For", "purposes", "of", "the", "present", "disclosure", ",", "the", "terms", "“", "ML", "application", "”", ",", "“", "AI", "application", "”", ",", "“", "AI", "/", "ML", "application", "”", ",", "and", "the", "like", "may", "be", "used", "interchangeably", ".", "\n\n", "The", "term", "“", "matrix", "”", "at", "least", "in", "some", "examples", "refers", "to", "a", "rectangular", "array", "of", "numbers", ",", "symbols", ",", "or", "expressions", ",", "arranged", "in", "rows", "and", "columns", ",", "which", "may", "be", "used", "to", "represent", "an", "object", "or", "a", "property", "of", "such", "an", "object", ".", "\n\n", "The", "terms", "“", "model", "parameter", "”", "and/or", "“", "parameter", "”", "in", "the", "context", "of", "ML", ",", "at", "least", "in", "some", "examples", "refer", "to", "values", ",", "characteristics", ",", "and/or", "properties", "that", "are", "learnt", "during", "training", ".", "Additionally", "or", "alternatively", ",", "“", "model", "parameter", "”", "and/or", "“", "parameter", "”", "in", "the", "context", "of", "ML", ",", "at", "least", "in", "some", "examples", "refer", "to", "a", "configuration", "variable", "that", "is", "internal", "to", "the", "model", "and", "whose", "value", "can", "be", "estimated", "from", "the", "given", "data", ".", "Model", "parameters", "are", "usually", "required", "by", "a", "model", "when", "making", "predictions", ",", "and", "their", "values", "define", "the", "skill", "of", "the", "model", "on", "a", "particular", "problem", ".", "Examples", "of", "such", "model", "parameters", "/", "parameters", "include", "weights", "(", "e.g.", ",", "in", "an", "ANN", ")", ";", "constraints", ";", "support", "vectors", "in", "a", "support", "vector", "machine", "(", "SVM", ")", ";", "coefficients", "in", "a", "linear", "regression", "and/or", "logistic", "regression", ";", "word", "frequency", ",", "sentence", "length", ",", "noun", "or", "verb", "distribution", "per", "sentence", ",", "the", "number", "of", "specific", "character", "n", "-", "grams", "per", "word", ",", "lexical", "diversity", ",", "and", "the", "like", ",", "for", "natural", "language", "processing", "(", "NLP", ")", "and/or", "natural", "language", "understanding", "(", "NLU", ")", ";", "and/or", "the", "like", ".", "\n\n", "The", "term", "“", "objective", "function", "”", "at", "least", "in", "some", "examples", "refers", "to", "a", "function", "to", "be", "maximized", "or", "minimized", "for", "a", "specific", "optimization", "problem", ".", "In", "some", "cases", ",", "an", "objective", "function", "is", "defined", "by", "its", "decision", "variables", "and", "an", "objective", ".", "The", "objective", "is", "the", "value", ",", "target", ",", "or", "goal", "to", "be", "optimized", ",", "such", "as", "maximizing", "profit", "or", "minimizing", "usage", "of", "a", "particular", "resource", ".", "The", "specific", "objective", "function", "chosen", "depends", "on", "the", "specific", "problem", "to", "be", "solved" ]	[]
and the Maison de la Culture, founded in 2017 , which protects and promotes Rundi literature. The Ministry also manages the operations of the National Library. With regard to schoolbooks, the materials used in basic and post-basic education are published by pedagogical offices operating through the Pedagogical Production Management (Régie de Production Pédagogique – RPP), which functions as a publishing house. The legal framework for the book sector is limited to Law No. 1/021 of December 30, 2005 on the protection of copyright and related rights. 4 PUBLIC POLICIES AND MEASURES There are no tax exemptions, reduced rates, or fiscal incentives applicable to the book and publishing sector, as confirmed by the national authority’s response to the survey. The Cultural Policy of Burundi, which dates back to 2007 and the update of which been expected since 2022, encourages the promotion of books, notably by recommending the creation of literary prizes to encourage writing.	[ "and", "the", "Maison", "de", "la", "Culture", ",", "founded", "in", "2017", ",", "which", "protects", "and", "promotes", "Rundi", "literature", ".", "The", "Ministry", "also", "manages", "the", "operations", "of", "the", "National", "Library", ".", "With", "regard", "to", "schoolbooks", ",", "the", "materials", "\n", "used", "in", "basic", "and", "post", "-", "basic", "education", "are", "published", "by", "pedagogical", "offices", "operating", "through", "the", "Pedagogical", "Production", "Management", "(", "Régie", "de", "Production", "Pédagogique", "–", "RPP", ")", ",", "which", "functions", "as", "a", "publishing", "house", ".", "\n", "The", "legal", "framework", "for", "the", "book", "\n", "sector", "is", "limited", "to", "Law", "No", ".", "1/021", "of", "December", "30", ",", "2005", "on", "the", "protection", "of", "copyright", "and", "related", "rights", ".", "\n", "4", "\n", "PUBLIC", "POLICIES", "AND", "MEASURES", "\n", "There", "are", "no", "tax", "exemptions", ",", "reduced", "rates", ",", "or", "fiscal", "incentives", "applicable", "to", "the", "book", "and", "publishing", "sector", ",", "as", "confirmed", "by", "the", "national", "authority", "’s", "response", "to", "the", "survey", ".", "The", "Cultural", "Policy", "of", "Burundi", ",", "which", "dates", "back", "to", "2007", "and", "the", "update", "of", "which", "been", "expected", "since", "2022", ",", "encourages", "the", "promotion", "of", "books", ",", "notably", "by", "recommending", "the", "creation", "of", "literary", "prizes", "to", "encourage", "writing", "." ]	[]
- 1. Fathallah F, Meyers J, Chapman L, Karsh B. Ergonomic industrial interventions: agriculture. Occupational Ergonomics Handbook. 2006. - 2. Rosecrance J, Rodgers G, Merlino L. Low back pain and musculoskeletal symptoms among Kansas farmers. Am J Ind Med. 2006;49(7):547 -56. - 3. Health and Safety Executive H. Self-reported work-related illness and workplace injuries in 2005. 2007. - 4. Osborne A, Blake C, Fullen BM, Meredith D, Phelan J, McNamara J, et al. Prevalence of musculoskeletal disorders - among farmers: a systematic review. Am J Ind Med. 2012;55:143 -58. - 5. Holmberg S, Stiernström E-L, Thelin A, Svärdsudd K. Musculoskeletal symptoms among farmers and non-farmers: a population-based study. Int J Occup Environ Health. 2002;8: 339 45. - - 6. Skovron ML, Szpalski M, Nordin M, Melot C, Cukier D. Sociocultural factors and back pain. A population-based study in Belgian adults. Spine (Phila Pa 1976). 1994;19(2):129 -37.7. - 7. Kolstrup CL. Work-related musculoskeletal discomfort of dairy farmers and employed workers. J Occup Med Toxicol. 2012; 7:23. - 8. Chapman L, Meyers J. Ergonomics and musculoskeletal injuries in agriculture: recognizing and preventing the industry s ' most widespread health and safety problem; 2001. - 9. Blondell J. Epidemiology of pesticide poisonings in the United States, with special reference to occupational cases. Occup Med. 1997;12(2):209 -20. - 10. Kirkhorn S, Greenlee RT, Reeser JC. The epidemiology of agriculture-related osteoarthritis and its impact on occupational disability. WMJ. 2003;102:38 -44. - 11. KOrean Statistical Information Service (KOSIS) [homepage on the Internet]: Statistics Korea; c2015 [cited 2015 March 22nd]. Available from: http://kosis.kr/statHtml/statHtml.do?orgId= 101&tblId=DT\_1IN0001\_32&conn\_path=I2. - 12. Lee KH, Koh SB, Kang D, Chung JJ, Kim HR, Kim IA, et al. Job stress and self-perceived fatigue in Korean farmers. Korean J Occup Environ Med. 2011;23:213 -24. - 13. Fairbank JC, Pynsent PB. The Oswestry Disability Index. Spine (Phila Pa 1976). 2000;25(22):2940 -52. - 14. Hwang HS, Kwon IS, Park BJ, Cho B, Yoon JL, Won CW. The validity and reliability of Korean frailty index. J Korean Geriatr Soc. 2010;14:191 -202. - 15. DY KOSaHAIP. Questionnaire for musculoskeletal symptoms. Guideline for evaluation of risk factors for musculoskeletal disorders. 2003:P.A 10-1. - 16. Jo MW, Yun SC, Lee SI. Estimating quality weights for EQ-5D health states with the time trade-off method in South Korea. Value Health. 2008;11:1186 -9. - 17. Jeong G. Handbook for safety management in agricultural work Gyeonggi-do. Rural Development Administration; 2003. - 18. Shealy CN. A review of dehydroepiandrosterone (DHEA). Integr Physiol Behav Sci. 1995;30:308 -13.	[ "-", "1", ".", "Fathallah", "F", ",", "Meyers", "J", ",", "Chapman", "L", ",", "Karsh", "B.", "Ergonomic", "industrial", "interventions", ":", "agriculture", ".", "Occupational", "Ergonomics", "Handbook", ".", "2006", ".", "\n", "-", "2", ".", "Rosecrance", "J", ",", "Rodgers", "G", ",", "Merlino", "L.", "Low", "back", "pain", "and", "musculoskeletal", "symptoms", "among", "Kansas", "farmers", ".", "Am", "J", "Ind", "Med", ".", "2006;49(7):547", "-56", ".", "\n", "-", "3", ".", "Health", "and", "Safety", "Executive", "H.", "Self", "-", "reported", "work", "-", "related", "illness", "and", "workplace", "injuries", "in", "2005", ".", "2007", ".", "\n", "-", "4", ".", "Osborne", "A", ",", "Blake", "C", ",", "Fullen", "BM", ",", "Meredith", "D", ",", "Phelan", "J", ",", "McNamara", "J", ",", "et", "al", ".", "Prevalence", "of", "musculoskeletal", "disorders", "\n", "-", "among", "farmers", ":", "a", "systematic", "review", ".", "Am", "J", "Ind", "Med", ".", "2012;55:143", "-58", ".", "\n", "-", "5", ".", "Holmberg", "S", ",", "Stiernström", "E", "-", "L", ",", "Thelin", "A", ",", "Svärdsudd", "K.", "Musculoskeletal", "symptoms", "among", "farmers", "and", "non", "-", "farmers", ":", "a", "population", "-", "based", "study", ".", "Int", "J", "Occup", "Environ", "Health", ".", "2002;8", ":", "339", "45", ".", "-", "\n", "-", "6", ".", "Skovron", "ML", ",", "Szpalski", "M", ",", "Nordin", "M", ",", "Melot", "C", ",", "Cukier", "D.", "Sociocultural", "factors", "and", "back", "pain", ".", "A", "population", "-", "based", "study", "in", "Belgian", "adults", ".", "Spine", "(", "Phila", "Pa", "1976", ")", ".", "1994;19(2):129", "-37.7", ".", "\n", "-", "7", ".", "Kolstrup", "CL", ".", "Work", "-", "related", "musculoskeletal", "discomfort", "of", "dairy", "farmers", "and", "employed", "workers", ".", "J", "Occup", "Med", "Toxicol", ".", "2012", ";", "7:23", ".", "\n", "-", "8", ".", "Chapman", "L", ",", "Meyers", "J.", "Ergonomics", "and", "musculoskeletal", "injuries", "in", "agriculture", ":", "recognizing", "and", "preventing", "the", "industry", "s", "'", "most", "widespread", "health", "and", "safety", "problem", ";", "2001", ".", "\n", "-", "9", ".", "Blondell", "J.", "Epidemiology", "of", "pesticide", "poisonings", "in", "the", "United", "States", ",", "with", "special", "reference", "to", "occupational", "cases", ".", "Occup", "Med", ".", "1997;12(2):209", "-20", ".", "\n", "-", "10", ".", "Kirkhorn", "S", ",", "Greenlee", "RT", ",", "Reeser", "JC", ".", "The", "epidemiology", "of", "agriculture", "-", "related", "osteoarthritis", "and", "its", "impact", "on", "occupational", "disability", ".", "WMJ", ".", "2003;102:38", "-44", ".", "\n", "-", "11", ".", "KOrean", "Statistical", "Information", "Service", "(", "KOSIS", ")", "[", "homepage", "on", "the", "Internet", "]", ":", "Statistics", "Korea", ";", "c2015", "[", "cited", "2015", "March", "22nd", "]", ".", "Available", "from", ":", "http://kosis.kr/statHtml/statHtml.do?orgId=", "101&tblId", "=", "DT\\_1IN0001\\_32&conn\\_path", "=", "I2", ".", "\n", "-", "12", ".", "Lee", "KH", ",", "Koh", "SB", ",", "Kang", "D", ",", "Chung", "JJ", ",", "Kim", "HR", ",", "Kim", "IA", ",", "et", "al", ".", "Job", "stress", "and", "self", "-", "perceived", "fatigue", "in", "Korean", "farmers", ".", "Korean", "J", "Occup", "Environ", "Med", ".", "2011;23:213", "-24", ".", "\n", "-", "13", ".", "Fairbank", "JC", ",", "Pynsent", "PB", ".", "The", "Oswestry", "Disability", "Index", ".", "Spine", "(", "Phila", "Pa", "1976", ")", ".", "2000;25(22):2940", "-52", ".", "\n", "-", "14", ".", "Hwang", "HS", ",", "Kwon", "IS", ",", "Park", "BJ", ",", "Cho", "B", ",", "Yoon", "JL", ",", "Won", "CW", ".", "The", "validity", "and", "reliability", "of", "Korean", "frailty", "index", ".", "J", "Korean", "Geriatr", "Soc", ".", "2010;14:191", "-202", ".", "\n", "-", "15", ".", "DY", "KOSaHAIP", ".", "Questionnaire", "for", "musculoskeletal", "symptoms", ".", "Guideline", "for", "evaluation", "of", "risk", "factors", "for", "musculoskeletal", "disorders", ".", "2003", ":", "P.A", "10", "-", "1", ".", "\n", "-", "16", ".", "Jo", "MW", ",", "Yun", "SC", ",", "Lee", "SI", ".", "Estimating", "quality", "weights", "for", "EQ-5D", "health", "states", "with", "the", "time", "trade", "-", "off", "method", "in", "South", "Korea", ".", "Value", "Health", ".", "2008;11:1186", "-9", ".", "\n", "-", "17", ".", "Jeong", "G.", "Handbook", "for", "safety", "management", "in", "agricultural", "work", "Gyeonggi", "-", "do", ".", "Rural", "Development", "Administration", ";", "2003", ".", "\n", "-", "18", ".", "Shealy", "CN", ".", "A", "review", "of", "dehydroepiandrosterone", "(", "DHEA", ")", ".", "Integr", "Physiol", "Behav", "Sci", ".", "1995;30:308", "-13", ".", "\n" ]	[ { "end": 3, "label": "CITATION_ID", "start": 2 }, { "end": 136, "label": "CITATION_SPAN", "start": 5 }, { "end": 140, "label": "CITATION_ID", "start": 139 }, { "end": 276, "label": "CITATION_SPAN", "start": 142 }, { "end": 280, "label": "CITATION_ID", "start": 279 }, { "end": 385, "label": "CITATION_SPAN", "start": 282 }, { "end": 389, "label": "CITATION_ID", "start": 388 }, { "end": 571, "label": "CITATION_SPAN", "start": 391 }, { "end": 575, "label": "CITATION_ID", "start": 574 }, { "end": 756, "label": "CITATION_SPAN", "start": 577 }, { "end": 760, "label": "CITATION_ID", "start": 759 }, { "end": 940, "label": "CITATION_SPAN", "start": 762 }, { "end": 944, "label": "CITATION_ID", "start": 943 }, { "end": 1070, "label": "CITATION_SPAN", "start": 946 }, { "end": 1074, "label": "CITATION_ID", "start": 1073 }, { "end": 1245, "label": "CITATION_SPAN", "start": 1076 }, { "end": 1249, "label": "CITATION_ID", "start": 1248 }, { "end": 1398, "label": "CITATION_SPAN", "start": 1251 }, { "end": 1403, "label": "CITATION_ID", "start": 1401 }, { "end": 1560, "label": "CITATION_SPAN", "start": 1405 }, { "end": 1565, "label": "CITATION_ID", "start": 1563 }, { "end": 1804, "label": "CITATION_ID", "start": 1802 }, { "end": 1969, "label": "CITATION_ID", "start": 1967 }, { "end": 2076, "label": "CITATION_ID", "start": 2074 }, { "end": 2228, "label": "CITATION_ID", "start": 2226 }, { "end": 2378, "label": "CITATION_ID", "start": 2376 }, { "end": 2536, "label": "CITATION_ID", "start": 2534 }, { "end": 2657, "label": "CITATION_ID", "start": 2654 }, { "end": 2754, "label": "CITATION_SPAN", "start": 2658 }, { "end": 2651, "label": "CITATION_SPAN", "start": 2538 }, { "end": 2531, "label": "CITATION_SPAN", "start": 2380 }, { "end": 2373, "label": "CITATION_SPAN", "start": 2230 }, { "end": 2223, "label": "CITATION_SPAN", "start": 2078 }, { "end": 2071, "label": "CITATION_SPAN", "start": 1971 }, { "end": 1964, "label": "CITATION_SPAN", "start": 1806 }, { "end": 1799, "label": "CITATION_SPAN", "start": 1567 } ]
teachers and had also been granted tenure around the same year. As those moments were almost simultaneous, one can conclude that age or generational traits did not have a significant impact on the opportunities that the new law opened for female doctors. Their professional paths seemed to have depended entirely on the financial capacity of the public school administration to accommodate them. ## Eliza Ștefănescu Eliza Ștefănescu was born in 1882 and studied medicine in Bucharest, obtaining her medical diploma in 1907. 61 In 1929, she was appointed school doctor at the Elena Doamna Normal School in Bucharest, and was paid a daily wage, along with other female physicians recently designated as school doctors at different girls' high schools in the city. 62 However, she was able to pass the special inspection that allowed her to get tenure only in 1934. By then, she had transferred to the Central School Marica Brâncoveanu, one of the most prestigious and oldest high schools for girls in Bucharest. According to the principal's recommendation, Eliza Ștefănescu had been appointed temporary school doctor in 1931; she was serving as both the boarding school's physician and hygiene teacher. Highly competent, with 1 6 3 a spotless reputation and genuinely interested in the well- being of her students, she was willing to pay medical visits at school outside her schedule. Having a good working relationship with all her colleagues and being a respected doctor, she was praised by the principal, who highly recommended her for tenure. Similar appreciation expressed the inspector who assisted her seventh- grade hygiene course on alcoholism and smoking, valuing her ability to relate and explain the lesson to make it intelligible to her teenage students: 'I too, along with her students, have listened with great pleasure and interest to the recommendations the doctor has made … to keep ourselves healthy.' Based on his report, there is no doubt that the inspector was truly impressed with doctor Ștefănescu s class activity and considered her worthy ʼ of getting tenure. 63 According to the doctor's 1941 yearbook, during the war she retained her teaching position and was still working as a physician at the Central School. However, seven years later, her name was missing from the medical catalogue published in 1948, a clear sign that she had passed away, since even the retired doctors were included in the volume. 64 ## Victoria Vasiliu The second	[ "teachers", "and", "had", "also", "been", "granted", "tenure", "around", "the", "same", "year", ".", "As", "those", "moments", "were", "almost", "simultaneous", ",", "one", "can", "conclude", "that", "age", "or", "generational", "traits", "did", "not", "have", "a", "significant", "impact", "on", "the", "opportunities", "that", "the", "new", "law", "opened", "for", "female", "doctors", ".", "Their", "professional", "paths", "seemed", "to", "have", "depended", "entirely", "on", "the", "financial", "capacity", "of", "the", "public", "school", "administration", "to", "accommodate", "them", ".", "\n\n", "#", "#", "Eliza", "Ștefănescu", "\n\n", "Eliza", " ", "Ștefănescu", " ", "was", " ", "born", " ", "in", " ", "1882", " ", "and", " ", "studied", " ", "medicine", " ", "in", " ", "Bucharest", ",", "obtaining", "her", "medical", "diploma", "in", "1907", ".", "61", " ", "In", "1929", ",", "she", "was", "appointed", "school", "doctor", "at", "the", "Elena", "Doamna", "Normal", "School", "in", "Bucharest", ",", "and", "was", "paid", "a", "daily", "wage", ",", "along", "with", "other", "female", "physicians", "recently", "designated", "as", "school", "doctors", "at", "different", "girls", "'", "high", "schools", "in", "the", "city", ".", "62", " ", "However", ",", "she", "was", "able", "to", "pass", "the", "special", "inspection", "that", "allowed", "her", "to", "get", "tenure", "only", "in", "1934", ".", "By", "then", ",", "she", "had", "transferred", "to", "the", "Central", "School", "Marica", "Brâncoveanu", ",", "one", "of", "the", "most", "prestigious", "and", "oldest", "high", "schools", "for", "girls", "in", "Bucharest", ".", "\n\n", "According", "to", "the", "principal", "'s", "recommendation", ",", "Eliza", "Ștefănescu", "had", "been", "appointed", "temporary", "school", "doctor", "in", "1931", ";", "she", "was", "serving", "as", "both", "the", "boarding", "school", "'s", "physician", "and", "hygiene", "teacher", ".", "Highly", "competent", ",", "with", "\n\n", "1", "\n\n", "6", "\n\n", "3", "\n\n", "a", "spotless", "reputation", "and", "genuinely", "interested", "in", "the", "well-", " ", "being", "of", "her", "students", ",", "she", "was", "willing", "to", "pay", "medical", "visits", "at", "school", "outside", "her", "schedule", ".", "Having", "a", "good", "working", "relationship", "with", "all", "her", "colleagues", "and", "being", "a", "respected", "doctor", ",", "she", "was", "praised", "by", "the", "principal", ",", "who", "highly", "recommended", "her", "for", "tenure", ".", "Similar", "appreciation", "expressed", "the", "inspector", "who", "assisted", "her", "seventh-", " ", "grade", "hygiene", "course", "on", "alcoholism", "and", "smoking", ",", "valuing", "her", "ability", "to", "relate", "and", "explain", "the", "lesson", "to", "make", "it", "intelligible", "to", "her", "teenage", "students", ":", "'", "I", "too", ",", "along", "with", "her", "students", ",", "have", "listened", "with", "great", "pleasure", "and", "interest", "to", "the", "recommendations", "the", "doctor", "has", "made", "…", "to", "keep", "ourselves", "healthy", ".", "'", "Based", "on", "his", "report", ",", "there", "is", "no", "doubt", "that", "the", "inspector", "was", "truly", "impressed", "with", "doctor", "Ștefănescu", "s", "class", "activity", "and", "considered", "her", "worthy", "ʼ", "of", "getting", "tenure", ".", "63", "\n\n", "According", "to", "the", "doctor", "'s", "1941", "yearbook", ",", "during", "the", "war", "she", "retained", "her", "teaching", "position", "and", "was", "still", "working", "as", "a", "physician", "at", "the", "Central", "School", ".", "However", ",", "seven", "years", "later", ",", "her", "name", "was", "missing", "from", "the", "medical", "catalogue", "published", "in", "1948", ",", "a", "clear", "sign", "that", "she", "had", "passed", "away", ",", "since", "even", "the", "retired", "doctors", "were", "included", "in", "the", "volume", ".", "64", "\n\n", "#", "#", "Victoria", "Vasiliu", "\n\n", "The", "second" ]	[ { "end": 538, "label": "CITATION_REF", "start": 536 }, { "end": 777, "label": "CITATION_REF", "start": 775 }, { "end": 2107, "label": "CITATION_REF", "start": 2105 }, { "end": 2456, "label": "CITATION_REF", "start": 2454 } ]
Carroll, J. M., O'Connor, R. E., & McDonald, C. A. (2004). Educational implications of reading achievement gaps: A study of students in the United States. Reading Research Quarterly, 39 (2), 164 -182. https://doi.org/10.1598/RRQ.39.2.3 Carter, E. (2008). Successful change requires more than change management. The Journal for Quality & Participation , 31 (1), 20 -23. Carter, P. L., & Welner, K. G. (2013). Closing the achievement gap: A synthesis of the literature on the role of schools in closing the achievement gap. In Handbook of educational policy research (pp. 2 -5, 74). Springer. Chetty, R., Friedman, J. N., & Rockoff, J. E. (2020). Measuring the impacts of teachers II: Teacher value-added and student outcomes in adulthood. American Economic Review , 104 (9), 2633 -2679. https://doi.org/10.1257/aer.104.9.2633 Chetty, R., Hendren, N., Kline, P., & Saez, E. (2020). The opportunity atlas: Mapping the childhood roots of social mobility. Quarterly Journal of Economics , 135 (4), 1593 -1640. https://doi.org/10.1093/qje/qjaa009 Chiu, T. K. F. (2016). Introducing electronic textbooks as daily-use technology in schools: A top-down adoption process. British Journal of Educational Technology , 47 (5), 1004 -1017. Chiu, T. K. F. (2021). Student engagement in K-12 online learning amid COVID-19. International Journal of Educational Technology in Higher Education , 18 (1). Cohodes, S. R. (2018). The effects of school accountability on student achievement and behavior: Evidence from New York City high schools. Journal of Policy Analysis and Management 37 , (3), 572 -603. https://doi.org/10.1002/pam.22070 Côté, S., Stellar, J. E., Willer, R., Forbes, R. C., Martin, S. R., & Bianchi, E. C. (2021). The psychology of entrenched privilege: High socioeconomic status individuals from affluent backgrounds are uniquely high in entitlement. Personality and Social Psychology Bulletin , 47 (1), 70 -88. https://doi.org/10.1177/0146167220916633 Creswell, J. W. (2003). Research design: Qualitative, quantitative, and mixed methods approaches (2nd ed.). Sage. Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches . Sage. Creswell, J., & Plano Clark, V. L. (2011). Designing and conducting mixed methods research (2nd ed.). Sage. Creswell, J., & Poth, C. (2018). Qualitative inquiry and research design: Choosing among five approaches (4th ed.). Sage. Darling-Hammond, L. (1998). Unequal opportunity: race and education from https://www.brookings.edu/articles/unequal-opportunity-race-and-education/ Darling-Hammond, L. (2010). equity will determine our future . Teachers College Press. . Brookings. Retrieved The flat world and education: How America's commitment to Davis-Kean, P. E. (2005). The influence of parent education and family income on child achievement: The indirect role of parental expectations and the home environment. Journal of Family Psychology, 19 (2), 294 -304. https://doi.org/10.1037/0893- 3200.19.2.294	[ "Carroll", ",", "J.", "M.", ",", "O'Connor", ",", "R.", "E.", ",", "&", "amp", ";", "McDonald", ",", "C.", "A.", "(", "2004", ")", ".", "Educational", "implications", "of", "reading", "achievement", "gaps", ":", "A", "study", "of", "students", "in", "the", "United", "States", ".", "Reading", "Research", "Quarterly", ",", "39", "(", "2", ")", ",", "164", "-182", ".", "https://doi.org/10.1598/RRQ.39.2.3", "\n\n", "Carter", ",", "E.", "(", "2008", ")", ".", "Successful", "change", "requires", "more", "than", "change", "management", ".", "The", "Journal", "for", "Quality", "&", "amp", ";", "Participation", ",", "31", "(", "1", ")", ",", "20", "-23", ".", "\n\n", "Carter", ",", "P.", "L.", ",", "&", "amp", ";", "Welner", ",", "K.", "G.", "(", "2013", ")", ".", "Closing", "the", "achievement", "gap", ":", "A", "synthesis", "of", "the", "literature", "on", "the", "role", "of", "schools", "in", "closing", "the", "achievement", "gap", ".", "In", "Handbook", "of", "educational", "policy", "research", "(", "pp", ".", "2", "-5", ",", "74", ")", ".", "Springer", ".", "\n\n", "Chetty", ",", "R.", ",", "Friedman", ",", "J.", "N.", ",", "&", "amp", ";", "Rockoff", ",", "J.", "E.", "(", "2020", ")", ".", "Measuring", "the", "impacts", "of", "teachers", "II", ":", "Teacher", "value", "-", "added", "and", "student", "outcomes", "in", "adulthood", ".", "American", "Economic", "Review", ",", "104", "(", "9", ")", ",", "2633", "-2679", ".", "https://doi.org/10.1257/aer.104.9.2633", "\n\n", "Chetty", ",", "R.", ",", "Hendren", ",", "N.", ",", "Kline", ",", "P.", ",", "&", "amp", ";", "Saez", ",", "E.", "(", "2020", ")", ".", "The", "opportunity", "atlas", ":", "Mapping", "the", "childhood", "roots", "of", "social", "mobility", ".", "Quarterly", "Journal", "of", "Economics", ",", "135", "(", "4", ")", ",", "1593", "-1640", ".", "https://doi.org/10.1093/qje/qjaa009", "\n\n", "Chiu", ",", "T.", "K.", "F.", "(", "2016", ")", ".", "Introducing", "electronic", "textbooks", "as", "daily", "-", "use", "technology", "in", "schools", ":", "A", "top", "-", "down", "adoption", "process", ".", "British", "Journal", "of", "Educational", "Technology", ",", "47", "(", "5", ")", ",", "1004", "-1017", ".", "\n\n", "Chiu", ",", "T.", "K.", "F.", "(", "2021", ")", ".", "Student", "engagement", "in", "K-12", "online", "learning", "amid", "COVID-19", ".", "\n\n", "International", "Journal", "of", "Educational", "Technology", "in", "Higher", "Education", ",", "18", "(", "1", ")", ".", "Cohodes", ",", "S.", "R.", "(", "2018", ")", ".", "The", "effects", "of", "school", "accountability", "on", "student", "achievement", "and", "behavior", ":", "Evidence", "from", "New", "York", "City", "high", "schools", ".", "Journal", "of", "Policy", "Analysis", "and", "Management", "37", ",", "(", "3", ")", ",", "572", "-603", ".", "https://doi.org/10.1002/pam.22070", "\n\n", "Côté", ",", "S.", ",", "Stellar", ",", "J.", "E.", ",", "Willer", ",", "R.", ",", "Forbes", ",", "R.", "C.", ",", "Martin", ",", "S.", "R.", ",", "&", "amp", ";", "Bianchi", ",", "E.", "C.", "(", "2021", ")", ".", "The", "psychology", "of", "entrenched", "privilege", ":", "High", "socioeconomic", "status", "individuals", "from", "affluent", "backgrounds", "are", "uniquely", "high", "in", "entitlement", ".", "Personality", "and", "Social", "Psychology", "Bulletin", ",", "47", "(", "1", ")", ",", "70", "-88", ".", "https://doi.org/10.1177/0146167220916633", "\n\n", "Creswell", ",", "J.", "W.", "(", "2003", ")", ".", "Research", "design", ":", "Qualitative", ",", "quantitative", ",", "and", "mixed", "methods", "approaches", "(", "2nd", "ed", ".", ")", ".", "Sage", ".", "\n\n", "Creswell", ",", "J.", "W.", "(", "2009", ")", ".", "Research", "design", ":", "Qualitative", ",", "quantitative", ",", "and", "mixed", "methods", "approaches", ".", "Sage", ".", "\n\n", "Creswell", ",", "J.", ",", "&", "amp", ";", "Plano", "Clark", ",", "V.", "L.", "(", "2011", ")", ".", "Designing", "and", "conducting", "mixed", "methods", "research", "(", "2nd", "ed", ".", ")", ".", "Sage", ".", "\n\n", "Creswell", ",", "J.", ",", "&", "amp", ";", "Poth", ",", "C.", "(", "2018", ")", ".", "Qualitative", "inquiry", "and", "research", "design", ":", "Choosing", "among", "five", "approaches", "(", "4th", "ed", ".", ")", ".", "Sage", ".", "\n\n", "Darling", "-", "Hammond", ",", "L.", "(", "1998", ")", ".", "Unequal", "opportunity", ":", "race", "and", "education", "from", "https://www.brookings.edu/articles/unequal-opportunity-race-and-education/", "\n\n", "Darling", "-", "Hammond", ",", "L.", "(", "2010", ")", ".", "equity", "will", "determine", "our", "future", ".", "Teachers", "College", "Press", ".", "\n\n", ".", "Brookings", ".", "Retrieved", "The", "flat", "world", "and", "education", ":", "How", "America", "'s", "commitment", "to", "\n\n", "Davis", "-", "Kean", ",", "P.", "E.", "(", "2005", ")", ".", "The", "influence", "of", "parent", "education", "and", "family", "income", "on", "child", "achievement", ":", "The", "indirect", "role", "of", "parental", "expectations", "and", "the", "home", "environment", ".", "Journal", "of", "Family", "Psychology", ",", "19", "(", "2", ")", ",", "294", "-304", ".", "https://doi.org/10.1037/0893-", "\n\n", "3200.19.2.294", "\n\n" ]	[ { "end": 239, "label": "CITATION_SPAN", "start": 0 }, { "end": 377, "label": "CITATION_SPAN", "start": 241 }, { "end": 604, "label": "CITATION_SPAN", "start": 379 }, { "end": 843, "label": "CITATION_SPAN", "start": 606 }, { "end": 1064, "label": "CITATION_SPAN", "start": 845 }, { "end": 1250, "label": "CITATION_SPAN", "start": 1066 }, { "end": 1646, "label": "CITATION_SPAN", "start": 1252 }, { "end": 1984, "label": "CITATION_SPAN", "start": 1648 }, { "end": 2099, "label": "CITATION_SPAN", "start": 1986 }, { "end": 2205, "label": "CITATION_SPAN", "start": 2101 }, { "end": 2318, "label": "CITATION_SPAN", "start": 2207 }, { "end": 2445, "label": "CITATION_SPAN", "start": 2320 }, { "end": 2594, "label": "CITATION_SPAN", "start": 2447 }, { "end": 2764, "label": "CITATION_SPAN", "start": 2596 }, { "end": 3027, "label": "CITATION_SPAN", "start": 2766 } ]
Nepal \| 9 \| 12 \| Mozambique \| 5 \| 17.4 \| \| France \| Unspecified by region \| 109 \| 15 \| Lebanon \| 24 \| 16.4 \| \| \| Morocco \| 56 \| 8 \| Niger \| 10 \| 7.0 \| \| \| \| \| \| \| \| 5.8 \| \| Germany \| Wallis and Futuna Unspecified by region \| 50 314 \| 7 23 \| Unspecified by region Jordan \| 8 47 \| 16.5 \| \| \| China \| 116 \| 8 \| Lebanon \| 33 \| 11.7 \| \| \| Jordan \| 114 \| 8 \| Türkiye \| 27 \| 9.5 85.6 \| \| Hungary \| Jordan \| 10 \| 8 \| Ukraine \| 2 \| \| \| \| Syrian Arab Republic \| 9 \| 7 \| Serbia \| 0 0 \| 4.8 3.8 \| \| \| China Unspecified by region \| 5 14 \| 4 \| Lebanon \| 10 \| 45.0 \| \| Ireland \| \| 5 \| 17 13 \| Unspecified by region \| \| \| \| \| Mozambique \| \| \| Mozambique \| 5 \| \| \| \| State of Palestine \| 4 \| 11 \| \| \| \| \| Israel \| \| \| \| \| \| 22.6 \| \| \| India \| 11 \| 49 \| Uganda \| 1 \| 4.3 \| \| \| \| 4 \| \| \| \| \| \| Italy \| China Ukraine Ukraine \| 2 71 \| 17 8 31 \| Jordan \| 13 2 \| 43.7 \| \| \| Unspecified by region Jordan \| 27 14 \| 12 6 \| Senegal Lebanon \| 2 \| 7.2 6.3 \| \| Japan \| Unspecified by region Morocco \| 154 \| 29 \| Morocco Burkina Faso \| 34 7 \| 33.4 \| \| \| India \| 36 \| 7 \| \| \| 7.4 \| \| Kuwait \| Jordan \| 30 \| 6 \| Syrian Arab Republic \| 7 \| 6.6 \| \| \| \| 9 \| 31 20 \| \| \| \| \| \| China \| 6 \| \| \| \| \| \| \| \| 4 \| 14 \| \| \| \| \| Netherlands \| Ghana Unspecified by region \| 79 \| 88 \| Unspecified by region Burkina Faso \| 31 2 \| 90.3 6.0 \| \| New Zealand \| Burkina Faso Ethiopia \| 3 1 \| 4 1 \| Burundi Timor-Leste \| 1 3 \| 3.2 \| \| \|	[ "Nepal", " ", "\|", "9", " ", "\|", "12", " ", "\|", "Mozambique", " ", "\|", "5", " ", "\|", "17.4", " ", "\|", "\n", "\|", "France", " ", "\|", "Unspecified", "by", "region", " ", "\|", "109", " ", "\|", "15", " ", "\|", "Lebanon", " ", "\|", "24", " ", "\|", "16.4", " ", "\|", "\n", "\|", " ", "\|", "Morocco", " ", "\|", "56", " ", "\|", "8", " ", "\|", "Niger", " ", "\|", "10", " ", "\|", "7.0", " ", "\|", "\n", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "5.8", " ", "\|", "\n", "\|", "Germany", " ", "\|", "Wallis", "and", "Futuna", "Unspecified", "by", "region", " ", "\|", "50", "314", " ", "\|", "7", "23", " ", "\|", "Unspecified", "by", "region", "Jordan", " ", "\|", "8", "47", " ", "\|", "16.5", " ", "\|", "\n", "\|", " ", "\|", "China", " ", "\|", "116", " ", "\|", "8", " ", "\|", "Lebanon", " ", "\|", "33", " ", "\|", "11.7", " ", "\|", "\n", "\|", " ", "\|", "Jordan", " ", "\|", "114", " ", "\|", "8", " ", "\|", "Türkiye", " ", "\|", "27", " ", "\|", "9.5", "85.6", " ", "\|", "\n", "\|", "Hungary", " ", "\|", "Jordan", " ", "\|", "10", " ", "\|", "8", " ", "\|", "Ukraine", " ", "\|", "2", " ", "\|", " ", "\|", "\n", "\|", " ", "\|", "Syrian", "Arab", "Republic", " ", "\|", "9", " ", "\|", "7", " ", "\|", "Serbia", " ", "\|", "0", "0", " ", "\|", "4.8", "3.8", " ", "\|", "\n", "\|", " ", "\|", "China", "Unspecified", "by", "region", " ", "\|", "5", "14", " ", "\|", "4", " ", "\|", "Lebanon", " ", "\|", "10", " ", "\|", "45.0", " ", "\|", "\n", "\|", "Ireland", " ", "\|", " ", "\|", "5", " ", "\|", "17", "13", " ", "\|", "Unspecified", "by", "region", " ", "\|", " ", "\|", " ", "\|", "\n", "\|", " ", "\|", "Mozambique", " ", "\|", " ", "\|", " ", "\|", "Mozambique", " ", "\|", "5", " ", "\|", " ", "\|", "\n", "\|", " ", "\|", "State", "of", "Palestine", " ", "\|", "4", " ", "\|", "11", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "\n", "\|", "Israel", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "22.6", " ", "\|", "\n", "\|", " ", "\|", "India", " ", "\|", "11", " ", "\|", "49", " ", "\|", "Uganda", " ", "\|", "1", " ", "\|", "4.3", " ", "\|", "\n", "\|", " ", "\|", " ", "\|", "4", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "\n", "\|", "Italy", " ", "\|", "China", "Ukraine", "Ukraine", " ", "\|", "2", "71", " ", "\|", "17", "8", "31", " ", "\|", "Jordan", " ", "\|", "13", "2", " ", "\|", "43.7", " ", "\|", "\n", "\|", " ", "\|", "Unspecified", "by", "region", "Jordan", " ", "\|", "27", "14", " ", "\|", "12", "6", " ", "\|", "Senegal", "Lebanon", " ", "\|", "2", " ", "\|", "7.2", "6.3", " ", "\|", "\n", "\|", "Japan", " ", "\|", "Unspecified", "by", "region", "Morocco", " ", "\|", "154", " ", "\|", "29", " ", "\|", "Morocco", "Burkina", "Faso", " ", "\|", "34", "7", " ", "\|", "33.4", " ", "\|", "\n", "\|", " ", "\|", "India", " ", "\|", "36", " ", "\|", "7", " ", "\|", " ", "\|", " ", "\|", "7.4", " ", "\|", "\n", "\|", "Kuwait", " ", "\|", "Jordan", " ", "\|", "30", " ", "\|", "6", " ", "\|", "Syrian", "Arab", "Republic", " ", "\|", "7", " ", "\|", "6.6", " ", "\|", "\n", "\|", " ", "\|", " ", "\|", "9", " ", "\|", "31", "20", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "\n", "\|", " ", "\|", "China", " ", "\|", "6", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "\n", "\|", " ", "\|", " ", "\|", "4", " ", "\|", "14", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "\n", "\|", "Netherlands", "\|", "Ghana", "Unspecified", "by", "region", " ", "\|", "79", " ", "\|", "88", " ", "\|", "Unspecified", "by", "region", "Burkina", "Faso", " ", "\|", "31", "2", " ", "\|", "90.3", "6.0", " ", "\|", "\n", "\|", "New", "Zealand", "\|", "Burkina", "Faso", "Ethiopia", " ", "\|", "3", "1", " ", "\|", "4", "1", " ", "\|", "Burundi", "Timor", "-", "Leste", " ", "\|", "1", "3", " ", "\|", "3.2", " ", "\|", "\n", "\|", " ", "\|" ]	[]
Q 8.47889E-01 4.83787E-01 5.59730E-02 2.09526E-01 VIEW -2.97649E-01 7.96940E-01 -5.25635E-01 RIGH 9.05932E-01 4.09467E-01 1.07814E-01 UP -3.01151E-01 4.44099E-01 8.43851E-01 FOV 2.48819E+01 !NAVIGATION MODE: ROTATING CAMERA !CENTER : 3.50000E+00 1.00000E+00 1.00000E+00 !RSPHERE: 3.77492E+00 !RADIUS : 2.07620E+01 !ASPECT : 1.00000E+00 !NEAR : 1.69871E+01 !FAR : 2.83119E+01 SCEN GEOM NAVI FREE LIMA ON SLER CAM1 1 NFRA 1 FREQ 0 TFRE 1.E-3 TRAC OFFS FICH AVI NOCL NFTO 86 FPS 10 KFRE 10 COMP -1 OBJE LECT base cube ncub TERM REND GOTR LOOP 84 OFFS FICH AVI CONT NOCL OBJE LECT base cube ncub TERM REND GO TRAC OFFS FICH AVI CONT OBJE LECT base cube ncub TERM REND 153 Tuesday 12thAugust, 2025 @ 13:38 ENDP ======================================================================= SUITE Post-treatment ECHO RESU ALIC TEMP GARD PSCR SORT GRAP AXTE 1. 't [s]' COUR 1 'dz_p5' DEPL COMP 3 NOEU LECT p5 TERM COUR 2 'dz_p6' DEPL COMP 3 NOEU LECT p6 TERM COUR 3 'dz_p7' DEPL COMP 3 NOEU LECT p7 TERM COUR 4 'dz_p8' DEPL COMP 3 NOEU LECT p8 TERM COUR 5 'dx_p5' DEPL COMP 1 NOEU LECT p5 TERM COUR 6 'dx_p6' DEPL COMP 1 NOEU LECT p6 TERM COUR 7 'dx_p7' DEPL COMP 1 NOEU LECT p7 TERM COUR 8 'dx_p8' DEPL COMP 1 NOEU LECT p8 TERM TRAC 1 2 3 4 AXES 1. 'Z-DISP (m)' YZER TRAC 5 6 7 8 AXES 1. 'X-DISP (m)' YZER LIST 1 2 3 4 AXES 1. 'Z-DISP (m)' LIST 5 6 7 8 AXES 1. 'X-DISP (m)' RCOU 15 'dx_p5' FICH 'sc3d00.pun' RENA 'dx_p5_3d_00' RCOU 25 'dx_p5' FICH 'sc2d01.pun' RENA 'dx_p5_2d_01' TRAC 5 15 AXES 1. 'X-DISP (m)' YZER COLO NOIR ROUG TRAC 5 25 15 AXES 1. 'X-DISP (m)' YZER COLO NOIR ROUG VERT FIN sc3d131.dgibi opti echo 0; 'DEBPROC' pxextr3d m'MAILLAGE' x1'FLOTTANT' x2'FLOTTANT' y1'FLOTTANT' y2'FLOTTANT' z1'FLOTTANT' z2'FLOTTANT'; -------------------------------------------------- Extracts from the 3D mesh m the elements whose nodes are * located in the box [x1-x2,y1-y2,z1-z2]. * * Input : * ----- * m : 3D mesh * x1, x2, y1, y2, z1, z2 : extremes of the box * Output : * ------ * box : mesh contained in the box -------------------------------------------------- x = coor 1 m; sx = x POIN COMP x1 x2; y = coor 2 sx; sy = y POIN COMP y1 y2; z = coor 3 sy; sz = z POIN COMP z1 z2; box = m ELEM APPU STRI sz NOVE;	[ "Q", "8.47889E-01", "4.83787E-01", "5.59730E-02", "2.09526E-01", "\n", "VIEW", "-2.97649E-01", "7.96940E-01", "-5.25635E-01", "\n", "RIGH", "9.05932E-01", "4.09467E-01", "1.07814E-01", "\n", "UP", "-3.01151E-01", "4.44099E-01", "8.43851E-01", "\n", "FOV", "2.48819E+01", "\n", "!", "NAVIGATION", "MODE", ":", "ROTATING", "CAMERA", "\n", "!", "CENTER", ":", "3.50000E+00", "1.00000E+00", "1.00000E+00", "\n", "!", "RSPHERE", ":", "3.77492E+00", "\n", "!", "RADIUS", ":", "2.07620E+01", "\n", "!", "ASPECT", ":", "1.00000E+00", "\n", "!", "NEAR", ":", "1.69871E+01", "\n", "!", "FAR", ":", "2.83119E+01", "\n", "SCEN", "GEOM", "NAVI", "FREE", "\n", "LIMA", "ON", "\n", "SLER", "CAM1", "1", "NFRA", "1", "\n", "FREQ", "0", "TFRE", "1.E-3", "\n", "TRAC", "OFFS", "FICH", "AVI", "NOCL", "NFTO", "86", "FPS", "10", "KFRE", "10", "COMP", "-1", "\n", "OBJE", "LECT", "base", "cube", "ncub", "TERM", "REND", "\n", "GOTR", "LOOP", "84", "OFFS", "FICH", "AVI", "CONT", "NOCL", "\n", "OBJE", "LECT", "base", "cube", "ncub", "TERM", "REND", "\n", "GO", "\n", "TRAC", "OFFS", "FICH", "AVI", "CONT", "\n", "OBJE", "LECT", "base", "cube", "ncub", "TERM", "REND", "\n", "153", "\n", "Tuesday", "12thAugust", ",", "2025", "@", "13:38", "\n", "ENDP", "\n", "", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "\n", "SUITE", "\n", "Post", "-", "treatment", "\n", "ECHO", "\n", "RESU", "ALIC", "TEMP", "GARD", "PSCR", "\n", "SORT", "GRAP", "AXTE", "1", ".", "'", "t", "[", "s", "]", "'", "\n", "COUR", "1", "'", "dz_p5", "'", "DEPL", "COMP", "3", "NOEU", "LECT", "p5", "TERM", "\n", "COUR", "2", "'", "dz_p6", "'", "DEPL", "COMP", "3", "NOEU", "LECT", "p6", "TERM", "\n", "COUR", "3", "'", "dz_p7", "'", "DEPL", "COMP", "3", "NOEU", "LECT", "p7", "TERM", "\n", "COUR", "4", "'", "dz_p8", "'", "DEPL", "COMP", "3", "NOEU", "LECT", "p8", "TERM", "\n", "COUR", "5", "'", "dx_p5", "'", "DEPL", "COMP", "1", "NOEU", "LECT", "p5", "TERM", "\n", "COUR", "6", "'", "dx_p6", "'", "DEPL", "COMP", "1", "NOEU", "LECT", "p6", "TERM", "\n", "COUR", "7", "'", "dx_p7", "'", "DEPL", "COMP", "1", "NOEU", "LECT", "p7", "TERM", "\n", "COUR", "8", "'", "dx_p8", "'", "DEPL", "COMP", "1", "NOEU", "LECT", "p8", "TERM", "\n", "TRAC", "1", "2", "3", "4", "AXES", "1", ".", "'", "Z", "-", "DISP", "(", "m", ")", "'", "YZER", "\n", "TRAC", "5", "6", "7", "8", "AXES", "1", ".", "'", "X", "-", "DISP", "(", "m", ")", "'", "YZER", "\n", "LIST", "1", "2", "3", "4", "AXES", "1", ".", "'", "Z", "-", "DISP", "(", "m", ")", "'", "\n", "LIST", "5", "6", "7", "8", "AXES", "1", ".", "'", "X", "-", "DISP", "(", "m", ")", "'", "\n", "RCOU", "15", "'", "dx_p5", "'", "FICH", "'", "sc3d00.pun", "'", "RENA", "'", "dx_p5_3d_00", "'", "\n", "RCOU", "25", "'", "dx_p5", "'", "FICH", "'", "sc2d01.pun", "'", "RENA", "'", "dx_p5_2d_01", "'", "\n", "TRAC", "5", "15", "AXES", "1", ".", "'", "X", "-", "DISP", "(", "m", ")", "'", "YZER", "\n", "COLO", "NOIR", "ROUG", "\n", "TRAC", "5", "25", "15", "AXES", "1", ".", "'", "X", "-", "DISP", "(", "m", ")", "'", "YZER", "\n", "COLO", "NOIR", "ROUG", "VERT", "\n", "FIN", "\n", "sc3d131.dgibi", "\n", "opti", "echo", "0", ";", "\n", "", "\n", "'", "DEBPROC", "'", "pxextr3d", "m'MAILLAGE", "'", "x1'FLOTTANT", "'", "x2'FLOTTANT", "'", "\n", "y1'FLOTTANT", "'", "y2'FLOTTANT", "'", "\n", "z1'FLOTTANT", "'", "z2'FLOTTANT", "'", ";", "\n", "", "\n", "", "--------------------------------------------------", "\n", "", "Extracts", "from", "the", "3D", "mesh", "m", "the", "elements", "whose", "nodes", "are", "\n", "", "located", "in", "the", "box", "[", "x1", "-", "x2,y1", "-", "y2,z1", "-", "z2", "]", ".", "\n", "", "\n", "", "Input", ":", "\n", "", "-----", "\n", "", "m", ":", "3D", "mesh", "\n", "", "x1", ",", "x2", ",", "y1", ",", "y2", ",", "z1", ",", "z2", ":", "extremes", "of", "the", "box", "\n", "", "Output", ":", "\n", "", "------", "\n", "", "box", ":", "mesh", "contained", "in", "the", "box", "\n", "", "--------------------------------------------------", "\n", "*", "\n", "x", "=", "coor", "1", "m", ";", "\n", "sx", "=", "x", "POIN", "COMP", "x1", "x2", ";", "\n", "y", "=", "coor", "2", "sx", ";", "\n", "sy", "=", "y", "POIN", "COMP", "y1", "y2", ";", "\n", "z", "=", "coor", "3", "sy", ";", "\n", "sz", "=", "z", "POIN", "COMP", "z1", "z2", ";", "\n", "box", "=", "m", "ELEM", "APPU", "STRI", "sz", "NOVE", ";", "\n" ]	[]
type of contractual arrangements for petroleum exploration and development. PSAs cover individual fields/projects (Bindeman, 1999). The fiscal liability is then determined with reference to specific contracts, which results in a de facto ring-fencing outcome. The burden of implementing ring-fencing rules could be perceived to be lower due to this contract-by-contract approach to the fiscal administration of oil projects. Cost recovery is typically ring-fenced, as explained in Box 3. • PSAs have not taken hold in mining. This issue is explored in Readhead et al. (2023).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 11 Ring-Fencing Mining Income: A toolkit for tax administrators and policy-makersBOX 3. RING -FENCING AND PSAS PSAs are typically designed to include cost recovery and production- sharing instruments.9 Revenue sharing between the host government and the investor is normally determined by arrangements for assigned shares of production volumes. The obligation to pay CIT and other taxes may be placed on the investor or on a state-owned company on the investor’s behalf. Cost recovery is often ring-fenced around the exploration and/or development licence within a contract area, which means that exploration and/or development costs associated with a particular licence must be recovered from revenues generated within that block or licence (Nakhle, 2010). In other words, if ring-fencing rules for different licences covered by a PSA exist, an investor should not be able to consolidate revenues and losses derived from different licences covered by a PSA.10 In summary, for most sectors of the economy, the corporate tax base is determined at the subsidiary or branch level, not at the project or activity level. In the mining sector, however, it is common for governments to ring-fence mining projects, and/or mining income from other sources of income. This allows them to administer the specific tax regime for each project and/or mining activities separately from other commercial activities, accelerating government revenues and protecting the tax base. The application of ring-fencing rules is not exclusive to the extractive sectors. Some countries also apply the ring-fencing rules in the finance11 and energy sectors.12 In deciding whether ring-fencing rules are adequate for their mining tax regime, governments in resource-rich countries should be aware of the benefits and challenges of ring-fencing rules and how they would fit into the overall structure of the taxation framework,	[ "type", "of", "contractual", "arrangements", "for", "petroleum", "exploration", "and", "\n", "development", ".", "PSAs", "cover", "individual", "fields", "/", "projects", "(", "Bindeman", ",", "1999", ")", ".", "\n", "The", "fiscal", "liability", "is", "then", "determined", "with", "reference", "to", "specific", "\n", "contracts", ",", "which", "results", "in", "a", "de", "facto", "ring", "-", "fencing", "outcome", ".", "The", "\n", "burden", "of", "implementing", "ring", "-", "fencing", "rules", "could", "be", "perceived", "to", "\n", "be", "lower", "due", "to", "this", "contract", "-", "by", "-", "contract", "approach", "to", "the", "fiscal", "\n", "administration", "of", "oil", "projects", ".", "Cost", "recovery", "is", "typically", "ring", "-", "fenced", ",", "\n", "as", "explained", "in", "Box", "3", ".", "\n", "•", "PSAs", "have", "not", "taken", "hold", "in", "mining", ".", "This", "issue", "is", "explored", "in", "\n", "Readhead", "et", "al", ".", "(", "2023).3.0", "THE", "BENEFITS", "\n", "AND", "RISKS", "OF", " \n", "RING", "-FENCING", "\n", "4.0", "DESIGNING", "\n", "RING", "-FENCING", "\n", "RULES", "\n", "5.0", "THE", "\n", "IMPLEMENTATION", "\n", "OF", "RING", "-FENCING", "\n", "RULES", "\n", "6.0", "CONCLUSION", "2.0", "THE", "\n", "FUNDAMENTALS", " \n", "OF", "RING", "-FENCING", "1.0", "INTRODUCTION", "\n", "11", "\n", "Ring", "-", "Fencing", "Mining", "Income", ":", "A", "toolkit", "for", "tax", "administrators", "and", "policy", "-", "makersBOX", "3", ".", "RING", "-FENCING", "AND", "PSAS", "\n", "PSAs", "are", "typically", "designed", "to", "include", "cost", "recovery", "and", "production-", "\n", "sharing", "instruments.9", "Revenue", "sharing", "between", "the", "host", "government", "\n", "and", "the", "investor", "is", "normally", "determined", "by", "arrangements", "for", "assigned", "\n", "shares", "of", "production", "volumes", ".", "The", "obligation", "to", "pay", "CIT", "and", "other", "\n", "taxes", "may", "be", "placed", "on", "the", "investor", "or", "on", "a", "state", "-", "owned", "company", "on", "\n", "the", "investor", "’s", "behalf", ".", "Cost", "recovery", "is", "often", "ring", "-", "fenced", "around", "the", "\n", "exploration", "and/or", "development", "licence", "within", "a", "contract", "area", ",", "which", "\n", "means", "that", "exploration", "and/or", "development", "costs", "associated", "with", "a", "\n", "particular", "licence", "must", "be", "recovered", "from", "revenues", "generated", "within", "\n", "that", "block", "or", "licence", "(", "Nakhle", ",", "2010", ")", ".", "In", "other", "words", ",", "if", "ring", "-", "fencing", "rules", "\n", "for", "different", "licences", "covered", "by", "a", "PSA", "exist", ",", "an", "investor", "should", "not", "be", "\n", "able", "to", "consolidate", "revenues", "and", "losses", "derived", "from", "different", "licences", "\n", "covered", "by", "a", "PSA.10", "\n", "In", "summary", ",", "for", "most", "sectors", "of", "the", "economy", ",", "the", "corporate", "tax", "base", " \n", "is", "determined", "at", "the", "subsidiary", "or", "branch", "level", ",", "not", "at", "the", "project", "or", "\n", "activity", "level", ".", "In", "the", "mining", "sector", ",", "however", ",", "it", "is", "common", "for", "governments", "\n", "to", "ring", "-", "fence", "mining", "projects", ",", "and/or", "mining", "income", "from", "other", "sources", "\n", "of", "income", ".", "This", "allows", "them", "to", "administer", "the", "specific", "tax", "regime", "for", "each", "\n", "project", "and/or", "mining", "activities", "separately", "from", "other", "commercial", "activities", ",", "\n", "accelerating", "government", "revenues", "and", "protecting", "the", "tax", "base", ".", "The", "\n", "application", "of", "ring", "-", "fencing", "rules", "is", "not", "exclusive", "to", "the", "extractive", "sectors", ".", "\n", "Some", "countries", "also", "apply", "the", "ring", "-", "fencing", "rules", "in", "the", "finance11", "and", "energy", "\n", "sectors.12", "In", "deciding", "whether", "ring", "-", "fencing", "rules", "are", "adequate", "for", "their", "\n", "mining", "tax", "regime", ",", "governments", "in", "resource", "-", "rich", "countries", "should", "be", "aware", "\n", "of", "the", "benefits", "and", "challenges", "of", "ring", "-", "fencing", "rules", "and", "how", "they", "would", "\n", "fit", "into", "the", "overall", "structure", "of", "the", "taxation", "framework", "," ]	[ { "end": 1554, "label": "CITATION_REF", "start": 1542 }, { "end": 1548, "label": "AUTHOR", "start": 1542 }, { "end": 1554, "label": "YEAR", "start": 1550 } ]
Gooday cau - tion against ‘glib[ly] describ[ing] their geographical scope as global’, the available data show that ICWES was regularly attended by women del - egates from around thirty countries, with variations in regional visibility 19 19 Introduction between different conferences: ‘South American nations were most visible in ICWES 1 (USA); African nations were first apparent at ICWES 2 (UK); and only at ICWES 4 (Poland) was there broad participation from Eastern European nations, with the USA constituency (44 attendees) for the first time overshadowed by a large majority of native (Polish) participants (423 attendees).’ As the two authors emphasize, the ICWES archive provides an oppor - tunity to place engineering firmly on the agenda of future historiographies of women in ‘science’, not least because engineering was less exclusionary a field than the fundamental or ‘pure’ sciences, as the participation of del - egates from African, Asian and South American countries also demonstrate. This is not to say that certain countries did not feature more prominently in the organization of these conferences than others. Indeed, as the authors point out, ‘the planning and programming of successive meetings relied on the national- level organisations for women in science and engineering most prominently in eight countries: Brazil, France, Italy, Japan, the Philippines, Poland, UK and USA’. Rees Koerner and Gooday’s chapter also renders visible the intersections of collective and individual agencies of women in STEMM, for example, by showing that transnational collaboration between national bodies and the untiring effort of individual engineers like Ira Rischowski were essential to the success of these events. The trans- regional approach they employ is particularly effective at exposing the politics and anxieties over the low number of women in sci - ence in the US and Western Europe, especially in the charged geopolitical climate of the Cold War, when comparison with the countries of the com - munist bloc became topical. As the authors point out, ‘it was left … to the communist countries participating in ICWES meetings to highlight their more developed capacity to educate, equip and enrol women for roles in engineering and applied science’. The political undertones of this mission cannot be ignored and delegates from communist countries likely regarded the promotion of women’s participation in engineering and applied science as a tool of science diplomacy. Of course, the link between science, gender and politics was not emblematic of that context alone. All	[ "Gooday", "cau", "-", "\n", "tion", "against", "‘", "glib[ly", "]", "describ[ing", "]", "their", "geographical", "scope", "as", "global", "’", ",", "the", "\n", "available", "data", "show", "that", "ICWES", "was", "regularly", "attended", "by", "women", "del", "-", "\n", "egates", "from", "around", "thirty", "countries", ",", "with", "variations", "in", "regional", "visibility", "\n", "19", "\n", "19", "\n", "Introduction", "\n", "between", "different", "conferences", ":", "‘", "South", "American", "nations", "were", "most", "visible", "\n", "in", "ICWES", "1", "(", "USA", ")", ";", "African", "nations", "were", "first", "apparent", "at", "ICWES", "2", "(", "UK", ")", ";", "\n", "and", "only", "at", "ICWES", "4", "(", "Poland", ")", "was", "there", "broad", "participation", "from", "Eastern", "\n", "European", "nations", ",", "with", "the", "USA", "constituency", "(", "44", "attendees", ")", "for", "the", "first", "\n", "time", "overshadowed", "by", "a", "large", "majority", "of", "native", "(", "Polish", ")", "participants", "(", "423", "\n", "attendees", ")", ".", "’", "\n", "As", "the", "two", "authors", "emphasize", ",", "the", "ICWES", "archive", "provides", "an", "oppor", "-", "\n", "tunity", "to", "place", "engineering", "firmly", "on", "the", "agenda", "of", "future", "historiographies", "\n", "of", "women", "in", "‘", "science", "’", ",", "not", "least", "because", "engineering", "was", "less", "exclusionary", "\n", "a", "field", "than", "the", "fundamental", "or", "‘", "pure", "’", "sciences", ",", "as", "the", "participation", "of", "del", "-", "\n", "egates", "from", "African", ",", "Asian", "and", "South", "American", "countries", "also", "demonstrate", ".", "\n", "This", "is", "not", "to", "say", "that", "certain", "countries", "did", "not", "feature", "more", "prominently", "\n", "in", "the", "organization", "of", "these", "conferences", "than", "others", ".", "Indeed", ",", "as", "the", "authors", "\n", "point", "out", ",", "‘", "the", "planning", "and", "programming", "of", "successive", "meetings", "relied", "on", "\n", "the", "national-", "level", "organisations", "for", "women", "in", "science", "and", "engineering", "most", "\n", "prominently", "in", "eight", "countries", ":", "Brazil", ",", "France", ",", "Italy", ",", "Japan", ",", "the", "Philippines", ",", "\n", "Poland", ",", "UK", "and", "USA", "’", ".", "Rees", "Koerner", "and", "Gooday", "’s", "chapter", "also", "renders", "\n", "visible", "the", "intersections", "of", "collective", "and", "individual", "agencies", "of", "women", "\n", "in", "STEMM", ",", "for", "example", ",", "by", "showing", "that", "transnational", "collaboration", "\n", "between", "national", "bodies", "and", "the", "untiring", "effort", "of", "individual", "engineers", "like", "\n", "Ira", "Rischowski", "were", "essential", "to", "the", "success", "of", "these", "events", ".", "\n", "The", "trans-", "regional", "approach", "they", "employ", "is", "particularly", "effective", "at", "\n", "exposing", "the", "politics", "and", "anxieties", "over", "the", "low", "number", "of", "women", "in", "sci", "-", "\n", "ence", "in", "the", "US", "and", "Western", "Europe", ",", "especially", "in", "the", "charged", "geopolitical", "\n", "climate", "of", "the", "Cold", "War", ",", "when", "comparison", "with", "the", "countries", "of", "the", "com", "-", "\n", "munist", "bloc", "became", "topical", ".", "As", "the", "authors", "point", "out", ",", "‘", "it", "was", "left", "…", "to", "\n", "the", "communist", "countries", "participating", "in", "ICWES", "meetings", "to", "highlight", "their", "\n", "more", "developed", "capacity", "to", "educate", ",", "equip", "and", "enrol", "women", "for", "roles", "in", "\n", "engineering", "and", "applied", "science", "’", ".", "The", "political", "undertones", "of", "this", "mission", "\n", "can", "not", "be", "ignored", "and", "delegates", "from", "communist", "countries", "likely", "regarded", "\n", "the", "promotion", "of", "women", "’s", "participation", "in", "engineering", "and", "applied", "science", "\n", "as", "a", "tool", "of", "science", "diplomacy", ".", "Of", "course", ",", "the", "link", "between", "science", ",", "gender", "\n", "and", "politics", "was", "not", "emblematic", "of", "that", "context", "alone", ".", "All" ]	[]
discharge, turbine, heat exchanger, collector, rectifier, condition, resistance, statorTable 3.3b. List of 50 most relevant keywords for each S&T domainTable 3.3a. List of identified S&T specialisation domains EaP S&T specialisation domains (in alphabetical order) Agrifood Biotechnology Energy Optics and photonicsHealth and wellbeingChemistry and chemical engineeringElectric and electronic technologies Environmental sciences and industries Governance, culture, education and the economy ICT and computer science TransportationNanotechnology and materialsFundamental physics and mathematics Mechanical engineering and heavy machinery 150 Part 3 Analysis of scientific and technological potential S&T domain Top keywords Environmental sciences and industriesspecie, water, soil, plant, environment, deposit, rock, population, basin, datum, reservoir, river, pollution, territory, concentration, condition, treatment, well, sea, caucasus, philtre, source, purification, ecosystem, temperature, contamination, metal, monitoring, forest, mine, mining, genus, sediment, mass, species, nov, station, accumulation, slope, extraction, tree, habitat, ore, massif, air, hole, removal, biomass, land, body Fundamental physics and mathematicstev, collision, equation, measurement, detector, mass, boson, gev, section, jet, datum, atlas detector, condition, particle, pp collision, luminosity, space, lhc, energy, integrated luminosity, momentum, coefficient, dependence, pair, decay, quark, proton-proton collision, lepton, prediction, channel, flow, mass, proton, electron, collider, confidence level, muon, fraction, frequency, resonance, transverse momentum, formula, cms detector, photon, sup, higgs boson, gas, cross section, simulation, excess Governance, culture, education and the economyenterprise, author, economy, policy, market, resource, environment, risk, society, industry, experience, security, regulation, culture, population, history, people, life, language, bank, business, government, reform, law, protection, identity, caucasus, city, text, investment, nature, competitiveness, capital, conflict, sustainable development, sphere, source, form, condition, teacher, crisis, publication, power, authority, tradition, attitude, legislation, image, perception, peculiarity Health and wellbeingpatient, treatment, cell, disease, child, therapy, tissue, woman, rat, disorder, gene, diagnosis, age, cancer, drug, syndrome, risk, population, animal, dose, infection, surgery, expression, complication, protein, care, prevalence, week, diabetes, people, tumour, examination, day, cavity, year, medicine, mortality, pathology, symptom, mutation, prevention, blood, intervention, hypertension, marker, month, stress, death, health, severity ICT and computer sciencealgorithm, network, datum, measurement, simulation, image, accuracy, error, signal, user, monitoring, software, modelling, detection, architecture, database, recognition, node, prediction, environment, condition, code, construction, server, resource, correction, station, complexity, sensor, uncertainty, neural network, form, source, communication, noise, sequence, channel, propose method, computer, connexion, message, rule, memory, author, transmission, interface, circuit, probability, distance, subsystem Mechanical engineering and heavy machineryplate, chamber, axis, body, rod, wall, hole, angle, surface, shaft, pipe, opening, housing, form, plane, machine, cylinder, drive, valve, diameter, groove, ring, shell, section, rotation, spring, portion, holder, pipeline, guide, cover, sleeve,	[ "discharge", ",", "turbine", ",", "heat", "exchanger", ",", "\n", "collector", ",", "rectifier", ",", "condition", ",", "resistance", ",", "statorTable", "3.3b", ".", "List", "of", "50", "most", "relevant", "keywords", "for", "each", "S&T", "domainTable", "3.3a", ".", "List", "of", "identified", "S&T", "specialisation", "domains", "\n", "EaP", "S&T", "specialisation", "domains", "(", "in", "alphabetical", "order", ")", "\n", "Agrifood", "Biotechnology", "\n", "Energy", "\n", "Optics", "and", "photonicsHealth", "and", "wellbeingChemistry", "and", "chemical", "\n", "engineeringElectric", "and", "electronic", "\n", "technologies", "\n", "Environmental", "sciences", "and", "\n", "industries", "\n", "Governance", ",", "culture", ",", "\n", "education", "and", "the", "economy", "\n", "ICT", "and", "computer", "science", "\n", "TransportationNanotechnology", "and", "\n", "materialsFundamental", "physics", "and", "\n", "mathematics", "\n", "Mechanical", "engineering", "and", "\n", "heavy", "machinery", "\n", "150", "\n ", "Part", "3", "Analysis", "of", "scientific", "and", "technological", "potential", "\n", "S&T", "domain", "Top", "keywords", "\n", "Environmental", "\n", "sciences", "and", "\n", "industriesspecie", ",", "water", ",", "soil", ",", "plant", ",", "environment", ",", "deposit", ",", "rock", ",", "population", ",", "basin", ",", "datum", ",", "reservoir", ",", "river", ",", "\n", "pollution", ",", "territory", ",", "concentration", ",", "condition", ",", "treatment", ",", "well", ",", "sea", ",", "caucasus", ",", "philtre", ",", "source", ",", "\n", "purification", ",", "ecosystem", ",", "temperature", ",", "contamination", ",", "metal", ",", "monitoring", ",", "forest", ",", "mine", ",", "mining", ",", "\n", "genus", ",", "sediment", ",", "mass", ",", "species", ",", "nov", ",", "station", ",", "accumulation", ",", "slope", ",", "extraction", ",", "tree", ",", "habitat", ",", "ore", ",", "\n", "massif", ",", "air", ",", "hole", ",", "removal", ",", "biomass", ",", "land", ",", "body", "\n", "Fundamental", "\n", "physics", "and", "\n", "mathematicstev", ",", "collision", ",", "equation", ",", "measurement", ",", "detector", ",", "mass", ",", "boson", ",", "gev", ",", "section", ",", "jet", ",", "datum", ",", "atlas", "\n", "detector", ",", "condition", ",", "particle", ",", "pp", "collision", ",", "luminosity", ",", "space", ",", "lhc", ",", "energy", ",", "integrated", "luminosity", ",", "\n", "momentum", ",", "coefficient", ",", "dependence", ",", "pair", ",", "decay", ",", "quark", ",", "proton", "-", "proton", "collision", ",", "lepton", ",", "prediction", ",", "\n", "channel", ",", "flow", ",", "mass", ",", "proton", ",", "electron", ",", "collider", ",", "confidence", "level", ",", "muon", ",", "fraction", ",", "frequency", ",", "\n", "resonance", ",", "transverse", "momentum", ",", "formula", ",", "cms", "detector", ",", "photon", ",", "sup", ",", "higgs", "boson", ",", "gas", ",", "cross", "\n", "section", ",", "simulation", ",", "excess", "\n", "Governance", ",", "\n", "culture", ",", "education", "\n", "and", "the", "economyenterprise", ",", "author", ",", "economy", ",", "policy", ",", "market", ",", "resource", ",", "environment", ",", "risk", ",", "society", ",", "industry", ",", "\n", "experience", ",", "security", ",", "regulation", ",", "culture", ",", "population", ",", "history", ",", "people", ",", "life", ",", "language", ",", "bank", ",", "\n", "business", ",", "government", ",", "reform", ",", "law", ",", "protection", ",", "identity", ",", "caucasus", ",", "city", ",", "text", ",", "investment", ",", "nature", ",", "\n", "competitiveness", ",", "capital", ",", "conflict", ",", "sustainable", "development", ",", "sphere", ",", "source", ",", "form", ",", "condition", ",", "\n", "teacher", ",", "crisis", ",", "publication", ",", "power", ",", "authority", ",", "tradition", ",", "attitude", ",", "legislation", ",", "image", ",", "perception", ",", "\n", "peculiarity", "\n", "Health", "and", "\n", "wellbeingpatient", ",", "treatment", ",", "cell", ",", "disease", ",", "child", ",", "therapy", ",", "tissue", ",", "woman", ",", "rat", ",", "disorder", ",", "gene", ",", "diagnosis", ",", "age", ",", "\n", "cancer", ",", "drug", ",", "syndrome", ",", "risk", ",", "population", ",", "animal", ",", "dose", ",", "infection", ",", "surgery", ",", "expression", ",", "complication", ",", "\n", "protein", ",", "care", ",", "prevalence", ",", "week", ",", "diabetes", ",", "people", ",", "tumour", ",", "examination", ",", "day", ",", "cavity", ",", "year", ",", "medicine", ",", "\n", "mortality", ",", "pathology", ",", "symptom", ",", "mutation", ",", "prevention", ",", "blood", ",", "intervention", ",", "hypertension", ",", "marker", ",", "\n", "month", ",", "stress", ",", "death", ",", "health", ",", "severity", "\n", "ICT", "and", "computer", "\n", "sciencealgorithm", ",", "network", ",", "datum", ",", "measurement", ",", "simulation", ",", "image", ",", "accuracy", ",", "error", ",", "signal", ",", "user", ",", "\n", "monitoring", ",", "software", ",", "modelling", ",", "detection", ",", "architecture", ",", "database", ",", "recognition", ",", "node", ",", "prediction", ",", "\n", "environment", ",", "condition", ",", "code", ",", "construction", ",", "server", ",", "resource", ",", "correction", ",", "station", ",", "complexity", ",", "sensor", ",", "\n", "uncertainty", ",", "neural", "network", ",", "form", ",", "source", ",", "communication", ",", "noise", ",", "sequence", ",", "channel", ",", "propose", "\n", "method", ",", "computer", ",", "connexion", ",", "message", ",", "rule", ",", "memory", ",", "author", ",", "transmission", ",", "interface", ",", "circuit", ",", "\n", "probability", ",", "distance", ",", "subsystem", "\n", "Mechanical", "\n", "engineering", "and", "\n", "heavy", "machineryplate", ",", "chamber", ",", "axis", ",", "body", ",", "rod", ",", "wall", ",", "hole", ",", "angle", ",", "surface", ",", "shaft", ",", "pipe", ",", "opening", ",", "housing", ",", "form", ",", "\n", "plane", ",", "machine", ",", "cylinder", ",", "drive", ",", "valve", ",", "diameter", ",", "groove", ",", "ring", ",", "shell", ",", "section", ",", "rotation", ",", "spring", ",", "portion", ",", "\n", "holder", ",", "pipeline", ",", "guide", ",", "cover", ",", "sleeve", "," ]	[]
… \| … \| … \| … \| … \| … \| … \| … \| \| Austria \| 97 ᵢ \| 97 ₋₁ ᵢ \| 1 \| 1 \| 1 \| 1 \| 7 \| 6 \| 100 \| 100 \| 99 \| 98 \| 85 \| 86 \| 3.4 \| 5.7 \| 5.7 \| \| Belarus \| 97 \| 98 \| 2 \| 4 \| 0.2 \| 0.4 \| 2 \| 1 \| 100 \| 100 \| 99 \| 99 \| 90 \| 93 \| 3.4 \| 2.1 \| 2.1 \| \| Belgium \| 98 ᵢ \| 99 ₋₁ ᵢ \| 1 \| 1 \| 1 \| 1 \| 1 \| 2 \| 99 \| 99 \| 87 \| 91 \| 83 \| 86 \| 8.1 \| 8.1 \| 8.1 \| \| Bermuda \| … \| … \| … \| … \| … \| … \| … \| … \| … \| … \| … \| … \| … \| … \| … \| … \| … \| \| Bosnia and Herzegovina \| 18 ₊₁ \| 32 \| 10 \| 10 \| 3 \| 13 \| 23 \| 27 \| 100 \| 100 \| 98 \| 99 \| 60 \| 65 \| 9.2 \| 11.3 \| 11.3 \| \| Bulgaria \| 94 ᵢ \| 94 ₋₁ ᵢ \| 2 \| 5 \| 3 \| 5 \| 11 \| 9 \| 99 \| 99 \| 94 \| 94 \| 85 \| 87 \| 0.1 \| 0.8 \| 0.8 \| \| Canada \| … \| 95 ₋₁ ᵢ \| 0.1 \| - \| 0.3 \| 0.2 \| 11 \| 9 \| 100 \| 100 \| 99 \| 99 \| 86 \| 88 \| 6.0 \| 6.4 \| 6.4 \| \| Croatia \| 98 ᵢ \| 100 ₋₁ ᵢ \| - \| - \| - \| - \| 9 \| 6 \| 100 \| 100 \| 99 \| 99 \| 96 \| 98 \| 0.7 \| 0.5 \| 0.5 \| \| Czechia \| 91 ᵢ \| 94 ₋₁ ᵢ \| 2 \| 1 \| 0.3 \| 1 \| 4 \| 4 \| 100 \| 100 \| 96 \| 96 \| 90 \| 90 \| 1.3 \| 1.8 \| 1.8 \| \| Denmark \| 99 ᵢ \| 98 ₋₁ ᵢ \| 0.3 \| 0.2 \| 1 \| 1 \| 9 \| 6 \| 100 \| 100 \| 100 \| 100 \| 75	[ "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "\n", "\|", "Austria", " ", "\|", "97", "ᵢ", " ", "\|", "97", "₋₁", "ᵢ", " ", "\|", "1", " ", "\|", "1", " ", "\|", "1", " ", "\|", "1", " ", "\|", "7", " ", "\|", "6", " ", "\|", "100", " ", "\|", "100", " ", "\|", "99", " ", "\|", "98", " ", "\|", "85", " ", "\|", "86", " ", "\|", "3.4", " ", "\|", "5.7", " ", "\|", "5.7", " ", "\|", "\n", "\|", "Belarus", " ", "\|", "97", " ", "\|", "98", " ", "\|", "2", " ", "\|", "4", " ", "\|", "0.2", " ", "\|", "0.4", " ", "\|", "2", " ", "\|", "1", " ", "\|", "100", " ", "\|", "100", " ", "\|", "99", " ", "\|", "99", " ", "\|", "90", " ", "\|", "93", " ", "\|", "3.4", " ", "\|", "2.1", " ", "\|", "2.1", " ", "\|", "\n", "\|", "Belgium", " ", "\|", "98", "ᵢ", " ", "\|", "99", "₋₁", "ᵢ", " ", "\|", "1", " ", "\|", "1", " ", "\|", "1", " ", "\|", "1", " ", "\|", "1", " ", "\|", "2", " ", "\|", "99", " ", "\|", "99", " ", "\|", "87", " ", "\|", "91", " ", "\|", "83", " ", "\|", "86", " ", "\|", "8.1", " ", "\|", "8.1", " ", "\|", "8.1", " ", "\|", "\n", "\|", "Bermuda", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "\n", "\|", "Bosnia", "and", "Herzegovina", " ", "\|", "18", "₊₁", " ", "\|", "32", " ", "\|", "10", " ", "\|", "10", " ", "\|", "3", " ", "\|", "13", " ", "\|", "23", " ", "\|", "27", " ", "\|", "100", " ", "\|", "100", " ", "\|", "98", " ", "\|", "99", " ", "\|", "60", " ", "\|", "65", " ", "\|", "9.2", " ", "\|", "11.3", " ", "\|", "11.3", " ", "\|", "\n", "\|", "Bulgaria", " ", "\|", "94", "ᵢ", " ", "\|", "94", "₋₁", "ᵢ", " ", "\|", "2", " ", "\|", "5", " ", "\|", "3", " ", "\|", "5", " ", "\|", "11", " ", "\|", "9", " ", "\|", "99", " ", "\|", "99", " ", "\|", "94", " ", "\|", "94", " ", "\|", "85", " ", "\|", "87", " ", "\|", "0.1", " ", "\|", "0.8", " ", "\|", "0.8", " ", "\|", "\n", "\|", "Canada", " ", "\|", "…", " ", "\|", "95", "₋₁", "ᵢ", " ", "\|", "0.1", " ", "\|", "-", " ", "\|", "0.3", " ", "\|", "0.2", " ", "\|", "11", " ", "\|", "9", " ", "\|", "100", " ", "\|", "100", " ", "\|", "99", " ", "\|", "99", " ", "\|", "86", " ", "\|", "88", " ", "\|", "6.0", " ", "\|", "6.4", " ", "\|", "6.4", " ", "\|", "\n", "\|", "Croatia", " ", "\|", "98", "ᵢ", " ", "\|", "100", "₋₁", "ᵢ", " ", "\|", "-", " ", "\|", "-", " ", "\|", "-", " ", "\|", "-", " ", "\|", "9", " ", "\|", "6", " ", "\|", "100", " ", "\|", "100", " ", "\|", "99", " ", "\|", "99", " ", "\|", "96", " ", "\|", "98", " ", "\|", "0.7", " ", "\|", "0.5", " ", "\|", "0.5", " ", "\|", "\n", "\|", "Czechia", " ", "\|", "91", "ᵢ", " ", "\|", "94", "₋₁", "ᵢ", " ", "\|", "2", " ", "\|", "1", " ", "\|", "0.3", " ", "\|", "1", " ", "\|", "4", " ", "\|", "4", " ", "\|", "100", " ", "\|", "100", " ", "\|", "96", " ", "\|", "96", " ", "\|", "90", " ", "\|", "90", " ", "\|", "1.3", " ", "\|", "1.8", " ", "\|", "1.8", " ", "\|", "\n", "\|", "Denmark", " ", "\|", "99", "ᵢ", " ", "\|", "98", "₋₁", "ᵢ", " ", "\|", "0.3", " ", "\|", "0.2", " ", "\|", "1", " ", "\|", "1", " ", "\|", "9", " ", "\|", "6", " ", "\|", "100", " ", "\|", "100", " ", "\|", "100", " ", "\|", "100", " ", "\|", "75", " " ]	[]
specialisation domains in Georgia ....................................................... 18 Table VII. Selected S&T specialisation domains in Moldova .................................................... 19 Table VIII. Selected S&T specialisation domains in Ukraine .................................................... 21 Table 2.1. Orbis data availability – Number of enterprises for which at least one data observation is available for 2011-2019 ............................................................................................ 38 Table 2.2. Thresholds used to identify economic specialisations .......................................... 40 Table 2.3. Economic mapping results for Georgia ........................................................................ 41 Table 2.4. Economic mapping results for Moldova ....................................................................... 44 Table 2.5. Economic mapping results for Ukraine ........................................................................ 46 Table 2.6. INDSTAT data availability at NACE three-digit level .............................................. 49 Table 2.7. Industries included in mapping the Manufacturing sector ................................. 52 Table 2.8. Thresholds used to identify economic specialisations in Manufacturing ..... 57 Table 2.9. Economic mapping results for Manufacturing for Armenia ................................ 58 Table 2.10. Economic mapping results for Manufacturing for Azerbaijan ........................ 59 Table 2.11. Economic mapping results for Manufacturing for Georgia .............................. 60 Table 2.12. Economic mapping results for Manufacturing for Moldova ............................. 61 Table 2.13. Economic mapping results for Manufacturing for Ukraine .............................. 62 Table 2.14. Available three-digit goods export data (number of goods categories) ....64 Table 2.15. Thresholds used to identify goods export specialisations ............................... 65 Table 2.16. Goods export specialisation for Armenia ................................................................. 66 Table 2.17. Goods export specialisation for Azerbaijan ............................................................. 68 Table 2.18. Goods export specialisation for Georgia .................................................................. 69 Table 2.19. Goods export specialisation for Moldova ................................................................. 71 Table 2.20. Goods export specialisation for Ukraine ................................................................... 75 Table 2.21. Thresholds used to identify services export specialisations ........................... 80 Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation265 Table 2.22. Services export specialisation for Armenia ............................................................. 81 Table 2.23. Services export specialisation for Azerbaijan ........................................................ 82 Table 2.24. Services export specialisation for Georgia .............................................................. 82 Table 2.25. Services export specialisation for Moldova ............................................................. 83 Table 2.26. Services export specialisation for Ukraine .............................................................. 84 Table 2.27. Weighted number of enterprises covered in the Enterprise Survey ............ 86 Table 2.28. Share of product, process and product and/or process innovators ............. 87 Table 2.29. Specialisation in innovation ............................................................................................ 89 Table 2.30. Number of patents for 2011-2018 ............................................................................ 91 Table 2.31. Industries with innovation potential based on 2011-2018 relative patent performance .................................................................................................................................................... 92 Table 2.32. Specialised industries using data for patents issued ......................................... 94 Table 2.33. Specialised industries using data for patent families* ...................................... 96 Table 2.34. Partial concordance between broad NACE groups and NICE ...........................	[ "specialisation", "domains", "in", "Georgia", ".......................................................", "18", "\n", "Table", "VII", ".", "Selected", "S&T", "specialisation", "domains", "in", "Moldova", "....................................................", "19", "\n", "Table", "VIII", ".", "Selected", "S&T", "specialisation", "domains", "in", "Ukraine", "....................................................", "21", "\n", "Table", "2.1", ".", "Orbis", "data", "availability", "–", "Number", "of", "enterprises", "for", "which", "at", "least", "one", "data", "\n", "observation", "is", "available", "for", "2011", "-", "2019", "............................................................................................", "38", "\n", "Table", "2.2", ".", "Thresholds", "used", "to", "identify", "economic", "specialisations", "..........................................", "40", "\n", "Table", "2.3", ".", "Economic", "mapping", "results", "for", "Georgia", "........................................................................", "41", "\n", "Table", "2.4", ".", "Economic", "mapping", "results", "for", "Moldova", ".......................................................................", "44", "\n", "Table", "2.5", ".", "Economic", "mapping", "results", "for", "Ukraine", "........................................................................", "46", "\n", "Table", "2.6", ".", "INDSTAT", "data", "availability", "at", "NACE", "three", "-", "digit", "level", "..............................................", "49", "\n", "Table", "2.7", ".", "Industries", "included", "in", "mapping", "the", "Manufacturing", "sector", ".................................", "52", "\n", "Table", "2.8", ".", "Thresholds", "used", "to", "identify", "economic", "specialisations", "in", "Manufacturing", ".....", "57", "\n", "Table", "2.9", ".", "Economic", "mapping", "results", "for", "Manufacturing", "for", "Armenia", "................................", "58", "\n", "Table", "2.10", ".", "Economic", "mapping", "results", "for", "Manufacturing", "for", "Azerbaijan", "........................", "59", "\n", "Table", "2.11", ".", "Economic", "mapping", "results", "for", "Manufacturing", "for", "Georgia", "..............................", "60", "\n", "Table", "2.12", ".", "Economic", "mapping", "results", "for", "Manufacturing", "for", "Moldova", ".............................", "61", "\n", "Table", "2.13", ".", "Economic", "mapping", "results", "for", "Manufacturing", "for", "Ukraine", "..............................", "62", "\n", "Table", "2.14", ".", "Available", "three", "-", "digit", "goods", "export", "data", "(", "number", "of", "goods", "categories", ")", "....", "64", "\n", "Table", "2.15", ".", "Thresholds", "used", "to", "identify", "goods", "export", "specialisations", "...............................", "65", "\n", "Table", "2.16", ".", "Goods", "export", "specialisation", "for", "Armenia", ".................................................................", "66", "\n", "Table", "2.17", ".", "Goods", "export", "specialisation", "for", "Azerbaijan", ".............................................................", "68", "\n", "Table", "2.18", ".", "Goods", "export", "specialisation", "for", "Georgia", "..................................................................", "69", "\n", "Table", "2.19", ".", "Goods", "export", "specialisation", "for", "Moldova", ".................................................................", "71", "\n", "Table", "2.20", ".", "Goods", "export", "specialisation", "for", "Ukraine", "...................................................................", "75", "\n", "Table", "2.21", ".", "Thresholds", "used", "to", "identify", "services", "export", "specialisations", "...........................", "80", "\n", "Smart", "Specialisation", "in", "the", "Eastern", "Partnership", "countries", "-", "Potential", "for", "knowledge", "-", "based", "economic", "cooperation265", "\n", "Table", "2.22", ".", "Services", "export", "specialisation", "for", "Armenia", ".............................................................", "81", "\n", "Table", "2.23", ".", "Services", "export", "specialisation", "for", "Azerbaijan", "........................................................", "82", "\n", "Table", "2.24", ".", "Services", "export", "specialisation", "for", "Georgia", "..............................................................", "82", "\n", "Table", "2.25", ".", "Services", "export", "specialisation", "for", "Moldova", ".............................................................", "83", "\n", "Table", "2.26", ".", "Services", "export", "specialisation", "for", "Ukraine", "..............................................................", "84", "\n", "Table", "2.27", ".", "Weighted", "number", "of", "enterprises", "covered", "in", "the", "Enterprise", "Survey", "............", "86", "\n", "Table", "2.28", ".", "Share", "of", "product", ",", "process", "and", "product", "and/or", "process", "innovators", ".............", "87", "\n", "Table", "2.29", ".", "Specialisation", "in", "innovation", "............................................................................................", "89", "\n", "Table", "2.30", ".", "Number", "of", "patents", "for", "2011", "-", "2018", "............................................................................", "91", "\n", "Table", "2.31", ".", "Industries", "with", "innovation", "potential", "based", "on", "2011", "-", "2018", "relative", "patent", "\n", "performance", "....................................................................................................................................................", "92", "\n", "Table", "2.32", ".", "Specialised", "industries", "using", "data", "for", "patents", "issued", ".........................................", "94", "\n", "Table", "2.33", ".", "Specialised", "industries", "using", "data", "for", "patent", "families", "*", "......................................", "96", "\n", "Table", "2.34", ".", "Partial", "concordance", "between", "broad", "NACE", "groups", "and", "NICE", "..........................." ]	[]
\| 4,7 ₋₁ \| 10,7 ₋₁ 12,7 \| 24 470 ₋₂ 11 676 ₋₂ \| 24 268 ₋₂ 28 \| 782 ₋₂ \| ₋₂ 53 195 ₋₂ 18 \| ₋₂ 18 ₋₂ \| 21 ₋₂ \| 39 ₋₂ 39 ₋₂ \| LUX \| \| 5,4 ₋₂ 1,2 ₋₁ \| ₋₂ 7,7 \| … \| 11 514 ₋₂ 17 \| 773 ₋₂ 20 \| 927 ₋₂ 22 \| ₋₂ 22 ₋₂ \| 33 ₋₂ \| \| MLT \| \| \| \| \| \| … \| … 6 \| ₋₁ 4 ₋₁ \| 8 ₋₁ \| 1 ₋₁ \| \| \| \| \| \| … \| \| \| \| \| \| MCO \| \| … \| … \| … \| … 12 \| … \| … \| … … \| … \| … \| MNE \| \| 5,1 ₋₁ \| 11,6 ₋₁ \| 9008 ₋₂ \| 767 ₋₂ 16 \| 046 ₋₂ 21 \| 412 ₋₂ \| 19 \| 24 \| 32 ₋₂ \| NLD \| \| … \| … \| … \| \| \| \| 13 ₋₂ … \| ₋₂ … \| … \| \| \| 4,0 ₋₁ \| 10,1 ₋₁ \| 210 ₋₂ \| … \| … \| \| \| ₋₂ … \| \| MKD \| \| \| \| 17 8087 ₋₂ \| … 907 ₋₂ \| 052 ₋₂ \| 29 270 ₋₂ 19 \| ₋₂ 20 ₋₂ 26 ₋₂ \| 24 ₋₂ \| 33 ₋₂ \| NOR \| \| 4,7 ₋₂ 4,8 ₋₂ \| 11,2 ₋₂ 9,7 ₋₂ \| 17 10 641 ₋₂ 6270 ₋₂ \| 21 7979 \| ₋₂ \| 12 195 ₋₂ 20 16 \| ₋₂ ₋₂ 25 ₋₂ \| 20 ₋₂ 29 ₋₂ \| 30 ₋₂ 21 ₋₂ \| POL PRT \| \| 6,3 \| 15,8 ₋₁ \| 4838 ₋₁ \| 9794 ₋₂ 11 ₋₁ \| 355 ₋₂ 3299 ₋₁ \| 8297 ₋₂ 3873 ₋₁ 32 \| ₋₁ 21 ₋₁ \| \| 25 ₋₁ \| \| \| 3,3 ₋₂ \| 8,1 ₋₂ \| 5009 ₋₂ \| 3206 3321 \| \| \| 9 ₋₂ \| 22 \| 26 ₋₂ \| MDA \| \| 4,1 ₋₁ \| 8,9 ₋₃ \| … \| ₋₂ \| 7013 ₋₂ \| 9786 ₋₂ 13 \| ₋₂ … \| ₋₁ 18 ₋₂ \| \| ROU RUS \| \| \| \| \| \| … \| 6872 \| \| … \| 19 \| \| \| 3,4 ₋₁ \| 7,5 ₋₁ \| 15 337 ₋₂ \|	[ "\|", "4,7", "₋₁", " ", "\|", "10,7", "₋₁", "12,7", " ", "\|", "24", "470", "₋₂", "11", "676", "₋₂", " ", "\|", "24", "268", "₋₂", "28", " ", "\|", "782", "₋₂", " ", "\|", "₋₂", "53", "195", "₋₂", "18", " ", "\|", "₋₂", "18", "₋₂", " ", "\|", "21", "₋₂", " ", "\|", "39", "₋₂", "39", "₋₂", " ", "\|", "LUX", " ", "\|", "\n", "\|", "5,4", "₋₂", "1,2", "₋₁", " ", "\|", "₋₂", "7,7", " ", "\|", "…", " ", "\|", "11", "514", "₋₂", "17", " ", "\|", "773", "₋₂", "20", " ", "\|", "927", "₋₂", "22", " ", "\|", "₋₂", "22", "₋₂", " ", "\|", "33", "₋₂", " ", "\|", " ", "\|", "MLT", " ", "\|", "\n", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "…", " ", "\|", "…", "6", " ", "\|", "₋₁", "4", "₋₁", " ", "\|", "8", "₋₁", " ", "\|", "1", "₋₁", " ", "\|", " ", "\|", "\n", "\|", " ", "\|", " ", "\|", " ", "\|", "…", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "MCO", " ", "\|", "\n", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", "12", " ", "\|", "…", " ", "\|", "…", " ", "\|", "…", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", "MNE", " ", "\|", "\n", "\|", "5,1", "₋₁", " ", "\|", "11,6", "₋₁", " ", "\|", "9008", "₋₂", " ", "\|", "767", "₋₂", "16", " ", "\|", "046", "₋₂", "21", " ", "\|", "412", "₋₂", " ", "\|", "19", " ", "\|", "24", " ", "\|", "32", "₋₂", " ", "\|", "NLD", " ", "\|", "\n", "\|", "…", " ", "\|", "…", " ", "\|", "…", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "13", "₋₂", "…", " ", "\|", "₋₂", "…", " ", "\|", "…", " ", "\|", " ", "\|", "\n", "\|", "4,0", "₋₁", " ", "\|", "10,1", "₋₁", " ", "\|", "210", "₋₂", " ", "\|", "…", " ", "\|", "…", " ", "\|", " ", "\|", " ", "\|", "₋₂", "…", " ", "\|", " ", "\|", "MKD", " ", "\|", "\n", "\|", " ", "\|", " ", "\|", "17", "8087", "₋₂", " ", "\|", "…", "907", "₋₂", " ", "\|", "052", "₋₂", " ", "\|", "29", "270", "₋₂", "19", " ", "\|", "₋₂", "20", "₋₂", "26", "₋₂", " ", "\|", "24", "₋₂", " ", "\|", "33", "₋₂", " ", "\|", "NOR", " ", "\|", "\n", "\|", "4,7", "₋₂", "4,8", "₋₂", " ", "\|", "11,2", "₋₂", "9,7", "₋₂", " ", "\|", "17", "10", "641", "₋₂", "6270", "₋₂", " ", "\|", "21", "7979", " ", "\|", "₋₂", " ", "\|", "12", "195", "₋₂", "20", "16", " ", "\|", "₋₂", "₋₂", "25", "₋₂", " ", "\|", "20", "₋₂", "29", "₋₂", " ", "\|", "30", "₋₂", "21", "₋₂", " ", "\|", "POL", "PRT", " ", "\|", "\n", "\|", "6,3", " ", "\|", "15,8", "₋₁", " ", "\|", "4838", "₋₁", " ", "\|", "9794", "₋₂", "11", "₋₁", " ", "\|", "355", "₋₂", "3299", "₋₁", " ", "\|", "8297", "₋₂", "3873", "₋₁", "32", " ", "\|", "₋₁", "21", "₋₁", " ", "\|", " ", "\|", "25", "₋₁", " ", "\|", " ", "\|", "\n", "\|", "3,3", "₋₂", " ", "\|", "8,1", "₋₂", " ", "\|", "5009", "₋₂", " ", "\|", "3206", "3321", " ", "\|", " ", "\|", " ", "\|", "9", "₋₂", " ", "\|", "22", " ", "\|", "26", "₋₂", " ", "\|", "MDA", " ", "\|", "\n", "\|", "4,1", "₋₁", " ", "\|", "8,9", "₋₃", " ", "\|", "…", " ", "\|", "₋₂", " ", "\|", "7013", "₋₂", " ", "\|", "9786", "₋₂", "13", " ", "\|", "₋₂", "…", " ", "\|", "₋₁", "18", "₋₂", " ", "\|", " ", "\|", "ROU", "RUS", " ", "\|", "\n", "\|", " ", "\|", " ", "\|", " ", "\|", " ", "\|", "…", " ", "\|", "6872", " ", "\|", " ", "\|", "…", " ", "\|", "19", " ", "\|", " ", "\|", "\n", "\|", "3,4", "₋₁", " ", "\|", "7,5", "₋₁", " ", "\|", "15", "337", "₋₂", " ", "\|" ]	[]
loop can connect enablers and features of public intent data with greater development value Source: WDR 2021 team.deliveryFinancing Technical capacit yG overnance Data demandEnablers of public in tent data Desirable features of public in tent data Adequat e coverage Completeness Timeliness FrequencyHigh quality Granularity Accurac y ComparabilityEasy to use Accessibility Understandability Interoperability Safe to use Impartiality Conﬁdentiality Appropriateness Value of public in tent data Impr oved service scar ce resour cesPrioritization of empow ermentAccountability and 66 \| World Development Report 2021 Underinvestment by governments. Underinvestment in public intent data systems is widespread. Only half of countries had a national statistical plan that was fully funded in 2019 (figure 2.7). 70 Lack of national funding for statistics is especially a struggle for frag - ile and conflict-affected countries, countries in Sub- Saharan Africa, and low-income countries. Whereas 93 percent of high-income countries have a fully funded national statistical plan, not a single low-income country has one. A recent review of public financing of statistics found that seven of 10 low- and middle- income countries analyzed funded less than half of their respective national statistical plans, with country contributions ranging from 9 percent to 77 percent. 71 This problem is more pressing in low-income countries with less government revenue to spend on multiple priorities. However, the cost of public data systems is modest relative to that of other government functions. Decision-makers in budget offices may not fully understand how much funding is needed to produce high-quality data or lack the incentives to prioritize data. How well public data systems are funded is thus also a matter of high-level government officials recognizing the value of public intent data and offering leadership to encourage col-lection of them. 72 A key factor in such an effort is the perceived relevance and credibility of public intent data and its producers. 73 Another reason for lack of funding for data is the absence of a benchmark guiding how much govern-ments should spend, unlike for other areas of gov - ernment spending. For example, the Education 2030 Framework for Action urges countries to allocate at least 4–6 percent of GDP or at least 15–20 percent of their total public expenditure to education. The Abuja Declaration urges countries to spend at least 15 percent of their annual budget to improve the health sector. 74 No similar guidelines are found on data. Underinvestment by donors. Donors also invest rel- atively	[ "loop", "can", "connect", "enablers", "and", "features", "of", "public", "\n", "intent", "data", "with", "greater", "development", "value", "\n", "Source", ":", "WDR", "2021", "team.deliveryFinancing", "Technical", "capacit", "yG", "overnance", "Data", "demandEnablers", " ", "of", "public", "in", "tent", "data", "\n", "Desirable", "features", "of", "public", "in", "tent", "data", "\n", "Adequat", "e", "coverage", "\n", "Completeness", "\n", "Timeliness", "\n", "FrequencyHigh", "quality", "\n", "Granularity", "\n", "Accurac", "y", "\n", "ComparabilityEasy", " ", "to", "use", "\n", "Accessibility", "\n", "Understandability", "\n", "Interoperability", "Safe", "to", "use", "\n", "Impartiality", "\n", "Conﬁdentiality", "\n", "Appropriateness", "\n", "Value", "of", "public", "in", "tent", "data", "\n", "Impr", "oved", "service", "\n", "scar", "ce", "resour", "cesPrioritization", "of", "\n", "empow", "ermentAccountability", "and", "\n", "66", " ", "\|", " ", "World", "Development", "Report", "2021", "\n", "Underinvestment", "by", "governments", ".", "Underinvestment", "\n", "in", "public", "intent", "data", "systems", "is", "widespread", ".", "Only", "half", "\n", "of", "countries", "had", "a", "national", "statistical", "plan", "that", "was", "fully", "funded", "in", "2019", "(", "figure", "2.7", ")", ".", "\n", "70", "Lack", "of", "national", "\n", "funding", "for", "statistics", "is", "especially", "a", "struggle", "for", "frag", "-", "\n", "ile", "and", "conflict", "-", "affected", "countries", ",", "countries", "in", "Sub-", " \n", "Saharan", "Africa", ",", "and", "low", "-", "income", "countries", ".", "Whereas", " \n", "93", "percent", "of", "high", "-", "income", "countries", "have", "a", "fully", "funded", "national", "statistical", "plan", ",", "not", "a", "single", "low", "-", "income", "country", "has", "one", ".", "A", "recent", "review", "of", "public", "financing", "of", "statistics", "found", "that", "seven", "of", "10", "low-", "and", "middle-", " \n", "income", "countries", "analyzed", "funded", "less", "than", "half", "of", "their", "respective", "national", "statistical", "plans", ",", "with", "country", "contributions", "ranging", "from", "9", "percent", "to", "77", "percent", ".", "\n", "71", "\n", "This", "problem", "is", "more", "pressing", "in", "low", "-", "income", "\n", "countries", "with", "less", "government", "revenue", "to", "spend", "on", "multiple", "priorities", ".", "However", ",", "the", "cost", "of", "public", "data", "systems", "is", "modest", "relative", "to", "that", "of", "other", "government", "functions", ".", "Decision", "-", "makers", "in", "budget", "offices", "may", "not", "fully", "understand", "how", "much", "funding", "is", "needed", "to", "produce", "high", "-", "quality", "data", "or", "lack", "the", "incentives", "to", "prioritize", "data", ".", "How", "well", "public", "data", "systems", "are", "funded", "is", "thus", "also", "a", "matter", "of", "high", "-", "level", "government", "officials", "recognizing", "the", "value", "of", "public", "intent", "data", "and", "offering", "leadership", "to", "encourage", "col", "-", "lection", "of", "them", ".", "\n", "72", "A", "key", "factor", "in", "such", "an", "effort", "is", "the", "perceived", "relevance", "and", "credibility", "of", "public", "intent", "data", "and", "its", "producers", ".", "\n", "73", "\n", "Another", "reason", "for", "lack", "of", "funding", "for", "data", "is", "the", "\n", "absence", "of", "a", "benchmark", "guiding", "how", "much", "govern", "-", "ments", "should", "spend", ",", "unlike", "for", "other", "areas", "of", "gov", "-", "\n", "ernment", "spending", ".", "For", "example", ",", "the", "Education", "2030", "Framework", "for", "Action", "urges", "countries", "to", "allocate", "at", "least", "4–6", "percent", "of", "GDP", "or", "at", "least", "15–20", "percent", "of", "their", "total", "public", "expenditure", "to", "education", ".", "The", "Abuja", "Declaration", "urges", "countries", "to", "spend", "at", "least", " \n", "15", "percent", "of", "their", "annual", "budget", "to", "improve", "the", "health", "sector", ".", "\n", "74", "No", "similar", "guidelines", "are", "found", "on", "data", ".", "\n", "Underinvestment", "by", "donors", ".", "Donors", "also", "invest", "rel-", "\n", "atively" ]	[ { "end": 207, "label": "CITATION_SPAN", "start": 101 } ]
leverage is notable especially in the case of pipeline gas, where the possibility of rerouting gas flows is more limited as shown by the latest unsuccessful efforts by Russia. During the 2022 crisis, for example, intra-EU competition for natural gas between actors willing to pay high prices contributed to an excessive and unnecessary rise in prices. In response, the EU introduced a coordination mechanism to aggregate and match demand with competitive supply offers (AggregateEU), but there is no obligation for joint purchasing on the platform. At the same time, although natural gas prices have fallen considerably from their peaks during the energy crisis, the EU faces an increasingly volatile outlook. With the loss of access to Russian pipeline gas, 42% of EU gas imports arrived as LNG in 2023, 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	[ "leverage", "is", "notable", "especially", "in", "the", "case", "of", "pipeline", "gas", ",", "where", "the", "possibility", "of", "\n", "rerouting", "gas", "flows", "is", "more", "limited", "as", "shown", "by", "the", "latest", "unsuccessful", "efforts", "by", "Russia", ".", "During", "the", "2022", "crisis", ",", "for", "\n", "example", ",", "intra", "-", "EU", "competition", "for", "natural", "gas", "between", "actors", "willing", "to", "pay", "high", "prices", "contributed", "to", "an", "excessive", "\n", "and", "unnecessary", "rise", "in", "prices", ".", "In", "response", ",", "the", "EU", "introduced", "a", "coordination", "mechanism", "to", "aggregate", "and", "match", "\n", "demand", "with", "competitive", "supply", "offers", "(", "AggregateEU", ")", ",", "but", "there", "is", "no", "obligation", "for", "joint", "purchasing", "on", "the", "platform", ".", "\n", "At", "the", "same", "time", ",", "although", "natural", "gas", "prices", "have", "fallen", "considerably", "from", "their", "peaks", "during", "the", "energy", "crisis", ",", "the", "\n", "EU", "faces", "an", "increasingly", "volatile", "outlook", ".", "With", "the", "loss", "of", "access", "to", "Russian", "pipeline", "gas", ",", "42", "%", "of", "EU", "gas", "imports", "\n", "arrived", "as", "LNG", "in", "2023", ",", "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" ]	[ { "end": 1938, "label": "CITATION_REF", "start": 1935 } ]
and/or some other example(s) herein, wherein retasking the MHU includes: causing the MHU to move from a current location within the MRF to a service center when an operating condition of the MHUs indicates that service is needed. Example [0238] includes the method of examples [0231]-[0237] and/or some other example(s) herein, wherein, when the MHU is a conveyor system, retasking the MHU includes: causing the conveyor system to change a speed, direction, or orientation of a conveyor mechanism. Example [0239] includes the method of examples [0231]-[0238] and/or some other example(s) herein, wherein, when the MHU is a baling system, to retasking the MHU includes: causing the baling system to change a baling process based on a composition of the material stream. Example [0240] includes the method of example [0239] and/or some other example(s) herein, wherein retasking the MHU includes: causing the baling system to queue material bales based on material composition such that individual material bales have different purity levels. Example [0241] includes the method of examples [0231]-[0240] and/or some other example(s) herein, wherein, when the MHU is an infeed system, retasking the MHU includes: autonomously controlling the infeed system to infeed different combinations of materials to achieve semi-homogeneous material distribution. Example [0242] includes the method of examples [0231]-[0241] and/or some other example(s) herein, wherein retasking the MHU includes: causing the MHU to activate or deactivate one or more sorting technologies to optimize resource consumption by the MHU. Example [0243] includes the method of examples [0228]-[0242] and/or some other example(s) herein, wherein the method includes operating a first machine learning model to perform the identification and classification of objects within the material stream based on the data streams. Example [0244] includes the method of example [0243] and/or some other example(s) herein, wherein the method includes operating a second machine learning model to determine the MRF arrangement. Example [0245] includes the method of example [0244] and/or some other example(s) herein, wherein the first machine learning model is different than the second machine learning model. Example [0246] includes the method of examples [0228]-[0245] and/or some other example(s) herein, wherein the MRF arrangement is based on a flow the material stream to one or more MHUs of the set of MHUs to achieve load balancing among the set of MHUs. Example [0247] includes the method of example [0228]-[0246] and/or some other example(s) herein, wherein the set of MHUs include one or more of	[ "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "retasking", "the", "MHU", "includes", ":", "causing", "the", "MHU", "to", "move", "from", "a", "current", "location", "within", "the", "MRF", "to", "a", "service", "center", "when", "an", "operating", "condition", "of", "the", "MHUs", "indicates", "that", "service", "is", "needed", ".", "\n\n", "Example", "[", "0238", "]", "includes", "the", "method", "of", "examples", "[", "0231]-[0237", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", ",", "when", "the", "MHU", "is", "a", "conveyor", "system", ",", "retasking", "the", "MHU", "includes", ":", "causing", "the", "conveyor", "system", "to", "change", "a", "speed", ",", "direction", ",", "or", "orientation", "of", "a", "conveyor", "mechanism", ".", "\n\n", "Example", "[", "0239", "]", "includes", "the", "method", "of", "examples", "[", "0231]-[0238", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", ",", "when", "the", "MHU", "is", "a", "baling", "system", ",", "to", "retasking", "the", "MHU", "includes", ":", "causing", "the", "baling", "system", "to", "change", "a", "baling", "process", "based", "on", "a", "composition", "of", "the", "material", "stream", ".", "\n\n", "Example", "[", "0240", "]", "includes", "the", "method", "of", "example", "[", "0239", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "retasking", "the", "MHU", "includes", ":", "causing", "the", "baling", "system", "to", "queue", "material", "bales", "based", "on", "material", "composition", "such", "that", "individual", "material", "bales", "have", "different", "purity", "levels", ".", "\n\n", "Example", "[", "0241", "]", "includes", "the", "method", "of", "examples", "[", "0231]-[0240", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", ",", "when", "the", "MHU", "is", "an", "infeed", "system", ",", "retasking", "the", "MHU", "includes", ":", "autonomously", "controlling", "the", "infeed", "system", "to", "infeed", "different", "combinations", "of", "materials", "to", "achieve", "semi", "-", "homogeneous", "material", "distribution", ".", "\n\n", "Example", "[", "0242", "]", "includes", "the", "method", "of", "examples", "[", "0231]-[0241", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "retasking", "the", "MHU", "includes", ":", "causing", "the", "MHU", "to", "activate", "or", "deactivate", "one", "or", "more", "sorting", "technologies", "to", "optimize", "resource", "consumption", "by", "the", "MHU", ".", "\n\n", "Example", "[", "0243", "]", "includes", "the", "method", "of", "examples", "[", "0228]-[0242", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "the", "method", "includes", "operating", "a", "first", "machine", "learning", "model", "to", "perform", "the", "identification", "and", "classification", "of", "objects", "within", "the", "material", "stream", "based", "on", "the", "data", "streams", ".", "\n\n", "Example", "[", "0244", "]", "includes", "the", "method", "of", "example", "[", "0243", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "the", "method", "includes", "operating", "a", "second", "machine", "learning", "model", "to", "determine", "the", "MRF", "arrangement", ".", "\n\n", "Example", "[", "0245", "]", "includes", "the", "method", "of", "example", "[", "0244", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "the", "first", "machine", "learning", "model", "is", "different", "than", "the", "second", "machine", "learning", "model", ".", "\n\n", "Example", "[", "0246", "]", "includes", "the", "method", "of", "examples", "[", "0228]-[0245", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "the", "MRF", "arrangement", "is", "based", "on", "a", "flow", "the", "material", "stream", "to", "one", "or", "more", "MHUs", "of", "the", "set", "of", "MHUs", "to", "achieve", "load", "balancing", "among", "the", "set", "of", "MHUs", ".", "\n\n", "Example", "[", "0247", "]", "includes", "the", "method", "of", "example", "[", "0228]-[0246", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "the", "set", "of", "MHUs", "include", "one", "or", "more", "of" ]	[]
of mintegers. 2.8 SciDetect Method The next approach [21] was invented to detect documents automatically generated using the software SCIGen, MathGen, PropGen and PhysGen. For this, the distancesbetween a text and others (inter-textual distances) are computed. Then these distancesare used to determine which texts, within a large set, are closer to each other and maythus be grouped together. Inter-textual distance depends on four factors: genre, author,subject and epoch. As the authors don ’t provide any numerical results of the method ’s work, we have implemented the method using the source Java code provided by SciDetect developers. 3 Choosing a Method Every arti ﬁcial content is generated for a speci ﬁc purpose. Here we focus only on fake scienti ﬁc paper for academic publishing or increase in the percentage of originality of the article. It is important to recognize the aim of fake content for its subsequent detection. Various generation strategies require different approaches to ﬁnd it. For example, algorithms for detecting word salad are clearly possible and are not particularly dif ﬁcult to implement. A statistical approach based on Zipf ’s law of word frequency has potential in detecting simple word salad, as do grammar checking and the use of naturallanguage processing. Statistical Markovian analysis, where short phrases are used todetermine if they can occur in normal English sentences, is another statistical approach that would be effective against completely random phrasing but might be fooled by dissociated press methods. Combining linguistic and statistical features can improvethe result of experiment. By contrast, texts generated with stochastic language modelsappear much harder to detect. One also needs to estimate the data capacity. Text corpuses are taken depending on the aim of the experiment and capabilities of getting them. Like a generation strategy,every data capacity needs different approach. For instance, small trainings samplespermit to use such indexes as Jaccard or Dice [ 5] to count the similarity measure or distance between documents. For big datasets, one can use some linguistics features424 D. Beresneva and variations of Support Vector Machine and Decision Trees algorithms. Table 1 summarizes results of described methods. The numerical results are provided by theauthors of the articles, except the last one. 4 Conclusion This work presents the results of a systematic review of arti ﬁcial content detection methods. About a hundred articles were considered for this review; perhaps one-sixthof them met our selection criteria. All the presented methods give good result	[ "of", "mintegers", ".", "\n", "2.8", "SciDetect", "Method", "\n", "The", "next", "approach", "[", "21", "]", "was", "invented", "to", "detect", "documents", "automatically", "generated", "\n", "using", "the", "software", "SCIGen", ",", "MathGen", ",", "PropGen", "and", "PhysGen", ".", "For", "this", ",", "the", "distancesbetween", "a", "text", "and", "others", "(", "inter", "-", "textual", "distances", ")", "are", "computed", ".", "Then", "these", "distancesare", "used", "to", "determine", "which", "texts", ",", "within", "a", "large", "set", ",", "are", "closer", "to", "each", "other", "and", "maythus", "be", "grouped", "together", ".", "Inter", "-", "textual", "distance", "depends", "on", "four", "factors", ":", "genre", ",", "author", ",", "subject", "and", "epoch", ".", "\n", "As", "the", "authors", "don", "’", "t", "provide", "any", "numerical", "results", "of", "the", "method", "’s", "work", ",", "we", "have", "\n", "implemented", "the", "method", "using", "the", "source", "Java", "code", "provided", "by", "SciDetect", "developers", ".", "\n", "3", "Choosing", "a", "Method", "\n", "Every", "arti", "ﬁcial", "content", "is", "generated", "for", "a", "speci", "ﬁc", "purpose", ".", "Here", "we", "focus", "only", "on", "fake", "\n", "scienti", "ﬁc", "paper", "for", "academic", "publishing", "or", "increase", "in", "the", "percentage", "of", "originality", "of", "\n", "the", "article", ".", "\n", "It", "is", "important", "to", "recognize", "the", "aim", "of", "fake", "content", "for", "its", "subsequent", "detection", ".", "\n", "Various", "generation", "strategies", "require", "different", "approaches", "to", "ﬁnd", "it", ".", "For", "example", ",", "\n", "algorithms", "for", "detecting", "word", "salad", "are", "clearly", "possible", "and", "are", "not", "particularly", "dif", "ﬁcult", "\n", "to", "implement", ".", "A", "statistical", "approach", "based", "on", "Zipf", "’s", "law", "of", "word", "frequency", "has", "\n", "potential", "in", "detecting", "simple", "word", "salad", ",", "as", "do", "grammar", "checking", "and", "the", "use", "of", "naturallanguage", "processing", ".", "Statistical", "Markovian", "analysis", ",", "where", "short", "phrases", "are", "used", "todetermine", "if", "they", "can", "occur", "in", "normal", "English", "sentences", ",", "is", "another", "statistical", "approach", "\n", "that", "would", "be", "effective", "against", "completely", "random", "phrasing", "but", "might", "be", "fooled", "by", "\n", "dissociated", "press", "methods", ".", "Combining", "linguistic", "and", "statistical", "features", "can", "improvethe", "result", "of", "experiment", ".", "By", "contrast", ",", "texts", "generated", "with", "stochastic", "language", "modelsappear", "much", "harder", "to", "detect", ".", "\n", "One", "also", "needs", "to", "estimate", "the", "data", "capacity", ".", "Text", "corpuses", "are", "taken", "depending", "on", "\n", "the", "aim", "of", "the", "experiment", "and", "capabilities", "of", "getting", "them", ".", "Like", "a", "generation", "strategy", ",", "every", "data", "capacity", "needs", "different", "approach", ".", "For", "instance", ",", "small", "trainings", "samplespermit", "to", "use", "such", "indexes", "as", "Jaccard", "or", "Dice", "[", "5", "]", "to", "count", "the", "similarity", "measure", "or", "\n", "distance", "between", "documents", ".", "For", "big", "datasets", ",", "one", "can", "use", "some", "linguistics", "features424", "D.", "Beresneva", "\n", "and", "variations", "of", "Support", "Vector", "Machine", "and", "Decision", "Trees", "algorithms", ".", "Table", "1", "\n", "summarizes", "results", "of", "described", "methods", ".", "The", "numerical", "results", "are", "provided", "by", "theauthors", "of", "the", "articles", ",", "except", "the", "last", "one", ".", "\n", "4", "Conclusion", "\n", "This", "work", "presents", "the", "results", "of", "a", "systematic", "review", "of", "arti", "ﬁcial", "content", "detection", "\n", "methods", ".", "About", "a", "hundred", "articles", "were", "considered", "for", "this", "review", ";", "perhaps", "one", "-", "sixthof", "them", "met", "our", "selection", "criteria", ".", "All", "the", "presented", "methods", "give", "good", "result" ]	[ { "end": 56, "label": "CITATION_ID", "start": 54 }, { "end": 2035, "label": "CITATION_ID", "start": 2034 } ]
extreme poverty. 59 It is therefore difficult to under - stand changes in living standards over time and design policies to eradicate poverty. Recent innova-tions in data collection in these countries suggest a slightly more optimistic picture for the future. 60 It is also important to note that some lack of comparabil-ity over time is necessary, particularly when adopting new global standards. When data are not easy to use: Lack of accessibility, understandability, and interoperabilityLack of data accessibility prohibits actors from using data. According to an assessment of the Open Data Inventory, lower-income countries lag far behind in overall data openness (table 2.1), although even high- income countries have mediocre openness scores. Only 11 percent of low-income countries consistently make data available with a license classifiable as open, compared with 19 percent of lower-middle-income countries, 22 percent of upper-middle-income coun-tries, and 44 percent of high-income countries. The Open Data Inventory assessment also reveals some limitations to machine readability. To the extent that governments publish official statistics, only 37 percent of low-income countries make at least some of these available in machine readable formats, compared with 51 percent of lower-middle-income countries, 61 percent of upper-middle-income coun-tries, and 81 percent of high-income countries. One reason for lack of data accessibility is that data systems in the public sector can be very fragmented. The health sector, for example, often has many dif - ferent health information systems because of its ten-dency to have many different service providers. These include many private providers whose data are often Data as a force for public good \| 63 unavailable to the Ministry of Health. In Ethiopia, a study of the health sector found 228 different digital health information applications, of which only 39 per - cent sent data to the Ministry of Health. 61 Administra- tive data, in particular, are too often siloed in different systems, prohibiting their effective use for monitoring and policy design. Although data coordination within agencies is often limited, the challenge of siloed sys-tems is even greater across government agencies. 62 Lack of understandability prevents even those data that are accessible from generating value. To be understandable, data must be well disseminated, backed up with sufficient metadata, responsive to user needs, and, for certain purposes, summarized and visualized for the user. A majority of countries have data portals and provide metadata for their pub-lished data—practices that facilitate wider data use. 63 Low-income	[ "extreme", "poverty", ".", "\n", "59", "It", "is", "therefore", "difficult", "to", "under", "-", "\n", "stand", "changes", "in", "living", "standards", "over", "time", "and", "design", "policies", "to", "eradicate", "poverty", ".", "Recent", "innova", "-", "tions", "in", "data", "collection", "in", "these", "countries", "suggest", "a", "slightly", "more", "optimistic", "picture", "for", "the", "future", ".", "\n", "60", "It", "is", "\n", "also", "important", "to", "note", "that", "some", "lack", "of", "comparabil", "-", "ity", "over", "time", "is", "necessary", ",", "particularly", "when", "adopting", "new", "global", "standards", ".", "\n", "When", "data", "are", "not", "easy", "to", "use", ":", " \n", "Lack", "of", "accessibility", ",", "understandability", ",", "and", "interoperabilityLack", "of", "data", "accessibility", "prohibits", "actors", "from", "using", "data", ".", "According", "to", "an", "assessment", "of", "the", "Open", "Data", "Inventory", ",", "lower", "-", "income", "countries", "lag", "far", "behind", "in", "overall", "data", "openness", "(", "table", "2.1", ")", ",", "although", "even", "high-", " \n", "income", "countries", "have", "mediocre", "openness", "scores", ".", "Only", "11", "percent", "of", "low", "-", "income", "countries", "consistently", "make", "data", "available", "with", "a", "license", "classifiable", "as", "open", ",", "compared", "with", "19", "percent", "of", "lower", "-", "middle", "-", "income", "countries", ",", "22", "percent", "of", "upper", "-", "middle", "-", "income", "coun", "-", "tries", ",", "and", "44", "percent", "of", "high", "-", "income", "countries", ".", "\n", "The", "Open", "Data", "Inventory", "assessment", "also", "reveals", "\n", "some", "limitations", "to", "machine", "readability", ".", "To", "the", " \n", "extent", "that", "governments", "publish", "official", "statistics", ",", "only", "37", "percent", "of", "low", "-", "income", "countries", "make", "at", "least", "some", "of", "these", "available", "in", "machine", "readable", "formats", ",", "compared", "with", "51", "percent", "of", "lower", "-", "middle", "-", "income", "countries", ",", "61", "percent", "of", "upper", "-", "middle", "-", "income", "coun", "-", "tries", ",", "and", "81", "percent", "of", "high", "-", "income", "countries", ".", "\n", "One", "reason", "for", "lack", "of", "data", "accessibility", "is", "that", "data", "\n", "systems", "in", "the", "public", "sector", "can", "be", "very", "fragmented", ".", "The", "health", "sector", ",", "for", "example", ",", "often", "has", "many", "dif", "-", "\n", "ferent", "health", "information", "systems", "because", "of", "its", "ten", "-", "dency", "to", "have", "many", "different", "service", "providers", ".", "These", "include", "many", "private", "providers", "whose", "data", "are", "often", "\n", "Data", "as", "a", "force", "for", "public", "good", " ", "\|", " ", "63", "\n", "unavailable", "to", "the", "Ministry", "of", "Health", ".", "In", "Ethiopia", ",", "a", "\n", "study", "of", "the", "health", "sector", "found", "228", "different", "digital", "health", "information", "applications", ",", "of", "which", "only", "39", "per", "-", "\n", "cent", "sent", "data", "to", "the", "Ministry", "of", "Health", ".", "\n", "61", "Administra-", "\n", "tive", "data", ",", "in", "particular", ",", "are", "too", "often", "siloed", "in", "different", "systems", ",", "prohibiting", "their", "effective", "use", "for", "monitoring", "and", "policy", "design", ".", "Although", "data", "coordination", "within", "agencies", "is", "often", "limited", ",", "the", "challenge", "of", "siloed", "sys", "-", "tems", "is", "even", "greater", "across", "government", "agencies", ".", "\n", "62", "\n", "Lack", "of", "understandability", "prevents", "even", "those", "data", "\n", "that", "are", "accessible", "from", "generating", "value", ".", "To", "be", "understandable", ",", "data", "must", "be", "well", "disseminated", ",", "backed", "up", "with", "sufficient", "metadata", ",", "responsive", "to", "user", "needs", ",", "and", ",", "for", "certain", "purposes", ",", "summarized", "and", "visualized", "for", "the", "user", ".", "A", "majority", "of", "countries", "have", "data", "portals", "and", "provide", "metadata", "for", "their", "pub", "-", "lished", "data", "—", "practices", "that", "facilitate", "wider", "data", "use", ".", "\n", "63", "\n", "Low", "-", "income" ]	[]

Vam k D. Volkan ı is an Emeritus Professor of Psychiatry at the University of Virginia and an Emeritus Training and Supervising Analyst at the Washington-Baltimore Psychoanalytic Institute. He is the Emeritus President of the International Dialogue Initiative. healing such traumas. This chapter explores psychopolitical concepts that have proven helpful in attempts to enable collective healing. ## Types of Massive Traumas Massive traumas vary in type. Some spring from natural causes, such as earthquakes, tropical storms, tsunamis, floods, forest fires or volcanic eruptions. Some are due to man-made but accidental disasters, such as the 1986 Chernobyl accident that contaminated the atmosphere with tons of radioactive dust. Society may also respond with trauma to the murder or sudden death of a person who functioned as a symbol that unconsciously stood for a parent figure and/or was perceived as a representative of a large-group identity. Assassinations of John F. Kennedy¹ and Martin Luther King, Jr. in the United States, Yitzhak Rabin in Israel,² Prime Minister Olof Palme in Sweden, the National Democratic Party leader Giorgi Chanturia in the Republic of Georgia, former Prime Minister Rafik Hariri in Lebanon, or the deaths of the American astronauts, especially teacher Christa McAuliffe, in the 1986 space shuttle Challenger explosion,³ and the death of Diana, Princess of Wales, in a car accident in 1997, ⁴ all led to responses that were experienced as shared trauma. Other massive traumas such as terrorist attacks, wars and even genocide can be ascribed to the deliberate actions of an enemy, an outsider. They might spring from a territorial conflict between two neighbouring countries that results in mass atrocities, such as the territorial conflict between India and Pakistan in Kashmir that has led to the disappearance of more than 8,000 persons since 1989, and thousands of extra-judicial killings, torture and rape, with Kashmiri Muslims fearing that they will lose their culture. Such deliberate catastrophes can also occur within a national boundary when there is chronic mistreatment or oppression of a smaller racial or ethnic group by the dominant Other. One of the best-known examples of this is the history of slavery in the United States and the discrimination towards black Americans 1 Wolfenstein & Kliman (Eds.) (1965). Children and the death of a president: Multi-disciplinary studies. 2 Erlich (1998). Adolescents ' reactions to Rabin s assassination: A case of patricide? ' Raviv et al. (2000). Young Israelis ' reactions to national

[ "Vam", "k", "D.", "Volkan", "ı", "is", "an", "Emeritus", "Professor", "of", "Psychiatry", "at", "the", "University", "of", "Virginia", "and", "an", "Emeritus", "Training", "and", "Supervising", "Analyst", "at", "the", "Washington", "-", "Baltimore", "Psychoanalytic", "Institute", ".", "He", "is", "the", "Emeritus", "President", "of", "the", "International", "Dialogue", "Initiative", ".", "\n\n", "healing", "such", "traumas", ".", "This", "chapter", "explores", "psychopolitical", "concepts", "that", "have", "proven", "helpful", "in", "attempts", "to", "enable", "collective", "healing", ".", "\n\n", "#", "#", "Types", "of", "Massive", "Traumas", "\n\n", "Massive", "traumas", "vary", "in", "type", ".", "Some", "spring", "from", "natural", "causes", ",", "such", "as", "earthquakes", ",", "tropical", "storms", ",", "tsunamis", ",", "floods", ",", "forest", "fires", "or", "volcanic", "eruptions", ".", "Some", "are", "due", "to", "man", "-", "made", "but", "accidental", "disasters", ",", "such", "as", "the", "1986", "Chernobyl", "accident", "that", "contaminated", "the", "atmosphere", "with", "tons", "of", "radioactive", "dust", ".", "Society", "may", "also", "respond", "with", "trauma", "to", "the", "murder", "or", "sudden", "death", "of", "a", "person", "who", "functioned", "as", "a", "symbol", "that", "unconsciously", "stood", "for", "a", "parent", "figure", "and/or", "was", "perceived", "as", "a", "representative", "of", "a", "large", "-", "group", "identity", ".", "Assassinations", "of", "John", "F.", "Kennedy¹", "and", "Martin", "Luther", "King", ",", "Jr.", "in", "the", "United", "States", ",", "Yitzhak", "Rabin", "in", "Israel,²", "Prime", "Minister", "Olof", "Palme", "in", "Sweden", ",", "the", "National", "Democratic", "Party", "leader", "Giorgi", "Chanturia", "in", "the", "Republic", "of", "Georgia", ",", "former", "Prime", "Minister", "Rafik", "Hariri", "in", "Lebanon", ",", "or", "the", "deaths", "of", "the", "American", "astronauts", ",", "especially", "teacher", "Christa", "McAuliffe", ",", "in", "the", "1986", "space", "shuttle", "Challenger", "explosion,³", "and", "the", "death", "of", "Diana", ",", "Princess", "of", "Wales", ",", "in", "a", "car", "accident", "in", "1997", ",", "⁴", "all", "led", "to", "responses", "that", "were", "experienced", "as", "shared", "trauma", ".", "\n\n", "Other", "massive", "traumas", "such", "as", "terrorist", "attacks", ",", "wars", "and", "even", "genocide", "can", "be", "ascribed", "to", "the", "deliberate", "actions", "of", "an", "enemy", ",", "an", "outsider", ".", "They", "might", "spring", "from", "a", "territorial", "conflict", "between", "two", "neighbouring", "countries", "that", "results", "in", "mass", "atrocities", ",", "such", "as", "the", "territorial", "conflict", "between", "India", "and", "Pakistan", "in", "Kashmir", "that", "has", "led", "to", "the", "disappearance", "of", "more", "than", "8,000", "persons", "since", "1989", ",", "and", "thousands", "of", "extra", "-", "judicial", "killings", ",", "torture", "and", "rape", ",", "with", "Kashmiri", "Muslims", "fearing", "that", "they", "will", "lose", "their", "culture", ".", "\n\n", "Such", "deliberate", "catastrophes", "can", "also", "occur", "within", "a", "national", "boundary", "when", "there", "is", "chronic", "mistreatment", "or", "oppression", "of", "a", "smaller", "racial", "or", "ethnic", "group", "by", "the", "dominant", "Other", ".", "One", "of", "the", "best", "-", "known", "examples", "of", "this", "is", "the", "history", "of", "slavery", "in", "the", "United", "States", "and", "the", "discrimination", "towards", "black", "Americans", "\n\n", "1", "Wolfenstein", "&", "amp", ";", "Kliman", "(", "Eds", ".", ")", "(", "1965", ")", ".", "Children", "and", "the", "death", "of", "a", "president", ":", "Multi", "-", "disciplinary", "studies", ".", "\n\n", "2", "Erlich", "(", "1998", ")", ".", "Adolescents", "'", "reactions", "to", "Rabin", "s", "assassination", ":", "A", "case", "of", "patricide", "?", "'", "Raviv", "et", "al", ".", "(", "2000", ")", ".", "Young", "Israelis", "'", "reactions", "to", "national" ]

[ { "end": 2331, "label": "CITATION_ID", "start": 2330 }, { "end": 2441, "label": "CITATION_ID", "start": 2440 }, { "end": 2455, "label": "CITATION_REF", "start": 2442 }, { "end": 2448, "label": "AUTHOR", "start": 2442 }, { "end": 2454, "label": "YEAR", "start": 2450 }, { "end": 2370, "label": "CITATION_REF", "start": 2332 }, { "end": 2363, "label": "AUTHOR", "start": 2332 }, { "end": 2369, "label": "YEAR", "start": 2365 }, { "end": 987, "label": "CITATION_REF", "start": 986 }, { "end": 1430, "label": "CITATION_REF", "start": 1429 }, { "end": 1358, "label": "CITATION_REF", "start": 1357 }, { "end": 1063, "label": "CITATION_REF", "start": 1062 } ]

, , functions/ , , , , , , , , , conveyors , , and/or any other device or system discussed herein. The includes one or more processors (also referred to as “ ”). The includes circuitry capable of sequentially and/or automatically carrying out a sequence of arithmetic or logical operations, and recording, storing, and/or transferring digital data. Additionally or alternatively, the includes any device capable of executing or otherwise operating computer-executable instructions, such as program code, software modules, and/or functional processes. The includes various hardware elements or components such as, for example, a set of processor cores and one or more of on-chip or on-die memory or registers, cache and/or scratchpad memory, low drop-out voltage regulators (LDOs), interrupt controllers, serial interfaces such as SPI, I2C or universal programmable serial interface circuit, real time clock (RTC), timer-counters including interval and watchdog timers, general purpose I/O, memory card controllers such as secure digital/multi-media card (SD/MMC) or similar, interfaces, mobile industry processor interface (MIPI) interfaces and Joint Test Access Group (JTAG) test access ports. Some of these components, such as the on-chip or on-die memory or registers, cache and/or scratchpad memory, may be implemented using the same or similar devices as the discussed infra. The is also coupled with and , and is configured to execute instructions stored in the memory/storage to enable various apps, OSs, or other software elements to run on the . In particular, the is configured to operate app software (e.g., , , ) to provide one or more services to a user of the and/or user(s) of remote systems/devices. As examples, the can be embodied as, or otherwise include one or multiple central processing units (CPUs), application processors, graphics processing units (GPUs), RISC processors, Acorn RISC Machine (ARM) processors, complex instruction set computer (CISC) processors, DSPs, FPGAs, programmable logic devices (PLDs), ASICs, baseband processors, radio-frequency integrated circuits (RFICs), microprocessors or controllers, multi-core processors, multithreaded processors, ultra-low voltage processors, embedded processors, a specialized x-processing units (xPUs) or a data processing unit (DPUs) (e.g., Infrastructure Processing Unit (IPU), network processing unit (NPU), and the like), and/or any other processing devices or elements, or any combination thereof. In some implementations, the is embodied as one or more special-purpose processor(s)/controller(s) configured (or configurable) to operate according to the various implementations and other aspects discussed herein. Additionally or alternatively, the includes one or more hardware accelerators (e.g., same or similar to

[ ",", ",", "functions/", ",", ",", ",", ",", ",", ",", " ", ",", ",", ",", "conveyors", ",", ",", "and/or", "any", "other", "device", "or", "system", "discussed", "herein", ".", "\n\n", "The", " ", "includes", "one", "or", "more", "processors", " ", "(", "also", "referred", "to", "as", "“", "”", ")", ".", "The", " ", "includes", "circuitry", "capable", "of", "sequentially", "and/or", "automatically", "carrying", "out", "a", "sequence", "of", "arithmetic", "or", "logical", "operations", ",", "and", "recording", ",", "storing", ",", "and/or", "transferring", "digital", "data", ".", "Additionally", "or", "alternatively", ",", "the", " ", "includes", "any", "device", "capable", "of", "executing", "or", "otherwise", "operating", "computer", "-", "executable", "instructions", ",", "such", "as", "program", "code", ",", "software", "modules", ",", "and/or", "functional", "processes", ".", "The", " ", "includes", "various", "hardware", "elements", "or", "components", "such", "as", ",", "for", "example", ",", "a", "set", "of", "processor", "cores", "and", "one", "or", "more", "of", "on", "-", "chip", "or", "on", "-", "die", "memory", "or", "registers", ",", "cache", "and/or", "scratchpad", "memory", ",", "low", "drop", "-", "out", "voltage", "regulators", "(", "LDOs", ")", ",", "interrupt", "controllers", ",", "serial", "interfaces", "such", "as", "SPI", ",", "I2C", "or", "universal", "programmable", "serial", "interface", "circuit", ",", "real", "time", "clock", "(", "RTC", ")", ",", "timer", "-", "counters", "including", "interval", "and", "watchdog", "timers", ",", "general", "purpose", "I", "/", "O", ",", "memory", "card", "controllers", "such", "as", "secure", "digital", "/", "multi", "-", "media", "card", "(", "SD", "/", "MMC", ")", "or", "similar", ",", "interfaces", ",", "mobile", "industry", "processor", "interface", "(", "MIPI", ")", "interfaces", "and", "Joint", "Test", "Access", "Group", "(", "JTAG", ")", "test", "access", "ports", ".", "Some", "of", "these", "components", ",", "such", "as", "the", "on", "-", "chip", "or", "on", "-", "die", "memory", "or", "registers", ",", "cache", "and/or", "scratchpad", "memory", ",", "may", "be", "implemented", "using", "the", "same", "or", "similar", "devices", "as", "the", " ", "discussed", "infra", ".", "The", " ", "is", "also", "coupled", "with", " ", "and", " ", ",", "and", "is", "configured", "to", "execute", "instructions", "stored", "in", "the", "memory", "/", "storage", "to", "enable", "various", "apps", ",", "OSs", ",", "or", "other", "software", "elements", "to", "run", "on", "the", " ", ".", "In", "particular", ",", "the", " ", "is", "configured", "to", "operate", "app", "software", "(", "e.g.", ",", " ", ",", " ", ",", " ", ")", "to", "provide", "one", "or", "more", "services", "to", "a", "user", "of", "the", " ", "and/or", "user(s", ")", "of", "remote", "systems", "/", "devices", ".", "\n\n", "As", "examples", ",", "the", " ", "can", "be", "embodied", "as", ",", "or", "otherwise", "include", "one", "or", "multiple", "central", "processing", "units", "(", "CPUs", ")", ",", "application", "processors", ",", "graphics", "processing", "units", "(", "GPUs", ")", ",", "RISC", "processors", ",", "Acorn", "RISC", "Machine", "(", "ARM", ")", "processors", ",", "complex", "instruction", "set", "computer", "(", "CISC", ")", "processors", ",", "DSPs", ",", "FPGAs", ",", "programmable", "logic", "devices", "(", "PLDs", ")", ",", "ASICs", ",", "baseband", "processors", ",", "radio", "-", "frequency", "integrated", "circuits", "(", "RFICs", ")", ",", "microprocessors", "or", "controllers", ",", "multi", "-", "core", "processors", ",", "multithreaded", "processors", ",", "ultra", "-", "low", "voltage", "processors", ",", "embedded", "processors", ",", "a", "specialized", "x", "-", "processing", "units", "(", "xPUs", ")", "or", "a", "data", "processing", "unit", "(", "DPUs", ")", "(", "e.g.", ",", "Infrastructure", "Processing", "Unit", "(", "IPU", ")", ",", "network", "processing", "unit", "(", "NPU", ")", ",", "and", "the", "like", ")", ",", "and/or", "any", "other", "processing", "devices", "or", "elements", ",", "or", "any", "combination", "thereof", ".", "In", "some", "implementations", ",", "the", " ", "is", "embodied", "as", "one", "or", "more", "special", "-", "purpose", "processor(s)/controller(s", ")", "configured", "(", "or", "configurable", ")", "to", "operate", "according", "to", "the", "various", "implementations", "and", "other", "aspects", "discussed", "herein", ".", "Additionally", "or", "alternatively", ",", "the", " ", "includes", "one", "or", "more", "hardware", "accelerators", "(", "e.g.", ",", "same", "or", "similar", "to" ]

[]

into a form that allows analysis. The statistical analysis allows us to understand the fine-grain choice structure of the individual characteristics by estimating the average marginal component effect. Through analysis, the relative statistical importance of each characteristic can be assessed by using the marginal effect of the attribute averaged over the joint distribution of the remaining attributes. This analysis will show the likelihood of how individual characteristics vary in importance in differ -ent informal settlements that have different levels of institutions in place. We pro -vide a greater understanding of the mechanisms at work in these broker and client choice relationships. We explore the emergence of brokers in different community types in Delhi, India, and how the broker builds a following from local residents. We seek to investigate the origins of hierarchy in clientelist spaces and study the processes through which informal leaders emerge within our different slum types. Now, let us look at each of the parts of the research in turn. First, we set out some of the discussions carried out with community members and brokers, allowing for Figure 4.2 Screenshot illustrating Qualtrics data collection software  voices from the grassroots to inform our research. Second, we describe how we set up the conjoint experiment. Third, these quantitative findings are presented to allow us to investigate the overarching themes of governance, politics and brokers in different slum types in Delhi. ## Voices from brokers and residents ## Capability When talking with the brokers, they expressed their desire to support their communities to gain popularity and a larger following. This support, they suggested, helps them climb the party ranks and enhances their value to their political party. As these neighbourhoods aren't electoral constituencies, the goal for brokers and political parties isn't to secure a majority but to enable as many resident votes as possible. Political parties in India are constantly seeking brokers who can deliver a significant voter base. Ambitious brokers aim to work in multiple neighbourhoods to maximise the number of voters they can influence for politicians. These brokers are often entrepreneurial, aspiring for political careers and promotions within the party by its leaders. Our data from the household survey shows that in each of our neighbourhoods, around 80% of residents say they voted in the last round of Delhi elections, both at the municipal and state levels. To do so, these residents must have a

[ "into", "a", "form", "that", "allows", "analysis", ".", "The", "statistical", "analysis", "allows", "us", "to", "understand", "the", "fine", "-", "grain", "choice", "structure", "of", "the", "individual", "characteristics", "by", "estimating", "the", "average", "marginal", " ", "component", " ", "effect", ".", " ", "Through", " ", "analysis", ",", " ", "the", " ", "relative", " ", "statistical", " ", "importance", " ", "of", "each", "characteristic", "can", "be", "assessed", "by", "using", "the", "marginal", "effect", "of", "the", "attribute", "averaged", "over", "the", "joint", "distribution", "of", "the", "remaining", "attributes", ".", "This", "analysis", "will", "show", "the", "likelihood", "of", "how", "individual", "characteristics", "vary", "in", "importance", "in", "differ", "-ent", "informal", "settlements", "that", "have", "different", "levels", "of", "institutions", "in", "place", ".", "We", "pro", "-vide", "a", "greater", "understanding", "of", "the", "mechanisms", "at", "work", "in", "these", "broker", "and", "client", "choice", "relationships", ".", "We", "explore", "the", "emergence", "of", "brokers", "in", "different", "community", "types", "in", "Delhi", ",", "India", ",", "and", "how", "the", "broker", "builds", "a", "following", "from", "local", "residents", ".", "We", "seek", "to", "investigate", "the", "origins", "of", "hierarchy", "in", "clientelist", "spaces", "and", "study", "the", "processes", "through", "which", "informal", "leaders", "emerge", "within", "our", "different", "slum", "types", ".", "Now", ",", "let", "us", "look", "at", "each", "of", "the", "parts", "of", "the", "research", "in", "turn", ".", "First", ",", "we", "set", "out", "some", "of", "the", "discussions", "carried", "out", "with", "community", "members", "and", "brokers", ",", "allowing", "for", "\n\n", "Figure", "4.2", "Screenshot", "illustrating", "Qualtrics", "data", "collection", "software", "\n\n", "<", "!", "--", "image", "--", ">", "\n\n", "voices", "from", "the", "grassroots", "to", "inform", "our", "research", ".", "Second", ",", "we", "describe", "how", "we", "set", "up", "the", "conjoint", "experiment", ".", "Third", ",", "these", "quantitative", "findings", "are", "presented", "to", "allow", "us", "to", "investigate", "the", "overarching", "themes", "of", "governance", ",", "politics", "and", "brokers", "in", "different", "slum", "types", "in", "Delhi", ".", "\n\n", "#", "#", "Voices", "from", "brokers", "and", "residents", "\n\n", "#", "#", "Capability", "\n\n", "When", "talking", "with", "the", "brokers", ",", "they", "expressed", "their", "desire", "to", "support", "their", "communities", "to", "gain", "popularity", "and", "a", "larger", "following", ".", "This", "support", ",", "they", "suggested", ",", "helps", "them", "climb", "the", "party", "ranks", "and", "enhances", "their", "value", "to", "their", "political", "party", ".", "As", "these", "neighbourhoods", "are", "n't", "electoral", "constituencies", ",", "the", "goal", "for", "brokers", "and", "political", "parties", "is", "n't", "to", "secure", "a", "majority", "but", "to", "enable", "as", "many", "resident", "votes", "as", "possible", ".", "Political", "parties", "in", "India", "are", "constantly", "seeking", "brokers", "who", "can", "deliver", "a", "significant", "voter", "base", ".", "Ambitious", "brokers", "aim", "to", "work", "in", "multiple", "neighbourhoods", "to", "maximise", "the", "number", "of", "voters", "they", "can", "influence", "for", "politicians", ".", "These", "brokers", "are", "often", "entrepreneurial", ",", "aspiring", "for", "political", "careers", "and", "promotions", "within", "the", "party", "by", "its", "leaders", ".", "Our", "data", "from", "the", "household", "survey", "shows", "that", "in", "each", "of", "our", "neighbourhoods", ",", "around", "80", "%", "of", "residents", "say", "they", "voted", "in", "the", "last", "round", "of", "Delhi", "elections", ",", "both", "at", "the", "municipal", "and", "state", "levels", ".", "To", "do", "so", ",", "these", "residents", "must", "have", "a" ]

[]

limited to cells that are hormone receptor positive, including most breast cancers. For these diseases, cell type -specific epigenetic clocks that mirror the cells at risk may be of use ( i.e., hormone -sensitive epithelial cells ), but these cells are lacking from blood or saliva samples. Conversely, cervical samples, routinely obtained from women aged 25 -64 years , are a source of hormone -sensitive epithelial and immune cells that could help to define epigenetic clocks indicating disease risk. Whether specific epigenetic clocks in cervical samples or a discordance in tick rates between general and cell type -specific epigenetic c locks could predict disease remained unknown. As part of Deliverable D8.2 we aimed to define: • an optimi sed “general epigenetic clock” – i.e., a list of CpGs – which collectively change with age in cervical samples . • cell type -specific epigenetic clocks for epithelial and immune cells within cervical samples. We analysed cervical liquid -based cytology samples and describe novel epigenetic clocks, the WID (W omen’s cancer risk IDentification clocks), which can indicate cancer risk and are altered upon hormone exposure . HEAP – D8.2 Ageing DNAme signatures page 6/15 Project No. 874662 HORIZON 2020 2 Methods 2.1 Samples Samples used for development of the general and cell type -specific clocks were collected as part of the FORECEE Programme, a European research project aimed at developing new strategies for female cancer prediction (Table 1) . Cervical screening was performed for women aged >18 years across five different European locations, including the Czech Republic, Germany, Italy, Norway, and the UK. FORECEE has received ethical approval from the UK Health Research Authority (R EC 14/LO/1633) and other contributing centres. Women with either breast, ovarian, or endometrial cancer as well as age -matched controls were included. Table 1. Samples in the FORECEE Study used for training and validation. SET TYPE NUMBER OF SAMPLES TRAINING Control 869 VALIDATION Control 225 Breast cancer 442 Ovarian cancer 289 Cervical smears were collected with a Rovers cervical brush and stored in PreservCyt solution (ThinPrep ). DNA was extracted from cervical samples on a Hamilton Star liquid handling platform using the Nucleo -Mag Blood 200 µL kit (Macherey Nagel, cat #744501.4) with prior modifications for optimal lysis of cervical cell pellets. Concentration and quality abso rbance ratios were measured using a Nanodrop- 8000 (Thermo Scientific) and extracted DNA was stored at -80°C until further analysis. 2.2

[ "limited", "to", "cells", "that", "are", "hormone", "receptor", "positive", ",", "including", "most", "breast", "cancers", ".", "For", "these", "diseases", ",", "cell", "type", "-specific", "\n", "epigenetic", "clocks", "that", "mirror", "the", "cells", "at", "risk", "may", "be", "of", "use", "(", "i.e.", ",", "\n", "hormone", "-sensitive", "epithelial", "cells", ")", ",", "but", "these", "cells", "are", "lacking", "from", "blood", "\n", "or", "saliva", "samples", ".", "Conversely", ",", "cervical", "samples", ",", "routinely", "obtained", "from", " \n", "women", "aged", "25", "-64", "years", ",", "are", "a", "source", " ", "of", "hormone", "-sensitive", "epithelial", "\n", "and", "immune", "cells", "that", "could", "help", "to", "define", "epigenetic", "clocks", "indicating", "disease", "risk", ".", " ", "Whether", "specific", "epigenetic", "clocks", "in", "cervical", "samples", "or", "a", "\n", "discordance", "in", "tick", "rates", "between", "general", "and", "cell", "type", "-specific", "\n", "epigenetic", "c", "locks", "could", "predict", "disease", "remained", "unknown", ".", " \n \n", "As", "part", "of", "Deliverable", "D8.2", "we", "aimed", "to", "define", ":", " \n", "•", "an", "optimi", "sed", "“", "general", "epigenetic", "clock", "”", "–", "i.e.", ",", "a", "list", "of", "CpGs", "–", " ", "which", "\n", "collectively", "change", "with", "age", "in", "cervical", "samples", ".", "\n", "•", "cell", "type", "-specific", "epigenetic", "clocks", "for", " ", "epithelial", "and", "immune", "cells", "\n", "within", "cervical", "samples", ".", " \n \n", "We", "analysed", "cervical", "liquid", "-based", "cytology", "samples", "and", "describe", "novel", "\n", "epigenetic", "clocks", ",", "the", "WID", "(", "W", "omen", "’s", "cancer", "risk", "IDentification", "clocks", ")", ",", " \n", "which", "can", "indicate", "cancer", "risk", " ", "and", "are", "altered", "upon", "hormone", " ", "exposure", ".", "\n \n \n \n \n", "HEAP", " ", "–", "D8.2", "Ageing", "DNAme", "signatures", " ", "page", "6/15", "\n \n", "Project", "No", ".", "874662", " \n \n \n", "HORIZON", "2020", " \n", "2", "Methods", " \n", "2.1", "Samples", " \n", "Samples", "used", "for", "development", "of", "the", "general", "and", "cell", "type", "-specific", "clocks", "\n", "were", "collected", "as", "part", "of", "the", "FORECEE", "Programme", ",", "a", "European", "research", "\n", "project", "aimed", "at", "developing", "new", "strategies", "for", "female", "cancer", "prediction", " \n", "(", "Table", "1", ")", ".", "Cervical", "screening", "was", "performed", "for", "women", "aged", ">", "18", "years", "\n", "across", "five", "different", "European", "locations", ",", "including", "the", "Czech", "Republic", ",", "\n", "Germany", ",", "Italy", ",", "Norway", ",", "and", "the", "UK", ".", "FORECEE", "has", "received", "ethical", "\n", "approval", "from", "the", "UK", "Health", "Research", "Authority", "(", "R", "EC", "14", "/", "LO/1633", ")", "and", "\n", "other", "contributing", "centres", ".", "Women", "with", "either", "breast", ",", "ovarian", ",", "or", "endometrial", "cancer", "as", "well", "as", "age", "-matched", "controls", "were", "included", ".", " \n \n", "Table", "1", ".", "Samples", "in", "the", "FORECEE", "Study", "used", "for", "training", "and", "validation", ".", " \n \n", "SET", "TYPE", " ", "NUMBER", "OF", "SAMPLES", " \n", "TRAINING", " ", "Control", " ", "869", "\n", "VALIDATION", " ", "Control", " ", "225", " \n", "Breast", "cancer", " ", "442", " \n", "Ovarian", "cancer", " ", "289", "\n ", "Cervical", "smears", "were", "collected", "with", "a", "Rovers", "cervical", "brush", "and", "stored", "in", "\n", "PreservCyt", "solution", "(", "ThinPrep", ")", ".", "DNA", "was", "extracted", "from", "cervical", "samples", "\n", "on", "a", "Hamilton", "Star", "liquid", "handling", "platform", "using", "the", "Nucleo", "-Mag", "Blood", "200", "\n", "µL", "kit", "(", "Macherey", "Nagel", ",", "cat", "#", "744501.4", ")", "with", "prior", "modifications", "for", "optimal", "\n", "lysis", "of", "cervical", "cell", "pellets", ".", "Concentration", "and", "quality", "abso", "rbance", "ratios", "\n", "were", "measured", "using", "a", "Nanodrop-", "8000", "(", "Thermo", "Scientific", ")", "and", "extracted", "\n", "DNA", "was", "stored", "at", "-80", "°", "C", "until", "further", "analysis", ".", " \n", "2.2" ]

[]

referred to as consolidation of the tax base of a taxpayer. In mining, a company may carry on multiple projects and/or undertake several activities along the mining value chain or be involved in non-mining activities, such as transport, manufacturing, or even sophisticated financial investment activities. In these cases, where consolidation rules are in place, the company may use costs incurred in one project (e.g., during exploration) and/or activity (e.g., when undertaking manufacturing activities) to offset profits earned in another. Such consolidation is fiscally attractive for mining taxpayers because it allows tax savings resulting from the deduction of costs related to one project/activity against the income generated by another project/activity. These tax savings reduce the after-tax costs of investments. They can, in turn, encourage mining companies to invest in exploration and continue other mining and non-mining activities because they can recover their costs sooner, which may improve their cash flows. For governments, attracting investments is an important policy objective, and these considerations related to consolidation play an important role in the decisions of investors. However, such consolidation can postpone government tax revenues. By offsetting costs or losses against the income of producing mines, companies can defer the payment of CITs—sometimes for very long periods or indefinitely. Consolidation can also result in revenue loss if exploration projects are unsuccessful or when a mining investor undertakes non-mining activities, such as speculative and high-risk financial investment activities. Furthermore, where mining investors engage in base erosion and profit shifting (BEPS) practices, consolidation might accelerate those effects and may result in permanent losses of tax revenues for the host jurisdiction. Balancing these potentially conflicting objectives through careful tax policy design is essential to ensure that investors do not lose the deductibility of legitimate expenses incurred, and governments ensure the collection of economic rents.1 1 Economic or resource rent has been defined as “the excess of the total project lifetime value arising from the exploitation of a deposit over the sum of all costs of exploitation including the compensation to all factors of production.” See Land (2008, p. 5).Ring-Fencing Mining Income: A toolkit for tax administrators and policy-makers 3 Ring-Fencing Mining Income: A toolkit for tax administrators and policy-makers1.0 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 In developing countries, a delay in tax payments or

[ "referred", "to", "as", "consolidation", "of", "the", "tax", "base", "of", "a", "taxpayer", ".", "\n", "In", "mining", ",", "a", "company", "may", "carry", "on", "multiple", "projects", "and/or", "undertake", "\n", "several", "activities", "along", "the", "mining", "value", "chain", "or", "be", "involved", "in", "non", "-", "mining", "\n", "activities", ",", "such", "as", "transport", ",", "manufacturing", ",", "or", "even", "sophisticated", "financial", "\n", "investment", "activities", ".", "In", "these", "cases", ",", "where", "consolidation", "rules", "are", "in", "place", ",", "\n", "the", "company", "may", "use", "costs", "incurred", "in", "one", "project", "(", "e.g.", ",", "during", "exploration", ")", "\n", "and/or", "activity", "(", "e.g.", ",", "when", "undertaking", "manufacturing", "activities", ")", "to", "offset", "\n", "profits", "earned", "in", "another", ".", "\n", "Such", "consolidation", "is", "fiscally", "attractive", "for", "mining", "taxpayers", "because", "it", "\n", "allows", "tax", "savings", "resulting", "from", "the", "deduction", "of", "costs", "related", "to", "one", "\n", "project", "/", "activity", "against", "the", "income", "generated", "by", "another", "project", "/", "activity", ".", "\n", "These", "tax", "savings", "reduce", "the", "after", "-", "tax", "costs", "of", "investments", ".", "They", "can", ",", "in", "\n", "turn", ",", "encourage", "mining", "companies", "to", "invest", "in", "exploration", "and", "continue", "\n", "other", "mining", "and", "non", "-", "mining", "activities", "because", "they", "can", "recover", "their", "costs", "\n", "sooner", ",", "which", "may", "improve", "their", "cash", "flows", ".", "\n", "For", "governments", ",", "attracting", "investments", "is", "an", "important", "policy", "objective", ",", "\n", "and", "these", "considerations", "related", "to", "consolidation", "play", "an", "important", "role", "\n", "in", "the", "decisions", "of", "investors", ".", "However", ",", "such", "consolidation", "can", "postpone", "\n", "government", "tax", "revenues", ".", "By", "offsetting", "costs", "or", "losses", "against", "the", "income", "of", "\n", "producing", "mines", ",", "companies", "can", "defer", "the", "payment", "of", "CITs", "—", "sometimes", "for", "\n", "very", "long", "periods", "or", "indefinitely", ".", "Consolidation", "can", "also", "result", "in", "revenue", "loss", "\n", "if", "exploration", "projects", "are", "unsuccessful", "or", "when", "a", "mining", "investor", "undertakes", "\n", "non", "-", "mining", "activities", ",", "such", "as", "speculative", "and", "high", "-", "risk", "financial", "investment", "\n", "activities", ".", "Furthermore", ",", "where", "mining", "investors", "engage", "in", "base", "erosion", "and", "\n", "profit", "shifting", "(", "BEPS", ")", "practices", ",", "consolidation", "might", "accelerate", "those", "effects", "\n", "and", "may", "result", "in", "permanent", "losses", "of", "tax", "revenues", "for", "the", "host", "jurisdiction", ".", "\n", "Balancing", "these", "potentially", "conflicting", "objectives", "through", "careful", "tax", "policy", "\n", "design", "is", "essential", "to", "ensure", "that", "investors", "do", "not", "lose", "the", "deductibility", "of", "\n", "legitimate", "expenses", "incurred", ",", "and", "governments", "ensure", "the", "collection", " \n", "of", "economic", "rents.1", "\n", "1", "Economic", "or", "resource", "rent", "has", "been", "defined", "as", "“", "the", "excess", "of", "the", "total", "project", "\n", "lifetime", "value", "arising", "from", "the", "exploitation", "of", "a", "deposit", "over", "the", "sum", "of", "all", "costs", " \n", "of", "exploitation", "including", "the", "compensation", "to", "all", "factors", "of", "production", ".", "”", "See", "Land", "\n", "(", "2008", ",", "p.", "5).Ring", "-", "Fencing", "Mining", "Income", ":", "A", "toolkit", "for", "tax", "administrators", "and", "policy", "-", "makers", "\n", "3", "\n", "Ring", "-", "Fencing", "Mining", "Income", ":", "A", "toolkit", "for", "tax", "administrators", "and", "policy", "-", "makers1.0", "INTRODUCTION", "\n", "2.0", "THE", "\n", "FUNDAMENTALS", " \n", "OF", "RING", "-FENCING", "\n", "3.0", "THE", "BENEFITS", "\n", "AND", "RISKS", "OF", " \n", "RING", "-FENCING", "\n", "4.0", "DESIGNING", "\n", "RING", "-FENCING", "\n", "RULES", "\n", "5.0", "THE", "\n", "IMPLEMENTATION", "\n", "OF", "RING", "-FENCING", "\n", "RULES", "\n", "6.0", "CONCLUSION", "In", "developing", "countries", ",", "a", "delay", "in", "tax", "payments", "or" ]

[ { "end": 2137, "label": "CITATION_REF", "start": 2136 }, { "end": 2402, "label": "CITATION_REF", "start": 2384 }, { "end": 2388, "label": "AUTHOR", "start": 2384 }, { "end": 2395, "label": "YEAR", "start": 2391 } ]

blocks that were not fully covered by water and do not intersect with GISCO country data for 2020 and 2024 at 1:1 ,000,000 or 1:100 ,000. The colour indicates if one or a combination of several GISCO datasets missed a block. Th e size of the blocks is exaggerated to make them visible at global level. The number after the hyphen indicates the amount of unique processing blocks for this category ( dataset combination ); in total there are 5 ,194 unique blocks identified by any of the three datasets. The high number of only GISCO 2020 at 1:1,000,000 scale (green) confirms the assumption that improved in the 2024 data release; high number of GISCO at 1:1 ,000,000 compared to data or combinations that include 1:100 ,000 indicates the before mentioned relationship to mapping scale. 21 Figure 7. LCFM processing blocks that were not fully covered by water and do not intersect with GISCO country data for 2020 or 2024 at 1:1,000,000 or 1:100,000. Source: JRC based on data from VITO – Flemish Institute for Technological Research (LCFM processing blocks) and Eurostat /GISCO (country boundaries) . Note: The size of the blocks is exaggerated to make them visible at global lev el. The number after the hyphen in the legend indicates the amount of unique processing blocks for this category (dataset combination) . Figure 7 indicates that all identified blocks are located along continental outlines either coastlines or shorelines for interior water bodies like the Caspian Sea that GISCO does not allocate to a specific country. The figure also indicates some geographic patterns with regards to individual GISCO datasets. — Africa, which the exception is the Red Sea, depicts only a few lo cations with identified blocks. This result is likely linked to 1) steeper coasts with little ambiguity to identify the water/land boundary 2) a relatively low complexity of the coastline i.e. elongated shorelines with few bends and small radius, and 3) fe w small coastal islands. — Asia indicates blocks predominantly identified for GISCO 2020 at 1:1 ,000,000 (green). This suggests that the country boundaries improved in terms of completeness for GISCO 2024. — Complex shorelines show a dominance of blocks for GIS CO data at 1:1 ,000,000 for both 2020 and 2024 (purple). Shorelines are characterized by a high fragmentation and low compactness. Reasons for shoreline complexity may be due to former presence of fjords in formerly

[ "blocks", "that", "were", "not", "fully", "covered", "by", "water", "and", "do", "not", "intersect", "\n", "with", "GISCO", "country", "data", "for", "2020", "and", "2024", "at", "1:1", ",", "000,000", " ", "or", "1:100", ",", "000", ".", "The", "colour", "indicates", "if", "\n", "one", "or", "a", "combination", "of", "several", "GISCO", "datasets", "missed", "a", "block", ".", "Th", "e", "size", "of", "the", "blocks", "is", "\n", "exaggerated", "to", "make", "them", "visible", "at", "global", "level", ".", "The", "number", "after", "the", "hyphen", "indicates", "the", "\n", "amount", "of", "unique", "processing", "blocks", "for", "this", "category", "(", "dataset", "combination", ")", ";", "in", "total", "there", "are", "5", ",", "194", "\n", "unique", "blocks", "identified", "by", "any", "of", "the", "three", "datasets", ".", "The", "high", "number", "of", "only", "GISCO", "2020", "at", "\n", "1:1,000,000", "scale", "(", "green", ")", "confirms", "the", "assumption", "that", "improved", "in", "the", "2024", "data", "release", ";", "high", "\n", "number", "of", "GISCO", "at", "1:1", ",", "000,000", " ", "compared", "to", "data", "or", "combinations", "that", "include", "1:100", ",", "000", "\n", "indicates", "the", "before", "mentioned", "relationship", "to", "mapping", "scale", ".", " \n\n", "21", "Figure", "7", ".", "LCFM", "processing", "blocks", "that", "were", "not", "fully", "covered", "by", "water", "and", "do", "not", "intersect", "with", "GISCO", "\n", "country", "data", "for", "2020", "or", "2024", "at", "1:1,000,000", "or", "1:100,000", ".", " \n", "Source", ":", "JRC", "based", "on", "data", "from", "VITO", "–", "Flemish", "Institute", "for", "Technological", "Research", "(", "LCFM", "processing", "blocks", ")", "and", "\n", "Eurostat", "/GISCO", " ", "(", "country", "boundaries", ")", ".", "Note", ":", "The", "size", "of", "the", "blocks", "is", "exaggerated", "to", "make", "them", "visible", "at", "global", "lev", "el", ".", "The", "\n", "number", "after", "the", "hyphen", "in", "the", "legend", "indicates", "the", "amount", "of", "unique", "processing", "blocks", "for", "this", "category", "(", "dataset", "\n", "combination", ")", ".", "\n", "Figure", "7", "indicates", " ", "that", "all", "identified", "blocks", "are", "located", "along", "continental", "outlines", "either", "coastlines", "\n", "or", "shorelines", "for", " ", "interior", "water", "bodies", "like", "the", "Caspian", "Sea", "that", "GISCO", "does", "not", "allocate", "to", "a", "\n", "specific", "country", ".", "The", "figure", "also", "indicates", "some", "geographic", "patterns", "with", "regards", "to", "individual", "\n", "GISCO", "datasets", ".", " \n", "—", "Africa", ",", "which", "the", "exception", "is", "the", "Red", "Sea", ",", "depicts", "only", "a", "few", "lo", "cations", "with", "identified", "blocks", ".", "\n", "This", "result", "is", "likely", "linked", "to", "1", ")", "steeper", "coasts", "with", "little", "ambiguity", "to", "identify", "the", "water", "/", "land", "\n", "boundary", "2", ")", "a", "relatively", "low", "complexity", "of", "the", "coastline", "i.e.", "elongated", "shorelines", "with", "few", "bends", "\n", "and", "small", "radius", ",", "and", "3", ")", "fe", "w", "small", "coastal", "islands", ".", " \n", "—", "Asia", "indicates", "blocks", "predominantly", "identified", "for", "GISCO", "2020", "at", "1:1", ",", "000,000", " ", "(", "green", ")", ".", "This", "\n", "suggests", "that", "the", "country", "boundaries", "improved", "in", "terms", "of", "completeness", "for", "GISCO", "2024", ".", " \n", "—", "Complex", "shorelines", "show", "a", "dominance", "of", "blocks", "for", "GIS", "CO", "data", "at", "1:1", ",", "000,000", " ", "for", "both", "2020", "\n", "and", "2024", "(", "purple", ")", ".", "Shorelines", "are", "characterized", "by", "a", "high", "fragmentation", "and", "low", "compactness", ".", "\n", "Reasons", "for", "shoreline", "complexity", "may", "be", "due", "to", "former", "presence", "of", "fjords", "in", "formerly" ]

[]

second capacitor, a first conductor, a second conductor, a third conductor, and a fourth conductor. - the first transistor includes a first gate, a first source, and a first drain. - the second transistor includes a second gate, a third gate over the second gate, a first low-resistance region, a second low-resistance region, and an oxide sandwiched between the second gate and the third gate. - the third transistor includes a fourth gate, a second source, and a second drain. - the fourth transistor includes a fifth gate, a sixth gate over the fifth gate, the second low-resistance region, a third low-resistance region, and the oxide sandwiched between the fifth gate and the sixth gate. - the first capacitor includes a first electrode, a second electrode over the first electrode, and a first insulator sandwiched between the first electrode and the second electrode. - the second capacitor includes a third electrode, a fourth electrode over the third electrode, and a second insulator sandwiched between the third electrode and the fourth electrode. - the first low-resistance region overlaps with the first gate. - the first conductor is electrically connected to the first gate. - the first conductor is connected to a bottom surface of the first low-resistance region. - the first capacitor overlaps with the first low-resistance region. - the first electrode is electrically connected to the first low-resistance region. - the third low-resistance region overlaps with the fourth gate. - the fourth conductor is electrically connected to the fourth gate. - the fourth conductor is connected to a bottom surface of the third low-resistance region. - the second capacitor overlaps with the third low-resistance region. - the third electrode is electrically connected to the third low-resistance region. - the second conductor is electrically connected to the first drain and the second drain. - the third conductor overlaps with the second conductor. - the third conductor is connected to the second conductor and a side surface of the second low-resistance region. - the first drain and the second drain are preferably provided in a fourth low-resistance region. - a distance between the second gate and the first gate be less than or equal to half the width of the first gate. - a distance between the second gate and the second conductor be less than or equal to half the width of the first gate. - the semiconductor device further include

[ "second", "capacitor", ",", "a", "first", "conductor", ",", "a", "second", "conductor", ",", "a", "third", "conductor", ",", "and", "a", "fourth", "conductor", ".", "\n", "-", "the", "first", "transistor", "\n", "includes", "a", "first", "gate", ",", "a", "first", "source", ",", "and", "a", "first", "drain", ".", "\n", "-", "the", "second", "transistor", "\n", "includes", "a", "second", "gate", ",", "a", "third", "gate", "over", "the", "second", "gate", ",", "a", "first", "low", "-", "resistance", "region", ",", "a", "second", "low", "-", "resistance", "region", ",", "and", "an", "oxide", "sandwiched", "between", "the", "second", "gate", "and", "the", "third", "gate", ".", "\n", "-", "the", "third", "transistor", "\n", "includes", "a", "fourth", "gate", ",", "a", "second", "source", ",", "and", "a", "second", "drain", ".", "\n", "-", "the", "fourth", "transistor", "\n", "includes", "a", "fifth", "gate", ",", "a", "sixth", "gate", "over", "the", "fifth", "gate", ",", "the", "second", "low", "-", "resistance", "region", ",", "a", "third", "low", "-", "resistance", "region", ",", "and", "the", "oxide", "sandwiched", "between", "the", "fifth", "gate", "and", "the", "sixth", "gate", ".", "\n", "-", "the", "first", "capacitor", "\n", "includes", "a", "first", "electrode", ",", "a", "second", "electrode", "over", "the", "first", "electrode", ",", "and", "a", "first", "insulator", "sandwiched", "between", "the", "first", "electrode", "and", "the", "second", "electrode", ".", "\n", "-", "the", "second", "capacitor", "\n", "includes", "a", "third", "electrode", ",", "a", "fourth", "electrode", "over", "the", "third", "electrode", ",", "and", "a", "second", "insulator", "sandwiched", "between", "the", "third", "electrode", "and", "the", "fourth", "electrode", ".", "\n", "-", "the", "first", "low", "-", "resistance", "region", "\n", "overlaps", "with", "the", "first", "gate", ".", "\n", "-", "the", "first", "conductor", "\n", "is", "electrically", "connected", "to", "the", "first", "gate", ".", "\n", "-", "the", "first", "conductor", "\n", "is", "connected", "to", "a", "bottom", "surface", "of", "the", "first", "low", "-", "resistance", "region", ".", "\n", "-", "the", "first", "capacitor", "\n", "overlaps", "with", "the", "first", "low", "-", "resistance", "region", ".", "\n", "-", "the", "first", "electrode", "\n", "is", "electrically", "connected", "to", "the", "first", "low", "-", "resistance", "region", ".", "\n", "-", "the", "third", "low", "-", "resistance", "region", "\n", "overlaps", "with", "the", "fourth", "gate", ".", "\n", "-", "the", "fourth", "conductor", "\n", "is", "electrically", "connected", "to", "the", "fourth", "gate", ".", "\n", "-", "the", "fourth", "conductor", "\n", "is", "connected", "to", "a", "bottom", "surface", "of", "the", "third", "low", "-", "resistance", "region", ".", "\n", "-", "the", "second", "capacitor", "\n", "overlaps", "with", "the", "third", "low", "-", "resistance", "region", ".", "\n", "-", "the", "third", "electrode", "\n", "is", "electrically", "connected", "to", "the", "third", "low", "-", "resistance", "region", ".", "\n", "-", "the", "second", "conductor", "\n", "is", "electrically", "connected", "to", "the", "first", "drain", "and", "the", "second", "drain", ".", "\n", "-", "the", "third", "conductor", "\n", "overlaps", "with", "the", "second", "conductor", ".", "\n", "-", "the", "third", "conductor", "\n", "is", "connected", "to", "the", "second", "conductor", "and", "a", "side", "surface", "of", "the", "second", "low", "-", "resistance", "region", ".", "\n", "-", "the", "first", "drain", "and", "the", "second", "drain", "\n", "are", "preferably", "provided", "in", "a", "fourth", "low", "-", "resistance", "region", ".", "\n", "-", "a", "distance", "between", "the", "second", "gate", "and", "the", "first", "gate", "\n", "be", "less", "than", "or", "equal", "to", "half", "the", "width", "of", "the", "first", "gate", ".", "\n", "-", "a", "distance", "between", "the", "second", "gate", "and", "the", "second", "conductor", "\n", "be", "less", "than", "or", "equal", "to", "half", "the", "width", "of", "the", "first", "gate", ".", "\n", "-", "the", "semiconductor", "device", "\n", "further", "include" ]

[]

PART III Entrepreneurship Source: Flooded Cellar Productions10.4324/9781003467342-7 55 Stories from the street An intricate sidewalk ballet This chapter has been made available under a CC-BY-NC-ND 4.0 license. The stretch of Hudson Street where I live is each day the scene of an intricate sidewalk ballet. I make my own first entrance into it a little after eight when I put out the garbage can, surely a prosaic occupation, but I enjoy my part, my little clang, as the droves of junior high school students walk by the centre of the stage dropping candy wrappers. (How do they eat so much candy so early in the morning?) While I sweep up the wrappers I watch the other rituals of morning: Mr Halpert unlocking the laundry’s handcart from its mooring to a cellar door, Joe Cornacchia’s son-in-law stacking out the empty crates from the delicatessen, the barber bringing out his sidewalk folding chair, Mr Goldstein arranging the coils of wire which proclaim the hardware store is open, the wife of the tenement’s superintendent depositing her chunky three-year-old with a toy mandolin on the stoop, the vantage point from which he is learning the English his mother cannot speak. (Jacobs 1961 , p. 61) DOI: 10.4324/9781003467342-810.4324/9781003467342-8 114 Urban life in Delhi slumsStories from the street Introduction As in the quote by Jane Jacobs, setting out the morning routine she encountered on Hudson Street, New York, in her 1961 book Death and Life in Great American Cities , we highlight the voices of the entrepreneurs we encountered during this research in our Delhi neighbourhoods. Stories of the street scenes where goods are being hawked and haggled over in shops and markets will be told alongside the voices of entrepre - neurs – the street vendors, textile workers, carpenters, painters, recyclers, beauticians, barbers and cooks. The atmosphere in these settlements is buoyant, friendly, exuding community cohesion and trust. The slums provide examples of organic growth where the poor are agents of change. Place attachment provides a feeling of community uniqueness and irreplaceability. With a sense of belonging, feelings of loyalty, trust and a life with value and dignity, there follows a desire for bottom-up approaches to alleviating poverty. It is an ‘infectious’ atmosphere, with the poor focused on their family, neighbourhoods and the next generation. According to Jane Jacobs A good way to see the problem of the city is to take a bus or

[ "PART", " ", "III", "\n", "Entrepreneurship", "\n", "Source", ":", "Flooded", "Cellar", "Productions10.4324/9781003467342", "-", "7", "\n", "55", "\n", "Stories", "from", "the", "street", "\n", "An", "intricate", "sidewalk", "ballet", "\n", "This", "chapter", "has", "been", "made", "available", "under", "a", "CC", "-", "BY", "-", "NC", "-", "ND", "4.0", "license", ".", "\n", "The", "stretch", "of", "Hudson", "Street", "where", "I", "live", "is", "each", "day", "the", "scene", "of", "an", "intricate", "\n", "sidewalk", "ballet", ".", "I", "make", "my", "own", "first", "entrance", "into", "it", "a", "little", "after", "eight", "when", "I", "\n", "put", "out", "the", "garbage", "can", ",", "surely", "a", "prosaic", "occupation", ",", "but", "I", "enjoy", "my", "part", ",", "my", "\n", "little", "clang", ",", "as", "the", "droves", "of", "junior", "high", "school", "students", "walk", "by", "the", "centre", "of", "the", "\n", "stage", "dropping", "candy", "wrappers", ".", "(", "How", "do", "they", "eat", "so", "much", "candy", "so", "early", "in", "the", "\n", "morning", "?", ")", "While", "I", "sweep", "up", "the", "wrappers", "I", "watch", "the", "other", "rituals", "of", "morning", ":", "\n", "Mr", "Halpert", "unlocking", "the", "laundry", "’s", "handcart", "from", "its", "mooring", "to", "a", "cellar", "door", ",", "\n", "Joe", "Cornacchia", "’s", "son", "-", "in", "-", "law", "stacking", "out", "the", "empty", "crates", "from", "the", "delicatessen", ",", "\n", "the", "barber", "bringing", "out", "his", "sidewalk", "folding", "chair", ",", "Mr", "Goldstein", "arranging", "the", "\n", "coils", "of", "wire", "which", "proclaim", "the", "hardware", "store", "is", "open", ",", "the", "wife", "of", "the", "tenement", "’s", "\n", "superintendent", "depositing", "her", "chunky", "three", "-", "year", "-", "old", "with", "a", "toy", "mandolin", "on", "the", "\n", "stoop", ",", "the", "vantage", "point", "from", "which", "he", "is", "learning", "the", "English", "his", "mother", "can", "not", "\n", "speak", ".", "(", "Jacobs", "1961", ",", "p.", "61", ")", "\n", "DOI", ":", "10.4324/9781003467342", "-", "810.4324/9781003467342", "-", "8", "\n", "114", "Urban", "life", "in", "Delhi", "slumsStories", "from", "the", "street", "\n", "Introduction", "\n", "As", "in", "the", "quote", "by", "Jane", "Jacobs", ",", "setting", "out", "the", "morning", "routine", "she", "encountered", "on", "\n", "Hudson", "Street", ",", "New", "York", ",", "in", "her", "1961", "book", "Death", "and", "Life", "in", "Great", "American", "Cities", ",", "\n", "we", "highlight", "the", "voices", "of", "the", "entrepreneurs", "we", "encountered", "during", "this", "research", "in", "\n", "our", "Delhi", "neighbourhoods", ".", "Stories", "of", "the", "street", "scenes", "where", "goods", "are", "being", "hawked", "\n", "and", "haggled", "over", "in", "shops", "and", "markets", "will", "be", "told", "alongside", "the", "voices", "of", "entrepre", "-", "\n", "neurs", "–", "the", "street", "vendors", ",", "textile", "workers", ",", "carpenters", ",", "painters", ",", "recyclers", ",", "beauticians", ",", "\n", "barbers", "and", "cooks", ".", "The", "atmosphere", "in", "these", "settlements", "is", "buoyant", ",", "friendly", ",", "exuding", "\n", "community", "cohesion", "and", "trust", ".", "The", "slums", "provide", "examples", "of", "organic", "growth", "where", "\n", "the", "poor", "are", "agents", "of", "change", ".", "Place", "attachment", "provides", "a", "feeling", "of", "community", "\n", "uniqueness", "and", "irreplaceability", ".", "With", "a", "sense", "of", "belonging", ",", "feelings", "of", "loyalty", ",", "trust", "\n", "and", "a", "life", "with", "value", "and", "dignity", ",", "there", "follows", "a", "desire", "for", "bottom", "-", "up", "approaches", "to", "\n", "alleviating", "poverty", ".", "It", "is", "an", "‘", "infectious", "’", "atmosphere", ",", "with", "the", "poor", "focused", "on", "their", "\n", "family", ",", "neighbourhoods", "and", "the", "next", "generation", ".", "\n", "According", "to", "Jane", "Jacobs", "\n", "A", "good", "way", "to", "see", "the", "problem", "of", "the", "city", "is", "to", "take", "a", "bus", "or" ]

[ { "end": 1214, "label": "CITATION_REF", "start": 1195 }, { "end": 1201, "label": "AUTHOR", "start": 1195 }, { "end": 1206, "label": "YEAR", "start": 1202 }, { "end": 1267, "label": "CITATION_SPAN", "start": 1216 } ]

4 4 2 2 7.107E-03 7.107E-03 1.000E+00 1.000E+00 4 4.00000E-01 3 3 3 3 2 2 1.071E-01 1.071E-01 1.000E+00 1.000E+00 5 5.00000E-01 6 6 6 6 3 2 1.381E-01 1.381E-01 1.000E+00 1.000E+00 In conclusion, the numerical tests performed so far seem to conrm that the REDP procedure performs correctly, and can be safely combined with REDU andASN. 94 Tuesday 12thAugust, 2025 @ 13:38 6.5 Penetration variation with lateral sliding The scope of this Section is to investigate the in uence of lateral sliding on the measurement of penetration between two contacting bodies using the pinball contact algorithm. In particular, we want to verify if and how the amount of penetration varies when two contacting bodies slide with respect to each other along two parallel lines. A certain variation of the penetration is expected, since pinballs may not exactly represent a at surface and they protrude from the elements in which they are embedded. The tests assume two continuum blocks meshed by quadrangles in 2D. The tests performed are summarized in Table 14 and are described in the following. Test Mesh Description Displacement Sub-cases step [m] MEPE41 2 Q42L Parent pinballs ( MLEV 0 ) 0 :1 10 MEPE42 2 Q42L Idem 41 but MLEV 1 0:1 10 MEPE43 2 Q42L Idem 42 but add REDP 0:1 10 MEPE44 2 Q42L Idem 42 but MLEV 2 0:1 10 Table 14: Tests to measure the penetration between two parallel sliding bodies. 95 Tuesday 12thAugust, 2025 @ 13:38 6.5.1 Case MEPE41 This test is geometrically similar to case MEPE01 of Section 6.1. Two unit quadrangles touch them- selves in the initial conguration so that there is penetration already at step 0. A vertical initial velocity is assigned to the projectile (upper body) so that the contact is not discarded by the a priori rebound algorithm. However, unlike in case MEPE01 and the following ones presented previously, we do not prescribe any constraints besides those stemming from contact. This ensures that the system is not fully- constrained due to the prescribed dofs (and it does not become over-constrained when contact is detected). Consequently, there is no need to add extra dummy elements. Furthermore, we only perform the initialization step (step 0) and immediately stop the simulation thereafter. In fact, the scope here is just that of measuring the penetration. The test is subdivided into several distinct sub-tests, which are obtained by using

[ "4", "4", "2", "2", "7.107E-03", "7.107E-03", "1.000E+00", "1.000E+00", "\n", "4", "4.00000E-01", "3", "3", "3", "3", "2", "2", "1.071E-01", "1.071E-01", "1.000E+00", "1.000E+00", "\n", "5", "5.00000E-01", "6", "6", "6", "6", "3", "2", "1.381E-01", "1.381E-01", "1.000E+00", "1.000E+00", "\n", "In", "conclusion", ",", "the", "numerical", "tests", "performed", "so", "far", "seem", "to", "con", "\f", "rm", "that", "the", "REDP", "procedure", "\n", "performs", "correctly", ",", "and", "can", "be", "safely", "combined", "with", "REDU", "andASN", ".", "\n", "94", "\n", "Tuesday", "12thAugust", ",", "2025", "@", "13:38", "\n", "6.5", "Penetration", "variation", "with", "lateral", "sliding", "\n", "The", "scope", "of", "this", "Section", "is", "to", "investigate", "the", "in", "\n", "uence", "of", "lateral", "sliding", "on", "the", "measurement", "of", "\n", "penetration", "between", "two", "contacting", "bodies", "using", "the", "pinball", "contact", "algorithm", ".", "\n", "In", "particular", ",", "we", "want", "to", "verify", "if", "and", "how", "the", "amount", "of", "penetration", "varies", "when", "two", "contacting", "\n", "bodies", "slide", "with", "respect", "to", "each", "other", "along", "two", "parallel", "lines", ".", "A", "certain", "variation", "of", "the", "penetration", "\n", "is", "expected", ",", "since", "pinballs", "may", "not", "exactly", "represent", "a", "\n", "at", "surface", "and", "they", "protrude", "from", "the", "elements", "\n", "in", "which", "they", "are", "embedded", ".", "\n", "The", "tests", "assume", "two", "continuum", "blocks", "meshed", "by", "quadrangles", "in", "2D.", "The", "tests", "performed", "are", "\n", "summarized", "in", "Table", "14", "and", "are", "described", "in", "the", "following", ".", "\n", "Test", "Mesh", "Description", "Displacement", "Sub", "-", "cases", "\n", "step", "[", "m", "]", "\n", "MEPE41", "2", "Q42L", "Parent", "pinballs", "(", "MLEV", "0", ")", "0", ":1", "10", "\n", "MEPE42", "2", "Q42L", "Idem", "41", "but", "MLEV", "1", "0:1", "10", "\n", "MEPE43", "2", "Q42L", "Idem", "42", "but", "add", "REDP", "0:1", "10", "\n", "MEPE44", "2", "Q42L", "Idem", "42", "but", "MLEV", "2", "0:1", "10", "\n", "Table", "14", ":", "Tests", "to", "measure", "the", "penetration", "between", "two", "parallel", "sliding", "bodies", ".", "\n", "95", "\n", "Tuesday", "12thAugust", ",", "2025", "@", "13:38", "\n", "6.5.1", "Case", "MEPE41", "\n", "This", "test", "is", "geometrically", "similar", "to", "case", "MEPE01", "of", "Section", "6.1", ".", "Two", "unit", "quadrangles", "touch", "them-", "\n", "selves", "in", "the", "initial", "con", "\f", "guration", "so", "that", "there", "is", "penetration", "already", "at", "step", "0", ".", "A", "vertical", "initial", "\n", "velocity", "is", "assigned", "to", "the", "projectile", "(", "upper", "body", ")", "so", "that", "the", "contact", "is", "not", "discarded", "by", "the", "a", "priori", "\n", "rebound", "algorithm", ".", "\n", "However", ",", "unlike", "in", "case", "MEPE01", "and", "the", "following", "ones", "presented", "previously", ",", "we", "do", "not", "prescribe", "\n", "any", "constraints", "besides", "those", "stemming", "from", "contact", ".", "This", "ensures", "that", "the", "system", "is", "not", "fully-", "\n", "constrained", "due", "to", "the", "prescribed", "dofs", "(", "and", "it", "does", "not", "become", "over", "-", "constrained", "when", "contact", "is", "\n", "detected", ")", ".", "Consequently", ",", "there", "is", "no", "need", "to", "add", "extra", "dummy", "elements", ".", "Furthermore", ",", "we", "only", "\n", "perform", "the", "initialization", "step", "(", "step", "0", ")", "and", "immediately", "stop", "the", "simulation", "thereafter", ".", "In", "fact", ",", "the", "\n", "scope", "here", "is", "just", "that", "of", "measuring", "the", "penetration", ".", "\n", "The", "test", "is", "subdivided", "into", "several", "distinct", "sub", "-", "tests", ",", "which", "are", "obtained", "by", "using" ]

[]

base erosion and profit shifting CAPEX capital expenditure CIT corporate income tax EPZ export processing zone IGF Intergovernmental Forum on Mining, Minerals, Metals and Sustainable Development IMF International Monetary Fund IRR internal rate of return MNE multinational enterprise OECD Organisation for Economic Co-operation and Development OPEX operating expenditure PNG Papua New Guinea PSA production-sharing agreement RRT resource rent tax SCA Supreme Court of Appeal ## TABLE OF CONTENTS | 1.0 Introduction..................................................................................................................................................1 | 1.0 Introduction..................................................................................................................................................1 | |-----------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | | 1.1 About This Practice Note................................................................................................................................................................................ 4 | | | 1.2 Who Is This Practice Note For?................................................................................................................................................................ 4 | | | 1.3 What Gap DoesThis Practice Note Fill? ..................................................................................................................................... 4 | | 2.0 The Fundamentals of Ring-Fencing................................................................................................ 5 | 2.0 The Fundamentals of Ring-Fencing................................................................................................ 5 | | | 2.1 The Source of Ring-Fencing Rules........................................................................................................................................................ 7 | | | 2.2 The Prevalence of Ring-Fencing Rules in the Extractive Sectors.................................................................. 8 | | 3.0 The Benefits and Risks of Ring-Fencing .................................................................................... 12 | 3.0 The Benefits and Risks of Ring-Fencing .................................................................................... 12 | | | 3.1 The Benefits.................................................................................................................................................................................................................. 13 | | | 3.2 The Risks ......................................................................................................................................................................................................................... 19 | | 4.0 Designing Ring-Fencing Rules......................................................................................................... 23 | 4.0 Designing Ring-Fencing Rules......................................................................................................... 23 | | | 4.1 When Ring-Fencing Is an Appropriate Policy Response....................................................................................... 24 | | | 4.2 Designing Ring-Fencing Rules..............................................................................................................................................................26 | | | 4.3 What Aspects of Mining Operations Should Be Ring-Fenced? .................................................................28 | | | 4.4 WhichTaxes Should Be Ring-Fenced?.......................................................................................................................................39 | | | 4.5 Who Ring-Fencing Rules Should ApplyTo............................................................................................................................. 41 | | | 4.6 Is It Reasonable to Consider Some Exceptions to Ring-Fencing Rules?.........................................43 | | | 4.7 How to Deal With Permanent Losses Where Ring-Fencing Rules Exist............................................ 46 | | 5.0 The Implementation of Ring-Fencing Rules.............................................................................. 51 | 5.0 The Implementation of Ring-Fencing Rules.............................................................................. 51 | | | 5.1 Introducing Ring-Fencing Rules Into the Applicable Legal Framework.............................................. 52 | | | 5.2 How Should the Apportionment of Revenues and Expenditures Work?............................................56 | | 5.3 How of Ring-Fencing | ...............................................................................................................................................................................................................62 | | | 5.4 How to Design Taxpayers' Compliance Obligations...................................................................................................63 | | 6.0 Conclusion.................................................................................................................................................. 67 | 6.0 Conclusion.................................................................................................................................................. 67 | | | Financial Support for the OECD Comes From the Following Donors:............................................................70 | | | Support for the IGF Comes From the Following:........................................................................................................................71 | | | References................................................................................................................................................................................................................................72 | 1.0 Introduction ## 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

[ "base", "erosion", "and", "profit", "shifting", "\n\n", "CAPEX", "\n\n", "capital", "expenditure", "\n\n", "CIT", "\n\n", "corporate", "income", "tax", "\n\n", "EPZ", "\n\n", "export", "processing", "zone", "\n\n", "IGF", "\n\n", "Intergovernmental", "Forum", "on", "Mining", ",", "Minerals", ",", "Metals", "\n\n", "and", "Sustainable", "Development", "\n\n", "IMF", "\n\n", "International", "Monetary", "Fund", "\n\n", "IRR", "\n\n", "internal", "rate", "of", "return", "\n\n", "MNE", "\n\n", "multinational", "enterprise", "\n\n", "OECD", "\n\n", "Organisation", "for", "Economic", "Co", "-", "operation", "and", "Development", "\n\n", "OPEX", "\n\n", "operating", "expenditure", "\n\n", "PNG", "\n\n", "Papua", "New", "Guinea", "\n\n", "PSA", "\n\n", "production", "-", "sharing", "agreement", "\n\n", "RRT", "\n\n", "resource", "rent", "tax", "\n\n", "SCA", "\n\n", "Supreme", "Court", "of", "Appeal", "\n\n", "#", "#", "TABLE", "OF", "CONTENTS", "\n\n", "|", "1.0", "Introduction", "..................................................................................................................................................", "1", " ", "|", "1.0", "Introduction", "..................................................................................................................................................", "1", " ", "|", "\n", "|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|", "\n", "|", " ", "|", "1.1", "About", "This", "Practice", "Note", "................................................................................................................................................................................", "4", " ", "|", "\n", "|", " ", "|", "1.2", "Who", "Is", "This", "Practice", "Note", "For", "?", "................................................................................................................................................................", "4", " ", "|", "\n", "|", " ", "|", "1.3", "What", "Gap", "DoesThis", "Practice", "Note", "Fill", "?", ".....................................................................................................................................", "4", " ", "|", "\n", "|", "2.0", "The", "Fundamentals", "of", "Ring", "-", "Fencing", "................................................................................................", "5", " ", "|", "2.0", "The", "Fundamentals", "of", "Ring", "-", "Fencing", "................................................................................................", "5", " ", "|", "\n", "|", " ", "|", "2.1", "The", "Source", "of", "Ring", "-", "Fencing", "Rules", "........................................................................................................................................................", "7", " ", "|", "\n", "|", " ", "|", "2.2", "The", "Prevalence", "of", "Ring", "-", "Fencing", "Rules", "in", "the", "Extractive", "Sectors", "..................................................................", "8", " ", "|", "\n", "|", "3.0", "The", "Benefits", "and", "Risks", "of", "Ring", "-", "Fencing", "....................................................................................", "12", " ", "|", "3.0", "The", "Benefits", "and", "Risks", "of", "Ring", "-", "Fencing", "....................................................................................", "12", " ", "|", "\n", "|", " ", "|", "3.1", "The", "Benefits", "..................................................................................................................................................................................................................", "13", " ", "|", "\n", "|", " ", "|", "3.2", "The", "Risks", ".........................................................................................................................................................................................................................", "19", " ", "|", "\n", "|", "4.0", "Designing", "Ring", "-", "Fencing", "Rules", ".........................................................................................................", "23", " ", "|", "4.0", "Designing", "Ring", "-", "Fencing", "Rules", ".........................................................................................................", "23", " ", "|", "\n", "|", " ", "|", "4.1", "When", "Ring", "-", "Fencing", "Is", "an", "Appropriate", "Policy", "Response", ".......................................................................................", "24", " ", "|", "\n", "|", " ", "|", "4.2", "Designing", "Ring", "-", "Fencing", "Rules", "..............................................................................................................................................................", "26", " ", "|", "\n", "|", " ", "|", "4.3", "What", "Aspects", "of", "Mining", "Operations", "Should", "Be", "Ring", "-", "Fenced", "?", ".................................................................", "28", " ", "|", "\n", "|", " ", "|", "4.4", "WhichTaxes", "Should", "Be", "Ring", "-", "Fenced?", ".......................................................................................................................................", "39", " ", "|", "\n", "|", " ", "|", "4.5", "Who", "Ring", "-", "Fencing", "Rules", "Should", "ApplyTo", ".............................................................................................................................", "41", " ", "|", "\n", "|", " ", "|", "4.6", "Is", "It", "Reasonable", "to", "Consider", "Some", "Exceptions", "to", "Ring", "-", "Fencing", "Rules?", ".........................................", "43", " ", "|", "\n", "|", " ", "|", "4.7", "How", "to", "Deal", "With", "Permanent", "Losses", "Where", "Ring", "-", "Fencing", "Rules", "Exist", "............................................", "46", " ", "|", "\n", "|", "5.0", "The", "Implementation", "of", "Ring", "-", "Fencing", "Rules", "..............................................................................", "51", " ", "|", "5.0", "The", "Implementation", "of", "Ring", "-", "Fencing", "Rules", "..............................................................................", "51", " ", "|", "\n", "|", " ", "|", "5.1", "Introducing", "Ring", "-", "Fencing", "Rules", "Into", "the", "Applicable", "Legal", "Framework", "..............................................", "52", " ", "|", "\n", "|", " ", "|", "5.2", "How", "Should", "the", "Apportionment", "of", "Revenues", "and", "Expenditures", "Work?", "............................................", "56", " ", "|", "\n", "|", "5.3", "How", "of", "Ring", "-", "Fencing", " ", "|", "...............................................................................................................................................................................................................", "62", " ", "|", "\n", "|", " ", "|", "5.4", "How", "to", "Design", "Taxpayers", "'", "Compliance", "Obligations", "...................................................................................................", "63", " ", "|", "\n", "|", "6.0", "Conclusion", "..................................................................................................................................................", "67", " ", "|", "6.0", "Conclusion", "..................................................................................................................................................", "67", " ", "|", "\n", "|", " ", "|", "Financial", "Support", "for", "the", "OECD", "Comes", "From", "the", "Following", "Donors:", "............................................................", "70", " ", "|", "\n", "|", " ", "|", "Support", "for", "the", "IGF", "Comes", "From", "the", "Following:", "........................................................................................................................", "71", " ", "|", "\n", "|", " ", "|", "References", "................................................................................................................................................................................................................................", "72", "|", "\n\n", "1.0", "Introduction", "\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" ]

[]

spent the past four years studying the manuscripts, said the volumes were “four versions of Thornton’s life as her circumstances changed and she looked back over the years trying to make sense of what happened”. Thornton was “particularly keen to restate her identity as a chaste wife and to lay the blame for the family’s downturn in fortune on various male family members, including her late husband”, she said. “Her writings show that, alongside domestic and familial responsibilities, early modern women were fully engaged with the political events of their day.” Thornton was born in Yorkshire in 1626. The family moved to Ireland seven years later, where her father became lord deputy shortly before he died. Amid the turmoil of the Irish Rebellion, the family returned to northern England, where they were caught up in the civil war. As royalists, their estates were confiscated, and parliamentarian and Scottish soldiers were billeted on their land. Thornton agreed to marry a parliamentarian to secure her family’s financial future. She gave birth to nine babies, later describing both the dangers of childbirth and the deaths of six of her infant children. Her husband, William, died in 1668 without a will and leaving her heavily in debt. Pages from Alice Thornton’s Book of Remembrances. Photograph: Durham Cathedral Library  Her financial woes are detailed in her books, but they show her to be financially shrewd and capable of negotiating complex legal matters. “She was quite switched on and adept at managing finances,” said Beattie. In Book One, Thornton defends herself against rumours that she was conducting a clandestine affair with the local curate, Thomas Comber, who was not only nearly 20 years her junior but was also engaged to her 14-year-old daughter. “She really struggles with this because she thinks of herself as a godly woman, a chaste wife. I think she does have a good relationship with Comber, but the fact that people think she might be cheating on her husband really worried her,” said Beattie. Comber is later appointed dean of Durham Cathedral. “He does well for himself. But people wonder why she married off her daughter at the age of 14, and the rumour is that it’s about Alice trying to get Comber for herself.” Thornton also writes about two attempted rapes. One of her attackers was a captain in the Scottish army “who did swear to ravish me

[ "spent", "the", "past", "four", "years", "studying", "the", "manuscripts", ",", "said", "the", "volumes", "were", "“", "four", "versions", "of", "Thornton", "’s", "life", "as", "her", "circumstances", "changed", "and", "she", "looked", "back", "over", "the", "years", "trying", "to", "make", "sense", "of", "what", "happened", "”", ".", "\n\n", "Thornton", "was", "“", "particularly", "keen", "to", "restate", "her", "identity", "as", "a", "chaste", "wife", "and", "to", "lay", "the", "blame", "for", "the", "family", "’s", "downturn", "in", "fortune", "on", "various", "male", "family", "members", ",", "including", "her", "late", "husband", "”", ",", "she", "said", ".", "\n\n", "“", "Her", "writings", "show", "that", ",", "alongside", "domestic", "and", "familial", "responsibilities", ",", "early", "modern", "women", "were", "fully", "engaged", "with", "the", "political", "events", "of", "their", "day", ".", "”", "\n\n", "Thornton", "was", "born", "in", "Yorkshire", "in", "1626", ".", "The", "family", "moved", "to", "Ireland", "seven", "years", "later", ",", "where", "her", "father", "became", "lord", "deputy", "shortly", "before", "he", "died", ".", "Amid", "the", "turmoil", "of", "the", "Irish", "Rebellion", ",", "the", "family", "returned", "to", "northern", "England", ",", "where", "they", "were", "caught", "up", "in", "the", "civil", "war", ".", "As", "royalists", ",", "their", "estates", "were", "confiscated", ",", "and", "parliamentarian", "and", "Scottish", "soldiers", "were", "billeted", "on", "their", "land", ".", "\n\n", "Thornton", "agreed", "to", "marry", "a", "parliamentarian", "to", "secure", "her", "family", "’s", "financial", "future", ".", "She", "gave", "birth", "to", "nine", "babies", ",", "later", "describing", "both", "the", "dangers", "of", "childbirth", "and", "the", "deaths", "of", "six", "of", "her", "infant", "children", ".", "Her", "husband", ",", "William", ",", "died", "in", "1668", "without", "a", "will", "and", "leaving", "her", "heavily", "in", "debt", ".", "\n\n", "Pages", "from", "Alice", "Thornton", "’s", "Book", "of", "Remembrances", ".", "Photograph", ":", "Durham", "Cathedral", "Library", "\n\n", "<", "!", "--", "image", "--", ">", "\n\n", "Her", "financial", "woes", "are", "detailed", "in", "her", "books", ",", "but", "they", "show", "her", "to", "be", "financially", "shrewd", "and", "capable", "of", "negotiating", "complex", "legal", "matters", ".", "“", "She", "was", "quite", "switched", "on", "and", "adept", "at", "managing", "finances", ",", "”", "said", "Beattie", ".", "\n\n", "In", "Book", "One", ",", "Thornton", "defends", "herself", "against", "rumours", "that", "she", "was", "conducting", "a", "clandestine", "affair", "with", "the", "local", "curate", ",", "Thomas", "Comber", ",", "who", "was", "not", "only", "nearly", "20", "years", "her", "junior", "but", "was", "also", "engaged", "to", "her", "14", "-", "year", "-", "old", "daughter", ".", "\n\n", "“", "She", "really", "struggles", "with", "this", "because", "she", "thinks", "of", "herself", "as", "a", "godly", "woman", ",", "a", "chaste", "wife", ".", "I", "think", "she", "does", "have", "a", "good", "relationship", "with", "Comber", ",", "but", "the", "fact", "that", "people", "think", "she", "might", "be", "cheating", "on", "her", "husband", "really", "worried", "her", ",", "”", "said", "Beattie", ".", "\n\n", "Comber", "is", "later", "appointed", "dean", "of", "Durham", "Cathedral", ".", "“", "He", "does", "well", "for", "himself", ".", "But", "people", "wonder", "why", "she", "married", "off", "her", "daughter", "at", "the", "age", "of", "14", ",", "and", "the", "rumour", "is", "that", "it", "’s", "about", "Alice", "trying", "to", "get", "Comber", "for", "herself", ".", "”", "\n\n", "Thornton", "also", "writes", "about", "two", "attempted", "rapes", ".", "One", "of", "her", "attackers", "was", "a", "captain", "in", "the", "Scottish", "army", "“", "who", "did", "swear", "to", "ravish", "me" ]

[]

23.39 | 1.22 | 77.23 | 401.76 | | | 10-6-1 | 3.95 | 3.04 | 23.95 | 1.23 | 77 | 406.03 | | | 100-6-1 | 4.22 | 3.04 | 24.1 | 1.22 | 76.36 | 399.91 | | | 1000-6-1 | 4.3 | 3.03 | 24.62 | 1.21 | 76.27 | 397.27 | Table 4: Analysis of the generated text among different dimensions. We used the prefix in the validation set and the small transformer model trained on CCNEWS to generate the text. Under the column params we report hyper parameters for the decoding strategy considered. For DELAYEDBS we we have varied only the parameter for top-k sampling and we used beam size equal to 6 and delay length of 1 . | prefix | Princess Margaret, Countess of Snowdon . Princess Margaret, Countess of Snowdon, (Margaret Rose 21 Au- gust 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. | Whitey Bulger . James Joseph Whitey Bulger Jr. ( Septem- ber 3, 1929 - October 30, 2018) was an Irish-American or- ganized crime boss and FBI informant who led the Winter Hill Gang in the Winter Hill neighborhood of Somerville, Massachusetts, a city directly northwest of Boston. | |----------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | top-k | She is the only surviving member from the Royal Family who was born in the same year as the Queen Mother. Princess Margaret, Countess of Snowdon, (Margaret Rose 21 August 1930 - 9 February 2002) was a British princess who married into the British Royal Family in 1939. She is a cousin to the Queen, Prince Philip, Prince Charles, Prince William, Prince Harry and Prince Edward. Princess Margaret, Countess of Snowdon, (Margaret Rose 21 August 1930 - 9 February 2002) is the younger daugh- ter of King George VI and Queen Elizabeth. She is the only survivor from the Royal Family who was born in the same year as Queen Elizabeth. | He was a fugitive for 16 years before his arrest in 2011. He was sentenced in 2013 to two life terms plus five years for his role in 11 murders and was released in 2014. Bulger was found dead in his cell at the U.S. penitentiary in West Virginia. He was 89. He was serving the life sentences for his role in the infa-

[ "23.39", "|", " ", "1.22", "|", " ", "77.23", "|", " ", "401.76", "|", "\n", "|", " ", "|", "10", "-", "6", "-", "1", " ", "|", " ", "3.95", "|", " ", "3.04", "|", " ", "23.95", "|", " ", "1.23", "|", " ", "77", " ", "|", " ", "406.03", "|", "\n", "|", " ", "|", "100", "-", "6", "-", "1", " ", "|", " ", "4.22", "|", " ", "3.04", "|", " ", "24.1", " ", "|", " ", "1.22", "|", " ", "76.36", "|", " ", "399.91", "|", "\n", "|", " ", "|", "1000", "-", "6", "-", "1", "|", " ", "4.3", " ", "|", " ", "3.03", "|", " ", "24.62", "|", " ", "1.21", "|", " ", "76.27", "|", " ", "397.27", "|", "\n\n", "Table", "4", ":", "Analysis", "of", "the", "generated", "text", "among", "different", "dimensions", ".", "We", "used", "the", "prefix", "in", "the", "validation", "set", "and", "the", "small", "transformer", "model", "trained", "on", "CCNEWS", "to", "generate", "the", "text", ".", "Under", "the", "column", "params", "we", "report", "hyper", "parameters", "for", "the", "decoding", "strategy", "considered", ".", "For", "DELAYEDBS", "we", "we", "have", "varied", "only", "the", "parameter", "for", "top", "-", "k", "sampling", "and", "we", "used", "beam", "size", "equal", "to", "6", "and", "delay", "length", "of", "1", ".", "\n\n", "|", "prefix", " ", "|", "Princess", "Margaret", ",", "Countess", "of", "Snowdon", ".", "Princess", "Margaret", ",", "Countess", "of", "Snowdon", ",", "(", "Margaret", "Rose", "21", "Au-", "gust", "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", ".", " ", "|", "Whitey", "Bulger", ".", "James", "Joseph", "Whitey", "Bulger", "Jr.", "(", "Septem-", "ber", "3", ",", "1929", "-", "October", "30", ",", "2018", ")", "was", "an", "Irish", "-", "American", "or-", "ganized", "crime", "boss", "and", "FBI", "informant", "who", "led", "the", "Winter", "Hill", "Gang", "in", "the", "Winter", "Hill", "neighborhood", "of", "Somerville", ",", "Massachusetts", ",", "a", "city", "directly", "northwest", "of", "Boston", ".", " ", "|", "\n", "|----------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|", "\n", "|", "top", "-", "k", " ", "|", "She", "is", "the", "only", "surviving", "member", "from", "the", "Royal", "Family", "who", "was", "born", "in", "the", "same", "year", "as", "the", "Queen", "Mother", ".", "Princess", "Margaret", ",", "Countess", "of", "Snowdon", ",", "(", "Margaret", "Rose", "21", "August", "1930", "-", "9", "February", "2002", ")", "was", "a", "British", "princess", "who", "married", "into", "the", "British", "Royal", "Family", "in", "1939", ".", "She", "is", "a", "cousin", "to", "the", "Queen", ",", "Prince", "Philip", ",", "Prince", "Charles", ",", "Prince", "William", ",", "Prince", "Harry", "and", "Prince", "Edward", ".", "Princess", "Margaret", ",", "Countess", "of", "Snowdon", ",", "(", "Margaret", "Rose", "21", "August", "1930", "-", "9", "February", "2002", ")", "is", "the", "younger", "daugh-", "ter", "of", "King", "George", "VI", "and", "Queen", "Elizabeth", ".", "She", "is", "the", "only", "survivor", "from", "the", "Royal", "Family", "who", "was", "born", "in", "the", "same", "year", "as", "Queen", "Elizabeth", ".", " ", "|", "He", "was", "a", "fugitive", "for", "16", "years", "before", "his", "arrest", "in", "2011", ".", "He", "was", "sentenced", "in", "2013", "to", "two", "life", "terms", "plus", "five", "years", "for", "his", "role", "in", "11", "murders", "and", "was", "released", "in", "2014", ".", "Bulger", "was", "found", "dead", "in", "his", "cell", "at", "the", "U.S.", "penitentiary", "in", "West", "Virginia", ".", "He", "was", "89", ".", "He", "was", "serving", "the", "life", "sentences", "for", "his", "role", "in", "the", "infa-" ]

[]

outputs to produce badges and indicators wh ich can highlight easy-to-reproduce or well-reproduced research outputs. Finally, SciLake has initiated 4 pilots, encompassing a diverse array of scientiﬁc domains (Neuroscience, Cancer, Transport, and Energy), to showcase and assess the value of the SciLake services and their capability to address needs of diverse research communities. During RP1, SciLake partners have conducted a broad range of activities which lay the groundwork for the rest of the project. The most important achievements we re: - The collection and initial analysis of the SciLake pilot needs and requirements regarding the SciLake ecosystem (partly reported in D1.1)Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far⌄ 2 of 4 - The design and implementation of the initial version of the SciLake ecosystem architecture (reported in D1.2) - The design and implementation of the initial versions of the Scientiﬁc Lake service (D2.1) the Smart Impact-driven Knowledge Discovery service (D3.1) and the Smart Reproducibility Assistance service (D4.1) - The groundwork for the creation of the domain-speciﬁc SKGs that will be used by the SciLake pilots - The engagement of partners in various dissemination activities As a RIA project, SciLake naturally focuses on innovation, striving to advance the current state of the art. Its main innovations are expected to be centered around the key technologies used for the creation of the Scientiﬁc Lake, the Smart Impact-driven Knowledge Discovery, and the Smart Reproducibility Assistance service. Regarding the Scientiﬁc Lake service, the main contribution is expected to be in the ﬁeld of the eﬃcient Knowledge Graph mining and querying techniques. Notably, the AvantGraph component already incorporates innovative approaches that oﬀer performance on par with, or superior to, state- of-the-art systems, under speciﬁc conditions. By testing scenarios within the SciLake pilot projects, the AvantGraph team aims to address cases of particular interest and develop advanced solutions that push the boundaries of the current technologies. Regarding the Smart Impact-Driven Knowledge Discovery service, the primary contribution is expected to lie in the development of improved impact indicators for research outputs. Currently, no adequate impact indicators exist for research datasets or software hence, we aim to provide meaningful solutions for that. Additionally, we investigate variations of indicators for papers, incorporating additional factors (e.g. citation intent, topics) to oﬀer a more nuanced impact assessment. Finally, we are experimenting on meaningful approaches to

[ "outputs", "to", "produce", "badges", "and", "indicators", "wh", "ich", "can", "highlight", "easy", "-", "to", "-", "reproduce", "or", "well", "-", "reproduced", "\n", "research", "outputs", ".", "\n", "Finally", ",", "SciLake", "has", "initiated", "4", "pilots", ",", "encompassing", "a", "diverse", "array", "of", "scientiﬁc", "domains", "\n", "(", "Neuroscience", ",", "Cancer", ",", "Transport", ",", "and", "Energy", ")", ",", "to", "showcase", "and", "assess", "the", "value", "of", "the", "SciLake", "\n", "services", "and", "their", "capability", "to", "address", "needs", "of", "diverse", "research", "communities", ".", "\n", "During", "RP1", ",", "SciLake", "partners", "have", "conducted", "a", "broad", "range", "of", "activities", "which", "lay", "the", "groundwork", "\n", "for", "the", "rest", "of", "the", "project", ".", "The", "most", "important", "achievements", "we", "re", ":", "\n", "-", "The", "collection", "and", "initial", "analysis", "of", "the", "SciLake", "pilot", "needs", "and", "requirements", "regarding", "the", "SciLake", "\n", "ecosystem", "(", "partly", "reported", "in", "D1.1)Work", "performed", "from", "the", "beginning", "of", "the", "project", "to", "the", "end", "of", "the", "\n", "period", "covered", "by", "the", "report", "and", "main", "results", "achieved", "so", "far", "⌄", "\n", "2", "of", "4", "\n", "-", "The", "design", "and", "implementation", "of", "the", "initial", "version", "of", "the", "SciLake", "ecosystem", "architecture", "(", "reported", "\n", "in", "D1.2", ")", "\n", "-", "The", "design", "and", "implementation", "of", "the", "initial", "versions", "of", "the", "Scientiﬁc", "Lake", "service", "(", "D2.1", ")", "the", "Smart", "\n", "Impact", "-", "driven", "Knowledge", "Discovery", "service", "(", "D3.1", ")", "and", "the", "Smart", "Reproducibility", "Assistance", "service", "\n", "(", "D4.1", ")", "\n", "-", "The", "groundwork", "for", "the", "creation", "of", "the", "domain", "-", "speciﬁc", "SKGs", "that", "will", "be", "used", "by", "the", "SciLake", "pilots", "\n", "-", "The", "engagement", "of", "partners", "in", "various", "dissemination", "activities", "\n", "As", "a", "RIA", "project", ",", "SciLake", "naturally", "focuses", "on", "innovation", ",", "striving", "to", "advance", "the", "current", "state", "of", "the", "\n", "art", ".", "Its", "main", "innovations", "are", "expected", "to", "be", "centered", "around", "the", "key", "technologies", "used", "for", "the", "\n", "creation", "of", "the", "Scientiﬁc", "Lake", ",", "the", "Smart", "Impact", "-", "driven", "Knowledge", "Discovery", ",", "and", "the", "Smart", "\n", "Reproducibility", "Assistance", "service", ".", "\n", "Regarding", "the", "Scientiﬁc", "Lake", "service", ",", "the", "main", "contribution", "is", "expected", "to", "be", "in", "the", "ﬁeld", "of", "the", "\n", "eﬃcient", "Knowledge", "Graph", "mining", "and", "querying", "techniques", ".", "Notably", ",", "the", "AvantGraph", "component", "\n", "already", "incorporates", "innovative", "approaches", "that", "oﬀer", "performance", "on", "par", "with", ",", "or", "superior", "to", ",", "state-", "\n", "of", "-", "the", "-", "art", "systems", ",", "under", "speciﬁc", "conditions", ".", "By", "testing", "scenarios", "within", "the", "SciLake", "pilot", "projects", ",", "\n", "the", "AvantGraph", "team", "aims", "to", "address", "cases", "of", "particular", "interest", "and", "develop", "advanced", "solutions", "\n", "that", "push", "the", "boundaries", "of", "the", "current", "technologies", ".", "\n", "Regarding", "the", "Smart", "Impact", "-", "Driven", "Knowledge", "Discovery", "service", ",", "the", "primary", "contribution", "is", "\n", "expected", "to", "lie", "in", "the", "development", "of", "improved", "impact", "indicators", "for", "research", "outputs", ".", "Currently", ",", "no", "\n", "adequate", "impact", "indicators", "exist", "for", "research", "datasets", "or", "software", "hence", ",", "we", "aim", "to", "provide", "\n", "meaningful", "solutions", "for", "that", ".", "Additionally", ",", "we", "investigate", "variations", "of", "indicators", "for", "papers", ",", "\n", "incorporating", "additional", "factors", "(", "e.g.", "citation", "intent", ",", "topics", ")", "to", "oﬀer", "a", "more", "nuanced", "impact", "\n", "assessment", ".", "Finally", ",", "we", "are", "experimenting", "on", "meaningful", "approaches", "to" ]

[]

emphasis on instructional leadership and quality assurance.

[ "emphasis", "on", "instructional", "leadership", "and", "quality", "assurance", ".", "\n\n", "<", "!", "--", "image", "--", ">", "\n\n", "<", "!", "--", "image", "--", ">", "\n\n", "<", "!", "--", "image", "--", ">" ]

[]

from millions to trillions. However, the origin of bacteria dates back to 3.5 billion years ago, and so the overall diversification rate among them is actually quite low. "If actual bacterial richness really is much higher than described richness for other groups, then a clade with low diversification rates [namely bacteria] would contain the majority of species across life - this would be in stark contrast to our results. Therefore, we caution that our results apply primarily to known species diversity," wrote the authors. RELATED TOPICS Plants & Animals New Species Ecology Research Birds Trees Earth & Climate Ecology Rainforests Exotic Species Environmental Awareness RELATED TERMS Adult stem cell Stem cell Evolution Earth Sociobiology Convergent evolution Biodiversity Biodiversity hotspot Story Source: Materials provided by Frontiers . Note: Content may be edited for style and length. Journal Reference : John J. Wiens, Daniel S. Moen. Rapid radiations underlie most of the known diversity of life . Frontiers in Ecology and Evolution , 2025; 13 DOI: 10.3389/fevo.2025.1596591 Cite This Page : MLA APA Chicago Frontiers. "Most of Earth’s species came from explosive bursts of evolution." ScienceDaily. ScienceDaily, 23 August 2025. <www.sciencedaily.com / releases / 2025 / 08 / 250822073805.htm>. Frontiers. (2025, August 23). Most of Earth’s species came from explosive bursts of evolution. ScienceDaily . Retrieved August 27, 2025 from www.sciencedaily.com / releases / 2025 / 08 / 250822073805.htm Frontiers. "Most of Earth’s species came from explosive bursts of evolution." ScienceDaily. www.sciencedaily.com / releases / 2025 / 08 / 250822073805.htm (accessed August 27, 2025). Explore More from ScienceDaily RELATED STORIES Violent Supernovae 'Triggered at Least Two Earth Extinctions' Mar. 13, 2025 — At least two mass extinction events in Earth's history were likely caused by the 'devastating' effects of nearby supernova explosions, a new study suggests. Researchers say these ... No Increase in Grain Dust Explosion Incidents Last Year, Decrease in Injuries Feb. 18, 2025 — Nine U.S. grain dust explosions in 2024 caused two injuries and no fatalities, according to a nationwide annual summary. These numbers are similar to last year's (nine explosions, 12 injuries ... Most Species Are Rare, but Not Very Rare Sep. 4, 2023 — More than 100 years of observations in nature have revealed a universal pattern of species abundances: Most species are rare but not very rare, and only a few species are very common. These so-called ... Biodiversity Engine for Fishes: Shifting Water Depth Feb.

[ "from", "millions", "to", "trillions", ".", "However", ",", "the", "origin", "of", "bacteria", "dates", "back", "to", "3.5", "billion", "years", "ago", ",", "and", "so", "the", "overall", "diversification", "rate", "among", "them", "is", "actually", "quite", "low", ".", "\n\n\n", "\"", "If", "actual", "bacterial", "richness", "really", "is", "much", "higher", "than", "described", "richness", "for", "other", "groups", ",", "then", "a", "clade", "with", "low", "diversification", "rates", "[", "namely", "bacteria", "]", "would", "contain", "the", "majority", "of", "species", "across", "life", "-", "this", "would", "be", "in", "stark", "contrast", "to", "our", "results", ".", "Therefore", ",", "we", "caution", "that", "our", "results", "apply", "primarily", "to", "known", "species", "diversity", ",", "\"", "wrote", "the", "authors", ".", "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n", "RELATED", "TOPICS", "\n\n\n\n\n\n\n", "Plants", "&", "Animals", "\n\n\n\n\n\n\n", "New", "Species", "\n\n\n\n\n\n\n", "Ecology", "Research", "\n\n\n\n\n\n\n", "Birds", "\n\n\n\n\n\n\n", "Trees", "\n\n\n\n\n\n\n\n\n\n\n", "Earth", "&", "Climate", "\n\n\n\n\n\n\n", "Ecology", "\n\n\n\n\n\n\n", "Rainforests", "\n\n\n\n\n\n\n", "Exotic", "Species", "\n\n\n\n\n\n\n", "Environmental", "Awareness", "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n", "RELATED", "TERMS", "\n\n\n\n\n\n\n", "Adult", "stem", "cell", "\n\n\n\n\n\n\n", "Stem", "cell", "\n\n\n\n\n\n\n", "Evolution", "\n\n\n\n\n\n\n", "Earth", "\n\n\n\n\n\n\n", "Sociobiology", "\n\n\n\n\n\n\n", "Convergent", "evolution", "\n\n\n\n\n\n\n", "Biodiversity", "\n\n\n\n\n\n\n", "Biodiversity", "hotspot", "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n", "Story", "Source", ":", "\n\n\n", "Materials", "provided", "by", "\n", "Frontiers", "\n", ".", "\n", "Note", ":", "Content", "may", "be", "edited", "for", "style", "and", "length", ".", "\n\n\n\n\n\n\n\n\n\n\n", "Journal", "Reference", "\n", ":", "\n\n\n\n\n", "John", "J.", "Wiens", ",", "Daniel", "S.", "Moen", ".", "\n", "Rapid", "radiations", "underlie", "most", "of", "the", "known", "diversity", "of", "life", "\n", ".", "\n", "Frontiers", "in", "Ecology", "and", "Evolution", "\n", ",", "2025", ";", "13", "DOI", ":", "\n", "10.3389", "/", "fevo.2025.1596591", "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n", "Cite", "This", "Page", "\n", ":", "\n\n\n\n\n\n\n", "MLA", "\n\n\n", "APA", "\n\n\n", "Chicago", "\n\n\n\n\n\n\n\n\n", "Frontiers", ".", "\"", "Most", "of", "Earth", "’s", "species", "came", "from", "explosive", "bursts", "of", "evolution", ".", "\"", "ScienceDaily", ".", "ScienceDaily", ",", "23", "August", "2025", ".", "<", "www.sciencedaily.com", "\n", "/", "\n", "releases", "\n", "/", "\n", "2025", "\n", "/", "\n", "08", "\n", "/", "\n", "250822073805.htm", ">", ".", "\n\n\n", "Frontiers", ".", "(", "2025", ",", "August", "23", ")", ".", "Most", "of", "Earth", "’s", "species", "came", "from", "explosive", "bursts", "of", "evolution", ".", "\n", "ScienceDaily", "\n", ".", "Retrieved", "August", "27", ",", "2025", "from", "www.sciencedaily.com", "\n", "/", "\n", "releases", "\n", "/", "\n", "2025", "\n", "/", "\n", "08", "\n", "/", "\n", "250822073805.htm", "\n\n\n", "Frontiers", ".", "\"", "Most", "of", "Earth", "’s", "species", "came", "from", "explosive", "bursts", "of", "evolution", ".", "\"", "ScienceDaily", ".", "www.sciencedaily.com", "\n", "/", "\n", "releases", "\n", "/", "\n", "2025", "\n", "/", "\n", "08", "\n", "/", "\n", "250822073805.htm", "(", "accessed", "August", "27", ",", "2025", ")", ".", "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n", "Explore", "More", "\n\n\n", "from", "ScienceDaily", "\n\n\n\n\n\n\n\n\n", "RELATED", "STORIES", "\n\n\n\n\n \n", "Violent", "Supernovae", "'", "Triggered", "at", "Least", "Two", "Earth", "Extinctions", "'", "\n\n\n\n\n", "Mar.", "13", ",", "2025", "—", "\n ", "At", "least", "two", "mass", "extinction", "events", "in", "Earth", "'s", "history", "were", "likely", "caused", "by", "the", "'", "devastating", "'", "effects", "of", "nearby", "supernova", "explosions", ",", "a", "new", "study", "suggests", ".", "Researchers", "say", "these", "...", "\n \n", "No", "Increase", "in", "Grain", "Dust", "Explosion", "Incidents", "Last", "Year", ",", "Decrease", "in", "Injuries", "\n\n\n\n\n", "Feb.", "18", ",", "2025", "—", "\n ", "Nine", "U.S.", "grain", "dust", "explosions", "in", "2024", "caused", "two", "injuries", "and", "no", "fatalities", ",", "according", "to", "a", "nationwide", "annual", "summary", ".", "These", "numbers", "are", "similar", "to", "last", "year", "'s", "(", "nine", "explosions", ",", "12", "injuries", "...", "\n \n", "Most", "Species", "Are", "Rare", ",", "but", "Not", "Very", "Rare", "\n\n\n\n\n", "Sep.", "4", ",", "2023", "—", "\n ", "More", "than", "100", "years", "of", "observations", "in", "nature", "have", "revealed", "a", "universal", "pattern", "of", "species", "abundances", ":", "Most", "species", "are", "rare", "but", "not", "very", "rare", ",", "and", "only", "a", "few", "species", "are", "very", "common", ".", "These", "so", "-", "called", "...", "\n \n", "Biodiversity", "Engine", "for", "Fishes", ":", "Shifting", "Water", "Depth", "\n\n\n\n\n", "Feb." ]

[ { "end": 1312, "label": "CITATION_SPAN", "start": 1138 } ]

898 774 973 Proportion of viral reads median (IQR)54% (40% - 68%)29% (18% - 54%)48% (27% - 65%) Proportion of reads assigned to newly described viruses median (IQR) mean (range)44% (29% - 60%) 45% (1% - 92%)22% (12% - 47%) 32% (2% - 93%)37% (19% - 58%) 40% (1% - 93%) IQR, interquartile range 102.3.2 Human viruses The identification of human viruses against established databases revealed an expected repertoire of childhood gut viruses. These were namely Human mastadenovirus A, B, C and F, Mamastrovirus ,Human bocaparvovirus, Rotavirus A, Norwalk virus, Human herpesvirus 5 (cytomegalovirus), Human herpesvirus 6 (roseolovirus), Human parechovirus, Enterovirus A, Cardiovirus, sequences of human endogenous retroviruses, and most importantly, various anelloviridae (Alpha-, Beta and Gammatorquevirus of various species). Anelloviruses were partly covered by specific PCR testing in one of our previous studies on CD (Tapia, Chuda et al. 2020) - therein published exploration using a single real-time PCR reaction did not however cover the whole spectrum of anelloviruses known today. Notably, although our metagenomic protocol was primarily designed to find DNA viruses, the signal included many known RNA viruses that commonly infect children. These included rotavirus, enterovirus and parechovirus. It is well known that DNA polymerases also have some RNA-dependent DNA polymerase activity, which is inconsistently reflected in these signals. Signals from human viruses, except Anelloviridae, did not meet the criteria for association testing (too few positive samples or too few positive individuals would preclude meaningful testing). The human virus data will be reported in a paper together with the bacteriophage data. 2.3.3 Known bacteriophages and novel viruses from the dark matter The DNA virome was dominated by bacteriophage genomes, but a large fraction of the viromes was unidentifiable prior to the novel virus extraction process. This unidentified fraction is commonly referred to as the dark matter . For example, the mean unidentified fraction in samples from the Finnish DIPP study was 95.5% against a collection of full-length and near-full-length viral sequences from NCBI GenBank, 70.0% against (Camarillo-Guerrero, Almeida et al. 2021); 88.9% against (Gregory, Zablocki et al. 2020); 70.7% against (Shah, Deng et al. 2023). As the authors of the latter publications are Partner 20 in this project, and because of the exceptionally high quality of their annotated non-redundant database, we decided to use their protocols and experience to construct a novel viral database of the dark matter observed in both MIDIA and DIPP studies. Using methods

[ "898", "774", "973", "\n", "Proportion", "of", "viral", "reads", "\n", "median", "(", "IQR)54", "%", "\n", "(", "40", "%", "-", "68%)29", "%", "\n", "(", "18", "%", "-", "54%)48", "%", "\n", "(", "27", "%", "-", "65", "%", ")", "\n", "Proportion", "of", "reads", "assigned", "to", "\n", "newly", "described", "viruses", "\n", "median", "(", "IQR", ")", "\n", "mean", "(", "range)44", "%", "(", "29", "%", "-", "60", "%", ")", "\n", "45", "%", "(", "1", "%", "-", "92%)22", "%", "(", "12", "%", "-", "47", "%", ")", "\n", "32", "%", "(", "2", "%", "-", "93%)37", "%", "(", "19", "%", "-", "58", "%", ")", "\n", "40", "%", "(", "1", "%", "-", "93", "%", ")", "\n", "IQR", ",", "interquartile", "range", "\n", "102.3.2", "Human", "viruses", "\n", "The", "identification", "of", "human", "viruses", "against", "established", "databases", "revealed", "an", "expected", "repertoire", "of", "childhood", "gut", "\n", "viruses", ".", "These", "were", "namely", "Human", "mastadenovirus", " ", "A", ",", "B", ",", "C", "and", "F", ",", "Mamastrovirus", ",", "Human", "bocaparvovirus", ",", "Rotavirus", "A", ",", "\n", "Norwalk", "virus", ",", "Human", "herpesvirus", "5", "(", "cytomegalovirus", ")", ",", "Human", "herpesvirus", "6", "(", "roseolovirus", ")", ",", "Human", "parechovirus", ",", "\n", "Enterovirus", "A", ",", "Cardiovirus", ",", "sequences", "of", "human", "endogenous", "retroviruses", ",", "and", "most", "importantly", ",", "various", "anelloviridae", "\n", "(", "Alpha-", ",", "Beta", "and", "Gammatorquevirus", "of", "various", "species", ")", ".", "Anelloviruses", "were", "partly", "covered", "by", "specific", "PCR", "testing", "in", "\n", "one", "of", "our", "previous", "studies", "on", "CD", "(", "Tapia", ",", "Chuda", "et", "al", ".", "2020", ")", "-", "therein", "published", "exploration", "using", "a", "single", "real", "-", "time", "PCR", "\n", "reaction", "did", "not", "however", "cover", "the", "whole", "spectrum", "of", "anelloviruses", "known", "today", ".", "\n", "Notably", ",", "although", "our", "metagenomic", "protocol", "was", "primarily", "designed", "to", "find", "DNA", "viruses", ",", "the", "signal", "included", "many", "\n", "known", "RNA", "viruses", "that", "commonly", "infect", "children", ".", "These", "included", "rotavirus", ",", "enterovirus", "and", "parechovirus", ".", "It", "is", "well", "\n", "known", "that", "DNA", "polymerases", "also", "have", "some", "RNA", "-", "dependent", "DNA", "polymerase", "activity", ",", "which", "is", "inconsistently", "reflected", "\n", "in", "these", "signals", ".", "\n", "Signals", "from", "human", "viruses", ",", "except", "Anelloviridae", ",", "did", "not", "meet", "the", "criteria", "for", "association", "testing", "(", "too", "few", "positive", "\n", "samples", "or", "too", "few", "positive", "individuals", "would", "preclude", "meaningful", "testing", ")", ".", "The", "human", "virus", "data", "will", "be", "reported", "in", "a", "\n", "paper", "together", "with", "the", "bacteriophage", "data", ".", "\n", "2.3.3", "Known", "bacteriophages", "and", "novel", "viruses", "from", "the", "dark", "matter", "\n", "The", "DNA", "virome", "was", "dominated", "by", "bacteriophage", "genomes", ",", "but", "a", "large", "fraction", "of", "the", "viromes", "was", "unidentifiable", "prior", "\n", "to", "the", "novel", "virus", "extraction", "process", ".", "This", "unidentified", "fraction", "is", "commonly", "referred", "to", "as", "the", "dark", "matter", ".", "For", "example", ",", "\n", "the", "mean", "unidentified", "fraction", "in", "samples", "from", "the", "Finnish", "DIPP", "study", "was", "95.5", "%", "against", "a", "collection", "of", "full", "-", "length", "and", "\n", "near", "-", "full", "-", "length", "viral", "sequences", "from", "NCBI", "GenBank", ",", "70.0", "%", "against", "(", "Camarillo", "-", "Guerrero", ",", "Almeida", "et", "al", ".", "2021", ")", ";", "88.9", "%", "\n", "against", "(", "Gregory", ",", "Zablocki", "et", "al", ".", "2020", ")", ";", "70.7", "%", "against", "(", "Shah", ",", "Deng", "et", "al", ".", "2023", ")", ".", "\n", "As", "the", "authors", "of", "the", "latter", "publications", "are", "Partner", "20", "in", "this", "project", ",", "and", "because", "of", "the", "exceptionally", "high", "quality", "of", "\n", "their", "annotated", "non", "-", "redundant", "database", ",", "we", "decided", "to", "use", "their", "protocols", "and", "experience", "to", "construct", "a", "novel", "viral", "\n", "database", "of", "the", "dark", "matter", "observed", "in", "both", "MIDIA", "and", "DIPP", "studies", ".", "\n", "Using", "methods" ]

[ { "end": 946, "label": "CITATION_REF", "start": 922 }, { "end": 941, "label": "AUTHOR", "start": 922 }, { "end": 946, "label": "YEAR", "start": 942 }, { "end": 2263, "label": "CITATION_REF", "start": 2224 }, { "end": 2258, "label": "AUTHOR", "start": 2224 }, { "end": 2263, "label": "YEAR", "start": 2259 }, { "end": 2310, "label": "CITATION_REF", "start": 2281 }, { "end": 2305, "label": "AUTHOR", "start": 2281 }, { "end": 2310, "label": "YEAR", "start": 2306 }, { "end": 2350, "label": "CITATION_REF", "start": 2328 }, { "end": 2350, "label": "YEAR", "start": 2346 }, { "end": 2345, "label": "AUTHOR", "start": 2328 } ]

880 PublicationsFigure 3.55. Number of publications and EC projects in collaboration between EaP actors in different countries, in the ‘Health and wellbeing’ domain Colour indicates the relative distribution of documents, computed row-wise. AM AZ BY GE MD UA Other 2 9 10 10 9 14 2 2 2 2 2 2 9 2 9 8 8 16 10 2 9 10 10 17 10 2 8 10 8 18 9 2 8 10 8 32 EC projectsAM AZ BY GE MD UA Other AM 4 19 21 5 18 189 AZ 4 4 5 4 51 157 BY 19 4 18 13 71 787 GE 21 5 18 6 24 238 MD 5 4 13 6 14 72 UA 18 51 71 24 14 2 730 PublicationsFigure 3.56. Number of publications and EC projects in collaboration between EaP actors in different countries, in the ‘ICT and computer science’ domain Colour indicates the relative distribution of documents, computed row-wise. Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation215 Regional collaboration in Mechanical en- gineering and heavy machinery In terms of publications, there are very few collab- orations in the domain of Mechanical engineer- ing and heavy machinery. Most collaborations are with external partners. There are very few collaborations on EC projects.Regional collaboration in Nanotechnolo- gy and materials In the case of Nanotechnology and materials publications, external collaborations again have a significant weight throughout all six EaP countries. Within the EaP, some of the highest-intensity col- laborations are Armenia and Georgia. For all coun- tries, Ukraine is one of the most relevant partners. The number of EC project collaborations is again very low, with Ukraine having the highest number of collaborations with one another and across the EaP. AM AZ BY GE MD UA Other 1 1 1 1 4 EC projectsAM AZ BY GE MD UA Other AM 1 2 1 38 AZ 1 2 97 BY 2 2 1 18 189 GE 1 2 1 4 23 MD 1 1 4 61 UA 2 18 4 4 1 154 PublicationsFigure 3.57. Number of publications and EC projects in collaboration between EaP actors in different countries, in the ‘Mechanical engineering and heavy machinery’ domain Colour indicates the relative distribution of documents, computed row-wise. AM AZ BY GE MD UA Other 3 2 3 5 1 1 1 3 1 2 2 13 28 2 2 3 4

[ "880", "\n", "PublicationsFigure", "3.55", ".", "Number", "of", "publications", "and", "EC", "projects", "in", "collaboration", "between", "EaP", "actors", "in", "different", "countries", ",", "in", "the", "\n", "‘", "Health", "and", "wellbeing", "’", "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", "2", "9", "10", "10", "9", "14", "\n", "2", "2", "2", "2", "2", "2", "\n", "9", "2", "9", "8", "8", "16", "\n", "10", "2", "9", "10", "10", "17", "\n", "10", "2", "8", "10", "8", "18", "\n", "9", "2", "8", "10", "8", "32", "\n", "EC", "projectsAM", "\n", "AZ", "\n", "BY", "\n", "GE", "\n", "MD", "\n", "UA", "\n", "Other", "\n", "AM", "4", "19", "21", "5", "18", "189", "\n", "AZ", "4", "4", "5", "4", "51", "157", "\n", "BY", "19", "4", "18", "13", "71", "787", "\n", "GE", "21", "5", "18", "6", "24", "238", "\n", "MD", "5", "4", "13", "6", "14", "72", "\n", "UA", "18", "51", "71", "24", "14", "2", "730", "\n", "PublicationsFigure", "3.56", ".", "Number", "of", "publications", "and", "EC", "projects", "in", "collaboration", "between", "EaP", "actors", "in", "different", "countries", ",", "in", "the", "\n", "‘", "ICT", "and", "computer", "science", "’", "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", "cooperation215", "\n", "Regional", "collaboration", "in", "Mechanical", "en-", "\n", "gineering", "and", "heavy", "machinery", "\n", "In", "terms", "of", "publications", ",", "there", "are", "very", "few", "collab-", "\n", "orations", "in", "the", "domain", "of", "Mechanical", "engineer-", "\n", "ing", "and", "heavy", "machinery", ".", "Most", "collaborations", "\n", "are", "with", "external", "partners", ".", "\n", "There", "are", "very", "few", "collaborations", "on", "EC", "projects", ".", "Regional", "collaboration", "in", "Nanotechnolo-", "\n", "gy", "and", "materials", "\n", "In", "the", "case", "of", "Nanotechnology", "and", "materials", "\n", "publications", ",", "external", "collaborations", "again", "have", "a", "\n", "significant", "weight", "throughout", "all", "six", "EaP", "countries", ".", "\n", "Within", "the", "EaP", ",", "some", "of", "the", "highest", "-", "intensity", "col-", "\n", "laborations", "are", "Armenia", "and", "Georgia", ".", "For", "all", "coun-", "\n", "tries", ",", "Ukraine", "is", "one", "of", "the", "most", "relevant", "partners", ".", "\n", "The", "number", "of", "EC", "project", "collaborations", "is", "again", "\n", "very", "low", ",", "with", "Ukraine", "having", "the", "highest", "number", "of", "\n", "collaborations", "with", "one", "another", "and", "across", "the", "EaP.", "\n", "AM", "\n", "AZ", "\n", "BY", "\n", "GE", "\n", "MD", "\n", "UA", "\n", "Other", "\n", "1", "1", "\n", "1", "\n", "1", "4", "\n", "EC", "projectsAM", "\n", "AZ", "\n", "BY", "\n", "GE", "\n", "MD", "\n", "UA", "\n", "Other", "\n", "AM", "1", "2", "1", "38", "\n", "AZ", "1", "2", "97", "\n", "BY", "2", "2", "1", "18", "189", "\n", "GE", "1", "2", "1", "4", "23", "\n", "MD", "1", "1", "4", "61", "\n", "UA", "2", "18", "4", "4", "1", "154", "\n", "PublicationsFigure", "3.57", ".", "Number", "of", "publications", "and", "EC", "projects", "in", "collaboration", "between", "EaP", "actors", "in", "different", "countries", ",", "in", "the", "\n", "‘", "Mechanical", "engineering", "and", "heavy", "machinery", "’", "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", "3", "2", "3", "5", "\n", "1", "1", "1", "\n", "3", "1", "2", "2", "13", "28", "\n", "2", "2", "3", "4", "\n" ]

[]

oversaw the chemical 110 Negotiating in/visibility department of Baghdad’s largest department store, granted my request and ordered medicines from several Czechoslovak pharmaceutical factories. The surgery was not even finished yet, and already patients were coming in. Or their family members with requests for medical consultation.44 It is obvious that after the opening of the clinic in the spring of 1925, Vlasta Kálalová was quite busy with various arrangements for her apartment and office, so that she did not have much time to write letters, but the letters that have been preserved are an important source to understand her life there: ‘I just want to keep busy now. There’s not that much work yet. The average daily income just covers the expenses (which are quite considerable here, at least CZK150 a day), only the operations are a welcome plus.’45 In July 1925, the necessary surgical equipment arrived from Prague and in September, Ruth Tobolářová arrived in Baghdad. In October 1925, when Masaryk received a further report on the development of the Czech ‘enclave’, Vlasta already had her regular patients and an important assistant in the person of nurse Ruth Tobolářová and could therefore afford to rent a larger house in a better area of the town. She found a suitable house that was larger than the previous one and could also accommodate rooms for post- operative patients. The house was situated in the centre of the city and was easily accessible for her patients: I rented a spacious house (10 rooms on the first floor with a kitchen, cool rooms for summer and servants’ quarters on the ground floor) for Rs. 3000 per year. My house is still being repaired and we will be able to move in about a week. It will have, besides the consulting room, rooms for diathermy and a waiting room, quite a nice operating theatre and two large rooms for patients, which can accommodate 8– 10 beds, and a third room can be added later!46 The new house, known as the Burazanli House, was repaired during the autumn (she moved in on 7 November 1925) and adapted to the needs of a small clinic. On 15 December, by a decree of the Baghdad director of health, the activity of the ‘Czekoslovak Mustausaf’47 was authorized. ‘Mustausaf’ indicated, according to Kálalová, a dispensary or small private clinic, and was a general term used for a medical facility with

[ "oversaw", "the", "chemical", " \n \n \n \n \n \n \n", "110", "\n ", "Negotiating", "in", "/", "visibility", "\n", "department", "of", "Baghdad", "’s", "largest", "department", "store", ",", "granted", "my", "request", "and", "\n", "ordered", "medicines", "from", "several", "Czechoslovak", "pharmaceutical", "factories", ".", "The", "\n", "surgery", "was", "not", "even", "finished", "yet", ",", "and", "already", "patients", "were", "coming", "in", ".", "Or", "\n", "their", "family", "members", "with", "requests", "for", "medical", "consultation.44", "\n", "It", "is", "obvious", "that", "after", "the", "opening", "of", "the", "clinic", "in", "the", "spring", "of", "1925", ",", "Vlasta", "\n", "Kálalová", "was", "quite", "busy", "with", "various", "arrangements", "for", "her", "apartment", "and", "\n", "office", ",", "so", "that", "she", "did", "not", "have", "much", "time", "to", "write", "letters", ",", "but", "the", "letters", "that", "\n", "have", "been", "preserved", "are", "an", "important", "source", "to", "understand", "her", "life", "there", ":", "‘", "I", "\n", "just", "want", "to", "keep", "busy", "now", ".", "There", "’s", "not", "that", "much", "work", "yet", ".", "The", "average", "\n", "daily", "income", "just", "covers", "the", "expenses", "(", "which", "are", "quite", "considerable", "here", ",", "at", "\n", "least", "CZK150", "a", "day", ")", ",", "only", "the", "operations", "are", "a", "welcome", "plus", ".", "’45", "\n", "In", "July", "1925", ",", "the", "necessary", "surgical", "equipment", "arrived", "from", "Prague", "\n", "and", "in", "September", ",", "Ruth", "Tobolářová", "arrived", "in", "Baghdad", ".", "In", "October", "1925", ",", "\n", "when", "Masaryk", "received", "a", "further", "report", "on", "the", "development", "of", "the", "Czech", "\n", "‘", "enclave", "’", ",", "Vlasta", "already", "had", "her", "regular", "patients", "and", "an", "important", "assistant", "\n", "in", "the", "person", "of", "nurse", "Ruth", "Tobolářová", "and", "could", "therefore", "afford", "to", "rent", "\n", "a", "larger", "house", "in", "a", "better", "area", "of", "the", "town", ".", "She", "found", "a", "suitable", "house", "that", "\n", "was", "larger", "than", "the", "previous", "one", "and", "could", "also", "accommodate", "rooms", "for", "\n", "post-", " ", "operative", "patients", ".", "The", "house", "was", "situated", "in", "the", "centre", "of", "the", "city", "and", "\n", "was", "easily", "accessible", "for", "her", "patients", ":", "\n", "I", "rented", "a", "spacious", "house", "(", "10", "rooms", "on", "the", "first", "floor", "with", "a", "kitchen", ",", "cool", "\n", "rooms", "for", "summer", "and", "servants", "’", "quarters", "on", "the", "ground", "floor", ")", "for", "Rs", ".", "3000", "\n", "per", "year", ".", "My", "house", "is", "still", "being", "repaired", "and", "we", "will", "be", "able", "to", "move", "in", "about", "\n", "a", "week", ".", "It", "will", "have", ",", "besides", "the", "consulting", "room", ",", "rooms", "for", "diathermy", "and", "a", "\n", "waiting", "room", ",", "quite", "a", "nice", "operating", "theatre", "and", "two", "large", "rooms", "for", "patients", ",", "\n", "which", "can", "accommodate", "8", "–", " ", "10", "beds", ",", "and", "a", "third", "room", "can", "be", "added", "later!46", "\n", "The", "new", "house", ",", "known", "as", "the", "Burazanli", "House", ",", "was", "repaired", "during", "the", "\n", "autumn", "(", "she", "moved", "in", "on", "7", "November", "1925", ")", "and", "adapted", "to", "the", "needs", "\n", "of", "a", "small", "clinic", ".", "On", "15", "December", ",", "by", "a", "decree", "of", "the", "Baghdad", "director", "\n", "of", "health", ",", "the", "activity", "of", "the", "‘", "Czekoslovak", "Mustausaf’47", "was", "authorized", ".", "\n", "‘", "Mustausaf", "’", "indicated", ",", "according", "to", "Kálalová", ",", "a", "dispensary", "or", "small", "private", "\n", "clinic", ",", "and", "was", "a", "general", "term", "used", "for", "a", "medical", "facility", "with" ]

[ { "end": 354, "label": "CITATION_REF", "start": 352 }, { "end": 885, "label": "CITATION_REF", "start": 883 }, { "end": 1986, "label": "CITATION_REF", "start": 1984 }, { "end": 2252, "label": "CITATION_REF", "start": 2250 } ]

44 19 Environmental sciences and industries 1 331 614 710 623 368 383 263 253 172 188 Fundamental physics and mathematics 5 398 4 606 3 907 4 495 3 734 3 438 3 608 3 123 3 028 2 832 Governance, culture, education and the economy 903 438 687 675 279 453 240 211 146 155 Health and wellbeing 1 731 1 414 1 249 2 126 986 1 465 925 707 366 599 ICT and computer science 678 496 823 466 383 201 189 137 281 121 Mechanical engineering and heavy machinery 388 182 319 96 67 60 55 30 55 23 Nanotechnology and materials 4 197 2 452 2 526 1 568 1 202 649 435 461 523 283 Optics and photonics 1 054 573 372 483 300 200 147 182 211 57 Transportation 70 67 104 42 15 24 8 9 23 2 PublicationsGermany France United Kingdom Spain Italy Belgium Greece Netherlands Poland Romania Agrifood 12 14 7 14 14 11 9 13 5 8 Biotechnology 12 10 13 9 7 5 5 6 10 4 Chemistry and chemical engineering 9 5 5 4 4 4 3 3 3 3 Electric and electronic technologies 6 4 5 3 5 4 4 1 Energy 40 23 22 24 25 28 17 14 15 19 Environmental sciences and industries 51 42 36 42 41 36 26 31 23 28 Fundamental physics and mathematics 7 6 6 5 5 2 2 2 4 3 Governance, culture, education and the economy 138 115 99 106 109 93 83 76 77 71 Health and wellbeing 34 26 29 27 21 16 12 17 14 10 ICT and computer science 37 33 37 39 34 29 29 24 22 22 Mechanical engineering and heavy machinery 3 1 4 1 2 2 1 2 2 Nanotechnology and materials 33 23 29 18 20 13 12 5 11 3 Optics and photonics 10 8 7 3 6 2 4 Transportation 17 10 13 11 13 11 8 7 8 5 EC projectsFigure 3.61. Number of publications and EC projects in collaboration between EaP actors and partners outside of the EaP Colour indicates the relative distribution, computed row-wise. 218 Part 3 Analysis of scientific and technological potential Extra-EaP international collaboration This last section of the chapter presents indicators of collaboration activity between EaP countries and external international partners. The Russian Federation was so far the

[ "44", "19", "\n", "Environmental", "sciences", "and", "industries", "1", "331", "614", "710", "623", "368", "383", "263", "253", "172", "188", "\n", "Fundamental", "physics", "and", "mathematics", "5", "398", "4", "606", "3", "907", "4", "495", "3", "734", "3", "438", "3", "608", "3", "123", "3", "028", "2", "832", "\n", "Governance", ",", "culture", ",", "education", "and", "the", "economy", "903", "438", "687", "675", "279", "453", "240", "211", "146", "155", "\n", "Health", "and", "wellbeing", "1", "731", "1", "414", "1", "249", "2", "126", "986", "1", "465", "925", "707", "366", "599", "\n", "ICT", "and", "computer", "science", "678", "496", "823", "466", "383", "201", "189", "137", "281", "121", "\n", "Mechanical", "engineering", "and", "heavy", "machinery", "388", "182", "319", "96", "67", "60", "55", "30", "55", "23", "\n", "Nanotechnology", "and", "materials", "4", "197", "2", "452", "2", "526", "1", "568", "1", "202", "649", "435", "461", "523", "283", "\n", "Optics", "and", "photonics", "1", "054", "573", "372", "483", "300", "200", "147", "182", "211", "57", "\n", "Transportation", "70", "67", "104", "42", "15", "24", "8", "9", "23", "2", "\n", "PublicationsGermany", "\n", "France", "\n", "United", "\n", "Kingdom", "\n", "Spain", "\n", "Italy", "\n", "Belgium", "\n", "Greece", "\n", "Netherlands", "\n", "Poland", "\n", "Romania", "\n", "Agrifood", "12", "14", "7", "14", "14", "11", "9", "13", "5", "8", "\n", "Biotechnology", "12", "10", "13", "9", "7", "5", "5", "6", "10", "4", "\n", "Chemistry", "and", "chemical", "engineering", "9", "5", "5", "4", "4", "4", "3", "3", "3", "3", "\n", "Electric", "and", "electronic", "technologies", "6", "4", "5", "3", "5", "4", "4", "1", "\n", "Energy", "40", "23", "22", "24", "25", "28", "17", "14", "15", "19", "\n", "Environmental", "sciences", "and", "industries", "51", "42", "36", "42", "41", "36", "26", "31", "23", "28", "\n", "Fundamental", "physics", "and", "mathematics", "7", "6", "6", "5", "5", "2", "2", "2", "4", "3", "\n", "Governance", ",", "culture", ",", "education", "and", "the", "economy", "138", "115", "99", "106", "109", "93", "83", "76", "77", "71", "\n", "Health", "and", "wellbeing", "34", "26", "29", "27", "21", "16", "12", "17", "14", "10", "\n", "ICT", "and", "computer", "science", "37", "33", "37", "39", "34", "29", "29", "24", "22", "22", "\n", "Mechanical", "engineering", "and", "heavy", "machinery", "3", "1", "4", "1", "2", "2", "1", "2", "2", "\n", "Nanotechnology", "and", "materials", "33", "23", "29", "18", "20", "13", "12", "5", "11", "3", "\n", "Optics", "and", "photonics", "10", "8", "7", "3", "6", "2", "4", "\n", "Transportation", "17", "10", "13", "11", "13", "11", "8", "7", "8", "5", "\n", "EC", "projectsFigure", "3.61", ".", "Number", "of", "publications", "and", "EC", "projects", "in", "collaboration", "between", "EaP", "actors", "and", "partners", "outside", "of", "the", "\n", "EaP", "\n", "Colour", "indicates", "the", "relative", "distribution", ",", "computed", "row", "-", "wise", ".", "\n", "218", "\n ", "Part", "3", "Analysis", "of", "scientific", "and", "technological", "potential", "\n", "Extra", "-", "EaP", "international", "collaboration", "\n", "This", "last", "section", "of", "the", "chapter", "presents", "indicators", "\n", "of", "collaboration", "activity", "between", "EaP", "countries", "\n", "and", "external", "international", "partners", ".", "\n", "The", "Russian", "Federation", "was", "so", "far", "the" ]

[]

be used interchangeably. Additionally, although the term “ML algorithm” may refer to different concepts than the term “ML model,” these terms may be used interchangeably for the purposes of the present disclosure. The term “machine learning application” or “ML application” at least in some examples refers to an application, program, process, algorithm, and/or function that contains some AI/ML model(s) and application-level descriptions. Additionally or alternatively, the term “machine learning application” or “ML application” at least in some examples refers to a complete and deployable application and/or package that includes at least one ML model and/or other data capable of achieving a certain function and/or performing a set of actions or tasks in an operational environment. For purposes of the present disclosure, the terms “ML application”, “AI application”, “AI/ML application”, and the like may be used interchangeably. The term “matrix” at least in some examples refers to a rectangular array of numbers, symbols, or expressions, arranged in rows and columns, which may be used to represent an object or a property of such an object. The terms “model parameter” and/or “parameter” in the context of ML, at least in some examples refer to values, characteristics, and/or properties that are learnt during training. Additionally or alternatively, “model parameter” and/or “parameter” in the context of ML, at least in some examples refer to a configuration variable that is internal to the model and whose value can be estimated from the given data. Model parameters are usually required by a model when making predictions, and their values define the skill of the model on a particular problem. Examples of such model parameters/parameters include weights (e.g., in an ANN); constraints; support vectors in a support vector machine (SVM); coefficients in a linear regression and/or logistic regression; word frequency, sentence length, noun or verb distribution per sentence, the number of specific character n-grams per word, lexical diversity, and the like, for natural language processing (NLP) and/or natural language understanding (NLU); and/or the like. The term “objective function” at least in some examples refers to a function to be maximized or minimized for a specific optimization problem. In some cases, an objective function is defined by its decision variables and an objective. The objective is the value, target, or goal to be optimized, such as maximizing profit or minimizing usage of a particular resource. The specific objective function chosen depends on the specific problem to be solved

[ "be", "used", "interchangeably", ".", "Additionally", ",", "although", "the", "term", "“", "ML", "algorithm", "”", "may", "refer", "to", "different", "concepts", "than", "the", "term", "“", "ML", "model", ",", "”", "these", "terms", "may", "be", "used", "interchangeably", "for", "the", "purposes", "of", "the", "present", "disclosure", ".", "\n\n", "The", "term", "“", "machine", "learning", "application", "”", "or", "“", "ML", "application", "”", "at", "least", "in", "some", "examples", "refers", "to", "an", "application", ",", "program", ",", "process", ",", "algorithm", ",", "and/or", "function", "that", "contains", "some", "AI", "/", "ML", "model(s", ")", "and", "application", "-", "level", "descriptions", ".", "Additionally", "or", "alternatively", ",", "the", "term", "“", "machine", "learning", "application", "”", "or", "“", "ML", "application", "”", "at", "least", "in", "some", "examples", "refers", "to", "a", "complete", "and", "deployable", "application", "and/or", "package", "that", "includes", "at", "least", "one", "ML", "model", "and/or", "other", "data", "capable", "of", "achieving", "a", "certain", "function", "and/or", "performing", "a", "set", "of", "actions", "or", "tasks", "in", "an", "operational", "environment", ".", "For", "purposes", "of", "the", "present", "disclosure", ",", "the", "terms", "“", "ML", "application", "”", ",", "“", "AI", "application", "”", ",", "“", "AI", "/", "ML", "application", "”", ",", "and", "the", "like", "may", "be", "used", "interchangeably", ".", "\n\n", "The", "term", "“", "matrix", "”", "at", "least", "in", "some", "examples", "refers", "to", "a", "rectangular", "array", "of", "numbers", ",", "symbols", ",", "or", "expressions", ",", "arranged", "in", "rows", "and", "columns", ",", "which", "may", "be", "used", "to", "represent", "an", "object", "or", "a", "property", "of", "such", "an", "object", ".", "\n\n", "The", "terms", "“", "model", "parameter", "”", "and/or", "“", "parameter", "”", "in", "the", "context", "of", "ML", ",", "at", "least", "in", "some", "examples", "refer", "to", "values", ",", "characteristics", ",", "and/or", "properties", "that", "are", "learnt", "during", "training", ".", "Additionally", "or", "alternatively", ",", "“", "model", "parameter", "”", "and/or", "“", "parameter", "”", "in", "the", "context", "of", "ML", ",", "at", "least", "in", "some", "examples", "refer", "to", "a", "configuration", "variable", "that", "is", "internal", "to", "the", "model", "and", "whose", "value", "can", "be", "estimated", "from", "the", "given", "data", ".", "Model", "parameters", "are", "usually", "required", "by", "a", "model", "when", "making", "predictions", ",", "and", "their", "values", "define", "the", "skill", "of", "the", "model", "on", "a", "particular", "problem", ".", "Examples", "of", "such", "model", "parameters", "/", "parameters", "include", "weights", "(", "e.g.", ",", "in", "an", "ANN", ")", ";", "constraints", ";", "support", "vectors", "in", "a", "support", "vector", "machine", "(", "SVM", ")", ";", "coefficients", "in", "a", "linear", "regression", "and/or", "logistic", "regression", ";", "word", "frequency", ",", "sentence", "length", ",", "noun", "or", "verb", "distribution", "per", "sentence", ",", "the", "number", "of", "specific", "character", "n", "-", "grams", "per", "word", ",", "lexical", "diversity", ",", "and", "the", "like", ",", "for", "natural", "language", "processing", "(", "NLP", ")", "and/or", "natural", "language", "understanding", "(", "NLU", ")", ";", "and/or", "the", "like", ".", "\n\n", "The", "term", "“", "objective", "function", "”", "at", "least", "in", "some", "examples", "refers", "to", "a", "function", "to", "be", "maximized", "or", "minimized", "for", "a", "specific", "optimization", "problem", ".", "In", "some", "cases", ",", "an", "objective", "function", "is", "defined", "by", "its", "decision", "variables", "and", "an", "objective", ".", "The", "objective", "is", "the", "value", ",", "target", ",", "or", "goal", "to", "be", "optimized", ",", "such", "as", "maximizing", "profit", "or", "minimizing", "usage", "of", "a", "particular", "resource", ".", "The", "specific", "objective", "function", "chosen", "depends", "on", "the", "specific", "problem", "to", "be", "solved" ]

[]

and the Maison de la Culture, founded in 2017 , which protects and promotes Rundi literature. The Ministry also manages the operations of the National Library. With regard to schoolbooks, the materials used in basic and post-basic education are published by pedagogical offices operating through the Pedagogical Production Management (Régie de Production Pédagogique – RPP), which functions as a publishing house. The legal framework for the book sector is limited to Law No. 1/021 of December 30, 2005 on the protection of copyright and related rights. 4 PUBLIC POLICIES AND MEASURES There are no tax exemptions, reduced rates, or fiscal incentives applicable to the book and publishing sector, as confirmed by the national authority’s response to the survey. The Cultural Policy of Burundi, which dates back to 2007 and the update of which been expected since 2022, encourages the promotion of books, notably by recommending the creation of literary prizes to encourage writing.

[ "and", "the", "Maison", "de", "la", "Culture", ",", "founded", "in", "2017", ",", "which", "protects", "and", "promotes", "Rundi", "literature", ".", "The", "Ministry", "also", "manages", "the", "operations", "of", "the", "National", "Library", ".", "With", "regard", "to", "schoolbooks", ",", "the", "materials", "\n", "used", "in", "basic", "and", "post", "-", "basic", "education", "are", "published", "by", "pedagogical", "offices", "operating", "through", "the", "Pedagogical", "Production", "Management", "(", "Régie", "de", "Production", "Pédagogique", "–", "RPP", ")", ",", "which", "functions", "as", "a", "publishing", "house", ".", "\n", "The", "legal", "framework", "for", "the", "book", "\n", "sector", "is", "limited", "to", "Law", "No", ".", "1/021", "of", "December", "30", ",", "2005", "on", "the", "protection", "of", "copyright", "and", "related", "rights", ".", "\n", "4", "\n", "PUBLIC", "POLICIES", "AND", "MEASURES", "\n", "There", "are", "no", "tax", "exemptions", ",", "reduced", "rates", ",", "or", "fiscal", "incentives", "applicable", "to", "the", "book", "and", "publishing", "sector", ",", "as", "confirmed", "by", "the", "national", "authority", "’s", "response", "to", "the", "survey", ".", "The", "Cultural", "Policy", "of", "Burundi", ",", "which", "dates", "back", "to", "2007", "and", "the", "update", "of", "which", "been", "expected", "since", "2022", ",", "encourages", "the", "promotion", "of", "books", ",", "notably", "by", "recommending", "the", "creation", "of", "literary", "prizes", "to", "encourage", "writing", "." ]

[]

- 1. Fathallah F, Meyers J, Chapman L, Karsh B. Ergonomic industrial interventions: agriculture. Occupational Ergonomics Handbook. 2006. - 2. Rosecrance J, Rodgers G, Merlino L. Low back pain and musculoskeletal symptoms among Kansas farmers. Am J Ind Med. 2006;49(7):547 -56. - 3. Health and Safety Executive H. Self-reported work-related illness and workplace injuries in 2005. 2007. - 4. Osborne A, Blake C, Fullen BM, Meredith D, Phelan J, McNamara J, et al. Prevalence of musculoskeletal disorders - among farmers: a systematic review. Am J Ind Med. 2012;55:143 -58. - 5. Holmberg S, Stiernström E-L, Thelin A, Svärdsudd K. Musculoskeletal symptoms among farmers and non-farmers: a population-based study. Int J Occup Environ Health. 2002;8: 339 45. - - 6. Skovron ML, Szpalski M, Nordin M, Melot C, Cukier D. Sociocultural factors and back pain. A population-based study in Belgian adults. Spine (Phila Pa 1976). 1994;19(2):129 -37.7. - 7. Kolstrup CL. Work-related musculoskeletal discomfort of dairy farmers and employed workers. J Occup Med Toxicol. 2012; 7:23. - 8. Chapman L, Meyers J. Ergonomics and musculoskeletal injuries in agriculture: recognizing and preventing the industry s ' most widespread health and safety problem; 2001. - 9. Blondell J. Epidemiology of pesticide poisonings in the United States, with special reference to occupational cases. Occup Med. 1997;12(2):209 -20. - 10. Kirkhorn S, Greenlee RT, Reeser JC. The epidemiology of agriculture-related osteoarthritis and its impact on occupational disability. WMJ. 2003;102:38 -44. - 11. KOrean Statistical Information Service (KOSIS) [homepage on the Internet]: Statistics Korea; c2015 [cited 2015 March 22nd]. Available from: http://kosis.kr/statHtml/statHtml.do?orgId= 101&tblId=DT\_1IN0001\_32&conn\_path=I2. - 12. Lee KH, Koh SB, Kang D, Chung JJ, Kim HR, Kim IA, et al. Job stress and self-perceived fatigue in Korean farmers. Korean J Occup Environ Med. 2011;23:213 -24. - 13. Fairbank JC, Pynsent PB. The Oswestry Disability Index. Spine (Phila Pa 1976). 2000;25(22):2940 -52. - 14. Hwang HS, Kwon IS, Park BJ, Cho B, Yoon JL, Won CW. The validity and reliability of Korean frailty index. J Korean Geriatr Soc. 2010;14:191 -202. - 15. DY KOSaHAIP. Questionnaire for musculoskeletal symptoms. Guideline for evaluation of risk factors for musculoskeletal disorders. 2003:P.A 10-1. - 16. Jo MW, Yun SC, Lee SI. Estimating quality weights for EQ-5D health states with the time trade-off method in South Korea. Value Health. 2008;11:1186 -9. - 17. Jeong G. Handbook for safety management in agricultural work Gyeonggi-do. Rural Development Administration; 2003. - 18. Shealy CN. A review of dehydroepiandrosterone (DHEA). Integr Physiol Behav Sci. 1995;30:308 -13.

[ "-", "1", ".", "Fathallah", "F", ",", "Meyers", "J", ",", "Chapman", "L", ",", "Karsh", "B.", "Ergonomic", "industrial", "interventions", ":", "agriculture", ".", "Occupational", "Ergonomics", "Handbook", ".", "2006", ".", "\n", "-", "2", ".", "Rosecrance", "J", ",", "Rodgers", "G", ",", "Merlino", "L.", "Low", "back", "pain", "and", "musculoskeletal", "symptoms", "among", "Kansas", "farmers", ".", "Am", "J", "Ind", "Med", ".", "2006;49(7):547", "-56", ".", "\n", "-", "3", ".", "Health", "and", "Safety", "Executive", "H.", "Self", "-", "reported", "work", "-", "related", "illness", "and", "workplace", "injuries", "in", "2005", ".", "2007", ".", "\n", "-", "4", ".", "Osborne", "A", ",", "Blake", "C", ",", "Fullen", "BM", ",", "Meredith", "D", ",", "Phelan", "J", ",", "McNamara", "J", ",", "et", "al", ".", "Prevalence", "of", "musculoskeletal", "disorders", "\n", "-", "among", "farmers", ":", "a", "systematic", "review", ".", "Am", "J", "Ind", "Med", ".", "2012;55:143", "-58", ".", "\n", "-", "5", ".", "Holmberg", "S", ",", "Stiernström", "E", "-", "L", ",", "Thelin", "A", ",", "Svärdsudd", "K.", "Musculoskeletal", "symptoms", "among", "farmers", "and", "non", "-", "farmers", ":", "a", "population", "-", "based", "study", ".", "Int", "J", "Occup", "Environ", "Health", ".", "2002;8", ":", "339", "45", ".", "-", "\n", "-", "6", ".", "Skovron", "ML", ",", "Szpalski", "M", ",", "Nordin", "M", ",", "Melot", "C", ",", "Cukier", "D.", "Sociocultural", "factors", "and", "back", "pain", ".", "A", "population", "-", "based", "study", "in", "Belgian", "adults", ".", "Spine", "(", "Phila", "Pa", "1976", ")", ".", "1994;19(2):129", "-37.7", ".", "\n", "-", "7", ".", "Kolstrup", "CL", ".", "Work", "-", "related", "musculoskeletal", "discomfort", "of", "dairy", "farmers", "and", "employed", "workers", ".", "J", "Occup", "Med", "Toxicol", ".", "2012", ";", "7:23", ".", "\n", "-", "8", ".", "Chapman", "L", ",", "Meyers", "J.", "Ergonomics", "and", "musculoskeletal", "injuries", "in", "agriculture", ":", "recognizing", "and", "preventing", "the", "industry", "s", "'", "most", "widespread", "health", "and", "safety", "problem", ";", "2001", ".", "\n", "-", "9", ".", "Blondell", "J.", "Epidemiology", "of", "pesticide", "poisonings", "in", "the", "United", "States", ",", "with", "special", "reference", "to", "occupational", "cases", ".", "Occup", "Med", ".", "1997;12(2):209", "-20", ".", "\n", "-", "10", ".", "Kirkhorn", "S", ",", "Greenlee", "RT", ",", "Reeser", "JC", ".", "The", "epidemiology", "of", "agriculture", "-", "related", "osteoarthritis", "and", "its", "impact", "on", "occupational", "disability", ".", "WMJ", ".", "2003;102:38", "-44", ".", "\n", "-", "11", ".", "KOrean", "Statistical", "Information", "Service", "(", "KOSIS", ")", "[", "homepage", "on", "the", "Internet", "]", ":", "Statistics", "Korea", ";", "c2015", "[", "cited", "2015", "March", "22nd", "]", ".", "Available", "from", ":", "http://kosis.kr/statHtml/statHtml.do?orgId=", "101&tblId", "=", "DT\\_1IN0001\\_32&conn\\_path", "=", "I2", ".", "\n", "-", "12", ".", "Lee", "KH", ",", "Koh", "SB", ",", "Kang", "D", ",", "Chung", "JJ", ",", "Kim", "HR", ",", "Kim", "IA", ",", "et", "al", ".", "Job", "stress", "and", "self", "-", "perceived", "fatigue", "in", "Korean", "farmers", ".", "Korean", "J", "Occup", "Environ", "Med", ".", "2011;23:213", "-24", ".", "\n", "-", "13", ".", "Fairbank", "JC", ",", "Pynsent", "PB", ".", "The", "Oswestry", "Disability", "Index", ".", "Spine", "(", "Phila", "Pa", "1976", ")", ".", "2000;25(22):2940", "-52", ".", "\n", "-", "14", ".", "Hwang", "HS", ",", "Kwon", "IS", ",", "Park", "BJ", ",", "Cho", "B", ",", "Yoon", "JL", ",", "Won", "CW", ".", "The", "validity", "and", "reliability", "of", "Korean", "frailty", "index", ".", "J", "Korean", "Geriatr", "Soc", ".", "2010;14:191", "-202", ".", "\n", "-", "15", ".", "DY", "KOSaHAIP", ".", "Questionnaire", "for", "musculoskeletal", "symptoms", ".", "Guideline", "for", "evaluation", "of", "risk", "factors", "for", "musculoskeletal", "disorders", ".", "2003", ":", "P.A", "10", "-", "1", ".", "\n", "-", "16", ".", "Jo", "MW", ",", "Yun", "SC", ",", "Lee", "SI", ".", "Estimating", "quality", "weights", "for", "EQ-5D", "health", "states", "with", "the", "time", "trade", "-", "off", "method", "in", "South", "Korea", ".", "Value", "Health", ".", "2008;11:1186", "-9", ".", "\n", "-", "17", ".", "Jeong", "G.", "Handbook", "for", "safety", "management", "in", "agricultural", "work", "Gyeonggi", "-", "do", ".", "Rural", "Development", "Administration", ";", "2003", ".", "\n", "-", "18", ".", "Shealy", "CN", ".", "A", "review", "of", "dehydroepiandrosterone", "(", "DHEA", ")", ".", "Integr", "Physiol", "Behav", "Sci", ".", "1995;30:308", "-13", ".", "\n" ]

[ { "end": 3, "label": "CITATION_ID", "start": 2 }, { "end": 136, "label": "CITATION_SPAN", "start": 5 }, { "end": 140, "label": "CITATION_ID", "start": 139 }, { "end": 276, "label": "CITATION_SPAN", "start": 142 }, { "end": 280, "label": "CITATION_ID", "start": 279 }, { "end": 385, "label": "CITATION_SPAN", "start": 282 }, { "end": 389, "label": "CITATION_ID", "start": 388 }, { "end": 571, "label": "CITATION_SPAN", "start": 391 }, { "end": 575, "label": "CITATION_ID", "start": 574 }, { "end": 756, "label": "CITATION_SPAN", "start": 577 }, { "end": 760, "label": "CITATION_ID", "start": 759 }, { "end": 940, "label": "CITATION_SPAN", "start": 762 }, { "end": 944, "label": "CITATION_ID", "start": 943 }, { "end": 1070, "label": "CITATION_SPAN", "start": 946 }, { "end": 1074, "label": "CITATION_ID", "start": 1073 }, { "end": 1245, "label": "CITATION_SPAN", "start": 1076 }, { "end": 1249, "label": "CITATION_ID", "start": 1248 }, { "end": 1398, "label": "CITATION_SPAN", "start": 1251 }, { "end": 1403, "label": "CITATION_ID", "start": 1401 }, { "end": 1560, "label": "CITATION_SPAN", "start": 1405 }, { "end": 1565, "label": "CITATION_ID", "start": 1563 }, { "end": 1804, "label": "CITATION_ID", "start": 1802 }, { "end": 1969, "label": "CITATION_ID", "start": 1967 }, { "end": 2076, "label": "CITATION_ID", "start": 2074 }, { "end": 2228, "label": "CITATION_ID", "start": 2226 }, { "end": 2378, "label": "CITATION_ID", "start": 2376 }, { "end": 2536, "label": "CITATION_ID", "start": 2534 }, { "end": 2657, "label": "CITATION_ID", "start": 2654 }, { "end": 2754, "label": "CITATION_SPAN", "start": 2658 }, { "end": 2651, "label": "CITATION_SPAN", "start": 2538 }, { "end": 2531, "label": "CITATION_SPAN", "start": 2380 }, { "end": 2373, "label": "CITATION_SPAN", "start": 2230 }, { "end": 2223, "label": "CITATION_SPAN", "start": 2078 }, { "end": 2071, "label": "CITATION_SPAN", "start": 1971 }, { "end": 1964, "label": "CITATION_SPAN", "start": 1806 }, { "end": 1799, "label": "CITATION_SPAN", "start": 1567 } ]

teachers and had also been granted tenure around the same year. As those moments were almost simultaneous, one can conclude that age or generational traits did not have a significant impact on the opportunities that the new law opened for female doctors. Their professional paths seemed to have depended entirely on the financial capacity of the public school administration to accommodate them. ## Eliza Ștefănescu Eliza Ștefănescu was born in 1882 and studied medicine in Bucharest, obtaining her medical diploma in 1907. 61 In 1929, she was appointed school doctor at the Elena Doamna Normal School in Bucharest, and was paid a daily wage, along with other female physicians recently designated as school doctors at different girls' high schools in the city. 62 However, she was able to pass the special inspection that allowed her to get tenure only in 1934. By then, she had transferred to the Central School Marica Brâncoveanu, one of the most prestigious and oldest high schools for girls in Bucharest. According to the principal's recommendation, Eliza Ștefănescu had been appointed temporary school doctor in 1931; she was serving as both the boarding school's physician and hygiene teacher. Highly competent, with 1 6 3 a spotless reputation and genuinely interested in the well- being of her students, she was willing to pay medical visits at school outside her schedule. Having a good working relationship with all her colleagues and being a respected doctor, she was praised by the principal, who highly recommended her for tenure. Similar appreciation expressed the inspector who assisted her seventh- grade hygiene course on alcoholism and smoking, valuing her ability to relate and explain the lesson to make it intelligible to her teenage students: 'I too, along with her students, have listened with great pleasure and interest to the recommendations the doctor has made … to keep ourselves healthy.' Based on his report, there is no doubt that the inspector was truly impressed with doctor Ștefănescu s class activity and considered her worthy ʼ of getting tenure. 63 According to the doctor's 1941 yearbook, during the war she retained her teaching position and was still working as a physician at the Central School. However, seven years later, her name was missing from the medical catalogue published in 1948, a clear sign that she had passed away, since even the retired doctors were included in the volume. 64 ## Victoria Vasiliu The second

[ "teachers", "and", "had", "also", "been", "granted", "tenure", "around", "the", "same", "year", ".", "As", "those", "moments", "were", "almost", "simultaneous", ",", "one", "can", "conclude", "that", "age", "or", "generational", "traits", "did", "not", "have", "a", "significant", "impact", "on", "the", "opportunities", "that", "the", "new", "law", "opened", "for", "female", "doctors", ".", "Their", "professional", "paths", "seemed", "to", "have", "depended", "entirely", "on", "the", "financial", "capacity", "of", "the", "public", "school", "administration", "to", "accommodate", "them", ".", "\n\n", "#", "#", "Eliza", "Ștefănescu", "\n\n", "Eliza", " ", "Ștefănescu", " ", "was", " ", "born", " ", "in", " ", "1882", " ", "and", " ", "studied", " ", "medicine", " ", "in", " ", "Bucharest", ",", "obtaining", "her", "medical", "diploma", "in", "1907", ".", "61", " ", "In", "1929", ",", "she", "was", "appointed", "school", "doctor", "at", "the", "Elena", "Doamna", "Normal", "School", "in", "Bucharest", ",", "and", "was", "paid", "a", "daily", "wage", ",", "along", "with", "other", "female", "physicians", "recently", "designated", "as", "school", "doctors", "at", "different", "girls", "'", "high", "schools", "in", "the", "city", ".", "62", " ", "However", ",", "she", "was", "able", "to", "pass", "the", "special", "inspection", "that", "allowed", "her", "to", "get", "tenure", "only", "in", "1934", ".", "By", "then", ",", "she", "had", "transferred", "to", "the", "Central", "School", "Marica", "Brâncoveanu", ",", "one", "of", "the", "most", "prestigious", "and", "oldest", "high", "schools", "for", "girls", "in", "Bucharest", ".", "\n\n", "According", "to", "the", "principal", "'s", "recommendation", ",", "Eliza", "Ștefănescu", "had", "been", "appointed", "temporary", "school", "doctor", "in", "1931", ";", "she", "was", "serving", "as", "both", "the", "boarding", "school", "'s", "physician", "and", "hygiene", "teacher", ".", "Highly", "competent", ",", "with", "\n\n", "1", "\n\n", "6", "\n\n", "3", "\n\n", "a", "spotless", "reputation", "and", "genuinely", "interested", "in", "the", "well-", " ", "being", "of", "her", "students", ",", "she", "was", "willing", "to", "pay", "medical", "visits", "at", "school", "outside", "her", "schedule", ".", "Having", "a", "good", "working", "relationship", "with", "all", "her", "colleagues", "and", "being", "a", "respected", "doctor", ",", "she", "was", "praised", "by", "the", "principal", ",", "who", "highly", "recommended", "her", "for", "tenure", ".", "Similar", "appreciation", "expressed", "the", "inspector", "who", "assisted", "her", "seventh-", " ", "grade", "hygiene", "course", "on", "alcoholism", "and", "smoking", ",", "valuing", "her", "ability", "to", "relate", "and", "explain", "the", "lesson", "to", "make", "it", "intelligible", "to", "her", "teenage", "students", ":", "'", "I", "too", ",", "along", "with", "her", "students", ",", "have", "listened", "with", "great", "pleasure", "and", "interest", "to", "the", "recommendations", "the", "doctor", "has", "made", "…", "to", "keep", "ourselves", "healthy", ".", "'", "Based", "on", "his", "report", ",", "there", "is", "no", "doubt", "that", "the", "inspector", "was", "truly", "impressed", "with", "doctor", "Ștefănescu", "s", "class", "activity", "and", "considered", "her", "worthy", "ʼ", "of", "getting", "tenure", ".", "63", "\n\n", "According", "to", "the", "doctor", "'s", "1941", "yearbook", ",", "during", "the", "war", "she", "retained", "her", "teaching", "position", "and", "was", "still", "working", "as", "a", "physician", "at", "the", "Central", "School", ".", "However", ",", "seven", "years", "later", ",", "her", "name", "was", "missing", "from", "the", "medical", "catalogue", "published", "in", "1948", ",", "a", "clear", "sign", "that", "she", "had", "passed", "away", ",", "since", "even", "the", "retired", "doctors", "were", "included", "in", "the", "volume", ".", "64", "\n\n", "#", "#", "Victoria", "Vasiliu", "\n\n", "The", "second" ]

[ { "end": 538, "label": "CITATION_REF", "start": 536 }, { "end": 777, "label": "CITATION_REF", "start": 775 }, { "end": 2107, "label": "CITATION_REF", "start": 2105 }, { "end": 2456, "label": "CITATION_REF", "start": 2454 } ]

Carroll, J. M., O'Connor, R. E., & McDonald, C. A. (2004). Educational implications of reading achievement gaps: A study of students in the United States. Reading Research Quarterly, 39 (2), 164 -182. https://doi.org/10.1598/RRQ.39.2.3 Carter, E. (2008). Successful change requires more than change management. The Journal for Quality & Participation , 31 (1), 20 -23. Carter, P. L., & Welner, K. G. (2013). Closing the achievement gap: A synthesis of the literature on the role of schools in closing the achievement gap. In Handbook of educational policy research (pp. 2 -5, 74). Springer. Chetty, R., Friedman, J. N., & Rockoff, J. E. (2020). Measuring the impacts of teachers II: Teacher value-added and student outcomes in adulthood. American Economic Review , 104 (9), 2633 -2679. https://doi.org/10.1257/aer.104.9.2633 Chetty, R., Hendren, N., Kline, P., & Saez, E. (2020). The opportunity atlas: Mapping the childhood roots of social mobility. Quarterly Journal of Economics , 135 (4), 1593 -1640. https://doi.org/10.1093/qje/qjaa009 Chiu, T. K. F. (2016). Introducing electronic textbooks as daily-use technology in schools: A top-down adoption process. British Journal of Educational Technology , 47 (5), 1004 -1017. Chiu, T. K. F. (2021). Student engagement in K-12 online learning amid COVID-19. International Journal of Educational Technology in Higher Education , 18 (1). Cohodes, S. R. (2018). The effects of school accountability on student achievement and behavior: Evidence from New York City high schools. Journal of Policy Analysis and Management 37 , (3), 572 -603. https://doi.org/10.1002/pam.22070 Côté, S., Stellar, J. E., Willer, R., Forbes, R. C., Martin, S. R., & Bianchi, E. C. (2021). The psychology of entrenched privilege: High socioeconomic status individuals from affluent backgrounds are uniquely high in entitlement. Personality and Social Psychology Bulletin , 47 (1), 70 -88. https://doi.org/10.1177/0146167220916633 Creswell, J. W. (2003). Research design: Qualitative, quantitative, and mixed methods approaches (2nd ed.). Sage. Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches . Sage. Creswell, J., & Plano Clark, V. L. (2011). Designing and conducting mixed methods research (2nd ed.). Sage. Creswell, J., & Poth, C. (2018). Qualitative inquiry and research design: Choosing among five approaches (4th ed.). Sage. Darling-Hammond, L. (1998). Unequal opportunity: race and education from https://www.brookings.edu/articles/unequal-opportunity-race-and-education/ Darling-Hammond, L. (2010). equity will determine our future . Teachers College Press. . Brookings. Retrieved The flat world and education: How America's commitment to Davis-Kean, P. E. (2005). The influence of parent education and family income on child achievement: The indirect role of parental expectations and the home environment. Journal of Family Psychology, 19 (2), 294 -304. https://doi.org/10.1037/0893- 3200.19.2.294

[ "Carroll", ",", "J.", "M.", ",", "O'Connor", ",", "R.", "E.", ",", "&", "amp", ";", "McDonald", ",", "C.", "A.", "(", "2004", ")", ".", "Educational", "implications", "of", "reading", "achievement", "gaps", ":", "A", "study", "of", "students", "in", "the", "United", "States", ".", "Reading", "Research", "Quarterly", ",", "39", "(", "2", ")", ",", "164", "-182", ".", "https://doi.org/10.1598/RRQ.39.2.3", "\n\n", "Carter", ",", "E.", "(", "2008", ")", ".", "Successful", "change", "requires", "more", "than", "change", "management", ".", "The", "Journal", "for", "Quality", "&", "amp", ";", "Participation", ",", "31", "(", "1", ")", ",", "20", "-23", ".", "\n\n", "Carter", ",", "P.", "L.", ",", "&", "amp", ";", "Welner", ",", "K.", "G.", "(", "2013", ")", ".", "Closing", "the", "achievement", "gap", ":", "A", "synthesis", "of", "the", "literature", "on", "the", "role", "of", "schools", "in", "closing", "the", "achievement", "gap", ".", "In", "Handbook", "of", "educational", "policy", "research", "(", "pp", ".", "2", "-5", ",", "74", ")", ".", "Springer", ".", "\n\n", "Chetty", ",", "R.", ",", "Friedman", ",", "J.", "N.", ",", "&", "amp", ";", "Rockoff", ",", "J.", "E.", "(", "2020", ")", ".", "Measuring", "the", "impacts", "of", "teachers", "II", ":", "Teacher", "value", "-", "added", "and", "student", "outcomes", "in", "adulthood", ".", "American", "Economic", "Review", ",", "104", "(", "9", ")", ",", "2633", "-2679", ".", "https://doi.org/10.1257/aer.104.9.2633", "\n\n", "Chetty", ",", "R.", ",", "Hendren", ",", "N.", ",", "Kline", ",", "P.", ",", "&", "amp", ";", "Saez", ",", "E.", "(", "2020", ")", ".", "The", "opportunity", "atlas", ":", "Mapping", "the", "childhood", "roots", "of", "social", "mobility", ".", "Quarterly", "Journal", "of", "Economics", ",", "135", "(", "4", ")", ",", "1593", "-1640", ".", "https://doi.org/10.1093/qje/qjaa009", "\n\n", "Chiu", ",", "T.", "K.", "F.", "(", "2016", ")", ".", "Introducing", "electronic", "textbooks", "as", "daily", "-", "use", "technology", "in", "schools", ":", "A", "top", "-", "down", "adoption", "process", ".", "British", "Journal", "of", "Educational", "Technology", ",", "47", "(", "5", ")", ",", "1004", "-1017", ".", "\n\n", "Chiu", ",", "T.", "K.", "F.", "(", "2021", ")", ".", "Student", "engagement", "in", "K-12", "online", "learning", "amid", "COVID-19", ".", "\n\n", "International", "Journal", "of", "Educational", "Technology", "in", "Higher", "Education", ",", "18", "(", "1", ")", ".", "Cohodes", ",", "S.", "R.", "(", "2018", ")", ".", "The", "effects", "of", "school", "accountability", "on", "student", "achievement", "and", "behavior", ":", "Evidence", "from", "New", "York", "City", "high", "schools", ".", "Journal", "of", "Policy", "Analysis", "and", "Management", "37", ",", "(", "3", ")", ",", "572", "-603", ".", "https://doi.org/10.1002/pam.22070", "\n\n", "Côté", ",", "S.", ",", "Stellar", ",", "J.", "E.", ",", "Willer", ",", "R.", ",", "Forbes", ",", "R.", "C.", ",", "Martin", ",", "S.", "R.", ",", "&", "amp", ";", "Bianchi", ",", "E.", "C.", "(", "2021", ")", ".", "The", "psychology", "of", "entrenched", "privilege", ":", "High", "socioeconomic", "status", "individuals", "from", "affluent", "backgrounds", "are", "uniquely", "high", "in", "entitlement", ".", "Personality", "and", "Social", "Psychology", "Bulletin", ",", "47", "(", "1", ")", ",", "70", "-88", ".", "https://doi.org/10.1177/0146167220916633", "\n\n", "Creswell", ",", "J.", "W.", "(", "2003", ")", ".", "Research", "design", ":", "Qualitative", ",", "quantitative", ",", "and", "mixed", "methods", "approaches", "(", "2nd", "ed", ".", ")", ".", "Sage", ".", "\n\n", "Creswell", ",", "J.", "W.", "(", "2009", ")", ".", "Research", "design", ":", "Qualitative", ",", "quantitative", ",", "and", "mixed", "methods", "approaches", ".", "Sage", ".", "\n\n", "Creswell", ",", "J.", ",", "&", "amp", ";", "Plano", "Clark", ",", "V.", "L.", "(", "2011", ")", ".", "Designing", "and", "conducting", "mixed", "methods", "research", "(", "2nd", "ed", ".", ")", ".", "Sage", ".", "\n\n", "Creswell", ",", "J.", ",", "&", "amp", ";", "Poth", ",", "C.", "(", "2018", ")", ".", "Qualitative", "inquiry", "and", "research", "design", ":", "Choosing", "among", "five", "approaches", "(", "4th", "ed", ".", ")", ".", "Sage", ".", "\n\n", "Darling", "-", "Hammond", ",", "L.", "(", "1998", ")", ".", "Unequal", "opportunity", ":", "race", "and", "education", "from", "https://www.brookings.edu/articles/unequal-opportunity-race-and-education/", "\n\n", "Darling", "-", "Hammond", ",", "L.", "(", "2010", ")", ".", "equity", "will", "determine", "our", "future", ".", "Teachers", "College", "Press", ".", "\n\n", ".", "Brookings", ".", "Retrieved", "The", "flat", "world", "and", "education", ":", "How", "America", "'s", "commitment", "to", "\n\n", "Davis", "-", "Kean", ",", "P.", "E.", "(", "2005", ")", ".", "The", "influence", "of", "parent", "education", "and", "family", "income", "on", "child", "achievement", ":", "The", "indirect", "role", "of", "parental", "expectations", "and", "the", "home", "environment", ".", "Journal", "of", "Family", "Psychology", ",", "19", "(", "2", ")", ",", "294", "-304", ".", "https://doi.org/10.1037/0893-", "\n\n", "3200.19.2.294", "\n\n" ]

[ { "end": 239, "label": "CITATION_SPAN", "start": 0 }, { "end": 377, "label": "CITATION_SPAN", "start": 241 }, { "end": 604, "label": "CITATION_SPAN", "start": 379 }, { "end": 843, "label": "CITATION_SPAN", "start": 606 }, { "end": 1064, "label": "CITATION_SPAN", "start": 845 }, { "end": 1250, "label": "CITATION_SPAN", "start": 1066 }, { "end": 1646, "label": "CITATION_SPAN", "start": 1252 }, { "end": 1984, "label": "CITATION_SPAN", "start": 1648 }, { "end": 2099, "label": "CITATION_SPAN", "start": 1986 }, { "end": 2205, "label": "CITATION_SPAN", "start": 2101 }, { "end": 2318, "label": "CITATION_SPAN", "start": 2207 }, { "end": 2445, "label": "CITATION_SPAN", "start": 2320 }, { "end": 2594, "label": "CITATION_SPAN", "start": 2447 }, { "end": 2764, "label": "CITATION_SPAN", "start": 2596 }, { "end": 3027, "label": "CITATION_SPAN", "start": 2766 } ]

Nepal | 9 | 12 | Mozambique | 5 | 17.4 | | France | Unspecified by region | 109 | 15 | Lebanon | 24 | 16.4 | | | Morocco | 56 | 8 | Niger | 10 | 7.0 | | | | | | | | 5.8 | | Germany | Wallis and Futuna Unspecified by region | 50 314 | 7 23 | Unspecified by region Jordan | 8 47 | 16.5 | | | China | 116 | 8 | Lebanon | 33 | 11.7 | | | Jordan | 114 | 8 | Türkiye | 27 | 9.5 85.6 | | Hungary | Jordan | 10 | 8 | Ukraine | 2 | | | | Syrian Arab Republic | 9 | 7 | Serbia | 0 0 | 4.8 3.8 | | | China Unspecified by region | 5 14 | 4 | Lebanon | 10 | 45.0 | | Ireland | | 5 | 17 13 | Unspecified by region | | | | | Mozambique | | | Mozambique | 5 | | | | State of Palestine | 4 | 11 | | | | | Israel | | | | | | 22.6 | | | India | 11 | 49 | Uganda | 1 | 4.3 | | | | 4 | | | | | | Italy | China Ukraine Ukraine | 2 71 | 17 8 31 | Jordan | 13 2 | 43.7 | | | Unspecified by region Jordan | 27 14 | 12 6 | Senegal Lebanon | 2 | 7.2 6.3 | | Japan | Unspecified by region Morocco | 154 | 29 | Morocco Burkina Faso | 34 7 | 33.4 | | | India | 36 | 7 | | | 7.4 | | Kuwait | Jordan | 30 | 6 | Syrian Arab Republic | 7 | 6.6 | | | | 9 | 31 20 | | | | | | China | 6 | | | | | | | | 4 | 14 | | | | | Netherlands | Ghana Unspecified by region | 79 | 88 | Unspecified by region Burkina Faso | 31 2 | 90.3 6.0 | | New Zealand | Burkina Faso Ethiopia | 3 1 | 4 1 | Burundi Timor-Leste | 1 3 | 3.2 | | |

[ "Nepal", " ", "|", "9", " ", "|", "12", " ", "|", "Mozambique", " ", "|", "5", " ", "|", "17.4", " ", "|", "\n", "|", "France", " ", "|", "Unspecified", "by", "region", " ", "|", "109", " ", "|", "15", " ", "|", "Lebanon", " ", "|", "24", " ", "|", "16.4", " ", "|", "\n", "|", " ", "|", "Morocco", " ", "|", "56", " ", "|", "8", " ", "|", "Niger", " ", "|", "10", " ", "|", "7.0", " ", "|", "\n", "|", " ", "|", " ", "|", " ", "|", " ", "|", " ", "|", " ", "|", "5.8", " ", "|", "\n", "|", "Germany", " ", "|", "Wallis", "and", "Futuna", "Unspecified", "by", "region", " ", "|", "50", "314", " ", "|", "7", "23", " ", "|", "Unspecified", "by", "region", "Jordan", " ", "|", "8", "47", " ", "|", "16.5", " ", "|", "\n", "|", " ", "|", "China", " ", "|", "116", " ", "|", "8", " ", "|", "Lebanon", " ", "|", "33", " ", "|", "11.7", " ", "|", "\n", "|", " ", "|", "Jordan", " ", "|", "114", " ", "|", "8", " ", "|", "Türkiye", " ", "|", "27", " ", "|", "9.5", "85.6", " ", "|", "\n", "|", "Hungary", " ", "|", "Jordan", " ", "|", "10", " ", "|", "8", " ", "|", "Ukraine", " ", "|", "2", " ", "|", " ", "|", "\n", "|", " ", "|", "Syrian", "Arab", "Republic", " ", "|", "9", " ", "|", "7", " ", "|", "Serbia", " ", "|", "0", "0", " ", "|", "4.8", "3.8", " ", "|", "\n", "|", " ", "|", "China", "Unspecified", "by", "region", " ", "|", "5", "14", " ", "|", "4", " ", "|", "Lebanon", " ", "|", "10", " ", "|", "45.0", " ", "|", "\n", "|", "Ireland", " ", "|", " ", "|", "5", " ", "|", "17", "13", " ", "|", "Unspecified", "by", "region", " ", "|", " ", "|", " ", "|", "\n", "|", " ", "|", "Mozambique", " ", "|", " ", "|", " ", "|", "Mozambique", " ", "|", "5", " ", "|", " ", "|", "\n", "|", " ", "|", "State", "of", "Palestine", " ", "|", "4", " ", "|", "11", " ", "|", " ", "|", " ", "|", " ", "|", "\n", "|", "Israel", " ", "|", " ", "|", " ", "|", " ", "|", " ", "|", " ", "|", "22.6", " ", "|", "\n", "|", " ", "|", "India", " ", "|", "11", " ", "|", "49", " ", "|", "Uganda", " ", "|", "1", " ", "|", "4.3", " ", "|", "\n", "|", " ", "|", " ", "|", "4", " ", "|", " ", "|", " ", "|", " ", "|", " ", "|", "\n", "|", "Italy", " ", "|", "China", "Ukraine", "Ukraine", " ", "|", "2", "71", " ", "|", "17", "8", "31", " ", "|", "Jordan", " ", "|", "13", "2", " ", "|", "43.7", " ", "|", "\n", "|", " ", "|", "Unspecified", "by", "region", "Jordan", " ", "|", "27", "14", " ", "|", "12", "6", " ", "|", "Senegal", "Lebanon", " ", "|", "2", " ", "|", "7.2", "6.3", " ", "|", "\n", "|", "Japan", " ", "|", "Unspecified", "by", "region", "Morocco", " ", "|", "154", " ", "|", "29", " ", "|", "Morocco", "Burkina", "Faso", " ", "|", "34", "7", " ", "|", "33.4", " ", "|", "\n", "|", " ", "|", "India", " ", "|", "36", " ", "|", "7", " ", "|", " ", "|", " ", "|", "7.4", " ", "|", "\n", "|", "Kuwait", " ", "|", "Jordan", " ", "|", "30", " ", "|", "6", " ", "|", "Syrian", "Arab", "Republic", " ", "|", "7", " ", "|", "6.6", " ", "|", "\n", "|", " ", "|", " ", "|", "9", " ", "|", "31", "20", " ", "|", " ", "|", " ", "|", " ", "|", "\n", "|", " ", "|", "China", " ", "|", "6", " ", "|", " ", "|", " ", "|", " ", "|", " ", "|", "\n", "|", " ", "|", " ", "|", "4", " ", "|", "14", " ", "|", " ", "|", " ", "|", " ", "|", "\n", "|", "Netherlands", "|", "Ghana", "Unspecified", "by", "region", " ", "|", "79", " ", "|", "88", " ", "|", "Unspecified", "by", "region", "Burkina", "Faso", " ", "|", "31", "2", " ", "|", "90.3", "6.0", " ", "|", "\n", "|", "New", "Zealand", "|", "Burkina", "Faso", "Ethiopia", " ", "|", "3", "1", " ", "|", "4", "1", " ", "|", "Burundi", "Timor", "-", "Leste", " ", "|", "1", "3", " ", "|", "3.2", " ", "|", "\n", "|", " ", "|" ]

[]

Q 8.47889E-01 4.83787E-01 5.59730E-02 2.09526E-01 VIEW -2.97649E-01 7.96940E-01 -5.25635E-01 RIGH 9.05932E-01 4.09467E-01 1.07814E-01 UP -3.01151E-01 4.44099E-01 8.43851E-01 FOV 2.48819E+01 !NAVIGATION MODE: ROTATING CAMERA !CENTER : 3.50000E+00 1.00000E+00 1.00000E+00 !RSPHERE: 3.77492E+00 !RADIUS : 2.07620E+01 !ASPECT : 1.00000E+00 !NEAR : 1.69871E+01 !FAR : 2.83119E+01 SCEN GEOM NAVI FREE LIMA ON SLER CAM1 1 NFRA 1 FREQ 0 TFRE 1.E-3 TRAC OFFS FICH AVI NOCL NFTO 86 FPS 10 KFRE 10 COMP -1 OBJE LECT base cube ncub TERM REND GOTR LOOP 84 OFFS FICH AVI CONT NOCL OBJE LECT base cube ncub TERM REND GO TRAC OFFS FICH AVI CONT OBJE LECT base cube ncub TERM REND 153 Tuesday 12thAugust, 2025 @ 13:38 ENDP *======================================================================= SUITE Post-treatment ECHO RESU ALIC TEMP GARD PSCR SORT GRAP AXTE 1. 't [s]' COUR 1 'dz_p5' DEPL COMP 3 NOEU LECT p5 TERM COUR 2 'dz_p6' DEPL COMP 3 NOEU LECT p6 TERM COUR 3 'dz_p7' DEPL COMP 3 NOEU LECT p7 TERM COUR 4 'dz_p8' DEPL COMP 3 NOEU LECT p8 TERM COUR 5 'dx_p5' DEPL COMP 1 NOEU LECT p5 TERM COUR 6 'dx_p6' DEPL COMP 1 NOEU LECT p6 TERM COUR 7 'dx_p7' DEPL COMP 1 NOEU LECT p7 TERM COUR 8 'dx_p8' DEPL COMP 1 NOEU LECT p8 TERM TRAC 1 2 3 4 AXES 1. 'Z-DISP (m)' YZER TRAC 5 6 7 8 AXES 1. 'X-DISP (m)' YZER LIST 1 2 3 4 AXES 1. 'Z-DISP (m)' LIST 5 6 7 8 AXES 1. 'X-DISP (m)' RCOU 15 'dx_p5' FICH 'sc3d00.pun' RENA 'dx_p5_3d_00' RCOU 25 'dx_p5' FICH 'sc2d01.pun' RENA 'dx_p5_2d_01' TRAC 5 15 AXES 1. 'X-DISP (m)' YZER COLO NOIR ROUG TRAC 5 25 15 AXES 1. 'X-DISP (m)' YZER COLO NOIR ROUG VERT FIN sc3d131.dgibi opti echo 0; * 'DEBPROC' pxextr3d m*'MAILLAGE' x1*'FLOTTANT' x2*'FLOTTANT' y1*'FLOTTANT' y2*'FLOTTANT' z1*'FLOTTANT' z2*'FLOTTANT'; * *-------------------------------------------------- * Extracts from the 3D mesh m the elements whose nodes are * located in the box [x1-x2,y1-y2,z1-z2]. * * Input : * ----- * m : 3D mesh * x1, x2, y1, y2, z1, z2 : extremes of the box * Output : * ------ * box : mesh contained in the box *-------------------------------------------------- * x = coor 1 m; sx = x POIN COMP x1 x2; y = coor 2 sx; sy = y POIN COMP y1 y2; z = coor 3 sy; sz = z POIN COMP z1 z2; box = m ELEM APPU STRI sz NOVE;

[ "Q", "8.47889E-01", "4.83787E-01", "5.59730E-02", "2.09526E-01", "\n", "VIEW", "-2.97649E-01", "7.96940E-01", "-5.25635E-01", "\n", "RIGH", "9.05932E-01", "4.09467E-01", "1.07814E-01", "\n", "UP", "-3.01151E-01", "4.44099E-01", "8.43851E-01", "\n", "FOV", "2.48819E+01", "\n", "!", "NAVIGATION", "MODE", ":", "ROTATING", "CAMERA", "\n", "!", "CENTER", ":", "3.50000E+00", "1.00000E+00", "1.00000E+00", "\n", "!", "RSPHERE", ":", "3.77492E+00", "\n", "!", "RADIUS", ":", "2.07620E+01", "\n", "!", "ASPECT", ":", "1.00000E+00", "\n", "!", "NEAR", ":", "1.69871E+01", "\n", "!", "FAR", ":", "2.83119E+01", "\n", "SCEN", "GEOM", "NAVI", "FREE", "\n", "LIMA", "ON", "\n", "SLER", "CAM1", "1", "NFRA", "1", "\n", "FREQ", "0", "TFRE", "1.E-3", "\n", "TRAC", "OFFS", "FICH", "AVI", "NOCL", "NFTO", "86", "FPS", "10", "KFRE", "10", "COMP", "-1", "\n", "OBJE", "LECT", "base", "cube", "ncub", "TERM", "REND", "\n", "GOTR", "LOOP", "84", "OFFS", "FICH", "AVI", "CONT", "NOCL", "\n", "OBJE", "LECT", "base", "cube", "ncub", "TERM", "REND", "\n", "GO", "\n", "TRAC", "OFFS", "FICH", "AVI", "CONT", "\n", "OBJE", "LECT", "base", "cube", "ncub", "TERM", "REND", "\n", "153", "\n", "Tuesday", "12thAugust", ",", "2025", "@", "13:38", "\n", "ENDP", "\n", "*", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "=", "\n", "SUITE", "\n", "Post", "-", "treatment", "\n", "ECHO", "\n", "RESU", "ALIC", "TEMP", "GARD", "PSCR", "\n", "SORT", "GRAP", "AXTE", "1", ".", "'", "t", "[", "s", "]", "'", "\n", "COUR", "1", "'", "dz_p5", "'", "DEPL", "COMP", "3", "NOEU", "LECT", "p5", "TERM", "\n", "COUR", "2", "'", "dz_p6", "'", "DEPL", "COMP", "3", "NOEU", "LECT", "p6", "TERM", "\n", "COUR", "3", "'", "dz_p7", "'", "DEPL", "COMP", "3", "NOEU", "LECT", "p7", "TERM", "\n", "COUR", "4", "'", "dz_p8", "'", "DEPL", "COMP", "3", "NOEU", "LECT", "p8", "TERM", "\n", "COUR", "5", "'", "dx_p5", "'", "DEPL", "COMP", "1", "NOEU", "LECT", "p5", "TERM", "\n", "COUR", "6", "'", "dx_p6", "'", "DEPL", "COMP", "1", "NOEU", "LECT", "p6", "TERM", "\n", "COUR", "7", "'", "dx_p7", "'", "DEPL", "COMP", "1", "NOEU", "LECT", "p7", "TERM", "\n", "COUR", "8", "'", "dx_p8", "'", "DEPL", "COMP", "1", "NOEU", "LECT", "p8", "TERM", "\n", "TRAC", "1", "2", "3", "4", "AXES", "1", ".", "'", "Z", "-", "DISP", "(", "m", ")", "'", "YZER", "\n", "TRAC", "5", "6", "7", "8", "AXES", "1", ".", "'", "X", "-", "DISP", "(", "m", ")", "'", "YZER", "\n", "LIST", "1", "2", "3", "4", "AXES", "1", ".", "'", "Z", "-", "DISP", "(", "m", ")", "'", "\n", "LIST", "5", "6", "7", "8", "AXES", "1", ".", "'", "X", "-", "DISP", "(", "m", ")", "'", "\n", "RCOU", "15", "'", "dx_p5", "'", "FICH", "'", "sc3d00.pun", "'", "RENA", "'", "dx_p5_3d_00", "'", "\n", "RCOU", "25", "'", "dx_p5", "'", "FICH", "'", "sc2d01.pun", "'", "RENA", "'", "dx_p5_2d_01", "'", "\n", "TRAC", "5", "15", "AXES", "1", ".", "'", "X", "-", "DISP", "(", "m", ")", "'", "YZER", "\n", "COLO", "NOIR", "ROUG", "\n", "TRAC", "5", "25", "15", "AXES", "1", ".", "'", "X", "-", "DISP", "(", "m", ")", "'", "YZER", "\n", "COLO", "NOIR", "ROUG", "VERT", "\n", "FIN", "\n", "sc3d131.dgibi", "\n", "opti", "echo", "0", ";", "\n", "*", "\n", "'", "DEBPROC", "'", "pxextr3d", "m*'MAILLAGE", "'", "x1*'FLOTTANT", "'", "x2*'FLOTTANT", "'", "\n", "y1*'FLOTTANT", "'", "y2*'FLOTTANT", "'", "\n", "z1*'FLOTTANT", "'", "z2*'FLOTTANT", "'", ";", "\n", "*", "\n", "*", "--------------------------------------------------", "\n", "*", "Extracts", "from", "the", "3D", "mesh", "m", "the", "elements", "whose", "nodes", "are", "\n", "*", "located", "in", "the", "box", "[", "x1", "-", "x2,y1", "-", "y2,z1", "-", "z2", "]", ".", "\n", "*", "\n", "*", "Input", ":", "\n", "*", "-----", "\n", "*", "m", ":", "3D", "mesh", "\n", "*", "x1", ",", "x2", ",", "y1", ",", "y2", ",", "z1", ",", "z2", ":", "extremes", "of", "the", "box", "\n", "*", "Output", ":", "\n", "*", "------", "\n", "*", "box", ":", "mesh", "contained", "in", "the", "box", "\n", "*", "--------------------------------------------------", "\n", "*", "\n", "x", "=", "coor", "1", "m", ";", "\n", "sx", "=", "x", "POIN", "COMP", "x1", "x2", ";", "\n", "y", "=", "coor", "2", "sx", ";", "\n", "sy", "=", "y", "POIN", "COMP", "y1", "y2", ";", "\n", "z", "=", "coor", "3", "sy", ";", "\n", "sz", "=", "z", "POIN", "COMP", "z1", "z2", ";", "\n", "box", "=", "m", "ELEM", "APPU", "STRI", "sz", "NOVE", ";", "\n" ]

[]

type of contractual arrangements for petroleum exploration and development. PSAs cover individual fields/projects (Bindeman, 1999). The fiscal liability is then determined with reference to specific contracts, which results in a de facto ring-fencing outcome. The burden of implementing ring-fencing rules could be perceived to be lower due to this contract-by-contract approach to the fiscal administration of oil projects. Cost recovery is typically ring-fenced, as explained in Box 3. • PSAs have not taken hold in mining. This issue is explored in Readhead et al. (2023).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 11 Ring-Fencing Mining Income: A toolkit for tax administrators and policy-makersBOX 3. RING -FENCING AND PSAS PSAs are typically designed to include cost recovery and production- sharing instruments.9 Revenue sharing between the host government and the investor is normally determined by arrangements for assigned shares of production volumes. The obligation to pay CIT and other taxes may be placed on the investor or on a state-owned company on the investor’s behalf. Cost recovery is often ring-fenced around the exploration and/or development licence within a contract area, which means that exploration and/or development costs associated with a particular licence must be recovered from revenues generated within that block or licence (Nakhle, 2010). In other words, if ring-fencing rules for different licences covered by a PSA exist, an investor should not be able to consolidate revenues and losses derived from different licences covered by a PSA.10 In summary, for most sectors of the economy, the corporate tax base is determined at the subsidiary or branch level, not at the project or activity level. In the mining sector, however, it is common for governments to ring-fence mining projects, and/or mining income from other sources of income. This allows them to administer the specific tax regime for each project and/or mining activities separately from other commercial activities, accelerating government revenues and protecting the tax base. The application of ring-fencing rules is not exclusive to the extractive sectors. Some countries also apply the ring-fencing rules in the finance11 and energy sectors.12 In deciding whether ring-fencing rules are adequate for their mining tax regime, governments in resource-rich countries should be aware of the benefits and challenges of ring-fencing rules and how they would fit into the overall structure of the taxation framework,

[ "type", "of", "contractual", "arrangements", "for", "petroleum", "exploration", "and", "\n", "development", ".", "PSAs", "cover", "individual", "fields", "/", "projects", "(", "Bindeman", ",", "1999", ")", ".", "\n", "The", "fiscal", "liability", "is", "then", "determined", "with", "reference", "to", "specific", "\n", "contracts", ",", "which", "results", "in", "a", "de", "facto", "ring", "-", "fencing", "outcome", ".", "The", "\n", "burden", "of", "implementing", "ring", "-", "fencing", "rules", "could", "be", "perceived", "to", "\n", "be", "lower", "due", "to", "this", "contract", "-", "by", "-", "contract", "approach", "to", "the", "fiscal", "\n", "administration", "of", "oil", "projects", ".", "Cost", "recovery", "is", "typically", "ring", "-", "fenced", ",", "\n", "as", "explained", "in", "Box", "3", ".", "\n", "•", "PSAs", "have", "not", "taken", "hold", "in", "mining", ".", "This", "issue", "is", "explored", "in", "\n", "Readhead", "et", "al", ".", "(", "2023).3.0", "THE", "BENEFITS", "\n", "AND", "RISKS", "OF", " \n", "RING", "-FENCING", "\n", "4.0", "DESIGNING", "\n", "RING", "-FENCING", "\n", "RULES", "\n", "5.0", "THE", "\n", "IMPLEMENTATION", "\n", "OF", "RING", "-FENCING", "\n", "RULES", "\n", "6.0", "CONCLUSION", "2.0", "THE", "\n", "FUNDAMENTALS", " \n", "OF", "RING", "-FENCING", "1.0", "INTRODUCTION", "\n", "11", "\n", "Ring", "-", "Fencing", "Mining", "Income", ":", "A", "toolkit", "for", "tax", "administrators", "and", "policy", "-", "makersBOX", "3", ".", "RING", "-FENCING", "AND", "PSAS", "\n", "PSAs", "are", "typically", "designed", "to", "include", "cost", "recovery", "and", "production-", "\n", "sharing", "instruments.9", "Revenue", "sharing", "between", "the", "host", "government", "\n", "and", "the", "investor", "is", "normally", "determined", "by", "arrangements", "for", "assigned", "\n", "shares", "of", "production", "volumes", ".", "The", "obligation", "to", "pay", "CIT", "and", "other", "\n", "taxes", "may", "be", "placed", "on", "the", "investor", "or", "on", "a", "state", "-", "owned", "company", "on", "\n", "the", "investor", "’s", "behalf", ".", "Cost", "recovery", "is", "often", "ring", "-", "fenced", "around", "the", "\n", "exploration", "and/or", "development", "licence", "within", "a", "contract", "area", ",", "which", "\n", "means", "that", "exploration", "and/or", "development", "costs", "associated", "with", "a", "\n", "particular", "licence", "must", "be", "recovered", "from", "revenues", "generated", "within", "\n", "that", "block", "or", "licence", "(", "Nakhle", ",", "2010", ")", ".", "In", "other", "words", ",", "if", "ring", "-", "fencing", "rules", "\n", "for", "different", "licences", "covered", "by", "a", "PSA", "exist", ",", "an", "investor", "should", "not", "be", "\n", "able", "to", "consolidate", "revenues", "and", "losses", "derived", "from", "different", "licences", "\n", "covered", "by", "a", "PSA.10", "\n", "In", "summary", ",", "for", "most", "sectors", "of", "the", "economy", ",", "the", "corporate", "tax", "base", " \n", "is", "determined", "at", "the", "subsidiary", "or", "branch", "level", ",", "not", "at", "the", "project", "or", "\n", "activity", "level", ".", "In", "the", "mining", "sector", ",", "however", ",", "it", "is", "common", "for", "governments", "\n", "to", "ring", "-", "fence", "mining", "projects", ",", "and/or", "mining", "income", "from", "other", "sources", "\n", "of", "income", ".", "This", "allows", "them", "to", "administer", "the", "specific", "tax", "regime", "for", "each", "\n", "project", "and/or", "mining", "activities", "separately", "from", "other", "commercial", "activities", ",", "\n", "accelerating", "government", "revenues", "and", "protecting", "the", "tax", "base", ".", "The", "\n", "application", "of", "ring", "-", "fencing", "rules", "is", "not", "exclusive", "to", "the", "extractive", "sectors", ".", "\n", "Some", "countries", "also", "apply", "the", "ring", "-", "fencing", "rules", "in", "the", "finance11", "and", "energy", "\n", "sectors.12", "In", "deciding", "whether", "ring", "-", "fencing", "rules", "are", "adequate", "for", "their", "\n", "mining", "tax", "regime", ",", "governments", "in", "resource", "-", "rich", "countries", "should", "be", "aware", "\n", "of", "the", "benefits", "and", "challenges", "of", "ring", "-", "fencing", "rules", "and", "how", "they", "would", "\n", "fit", "into", "the", "overall", "structure", "of", "the", "taxation", "framework", "," ]

[ { "end": 1554, "label": "CITATION_REF", "start": 1542 }, { "end": 1548, "label": "AUTHOR", "start": 1542 }, { "end": 1554, "label": "YEAR", "start": 1550 } ]

Gooday cau - tion against ‘glib[ly] describ[ing] their geographical scope as global’, the available data show that ICWES was regularly attended by women del - egates from around thirty countries, with variations in regional visibility 19 19 Introduction between different conferences: ‘South American nations were most visible in ICWES 1 (USA); African nations were first apparent at ICWES 2 (UK); and only at ICWES 4 (Poland) was there broad participation from Eastern European nations, with the USA constituency (44 attendees) for the first time overshadowed by a large majority of native (Polish) participants (423 attendees).’ As the two authors emphasize, the ICWES archive provides an oppor - tunity to place engineering firmly on the agenda of future historiographies of women in ‘science’, not least because engineering was less exclusionary a field than the fundamental or ‘pure’ sciences, as the participation of del - egates from African, Asian and South American countries also demonstrate. This is not to say that certain countries did not feature more prominently in the organization of these conferences than others. Indeed, as the authors point out, ‘the planning and programming of successive meetings relied on the national- level organisations for women in science and engineering most prominently in eight countries: Brazil, France, Italy, Japan, the Philippines, Poland, UK and USA’. Rees Koerner and Gooday’s chapter also renders visible the intersections of collective and individual agencies of women in STEMM, for example, by showing that transnational collaboration between national bodies and the untiring effort of individual engineers like Ira Rischowski were essential to the success of these events. The trans- regional approach they employ is particularly effective at exposing the politics and anxieties over the low number of women in sci - ence in the US and Western Europe, especially in the charged geopolitical climate of the Cold War, when comparison with the countries of the com - munist bloc became topical. As the authors point out, ‘it was left … to the communist countries participating in ICWES meetings to highlight their more developed capacity to educate, equip and enrol women for roles in engineering and applied science’. The political undertones of this mission cannot be ignored and delegates from communist countries likely regarded the promotion of women’s participation in engineering and applied science as a tool of science diplomacy. Of course, the link between science, gender and politics was not emblematic of that context alone. All

[ "Gooday", "cau", "-", "\n", "tion", "against", "‘", "glib[ly", "]", "describ[ing", "]", "their", "geographical", "scope", "as", "global", "’", ",", "the", "\n", "available", "data", "show", "that", "ICWES", "was", "regularly", "attended", "by", "women", "del", "-", "\n", "egates", "from", "around", "thirty", "countries", ",", "with", "variations", "in", "regional", "visibility", "\n", "19", "\n", "19", "\n", "Introduction", "\n", "between", "different", "conferences", ":", "‘", "South", "American", "nations", "were", "most", "visible", "\n", "in", "ICWES", "1", "(", "USA", ")", ";", "African", "nations", "were", "first", "apparent", "at", "ICWES", "2", "(", "UK", ")", ";", "\n", "and", "only", "at", "ICWES", "4", "(", "Poland", ")", "was", "there", "broad", "participation", "from", "Eastern", "\n", "European", "nations", ",", "with", "the", "USA", "constituency", "(", "44", "attendees", ")", "for", "the", "first", "\n", "time", "overshadowed", "by", "a", "large", "majority", "of", "native", "(", "Polish", ")", "participants", "(", "423", "\n", "attendees", ")", ".", "’", "\n", "As", "the", "two", "authors", "emphasize", ",", "the", "ICWES", "archive", "provides", "an", "oppor", "-", "\n", "tunity", "to", "place", "engineering", "firmly", "on", "the", "agenda", "of", "future", "historiographies", "\n", "of", "women", "in", "‘", "science", "’", ",", "not", "least", "because", "engineering", "was", "less", "exclusionary", "\n", "a", "field", "than", "the", "fundamental", "or", "‘", "pure", "’", "sciences", ",", "as", "the", "participation", "of", "del", "-", "\n", "egates", "from", "African", ",", "Asian", "and", "South", "American", "countries", "also", "demonstrate", ".", "\n", "This", "is", "not", "to", "say", "that", "certain", "countries", "did", "not", "feature", "more", "prominently", "\n", "in", "the", "organization", "of", "these", "conferences", "than", "others", ".", "Indeed", ",", "as", "the", "authors", "\n", "point", "out", ",", "‘", "the", "planning", "and", "programming", "of", "successive", "meetings", "relied", "on", "\n", "the", "national-", "level", "organisations", "for", "women", "in", "science", "and", "engineering", "most", "\n", "prominently", "in", "eight", "countries", ":", "Brazil", ",", "France", ",", "Italy", ",", "Japan", ",", "the", "Philippines", ",", "\n", "Poland", ",", "UK", "and", "USA", "’", ".", "Rees", "Koerner", "and", "Gooday", "’s", "chapter", "also", "renders", "\n", "visible", "the", "intersections", "of", "collective", "and", "individual", "agencies", "of", "women", "\n", "in", "STEMM", ",", "for", "example", ",", "by", "showing", "that", "transnational", "collaboration", "\n", "between", "national", "bodies", "and", "the", "untiring", "effort", "of", "individual", "engineers", "like", "\n", "Ira", "Rischowski", "were", "essential", "to", "the", "success", "of", "these", "events", ".", "\n", "The", "trans-", "regional", "approach", "they", "employ", "is", "particularly", "effective", "at", "\n", "exposing", "the", "politics", "and", "anxieties", "over", "the", "low", "number", "of", "women", "in", "sci", "-", "\n", "ence", "in", "the", "US", "and", "Western", "Europe", ",", "especially", "in", "the", "charged", "geopolitical", "\n", "climate", "of", "the", "Cold", "War", ",", "when", "comparison", "with", "the", "countries", "of", "the", "com", "-", "\n", "munist", "bloc", "became", "topical", ".", "As", "the", "authors", "point", "out", ",", "‘", "it", "was", "left", "…", "to", "\n", "the", "communist", "countries", "participating", "in", "ICWES", "meetings", "to", "highlight", "their", "\n", "more", "developed", "capacity", "to", "educate", ",", "equip", "and", "enrol", "women", "for", "roles", "in", "\n", "engineering", "and", "applied", "science", "’", ".", "The", "political", "undertones", "of", "this", "mission", "\n", "can", "not", "be", "ignored", "and", "delegates", "from", "communist", "countries", "likely", "regarded", "\n", "the", "promotion", "of", "women", "’s", "participation", "in", "engineering", "and", "applied", "science", "\n", "as", "a", "tool", "of", "science", "diplomacy", ".", "Of", "course", ",", "the", "link", "between", "science", ",", "gender", "\n", "and", "politics", "was", "not", "emblematic", "of", "that", "context", "alone", ".", "All" ]

[]

discharge, turbine, heat exchanger, collector, rectifier, condition, resistance, statorTable 3.3b. List of 50 most relevant keywords for each S&T domainTable 3.3a. List of identified S&T specialisation domains EaP S&T specialisation domains (in alphabetical order) Agrifood Biotechnology Energy Optics and photonicsHealth and wellbeingChemistry and chemical engineeringElectric and electronic technologies Environmental sciences and industries Governance, culture, education and the economy ICT and computer science TransportationNanotechnology and materialsFundamental physics and mathematics Mechanical engineering and heavy machinery 150 Part 3 Analysis of scientific and technological potential S&T domain Top keywords Environmental sciences and industriesspecie, water, soil, plant, environment, deposit, rock, population, basin, datum, reservoir, river, pollution, territory, concentration, condition, treatment, well, sea, caucasus, philtre, source, purification, ecosystem, temperature, contamination, metal, monitoring, forest, mine, mining, genus, sediment, mass, species, nov, station, accumulation, slope, extraction, tree, habitat, ore, massif, air, hole, removal, biomass, land, body Fundamental physics and mathematicstev, collision, equation, measurement, detector, mass, boson, gev, section, jet, datum, atlas detector, condition, particle, pp collision, luminosity, space, lhc, energy, integrated luminosity, momentum, coefficient, dependence, pair, decay, quark, proton-proton collision, lepton, prediction, channel, flow, mass, proton, electron, collider, confidence level, muon, fraction, frequency, resonance, transverse momentum, formula, cms detector, photon, sup, higgs boson, gas, cross section, simulation, excess Governance, culture, education and the economyenterprise, author, economy, policy, market, resource, environment, risk, society, industry, experience, security, regulation, culture, population, history, people, life, language, bank, business, government, reform, law, protection, identity, caucasus, city, text, investment, nature, competitiveness, capital, conflict, sustainable development, sphere, source, form, condition, teacher, crisis, publication, power, authority, tradition, attitude, legislation, image, perception, peculiarity Health and wellbeingpatient, treatment, cell, disease, child, therapy, tissue, woman, rat, disorder, gene, diagnosis, age, cancer, drug, syndrome, risk, population, animal, dose, infection, surgery, expression, complication, protein, care, prevalence, week, diabetes, people, tumour, examination, day, cavity, year, medicine, mortality, pathology, symptom, mutation, prevention, blood, intervention, hypertension, marker, month, stress, death, health, severity ICT and computer sciencealgorithm, network, datum, measurement, simulation, image, accuracy, error, signal, user, monitoring, software, modelling, detection, architecture, database, recognition, node, prediction, environment, condition, code, construction, server, resource, correction, station, complexity, sensor, uncertainty, neural network, form, source, communication, noise, sequence, channel, propose method, computer, connexion, message, rule, memory, author, transmission, interface, circuit, probability, distance, subsystem Mechanical engineering and heavy machineryplate, chamber, axis, body, rod, wall, hole, angle, surface, shaft, pipe, opening, housing, form, plane, machine, cylinder, drive, valve, diameter, groove, ring, shell, section, rotation, spring, portion, holder, pipeline, guide, cover, sleeve,

[ "discharge", ",", "turbine", ",", "heat", "exchanger", ",", "\n", "collector", ",", "rectifier", ",", "condition", ",", "resistance", ",", "statorTable", "3.3b", ".", "List", "of", "50", "most", "relevant", "keywords", "for", "each", "S&T", "domainTable", "3.3a", ".", "List", "of", "identified", "S&T", "specialisation", "domains", "\n", "EaP", "S&T", "specialisation", "domains", "(", "in", "alphabetical", "order", ")", "\n", "Agrifood", "Biotechnology", "\n", "Energy", "\n", "Optics", "and", "photonicsHealth", "and", "wellbeingChemistry", "and", "chemical", "\n", "engineeringElectric", "and", "electronic", "\n", "technologies", "\n", "Environmental", "sciences", "and", "\n", "industries", "\n", "Governance", ",", "culture", ",", "\n", "education", "and", "the", "economy", "\n", "ICT", "and", "computer", "science", "\n", "TransportationNanotechnology", "and", "\n", "materialsFundamental", "physics", "and", "\n", "mathematics", "\n", "Mechanical", "engineering", "and", "\n", "heavy", "machinery", "\n", "150", "\n ", "Part", "3", "Analysis", "of", "scientific", "and", "technological", "potential", "\n", "S&T", "domain", "Top", "keywords", "\n", "Environmental", "\n", "sciences", "and", "\n", "industriesspecie", ",", "water", ",", "soil", ",", "plant", ",", "environment", ",", "deposit", ",", "rock", ",", "population", ",", "basin", ",", "datum", ",", "reservoir", ",", "river", ",", "\n", "pollution", ",", "territory", ",", "concentration", ",", "condition", ",", "treatment", ",", "well", ",", "sea", ",", "caucasus", ",", "philtre", ",", "source", ",", "\n", "purification", ",", "ecosystem", ",", "temperature", ",", "contamination", ",", "metal", ",", "monitoring", ",", "forest", ",", "mine", ",", "mining", ",", "\n", "genus", ",", "sediment", ",", "mass", ",", "species", ",", "nov", ",", "station", ",", "accumulation", ",", "slope", ",", "extraction", ",", "tree", ",", "habitat", ",", "ore", ",", "\n", "massif", ",", "air", ",", "hole", ",", "removal", ",", "biomass", ",", "land", ",", "body", "\n", "Fundamental", "\n", "physics", "and", "\n", "mathematicstev", ",", "collision", ",", "equation", ",", "measurement", ",", "detector", ",", "mass", ",", "boson", ",", "gev", ",", "section", ",", "jet", ",", "datum", ",", "atlas", "\n", "detector", ",", "condition", ",", "particle", ",", "pp", "collision", ",", "luminosity", ",", "space", ",", "lhc", ",", "energy", ",", "integrated", "luminosity", ",", "\n", "momentum", ",", "coefficient", ",", "dependence", ",", "pair", ",", "decay", ",", "quark", ",", "proton", "-", "proton", "collision", ",", "lepton", ",", "prediction", ",", "\n", "channel", ",", "flow", ",", "mass", ",", "proton", ",", "electron", ",", "collider", ",", "confidence", "level", ",", "muon", ",", "fraction", ",", "frequency", ",", "\n", "resonance", ",", "transverse", "momentum", ",", "formula", ",", "cms", "detector", ",", "photon", ",", "sup", ",", "higgs", "boson", ",", "gas", ",", "cross", "\n", "section", ",", "simulation", ",", "excess", "\n", "Governance", ",", "\n", "culture", ",", "education", "\n", "and", "the", "economyenterprise", ",", "author", ",", "economy", ",", "policy", ",", "market", ",", "resource", ",", "environment", ",", "risk", ",", "society", ",", "industry", ",", "\n", "experience", ",", "security", ",", "regulation", ",", "culture", ",", "population", ",", "history", ",", "people", ",", "life", ",", "language", ",", "bank", ",", "\n", "business", ",", "government", ",", "reform", ",", "law", ",", "protection", ",", "identity", ",", "caucasus", ",", "city", ",", "text", ",", "investment", ",", "nature", ",", "\n", "competitiveness", ",", "capital", ",", "conflict", ",", "sustainable", "development", ",", "sphere", ",", "source", ",", "form", ",", "condition", ",", "\n", "teacher", ",", "crisis", ",", "publication", ",", "power", ",", "authority", ",", "tradition", ",", "attitude", ",", "legislation", ",", "image", ",", "perception", ",", "\n", "peculiarity", "\n", "Health", "and", "\n", "wellbeingpatient", ",", "treatment", ",", "cell", ",", "disease", ",", "child", ",", "therapy", ",", "tissue", ",", "woman", ",", "rat", ",", "disorder", ",", "gene", ",", "diagnosis", ",", "age", ",", "\n", "cancer", ",", "drug", ",", "syndrome", ",", "risk", ",", "population", ",", "animal", ",", "dose", ",", "infection", ",", "surgery", ",", "expression", ",", "complication", ",", "\n", "protein", ",", "care", ",", "prevalence", ",", "week", ",", "diabetes", ",", "people", ",", "tumour", ",", "examination", ",", "day", ",", "cavity", ",", "year", ",", "medicine", ",", "\n", "mortality", ",", "pathology", ",", "symptom", ",", "mutation", ",", "prevention", ",", "blood", ",", "intervention", ",", "hypertension", ",", "marker", ",", "\n", "month", ",", "stress", ",", "death", ",", "health", ",", "severity", "\n", "ICT", "and", "computer", "\n", "sciencealgorithm", ",", "network", ",", "datum", ",", "measurement", ",", "simulation", ",", "image", ",", "accuracy", ",", "error", ",", "signal", ",", "user", ",", "\n", "monitoring", ",", "software", ",", "modelling", ",", "detection", ",", "architecture", ",", "database", ",", "recognition", ",", "node", ",", "prediction", ",", "\n", "environment", ",", "condition", ",", "code", ",", "construction", ",", "server", ",", "resource", ",", "correction", ",", "station", ",", "complexity", ",", "sensor", ",", "\n", "uncertainty", ",", "neural", "network", ",", "form", ",", "source", ",", "communication", ",", "noise", ",", "sequence", ",", "channel", ",", "propose", "\n", "method", ",", "computer", ",", "connexion", ",", "message", ",", "rule", ",", "memory", ",", "author", ",", "transmission", ",", "interface", ",", "circuit", ",", "\n", "probability", ",", "distance", ",", "subsystem", "\n", "Mechanical", "\n", "engineering", "and", "\n", "heavy", "machineryplate", ",", "chamber", ",", "axis", ",", "body", ",", "rod", ",", "wall", ",", "hole", ",", "angle", ",", "surface", ",", "shaft", ",", "pipe", ",", "opening", ",", "housing", ",", "form", ",", "\n", "plane", ",", "machine", ",", "cylinder", ",", "drive", ",", "valve", ",", "diameter", ",", "groove", ",", "ring", ",", "shell", ",", "section", ",", "rotation", ",", "spring", ",", "portion", ",", "\n", "holder", ",", "pipeline", ",", "guide", ",", "cover", ",", "sleeve", "," ]

[]

… | … | … | … | … | … | … | … | | Austria | 97 ᵢ | 97 ₋₁ ᵢ | 1 | 1 | 1 | 1 | 7 | 6 | 100 | 100 | 99 | 98 | 85 | 86 | 3.4 | 5.7 | 5.7 | | Belarus | 97 | 98 | 2 | 4 | 0.2 | 0.4 | 2 | 1 | 100 | 100 | 99 | 99 | 90 | 93 | 3.4 | 2.1 | 2.1 | | Belgium | 98 ᵢ | 99 ₋₁ ᵢ | 1 | 1 | 1 | 1 | 1 | 2 | 99 | 99 | 87 | 91 | 83 | 86 | 8.1 | 8.1 | 8.1 | | Bermuda | … | … | … | … | … | … | … | … | … | … | … | … | … | … | … | … | … | | Bosnia and Herzegovina | 18 ₊₁ | 32 | 10 | 10 | 3 | 13 | 23 | 27 | 100 | 100 | 98 | 99 | 60 | 65 | 9.2 | 11.3 | 11.3 | | Bulgaria | 94 ᵢ | 94 ₋₁ ᵢ | 2 | 5 | 3 | 5 | 11 | 9 | 99 | 99 | 94 | 94 | 85 | 87 | 0.1 | 0.8 | 0.8 | | Canada | … | 95 ₋₁ ᵢ | 0.1 | - | 0.3 | 0.2 | 11 | 9 | 100 | 100 | 99 | 99 | 86 | 88 | 6.0 | 6.4 | 6.4 | | Croatia | 98 ᵢ | 100 ₋₁ ᵢ | - | - | - | - | 9 | 6 | 100 | 100 | 99 | 99 | 96 | 98 | 0.7 | 0.5 | 0.5 | | Czechia | 91 ᵢ | 94 ₋₁ ᵢ | 2 | 1 | 0.3 | 1 | 4 | 4 | 100 | 100 | 96 | 96 | 90 | 90 | 1.3 | 1.8 | 1.8 | | Denmark | 99 ᵢ | 98 ₋₁ ᵢ | 0.3 | 0.2 | 1 | 1 | 9 | 6 | 100 | 100 | 100 | 100 | 75

[ "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "\n", "|", "Austria", " ", "|", "97", "ᵢ", " ", "|", "97", "₋₁", "ᵢ", " ", "|", "1", " ", "|", "1", " ", "|", "1", " ", "|", "1", " ", "|", "7", " ", "|", "6", " ", "|", "100", " ", "|", "100", " ", "|", "99", " ", "|", "98", " ", "|", "85", " ", "|", "86", " ", "|", "3.4", " ", "|", "5.7", " ", "|", "5.7", " ", "|", "\n", "|", "Belarus", " ", "|", "97", " ", "|", "98", " ", "|", "2", " ", "|", "4", " ", "|", "0.2", " ", "|", "0.4", " ", "|", "2", " ", "|", "1", " ", "|", "100", " ", "|", "100", " ", "|", "99", " ", "|", "99", " ", "|", "90", " ", "|", "93", " ", "|", "3.4", " ", "|", "2.1", " ", "|", "2.1", " ", "|", "\n", "|", "Belgium", " ", "|", "98", "ᵢ", " ", "|", "99", "₋₁", "ᵢ", " ", "|", "1", " ", "|", "1", " ", "|", "1", " ", "|", "1", " ", "|", "1", " ", "|", "2", " ", "|", "99", " ", "|", "99", " ", "|", "87", " ", "|", "91", " ", "|", "83", " ", "|", "86", " ", "|", "8.1", " ", "|", "8.1", " ", "|", "8.1", " ", "|", "\n", "|", "Bermuda", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "\n", "|", "Bosnia", "and", "Herzegovina", " ", "|", "18", "₊₁", " ", "|", "32", " ", "|", "10", " ", "|", "10", " ", "|", "3", " ", "|", "13", " ", "|", "23", " ", "|", "27", " ", "|", "100", " ", "|", "100", " ", "|", "98", " ", "|", "99", " ", "|", "60", " ", "|", "65", " ", "|", "9.2", " ", "|", "11.3", " ", "|", "11.3", " ", "|", "\n", "|", "Bulgaria", " ", "|", "94", "ᵢ", " ", "|", "94", "₋₁", "ᵢ", " ", "|", "2", " ", "|", "5", " ", "|", "3", " ", "|", "5", " ", "|", "11", " ", "|", "9", " ", "|", "99", " ", "|", "99", " ", "|", "94", " ", "|", "94", " ", "|", "85", " ", "|", "87", " ", "|", "0.1", " ", "|", "0.8", " ", "|", "0.8", " ", "|", "\n", "|", "Canada", " ", "|", "…", " ", "|", "95", "₋₁", "ᵢ", " ", "|", "0.1", " ", "|", "-", " ", "|", "0.3", " ", "|", "0.2", " ", "|", "11", " ", "|", "9", " ", "|", "100", " ", "|", "100", " ", "|", "99", " ", "|", "99", " ", "|", "86", " ", "|", "88", " ", "|", "6.0", " ", "|", "6.4", " ", "|", "6.4", " ", "|", "\n", "|", "Croatia", " ", "|", "98", "ᵢ", " ", "|", "100", "₋₁", "ᵢ", " ", "|", "-", " ", "|", "-", " ", "|", "-", " ", "|", "-", " ", "|", "9", " ", "|", "6", " ", "|", "100", " ", "|", "100", " ", "|", "99", " ", "|", "99", " ", "|", "96", " ", "|", "98", " ", "|", "0.7", " ", "|", "0.5", " ", "|", "0.5", " ", "|", "\n", "|", "Czechia", " ", "|", "91", "ᵢ", " ", "|", "94", "₋₁", "ᵢ", " ", "|", "2", " ", "|", "1", " ", "|", "0.3", " ", "|", "1", " ", "|", "4", " ", "|", "4", " ", "|", "100", " ", "|", "100", " ", "|", "96", " ", "|", "96", " ", "|", "90", " ", "|", "90", " ", "|", "1.3", " ", "|", "1.8", " ", "|", "1.8", " ", "|", "\n", "|", "Denmark", " ", "|", "99", "ᵢ", " ", "|", "98", "₋₁", "ᵢ", " ", "|", "0.3", " ", "|", "0.2", " ", "|", "1", " ", "|", "1", " ", "|", "9", " ", "|", "6", " ", "|", "100", " ", "|", "100", " ", "|", "100", " ", "|", "100", " ", "|", "75", " " ]

[]

specialisation domains in Georgia ....................................................... 18 Table VII. Selected S&T specialisation domains in Moldova .................................................... 19 Table VIII. Selected S&T specialisation domains in Ukraine .................................................... 21 Table 2.1. Orbis data availability – Number of enterprises for which at least one data observation is available for 2011-2019 ............................................................................................ 38 Table 2.2. Thresholds used to identify economic specialisations .......................................... 40 Table 2.3. Economic mapping results for Georgia ........................................................................ 41 Table 2.4. Economic mapping results for Moldova ....................................................................... 44 Table 2.5. Economic mapping results for Ukraine ........................................................................ 46 Table 2.6. INDSTAT data availability at NACE three-digit level .............................................. 49 Table 2.7. Industries included in mapping the Manufacturing sector ................................. 52 Table 2.8. Thresholds used to identify economic specialisations in Manufacturing ..... 57 Table 2.9. Economic mapping results for Manufacturing for Armenia ................................ 58 Table 2.10. Economic mapping results for Manufacturing for Azerbaijan ........................ 59 Table 2.11. Economic mapping results for Manufacturing for Georgia .............................. 60 Table 2.12. Economic mapping results for Manufacturing for Moldova ............................. 61 Table 2.13. Economic mapping results for Manufacturing for Ukraine .............................. 62 Table 2.14. Available three-digit goods export data (number of goods categories) ....64 Table 2.15. Thresholds used to identify goods export specialisations ............................... 65 Table 2.16. Goods export specialisation for Armenia ................................................................. 66 Table 2.17. Goods export specialisation for Azerbaijan ............................................................. 68 Table 2.18. Goods export specialisation for Georgia .................................................................. 69 Table 2.19. Goods export specialisation for Moldova ................................................................. 71 Table 2.20. Goods export specialisation for Ukraine ................................................................... 75 Table 2.21. Thresholds used to identify services export specialisations ........................... 80 Smart Specialisation in the Eastern Partnership countries - Potential for knowledge-based economic cooperation265 Table 2.22. Services export specialisation for Armenia ............................................................. 81 Table 2.23. Services export specialisation for Azerbaijan ........................................................ 82 Table 2.24. Services export specialisation for Georgia .............................................................. 82 Table 2.25. Services export specialisation for Moldova ............................................................. 83 Table 2.26. Services export specialisation for Ukraine .............................................................. 84 Table 2.27. Weighted number of enterprises covered in the Enterprise Survey ............ 86 Table 2.28. Share of product, process and product and/or process innovators ............. 87 Table 2.29. Specialisation in innovation ............................................................................................ 89 Table 2.30. Number of patents for 2011-2018 ............................................................................ 91 Table 2.31. Industries with innovation potential based on 2011-2018 relative patent performance .................................................................................................................................................... 92 Table 2.32. Specialised industries using data for patents issued ......................................... 94 Table 2.33. Specialised industries using data for patent families* ...................................... 96 Table 2.34. Partial concordance between broad NACE groups and NICE ...........................

[ "specialisation", "domains", "in", "Georgia", ".......................................................", "18", "\n", "Table", "VII", ".", "Selected", "S&T", "specialisation", "domains", "in", "Moldova", "....................................................", "19", "\n", "Table", "VIII", ".", "Selected", "S&T", "specialisation", "domains", "in", "Ukraine", "....................................................", "21", "\n", "Table", "2.1", ".", "Orbis", "data", "availability", "–", "Number", "of", "enterprises", "for", "which", "at", "least", "one", "data", "\n", "observation", "is", "available", "for", "2011", "-", "2019", "............................................................................................", "38", "\n", "Table", "2.2", ".", "Thresholds", "used", "to", "identify", "economic", "specialisations", "..........................................", "40", "\n", "Table", "2.3", ".", "Economic", "mapping", "results", "for", "Georgia", "........................................................................", "41", "\n", "Table", "2.4", ".", "Economic", "mapping", "results", "for", "Moldova", ".......................................................................", "44", "\n", "Table", "2.5", ".", "Economic", "mapping", "results", "for", "Ukraine", "........................................................................", "46", "\n", "Table", "2.6", ".", "INDSTAT", "data", "availability", "at", "NACE", "three", "-", "digit", "level", "..............................................", "49", "\n", "Table", "2.7", ".", "Industries", "included", "in", "mapping", "the", "Manufacturing", "sector", ".................................", "52", "\n", "Table", "2.8", ".", "Thresholds", "used", "to", "identify", "economic", "specialisations", "in", "Manufacturing", ".....", "57", "\n", "Table", "2.9", ".", "Economic", "mapping", "results", "for", "Manufacturing", "for", "Armenia", "................................", "58", "\n", "Table", "2.10", ".", "Economic", "mapping", "results", "for", "Manufacturing", "for", "Azerbaijan", "........................", "59", "\n", "Table", "2.11", ".", "Economic", "mapping", "results", "for", "Manufacturing", "for", "Georgia", "..............................", "60", "\n", "Table", "2.12", ".", "Economic", "mapping", "results", "for", "Manufacturing", "for", "Moldova", ".............................", "61", "\n", "Table", "2.13", ".", "Economic", "mapping", "results", "for", "Manufacturing", "for", "Ukraine", "..............................", "62", "\n", "Table", "2.14", ".", "Available", "three", "-", "digit", "goods", "export", "data", "(", "number", "of", "goods", "categories", ")", "....", "64", "\n", "Table", "2.15", ".", "Thresholds", "used", "to", "identify", "goods", "export", "specialisations", "...............................", "65", "\n", "Table", "2.16", ".", "Goods", "export", "specialisation", "for", "Armenia", ".................................................................", "66", "\n", "Table", "2.17", ".", "Goods", "export", "specialisation", "for", "Azerbaijan", ".............................................................", "68", "\n", "Table", "2.18", ".", "Goods", "export", "specialisation", "for", "Georgia", "..................................................................", "69", "\n", "Table", "2.19", ".", "Goods", "export", "specialisation", "for", "Moldova", ".................................................................", "71", "\n", "Table", "2.20", ".", "Goods", "export", "specialisation", "for", "Ukraine", "...................................................................", "75", "\n", "Table", "2.21", ".", "Thresholds", "used", "to", "identify", "services", "export", "specialisations", "...........................", "80", "\n", "Smart", "Specialisation", "in", "the", "Eastern", "Partnership", "countries", "-", "Potential", "for", "knowledge", "-", "based", "economic", "cooperation265", "\n", "Table", "2.22", ".", "Services", "export", "specialisation", "for", "Armenia", ".............................................................", "81", "\n", "Table", "2.23", ".", "Services", "export", "specialisation", "for", "Azerbaijan", "........................................................", "82", "\n", "Table", "2.24", ".", "Services", "export", "specialisation", "for", "Georgia", "..............................................................", "82", "\n", "Table", "2.25", ".", "Services", "export", "specialisation", "for", "Moldova", ".............................................................", "83", "\n", "Table", "2.26", ".", "Services", "export", "specialisation", "for", "Ukraine", "..............................................................", "84", "\n", "Table", "2.27", ".", "Weighted", "number", "of", "enterprises", "covered", "in", "the", "Enterprise", "Survey", "............", "86", "\n", "Table", "2.28", ".", "Share", "of", "product", ",", "process", "and", "product", "and/or", "process", "innovators", ".............", "87", "\n", "Table", "2.29", ".", "Specialisation", "in", "innovation", "............................................................................................", "89", "\n", "Table", "2.30", ".", "Number", "of", "patents", "for", "2011", "-", "2018", "............................................................................", "91", "\n", "Table", "2.31", ".", "Industries", "with", "innovation", "potential", "based", "on", "2011", "-", "2018", "relative", "patent", "\n", "performance", "....................................................................................................................................................", "92", "\n", "Table", "2.32", ".", "Specialised", "industries", "using", "data", "for", "patents", "issued", ".........................................", "94", "\n", "Table", "2.33", ".", "Specialised", "industries", "using", "data", "for", "patent", "families", "*", "......................................", "96", "\n", "Table", "2.34", ".", "Partial", "concordance", "between", "broad", "NACE", "groups", "and", "NICE", "..........................." ]

[]

| 4,7 ₋₁ | 10,7 ₋₁ 12,7 | 24 470 ₋₂ 11 676 ₋₂ | 24 268 ₋₂ 28 | 782 ₋₂ | ₋₂ 53 195 ₋₂ 18 | ₋₂ 18 ₋₂ | 21 ₋₂ | 39 ₋₂ 39 ₋₂ | LUX | | 5,4 ₋₂ 1,2 ₋₁ | ₋₂ 7,7 | … | 11 514 ₋₂ 17 | 773 ₋₂ 20 | 927 ₋₂ 22 | ₋₂ 22 ₋₂ | 33 ₋₂ | | MLT | | | | | | … | … 6 | ₋₁ 4 ₋₁ | 8 ₋₁ | 1 ₋₁ | | | | | | … | | | | | | MCO | | … | … | … | … 12 | … | … | … … | … | … | MNE | | 5,1 ₋₁ | 11,6 ₋₁ | 9008 ₋₂ | 767 ₋₂ 16 | 046 ₋₂ 21 | 412 ₋₂ | 19 | 24 | 32 ₋₂ | NLD | | … | … | … | | | | 13 ₋₂ … | ₋₂ … | … | | | 4,0 ₋₁ | 10,1 ₋₁ | 210 ₋₂ | … | … | | | ₋₂ … | | MKD | | | | 17 8087 ₋₂ | … 907 ₋₂ | 052 ₋₂ | 29 270 ₋₂ 19 | ₋₂ 20 ₋₂ 26 ₋₂ | 24 ₋₂ | 33 ₋₂ | NOR | | 4,7 ₋₂ 4,8 ₋₂ | 11,2 ₋₂ 9,7 ₋₂ | 17 10 641 ₋₂ 6270 ₋₂ | 21 7979 | ₋₂ | 12 195 ₋₂ 20 16 | ₋₂ ₋₂ 25 ₋₂ | 20 ₋₂ 29 ₋₂ | 30 ₋₂ 21 ₋₂ | POL PRT | | 6,3 | 15,8 ₋₁ | 4838 ₋₁ | 9794 ₋₂ 11 ₋₁ | 355 ₋₂ 3299 ₋₁ | 8297 ₋₂ 3873 ₋₁ 32 | ₋₁ 21 ₋₁ | | 25 ₋₁ | | | 3,3 ₋₂ | 8,1 ₋₂ | 5009 ₋₂ | 3206 3321 | | | 9 ₋₂ | 22 | 26 ₋₂ | MDA | | 4,1 ₋₁ | 8,9 ₋₃ | … | ₋₂ | 7013 ₋₂ | 9786 ₋₂ 13 | ₋₂ … | ₋₁ 18 ₋₂ | | ROU RUS | | | | | | … | 6872 | | … | 19 | | | 3,4 ₋₁ | 7,5 ₋₁ | 15 337 ₋₂ |

[ "|", "4,7", "₋₁", " ", "|", "10,7", "₋₁", "12,7", " ", "|", "24", "470", "₋₂", "11", "676", "₋₂", " ", "|", "24", "268", "₋₂", "28", " ", "|", "782", "₋₂", " ", "|", "₋₂", "53", "195", "₋₂", "18", " ", "|", "₋₂", "18", "₋₂", " ", "|", "21", "₋₂", " ", "|", "39", "₋₂", "39", "₋₂", " ", "|", "LUX", " ", "|", "\n", "|", "5,4", "₋₂", "1,2", "₋₁", " ", "|", "₋₂", "7,7", " ", "|", "…", " ", "|", "11", "514", "₋₂", "17", " ", "|", "773", "₋₂", "20", " ", "|", "927", "₋₂", "22", " ", "|", "₋₂", "22", "₋₂", " ", "|", "33", "₋₂", " ", "|", " ", "|", "MLT", " ", "|", "\n", "|", " ", "|", " ", "|", " ", "|", " ", "|", "…", " ", "|", "…", "6", " ", "|", "₋₁", "4", "₋₁", " ", "|", "8", "₋₁", " ", "|", "1", "₋₁", " ", "|", " ", "|", "\n", "|", " ", "|", " ", "|", " ", "|", "…", " ", "|", " ", "|", " ", "|", " ", "|", " ", "|", " ", "|", "MCO", " ", "|", "\n", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", "…", "12", " ", "|", "…", " ", "|", "…", " ", "|", "…", "…", " ", "|", "…", " ", "|", "…", " ", "|", "MNE", " ", "|", "\n", "|", "5,1", "₋₁", " ", "|", "11,6", "₋₁", " ", "|", "9008", "₋₂", " ", "|", "767", "₋₂", "16", " ", "|", "046", "₋₂", "21", " ", "|", "412", "₋₂", " ", "|", "19", " ", "|", "24", " ", "|", "32", "₋₂", " ", "|", "NLD", " ", "|", "\n", "|", "…", " ", "|", "…", " ", "|", "…", " ", "|", " ", "|", " ", "|", " ", "|", "13", "₋₂", "…", " ", "|", "₋₂", "…", " ", "|", "…", " ", "|", " ", "|", "\n", "|", "4,0", "₋₁", " ", "|", "10,1", "₋₁", " ", "|", "210", "₋₂", " ", "|", "…", " ", "|", "…", " ", "|", " ", "|", " ", "|", "₋₂", "…", " ", "|", " ", "|", "MKD", " ", "|", "\n", "|", " ", "|", " ", "|", "17", "8087", "₋₂", " ", "|", "…", "907", "₋₂", " ", "|", "052", "₋₂", " ", "|", "29", "270", "₋₂", "19", " ", "|", "₋₂", "20", "₋₂", "26", "₋₂", " ", "|", "24", "₋₂", " ", "|", "33", "₋₂", " ", "|", "NOR", " ", "|", "\n", "|", "4,7", "₋₂", "4,8", "₋₂", " ", "|", "11,2", "₋₂", "9,7", "₋₂", " ", "|", "17", "10", "641", "₋₂", "6270", "₋₂", " ", "|", "21", "7979", " ", "|", "₋₂", " ", "|", "12", "195", "₋₂", "20", "16", " ", "|", "₋₂", "₋₂", "25", "₋₂", " ", "|", "20", "₋₂", "29", "₋₂", " ", "|", "30", "₋₂", "21", "₋₂", " ", "|", "POL", "PRT", " ", "|", "\n", "|", "6,3", " ", "|", "15,8", "₋₁", " ", "|", "4838", "₋₁", " ", "|", "9794", "₋₂", "11", "₋₁", " ", "|", "355", "₋₂", "3299", "₋₁", " ", "|", "8297", "₋₂", "3873", "₋₁", "32", " ", "|", "₋₁", "21", "₋₁", " ", "|", " ", "|", "25", "₋₁", " ", "|", " ", "|", "\n", "|", "3,3", "₋₂", " ", "|", "8,1", "₋₂", " ", "|", "5009", "₋₂", " ", "|", "3206", "3321", " ", "|", " ", "|", " ", "|", "9", "₋₂", " ", "|", "22", " ", "|", "26", "₋₂", " ", "|", "MDA", " ", "|", "\n", "|", "4,1", "₋₁", " ", "|", "8,9", "₋₃", " ", "|", "…", " ", "|", "₋₂", " ", "|", "7013", "₋₂", " ", "|", "9786", "₋₂", "13", " ", "|", "₋₂", "…", " ", "|", "₋₁", "18", "₋₂", " ", "|", " ", "|", "ROU", "RUS", " ", "|", "\n", "|", " ", "|", " ", "|", " ", "|", " ", "|", "…", " ", "|", "6872", " ", "|", " ", "|", "…", " ", "|", "19", " ", "|", " ", "|", "\n", "|", "3,4", "₋₁", " ", "|", "7,5", "₋₁", " ", "|", "15", "337", "₋₂", " ", "|" ]

[]

loop can connect enablers and features of public intent data with greater development value Source: WDR 2021 team.deliveryFinancing Technical capacit yG overnance Data demandEnablers of public in tent data Desirable features of public in tent data Adequat e coverage Completeness Timeliness FrequencyHigh quality Granularity Accurac y ComparabilityEasy to use Accessibility Understandability Interoperability Safe to use Impartiality Conﬁdentiality Appropriateness Value of public in tent data Impr oved service scar ce resour cesPrioritization of empow ermentAccountability and 66 | World Development Report 2021 Underinvestment by governments. Underinvestment in public intent data systems is widespread. Only half of countries had a national statistical plan that was fully funded in 2019 (figure 2.7). 70 Lack of national funding for statistics is especially a struggle for frag - ile and conflict-affected countries, countries in Sub- Saharan Africa, and low-income countries. Whereas 93 percent of high-income countries have a fully funded national statistical plan, not a single low-income country has one. A recent review of public financing of statistics found that seven of 10 low- and middle- income countries analyzed funded less than half of their respective national statistical plans, with country contributions ranging from 9 percent to 77 percent. 71 This problem is more pressing in low-income countries with less government revenue to spend on multiple priorities. However, the cost of public data systems is modest relative to that of other government functions. Decision-makers in budget offices may not fully understand how much funding is needed to produce high-quality data or lack the incentives to prioritize data. How well public data systems are funded is thus also a matter of high-level government officials recognizing the value of public intent data and offering leadership to encourage col-lection of them. 72 A key factor in such an effort is the perceived relevance and credibility of public intent data and its producers. 73 Another reason for lack of funding for data is the absence of a benchmark guiding how much govern-ments should spend, unlike for other areas of gov - ernment spending. For example, the Education 2030 Framework for Action urges countries to allocate at least 4–6 percent of GDP or at least 15–20 percent of their total public expenditure to education. The Abuja Declaration urges countries to spend at least 15 percent of their annual budget to improve the health sector. 74 No similar guidelines are found on data. Underinvestment by donors. Donors also invest rel- atively

[ "loop", "can", "connect", "enablers", "and", "features", "of", "public", "\n", "intent", "data", "with", "greater", "development", "value", "\n", "Source", ":", "WDR", "2021", "team.deliveryFinancing", "Technical", "capacit", "yG", "overnance", "Data", "demandEnablers", " ", "of", "public", "in", "tent", "data", "\n", "Desirable", "features", "of", "public", "in", "tent", "data", "\n", "Adequat", "e", "coverage", "\n", "Completeness", "\n", "Timeliness", "\n", "FrequencyHigh", "quality", "\n", "Granularity", "\n", "Accurac", "y", "\n", "ComparabilityEasy", " ", "to", "use", "\n", "Accessibility", "\n", "Understandability", "\n", "Interoperability", "Safe", "to", "use", "\n", "Impartiality", "\n", "Conﬁdentiality", "\n", "Appropriateness", "\n", "Value", "of", "public", "in", "tent", "data", "\n", "Impr", "oved", "service", "\n", "scar", "ce", "resour", "cesPrioritization", "of", "\n", "empow", "ermentAccountability", "and", "\n", "66", " ", "|", " ", "World", "Development", "Report", "2021", "\n", "Underinvestment", "by", "governments", ".", "Underinvestment", "\n", "in", "public", "intent", "data", "systems", "is", "widespread", ".", "Only", "half", "\n", "of", "countries", "had", "a", "national", "statistical", "plan", "that", "was", "fully", "funded", "in", "2019", "(", "figure", "2.7", ")", ".", "\n", "70", "Lack", "of", "national", "\n", "funding", "for", "statistics", "is", "especially", "a", "struggle", "for", "frag", "-", "\n", "ile", "and", "conflict", "-", "affected", "countries", ",", "countries", "in", "Sub-", " \n", "Saharan", "Africa", ",", "and", "low", "-", "income", "countries", ".", "Whereas", " \n", "93", "percent", "of", "high", "-", "income", "countries", "have", "a", "fully", "funded", "national", "statistical", "plan", ",", "not", "a", "single", "low", "-", "income", "country", "has", "one", ".", "A", "recent", "review", "of", "public", "financing", "of", "statistics", "found", "that", "seven", "of", "10", "low-", "and", "middle-", " \n", "income", "countries", "analyzed", "funded", "less", "than", "half", "of", "their", "respective", "national", "statistical", "plans", ",", "with", "country", "contributions", "ranging", "from", "9", "percent", "to", "77", "percent", ".", "\n", "71", "\n", "This", "problem", "is", "more", "pressing", "in", "low", "-", "income", "\n", "countries", "with", "less", "government", "revenue", "to", "spend", "on", "multiple", "priorities", ".", "However", ",", "the", "cost", "of", "public", "data", "systems", "is", "modest", "relative", "to", "that", "of", "other", "government", "functions", ".", "Decision", "-", "makers", "in", "budget", "offices", "may", "not", "fully", "understand", "how", "much", "funding", "is", "needed", "to", "produce", "high", "-", "quality", "data", "or", "lack", "the", "incentives", "to", "prioritize", "data", ".", "How", "well", "public", "data", "systems", "are", "funded", "is", "thus", "also", "a", "matter", "of", "high", "-", "level", "government", "officials", "recognizing", "the", "value", "of", "public", "intent", "data", "and", "offering", "leadership", "to", "encourage", "col", "-", "lection", "of", "them", ".", "\n", "72", "A", "key", "factor", "in", "such", "an", "effort", "is", "the", "perceived", "relevance", "and", "credibility", "of", "public", "intent", "data", "and", "its", "producers", ".", "\n", "73", "\n", "Another", "reason", "for", "lack", "of", "funding", "for", "data", "is", "the", "\n", "absence", "of", "a", "benchmark", "guiding", "how", "much", "govern", "-", "ments", "should", "spend", ",", "unlike", "for", "other", "areas", "of", "gov", "-", "\n", "ernment", "spending", ".", "For", "example", ",", "the", "Education", "2030", "Framework", "for", "Action", "urges", "countries", "to", "allocate", "at", "least", "4–6", "percent", "of", "GDP", "or", "at", "least", "15–20", "percent", "of", "their", "total", "public", "expenditure", "to", "education", ".", "The", "Abuja", "Declaration", "urges", "countries", "to", "spend", "at", "least", " \n", "15", "percent", "of", "their", "annual", "budget", "to", "improve", "the", "health", "sector", ".", "\n", "74", "No", "similar", "guidelines", "are", "found", "on", "data", ".", "\n", "Underinvestment", "by", "donors", ".", "Donors", "also", "invest", "rel-", "\n", "atively" ]

[ { "end": 207, "label": "CITATION_SPAN", "start": 101 } ]

leverage is notable especially in the case of pipeline gas, where the possibility of rerouting gas flows is more limited as shown by the latest unsuccessful efforts by Russia. During the 2022 crisis, for example, intra-EU competition for natural gas between actors willing to pay high prices contributed to an excessive and unnecessary rise in prices. In response, the EU introduced a coordination mechanism to aggregate and match demand with competitive supply offers (AggregateEU), but there is no obligation for joint purchasing on the platform. At the same time, although natural gas prices have fallen considerably from their peaks during the energy crisis, the EU faces an increasingly volatile outlook. With the loss of access to Russian pipeline gas, 42% of EU gas imports arrived as LNG in 2023, 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

[ "leverage", "is", "notable", "especially", "in", "the", "case", "of", "pipeline", "gas", ",", "where", "the", "possibility", "of", "\n", "rerouting", "gas", "flows", "is", "more", "limited", "as", "shown", "by", "the", "latest", "unsuccessful", "efforts", "by", "Russia", ".", "During", "the", "2022", "crisis", ",", "for", "\n", "example", ",", "intra", "-", "EU", "competition", "for", "natural", "gas", "between", "actors", "willing", "to", "pay", "high", "prices", "contributed", "to", "an", "excessive", "\n", "and", "unnecessary", "rise", "in", "prices", ".", "In", "response", ",", "the", "EU", "introduced", "a", "coordination", "mechanism", "to", "aggregate", "and", "match", "\n", "demand", "with", "competitive", "supply", "offers", "(", "AggregateEU", ")", ",", "but", "there", "is", "no", "obligation", "for", "joint", "purchasing", "on", "the", "platform", ".", "\n", "At", "the", "same", "time", ",", "although", "natural", "gas", "prices", "have", "fallen", "considerably", "from", "their", "peaks", "during", "the", "energy", "crisis", ",", "the", "\n", "EU", "faces", "an", "increasingly", "volatile", "outlook", ".", "With", "the", "loss", "of", "access", "to", "Russian", "pipeline", "gas", ",", "42", "%", "of", "EU", "gas", "imports", "\n", "arrived", "as", "LNG", "in", "2023", ",", "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" ]

[ { "end": 1938, "label": "CITATION_REF", "start": 1935 } ]

and/or some other example(s) herein, wherein retasking the MHU includes: causing the MHU to move from a current location within the MRF to a service center when an operating condition of the MHUs indicates that service is needed. Example [0238] includes the method of examples [0231]-[0237] and/or some other example(s) herein, wherein, when the MHU is a conveyor system, retasking the MHU includes: causing the conveyor system to change a speed, direction, or orientation of a conveyor mechanism. Example [0239] includes the method of examples [0231]-[0238] and/or some other example(s) herein, wherein, when the MHU is a baling system, to retasking the MHU includes: causing the baling system to change a baling process based on a composition of the material stream. Example [0240] includes the method of example [0239] and/or some other example(s) herein, wherein retasking the MHU includes: causing the baling system to queue material bales based on material composition such that individual material bales have different purity levels. Example [0241] includes the method of examples [0231]-[0240] and/or some other example(s) herein, wherein, when the MHU is an infeed system, retasking the MHU includes: autonomously controlling the infeed system to infeed different combinations of materials to achieve semi-homogeneous material distribution. Example [0242] includes the method of examples [0231]-[0241] and/or some other example(s) herein, wherein retasking the MHU includes: causing the MHU to activate or deactivate one or more sorting technologies to optimize resource consumption by the MHU. Example [0243] includes the method of examples [0228]-[0242] and/or some other example(s) herein, wherein the method includes operating a first machine learning model to perform the identification and classification of objects within the material stream based on the data streams. Example [0244] includes the method of example [0243] and/or some other example(s) herein, wherein the method includes operating a second machine learning model to determine the MRF arrangement. Example [0245] includes the method of example [0244] and/or some other example(s) herein, wherein the first machine learning model is different than the second machine learning model. Example [0246] includes the method of examples [0228]-[0245] and/or some other example(s) herein, wherein the MRF arrangement is based on a flow the material stream to one or more MHUs of the set of MHUs to achieve load balancing among the set of MHUs. Example [0247] includes the method of example [0228]-[0246] and/or some other example(s) herein, wherein the set of MHUs include one or more of

[ "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "retasking", "the", "MHU", "includes", ":", "causing", "the", "MHU", "to", "move", "from", "a", "current", "location", "within", "the", "MRF", "to", "a", "service", "center", "when", "an", "operating", "condition", "of", "the", "MHUs", "indicates", "that", "service", "is", "needed", ".", "\n\n", "Example", "[", "0238", "]", "includes", "the", "method", "of", "examples", "[", "0231]-[0237", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", ",", "when", "the", "MHU", "is", "a", "conveyor", "system", ",", "retasking", "the", "MHU", "includes", ":", "causing", "the", "conveyor", "system", "to", "change", "a", "speed", ",", "direction", ",", "or", "orientation", "of", "a", "conveyor", "mechanism", ".", "\n\n", "Example", "[", "0239", "]", "includes", "the", "method", "of", "examples", "[", "0231]-[0238", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", ",", "when", "the", "MHU", "is", "a", "baling", "system", ",", "to", "retasking", "the", "MHU", "includes", ":", "causing", "the", "baling", "system", "to", "change", "a", "baling", "process", "based", "on", "a", "composition", "of", "the", "material", "stream", ".", "\n\n", "Example", "[", "0240", "]", "includes", "the", "method", "of", "example", "[", "0239", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "retasking", "the", "MHU", "includes", ":", "causing", "the", "baling", "system", "to", "queue", "material", "bales", "based", "on", "material", "composition", "such", "that", "individual", "material", "bales", "have", "different", "purity", "levels", ".", "\n\n", "Example", "[", "0241", "]", "includes", "the", "method", "of", "examples", "[", "0231]-[0240", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", ",", "when", "the", "MHU", "is", "an", "infeed", "system", ",", "retasking", "the", "MHU", "includes", ":", "autonomously", "controlling", "the", "infeed", "system", "to", "infeed", "different", "combinations", "of", "materials", "to", "achieve", "semi", "-", "homogeneous", "material", "distribution", ".", "\n\n", "Example", "[", "0242", "]", "includes", "the", "method", "of", "examples", "[", "0231]-[0241", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "retasking", "the", "MHU", "includes", ":", "causing", "the", "MHU", "to", "activate", "or", "deactivate", "one", "or", "more", "sorting", "technologies", "to", "optimize", "resource", "consumption", "by", "the", "MHU", ".", "\n\n", "Example", "[", "0243", "]", "includes", "the", "method", "of", "examples", "[", "0228]-[0242", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "the", "method", "includes", "operating", "a", "first", "machine", "learning", "model", "to", "perform", "the", "identification", "and", "classification", "of", "objects", "within", "the", "material", "stream", "based", "on", "the", "data", "streams", ".", "\n\n", "Example", "[", "0244", "]", "includes", "the", "method", "of", "example", "[", "0243", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "the", "method", "includes", "operating", "a", "second", "machine", "learning", "model", "to", "determine", "the", "MRF", "arrangement", ".", "\n\n", "Example", "[", "0245", "]", "includes", "the", "method", "of", "example", "[", "0244", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "the", "first", "machine", "learning", "model", "is", "different", "than", "the", "second", "machine", "learning", "model", ".", "\n\n", "Example", "[", "0246", "]", "includes", "the", "method", "of", "examples", "[", "0228]-[0245", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "the", "MRF", "arrangement", "is", "based", "on", "a", "flow", "the", "material", "stream", "to", "one", "or", "more", "MHUs", "of", "the", "set", "of", "MHUs", "to", "achieve", "load", "balancing", "among", "the", "set", "of", "MHUs", ".", "\n\n", "Example", "[", "0247", "]", "includes", "the", "method", "of", "example", "[", "0228]-[0246", "]", "and/or", "some", "other", "example(s", ")", "herein", ",", "wherein", "the", "set", "of", "MHUs", "include", "one", "or", "more", "of" ]

[]

of mintegers. 2.8 SciDetect Method The next approach [21] was invented to detect documents automatically generated using the software SCIGen, MathGen, PropGen and PhysGen. For this, the distancesbetween a text and others (inter-textual distances) are computed. Then these distancesare used to determine which texts, within a large set, are closer to each other and maythus be grouped together. Inter-textual distance depends on four factors: genre, author,subject and epoch. As the authors don ’t provide any numerical results of the method ’s work, we have implemented the method using the source Java code provided by SciDetect developers. 3 Choosing a Method Every arti ﬁcial content is generated for a speci ﬁc purpose. Here we focus only on fake scienti ﬁc paper for academic publishing or increase in the percentage of originality of the article. It is important to recognize the aim of fake content for its subsequent detection. Various generation strategies require different approaches to ﬁnd it. For example, algorithms for detecting word salad are clearly possible and are not particularly dif ﬁcult to implement. A statistical approach based on Zipf ’s law of word frequency has potential in detecting simple word salad, as do grammar checking and the use of naturallanguage processing. Statistical Markovian analysis, where short phrases are used todetermine if they can occur in normal English sentences, is another statistical approach that would be effective against completely random phrasing but might be fooled by dissociated press methods. Combining linguistic and statistical features can improvethe result of experiment. By contrast, texts generated with stochastic language modelsappear much harder to detect. One also needs to estimate the data capacity. Text corpuses are taken depending on the aim of the experiment and capabilities of getting them. Like a generation strategy,every data capacity needs different approach. For instance, small trainings samplespermit to use such indexes as Jaccard or Dice [ 5] to count the similarity measure or distance between documents. For big datasets, one can use some linguistics features424 D. Beresneva and variations of Support Vector Machine and Decision Trees algorithms. Table 1 summarizes results of described methods. The numerical results are provided by theauthors of the articles, except the last one. 4 Conclusion This work presents the results of a systematic review of arti ﬁcial content detection methods. About a hundred articles were considered for this review; perhaps one-sixthof them met our selection criteria. All the presented methods give good result

[ "of", "mintegers", ".", "\n", "2.8", "SciDetect", "Method", "\n", "The", "next", "approach", "[", "21", "]", "was", "invented", "to", "detect", "documents", "automatically", "generated", "\n", "using", "the", "software", "SCIGen", ",", "MathGen", ",", "PropGen", "and", "PhysGen", ".", "For", "this", ",", "the", "distancesbetween", "a", "text", "and", "others", "(", "inter", "-", "textual", "distances", ")", "are", "computed", ".", "Then", "these", "distancesare", "used", "to", "determine", "which", "texts", ",", "within", "a", "large", "set", ",", "are", "closer", "to", "each", "other", "and", "maythus", "be", "grouped", "together", ".", "Inter", "-", "textual", "distance", "depends", "on", "four", "factors", ":", "genre", ",", "author", ",", "subject", "and", "epoch", ".", "\n", "As", "the", "authors", "don", "’", "t", "provide", "any", "numerical", "results", "of", "the", "method", "’s", "work", ",", "we", "have", "\n", "implemented", "the", "method", "using", "the", "source", "Java", "code", "provided", "by", "SciDetect", "developers", ".", "\n", "3", "Choosing", "a", "Method", "\n", "Every", "arti", "ﬁcial", "content", "is", "generated", "for", "a", "speci", "ﬁc", "purpose", ".", "Here", "we", "focus", "only", "on", "fake", "\n", "scienti", "ﬁc", "paper", "for", "academic", "publishing", "or", "increase", "in", "the", "percentage", "of", "originality", "of", "\n", "the", "article", ".", "\n", "It", "is", "important", "to", "recognize", "the", "aim", "of", "fake", "content", "for", "its", "subsequent", "detection", ".", "\n", "Various", "generation", "strategies", "require", "different", "approaches", "to", "ﬁnd", "it", ".", "For", "example", ",", "\n", "algorithms", "for", "detecting", "word", "salad", "are", "clearly", "possible", "and", "are", "not", "particularly", "dif", "ﬁcult", "\n", "to", "implement", ".", "A", "statistical", "approach", "based", "on", "Zipf", "’s", "law", "of", "word", "frequency", "has", "\n", "potential", "in", "detecting", "simple", "word", "salad", ",", "as", "do", "grammar", "checking", "and", "the", "use", "of", "naturallanguage", "processing", ".", "Statistical", "Markovian", "analysis", ",", "where", "short", "phrases", "are", "used", "todetermine", "if", "they", "can", "occur", "in", "normal", "English", "sentences", ",", "is", "another", "statistical", "approach", "\n", "that", "would", "be", "effective", "against", "completely", "random", "phrasing", "but", "might", "be", "fooled", "by", "\n", "dissociated", "press", "methods", ".", "Combining", "linguistic", "and", "statistical", "features", "can", "improvethe", "result", "of", "experiment", ".", "By", "contrast", ",", "texts", "generated", "with", "stochastic", "language", "modelsappear", "much", "harder", "to", "detect", ".", "\n", "One", "also", "needs", "to", "estimate", "the", "data", "capacity", ".", "Text", "corpuses", "are", "taken", "depending", "on", "\n", "the", "aim", "of", "the", "experiment", "and", "capabilities", "of", "getting", "them", ".", "Like", "a", "generation", "strategy", ",", "every", "data", "capacity", "needs", "different", "approach", ".", "For", "instance", ",", "small", "trainings", "samplespermit", "to", "use", "such", "indexes", "as", "Jaccard", "or", "Dice", "[", "5", "]", "to", "count", "the", "similarity", "measure", "or", "\n", "distance", "between", "documents", ".", "For", "big", "datasets", ",", "one", "can", "use", "some", "linguistics", "features424", "D.", "Beresneva", "\n", "and", "variations", "of", "Support", "Vector", "Machine", "and", "Decision", "Trees", "algorithms", ".", "Table", "1", "\n", "summarizes", "results", "of", "described", "methods", ".", "The", "numerical", "results", "are", "provided", "by", "theauthors", "of", "the", "articles", ",", "except", "the", "last", "one", ".", "\n", "4", "Conclusion", "\n", "This", "work", "presents", "the", "results", "of", "a", "systematic", "review", "of", "arti", "ﬁcial", "content", "detection", "\n", "methods", ".", "About", "a", "hundred", "articles", "were", "considered", "for", "this", "review", ";", "perhaps", "one", "-", "sixthof", "them", "met", "our", "selection", "criteria", ".", "All", "the", "presented", "methods", "give", "good", "result" ]

[ { "end": 56, "label": "CITATION_ID", "start": 54 }, { "end": 2035, "label": "CITATION_ID", "start": 2034 } ]

extreme poverty. 59 It is therefore difficult to under - stand changes in living standards over time and design policies to eradicate poverty. Recent innova-tions in data collection in these countries suggest a slightly more optimistic picture for the future. 60 It is also important to note that some lack of comparabil-ity over time is necessary, particularly when adopting new global standards. When data are not easy to use: Lack of accessibility, understandability, and interoperabilityLack of data accessibility prohibits actors from using data. According to an assessment of the Open Data Inventory, lower-income countries lag far behind in overall data openness (table 2.1), although even high- income countries have mediocre openness scores. Only 11 percent of low-income countries consistently make data available with a license classifiable as open, compared with 19 percent of lower-middle-income countries, 22 percent of upper-middle-income coun-tries, and 44 percent of high-income countries. The Open Data Inventory assessment also reveals some limitations to machine readability. To the extent that governments publish official statistics, only 37 percent of low-income countries make at least some of these available in machine readable formats, compared with 51 percent of lower-middle-income countries, 61 percent of upper-middle-income coun-tries, and 81 percent of high-income countries. One reason for lack of data accessibility is that data systems in the public sector can be very fragmented. The health sector, for example, often has many dif - ferent health information systems because of its ten-dency to have many different service providers. These include many private providers whose data are often Data as a force for public good | 63 unavailable to the Ministry of Health. In Ethiopia, a study of the health sector found 228 different digital health information applications, of which only 39 per - cent sent data to the Ministry of Health. 61 Administra- tive data, in particular, are too often siloed in different systems, prohibiting their effective use for monitoring and policy design. Although data coordination within agencies is often limited, the challenge of siloed sys-tems is even greater across government agencies. 62 Lack of understandability prevents even those data that are accessible from generating value. To be understandable, data must be well disseminated, backed up with sufficient metadata, responsive to user needs, and, for certain purposes, summarized and visualized for the user. A majority of countries have data portals and provide metadata for their pub-lished data—practices that facilitate wider data use. 63 Low-income

[ "extreme", "poverty", ".", "\n", "59", "It", "is", "therefore", "difficult", "to", "under", "-", "\n", "stand", "changes", "in", "living", "standards", "over", "time", "and", "design", "policies", "to", "eradicate", "poverty", ".", "Recent", "innova", "-", "tions", "in", "data", "collection", "in", "these", "countries", "suggest", "a", "slightly", "more", "optimistic", "picture", "for", "the", "future", ".", "\n", "60", "It", "is", "\n", "also", "important", "to", "note", "that", "some", "lack", "of", "comparabil", "-", "ity", "over", "time", "is", "necessary", ",", "particularly", "when", "adopting", "new", "global", "standards", ".", "\n", "When", "data", "are", "not", "easy", "to", "use", ":", " \n", "Lack", "of", "accessibility", ",", "understandability", ",", "and", "interoperabilityLack", "of", "data", "accessibility", "prohibits", "actors", "from", "using", "data", ".", "According", "to", "an", "assessment", "of", "the", "Open", "Data", "Inventory", ",", "lower", "-", "income", "countries", "lag", "far", "behind", "in", "overall", "data", "openness", "(", "table", "2.1", ")", ",", "although", "even", "high-", " \n", "income", "countries", "have", "mediocre", "openness", "scores", ".", "Only", "11", "percent", "of", "low", "-", "income", "countries", "consistently", "make", "data", "available", "with", "a", "license", "classifiable", "as", "open", ",", "compared", "with", "19", "percent", "of", "lower", "-", "middle", "-", "income", "countries", ",", "22", "percent", "of", "upper", "-", "middle", "-", "income", "coun", "-", "tries", ",", "and", "44", "percent", "of", "high", "-", "income", "countries", ".", "\n", "The", "Open", "Data", "Inventory", "assessment", "also", "reveals", "\n", "some", "limitations", "to", "machine", "readability", ".", "To", "the", " \n", "extent", "that", "governments", "publish", "official", "statistics", ",", "only", "37", "percent", "of", "low", "-", "income", "countries", "make", "at", "least", "some", "of", "these", "available", "in", "machine", "readable", "formats", ",", "compared", "with", "51", "percent", "of", "lower", "-", "middle", "-", "income", "countries", ",", "61", "percent", "of", "upper", "-", "middle", "-", "income", "coun", "-", "tries", ",", "and", "81", "percent", "of", "high", "-", "income", "countries", ".", "\n", "One", "reason", "for", "lack", "of", "data", "accessibility", "is", "that", "data", "\n", "systems", "in", "the", "public", "sector", "can", "be", "very", "fragmented", ".", "The", "health", "sector", ",", "for", "example", ",", "often", "has", "many", "dif", "-", "\n", "ferent", "health", "information", "systems", "because", "of", "its", "ten", "-", "dency", "to", "have", "many", "different", "service", "providers", ".", "These", "include", "many", "private", "providers", "whose", "data", "are", "often", "\n", "Data", "as", "a", "force", "for", "public", "good", " ", "|", " ", "63", "\n", "unavailable", "to", "the", "Ministry", "of", "Health", ".", "In", "Ethiopia", ",", "a", "\n", "study", "of", "the", "health", "sector", "found", "228", "different", "digital", "health", "information", "applications", ",", "of", "which", "only", "39", "per", "-", "\n", "cent", "sent", "data", "to", "the", "Ministry", "of", "Health", ".", "\n", "61", "Administra-", "\n", "tive", "data", ",", "in", "particular", ",", "are", "too", "often", "siloed", "in", "different", "systems", ",", "prohibiting", "their", "effective", "use", "for", "monitoring", "and", "policy", "design", ".", "Although", "data", "coordination", "within", "agencies", "is", "often", "limited", ",", "the", "challenge", "of", "siloed", "sys", "-", "tems", "is", "even", "greater", "across", "government", "agencies", ".", "\n", "62", "\n", "Lack", "of", "understandability", "prevents", "even", "those", "data", "\n", "that", "are", "accessible", "from", "generating", "value", ".", "To", "be", "understandable", ",", "data", "must", "be", "well", "disseminated", ",", "backed", "up", "with", "sufficient", "metadata", ",", "responsive", "to", "user", "needs", ",", "and", ",", "for", "certain", "purposes", ",", "summarized", "and", "visualized", "for", "the", "user", ".", "A", "majority", "of", "countries", "have", "data", "portals", "and", "provide", "metadata", "for", "their", "pub", "-", "lished", "data", "—", "practices", "that", "facilitate", "wider", "data", "use", ".", "\n", "63", "\n", "Low", "-", "income" ]

[]