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Ahmed Hussein Subki,1 Abdel Moniem Mukhtar,2 Omar M Saggaf,1 Ragaa A Ali,3 Khalid A Khalifa,3 Dalia M Al-Lulu,3 Mohammed Saad Alsallum,1 Diyaa H Bokhary,1 Ayman M Baabdullah,1 Sulaiman M Kassar,1 Basil M Jan,4 Muhab M Hindi,1 Mohammed M Jan1 1Department of Pediatrics, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia; 2Department of Family and Community Medicine, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia; 3Batterjee Medical College, Jeddah, Saudi Arabia; 4Faculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia Background: Epilepsy is a common neurological disorder in childhood. However, there have been limited studies on its impact on the oral health of affected children. Our study aimed to assess the oral health of children with epilepsy in the city of Jeddah, Saudi Arabia, as perceived by their mothers. Methods: We conducted a cross-sectional study in three hospitals. We included children 2–18 years old with physician-confirmed epilepsy diagnosis. We assessed parental perception of dental status and need for dental care using a standardized questionnaire that was completed by the mothers. To adjust for potential confounding variables, we used univariate and multivariate logistic regression. Results: We included 96 children with epilepsy in our study. Their mean age was 6.4±3.4 years. In 55.2% (n=53), dental status was rated as bad, and in 84.4% (n=81) a need for dental care was expressed. Cerebral palsy (OR 5.06, 95% CI 1.28–19.99; P=0.021), motor disability (OR 6.41, 95% CI 1.12–36.73; P=0.037), referral from a pediatric neurology clinic to a dentist (OR 10.755, 95% CI 3.290–35.151; P

Reem A Ali,1 Ahlam Alnatour,2 Karimeh Alnuaimi,1 Fatmeh Alzoubi,1 Maysa Almomani,3 Areej Othman4 1Department of Maternal and Child Health Nursing, Faculty of Nursing, Jordan University of Science and Technology, Irbid, Jordan; 2Department of Community and Mental Health Nursing, Faculty of Nursing, Jordan University of Science and Technology, Irbid, Jordan; 3Department of Adult Health Nursing, Faculty of Nursing, Jordan University of Science and Technology, Irbid, Jordan; 4Department of Maternal and Child Health Nursing, School of Nursing, The University of Jordan, Amman, Jordan Background: Youths in Jordan lack knowledge related to reproductive health (RH). Interactive teaching methods showed positive results in enhancing health awareness and adopting healthy practices among students. Objectives: The objective of this study was to examine the usefulness of interactive teaching in promoting health awareness of RH among nonmedical university students in Jordan.Methods: We employed a quasi-experimental one group pretest and posttest design for a purposive sample of 210 students (18–24 years). Knowledge and attitudes regarding RH issues were assessed using a questionnaire developed by the researchers. Results: A significant improvement in students’ knowledge and attitudes toward RH was evident. Female students had higher scores on knowledge than male students in the pretest; this difference was smaller in the posttest. Also, female students had significantly more positive attitudes toward RH in pretest than males, although this difference vanished in the posttest. Study results indicated that students benefit from study intervention regardless their gender. Conclusion: Integrating RH into university’s curriculum coupled with interactive learning approach is a powerful way to promote RH awareness among youths. Keywords: STIs, young adult, family planning, premarital examination, health promotion

Abstract Morphine, as one of the most important narcotic drugs, significantly affects the nervous system and increases euphoria, which raises the likelihood of its misuse. Therefore, its measurement is of great importance. In this work, a new electrochemical sensor based on a nanocomposite of CuS/g-C3N5/AgNPs was developed for modifying Screen printed carbon electrodes (SPCEs) and used for the measurement of morphine through cyclic voltammetry and differential pulse voltammetry. Various analytical methods initially characterized the nanocomposite. The prepared sensor, which also has an extensive surface area, achieved a detection limit of 0.01 µM for morphine in a concentration range of 0.05–100 µM at pH 7. Besides its excellent capability in measuring morphine in real samples, the sensor exhibits good stability, reproducibility, and repeatability. The presence of CuS, due to its excellent high surface area alongside silver nanoparticles, leads to an increase in the conductivity of the g-C3N5 modified electrode, resulting in an increased oxidative current of morphine at the surface of the prepared sensor. Therefore, measuring low concentrations of morphine with this sensor was made possible. Additionally, measuring morphine without interference from various species is a strong point of the electrochemical sensor for morphine detection, and combined with the simplicity and ease of the method, it allows for morphine measurements to be conducted in the shortest possible time.

Abstract Vaccine acceptance is a crucial component of a viable immunization program in healthcare system, yet the disparities in new and existing vaccination adoption rates prevail across regions. Disparities in the rate of vaccine acceptance result in low immunization coverage and slow uptake of newly introduced vaccines. This research presents an innovative AI-driven predictive model, designed to accurately forecast vaccine acceptance within immunization programs, while providing high interpretability. Primarily, the contribution of this study is to classify vaccine acceptability into Low, Medium, Partial High, and High categories. Secondly, this study implements the Feature Importance method to make the model highly interpretable for healthcare providers. Thirdly, our findings highlight the impact of demographic and socio-demographic factors on vaccine acceptance, providing valuable insights for policymakers to improve immunization rates. A sample dataset containing 7150 data records with 31 demographic and socioeconomic attributes from PDHS (2017–2018) is used in this paper. Using the LightGBM algorithm, the proposed model constructed on the basis of different machine-learning procedures achieved 98% accuracy to accurately predict the acceptability of vaccines included in the immunization program. The association rules suggest that higher SES, region, parents’ occupation, and mother’s education have an association with vaccine acceptability.

Unhealthy eating habits and a high intake of energy, salt, sugar, fat and trans-fatty acids are introduced as dietary risk factors for non-communicable diseases (NCDs). Since one of the key strategies to combat high-risk food behaviors in families is the establishment of healthy eating habits by mothers, this study aims to investigate the effect of nutrition traffic light (TL) education on mothers’ knowledge, attitude and practice. This semi-experimental intervention was conducted among 84 mothers covered by the health centers of Shahid Beheshti University of Medical Sciences, Tehran, Iran. The participants were randomly divided into the intervention and control groups (42 participants in each group). Data were collected through a standard questionnaire at three points (before, one week after, and one month after the intervention) across 12 sessions from June 15 to August 15, 2022. The data were analyzed using repeated measures ANOVA, t-test, and chi-square test through SPSS software, version 21. After education, the mean scores of knowledge, attitude and practice improved from 8.61±1.36, 25±2.81 and 22.61±8.6 to 11.71±0.63, 28.04±2.52 and 28.38±4.74, respectively. A comparison of the two groups revealed a significant increase in the scores of knowledge, attitude and practice in the intervention group compared to the control group (P

Abstract In this study, a novel magnetic and pH-responsive nanocarrier was developed, incorporating both natural and synthetic polymers, for delivering curcumin (CUR) to breast cancer cells. For this purpose, CuFe2O4@poly(methacrylic acid) (CuFe2O4@PMAA) nanogel was developed and conjugated with amino-modified lignin (Lignin-adipic acid dihydrazide conjugate, Lig-ADH) to achieve the CuFe2O4@PMAA@Lig-ADH nanocarrier. The morphology, structure, and physical properties of the synthesized nanomaterials were examined using a range of techniques, including transmission electron microscopy (TEM), field emission scanning electron microscopy (FESEM), Fourier transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD), energy dispersive X-ray (EDX), and vibrating sample magnetometer (VSM). The synthesized nanocarrier exhibited a spherical shape, with an average diameter of approximately 15 nm, and demonstrated good magnetic responsiveness. Moreover, the in vitro drug release was found to be pH-dependent, with an increased release rate in acidic conditions. To evaluate cytotoxicity, the survival of MCF-7 cells was measured using the MTT assay for 24 h. Notably, the synthesized CuFe2O4@PMAA@Lig-ADH@CUR and CUR exhibited significant cytotoxic effects, effectively eliminating MCF-7 cells with IC50 values of 39.80 µg/mL and 4.27 µg/mL, respectively. Also, the significant intracellular uptake of NPs was confirmed by FITC and DAPI staining after 4 h. This research highlighted the potential of CuFe2O4@PMAA@Lig-ADH@CUR as a highly effective nano-delivery system and demonstrated a straightforward method for utilizing renewable lignin.

Abstract The porous underground structures have recently attracted researchers’ attention for hydrogen gas storage due to their high storage capacity. One of the challenges in storing hydrogen gas in aqueous solutions is estimating its solubility in water. In this study, after collecting experimental data from previous research and eliminating four outliers, nine machine learning methods were developed to estimate the solubility of hydrogen in water. To optimize the parameters used in model construction, a Bayesian optimization algorithm was employed. By examining error functions and plots, the LSBoost method with R² = 0.9997 and RMSE = 4.18E-03 was identified as the most accurate method. Additionally, artificial neural network, CatBoost, Extra trees, Gaussian process regression, bagged trees, regression trees, support vector machines, and linear regression methods had R² values of 0.9925, 0.9907, 0.9906, 0.9867, 0.9866, 0.9808, 0.9464, and 0.7682 and RMSE values of 2.13E-02, 2.43E-02, 2.44E-02, 2.83E-02, 2.85E-02, 3.40E-02, 5.68E-02, and 1.18E-01, respectively. Subsequently, residual error plots were generated, indicating the accurate performance of the LSBoost model across all ranges. The maximum residual error was − 0.0252, and only 4 data points were estimated with an error greater than ± 0.01. A kernel density estimation (KDE) plot for residual errors showed no specific bias in the models except for the linear regression model. To investigate the impact of temperature, pressure, and salinity parameters on the model outputs, the Pearson correlation coefficients for the LSBoost model were calculated, showing that pressure, temperature, and salinity had values of 0.8188, 0.1008, and − 0.5506, respectively, indicating that pressure had the strongest direct relationship, while salinity had an inverse relationship with hydrogen solubility. Considering the results of this research, the LSBoost method, alongside approaches like state equations, can be applied in real-world scenarios for underground hydrogen storage. The findings of this study can help in a better understanding of hydrogen solubility in aqueous solutions, aiding in the optimization of underground hydrogen storage systems.

Abstract Glioblastoma multiforme (GBM) is the most common harmful high-grade brain tumor with high mortality and low survival rate. Importantly, besides routine diagnostic and therapeutic methods, modern and useful practical techniques are urgently needed for this serious malignancy. Correspondingly, the translational medicine focusing on genetic and epigenetic profiles of glioblastoma, as well as the immune framework and brain microenvironment, based on these challenging findings, indicates that key clinical interventions include immunotherapy, such as immunoassay, oncolytic viral therapy, and chimeric antigen receptor T (CAR T) cell therapy, which are of great importance in both diagnosis and therapy. Relatively, vaccine therapy reflects the untapped confidence to enhance GBM outcomes. Ongoing advances in immunotherapy, which utilizes different methods to regenerate or modify the resistant body for cancer therapy, have revealed serious results with many different problems and difficulties for patients. Safe checkpoint inhibitors, adoptive cellular treatment, cellular and peptide antibodies, and other innovations give researchers an endless cluster of instruments to plan profoundly in personalized medicine and the potential for combination techniques. In this way, antibodies that block immune checkpoints, particularly those that target the program death 1 (PD-1)/PD-1 (PD-L1) ligand pathway, have improved prognosis in a wide range of diseases. However, its use in combination with chemotherapy, radiation therapy, or monotherapy is ineffective in treating GBM. The purpose of this review is to provide an up-to-date overview of the translational elements concentrating on the immunotherapeutic field of GBM alongside describing the molecular mechanism involved in GBM and related signaling pathways, presenting both historical perspectives and future directions underlying basic and clinical practice. Graphical Abstract

Abstract The concept of happiness is becoming an increasingly significant area of focus in the evaluation of overall quality of life. This research examines the impact of migration on the well-being of women who remain in their place of residence following the migration of their family members. The study employs data from the Multiple Indicators Cluster Survey (2017–2018) in Punjab, Pakistan, and addresses sample selection bias through Propensity Score Matching (PSM). Moreover, as the dependent variable is ordinal, the study employed ordered logistic regression to examine the correlation between migration and happiness, taking into account migration status and other variables. The findings indicate that women from migrant backgrounds tend to benefit from migrating, primarily in terms of enhanced financial resources. In order to gain insight into the varying effects of migration on women’s happiness, the study employed heterogeneity analysis, which revealed that the influence of migration on women’s happiness differs across various areas. In conclusion, the combination of propensity score matching (PSM) with ordered logistic regression and heterogeneity analysis represents a robust methodology for evaluating the impact of migration on women’s perceptions of happiness. The study demonstrates that migration has the potential to improve the quality of life of women who remain in their home countries, particularly those residing in financially disadvantaged households.

Abstract Accurate classification of rail transit stations is crucial for successful Transit-Oriented Development (TOD) and sustainable urban growth. This paper introduces a novel classification model integrating traditional methodologies with advanced machine learning algorithms. By employing mathematical models, clustering methods, and neural network techniques, the model enhances the precision of station classification, allowing for a refined evaluation of station attributes. A comprehensive case study on the Chengdu rail transit network validates the model’s efficacy, highlighting its value in optimizing TOD strategies and guiding decision-making processes for urban planners and policymakers. The study employs several regression models trained on existing data to generate accurate ridership forecasts, and data clustering using mathematical algorithms reveals distinct categories of stations. Evaluation metrics confirm the rationality and accuracy of the results. Additionally, a neural network achieving high accuracy on labeled data enhances the model’s predictive capabilities for unlabeled instances. The research demonstrates high accuracy, with the Mean Squared Error (MSE) for regression models (Multiple Linear Regression (MLR), Deep-Learning Neural Network (DNN), and K-Nearest Neighbor (KNN)) remaining below 0.012, while the neural networks used for station classification achieve 100% accuracy across seven time intervals and 98.15% accuracy for the eighth, ensuring reliable ridership forecasts and classification outcomes. Accuracy in rail transit station classification is critical, as it not only strengthens the model’s predictive capabilities but also ensures more reliable data-driven decisions for transit planning and development, allowing for more precise ridership forecasts and evidence-based strategies for optimizing TOD. This classification model provides stakeholders with valuable insights into the dynamics and features of rail transit stations, supporting sustainable urban development planning.

Abstract The disease dynamics affect the human life. When one person is affected with a disease and if it is not treated well, it can weaken the immune system of the body. Human Immunodeficiency Virus (HIV) is a virus that attacks the immune system, of the body which is the defense line against diseases. If it is not treated well then HIV progresses to its advanced stages and it is known as Acquired Immunodeficiency Syndrome (AIDS). HIV is typically a disease that can transferred from one person to another in several ways such as through blood, breastfeeding, sharing needles or syringes, and many others. So, the need of the hour is to consider such important disease dynamics and that will help mankind to save them from such severe disease. For the said purpose the reaction-diffusion HIV CD4 $$^{+}$$ + T cell model with drug therapy under the stochastic environment is considered. The underlying model is numerically investigated with two time-efficient schemes and the effects of various parameters used in the model are analyzed and explained in a real-life scenario. Additionally, the obtained results will help the decision-makers to avoid such diseases. The random version of the HIV model is numerically investigated under the influence of time noise in It $${\hat{o}}$$ o ^ sense. The proposed stochastic backward Euler (SBE) scheme and proposed stochastic Implicit finite difference (SIFD) scheme are developed for the computational study of the underlying model. The consistency of the schemes is proven in the mean square sense and the given system of equations is compatible with both schemes. The stability analysis proves that both schemes and schemes are unconditionally stable. The given system of equations has two equilibria, one is disease-free equilibrium (DFE) and the other is endemic equilibrium. The simulations are drawn for the different values of the parameters. The proposed SBE scheme showed the convergent behavior towards the equilibria for the given values of the parameters but also showed negative behavior that is not biological. The proposed SIFD scheme showed better results as compared with the stochastic SBE scheme. This scheme has convergent and positive behavior towards the equilibria points for the given values of the parameters. The effect of various parameters is also analyzed. Simulations are drawn to evaluate the efficacy of the schemes.

Abstract Background Transcatheter aortic valve implantation (TAVI) is a growing treatment for aortic stenosis, but anatomical variations exist across populations. Asians tend to have smaller aortic annuli and higher bicuspid valve morphology compared to Westerners, potentially impacting TAVI valve selection and outcomes. This study analyzes aortic root parameters in Pakistani patients undergoing TAVI. Results We conducted a retrospective analysis of 78 patients who underwent TAVI at the Peshawar Institute of Cardiology from January 2021 to March 2024. Pre-procedural CT scans were analyzed for aortic annulus diameters, area, and other relevant parameters. The mean age was 72.41 years (SD ± 11.99), and 61.5% were male. Aortic annulus diameters (minimum, mean, maximum) were 21.18 mm (SD ± 3.99), 24.21 mm (SD ± 3.93), and 27.49 mm (SD ± 4.43), respectively. Bicuspid aortic valves were present in 34.61% of patients. Conclusions Our findings suggest that Pakistani patients undergoing TAVI may have aortic root dimensions comparable to Western populations, with a substantial prevalence of bicuspid valves. However, coronary heights were similar to those reported in Asian populations with smaller annuli. Further studies are needed to assess TAVI outcomes in Pakistani patients and determine if tailored valve sizing strategies are required.

The contemporary world is marked by generation and consumption of vast volume, high velocity, and considerable diverse data, leading us to the concept of big data. In this study, a system design thinking approach was employed to identify the requirements of Iran's public sector big data system. National big data systems would help governments to support their decisions by data and answer to national problems faster. Given the complexity and time-intensive nature of traditional system requirement analysis methods, their practical application in the industry has been declined. Therefore, in this research, system design thinking as an agile alternative for identifying system requirements has been discussed. To accomplish this, the LDA machine learning method has been utilized to analyze approximately 88,000 articles, a thematic analysis on around 600 Instagram and Twitter posts has been conducted, and six experts representing targeted problem persona were interviewed. The objective of this research is to extract insights to serve as a foundation for formulating big data policies in Iran. Findings reveal that Iran big data system requirements can be classified into four categories which indicate on increasing managed access to data while considering security and privacy, encouraging private and public sectors cooperation, transformation to smart governance, and establishing national data organization which would be responsible of data ID documents.

Abstract Background Triglyceride-glucose index (TyG), a surrogate marker of insulin resistance (IR), could be a potential prognostic marker in patients with acute coronary syndromes (ACS). We evaluated the effect of the TyG index on major adverse cardiac and cerebrovascular events (MACCE) in patients with ACS undergoing percutaneous coronary intervention (PCI). Methods This registry-based cohort study was conducted at Tehran Heart Center from 2015 to 2021 and the median follow-up duration was 378 days. The primary outcome was MACCE and the secondary outcomes were MACCE components: all-cause mortality, myocardial infarction, stroke, target vessel revascularization, target lesion revascularization, and coronary artery bypass grafting. For comparison among TyG quartiles (Q), the log-rank test was used. Unadjusted and adjusted hazard ratios (HRs) and their 95% confidence intervals (CIs) were used to describe the association between TyG quartiles and MACCE. A subgroup of euglycemic patients was also evaluated. Results A total of 13,542 patients were included. Patients in the fourth TyG quartile (Q4) were younger, had higher mean BMI, and higher prevalence of hypertension, diabetes, and dyslipidemia. The adjusted Cox model showed that a 1-unit increment of the TyG index was associated with a significantly higher risk of MACCE (aHR 1.18, 95% CI 1.08 to 1.30, p

Abstract The study investigates the interplay of land use dynamics and climate change on the hydrological regime of the Ravi River using a comprehensive approach integrating Geographic Information System (GIS), remote sensing, and hydrological modeling at the catchment scale. Employing the Soil and Water Assessment Tool (SWAT) model, simulations were conducted to evaluate the hydrological response of the Ravi River to both current conditions and projected future scenarios of land use and climate change. This study differs from previous ones by simulating future land use and climate scenarios, offering a solid framework for understanding their impact on river flow dynamics. Model calibration and validation were performed for distinct periods (1999–2002 and 2003–2005), yielding satisfactory performance indicators (NSE, R2, PBIAS = 0.85, 0.83, and 10.01 in calibration and 0.87, 0.89, and 7.2 in validation). Through supervised classification techniques on Landsat imagery and TerrSet modeling, current and future land use maps were generated, revealing a notable increase in built-up areas from 1990 to 2020 and projections indicating further expansion by 31.7% from 2020 to 2100. Climate change projections under different socioeconomic pathways (SSP2 and SSP5) were derived for precipitation and temperature, with statistical downscaling applied using the CMhyd model. Results suggest substantial increases in precipitation (10.9 − 14.9%) and temperature (12.2 − 15.9%) across the SSP scenarios by the end of the century. Two scenarios, considering future climate conditions with current and future land use patterns, were analyzed to understand their combined impact on hydrological responses. In both scenarios, inflows to the Ravi River are projected to rise significantly (19.4 − 28.4%) from 2016 to 2100, indicating a considerable alteration in seasonal flow patterns. Additionally, historical data indicate a concerning trend of annual groundwater depth decline (0.8 m/year) from 1996 to 2020, attributed to land use and climate changes. The findings underscore the urgency for planners and managers to incorporate climate and land cover considerations into their strategies, given the potential implications for water resource management and environmental sustainability.

Abstract Background Sea buckthorn (Hippophae rhamnoides), a deciduous species plant, is widely distributed around the globe, and native to the cold-temperate regions of Europe and Asia. This medicinal herb contains several bioactive constituents including chlorogenic acid. The conventional methods used for the extraction of phenolic antioxidants from natural herbs often result in low yields, high toxicity, and pose environmental hazards limiting their effectiveness and scalability. Therefore, green extraction techniques using deep eutectic solvents, composed of natural, non-toxic, and biodegradable components were applied for extraction of chlorogenic acid from sea buckthorn weed. Fourteen deep eutectic solvent mixtures were prepared and evaluated for extraction yield of chlorogenic acid. Parameters such as hydrogen bond donor-to-hydrogen bond acceptor ratio, liquid-to-solid ratio, shaking speed, and shaking time were optimized for the best mixture. Results The combination of lactic acid and maltose (1:1) was found to give best extraction yield using response surface methodology. The deep eutectic solvent system under optimum conditions produced 12.2 g/100 g of crude extract sea buckthorn containing 174.7 mg gallic acid equivalents (mg GA)/g) of extract. Moreover, the optimized extract exhibited appreciable radical scavenging capacity (91%), trolox equivalent antioxidant capacity (11.2% of extract), and inhibition of peroxide in linoleic acid (80.6%). High-performance liquid chromatography-based characterization revealed the extracts contained chlorogenic acid (20.1 mg/g of extract) as the major constituent. Conclusions In summary, the adoption of DES for the extraction of bioactive phenolic constituents from sea buckthorn offers multiple benefits, including economic efficiency, enhanced extraction performance, and environmental sustainability. The findings of this study not only advance the understanding of DES in phytochemical extraction but also pave the way for broader application of green solvents in the natural products industry. Future research should focus on further optimizing DES formulations and scaling up the extraction process to fully realize the potential of this innovative extraction method in commercial applications.

Abstract Stochastic delayed modeling has a significant non-pharmaceutical intervention to control transmission dynamics of infectious diseases and its results are close to the reality of nature. The covid-19 has been controlled globally but there is still a threat and appears in different variants like omicron and SARS-CoV-2 etc. globally. This article, considered pattern a mathematical model based on Susceptible, Infected, and recovered populations with highly nonlinear incidence rates. we studied the dynamics of the coronavirus model; a newly proposed version is a stochastic delayed model that is based on nonlinear stochastic delayed differential equations (SDDEs). Transition probabilities and parametric perturbation methods were used for the construction of the stochastic delayed model. The fundamental properties like positivity, boundedness, existence and uniqueness, and stability results of equilibria of the model with certain conditions of reproduction number are studied regularly. Also, the extinction and persistence of disease are studied with the help of well-known theorems. The numerical methods used to find a visualization of results due to the complexity of stochastic delayed differential equations. Furthermore, for computational analysis, we implemented existing methods in the literature and compared their results with the proposed method like nonstandard finite difference for stochastic delayed model. The proposed method restores all dynamical properties of the model with a free choice of time steps.

The gene editing and synthetic biological tools have led to the implementation of diverse metabolic engineering approaches to enhance the production of specific enzymes. Microbial keratinases can convert keratin wastes into valuable compounds for mankind. Since the market for keratinases cannot be satisfied by production from wild hosts, it is obligatory to develop hosts with high keratinase yields. The intention of this review is to evaluate microbial keratinase advancement through protein engineering, breeding techniques, and fermentation optimization. The main aim of protein engineering is to improve the heat resistance ability and catalytic activity of keratinases by employing mutagenesis methods. Moreover, modifying the expression elements and host engineering are also two unique ways to augment the keratinase yield. Intending to accelerate the production of modified keratinase, this review attempts to highlight the optimization of expression elements, such as promoter engineering, UTR, signal peptide, and codon optimization. Moreover, the approaches of host engineering including strengthening precursor supply, membrane surface engineering, and optimization of secretion pathways were also explained here. Furthermore, it is also essential to optimize the medium composition and fermentation condition for high keratinase yield. This review also addressed the present advancements, difficulties, and tendencies in the field of microbial keratinase production, along with its potential.

Delay factors demonstration has a significant role in controlling a strain of infectious disease instead of a pharmaceutical strategy. According to the World Health Organization (WHO), 3–5 million cases are reported annually and approximately 290,000 to 650,000 respiratory deaths annually. So, in the present study, we develop a delayed mathematical model based on delay differential equations (DDEs) for the influenza epidemic using a deterministic approach by introducing double delay parameters. The four distinct sub-populations are considered susceptible, exposed, infected, and recovered. For the rigorous analysis, the fundamental properties of the model like positivity, boundedness, existence, and uniqueness, were studied. The influenza-free equilibrium (IFE) and influenza-existing equilibrium (IEE), are the two nonnegative equilibrium points that the model demonstrates. Both locally and globally, the asymptotic stability of the equilibrium points of the model is established and shown under specific situations of reproduction number. Additionally, investigated the model's parameter sensitivity and determined the relative sensitivity of each parameter. Both standard and nonstandard methods—such as Euler, Runge-Kutta, and nonstandard finite difference with a delayed sense—are presented to make computational analysis support a dynamical analysis and the best visualization of results. The stability of the non-standard finite difference scheme is thoroughly analyzed around the steady states of the model. Additionally, the results show that the nonstandard finite difference approximation is an efficient, cost-effective method, independent of time step size, to solve such highly nonlinear and complex real-world problems.

Background: In the last decade, the use of microwave ovens throughout the world, including Iran, has increased significantly. Therefore, it is important to understand the knowledge, attitude, and behavior of microwave oven use among employees of the Eastern Health Center to promote safe and responsible practices in the workplace. Assessing their familiarity and attitudes with microwave ovens, this study aims to identify potential areas for improvement and training. This, in turn, can create a safer and more efficient work environment for all involved. Methods: In this cross-sectional study in 2022, the study population was all employees working in the health center and comprehensive health service centers affiliated with the East of Shahid Beheshti University of Medical Sciences, numbering 162 people. The research tool was a questionnaire adapted from Nadiri's thesis (2015). After collecting the questionnaires, the data was obtained by SPSS 26 software and were analyzed using Pearson's correlation coefficient, multiple regression, independent t-test, and one-way ANOVA. Results: Although the attitude (36.35±3.579) and the behavior (61.16±6.402) towards using microwave ovens are favorable, there is still room for improvement of knowledge and awareness. Knowledge has a positive and significant effect on behavior (P=0.002, B=0.245) and attitude (P=0.001, B=0.263), which shows that improving knowledge about the safe and responsible use of microwave devices can lead to behavior. and a more favorable attitude among employees. In addition, the attitude has a strong positive and significant effect on behavior (P=0.001, B=0.417), and promoting a positive attitude toward using microwave devices can also lead to more favorable behavior. However, the relatively weak effect of awareness on attitude indicates that other factors may also play a role in determining the attitude toward using microwave devices. Conclusion: These findings highlight the importance of educational and awareness campaigns to promote the safe and responsible use of microwave devices among healthcare workers.

Abstract Today's banking industry achieving sustainable profitability necessitates by integrating economic, environmental, and social factors due to pressing environmental concerns. This study investigates the impact of sustainability on financial performance in the United Arab Emirates (UAE) banking sector, using the Autoregressive Distributed Lag (ARDL) and Bootstrapping ARDL approaches on data from 2002 to 2022. The analysis revealed that economic sustainability, environmental and social sustainability exhibit a significant impact on financial performance in the short run and the long run at a (p

Abstract Background Hermansky-Pudlak Syndrome (HPS), a rare autosomal recessive disorder, is characterized by oculocutaneous albinism, bleeding diathesis, and sometimes severe lung problems and inflammatory bowel disease. Symptoms include skin and hair pigmentation variations, along with visual impairments. Variants in eleven genes encoding protein complexes essential for membrane trafficking and intracellular endosomal transport pathways underlie various recognized HPS subtypes. This study focuses on HPS-9, a subtype of Hermansky-Pudlak Syndrome caused by a variant in the BLOC1S6 gene, which is a subunit of the BLOC1 complex. In this study, a novel Copy Number Variation (CNV) in the aforementioned gene in an Iranian family is reported. The study aims to better understand the etiology of HPS-9 symptoms by identifying and confirming the variant and determining whether the gene is expressed despite the deletion. There have only been five reports of this syndrome in the literature thus far. Our novel CNV represents a significant contribution to understanding the genetic basis of HPS-9. Results This study investigates a male patient presenting with albinism. Whole Exome Sequencing (WES) identified a homozygous deletion of approximately 350 bp using CNV analysis. The deletion affects the intronic region of the BLOC1S6 gene, causing uncertainties in defining the exact boundaries due to WES limitations. Primer walking and GAP-PCR techniques were used to define the deletion boundaries. Subsequent assessments of this variant across other family members helped identify homozygous affected members and heterozygous carriers. The absence of BLOC1S6 expression in the affected individual was confirmed through Real-time PCR experiments. These findings underscore the importance of understanding the implications for the patient’s healthcare and potential therapeutic approaches. Conclusion This study introduces a case of Hermansky-Pudlak Syndrome Type 9 (HPS-9) caused by a homozygous deletion in the BLOC1S6 gene. We identified an approximately 7-kb deletion encompassing exon 1 and the intronic region of the gene. The absence of BLOC1S6 expression, confirmed via Real-time PCR, highlights the importance of studying the pathogenicity of the deletion and its impact on the patient’s health. Our findings contribute to the sparse knowledge on HPS-9 and underscore the need for further exploration into the genetic causes of this rare disorder.

Abstract Efflux-mediated β-lactam resistance is a major public health concern, reducing the effectiveness of β-lactam antibiotics against many bacteria. Structural analyses show the efflux protein TolC in Gram-negative bacteria acts as a channel for antibiotics, impacting bacterial susceptibility and virulence. This study examines β-lactam drug efflux mediated by TolC using experimental and computational methods. Molecular dynamics simulations of drug-free TolC reveal essential movements and key residues involved in TolC opening. A whole-gene-saturation mutagenesis assay, mutating each TolC residue and measuring fitness effects under β-lactam selection, is performed. Here we show the TolC-mediated efflux of three antibiotics: oxacillin, piperacillin, and carbenicillin. Steered molecular dynamics simulations identify general and drug-specific efflux mechanisms, revealing key positions at TolC’s periplasmic entry affecting efflux motions. Our findings provide insights into TolC’s structural dynamics, aiding the design of new antibiotics to overcome bacterial efflux mechanisms.

The aim of this study is to evaluate the Islamic banking sector with the help of financial performance criteria and to reveal whether the sector is sustainable or not. The sustainability analysis uses the latest unit root tests that take into account Fourier expansions. The study uses unit root tests, which are generally used to analyze the sustainability of public debt, with updated versions that differ from the literature and with the help of financial performance indicators of the banking sector for sustainability analysis. The study uses the data of the Islamic banking sector operating in the member countries of the Gulf Cooperation Council (GCC) for the 4th quarter of 2013 and the 2nd quarter of 2022. The quarterly data of “ROA, ROE and Net Profit Margin” are considered as financial performance indicators for sustainability analysis. Although the results of the empirical analysis show different results for each of the financial indicators of Islamic banking in the analyzed countries, in general it shows that the Islamic banking sector operating in all GCC countries except the UAE is sustainable in terms of the financial indicators used in at least one category. These results show that the development of Islamic banking is real and promising for the future. Therefore, the development of projects that contribute to the development of the Islamic financial sector and the support of this sector is an important responsibility for the relevant parties. It is expected that these results will provide important signals to the policymakers of the respective countries and contribute to the healthy development of the Islamic banking sector.

Cranial operations are associated with a high risk of postoperative intracranial hemorrhage (pICH) and venous thromboembolic events, along with increased mortality and morbidity. With the use of acetylsalicylic acid (ASA) for prophylaxis becoming more prevalent, the risk of bleeding when ASA is administered preoperatively is unknown, as are the effects of discontinuation upon the occurrence of thromboembolic events, especially in societies with aging demographics. To address these questions, a retrospective analysis was performed using medical records and radiological images of 1862 patients subjected to brain tumor surgery over a decade in our department. The risk of pICH was compared in patients with metastases receiving ASA treatment versus patients not receiving ASA treatment. The occurrence of venous thromboembolic events after surgery was also evaluated. The study group consisted of 365 patients with different types of brain metastases. In total, 20 patients suffered pICH and 7 of these were associated with clinical neurological deterioration postoperatively. Of the 58 patients who took ASA preoperatively, 2 patients experienced pICH, compared with 5 patients in the non-ASA impact group (p = 0.120). Patients who took ASA were not at significantly higher risk of pICH and therefore a worse outcome compared to the group without ASA. Therefore, these data suggest that in patients at high cardiovascular risk, ASA can be safely continued during elective brain tumor surgery.

Abstract In this work, microcapsules were developed by the complex coacervation of sodium caseinate and pectin as a carrier for saffron extract. Parameters such as Zeta potential, dynamic light scattering, and microscopic techniques were investigated for their influence on the formation of these complexes. Furthermore, Fourier transform infrared (FTIR) analysis confirmed the reaction mechanism between the protein and tannic acid or saffron extract. The study revealed that core/shell and protein/polysaccharide (Pr/Ps) ratios play a role in the encapsulation efficiency (EE) and loading capacity (LC) of saffron extract, with EE and LC ranging from 48.36 to 89.38% and 1.14 to 5.55%, respectively. Thermal gravimetric analysis revealed that the degradation temperature of saffron increased significantly with microencapsulation. The use of tannic acid for hardening the microcapsules led to an increase in size from 13 μm to 27 μm. Rheological findings indicated that shear-thinning behavior in the coacervates, with cross-linking, has a minor effect on the interconnected elastic gel structures. However, cross-linking improved the microcapsules' thermal and structural properties. The increase in polymer chain length due to cross-linking and the presence of the guest molecule (saffron extract) resulted in higher rheological moduli, reflecting enhanced entanglements and correlating well with the thermal, structural, and microstructural properties of the coacervates. Kinetic release studies showed a slower release in the gastric phase compared to the intestinal phase, with the Ritger–Peppas model effectively describing saffron extract release, highlighting a dominant swelling and dissolution release mechanism. Therefore, the NaCas/HMP coacervate wall materials made saffron stable in the gastric stage and sustainably release. It in the intestinal stage, promoting excellent absorption of saffron in simulated digestion. Graphical Abstract

Abstract Strengthening international collaboration is essential to achieving the United Nations’ SDGs. The Group of Seven (G7) is recognized for acting and enhancing cooperation to achieve the SDGs. However, the current understanding of G7’s cooperation is rather subjective without quantitative measurements. Here we show a comprehensive and quantitative analysis of G7’s cooperation with regards to the economic and environmental SDGs over the period of 2000-2020. The results suggest that G7 countries have all contributed positively to economic indicators thanks to their closely binding relationship. By contrast, significant discrepancies and uncooperative performances in environmental indicators have been revealed. Particularly, Canada and Germany have shown considerable negative synergy contributions to environmental indicators, which might offset the positive contributions brought by France and Italy and lead to an overall negative synergy. Our results highlight the need for further collaboration among G7 to tackle emerging environmental issues, such as climate change and shrinking biodiversity.

Abstract Background Studies have been conducted worldwide to investigate the level of adherence to personal protective measures or fear of COVID-19 among healthcare providers. However, few studies have examined the relationship between adherence to personal protective measures and fear of COVID-19. There is also a need for more information on this topic from Iran. This study investigated the relationship between adherence to personal protective measures against COVID-19 and fear of COVID-19 in the healthcare providers at Pastor Hospital of Bam, Iran, in 2022. Methods This cross-sectional study was conducted in August and September 2022 with 199 healthcare providers of Pastor Hospital of Bam, Iran. The study included medical, nursing, and paramedical staff at Pastor Hospital at the time of the study. Incomplete responses and failure to return the questionnaire to the researcher were exclusion criteria. The fear of COVID-19 scale and a checklist of personal protective measures were used to collect data. Descriptive statistics, t-tests, analysis of variance, and Pearson’s correlation coefficient were used to analyze the data. Results Of the 199 participants, 67.3% were female, and their mean age was 31 ± 4.55 years. The mean score for adherence to personal protective measures was 14.46 ± 3.39 (out of 23), and the mean score for fear of COVID-19 was 17.04 ± 4.58 (out of 35). Adherence to personal protective measures was higher among females than males (14.96 ± 2.99 vs. 13.43 ± 3.92, p = 0.003), in individuals who had attended infection control courses than in those who had not (15.57 ± 2.88 vs. 13.30 ± 3.50, p

This article discusses the challenges that African heritage youth1 face as they navigate their African-ness and Kiwi-ness in the Aotearoa/New Zealand context. Data were drawn from a qualitative study guided by participatory action research (PAR) methodology principles exploring the opportunities and challenges these youth face while navigating their multiple cultural identities. The study used research workshops and anonymous qualitative questionnaire surveys to engage with 35 youth from African communities. PAR’s transformative lens, narrative inquiry, and inductive thematic analysis were used to identify the challenges reported in this paper. Findings show that cultural identity confers a sense of personhood and belonging. African heritage youth born or migrated to Aotearoa/New Zealand at a young age have a strong desire to express and authentically live their African-ness, Kiwi-ness, and other cultural identities. However, this is challenged by the personal, community, and societal factors explained in this paper. The findings of this research contribute towards a greater understanding of the threats to well-being linked to cultural identity construction among African youth in Aotearoa. It also makes a methodological contribution, demonstrating a transformative approach to engaging marginalized or minority groups in a research process that validates their experiences and empowers them.

Damaged articular cartilage has limited self-healing potential and often leads to osteoarthritis (OA), pain, anddysfunction of the affected joint. Autologous and allogenic transplants cannot fully meet the needs of clinical treatment.Two dimensional (2D) and three-dimensional (3D) cell cultures can help to study growth modeling and physiologicalcharacteristics of the human body. Among the problems that 2D and single-layer cultures have the lack of proper andaccurate tissue modeling and the lack of tissue complications similar is to the original tissue. With organoid models,cellular and tissue structural studies and functional and physiological studies of tissues have been revolutionizedand more accurate. Organoids are useful for studying repair and drug efficacy. Physiological and pathologicalinvestigations by combining in vitro and in vivo methods have become more effective today. The purpose of this studyis to investigate the factors involved in the formation of cartilage organoids so that we can introduce the best methodof organoid production for the healing of cartilage damage by using cell types and organoid model.

This study investigates the factors influencing Corporate Social Responsibility (CSR) disclosure among companies listed in the PROPER KLH within the Indonesian Sharia Stock Index (ISSI) from 2017 to 2022. Utilizing a quantitative approach, the research employs secondary data and panel data regression analysis. The results reveal that environmental performance, company age, and tax aggressiveness significantly affect CSR disclosure, as measured by the Global Reporting Initiative (GRI) index. These findings underscore the crucial role of these factors in shaping a company's commitment to social and environmental responsibilities, while also highlighting the complex dynamics between corporate actions and their environmental impact. Companies with strong environmental performance not only contribute positively to the planet but also enhance their long-term reputation. The relationship between tax aggressiveness and CSR disclosure suggests a significant interplay between financial strategies and ethical considerations in corporate decision-making. This underscores the need for a comprehensive approach to corporate governance that integrates financial objectives with ethical responsibilities. Consequently, policymakers and stakeholders should leverage these insights to develop more effective regulations and incentives that promote responsible corporate conduct.

Hadis şerhçiliği, rivayetlerin isnad ve metin açısından analiz edilip yorumlandığı bir bilgi birikim sürecidir. Geniş bir dönemi kapsayan; tahkik, tenkit ve ikmal yöntemleriyle yürütülen bu faaliyetler müstakar şerh metinlerinin teşekkülünü sağlamıştır. Bir şerhin sonraki dönem eserlerinin yazımına etkisini belirlerken kullanılabilecek en önemli veri ise atıflardır. Bir eserin alıntılama yoluyla kendisinden söz ettirmesi, onun âlimler tarafından kabul görüldüğünün bir göstergesidir. Kâhire’de yaşamış ve dönemin önemli hadis hafızlarından biri olan Moğultay b. Kılıç’ın (öl. 762/1361) Sahîhu’l-Buhârî şerhi et-Telvîh, hadis şerh literatüründe önemli bir yere sahiptir. Bu çalışma, Hanefî şârihlerce yazılan ilk şerhlerden biri olma özelliğini taşıyan et-Telvîh’in hadis şerh literatüründeki etkisini, esere yapılan atıflar üzerinden incelemeyi amaçlamaktadır. Bu hedefle, öncelikle Moğultay’ın talebesi İbnü’l-Mülakkın’ın (öl. 804/1401), İbn Hacer’in (öl. 852/1449) ve Aynî’nin (öl. 855/1451) Buhârî şerhleri incelenmiştir. İbnü’l-Mülakkın’ın eseri ile müderris-talebe münasebetinin, İbn Hacer’in kitabıyla mezhep farklılığının ve Aynî’nin kaleme almış olduğu çalışması ile aynı mezhebe aidiyetin atıflara nasıl yansıdığı gözlemlenmiştir. Hint alt kıtası dönemi şerhlerinin incelenmesiyle de diğer hadis şerh ekollerine etkisinin boyutu ortaya konmaya çalışılmıştır. İbnü’l-Mülakkın’ın hocasından alıntılarının az olduğu ve onun eserinin adına doğrudan atıf yapmadığı, diğer iki şârihin ise farklı ifadelerle ona çokça iktibaslarda bulundukları görülmüştür. Diğer ekollerde ise Moğultay’ın referanslarına çok az rastlanmıştır. et-Telvîh’e atıfta bulunan şârihler muallak rivayetlerden isnat meselelerine, ravî kimlik bilgisinden tahrîc bilgisine, hadis metninin tespitinden siyer ve bâb başlığına kadar çok farklı konularda göndermelerde bulunmuşlardır. Bu durum Moğultay’ın hadis ilminin neredeyse tüm alanlarıyla ilgili farklı âlimlerden atıf aldığını göstermektedir.

Capillary pressure is a significant parameter in characterizing and modeling petroleum reservoirs. However, costly laboratory measurements may not be sufficiently available in some cases. The problem amplifies for carbonate reservoirs because relatively enormous capillary pressure curves are required for reservoir study due to heterogeneity. In this work, the laboratory measurements of capillary pressure and formation resistivity index were correlated as both parameters are functions of saturation. Forty-one core samples from an Iraqi carbonate reservoir were used to develop the correlation according to the hydraulic flow units concept. Flow zone indicator (FZI) and Pore Geometry and Structure (PGS) approaches were used to identify the reservoir hydraulic flow units. The experimentally derived correlations can be used to predict capillary pressure from resistivity, which is widely available from well-logs. FZI and PGS rock typing methods were applied to characterize the reservoir rock types. For both methods, the log-log plot of Leverett J-function and capillary pressure versus resistivity index for each rock type represent a power-law model relationship between these parameters. Despite the good permeability-porosity prediction results, the FZI approach did not yield a good correlation between J and I. PGS resulted in a better performance in terms of both permeability-porosity prediction and Pc with I correlation because PGS honors the pore geometry and structure relationship with the mean hydraulic radius more than FZI. This work introduces a new correlating approach that aims to assist in reservoir characterization and simulation.

The mathematics performance of Australian high-school students in Year 9 and their participation in mathematics subjects in Year 12 has plummeted in the last 20 years. In this paper, a retrospective cohort study was conducted to understand how non-cognitive variables controlled or explained the correlation between mathematics performance in Year 9 and mathematics participation in Year 12. The sample consisted of a cohort of Australian students (N = 6653; n = 3115, 46.8% male) who participated in the Longitudinal Survey of Australian Youth (LSAY) in 2007 to 2017. Partial least squares structural equation modelling (PLS-SEM) was conducted to explore the degree to which one moderating variable and five mediating variables intervened in the relationship between mathematics performance in Year 9 and mathematics participation in Year 12. Mathematics performance in Year 9 predicted mathematics participation in Year 12 (R2 = 18.4%). The positive correlation was moderated by gender and mediated by five non-cognitive factors associated with self-related beliefs: mathematics self-concept, self-efficacy, interest, motivation, and anxiety (R2 = 28.9%). At any given level of mathematics performance in Year 9, a male student with a higher level of mathematics self-concept, self-efficacy, interest, and motivation, and a lower level of anxiety, was more likely to participate in mathematics subjects in Year 12 than a female student with a lower level of mathematics self-concept, self-efficacy, interest, and motivation, and a higher level of anxiety. These finding have implications for ameliorating the declining levels of mathematics performance and participation.

Paper production is a process that consumes a lot of water, in this process the use of water should be carefully considered. Most of the industrialized countries have developed standards for the discharge of sewage or wastewater, the purpose of which is to ensure that the society does not have to bear the costs caused by the industrial use of water. Wastewater, after processing, should be returned in a suitable form for almost any type of purpose. The stricter standards have caused the complete closure of paper mill water systems (that is, bringing the amount of effluent to zero) to be emphasized more. In the discussion of recycling, the fibers should be separated from the wastewater due to their economic value and returned to the system. Therefore, in this research, in one of the OCC recycling factories, the amount of water consumption and effluent output and the amount of fibers in the effluent output of this factory before pre-treatment and after pre-treatment were investigated and it was observed that if the water intake is not controlled and If pre-treatment is not used, a significant amount of fibers will be thrown away along with the waste water, which is 8441 kg per 390.651 tons of production in one month based on TSS The basis of purchase price of OCC was done in the same period.

Abstract MgFe2O4@ZnAl2O4 magnetic nanocomposites were synthesized with the easy and green sol–gel method, and their photocatalytic efficiency was followed toward degradation of reactive blue 222 (RB222) dye under visible light irradiation. Prepared nanocomposites were fully characterized. The SEM and TEM images revealed the spherical morphology of the produced nanocomposites, with average size of 20–25 nm. The XRD pattern of sample exhibited the successful synthesis of the MgFe2O4@ZnAl2O4 MNCs with crystallite size 13 nm. The saturation magnetization (Ms) of the nanocomposites was examined using VSM, indicating a value of 6.59 emu/g. The absence of Hc and Mr values confirms the superparamagnetic nature of the nanoparticles. In addition, the surface area was calculated to be 78.109 m2/g utilizing BET analysis, and the band gap was determined to be 1.88 eV by DRS analysis. The photocatalytic, photolysis, and adsorption performance were investigated and result shown photodegradation activity was higher than others. These results confirm the synergetic effect between the MgFe2O4@ZnAl2O4 MNCs and visible light irradiation to degradation of organic dye. The results indicate that rapid degradation of 96% of RB222 dye occurred in just 10 min, with a TOC removal rate of approximately 59%. Furthermore, radical scavenger agents also clarified photodegradation of RB222 dye.

Abstract Venus, lacking an intrinsic global dipole magnetic field, serves as a textbook example of an induced magnetosphere, formed by interplanetary magnetic fields (IMF) enveloping the planet. Yet, various aspects of its magnetospheric dynamics and planetary ion outflows are complex and not well understood. Here we analyze plasma and magnetic field data acquired during the fourth Venus flyby of the Parker Solar Probe (PSP) mission and show evidence for closed topology in the nightside and downstream portion of the Venus magnetosphere (i.e., the magnetotail). The formation of the closed topology involves magnetic reconnection—a process rarely observed at non-magnetized planets. In addition, our study provides an evidence linking the cold Venusian ion flow in the magnetotail directly to magnetic connectivity to the ionosphere, akin to observations at Mars. These findings not only help the understanding of the complex ion flow patterns at Venus but also suggest that magnetic topology is one piece of key information for resolving ion escape mechanisms and thus the atmospheric evolution across various planetary environments and exoplanets.

Various soft markers can be detected in the ultrasonography of foetuses, which can be related to chromosomal abnormalities and increases the risk of abnormalities, or they can be considered as normal variations that can disappear due to the pregnancy progress. There are different tools to detect chromosomal abnormalities like conventional karyotyping, chromosomal microarray analysis (CMA), single nucleotide polymorphism (SNP) array, non-invasive prenatal test (NIPT), and non-invasive prenatal screening (NIPS). Therefore, in the present study, we aim to assess the accuracy of ultrasonic soft markers in the diagnosis of chromosomal abnormalities such as chromosomal structural abnormalities, aneuploidy, and triploidy, especially Trisomy 21 and Trisomy 18. A systemic literature search was performed using PubMed, Scopus, Google Scholar, and Web of Science. We gathered all articles published before August 2023. We selected English studies such as retrospective and cross-sectional ones that assessed the relationship between ultrasonic soft markers and foetal chromosomal abnormalities. A total of 10 articles with 18,580 cases were included in our systematic review article that assessed the foetal abnormalities and aneuploidies by using conventional karyotyping, SNP array, CMA, and NIPT (or NIPS). Trisomy 21, Trisomy 18, and chromosomal structural abnormalities were the most common abnormalities related to ultrasonic soft markers by karyotyping; however, Trisomy 13, 47, XXY, 45, X, and mosaic chromosomal abnormalities were other abnormalities detected. Results by CMA showed Trisomy 21 and Trisomy 18 as the most common abnormalities in the foetuses also with ultrasonic soft markers, and other abnormalities were pathogenic copy-number variations, Turner (XO), polyploidy, 22q11.2deletion, and Trisomy13, respectively. It was discovered that there is a greater possibility of having pathogenic copy number variations (CNVs) in the groups with multiple ultrasonic soft markers, while foetuses with ultrasonic soft markers have a decreased prevalence of CMA abnormality compared to those who had significant abnormalities or abnormal nuchal translucency. Trisomy 21 was the only abnormality found by NIPT in the groups with 1 and 2 soft markers, while groups with multiple soft markers were all normal. By using SNP array, it was identified that the rate of chromosomal abnormalities such as aneuploidy and triploidy, LOH, and CNVs was lower in the group with a single ultrasonic soft marker compared to the group with structural abnormalities in multiple systems. Trisomy 21, Trisomy 18, and chromosomal structural abnormalities were the most common chromosomal abnormalities that ultrasound soft markers could diagnose. Therefore, it is recommended to employ soft markers besides CMA, SNP array, and NIPS (or NIPT) for greater accuracy in detecting foetus abnormalities.

Adaptive Cruise Control (ACC) is a technology that can reduce traffic. However, its availability in Iran is relatively limited compared to more developed countries. This research examines the acceptance and willingness to pay for ACC among Iranian drivers. Data from an online survey of 453 respondents were analyzed using an ordered logit model and a structural equation model. The results of modelings show that perceived ease of use and perceived usefulness affect attitudes towards using ACC, which in turn influence behavioural intentions. In addition, drivers who find ACC easy to use and user-friendly, own expensive vehicles, and female drivers who have experience with cruise control are more likely to pay for ACC. To enhance the adoption of ACC in Iran, it is recommended to target early adopters, especially women and capitalists, who can influence others with their positive feedback. The benefits of ACC for traffic safety and environmental sustainability should also be emphasized. Furthermore, future studies would better concentrate on public perceptions and assessing the necessary infrastructure for ACC in Iran.

Cerebrovascular events are linked to ankylosing spondylitis. Accelerated atherosclerosis and endothelial dysfunction against a backdrop of inflammation have been widely blamed for the increased cerebrovascular risk in ankylosing spondylitis. The absence of a comprehensive review encouraged us to consider the link between ankylosing spondylitis and cerebrovascular diseases. Web of Science, PubMed, Medline, Scopus, and EMBASE were searched to identify studies published from 2000 to June 10, 2023. All observational and cohort studies reporting myocardial infarction or stroke and considering classic cerebrovascular risk in ankylosing spondylitis patients and healthy controls were included. Most of the included studies reported that the risk of cerebrovascular disorders was greater in ankylosing spondylitis than in the general population. Also, most studies showed that for both sexes, the prevalence of cardiovascular illnesses rose with age, and this trend was consistent across all subgroups of cardiovascular disorders. Also, most studies reported that the rate of cerebrovascular accidents in ankylosing spondylitis patients was higher than in control groups. Some studies reported that the risk of developing an ischemic stroke was higher in young patients with ankylosing spondylitis, while others did not. Our systematic analysis found that most studies agreed that ankylosing spondylitis patients had a higher risk of cerebrovascular diseases than the general population. Still, this increased risk was influenced by several factors that need further research exploration.

Amidst Iran's confrontation with Western modernity and the subsequent discursive conflicts, women's lives, identities, and living conditions came to the forefront as prominent topics of discourse. This resulted in an extensive array of discussions concerning them, thereby transforming women into a subject of tension. This article analyzes the discourses that emerged concerning women in the writings of the Constitutional era. It employs critical discourse analysis to investigate how the modern woman subject was formulated in the most prominent discourses of this era. The objective of this study is to comprehend the ideologies that govern each discourse of the Constitutional era as they pertain to the modern woman subject. Additionally, the position and status of each discourse within the hegemonic discourse are examined. The results suggest that the progressive discourse presents the modern woman as a demanding and critical subject, having been formed in opposition to tradition. Conversely, the traditional discourse depicts her as a liberated and European-like figure. In the midst of these semantic disputes, the integrative discourse constructs the subject of a woman who is acknowledged as a conscientious, Sharia-compliant, and duty-oriented individual. The integrative discourse's construction of meaning, which avoided explicit conflict with religious traditions, attained a more advantageous position and has maintained its existence throughout subsequent eras.

So far, many researches have been conducted in various fields of the water shortage crisis, mostly in environmental and economic fields, and in a few of them, attention has been paid to the influence of cultural elements as a moderating factor of the effects of this crisis. The present research has been formed to provide a paradigmatic pattern of cultural resilience in the water shortage crisis of Zayandehrud, which was carried out using a qualitative method and grounded theory approach. Using theoretical sampling and the snowball method, the number of 24 people who were interested and concerned in the field of water shortage issues and had sufficient information, experience, or knowledge in this field were selected and during the in-depth interview Semi-structured, they expressed their answers. Data analysis was done with the Colaizzi method in the framework of grounded theory. The Lincoln and Goba evaluation method was used to validate the research, and the validity of the data was confirmed by going back to the interviewees and two coders. The findings were 22 categories, "accepting the phenomenon of water shortage as a reality" as the pivotal phenomenon, 3 categories of causal condition (sufficient information, water literacy, communication) 4 categories of contextual condition (hope, religious beliefs, attachment to the residence, economic dependence) 5 categories of intervening condition (trust, pragmatism, attitude, social responsibility, collective cooperation) 5 interaction strategy (change in habits of oneself and others, participation, prevention, saving) and 4 categories of consequences (productivity, entrepreneurship, creativity and awareness) were categorized.

Resilience is one of the most crucial parameters in the electricity supply chain, and the absence of this concept can lead to various issues in service provision. One perspective that can greatly contribute to resilience is utilizing the Industry 4.0 approach. This study examines the challenges and strategies for the flexibility of the electricity supply chain in the Industry 4.0 era. A descriptive-analytical method employing library research and field studies has been employed. Subsequently, using the factors and criteria obtained from Value-Focused Thinking (VFT) from Soft Operational Research and verification by literature, a fuzzy IVIF-WASPAS-based analysis was conducted. The decision-making team comprised internal experts in the electricity supply chain in Iran, focusing on the principles of resilience in the Industry 4.0 era to analyze key issues. A case study was also conducted within the electricity supply chain, incorporating insights from academic experts and the team's experiences. Strategies like smart network systems, blockchain technology, cybersecurity, and education are fundamental to enhancing the supply chain's flexibility. This study's findings indicate a long journey in developing Industry 4.0 in Iran's electricity supply chain. However, relying on the proposed strategies can minimize existing issues and propel the system toward growth.

This article develops and investigates the behavior of soliton solutions for the spatiotemporal conformable Klein–Gordon equation (CKGE), a well-known mathematical physics model that accounts for spinless pion and de-Broglie waves. To accomplish this task, we deploy an effective analytical method, namely, the modified extended direct algebraic method (mEDAM). This method first develops a nonlinear ordinary differential equation (NODE) through the use of a wave transformation. With the help of generalized Riccati NODE and balancing nonlinearity with the highest derivative term, it then assumes a finite series-form solution for the resulting NODE, from which four clusters of soliton solutions – generalized rational, trigonometric, exponential, and hyperbolic functions – are derived. Using contour and three-dimensional visuals, the behaviors of the soliton solutions – which are prominently described as dark kink, bright kink, breather, and other NN-soliton waves – are examined and analyzed. These results have applications in solid-state physics, nonlinear optics, quantum field theory, and a more thorough knowledge of the dynamics of the CKGE.

Abstract Excessive Cu2+ intake can cause neurological disorders (e.g. Wilson’s disease) and adversely affect the gastrointestinal, liver, and kidney organs. The presence of Cu2+ is strongly linked to the emergence and progression of Wilson's disease (WD), and accurately measuring the amount of copper is a crucial step in diagnosing WD at an early stage in a clinical setting. In this work, CQDs were fabricated through a facile technique as a novel fluorescence-based sensing platform for detecting Cu(II) in aqueous solutions, and in the serum samples of healthy and affected individuals by WD. The CQDs interact with Cu(II) ions to produce Turn-on and Turn-off states at nano-molar and micro-molar levels, respectively, with LODs of 0.001 µM and 1 µM. In fact, the Cu2+ ions can act like a bridge between two CQDs by which the charge and electron transfer between the CQDs may increase, possibly can have significant effects on the spectroscopic features of the CQDs. To the best of our knowledge, this is the first reported research that can detect Cu(II) at low levels using two different complexation states, with promising results in testing serum. The potential of the sensor to detect Cu(II) was tested on serum samples from healthy and affected individuals by WD, and compared to results obtained by ICP-OES. Astonishingly, the results showed an excellent correlation between the measured Cu(II) levels using the proposed technique and ICP-OES, indicating the high potential of the fluorimetric CQD-based probe for Cu(II) detection. The accuracy, sensitivity, selectivity, high precision, accuracy, and applicability of the probe toward Cu(II) ions make it a potential diagnostic tool for Wilson's disease in a clinical setting.

Abstract Evapotranspiration plays a pivotal role in the hydrological cycle. It is essential to develop an accurate computational model for predicting reference evapotranspiration (RET) for agricultural and hydrological applications, especially for the management of irrigation systems, allocation of water resources, assessments of utilization and demand and water use allocations in rural and urban areas. The limitation of climatic data to estimate RET restricted the use of standard Penman–Monteith method recommended by food and agriculture organization (FAO-PM56). Therefore, the current study used climatic data such as minimum, maximum and mean air temperature (T max, Tmin, T mean), mean relative humidity (RHmean), wind speed (U) and sunshine hours (N) to predict RET using gene expression programming (GEP) technique. In this study, a total of 17 different input meteorological combinations were used to develop RET models. The obtained results of each GEP model are compared with FAO-PM56 to evaluate its performance in both training and testing periods. The GEP-13 model (T max, T min, RHmean, U) showed the lowest errors (RMSE, MAE) and highest efficiencies (R 2, NSE) in semi-arid (Faisalabad and Peshawar) and humid (Skardu) conditions while GEP-11 and GEP-12 perform best in arid (Multan, Jacobabad) conditions during training period. However, GEP-11 in Multan and Jacobabad, GEP-7 in Faisalabad, GEP-1 in Peshawar, GEP-13 in Islamabad and Skardu outperformed in testing period. In testing phase, the GEP models R 2 values reach 0.99, RMSE values ranged from 0.27 to 2.65, MAE values from 0.21 to 1.85 and NSE values from 0.18 to 0.99. The study findings indicate that GEP is effective in predicting RET when there are minimal climatic data. Additionally, the mean relative humidity was identified as the most relevant factor across all climatic conditions. The findings of this study may be used to the planning and management of water resources in practical situations, as they demonstrate the impact of input variables on the RET associated with different climatic conditions.

Background: COVID-19 epidemiology changed with the emergence of SARS-CoV-2 variants of concern (VOC). Pakistan administered mostly inactivated vaccines. We investigated the association between VOC and breakthrough infections in a mixed-vaccination-status population of Karachi. Methods: We investigated SARS-CoV-2 VOC tested in 392 respiratory specimens collected between May and December 2021. Data for age, sex, hospital admission, vaccinations, together with CT values of the diagnostic PCR test were analyzed. Results: The median age of COVID-19 cases tested was 40 (27−57) years and 43.4% were female. Delta variants were most common (56.4%) followed by Alpha (15.9%), Omicron (12.2%), Beta/Gamma (11.3%), and others (4.3%). Eighteen percent of cases were hospitalized whereby, predominant VOC were Beta/Gamma (40.8%), Alpha (35.2%) and Delta (22.5%). Overall, 55.4% of individuals were fully vaccinated, 7.4% were partially vaccinated and 37.2% were unvaccinated. Most (74.6%) inpatients were unvaccinated. Vaccines comprised inactivated (85.34%), single-shot vector (8.62%), two-shot vector (3.02%) and mRNA (3.02%) types. Omicron variants showed lower viral loads as compared to Alpha, Beta/Gamma, and Delta (p = 0.017). The risk of infection with Delta and Omicron variants was higher, 8 weeks after vaccination. The majority of those with breakthrough infections after receiving inactivated vaccines acquired COVID-19 within 4 months of vaccination. Conclusion: Our data highlights the shifting of VOC from Delta to Omicron during 2021 and that COVID-19 vaccinations reduced both hospitalizations and viral transmission. It informs on the increased risk of breakthrough infection within 8 weeks of vaccination, indicating the need for booster vaccinations.

Wetland ecosystems provide numerous services to humanity and the biosphere at large. However, these services are constantly dwindling due to the massive wetland loss caused by urbanization. Urbanization-induced wetland loss is a global problem, with most developing countries experiencing it currently. Several studies on wetland loss have been conducted. However, there is a dearth of studies integrating GIS and other ecological models to estimate the periodic deterioration of wetlands in rural settings in underdeveloped nations. As a result, this study aims to determine wetland loss in a developing country’s countryside, using the Greater Amanzule Wetland in the Ellembelle District of Ghana as a case study. The study used the GIS and Remote Sensing dataset, the Normalization Difference Vegetation Index, and the InVEST-Habitat Quality model to analyze the spatial pattern of wetland loss and habitat quality variations caused by industrialization and community expansions between 2000 and 2020. Our results indicate that, from 2000 to 2015, community built-up and industrial land areas grew from 25.19 ha to 84.21 ha and 0–4.71 ha respectively, causing a wetland loss of −39.64 ha (−31.10%). Between 2015 and 2020, community built-up land grew to 78.65 ha while industrial land slightly reduced to 2.54 ha, leading to the wetland degradation of approximately −69.06 ha (−42.53%). Wetland habitat quality steadily declined, from 0.97 in 2000 to 0.93 in 2015 and 0.93 in 2020. The study findings led to policy recommendations to reduce wetland encroachment and enhance sustainability. These recommendations included conducting effective land-use plan inspections before issuing permits, coordinating effective management, and promoting the recovery of natural and artificial vegetation to sustain the wetland.