The sudden advent of the COVID-19 pandemic and the associated containment measures require educational institutions of all sizes to adopt eLearning as the only option for sustainable education. Despite the numerous Learning Management Systems, the rapid migration to eLearning posed numerous challenges that negatively affect the effectiveness and sustainability of the educational activities. The current study systematically reviewed recent articles that recognized the value and feasibility of using Social Networking Sites (SNSs) in education. The study highlighted the current eLearning challenges and illustrated effective strategies for the sustainable educational use of SNSs by both institutions, teachers, and students. Thus, solutions to the problems experienced in education during the COVID-19 period were highlighted based on SNS-supported strategies.

Autism spectrum disorder (ASD) is associated with significant social, communication, and behavioral challenges. The insufficient number of trained clinicians coupled with limited accessibility to quick and accurate diagnostic tools resulted in overlooking early symptoms of ASD in children around the world. Several studies have utilized behavioral data in developing and evaluating the performance of machine learning (ML) models toward quick and intelligent ASD assessment systems. However, despite the good evaluation metrics achieved by the ML models, there is not enough evidence on the readiness of the models for clinical use. Specifically, none of the existing studies reported the real-life application of the ML-based models. This might be related to numerous challenges associated with the data-centric techniques utilized and their misalignment with the conceptual basis upon which professionals diagnose ASD. The present work systematically reviewed recent articles on the application of ML in the behavioral assessment of ASD, and highlighted common challenges in the studies, and proposed vital considerations for real-life implementation of ML-based ASD screening and diagnostic systems. This review will serve as a guide for researchers, neuropsychiatrists, psychologists, and relevant stakeholders on the advances in ASD screening and diagnosis using ML.

Including learners with autism spectrum disorder (ASD) in mainstream classrooms is associated with challenges that could impede their academic participation. However, studies have shown the value of inclusive education, especially when supported with computer technologies, learners with ASD can effectively learn alongside their non-autistic peers. Despite that, there has been minimal research on ASD inclusion with emerging computer technologies. This paper presents a systematic review of the literature on the application of emerging computer technologies in supporting the inclusion of learners with ASD. By analyzing a wide range of scholarly articles, this research goes beyond the existing literature by thoroughly examining the unique contributions and advancements made in this field. The study findings revealed valuable strategies and technologies for ASD-inclusive education that could be utilized by educationists, researchers, and relevant stakeholders. Moreover, this research bridges the knowledge gap and provides a foundation for future investigations into effective and sustainable technological interventions for ASD-inclusive education.

Problem-solving skills are paramount to university students while learning programming languages. Many researchers have identified a lack of problem-solving skills among university students across various disciplines, but little is known on how certain subjects could ease the acquisition of these skills and vice versa. Educational researchers should focus on exploring the role problem-solving skills could play in preparing students toward standard approaches to learning programming languages. This paper provides an understanding of the difficulties faced by university students while learning programming language using problem-solving skills. The questionnaire used in the study has 32 items categorized into four dimensions of Analysis, Design, Coding and Testing. Data were collected randomly from 113 voluntary participants from Information Technology and Engineering Departments of Near East University, Cyprus. Statistical analysis applied to the data revealed a significant correlation between all the dimensions and existence of a level of difficulties above average on all the dimensions. This research will augment related literary findings and help academicians situate the best practices in teaching problem-solving skills as well as a programming language.

Background: Infections caused by multi-drug resistance (MDR) strains are potentially fatal public health issues worldwide that need pressing attention. Previous reports suggested using snake venom fractions as an effective alternative mechanism to the already available antibacterial drugs. In this study, we conducted a systematic review to analyze the bactericidal effects of snake venom phospholipases (PLA₂s). Methods: From the beginning through 30 March 2022, we searched the PubMed and Embase databases in accordance with the most recent PRISMA recommendations. We also conducted a manual search to identify relevant reports to improve literature coverage. Results: A total of 24 studies were included based on the selection criteria to compile this review. Of them, 16 studies were obtained from the abovementioned databases and eight through manual searches. The other 8 studies were obtained through the references of the included studies. According to the review, we reported that some PLA₂s showed more vigorous bactericidal activity on some Gram-negative and a moderate effect on Gram-negative and Gram-positive. Furthermore, we reported that the presence of p-bromophenacyl bromide (p-BPP) showed a significant decrease in enzymatic and associated antibacterial activities. Moreover, we observed that about 80% of the PLA₂s reported in our systematic review study were those from the Viperidae family, whereas 20% came from the Elapidae family. Moreover, some variations were revealed in the current study regarding the mechanism of actions of the snake venom PLA₂s (svPLA₂s). Conclusion: This systematic review provides a comprehensive overview of the bactericidal effect of snake venom PLA₂s and the analysis of the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of PLA₂s for bacterial strains. Varying bactericidal effects from various snake species and South American rattlesnakes were reported, presenting compelling concepts to the alternative search for therapies against bacterial resistance. Thus, further analysis of the bactericidal effects of other snake venoms PLA₂s considering different strains is needed. Moreover, more data are needed to investigate other bacteria of public health priority using peptides and other purified snake toxins.