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Desulfurization is the process of removing the organic sulfur component from fuel oils. In this work, model fuel containing the sulfur compounds benzothiophene and dibenzothiophene was oxidized using plasma technique and plasma technique assisted by 30% hydrogen peroxide. Acetonitrile was used as a polar solvent in a liquid-liquid extraction stage that followed the oxidation reaction to remove the produced sulfones from the model fuel. The oxidation process was performed at operating conditions including the molar ratio of hydrogen peroxide to sulfur (5:1), temperature 50 ºC, air flow rate 75 ml/min, and voltage 11000 volts. The oxidation reaction was done using a dielectric barrier discharge process for generating non-thermal plasma. The plasma technique and a combination of plasma with hydrogen peroxide together to oxidize BT and DBT. The results showed that both methods follow the pseudo-first-order reaction and that the removal efficiency is 93.78% per cent for plasma compared to the combination of plasma and hydrogen peroxide together, which reached 95.12%. Hydrogen peroxide (H2O2) in an aqueous solution is the most commonly used oxidant in oxidative desulfurization. However, the use of hydrogen peroxide creates organ wastewater, which must be collected and disposed of after the reaction, whereas ozone is a highly promising oxidant for oxidative desulfurization(ODS) since it does not produce wastewater and has a greater oxidation potential (2.8V) than hydrogen peroxide (1.7V). To put oxidative desulfurization with ozone into practice, establishing a more efficient desulfurization process with ozone is extremely desirable.

In this study, lead ions were removed from simulated wastewater by batch adsorptive filtration. A three-dimensional printed water filtration was designed using a blender and successfully synthesized from a PLA spool and a 3d printer machine. The filter surface was treated with NaOH solution to hydrolyze the polyester group in PLA. After that, α-Fe2O3 was prepared by the coprecipitation method and coated on the filter through doping and drying. α-Fe2O3 was characterized by X-ray diffraction (XRD), Energy-dispersive X-ray spectroscopy (EDX), and Brunauer-Emmet-teller (BET). The results successfully indicate the synthesis of α-Fe2O3 consisting of 67.3% Fe and 32.7% O2. α-Fe2O3 appeared to have a surface area of 95 m²/g with distinct morphology and functional group. The effect of initial Pb concentration (100-800) ppm and the effect of contact time (5-120) min on the removal process were studied. Lab data was collected, and the adsorption was investigated kinetically. The 3d printed filter system coated by iron oxide showed significant and promised results for wastewater treatment and lead ions removal using this technique. Also, the results showed that the adsorption of Pb ions on the α-Fe2O3 surface fitted with the Langmuir model, with a correlation coefficient (R²) of 98.65%. The kinetic model’s investigations revealed that the pseudo-second-order model was the most fitted model for the process with R² of 99.997%. The highest adsorption saturation capacity was 165.2 mg/g adsorbent.

An accurate prediction of fetal birth weight is crucial in ensuring safe delivery without health complications for the mother and baby. The uncertainty surrounding the fetus’s birth situation, including its weight range, can lead to significant risks for both mother and baby. As there is a standard birth weight range, if the fetus exceeds or falls below this range, it can result in considerable health problems. Although ultrasound imaging is commonly used to predict fetal weight, it does not always provide accurate readings, which may lead to unnecessary decisions such as early delivery and cesarian section. Besides that, no supporting system is available to predict the weight range in Saudi Arabia. Therefore, leveraging the available technologies to build a system that can serve as a second opinion for doctors and health professionals is essential. Machine learning (ML) offers significant advantages to numerous fields and can address various issues. As such, this study aims to utilize ML techniques to build a predictive model to predict the birthweight range of infants into low, normal, or high. For this purpose, two datasets were used: one from King Fahd University Hospital (KFHU), Saudi Arabia, and another publicly available dataset from the Institute of Electrical and Electronics Engineers (IEEE) data port. KFUH’s best result was obtained with the Extra Trees model, achieving an accuracy, precision, recall, and F1-score of 98%, with a specificity of 99%. On the other hand, using the Random Forest model, the IEEE dataset attained an accuracy, precision, recall, and F1-score of 96%, respectively, with a specificity of 98%. These results suggest that the proposed ML system can provide reliable predictions, which could be of significant value for doctors and health professionals in Saudi Arabia.

Abstract Background To investigate the genetics of early-onset progressive cerebellar ataxia in Iran, we conducted a study at the Children’s Medical Center (CMC), the primary referral center for pediatric disorders in the country, over a three-year period from 2019 to 2022. In this report, we provide the initial findings from the national registry. Methods We selected all early-onset patients with an autosomal recessive mode of inheritance to assess their phenotype, paraclinical tests, and genotypes. The clinical data encompassed clinical features, the Scale for the Assessment and Rating of Ataxia (SARA) scores, Magnetic Resonance Imaging (MRI) results, Electrodiagnostic exams (EDX), and biomarker features. Our genetic investigations included single-gene testing, Whole Exome Sequencing (WES), and Whole Genome Sequencing (WGS). Results Our study enrolled 162 patients from various geographic regions of our country. Among our subpopulations, we identified known and novel pathogenic variants in 42 genes in 97 families. The overall genetic diagnostic rate was 59.9%. Notably, we observed PLA2G6, ATM, SACS, and SCA variants in 19, 14, 12, and 10 families, respectively. Remarkably, more than 59% of the cases were attributed to pathogenic variants in these genes. Conclusions Iran, being at the crossroad of the Middle East, exhibits a highly diverse genetic etiology for autosomal recessive hereditary ataxia. In light of this heterogeneity, the development of preventive strategies and targeted molecular therapeutics becomes crucial. A national guideline for the diagnosis and management of patients with these conditions could significantly aid in advancing healthcare approaches and improving patient outcomes.

Abstract Background Cardiovascular (CV) disease is a leading cause of death in breast cancer (BC) patients due to the increased age and treatments. While individual β-blockers have been investigated to manage CV complications, various β-blockers have not been compared for their effects on CV death in this population. We aimed to compare CV mortality in older BC patients taking one of the commonly used β-blockers. Methods This retrospective cohort study was conducted using the Surveillance, Epidemiology and End Results (SEER) - Medicare data (2010–2015). Patients of age 66 years or older at BC diagnosis receiving metoprolol, atenolol, or carvedilol monotherapy were included. The competing risk regression model was used to determine the risk of CV mortality in the three β-blocker groups. The multivariable model was adjusted for demographic and clinical covariates. The adjusted hazard ratio (HR) and 95% confidence intervals (CI) were reported for the risk of CV mortality. Results The study cohort included 6,540 patients of which 55% were metoprolol users, 30% were atenolol users, and 15% were carvedilol users. Metoprolol was associated with a 37% reduced risk of CV mortality (P = 0.03) compared to carvedilol after adjusting for the covariates (HR = 0.63; 95% CI 0.41–0.96). No significant difference in the risk of CV mortality between atenolol and carvedilol users was observed (HR = 0.74; 95% CI 0.44–1.22). Conclusions Our findings suggest that metoprolol is associated with a reduced risk of CV mortality in BC patients. Future studies are needed to confirm these findings and understand the mechanism of action.

Herbs, as the pomegranate (Punica granatum L.)(P. granatum), has significant chemical constituents with distinct pharmacological properties. These chemicals confer neuroprotective, antioxidant, anticancer, anti-inflammatory, and antibacterial properties to the plant. Pomegranate has specific components that enable its pharmacological actions; one of the functions of pomegranate extracts is to deactivate what is called extended spectrum beta-lactamase (ESBL) that makes Escherichia coli (E. coli) resistant to standard antibiotics. Twenty E. coli strains identified as beta-lactamase producers, the strains isolated from urine samples collected from patients with symptomatic urinary tract infection (UTI) and molecularly characterised using 16S rDNA. The study evaluated the antibiotic sensitivity and antibacterial activities of acetone and ethanolic pomegranate leaf and peel extracts, assessing their antimicrobial susceptibility against nineteen antibiotics. The ehanolic peel (EP) and leave (EL) extracts showed inhibitory potential inhibition zones spanning (9.0-12.6-18.3 mm) against E. coli pathogen producing extended-spectrum beta-lactamase as compared with (10.2-15.3 mm) inhibition scale exhibited by acetone peel (AP) and leave (AL) extracts treatment. Pomegranate leaves and peel extracts contain bioactive compounds with antioxidant, antimicrobial, and other biological effects, and can be fractionated for the identification of new antibacterial bioactive compounds for the development of drugs against ESBL- E. coli, in addition to their synergy with antibiotics for combination therapy that may have effective management and treatment of multidrug-resistant infections such as urinary tract infection.

This work presents an investigation into the ultra-desulfurization of heavy naphtha fuel (model using BT and DBT) using oxidation and solvent extraction techniques. Ozone produced by the DBD (Dielectric barrier discharge) plasma generator was employed in the oxidation process as an oxidant, and acetonitrile was used as a solvent extraction. Box-Behnken experimental design was adopted in the current study to examine oxidation desulfurization by non-thermal plasma for the various operation conditions including time, flow rate, and temperature on sulfur removal efficiency. Acetonitrile with an oxidized oil/solvent ratio of 1:1(v/v ratio) was utilized as the extraction solvent. The results showed that the maximum sulfur removal of about 91% was obtained with a temperature of 50°C, flow rate of 75 ml/min, and time of 4 hours.

BACKGROUND: Multiple sclerosis (MS) is a chronic, inflammatory demyelinating disease that affects various parts of the central nervous system. Fatigue, a common symptom, transient, prolonged, or chronic experienced by individuals with MS, can significantly impact daily functioning. It can be associated with underlying pathological processes or can have an idiopathic cause, such as chronic fatigue syndrome (CFS). The study aimed to assess the presence and etiology of fatigue in MS patients and its relationship with CFS. MATERIALS AND METHODS: This cross-sectional study was conducted in the Eastern Province of Saudi Arabia. Data were collected using a questionnaire from a sample of 225 MS patients receiving care at our university hospital. The questionnaire included the Centers for Disease Control and Prevention (CDC) criteria for diagnosing CFS and the Expanded Disability Status Scale to evaluate fatigue in MS patients. RESULTS: Of the total of 225 MS patients who participated in this study, 87.1% were diagnosed with relapsing-remitting MS, 6.7% with primary progressive MS, 3.6% with clinically isolated syndrome, and 2.7% with secondary progressive MS. About 53% had experienced fatigue that persisted for over 6 months. Analysis of CFS diagnosis revealed that 7.3% of patients met both CDC criteria and self-reported answers while 17.5% reported having CFS despite not meeting the CDC criteria. These findings highlight a significant lack of agreement between patient-reported diagnoses and established criteria, indicating poor agreement (P = 0.028). CONCLUSION: The study found an association between CFS and MS, and a significant impact on daily functioning. The study revealed lack of agreement between patient-reported diagnoses and established criteria for CFS. This emphasizes the need for a standardized approach to diagnosis and evaluation of fatigue in MS patients.

Traffic lights play an important role in efficient traffic management, especially in crowded cities. Optimizing traffic helps to reduce crowding, save time, and ensure the smooth flow of traffic. Metaheuristic algorithms have a proven ability to optimize smart traffic management systems. This paper investigates the effectiveness of two metaheuristic algorithms: particle swarm optimization (PSO) and grey wolf optimization (GWO). In addition, we posit a hybrid PSO-GWO method of optimizing traffic light control using IoT-enabled data from sensors. In this study, we aimed to enhance the movement of traffic, minimize delays, and improve overall traffic precision. Our results demonstrate that the hybrid PSO-GWO method outperforms individual PSO and GWO algorithms, achieving superior traffic movement precision (0.925173), greater delay reduction (0.994543), and higher throughput improvement (0.89912) than standalone methods. PSO excels in reducing wait times (0.7934), while GWO shows reasonable performance across a range of metrics. The hybrid approach leverages the power of both PSO and GWO algorithms, proving to be the most effective solution for smart traffic management. This research highlights using hybrid optimization techniques and IoT (Internet of Things) in developing traffic control systems.

This paper considers problems related to output error models for output data estimation and parameter identification in missing output data systems. In this regard, a new sequentially parallel distributed adaptive signal processing method with the implementation of a low complexity least squares algorithm is introduced to estimate the parameters of an auxiliary model relative to the original system, as well as handling irregularly missing output data in a stochastic framework. The validation of the proposed distributed architecture using the low complexity least squares algorithm is presented in terms of computational complexity and processing time. Measurement results show that the proposed architecture using the low complexity least squares approach provides fast convergence, parallel linear computational complexity, and significantly reduced processing time compared to the sequentially operated recursive least square (RLS) algorithm for parameter identification in missing output data systems. Finally, the effectiveness of the low complexity least squares algorithm is tested with a system example

Abstract The research aims to assess the water quality of the Tharthar Canal and its suitability for human activities in the study area by conducting physical and chemical analyzes of that water and showing its suitability for human uses. The results of the study show that most of the samples in the study area are not suitable for human use, especially drinking. The total hardness, sulfate and calcium values were determined only after filtering and processing to become drinkable, while laboratory analyzes showed that they are suitable for agricultural use in all samples of the study area. Because of the importance of the research, the physical and chemical properties were addressed to find out if they were affected by the natural or human geographical characteristics and their impact on the residents of the nearby areas and their various activities to find out the problems and develop appropriate solutions that would address the problems and adopt it as a fixed water source. It became clear through the field study that the Al-Tharthar-Euphrates Canal is not approved by the population as a main water resource, but most of the residents of the areas relied on wells for their various activities, foremost of which is agriculture and drinking.

Background: Obesity in children is a critical public health issue in developed countries and developing countries. The establishment of health-related behaviors in childhood, significantly influenced by parental involvement, underscores the need for effective intervention measures. Aim: This original research is a systematic review and meta-analysis that aimed to investigate the impact of parental involvement on the prevention and management of childhood obesity, focusing on outcomes such as BMI z-score, exercise levels, screen time, dietary self-efficacy, and percentage body fat. Methods: Adhering to the PRISMA guidelines, we conducted a systematic review and meta-analysis of 12 randomized controlled trials (RCTs) identified through comprehensive searches of PubMed, Scopus, Web of Science, and the Cochrane Library, including RCTs involving children aged 2–18 years with parental or caregiver participation, reporting on the specified outcomes. Data analysis was performed using RevMan 5.3, employing a random effects model. Results: A total of 5573 participants were included. The meta-analysis revealed a significant reduction in BMI z-score (MD = −0.06, 95% CI: −0.09 to −0.02, p = 0.005, I2 = 58%), a non-significant increase in exercise levels (SMD = 0.26, 95% CI: −0.01 to 0.52, p = 0.05, I2 = 52%), and a significant reduction in screen time (MD = −0.36 h per day, 95% CI: −0.61 to −0.11, p = 0.005, I2 = 0%). Dietary self-efficacy also improved significantly (MD = 0.59, 95% CI: 0.12 to 1.05, p = 0.01, I2 = 0%). However, changes in percentage body fat did not reach statistical significance (MD = −1.19%, 95% CI: −2.8% to 0.41%, p = 0.15, I2 = 0%). Conclusion: Parental involvement in childhood obesity interventions significantly impacts BMI z-score, exercise levels, screen time, and dietary self-efficacy but not percentage body fat. These findings highlight the importance of engaging parents in obesity prevention and management strategies.

Nasser Abu-El-Noor,1,2,* Yousef Aljeesh,1,2,* Saeb Aliwaini,2,3,* Sohaib Alhamss,2,4,* Reda Darwish,2,* Mysoon Abu-El-Noor1,2,* 1Faculty of Nursing, Islamic University of Gaza, Gaza, Palestine; 2Research and Development Center at Turkish-Palestinian Friendship Hospital, Gaza, Palestine; 3Faculty of Science, Islamic University of Gaza, Gaza, Palestine; 4Faculty of Medicine, Islamic University of Gaza, Gaza, Palestine*These authors contributed equally to this workCorrespondence: Mysoon Abu-El-Noor, Islamic University of Gaza, PO Box 108, Gaza, Palestine, Tel + 970 8 2832000, Fax + 970 8 2644800, Email maziz@iugaza.edu.psPurpose: The purpose of this study was to (1) identify the priorities of oncology research in the Gaza Strip; (2) explore the needs for improving oncology research in the Gaza Strip, Palestine.Participants and Methods: A qualitative approach for data collection was used in this study. After obtaining the ethical approvals to conduct this study, a sample of 42 health-care providers who are involved in providing oncology care and research in the Gaza Strip were included in this study. Data were collected by the researchers through seven focus groups. Thematic coding was used for data analysis. Two main themes and several sub-themes were extracted during the data analysis.Results: The two main themes extracted from data analysis were research priorities and research needs. Participants identified several priorities in relation to oncology research that are assessing for cancer awareness, cancer prevention, exploring and finding new molecular biomarkers, screening for germ-line mutations related to the most common cancers, determining genetic and environmental risk factors for developing cancer, and exploring and testing new cancer therapies. Concerning research needs, participants identified several needs to enhance oncology research, which are financial needs, need for training, availability of data, creation of interdisciplinary research teams, and transforming in vitro studies to in vivo.Conclusion: Well-designed studies will certainly help to identify the priorities and needs to improve oncology research in the Gaza Strip, which is considered one of the most important steps to help push these priorities onto the agenda of health policymakers. Therefore, they will work to set goals and design policies and programs aiming to reduce incidence and prevalence rates of cancer in the Gaza Strip, promote early detection of cancer, improve prognosis, and reduce mortality related to cancer.Keywords: research needs, research priorities, oncology care, focus group, gaza strip

Accurately prediction of dispersion and polydispersity of droplet flow is not a trivial task due to the complex behavior of the droplet size distribution (DSD) and the strong state of the instantaneous velocity of a droplet on the shape and size of the droplet. Describing the distribution of sizes and velocities of droplets initially formed in sprays is an essential piece of information needed in spray modeling, which is used to define the initial state of the spray droplets in the downstream two-phase flow fields’ predictive computations. The predictive model for the droplet size and velocity distributions in sprays is formulated as the droplet’s velocity magnitude has a power–law relationship with the droplet in this study. The present model incorporates the deterministic and stochastic aspects of the spray formation process. The quadrature method of moments (QMOM) is applied to solve numerically the transport equations of the probability density function coupled with conserved source terms incompressible Navier-Stokes equations for the liquid phase. The sub-models are connected by different source terms signifying the liquid-gas interaction. Equations of transport for spray moments are derived from DSD, and closure is attained using a gamma distribution. The integer spray moments concerning the volume are used to construct the continuous distribution of QMOM. In contrast, the velocity moments are used to determine the droplet velocity as a constant function of the droplet diameter. The model is first applied to simulate a diesel spray tip penetration under nonreactive conditions with different droplet velocity profiles to validate the approach with experimental data. An additional case of a liquid nitrogen spray is applied to show the gamma distribution’s ability to describe spray drop size distribution. The model generally predicts reasonable agreement with the experimental for both cases.

Actinomycetes (Actinobacteria) are Gram-positive bacteria that grow in a variety of environments and have a filamentous shape similar to fungi. The actinomycetes distinguish themselves morphologically by forming a layer of hyphae that carry chains of spores. The aim of this study was to update the recent developments related to the actinomycetes. Streptomyces; as an actinomycete, is known for producing a number of bioactive secondary metabolites, including anti-tumour agents; antibiotics, antifungals, antivirals, anti-hypertension drugs, and immunosuppressives. In order to compete with other microorganisms, including those of the same genera, Streptomyces species produce several secondary metabolites. However, despite the discovery of antibiotics, the infectious diseases remain the second- leading cause of death worldwide. Each year, around 17 million people die from bacterial infections; mainly children and the elderly. In addition to the overuse of antibiotics, a key factor contributing to antibiotic resistance is self-medication, which reduces the lifespan of antibiotics.

The emergence of antibiotic-resistant microorganisms poses a significant threat to human health worldwide. Recent advances have led to the discovery of molecules with potent antimicrobial activity from environmental sources. In this study, fifteen bacterial isolates were obtained from agricultural and polluted soil samples collected from different areas of the cities of Jizan and Jeddah. These isolates were screened for antagonistic activity against a set of human pathogenic bacterial strains. The results showed that two Bacillus strains, identified as Bacillus atrophaeus and Bacillus amyloliquefaciens based on 16S rDNA, synthesized bacteriocin with strong antibacterial activity against Methicillin-resistant Staphylococcus aureus (MRSA) ATCC 33591, Pseudomonas aeruginosa ATCC 9027, Salmonella typhimum ATCC 14028, carbapenem-resistant E. coli, and MRSA 2. To optimize bacteriocin production, the effects of medium composition, incubation period, temperature, and pH were investigated. Nutrient broth and Mueller–Hinton broth were chosen as the optimal original media for bacteriocin production. The optimal incubation period, temperature, and pH were found to be 48 h at 37 °C and 7 pH in Bacillus atrophaeus and 72 h at 37 °C and 8 pH in Bacillus amyloliquefaciens. Batch cultures of Bacillus atrophaeus and Bacillus amyloliquefaciens were grown in a 10 L benchtop bioreactor, and pH control was found to significantly increase the production of bacteriocin by two-fold compared to uncontrolled conditions. The time course of growth, substrate consumption, pH, and enzyme production were investigated. This study demonstrates the potential of optimizing culture conditions and batch process control to enhance bacteriocin production by Bacillus spp.

The Analytical Hierarchy Process (AHP) is a mathematical method which is considered This method is considered one of the most accurate methods in terms of making decisions by providing multiple options so that the decision-maker can calibrate and evaluate the alternatives. The city of Baghdad suffers from stifling traffic congestion due to the increase in population, which leads to a significant increase in the number of trips inside and outside the city, and with this, the number of vehicles is more than the capacity of the city’s road network; especially on the Karkh side. Three alternative roads were proposed in the network; namely: the first alternative is the fourth ring road that connects the Abu Ghraib highway and the roundabout bridge, the second road represents the link between the Washash roundabout and the Muthanna Airport intersection, the third alternative is constructing a tunnel from the Al-Paratha Mosque intersection in the direction of Haifa Street. The purpose of the study is to analyze and select the best alternative by using multi-criteria decision-making. Based on the results, it appears that the economic factor has the greatest effect on the selection of alternatives with its weight equal to 55%, followed by the accessibility factor with a weight of 29.8%. Although the second alternative was chosen as the best alternative in this manuscript, the first alternative is also important in terms of reducing traffic congestion and truck crossing within the city. To increase the efficiency of the network, it is proposed to implement the first and second proposals as well as widen the study region.

Experiments on female fruit flies reveal more about the molecular mechanisms involved as germline stem cells transition to become egg cells.

The retinal ganglion cell (RGC) competence factor ATOH7 is dynamically expressed during retinal histogenesis. ATOH7 transcription is controlled by a promoter-adjacent primary enhancer and a remote shadow enhancer (SE). Deletion of the ATOH7 human SE causes nonsyndromic congenital retinal nonattachment (NCRNA) disease, characterized by optic nerve aplasia and total blindness. We used genome editing to model NCRNA in mice. Deletion of the murine SE reduces Atoh7 messenger RNA (mRNA) fivefold but does not recapitulate optic nerve loss; however, SEdel/knockout (KO) trans heterozygotes have thin optic nerves. By analyzing Atoh7 mRNA and protein levels, RGC development and survival, and chromatin landscape effects, we show that the SE ensures robust Atoh7 transcriptional output. Combining SE deletion and KO and wild-type alleles in a genotypic series, we determined the amount of Atoh7 needed to produce a normal complement of adult RGCs, and the secondary consequences of graded reductions in Atoh7 dosage. Together, these data reveal the workings of an evolutionary fail-safe, a duplicate enhancer mechanism that is hard-wired in the machinery of vertebrate retinal ganglion cell genesis.