Search Results (619)

This study examines the long- and short-run determinants of green employment in Saudi Arabia over the period 1990–2024 using an Autoregressive Distributed Lag (ARDL) bounds testing framework within an error-correction model. Six macroeconomic and structural variables are analyzed: renewable energy capacity, GDP growth, domestic credit, urbanization, foreign direct investment, and the Vision 2030 policy regime shift. Supplementary analyses test the Environmental Kuznets Curve (EKC) hypothesis and map causal relationships using pairwise Granger causality tests. The bounds test indicates long-run cointegration among the variables (F = 8.45, exceeding the 5% I(1) critical bound of 3.61). The model explains 89% of the variation in log green employment (R² = 0.89) and passes standard diagnostic tests for serial correlation, heteroskedasticity, normality, and parameter stability. Three correlates of long-run green employment are identified. The post-2016 dummy used to capture the Vision 2030 regime shift is associated with the largest coefficient in the long-run equation (θ = 1.75, p = 0.008), although this estimate should be interpreted with caution because the dummy absorbs all post-2016 changes, including policy effects, the rapid expansion of renewable capacity, broader institutional reforms, and possibly changes in measurement practices. Renewable energy capacity is the primary continuously measurable driver (θ = 0.145, p = 0.018), with Toda–Yamamoto modified Wald tests indicating a bidirectional predictive relationship between investment and employment. Urbanization exerts a significant positive long-run effect (θ = 0.098, p = 0.001). The error correction term (δ = −0.520, p < 0.001) implies equilibrium reversion with a half-life of approximately one year. The EKC hypothesis is not supported in the Saudi context, suggesting that active decarbonization policy—rather than income-driven structural change alone—is needed for environmental improvement. The findings carry implications for Vision 2030 implementation and for other resource-dependent economies undertaking structural green transitions. Full article

Schistosomiasis (bilharzia) is a parasitic infection caused by trematodes of the Schistosoma genus and remains a significant health burden in endemic regions. Granulomatous host responses to deposited Schistosoma eggs in small veins and tissues result in progressive changes and characteristic imaging findings. This diagnostic radiological review synthesizes the published literature and highlights key and robust imaging findings that facilitate the diagnosis of Schistosoma mansoni and Schistosoma haematobium, with emphasis on modality-specific patterns and disease staging. Schistosoma mansoni primarily affects the liver, causing periportal fibrosis visible as “pipe-stem” echogenic thickening upon ultrasonography, which may progress to portal hypertension and chronic liver disease. Liver cirrhosis is the end-stage disease manifested as an irregular liver contour with surface nodularity and lobar redistribution as right lobe atrophy with left and/or caudate lobe hypertrophy. Schistosoma haematobium predominantly affects the genitourinary system, causing urinary bladder wall thickening and calcification. Early disease, within three months of infection, may present with fine calcification, firstly in the bladder base and then extending to the whole bladder and even to the ureters. Calcification appears as a line or two parallel lines on radiography and as a circle in axial computed tomography (CT) images, which is pathognomonic for early-stage Schistosomiasis. In contrast studies, including conventional urography and CT urography, Schistosoma eggs appear as bubble-like filling defects in the ureter, kidney, and bladder, manifested as ureteritis, pyelitis, and cystitis cystica. Late stages appear as coarse calcification, fibrosis, strictures, and reduced bladder capacity and are associated with an increased risk of bladder squamous cell carcinoma. Moreover, Schistosomiasis calcification can present in genital organs, especially in the seminal vesicles; in the prostate in males; and in the vulva, cervix, and perineum in females. Ultimately, Schistosoma mansoni and haematobium eggs can reach the spinal cord, leading to acute myelopathy with paraparesis, urinary retention, or paraplegia. Recognition of characteristic imaging patterns of Schistosomiasis is essential for early diagnosis, accurate staging, and prevention of long-term complications. Full article

Spi-1 Proto-Oncogene (SPI1) encodes Purine-rich box 1 Transcription Factor (PU.1), a transcription factor of the ETS family that regulates hematopoietic lineage commitment and immune cell differentiation. Alteration of PU.1 dose or ETS domain integrity may interfere with transcriptional programs, which adds to hematopoietic dysregulation and leukemogenesis. Even though changes in SPI1 expression have been associated with acute myeloid leukemia (AML), the structural and regulatory effects of missense mutations at the PU.1 ETS domain have not been entirely studied, and targeting the PU.1 ETS domain by ligands is an area of computational analysis that should be further pursued. To computationally describe deleterious missense variants of SPI1 in terms of structural stability, evolutionary conservation, post-translational modification (PTM) context and interaction networks, and to measure ADMET-mediated molecular docking of cinnamic acid with the PU.1 ETS domain (8EQG) as a potential modulator. Missense nsSNPs were obtained through Ensembl and narrowed down by consensus prediction of pathogenicity (PredictSNP, combining SIFT, PolyPhen, SNAP and PhD-SNP and other tools). InterPro/UniProt was used for domain mapping. SWISS-MODEL was used to produce wild-type and mutant PU.1 versions, which were analyzed on the structural alignment and Cα–Cα displacement parameters in UCSF Chimera (v1.19). The estimation of stability change was carried out with I-Mutant and MUpro. Prediction of PTM sites was done using MusiteDeep and exploration of functional partners was done using STRING. Human, mouse and zebrafish orthologue conservation was measured by means of MAFFT alignment. GEPIA2 was used to compare the expression of SPI1 in AML (TCGA-LAML) and normal tissues (GTEx). AutoDock Vina (grid center 6, −2, −9 A; 20 × 20 × 20 A; 16 exhaustiveness) was used to prepare cinnamic acid and dock it into the PU.1 ETS domain (8EQG), with SwissDock being used for consistency checks. SwissADME and ADMETlab 2.0 were used to predict drug-likeness, pharmacokinetics, and toxicity. Nine missense mutations were routinely considered as deleterious with the majority of them being located in or near the ETS DNA-binding domain. Structural comparisons showed local perturbations of the structure and I189F and H211P yielded the greatest conformational changes between prioritized variants whereas other forms had minimal movements. A predominantly destabilizing trend was supported by stability prediction whereby V241G had the strongest destabilization signal with further destabilizations being predicted in I189F and R259C. PTM mapping revealed several potential regulatory residues (phosphorylation, acetylation, ubiquitination, and methylation), which indicated that there could be crosstalk between the sequence variation and the transcriptional regulation. The SPI1 was placed in a central hematopoietic transcriptional module (containing RUNX1, CEBP members, GATA1 and IRF factors) by the STRING network. The cross-species alignment showed that there was high conservation of a number of the mutation sites, which would support functional constraint at the ETS region. The expression analysis revealed that the level of SPI1 mRNA in AML was significantly elevated compared to normal tissues. Docking also indicated a slight and reproducible interaction of cinnamic acid with the ETS domain (top affinity −4.27 kcal/mol), with a solitary leading polar anchor and supportive hydrophobic interactions, which is akin to interaction between fragments. The ADMET profiling revealed the likelihood of success in the oral drug-likeness and low CYP inhibition liability, as well as signifying the presence of a possible hepatotoxicity signal that needs further confirmation through experiments. Comprehensive computational studies suggest that certain pathogenic variants of SPI1 missense defects, especially in the ETS domain, can result in loss of PU.1 structural stability and regulatory environment, which are in line with the disturbed hematopoietic regulation and AML-related dysregulation. Cinnamic acid demonstrates moderate yet reproducible binding to the PU.1 ETS domain and has an overall favorable developability profile, which indicates that it is better considered as a starting scaffold, as opposed to an active inhibitor. The results give a logical basis of focused biochemical validation and structure-directed optimization of ETS domain modulators in hematologic disease settings. Full article

Background: Speech-language pathology (SLP) and audiology services are essential components of multidisciplinary rehabilitation, particularly for individuals with developmental, neurological, and communication-related disorders. National-level data describing the distribution and utilization of these services in Saudi Arabia remain limited. This study aimed to examine national patterns of rehabilitation service utilization, with a focus on SLP and audiology services in comparison to other rehabilitation specialties. Methods: A retrospective cross-sectional analysis was conducted using publicly available national open data released by the Saudi Ministry of Health (MOH). Aggregated rehabilitation service encounters (n = 1,872,328 to 1,930,695) from 2023–2024 were analyzed by specialty, geographic region, sector (MOH clusters versus private sector), and pediatric age groups. Descriptive statistics were used to characterize utilization patterns and regional variation. Results: Rehabilitation services were widely delivered across both public and private sectors, with physiotherapy representing the largest share of encounters. SLP and audiology services contributed a smaller proportion of total rehabilitation encounters compared to other specialties. Service distribution varied regionally, with higher volumes concentrated in major urban areas including Riyadh, Makkah, and the Eastern Region. Pediatric service encounters were highest in early childhood (ages 3–7), with SLP and audiology services forming a consistent component of rehabilitation during this period. Conclusions: This study provides a descriptive overview of rehabilitation service utilization in Saudi Arabia, highlighting the distribution of SLP and audiology services relative to other specialties and across regions. Findings emphasize the importance of addressing regional variation, supporting workforce development, and enhancing national rehabilitation data systems to inform planning and ensure comprehensive access to communication and hearing services. Full article

Quadratic-phase (deformed) transforms are a recent extension within the class of linear canonical transformations and have attracted increasing interest in signal analysis and related fields. Motivated by the fundamental role of uncertainty principles in theoretical analysis and practical applications, this article presents a thorough study of the uncertainty inequalities associated with the quadratic-phase deformed Hankel transform (QPDHT), which has recently been introduced into the literature. We first establish qualitative results. We then derive several forms of the Heisenberg’s uncertainty inequality using different analytical approaches, highlighting the interplay between spatial and frequency localization. Finally, we complete our study by proving local uncertainty inequalities, which provide refined quantitative bounds on the concentration of the transform. These results contribute to a deeper understanding of the localization properties of the QPDHT and extend classical uncertainty principles to a broader analytical framework. Full article

Afghanistan is located within one of the world’s most seismically active regions, where recurrent earthquakes pose a persistent threat to human life and the built environment. The 7 October 2023 Herat earthquake exposed critical vulnerabilities in both the construction sector and institutional frameworks, manifested through the widespread presence of non-engineered buildings, poor construction quality, and the absence of mandatory and enforceable seismic design regulations. This study examines the structural, construction-related, and governance deficiencies that significantly contributed to extensive building damage and high casualty rates, while also assessing shortcomings in public preparedness and disaster risk governance. A comparative case-study approach is adopted to evaluate seismic resilience and disaster management practices in India, Pakistan and Iran. The findings indicate that the elevated vulnerability observed in Herat primarily resulted from deficient construction practices, the lack of codified seismic standards, weak regulatory enforcement, and limited technical capacity within the construction industry. In contrast, regions characterized by well-established seismic codes, engineered structural systems, and coordinated institutional mechanisms experienced substantially reduced levels of structural damage and human losses, although earthquake impacts are also influenced by factors such as hazard characteristics, site conditions, exposure levels, and population distribution. The study highlights that seismic safety and sustainable development are inherently interdependent objectives. Improving earthquake resilience in Afghanistan requires the integration of earthquake-resistant engineering with sustainable construction practices, enhancement of technical and professional capacity, rigorous enforcement of region-specific seismic regulations, and strengthened community-based awareness programs. The adoption of internationally recognized best practices and risk-informed planning strategies is essential for fostering safer, more resilient, and environmentally sustainable urban development capable of withstanding future seismic events. Full article

Background/Objectives: Artificial intelligence (AI) is increasingly used in healthcare to support clinical decision-making, patient monitoring, and administrative tasks. Nurses are expected to work with these technologies. However, the evidence suggests that their knowledge and preparedness remain limited. As future healthcare providers, nursing students must be prepared to integrate AI into their practice. This study aimed to assess nursing students’ knowledge, attitudes, perceived benefits and risks, barriers, professional impact, and preparedness toward AI in healthcare. Methods: This cross-sectional descriptive study was conducted between April and July 2024 at the College of Nursing, University of Hail, Saudi Arabia. A convenience sample of 320 undergraduate nursing students completed an online structured questionnaire that assessed their demographics, knowledge, attitudes, perceived barriers, benefits, risks, professional impact, and preparedness. Data were analyzed using IBM SPSS version 27 with descriptive statistics. Inferential analyses, including independent t-tests and one-way ANOVA, were performed to examine differences between groups. Pearson’s correlation was used to identify correlations between the study variables. Statistical significance was set at p < 0.05. Results: Most students (79.7%) had poor AI knowledge, whereas 52.5% reported positive attitudes. Older students (≥24 years) and internship students showed significantly more positive attitudes (p < 0.001). Knowledge was weakly correlated with attitudes (r = 0.147), benefits (r = 0.222), and risks (r = 0.152). Attitudes were weakly positively correlated with benefits (r = 0.243) and negatively correlated with barriers (r = −0.219). Conclusions: Despite their positive attitudes, nursing students showed limited knowledge and preparedness. Integrating AI education and practical training into nursing curricula is therefore essential. These findings should be interpreted cautiously given the cross-sectional design, single-institution sampling, and reliance on self-reported measures, which may limit generalizability. Full article

A new species of Scorpio Linnaeus, 1758 is described from Al Ula Governorate, Al Madinah Province, Saudi Arabia. Scorpio furvus sp. nov. is distinguished from closely related congeners, including S. fuscus, S. kruglovi, S. palmatus, S. jordanensis, and S. yemenensis, by a unique combination of morphological characters notably the granulation pattern of the pedipalp chela, metasomal proportions, pectinal structure and length, and overall dark coloration. Morphometric comparisons further support its distinct status. The discovery of this species highlights the underestimated diversity of the genus Scorpio in the Arabian Peninsula and reinforces the view that the Scorpio maurus complex comprises multiple geographically restricted taxa requiring continued integrative taxonomic investigation. Full article

Background: The characterization of thyroid lesions is essential in clinical practice. Recent advances in imaging modalities, including nuclear imaging (NM), color Doppler ultrasonography, and sonography, have markedly improved the diagnostic accuracy for thyroid nodules. Objective: To assess thyroid diseases using Doppler ultrasound, nuclear scintigraphy, and sonography. Results: In this cross-sectional single-center study, 144 patients were examined to determine their thyroid structure and function using a multimodal imaging approach. Fine-needle aspiration cytology (FNAC) indicated that most thyroid nodules were benign (62.5%), with 37.5% being malignant. Doppler vascularity demonstrated a sensitivity of 70.4% and a specificity of 40% (AUC = 0.514) for malignancy detection, while scintigraphy uptake in hypofunctioning nodules (nodules with decreased radionuclide uptake) showed a sensitivity of 37% and a specificity of 54.4% (AUC = 0.388). Thyroxine hormone levels showed a sensitivity of 57.4% and a specificity of 45.6% (AUC = 0.503) for detecting malignant thyroid nodules. In multivariate logistic regression, increased Doppler vascularity remained an independent predictor of malignancy (OR = 2.39; 95% CI: 1.15–4.96; p = 0.019), whereas decreased scintigraphic uptake showed a borderline effect (OR = 1.82; p = 0.069); high T4 level and increased uptake were not significant predictors. The combined Doppler ultrasound, scintigraphy, and thyroxine level model yielded an AUC of 0.72 (95% CI: 0.63–0.81), markedly higher than any single parameter. At the optimal Youden threshold (0.43), the model achieved 79.6% sensitivity, 68.2% specificity, and 72.4% accuracy, highlighting the superior diagnostic performance of the integrated approach for pre-FNAC stratification of thyroid malignancies. There was a strong, significant linear association between thyroxine levels and thyroid scintigraphy uptake (p-value < 0.001). Most patients with normal thyroxine levels exhibited decreased uptake (66.1%), whereas a minority (6.5%) demonstrated elevated uptake levels. This study found a strong correlation between mixed-echogenicity nodules and thyroid scintigraphy uptake (p-value = 0.019). Mixed-echogenicity nodules were most often associated with reduced uptake (57.8%), and hypoechoic nodules often had normal uptake (57.1%). Conclusions: The complementary integration of color Doppler vascularity, Tc-99m thyroid scintigraphy, and serum thyroxine levels yields superior Doppler–scintigraphy uptake correlation, increases the overall diagnostic accuracy, and offers a practical, non-invasive algorithm for differentiating benign from malignant thyroid nodules prior to FNAC or surgery. Full article

Rainfall is a significant input for several engineering designs such as hydraulic structures, culverts, bridges and ducts, rainfall water sewer, and highway drainage system. The detailed statistical analysis of extreme daily rainfall of each arid environment’s region is essential to estimate the relevant input value for designing and analyzing engineering structures and agricultural planning. This paper aims to assess the best-fitting distribution to estimate the design of rainfall depth (XT) and maximum rainfall values for different return periods (2, 10, 25, 50, 100, and 150). This study used extreme daily rainfall historical data collected in period of 1970–2020, collected from four rainfall gauge stations nearby the Wadi Al-Aqiq that are selected for analysis; they are Al Faqir (J109), Umm Al Birak (J112), Madinah Munawara (M001), and Bir Al Mashi (M103). The methodology approved in this paper examined four frequency distributions, namely: GEV (Generalised Extreme Value), Gumbel, Weibull, and Pearson type III to identify the most suitable and extreme storm design depth corresponding to different return periods. The results demonstrate that GEV and Pearson Type 3 produce higher extremes values, while the Weibull method is commonly suggested in the HYFRAN-PLUS MODEL (DSS) for criterion suitability. The findings for the 100-year storm design demonstrate that extreme values generated by the Hyfran-Plus model are higher than the decision support system (DSS). All (DSS) comparative values are less than the maximum historical data from 1970–2020, except the Al Faqir station (DSS), which has a value of 79.6 mm that exceeds the historical maximum of 71 mm. This study will provide advantageous information about the study area for water resources planners, farmers, and urban engineers to assess water availability and create storage. Full article

In this article, we present a new approximate solution for blood nanofluid having gold nanoparticles as it flows near a stretching porous cylinder in fractal space. A Casson non-Newtonian magneto-bio-nanofluid flowing through a porous medium is considered a potential application in chemotherapy for eradicating cancer cells. Without the need for the nonperturbative approach, the proposed solution uses an alternative approach to dealing with nonlinear problems. This approach transforms the nonlinear cubic jerk model resulting from the simplification of the governing fractional partial differential equations into an equivalent linear formula. This approach is known as highly efficient linear approximation (HELA) or non-perturbation technique (NPT), and this represents a significant advancement over traditional perturbation methods in the analysis of non-linear systems. As a robust mathematical approach, it excels at handling a wide range of coefficient values, particularly in cases of clear nonlinearity. This study also utilized the masking technique simultaneously with HELA, which played a crucial role, as they simplify the complex dynamics of the system, making it more amenable to analysis. The numerical solution by the Runge–Kutta fourth-order (RK-4) method integrated with a shooting technique compared favorably with graphs drawn for the analytical solution from the proposed strategy HELA. The current results show that an increase in the fractal factors enhances the resistance to fluid motion, leading to a suppression of the velocity field. Physically, this often relates to the complexity of the medium or the fractal nature of the transport process, where higher fractal dimensions or factors can lead to slower diffusion or flow rates, like the role of porous media. Therefore, the current study has significant implications in the promotion of nanotechnology fields in medicine, particularly the use of gold nanoparticles in chemotherapy for the eradication of cancerous cells. Full article

The goal of this study is to establish a new type of Milne-type inequality in the scope of fractional calculus with the aid of proportional Caputo-hybrid operators. We will focus on two different scopes of regularity, which contain functions whose first and second derivatives are convex, and functions whose first and second derivatives are Lipschitz continuous. We will base these estimates on a new integral identity of proportional Caputo-hybrid integrals. We will show that the smoothness of the derivative influences the shape of the bounds. Convexity will cause symmetry. Lipschitz continuity will contain bounds on the modulus of continuity. To show that our results are accurate and easy to obtain, we included a full numerical example with graphics and applications to quadrature error estimation. Full article

Climate change disproportionately threatens low- and middle-income countries, yet integrated assessments combining socio-economic fragility with physical hazards remain limited. This study quantifies multi-dimensional climate vulnerability and derives optimized adaptation policies for six representative nations (Bangladesh, Colombia, Kenya, Morocco, Pakistan, Vietnam) by fusing socio-economic indicators with climate risk data (2000–2024). A computational framework integrating unsupervised learning, dimensionality reduction, and predictive modeling was employed. Principal Component Analysis synthesized eight indicators into a Compound Vulnerability Score (CVS), while K-Means and DBSCAN identified distinct vulnerability regimes. XGBoost quantified driver importance, and Graph Neural Networks captured systemic interconnections. XGBoost identified projected drought risk (31.2%), precipitation change (18.1%), and poverty headcount (14.3%) as primary drivers. Graph networks demonstrated significant risk amplification in African nations (Morocco SRS: 0.728–0.874; Kenya SRS: 0.504–0.641) versus damping in Asian countries. A Reinforcement Learning (RL) agent was trained using Deep Q-Networks with experience replay to optimize intervention portfolios under budget constraints. The RL policy achieved a 23% reduction in systemic risk compared to uniform allocation baselines, generating context-specific priorities: drought management for Morocco (score 50) and Pakistan (40); poverty alleviation for Kenya (40); coastal protection for Bangladesh (40); agricultural resilience for Vietnam (35); and institutional capacity building for Colombia (50). In conclusion, socio-economic fragility non-linearly amplifies climate hazards, with poverty and drought risk constituting critical vulnerability multipliers. The AI-driven framework demonstrates that targeted interventions in high-sensitivity systems maximize systemic risk reduction. This integrated approach provides a replicable, evidence-based foundation for strategic adaptation finance allocation in an increasingly uncertain climate future. Full article

Accuracy in fractional numerical integration is often limited by the regularity of the integrand. This work proposes a flexible error estimation framework for proportional Caputo-hybrid integral operators based on $\mathfrak{s}$-convexity. We introduce a parametric Newton–Cotes formula ($\nu \in [0,1]$) that bridges the gap between classical quadrature rules, recovering the fractional Trapezoidal, Midpoint, and Simpson’s methods as specific instances. In order to confirm the correctness of our results, we provide an illustrative example with graphical representations. Furthermore, we provide some additional results using Hölder’s and power mean inequalities and employ a verification strategy based on an Artificial Neural Networks (ANNs) model. The ANN approach allows for high-dimensional parameter space exploration, demonstrating that the proposed inequalities provide robust and precise error estimates. Full article

Background: Antimicrobial resistance continues to threaten effective infection management worldwide and is driven largely by inappropriate prescribing practices. In Saudi Arabia, the cities of Makkah and Al-Madinah experience intense seasonal healthcare demand due to the annual pilgrimage, creating additional challenges for rational antibiotic use. This study aimed to evaluate physicians’ knowledge, attitudes, and prescribing behaviors related to antibiotics in these high-demand settings. Methods: A cross-sectional analytic study was conducted between June and August 2024 among physicians practicing in Makkah and Al-Madinah, including those participating in Hajj services. A previously validated, structured electronic questionnaire assessed knowledge of common pathogens, perceptions of antimicrobial resistance, prescribing influences, and counseling practices. The survey was distributed electronically to eligible physicians. Descriptive statistics were generated, and associations were examined using appropriate inferential tests with a 95% confidence level. Results: A total of 487 physicians participated. Most respondents (74%) correctly identified major bacterial causes of upper respiratory tract infections, and 90% acknowledged the association between prior antibiotic exposure and resistance. Nonetheless, misconceptions persisted regarding the benefit of antibiotics in viral conditions. Workload and patient expectations influenced prescribing behavior; 77% reported a greater likelihood of prescribing antibiotics during periods of high clinical pressure. While adherence to guideline-based practice was generally reported, variability existed in counseling practices and perceptions of stewardship policies. Conclusions: Although baseline knowledge was satisfactory, contextual and behavioral factors continue to influence prescribing decisions and may contribute to unnecessary antibiotic exposure, highlighting the need for strengthened antimicrobial stewardship strategies in high-demand healthcare environments. Full article