Arabic language retention is widely theorised as central to the cultural reproduction of Arab diaspora communities, yet its empirical relationship with cultural maintenance has rarely been examined through systematic multivariate analysis in the Indian context. Drawing on original survey data from 214 third-generation and beyond Yemeni-origin households across three Indian states Telangana, Maharashtra, and Karnataka this study tests Arabic language ability as a predictor of cultural maintenance practices, supranational identity, and employment outcomes. OLS regression analysis reveals that Arabic ability is the single strongest predictor of cultural maintenance (β = .497, p < .001), accounting for over 52% of variance in cultural maintenance scores in a five-predictor model (R² = .528). Kruskal-Wallis tests demonstrate significant state-level variation in both Arabic retention and cultural maintenance (H = 142.35 and H = 145.04, respectively, both p < .001), with Telangana communities exhibiting substantially higher scores than Maharashtra and Karnataka counterparts. Joint family structure further moderates cultural maintenance (H = 19.005, p < .001). These findings suggest that language is not merely a marker of heritage but an active transmission mechanism a cultural carrier that transports and reproduces Yemeni identity across centuries of settlement. The results have implications for theories of long-settled diaspora, heritage language maintenance, and the relationship between linguistic and cultural assimilation in South Asian Muslim communities.

Background: Premature rupture of membranes (PROM) is the rupture of fetal membranes before labour. When it occurs before 37 weeks, it is termed preterm prelabour rupture of membranes (PPROM), which is associated with increased maternal and perinatal morbidity and mortality. The early identification of at-risk cases is crucial. The platelet–lymphocyte ratio (PLR) from routine blood counts has emerged as a low-cost inflammatory biomarker for obstetric conditions. This study evaluated the association between maternal PLR and PPROM and explored its predictive value. Methods: This cross-sectional analytical study was conducted at the Department of Obstetrics and Gynaecology, Dhaka Medical College Hospital, from June 2022 to May 2023. Sixty pregnant women between 28 and 36+6 weeks of gestation were included: 30 with PPROM (Group A) and 30 healthy controls (Group B). Complete blood counts were performed and the PLR was calculated as the ratio of the platelet to lymphocyte count. Data were analyzed using SPSS version 26.0. Results: The mean age did not differ significantly between the groups (27.57±5.14 vs. 28.33±5.02 years; p=0.56). The platelet count was significantly higher in the PPROM group (269.63±63.4 vs. 207.43±46.5 ×10³/mm³; p<0.001), whereas the lymphocyte counts were comparable (p>0.05). The mean PLR was significantly higher in PPROM cases than in those with intact membranes (123.15±27.73 vs. 104.48±26.09; p=0.009). Conclusion: Elevated maternal PLR is significantly associated with PPROM and may serve as a simple, cost-effective inflammatory marker for risk identification in pregnancies. Larger multicenter studies are needed to confirm its clinical utility.

Education is a prominent weapon for nation-building. No nation can move forward without quality education among its people. In India, several commissions and committees have been established, and numerous recommendations have been made to spread equal educational opportunities among all sections of society. It indicated that education is the means of promoting inclusivity within society with respect to casts, creed, gender, and geographical constraints. But it is a very pathetic and sorrowful situation that many indigenous communities are lagging in education, especially the ‘Particularly Vulnerable Tribal Group’, or PVTG (previously known as a primitive tribal group). Their educational status is very low, and their condition is inferior, deprived, and increasingly endangered and marginal. Thus, it was evident that educational opportunities are not equally distributed. The tribal community has still not benefited much from education. The Sabar community is one among them. They thought education was a luxury for them. Under the guise of education, it's merely time-wasting, with no practical application or connection to real-life situations. The tribal community is fed up with this modern education. They do not show interest in this education system. As a marginalized tribal group, the Sabars have their own culture, knowledge system, and tradition, which affect their education. Their storytelling, folklore, rituals, daily life experiences, and lack of education are significant. Education through these programs helps increase their social cohesion, motivation, and life skills, among other benefits. The objective of this research is to identify and analyze the indigenous pedagogical practices among the Sabar community, and this work also highlights how indigenous cum cultural context pedagogy helps them to bring mainstreaming in education. Keeping the above objectives in mind, the researcher employed an ethnographic research design and collected data through participatory observation, focus group discussions, and field notes. This article shows that, in its cultural context, indigenous pedagogy has the potential to promote education among the Sabar Community. So, it's our responsibility to identify their informal ways of knowing and incorporate them into the modern educational process, allowing them to find their culture and ways of living within the institutional framework.

Background: Oral cancer remains a significant global health burden, often diagnosed at advanced stages, leading to high morbidity and mortality. The quality of life and survival rates are significantly increased by early identification. Purpose: This systematic review is to assess the available data on artificial intelligence's potential to aid in the early detection and diagnosis of oral cancer. It focuses on evaluating the clinical applicability, sensitivity, specificity, and diagnostic accuracy of AI-based tools in contrast to traditional diagnostic techniques. Study selection: A systematic literature search was performed using PUBMED, MEDLINE, EMBASE, and COCHRANE Library with language restriction to English. The search was carried out incorporating the published literature till 2026 using the MeSH (medical subject heading) terms. A literature search was done out of 245 publications, related to search strategy, 57 full articles, which were related to the study, were acquired for further inspection. Out of the 49 articles, 6 articles met the inclusion criteria. Information related to study characteristics, types of AI models used, imaging techniques, and reported diagnostic performance was collected and reviewed. Results: The reviewed studies demonstrate that AI models, particularly convolutional neural networks, exhibit high diagnostic accuracy in evaluating clinical photographs, histopathology, radiographs, and autofluorescence images. Many reports showed sensitivity and specificity above 85%, signifying ability of AI to differentiate malignant and potentially malignant lesions from benign conditions. Conclusion and Relevance: Artificial Intelligence serves as a promising adjunct in the early detection and diagnosis of oral cancer, offering high diagnostic accuracy and improved support for clinical decision-making without replacing professional expertise. This review highlights the potential of artificial intelligence to enhance early and accurate detection of oral cancer, which can significantly improve patient survival and treatment outcomes. It also underscores the role of AI as a supportive clinical tool that can increase diagnostic consistency and aid clinicians in timely decision-making.

Isolated dissection of the celiac trunk is a rare vascular condition that is often discovered incidentally on contrast-enhanced computed tomography (CT). We report the case of a 72-year-old male who presented to the emergency department with acute biliary pancreatitis. Contrast-enhanced abdominal CT revealed biliary obstruction and an incidental aneurysmal dilatation of the celiac trunk associated with two distinct dissection planes extending toward the splenic artery without vascular occlusion or organ ischemia. As the vascular lesion was asymptomatic, conservative management with clinical and imaging follow-up was recommended. This case highlights the importance of systematic evaluation of vascular structures during emergency CT examinations, even when imaging is performed for non-vascular indications.

Hybrid nanomaterials have become a revolutionary group of designed systems that combine the complementary physicochemical characteristics of various constituents on the nanoscale, presenting novel prospects in developing technologies that are sustainability-oriented. These materials incorporate organic, inorganic, and bio-inspired constituents into a single architecture, which makes the materials allow synergistic capabilities that cannot be achieved by single-component systems. Their use has grown substantially in the last few years in catalysis, environmental remediation, and advanced energy systems due to the pressing necessity to solve global problems of resource depletion, pollution and climate change. Hybrid nanomaterials in catalytic processes exhibit superior activity, selectivity and stability as a result of optimized surface interfaces and adjustable electronic structures that enable effective generation of pollutants and renewable feedstocks. Simultaneously, their use in environmental science has become mainstream due to their application in water purification, air filtration, and sensing platforms, where the high surface area and versatile use allow quick and selective removal of contaminants. These materials are also used in energy-related fields, such as supercapacitors, batteries and photocatalytic devices, where they advance the high-performance of storage and conversion systems by enhancing the charge transport, energy density and cycling stability. Even with these developments, scalability and long-term stability issues, as well as environmental impact, are a key obstacle to large-scale adoption. This review shows that in recent times, there has been an advancement in the rational design, synthesis and functional optimization of hybrid nanomaterials, with a focus on structure-property interactions and their potential application in sustainability. Moreover, it discusses new directions and the future visions targeted at closing the gap between laboratory development and industrial adoption.

Purpose: This research aims to study the extent of customers’ acceptance of mobile payment services in Sudan during the political instability period, and critically analysis the impact of the war and lack of liquidity (cash shortage) on the intention and actual use of service. The study also adapts and extend the UTAUT model by taking into account factors such as system speed, political instability and illiquidity influence. Design/Methodology/Approach: The study takes a quantitative research technique to evaluate the relationship between many independent and dependent variables. The data have been collected using an online survey, statistical analysis is conducted using the SPSS software and SPSS AMOS 24. Findings: The empirical findings validate that the intention to use mobile payment systems and their actual usage during the Sudan war crisis is significantly and positively influenced by performance expectancy, effort expectancy, facilitating conditions, political instability influence, and illiquidity influence, while social influence and system speed found to have no significant effect of Sudanese intention to use the mobile payment system during the crisis time. Originality/Value: The importance of this study stems from the fact that it is one of the first studies to investigate the impact of political instability, and severe cash shortages on consumers' intention to adopt and use mobile payment services, coinciding with the ongoing war in Sudan.

Background: Polycystic Ovary Syndrome (PCOS) is a prevalent endocrine disorder in which insulin resistance (IR) drives reproductive and metabolic abnormalities. Baseline characterization of clinical, hormonal, and IR profiles is critical for personalized management. Objective: To establish baseline clinical, hormonal, and IR profiles in women with PCOS and examine correlations between IR severity and phenotypic features. Methods: This randomized controlled trial enrolled 90 women with PCOS (Rotterdam 2003 criteria) and IR (HOMA-IR >2.0) aged 18–40 years at BSMMU, Dhaka, Bangladesh (July 2023–June 2024). Clinical, hormonal, and metabolic parameters were assessed. Correlations with HOMA-IR and comparisons between mild-moderate (HOMA-IR 2.1–3.5) and severe IR (>3.5) groups were performed. Results: Mean age was 25.3±3.7 years; mean BMI 26.1±2.5 kg/m². Oligomenorrhea (96.7%), hirsutism (90.0%), acanthosis nigricans (73.3%), and primary infertility (81.1%) were common. Hormonal profile showed elevated LH/FSH ratio (1.72±0.59), elevated total testosterone (2.8±0.9 nmol/L), elevated free androgen index (10.5±4.2), and low SHBG (28.4±8.6 nmol/L). Mean HOMA-IR was 3.46±0.96 despite normal fasting glucose. HOMA-IR correlated positively with BMI (r=0.52), waist circumference (r=0.48), testosterone (r=0.41), and FAI (r=0.46), and negatively with SHBG (r=-0.38), but not with LH or LH/FSH ratio. Severe IR group had significantly higher adiposity and androgens and lower SHBG than mild-moderate IR group, with no difference in gonadotropins. Conclusion: In Bangladeshi women with PCOS, IR severity is associated with greater adiposity and hyperandrogenemia but not with gonadotropin abnormalities. Routine IR assessment is essential for phenotype-guided therapy.

The high environmental impact and cost of cement-based construction materials have intensified the search for sustainable alternatives. This study investigates the mechanical, durability, and microstructural performance of compressed stabilized earth blocks (CSEBs) incorporating Parkia biglobosa (Makuba) as a bio-based stabilizer. Lateritic soil was characterized using particle size distribution, Atterberg limits, and compaction tests, while Makuba extract was chemically analyzed. Blocks were produced with varying Makuba contents and cured for 7–28 days. Compressive strength, water absorption, and microstructural properties (SEM, EDX, XRD) were evaluated. Results show strength improvements of 25–60%, with peak values exceeding 3.0 N/mm², satisfying Nigerian Industrial Standard requirements. Water absorption decreased by 15–35%, remaining below 12%, while microstructural analysis revealed pore refinement, enhanced particle bonding, and matrix densification. The findings confirm Makuba as a viable low-cost, eco-friendly stabilizer capable of producing durable structural earth blocks suitable for sustainable housing applications.

This study presents an applied research approach aimed at implementing a continuous improvement framework for the development of commercial strategies within an emerging company. The proposed framework integrates information gathering, data analysis, and strategic design within an iterative cycle supported by project management tools. Its primary objective is to structure commercial decision-making processes and enhance sales performance through measurable and replicable mechanisms. The methodology combines qualitative data collection, analytical processing, and project planning techniques, incorporating the Earned Value Method (EVM) as a control tool to monitor execution in terms of scope, time, and cost. The results demonstrate that EVM enables objective performance tracking, identifying schedule deviations (SPI = 0.67) while maintaining cost efficiency (CPI = 1.02). This facilitated the implementation of timely corrective actions and the consolidation of commercial strategies aligned with key performance indicators.

Workforce productivity remains a key factor in the performance of service-oriented organizations where employee activity directly affects service delivery and operational outcomes. Effective productivity measurement requires systematic analysis of workforce performance indicators and operational data. This study presents a workforce productivity measurement framework designed for service environments. The framework integrates workforce analytics, management information systems data, and operational performance indicators to calculate a Workforce Productivity Index (WPI). The model uses several indicators, including task completion rate, customer satisfaction score, operational efficiency index, attendance consistency, and service response time. Enterprise information systems provide operational records that support quantitative evaluation of workforce productivity across service teams. The proposed model combines these indicators through a weighted productivity formula that generates productivity scores for employees or operational units. Evaluation results show clear performance differences across workforce groups and identify productivity patterns within service operations. Higher productivity scores correspond to efficient task completion, consistent attendance, and positive service feedback. The framework provides a structured approach for productivity evaluation using operational indicators and enterprise system data. The proposed model also supports workforce performance assessment and organizational productivity analysis within service-based operations.

Cloud-based SaaS platforms now run essential services across finance, healthcare, and government sectors. Many of these systems include automated agents and decision engines that operate at high speed and scale. Identity and access governance therefore serves as a central control layer. Traditional IAM models depend on fixed roles, centralized authorization servers, and periodic reviews. Such structures struggle in distributed, multi-tenant environments that process millions of access requests each day. Prior studies address adaptive authentication, Zero Trust security, decentralized identity, anomaly detection, and cloud resilience. However, these solutions often function separately rather than within a unified framework. This paper introduces a Resilient Identity and Access Governance Architecture that integrates real time risk evaluation, distributed policy enforcement, lifecycle governance for human and machine identities, and fault tolerance in a single design. The framework defines measurable targets for availability, detection time, throughput, and policy propagation. Risk scoring occurs during live authorization decisions, and enforcement spans multiple nodes. The result is a scalable identity governance model suitable for complex SaaS ecosystems that require high availability and consistent control.

Power electronic converters have been at the center of industrial systems and various energy systems such as renewable energy systems, industrial motor drives, and grid-connected power systems. The systems face harsh conditions, making reliability an essential factor for the design. The traditional procedure for the design of converters considers the reliability of the system after the parameters have been selected for the design, making it difficult to consider the parameters of the system during the design stage. This paper proposes a reliability-oriented design optimization framework for power electronic systems operating in industrial and utility-scale applications. The proposed methodology integrates electro-thermal modeling, physics-of-failure lifetime estimation, and mission-profile-based stress evaluation within a unified multi-objective optimization framework. Junction temperature profiles and thermal cycling patterns are obtained through electro-thermal simulation under realistic operating conditions. Device lifetime is then estimated using fatigue-based models, and the resulting reliability metrics are incorporated into a multi-objective optimization algorithm that considers lifetime, efficiency, and system cost. A case study involving a 500-kW grid-connected converter demonstrates the effectiveness of the proposed approach. Simulation results show that the optimized design reduces thermal stress and increases predicted semiconductor lifetime from 6.8 years to 13.6 years while maintaining high efficiency with a moderate increase in system cost. The proposed framework provides a systematic approach for reliability-oriented design of industrial power electronic systems.

In the crystalline basement terrains of Southwestern Nigeria, groundwater exploration remains a significant challenge due to the extreme lateral and vertical heterogeneity of the subsurface. This study investigates the Agbaje–Ijokodo area in Ibadan, a region historically plagued by high borehole failure rates, using an integrated geophysical approach. By combining 1D Vertical Electrical Sounding (VES) at 28 locations with 2D Electrical Resistivity Tomography (ERT) across 14 profiles, we mapped the complex architecture of the local aquifer system. The results reveal a predominant three-layer geoelectric sequence: a clayey topsoil, a weathered saprolite layer (averaging 10.8 m in thickness), and a basal fractured-to-fresh basement. Interpretation of geoelectric curves, primarily H-type (57%) and Dar-Zarrouk parameters indicates that while the weathered regolith provides storage, its productivity is often hampered by high clay content. Critical secondary porosity was identified in deep-seated fracture zones and basement depressions, particularly in the Agbaje sector, where reflection coefficients below 0.75 and longitudinal conductance values (0.2 - 0.69 mhos) suggest both high groundwater potential and moderate protective capacity. In contrast, the Ijokodo area is characterized by shallow bedrock ridges and thin overburden, explaining its poor-to-fair yield history. These findings suggest that sustainable groundwater development in the area must shift from targeting shallow saprolite to deeper, localized fracture networks. This research demonstrates that an integrated resistivity framework is indispensable for reducing the risks associated with borehole siting in complex metamorphic terrains.

Digital banking platforms generate large volumes of operational information through transaction processing systems, system logs, and customer communication channels. Many studies examine transaction monitoring, fraud detection, and cybersecurity events. Customer interaction records receive less attention as a source of operational risk information. This study investigates the use of customer interaction data as indicators of operational conditions in digital banking platforms. The research examines interaction records collected from support tickets, complaint submissions, chat conversations, and service request logs. These records are analyzed together with Management Information System (MIS) event logs in order to identify recurring service issues and operational patterns. The proposed analytical framework organizes interaction data through several stages that include data collection, preprocessing, interaction pattern detection, and operational risk indicator generation. Repeated reports related to transaction delays, authentication failures, and application performance problems appear within the interaction dataset. These patterns correspond to operational events recorded in system activity logs. The study also introduces a quantitative operational risk score calculated from the frequency and severity of interaction categories. The results indicate that customer interaction datasets contain measurable signals related to operational disruptions within digital banking platforms. The analytical framework demonstrates that interaction records provide an additional information source for operational monitoring and risk analysis in digital financial services.