The current state of energy insecurity in Maiduguri calls for immediate action to explore and implement alternative energy sources, especially off-grid sources such as solar power, wind power etc. which could provide reliable, cost-effective, and sustainable energy solutions to the town and neighbourhoods. The University of Maiduguri is not an exception, equally faced with electricity disruptions that almost ground down the academic and administrative activities. This study aims at modeling and simulation of a solar farm using HOMER PRO software for University of Maiduguri senate complex to enhance power supply. It involves conducting an energy audit to determine the complex's electrical energy consumption, Prediction of future energy demand using HOMER PRO software, designing a solar farm model based on the energy audit and the predicted energy demand of the Senate Complex using same software. Data collected were analysed and optimised for system sizing. Based on the optimization results, model 1682 CanadianSolar Max Power CS6U-340M, 340 W per panels, 144 lead acid generic batteries rated at 1KW each (totalling 4603Ah) and 2 inverters with a combined capacity of 318kW were designed, which met the annual load demand of the complex (1.03 GWh). This study, if implemented will address the power challenges faced by the Senate complex building, thereby reducing the administrative and academic bottle neck faced by the University

Guna (Citrullus vulgaris) is a type of melon seed traditionally extracted from its gourds after fermentation. This study investigated the effect of fermentation on the physical, proximate, and functional properties of guna seeds. Fresh gourds were divided into three treatments namely; control (0 day), 7-day fermentation, and 14-day fermentation and shade-dried. Standard analytical methods were employed for the analyses. The results showed that fermentation had no significant effect (P > 0.05) on seed length (6.05–6.07 mm), width (3.43–3.46 mm), thickness (1.46–1.51 mm), sphericity (0.51–0.52), arithmetic diameter (3.65–3.68 mm), geometric diameter (3.12–3.17 mm), aspect ratio (56.69–57.10), or surface area (30.54–31.48 mm²). However, 1000-seed mass (31.78–34.60 g) and bulk density (1.64–1.82 g/cm³) were significantly affected (P < 0.05), decreasing with longer fermentation time. Proximate analysis revealed moisture (4.63–4.78%), ash (3.11–3.37%), protein (23.70–29.95%), fat (25.71–28.63%), fibre (18.54–19.21%), and carbohydrate (17.67–20.72%). Fermentation significantly (P < 0.05) increased moisture, protein, and ash contents, while reducing fat, fibre, and carbohydrate values. Functional properties improved with fermentation time, including higher water absorption capacity (73.97–82.00%), oil absorption capacity (54.12–66.67%), foam capacity (17.22–21.11%), and foam stability (12.78–13.89%), alongside reduced flour bulk density (1.15–1.18 g/cm³). In conclusion, 14-days fermentation time enhanced protein and ash content, improved hydration and oil-binding properties, and lowered bulk density, indicating potential for guna seed protein supplementation in food applications.

Energy policy plays a crucial role in shaping the energy landscape of any region. The reform of the Nigerian Electricity Act in 2023 marked a significant milestone for the Nigerian electricity market. It established a legal foundation aimed at addressing the nation’s perennial energy crisis by enabling the adoption of modern sustainable technologies and initiatives into the Nigerian power industry. Poor policy implementation, inadequate generation, and unplanned downtime due to faults on the defunct transmission and distribution networks have stifled the growth of power delivery in Nigeria, emphasizing the need for more intelligent and sustainable power infrastructure. This paper presents a comprehensive review of the challenges in Nigeria’s power sector andexplores how emerging technologies can provide effective solution at every node of the power chain. It draws insights from global case studies and outlines a strategic roadmap and timeline for planning and implementing smart grid and sustainable initiatives in Nigeria. Additionally, it highlights critical considerations necessary to promoting long-term sustainability within Nigeria’s power industry.

The climatic, environmental, and health concerns of fossil fuels have spurred the development of biodiesel as an alternative fuel. Biodiesel production has transitioned from single lipid-based feedstock to hybrid lipid-based feedstock owing to the challenges related to the former. Unlike previous studies that focused on singular and binary feedstock, this study uniquely employed ternary oil blends to synthesize biodiesel via alkaline transesterification and measured selected oil and biodiesel fuel properties using standard test methods. The studied hybrid oils were extracted (using the Soxhlet method) from ternary feedstock (72%, 20%, and 8% by weight of soybeans, avocado seeds, and sunflower seeds) and characterized for the physicochemical properties: viscosity, moisture content, volatile content, ash content, higher heating value, free fatty acids, and density. The measured biodiesel fuel properties were kinematic viscosity, density, flash point, pour point, and lower heating value. Results revealed that the hybrid oil properties were observed to be within the range of values for individual feedstock that made up the oil. The biodiesel produced has a yield of 81% and exhibited a kinematic viscosity of 3.75 mm2/s, density of 893 kg/m3, flash point of 122 °C, pour point of -11°C, and lower heating value of 34.96 MJ/kg. These fuel properties were observed to conform to biodiesel standards. Relatively low kinematic viscosity and pour point, and high lower heating value and flash point of the studied biodiesel were recorded due to the synergetic effect of oil hybridization. Therefore, selective mixing of different oils from existing feedstock for biodiesel production is recommended as this would further improve biodiesel fuel properties and consequently, enhance the performance, combustion, and emissions of biodiesel-fueled engines. Hybrid oil deployment will assist in addressing existing problems related to the use of single-feedstock based oil, with the ultimate view of promoting carbon neutrality in agreement with the Sustainable Development Goals.

This study develops a deterministic mathematical model for simulating the spray drying of pineapple juice. The model applies advanced vaporization kinetics and a receding interface-porous diffusion approach to predict moisture content, droplet density, and temperature. Validated experimentally at feed solids concentrations of 20% and 40% and drying temperatures of 130 °C and 140 °C, the model accurately predicted final moisture content with absolute errors ranging from 2.3% to 5.2% as drying gas temperature decreases from 140 °C to 130 °C for the 20% feed, and from 1% to 1.8% for the 40% feed. Key results quantitatively demonstrate that higher air temperatures reduce final moisture content and reveal the critical role of crust formation in shifting the drying kinetics from a rapid evaporation phase to a slower, diffusion-limited regime. The model's computational efficiency and physics-based foundation make it a valuable tool for the optimization of spray drying processes, potentially reducing reliance on costly and time-consuming experimental trials.

Variations in material properties, such as strength or durability, material defects and substandard materials can affect the structure’s performance. This study assesses the level of quality control of building materials (Cement, sand and blocks) availablein Maiduguri Metropolis. Generally, it included the Survey and collection of data of the existing supply markets, samples collection, laboratory tests, and analyses of results were conducted. Observation made from the survey showed that the price of blocks 150mm and 225mm thick range from 450 -500 naira and 550 -650 naira respectively. The particle size distribution of the sand sample used in the sand combination shows that the sand fell mostly in zone 2 except one which fell in zone 3 in accordance withFederal Ministry of Works and Housing Design Manual (FMWH). The average dry density of the investigated sandcrete blocks ranged from 1777.10kg/m3-2098.67kg/m3. The average compressive strength of the 150 mm thick blocks ranged between 0.12 -0.45N/mm2.The maximum value 0.45N/mm2recorded is less than 85% of the recommended minimum strength. The findings on the hydration properties of cement are within the BS 449 standard. The results show that the quality control of the building materials in Maiduguri Metropolis is generally inadequate, with many suppliers and contractors are unaware or failing to adhere to standard specifications and regulations.

Cracks and spalls in building structures pose serious risks to safety and durability. Conventional methods of detecting these defects are manual, time-consuming, and error-prone. Hence, this study develops a web-based system for automated defect detection using deep learning models. Two object detection models (YOLOv8 and Detectron2), and a CNN model (Resnet18), were trained on 1798 annotated images which consisted of benchmark datasets (METU, VCC) and with locally acquired images. Classification and object detection were done on both datasets acquired. YOLOv8 achieved a weighted average of 99.0% precision, 99.0% recall, and 99.0% accuracy, while Resnet18 reached 98.8.0% precision, 98.8% recall, and 98.8% accuracy weighted average for mild crack, severe crack and spall. For the object detection, YOLOv8 (mask mAP50 of 93.0%) achieved superior segmentation accuracy than Detectron2 (mask mAP50 of 87.5%). Both models demonstrated strong performance in detecting spalls, mild and severe cracks (mAP > 0.73). The Detectron2 model was deployed in a web-based application to enable real-time crack and spall identification. These results confirm the feasibility of AI-assisted structural health monitoring and highlight pathways for improving crack detection through balanced datasets, synthetic augmentation, and higher-resolution training in both Nigerian and global contexts.

Motorcycle theft has become a critical security challenge globally, with existing security measures proving inadequate against sophisticated theft techniques. In Nigeria, motorcycle theft accounts for 22.2% of over 45,000 documented criminal cases by 2021, necessitating advanced technological solutions. Current motorcycle security systems lack integration, real-time monitoring capabilities, and reliable alert mechanisms, making motorcycles vulnerable to theft. This research presents an integrated Internet of Things (IoT) based motorcycle theft prevention system utilizing ESP32 microcontroller, gyroscope sensors for vibration detection, load sensors for weight monitoring, GPS for location tracking, and GSM for communication. The system incorporates a mobile application developed using Flutter for real-time monitoring and alert notifications. Experimental validation demonstrated high location tracking accuracy with minimal coordinate deviations (±0.000005 degrees), effective sensor detection capabilities across various weight ranges (5-25 kg) and vibration levels (800-3500 units), and efficient alert delivery with response times ranging from 1-14 seconds across different network providers. The developed system provides a comprehensive, cost-effective solution for motorcycle security, offering real-time monitoring, multi-channel alert mechanisms, and reliable theft detection capabilities that significantly enhance motorcycle protection compared to existing solutions.

Milk derived from animal sources often contains anti-nutrient elements such as α-lactoglobulin, β-lactoglobulin, lactose and cholesterol, which can contribute to various health challenges. Plant-based milk alternatives, such as tiger-nut milk, offer a healthier option but often face limitations like short shelf life and high storage costs. This study aimed to investigate the drying kinetics and proximate composition of tiger-nut milk powder. Tiger-nut tubers were processed into milk from brown varieties and subsequently dried at 50, 60, and 70°C. Data obtained were fitted to five commonly applied drying mathematical models (Newton, Logarithmic, Page, Henderson and Pabis) to determine the one which predicted the drying kinetics of the milk more accurately. The dried powder was then analyzed for its proximate composition, including moisture content, crude fiber, carbohydrates, protein, lipids, ash, and pH using standardized procedures developed by Association of Official Analytical Chemists (AOAC). The best fit model for the drying kinetics analysis was determined using the coefficient of determination (R²), with the Page model having the highest R² values of 0.998-0.999. This analysis revealed that the Page model accurately describes the drying behavior, with both drying time and equilibrium moisture content decrease as the drying temperature increases. The results also indicated that tiger-nut milk powder contains a moderate protein content (7.12-7.26%), a high carbohydrate content (63.68-64.17%), and relatively low levels of lipids (6.12-6.24%) and ash (1.42%). These findings suggest that tiger-nut milk powder has the potential to be a valuable plant-based food alternative. Future research should focus on determining its specific mineral composition, bioactive compounds, and potential health benefits.