Miracle-dz/UniFAR-FTUs huggingface dataset:
Guidelines for reliable and reproducible functional enrichment analysis

Gene set enrichment tests (a.k.a. functional enrichment analysis) are among the most frequently used methods in computational biology. Despite this popularity, there are concerns that these methods are being applied incorrectly and the results of some peer-reviewed publications are unreliable. These problems include the use of inappropriate background gene lists, lack of false discovery rate correction and lack of methodological detail. An example analysis of public RNA-seq reveals that these methodological errors alter enrichment results dramatically. To ascertain the frequency of these errors in the literature, we performed a screen of 186 open access research articles describing functional enrichment results. We find that 95% of analyses using over-representation tests did not implement an appropriate background gene list or did not describe this in the methods. Failure to perform p-value correction for multiple tests was identified in 43% of analyses. Many studies lacked detail in the methods section about the tools and gene sets used. Only 15% of studies avoided major flaws, which highlights the poor state of functional enrichment rigour and reporting in the contemporary literature. We provide a set of minimum standards that should act as a checklist for researchers and peer-reviewers.
Dissecting the roles of Haspin and VRK1 in Histone H3 threonine-3 phosphorylation during mitosis

Protein kinases that phosphorylate histones are ideally-placed to influence the behavior of chromosomes during cell division. Indeed, a number of conserved histone phosphorylation events occur prominently during mitosis and meiosis in most eukaryotes, including on histone H3 at threonine-3 (H3T3ph). At least two kinases, Haspin and VRK1 (NHK-1/ballchen in Drosophila), have been proposed to carry out this modification. Phosphorylation of H3 by Haspin has defined roles in mitosis, but the significance of VRK1 activity towards histones in dividing cells has been unclear. Here, using in vitro kinase assays, KiPIK screening, RNA interference, and CRISPR/Cas9 approaches, we were unable to substantiate a direct role for VRK1, or its homologue VRK2, in the phosphorylation of threonine-3 or serine-10 of Histone H3 in mitosis, although loss of VRK1 did slow cell proliferation. We conclude that the role of VRK1, and its more recently identified association with neuromuscular disease in humans, is unlikely to involve mitotic histone kinase activity. In contrast, Haspin is required to generate H3T3ph during mitosis.
A G-lectin Receptor Kinase is a Negative Regulator of Arabidopsis Immunity Against Root-Knot Nematode Meloidogyne incognita

Root-knot nematodes (Meloidogyne spp., RKN) are responsible for extensive crop losses worldwide. For infection, they penetrate plant roots, migrate between plant cells, and establish feeding sites, known as giant cells, in the root pericycle. Previously, we found that nematode perception and early plant responses were similar to those for microbial pathogens and require the BAK1 co-receptor in Arabidopsis thaliana and tomato. To identify additional receptors involved in this process, we implemented a reverse genetic screen for resistance or sensitivity to RKN using Arabidopsis T-DNA alleles of genes encoding transmembrane receptor-like kinases. This screen identified a pair of allelic mutations with enhanced resistance to RKN in a gene we named ENHANCED RESISTANCE TO NEMATODES 1 (ERN1). ERN1 encodes a G-type lectin receptor kinase (G-LecRK) with a single pass transmembrane domain. Further characterization showed that ern1 mutants displayed stronger activation of MAP kinases, elevated levels of the defense marker MYB51, and enhanced H202 accumulation in roots upon RKN elicitor treatments. Elevated MYB51 expression and ROS burst were also observed in leaves of ern1 mutants upon flg22 treatment. Complementation of ern1.1 with 35S- or native promotor-driven ERN1 rescued the RKN infection and enhanced defense phenotypes. Taken together, our results indicate that ERN1 is an important negative regulator of immunity. One sentence summary A plasma membrane localized G-lectin receptor kinase acts as a negative immune regulator by interfering with defense responses activated by nematode and microbial elicitors.
Open-Access STRS Database Of Populations From The 1000 Genomes Project Using High Coverage Phase 3 Data

Accurate STR genotyping from next-generation sequencing (NGS) data has been challenging. Haplotype inference and phasing for STRs (HipSTR) was specifically developed to deal with genotyping errors and obtain reliable STR genotypes from whole-genome sequencing datasets. The objective of this investigation was to perform a comprehensive genotyping analysis of a set of STRs of broad forensic interest from the 1000 Genomes populations and release a reliable open-access STR database to the forensic genetics community. A set of 22 STR markers were analyzed using the CRAM files of the 1000 Genomes Project Phase 3 high-coverage (30x) dataset generated by the New York Genome Center (NYGC). HipSTR was used to call genotypes from 2,504 samples from 26 populations organized into five groups: African, East Asian, European, South Asian, and admixed American. The D21S11 marker could not be detected in the present study. Moreover, the Hardy-Weinberg equilibrium analysis, coupled with a comprehensive analysis of allele frequencies, revealed that HipSTR could not identify longer Penta E (and Penta D at a lesser extent) alleles. This issue is probably due to the limited length of sequencing reads available for genotype calling, resulting in heterozygote deficiency. Notwithstanding that, AMOVA, a clustering analysis using STRUCTURE, and a Principal Coordinates Analysis revealed a clear-cut separation between the four major ancestries sampled by the 1000 Genomes Consortium (AFR, EUR, EAS, SAS). Meanwhile, the AMOVA results corroborated previous reports that most of the variance is (97.12%) observed within populations. This set of analyses revealed that except for larger Penta D and Penta E alleles, allele frequencies and genotypes defined by HipSTR from the 1000 Genomes Project phase 3 data and offered as an open-access database are consistent and highly reliable.
Lighthill-Whitham-Richards Model for Traffic Flow Mixed with Cooperative Adaptive Cruise Control Vehicles

In the future, road traffic will incorporate a random mix of manual vehicles and cooperative adaptive cruise control (CACC) vehicles, where a CACC vehicle will degrade to an adaptive cruise control (ACC) vehicle when vehicle-to-vehicle communications are not available. This paper proposes a generalized framework of the Lighthill-Whitham-Richards (LWR) model for such mixed vehicular flow under different CACC penetration rates. In this approach, the kinematic wave speed propagating through the mixed platoon was theoretically proven to be the slope of mixed fundamental diagram. In addition, the random degradation from CACC to ACC was captured in mathematical expectation for traffic scenarios where the CACC only monitors one vehicle ahead. Three concrete car-following models, the intelligent driver model (IDM) and CACC/ACC models validated by Partners for Advanced Transit and Highways (PATH) program, were selected as examples to investigate the propagation of small perturbations and shock waves. Numerical simulations were also performed based on the selected car-following models. Moreover, the derived mixed LWR model was applied to solve some traffic flow problems. It indicates that the proposed LWR model is able to describe the propagation properties of both small perturbations and shock waves. The mixed LWR model can also be used to solve some practical problems, such as the queue caused by a traffic accident and the impact of a moving bottleneck. More importantly, the proposed generalized framework admits other CACC/ACC/regular car-following models, including those developed from further experiments.
Colorization of fusion image of infrared and visible images based on parallel generative adversarial network approach

Fusing the infrared (IR) and visible images has many advantages and can be applied to applications such as target detection and recognition. Colors can give more accurate and distinct features, but the low resolution and low contrast of fused images make this a challenge task. In this paper, we proposed a method based on parallel generative adversarial networks (GANs) to address the challenge. We used IR image, visible image and fusion image as ground truth of ‘L’, ‘a’ and ‘b’ of the Lab model. Through the parallel GANs, we can gain the Lab data which can be converted to RGB image. We adopt TNO and RoadScene data sets to verify our method, and compare with five objective evaluation parameters obtained by other three methods based on deep learning (DL). It is demonstrated that the proposed approach is able to achieve better performance against state-of-arts methods.
Bidirectional projection method for multi-attribute group decision making under probabilistic uncertain linguistic environment

The financial products selection in the financial services sector is a traditional multi-attribute group decision making (MAGDM) problem. Probabilistic uncertain linguistic sets (PULTSs) could be used to evaluate the financial products with uncertain linguistic terms and corresponding weights (probabilistic). The bidirectional projection (BP) method could take the bidirectional projection values into account. In this paper, we develop an integration model of information entropy and BP method under PULTSs. First of all, utilizing information entropy derives the priority weights of attributes. Next, utilizing the BP method of the PULTSs to obtain the final ranking of the alternatives. To depict the BP method, the formative vectors of two alternatives are defined, and a weighted vector model and inner product are improved under the PULTSs. In addition, through giving the case of financial products selection and some existing MAGDM methods for comparative analysis, it is proved that the method is practical and effective. The proposed approach also contributes to the effective selection of appropriate options in other decision-making matters.
DTA-PUF: Dynamic Timing-aware Physical Unclonable Function for Resource-constrained Devices

In recent years, physical unclonable functions (PUFs) have gained a lot of attention as mechanisms for hardware-rooted device authentication. While the majority of the previously proposed PUFs derive entropy using dedicated circuitry, software PUFs achieve this from existing circuitry in a system. Such software-derived designs are highly desirable for low-power embedded systems as they require no hardware overhead. However, these software PUFs induce considerable processing overheads that hinder their adoption in resource-constrained devices. In this article, we propose DTA-PUF, a novel, software PUF design that exploits the instruction- and data-dependent dynamic timing behaviour of pipelined cores to provide a reliable challenge-response mechanism without requiring any extra hardware. DTA-PUF accepts sequences of instructions as an input challenge and produces an output response based on the manifested timing errors under specific over-clocked settings. To lower the required processing effort, we systematically select instruction sequences that maximise error-rate. The application to a post-layout pipelined floating-point unit, which is implemented in 45 nm process technology, demonstrates the effectiveness and practicability of our PUF design. Finally, DTA-PUF requires up to 50× fewer instructions than existing software processor PUF designs, limiting processing costs and resulting in up to 26% power savings.
A novel pseudo‐polynomial approach for shortest path problems

This article presents a novel shortest path algorithm for connected networks with nonnegative edge weights. The worst case running time of the single source shortest path version of the algorithm is O(max(m, ϵ^vs )) where m is the number of edges of the input network and ϵ^vs is the normalized eccentricity of the source vertex vs. The pseudo‐polynomial nature of the time complexity is overcome with a simple speed‐up technique. The proposed approach can be implemented on a wide class of shortest path problems. Approximate solutions can be easily maintained in the preprocessing phase. An experimental efficiency analysis shows that the proposed approach outperforms existing algorithms in total computing time. The proposed algorithm is efficient for all classes of networks and particularly for networks with small diameter.
The Mechanics of Enterprise Architecture Principles

Inspired by the city planning metaphor, enterprise architecture (EA) has gained considerable attention from academia and industry for systematically planning an IT landscape. Since EA is a relatively young discipline, a great deal of its work focuses on architecture representations (descriptive EA) that conceptualize the different architecture layers, their components, and relationships. Beyond architecture representations, EA should comprise principles that guide architecture design and evolution toward predefined value and outcomes (prescriptive EA). However, research on EA principles is still very limited. Notwithstanding the increasing consensus regarding the role and definition of EA principles, the limited publications neither discuss what can be considered suitable principles nor explain how they can be turned into effective means to achieve expected EA outcomes. This study seeks to strengthen the extant theoretical core of EA by investigating EA principles through a mixed methods research design comprising a literature review, an expert study, and three case studies. The first contribution of this study is that it sheds light on the ambiguous interpretation of EA principles in the extant research by ontologically distinguishing between principles and nonprinciples, as well as deriving a set of suitable EA (meta)principles. The second contribution connects the nascent academic discourse on EA principles to studies on EA value and outcomes. This study conceptualizes the “mechanics” of EA principles as a value-creation process, where EA principles shape architecture design and guide its evolution and thereby realize EA outcomes. Consequently, this study brings the underserved, prescriptive aspect of EA to the fore and helps enrich its theoretical foundations.
Intrusion detection algorithm based on image enhanced convolutional neural network

Intrusion Detection System (IDS) can reduce the losses caused by intrusion behaviors and protect users’ information security. The effectiveness of IDS depends on the performance of the algorithm used in identifying intrusions. And traditional machine learning algorithms are limited to deal with the intrusion data with the characteristics of high-dimensionality, nonlinearity and imbalance. Therefore, this paper proposes an Intrusion Detection algorithm based on Image Enhanced Convolutional Neural Network (ID-IE-CNN). Firstly, based on the image processing technology of deep learning, oversampling method is used to increase the amount of original data to achieve data balance. Secondly, the one-dimensional data is converted into two-dimensional image data, the convolutional layer and the pooling layer are used to extract the main features of the image to reduce the data dimensionality. Thirdly, the Tanh function is introduced as an activation function to fit nonlinear data, a fully connected layer is used to integrate local information, and the generalization ability of the prediction model is improved by the Dropout method. Finally, the Softmax classifier is used to predict the behavior of intrusion detection. This paper uses the KDDCup99 data set and compares with other competitive algorithms. Both in the performance of binary classification and multi-classification, ID-IE-CNN is better than the compared algorithms, which verifies its superiority.
A Dual-Identity Perspective of Obsessive Online Social Gaming

Obsessive online social gaming has become a worldwide societal challenge that deserves more scholarly investigation. However, this issue has not received much attention in the information systems (IS) research community. Guided by dual-system theory, we theoretically derive a typology of obsessive technology use and contextually adapt it to conceptualize obsessive online social gaming. We also build upon identity theory to develop a dual-identity perspective (i.e., IT identity and social identity) of obsessive online social gaming. We test our research model using a longitudinal survey of 627 online social game users. Our results demonstrate that the typology of obsessive technology use comprises four interrelated types: impulsive use, compulsive use, excessive use, and addictive use. IT identity positively affects the four obsessive online social gaming archetypes and fully mediates the effect of social identity on obsessive online social gaming. The results also show that IT identity is predicted by embeddedness, self-efficacy, and instant gratification, whereas social identity is determined by group similarity, group familiarity, and intragroup communication. Our study contributes to the IS literature by proposing a typology of obsessive technology use, incorporating identity theory to provide a contextualized explanation of obsessive online social gaming and offering implications for addressing the societal challenge.
PPA_A_308571 1177..1185

1Department of Clinical Pharmacy, School of Pharmacy, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia; 2Department of Human Nutrition, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia; 3Department of Health Informatics, College of Medicine and Health Sciences, Debre Markos University, Debre Markos, Ethiopia Introduction: Treatment satisfaction is patient’s evaluation of the process of taking the medication and its use. Currently dolutegravir based regimen is first-line agent for treatment of human immunodeficiency virus. But evidence is scarce regarding treatment satisfaction. Thus, the aim of the current study was to assess treatment satisfaction and associated factors of dolutegravir based regimen among adult human immunodeficiency virus patients attending at Debre Markos referral 2020. Methods: Institutional-based cross-sectional study was conducted. A systematic random sampling technique was used to collect data from June 25 to August 25, 2020 at Debre Markos referral hospital. It was entered into Epi Info and exported to SPSS version 23 for analysis. Bivariable and multivariable logistic regression was used to identify factors. Variables with p<0.05 were considered as statistically significant. Results: From a total of 359, 349 participants (97.2%) responded to the study. In this study, 70.5% of participants reported higher treatment satisfaction. Monthly average income of ≥3500 birr (AOR: 2.88; 95% CI: 1.26, 6.58), 1600–2500 birr (AOR: 2.47; 95% CI: 1.11, 5.48), 800–1600 birr (AOR: 3.11; 95% CI: 1.31, 7.37), positive belief about medications (AOR: 3.05; 1.76, 5.28), having a discussion with health care providers (AOR: 3.05, 95% CI: 1.58, 5.88), patients without concurrent medication (AOR: 7.72, 95% CI: 3.29, 18.07), and being male (AOR: 2.10, 95% CI: 1.14, 3.87) were associated with treatment satisfaction. Conclusion: Overall, dolutegravir based regimen showed high treatment satisfaction. Monthly income, positive beliefs about medications, discussing about treatment options, sex and concurrent medications were associated with treatment satisfaction. Thus, it is crucial to improve treatment satisfaction by promoting positive belief towards medication and also by engaging patients in treatment decisions.
Hypertension Predisposes to Radiation Toxicity in a Rat Model of Localized Intestinal Irradiation

Purpose: Vascular disease is believed to be a risk factor for radiation injury in normal tissues, including the intestine. Clinical studies evaluating the relationship between hypertension and radiation enteropathy have been inconclusive, possibly because most hypertensive subjects were receiving blood pressure reducing treatment. This study assessed the association between uncontrolled hypertension and intestinal radiation injury in a clinically relevant rat model.
Towards Unified Metrics for Accuracy and Diversity for Recommender Systems

Recommender systems evaluation has evolved rapidly in recent years. However, for offline evaluation, accuracy is the de facto standard for assessing the superiority of one method over another, with most research comparisons focused on tasks ranging from rating prediction to ranking metrics for top-n recommendation. Simultaneously, recommendation diversity and novelty have become recognized as critical to users’ perceived utility, with several new metrics recently proposed for evaluating these aspects of recommendation lists. Consequently, the accuracy-diversity dilemma frequently shows up as a choice to make when creating new recommendation algorithms. We propose a novel adaptation of a unified metric, derived from one commonly used for search system evaluation, to Recommender Systems. The proposed metric combines topical diversity and accuracy, and we show it to satisfy a set of desired properties that we formulate axiomatically. These axioms are defined as fundamental constraints that a good unified metric should always satisfy. Moreover, beyond the axiomatic analysis, we present an experimental evaluation of the metric with collaborative filtering data. Our analysis shows that the metric respects the desired theoretical constraints and behaves as expected when performing offline evaluation.
Conditioned Fear Extinction , Neuropsychological , and Psychological Aspects of OCD in Puerto Ricans

Background: Although culture can affect emotional and behavioral reactions, there is little research on the manifestations of obsessive-compulsive disorder (OCD) among Latinos. Previous studies using a fear extinction model with non-Latino populations showed that individuals with OCD have difficulty maintaining safety memories. Their neuropsychological performance has indicated inconsistent findings. We compared Puerto Ricans with OCD and healthy controls in fear of extinction retention, neuropsychological performance, and psychological symptoms to enhance understanding of OCD in Puerto Rico. Method: 17 healthy and 11 Puerto Rican adults with OCD underwent a fear conditioning and extinction paradigm using neutral visual cues that were paired or unpaired with an electric stimulus to elicit skin conductance responses. Neuropsychological tests and psychological self-reports were administered. Results: OCD subjects did not show impaired extinction recall, but showed higher reaction times towards neutral than threat-related words on the Emotional Stroop Task, compared to healthy controls. No differences in neuropsychological tests that lacked emotional content were observed. OCD subjects showed increased symptoms of anxiety, trait anxiety, depression, negative affect, and emotional dysregulation. Conclusions: Puerto Ricans with OCD may have physiological and neuropsychological characteristics that are similar to healthy subjects. Still, a different psychological profile can be used to tailor cultural adaptations of evidence-based treatments for OCD.