dataesr/scientific-paragraphs-categorization huggingface dataset:
Stepwise selection with backward elimination was applied, with p > 0. 05 for exclusion (model 1). For each outcome, the final model was built from model 1, to which the variable "pain at 5 years" was added (model 2). QoL was also analyzed separately for casualties with and without PTSD, and interactions between whiplash and pain were investigated. Statistical Analysis System software, version 9. 3 for Windows (SAS Institute Inc. , Cary, NC, USA) (proc genmod and proc glm) was used for all analyses.
Ethics and consent The study protocol was submitted to and approved by the French Ministry of Research (CCTIRS: Advisory Committee on Information Processing in Material Research in the Field of Health) (CCTIRS Number 04. 159). Data collection and analysis were approved by the national data protection authority (CNIL: CNIL Number 04-1417). Lastly, only patients (or their family) who gave written consent for follow-up were included in the cohort. At any time during the follow-up period, subjects were free to cease participation, and, in that case, to be totally withdrawn from the study files and analyses.
Acknowledgments The authors are grateful to the accident casualties for their cooperation in data collection. The authors would like to thank all those who assisted in carrying out this study:  Nadia Baguena ,  Jean-Yves Bar ,  Amélie Boulanger ,  Elodie Paquelet ,  Stuart Nash  and  Véronique Sotton  for collecting the data;  Irène Vergnes  for organizing the databases;  Anne-Marie Bigot ,  Nathalie Demangel  and  Geneviève Boissier  for subject database management;  Blandine Gadegbeku ,  Amina Ndiaye  and The Association for the  Rhône Road Trauma Registry (ARVAC)  for their help in collecting and providing medical data; the  Scientific Committee  ( Daniel Floret ,  Bernard Laumon ,  Jean-Michel Mazaux ,  Jean-Louis Martin  and  Etienne Javouhey );  Dominique Boisson  and  Jacques Luauté  for their participation in the ESPARR scientific management team; and all the hospital staff who accepted the interviewers' presence and referred casualties.
Funding sources We acknowledge funding from the  French Ministry of Equipment, Transport, Housing, Tourism  and the  Sea (Program Predit 3 "New Knowledge in the Field of Road Safety ":  N°SU0400066 ), from the  National Agency for Research (Program Predit "Safe , reliable and adapted transport" No. ANR-07-TSFA-007-01 ), from the  French Ministry of Health  ( Program PHRC 2003: PHRC-N03  and  PHRC 2005: PHRC-N051 ) and from the  Road Safety Foundation  ( 2010/MP/01 /). Received: 28 September 2015 Accepted: 18 December 2015.
In order to estimate seroprevalence with a 90% confidence level and 5% desired precision, at least 52 animals needed to be sampled per region. We sampled 60 buffalo per wildlife area. In both districts, cattle crush pens to be sampled were chosen according to their proximity to protected area boundaries and the availability of the National Veterinary Services teams to operate in the area. In this manner, 10 crush pens were selected in Ngamiland District and five in Chobe District. Cattle in this region are regularly vaccinated against FMD, brucellosis, and other diseases but are not vaccinated against RVF. Data on cattle numbers at crush pens were not available at the time of sampling. From previous fieldwork in the study regions, we estimated cattle numbers at 500 animals per crush pen. Using an estimated seroprevalence of 5% derived from previous studies conducted in sub-Saharan Africa  (23, 24) , at least 48 animals per crush pen would need to be sampled to estimate seroprevalence with a 90% confidence level and a desired precision of 5%.
Statistical Analysis Sample sizes were calculated with the use of Epi Tools (http: //epitools. ausvet. com. au). Descriptive epidemiological measures were conducted using the software program Epi-Info (CDC, Atlanta, GA, USA) and were reported as percentages of positive animals with 95% Clopper-Pearson binomial confidence intervals (CI). The chi-square test for homogeneity of two populations was used to evaluate the potential influence of age, sex, and capture location on the observed seroprevalence in sampled buffalo, influence of location in sampled cattle, and species and region in the total sample. Stratified analyses were conducted to compare prevalence between species after stratifying by region. Values of p < 0. 05 were considered significant.
Buffalo Buffalo were sampled from 15 different herds. The herd size varied widely ranging between bachelor groups of five individuals to megaherds (e. g. , temporal aggregation of several subherds potentially reaching more than 1500 individuals). Among the sampled buffalo of known age, 10. 5% (n = 144) were young animals (1. 5 years or younger), 28% (n = 144) were subadults (1. 5-3 years), and 62% (n = 144) were adults (older than 3 years). The median estimated age of the sampled population was 5 years (2-9). Among animals sampled, 59% were female and 37% were male. For a limited number of individuals, age or sex data were not available (seven and five individuals, respectively). These samples were excluded from analyses of sex or age. Neutralizing antibodies against RVFV were detected in 10 out of the 15 herds sampled with values ranging between 6 and 29%.
Our data further suggest that, as shown in other parts of Southern Africa  (28) , buffalo might be important as a natural host playing a role in the amplification of RVFV in Northern Botswana. Other wildlife species may also be involved and act as amplification hosts  (22, 25, 32, 33). However, the full spectrum of wild and domestic host involvement and their contribution to the virus circulation in Northern Botswana is presently unknown. Weather conditions are known to affect the dynamics and intensity of RVF outbreaks through influence on both vector and host population dynamics and viral transmission. In the 1986 human survey (13), a higher seroprevalence of anti-RVFV antibodies was detected in December after the onset of heavy rains. Equally, the abortion cases reported in 2014 were detected in April most likely resulting from an infection during the rainy season suggesting that the virus could be more active during the first months of the year and could circulate periodically during the rainy season.
ACKNOWLEDGMENTS We would like to acknowledge the personnel from the  Veterinary Services of Botswana  and the  Department of Wildlife and National Parks  for facilitating staff, logistics, and permits for this work. This study was funded by the  Food and Agriculture Organization, EMPRES Animal Health Unit , and the  Wildlife Health and Ecology Unit, through two Letters of Agreement  with  CIRAD  ( PR 43231  and  PR 45371 ).
The origin of the BSI was determined by the doctor responsible for patient care, taking clinical and biological data into account. During the 2014 survey period, incontinence, recent history of hospitalization, living in a nursing home, and recent antibiotic treatment were also recorded. Data were analyzed with Epi Info version 6 software. Ethics approval for the survey was obtained from the Réseau Alerte Investigation Surveillance des Infections Nosocomiales (RAISIN). The study was managed jointly with the directors of the hospitals, the doctors responsible for patient care and the regional infection-control team.
(2014). MLST was used to study the genetic diversity of the isolates, as described by  Wirth et al. (2006). All the allelic profiles obtained were analyzed, sequence type (ST) and ST complex (STC) were assigned according to the E. coli MLST database (http:// mlst. warwick. ac. uk/mlst/). STCs were defined as groups of at least 3 STs sharing 6 alleles in pair-wise comparisons. Previous publications and the eBURST algorithm were used to assign STCs to STs that were not available from the E. coli MLST database. A neighbor-joining tree of the seven concatenated MLST genes was also used to classify our collection of isolates. The analysis was performed with MEGA6 software.
Data Analysis We took fluctuations in the population of the region during the study period into account, by expressing the incidence of CA-BSI cases (numerator) relative to the population of the region (denominator). The population data were obtained from the INSEE national database (Institut National de la Statistique et des Etudes Economiques, www. insee. fr). As our network covered most of the hospital centers of the region, we were confident that the participating centers were representative of the whole region. The statistical significance of temporal trends was assessed by Poisson or negative binomial regression for incidence rates, the Cochran-Armitage test for proportions and Spearman's rank correlation analysis for continuous variables. For categorical variables, we used Pearson's chi-squared test to compare groups.
Conclusion This study has incidence data spanning 2005-2014 and provides insight into changes in the epidemiological features of BSIs due to E. coli. Nevertheless, molecular data were only obtained for the isolates recovered in 2014. Further studies should be performed in different geographic areas and with the incorporation of more clinical data, to improve our understanding of the dynamics of the increase in E. coli BSIs in the elderly population. Molecular studies should investigate the genetic factors associated with the ability of the group A/B1 isolates to cause increasing numbers of invasive infections. In addition, investigations are required to determine whether these antibiotic-resistant isolates colonizing the human gut originate from contaminated food products.
Data set A total of 21 species of raptors were considered in our study. Data concerning body mass (BM), wing span (WS), wing area (WA)  (Clark 1999, Bruderer and Boldt 2001) , and maximum water crossing length (WCL) regularly performed by adult birds were collected from published literature  (Kerlinger, 1989; Kjellén, 1992; Kjellén and Roos, 2000; Zalles and Bildstein, 2000; Hake et al. , 2001; Meyburg et al. , 2002 Meyburg et al. , , 2003 Meyburg et al. , , 2011 Meyburg et al. , , 2012;; Meyburg and Meyburg, 2009; Panuccio et al. , 2004 Panuccio et al. , , 2012;; Agostini et al. , 2000 Agostini et al. , , 2001 Agostini et al. , , 2004 Agostini et al. , , 2012;; Agostini and Panuccio, 2010; Ceccolini et al. , 2009; Mellone et al. , 2011a Mellone et al. , , 2011b;; Limiñana et al. , 2012; Trierweiler et al.
Statistical analyses We used Pearson' s correlation tests to evaluate the relationships among the following variables: aspect ratio, wing load (body mass/wing area), and energy consumption during powered flight to evaluate the collinearity among possible predictors of the water crossing length. We used a Shapiro-Wilk test to determine whether data were normally distributed. Energy consumption during powered flight (PF) was log-transformed to meet the assumption of normality. Before modelling, we tested whether the observed variation in the water crossing trait was determined by a phylogenetic relationship among species. Since several possible phylogenetic comparative methods are available in the literature, we decided to compare results derived from at least two of the most used ones. At first we tested whether the phylogenetic signal (defined as the non-independence of a trait among species) was significantly different from 0 using a randomization procedure  (Blomberg et al.
, 2003). If the ratio of the observed residual standard error on its randomized expected value among species (K) is < 1, the trait analyzed is not significantly influenced by the phylogenetic relationships. The phylogeny link among species was tested using the "phylosignal" function in the R package "picante"  (Kembel et al. , 2010). As a second phylogenetic method, we built 1000 phylogenetic trees using the website birdtree. org (Jetz et al. , 2012 , 2014 , Rubolini et al. , 2015). After that, we have computed a consensus tree using MEGA 5. 0 software (Fig. 1 ;  Tamura et al. , 2011). In the analysis, we have fitted and compared two Generalized Least Squares (GLS) linear models, one with phylogeny correlation structure  (Grafen, 1989 ) and one without it, to explain variation in water crossing length (WCL) using energy consumption of powered flight and aspect ratio as fixed effects (phylogenetic tree available as supplementary material).
Discussion Our results suggest that energy consumption during PF is the most important variable affecting water-crossing tendencies in raptors (Fig. 3 ). Considering the aspect ratio (AR) which is the other variable affecting the water crossing length (WCL), we can find some substantial discrepancies (Fig. 4 ) in comparison with a previous study  (Kerlinger, 1985). Since AR does not consider the shape of the wing tip, in particular if it is more or less pointed or rounded, it could be less suitable for   and Bildstein, 2000; Limiñana et al. , 2012. explaining the WCL of birds than the PF value. Indeed the expected positive influence of AR on WCL does not have a significant effect in our dataset (Fig. 4 , Table  2 ). Conversely, PF values give us a direct measure of energy consumption during powered flight taking into account both the wing shape and the weight of the bird  (Pennycuick, 2008).
Acknowledgments We are grateful to  Zhi-Yun Jia  (Executive Editor) and to two anonymous referees for their useful comments on an earlier draft of the manuscript and to  Kelsey Horvath  for reviewing the English of the manuscript. We wish to thank MEDRAPTORS (www. raptormigration. org), a network of ornithologists involved in the research and the protection of migrating birds of prey through specific projects and observation camps.
Methods and Materials Data from inoperable patients with non-small-cell lung cancer treated with SBRT between August 2007 and April 2013 were retrospectively analyzed. Patients with Performance Status under or equal to 2 with T1 or T2 tumors over 15 mm without lymph node or distant metastasis were included in this study. Initial staging included CT-Scan and 18 F-FDG-PET-Scan. Patients with histologically unverified tumors were treated if the lesion grew on two consecutive CT-Scans (two months apart) and had an FDG uptake. A tumor board discussed each patient's case with a thoracic surgeon. Previous contra-or ipsilateral lung surgery or radiation therapy was allowed. Patients did not receive chemotherapy before, during, or after treatment until any progression. A thin-sliced CT-scan without contrast was recorded with millimetric slices.
The Gross Tumor Volume (GTV) and organs at risk (spinal cord, left and right lung, heart, and esophagus) were contoured. No GTV to CTV margin was added. A 3-mm margin was added to the GTV to create the planning target volume (PTV). Patients were treated with tumor tracking (with or without fiducial placement) or without tracking after an ITV was contoured on a 4D CT-Scan. Treatments were planned on Accuray's Multiplan software. The prescription dose was calculated with the Monte Carlo algorithm with a 2% uncertainty on a 1x1x1-mm resolution with Gaussian smoothing. The following prescription method was adopted. 50% of the GTV was to receive the dose as follows: 54 Gy in three fractions for peripheral lesions with a diameter under 30 mm, 60 Gy in three fractions for lesions with a diameter over 30 mm, and 55 Gy in five fractions for central lesions.
Toxicity was assessed with the CTCAE v4. 0 scale  [11]. All plans were recalculated with TA and MC with identical monitor units per beam to assess the correlation between the two algorithms. We estimated the average difference between the calculated TA dose and the dose actually delivered: dose to 95% of the PTV (D95PTV), to 98% (D98GTV) and 50% (D50GTV) of the GTV, average dose received by the lungs and V20 lungs calculated with MC were chosen as representative dosimetric indices for comparison. Statistical analysis was performed with Stata v11. 2 (StataCorp. 2009. Stata Statistical Software: Release 11. College Station, TX: StataCorp LP). Pearson's chi-square tests were used to compare groups when events frequencies were more than 5. Fisher exact tests were used when events frequencies were less than 5.
Statistics The subjects' baseline characteristics were summarized using the means and standard deviations or frequencies and percentages, as appropriate. The normality of the data distribution was verified using the skewness-kurtosis test. Because the number of observations was >40 for each group, no transformations were applied to the variables of interest. Subjects were separated into two groups based on the overuse or no overuse of a PPI. Between-group comparisons were performed using an independent samples t-test or Chi-square test, as appropriate. Univariate and multiple linear logistic analyses were performed to specify the association between overuse (dependent variable) and multimorbidities (independent variable), adjusted by the subjects' baseline characteristics. Odds ratios (OR) with 95% confidence intervals (95% CI) were presented.
Quality assessment of the raw sequencing data was done using FASTQC. Reads with Ͼ70% bases with quality lower than Phred score of 20 were removed. Quality score filtered reads were then aligned to the mouse reference genome NCBI37 (mm9) using Burrows-Wheeler aligner. Identification of transcription binding sites was performed using the peak calling algorithm, QuEST. A -fold-change cutoff of three was applied to identify peaks in the experimental ChIP that were significantly above background. The identified peaks were annotated using HOMER. Peaks were mapped to miRNAs if they were located upstream or upstream of an miRNA locus (independent of distance) and no intervening gene was present between the miRNA and the binding site. MicroRNA Microarrays-53A cells were incubated for 48 h with mifepristone to induce the expression of dominant-negative mutant HNF-1␤ or vehicle as a control.
Quantitative real-time PCR was performed by loading samples in triplicate on a CFX Connect TM Real-time PCR detection system. 18S and 5S RNA were used to normalize expression of mRNA and miRNA, respectively. Data were analyzed using the Bio-Rad CFX software. For semi-quantitative PCR, products were loaded on a 1% agarose gels and stained with ethidium bromide. The images were visualized and analyzed on a Gel Doc TM XRϩ system (Bio-Rad). The sequences of the PCR primers are shown in Table  1. Statistical Analysis-Data are shown as the mean Ϯ S. E. or mean Ϯ S. D. as indicated in the figure legends. Statistical analysis was performed using Student's t tests. Analysis of variance followed by Dunnett's post hoc test was used for multiple comparisons.
3B ). This region contains two evolutionary conserved HNF-1␤ binding sites, S1 and S2, which are separated by ϳ1. 5 kb (Fig. 3, B  and C ). Quantitative ChIP analysis revealed that HNF-1␤ binding is enriched ϳ3-fold at the S1 site and 6-fold at the S2 site (Fig. 3D ). ChIP performed using an antibody that recognizes the phosphorylated C-terminal domain of RNA polymerase II showed enrichment at the S1 and S2 sites, indicating that this region may be transcriptionally active (Fig. 3E ). Analysis of the mouse ENCODE database indicated that epigenetic marks of active transcription, including H3K4me3, H3K27ac, and H3K4me1, co-localized with the HNF-1␤ binding sites in adult kidney (Fig. 3B ). Taken together, these results indicate that the genomic region containing the HNF-1␤ binding sites is bound by RNA polymerase II and is transcriptionally active.
* This work was supported, in whole or in part, by  National Institutes of Health (NIH)  Grants  R37DK042921  (to P. I. ),  P30DK079328  (to P. I. ),  K08DK084311  (to V. P. ),  NIH   Training Grant   T32DK007257  (to P. I. ). The authors declare that they have no conflicts of interest with the contents of this article. 1Supported by  Fondation pour la Recherche Médicale  (equipe FRM) and the  Fondation Bettencourt-Schueller  ( Prix Coup d'Elan) ;  European Community 's  Seventh Framework Programme   FP7/2009  (agreement  241955 , SYSCILIA).
The improvements in resolution obtained thanks to this increases are playing a fundamental role in the understanding of existing experiments in observational cosmology, as well as in the design of future ones. The trend is expected to at least continue (green line) or accelerate thanks to the increasing availability of supercomputers with very large memory (red line), so by the year 2025 the expectation is to have 0. 01 to 1. 0 Exa-objects (10 16 to 10 18 objects) per simulation. The volume of scientific data is also increasing exponentially. The best known example comes from particle physics, where the data volume has grown from hundreds of Gigabytes in the mid-1980s to over a hundred Petabytes stored by the detectors at CERN's Large Hadron Collider. Again, the trend is expected to continue or even accelerate, with expectations of reaching 0.
Deployments are restricted to single sites, with a few exceptions  [16] , and only manage the technical metadata needed to emulate a traditional file system. In parallel, redirector schemes have been deployed which return handles (in the form of URLs) to file system based storage at multiple sites. Examples are the xrootd and http/WebDAV redirectors deployed over the last few years by the CERN LHC experiments. It is clear that much more work is needed in order to attain DV components which fulfil the requirements at Zettabyte-Exascale. Key areas were activity should be stimulated are: • Information modelling on how to support in an extensible way a coherent view of dynamic scientific and technical metadata. • End-to-end support to enable global authentication, authorization and accounting.
• Exploration of the use of "Big Data" techniques, such as MapReduce  [17]  or NoSQL databases, to handle queries on complex metadata with volumes ranging from Terabytes to Petabytes. • High frequency metadata update schemes needed to maintain technical information on a per object basis, such as time of last access, input-output performance, etc. • Support for bulk operations on groups of objects, such as changing the access control on a complete dataset from being restricted to an experiment to being open-access. Work in these areas should yield in the next few years a number of suitable candidates for Zettabyte-Exascale DV, so that prototypes can be built and scalability verified before the onset of requirements.
These technical processes need to be linked to the analysis techniques and review processes used by scientists. Clearly, all data generated in an experiment or simulation need not be tagged with external bibliographic information (though it may be desirable or even required to tag it with internal information in order to support data provenance). Therefore, the concept of "depositing" data into a given category (internal or external) after the necessary checks have been performed is a useful one. A possible metaphor to be explored is that of Gatekeepers, which would use the bulk operations capabilities mentioned in section 4. 3 to appropriately tag entire datasets, which in the Zettabyte-Exascale may contain millions of objects amounting to Terabytes of data volume. The specification, design and prototyping of such Gatekeepers are areas where work should be stimulated.
4 n the last decade, new prognostic factors have refined the identification of CBF-AML patients at higher risk of relapse. 6] [7]  Among them, KIT and FLT3 gene mutations have been associated with a higher risk of relapse in many retrospective studies. In the CBF-2006 study (EudraCT n. 2006-005163-26; clinicaltrials. gov identifier: 00428558), the French AML Intergroup prospectively assessed the respective prognostic values of RTK mutations and MRD in CBF-AML patients in a therapeutic program consisting in three consecutive high-dose AraC courses (HiDAC) as consolidation program after achievement of complete remission (CR) by anthracycline and standard dose cytarabine induction sequence. 8 A high white blood cell count (WBC), KIT and/or FLT3 mutations, and a less than 3-log MRD reduction were associated with a higher risk of relapse, MRD reduction being the main prognostic factor identified by multivariate analysis.