dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical Analysis From behavioral data, we summarized duration and frequency by day (24-h observation period beginning at 1200 h of each calendar day). We calculated social use of the shelter as a percentage of total shelter use, social use within treatment (in shelter with another calf on the same treatment) as a percentage of total shelter use, lying in the shelter as a percentage of total shelter use, and lying in the shelter as a percentage of total lying time. Additionally, hourly shelter use duration was calculated for analysis of diurnal patterns. Data were screened for normality before analysis using the PROC UNIVARIATE procedure within SAS (version 9. 4, SAS Institute Inc. , Cary, NC), and transformed to meet assumptions of normality if needed. Daily duration of shelter use was log-transformed and the following variables were square root-transformed: frequency of entering and exiting the shelter when it was occupied (social entrance and social exit), social use within treatment as a percentage of shelter use, frequency of lying bouts in the shelter, lying in the shelter as a percentage of total lying time.
Hourly shelter use duration was transformed using a Box-Cox transformation  (Box and Cox, 1964) , where log(y + 1), rather than the log-transformation used for daily shelter use duration, due to the presence of zero values in the hourly data set. Data summarized daily were analyzed using the MIXED procedure of SAS, with day as a repeated measure. For the analysis of duration of social shelter use within treatment (time that the focal calf spent with the other calf on the same treatment), data were summarized by pair within pen, such that the experimental unit for analysis was pair (n = 6 pairs of calves/treatment). For all other analysis, the experimental unit was the individual calf. The model included the fixed effects of treatment, day (categorical variable), treatment by day interaction, with calf (or pair of calves, for analysis of social use within treatment) as the subject and pen as a random effect.
The variance-covariance matrix structure on the basis of best fit according to Schwarz's Bayesian information criterion (compound symmetry or autoregressive were selected for all data). Consistency in shelter use between observation days was assessed using linear regression (using PROC REG in SAS). To assess shorter-term treatment effects within each day, hourly shelter use duration was averaged by day across daytime hours (between 0700 and 2000 h) and nighttime hours (between 2000 and 0700 h; based on times of sunrise and sunset). The effect of treatment To characterize diurnal patterns of shelter use, hourly duration of shelter use was averaged by hour across consecutive observation d 1 and 2, excluding d 0 during which the anesthetic and analgesic were effective for part of the day. Evaluation of diurnal patterns of shelter use on individual days was not possible due to insufficient data at this time scale; many calves did not enter the shelter each hour.
Hourly data were analyzed in a similar model to daily data, with hour as the repeated measure (categorical variable, to assess hourly differences between treatments). Homogeneity of variance was verified by plotting residuals from the model against predicted values. Data are reported as (back-transformed) least squares means and 95% confidence intervals. Significance was declared at P < 0. 05, and trends were reported if 0. 05 ≤ P ≤ 0. 10.
ACKNOWLEDGMENTS We thank the staff at the  University of Florida Dairy Unit  and our undergraduate research assistants  Lisette Coll-Roman ,  Emily Lindner ,  Alejandro Forero ,  Alexis Brocious ,  Bianca Hofmann ,  Harrison Warman ,  Margaret Fant ,  Megan McDowell ,  Lauren Peter , and  Samantha Stella  for their technical assistance. Thank you to  Fiona Maunsell  ( College of Veterinary Medicine, University of Florida, Gainesville ) for her guidance and oversight of the disbudding procedures. Thank you also to  Dave Gingerich  ( Bear Design LLC, Clearwater, FL ) for contributing the illustrations of the pen layout and shelter design. KG was supported on a research assistantship by funds awarded through the  Department of Animal Sciences, University of Florida. This research was supported by the  USDA National Institute of Food and Agriculture (Washington, DC) ,  Hatch Multistate  project  1012277.
| Data collection Collection and storage of blood and urine samples were performed with the informed consent of the owners and approval of the Ethics and Welfare Committee of the Royal Veterinary College (URN20131258 and URN20131258E). Blood samples were obtained by jugular venipuncture and transferred to heparinized and ethylene-diaminetetraacetic acid (EDTA) tubes. Urine samples were collected by cystocentesis. All samples were stored at 4 C after collection, for a maximum of 6 hours before centrifugation and separation. Heparinized plasma was submitted to an external laboratory (IDEXX laboratories, Wetherby, UK) for biochemical analyses on the day of sample collection, including tCa. Ionized calcium concentration measurement was made immediately on untreated whole blood after venipuncture, using a point-of-care blood analyzer (i-STAT 1, Abbott Point of Care, Inc, Princeton, New Jersey) that also measured venous pH and bicarbonate (HCO 3 -) concentration, in accordance with the manufacturer's instructions.
2 pg/mL. 20 Therefore, any samples with PTH concentration <5. 2 pg/mL were arbitrarily assigned a concentration of 2. 6 pg/mL, half the value of the lower limit of detection. 19 stolic blood pressure (SBP) measurements were obtained following a previously described Doppler method. 21 Fundic examination using a retinal camera (ClearView, Optibrand, Fort Collins, Colorado) or by indirect ophthalmoscopy was performed in cats with an average SBP >160 mm Hg. Systemic hypertension was diagnosed in cats with an average SBP >160 mm Hg in conjunction with evidence of ocular pathology consistent with hypertensive damage, or SBP >170 mm Hg on 2 consecutive occasions. The clinical records were reviewed, with the following historical findings, physical examination findings, and biochemical data extracted: tCa, iCa, plasma creatinine, symmetric dimethylarginine (SDMA), urea, phosphate, potassium, sodium, chloride, total magnesium (tMg), total protein, albumin, TT4, glucose, FGF23 and PTH concentrations, plasma activity of alanine aminotransferase (ALT) and alkaline phosphatase (ALP), PCV, venous blood gases including pH and HCO Univariable binary logistic regression analyses identified that lower plasma phosphate, potassium and sodium concentrations and hypertension status were associated with increasing plasma tCa concentration after the initiation of a phosphate-restricted diet at the 10% level (Table  2 ).
Acknowledgements We thank  C eline Maurice  for technical assistance and  Nick Duesbery ,  Simon Hawkins ,  Yanele Poteaux  and  Corentin Spriet  for fruitful and helpful discussions. We thank the  Department of Biology and the Centre d'Accompagnement des Pratiques Enseignantes (CAPE)  for their support, and especially  Marie-H el ene Canu ,  Matthieu Marin  and  Jacopo Vizioli.
Acknowledgments: We are grateful to all the many individuals who participated in the multiple studies summarized in this article. Financial Support: This work received financial support from the  University of Georgia Research Foundation, Inc. , which was funded by the  Bill & Melinda Gates Foundation  for the  SCORE  project. Disclaimer: The funders had no role in the studies, data collection, analyses, or the decision to prepare or publish the manuscript. Disclosure: A significant amount of the praziquantel provided as treatment during these studies was donated through the  WHO, USAID ,  RTI ,  World Vision , and  SCI.
Bioluminescence for all mice was recorded across the experimental period. Plots for the different treatment groups show the progression in bioluminescence over time (Fig3B-F). Mice from the ER alone, R4Pam2Cys alone and unvaccinated treatment groups displayed the first detectable bioluminescence at week 7. There also appeared to be threshold in bioluminescence, whereby animals expressing ≥5x10 5 photons/second from tail lesions became less able to control the infection and progressed to the clinical endpoint (Fig. 3B ). The immune response data for all mice is provided (Supplementary Table  S1 ). Using these data, failure-to-protect was defined as tail bioluminescence equal to or greater than 5x10 5    photons/second at or before week 24 (end of experiment). Therefore, mice were defined as 'protected' if bioluminescence was less than 5x10 5 photons/second at week 24.
IVIS imaging Infected mice were imaged weekly from 6-weeks post-infection to detect the emission of bioluminescence. Images were captured using the Lumina XRS Series III In Vitro Imaging System (IVIS®) (Perkin Elmer, MA, USA) and Living Image Software v3. 2 with the following settings: Field of View 24, relative aperture f'1. 2, medium binning, 60s exposure. Bioluminescence was calculated using Living Image Software v3. 2.
Cells were then stained with 7AAD-Live/Dead stain dye (Biolegend, CA, USA), BV510-anti-B220 (BD Horizon, Becton Dickinson, Clone RA3-6B2), BV605-antiCD4 (Biolegend, Clone RM4-5), APC-Cy7-anti-TCRb (BD Pharmingen, Clone H57-597) and PE-Cy7-anti-CD8 (BD Pharmingen, Clone 53-6. 7) anti-mouse monoclonal antibodies at 4°C in the dark. Intracellular staining was performed by fixing cells with Cytofix/Cytoperm solution (Becton Dickinson, USA) followed by permeabilisation and intracellular staining with Perm/Wash buffer (Becton Dickinson) and BV786-IFN-g (BD Horizon, Clone XM G1. 2), AF647-IL-17A (BD Pharmingen, Becton Dickinson, Clone TCII-18H10) and PE-TNF-a (BD Biosciences, Clone MP6-XT22) antibodies for 30 minutes at 4°C before analysis on an LSR Fortessa flow cytometer (BD Biosciences, US). Data analyses were performed using FlowJo (Tree Star, OR, USA).
Cytokine Bead Array Spleen and lymph node-derived cells were incubated in 500 µl RP10 supplemented with 25 µg/ml ER protein for 72 hours at 37°C in 5% CO2. Supernatant was collected and a cytokine bead array was performed using a mouse flex set (BD Biosciences, USA) to detect IL-2, IL-4, IL-6, IL-10, IL-12/IL-23p40, IL-17, IFN-g, TNF, MCP-1, MIP1a, MIP1b as per the manufacturer's instructions. Samples were acquired using a FACSCanto II flow cytometer (BD Biosciences) and cytokine quantities calculated using FCAP Array TM Software v3. 0.
Statistical analysis GraphPad Prism software (GraphPad Software v7, CA, USA) was used to perform statistical analyses on the antibody titre, time to luminescence, T cell numbers and cytokine titre data. Antibody titres were analysed using one-way ANOVA with Tukey's correction for multiple comparisons. The time to bioluminescence data was displayed as a Kaplan-Meier plot and differences determined using a Log-Rank (Mantel-Cox) test. Mann-Whitney tests were performed to compare cytokine titres between protected and diseased mice and for comparisons between vaccination groups. All tests were conducted at the 5% significance level.
Statistical modelling Twenty-eight data features (i. e. the immune parameters measured in each mouse, refer to Table  S1 ) were transformed using the R package bestNormalize  (106). Transformed features were then normalised (between 0 and 1 for each feature) using the MinMaxScaler function of Scikit-learn  (107). As many of the vaccination outcome observations (time-to-bioluminescence) were rightcensored, we employed the Cox proportional hazards regression analysis using the Scikit-survival module of Scikit-learn in Python  (108). Here, univariate analyses were run for each of the 28 features using the continuous response variable of time-to-bioluminescence. The standard metric for assessing the predictive performance of a survival model is the concordance index (CI)  (62, 109, 110). A CI >0.
7 was used to identify the top six features of this model. Unsupervised learning and data dimensionality reduction is an ideal way to identify structure in continuous data without the influence of labels. The method of t-Distributed Stochastic Neighbor Embedding (t-SNE) is a dimensionality reduction technique that retains both the global structure and local layout of the high-dimensional data through exchanging the Euclidean distances between all pair of data points into heavy-tailed conditional probabilities  (111). This method is advantageous over conventional principal component analysis (PCA), as it does not rely on a linear assumption and can capture nonlinear relationships  (111). We explored the data, independent of labels, by reducing the top six features obtained from the Cox proportional hazards regression analysis to a two-dimensional space using the t-SNE package in Scikit-learn  (107).
Such papers encourage us to use inertial sensors with caution, but also suggest ways for improvement. The second sport-related research paper is focused on the use of inertial sensors to classify skiing practice and techniques  [5]. In their paper, the authors present four skiing turn styles: snowplow, snowplowstreering, drifting and carving. Data were captured by inertial sensors located at the skiing boots. Using data from 2063 segmented individual turns, 75% were used as a training set for the classifier and 25% as test data to quantify the performance of the classifier. The authors tested three classifier methods: decision tree, random forest and the gradient-boosted decision tree. They demonstrated that the last method gives a slightly better prediction. The authors also detailed the 10 most important variables, which help to differentiate between parallel and non-parallel turns.
Therefore, the inertial sensor is located in the saddle and a machine learning method is applied to relate the six signals of the accelerometers and the gyrometer to the speed per strike. The data obtained were compared with results of an optical motion capture system, which were used as reference data. The authors presented an original method, confirming that inertial sensors can offer various approaches to extract kinematic parameters. The third set of two more research papers proposed innovative methods to explore kinematics by inertial sensors. The first one deals with the estimation of the axis of rotation  [10]  and the other one with the use of inertial sensors in smartphones to identify gait. The first research paper with innovative methods proposes determining the orientation of the axis of rotation between two rigid bodies using inertial sensors fixed on these bodies  [10].
The authors also presented an experimental validation. As additional material, the authors proposed a full dataset of 77 subjects to the scientific community, in order to compare the performance of their method to others. Finally, the last set of two research papers concerns industry applications  [12, 13]. The first one is focused on the benefit of the use of a virtual reality system to practice and improve the postural stability of workers working at height  [12]. The authors mainly detail the consequence of the practice of specific exercises through virtual reality on the displacement of the center of pressure. In the context of this Special Issue dedicated to inertial sensors, this research paper is interesting as it presents how the orientation of a balance platform is tracked by inertial sensors.
e diagnosis of leptospirosis was based on a clinical picture of patients with an IgM-ELISA serology. To generate data about leptospirosis, routine data collected from clinical and laboratory structures during 2005 to 2012 period were analysed. A total of 305 human cases were reported during this period corresponding to an estimated annual incidence of 0. 1 per 100 000. Similar results were previously/recently reported in temperate countries. In this Moroccan study, a seasonal increase of cases was observed during the summerautumn period with regular epidemic peaks in some provinces with highest rate (17. 0%). Most reported cases originating from the region of Casablanca were living in particular areas close to high-risk occupational sites like Sidi Moumen and Hay Mohammadi. In 2014, the Direction of Epidemiology and Disease Control and Institut Pasteur du Maroc in collaboration with the local authorities decided to carry out a seroepidemiological investigation on the suspected sites of Casablanca.
Study Population. In this study, we enrolled adult participants from 3 occupational high-risk sites of leptospirosis and a control group. Recruitment of the participants was done after signing the written consent. e study design was submitted and approved by the Ethics Committee of Casablanca Medicine University of Morocco. e study was conducted in accordance with the principles of Helsinki Declaration. Participation to our study was voluntary, anonymous, confidential, and only for research purposes to protect privacy and ensure data integrity.
Sample Size and Power Calculation. In the absence of any data about estimates of the seroprevalence of leptospirosis in Morocco, we considered first a convenience global sample of about 500 individuals in the 3 high-risk occupational sites based on 80% power, a type I error of 5%, a 10% nonresponse rate, and an expected seroprevalence around 12% according to published international studies  [12] [13] [14]. We have therefore expected our samples as follows: 250 subjects at the biggest abattoir, 125 subjects in the poultry market, and 125 subjects in the port, according to the number of employees in each site. A total of 125 subjects were also provided from the general population.
Data Collection. e questionnaire was designed by researchers. e interviews were conducted in Arabic. It includes information about work-related risk factors including work positions, occupational animal contact, personal protective equipment (e. g. , gloves, etc. ), and personal data such as age, gender, grade level, type and place of residence, and prior diagnosis of leptospirosis. 2. 5. Serological Testing. 5 ml blood was collected from each participant by venipuncture in a sterile tube and kept cool (5 °C). After centrifugation, sera collected were kept frozen at -20 °C until use. Serology for leptospirosis was performed at the National Reference Center for Leptospirosis at Institut Pasteur of Paris, France. Enzyme-linked immunosorbent assay (ELISA) and Microscopic Agglutination Technique (MAT) tests were carried out.
Acknowledgments e authors gratefully acknowledge the support from the  Reseau International des Instituts Pasteur (RIIP)  and the technicians ( Sylvie Brémont ,  Annie Landier  and  Farida Zinini ) from the  National Reference  Center for Leptospirosis,  Institut Pasteur of Paris , for serological analysis of sera. is research was supported by  Institut Pasteur du Maroc.
Also, the toxicological data obtained for guaranteeing the safety of workers may be used (ECHA (European Chemicals Agency), 2014). It should, however, be noted that there are only few examples where companies have chosen to include such post-ban animal test data. After the deadline of 2013, no new compounds for exclusive use in cosmetics have been introduced. This clearly shows the pressing need for additional methodologies and out of the box thinking for the safety evaluation of cosmetic ingredients to avoid a roadblock to the development of new cosmetic ingredients. In this context, the recently proposed "Next Generation Risk Assessment (NGRA)" concept could be of interest for the safety evaluation of cosmetic ingredients  (Berggren et al. , 2017; Dent et al. , 2018 ) (See Fig. 1 ). To further explore this concept, its tools and future perspectives, the SCCS Workshop on the way forward for assessing the human health safety of cosmetics in the EU, held on February 27, 2019, was focused on NGRA.
This is where the ICCR principle of differentiating between biological activity and adversity ('the Fig. 1. Framework of the New Generation Risk Assessment (NGRA) (adopted from  Berggren et al. , 2017 and Dent ; et al. , 2018; ). TTC: Threshold of Toxicological Concern; MoA: Mode of Action. Copyright from Elsevier, first published in Computational Toxicology, 4, 2017. assessment is designed to prevent harm') needs to be applied. However, because the assessment is tiered and iterative this step may not be needed to make a safety decision where the conservative assessment based on the bioactivity data provides a wide Margin of Safety (MoS). A critical question for NGRA is 'what MoS is necessary or appropriate to assure safety?' Historically a margin of exposure of 100 was considered adequate to cover uncertainties relating to exposure and effects when assessing risks based on animal test data (SCCS (Scientific Committee on Consumer Safety), 2016).
The figure of 100 comprises a factor of 10 for the extrapolation from test animals to an average human being (interspecies extrapolation) and another factor of 10 to account for variability within the human population (intraspecies extrapolation). These factors of 10 are further subdivided to explicitly account for inter and intraspecies differences in toxicokinetics and toxicodynamics. Therefore, one approach could be to re-define the acceptable MoS to ensure they are relevant for use with in vitro data and computational models instead of in vivo data. Indeed, the more thorough characterisation of uncertainty and variability that is possible using information-rich datasets and approaches may make some uncertainty/assessment factors redundant. For example, computer simulations of variability in systemic consumer exposure across a population has the very real potential to replace the need for uncertainty factors for toxicokinetic differences.
Analogue and category read-across depend on the availability of pre-2013 animal data for the read-across source. TTC is a concept allowing, under specific conditions, to conclude without the need to run new animal studies whether a certain low level chronic human exposure is of negligible health concern or whether further work is necessary. The TTC concept includes a decision tree and series of assessments to exclude chemical structures excluded from the concept, and to address cancer and non-cancer endpoints. For information on the TTC concept, the reader is referred to some pivotal publications and reviews:  Munro, 1990; Munro, 1996; Kroes et al. , 2004; EPFA, 2012 ; EFSA/WHO, 2016. In a regulatory context, the TTC approach is being applied by agencies to flavors and fragrances, food contact material migrants, pesticide metabolites and impurities, and drug impurities.
The derivation of the various exposure thresholds is based on databases of existing oral animal studies, which are used in a broad read-across within 5 classes: DNA-reactive structures, organophosphates/carbamates, and Cramer Classes I, II and III. DNA-reactive structures are assessed with a specific threshold derived from cancer study data, which are not further discussed here. The span of types of chemical structures represented in the TTC databases becomes relevant for whether TTC is an appropriate safety assessment tool or not, as readacross as a concept is mostly based on the observation that structural similarities lead to biological similarity. Hence, the objective of TTC databases is to capture toxicity data on as many chemicals as possible, to achieve that a broad range of structures can be assessed.
In the past decades, toxicological testing was prioritised for compounds which were suspected to be relevant and potent toxicants. This led to a testing and reporting bias within most toxicology databases with an over-representation of more potent compounds. Specifically, compounds traditionally used in personal care products which typically have a history of safe use and low concern for toxicity, are less abundant in toxicology databases. Similarly, a lack of representation of some structural classes had been noticed. This inspired a multi-stakeholder EU project (the COSMOS project) which set out to add cosmetic-related compounds to the TTC databases  (Yang et al. , 2017). The first step was to identify which chemical structures were described by databases and the literature to be associated with personal care products/cosmetic products.