African Multidisciplinary Journal of Sciences and Artificial Intelligence

Smoking Behaviors and Perceived Health Risks Among Out-of-School Youth in Tella, Taraba State

2026-04-09T21:17:15+08:00

Tobacco use among adolescents remains a significant public health concern, particularly among out-of-school youth who often have limited access to formal health education and support systems. In response to anecdotal indications of increasing smoking behavior in Tella, this study aimed to assess the prevalence, patterns, and determinants of smoking among out-of-school youth, examine their perceptions of smoking-related health risks, and identify the socio-cultural and economic factors associated with tobacco use. A cross-sectional descriptive survey was conducted using structured questionnaires administered to a purposive sample of out-of-school youth aged 13–24 years, and the data were analyzed using descriptive statistics and presented in tabular form. The findings showed that 58% of respondents were current tobacco users, with cigarettes as the most commonly used product (60%), while 40% reported initiating smoking before the age of 15. Although 70% acknowledged that smoking is harmful, only 35% could identify specific smoking-related diseases, and 45% believed that occasional smoking was not harmful. Peer pressure (60%) and stress related to unemployment (50%) emerged as the most frequently cited reasons for smoking. The respondent profile further indicated that most participants were male (65%), aged 17–21 years (58%), and characterized by high levels of unemployment (42%) and informal labor participation (30%). The study concludes that out-of-school youth in Tella are highly vulnerable to tobacco use due to the combined effects of limited education, economic hardship, peer influence, and cultural norms. These findings highlight the need for integrated interventions that combine health education, peer-based support, economic empowerment, and policy enforcement to reduce tobacco use and promote healthier lifestyles among this at-risk population.

Efficiency of Rice Processing Among Women Processors in Southern Taraba, Taraba State, Nigeria

2026-04-10T08:36:59+08:00

Rice processing plays an important role in rural livelihoods and local food systems in Nigeria; however, evidence on the economic efficiency of women processors remains essential for informing productivity-enhancing interventions. This study analyzed the efficiency of rice processing among women processors in Southern Taraba, Taraba State, Nigeria. A multi-stage sampling technique was used to select 70 respondents from Wukari and Donga Local Government Areas. Primary data were collected through structured questionnaires and analyzed using descriptive statistics, gross margin analysis, and net income estimation. The results showed that 89% of the processors were aged 50 years or below, with a mean age of 38.6 years, indicating a relatively young and active workforce. Most respondents had formal education (90%), 63% were married, and the average household size was five persons. Profitability analysis demonstrated that rice processing was a viable enterprise, with a total revenue of ₦711,064.40 and a total cost of ₦471,638.87 per processing day, resulting in a gross margin of ₦240,751.33 and a net income of ₦239,425.53. The return per naira invested was 0.51, implying that processors realized a gain of 51 kobo for every naira invested. Paddy rice constituted the largest cost component, accounting for 90.37% of variable costs. The study concludes that rice processing among women in the study area is profitable, although its efficiency is constrained by inadequate capital, limited access to modern equipment, and insufficient technical training. These findings highlight the need for improved access to modern milling technology, credit facilities, and regular capacity-building programs to enhance processing efficiency and support broader food security goals in Nigeria.

Sustainable Rice Husk Mixture Fibre–Stripe Polyethylene Film Composites: Effects of Recycling and Alkali Treatment on Water Absorption, Flammability, Density, and Mechanical Properties

2026-05-07T15:01:33+08:00

The increasing accumulation of plastic and agricultural waste has intensified interest in sustainable polymer composites that combine improved material performance with environmental value. This study investigates the water absorption, flammability, density, hardness, and tensile strength of composites prepared from used and unused stripe polyethylene (PE) films and rice husk mixture fibres, with and without NaOH treatment. Water absorption testing showed that composites made with used PE exhibited the highest uptake, reaching 88.35% after 24 hours, which was attributed to polymer degradation and microvoid formation, whereas unused PE composites demonstrated superior moisture resistance, with absorption as low as 2.19%. NaOH-treated rice husk improved fibre–matrix adhesion and produced intermediate absorption values. Flammability analysis revealed that used PE composites burned faster, with rates of 0.88–0.39 mm/sec, compared with unused PE composites, which recorded 0.65–0.28 mm/sec, while NaOH treatment reduced flammability through enhanced char formation and silica content. Density measurements indicated lower values for used PE composites, ranging from 1.18 to 2.25 g/cm³, due to chain scission and void formation, whereas unused PE composites maintained higher densities of up to 2.75 g/cm³. Hardness and tensile strength increased with PE content, with unused PE composites achieving the highest values of 36.60 MPa and 54.90 MPa, respectively, while NaOH-treated rice husk composites provided balanced mechanical reinforcement. The study concludes that unused PE offers superior mechanical performance and moisture resistance, whereas NaOH-treated rice husk enhances interfacial bonding and fire-safety characteristics. These findings contribute to the development of sustainable rice husk–polyethylene composites as potential eco-friendly materials for packaging, construction, and automotive applications.

Data-Driven Identification of Stochastic Dynamical Systems

2026-05-23T15:47:02+08:00

Identifying stochastic dynamical systems from observational data remains a major challenge in applied mathematics and engineering, particularly when complex systems are influenced by random perturbations and incomplete empirical information. This comprehensive review aims to examine state-of-the-art data-driven methods for discovering governing equations, estimating parameters, and predicting the behavior of stochastic dynamical systems. The review systematically analyzes key methodological approaches, including Sparse Identification of Nonlinear Dynamics (SINDy), Dynamic Mode Decomposition (DMD) and its extensions, Koopman operator theory, neural ordinary differential equations, and Bayesian inference. Each approach is evaluated in terms of its theoretical foundations, computational requirements, robustness to noise, and applicability to different classes of stochastic systems. Drawing on numerical experiments and real-world case studies, the findings show that no single method consistently outperforms others across all scenarios. Instead, hybrid approaches that integrate physics-informed constraints with machine learning demonstrate the strongest potential for advancing data-driven system identification. The review concludes that future research should address real-time identification, uncertainty quantification, and the integration of multi-fidelity data sources to improve the reliability and scalability of stochastic system modeling. This work contributes a comprehensive framework for guiding researchers and practitioners in selecting and implementing appropriate identification methods for stochastic dynamical systems.