Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Risk Profiles Identify Different Molecular Etiologies for Glioma

Purpose: Genome-wide association studies have recently identified single-nucleotide polymorphisms (SNP) in five loci at 5p15.33 (rs2736100, TERT), 8q24.21 (rs4295627, CCDC26), 9p21.3 (rs4977756, CDKN2A/CDKN2B), 20q13.33 (rs6010620, RTEL1), and 11q23.3 (rs498872, PHLDB1) to be associated with glioma risk. Because gliomas are heterogeneous in histology, molecular alterations, and clinical behavior, we have investigated these polymorphisms for potential correlations with tumor histology and patient survival. Experimental Design: We studied the relationship between SNPs and glioma subtype in two large patient cohorts from France and Germany, totaling 1,577 patients, as well as the relationship between SNP genotype and overall survival. Results: In both cohorts, the frequencies of rs2736100 and rs6010620 risk genotypes were highly correlated with high-grade disease (P < 0.001), whereas rs4295627 and rs498872 risk genotypes were inversely related to tumor grade (P < 0.001). These data show that genetic variations at these loci have subtype-specific effects on the risk of developing glioma. In contrast, the rs4977756 genotype was not correlated with tumor grade, consistent with the causal variant having a generic influence on glioma development. None of the five SNPs was associated with prognosis independent of tumor grade. Conclusions: Our findings provide novel insight into etiologic pathways in the different glioma subtypes. Clin Cancer Res; 16(21); 5252–9. ©2010 AACR.
Cardiogenesis and the Complex Biology of Regenerative Cardiovascular Medicine

The heart is a complex organ system composed of a highly diverse set of muscle and nonmuscle cells. Understanding the pathways that drive the formation, migration, and assembly of these cells into the heart muscle tissue, the pacemaker and conduction system, and the coronary vasculature is a central problem in developmental biology. Efforts to unravel the biological complexity of in vivo cardiogenesis have identified a family of closely related multipotent cardiac progenitor cells. These progenitors must respond to non–cell-autonomous signaling cues to expand, differentiate, and ultimately integrate into the three-dimensional heart structures. Coupling tissue-engineering technologies with patient-specific cardiac progenitor biology holds great promise for the development of human cell models of human disease and may lay the foundation for novel approaches in regenerative cardiovascular medicine.
Acute UV Irradiation Increases Heparan Sulfate Proteoglycan Levels in Human Skin

Glycosaminoglycans are important structural components in the skin and exist as various proteoglycan forms, except hyaluronic acid. Heparan sulfate (HS), one of the glycosaminoglycans, is composed of repeated disaccharide units, which are glucuronic acids linked to an N-acetyl-glucosamine or its sulfated forms. To investigate acute ultraviolet (UV)-induced changes of HS and HS proteoglycans (HSPGs), changes in levels of HS and several HSPGs in male human buttock skin were examined by immunohistochemistry and real-time quantitative polymerase chain reaction (qPCR) after 2 minimal erythema doses (MED) of UV irradiation (each n = 4-7). HS staining revealed that 2 MED of UV irradiation increased its expression, and staining for perlecan, syndecan-1, syndecan-4, CD44v3, and CD44 showed that UV irradiation increased their protein levels. However, analysis by real-time qPCR showed that UV irradiation did not change mRNA levels of CD44 and agrin, and decreased perlecan and syndecan-4 mRNA levels, while increased syndecan-1 mRNA level. As HS-synthesizing or -degrading enzymes, exostosin-1 and heparanase mRNA levels were increased, but exostosin-2 was decreased by UV irradiation. UV-induced matrix metalloproteinase-1 expression was confirmed for proper experimental conditions. Acute UV irradiation increases HS and HSPG levels in human skin, but their increase may not be mediated through their transcriptional regulation.
Mediating role of organisation commitment in the relationship between job satisfaction and organisational citizenship behaviour: a study of Indian IT professionals

The present study was conducted to explore the effect of job satisfaction and organisational commitment on the four dimensions of organisational citizenship behaviour. These dimensions are interpersonal helping, individual initiative, personal industry and loyal boosterism. The study further aimed to see the mediating role of organisational commitment in the relationship of job satisfaction and the above mentioned dimensions of organisational citizenship behaviour. Data was collected from Indian IT professionals using a structured questionnaire comprising of standard scales for job satisfaction, organisational commitment and organisational citizenship behaviour. The results show a positive relationship between job satisfaction, organisational commitment and various dimensions of organisational citizenship behaviour. Further, Sobel test of mediation results show that organisational commitment mediates the relationship between job satisfaction and three dimensions of OCB, i.e., interpersonal helping, individual initiative and loyal boosterism. The findings have important implications for human resource development.
The Environmental Quality Evaluation Based on BP Neural Network and PSO and Case Study

Using particle swarm optimization (PSO) to optimize BP neural network model is proposed in this paper. The new model is more quickly and accurate. The basic idea of this model is: Firstly PSO is used to optimize the BP neural network's initialized weights, an optimized result is got; then based on the optimized result the BP neural network is used for further optimization. We can use this model for the environmental quality evaluation of Qinhuangdao Port regional. Finally we can get exactly appraise, this can be direct the environmental protection.
A Cubic Non-Isolated High Step-Up DC-DC Converter Suitable for Distributed Applications

This study presents a novel cubic step-up DC-DC converter that offers a substantial voltage gain. It is well-suited for applications requiring high voltage amplification at low-duty cycles, such as a fuel cell step-up converter. Furthermore, the converter can achieve a compact form factor due to the absence of a transformer. In addition, there is a common ground between the input and the output. The equations describing the converter have been derived, and both ideal and non-ideal conditions have been employed to analyze the converter. The non-ideal voltage gain, as well as its associated losses, have been discussed. Simulations are carried out to validate the extracted equations, and the results are presented.
Improving Storage Concepts for Semantic Models and Ontologies

Ontologies are more commonly used today but still little consideration is given of how to efficiently store them. The proposed approach is built on reliable and efficient relational database management systems (RDBMS). It can be easily implemented for other systems and due to its vendor independence existing data can be migrated from one RDBMS to another relatively easy.
Online Q&A for Machine Learning Courses Based on Formula Recognition

Mathematical formulas are ubiquitous in courses such as Machine Learning. Understanding these formulas is the primary challenge for studying of students. If a searchable knowledge base can be built for these formulas, it will help students learn. Accurate identification of these formulas is an important step in building and querying the knowledge base. However, mathematical formulas have complex two-dimensional and nested structures, which makes them inconvenient to search like ordinary text. This paper employs Faster R-CNN to detect regions containing mathematical formulas and improves its backbone network, anchor box dimensions, and pre-training network to make it more accurate and efficient in identifing these formulas. Furthermore, in order to enhance the features and meaningful representation of mathematical formulas in the input image, we introduce the distance transformation. Finally, comparative experiments were conducted on the publicly dataset GTDB. Our proposed approach achieved recognition rates of 91.22% and 85.74% for isolated and hybrid formulas detection.
Self-Determination for Students with Disabilities: Views of Parents and Teachers

Parents and general and special education teachers of high school students with high-and low-incidence disabilities were surveyed about their views on self-determination. Factor analyses of parent data yielded three factors: student participation in individualized education program (IEP) meetings, teaching self-determination, and students' opportunity to make choices and express interests. Analysis of teacher data yielded two factors: familiarity with self-determination and students' opportunity to learn and practice self-determination. Parents strongly supported participation in IEP meetings and the teaching of self-determination. Teachers slightly agreed that they were familiar with self-determination and that students had the opportunity to learn and apply these skills. Students' instructional program mediated parents' beliefs. Interactions between teacher type, incidence of disability, instructional program, and teaching experience mediated teacher beliefs.
Efficient resource allocation for mobile social networks in D2D communication underlaying cellular networks

With the fast development of mobile terminals and wireless communication networks, mobile social networks (MSNs) play an important role in everyday lives to access social activities. However, most research on MSNs typically focuses on the relations of the users' physical location, but not make sufficient use of social ties. Consequently, in this paper, we consider a scenario of MSNs with online social networks and offline Device-to-Device (D2D) communication underlaying cellular networks, and study the problem of data dissemination to the mobile users under the constraint of limited spectrum resources. We first present a novel approach to formulate the social relationships for the offline mobiles by comparing the similarity of mobile users' social activities with the Bayesian model. And then we realize efficient data propagation using coalitional graph game. Finally, we provide simulation results to verify effectiveness of our studies.
An Enhanced Qualitative Evaluation of User-Generated Online Gaming Videos

In recent times, there have been notable advancements in the field of virtual reality (VR) and augmented reality (AR). These technological developments have facilitated the generation of immersive content, hence raising concerns among both consumers and production organizations over the necessity for superior quality materials that provide a deeply engaging experience. According to this, researchers are now more focused on contributing to many disciplines of computer vision due to deep learning's current record-breaking success across several artificial intelligence areas. A crucial part of guaranteeing end-users' watching experiences is quality evaluation of User Generated Content (UGC) videos. The increased popularity of UGC videos for games, which has benefited from the fast expansion of the digital game business, has sped up the advancement of perceptual video quality assessment (VQA) models particularly for gaming videos. The suggested advanced spatial Visual Question Answering (VQA) model in the research utilizes a spatial feature extraction system that is trained to continuously learn the representation of spatial features with an emphasis on quality, using raw pixel data from the video frames. This is done in order to address the issue. In order to quantify the temporal-related aberrations that the spatial features are unable to predict, we additionally extract the motion features. The suggested model, which has a low computational cost, extracts motion data from dense frames with a very low spatial resolution using extremely sparse frames for spatial features. The experimental findings highlight the efficiency of the proposed model by showing that it performs well on well-known LIVE-VQA datasets.
A malformação do bebé: Vivências psicológicas do casal

The relationship between mother and infant is progressively set since pre-birth. Both parents replenish the pregnancy with countless expectations and ideals about the new baby. So, a diagnosis of fetal malformation obviously raises a great parental disappointment and disbelief, forcing them to mourn an imagined baby. This communication seeks to deepen the subject of fetal malformation having in view the psychological and emotional responses of the parents concerning not only the impact of an unfavourable diagnosis but also the whole process of adaptation they have to face. This communication also intends to develop and obtain a deeper understanding of the health workers role this complex area, confronting the several theories with the clinical practice. As a matter of fact it is ever more possible to detect in-uterus malformations enabling the parents the information thereof, thus rendering absolutely necessary the of well informed and expert health technicians ready to deal with these situations.
Mining and Visualizing Visited Trails in Web-Based Educational Systems

A data mining and visualization tool for the discovery of student trails in web-based educational systems is presented and described. The tool uses graphs to visualize results, allowing non-expert users, such as course instructors, to interpret its output. Several experiments have been conducted, using real data collected from a web-based intelligent tutoring system. The results of the data mining algorithm can be adjusted by tuning its parameters or filtering to concentrate on specific trails, or to focus only on the most significant paths.
SOCIAL WITHDRAWAL BEHAVIOR IN INSTITUTIONALIZED TODDLERS: INDIVIDUAL, EARLY FAMILY AND INSTITUTIONAL DETERMINANTS

Eighty-five Portuguese children, aged 12 to 30 months, placed in residential institutions were assessed to investigate the influence of variations in the institutionalization experience of social withdrawal behavior, after taking into account potentially confounding individual characteristics and pre-admission experiences. In light of the limited attention in institutionalization research on social withdrawal, the determinants of the identified predictors of withdrawal symptoms also were examined. Current quality of care experienced in the institution, operationalized in terms of the absence (vs. presence) of a preferred attachment relationship, predicted social withdrawal, such that absence of such a relationship forecasted greater withdrawal. Moreover, existence of a preferred attachment relationship was itself predicted by better child socioemotional functioning, greater caregiver sensitive-responsiveness, and better quality of individualized care provided by the staff. © 2013 Michigan Association for Infant Mental Health.
Anaerobicity Prepares Saccharomyces cerevisiae Cells for Faster Adaptation to Osmotic Shock

ABSTRACT Yeast cells adapt to hyperosmotic shock by accumulating glycerol and altering expression of hundreds of genes. This transcriptional response of Saccharomyces cerevisiae to osmotic shock encompasses genes whose products are implicated in protection from oxidative damage. We addressed the question of whether osmotic shock caused oxidative stress. Osmotic shock did not result in the generation of detectable levels of reactive oxygen species (ROS). To preclude any generation of ROS, osmotic shock treatments were performed in anaerobic cultures. Global gene expression response profiles were compared by employing a novel two-dimensional cluster analysis. The transcriptional profiles following osmotic shock under anaerobic and aerobic conditions were qualitatively very similar. In particular, it appeared that expression of the oxidative stress genes was stimulated upon osmotic shock even if there was no apparent need for their function. Interestingly, cells adapted to osmotic shock much more rapidly under anaerobiosis, and the signaling as well as the transcriptional response was clearly attenuated under these conditions. This more rapid adaptation is due to an enhanced glycerol production capacity in anaerobic cells, which is caused by the need for glycerol production in redox balancing. Artificially enhanced glycerol production led to an attenuated response even under aerobic conditions. These observations demonstrate the crucial role of glycerol accumulation and turgor recovery in determining the period of osmotic shock-induced signaling and the profile of cellular adaptation to osmotic shock.
Natural User Interface (NUI): A Case Study of a Video Based Interaction Technique for a Computer Game

To compare the advantages and disadvantages of a Natural User Interface [1] a field study was carried out. During five days of the largest computer fair in Switzerland four different computer stations with (1) a command language, (2) a mouse, (3) a touch screen, and (4) a Digital Playing Desk (DPD) interface was presented for public use. In this version of the DPD the user has to play a board game by moving a real chip on a virtual playing field against a virtual player. The task was to win the computer game Go-bang. The reactions of the virtual player were simulated by emoticons as colored comic strip pictures with a corresponding sound pattern. We investigated the effects of these four different interaction techniques with an inquiry with a questionnaire. Results of the inquiry: 304 visitors rated the usability of all four stations on a bipolar scale. The touch screen station was rated as the easiest to use interaction technique, followed by the mouse and DPD interface; the tail-light was the command language interface. One very important result was a significant correlation between age and DPD usability. This correlation means that older people prefer significantly more a graspable user interface in form of the DPD than younger people.
Scriptclud.com: Content Clouds for Screenplays

To initiate my research into feature film screenplay content analytics and visualization, I designed and made available for public use the Scriptcloud website at www.scriptcloud. com. The website enables screenwriters to upload a screenplay text file and create a visual content cloud - similar to a tag cloud - from the textual content of the screenplay. The user can upload as many screenplays as they wish and also define additional custom scriptclouds from the same uploaded screenplay file either by defining specific keywords to include or specific keywords to exclude in the generated cloud.generated cloud.
Multi-step Loading of Human Minichromosome Maintenance Proteins in Live Human Cells*

Background: MCM2–7 loading onto chromatin licenses origins for replication. Results: MCMs exhibit transient interactions with chromatin in late mitosis, stable binding in G1 phase and increased loading in late G1 phase. Conclusion: Multilevel regulation of MCM2–7 loading to chromatin occurs during mitosis and preceding the G1/S phase transition. Significance: The dynamics of the DNA licensing system within live human cells reveal multiple control points. Once-per-cell cycle replication is regulated through the assembly onto chromatin of multisubunit protein complexes that license DNA for a further round of replication. Licensing consists of the loading of the hexameric MCM2–7 complex onto chromatin during G1 phase and is dependent on the licensing factor Cdt1. In vitro experiments have suggested a two-step binding mode for minichromosome maintenance (MCM) proteins, with transient initial interactions converted to stable chromatin loading. Here, we assess MCM loading in live human cells using an in vivo licensing assay on the basis of fluorescence recovery after photobleaching of GFP-tagged MCM protein subunits through the cell cycle. We show that, in telophase, MCM2 and MCM4 maintain transient interactions with chromatin, exhibiting kinetics similar to Cdt1. These are converted to stable interactions from early G1 phase. The immobile fraction of MCM2 and MCM4 increases during G1 phase, suggestive of reiterative licensing. In late G1 phase, a large fraction of MCM proteins are loaded onto chromatin, with maximal licensing observed just prior to S phase onset. Fluorescence loss in photobleaching experiments show subnuclear concentrations of MCM-chromatin interactions that differ as G1 phase progresses and do not colocalize with sites of DNA synthesis in S phase.
Position Mapping using Content Based Image Retrieval and Annoy

Geolocation refers to the identification of the geographic location of a user or computing device via a variety of data collection mechanisms. The proposed system aims to enable accurate and efficient localization of objects within a given environment. Traditional positioning systems often rely on GPS or other sensor-based technologies, which may face limitations in indoor or highly cluttered environments. To overcome these challenges, our approach leverages the power of CBIR, which involves matching query images with a pre-existing database of reference images. By extracting key features from images and employing Annoy, a fast approximate nearest neighbor library, we achieve efficient retrieval and comparison of images. The extracted features act as robust descriptors, enabling accurate positioning of objects based on visual similarities. This research contributes to the advancement of positioning systems by introducing a novel methodology that combines CBIR, Annoy, and feature extraction techniques, offering a promising solution for accurate object localization in challenging environments.The dataset that has been is used is gathered by the authors and the dataset plays a crucial role in position mapping, enabling accurate and context-aware positioning within a given environment.The results demonstrate the effectiveness of the proposed position system, as it achieves high accuracy and real-time performance. This research contributes to the advancement of positioning systems by introducing a novel methodology that combines CBIR, Annoy, and feature extraction techniques, offering a promising solution for accurate object localization in challenging environments.
Afrikaans Literary Genre Recognition using Embeddings and Pre-Trained Multilingual Language Models

Automatic literary genre recognition is pivotal in various domains, including digital libraries, literary studies, and computational linguistics. Efficiently categorizing texts into genres, such as poetry or prose, facilitates the organization and retrieval of literary works, enhancing accessibility for readers, researchers, and academics. Recognizing genre-specific patterns, themes, and stylistic elements enables in-depth analysis and comprehension of literary texts. This study focuses on fine-tuning several state-of-the-art multilingual pre-trained language models, including mBERT, DistilmBERT, and XLM-RoBERTa, to distinguish between Afrikaans poetry and prose. A baseline Support Vector Machine (SVM) classifier and a self-attention transformer model were also trained for comparison.Results demonstrated that the SVM model with text-embeddings-ada-002 embeddings achieved the highest test F1-score of 0.936. The XLM-RoBERTa model exhibited the best performance during validation with an F1-score of 0.924, while the DistilmBERT model surpassed all others, including the SVM during testing, achieving the highest F1-score of 0.942. Notably, the self-attention model demonstrated comparable F1-scores for training (0.923) and testing (0.929), establishing itself as the second-best performing genre classifier.This study contributes to advancing automatic literary genre recognition in Afrikaans by exploring the capabilities of state-of-the-art multilingual language models and traditional classifiers, providing insights into their comparative performance and potential applications in real-world scenarios.