2026

The exponential distribution became the cornerstone of survival analysis and reliability engineering throughout the latter half of the 20th century and it is imperative to mention that the Successive times in exponential distribution are assumed to occur independently and randomly over time with a constant rate. The aim of the study was to develop a generalized and flexible bivariate exponential distribution that will incorporate correlation parameter 𝜌, extending the domain to a positive real-line using the framework of linear regression. A secondary dataset from Federal Road Safety Corps on road accidents in Imo State from 2020 to
2024 was used in the study and it was obtained from the Head office of Federal Road Safety Corps, off Egbu road Owerri, Imo state. In the study, we developed a generalized and bivariate exponential model that incorporates a correlation parameter, while preserving analytical simplicity. The proposed model, referred to as the New Correlated Bivariate Exponential Distribution (NCBED). The consistency of the NCBED was assessed using Kolmogorov Smirnov and Cramer Von Mises tests, in comparison with the baseline Grine model (2018). The Federal Road Safety (FRSC) dataset demonstrates that both injury and fatality data follow heavy-tailed exponential-type distributions and the NCBED provided a superior fit compared to the baseline model, capturing real-world correlations between crash outcomes. The findings indicate that the Maximum Likelihood estimates of the proposed model are consistent with the nature of the model.

Background: Artificial intelligence (AI) offers potential to enhance community health surveillance through early outbreak detection and improved reporting. However, adoption in low-resource primary healthcare settings remains poorly understood. This study assessed the knowledge, attitudes, uptake, utilisation, and factors influencing AI use in disease surveillance among health workers in selected Primary Health Centres (PHCs) in Benin City, Edo State, Nigeria. Methods: An analytical cross-sectional study was conducted among 230 health workers selected by stratified multistage sampling from 23 PHCs in Oredo and Egor Local Government Areas. Data were collected using a structured, self-administered questionnaire adapted from the Technology Acceptance Model and standard KAP frameworks. Knowledge,attitude, uptake, utilisation, and influencing factors were assessed using descriptive and inferential statistics (chi- square, Fisher’s exact test, and logistic regression). Results: All respondents had heard of AI (100%); the internet was the primary source (99.1%). Good knowledge of AI in disease surveillance was found in 77.8% of respondents,while 65.2% had a positive attitude towards AI use. However, actual uptake was very low(7.4%). Among the few users (n=17), the most used tools were HealthMap (76.5%) and ChatGPT (52.9%), mainly for report writing (100%) and trend analysis (52.9%). Most users reported rare use (64.7%) and had discontinued use (76.5%) due to accuracy concerns, lack of institutional support, and technical issues. Factors significantly associated with uptake included age, marital status, occupation, and knowledge level (p<0.05). Major barriers to AI use were lack of funding (100%), absence of institutional training (100%), inadequate infrastructure (99.6%), unclear ethical guidelines (69.6%), and data privacy concerns (67.0%).Unclear ethical guidelines were the only independent predictor of AI uptake (OR=0.069,p<0.001).Conclusion: While knowledge and attitudes towards AI are reasonably favourable among PHC health workers in Benin City, actual uptake and sustained use remain very low. Systemic barriers especially lack of ethical guidelines, infrastructure, training, and funding must be addressed to translate awareness into practice. Recommendations: Federal and state health authorities should develop clear ethical and operational guidelines for AI in disease surveillance, integrate AI literacy into training curricula, invest in digital infrastructure, and implement phased, supervised AI tools starting with low-risk functions such as report generation and trend analysis

Background: Artificial Intelligence (AI) is transforming global healthcare by enhancing diagnostics and clinical workflows. However, in resource-constrained settings like Nigeria, the integration of AI remains uneven, often hindered by infrastructure deficits and limited training. While awareness of AI is growing, there is a significant gap between knowledge and actual clinical implementation among healthcare professionals. Aim: The study aimed to assess the uptake and level of utilisation of artificial intelligence in clinical support among healthcare professionals at the University of Benin Teaching Hospital (UBTH). Specifically, it determined the level of knowledge, attitudes, and factors influencing AI adoption within the institution. Methods: An analytical cross-sectional study design was employed, involving 409 healthcare professionals including doctors, nurses, pharmacists, medical laboratory scientists, and physiotherapists. Participants were selected using a multistage sampling technique. Data were collected through structured, pre-tested, self-administered questionnaires comprising sections on socio-demographic characteristics, level of knowledge, attitude, uptake and level of utilisation,and factors influencing AI use. Knowledge, uptake and level of utilisation scores were categorized based on a 70% cut-off, while attitud was assessed using a 5-point likely scale which was grouped into appropriate and inappropriate responses and scored using a cut-off of 70%. Data were analyzed using IBM SPSS version 27.0. Descriptive and inferential statistics were used to identify predictors of AI uptake and utilisation. Statistical significance was set at p< 0.050, and 95% confidence interval. Results: Among the 409 healthcare professionals surveyed, the majority were aged 20–29 years(50.4%), female (63.3%), Christians (97.3%), and single (61.9%). Nurses constituted the largest professional group (47.4%), followed by doctors (39.9%), while most respondents were junior staff (55.7%) with less than 10 years of work experience (85.3%). All respondents (100%) were aware of AI, with 61.1% demonstrating good knowledge. While more than half (51.3%) had ever used an AI tool, predominantly ChatGPT, routine clinical utilisation remained low. Slightly more than half (51.1%) of the respondents expressed a negative attitude toward AI in clinical assessment. Positive attitudes (OR = 1.59; 95% CI: 1.034–2.447; p = 0.035) and higher educational qualifications (OR = 3.169; 95% CI: 1.040 9.651; p = 0.042) were significant predictors of AI uptake and utilisation. Major barriers identified included unclear ethical guidelines, patient’s attitude towards AI use, infrastructurallimitations (such as unstablepower and internet), and concerns regarding patient data privacy. However, patients’ attitude was the only significant predictor (p = 0.049) Conclusion: While healthcare professionals at UBTH have relatively high awareness and initial uptake of AI, sustained and routine utilisation remains constrained by negative attitudes and perceived patient’s attitude. These perceptions appear to shape hesitancy in fully integrating AI into clinical workflows. To address this, there is an urgent need for structured institutional training, clear ethical frameworks, and improved digital infrastructure to shift attitudes and support safe, routine and effective integration of AI into clinical practice. Keywords: Artificial Intelligence, Clinical Assessment, Healthcare Professionals, Uptake,Utilisation, UBTH, Nigeria

The interaction between plant fibers and digestive enzymes is a critical aspect of gastrointestinal physiology, and plant fibers from traditional medicinal plants have attracted attention for their potential effects on digestive processes and metabolic health. However, the specific effects of Irvingia gabonensis (bush mango), Hunteria umbellata (osu), and Abelmoschus esculentus (okra) fibers on key small intestinal enzymes in a mammalian model are not fully elucidated. This study, therefore, investigated the effects of these plant fibers on the activities of disaccharidases (maltase, lactase, sucrase) and alkaline phosphatase, as well as total protein content and body weight, in the small intestinal mucosa of Wistar rats. Fifty-four (54) male wistar rats were divided into nine (9) groups of six (6) animals each, Control 1- fiber-free group, Control 2 Fybogel 1.5 %, Fybogel 3.0 %, Bush mango 5.0 %, Bush mango 10.0 %, Okra 5.0 %, Okra 10.0 %, Osu 5.0 %, and Osu 10.0 %. The animals were fed formulated diets containing different concentrations of each plant fiber for 36 days. The primary data collected were measurements of enzymatic activity, total protein content, and body weight gain. Enzyme activities (maltase, lactase, sucrase, and alkaline phosphatase) were assessed using spectrophotometric assays on the small intestinal mucosal homogenates. Statistical analysis was performed to determine significant variations in enzymatic activity, total protein, and body weight gain across the different dietary groups, with a threshold of p < 0.05 defining statistical significance. The findings demonstrated significant (p < 0.05) variations in enzymatic activity and metabolic parameters across the fiber-supplemented groups. Lactase activity was significantly elevated (122% increase) in the I. gabonensis 10.0 g group but significantly reduced by both doses of A. esculentus and the H. umbellata 10.0 g dose. Sucrase activity was consistently reduced across all plant fiber treatments, with H. umbellata showing the greatest reduction (44% decrease). Notably, alkaline phosphatase activity was significantly (p < 0.05) elevated in all fiber-supplemented diets compared to the fiber-free control (ranging from 105% to 353% increase). All plant fibers also significantly (p < 0.05) increased total protein content (up to 76% increase) and significantly (p < 0.05) reduced body weight gain (up to 35% decrease) compared to the control. These results suggested that supplementation with these plant fibers significantly modulated intestinal enzyme xi activities and influenced metabolic processes. The significant alterations in enzyme activities and weight control highlighted the potential therapeutic benefits of I. gabonensis, H. umbellata, and A. esculentus fibers in improving gastrointestinal health and metabolic function.

BACKGROUND: Hepatitis B remains a major global public health problem, particularly in low- and middle-income countries such as Nigeria, where it contributes significantly to chronic liver disease, cirrhosis, and hepatocellular carcinoma. Despite the availability of an effective vaccine, poor knowledge of the infection and its vaccine, as well as low vaccine uptake, continue to sustain transmission. AIM: This study assessed knowledge of the Hepatitis B vaccine, vaccination uptake, associated factors, and barriers to uptake of the vaccine among young adults in Benin City, Edo State. METHODS: A descriptive cross-sectional study was conducted among 543 respondents selected using a multistage sampling technique. Data was collected using a pretested structured interviewer and self-administered questionnaire covering socio-demographic characteristics, knowledge of Hepatitis B virus infection, knowledge of the Hepatitis B vaccine, vaccination status, and factors associated with these outcomes. Data was analyzed using IBM SPSS Statistics version 27.0. Univariate analysis summarized means, frequencies, and percentages. Bivariate analysis using chi-square tests determined associations between socio-demographic factors and respondents’ knowledge of Hepatitis B infection, knowledge of the vaccine, and vaccination uptake. Binary logistic regression identified predictors of good vaccine knowledge and full vaccination status. Statistical significance was set at p < 0.05, and results were presented in prose and tables. RESULTS: A total of 543 individuals took part in the study. The mean age of participants was 21.0 ± 2.8 years and 302 (55.6%) were females. Overall, 99 (24.6%) respondents had good knowledge of Hepatitis B virus infection, while 303 (75.4%) had poor knowledge. Regarding knowledge of the Hepatitis B vaccine, 50 (16.9%) had good knowledge, while 246 xv (83.1%) had poor knowledge. At the bivariate level, respondents age (χ²=17.131, p= <0.001), sex (χ²=5.122, p= 0.024), monthly income (χ²=14.319, p= 0.001), and individuals with good knowledge of Hepatitis B infection (χ²=91.056, p= <0.001) were significantly associated with
knowledge of the vaccine. Older respondents, females, individuals with higher monthly income, and those with good knowledge of Hepatitis B infection were more likely to have good knowledge compared to their counterparts. Ethnic group, marital status, religion, employment status and occupation were not statistically significant. Multivariate analysis showed that respondents earning ≥₦70,000 were 2.467 times more likely to have good knowledge of the vaccine (95% CI: 0.909–6.698), while respondents with good knowledge of Hepatitis B infection were 45.414 times more likely to have good knowledge of the vaccine (95% CI: 12.092–170.561), this was statistically significant (p < 0.001). Regarding vaccine uptake, 33 (6.1%) respondents were fully vaccinated, 66 (12.2%) were partially vaccinated, and 444 (81.8%) were not vaccinated. Bivariate analysis showed that age (χ² = 36.067, p < 0.001), sex (χ² = 10.591, p = 0.005), knowledge of Hepatitis B infection (χ² = 105.384, p < 0.001), and knowledge of the Hepatitis B vaccine (χ² = 93.812, p < 0.001) were significantly associated with vaccination status. Respondents aged ≥25 years had the
highest proportion of full vaccination 12 (16.7%), while those aged <20 years had the highest proportion of non-vaccination 190 (92.2%). Females had a higher proportion of partial vaccination 49 (16.2%), while males had a higher proportion of non-vaccination 206 (86.7%). Among respondents with good knowledge of Hepatitis B infection, 27 (27.3%) were fully vaccinated compared to 5 (1.7%) among those with poor knowledge. Similarly, 21 (42.0%) respondents with good vaccine knowledge were fully vaccinated compared to 9 (3.7%) among those with poor knowledge. Multivariate analysis showed that respondents with good knowledge of Hepatitis B infection were 9.011 times more likely to be fully vaccinated (95% xvi CI: 1.962–41.393, p = 0.005), while those with good knowledge of the Hepatitis B vaccine were 5.618 times more likely to be fully vaccinated (95% CI: 1.813–17.410, p = 0.003).
CONCLUSION: Knowledge of Hepatitis B infection and its vaccine was generally poor among respondents, and vaccination uptake was suboptimal. However, better knowledge of the infection and vaccine significantly improved the likelihood of full vaccination. Strengthening health education and awareness campaigns through healthcare workers, schools, and media platforms is essential to improve knowledge and increase vaccine uptake among the population.

This study examined the relationship between workplace toxicity and employees’ performance in virtual organisations in Lagos State. Virtual organisations have become an increasingly prominent feature of the modern business landscape as technological advancements, global connectivity and digital work platforms continue to redefine the nature of organisational operations. It is aimed at determining how workplace bullying influences employee performance; ascertaining the relationship between workplace harassment and employee performance; examining the extent to which toxic leadership influences employee performance; and ascertaining whether cyber incivility affects employee performance in virtual organisations in Lagos State. Four dimensions of workplace toxicity, which are: workplace bullying, workplace harassment, toxic leadership and cyber incivility in relation to employees’ performance, were examined. The study specifically adopted a descriptive survey research design to gather information from primary sources, using structured questionnaires administered to employees in the selected virtual organisations in Lagos State. A total number of three hundred and sixty-four (364) valid responses were collected from employees in the selected virtual organisations. The data gathered were analysed using both descriptive and inferential statistics. Findings indicated that each dimension of workplace toxicity examined, which are workplace bullying, workplace harassment, toxic leadership and cyber incivility, was significantly and positively associated with employees’ performance among the respondents. The analysis demonstrates a very strong association between the independent variables (workplace toxicity) and employees’ performance, as indicated by the correlation coefficient (R) of 0.872. This value signifies a very strong positive linear relationship. Furthermore, the coefficient of determination (R²) is 0.746, indicating that only 74.6% of the variance in employees’ performance is explained by the predictors. Based on these results, it is recommended that the organisation strengthen internal policies that address harassment, enforce fair treatment among staff, and develop transparent reward systems that minimise favouritism. In addition, the organisation should recommend continuous employee counselling, improved supervisory conduct, and policy reforms targeting toxic managerial practice

BACKGROUND: Artificial Intelligence (AI) is transforming higher education globally, yet data on AI knowledge, perception, and usage among Nigerian university students remain limited. Understanding these factors is essential for effective curriculum integration and preparing students for an AI-driven workforce.
OBJECTIVE: This study assessed the knowledge, perception, and use of Artificial Intelligence among students of the University of Benin, Benin City, Nigeria.
METHODS: A descriptive cross-sectional study was conducted among 603 undergraduate students selected using multistage random sampling from six faculties. Data were collected using a structured pretested, self-administered questionnaire and analysed with IBM SPSS version 27. Associations between sociodemographic factors and knowledge/perception/use were tested using chi-square and logistic regression, with statistical significance set at p < 0.05 (95% CI). RESULTS: The mean age of respondents was 19.9 ± 2.87 years and majority were females 355 (58.9%). Overall, 340 (56.4%) demonstrated good knowledge of AI, while 427 (70.8%) held positive perceptions. High AI usage was reported by 329 (54.6%) respondents, with ChatGPT being the most commonly used platform 450 (32.8%). Significant predictors of good knowledge included female sex (OR = 1.980, p = 0.001), being in the Faculty of Medicine (OR = 14.069, p = 0.001), and higher academic level (OR = 1.717, p = 0.020). Positive perception was significantly associated with high AI usage (OR = 8.020, p < 0.001) and excellent internet access (p = 0.041). AI usage was significantly influenced by positive perception (OR = 2.087, p = 0.025), peer interest (OR = 0.423, p = 0.004), and access to online learning platforms (OR = 0.528, p = 0.037). The most common concerns about AI were that it

Colour is an inextricable element of the world we are in, and its influence on how people perceive their surroundings is irrefutable. Colour is considered as an integral element of our environment, natural and constructed. The psychological effects of color mean that color’s impact on each and every individual are vast, however, people rarely have a clue of how these effects are even occurring. Psychologically certain feelings or reactions can be induced by colour, the same applies in architecture colour impacts how the users of the building feels. Even though most of people don’t spend a lot of time thinking about the effects of color in their homes, the color and design in our home should reflect the people who live inside, the designers and homeowners should use colors wisely to create the intended atmosphere in each space. This study highlights the important role of colour in residential designs. It is an undertaken study comprising of a survey of interviewed people from different walks of life in Benin City to assess their perception and colour preference in the use of colors in residential buildings and concluded that people expressed color as an important factor in their homes. They also believe that color affects health, mood & emotions of the person.

Crime remains a major social problem that negatively affects individuals and society through economic, psychological, and health-related consequences. In response to the increasing rate of crime, the police as a formal institution of social control are charged with the responsibility of maintaining law and order. However, traditional policing methods have often proven inadequate in addressing modern security challenges. This led to the emergence of community policing, which emphasizes partnership and collaboration between the police and members of the community in crime prevention and control. Community policing encourages proactive policing strategies, problem-solving, and public participation in maintaining peace and security. In Nigeria, the adoption of community policing in 2004 marked a significant step toward police reform aimed at improving public trust, professionalism, and effective service delivery. This approach seeks to transform citizens into co-producers of justice and security by strengthening police-community relations. The study therefore examines the role of community policing in crime prevention and control, highlighting its importance as a proactive strategy for ensuring the protection of lives and property in society.

This research presents a descriptive analysis of the semantic functions of reduplication in the Esan language, a member of the Edoid language family spoken predominantly in Edo State, Nigeria. Reduplication is a highly productive morphological process in Esan, used by native speakers to extend, intensify, or modify the meaning of base forms across various word classes. The primary objective of the study was to identify the types of reduplication in Esan, explore the semantic functions they perform, analyze how they operate within different grammatical categories, and determine what insights they offer into Esan speaker usage and morphology. The study was anchored on the Descriptive Linguistic Approach, backed by Basic Linguistic Theory (BLT), which emphasizes that grammatical and semantic patterns should be described as they are naturally used by speakers. Data were collected from native speakers through interviews, observations, and recordings of natural speech. The analysis revealed that Esan
employs both total and partial reduplication, with total reduplication being more common and used across all word classes including nouns, pronouns, verbs, adjectives, and time expressions. Reduplication in Esan was found to serve multiple semantic functions such as abundance, intensification, aspect marking, emphasis, repetition, plurality, diminutiveness, and emotional
or figurative expression. The study concludes that reduplication in Esan reflects both linguistic functionality and cultural expressiveness, making it a fundamental part of the language’s morphological and semantic system. This research contributes to the field of African linguistics by expanding the documentation and understanding of Esan grammar, while also showcasing
reduplication as a practical and versatile tool for meaning-making natural language use.