dataesr/scientific-paragraphs-categorization huggingface dataset:
In our case, we found that a competitor had prepared a document presenting the typology of the various tailored offers on the market, prepared. This approach is based on the idea that actors submit to the reality of the environment. The culture of Resource Management to reach a goal is neglected in favor of reality exploitation. In the absence of many investigation resources, such as consulting, expensive databases, large sophisticated personal network, this little company only adapts to the shape of reality without being able to make it or to change it. Questioning works in a cascade, based on Sun Tzu's precepts selected at random. This channeling of Sun Tzu's precepts produces creativity in the questioning. It favors the generation of pertinent questions for which the absence of answer becomes an issue.
EVALUATioN oF THE LiNGUiSTiC DATA AND CLASSiFiCATioN oF THE JoRÁ LANGUAGE the present corpus of the Jorá language is taken from the above mentioned sources, that is in detail: 1. Wanda Hanke (WH); 2. françois-Xavier Béghin in his own publication (fXB); 3. b they used the vowel [ɨ]   c their language was difficult to learn data (sd). table 2 summarizes the numbers of entries from each source, the number of phrases therein, and also the number of uniquely occurring entries in each of the word lists 7 : the Jorá database is not large, but the amount of vocabulary allows for a classification of Jorá in comparison to other possibly related languages, not only on a lexical level, but also with respect to some grammatical characteristics. our word lists contains the following languages for comparison: siriono (Gasparini, our data), Yuki (Jabin, p.
c. ) 8 , Guarasu (generally known as Pauserna, von Horn fitz Gibbon, 1955), Guarayo  (Armoye, 2009) , Baure (danielsen, our data), and Proto-tupí-Guaraní (PtG, sources are indicated with the proto-forms). in our database, each entry (E) has an id in table 7 of the Appendix and throughout the text, e. g. E124 is "entry 124". BoLiViAN TUPÍ-GUARANÍ LANGUAGES oF SUBGRoUP ii (TG2)  Hanke (1959)  was the first one to compare Jorá to tupí-Guaraní languages and Baure (Arawakan), followed by  Loukotka (1963, p. 42-44) , who identified Jorá as a tupí language with no further specification  (Loukotka, 1963, p. 8). Later on, it was generally assumed that Jorá was a language in the same subgroup of tupí-Guaraní with its closest geographical relative: siriono (rodrigues;  Cabral, 2002, p. 335). our attempt to classify Jorá is challenging due to the limits of the dataset.
g. <kw> [k w ], <gw> [g w ]; palatalized consonants e. g. <ky> [k j ]. the accent is on the penultimate syllable, unless marked differently. 8 david Jabin's data are based on field observation and  Garland's dictionary (1978). We are very grateful for his contribution to our comparative database and many discussions of the subject. 9 Aché is a tG language, and its classification is still under investigation, for details see dietrich, this volume. it is currently being investigated in the documentation Project on Aché by rössler and her colleagues. internal classification is based on the fact that siriono and Yuki are languages with a great number of lexemes which are apparently not of tG origin  (dietrich, 2002, p. 362) , but his analyses of schermair (1949) resulted in the conclusion that siriono is "less 'extravagant' than what was formerly thought"  (dietrich, 2002, p.
However, it is in general difficult to compare languages of tG2, because they diverge so strongly for some characteristics. on the basis of our findings, we assume that all three languages, Jorá, siriono and Yuki, derive from one protolanguage and form a sirionoan group. Ethnographic descriptions support the thesis of the sirionoide group  (Jabin, 2012)  and the membership of Jorá in this group (cf. table 1), and linguistic comparison reinforces this claim of a group forming a large dialectal continuum. stearman  (1984, p. 649 ) presents a possible relation among Bolivian tG ethnic groups and dietrich (2008, p. 47) tried to unite all Bolivian languages. A new collaboration arose to clarify this claim with the team developing the tG Comparative Lexical database  (o'Hagan et al. , 2015). We integrated Jorá into a new phylogenetic classification and searched for borrowings through a list of innovations for sirionoan languages  (Gasparini et al.
All the languages of tG2 still need more intensive investigation where possible. Guarasu, Guarayo and siriono, are now the focus of documentation projects with grants from the Endangered Languages documentation Programme (ELdP). We have tried to gather as much data for Jorá as possible. nonetheless, there is a small possibility that we will be able to collect more data in the field from one remaining Jorá woman. this means that more studies of tG2 can still be expected in the future. And in addition to this, there will be more descriptions of other tG languages and Bolivian languages of the area, so that a broader comparison is another task. /ã/ 1 1 (1 = most certain ; 2 = not so sure ; 3 = unsure ; 4 = no phonemic evidence ; 5 = not in the corpus but may be in the language knowing siriono and Yuki) 2 Conclusion based on the flap presence and lateral flap absence in other languages in consideration.
ACKNoWLEDGMENTS We would like to express a deep debt of gratitude to the last Jorá speaker. thanks to two anonymous reviewers for many helpful comments. thanks to  Wolf dietrich , david Jabin, sandy ritchie,  Jorge Emilio rosés Labrada ,  Emily Clem , françoise rose and natalia  Chousou-Polydouri  for helping us and leading to more precise analyses. Many thanks to  Zachary o'Hagan  for discussions at different stages of this analysis and precise comments. thanks to our financial support for this research:  Endangered Languages documentation Programme (ELdP)  for the documentation projects (danielsen project #iGs0385 on Guarayo and Guarasu;  Gasparini  project # iGs0185  on siriono) and the  Laboratiore dynamique du Langage (ddL)/AsLAn  for institutional support.
Background-The Global Burden of Disease Study 2013 (GBD 2013) aims to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and transparent data sources to enable comparisons of health loss over time and across causes, age-sex groups, and countries. The GBD can be used to generate summary measures such as disability-adjusted life-years (DALYs) and healthy life expectancy (HALE) that make possible comparative assessments of broad epidemiological patterns across countries and time. These summary measures can also be used to quantify the component of variation in epidemiology that is related to sociodemographic development. Methods-We used the published GBD 2013 data for age-specific mortality, years of life lost due to premature mortality (YLLs), and years lived with disability (YLDs) to calculate DALYs and HALE for 1990, 1995, 2000, 2005, 2010, and 2013 for 188 countries.
Introduction The Global Burden of Disease study 2013 (GBD 2013) seeks to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and transparent data sources to allow comparisons of health loss to be made over time and across causes, age-sex groups, and geographies. The GBD 2013 data for disease and injury incidence and prevalence, years lived with disability (YLDs), causes of death, and years of life lost because of premature mortality (YLLs) for 188 countries provide an opportunity to assess the effect of recent changes in population health by examining summary measures of health loss attributed to specific causes, expressed in DALYs, and summary measures of average population health, expressed as HALE. 1, 2 These measures are crucial to track health progress, strengthen policy decisions, assess programme effects and results, and inform health service and research priorities.
] [5]  A hallmark of the GBD approach is an emphasis on making national data easier to compare by taking into account the extensive variation that exists in national medical certification and cause of death coding practices and widely varying case definitions and measurement methods used to track the incidence and prevalence of diseases and injuries. 1, 2 The GBD not only provides detailed metrics for specific causes, but also generates summary measures, such as DALYs and HALE, which enable comparative assessments of broad epidemiological patterns across countries and different time periods. HALE is a useful summary of overall health for a country and DALYs allow assessment of both premature mortality and non-fatal outcomes by cause. 5] [16] [17] [18]  The GBD provides an opportunity to quantify these patterns and explore the extent to which epidemiological change is driven by sociodemographic change, reduction of health risks, improvement of health management, or other local factors.
Wang and colleagues 2 have described data sources and methods to estimate mortality and life tables, and Vos and colleagues  1  have described these for the measurement of prevalence of sequelae and disability weights. 1  We combined information about prevalence and disability weights into measures of the overall rate of YLDs per person in each age-sex-country group. We make the strong assumption that uncertainty in YLDs per person is independent of uncertainty in age-specific death rates to calculate uncertainty distributions for HALE.
An example of these demands is the fact that the number of individuals in the world living in states of health characterised by a disability weight greater than 0•1 has increased by 43% from 1990 to 2013. In 1971, Omran  27  outlined the concept of the epidemiological transition to describe the changing pattern of causes of death that results from sociodemographic development. 4] [35]  Taking advantage of the database of the GBD 2013 country-level results from 1990 to 2013, we have quantified the extent to which sociodemographic status accounts for changes in epidemiological patterns, as opposed to other factors changing over time or static variation between countries. Isolation of this component of the variation of DALY rates allows examination of the shifts in disease and injury patterns that would be expected purely as a function of changing sociodemographic status.
These findings raise the question of whether the division of countries into 21 regions in GBD based on geographic contiguity and the levels and patterns of adult and child mortality rates is the best way to explain the variance in DALY rates. With country-specific results now available, more sophisticated clustering methods could be used, with various constraints, to propose a more empirically calculated set of regions. Regions have two dimensions: analytical and presentational. The presentational dimension is easily addressed because results for any set of countries can easily be generated from the country-specific results. In fact, the GBD Compare data visualisation tool provides several alternative presentational groupings, such as WHO political regions or World Bank regions. However, regions have an analytical effect on the results if the super-region and region hierarchy have been used in the Bayesian modelling.
In the GBD cause of death analysis, spatiotemporal Gaussian process regression models use the GBD hierarchy to borrow strength. In DisMod-MR 2. 0, the regional hierarchy also affects estimation of the prior for each country analysis. More simply, where data are sparse or not available, the GBD regional groupings can have an important analytical effect. More research is needed on two fronts. First, to explore the extent to which alternative regional groupings would explain more of the variance in the DALY results (or any other GBD indicator). Second, whether analytical tools, such as cause of death ensemble modelling (CODEm)  60  or DisMod-MR 2. 0, 1 could be modified to easily allow for different regional hierarchies for different causes. This study has all the limitations previously reported for the GBD 2013 analysis of YLLs and YLDs.
Evidence before this study In 2012, results from the first complete revision of the Global Burden of Disease (GBD) since the first assessment in 1993 became available. This effort was called the GBD 2010 study and reported on disability-adjusted life-years (DALYs) and health-adjusted life expectancy (HALE) by country for 1990 and 2010 based on analyses of an extensive data collection effort to collate all available information on causes of death and disease occurrence in 187 countries. In response to the need for up-to-date information about the health of populations to inform health policy decision making, a decision was made to produce annual updates. The GBD 2013 is the first of these annual updates. In previous papers on the GBD 2013 study, we have documented the new data and new methods used to assess mortality and morbidity by country and over time.
Acknowledgments On behalf of the GBD 2010 Genitourinary Diseases Expert Group, GR, NoP, and BB would like to acknowledge that their activities within the GBD 2013 have been made on the behalf of the  International Society of Nephrology (ISN). ATA received institutional support and grants from the  Graduate School of Medical Sciences, University Medical Center Groningen (UMCG). JM has received support from the  National Health and Medical Research Council. LLY is also supported by the  National Natural Sciences Foundation of China. UOM  would like to acknowledge his funding by the  German National Cohort Consortium. RB was provided funding support by the  Brien Holden Vision Institute. INA would like to acknowledge her funding support from the  National Health and Medical Research Council Public Health (Australian)   Early Career Fellowship.
KD is supported by a  Wellcome Trust Fellowship in Public Health and Tropical Medicine  (grant number  099876 ). The funding sources had no role in the writing of the manuscript or the decision to submit it for publication. JS was supported by the  National Natural Science Foundation for Young Scholars of China , (number  81200051 );  Research Fund for the Doctoral Program of Higher Education of China  (number  20110071120060 );  Science Foundation for Young Scholars in Zhongshan Hospital  (number  2012ZSQN04 ); and the  Scientific Project for Fudan University  (number 20520133474). RB is funded by an  Australian National Health and Medical Research Council   Senior Principal Research Fellow. TF is grateful to the  Swiss National Science Foundation  for an  Early  and an  Advanced Postdoc Mobility fellowship  (project numbers  PBBSP3-146869  and  P300P3-154634 ).
SJY and IHO received funding for their work in a grant from the  Korean Health Technology R&D Project (Ministry of Health & Welfare, Republic of Korea ; grant number  HI13C0729 ). ALT-L was supported by the  CGIAR Research Program on Aquatic Agricultural Systems. Wellcome Trust ,  Public Health Foundation of India  and a  Consortium of UK Universities. SIH is funded by a  Wellcome Trust  Grant. JAS has received grant support from  Takeda  and  Savient Pharmaceuticals  and consultant fees from  Takeda ,  Regeneron ,  Allergan , and Savient. JAS is an executive member of OMERACT, an organisation that received armslength funding from 36 pharmaceutical companies. KJL was funded by  WHO  to conduct the review of HSV-2 seroprevalence which informs this study. During the study, KJL received funding from  Health Protection Scotland , the  National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Evaluation of Interventions , and Sexual Health 24: the funding sources had no role in the writing of the manuscript or the decision to submit it for publication.
CKi has also received authorship royalties from publishers Artmed and Manole. KBG received the  NHMRC-Gustav Nossal scholarship  sponsored by CSL in 2012. This award is peer-reviewed through the standard NHMRC peer-review process; CSL played no part in selection of the awardee. HAW, AJF, FJC, and HEE are all affiliated with the  Queensland Centre for Mental Health Research , which receives funding from the  Queensland Department of Health. DJS has received research grants and consultancy honoraria in the past three years from  AMBRF, Biocodex, Cipla ,  Lundbeck ,  National Responsible Gambling Foundation ,  Novartis ,  Servier , and  Sun. DJS is also supported by the  Medical Research Council of South Africa. DM reports being on the scientific advisory board of  Unilever North America  and ad hoc honoraria or consulting from  Bunge, Nutrition Impact ,  Amarin ,  AstraZeneca , and  Life Sciences Research Organization.
Methodology and data source HDI is an index developed arbitrarily  (Mărginean, 2012). Human Development Index comprises three basic elements: longevity (measured by life expectancy at birth), environment education (calculated as a weighted arithmetic average between the average years of schooling and expected years of schooling); standard of living (expressed in GNI per capita calculated at purchasing power parity). The HDI measures the relative distance that separates every country of the world from the prioritized goals for social development, namely providing an overall assessment of progress and different strategies followed by states to achieve human welfare. The index is calculated as a geometric average of the three dimensions: health, education and living standard. HDI level varies on a scale between 0 and 1, so that the level of human development is the greater the more close to the value 1.
HDIit = c + LEBit + MYSit + EYSit + GNIit + εit (1) where: HDI -Human Development Index LEB -life expectancy at birth MYS -mean years of schooling EYS -expected years of schooling GNI -gross national income i -Continental (if Europe or America, Africa, Asia or Oceania) t -time (t = 2005,. , 2013) ε t -residual value The analyzed period covers 2005-2013 periods. The frequency data is annual. Data were collected from the database of the United Nations Development Programme. The sample comprises 37 countries in Europe (Annex 1). In the sample of European countries: 9 countries have a very high Human Development rank, 25 countries have high human development, and 3 countries have a medium rank.
3. We used Google Scholar for this search, as this is the most widely used search engine for academic publications. A methodological issue that arises here pertains to the publication date, which in more than 100 cases was not given or was unclear (category "N. C. " in Figure  1 ). ambassadors located in five world capitals, and former Foreign Ministers Ali Babacan and President Abdullah Gül. There are also some background papers on the MFA and two speeches by counsellor generals. While the documents on the website are clearly selected, and hence not necessarily exhaustive, we can assume that they were chosen by the MFA and, therefore, can be considered as representative of the messages the MFA intends to project. In contrast, the Turkish-language website of the Prime Minister's website only delivers three entries, which are also discussed.
10  Fariba Adelkhah, Être moderne en Iran, Paris, Karthala, coll. «Recherches internationales  », 1998, p. 10-11. 11   Nader Vahabi, La migration iranienne en Belgique, une diaspora par défaut, Paris, l'Harmattan, 2011, p. 74-77. 12  To understand the meaning of the wave, cf. E. K. KUNZ, Les réfugiés en exode: les modèles dynamiques et les formes  de déplacement, International Migration, vol 7, 2,  For these years, see, http://www. unhcr. org/statistics/populationdatabase, consulted 06. 05 2012. 14  For the riots at Teheran University cf. Mohammad Reza Djalili, Iran: l'illusion réformiste, Paris, Presses de Sciences Po, coll. «La bibliothèque du citoyen », 2001, p. 112. Iranians to go directly and without a visa to countries close to the European Union; this has an impact on the third factor, a geographical one, since Belgium had become the anti-chamber to enter the easily accessible England where immigrants found work and promotion  15.
In this paper, we investigate the issue of detecting the real-life influence of people based on their Twitter account. We propose an overview of common Twitter features used to characterize such accounts and their activity, and show that these are inefficient in this context. In particular, retweets and followers numbers, and Klout score are not relevant to our analysis. We thus propose several Machine Learning approaches based on Natural Language Processing and Social Network Analysis to label Twitter users as Influencers or not. We also rank them according to a predicted influence level. Our proposals are evaluated over the CLEF RepLab 2014 dataset, and outmatch state-of-the-art ranking methods.
In other words, we investigate for specific Twitter characteristics that can describe people known to be influential in real-life. To answer this question, we conduct experiments on the CLEF RepLab 2014 dataset 1 , which contains Twitter data including influence-annotated Twitter profiles. We take advantage of these manual annotations to train several Machine Learning (ML) tools and assess their performance on classification and ranking issues. The former consists in determining if a user is influential or non-influential, whereas the latter aims at ranking users depending on their estimated influence level. Our first contribution is to review the most widespread Twitter-based features used for user profile characterization problems. In particular, we simultaneously consider features traditionally used separately by researchers from the Social Network Analysis (SNA) and Natural Language Processing (NLP) domains; and additionally propose a few new features.
Our second contribution is the systematic assessment of these features, relatively to the prediction of real-life influence. We show that most features behave rather poorly, and discuss the questions raised by this observation. Finally, we describe two NLP ranking methods that give better results than known stateof-the-art approaches. The rest of this paper is organized as follows: the next Section reviews the main recent works related to the characterization of Twitter users, in particular in terms of influence. We then describe the RepLab 2014 task in Section III, focusing on the dataset, the evaluation methods, and the results obtained during the campaign. In Section IV, we describe the features selected and defined for our experiments. In Section V, we present our methods and the results we obtained.
Recently, Werren et al  [24]  proposed an important number of experiments combining several features (Flesch-Kinkaid readilibity index), psycholinguistic concepts (using MRC and LIWC  [25]  features) and distance metrics (Cosine, OkapiBM25) evaluated on the PAN 2014 dataset. Participants also considered these readability indexes in linear classifier such as SVM and libLINEAR. PAN participants approached the task using ML techniques. All these features were used to feed several algorithms such as logistic regression, logic boost, multinominal Naïve Bayes, etc. The RepLab 2014 "Author Ranking" task was specifically focused on influence  [19] , as explained in more details in Section III. Participants mainly considered the tweet textual content to model each user, and applied various ML tools.
III. REPLAB CHALLENGE The CLEF RepLab 2014 dataset  [19]  was designed for an influence ranking challenge organized in the context of the Conference and Labs of the Evaluation Forum 2  (CLEF). As mentioned before, we use these data for our own experiments. In this Section, we first describe the context of the challenge and the data, then how the performance were evaluated, and we also discuss the obtained results. Finally, we present a classification variant of the task.