Abstract: Cleft palate is a congenital condition result from incomplete fusion of palatine shelves. The current study aimed to assess the effects of vitamin B6 on the incidence of corticosteroid-induced cleft palate model. Eighteen pregnant mice were divided into three groups. Mice of control group were injected with sterile physiological saline from 11th - 14th days of gestation. Mice of group II were injected with 125 mg/kg hydrocortisone from 11th - 14th days of gestation. Mice of group III were injected with hydrocortisone as in group II and given drinking water containing 500 µg/ml of vitamin B6 from day zero of gestation until delivery. Two days after delivery, the offspring were counted, and their head circumferences were taken for statistical analysis. The heads of the offspring were fixed and processed for paraffin sectioning and stained with hematoxylin and eosin. Cleft palates were counted and statistically analyzed using ANOVA test to determine any significances (P

The advent of social commerce (SC) has transformed the landscape of online consumer behavior, emphasizing the significance of customer-to-customer relations in shaping sustainable relation-ships with customers. This research investigated the intricate relationships between social com-merce dimensions, particularly suggestions and recommendations, forums and communities, and ratings and reviews, and their influence on customer-to-customer value co-creation (C2CVCC) and sustainable customer relationships (SCRs). A questionnaire was designed and administered to 635 respondents. We examined the psychometric properties of the measurements and subse-quently applied Partial Least Squares as a Structural Equation Modeling method (PLS-SEM) for hypothesis testing. The findings reveal that the dimensions of SC significantly impact C2CVCC, with ratings and reviews playing a pivotal role. Furthermore, C2CVCC emerges as a substantial mediator in the path between SC and SCRs. The empirical analysis showcases strong support for the proposed model, with robust path coefficients (β) and p-values confirming direct and indirect effects. These findings offer valuable insights for businesses seeking to leverage SC and customer interactions to enhance SCRs in the digital era. Understanding the dynamics of C2CVCC within the context of SC has become essential for marketers and businesses aiming to thrive in today's competitive online marketplace.

Immune checkpoint inhibitors (ICI) are a promising form of immunotherapy that has significantly changed the therapeutic landscape for many advanced cancers. They have shown unique clinical benefit against a broad range of tumour types and a strong overall impact on survival in studied patient populations. However, there are still many limitations holding back this immunotherapy from reaching its full potential as a possible curative option for advanced cancer patients. A great deal of research is being undertaken in the hope of driving advancements in this area, building a better understanding of the mechanisms behind immune checkpoint inhibition and ultimately developing more effective, safer, and wider-reaching agents. Taking into account the current literature on this topic, this review aims to explore in depth the basis of the use of ICIs in the treatment of advanced cancers, evaluate its efficacy and safety, consider its current limitations, and finally reflect on what the future holds for this very promising form of cancer immunotherapy.

Abstract Background: Hypochlorous acid (HA) is a potent disinfectant with broad-spectrum antimicrobial activity against bacteria, fungi, and viruses. Aim: This study aimed to investigate the factors that influence the stability of hypochlorous acid (HOCl) and their impact on its disinfectant properties Methods: This study explored the stability of hypochlorous acid, emphasizing factors that affect its disinfectant efficiency, such as pH level, temperature, and the presence of organic materials. Findings: Our investigation revealed that HOCl is the most stable and effective disinfectant under weakly acidic conditions, where the undissociated form of hypochlorous acid is predominant. Although it is stable under various conditions, its efficacy is compromised by the presence of heavy metals, organic matter, and UV radiation. Conclusions: This comprehensive analysis concludes that, while hypochlorous acid is a highly effective disinfectant, understanding and maintaining the optimal conditions for its stability is crucial for maximizing its disinfection potential. Implications: The findings can be used to formulate new guidelines and regulations to guide the proper formulation, storage, and use of stable HOCL as disinfectants.

Wetland ecosystems in the Qinghai-Tibet Plateau are pivotal for global ecology and regional sustainability, contributing significantly to terrestrial ecosystems by regulating runoff, mitigating floods, and enhancing water quality. This study investigates the dynamic changes in wetland ecosystems within the Chaidamu Basin and their response to drought, aiming to foster sustainable wetland utilization in the Qinghai-Tibet Plateau. Using Landsat TM/ETM/OLI data on the Google Earth Engine platform, we employed a random forest method for annual long-term land cover classification. Meteorological drought conditions were assessed using SPEI3, SPEI6, SPEI9, and SPEI12, derived from monthly precipitation and evapotranspiration data. Pearson correlation analysis examined the relationship between wetland changes and various SPEI scales. The BFASAT method evaluated the impact of SPEI12 trends on wetlands, while cross-wavelet analysis explored teleconnections between SPEI12 and atmospheric circulation factors. Our findings revealed that the land cover dataset of the Chaidamu Basin (1990-2020) exhibited diverse categories with high classification accuracy (OA: 90.27%, Kappa: 88.34%). Wetlands, including lake, glacier, and marsh types, exhibited a noticeable increasing trend. Wetland expansion occurred during specific periods (1990-1997, 1998-2007, 2008-2020), featuring extensive conversions between wetland and other types, notably from other types to wetlands. Spatially, lake and marsh wetlands predominated in the low-latitude basin, while glacier wetlands were situated at higher altitudes. The study identified significant negative correlations between SPEI at various scales and total wetland area and types, with SPEI12 exhibiting the most substantial effect between September and December (r <-0.75) on wetlands. SPEI12 displayed a decreasing trend with non-stationarity and distinct breakpoints in 1996, 2002, and 2011, indicating heightened drought severity. Atmospheric circulation indices (ENSO, NAO, PDO, AO, WP) exhibited varying resonance with SPEI12, with NAO, PDO, AO, and WP demonstrating longer resonance times and pronounced responses.The continuous growth of wetlands amidst increasing aridification emphasizes the need for thoughtful wetland development to establish a sustainable "forest-lake-grass-field-river" ecological community. These findings underscore the significance of comprehending wetland changes and drought dynamics for effective ecological management in the Chaidamu Basin of the Qinghai-Tibet Plateau.

This enables the chip to regulate the voice recognition function of the gadget, leading to a more natural and human-like process. Integrating this technique into the English language voice recognition system can greatly improve its precision in identifying the speech of a particular person. This research seeks to investigate and create an automatic error detection technique for an embedded speech instruction recognition system for English using artificial intelligence. The study commences with a conventional introduction to artificial intelligence, thereafter delving into a comprehensive investigation of the speech recognition algorithm. The MATLAB programme is used to determine the accurate number of words recognised by the system and its accuracy rate. The embedded teaching recognition system for English is then tested in different contexts to assess its performance. Several tests are performed to compare and analyse the results, which indicate that the integrated English voice recognition system achieves an accuracy rate of over 90% and has a low error rate in a calm environment. In a bustling environment with numerous auditory stimuli, the accurate recognition rate typically exceeds 60%.

As the global transition towards renewable energy accelerates, the integration of grid-scale energy storage systems has become increasingly critical for stabilizing energy supply and enhancing grid reliability. Among various storage technologies, lithium-ion batteries stand out for their high energy density, scalability, and relatively low environmental impact. This study investigates the performance and longevity of lithium-ion batteries in grid-scale applications, focusing on the impact of operational parameters such as cycling frequency, depth of discharge, temperature fluctuations, and charging/discharging rates. Employing a mixed-methods approach, we combined quantitative analysis of performance metrics (cycle life, capacity fade, efficiency) with qualitative assessments from case studies of existing grid-scale projects. Our findings reveal that while lithium-ion batteries exhibit robust performance in grid-scale storage, their longevity and efficiency are significantly influenced by operational conditions. Specifically, temperature management and optimized cycling strategies were identified as key factors in mitigating degradation and extending battery life. This research provides a comprehensive understanding of lithium-ion battery behavior in grid-scale environments, offering valuable insights for the design, optimization, and management of energy storage systems. By addressing the challenges of battery performance and longevity, our study contributes to the development of more sustainable and reliable grid storage solutions, facilitating the broader adoption of renewable energy sources.

This study aimed to introduce a novel machine learning (ML) model designed to predict the need of interventions during endoscopy in patients with upper gastrointestinal bleeding (UGIB). The risk stratification tools in current use, such as the Glasgow Blatchford Score (GBS) and pre-endoscopic Rockall score, have limitations in accurately predicting the need for endoscopic interventions. All patients diagnosed with UGIB from January 2013 to October 2023 who underwent endoscopy were included in the study. Variables extracted included demographics, social history ,clinical history, clinical presentation and symptoms, drug history, management prior to endoscopy, findings during endoscopy, laboratory variables and vitals, and post-endoscopic results. Three machine learning models including Random Forest Classifier (RFC), Gradient Boosting Classifier (GBC), and AdaBoost Classifier were used to evaluate the need for intervention during endoscopy in our study. A total of 1372 patients were included from three major hospitals in Jordan, of whom 242 underwent endoscopic intervention. The GBC outperformed all other models and pre-endoscopic scores in predicting the need for endoscopic intervention with an area under the curve of 0.861. Findings during endoscopy, platelet count, pulse rate and systolic blood pressure during admission were the most contributing features in predicting the need for the need of endoscopic intervention. This study highlights the potential of machine learning models in enhancing decision making for UGIB management.

Rhodotorula mucilaginosa fungaemia is rare and highly resistance to antifungal therapy. We herein report a case involving a 31-year-old male admitted after a high-velocity road traffic accident. He sustained a grade IV liver injury with right hepatic vein thrombosis, necessitated an urgent laparotomy. Post-operatively, repeated imaging of the abdomen revealed presence of biloma. Percutaneous subdiaphragmatic drainage was done but appeared ineffective, prompting second surgery for a urgent hemi-hepatectomy. Patient then was nursed in the intensive care unit (ICU) however during his stay in the ICU he became more sepsis evident by worsening ventilatory support and rise in septic parameters from the biochemistry parameters. Despite on intravenous piperacillin-tazobactam and fluconazole, his septic parameters did not improve and a full septic workup was done and was found to be positive for Rhodotorula mucilaginosa from the blood cultures. After discussion with the infectious disease physicians and clinical microbiologist, it was decided to initiate a course of intravenous meropenem and amphotericin B based on minimum inhibitory concentration (MIC) values, considering the patient's extended ICU stay and catheter use. Eventually, successful weaning off mechanical ventilation was discharge from ICU care. This case underscores the necessity of individualized approaches, combining timely imaging, appropriate drainage techniques, and tailored treatments to optimize outcomes for such intricate post-traumatic complications.

BACKGROUND: Lower limb skeletal muscle ischemia-reperfusion (IR) injury associated with increased morbidity and mortality is common in several clinical situations such as aortic aneurysms repairment, peripheral arterial surgery, vascular injury repairment, and shock. Although it is generally accepted that oxidative stress mediators have a significant role in IR injury, its precise mechanism is still unknown. Anecdotally, it is sustained not only by structural and functional changes in the organ it affects but also by damage to distant organs. The purpose of this report is to illustrate the effect of proanthocyanidin on IR injury. METHODS: In our study, 18 male Wistar albino rats were used. The subjects were divided into three groups of six each. (Group Control-C, Group Ischemia-Reperfusion -IR, Group Ischemia-Reperfusion and Proanthocyanidin-IR-PRO). Intraperitoneal proanthocyanidin was given to the IR and proanthocyanidin groups 30 minutes before laparotomy and 1-hour ischemia led to these two groups. After one hour, reperfusion started. Muscle atrophy-hypertrophy, muscle degeneration-congestion, fragmentation-hyalinization, muscle oval-central nucleus ratio, leukocyte cell infiltration, catalase enzyme activity, and TBARS were all examined in lower-limb muscle samples after one hour of reperfusion. RESULTS: When skeletal muscle samples were evaluated histopathologically, it was discovered that muscle atrophy-hypertrophy, muscle degeneration-congestion, fragmentation-hyalinization, and leukocyte cell infiltration with oval-central nucleus standardization were significantly higher in the IR group than group control and group IR-proanthocyanidin. Besides, oval-central nucleus standardization was significantly higher in the IR and proanthocyanidin group than in the control group. TBARS levels were significantly higher in the IR group than in the control and IR-proanthocyanidin groups while, catalase enzyme activity was found to be significantly lower in the IR group than in the control and IR and proanthocyanidin groups. CONCLUSION: As a consequence of our research, we discovered that proanthocyanidins administered before IR have a protective impact on skeletal muscle in rats. Further research in this area is required.

Evolution remains an incessant process in viruses, allowing them to elude host immune response and induce severe diseases, impacting the diagnostic and vaccine effectiveness. Predicting emerging viral genomes is crucial, particularly in diseases like dengue, where viruses disrupt host cells, leading to fatal outcomes. Deep learning has been applied to predict dengue fever cases; there has been relatively less emphasis on its significance in forecasting emerging Dengue Virus (DENV) serotype. While Recurrent Neural Networks (RNN) were originally designed for modeling temporal sequences, our proposed DL-DVE generative and classification model, trained on complete genome data of DENV, transcends traditional approaches by learning semantic relationships between nucleotides in a continuous vector space instead of representing contextual meaning of nucleotide characters. Leveraging 2000 publicly available DENV complete genome sequences, our Long Short-Term Memory (LSTM) based generative and Feedforward Neural Network (FNN) based classification DL-DVE model showcases proficiency in learning intricate patterns and generating sequences for emerging serotype of DENV. The generative model showed accuracy of 93% and the classification model provided insight into the specific serotype label, corroborated by BLAST search verification. Evaluation metrics such as ROC-AUC value 0.818, accuracy, precision, recall and F1 score all to be around 99.00%, demonstrated the classification model’s reliability.  Our model classified the generated sequences as DENV-4, exhibiting 65.99% similarity to DENV-4 and around 63-65% similarity with other serotypes, indicating notable distinction from other serotypes. Moreover, the intra-serotype divergence of sequences with a minimum 90% similarity underscored their uniqueness. We analyzed the conserved motifs in the genome through MEME Suite (version 5.5.5). Our research strives to contribute to the ongoing fight against the Dengue virus by offering predictive insights into its genomic evolution. Looking ahead, proactive predictive modeling before mutations occur holds potential for guiding vaccine design and diagnostic kit development.

The escalating levels of atmospheric carbon dioxide (CO₂) due to anthropogenic activities have raised significant concerns regarding their far-reaching consequences, including potential impacts on human brain function. This study employs Agent-Based Modeling (ABM) and a comprehensive literature review to comprehensively examine the effects of varying atmospheric CO₂ concentrations on human brain activity. Historical and projected CO₂concentration data, along with neuroscientific insights, were integrated into the ABM framework to simulate brain activity responses under different CO₂ scenarios. The simulations revealed that elevated CO₂ levels disrupt neural activity and alter neurotransmitter profiles, indicating potential cognitive consequences. Sensitivity analysis emphasized the importance of accurate parameterization for robust simulations. The findings underscore the urgent need to address global CO₂ emissions to preserve cognitive health. Further research is essential to validate and refine the model, incorporating additional factors for a comprehensive understanding of the cognitive repercussions of rising CO₂ levels, crucial for informed policy-making and public awareness campaigns.

Background: Asthma is a widespread chronic respiratory disease that poses a significant public health challenge. The current study investigated the associations between air pollution and asthma severity among individuals residing near the Sohar industrial port (SIP) in Oman. Despite the presence of multiple major industrial complexes in Oman, limited knowledge regarding their impact on respiratory health is accredited. Hence, the primary objective of this study is to offer valuable insights into the respiratory health consequences of industrial air pollution in Al Batinah North. Methods: The state health clinics' records for patient visits related to asthma were collected for the timeframe spanning 2014 to 2022. Exposure was defined as the distance from SIP, Majan Industerial Area (MIA) and Sohar Industerial Zone (SIZ) to determine high, intermediate, and low exposure zones (12 km, respectively). Exposure effect modifications by age, gender, and smoking status were also examined. Results: The conducted cross-sectional study of 410 patients (46.1% males and 53.9% females) living in over 17 areas around SIP revealed that 73.2% of asthmatics were under 50 years old, with severity significantly associated with closeness to the port. Risk ratios were estimated to be (RR:2.42; CI95%: 1.01–5.78), (RR:1.91; CI95%: 1.01–3.6), and (RR:1.68; CI95%: 0.92–3.09) for SIP, MIP and SIZ areas, respectively, compared to the control area. Falaj Al Qabail (6.4 km) and Majees (6 km) had the highest number of asthma patients (N. 69 and N. 72), and highest percentages of severe asthma cases among these patients (28% and 24%) with significant risk ratios (RR:2.97; CI95%: 1.19–7.45 and RR:2.55; CI95%: 1.00–6.48), correspondingly. Moreover, severe asthma prevalence peaked in the 25-50 age group (RR:2.05; CI95%: 1.26–3.33), and this linkage between asthma and age was much more pronounced in males than females. Smoking and exposure to certain contaminant (dust and smoke) increased also the risk of severe asthma symptoms, but their effects were less important in the high risk zone, suggesting much more important risk factor. A neural network model accurately predicted asthma risk (94.8% accuracy), with proximity to Sohar Industrial Port as the most influential predictor. Conclusion: The study highlights the High asthma burden near Sohar Industrial Port, linked to port proximity and smoking and wind direction as major risk factors. These findings inform vital public health policies to reduce air pollution and improve respiratory health in the region, prompting national policy review.

Over the years, the need for autonomous systems such as drones, also known as unmanned aerial vehicles (UAVs), has significantly increased in popularity across several industries, including the military. The Internet of Battlefield Things (IoBT) represents a modern technological advancement that significantly enhances the operational efficacy of defense systems. It establishes an integrated military force by connecting individuals to intelligent technology in drones, radios, equipment, antennas and ground stations. This is achieved through the utilization of cloud and edge computing, sensors, mobile devices, embedded systems, and IoT-based systems. However, IoBT security is significantly compromised by enemies that exploit the vulnerabilities and malicious intrusions that specifically target the external environment or to obtain sensitive data. In addition, a comprehensive understanding of cyberattacks and countermeasures is essential for assuring the security of IoBT. On the other hand, as cyber threats get more complicated, trust becomes increasingly important for the security of digital systems. Within this context, the zero trust architecture contends that the security of a complex network is inherently vulnerable to internal and external threats. In defense, UAV security system applications, for example, the primary purpose of the zero trust architecture is to limit the vulnerability of military UAV systems to cyberattacks, hence reducing the possibility of data breaches and illegal entry. This study conducts a systematic review aimed at identifying different aspects of cybersecurity strategies for protecting UAV systems within the IoBT domain. Furthermore, zero trust architecture is presented in the study as an effective prospective solution to the security issues that develop in defense UAV systems.

It has been shown that Human papillomavirus (HPV) infection is associated with several forms of cancer. Additionally, although there are more than 100 types of HPV, more than ten types of it, including types 16 and 18, are considered high-risk. The two proteins that make up the viral capsid of HPV 16 are L1, the major capsid protein, and L2, the minor capsid protein. FDA (The Food and Drug Administration) approved HPV vaccines mostly target L1 and L2 capsid proteins, which facilitate intracellular entry during infection. In this study, it was set out to analyze the creation of phylogenetic relations of L1 nucleic acid sequences of viral isolates. This study also analyzed sequences of three key elements within the amino acid sequences of HPV 16 L1: loops critical for structural stability, nuclear localization signal sequences, and residues implicated in viral attachment. As highlighted by the literature, these elements represent pivotal aspects of viral function. Furthermore, the report highlighted the particular inter-sequence variability within the HPV 16 L1 protein sequences. Overall analysis revealed clustering of sequences primarily due to geographical and characterized by more phylogenetic relatedness within location-specific clusters.

Candida (C.) infections represent a serious health risk for people affected by inflammatory bowel disease. An important fungal virulence factor is the capacity to form biofilms on the colonized surface of the host. This research study aimed to determine the effect of C. tropicalis and C. albicans co-infection on dextran sodium sulfate (DSS)-induced colitis in mice. Colitis severity was evaluated using histology and colonoscopy. Mice were mono-inoculated with C. albicans, C. tropicalis or co-challenged with both species. Mice were administered 3% DSS to induce acute colitis. Biofilm activity was assessed using (2-methoxy-4-nitro-5-sulfophenyl)-5-[(phenylamino)carbonyl] 2H-tetrazoliumhydroxide (XTT) assay. Abundance of C. albicans in the colon tissues was assessed by immunohistochemistry. Co-challenged mice showed decreased colitis severity compared to mono-inoculated mice. The XTT assay demonstrated a marked decrease of C. albicans biofilm production in a C. albicans culture incubated with C. tropicalis supernatant. Immunohistochemical staining showed that C. albicans was more abundant in the mucosa of C. albicans mono-inoculated mice compared to the co-inoculated group. These data indicate an antagonistic microbial interaction between the two Candida species, where C. tropicalis may produce molecules capable of limiting the ability of C. albicans to adhere to the host intestinal surface leading to a reduction in biofilm formation.

Chronic kidney disease (CKD) bears a heavy burden on patients and the health care system as whole. The incidence of CKD has been increasing in the Arab world over the years due to increases in Diabetes and hypertension which are the most prominent causes of CKD. Syrians are at higher risk for diabetes and hypertension due to the crisis that the country has been going through. 297 patients’ charts were examined in the kidney surgical hospital in Damascus Syria to determine risk factors for CKD, prevalence of diabetes among them and its associating demographic factors along with changes in serum creatinine, urea, fasting blood glucose levels and MDRD score among diabetic CKD patients. 64.6% of patients were above 50, 61.6% were males and 35.4% were diabetic. Patients with diabetes had lower creatinine levels upon admission than non-diabetics. The correlation between fasting blood glucose level and serum creatinine, urea and MDRD was not statistically significant. This paper shows that the prevalence of diabetes among CKD patients is similar in Syrians to the rest of the world despite the increase of diabetes incidence.

Background: Maternal diabetes mellitus (MDM) is associated with increased risks for adverse neonatal outcomes. However, the impact of MDM on neonatal outcomes in Bisha, a city in Saudi Arabia, is not well-documented. This study aims to investigate the impact of MDM on neonatal outcomes in the Maternity and Children’s Hospital (MCH), Bisha, Saudi Arabia. Methods: A retrospective cohort study was conducted on 181 pregnant women with diabetes and their neonates diagnosed at Maternity and Children’s Hospital (MCH), Bisha, Saudi Arabia, between October 5, 2020, and November 5, 2022. The primary outcome was a composite of adverse neonatal outcomes, including stillbirth, neonatal death, macrosomia, preterm birth, respiratory distress syndrome, hypoglycemia, and congenital anomalies. Logistic regression analyses were used to adjust for potential confounders. Results: The total sample size was 181. The average age of patients was 34 years (SD=6.45). The majority of the patients were diagnosed with GDM, 147 (81.2%), and pre-GDM, 34 (18.8%). Neonates born to mothers with MDM had a higher risk of adverse neonatal outcomes compared to those born to mothers without MDM (adjusted odds ratio [aOR] = 1.46, 95% confidence interval [CI]: 1.25-1.70). The risks of macrosomia (aOR = 1.74, 95% CI: 1.38-2.19), LBW (aOR = 1.32, 95% CI: 1.06-1.66), and RDS (aOR = 1.57, 95% CI: 1.28-1.93) were significantly higher among neonates born to mothers with MDM. Types of DM were statistically significant with some neonatal outcomes: hypoglycemia (p-value = 0.017), macrosomia (p-value = 0.050), and neonatal death (p-value = 0.017). Conclusion: MDM is associated with an increased risk of adverse neonatal outcomes in Bisha. Early identification and management of MDM may improve neonatal outcomes and reduce the burden of neonatal morbidity and mortality in this population.

Human action recognition (HAR) based on skeleton data is a challenging yet important technique because of its wide range of applications in many fields, including patient monitoring, security surveillance, and observing human-machine interactions. Many algorithms that attempt to distinguish between many types of activities have been proposed. However, most practical applications require highly accurate detection of specific types of activities. In this study, a novel and highly accurate spatiotemporal graph autoencoder network for HAR based on skeleton data is proposed. Furthermore, an extensive study was conducted using different modalities. For this purpose, a spatiotemporal graph autoencoder that automatically learns spatial as well as temporal patterns from human skeleton datasets was built. The powerful graph convolutional network named GA-GCN, developed in this study, notably outperforms most of the existing state-of-the-art methods based on two common datasets, namely NTU RGB+D and NTU RGB+D 120 . On the first dataset, we achieved an accuracy of 92.3% and 96.7% based on the cross-subject and cross-view evaluations, respectively. On the other more challenging dataset (i.e. NTU RGB+D 120), GA-GCN achieved 88.8% and 90.4% based on the cross-subject and cross-set evaluation, respectively.

Batch and transport experiments were used to investigate the remediation of a loamy sand soil contaminated with Cr(VI) using zero valent iron nanoparticles (nZVI) stabilized by the carboxy methyl cellulose (CMC-nZVI). The effect of pH, ionic strength (IS), and flow rate on the removal efficiency of Cr(VI) were investigated under equilibrium (uniform transport) and non-equilibrium (Two-site sorption) transport using the Hydrus-1D model. The overall removal efficiency ranged from 70 to over 90% based on the chemical characteristics of the CMC-nZVI suspension and the transport conditions. The concentration and pH of the CMC-nZVI suspension had the most significant effect on the removal efficiency and transport of Cr(VI) in the soil. The average removal efficiency of Cr(VI) was increased from 24.1 to 75.5% when the concentration of CMC-nZVI nanoparticles was increased from 10 to 250 mg L-1, mainly because of the increased total surface area at larger particle concentration. Batch experiments showed that removal efficiency of Cr(VI) was much larger under acidic conditions. The average removal efficiency of Cr(VI) reached 90.1 and 60.5 % at pH 5 and 7, respectively. The Two-site sorption model described quite well (r2 = 0.96-0.98) the transport of Cr(VI) in soil as compared to the uniform transport model (r2 = 0.81-0.98). The average retardation of Cr(VI) was 3.51 and 1.61 at pH 5 and 7, respectively, indicating earlier arrival for the breakthrough curves and shorter time to reach maximum relative concentration at lower pH. The Hydrus-1D model has proven to be an efficient tool for assessing the removal of Cr(VI) pollutants, offering innovative, cost-effective, and environmentally friendly remediation methodologies.

Objective: Lower extremity ischemia-reperfusion injury (IRI) may occur with trauma-related vascular injury and various vascular diseases, during the use of a tourniquet, temporary clamping of the aorta in aortic surgery, and acute or bilateral acute femoral artery occlusion. Mitochondrial dysfunction and increased basal oxidative stress in diabetes may cause an increase in the effects of increased reactive oxygen species (ROS) and mitochondrial dysfunction due to IRI. It is of great importance to examine therapeutic approaches that can minimize the effects of IRI, especially for patient groups under chronic oxidative stress. Cerium oxide (CeO2) nanoparticles mimic the antioxidant enzymes and act as a catalyst that scavenges ROS. In this study, it was aimed to investigate whether CeO2 has protective effects on skeletal muscles in lower extremity IRI in mice with streptozocin-induced diabetes. Methods: A total of 38 Swiss albino mice were divided into six groups as follows: control group (group C, n=6), diabetes group (group D, n=8), diabetes-CeO2 (group DCO, n=8), diabetes-ischemia/reperfusion (group DIR, n=8), and diabetes-ischemia/reperfusion-CeO2 (group DIRCO, n=8). DCO and DIRCO groups were given doses of CeO2 0.5mg/kg intraperitoneally 30 minutes before the IR procedure. A 120-minute ischemia-120-minute reperfusion period with 100% O2 was performed. At the end of the reperfusion period, muscle tissues were removed for histopathological and biochemical examinations. Results: Total antioxidant status (TAS) levels were found to be significantly lower in group DIR compared with group D (p=0.047 and p=0.022, respectively). In group DIRCO and total oxidant status (TOS) levels were found to be significantly higher than in group DIR (p

A microfinance scheme has emerged as a crucial tool in reducing poverty gaps in many developing countries. A notable player in the arena is Amanah Ikhtiar Malaysia (AIM), a pioneer in microfinancing in Malaysia since 1987. AIM’s microfinance program injects small-scale businesses, particularly benefiting single mother entrepreneurs, contributing to capacity-building and empowerment. However, the advent of the COVID-19 pandemic, coupled with Movement Control Order (MCO), has adversely affected various business sectors and vulnerable groups, including single mothers engaged in microfinancing enterprises. This study employs primary data to assess the impact of AIM’s microfinancing programs on single-mother entrepreneurs during the crisis. Utilizing a quantitative approach with a two-stage sampling process involving 422 respondents in urban areas, the research evaluates the relationship between empowerment indicators (economic, social, digital, and psychological) and management and governance aspects of program effectiveness. The findings reveal that the microfinancing program’s overall effectiveness, economic, digital and psychological empowerment indicators, and program management are at a moderate level, while social empowerment is high. Economic and digital empowerment, along with effective management, positively and significantly influence program effectiveness, whereas social empowerment has a negative and significant impact. The study concludes with recommendations for enhancing AIM’s microfinance program, equipping single mother entrepreneurs to better navigate future challenges, and informing policy formulation related to their empowerment.

Light is an electromagnetic radiation that has visible and invisible wavelength spectrum. The visible light can only be detected by the eyes through the optic pathways. With the presence of scalp, cranium and meninges, the brain is seen as being protected from direct exposure to light. For that reason, the brain can be viewed as a black body lying inside a black box. In physics, a black body tends to be in thermal equilibrium with its environment and can tightly regulate its temperature via thermodynamics principles. Therefore, a healthy brain inside a black box should not get exposed to light. On the contrary, photobiomodulation, a form of light therapy to the brain has been shown to have beneficial effects for some neurological conditions. The proposed underlying mechanisms are multiple. Herein we present our intraoperative findings of rapid electrocorticographic brainwave changes when the brain was shone directly with different wavelengths of light during awake brain surgery. Our findings provide literature proof on light’s ability to influence human brain energy and function. Our proposed mechanism for these rapid changes is the presence of plasma-like energy inside the brain which causes fast brain activities that are akin to lightning strikes.

Polyphenols, long-used components of medicinal plants, have drawn great interest in recent years as potential therapeutic agents because of their safety, efficacy, and wide range of biological effects. Approximately 74% of the world's population still uses plant-based medicines, indicating the ongoing significance of phytochemicals for human health. The study emphasizes the growing body of research examining the role of polyphenols in uncovering their anti-adipogenic and anti-obesity properties. Functions of polyphenols including phenylpropanoids, flavonoids, terpenoids, alkaloids, glycosides, and phenolic acids are distinct due to changes in chemical diversity, and structural characteristics. This review methodically investigates the mechanism of how naturally occurring polyphenols mediate obesity and metabolic function. To this end, hormonal control of hunger has the potential to inhibit pro-obesity enzymes such as pancreatic lipase, the promotion of energy expenditure, and the modulation of adipocytokine production. Specifically, polyphenols affect insulin, a hormone that is essential for regulating blood sugar, and they also play a role in part in a complex web of factors that affect the progression of obesity. This review also explores the immunomodulatory properties of polyphenols, providing insight into their ability to improve immune function. The effects of polyphenols on gut health, improving the number of commensal bacteria, cytokine production suppression, and immune cell mediation, including natural killer cells and macrophages. Taken together, continuous studies are required for prudent and precise mechanisms underlying polyphenols' therapeutic potential in obesity and immunomodulation. In the interim, this review emphasizes the holistic approach to health and promotes the consumption of a wide range of foods and drinks high in polyphenols. This review lays the groundwork for future developments, indicating that the components of polyphenols and their derivatives may provide the answer to urgent worldwide health issues. This compilation of the body of knowledge paves the way for future discoveries in the global treatment of pressing health concerns in obesity and metabolic diseases.

Contacting bodies in extreme environments are prone to severe wear and failure due to friction and seizure, which are associated with significant thermal and mechanical loads. This phenomenon greatly impacts the economy since most essential components encounter these challenges during machining, an unavoidable step in most manufacturing processes. In machining, stress can reach 4 GPa, and temperatures can exceed 1000 °C at the cutting zone. Severe seizure and friction are the primary causes of tool and workpiece failures. Liquid lubricants are popular in machining for combatting heat and friction; however, concerns about their environmental impact are growing, as two-thirds of the 40 million tons used annually are discarded and they produce other environmental and safety issues. Despite their overall efficacy, these lubricants also have limitations, including ineffectiveness in reducing seizure at the tool/chip interface and susceptibility to degradation at high temperatures. There is therefore a push towards solid lubricants, which promise a reduced environmental footprint, better friction management, and improved machining outcomes but also face challenges under extreme machining conditions. This research aims to provide a thorough insight into solid lubricant use in machining, discussing their mechanisms, effectiveness, constraints, and potential to boost productivity and environmental sustainability.

Background. Azithromycin (AZM) is widely used in cystic fibrosis (CF) treatment following clinical trials demonstrating improved lung function and fewer pulmonary exacerbations. While the precise mechanisms remain elusive, immunomodulatory actions are thought to be involved. We previously reported impaired phagocytosis and defective anti-inflammatory M2 macrophage polarization in CF macrophages. This study systematically analyzed the effect of AZM on the functions of unpolarized and M1/M2 polarized macrophages in CF. Methods: Monocytes, isolated from the venous blood of patients with CF (pwCF) and healthy controls (HCs) were differentiated into monocyte-derived macrophages (MDMs) and infected with P. aeruginosa. P. aeruginosa uptake and killing by MDMs in the presence or absence of AZM was studied. M1 and M2 macrophage polarizations were induced and their functions and cytokine release were analyzed. Results: Following AZM treatment, both HC and CF MDMs exhibited a significant increase in P. aeruginosa uptake and killing, however, lysosomal acidification remained unchanged. AZM treatment led to higher activation of ERK1/2 in both HC and CF MDMs. Pharmacological inhibition of ERK1/2 using U0126 significantly reduced P. aeruginosa uptake in HC MDMs. M1 macrophage polarization remained unaffected, however, AZM treatment led to increased IL-6 and IL-10 release in both HC and CF M1 macrophages. AZM also significantly increased the phagocytic index for both pHrodo E. coli and S. aureus in CF M1 macrophages. In CF, AZM treatment promoted anti-inflammatory M2 macrophage polarization, with an increased percentage of CD209+ M2 macrophages, induction of the M2 gene CCL18, along with its secretion in the culture supernatant. However, AZM did not restore endocytosis in CF, another essential feature of M2 macrophages. Conclusions: This study highlights the cellular functions and molecular targets of AZM which may involve improved uptake of both gram-positive and gram-negative bacteria, restored anti-inflammatory macrophage polarization in CF. This may in turn shape the reduced lung inflammation observed in clinical trials. In addition, we confirmed the role of ERK1/2 activation for bacterial uptake.

The classification and summarization of online reviews using machine learning and deep learningbased approaches are the subject of this systematic literature review. Consumers, companies, and researchers can now find vital information from online reviews. Automatically categorizing and summarizing these reviews can offer useful information and facilitate decision-making. The purpose of this study is to offer a thorough overview of the current methodology, approaches, and developments in this area. The review concentrates on machine learning-based methods for categorization and summarizing tasks, highlighting their advantages, drawbacks, and new developments. This systematic review provides insights into the most recent methodologies and indicates prospective directions for further investigation by synthesizing the data from a wide range of pertinent research publications

Due to the ever increasing global warming, the scientific community is concerned with finding immediate solutions to reduce or utilize carbon dioxide (CO2) and convert it in useful compounds. In this context, the reductive process of CO2 methanation is well investigated and attractive due to its simplicity. However, it requires the development of highly active catalysts. In this mini-review, the focus is on biochar-immobilized nanocatalysts for CO2 methanation. We summarize the recent literature on the topic, reporting strategies for the design of biochar with immobilized nanocatalysts and their performances in CO2 methanation. We review the thermochemical transformation of biomass into biochar and its decoration with CO2 methanation catalysts. We also tackle direct methods of obtaining biochar-nanocatalysts, in one pot, from nanocatalyst precursor-impregnated biomass. We review the effect of the initial biomass nature, as well as the conditions that permit to tune the perfomances of the composite catalysts. Finally, we discuss the CO2 methanation performances and how they could be improved keeping in mind low operation cost and particularly sustainability.

In this work, we report the engineering of a sub-70 nm nanocomposite of ZnO/Zn2TiO4 using a low-temperature solution-phase method. Titanium isopropoxide and zinc acetate were used as precursors, and isopropyl alcohol and water were used as solvents. The investigation focused on the growth of nanocomposites by varying the concentrations of precursors and surfactants, as well as their efficiency within different pH ranges. All three ZnO/Zn2TiO4 nanocomposites consist of hexagonal wurtzite ZnO and Zn2TiO4 structures in the three nanocomposites. The crystallite size in three ZnO/Zn2TiO4 nanocomposites, with a hexagonal wurtzite ZnO structure, were measured to be 62.67, 40.34, and 39.50 nm. The crystallite size values in three ZnO/Zn2TiO4 nanocomposites were 26.15 nm, 25.36 nm, and 21.24 nm, respectively, with Zn2TiO4. Morphological observations, conducted using FESEM, reveal the formation of three ZnO/Zn2TiO4 nanocomposites across the entire sample. These nanocomposites resemble dispersed cotton packets, with sizes ranging from 18 to 350 nm. Peaks in the range of 610-1250cm-1 are attributed to Ti-O bond formation and peak located at 1350-1450 cm-1 are attributed to Zn-O bond formation. Also, EDX spectrum reveals peaks for various sample components such as Ti, O and Zn. UV spectrums confirmed the formation of three nanocomposite of ZnO/Zn2TiO4 as showing two peaks for each sample. Photocatalytic investigation carried out by analyzing the UV-Visible absorption spectra of methylene blue dye on the surface of ZnO/Zn2TiO4 nanocomposites, dye degradation at various irradiation time intervals, dye degradation at varied catalyst concentrations and the influence of pH on dye-degradation. Furthermore, the said nanocomposites were used to degrade environmental pollutant (Methylene blue dye). Different sets of experiments were conducted under ambient conditions which show an excellent photo catalytic degradation efficiency.

Abstract: Background: Bangladesh has achieved remarkable progress in reducing maternal mortality, yet postpartum deaths remain a significant issue. Emphasis on quality postnatal care (qPNC) is crucial, as increased coverage alone has not sufficiently reduced maternal morbidity and mortality. Methods: This study included data from the Bangladesh Maternal Mortality Survey of 32,106 mothers who delivered within three years prior to the survey. Descriptive statistics were used to report coverage and components of postnatal care stratified by covariates. Log-linear regression models were used to assess the determinants of quality postnatal care among facility and home births. Results: From 2010 to 2016, postnatal care coverage within 48 hours of delivery by a qualified provider rose from 23% to 47%. 94% of facility births received timely PNC, contrasted with only 6% for home births. Despite the increased coverage, quality of care remained as low as 1% for home births and 13% for facility births. Key factors affecting qPNC utilization included socio-demographic factors, pregnancy complications, delivery method, financial readiness, and mobile ownership. Conclusion: Importantly, deliveries assisted by skilled birth attendants correlated with higher quality postnatal care. The study reveals a significant gap between the coverage and quality of postnatal care in rural Bangladesh, especially for home births. It underscores the need for targeted interventions to enhance qPNC.

Introduction: Dental students’ use of online material to supplement learning has been studied, but educator awareness and reaction to the findings of this research is unknown. This small local study aimed to investigate dental students’ use of online content as a learning tool from an educator’s perspective.Methods: Educators at an Irish dental school completed a survey based on dental students’ use of online learning. Quantitative descriptive analyses were carried out as appropriate on the data collected, and a subsequent focus group was held to gain deeper insight into survey results. Data were analysed for themes by deductive and inductive coding methods.Results: This study found a sample of educators were aware of some student behaviours around online videos. Most educators correctly thought that students are likely to refer to online videos to prepare for dental procedures. Several educators believed that teachers should incorporate videos into their learning, but do not themselves upload or recommend online videos. Most recalled discussing accuracy and/or relevancy of online content with their students. Fewer thought that students would discuss contradictory videos with them. Focus group participants expressed concern over the accuracy of online content. This along with a lack of time were some reasons deterring them from referring students to online videos. Conclusions: An opportunity exists for dental educators and their students to have local dialogue around (1) student use, critical appraisal, and sharing of dental procedural video material; and (2) perceived benefits and challenges of incorporating both school-produced and online videos into teaching and learning. Although arguably non-generalizable beyond this context, this study may inform future research and serve to spark conversations within schools regarding video use for teaching clinical dental procedures.

Saudi Arabia is a prominent producers of dates, with 1.6 million tons annually. There is a need to evaluate physical properties and quality of fruits non-destructively and then be modeled and predicted throughout the storage period. The aim of the current study was to generate a quality index (Qi) and Near-infrared spectra (NIR) models non-destructively to predict properties of Barhi dates fruits including objective and sensory evaluations. The engineering properties of Barhi dates were measured and modeled with quality index (Qi) based on NIR of fresh Barhi fruits (hardness, color, TSS, pH, and sensory evaluations) and during storage in cold, ambient, and controlled at-mosphere (CA) for up to four months. The prediction of Qi is non- destructively based on NIR utilizing PLSR and ANN data analysis. The results showed that the Qi generated corresponds with high precision to the characteristics of the examined fruits through the duration of the storage period with R2 of 0.96. The NIR spectrum proves to be an efficient method to evaluate the Barhi fruits' quality index. where ANN was found to be more suitable than PLSR analysis. Thus, NIR can be utilized to accurately predict the Qi of fruits quality effectively throughout the handling, processing, transporting, storage, and retail sector supply chain.

A milk drink flavored with dates syrup produced at a lab scale level was evaluated. The production process of date syrup involves a sequence of essential unit operations, commencing with the extraction, filtration, and concentration processes from two cultivars: Sukkary and Khlass. Date syrup was then mixed with cow’s and camel’s milk at four percentages to form a nutritious, natural, sweet, and energy milk drink. Sensory, physical, and chemical characteristics of the milk drinks flavored with date syrup were examined. The objective of this work was to measure physiochemical properties of dates fruits and milk drinks flavored with dates syrup, then to evaluate the physical properties of milk drinks utilizing a non-destructive NIR spectra. The study assessed the characteristics of the milk drink enhanced with date syrup by employing near-infrared spectra (NIR) spectra and analyzed utilizing partial least-square regression (PLSR) and artificial neural network (ANN) analysis. The NIR spectrum proved to be highly effective in estimating the physiochemical attributes of the flavored milk drink. The ANN model outperformed the PLSR model in this context. RMSECV is considered a more reliable indicator of a model's future predictive performance compared to RMSEC, R2 ranged between 0.946 and 0.989. Consequently, non-destructive NIR technology demonstrates significant promise for accurately predicting and contributing to the entire production process of the product's properties examined.

Introduction: COVID-19's emergence caused devastating consequences worldwide, with high morbidity and mortality rates. Critically ill patients face challenges like acute respiratory failure requiring intensive measures, including mechanical ventilation. Mortality rates in ARDS are influenced by various factors. This paper focuses on describing characteristics, management, and survival factors of mechanically ventilated ICU patients in Saudi Arabia. Methods: a retrospective, noninterventional approach, we reviewed charts and data of all COVID-19-infected patients who were admitted to the ICU, particularly those requiring ventilation support at Aseer Central Hospital (ACH) in the southern region of Saudi Arabia. Results: The study enrolled 594 COVID patients, mean age 60.5 ± 17.3 years, with 67% males. Approximately half had O negative blood group. Common chronic health issues: diabetes mellitus (35.5%). Positive culture findings in almost 340 (57.2%), with Klebsiella pneumoniae being the most isolated microorganism (45.5%). Significant correlations found with mortality: age, blood culture, Rh positive group (P<0.05). Conclusion: this study provides critical insights into the clinical and epidemiological aspects of COVID-19 patients admitted to the ICU in a Saudi Arabian hospital. The research underscores the impact of age, comorbidities, laboratory markers, and treatment interventions on patient out-comes, emphasizing the significance of tailored management strategies in this context.

There is a need to develop enriched milk drinks with healthy and natural additives. A consumer test was conducted to compare milk (cow and camel) flavored with date syrup (Khlass and Sukkary varieties) at different percentage. The objective of the present work was to study consumers liking patterns for flavored milk drinks from dates syrup (from Khlass and Sukkary dates), at different percentages, added to milk (cow and camel) utilizing preference mapping analysis. A total of sixteen trained panelists took part in the test. The obtained data were used to develop an internal preference map for these samples. Principal component analysis (PCA) and Agglomerative hierarchical clustering (AHC) algorithms were used to construct the preference map. The first component signifies overall acceptance of taste and color, while the second focuses on texture and flavor. Consumers were grouped into five clusters based on preferences. Cluster two favored both components positively, while cluster four leaned negatively on both. A factorial ANOVA was performed and the results showed a significant effect of the main factors as well as the interactions. Panelists preferred cow's milk over Camel’s milk in all aspects. For taste, cow’s milk with 20% Khlass syrup or 10% Sukkary syrup was favored, while in flavor, it was cow’s milk with 5% Khlass syrup and Camel’s milk with 10% Sukkary syrup. Texture-wise, Camel’s milk with 5% Khlass syrup and 15% Sukkary syrup, along with cow’s milk with 10% Khlass syrup, received top marks. In color evaluation, cow’s milk with 15% Sukkary syrup was the preferred choice. Finally, for overall color score, cow’s milk with 10% Sukkary syrup led, followed by cow’s milk with 5% Sukkary syrup. This research suggests that dairy companies may have more impact if they use date syrup as a natural and healthy flavor. The preference map includes two main dimensions; the first represents overall acceptance, taste, and color while the second is related to flavor and texture attributes. The preference map can be used in product optimization and development.

Nephrotoxicity is a common adverse effect associated with gentamicin administration. The current study investigated the potential protective effects of dates fruit against Gentamicin-induced renal nephrotoxicity in female albino rats. Date fruit antioxidants were measured using a spectropho-tometer, and GC-MS was performed using a Perkin Elmer Clarus 600 GC and Turbomass mass spectrometer. Thirty experimental animals were assigned at random to one of three Prevention and Treatment subgroups. Gentamicin (GM) administration at a dose of 100mg/kg resulted in renal toxicity, as evidenced by alterations in kidney function tests and histological changes in the proximal convoluted tubules. Date fruit improved kidney function (albumin, total protein, uric acid, urea, creatinine) and tubule histology, according to the findings. The GC-MS analysis reveals the presence of 20 chemicals. Date fruit antioxidants include 14mg/gallic acid total phenolic, 32.22 mg/rutin equivalent total flavonoid, and 1000 ug/ml DPPH free radical scavenging. According to the study, date fruit and Gentamicin performed the best. Date fruit had a significant impact on prevention during Gentamicin treatment.

Hybrid materials derived adsorbents have showed a great applicable efficiency in various fields including industrial uses and environmental remediation. Herein, the zinc oxide nanoparticles anchored carbon (ZnO-C) is fabricated and utilized for wastewater treatment by adsorption of Zn(II), Cd(II), Co(II) and Mn(II). The surface and structural characteristics are examined by TEM, SEM, XRD, FTIR, EDS and BET surface area. The Kinetics and equilibrium investigations are applied to optimize the adsorptive removal of Zn(II), Cd(II), Co(II) and Mn(II) onto ZnO-C. Results indicated formation of ZnO-C in crystalline spherical granules with nano-size between 29.3 and 48.8 nm. In addition, the spherical granules are gathered to form clusters. The FTIR indicated that the ZnO-C surface is rich with OH groups and ZnO. The adsorption capacity is reported as 212, 209, 200 and 230 mg/L for Zn(II), Cd(II), Co(II) and Mn(II) respectively. The optimum condition for maximum adsorption were pH between 5 and 6, contact time of 180 min and adsorbent dose of 0.1 g/L. The adsorptive removal data modeling for uptake of Zn(II), Cd(II), Co(II) and Mn(II) onto ZnO-C showed agreement with the assumption of pseudo 2nd order kinetic model and Freundlich isotherm suggesting fast adsorption rate and multilayer mechanism. The achieved adsorption capacity using the prepared ZnO-C is more effective compared to ZnO, carbon, Fe3O4 and Fe3O4-C. Real wastewater samples are applied including valley water, industrial wastewater and rain wastewater and evaluated for applicable uptake of Zn(II), Cd(II), Co(II) and Mn(II) using ZnO-C and Fe3O4-C with high efficiency.

(1) Background: It is crucial to provide safe and knowledgeable healthcare practices because no research has been done on the knowledge and usage patterns of NSAIDs among the Hail population. (2) Method: Structured questionnaires were utilized to gather data from 399 individuals in Hail, Saudi Arabia for the cross-sectional analysis. The study assessed participants' knowledge regarding NSAIDs, patterns of use, reasons for use, and awareness of potential side effects. (3) Results: In the study, the gender distribution indicated that 170 participants (42.61%) were male, while 229 (57.39%) were female. Gender, occupation, and marital status showed non-significant associations (p>0.01), except for menstrual cycle and joint pain, where marital status displayed significant associations. Age had significant associations with muscle pain, menstrual cycle, and joint pain (p<0.01). Education and monthly income exhibited non-significant associations for all the reasons. The regression analysis demonstrated that gender played a significant role, with females having higher odds of knowledge (AOR = 1.75, 95% CI 1.10-2.88) than males. Age also had a notable impact, with individuals aged 50-59 (AOR = 0.21, 95% CI 0.07-0.66) exhibiting lower odds of knowledge. Education holding a Ph.D (AOR = 3.50, 95% CI 0.54-22.51) and business as an occupation (AOR = 6.12, 95% CI 1.10-35.10) had significantly higher odds of knowledge while housewives (AOR = 0.76, 95% CI 0.25-2.27) had lower odds. Meanwhile, >50% of the participants had knowledge of adverse events related to the use of NSAIDs while 25% had no knowledge. Moreover, 59 (25.766%) participants reported discomfort with the use of NSAIDs. In addition, 50% and >75% of participants’ considered NSAIDs can cause peptic ulcers and damage kidneys, respectively (4) Conclusions: This study shed light on the knowledge and patterns of NSAIDs use in the population of Hail, Saudi Arabia. While NSAIDs are commonly utilized for pain management, there exists a need for improved public awareness regarding potential risks and safe usage practices. Healthcare providers and policymakers should consider these insights to develop targeted educational initiatives and healthcare interventions to promote safe and informed NSAID utilization in the region.

Crack inspection in railway sleepers is crucial for ensuring rail safety and avoiding deadly accidents. Traditional methods for detecting cracks on railway sleepers are very time-consuming and lack efficiency. Therefore nowadays, researchers are paying attention to the vision-based algorithm, especially Deep Learning algorithms. In this work, we adopted the U-net for the first time for detecting cracks on a railway sleeper and proposed a modified U-net architecture named Dense U-net for segmenting the cracks. In the Dense U-net structure, we established several short connections between the encoder and decoder blocks, which enabled the architecture to obtain better pixel information flow. Thus, the model extracted the necessary information in more detail to predict the cracks. We collected images from railway sleepers, processed them in a dataset, and finally trained the model with the images. The model achieved an overall F1-score, precision, Recall, and IoU of 86.5% 88.53%, 84.63%, and 76.31% respectively. We compared our suggested model with the original U-net, and the results demonstrate that our model outperformed the U-net in both quantitative and qualitative results. Moreover, we considered the necessity of crack severity analysis and measured a few parameters of the cracks (e.g., length, maximum width, area, density). The engineers must know the severity of the cracks to have an idea about the most severe locations and take the necessary steps to repair the badly affected sleepers.

The study of angiosperm flora, endemic plants in the literature, and investigations of ‘POWO Build a checklist’ were used to compile an updated list of Bangladesh's endemic plants. According to the study, at least 49 (1.24%) of Bangladesh's 3,956 plant species are endemic to the country including 5 varieties, belonging to 41 genera in 26 families. Magnoliopsida account for thirty of them, Liliopsida for the remaining sixteen, and Pteridohpytes for the final three. The four families Zingiberaceae (9 taxa), Araceae (6 taxa), Rubiaceae (4 taxa), and Euphorbiaceae (3 taxa), include the most endemic taxa. The five most numerous endemic taxa belong to the Curcuma genus. The endemic flora, which is mostly found in the districts of Chattogram, Moulvibazar, and Rangamati, consists of 13 tree species, 4 shrubs, 5 climbers, and 27 herbaceous plant species.

Organic-rich shale deposits of the Paleocene-Eocene Palana Formation in western Rajasthan, India were systematically analyzed based on the elemental composition and organic geochemistry combined with microscopic examinations to evaluate the sedimentary paleoenvironmental conations and volcanic activity and their impact on the high organic carbon accumulation. The Palana shales are categorized by high OM and sulfur contents with total values up to 36.23 wt. % and 2.24 wt. %, respectively, suggesting marine setting and anoxic environmental conditions during the Paleocene-Eocene period. The richness of phytoplankton algae (i.e., telalginite and lamalginite) together with redox-sensitive trace elements further suggests anoxic environmental conditions. The significant low oxygen conditions may contributes to enhance preservation of organic matter during deposition. The mineralogical and inorganic geochemical indicators demonstrate that the Palana organic-rich shale facies was accumulated in warm and humid climate and low salinity stratification conditions of the water columns, thereby contributing to high bioproductivity of the phytoplankton algae blooms within the photic zone. The presence of the high concentrations of Fe-rich silica minerals such as olivine in most of the Palana organic-rich shales facility volcanic origin and supports hydrothermal activities during the Paleocene-Eocene period. These volcanic activities in this case are considered influx of large masses of nutrients into the photic zone due to the ash accumulation. Therefore, high bio-productivity associated with effective OM preservation contributed to the organic carbon accumulation in the Palana Formation during the Paleocene-Eocene.

Mosquito-borne diseases (MBDs) are a group of illnesses transmitted by mosquitoes and can be caused by bacteria, viruses, or parasites. These diseases represent a significant global burden of infectious diseases, including morbidity and mortality. This systematic review delves into the multifaceted factors contributing to the spread of mosquito-borne diseases (MBDs) in the Middle East and North Africa (MENA) region. Following PRISMA guidelines, a thorough analysis of peer-reviewed articles from May 1990 to Jan 2023 was conducted, highlighting the interplay of population, environmental, disease, and mosquito factors in disease transmission and prevalence. The review incorporated 31 studies that revealed a complex relationship between various risk factors and the presence of MBDs. Significant associations were observed with age, certain occupations, environmental conditions such as rainfall and temperature, sanitation practices, specific pathogen variants, clinical symptoms, and Aedes aegypti mosquitoes. Conversely, gender, socioeconomic status, educational status, and certain sanitation-related factors showed inconsistent association with the spread of MBDs. The review underscores the need for targeted interventions, including vector control, improved sanitation, and educational campaigns to mitigate the spread of MBDs in the MENA region. This review could guide research studies to address data gaps and assist in developing effective surveillance programs in the MENA region. This work emphasizes the need for region-specific public health strategies and further research to understand and curb the burden of these diseases effectively.

Background: COVID-19 is a respiratory illness caused by SARS-CoV-2 that has become a global pandemic. Although children can contract the virus, they are generally less likely than adults to develop severe symptoms. Parents and caregivers should monitor their children for symptoms and seek medical attention if their child becomes ill. Practicing good hygiene and social distancing can help prevent the spread of the virus. Vaccines are available for children and can provide additional protection against COVID-19. Understanding the impact of COVID-19 on children is crucial for developing effective public health strategies to control the pandemic.Objectives: The current study aims to determine the prevalence of Covid-19 in pediatric age group in Duhok province and Zakho city, in Kurdistan region. among the children who tested positive for IgG test. If IgG antibodies are detected in a person's blood sample, it suggests that they have been infected with SARS-CoV-2 at some point in the past and their immune system has responded by producing antibodies against the virus.Methods: A cross-sectional investigation was undertaken involving youngsters aged 5 to 12 years. The study encompassed a total of 330 participants, selected between October and December 2022. The children underwent testing to detect IgG antibodies. Moreover, a questionnaire was employed to gather demographic and individual information from each contributor.Results: Among the studied sample, 302/330 (91.5%) of children were positive to IgG antibody test. No gender difference for COVID-19 was found in pediatric age group. Case fatality rate was 0%. 22/302 (6.6%) cases were symptomatic during the infection. However, 282(93.4%) cases were asymptomatic. Conclusions: Covid-19 infection in pediatric age group has good prognosis compared to adults. Intensive care unit (ICU) and death are rare. High-risk groups should be targeted for education and immunization/vaccination. Furthermore, more studies are needed to be conducted in order to investigate the risk factors of the infection and to assess the awareness among the general population about the risk of infection.

Coronavirus Disease 2019 (COVID-19) exhibits a significant variation in presentation of symptoms ranging from mild to severe life-threatening symptoms, including death. COVID-19 infection susceptibility has been linked with various covariates, but studies in Qatar are limited. Data from Qatar Biobank (QBB) (n = 10,000; 18- to 79-year-old adults) were analyzed for associations between sociodemographic and lifestyle factors and susceptibility to COVID-19. Logistic regression was used to assess the associations between COVID-19 and age, gender, body mass index (BMI), smoking status, education level, dietary patterns, supplement use, physical activity, history of bariatric surgery, diabetes, and hypertension. In total, 10.5% (n = 1045) of the participants had COVID-19. Compared to non-smokers, current and ex-smokers had lower odds of having COVID-19 (odds ratio [OR]= 0.55; 95% CI: 0.44-0.68 and OR= 0.70; 95% CI: 0.57-0.86, respectively). Vitamin D supplement use was associated with an 18% reduction of the likelihood of contracting COVID-19 (OR = 0.82; 95% CI: 0.69-0.97). Obesity (BMI ≥30 kg/m2), history of bariatric surgery and higher adherence to the modern dietary pattern– characterized by consumption of foods high in saturated fat and refined carbohydrates– were positively associated with COVID-19. Our findings indicate that adopting a healthy lifestyle may be helpful in the prevention of COVID-19 infection.

Consumer IoT (CIoT) manufacturers seek customer feedback to enhance their products and services, creating a smart ecosystem like a smart home. Due to security and privacy concerns, Blockchain-based federated learning (BCFL) ecosystems can let CIoT manufacturers update their Machine Learning (ML) model using end-user data. FL uses privacy-preserving ML techniques to forecast customers' needs and consumption habits, and blockchain replaces the centralised aggregator to safeguard the ecosystem. However, Blockchain technology (BCT) struggles with scalability and quick ledger expansion. In BCFL, local model generation and secure aggregation are other issues. This research contributes a novel architecture emphasising Gateway Peer (GWP) in blockchain network to resolve scalability, ledger optimisation and secure model transmission issues. In the architecture we replace the centralised aggregator by the blockchain network, while GWP restricts the number of local transactions to execute in BCN. Considering the security and privacy of FL processes, we have added differential privacy and advanced normalisation techniques to ML processes. The approaches strengthen end-users' cyber security and encourage the adoption of technological innovation standards by service providers. The proposed approach has been tested extensively using a well-respected Stanford Cars dataset. We experimentally demonstrate that the proposed architecture makes the network scalable and optimises the ledger significantly. In addition, the normalisation technique outperforms batch normalisation when features are under DP protection.

Meningiomas are the most prevalent primary intracranial tumors. The majority are benign but can undergo dedifferentiation into advanced grades classified by World Health Organization (WHO) into Grades 1 to 3. Meningiomas tremendous variability in tumor behavior and slow growth rates complicate their diagnosis and treatment. A deeper comprehension of the molecular pathways and cellular microenvironment factors implicated in meningioma survival and pathology is needed. This review summarizes the known genetic and epigenetic aberrations involved in meningioma, with a focus on Neurofibromatosis type 2 (NF2) and non-NF2 mutations. Novel potential biomarkers for meningioma diagnosis and prognosis are also discussed, including epigenetic-, RNA-, metabolomics, and protein-based markers. Finally, the landscape of available meningioma-specific animal models is overviewed. Use of these animal models can enable planning of adjuvant treatment, potentially assisting in preoperative and postoperative decision-making. Discovery of novel biomarkers will allow, in combination with WHO grading, more precise meningioma grading, including meningioma identification, subtype determination, and prediction of metastasis, recurrence, and response to therapy. Moreover, these biomarkers may be exploited in the development of personalized targeted therapies that can distinguish between the 15 diverse meningioma subtypes.

Valsartan (Val) is an important antihypertensive medication with side effects such as dizziness and angioedema. These constraints are due to the low oral bioavailability and relatively short half-life. The goal here is to incorporate Val into a mixed micelles system that can enhance transdermal delivery. Thin-film hydration and micro-phase separation were used to produce Val-loaded mixed micelle systems. A variety of factors, including surfactant type and drug-to-surfactant ratio, were optimized to produce micelles with low size and high Val entrapment efficiency (EE). The size, polydispersity index (PDI), zeta-potential, and drug entrapment efficiency of the prepared micelles were all measured. The drug release profiles in vitro were assessed using dialysis bags, and the permeation through abdominal rat skin was assessed using a Franz diffusion cell. All formulations had high EE levels exceeding 90% and low particle charges. The micellar sizes ranged from 107.6 to 191.7nm, with average PDI values of 0.3. The in vitro release demonstrated a uniform slow rate that lasted one week with varying extents. F7 demonstrated a significant (P < 0.01) transdermal efflux of 68.84 ± 3.96 µg/cm2/h through rat skin when compared to the control. As a result, the enhancement factor was 16.57. Val-loaded mixed micelles were successfully prepared using two simple methods with high reproducibility, and extensive transdermal delivery was demonstrated in the absence of any aggressive skin modifying enhancers.

Utilization of medicine derived from plants has been documented in various traditional systems of medicines throughout the world for different diseases. Therefore, the current research work was carried out to evaluate the phytochemical and biological potential of Ficus carica L ethanolic leaf extract. For this purpose, physicochemical and phytochemical analysis, total phenolic and flavonoids contents was performed. Antioxidant potential was determined by FRAP, DPPH and H2O2 assay. Proteinase inhibition, heat induced hemolysis and BSA denaturation assay was carried out for inflammation. Antiglycation potential was assessed by fructosamine assay, Congo-red assay and estimation of free carbonyl groups. In-vivo antidiabetic, anti-obesity, effect on liver and kidney were investigated by high fat high sugar diet model. FTIR, HPLC and LCMS/MS analysis was performed to find out the compounds. Tablet based formulation was developed using wet granulation method and tested for physicochemical parameters. Results shows that total phenolic and flavonoids content was (333 mg GAE/g) and (123 mg RE/g) respectively, H2O2 assay shows 35.6% free radical inhibition potential, DPPH assay shows (IC50) inhibitory concentration at 0.58 mg/mL, and 88.769 µg/g Fe2SO4 solution FRAP values. Proteinase inhibition assay, Heat induced hemolysis and BSA-denaturation assay shows percentage inhibition of 28 ± 0.01, 55 ± 0.03 and 51.2 ± 0.05 respectively. In Antiglycation activity β-amyloid formation assay shows absorption of 0.017, Fructosamine assay shows inhibition of 19.4±0.06 and free carbonyl group estimation shows inhibition of 17.0±0.03. In in-vivo study FLE at (500 mg/kg) significantly decreased total bilirubin (p ≤ 0.001), decreased (p ≤ 0.05) alanine transferase, aspartate aminotransferase, alkaline phosphatase, decreased blood glucose, triglycerides and total cholesterol (p ≤ 0.01) while HDL (p ≤ 0.01) was significantly increased in comparison to obesity and diabetic-obesity groups. Different functional groups presence was confirmed by FTIR spectrum. HPLC analysis revealed the existence of ferulic acid, rutin, chlorogenic acid, coumarin and thymoquinone and these results are corelated by LC-MS/MS. Pre-compression characterization showed angle of repose (33.04°), bulk density (0.54 g/cm3), tapped density (0.73 g/cm3), compressibility index (35.179 %) and Hausner’s ratio (1.35), while the post-compression characterization showed weight variation 826±4.17 mg, thickness 10.50±0.25 kg/cm2, friability 0.57 %, and disintegration time 8.19 min. From the above results it is concluded that F. carica L. leaves extract has strong antioxidant, antidiabetic and hypolipidemic potential and can be used for an obesity and diabetes treatment.

Website defacement is an illegal electronic act of changing a website. In this paper, robust machine learning classifiers’ capabilities were exploited to select the best input feature set for evaluating a website’s defacement risk. Zone-H, a private organization, offered us a defacement mining dataset. A sample of 93644 datapoints was concisely pre-processed and used for modelling purposes. Considering multidimensional features as input, reason and hackmode variables were chosen as outputs. Massive machine learning models were examined; however, decision tree (DT), k-nearest neighbour (k-NN), and random forest (RF) were the most powerful algorithms used to predict the target model. The input variables 'domain', 'system', 'web_server','redefacement', 'type', 'def_grade', and 'reason/hackmode' were tested and used to shape the final model. Using the cross-validation (CV) technique, the model’s key performance factors were calculated and reported. After calculating the average scores for the hyperbolic metrics (i.e., max-depth, min-sample-leaf, weight, max-features, and CV), both targets were evaluated, and the learning algorithms were ranked as RF, DT, and k-NN. The reason and hackmode variables were thoroughly analysed. The average score accuracies for the reason and hackmode targets were 0.85 and 0.585, respectively. The results showed a significant development in terms of modelling and optimizing website defacement risk. The study also successfully addresses the main cybersecurity concerns, in particular website defacement.

The success rate of extracorporeal shock wave lithotripsy (ESWL) is influenced by various factors, including stone density, which is determined through computed tomography scans in Hounsfield Units (HU). Materials and method: This retrospective single-center study was conducted in King Fahad hospital. Sixty-seven adult patients with renal and ureteric stones were selected randomly and enrolled in the study. Their age ranged from 20 to 69 years. The patients were examined with non-contrast enhancement (NCCT) to assess the HU of stones, consequently, treated with ESWL. Results: of the 67 patients, 37.3% of the stones were completely fragmented, while 62.7% were partially fragmented. HU, location of the stone, a multiplicity of the stone, and patient age were significant factors contributing to stone fragility (p-values&lt; 0.05). The HU has a positive significant linear correlation with serum calcium (r= .28, p-value=.036), while serum acid has a negative correlation (r=-.55, p-value= &lt; .001). Thus, the probability of calcium-containing stones formation increased with increased HU. In contrast, uric acid stone formation is likely to develop with decreasing HU with serum uric acid. Renal stones in patients with diabetes mellitus and hypertension were not completely fragmented compared to those without clinical history. Conclusion: Mean HU, location of the stone, laterality, status of stone, and the number of ESWL sessions were the most significant factors affecting stone fragility. CT attenuation values can predict the composition of stones from serum calcium and uric acid examinations. Hypertension and Diabetes mellitus are risk factors for renal stone fragmentation.

Traumatic brain injury (TBI) is among the leading causes of mortality and long-term impairment globally. TBI has a dynamic pathology encompassing a variety of metabolic and molecular events that occur in two phases, primary and secondary. An external forceful blow to the brain initiates the primary phase, which is followed by a secondary phase that involves the release of calcium ions (Ca2+) and the initiation of a cascade of inflammatory processes, including mitochondrial dysfunction, rise in oxidative stress, activation of glial cells, and damage to the blood-brain barrier (BBB), resulting in paracellular leakage. There is currently no FDA-approved drug for TBI, but existing approaches rely on delivering small and macromolecular treatments, which are severely constrained by the BBB, poor retention, off-target toxicity, and complex pathology of TBI. Therefore, there is a demand for innovative and alternative therapeutics with effective delivery tactics for diagnosis and treatment of TBI. Tissue engineering and use of biomaterials is one such alternative approach. With this approach, neuronal stem cell therapy is combined with synthetically generated tissue materials such as hydrogels, self-assembling peptides, and electrospun nanofibers, which may induce neurite outgrowth, differentiation of human neural stem cells, and nerve gap bridging in TBI. This review examines tissue engineering and the use of biomaterials as potential treatments for TBI, including their synthesis, mechanisms of action, and limitations. The review also discusses challenges facing tissue engineering and biomaterial technology including survival rate of transplanted stem cells and the development of biodegradable, biocompatible, and mechanically flexible biomaterials. A better understanding of the mechanisms and drawbacks of these novel therapeutic approaches will help guide the design of future TBI therapies.

Developing a biomolecular detection method that minimizes photodamage while maintaining an environment suitable for biological constituents to maintain their physiological state is expected to drive new diagnostic and mechanistic breakthroughs. In addition, ultra-sensitive diagnostic platforms are needed for rapid and point-of-care technologies for various diseases. Considering this, surface-enhanced Raman scattering (SERS) is proposed as a non-destructive and sensitive approach to address the limitations of fluorescence, electrochemical, and other optical detection techniques. However, to advance the applications of SERS, novel approaches to enhance the signal of substrate materials are needed to improve reproducibility and costs associated with manu-facture and scale-up. Due to their physical properties and synthesis, semiconductor-based nanostructures have gained increasing recognition as SERS substrates; however, low signal en-hancements have offset their widespread adoption. To address this limitation and assess the po-tential for use in biological applications, zinc oxide (ZnO) was coated with different concentra-tions (0.01-0.1 M) of gold (Au) precursor. When crystal violet (CV) was used as a model target with the synthesized substrates, the highest enhancement was obtained with ZnO coated with 0.05 M Au precursor. This substrate was subsequently applied to differentiate exosomes derived from three cell types to provide insight into their molecular diversity. We anticipate this work will serve as a platform for colloidal hybrid SERS substrates in future bio-sensing applications.

Background: Several reports indicate that long stay at home for online schools due to the COVID-19 pandemic changed the normal physical activity and body weight of school-age students. Previous studies revealed that almost 50% of school students complained of increased or decreased more than 3 kg of weight due to lower physical activity. This study aims to provide insight about the Body Mass Index (BMI) among school students during COVID-19 pandemic. Methods: A retrospective matched-longitudinal study was conducted in 2022 based on previous data about BMI-for-age percentile in school-age students aged 6 to 18 years. These data were collected the year before and during COVID-19 pandemic (2019-2021). Results: All the included students were Arabic (N = 53,580) and were not diagnosed with chronic illness. The outcomes showed that the overall percentage of students with normal weight was 54%, 56%, and 53% during the 2019-2021 years, respectively. Overweight among students increased during the COVID-19 pandemic years, as almost 10% of the students were overweight in 2019 compared with 12% in 2020 and 2021 years. Besides, obese students also increased in the 2020-2021 period compared with the 2019 year (15-17% vs. 10%). In contrast, underweight trends among students declined, as 26% reported in 2019 compared to 17-18% in 2020 and 2021. Conclusion: There are significant variations in Arabic school-age students regarding their BMI values. Obesity was highly detected among children and adolescents during the COVID-19 pandemic years compared to 2019, while underweight cases declined.

Background: Migraine is one of the most common health conditions in the reproductive male and female population. Premenstrual syndrome (PMS) is a common condition that affects many women during their menstrual cycle. around 50 to 60% have menstrual headaches among the migraineur women. The symptoms in the majority were mild, but 5–8% may suffer moderate to severe symptoms, accompanied by considerable distress or functional dysfunction. Premenstrual migraine (PMM) refers to migraines that occur with the menstrual cycle. It affects approximately 50% of women with migraine and can be debilitating in terms of both frequency and severity of symptoms. This information is important for medical professionals in Saudi Arabia to be aware of so, as to provide better medical care and support which can significantly improve the person's quality of life of women who suffer from PMS and menstrual migraines. Objectives: To estimate the prevalence of menstrual migraines in women, to evaluate the severity and frequency of menstrual migraines in women with PMS, and to identify potential risk factors aggravating menstrual migraines in women with PMS. Methodology: A cross-sectional community-based study was conducted on reproductive age (18-50Years) women who have regular menstrual cycles with experience migraine headaches and are diagnosed with PMS and menstrual migraine, using a self-administered questionnaire between December 2022 to May 2023 in Saudi Arabia. Results: Out of 2130 women participants 397 were suffering from migraine which is 18.6%. Of the total 397(18.6%) Migraineurs individuals 230 (57.9%) were suffering from menstrual migraine and 167 (42.1%) were non-menstrual migraineurs, in general, reproductive women menstrual migraine is 10.7% and non-menstrual migraine is 7.8%. The BMI is increasing the incidence of menstrual migraines is increasing. Migraine Disability Around one-third of the participants were suffering from III–moderate disability 134 (33.8) Most of the menstrual migraine victims at least 3 days in the last three months were absent from their duties due to their menstrual migraines. Conclusions: Migraine attacks during the menstrual cycle cause the impairment of their social and physical ability to perform their routine household, and academic activities and unable to fulfill their professional commitments. To better understand the Menstrual Migraine and Non-menstrual migraine large prospective studies are required to plan the best management methods.

Abstract Background: Gastric cancer, particularly adenocarcinoma, is a significant global health concern. Environmental risk factors, such as Helicobacter pylori infection and diet, play a role in its development. Purpose: This study aimed to characterize the chemical composition and evaluate the in vitro antibacterial and antitumor activities of AOME. Additionally, morphological changes in gastric cancer cell lines were analyzed. Study design: AOME was analyzed using HPLC-MS/MS and its antibacterial activity against H. pylori was assessed using the broth microdilution method. MIC and MBC values were determined, and positive and negative controls were included in the evaluation. Methods: Anticancer effects were assessed through in vitro experiments using AGS, KATO-III, and SNU-1 cancer cell lines. The morphological changes were examined through SEM and TEM analyses. Results: AOME contained several compounds, including caffeic acid, rutin, and hyperoside. The extract displayed significant antimicrobial effects against H. pylori, with consistent MIC and MBC values of 3.70 ± 0.09 mg/mL. AOME reduced cell viability in all gastric cancer cell in a dose and time-dependent manner. Morphological analyses revealed significant ultrastructural changes in all tumor cells lines, suggesting the occurrence of cellular apoptosis. Conclusions: This study demonstrated that AOME possesses antimicrobial activity against H. pylori and potent antineoplastic properties in gastric cancer cell lines. AOME holds promise as a natural resource for innovative nutraceutical approaches in gastric cancer management. Further research and in vivo studies are warranted to validate its potential clinical applications.

Robotics and autonomous technologies enable space travel. Robotics change space colonization. We study space-based robotics. Human-centric missions need robotics. Vision, decision-making, movement, and manipulation follow. These developments influence resource utilization, extravehicular activities, planetary surface exploration, long-duration space missions, and colonization. Robots improve research, productivity, and astronaut safety but present problems. Highlighting research and knowledge gaps. Space ethics, human-robot interaction, and failure recovery are gaps. This extensive study showed how robots and autonomous systems may transform space exploration and colonization. Researchers, engineers, and mission planners may benefit. Robotics and autonomy will improve space exploration.

Ankylosing spondylitis (AS) is a chronic inflammatory arthritis that affects the axial skeleton, causing intense pain, progressive joint destruction, and a gradual reduction in physical function. It has been recognized not only as affecting the axial skeleton but as a systemic disease. Since it also causes an increase in the rates of inflammatory bowel disease, psoriasis, acute anterior uveitis, and mental disorders affecting the quality of life. Furthermore, an association with neurological and cardiovascular events is documented. With the advent of biologics, treating AS dramatically changed due to its high efficacy and tolerable safety. AS can be treated with various biological treatments. Nevertheless, there are differences in traits, including rapidity of onset, long-term efficacy, safety profile, and influence on comorbidities. A better understanding of such traits enables clinicians to make the best decision for each patient, increasing persistence, extending medication survival, enhancing patient satisfaction, and reducing the disease effect of ankylosing spondylitis. In this article, we emphasize biologics' efficacy and safety profile in patients with ankylosing spondylitis. In addition, we discuss the impact of biologics on comorbidities and health-related quality of life.

The most modern technique utilized to create intricate and complexly manufactured parts for a variety of applications is called additive manufacturing (AM). Fused deposition modeling (FDM) has received the greatest attention in the development and manufacturing sectors. The main objective of this study was to investigate how printing factors affected the mechanical characteristics of printed samples. Samples were produced using an FDM 3D printer in compliance with ASTM D638 using a variety of input settings, including orientation, layer thickness, speed, and infill pattern. On the printed samples, tensile tests and morphological analysis using a scanning electron microscope (SEM) were done. The findings of this study demonstrate that factors including layer thickness, printing speed, and orientation significantly affect the tensile strength of ABS printed samples. Discovering the process settings that could lead to superior mechanical and physical characteristics would undoubtedly assist designers and manufacturers worldwide as the FDM 3D printer becomes more and more crucial in manufacturing engineering parts.

The development of sustainability, the improvement of the quality of life, and the protection of future generations have become of prime importance in light of climate changes and carbon emissions. Universities are at the top of institutions that should participate in creating an environmentally friendly infrastructure. This study thus aimed to explore the extent to which Saudi universities achieve sustainability in the light of the Saudi Green Initiative from the faculty members’ perspective. Surely, this investigation would produce a proposal to promote sustainability in Saudi universities. A questionnaire consisting of five dimensions, namely academic sustainability, community partnership, resource management, planning and administration, and innovation and leadership was developed and administered to 120 faculty members from five Saudi universities. The participants’ ratings of Saudi universities’ achievement of sustainability dimensions ranged from high to moderate. Based on the results, a proposal was offered to take sustainability in Saudi universities to a higher level.

The objective of this work was to improve the thermal stability, flame resistance and surface properties of black poplar (Populus nigra L.) wood via different impregnation methods. The impregnation method was employed through two distinct modalities: vacuum impregnation and immersion impregnation. Here, poplar wood was impregnated with calcium oxide solutions (1%, 3% and 5%). Fourier transform infrared spectroscopic analysis revealed a shift in the typical peaks of cellulose, hemicellulose, and lignin depending on the impregnation method and solution ratio. Thermogravimetric analysis and the limiting oxygen index indicated that the samples impregnated with lime solutions exhibited higher thermal stability than the unimpregnated wood. In both impregnation methods caused a decrease water absorption and thickness swelling of the sample groups. Using a scanning electron microscope, the effect of the impregnation process on the structure of the wood was examined. In terms of surface properties, it was determined that the surface roughness value increased. On the contrary, it was observed that the contact angle value also increased. A significant difference emerged between the applied methods. In conclusion, the applied lime minerals are suitable substances to increase flame resistance and thermal stability of black poplar wood.

Background: The immunomodulatory role of 1,25-Dihydroxy vitamin D3 (1,25(OH)2D3) is exerted through its interaction with the Vitamin D receptor (VDR) present on pancreatic and immune cells. While a deficiency in Vitamin D has been linked to Type 1 Diabetes Mellitus (T1DM), the exact molecular mechanism driving this down-regulation in T1DM is yet to be fully understood. This study aimed to decipher differences in the expression of genes associated with Vitamin D metabolism in T1DM patients and to ascertain if there is a correlation between serum 1,25(OH)2D3 levels and the expression of these genes. We also sought to understand the influence of specific microRNAs (miRNAs) on the expression of Vitamin D metabolism genes in peripheral blood mononuclear cells (PBMCs) of T1DM patients. Furthermore, the study delved into the potential implications of altered Vitamin D metabolism genes and miRNAs on autoimmune processes. Methods: Utilizing real-time PCR, we assessed the expression profiles of genes encoding for 1-hydroxylases (CYP27B1) and 24-hydroxylases (CYP24A1), as well as related miRNAs, in PBMCs from 30 T1DM patients and 23 healthy controls. ELISA tests facilitated the measurement of 1,25(OH)2D3, GAD65, and IA-2 levels. Results: Our findings showcased down-regulated CYP27B1 mRNA levels, while CYP24A1 expression remained stable compared to healthy subjects (CYP27B1, p = 0.0005; CYP24A1, p = 0.205, respectively). In T1DM patients, the levels of has-miR-216b-5p were found to be increased, while the levels of has-miR-21-5p were decreased in comparison to the control group. Notably, no correlation was identified between the expression of CYP27B1 in T1DM patients and the levels of has-miR-216b-5p, has-miR-21-5p, and 1,25(OH)2D3. A significant negative correlation was identified between CYP27B1 mRNA levels in PBMCs of T1DM and IA2, but not with GAD65. Conclusions: The study highlights there were reduced levels of both CYP27B1 mRNA and has-miR-21-5p, along with elevated levels of has-miR-216b-5p in the PBMCs of T1DM. However, the absence of a correlation between the expression of CYP27B1, levels of has-miR-216b-5p, and the status of 1,25(OH)2D3 suggests the possible existence of other regulatory mechanisms. Additionally, the inverse relationship between IA2 autoantibodies and CYP27B1 expression in T1DM patients indicates a potential connection between this gene and the autoimmune processes inherent in T1DM.

Background As a major virus outbreak in the 21st century, the Coronavirus disease 2019 (COVID-19) pandemic has led to unprecedented hazards to mental health globally. Health care workers, patients with COVID-19 are experiencing post-traumatic stress disorders, anxiety, depression, and insomnia. Methods: A cross-sectional study using a questionnaire consisted of four parts: sociodemographic, current and previous health status, measures in a social isolation, and the Arabic version of Depression, Anxiety and Stress Scale (DASS-21). Results: We had 110 patients who completed the data. 89 (80.9%) of patients recovered from COVID-19. They ranged from 18-84 with a mean of 37.6 years (SD = 9.8 years). We had 33.6% of patients re-ported moderate to extremely severe depression compared to 18.2% with mild reported symptoms. The anxiety severity showed that (35.4%) out of patients had moderate to extremely severe anxiety, compared to (6.4%) who had mild anxiety. While stress severity showed that (22.7%) had moderate to extremely severe stress compared to (13.6%) who had mild stress. Conclusion: COVID-19 has caused a significant increase in the prevalence of mental health illness in the general population. Large systematic reviews are required to set the general overall of impact of this pandemic on mental health.

This research paper is about to obtain new soliton solutions to the M-fractional (1+1)-dimensional nonlinear Westervelt model by utilizing $\exp_a$ function and modified simplest equation techniques. The gained solutions involving dark, bright, periodic, dark-bright and other solitons. These results have many applications in wave propagation of sound waves, high amplitude in medical imaging and therapy. Achieved results are verified by Mathematica tool and the effect of M-fractional derivative on the solutions is explained through 2-Dimensional, 3-Dimensional and contour plots. At the end, these techniques are simple, fruitful and effective to deal with nonlinear FPDEs.

Cloud computing is a strong and efficient technology facing some efficiency challenges attributable to its decentralized nature. The emergence of fog computing has subdivided the expansive cloud into numerous smaller units known as "cloudlets." Fog computing is one of the most recent advancements in today’s cloud computing landscape. Each cloudlet is a novel and diminutive architectural element extending the contemporary cloud computing infrastructure. The term "cloudlets" has been integrated with fog computing due to its augmenting impact on the attributes of cloud computing. F fog computing is a significant foundation and an indispensable cloud component. Consequently, this technology holds the potential to address efficiency concerns effectively. As a result, this paper focuses on enhancing the efficiency of the cloud computing environment by fine-tuning the efficiency parameters derived from fog computing. These parameters encompass response time, latency, and network utilization. The proposed solution involves developing a simulation system to minimize task redundancy and increase performance levels in the healthcare environment. The outcomes manifest a substantial improvement in the performance of the suggested system, with a clear increase depending on the three key parameters (response time, network utilization, and latency). Therefore, these findings are encouraging and carry significant implications, promoting the application of the proposed system in the real healthcare environment.

Background: The current review was conducted to determine the effectiveness of atenolol on all-cause mortality rate among Asian patients with chronic progressive diseases, mainly diabetes mellitus, primary hypertension, and coronary artery disease. Methods: We searched the COCHRANE, MEDLINE, TRIP, and EMBASE databases for published articles up to 31 March 2023. Studies that compared all-cause mortality rates among Asian patients who were on atenolol or other medications were included. Results: The review included 79603 Asian patients from three cohort studies. Out of the studied patients, 36046 were atenolol users and 43557 were non-atenolol users. The review revealed that atenolol users recorded lower all-cause mortality rates compared to non-users with a significant difference (OR= 0.57, CI= 0.44-0.75, P<0.001). The pooled estimate of the all-cause mortality rate was also lower among atenolol users (7.02%) compared to metoprolol tartrate users (13.15%) with a significant difference (OR= 0.50, CI= 0.47-0.53, p < 0.0001). Although the included studies were categorized as having a low risk of bias for most of the studied domains, significant heterogeneity was recorded across these studies (I2 =88%, P=0.001). Conclusion: This review found that atenolol when compared to a control or metoprolol tartrate, has a significant effect in reducing the all-cause mortality rate among Asian patients with chronic progressive disease.

Cobalt (Co) is a transition metal and is classified as a beneficial metal for plants, but its benefits for plants remain obscure. Cobalt has been reported to negatively affect plant physiochemical processes both at higher (toxic) and lower (deficient) applied levels. High concentrations of cobalt in plant organs cause irreversible changes to the plant cells, mainly via enhanced production of reactive radicals. Moreover, Co and its compound play an essential role in humans as they are the central atoms of cobalamin, a co-enzyme precursor whose absence causes anemia. Hence, the optimum Co supply to plants is critical for customary plant metabolic workings. Henceforth, monitoring Co behavior in the soil-plant-human system is highly imperative. This review highlighted the latest literature on (i) Co in soil and plants; (ii) its mobility and phyto-availability in soil; (iii) phytouptake and translocation towards shoot tissues; (iv) toxic and deficient effects of Co on plants; (v) plant detoxification mechanisms under increased Co levels inside plants; and (v) its role in the human body. For this purpose, 1026 plant observations from literature data were analyzed related to Co biogeochemical behavior in the soil-plant system. The data analysis revealed an overall increase in 567 observations and a decrease in 381 observations. However, these general trends in plant responses vary significantly for different types of plant species and physiological attributes. Overall, the current review delineates an updated and critical representation of the biogeochemical behavior of Co in the soil-plant-human system, supported by up-to-date 9 main tables, 14 supporting tables, and 3 figures. The authors believe that the literature presented here can be of great interest to scientists, researchers, policymakers, and graduate-level students.

Nicotinamide riboside (NR) is an NAD+ precursor capable of regulating mammalian cellular metabolism. Phycocyanin oligopeptide (PC), a phytonutrient found in blue-green algae, has antioxidant and anti-inflammatory properties. This study explored the effects of NR, PC, and their combination on telomere length, inflammatory and antioxidant status in rats under chronic stressed conditions (CS). Forty-nine rats were allocated into seven groups: Control, chronic stress (CS), CS with NR (26.44 mg/kg), a low dose of 2.64 mg/kg of PC (PC-LD), or a high dose of 26.44 mg/kg PC (PC-HD), NR+PC-LD and NR+PC-HF. Rats were given daily corticosterone injections (40 mg/kg) to induce stressed conditions, or NR and PC were orally administered for 21 days. NR and PC supplementation, particularly NR plus PC, increased the serum antioxidant enzyme activities, hepatic nicotinamide adenine (NAD+) content, and telomere length (P&lt;0.001 for all) compared with the CS group. The levels of serum malondialdehyde (MDA), liver interleukin-6 (IL-6), tumor necrosis factor α (TNF-α), IL-1β, and IL-8 were reduced under CS condition (P&lt;0.001). In addition, CS decreased the levels of hepatic telomere-related proteins and sirtuin1 (SIRT1-3), while supplementation of NR and PC alone or in combination increased the levels of telomere-related proteins (e.g., POT1b, TRF1, and TRF2), and SIRT3, NAMPT P&lt;0.05. In conclusion, NR and PC, especially their combination, can alleviate metabolic abnormalities by enhancing hepatic cytokines, SIRT3, NAMPT, and NAD+ levels in CS-exposed rats. More research is needed to elucidate further the potential health effects of the combination of NR and PC in humans.

Cancer is second leading cause of death, worldwide. Lung cancer is the leading cause of cancer-related mortality. Plant-based therapeutics and herbal medicine have played a vital role in the development of several anti-cancerous agents, and has been used to reduce the severe side effects of chemotherapy as well. Since the anti-lung cancer properties of the plant Medicago. orbicularis are not explored yet, we identified its phytochemical composition and investigated the anti-oxidant, anti-hemolytic, and anti-cancerous properties of extracts of this plant in A549 human lung adenocarcinoma cells. Results show that all parts of M. orbicularis (stems, leaves, and fruits) exhibit remarkable anti-oxidant and hemolytic activities. In addition, all extracts showed a dose-dependent anti-cancerous cytotoxic activity against A549 cells; with fruit extracts being the most potent. This cytotoxic effect could be related, at least partly, to the induction of apoptosis, where M. orbicularis fruit extracts activated Caspase-3 and PARPP-1, and reduced the ratio of anti-apoptotic BCL-2/ pro-apoptotic BAX, thereby promoting cellular death. Furthermore, the use of M. orbicularis, in combination with a conventional chemotherapeutic agent, cisplatin, was assessed. Indeed, combination of cisplatin and M. orbicularis fruit extracts was more cytotoxic and induced more aggregation of A549 cells than either treatment alone. GC-MS analysis and total polyphenol and flavonoid content determination indicated that M. orbicularis is rich in compounds that have anti-cancerous effects. M. orbicularis may be a potential source of anti-cancerous agents to manage progression of lung cancer and its resistance to therapy.

SARS-CoV-2, influenza A/B virus (IAV/IBV) and respiratory syncytial virus (RSV) are among the common viruses causing acute respiratory infections. Clinical diagnosis to differentiate these viruses is challenging due to similar clinical presentations, thus laboratory-based real-time RT PCR is the gold standard for diagnosis. The study aimed to evaluate the diagnostic performance of STANDARD M10 Flu/RSV/SARS-CoV-2 (SD Biosensor Inc, Seoul, Korea). This retrospective study was conducted with archived respiratory samples positive and negative for SARS-CoV-2, IAV, IBV or RSV. The evaluation study involved a total of 322 respiratory samples comprising 215 positive samples (49 SARS-CoV-2, 48 IAV, 53 IBV, 65 RSV) and 107 negative samples. All samples were tested with both STANDARD M10 and either Xpert Xpress SARS-CoV-2 or Xpert Xpress Flu/RSV (Cepheid, USA). The sensitivity, specificity, positive predictive value and negative predictive value rates of STANDARD M10 were very similar to Xpert Xpress SARS-CoV-2 or Xpert Xpress Flu/RSV ranges for each virus (98-100%). The overall agreement was 99.4% with 99.1% agreement for positive samples and 100% agreement for negative samples. In conclusion, the STANDARD M10 point-of-care test is suitable for rapid simultaneous detection of SARS-CoV-2, IAV, IBV and RSV.

In this study, we investigate the existence of positive solutions within a system of Riemann-Liouville fractional differential equations that incorporate the (r1,r2,r3)-Laplacian operator while being subject to three-point boundary conditions. These equations incorporate various fractional derivatives and are influenced by parameters represented as (ψ1,ψ2,ψ3). Our approach involves employing techniques such as cone expansion and compression of the functional type, in conjunction with the Leggett-Williams fixed point theorem, to establish the existence of positive solutions. To emphasize the practical significance of our findings in the realm of fractional differential equations, we provide two illustrative examples.

Brain disorders pose a significant global healthcare challenge due to their complexity and profound impact on individuals and society. This review explores recent advancements in brain disease research, deepening our understanding and progress towards treatments. Technological innovations, like high-resolution imaging and optogenetics, play a pivotal role in illuminating cellular structures and dissecting neural circuits. Genetic analysis identifies dis-ease-associated genes and mutations, yet translating findings to clinical applications remains challenging. Epigenomics, transcriptomics, and proteomics provide molecular insights, un-covering disrupted pathways in conditions like Alzheimer's disease. Stem cell models elucidate developmental mechanisms, and immunotherapies, including CAR T cells, emerge as prom-ising strategies for brain cancers like glioblastoma. Genome editing tools, exemplified by CRISPR, enable precise modification of disease genes in models, deepening our understanding of pathogenesis. Multifaceted approaches integrating human studies, animal models, and bi-oinformatics propel the field forward. However, complexities persist, as disease specificity for cell types or brain regions remains an enigma, and genetic factors interact with environmental influences, highlighting disease intricacies. Ultimately, interdisciplinary efforts combining bi-ophysical and psychospiritual perspectives are essential to fully understand brain health and unlock transformative treatments for these debilitating disorders. A comprehensive under-standing of brain disorders is vital to improve the quality of life for millions and alleviate the global burden of neurological afflictions. Continued collaborative research will lead to an era of improved brain health worldwide.

In the food sector, packaging is one of the important steps that ensures the safe, unspoiled, min-imum cost of storing, transporting and delivering the food that goes into production to the con-sumer. Food spoilage caused by foodborne pathogens and microorganisms is a serious problem in the food chain, reducing the shelf life of foods. Therefore, consumers' demands for more natural, disposable, biodegradable and recyclable antibacterial food packaging materials have considera-bly increased. This review covers a comprehensive current literature review of antibacterial food packaging, which includes with titles antibacterial agents, organic acids and other compounds, enzymes, bacteriocins, natural extracts, essential oils, application of encapsulation and antimi-crobial packaging. Research findings on antimicrobial food packaging used to extend the shelf life of foods were collected from online databases such as PubMed/MedLine, Wiley Online Li-brary, Scopus, Web of Science, and Google Scholar. In this review, the activities of different bio-materials and compounds used to extend the shelf life of foods were compared

Hate Speech Detection in Arabic presents a multifaceted challenge due to the broad and diverse linguistic terrain. With its multiple dialects and rich cultural subtleties, Arabic requires particular measures to address hate speech online successfully. To address this issue, academics and developers have used natural language processing (NLP) methods and machine learning algorithms adapted to the complexities of Arabic text. However, many proposed methods were hampered by a lack of a comprehensive dataset/corpus of Arabic hate speech. In this research, we propose a novel multi-class public Arabic dataset comprised of 403,688 annotated tweets categorized as extremely positive, positive, neutral, or negative based on the presence of hate speech. Using our developed dataset, we additionally characterize the performance of multiple machine learning models for Hate speech identification in Arabic Jordanian dialect tweets. Specifically, the Word2Vec, TF-IDF, and AraBert text representation models have been applied to produce word vectors. With the help of these models, we can provide classification models with vectors representing text. After that, seven Machine learning classifiers have been evaluated: Support Vector Machine (SVM), Logistic Regression (LR), Naive Bays (NB), Random Forest (RF), AdaBoost (Ada), XGBoost (XGB), and CatBoost (CatB). In light of this, the experimental evaluation revealed that, in this challenging and unstructured setting, our gathered and annotated datasets were rather efficient and generated encouraging assessment outcomes. This will enable academics to delve further into this crucial field of study.

Breast cancer (BC) is the second leading cause of death in the United States in women. 1 in 8 women in their lifetime has a risk of developing breast cancer. With advances in omics technology, more data is available for diagnosis, treatment, and prognosis. The help of Machine Learning algorithms, a subdomain of Artificial Intelligence, would allow for a better clinical support tool. Machine Learning could be the key to answering a complex problem in BC. The methodology of this research question involves collecting and finding data such as RNA-Seq datasets, selecting and training appropriate machine learning algorithms, and evaluating the performance of the algorithms in predicting BC prognosis. Also, the study explores and tries to identify the most relevant genes and pathways through feature selection extraction and dimensionality reduction techniques. After applying feature extraction, the top 10 genes were extracted using the Univariate Feature Selection (UFS) method, precisely the SelectKBest technique. After employing different machine learning algorithms, such as Networks, Random Forest, Linear SVM, Logistic Regression, and Quadratic Discriminant Analysis (QDA), we found QDA was the best model in classifying the RNA-seq dataset with a 96% accuracy rate and 94% ROC AUC. This study suggests that AK2 and CD68 have a positive correlation with each other, and it could potentially be a biomarker and therapeutic target for BC.

Melanoma is widely recognized as one of the most lethal forms of skin cancer, with its incidence showing an upward trend in recent years. Nonetheless, the timely detection of this malignancy substantially enhances the likelihood of patients’ long-term survival. Several computer-based methods have recently been proposed in the pursuit of diagnosing skin lesions at their early stages. Despite achieving some level of success, there still remains a margin of error that the machine learning community considers to be an unresolved research challenge. This study presents a novel framework for the classification of skin lesions. The framework incorporates deep features to generate a highly discriminant feature vector, while also maintaining the integrity of the original feature space. Recent deep models including Darknet53, DenseNet201, InceptionV3, and InceptionResNetV2 are employed in our study for the purpose of feature extraction. Additionally, transfer learning is leveraged to enhance the performance of our approach. In the subsequent phase, the extracted feature information from the chosen pre-existing models is combined, with the aim of preserving maximum information, prior to undergoing the process of feature selection using a novel entropy-controlled grey wolf optimization (ECGWO) algorithm. The integration of fusion and selection techniques is employed to initially incorporate the feature vector with a high level of information and subsequently eliminate redundant and irrelevant feature information. The efficacy of our design is substantiated through the evaluation on three benchmark dermoscopic datasets, namely PH2, ISIC-MSK, and ISIC-UDA. In order to validate the proposed methodology, a comprehensive evaluation is conducted, including a rigorous comparison with established techniques in the field.

According to WHO, reducing salt intake to less than 5 g/day means less death, disability, and suffering from heart disease and stroke, with around 1.89 million lives saved every year. In this scoping review, we have reviewed the salt consumption pattern of South Asia. For this purpose, we searched online databases and websites and consulted key informants to address relevant unpublished reports. The inclusion criteria are English-language publications between January 2011 and October 2021, as well as research that evaluated salt intake in the South Asian region and reported salt/sodium 24-hr urine or spot urine samples involving at least 100 participants. A total of 2043 studies were screened, out of which 12 studies fulfilled all the criteria. Our review revealed that reported salt intake in the South Asian region ranges from 6.7-13.3 g/day, which was higher than the WHO-recommended maximum level of 5 g/day in all countries. Men consumed more salt than women. This review demonstrates the critical importance of implementing a salt reduction program in South Asian countries.

Rapid climate change requires more powerful and precise modeling methods to forecast future climate variability. The GSTARIMA Model is efficient, combining space-time analysis with the Autoregressive Moving Average (ARIMA) Model. The integration of heteroscedasticity error and the Kriging method can strengthen the Model's ability to handle the problem of non-constant error variance in the GSTARIMA Model and forecast at unobserved locations of climate observations. This paper's Systematics Literature Review (SLR) is presented comprehensively with the principal aim of developing a thorough understanding of applying the GSTARIMA Model with heteroskedasticity error and the Kriging Method in climate forecasting following the Data Analytics Lifecycle methodology. The Systematic Literature Review (SLR) process consists of three main stages. We sourced the articles from databases such as Scopus, Dimensions, and EBSCO-Host The subsequent stage involved conducting a comprehensive literature review using the PRISMA method to ensure rigor and depth. Additionally, we performed bibliometric analysis to enhance rigor. Lastly, we conducted a gap analysis session to scrutinize existing research on the GSTARIMA Model and identify new opportunities. This literature review reveals that integrating GSTARIMA Model with heteroscedasticity errors and the Kriging method is suitable for climate forecasting. This research inspires researchers to contribute to the improvement and refinement of the Model, making it a more potent and valuable tool in climate forecasting.

Contrast agents developed for X-ray computed tomography (CT) offer extremely valuable tools and techniques in diagnostics via contrast enhancements. Heavy metal-based nanoparticles (NPs) can provide high contrast in CT images. These result from a high density of heavy metal atoms with high X-ray attenuation coefficients that exceed that of iodine (I), which is currently used in hydrophilic organic CT contrast agents. Nontoxicity and colloidal stability are vital characteristics in designing heavy metal-based NPs as CT contrast agents. In addition, the particle size must be small for in vivo renal excretion. In vitro phantom imaging studies can provide X-ray attenuation efficiency, which is a critical parameter for CT contrast agents, and the imaging performance of CT contrast agents can be demonstrated via in vivo experiments. This review focuses on in vitro and in vivo studies of various heavy metal-based NPs (metal: Au, Pt, Pd, Ag, Ce, Gd, Dy, Ho, Yb, Ta, W, and Bi) and provides an outlook on their use as high-performance CT contrast agents.

Motivation: It is essential for the diagnosis and treatment of renal cancers to segment kidney tumours precisely and effectively. In medical image segmentation tasks, deep learning models have demonstrated promising results, and the UNet model is widely employed in this field. However, optimising the UNet model for kidney tumour segmentation further can improve its efficacy and deployment feasibility. Related Works: Previous works have explored various techniques to improve the efficiency of deep learning models in medical image segmentation. Image partitioning methods divides the input image into smaller regions, enabling parallel processing and reducing memory requirements. Pruning techniques eliminates redundant or insignificant weights, neurons and connections, resulting in a more compact and efficient model architecture. However, the UNet model architecture and its complexity in the context of kidney tumor segmentation using UNet remains unexplored. Methodology: The proposed methodology consists of adaptive partitioning and weight pruning. Adaptive partitioning divides the UNet model into smaller sub-models, facilitating parallel processing and accelerating inference without compromising segmentation accuracy. Weight pruning techniques remove redundant or less significant weights from the UNet-P model, reducing complexity and improving inference time by eliminating unnecessary computations. The adaptive partitioning and weight pruning processes are seamlessly integrated within the UNet-P architecture, resulting in an optimized model for kidney tumor segmentation. Results: We performed experiments utilising a dataset of KiT 23 CT scan images containing images of kidney malignancies. Compared to the standard UNet model, the optimised UNet-PWP model with adaptive partitioning and weight pruning obtained significant efficiency gains. The adaptive partitioning permitted parallel computation of sub-models, which accelerated inference times. Weight pruning decreased the UNet-PWP model’s complexity without compromising segmentation accuracy, thereby enhancing efficiency. The results of our experiments demonstrated the efficacy of the proposed method with 98% accuracy, demonstrating its potential for deployment in health sector.

Synthesis and antitumour activity of a palladium compound, [Bis (quinoline) palladium (II) chloride] (coded as NH1) alone and in combination along with its proposed mechanism of action has been described in the present study. Antitumour activity has been performed in seven different cancer cell lines using colorimetric 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay. The investigated palladium compound demonstrated superiority over clinical standard cisplatin against drug resistant ovarian cancer cell lines. NH1 also demonstrates 4.4 times greater activity than cisplatin against breast cancer model. Binary sequenced combination study showed that NH1 in combination with curcumin is mostly additive to antagonistic. However, combination of NH1 with 6-shogaol demonstrated synergism depending on dose and sequence. Proteomic study revealed that changes in expression of 14 proteins were significantly associated with anticancer mechanism of NH1. In vivo anticancer activity of NH1 at a dose of 0.75 mg/kg was also evaluated using Erlich Ascites Carcinoma (EAC) cell lines in Swiss-albino mice model. Preliminary toxicity study in Swiss-albino mice proved that NH1 is comparatively less toxic at both of the administered doses, either 2.5 mg/kg or 5 mg/kg. However, cisplatin demonstrated significant toxicity at both of the administered doses. Biochemical investigations also supported that NH1 demonstrated lesser toxicity profile towards liver or kidney compared to clinical standard cisplatin.

The coast of Oman is observing huge coastal developments to materialize Oman Vision 2040 covering all the strategic sectors. Historical data of coastal hydrodynamic parameters is scarce, even though its importance for a proper design of coastal structures is recognized. Acoustic Doppler Current Profilers were deployed at eleven locations along the coast of Oman. These locations were selected based on their strategic importance for the country. The duration of deployment was from 60 to 265 days. The measured data of waves and current were collected and analyzed using the equipment-specific software and Excel. The significant wave heights can reach 2m along the whole coast of Oman. The southern coast is dominated by the swells. The maximum to significant wave height ratio is approximately 1.5 which is less than a value of 2 obtained using Rayleigh distribution. The coastal currents are stronger along the southern coast than those along the northern coast. The range of current magnitude is from 0.02 m/s to 0.8 m/s. This baseline study will help the public authorities in establishing permanent hydrodynamic measurement stations along the coast of Oman. Moreover, these measurements will serve the practicing engineers in designing coastal structures along the coast of Oman.

Objectives: Studies on the association between non-steroidal anti-inflammatory drugs (NSAIDs) and major adverse cardiovascular events (MACE) in the Arabian Gulf are scarce. The aim of this study was to evaluate the association between NSAIDs use and MACE in acute coronary syndrome (ACS) patients in the Arabian Gulf region. Methods: Data was analyzed from 3,007 consecutive patients diagnosed with ACS admitted to 29 hospitals in four Arabian Gulf countries from January 2012 to January 2013 as well as being on prior NSAIDs use during the index admission. MACE included stroke/transient ischemic attacks (TIAs), myocardial infarction (MI), all-cause mortality and readmissions for cardiac reasons. Results: The overall mean age of the cohort was 62 ± 12 years and 9.6% (n = 290) of the patients were on prior NSAID use during the index admission. At 12-months follow-up, after adjusting for confounding factors, those on NSAIDs were significantly more likely to have had MACE (adjusted OR (aOR), 1.89; 95% confidence interval (CI): 1.44-2.48; p < 0.001). Specifically, the higher event rates observed were stroke/TIA (aOR, 2.50; 95% CI: 1.51-4.14; p < 0.001) and readmissions for cardiac reasons (aOR, 2.09; 95% CI: 1.59-2.74; p < 0.001) but not MI (aOR, 1.26; 95% CI: 0.80-1.99; p = 0.320) and all-cause mortality (aOR, 0.79; 95% CI: 0.46-1.34; p = 0.383). Conclusions: NSAIDs use was associated with significant stroke/TIA events as well as readmissions for cardiac reasons. However, NSAIDs were not associated with increased MI or all-cause mortality rates in ACS patients in the Arabian Gulf.

Most historical buildings and structures in Oman were built using unreinforced stone masonry. These structures have deteriorated due to ageing of materials, environmental degradation, and lack of maintenance. This research investigates the physical, chemical, and mechanical properties of local building materials and the results of an experimental study on the out-of-plane bending effectiveness of an innovative strengthening technique applied to existing masonry walls. The technique consists of the application on one face of the walls of a basalt textile-reinforced sarooj mortar (TRM). Four-point bending tests of full-scale masonry samples (1000 mm width, 2000 mm height, and 350 mm depth) were carried out using one unreinforced specimen and three different cases of reinforced specimens. The performance of unreinforced and reinforced specimens was analyzed and compared. The strengthened specimens were able to resist moments of out-of-plane bending 2.5 to 3 times greater than those of unreinforced specimen (160%- 233% increase). Moreover, the strengthened walls were able to sustain higher deformations (deflections) than the unreinforced specimen ranging from 20%-130%. The results showed that using TRM was effective for the out-of-plane strengthening of stone masonry using a local material (sarooj) that is compatible with existing stone masonry building materials.

Historical and Endowment Properties are different from Heritage and cultural Properties, as Historical and Endowment properties are governed by a unique set of laws that Waqf recipients must abide by. Property that is entrusted is usually in the form of buildings, land or valuables which in preservation is not limited to time as long as the property can be utilized. Reliable information technology is needed to ensure data security both digitally and physically, while the rapid development of information technology demands information openness and this will be a challenge in itself. The objectives of this study include examining the collection of historical databases and endowments, the relationship between digital data and physical data and management organizations. The method of how to design a query model to display data is then analyzed whether the data conforms to the rules in waqf management. The results are expected to bring up accurate data between digital data and physical data and if there are differences into findings for the next analysis.

Hand, foot and mouth disease (HFMD) is a childhood disease caused by enterovirus A71 (EV-A71) and coxsackievirus A16 (CV-A16). We hypothesize that capsid loops are important epitopes for EV-A71 and CV-A16. Seven chimeric EV-A71 (ChiE71) involving VP1 BC, DE, EF, GH and HI loops, VP2 EF loop, and VP3 GH loop were substituted with corresponding CV-A16 loops. VP3 GH loop is the most conserved (91.3%) while VP1 BC loop has only 45.5% similarity. Only ChiE71-1-BC, ChiE71-1-EF, ChiE71-1-GH and ChiE71-3-GH were viable. EV-A71 and CV-A16 antiserum neutralized ChiE71-1-BC and ChiE71-1-EF. Mice immunized with inactivated ChiE71 elicited high IgG, IFN-γ, IL-2, IL-4 and IL-10. Neonatal mice receiving passive transfer of WT EV-A71, ChiE71-1-EF and ChiE71-1-BC immune sera had 100%, 80.0% and no survival, respectively, against lethal challenges with EV-A71, suggesting that the substituted CV-A16 loops disrupted EV-A71 immunogenicity. Passive transfer of CV-A16, ChiE71-1-EF and ChiE71-1-BC immune sera provided 40.0%, 20.0% and 42.9% survival, respectively, against CV-A16. One-day-old neonatal mice actively immunized with WT EV-A71, ChiE71-1-BC, ChiE71-1-EF and CV-A16 achieved 62.5%, 60.0%, 57.1% and no survival respectively, after the EV-A71 challenge. Active immunization using CV-A16 provided full protection while WT EV-A71, ChiE71-1-BC, ChiE71-1-EF immunization showed partial cross-protection in CV-A16 lethal challenge with survival rates of 50.0%, 20.0%, and 40%, respectively. Taken together, the EV-A71 VP1 BC loop is essential in immunogenicity of EV-A71 and substitution with CV-A16 VP1 BC loop was insufficient to confer protection against CV-A16. The EF loop maintains the cross-protective immune responses. Disruption of a capsid loop could affect virus immunogenicity, and future vaccine design should include conservation of the enterovirus capsid loops.

The connection between marital status and suicidal behavior has been poorly assessed in South Asia. We aimed to see the proportion of marital status in individuals in suicidal behavior in South Asian countries. We followed PRISMA guidelines and registered the protocol in advance (PROSPERO 2023 CRD42023399906). A systematic search was conducted in Medline, Embase, and PsycINFO. Meta-analyses were performed to pool the proportion of married individuals with suicidal behavior (total, suicide, and suicide attempt) in South Asian countries. Our search identified 47 studies for this review from six countries published from 1999 to 2022 with a sample size ranging from 27 to 89178. The proportion of married individuals was 55.4% (95% CI 50.1-60.5) for suicidal behavior, 52.7% (95% CI 44.5 – 60.7) for suicides, and 43.1 (95% CI 32.9 – 53.9) for suicide attempts. The proportion of married persons among suicide attempts varied significantly across countries (p=0.016) which was highest (61.8%; 95% CI: 57.2 – 66.2) in India, followed by Bangladesh (52.5%; 95% CI 41.8% - 62.9%) and Pakistan (45.1%; 95% CI 30.9 – 59.9). As the current study did not assess any cause-and-effect association, a cautious interpretation is warranted while considering married marital status as a risk factor.

Polymorphism in cytochrome P450 (CYP) 2C9 enzyme is known to cause significant inter-individual differences in drug response and occurrence of adverse drug reactions. Different alleles of the CYP2C9 gene have been identified but the notable alleles responsible for reduced enzyme activity are CYP2C9*2 and CYP2C9*3. No pharmacogenetic data is available on CYP2C9*2 and CYP2C9*3 alleles in Pakistani population. In Pakistan pharmacogenetics which examines the relationship between genetic factors and drug response, are in the early stages of development. We for the first time investigated the association between the CYP2C9 variant alleles CYP2C9*2 and CYP2C9*3 and the incidence of hypoglycemia in diabetic patients who were receiving the sulfonylurea medications. A total of n=400 individuals of Pashtun ethnicity were recruited from ten different districts of Khyber Pakhtunkhwa, Pakistan to participate in the study. The study participants were divided into two distinct groups: the case group (n=200) and the control group (n=200). The case group consisted of individuals with Type 2 Diabetes Mellitus (T2DM) who were receiving sulfonylurea medications and experience hypoglycaemia with it whereas the control group included individuals with T2DM who were receiving sulfonylurea medication but did not experience sulfonylurea-induced hypoglycaemia (SIH). Blood samples were obtained from study participants following informed consent. DNA was isolated from whole blood samples using Wiz-Prep DNA extraction kit. Following DNA isolation, CYP2C9 alleles were genotyped using MassARRAY sequencing platform at centre of genomics Rehman Medical Institute (RMI). The frequency of CYP2C9*2 (low activity allele) was more frequent in the diabetic patients with sulphonylurea-induced hypoglycaemia (SIH) compared to the control group (17.5% vs. 6.0%, p=0.021). The frequency of its corresponding genotype CYP2C9*1/*2 was higher in cases compared to control group (10% vs. 6% with P=0.036), same was true for genotype CYP2C9*2/*2 (7% vs. 3.5 % with P=0.028). Logistic regression analysis evident potential association of CYP2C9*2 allele and its genotypes with SIH. When adjusted for confounding factors such age, weight, sex, daily dose of sulphonylurea and triglyceride level the association between the CYP2C9*2 allele and hypoglycemia remains consistent. Confounding factors played no role in SIH because both groups (cases and controls) were closely matched in term of age, weight, sex, mean daily dose of sulphonylurea and trigyleride levels. Our study suggests that genetic information about a patient's CYP2C9 gene/enzyme can potentially assist physicians in prescribing the most suitable and safest drug based on their genetic make-up.

The underlying mechanisms of secondary neuronal damage following intracerebellar hemorrhage are not yet clear. We aimed to study the possible mechanisms in the mediation of secondary neuronal damage following intracerebellar hemorrhage. ICbH was induced by collagenase type VII-S into mice in 2 phases (n=24/phase): 12 in control group, 12 in day 1 group, 12 in day 3 group and another 12 in day 7 group. All mice underwent locomotor assessment and subsequently sacrificed on day 1, day 3 and day 7 respectively. Cerebellum from phase one and phase two were taken to study morphological, immunohistochemistry and oxidative stress respectively. Mice behavior disturbed following ICbH at day 3 and y 7 as compared with control. Besides, NO increased-on day 1 post induction and suppressed on day 3 and 7. Expressions of SOD, CAT, nNOS, GPX1 and COX-2 were significantly raised on day 3. Morphological studies of the perihaematoma region and tissue showed neuronal damage occurred from day 1 onwards, peaked on day 3 and continued day 7. NO and expression of genes be correlating with morphological changes. Briefly, NO and oxidative stress has an important role in the cascade of secondary neuronal damage of the perihematomal region of ICbH.

The evaluation of suitability for bioclimatic viticulture indices (BVIs) zones, as with any other crop, requires a well-founded knowledge of the spatial variability in climate data, which is also used to assess different grapevine cultivars and to delimit appropriate regions for vineyard production under the current climate and projected climate change. BVIs, on the other hand, are typically calculated using a small number of locations linked by climatic station sites or applied using a coarsely-resolution distributed dataset. Furthermore, often the methods applied to precisely delineate symmetrical regions are not appropriate to generate accurate maps. To provide an analysis using three temperature-based indices and the hydrothermal coefficient (HTC), quantifying their spatial variation, and representing the spatial patterns of each BVI throughout the Jabal Al Arab viticulture—one of the most important Syrian viticulture regions in the Eastern Mediterranean—daily temperature data from 15 meteorological stations and 57 rain gauges, considering the 1984–2014 period, and downscaled future scenarios (RCPs based on CanESM2), considering the 2016–2100 period, were utilized. The statistical method of each BVI was analyzed, and, later, they were mapped by using GIS and a hybrid interpolation (regression-kriging) approach. The regression fitting method revealed that the sum accumulation of heat and the hydro-thermal index during the growing season were highly related to elevation and distance to the seacoast variables; however, the viticulture zones varied spatially depending on which index was used and under suggested future scenarios compared to the current climate. The spatial distribution of climate in the Jabal Al Arab regions exhibits significant variability. The findings suggest that climate change projections indicate a prevalence of warmer conditions in the future. Under the RCP scenarios, the territory can be categorized into up to three bioclimatic classes for both the Heat Index (HI) and the Winter Index-Growing Degree Days (WI-GDD), in contrast to the current climate which has six classes. These results provide valuable insights into the suitability of viticulture within each climatic region and facilitate the identification of homogeneous zones. The utilization of consistent bioclimatic indices and an advanced hybrid interpolation method has enabled the delineation and comparison of bioclimatic variables of Jabal Al Arab with other regions worldwide. Such comparisons should be considered when selecting grapevine varieties and assessing the potential for grape production.

Against the backdrop of global climate change, the frequency of drought events is increasing, leading to significant impacts on human society and development. Therefore, it is crucial to study the propagation patterns and trends of drought characteristics over a long-time scale. The main objective of this study is to delineate the dynamics of drought characteristics by examining their propagation patterns in China from 1951 to 2020. In this study, precipitation data from meteorological stations across mainland China were used. A comprehensive dataset consisting of 700 stations over the past 70 years was collected and analyzed. To ensure data accuracy, the GPCC database was employed for data correction and gap filling. Long-term drought evolution was assessed using both the SPI-12 and SPEI-12 indices to detect drought characteristics. Two Moran indices were applied to identify propagation patterns, and the MK analysis method along with the Theil-Sen slope estimator were utilized to track historical trends of these indices. The findings of this study reveal the following key results: (i) Based on the SPI-12, the main areas of China that are prone to drought are mostly concentrated around the Hu Huanyong Line. Indicating a tendency towards drying based on the decadal change analysis. (ii) The distribution of drought-prone areas in China, as indicated by the SPEI-12, is extensive and broadly distributed, with a correlation to urbanization and population density. These drought-prone areas are gradually expanding. (iii) Between 2010 and 2011, China experienced the most severe drought event in nearly 70 years, affecting nearly 50% of the country's area with a high degree of severity. This event may be attributed to atmospheric circulation variability, exacerbated by the impact of urbanization on precipitation and drought. (iv) The frequency of drought occurrence in China gradually decreases from south to north, with the northeast and northern regions being less affected. However, areas with less frequent droughts experience longer and more severe drought durations. In conclusion, this study provides valuable insights into the characteristics and propagation patterns of drought in China, offering essential information for the development of effective strategies to mitigate the impacts of drought events.

Anemia is a well-developed discipline where the concepts of precision medicine have, in part and being studied extensively. This review discusses the treatment of EPO-deficient anemia and resistance in Chronic Kidney Disease (CKD). Traditionally, erythropoietin-stimulating agents (ESA) and iron supplementation have been used to manage anemia in CKD. However, these treatments have potential risks, including cardiovascular and thromboembolic events. Newer treatments have emerged to address these risks, such as slow-release and low-dosage intravenous iron, oral iron, and erythropoietin-iron combination therapy. Another novel approach is using hypoxia-inducible factor prolyl hydroxylase inhibitors (HIF-PHI). This review highlights the need for precision medicine targeting genetic components of EPO-deficient anemia in CKD and discusses individual variability of genes such as the erythropoietin gene (EPO), Interleukin-β gene (IL-β), and hypoxia-inducible factor gene (HIF). Pharmacogenomics testing aims to provide targeted therapies and interventions that are tailored to the specific characteristics of an individual, optimizing treatment outcomes and minimizing resistance and adverse effects. The article concludes by suggesting the potential of receptor modification to revolutionize treatment outcome of erythropoietin deficiency anemia through integration of the mentioned approach.

The Lead-DBS imaging toolbox reconstructs the location of β-oscillations in the subthalamic nucleus (STN) in patients with Parkinson’s disease. The objective was to compare this probabilistic location with those of intraoperative monopolar β-oscillations (Vercise Cartesia directional electrodes, Boston Scientific). Also, the efficacy of stimulated structures in reducing motor symptoms were analysed. β-oscillations were computed from local field potentials [0.5-3kHz] by using shielded wires for monopolar recordings with an extracranial shielded reference. For each electrode contact, power spectral densities of the β-band [13-31Hz] were compared with those of all eight electrode contacts. The DISTAL, electrophysiological, and DBS target atlases of the Lead-DBS toolbox were applied to the reconstructed electrodes from preoperative MRI and postoperative CT. Thirty-six electrodes (20 patients: 7 female, 13 male; 16/20 both, 4/20 single STN) were analysed. Stimulation sites dorsal and/or lateral to the sensorimotor STN were most efficient. In 33/36 electrodes at least one contact was measured with stronger β-oscillations, 23 in or touching the ventral subpart of the probabilistic volume with β-oscillations, 10 not located in or touching but adjacent to this volume; in 3/36 electrodes, no contact was found with β-oscillations, they were distant from this volume. Monopolar local field potentials confirmed the ventral subpart of the probabilistic β-oscillations.

Traffic shaping is a critical task in software-defined -IoT networks (SDN-IoTs) to efficiently manage network resources and ensure Quality of Service (QoS) for end-users. However, traditional traffic shaping approaches based on queuing theory or static policies may not be effective due to the dynamic and unpredictable nature of network traffic. In this paper, we propose a novel approach that leverages Graph Neural Networks (GNNs) and Multi-arm Bandit algorithms to dynamically optimize traffic shaping policies based on real-time network traffic patterns. Specifically, our approach uses a GNN model to learn and predict network traffic patterns and a Multi-arm Bandit algorithm to optimize traffic shaping policies based on these predictions. We evaluate the proposed approach on three different datasets, including a simulated corporate network (KDD Cup 1999), a collection of network traffic traces (CAIDA), and a simulated network environment with both normal and malicious traffic (NSL-KDD). The results demonstrate that our approach outperforms other state-of-the-art traffic shaping methods, achieving higher throughput, lower packet loss, and lower delay, while effectively detecting anomalous traffic patterns. The proposed approach offers a promising solution to traffic shaping in SDNs, enabling efficient resource management and QoS assurance

Leukemia, characterized by abnormal blood cell proliferation, remains a significant challenge in cancer treatment. Thymoquinone (TQ), a bioactive compound derived from black seed, has demonstrated anticancer properties, including telomerase inhibition and induction of apoptosis. However, TQ's poor solubility and limited bioavailability hinder its clinical application. This study explores the use of SBE-β-CD, a cyclodextrin derivative, to enhance the solubility and stability of TQ for leukemia treatment. SBE-β-CD offers low hemolytic activity and has been successfully employed in controlled drug release systems. The study investigates the formation of inclusion complexes between TQ and SBE-β-CD and assesses their effects on leukemia cell growth. Results indicate that the TQ/SBE-β-CD complex exhibits improved solubility and enhanced cytotoxic effects compared to TQ alone, suggesting the potential of SBE-β-CD as a drug delivery system for TQ. Annexin V-FITC tests demonstrate increased apoptosis and reduced telomerase activity in leukemia cells treated with TQ/SBE-β-CD, supporting its anti-leukemic potential. Molecular docking analysis reveals a strong binding affinity between TQ and telomerase. However, further research is needed to optimize the apoptotic effects and minimize necrosis induction. In conclusion, TQ/SBE-β-CD shows promise as a novel strategy for leukemia treatment by targeting telomerase and enhancing the cytotoxic effects of TQ, offering a potential solution to overcome the limitations of TQ's poor solubility and bioavailability.

In this study, we introduce a new class of bi-univalent functions using q-Janowski Function. We derive the Fekete-Szegö functional problems for functions in this new subclass, as well as estimates for the Taylor-Maclaurin coefficients |α2| and |α3|. Furthermore, a collection of fresh outcomes are3 presented by customizing the parameters employed in our initial discoveries.

The battle of currents between AC and DC reignited as a result of the development in the field of power electronics. The efficiency of DC distribution systems is highly dependent on the efficiency of distribution converter, which calls for optimized schemes for efficiency enhancement of distribution converters. Modular solid-state transformers play a vital role in DC Distribution Networks and Renewable Energy systems (RES).This paper deals with efficiency-based load distribution for Solid State Transformers (SSTs) in DC distribution networks. Aim is to achieve a set of minimum inputs that are consistent with output while considering constraints and efficiency. As the main feature of modularity is associated with a three-stage structure of SSTs. This modular structure has been optimized using Ant Lion Optimizer (ALO) and validated by applying it EIA (Energy Information Agency) DC Distribution Network which contains SSTs. In the DC distribution grid, modular SSTs provide promising conversion of DC power from medium voltage to lower DC range (400V). The proposed algorithm is simulated in MATLAB and also compared with two other metaheuristic algorithms. The obtained results prove that the proposed method can significantly reduce input requirements for producing the same output while satisfying the specified constraints.

This paper presents a systematic literature review that identifies critical factors impacting the implementation of advanced manufacturing technology (AMT) worldwide. The study utilizes two databases, ProQuest and Compendex, as well as Google Scholar. The study identified eight dimensions that illustrate the critical factors of AMT adoption and implementation: education, planning, top management know-how, technical know-how, business, economic impact, regulations, and social impact. The results highlight a research gap in understanding the need for effective integration among these eight dimensions in developed and developing economies. Consequently, the study recommends the adoption of a broader perspective that considers the role of integration and interaction between critical factors in each category and their impact on AMT implementation. The systematic literature review conducted in this study reviews several critical factors related to the adoption and implementation of AMT.

Rivaroxaban and aspirin are commonly used antithrombotic agents that are used in combination for the prevention of coronary artery disease (CAD) and atherothrombotic events in adult patients after an acute coronary syndrome (ACS) with elevated cardiac biomarkers, or with coronary artery disease (CAD) or symptomatic peripheral artery disease (PAD) in high-risk patients. The recommended dosage is 2.5 mg Rivaroxaban twice daily with 75–100 mg aspirin daily. This study aimed to develop a fixed-dose combination tablet of rivaroxaban (2.5 mg) and aspirin (50 mg) to decrease the patient's pill burden and enhance medication adherence. The product formula was developed based on compatibility studies among the active ingredients and the active ingredients' compatibility studies. The formula and the manufacturing procedure were chosen based on the risk assessment for each active substance, wet granulation with both actives intragranular was found to have faster dissolution than direct mix formulae. Furthermore, a validated reverse-phase HPLC stability indicator method was developed to detect APIs and their possible degradants in the formula.

Plants attained cellular homeostasis of phosphate (Pi) through an integrated response pathway regulated by different families of transcription factors including MYB, WRKY, bHLH and ZFP. The systemic response to Pi limitation showed the critical role played by inositol pyrophosphate (PP-InsPs) as signaling molecule and SPX (SYG1/PHO81/XPR1) domain proteins as sensor of cellular Pi status. Binding of SPX to PP-InsPs regulates the transcriptional activity of the MYB-CC proteins, phosphate starvation response factors (PHR/PHL) as the central regulator of Pi-deficiency response in plants. Vacuolar phosphate transporter, VPT may sense the cellular Pi status by its SPX domain, and vacuolar sequestration is activated under Pi replete condition and the stored Pi is an important resource to be mobilized under Pi deficiency. Proteomic approaches led to new discoveries of proteins associated with Pi-deficient response pathways and post-translational events that may influence plants in achieving Pi homeostasis. This review provides current understanding on the molecular mechanisms at the transcriptional and translational levels for achieving Pi homeostasis in plants highlighting the importance of DNA-protein and protein-protein interactions. The potential strategies for employing the CRISPR technology to modify the gene sequences of key regulatory and response proteins for attaining plant Pi homeostasis are discussed.

Background: Arm elevation plays an important role in simple and complex daily tasks. Muscles that stabilize the shoulder girdle also function as respiratory accessory muscles. Dual demand on these muscles, particularly in patients with chronic respiratory conditions, leads to dyspnea and fatigue of the upper limb, making simple daily activities difficult. Various tests, including Grocery Shelving Task (GST), are designed to assess functional performance during upper limb activities. The aim of the study is to derive reference values for GST among the population of the United Arab Emirates Methods: This cross-sectional study was conducted with 220 healthy individuals of both genders between the ages of 20 and 69. Duration required to complete GST was recorded. The correlation between duration and age, height, body mass and body mass index (BMI) were also assessed. Results: Reference values for duration (in seconds) in females for age groups 20-29, 30-39, 40-49, 50-59 and 60-69 are 43.5±5.5, 43.1±8.08, 48.1±6.7, 44.9±7.1, 46.7±6.5 respectively. Values for males of age groups 20-29, 30-39, 40-49, 50-59 and 60-69 are 45.7±6.7, 44.8±8.9, 42.5±10.01, 53.4±4.2, and 53.9±5.4 respectively. Conclusion: Reference values for GST duration were obtained. Weak correlations were found between duration and age, height, body mass, BMI of the participants.