Miracle-dz/UniFAR-FTUs huggingface dataset:
Book-Review - Gauge Theories in Particle Physics - a Practical Introduction

Experimental and theoretical elements - quarks and leptons and the forces between them electromagnetism as a gauge theory the Klein-Gordon and Dirac wave equations and the interpretation of their negative energy solutions quantum field theory quantum electrodynamics - the electromagnetic interactions of spin-O particles forces and particle exchange processes the electromagnetic interactions of spin-1/2 particles deep inelastic electron-nucleon scattering and the quark parton model non-abelian gauge theory an introduction to quantum chromodynamics phenomenology of weak interactions - introduction to weak interactions the hadronic weak current and neutral currents difficulties with weak interaction phenomenology theory of electroweak interactions hidden gauge variance - the U(1) case the Glashow-Salam-Weinberg theory of electroweak interactions.
Mortality and risk factors for COVID-19 in hemodialysis patients: A systematic review and meta-analysis

Introduction: The present study systematically reviewed the clinical features and risk factors in patients undergoing maintenance hemodialysis (MHD) who also acquired coronavirus disease 2019 (COVID-19). More specifically, clinical manifestations, prognosis, and risk factors for death among this population were explored. Method: A literature search using the PubMed, Web of Science, and Embase databases, for articles involving patients with laboratory-confirmed COVID-19 and undergoing MHD published between January 1, 2020, and March 13, 2022, was performed. Random-effects meta-analyses were performed to calculate the weighted mean prevalence and corresponding 95% confidence interval (CI) or weighted means and 95% CI. Heterogeneity among studies was assessed using I2 statistics. Results: Twenty-two studies including 13,191 patients with COVID-19 undergoing MHD were selected. The most common symptoms included fever (53% [95% CI 41%–65%]) and cough (54% [95% CI 48%-60%]); however, 17% (95% CI 11%–22%) of the cases were asymptomatic. In subgroup analysis, the proportion of male patients (65% [95% CI 58%–71%]), and patients with coronary artery disease (30% [95% CI 17%–44%) and chronic obstructive pulmonary disease (9% [95% CI 4%–15%]) was greater in the non-survivor group compared with the survivor group. Furthermore, patients undergoing MHD, who were also positive for COVID-19, exhibited a high mortality rate (24% [95% CI 19%–28%]). Conclusions: MHD patients with COVID-19 may initially present as asymptomatic or with mild symptoms; nevertheless, in this study, these patients exhibited a higher risk for death compared with COVID-19 patients not undergoing MHD. Moreover, male sex and underlying cardiovascular and respiratory diseases increased the mortality risk.
Value of combined detection of serum amyloid A, C-reactive protein and procalcitonin in differential diagnosis of respiratory tract infection in children of China

Abstract Objective To explore the diagnostic value of combined detection of serum amyloid A (SAA), C-reactive protein (CRP) and procalcitonin (PCT) in children with bacteria or non-bacterial respiratory tract infection. Methods 200 children with respiratory tract infections diagnosed in our hospital were included in the study. According to the results of the aetiological examination, they were divided into bacterial infection group and non-bacterial infection group. At the same time, 100 healthy children admitted to the hospital for physical examination during the same period were selected as the healthy subjects control group. Changes in serum SAA, PCT and CRP in three groups were compared. Comparison of a positive rate of the single index and combined detection were performed. Children with bacterial infections were treated with conventional antibiotics. The changes in serum SAA, PCT and CRP in the infection group before and after treatment were compared. The efficacy of SAA, PCT and CRP alone and in combination was compared. Results The serum SAA, PCT and CRP levels in the bacterial infection group were higher than those in the non-bacterial infection group and healthy children, and the differences were statistically significant. The positive detection rates and combined detection rates of serum SAA, PCT and CRP in the bacterial infection group were higher than those in the non-bacterial infection group and the healthy subject's control group. After conventional antibiotic treatment, serum SAA, PCT and CR levels in children with bacterial infection were significantly decreased. Conclusion The combined detection based on SAA, CRP and PCT can effectively identify and diagnose respiratory tract infection in children, providing a certain reference for the promotion of the diagnostic scheme. Key messages Serum SAA, PCT and CRP were highly expressed in children with respiratory tract infection, and the expression level was the highest in children with bacterial pneumonia. The combined detection of serum SAA, CRP and PCT indicators have higher diagnostic efficiency and can effectively make a differential diagnosis of respiratory tract infection in children.
Association between psychological distress and coping strategies among students engaged in online learning

Distant or online learning on digital platforms has become the norm in education worldwide, putting students under immense mental strain. The present study examined the association between psychological distress and coping strategies among students engaged in online learning. This study used a cross-sectional design. A structured questionnaire was sent to each of the 210 university students at two prestigious public and private universities in Bangladesh through email. Data was collected from March 26 to April 27, 2021. Severe psychological distress was found in 55.2 percent of the population. Younger age groups, public university students, students with no self-income, moderate aid from the university in providing resources from home, and students with existing mental health illnesses were significantly associated with psychological distress (p-value<0.05). Among all 14 items of Brief COPE, active coping, using emotional support, and self-blame significantly influenced the psychological distress instrument Kessler-10 (p-value<0.01). Given the perspective of this study, coping strategies alleviate stress and facilitate positive psychological outcomes. Students’ mental health is a prioritized issue that needs more attention. Because of its higher prevalence and adverse consequences, institution authorities should support each student by providing study materials, student loans, and scholarships. Routine screening will allow identifying students going through a difficult time who can get help from experts through counseling.
Acceptability and feasibility of an online version of the Self-Compassion for Healthcare Communities program

ABSTRACT Self-compassion, a way of relating to oneself like a good friend, may be an essential skill for healthcare professionals to develop in order to cope with the stressors of their job and avoid burnout, secondary traumatic stress, and other mental health problems during and after the COVID-19 pandemic. This study examined the acceptability and feasibility of an online version of the 6-session Self-Compassion for Healthcare Communities program (SCHC) during the COVID-19 pandemic in 2020. Similar to in-person studies of the program, participants (n = 37) reported significant increases in self-compassion and mindfulness, and significant decreases in burnout, secondary traumatic stress, depression, and stress from pre to post intervention. Number of sessions attended predicted gains in self-compassion and increases in self-compassion predicted changes in mindfulness, secondary traumatic stress, burnout, depression, and resilience decompression. Online programs such as SCHC may be an accessible way to support healthcare professionals’ mental health even after the pandemic is over.
Improving the CFD modeling of Cross-ventilation in Highly-packed Urban Areas

Computational Fluid Dynamics (CFD) simulations are widely used in many wind-related studies, including cross-ventilation, in urban areas. The accuracy of the CFD models, however, is still a challenging issue for accurate prediction of the complex flow behavior around and inside the buildings. Application of sophisticated CFD models, such as Large Eddy Simulation (LES) and unsteady Reynolds averaged Navier-Stokes (RANS), are generally limited, so many researchers and designers utilize the steady RANS models for design and analysis of cross-ventilation performance in urban areas. The RANS models, however, provide poor results in predicting the cross-ventilation in street canyons. Thus, this study aims to understand and quantify limitations of the steady RANS models for cross-ventilation applications in highly-packed urban areas. To this end, a series of CFD simulations were conducted for a group of buildings, which were arranged in regular and staggered orders with different urban area densities. Both sealed-body and cross-ventilated scenarios were considered in this study while the surface-averaged and local values of the wind pressure were compared with the results from a wind tunnel measurement by Tamura (2012). Furthermore, the possibility of the RANS model improvement was considered using a parameter sensitivity study over the closure coefficients of a RANS model. Therefore, new coefficients for urban area with densities between 0.2 and 0.4 were found to significantly improve the accuracy of the RANS model. Nonetheless, as an interesting finding of this study, for higher values of urban area densities above 0.4, CFD results went outside the expected measurement ranges; this implies that CFD modeling of higher density urban areas should be treated with more cautious and further studies are required to develop a guideline for such applications.
The adverse inflammatory response of tobacco smoking in COVID-19 patients: biomarkers from proteomics and metabolomics

Whether tobacco smoking affects the occurrence and development of coronavirus disease 2019 (COVID-19) is still a controversial issue, and potential biomarkers to predict the adverse outcomes of smoking in the progression of COVID-19 patients have not yet been elucidated. To further uncover their linkage and explore the effective biomarkers, three proteomics and metabolomics databases (i.e. smoking status, COVID-19 status, and basic information of population) from human serum proteomic and metabolomic levels were established by literature search. Bioinformatics analysis was then performed to analyze the interactions of proteins or metabolites among the above three databases and their biological effects. Potential confounding factors (age, body mass index (BMI), and gender) were controlled to improve the reliability. The obtained data indicated that smoking may increase the relative risk of conversion from non-severe to severe COVID-19 patients by inducing the dysfunctional immune response. Seven interacting proteins (C8A, LBP, FCN2, CRP, SAA1, SAA2, and VTN) were found to promote the deterioration of COVID-19 by stimulating the complement pathway and macrophage phagocytosis as well as inhibiting the associated negative regulatory pathways, which can be biomarkers to reflect and predict adverse outcomes in smoking COVID-19 patients. Three crucial pathways related to immunity and inflammation, including tryptophan, arginine, and glycerophospholipid metabolism, were considered to affect the effect of smoking on the adverse outcomes of COVID-19 patients. Our study provides novel evidence and corresponding biomarkers as potential predictors of severe disease progression in smoking COVID-19 patients, which is of great significance for preventing further deterioration in these patients.
Impact of COVID-19 pandemic on hand injuries

ABSTRACT BACKGROUND: The aim of the study was to evaluate etiologies of hand injuries in emergency department (ED), to compare the etiologies of hand injuries at the time of this study with the previous year, to assess whether novel coronavirus-2019 (COVID-19) pandemic affected the treatment decisions, and to investigate the COVID-19 infection rate within the first 14 days after admission. METHODS: A total of 229 patients admitted to ED with hand injury between March 15 and April 30, 2020, were included in the study. The control group consisted of 439 ED admissions with hand injury in the previous year (March 15–April 30, 2019). Data including age, sex, cause of trauma, treatment, and COVID-19 infection status within 14 days after ED admission were compared between groups. RESULTS: The mean age was 32.30±15.63 years in the study group and 30.85±18.54 years in the control group. The number of patients consulted to the surgery department decreased by 52.6% and the number of patients admitted to ED with hand injuries decreased by 47.6% during the pandemic, compared to the previous year (p=0.0001). The incidence of home accidents increased and the glass cuts and penetrating/perforating injuries were the most common causes during the pandemic most of which occurred at home. CONCLUSION: The COVID-19 pandemic-mandated social restrictions led to a significant decrease in the number of ED admissions with hand injuries and the type of injuries. The incidence of home accidents increased with more time spent indoors. This study may be a useful guide for ED admissions of hand injury cases and management planning in the current and future pandemics.
Further delineation of SLC9A3 ‐related congenital sodium diarrhea

Congenital sodium diarrhea (CSD) is a rare enteropathy displaying both broad variability in clinical severity and genetic locus and allelic heterogeneity. Eleven CSD patients were reported so far with SLC9A3 variants that impair the function of the encoded intestinal sodium‐proton exchanger 3 (NHE3).
Interpreting declines in HIV test positivity: an analysis of routine data from Zimbabwe's national sex work programme, 2009–2019

Early diagnosis of HIV is critical for epidemic control. To achieve this, successful testing programmes are essential and test positivity is often used as a marker of their performance. The aim of this study was to analyse trends and predictors of HIV test positivity over time and explore how an understanding of seroconversion rates could build on our interpretation of this indicator among female sex workers in Zimbabwe.
The Human Papillomavirus Type 16 E6 Oncoprotein Activates mTORC1 Signaling and Increases Protein Synthesis (cid:1) †

The mammalian target of rapamycin (mTOR) kinase acts as a cellular rheostat that integrates signals from a variety of cellular signal transduction pathways that sense growth factor and nutrient availability as well as intracellular energy status. It was previously reported that the human papillomavirus type 16 (HPV16) E6 oncoprotein may activate the S6 protein kinase (S6K) through binding and E6AP-mediated degradation of the mTOR inhibitor tuberous sclerosis complex 2 (TSC2) (Z. Lu, X. Hu, Y. Li, L. Zheng, Y. Zhou, H. Jiang, T. Ning, Z. Basang, C. Zhang, and Y. Ke, J. Biol. Chem. 279:35664–35670, 2004; L. Zheng, H. Ding, Z. Lu, Y. Li, Y. Pan, T. Ning, and Y. Ke, Genes Cells 13:285–294, 2008). Our results conﬁrmed that HPV16 E6 expression causes an increase in mTORC1 activity through enhanced phosphorylation of mTOR and activation of downstream signaling pathways S6K and eukaryotic initiation factor binding protein 1 (4E-BP1). However, we did not detect a decrease in TSC2 levels in HPV16 E6-expressing cells. We discovered, however, that HPV16 E6 expression causes AKT activation through the upstream kinases PDK1 and mTORC2 under conditions of nutrient deprivation. We show that HPV16 E6 expression causes an increase in protein synthesis by enhancing translation initiation complex assembly at the 5 (cid:1) mRNA cap and an increase in cap-dependent translation. The increase in cap-dependent translation likely results from HPV16 E6-induced AKT/mTORC1 activation, as the assembly of the translation initiation complex and cap-dependent translation are rapamycin sensitive. Lastly, coexpression of the HPV16 E6 and E7 oncoproteins does not affect HPV16 E6-induced activation of mTORC1 and cap-dependent translation. HPV16 E6-mediated activation of mTORC1 signaling and cap-dependent translation may be a mechanism to promote viral replication under conditions of limited nutrient supply in differentiated, HPV oncoprotein-expressing proliferating cells.
Electricity load forecasting using a deep neural network

Forecasting the daily load demand of an electric utility provider is a complex problem as it is nonlinear and influenced by external factors. Deep learning, machine learning and artificial intelligence techniques have been successfully employed in electric consumption load, financial market, and reliability predictions. In this paper, we propose the use of a deep neural network (DNN) for short-term load forecasting (STLF) to overcome nonlinearity problems and to achieve higher forecasting accuracy. Historical data was collected every 30 minutes for 24 hour periods from the Electricity Generating Authority of Thailand (EGAT). The proposed techniques were tested with cleaned data from 2012 to 2013, where holidays, bridging holidays, and outliers were replaced. The forecasting accuracy is indicated by the mean absolute percentage error (MAPE). In this paper, there are two different training datasets, everyday training dataset which is arranged by day sequentially and same day training dataset which is separated seven groups of day (for e.g., only Monday training is used to forecast Monday). The outcomes of a deep neural network (DNN) are compared with an artificial neural network (ANN) and support vector machines (SVM) with an everyday training dataset. The empirical results reveal that the proposed DNN model outperforms the ANN and SVM models. Moreover, the DNN model trained with same day training datasets provides better performance than a DNN trained with an everyday training dataset for weekends, bridging holidays, and Mondays. Additionally, the DNN using a same day training datasets provides higher accuracies for December and January.
Meaningless gestures or pathway to healing and reconciliation? Comparing the perspectives on political apologies in victim and non‐victim communities in El Salvador, the Republic of Korea and the United Kingdom

Abstract Political apologies have been theorized to play an important role in healing and reconciliation processes in post‐conflict settings. Whether they actually fulfil this function, however, remains unclear as the voices and perspectives of victim communities have largely been underrepresented in research. To address this, we examined the role of apologies that were offered for the El Mozote massacre (El Salvador), the Jeju 4.3 massacres (Republic of Korea) and Bloody Sunday (United Kingdom), according to members of these communities and the broader public. Although we anticipated that victim community members should find the apology more valuable and meaningful and should, therefore, be more positive about its role in healing and reconciliation processes, we found that this varies across countries. This variation could be explained by people's trust in the country's institutions. Across the samples, we found that the apology was seen as a relatively important gesture. For the apology to be perceived as impactful, however, it had to be seen as a meaningful (i.e. sincere) gesture. Our findings suggest that apologies have a role to play in the aftermath of human rights violations, but that it is essential to take the broader context into account.
Unexpected Presence of Blastocystis Subtype 1–3 DNA in Human Vaginal and Sperm Samples Coinfected with Trichomonas vaginalis

There have been few reports on extra-enteric infections by Blastocystis STs and none have been molecularly identified in samples from human reproductive organs. We report for the first time the identification of 3 different subtypes of Blastocystis (ST1–3) in vaginal and sperm samples, from patients infected with Trichomonas vaginalis. Blastocystis STs were identified by PCR-sequencing and by phylogenetic inferences using 28 vaginal swab samples and 7 sperm samples from patients trichomoniasis. Blastocystis STs were identified in 6 of 28 vaginal swabs (21.4%) and in 3 of 7 sperm samples (42.8%). In both biological samples, STs 1–3 were found; one vaginal sample showed subtype co-infection with ST1 and ST3. High genetic variation was observed in the sequences obtained and no specific clustering in the phylogenetic trees was detected. Most of the haplotypes identified were placed far from the main dispersal centers. Our finding suggested that incorrect cleaning of the genital area or a contamination by combination of anal and vaginal intercourse.
Real‐world study on adoption of standard‐of‐care for transplant‐eligible newly diagnosed multiple myeloma patients between 2017 and 2020/2021 across France, Germany, Spain, and Italy

This non‐interventional observational study described the current standard‐of‐care for transplant‐eligible newly diagnosed multiple myeloma (TE‐NDMM) patients in France, Germany, Spain, and Italy, and recorded the evolution in regimen adoption in distinct elements of frontline treatment during 2017–2020/2021.
Fully automated determination of the cervical vertebrae maturation stages using deep learning with directional filters

Introduction We aim to apply deep learning to achieve fully automated detection and classification of the Cervical Vertebrae Maturation (CVM) stages. We propose an innovative custom-designed deep Convolutional Neural Network (CNN) with a built-in set of novel directional filters that highlight the edges of the Cervical Vertebrae in X-ray images. Methods A total of 1018 Cephalometric radiographs were labeled and classified according to the Cervical Vertebrae Maturation (CVM) stages. The images were cropped to extract the cervical vertebrae using an Aggregate Channel Features (ACF) object detector. The resulting images were used to train four different Deep Learning (DL) models: our proposed CNN, MobileNetV2, ResNet101, and Xception, together with a set of tunable directional edge enhancers. When using MobileNetV2, ResNet101 and Xception, data augmentation is adopted to allow adequate network complexity while avoiding overfitting. The performance of our CNN model was compared with that of MobileNetV2, ResNet101 and Xception with and without the use of directional filters. For validation and performance assessment, k-fold cross-validation, ROC curves, and p-values were used. Results The proposed innovative model that uses a CNN preceded with a layer of tunable directional filters achieved a validation accuracy of 84.63%84.63% in CVM stage classification into five classes, exceeding the accuracy achieved with the other DL models investigated. MobileNetV2, ResNet101 and Xception used with directional filters attained accuracies of 78.54%, 74.10%, and 80.86%, respectively. The custom-designed CNN method also achieves 75.11% in six-class CVM stage classification. The effectiveness of the directional filters is reflected in the improved performance attained in the results. If the custom-designed CNN is used without the directional filters, the test accuracy decreases to 80.75%. In the Xception model without the directional filters, the testing accuracy drops slightly to 79.42% in the five-class CVM stage classification. Conclusion The proposed model of a custom-designed CNN together with the tunable Directional Filters (CNNDF) is observed to provide higher accuracy than the commonly used pre-trained network models that we investigated in the fully automated determination of the CVM stages.