ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
How cynicism and exhaustion influence the turnover intention of medical social workers: moderation effect of social work educational background and organizational type

Although exhaustion and cynicism are two dimensions of burnout, due to professionalism, they have different influence on the turnover intentions of medical social workers. Using a sample of 405 medical social workers in China, this study found that the influence mechanisms of exhaustion and cynicism on turnover intention are different. Social work educational background has a significant moderation effect on the relationships between exhaustion, cynicism, and turnover intention. A moderation effect of organizational type was also observed, although it was not significant.
Can air pollution reduce technology transfer? Evidence from China's prefecture-level cities

Air pollution hinders technological innovation, but the causal effects of air pollution on technology transfer are overlooked. We use thermal inversion as an instrumental variable for addressing air pollution endogeneity. The empirical results show that a one-unit increase in air pollution reduces technology transfer strength by 4.5 %. However, air pollution has a strong asymmetry in two directions of technology transfer strength. We find that those cities with worse pollution have an intention to transfer their technologies to cities in other provinces. In the PLFC model, heterogeneity varying with GDP can be addressed to estimate the marginal effect between them. Findings suggest that the marginal effects of air pollution on technology transfer can be divided into two parts based on GDP levels. Within the thresholds (lngdp = 11), the effect of environmental regulations will keep increasing and keep stable beyond the thresholds. In addition, different effects on different cities are also discussed.
Prolificacy Assessment of Spermatozoan via State-of-the-Art Deep Learning Frameworks

Childlessness or infertility among couples has become a global health concern. Due to the rise in infertility, couples are looking for medical supports to attain reproduction. This paper deals with diagnosing infertility among men and the major factor in diagnosing infertility among men is the Sperm Morphology Analysis (SMA). In this manuscript, we explore establishing deep learning frameworks to automate the classification problem in the fertilization of sperm cells. We investigate the performance of multiple state-of-the-art deep neural networks on the MHSMA dataset. The experimental results demonstrate that the deep learning-based framework outperforms human experts on sperm classification in terms of accuracy, throughput and reliability. We further analyse the sperm cell data by visualizing the feature activations of the deep learning models, providing a new perspective to understand the data. Finally, a comprehensive analysis is also demonstrated on the experimental results obtained and attributing them to pertinent reasons.
Behavioral similarity of residential customers using a neural network based on adaptive resonance theory

This article presents a methodology aiming at the comprehension and analysis of the residential electricity consumption habitual behavior by means of a similarity analysis, based on the use of an ART (Adaptive Resonance Theory) neural network, which is a neural network composed of two fuzzy ART modules whose training is performed in an unsupervised mode. ART neural networks are stable and plastic and these properties, combined with the processing of essentially binary data, give the neural system a wide capacity for producing objectives that may be easily modified to satisfy requirements predetermined by consumer. The expected result is to obtain information regarding the similarity of consumers. Thus, some benefits may be derived by consumers, such as improved habits of electricity consumption and better strategies for negotiating more favorable rates, especially in the case of smart grid systems. In this new electricity sector paradigm, there is a strong consumer trend for free choice among electricity suppliers. This methodology also benefits load forecasting studies at grid points, where there is greater uncertainty, e. g., the busbars that are closest to consumers, i.e., the uncertainties in the context of the total load forecasting system are increased from the global load to the final consumer.
Gene expression profile suggests different mechanisms underlying sporadic and familial mesial temporal lobe epilepsy

Most patients with pharmacoresistant mesial temporal lobe epilepsy (MTLE) have hippocampal sclerosis on the postoperative histopathological examination. Although most patients with MTLE do not refer to a family history of the disease, familial forms of MTLE have been reported. We studied surgical specimens from patients with MTLE who had epilepsy surgery for medically intractable seizures. We assessed and compared gene expression profiles of the tissue lesion found in patients with familial MTLE (n = 3) and sporadic MTLE (n = 5). In addition, we used data from control hippocampi obtained from a public database (n = 7). We obtained expression profiles using the Human Genome U133 Plus 2.0 (Affymetrix) microarray platform. Overall, the molecular profile identified in familial MTLE differed from that in sporadic MTLE. In the tissue of patients with familial MTLE, we found an over-representation of the biological pathways related to protein response, mRNA processing, and synaptic plasticity and function. In sporadic MTLE, the gene expression profile suggests that the inflammatory response is highly activated. In addition, we found enrichment of gene sets involved in inflammatory cytokines and mediators and chemokine receptor pathways in both groups. However, in sporadic MTLE, we also found enrichment of epidermal growth factor signaling, prostaglandin synthesis and regulation, and microglia pathogen phagocytosis pathways. Furthermore, based on the gene expression signatures, we identified different potential compounds to treat patients with familial and sporadic MTLE. To our knowledge, this is the first study assessing the mRNA profile in surgical tissue obtained from patients with familial MTLE and comparing it with sporadic MTLE. Our results clearly show that, despite phenotypic similarities, both forms of MTLE present distinct molecular signatures, thus suggesting different underlying molecular mechanisms that may require distinct therapeutic approaches.
A comprehensive assessment of the state-of-the-art virtual synchronous generator models

The large-scale penetration of renewable energy sources has a significant impact on the steady-state operation and emergency control of modern electric power systems (EPS). Moreover, as a rule, the mentioned impact is negative. Therefore, the challenge associated with the development of a 'comprehensive' control strategy for renewables becomes extremely relevant. Such a strategy should ensure the same reliable operation of EPSs, as in the case of conventional synchronous generation. Among the existing directions, the concept of a virtual synchronous generator (VSG) is the most preferable. Within this paper, the synthesis and combination of the state-ofthe-art concepts of VSG into generic structures has been performed. For the obtained structures, a comprehensive assessment and an experimental comparison were performed. On the basis of the results obtained, the benefits and drawbacks of the generic structures are highlighted, and a conclusion is made about the VSG structure, demonstrating the most effective and reliable operation.
Depression and Quality of Life among Patients Living with HIV/AIDS in the Era of Universal Treatment Access in Vietnam

Although antiretroviral treatment (ART) access has been universal in recent years, few studies have examined if this policy contributes to the mental health of the patients. This study assessed depression and its relations with health-related quality of life (HRQOL), which is defined as the status of general well-being, physical, emotional, and psychological, among HIV patients. A cross-sectional study was conducted in 482 patients at five outpatient clinics. Patient Health Questionnaire-9 (PHQ-9) and EuroQol-5 dimensions-5 levels (EQ-5D-5L) were used to assess the severity of depression and HRQOL. About one-fifth of patients reported symptoms of depression. According to the result of a multivariate logistic regression model, patients who had a lower number of CD4 cells at the start of ART, who received ART in the clinic without HIV counseling and testing (HCT) services, who had a physical health problem, and who experienced discrimination were more likely to have depression. Depression was associated with significantly decreased HRQOL. Depression is prevalent and significantly negatively associated with HRQOL of HIV/AIDS patients. We recommend screening for depression and intervening in the lives of depressed individuals with respect to those who start ART late, and we also recommend community-based behavioral change campaigns to reduce HIV discrimination.
A 400 mV 160 nW/Ch Compact Energy Efficient Delta Sigma Modulator for Multichannel Biopotential Signal Acquisition System

Analog to digital converter circuit design for biomedical systems with multiple recording channels presents challenges in high density and very low power consumption. Passive integrator and loop-filter based delta-sigma modulators (DSMs) have been recently reported for ultra-low-power and highly energy-efficient data converters for multi-channel biopotential acquisition. However, these modulators rely on a very high oversampling ratio (OSR) to achieve the target resolution. Higher OSR leads to higher power consumption in the modulator and the digital low-pass and decimation filter succeeding the DSM. We present a low OSR passive integrator-based DSM in this work by relying on a duty-cycled resistor (DCR). DCR enables the realization of large time constants in the already passive loop-filter, with minimal area and overhead power consumption. This leads to design ofDSMsthat are highly area, power and energy-efficient, suitable for multi-channel biopotential recording systems. We demonstrate a second order, duty-cycled passive integrator based CTDSM in a 65 nm CMOS technology for a 10 kHz biopotential bandwidth. Measurement results show that the fabricated design achieves an SNDR/DR of 56.36/63.1 dB while consuming only 160 nW power with an OSR of 32 and occupies an area of 0.035 mm(2) with a state-of-the-art energy efficiency of 14.9 fJ/conv. In-vitro and in-vivo measurements are provided to further demonstrate the operation of the proposed DSM.
Random Discriminative Projection Based Feature Selection with Application to Conflict Recognition

Computational paralinguistics deals with underlying meaning of the verbal messages, which is of interest in manifold applications ranging from intelligent tutoring systems to affect sensitive robots. The state-of-the-art pipeline of paralinguistic speech analysis utilizes brute-force feature extraction, and the features need to be tailored according to the relevant task. In this work, we extend a recent discriminative projection based feature selection method using the power of stochasticity to overcome local minima and to reduce the computational complexity. The proposed approach assigns weights both to groups and to features individually in many randomly selected contexts and then combines them for a final ranking. The efficacy of the proposed method is shown in a recent paralinguistic challenge corpus to detect level of conflict in dyadic and group conversations. We advance the state-of-the-art in this corpus using the INTERSPEECH 2013 Challenge protocol.
Clinical application guidelines for blood glucose monitoring in China (2022 edition)

Glucose monitoring is an important component of diabetes management. The Chinese Diabetes Society (CDS) has been producing evidence-based guidelines on the optimal use of glucose monitoring since 2011. In recent years, new technologies in glucose monitoring and more clinical evidence, especially those derived from Chinese populations, have emerged. In this context, the CDS organised experts to revise the Clinical application guidelines for blood glucose monitoring in China in 2021. In this guideline, we focus on four methods of glucose monitoring that are commonly used in clinical practice, including capillary glucose monitoring, glycated haemoglobin A1c, glycated albumin, and continuous glucose monitoring. We describe the definitions and technical characteristics of these methods, the factor that may interfere with the measurement, the advantages and caveats in clinical practice, the interpretation of glucose metrics, and the relevant supporting evidence. The recommendations for the use of these methods are also provided. The various methods of glucose monitoring have their strengths and limitations and cannot be replaced by one another. We hope that these guidelines could aid in the optimal application of common methods of glucose monitoring in clinical practice for better diabetes care.
Long-Term Monitoring of Fresco Paintings in the Cathedral of Valencia (Spain) Through Humidity and Temperature Sensors in Various Locations for Preventive Conservation

We describe the performance of a microclimate monitoring system that was implemented for the preventive conservation of the Renaissance frescoes in the apse vault of the Cathedral of Valencia, that were restored in 2006. This system comprises 29 relative humidity (RH) and temperature sensors: 10 of them inserted into the plaster layer supporting the fresco paintings, 10 sensors in the walls close to the frescoes and nine sensors measuring the indoor microclimate at different points of the vault. Principal component analysis was applied to RH data recorded in 2007. The analysis was repeated with data collected in 2008 and 2010. The resulting loading plots revealed that the similarities and dissimilarities among sensors were approximately maintained along the three years. A physical interpretation was provided for the first and second principal components. Interestingly, sensors recording the highest RH values correspond to zones where humidity problems are causing formation of efflorescence. Recorded data of RH and temperature are discussed according to Italian Standard UNI 10829 (1999).
COVID-19 Vaccine as a Potential Triggering Factor for Anti-Glomerular Basement Membrane (GBM) Disease: A Case Report and Literature Review

Coronavirus 2019 (COVID-19) is considered one of the most significant medical pandemics of this century, with high morbidity and mortality associated with the pandemic. The virus was recognized initially as a cause of pneumonia, but subsequent studies showed significant association with gastrointestinal, neurological, and autoimmune diseases. By 2020, several vaccines became available for use, significantly reducing the infection rate. A good safety profile supported most of the studies related to vaccines. However, this area is still under study, and some reports linked the COVID-19 vaccine to the development of thrombocytopenia, thrombosis, Guillain-Barre syndrome, autoimmune diseases, and myocarditis. These side effects need to be reported to VAERS (Vaccine Adverse Event Reporting System). The exact etiology of anti-glomerular basement (Anti-GBM) disease remains unknown, but the disease is thought to be triggered by environmental factors in genetically predisposed individuals. It is considered one of the serious diseases that could lead to permanent kidney impairment if not treated early and adequately. That's why a great effort is being made by health care practitioners to figure out and avoid the risk and triggering factors. Few previously published papers linked the COVID-19 vaccine and the development of anti-GBM disease, which raised concerns about digging more into this area. Herein, we are reporting a case of a patient who developed rapidly progressive glomerulonephritis (RPGN) due to anti-glomerular basement membrane (GBM) antibody disease two days after receiving the second dose of the COVID-19 vaccine.
Complete mitochondrial genome of Schizothorax nukiangensis Tsao (Cyprinidae: Schizothorax)

In this work, we reported the complete mitochondrial genome sequence of the Schizothorax nukiangensis Tsao for the first time. The complete mtDNA genome sequence of S. nukiangensis Tsao was 16 585 bp in length, which contains 22 transfer RNA genes, 2 rRNA genes, 13 protein-coding genes, an origin of light-strand replication (OL) and a control region (D-Loop). The overall base composition of the mitogenome was calculated to be 29.6% for A, 27.0% for C, 17.9% for G and 25.5% for T. The complete mitogenome of the S. nukiangensis Tsao can provide an important data set for further studies on population history, molecular systematics, phylogeography and stock assessment.
Energy saving potential of hybrid membrane and distillation process in butanol purification: Experiments, modelling and simulation

Pervaporation experiments of dilute aqueous butanol solutions were carried out with three PDMS [poly (dimethyl siloxane)] membranes. Based on the experimental results of the best performing membrane a regression for both butanol and water permeability was done in the software R and implemented in a user defined pervaporation unit operation in the software Aspen Custom Modeler. With the implementation of the pervaporation step in Aspen Plus the hybrid pervaporation and distillation purification chain can be simulated in consistent way. Calculation of pervaporation of a 0.5 wt% BuOH-water solution with the experimentally investigated PDMS membrane results in a permeate stream with a concentration of 9 wt% BuOH. Application of membrane distillation resulted in a permeate butanol concentration of only 3 wt% and a considerable higher specific energy demand compared to pervaporation. For product purities of 99 wt% of BuOH a hybrid pervaporation and distillation process saves around 50% of the energy demand compared to state of the art distillation. A sensitivity analysis of the pervaporation step reveals, that for the hybrid pervaporation and distillation process compared to state of the art distillation the energy demand decreases already exceeding 5 wt% BuOH in the permeate stream. (c) 2016 Published by Elsevier B.V.
Squamous cell carcinoma of the tongue: subtypes and morphological features affecting prognosis

Squamous cell carcinoma (SCC) is the most common histological type of mobile tongue carcinoma. The incidence of mobile tongue carcinoma is decreasing in some countries owing to decreasing exposure to risk factors, but it has been reported to be increasing in younger people. The majority of mobile tongue cancers are conventional SCCs. Pathological diagnosis of conventional SCC is relatively easy. However, mobile tongue SCCs involve several subtypes that have distinct pathological features and biological behaviors. Some subtypes are relatively rare, and the pathological subtype influences treatment decision-making. Therefore, the recognition of SCC subtypes is crucial for proper treatment. In this review, we summarize nine SCC subtypes, including conventional SCC and highlight their pathological characteristics. We also report some morphological factors, such as the pattern of invasion, budding, desmoplastic reaction, lymphovascular invasion, and perineural invasion, which could be predictive of prognosis. As some morphological factors are closely associated with prognosis, pathologists may need to evaluate additional factors in pathological reports of near features. In summary, we highlight the basic knowledge of mobile tongue SCC with an emphasis on pathological subtypes, morphological features, and their relationship. We provide information to further elucidate SCC in the oral region.
On Load Balancing via Switch Migration in Software-Defined Networking

Switch-controller assignment is an essential task in multi-controller software-defined networking. Static assignments are not practical because network dynamics are complex and difficult to predetermine. Since network load varies both in space and time, the mapping of switches to controllers should be adaptive to sudden changes in the network. To that end, switch migration plays an important role in maintaining dynamic switch-controller mapping. Migrating switches from overloaded to underloaded controllers brings flexibility and adaptability to the network but, at the same time, deciding which switches should be migrated to which controllers, while maintaining a balanced load in the network, is a challenging task. This work presents a heuristic approach with solution shaking to solve the switch migration problem. Shift and swap moves are incorporated within a search scheme. Every move is evaluated by how much benefit it will give to both the immigration and outmigration controllers. The experimental results show that the proposed approach is able to outweigh the state-of-art approaches, and improve the load balancing results up to approximate to 14% in some scenarios when compared to the most recent approach. In addition, the results show that the proposed work is more robust to controller failure than the state-of-art methods.
Spectral brain signatures of aesthetic natural perception in the α and β frequency bands

During our everyday lives, visual beauty is often conveyed by sustained and dynamic visual stimulation, such as when we walk through an enchanting forest or watch our pets playing. Here, I devised an MEG experiment that mimics such situations: participants viewed 8 s videos of everyday situations and rated their beauty. Using multivariate analysis, I linked aesthetic ratings to 1) sustained MEG broadband responses and 2) spectral MEG responses in the α and β frequency bands. These effects were not accounted for by a set of high- and low-level visual descriptors of the videos, suggesting that they are genuinely related to aesthetic perception. My findings provide the first characterization of spectral brain signatures linked to aesthetic experiences in the real world.NEW & NOTEWORTHY In the real world, aesthetic experiences arise from complex and dynamic inputs. This study shows that such aesthetic experiences are represented in a spectral neural code: cortical α and β activity track our judgments of the aesthetic appearance of natural videos, providing a new starting point for studying the neural correlates of beauty through rhythmic brain activity.