dataesr/scientific-paragraphs-categorization huggingface dataset:
There have also been reports of different use of ungulate carcasses by adults compared to subadults  (Young & Mccabe, 1997)  as well as seasonal patterns of prey consumption by males and females  (Milakovic & Parker, 2013). We used an "all-combinations" approach to select the three bestperforming models as ranked by the Akaike's information criterion (AIC) with a correction for small sample size (AICc) using the R statistical package MuMIn  (Burnham & Anderson, 2002; R Core Team 2014 ). Among the best three models, we selected those with the highest sensitivity (proportion of correctly classified positive events: predation events or small/medium carcass). Model performance was also assessed by plotting the receiver operating characteristic curves (ROC)  (Fielding & Bell, 1997)  and by comparing sensitivity at multiple probability cutoff thresholds (0.
| DISCUSSION Our method, based on an advanced spatiotemporal algorithm (spacetime permutation scan statistic) used on almost real-time GPS data to detect predation event clusters, allowed for early identification (within two weeks from cluster) and proved to be very efficient in detecting grizzly bear predation events in west-central Alberta. While there are computational and logistical limitations to this approach, we argue that this result is a significant advance in our ability to measure predation rates, prey characteristics, and predator behavior. When applied to randomly selected daily GPS locations, our clustering methods successfully identified grizzly bear predation events 85. 1% of the time. Only four carcasses in the 2006-2007 dataset were not identified as predation events. The first two were moose calves, the third was likely a scavenging event, and the fourth was an adult moose.
While not all of these misclassifications can be directly accounted for, even with short-interval GPS data  (Cristescu et al. , 2014b; Webb et al. , 2008)  small prey and scavenging events can go undetected due to the short time it takes to consume or move the carcass  (Cavalcanti & Gese, 2010; Webb et al. , 2008). Using our cluster-oriented approach, we increased the probability of finding a carcass site by 2. 75 times. The probability increased from 0. 058 carcasses per site visit in 2006-2007 to 0. 161 in 2013-2014. While this might be attributed to simply a difference in predation patterns between sampling periods, we suggest that a result of this magnitude represents an improvement in detection between the two datasets due to the clustering method combined with quick site visits. Early detection of predation events (mean = 11 days) represented a substantial improvement over previous studies.
ACKNOWLEDGMENTS Special thanks go to the fRI  Research Grizzly Bear Program  for funding support and field assistance. Animals were captured according to animal care protocol # 20010016  ( University of Saskatchewan ). Funding was provided by the  Canadian Association of Petroleum Producers ,  Weyerhaeuser Company ,  Shell ,  Alberta Conservation Association , and  NSERC. We thank  Karen Graham  for field assistance and data preparation. We thank  Steve Wotton  of  Peregrine Helicopters ,  Laura Finnegan , and  Tracy McKay  for their support in collecting field data. We thank the field assistants  C. Arnison ,  M. Cavedon ,  C. Dubesky ,  D. Ducros ,  C. Gubili ,  L. Hibbeler , and  B. McLeod.
Litter and/or permanent mother effects are commonly included in genetic analysis of domestic pig data to avoid overestimation of genetic variances due to partial confounding of genetic effects with early-life environmental effects. Litter effects account for a nonheritable covariance among phenotypes of litter mates that may occur because they share the same early-life environment. In addition, permanent environmental effects of the mother account for nongenetic covariances among offspring of the same mother born in different litters, originating from, for example, lifelong differences in maternal ability among mothers. Data were analyzed using restricted maximum likelihood methodology as implemented in the ASReml software package  (Gilmour et al. , 2006). The basic model included the fixed effects of number of group mates (10 levels), sex (castrated male or female), the combination of herd, year and season as a factor, age and age 2 at weighing as covariates, and the random effects of the physical pen, the group identity, the litter of birth and the permanent environment of the mother.
Methods We reviewed several databases (PubMed, Science Direct, MEDLINE, LISTA, Web of Sciences, Scopus, and Google Scholar) to search for official documents, in English or French, published after 2010. We consulted the legislative and policy database (Faolex: http://faolex. fao. org/) of the Food and Agriculture Organization of the United Nations (FAO) and made contact with the FAO and OIE national focal points for veterinary products. We retrieved documents from eight countries, including 16 legal documents and 11 policies, related strategies, and action plans (table  1 ). For each document we extracted information on the topic (drug and medicine production and marketing, drug and medicine use, antibiotic resistance surveillance and monitoring); the competent authority in charge; the type of document (policy or legal document); the objective(s); the key components and limitations.
MATeRIAlS AND MeThODS The data were kindly given by JBS Foods Brazil (one of the biggest companies producing broilers in Brazil), so that the owner gave full permission to use it. This did not involve endangered species. As it is a statistical analysis of the biggest dataset of broiler production in the world, we do not have other information regarding sacrifice procedure other than those provided by certification. Indeed, a large number of chicken producing units of the JBS Foods are certified by international bodies such as: Global GAP, BRC, Alo Free and follow important codes of good practices of production and slaughter of global customers  (GLOBALGAP, 2013). Data collection: All data was collected over one year (2012) from 3516 commercial chicken flocks located in north region to state of Santa Catarina-Brazil, raised on 977 different farms belonging to one major producer company.
The daily slaughtering of the production unit is about 160,000 chickens, essentially meant for export. Flock is defined as a group of chickens placed in a house and present in the house at the same time. Typical commercial flock size was between 10,000 and 30,000 birds (Figure  1 ), with a mean of 29,340 individuals. The performance results of different broiler flocks were collected as well as the features of the shed from which they belonged. This represents data for 103,160,987 male broiler chickens. Birds and feed: Male broiler chicks Ross 308 ® breed were reared from one day old to forty-two day old. The chickens were fed ad libitum with a diet specific for each phase of growth, following the recommendations of the broiler management manual, which also lists the dry bulb temperatures required to achieve good growing performances.
These data were then confronted with data of performance (Food conversion rate) and welfare (assessed through percentage of mortality of each flock). Performance: Aiming at standardizing data to allow more accurate analysis, feed conversion ratio was adjusted to 2. 0 kg live weight. Live weight was adjusted by dividing total flock weight by days until slaughter. Feed conversion ratio (FCR) was calculated dividing total flock feed intake by total flock weight gain during the grow-out. Corrected feed conversion ratio (cFCR), using cFCR for 2. 0 standard live weight, was calculated using the following equation  (Patricio et al. , 2012) : cFCR= (SW -AW)/3. 2 + FCR. Where: SW = standard weight, AW = average flock weight, 3. 2 = correction factor, FCR= flock feed conversion ratio. Mortality was assessed at the end of the growing process.
ACKNOWLEDGMENT Th e authors would like to express their sincere gratitude to the company  FEIX NUTRITION d. o. o. Feed Additives , 21000  Novi Sad, Serbia , who provided Actisaf Sc 47 ® (product of  Société Industrielle Lesaff re, Marcq-en-Baroeul, France ) for this research. Also, this paper is a result of the research within the project  TR 31084 , funded by the  Ministry of Education, Science and Technological Development, Republic of Serbia.
Eur. asking for deletion of the ATT from all monographs. Subsequent to the international EPAA workshop, this request was discussed at the next 'Group 15' meeting, in Spring 2016, and will also be considered by other relevant EDQM working groups. With regard to the WHO, it was agreed to present the recommendations from the EPAA workshop at the upcoming WHO Expert Committee on Biological Standardization (ECBS) meeting, proposing to include deletion of the test for innocuity on the agenda for the 2016 ECBS meeting. Generally, industry representatives, in striving for deletion of the ATT, were invited to approach relevant regulators via their interest groups. Companies were further encouraged to include proposals for the deletion of these tests in their applications for batch release even though this would necessitate submission of full in-process testing data to justify the deletion.
Statistical analysis: Economic model environment and software The economic model was run for 10,000 times using a Latin Hypercube simulation using the software package @Risk (@Risk version 5. 5. 0 Professional edition, 2009,© Palisade Corporation, 31 Decker Road, Newfield, NY) add-in for Microsoft Excel (©Microsoft Office Professional Edition, 2010). The results of the simulation were used to determine the mean, the 2. 5th percentile and the 97. 5th percentile of the resulting distribution of the cost index. A sensitivity analysis was run using rank order correlation coefficient, in order to avoid any assumption about the relationship between inputs and outputs  (Vose, 2000). This analysis provided coefficients that illustrate the impact of the variability or uncertainty of the inputs on the uncertainty of the output (the cost index).
ERα, PR, and Ki-67 were assessed based on the number of positive nuclei among > 500 neoplastic cells (manual image analysis, Image J software, National Institute of Health, Bethesda, Maryland, USA), and considered positive at threshold ≥ 10% for ERα and PR  [45, 49] , CK5/6, and EGFR  [50]. The > 33. 3% threshold for Ki-67 was evaluated by the receiver-operator-characteristic curve calculated for 2-year cancer-specific mortality. HER2 was scored 0 for no staining at all or incomplete, faint/barely perceptible membrane staining in ≤ 10% of tumor cells; 1 + for incomplete and faint/barely perceptible membrane staining in > 10% of tumor cells; 2 + for circumferential and incomplete and/ or weak/moderate membrane staining in > 10% of tumor cells; or incomplete and circumferential membrane staining that is intense but within ≤ 10% of tumor cells; and 3 + for circumferential, complete, and intense membrane staining in > 10% of tumor cells.
Statistical analyses The MedCalc ® statistical software (Ostend, Belgium) was used. Continuous variables are expressed as median, [range], mean ± standard deviation. Correlations between categorical variables were analyzed using the Pearson Chi-square test. The Kaplan-Meier method and log-rank tests were used for univariate survival analyses, and Cox proportional hazards models for multivariate survival analyses, whose results are reported using the Hazard Ratio (HR), its confidence interval (95%-CI), and the p value of each covariate. For all statistical tests, a p value < 0. 05 was considered significant.
Acknowledgements The authors deeply acknowledge  Dr. Chand Khanna  ( EthosDiscovery, EthosVeterinary Health ) for his help in reviewing the manuscript. The authors thank  Dr. Claire Hanzenne ,  Dr. Ingrid Bemelmans ,  Dr. Floriane Morio , and  Dr. Clotilde de Brito , who helped in collecting the clinical and follow-up data. The authors also thank  Dr. Laëtitia Jaillardon  for her involvement in data analysis, the veterinary pathologists ( Dr. Jean-Loïc Le Net ,  Dr. Virginie Théau ,  Dr. Pierre Lagourette ,  Dr. Olivier Albaric  and  Dr. Sophie Labrut ) who performed the initial diagnoses of canine mammary carcinomas, as well as the technicians in histopathology ( Mr. Bernard Fernandez ,  Mrs. Florence Lezin , and  Mrs. Catherine Guéreaud ) who made the slides. Finally, we thank the referring veterinarians and the owners of the dogs included in this study, who gave us the clinical and follow-up data.
Statistical analyses The MedCalc ® statistical software (Ostend, Belgium) was used. Continuous variables are expressed as median [range], mean ± standard deviation. Correlations between categorical variables were analyzed using the Pearson χ 2 test. The Kaplan-Meier method and logrank tests were used for univariate survival analyses, and Cox proportional hazards models for multivariate survival analyses, whose results are reported using the Hazard Ratio (HR), its confidence interval (95%-CI), and the p value of each covariate. For all statistical tests, a p-value < 0. 05 was considered significant.
Acknowledgements The authors deeply acknowledge the help of  Dr. Chand Khanna  ( EthosDiscovery, EthosVeterinary Health ) in reviewing the manuscript. The authors thank  Dr. Claire Hanzenne ,  Dr. Floriane Morio , and  Dr. Clotilde de Brito , who helped in collecting the clinical and follow-up data of the dogs. The authors also thank the veterinary pathologists ( Dr. Jean-Loïc Le Net ,  Dr. Virginie Théau ,  Dr. Pierre Lagourette ,  Dr. Olivier Albaric  and  Dr. Sophie Labrut ) who performed the initial diagnoses of canine mammary carcinomas, as well as  Mr. Bernard Fernandez ,  Mrs. Florence Lézin , and  Mrs. Catherine Guéreaud  for technical support. Finally, the authors thank the referring veterinarians and the owners of the dogs included in this study, who gave us the clinical and follow-up data.
malmoense. During the following 3-month period, M. malmoense was repeatedly isolated from six sputum and bronchial aspiration control specimens. According to local procedures, isolates were recovered from BACTEC ™ MGIT ™ (Becton-Dickinson, New Jersey, United States) radiometric mycobacterial broth culture system with incubation at 37 °C for an average of 25 days. Identification to the species level was confirmed by mass spectrometry and RNA polymerase ß-subunit coding rpoB gene sequence analysis per local procedures  [8, 9]. The rpoB sequence was 612-bp long and shared 99. 8% similarity with M. malmoense ATCC 29671 strain (GenBank Accession No. GQ153314). The second closest mycobacterium species was Mycobacterium palustre sharing only 571/612-bp 93. 3% (GenBank Accession No. HM022210). Broth dilution antimicrobial susceptibility testing was performed per published Clinical Laboratory Standard Institute guidelines  [10]  and showed the isolate to be in vitro susceptible to rifampicin, clarithromycin, streptomycin and amikacin; and in vitro resistant to isoniazid, ethambutol, ofloxacin, doxycycline, tigecycline and linezolid.
Background: Quantitative information about equine mortality is relatively scarce, yet it could be of great value for epidemiological purposes. In France, data from rendering plants are centralised in the Fallen Stock Data Interchange database (FSDI), managed by the French Ministry of Agriculture, while individual equine data are centralised in the French equine census database, SIRE, managed by the French horse and riding institute (IFCE). Objectives: To evaluate whether the combined use of the FSDI and SIRE databases can provide representative and accurate quantitative information on mortality for the French equine population and to propose enhancements of these databases to improve the quality of the resulting demographic information. Study design: Descriptive study. Methods: Mortality ratios for the French equine population were calculated per year between 2011 and 2014 and temporal variations in equine mortality modelled during the same period.
Survival analyses were performed on a sample of equines traceable in both the FSDI and SIRE databases. Results: Estimates of the annual mortality ratios varied from 3. 02 to 3. 40% depending on the years. Survival rates of equines 2-years-old and over differed according to breed categories with the highest median age at death for the ponies. The weekly description of mortality highlighted marked seasonality of deaths whatever the category of equines. Modelling temporal variations in equine mortality also brought to light excess mortality. Main limitations: Insufficient traceability of equines between the two databases.
Introduction Equine mortality is both an economic and welfare issue. Several studies have focused on the causes of death in horses  [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] , but information on quantitative mortality remains relatively scarce. Current published information on quantitative equine mortality in Europe is mainly derived from surveys, or databases of limited equine populations  [5] [6] [7] 11, 12]  that require the collection and centralisation of a minimum of information on horses. Even today, this information is often disseminated among various professional organisations and difficult to access for demographical or epidemiological purposes  [13, 14]. In France, individual equine data are centralised in the French equine census database, SIRE, which is managed by the French horse and riding institute (IFCE).
The SIRE database provides individual information (unique SIRE identification number, microchip number, date of birth, sex and breed) for 95% of French equines whose owners have complied with regulations  [15, 16]. Legally, owners are responsible for notifying the IFCE of any change during the life of the horse and in the event of death, have to return the animal's passport to the IFCE. However, owners do not systematically comply or take a long time in doing so, meaning that information in the SIRE database on the date of death of the horse is often unreliable, even when available. In this context, rendering plants are the main source of quantitative equine mortality data, since all animal cadavers have to be collected by fallen stock companies (law of  31 December 1975). These data are centralised daily in the Fallen Stock Data Interchange database (FSDI), managed by the French Ministry of Agriculture  [17, 18].
A recent assessment of FSDI equine data  [19]  showed that their quality, if perfectible, is sufficient to provide detailed and representative descriptions of equine mortality. No comprehensive quantitative information about equine mortality has yet been published. The objectives of this study were to evaluate whether the combined use of the comprehensive FSDI and centralised SIRE databases can provide representative and accurate quantitative information on mortality outside slaughterhouses for the French equine population and to propose enhancements of these databases to improve the quality of the resulting demographic information.
Materials Fallen stock data interchange (FSDI) database: The FSDI database contains records relating removal of cadavers from holdings where equines are kept (farms, livery yards, etc. ) and veterinary premises: cases are registered during telephone calls, or online requests for the removal of one or more dead animals. Thereafter, data collected for each visit are the date and time of the removal request, date of removal, identification, address and postcode of the holding, number of animals collected and their age/breed category, individual identification number and an estimation of global cadaver weight. The FSDI database does not record individual information on equines, such as date of birth or sex. This information can be found in the SIRE database for animals whose individual identification numbers are registered in the FSDI database.
5%). Age/breed categories are used by fallen stock companies for billing the owner of the dead equine, with a specific billing rate for each category. Animals were thus classified into six age/breed categories: stillbirth and foal (animals <1-year-old) or yearling (≥1-year-old and <2 years old) and adult animals (≥2 years old) classified by breed: pony, donkey, draught horse and saddle horse (i. e. any horse breed except draught horse breeds). Recent assessment of FSDI equine data  [19]  showed an unclear delineation of the age categories for young animals, with an overlap between categories (stillbirth and foal and yearling) and these were grouped into a single young animal category for the purpose of this study. Information from the SIRE database: The estimated size of the live equine population based on SIRE data is biased because owners rarely notify SIRE managers of the death of their animals (only around 30% of deaths are registered).
An estimation of the population size is nevertheless calculated annually by the IFCE using the number of animals identified by microchip in each birth cohort and an estimation of the number of deaths each year in each cohort  [15, 20, 21]. This estimate is then refined based on additional data sources such as customs, the National Federation of Horse Racing, the French Equestrian Federation and regional surveys. In order to evaluate the survival of equines by breed and sex, we extracted from the SIRE database individual data (exact breed, sex and date of birth) for a subset of 18,884 animals for which the identification number registered in the FSDI database was traceable in the SIRE database. We additionally excluded 1291 animals under 2 years old because young animals were underrepresented in the subset of animals with a correct identification number in the FSDI database  [19]  and an estimate of survival from birth would therefore be biased.
52), time an index of time (1,. ,208) and e i = φ e iÀ1 + e i , with e i the stochastic error normally distributed N(0,r 2 ) and φ the autocorrelation parameter, f 1 a cyclic cubic regression spline with the value and first two derivatives matching at year ends and f 2 a cubic regression spline  [22]. Model adequacy was checked by examination of residual plots. Statistical tests were performed to assess the significance of the trend and the seasonal component in the model  [23]. Analyses were performed using R software packages 'mgcv' and 'nlme'.
2% has been reported in racehorses  [12]. In a large population of insured Swedish horses, Egenvall et al. [5]  estimated an incidence-based mortality rate of 415 deaths per 10,000 horse-years. In our study, all age categories were included, encompassing animals under 12 months old for which the mortality ratio is higher than in the adult population  [26, 27]. This could explain the higher mortality ratio we calculated compared with previous studies on populations excluding very young animals. Our estimates are based on comprehensive data covering the whole French equine population and recorded over four successive years. They should be more representative of mortality for the general population, even if some animals (stillbirths or very young foals) could potentially escape the rendering plant through illegal burial.
This trend follows changes in the equine population from 2011 to 2014  [20] , caused by historical variations in births. The weekly description of mortality also highlighted apparent excess mortality during the winters of 2011-2012 and 2012-2013. Insofar as no unusual health events had affected the French horse industry during these periods, the causes of this excess mortality are unknown and appear difficult to explore retrospectively. Nevertheless, the possibility of an objectification of abnormal peaks through the modelling of FSDI data strongly suggests its potential for the surveillance of equine mortality. Lastly, a combination of FSDI and SIRE data allowed us to explore survival by breed and sex for animals over a certain age. The survival analysis by breed category was limited to animals that had already reached  the age of 2 years and did not investigate the mortality of foals or yearlings.