The dramatic increased rates of uncontrolled urbanization in various parts of the World have resulted in loss of native species and overall threats to biodiversity. Over the last few decades Saudi Arabia has witnessed a remarkably rapid population growth and unparalleled levels of urbanization, leading to threats to biodiversity. Ants were pitfall-trapped across an urban-rural gradient to evaluate ant assemblage responses to urbanization in Wadi Hanifa, Riyadh, Central Saudi Arabia. Fifteen sampling sites were selected along three different urbanization gradients, each traversing urban, suburban and rural zones. Within each site 10 traps were distributed and operated for 7 consecutive days, at 3-monthly intervals throughout one year. Vegetation, ground cover, and chemical and physical soil variables at sampling sites were analyzed concurrently. Ant abundance, species richness, evenness, and diversity indices of Shannon and Simpson were calculated for each site using PC-ORD to demonstrate diversity patterns along the urbanization gradients. Ant assemblages were assessed by detrended corresponding analysis (DCA), canonical correspondence analysis (CCA), and analysis of similarity (ANOSIM) using PC-ORD. Indicator species analysis was conducted to define representative species along the urbanization gradient. A total of 42 ant species were identified. The diversity parameters were consistent across the urbanization gradient. However, significant differences were observed in the ant assemblages between rural and urban, suburban and urban, but only marginal between rural and suburban. Eleven ant species were identified as indicator species (IV values between 50.7-80.7%). The ant assemblages were influenced by flora, ground cover, and soil variables.

Urbanization affects all elements of the pre-urban environment, including soils, hydrology, vegetation, and microclimate. Recently, Saudi Arabia has experienced rapid urbanization and growth. Thus, the country's biodiversity has been threatened. In Riyadh, beetle assemblages were assessed along a rural-suburban-urban gradient. A total of 2,791 individuals from 94 species belonging to seven families were collected at 15 sites along three different gradients of urbanization in Wadi Hanifa. Tenebrionidae dominated abundance (60.1%) and richness (38%). Beetle abundance, evenness, and diversity were not different among habitats; however, species richness was higher in rural habitats. DCA and CCA analyses showed distinct differences among sites along gradients. Urbanization intensity, soil variables, and land cover were significantly correlated with DCA axis 1, while elevation and flora were significantly correlated with DCA axis 2. The most critical operating environmental variables in Wadi Hanifa were buildings, elevation, soil organic carbon, litter cover, and litter depth, as well as plants such as Launaea capitata, Lycium shawii, Alhagi graecorum, and Heliotropium currasavicum. Ten species in our study are associated with urban habitats, six with suburban habitats, and seven with rural habitats. Consequently, expanding urban areas may negatively affect the richness and composition of beetles and may result in the loss of some native species.

Solar radiation prediction is an important process in ensuring optimal exploitation of solar energy power. Numerous models have been applied to this problem, such as numerical weather prediction models and artificial intelligence models. However, well-designed hybridization approaches that combine numerical models with artificial intelligence models to yield a more powerful model can provide a significant improvement in prediction accuracy. In this paper, we propose novel hybrid machine learning approaches that exploit auxiliary numerical data. The proposed hybrid methods invoke different machine learning paradigms, including feature selection, classification, and regression. Additionally, numerical weather prediction (NWP) models are used in the proposed hybrid models. Feature selection is used for feature space dimension reduction to reduce the large number of recorded parameters that affect estimation and prediction processes. The rough set theory is applied for attribute reduction and the dependency degree is used as a fitness function. We investigate the effect of the attribute reduction process with thirty different classification and prediction models in addition to the proposed hybrid model. Then, different machine learning models are constructed based on classification and regression techniques to predict solar radiation. Moreover, other hybrid prediction models are formulated to use the output of the numerical model of Weather Research and Forecasting (WRF) as learning elements in order to improve the prediction accuracy. The proposed methodologies are evaluated using a data set that is collected from different regions in Saudi Arabia.

The design of highly efficient sensitizers is one of the most significant areas in dye-sensitized solar cell (DSSC) research. We have studied a series of benzothiadiazole-based D-π-π-A organic dyes, putting emphasis on the influence of the donor moiety on the DSSC’s efficiency. Using linear response time-dependent density functional theory (TDDFT) with the CAM-B3LYP functional different donor groups were characterized in terms of electronic absorption spectra and key photovoltaic parameters. As a reference a dye has been considered which has a benzothiadiazole fragment linked via thiophene rings to a diphenylamine donor and a cyanoacrylic acid acceptor. The different systems are first studied in terms of individual performance parameters, which are eventually aggregated into the power conversion efficiency. Here only the amino-substituted species shows a modest increase, whereas the dimethylamino case even shows a decrease.

Researches are moving to iron and ammonia elimination from ground water. Here, we are using poly acrylic–poly acrylamide hydrogel which grafted with 3-chloroaniline. This copolymer was synthesized by addition polymerization. Effect of agitation time, dosage and adsorbents temperature on the removal process sensitivity has been investigated. The copolymer was described experientially and theoretically. Isothermal, kinetic adsorption models and were discussed. This hydrogel could be regenerated efficiently (98.3%removal of iron and 100% removal of ammonia). Density functional theory DFT method using B3LYP/6-311G(d,p),LANL2DZ level of the theory were managed to investigate stationary states of grafted co-polymer and the complexation energy of the hydrogel with the studied cations. NBO analysis is using DFT to investigate the negative centers on the hydrogel. The complexation energy showed selectively of hydrogel to studied cations.

In this work, meshless methods are applied for the solution of two-dimensional steady-state heat conduction problems with nonlocal multi-point boundary conditions (NMBC). These meshless procedures are based on multiquadric radial basis function (MQ RBF) and its modified version (i.e. integrated MQ RBF). The proposed meshless methods which were recently published in \cite{Reutskiy2016} is compared with standard collocation method (i.e. Kansa's method). Three different sorts of solution domain are considered in which Dirichlet boundary condition is specified on some part of the boundary and is related to the unknown function values at a discrete set of interior points. The influence of NMBC on the accuracy and condition number of the system matrix associated to the proposed methods is investigated. The sensitivity of the shape parameter is also analyzed in the proposed methods. Performance of the proposed approaches in terms of accuracy and efficiency is confirmed on the benchmark problems.

Background: In spinal cord injury, radical treatment is still a persistent hope for patients and clinicians. Our study aimed to determine the different histological changes in central, cranial and caudal sites of compressed spinal cord as a result of neuroectodermal stem cells (NESCs) transplantation in rats. Material and methods: For extraction of NESCs, future brains were extracted from mice embryos (10-days old) and cultured. Eighty, male rats were divided randomly into control, sham (20 rats each); while 40 rats were subjected to compressed spinal cord injury (CSCI). Seven days after spinal cord injury, rats were subdivided into 2 groups (20 rats each); an untreated and treated with NESCs injected cranial and caudal to the site of the spinal cord injury. Rats were sacrificed 4 weeks after transplantations of NESCs and specimens from the spinal cord at the central, cranial and caudal to site of spinal cord injury were proceeded to be stained with haematoxylin & eosin, osmic acid and Immunohistochemistry of glial fibrillary acidic protein (GFAP). Results: Sections of CSCI revealed areas of hemorrhages, necrosis and cavitation limited by reactive astrocytosis, with upregulation of GFAP expression. Evidence of remyelination and mitigation of histopathological features, reactive astrocytosis in CSCI sections were more pronounced in cranial than in caudal region. Conclusions: NESCs transplantation ameliorated the pathological changes, promoted remyelination.

In the present study, fish were exposed to sub-lethal doses of CuONPs (68.92 ± 3.49 nm) (10, 20, and 50 mg/L) for a long exposure period (25 days). Compared to the control group (0.0 mg/L CuONPs), a significant dose-dependent elevation in blood urea and creatinine values, serum alanine transaminase, aspartate transaminase, and alkaline phosphatase enzyme activities were evident in CuONPs-exposed groups (P < 0.05). Fish exposure to 50 mg/L CuONPs significantly upregulated the transcription of pro-inflammatory cytokines (tumor necrosis factor-alpha, interleukin-1beta, interleukin 12, and interleukin 8), heat shock protein 70, apoptosis-related gene (caspase 3), and oxidative stress-related (superoxide dismutase, catalase, and glutathione peroxidase) genes in liver and gills of the exposed fish in comparison with those in the control group (P < 0.05). Moreover, varying histopathological injuries were noticed in the hepatopancreatic tissues, posterior kidneys, and gills of fish groups correlated to the examined exposure dose of CuONPs. In summary, our results provide new insights and helpful information for better understanding the mechanisms of CuONPs toxicity in Nile tilapia at hematological, molecular levels, and tissue levels.

In this study, a novel porous geopolymer mortar (GP) was produced and tested experimentally. Industrial waste materials/by-products were used as constituents of the GP, along with dune sand. One sample was produced as a control sample for benchmarking. For the rest of the samples, 15%, 30%, and 45% by volume, the solid constituents were replaced with expanded polystyrene foam (EPS) beads. These mortar samples were heat cured to depolymerize the EPS to cause porosity inside the samples. Indoor experiments were conducted to evaluate the response of produced porous GP to high heat flux. The porous samples were able to reduce heat transmission across the opposite surfaces. Induced porosity resulted in a decrement in compressive strength from 77.2 MPa for the control sample to 15.8 MPa for 45% porous sample. However, the limit lies within the standards for partitioning walls in buildings and pavements in urban areas to absorb rainwater.

Mycotoxins are produced by more than one hundred fungi and produce secondary metabolites that contaminate various agricultural commodities, especially rice and corn. Their presence in the food chain is considered a serious problem worldwide. In recent years, a link between exposure to mycotoxins and impaired fertility has been suggested. Consequently, it has become vital to investigate the interactive effects of these mycotoxins on ovarian function. In this study, we investigated the intergenerational effects of mycotoxin fumonisin B1 (FB1) on ovarian structure and function. Virgin Wistar albino female rats were separated into control and FB1 treatment groups and examined from day 6 of pregnancy until delivery (20 and 50 mg/kg/day). The obtained females of the first (F1) and second generations (F2) were euthanized at 4 weeks of age, and ovary samples were collected. We found that the ovary weight index increased with the high dose of treatment (50 mg/kg/day) among both F1 and F2, similar to that observed in polycystic ovary syndrome. As expected, FB1 at a high dose (50 mg/kg) reduced the number of primordial follicles in F1 and F2, leading to an accelerated age-related decline in reproductive capacity. Moreover, it reduced the fertility rate among F1 females by affecting follicle growth and development, as the number of secondary and tertiary follicles was decreased. Histopathological changes were evidenced by the altered structures of most of the growing follicle oocytes, as revealed by a thinning irregular zona pellucida and pyknosis in granulosa cells. These findings are concomitant with steroidogenesis- and folliculogenesis-related gene expression, as evidenced by the decrease in CYP19 activity and estrogen receptor beta (ESR2) gene expression. Additionally, GDF-9 mRNA levels significantly decreased, and IGF-1 mRNA levels significantly increased. However, the results from the ovaries of the F2 treatment groups were different and unexpected. While there was no significant variation in CYP19 compared to the control, ESR2 significantly increased, leading to stereological and histopathological changes similar to those of the control, except for some altered follicles. The hallmark histological feature was the appearance of vacuolar structures within the oocyte and between granulosa cell layers. Interestingly, the autophagic marker LC3 significantly increased in F2 offspring, whereas this protein significantly decreased in F1 offspring. Therefore, we suggest that the promotion of autophagy among the ovaries of F2 offspring may be considered a recovery mechanism from the effect of prenatal FB1 exposure. Thus, autophagy corrected the effect of FB1 during the early life of F1 females, leading to F2 offspring with ovarian structure and function similar to those of the control. However, the offspring treated females may have early ovarian aging because their ovarian pool was affected.

Abstract: Polylactic acid (PLA) is brittle in nature with extensive deformation property. For improvement of the end-use quality, it is of significant importance to enhance the producibility of fused deposition modeling (FDM)-printed objects in PLA. The purpose of this investigation is to boost toughness and to reduce the production cost of the FDM-printed tensile test samples with the desired part thickness. To attain the research purpose number of experiments are designed and analyzed by the Response Surface Method (RSM). The statistical analysis is performed to deal with this concern considering layer thickness, infill percentage, and extruder temperature as controlled factors. The tensile test specimens are printed based on the designed experiments, and the tensile strength tests are conducted by SANTAM 150 universal testing machine based on ASTM D638. The honeycomb internal fill pattern is applied for the production of light-weight and high-strength specimens. The area under Force- Extension curve up to fracture is acquired as the toughness of the printed specimens. This study also developed a modeling process using ANN and ANN-GA techniques for developing an accurate estimation for toughness, part thickness, and production cost as dependant variables. Results were evaluated by correlation coefficient and RMSE values. According to the modeling results, ANN-GA as a hybrid ML technique could successfully improve the accuracy of modeling about 7.5, 11.5 and 4.5 % for toughness, part thickness, and production cost, respectively, in comparison with those for the single ANN method. In the other side, the optimization results confirm that the optimized specimen is cost-effective and able to comparatively undergo deformation, which develops the usability of printed PLA objects. The research is accomplished under the constraints of PLA compatibility with existing fused deposition modeling setup without changing the functional hardware/software of the machine. Although the mechanical properties and dimensional accuracy of PLA have already been studied, there is little literature on the toughness of the printed PLA with honeycomb internal fill pattern.

In the context of healthcare technology management (HTM) in Saudi Arabia and the Gulf region, this study addresses a significant gap by exploring both external and internal risk factors affecting HTM performance. Previous research has primarily focused on modeling or predicting failures in medical devices, mostly examining internal (endogenous) factors that impact device performance and the development of optimal service strategies. However, a comprehensive investigation of external (exogenous) factors has been notably absent. This research introduces a novel hierarchical risk management framework, designed to accommodate the broad array of healthcare technologies, not limited to medical devices. It significantly advances the field by thoroughly investigating and validating a comprehensive set of 53 risk factors and assessing their influence on HTM. Additionally, this study embraces the perspective of enterprise risk management (ERM) and expands it to identify and incorporate a wider range of risk factors, offering a more holistic and strategic approach to risk assessment in healthcare technology management. The findings reveal that several external and internal factors previously underexplored significantly impact HTM performance. Notably, the Fuzzy AHP survey identified “design risk” under facility and environmental risks as the highest risk for HTM in the region. Furthermore, the study reveals that three out of the top ten risks are related to “facility and internal environmental” factors, six are related to technological endogenous factors, and only one is related to managerial factors. This distribution underscores the critical areas for intervention and the need for robust facility and technology management strategies. In conclusion, this research not only fills a critical void by providing a robust framework for healthcare technology risk assessment but also broadens the scope of risk analysis to include a wider array of technologies, thereby enhancing the efficacy and safety of healthcare interventions in the region. Additionally, the proposed hierarchy provides insights into the underlying risk factors for healthcare technology management, with potential applications extending beyond the regional context to a global scale. Moreover, the equation we propose offers a novel perspective on the key risk factors involved in healthcare technology management, presenting insights with far-reaching implications applicable not only regionally but also on a global level. This framework also supports sustainability goals by encouraging the efficient and responsible utilization and management of healthcare technologies, essential for ensuring the long-term economic and environmental sustainability of medical technology use.

The prolonged exposure to nicotine and the development of nicotine dependence have significant implications for cancer risk. Tobacco use, driven by nicotine addiction, is a major contributing factor to the development of various types of cancer. Smoking tobacco, in particular, has been strongly associated with an increased risk of lung cancer, as well as other malignancies. The harmful chemicals present in tobacco products, including carcinogens, can cause DNA damage and promote the initiation and progression of cancerous cells. This article presents a comprehensive literature review on the neurobiology of nicotine dependence and its implications for tobacco use treatment. Nicotine dependence is a complex phenomenon involving various neurobiological mechanisms. When nicotine enters the body, it binds to nicotinic acetylcholine receptors in the brain's reward circuitry, triggering the release of neurotransmitters like dopamine, serotonin, and norepinephrine. Over time, repeated nicotine exposure leads to neuroadaptive changes in the brain, resulting in increased motivation to seek and use the drug. Understanding the neurobiology of nicotine dependence is crucial for developing effective treatment strategies. Pharmacological interventions, such as nicotine replacement therapy and medications like bupropion and varenicline, can help individuals manage cravings and withdrawal symptoms. Additionally, behavioral therapies and counseling play a vital role in enhancing self-efficacy and providing support for smoking cessation efforts. By reviewing the existing literature, this article sheds light on the intricate neural pathways and processes involved in nicotine addiction. It emphasizes the importance of a multidimensional approach that combines pharmacological treatments and behavioral interventions to address the physiological and psychological aspects of nicotine dependence. This knowledge can inform the development of more targeted and personalized treatment approaches to help individuals overcome tobacco addiction and improve their chances of successful smoking cessation.

We report the isolation of two novel degrading bacterial strains active against the potential environmental pollutant acetamino-phen/paracetamol. Streptomyces Chrestomyceticus (RS2) and Streptomyces Flavofuscus (M33) collected from El-Natrun Valley, Egypt, water, sediment, and sand samples were taxonomically characterized via conidiophores morphologic characterization under Trans-mission Electron Microscope (TEM). Genotypic identification, done based on their 16S rRNA gene sequence analysis followed by BLAST alignment and deposited on the NCBI as 2 novel strains. The phylogenetic tree was constructed using an appropriate software. Acetaminophen degradation-products chemical structure was identified by GC/LC MS. The biological antimicrobial activity of some selected acetaminophen degradation-products extracts and derived compounds was examined against panel of test micro-organisms and found to be have high anti-microbial effect. In addition, in silico cheminformatics Swiss ADMET evaluation of these selected deg-radation extract for gastric absorption, distribution, hepatic metabolism, renal excretion as well as distribution to CNS and finally not mutagenic/teratogenic or genotoxic virtually. In vitro cytotoxic activity of these selected bio-degradation products was performed against HepG2 and MCF7 cancer cell lines, revealing that M33 and RS2 extract effect on acetaminophen/paracetamol bio-degradation products are potentially safe with higher IC50 on HepG2 and MCF7, in comparison to acetaminophen/paracetamol with IC50 of 108.5 μg/ml. Moreover, the in vivo acute oral single dose toxicity experiment was conducted, being compared with acetamino-phen/paracetamol to confirm that the bio-degradation products have lower toxicity than acetaminophen in vivo and in silico.

Mining can impact the environment, biodiversity and human health through direct and indirect practices. This study investigated the effects of gold mining on Gerbillus nanus, pointing to organ dysfunction and redox imbalance. Soil samples, Lycium shawii and G. nanus were collected from a site near a mining planet and a control site. Soil and L. shawii samples from the mining site showed a significant increase cadmium (Cd), cupper (Cu), mercury (Hg), arsenic (As), zinc (Zn), lead (Pb) and vanadium (V). Hepatic, renal and pulmonary Cd, Pb, Hg, Zn, Cu, Fe, As and V concentrations were increased significantly in G. nanus at the mining site. Markers of liver and kidney function were elevated in serum, and several histological manifestations were demonstrated in liver, kidney and lung of G. nanus at the mining site. Malondialdehyde and nitric oxide were increased, and glutathione and antioxidant enzyme were declined in the liver and kidney of G. nanus. In conclusion, mining practices triggered tissue damage and oxidative stress in G. nanus living close to the mining site. These findings can represent the scientific basis for evaluating the environmental and health impact of mining in the on the nearby communities.

Natural product especially secondary metabolites that produced by plants under the stressed condition shown to have a different pharmacological impact. Aeluropus lagopoides is one of the typical halophyte plants survivals under stressed conditions. It has been used for wound healing and as a painkiller. The bioactivity and the chemical composition of this plant have poorly investigated. Consequently, chemical components of A. lagopoides leaves were extracted using hexane (nonpolar), ethyl acetate (semi-polar), n-butanol (polar) to extract the most extensive variety of metabolites. The cytotoxicity and anticancer impact of extracted secondary metabolites evaluated against breast (MCF-7), colon (HCT-116), and liver (HepG2) cancer cell lines using SRB test. The mechanism of action verified by observing the appearance of apoptotic bodies using the fluorescent microscope while their antiproliferative impact had been evaluated using flow cytometer. Results revealed that secondary metabolites extracted using hexane and ethyl acetate were having the highest cytotoxicity and thus anticancer activity effect on HepG2 with IC₅₀ (24.29 ± 0.85, 11.22 ± 0.679 µg/mL) respectively. Where apoptotic bodies observed, flow cytometer results exhibited that secondary metabolites can inhibit cell cycle in G0/G1 phase. Accordingly, A. lagopoides hexane and ethyl acetate extracts may consider as a candidate anti-cancer drug.

Two experiments were conducted to develop a Nano green manganese and assess its effect on grapevines. The first experiment was microbiological, where several incorporation strategies were utilized to enrich the yeast with manganese, as follows: (1) adding manganese to the liquid medium (growth phase), (2) adding after 24 h of incubation (non-growth phase). As the results, growth phase reduced the possibility of medium contamination. Manganese concentration in the yeast cells was increased as that of manganese sulphate in the medium. Manganese incorporation in yeast cells was 99.93% higher than that of the medium at 0.0195 g/l of manganese. Although the concentration of manganese in the medium raised the OD of yeast cell biomass, manganese sulphate had no passive influence on it. The second experiment was horticultural, done on Flame Seedless grapevines, since both active fresh and frozen yeast enriched with manganese resulted from the first experiment were sprayed twice a year at 10 or 20 cm3/l comparing with manganese sulphate, and manganese chelate. The results demonstrated that yeast extracts in both forms increased the yield and improved fruit properties. The most effective treatment on vegetative growth, yield and fruit properties was the frozen yeast enriched with manganese at 20 cm3/l.

Background: Acute heart failure (AHF) is a serious medical problem that necessitates hospitalisation and often results in death. Patients hospitalised to the emergency department (ED) should therefore receive an immediate diagnosis and treatment. Unfortunately, there is not yet a fast and accurate laboratory test for identifying AHF. The purpose of this research is to apply the principles of explainable artificial intelligence (XAI) to the analysis of hematological predictors for AHF. Methods: In this retrospective analysis, 425 patients with AHF and 430 healthy individuals served as assessments. Patients' demographic and hematological information was analyzed to determine AHF. Important risk variables for AHF diagnosis were identified using LASSO feature selection. To test the efficacy of the suggested prediction model (XGBoost), a 10-fold cross-validation procedure was implemented. The area under the receiver operating characteristic curve (AUC), F1 score, Brier score, and Positive Predictive Value (PPV) and Negative Predictive Value (NPV) were all computed to evaluate the model's efficacy. Permutation-based analysis and SHAP, were used to assess the importance and influence of the model's incorporated risk factors. Results: White blood cell (WBC), monocytes, neutrophils, neutrophil-lymphocyte ratio (NLR), red cell distribution width-standard deviation (RDW-SD), RDW-coefficient of variation (RDW-CV), and platelet distribution width (PDW) values were significantly higher than the healthy group (p<0.05). On the other hand, erythrocyte, hemoglobin, basophil, lymphocyte, mean platelet volume (MPV), platelet, hematocrit, mean erythrocyte hemoglobin (MCH) and procalcitonin (PCT) values were found to be significantly lower in AHF patients compared to healthy controls (p <0.05). When XGBoost was used in conjunction with LASSO to estimate AHF, the resulting model had an AUC of 87.9%, an F1 score of 87.4%, a Brier score of 0.036, and an F1 score of 87.4%. PDW, age, RDW-SD, and PLT were identified as the most crucial risk factors in differentiating AHF. Conclusions: The XGBoost model demonstrated exceptional performance in accurately estimating Acute Heart Failure, and the application of Explainable Artificial Intelligence effectively provided intuitive explanations for the model's estimations. The suggested interpretable model holds potential for the identification of patients at high risk, thereby facilitating the optimization of treatment and planning for follow-up in cases of AHF.

This study aims to explore the E-marketing orientations and relationship management constructs in Jordanian startup enterprises to examine their influence on brand visibility and loyalty in the context of the digital market . The sample consists of 161 managers in startup companies, and structural equation modeling is used to study the relationships between the constructs of e-marketing orientation, capabilities, E-relationship management, brand visibility, and loyalty. The results illustrate that the realization of e-marketing orientation is directly achieved by capabilities and visibility, thereby stressing the importance of a formulated digital market approach and that the realization of effective e-relationship management directly expression by e-marketing capabilities, demonstrating the significance of the digital market concept’s approach. The results further demonstrate that e-marketing capabilities and visibility serve as mediators between the realization of e-marketing orientations and loyalty, Two explanations may be drawn, one from the R resource-Based View theory, and another derived from R elationship M arketing T heory Thus, the study has theoretical implications in terms of R esource-Based V iew and R elationship M arketing T heory. The study offers essential managerial insights for practitioners into the entrepreneurship domain concerned with the necessity of e-marketing capabilities and E-RM attitudes at a customer-centered approach and the strategic application of digital channels to enhance visibility in the intense competition context. Therefore, the empirical results have contributions as essential insights for both stakeholders and account for practical, theoretical, and managerial perspectives in the entrepreneurship domain.

Plants especially in their natural habitat are considered part of a rich ecosystem that includes many various microorganisms in the soil. The current study aimed to identify the bacterial profile of agriculture-related soil samples using the metabarcoding technique to compare and explore relevant rhizosphere bacteria associated with plant cultivations in newly reclaimed land and habitual cultivated ones. Total environmental DNA was extracted from rhizosphere and non-cultivated samples derived from three land types in Egypt. The bacterial 16S rDNA was amplified and sequenced by NGS technology to profile each sample. The microbial profile was characterized by statistical and literature-based methods. Among all samples, the most identified phyla were Actinobacteriota (28%), followed by Proteobacteriota (26%), Firmicutes (14%), Ac-idobacteriota and Chloroflexi (7%), Gemmatimonadota (5%), Bacteriodota and Crenarchaeota (3%), and Myxococcota (2%), in addition to 37 other phyla with <1% counts. A total of 74 OTU was unique to the plant rhizosphere area and classified as Bacteriodota (5.1%:0.3%), Firmicutes (2.4%:0.1%), and Proteobacteria (3.5%:2%) phyla in agriculture and reclaimed lands, respectively. Moreover, the rhizosphere profile included a large portion of uncultured and unidentified bac-terial species, which opened a window to further analysis. Our analysis provides a key Knowledge about the rhizosphere microbiome and highlights its possible use to create microbial-based bi-ofertilizers targeting plant performance in contrast to traditional fertilizers and their side effect on the agriculture sector.

Water microbial contamination is a serious issue that poses a risk to both animal and human health. 120 water samples collected from main water source and drinkers from a poultry farm. Different bacterial pathogens were isolated from water sources. Escherichia (E.) coli, Pseudomonas (P.) aureoginosa, (Salmonella) S. Typhimurim, Aeromonas (A.) hydrophila at different percentages. Variable degree of bacterial resistance to some commercial disinfectants commonly used to disinfect water system (iodine, terminator and H2O2). Nanoparticles were used to control bacteria in water. About the safety investigation for the prepared nanomaterials, the work results demonstrated that zinc oxide (ZnO) nanoparticles (NPs) exhibit the highest safety profile among the manufactured materials. The median fatal dose (LD50) for ZnO NPs was determined to be 3709 mg/kg body weight. In comparison, the LD50 values for zeolites and nanocomposites were 3251 mg/kg and 2658 mg/kg, respectively. Therapeutic dosages were estimated based on the LD50. Zeolite NPs, ZnO NPs and ZnO/zeolite NPs showing promising results in control of those bacteria. It was concluded that the escalating resistance of bacteria to disinfectants have led to a need to find alternative such as nanoparticles that proved promising results in control of pathogens, particularly it showed a safe effect on laboratory animals.

Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex and debilitating disease with a significant global prevalence of over 65 million individuals. It affects various systems, including the immune, neurological, gastrointestinal, and circulatory systems. Studies have shown abnormalities in immune cell types, increased inflammatory cytokines, and brain abnormalities. Further research is needed to identify consistent biomarkers and develop targeted therapies. A multidisciplinary approach is essential for diagnosing, treating, and managing this complex disease. The current study aims at employing explainable artificial intelligence (XAI) and machine learning (ML) techniques to identify discriminative metabolites for ME/CFS. Material and Methods: The present study used a metabolomics dataset of CFS patients and healthy controls, including 26 healthy controls and 26 ME/CFS patients aged 22-72. The dataset encapsulated 768 metabolites, classified into nine metabolic super-pathways: amino acids, carbohydrates, cofactors, vitamins, energy, lipids, nucleotides, peptides, and xenobiotics. Random forest-based feature selection and Bayesian Approach based-hyperparameter optimization were implemented on the target data. Four different ML algorithms [Gaussian Naive Bayes (GNB), Gradient Boosting Classifier (GBC), Logistic regression (LR) and Random Forest Classifier (RFC)] were used to classify individuals as ME/CFS patients and healthy individuals. XAI approaches were applied to clinically explain the prediction decisions of the optimum model. Performance evaluation was performed using the indices of accuracy, precision, recall, F1 score, Brier score, and AUC. Results: The metabolomics of C-glycosyltryptophan, oleoylcholine, cortisone, and 3-hydroxydecanoate were determined to be crucial for ME/CFS diagnosis. The RFC learning model outperformed GNB, GBC, and LR in ME/CFS prediction using the 1000 iteration bootstrapping method, achieving 98% accuracy, precision, recall, F1 score, 0.01 Brier score, and 99% AUC. Conclusion: RFC model proposed in this study correctly classified and evaluated ME/CFS patients through the selected biomarker candidate metabolites. The methodology combining ML and XAI can provide a clear interpretation of risk estimation for ME/CFS, helping physicians intuitively understand the impact of key metabolomics features in the model.

This research aims to explore the complex interplay between supply chain resilience (SCR), digital supply chain (DSC), and sustainability, focusing on the moderating influence of supply chain dynamism. The goal is to understand how these elements interact within the framework of contemporary supply chain management and how they collectively contribute to enhancing sustainability outcomes. The sample size is 300 CEOs and managers. The study approach integrates quantitative research methods. Structural equation modeling (SEM) is utilized to quantitatively analyze the direct and indirect effects of SCR and DSC on sustainability. The numerous surveys we conduct among supply chain ecosystem stakeholders provide a rich picture of practical implications and contextual nuances. In sum, our early findings generally support a positive relationship between SCR and sustainability in and of itself decrying the need for more resilient supply networks for sustainability. We further find the beneficial impact of digital technologies in promoting sustainability via enhancing environmental control and controlling for efficiency in supply chains. We also offer evidence to show that supply chain dynamism compounds the positive logic between SCR and DSC and sustainability. As a final word, it must be noted that our work speaks to the burgeoning Supply Chain Dynamism as moderator literature by examining the direct and contingent effects of SCR and DSC on not only performance but sustainability. By shedding light on the moderating role of dynamism, the study provides fresh insights into the multifaceted nature of supply chain management and sustainability practices. The study's findings enhance theoretical understanding by elucidating the synergistic effects of SCR, DSC, and sustainability in dynamic supply chain settings. It augments existing theoretical frameworks by integrating concepts of resilience, digitalization, and sustainability into a comprehensive model. Practical and economical, the research offers actionable guidance for organizations aiming to improve sustainability performance through resilient and digitally advanced supply chains. By acknowledging the role of supply chain dynamism, managers can tailor strategies to manage disruptions effectively and leverage digital innovations. Economically, adopting sustainable practices can result in cost savings and competitive advantages. The research emphasizes the importance of aligning supply chain strategies with sustainability goals to drive long-term value and societal impact.

This paper presents preliminary operational performance results of a pilot grid-connected photovoltaic (PV) system designed and installed on the rooftop of the Ministry of Petroleum, Energy and Mining headquarter in Nouakchott (latitude of 18.1°N and the longitude of 16.0°W), Mauritania. The aim is for the government to demonstrate the relevance of using solar energy and to encourage the uptake of solar PV technology for commercial and residential building applications in Mauritania.. In this study, the grid-connected PV system has a peak power of 48 kW and the performance monitoring was carried out during one year, with a system that allow to measure DC power, inverter and system conversion efficiency, energy generated by the PV arrays, solar radiation in the inclination plane of panels, ambient temperature and module temperature. During this period, the PV plant was found to supply 65,668 kWh to the grid. The final yield ranged from 3.91 to 5.09 kWh/kWp/day. The performance ratio was found to vary from 69.69% to 89.35% and the annual capacity factor was found to be 19%. Finally, performance parameters were compared with other PV plants installed in the same region of Northern Africa. The outcome of this work is deemed important in assisting accurate PV system design and decision-making.

The solid-state technique was utilized to make a single phase of delafossite CuAlO2, along with 1%, 2%, 3% and 4% silver doped CuAlO2 samples in this study. The content of the samples was investigated using energy dispersive X-ray spectroscopy (EDS) equipped with a field emission scanning electron microscope (FE-SEM). The polycrystalline nature of all of the analyzed cases was confirmed by structural analyses utilizing an X-ray diffraction (XRD) pattern with a simple typical peak of CAO rhombohedral phase. Raman, FT-IR and UV–Vis spectroscopy were used to study the structural, and optical energy band gap (Eg) of Ag doped CuAlO2 nanoparticles. The Kubelka–Munk function was used to calculate the optical band gap of ACAO alloys using diffuse reflectance spectra, and it altered as the Ag ion concentration increased. A. c. impedance spectroscopy was used to investigate the dielectric characteristics of Ag doped CuAlO2 nanoparticles.

Kinesio tape is considered one of the most common techniques which using recently, where it is used as a therapeutic technique for pain relief, correction of joint position, prevention of oedema and injuries, improve range of motion and muscular activity for the individual. This study is a descriptive research design and aims to identify the effect of using Kinesio tape on the neuromuscular activity of quadriceps muscle after the rehabilitation program of the knee joint. The study sample consists of (10) players from different sports (football, basketball …etc.) and suffering from knee joint injuries. This sample was taken from Kafr-El sheikh and Kaleen club. Results showed that Kinesio tape doesn’t have any explicit effect on the neuromuscular activity of muscle but acts as a catalyst for muscle and promote a person’s feeling of psychological wellbeing and reassurance.When comparing results of using Kinesio tape during performing leg squatting and balance test with not using tape, founded that when performing leg squatting and balance test with using Kinesio tape, there were significant effects on muscle activity compared to not using it.

Background: As the impacts of diabetes-induced reproductive damage are now evident in young people, we are now in an urgent need to devise new ways to protect and enhance the reproductive health of diabetic people. The purpose of this study was to assess the protective impact of enalapril (an ACE inhibitor) and paricalcitol (a vitamin D analogue) alone and in combination, on streptozotocin (STZ) diabetes-induced testicular dysfunction in rats. Material and methods: This study was carried on 50 male Sprague-Dawley rats; 10 normal rats were allocated as non-diabetic control group. 40 rats developed diabetes after receiving a single dose of STZ, then the diabetic rats were divided into four groups of equivalent number assigned as diabetic control, enalapril treated, paricalcitol treated, in addition to combined enalapril and paricalcitol treated groups. The effects of mono and combined therapy with paricalcitol and enalapril on testicular functions, sperm activity, glycemic state oxidative stress and inflammatory parameters as well as histopathological examination were assessed when compared to the normal and diabetic control rats. Results: As a result of diabetes induction, epididymal sperm count, sperm motility, serum levels of testosterone, follicle stimulating hormone (FSH) as well as luteinizing hormone (LH) and the antioxidant enzyme activities were significantly decreased, while abnormal sperm (%), insulin resistance, nitric oxide (NO), malondialdehyde (MDA), interleukin-6 (IL-6) as well as tumor necrosis factor-α (TNF-α) were significantly increased, along with sever distortion of testicular structure. Interestingly, treatment with paricalcitol and enalapril either alone or in combination significantly improved the sperm parameters, increased antioxidant enzyme activities in addition to serum levels of testosterone, FSH and LH, reduced insulin resistance, IL-6 and TNF-α levels and finally ameliorated the diabetes-induced testicular oxidative stress and histopathological damage with somewhat superior effect for paricalcitol monotherapy and combined therapy with both drugs than monotherapy with enalapril alone. Conclusion: Monotherapy with paricalcitol and its combination therapy with enalapril has a somewhat superior effect in improving the diabetes-induced testicular dysfunction (most probably as a result of their hypoglycemic, antioxidant, anti-inflammatory and anti-apoptotic properties), than monotherapy with enalapril alone in male rats, recommending a synergistic impact of both drugs.

Background: Antibiotic resistance is an urgent issue everywhere in the globe. It is necessary to look into new sources of antibiotics to address this issue. Aim of the study: studying the purification of Corallopyronin B from various soil conditions in Egypt, as well as the antibacterial effectiveness of Corallopyronin B in preclinical animal testing and randomized human clinical trials phases 1/2. Type of the study: Screening experimental study. Methodology: Several soil conditions in Egypt were examined to create bacterial isolates that generated the antibiotic chemical Corallopyronin B. Using reversed-phase HPLC, Myxopyronin B was purified. The test antibiotic's minimum inhibitory concentration( MIC) and in vitro antibacterial activity were ascertained using the paper disc diffusion assay and the broth microdilution technique. Furthermore, in stages 1/2 of randomized clinical trials including human and animal models, pharmacokinetics, adverse drug reactions, and the in vivo antibacterial spectrum were discovered. Results: The soil bacterial isolate Corallococcus coralloides DSM 2259, which was grown on a Casein yeast peptone( CYP) plate, produced Corallopyronin B from its culture supernatant. At MICs more than 100 mcg/ml, the test antibiotic inhibited the growth of many Gram -ve bacteria, including Escherichia coli, while also preventing the growth of numerous Gram +ve bacteria, with MICs ranging from 1 to 10 mcg/ml. Eukaryotic cells, on the other hand, including those in humans and fungi, were unharmed. The test antibiotic was shown to have a bactericidal effect by inhibiting bacterial DNA-dependent RNA polymerase( RNLP). In phases 1/2 of randomized human clinical trials, when 600 mg of the dose per 70 kg of body weight was administered SC, the Cmax was 8.6 mcg/ml at Tmax 1 hour; T1/2 reached 136 min following first-order kinetics of elimination. It stopped acting around 6-7 hours after SC was administered. In the preclinical and randomized human clinical trial phases 1/2, less than 6 percent of experimental candidates had uncommon toxicity, which showed up as reduced bile flow. Protein binding with plasma albumin was detected which reached about 83%. Conclusion: The current work was noteworthy since it involved the production of the bactericidal antibiotic Corallopyronin B from Corallococcus coralloides DSM 2259 which was isolated from several soil environments in Egypt.

Background: Bacterial resistance to several antibiotic classes is seen as a grave threat worldwide. Bacterial resistance to antibiotics was mostly caused by the abuse and overuse of antibiotics, particularly penicillins and first-generation cephalosporins, in Egypt's primary healthcare facilities. Aim of the study: To investigate the main resistant bacteria to a few chosen penicillins and first-generation cephalosporins, as well as the characterization of these antibiotics' resistant genes and their detrimental effects in Egypt's main medical facilities. Methodology: Two hundred respiratory and urinary tract infection (RTI and UTI) specimens were gathered from Egyptian primary medical center patients. The turbidimetric assay at 630 nm wavelength, the broth dilution technique, and the nanopore sequencing homology approach were used to characterize the major resistant pathogenic bacteria and their resistant genes to cefadroxil (first generation cephalosporins) and nafcillin (antipseudomonal penicillin). Moreover, adverse outcomes resulting from antibiotic resistance were noted. Results: Out of 200 specimens with RTI and UTI, 186 samples showed the proliferation of resistant bacteria isolates. Enterococcus faecium strain NFC and Staphylococcus aureus strain CDX were among them. Nanopore sequencing confirmed that the antibiotic-resistant gene in Enterococcus faecium was the NFC gene, whereas the antibiotic-resistant gene in Staphylococcus aureus was the CDX gene. Penicillin-binding proteins with modest affinity were encoded by both genes. These bacterial resistance patterns were linked to a low death rate of 5% and a high morbidity rate of 47%. Conclusion: By expressing low-affinity penicillin-binding proteins through resistant NFC and CDX genes, Enterococcus faecium strain NFC and Staphylococcus aureus strain CDX were found to be the predominant bacterial isolates that cause antibiotic resistance to first-generation cephalosporins and penicillins.

Background: Across the world, antibiotic resistance is a critical challenge. To address such a problem, it has to be done to investigate new antibiotic sources. Aim of the study: Study of the antibacterial activity of Corallopyronin A in preclinical animal testing and randomized human clinical trials stages 1/2, as well as investigating the purification of Corallopyronin A from different soil conditions in Egypt. Type of the study: Screening experimental study. Methodology: Egypt's various soil conditions were tested to develop bacterial isolates that produced the antibiotic compound Corallopyronin A. Reversed phase HPLC was used to purify Myxopyronin A. The broth microdilution method and the paper disc diffusion assay determined the test antibiotic's minimum inhibitory concentration( MIC) and in vitro antibacterial activity. Moreover, in vivo antibacterial spectrum, adverse medication responses, and pharmacokinetics were found in phases 1/2 of randomized clinical studies involving humans and animal models. Results: Corallopyronin A was generated from the culture supernatant of the soil bacterial isolate Corallococcus coralloides M2, cultivated on a Casein yeast peptone( CYP) plate. The test antibiotic prevented the growth of several Gram-ve bacteria, including Escherichia coli, at MICs higher than 100 mcg/ ml; while blocking the development of many Gram +ve bacteria, with MICs ranging from 3 to 15 mcg/ ml. However, eukaryotic cells—such as those found in fungi and humans—were unaffected. A bactericidal consequence of the test antibiotic was detected in the inhibition of prokaryotic DNA-dependent RNA polymerase( RNLP). Conclusion: The synthesis of the bactericidal antibiotic Corallopyronin A from Corallococcus coralloides M2 isolated from different soil settings in Egypt intrigued the current investigation.

Background: Antibiotic resistance is an overwhelming serious difficulty globally. This necessitates the exploration of novel sources of antibiotics to overcome this challenge. Aim of the study: Bacterial Myxopyronin A production from various soil environments Egypt; as well as testing its antimicrobial activity in preclinical animal testing and randomized human clinical trials phases 1/2. Type of the study: Screening experimental study. Methodology: Different soil environments in Egypt were screened for the growth of bacterial isolates producing Myxopyronin A as an antimicrobial agent. Purification of Myxopyronin A was performed via reversed-phase HPLC. Paper disc diffusion assay, as well as the Broth dilution technique, were exploited to assess the invitro antimicrobial and minimum inhibitory concentration( MIC) of the test antibiotic. Furthermore, in vivo antimicrobial spectrum, adverse drug reactions, and pharmacokinetics were detected during animal model testing stages and human randomized clinical trials phases 1/2. Results: From the culture supernatant of the Myxobacterium Myxococcus fulvus 124B02 which was the predominant soil bacterial isolate grown on the Casein yeast peptone plate, Myxopyronin A was produced. The test antibiotic blocked the growth of many Gram +ve bacteria with MICs less than 100 mcg/ ml. In contrast, it inhibited the growth of a few Gram -ve bacteria such as Escherichia coli at MICs greater than 100 mcg/ ml. On the other hand, Eukaryotic cells such as fungal and human cells were not affected. Prokaryotic DNA-dependant-RNA polymerase( RNLP) was noticed to be inhibited via the test antibiotic suggesting its bactericidal action. The maximum concentration was 7-8 mcg/ ml at a maximum time of 2 hours when 600 mg dose was orally administered in randomized human clinical trials phases 1/2, and T1/2 reached 2.5 hours following first-order kinetics of elimination. The duration of its action was nearly 12 hours after oral administration. Rare toxicity was detected during preclinical and randomized human clinical trials phases 1/2 in the form of mild diarrhea and cholestatic jaundice in less than 5 % of experimental candidates. Conclusion: The present study was promising due to the bactericidal antibiotic Myxopyronin A production from Myxococcus fulvus 124B02 isolated from different soil environments in Egypt.

In the present paper, the effect of the non-linear thermal radiation on the neutral gas mixture in the unsteady state is investigated for the first time. The unsteady BGK technique of the Boltzmann kinetic equations for a neutral non-homogenous gas is solved. The solution of the unsteady case makes the problem more general significance than the stationary one. For this purpose, the moments' method, together with the traveling wave method, is applied. The temperature and concentration are calculated for each gas component and mixture for the first time.Furthermore, the study is held for aboard range of temperatures ratio parameter and a wide range of the molar fraction. The distribution functions are calculated for each gas component and the gas mixture. The significant non-equilibrium irreversible thermodynamic characteristics the entire system is acquired analytically. That technic allows us to investigate the consistency of Boltzmann's H-theorem, Le Chatelier principle, and thermodynamics laws. Moreover, the ratios among the different participation of the internal energy alteration are evaluated via the Gibbs formula of total energy. The final results are utilized to the argon-helium non-homogenous gas at different magnitudes of radiation force strength and molar fraction parameters. 3D-graphics are presented to predict the behavior of the calculated variables, and the obtained results are theoretically discussed.

Introduction: The attitudes of doctors and nurses toward patient safety is a significant factor in hospital safety climates and medical error rates. Yet, there are very few studies of patient safety attitudes in Saudi hospitals and none conducted in hospital emergency departments. Aims: The current study aims to investigate the discrepancy between the patient safety attitudes of doctors and nurses in a Saudi hospital emergency department. Materials and Method: The study employed a qualitative research designvia semi-structured interviews with Saudi and non-Saudi doctors and nurses working in a Saudi hospital emergency department to determine their attitudes and experiences about the patient safety climate. Results: The findings showed doctors and nurse held some similar safety attitudes, however, nurses reported issues with doctors with respect to their teamwork, communication, and patient safety attitudes. Moreover, several barriers to the patient safety climate were identified such as limits to resources, teamwork, communication, and incident reporting. Conclusion: The findings provide one of the few research contributions to knowledge on the differential patient safety attitudes of Saudi and non-Saudi doctors and nurses and suggest the application of such knowledge would enhance positive patient outcomes in emergency departments.

المستخلص تصنيع لقاح مكون من الحمض النووي الريبوزي الرسول الخاص بالبروتينات المسئولة عن انتاج البروتينات نيورامنيديز والهيم اجليوتونين لفيروسي الانفلونزا الخنازير والطيورمحاط بجزيئات دهنية بحجم النانوميتر عدوى انفلونزا الخنازير وانفلونزا الطيور مشكلة خطيرة تؤرق العالم كله هذه الايام خصوصا انها مميتة لكثير من اطفال العالم . بعد فترة التعافي من الاصابة تتكون المناعة المكتسبة ضدها لمدة عام تقريبا. هذه الانفلونزا تسبب تسمم فيروسي في الدم بالاضافة للالتهاب الرئوي وهذامن بين اكبرالاسباب للوفاة بين الاطفال قبل سن عامين عالميا بشكل مباشر. الهدف من الدراسة هو انتاج لقاح الحمض النووي الريبوزي الرسول من نوع الام بالنانوتكنولوجي لبروتينات الهيم اجليوتونين والنيورامنيديز الموجودة على سطح هذه الفيروسات التي تساعدتها في الاتصاق بالعائل الذي ستتكاثر داخل خلاياه بالجهاز التنفسي. هذه الدراسة دراسة استكشافية ومن خلالها استطاعنا تصميم هذا اللقاح باستعمال نظام توصيل للقاح بالنانوتكنولوجي حجم جزيئاته 70نانوميمتر. اللقاح الجديد اظهر فاعلية بنسبة 60% واظهر فاعلية حيوية مقاربة واثار جانبية اقل بالمقارنة باللقاحات المتوفرة حاليا بالسوق الدوائي ضد هذا النوع من الفيروسات الوبائية. ABSTRACT Background: Worldwide, Swine and Avian influenza, or the H1N1 and H5N1 serotypes of the Influenza A virus, is a highly contagious illness. In recent years, the global incidence of mortality rate has surpassed 284,000 fatalities. Aim of the study: The production of mRNA vaccine lipid nanoparticles (LNP) to combat the deadly strains of Avian and Swine influenza (H1N1 and H5N1 of the influenza A serotype). Methodology: Polymerase chain reaction (PCR) was used to clone genes of interest encoding Haemagglutinin (HA) and Neuraminidase (NA) of Influenza A virus strains (H5N1 and H1N1) known as Avian flu and Swine flu, respectively. The genes were then inserted using the EcoR1, BAM Hind II restriction endonuclease type II, and Ligase enzyme into the pET-21(+) transcription vector plasmid. On the other hand, the hybrid transcription vectors were mixed with T7 RNA polymerase and ribonucleotides within a test tube after being linearized using EcoR II. Following their purification via reversed-phase high-performance liquid chromatography (RP-HPLC), the mRNAs of the HA and NA were encased in 70 nm LNPs and subjected to reverse-phase high-performance liquid chromatography (RP-HPLC). Lastly, immunogenicity studies were performed in stages 1/2 of randomized human and preclinical clinical trials. Results: The bivalent vaccination had around 63% efficacy in preclinical studies and approximately 60% efficacy in randomized human clinical trials. As shown by the ELISA test, strong neutralizing antibodies against HA were prevalent. Conclusion: The current study is a promising effort because of the development of the novel LNP-mRNA vaccine, which could lower the incidence of Avian and Swine flu infectious disorders.

Background: Breast cancer and other neoplasms like acute lymphocytic leukemia pose a serious threat to public health worldwide. Treatment for malignancies including acute lymphocytic leukemia and breast cancer requires enzymes that break down L-glutamine. An amidohydrolase called L-glutaminase can be an effective chemotherapeutic tool for treating various cancers. Methods: On mineral L-glutamine agar selective medium (MGA), a few bacterial isolates were examined in the current investigation to see if they produced L-glutaminase. However, the most effective positive bacterial isolates generating L-glutaminase were identified using morphological and biochemical testing. Molecular detection using the direct Southern blotting approach was also used to determine the main positive isolate that produces L-glutaminase. L-glutaminase synthesis by bacteria was evaluated for its characteristics. Using an MTT test, the anticancer activity was evaluated. Results: exclusive bacterial isolates that used L-glutamine as their sole source of metabolic nitrogen exhibited favorable growth on MGA. PH 7.4 and a temperature of 37 0C were the ideal environmental and physiological conditions for developing positive bacterial isolates. From the soil samples taken from various soil conditions in Egypt, the morphological and biochemical analyses showed that Bacillus cereus 14579 was the main positive bacterial generating L-glutaminase isolate. At a pH of 7.4 and a temperature of 37 °C, the following activators—KCL, ZnSO4, FeSO4, K2HPO4, and MgSO4—provided the high-grade circumstances for characterizing L-glutaminase synthesis. Bacillus cereus-produced L-glutaminase has shown excellent bioavailability and effectiveness as an anticancer therapy. The yield [productivity] was 5.2 U/ml during the original manufacture from MGA, but it increased to 42.96 U/ ml by bacterial recombinant DNA manufacturing. The molecular mass of L-glutaminase was roughly 37 KDa. L-glutaminase was purified, yielding final enzyme recovery of 55 1.23%, total activity 12,990± 19.76 ( U), specific activity 384.66± 8.92( U/ mg of protein), and purification fold 2± 2.99. Furthermore, the L-glutaminase activity was raised by 19%, 23%, 15%, and 9%, respectively, by the enzymatic activators Mn2+, K+, Na+, and Fe3+. It demonstrated strong DPPH scavenging activity (IC50 = 61 μg/ mL) and anticancer activity( IC50 = 40.72, 9.7, 7.39, 20.61, 51.28, and 11.55 μg/ mL, respectively) against human liver (HepG-2), colon ( HCT-116), breast ( MCF-7), lung( A-549), lymphocytic( CCL-120), and cervical( Hela) cancer cell lines. A stronger affinity for its substrate was shown by the kinetic parameters of Km and Vmax, which were 13.2 10-5 M and 119.86 μmol/ ml/ min, respectively. Conclusion: Acute lymphocytic leukemia and breast cancer are examples of auxotrophic malignancies for which L-glutamine serves as the only metabolic source, and L-glutaminase generated by Bacillus cereus was an appropriate enzyme in the therapy of these diseases.

Background: RSV, or respiratory syncytial virus, is a deadly condition that is present all over the world today. The infection is initially contained in the lower respiratory tract without systemic transmission. The objective of the study: Bioinformatics was used in Egypt to create an mRNA vaccine against the Respiratory syncytial virus (RSV). Methodology: In the present screening experimental study, a lipid nanoparticles vaccine of mRNA of the surface fusion protein of Respiratory syncytial virus was manufactured. The present vaccine delivery system was lipid nanoparticles with a particle size of approximately 90 nanometres, manufactured by the hot micro-emulsion method. In stages 1 and 2 of clinical trials, the immunogenicity of the current mRNA RSV vaccine was evaluated. Results: The current vaccine demonstrated 81% immunogenicity in animal testing, but only 69% in stages 1 and 2 of clinical trials. Its side effects were manageable. The results persisted for a while. In the current trial, the vaccination proved effective as a preventative measure against RSV infection. The current vaccination lacked antibody-dependent enhancement, which causes non-protective antibodies to develop. These non-neutralizing antibodies exacerbate infection by activating cytokines and complement cascade through the formation of immune complexes or enhancement of the virus entry and replication in the host cells. On the other hand, the current RSV mRNA vaccine of the surface fusion protein consequent on the production of powerful neutralizing antibodies with prolonged immunity especially to infants and elderly candidates who received the optimal dosage regimen.

Cancer ranks second among the causes of mortality worldwide,following cardiovascular diseases.Brain cancer, in particular, has lowest survival rate of any kind of cancer. Brain tumours vary in their morphology, texture, and location, which determine their classification. Accurate diagnosis of the tumour category enables physicians to select optimal treatment strategies and potentially prolong patients’ lives. Researchers who also implemented deep learning models for diagnosing diseases in recent years largely focused on deep neural network optimization to enhance neural network performance. This implicates implementing models with the best performance and incorporating various network architectures by configuring their hyperparameters. This paper presents a novel hybrid approach method for improved brain tumour classification by combining CNN and EfficientNetV2B3 as feature extraction, followed by (KNN) for classification. To evaluate the recommended method’s efficacy, two widely known benchmark MRI datasets were utilized in the experiments. The initial dataset consisted of 3064 MRI images depicting meningiomas,pituitary,and gliomas tumours.Images from two classes of normal brain and brain tumour were included in the second dataset, which was obtained from Kaggle.In order to enhance performance even more, the study concatenates the CNN and EfficientNetV2B3 flattened outputs before feeding them into the KNN classifier. The proposed framework run on two different dataset and demonstrates outstanding performance with an accuracy of 99.51% and 99.8% on each dataset.

We evaluated the mono- and combination-therapy effects of valproic acid (VPA) and doxorubicin (DOX) in hepatocellular carcinoma (HCC) and identified a specific and efficient, synergistic anti-proliferative effect of the VPA and DOX combination in HCC cells, especially HepG2 cells; this effect was not apparent in MIHA cells, a normal hepatocyte cell line. The calculation of the coefficient of drug interaction confirmed the significant synergistic effect of the combination treatment. Concurrently, the synergistic apoptotic cell death caused by the VPA and DOX combination treatment was confirmed by Hoechst nuclear staining and western blot analysis of caspase-3 and poly (ADP-ribose) polymerase (PARP) activation. Co-treatment with VPA and DOX enhanced reactive oxygen species (ROS) generation and autophagy, which were clearly attenuated by ROS and autophagy inhibitors, respectively. Furthermore, as an indication of the mechanism underlying the synergistic effect, we observed that DOX internalization, which was induced in the VPA and DOX combination-treated group, occurred via by the caveolae-mediated endocytosis pathway. Taken together, our study uncovered the potential effect of the VPA and DOX combination treatment with regard to cell death, including induction of cellular ROS, autophagy, and the caveolae-mediated endocytosis pathway. Therefore, these results present novel implications in drug delivery research for the treatment of HCC.

Biofuels have many environmental and practical benefits as a transportation fuel. They are among the best alternatives to fossil fuels due to their capacity for negative carbon emissions, which is vital for archiving the global ambition of a Net-Zero Economy. However, conventional biofuel production takes place on inland sites and relies on freshwater and edible crops (or land suitable for edible crop production), which has led to the food vs fuel debate. It also suffers technical and economical barriers due to the energy balance and the cost of production compared to fossil fuels. Establishing a coastal integrated marine biorefinery (CIMB) system for the simultaneous production of biofuels, high-value chemicals, and other co-products could be the ultimate solution. The proposed system is based on coastal sites and relies on marine resources including seawater, marine biomass (seaweed) and marine microorganisms (marine yeasts and marine microalgae). The system will not require the use of arable land and freshwater in any part of the production chain and will be linked to offshore renewable energy sources to increase its economic and environmental value. This article aims to introduce the CIMB system as a potential vehicle for addressing global warming and speeding the global effort on climate change mitigation as well as increasing global water, food and energy security. I hope this perspective may serve to draw attention into research funding for this approach.

The purpose of the current study was directed to investigate the effectiveness of docosahexaenoic acid (DHA) as a chemopreventive agent on experimentally induced hamster buccal pouch (HBP) carcinogenesis; Material and methods: 40 Syrian male hamsters, five weeks old, were divided into 4 groups of 10 animals in each as follows, GI: Topical application of liquid paraffin alone (thrice a week for 14 weeks), GII: Topical application of 7, 12 dimethyl benz[a]anthracene (DMBA) alone (0.5 % in liquid paraffin, thrice a week for 14 weeks), GIII: Topical application of DMBA (0.5 % in liquid paraffin, thrice a week for 14 weeks) + Oral administration of DHA (125 mg/kg b.w. in 1 ml distilled water by oral gavage, thrice a week for 14 weeks on alternative days of DMBA application), GIV : Oral administration of DHA alone (125 mg/kg b.w. in 1 ml distilled water by oral gavage, thrice a week for 14 weeks); Results: Gross observations and histopathological findings revealed a-GI: normal stratified squamous epithelium b- GII: well and moderately differentiated squamous cell carcinoma (SCC) c-: GIII: showed variable results ranges from hyperkeratosis, hyperkeratosis and focal hyperplasia, mild dysplasia, and well differentiated SCC with superficial invasion of tumor cells not extended to deeper areas d: GIV: normal similar to GI. Immunohistochemical results revealed that oral DHA treatment to DMBA treated hamsters restored the normal expression of bcl-2; Conclusion: DHA has the potential to be a dietary chemopreventive agent due to its capacity to improve carcinogen detoxification and to block/suppress the initiation and promotion stages of experimentally produced HBP carcinogenesis.

A comparative efficacy of apathogenic genotype I (V4) and lentogenic genotype II (LaSota) strains of live Newcastle disease virus (NDV) vaccines was done following vaccination with pathogen-associated molecular pattern (PAMP) H9N2 avian influenza vaccine and challenge with velogenic NDV genotype VII.1.1 (vNDV-VII.1.1). Eight groups (Gs) of day-old chicks were used (n=25). Groups 1-4 received a single dose of PAMP-H9N2 subcutaneously, while Gs (1, 5) and (2, 6) received eye drops of V4 and LaSota respectively as twice doses. All Gs except 4 and 8 were intramuscularly challenged with vNDV-VII.1.1 at 28th days of age. No signs were detected in Gs 1, 5, 4, and 8. The mortality rates were 0% in Gs 1, 4, 5, and 8; 40% in G2; 46.66% in G6; and 100% in Gs 3 and 7. Lesions were recorded as minimal in Gs 1 and 5, but mild to moderate in Gs 2 and 6. The lowest significant viral shedding was detected in Gs 1, 2, and 5. In conclusion, two successive vaccinations of broilers with a live V4 NDV vaccine provided a higher protection against vNDV-VII.1.1 challenge than LaSota. Besides, PAMP-H9N2 with live NDV vaccines induced more protection than live vaccine alone.

The Industrial Revolution 4.0 (IR4.0) is transforming the global economy, necessitating mall and medium-sized enterprises (SMEs) to adopt new technologies like artificial intelligence (AI), the Internet of Things (IoT), blockchain, and cloud computing. Therefore, SMEs need to assess their readiness to identify capabilities and areas for improvement to remain competitive. However, existing IR4.0 readiness assessment such as the Industry4WRD Readiness Assessment and Industry 4.0-Readiness by IMPULS German are time-consuming and restrict the participation of various sectors. Using the understanding of theories such as Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), Technology Readiness Index (TRI), and Diffusion Of Innovation (DOI), this study developed an initial research model that identifies the dimensions of IR4.0 readiness; (i) organization, (ii) data, (iii) infrastructure, (iv) analytics, and (v) IT, development and operations. This study carried out qualitative methods through four different phases. The first phase is a systematic literature review, and data collection through participant observation (PO) in IR4.0 skills training programs, seminars, and workshops. The second phase is the development of an initial research model to identify the dimensions of IR4.0 readiness that will be used in the next phase. The third phase is a survey on SME’s IR4.0 readiness via the IR4.0 e-Readiness Checker (IR4.0 eRC) readiness assessment system, which produces the final research model, IR4.0 SME Readiness Model. In the fourth phase, the IR4.0 Readiness Model is confirmed for use by SMEs in Malaysia through interviews with three industry experts in Malaysia. Based on the 50 responses in the IR4.0 eRC evaluation, the average IR4.0 readiness of SMEs is 66%, and only 10 SMEs with less than 50%, showing room and improvement opportunities for the continuous research and development of IR4.0 transformation. This study developed IR4.0 readiness model for SMEs to assess readiness for IR4.0 transformation, support investments in IoT projects and employee upskilling programs.

This study focuses on a new class of functions called sub-b-s-preinvex, that is a generalization of sub-b-s-convex and preinvex functions, and discusses some of their properties. A new sub-b-s-preinvex programming is introduced and the sufficient conditions of optimality under this type of function is established.

This article is a continuity of prevouse two reserch in daylight harvastion control that were deigned using classical control apoproach and then fuzzy logic technique, In this article ANN controller is designed and its response is compared with the performance of the other two controllers. Detailed compression for the different error type is illustrated, however, the results show that the three controller operate with satisfactory accuracy.

Global warming and climate change have been the major concern for multiple disciplines. Population growth, urbanization, and industrialization are major contributing factors to such a problem by escalating the use of fossil fuels to meet their energy demands. The building sector has the largest share in using the total globally produced energy and emitting tons of greenhouse gas emissions. Emerging eco-friendly technologies such as solar and wind energy harvesting are being extensively explored but still, they are insufficient. Nature-inspired technologies can be the solution to our problem. For instance, algae are microorganisms that use water, light, and CO2 to produce energy and sustain life. Exploiting such characteristics in the built environment is termed algae building technology, a very efficient and green application for a sustainable future. Algae-integrated façades show great versatility through biomass and energy production, wastewater treatment, shading, and thermal and acoustic insulation. In this paper, algae will be introduced as a robust tool toward a greener and more sustainable future, The algae-building technology and its implementation will be demonstrated. Steps for applying this sustainable approach in Egypt will be discussed.

The Kingdom of Saudi Arabia (KSA) is known for its high car ownership and usage as well its high GDP per capita. This is combined with low/ or no provision of public transportation (PT) systems, has been resulting in perceptual attitudes of full dependency on private car travel. The level of awareness of the benefits of reducing car use and increasing the travel by more sustainable options, has a great impact on social change and behaviour. The Kingdom is currently progressing towards a new phase of “national transfer” through implementation of strategic and sustainable measures and programs. The city of Riyadh is construction a massive metro-system in Riyadh, that is nearing completion and operation. The public is aware of the national agenda, aware of the newly constructed projects and aware of the needed social change to realize the new vision of the country. This paper aims to assess travel behaviour and attitudes towards public transportation of Saudi travellers’ who are witnessing the new transformation in the Kingdom and who are aware of the new sustainable projects. Depicted from the theory of random utility, a discrete choice model of the intent to use public transportation is calibrated as a function of social and attitudinal factors. An online survey was designed and carried out using social media means; a completed 399 questionnaires have been obtained and studied. The methodology includes examining attitudes and preferences of the participants towards using public transportation options against participants’ socio-economic data. The analysis was carried out using ordinal logistic regression analysis (OLR) which is an efficient technique that is derived from the theory of random utility. The results show a good support for PT; a higher support for public transportation modes, form participants who are young females, lower income groups and the university graduates were reported. The level of support seems higher with the higher level of awareness about the new PT system.

Carbon fiber reinforced polymers (CFRPs) are being used extensively in modern industries that require high strength-to-weight ratio such as aerospace, automotive, motorsport, and sports equipment. However, although reinforcement with carbon fibers improves the mechanical properties of polymer, this comes on the expense of abrasive wear resistance. Therefore, to efficiently utilize CFRPs in dry sliding contacts, solid lubricant is used as a filler. Further, to facilitate fabrication of objects with complex geometries, selective laser sintering (SLS) can be employed. Accordingly, in the present work, graphite-filled carbon fiber-reinforced polyamide 12 (CFR-PA12) specimens were prepared using SLS process to explore the dry sliding friction and wear characteristics of the composite. The test specimens were aligned along four different orientations in the build chamber of SLS machine to determine the orientation-dependent tribological properties. The experiments were conducted using pin-on-disc tribometer to measure the coefficient of friction (COF), interface temperature, friction-induced noise, and specific wear rate. In addition, scanning electron microscopy (SEM) of tribo-surfaces was conducted to specify the dominant wear pattern. The results indicated that the steady state COF, contact temperature, and wear pattern of graphite-filled CFR-PA12 are orientation-independent, and that the contact temperature is likely to approach an asymptote far below the glass transition temperature of amorphous PA12 zones, thus eliminating the possibility of matrix softening. Additionally, the results showed that the Z-oriented specimen exhibits the lowest level of friction-induced noise along with the highest wear resistance. Moreover, SEM of tribo-surfaces determined that abrasive wear is the dominant wear pattern.

This article introduces new method using ANN to control SVC in order to correct the source power factor of low voltage network. Two ANN approaches are investigated to design accurate and fast power factor correction (PFC) controller. First approach uses simple ANN (SANNA). Second approach uses cascaded ANN (CANNA). ANN regression, performance and the calculated error for both approaches are investigated to select between the two approaches. CANNA is selected as a better solution and it used to build the ANN PFFC controller using database, generated by MATLAB-Simulink, for standard three low voltage levels (240V, 220V and 110V). Nine test cases are carried out to validate the performance of proposed ANN PFC controller with a network has variable loads and low power factor (0.6 approximately). In order to extend the use of the controller to other voltage levels not included in the training process of the cascaded ANN, only the SVC is resized. Another nine cases are carried out with the same loads using the same ANN controller, as it is, to test its performance with the extended voltage level range (415V, 230V and 120V). The results show accurate and fast response in all test cases.

Abstract. This article proposes new fuzzy controller to regulation the voltage, damp the oscillations and limit the overshoot behavior in single-machine infinite-bus power system. Two different independent MISO fuzzy controllers are designed. First controller, is voltage stabilizer and it composes of two adaptive fuzzy modules and proportional gain AVR. The voltage stabilizer is designed to regulate the terminal voltage, damp the voltage oscillation and limit the voltage overshoot to the industrial maximum allowable limit. The input signals of this stabilizer is are taken from the terminal voltage and the imposed voltage disturbance that can be read from any smart relay. The fuzzy output is used as feedback signal to control the AVR in order to achieve stabilized voltage equal to the reference voltage. The second fuzzy controller is designed with two input signals; “mechanical angle” and its derivative, and one output which is used as feedback signal to adapt the damping torque in order to damp the mechanical oscillation fast and with maximum overshoot not exceeding 10%, and hence damp the power angle oscillation that is important in the PSS improvement. MATLAB-SIMULINK was used for modelling and the test cases simulation. The results show very good performance for the proposed fuzzy controllers.

This paper attempts to compare two different approaches to solve the problem of accident rates prediction based on human factors for industrial workers. One of the methods has already been done using Fuzzy c-Means Clustering and proved to be working with decent results. The second method which will be covered in this paper is using Artificial Neural Networks. The primary goal of this work is to insure that ANN will work efficiently in such prediction problem. The second goal is to reveal the fact that which one of the two selected methodologies is better at defining the estimation of accident rates among people who work in different industrial fields. The purpose has been achieved when the outcome of the ANN was obtained and compared accordingly with the output of the research previously carried out with Fuzzy c-means clustering method. Comparing the outcomes of these two different methods gave an immense insight on which features are more important than others when it comes to laborers properties with completely different background such as varying levels of health, knowledge, experience, training and physical properties. At the end of the research, it becomes clear that accident rates estimation for laborers with properly trained Artificial Neural Network gives better results when it is compared with Fuzzy c-Means Clustering method. Standard deviation method was used to calculate the validity of ANN technique. The result was compared with Fuzzy c-mean clustering technique. Impressive improvement of 8.8% in the accident rate prediction was achieved using Tailored-Made-ANN.

Global temperature rise due to hydrocarbon gases emission that are produced by generating the electrical power has a great attention by the researchers to reduce it till zero emission is successfully achieved. Sustainable energy source such as solar energy, wind, hydro-energy and sea wave energy are focal areas to replace the fossil fuel by clean energy. In this article, daylight is used to minimize the power consumption that required for indoor lighting using electric roller blind. Smart controller is designed to adjust the position of the roller blind stepper motor, and hence, adjust the roller blind opening, based on the preset light intensity, to achieve precise utilization of daylight inside the room. If the desired Lux is not achieved for any reason, the smart controller adjusts the LED circuit current to boost the light intensity to achieve precisely the desired Lux. Comprehensive test cases using MATLAB-Simulink is carried out to verify the performance of the proposed smart controller. Techno-economic analysis is introduced to evaluate the benefits of installing the controller. Summary and recommendation are given at the end.

A ducted photovoltaic façade (DPV) unit Studied using experimental Prototype and simulated in a full scale Computational Fluid Dynamics CFD Model. The Study comes in two parts; This is Part I with the title detailed above and Part II titled ‘A Ducted Photovoltaic Façade Unit with Buoyancy Cooling: Part II CFD Simulation’.. The process adopted in the experimental study is replicated in the simulation Part. The aim was to optimize the duct width behind the solar cells to allow for maximum buoyancy-driven cooling for the cells during operation. Duct widths from 5 to 50 cm were tested in a Proto-type. A duct width of 45 cm had the maximum calculated heat removed from the duct; however, the lowest cell-operating temperature was reported for duct width of 50 cm. It was found that the DT between ducts' inlets and outlets range from 5.47 °C to 12.32 °C for duct widths of 5–50 cm, respectively. The ducted system enhanced module efficiency by 12.69% by reducing PV temperature by 27 °C from 100°C to 73 °C. The maximum calculated heat recovered from the ducted PV system is 422 W. This is 47.98% from the incident radiation in the test. Total summation of heat recovered and power enhanced by the ducted system is 61.67%.

This paper is an extension to previous work that introduced successful classical-control for indoor lighting system that simultaneously control LED system and roller curtain to achieve accurate light intensity for indoor lighting applications. In this paper, Multi Input Multi Output Fuzzy Logic Controller (MIMO FLC) is proposed to replace the classical-controller. Detailed method is provided to illustrate the steps to design the required MIMO FLC that has two fuzzy input, two fuzzy output and forty-five fuzzy rules with mamdani fuzzy engine. The proposed MIMO FLC is simulated in Matlab using Simulink tools. The results are illustrated, analyzed and compared with the classical-control. The response showed very close performance to the classical-controller. The maximum average error and the maximum error with respect to “Desired Lux” inside the room is -6% and -10% respectively.

This review provides an understanding of the teaching and practising of forensic accounting across the globe. It includes a review of published forensic accounting studies that conclude that forensic accounting is of benefit to both students and professionals. Despite this, there are areas of concern; namely, the insufficiency of an appropriate structure of regulation and a lack of control over the academic qualifications to enter the profession. This review of both the teaching and practising of forensic accounting provides an overview of the vital issues and concerns that must be understood in order to advance the essential application of forensic accounting. It is expected that this review will influence future policy that will advance business and limit episodes of fraud. The amount of published literature on the subject of forensic accounting is widespread and diverse. However, there is a lack of comprehensive understanding regarding the strengths and weaknesses of forensic accounting; this review will address this and provide policymakers with a thorough explanation of the subject.

Abstract: Ovulation failure was associated with a reduction in pre-mating concentrations of oestradiol-17β and prolactin (PRL). The present study aimed to evaluate whether pre-mating PRL levels have a role on the reproductive efficiency of doe rabbits. A total of 78 multiparous California does (2nd parity) were divided, according to plasma pre-mating PRL, into five categories, >20-25, >25-30, >30-35, >35-40, and >40-45 ng/ml. Does in all categories were naturally mated and kindled, then their reproductive measurements and progesterone (P4) levels were determined. Results show that pre-mating PRL averaged 23.60±0.78, 28.00±0.83, 33.46±0.43, 38.17±0.49 and 41.98±0.68 ng/ml in five categories (p < 0.05), respectively, representing the highest distribution (38.5%) in the 3rd-category. Live body weight of doe rabbits, at mating, pregnancy, and parturition increased (p < 0.05) with increasing pre-mating PRL level. The number of services, litter size, and pregnancy rate increased (p < 0.05) by increasing PRL levels. Reproductive traits and P4 level at mid-pregnancy of does, and average weight of kits at birth increased (p < 0.05) by increasing PRL levels. The pre-mating PRL profile is important for the identification of reproductive performance in doe rabbits.

With the rapid expansion of intelligent resource-constrained devices and high-speed communication technologies, Internet of Things (IoT) has earned a wide recognition as the primary standard for low-power lossy networks (LLNs). Nevertheless, IoT infrastructures are vulnerable to cyber-attacks due to the constraints in computation, storage, and communication capacity of the endpoint devices. From one side, the majority of newly developed cyber-attacks are formed by slightly mutating formerly established cyber-attacks to produce a new attack tending to be treated as a normal traffic through the IoT network. From the other side, the influence of coupling the deep learning techniques with cybersecurity field has become a recent inclination of many security applications due to their impressive performance. In this paper, we provide a comprehensive development of a new intelligent and autonomous deep learning-based detection and classification system for cyber-attacks in IoT communication networks leveraging the power of convolutional neural networks, abbreviated as (IoT-IDCS-CNN). The proposed IoT-IDCS-CNN makes use of the high-performance computing employing the robust CUDA based Nvidia GPUs and the parallel processing employing the high-speed I9-Cores based Intel CPUs. In particular, the proposed system is composed of three subsystems: Feature Engineering subsystem, Feature Learning subsystem and Traffic classification subsystem. All subsystems are developed, verified, integrated, and validated in this research. To evaluate the developed system, we employed the NSL-KDD dataset which includes all the key attacks in the IoT computing. The simulation results demonstrated more than 99.3% and 98.2% of cyber-attacks’ classification accuracy for the binary-class classifier (normal vs anomaly) and the multi-class classifier (five categories) respectively. The proposed system was validated using k-fold cross validation method and was evaluated using the confusion matrix parameters (i.e., TN, TP, FN, FP) along with other classification performance metrics including precision, recall, F1-score, and false alarm rate. The test and evaluation results of the IoT-IDCS-CNN system outperformed many recent machine-learning based IDCS systems in the same area of study.

This work probes the combined effects of magnetic field and viscous dissipation on heat field and examine the second law analysis (entropy generation) in an electrically conducting fluid under the effect of wall mass transfer over continuous stretched non-isothermal surface with variable viscosity. The viscosity of the fluid is assumed to be an inverse linear function of temperature. The governing equation for the problem are changed to dimensionless ordinary differential equations by using similarity transformation and solved numerically by using Rung Kutta and Shooting technique. Velocity, concentration and temperature distribution are obtained and used to compute the entropy generation and the Bejan number in the flow field. The effect of variable viscosity, Schmidt number, Hartman and Reynolds number on the velocity, concentration, temperature, entropy generation and Bejan number are studied and discussed.

Molecular analysis is an easier means to identify and isolate a specific gene which has imperative function for growth, body composition , fat deposition, metabolic and skeletal traits as well as the molecular genetics selection on individual genes is a very efficient method to genetically improve economically important traits in chickens. Insulin- like growth factor 1 ( IGF-1)is a member of a heterogeneous group of peptides with important growth.Transforming growth factorβ ( TGF-β) belongs to a large family of growth and differentiation factors that play a pivotal role in a great variety of biological activities including morphogenesis, development and differentiation. DNA was extracted from 48 chickens sampled from three strains Lohman (17) , Sinai (24) and Gimmizah (7) IGF-1 gene and TGFβ2 gene were amplified using PCR protocol. Electrophoresis was carried out on the products of PCR , bands viewed on transilluminator. The size of IGF-1 gene was 675 bp while the size of TGFβ2 gene was 188bp. Sharp bands were purified and sequenced and used the dendrogram to show the relationships between other vertebrate species

(1) Background: The present study was carried out to provide new information about the relation between angiogenesis, tumor stage Oral squamous cell carcinoma (OSCC); (2) Materials and methods: Thirty formalin-fixed paraffin embedded blocks were used, 10 of them were previously diagnosed as well differentiated OSCC, 10 moderate differentiated OSCC and 10 poorly differentiated OSCC. To determine the expression of CD31 and D2-40 proteins, streptavidin-biotin immunoperoxidase staining technique was used. The areas with the most vascular density (hot spots) were determined. The stained vessels were counted independently in intratumoral and peritumoral stroma in five areas of hot spot at ×400 magnification; (3) Results: Immunohistochemical staining using CD 31 protein showed that CD31-positive vessels in the peritumoral and intratumoral stroma subjacent to the malignant invading nests which was recorded highest values in poor differentiated OSSC followed by moderate differentiated OSSC then well differentiated OSSC. D2-40 expression was positive in lymphatic vessel in the peritumoral and intratumoral stroma subjacent to the malignant invading nests. Poorly differentiated OSSC tissue sections recorded the highest vessels count followed by moderate differentiated OSSC then well differentiated OSSC. There was statistically significant difference found between the three studied groups regarding CD31 and D2-40 levels. Also there was statistically significant positive correlation found between CD31 level and D2-40 level and vice versa; (4) Conclusion: CD31 and D2-40 are related to stage of OSCC and are consistent with angiogenesis in tumor progression.

A comprehensive kinetic model of the Fischer-Tropsch synthesis (FTS) is developed in a fixed bed reactor under operating conditions (temperature, 230–235°C, pressure, 20–25 bar, gas hourly space velocity, 4000–5000 cm³(STP)/h/g_catalyst ,H₂/CO feed molar ratio, 2.1) over a Co based catalyst. Reaction rate equations based on Eley-Rideal (ER) type model for initiation step and Langmuir-Hinshelwood-Hougen-Watson (LHHW) type model for propagation and termination steps of the FTS reactions have been considered and the readsorption of olefins were taken into account. The model that was reported in the literature was modified in order to explain many significant deviations from the ASF distribution. Optimum parameters have been obtained by Genetic Algorithms (GA). The calculated activation energies to produce n-paraffins and 1-olefins were in the range of 82.24 to 90.68 kJ/mol and 100.66 to 105.24 kJ/mol, respectively. The hydrocarbon distribution in FTS reactions was satisfactorily predicted particularly for paraffins.

Abstract: This article explores the intricate relationship between environmental degradation, specifically air pollution, and economic growth in the Sultanate of Oman spanning the period from 1990 to 2022. We employ cointegration and vector error correction models to uncover both short- and long-term dynamics in the association between air pollution and economic growth. Fur-thermore, Granger causality analysis is utilized to investigate the causal links between these crucial variables. This data encompasses factors related to environmental quality and various control variables. The empirical results unveil a sustained long-term cointegration connection between the variables. Additionally, our findings highlight a statistically significant positive impact of economic growth and energy consumption on CO2 emissions. Furthermore, the short-term analysis reveals an annual adjustment of approximately 14.1% in N2O emissions dis-equilibrium. The Granger causality study indicates unidirectional causal relationships involving N2O emissions, economic growth, and CO2 emissions. The implications of these findings for Oman's policy landscape are substantial. To effectively reduce greenhouse gas emissions, it is imperative for Oman to establish robust climate change policies. Additionally, the government can play a pivotal role in encouraging and endorsing the use of renewable energy sources, such as green hydrogen, as a promising alternative to traditional oil and gas resources.

The physicochemical treatment/recovery techniques, including precipitation, membrane technology, solvent extraction, foam fractionation, adsorption, and aqueous two-phase systems, will be reviewed. The bio-treatment processes, based on microorganisms and/or enzymes consuming nutrients available in food-processing wastewater as low-cost substrates to produce valuable products, will be discussed in detail, including the production of microalga biomass in wastewater treatment systems. Finally, future research direction will be proposed to integrate the circular economy and develop integrated food processing wastewater management systems.

In this paper, we implement a new method binary Particle Swarm Optimization (PSO) for solving the kidney exchange problem, which will improve the future decisions of kidney exchange programs. Because using a kidney exchange, we can help incompatible patient-donor couples to swap donors to receive a compatible kidney. Kidney paired donation programs provide an innovative approach for increasing the number of available kidneys. Further, we implementing binary particle swarm optimization in parallel with MATLAB with one, two, three and four threads and from the computations point of view, the authors compare the performance to reduce the running time for kidney exchange to match patients as fast as possible to help clinicians. Moreover, implementing binary particle swarm optimization in solving the kidney exchange problem is an effective method. The obtained results indicate that binary PSO outperforms other stochastic-based methods such as genetic algorithm, ant lion optimization, and efficient the number of resulting exchanges.

This paper discusses domestic problem of waiting hot water for the shower use till it reaches satisfactory temperature, which result a lot of wastage in fresh water. The outcome from research survey shows that there is no satisfactory solution till now as all solutions were either expensive or with no effective results. Local small inline electric heater equipped with fuzzy logic controller is proposed in this paper to be installed just before the showerhead to measure the water temperature and flow before the showerhead, as control input-variables, and decide the operating voltage of the heater, as control output-variable (MISO). MATLAB Simulink is used to model the proposed system. Different test cases are simulated to prove the performance and the safe operation of the system. Techno-economic study is carried out to determine the “Direct Benefits” and “Indirect Benefits” that can be achieved if such system is implemented in wide range. Azerbaijan data is taken as an example to calculate the economic benefits. The results show important benefits not only for economy but also for climate and the reduction of CO₂ gas emission. Different economic indices are provided to be an easy reference for decision makers and project managers.

Deep sky observation is a fascinating activity, but it requires favourable conditions in order to be fully appreciated. Complex equipment, light pollution around urban areas, lack of contextual information often prevents newcomers from making the most of their observations, restricting the field to a niche expert audience. In this paper, we show how combining the usage of smart telescopes with eXplainable Artificial Intelligence makes the practice of astronomy even more accessible and educative, and how it has been applied during outreach sessions In Luxembourg Greater Region.

In recent years, the implementation of artificial intelligence (AI) in accounting has grown in many domains, including auditing. AI permits auditors to evaluate large data sets and rapidly identify discrepancies and sequences in audit. This means auditors can review all of a client's transactions via a low time and effort. This entails auditing firms investing heavily in technological infrastructure as well as training their human resources to use cutting-edge AI technologies. Thus, this research sought to investigate the impact of the use of AI techniques by Jordanian external auditors in fraud risk assessment, the moderating effect of auditor size. The descriptive analytical method was used by distributing 280 questionnaires electronically to auditors employed in auditing firms operating in Jordan, The result reveals that AI techniques are extremely beneficial in fraud risk assessment at all levels, and the relationship between the use of AI techniques and the assessment of fraud risk has improved as auditor size has increased.

Competition between cotton, winter, and summer crops is the greatest obstacle for plant breeders in Egypt. Breeders are thus seeking early maturing, high-yielding cultivars that are suited for planting following winter crops. This study was conducted during the 2016 and 2018 growing seasons at the Sakha agriculture research station, Egypt's agricultural research facility. This research used breeding material from the F2, F3, and F4 generations that resulted from crossing Giza 94 and Uzbekistan. During the 2016 growing season, the F2 population was cultivated, and the top 5% of the F2 population (75 plants) were chosen based on the selection criteria. In the summer of 2017, the F3 families were cultivated, and 5% of the superior F3 families were chosen to become the F4 fam-ilies, which were planted in the summer of 2018 at the single plant and bulk studies in a randomised full block design with three replications. The average performance of the characteristics boll weight, seed cotton yield, lint percentage, and lint index increased as generations passed from F2 to F4. In the meanwhile, the characteristic value of the first flower to open decreased, showing the accu-mulation of advantageous alleles. For all examined characteristics, the phenotypic coefficient of variance was greater than the genotypic coefficient of variation. In addition, the data demonstrated that heritability in a broad sense was greater in F4 populations than in F3 and F2 populations. With a few exceptions, the phenotypic and genotypic associations for all investigated characteristics were positive and very significant. According to the data, initial opening flowering and boll weight had a substantial impact on seed cotton output per feddan. In general, five superior families No. 9, 13, 18, 19, and 20 were chosen from the F4 population, which were more significant for yield and yield component than the commercial variety, and these genotypes may be promising for the breeding programme to develop new genotypes with superior yield.

In the present work we study the properties of geodesic sub-$ (\alpha,b,s) $-preinvex functions on Hadamard manifolds and establish some basic properties in both general and differential cases. Further, we study sufficient conditions of optimality and proved some new inequalities under geodesic sub-($ \alpha,b,s $)-preinvexity.

The concept of this prototype is to create a cold air film layer, in indoor side of the window. The function of this extra cold air layer is to increase the amount of window resistance and decrease its U-Value. It provide air film layer by using the same concept of desert cooler or wind catcher. They both bring the hot air from outside then let it go throw straw miost with cold water. After hot air move through straw, it would become cold, thus increase the window resistance and decrease the haet gian, therefore, decrease the cooling load. So, this window model works by heating the air in air room by sun radiation, then after a while, air pressure will rise and its volume will increase then it will impulse to wet hay, and become cold. Then there is fins to guide air flow to its correct direction, thus inner side of window will become cold, not like other type of window which when temperature rise, the inner side of window become hot. So, this window prevents heat transition and creare regenereted trubouland air flim in the inner side of the window. Using calculation to find air film characteristics and WINDOW7.7 software to calculate heat gain through window, shows that it is expected from this prototype to reduce heat gain by 6.85 % for double glazed clear window.

Long-term health consequences are influenced by circumstances that occur during pregnancy. The confluence of the maternal and fetal circulations occurs at the placenta, which is the first or-gan to develop. Placental pathology can provide an accurate diagnosis of inflammation inside the amniotic sac. The pathological alterations of preterm placentas provide evidence for the causes of numerous perinatal pathologies, including spontaneous preterm births. This retrospec-tive study aimed to re-examine placentas regarded as normal by the Obstetrics and Gynecology Department in our institution so that grading and staging of any evident inflammatory response could be evaluated and associated with baby gender. Eighty-four full-term placentas were col-lected after delivery. Placentas that were considered normal and were not sent to the histo-pathology department were taken. Morphological examination of fresh placenta was conducted. Full thicknesses of placenta samples were taken from central and marginal regions of placental disc. Fetal and maternal inflammatory responses syndrome were assessed. Villitis of unknown etiology (VUE) and chronic deciduitis also were evaluated in the placenta. Immunohistochemis-try (IHC) was also performed to evaluate patterns of inflammation in the placenta using an-ti-CD8 and anti-CD68 antibodies. The correlation between the silent pathologies and clinical complications or involvement of developing fetal inflammatory response syndrome was meas-ured. In this study, seventeen (20%) maternal inflammatory samples and ten (12%) fetal inflam-matory samples showed inflammatory responses. The frequency of chronic deciduitis and villi-tis of unknown etiology was more remarkable among Saudi pregnant women than the previ-ously reported findings in the literature of placental pathology. The prevalence of fetal and ma-ternal inflammatory response was greater in the placentas of mothers of males than in placentas of female mothers. Grading placental inflammation usually predict the degree of maternal an-ti-fetal cellular rejection. Fetal inflammatory response syndrome usually goes unnoticed in Sau-di Arabia. There are differences in the inflammatory response in the placenta based on the sex of the newborn. Increasing the number of placental samples that must be sent for microscopic in-spection may be preferable due to their significance in identifying the causes of chronic disor-ders.

Pancreatic neuroendocrine tumors (PNETs) are characterized by dysregulated signaling pathways that are crucial for tumor formation and progression. The efficacy of traditional therapies is limited, particularly in treatment of PNETs at advanced stage. Epigenetic alterations profoundly impact the activity of signaling pathways in cancer development, offering potential opportunities for drug development. There is currently a lack of extensive research on epigenetic regulation in PNETs. To fill this gap, we first summarize major signaling events which are involved in PNET development. Then, we discuss the epigenetic regulation of these signaling pathways in the context of both PNET and commonly occurring, and therefore more extensively studied, malignancies. Finally, we will offer perspective on the future research direction of PNET epigenome and its potential applications in patient care.

This paper aims to investigate impact of employees’ gender on OCB as per the employees’ perception in Jordanian governmental hospitals. A convenient sample of 126 employees working in the three main governmental hospitals in north of Jordan has been taken for the purpose of this study. The collected data includes linguistic terms that suffer from uncertainty which, in turn, cannot be dealt with traditional numerical values. The result prove that gender impact on OCB has shown statistically significant differences at (α=0.05) as far as altruism, courtesy, and civic virtue are concerned; and this variable stands in favor of males with the total score of 0.011%. Similarly, as far as the effect of age factor on OCB is concerned, there have been statistically significant differences at (α=0.05) in relation to courtesy, sportsmanship, and civic virtue with the total score of 0.27%. Finally, the results provide a baseline data for further studies which may contribute more significant in the field of OCB.

Almost one fifth of breast cancer cases express Human Epidermal Growth Factor-2 (HER2), and such expression is associated with highly proliferative tumor and poor prognosis. The introduction of anti-HER2 therapies has dramatically changed the natural course of this aggressive subtype of breast cancer. However, anti-HER2 therapy can be associated with substantial toxicities, mostly cardiac, and high cost. Over the past few years, there has been growing interest in de-escalation of anti-HER2 therapies to minimize adverse events and healthcare costs, while maintaining the efficacy of treatment. Data from clinical observations and single-arm studies have eluted to the minimal impact of anti-HER2 therapy in low-risk patients, like those with node-negative and small tumors. Though single-arm, the APT trial, in which patients with node-negative, small tumors received single-agent paclitaxel for 12 cycles plus trastuzumab for 1 year, was a practice-changing study. Several other recently published studies, like the PERSEPHONE trial, have shown more convincing data that 6 months of trastuzumab is not inferior to 12 months, in terms of disease-free survival (DFS), suggesting that de-escalating strategies with shorter treatment may be appropriate for some low-risk patients. Other de-escalating strategies involved adaptive, response-directed approach, and personalized therapy that depends on tumor genomic profiling.

The excited-state lifetimes of the anticoagulant drug warfarin (W) in water and in the absence and presence of methyl-β-cyclodextrins (Me-β-CD) were recorded using time-resolved fluorescence measurements. Selective excitation of the open and cyclic protonated isomers of W were acquired with laser emitting diodes (LED) producing 320 and 280 nm excitation pulses, respectively. Formation of the inclusion complex was checked by UV–visible absorption spectroscopy, and the values of binding constants (2.9 × 10³ M^–1 and 4.2 × 10² M^–1 for protonated and deprotonated forms, respectively) were extracted from the spectrophotometric data. Both absorption and time-resolved fluorescence results established that the interior of the macromolecular host binds preferentially the open protonated form, red shifts the maximum of its absorption of light at ~305 nm, extends its excited-state lifetime, and decreases its emission quantum yield (ФF). Collectively, sequestration of the open guest molecules decreases markedly their radiative rate constants (kr), likely due to formation of hydrogen-bonded complexes in both the ground and excited states. Due to lack of interactions, no change was observed in the excited-state lifetime of the cyclic form in the presence of Me-β-CD. The host also increases the excited-state lifetime and ФF of the drug deprotonated form (W¯). These later findings could be attributed to the increased rigidity inside the cavity of Me-β-CD. The pKa values extracted from the variations of the UV–visible absorption spectra of W versus the pH of aqueous solution showed that the open isomer is more acidic in both ground and excited states. The positive shifts in pKa values induced by three derivatives of cyclodextrins: HE-β-CD, Ac-β-CD, and Me-β-CD supported the preferential binding of these hosts to open isomers over cyclic.

This article discuss the estimation of electrical stresses input that is required to determine lifetime degradation of the HV cables installed within overhead transmission lines (OHTL’s). Abort from lightning effects, these electrical stresses are mainly generated due to repetitive switching operation of the transmission line that produces transient overvoltage (TOV) stress and high frequency stress. The transient overvoltage (TOV) due to switching-off the transmission line at the interface points between the cable and OHTL is estimated using artificial neural network (ANN). PSCAD software is used to build the transmission line model for 749 different case in order to build the required database for ANN training. Two different algorithm input to train ANN with one hidden layer and one output layer using different number of nodes are modeled in MATLAB. The results performance is continuously compared and evaluated till acceptable Regression is achieved to insure the error is less than +/-1.5%. The high frequency due to switching-on the transmission line is also recorded and analyzed. The results show that this new method is efficient, accurate and useful as there is no cable monitoring system is available for each HV cable installed within the transmission line.

This paper proposes a novel deterministic methodology for estimating the optimal sampling frequency (SF) of water quality monitoring systems. The proposed methodology is based on employing two-dimensional contaminant transport simulation models to determine the minimum SF considering all the potential changes in the boundary conditions of a water body. A two-dimensional contaminant transport simulation model (RMA4) was implemented to estimate the distribution patterns of the total dissolved solids (TDS) within the Al-Hammar Marsh in the southern part of Iraq for 30 cases of potential boundary conditions. Using geographical information system (GIS) tools, a spatiotemporal analysis approach was applied to the results of the RMA4 model to determine the minimum SF of the monitoring stations with an accuracy level of detectable change in TDS concentration (ALC) of 5%, 10% and 15%. The proposed methodology specified a minimum and maximum SF for each monitoring station (MS) that ranged between 12 and 33 times per year, respectively. Additionally, increasing the ALC to 10% and 15% increase the minimum SF for some MSs by approximately 18% and 21%, respectively. However, the proposed methodology includes all the potential values and cases of boundary conditions, which increases the certainty of monitoring the system and the efficiency of the SF schedule. Moreover, the proposed methodology can be effectively applied to all types of surface water resources.

This paper aims to provide an adaptation of the TL-moments method to censored data. The present study concentrates on Type-I censored data. The idea of using TL-moments with censored data may seem conflicting. But our perspective in that, we may use data censored from one side and trimmed from the other side. This study is applied to estimate the two unknown parameters of the Weibull distribution. The suggested point is compared with Direct L-moments and ML methods. A Monte Carlo simulation study is carried out to compare these method in terms of estimate average, root of mean square error (RMSE) and relative absolute biases (RAB).

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.

Inflation is a crucial macroeconomic indicator which measures changes in the general level of prices of goods and services. In recent years, a series of successive events affected the inflation rates. To fight this increase in inflation, governments start to take different actions through their monetary and fiscal policies. In this research 10 independent parameters were used to see their effect on inflation rates. Some are traditional like GDP, Population, and exchange rate while others are some new technology related parameters like E-money payments transactions and number of Institutions offering payment services/instruments. The dependent parameter is the consumer price index (CPI). All parameters were taken in 8 years period (2013-2020). Supervised machine learning is used to run a robust regression model. The results show that technology advancement in payments is not a catalyst for price inflation if it is used properly and under regulations and control monetary policies. The results direct regulators to have a good understanding of the situation and take the right action in their policies of adopting fintech businesses.

Livability is one of the paramount characteristics of the current era that architects striving to achieve. This situation becomes even more important on commercial streets, whose functional diversity and constant movement of people require special action. In Erbil, commercial streets suffer from neglect in terms of adopting places for livability. Although it has huge potential to form an attractive and entertaining environment other than shopping. Some countries have developed standards for the design of commercial streets. The basic requirements are the same, but details usually vary according to the diverse needs of people. The research aims to identify a comprehensive framework (A Checklist) for placemaking to form the basis for measuring livability in one of the vital streets in Erbil city. This Framework is considered the basis for assessing and designing at the same time, supporting designers to achieve two main pillars: develop existing streets and suggest basic principles for future street design. This article adopts a practical framework, a questionnaire, a field survey, and observation as research methods. The research concluded that altogether placemaking dimensions are essential in activating livability, and a sort of balance between the main dimensions appeared. The more applied strategies, the higher the street livability.

This paper presents a new adaptive and optimal algorithm for the trajectory tracking control of a quadrotor using iterative learning algorithm (ILA) and enumerative learning algorithm. Ordinarily the ILA, as an adaptive method, can perform well with PID control to improve the controller’s performance for a nonlinear system. Quadrotors are considered as non-linear and unstable systems which the use of an adaptive and optimal controller can increase its stability and decrease error level. In this method, a PID controller is proposed for the outer and inner control loops of a quadrotor and the ILA is used to adapt PID control gains. Subsequently, an enumerative learning algorithm is used to optimize the learning rates of the ILA. For this purpose, at first, the dynamic model of the quadrotor is acquired. After that, the structure of the inner and outer control loops is defined. In the end, the simulation results for the trajectory tracking control of a quadrotor are demonstrated. Through simulation, it is concluded that as time increases, the performance of the suggested control method in trajectory tracking control becomes better and better and error signals convergence to zero.

Modern advances in technology have increased the demand for traditional accounting systems to be upgraded for real-time data processing, security, and standardized reports. Thus, this paper proposes a new accounting information system that integrates IoT, blockchain, and XBRL. The proposed system aims to automate the accounting process by using IoT to collect data and send it automatically to a blockchain, which acts as a database that will generate journal entries automatically through smart contracts. XBRL will then be used as an output method for standardized financial reports based on the data transferred from the blockchain. This paper uses a qualitative research design based on semi-structured interviews with 13 industry experts from IT engineering, academia, and financial systems analysis. NVivo software was used to conduct a thematic analysis of interview transcripts. The findings revealed the technical feasibility, challenges, and benefits of the proposed integration and identified the most efficient mechanism for data transmission across the three technologies. The paper concluded that while integration complexity and user adoption are challenging, this integrated system can revolutionize accounting by enabling real-time data capture, automation of essential operations, data security, and integrity improvements. To our knowledge, this is the first paper to develop a comprehensive accounting information system framework using IoT, blockchain, and XBRL to automate data collection, improve data security, and streamline financial reporting. The study's potential to impact accounting systems and financial reporting research and practice emphasizes its importance.

Full depth precast deck panel (FDDP) is one element of the prefabricated bridge element and systems (PBES) that allows for quick un-shored assembly of the bridge deck on-site as part of the accelerated bridge construction (ABC) technology. This paper investigates the structural response of full-depth precast deck panels (FDDPs) constructed with new construction materials and connection details. FDDP is cast with normal strength concrete (NSC) and reinforced with high modulus (HM) glass fiber reinforced polymer (GFRP) ribbed bars. The panel-to-girder V-shape connections use the shear pockets to accommodate the clustering of the shear connectors. A novel transverse connection between panels has been developed, featuring three distinct female-to-female joint configurations, each with 175-mm projected GFRP bars extending from the FDDP into the closure strip, complemented by a female vertical shear key and filled with cementitious materials. The ultra-high performance fiber reinforced concrete (UHPFRC) was selectively used to joint-fill the 200-mm transverse joint between adjacent precast panels and the shear pockets connecting the panels to the supporting girders to ensure full shear interaction. Two actual-size FDDP specimens for each type of the three developed joints were erected to perform fatigue tests under the footprint of the Canadian Highway Bridge Design Code (CHBDC) truck wheel loading. The FDDP had a 200-mm thickness, 2500-mm width, and 2400-mm length in traffic direction; the rest was over braced steel twin girders. Two types of fatigue tests were performed; incremental variable amplitude fatigue (VAF) loading and constant amplitude fatigue (CAF) loading, followed by monotonically loading the slab ultimate-to-collapse. It was observed that fatigue test results showed that the ultimate capacity of the slab under VAF loading or after 4 million cycles of CAF exceeds the factored design wheel load specified into the CHBDC. Also, punching shear failure mode was dominant in all the tested FDDP specimens.

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.

The purpose of this paper is to explore the impact on corporate social responsibility when Jordanian banks disclose risks. The main objective of the study is to investigate the relationship between risk disclosure and corporate social responsibility in the banking sector in Jordan. To achieve this goal, data was collected from 23 Jordanian banks listed on the Amman Stock Exchange (ASE) over a period of 10 years, from 2010 to 2019. The data was analyzed using a regression model with four independent variables that represent the risk disclosure; corporate social responsibility was used as the dependent variable. The study also built in controls for the age of each bank, its size, leverage, and ROE, to ensure that the results were not affected by these factors. The results of the study show that all independent variables are positively correlated with corporate social responsibility. This suggests that disclosing risks is an effective way to improve corporate social responsibility in the banking industry. The findings of this study have important practical implications for bank managers, future researchers, and policymakers. The study also highlights the importance of future research in this field in order to understand the relationship between risk disclosure and corporate social responsibility in other countries and within other sectors of industry.

Digital transformation systems generate a substantial volume of data, creating opportunities for potential innovation, particularly those driven by artificial intelligence. This study focuses on the intricate relationship between artificial intelligence and innovation as foundational elements in the digital transformation framework for sustained growth and operational excellence. This study provides a holistic perspective on the cultivation and pillars of AI-powered innovation, highlighting their pivotal role in revolutionizing industries, including healthcare, education, finance, manufacturing, transportation, and agriculture. The work emphasizes the key pillars essential for fostering AI-powered innovation, including monitoring performance measurement to use the power of the present, continuous learning and innovation, data analytics and insights, predictive analytics, and innovative product development. This study investigates how these pillars serve as the foundation for groundbreaking advancements, driving efficiency, enhancing decision-making processes, and fostering creativity within organizations. This study explores the significance of continuous learning, interdisciplinary collaboration, and industry partnerships in nurturing a thriving AI-powered innovation ecosystem. By understanding and harnessing these fundamental elements, businesses can navigate the complexities of the digital age, fostering innovation that not only optimizes processes but also enhances the overall human experience, ushering in a new era of technological excellence and societal progress.

The proliferation of mobile and IoT devices, coupled with the advances in the wireless communication capabilities of these devices, have urged the need for novel communication paradigms for such heterogeneous hybrid networks. Researchers have proposed opportunistic routing as a means to leverage the potentials offered by such heterogeneous networks. While several proposals for multiple opportunistic routing protocols exist, only a few have explored fuzzy logic to evaluate wireless links status in the network to construct stable and faster paths towards the destinations. We propose FQ-AGO, a novel Fuzzy Logic Q-learning Based Asymmetric Link Aware and Geographic Opportunistic Routing scheme that leverages the presence of long-range transmission links to assign forwarding candidates towards a given destination. The proposed routing scheme utilizes fuzzy logic to evaluate whether a wireless link is useful or not by capturing multiple network metrics, the available bandwidth, link quality, node transmission power, and distance progress. Based on the fuzzy logic evaluation, the proposed routing scheme employs a Q-learning algorithm to select the best candidate set toward the destination. We implement FQ-AGO on the NS-3 simulator and compare the performance of the proposed routing scheme with three other relevant protocols: AODV, DSDV, and GOR. For precise analysis, we consider various network metrics to compare the performance of the routing protocols. Our simulation result validates our analysis and demonstrates remarkable performance improvements in terms of total network throughput, packet delivery ration, and end-to-end delay.

Mental health issues can have significant impacts on individuals and communities and hence on social sustainability. There are several challenges facing mental health treatment, however, more important is to remove the root causes of mental illnesses because doing so can help prevent mental health problems from occurring or recurring. This requires a holistic approach to understanding mental health issues that are missing from the existing research. Mental health should be understood in the context of social and environmental factors. More research and awareness are needed, as well as interventions to address root causes. The effectiveness and risks of medications should also be studied. This paper proposes a big data and machine learning-based approach for the automatic discovery of parameters related to mental health from Twitter data. The parameters are discovered from three different perspectives, Drugs & Treatments, Causes & Effects, and Drug Abuse. We used Twitter to gather 1,048,575 tweets in Arabic about psychological health in Saudi Arabia. We built a big data machine learning software tool for this work. A total of 52 parameters were discovered for all three perspectives. We defined 6 macro-parameters (Diseases & Disorders, Individual Factors, Social & Economic Factors, Treatment Options, Treatment Limitations, and Drug Abuse) to aggregate related parameters. We provide a comprehensive account of mental health, causes, medicines and treatments, mental health and drug effects, and drug abuse, as seen on Twitter, discussed by the public and health professionals. Moreover, we identify their associations with different drugs. The work will open new directions for social media-based identification of drug use and abuse for mental health, as well as other micro and macro factors related to mental health. The methodology can be extended to other diseases and provides a potential for discovering evidence for forensics toxicology from social and digital media.

Despite the successful reconciliation of special relativity and quantum mechanics (QM), a good century ago, general relativity (GR) in its current classical formulation still does not compile with QM. While GR gives precise sensical predictions at large scales, QM is obviously dominated at small scales! We think that the everlasting battle for exploring and understanding the Universe and for privileging a consistent perception of reality is therefore awaiting a consolidator rather than a conqueror. This should be capable of either unifying the two different benchmarks or at least bringing one closer to the other! The latter describes the consolidating approach, which is based on extending QM to relativistic energies and gravitational fields and generalizing Riemann to discretized Finsler geometry. Some properties of the additional geometric structures and curvatures which are disclosed by the proposed quantization and apparently overlooked in Einstein's GR, are analytically and numerically characterized. The analytical analyses introduce dynamics with possible nonlinear connections. We conclude that i) additional geometric structures and curvatures are intrinsic essential and ii) the spacetime at the quantum scale is no longer smooth or continuous. A maximal proper force is predicted, which maximally gravitationally accelerates a test particle and importantly manifests the quantum geometric nature of the generalized spacetime curvature.

In this paper, we study singularities of the spherical indicatrix and evolute of spacelike ruled surface with spacelike ruling. Finally, we give an example to illustrate our results.

In this study, we mainly focus on the behavior of an electron gas produced by argon plasma that is bounded by a moving rigid flat plate. The effects of an external magnetic field on the electrons collected with each other, with positive ions, and with neutral atoms in the plasma fluid are investigated. We used the BGK model of the Boltzmann kinetic equation, which is fundamental in the study of the gas dynamics from the continuum flow to the free-molecular regimes with Maxwellian velocity distribution functions of the various species. An exact analytical solution of the model equations for the unsteady flow is given using the moment and the traveling wave methods. The behavior of the mean velocity of electrons is illustrated, which compatible with the variation of the shear stress, viscosity coefficient, and the initial and boundary conditions. Besides, the thermodynamic prediction is investigated by applying the principles of irreversible thermodynamics and Gibbs formula. It is found that the thermodynamic variables verify the Boltzmann’s H–theorem, the principle of Le Chatelier, and the Thermodynamics Second Law for the non-equilibrium processes of the system. Qualitative agreements with previous related papers are introducing. 3-Dimensional graphics for the calculating variables are offering, and their behavior is deeply discussed.

Scientific studies on the impact of wood species on solid fuel production, performance, and sustainability are grossly inadequate. The knowledge of this is imperative as users of solid fuels are increasing rapidly, especially in Africa. On this note, it becomes necessary to explore measures that will improve its efficiency and sustainability as an energy source. This study investigates some properties of selected wood species used as an energy source in Nigeria and their pelleting potential. Nine (9) samples were characterized and assessed for suitability of pelleting following four wood pellet quality standards. The findings revealed Anogeissus leiocarpus as the species with the best rating score in terms of fuel properties while Vitellaria paradoxa as the lowest. However, in terms of conformity with the four wood pellets standards, Khaya senegalensis, Parkia biglobosa and Anogeissus leiocarpus having presented density, calorific value, sulfur, arsenic, cadmium, and lead within the limits of the wood pellet quality standards were considered the best wood species in terms of fuel suitability and pelleting potential. The findings therefore suggest that not all wood species are suitable as fuel. Thus, for species that do not meet the standard wood pellet requirements, alternatives such as the use of biomass blends, additives, or process adjustments can be employed to adapt the quality to the standards or by using the fuels in improved cookstoves.

The present paper presents findings from the follow-up of 185 of these nurses who had been involved in the front-line care of COVID-19 patients in urban centres in Northern England, during and after the “second wave” of COVID patients in November, 2020. Measures of adjustment, stress (including PTSD), and Maslowian self-actualization were added to earlier measures of personality, adjustment, work-life stress, and career intention. Cluster analysis identified three types in the 2020-2023 cohort: I ‘Actualizing Professionals’; (N=62); II ‘Strong Professionals’ (N=56); III ‘Highly Stressed Nurses’ (N=45). These latter very stressed nurses included all nurses (N=16) identified as having PTSD symptoms.

This initial report of a longitudinal study of 192 English hospital nurses has measured Nursing Values (the 6Cs of nursing); Personality, Self-Esteem and Depression; Burnout Potential; Work-Life Balance Stress; ‘Hardy Personality’; and Intention to Leave Nursing. Correlational, component and cluster analysis identifies four groups: “The Soldiers” (N = 79) , with medium scores on most measures, who bravely ‘soldier on’ in their nursing roles, in the face of numerous financial cuts to the National Health Service, and worsening nurse-patient ratios; “Cheerful Professionals” (N = 54), coping successfully with nursing roles, and a variety of challenges, in upwardly mobile careers; “High Achievers” (N = 39), senior nurses with strong profiles of a ‘hardy personality’, and commitment to fundamental nursing values; “Highly Stressed, Potential Leavers” (N = 20), with indicators of significant psychological distress, and difficulty in coping with nursing role challenges. We propose a model of co-counselling and social support for this distressed group, by nurses who are coping more successfully with multiple challenges. We discuss the role of nurse educators in fostering nursing values, and developing and supporting ‘hardy personality’ and emotional resilience in recruits to nursing. This study is framed within the disciplinary approach of Critical Realism, which identifies the value basis for research and dialogue in developing strategies for social change.

Artificial intelligence (AI) systems of autonomous systems such as drones, robots and self-driving cars may consume up to 50% of total power available onboard, thereby limiting the vehicle’s range of functions and considerably reducing the distance the vehicle can travel on a single charge. Next-generation onboard AI systems need an even higher power since they collect and process even larger amounts of data in real time. This problem cannot be solved using the traditional computing devices since they become more and more power-consuming. In this review article, we discuss the perspectives of development of onboard neuromorphic computers that mimic the operation of a biological brain using nonlinear-dynamical properties of natural physical environments surrounding autonomous vehicles. Previous research also demonstrated that quantum neuromorphic processors (QNPs) can conduct computations with the efficiency of a standard computer while consuming less than 1% of the onboard battery power. Since QNPs is a semi-classical technology, their technical simplicity and low, compared with quantum computers, cost make them ideally suitable for application in autonomous AI system. Providing a perspective view on the future progress in unconventional physical reservoir computing and surveying the outcomes of more than 200 interdisciplinary research works, this article will be of interest to a broad readership, including both students and experts in the fields of physics, engineering, quantum technologies and computing.

In this article, we are interested in a new generic class of nonlocal fractional impulsive differential inclusions with linear sectorial operator and Lipschitz multivalued function in the setting of finite dimensional Banach spaces. By modifying the definition of PC-mild solutions initiated by Shu, we succeeded to determine new conditions that sufficiently guarantee the existence of the solutions. The results are obtained by combining techniques of fractional calculus and fixed point theorem for contraction maps. We also characterize the topological structure of the set of solutions. Finally, we provide a demonstration to address the applicability of the theoretical results.

Listwaenite rocks are widely spread in Fenja area of the Semail ophiolite of Oman and in Islam Abad area of the Neyriz ophiolite of Iran. There are three types of listwaenites found in these regions: silica-, carbonate-, and carbonate-silica (which includes dolomite, calcite, and magnesite. The alteration of host harzburgites started with hydrothermal alteration to serpentinite, followed by carbonation and silicification of serpentinite. Calcite- and magnesite-dolomite- listwaenites are more abundant in the Fenja area of Oman, while dolomite-listwaenites are more abundant in Islam Abad area in Iran. The mineralogy of listwaenites varies in both Iran and Oman; common minerals include quartz, calcite, goethite, magnesite, dolomite, serpentine, hematite, magnetite, Cr-mica, and Cr-spinel The major element chemistry of the different types of listwaenites in both Fenja and Islam Abad area generally comparable, and is largely similar to that of hydrothermally carbonated harzburgites, serpentinite, and listwaenites worldwide, despite spanning extraordinary and highly variable contents in major oxides, such as CaO, SiO2, MgO and LOI. Relict texture and common occurrence of Cr-spinel as well as the high concentrations of Cr, Ni and Co suggest that the protolith of the listwaenites in both regions was serpentinized harzburgites and serpentines. In comparison to the primary mantle and chondrite in spider diagrams, the Neyriz listwaenites have higher trace and REE element abundances than comparable listwaenites in the Fenja region. Harzburgite-normalized patterns of trace elements and REE in serpentinite and listwaenites overlap the average composition of harzburgite. PM-normalized trace element and REE patterns for serpentinized harzburgite and serpentinite show enrichment in Cs, U, Pb and Sr, with no Eu anomaly, comparable to mantle wedge serpentinites. The variable and high abundances of Ca, Mg, Ba, Zr, Sr, Pb, Zn, Mo and W in the carbonate- and silica-carbonate listwaenites, with unique Si enrichment and Mg, Na2O, Zr, Y, Ba, Sr, Rb, Cu, Pb, Sc, Cs, Nb, Mo and W. depletion in silica listwaenites are indicative of large fluctuations in major and trace element mobility. Cr, Ni and Co were immobile during alteration Enrichment in Ca and Si could occur by internal or late outside supply. Ca, Mg and Si are conceivably the foremost mobile major components amid harzburgite and serpentinite carbonation with mobilization confirmed by formation of quartz and Mg-carbonate in silica-carbonate listwaenites and quartz in silica listwaenites. The listwaenites in Islam Abad and Fenja area were formed due to hydrothermal alteration of serpentinite along thrust faults and shear zones which acted as pathway for Ca and/or Si rich fluids. The intensity of deformation in Islamabad listwaenites has been higher than Fenja listwaenites as indicated by higher abundance of trace elements.

Faba bean (Vicia faba L.) is one of the popular pulse crops grown for traditional consumption, not only in Oman but also in Arabian Peninsula and other countries. In Oman, the famers living in and around high altitude mountain areas mostly grow it. This paper highlights features of variation in seed color and diversity in seed traits found in collected accessions from the joint collecting missions of 2008-2010 between the staff of College of Agriculture, Sultan Qaboos University and the Ministry of Agriculture & Fisheries throughout all the governorates of the Sultanate of Oman. 41 seed samples/accessions were collected from 38 sites. Of these, the highest number of accessions was collected from Batinah South governorate (38) represented mostly by the mountains of Rustaq, followed by the mountains of Interior/Al-Dakhliyah (8), and Dhahira & Buraimi (4). Only one accession was collected from mountains of the Eastern/ Al-Sharqiyah governorates. The seed accessions were found diverse with respect to all seed characters studied, i.e. seed length (cm) and width (cm) and 1000-seed weight (g) besides seed color. The faba bean accessions were classified into 9 genetically diverse clusters based on the Principal Component Analysis, which indicated that the contribution of seed width and 100-seed weight to the total variation existing in indigenous germplasm collected from all the governorates of Oman. It was found from the critical analysis of seed colors that 38 accessions were homogenous (pure) with one color and three were heterogeneous with combinations of colors.

Sodium glucose cotransporter 2 inhibitors (SGLT2i) are currently available for the management of type 2 diabetes mellitus. SGLT2i act by inhibiting renal SGLT2, thereby increasing glucosuria and lowering serum glucose. Recent trials are emerging supporting a role for SGLT2i irrespective of the diabetic status pointing towards that SGLT2i have other mechanisms of actions beyond blood sugar control. In this review, we will shed light on the role of this group of medications that act as SGLT2i in non-diabetics focusing on pre-clinical and clinical data highlighting the mechanism of renoprotection and effects of SGLT2i in the non-diabetic kidneys.

This work investigated the effects of manufacturing variations including coil resistance, initial pod mass, and e-liquid color on coil lifetime and aerosol generation of Vuse ALTO pods. Random samples of pods were used until failure (where e-liquid was consumed, and coil resistance increased to high value indicating a coil break). Initial coil resistance, initial pod mass, and e-liquid net mass ranged between 0.89 to 1.14 [], 6.48 to 6.61 [g], and 1.88 to 2.00 [g] respectively. Coil lifetime with light color e-liquid was (mean) = 149, (standard deviation) = 10.7 puffs while pods with dark color e-liquid was = 185, = 22.7 puffs with a difference of ~36 puffs (p &lt;0.001). Total mass of e-liquid consumed until coil failure was = 1.93, = 0.035 [g]. TPM yield per puff of all test pods for the first session (brand new pods) was = 0.0123, = 0.0003 [g]. During usage, TPM yield per puff of pods with light color e-liquid was relatively steady while it was continuously decreasing for pods with dark e-liquid. Coil lifetime and TPM yield per puff were not correlated with either variation in initial coil resistance or variation in initial pod mass. The absence of e-liquid in the pod is an important factor in causing coil failure. Small bits of the degraded coil could be potentially introduced to the aerosol. There is a potential correlation of e-liquid color with both coil lifetime and TPM yield per puff. Change of e-liquid color might have been a result of oxidation which changed some nicotine into nicotyrine.