Cloud computing has become key to modern digital infrastructure, yet traditional reactive auto-scaling systems struggle to balance performance requirements with cost efficiency. This study addresses the limitations of existing cloud resource management approaches by developing the Predictive and Cost-Optimized Auto-Scaling Framework (PCOAF), a conceptual model that integrates machine learning-based workload forecasting with multi- objective optimization. Through systematic application of Design Science Research Methodology, the research analyzed current auto-scaling systems, identified critical deficiencies including reactive latency, prediction inaccuracy, and cost inefficiency, and designed a three-layered architecture comprising monitoring, prediction and decision, and optimization and execution modules. The framework employs archetype-aware prediction to classify workloads into four behavioral patterns; SPIKE, PERIODIC, RAMP, and STATIONARY enabling tailored scaling strategies for each type. Theoretical validation demonstrates that PCOAF achieves 99.8% workload classification accuracy, reduces mean absolute percentage error to 15%, and projects cost reductions of 22% while decreasing service-level objective violations by 61.4% compared to baseline reactive systems. The study establishes PCOAF's feasibility across five design criteria: relevance, consistency, feasibility, scalability, and economic viability. By addressing identified gaps in both international research and Nigeria's emerging cloud ecosystem, this framework contributes a theoretically grounded and practically applicable solution for intelligent, cost-aware cloud resource management in resource-constrained environments.

Asthma is characterized by chronic inflammation of the lower respiratory tract, a state frequently seen alongside inflammatory disorders of the upper airway (Mims, 2015). The 1995 GINA guidelines classified a patient's off-treatment asthma status (intermittent to severe persistent) to guide initial therapy. However, modern guidelines have abandoned this severity-based classification in favor of a focus on achieving and maintaining disease control. Current clinical practice defines asthma severity by the level of pharmacological treatment required to keep the disease controlled; in the most difficult cases, severity is determined by the condition's refractoriness to therapy(Song et al., 2019). Asthma is typically suspected based on a patient's recurring symptoms and their positive response to a bronchodilator medication, which helps relax the airway muscles(Sockrider and Fussner, 2020). For individuals over the age of five, the diagnosis is usually confirmed with a breathing test called spirometry (a type of pulmonary function test or PFT), which detects airway narrowing or obstruction. However, a normal spirometry result does not rule out asthma(Sockrider and Fussner, 2020). First-line asthma medications include the short-acting β2-adrenergic agonist salbutamol for rapid relief of bronchoconstriction, the leukotriene receptor antagonist montelukast for its anti-inflammatory and bronchodilatory effects, and the corticosteroid prednisolone for potent anti-inflammatory action(Whirledge and Cidlowski, 2010), these drugs exert their effects through different mechanisms, including bronchodilation, anti inflammatory actions, and inhibition of leukotriene-mediated inflammation (Barnes, 2008). The induction of airway inflammation using Ovalbumin (OVA) in Sprague-Dawley rats serves as a widely recognized model for studying asthma (Kumar and Herbert, 2013). This model triggers a Th2-mediated inflammatory response, which subsequently elevates the production of reactive oxygen species (ROS), resulting in oxidative stress (Rahman andMacNee, 2000)

The rapid expansion of internet usage and digital commerce has significantly transformed business operations in Nigeria, creating new opportunities for economic growth and entrepreneurship. However, this increased reliance on digital technologies has also exposed online businesses to a wide range of cybersecurity threats, including phishing, malware, ransomware, and denial-of-service attacks. These threats pose serious risks to business continuity, financial stability, customer trust, and national economic development. This study investigates the impact of cybersecurity threats on online businesses in Nigeria, examining the nature, prevalence, and consequences of cyber-attacks on business operations. The study adopts a descriptive research approach and utilizes secondary data obtained from academic journals, industry reports, government publications, and cybersecurity studies. Findings reveal that cyber threats have become increasingly sophisticated, resulting in substantial financial losses, data breaches, reputational damage, and disruptions to online business activities. The study further identifies inadequate cybersecurity awareness, weak security infrastructure, and limited regulatory compliance as major factors contributing to the vulnerability of online businesses in Nigeria. The research concludes that effective cybersecurity strategies, including employee training, implementation of robust security frameworks, regular risk assessments, and stronger regulatory enforcement, are essential for mitigating cyber threats. The study contributes to the growing body of knowledge on cybersecurity in developing economies and provides practical recommendations for business owners, policymakers, and stakeholders seeking to enhance the security and resilience of Nigeria's digital business environment.

This study investigates the application of Exponential, Weibull, and Gamma distributions in modeling lifetime data. The primary objective is to compare these distributions in real world survival analysis and reliability modeling. The study utilizes secondary data from published research, including survival times of head and neck cancer patients and waiting times of bank customers .
Maximum Likelihood Estimation (MLE) was employed to estimate distribution parameters, and model comparisons were performed using Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) to determine the best fitting distribution.

Findings reveal that while the Exponential distribution provides a simple model for constant failure rates, the Weibull distribution offers greater flexibility in modeling varying failure rates. The Gamma distribution demonstrates robust applicability in complex survival data. Results indicate that the Weibull and Gamma distributions provide superior fits in most real world cases.
This study contributes to the field of survival analysis and reliability engineering by providing insights into selecting appropriate lifetime distributions for different applications. The findings have practical implications for fields such as healthcare, engineering, and risk assessment, where accurate lifetime modeling is crucial for decision making.

The digital revolution has fundamentally transformed the landscape of evidence in legal proceedings worldwide, with Nigeria taking a decisive step forward through the Evidence (Amendment) Act 2023. This research examines the evolving role of digital evidence in Nigerian courts, focusing on the critical issues of admissibility and credibility within the framework of the newly amended Evidence Act. The study addresses the transformative impact of sections 84A-84D, which revolutionized how electronic records, digital signatures, and computer-generated documents are treated in judicial proceedings. Prior to the 2023 amendments, Nigerian courts grappled with significant challenges in authenticating and admitting digital evidence under the restrictive provisions of Section 84 of the Evidence Act 2011. The landmark case of Atiku Abubakar v. Muhammadu Buhari exemplified these challenges, where the Supreme Court struggled with the admissibility of electronic voting records and server-generated data. This research investigates how the Evidence (Amendment) Act 2023 addresses these longstanding issues while establishing new standards for digital evidence credibility. The study employs doctrinal analysis, comparative jurisprudence, and empirical research methodologies to examine the practical implications of Nigeria's modernized digital evidence framework. Key findings reveal that while the 2023 amendments significantly enhance the admissibility of electronic records, challenges remain in ensuring credibility, particularly regarding authentication protocols and technical expertise requirements within the judiciary. This research contributes to legal scholarship by providing the first comprehensive analysis of Nigeria's reformed digital evidence regime, offering practical guidance for legal practitioners, and proposing recommendations for effective implementation of the new legislative framework

Fish farmers and fishermen have often complained of low profit margin due to the impact of fish marketing agents who often fix fish price without minding the cost of fish production It is therefore important to investigate the roles and impacts of marketig agents.This study examined the impact of fish marketing agents on fish prices in Benin City, Edo State, Nigeria. Four major markets namely New Benin, Uselu, Yanga, and Oka were purposively selected, and primary data were obtained from 101 respondents through the use of structured questionnaires and interviews. Descriptive statistics and Analysis of Variance (ANOVA) at a 5% significance level were employed to analyze the data. The results revealed that fish marketing in Benin City is dominated by women (59.4%), mostly between the ages of 26–35 years, with moderate educational attainment. Retailers (38.6%) and wholesalers (23.8%) constituted the major categories of marketing agents, with wholesalers (35.6%) identified as having the greatest influence on fish prices. The majority (64.4%) of respondents believed that marketing agents cause price increases and price fluctuations, mainly through transportation cost manipulation (35.6%) and hoarding (33.7%). The major challenges identified included unfair pricing (47.5%), low profit margins (22.8%), and limited access to capital (12.9%). Government intervention (52.5%) and regulation of market agents (45.5%) were the most suggested measures for achieving fair pricing. The study concludes that while marketing agents play a vital role in fish distribution, their activities often lead to price distortions that negatively affect both producers and consumers. It recommends strengthened institutional regulation, improved infrastructure, cooperative marketing, and capacity building to enhance transparency, efficiency, and fairness in fish marketing within Benin City.

Background: Medical students experience disproportionately high rates of psychological distress, including depression, anxiety, and burnout, yet mental health service utilization remains strikingly low. At the University of Benin, despite the availability of counselling and psychiatric services, little empirical data exists on students' awareness, accessibility perceptions, utilization patterns, and barriers to care. Objective: To examine the awareness, accessibility, utilization, and perceived barriers related to mental health services among medical students at the University of Benin. Methods: A descriptive cross-sectional study was conducted among 550 medical students selected through stratified random sampling from all six years of the MB;BS program. Data were collected using a structured, self-administered questionnaire assessing socio-demographic characteristics, awareness of mental health services, perceived accessibility, utilization patterns, and barriers to care. Descriptive statistics, chi-square tests, and binary logistic regression were employed for analysis, with statistical significance set at p < 0.05. Results: The mean age was 22.4 years (SD ± 3.1), with a slight female majority (52.2%). Good overall awareness of mental health services was observed in 59.3% of students, with 76.7% aware that University of Benin provides mental health services. However, practical knowledge gaps existed: only 55.8% knew service locations and 58.2% understood confidentiality provisions. Perceived accessibility was positive among 91.8% of students, though only 48.5% found operating hours convenient. Actual utilization was extremely low (12.9%), with peer support groups (45.1%) and helpline/online support (45.1%) being the most used services. Academic pressure (11.3%) and depression (7.0%) were the commonest reasons for seeking ~ xvi ~ Commented [NM1]: Awareness of what? help. Barriers were widely endorsed: confidentiality fears (79.1%), fear of judgment (78.7%), perceived ineffectiveness of services (77.4%), and lack of time (76.3%). Significant predictors of good accessibility and awareness included: male sex (aOR = 0.51, 95% CI: 0.27–0.98, p = 0.042) for lower odds of good accessibility, and monthly allowance below ₦60,000 (aOR = 0.69, 95% CI: 0.48–0.98, p = 0.037) for lower odds of good awareness. Conclusion: Despite goodawareness and favorable accessibility perceptions, mental health service utilization among medical students at the University of Benin is critically low, driven by intersecting stigma-related, practical, and cultural barriers. Urgent institutional interventions are required to address confidentiality concerns, time constraints, and socio-demographic inequities to bridge the treatment gap. Keywords: Mental health services, medical students, awareness, accessibility, utilization, barriers, University of Benin, Nigeria.

This research studied the interplay between racism, intra-Black discriminations and the language used in Sefi Atta’s The Bad Immigrant (2021) to show social inequality and power relations. The research employed Norman Fairclough’s social-critical approach to discourse analysis, and explored how words and communication in the novel fueled racism, classism, and discrimination among Nigerian immigrants in the United States. Drawing insight from critics such as Frantz Fanon, Isabella Fairclough, Norman Fairclough and Friday Darboe, the study situated this work among broader social-political debates about anti-Black racism and intra-racial discrimination in the diaspora. Findings in the study revealed that language helped to build and maintain social hierarchies. The speech and actions used in the novel reflect how immigrants adapt and respond to prejudice. It showed how characters in the novel face racism and also how they sometimes repeat the same prejudiced behaviors toward others. The research also revealed that African immigrants are not just victims but can also actively reproduce systems of prejudice while trying to survive and succeed in a society shaped by inequality. Overall, this study concluded that language plays a powerful role in shaping identity and social position. It adds to the discussion on intra-Black conflict by showing that discrimination happens both from outside and within minority groups

Urban markets in Benin City function as vital economic spaces and cultural landmarks that reflect community identity, traditional practices and social interaction. Recent modernization efforts across Nigerian cities have focused heavily on physical redevelopment, often neglecting the cultural significance and spatial dynamics that shape these markets. This study examines the relationship between urban market revitalization and cultural sustainability in selected markets in Benin City—Oba Market, Uselu Market, Ekosodin Market, Orgie-Ode Market. Using a mixed methods approach, data were collected from 100 respondents through questionnaires, interviews, field observations and photographs. Findings indicate major infrastructural and organizational challenges, including inadequate drainage, sanitation, security and spatial planning, which affect market efficiency and user experience. Despite these issues, traders and users maintain strong cultural attachment to the markets, underscoring their historical and symbolic importance. The study concludes that revitalization strategies must integrate cultural preservation with infrastructural improvement to ensure sustainable and socially inclusive market renewal. Recommendations emphasize participatory planning, heritage-sensitive design and improved governance frameworks.

This study examines the awareness and perception of librarians toward the adoption of artificial intelligence (AI) in academic libraries, with a specific focus on John Harris Library at the University of Benin. The research aims to assess the extent and variety of AI technologies utilized, best practices for AI integration, and practical ways to enhance information delivery through AI adoption. Using a survey research design, data were collected from 80 respondents through structured questionnaires and analyzed using frequency counts and simple percentages. The findings reveal that while AI adoption in John Harris Library is still at a developing stage, there is a growing awareness among librarians regarding its potential to enhance library services. However, challenges such as inadequate funding, insufficient technological infrastructure, and limited staff training hinder effective implementation. The study also highlights the need for a structured approach to AI integration, emphasizing user-centered strategies, staff capacity development, and improved technological investments. Based on these findings, the study recommends increased financial support for AI initiatives, enhanced technological infrastructure, continuous staff training, and regular policy updates to align with evolving user needs. Addressing these challenges through strategic funding and systematic policy evaluation will ensure that academic libraries effectively integrate AI, improving resource accessibility and enhancing user satisfaction.