dataesr/scientific-paragraphs-categorization huggingface dataset:
Patients' characteristics UTIs were diagnosed 1265 times during the study period (1. 2% of all visits to EDs), with 353 ineligible episodes (chronic prostatitis, urinary catheter and/or healthcare-acquired infections). A total of 1097 UTI episodes were eligible, with 912 patients finally included in the study (as 185 had missing data). The demographic details of the patients in each time period were fairly comparable, both overall (Table  1 ) and for each ED (Tables S2, S3 and S4, all available as Supplementary data at JAC Online). Junior doctors (supervised by a senior clinician) took care of 629/912 (69%) UTI episodes.
9, 11, 15 This study, in contrast, describes a transferable CDSS that can be integrated with many existing clinical databases in different hospitals. Moreover, previous reviews have noted the paucity of reports of CDSSs in Europe,  7, 15  and reported studies assessing the impact of a CDSS on antibiotic prescribing in hospitals have been mainly single-centre studies;  15  this paper therefore provides an important contribution. Finally, our results are strengthened by an ORION-compliant methodological design and sufficient statistical power. Our work presents, however, some limitations. First, some collected data were entered by the clinicians themselves. Second, we excluded UTI episodes with missing data from the analysis, and these episodes might correspond to the antibiotic prescriptions that were the least compliant with guidelines.
Acknowledgements We would like to express our thanks to all the doctors who worked in the EDs during the study period. We are additionally grateful for the support we received in implementing the intervention from  Noe ¨l Guilhem (Marseille), Laurent Jacquin (Marseille)  and  Gilles Viudes  (Hyeres). This work was presented as an oral presentation at the 2013 ECCMID ( European Society of Clinical Microbiology and Infectious Diseases)  (Abstract  O657 ) and as a poster at the 2014  French Infectious Diseases Society Congress (Journees Nationales d'Infectiologie)  (Poster M-15).
The first French National Rare Disease Plan allowed the establishment of 131 centres of expertise (CEs) from 2004 to 2007. The process of evaluation elaborated with the HAS (Haute Autorité de Santé) was based on a cycle of 5 years: three years after the certification, the CEs were asked for a document of auto-evaluation and at 5 years there was a visit on site to complete the evaluation. As the certification of CEs was done over a period of 4 years, all the CEs were not evaluated at the same time and it resulted in a complex scheme with heterogeneity of the evaluation according to the time point of the process. The items collected during autoevaluation consisted in general information regarding the composition of the team and of the steering committee, the methods used for the elaboration of the document and quantitative data concerning the activities (clinics, hospitalizations, geographical origin of the patients, proportion of children).
e. , work-family conflicts and availability of technical and human resources. We argued that the availability of technical and human resources may contribute to meet job demands more accurately, together with the well-documented resources already mentioned. In addition, control and its sub-dimensions (autonomy and skill expression) may critically depend on the availability of technical and human resources. Data summarized in the previous section further provided clear evidence of an incidence of work-family conflicts on sleep and fatigue, and thus on job-perception on a given shift or a given shift-phase. In consequence, our job perception questionnaire addressed work demands (psychological, 19 items; physical, six items), control (autonomy, four items; skill expression, eight items), social support (supervisor, five items; co-worker, three items), work-family conflicts (five items), technical and human resource availability (five items).
Briefly, controllers rated either of four responses ["I feel very. ," "I feel a little. ," "I don't know," or "I don't feel. " scoring respectively 4, 3, 2, and 1 point(s)] for each of 20 adjectives relating either to alertness or tension. Workload measures and alertness were collected three times: 1 h after shift-beginning, in the middle of the shift, 1 h prior shift-end. In consequence, control activities were only recorded during the first test flight as it was operated within the first hour of the shift and the data could thus be confronted to the other measures recorded 1 h after shiftbeginning. The irregular flight schedule of later flights did not fit with the procedure described above, so that no further control activity recordings were performed  (Maruque et al. , 2013). As several variables did not meet the criteria of a normal distribution, non-parametric comparisons were performed for each measure across the three shift-phases by using Friedman's test (three related samples with nine observations) and post hoc pair-wise comparisons with Wilcoxon's test.
The same procedure and methodology were used than in the previous experiment. Briefly, three recordings were performed on each shift (1 h following shift-beginning, middle of the shift and 1 h prior shift-end), except for the 5 h-day-shifts where only two recordings were performed. Due to the particular shiftscheduling system, we compared the data collected during the night-shift to those recorded on the day-shifts (pooling data from the morning and afternoon-shifts). Workload was assessed on three (two on short day-shifts) 1-h periods by a job activity index corresponding to the sum of activities performed (phone calls, alarms, supervisory activity, archiving activity), and by the jobperception questionnaire. On each recording they also completed Thayer's adjective check-list, and performed the working memory task in the conditions of low intrinsic load (low difficulty) associated with either low or high extraneous load (high or low time pressure), described in experiment 1.
Cognitive load in the experimental task was assessed by objective measures (response latency, number of correct responses) and by subjective measures (mental effort, perceived task difficulty, time pressure, and task commitment). For the latter, participants were asked to rate 10 cm visual analog scales following completion of each task condition. Skewness and kurtosis tests indicated a normal distribution of the data for most variables, except for tension ratings and for job activity which were therefore discarded from the parametric analyses. Analyses of variance with two repeated measures investigated the effects of shift (day-shift versus night-shift), and of shift-phase (shift-beginning, shift-middle and shift-end), and more especially interactions between the two factors. Correlation analyses with Pearson's test explored the putative relationships between work activity (real-job activity and job-perception) cognitive performance and alertness, separately on each shift-phase of the dayand night-shifts.
Statistics Our aim was to detect the possible existence of executive function impairment from WTMT walking characteristics only. The ascendant hierarchic classification method, or cluster analysis (Ward's method,  37  Euclidean distance), makes it possible to regroup subjects, according to their functional similarities, from the spatiotemporal parameters of walking. The differences between groups formed by the cluster analysis method, be it WTMT or cognitive and functional tests, were studied using analysis of variance (ANOVA), followed by a post hoc Tukey's test. The correlation coefficient between ∆TMT and single-task walking speed and the correlation coefficient between ∆TMT and WTMT were studied using Pearson's R coefficient. Statistical analysis was performed using Statistica Version 9 software (StatSoft Inc, Tulsa, OK, USA).
Introduction: HIV care and treatment programmes worldwide are transforming as they push to deliver universal access to essential prevention, care and treatment services to persons living with HIV and their communities. The characteristics and capacity of these HIV programmes affect patient outcomes and quality of care. Despite the importance of ensuring optimal outcomes, few studies have addressed the capacity of HIV programmes to deliver comprehensive care. We sought to describe such capacity in HIV programmes in seven regions worldwide. Methods: Staff from 128 sites in 41 countries participating in the International epidemiologic Databases to Evaluate AIDS completed a site survey from 2009 to 2010, including sites in the Asia-Pacific region (n020), Latin America and the Caribbean (n07), North America (n07), Central Africa (n012), East Africa (n051), Southern Africa (n016) and West Africa (n015).
Methods The International epidemiologic Databases to Evaluate AIDS (IeDEA) consortium (http://www. iedea. org) is a research network of HIV care and treatment programmes in seven geographical regions: Asia-Pacific, the Caribbean/Latin America, North America, Central Africa, East Africa, Southern Africa and West Africa [26Á30]. Each IeDEA region has an independent data centre and governance structure, although the regions collaborate on cross-region projects. IeDEA is funded by the US National Institutes of Health (NIH) to address key clinical and operational research questions that require data on large numbers of patients receiving care across a spectrum of clinical care settings.
Data collection All seven IeDEA regions agreed to participate in the study. Data managers from each IeDEA region distributed a link to the web-based site assessment survey and a PDF of the paper survey to clinical staff at the adult-only or combined adult-paediatric care clinics within their geographic region. Any surveys returned on paper were entered into REDCap and verified by the regional data teams. The Southern Africa region completed a subset of the survey questions, soliciting data on facility characteristics and opportunistic infection management, but not on other programme characteristics or laboratory capacity. Southern Africa used the WHO DataCol software package (https://extranet. who. int/datacol/home. asp), which was an established data collection tool in their region, and entered data in duplicate into REDCap.
Nevertheless, the diversity in survey participants allowed us to examine a wide array of programme-level characteristics. The 96% response rate indicated that electronic surveys were effective in recruiting participating sites. Nevertheless, our study was limited as we relied on self-reported assessments of clinic services from HIV clinical providers at each site. The responses of health facility staff and survey responses were not independently verified by the research team, so we cannot rule out the possibility of facility staff over-or underreporting the availability of specific aspects of HIV services. Where possible, however, we checked the internal consistency of the survey data and resolved any discrepancies by consulting with regional data managers. Finally, the HIV clinic survey only collected the selfreported availability of HIV prevention, care and treatment services and did not assess patient access to, routine use of and quality of these services.
Acknowledgements We would like to thank  Rosemary McKaig ,  IeDEA Project Scientist at the Epidemiology Branch  of the  National Institute of Allergy and Infectious Diseases Division of AIDS (DAIDS) , for her valuable scientific contribution to the development of this survey. We would also like to thank the following site investigators, clinicians and data managers who distributed and completed the  IeDEA Site Assessment  and made this analysis possible. IeDEA Asia Pacific: The TREAT Asia HIV Observational Database -Cambodia:  Vonthanak Saphonn ,  Sarun Saramony ; China:  Ning Han ,  Man Po Lee ,  Fujie Zhang ;  India: Vivek Bele ,  Sanjay Pujari ; Indonesia:  Tuti Merati ,  Okki Ramadian ,  Flora Yuliana ,  Evy Yunihastuti ; Japan:  Shinichi Oka ,  Misao Takano ; Malaysia:  Anna Kajindran ,  Adeeba Kamarulzaman ,  Lee Lee Low , Benedict LH Sim; Philippines:  Rowena Capistrano ,  Rossana Ditangco ; Taiwan:  Lou Hui Kuo ,  Wing Wai Wong ; Thailand:  Romanee Chaiwarith ,  Mana Khongpattanayothin ,  Sasisopin Kiertiburanakul ,  Wilai Kotarathititum ,  Praphan Phanuphak ,  Bucha Piyavong ; Singapore:  Estelle Fou ,  Oon Tek Ng ; South Korea:  Jun Yong Choi ,  Sang Hoon Han.
The Australian HIV Observational Database - Andrew Carr ,  John Chuah ,  Bridget Dickson ,  Jennifer Hoy ,  Jing Ji ,  Richard Norris ,  David Templeton ,  Kerrie Watson. The Kirby Institute,  UNSW Australia -Courtney Bendall ,  David A Cooper ,  Awachana Jiamsakul ,  Matthew G Law ,  Hamish McManus. TREAT Asia , amfAR Á The Duda SN et al. Journal of the International AIDS Society 2014, 17:19045 http://www. jiasociety. org/index. php/jias/article/view/19045| http://dx. doi. org/10. 7448/IAS. 17. 1. 19045.
Ethics statement For Experiment 1 we reanalyzed a part of the raw dataset of a previously published study  [38]. These data were collected at the ISM in Marseille in 2006. Both experiments reported here were approved by the local institutional review board (Comited'Ethique de l'Institut des Sciences du Mouvement d'Aix-Marseille Universite). In both cases, written informed consent was obtained prior to the study. Both studies were performed in accordance with local University regulations and the 1964 Declaration of Helsinki. None of the participants received compensation. None of the participants were younger than 18.
Task and apparatus In both experiments participants performed two reciprocal aiming tasks. In the (evoked MT) Fitts task they were to move as fast as possible between two target bars whose widths were varied over experimental conditions. Different MTs were evoked by manipulating the spatial precision requirements defining task difficulty. In the (prescribed MT) Schmidt task they were to move at the rhythm of an auditory metronome between two lines while minimizing spatial deviation from the target lines. MT was varied over experimental conditions by manipulating the metronome frequency. The two experiments differed in their settings: Experiment 1 was performed in a standard reciprocal aiming setting and Experiment 2 in a setting with an elastic force-field. In Experiment 1 we report the results of a re-analysis of the raw data collected for the study of Bongers et al  [38].
Data analysis In Experiment 1, half cycles 11 to 50 (i. e. , 40 movements between targets) were used for the analyses whereas in Experiment 2 all half cycles performed during the last 20 s of each trial were analyzed. To determine movement distance (MD) and movement time (MT), the reversal points were detected for each half cycle from the extremes in the raw position data along the horizontal axis. From these reversal positions MD and MT were computed for each aiming movement. Subsequently we computed, for each trial, a mean and a standard deviation of MD and MT, as well as a temporal CV (CVtime = SD of MT/mean MT) and a spatial CV (CVspace = SD of MD/mean MD). Spatial and temporal variabilities were also examined separately for the acceleration and deceleration phases of each aiming movement.
In 2009 Sperlich et al. [10]  completed the study of Samuelson et al. [8]  focusing their research on the effect of vibrations on the cardiopulmonary system of the cyclist. Their study involved 12 cyclists; each one realized a test on ergometer with vibration and another without vibration (the ergometer is placed on a vibration platform with a frequency of 20 Hz and amplitude of 4 mm). The exercise was to increase the pedaling power of 50 W every 5 min starting with an effort to 100 W. The following data were measured during and after the exercise: heart rate, blood lactate concentration, perception of muscular effort and oxygen consumption. As in the study of Samuelson et al. [8]  no significant difference in heart rate was revealed. The comparison of lactate rate and perception of muscular effort did not show significant differences either.
In the study by Arpinar-Avsar  [16] , a field and laboratory study of vibrations is presented. In this study they use the protocol established by the standard ISO2631, concerning the placement of the sensors and the analysis of the acceleration measured. They used tri-axial accelerometers and an EMG system for the data acquisition. They analyze the frequency and amplitude characteristics of vibration exposed to the bicycle and the rider under different characteristics. The study conducted by Peretti et al. [17]  shows the difference of that comfort for two different kinds of bikes indicating a slightly lower acceleration in a racing bike than in a city bike. Other studies focus on the resistance of the rider at different vibrations conditions  [8, 14]  and also the level of vibration under different conditions as speed  [18]  or tyre air pressure in the bike  [17, 19].
Covariates Data on sociodemographic characteristics, socioeconomic position, and medical conditions were recorded via questionnaire. the following set of covariates based on the 2007-2009 assessment was considered in the analysis. Sociodemographic variables included age (continuous in years), sex, ethnicity (white or nonwhite), marital status (married/cohabiting, single, divorced/separated/widowed), educational achievement (none or lower primary school, lower secondary school, higher secondary school, university, or higher degree), socioeconomic position (using the British civil service grades of employment, high, intermediate, low). Health behaviors included: smoking status (current, past, never); alcohol use (none, moderate, heavy use derived from the number of drinks consumed in the past week); frequency of fruit and vegetable consumption; physical activity categorized as active (≥2.
Statistical Analysis to allow comparability across cognitive tests, all scores were converted to z-scores (mean = 0, standard deviation = 1), such that a positive score represents better performance. For the analysis of cognitive data assessed in 2007-2009, scores were standardized using distributions at that wave. For the analysis of cognitive decline between 2002-2004 and 2007-2009, scores were standardized using the 2002-2004 distributions. Only participants with complete covariate data were included in the models. For the analysis of cognitive data from 2007 to 2009, we used linear regression models to estimate the association between pollutants and standardized cognitive scores. to allow comparability across pollutants, associations are reported per interquartile range (iQr) change in 5-year average exposure.
the functional form of the exposures and each continuous covariate was explored by fitting a smooth function in a generalized additive model. We then used an analysis-of-deviance approach to test whether a nonlinear function improved the model fit compared with a linear term. analyses were conducting using r software (2. 15. 2, r Foundation for Statistical computing, Vienna, austria). in sensitivity analyses, participants who moved outside of london between study waves were excluded (n = 213). For the analysis of cognitive decline, linear mixed models were used to estimate the association between exposure to pollutants and cognitive decline between the 2002-2004 and 2007-2009 assessments. We included 2 exposure windows: (1) 5-year average exposure and (2) 4 years prior to the 2007-2009 assessment (yearly lag 4), which was included because residential address was most certain for all participants at that time.
the air pollution-by-time interaction term represents the mean difference in cognition over a 5-year period per iQr change in air pollution. Mixed models were run using SaS software (9. 3, SaS institute, cary, nc). in sensitivity analyses, we (1) excluded participants who moved outside of london between study waves; (2) adjusted the models for area-level income; and (3) adjusted for education scores from the index of Multiple Deprivation at the lower layer Super Output area level. 21.
Crude rates such as the crude death rate are functions of both the age-specific rates and the age composition of a population. However, differences in the age structure between two populations or two time periods can result in specious differences in the corresponding crude rates making direct comparisons between populations or across time inappropriate. Therefore, when comparing crude rates between populations, it is desirable to eliminate or minimize the influence of age composition. This task is accomplished by using a standard age structure yielding an age-standardized rate. This paper proposes an updated International Network for the Demographic Evaluation of Populations and Their Health (INDEPTH) standard for use in low-and middle-income countries (LMICs) based on newly available data from the health and demographic surveillance system site members of the INDEPTH network located throughout Africa and southern Asia.
Compared to the Segi standard, the WHO standard has fewer children proportionally and a greater proportion of adults aged 70'. The International Network for the Demographic Evaluation of Populations and Their Health (INDEPTH) also proposed a standard in 2002 specifically for low-and middle-income countries (LMICs) based on data from 17 health and demographic surveillance system (HDSS) sites located throughout Africa and southeast Asia  (4, 5). Since that time, the availability of high-quality data from INDEPTH member sites has increased to 32 HDSSs. The greater amount of available data, representing a wider range of contexts in LMICs, calls for an updated INDEPTH standard. Although the choice of a standard is ultimately arbitrary, use of varying standards can change comparisons between populations considerably  (1, 2, 5).
The updated INDEPTH standard should better reflect the age structure of LMICs. 1   The INDEPTH standard for LMICs The INDEPTH standard is constructed from a database containing 332 single year age distributions of observed person-years. These data represent 32 HDSSs with varying years of observation from 1983 to 2011. The HDSS data availability along with the total person-years contributed from each HDSS is summarized in Table  1. These data have been screened for consistency and plausibility before inclusion in the final data set. For each HDSS, we first plotted the age-specific deaths and personyears by year and removed HDSS-years that were out of trend given historical rates at that HDSS or an entire HDSS's data series if the data were demographically implausible. We next calculated a life table for each HDSSyear and plotted the annual age-specific mortality rates as well as the annual trend in child mortality ( 5 q 0 or the probability a newborn will die before his or her fifth birthday), adult mortality ( 45 q 15 or the probability that a 15-year-old will die before reaching his or her 60th birthday), and life expectancy at birth and removed any outof-trend years.
INDEPTH standards for sub-Saharan Africa and Asia For comparing LMIC populations across continents, a single standard for LMICs is useful but in the event of comparing just sub-Saharan African (SSA) populations in SSA, it may be more intuitive to use a standard simply for SSA. In addition, African and Asian HDSSs differ considerably in the proportion of their populations aged less than 15 years. To this end, we have calculated separate standard age structures using HDSSs from SSA and those from Asia. These additional standards can be found in Compared to the overall 2013 INDEPTH standard, the region-specific standard for SSA reflects the relatively higher fertility and mortality of the HDSSs in this region. Roughly 44% of the total average person-years lived under age 15 for the SSA life tables in this collection compared to 41% for the entire dataset.