dataesr/scientific-paragraphs-categorization huggingface dataset:
From this information, only vehicles with diesel or gasoline engines were selected. Hybrid and electric engines were eliminated because these vehicle categories are not yet defined in the noise prediction models. Furthermore, these vehicles were only recorded on track measurements and they passed very few times. Two filters were also applied to ensure that vehicles on the track had a constant speed. The first filter was to select acceleration in the range between -0. 1 and 0. 1 m/s 2. Secondly, measurements of vehicles with an engine speed higher than 3000 r. p. m. were eliminated. However, not all data recorded acceleration and engine speed. In such cases, the engine speed was computed from the ratio between speed and the gearbox of the registered vehicles. A total of 33 models of light vehicles with 14 tyre types, and seven models of heavy vehicles with three configurations (without trailer, with trailer and with loaded trailer) and two types of tyres were analysed on test tracks.
Distribution of the residuals An example of the distribution of residuals (R ij ) for the different speed intervals is shown in Fig. 3  for the example of the Satolas campaign, in which light vehicle pass-bys were registered in all speed ranges. The distributions shown in Fig. 3  are Gaussian except in the ranges from 0 to 30 km/h and from 40 to 70 km/h. The increase in variability of the residuals with a decrease in speed is also shown in Fig. 3. Adjustment of the residuals distribution to normal distributions was analysed for the complete dataset. Kolmogorov-Smirnov (with Lilliefors significance correction) and Shapiro-Wilk tests show that 92% of the residuals analysed at the different speed intervals follow a normal distribution (p > 0. 05), for which Eq. (  3 ) provides ΔLw vehicles-Gauss with the standard deviation as a single parameter.
Acknowledgments This work was supported by  IFSTTAR (France) , a  Juan de la Cierva-Incorporación  contract from the  Spanish Ministry of Economy, Industry and Competitiveness  ( IJCI-2016-28923 ), and by  Consejería de Economía ,  Ciencia y Agenda Digital of Junta de Extremadura , through grants for attracting and returning research talent to R&D&I centres belonging to the  Extremadura Science, Technology and Innovation System  ( TA18019 ), where  University of Extremadura  was the beneficiary entity.
We also conceptualize the sensorimotor experience involved by MM and FR to delineate perspectives and research avenues. More specifically, we discuss whether MM should be considered a retroactive closed-loop convergence process while FR should rather be considered a proactive mode of action control. We consider to which extent future developments in the field, such as robotic solutions, might allow switching from a proactive to a retroactive mode of action control in specific massaging routines. We examine whether assisting classical massages with interactive and intelligent massaging robots might represent a promising and fruitful avenue. This literature review was conducted using four search engines, Google Scholar, PubMeb, ResearchGate and Kinedoc, preceding and including 2020, without language restrictions.
Psychometric and Behavioral Assessments MM is an ancestral practice found in many civilizations. Beyond these origins, it is available in three forms: wellness, therapeutic, and sports MM. To appreciate its impact, researchers first collected subjective evaluations through self-report ratings. These tools are simple to use, cost-effective, and non-invasive. While monitoring objective data is likely to provide greater levels of precision, it remains costly and invasive. There are nonetheless several reports of behavioral assessments of the effects of MMs. Joint amplitude is assessed by means of goniometers and functional tests  (Leivadi et al. , 1999; Hilbert et al. , 2003; Zainuddin et al. , 2005; McKechnie et al. , 2007; Arabaci, 2008; Arazi et al. , 2012; Iwamoto et al. , 2016 ; Table  1 ).
ACKNOWLEDGEMENTS 1. The authors thank the  Claude Bernard Lyon 1 University Department of Anatomy  for the provision of the cadavers. 2. Presentation: This work was presented at the  French Society of Anaesthesiology  and Intensive Care annual meeting ( Congrès de la Société Française d' Anesthésie et de Réanimation ), September 19-21, 2019, Paris, France. 3. Financial support and sponsorship: none. 4. Conflict of interest: none.
Recruitment The expected initial duration of patient enrolment is 2 years, starting in January 2020. ► End of 2018: national grant award. ► 2019: approval by an independent ethics committee. ► 2020-2021: inclusion of patients (the first participant was enrolled the 31 January 2020). ► 2021-2022: end of inclusions, monitoring of participating centres and queries to investigators; blind review to determine protocol violation, to define intention-to-treat and per-protocol analysis populations; new queries to investigators, cleaning and closure of the database. ► 2022-2023: data analysis, writing of the manuscript and submission for publication.
METHODS: ASSIGNMENT OF INTERVENTION, DATA COLLECTION, MANAGEMENT AND ANALYSIS Allocation and sequence intervention After obtaining consent from the patient or his/her relative, all inclusion/exclusion criteria will be verified by the investigator before randomisation. Before the initial SBT the investigator will randomise patients to determine the type of trial allocated (T-piece or PSV trial). Randomisation will be stratified on centre and carried out by connecting to the electronic case report form (e-CRF) website https:// chu-poitiers. hugo-online. fr/ CSOnline/ after fulfilling the 'randomisation' page including all the criteria for eligibility.
Descriptive analysis of patient groups at baseline The analysis will be performed on an intention-to-treat basis after validation by a blind review committee of the inclusion/exclusion criteria for each patient. The continuous variables will be summarised with the classic parameters of descriptive analysis (median, IQRs and extreme values or mean and SD), while indicating the number of missing data. The category variables will be presented in the form of absolute frequency and percentage in each modality. Eligibility criteria will be verified on the basis of the data recorded in the case reports. Wrongly included subjects as well as those lost to follow-up will be described. Deviations from the protocol will be described and analysed on a case-by-case basis.
Data monitoring The trial will be overseen by a steering committee regarding the progression and monitoring of the study at Réseau Européen Ventilation Artificielle Network meetings every 6 months. Research assistants from the coordinating centre will regularly monitor all the centres on site to check adherence to the protocol and the accuracy of the recorded data. After being trained to conduct the protocol and to fulfil the e-CRF, an investigator at each centre will be responsible for daily patient screening, enrolling patients in the study, ensuring adherence to the protocol and completing the electronic case report form. Although the individual study assignments of the patients cannot be masked, the coordinating centre and all the investigators will remain unaware of the study group outcomes until the database will be locked.
Confidentiality Data will be handled according to French law. Coding subjects will be done by recording the first letter of the name and forename, accompanied by a single study identifier indicating the order of subject inclusion, in order to store anonymised data in the e-CRF. The sponsor will ensure that each study participant has given his/her consent for access to his/her personal data that is strictly required for quality control of the study. All original records will be archived at trial sites for 15 years.
METHODS: SEARCH STRATEGY We performed a literature review using PubMed/MEDLINE database (up to April 2020). Relevant articles were selected, based on combinations of MeSH or other search terms, without language or time restriction. The terms "primary immune deficiency" OR "primary immunodeficiency" OR "inborn errors of immunity" AND "innate immunity, " or the terms referring to the different diseases (e. g. , "severe congenital neutropenia, " "Papillon-Lefevre syndrome, " "chronic granulomatous disease, " "mendelian susceptibility to mycobacterial disease"), were used in combination with the following terms: "oral, " "oral mucosa, " "mouth, " "orofacial, " "teeth, " "oral ulcer, " "periodontal disease, " "periodontitis, " "candidiasis, " "gingivostomatitis. ".
The treatment allowed a significant reduction of oral inflammation and a complete resolution of the deep cutaneous wounds without significant adverse effect. Inhibition of IL23 and IL17 appears as a promising strategy in the management of moderate forms of LAD1, in particular for severe periodontal involvement  (87) , and an interventional protocol has been recently initiated (NCT03366142)  (66). Indeed, despite strict oral hygiene regimen and regular periodontal treatment, most of the patients lose their teeth  (99, 100). Their replacement relies on prosthetic rehabilitation with an age-specific approach. In growing patients, removable prostheses are favored and can be adapted depending on the teeth that are lost. To date, dental implants have been reported in only one patient with LAD (101).
General management The management of WHIM syndrome includes HPV vaccination (although WHIM patients respond less robustly than healthy individuals), prophylactic antibiotics, intravenous or subcutaneous immunoglobulins (IV Igs/SC Igs) substitution to prevent oto-sinopulmonary infections, as well as G-CSF injections to enhance the release of neutrophils from the bone marrow  (214). More recently, some patients have been treated with low-dose plerixafor, a CXCR4 antagonist, with encouraging results (NCT02231879)  (215).
ACKNOWLEDGMENTS We thank  Pr. Agnès Bloch-Zupan  (Reference Center for Rare Diseases with Oral and  Dental Manifestations ,  University Hospital, Strasbourg ) for the photographs of PLS patients and  Mrs. Marzena Kawczynski  (Reference Center for Rare Diseases with Oral and  Dental Manifestations ,  University Hospital, Strasbourg ) for her help with the patients' data. We thank  Pr. Olivier Huck  ( Department of Periodontology, University Hospital, Strasbourg ) for careful proofreading of the manuscript.
Movement recording system and movement reconstruction The setting was structured in order to define the space of action equally for each participant (Fig  1 ). For the soccer action, vortex howler throws and step action, two position markers were placed on the floor designating a start point and an end point (start position: blue line; end position: black line,  Fig 1). The start position of the shoulder stand action was marked by the edge of the mat and the end position was the maximal leg extension towards the ceiling. The sports actions were recorded from a left lateral view using a digital camera (Canon Legria HF R706), and subsequently analyzed off-line. Using software for 2D kinematic analysis (Tracker Video Analysis and Modeling Tool, 4. 11. 0), the first and the last repetition of each action were analyzed.
Statistical analysis For the first and last repetition of each sport action, the following kinematic parameters were considered as dependent measures: Norm_Path, Norm_Distance, Norm_X_Distance, Nor-m_Y_Distance, Max_PeakVelocity, Max_PeakAcceleration. For each mean value of the dependent measure, a mixed-design repeated measures ANOVA was carried out with repetition of the exercise (first vs last) as a within-subject factor, and group (type of instruction OIM vs DDM) and gender (female vs males) as between-subject factors  [52] [53] [54]. In all analyses, post hoc comparisons were performed using the Newman-Keuls procedure. The significance level was fixed at p = 0. 05. Sphericity of the data was checked for before performing statistical analyses (Mauchly's test, p > 0. 05). η 2 was also calculated.
Acknowledgments We thank the  Giocampus Scientific Committee  and the  National Technical Committee of Coni. A special thanks to  Paolo Seclı  `,  Gianluca Crespi ,  Cristina Caprile ,  Angelo Gadina  for their precious contribution and all children enrolled and their families. We are grateful to  Holly Rayson  for proofreading the manuscript. We also thank  Dario Alberini  for his help during data collection.
Materials and Methods Two general questions guided our scoping review: How is the scientific literature linking HL with the upstream SDoH? How does HL reflect the need for collective action on these SDoH? To answer our research questions, we conducted a scoping review from March to July 2018. We searched the PubMed database with the term "health literacy". We included all the systematic reviews and review papers that were published between January 2013-January 2018 in English and French that feature a definition of HL (see Figure  1  for the inclusion/exclusion criteria). We analysed the papers against four main dimensions:  (1)  the definitions of HL they featured, (2) their linkage to the SDoH, (3) the target of actions, i. e. , whether the actions were on individuals or communities and, (4) the nature of the determinants of health targeted.
Through education Better reading and understanding medication labels, appointment slips and other health related materials We felt it was important to not just distinguish between actions on the intra-individual determinants vs. actions on upstream determinants. We hypothesized that a programme aimed at changing intra-individual factors (e. g. , knowledge, attitudes, skills, motivation) could still prove to be thought out as a strategy to generate changes in the upstream SDoH (e. g. , improving knowledge on health services to increase capacity to advocate for system change). The analysis was also carried out on relevant HL documents available on the WHO websites. In addition, the review of the definitions of HL conducted by Sørensen et al. [3]  has proven a valuable starting point to appraise the range of definitions available that could not be captured within the time period covered by the search of databases.
Obviously collective action requires first of all recognizing the structural determinants of population health. This could be followed by determining the necessary steps forward such as increasing capacity for action, creation of citizen networks or advocating for structural/environmental change. Although we are confident in the validity of the observations and conclusions we derived from our dataset, our study is not exempt of limitations. Constraints in time and budget had us limit our search of papers to the PubMed database. Whereas we cannot dismiss the possibility of having failed to catch significant contributions, we believe this is unlikely as we looked for systematic review papers and review papers that in most cases carried out searches from multiple databases. We also had to restrict the publication period covered, a limit to our results which was to some extent offset by scrolling through the list of references of the papers we retrieved.
Testing protocol Participants performed the OLS on their preferred leg with their eyes open for all tests. Participants performed the OLS three times when standing on a force plate (Bertec Corporation, Columbus, OH, USA; Model 4060-80). Participants were asked to step on the force plate, stabilise on two feet then perform the OLS on their preferred leg, with their best time taken as their OLS performance. Data was collected at 1000 Hz using Bertec's Digital Acquire software (Version 4. 0). Immediately after the OLS test, participants performed two other functional screening tests, the Five Times Sit to Stand Test (5STS)  [12]  and the Timed Up and Go Test (TUG) test  [11]. Older participants were classified as being at risk of falling if their performance did not meet one of the previously-established cut-offs of 15 seconds for the 5STS  [21]  and 13.
Data analysis All force plate data were analysed in Matlab (MathWorks Inc, Natick, Massachusetts, USA). Data were low pass filtered using a Butterworth filter with a cut-off of 10Hz and segmented into different phases. The start of the signal was taken to be the instant when vertical force (Fz) exceeded the subject's body weight (TStart), while the end of the signal was taken to be when vertical force (Fz) exceeded the subject's body weight, calculated backwards from the end of the signal (TStop). When the subject began to transfer their weight from two feet to one foot, a clear shift in mediolateral CoP displacement was visible (TShift), with the start of the OLS (TOLS1) taken to be the moment the initial shift in CoP towards the single leg reversed (Figure  1 ). The end of the OLS (TOLS2) was taken as 10 seconds, with all but three of the 67 participants achieving a 10 sec OLS in their best performance on the force plate.
Statistical analyses were performed using SPSS version 25 (IBM Corp, Armonk, New York, USA). Data were assessed for normality using the Shapiro-Wilk test. All data was non-normal, therefore the bootstrap method was used to produce unbiased estimates of the confidence limits around the mean  [24]. When the Kruskal-Wallis Test identified a significant effect of group, pairwise comparisons were performed, with effect sizes were calculated using the methods described by Fritz and colleagues  [25]  as: 𝑎𝑏𝑠(𝑟) = 𝑍 √𝑁 where r is the effect size for the pairwise comparison, Z is the Z-score of the test, and N is the sample size. Comparisons were also made for postural sway within groups between the first time period and all other time periods. Owing to the post-hoc nature of this analysis, Bonferroni adjustments were made to p values for statistical significance.
Data Processing and Statistics Data are presented as mean and standard deviation (SD), median and interquartile range (IQR), or absolute and relative frequency, as appropriate. Factors influencing (a) the willingness to exercise and (b) the preference of specific components (e. g. , resistance or endurance exercise) were investigated using multiple binary logistic regression. The results were presented as adjusted odds ratios (OR) and 95% confidence intervals (CI). Calculations were made with SPSS 22 (SPSS Inc. , Chicago, IL, USA).
Funding: The authors received no financial support for the research, authorship, and/or publication of this article. Acknowledgments:  Luiz Hespanhol  was granted with a  Young Investigator Grant  from the  Sao Paulo Research Foundation (FAPESP) , grant  2016/09220-1. Gustavo Yuki  received a grant from the  Coordenação de Aperfeiçoamento de Pessoal de Nível Superior-Brasil  ( CAPES)-Finance Code 001.
RePORT International RePORT International represents a consortium of regional cohorts (RePORT India, RePORT Brazil, RePORT South Africa, RePORT China, RePORT Philippines and RePORT Indonesia) that are linked through the implementation of a common protocol for data and specimen collection. The objectives and composition of RePORT International are described elsewhere. 15 ne of the five teams under RePORT India, the Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Boston Medical Centre and Rutgers University, has established a pulmonary TB cohort of adults and children ≥6 years and their household contacts to identify biomarkers for risk of TB treatment failure and risk of development of TB in household contacts. TB cases diagnosed under NTP in the three districts (Puducherry, Cuddalore and Villupuram) were enrolled in the cohort at the DMCs and public health centres since 2014.
Data extraction, analysis and statistics Of a total of 1229 TB cases enrolled in the cohort, we extracted data for 765 cases excluding two childhood TB cases; the initial 462 cases enrolled were not assessed for HFI because of not having the HFIAS in the study proforma during the initial phase of the project. The HFIAS was introduced in the revised study proforma after the 462 patients were already enrolled in the project. However, there was no difference in the baseline sociodemographic and clinical characteristics of the 462 patients excluded, compared with those included in the study. Data were extracted from the RePORT India project database for the JIPMER site in a deidentified manner and analysed using Stata V. 12. 0 software. The proportion of HFI was summarised as percentage with 95% CI.
Open access Strengths of the study include use of a validated tool 4 for assessing HFI which allows cross-country comparisons. We used the data from a prospective cohort study which implemented quality assurance checks for data collection and entry that would have reduced missing data and data errors. There were a few limitations in the study. Our study included patients identified in the public sector alone and food insecurity levels may be different in patients accessing TB care in the private sector. Since, repeated episodes of TB may be a cause for financial loss leading to food insecurity, the levels could be higher in previously treated patients with TB and we did not study this subgroup. The study participants were from three selected districts in South India, so generalisability of the findings is limited.
Acknowledgements This cross-sectional analysis was conducted through the  Structured Operational Research and Training Initiative (SORT IT ), a global partnership led by the  Special Programme for Research and Training in Tropical Diseases at the World Health Organisation (WHO/TDR ). The model is based on a course developed jointly by the  International Union Against Tuberculosis and Lung Disease  ( The Union ) and Medécins sans Frontières (MSF/Doctors Without Borders). The specific SORT IT programme which resulted in this publication was jointly developed and implemented by: The  Union South-East Asia Office, New Delhi, India ; the  Centre for Operational Research, The Union, Paris, France ;  Department of Preventive and Social Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India; Department of Community Medicine and School of Public Health, Postgraduate Institute of Medical Education and Research, Chandigarh, India; Department of Community Medicine, All India Institute of Medical Sciences, Nagpur, India ;  Dr.
The advantage of using a dietary challenge is that it can be standardized, and does not raise ethical issues, as using antibiotics in healthy subjects might do. A resilience index can be computed by using parameters that are known to be modified by stress such as microbiota composition, function and/or metabolites. The resilience index can be used to give a quantitative measure of how much the microbiota has deviated and how quickly and fully it has recovered, thereby quantifying resilience. Such a resilience index provides a measure which can possibly be used to compare different stressors across studies. Ideally, one should be able to assess the microbiota resilience of an individual without applying a stressor. Machine learning with comprehensive and big data may help design algorithms based on microbiota and host parameters that can be used to predict microbiota resilience.
Study design and data sources In this crosssectional study, we analysed data from Demographic and Health Surveys (DHS) from 16 sub Saharan African countries to quantify socioeconomic inequalities in uptake of HIV testing in the previous 12 months. DHS are nationally representative cross sectional surveys in which data are collected for a wide range of health indicators. DHS have a multistage design: households are sampling units, and generally all people aged 15-59 years from selected households are eligible for inclusion. However, the bulk of the surveys were done in participants aged 15-49 years, and depending on the survey, data for men or for HIV indicators and biomarkers, or both, might be collected in.