Volume 21 Issue 5 2026

Background and Objective Sickle Cell Disease is a blood genetic disorder and a major problem among the tribal population of India. There is no structured program in action in the country for the diagnosis, treatment, and management of the disease. This study protocol aims to train health care workers i.e., Medical officers, Auxiliary Nursing Midwifery , Laboratory Technician, and Community Health Officers , for diagnosis and counseling for sickle cell disease through a training program in eight SCD- endemic tribal districts of Rajasthan, India. Methodology The sub-districts of Udaipur, Banswara, Sirohi, Dungarpur, Pratapgarh, Pali, Chittorgarh, and 25 Rajsamand will be included in the study. The sub-districts having more than 50% tribal 26 population will be included in the study. The training sessions will be organized at the CHC/PHC in eight districts. Data for this study will be collected from pre- and post-questionnaires given to healthcare professionals during the training program. A counseling module in English and the 29 local language will be circulated to health worker to improve their knowledge regarding 30 diagnosis, management, and prevention strategies for sickle cell disease. Discussion The results of this study could provide information on the necessity of bolstering the capacity for implementation research in endemic areas. Expected outcomes The outcomes of the study will provide a better understanding regarding the diagnosis, control, and management of sickle cell disease among the health workers. The primary outcome will be capacity building of the health workers in conducting screening of SCD and creating awareness of sickle cell disease among tribes.

The employability of graduates in Information Technology (IT) is a crucial indicator of how well academic programs work and how well educational outputs match industrial needs. This study aims to track job positions, examine employer feedback, and pinpoint employment patterns among IT graduates using data analytics techniques, particularly time series analysis and linear regression. The research identified that the trends of graduates will increase by approximately 42% in the next three years. 92% of graduates are actively employed, seven percent (7%) are not employed, and only one percent (1%) have taken a chance on entrepreneurship. 60% of graduates hold positions directly connected to their study area, such as IT technician, network management, and software development, and 24% of the workforce is working in roles that utilize their IT expertise in broader areas, such as content creator, Office Secretary, service worker, and market sales worker. 8% of graduates have launched their own companies, and 87% of companies are happy with the work that IT graduates do. The findings provide a thorough understanding of the current situation of IT graduate employment by tying graduate characteristics to employer expectations. These insights can improve future graduates' employability and career success by assisting companies, policymakers, and educational institutions make data-driven decisions that better connect IT education with industry demands.

The rapid expansion of Nigeria's fintech ecosystem, accelerated by recent cashless policy drives, presents a transformative potential for the nation's economic landscape. However, the informal sector, which constitutes a significant portion of Nigeria's GDP, remains largely marginalized in the digital financial narrative. This phenomenological study explores the lived experiences and perceptions of informal sector Small and Medium Enterprises (SMEs) regarding their adoption and utilization of fintech solutions. Through in-depth interviews with traders and artisans, the research reveals a complex interplay of trust, convenience, and systemic barriers. While participants appreciate the efficiency and security of digital payments over physical cash, they express profound apprehension regarding transaction failures, hidden charges, and the prevalence of electronic fraud. The study finds that utilization is largely reactive rather than strategic; SMEs adopt tools like USSD and payment gateways primarily to meet customer demand rather than to optimize their own business operations. The findings suggest that current fintech interfaces often fail to accommodate the low-digital literacy and high-risk aversion characteristic of the informal sector. Consequently, the study recommends a paradigm shift towards user-centric designs, robust consumer protection frameworks, and targeted digital literacy programs to bridge the trust gap and integrate informal SMEs effectively into the formal digital economy.

The removal of the Premium Motor Spirit (PMS) subsidy in Nigeria represents a pivotal macroeconomic shock that drastically escalated operational costs, threatening the survival of the non-oil sector. This study investigates the resilience of Small and Medium Enterprises (SMEs) by exploring the adaptive strategies and coping mechanisms these businesses have employed in the wake of this policy reform. Adopting a multiple case study design, the research utilizes in-depth semi-structured interviews and observational data from 20 SMEs across the manufacturing, retail, and service sectors. The analysis reveals a complex spectrum of survival strategies, ranging from immediate cost-cutting measures such as staff downsizing, inventory rationing, and reduction of operating hours to more structural adaptations, including the aggressive passing of costs to consumers and the tentative shift toward alternative energy sources. The findings indicate that while SMEs exhibit significant organizational resilience, these coping mechanisms are predominantly reactive and increasingly unsustainable, pushing many firms to the brink of insolvency. The study concludes that ensuring the longevity of the SME sector requires government interventions that move beyond general palliatives to include targeted fiscal relief, subsidized energy tariffs, and access to low-interest credit facilities tailored to the post-subsidy economic reality.

The study examined the relationship between selected Artificial Intelligence (AI) tools and the management of teaching and learning in Universities in the North-Central States of Nigeria. Specifically, the study focused on the use of chatbots and automated grading systems. A correlational design was adopted, and a sample of 386 university staff was drawn using stratified random sampling from a population of 10,787 staff from nine (9) Universities in North-central Nigeria, determined by the Taro Yamane calculator. Data was collected using a 16-item questionnaire titled Artificial Intelligence and the management of teaching and learning in Universities in the North-Central States of Nigeria (AIMTLUNCN). The instrument was validated by experts, yielding a validity index of 0.79, while the reliability coefficient of 0.71 was obtained through pilot testing. Pearson’s Product-Moment Correlation was used to answer the research questions, while Regression analysis was used to test the hypotheses of the study at a 0.05 level of significance. Findings reveal a very weak and non-significant relationship between Chatbots and the management of teaching and learning (r = 0.062, p > 0.05) as well as between automated grading systems and the management of teaching and learning (r = 0.026, p > 0.05). The study concludes that there is no significant relationship between the selected AI tools and the management of teaching and learning, indicating limited adoption and ineffective integration of AI in university teaching and learning management systems.

This study investigated the relationship between Artificial intelligence-based adaptive learning systems, intelligent tutoring systems and students’ learning in universities in North-central Nigeria. The study was guided by two (2) research objectives, questions, and corresponding hypotheses. The study was anchored on the Technology Acceptance Model (TAM) and adopted a correlational research design. The population comprised 10,787 students across nine universities in North-Central, from which a sample size of 399 was selected using a stratified random sampling. Data was collected using a validated questionnaire and analysed through Pearson’s Product-Moment Correlation, and Regression analysis was used to test the formulated hypotheses at a 0.05 level of significance. The finding revealed that both the adaptive learning systems and the intelligent tutoring systems have a weak positive relationship with students’ learning (r=0.055) and were not statistically significant. Consequently, both hypotheses were accepted. The result indicated that although AI technologies have the potential to enhance personalised and interactive learning, their current utilisation in universities within the North-central zone of Nigeria has not significantly influenced students’ learning outcomes. This weak relationship suggests low acceptance and utilisation of AI tools, which aligns with TAM constructs of perceived usefulness and perceived ease of use. The study concludes that the limited impact of these technologies may be linked to low perceived usefulness and ease of use, as well as infrastructural and institutional challenges affecting their adoption. It is recommended that universities should improve technological infrastructure, enhance digital literacy and provide adequate support systems to facilitate the effective integration of AI tools in teaching and learning

This research article explores the origins, historical significance, ritual practices, and sociocultural importance of Maa Abhaya, a local folk deity worshipped in Kutasingha village, Balangir district, Odisha, India. The veneration of Maa Abhaya is deeply rooted in the collective memory of the community and is linked to a miraculous healing event during an ancient cholera epidemic. Notably, the cult distinguishes itself within the landscape of Odishan folk religion by its unwavering commitment to non-violent offerings primarily coconuts in sharp contrast to the widespread practice of animal sacrifice among village deities in the region. The annual festival, celebrated during the auspicious month of Jyeshtha (Jyoshtha Masa), serves as a significant unifying occasion for the community. Drawing from oral traditions, ethnographic observation, and comparative religious analysis, this article contends that the cult of Maa Abhaya represents a rare embodiment of ahimsa (non-violence) within an ancient folk religious context. This unique tradition merits scholarly attention and cultural preservation for its exceptional commitment to non-violence and its enduring role in local religious identity.

Background: Radiation exposure remains a critical concern in pediatric computed tomography (CT) due to heightened radiosensitivity and increased lifetime attributable risk of malignancy. Technological advances in image reconstruction have enabled substantial radiation dose optimization. Deep learning reconstruction (DLR), a novel artificial intelligence-based approach, has emerged as a promising method to improve image quality while permitting further dose reduction. Purpose: To systematically evaluate current evidence regarding the impact of deep learning reconstruction on image quality and radiation dose reduction in pediatric low-dose CT. Method: A systematic review was conducted in accordance with PRISMA 2020 guidelines. PubMed and Google Scholar were searched for English-language original research article published between January 2019 and March 2026. Studies were eligible if they include pediatric patients (≤18 years), evaluated CT imaging with deep learning reconstruction and reported objective or subjective image quality metrics and/or radiation dose outcomes. Data were extracted using standardized forms, and risk of bias was assessed using an adapted Newcastle-Ottawa framework. Due to heterogeneity in reporting and incomplete availability of variance data, a structured narrative synthesis was performed. Result: Fifty-three records were identified; for studies met inclusion criteria. All included studies demonstrated significant reductions in image noise and improvements in signal-tonoise ratio (SNR) and contrast-to-noise ratio (CNR) with DLR compared to conventional iterative reconstruction techniques. Two studies reported radiation dose reductions of approximately 50-55% while maintaining diagnostic image quality. Risk of bias was low to moderate across studies. Conclusion: Available pediatric evidence indicates that deep learning reconstruction improves image quality and enables meaningful radiation dose reduction in low- dose CT protocols. Although current data remain limited, findings consistently support integration of DLR into pediatric CT imaging strategies.

Figurative language (metaphors, idioms, proverbs, evaluative comparisons, and symbolic images) is one of the most sensitive zones in which a society’s gender concept becomes visible. Gender, understood as a socio-cultural construct rather than a purely biological category, is repeatedly encoded in imagery that evaluates women and men, prescribes “appropriate” behavior, and legitimizes power relations through seemingly neutral expressions [1, 2]. This article examines how the gender concept operates in figurative language as (1) a cognitive mechanism that maps abstract social meanings onto concrete bodily and cultural images [3], (2) a discourse mechanism that indexes stereotypes and normative expectations [4, 5], and (3) a pragmatic mechanism that strengthens persuasion and social control in everyday interaction and media. Using a qualitative comparative approach, the study analyzes representative figurative patterns from Azerbaijani, Russian, English, and selected European languages (French, German, Italian), with brief parallels from Turkish context, to demonstrate cross-cultural similarities (e.g., metaphors of strength, purity, danger, leadership) and culturally specific models (e.g., honor/shame frames; family-role symbolism). Brief parallels from Turkish figurative language further support the cross-cultural patterns discussed above. In Turkish, masculinity is frequently conceptualized through metaphors of moral strength and responsibility, as in “Erkek adam sözünün eri olur” (“A real man stands by his word”) or “aslan gibi adam” (“a man like a lion”), which align leadership and authority with strength and reliability. Femininity, by contrast, is often evaluated through metaphors of modesty, honor, and domestic responsibility, for example “Yuvayı dişi kuş yapar” (“The female bird builds the nest”) or “namus kadının süsüdür” (“Honor is a woman’s ornament”). These Turkish examples parallel Azerbaijani and Russian data by showing how figurative language encodes gender roles through culturally salient values such as honor, family reputation, and moral restraint, rather than through explicit gender labeling.The discussion integrates conceptual metaphor theory, gender linguistics, and critical discourse perspectives to show that gendered imagery is not decorative: it structures meaning, guides interpretation, and shapes attitudes in communication. The article proposes a classroom- and research-friendly analytical framework for identifying gender metaphors and gendered idioms, with practical implications for language education, translation, and intercultural communication—especially in contexts such as Azerbaijan where multilingual contact intensifies the circulation of global and local figurative models [6].

A comprehensive investigation into the progress in solar water heating technologies since inception is presented in this paper. The efficient utilization of solar energy for heating water is crucial for sustainable energy practices, and thermal energy storage in the form of latent heat emerges as a promising solution. The research summarizes various studies examining thermal storage systems with and without phase change materials (PCMs), classifying them into the kind of collector and the category of storage in action (either sensible or latent). An exhaustive literature study underscores the importance of PCM selection criteria, emphasizing the requirement for materials that possess high latent heat capacity and extensive surface areas to ensure heat transfer optimally. This article highlights the significance of PCM-based thermal storage in enhancing the performance (thermal) of solar water heaters, paving the way for more efficient and sustainable heating solutions.

Centrifugal fans are used extensively in industries where their aerodynamics play an important role in affecting the efficiency of the process and energy consumed. This paper reviews the state of the art related to centrifugal fan design, aerodynamics, CFD analyses, optimization methods, experimentation, structure, and noise. Analysis of the effect of important geometric variables, such as blades profile, impeller arrangement, and volute shape, is done to determine their impact on performance. Effectiveness of numerical models, especially Computational Fluid Dynamics (CFD), in simulating flow, pressure, and losses in the fan is evaluated. Several optimization methods, such as Response Surface Methodology (RSM), Genetic Algorithm (GA), Artificial Neural Network (ANN), and multi-objective optimization, are discussed. The significance of experiments and structural analysis for reliable and durable systems is also explored. The key trends, research areas, and recommendations have been developed based on the comparative analysis of the existing literature to provide insights into the design of efficient centrifugal fans.

The article examines the nature of humanity through a synthesis of psychological theories and contemporary data from paleogenetics. Classical psychological theories do not account for the genetic diversity of modern humans. Meanwhile, modern achievements in paleogenetics pose the problem of revising many models of human behavior and nature. A theoretical, comparative analysis of works by classics of psychology and articles from the search systems PubMed, Google Scholar, and e-library was conducted, as well as a descriptive analysis of modern paleogenetic studies on the sequencing of hominin genes. The research hypothesis suggests that differences are conditioned not only by social factors but also by the biological heritage from various hominin species. The study's main results are presented in a critique of Maslow's concept of the hierarchy of needs, which cannot be viewed as universal. The theory ignores the biological diversity of humans, who have inherited up to 6% of their genes from Neanderthals and Denisovans, which may influence behavior. Biological heritage explains the variability in human needs. Cultural differences also alter the "hierarchy" of humanity. It is shown that humanity cannot be reduced to a single model, as it depends on genetics, culture, and context. It is emphasized that the evolutionary approach explains such manifestations in different groups of people as aggression, creativity, or altruism. However, while there is no direct evidence of a link between specific genes and psychological traits, the hypothesis requires further research. Humanity is the product of a complex interaction between biology (genes of ancient hominins) and the social environment. Psychological theories must integrate paleogenetic data for more accurate models of motivation. Interdisciplinary research at the intersection of psychology, anthropology, and genetics can yield new analytical material.

The present study is aimed to evaluate the antidiabetic and antioxidant properties of a newly synthesized Metformin–Resveratrol Aldehyde complex (Met-Res-Aldehyde complex) in high-fat diet-fed, lowdose streptozotocin-induced experimental type 2 diabetes mellitus in rats. The effect of oral administration of the Met-Res-Aldehyde complex (5 mg/kg body weight) for a period of 30 days on the levels of biochemical parameters was evaluated in experimental groups of rats. The antidiabetic efficacy of the complex were assessed by measuring a range of biochemical indices, including fasting blood glucose, plasma insulin, haemoglobin, glycosylated haemoglobin, total protein, urea, uric acid, and creatinine. Oxidative stress markers such as TBARS, lipid peroxides, hydroperoxides and protein carbonyls were analyzed in plasma, pancreatic, hepatic, and renal tissues. The status of enzymatic antioxidants, including superoxide dismutase (SOD), catalase, glutathione peroxidase (GPx), and glutathione S-transferase (GST), gluatathione reductase (GR) as well as non-enzymatic antioxidants such as vitamin E, vitamin C and ceruloplasmin, were also evaluated. Diabetic rats showed significantly increased levels of fasting blood glucose and glycosylated haemoglobin. Oral treatment with the Met-Res-Aldehyde complex resulted in the maintenance of normoglycemia by decreasing oxidative stress markers and improving antioxidant status in diabetic rats. The results of the study indicate that the Met-Res-Aldehyde complex is non-toxic and possesses significant antioxidant properties which in turn responsible for its observed antidiabetic efficacy. These effects are comparable to those of metformin, a standard oral hypoglycemic drug.