Background: Vaccinating children against COVID-19 is an essential public health approach for preventing infection in children and adults. This study aimed to explore parents' attitudes toward and the rate of COVID-19 vaccine hesitancy among children in Oman. Methods: This cross-sectional study used an online, self-administered questionnaire. The 9-item questionnaire was validated earlier and administered between June 2021 and May 2022. Multiple logistic regression was used to determine the factors associated with vaccine hesitancy. The parents received a pre-validated Google questionnaire. Responses from the parents of children younger than 11 years of age were accepted. Results: 384 participants completed the questionnaire, including 207 males (54%). The response rate was 86% (384/447). Of the 384 participants, 69% of the parents hesitated to vaccinate their children aged 1-11-year-old children). In parents of children aged 1–4 years, parental vaccination status was significantly associated with vaccine hesitancy (odds ratio [OR]: 0.116, 95% confidence interval [CI]: 0.044–0.306; p < 0.001). Additionally, vaccine hesitancy was significantly more common in mothers than in fathers (OR: 0.451, 95% CI: 0.240–0.848; p = 0.013). . Mothers of children were 77% more likely to be hesitant than fathers (.78, 95% confidence intervals (CI) = 0.50–0.1.23; p = 0.283). Conclusion: Many parents hesitated to vaccinate their children against COVID-19. Consequently, future awareness campaigns and strategies should target new vaccines. The results of our study show that the Arabic version of the 5-point Likert Scale for Vaccination Hesitancy is a valid and reliable tool.

This study introduces an integrated method for managing process risks in a Business Process Reengineering (BPR) project, using Robust Data Envelopment Analysis (RDEA) and machine learning (ML). The goal is to prioritize risks based on three standard factors of PFMEA: Severity, Occurrence, and Detection (S-O-D), and incorporating two additional factors (Breakdown Cost and Breakdown Duration) seen as undesirable outputs. The model also accounts for the effect of uncertainty on expert-estimated values by applying disturbance percentages in the linear PFMEA-RDEA model. A machine learning model is proposed to predict new values if partial or total modifications have been made to the processes. The approach was implemented in an au-tomotive sector company, and the results showed the impact of uncertainty on values by com-paring different approaches such as RPN, PFMEA-DEA, and PFMEA-RDEA. A new reduced risk categorization was achieved, who allowed for decision-makers to focus on necessary actions for reengineering.

As abiotic stress, drought limits plant growth and minimizes productivity. The increased request for valuable essential oil extracted from geranium (Pelargonium graveolens L.) is mainly associated with plant growth, which is adversely affected by drought. Melatonin (MT) has been used to enhance plant growth under abiotic stress, however, its impact to overcome drought stress of aromatic plants including geranium is poorly investigated. In the current investigation, MT application at 100 µM was applied under 100 % (well-watered) or 50 % (drought stress) of FC to verify this role. Drought stress markedly reduced growth parameters, herb yield, and total chlorophyll; however, MT alleviated these effects. In contrast, drought enhanced the essential oil percentage in geranium leaves. Despite the reduction in oil yield caused by drought, MT application mitigated this reduction and improved both oil yield and oil components. Besides, MT treatment enhanced the accumulation of total phenols, glutathione, and proline and improved the activity of ascorbate peroxidase, catalase, and glutathione reductase with possible alleviation of drought-induced oxidative damage. Therefore, it reduced both H2O2 and malondialdehyde accumulation, and finally maintained membrane integrity. Overall, this is the first report that reveals that MT application can improve geranium resistance to drought by enhancing the antioxidant potential and protecting the cell membrane from oxidative damage.

Diabetes mellitus (DM) is one of the major risk factors for COVID-19 complications as it is one of the chronic immune-compromising conditions especially if patients have uncontrolled diabetes, poor HbA1c &/or irregular blood glucose levels. Diabetic patient’s mortality rates with COVID-19 are higher than cardiovascular or cancer patients. Recently Bacillus Calmette–Guérin (BCG) has shown successful results in reversing diabetes in both rats and clinical trials based on different mechanisms from aerobic glycolysis to Beta cells regeneration. BCG is a multi-face vaccine that has been used extensively in protection from TB and leprosy and has been repositioned for treatment of bladder cancer, diabetes & multiple sclerosis. Recently, the COVID-19 epidemiological study confirmed that universal BCG vaccination reduced morbidity and mortality in certain geographical areas. Countries without universal policies of BCG vaccination (Italy, Nederland, USA) have been more severely affected compared to countries with universal and long-standing BCG policies that have shown low numbers of reported COVID-19 cases. Some countries have started clinical trials that included a single dose BCG vaccine as prophylaxis from COVID-19 or an attempt to minimize its side effects. This proposed research aims to use BCG vaccine as a double-edged weapon countering both COVID-19 & diabetes, not only as protection but also as therapeutic vaccination. The work includes a case study of regenerated pancreatic beta cells based on improved C-peptide & PCPRI laboratory findings after BCG vaccination for a 9 years’ patient. The patient was re-vaccinated based on a negative tuberculin test & no scar at the site of injection of the 1st BCG vaccination at birth. Furthermore, the authors in the present article described a prospective BCG multi-dose clinical study in full details that they will apply in case of acceptance of their submitted grant & the ethical committee approval. The aim of the clinical study is to check if double dose BCG (4 weeks apart) will show a significant difference in the protection of health care professionals in Egypt. The authors suggest and invite the scientific community to take into consideration the concept of direct BCG re-vaccination (after 4 weeks) because of the reported gene expressions & exaggerated innate immunity consequently. As the diabetic MODY-5 patient (mutation of HNF1B, Val2Leu) was on low dose Riomet® while eliminating insulin gradually, a simple analytical method for metformin assay was recommended to ensure its concentration before use as it is not approved yet by the Egyptian QC labs.

Introduction: Blood transfusion involves the transfer of blood from donors to patients. A blood transfusion is carried out every 2 seconds in the US. It is made up of about 29000 units of red blood cells and is transfused every day in the US. When blood transfusion is done correctly, it can result in the saving of lives and the improvement of healthcare. However, it may also lead to immediate, late, delayed, and chronic complications. No previous studies have been conducted in Qatar to address this issue. Methods: This is a cross-sectional study intended to determine the knowledge, attitude, and practice toward blood transfusion among healthcare providers at Hamad Medical Corporation (HMC), which is the principal healthcare provider in Qatar. Participants between 18 and 25 years of age were selected for the research study. A 10-item online questionnaire that people can fill out on their own will be used to get the data needed for the analysis and meet the study's goals. Results: the analysis has indicated that facing negative reactions after blood transfusion and being worried about getting affected by any infection have a small positive association, with the specific values coming in at r = 0.317, p = 0.000. Fever after blood transfusion and feeling like refusing blood transfusion have a significant and moderate positive correlation, with the specific values coming in at r = 0.630 and p = 0.000. Conclusion: The findings of this study have helped us figure out how healthcare providers feel, what they know, and what they do during a blood transfusion.

A lot of research studies have been surveyed the completed genomes of prokaryotic and eukaryotic and focused on the correlation between the percentage of microsatellite sequences in completed genomes and the whole size of the organism genomes. There are fewer studies made in repetitive sequences otherwise simple sequence repeats or long tandem repeats of virus genomes. simple sequence repeats (SSRs) are the most important regions for recombination and moving repeats blocks from site to another site in the genomes. A tool was programmed and designed by visual basic 6.0 to find the long tandem repeats in DNA sequences of the small genomes. The tool named “Repeater Finder Regular Expression”, (RFRE) Version 1.0, 2016. The tool was utilized to discover different pattern of long tandem repeats (LTR) motifs on the completed genomes of human corona virus strains by using a joined regular expression language. In this study, a twenty-nine accession numbers of human coronavirus completed genomes, (hku1) strains were retrieved from the Genbank. The researcher can write a different regular expression patterns and joined regular expression patterns through the designed tool to search and find a specific motif of nucleotide sequences inside the complete genomes. The RFRE tool searched and found three different total lengths of a perfect long tandem repeats (240bp, 300bp and 480bp). A Dot plot gave a picture view for the long tandem repeat sequences in the completed genome sequence (KF430201.1) of human coronavirus. The genomic dot plot tool YASS was used as a genomic similarity searching tool to check for the uninterrupted repeats and confirm the sensitivity of the (RFRE) tool. To identify the recombination site in the genomes of human coronavirus the RAT tool was applied to find the recombination sites between the completed genomes of human corona viruses .The RAT tool recognized the recombination site in the nucleotide position (3012) and at the same time this recombination site position (3012) was also recognized as a beginning position of a long tandem repeat. A precise motif was predicted from the translated repeats of Human Corona Virus which found by PRATT tool. There was a relationship between the total length of long tandem repeats and genome size of Human Corona Virus and the correlation value R² was equal to (0,451). In conclusion, this study presented the importance of finding the long tandem repeats of human coronavirus and gives a relationship between the completed genome size of human coronavirus types and long tandem repeats. The nucleotide position (3012) was a hot spot site for a recombination among the complete genomes of human coronavirus and also identified as a repetitive site in the genomes of human corona virus (hku1). The repeats in human coronavirus (hku1) were predicated to be a main major role of virus evolution.

Maxillofacial fractures are a prevalent occurrence, and the widespread use of miniplates to stabilize and secure these fractures during surgery is common. However, the post-surgical fate of these miniplates remains a subject of contention among surgeons. Some advocate for their removal, while others suggest leaving them in place. This study aims to perform an extensive meta-analysis of pertinent studies to ascertain the destiny of miniplates employed in maxillofacial surgery and discuss the consequences of either their extraction or retention. To execute this meta-analysis, an exhaustive search was conducted across multiple databases, encompassing PubMed, Scopus, and Google Scholar. Keywords such as "titanium miniplates," "screws," "maxillofacial surgery," "complications," and "removal" were utilized to identify pertinent studies. The search was constrained to studies published between 1989 and 2022. The analysis encompassed only studies reporting outcomes related to miniplates in maxillofacial surgery, including complication rates and removal frequencies. Eleven studies conformed to the inclusion criteria and were incorporated into the meta-analysis, encompassing a total of 2240 patients. All the studies had a retrospective design, with the largest study involving 800 patients. The overall complication rate was determined to be 13.3%. The most prevalent reasons for miniplate removal included patient preference, tooth extraction, and infections. The average time span for miniplate removal was 10.7 months, with the most prolonged reported duration being 24 years. These findings imply that immediate removal might not be imperative in the majority of instances. In conclusion, our meta-analysis underscores the necessity of removing miniplates in cases where hardware leads to a variety of complications and physical discomfort. Principal factors driving plate removal included patient requests, tooth extractions, and infections. Ordinarily, plate removal took place within the span of 6 to 12 months, with the mandible being the most frequent site for removal. These findings accentuate the significance of extended monitoring to assess the trajectory of miniplates in maxillofacial surgery and provide valuable insights for future clinical decisions. To validate these conclusions and gain deeper insights into the factors influencing plate removal in maxillofacial surgery, further research with larger participant cohorts and standardized outcome reporting is imperative.

Fractional differential systems have received much attention in recent decades likely due to its powerful ability in modeling memory processes, which are mostly observed in real world. Fractional models have been widely investigated and applied in many fields such as physics, biochemistry, electrical engineering, continuum and statistical mechanics. It is shown by many researchers that fractional derivatives can provide more accurate models than integer order derivatives do. Obviously, bang-bang property is of a significant importance in optimal control theory. In this paper a Bang-Bang property and time-optimal control problem for time-Fractional Differential System (FDS) is under consideration. First we formulate our problem and we prove the existence theorem. We state and prove the bang-bang theorem. Finally we give the optimality conditions that characterized the optimal control. Some illustrate applications are given to clarify our results.

The use of miniplates for stabilizing bones after orthognathic surgeries, has become increasingly popular for their effectiveness in ensuring stability and promoting swift recovery. However, the post-surgical fate of these miniplates remains a subject of contention among surgeons. Some advocate for their removal, while others suggest leaving them in place. The aims of this study, is to evaluate the incidence, causes, and potential risk factors associated with the removal of miniplates in orthognathic surgeries. A comprehensive meta-analysis was conducted by reviewing studies from various databases like PubMed, Google Scholar, Research Gate, Embase, and Scopus, focusing on publications from 1989 to 2023. Ten studies encompassing a total of 1603 patients which conformed to the inclusion criteria were selected and included in the meta-analysis. With M:F ratio range from 4:1 to 109:141. Total number of miniplates inserted was 5595, and total number of miniplates removed were 294 (5.3%). The most common reasons for miniplates removal were, infection was reported in 161 cases (2.9%), followed by miniplates exposure (34 cases, 0.6%) and palpable plates (23 cases 0.4%). Other indications included pain, patient’s preference, and temperature sensitivity. Relatively less common reasons that resulted in miniplates removal include, sinusitis, second surgery and dental pathology. The mean duration of miniplates removal was 5.5 months with the majority of miniplates (56.1%) were removed from the mandible compared to maxilla. In conclusion, this meta-analysis underscores the importance of miniplate removal in cases where hardware causes diverse complications and physical discomfort. The primary reasons for miniplates removal were infections and plates exposure, with the mandible being the most common site for removal. These findings emphasize the need for continued monitoring to assess the fate of miniplates in orthognathic surgery and provide valuable insights for future clinical decision-making.

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.

In this study, our goal was to research land-use change by combining spatio–temporal land use/land cover monitoring (LULC (1989–2019) and urban growth modeling (1999–2039) in Benslimane, Morocco, to determine the effect of urban growth on different groups based on cellular automata (CA) and geospatial methods. A further goal was to test the reliability of the AC algorithm for urban expansion modeling. To do this, four years of satellite data were used at the same time as population density, downtown distance, slope, and ground road distance. The LULC satellite reported a rise of 3.8 km2 (318% variation) during 1989–2019. Spatial transformation analysis reveals a good classification similarity ranging from 89% to 91% with the main component analysis (PCA) technique. The statistical accuracy between the satellite scale and the replicated built region of 2019 gave 97.23 %t of the confusion matrix overall accuracy, and the region under the receiver operational characteristics (ROC) curve to 0.94, suggesting the model's high accuracy. Although the constructed area remains low relative to the total area of the municipality's territory, the LULC project shows that the urban area will extend to 5,044 km2 in 2019, principally in the western and southwestern sections. In 2019–2039, urban development is expected to lead to a transformation of the other class (loss of 1,364 km2), followed by vegetation cover (loss of 0.345 km2). In spatial modeling and statistical calculations, the GDAL and NumPy Python 3.8 libraries were successful.

Direct Energy Deposition (DED) is a versatile and efficient method in metal additive manufacturing. However, humping, caused by abnormal dynamics in the melt pool (MP), poses a significant threat to the geometric integrity of manufactured products. Current state-of-the-art (SOTA) methods primarily detect humping by analyzing late-stage spatial abnormalities, such as MP detachment. This approach is fundamentally reactive, leading to a tendency to miss early humping spatiotemporal dynamics, like cyclic elongation of the MP. This study introduces a novel, proactive indicator named VIMPS (Variability of Instantaneous MP Solidification-Front Speed), a physics-based tool designed to quantify early abnormal fluctuations in MP solidification speed. The experiments demonstrate VIMPS correlation with humping-induced geometric inaccuracies. By capturing early spatiotemporal dynamics of the MP, VIMPS reduces detection latency by 30 seconds compared to existing SOTAs that focus solely on spatial abnormalities. This significant improvement transforms detection from reactive to proactive, providing the time needed for corrective actions to enhance the overall productivity and quality of the DED process.

This study involved the fabrication of a set of Aluminum ion-grafted SBA-15 utilizing ethylene-diamine and trimethylamine ionic liquids. The primary objective was to examine the impact of the fabrication environment on the physicochemical characteristics of the catalysts. Comprehensive characterization of the Al-SBA-15 catalysts was conducted using various techniques, including XRD, FTIR, surface area, pyridine FTIR, 27Al-NMR, TGA, HRTEM, and FESEM, to analyze their physicochemical characteristics. Furthermore, the acidic characteristics were examined by con-ducting potentiometric titration in a nonaqueous solvent and employing FTIR spectroscopy to an-alyze the chemisorbed pyridine. The effectiveness of the fabricated acid materials was evaluated by testing their performance in the acetic acid esterification with butanol. The findings obtained reveal that the mesostructured of SBA-15 remains intact following the successful inclusion of Al3+ ions into the silica frameworks. Additionally, a remarkable enhancement in the existence of both Bronsted and Lewis acid centers is noted due to the grafting process of Al3+ ions. At temperatures of 80°C and 100°C, the reaction in Al-SBA-15(T-120) proceeds swiftly, reaching approximately 32% and 38% conversion, respectively, within a span of 110 minutes. The excellent catalytic performance observed in the esterification reaction can be attributed to two factors: the homogeneous distribution of Al3+ ions within the SBA-15 frameworks and the acidic character of Al-SBA-15. The findings further indicate that the grafting process for incorporating Al3+ ions into the silica matrix is more efficient.

Due to a lack of knowledge about arthropod biodiversity in Egyptian organic agro-ecosystems; the study aimed to introduce information on the diversity, richness, and distribution of insect and mite species in two organic agro-ecosystems, also, to investigate the impact of plant-arthropod interactions. Samples collected from two organic farms, i) Shampoliah farm, Fayoum (GCS 29°21'07.4"N 30°44'17.8"E), and ii) SEKEM farm, Sharkia (GCS 18 30°22'56.1"N 31°39'17.4"E). Results shown 39 species recorded in Shampoliah farm, and 35 species in SEKEM of mite, insect, medicinal, and weed species. When 14 species shared among two sites. Study has measured the H', D and 1/D indices within each location, and the similarity/dissimilarity between locations. The study hypothesized the possible plant-arthropod interactions that explain why diversity differs from an ecosystem to another; due to; plant size, plant morphological characters, soil fertilization, plant nutritional content, and the prey-predator interactions. The added hypothesis; is to show that the importance of natural habitat is supporting natural enemies and distribution of arthropods, which could vary dramatically with the type of pest species, IPM, and landscape type considered.

The main objective of the present study was to investigate arsenate [As (V)] resistance genes in rice cultivars grown in arsenic contaminated Egyptian soil in order to genetically induce resistance against arsenic in the local rice varieties as well as defining contaminated rice grains and/or soil. Three local rice cultivars; Sakha 102-104 were cultivated on modified Murashige and Skoog Basal Medium (MS medium) containing elevated concentrations of arsenate (0.1, 1 and 10 mg/l). The three varieties showed different resistant attitudes against arsenate with Sakha 104 being the most resistant. Extracted messenger RNA (mRNA) from treated and untreated Sakha 104 plantlets was scanned using differential display to demonstrate the arsenate resistant genes using three different arbitrary primers. About 100 different RNAs with (1500 bp - 50 bp) were obtained from which seven were up-regulated genes, subjected to DNA cloning using TOPO TA system and the selected clones were sequenced. The sequence analysis described four genes out of the seven namely disease resistance protein RPM1, Epstein-Barr virus EBNA-1-like, CwfJ family protein and outer membrane lipoprotein OmlA while the other three genes were hypothetical proteins. It is concluded the four induced genes in the resistant rice cultivar considered as a direct response to arsenic soil pollution. Genes detected in the present study can be used as geno-sensors for rice grains and soil contamination with As (V). Moreover, local rice cultivars may be genetically modified with such genes to induce high resistance and to overcome arsenic soil pollution.

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.

Three hundred ten 12-wek-old laying quails (155 each) were randomly selected from the initial population and kept in individual battery cages. The measurements of growth and egg production were determined to derive RFI. The relationship between RFI and egg quality, blood parameters and carcass characteristics was also determined. The results indicated that the gray quails had significantly higher egg mass and lower broken eggs compared to the white quails. A significant increase for eggshell strength and shell % was found in eggs produced from gray quails compared to white counterparts, although the shell thickness was the same. The results of multiple regression analysis clearly identified a significant effect of metabolic body weight and egg mass in computing expected feed intake rather than body weight gain in both varieties of Japanese quails. Strongly positive correlation between RFI and feed intake in both gray and white quail varieties was found. The same trend was also observed for feed conversion ratio (FCR). Therefore, including RFI in selection criteria of Japanese quail to improve FCR under high environmental temperature is highly recommended.

Alzheimer's disease is a multifactorial neurodegenerative disorder, with Acetylcholinesterase, Butyrylcholinesterase, Beta secretase, Glycogen Synthase Kinase beta and Monoamine oxidase B playing central role in it's pathogenesis. Therefore, this research aims to discover potential curative multitarget drugs derived from African natural products capable of addressing the multifactorial characteristics of the disease. In silico approaches were used to filter a 880 african natural compounds library based on selected pharmacokinetic properties. Molecular docking against the five aforementioned proteins, followed by Molecular Mechanics with Generalised Born and Surface Area Solvation scoring for the top compounds were used to assess binding. Density Functional Theory studies were used to assess electronic transitions. Pharmacokinetic filters resulted in 200 compounds, of which only five were selected after molecular docking. Density Functional Theory and Molecular Mechanics with Generalised Born and Surface Area Solvation scoring resulted in 3 potential multitarget compounds. Compound 157 (ZINC000095485950) showed triple-target inhibitory activity against Butyrylcholinesterase, Glycogen Synthase Kinase beta and Beta-secretase, while compounds 159 (ZINC000095485952) and 696 (ZINC000039144622) showed dual-target inhibitory activity against Butyrylcholinesterase and Glycogen Synthase Kinase beta. Molecular dynamics simulation and further experimental assessments are suggested.

In this paper we designed system for smart university building based on artificial intelligence (AI) and internet of things (IOT). Our idea can be summarized in smart security system that has different sensors to detect the surrounding environment of the class room in campus which keep everyone and everything on campus safer. By using (IOT), (AI) technologies and applications and by using microcontroller programming we can make the university building safer, secure and more energy saves.

Three-dimensional (3D) facies and petrophysical models were generated from previously published data of carbonate strata in the Dam Formation (eastern Saudi Arabia) to quantitatively investigate, describe, understand, model, and predict the permeability anisotropy of tidal flat carbonate within a sequence stratigraphic framework. The resulting 3D models were used to conduct fluid flow simulations to demonstrate how permeability anisotropy influences the production of hydrocarbons and ultimately affects decisions concerning future drilling in the exploration and development of carbonate reservoirs that have tidal flat strata. The constructed 3D facies model consists of four lithofacies associations, two of which were grain-dominated associations and two of which were mud-dominated associations. These lithofacies associations varied spatially in four reservoir zones (zones 1 to 4), which represent two fourth-order sequences in the uppermost part of the Dam Formation. Zones 1 and 3 consist of transgressive parasequences, and zones 2 and 4 consist of the regressive parasequences of these sequences. The 3D porosity and permeability models have a coherent match with the distribution of the lithofacies and the stratigraphic framework of the Dam Formation. The results suggested that the permeability anisotropy in zones 1 and 3 is controlled by the occurrence of the grain-dominated lithofacies associated with tidal flat channels. This lithofacies association overlies the sequence boundaries of sequences 1 and 3, forms reservoir bodies with relatively high permeability values, and is elongated perpendicular to the shoreline of the depositional environments. In contrast, permeability anisotropy in zones 2 and 4 is thought to be controlled by the occurrence of the grain-dominated lithofacies associated with the oolitic shoal. This lithofacies association overlies the maximum flooding surface of sequences 2 and 4, forms reservoir bodies with relatively high permeability values, and is elongated parallel to the shoreline of the depositional environments. Fluid flow simulation results suggested that the trend in hydrocarbon production from the constructed 3D models depends on permeability anisotropy in each reservoir zone. Thus, recognizing trends in permeability anisotropy, which might be predicted using sequences stratigraphy, could help to identify potential areas for future drilling.

Background: Fine-needle aspiration cytology (FNAC) is widely used to diagnose and monitor thyroid nodules. The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) is the standard for interpreting FNAC specimens. The risk of malignancy in Bethesda III nodules also known as Atypia of Undetermined Significance (AUS) varies significantly throughout several studies published worldwide. This retrospective study examines the risk of cancer in thyroid FNAC categorized as Bethesda III, as identified in the final histopathology of thyroidectomy specimens at a single endocrine surgery center. Methods: This retrospective cohort analysis included 1038 consecutive patients who underwent elective thyroid surgery with complete follow up data between January 2020 and March 2024. Preoperative data on clinical and pathological characteristics have been collected. The final histopathology report from the thyroidectomy specimen was compared to the results of the preoperative FNAC on nodules that were judged to be Bethesda category III. Statistical methods were performed using SPSS version 29. Results: A total of 670 ultrasound-guided FNACs (64.5%) performed during the study period were included in the final analysis. The study population was predominantly female, represented by 79.6% of patients with a mean age of 42.5 (SD 12.1), while 20.4% were male and significantly older with mean age 45.13 years (p = 0.02). The FNAC inadequacy rate was 5.1%, which was associated with a high risk of malignancy (6 out of 34, 17.6%). Out of the total sample size of 170 patients classified as group III, 57 were found to have malignancies in final surgical histopathology, representing 33.5% of the cases within this category. The secondary gender-related outcome analysis showed that female patients classified under the Bethesda II category had a significantly higher risk of malignancy, with a rate of 21.2%, compared to males who had a malignancy rate of 3.4% in the same Bethesda category (p = 0.001, chi square test). However, female had more better prognostic non-invasive tumors than male (p = 0.02, chi square test). Conclusion: The study's results indicate that Bethesda categories II and III are associated with a higher risk of malignancy in comparison to the reports of the first and third editions of the TBSRTC, particularly for female patients classified under category II.

Introduction: Hypertension is a serious public health problem in Morocco. The objective of this pilot study was to estimate the salt intake of Moroccan adults by measuring 24-hour urinary sodium excretion. Methods: 132 participants were recruited from the central region of Morocco. Sodium, potassium and creatinine levels were measured using the 24-hour urine samples. Additional data included anthropometric measurements and socio-demographic questionnaire. Results: The daily sodium, potassium and creatinine excretions were 2779.1±1334.9 mg, 1350.0±642.8 mg and 820.3 ± 381.2 mg, respectively. Data analysis revealed that 71.2% of the participants had a daily sodium intake more than 2000 mg (5g of salt) recommended by the WHO. The mean of potassium excretion was 1350.0±642.8 mg /day, this average was lower than 3.51g per day recommended by the WHO. Conclusion: Public health measures to reduce sodium and increase potassium consumption in order to decrease the population’s risk of high blood pressure and heart disease are recommended.

Exotic plants are usually problematic for the native species where they coexist. This study evaluated the effect of naturalised alien Cenchrus echinatus L. on native plants in the urban vegetation. A field trial was conducted to assess the effect of this species on cover and diversity of the native vegetation. The allelopathic potential of such species was examined. Plots comprising C. echinatus had lower cover of some native species. Lower floristic diversity was observed at more dense cover of this plant. The soil under Cenchrus attained lower N, P and K contents. This soil had no effect on germination and growth of the native species. It also comprised germinable seeds of some species which were absent from the standing vegetation. Exotic C. echinatus may exert a negative effect on the native vegetation of the urban plant communities. Dense cover of Cenchrus may inhibit germination of native species, leading to reduction in their cover. The reduction in cover and diversity of native species was not attributed to allelopathy. These results suggest that naturalised C. echinatus may be more competitor than the native ones, particularly at higher densities. Furthermore, it may represent a threat for the native plants in the urban vegetation.

The requirement for developing tools capable of detecting and monitoring heavy metals (HMs) has recently taken on more significance due to worries about their toxic effect on human health and aquatic habitats. In this study, a simple electrochemical sensing carbon paste electrode (CPE) based on composite of Zinc/Iron layered double hydroxide (LDH) and polyaniline (PANI) was developed for the determination of lead ions in aquatic solutions. For this purpose, Zn-Fe LDH/PANI was prepared and characterized by Fourier transform infrared (FTIR), X ray diffraction (XRD), and scanning electron microscopy (SEM). Modified carbon electrode based Zn-Fe LDH/PANI was electrochemically characterized compared with unmodified electrode in FCN as a redox probe using cyclic voltammetry (CV). Thus, Zn-Fe LDH/PANI was utilized as sensing material for the electrochemical determination of lead ions using differential pulse voltammetry (DPV). Zn-Fe LDH/PANI/CPE show limits of detection (LOD) and quantification (LOQ) of 167.8 nM and 559.4 nM, respectively. Zn/Mg/Fe LDH was prepared using co-precipitation method and characterized by XRD, FTIR, SEM and BET, used for removal of Pb+2 ions. Removal process was investigated at different conditions as pH, metal ion concentrations, starting adsorbent dose at first and contact time. Zn/Mg/Fe LDH was evaluated as an effective adsorbent material for lead ions elimination in aquatic solutions, with capacity of adsorption 700 mg/g. The elimination of lead ions on Zn/Mg/Fe LDH fitted the pseudo first-order kinetics model and the isotherm was matched with Langmuir model. Studies revealed that the ideal removal conditions were pH = 5.0, an adsorbent mass of 0.05 g, and 20 ml of 50 ppm metal ion concentration at 60 min. The Zn-Fe LDH/PANI composite also showed potential anti-cancer properties against lung cancer cells (A549) while maintaining safety for normal lung fibroblast cells (WI-38). Collectively, advancements in electrochemical sensors offer promising solutions for lead ion detection, with wide-reaching applications in wastewater treatment and cytotoxicity assessment. These innovations have the potential to enhance environmental monitoring and public health safety.

Facial emotion detection is a challenging task that deals with emotion recognition. It has applications in various domains, such as behavior analysis, surveillance systems and human-computer interaction (HCI). Numerous studies have been implemented to detect emotions, including classical machine learning algorithms and advanced deep learning algorithms. For the machine learning algorithm, the hand-crafted feature needs to be extracted, which is a tiring task and requires human effort. Whereas in deep learning models, automated feature extraction is employed from samples. Therefore, in this study, we have proposed a novel and efficient deep learning model based on Neural Architecture Search Network utilizing superior artificial networks such as RNN and child networks. We performed the training utilizing the FER 2013 dataset comprising seven classes: happy, angry, neutral, sad, surprise, fear, and disgust. Furthermore, we analyzed the robustness of the proposed model on CK+ datasets and comparing with existing techniques. Due to the implication of reinforcement learning in the network, most representative features are extracted from the sample network. It extracts all key features without losing the key information. Our proposed model is based on one stage classifier and performs efficient classification. Our technique outperformed the existing models attaining an accuracy of 98.14%, recall of 97.57%, and precision of 97.84%.

Quite a number of cottonseed varieties are existed. The seeds of each variety produce a different amount of gossypol as a natural toxic compound. The increased interest in this natural product and its toxic effects were enhanced the demand for establishing simple silica-gel-based methods for its isolation, purification, and characterization. Historically, silica gel plays a significant role in isolation and purification of many different natural products. Silica gel is variants and can intro-duce a lab, simple tool for tracking a compound in certain plants during its purification process. In this study, gossypol was isolated and purified in the form of yellow crystals as gossypol acetic ac-id. Several methods and tools were used for its characterization including TLC, preparative TLC, silica gel column, UV/IR spectrophotometer and HPLC (Robust spherical silica gel). A compara-tive study between its amounts in both Egyptian and Chinese varieties were performed. Under the experimental condition, the Egyptian cottonseeds contain 8.705 gm/kg, while the Chinese contains 5.395 gm/kg. Thin Layer Chromatography (TLC) had been flourished the science of the phytochemistry and still popular till nowadays and is recommended for fast, accurate, and inex-pensive evaluation and quantification of gossypol. It is recommended to isolate and purify gossy-pol as gossypol acetic acid using optimized combined methods used in this study. Using Silica gel different protocols will assist and facilitate the parallel comparison and save the compact column from any unexpected contaminants during the purification steps. During each step the silica gel itself could be simply removed by paper filtration.

Abstract: This paper aimed to investigate the entrepreneurial intentions of female students in Saudi Arabia, utilizing the Theory of Planned Behavior (TPB) as the theoretical framework. Employing a quantitative research methodology, data was collected through a questionnaire administered to female students at Princess Nourah University. The results revealed a positive inclination towards entrepreneurship, with over 64% expressing a desire to pursue entrepreneurial ventures in the future. This optimistic trend among female students suggests a potential pool of future entrepreneurs. Interestingly, a small percentage (3.21%) categorically rejected entrepreneurship as a career option, indicating a relatively low level of disinterest in entrepreneurial pursuits. However, many respondents (32%) remained undecided, presenting a valuable opportunity for mentorship and support to cultivate their entrepreneurial intentions. These findings underscore the significance of providing guidance and education to encourage entrepreneurship among female students. The TPB analysis highlighted that attitudes and perceived behavioral control towards entrepreneurship were favorable among female students, indicating a positive mindset and belief in their ability to embark on entrepreneurial endeavors. However, societal norms still exert a negative influence on some student’s entrepreneurial intentions, suggesting a need to address cultural barriers that might hinder female students' willingness to pursue entrepreneurship. The study suggests enhancing female entrepreneurship through societal encouragement and support from personal networks. It highlights the importance of fostering entrepreneurial aspirations in female students. Crucially, the study underscores the role of universities in cultivating entrepreneurial intentions by proposing the implementation of entrepreneurship-focused curricula and the creation of university-based training units or incubators.

Introduction: Hospitalization in a COVID-19 unit represents a significant source of stress and psychological distress for patients. Our study aims to determine the factors of psychological distress in the therapeutic and psychosocial management of patients hospitalized with a COVID-19 infection. Methods: This cross-sectional study was carried out over 8 months at the COVID-19 zone of the CHU HASSAN II of FES. 99 patients were evaluated within days of diagnosis by psychometric scales of anxiety, depression, and post-traumatic stress. In the course of this follow-up, we found the presence of psychological impacts in these patients, and we tried to find correlating factors between the occurrence of psychiatric disorders and the set of factors related to sociodemographic data, hospitalization course and treatments taken, as well as family support. Results: 35% of patients had scores in favor of post-traumatic stress disorder, 37% of the patients had definite depression and 50% had anxiety. Post-traumatic stress, depression, and anxiety were correlated with sociodemographic factors, hospitalization, treatments received, and length of stay. Conclusion: The prevalence of anxiety-depressive disorders and post-traumatic stress disorder was high in patients with COVID-19, hence the interest in providing psychological and psychosocial care in the emergency department.

This study challenges the prevailing belief in the necessity of complex models for accurate forecasting by demonstrating the effectiveness of parsimonious econometric models, namely ARCH(1) and GARCH(1,1), over deep learning robust approaches, such as LSTM and 1D-CNN neural networks, in modeling historical volatility within pre-emerging stock markets, specifically the Moroccan and Bahraini stock markets. The findings suggest reevaluating the balance between model complexity and predictive accuracy. Future research directions include investigating the potential existence of threshold effects in market capitalization for optimal model performance. This research contributes to a deeper understanding of volatility dynamics and enhances forecasting models’ effectiveness in diverse market conditions.

As prominent oil producers, the Gulf Cooperation Council (GCC) countries have played a significant role in the global energy market. However, as the world's attention increasingly shifts towards environmental sustainability, understanding the implications of the GCC's economic activities on CO2 emissions becomes indispensable. This research paper investigates the relationship between specific economic indicators and their impact on CO2 emissions in the GCC from 2001 to 2021. The study employs quantile regression, a powerful statistical method that estimates the conditional quantiles of a response variable given a set of predictor variables. The findings reveal several important insights: Financial institution efficiency is significant and negative at a 1% level at the lower (10th) -83537.3 and the higher quantile (90th) -549002.3. The relationship between GDP per capita and CO2 emissions varies across quantiles, highlighting the complexity of the growth-environment nexus. Total patents exhibit a positive and significant relationship with emissions, underscoring the importance of directing innovation towards environmentally sustainable solutions. Renewable energy consumption displays a nuanced relationship with CO2 emissions, with a stronger negative impact observed at higher consumption levels. This underscores the potential of renewable energy to mitigate emissions when integrated at scale. The study's outcomes hold crucial policy implications for the GCC countries as they seek to align economic growth with environmental sustainability. The findings emphasize the importance of fostering financial institution efficiency, promoting green innovation, and expanding renewable energy sources to reduce emissions

(1) Background: Factors reported in literature associated with inappropriate prescribing of antimicrobials, such as physicians with less experience, uncertain diagnosis, and patient caregiver influences on physicians' decisions. Monitoring antimicrobial resistance is critical for identifying emerging resistance patterns, developing, and assessing the effectiveness of mitigation strategies. Improvement in prescribing `antimicrobials would minimize the risk of resistance and, consequently, improve patients' clinical and health outcomes. The purpose of the study is to delineate factors associated with antimicrobial resistance, describe the factors influencing prescriber’s choice during prescribing of antimicrobial, and examine factors related to consequences of inappropriate prescribing of antimicrobial. (2) Methods: Cross-sectional study conducted among healthcare providers (190) in six tertiary hospitals in the Eastern province of Saudi Arabia. The research panel has developed validated and piloted survey specific with closed-ended questions. A value of P &lt;0.05 was considered for statistical significance. All data analysis was performed using Statistical Package for Social Sciences (IBM SPSS version 23.0). (3) Results: 72.7% of the respondents have agreed that poor skills and knowledge are key factors that contribute to the inappropriate prescribing of antimicrobials. All the respondents acknowledged effectiveness and previous experience with the antimicrobial, and reading scientific materials (such as books, articles, and the internet) were key factors influencing physicians’ choice during antimicrobial prescribing. (4) Conclusion: The current study has identified comprehensive education and training needs for healthcare providers about antimicrobial resistance. Using antimicrobials unnecessarily, insufficient duration of antimicrobial use, and using broad spectrum antimicrobials, were reported to be common practices. Further, poor skills and knowledge were a key factor that contributed to the inappropriate use and overuse of antimicrobials and using antimicrobials without physician prescription (self-medication) were the key factors which contribute to AMR from participants’ perspectives. Furthermore, internal policy and guidelines are needed to ensure that the antimicrobials are prescribed in accordance with standard protocols and clinical guidelines.

Breast cancer is the most widespread malignancy in women from corner to corner of the world. Nanostructured lipid carrier (NLC) proved its efficacy in the treatment of cancer. NLC loaded with Imatinib (IMA) (NANIMA) was prepared and evaluated for in vitro efficacy in MCF-7 breast cancer cells. Hot homogenization method was used for the preparation of NANIMAs. Aqueous solution of surfactants (hot) was mixed with molten mixture of stearic acid and sesame oil (hot) under homogenization. The prepared NANIMAs were characterized and evaluated for size, polydispersity index, zeta potential, encapsulation efficiency, release studies, stability studies and MTT assay (cytotoxicity studies). The optimized NANIMA revealed particle size of 104.63 ± 9.55 d.nm, PdI of 0.227 ± 0.06 and EE of 99.79 ± 0.03. All NANIMAs revealed slow and sustained release behaviour. The surfactants used in the preparation of NANIMAs exhibited their effects on particle size, zeta potential, encapsulation efficiency, stability studies and release studies. The cytotoxicity studies unveiled 8.75 times increase in cytotoxicity for optimized NANIMA (IC50 = 6 µM) when compared with IMA alone (IC50 = 52.5 µM) on MCF-7 breast cancer cells. After this, NLC containing IMA possibly will be employed for the cure of breast cancer. A lesser amount of IMA loaded NLC will be sufficient than IMA alone for the treatment of breast cancer. Moreover, the patient will exhibit not as much of adverse effects as in case of IMA alone. Consequently, NANIMA could prove to be useful for effective therapeutic outcome in breast cancer treatment.

Failaka Island is located 20 kilometers east of the Kuwait mainland. The island includes archaeological sites dating back to the Bronze, Hellenistic, Christian, and Islamic ages. To develop the island as a tourist attraction the state is pursuing a new urban plan based on the island's environmental potential. This study is the basis of the urban plan depends on environmental criteria from the view of Geoarchaeology. The study analysis the land-use and land-cover changes of Failaka Island between 1958- 2018. It provides a topographic survey of the island's coastline and a classification of its geomorphological features and a state of the art identification of its archaeological sites by using a drone to make a terrain model. The study used a medium to high-resolution image analysis of the land-use and land-cover changes: WorldView2-50cm 2010 and 2018; Landsat 8; aerial photography; Drone images and a digital elevation model (DEM), to analysis the expected sea level changes by the end of this century. This study also created a geodatabase of the island that can be adapted for future studies. The results emphasize the importance of preserving the historical and ecological features of the island while developing its infrastructure.

Interactive Digital Media have become the most important pillars on which contemporary 21st century scenography is based, allowing for the use of many modern digital media as scenographic elements. With the steady development of digital arts, particularly digital animation, it has become a key role as a 21st century in presenting their theatrical visions. My own issue is the use of digital Media as an Interactive scenographic element, as evidenced by the design of several spatial environments within the framework of an idea and a dynamic scenario that interacts with the Several Scenes of the theatrical Performances and is displayed on screen walls or dropped on thematic elements, resulting in a type of interaction between them and the Scenic Design. My project includes instances of models exhibiting the link of designs to theme composition on stage, such as works utilized in plays, musical/motion drama, and event performances . The design used music synced with digital animated media designs as a scenographic element to reinforce the overall visual picture. The study paper examines a theory of my own project, in which I offer a dynamic exhibition of full-back digital settings in rhythm with the music, suited to its movement and the character of the performance, to be employed as a Scenographic element at a Proscenium Theater (12W x 10D x 7H).

The coexistence of SAH with T2DM is a common comorbidity. In this present study, we investigated the link between altered plasma antioxidant trace elements (ATE: Manganese, Selenium, Zinc and Copper) and fatty acids ratio (FAR: polyunsaturated/saturated) imbalance as transition biomarkers between vascular pathology (SAH) to metabolic pathology (T2DM). Our data revealed strong correlation between plasma ATE and FAR profile which is modified during SAH-T2DM association compared to healthy group. This relationship is mediated by lipotoxicity (simultaneously prominent visceral adipose tissue lipolysis, significant flow of non-esterified free fatty acids release, TG-Chol-dyslipidemia, high association of Total SFA, Palmitic acid, Arachidonic acid and PUFA 6/ PUFA 3; drop in tandem of PUFA / SFA and EPA+DHA); oxidative stress (lipid peroxidation confirmed by TAS depletion and MDA raise, concurrently drop of Zn/Cu-SOD, GPx, GSH, Se, Zn, Se/Mn, Zn/Cu; concomitantly enhance Cu, Mn and Fe); endothelial dysfunction (endotheline-1 increase); athero-thrombogenesis risk (concomitantly raise of ApoB100/ApoA1, Ox-LDL, tHcy and Lp(a)) and inflammation (higher of Hs-CRP, Fibrinogen and Ferritin). Our study open to new therapeutic targets and to better dietary management, such as to establish dietary ATE and PUFA 6 / PUFA 3 or PUFA / SFA reference values for atherosclerotic risk prevention in hypertensive-diabetics patients.

Change Detection (CD) of aerial images refers to identifying and analyzing changes between two or more aerial images of the same location taken at different times. The CD is a highly challenging task due to the need to distinguish relevant changes, such as urban expansion, deforestation, or post-disaster damage assessment, from irrelevant ones, such as light conditions, shadows, and seasonal variations. Many CD papers have recently been published, where most of the papers that proposed a new model contained a comparison between their proposed and state-of-the-art (SOTA) models. While many recent studies propose new deep learning (DL) models for improving CD performance, their comparative analyses are often restricted, lacking comprehensive insights into the proposed models' real-world generalizability, robustness, and performance trade-offs across diverse change characteristics. This paper presents a novel generic framework to systematically benchmark and assess DL-based CD models through three parallel pipelines: 1) cross-testing models on diverse benchmark datasets to evaluate generalization, 2) robustness analysis against different image corruptions, and 3) multi-faceted contour-level analytics evaluating detection sensitivity to change size/complexity. The framework is applied to comparatively evaluate five state-of-the-art DL-based CD models - Changeformer, BIT, Tiny, SNUNet, and CSA-CDGAN. Extensive experiments unveil each model's strengths, limitations and biases, highlighting their relative proficiencies in generalizing across data distributions, resilience to noise corruption, and discriminative capabilities for changes of varying characteristics. The proposed benchmarking framework demonstrates significant potential for guiding the selection of suitable CD models tailored to specific application requirements by comprehensively evaluating their generalizability, robustness, and detection capabilities across diverse real-world scenarios. This systematic evaluation approach can drive future research into developing more robust and versatile CD solutions aligned with practical needs.

Plant-based essential oils are important natural products rich in volatile compounds, and they have various applications in medicine, food, perfumery and cosmetics. These substances can be produced using various methods, such as steam distillation and solvent extraction. Their chemical composition is influenced by geographical and climatic conditions, production methods, and intrinsic factors. Published articles and literature were scanned to gather the required information. Previous studies have shown that essential oils possess chief health benefits, including antimicrobial, anti-inflammatory, antioxidant, and psychological effects. Consequently, they have wide applications in the food industry as preservatives in food systems and in active packaging, edible coating, probiotic foods, and flavoring. Essential oils can be successfully utilized in flavoring foods and beverages such as cheese, ice cream, and soft drinks. Despite their great antimicrobial and flavoring roles, it is important to further investigate their possible interactions with food components and the physiochemical characteristics of foods flavored with essential oils.

Background: Convectional methods for drug delivery often faces setbacks due to systemic distribution, short half-life and degradation of therapeutics and therefore reduce concentrations of drug available to target tissue. Nanotheranostic provide a novel method for treating and diagnosing diseases Methodology: collection and review of relevant literatureResult: while nanotheranostic offer advantage of personalized medicine and often combines diagnosis and therapy using single molecular approach, nuclear medicine relies on radioactive isotopes to diagnosed and destroys cancer cells. In both cases, nanocarriers such as lipid-based, polymer-based, drug-conjugate, inorganic nanoparticles are used to deliver drugs/probes/isotopes to target site, generating images and thereafter chemotherapy/radiotherapy begins.Conclusion: Nanotheranostic plays important role in diseases diagnostic, therapy, imaging, monitoring of disease progression / response through the use of nanocarriers. This is made possible through nanoparticles/nanocarriers that delivers drug to the target tissues/cells.

The implementation of systems condition monitoring is of utmost importance in ensuring effective maintenance, optimal efficiency, and adherence to established design criteria. This research presents a novel and economically efficient Digital Twin Model (DTM) designed for the purpose of Live Condition Monitoring (LCM) and Predictive Lifecycles. This study discusses the enhancement of DTs modelling by decreasing the number of dimensions from five to three: Physical, Digital, and Connection entities. The resulting model exhibits a notable improvement in accuracy and efficiency. The suggested Dynamic Time Model (DTM) enhances the empirical pre-set average load for both simulation and experimentation by 35.7%, which is equivalent to a 1.6-fold increase. The DTM demonstrates a significant enhancement in the empirical predefined average lifecycles of the system, as shown in the real-life case study. Specifically, the DTM achieves a 12-fold improvement compared to the simulated results and a nine-fold improvement compared to the experimental findings. The suggested Dynamic Time Management (DTM) demonstrates a significant enhancement in the average lifecycles of the system, with a 19.7% improvement (equivalent to 1.2 times greater) compared to the wireless DTM results obtained through the application of the real system load. The suggested Dynamic Time Warping (DTW) method's accuracy and efficiency are shown via a practical case study using the suspension system of a Peugeot 3008 vehicle.

The main purpose of our research is the evaluation of the efficacity of solvent polarity on phenolic composition, as well as the antibacterial, and antioxidant activities of extract of Moroccan Mentha aquatica L., leaves. To attempt these objectives, the HPLC-DAD was used to identify the biomolecules. The total amount of phenolic and flavonoid content was determined using the Folin-Ciocalteu and aluminum trichloride processes as well as the DPPH, RP, and TAC tests were used to evaluate the antioxidant capabilities. In addition, by employing both in vitro and in silico analysis through the microdilution method, the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of the extracts were assessed against multidrug-resistant bacteria. Furthermore, the High-Performance Liquid Chromatography (HPLC) analysis indicated that all extracts of M. aquatica were abundant in noteworthy phytochemical compounds, especially gallic acid, vanillic acid, chlorobenzoic acid, quercetin, and kaempferol. Furthermore, the results indicated that the total phenolic content was higher in hydroethanolic extract (62.19 ± 1.19 mg GAE/g DW) in contrast to the acetonic and aqueous extracts (22.22 ± 0.64, and 22.44± 0.57 mg GAE/g DW) respectively. Similarly, the aqueous ethanol extract contained the greatest flavonoid concentration, with values of 29.15± 0.09 mg QE/g DW when compared with the other extracts. The seam extract poses excellent antioxidant power with an IC50 of 0.06 ± 0.00 mg/mL for the DPPH test, and lower RP with EC50 of 80± 0.00 µg/ml when compared with acetonic and aqueous extract (370± 0.00 and 460± 0.01 µg/mL) respectively. Moreover, the hydroethanolic extract has a high level of TAC 75.09± 2.00 mg EAA/g DW, followed by aqueous extract carrying a value of 28.53 ± 1.36 mg EAA/g DW. The antibacterial capacity is ranged between 0.78 ± 0.05 mg/mL and 12.60 ± 0.00 mg/L. The results of the in-silico study demonstrated that quercetin, vanillic acid, and naringenin components contribute to the antioxidant capability. While gallic acid, kaempferol, and quercetin components are attributed to the antibacterial capacity.

The aim of this research work is to study the influence of temperature, solar irradiation and wind dust on the production of solar energy. In addition, it aims to study the assessment of water quality, in particular groundwater used for cooling and cleaning photovoltaic panels (quality analysis). it's an important source, stable and sustainable can be used entirely for cooling and cleaning PV modules from the sales dust, in order to improve their performance. To date, all research studies carried out in this context of cooling and cleaning using water have not taken account of the nature of this water. We have taken a sample of water from a well in a rural area in the Darra Tafilalet region of Morocco. This region has an arid and semi-arid climate, with very high temperatures and dust-laden winds, particularly in summer. These meteorological characteristics influence the efficiency of cells, particularly photovoltaic (PV) panels, reducing their performance. Next, the water sample was analysed in the laboratory. The results obtained show that the groundwater in this area is very sensitive to cooling and cleaning photovoltaic panels. Moreover, these results indicate that the temperature, solar irradiation and wind-blown dust have a significant influence on energy production.

Global health is significantly impacted by antimicrobial resistance. Antibiotic misuse and overuse have resulted in the emergence of drug-resistant bacteria, viruses, parasites and fungi, which makes ordinary infections more difficult to cure and accelerates the spread of disease. The World Health Organisation has declared that antimicrobial resistance could result in up to 10 million deaths yearly by 2050, making it a worldwide health emergency. One of the greatest challenges to global health, food security, and development today, according to the World Health Organisation is the emergence of antibiotic resistance. Even though antibiotic resistance can arise naturally, improper usage of these medications and many other factors are accelerating its global spread. Antimicrobial resistance is frequently referred to as the "Silent Pandemic" and is a problem that requires current action and should be managed more effectively rather than considered as a future situation. This paper address a number of antimicrobial classes, global health, Onehealth and how drug resistance affects human health, and related risk factors. This review will also provide background information on the causes and processes of antimicrobial resistance in brief by identifying these characteristics, targeted interventions can be developed to lower the risk of illnesses that are resistant to antibiotics. It will also offer insights into new and emerging solutions that are being studied and may be created in the future to address the advancement of antimicrobial resistance.

as the growth and popularity of technology has become simultaneous ascend in both impacts and numbers of cyber criminals thanks to the web. For many years, the organization has strived in ways of preventing any attacks from cyber-criminal with advanced techniques. Cybercriminals and intruders are developing a more advanced way to breach the security surface of an organization. Advanced Persistent Threats are also known as APT are new and a lot more sophisticated version for multistep attack scenarios that are known and are targeted just to achieve a goal most commonly undercover activities. this report, there will cover everything I know that tells us about APT with more word and brief explanations

Background: Parkinson's disease (PD) is a global disease. However, there is a lack of research specifically focused on the AfrAbia population. Climate change, driven mainly by global warming, is linked to detrimental health impacts, including an increased frequency and intensity of heat waves. Neurological diseases, including neurodegenerative syndromes like Alzheimer's disease, Parkinson's disease, and motor neuron illnesses, have been increasingly seen and recorded in scientific literature. Although there is much literature demonstrating the growth in neurodegenerative disorders, the relationship between environmental variables such as global warming, air pollution, heavy metals, and pesticides and the higher occurrence of these illnesses is still unknown. Objective: The current article primarily aims to examine the relationship between climatic changes, air pollution, pesticides, heavy metals, and the occurrence of PD. Initially, we evaluate the influence of exposure to these variables on the cause or origin of Parkinson's disease. In addition, we will investigate how these variables disrupt processes such as excitotoxicity, oxidative stress, and neuroinflammation, all of which are strongly linked to Parkinson's disease (PD). Conclusions: This research presents a plausible rationale for the adverse effects of environmental influences on the brain, which are pivotal in the progression or onset of Parkinson's disease from an AfrAbian standpoint.

The transition to sustainable energy systems in the Middle East and North Africa (MENA) region addresses critical challenges of environmental protection, energy security, and socio-economic resilience. Using neo-institutional theory, this paper examines the intricate relationship between formal and informal institutions and their significant impact on the region’s energy transition. Despite the MENA region’s abundant renewable energy resources, numerous institutional barriers, such as governance inefficiencies, regulatory inconsistencies, and entrenched socio-cultural norms, significantly hinder this transition. Through a review of existing literature, this study presents a comprehensive analytical framework designed to overcome these barriers, with a focus on the Just and Sustainable Energy Transition model. This strategic model emphasizes equity, sustainability, and inclusive governance as pillars for reform. The study offers detailed recommendations for institutional change and underscores the importance of collaborative efforts among governments, industry stakeholders, and international partners to unlock the MENA region’s renewable energy potential, advance global sustainability goals, and ensure a more secure and resilient energy future.

There is growing interest in the discovery of novel xanthine oxidase inhibitors for gout prevention and treatment with fewer side effects. This study aimed to identify the xanthine oxidase (XO) inhibitory potential and drug-likeness of the metabolites present in the methanolic leaves extract of Anastatica (A.) hierochuntica L. using in vitro and in silico models. The extract-derived metabolites were identified by liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF-MS). Molecular docking predicted the XO inhibitory activity of the identified metabolites and validated the best scored in vitro XO inhibitory activities for experimental verification as well as predictions of their anticancer, pharmacokinetic and toxic properties, oral bioavailability, and endocrine disruption using SwissADMET, PASS, ProTox-II and Endocrine Disruptome web servers. A total of 12 metabolites with a majority of flavonoids were identified. Rutin, quercetin and luteolin flavonoids demonstrated the highest ranked docking score of -12.39, -11.15 and -10.43, respectively, while the half-maximal inhibitory concentration (IC50) values of these metabolites against XO activity were 11.35 µM, 11.1 µM and 21.58 µM, respectively. In addition, SwissADMET generated data related to physicochemical properties and drug-likeness of the metabolites. Similarly, PASS, ProTox-II and Endocrine Disruptome prediction models stated the safe and potential use of these natural compounds. However, in vivo studies are necessary to support the development of prominent and promising therapeutic use of A. hierochuntica methanolic leaves extract-derived metabolites as XO inhibitors for the prevention and treatment of hyperuricemic and gout patients. Furthermore, the predicted findings of the present study open a new paradigm for these extract-derived metabolites by revealing novel oncogenic targets for the potential treatment of human malignancies.

The classification of kidney tumors has undergone a remarkable evolution since the early 19th century, reflecting advances in medical science and technology. This historical overview traces the development of renal tumor classification, beginning with early clinical observations and macroscopic descriptions to the integration of molecular diagnostics in contemporary classifications. The establishment of international organizations like the World Health Organization (WHO) facilitated collaboration and standardization in tumor classification, leading to refined classifications and standardized nomenclature. Advancements in histological and molecular studies, particularly genetic analyses, revolutionized the understanding of renal cell carcinomas, enabling precise categorization based on molecular characteristics. The journey from rudimentary classifications to sophisticated systems based on detailed histological, immunohistochemical, and molecular criteria underscores the continuous evolution of kidney tumor classification. This article provides a comprehensive overview of this evolution, highlighting the contributions of scholars and the impact of technological advancements on our understanding and management of kidney tumors.

Peste des Petits Ruminants (PPR), a highly contagious viral disease, causes significant economic losses in sheep and goats. Laboratory diagnosis is crucial to disease control and eradication. Since PPRVs have recently adopted new hosts, genetic diversity within isolates of the same lineage is more likely than if they were host-specific, sheep and goats most often. ELISA detects antibodies and antigens in serology. However, mishandling, environmental conditions (temperature and humidity), storage, and sensitivity issues of commercially available ELISA kits prevent rapid PPR virus detection in third-world countries like Pakistan. In the 2020-21 outbreaks in Pakistan, 325 blood samples, 19 swabs, and 6 virus tissue samples of sheep and goats were collected from Gilgit, Islamabad, and Fateh Jang. These virus isolates were submitted to NCBI for partial N gene sequencing. Antigen was prepared from indigenous virus Using semi-purified antigen from PPRV, an indirect ELISA for the detection of PPR antibodies in goat and sheep serum was developed using MW600922 grown in Vero cells. Dilutions of 1:200 serums and 1:32 antigens improve antibody detection. The N-gene-based analysis revealed a better understanding of PPRV genetic characterization. This study develops an RT-PCR assay to detect PPRV by targeting the N-protein gene. This assay offers an accurate and affordable diagnostic tool for PPRV and partial genome sequencing. Results described that PPRV isolates from the current study have 99.73% and 99.4% similarity to previously published Lahore and Faisalabad isolates from Pakistan, respectively. Compared to previous isolates from NCBI data, the virus showed high divergence rates with the Turkish strain. The comparative analysis between Commercial kit (c-ELISA) and I-ELISA revealed that the former had a high sensitivity of 90.60% and specificity of 85.23% compared with the cELISA kit. By comparing I-ELISA and VNT, we find that the current assay is 100% specific and 82.14 % sensitive. Based on these results, serological surveys for PPR antibodies, on a larger scale, in small ruminants can be conducted with indirect ELISA rather than competitive ELISA. Furthermore, the cost and storage efficiency was highly significant because the currently developed method has a low production cost, which is much lesser than the commercially available kit. Our findings demonstrated a significant breakthrough in terms of cost-effectiveness and storage efficiency, and they are highly recommended for developing countries.

Water pollution with dyes is a critical environmental issue because off the huge amount of dyes disbarred annually which cause severe damage for the ecosystem and human life. On the other hand, the core-shell based magnetic materials have showed amazing character for controlling the material synthesis with targeted structure to enhance the adsorptive-removal of pollutants. Herein, Fe3O4 core-TiO2/mesoSiO2 and Fe3O4 core-mesoSiO2/TiO2 double shell nanoparticles were prepared by first (R1) and second (R2) routes. The preparation procedure is controlled to prepare the magnetic core with further coating layers from silica and titania for the uptake of methylene blue from aqueous solutions. The reported adsorption capacities for R1-0.2, R1-0.4 and R2 samples were 46, 38 and 50 mg/g respectively at pH 6 after 80 min contact time form 50 ppm methylene blue solution. The adsorption process of methylene blue onto Fe3O4core-meso SiO2/TiO2 double shell was well fitted with the pseudo-second-order kinetic model and Freundlish isotherm which suggested the quick and multilayer adsorption mechanism. In addition, results of thermodynamic investigation indicated that the surfaces of Fe3O4 core-mesoSiO2/TiO2 and Fe3O4 core-TiO2/mesoSiO2 double shell exhibit spontaneous tendency to adsorb methylene blue from the aqueous solutions. These results will encourage the further application of Fe3O4 core-meso SiO2/TiO2 and Fe3O4 core-TiO2/meso SiO2 double shell for removal of other dyes and pollutants from wastewater.

Electric energy has become essential nowadays not only for the daily life of each of us but also for the economy of different countries. The dissemination of geographic information plays an important role in national development as it facilitates communication between managers, investors, and consumers in this sector. Since the management of electricity network data was previously done in Tunisia based on paper maps and plans, the purpose of this article is to present a case of planning based on GIS, Web, and 3D Web GIS, which would have significant positive consequences on this sector from a technical and financial sides with an improvement in customer satisfaction and the creation of an intelligent electricity network which will be a real decision-making tool. This work draws up an inventory of the network MV (Medium Voltage)/LV (Low Voltage) of the region of Medjez El Bab which routes electricity to the big centers of consumption with access to MV/LV subscribers. The analysis of the network's impedance allowed carrying out different scenarios to optimize performance and obtain more realistic routes. Many thematic maps were produced as part of this project (Slope map, Land use map, map of the MV voltage domains, map of the MV/LV transformer stations power, etc.). A three-dimensional virtual city has been developed to visualize the graphical and attribute data for the study area. A Web and 3D Web GIS applications that allows the publication of the interactive maps on the Web as well as the database information have been developed to offer users the possibility of consulting the produced products by internet. Finally, a website related to the study was developed.

The capacitated team orienteering problem with time windows (CTOPTW) is a NP-hard combinatorial optimization problem. In the CTOPTW, a set of customers is given each with a profit, a demand, a service time and a time window. A homogeneous fleet of vehicles is available for serving customers and collecting their associated profits. Each vehicle is constrained by a maximum tour duration and a limited capacity. The CTOPTW is concerned with the determination of a preset number of vehicle tours that begin and end at a depot, visit each customer no more than once while satisfying the time duration, time window and vehicle capacity constraints on each tour. The objective is to maximize the total profit collected. In this study we propose an iterated local search (ILS) algorithm to deal with the CTOPTW. ILS is a single solution based meta-heuristic that successively invokes a local search procedure to explore the solution space. A perturbation operator is used to modify the current local optimum solution in order to provide a starting solution for the local search procedure. As different problems and instances have different characteristics, the success of the ILS is highly dependent on the local search procedure, the perturbation operator(s) and the perturbation strength. The basic ILS uses a single perturbation operator and the perturbation strength remains the same during the optimization process. To address these issues, we use three different perturbation operators and a varying perturbation strength which changes as the algorithm progresses. The idea is to assign a larger perturbation strength in the early stages of the search in order to focus on exploring the search space. The perturbation strength is gradually decreased so that we focus more on exploitation. The computational results show that the proposed ILS algorithm is able to generate high quality solutions on the CTOPTW benchmark instances taken from the scientific literature, demonstrating its efficiency in terms of both the solution quality and computational time. Moreover, the proposed ILS produces 21 best known results and 5 new best solutions.

This paper presents how social media platforms and their components could be integrated into the KMS for the purpose of managing and sustaining Somali Indigenous knowledge (IK). The discovery of knowledge and its utilization is now fuelled by the advancement of technology, which connects users to external sources through using different platforms. The rapidly increasing use of SM and mobile technologies create opportunities to form knowledge networks that can facilitate the process of creating, preserving, and sharing knowledge and skills that are unique to communities in the Somali context. Somali society being an oral society with rich IK and other cultural practices lacked a framework in place to organize the existing knowledge in various methods. The paper refers to existing methodology E-learning and KM functions. This method first identifies functional similarities between SM, E-Learning, and KM systems and their interactions if they are properly integrated. The proposed framework consists of two functional parts; KM and SM. The KM part involves knowledge capturing, validation, formatting, storing, and distribution. SM part of the framework involves knowledge presentation, sharing, and application. Since the Somalis are said to be an oral society, this framework helps to capture and disseminate IK residing in knowledge holders.

Background: Aberrations in endothelial cells, immune and oxidative pathways are associated with atherosclerosis (ATS) and unstable angina (UA). The role of trace elements, minerals, and the endogenous opioid system (EOS) in UA are less well established. Methods: We measured lipid, insulin resistance (IR), and immune, trace element (copper and zinc), mineral (magnesium, calcium), EOS (β-endorphin and mu-opioid receptor (MOR)) and antioxidant (vitamin D3) biomarkers in patients with ATS (n=60) and UA (n=60) and healthy controls (n=58). Results: ATS patients showed increased atherogenic and IR indices, IL-6, IL-10, β-endorphin, copper and magnesium, and lower zinc than healthy controls. Logistic regression showed that UA was significantly discriminated from ATS without UA with an accuracy of 85.5% using calcium, IL-10, β-endorphin, MOR, triglycerides, IR (all positively), and copper and vitamin D3 (inversely). Neural networks showed that UA was discriminated from ATS without UA with an area under the ROC curve of 0.942 using MOR, β-endorphin, calcium, insulin resistance, vitamin D3 and copper as input variables. We found that 50.0% of the variance in IR was explained by the regression on copper, IL-10, IL-6 (all positively), and zinc (inversely), while 32.9% of the variance in the atherogenic index of plasma was explained by copper, IL-10 (both positively), and magnesium (inversely). Conclusion: UA is not only mediated by insulin resistance, atherogenicity, and immune disorders, but also by aberrations in the endogenous opioid system and trace elements as well as lowered antioxidant levels. Copper appears to play a key role in IR and atherogenicity.

With the emergence of the Internet and WWW has become a comprehensive source of information for the extraction of meaningful information has become a significant challenge in the past decade. Furthermore, the available information is classified in unstructured, structured, and semi-structured forms. Numerous amount of information on the web is also characterized in an unstructured or semi-structured format. This usually extracts the potential useful information from these multiple forms and has been considered a leading area of research in this modern era. The authors presented web content mining as a subcategory of web mining that focuses on important extracting patterns from the contexts available in the documents on the web. Hence, this paper focuses on the multiple content mining concepts, tools, and techniques implemented on the documents available on WWW.

The border between Niger and Libya, often described as an "ungoverned space," epitomizes the complex interplay of economic, political, and security challenges within the Sahel region. Authorities and international actors have made various efforts to establish control, but tribal structures predominantly manage governance in these areas. These structures lack formal institutions and rely heavily on external security interventions to combat terrorism and irregular migration. The increasing militarization of the region raises significant concerns about the long-term efficacy of these approaches in achieving sustainable security. This study argues that enduring stability in such contexts requires a nuanced balance of economic, political, and social factors. The research methodology includes a comprehensive literature review of security issues, governance, state fragility, and counter-terrorism, utilizing scientific journals, books, reports, and newspapers. The study investigated the dual nature of ungoverned spaces, examining their role in facilitating terrorism and organized crime while highlighting the critical need for governance to enhance citizen welfare and support state functions. Recent developments in Libya and the Sahel under-score the urgency of addressing security and developmental challenges. The study concludes by advocating for sustainable political and development initiatives over militarization, emphasizing the necessity of a new social contract to address the security challenges in the Sahel region effectively.

Single Image Super Resolution (SSIR) is a problem in computer vision where the goal is 1 to create high-resolution images from low-resolution ones. It has important applications in fields 2 such as medical imaging and security surveillance. While traditional methods such as interpolation 3 and reconstruction-based models have been used in the past, deep learning techniques have recently 4 gained attention due to their superior performance and computational efficiency. This article proposes 5 an Autoencoder based Deep Learning Model for SSIR, in particular, a light model that uses fewer 6 parameters without compromising performance. The down-sampling part of the Autoencoder 7 mainly uses 3 by 3 convolution and has no subsampling layers. The up-sampling part uses transpose 8 convolution and residual connections from the down sampling part. The model is trained using a 9 subset of the VILRC ImageNet database. The model is evaluated using quantitative metrics PSNR, 10 SSIM as well as qualitative measures such as perceptual quality. PSNR and SSIM figures as high as 11 76.06 and 0.93 are reported.

Synthesis of a novel series of chromen-3-yl-pyridine moieties. IR, NMR, and MS spectroscopy were used to confirm the structure of these novel compounds and study of antitumor activity of these compounds. The structure activity relationship investigation demonstrated that 2,4-diamino-5-(3-methoxyphenyl)-7-(2-oxo-2H-chromen-3-yl)-1,8-naphthyridine-3-carbonitrile (16), was more effective and naphthyridine-3-carbonitrile derivatives 17, 18 and pyrido[2,3-d]pyrimidine derivative 12, while compounds 5a,b, 9c, 11, 13 and 14 were moderate activity for antitumor activities.

Colistin [polymyxin E] is a veterinary exclusive antimicrobial and one of the oldest antibiotics that is currently recognised as one of the highest priority critically important antimicrobials for humans. It is extensively used for multiple medical and non-medical purposes particularly for growth promotion, prophylaxis/metaphylaxis and therapeutic in food animals. As a result, colistin resistance was widespread along the food-chain linking to multidrug resistant bacterial infections in humans reflected by greater use of colistin in healthcare settings resulted in different types of bans/restrictions in food-producing animals, around the world. This report debates the testimonies of 23 countries representing the bulk of global food producing animal production, providing robust evidence on the essential need for colistin in animal production.

Recently, microfluidics deformability cytometry has emerged as a powerful tool for high throughput mechanical phenotyping of large populations of cells. These methods characterize cells by their mechanical fingerprints through exerting hydrodynamic forces and monitoring the resulting deformation. These devices have shown great promise for label free cytometry, yet there is a critical need to improve their accuracy and reconcile any discrepancies with other methods, such as atomic force microscopy. In this study, we employ computational fluid dynamics simulations and uncover how the elasticity of frequently used carrier fluids such as methyl-cellulose dissolved in phosphate-buffered saline is significantly influential to the resulting cellular deformation. We conducted CFD simulations that are conventionally used within the deformability cytometry field, which neglect fluid elasticity. Subsequently, we incorporated a more comprehensive model that simulates the viscoelastic nature of the carrier fluid. A comparison of the predicted stresses between these two approaches underscores the significance of the emerging elastic stresses in addition to the well-recognized viscous stresses along the channel. Furthermore, we utilize a two-phase flow model to predict the deformation of a promyelocyte (i.e. HL-60 cell type) within a hydrodynamic constriction channel. The obtained results highlight a substantial impact of the elasticity of carrier fluid on cellular deformation and raise questions about the accuracy of mechanical property estimates derived by neglecting elastic stresses.

This paper identifies a criterion for choosing the largest set of rejected hypotheses in high-dimensional data analysis where Multiple Hypothesis testing is used in exploratory research to identify significant associations among many variables. The method neither requires predetermined thresholds for level of significance, nor uses presumed thresholds for false discovery rate. The upper limit for number of rejected hypotheses is determined by finding maximum difference between expected true hypotheses and false hypotheses among all possible sets of rejected hypotheses. Methods of choosing a reasonable number of rejected hypotheses and application to non-parametric analysis of ordinal survey data are presented.

The flavonoid silymarin (SMN) has been widely used in preclinical and clinical studies to treat various types of cancer, either alone or in combination with chemotherapy agents. Herein, we investigated the therapeutic efficacy of SMN and its combination with capecitabine (CAP) and irinotecan (IRI) in a mouse model of colon cancer. A modified diet supplemented with SMN (2500 ppm) with mono- and combined therapy of CAP and IRI were used following 1, 2 dimethylhydrazine (DMH)-induced colon cancer. The lipid profile, liver function tests, and cytokine levels were measured. Additionally, the lipid peroxidation and inflammation indices as well as the antioxidant activities were examined. Eventually, western blotting analysis for colonic BAX and Bcl-2 levels and histopathological examination of colon sections were carried out. SMN alone and in combination with the chemotherapeutic agents could attenuate the DMH-induced hyperlipidemia and elevated liver function enzyme levels. SMN supplementation with chemotherapy agents could also improve antioxidant activity and reverse the elevated levels of lipid peroxidation and inflammatory markers. Furthermore, significant upregulation of BAX and downregulation of Bcl-2 were observed. Besides, carcinogen-induced polyp multiplicity, dysplastic, and inflammatory changes were ameliorated considerably by treatment regimens. Our results showed that the potential anticancer properties of SMN could enhance the therapeutic effects of chemotherapy agents and reduce hepatotoxicity.

The field of biosensors has found great use for surface plasmon resonance (SPR), which has attracted attention for its multiple applications. With the goal of early cancer detection at the level of a single living cell, this research numerically investigates a very sensitive D-shaped fiber-optic biosensor based on surface plasmon resonance (SPR). The titanium oxide (TiO2) is coated on gold (Au), which is utilized as a thin-film plasmonic material in the suggested biosensor structure. The guiding of light in the fiber is modeled using the finite element method (FEM) when six different types of healthy human cells and their malignant counterparts are exposed to its sensitive region. Refractive index (RI) differences between cancer cells and healthy cells are found through the analysis of the optical spectra and their amplitudes. This enables us to identify small changes in the optical characteristics of cells that could be a sign of pathogenic alterations. In this work, we concentrated on three forms of cancer: skin cancer (basal cell) and breast cancer (MDA-MB-231 and MCF-7). The results show which parameters are optimal to ensure that the sensor performs well when used to detect the three types of cancer under study. When the suggested sensor’s performance is compared to SPR sensors that have previously been published in the literature, it becomes clear that our sensor offers great promise for early cancer detection.

Glass samples (59.5 – x) B2O3 – 20Na2O – 20CaO – xV2O5 – Er2O3 – 0.5AgCl (x = 0 – 2.5 mol%) were prepared using melt – quenching method to investigate the structural and optical properties of the glass. The structural of the glass were characterized by using XRD, TEM and FTIR, meanwhile the optical properties were characterized by UV – VIS absorption. The XRD patterns confirmed the amorphous nature of the prepared glass samples. FTIR confirmed the presence of VO4, VO5, BO3, and BO4 vibration, and this result showed NBO increased with increasing vanadium concentration. The UV – Vis – NIR spectra exhibits six absorption band centered at 490, 520, 540, 660, 800, and 980 nm. The optical band gap (Eopt), Urbach energy and refractive index shown decrease, increase and increase, respectively. The Judd – Ofelt intensity parameter reveal the trends was Ω2 &gt; Ω4 &gt; Ω6. There are three emission bands at 516 nm, 580 nm, and 673 nm which are represented by 2H11/2 – 4I15/2, 4S3/2 – 4I15/2, and 4F15/2 – 4I15/2, respectively under 800 nm excitation was obtained.

Soil erosion is one of the most important environmental problems which can have various negative consequences, such as land degradation affecting the sustainable development and the agricultural production, especially for developing countries like Tunisia. Moreover, soil erosion is a major problem around the world because of its effects on soil fertility by nutriment loss and siltation in water bodies. Apart from this, soil erosion by water is the most serious type of land loss in several regions both locally and globally. This study evaluated regional soil erosion risk through the derivation of appropriate factors, using the Revised Universal Soil Loss Equation (RUSLE), which was applied to establish a soil erosion risk map of the whole Tunisian territory and to identify the vulnerable areas of the country. RUSLE model take into account all the factors playing a major role in erosion processes, namely the erodibility of soils, topography, land use, rainfall erosivity and anti-erosion farming practices. The equation is thus implemented under Geographic Information System (GIS) “Arc GIS Desktop”. The results indicated that Tunisia has a serious risk of soil water erosion, showing that 6.43% of the total area of the country is affected by a very high soil loss rate estimated at more than 30 t/ha/year and 4.20% are affected by high mean annual soil loss ranging from 20 to 30 t/ha/year. The most eroded areas were identified in west southern, central and western parts of the country. The spatial erosion map can be used as a decision support document to guide decision-makers towards better land management and provide the opportunity to develop management strategies for soil erosion prevention and control in the global scale of Tunisia.

The paper examines the impact of inward remittances flows on per capita GDP growth in Bangladesh during 1976-2012. We find that the growth effect of remittances is negative at first but becomes positive at a later stage, an evidence of a non-linear. Unproductive use of remittances was rampant in the beginning when they were received by migrant families but better social and economic investments led to more productive utilisation of remittances receipts at later periods. This was the possible mechanism behind the U-shaped relationship. Unlike what is suggested in the literature that the effect of remittances is more pronounced in a less financially developed economy, our evidence do not show that the effect of remittances on per capita GDP growth in Bangladesh is conditional on the level of financial development.

Our study essentially concerns the dynamic behavior of an SIRS epidemic model in discrete time. Two equilibrium points are obtained; one is disease-free while the other is endemic. We are interested in the endemic fixed point as well as its asymptotic stability. Depending on the parameters which are estimated using the data from US Department of health and SIRS modelling with optimization, two Flip and Transcritical bifurcations appear. We illustrate their diagrams, as well as their bifurcation curves using the method of Carcasses \cite{carcasses1993determination,carcasses1995singularities} for the Flip bifurcation and by an implicit function deduced from such an equation for the Transcritical bifurcation. We use the scanning of the parametric plane to have a global view of the behavior of the model and to highlight the zones of stability of the existing singularities. A superposition of the bifurcation curves with the parametric plane can show the overlap of the curves with the boundaries of the stability domains, which confirms the smooth running of the simulation and its correspondence with the theory, we finish this article with constrained optimal control applied to infection rate and recruitment rate for an SIRS discrete epidemic model. Pontryagin's maximum principle is used to determine these optimal controls. Finally using COVID-19 data in the USA, we obtain results that demonstrate the effectiveness of the proposed control strategy to mitigate the spread of the pandemic.

Fermented milk product "Laban" in Libya is one of the most a traditional fermented milk product consumed a refreshing drink, particularly in the warm season The average values of the physicochemical including titratable acidity, pH, total solids, and fat were 0.73%, 4.16, 8.12%, and 1.54% respectively. Coliform, yeast and mold counts were 21×10⁴, 39×10⁴, and 41 ×10³ cfu/ ml., respectively. Most strains of coliform bacteria were Serratia odorifera, Escherichia coli 1, E. coli 2. and Klebsiella oxytoca. The average Lactococcus, Streptococcus, Mesophilic Lactobacillus / Leuconostoc and Thermophilic Lactobacillus counts were 99 ×10⁷, 96 ×10⁷, 93 ×10⁷ and 15 ×10⁷ cfu / ml. respectively. A total of 142 lactic acid bacteria (LAB) isolates were identified to the genus level as Lactobacillus (48.59%), Lactococcus (43.66%), Streptococcus (4.93%) and Leuconostoc (2.82%). Sugar fermentation tests revealed the most frequent Lactobacillus species found to be Lactobacillus delbrueckii ssp. lactis (62.32%), followed by Lactobacillus plantarum (31.88%). Furthermore, other selected LAB isolates were identified by API 50 CH test as Lactococcus lactis ssp. lactics, Lactobacillus pentosus, Lactobacillus brevis, and Leuconostoc mesenteroides ssp. cremoris. Thus, our research documented the lactic acid bacteria strains and will provides fundamental basic and useful information for further studies of strain selection starter culture, with regard to the industrial production of fermented dairy milk products.

The beneficial effects of Lanthanide incorporation into 0.94Na0.5Bi0.5TiO3-0.06BaTiO3 (BNT-BT) matrix on its functional properties were investigated. The conventional solid-state method was used for synthesizing samples. The structural refinement revealed that all samples crystallized in R3c rhombohedral symmetry. Raman spectroscopy study was carried out using green laser excitation and revealed that no clear perceptible variation in frequency is observed. Dielectric measurements unveiled that the introduction of rare earth obstructed the depolarization temperature promoted in BNT-BT with decreasing the diffusive phase transition with increasing the lanthanide size. Only Dysprosium addition showed comparable diffusion constant and dielectric behavior as the unmodified composition. Further, the comparison of the obtained ferroelectric hysteresis and strain-electric field loops revealed that only Dy-phase exhibited interesting properties comparing parent composition. In addition, the incorporation of lanthanides Ln3+ into the BNT-BT matrix led to the development of luminescence characteristics in the visible and near infrared regions, depending on the excitation wavelengths. The simultaneous occurrence of photoluminescence and ferroelectric/piezoelectric properties opens up possibilities for BNT-BT-Ln to exhibit multifunctionality in a wide range of applications.Keywords: Sodium Bismuth Titanate; structural refinement; dielectric properties; ferroelectric properties; piezoelectric properties; Photoluminescence.

This paper presents the results of an experimental investigation about target detecting with passive sonar in Persian Gulf. Detecting propagated sounds in the water is one of the basic challenges of the researchers in sonar field. This challenge will be complex in shallow water (like Persian Gulf) and noise less vessels. Generally, in passive sonar the targets are detected by sonar equation (with constant threshold) which increase the detection error in shallow water. Purpose of this study is proposed a new method for detecting targets in passive sonars using adaptive threshold. In this method, target signal (sound) is processed in time and frequency domain. For classifying, Bayesian classification is used and prior distribution is estimated by Maximum Likelihood algorithm. Finally, target was detected by combining the detection points in both domains using LMS adaptive filter. Results of this paper has showed that proposed method has improved true detection rate about 27% compare other the best detection method.

Fusion protein therapeutics engineering is advancing to meet the need for novel medicine. Herein, we further characterize the development of novel RTA & PAP-S1 antiviral fusion proteins. In brief, RTA/PAP-S1 and PAP-S1/RTA fusion proteins were produced in both cell free and E. coli in vivo expression systems, purified by His-tag affinity chromatography, and protein synthesis inhibitory activity assayed by comparison to the production of a control protein, CalmL3. Results showed that the RTA/PAP-S1 fusion protein is amenable to standardized production and purification and has both increased potency and less toxicity compared to either RTA or PAP-S1 alone. Thus, this research highlights the developmental potential of novel fusion proteins with reduced cytotoxic risk and increased potency.

Enhanced oil recovery (EOR) refers to the various techniques used to increase the amount of crude oil that can be extracted from an oil field. These techniques are used after the primary and secondary recovery methods have been depleted. There are three main types of EOR: thermal, gas injection, and chemical. EOR techniques can be expensive and complex, but they can help to recover additional oil that would otherwise be left in the reservoir. EOR can also extend the life of an oil field and increase the overall production from a given field. The parameters affecting oil recovery are a major concern in EOR systems, and these parameters need more consideration with the factors affecting them. In this study, the influence of permeability variations on fluid flow in a sandstone reservoir was explored, as well as an up-to-date description of three states of EOR with thorough explanations of the methods utilized and the mechanisms driving their oil recovery application. The difficulties encountered in the use of the different standard EOR Mechanisms were noted, and solutions to these difficulties were proposed. Furthermore, the contemporary trend of adding nanotechnology and its synergistic effects on the stability and efficiency of traditional chemicals for EOR were examined and analysed. Finally, laboratory findings and field initiatives were discussed. The review went into detail about the transport of nanoparticles across reservoirs, as well as the evaluation of EOR, mobility ratio, and fluid displacement efficiency. This review provides thorough information on the uses of improved oil recovery mechanisms for sustainable energy production.

Emotions play a vital role in understanding human behavior and interpersonal relationships. The ability to recognize emotions through Electroencephalogram (EEG) signals offers an alternative to traditional methods, such as questionnaires, enabling the identification of emotional states in a non-intrusive manner. Automatic emotion recognition holds great potential, eliminating the need for clinical examinations or physical visits, thereby contributing significantly to the advancement of Brain-Computer Interface (BCI) technology. However, one of the key challenges lies in effectively selecting and extracting relevant features from the EEG signal to establish meaningful distinctions between different emotional states. The process of feature selection is often time-consuming and demanding. In this research, we propose a groundbreaking approach for automatically identifying three emotional states (positive, negative, and neutral) by leveraging auditory stimulation of EEG signals. Our novel method directly applies the raw EEG signal to a Convolutional Neural Network-Long Short Term Memory (CNN-LSTM) architecture, bypassing the conventional feature extraction and selection steps. This unconventional approach offers a significant departure from existing literature. Our proposed network architecture comprises ten convolutional layers, followed by three LSTM layers and two fully connected layers. Through extensive simulations and evaluations on 12 active channels, our algorithm demonstrates exceptional performance, achieving an accuracy of 97.42\% and 95.23\% for the binary classification of negative and positive emotions, as well as a Cohen's Kappa coefficient of 0.96 and 0.93 for the three-class classification (negative, neutral, and positive), respectively. These promising results highlight the efficacy of our novel methodology and its potential implications in advancing emotion recognition using EEG signals.

In this article, the usual factorials and binomial coefficients have been generalized and extended to the negative integers. Basing on this generalization and extension, a new kind of polynomials has been proposed, which led directly to the non-classical hypergeometric orthogonal polynomials and the non-classical second-order hypergeometric linear DEs. The resulting polynomials can be used in non-relativistic and relativistic QM, particularly, in the case of the Schrödinger equation, and Dirac equations for an electron in a Coulomb potential field.

The study is based on the notion that big data predictive analytics is important for developing strategic alliances performance of companies. this study investigates the relationship between big data predictive analytics, big data culture, and competitive strategies 'techniques were adopted, such as descriptive statistics, correlation,regression, etc. using SPSS and SmartPLS statistical software. Hypotheses were tested with bootstrapped analysis using SEM (through SmartPLS). The study developed a structural equation model by using the SEM analysis. The results of the SEM analysis suggested the hypothesized model of the study was valid. The results supported all the hypotheses of the study.Through empirical analysis, demonstrated the conclusion is that the big data predictive analytics has a positive and significant relationship with strategic alliance performance

This study proposes a structure for companies to use when implementing human resource practices in open innovation. Despite the fact that open innovation has received a lot of attention in the innovation management field as companies open their doors to information exchange in an effort to spur creative thinking, there are very few empirical articles that connect this trend to the human resource management literature. Our findings are the result of an extensive qualitative investigation into Julphar Gulf Pharmaceutical Industries Manufacturers in the United Arab Emirates (UAE) and its open innovation program. Internal, external, and combined are the three primary pillars of human resource management. We also demonstrate how the evolution of the open innovation initiative is linked to the state of the art in HRM and open innovation literature. The framework identifies HRM practices for both internal and external participants in the open innovation effort. Much of this HRM is done off the books, in a setting separate from the host company. By providing actual evidence of how firms use HRM to manage open innovation projects, our research adds to the scant and mostly theoretical literature linking open innovation and HRM.

Blockchain and Machine Learning gives the best solutions together in performing various tasks in the Smart Health care system. With these two new emerging technologies, that have materialized in the last decade. In this paper, we proposed secure, transparent and intelligent methods in the Internate of medical things industry using Machine learning models and blockchain technology to enhance security level and train our models to improve diagnostic, prevention, treatment of the patient, patient rights, patient autonomy and equality in the health care system.

In January 2020, the World Health Organization declared a public health emergency and announced a new coronavirus disease (COVID-19), which would later go on to be declared as a pandemic, changing the global sphere and placing the economies of almost all countries under heavy stress. The airline industry, that had just begun recovering after facing crises one after another in the last two decades, from early 2000 due to 9/11, to the global financial crisis later, is now oce again facing an enormous challenge of closed borders and greater lockdowns due to the pandemic. Borders are closed, with very few planes are in the air, while the rest are grounded. The purpose of this paper is to give a conceptual understanding of the current pandemic situation and its consequences on the airline industry. The paper takes a unique perspective of human resource management (HRM) that is rarely used in the airline industry.

A thin-shell wormhole is crafted by the cut-and-paste method of two Bardeen de-Sitter black holes using Darmois-Israel formalism. Energy conditions are considered for different values of magnetic charge while both mass and cosmological constant are fixed. The attractive and repulsive characteristics of the throat of the thin-shell wormhole are also examined through the radial acceleration. Dynamics and stability of the wormhole are studied around the static solutions of the linearized radial perturbations at the throat of the wormhole. The regions of stability are determined by checking out the condition of concavity of the potential as a function in the throat radius for different values of magnetic charges.

Severe malaria in adults is not well studied in Sahelian Africa. Clinical features and mortality associated with severe Plasmodium falciparum malaria in adult patients hospitalized in Kiffa, southern Mauritania, were analysed. Patients over 15 years old admitted for severe malaria between August 2016 and December 2019 were included in the present retrospective study. The World Health Organization (WHO) criteria were used to define severe malaria. The presenting clinical characteristics and outcome were compared. Of 4266 patients hospitalized during the study period, 573 (13.4%) had a positive rapid diagnostic test for malaria, and 99 (17.3%; mean age, 37.5 years; range 15–79 years; sex-ratio M/F, 2.1) satisfied the criteria for severe malaria. On admission, the following signs and symptoms were observed in more than one-fourth of the patients: fever (98%), impairment of consciousness (81.8%), multiple convulsions (70.7%), cardiovascular collapse (61.6%), respiratory distress (43.4%), severe anaemia ≤ 80 g/L (36.4%), haemoglobinuria (27.3%), and renal failure (25.3%). Patients were treated with parenteral quinine or artemether. Fourteen (14.1%) patients died. Multiple convulsions, respiratory distress, severe anaemia, haemoglobinuria, acute renal failure, jaundice, and abnormal bleeding occurred more frequently (P < 0.05) in deceased patients. Mortality due to severe falciparum malaria is high among adults in southern Mauritania. An adoption of the WHO-recommended first-line treatment for severe malaria, i.e. parenteral artesunate, is required to lower the mortality rate associated with severe malaria.

Successful strategies that can contribute to poverty reduction and improve the livelihoods of the poor, particularly in Sub-Saharan Africa (SSA), are critically needed to address the technology adoption constraints. The objectives of this study were to assess the adoption rate of improved technologies and management practices and to identify the key factors influencing their adoption in the major wheat-producing areas of Sudan's irrigated, dry, and heat-prone environments. A farm survey was conducted in 2021 using a structured questionnaire that included all recommended technological options for optimum and sustainable wheat production. A total of 300 farmers, 93, 101, and 106 from Northern (NS), Kassala (KS), and Gezira (GS) states, respectively, were selected and interviewed. Besides descriptive statistics, a binary logistic model was used to identify the socioeconomic and production factors affecting farmers' perceptions of improved and recommended technological options. The study found a wide range of adoption rates depending on the specific technology practice and the area surveyed. The lowest adoption rate was observed for land preparation (6.5%) in NS. Adoption rates ranging from 26-100% were observed for technologies such as sowing date, seed rate, seed treatment, awareness of released varieties, nitrogen and phosphorus fertilizers application, and chemical weed control. The difference in the productivity of technological options adopters was significant (P = 0.015) compared to non-adopters. The binary logistic regression results showed that five out of seven explanatory variables hypothesized to influence wheat farmers' perceptions on the decision to adopt improved and recommended technologies significantly influenced farmers' decision to adopt the technologies. In particular, access to quality seed, financial credit, and extension services were found to be the most critical determinants of adopting improved technologies. Approaches that bring together all stakeholders along the crop value chain, including policymakers, to jointly analyze, identify, and prioritize challenges, develop and apply solutions and work plans using feedback and learning mechanisms are expected to increase farmer awareness and adoption of improved technologies, ultimately leading to sustainable wheat production.

Deep Learning (DL) oriented document processing is widely used in different fields for extraction, recognition, and classification processes from raw corpora of data. The article examines the application of deep learning approaches, based on different neural network methods, including Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM), and Convolutional Neural Networks (CNN). The compared models were combined with two different word embedding techniques, namely: Bidirectional Encoder Representations from Transformers BERT and Gensim Word2Vec. The models are designed to evaluate the performance of architectures based on neural network techniques for the classification of CVs of Moroccan engineering students at ENSAK(National School of Applied Sciences of Kenitra, Ibn Tofail University). The used dataset included resumes collected from engineering students at ENSAK in 2023 for a project on the employability of Moroccan engineers in which new approaches were applied, especially machine learning, deep learning, and big data. Accordingly, 867 resumes were collected from five specialties of study (Electrical Engineering, Networks and Systems Telecommunications, Computer Engineering, Automotive Mechatronics Engineering, Industrial Engineering). The results revealed good performance of the proposed models based on the BERT embedding approach compared to models based on the Gensim Word2Vec embedding approach. Accordingly, the CNN-GRU/Bert model achieved slightly better accuracy with 0.9251 compared to other hybrid models.

In recent years there has been a clear increase in bottled water consumption, globally which translates to significant health and environmental concerns. This cross-sectional study aims to understand the attitude and preferences of university students in Qatar towards use of bottled and tap water for drinking purposes using an online survey questionnaire. The number of students who responded to the online survey was 14% of the entire student population within the university (n = 688). Overall, majority of the students reported plastic bottled water as the main source of drinking water they preferred to use on campus (n=468; 68.02%), with a higher proportion of females (72.08%) preferring the use of plastic bottled water. Out of the 468 students who preferred plastic bottled water, safety was the most important factor (43.80%) followed by convenience (16.88%) and taste (15.60%). Cost (15.17%), personal/family habits (5.13%), Environmental concerns (2.14%) and minerals (1.28%) were found to be the least important factors. Among the 45 students who preferred tap water over plastic bottled water, cost (46.67%) was the dominant factor followed by convenience (20.00%) and environmental concerns and safety (13.33% each), taste (4.44%), and personal/family habits (2.22%). This study recommends campaigns to focus on attitude and behavior change and not solely emphasize knowledge; 71.7% believed that plastic water bottles are more harmful to the environment, yet the greater majority still resorted to this source. There is an immediate need to further educate students through environmental and health literacy programs on water consumption and quality. Enabling the population to understand the positive and negative aspects of their choices, may be an effective remedy to ensuring a healthy population and healthy environment.

A precise understanding of the genes and associated genomes of SARS-CoV2 is important for various reasons such as discovering origin of the virus and virulence and so on. A thorough descriptive understanding of the SARS-CoV2 genomes and other coronavirus of the beta-coronavirus genus is primarily important. In this article, a set of ten genomes of four CoVs and their associated genes are considered for this present study. A spatial representations of nucleotide bases including purine-pyrimidine representations of the different genes of the corresponding genomes are quantified using Hurst exponent, Shannon entropy and density estimation of different nucleotides including GC content, in order to draw a comparison and contrast among the ten genomes of different types of CoVs which include MERS, SARS-CoV, HKU1 (Human Coronavirus) and associated their genes.

Continuous object tracking in WSNs, such as monitoring of mud-rock flows, forest fires etc., is a challenging task due to characteristic nature of continuous objects. They can appear randomly in the network field, move continuously, and can change in size and shape. Monitoring such objects in real-time generally require tremendous amount of messaging between sensor nodes to synergistically estimate object’s movement and track its location. In this paper, we propose a novel twofold-sink mechanism, comprising of a mobile and a static sink node. Both sink nodes gather information about boundary sensor nodes, which is then used to uniformly distribute energy consumption across all network nodes, thus helping in saving residual energy of network nodes. Numerous object tracking schemes, using mobile sink, have been proposed in the literature. However, existing schemes employing mobile sink cannot be applied to track continuous objects, because of momentous variation of network topology. Therefore, we present in this paper a mechanism, transformed from K-means algorithm, to find the best sensing location of the mobile sink node. It helps to reduce transmission load on the intermediate network nodes situated between static sink node and the ordinary network sensing nodes. The simulation results show that the proposed scheme can distinctly improve life time of the network, compared to one-sink protocol employed in continuous object tracking.

This paper relies on accounting-based measures of country risk to investigate U.S. global banks' exposure to foreign country risk over the 2017 fiscal year as measured by the sum of cross-border risk, foreign office risk, and derivative risk claims. We achieve this using panel linear modeling methods with country level heterogeneity and time fixed effects, along with a constructed panel data of 284 observations on 71 countries distributed across 6 world regional blocks, and observed over 4 consecutive quarters starting from 4th quarter 2016 and ending with 3rd quarter 2017. The results show that on average, over the four quarters, a 1% increase in foreign banking sector's claims significantly increases U.S. global banks cross border risk exposure by 0.34%, while reducing derivative risk exposure by 0.22%, but have no significant impact on foreign office risk exposure. Similar results are observed with public sector claims which significantly increase banks' exposure to cross border risk by 0.21%, while reducing derivative risk exposure by 0.19%. Conversely however, non-bank financial sector claims are found to have no significant affect on cross-border risk exposure, but significantly reduce foreign office risk exposure by 0.09%, while increasing derivative risk exposure by 0.06%. These results indicate the presence of sectoral heterogeneities in U.S. banks' exposure to foreign counterparties' risk, and also that overall, over the course of 2017 the level of U.S. global banks' cross-border risk exposure increased, while their level of derivative risk exposure decreased, and the level of foreign office risk exposure remained relatively unchanged.

Nonsteroidal anti-inflammatory drugs (NSAIDs), which block the activity of cyclooxygenase (COX) isoenzymes and inhibit the synthesis of prostaglandin, have been used for pain relief. We have developed a method to separate a mixture of three NSAIDs, such as aspirin, paracetamol, and naproxen, using reverse-phase high-performance liquid chromatography (RP-HPLC). An isocratic mobile phase consisting of acidic water and acetonitrile was selected to run at a low flow rate, such as 0.8 mL/min. The mixture of three NSAIDs was injected at a low volume into a C18 column that was 150 mm in length and characterized using a UV detector at 230 nm. We identified three peaks in the chromatogram indicating the three compounds. The elution time of the peaks was less than 10 minutes. To identify multiple peaks on the isocratic flow using a short column, further studies are required regarding the proposed method to generate microfluidic devices for nanoLC.

The Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) first emerged in 2019 in China and has resulted in millions of human morbidities and mortalities across the globe. It has been shown that this novel virus originated in animals, mutated, and made the cross-species jump to humans. At the time of this communication, the Coronavirus disease (COVID-19) may be on way to an endemic form, however the threat of the virus is more for susceptible (older people and immunocompromised) people. The human body has more bacterial cells than its own, thus making us more bacterial than humans. As a consequence, the bacteriomes in the human body heavily influence human health and disease. The bacteriomes in the body and the immune system seem to be in constant association during bacterial and viral infections. In this review, we identify various bacterial spp. in major bacteriomes (oral, nasal, lung, and gut) of the body in healthy humans and compare them with dysbiotic bacteriomes of COVID-19 patients. We try to identify key bacterial spp. that have a positive effect on the functionality of the immune system and human health. These select bacterial spp. could be used as potential probiotics to counter or prevent COVID-19 infections. In addition, we try to identify key metabolites produced by probiotic bacterial spp. that could have potential anti-viral effects against SARS-CoV-2. These metabolites could be subject to future therapeutic trials to determine their anti-viral efficacy.

This paper aims to investigate carbon monoxide (CO) concentrations on roadways of Karachi, potential blood levels carboxy-hemoglobin (COHb) in Karachi. Geographical information system (GIS) was used for spatial analysis of diseases potentiality while an interpolation technique has been applied for surface generation with town boundaries and later evaluates risk areas.The higher concentration of carbon monoxide in the ambient is mainly due to automobile emissions. The City center and CBD areas are more perilous.

Recently, the Integrated Air Defense System (IADS) has become vital for the defense system as the military defense system is vital for national security. Placing Integrated Air Defense System batteries among locations to protect locations assets is a crucial problem because optimal solutions are needed for interceptor missiles to intercept attacker missiles for maximizing protection of assets across locations or places. In this research, the procedures of using network algorithms along with developing several network algorithms are going to be demonstrated to develop a model for sequential development of seven network securing strategies of placing Surface to Air Missile (SAM) batteries to maximize the protection of assets across locations (based on given asset values) by generating optimal solutions through computation to destroy maximum attacker missiles by using minimum interceptor missiles with given intercept probability. This network securing strategies can be implemented not only for Integrated Air Defense System (IADS) planning but also Counter Air (CA) planning as Integrated Air Defense System (IADS) is conducted with defensive counter air supported by attack operations in offensive counter air.

This paper presents a cooperative parallel tabu search meta-heuristic for the vehicle routing problem with time windows. It is based on the scheme in which several search threads cooperate by asynchronously exchanging information on the best solutions identified. The exchanges are performed through a mechanism called adaptive memory which holds and manages a pool of solutions. This enforces the asynchronous strategy of information exchanges and ensures the independence of the individual search threads. Each of these independent threads implements a tabu search meta-heuristic. Comprehensive computational experiments and comparisons to best known solutions show that the proposed cooperative parallel tabu search algorithm is able to achieve 48 new best solutions on VRPTW benchmark instances.

A second order rational difference equation $$x_{n+1}=px_{n}+\frac{q}{x_{n-1}^2}$$ with the parameters $p$ and $q$ which lies in $(0,1)$, is studied. The dynamics of the equilibrium is characterized through the trichotomy of the parameter $p<\frac{1}{2}$, $p=\frac{1}{2}$ and $p>\frac{1}{2}$. It is found that there is no periodic solution of period $2$ and $3$ but there exists periodic solutions with only periodic solution $5$ and $10$ are achieved computationally.

Background: We aimed to describe the patterns, management, and outcome of traumatic femoral shaft fractures. Methods: An observational descriptive retrospective study was conducted for all trauma patients admitted with femoral shaft fractures between January 2012 and December 2015 at the only level 1 trauma center and tertiary hospital in the country. Data were analyzed and compared according to the time to intramedullary nailing, mechanisms of injury and age groups. Main outcomes included in-hospital complications and mortality Results: A total of 605 cases were analyzed, with mean age of 30.7±16.2 years. The majority of fractures were unilateral (96.7%) and 91% were closed fractures. Three-fourth of fractures were treated by reamed intramedullary nailing (rIMN); antegrade in 80%. The pyriform fossa nails were used in 71.6% while trochanteric entry nails were used in 28.4%. Forty-five (8.9%) of fractures were treated with external fixator, 37 (6.1%) had conservative management. Traffic-related injuries occurred more in patients aged 14-30 years whereas; injuries related to fall were significantly higher in patients aged 31-59 years. Thirty-one patients (7.8%) had rIMN < 6 h post-injury, 106 (25.5%) had rIMN < 6-12 h and 267 (66.8%) had rIMN > 12 h. The implant type, duration of surgery, DVT prophylaxis, in-hospital complications and mortality were comparable among the three treatment groups. Conclusion: In our center, the frequency of femoral fracture is 11% which mainly affects severely injured young males due to traffic-related collisions or falls. Further multicenter studies are needed to reach a consensus for the appropriate management based on the location and timing of injury

Molecular dynamics simulations were performed to examine the impact of temperature (ranging from 250K to 350K) on the structural behavior of cellulose chains when dissolved in an aqueous cuprammonium hydroxide Cuam solvent system. By monitoring the root mean square deviation (RMSD) and radius of gyration (Rg) values at each temperature, we found that the geometric deformation of the cellulose chains changed significantly at T=300K. In contrast, Rg and RMSD values remained stable at temperatures in the range of 250K, 270K and the range of 330K, 350K. Calculating the interaction energy between the solvent and cellulose chains revealed that temperature significantly influences the cellulose dissolution process in the Cuam solvent system and that T=300K is an efficient temperature for its dissolution. The number of intra- and interchain hydrogen bonds was also calculated as a function of temperature, and the analysis confirmed that there is no breakage of these bonds at temperatures below 300 K (i,e: 250K, 270K) and above 310 K (I,e, : 330K and 350K) either between two native chains or between a native chain and another derivative.

Seasonal snowpacks, characterized by their snow water equivalent (SWE), play a major role in the hydrological cycle, snow melt contributions to floods and the subsequent availability of water resources downstream. Accurately estimating SWE and understanding its spatial and temporal variations presents a considerable challenge, particularly within mountainous regions characterized by complex terrain and limited observational data. Seeking to enhance the performance of the widely used Soil and Water Assessment Tool (SWAT), we report a new approach characterising snowpack behaviour incorporating both modelled and remotely sensed derived SWE calibration data. We focus on the Chenab River Basin (CRB) a headwater catchment of the Indus Basin, globally significant in terms of human inhabitants and intensifying flood risk due to climate change. We conducted a thorough assessment of five satellite-derived and reanalysis-based precipitation datasets: ERA5-Land, CMORPH, TRMM, APHRODITE, and CPC UPP. This reveals significant levels of uncertainty in global precipitation products when compared to reference data from observed stations as well as in the resulting simulated streamflow from the SWAT model. Subsequently, we expanded the scope of the SWAT model to encompass the spatial and temporal simulation of SWE. This was achieved by incorporating information from remotely sensed and modelled SWE products, manually adjusting snow parameters in R-SWAT for both the main basin and at sub-basin scales. Integrating SWE from reference snow products into the calibration process, alongside streamflow data, substantially enhanced modelling accuracy to simulate SWE compared to the conventional auto-calibration and single-variable approaches reliant solely on streamflow data. This approach results in considerable improvement in SWE predictions and to some extent in streamflow simulation in catchments dominated by snow. This research highlights the potential of remote sensing and modelled SWE parameterisation in the absence of in-situ snowpack data in high-altitude environments. An improved understanding of SWE behaviour is vital for predicting hydrological responses spanning hazards to water resources in the populous downstream regions of the Indus Basin, especially in the face of climate change.

The Gulf of Suez is a sedimentary rift-basin with thick evaporites and complex structural settings that presents challenges to achieving quality imaging based on seismic reflection data. Such subsurface settings and the lack of 3D seismic data poses challenges in building reservoir models to guide hydrocarbon exploration and development, especially in southern parts the Gulf of Suez. This study attempts to overcome the challenges of both 2D seismic interpretation and building a static reservoir model of two Miocene reservoir formations, Ras Ghara Field, Southern Gulf of Suez. Integration of well log data analysis of nine wells and regional-tectonics cognizant 2D seismic interpretation of nineteen 2D seismic lines enabled a reliable 3D static reservoir model. The Miocene reservoir characterization reveals heterogeneity in lithofacies distribution, with thick evaporite sequences causing seismic reflection distortions. Significant hydrocarbon accumulations are associated with horst fault blocks. The Miocene reservoirs demonstrate effective porosity of 14-33%, water saturation of 16-65%, and hydrocarbon saturation of 35-84%. Two new prospects are identified based on structure, facies distribution, and petrophysical results, with estimated original oil in place (OOIP) of 2,002,404 stock tank barrels (STB) and 1,175,580 STB for the Kareem Formation, and 6,302,916 STB and 2,841,894 STB for the Rudeis Formation.

A novel coronavirus has been reported as the causative pathogen of the Coronavirus disease 2019 (COVID-19) outbreak Wuhan city, China in December 2019. Due to the rapid spreading of COVID-19 worldwide, it has been announced as a pandemic by the World Health Organization (WHO). Hospitalized patients in Wuhan are associated with the Huanan seafood wholesale market where live animals, such as poultry, bats, snakes, frogs, rabbits, marmots, and hedgehogs are sold in that market which suggests a possible zoonotic infection. Therefore, it is essential to identify the potential animal reservoir, and the possibility of infection for other animal species. This short review aims to provide an overview on the relation between severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) infection and animals.

A convolutional neural network (CNN) is sometimes understood as a black box in the sense that while it can approximate any function, studying its structure will not give us any insights into the nature of the function being approximated. In other terms, the discriminative ability does not reveal much about the latent representation of a network. This research aims to establish a framework for interpreting the CNNs by profiling them in terms of interpretable visual concepts and verifying them by means of Integrated Gradient. We also ask the question, "Do different input classes have a relationship or are they unrelated?" For instance, could there be an overlapping set of highly active neurons to identify different classes? Could there be a set of neurons that are useful for one input class whereas misleading for a different one? Intuition answers these questions positively, implying the existence of a structured set of neurons inclined to a particular class. Knowing this structure has significant values; it provides a principled way for identifying redundancies across the classes. Here the interpretability profiling has been done by evaluating the correspondence between individual hidden neurons and a set of human-understandable visual semantic concepts. We also propose an integrated gradient-based class-specific relevance mapping approach that takes the spatial position of the region of interest in the input image. Our relevance score verifies the interpretability scores in terms of neurons tuned to a particular concept/class. Further, we perform network ablation and measure the performance of the network based on our approach.

The present work is focused on the numerical solution of the complete energy equation used in fluid film lubrication. The work was motivated by the fact the complete energy equation has no analytic solution that could be used for validations. Its accuracy and computation time are related to the employed numerical method and to the grid resolution. The natural discretization method (NDM) applied on different grids is systematically compared with the spectral method (the Lobatto Point Colocation Method or LPCM) with different polynomial degrees. A one dimensional inclined slider is used for the numerical tests and the energy equation is artificially decoupled from Reynolds. This approach enables to focus all the attention on the numerical solution of the energy equation. The results show that the LPCM is one or two orders of magnitudes more efficient than the NDM in terms of computation time. The energy equation is then coupled with Reynolds equation in a thermo-hydrodynamic analysis of the same 1D slider; the numerical results confirm again the efficiency of the LPCM. A thermo-hydrodynamic analysis of a two-lobe journal bearing is then presented as a practical application.

The purpose of this paper is to study the influence of diffusion and thermal loading due to pulsed laser heating on a thermoelastic solid with voids in the context of the model of three-phase-lag. The non-dimensional governing equations are formulated and then the exact expressions for the temperature field, the displacement components, the stress components, the concentration field and the change in the volume fraction field are obtained using the normal mode technique. The material is an isotropic, homogeneous elastic half-space and heated by a non-Gaussian laser beam with pulse duration of ps. The magnesium crystal element is used as an application to compare the predictions induced by diffusion and laser pulse on poro-thermoelastic medium of the model of three-phase-lag with those for the theory of Green–Naghdi of type III. The results obtained for thermal changes are verified by comparison with two theories of thermoelasticity, namely the model of three-phase lag (3PHL) and the Green and Nagdi type III theory. Plot the expressions to examine the effect of the laser pulse at two different values of time and the effect void parameter. This study also yields some interesting special cases.

Since the start of the COVID-19 pandemic, the world has witnessed a digital revolution that has transformed the way information are broadcast and consumed. This rapid evolution was accompanied by an “infodemic” (Beaulieu, 2019), a transformation of workplaces (Lulli LG, 2021)and difficulties in managing information flows (Bendahan & Nader, 2020). In this scientific article, we examine the communication strategies adopted by hospital structures as they are perceived by staff, highlighting their psychological and professional experiences throughout the crisis period. The results of the study carried out among hospital staff (n=200) demonstrate that the perception of communication strategies is generally positive for 78.56% of participants (M=1.85). The assessments of the staff interviewed as for the effect of this communication on the psychological experience and on the management of professional tasks have a positive trend respectively (M=2.15) and (M=1.86)