Low learning quality and weak initial Academic Ability Test (Tes Kemampuan Akademik/TKA) results at SMP Negeri 1 Kendal (State Junior Secondary School 1, Kendal), Indonesia, were traced to slow, manual academic supervision with little concrete modeling for teachers. The 2024 Education Report Card recorded a Learning Quality score of 60.00 (Moderate), and an initial TKA Mathematics simulation of only 32.10. This paper describes the implementation and documented impact of the DITA-AI Strategy (Data-Driven, Insight-Generating with AI, Targeted Coaching, Action & Assessment), applied as part of the KAPAS GULA Module 125 teacher-capacity program in Kendal Regency. The study is a single-school, descriptive best-practice case study led by the school principal, comparing baseline (2024) and post-intervention (2025-2026) documentation, without a comparison group or inferential statistical testing. The strategy combined data-based diagnosis, structured prompt-engineering on generative-AI platforms to draft teaching modules and higher-order-thinking-skill (HOTS) item banks, and three-stage clinical supervision under a teacher-as-final-validator principle. Documented changes include a reduction in pre-supervision analysis time from 3-4 days to a principal-estimated 15-30 minutes per teacher; a rise in teachers delivering HOTS-based instruction from 35.00% to 87.50%; an increase in the Learning Quality indicator from 60.00 to 70.83; and higher mean TKA scores in Indonesian Language (65.60) and Mathematics (41.84), both above the national average. These findings are consistent with the strategy's effectiveness, but because the design is a single-site descriptive account without a control group, causal claims cannot be statistically confirmed and require further quasi-experimental or multi-school verification.

Due to their varied phytochemical makeup and possible cosmetic advantages, herbal compounds have drawn more attention in lip-care formulations. The development of various lip-care products can benefit from the moisturizing, antioxidant, calming, anti-inflammatory, antibacterial, and natural colouring qualities of various herbs and plant-derived compounds. The significance of herbal substances in lip care, their key characteristics, and their uses in different formulations are all outlined in this paper. It also covers the benefits and drawbacks of using herbal compounds, such as stability issues, standardization issues, and variations in phytochemical makeup. Additionally highlighted are recent advancements and potential future improvements in the application of sophisticated delivery technologies and enhanced scientific assessment of herbal compounds. All things considered, herbal substances are promising components for the creation of multipurpose, organically produced lip care solutions.

This study was conducted to find teachers' challenges in teaching reading. It followed the descriptive-correlational research design and was conducted in the elementary schools of Dangcagan District, Division of Bukidnon, SY 2023-2024. The respondents were all public school teachers. Complete Enumeration was used as a sampling procedure. A researcher-made survey questionnaire was used to gather data. The data were analyzed using descriptive statistics such as frequency count, percentage, mean, standard deviation, t-test of significant difference, and Pearson r Product Moment Correlation Coefficient.
The research yielded the following findings: There was a Large Extent of challenge sexperienced by teachers in teaching reading. The interventions implemented to address the challenges experienced by teachers in teaching reading after the COVID-19 lockdown were rated as Effective. Most of the learners' level of oral reading skills in Dangcagan District, Division of Bukidnon, SY 2023-2024 were Instructional Readers.
Four factors, including student assistance, technology utilization, diverse reading resources, and parental partnerships, exhibit a highly significant positive correlation with students' reading proficiency at a high level of statistical significance. These findings indicate that these interventions have a beneficial effect on pupils' reading proficiency.
In light of the findings and conclusions, the following recommendations are offered: Teachers need specific treatments and instructional techniques to assist these learners in enhancing their oral reading abilities. Teachers may prioritize assisting children, conducting lessons in small groups or individually, utilizing technology, providing reading materials, and enhancing collaborations with parents or guardians.
Teachers should concentrate on implementing specific tactics to assist these students. School heads may commit resources towards student support programs, facilitate the efficient utilization of technology in reading instruction, provide access to a wide range of reading materials, and foster active participation of parents in promoting their children's reading development.

This study examined the impact of computerized media on students’ English language learning in public secondary schools in Mbeya City, Tanzania. The study adopted a quantitative approach and descriptive research design to examine the perceived impact of computerized media on students’ English language learning. The study employed purposive sampling to select Form Three students and four public secondary schools that utilized computerized media. A sample of 242 out of 612 Form Three students was selected from four public secondary schools using the Yamane formula, whereby simple random sampling was used to select the number of students from each selected school. Grounded in Mayer’s Cognitive Theory of Multimedia Learning, data were collected through a semi-structured questionnaire and analyzed using descriptive statistics, particularly frequencies and percentages. Findings revealed that computerized media had a significant positive impact on students’ English language learning by enhancing their language skills and lesson engagement. However, significant challenges constrained effective utilization of computerized media, including poor internet connectivity, unreliable electricity, limited digital skills, authority restrictions and limited access to devices. The study concludes that computerized media significantly improves English language learning; however, their educational potential depends on reliable digital infrastructure, adequate devices and students’ digital competencies.

The present research focuses on the formulation and evaluation of nanocrystals of Losartan Potassium to enhance its solubility and bioavailability, utilizing the antisolvent precipitation technique. Losartan Potassium, an antihypertensive agent, belongs to Biopharmaceutical Classification System (BCS) Class II drugs, characterized by low aqueous solubility and high permeability. To overcome its solubility limitations, nanocrystals were prepared using a bottom-up antisolvent precipitation method, employing stabilizers to prevent agglomeration and promote uniform particle size. The prepared nanocrystals were characterized by particle size analysis, zeta potential, scanning electron microscopy (SEM), differential scanning calorimetry (DSC), and X-ray diffraction (XRD) to assess their physical and chemical properties. In vitro solubility and dissolution studies demonstrated a significant improvement in the solubility and dissolution rate of the nanocrystals compared to the pure drug. The results indicate that the antisolvent precipitation technique is an effective and scalable approach for enhancing the solubility of poorly water-soluble drugs like Losartan Potassium.

This study examined Monetary Incentive and the performance of selected small and medium scale enterprise, Abuja Nigeria. Specifically, the study examined the effect of Wages and Bonus on performance of selected small and medium scale enterprise in Abuja Nigeria. A survey research design was adopted for the study. The research focused on employees of selected small and medium scale enterprise, Abuja Nigeria, with a total population of 653 employees. The sample size of 251 respondents was determined using Taro Yamane’s formula. The study relied on primary data, with a structured questionnaire serving as the instrument for data collection. Regression was employed to test the formulated hypotheses, using the Statistical Package for the Social Sciences (SPSS, version 25). The study found that Wages and Bonus, all statistically had significant positive effects on the performance of selected small and medium scale enterprise, Abuja, Nigeria. The study concluded that, competitive and well-structured compensation serves as a key motivator, employee commitment, productivity, and overall performance of selected small and medium scale enterprise, Abuja. Based on these findings, it was recommended that the management of selected small and medium scale enterprise Abuja, Nigeria should ensure that wages and bonus are aligned with organisational standards to improved overall performance.

Large language models (LLMs) are increasingly used in educational applications for tutoring, question generation, formative feedback, summarization, programming assistance, and learning support. However, model performance is strongly influenced by how tasks are specified through prompts. This paper presents a comparative framework for evaluating prompt engineering techniques in educational scenarios. Five prompting strategies—zero-shot, few-shot, structured role-and-constraint prompting, reasoning-oriented prompting, and retrieval-augmented/context-grounded prompting—are compared using a common evaluation protocol. The framework evaluates response correctness, relevance, pedagogical alignment, groundedness, hallucination tendency, consistency, and prompt efficiency. Rather than claiming universal superiority of one technique, the study analyzes task-dependent trade-offs and proposes a reproducible evaluation matrix for educational LLM systems. Recent literature indicates that simple prompting remains useful for low-complexity tasks, demonstrations and structured prompts can improve task alignment, reasoning-oriented prompting can support complex problem solving, and retrieval-grounded approaches can improve grounding when authoritative course material is available. The paper concludes with recommendations for selecting prompting strategies according to educational task characteristics and identifies directions for automated prompt optimization and human-centered evaluation.

The investigation was based on using rice husk ash as filler(reinforcement) with 0%, 5%, 10%, 15%, 20% and 25% by weight of the LDPE binder with average melting point of 1100C (sachet water nylon). RHA was obtained by burning the Rice husk at 6000C for 2 hours and later grinded after cooling and sieved using 300micron sieve to obtained a very finer material. A mix ratio of 1:4 was adopted in producing the pavement block. The laboratory tests conducted for both the materials and pavement blocks include specific gravity, particle size distribution (sieve analysis), chemical composition of RHA, temperature resistivity test, water absorption and chemical resistivity test. The specific gravity of the fine aggregate and RHA was 2.64 and 2.17 respectively, with the fine aggregate classified under zone II. The sieve analysis confirmed the fine aggregate as well graded and suitable for manufacturing. Key findings include a significant improvement in compressive strength with optimal RHA dossage at 15%, leading to an enhancement of up to 33% compared to conventional blocks. Also, the Temperature resistance analysis indicated that blocks with 15% RHA retained higher compressive strength than controls after 1 and 2 hours at 50°C, though extended exposure led to strength reductions or even collapse. The highest notable water absorption was 4.18% at control, decreases as the content of RHA was increases. The study further revealed that RHA enhances chemical Resistance, with blocks showing increased in compressive strength when exposed to hydrochloric acid and sodium hydroxide, improving by (18N/mm2 and 19N/mm2) 20% and 31.6% respectively compared to controls. These findings underscore the potential of RHA as a sustainable additive in pavement block manufacturing, enhancing durability under various environmental conditions.

Market failures occur when goods and services alocated through market mechanisms results in inefficient outcomes that fail to maximize social welfare.These failures may arise from various sources,which includes externalities publicgoods,information asymmetry,monopoly power,and factor immobility.Market failure have disadvantages for economic development because they distort how resources are allocated,reduces production,deject investment,and enhance inequality.While competitive markets are generally expected to allocate resources efficiently,numerous studies point out that market imperfections often prevent economies from achieving best possible outcomes(Stiglitz,2000; Mankiw,2021).This article examines the impact of market failures on economic development by reviewing theoretical and empirical literature from different scholars. The article is based on welfare, economics, Public Goods Theory, Externality Theory information Asymmetry Theory,and Institutional Theory to explain how market imperfections affect growthand development. The article reveals that negative externalities, monopolistic practices,insufficient provision of public goods, and information asymmetry contribute extensively to inefficiencies in how goods are produced and sfects the level of the production and consumption. These, distortions avertinnovation level which leads to low level of ,productivity,andaggravate poverty and inequality, particularly in global south economies(Acemoglu& Robinson2012,Rodrik2018).This article concludes that there must be effective government intervention necessary to correct market failures and promote sustainable growth.Policiesintend at regulating monopolies, improving information transparency,strengthening institutions, and investing in public goods which should be an essential goal for achieving long-term economic development and social welfare.The article contributes to existing literature by integrating theoretical perspectives and pragmaticproof to provide a complete understanding of the relationship between market failures and economic development.

Fungal infections affecting the skin, hair, and nails are among the most prevalent infectious diseases worldwide and continue to increase due to immunosuppression, antimicrobial resistance, and environmental factors. Conventional antifungal therapies often suffer from toxicity, resistance, and limited efficacy. Therefore, the development of novel antimicrobial systems is essential. Silver nanoparticles (AgNPs) have emerged as potent antimicrobial agents because of their broad-spectrum activity, multi-target mechanisms, and low incidence of microbial resistance. The present study aimed to synthesize silver nanoparticles using Aconitum ferox root extract through a green synthesis approach and formulate them into a topical gel for antifungal application. Root extracts were prepared using hydroalcoholic extraction after defatting with petroleum ether. Phytochemical screening confirmed the presence of alkaloids, flavonoids, tannins, phenols, saponins, proteins, carbohydrates, glycosides, and diterpenes. Total flavonoid and phenolic contents were estimated using aluminium chloride and Folin-Ciocalteu methods, respectively. AgNPs were biosynthesized using varying concentrations of silver nitrate and characterized by UV-Visible spectroscopy, FTIR, particle size analysis, zeta potential, and entrapment efficiency studies. The nanoparticle-loaded gel was prepared using Carbopol 940 and evaluated for physicochemical properties including pH, spreadability, viscosity, extrudability, drug content, and in vitro drug release. Antifungal activity was assessed by the well diffusion method using potato dextrose agar medium. The formulated AgNP gel demonstrated promising antifungal activity, suggesting that Aconitum ferox-mediated silver nanoparticles may serve as an effective topical antifungal delivery system.

Background: Immunomodulation maintains immune homeostasis by regulating innate and adaptive responses; dysregulation of immunomodulation contributes to autoimmune and inflammatory diseases. Homoeopathic medicines may influence cytokines, immune cells, inflammation and gene expression.
Objective: To review the evidence on immunomodulatory effects of homoeopathic medicines from experimental, preclinical and clinical studies.
Methods: We conducted a PRISMA 2020-based review of peer-reviewed in vitro, animal and clinical studies that assessed outcomes including cytokines, immune cells, inflammatory markers, antibodies and gene expression.
Results: Evidence suggests possible regulation of cytokines, restoration of Th1/Th2 balance, activation of immune cells and reduction of inflammation and oxidative stress. Animal and in vitro studies showed increased immunity and alterations in inflammatory mediators. Clinical data demonstrated symptomatic and biomarker improvement.
Conclusion: Experimental findings suggest immunomodulatory potential, but robust clinical trials are needed.

Maize production plays a critical role in ensuring food security, economic growth, and agricultural sustainability in developing countries, where maize is a major staple crop. Yet maize yield prediction remains difficult because of the complex interactions among soil characteristics, rainfall, temperature, and other climatic and management variables. This study develops and compares five supervised machine learning models, Linear Regression, Support Vector Regression (SVR), Random Forest Regression, Artificial Neural Network (ANN), and Extreme Gradient Boosting (XGBoost), for predicting maize yield from soil nutrient composition and weather data collected from farms in Owo, Ondo State, Nigeria, between 2020 and 2025. Model inputs included soil nitrogen, phosphorus, potassium, pH and organic carbon, alongside rainfall, temperature and relative humidity; data were cleaned, Min-Max normalised, and split 80:20 into training and test sets. Model performance was evaluated using Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and the coefficient of determination (R²). Linear Regression achieved an R² of 0.72; SVR, 0.83; Random Forest, 0.88; ANN, 0.93; and XGBoost, the best-performing model, an R² of 0.95 with the lowest error values (MAE = 0.19, RMSE = 0.29). Feature-importance analysis identified rainfall (28%) and nitrogen (25%) as the strongest predictors, followed by temperature, phosphorus, potassium and humidity. These results confirm that ensemble and deep-learning approaches outperform conventional statistical methods for maize yield forecasting and that soil fertility and rainfall jointly determine productivity. The study recommends integrating the model into a farmer-facing decision-support tool and expanding data collection to strengthen future predictions.

English communication competence is an essential component of graduate employability, particularly in engineering education, where technical knowledge must be communicated effectively in academic and professional contexts. Rural engineering students may face challenges due to limited exposure to English-speaking environments, fewer opportunities for practice, and lack of confidence. This study examines the communication competence of rural engineering students and explores its relationship with employability. It focuses on speaking, listening, reading, writing, pronunciation, vocabulary, presentations, group discussions, interviews, and professional writing. The study adopts a mixed-methods approach using a structured questionnaire, classroom observations, and interviews with English faculty. It also investigates barriers such as communication anxiety, vocabulary limitations, mother-tongue influence, and inadequate opportunities for authentic interaction. The study proposes an employability-oriented framework integrating needs analysis, language practice, workplace tasks, feedback, and reflective assessment to strengthen students’ communication competence and improve their readiness for professional employment.

This study investigated how combining educational technology (EdTech) with traditional laboratory equipment affects STEM competency among secondary school students in Nigeria. Conducted over 12 weeks, it involved 227 senior secondary students (112 control; 115 experimental) from six government schools in Maiduguri, Borno State, using a quasi-experimental design with Structural Equation Modelling (SEM). The experimental group used virtual laboratory simulations, digital microscopes, augmented reality modules, smart sensors, and data-logging devices alongside conventional science equipment. Structural relationships among EdTech integration, laboratory usage, student engagement, science learning outcomes, and STEM competency were examined across six hypotheses. Results showed excellent model fit (CFI = 0.963; RMSEA = 0.048). EdTech integration strongly predicted student engagement (β = 0.71) and science learning outcomes (β = 0.43), while laboratory equipment usage predicted learning outcomes (β = 0.64) and engagement (β = 0.38). Both mediators significantly predicted STEM competency. Experimental group post-test scores Biology (78.6%), Chemistry (76.2%), and Physics (80.1%), notably exceeded control group scores.

Secondary education is a developmental stage of education that shapes the perception and knowledge of children all over the world including Nigeria, and the management of safety and health in schools is essential for creating safe and healthy learning environments for learners and staff. The aim of this research was to assess the health and safety practices in selected secondary schools in Akwa Ibom State, Nigeria. The study used a cross-sectional survey design. Purposive sampling was used in the selection of schools based on their field of study (science and technology), location (urban), size (large), and type (public and private). The respondents used were science and technology teachers and students, and they were selected through simple random sampling. Copies of safety awareness questionnaires were used to collect data which were analyzed using descriptive statistical techniques which included frequencies and percentages presented in tables. Overall, the study indicated a reasonable positive level of awareness among students and teachers regarding health and safety hazards in school. Revealed significant gaps in safety practices within schools, found an overwhelming consensus among students and teachers regarding the importance of health and safety in schools, and identified the numerous benefits of implementing effective safety practices in schools. The data interpretation showed that there is a significant positive correlation between the level of awareness among the teachers and students about the health and safety hazards and the implementation of effective safety practices within schools. It was recommended that there is a need to prioritize safety as a core value, providing comprehensive training to all staff and students. Encouraging a safety culture, involving students in decision-making, and conducting regular safety audits are essential to identifying and addressing potential hazards. Developing and implementing comprehensive emergency response plans, particularly for students with special needs, is also crucial. Policymakers to allocate enough funding to support safety programs, create clear guidelines and regulations, and encourage collaboration between stakeholders.

This paper presents the development of a robust H∞ Power System Stabilizer (PSS) using a Linear Matrix Inequality (LMI) approach to enhance the dynamic stability of the Nigerian 330 kV transmission network. A detailed 54-bus, 13-generator multi-machine model was developed using real network data and linearised around its operating point obtained through Newton–Raphson load flow analysis. The H∞ control problem was formulated using a mixed-sensitivity framework and solved as an LMI optimisation problem to obtain a centralised dynamic output-feedback controller. The controller was evaluated under small-signal disturbances using time-domain and frequency-domain analyses. Simulation results demonstrated significant improvements in system damping, voltage regulation, and oscillation suppression. The minimum damping ratio was substantially increased, rotor speed deviations were reduced from ±0.05 p.u. to below ±0.02 p.u., and settling times were improved to approximately 3 to 5 seconds. Furthermore, voltage violations observed in the uncompensated network were effectively mitigated, with most bus voltages maintained within acceptable operating limits. The results confirm that the LMI-based H∞ PSS provides superior robustness and stability enhancement compared with conventional stabiliser approaches, making it a viable solution for improving the reliability and operational security of the Nigerian interconnected power system.

Ethnomedicinal plants are medicinal plants used by the indigenous communities, tribes or local inhabitants for therapeutic purposes. They’re part of traditional medicine passed down through generations, relaying on traditional knowledge and cultural practices rather than scientific methods.Jaundice is a prevalent symptom of liver dysfunction. It is one of the medical conditions related to liver dysfunction, hemolytic disorders, and biliary obstruction, where the skin and eyes turn yellow due to elevated levels of bilirubin in the blood.Ethnomedicinal plants have been being used for centuries to manage jaundice, offering a promising alternative or adjunct therapy even as conventional treatments are available. Traditional formulations typically combine multiple plant species or specific plant parts, enhancing efficacy and reducing bilirubin levels. From the bitter root of “Picrorhizakurroa” to the anti-oxidant rich leaves of “Phyllanthus amarus”, these plants have been being used for centuries to soothe the liver.Notable species with reported therapeutic efficacy are Tinospora Cordifolia, Phyllanthus niruri, Emblica officinalis, Terminalia chebula, Ricinus communis, Boerhaviadiffusa, and Justicaadhatoda. Traditional preparations involved decoctions, leaf juices, powders, and combinations with ghee, honey, or milk, administered orally or topically for periods ranging from 5 to 14 days. A comprehensive analysis of existing literature reveals a diverse array of plants with hepatoprotective, antioxidant and anti-inflammatory properties, masking them significant in traditional system like Ayurveda, which may contribute their therapeutic efficacy. Ethnomedicinal plants can facilitate the development of cost-effective, accessible, and culturally acceptable therapeutic agents for treating jaundice. This review highlights the enduring relevance and therapeutic promise of ethnomedicinal plants in managing jaundice and liver disorders. It explores plants traditionally used to treat jaundice, covering the plant organs used, methods of preparation, ethnomedicinal uses, and their bioactive compounds.

Successful adoption of electronic health records (EHRs) depends on more than technical installation; it depends on the beliefs, attitudes, and organizational conditions of the clinical workforce expected to use the system. This study assessed the perception and attitude of health workers toward EHR adoption at State Specialist Hospital, Lisaluwa, Ondo, Ondo State, Nigeria, examining perception, attitude, facilitating conditions, perceived barriers, and behavioral intention together, and their inter-relationships, among the hospital's clinical workforce.
An institution-based descriptive cross-sectional design with an analytical component was employed. Of 420 questionnaires distributed to clinical health workers across seven cadres, using Cochran's formula for sample-size determination, 357 were returned complete and analysed, a response rate of 85.0%. The structured, validated instrument (Cronbach's alpha 0.869–0.950 across scales) measured perception (15 items), attitude (10 items), facilitating conditions (8 items), perceived barriers (10 items), and behavioral intention (5 items). Data were analysed descriptively and inferentially in SPSS, including Pearson correlation, multiple linear regression with heteroscedasticity-consistent (HC3) standard errors, a Yates-corrected chi-square test, and Welch's one-way ANOVA.
Positive perception was recorded among 236 respondents (66.1%), 231 (64.7%) had a favourable attitude, and 221 (61.9%) had high behavioral intention. Mean scores were 3.77 (SD = 0.74) for perception, 3.72 (SD = 0.78) for attitude, 3.43 (SD = 0.79) for facilitating conditions, 3.36 (SD = 0.81) for perceived barriers, and 3.68 (SD = 0.81) for behavioral intention. Behavioral intention correlated positively with perception (r = .513), attitude (r = .583), and facilitating conditions (r = .329), and negatively with perceived barriers (r = −.425; all p < .001). The regression model explained 54.0% of the variance in intention (F(7,349) = 58.62, p < .001; adjusted R² = .531). Attitude (β = .369), computer proficiency (β = .295), perceived barriers (β = −.201), and facilitating conditions (β = .150) remained independently significant predictors, whereas perception, formal computer training, and prior EHR use did not remain significant after adjustment. Formal computer training was associated with high intention at the bivariate level (OR = 2.12, 95% CI [1.37, 3.28]).
The results indicate broad, conditional support for EHR adoption at the study hospital, but willingness is closely tied to digital competence and credible organizational support rather than to general approval alone. The hospital should prioritize competency-based training, workflow preparation, reliable connectivity, clear operating policies, and phased implementation with sustained technical support to translate this favourable disposition into effective, routine use.

This paper examines the manifestation and dynamics of case conflict in Ngũgĩ wa Thiong’o’s Devil on the Cross (1980) and Festus Iyayi’s Violence (1979), with a focus on economic inequality, gender oppression, ideological manipulation, and the development of resistance and consciousness. Employing a qualitative, comparative literary analysis, the paper integrates textual evidence from both novels under thematic categories: economic and class conflict, gender conflict, ideological conflict, and resistance and consciousness, and leans on Marxist and postcolonial theoretical frameworks to interpret the social, political, and psychological dimensions of conflict. The analysis reveals that economic disparity and structural inequality serve as primary sources of tension, while patriarchal and ideological systems reinforce oppression and obscure the mechanisms of exploitation. Again, both writers’ narrative strategies - Ngũgĩ utilizes satire and allegory, and Iyayi employs social realism – vividly expose systemic injustice, and the lived experiences of the oppressed. The paper argues that Ngugi and Iyayi, through their major characters, Wariinga in Devil on the Cross and Idemudia and Adisa in Violence, demonstrate that conflict catalyzes awareness, ethical reflection, and forms of resistance, whether overt or subtle. This paper concludes that literature not only reflects societal inequities but also serves as a medium for critical reflection and socio-political engagement, and that class, gender and ideology are the wheel upon which case conflict spins in African literature .The paper recommends among others, that the case conflict in African Literature should be approached from a comparative and interdisciplinary perspective to uncover how historical, political, cultural, economic and religious underpinnings engender Class, gender and ideological conflicts.

Event-streaming platforms such as Apache Kafka guarantee ordering only within a single partition, yet production pipelines routinely fan events out across many partitions, where causal relationships between events are silently lost. Logical clocks restore causal reasoning, but their relative cost and correctness under realistic streaming conditions have not been quantified. This paper presents causality-bench, a benchmark harness that empirically compares Lamport clocks, vector clocks, and hybrid logical clocks (HLC), together with a Kafka-offset baseline, across five research questions: header overhead, CPU cost, skew-induced mis-ordering, stream-join correctness, and causal-graph replay fidelity. Every experiment runs on two transports, an in-process simulator and a real single-node Kafka (KRaft) broker, allowing transport effects to be isolated. Vector clocks are the only mechanism that maintains 0% mis-ordering at every skew level and achieves recall = precision = 1.000 in causal replay at every partition count, at a header cost that grows linearly with node count. The central empirical finding is that HLC's safe operating window relative to Lamport clocks is transport-dependent: HLC mis-orders fewer event pairs than Lamport only below approximately 375 ms of injected clock skew in-process, but only below approximately 60 ms over a real broker, a roughly six-fold narrowing caused by real delivery jitter. These results provide practitioners with measured decision thresholds for selecting a causality mechanism in partitioned streaming systems.

The increasing use of digital transformation has raised expectations for better organizational competitiveness and performance among companies listed on the Nairobi Securities Exchange (NSE).However, many companies listed on the exchange continue to face issues such as falling profitability, low returns on assets and equity, inefficient operations, and limited growth. These problems were linked to increasing operating costs, fluctuating exchange rates, high interest rates, and stronger competition. In response, many firms invested substantially in digital transformation initiatives to enhance competitiveness. Nevertheless, the varying performance outcomes among firms undertaking similar digital transformation initiatives still remains a major concern for the firms. This study sought to investigate the effect of digital transformation on firm the operational performance of firms listed in the NSE. The study was anchored on Dynamic Capabilities Theory and used a positivist research approach with a correlational design.The focus was on NSE-listed firms, with top management executives serving as key sources of information.Data was gathered using structured electronic questionnaires sent to a systematically selected sample of executives from listed firms. The results showed that digital transformation had a positive and statistically significant effect on firm performance (β = 0.572, p < 0.001), explaining 32.7% of the variation in firm performance (R² = 0.327).Among its components, Digital Technology Adoption (β = 0.297, p < 0.001) and Digital Culture (β = 0.254, p = 0.002) significantly improved firm performance, while Digital Process Integration (β = 0.103, p = 0.209) had a positive but statistically insignificant effect, indicating that technology adoption and a supportive digital culture contribute more directly to better organizational performance than process integration alone. The study recommends that management of companies listed on the Nairobi Securities Exchange should strengthen investments in comprehensive digital transformation initiatives by prioritizing the adoption of modern digital technologies while simultaneously fostering a digital organizational culture that encourages innovation, continuous learning, employee empowerment, and effective digital leadership.

Genetic algorithm-finite element streamflow-based optimization model application was developed and applied for the Upper Ebonyi Watershed. To assess the performance capability of the model, hydrograph of the simulated and the optimized for the downstream phase of the watershed were compared with measured hydrograph, and statistically analyzed using three efficiency criteria: coefficient of determination , Nash Sutcliffe efficiency coefficient , and index of agreement The comparison of the simulated hydrograph with the measured gave efficiency criteria values of and respectively for coefficient of determination , Nash-Sutcliffe efficiency and Index of agreement , while the optimized hydrograph with measured hydrograph gave efficiency values of and respectively, showing an improvement of and respectively with optimization techniques. The simulated and optimized hydrographs were similar, with efficiency values of and respectively for , and . From the efficiency criteria results obtained, the incorporation of an optimization capability improved the model prediction, and the model is relatively satisfactory considering the fact that no model can be said to be absolutely perfect as there often uncertainties (errors) still inherent in such a model.

Introduction: Problematic social media scrolling is an emerging public health concern among adolescents and young adults. Although it is not yet recognized as a formal diagnostic category by the DSM-5-TR or the ICD-11, this behavior is increasingly studied through the lens of behavioral addiction models. This study aimed to describe scrolling habits in adolescents and young adults and to examine their psychological correlates and their association with sleep and life satisfaction.
Methods: This descriptive and analytical, quantitative study included 110 participants aged 15 to 22 years, recruited online through social media platforms. Data were collected using the Bergen Social Media Addiction Scale (BSMAS), the Fear of Missing Out Scale (FoMO), the Insomnia Severity Index (ISI), the Satisfaction With Life Scale (SWLS), and study-specific self-control and post-scrolling satisfaction scales. Pearson correlation coefficients were used to examine associations among variables, with significance set at P < 0.05.
Results: The mean BSMAS score was 19.7 (SD 4.8), close to the commonly used cut-off of 19 for problematic use. Ninety percent of participants reported at least mild insomnia, and a majority reported low to average life satisfaction. FoMO, BSMAS, and self-control scores all decreased with age. Significant correlations were found between BSMAS scores, FoMO, self-control, sleep difficulties, and life satisfaction (all P < 0.05). An at-risk profile emerged, characterized by younger age (15-17 years), high FoMO, low self-control, use of more than three platforms, and scrolling distributed throughout the day.
Conclusions: Problematic scrolling among adolescents and young adults is closely associated with fear of missing out, poor self-control, sleep disturbance, and reduced life satisfaction, consistent with mechanisms described in behavioral addiction frameworks, particularly the developmental mismatch between reward sensitivity and prefrontal control. These findings support targeted screening of younger adolescents and routine clinical assessment of scrolling habits when sleep complaints or life dissatisfaction are reported.

This study examines the effect of firms' perception of government tax officials' corruption on their tax compliance perception in Nigeria, using trust in the tax authority, perceived fairness of the tax system, and tax morale as sequential mediating mechanisms. Anchored on fiscal exchange theory and the slippery slope framework, a structural model comprising five reflective constructs — Perceived Corruption of Tax Officials (PCTO), Trust in Tax Authority (TTA), Perceived Fairness of the Tax System (PFTS), Tax Morale (TM), and Tax Compliance Perception (TCP) — was estimated using Partial Least Squares Structural Equation Modelling (PLS-SEM) on data from 385 registered firms operating across Nigeria's six geopolitical zones. The measurement model demonstrated satisfactory convergent validity (average variance extracted ranging from 0.576 to 0.677) and internal consistency reliability (composite reliability ranging from 0.870 to 0.893), while the Fornell-Larcker criterion and heterotrait-monotrait ratio confirmed discriminant validity across constructs. The structural model results indicate that perceived corruption of tax officials significantly and negatively predicts both trust in the tax authority (β = -0.308, p < .001) and perceived fairness of the tax system (β = -0.264, p < .001), and exerts a direct negative effect on tax compliance perception (β = -0.175, p < .001). Trust and fairness both positively predict tax morale, which in turn is the strongest positive predictor of tax compliance perception (β = 0.366, p < .001). The model explains 34.9% of the variance in tax compliance perception. The findings extend the fiscal-exchange and slippery-slope literatures to a firm-level, corruption-salient developing-economy context and suggest that anti-corruption reform within revenue agencies is a precondition, rather than a substitute, for morale-based voluntary compliance strategies. Practical and policy implications for the Federal Inland Revenue Service, state internal revenue services, and firm-level tax administration reforms in North-East Nigeria are discussed.

Background: Tuberous sclerosis complex (TSC) is a multisystem genetic disorder characterized by hamartomatous lesions affecting multiple organs. Beyond its neurological manifestations, TSC is frequently associated with a broad spectrum of neuropsychiatric disorders, collectively referred to as TSC-associated neuropsychiatric disorders (TAND), including autism spectrum disorder (ASD), intellectual disability (ID), behavioural disturbances, and psychiatric comorbidities. These manifestations represent a major source of disability but remain under-recognized and often undertreated.
Case presentation: We report the case of a 13-year-old boy, the youngest of three siblings, born to non-consanguineous parents with no family history of TSC or neurodevelopmental disorders. Early psychomotor development was initially reassuring, with emergence of expressive language and reciprocal social interaction before two years of age. He subsequently developed recurrent seizures that never achieved sustained control despite several successive antiseizure-medication combinations, evolving into drug-resistant epilepsy (currently generalized tonic-clonic seizures). Developmental regression followed, with loss of language, impaired social communication, stereotyped behaviours, and marked intolerance to change. Brain magnetic resonance imaging (MRI) revealed multiple cortical tubers and subependymal nodules, and dermatological examination identified hypomelanotic macules, confetti skin lesions, and facial angiofibromas, fulfilling the 2021 International TSC clinical diagnostic criteria for definite TSC; molecular genetic testing was not performed. At three years of age, ASD (DSM-5, supported by ADI-R and ADOS) and severe ID (uniformly very low adaptive functioning on the Vineland Adaptive Behavior Scales) were diagnosed. Despite intensive multidisciplinary rehabilitation, clinical improvement remained minimal. During adolescence, the clinical picture became dominated by severe TAND: non-verbal ASD, persistent intellectual disability, repetitive head-banging requiring protective measures, and frequent heteroaggression. Management was particularly challenging because drug-resistant epilepsy limited pharmacological options, while serial follow-up MRI demonstrated progression of cerebral lesions, leading to evaluation for epilepsy surgery.
Conclusion: This case highlights the complex interplay between progressive TSC, early drug-resistant epilepsy, developmental regression, and severe neuropsychiatric comorbidities. It emphasizes that TAND may become the predominant source of long-term disability and underscores the need for early multidisciplinary assessment, systematic psychiatric evaluation, and individualized therapeutic strategies in children with TSC.

This paper examines the manifestation and dynamics of case conflict in Ngũgĩ wa Thiong’o’s Devil on the Cross (1980) and Festus Iyayi’s Violence (1979), with a focus on economic inequality, gender oppression, ideological manipulation, and the development of resistance and consciousness. Employing a qualitative, comparative literary analysis, the paper integrates textual evidence from both novels under thematic categories: economic and class conflict, gender conflict, ideological conflict, and resistance and consciousness, and leans on Marxist and postcolonial theoretical frameworks to interpret the social, political, and psychological dimensions of conflict. The analysis reveals that economic disparity and structural inequality serve as primary sources of tension, while patriarchal and ideological systems reinforce oppression and obscure the mechanisms of exploitation. Again, both writers’ narrative strategies - Ngũgĩ utilizes satire and allegory, and Iyayi employs social realism – vividly expose systemic injustice, and the lived experiences of the oppressed. The paper argues that Ngugi and Iyayi, through their major characters, Wariinga in Devil on the Cross and Idemudia and Adisa in Violence, demonstrate that conflict catalyzes awareness, ethical reflection, and forms of resistance, whether overt or subtle. This paper concludes that literature not only reflects societal inequities but also serves as a medium for critical reflection and socio-political engagement, and that class, gender and ideology are the wheel upon which case conflict spins in African literature .The paper recommends among others, that the case conflict in African Literature should be approached from a comparative and interdisciplinary perspective to uncover how historical, political, cultural, economic and religious underpinnings engender Class, gender and ideological conflicts.

The rapid expansion of digital technology has transformed the way individuals communicate, work, study, shop, access public services, and participate in social life. Alongside these developments, however, personal information has become one of the most valuable forms of digital currency. Every online search, financial transaction, social-media interaction, location update, and application may generate information about an individual. This development raises an important constitutional and legal question: how can the right to privacy be protected when personal information is continuously collected, processed, shared, and analysed?
In India, privacy has evolved from being viewed primarily as a matter of personal liberty into a constitutionally protected fundamental right. The recognition of privacy as an intrinsic part of life and personal liberty has created a constitutional foundation for protecting individuals against unjustified interference by both the State and private actors. At the same time, technological development has created new challenges that cannot always be addressed through traditional legal principles.
This article examines the changing nature of the right to privacy in India, its constitutional foundations, the challenges created by digital technology, the importance of data protection, and the need to balance individual privacy with legitimate State and commercial interests. It argues that privacy in the digital age should not be understood merely as the right to keep information secret. Rather, it should be understood as a right to dignity, autonomy, informed choice, and meaningful control over personal information.

The Goods and Services Tax (GST), introduced on 1 July 2017, transformed India's indirect-tax framework by replacing several Central and State levies and creating a technology-enabled compliance system. Although GST seeks to reduce cascading taxes, improve market integration, and strengthen transparency, its compliance architecture can impose disproportionate administrative and financial burdens on small businesses with limited accounting capacity, digital infrastructure, and working capital. This literature review examines statutory provisions, official guidance, and selected academic literature concerning registration, return filing, input tax credit (ITC), digital compliance, professional costs, regulatory change, and liquidity pressures. It also considers relief measures such as the Quarterly Return Monthly Payment (QRMP) scheme and GST Council recommendations. The review concludes that simplification must be assessed not only by filing frequency but also by the practical ability of small taxpayers to comply accurately and at reasonable cost.

Tinospora cordifolia, commonly known as guduchi or giloy, is an important medicinal plant belonging to the Menispermaceae family and is widely used in traditional Indian medicine, particularly in Ayurveda. The plant has attracted considerable scientific interest due to its diverse phytochemical constituents and extensive pharmacological potential. T. Various parts of Cordifolia, especially stems and roots, contain several bioactive compounds, including alkaloids, diterpenoid lactones, glycosides, steroids, sesquiterpenoids, phenolic compounds, polysaccharides and other secondary metabolites. These components are associated with various biological activities.
In the present review, T. The herbal characteristics, traditional uses, pharmacognostic properties, phytochemical constituents and pharmacological activities of cordifolia are summarized. Reported pharmacological properties include antidiabetic, antioxidant, anti-inflammatory, antimicrobial, immunomodulatory, hepatoprotective, anticancer, ulcer, antipruritic and neuroprotective activities.
Review t. It also highlights the importance of standardization, quality control, toxicity evaluation and well-designed clinical studies to establish the therapeutic efficacy and safety of cordifolia. Overall, T. Cordifolia represents a promising medicinal plant with significant potential for the development of standard herbal preparations and novel phytopharmaceutical products.

Artificial Intelligence (AI) is rapidly transforming modern society. It is increasingly used in healthcare, education, finance, employment, policing, public administration, communication and commercial activities. While Artificial Intelligence provides significant opportunities for economic and social development, its increasing use also raises serious questions concerning constitutional rights. Automated decision-making, algorithmic profiling, facial recognition, predictive policing and large-scale data processing may directly affect an individual’s equality, liberty, privacy and dignity.
The Constitution of India was enacted long before the emergence of modern Artificial Intelligence. However, its fundamental rights framework is sufficiently broad to address technological developments that affect constitutional values. Articles 14, 19 and 21 are particularly relevant to AI governance. Article 14 protects individuals against arbitrary and discriminatory State action; Article 19 protects important freedoms including freedom of speech and expression; and Article 21 has been judicially interpreted to protect dignity, autonomy and privacy.
This paper examines the constitutional implications of Artificial Intelligence in India with particular emphasis on privacy, equality and procedural fairness. It analyses the landmark decision in Justice K.S. Puttaswamy (Retd.) v. Union of India, in which the Supreme Court recognised privacy as a constitutionally protected right. The paper also considers India’s Digital Personal Data Protection Act, 2023 and the Digital Personal Data Protection Rules, 2025. It argues that data protection alone cannot address all AI-related constitutional concerns. Algorithmic transparency, accountability, human oversight, non-discrimination and effective remedies are equally important.
The paper concludes that India should adopt a rights-based approach to Artificial Intelligence in which innovation is encouraged but technological power remains subject to constitutional principles of dignity, equality, liberty, proportionality and rule of law.

This study assessed the level of employees’ awareness of labour dispute resolution procedures at Iringa Municipal Council. The study adopted a mixed-methods approach and a descriptive research design. The study targeted approximately 1,270 employees, from whom 100 respondents were selected using stratified random sampling, while key informants were selected purposively. Primary data were collected through structured questionnaires and semi-structured interviews, while secondary information was obtained from relevant Council records, labour-related documents, government publications and academic literature. The assessment of awareness focused on employees’ understanding of grievance procedures, knowledge of the steps involved in resolving labour disputes, awareness of appropriate reporting channels and understanding of employee rights under labour laws. Quantitative data were analysed using frequencies and percentages, while qualitative information was analysed thematically. The reliability of the research instrument was satisfactory, with a Cronbach’s Alpha coefficient of 0.941. The findings revealed that employees had a generally high level of awareness of labour dispute resolution procedures. Specifically, 93% of respondents agreed or strongly agreed that they understood grievance procedures, 93% indicated that they knew the steps involved in resolving labour disputes and 93% reported understanding their rights under labour laws. Awareness of the channels used to report labour disputes was comparatively lower, with 78% agreeing or strongly agreeing, while 15% disagreed and 7% remained neutral. The study concludes that employees at Iringa Municipal Council possess substantial awareness of labour dispute resolution procedures, although some gaps remain regarding formal reporting channels. The study recommends that the Council strengthen regular sensitisation and communication programmes, particularly for newly recruited employees, through staff meetings, orientation programmes, circulars and accessible labour-policy documents to improve employees’ understanding of where and how labour disputes should be reported.

Entrepreneurship is widely regarded as a central engine of job creation, innovation, and structural transformation in developing economies, and Nigeria is no exception. Yet the same economy that offers Africa's largest consumer market, a fast-digitising population, and an expanding services sector also confronts entrepreneurs with a demanding risk environment: currency instability, double-digit inflation, high borrowing costs, insecurity, multiple and overlapping taxation, unreliable power supply, and weak institutional support. This paper examines the relationship between entrepreneurial risk and business opportunity in Nigeria, drawing on recent empirical and policy literature (2023–2026) alongside macroeconomic and survey data from the Central Bank of Nigeria, the National Bureau of Statistics, and the Small and Medium Enterprises Development Agency of Nigeria. The paper classifies the principal categories of entrepreneurial risk confronting Nigerian businesses financial, operational, regulatory/policy, security, and market risk and matches these against emerging opportunity spaces in digital financial services, agribusiness, the creative and digital economy, renewable energy, and youth-driven micro enterprise. It argues, consistent with classical Knightian theory, that Nigeria's high-risk operating environment is also a source of above-average returns for entrepreneurs who can manage uncertainty through diversification, digital adoption, cooperative financing, and policy engagement. The paper concludes with recommendations for entrepreneurs, financial institutions, and policymakers aimed at converting risk exposure into sustainable opportunity capture.

Andrographis paniculata (Burm. f.) Wall. Ex Nees, commonly known as Kalmegha or the “King of Bitters”, is an important medicinal plant widely used in traditional systems of medicine such as Ayurveda, Siddha, and Traditional Chinese Medicine. The plant has been traditionally employed for the treatment of fever, liver disorders, infections, inflammation, and immune-related diseases. Modern pharmacological studies have validated many of these traditional claims and revealed a wide range of biological activities attributed mainly to diterpenoid lactones such as andrographolide. This review summarizes the ethnobotany, morphology, phytochemistry, and pharmacological properties of A. paniculata based on experimental and clinical evidence.

A school's safety, like a country's justice system, is only as strong as the weakest point in the chain between a rule being written and a rule being known. This paper compares the institutional safeguards that protect K-12 students from sexual harassment by staff and by peers across three very different legal traditions: the United States, where protection is enforced mainly through the threat of a lawsuit; the United Kingdom, where protection is enforced mainly through a standing duty and a named inspector's clipboard; and India, where protection is enforced mainly through the threat of criminal prosecution. Drawing on peer-reviewed secondary research, I argue that each system's safeguards are strongest exactly where its underlying legal logic applies the most pressure, and weakest everywhere else, and that in all three countries, the single most common point of failure is not the absence of a rule, but a child's inability to say what the rule is, who enforces it, or how to invoke it.

Artificial Intelligence (AI) is increasingly being used in criminal investigations through tools such as facial recognition, predictive systems, and digital forensic technologies. These tools can help investigators work faster and find evidence more efficiently. However, the use of AI-generated evidence in Indian criminal trials raises important questions about its reliability, authenticity, and admissibility. The Bharatiya Sakshya Adhiniyam, 2023 deals with electronic and digital evidence, but it does not clearly provide specific rules for AI-generated evidence. This paper examines major issues such as AI bias, lack of transparency, difficulty in checking the accuracy of AI results, and the risk of manipulation and deepfakes. It also discusses the possible impact of AI evidence on the right to a fair trial and the presumption of innocence. The paper suggests that India needs clearer legal rules and proper standards to ensure that AI-generated evidence is reliable, transparent, and fairly used in criminal trials.