Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effects of Attention-Deficit/Hyperactivity Disorder Symptoms on the Association between Head Impacts and Post-Season Neurocognitive and Behavioral Outcomes

Abstract Objective: Having attention-deficit/hyperactivity disorder (ADHD) is a risk factor for concussion that impacts concussion diagnosis and recovery. The relationship between ADHD and repetitive subconcussive head impacts on neurocognitive and behavioral outcomes is less well known. This study evaluated the role of ADHD as a moderator of the association between repetitive head impacts on neurocognitive test performance and behavioral concussion symptoms over the course of an athletic season. Method: Study participants included 284 male athletes aged 13–18 years who participated in high school football. Parents completed the Strengths and Weaknesses of ADHD Symptoms and Normal Behavior (SWAN) ratings about their teen athlete before the season began. Head impacts were measured using an accelerometer worn during all practices and games. Athletes and parents completed behavioral ratings of concussion symptoms and the Attention Network Task (ANT), Digital Trail Making Task (dTMT), and Cued Task Switching Task at pre- and post-season. Results: Mixed model analyses indicated that neither head impacts nor ADHD symptoms were associated with post-season athlete- or parent-reported concussion symptom ratings or neurocognitive task performance. Moreover, no relationships between head impact exposure and neurocognitive or behavioral outcomes emerged when severity of pre-season ADHD symptoms was included as a moderator. Conclusion: Athletes’ pre-season ADHD symptoms do not appear to influence behavioral or neurocognitive outcomes following a single season of competitive football competition. Results are interpreted in light of several study limitations (e.g., single season, assessment of constructs) that may have impacted this study’s pattern of largely null results.
An ultra-thinned groin flap for reconstruction of complete digital ring avulsion injuries

In complete digital ring avulsions, amputation is usually carried out when replantation of the avulsed tissue is not an option or has failed. The purpose of this study was to report our experience in treating Urbaniak Class III degloved fingers using an ultra-thinned pedicled groin flap. Sixteen patients from ages 11 to 26 years were included. In all cases, the flexor digitorum superficialis tendon, extensor apparatus and proximal interphalangeal joint were intact. Rehabilitation included immediate active mobilization, with flap division at day 21. At a mean follow-up of 15 months, all patients but one were satisfied with the appearance. Two had mild subjective cold intolerance. No flap failure was recorded. The mean total active motion was 183° and the mean QuickDASH score was 8.8/100. Patients recovered S1 sensibility according to the Mackinnon and Dellon classification. The ultra-thinned groin flap has proved to be a reliable technique for non-replantable ring avulsions. Level of evidence: IV
Bacterial biofilm infections, their resistance to antibiotics therapy and current treatment strategies

Nearly 80% of human chronic infections are caused due to bacterial biofilm formation. This is the most leading cause for failure of medical implants resulting in high morbidity and mortality. In addition, biofilms are also known to cause serious problems in food industry. Biofilm impart enhanced antibiotic resistance and become recalcitrant to host immune responses leading to persistent and recurrent infections. It makes the clinical treatment for biofilm infections very difficult. Reduced penetration of antibiotic molecules through EPS, mutation of the target site, accumulation of antibiotic degrading enzymes, enhanced expression of efflux pump genes are the probable causes for antibiotics resistance. Accordingly, strategies like administration of topical antibiotics and combined therapy of antibiotics with antimicrobial peptides are considered for alternate options to overcome the antibiotics resistance. A number of other remediation strategies for both biofilm inhibition and dispersion of established biofilm have been developed. The metallic nanoparticles (NPs) and their oxides have recently gained a tremendous thrust as antibiofilm therapy for their unique features. This present comprehensive review gives the understanding of antibiotic resistance mechanisms of biofilm and provides an overview of various currently available biofilm remediation strategies, focusing primarily on the applications of metallic NPs and their oxides.
Effect of daily 3‐s maximum voluntary isometric, concentric, or eccentric contraction on elbow flexor strength

The present study compared a 3‐s isometric maximal voluntary contraction (MVC), concentric MVC and eccentric MVC of the elbow flexors performed daily for 5 days a week for 4 weeks for changes in muscle strength and thickness. Young sedentary individuals were assigned to one of three training groups (n = 13 per group) that performed either 3‐s isometric, concentric, or eccentric MVC once a day for 20 days, or to a control group (n = 10) that had measurements without training. The participants in the isometric group performed isometric MVC at 55° (0.96 rad) elbow flexion, and those in the concentric or eccentric group performed concentric MVC or eccentric MVC between 10° (0.17 rad) and 100° (1.75 rad) elbow flexion at 30°/s (0.52 rad/s) on an isokinetic dynamometer. MVC isometric torque at 20° (0.35 rad), 55° (0.96 rad), and 90° (1.57 rad) elbow flexion, MVC concentric and eccentric torque at 30°/s (0.52 rad/s) and 180°/s (3.14 rad/s), and muscle thickness (MT) of biceps brachii and brachialis were measured before and several days after the 20th exercise session. The control group did not show any changes. The eccentric group showed increases (p < 0.01) in isometric (three angle average: 10.2 ± 6.4%), concentric (two velocity average: 12.8 ± 9.6%), and eccentric MVC torque (12.2 ± 7.8%). An increase (p < 0.05) was limited for isometric MVC torque (6.3 ± 6.0%) in the concentric group, and for eccentric MVC torque (7.2 ± 4.4%) in the isometric group. No significant changes in MT were evident for all groups. Performing one 3‐s MVC a day increased muscle strength, but eccentric MVC produced more potent effects than isometric or concentric MVC.
Rippled Sheets: The Early Polyglycine Days and Recent Developments in Nylons

The rippled sheet structure is a remarkable insight due to Pauling and Corey, that supplements the pleated sheet structure of homochiral proteins introduced in 1951. Whereas the pleated sheet was immediately adopted by the scientific community, the rippled sheet has remained more confidential since it applies only to blends of poly(L‐peptides) and poly(D‐peptides). The present account tells the intimate but patchy relationship developed by the author with the rippled sheet. In the 1970s, twenty years after Pauling and Corey's proposal, the rippled sheet was recognized as a valid model for the sheet structure of the achiral polyglycine, polyglycine I, which helped improve the structure of Bombyx mori silk fibroin. Very recently, pleated and rippled sheets were found to account for unsolved crystal structures of a variety of nylons. These structures help to explain a mysterious high temperature “Brill transition” first reported in nylon 6–6 by Brill in 1942.
Inferring Protein Function in an Emerging Virus: Detection of the Nucleoprotein in Tilapia Lake Virus

Tilapia is an important source of dietary protein, especially in developing countries. Massive losses of tilapia were identified worldwide, risking the food security of millions of people. ABSTRACT Emerging viruses impose global threats to animal and human populations and may bear novel genes with limited homology to known sequences, necessitating the development of novel approaches to infer and test protein functions. This challenge is dramatically evident in tilapia lake virus (TiLV), an emerging “orthomyxo-like” virus that threatens the global tilapia aquaculture and food security of millions of people. The majority of TiLV proteins have no homology to known sequences, impeding functionality assessments. Using a novel bioinformatics approach, we predicted that TiLV’s Protein 4 encodes the nucleoprotein, a factor essential for viral RNA replication. Multiple methodologies revealed the expected properties of orthomyxoviral nucleoproteins. A modified yeast three-hybrid assay detected Protein 4-RNA interactions, which were independent of the RNA sequence, and identified specific positively charged residues involved. Protein 4-RNA interactions were uncovered by R-DeeP and XRNAX methodologies. Immunoelectron microscopy found that multiple Protein 4 copies localized along enriched ribonucleoproteins. TiLV RNA from cells and virions coimmunoprecipitated with Protein 4. Immunofluorescence microscopy detected Protein 4 in the cytoplasm and nuclei, and nuclear Protein 4 increased upon CRM1 inhibition, suggesting CRM1-dependent nuclear export of TiLV RNA. Together, these data reveal TiLV’s nucleoprotein and highlight the ability to infer protein functionality, including novel RNA-binding proteins, in emerging pathogens. These are important in light of the expected discovery of many unknown viruses and the zoonotic potential of such pathogens. IMPORTANCE Tilapia is an important source of dietary protein, especially in developing countries. Massive losses of tilapia were identified worldwide, risking the food security of millions of people. Tilapia lake virus (TiLV) is an emerging pathogen responsible for these disease outbreaks. TiLV’s genome encodes 10 major proteins, 9 of which show no homology to other known viral or cellular proteins, hindering functionality assessment of these proteins. Here, we describe a novel bioinformatics approach to infer the functionality of TiLV proteins, which predicted Protein 4 as the nucleoprotein, a factor essential for viral RNA replication. We provided experimental support for this prediction by applying multiple molecular, biochemical, and imaging approaches. Overall, we illustrate a strategy for functional analyses in viral discovery. The strategy is important in light of the expected discovery of many unknown viruses and the zoonotic potential of such pathogens.
Brain Age Prediction With Improved Least Squares Twin SVR

Alzheimer’s disease (AD) is the prevalent form of dementia and shares many aspects with the aging pattern of the abnormal brain. Machine learning models like support vector regression (SVR) based models have been successfully employed in the estimation of brain age. However, SVR is computationally inefficient than twin support vector machine based models. Hence, different twin support vector machine based models like twin SVR (TSVR), <inline-formula><tex-math notation="LaTeX">$\varepsilon$</tex-math></inline-formula>-TSVR, and Lagrangian TSVR (LTSVR) models have been used for the regression problems. <inline-formula><tex-math notation="LaTeX">$\varepsilon$</tex-math></inline-formula>-TSVR and LTSVR models seek a pair of <inline-formula><tex-math notation="LaTeX">$\varepsilon$</tex-math></inline-formula>-insensitive proximal planes for generation of end regressor. However, SVR and TSVR based models have several drawbacks- i) SVR model is computationally inefficient compared to the TSVR based models. ii) Twin SVM based models involve the computation of matrix inverse which is intractable in real world scenario’s. iii) Both TSVR and LTSVR models are based on empirical risk minimization principle and hence may be prone to overfitting. iv) TSVR and LTSVR assume that the matrices appearing in their formulation are positive definite which may not be satisfied in real world scenario’s. To overcome these issues, we formulate improved least squares twin support vector regression (ILSTSVR). The proposed ILSTSVR modifies the TSVR by replacing the inequality constraints with the equality constraints and minimizes the slack variables using squares of <inline-formula><tex-math notation="LaTeX">$L_2$</tex-math></inline-formula> norm instead of <inline-formula><tex-math notation="LaTeX">$L_1$</tex-math></inline-formula>. Also, we introduce a different Lagrangian function to avoid the computation of matrix inverses. We evaluated the proposed ILSTSVR model on the subjects including cognitively healthy, mild cognitive impairment and Alzheimer’s disease for brain-age estimation. Experimental evaluation and statistical tests demonstrate the efficiency of the proposed ILSTSVR model for brain-age prediction.
A Survey of Deep Learning Techniques for Underwater Image Classification

In recent years, there has been an enormous interest in using deep learning to classify underwater images to identify various objects, such as fishes, plankton, coral reefs, seagrass, submarines, and gestures of sea divers. This classification is essential for measuring the water bodies’ health and quality and protecting the endangered species. Furthermore, it has applications in oceanography, marine economy and defense, environment protection, underwater exploration, and human-robot collaborative tasks. This article presents a survey of deep learning techniques for performing underwater image classification. We underscore the similarities and differences of several methods. We believe that underwater image classification is one of the killer application that would test the ultimate success of deep learning techniques. Toward realizing that goal, this survey seeks to inform researchers about state-of-the-art on deep learning on underwater images and also motivate them to push its frontiers forward.
Large-Scale Phylogenetic Analysis Reveals a New Genetic Clade among Escherichia coli O26 Strains

Shiga toxin-producing Escherichia coli (STEC) O26 is the second prevalent STEC serogroup only to O157, which can cause a series of diseases ranging from mild diarrhea to life-threatening hemolytic uremic syndrome (HUS). The serogroup is highly diverse and multiple clones are characterized, including ST29C1-C3 and ST21C1-C2. ABSTRACT Shiga toxin-producing Escherichia coli (STEC) O26 is the predominant non-O157 serogroup causing hemolytic uremic syndrome worldwide. Moreover, the serogroup is highly dynamic and harbors several pathogenic clones. Here, we investigated the phylogenetic relationship of STEC O26 at a global level based on 1,367 strains from 20 countries deposited in NCBI and Enterobase databases. The whole-genome-based analysis identified a new genetic clade, called ST29C4. The new clade was unique in terms of multilocus sequence type (ST29), CRISPR (group Ia), and dominant plasmid gene profile (ehxA+/katP-/espP-/etpD-). Moreover, the combination of multiple typing methods (core genome single nucleotide polymorphism [SNP] typing, CRISPR typing, and virulence genes analysis) demonstrated that this new lineage ST29C4 was in the intermediate phylogenetic position between ST29C3 and other non-ST29C3 strains. Besides, we observed that ST29C4 harbored extraintestinal pathogenic E. coli (ExPEC)-related virulence gene (VG), tsh, and STEC-associated VG, stx2a, suggesting the emergence of a hybrid pathogen. The ST29C4 strains also exhibited high similarity in stx2a-prophage and integrase with the O104:H4 strain, further demonstrating its potential risk to human health. Collectively, the large-scale phylogenetic analysis extends the understanding of the clonal structure of O26 strains and provides new insights for O26 strain microevolution. IMPORTANCE Shiga toxin-producing Escherichia coli (STEC) O26 is the second prevalent STEC serogroup only to O157, which can cause a series of diseases ranging from mild diarrhea to life-threatening hemolytic uremic syndrome (HUS). The serogroup is highly diverse and multiple clones are characterized, including ST29C1-C3 and ST21C1-C2. However, the phylogenetic relationship of these clones remains fully unclear. In this study, we revealed a new genetic clade among O26 strains, ST29C4, which was unique in terms of CRISPR, multilocus sequence type (MLST), and plasmid gene profile (PGP). Moreover, the combination of multiple typing methods demonstrated that this new clone was located in the intermediate phylogenetic position between ST29C3 and other non-ST29C3 strains (i.e., ST29C1-C2 and ST21C1-C2). Overall, the large-scale phylogenetic analysis extends our current understanding of O26 microevolution.
Diverse, Neural Trojan Resilient Ecosystem of Neural Network IP

Adversarial machine learning is a prominent research area aimed towards exposing and mitigating security vulnerabilities in AI/ML algorithms and their implementations. Data poisoning and neural Trojans enable an attacker to drastically change the behavior and performance of a Convolutional Neural Network (CNN) merely by altering some of the input data during training. Such attacks can be catastrophic in the field, e.g. for self-driving vehicles. In this paper, we propose deploying a CNN as an ecosystem of variants, rather than a singular model. The ecosystem is derived from the original trained model, and though every derived model is structurally different, they are all functionally equivalent to the original and each other. We propose two complementary techniques: stochastic parameter mutation, where the weights θ of the original are shifted by a small, random amount, and a delta-update procedure which functions by XOR’ing all of the parameters with an update file containing the Δ θ values. This technique is effective against transferability of a neural Trojan to the greater ecosystem by amplifying the Trojan’s malicious impact to easily detectable levels; thus, deploying a model as an ecosystem can render the ecosystem more resilient against a neural Trojan attack.
NN-Lock: A Lightweight Authorization to Prevent IP Threats of Deep Learning Models

The prevalent usage and unparalleled recent success of Deep Neural Network (DNN) applications have raised the concern of protecting their Intellectual Property (IP) rights in different business models to prevent the theft of trade secrets. In this article, we propose a lightweight, generic, key-based DNN IP protection methodology, NN-Lock, to defend against unauthorized usage of stolen DNN models. NN-Lock utilizes SBox, a cryptographic primitive, with good security properties to encrypt each parameter of a trained DNN model with the secret keys derived from a master key through a key-scheduling algorithm. The method ensures that only an authorized user with a correct master key can accurately use the locked DNN model. Evaluation results of NN-Lock on a Google Coral edge device for various DNN architectures on several datasets show that for an incorrect master key, the accuracy of a locked model is that of a random classifier. The dense network of encrypted parameters makes the method robust against the model fine-tuning attack and a novel approximation attack using the Genetic Algorithm, which achieves reasonable success against another recent IP protection scheme called HPNN Chakraborty et al. 2020. The security evaluation of NN-Lock against other families of attacks demonstrates its soundness in practical scenarios. NN-Lock does not modify any internal structure of a DNN model, making it scalable for all of the existing DNN implementations without adversely affecting their performance.
Success determinants of projects of business software implementation: Research framework

Abstract The experience of many organizations so far has shown that the risk of failure of the software implementation project is high, and in order to reduce this risk, significant efforts have been made so far to implement the project management methodology. However, research to date shows that, despite improvements in project management, a relatively significant number of projects still fail by some of the performance criteria. A methodology is proposed that includes: (i) analysis of previous research; (ii) design a research instrument to measure project performance and define key determinants of project performance; (iii) development of a multi-criteria model for measuring the performance of software projects; (iv) development of software project management performance models for Croatian organizations using a data mining approach. These activities can be carried out using the following methods: bibliographic analysis of previous research, survey research method, descriptive and inferential statistics methods, structural equations method and data mining methods (supervised and unsupervised learning, text mining). The results of this research framework can be used as a starting point for researching the success of business software implementation projects.
Regulation of ER‐derived membrane dynamics by the DedA domain‐containing proteins VMP1 and TMEM41B

The endoplasmic reticulum (ER) is a central hub for the biogenesis of various organelles and lipid‐containing structures. Recent studies suggest that vacuole membrane protein 1 (VMP1) and transmembrane protein 41B (TMEM41B), multispanning ER membrane proteins, regulate the formation of many of these ER‐derived structures, including autophagosomes, lipid droplets, lipoproteins, and double‐membrane structures for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) replication. VMP1 and TMEM41B possess a DedA domain that is widely distributed not only in eukaryotes but also in prokaryotes and predicted to adopt a characteristic structure containing two reentrant loops. Furthermore, recent studies show that both proteins have lipid scrambling activity. Based on these findings, the potential roles of VMP1 and TMEM41B in the dynamic remodeling of ER membranes and the biogenesis of ER‐derived structures are discussed.
Learning to Work in China's Leading Metropolis

This article examines the skills development needs and learning opportunities of the workforce in the city of Shanghai in the People's Republic of China. It attempts to elucidate the factors that influence employees’ participation in workplace training and adult education activities. By tapping the views of firm executives and employees, this article discusses the combined efficacy of three types of education and training activities for vocational learning: informal learning, nonformal training, and formal adult education. The major findings of this article suggest that working adults in Shanghai are willing to participate in a variety of adult education and training activities so long as they can see the utility of these activities. Their willingness is especially apparent when adult education and training can yield widely recognized qualifications that enhance their marketability. As the leading metropolis of China, Shanghai has great aspirations for its own role in national development as well as on the world stage. Its endeavor in providing skills development for a large workforce during a period of economic transformation should afford conceptual and policy insights into the implementation of adult education and training in changing societal contexts.
In-vivo egfp expression in the honeybee Apis mellifera induced by electroporation and viral expression vector

In this study we describe egfp expression induced by two techniques: in vivo electroporation and viral transduction in several cell types of the adult honeybee brain. Non-neuronal and neuronal cell types were identified and the expression persisted at least during three days. Kenyon cells, optic lobe neurons and protocerebral lobe neurons were electroporated. Astrocyte-like glia cells, fibrous lamellar glia cells and cortex glia cells were identified. Viral transduction targeted one specific type of glia cells that could not be identified. EGFP positive cells were rather variable after electroporation, and viral transduction resulted in more homogenous groups of positive cells. We propose that these techniques remain a good alternative to transgenic animals because they potentially target only somatic cells.