dataesr/scientific-paragraphs-categorization huggingface dataset:
(2016) , the total deposition of 137 Cs in Europe was 75 PBq, based on approximately 12 000 measurements (shown also in Fig. 3 ) that were interpolated onto a regular grid. We calculated that 71 PBq of 137 Cs were deposited over Europe using the prior release (Fig. 2 ) and ERA-40 fields. In contrast, deposition of 137 Cs using ERA-Interim was much lower (56 PBq). The same deposition pattern was found for 131 I and 134 Cs, with deposited amounts to be 35 % higher when using the ERA-40 reanalysis data set. The largest relative increase in deposition was estimated in Scandinavia, where models have struggled to reproduce deposition, in Belarus and in different parts of Russia. While it is somewhat surprising that ERA-40 allowed more realistic simulations than the more modern ERA-Interim data set, we therefore selected the ERA-40 data as our reference data set for the inversion.
Validation of the inversion results against observations It was mentioned in Sect. 3. 4 that a fraction of the measurements was excluded from the inversion. These data were used here for investigating the improvement obtained with the posterior source term compared to the prior source term. Comparison of simulated surface activity concentrations and deposition values of 134 Cs, 137 Cs and 131 I using the prior and the optimized (posterior) source terms are shown in Fig. 7. Furthermore, time series of activity concentrations that were excluded from the inversion (see Sect. 3. 4) were compared with simulated concentrations obtained using the prior and posterior emissions (Fig. 8 ) for remote stations (Athens, Greece; Glasgow, UK; Umea, Sweden) and stations located closer to the Chernobyl NPP (Budapest, Hungary; Göttingen, Germany; Prague, Czechia).
In tests we found that the model produced more realistic radionuclide deposition patterns with the ERA-40 reanalysis data set than with the ERA-Interim, especially in areas located far from the source (e. g. , in Scandinavia, southeastern France and Scotland); thus ERA-40 was used as a reference for the inverse modeling. We calculated that 71 PBq of 137 Cs were deposited over Europe using the prior release (Fig. 2 ) and ERA-40 fields, achieving 35 % more deposition, at maximum, than using the ERA-Interim reanalysis data set. Regarding the posterior emissions of 134 Cs, about 80 PBq were released in total with the same temporal pattern as in the prior source term, although these emissions are 32 % higher than in  Brandt et al. (2002 ), SCUAE (1986)  and  Waight et al. (1995)  and 55 % higher than those reported from  Davoine and Bocquet (2007).
The posterior emissions of 137 Cs were assessed independently using a Eulerian CTM (LMDz-OR-INCA) to simulate transport and deposition. We calculated that 87 % (or 75 PBq) of 137 Cs posterior releases were deposited over Europe with LMDz-OR-INCA vs. 85 % (63 PBq) using the prior releases of 137 Cs (in prior and posterior fluxes, the total released amount were 74 and 86 PBq, respectively). This deposited amount in Europe is similar to the reported one in the Atlas (77 PBq) and identical to the most recently published estimation that used different data but the same methodology as in the Atlas (75 PBq). The model tends to underestimate deposition in countries that are not in the main direction of the fallout, but it manages to reproduce contamination levels in most countries with correlation coefficients above 0.
Acknowledgements. The present work was carried out in the frame of the  STRADI  project  (Source Term Determination of Radionuclide Releases by Inverse Atmospheric Dispersion Modelling ) of the  Czech-Norwegian Research Programme  (project  ID :  7F14287 ). Computational and storage resources for the FLEXPART simulations have been provided by  NOTUR  ( NN9419K ) and  NORSTORE  ( NS9419K ). The development of inverse modeling tools was also supported by the  Nordic Centre of Excellence eSTICC , funded by  Nordforsk  (number  57001 ).
Mortality data and profiles based on observations of dental eruption, wear and replacement stages can be used to study and characterize cattle slaughter management, which in turn can be used to study husbandry practices  [34] [35] [36]. For the LBK area, these types of studies have so far been limited to regional studies  [25, [27] [28] [29]. Here, we investigate LBK cattle husbandry through statistical analyses of an age-at-death dataset based on 19 sites from across the LBK cultural zone. These analyses will help us to characterize LBK cattle husbandry on a global scale for the first time, and explore its evolution in subsequent cultural phases.
Material and methods (a) Material The dataset represents 19 sites (27 contexts; total number of teeth ¼ 1142) from central and northwestern Europe (figure  1 ; electronic supplementary material, S1). These sites date from 5600 to 4600 cal. BC. Four sites from Hungary represent the LBK. One of them belongs to the LBK in Transdanubia (TLP; Apc-Berekalja) and the remaining sites belong to the so-called Alfo ¨ld Linear Pottery (ALP; Fu ¨zseabony-Gubakut, Polgar-Piocasi-du´lo´and Polgar-Ferenci-hat). The LBK phenomenon in Hungary was distributed mainly to the west of the Danube, whereas the ALP lies east of the Danube. This culture differs in pottery styles from TLP/LBK, although it has many similarities with TLP and LBK phenomenon  [37]. Furthermore, the ALP and TLP cultures are dated to the Hungarian Middle Neolithic and follow the Starc ˇevo (Transdanubia) and the Ko ¨ro ¨s (Hungarian Plain).
(c) Statistical analysis The mortality profiles were based on number of teeth (N ) and not minimum number of individuals, which is not linearly connected to sample size  [41]  and were generated using an R code described in  [42]  adapted for Legge  [35]  age classes to analyse cattle mortality (electronic supplementary material, S2 and S3). The published code in  [42]  being for caprines and is based on the Payne  [43]  age classes. Credible intervals for each age class were computed using the Dirichlet function (Dirichlet prior ¼ 0. 5; number of simulations ¼ 2000). The correspondence analysis (CA) of the mortality data was carried out using the Dirichlet function as described in  [42]  and adapted for Legge age classes  [35]. The use of the Dirichlet function reduces the stochastic effect from small samples.
The CA biplots can be used to elucidate trends within the data to generate hypotheses. We chose four reference profiles for milk and meat exploitation based on archaeological examples to aid the interpretation of the CA. These did not contribute to the overall inertia of the plot, so therefore did not affect the profile and age class distribution. All analyses and biplots were produced using the free platform R program (v. 3. 03. 3 [44] ) using R studio. R packages: ggplot2 (v. 1  [45] ), grid (v. 3. 0. 2 [44] ), gridExtra (v. 0. 9. 1  [46] ), gtools (v. 3. 4. 2 [47] ), ca (v. 0. 55  [48] ), LaplacesDemon (v. 16. 0. 1  [49] ), MASS (v. 7. 3-37  [50] ) and PAST (v. 3. 15)  [51].
(b) Correspondence analysis CA is a descriptive statistical analysis and is used to highlight possible trends within the dataset. CA was based on 54 026 Dirichlet deviates generated from the age-at-death dataset. The overall inertia was 0. 59 with 64. 8% explained in the first three dimensions (F 1 : 24. 2%: F 2 : 21. 6%; F 3 : 18. 7%). Table  1  presents the summary for the CA for the seven age classes. Based on the coordinates and contributions of individual age classes, we can determine what age classes explain the inertia for each axis. F 1 was explained by the opposition between greater than 8 years, 6-15 months and 6-8 years, whereas F 2 was by the opposition between 0 and 6 months, 26 and 36 months and 3 and 6 years. Finally, F 3 was explained between greater than 8 years, 6-8 years and 15-26 months.
Acknowledgements. Many thanks to those who allowed access to material during the  NeoMilk  project:  Elis ˇka Kazdova(Masaryk University, Czech Republic );  Prof. Erich Pucher  ( Museum of Natural History, Vienna );  Sandor Tanyi and Kristof Racz (Eger) ;  Prof. Pal Raczky  and  Dr Peter Csippan  ( Institute of Archaeological Sciences, Budapest );  Dr Henriette Obermaier  ( Staatssammlung fu ¨r Anthropologie und Pala ¨oanatomie Mu ¨nchen ). Access to the Eilsleben material was facilitated by  Dr Hans-Ju ¨rgen Do ¨hle  ( Landesamt fu ¨r Denkmalpflege und Archa ¨ologie Sachsen-Anhalt, Halle ) and studied by S. B. during a post-doctoral fellowship funded by the  ANR  project  OBRESOC  (Dir. J. -P. Bocquet-Appel ;  ANR-09-CEP-004-01/OBRESOC ).
Flow cytometry Human monocyte-derived macrophages were treated with P17 (200 µg/ml) for 24 h and then incubated with ice-cold PBS and gently scraped. Collected cells were centrifuged at 1,500 rpm for 10 min, and the cell pellet was suspended in PBS medium supplemented with 1% fetal calf serum (FCS). Surface expressed MR, Dectin-1, DC-SIGN, CD16, or CD36 was detected, respectively, using PerCP-Dectin-1 monoclonal antibody (mAb; R&D FAB1859C-100, 1/40), PE-DC-SIGN (mAb; BD Biosciences 551 265, 1/20), FITC-CD16 (mAb; PNIM 0814, 1/20), or APC-CD36 monoclonal antibodies (mAb; BD Biociences 550 956, 1/40). To evaluate the MR surface expression, we have used MR-specific ligand conjugated with FITC (Sigma A7790, 1 mg/ml, 1/100). All staining were performed on PBS -/-1% FCS medium. A population of 10,000 cells was analyzed for each data point.
reverse Transcription and real-time Pcr Human monocyte-derived macrophages were treated with P17 (200 µg/ml) and/or LTB4 (100 nM; Cayman Chemical Company) for 8 h. The mRNA preparation was made using the EZ-10 Spin Column Total RNA Minipreps Super Kit (Bio Basic) using the manufacturer's protocol. Synthesis of cDNA was performed according to the manufacturer's recommendations (Thermo electron). RT-qPCR was performed on a LightCycler 480 system using LightCycler SYBR Green I Master (Roche Diagnostics). The primers (Eurogentec) were designed with the software Primer 3. GAPDH mRNA was used as the invariant control. Serially diluted samples of pooled cDNA were used as external standards in each run for the quantification. Primer sequences are listed in Table  1.
Poor Fewer visits to a nephrologist and the lack of erythropoiesis-stimulating agent (ESA) in the predialysis period have also been associated with catheter use at hemodialysis initiation  [17]. Studies specifically comparing nonfunctional with functional AV accesses have found similar associations  [5, 14]. They were, however, restricted to the United States. Because of differences in patient selection and practices for predialysis AV access placement  [18] [19] [20] , nonfunctionality rates and their determinants may differ between Europe and North America. For instance, only 18% of US patients start hemodialysis with an AV access while this rate reaches 30 to 45% in Europe  [5, 6, 21, 22 ]. We therefore used data from the French REIN Registry to study the timing of AV access placement and determinants of nonfunctional AV access at hemodialysis initiation in a context of relatively high AV access use.
Other data Patient-level data at baseline included date of RRT start, geographic region, age, gender, primary renal disease, body mass index (BMI), laboratory values over the 1-month period before RRT (serum albumin, hemoglobin level, and estimated glomerular filtration rate), comorbidities, predialysis use of ESA, and dialysis start condition (planned or emergency). Estimated glomerular filtration rate (eGFR) was calculated with the Modification of Diet in Renal Disease (MDRD) equation. Comorbidities included diabetes, number of cardiovascular diseases (among ischemic heart disease, stroke, peripheral vascular disease, heart failure, and dysrhythmia), lower limb amputation, malignancy, and mobility status as a proxy for frailty. Emergency dialysis start was defined in the registry as any first dialysis session initiated in life-threatening circumstances requiring dialysis within 24 h.
Statistical analyses Patient characteristics at baseline were described and compared between the 2 groups defined by AV access functionality at hemodialysis initiation, as described above. Categorical variables are presented as percentages and continuous variables as means ± standard deviations or medians (interquartile range), depending on the normality of their distributions. Chi-square, ANOVA, and Kruskal-Wallis tests were used as appropriate. Because of missing data for some variables (Table  1 ), we performed multiple imputation of 20 datasets with the fully conditional specification method  [24, 25]. The imputation model included all variables in Table  1 , as well  as geographic region, year of first ESRD treatment, and vital status at the end of the follow-up. Analyses through the 20 complete datasets were combined according to Rubin and Schencker's rules  [26].
Nevertheless, the simulation of missing dates on the prevalence estimate showed that their potential impact would be low; for example, if the missing date rate in this group was twice (30%) that in the group with function AV access, the prevalence of nonfunctional AV access would rise from 18% only to 21%. A recent study from the French national health insurance database (covering 77% of the French population) showed that 30. 3% of the patients starting hemodialysis had an arteriovenous fistula created within 1 to 12 months before initiation in 2013  [45]. In our study, for the same period, 29. 4% of patients starting dialysis had undergone predialysis AV access creation. Most missing dates of AV access creation at baseline may thus correspond to a lack of AV access placement before hemodialysis initiation.
Acknowledgments We thank all the registry participants, especially the nephrologists and professionals who collected the data and conducted the quality control for the REIN registry. The dialysis units participating in the registry are listed in its annual report: http://www. agence-biomedecine. fr/ IMG/pdf/rapport_rein2013. pdf. We also thank  Dr Christian Jacquelinet  (christian. jacquelinet@biomedecine. fr), the coordinator of the REIN Registry and co-author of this paper. Part of this work was presented orally at the 17th joint meeting of the  Société Francophone de Dialyse  and the  Société de Néphrologie.
Methods sources The source of the data used in this study was the Disability and Health Survey -Ordinary Household Section and Institutions Section, which was performed The authors confirm that all data underlying the findings are fully available without restriction. 21 These data yielded information on the patients questioned (age, gender, educational level, and level of income), their health status (diseases, use of health care, and prevention), identification of disability (deficits, functional limitations, and restrictions of activity), and lastly, items relating to their social participation and their environment (family environment, presence of family and/or professional caregivers, type of accommodation, accessibility, education, employment, income and benefits, leisure occupations, and perceived discrimination).
Conversely, oral health that is perceived as satisfactory may mask an oral situation that requires specialized management. Regular clinical oral examination of institutionalized patients and home-dwellers aged. 60 years would certainly ensure early management of and improved oral health. The data used in our study were taken from the national Disability and Health surveys carried out among patients of all ages living in institutions and in their own homes. These two large structural surveys collected numerous elements relating to functional status (diseases, disabilities, and limitations), restrictions on social participation (access to employment, training and leisure activities, and elements of standard of living), and environmental factors (family, relatives and friends, technical assistance, home alterations, accessibility of public places, and perceived discriminations) reported by individuals in each of the populations.
Data analysis To capture as many responses as possible, data were collected between 21 st March 2016 and 6 th November 2016  (Dataset 1; Riddiford, 2017). In this time period, the survey was answered by 1,128 scientists. Initially, to give an overview of the distribution of respondents by country, IP addresses associated with each respondent were used to query a free-to-use geolocation database (http:// freegeoip. net). Resulting data were then plotted on a world map, and focussed on Europe and the UK for a finer distribution of IP addresses. All the code used to generate the plots shown in Figure  1  is deposited in the Github repository https://github. com/nriddiford/ Mapped-IP-addresses. Next, data were filtered to select only for responses from UK-based biomedical researchers (Q2 response: "biomedical sciences"; Q3: "UK") to give a broad overview of working conditions within this cohort.
Data for each discrete profile were then analysed using a custom Perl script (Supplementary File 2) to parse downloaded data and include non-standard question answers (i. e. where respondents opted to specify a non-listed answer, or to elaborate on their selected response) in the analysis. Average salaries for each group were calculated by using the mean number of hours and salary for each cohort as queries for the web-based UK salary calculator (http://www. thesalarycalculator. co. uk/salary. php). The average salary for PhD students was calculated using the option "no NI". For the 299 respondents who provided a written answer to describe in detail the reasons they were planning on leaving research (Q10: "not at all -I'm planning on leaving research"), four statements were selected for each career stage as being broadly representative of the issues addressed by others in the same cohort, and are presented in Box 1-Box 3.
Discrete profiles for UK-based biomedical researchers The data were then filtered to select only for UK-based biomedical researchers, yielding a total of 520 responses, comprising 306 PhD students, 142 postdocs, 30 PIs and 42 working in roles outside of these three categories (such as research assistant), that were not included in further analyses. PhD students. The majority of respondents to the survey were PhD students (59%), representing the youngest, and most mobile cohort, with 94% aged between 25-29 and 35% having worked in two or more countries over the past five years (Dataset 1 (Riddiford, 2017); Supplementary File 1). On average, they also reported working more hours per week than other cohorts (37% work over 50 hours a week) and the majority worked more than five days in the week before answering the survey (55%, > five days; 16%, seven days; Figure  2  -'PhD').
The large majority that didn't feel comfortable in a future in research and felt that they were competing for too few jobs (66% answered "It's too competitive, and there aren't enough jobs") and working too hard (33% answered "I can't keep working this hard"). Principal investigators. The final group comprises those who identified as being a principal investigator ("PI"), and therefore represent an older and more stable cohort that PhD students or postdocs. In total, 63% of respondents in this group were employed on a permanent contract, and only 20% reported working in more than two countries over the last five years. In addition, 80% were over 35 years old and 48% reported being employed at the same level for four years or more (≥ ten years: 28%; Dataset 1 (Riddiford, 2017)). However, this category was vastly underrepresented in the survey data -only 30 individuals responded in total, and only eight were aged over 45 years -representing a major caveat in the interpretation of such data.
Overall, the data presented here suggest a large faction of biomedical researchers working in the UK are deeply concerned about their long-term future in research. In each discrete career stage analysed, roughly equal numbers (PhD: 28%; postdoc: 30%; PI: 31%; Dataset 1; (Riddiford, 2017)) plan on leaving academic research, largely due to the lack of job opportunities, and the degree of competition involved in attaining a permanent position. Such findings are largely consistent with the number of scientists reported to be planning on leaving research in the US  (Sauermann & Roach, 2016) , and represent a major problem -the "brain-drain" -facing biomedical research  (Benderly, 2015; Healy, 1988). The data also suggest that biomedical scientists in the UK are working long hours and over weekends for relatively little financial reward: 53% worked more than five days in the week before they took the survey, and only 16% reported receiving an annual salary of over £35,000.
A recent online poll of readers conducted by the journal Nature revealed that almost 40% of the 12,000 respondents worked more than 60 hours a week on average  (Powell, 2016) , a substantially higher number than that found in this survey (12% across all career stages). One explanation is that while the Nature poll asked readers (from all scientific disciplines) to report their average working week, the survey presented here instead asked respondents to report the number of hours worked in the week immediately preceding the survey, and to estimate an average only if this value was atypical. This approach was adopted to limit overestimation and to provide a more accurate dataset. The same Nature poll also reported that almost two thirds of readers have considered leaving research altogether, and that 15% have actually left, again, far higher than numbers reported here  (Powell, 2016).
PubMed Abstract | Abstract Publisher Full Text Riddiford N: Dataset 1 in: A survey of working conditions within biomedical research in the United Kingdom. F1000Research. 2017. Data Source Riddiford N: The hidden costs of a career in scientific research. Nature blogs. Maricque B, Lewis C: The missing piece to changing the university culture. Nat Biotechnol. 2013; 31(10): 938-941.
Data collected through personal contacts with instructors Through personal contacts, we obtained information on courses that cover COI at seven medical schools. These were at Lyon Est, Aix-Marseille, Strasbourg, Toulouse Purpan, Rennes 1, Paris 5, and Paris 7. These courses represent isolated initiatives by teachers who recognize the importance of COI issues. They are electives (optional courses, not within core curriculum). For this reason, all of them received a score of one for the curriculum category, according to our grading system (see S1 File).
The 2003-303 law, introduced on 4 March 2002 regulates the links between medical professionnals and pharmaceutical companies, prohibiting receipt of any in-kind or cash benefit, except in the context of scientific research. The latter must be approved by a professional council. Physicians who are on the staff of medical faculties are among those covered by these provisions. Recent legislation also requires professors to declare conflicts of interest at the beginning of each course or lecture  [11]. Not enough time has elapsed, however, to assess compliance in practice. In France, there is a public database covering industry payments to physicians (www. transparence. sante. gouv. fr) including gifts and meals. The database indicates that from January 2012 to June 2014, French students and residents received gifts worth a total of € 3.
Participants Twenty-nine senior male European professional soccer players participated within the investigation. At the time of the study, the players were competing in the Swiss Professional soccer league. Thirteen of the players involved were members of their national team. Players' age, height, body mass, maximal aerobic capacity and sum of eight skinfold sites were 26. 7 ± 4. 0 years, 183. 4 ± 5. 8 cm, 78. 4 ± 8. 0 kg, 57. 5 ± 5. 3 ml • kg -1 • min -1 and 54. 1 ± 13. 6 mm, respectively. Informed consent was received from all players to include their data after a brief but detailed explanation about the investigation. Players were told that they were free to withdraw their information and data from the study at any time and the study conducted was fully approved by the involved Sports Science and Medical Department at the Football Club precommencement of the monitoring.