LLukas22/scidocs huggingface dataset:
Stroke Treatment Associated with Rehabilitation Therapy and Transcranial DC Stimulation (START-tDCS): a study protocol for a randomized controlled trial.

BACKGROUND
Traditional treatment for motor impairment after stroke includes medication and physical rehabilitation. The transcranial direct current stimulation associated with a standard physical therapy program may be an effective therapeutic alternative for these patients.


METHODS
This study is a sham-controlled, double-blind, randomized clinical trial aiming to evaluate the efficacy of transcranial direct current stimulation in activities of daily living and motor function post subacute stroke. In total there will be 40 patients enrolled, diagnosed with subacute, ischemic, unilateral, non-recurring stroke. Participants will be randomized to two groups, one with active stimulation and the other with a placebo current. Patients and investigators will be blinded. Everyone will receive systematic physical therapy, based on constraint-induced movement therapy. The intervention will be applied for 10 consecutive days. Patients will undergo three functional assessments: at baseline, week 2, and week 4. Neuropsychological tests will be performed at baseline and week 4. Adverse effects will be computed at each session. On completion of the baseline measures, randomization will be conducted using random permuted blocks. The randomization will be concealed until group allocation.


DISCUSSION
This study will investigate the combined effects of transcranial direct current stimulation and physical therapy on functional improvement after stroke. We tested whether the combination of these treatments is more effective than physical therapy alone when administered in the early stages after stroke.


TRIAL REGISTRATION
NCT02156635---May 30, 2014. Randomization is ongoing (40 participants randomized as of the end of December 2015).
M. Poincaré visits Jefferson lab: Relativistic models of few-nucleon systems

Abstract I discuss relativistic models of few-nucleon systems, with particular emphasis on calculations of electron-deuteron scattering and the comparison of these calculations with recent data from Jefferson Lab.
Balancing Public and Private Resources for Basic Education: School Fees in Post-Apartheid South Africa

Paper initially prepared for Education and Social Change in South Africa: The Challenge of Policy, a book project of the Human Sciences Research Council Pretoria, South Africa.. This paper is part of a larger research project on South Africa's efforts to make its education system more equitable and democratic. The larger project was supported by a Fulbright grant to Helen Ladd that enabled the two authors to spend 6 months at the University of Cape Town in 2002. The authors are extremely grateful to the Fulbright Association, to the Department of Economics at the University of Cape Town and to the Spencer Foundation, which provided supplemental funds for the research. In addition, the authors appreciate the able research assistance of Steven Kent and Richard Walker, and the cooperation of Education Department officials in the Western Cape and Eastern Cape, who provided the school level data for those provinces. 3 Abstract A major issue facing education policy makers in South Africa since 1994 has been the appropriate balance to strike between reliance on public and private funds. Despite growing international pressure for developing countries to provide free basic education and the language of the new South African Constitution affirming the right of individuals to basic education, South Africa has chosen to encourage primary and secondary school governing bodies to supplement public funding with revenue from school fees or other sources. This mixed funding arrangement reflects political compromises during the transition period before 1994, fiscal constraints, and political economy concerns such as the desire to maintain support for public education among middle class South Africans. This paper describes and evaluate the effects of this mixed funding arrangement on student access to education, enrollment patterns among schools, disparities in publicly funded resources across schools, and disparities in the total of public and private resources across schools. We find that the policy of school fees has been successful in keeping middle class families in the public school system, but has done little to improve the quality of education available to disadvantaged students. We conclude with a suggestion for modifying the fee policy.
Impact of delaying school start time on adolescent sleep, mood, and behavior.

OBJECTIVE
To examine the impact of a 30-minute delay in school start time on adolescents' sleep, mood, and behavior.


DESIGN
Participants completed the online retrospective Sleep Habits Survey before and after a change in school start time.


SETTING
An independent high school in Rhode Island.


PARTICIPANTS
Students (n = 201) in grades 9 through 12. Intervention Institution of a delay in school start time from 8 to 8:30 am.


MAIN OUTCOME MEASURES
Sleep patterns and behavior, daytime sleepiness, mood, data from the Health Center, and absences/tardies.


RESULTS
After the start time delay, mean school night sleep duration increased by 45 minutes, and average bedtime advanced by 18 minutes (95% confidence interval, 7-29 minutes [t(423) = 3.36; P < .001]); the percentage of students getting less than 7 hours of sleep decreased by 79.4%, and those reporting at least 8 hours of sleep increased from 16.4% to 54.7%. Students reported significantly more satisfaction with sleep and experienced improved motivation. Daytime sleepiness, fatigue, and depressed mood were all reduced. Most health-related variables, including Health Center visits for fatigue-related complaints, and class attendance also improved.


CONCLUSIONS
A modest delay in school start time was associated with significant improvements in measures of adolescent alertness, mood, and health. The results of this study support the potential benefits of adjusting school schedules to adolescents' sleep needs, circadian rhythm, and developmental stage.
Artificial intelligence in diagnosis of obstructive lung disease: current status and future potential.

PURPOSE OF REVIEW
The application of artificial intelligence in the diagnosis of obstructive lung diseases is an exciting phenomenon. Artificial intelligence algorithms work by finding patterns in data obtained from diagnostic tests, which can be used to predict clinical outcomes or to detect obstructive phenotypes. The purpose of this review is to describe the latest trends and to discuss the future potential of artificial intelligence in the diagnosis of obstructive lung diseases.


RECENT FINDINGS
Machine learning has been successfully used in automated interpretation of pulmonary function tests for differential diagnosis of obstructive lung diseases. Deep learning models such as convolutional neural network are state-of-the art for obstructive pattern recognition in computed tomography. Machine learning has also been applied in other diagnostic approaches such as forced oscillation test, breath analysis, lung sound analysis and telemedicine with promising results in small-scale studies.


SUMMARY
Overall, the application of artificial intelligence has produced encouraging results in the diagnosis of obstructive lung diseases. However, large-scale studies are still required to validate current findings and to boost its adoption by the medical community.
Feature Denoising and Nearest–Farthest Distance Preserving Projection for Machine Fault Diagnosis

It is a big challenge to identify the most effective features for enhancement of fault classification accuracy in rotating machines due to nonstationary and nonlinear vibration characteristics of the machines under varying operating conditions. To find discriminative features, a novel dimension reduction algorithm, referred to as the nearest and farthest distance preserving projection (NFDPP), is proposed for machine fault feature extraction and classification. With the NFDPP, both the nearest and farthest samples of the data manifold can be analyzed simultaneously to identify features leading to fault classification. Additionally, we denoise the features directly in the feature space to save computation time and storage space, and prove its equivalence to denoising the signals in the time domain. Through analysis of measured vibration data for bearings with different defects, it is demonstrated that the proposed NFDPP approach can effectively classify different bearing faults and identify the severity of the bearing ball defect, and the direct denoising of features yield a significant improvement in fault classification. The effectiveness of the proposed method is further validated in identifying compound faults in locomotive bearings in an industrial setting.
Acute Limb Ischemia in Pediatric Population Secondary to Peripheral Vascular Cannulation: Literature Review and Recommendations.

INTRODUCTION
In this article, we discuss published literature on the management of pediatric patients with acute limb ischemia and also present our center's experience.


RESULTS
Literature review suggests that in the absence of imminent risk of limb loss, noninterventional management with anticoagulants and systemic thrombolysis is preferable and associated with better clinical outcomes than surgery such as reduced per operative morbidity and mortality. In selected more severe cases, surgery may be required. We propose an algorithm for improved clinical outcomes based on the published literature and the American College of Chest Physicians' recommendations for antithrombotic management in the pediatric population.


CONCLUSION
Literature review suggests an inverse relationship between age and surgical success, particularly in preschool pediatric population. Conservative management as a preliminary strategy seems most beneficial. It is hoped that the proposed intercalated algorithm of medical and surgical management of these patients can further improve clinical outcomes.
Design principles for origin-destination flow maps

Origin-destination flow maps are often difficult to read due to overlapping flows. Cartographers have developed design principles in manual cartography for origin-destination flow maps to reduce overlaps and increase readability. These design principles are identified and documented using a quantitative content analysis of 97 geographic origin-destination flow maps without branching or merging flows. The effectiveness of selected design principles is verified in a user study with 215 participants. Findings show that (a) curved flows are more effective than straight flows, (b) arrows indicate direction more effectively than tapered line widths, and (c) flows between nodes are more effective than flows between areas. These findings, combined with results from user studies in graph drawing, conclude that effective and efficient origin-destination flow maps should be designed according to the following design principles: overlaps between flows are minimized; symmetric flows are preferred to asymmetric flows; longer flows are curved more than shorter or peripheral flows; acute angles between crossing flows are avoided; sharp bends in flow lines are avoided; flows do not pass under unconnected nodes; flows are radially distributed around nodes; flow direction is indicated with arrowheads; and flow width is scaled with represented quantity. ARTICLE HISTORY Received 11 September 2016 Accepted 15 November 2016
Can music preference indicate mental health status in young people?

OBJECTIVE
In the aftermath of the double suicide of two teenage girls in 2007, the media linked the themes of 'emo' music and the girls' mental state. But it is not just emo music that has been the subject of scrutiny by the media. Rap music, country, and heavy metal have also been blamed for antisocial behaviours including violence, theft, promiscuity and drug use. It remains an important research and clinical question as to whether music contributes to the acting out of behaviours described in the music lyrics or whether the preferred music represents the already existing behavioural tendencies in the subject. This paper surveys and discusses the relevant literature on music preference and adolescent music listening behaviours, and their links with adolescent mental health.


CONCLUSION
Studies have found a relationship between various genres of music and antisocial behaviours, vulnerability to suicide, and drug use. However, studies reject that music is a causal factor and suggest that music preference is more indicative of emotional vulnerability. A limited number of studies have found correlations between music preference and mental health status. More research is needed to determine whether music preferences of those with diagnosed mental health issues differ substantially from the general adolescent population.
Intergroup bias toward “Group X”: Evidence of prejudice, dehumanization, avoidance, and discrimination against asexuals

Although biases against homosexuals (and bisexuals) are well established, potential biases against a largely unrecognized sexual minority group, asexuals, has remained uninvestigated. In two studies (university student and community samples) we examined the extent to which those not desiring sexual activity are viewed negatively by heterosexuals. We provide the first empirical evidence of intergroup bias against asexuals (the so-called “Group X”), a social target evaluated more negatively, viewed as less human, and less valued as contact partners, relative to heterosexuals and other sexual minorities. Heterosexuals were also willing to discriminate against asexuals (matching discrimination against homosexuals). Potential confounds (e.g., bias against singles or unfamiliar groups) were ruled out as explanations. We suggest that the boundaries of theorizing about sexual minority prejudice be broadened to incorporate this new target group at this critical period, when interest in and recognition of asexuality is scientifically and culturally expanding.
Antidepressant effects of ketamine in depressed patients

BACKGROUND
A growing body of preclinical research suggests that brain glutamate systems may be involved in the pathophysiology of major depression and the mechanism of action of antidepressants. This is the first placebo-controlled, double-blinded trial to assess the treatment effects of a single dose of an N-methyl-D-aspartate (NMDA) receptor antagonist in patients with depression.


METHODS
Seven subjects with major depression completed 2 test days that involved intravenous treatment with ketamine hydrochloride (.5 mg/kg) or saline solutions under randomized, double-blind conditions.


RESULTS
Subjects with depression evidenced significant improvement in depressive symptoms within 72 hours after ketamine but not placebo infusion (i.e., mean 25-item Hamilton Depression Rating Scale scores decreased by 14 +/- SD 10 points vs. 0 +/- 12 points, respectively during active and sham treatment).


CONCLUSIONS
These results suggest a potential role for NMDA receptor-modulating drugs in the treatment of depression.
Iodine biokinetics and dosimetry in radioiodine therapy of thyroid cancer: procedures and results of a prospective international controlled study of ablation after rhTSH or hormone withdrawal.

UNLABELLED
Technical aspects and results of the dosimetric assessments of postoperative radioiodine ablation in the framework of an international, prospective, controlled, randomized, comparative study of the effectiveness of ablation therapy with 3.7 GBq (131)I in differentiated thyroid cancer after stimulation with recombinant human TSH (rhTSH) or by thyroid hormone withdrawal (THW) are presented.


METHODS
Sixty-three patients were randomized after thyroidectomy to either the THW or the rhTSH group. Scintigraphic neck images were acquired starting 48 h after radioiodine administration to assess biokinetics in the thyroid remnant. The activity in blood samples was quantified and data from whole-body probe measurements and scintigraphic whole-body scans were combined to deduce retention curves in blood and whole body, respectively. The absorbed dose to the blood was calculated using a modified approach based on the formalism of the MIRD Committee of the Society of Nuclear Medicine.


RESULTS
The effective half-time in the remnant thyroid tissue was significantly longer after rhTSH than THW (67.6 +/- 48.8 vs. 48.0 +/- 52.6 h, respectively; P = 0.01), whereas the observed differences of the mean 48-h (131)I uptakes (0.5% +/- 0.7% vs. 0.9% +/- 1.0% after THW; P = 0.1) and residence times (0.9 +/- 1.3 vs. 1.4 +/- 1.5 h after THW; P = 0.1) between the rhTSH and THW groups were not statistically significant. The specific absorbed dose to the blood was significantly (P <0.0001) lower after administration of rhTSH (mean, 0.109 +/- 0.028 mGy/MBq; maximum, 0.18 mGy/MBq) than after THW (mean, 0.167 +/- 0.061 mGy/MBq; maximum, 0.35 mGy/MBq), indicating that higher activities of radioiodine might be safely administered after exogenous stimulation with rhTSH.


CONCLUSION
Indication of an influence of the residence time of radioiodine in the blood on the fractional uptake into thyroid remnant was found. A novel regimen is proposed in which therapeutic activities to be administered are determined from the individual specific blood dose.
accines are not associated with autism : An evidence-based eta-analysis of case-control and cohort studies uke

There has been enormous debate regarding the possibility of a link between childhood vaccinations and the subsequent development of autism. This has in recent times become a major public health issue with vaccine preventable diseases increasing in the community due to the fear of a ‘link’ between vaccinations and autism. We performed a meta-analysis to summarise available evidence from case-control and cohort studies on this topic (MEDLINE, PubMed, EMBASE, Google Scholar up to April, 2014). Eligible studies assessed the relationship between vaccine administration and the subsequent development of autism or autism spectrum disorders (ASD). Two reviewers extracted data on study characteristics, methods, and outcomes. Disagreement was resolved by consensus with another author. Five cohort studies involving 1,256,407 children, and five case-control studies involving 9920 children were included in this analysis. The cohort data revealed no relationship between vaccination and autism (OR: 0.99; 95% CI: 0.92 to 1.06) or ASD (OR: 0.91; 95% CI: 0.68 to 1.20), or MMR (OR: 0.84; 95% CI: 0.70 to 1.01), or thimerosal (OR: 1.00; 95% CI: 0.77 to 1.31), or mercury (Hg) (OR: 1.00; 95% CI: 0.93 to 1.07). Similarly the case-control data found no evidence for increased risk of developing autism or ASD following MMR, Hg, or thimerosal exposure when grouped by condition (OR: 0.90, 95% CI: 0.83 to 0.98; p = 0.02) or grouped by exposure type (OR: 0.85, 95% CI: 0.76 to 0.95; p = 0.01). Findings of this meta-analysis suggest that vaccinations are not associated with the development of autism or autism spectrum disorder. Furthermore, the components of the vaccines (thimerosal or mercury) or multiple vaccines (MMR) are not associated with the development of autism or autism spectrum disorder.
Learning Depth with Convolutional Spatial Propagation Network

Depth prediction is one of the fundamental problems in computer vision. In this paper, we propose a simple yet effective convolutional spatial propagation network (CSPN) to learn the affinity matrix for various depth estimation tasks. Specifically, it is an efficient linear propagation model, in which the propagation is performed with a manner of recurrent convolutional operation, and the affinity among neighboring pixels is learned through a deep convolutional neural network (CNN). We can append this module to any output from a state-of-the-art (SOTA) depth estimation networks to improve their performances. In practice, we further extend CSPN in two aspects: 1) allow it to take sparse depth map as additional input, which is useful for the task of depth completion [2], [3]; 2) extend to 3D CSPN to handle features with one additional dimension, similar to the commonly used 3D convolution operation. It is effective in the task of stereo matching using 3D cost volume [4]. For the task of single image depth estimation and depth completion, we experiment the proposed CPSN conjunct algorithms over the popular NYU v2 [5] and KITTI [6] datasets, where we show that our proposed algorithms not only produce high quality (e.g., 30% more reduction in depth error), but also run faster (e.g., 2 to 5 × faster) than previous SOTA spatial propagation network [7]. We also evaluated our stereo matching algorithm on the Scene Flow [8] and KITTI Stereo datasets [6], [9], and rank 1st on both the KITTI Stereo 2012 and 2015 benchmarks , which demonstrates the effectiveness of the proposed module. The code of CSPN proposed in this work will be release at https://github.com/XinJCheng/CSPN.
Nonorthogonal Multiple Access in Large-Scale Underlay Cognitive Radio Networks

In this paper, nonorthogonal multiple access (NOMA) is applied to large-scale underlay cognitive radio (CR) networks with randomly deployed users. To characterize the performance of the considered network, new closed-form expressions of the outage probability are derived using stochastic geometry. More importantly, by carrying out the diversity analysis, new insights are obtained under the two scenarios with different power constraints: 1) fixed transmit power of the primary transmitters (PTs); and 2) transmit power of the PTs being proportional to that of the secondary base station. For the first scenario, a diversity order of m is experienced at the mth-ordered NOMA user. For the second scenario, there is an asymptotic error floor for the outage probability. Simulation results are provided to verify the accuracy of the derived results. A pivotal conclusion is reached that by carefully designing target data rates and power allocation coefficients of users, NOMA can outperform conventional orthogonal multiple access in underlay CR networks.
KNN-CF Approach: Incorporating Certainty Factor to kNN Classification

 Abstract—KNN classification finds k nearest neighbors of a query in training data and then predicts the class of the query as the most frequent one occurring in the neighbors. This is a typical method based on the majority rule. Although majority-rule based methods have widely and successfully been used in real applications, they can be unsuitable to the learning setting of skewed class distribution. This paper incorporates certainty factor (CF) measure to kNN classification, called kNN-CF classification, so as to deal with the above issue. This CF-measure based strategy can be applied on the top of a kNN classification algorithm (or a hot-deck method) to meet the need of imbalanced learning. This leads to that an existing kNN classification algorithm can easily be extended to the setting of skewed class distribution. Some experiments are conducted for evaluating the efficiency, and demonstrate that the kNN-CF classification outperforms standard kNN classification in accuracy.
Condition Assessment of Power OLTC by Vibration Analysis Using Wavelet Transform

The suitable condition of an onload tap changer (OLTC) is essential for the operation of a power transformer. It is extremely desirable to have some indicators to assess the OLTC condition, especially if these indicators are capable of being used in an online monitoring system that does not affect the normal operation of the transformer. This paper describes a methodology by using envelope analysis based on the Hilbert transform and orthogonal decomposition of the wavelet to determine the main diagnostic parameters for power transformer OLTC condition assessment by means of vibration measurements during the tap changer operation.