LLukas22/scidocs huggingface dataset:
Implementation of a Highly Reliable Hybrid Electric Scooter Drive

In contrast to hybrid electric cars (HECs), the issues concerning cost, volume, and reliability are even more rigorous when developing hybrid electric scooters (HESs). Therefore, the drive topology and control strategy used in HEC cannot be applied to HES directly. This paper presents a single-stage bidirectional dc/ac converter based on a general full-bridge inverter. The converter is designed for a low-voltage brushless dc motor/alternator (BLDCM/A) used in HESs, in which the additional bulky inductor and power switches are eliminated in the proposed design. In order to increase the reliability of the commutation process, a cost-effective sensorless control scheme for the motor and alternator commutation is developed. The commutation signals are extracted directly from the average terminal voltages, in which the motor neutral voltage, multistage analog Alters, analog-to-digital converters, and the complex digital phase-shift (delay) circuits are eliminated. In addition, instead of using the complex flux- weakening control technique, the winding-changeover technique is exploited to extend the range of the operating speed. With attractive features, such as low cost and ease of implementation, the proposed approach is particularly suitable for electric bikes, electric scooters, HESs, etc. Theoretical analysis and several experiments are conducted to justify the effectiveness of the proposed method.
Comprehensive intensive therapy for Chinese gestational diabetes benefits both newborns and mothers.

OBJECTIVE
This study identified the impact of intensive therapy on neonatal outcomes in women with gestational diabetes mellitus (GDM) and determined the effects on the postpartum metabolic status of the mothers.


RESEARCH DESIGN AND METHODS
In total, 127 pregnant women with GDM were randomly selected to receive an intensive treatment regimen, which included one-to-one education, lifestyle intervention, scheduled clinic visits, strict glucose control, and frequent glucose self-monitoring. Meanwhile, 148 age-matched pregnant women with GDM were selected as controls and given the standard treatment regimen. Pregnancy outcomes including parameters related to the GDM mothers and to their neonates were comparatively analyzed between the two treatment groups. GDM patient follow-up (range, 1-3 years after delivery) included an oral glucose tolerance test and measurements of lipid concentration and insulin secretion. The insulinogenic index (ΔInsulin(30 min)/ΔBlood glucose(30 min)) and homeostasis model assessment index of β-cell function and insulin resistance were calculated. The patients' demographic and anthropometric data were also recorded for comparative analysis.


RESULTS
Compared with GDM patients receiving standard treatment, GDM patients receiving intensive treatment had lower instances of premature delivery (2.4% vs. 8.3%, P<0.05) and neonatal care unit admission (21.3% vs. 33.3%, P<0.05) and lower neonatal birth weight (3.26±0.53 vs. 3.45±0.55 kg, P<0.0001). At follow-up, GDM patients from the intensive treatment group had a smaller waist circumference (75.83±3.11 vs. 78.34±4.20 cm, P<0.01), lower 30-min glucose levels after a 75-g glucose load (8.26±1.85 vs. 9.46±2.74 mmol/L, P<0.05), and higher high-density lipoprotein levels (1.30±0.24 vs. 1.18±0.23 mmol/L, P<0.05).


CONCLUSIONS
The intensive GDM treatment regimen led to healthier outcomes for the women, the neonates, and the birth event and was associated with better maternal metabolic situations in the months and years after delivery.
Interaction of physical activity, mental health, health locus of control and quality of life : a study on university students in Pakistan

Bazila Akbar Kahn, 2013. Interaction of Physical Activity, Mental Health, Health Locus of Control and Quality of Life: A Study on University Students in Pakistan. Department of Sport Sciences. University of Jyväskylä. Master’s Thesis of Sport and Exercise Psychology. 66 pages Physical activity involvement is considered as beneficial both for physiological and psychological health. In Pakistani society an elevated level of physical inactivity has been identified lately. Nevertheless, studies examining the association between physical activity and psychological health are limited to the young population of university students in Pakistan. University students are considered to be at a risk stage due to academic stress and physiological changes Therefore, the purpose of this study was to explore the associations between physical activity, quality of life and psychological health related variables to university students in Pakistan. Participants (N=378) of the current study were from seven universities in Pakistan (265 female, 112 males). General Health Questionnaire, SF-36 quality of life matrix, multidimensional health locus of control and international physical activity questionnaire were administered. Results reveal a large number of students as physically inactive (37.6%). t-Test revealed male students were more active and having a better quality of life in comparison to the female. The high prevalence of psychological distress (25%) has also been identified by using correlation. Results indicated a linear positive relationship of physical activity with mental component summary and a negative association with psychological distress. Conversely, psychological distress was negatively related overall health related quality of life and PA. Results also demonstrated that students with a better internal locus of control were discovered to be more physically active. Findings were discussed in comparison with studies from other countries e.g. US, UK, Norway, Poland, Turkey and Australia However, the results suggest the replication of the study with a larger sample size. Additionally, it is also imperative to explore the barriers to PA among the student population in Pakistan. Keys words: Physical activity, mental health, health locus of control, psychological distress, university students in Pakistan.
Combination immunotherapy of B-cell non-Hodgkin's lymphoma with rituximab and interleukin-2: a preclinical and phase I study.

PURPOSE
Cytokine-induced modulation of innate immunity is being explored to enhance the activity of monoclonal antibodies. Severe combined immunodeficient (SCID) mice engrafted with peripheral blood leukocytes (PBLs) from Epstein Barr virus-seropositive donors develop human B-cell non-Hodgkin's lymphomas [B-NHLs (hu-PBL-SCID mouse model)]. We used this hu-PBL-SCID mouse model to study the synergism between interleukin (IL)-2 and rituximab. We also conducted a phase I trial of IL-2 and rituximab in relapsed B-NHL to study whether expansion of natural killer (NK) cells and enhanced cellular cytotoxicity could be safely accomplished in vivo.


EXPERIMENTAL DESIGN
Hu-PBL-SCID mice were treated with various schedules of rituximab and IL-2, with survival as the end point. Patients with relapsed B-NHL received rituximab (375 mg/m2 weekly x 4) followed by daily low-dose IL-2 (1 MIU/m2/day x 4 weeks) with pulses of intermediate-dose IL-2 (3-15 MIU/m2). Toxicity, NK cell numbers, and cellular cytotoxicity were measured.


RESULTS
In the hu-PBL-SCID mouse, the combination of rituximab and IL-2 showed greater activity against B-NHL than either agent alone. Treatment was most effective when IL-2 was given before rituximab. Twelve patients with heavily pretreated B-NHL entered the phase I trial. Toxicity was manageable, and responses were observed. NK cell expansion and enhanced cellular cytotoxicity against a B-cell lymphoma target were observed but did not correlate with response.


CONCLUSIONS
The combination of IL-2 and rituximab is synergistic against B-NHL in the hu-PBL-SCID model. In the phase I trial, a sequential combination of rituximab and IL-2 was well tolerated and achieved biological end points. Responses were observed.
Recruitment and retention of participants in randomised controlled trials: a review of trials funded and published by the United Kingdom Health Technology Assessment Programme

BACKGROUND
Substantial amounts of public funds are invested in health research worldwide. Publicly funded randomised controlled trials (RCTs) often recruit participants at a slower than anticipated rate. Many trials fail to reach their planned sample size within the envisaged trial timescale and trial funding envelope.


OBJECTIVES
To review the consent, recruitment and retention rates for single and multicentre randomised control trials funded and published by the UK's National Institute for Health Research (NIHR) Health Technology Assessment (HTA) Programme.


DATA SOURCES AND STUDY SELECTION
HTA reports of individually randomised single or multicentre RCTs published from the start of 2004 to the end of April 2016 were reviewed.


DATA EXTRACTION
Information was extracted, relating to the trial characteristics, sample size, recruitment and retention by two independent reviewers.


MAIN OUTCOME MEASURES
Target sample size and whether it was achieved; recruitment rates (number of participants recruited per centre per month) and retention rates (randomised participants retained and assessed with valid primary outcome data).


RESULTS
This review identified 151 individually RCTs from 787 NIHR HTA reports. The final recruitment target sample size was achieved in 56% (85/151) of the RCTs and more than 80% of the final target sample size was achieved for 79% of the RCTs (119/151). The median recruitment rate (participants per centre per month) was found to be 0.92 (IQR 0.43-2.79) and the median retention rate (proportion of participants with valid primary outcome data at follow-up) was estimated at 89% (IQR 79-97%).


CONCLUSIONS
There is considerable variation in the consent, recruitment and retention rates in publicly funded RCTs. Investigators should bear this in mind at the planning stage of their study and not be overly optimistic about their recruitment projections.
Data envelopment analysis classification machine

Article history: Received 4 December 2009 Received in revised form 1 June 2011 Accepted 2 July 2011 Available online 12 July 2011
A KT intervention including the evidence alert system to improve clinician’s evidence-based practice behavior—a cluster randomized controlled trial

BACKGROUND
It is difficult to foster research utilization among allied health professionals (AHPs). Tailored, multifaceted knowledge translation (KT) strategies are now recommended but are resource intensive to implement. Employers need effective KT solutions but little is known about; the impact and viability of multifaceted KT strategies using an online KT tool, their effectiveness with AHPs and their effect on evidence-based practice (EBP) decision-making behavior. The study aim was to measure the effectiveness of a multifaceted KT intervention including a customized KT tool, to change EBP behavior, knowledge, and attitudes of AHPs.


METHODS
This is an evaluator-blinded, cluster randomized controlled trial conducted in an Australian community-based cerebral palsy service. 135 AHPs (physiotherapists, occupational therapists, speech pathologists, psychologists and social workers) from four regions were cluster randomized (n = 4), to either the KT intervention group (n = 73 AHPs) or the control group (n = 62 AHPs), using computer-generated random numbers, concealed in opaque envelopes, by an independent officer. The KT intervention included three-day skills training workshop and multifaceted workplace supports to redress barriers (paid EBP time, mentoring, system changes and access to an online research synthesis tool). Primary outcome (self- and peer-rated EBP behavior) was measured using the Goal Attainment Scale (individual level). Secondary outcomes (knowledge and attitudes) were measured using exams and the Evidence Based Practice Attitude Scale.


RESULTS
The intervention group's primary outcome scores improved relative to the control group, however when clustering was taken into account, the findings were non-significant: self-rated EBP behavior [effect size 4.97 (95% CI -10.47, 20.41) (p = 0.52)]; peer-rated EBP behavior [effect size 5.86 (95% CI -17.77, 29.50) (p = 0.62)]. Statistically significant improvements in EBP knowledge were detected [effect size 2.97 (95% CI 1.97, 3.97 (p < 0.0001)]. Change in EBP attitudes was not statistically significant.


CONCLUSIONS
Improvement in EBP behavior was not statistically significant after adjusting for cluster effect, however similar improvements from peer-ratings suggest behaviorally meaningful gains. The large variability in behavior observed between clusters suggests barrier assessments and subsequent KT interventions may need to target subgroups within an organization.


TRIAL REGISTRATION
Registered on the Australian New Zealand Clinical Trials Registry (ACTRN12611000529943).
An economic analysis of robot-assisted therapy for long-term upper-limb impairment after stroke.

BACKGROUND AND PURPOSE
Stroke is a leading cause of disability. Rehabilitation robotics have been developed to aid in recovery after a stroke. This study determined the additional cost of robot-assisted therapy and tested its cost-effectiveness.


METHODS
We estimated the intervention costs and tracked participants' healthcare costs. We collected quality of life using the Stroke Impact Scale and the Health Utilities Index. We analyzed the cost data at 36 weeks postrandomization using multivariate regression models controlling for site, presence of a prior stroke, and Veterans Affairs costs in the year before randomization.


RESULTS
A total of 127 participants were randomized to usual care plus robot therapy (n=49), usual care plus intensive comparison therapy (n=50), or usual care alone (n=28). The average cost of delivering robot therapy and intensive comparison therapy was $5152 and $7382, respectively (P<0.001), and both were significantly more expensive than usual care alone (no additional intervention costs). At 36 weeks postrandomization, the total costs were comparable for the 3 groups ($17 831 for robot therapy, $19 746 for intensive comparison therapy, and $19 098 for usual care). Changes in quality of life were modest and not statistically different.


CONCLUSIONS
The added cost of delivering robot or intensive comparison therapy was recuperated by lower healthcare use costs compared with those in the usual care group. However, uncertainty remains about the cost-effectiveness of robotic-assisted rehabilitation compared with traditional rehabilitation. Clinical Trial Registration- URL: http://clinicaltrials.gov. Unique identifier: NCT00372411.
Measuring Network Security Using Bayesian Network-Based Attack Graphs

Given the increasing dependence of our societies on information systems, the overall security of these systems should be measured and improved. Existing work generally focuses on measuring individual vulnerabilities instead of measuring their combined effects. Recent research has explored the application of attack graphs and probabilistic security metrics to address this challenge. However, such work usually assumes metrics of individual vulnerabilities to be independently distributed and combines them in an arbitrary manner. They cannot address more realistic cases, such as exploiting one vulnerability makes another vulnerability easier to exploit. In this paper, we propose to model probability metrics based on attack graphs as a special Bayesian Network. This approach provides a sound theoretical foundation to such metrics. It can also provide the capabilities of using conditional probabilities to address the general cases of interdependency between vulnerabilities.
Automatic, Dimensional and Continuous Emotion Recognition

Recognition and analysis of human emotions have attracted a lot of interest in the past two decades and have been researched extensively in neuroscience, psychology, cognitive sciences, and computer sciences. Most of the past research in machine analysis of human emotion has focused on recognition of prototypic expressions of six basic emotions based on data that has been posed on demand and acquired in laboratory settings. More recently, there has been a shift toward recognition of affective displays recorded in naturalistic settings as driven by real world applications. This shift in affective computing research is aimed toward subtle, continuous, and context-specific interpretations of affective displays recorded in real-world settings and toward combining multiple modalities for analysis and recognition of human emotion. Accordingly, this paper explores recent advances in dimensional and continuous affect modelling, sensing, and automatic recognition from visual, audio, tactile, and brain-wave modalities.
The Fourth Paradigm: Data-Intensive Scientific Discovery

from these individual steps to produce global behavior, usually averaged over time. Computer science provides the key elements to describe mechanistic steps: algorithms and programming languages [3]. Following the metaphor of molecules as processes introduced in [4], process calculi have been identified as a promising tool to model biological systems that are inherently complex, concurrent, and driven by the interactions of their subsystems. Visualization in Process Algebra Models of Biological Systems
MEANS: A medical question-answering system combining NLP techniques and semantic Web technologies

The Question Answering (QA) task aims to provide precise and quick answers to user questions from a collection of documents or a database. This kind of IR system is sorely needed with the dramatic growth of digital information. In this paper, we address the problem of QA in the medical domain where several specific conditions are met. We propose a semantic approach to QA based on (i) Natural Language Processing techniques, which allow a deep analysis of medical questions and documents and (ii) semantic Web technologies at both representation and interrogation levels. We present our Semantic QuestionAnswering System, called MEANS and our proposed method for ‘‘Answer Search’’ based on semantic search and query relaxation. We evaluate the overall system performance on real questions and answers extracted from MEDLINE articles. Our experiments show promising results and suggest that a query-relaxation strategy can further improve the overall performance. 2015 Elsevier Ltd. All rights reserved.
Beyond the Kalman Filter: Particle Filters for Tracking Applications

Target tracking is an important element of surveillance, guidance or obstacle avoidance, whose role is to determine the number, position and movement of targets. The fundamental building block of a tracking system is a filter for recursive state estimation. The Kalman filter has been flogged to death as the work-horse of tracking systems since its formulation in the 60's. In this talk we look beyond the Kalman filter at sequential Monte Carlo methods, collectively referred to as particle filters. Particle filters have become a popular method for stochastic dynamic estimation problems. This popularity can be explained by a wave of optimism among practitioners that traditionally difficult nonlinear/non-Gaussian dynamic estimation problems can now be solved accurately and reliably using this methodology. The computational cost of particle filters have often been considered their main disadvantage, but with ever faster computers and more efficient particle filter algorithms, this argument is becoming less relevant. The talk is organized in two parts. First we review the historical development and current status of particle filtering and its relevance to target tracking. We then consider in detail several tracking applications where conventional (Kalman based) methods appear inappropriate (unreliable or inaccurate) and where we instead need the potential benefits of particle filters. 1 The paper was written together with David Salmond, QinetiQ, UK.
Database Architecture Optimized for the New Bottleneck: Memory Access

In the past decade, advances in speed of commodity CPUs have far out-paced advances in memory latency. Main-memory access is therefore increasingly a performance bottleneck for many computer applications, including database systems. In this article, we use a simple scan test to show the severe impact of this bottleneck. The insights gained are translated into guidelines for database architecture; in terms of both data structures and algorithms. We discuss how vertically fragmented data structures optimize cache performance on sequential data access. We then focus on equi-join, typically a random-access operation, and introduce radix algorithms for partitioned hash-join. The performance of these algorithms is quantified using a detailed analytical model that incorporates memory access cost. Experiments that validate this model were performed on the Monet database system. We obtained exact statistics on events like TLB misses, L1 and L2 cache misses, by using hardware performance counters found in modern CPUs. Using our cost model, we show how the carefully tuned memory access pattern of our radix algorithms make them perform well, which is confirmed by experimental results. *This work was carried out when the author was at the University of Amsterdam, supported by SION grant 612-23-431 Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment. Proceedings of the 25th VLDB Conference, Edinburgh, Scotland, 1999.
Demographic Factors and Knowledge Sharing Quality among Malaysian Government Officers

Knowledge sharing is one of the important elements in knowledge management. Previous works indicate that employees are reluctant to share knowledge among themselves. Many factors impede knowledge sharing among employees in organizations. One of those factors is demography. The purpose of this study is to find out the differences among government officers’ knowledge sharing quality in terms of demographic factors. A survey of 48 respondents using questionnaire as data collection method was conducted. The results show that demographic variables are not significant predictors to government officers’ knowledge sharing quality.
Modeling indoor space

This paper begins by reviewing the motivation for an informatics of indoor space. It then discusses application domains and consider why current geospatial technology, with its focus on outdoor space, needs to be extended. We review existing formal models of indoor space, along with their applications, and introduce a new model that is the subject of the author's current research. We conclude with some observations about the development of a unified model of both indoor and outdoor space.
Performance Evaluation of Wavelet Based Coders on Brain MRI Volumetric Medical Datasets for Storage and Wireless Transmission

In this paper, we evaluate the performance of some wavelet based coding algorithms such as 3D QT-L, 3D SPIHT and JPEG2K. In the first step we achieve an objective comparison between three coders, namely 3D SPIHT, 3D QT-L and JPEG2K. For this purpose, eight MRI head scan test sets of 256 x 256x124 voxels have been used. Results show superior performance of 3D SPIHT algorithm, whereas 3D QT-L outperforms JPEG2K. The second step consists of evaluating the robustness of 3D SPIHT and JPEG2K coding algorithm over wireless transmission. Compressed dataset images are then transmitted over AWGN wireless channel or over Rayleigh wireless channel. Results show the superiority of JPEG2K over these two models. In fact, it has been deduced that JPEG2K is more robust regarding coding errors. Thus we may conclude the necessity of using corrector codes in order to protect the transmitted medical information. Keywords—Image coding, medical imaging, wavelet based coder, wireless transmission.