dataesr/scientific-paragraphs-categorization huggingface dataset:
Open access The hierarchical structure of the data will be taken into account in calculating CIs. For secondary outcomes, the rate of hospitalisations and/or consultation due to disruptive NPS, the prevalence of psychotropic drugs use and health costs will be described over the 2-month follow-up in both groups. Mixed models with a random intercept (corresponding to the cluster units) will be applied to handle within cluster correlation; models will be adjusted for potential confounders. An estimation of the cluster effect ('design effect') will also be performed over the 2-month follow-up in both groups to estimate more accurately the sample size of a nationwide effectiveness demonstration study. Qualitative variables will be described by the percentages of both modalities. Quantitative variables will be expressed by means, SD, minimum, maximum, quartiles and medians.
Multiple imputations will be used in order to handle missing data. Statistical analyses will be performed with STATA software. Analyses will be conducted by the Department of Epidemiology of the Toulouse University Hospital in Toulouse, France. Statistical analysis for costs data will be performed using deterministic and probabilistic sensitivity analyses. In particular, the non-parametric bootstrap method will be used to estimate the 95% CI of costs. 40 Statistical cost analysis will be performed with STATA software and conducted by the Unit of Medico-economic Evaluation of the Toulouse University Hospital in Toulouse, France.
EthICs And dIssEMInAtIon Written informed consent is required from all participants (or legal representatives). The trial has been registered in ClinicalTrials. gov: NCT02472015, registered 1 June 2015. Two times during the study, a clinical research technician acting for the Toulouse University Hospital will conduct an audit of the trial. We plan to communicate the final results to the public via conferences and results will also be submitted for publication in international peer-reviewed scientific journals, approximately 6 months after finishing data collection. All participants will be informed about the final results, if they ask for, as required by French law (article L. 1122-1). All authors will have access to the final trial dataset.
Factorial validity of the EDMCQ First, we studied the factors underlying the EDMCQ. Using the answers to the 35 EDMCQ items, we reduced the data by factor analysis in a couple of latent variables, also called factors. Factor analysis was performed in two steps (exploratory and confirmatory factor analysis) using the statistical software R Studio version 3. 1. 2 and packages "nFactors", "parallel", "sem" and "lavaan"  [48] [49] [50] [51]. First, an exploratory factor analysis was used to identify the underlying factor structure for the set of 35 items and to determine the number of latent factors, without making a priori assumptions about the relationships among factors. The factor solution is based on Kaiser criterion, scree plot, the amount of variance explained, and interpretability of the factors.
A broad integration of the mobile devices has emerged that allows a wide range of activities, including greater functionality in comparison with the original purposes for which they were initially developed. Here, our interest is presented a proposal methodology to verify the impact of studies of medical evaluations in which cardiac applications have been evaluated. When we refer to normal heart rate, the normal heart rate at rest is 60 to 100 beats per minute. It is usually measured by the electrocardiogram (ECG). The ECG measures the electrical activity of the heart  [2]. Currently, it is a fact the wide penetration of mobile devices with Internet access, including the smartphones. They can allow specific and/or complementary activities in the health field. On the other hand, advances in sensors, mobile and built-in devices have made it possible to monitor the medical condition of the patient, have provided medical treatments and other healthcare assistance based on a communication platform that allows the safe transmission of medical data  [3].
Methodology The information search strategy has been structured as follows: 1. The review corresponds to scientific journals of high impact, with the intention of verifying how they have evaluated the performance of mobile applications related to health topics with special interest in cardiac issues. The main scientific databases used are: IEEE Xplore, Web of Science, Science Direct and Scopus. 2. In view of this situation, information has been searched with the keywords like "app" & "Heart" & "rate" where scientific articles have been searched, which have been selected by title and abstract, later organized in the following categories. 3. Multiple information has been found of some professionals, who evaluate their own applications. However, there are little information related to the evaluation and comparisons of apps in the health sector.
They were sensor contact, location, rotation, signal correlation, and patient comfort. This method had two objective functions that were functionality and wearability. These variables were optimized using linear and nonlinear models with the purpose of maximize those objective functions simultaneously. In Kutyifa et al. ,  [24]  presented a prospective registry of patients using the Wearable Defibrillator, called WEARIT-II. This registry was designed to provide real world data on the wearable cardioverter defibrillator (WCD) as a strategy during a period of risk stratification. WEARIT-II registry enrolled 2000 patients with ischemic condition (n = 805, 40%), or non-ischemic cardiomyopathy (n = 927, 46%), or congenital/inherited heart disease (n = 268). This WCD was prescribed between the period of August 2011 and February 2014.
Study settings and participants We conducted a cross-sectional population-based survey combining quantitative and qualitative components. The parent study took place in eight sites with a larger sample size and recruited multiple nationalities. However, this paper will focus on data from Syrian populations, collected at six different sites representing a range of temporary settlements: (1) the Ritsona camp in the Attica region near Athens, where the population was living in bungalows;  (2)  the Katsikas camp in Ioannina, in the northwest of Greece; (3) a hotel where a proportion of the Katsikas camp population had been temporarily relocated while the camp was being refurbished for the winter; (4) the island of Samos, one of the first entry points in Greece and a designated UNHCR hotspot; and (5, 6) a pair of squat-hotels in central Athens.
Data collection and analyses Quantitative data were collected on paper and entered into the RedCap software. Data quality double-checks were performed on 10% of questionnaires. Descriptive analyses were performed using Stata 13 (Stata Corp). Comparisons of proportions were performed using a chi-squared test. The prevalence of anxiety disorder was stratified by key group characteristics, of which those associated with anxiety were analyzed using a test of proportions. Audio-recordings of IDIs and FGDs were transcribed into English and reviewed and revised by the qualitative researcher in the field. Qualitative data analyses, aided by NVivo 11 qualitative software, included both thematic analysis and grounded theory  [16]. Emergent patterns, categories, and concepts from participants' accounts were identified by meticulous and systematic reading and coding of the transcripts.
All questionnaires were in English and had the same structure: (1) a section on demographic content (2) questions on the experience of HCWs in providing HIV services (the content of this section was adapted to the specificities of the staff profession), (3) questions eliciting their perceptions of various UTT interventions, and (4) questions measuring their job satisfaction. The instrument was piloted with staff of the TasP trial, which resulted in some minor changes related to item wording. Data were captured using the Research Electronic Data Capture (REDCap) software. Qualitative component: Four local experienced qualitative interviewers were recruited to carry out FGDs and SSIs in isiZulu. They received specific training on interviewing techniques with staff members, to minimize bias from respondents when questioned about the institution they work for.
SSIs lasted for 60 to 90 minutes, and FGDs for 120 to 160 minutes. They were held either in a closed meeting room at AHRI for the TasP staff, or at a place of convenience for the participants from the government clinics. Semi-structured guides for the SSIs and FGDs were designed to fit the specificities of the range of professions interviewed. Participants were asked about their roles and motivations in their work, the challenges they faced and their perceptions of the strengths and weaknesses of the interventions delivered in the TasP trial, as well as their opinion on the scale-up of those interventions to the whole of Hlabisa sub-district and beyond. Data were audio recorded, transcribed in isiZulu and translated to English. The quality of the translations was checked by the most experienced qualitative interviewer.
Analysis process Quantitative component: This publication explores quantitative data extracted from the third section of the study questionnaire, regarding the perceptions of HCWs on home-based HIV services, including HIV testing and personalized support for linkage to care. Respondents rated the degree to which they agreed or disagreed with statements using a five point ordinal Likert scale (totally disagree, partially disagree, no opinion, partially agree, totally agree). Results were analysed using R software version 3. 0. 1. Qualitative component: An inductive approach based on descriptive thematic coding was used to explore the qualitative data. All transcripts were entered in a qualitative data analysis management software (NVivo version 11, QSR International Pty Ltd. , Doncaster, Victoria, 3108, Australia).
Acknowledgments The authors wish to thank the  Department of Health of KwaZulu-Natal and of South Africa  for their support for this study, the community of the Hlabisa sub-district for hosting our research and all participants for their contribution to the study. We would especially like to thank  AHRI  for their constant support:  Sphephelo Dlamini , whose knowledge of the local area was key for the smooth conduct of the overall study; the qualitative interviewers ( Lindiwe Sibiya ,  Lobenguni Simelane ,  Mumsy Mthethwa , and  Ntokozo Zitha ) who collected the qualitative data, and the  AHRI nurses  ( Patrick Gabela ,  Nontando Hlophe ,  Zandile Shabalala ) who.
We constructed three distinct sampling frames (one for each healthcare specialty) by each half-day that the healthcare facilities were open. All eligible patient visits were included from each healthcare facility and each half-day time interval. To construct a sample that reflected the contribution of the various types of healthcare facility found in I ˆle-de-France, the number of individuals to include from each facility was determined according to the group's weight within the total population of migrants from sub-Saharan Africa in the Paris metropolitan era. The data were weighted according to each individual's probability of inclusion in the survey. Patients were eligible if they were born in sub-Saharan Africa, were citizens of a sub-Saharan African country at birth, were between 18 and 59 years old, and had not been diagnosed with HIV or hepatitis B (for the primary-care group) or with HIV infection or CHB (the other two groups) for at least 3 months.
Recruitment occurred at the healthcare facilities. Physicians asked their eligible patients to participate and acquired their written consent. A trained interviewer administered a face-to-face standardized life-event history questionnaire to each participant. Information collected included sociodemographic characteristics, conditions of migration and life in France, relational, sexual, and reproductive histories, and healthcare pathways that included HIV and hepatitis B virus (HBV) testing, healthcare insurance coverage, and engagement in care. Each parameter of interest was documented year to year from birth until the time of data collection. To collect retrospectively this life-event information, we used the life history calendars or "Ageven" sheet (also known as life event or life grid calendars).
This tool has been shown to be effective in reducing recall bias and improving data quality in retrospective studies by providing a graphical time line that helps participants to anchor their responses in relation to different life stages and events. [39] [40] [41] [42]  Clinical and laboratory information was documented from medical records. All information was anonymously collected. The complete survey protocol is registered and available on Clinicaltrials. gov (NCT02566148 https://clinicaltrials. gov/ct2/show/NCT02566148). Other aspects of the study have already been presented elsewhere  [43, 44].
Ethical considerations The Advisory Committee on Data Collection in Health Research (CCTIRS) and the French Data Protection Authority (CNIL) approved the study protocol (CD-2011-484 approval on 7 December 2011). All information was anonymously collected. To take into account difficulties in participating in the survey due to poor or no knowledge of the French language, the patient questionnaire was available in French or English, and, by appointment, an interpreter could be made available to conduct the interview in an African language spoken by the respondent.
Outcomes and variables of interest For each year between the arrival in France and the year of data collection, HIC was documented. The first outcome was the delay of acquisition of first HIC since arrival in France. HIC was defined as any type of basic HIC that lasted for at least one year without considering supplementary health insurance. The others outcome were incidence of first HIC interruption after obtaining it and basic HIC at the time of the study (HI, UHC, SMA or none). The fixed covariates for the analysis of the factors associated with the acquisition delay included the period of arrival, the age, the level of education, place of birth and the reported reasons for migration. Living conditions in France were documented for each year between arrival and the year of data collection through several time-dependent variables: permit of residence, housing situation, economic resources, and activity.
Statistical analyses The analysis focused on people who arrived in France after 1980, who have been in France at time of interview for at least 2 years, aged over 18 on arrival and without missing data in the model variables. Persons who arrived before 1980 or who were under 18 years of age on arrival were not included. Persons who arrived in the previous year did not allow for a satisfactory analysis of the factors related to time. The database and analysis file for reproducing this analysis is available in supporting information (S1 Table and S2 Text) Sociodemographic characteristics, including the main reasons for coming to France and the hardships experienced in France were compared between groups with a design-based [chi] 2 test to compare proportions. Medians of duration were compared with non-parametric equality-of-medians tests.
Characteristics associated with the acquisition of HIC each year since the time of arrival in France were identified using mixed-effect logistic regression models. Models included both fixed and time-dependent covariates and were systematically adjusted for time since arrival in France. Given the retrospective nature of the data and the heterogeneity regarding the time since arrival in France, migrants with a delayed access to HIC may have been particularly underrepresented among those who arrived within the most recent period. To assess possible bias, an additional analysis was performed in a database restricted to participants who had been in France for at least 3 years at the time of interview. In the same way, we analysed factors associated with the loss over time of this first HIC among men and women in the 4 years after it was obtained.
Study population A total of 1184 (reference group), 1829 (HIV) and 1169 (CHB) individuals met the eligibility criteria, among which 124, 141 and 25, respectively, were not offered participation by their physicians due to health problems or cognitive impairment. Eventually, 763 migrants in the reference group, 926 migrants with HIV, and 778 migrants with CHB agreed to participate. A total of 552 subjects were excluded for different reasons: 76 people arrived in France before 1980, 81 had been in France for less than a year, 210 were under the age of 18 at the time of their arrival, and 185 were excluded because of missing data in the variables. Consequently, a total of 1008 men and 907 women were included in the analysis: 547 in the reference group, 749 in the HIV group and 619 in the CHB group.
Continued) When the same analysis was performed on the restricted database (first 3 years after the arrival in France in people who had arrived more than 3 years ago, N = 1736), the period effect was still significant. Participants who arrived after the year 2000 acquired HIC more rapidly than participants who had arrived before the year 2000 (adjusted OR = 1. 57 [1. 12-2. 20] for men and 1. 94  [1. 38-2. 72 ] for women, detailed results not shown and available on request).
Acknowledgments The authors would like to thank all the people who participated in the study, the  RAAC-Sida , COMEDE, FORIM and SOS hepatitis associations for their support in preparing and conducting the survey,  Geraldine Vivier ,  Eva Lelièvre  (INED) and  Anne Gervais  ( AP-HP ) for their support in preparing the questionnaire,  A Guillaume  for the communication tools, ClinSearch and Ipsos for data collection,  Pierre Chauvin  for the discussion of the results, and staff at all participating centres. Participating centres and investigators: HIV group:  Hopital intercommunal de Creteil, service de Medecine Interne  ( I Delacroix ,  B El Harrar V Garrait ,  L Richier );  CHU le Kremlin Bicêtre, service de Medecine Interne  ( K Bourdic ,  M Duracinski ,  C Goujard ,  Y Quertainmont ,  D Peretti );  Hopital Delafontaine, service de Maladies Infectieuses (MA Khuong ,  J Krause ,  M Poupard ,  B Taverne ,  G Tran Van ); Hopital.
Most importantly, there is no model of what best care looks like following discharge from specialist services. The large and growing number of stroke survivors with long-term needs must be addressed; we need to develop minimum standards of care and measure these. There is a growing interest in collecting patientreported outcome measures (PROMs) data that would best reflect patients' views about their care and provide additional information beyond the traditional clinician-reported measures. Patient representatives have played an important role in the development of these measures. The American Heart Association has advocated broader use of PROMs in both clinical practice and research. 96 Similarly, the Swedish Stroke Register 97 has gradually broadened to more fully cover the quality of services and late outcomes after stroke, through follow-up at three months and at one year after the event.
What are the most effective and efficient systems for the collection of data on the quality of stroke care across Europe? 3. How can data on the quality of care be used to compare process and outcomes of care, taking into account variations in case-mix, and what is the min- 2. imum dataset that is needed? 4. What are the systems needed to allow international comparisons of the clinical and cost-effectiveness of care, and reporting of within-country variations and variations by other factors such as geographical region (urban versus rural), and variations over time? 5. What are the most effective quality improvement tools that will enable learning from examples of best practice? Targets for 2030 1. Defining a Common European Framework of Reference for Stroke Care Quality that includes: (a) development or update of European guidelines for management of acute stroke care, longer term rehabilitation and prevention; (b) definition of a common dataset covering core measures of stroke care quality to enable accurate international com- parisons of care both in hospital and in the commu- nity (including structure, process, outcome measures and patient experience).
Blood pressure measurement At each health visit, brachial BP was measured non-invasively three times (with a one-minute interval at least), in the presence of the practitioner, using an automatic standard sphygmomanometer (OMRON 705CP) with adapted arm cuff. Measurement was performed in a back-supported seated position, the arm placed at the same level as the heart, with a 5-min rest at least and without eating, smoking, and exercising at least 30 min before medical examination. The mean of the three measures was used for data analysis (see Additional file 2). The within-visit SBP and DBP variability was evaluated and expressed as standard deviation (SD): concerning SBP between and within-individuals, SDs were respectively 18. 6 and 6. 6 mmHg at T1, and 18. 8 and 5. 5 mmHg at T2; for DBP SDs were respectively 11.
Acknowledgements The authors are grateful to the occupational physicians and other researchers of the VISAT group. Author's contribution YE and SHYK: Conducted the literature review and prepared the material and methods and results and the discussion sections of the text: JCM and JBR designed the study and directed its implementation in each centre, including quality and control of data set. JF supervised the field activities and designed the study analytic strategy: VB supervised statistical analyses and results. DL and CC contributed to literature review and reviewed the manuscript. All authors read and approve the final manuscript.
This article presents a method for step detection from accelerometer and gyrometer signals recorded with Inertial Measurement Units (IMUs). The principle of our step detection algorithm is to recognize the start and end times of the steps in the signal thanks to a predefined library of templates. The algorithm is tested on a database of 1020 recordings, composed of healthy subjects and patients with various neurological or orthopedic troubles. Simulations on more than 40,000 steps show that the template-based method achieves remarkable results with a 98% recall and a 98% precision. The method adapts well to pathological subjects and can be used in a medical context for robust step estimation and gait characterization.
In this context, a template can be seen as a typical step, whose characteristics (amplitude, shape, duration) are typical of a type of step. Existing step detection methods using templates have only investigated the possibility of using one  [19] [20] [21]  or two  [18]  templates. These templates can either be manually defined  [20]  or extracted from the data for one subject  [19, 21]  or from a training database  [18]. We propose to extend this idea by constructing and using a library of several templates, composed of a large set of typical steps that may be found in several pathologies or experimental conditions. The main intuition behind this is that it is a known medical fact that there exist several types of steps (according to interpersonal variability, age, speed and pathology). The existence of different types of steps is in fact a taxonomy based on the clinical examination of the patients as it developed throughout the past century in hospitals.