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Cooling water systems (CWSs) are extensively utilized in various industries to eliminate the excess heat and converse energy. Studies on CWSs mainly concentrated on finding the optimal cooler network structure. In addition, some works also considered the optimal design under varied operation conditions. However, in these works, once the optimal design of the cooler's network is determined, its arrangement remains fixed and cannot be adapted to accommodate diverse operating conditions. In this work, a flexible topology network concept is proposed to make the adjustment of network structure possible under different operation conditions. The CWS with integrated air cooler and flexible topology network has better overall performance, represented by a mixed integer nonlinear programming (MINLP) model that require advanced tools such as GAMS software. Case studies revealed that the proposed methodology can realize better energy-saving performance, and improve the economic performance under varied operation conditions. The impact of critical flexible nodes on system configuration and economy is achieved by sensitivity analysis.

Abstract Objectives Sabkhas represent polyextreme environments characterized by elevated salinity levels, intense ultraviolet (UV) radiation exposure, and extreme temperature fluctuations. In this study, we present the complete genomes of five bacterial isolates isolated from the sabkha-shore region and investigate their genomic organization and gene annotations. A better understanding of the bacterial genomic organization and genetic adaptations of these bacteria holds promise for engineering microbes with tailored functionalities for diverse industrial and agricultural applications, including bioremediation and promotion of plant growth under salinity stress conditions. Data description We present a comprehensive genome sequencing and annotation of five bacteria (kcgeb_sa, kcgeb_sc, kcgeb_sd, kcgeb_S4, and kcgeb_S11) obtained from the shores of the Abu Dhabi Sabkha region. Initial bacterial identification was conducted through 16 S rDNA amplification and sequencing. Employing a hybrid genome assembly technique combining Illumina short reads (NovaSeq 6000) and Oxford Nanopore long reads (MinION), we obtained complete annotated high-quality gap-free genome sequences. The genome sizes of the kcgeb_sa, kcgeb_sc, kcgeb_sd, kcgeb_S4, and kcgeb_S11 isolates were determined to be 2.4 Mb, 4.1 Mb, 2.9 Mb, 5.05 Mb, and 4.1 Mb, respectively. Our analysis conclusively assigned the bacterial isolates as Staphylococcus capitis (kcgeb_sa), Bacillus spizizenii (kcgeb_sc and kcgeb_S11), Pelagerythrobacter marensis (kcgeb_sd), and Priestia aryabhattai (kcgeb_S4).

الملخص: أهداف البحث: يعد الالتحاق بكليات الطب أمرا مطلوبا للغاية في جميع أنحاء العالم مع وجود منافسة شرسة بين المتقدمين. ومع ذلك، فإن بعض أفضل الطلاب ينسحبون بعد قبولهم في كلية الطب. الهدف من هذه الدراسة هو دراسة تناقص الطلاب الأوائل خلال العامين الأولين في كلية الطب وتحديد علاقته بأدوات اختيار القبول. طريقة البحث: تم إجراء بحث كمي في كلية الطب والعلوم الصحية بجامعة الإمارات العربية المتحدة خلال الفترة من 2016 حتى 2020 حيث تم جمع وتحليل بيانات القبول الروتينية ونتائج امتحانات الطلاب للسنتين الأولى. النتائج: بلغ معدل التناقص خلال فترة الدراسة 31.7٪. كانت درجات الامتحانات الكتابية في المدارس الثانوية والكليات مرتبطة بشكل كبير باجتياز برنامج ما قبل الطب. سجلت الطالبات درجات أعلى بكثير في المقابلات المصغرة المتعددة مقارنة بنظرائهن من الذكور. ومع ذلك، فإن الاختلاف في نتيجة المقابلات المصغرة المتعددة لم يكن مرتبطا بتناقص الطلاب. الاستنتاجات: سبب التناقص المبكر معقد ولا يمكن إرجاعه إلى عامل واحد. كانت نتيجة الدراسة الثانوية في المرحلة الجامعية وامتحان القبول الكتابي من العوامل ذات الأهمية الإحصائية فيما يتعلق بمعدل تناقص الطلاب وانخفاض الأداء الأكاديمي. وأظهرت الدراسة أن الطالبات سجلن درجات أعلى بكثير في اختبارات المقابلة المصغرة المتعددة مقارنة بالطلاب الذكور. ومع ذلك، فإن نتيجة المقابلات المصغرة المتعددة وحدها لم تكن مرتبطة بشكل كبير بتناقص الطلاب. Abstract: Objectives: Placement in medical schools is highly sought after worldwide with fierce competition among applicants. However, some of the best students withdraw after being accepted to medical school. The aim of this study was to investigate early student attrition within the first 2 years of medical school and determine its relationship to admission selection tools. Methods: Quantitative research was conducted at the College of Medicine and Health Sciences from 2016 until 2020, during which time routine admission data and students’ examination results for the first 2 years were collected and analyzed. Results: The attrition rate during the study period was 31.7%. High school and college written examination scores were significantly related to completing the premedical program (p = 0.001 and p = 0.002, respectively). Female students scored significantly higher in multiple mini interviews (MMIs) compared with male counterparts (p

Abstract Salinity stress has detrimental effects on various aspects of plant development. However, our understanding of strategies to mitigate these effects in crop plants remains limited. Recent research has shed light on the potential of sodium acetate as a mitigating component against salinity stress in several plant species. Here, we show the role of acetate sodium in counteracting the adverse effects on oat (Avena sativa) plants subjected to NaCl-induced salinity stress, including its impact on plant morphology, photosynthetic parameters, and gene expression related to photosynthesis and antioxidant capacity, ultimately leading to osmoprotection. The five-week experiment involved subjecting oat plants to four different conditions: water, salt (NaCl), sodium acetate, and a combination of salt and sodium acetate. The presence of NaCl significantly inhibited plant growth and root elongation, disrupted chlorophylls and carotenoids content, impaired chlorophyll fluorescence, and down-regulated genes associated with the plant antioxidant defense system. Furthermore, our findings reveal that when stressed plants were treated with sodium acetate, it partially reversed these adverse effects across all analyzed parameters. This reversal was particularly evident in the increased content of proline, thereby ensuring osmoprotection for oat plants, even under stressful conditions. These results provide compelling evidence regarding the positive impact of sodium acetate on various plant development parameters, with a particular focus on the enhancement of photosynthetic activity.

The current study focuses on the effects of different weather conditions, including temperature and humidity, on the impact energy properties of composite materials tested using a Charpy impact tester connected to a special hygro-thermal device. This is a unique device, handcrafted and equipped with sensors and control panels The composite materials, used in this study, combine polyester and reinforced with fiberglass in various shapes and loadings. Nanopowder materials including titanium oxide nanoparticles (TiO2) and aluminum oxide nanoparticles (Al2O3) were also added to the composite materials and their effects were assessed. The obtained results showed that all the different factors studied in this research have a positive effect on the impact test, except the nanomaterials in both cases (Al2O3 and TiO2 nanopowders) at 2 wt.% of the sample and at approximately 10 wt.%. Hence, at this percentage, there is not enough effect on the impact energy

IntroductionThe emergence and resurgence of pathogens have led to significant global health challenges. Wastewater surveillance has historically been used to track water-borne or fecal-orally transmitted pathogens, providing a sensitive means of monitoring pathogens within a community. This technique offers a comprehensive, real-time, and cost-effective approach to disease surveillance, especially for diseases that are difficult to monitor through individual clinical screenings.MethodsThis narrative review examines the current state of knowledge on wastewater surveillance, emphasizing important findings and techniques used to detect potential pathogens from wastewater. It includes a review of literature on the detection methods, the pathogens of concern, and the challenges faced in the surveillance process.ResultsWastewater surveillance has proven to be a powerful tool for early warning and timely intervention of infectious diseases. It can detect pathogens shed by asymptomatic and pre-symptomatic individuals, providing an accurate population-level view of disease transmission. The review highlights the applications of wastewater surveillance in tracking key pathogens of concern, such as gastrointestinal pathogens, respiratory pathogens, and viruses like SARS-CoV-2.DiscussionThe review discusses the benefits of wastewater surveillance in public health, particularly its role in enhancing existing systems for infectious disease surveillance. It also addresses the challenges faced, such as the need for improved detection methods and the management of antimicrobial resistance. The potential for wastewater surveillance to inform public health mitigation strategies and outbreak response protocols is emphasized.ConclusionWastewater surveillance is a valuable tool in the fight against infectious diseases. It offers a unique perspective on the spread and evolution of pathogens, aiding in the prevention and control of disease epidemics. This review underscores the importance of continued research and development in this field to overcome current challenges and maximize the potential of wastewater surveillance in public health.

This study investigates the photon interaction mechanism of various small molecule radiosensitizers, including Hydrogen Peroxide, Nimorazole, 5-Fluorouracil, NVX-108, and others, using the MCNP 6.3 Monte Carlo simulation code. The simulations focused on quantifying the linear attenuation coefficients, mean free path, and accumulation factors of these radiosensitizers, as well as their interactions in a simulated spherical water phantom irradiated with a 100 keV mono-energetic X-ray source. Our findings reveal significant variations in deposited energy, collision events, and mean free path among the radiosensitizers, indicating different efficacy levels in enhancing radiation therapy. Notably, NVX-108 demonstrated the highest energy deposition, suggesting its potential as a highly effective radiosensitizer. The study also examined the individual attenuation properties of these radiosensitizers against energetic photons, with NVX-108 showing the highest attenuation coefficient and a shorter mean free path, further supporting its superior potential in effective radiosensitization. It can be concluded that NVX-108 has higher interaction tendency with the energetic photons comparing other small-molecules under investigation.

Abstract Alzheimer’s disease (AD) is an incurable neurodegenerative disorder that leads to dementia. This study employs explainable machine learning models to detect dementia cases using blood gene expression, single nucleotide polymorphisms (SNPs), and clinical data from Alzheimer’s Disease Neuroimaging Initiative (ADNI). Analyzing 623 ADNI participants, we found that the Support Vector Machine classifier with Mutual Information (MI) feature selection, trained on all three data modalities, achieved exceptional performance (accuracy = 0.95, AUC = 0.94). When using gene expression and SNP data separately, we achieved very good performance (AUC = 0.65, AUC = 0.63, respectively). Using SHapley Additive exPlanations (SHAP), we identified significant features, potentially serving as AD biomarkers. Notably, genetic-based biomarkers linked to axon myelination and synaptic vesicle membrane formation could aid early AD detection. In summary, this genetic-based biomarker approach, integrating machine learning and SHAP, shows promise for precise AD diagnosis, biomarker discovery, and offers novel insights for understanding and treating the disease. This approach addresses the challenges of accurate AD diagnosis, which is crucial given the complexities associated with the disease and the need for non-invasive diagnostic methods.

The Jolly Phonics Lessons application is a digital tool that is designed to enhance the preschoolers’ reading and writing skills through synthetic phonics approach. This study examined the impact of integrating Jolly Phonics Lessons application into literacy lessons on the emergent reading and writing skills among kindergarten students, ages 4-6, in the United Arab Emirates through a comparative study between pupils (Group-A), whose literacy classes were integrated with the application, and pupils (Group-B) who were taught using the traditional method of teaching literacy. Mixed methods research design was followed to analyze the effects of integrating the application. The Phonemic Awareness Assessment Inventory (PAAI) tool, field notes, and artifacts were utilized to measure the development of students’ letter-sound identification, letter formation, phoneme blending and segmenting abilities. In addition, the paper compared the growth on phonics skills between students in Groups A and B. The results showed that students in Group-A outperformed pupils who received literacy instruction through traditional methods. The findings from the PAAI scores exhibited dramatic growth in letter-sound recognition and letter formation, and substantial increase in phoneme blending and segmenting abilities of Group-A. The T-statistic for differences between two means at 95% confidence revealed that there is a significant difference between the performance of students in Groups-A and B. Implications from this study highlight the positive impact of incorporating Jolly Phonics Lessons application into literacy classes on low-achieving students. On this bases, future research of Jolly Phonics Lesson application to support mixed-ability classes or students with dyslexia.

Background: Mobile phones, used in billions throughout the world, are high-touch devices subject to a dynamic contamination of microorganisms and rarely considered as an important fomite to sanitise systematically. The emergence of SARS-CoV-2 resulted in the COVID-19 pandemic, arguably the most impactful pandemic of the 21st century with millions of deaths and disruption of all facets of modern life globally. Aim: To perform a systematic review of the literature exploring SARS-CoV-2 presence as a contaminant on mobile phones. Methods: A systematic search (PubMed and Google Scholar) of literature was undertaken from December 2019 to March 2023 identifying English language studies. Studies included in this review specifically identified or tested for the contamination of the SARS-CoV-2 virus or genome on mobile phones while studies testing for SARS-COV-2 in environments and/or other fomites samples than but not mobile phones were excluded. Results: A total of 15 studies with reports of SARS-CoV-2 contamination on mobile phones between 2020 and 2023 were included. Amongst all studies, which encompassed ten countries, 511 mobile phones were evaluated for the presence of SARS-CoV-2 contamination and 45% (231/511) were positive for SARS-CoV-2. All studies were conducted in the hospital setting and two studies performed additional testing in residential isolation rooms and a patient’s house. Four studies (3 in 2020 and one in 2021) reported 0% contamination while two other studies (in 2020 and 2022) reported 100% of mobile phone contamination with SARS-COV-2. All other studies report mobile phones positive for the virus within a range of 4–77%. Conclusion: A total of 45% of mobile phones are contaminated with SARS-CoV-2 virus. These devices might be an important fomite vector for viral dissemination worldwide. Competent health authorities are advised/recommended to start a global implementation of mobile phone decontamination by introducing regulations and protocols in public health and health care settings such as the 6th moment of hand washing.

Semantic segmentation is one of most the important computer vision tasks for the analysis of aerial imagery in many remote sensing applications, such as resource surveys, disaster detection, and urban planning. This area of research still faces unsolved challenges, especially in cluttered environments and complex sceneries. This study presents a repurposed Robust UNet (RUNet) architecture for semantic segmentation, and embeds the architecture with attention mechanism in order to enhance feature extraction and construction of segmentation maps. The attention mechanism is achieved using Squeeze-and-Excitation (SE) block. The resulting network is referred to as SE-RUNet. SE is also tested with the classical UNet, termed SE-UNet, to verify the efficiency of introducing SE. The proposed approach is trained and tested using “Semantic Segmentation of Aerial Imagery” dataset. The results are evaluated using Accuracy, Precision, Recall, F-score and mean Intersection over Union (mIoU) metrics. Comparative evaluation and experimental results show that using SE to embed attention mechanism into UNet and RUNet significantly improves the overall performance.

Hydroxyapatite (HAp) polymer composites have gained significant attention due to their applications in bone regeneration and tooth implants. This review examines the synthesis, properties, and applications of Hap, highlighting various manufacturing methods, including wet, dry, hydrothermal, and sol–gel processes. The properties of HAp are influenced by precursor materials and are commonly obtained from natural calcium-rich sources like eggshells, seashells, and fish scales. Composite materials, such as cellulose–hydroxyapatite and gelatin–hydroxyapatite, exhibit promising strength and biocompatibility for bone and tissue replacement. Metallic implants and scaffolds enhance stability, including well-known titanium-based and stainless steel-based implants and ceramic body implants. Biopolymers, like chitosan and alginate, combined with Hap, offer chemical stability and strength for tissue engineering. Collagen, fibrin, and gelatin play crucial roles in mimicking natural bone composition. Various synthesis methods like sol–gel, hydrothermal, and solution casting produce HAp crystals, with potential applications in bone repair and regeneration. Additionally, the use of biowaste materials, like eggshells and snails or seashells, not only supports sustainable HAp production but also reduces environmental impact. This review emphasizes the significance of understanding the properties of calcium–phosphate (Ca-P) compounds and processing methods for scaffold generation, highlighting novel characteristics and mechanisms of biomaterials in bone healing. Comparative studies of these methods in specific applications underscore the versatility and potential of HAp composites in biomedical engineering. Overall, HAp composites offer promising solutions for improving patient outcomes in bone replacement and tissue engineering and advancing medical practices.