dataesr/scientific-paragraphs-categorization huggingface dataset:
gov number NCT01446601)  [8]. Inspire Medical Systems currently manufactures the only United States Food and Drug Administration-approved HNS device for OSA. This device is an implantable, pacemaker-like pulse generator with a sensing lead placed between the external and internal intercostal muscles to detect breathing effort, and a stimulation lead connected to a cuff electrode wrapped around one (unilateral) hypoglossal nerve  [9]. A 60-month outcome study, the STAR trial, reported a significant decrease in OSA severity and symptoms  [10]. ImThera Medical has developed the aura6000™ system, another HNS device. This system does not include a sensing lead and stimulates the hypoglossal nerve with six electrodes at a more proximal location, co-activating the tongue protrusors and retractors (using different stimulation vectors) to stiffen the posterior aspect of the tongue and pharyngeal walls to open the airway  [11].
Statistical analysis In order to detect a clinically meaningful reduction of ⩾15 events•h -1 in AHI with 90% power at a 5% level of significance, and assuming a standard deviation of 20 events•h -1 , a total sample size of 21 subjects was required to test the null hypothesis. Allowing for a 15% drop-out, 25 subjects were included. The changes from baseline to 6 months after surgery in AHI, ODI, the ESS and FOSQ-10 were calculated for each participant. p-values from a paired t-test were provided for the different measures and all data were presented as mean±SD, unless otherwise stated. Safety-related analyses were performed on an intention-to-treat basis and included all participants who underwent study procedures with data available for analysis (n=27). Modified intention-to-treat analyses were performed on all other measures by excluding two participants in whom no titration was performed (i.
Listeners Ten listeners (seven female) between 20 and 30 years old (mean 25. 3 years) participated. Audiometric thresholds were tested at 0. 25, 0. 5, 1, 2, 4, 6, and 8 kHz using a Madsen Itera II (Otometrics, Taastrup, DK) audiometer, following the recommended procedure of the British Society of Audiology (British Society of Audiology, 2011). All listeners had audiometric thresholds at or below 20 dB hearing level (HL), for both ears, at all frequencies tested. All listeners also had puretone absolute thresholds of less than 20 dB sound pressure level (SPL) at 0. 5 and 5 kHz (see below). Listeners were recruited through a national research participation database (the Relais d'information sur les sciences de la cognition) and from the students and staff of the laboratory, including the first author (S01).
Stimuli All stimuli were generated digitally at a sample rate of 48 kHz using MATLAB R2013b (The Mathworks, Natick, MA) and, using the built-in "audioplayer" command, sent to an audioengine D3 digital-to-analog audio converter (Austin, TX) for conversion at a bit depth of 2 24. The analog signals were presented to listeners with Sennheiser HD600 headphones (Old Lyme, CT) within a double-walled sound-proof booth via a wall patch. HD600 headphones have a diffusefield equalized frequency response. Hence the response is not flat across frequency, but varies smoothly. These variations in level across frequency could transform FM into AM before the stimulus even reaches the ear. Fluctuations in level with frequency were measured with a sound level meter (Br€ uel and Kjaer type 2250) and an artificial ear (Br€ uel and Kjaer type 4153) with pure tones at 0.
Procedure The 3-AFC absolute detection and 2-AFC modulation detection tasks were conducted in the MATLAB environment using the psychoacoustics framework AFC  (version 1. 40. 1; Ewert, 2013). Thresholds were estimated with adaptive staircases that attempted to converge on 71% correct detection using transformed 2-down, 1-up method (e. g. ,  Levitt, 1971). Two consecutive correct responses resulted in a reduction in the dependent variable (DV) for the subsequent trial, whereas any incorrect response resulted in an increase in the DV for the subsequent trial (up to maximum limits). Listeners were given visual feedback after each trial. If the maximum limit was reached three times in any given staircase, that staircase was terminated and skipped. The maximum limit was 0 dB for AM detection and 10% of the f c for FM detection.
03 for f c ¼ 0. 5 kHz and 0. 015 for f c ¼ 5 kHz. Below an FM rate of 8 Hz, FMDTs were lower for 1 s stimuli than the 0. 5 stimuli, but at 8 Hz and above, FMDTs were similar for both stimulus durations. The bottom two panels of Fig. 2  show the ratios of the thresholds with a 16-Hz AM masker to thresholds without AM masking. They show that masking peaked at an FM rate of 16 Hz, with a peak ratio of about 2. 8 to 3. There was little effect of duration for f c ¼ 0. 5 kHz and slightly more masking for 1-s duration stimuli than 0. 5-s duration stimuli for f c ¼ 5 kHz. An ANOVA with four factors was performed on the log-transformed thresholds (2Df divided by the f c ) using the afex R-package  (Singmann et al. , 2017). The factors were  [FM rate (8 levels: 2, 4, 8, 14, 16, 18, 32, and 64 Hz) ; f c (2 levels: 0.
ACKNOWLEDGMENTS The authors thank  Brian C. J. Moore  and  Laurent Demany  for suggestions on interpretation of the data. The authors were supported by two grants from  ANR  (HEARFIN and HEART projects). This work was also supported by  ANR-11-0001-02 PSL*  and  ANR-10-LABX-0087. The authors wish to thank the associate editor,  V. Richards , and two anonymous reviewers for helpful comments on a preliminary version of this manuscript.
Study Design and Sampling This study analyzed data from the 2014 STEPS survey on noncommunicable diseases (NCD) risk factors in Kuwait, which was supported by the Kuwait Ministry of Health (MOH) and the World Health Organization (WHO)  (5). The STEPS survey methods have been previously described in detail  (6). In brief, the target population of this cross-sectional survey included adult Kuwaiti nationals from all Kuwait governorates. The Kuwait Ministry of Information randomly sampled Kuwaiti citizens aged 18-69 years from the national civil registration rolls, with separate random sampling according to eight sub-groups stratified by sex and four age groups  (18-29, 30-44, 45 -59, and 60-69 years). The study estimated that 3,842 participants were needed to achieve a 5% acceptable margin of error within each stratum, assuming Z = 1.
96, a 50% prevalence of a specific characteristic and equal representations in the eight strata. To account for incomplete data and non-responders, this sample selection estimate was increased by 12. 5%, yielding a sample selection size of 4,391. The response rate for the questionnaire and physical examination steps of the study was 89% (n = 3,915; women, 96%; men, 80%). The analysis dataset included the 3,589 participants who had valid measurements of both height and weight. Of these, 307 were missing waist and hip circumference, so analyses of waist-hip ratio (WHiR) and waist-height ratio (WHtR) included 3,282 participants.
Data Collection The WHO STEP-Wise Approach to Surveillance survey methods were used, including a structured questionnaire (Step 1), physical examination (Step 2), and a blood draw (Step 3). Data from Steps 1 and 2 were used for the present analysis. The questionnaire, administered by face-to-face interview, included information regarding sociodemographic factors, tobacco smoking, exercise, and medical history, among other characteristics. The physical examination included measurement of weight (0. 1 kg precision) and height (0. 5 cm precision) using the Growth Management Scale, a device suitable for survey purposes (employing a weight scale and a height gauge with laser). BMI was calculated as weight (kilograms) divided by the height (meters) squared and classified according to the WHO cut-points for underweight (<18.
Bare hip circumference was measured using the same device placed at the maximum circumference of the buttocks. WHiR and WHtR were computed for all respondents consenting to the measurement except for pregnant women. Fourteen individuals had a WHiR ≤0. 55 and 10 individuals had a WHiR ≥1. 8, all of whom had biologically inconsistent waist and hip circumferences in relation to their weight and height. Therefore, waist and hip circumference and WHiR were coded as missing for these outliers. Cut-off values for elevated WHiR were ≥0. 90 for males and ≥0. 85 for females, according to WHO recommendations. Teams composed of physicians, nurses, dieticians, social workers, and phlebotomists collected data at MOH primary healthcare centers within each governorate. The selected survey candidates were contacted and informed regarding the scope and purpose of the study, after which they were invited to come to the center for full informed consent and data collection procedures.
Data Management and Statistical Analyses Statistical analyses were conducted using SAS Statistical Package (version 9. 4), including the package survey commands to account for the sampling weights and provide populationbased estimate, and the STATA Statistical Package (version 14). Sample weights for each of the eight study strata defined by age (18-29 years; 30-44 years; 45-59 years, and 60-69 years) and sex were calculated as the product of the sample selection weight (population number/sample number), the nonresponse weight (1/response rate) and the population weight (population proportion/sample proportion). The Chi-square test, Chi-square test for trend and Mann-Whitney-U test were used to assess the statistical significance of sex (men vs. women) with categorical, ordinal and continuous variables, respectively (Table  1 ).
INTRODUCTION Smoking cessation should be part of tuberculosis (TB) treatment, but a cessation service is not available as part of a routine TB service in most low-and middle-income countries. WHO and The International Union Against Tuberculosis and Lung Disease (The Union) issued a guideline and China implemented a pilot project 5 years ago. This study aimed to determine changes in smoking status among TB patients at 5 years after completion of anti-TB treatment to observe long-term outcome of a smoking cessation project whose baseline characteristics were associated with a relapse of smoking behavior. METHODS A prospective longitudinal study was conducted 5 years after completion of anti-TB treatment to assess changes in patient smoking status against individual baseline data that were entered into a database at the time of TB registration.
The patients were tracked by trained village doctors and validated by township health staff. Their smoking status was assessed and entered into the database and analysed. RESULTS Of the 800 TB patients registered at baseline, 650 (81. 2%) were tracked. Ninety-one (11. 4%) patients died and 59 (7. 4%) were lost to follow-up. The rates of remaining non-smoking after 5 years were 82. 0%, 63. 0%, 49. 6%, 43. 5% and 30. 0%, respectively for non-smokers, ex-smokers, current smokers who received cessation intervention, recent quitters, and current smokers not on a cessation intervention. The odds of smoking relapse were significantly higher for those aged ≥65 years (p=0. 003) and registered in Xingguo County (p=0. 025). CONCLUSIONS Findings from this study confirmed that non-smokers, ex-smokers and current smokers who received cessation intervention at baseline maintained higher non-smoking rates compared with those who did not receive the intervention.
Data collection and analysis Individual patient data at baseline were entered into a database that was kept in the China Office of The Union. The follow-up data were reviewed by the TB dispensary staff and then entered and analyzed by the principal investigator. Categorical comparisons of various current smoking statuses between TB patients originally classified as nonsmokers, ex-smokers, recent quitters and current smokers were carried out using a chi-squared test. Relationships between relapse or continuing smoking and associated exposure variables were evaluated with odds ratios (OR) and 95% confidence intervals using logistic regression. Levels of significance were set at 5%. Variables with unadjusted ORs with p<0. 05 were included in a multivariate logistic regression model.
Limitations This study has some limitations. First, the individual patient data were collected only once after completion of their anti-TB treatment, and it follows that this design may not be able to appropriately answer the overall research question on the long-lasting benefit of the intervention. Second, the smoking status at the TB registration and at follow-up was self-reported and not confirmed through biochemical validation. Previous research has confirmed the reliability of using self-reports via plasma cotinine analysis  34  , but a recent report questioned the accuracy of selfreported smoking status  35. There could have been some reporting bias in our study. Third, almost one in five patients could not be tracked (died or lost to follow-up) and their smoking status at 5 years after completion of anti-TB treatment remained unknown.
Fourth, we did not collect data on patient's economic status, educational background and co-morbid condition, factors that might have impacted on smoking status. Last, the number of current smokers who did not receive the intervention was small, and this may have diminished the power of comparison. Our study aimed to assess long-term changes among TB patients with different smoking status and baseline characteristics at the time of TB registration. A large number of TB patients with different smoking behaviors were consecutively recruited in a routine program setting and were then followed up at 5 years after the completion of anti-TB treatment.
8 seconds to 6. 4 seconds, yielding an effective stimulus bandwidth of 0. 1-2. 5 Hz. The subjects stood on a pressure platform where postural sway was monitored by recording anterioposterior and medial-lateral stance pressure changes  [43] ; it is important to note that although sway and its corresponding EEG may be the product of the same perturbance, these responses are not necessarily dependent upon each other. As such, postural sway was monitored here as a quality control method to ensure appropriate stimulation response. Simultaneous to postural sway, EEG data were recorded continuously from 64 channels in bipolar configuration, with each experimental trial segmented into two phases lasting a total of 230 seconds: the quiet stance phase (30 seconds), designated as the prestimulus baseline (  ), and the stimulation phase (200 seconds).
EEG Data Acquisition The acquisition of EEG data was performed using a 64-channel wet-electrode cap in bipolar configuration with a portable amplifier and recording tablet using EEGO software (ANT Neuro, Enschede Netherlands). A standardized 10-20 system montage was used, and 3D head models were generated with each subject in accordance with standard montage electrode positions  [44]. After strapping the calf muscle vibrators to both legs, participants were informed of the experiment protocol, and the EEG cap was attached, followed by the application of conductive electrode gel to reduce measured impedance to less than 10 kΩ in each channel. Next, a pair of bipolar electrodes were placed proximal to each vibrator to isolate and define vibratory epochs for each stimulation phase. After completing this instrumentation setup, the proprioceptive stimulation experiment was initialized, with EEG data acquired at a sampling frequency of 512 Hz.
Data Processing Following data acquisition, recorded EEG was manually segmented for subject into OE and CE recordings. Next, each dataset was processed according to a series of transformation operations to prepare the measurements for analysis in a customized GUI in Matlab (MathWorks, Inc. , Natick, Massachusetts, USA). Initial preprocessing operations were performed as outlined: 1. Baseline and Stimulation Phase Extraction: each baseline () and stimulation phase which were identified and extracted from each collected dataset to be separately processed. 4. Artifact Detection: automatic artefact detection using a manual voltage threshold set between -100µV and +100µV was used to exclude segments contaminated by eye blinks and/or motion artifacts. An artefact was detected automatically with the ASA feature "Artefact Detection", if EEG data exceed threshold values in at least one channel.
Vibratory Stimuli Finally, the following series of postprocessing operations were then executed: 1. Fast Fourier Transformation (FFT): FFT processing of each EEG dataset was performed using ASA software (ANT Neuro, Enschede Netherlands) using a frequency resolution of 0. 977 Hz  [62] , and epoch durations set to 30 seconds for  data and the entire stimulus duration (as previously noted, ranging from 0. 8-6. 4 seconds) for 1 and 4 stimulation datasets. 2. Power Spectrum Extraction: power spectral density (PSD) values and topologies were then obtained from FFT analysis, normalized in ASA, and finally exported in ASCII format. PSD values were exported in this regard for cohort comparison and statistical analysis using Matlab.
To do this, PSD values were extracted and averaged within each band over all electrodes, resulting in 6x1 vectors for each subject for both OE and CE trials, according to the following expressions: Adaptation: 𝛿(𝑄1 -𝐵𝐿)% = 100 × 𝜇 𝑄1 -𝜇 𝐵𝐿 𝜇 𝐵𝐿 (1) Habituation: 𝛿(𝑄4 -𝑄1)% = 100 × 𝜇 𝑄4 -𝜇 𝑄1 𝜇 𝑄1 (2) To assess statistical significance between datasets, pairwise, two-sample Z-tests were performed, and  < 0. 05 was analogously considered the threshold for significance. To correct for multiple comparisons, the -values of sensor-wise comparisons were corrected using the Benjamini-Hochberg (BH) method  [71].
Acknowledgments This research was supported jointly by the  Institute for Biomedical and Neural Engineering at the University of Reykjavík , the  Department of Anatomy at the University of Iceland , and the  Icelandic National Hospital (Landspítali Scientific Fund, PI: Paolo Gargiulo)  with additional funding support from the  Rannís Icelandic Research Fund (Rannsóknasjodur, PI: Paolo Gargiulo). We would likewise like to acknowledge our international collaborators at the  University of Rennes , the  School of Life and Health Sciences at Aston University , and the  Department of Electrical Engineering and Information Technology at the University of Naples, Federico II.
Given the current legislation  (Decision nos. 1. 148, 2008 and 68, 2012) , each hospital must be accredited, accreditation being how it is demonstrated that a medical unit endeavors to provide medical care services to meet patients' expectations, both in terms of results, and in terms of the conditions under which accreditation is granted. The accreditation assessment visit, ensured by the National Authority for Quality of Health Management (ANMCS) in 2014, responded to eighteen indicators concerning the pharmacy, of which only one did not apply, the rest being in conformity. Notable among these indicators are: the decision as to the person responsible for the pharmacy database; analysis, carried out by the pharmacy, of antibiotic use in the hospital; reports to be completed by the pharmaceutical service on monthly consumption and needs of medication, sent monthly to the hospital sectors; regular training of employee personnel who handle toxic substances; and procedures concerning the handling of volatile and dangerous substances.
This involvement could help to better define the scope of research and improve factors, such as sustainability  [7] , dignity, self-respect, responsibility, social identity, and empowerment of research participants  [8]. According to some researchers, involvement would balance the power between researchers and research participants  [9]. It is ethically recommended to involve participants in the design of health interventions. Furthermore, many research projects are funded by governments through taxes  [9]  that are supported by the general population. Rifkin and her colleagues proposed an analytical framework in the form of a pentagram  [7, 10]. They defined involvement as "the social process by which specific groups with shared needs living in a defined geographical area actively pursue the identification of their needs, make decisions, and establish mechanisms to meet their needs".
Search Strategy, Criteria, and Approach Four databases considered relevant with regards to our research question were screened to identify articles written in English or French, published from 1 January, 2016 to 30 April, 2018. This time period was chosen in order to obtain better insights into the most recent interventions targeting residents, their relatives, and health professionals (nurses and doctors), and according to the date of the beginning of this review. This time period was also used to inform an upcoming interventional study in nursing homes. The four selected databases were MEDLINE, SCOPUS, WEB OF SCIENCE, and CINHAL. Prior to the search equation, the authors screened PUBMED to analyze reviews of systematic review dealing with interventions implemented in long-term facilities.
The purpose of this preliminary work was to identify relevant keywords for designing the combination query (Table  S1 ). Then, a combination of keywords was used to query the databases and identify eligible relevant studies that focus on interventions targeting knowledge, practices, or behaviors in long-term care facilities  [13, 14]  (Table  S1 ). Articles eligible for the present study met the following study design criteria: Single or cluster randomized trials, before-after studies or time series, cross sectional studies, case report or qualitative studies, and mixed studies approach. Literature reviews, drugs clinical researches, and diagnostic and prognostic tests were not included in this study. Clinical, diagnostic, and prognostic studies were too specific to be included and were out of scope of the present work as we did not aim to implement a review of systematic review studies.
In the perspective of a planned intervention by our research team, all interventions in the articles included in this study targeted nurses, physicians, residents, and their families. We imported all the references found in the four aforementioned databases to ZOTERO software version 5. 0. 55. 1 (Center for History and New Media, Fairfax, VA, USA) to identify duplicate articles and remove them. The different steps of screening and analyses were conducted by the two authors with discussion in case of discrepancies. The next steps consisted of checking the abstracts, the language of the publication, the type of intervention involved, and the participants included in these interventions, as well as the study designs. When a summary of an article fulfilled all the criteria described above, the full article was retained for a full-text assessment.
Design and Translation of the Questionnaire Cross-sectional data collection was conducted in May 2016 with students who completed an online questionnaire available in French, German, and English. We created the items of our instrument after a qualitative pilot study among adolescents' focus groups. Although Luxembourg is multilingual and very culturally diverse (more than 170 different nationalities), the official languages are Luxembourgish, but also French and German. English, then, is the most common foreign language taught in the international school where we organized this survey. Each version had been translated, back-translated, and then proofread by native-speaking professional translators. In order to avoid mis-comprehension of the questionnaire, because of the differences of maturity between children of 11 and of 15 years old, we have tested the self-administrated questionnaire in focus-groups before its administration, and modified it according to the students comprehension and reactions.