dataesr/scientific-paragraphs-categorization huggingface dataset:
Discussion Functional annotation may be separated into two ways of analyses: a quantitative one by means of GES, which assigns scores to patients, and a qualitative one based on gene lists, which assigns a "Gene Ontology" enrichment score to a cluster representative gene list  [49]. In this work, we focused on GES scoring and used "Gene Ontology" enrichment score to corroborate our findings. Functional annotation according to the three age groups by means of clinico-pathological data was done to confirm that our cohort was representative of breast cancer population. Because of a possible ethnic bias, analyses were done twice: on the whole cohort and on the Caucasian one. Finally, there were only slight differences between whole cohort results and Caucasian results. Statistical comparisons could not be done because these cohorts were not independent.
(3) We predicted that the abundance of pathogenic bacteria on nestlings would increase with delay in laying date and that this effect would be stronger in a year characterized by unfavorable environmental conditions. (4) We predicted that hatching failure and fledging failure would increase in nests with a higher abundance of bacteria, even when controlling statistically for the potentially confounding effects of laying date, clutch size, and number of years occupied. We tested these predictions by relying on extensive samples of bacteria and reproductive data obtained from goshawks during 2012-2013. The goshawk is the second-most common avian predator of full-grown birds in Europe and North America  (Cramp and Simmons 1980; Burfield and van Bommel 2004). It is sexually size-dimorphic forming two size classes of predators potentially exploiting all species of the bird community by largely similar foraging habits  (Cramp and Simmons 1980; Kenward 2006).
Acknowledgments We thank  E. Lopez-Hern  andez and  E. Campanario-Mart  ınez for technical assistance with bacterial cultures and counts. JTN captured and ringed raptors with permission from the  Danish Ministry of the Environment  (J. nr. Ref. cabal) and the  Bird Ringing Centre at Zoological Museum, Copenhagen, Denmark. Funding was provided by the  Spanish Ministerio de Educaci on y Ciencia and European funds (FEDER)  ( CGL2010-19233-C03-01 ) and  Junta de Andaluc ıa  ( RNM 340 ) to JJS, and IG was supported by a  Marie Curie Intra-European Fellowship  ( PIEF-GA-2009-252145 ) within the  7th European Community Framework Programme.
Funding Information Funding was provided by the  Spanish Ministerio de Educaci on y Ciencia and European funds (FEDER)  ( CGL2010-19233-C03-01 ) and  Junta de Andaluc ıa  ( RNM 340 ) to JJS, IG was supported by a  Marie Curie Intra-European Fellowship  ( PIEF-GA-2009-252145 ) within the  7th European Community Framework Programme.
Barley-pea silage was distributed daily (~30 to 50 g/hen) on the floor in the veranda. Water consumption (l/ day) was automatically registered by a computer for the whole flock. Measurements, data collection and analyses Mortality, clinical examination and hen weight. Mortality was recorded daily on a room basis. For each flock, a sample of birds (n = 50 and 30 for years 1 and 2, respectively) from each room were weighed individually upon arrival at 18 weeks of age. Twice in each flock (at 36 and 65 weeks of age) a sample of 30 hens were caught in each room, weighed individually, and clinically examined for signs of disease and injury, and the plumage quality was scored (except at 36 weeks in year 1). Plumage condition was assessed using a four-point scale from 0 (no damage) to 3 (almost or completely devoid of feathers).
Data were multiplied by 6 to reflect the total length of top perches on both tiers, and proportions adjusted to the exact number of birds in each room on the day of observation. Manure weighing. In order to obtain a measure of the use of the aviary system and to supplement the video recordings of the use of top perches, we weighed the manure from the three manure conveyor belts in each section. This was done per room by calculating the time taken to empty each room based on the speed of the conveyor belt. The manure belts were emptied 12 or 24 h before the weighing, which started at 0800 h. For each of the six conveyor belts, a trough the width of the conveyor belt was placed on a custom-build scale at the end of the belt, the weigh scale was tared and the belt was started. The electronic display on the weigh scale was noted every 81 s thereby recording the accumulated amount of manure for each room.
Weighing was carried out on 15 days (24 h), and three nights (12 h) across the two flocks. The amount of manure was adjusted for sand content (estimated from the chemical analysis of manure samples) to prevent potential bias caused by soil from the feet of the hens, of which more would be deposited on the manure belt closest to the outdoor area. Statistical analyses. Data were analysed using Minitab (ver. 17, www. minitab. com) including all four treatments to allow direct comparisons between treatments with similar access to certain resources (see Table  1 ). A general linear model was fitted on a room basis to mortality and live weight gain, as well as hen live weight at each recording and breast plumage score at 65 weeks, with year/flock (n = 2) and treatment (n = 4) as fixed effects with their interaction.
Acknowledgements The authors are grateful for the hospitality and collaboration of Arend (André)  M. Hingstman , who owns and runs the organic egg production farm on which the study was carried out. They also thank  Erik L. Decker ,  Henrik K. Andersen ,  Carsten K. Christensen , and  Leif Rasmussen  for their indispensable technical and practical assistance. This project was funded by  Aarhus University  and the  Danish Ministry of Food, Agriculture and Fisheries.
Acknowledgment This material is based upon work supported in part by the  U. S. Army Research Laboratory  and the  U. S. Army Research Office  through the  Institute for Soldier Nanotechnologies , under contract number  W911NF-13-D-0001. The authors gratefully acknowledge  Rudolf Bratschitsch  for the photoluminescence experiments,  Marie-Pierre Crosnier-Lopez  for TEM images,  Guillaume Brotons  for SAXS experiments,  Alex Maznev ,  Alexey Lomonosov , and  Pavel Zinin  for fruitful discussions.
Acknowledgements: We thank  Maxim Pschenichnikov  for useful discussions. This work was supported by the  Netherlands Organization for Scientific Research (NWO)  through the " Stichting voor Fundamenteel Onderzoek der Materie" (FOM) research program. A. A. B. also acknowledges a  VENI grant  from the  NWO. A. A. B. is currently a  Royal Society University Research Fellow.
Z. S. and Z. C. acknowledge the ANR-2011-JS09-004-01-PvCoNano project and the EU Marie Curie Career Integration Grant (303824). A. A. B. , Z. S. and Z. C. thank Dutch-French Academy for the support through van Gogh grant. Supporting Information Available: sample preparation and morphology characterization, ultrafast spectroscopy setup description, additional transient absorption and 2DIR spectra, details of molecular dynamics simulations and 2D IR spectra calculations, modelled cation orientation trajectories. This material is available free of charge via the Internet http://pubs. acs. org.
Data treatment Each trial was recorded by an infra-red video camera located above the apparatus, which allowed off-line analysis of the exploratory behavior of the mouse lemur. The time spent exploring each object during T1 and T2, and the latency of the first exploratory behavior were recorded manually by an observer blind for animal age, for the ITI and for object novelty. Indeed, the amount of time spent exploring objects during the choice trial was scored before measuring the amount of exploration during the sample trial. This reverse-order of analysis ensured that the scorer was blind with respect to which object was familiar and which object was new. Object location and objects (familiar and novel) were used in a balanced manner among the age categories to reduce potential bias of location or object preference.
ACKNOWLEDGMENTS This work was financially supported as part of the  Pharma-Cog consortium  by the  European Community 's  Seventh Framework Programme  ( FP7/2007-2013 ) for the  Innovative Medicine Initiative  under Grant Agreement n •  115009. For further information please refer to www. pharmacog. org. We thank  Sabine Chahory , from the  National Veterinary School of Alfort , for performing the eye examinations, and  Eric Guéton ,  Léonie Lelli  and  Julia Marchal  for their help with the apparatus construction.
Exclusion criteria for all participants were the presence of conventional contraindications for CMR, claustrophobia, and arrhythmias (e. g. , atrial fibrillation, frequent atrial or ventricular ectopics). An ethics committee of the UK National Research Ethics Service approved the generic analysis of anonymized clinical scans. The genotyping project was approved by the UCL/UCLH Joint Research Ethics Committee. All participants gave written informed consent conforming to the Declaration of Helsinki  (fifth revision, 2000). Study data were collected and managed using REDCap electronic data capture tool (Research Electronic Data Capture, REDCap Software -Version 5. 9. 6, http://www. project-redcap. org/).
Measurement of other previously-described markers of HCM LV mitral angle, mitral papillary muscles angle, and LV-aortic root angle were analyzed on the open source software OsiriX® (http://www. osirix-viewer. com) as previously described  [20]. The angle between LV outflow tract and basal septum was also analyzed. Left ventricular end-diastolic sphericity index was measured (as previously described), as the ratio of LV end-diastolic diameter measured in short axis view at papillary muscle level (septal to lateral wall distance) divided by the LV end-diastolic long axis diameter measured in the apical 4 chamber view  [12]. LV end-diastolic and end-systolic eccentricity indexes were calculated in the short-axis at the level of papillary muscles as the ratio of septal to lateral wall distance divided by inferior to anterior wall distance  [11].
Statistical analysis Descriptive data were analyzed for normality using the Shapiro-Wilks test and were expressed as mean ± standard deviation except where otherwise stated. Categorical variables were compared using χ 2 tests. Non-categorical data were directly compared using paired t test. An optimal threshold value for SCx within this case-control population was calculated as the Youden Index derived from the area under the receiver operating characteristics curve. Mean variability within and between readers was evaluated using the mean of differences between two measurements. Paired measurements for repeatability of SCx were evaluated using the Bland-Altman method  [28]. A 2-sided p value <0. 05 was considered significant. Statistical analysis was performed using SPSS for Windows version 20.
Acknowledgements This work was undertaken at  University College London Hospitals/University College London , which receives a proportion of funding from the  Department of Health's NIHR Biomedical Research Centre funding scheme. Professors JCM , PME and WJM were funded by the  Higher Education Funding Council for England. Dr GC  is funded by the  University College London  ( UCL ), a  Charlotte and Yule Bogue Research Fellowship , and a  European Union Science and Technology Grant. Drs PR  and MM were supported by the  French Federation of Cardiology (France). Dr AN  was supported by a  Victoria Fellowship  from the  State Government of Victoria (Australia)  and by funding from the  Royal Australian College of Physicians. Dr SC  was founded by the 2014  ESC  research grant. We thank  Mrs Shaughan Dickie  and  Mrs Sarah Anderson  for their help.
The cases We analyzed prospectively 62 consecutive cases included in a preliminary study according to the classical indications and contraindications for cervical disk replacement. The aim of this work is to provide a snapshot of the evolution of our series since the first implantations. The surgeries were performed by two senior surgeons. There were 39 women and 23 men in this group. The average age was 45 ± 8 years (29-60). The implantation was on a single level in 74 % of the CP ESP and on two levels in 26 %. Globally, 71 CP ESP prostheses were analyzed (Table  4 ). Clinical data and X-rays were collected at the preoperative time and at 3, 6, 12 and 24 months post-op. The functional results were measured using Neck and Arm VAS, NDI, SF-36 (physical component PCS and mental component MCS).
General NMR spectra were recorded on an NMR 400 WP apparatus (Bruker BioSpin GmbH, Silberstreifen 4, 76287Rheinstetten, Germany). FAB-MS spectra were recorded on a JOEL JMS-DX 300 spectrophotometer (JEOL Europe, Planet II, Gebouw B. , Leuvensestreenweg 542, B-1930 Zaventem, Belgium). Uncorrected points of fusion were assessed with a Buchi 510 apparatus (BüchiLabortechnik AG, Meierseggstrasse 40, 9230Flawil, Switzerland). Cyclic voltammetry was carried out on a PAR-273 potentiostat/galvanostat (Alltest Instruments, Inc. 500 Central Ave. Farmingdale, NJ, USA). All computations were performed with the Gaussian 09 program package (Gaussian, Inc. 340 Quinnipiac St Bldg 40 Wallingford, CT, USA) 8 using the 6-31G(d,p) basis set. Density functional theory (DFT) calculations were carried out using a B3LYP method (public field method).
While some of the variation may be attributed to a purely random molecular clock pattern, in GP, VP35, NP and L there are some amino acid variations that are present in over ,15% of the genomes sampled. For example, in GP there is an A to V substitution in ,70. 5% of the genomes sampled compared to the reference genome. Implications of the mutations within GP in relation to immune escape of therapeutics and vaccines will need to be assessed in pseudotype neutralization assays using EBOV monoclonal antibodies and serum from people who have been vaccinated. Online Content Methods, along with any additional Extended Data display items and Source Data, are available in the online version of the paper; references unique to these sections appear only in the online paper.
Acknowledgements The authors would like to acknowledge that the EMLab response and the subsequent EBOV genome sequencing study would not have been possible without the extensive support from the many different agencies and organisations working in the West African EBOV disease outbreak region. EMLab worked with  WHO, MSF  and the Guinean authorities to tackle the outbreak in the Gueckedou area where the samples from this study were collected. We thank those who helped make this possible and the Guinean authorities for their decision to release the diagnostic samples to EMLab for shipment to Europe to undergo further analysis, including sequencing. We acknowledge  Air France ,  Brussels Airlines  and  Virgin Airlines  for transporting EMLab personnel and equipment in and out of West Africa during the outbreak period;  World Courier  for shipping our EBOV-positive samples out of Guinea to Europe; and the logistics support units and pilots and drivers of  WHO/United Nations in West Africa  for transporting our people and equipment throughout the region, and especially the drivers who made the 28 h round trip journey from Conakry to enable the EMLab unit to be established and resupplied in Gueckedou.
We appreciate the work of the numerous European Embassies operating in West Africa who provided emergency support to our personnel at times of need. We thank  M. Bull ,  J. Lewis ,  P. Payne  and  S. Leach  from the  Microbial Risk Assessment and Behavioural Science Team, Emergency Response Department, Public Health England ;  J. Tree  from  Public Health England  for help with GenBank submission; and  S. Price  and  I. Stewart  for helping with the running of our software on BlueCrystal,  University of Bristol. We thank the people of  West Africa  for their gratitude and optimism, and for their positive attitude to our presence that we encountered on the daily journey to the  Ebola Treatment Centre in Gueckedou. We acknowledge the efforts of the late  Dr Lamine Ouendeno , who was one of the first healthcare workers to die during the current EBVD outbreak.
We also thank  Isabel  and  Maurice Ouendeno  for providing us with food and shelter whilst delivering our Ebola response duties. This work was carried out in the context of the project EVIDENT (Ebola virus disease: correlates of protection, determinants of outcome, and clinical management) that received funding from the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement No  666100  and in the context of service contract  IFS/2011/272-372  funded by  Directorate-General for International Cooperation and Development. The EMLab is a technical partner in the  WHO Emerging and Dangerous Pathogens Laboratory Network (EDPLN) , and the  Global Outbreak Alert and Response Network (GOARN)  and the deployments in West Africa have been coordinated and supported by the  GOARN Operational Support Team at WHO/HQ.
The clinical status is also indicated as well as malaria co-infection where known. Extracted RNA was DNase treated with Turbo DNase (Ambion) using the rigorous protocol. RNA sequencing libraries were prepared from the resultant RNA using the Epicentre ScriptSeq v2 RNA-Seq Library Preparation Kit. Following 10-15 cycles of amplification, libraries were purified using AMPure XP beads. Each library was quantified using Qubit and the size distribution assessed using the Agilent 2100 Bioanalyzer. These final libraries were pooled in equimolar amounts using the Qubit and Bioanalyzer data with 9-10 libraries per pool. The quantity and quality of the pool was assessed by Bioanalyzer and subsequently by qPCR using the Illumina Library Quantification Kit from Kapa on a Roche Light Cycler LC480II according to manufacturer's instructions.
Most often, data recorded through 2D scans is followed by projection of v in order to extract the two orthogonal transverse phase gradient components. One-dimensional scans with much less points have also proved to be efficient for recovering the 1D phase gradient  [31]. The absorption, or here the transmission image T , can be correctly calculated free from the flat field correction errors that occur in presence of a strongly dephasing object and/or of a high magnification projection geometry  [25, 44]. Its formulae can be obtained by consideration of Fig. 4 : T (r) = µ (f (r)) µ (g(r + Γs s v)) (4) where µ denotes the mean operator over the variable p. Finally, the darkfield image D f can be reconstructed by considering the decrease of speckle contrast that occurs when introducing the sample in the beam.
Weather data Data were collected from the agrometeorological station mentioned above. This CIMEL 140 device (CIMEL Electronique, Paris, France) was positioned at a height of 1. 50 m above the ground and recorded air temperature every 20 minutes. The output consisted of daily averages, each computed with 72 data values. Over the period from 1996 to 2013, a total of 5173 averages were computed and these daily averages ranged from -5°C to 26°C between 1 September and 31 May, with 98% of the values between 3°C and 20°C. The weather station also recorded hourly rain intensity with a 0. 2 mm tipping bucket rain gauge.
Construction and validation of a predictive model for ascospore release Based on the ABCD function described above, a model was constructed to fit ascospore release as a function of thermal time. Using 11 data sets from 1996 to 2008, regression analysis was carried out with the Levenberg-Marquardt algorithm  (Marquardt, 1963)  to parameterise the 33 possible functions proposed by the CurveExpert 1. 3 software (http://www. curveexpert. net). Residual analysis and a Student's T test were used to compare the fit of this ABCD-based model with that of a reference NH-based model adapted to climatic conditions and dynamics of ascospore release of southern France  (Lagarde, 1988). The ABCD-based model was then validated with data sets of 2009, 2011, 2012 and 2013 and its predictive value was compared to that of the reference NH-based model.
Accepted Article This article is protected by copyright. All rights reserved. As the occurrence of rainy days before the onset of ascospore release was also reported to influence the maturation process  (Stensvand et al. , 2006b) , this phenomenon was investigated in the context of Southern France. For this, the relation between the number of rainy days before ascospore release and the estimated date of its onset was examined through regression analysis, using data sets from 1996 to 2008. In a first step, the period considered for the quantification of rainy days was defined as the month preceding the first ascospore maturity and the minimal amount of recorded rain needed for a day to be considered as "rainy" was 0. 2 mm  (Stensvand et al. , 2006b). The onset of ascospore release was assessed as the date when 10% of cumulated ascospore release was reached.
This date was estimated each year by linear interpolation from the observed data. Only 10 of the 11 data sets were used at this stage, as the dynamics of ascospore release did not allow an accurate interpolation in 2000. On that year, the first rain occurred 40 days after the observation of the first mature ascospores and resulted in the sudden release of 41% of the total ascospore stock (Figure  4 ). The 10 years were ranked according to the timing of estimated 10% ascospore release dates. Regression analysis was then carried out on the number of rainy days of a year vs its rank for ascospore release. In a second step, the relation between the number of rainy days before ascospore release and the estimated date of its onset was refined. For this, the minimal amount of recorded rain needed for a day to be considered as "rainy" was adjusted (among 29 threshold values between 0.
Observed ascospore release Over the 13 years of observations, the first mature ascospores were recorded over a broad range of calendar dates, spanning from 7 February to 27 March (Table  2 ). The first and last dates of ascospore release also varied widely over the years. The total numbers of ascospores counted over a season varied from less than 500 to over 48000. Due to the low spore counts, the data from 1998 and 2003 were not considered as sufficiently reliable and were not retained for further analysis. Another year (2000) was somewhat atypical with a 40-day long dry period after the first observation of mature ascospores, which resulted in the release of 41% of the yearly ascospore potential at the first rain. This year was retained for modelling, to take into account the widest possible range of climatic variability.
Comparison of thermal time scales With this 1 January biofix, higher ρ values were obtained with all thermal time scales based on non-linear temperature functions than with the NH model (Table  1 ). The ρ value of the NH model remained low when taking the date of the first observation of mature ascospores as a biofix. The ABCD function and the two continuously differentiable functions with similar shapes (modified Gauss and Analytis) all had very similar ρ values. These three functions also had a shape similar to that of the function established by  James & Sutton (1982b) , which presented a slightly lower but comparable ρ value (Table  1 ). Predictive model for ascospore release, using the parameterised ABCD thermal time scale Based on regression analysis, the best fit to the 11 ascospore release datasets (R² = 0.