dataesr/scientific-paragraphs-categorization huggingface dataset:
Loci with statistically significant changes (Benjamini-Hochberg adjusted P value <0. 05) in chromatin accessibility were checked for whether they overlap with T-bet ChIP-seq peaks in Th1 cells or GATA-3 ChIP-seq peaks in Th2 cells. Among all loci that overlapped with GATA-3 ChIP-seq peaks, 413 loci, the chromatin accessibilities of which were increased in T-bet-deficient CD4 + T cells but reversed by WT T-bet complementation, and 849 loci, the chromatin accessibilities of which were decreased in a T-bet-dependent manner, were visualized within a heatmap using the pheatmap R package (version 1. 0. 12). ChIP-seq and omni-ATAC-seq peaks were reviewed using the Broad's Integrative Genomics Viewer  (Robinson et al. , 2011).
Statistical analysis Statistical analysis was performed with PRISM software (Graphpad). All values are expressed as the mean ± SD or SEM, as indicated in the figure legends. Student's t tests, one-way ANOVA, two-way ANOVA, or nonparametric tests were performed, depending on the hypotheses tested, as explained in the figure legends. An α < 0. 05 was considered statistically significant. ). (E-K) Libraries of memory CD4 + T cells from a healthy donor (CTRL) and the patient (M/M) were screened for antigen reactivity by culturing T cells with autologous antigen-presenting cells, with or without peptide pools derived from the microbes indicated. T cell clones from memory CD4 + T cell libraries responding to peptide pools from indicated pathogens were subjected to Luminex assays to determine the levels of IL-4 (E), IL-9 (F), IL-13 (G-J), and IL-5 (K).
ICS for IFN-γ and IL-5 is shown. (I) ICS for IL-5, IL-4, IL-13, and IL-17A is shown as in H. (J-L) Percentages of IL-5-producing (J), IL-4 + IFN-γ -(K), and IL-13 + IFN-γ -(L) cells as in H and I are shown. In J-L, bars represent the mean and SD. Dots represent individual samples. Data from A-G were summarized from a single scRNA-seq experiment containing >2,000 single-cell datasets, which secures enough replications. Data from H-L were verified in at least two independent experiments.
Acknowledgments We thank the patients and their families; the members of the laboratory;  Cecilia Lindestam Arlehamn  and  Alessandro Sette ;  David Jarrossay ,  Mathilde Foglierini ,  Ivo Kwee , and  Murodzhon Akhmedov ;  Jean-Pierre Lantin ; and the  Genomics  and the Flow We thank the  National Center for Advancing Translational Sciences  of the  National Institutes of Health  ( UL1TR001866  to  Rockefeller University ); the  National Institute of Allergy and Infectious Diseases, National Institutes of Health  ( R37AI095983  to  J. -L. Casanova  and  J. Bustamante ); the  Sackler Center for Biomedicine and Nutrition at the Center for Clinical and Translational Science ; the  Shapiro-Silverberg Fund for the Advancement of Translational Research at the Center for Clinical and Translational Science, Rockefeller University  (to R.
Yang); the  Research Grant Program  of the  Immune Deficiency Foundation  (to  R. Yang ); the  Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence  ( ANR-10-LABX-62-IBEID ); the  French National Research Agency  under the  "Investments for the Future" program  ( ANR-10-IAHU-01 );  ANR-GENMSMD  ( ANR-16-CE17-0005-01  to  J. Bustamante );  ANR-LTh-MSMD-CMCD  ( ANR-18-CE93-0008-01  to  A. Puel  and  F. Sallusto );  Fonds de Recherche en Santé Respiratoire  ( SRC2017  to  J. Bustamante ); the  French Foundation for Medical Research  ( EQU201903007798 ); the  SCOR Corporate Foundation for Science ; and the  Swiss National Science Foundation  ( 310030L_182728  to  F. Sallusto ). J. Rosain  was supported by an Institut national de la santé et de la recherche médicale Poste d'accueil;  J.
T cell clones from memory CD4 + T cell libraries responding to peptide pools from indicated pathogens were subjected to Luminex assays to determine the levels of IL-4 (E), IL-9 (F), IL-13 (G-J), and IL-5 (K). In E-K, the bars represent the mean and SD. Dots represent individual T cell clones. Unpaired Student's t tests were used in E-K. In E-K, *, P < 0. 05; **, P < 0. 01; ****, P < 0. 0001. Data from A-D were summarized from a single experiment with library preparations from three CTRLs and independent repeats of library preparations from M/M and M/M complemented with EV or WT. Data from E-K summarized from a single experiment that contained hundreds of single-cell clones that were independently measured to secure enough replications.
In this study the reference speed is fixed to V ref = 50 km/h. Noise data can be analysed by means of a logarithmic regression on the experimental data for each combination of EV and road surface. Figure  8  plots the regression line obtained from the overall noise level L Amax and the vehicle speed V in the case of the Nissan LEAF rolling on the E1 test section. The values of the parameters L Amax (V ref ) and b L Amax are displayed on the graph. The standard deviation of the parameters can be estimated via the 95% confidence interval of the regression. The coefficient of determination of the regression r 2 is also indicated and is very close to 1 in most of the configurations. From these data, one can estimate the CPB noise level at any vehicle speed between 20 and 110 km/h. In the following, the analysis focuses on the results at the reference urban speed of 50 km/h.
2 are applied uniformly over the entire frequency range to provide vehicle noise spectra at the reference air temperature of 20 ∘ C and derive the average EV spectrum. Vehicle noise emission models provided for noise mapping, like in the European method CNOSSOS-EU  [28] , mostly rely on frequency spectrum data and global noise levels are computed by frequency integration. The same approach has been taken here to derive the global pass-by noise of an average EV (Figure  12 ). It turns out that considering the French EV traffic mix or the European one does not really matter, since the distribution of noise levels is poorly correlated with the vehicle segment. Therefore, the distribution of EV classes in the traffic has a very minor impact on average noise spectrum and average global noise, whatever the road surface in urban situation.
Conclusions In this study, the CPB noise levels of five EV models have been measured on six reference road surfaces with different texture and sound absorption properties. CPB tests have been performed at constant vehicle speed ranging between 20 km/h and 110 km/h. Special care was taken towards the immunity of the pass-by maximum noise levels and associated spectra towards the background noise levels. Invalid data (i. e. with ∆L < 6 dBA) have been pointed out in the frequency domain, at low vehicle speed only and mainly in the frequency range below 315 Hz. For overall and spectral noise levels with ∆L ≥ 6 dBA, a correction factor was applied. A logarithmic regression of noise levels versus vehicle speed was performed from the set of valid data. This gives the possibility to assess the CPB noise levels at any vehicle speed for the 30 combinations of EV and test section.
Acknowledgements Many sources of information are available regarding the history of  Marie Curie  and the  International Radium Standard. This paper is mainly based on the Archives of the BIPM. André Allisy  (1924Allisy ( -2017) ) with his paper published in Metrologia in 1994 wrote an interesting summary of the history of the  Radium International Standard and documented the establishment of the Ionizing Radiation Section at the BIPM. Prof. Allisy  worked at the BIPM from 1961 to 1989 as Director of the Ionizing Radiation Section, which he created. Prof. Allisy  used his skill and good judgment to establish the four BIPM laboratories dedicated to: dosimetry measurements for x-rays and gamma-rays; neutron measurements; activity measurement for beta and gamma emitters; and determination of absolute alpha emitter energies.
Monitoring With Limited Information We consider a system with an evolving state that can be stopped at any time by a decision maker (DM), yielding a state-dependent reward. The DM does not observe the state except for a limited number of monitoring times, which he must choose, in conjunction with a suitable stopping policy, to maximize his reward. Dealing with this type of stopping problems, which arise in a variety of applications from healthcare to finance, often requires excessive amounts of data for calibration purposes, and prohibitive computational resources. To overcome these challenges, we propose a robust optimization approach, whereby adaptive uncertainty sets capture the information acquired through monitoring. We consider two versions of the problem-static and dynamic-depending on how the monitoring times are chosen.
predict CAV progression. Indeed, very little data is available from prior studies of CAV patients, a problem that is compounded by the disease's pathology, which is known to be very complex (see §5). How should CAV patients and their physicians make monitoring and treatment decisions facing this considerable uncertainty? Similarly, consider a lending institution that extends commercial loans backed by working assets, such as inventory. For a given loan, the lender can occasionally monitor the value of the pledged collateral through costly field visits and inspections, and decide whether to request early repayment or force collateral liquidation, to avert future possible losses. Making predictions about future collateral value, however, could be a very challenging task, as it would involve tracking the value of a considerable number of assets classes that are present in or correlated with the pledged assets.
When the bounding functions are concave, all monitoring times are needed for reducing the uncertainty, and it is optimal for the DM to distribute these times uniformly over the horizon. We discuss conditions relying on complementarity properties (e. g. , supermodularity) of the reward function and uncertainty envelopes that allow solving the problem through combinatorial algorithms. Article submitted to Management Science; manuscript no. • We leverage our approach to devise monitoring and transplantation policies for patients suffering from Cardiac Allograft Vasculopathy (CAV). We calibrate our model using data from health studies and published medical papers, and show how optimal monitoring and stopping policies can be found by solving mixed-integer linear programming problems. Simulation suggests that our policies generate life year gains that stochastically dominate those provided by existing medical guidelines, with a substantial increase in lower percentiles and a slight increase in median and higher percentiles.
Data Description There is limited data that can be used to guide CAV disease management decisions. To calibrate CAV development, we use a dataset from the Papworth Hospital that was compiled by monitoring 622 heart-transplanted patients on a yearly basis and recording their disease progression, starting from the transplant surgery. 9 The length of the monitoring horizon across all patients varies from a few days to 20 years, with an average of 3. 85 years and a standard deviation of 3. 34 years. At each monitoring time, the patient's CAV stage 9 Data is publicly available in an R package called 'msm. ' Article submitted to Management Science; manuscript no. is recorded; CAV progression is classified into three stages-stage 1 (Not Significant), stage 2 (Mild) and stage 3 (Severe)-depending on the observed degree of angiographic lesion and allograft dysfunction.
The dataset comprises 2,846 monitoring observations. To calibrate survival after re-transplantation, we obtained data from  Tjang (2007) ,  Copeland et al. (2011 ), Schnetzler et al. (1998) ,  Novitzky et al. (1985) ; in particular, we obtained 37 observations of survivability outcomes after the second transplantation, for different intervals between the two transplants.
Uncertainty Sets for CAV Progression To = β ij 0 + β ij 1 * t + β ij 2 * age(t), ∀ (i, j) ∈ (1, 2), (1, 3), (2, 3). (23) Table  2  reports the coefficients we obtained after fitting this model to our CAV monitoring data using maximum likelihood estimation. (i, j) β ij 0 β ij 1 β ij 2 (1,2) 18. 0826 (0. 8900) -0. 6511 (0. 0456) -0. 1820 (0. 0177) (1,3) 38. 8900 (2. 8844) -1. 1412 (0. 1754) -0. 3991 (0. 0573) (2,3) 6. 5479 (0. 9671) -0. 1576 (0. 0745) -0. 0492 (0. 0178) Using the model for transition times, we then derive confidence intervals that we use to construct uncertainty sets for the amount of time spent in each disease state. Specifically, suppose a patient is monitored post-transplant at time t, resulting in an observation (x 2 (t), x 3 (t), age(t)). When the patient is again monitored after an additional ∆t time units, the possible values for x 2 (t + ∆t) can be described as follows.
Data sources A literature search was performed using the electronic database PubMed. In total, we conducted six literature reviews for each new technology, namely, open-field camera, telemedicine, 3D printing, social networks, serious games and virtual reality. The keywords used were selected from key articles to create a broad search as described in Table  1. We screened all the articles, a first selection was made after reading titles, then a second selection after reading abstracts and the final selection was made after reading full-texts. The final search was conducted on November 20, 2020.
But a new solution has emerged in recent years. Threedimensional printing, also known as rapid prototyping, additive manufacturing or solid free-form technology, is a process used to make a 3D entity from series of two-dimensional images  [54, 56, 60, [64] [65] [66] [67]. It is a method made by fusing or depositing materials in layer to create a 3D object  [54, 62]. It is a recent development, the first applications date from 1980s with Charles Hull  [54, 68]. In medicine, it is possible to use data coming from scans or MRIs to recreate 3D models  [54, 60, 66, 69]. All the software that can transform a scan into a 3D digital image can be found online free of charge, they are easy and intuitive to use and there are several online tutorials giving accurate instructions. The main software are OsiriX 1 (Pixmeo, Geneva, Swiss), Meshlab 1 (Instituto di Scienza e Tecnologie dell'informazione, Roma, Italia) Netfabb 1 (Autodesk, San Rafael, USA) and Blender 1 (Blender Foundation, Amsterdam, Netherlands)  [70].
Study design A cross-sectional study was conducted among working health-care professionals all over Lebanon for a period of 3 months starting from March, when our first participant was recruited, till June 2021, when our data collection ended. The questionnaire included three main parts and required 7-10 min to complete. It was first written in English and then translated to Arabic in order to target a larger number of participants. The first part included sociodemographic questions such as those on age, gender, residence, profession, and working region. The second part aimed at work conditions such as working schedule, work type, years of working experience, and job satisfaction. The third part of the questionnaire included the Maslach Burnout Inventory for Health Services Survey (MBI-HSS) and the Trait Meta-Mood Scale (TMMS-24) to assess emotional intelligence, as well as a soft skill assessment scale using a five-point Likert scale ranging from strongly disagree (=1) to strongly agree (=5).
Statistical analysis SPSS 25 for Windows was used for analyzing the data. Regarding the bivariate analysis, T test, Mann-Whitney test, analysis of variance (ANOVA), and Kruskal-Wallis tests were used to compare the means, whenever the association between a qualitative and a quantitative variable was tested. Pearson and Spearman correlations were used to test the association between two quantitative variables. P-value <0. 05 was considered as significant, and the CI was set at 95%. A Cronbach alpha was recorded for reliability analysis of all the scales. A linear regression was used to assess the effect of soft skills and emotional intelligence on burnout. Variables with a P-value <0. 2 were included in the multivariable analyses.
These factors collectively affected the representativeness of our sample. In addition, many factors were not addressed during data collection, such as financial situation and income, psychological support, and antipsychotics consumption  (Fond et al. , 2019). A volunteer bias might thus be present since it is an observational study and participants had the option to refuse participation. In addition, a non-response bias might as well occur, which affects the precision of the study by reducing the sample size. Third, the scales used in this study are not validated in Lebanon, which might cause some non-differential information bias. Furthermore, the collected data was based on self-reported measures, which may lead to an information bias. Despite the previously mentioned limitations, our study had many strengths.
Study Design and Data Analysis The evaluation consisted of assessing three components: the validity, reliability, and usability of the TEMAS. Participants were asked to independently use the TEMAS to evaluate the medication alerting system in use at their hospital and then complete a 7-item survey. To assess validity, the survey included a free-text item on the perceived effectiveness of the alerts in the CPOE system and asked for supporting information or evidence with their response (eg, information on alert override rates, any formal or informal feedback received from users, and results from any in-house user surveys). Data collected from this item were analyzed by categorizing responses according to their positive or negative valence. Supporting information provided by participants was compared with TEMAS results to check whether the shortcomings of the alerting system identified by the TEMAS were consistent with those identified by in-house evaluations carried out by the hospitals.
To assess reliability, we compared the responses of participants working at the same hospital. Krippendorff α was calculated to determine interrater reliability. To assess usability, participants were given the opportunity to provide feedback on each TEMAS item to indicate whether an item was difficult to understand or was not useful (Figure  1 ). In addition, participants completed a usability survey (Multimedia Appendix 2), which collected basic demographic information, data on the ease of use using a five-point Likert scale (eg, item 1: I thought the TEMAS was easy to use), and free-text comments on the tool. The Likert-scale items were adapted from the system usability scale  [27].
a b s t r a c t Background. -Various vascular closure devices (VCDs) are available for local hemostasis after percutaneous transfemoral approach for neuroendovascular procedures but they have been associated with an increased complication rate and limitations to a re-puncture of the artery. We evaluated the safety and efficacy of Safeguard ® 24 cm pressure assisted device (Merit Medical, West Jordan, UT, USA) and the associated complications. Methods. -From September 2016 to December 2019, 879 patients underwent neuroendovascular procedures via transfemoral approach using an introducer sheath ranging from 4 to 6-French and they were included in a prospective database. We registered the demographic characteristics and procedural factors. We evaluated the device failure and associated complications.
Safeguard ® 24 cm pressure assisted device, (Merit Medical, West Jordan, UT, USA) is a pneumatic compression device that has been developed for local hemostasis of the femoral artery after brief manual compression. We evaluated the efficacy of the Safeguard ® in a series of 879 patients and we report the complications associated with its routine use following femoral arterial puncture for neuroendovascular diagnostic and interventional procedures. in our department, via a percutaneous transfemoral approach, using an introducer sheath ranging from 4-French to 6-French and they were managed by Safeguard in order to achieve local hemostasis. We conducted a retrospective study, based on a prospective database, in order to evaluate the safety and efficacy of the Safeguard Manual Assist Technique in the post angiography local hemostasis management of the femoral percutaneous access.
6 corresponds to poor and 1 to excellent. The threshold between bleeding and no bleeding was set at the "Age" for which three parameters associated with the ROC curveharmonic mean HM of specificity and sensitivity, Youden index = Sensitivity (SNS) + Specificity (SPC) -1 were maximum and the distance from the top left corner (SNS = SPC = 1) was minimum. The relation between the two sets of data was explored with Pearson's linear correlation coefficient r with the associated regression coefficient. Open source software (www. openepi. com) was used along with Statplus for Macintosh ver. 6 (AnalystSoft, Walnut, CA, USA).
FOTT-SAS: The results of the SWADOC-scored in one session will be compared to those of the FOTT Swallowing Assessment of Saliva (FOTT-SAS)  (30). The test comprises seven questions; if items 1-4 are answered "Yes" and items 5-7 are answered "No, " oral intake should be initiated (Supplementary Material 4). The FOTT-SAS includes items that can be scored based on the administration of the SWADOC. In that respect, no additional administration will be required. The clinical protocol procedure is illustrated in Figure  3. Because of clinical realities, no attempt will be made beforehand to standardize the order (SECONDs before or after SWADOC and examiner 2 before or after examiner 1) or time of day (morning or afternoon) of evaluations. However, during data collection, efforts will progressively be made to balance the order and time of day and the time of evaluation of examiner 2 (before or after examiner 1).
ACKNOWLEDGMENTS We thank in advance all the patients and their families who will be included in this study, the staff of the intensive care unit of the  University Hospital of Liège , the  William Lennox Neurological Hospital , the  Center of Traumatology and Readaptation (CTR Jette, Erasme) , the rehabilitation center of Fraiture-en-Condroz, the neurology unit of the  Péri-Valdor Clinics , the  University Hospital of Nîmes , the  Hospital of Uzès  and the  Functional Rehabilitation Clinic of Fontfroide (Montpellier) , as well as the 10 experts for their much-appreciated review of the tool.
Ethical approval and consent to participate The study was approved by the Ethics Committee of the Regional Health Agency Network (LINUT) prior to data collection. The data were collected within the framework of the agreements signed between the Limousin Nutrition network (LINUT), health network of the Nouvelle Aquitaine Regional Health Agency and the Elderly Nursing Homes, which stipulate that patient data can be used for research purposes after approval by the patients or their legal representatives. The NH were all volunteers, they were contracted for clinical research with the LINUT network, and residents or their legal representatives had given their verbal informed consent for the assessments, noted on each residents' file by the LINUT dieticians.
Consent for publication According to the agreement signed between the Limousin Nutrition network (LINUT), health network of the Nouvelle Aquitaine Regional Health Agency and the Elderly Nursing Homes, data collected with the approval of patients or their legal representatives can be used for publication. The exhaustive descriptive cross-sectional study covered 13 NH in the Limousin territory (including three departments and around 800,000 inhabitants), between 2008 and 2014. All residents of each NH were included, except those whose state of health, according to the doctor, did not allow the measurements or those who refused the measurements after being informed. The assessments were carried out by a doctor and a dietician from the network specializing in geriatrics, and lasted two to three days by NH, depending on the number of residents to be assessed.