dataesr/scientific-paragraphs-categorization huggingface dataset:
Measurement of  entry into care is generally robust because a CD4 count and/or a viral load is almost associated with first clinic visit. However, the identification of individuals exiting care is delayed for individuals matched only to NHLS database. In addition, considering our matching algorithm, the probability that a trial participant was wrongly associated with a record in ACCDB or NHLS (type-I error) is relatively small. However, some patients who resided in the trial area could not be matched (type-II error), for reasons such as data entry errors or use of different names in different settings  [25]. Third, we did not have any data on individuals receiving HIV care in the private sector or in primary care clinics located outside the Hlabisa sub-district, potentially resulting in an underestimation of population progression through the HIV care cascade.
Methods: Data will be collected via systematic literature reviews, pan-European surveys, and focus groups with service providers, users and carers, and members of youth advocacy and mental health advocacy groups. A prospective cohort study will be conducted with a nested cluster randomised controlled trial in eight European Union (EU) countries (Belgium, Croatia, France, Germany, Ireland, Italy, Netherlands, UK) involving over 1000 CAMHS users, their carers, and clinicians. Discussion: Improving transitional care can facilitate not only recovery but also mental health promotion and mental illness prevention for young people. MILESTONE will provide evidence of the organisational structures and processes influencing transition at the service interface across differing healthcare models in Europe and longitudinal outcomes for young people leaving CAMHS, solutions for improving transitional care in a cost-effective manner, training modules for clinicians, and commissioning and policy guidelines for service providers and policy makers.
Methods/design WP 1: Mapping the CAMHS-AMHS interface across European mental health services The aim of this work package is to analyse the clinical, organisational and legal aspects of CAMHS-AMHS interface at national and regional levels across all 28 EU states. The mapping exercise will help identify transition policies and models in different EU healthcare and social settings, and clarify how and by whom decisions about transition are made within each national mental health system. A futher aim is to examine transition in other health areas and social services in the different European countries. A list of European governmental and non-governmental associations able to provide data on CAMHS/AMHS interface and transition was collated. Two measures were developed in English for completion online via a dedicated web domain by country expertschild psychiatrists and representatives of national childpsychiatry associationswithin each of the 28 EU member states: 1) the European CAMHS Mapping Questionnaire (ECM-Q), which was based on the European Service Mapping Schedule  [64]  and integrated many of the domains used WHO CAMHS Atlas  [65] ; and 2) the Standardized Assessment Tool for Mental Health Transition (SATMEHT), which was developed from an instrument used in the TRACK study  [29]  and other questionnaires  [34, 43, 66, 67].
For the ECM-Q, the primary aim was to characterise child and adolescent mental health care provision across countries (e. g. number of CAMHS per 100,000 young people), including collaboration with other services, activity data and funding sources. For the SATMEHT, the primary aim was to characterise the transition process and services configuration per country (e. g. proportion of young people attending CAMHS needing a transition to AMHS), including the availability of policies regulating the CAMHS-AMHS interface and the degree of stakeholders' involvement. More detailed methodology and findings from the ECM-Q and SATMEHT have been reported elsewhere  [68, 69].
The TRAM forms the basis of 'managed transition' , as described below. TRAM and TROM were developed using qualitative and quantitative methods following the US FDA Guidance for Patient-reported Outcome Measures  [72]. Literature was critically reviewed for item/concept identification, and three waves of focus groups on item/concept elicitation were carried out involving young people with experience of CAMHS, their parents/carers and mental health professionals at two mental health NHS trusts in the UK. Based on the analysis of the data thus obtained, items were formed into scales and subjected to user testing so that problems with the format and completion issues could be identified. The final versions were translated into French, Italian, German, Dutch and Croatian. Participant-optimised web-based versions were developed using HealthTracker™ (https://www.
In the intervention arm clusters, clinicians are provided with TRAM Score summary reports for the young people participating in the study. Clinicians are advised to discuss the report with the young person and parent/carer, include relevant points in a transitional care plan, and to attach it to the referral letter, if further care is indicated. Young people in the control clusters receive treatment as usual, which depends on service and may or may not include transition planning. The cohort study and cRCT share recruitment and data collection. Detailed information about eligibility criteria and methodology have been described elsewhere  [76]. The primary outcome for the trial is mental health and social functioning status as measured by the Health of the Nation Outcome Scale for Child and Adolescents (HoNOSCA) at 15 months after baseline  [77] [78] [79].
The measure is completed by a trained MILE-STONE research assistant by interviewing the young person and taking into account all other available sources of information (parent/carer, relevant clinician and the medical records) to ensure accuracy of data  [80]. The secondary outcomes are detailed in the study protocol, and include transition outcomes (TROM), self-reported and parent/carer reported psychopathology, emotional and behaviour problems of the service user (reported by both parent/carer and the young person him/ herself ), illness severity, quality of life, independent behaviour, illness perception, barriers to care, transition experience and readiness, and adult functioning  [76]. Data collection is the same in the intervention and control clusters. Outcomes are measured 9 months (T2), 15 months (T3) and 24 months (T4) after baseline (T1).
The focus groups with young people and parents/ carers who have participated in the MILESTONE study will be conducted during the last assessment time point of the MILESTONE study in at least the three above countries. The aim will be to explore the actual experiences of the young people regarding services at the transition boundary, but also their views regarding the ethical aspects of service provision. Separate focus groups with a maximum of five participants will be held for young people and parent/carers, with a total of approximately 20 young people and 10 parent/carers taking part per country. Data from the separate arms of the ethics work package will be integrated during the analysis phase, and linked up with findings from the MILESTONE study. WP 8: Training of professionals for improving transitional care across the EU Many of the profound clinical, conceptual and ideological differences between child and adult mental health service models that contribute to transitional problems are related to psychiatry and other associated professional training.
Acknowledgements We are very grateful for the CAMHS and AMHS services and research teams who are collaborating in the MILESTONE study in the eight European countries. We also extend thanks to all the participating service users and their parents/carers. We are also grateful for the members of the  MILESTONE Scientific Clinical and Ethical Advisory Board (SCEAB) :  Norman Sartorius ,  Pat McGorry ,  Maryann Davis , and  Adriana Mihai. We would also like to thank members of the wider  MILESTONE Consortium  for their contribution. We extend a special thanks to  Andrea Wohner , our project manager based at concentris research management gmbh,  Fürstenfeldbruck, Germany , for excellent project management and delivery.
Acknowledgments This work was supported by  Ukrainian Medical Stomatological Academy ,  Poltava, Ukraine ("Comprehensive study of the pathogenetic role of the subpopulation of macrophages M1  and  M2  in the development of COPD for the reasoning and substantiation of personalized therapy based on body weight", Fundamental research project, State registration No. 0117U005252 ,  Ukrainian Ministry of Health Public Service ) and by  University of Toulouse, France ;  Institute of Metabolic and Cardiovascular Diseases, Toulouse, France , and ERASMUS + project.
The coordinating centres will also manage the raw data that will be obtained from the collaborating centres and provide a "clean" dataset to the executive committee. • We aim to incorporate at least one collaborating centre from each of the 23 districts of the state. Collaborating centres will carry out the PERFORMANCE study as per the instructions of the executive committee and the coordinating centres, adhere to the coordinating centres throughout the course of the study, and provide "raw" datasets to the coordinating centres for quality check and management. The collaborating centres are required to obtain the necessary ethical clearance from their respective human research ethics committee and other documents as applicable. The study will be performed in three habitation settings (rural, suburban and urban) across multiple locations in West Bengal.
, 2014). To assist the participants in following ankle strategy during the balance task, we designed a heel lift detection (HLD) module interfaced wirelessly with the VR-based task platform. The objectives of our present study are threefold: (i) develop a CoM-assisted balance training platform having a VR-based system (Virtual CoMBaT) augmented with Kinect to offer balance rehabilitation exercises in an individualized and adaptive manner based on one's performance capabilities and (ii) develop a HLD module to assist in maintaining ankle strategy (iii) conduct a usability study with the Virtual CoMBaT system, with an aim to understand the users' perspective on the usage of the system and implications of such a system on task performance of individuals having balance disorders. Additionally, we plan to use one's performance indicators derived from the usability study with the Virtual CoMBaT system as possible metrices to quantify participants' initial (residual) weight shifting ability.
Design and Control of VR-based Balance Rehabilitation Tasks In this study, the VR-based tasks were developed to (i) leverage one's weight shifting ability in different directions while following ankle strategy and (ii) quantitatively estimate one's balance capability during the weight-shifting task. We used Vizard software toolkit (from Worldviz Llc. ) to design VR environments. We created a database of 30 unique combinations of VR-based environments (such as, road, playground, river, etc. ) and virtual objects (such as, car, ball, fish, etc. ) related to stimuli that one often might come across in daily living and entertainment. The tasks required participants to shift their weight (by varying CoM position) in predefined directions, namely, North (N), East (E), West (W), North East (NE), and North West (NW) while maintaining stability that is moving within their limit of stability by following ankle strategy (without lifting their heel from the ground surface).
Performance Evaluation Module We wanted to evaluate and understand a participant's ability to shift weight in different directions while interacting with the VRbased tasks presented by the Virtual CoMBaT system. The Virtual CoMBaT system computed the performance scores for the tasks of DL1 and DL2 in each of the five directions based on (i) P S1 : length of trajectory (T L ) of one's CoM before reaching the Target position, (ii) P S2 : deviation of one's CoM from the instructed straight path between Central Hold and Target positions, (iii) P S3 : measure of one's ability to hold his weight at the Target position for hold time (H T ) of 1 s, and (iv) P S4 : penalizing factor to discourage one's heel lifting  (Verma et al. , 2017). The first metric (P S1 ) evaluated the participant's CoM trajectory for body sway while shifting weight by using Eq.
Task Switching Module The Virtual CoMBaT system switched tasks presented to the participants while being adaptive to their individualized performance score in a task. The task switching algorithm had two switching conditions (C1 and C2; Table  1 ). We were interested to see one's trajectory of improvement in performance score in each difficulty level. If a participant was interacting with a task of DL1, the Virtual CoMBaT looked for whether there was (i) improvement [(Pf [CT] -Pf [PT]) > 0; P f = Percentage performance score, CT = current task, and PT = previous task] in his/her task performance through repeated exposure to tasks of DL1 (Table  1  and Figure 6 ) and (ii) his/her performance in any of the task trials of DL1 was "Adequate" (Condition "C1"). Again, even after performing adequately in one of the task trials of DL1, it might so happen that due to repeated exposures to the tasks of same challenge level (DL1), the participant might lose interest.
Then the participant was asked to make a series of static postures, namely, lean forward and lift one leg at a time away from the body (Figure  7B ). Once the SESC parameters were identified, we asked participants to repeat the same static body posture once again and recorded the measured CoP data from WiiBB and estimated CoM data using SESC method to compare the variation in CoP and CoM movement (CoP-CoM comparison stage). This stage was followed by the Threshold Estimation stage (see Experimental Setup). Before participating in this stage, the participant was asked to sit on a chair and wear a pair of shoes with the help of the experimenter, who in turn mounted the HLD module (see Monitoring of Ankle Strategy during Task Execution) on the shoe of the affected leg (Figure  4B ). Also, the experimenter removed the WiiBB from the Base Location and asked the participant to stand on the ground at the Base Location (Figure  7C ) while facing the Kinect sensor.
Statistical Analysis While the participants interacted with our VR-based tasks during the Task Execution stage, Virtual CoMBaT computed the participant's performance (P S x ; see Performance Evaluation Module) corresponding to each direction in the tasks offered in each difficulty level. We were interested to understand whether the repeated exposure to tasks in each difficulty level contributed to any statistical improvement in one's performance. Before performing the statistical test of the hypothesis, we performed Shapiro-Wilk test of normality  (Shapiro and Wilk, 1956)  on the participant's performance score in different directions of tasks of DL1 and DL2. For the sample size of 12, we computed W value and found with significance level of p-value = 0. 05 that the data was not normally distributed Subsequently, we opted for non-parametric statistical hypothesis testing, namely, Wilcoxon signed rank test  (Gibbons and Chakraborti, 2011)  to determine whether the improvement (if any) in the participants' performance score from their task in the First Attempt to task (within each difficulty level) in which they achieved Best score (Best Case henceforth) in each direction (such as.
RESULT In the current work, we have designed a Virtual CoMBaT system. Our aim was to design a usability study to understand the users' perspective on the usage of Virtual CoMBaT system. In the section below, we present our findings on the participants' views on the usage of our system. Additionally, since, Virtual CoMBaT was designed with an ultimate aim to serve as a rehabilitation tool, we analyzed the data of our usability study to see whether this system can also contribute to at least some improvement in performance even over a limited exposure duration. Thus, when the participants interacted with the Virtual CoMBaT system, we monitored their weight-shift capability while they followed ankle strategy. To ensure that the ankle strategy was followed, we have designed HLD module. Here, we will present our observation on the implication of the HLD assisted Virtual CoMBaT system on the participants' weight-shifting status along with improved usage of ankle strategy.
Virtual CoMBaT System Used for Quantification of Balance Ability Based on Weight-Shifting Capability We wanted to see whether Virtual CoMBaT system can quantify one's ability to shift weight in the five different directions using the task performance measure. We analyzed one's NEP (see Performance Evaluation Module) using estimated CoM. Figure  8  shows each participant's NEP for all the five directions, their BBS scores, and hemiplegic side. From Figure  8 , we see that the participants' NEP was lesser in a direction(s) that required weight-shifting on their affected side for maneuvering the VR obj in that direction compared to the other directions. For example, participant S1 was left hemiplegic and thereby had restricted weight-shifting capability on the left side. This caused him to score less in the VR-based tasks while shifting his weight to maneuver the VR obj toward the W, NW, and N directions than that in the other directions.
Again, we wanted to understand if there existed any correlation of the quantitative clinical measure with one's task performance while participating in the study with Virtual CoMBaT. As we had the participants' BBS data, we wanted to use this data as the quantitative clinical score. Since, (i) our participants were all hemiplegic and had direction-specific performance score (N, E, W, NE, and NW) while participating in the usability study and (ii) BBS score is not a measure of one's direction-specific weight shifting ability, we decided to choose that measure out of the 14 measures (each scaled 1-4) of BBS score that can provide some direction-specific information. Specifically, we chose the score for "Reaching Forward with Outstretched Arm while Standing" task of BBS (when the participant needs to shift weight toward the front (North)) and tried to understand the correlation of this quantitative clinical score with participants' task performance score toward the North direction (that is when the participant shifted weight toward N direction) in the First Attempt of DL1 task.
Effect of Virtual CoMBaT System on Following of Ankle Strategy While interacting with the Virtual CoMBaT system, we encouraged the participants to follow ankle strategy. Our HLD module (see Monitoring of Ankle Strategy during Task Execution) was used to record the participant's heel lift during Task Execution stage. While measuring one's heel lift, we recorded the duration for which a participant lifted his/her heel (Not Following ankle strategy). Subsequently, for each task trial, we computed the duration of one's heel lift (if any) as a percentage of the total time taken to execute that task trial. Here, we present our findings on the% heel lift time (out of the total time taken) for each of the First Attempt and Best Case tasks for both DL1 and DL2 tasks. The aim was to understand whether repeated exposure to our Virtual CoMBaT system facilitated the participants to acquire improved weight-shifting capability while reducing the duration of heel lift.
Specifically, for the sake of simplicity and lack of available database on stroke patients, we tried to decide threshold measure such as, D TH in Eq. 4 based on pilot trials with agematched healthy participants. The choice of such thresholds might have implications on the performance score of the stroke group for whom the thresholds might be different. However, this was an initial approximation. In future, we plan to extend our study while modifying parameters such as, threshold measures while computing the performance scores by using the database that we have developed in our present study with poststroke patients.
Statistical analysis The demographic and clinical characteristics were compared using unpaired t-tests for continuous variables (presented as the mean ± SD) or the Mann-Whitney U-test for nonparametric variables (presented as the median along with range). Categorical variables were compared using Fisher's exact test and are presented as a percentage (%). Because plasma concentrations of sTLR2 were not distributed normally, a non-parametric test (Mann-Whitney U-test) was used for analyses. Spearman partial correlation analysis was used to adjust data for the CD4 count. Differences were considered statistically significant at p< 0. 05 for 2-sided test. Statistical analyses were performed using either GraphPad Prism 5. 03 for Mac OSX (GraphPad Software, San Diego, CA, USA).
Demographic data Overall a total of 283 mothers were included from 2012 to 2015 in the present study. 73. 4% (208/283) were HIV infected and 26. 5% (75/283) were HIV non infected (controls). A percentage of 63. 5% (132/208) mothers were HIV infected who have followed the PMTCT protocol with HIV non infected babies (NTWP). That of 9% (19/208) were HIV infected who have followed the PMTCT protocol with HIV infected babies (TWP). Thirty-four mothers (16. 5%) were HIV infected who have not followed the PMTCT protocol with HIV non infected babies (NTWDP). Finally 11% (23/208) mothers were HIV infected who have not followed the PMTCT protocol with HIV infected babies (TWDP). A total of 42 (18. 7%) children were HIV infected. The ARV drugs taken by mother in the study vary from monoprophylaxis (sdNVP) to the highly active antiretroviral therapy (with option B+ as the mostly used protocole).
Reads were classified into 909 OTUs. OTUs were assigned using the silva123 16S database. Multi-affiliation was manually checked: all sequences with a low pintail quality in the silva database were removed; a single affiliation was accepted when corresponding to more than 90% of all OTU sequences. The phylogenetic tree was constructed using Phy_tree. After multi-affiliation management, the resulting OTU table (unrarefied raw data) was used for subsequent statistical analyses. Data were filtered to keep only those that contributed to at least 0. 1% of the microbial community in at least 5% of the samples. Differences in phyla, genera and OTUs, were assessed with pairwise comparisons, after aggregation at the desired taxonomic rank (phyloseq' tax_glom function) by using EdgeR package (Bioconductor)  65  , correcting for a sex effect.
1 H NMR spectra were acquired at 300 K using the Carr-Purcell-Meiboom-Gill (CPMG) spin-echo pulse sequence with presaturation, with a total spin-echo delay of 240 ms to attenuate broad signals from proteins and lipoproteins for faecal samples. A total of 512 scans were collected, using a spectral width of 20 ppm and a relaxation delay of 2 s. All spectra were Fourier transformed, manually phased, baseline corrected and referenced to TMSP using Bruker TopSpin 3. 5 software (Bruker, GMBH, Karlsruhe, Germany). The spectral assignment was based on matching data to reference spectra in a home-made reference database. Data reduction and multivariate statistical analysis. Data were reduced using the AMIX software (version 3. 9. 11, Bruker, Rheinstetten, Germany) to integrate 0. 01 ppm regions corresponding to the δ 9-0.