dataesr/scientific-paragraphs-categorization huggingface dataset:
The data were collected 10 years ago but the tobacco epidemic only marginally changed since then and it is unlikely that our estimations of relations between family events and tobacco smoking would have changed in the meanwhile. It is worth noting that we focus on some key family events related to the life cycle, adjusting on the mean time passed in each configuration (couple, first childbirth and separation/single) during the whole life. Couple formation and separation may occur many times during life and it has been shown that multiple broken partnerships reduce the probability of smoking cessation in men  [36] , while it is likely that the anticipation or adaptation effect would vary over age and repetition of the same events. Yet, the succession of the events and their timing are likely to moderate the effects on tobacco smoking: for example maternal age is strongly linked to an initiation after birth  [37].
Quantitative gait assessment Gait performance under ST and DT task was assessed using a 3-D-acceleration sensor, a data logger and a computer program for processing the acceleration signal and calculating the gait parameters (Locometrix®  [31, 32] ). From a period of steady state walking of 21 s. , the software calculated the stride frequency (Hz) and the stride regularity (dimensionless), which describes the similarity of vertical movements over successive strides. Further explanations on the calculation of the variables are described in previous papers  [31, 32]. In addition, walking speed (m/s) was measured using a stopwatch. For the ST and DT, patients were asked to walk along a straight 30 m corridor, free of obstacles, using their regular walking shoes, at their preferred speed. First the ST trial consisted in walking at their usual pace.
Gait assessment Wireless reliable triaxial accelerometers are widely used for gait analysis in ambulatory conditions  [20-22, 44, 45]. From raw acceleration data recorded next to the body mass center, gait characteristics, such as stride frequency and stride regularity may be calculated. Reliability tests such as precision, accuracy  [46] , effective testretest reliability and reproducibility  [32, 47, 48]  during stabilized walking were carried out. Accelerometers were used as they are well adapted to continuous measurement over a period of stabilized walking, which must consist of at least 20 gait cycles in frail elderly people, especially if gait variability has to be assessed  [49].
Materials and Methods The present report is a post hoc analysis of the DIET study. The DIET PE study was an international multicenter prospective, non-randomized, non-interventional diagnostic accuracy study (NCT01221805) in a standard-of-care setting, conducted in consecutive outpatients presenting to the emergency unit or outpatient clinic and suspected of having PE. Patients were recruited from nine different centers, located in Canada (one center), France (two centers), Italy (two centers), Spain (two centers) and the USA (two centers) (see S1 Appendix). According to the protocol, consecutive patients suspected of having PE (hemoptysis, lung-related chest pain or dyspnea), younger than 80 years, without cancer or surgery within the previous month, were managed using the Wells score, STA 1 -Liatest 1 D-Dimers (for low and moderate pretest clinical probability only) and imaging (especially CTPA), according to local practice.
Acknowledgments We thank all investigators of the  DIET Study: Emmanuel de Maistre (France) ,  Carlos Aguilar (Spain) ,  Pascual M Vera (Spain), Gualtiero Palareti (Italy) ,  Armando D'Angelo (Italy) ,  Fabienne Dutrillaux  (France),  Gary Headden (USA) ,  Colin Kaide (USA) ,  Raphael Marlu  (France),  Anais Richard  (France). We thank  Y Gavrilov, PhD ,  Technostat Ltd , for statistical analysis. G Pernod  was a member of F-CRIN,  INNOVTE (Investigation Network On Venous Thrombo-Embolism ).
Conclusions The present study underlined the difficulty to obtain willing maximal clench. In this context, a method to measure jaw muscle activity during a sub-maximal and controlled biting task is proposed. The evolution of the myoelectric activities as a function of the global force delivered on the dynamometer provides new insights of the behavior of the masticatory muscles. These results give also promising data to improve the subject-specific numerical models of the cranio-maxillofacial area, either as inputs or as validation data. the density spectrums of the first and the last five seconds of the MVC signal were estimated using the Welch's method (Hamming window, 50% of overlap,  Giannasi et al. 2014)  and their mean power frequencies (MPF) were computed and compared. Finally, the average value of the muscle activities at maximal force of biting was computed.
General organization and planning We developed GRADE-ADOLPMENT as a result of establishing a new national guideline program by the Ministry of Health in the Kingdom of Saudi Arabia (KSA). Our work began by creating a handbook for guideline production that described the approach and built on our prior work  [2, 12, 24]. The project planning began in June 2012 and implementation of the guideline development started in July 2013. ''Wave 1'' included generating practice guidelines on 10 different topics in 2013, and ''wave 2'' included generating 12 practice guidelines from 2014 to 2015  [25]. Our main goal was to guide the development of recommendations for questions that were relevant for stakeholders in the KSA, using the GRADE EtDs tables.
The guidelines developed addressed a wide range of topic areas, and with the use of the EtDs and software tools (www. gradepro. org), recommendations were formulated specifically for the KSA health care setting. Another advantage of our approach is that the methodology as well as the tools and materials used in the project provide a generalizable approach for various health care and country-specific contexts. It may prove particularly helpful for international organizations such as WHO that often develop global recommendations, which require contextualization and localization. The EtDs facilitate identifying the criteria that may alter the strength or direction of a recommendation. It is important to note some of the limitations of the described approach. Most of the available evidence syntheses were restricted to effects of intervention, and little evidence was available for the other EtD criteria.
Until guideline developers make the criteria clearer that are included in the EtD framework, guideline adolopers will need to extract information from existing guidelines that is often not provided in transparent formats. Thus, the adoption element of GRADE-ADOLOPMENT will be facilitated by the availability of EtD frameworks which, like in this effort, are becoming increasingly available. The GRADE app GRADEpro currently receives an adaptation module that will be further evaluated and refined in subsequent ADOLOPMENT work. The results of the current and future work are available for guideline adolopers on the GRADE database (http://dbep. gradepro. org/). Many current recommendations are supported by limited evidence about EtD criteria. For example, our extensive searches for patients' values and preferences specific to the local setting as well as cost-effectiveness and resource use were well received by panel members but often produced limited data.
Data collection and measures At the time of inclusion, data were collected directly from self-administered questionnaires completed by patients agreeing to participate, including demographic, psycho-social and medical characteristics. The dependent variable was Internet status. Three categories of Internet status were analyzed: no Internet access, Internet access without social networks use and Internet access with social network use. Concerning the independent variables, only the following characteristics were analyzed in this report: ➢ Demographic characteristics: Age, gender, level of education, employment status (unemployed versus employed), living arrangement (living alone versus other status), having children, invalidity and monthly incomes in the household. ➢ Psycho-social characteristics: measured by the perceived social support questionnaire  [17]  composed of four main subscales: esteem, financial, informative and emotional supports.
Data analysis Data were analyzed on SPSS® Statistics 20 software and included both descriptive and multivariate analyses. First, to compare the three groups (no Internet access, Internet access with or without social network use) according to the different characteristics, we used Student test for quantitative variables and chi-square test for categorical ones. Then, to determine characteristics associated with the use of internet and social networks (the dependent variable, categorical with 3 categories), we performed the Polytomous Logistic Regression model (PLR)  [18] , using no Internet access as the comparison category. We introduced all the variables into the multivariate model with a p-value <0. 20 in the univariate model, then we performed a backward elimination procedure with the purpose of conserving only the variables with p-value < 0.
Two potentiometers positioned in the joints of the manipulandum allowed us to measure the angle of each segment, from which the kinematics of the stylus were estimated in the X (left, right) and Y (near, far) dimensions. This information was then used to project a cursor corresponding to participants' hands in real time on the mirror. During recording, raw kinematic data were spatially corrected with a Kalman filter to estimate hand position in real time. With this procedure, the total time necessary to collect the X and Y coordinates of the hand and present the corresponding visual cursor was estimated to be ~7-9 ms. The sampling rate of the manipulandum was 1,000 Hz. Task. Participants were instructed to make center-out reaching movements with the right hand, bringing the visual cursor (green circle; 6 mm in diameter) toward the visual targets.
2001; Khan et al. 2003 Khan et al. , 2006;; Woodworth 1899). Visual inspection of the data revealed that trajectories were very straight. Figure  1B  illustrates the sequence of events for a single trial. Participants brought the cursor into the starting point to begin a trial. After a 1,500-ms resting period, a target was presented, prompting participants to perform the fast reaching movement. The end of the movement was defined as the time when the cursor crossed the target radius, 10 cm away from the starting point. Binary feedback regarding task success was provided immediately at movement end, i. e. , at the crossing of the target radius, hence while in motion. The target turned green if participants successfully achieved the target or turned red if they missed it (see "Success rate" for more details).
Finally, in the readaptation phase, all participants were submitted to a constant 15°CCW cursor rotation. Breaks of ~1 min were given between each phase. Overall, the experiment comprised 560 trials and lasted ~55 min. Reaction time. Reaction time (RT) was calculated as the time between target onset and movement onset, which was defined as the moment when the distance between the manipulandum and the starting point exceeded 2 mm. In a first rejection phase, trials for which RT was smaller than 100 ms or larger than 1,000 ms were discarded. In a second phase, trials were rejected on a per-participant basis. Specifically, trials for which RT was beyond Ϯ3 SD from a participant's mean were rejected. This corresponded to 1. 6% of the data across participants (492 trials). Movement time. Movement time (MT) was calculated as the time between movement onset and movement end, which corresponded to the moment the cursor crossed the 10-cm target radius.
Overall, a total of 4. 1% of the data were rejected. Variability in reach direction. It was hypothesized that uncertainty of the forward (i. e. , inverse) model would be influenced by variance in exposed rotations. As a proxy for uncertainty, the variability in reach directions was measured, because it reflects the level of noise in motor commands  (Bays and Wolpert 2007; Harris and Wolpert 1998; Izawa and Shadmehr 2011). Specifically, the SD of reach directions was computed over the last 40 trials of the baseline phase (cycles 6 -10), providing a baseline assessment of variability, and over the last 40 trials of the adaptation phase (i. e. , cycles 36 -40), when participants were adapted to the visual perturbation. Success rate. To provide feedback regarding task success, the angular difference between the cursor and the target at movement end was computed.
This was done by conducting a three-group (C, LV, HV) ϫ five-phase (baseline, adaptation, no vision, washout, readaptation) mixed-effects analysis of variance (ANOVA). Another analysis sought to confirm that movements did not differ across groups during baseline. To do so, reach directions, variability in reach directions and success rates were measured over the last 40 trials of the baseline phase (i. e. , cycles 6 -10). These data were submitted to separate three-group (C, LV, HV) one-way ANOVAs. The next analysis sought to evaluate the influence of variance in exposed rotations on the initial rate of adaptation to the new visuomotor relationship. This was calculated in two ways. First, adaptation rates were measured for each participant by fitting an exponential function over all trials of the adaptation phase  (Huang et al.
2011; Morehead et al. 2015). The function had the following form: y ϭ a Ϫ b * e x*c Parameter fitting was implemented using the MATLAB function fminbnd to minimize squared error (y). The asymptotic performance parameter, a, was set to the mean of the last five cycles of the adaptation phase (i. e. , cycles 36 -40). The parameter corresponding to the total amount of adaptation, b, was taken as the difference between the mean of the last five cycles of the adaptation phase and the mean of the last five cycles of the baseline phase. The variable x refers to the trial number, and c is the adaptation rate constant, which was the only free parameter in the equation  (Huang et al. 2011). This analysis was supplemented by a model-free analysis in which mean reach direction over the first five cycles of the adaptation phase (i.
e. , cycles 36 -40). To do so, the mean reach direction data were submitted to a three-groups (C, LV, HV) one-way ANOVA. To evaluate whether exposure to different levels of variance in rotations influenced the variability in reach directions as well as success rates, these data were measured over the last five cycles of the adaptation phase (i. e. , cycles 36 -40) and submitted to separate threegroup (C, LV, HV) one-way ANOVAs. Finally, a last set of analyses assessed the influence of variance in exposed rotations on the retention of the new visuomotor relationship. The main test of retention consisted of the no-vision phase, which immediately followed adaptation. Indeed, in the absence of corrective feedback, the persistence of the adapted behavior can be taken as evidence for retention  (Galea et al.
3 Ϯ 0. 5°; F (2, 29) ϭ 1. 1; P ϭ 0. 34; p 2 ϭ 0. 07]. Overall, these data suggest that the initial rate of adaptation was unaffected by variance in exposed rotations. As also shown in Fig. 2A , the three groups tended to plateau at a similar level of performance (~14°) late in adaptation, compensating near fully for the mean rotation of 15°CCW to which they were exposed. To assess the final extent of adaptation, mean reach direction over the last five cycles of the adaptation phase was compared across groups. As shown in Fig. 2C , there was minimal difference across groups, with the C, LV, and HV groups presenting mean reach directions of 13. 9 Ϯ 0. 1°, 13. 7 Ϯ 0. 2°, and 13. 6 Ϯ 0. 2°, respectively. Accordingly, the ANOVA revealed no significant difference across groups [F (2, 29) ϭ 0. 55; P ϭ 0.
Background: Low levels of physical activity (PA) are a global concern and increasing PA engagement is becoming a priority in current public health policies. Despite the large number of studies and reviews available, the evidence regarding the behavioral determinants of PA is still inconclusive. Thus, the aim of this umbrella systematic literature review (SLR) was to summarize the evidence on the behavioral determinants of PA across the life course. Methods: A systematic online search was conducted on MEDLINE, ISI Web of Science, Scopus, and SPORTDiscus databases. The search was limited to studies published in English from January, 2004 to April, 2016. SLRs and meta-analyses (MAs) of observational studies that investigated the behavioral determinants of PA were considered eligible. The extracted data were assessed based on the importance of the determinants, the strength of evidence, and the methodological quality.
Materials The manuscript has been drafted following the PRISMA checklist  [20]. A common protocol of the seven umbrella SLRs (biological, psychological, behavioral, physical, socio-cultural, socio-economic, and policy) was registered and is available on PROSPERO (Record ID: CRD42015010616), the international prospective register of systematic reviews  [21]. Review title, timescale, team details, methods, and general information were all recorded in the PROSPERO register prior completing data extraction.
Data extraction For each included review, data was extracted on a predefined data extraction form, developed by the DEDIPAC-KH and checked by two authors (AK, PA). In reporting data, authors agreed to use the terms "reviews" as those SLRs and MAs found eligible for the umbrella SLR, and 'primary studies' as those studies included in the eligible SLRs and MAs. Moreover, authors agreed to consider all of the terminologies and forms of PA, including unstructured (i. e. , PA linked with daily life) and structured (i. e. , exercise and sports) independently from their frequency, duration, and intensity. The following information was extracted from each included review: year of publication, type of review (either SLR or MA), number of eligible primary studies included in the behavioral umbrella SLR over the total number of primary studies included in the review, continent/s of the included primary studies, primary study design, overall sample size, age range or mean age, gender proportion, year of publication range of included primary studies, outcome details, type of determinant/s, aim of the review, overall results (qualitative or quantitative), overall recommendations, and limitations as provided by the review itself.
15 Figure 3. 153 Figure 3. Integrative scheme of studies focusing on respiratory virus infections. All three actors of the viral disease need to first be completely characterized (microbiome characterization for the environment, viral genome to study the pathogen itself and transcriptomic analyses for the host response). These interactions between host, its microbiome and the pathogen are very important in viral infections pathogeneses. After a complete characterization of these parameters, mechanistic understanding, using animal models, is needed before using these data in clinical diagnosis optimization or for the development of new therapies. Acknowledgments:The authors thank Philip Robinson (DRCI-Hospices Civils de Lyon) for valuable feedback on the manuscript. This project was funded in part by the European Society of Clinical Microbiology and Infectious Diseases (ESCMID) Research Grant 20170223 (L.
Comparison Groups We sought to compare hospitals with similar characteristics. We did so because we reasoned that patients who used not-for-profit academic medical centers (those having residency programs) might be different than those who did not. Therefore, we used the American Hospital Association annual dataset to identify, and limit our analysis to, HVHC and non-HVHC-member hospitals that were not-for-profit, had at least 1 Accreditation Council for Graduate Medical Education (ACGME) accredited residency program, and were accredited by The Joint Commission. This resulted in 26 HVHC hospitals and 92 comparison hospitals, all of which met the inclusion criteria, in 15 HRRs. For each HRR, we present data for HVHC-member and non-HVHC-member hospitals.
Data Elements The outcomes measures that we measured included length of stay, measures of episode costs, and complication rates. Length of stay was calculated as the number of days between admission and discharge from the index admission claim. Acute care cost was defined as the sum of all Medicare claim costs found within 3 days before admission through discharge for index event. Postacute care cost was defined as the sum of all Medicare claims with service in the 30-day episode, beginning at the date of discharge from the index admission; for institutional claims, when admission occurred during the episode but discharge occurred after the end of the episode, the cost for the institutional claim was prorated using the proportion of days which occur during the episode period. Total episode cost was the sum of acute and postacute care costs.
Far targets were located 25 cm away and 20 cm below the close targets: in that case, participants had to perform additional trunk displacement to reach these targets (Figure  1B ). For both target locations, the diameter was also manipulated through Light-Emitting Diodes (LEDs) equally distributed to define two target sizes: Small targets 4 cm or Large targets 10 cm (Figure  1C ). Therefore, in this experiment, combining location and size corresponded to the presentation of four targets: CS (Close-Small), CL (Close-Large), FS (Close-Small), FL (Far-Large). Switching targets on and off were achieved by a homemade software (Docometre©) piloting a real-time acquisition/control system running at 10 kHz (ADwin-Gold © , Jäger, Lorsch, Germany). Markers were positioned onto the participants' index, shoulder and hip.
Data Processing Data presented below describe behavioral features of reaching movements in the sagittal plane and some of them are detailed in  Macaluso et al. (2016). First, we analyzed the fingertip trajectory, success rate (index fingertip within a given target area), index final deviation from target center, reaction time (RT), movement duration (MD), and mean tangential velocity (Vmean endpoint ). The index final deviation was measured as the mean absolute distance of the final position of the index fingertip relative to the target center along the Z vertical axis. For each trial, the time elapsed between target illumination and the release of the start push-button by the participants defined RT. Index position in the sagittal plane was filtered (digital second-order dual-pass Butterworth filter; cutoff frequency 6 Hz in NormoG and 10 Hz in MicroG) and differentiated to obtain the endpoint tangential velocity in m.
s -1. Regarding the different sampling rates of acquisition systems used in both environments, we found that the cutoff frequencies mentioned above were the most suitable to reflect the raw data in normo and microgravity. The movement onset was defined as the time when the index tangential velocity reached 1. 5% of its peak. Conversely, movement end was defined when the tangential velocity dropped below 1. 5% of its peak. The focal component of whole-body reaching movements was analyzed by considering the arm angular elevation over time (i. e. , angle evolution of the extended arm around the shoulder with respect to its initial orientation). Arm angular elevation was computed from the index and shoulder XZ raw data, filtered (digital second-order dual-pass Butterworth filter; cutoff frequency 6 Hz in NormoG and 10 Hz in MicroG) and differentiated to obtain the arm angular velocity profile.