The University of Maiduguri (UNIMAID) is a Federal higher institution located in Maiduguri, the capital city of Borno State in northeast Nigeria. The university was created by the federal government of Nigeria in 1975, with the intention of its becoming one of the country's principal higher-education institutions. It enrolls about 25,000 students in its combined programs, which include a college of medicine and faculties of agriculture, arts, environmental science, Allied health science, Basic medical science, dentistry, education, engineering, law, management science, pharmacy, science, social science, and veterinary medicine. With the encouragement of the federal government, the university has recently been increasing its research efforts, particularly in the fields of agriculture, medicine and conflict resolution, and expanding the university press. The university is the major higher institution of learning in the north-eastern part of the country.
Landslides pose significant threats to life, property and sustainable development in mountainous regions worldwide, with their occurrence increasingly influenced by climate change. This study addresses the critical need for accurate landslide susceptibility models in the Western Province of Rwanda, where traditional methods have shown limitations. It employed and compared three deep learning models: convolutional neural network (CNN), deep neural network (DNN), and multi-layer perceptron (MLP), to assess the landslide risks, incorporating climate change considerations. The study utilised 16 conditioning factors, carefully selected to avoid multicollinearity, with the digital surface model (DSM) showing the highest variance inflation factor (VIF) of 3.9730. The CNN model demonstrated superior performance, achieving the highest overall accuracy (93.7
Coking coal is an essential feedstock for coke production, and its thermoplastic properties are the primary determinant of coke quality. Thermoplastic behavior is influenced by the coal rank, maceral composition, and rheological properties. Understanding these thermoplastic characteristics is essential for optimizing coke production processes. This work extends our previous publication on in situ FTIR/MS spectroscopy, in which spectra were acquired at 10 degrees C intervals at a heating rate of 5 degrees C/min from 30 to 600 degrees C. However, this study focused exclusively on the 900-700 cm-1 region-the spectral region most relevant to aromatic substitution patterns. In situ FTIR was used to characterize and quantify structural changes in three Australian metallurgical coals during coking. The findings showed that as the coking temperature increases beyond the plastic region, fused aromatic C-ring structures become progressively ordered and more condensed, and aromatic clusters grow due to aromatic carbon hybridization. Thus, the degree of substitution (DOS) of aromatic rings increased with coal rank and vitrinite composition, and the maximum fluidity in mid-ranked coal also contributed, as exhibited by coal B. The methodology and techniques employed in this work can be applied to coal and coal maceral blends to provide further insights into the chemistry underlying the transformation of coal to metallurgical coke. This will guide coal experts and marketers in selecting optimal coal blends for producing high-quality coke-critical for the iron and steel industries. More samples with distinct properties will be considered in future work.
Abstract Electrochemical hydrogen production in alkaline media faces distinct mechanistic challenges compared with acidic conditions, largely due to the extra water dissociation step (Volmer reaction) and slower hydrogen adsorption and desorption kinetics. Non-noble electrocatalysts have attracted significant attention as cost-effective alternatives to platinum, offering a balance between activity, stability, and scalability using earth-abundant elements. This review provides a comprehensive overview of non-noble alkaline HER catalysts, spanning transition metal oxides and hydroxides, layered double hydroxides (LDHs), transition metal phosphides, nitrides, borides, MOF-derived materials, single- and dual-atom catalysts, MXene-based hybrids, boron-rich metal-free frameworks, and advanced 1D/2D architectures. Emphasis is placed on the evolving nature of catalyst surfaces, highlighting phenomena such as in situ reconstruction and the pre-catalyst concept, which often dictate the true active sites under reaction conditions. We examine how intrinsic catalytic kinetics, electron and mass transport, structural durability, and high-current operation interact, and highlight strategies such as heterostructure engineering, hierarchical design, doping, and integration with conductive scaffolds. By combining fundamental understanding with practical electrode considerations, this review outlines the principles necessary for designing alkaline HER catalysts that are both efficient and durable, moving closer to practical water electrolysis applications.
Groundwater is the primary source of potable and irrigation water in Gashua, Northeastern Nigeria, where arid climatic conditions limit surface water availability. Unlike previous studies in the Chad Basin that focused on limited chemical parameters, this study applies integrated geospatial modelling and multivariate statistics to delineate hydrochemical facies and anthropogenic hotspots in a semi-arid aquifer. Twenty-five groundwater samples were analyzed for pH, electrical conductivity, total dissolved solids, total hardness, major cations (Ca²⁺, Mg²⁺, Na⁺, K⁺), and anions (Cl⁻, SO₄²⁻, NO₃⁻, HCO₃⁻). Results showed pH values from 5.7 to 7.9, EC between 415 and 1464 µS/cm, and TDS from 265.6 to 937.0 mg/L. 80% (20/25) of the samples exceeded the Nigerian Standard for Drinking Water Quality (NSDWQ) limit for hardness. Piper and Durov diagrams revealed Ca²⁺–Mg²⁺–Cl⁻–SO₄²⁻ and Ca²⁺–Mg²⁺–HCO₃⁻ facies, reflecting carbonate and sulphate dissolution, cation exchange, and evaporative concentration. Spatial analysis delineated recharge zones in the north and discharge zones in the south, with higher salinity and nitrate levels in peri-urban areas. Nitrate ranged from 10.8 to 88 mg/L, with one sample exceeding the World Health Organization (WHO) limit of 50 mg/L; sampling was conducted during the dry season. Principal Component Analysis (PCA) explained 79% of total variance and identified mineralization, pH buffering, and nitrate pollution as key processes. Hierarchical Cluster Analysis (HCA) classified wells into recharge, transitional, and discharge zones. Irrigation suitability assessed by SAR, Na⁺%, PI, KR, and MH confirmed that most samples are suitable, though moderate salinity (C2S1) and isolated sodicity risks highlight the need for site-specific management. These findings emphasize the vulnerability of groundwater to both natural geochemical evolution and human activities. The integrated hydrogeochemical and multivariate approach provides actionable implications: protecting recharge areas in the north, routine surveillance of southern salinity and nitrate hotspots, and tailored farmer advisories for irrigation practices. Such measures are critical for sustainable aquifer management in arid regions.
Malaria transmission in Adamawa State is strongly driven by climatic conditions, particularly rainfall and temperature, which influence Anopheles mosquito breeding, survival, and parasite development. This study investigates the climate malaria relationship using monthly data from January 2015 to April 2024 and applies time series methods to characterize temporal patterns and generate forecasts. Using the Box Jenkins ARIMA framework with model selection informed by AIC and BIC, and performance evaluated through RMSE, MAE, and MAPE, the $$SARIMAX(1,0,1)(1,1,1)_{12}$$ model emerged as the best fitting specification. This model integrates lagged temperature and rainfall, successfully capturing both the inherent annual seasonality of malaria and the climatic drivers that modulate transmission. Forecasts for May 2024 to December 2025 indicate pronounced seasonal surges, with cases expected to rise sharply between June and October. Incidence is projected to reach approximately 67,052 cases in August 2024 and peak again at about 80,004 cases in October 2025, the highest value within the 20 month horizon. Early forecast months exhibit narrower confidence intervals due to proximity to observed data, whereas wider intervals toward late 2025 reflect increasing long range uncertainty, a common feature of time series predictions. These findings underscore the substantial influence of climate variability on malaria dynamics in Adamawa State and highlight the value of SARIMAX based forecasting for strengthening early warning systems. The projections support the need for proactive public health planning, including intensified seasonal preparedness and reinforcement of malaria vaccination and vector control strategies to reduce disease burden.
