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Computer-assisted language assessment literacy (LAL) has gained momentum in English as a foreign language (EFL) teaching since computer-based education became particularly common in language education. As EFL teachers play a critical role in administering computer-assisted language assessments, Iranian EFL teachers need to learn, relearn, and improve their computer-assisted LAL. Iranian EFL teachers can use collaborative reflection (CR) to improve their computer-assisted LAL and practices. This study, therefore, qualitatively investigated how collaborative reflective practices can improve novice and experienced EFL teachers' computer-assisted LAL. To achieve the goals of the present study, we adopted an instrumental case study to explore how EFL teachers perceive the benefits, applications, and challenges of computer-assisted language assessment practices and how teachers could improve their computer-assisted LAL through virtual CR. Four novice and experienced EFL teachers were selected purposively to explore internet-based CR through social media, observations, and interviews. The data were qualitatively analyzed through inductive thematic analysis. The results of the study demonstrated that computer-assisted language assessment practices enhanced the quality of formative assessment and assessment for learning, authenticity, and meaningfulness of tasks, administration, scoring, and interpretation, among others. Furthermore, EFL teachers experienced various personal, social, educational, and professional advantages of their computer-based language assessment practices through internet-based CR. The pedagogical implications of the study for the development of computer-assisted LAL of EFL in-service language teachers through online reflective practices are discussed.

Online teacher education programs can be more situated by engaging student teachers in Internet-based collaborative reflection (ICR) and e-learning-oriented assessment (ELOA) via Web 2.0 technology. Thus, this study explored how the role of English-as-a-foreign-language (EFL) student teachers' ICR practices and ELOA can enhance student teachers' situated online teacher education. In this qualitative study, 15 Iranian EFL student teachers were chosen purposively within a transcendental phenomenology to conduct ICR on ELOA practices during situated learning in online teacher education. The results showed that implementing ICR on ELOA tended to enhance student-centered teacher education; collaborative and reflective teacher development; social, professional, cognitive, and emotional growth; and the connection of teaching, learning, and assessment within online teacher education. More specifically, ELOA practices allowed for meaningful tasks and authentic activities based on practical experience, triggered continuous feedback on EFL student teachers' performance via technology, directed online learning and teaching, and enhanced a performance-based and learning-oriented assessment process. Pedagogical implications for the design of student teacher programs are discussed.

Abstract Atopic dermatitis often begins in infancy and follows a chronic course of exacerbations and remissions. The etiology is complex and involves numerous factors that contribute to skin barrier defect and inflammation. In the Middle East, the burden of atopic dermatitis is understudied. Epidemiological data specific to the Gulf region are scarce but reveal a prevalence of up to about 40% in the United Arab Emirates. Region-specific factors, such as the climate and the frequency of consanguineous marriages, may affect atopic dermatitis incidence, prevalence, and evolution over time. A panel of experts predominantly from the United Arab Emirates analyzed the evidence from published guidelines, and considered expert guidance and local treatment practices to develop clear recommendations for the management of atopic dermatitis in the United Arab Emirates. They encourage a systematic approach for the diagnosis and treatment, using disease severity scores and quality-of-life measurement tools. Treatment recommendations take into consideration both established therapies and the approved systemic biologics dupilumab and tralokinumab, and the Janus kinase inhibitors baricitinib, upadacitinib, and abrocitinib.

The brain plays a central role in controlling and regulating bodily activities. Given its significance, the brain needs to remain in optimal condition to function properly. Neurodegenerative diseases arise when the mechanisms maintaining brain homeostasis fail, resulting in prolonged and uncontrolled activation of cell death pathways. Increasingly, researchers are focusing on specific types of cell death, such as ferroptosis and pyroptosis, due to their potential as targets for preventing and treating neurodegenerative diseases. Brain-derived neurotrophic factor (BDNF) is a crucial growth factor for neurogenesis, neuronal survival, and maintenance, and is thus implicated in cell death mechanisms. This review aims to elucidate the role of BDNF in the ferroptosis and pyroptosis mechanisms that impact brain health. To achieve this, three databases – PubMed, Scopus, and Web of Science – were searched for relevant studies, yielding 95 articles, of which only 14 were aligned with the study’s aim. Ferroptosis (iron-dependent cell death) and pyroptosis (inflammatory cell death) are distinct modes of cell death; however, this review found both mechanisms are associated with oxidative stress. Consequently, the findings suggest that ferroptosis and pyroptosis collectively impact brain health conditions such as depression, cognitive deficiencies, and anxiety, which are notably linked to reduced BDNF levels.

Abstract The growth factor Neuregulin-1 (NRG1) has pleiotropic roles in proliferation and differentiation of the stem cell niche in different tissues. It has been implicated in gut, brain and muscle development and repair. Six isoform classes of NRG1 and over 28 protein isoforms have been previously described. Here we report a new class of NRG1, designated NRG1-VII to denote that these NRG1 isoforms arise from a myeloid-specific transcriptional start site (TSS) previously uncharacterized. Long-read sequencing was used to identify eight high-confidence NRG1-VII transcripts. These transcripts presented major structural differences from one another, through the use of cassette exons and alternative stop codons. Expression of NRG1-VII was confirmed in primary human monocytes and tissue resident macrophages and induced pluripotent stem cell-derived macrophages (iPSC-derived macrophages). Isoform switching via cassette exon usage and alternate polyadenylation was apparent during monocyte maturation and macrophage differentiation. NRG1-VII is the major class expressed by the myeloid lineage, including tissue-resident macrophages. Analysis of public gene expression data indicates that monocytes and macrophages are a primary source of NRG1. The size and structure of class VII isoforms suggests that they may be more diffusible through tissues than other NRG1 classes. However, the specific roles of class VII variants in tissue homeostasis and repair have not yet been determined.

Abstract Suspensions containing microencapsulated phase change materials (MPCMs) play a crucial role in thermal energy storage (TES) systems and have applications in building materials, textiles, and cooling systems. This study focuses on accurately predicting the dynamic viscosity, a critical thermophysical property, of suspensions containing MPCMs and MXene particles using Gaussian process regression (GPR). Twelve hyperparameters (HPs) of GPR are analyzed separately and classified into three groups based on their importance. Three metaheuristic algorithms, namely genetic algorithm (GA), particle swarm optimization (PSO), and marine predators algorithm (MPA), are employed to optimize HPs. Optimizing the four most significant hyperparameters (covariance function, basis function, standardization, and sigma) within the first group using any of the three metaheuristic algorithms resulted in excellent outcomes. All algorithms achieved a reasonable R-value (0.9983), demonstrating their effectiveness in this context. The second group explored the impact of including additional, moderate-significant HPs, such as the fit method, predict method and optimizer. While the resulting models showed some improvement over the first group, the PSO-based model within this group exhibited the most noteworthy enhancement, achieving a higher R-value (0.99834). Finally, the third group was analyzed to examine the potential interactions between all twelve HPs. This comprehensive approach, employing the GA, yielded an optimized GPR model with the highest level of target compliance, reflected by an impressive R-value of 0.999224. The developed models are a cost-effective and efficient solution to reduce laboratory costs for various systems, from TES to thermal management.

Abstract Background Information on previous traumatic dental injuries is important as they can lead to increased complications during orthodontic treatment and impact the treatment planning and outcomes. The aim of this study was to assess the knowledge of Jordanian orthodontists in orthodontic management of traumatized permanent teeth. Methods Cross-sectional survey among active registered orthodontists using a questionnaire distributed by hand. Results The study included 139 orthodontists. Nearly half of orthodontists treated between one to three patients with a history of traumatic dental injuries in the past 3 months. Only 43.2% of the participant asked routinely about history of trauma. A vast discrepancy in times waited before orthodontic movement and in the orthodontic management approach of traumatized teeth was noted. A statistically significant negative relationship between age and knowledge level was found (p = 0.002). A significantly higher level of knowledge was found among participants who had fellowship or board certification than those having the high diploma degree (P-0.032) and also who had treated patients with history of dental trauma in the last 3 months than those who did not (p = 0.001). Conclusions The knowledge of the surveyed orthodontists in both the recommended observation period before orthodontic treatment and management approaches of traumatized teeth during orthodontic treatment was insufficient. Years of clinical experience significantly affected knowledge, with older participants having lower levels of knowledge. Orthodontists who treated patients with history of dental trauma in the last 3 months had significantly higher knowledge in orthodontic management of traumatized teeth. Orthodontists needs to be aware of the proper timing and strategies on orthodontic management of traumatized permanent teeth to improve the long term prognosis and to reduce further complications during orthodontic treatment through proper management.

Abstract Online teacher education programs can be more situated by engaging student teachers in Internet-based collaborative reflection (ICR) and e-learning-oriented assessment (ELOA) via Web 2.0 technology. Thus, this study explored how the role of English-as-a-foreign-language (EFL) student teachers’ ICR practices and ELOA can enhance student teachers’ situated online teacher education. In this qualitative study, 15 Iranian EFL student teachers were chosen purposively within a transcendental phenomenology to conduct ICR on ELOA practices during situated learning in online teacher education. The results showed that implementing ICR on ELOA tended to enhance student-centered teacher education; collaborative and reflective teacher development; social, professional, cognitive, and emotional growth; and the connection of teaching, learning, and assessment within online teacher education. More specifically, ELOA practices allowed for meaningful tasks and authentic activities based on practical experience, triggered continuous feedback on EFL student teachers’ performance via technology, directed online learning and teaching, and enhanced a performance-based and learning-oriented assessment process. Pedagogical implications for the design of student teacher programs are discussed.

Abstract This paper presents a comprehensive approach to harmonizing lunar calendars across different global regions, addressing the long-standing challenge of variations in new crescent Moon sightings that mark the beginning of lunar months. We propose a machine learning (ML)-based framework to predict the visibility of the new crescent Moon, representing a significant advancement toward a globally unified lunar calendar. Our study utilized a dataset covering various countries globally, making it the first to analyze all 12 lunar months over a span of 13 years. We applied a wide array of ML algorithms and techniques. These techniques included feature selection, hyperparameter tuning, ensemble learning, and region-based clustering, all aimed at maximizing the model’s performance. The overall results reveal that the gradient boosting (GB) model surpasses all other models, achieving the highest F1 score of 0.882469 and an area under the curve (AUC) of 0.901009. However, with selected features identified through the ANOVA F-test and optimized parameters, the Extra Trees model exhibited the best performance with an F1 score of 0.887872, and an AUC of 0.906242. We expanded our analysis to explore ensemble models, aiming to understand how a combination of models might boost predictive accuracy. The Ensemble Model exhibited a slight improvement, with an F1 score of 0.888058 and an AUC of 0.907482. Additionally, the geographical segmentation of the dataset enhanced predictive performance in certain areas, such as Africa and Asia. In conclusion, ML techniques can provide efficient and reliable tool for predicting the new crescent Moon visibility that would support the decisions of marking the beginning of new lunar months.

In this work, we analyze the approximate solution of a specific partial integro-differential equation (PIDE) with a weakly singular kernel using the spectral Tau method. It present a numerical solution procedure for this PIDE, which is transferred into a Volterra–Fredholm integral equation (VFIE), and the spectral method is performed on VFIE. In some illustrated examples, we show that the VFIE problem has high numerical stability with respect to the original form of the PIDE problem. For this aim, we apply the spectral Tau method in two cases, first for the problem in the form of VFIE and then also for the problem in the form of PIDE. The remarkable numerical results obtained from the VFIE problem form compared to those gained from the PIDE problem form show the efficiency of the proposal method. Also, we prove the convergence theorem of the numerical solution of the Tau method for the VFIE problem, and then it is generalized to the PIDE problem.

This work is focused on increasing the capturing efficiency of carbon dioxide (CO2) through flue gas purification systems. To maximize the CO2 capture process, many process variables such as temperature, flow rates, absorbent concentrations, and nanoparticles were investigated. This study describes the use of a polypropylene hollow fiber membrane contactor to separate CO2 from nitrogen using different solvents, including Potassium carbonate (K2CO3), N-methyl diethanolamine (MDEA), and monoethanolamine (MEA). Also, the presence of silica nanoparticles and piperazine (PZ) enhances the process performance. On the other hand, the amine and mixed amino absorbents MDEA-PZ and MDEA-MEA were prepared and compared based on the absorption capacity. The optimal order of amine absorbent performance when applied to CO2 membrane absorption is MDEA-MEA followed by MDEA-PZ. At a solute concentration of 9%, MDEA-MEA exhibits the highest CO2 removal efficiency, which is 74.12%. However, at a concentration of 11%, MEA, MDEA-PZ, and MDEA have the highest CO2 removal efficiencies of 80.15%, 75.13%, and 63.12%, respectively.

The coronavirus disease 2019 (COVID-19) pandemic that was spread worldwide since 2019 and showed a highly contagious character affecting the lifestyle of people worldwide causing symptoms that are not limited to the respiratory system only but had multi-systemic effects that may progress to severe complications that roughly affect people's health. A newly recognized SARS-CoV-2-associated syndrome called pediatric multisystem inflammatory syndrome has been described worldwide. Initially, it was reported as hyper-inflammatory shock and “Kawasaki-like” symptoms with fever and conjunctivitis, a similar syndrome is also reported in neonates and called Multisystem Inflammatory Syndrome of neonates (MIS-N). In this paper, we presented a case of a newborn baby girl born by caesarian section affected by multisystem inflammatory syndrome of neonates presenting with respiratory distress on her third day of life, then she developed bilateral pneumothorax and pneumomediastinum respectively that required intubation, which highlights that the recognition of pneumothorax and pneumomediastinum as potential presentations of immunoglobulin G (IgG) positive MIS-N in newborns remains crucial.