Miracle-dz/UniFAR-FTUs huggingface dataset:
Network-Based Identification and Prioritization of Key Regulators of Coronary Artery Disease Loci

Objective—Recent genome-wide association studies of coronary artery disease (CAD) have revealed 58 genome-wide significant and 148 suggestive genetic loci. However, the molecular mechanisms through which they contribute to CAD and the clinical implications of these findings remain largely unknown. We aim to retrieve gene subnetworks of the 206 CAD loci and identify and prioritize candidate regulators to better understand the biological mechanisms underlying the genetic associations. Approach and Results—We devised a new integrative genomics approach that incorporated (1) candidate genes from the top CAD loci, (2) the complete genetic association results from the 1000 genomes-based CAD genome-wide association studies from the Coronary Artery Disease Genome Wide Replication and Meta-Analysis Plus the Coronary Artery Disease consortium, (3) tissue-specific gene regulatory networks that depict the potential relationship and interactions between genes, and (4) tissue-specific gene expression patterns between CAD patients and controls. The networks and top-ranked regulators according to these data-driven criteria were further queried against literature, experimental evidence, and drug information to evaluate their disease relevance and potential as drug targets. Our analysis uncovered several potential novel regulators of CAD such as LUM and STAT3, which possess properties suitable as drug targets. We also revealed molecular relations and potential mechanisms through which the top CAD loci operate. Furthermore, we found that multiple CAD-relevant biological processes such as extracellular matrix, inflammatory and immune pathways, complement and coagulation cascades, and lipid metabolism interact in the CAD networks. Conclusions—Our data-driven integrative genomics framework unraveled tissue-specific relations among the candidate genes of the CAD genome-wide association studies loci and prioritized novel network regulatory genes orchestrating biological processes relevant to CAD.
Business Analytics Contribution in the Growth of Indian Digital Business

Use of Business analytics in business will increase productivity and efficiency of a business entity. Business analytics has made a significant impact in various business sectors across the world. India being a developing economy can make use of business analytics in developing all its sectors. The present study explores the current usage and its future usage of business analytics in the various sectors of the Indian economy. The researcher has considered the secondary data to analyse the penetration of business analytics in various sectors of India. It is observed that sectors like IT, Travel and transport, Pharma and healthcare and retail and e-commerce show a positive growth in the use of business analytics while sectors like FMCG, Telecom, Engineering and manufacturing and energy & utility have shown a negative growth in use of business analytics in India during the period of study. However, there is a potential growth in the use of business analytics across various sectors in India, since there is a huge unexplored market available in India.
Scientific Realism and the Stratagema de Divide et Impera

In response to historical challenges, advocates of a sophisticated variant of scientific realism emphasize that theoretical systems can be divided into numerous constituents. Setting aside any epistemic commitment to the systems themselves, they maintain that we can justifiably believe those specific constituents that are deployed in key successful predictions. Stathis Psillos articulates an explicit criterion for discerning exactly which theoretical constituents qualify. I critique Psillos's criterion in detail. I then test the more general deployment realist intuition against a set of well-known historical cases, whose significance has, I contend, been overlooked. I conclude that this sophisticated form of realism remains threatened by the historical argument that prompted it. 1. A criterion for scientific realism2. Assessing the criterion3. A return to the crucial insight: responsibility4. A few case studies5. Assessing deployment realism A criterion for scientific realism Assessing the criterion A return to the crucial insight: responsibility A few case studies Assessing deployment realism
Pre‐B and pre‐T‐cell receptors: conservation of strategies in regulating early lymphocyte development

Summary: Early lymphocyte development is characterized by the regulated activity of the V(D)J recombinase and the positive and negative selection of cells based on the structure of their assembled antigen receptor genes. Developing B and T cells use remarkably similar signaling complexes, the pre‐B‐cell receptor (pre‐BCR) and the pre‐T‐cell receptor (pre‐TCR) respectively, to monitor the progress of antigen receptor gene assembly. This review will compare and contrast the regulation and activities of the pre‐BCR and pre‐TCR signaling complexes. In addition, we will consider a number of critical but as yet unanswered questions prompted by such an analysis.
A bidirectional relationship between physical activity and executive function in older adults

Physically active lifestyles contribute to better executive function. However, it is unclear whether high levels of executive function lead people to be more active. This study uses a large sample and multi-wave data to identify whether a reciprocal association exists between physical activity and executive function. Participants were 4555 older adults tracked across four waves of the English Longitudinal Study of Aging. In each wave executive function was assessed using a verbal fluency test and a letter cancelation task and participants reported their physical activity levels. Fixed effects regressions showed that changes in executive function corresponded with changes in physical activity. In longitudinal multilevel models low levels of physical activity led to subsequent declines in executive function. Importantly, poor executive function predicted reductions in physical activity over time. This association was found to be over 50% larger in magnitude than the contribution of physical activity to changes in executive function. This is the first study to identify evidence for a robust bidirectional link between executive function and physical activity in a large sample of older adults tracked over time.
Assessing quality in early childhood education and care: sustained shared thinking and emotional well-being (SSTEW) scale for 2–5-year-olds provision

Book synopsis: The Sustained Shared Thinking and Emotional Well-being (SSTEW) Scale is designed to consider some of the intentional and relational pedagogical strategies strongly associated with child outcomes. It considers practice that supports children aged between 2 and 5 years of age in developing skills in sustained shared thinking and emotional well-being as well as developing strong relationships, effective communication and aspects of self-regulation. It is designed to be used for research, self-evaluation and improvement, audit and regulation. Using the SSTEW Scale alongside other environment scales (including ECERS-E, ECERS-R or ITERS-R) gives users a more complete picture of what high-quality early childhood education and care can look like. It is aspirational in that it considers high quality pedagogy and practice. It can be used by researchers, heads of centres, managers, teaching staff and practitioners, as well as advisory staff and in professional development.
Is marriage a dying institution in South Africa? Exploring changes in marriage in the context of ilobolo payments

abstract This article describes racial differences in marriage rates in post-apartheid South Africa and considers one possible reason for these differences related to the traditional practice of ilobolo among African families. We use nationally representative micro data to document very low and declining marriage rates among young Africans, large differences in marriage rates between Africans and whites, as well as rising rates of cohabitation, particularly among young African women and men. We then review the payment of bride wealth in this context, drawing on the historical literature as well as on popular media resources and quantitative data collected in the South African Social Attitudes Survey of 2005, to explore attitudes towards ilobolo as practised in contemporary African society.
A fast based on mathematical morphology smoothing approach in level set methods

This paper presents a novel narrow band smoothing framework for level set methods. This framework is based on mathematical morphology operators. Previous methods such as straightforward ways and partial differential equation methods are available to smooth narrow band, but they are accompanied with extensive computational cost or a great deal of numerical iterations. The proposed scheme in this paper considers both smoothing accuracy and real-time application. Through a binary mirror image, complicated narrow band smoothing procedure is reduced to usual noise filtering, where all the unreasoned points in the grids correspond to pepper-salt noises. The filtering method also performs a global analysis on the front, and makes results more desirable. Furthermore, this paper also presents a new reconstruction approach. This approach can be naturally embedded into the proposed smoothing framework. Experimental results on several images show that this method has an excellent performance in terms of accuracy and velocity. The computation time also make it suitable for real-time application in active contour evolution.
Isolation and characterization of monoclonal antibodies directed against subunits of human RNA polymerases I, II, and III.

Human nuclei contain three different RNA polymerases: polymerases I, II, and III. Each polymerase is a multi-subunit enzyme with 12-17 subunits. The localization of these subunits is limited by the paucity of antibodies suitable for immunofluorescence. We now describe eight different monoclonal antibodies that react specifically with RPB6 (also known as RPA20, RPB14.4, or RPC20), RPB8 (RPA18, RPB17, or RPC18), RPC32, or RPC39 and which are suitable for such studies. Each antibody detects one specific band in immunoblots of nuclear extracts; each also immunoprecipitates large complexes containing many other subunits. When used for immunofluorescence, antibodies against the subunits shared by all three polymerases (i.e., RPB6, RPB8) gave a few bright foci in nucleoli and nucleoplasm, as well as many fainter nucleoplasmic foci; all the bright foci were generally distinct from speckles containing Sm antigen. Antibodies against the two subunits found only in polymerase III (i.e., RPC32, RPC39) gave a few bright and many faint nucleoplasmic foci, but no nucleolar foci. Growth in two transcriptional inhibitors-5, 6-dichloro-1-beta-d-ribofuranosylbenzimidazole and actinomycin D-led to the redistribution of each subunit in a characteristic manner.
Base Station Deployment for Path-Aware UAV Communications

In this study, we consider a UAV communication system characterized by a predefined path. This paper introduces a path model consisting of consecutive path points and establishes performance metrics at the path level. The defined metrics include the average achievable rate for the path and the number of handovers occurring along the trajectory. Considering that these metrics depend on the positions of base stations, our goal is to determine the placement of base stations that maximizes the average achievable rate within a specified handover number. To achieve this objective, an algorithm is proposed to find optimal locations for base stations. This algorithm adopts a strategy of dividing regions and alternately exploring the positions of base stations to determine their optimal locations. Simulation results demonstrate that the proposed algorithm produces performance that closely approximates optimal results under the weak constraint of handover.
Contributions of classroom discourse to what content students learn during curriculum enactment.

This case study investigates how classroom discourse contributed to what content students learned during a Grade 8 social studies unit taught in two different classrooms. It used a purposive sample and entailed 8 weeks of nonparticipant observation of each teacher-class enactment of a unit about ancient Egyptian society. Field notes and lesson transcripts were coded to inductively identify kinds of messages, forms of discourse, patterning of forms of discourse associated with curriculum events, and system of discourse for each enactment of the unit. There were significant quantitative differences between and within classrooms in the content recalled from curriculum events. These content-learning differences were associated with the forms of discourse used within curriculum events and the system of classroom discourse that evolved during a unit.
Políticas públicas en seguridad social para la protección de los trabajadores informales en Colombia

El crecimiento de la economia informal mundial ha generado el no acceso de los trabajadoresinformales a los mecanismos formales de seguridad social. El objetivo de este articulo es revisarlas politicas publicas en seguridad social dirigidas a proteger a los trabajadores informales enColombia y analizarlas a la luz de la situacion de otros paises de America Latina. Se realizo unarevision bibliografica con analisis documental, en el contexto del Sistema General de SeguridadSocial, y se analizo comparativamente con otros paises latinoamericanos. Se concluye que sibien existen politicas para proteger a los trabajadores informales, la afiliacion a seguridad socialsigue siendo baja y que esta situacion no difiere sustancialmente de la de los demas paisesde America Latina. Se deben generar mecanismos alternativos de aseguramiento para estapoblacion, con responsabilidad estatal y que promuevan formas de asociacion y organizacionde las personas ocupadas en este sector.
The impact of vitamin A supplementation on mortality inequalities among children in Nepal.

OBJECTIVE This paper examines gender, caste and economic differentials in child mortality in the context of a cluster-randomized trial of vitamin A distribution, in order to determine whether or not the intervention narrowed these differentials. DESIGN The study involved secondary analysis of data from a placebo-controlled randomized field trial of vitamin A supplements. The study took place between 1989-1991 in rural Sarlahi District of Nepal, with 30,059 children age 6 to 60 months. The main outcome measures were differences in mortality between boys and girls, between highest Hindu castes and others, and between the poorest quintile and the four other quintiles. RESULTS Without vitamin A, girls in rural Nepal experience 26.1 deaths per 1000, which is 8.3 deaths more than the comparison population of boys. With vitamin A the mortality disadvantage of girls is nearly completely attenuated, at only 1.41 additional deaths per 1000 relative to boys. Vitamin A supplementation also narrowed mortality differentials among Hindu castes, but did not lower the concentration of mortality across quintiles of asset ownership. The vitamin A-related attenuation in mortality disadvantage from gender and caste is statistically significant. CONCLUSIONS We conclude that universal supplementation with vitamin A narrowed differentials in child death across gender and caste in rural Nepal. Assuring high-coverage vitamin A distribution throughout Nepal could help reduce inequalities in child survival in this population.
Further analyses support the association between light eye color and alcohol dependence

Further Analyses Support the Association Between Light Eye Color and Alcohol Dependence Arvis Sulovari, Henry R. Kranzler, Lindsay A. Farrer, Joel Gelernter, and Dawei Li* Department of Microbiology and Molecular Genetics, University of Vermont, Burlington, Vermont Cell, Molecular and Biomedical Sciences Graduate Program, University of Vermont, Burlington, Vermont Department of Psychiatry, University of Pennsylvania School of Medicine and VISN 4 MIRECC, Philadelphia VAMC, Philadelphia, Pennsylvania Departments of Medicine (Biomedical Genetics), Neurology, Ophthalmology, Genetics & Genomics, Biostatistics, and Epidemiology, Boston University Schools of Medicine and Public Health, Boston, Massachusetts Department of Psychiatry, School of Medicine, Yale University, New Haven, Connecticut Department of Genetics, School of Medicine, Yale University, New Haven, Connecticut VA Connecticut Healthcare Center, West Haven, Connecticut and Department of Neurobiology, Yale University School of Medicine, New Haven, Connecticut Department of Computer Science, University of Vermont, Burlington, Vermont Neuroscience, Behavior, and Health Initiative, University of Vermont, Burlington, Vermont
Fusing AraBERT and Graph Neural Networks for Enhanced Arabic Text Classification

Text classification is a fundamental task in natural language processing, and has been widely studied for various languages. However, Arabic text classification is challenging due to the complexity of Arabic (i.e., rich morphological structure), high degree of ambiguity, and optional diacritics in the writing system. Large-scale pre-trained contextualized models (e.g., AraBERT) can successfully capture semantics in the local context. On the other hand, graph-based models could capture the global context by incorporating long-distance semantics. A text classification model combining the local and global context can enhance classifier performance for highly complex and ambiguous languages. In this work, we introduce the Arabic BERT Graph Convolutional Network (AraBERT-GCN), that can leverage the advantage of using large-scale pre-trained models alongside graph convolutional networks. Experimental results show that AraBERT-GCN outperforms the state-of-the-art (SOTA) on our Arabic text datasets.
Treatment of Escape-Maintained Behavior with Positive Reinforcement: The Role of Reinforcement Contingency and Density

Functional analyses suggested that the disruptive behavior of three preschool children was maintained by escape from demands. While keeping the escape contingency intact, we conducted (a) a density analysis in which the children earned preferred items for task completion according to two schedules that varied in reinforcement density, and (b) a contingency analysis in which preferred items were delivered either contingent on task completion or provided noncontingently. Edible delivery (regardless of density or contingency) without escape extinction resulted in clinically significant decreases in the disruptive behavior of one child, and consistent but nonclinically significant reductions for a second child. An increase in compliance was observed for all three children. No effects of reinforcement density were detected at the parameters manipulated in this study, and no differences were observed between contingent and noncontingent reinforcement conditions. Escape extinction was eventually implemented with two children, and was effective with one of them. Additional interventions (instructional fading and embedding) were required to reduce the remaining child’s rate of disruptive behavior. Our results suggest that noncontingent delivery of preferred items may be effective in decreasing escape-maintained behavior and promoting compliance for some children.
Self-Supervised Training for Bearing Fault Diagnosis via Momentum Contrast Learning

With the development of modern industry, data-driven intelligent fault diagnosis has become increasingly popular. The conflict between the need for large amounts of data and the high cost of manual labeling has led researchers to focus on how to better utilize the data itself to reduce costs. In the case of vibration signals, factors such as the category and severity of failure, mechanical operating environment, bearing operating speed, and compound failures can influence them in real environments. These excessive uncontrollable factors make datasets collected from industrial environments nearly unusable. In this paper, we address this issue by introducing momentum contrast. The model is trained by treating all samples except the current one as negative samples and comparing them with positive sample. This approach avoids the need to know the number of fault categories in the dataset in advance. Based on this idea, we conducted experimental validation and found that the pre-trained model possesses high classification accuracy after fine-tuning.
Development of a YOLO-Based Model for Bird Droppings Occlusion Detection on Photovoltaic

The obstruction of bird droppings in photovoltaic power plants can cause phenomena such as hotspots on the solar panels and a decrease in power generation. To address the problem of slow detection rates and high false detection rates caused by bird droppings, which are often small targets, a bird droppings detection method called YOLOv8-NCS (YOLOv8-based method for bird droppings detection in photovoltaic arrays) is proposed. In order to achieve fast detection and localization of small targets in complex scenes, this algorithm first introduces the RFBNet feature extraction network on the basis of YOLOv8 to achieve simple and fast multi-scale feature fusion, thereby enhancing the detection ability of small targets. Secondly, to reduce the detection load of the unmanned aerial vehicle (UAV) detection system, the WIoU loss function is adopted. Finally, the NAM (non-local attention module) attention mechanism is introduced in the C2f module to better capture the dependencies between sequences and reduce background interference, thereby improving the ability to resist background interference. Experimental results show that compared to YOLOv5, YOLOv7, SSD, Faster-rcnn and CenterNet, the proposed YOLOv8-NCS achieves higher accuracy and detection speed on the bird droppings dataset in photovoltaic arrays, with precision and recall reaching 93.18% and 91.71% respectively.
Differential conditioning and long-term olfactory memory in individual Camponotus fellah ants

SUMMARY Individual Camponotus fellah ants perceive and learn odours in a Y-maze in which one odour is paired with sugar (CS+) while a different odour (CS–) is paired with quinine (differential conditioning). We studied olfactory retention in C. fellah to determine whether olfactory learning leads to long-term memory retrievable 24 h and 72 h after training. One and 3 days after training, ants exhibited robust olfactory memory through a series of five successive retention tests in which they preferred the CS+ and stayed longer in the arm presenting it. In order to determine the nature of the associations memorized, we asked whether choices within the Y-maze were driven by excitatory memory based on choosing the CS+ and/or inhibitory memory based on avoiding the CS–. By confronting ants with a novel odour vs either the CS+ or the CS– we found that learning led to the formation of excitatory memory driving the choice of the CS+ but no inhibitory memory based on the CS– was apparent. Ants even preferred the CS– to the novel odour, thus suggesting that they used the CS– as a contextual cue in which the CS+ was embedded, or as a second-order cue predicting the CS+ and thus the sugar reward. Our results constitute the first controlled account of olfactory long-term memory in individual ants for which the nature of associations could be precisely characterized.