Miracle-dz/UniFAR-FTUs huggingface dataset:
Electroconvulsive therapy in various psychiatric disorders: A Retrospective Study from North East India

Background: Electroconvulsive therapy has been found to be effective treatment in Depressive disorder and in actively suicidal patient. This treatment has been also prescribed in different psychiatric disorders. Hence the objective of the study is to explore the various psychiatric diagnosis and indications of patients receiving ECT and is there any gender difference in the treatment sessions. Method: Data of 28 Patients diagnosed as per ICD -10 criteria and advised for Brief pulse ECT are collected for the study. Unpaired t test is used for inferential statistics and P value <0.05 is considered significant in this study. Result: Among the patients with psychiatric diagnosis receiving ECT; depressive disorder (35.73%) was highest followed by schizophrenia (25%). Majority cases indication of ECT was severe depression, suicidal attempt, psychosis and treatment resistant. The mean age difference between male and female was statistically significant (P<0.02237). Gender influence on ECT sessions was statistically not significant (P<0.2218). Conclusion: Brief pulse ECT has been prescribed in various psychiatric diagnosis without any immediate adverse effect and gender has no influence on ECT sessions.
Chronic Pain and Depression in Low Back (Spinal) Injured Patients

Depression caused by physical dysfunction and associated symptoms as the aftermath of the low back (spinal) injury is commonly undiagnosed and untreated. In this paper, based on our clinical experience, we have described a relation between depression and lumbosacral injury. In our research, we selected 54 (26 female and 28 male) patients in two different groups: (1) those whose low back injury occurred less than 12 months before research commenced; and (2) those whose injuries occurred more than 12 months before the research (their condition has been considered as a chronic). All of the patients (n=54) were assessed by using the Beck Depression Inventory (BDI), Montgomery-Asberg Depression Rating Scale (MADRS), and General Health Questionnaire-28 (GHQ-28) in order to evaluate their level of depression. The results show that low back (spinal) injured patients suffered depression due to their body discomfort and changed day-to-day capacities. Those who sustained injury more than one year developed an upper level of a moderate depression. However, if not taking any treatment following their psychological disturbances, the patients had suffered a severe depression. Their level of depression increases with a chronicity of the physical pain making also depression as a chronic disorder.
Health Promoting Schools in Kerala, India

Introduction: Health promoting school (HPS) is a holistic concept where health and learning coexist. The objective of this study was to assess the health promoting standards of schools in Kerala. Methodology: A cross-sectional study was designed in Kerala, India, with schools in Kerala as a study unit. A questionnaire which consisted of 37 items across eight domains of the HPS concept was developed and validated. The schools were then graded into compliant and not compliant categories based on scores obtained. Bivariate and multivariate analysis was also done. Results: Of 120 schools, 90.8% were compliant toward health education domain and only 8.3% were compliant with nutrition services. Majority of schools showed compliance with the other six domains. Average overall scores were 153 (58.8%) with the equal number of schools in both compliant and not compliant categories. There was a significant association between health education and physical education domain with respect to the type of school, i.e., privately managed had six times more chances of being compliant toward health education domain compared to government schools (odds ratio [OR] 6.05; 95% confidence interval [CI] 1.10–33.29). Hence, also private schools had two times more chance of being compliant toward physical education compared to government schools (OR 2.52; 95% CI 1.0 – 4.32). Physical education domain showed a significant association with respect to geographic region, i.e., the schools in North Kerala were found to be three times more compliant compared to South Kerala (OR 3.48; 95% CI 1.05–11.53). Conclusions: Despite the good health and social indicators in Kerala, there is a deficiency in schools promoting health of children. A coordinated effort by the government and the education system can convert existing schools into health promoting.
CD14highCD16+ Rather Than CD14lowCD16+ Monocytes Correlate With Disease Progression in Chronic HIV-Infected Patients

Objective:CD14+CD16+ monocytes are an important cellular target for HIV-1 entry and expand in the peripheral blood of HIV-infected individuals. Because CD14+CD16+ monocytes are a heterogeneous population and consist of CD14highCD16+ and CD14lowCD16+ subsets, we evaluated the effects of HIV infection on distinct subsets of CD16+ monocytes. Methods:Untreated HIV-infected patients were recruited to investigate the relationship between the proportions of monocyte subsets with plasma viral loads and CD4+ T-cell counts. Patients receiving highly active antiretroviral therapy (HAART) were followed up in a cross-sectional and a longitudinal study. Results:Compared with CD14lowCD16+, CD14highCD16+ monocytes showed higher levels of CD64 and HLA-DR antigens, which imply that these 2 distinct subsets have different immunoregulatory phenotypes. In HAART-naive patients, elevated proportions of CD14highCD16+ monocytes were correlated with increased viral loads and decreased CD4+ T-cell counts, whereas CD14lowCD16+ monocytes did not show such correlation with disease progression. Of importance, HAART recovered the proportion of CD14highCD16+ monocytes, whereas CD14lowCD16+ monocytes did not decrease during 1 year of antiviral therapy. Conclusions:Taken together, our observations elucidate distinct immune responses of monocyte subsets during HIV infection and antiviral therapy and provide new insight into the roles of innate immunity in HIV-related pathogenesis.
A Survey on Adaptive Wildcard Rule Cache Management with Cache Replacement Algorithms for Software - Defined Networks

: Software Defined Networking empowers adaptable stream control by reserving rules at OpenFlow switches. Trump card run the show storing empowers administration of movement totals, diminishes stream setup questions, and disentangles strategy administration. Ternary Content Addressable Memory (TCAM) limit issue is a vital issue in Software-Defined Networking. Lead reserving is an effective method to tackle the TCAM limit issue. Be that as it may, there exists run reliance issue in special case run storing procedure. A Cover-set method to solve the rule dependency problem and wildcard-rule caching algorithm to cache rules into TCAM. Cache replacement algorithm considering both temporal and spatial localities.
Electronic health records for integrated mental health care: protocol for a scoping review

ABSTRACT Objective: Mental health care is known to be poorly integrated into many health systems and could benefit from improved information sharing facilitated by electronic health records (EHRs). Specific issues appear to have limited the application of EHRs in mental health care, including the sensitivity of mental health-related information and issues with data standardisation. This scoping review aims to explore how EHRs have been implemented and adopted in mental health contexts, and their impacts on information sharing. Further, it aims to explore how the unique issues of sensitive information and data standardisation have been addressed in examples of EHRs, if at all. Method: A comprehensive literature search is planned for relevant electronic databases and grey literature sources. Articles from any date that describe the implementation or adoption of an EHR in a mental health context will be included in the review. Articles that describe only the design or development of an EHR in a mental health context will be excluded. Half of the full-text articles will be screened by a second reviewer, with any disagreement mediated by a third reviewer. Results: Abstract screening is currently underway with results being planned for publication in late 2019. The charting of the results will occur in both tabular form and descriptive summaries with results categorised into themes using a deductive content analysis approach. Discussion: The findings from this scoping review have the potential to inform the development of a conceptual framework to guide empirical research on EHRs in mental health contexts.
TPACK learning activity types for secondary computer science courses

Learning activity types for secondary computer science courses support educators in integrating technology and developing their TPACK (technological, pedagogical, and content knowledge) authentically. The taxonomy of computer science activity types presented in this project report provide seven identified activity types and descriptions aligned with the Computer Science Teachers' Association (CSTA) standards and framework. Included in the taxonomy are possible technologies for each activity type. Along with the CSTA standards and framework, ten peer-reviewed studies published between 2009 and 2015 were selected for analysis in the literature review and as research backing the construction of the taxonomy. Further research and expansion of the computer science learning activity types and technologies was recommended.
Plant-derived oleanolic acid ameliorates markers associated with non-alcoholic fatty liver disease in a diet-induced pre-diabetes rat model

Background The increased prevalence of non-alcoholic fatty liver disease (NAFLD) in type 2 diabetes mellitus (T2DM) patients is becoming a worldwide health burden. Studies have indicated, however, that the onset of NAFLD occurs during pre-diabetes, a condition that often precedes the onset of T2DM. Oleanolic acid has been reported to improve glucose homeostasis in diet-induced pre-diabetes; however, the effects of this triterpene on liver function have not been evaluated. Purpose This study was aimed at evaluating the therapeutic effects of oleanolic acid (OA) on selected markers of NAFLD in a pre-diabetes rat model. Methods and materials Pre-diabetes was induced by exposing Sprague Dawley rats to a high-fat high-carbohydrate diet for 20 weeks. The pre-diabetic rats were then treated with OA (80 mg/kg) or metformin (500 mg/kg) in the presence and absence of dietary interventions for a period of 12 weeks. The effects of OA were evaluated on parameters including plasma triglycerides (TGs), very low-density lipoprotein (VLDL) particles, bilirubin, AST, ALT, SREBP and antioxidant profile while the livers were collected for histological analysis. Results The findings of this study showed that the administration of OA to pre-diabetic rats ameliorated body/liver weights ratio and significantly decreased plasma triglycerides (TGs) and VLDL. Furthermore, OA also ameliorated hepatic oxidative stress, lowered the SREBP expression and intrahepatic TGs. In addition, OA administration decreased plasma concentrations of bilirubin and liver damage enzyme biomarkers. Conclusion The findings of the study suggest that OA ameliorates the risk of developing pre-diabetes-related NAFLD through the prevention of intrahepatic fat accumulation while also lowering hepatic inflammation.
System Modeling, Performance Evaluation, and Control of Battery System Charge Balance

As the major energy storage device and power supply source in numerous energy applications, battery systems often face the issue of charge imbalance among battery cells/modules/packs, which can accelerate battery degradation, cause more energy loss, and even incur fire hazard. This thesis is focused on the system modeling, performance evaluation, and control of battery systems with various charge balancing circuits. Specifically, based on the proposed mathematical models for battery charge equalization systems, computationally efficient methods are developed to estimate the evolution of battery state of charge and to evaluate critical system performance measures. Then, near-optimal battery cell/module reconfiguration algorithms are proposed to expedite the battery charge equalization process. Besides, for the battery power modules, a new current allocation method based on charging/discharging spaces is derived for the coordinated control of module charge balance and total power efficiency. Extensive numerical experiments are carried out and the results are compared with those obtained from computer simulations and/or circuit experiments to justify the estimation accuracy and computational efficiency of the proposed methods. System Modeling, Performance Evaluation, and Control of Battery System Charge Balance
DETERMINANT FACTORS OF LENGTH OF STAY AMONG UNDER-FIVE CHILDREN WITH PNEUMONIA DISEASES: A LITERATURE REVIEW

Pneumonia is a public health problem in the worldwide, in Indonesia around 22.7% of under-five child mortality caused by pneumonia. The study aimed at identifying factors associated with length of stay among children under five years with pneumonia. This literature review was conducted in 4 databases: ScienceDirect, EBSCOhost, Clinical Key, and SpringerLink by combining keywords: length of stay; hospitalization; length in hospital; pneumonia; child; pediatric; pediatric; and children. The results showed that the period of length of stay pneumonia ranged 1 to 21 days. Some factors which extend the inpatient period including family history with cigarette smoke, less of nutrient and influenza. Meanwhile, some factors were noted to decrease the length of stay pneumonia among children, including early vaccine, examination, and family empowerment through health education. Mostly factors could reduce or increase LOS pneumonia in children under five years, depending on family factors. It requires further research; it is necessary to consider the effect of family education to decrease LOS pneumonia of children. Keywords: Determination factor, Length of Stay, Pneumonia, Children
Semantic Segmentation of Building Roof in Dense and Diverse Urban Environment with Deep Convolutional Neural Network

This paper presents a novel approach for semantic segmentation of building roof in dense urban environment with Deep Convolution Neural Network (DCNN) using imagery acquired by a Chinese Very High Resolution (VHR) satellite mission, i.e. GaoFen-2 (GF-2). To provide an operational end-to-end work flow for accurate build roof mapping with feature extraction as well as image segmentation, a fully convolutional DCNN with both convolutional and deconvolutional layers is designed to perform the VHR image analysis for labeling pixels. Since the diverse urban patterns and building styles in large areas, sample image data sets of building roof and non-building roof are collected over different metropolitan regions in China. We selected typical cities with dense urban environment in each metropolitan region as study areas for collecting training and test samples. High performance cluster with GPU-mounted workstations is employed to perform the model training and optimization. With the building roof samples collected over different cities, the predictive model with multiple NN layers is developed for building roof labeling. The validation of the building roof map shows that the overall accuracy(OA) and the mean Intersection Over Union( mIOU) of DCNN based segmentation are 94.67%, 0.85 respectively, while CRF-refined segmentation achieved OA of 94.69% and mIOU of 0.83. The results suggest that the proposed approach is a promising solution for building roof mapping with VHR images over large areas across different urban and building patterns. With the operational acquisition of GF2 VHR imagery, it is expected to develop an automated pipeline for operational built-up area monitoring and timely update of building roof map over large areas.
Rate Loss Mitigation for 60-GHz mmWave Massive MIMO Lens Antenna Array Systems.

The rate loss is an important issue for multi-user massive millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems. In such systems, multi-cluster channel propagation leads as a function of the quantization error and, as a result, each active user suffers a significant rate loss. A conventional single beam selection (SBS) scheme is used in an equivalent beamspace MIMO channel to reduce the cost of radio frequency (RF) chains, but this scheme does not diminish the baseband processing cost such as digital-to-analog converter (DAC) because of the incomprehensible relation between selected RF chains and active users. In addition, optimally selected beams or RF chains are operated at the same number of the precoded data streams. Consequently, each active user achieves the number of unfeasible propagation clusters using the traditional SBS scheme. To overcome this problem, we propose a hybrid beam selection (HBS) scheme in an equivalent beamspace MIMO channel to dominate the number of feasible propagation clusters for every active user and to mitigate dimensional and rate loss issues. The numerical result is verified by computer simulations in terms of a feedback-based hybrid zero-forcing precoding.
The Combination of Cranial Morphoscopic and Dental Morphological Methods to Improve the Forensic Estimation of Ancestry

The estimation of ancestry is central to the construction of a biological profile, and has traditionally been done through the analysis of cranial morphoscopic traits. Morphological traits of the dentition have also been used to assess population affinity, though largely outside of the forensic sphere. The Daubert standard of evidence requires that methods used in the forensic sciences be testable and have known rates of error. With few exceptions, the methods employed by anthropologists in the analysis of cranial morphoscopic and dental morphological traits do not comply with that standard. Furthermore, no method exists for reliably producing an ancestry estimate from multiple data sources. This research examines 79 cranial and dental traits in a sample of 693 individuals from various ancestry groups, including several newly or recently standardized traits that have not been fully explored. The Asian/Native American sample was excluded due to sample size. For the remaining sample, the pool of 79 variables was reduced to 34, removing those that did not differ significantly among ancestry groups or were highly correlated with other variables. These 34 variables were used to build classificatory models using random forest modeling and naïve Bayes classification. Overall these models correctly estimated ancestry in 67%-84% of cases. In general, the naïve Bayes classifier performed better than the random forest models. Also, models that combined cranial and dental data outperformed models based on a single data source. Although the improvement of the combined data models over the cranial data models was not statistically significant. Interestingly, the combined data model showed the most marked improvement in estimating the ancestry of Hispanic individuals. This suggests that
Threshold Voltage Roll-off by Structural Parameters for Sub-10 nm Asymmetric Double Gate MOSFET

This study is to analyze threshold voltage roll-off according to structural parameters of sub-10 nm asymmetric double gate MOSFET. In case of sub-10nm channel length, because of short channel effects resulting from the rapid increase of tunneling current, even asymmetric double gate (DG) MOSFET, which has been developed for reducing short channel effects, will increase threshold voltage roll-off, and this is an obstacle against the miniaturization of asymmetric DGMOSFET. Especially, since asymmetric DGMOSFET can be produced differently in top and bottom oxide thickness, top/bottom oxide thickness will affect the threshold voltage roll-off. To analyze this, thermal emission current and tunneling current model have been calculated, and threshold voltage roll-off in accordance with the reduction of channel length has been analyzed by using channel thickness and top/bottom oxide thickness as parameters. As a result, it is found that, in short channel asymmetric double gate MOSFET, threshold voltage roll-off is changed greatly according to top/bottom gate oxide thickness, and that threshold voltage roll-off, in particular, is generated more greatly according to silicon thickness. In addition, it is found that top and bottom oxide thickness have a relation of inverse proportion mutually for maintaining identical threshold voltage
Brawny cores still beat wimpy cores, most of the time

Slower but energy efficient " wimpy " cores only win for general workloads if their single-core speed is reasonably close to that of mid-range " brawny " cores. At Google, we've been long-term proponents of multicore architectures and throughput-oriented computing. In warehouse-scale systems 1 throughput is more important than single-threaded peak performance, because no single processor can handle the full workload. In addition, maximizing single-threaded performance costs power through larger die areas (for example, for larger reorder buffers or branch predictors) and higher clock frequencies. Multicore architectures are great for warehouse-scale systems because they provide ample parallelism in the request stream as well as data parallelism for search or analysis over petabyte data sets. We classify multicore systems as brawny-core systems, whose single-core performance is fairly high, or wimpy-core systems, whose single-core performance is low. The latter are more power efficient. Typically, CPU power decreases by approximately O(k 2) when CPU frequency decreases by k, and decreasing DRAM access speeds with core speeds can save additional power. So why doesn't everyone want wimpy-core systems? Because in many corners of the real world, they're prohibited by law—Amdahl's law. Even though many Internet services benefit from seemingly unbounded request-and data-level parallelism, such systems aren't above the law. As the number of parallel threads increases, reducing serialization and communication overheads can become increasingly difficult. In a limit case, the amount of inherently serial work performed on behalf of a user request by slow single-threaded cores will dominate overall execution time. Cost numbers used by wimpy-core evangelists always exclude software development costs. Unfortunately, wimpy-core systems can require applications to be explicitly parallelized or otherwise optimized for acceptable performance. For example, suppose a Web service runs with a latency of one second per user request, half of it caused by serial CPU time. If we switch to wimpy-core servers, whose single-threaded performance is three times slower, the response time doubles to two seconds and developers might have to spend a substantial amount of effort to optimize the code to get back to the one-second latency. Software development costs often dominate a company's overall technical expenses, so forcing programmers to parallelize more code can cost more than we'd save on the hardware side. Most application programmers prefer to think of an individual request as a single-threaded program, leaving the more difficult parallelization problem to middleware that exploits request-level parallelism (that is, it runs independent user requests …