Attitudes of Undergraduate Students Towards Self-employment in Yemen Public Universities

To the best of the authors’ knowledge, the intention of undergraduate students towards self-employment has not been yet studied in Yemen. We aimed to study the intentions of undergraduate students towards self-employment as a career choice. Since most literature agrees that future intention towards self-employment can be determined by using the Theory of Reasoned Action (TRA), this theory is used as a theoretical framework in this study. A questionnaire survey was completed by a random sample (n = 451) of university students, undergraduate level, at one of the major public universities in Yemen. Results were based on descriptive analysis and multivariate statistical analysis including crosstabs, bivariate correlation and binary logistic regressions. Results of correlation test indicates that there are positive and significant correlations between dependent variable students’ intention to be self-employed and independent variables; entrepreneurial awareness (r = .338, n = 401, P < .00) and attitude (r =.569, n = 401, P < .00), whereas social norms variable, has derived low and not significant correlation value (r = .066, n = 373, P >.20). Binary logistic regression results showed that both variables, entrepreneurial awareness (ß = 2.154, p < 0.005) and attitude (ß = 3.117, p < 0.005), are significantly correlated with the students’ intention to start a business, whereas there is no significant correlation between the social norms and the students’ intention to start a business (ß = – 0.153, p > 0.744). Our study suggests that providing entrepreneurial capabilities among citizens may improve social norms toward entrepreneurship. The study also makes a valuable contribution to the under-researched context of Yemen entrepreneurship. Keywords: Self-employment intention, Undergraduate students, Yemen, Theory of Reasoned Action. DOI: 10.7176/RHSS/10-2-08 Publication date: January 31st 202

Coordinated Regulation by AgrA, SarA, and SarR To Control agr Expression in Staphylococcus aureus

The agr locus of Staphylococcus aureus is composed of two divergent transcripts (RNAII and RNAIII) driven by the P2 and P3 promoters. The P2-P3 intergenic region comprises the SarA/SarR binding sites and the four AgrA boxes to which AgrA binds. We reported here the role of AgrA, SarA, and SarR on agr P2 and P3 transcription. Using real-time reverse transcription (RT)-PCR and promoter fusion studies with selected single, double, triple, and complemented mutants, we showed that AgrA is indispensable to agr P2 and P3 transcription, whereas SarA activates and SarR represses P2 transcription. In vitro runoff transcription assays revealed that AgrA alone promoted transcription from the agr P2 promoter, with SarA enhancing it and SarR inhibiting agr P2 transcription in the presence of AgrA or with SarA and AgrA. Electrophoretic mobility shift assay (EMSA) analysis disclosed that SarR binds more avidly to the agr promoter than SarA and displaces SarA from the agr promoter. Additionally, SarA and AgrA bend the agr P2 promoter, whereas SarR does not. Collectively, these data indicated that AgrA activates agr P2 and P3 promoters while SarA activates the P2 promoter, presumably via bending of promoter DNA to bring together AgrA dimers to facilitate engagement of RNA polymerase (RNAP) to initiate transcription

Research on the Current Situation of Mental Health in Rural Community and Urban Community

There are few studies on the treatment orientation of psychological counseling and psychotherapy practitioners in China. Additionally, integrative therapy as the first choice is much commoner in less developed areas and among unsupervised practitioners, which reflects the risk of technical confusion relating to the use of integrative therapy in China. The counseling and psychotherapy practitioners are treated as "variables", and researchers are concerned because these "variables" can have a significant impact on the course of treatment and outcomes. Therefore, we analyze the effects of socioeconomic development level on practitioners' treatment orientation. Based on the results, in addition to areas of employment, urban stratification and practitioners’ system factors, gender, age, education, professional background, work hours, and other factors affect psychological counseling and psychological treatment practitioners

The Novel Protease Activities of JMJD5–JMJD6–JMJD7 and Arginine Methylation Activities of Arginine Methyltransferases Are Likely Coupled

The surreptitious discoveries of the protease activities on arginine-methylated targets of a subfamily of Jumonji domain-containing family including JMJD5, JMJD6, and JMJD7 pose several questions regarding their authenticity, function, purpose, and relations with others. At the same time, despite several decades of efforts and massive accumulating data regarding the roles of the arginine methyltransferase family (PRMTs), the exact function of this protein family still remains a mystery, though it seems to play critical roles in transcription regulation, including activation and inactivation of a large group of genes, as well as other biological activities. In this review, we aim to elucidate that the function of JMJD5/6/7 and PRMTs are likely coupled. Besides roles in the regulation of the biogenesis of membrane-less organelles in cells, they are major players in regulating stimulating transcription factors to control the activities of RNA Polymerase II in higher eukaryotes, especially in the animal kingdom. Furthermore, we propose that arginine methylation by PRMTs could be a ubiquitous action marked for destruction after missions by a subfamily of the Jumonji protein family

The CD27L and CTP1L Endolysins Targeting <i>Clostridia</i> Contain a Built-in Trigger and Release Factor

<div><p>The bacteriophage ΦCD27 is capable of lysing <i>Clostridium difficile</i>, a pathogenic bacterium that is a major cause for nosocomial infection. A recombinant CD27L endolysin lyses <i>C. difficile</i> in vitro, and represents a promising alternative as a bactericide. To better understand the lysis mechanism, we have determined the crystal structure of an autoproteolytic fragment of the CD27L endolysin. The structure covers the C-terminal domain of the endolysin, and represents a novel fold that is identified in a number of lysins that target Clostridia bacteria. The structure indicates endolysin cleavage occurs at the stem of the linker connecting the catalytic domain with the C-terminal domain. We also solved the crystal structure of the C-terminal domain of a slow cleaving mutant of the CTP1L endolysin that targets <i>C. tyrobutyricum</i>. Two distinct dimerization modes are observed in the crystal structures for both endolysins, despite a sequence identity of only 22% between the domains. The dimers are validated to be present for the full length protein in solution by right angle light scattering, small angle X-ray scattering and cross-linking experiments using the cross-linking amino acid p-benzoyl-L-phenylalanine (pBpa). Mutagenesis on residues contributing to the dimer interfaces indicates that there is a link between the dimerization modes and the autocleavage mechanism. We show that for the CTP1L endolysin, there is a reduction in lysis efficiency that is proportional to the cleavage efficiency. We propose a model for endolysin triggering, where the extended dimer presents the inactive state, and a switch to the side-by-side dimer triggers the cleavage of the C-terminal domain. This leads to the release of the catalytic portion of the endolysin, enabling the efficient digestion of the bacterial cell wall.</p></div

Improving text classification using local latent semantic indexing

Latent Semantic Indexing (LSI) has been shown to be extremely useful in information retrieval, but it is not an optimal representation for text classification. It always drops the text classification performance when being applied to the whole training set (global LSI) because this completely unsupervised method ignores class discrimination while only concentrating on representation. Some local LSI methods have been proposed to improve the classification by utilizing class discrimination information. However, their performance improvements over original term vectors are still very limited. In this paper, we propose a new local LSI method called “Local Relevancy Weighted LSI ” to improve text classification by performing a separate Single Value Decomposition (SVD) on the transformed local region of each class. Experimental results show that our method is much better than global LSI and traditional local LSI methods on classification within a much smaller LSI dimension. 1

Crystal Structure of the SarS Protein from Staphylococcus aureus

The expression of virulence determinants in Staphylococcus aureus is controlled by global regulatory loci (e.g., sarA and agr). One of these determinants, protein A (spa), is activated by sarS, which encodes a 250-residue DNA-binding protein. Genetic analysis indicated that the agr locus likely mediates spa repression by suppressing the transcription of sarS. Contrary to SarA and SarR, which require homodimer formation for proper function, SarS is unusual within the SarA protein family in that it contains two homologous halves, with each half sharing sequence similarity to SarA and SarR. Here we report the 2.2 A ˚ resolution X-ray crystal structure of the SarS protein. SarS has folds similar to those of SarR and, quite plausibly, the native SarA structure. Two typical winged-helix DNA-binding domains are connected by a well-ordered loop. The interactions between the two domains are extensive and conserved. The putative DNA-binding surface is highly positively charged. In contrast, negatively charged patches are located opposite to the DNA-binding surface. Furthermore, sequence alignment and structural comparison revealed that MarR has folds similar to those of SarR and SarS. Members of the MarR protein family have previously been implicated in the negative regulation of an efflux pump involved in multiple antibiotic resistance in many gram-negative species. We propose that MarR also belongs to the winged-helix protein family and has a similar mode of DNA binding as SarR and SarS and possibly the entire SarA protein family member. Based on the structural differences of SarR, SarS, and MarR

A combined priority scheduling method for distributed machine learning

Abstract Algorithms and frameworks for distributed machine learning have been widely used in numerous artificial intelligence engineering applications. A cloud platform provides a large number of resources at a lower cost and is a more convenient method for such applications. With the rapid development of containerization, native cloud combinations based on Docker and Kubernetes have provided effective resource support for distributed machine learning. However, native Kubernetes does not provide efficient priority or fair resource scheduling strategies for distributed machine learning in computationally intensive and time-consuming jobs, which easily leads to resource deadlock, resource waste, and low job execution efficiency. Therefore, to utilize the execution order between multiple jobs in distributed machine learning as well as the dependencies between multiple tasks for the same job, considering intra- and inter-group scheduling priorities, a combined priority scheduling method is proposed for distributed machine learning based on Kubernetes and Volcano. Considering the user priority, task priority, longest wait time, task parallelism, and affinity and non-affinity between the parameter server and worker nodes, a combined priority scheduling model of inter- and intra-job priority is proposed, which is mapped into a scheduling strategy of inter- and intra-group priorities of pods, enabling the efficient scheduling and training of distributed machine learning. The experiment results show that the proposed method achieves preferential resource allocation for urgent, high parallelism, and high-priority jobs with high-priority users and improves the job execution efficiency. The affinity and anti-affinity settings among pods reduce the time of information interaction between the parameter server and worker nodes to a certain extent, thereby improving the job completion efficiency. This group scheduling strategy alleviates the problems of resource deadlock and waste caused by insufficient resources in cloud computing