dataesr/scientific-paragraphs-categorization huggingface dataset:
According to the above, this work presents the implementation of an HREI interface in order to join the multiple advantages of the current HRI and REI interfaces on the AGoRA Smart Walker. The AGoRA Walker is equipped with a sensory and actuation interface that enables the implementation of several functionalities for HRI and REI, as well as a set of control strategies for shared control and social interaction. Moreover, the developed interface is equipped with a robust navigation system, a user interaction system (i. e. , a gait analyzer module and an user's intention detector), a low-level safety system, a people detection system for social interaction, and a safe strategy for shared control of the walker.
Robotic Platform Description According to the different motivations and related approaches presented in Sections 1 and 2, this work covers the design, development, and implementation of a set of control strategies and interaction systems that establish an HREI interface on a robotic walker. Hence, a robotic platform was adapted to emulate the structural frame of a conventional assistance walker, by attaching two forearm support handlebars on the platform's main deck. Specifically, the Pioneer LX research platform (Omron Adept Technologies, Pleasanton, CA, USA), named as AGoRA Smart Walker, was used to implement and test the interface systems. The platform is equipped with an onboard computer running a Linux operating system distribution providing support for the Robotic Operating System (ROS) framework.
Additionally, to leverage the AGoRA Smart Walker's processing capabilities, an external computer is used for running several non-critical systems. The communication with the external CPU can be achieved through the walker's Ethernet and Wi-Fi modules. As shown in Figure  1b , the position of the force sensors on the platform's deck is not vertically aligned with the actual supporting points of the user on the handlebars. Essentially, the forces in yand z-axis read by the sensors (i. e. , F yRight , F yLe f t , F zRight and F zLe f t ) will be a combination of the forces in yand z-axis at the supporting points (i. e. , Fsp yRight , Fsp yLe f t , Fsp zRight and Fsp zLe f t ). The forces in x-axis (i. e, F xRight , F xLe f t , Fsp xRight and Fsp xLe f t ) are discarded, as they do not provide additional relevant information.
Map Building and Robot Localization Relying on the ROS navigation stack, a 2D map building algorithm, that uses a Simultaneous Localization and Mapping (SLAM) technique to learn a map from the unknown environment was integrated. Specifically, the ROS GMapping package for map learning was used  [53]. This package is aimed at creating a static map of the complete interaction environment. The static map is made off-line and is focused on defining the main constrains and characteristics of the environment. Figure  7a  shows the raw static map obtained at the authors' research center. This map is also used for the walker on-line localization. For this purpose, the Adaptive Monte Carlo Localization Approach (AMCL)  [54]  was configured and integrated. In general, zones such as stairs, elevator entrances, and corridor railings, among others, are defined as non-interaction zones (i.
Experimental Tests To evaluate the described HREI interface, several performance and usability tests were proposed, regarding the control strategies previously described. The main goal of these tests was to assess the performance of every module of the AGoRA Smart Walker, both independently and simultaneously. Several healthy subjects were recruited to voluntarily participate in the validation study. Specifically, seven volunteers conformed the validation group (6 males, 1 female, 33. 71 ± 16. 63 y. o. , 1. 69 ± 0. 056 m, 65. 42 ± 7. 53 kg) with no gait assistance requirements accomplished the tests that are further presented (see Table  3  for additional information). The experimental trials took place at the laboratories building of the Colombian School of Engineering. A total of 21 trials divided into 7 sessions were performed.
Questionnaires Responses To qualitatively assess the interactions between the participants and the AGoRA Walker, at the end of each trial, the volunteers were asked to fill out a usability questionnaire to obtain instant perceptions of the mode of operation. The participants were also encouraged to highlight perceptions regarding the interaction with the smart walker. Regarding the perception questionnaire, based on the UTAUT models in  [66, 67] , an acceptance and usability questionnaire was designed. The questionnaire was adapted to be relevant to the interaction with the AGoRA Walker (see Table  5  for further details). In this session, I felt that I had control of the device Q9 In this session, I felt that the device had the control of the path to be followed Q10 In this session, I felt that the device control was shared with me The Likert data obtained from the acceptance and usability questionnaires were aimed at assessing the participants' perceptions of the interaction with the AGoRA Walker.
Consequently, resembling survey answers were obtained under each control mode with major positive distributions. These results might suggest safe, natural and intuitive interactions perceived by the volunteers who participated in the study. Moreover, some participants stated additional comments regarding to the navigation control mode. Specifically, the volunteers suggested that at specific trajectory points the device stopped, in such a way that the path following task was not very comfortable. These impressions occurred at several trajectory goals, since the navigation system was configured to reach them at specific orientations. To analyze the participants' behavior perception under each control mode, the responses from Questions Q8-Q10 were statistically analyzed. As found in  [68, 69] , Mann-Whitney-Wilcoxon (MWW) tests have shown optimal results comparing Likert data for small sample sizes MWW.
Specifically, data were collected from 21 trials divided into seven sessions, where all participant interacted with each control mode. Regarding the user control mode, a squared-shaped trajectory was proposed to be followed by each participant. The achieved trajectories for all the volunteers, as well as the admittance responses for a specific subject were presented. According to the participants' performance under this control mode, preferences for less steeped curves were found. Concretely, the participants did not strictly execute 90-degree turns at trajectory corners. Such behavior is mainly supported by the not aligned axes of rotation of the walker and the users. Moreover, ignoring path corners allowed the participants to ensure balance and stability during walking. The validation trials were also aimed at assessing the performance of the navigation system in guidance tasks, as well as at evaluating the performance of the navigation and people detection systems working together.
Acknowledgments: This work was supported by  Colombian Department Colciencias  (Grant  801-2017 ) and the  Colombian School of Engineering Julio Garavito Funds. The authors also wish to acknowledge the support from project  CAMPUS  ( Connected Automated Mobilty Platform for Urban Sustainability ) sponsored by  Programme d'Investissements d'Avenir (PIA)  of the  French Agence de l'Environnement et de la Maîtrise de l'Énergie (ADEME).
Sample size Sample size calculations were based on an a priori power analysis based on a previous study carried out on similar primary outcomes in the workplace  [37, 66]. This study has reported a positive effect of the PA intervention on the emotional exhaustion component of burnout, with a small effect size (η 2 = 0. 03; f = 0. 176). According to this result, we conducted an analysis with G*Power software  [70]  examining the evolution of burnout and vigor depending on the conditions as inter-individual factors, with an moderate effect size of d = 0. 35, a statistical power of 80%, a threshold of significance at p < 0. 025 considering our two primary outcomes, a correlation of. 5 across repeated measures, and a potential dropout rate of 25% for a 10-week program with 4 groups. The results of this analysis recommend recruiting a minimum of 140 participants, 35 per group.
Randomization and blinding Participants will be randomly assigned to one of the four conditions. A laboratory engineer will carry out the randomization once all participants are included, using the random function of Excel® software. Then, a second randomization will be done with the next 60 participants. A laboratory engineer will carry out the randomization, using the random function of Excel® software. In order to reduce bias, participants in PA Fig. 1  Protocol flowchart conditions will not know their motivational style allocation (i. e. PA-TS or PA-NSS), and the instructor of each PA condition will not know the existence of the other condition. Finally, research assistants collecting data will be blinded to the treatment allocation.
Primary outcomes Burnout at work Burnout will be assessed with the French version  [74]  of the SMBM  [5]. The scale consists of 14 items divided into three subscales: physical fatigue (e. g. , "I feel physically drained"), cognitive weariness (e. g. , "I feel I'm not thinking clearly"), and emotional exhaustion (e. g. , "I feel I am not capable of investing emotionally in coworkers and customers"). Scores are rated using a seven-point Likert scale (1 = never; 7 = always). In prior research, the English  [22, 75, 76]  and French  [74]  version of the SMBM has proved to be a valid and reliable instrument to assess burnout. Using data from the baseline measurements, we will select the three most representative items according to their loading on each of the three factors to assess weekly burnout.
Vigor at work Vigor will be measured with the French version  [77]  of the SMVM  [7]. The scale consists of 12 items divided into three subscales: physical strength (e. g. , "I feel I have physical strength"), cognitive liveliness (e. g. , "I feel able to be creative"), and emotional energy (e. g. , "I feel able to show warmth to others"). Scores are rated using a seven-point Likert scale (1 = never; 7 = always). In prior research, the English  [78] [79] [80]  and French  [77]  version of the SMVM has proved to be a valid and reliable instrument to assess vigor at work. Using data from the baseline measurements, we will select the three most representative items according to their loading on each of the three factors to assess weekly vigor.
Psychological recovery experiences To accurately identify the psychological experiences that may underlie the recovery process, we will use a French adapted version of the Recovery Experience Questionnaire (REQ;  [55] ). to learn new things"). In order to assess the experience of relatedness  [58] , the REQ items will be completed with a French adapted version of the relatedness subscale of the Balanced Measure of Psychological Needs  [85]  (4 items, e. g. ,  […]  to feel close and connected with one or more people who participated with you in these activities). The answers will be provided on a Likert-type scale ranging from (1) strongly disagree to (7) strongly agree. Factorial validity and reliability will be tested in a pilot study. Using data from the baseline measurements, we will select the most representative items of each of these five dimensions according to their loading on each of the five factors to assess weekly psychological recovery experiences (see below).
Following the stem "In the past month, in my work I generally felt. ", participants will be asked to respond to 12 items assessing employee competence (4 items, e. g. , "I felt competent (vs. incompetent) at my job"), autonomy (4 items, e. g. , "I felt I was free to make my own decisions (vs. I had to follow the decisions that were made for me)") and colleague relatedness (4 items, e. g. , "I felt supported (vs. unsupported by my colleagues") satisfaction and frustration. This scale demonstrated satisfactory factorial validity and reliability  [87]. Using data from the baseline measurements, we will select the three most representative items according to their loading on each of the three factors to assess psychological recovery experiences (see below).
PA intensity during sessions To check that the two PA interventions produce more physical effort than the Theatre intervention, we will assess participants' objective and their perceived effort. First, participants in the three intervention groups will be asked to wear a tri-axial accelerometer (ActiGraph LLC, Pensacola, FL, USA; ActiGraph GT3x) on the waist during a session in the sixth week of the intervention. The devices will be initialized with 30 s epochs and the data will be analyzed with Freedson's algorithm  [89]. Moderate to vigorous PA and energy expenditure will be calculated for each participant. Moreover, the perceived effort during the sessions will be assessed weekly with one single-item: "How intense was the effort you made during the last session?" ("Very slightly intense" vs.
In contrast, on a global scale the risk of nutritional abnormalities in individual regions and countries is likely to be affected by a range of medical and non-medical factors including the patient case-mix regarding age, underlying disease and co-morbidities, national economic strength and healthcare expenditure, cultural acceptability of dietary and feeding prescriptions, availability of special formula diets and enteral feeding equipment, and differences in local, national or regional nutritional recommendations  4. The International Pediatric Peritoneal Dialysis Network (IPPN) has been collecting comprehensive clinical and laboratory data in a standardized manner from children undergoing CPD worldwide since 2007. Since these data include detailed anthropometric measures, feeding prescriptions and outcome measures, it provides an opportunity to address the global demographics of nutritional abnormalities in children receiving CPD.
Methods Data collection. The IPPN Registry was established in 2007 and currently collects comprehensive clinical and laboratory information from children undergoing CPD at 95 pediatric dialysis centers in 37 countries around the globe. Patient status is updated every 6 months via an Internet-based web platform (www. pedpd. org). The complete list of data items collected has been published previously  2, 4. Data is automatically checked for plausibility and completeness. Data protection is ensured by pseudonymized data input. The study is performed in accordance with the relevant medical association's professional codes of conduct with the Declaration of Helsinki from 2008. Approval for the registry project was obtained from The Children's Mercy Hospital Pediatric Institutional Review Board, Kansas City, USA and local Institutional Review Boards or ethical committees.
e. -2 to 1. 036 SDS), overweight (>85 th -95 th percentile, i. e. >1. 036 to 1. 645 SDS), and obesity (>95 th percentile, i. e. >1. 645 SDS). The Schwartz bedside formula was used to estimate GFR at initiation of CPD  8. statistics. Data collection was complete for all observations except residual urine output (7. 6% missing data), daily ultrafiltration rate (5. 2%), eGFR (1. 2%), total PD fluid turnover and dialytic glucose exposure (0. 8%), PD modality (0. 5%), serum bicarbonate (0. 3%), serum albumin (0. 2%), and estimated dry weight (0. 2%). Multiple imputation by chained equations was conducted to replace these missing values  9. All analyses were performed using the imputed dataset. Additionally, sensitivity analyses were performed using only cases with complete data sets. ANOVA or Kruskal-Wallis tests were conducted to compare differences between BMI groups.
A stepwise variable selection procedure was applied to identify the relevant covariates for the cross sectional model as well as for the longitudinal model, using p = 0. 2 as a cutoff criterion for model entry. Kaplan-Meier analysis with log-rank testing was used to assess differences in patient survival. Cox proportional hazard modeling with time dependent covariates and interaction term was applied to identify risk factors of death on dialysis. Data were analyzed using SAS, version 9. 3 (SAS Institute, Inc. , Cary, NC), and R, version 3. 1. 1  10. Of the 1,001 patients, 702 (70%) patients had at least two BMI records available. Median follow-up time was 14. 5 (IQR 17. 8) months. Altogether, the data set contained 2,931 follow-up entries.
Discussion At variance with historical epidemiological studies on nutrition in children with CKD, which focused mainly on uremic underweight, this study highlights a changing trend of the nutritional status in pediatric end stage kidney disease (ESKD). Both underweight and overweight/obesity were common. Using the 2. 5 th and the 85 th BMI percentiles as cutoffs for underweight and overweight/obesity respectively, 28. 6% of patients receiving CPD, as compared to an expected 17. 5%, exhibited an abnormal body composition. A relatively low rate of underweight, but an increased prevalence of overweight and obesity was recently also observed in North American CKD cohorts  11, 12  and in European children undergoing dialysis  13. While it is tempting to merely attribute this trend to the global childhood obesity epidemic, the comprehensive and worldwide   data collection in the IPPN Registry allowed us to dissect in detail and on a global scale, the impact of macroeconomic factors, patient characteristics, and pediatric CKD and dialysis management practices on nutritional outcome.
All children and adolescents enrolled in the IPPN registry with initiation of CPD between March 2007 and December 2014 were analyzed for this study. Five patients with syndromic and metabolic disorders associated with intrinsic abnormalities of growth and body composition were excluded from the analysis. The final dataset comprised a total of 1,001 incident patients from 85 nephrology centers in 35 countries. Children originated from Western Europe (n = 300), Central Europe (n = 120), Turkey (n = 105), the Middle East (n = 15), China and Hong Kong (n = 77), Korea (n = 24), India and South East Asia (n = 30), New Zealand (n = 18), USA (n = 97), Canada (n = 13) and Latin America (n = 202). One or more comorbidities were reported in 369 patients (35. 6%); these included mainly defined syndromic disorders (n = 107), impaired cognitive development (n = 119), cardiac (n = 130) and pulmonary abnormalities (n = 52).
study population. All children and adolescents enrolled in the IPPN registry with initiation of CPD between March 2007 and December 2014 were analyzed for this study. Five patients with syndromic and metabolic disorders associated with intrinsic abnormalities of growth and body composition were excluded from the analysis. The final dataset comprised a total of 1,001 incident patients from 85 nephrology centers in 35 countries. Children originated from Western Europe (n = 300), Central Europe (n = 120), Turkey (n = 105), the Middle East (n = 15), China and Hong Kong (n = 77), Korea (n = 24), India and South East Asia (n = 30), New Zealand (n = 18), USA (n = 97), Canada (n = 13) and Latin America (n = 202). One or more comorbidities were reported in 369 patients (35. 6%); these included mainly defined syndromic disorders (n = 107), impaired cognitive development (n = 119), cardiac (n = 130) and pulmonary abnormalities (n = 52).
To summarize recent research and select the best papers published in 2018 in the field of computerized clinical decision support for the Decision Support section of the International Medical Informatics Association (IMIA) yearbook. Methods: A literature review was performed by searching two bibliographic databases for papers referring to clinical decision support systems (CDSSs). The aim was to identify a list of candidate best papers from the retrieved bibliographic records, which were then peer-reviewed by external reviewers. A consensus meeting of the IMIA editorial team finally selected the best papers on the basis of all reviews and the section editors' evaluation. Results: Among 1,148 retrieved articles, 15 best paper candidates were selected, the review of which resulted in the selection of four best papers.
Paper Selection Method A comprehensive literature search on topics related to CDSSs and CPOE systems was performed to identify candidate best papers following the protocol previously described by Lamy et al. [2]. Two bibliographic databases were used: first, the PubMed/Medline database (from NCBI, National Center for Biotechnology Information) which is dedicated to the biomedical domain, and the Web of Science® (WoS, Clarivate Analytics) which has a broader scope. Both databases were searched with similar queries targeting journal papers published in 2018, written in English language, and on the aforementioned topics. The adopted strategy, which was implemented for the last 2 years  [3] [4]  and replicated this year, was based on four exclusive queries yielding four disjoint citation subsets: Q Pub_plain , based on a plain-text search in PubMed titles and abstracts using keywords; Q Pub_indexed , based on the PubMed indexing scheme using MeSH terms and exclusive of the previous set; Q WoS_restricted , based on a WoS search on non PubMed-indexed papers restricted to the two subject areas "Medical Informatics" and "Health Care Sciences & Services" and, finally, Q WoS_filtered , based on other non-PubMed-indexed papers filtered by non-relevant subject areas.
Especially the last part constitutes an important contribution in the domain with an explicit focus on explainability, which constitutes currently a central issue for the adoption of AI in medicine. Data from relevant databases from the Stanford Cancer Center were employed in the study that demonstrated both high accuracy and explainability, and showcased a promising decision support tool to personalize metastatic cancer treatment. In the second paper, Ray et al. [6]  take note that automated CDSSs have become integral components of EMRs and that any unnoticed malfunction of them might impair the quality or safety of care. The goal of this research was to use and compare anomaly detection models to identify potential CDS malfunctions. Authors focused on three types of anomalies that occur in time and which can be detected by statistical models applied on time series.
The work extends prior works targeting the prediction of complex disease trajectories by exploiting rich unstructured clinical data, rather than structured (e. g. lab values, demographics, etc. ), or relatively simplistic information extracted from unstructured narratives (e. g. bag of words and term frequency-inverse document frequency). In technical terms, PPES-Met combines semantic data mining and neural embedding for creating a context-aware dense vector representation of the clinical notes, which was used as input to the prognostic model for estimating in turn the probability of short-term life expectancy (>3 months). The model was trained on a large dataset (10,293 patients) and validated on a separated dataset (1,818 patients), exhibiting an AUC (area under the ROC curve) value of 0.
Methods We included all randomized controlled trials assessing the efficacy of PT on balance and postural control in adult patients after stroke without language restriction. Medline, Embase/ Scopus, Cochrane Central Register of Controlled Trials, PEDro, Pascal, and Francis databases were searched until January 2019. Primary outcomes were balance (Berg Balance scale and Postural Assessment Scale for Stroke) and postural control with postural deviation or stability measurement in sitting or standing static evaluation. A pair of independent.