Miracle-dz/UniFAR-FTUs huggingface dataset:
Refined experimental design may increase the value of murine models for estimation of bluetongue virus virulence

Bluetongue is a serious non-contagious vector-borne viral disease in ruminants, causing poor animal welfare and economic consequences globally. Concern has been raised about the development of novel bluetongue virus (BTV) strains and their possibly altered virulence through the process of viral reassortment. Virulence is traditionally estimated in lethal dose 50 (LD50) studies in murine models, but agreement with both in vitro and virulence in ruminants is questionable, and a refined experimental design is needed. Specific reassortants between wild-type and vaccine strains of BTV-1, -6 and -8 have previously been developed by reverse genetics. The aim of the present study was to rank the in vivo virulence of these parental and reassortant BTV strains by calculating LD50 in a murine model by using an experimental design that is new to virology: a between-patient optimised three-level response surface pathway design. The inoculation procedure was intracranial. Fifteen suckling mice were used to establish LD50 for each strain. Three parental and five reassortant virus strains were included. The LD50s varied from of 0.1 (95% confidence interval (CI) 0–0.20) to 3.3 (95% CI 2.96–3.72) tissue culture infectious dose 50/ml. The results support the hypothesis that reassortment in BTV may lead to increased virulence in mice with potential negative consequences for the natural ruminant host. The ranking showed low agreement with in vitro properties and virulence in ruminants according to existing literature. Refined design such as response surface pathway design was found suitable for use in virology, and it introduces significant ethical and scientific improvements.
A Combined Nutrition and Exercise Intervention Influences Serum Vitamin B-12 and 25-Hydroxyvitamin D and Bone Turnover of Healthy Chinese Middle-Aged and Older Adults

ABSTRACT Background Hong Kong faces several public health problems including malnutrition and osteoporosis. Considering the typical Chinese diet and overall low physical activity levels of Chinese adults, timely interventions to improve nutritional status and bone health are needed. Objectives We examined the effects of a nutrition plus exercise intervention on serum vitamin B-12 and 25-hydroxyvitamin D [25(OH)D], bone turnover markers, and parathyroid hormone (PTH) concentrations in apparently healthy Chinese middle-aged and older adults. Methods In this 24-wk randomized controlled trial, 180 Chinese adults (85 women, mean ± SD age: 61 ± 6 y) were randomly assigned to receive a fortified milk supplement (2 × 30 g/d) and an exercise program (2 × 1 h/wk including resistance, balance, and aerobic training) or no intervention. The primary outcome was physical performance. In this article we analyzed the secondary outcomes serum vitamin B-12 and 25(OH)D concentrations, assessed at baseline, 12 wk, and 24 wk. Also, bone turnover markers and PTH concentrations were studied. Linear mixed models evaluated group differences over time. Results A significant time × group interaction (P < 0.001) was found for serum vitamin B-12 and 25(OH)D concentrations and the bone turnover markers, but not for serum PTH concentrations (P = 0.09). The intervention increased mean ± SD vitamin B-12 concentrations from baseline (345 ± 119 pmol/L) to 24 wk (484 ± 136 pmol/L), whereas concentrations remained stable within the control. For 25(OH)D concentrations, the intervention group had a greater increase from baseline (54.7 ± 14.2 nmol/L) to 24 wk (80.1 ± 19.2 nmol/L) than the control (60.6 ± 15.2 compared with 65.6 ± 14.6 nmol/L). The ratio of the net effect of bone formation and resorption was greater in the intervention group, suggesting less bone remodeling, irrespective of sex. Conclusions A fortified milk supplement and exercise intervention successfully improved vitamin B-12 and 25(OH)D concentrations as well as the balance of bone turnover markers of Chinese middle-aged and older adults. This trial was registered at trialregister.nl as NTR6214.
Fusing Convolutional Neural Network Features With Hand-Crafted Features for Objective Fabric Smoothness Appearance Assessment

In the textile and apparel industry, it remains a challenging task to evaluate the fabric smoothness appearance objectively. In existing studies, with computer vision technology, researchers use the hand-crafted image features and deep convolutional neural network (CNN) based image features to describe the fabric smoothness appearance. This paper presents an image classification framework to evaluate the fabric smoothness appearance degree. The framework contains a feature fusion module to fuse the hand-crafted and CNN features to take both advantages of them. The framework uses the multi-scale spatial masking model and a pre-trained CNN to extract hand-crafted and CNN features of fabric images respectively. In addition, a mislabeled sample filtering module is set in the framework, which helps to avoid the negative impact of mislabeled samples in training. In the experiments, the proposed framework achieves 85.2%, 96.1%, and 100% average evaluation accuracies under errors of 0 degree, 0.5 degree, and 1 degree respectively. The experiments on the feature fusion and mislabeled sample filtering verified their effectiveness in improving the evaluation accuracies and the label noise robustness. The proposed method outperforms the state-of-the-art methods for fabric smoothness assessment. Promisingly, this paper can provide novel research ideas for image-based fabric smoothness assessment and other similar tasks.
Gene Expression and Phylogenetic Relationship of Defensin Genes from Egyptian Sources for Biocontrol

Defensins are subgroup of antimicrobial peptides that play an indespensible role in innate immunity in almost all eukaryotic animal and plant cells ranging from insects to mammals. They represent a wide range of structure and mode of action depending on their source. The main objective of this study is to isolate the defensin gene from various Egyptian sources to study the phylogenetic relationship among these organisms. Defensin genes were isolated from various Egyptian sources including Sitophilus oryzae (rice weevil), Callosobruchus chinensis, Bos Taurus (Egyptian and Friesian), Homo sapiens (human blood cells). Using PCR technology, various amplicons were amplified from the different organisms. An amplicon of 150 bp was amplified and isolated from Sitophilus oryzae, Callosobruchus chinensis. Amplicon of 429 bp was amplified from Egyptiam cows and three amplicons of 1650 bp, 1300 bp, and 429 bp were amplified from Friesian cows. Three amplicons of 800 bp, 215 bp, and 179 bp were amplified using primer hBD-1, two amplicons of 1000 and 179 bp were amplified using primer hBD-2. Sequences obtained from the amplified amplicons were used to construct a phylogenetic tree among the used organisms. The results confirm that defensins from Egyptian sources are highly diversed within the same species as well as among different species.
Real-Time Joint Angular-Acceleration Planning for Vision-Based Kinematically Redundant Manipulator in Dynamic Environment

This paper presents an angular acceleration planning for joint configuration spaces of vision-based kinematically redundant robot manipulators to achieve real-time tracking tasks in dynamic environment. In accordance with the proved proposition, the joint velocity formed by the inverse kinematics mapping of the defined pose error is regarded as the system error, and utilized to further deduce the planned joint angular acceleration and with kinematic redundancy for obstacle avoidance simultaneously. Highly-complex nonlinearities in the angular acceleration are equivalent to a system perturbation represented by a synthetic form, thereby simplifying the tedious calculations of the angular acceleration theoretically and converting the planning problem into a control problem. Hyperbolic tangent-based super twisting algorithm, as the control input of manipulator system, is designed to resist the synthetic perturbation. The collision-free movement of redundant manipulators for tracking tasks is thus achieved through the integration of the control input in real time. An error-based S-function is proposed as the internal parameter of the planned joint acceleration to prevent the integral saturation. Lyapunov theoretical analysis proves the stability of the proposed super twisting algorithm. Simulation and contrast experiments in dynamic-obstacles environments indicate that the proposed joint angular acceleration planning for kinematically redundant manipulators owns feasibility, smoothness and practicability.
CDS: A Cross–Version Software Defect Prediction Model With Data Selection

Over the past decade, a large number of software defect prediction approaches have been proposed to identify the defect-prone modules by mining software repositories. Recently, a novel scenario called Cross–Version Defect Prediction (CVDP) begins to draw increasing research interests, as it is more reasonable and applicable in practice to adopt the labeled defect data of previous versions to predict defects in the current version of the same project. As a software project often has multiple previous versions, CVDP on this kind of projects will face the following two critical but seldom reported issues, namely, data distribution difference and class overlapping. In this paper, we address these two issues by solving a version selection problem via a Cross–version model with Data Selection (CDS). The proposed CDS is a novel framework which treats the defect prediction of existing and new files in different ways. For the existing files, we propose a novel Clustering–based Multi–Version Classifier (CMVC), which can automatically select the training data from the most relevant and noise-free versions by assigning them higher weights than the others. We proposed a Weighted Sampling Model (WSM) for the new files which have never appeared in previous version by incorporating the outputs of CMVC. We evaluate the proposed CDS model on 28 versions across 8 software projects, and the experimental results demonstrate that CDS outperforms three baseline methods and a state-of-the-art approach in terms of three prevalent performance indicators.
Measurement of the urban sprawl of Casablanca between 1984 and 2018 and the comparison of its evolution with the evolutions of the population and the private and public transport equipment

Casablanca, like the big cities of developing countries, has experienced a rapid urbanization in the last three decades. It also affected urban transport systems (supply and demand). The main objective of this work is to measure the evolution of the urban sprawl of the city of Casablanca between 1984 and 2018 on the one hand, and on the other hand to compare the evolution of this urban sprawl with the evolutions of the population and private transport (cars) and urban public transport equipment (bus). The results of our work show a divergence between the evolution of urban sprawl and population on one side, and the equipment of urban transport on the other side, and this explains the very significant evolution of private transport equipment (cars).
Design and Analysis of an Indirect control Strategy for Reactive VAR Compensation in single-phase AC Microgrid system

Integration of non-conventional sources of energy via power electronic interface with the contemporary AC micro-grid gives new challenges for maintaining the power quality (PQ). These interfaces being static in nature different control mechanisms are embedded inside the voltage source converter (VSC) to provide requisite VAR compensation. In this paper a d-q based decoupled indirect current control technique is proposed for appropriate VAR compensation. The proposed controller is used to provide appropriate switching sequence via SPWM scheme. Moreover, a detailed mathematical analysis and indirect control strategy is presented. The effectiveness of the proposed control logic designed is validated through MATLAB simulation.
Clitolyophyllum akcaabatense gen. nov., sp. nov. (Agaricales, Tricholomatineae); a new fan-shaped clitocyboid agaric from Turkey

Clitolyophyllum akcaabatense gen. nov., sp. nov., is described based on both morphological and molecular data from Akcaabat, Trabzon, Turkey. Its characterizing features are a fan-shaped pileus, an eccentric and fibrillose stipe, 2–4 spored basidia, smooth, ellipsoid, and inamyloid white basidiospores, and growth on the bark of Picea orientalis (L.) Link. Phylogeny based on multigene molecular analysis (nrITS, nrLSU, rpb2 datasets) of the Tricholomatoid clade is provided. Photographs of fresh basidiomata and of the main micromorphological features are included.
Circulating Inflammatory miRNAs Associated with Parkinson’s Disease Pathophysiology

Parkinson’s disease (PD) is the second most common neurodegenerative disease worldwide, being largely characterized by motor features. MicroRNAs (miRNAs) are small non-coding RNAs, whose deregulation has been associated with neurodegeneration in PD. In this study, miRNAs targeting cell death and/or inflammation pathways were selected and their expression compared in the serum of PD patients and healthy controls. We used two independent cohorts (discovery and validation) of 20 idiopathic PD patients (iPD) and 20 healthy controls each. We also analyzed an additional group of 45 patients with a mutation in the leucine-rich repeat kinase 2 (LRRK2) gene (LRRK2-PD). miRNA expression was determined using Taqman qRT-PCR and their performance to discriminate between groups was assessed by receiver operating characteristic (ROC) curve analysis. We found miR-146a, miR-335-3p, and miR-335-5p downregulated in iPD and LRRK2-PD patients versus controls in both cohorts. In addition, miR-155 was upregulated in LRRK2-PD compared to iPD patients showing an appropriate value of area under the ROC curve (AUC 0.80) to discriminate between the two groups. In conclusion, our study identified a panel of inflammatory related miRNAs differentially expressed between PD patients and healthy controls that highlight key pathophysiological processes and may contribute to improve disease diagnosis.
Identification and Analysis of Mot3, a Zinc Finger Protein That Binds to the Retrotransposon Ty Long Terminal Repeat (δ) in Saccharomyces cerevisiae

ABSTRACT Spt3 and Mot1 are two transcription factors of Saccharomyces cerevisiae that are thought to act in a related fashion to control the function of TATA-binding protein (TBP). Current models suggest that while Spt3 and Mot1 do not directly interact, they do function in a related fashion to stabilize the TBP-TATA interaction at particular promoters. Consistent with this model, certain combinations of spt3 and mot1 mutations are inviable. To identify additional proteins related to Spt3 and Mot1 functions, we screened for high-copy-number suppressors of the mot1 spt3inviability. This screen identified a previously unstudied gene,MOT3, that encodes a zinc finger protein. We show that Mot3 binds in vitro to three sites within the retrotransposon Ty long terminal repeat (δ) sequence. One of these sites is immediately 5′ of the δ TATA region. Although a mot3 null mutation causes no strong phenotypes, it does cause some mild phenotypes, including a very modest increase in Ty mRNA levels, partial suppression of transcriptional defects caused by a mot1 mutation, and partial suppression of an spt3 mutation. These results, in conjunction with those of an independent study of Mot3 (A. Grishin, M. Rothenberg, M. A. Downs, and K. J. Blumer, Genetics, in press), suggest that this protein plays a varied role in gene expression that may be largely redundant with other factors.
A Heuristic Algorithm Focusing on the Rich-Club Phenomenon for the Influence Maximization Problem in Social Networks

The strength of information diffusion on social networks depends on many factors, including the selected influential nodes. The problem of finding such nodes in the network is modeled by influence maximization problem, which faces two essential challenges: (1) inadequate selection of the seed nodes due to the lack of focus on the rich-club phenomenon and (2) high running time due to the lack of focus on pruning the graph nodes and localization. To solve these challenges, a computational localization-based RLIM algorithm is presented here to prevent the rich-club phenomenon. In this algorithm, the graph nodes are pruned based on the eigenvector centrality to reduce the computational overhead, and then the computations are performed locally using localization criteria. After that, influential nodes are selected by avoiding the rich-club phenomenon. In the RLIM algorithm, the seed nodes provided a better influence spread than the other algorithms. Experimental results on the synthetic and real-world datasets shows that the RLIM algorithm can verify the high effectiveness and efficiency than the comparable algorithms for an influence maximization problem.
Doa10 is a membrane protein retrotranslocase in ER-associated protein degradation

In endoplasmic reticulum-associated protein degradation (ERAD), membrane proteins are ubiquitinated, extracted from the membrane, and degraded by the proteasome. The cytosolic ATPase Cdc48 drives extraction by pulling on polyubiquitinated substrates. How hydrophobic transmembrane (TM) segments are moved from the phospholipid bilayer into cytosol, often together with hydrophilic and folded ER luminal protein parts, is not known. Using a reconstituted system with purified proteins from Saccharomyces cerevisiae, we show that the ubiquitin ligase Doa10 (Teb-4/MARCH6 in animals) is a retrotranslocase that facilitates membrane protein extraction. A substrate’s TM segment interacts with the membrane-embedded domain of Doa10 and then passively moves into the aqueous phase. Luminal substrate segments cross the membrane in an unfolded state. Their unfolding occurs on the luminal side of the membrane by cytoplasmic Cdc48 action. Our results reveal how a membrane-bound retrotranslocase cooperates with the Cdc48 ATPase in membrane protein extraction.
A Single-Neuron: Current Trends and Future Prospects

The brain is an intricate network with complex organizational principles facilitating a concerted communication between single-neurons, distinct neuron populations, and remote brain areas. The communication, technically referred to as connectivity, between single-neurons, is the center of many investigations aimed at elucidating pathophysiology, anatomical differences, and structural and functional features. In comparison with bulk analysis, single-neuron analysis can provide precise information about neurons or even sub-neuron level electrophysiology, anatomical differences, pathophysiology, structural and functional features, in addition to their communications with other neurons, and can promote essential information to understand the brain and its activity. This review highlights various single-neuron models and their behaviors, followed by different analysis methods. Again, to elucidate cellular dynamics in terms of electrophysiology at the single-neuron level, we emphasize in detail the role of single-neuron mapping and electrophysiological recording. We also elaborate on the recent development of single-neuron isolation, manipulation, and therapeutic progress using advanced micro/nanofluidic devices, as well as microinjection, electroporation, microelectrode array, optical transfection, optogenetic techniques. Further, the development in the field of artificial intelligence in relation to single-neurons is highlighted. The review concludes with between limitations and future prospects of single-neuron analyses.
Intrusion Detection in IoT-Based Smart Grid Using Hybrid Decision Tree

Considering the growing trend of electric power consumption, resource constraints and the exhaustion of existing grid equipment, the issue of restructuring the electricity industry has been considered. Meanwhile, the use of Internet of Things (IoT) technology and upgrading the power grid to a Smart Grid (SG), in addition to the many benefits, poses challenges to security issues. Since Intrusion Detection System (IDS) is one of the ways forward to combat cyber-attacks, Therefore, in this paper, a smart method for intrusion detection in these types of networks is presented. In this method, a combination of three decision trees was used to detect intrusion and the performance of the proposed method was compared with the Support Vector Machine (SVM), K-Nearest Neighbors (KNN) and Decision Tree (DT) methods. Experiments have been performed on the NSL-KDD dataset and the results show that the proposed method performs better than other methods for Intrusion Detection in IoT-Based SG.
Optimal placement of FACTS devices in power transmission network using power stability index and fast voltage stability index

In this paper two techniques have been introduced to locate suitable position of FACTS devices in 14 bus IEEE interconnected transmission network to improve voltage profile, enhance power transfer capability and increase the efficiency of the overall power transmission. The techniques introduced here are power stability index (PSI) and fast voltage stability index (FVSI). These indices are calculated from the data obtained after performing load flow analysis in 14 bus IEEE interconnected transmission networks by using Newton Rapson's method in MIPOWER software. The FVSI technique shows better results in terms of reduction of reactive power losses, minimization of active and reactive power flow and The PSI technique shows better result in the reduction of active power losses.
Effects of Multi-Genre Digital Game-Based Instruction on Students’ Conceptual Understanding, Argumentation Skills, and Learning Experiences

Studies have shown that although traditional instruction is effective in developing students’ conceptual understanding, it lacks in strengthening their thinking skills. To enhance traditional instruction and establish an approach using game-based instruction, this study developed Multi-genre digital Game-based Instruction (MGI), which integrates various game genres—situated and competitive—with traditional instruction. A total of 115 fourth-graders (9–10 years old) of 4 classes participated in the study, of which 2 classes made up the MGI (experimental) group and the other 2, the traditional instruction (control) group. Quantitative and qualitative data were collected to answer research questions by examining the comparative effectiveness of the two groups separately as well as the effectiveness by achievement level, and exploring students’ learning experiences. Findings showed that using MGI resulted in a significant improvement in conceptual understanding and argumentation skills compared to those who were taught only with traditional instruction. Furthermore, it showed that MGI was significantly more effective than traditional instruction in improving low-achieving students’ conceptual understanding, as well as improving argumentation skills for all achievement levels. Students’ learning experiences with MGI showed how the proposed instruction is superior compared to existing traditional instruction.
Coupled-Physics Based FEM Simulation to Conform Structural Integrity of an Earth Switch During Short Circuit Condition

Transmission and distribution of power has become a critical part of the modern power system. Transmitting power at high voltage decrease the losses in transmission line. With the increase in need for higher voltage transmission of power, the standards for designing such high voltage equipment has become stringent. Isolators, being one of the main high voltage equipment, is a challenge to design under such stringent standards. This is where virtual validation has gained an immense interest amongst isolator designers. It helps to predict the behavioural aspect of the equipment. Prominent research has been done in the field of exploring virtual validation as a distinguished tool for designing isolators. This paper deals with an FEM based simulation as well as the validation from practical aspects.