Journal of the Nigerian Society of Physical Sciences
Journal of the Nigerian Society of Physical Sciences is a peer-reviewed journal published quarterly (February, May, August & November) by the Nigerian Society of Physical Sciences. It offers an exciting publication outlet for Physical Science reports.
Velocity-in/dependent double folding analysis of 12C + 12C elastic scattering cross section at different energies
This study investigates the elastic scattering cross sections for 12 C + 12 C over a wide range of incident energies from 78.85 to 420 MeV using the velocity–dependent São Paulo Potential version 2 (SPP2) and the velocity–independent Brazilian Nuclear Potential (BNP) within the optical-model-based double folding (DF) framework. Two different density distributions for 12C, experimental matter density (ED), and the Dirac-Hartree-Bogoliubov (DHB) theoretical matter density, were employed. The analysis compares the computed potentials, obtained by folding the density distributions, and evaluates the accuracy of the results through comparison with experimental data. Two approaches were explored to determine the depths of the potentials, highlighting their performance and sensitivity to energy and density distributions. Results indicate good agreement with experimental data, with SPP2 generally outperforming BNP. Analysis of volume integrals and reaction cross sections further elucidates the behavior of the potentials and their implications on scattering phenomena. Overall, this study provides insights into the dynamics of nuclear interactions at intermediate energies, contributing to the understanding of nuclear reactions.
Copyright (c) 2026 Sunday D. Olorunfunmi, Armand Bahini, Samuel A. Adeojo (Author) https://creativecommons.org/licenses/by/4.0
Synergistic intelligence: a novel hybrid model for precision agriculture using k-means, naive Bayes, and knowledge graphs
This study presents a novel hybrid knowledge discovery model integrating K-Means clustering, Naive Bayes classification, and Knowledge Graph technology to address interpretability and data heterogeneity challenges in precision agriculture. The proposed framework first applies K-Means to segment agro-ecological zones using multi-source data (soil, climate, satellite imagery), then employs Naive Bayes to classify crop productivity tiers, achieving 89% accuracy—surpassing standalone benchmarks (Naive Bayes: 86%, Random Forest: 87.5%). A Neo4j-based Knowledge Graph contextualizes these outputs, demonstrating 95% schema completeness and efficient querying (0.1559s latency), while enabling dynamic analysis of soil-climate-crop relationships. Pilot trials confirmed actionable impacts, including 22% reduced water use and 18% less fertilizer waste in targeted farms. By unifying unsupervised/supervised learning with semantic reasoning, this work advances scalable, interpretable decision support systems for sustainable agriculture, offering a replicable template for global food security initiatives.
Mathematical, Computer & Statistical Sciences
Copyright (c) 2025 Catherine N. Ogbizi-Ugbe, Osowomuabe Njama-Abang, Samuel Oladimeji, Idongetsit E. Eteng, Edim A. Emanuel (Author) https://creativecommons.org/licenses/by/4.0
Concentrations of heavy metal content in indoor dust and potential exposure in preschool children
Indoor dust serves as a medium for the deposition of heavy metals, and young children's rapid physical growth and hand-to-mouth behavior expose them to the impacts of heavy metals. This project aimed to measure the concentrations of heavy metals in classroom dust from the selected preschools in southwestern Nigeria. Dust samples were taken via a dust collector and analyzed quantitatively and qualitatively via the Atomic Absorption Spectroscopy (AAS) scheme. The descriptive and inferential statistical method was employed for the data analysis, and standard calibration, recovery analysis, and blank determination were carried out for the quality control measures. It was found that, in the dry season, the total metal concentrations in dust were 1.82 gg-1 Cu to 80.00 gg-1 Zn, whereas, in the wet season, the heavy metal concentrations were 0.83 gg-1 Co to 38.43 gg-1 Zn. Hence, the selected preschool dust was significantly enriched with high levels of Cd and As contamination but unpolluted for Co, Cu, Mn, and Pb across all examined metals. The results indicate elevated concentrations of lead (Pb) and cadmium (Cd) in high-traffic indoor spaces, with levels exceeding recommended safety thresholds. Lead (Pb) exposure is linked to neurodevelopmental disorders and reduced cognitive function, Cadmium (Cd) can cause kidney damage and impair bone development, while arsenic (As) is associated with immunotoxicity and an increased risk of cancer. To mitigate these risks, this study recommends practical measures, including frequent wet cleaning of floors and surfaces to reduce dust accumulation and limiting the use of materials known to contain heavy metals, such as lead-based paints and older plumbing fixtures.
Copyright (c) 2025 J. A. Akinpelu, K. P. Ojo, S. O. Salawu, G. O. Olutona, F. O. Aweda, O. O. Jegede (Author) https://creativecommons.org/licenses/by/4.0
On graded Jgr-2-absorbing primary submodule
This paper introduces the concept of graded Jgr-2-absorbing primary submodules, a new intermediate structure in graded module theory. Motivated by the need to extend and unify classical notions such as graded prime and graded primary submodules, the study develops a comprehensive framework describing their defining characteristics and relationships. Through a sequence of rigorous theorems and illustrative examples, we establish fundamental properties, equivalence conditions, and inclusion relations that clarify the behavior of these submodules within graded modules. The findings show that graded Jgr-2-absorbing primary submodules generalize several known structures while maintaining distinctive algebraic flexibility. Moreover, the results concerning graded homomorphisms and multiplication modules demonstrate the robustness of the concept and its potential applications in graded algebra. Overall, this work deepens the theoretical understanding of graded algebraic systems and provides a foundation for further research in module and ring theory.
Graded J_{gr}-2-absorbing primary submodule
commutative algebra, graded rings, graded modules
Copyright (c) 2025 Shatha Alghueiri, Khaldoun Al-Zoubi (Author) https://creativecommons.org/licenses/by/4.0
Effect of a moving thermal load in a modified couple stress medium with double porosity and hyperbolic two-temperature theory
In this study, a two-dimensional thermoelastic problem is investigated within the framework of Modified Couple Stress Theory (MCST) incorporating double porosity and governed by the Hyperbolic Two-Temperature (HTT) model under the influence of a moving thermal source. The governing equations are reformulated in non-dimensional form and potential function techniques are employed to simplify the analysis. By applying normal mode analysis, closed-form analytical expressions are derived for key physical fields including displacement components, stress distributions, equilibrated stress tensors and temperature profiles. Numerical computations are carried out using MATLAB and the effects of the HTT model and the moving thermal load on the thermoelastic response are illustrated through graphical representations. Several particular cases of interest are examined to validate and interpret the model’s behaviour under different physical conditions. The problem finds practical significance in areas such as microelectronics, civil engineering and biomedical devicedesign particularly in areas involving thermal shock.
Copyright (c) 2025 Pragati, Rajneesh Kumar, Sachin Kaushal (Author) https://creativecommons.org/licenses/by/4.0
Structural, electronic and optical properties of theFeAs(1-x)La(x) ternary alloys: a first principles calculations
This study investigates the structural, electronic, and optical properties of FeAs(1-x)La(x) alloys (x = 0, 0.25, 0.5, 0.75, 1) using the FP-LAPW method within the framework of density functional theory (DFT). The lattice parameter, bulk modulus, and its derivative were determined through Murnaghan’s equation of state, revealing deviations from Vegard's law with increasing lanthanum concentration. Analysis of the electronic band structure and refractive indices highlights changes in the band gap, while energy-volume relationships indicate stability in the Zinc-Blende structure. Further exploration of the orthorhombic phase is suggested to confirm the structural properties. Doping FeAs with rare-earth elements introduces significant challenges due to disparities in ionic size, charge, and chemical behavior, yet it can profoundly impact structural, electronic, and superconducting properties such as charge carrier density and lattice parameters. The results emphasize the importance of precise control over doping concentrations and preparation techniques to achieve stable compounds. This theoretical work underscores the potential of FeAs-based materials for advanced applications, paving the way for further experimental validation.
FP-LAPW, DFT, FeAs(1-x)La(x), Ternary alloys, Superconductors,WIEN2K
Copyright (c) 2025 F. L. Kherfane, A. BOUKRAA, B. Beladel, A. Douara, I. E. Tibermacine, A. Rabehi, M. Benghanem (Author) https://creativecommons.org/licenses/by/4.0
Development and validation of hybrid drying kinetics models with finite element method integration for black paper in a v-groove solar dryer
Preserving agricultural products requires drying techniques to avoid spoilage and financial setbacks. Sun drying is unreliable because of changing weather conditions; hybrid solar dryers provide an option. However, it is not easy to forecast the drying process of crops such, as black pepper due to its drying characteristics. This research examines how accurately different models predict the drying process of black pepper in a v Groove Hybrid Solar Dryer using a modeling framework and a Finite Element Method (FEM) inspired approach that is newly developed. Black pepper was dried for four days, with the moisture ratio data collected every 30 minutes from 8 AM to 5 PM. Twenty-seven drying kinetics models were tested on the data, with the Alibus model, Aghbashlo, and Infiltration Approximation models being the three best performers. To improve the accuracy of predictions, a total of 220 hybrid models were created by merging pairs of the 11 best-performing models using a specialized formula based on weights. The analysis indicated that more than thirty (30) hybrid models performed better than single models with Hybrid M28 (combining Logarithmic and Alibus), Hybrid M38 (pairing Lewis and Alibus), and Hybrid M101 (merging Infiltration Approximation and Kaleemullah), showing exceptional results. Furthermore, a model based on FEM was developed and validated using MATLAB and CurveExpert Professional to account for the physical diffusion characteristics. While it demonstrated good alignment with the experimental data, it equally acted as a solid foundation based on physics principles. The results highlighted the capability of combining hybrid and FEM based models to better understand intricate drying patterns in a more efficient way which can lead to improved solar drying system designs with enhanced reliability for future optimization efforts, across various crop types.
Evaluation, Drying kinetics, Black pepper,
Copyright (c) 2025 Ibrahim Adamu Mohammed, Majid Khan Majahar Ali, Sani Rabiu, Raja Aqib Shamim, Shahida Shahnawaz (Author) https://creativecommons.org/licenses/by/4.0
Computation of vibrational partition function: a comparative analysis between Poisson summation and classical limit
The computation of partition function (Z) is the bedrock of the study of statistical mechanics as it plays a significant role in the thermodynamic properties (TP) where microscopic properties are connected to macroscopic properties. Several studies have reported TP via the Z using one of the classical limit approach or Poisson summation formula. No study however justifies the agreement or discrepancy between the methods. This study therefore, investigates the two methods for theoretical determination of the vibrational partition function by considering the energy levels of Tietz molecular potential. The first approach employs Poisson summation method with a defined energy levels of the Tietz molecular potential while the second approach adopts the utilization of the classical limit approach with the same energy levels of the Tietz molecular potential. By comparing the results of the two approaches, our result reveals discrepancy between the analytic equations for Z. However, the numerical results obtained for the thermal properties of NaBr and CuCl molecules showed a perfect agreement between the two approaches and the experimental data with the results from classical limit approach closer to the experimental data. This study therefore, provides guidelines for choosing the appropriate approach based on the characteristics of the system under study for theoretical research.
Copyright (c) 2025 C.A. Onate, I.B. Okon, E.S. Eyube, E. Omugbe, A.D. Ahmed (Author) https://creativecommons.org/licenses/by/4.0
Onchocerciasis control via Caputo-Fabrizio fractional dynamics: a focus on early treatment and vector management strategies
The socio-economic burdens of onchocerciasis have prompted the formulation of several mathematical models to better comprehend the epidemic. However, existing models either use integer-order derivatives, which often do not capture the memory and non-local effects seen in infectious diseases, or fractional order with singularity kernels, which may inadequately represent memory effects due to their singularity kernels. Onchocerciasis has a prolonged incubation and slow progression, making past conditions impactful on the disease's current and future course. Fractional derivatives effectively capture this memory effect, providing a more realistic depiction of the infection dynamics than integer-order models. We propose a non-local, non-singular exponential kernel fractional-order onchocerciasis model in the Caputo-Fabrizio fractional derivative sense to capture the disease's memory effects. Our model incorporates early treatment of exposed individuals as a critical intervention parameter, and vector management strategies are also incorporated. Using fixed-point theorem and iterative methods, we establish the existence and uniqueness of solutions, derive conditions for onchocerciasis-free and endemic equilibrium points, and analyze their stability, confirming the model's biological feasibility. Numerical simulations are conducted using a three-step fractional Adams-Bashforth method. Sensitivity analyses indicate that vector management and early treatment effectively reduce the effective reproduction number, while increases in the human-to-vector contact rate elevate it. Numerical results demonstrate that early treatment and vector management can significantly control onchocerciasis. The fractional-order "memory effect" highlights the importance of continuous monitoring and consistent application of control measures to reduce the memory index and curb onchocerciasis prevalence over time.
Fractional Adams-Bashforth Numerical scheme
Copyright (c) 2025 Danat Nanle Tanko, Farah Aini Abdullah, Majid K. M Ali, Matthew O. Adewole, James Andrawus (Author) https://creativecommons.org/licenses/by/4.0
Effect of radial non-uniformity on mechanical response of functionally graded discs
This study investigates the stress distribution in functionally graded material (FGM) discs composed of compressible and incompressible constituents, subjected to nonhomogeneity and external loading. Analytical results are presented for radial and tangential stresses as functions of the radii ratio r/b the gradation parameter m, and Poisson’s ratio $\nu$. However, the combined effect of compressibility and material gradation on the stress response of discs remains insufficiently explored, particularly in cases where both compressible (\nu < 0.5) and incompressible (\nu \rightarrow 0.5) material behaviors are considered under identical loading conditions. The methodology is designed to systematically evaluate how radial stress (\sigma_r) and tangential stress (\sigma_\theta) evolve across the disc geometry in response to the combined influences of material gradation and volumetric compressibility. Figures are generated by MATLAB to provide comparative insights, separating compressible and incompressible cases, and highlighting the stress sensitivity to parameter variations. The focus of the investigation is twofold. First, the study seeks to establish the relationship between Poisson’s ratio and stress magnitudes, particularly assessing whether compressible materials exhibit sharper stress gradients that could lead to structural instability. Second, the work examines the extent to which nonhomogeneity, represented by the parameter m, modifies these trends in both compressible and incompressible regimes. Furthermore, by delineating the contrasting behavior of compressible and incompressible FGMs, the study provides a decision-making basis for selecting appropriate material gradations in scenarios where crack initiation, fatigue resistance, or tensile failure are of concern. Thus, the present work sets out to systematically examine how compressibility and gradation interact to determine stress responses in FGM discs, with the ultimate objective of offering practical guidelines for the safe and efficient application of these advanced materials in engineering design.
Copyright (c) 2025 Namarta Singh, Jatinder saini (Author) https://creativecommons.org/licenses/by/4.0
Environmental and health risk assessment of cadmium, zinc,iron, copper in crops and soil at Enugu State dumpsite
Contamination of soils and food crops around the Ugwuaji dumpsite in Enugu State, Nigeria was evaluated. Zinc (Zn), copper (Cu), iron (Fe), and cadmium (Cd) were determined in seventy-three (73) samples, which included pre-planting and post-harvest soils, control soils, ash from the New Artisan abattoir, and edible parts of Dioscorea bulbifera, Zea mays, and Telfairia occidentalis. Samples were digested with aqua regia and analyzed using atomic absorption spectrophotometry (AAS). The analytical recovery was 96% with a relative standard deviation (RSD) of 5.7%. Soil properties showed pH values between 5.2-6.7 (slightly acidic), cation exchange capacity (CEC) of 8.7-14.5 cmol/kg, and organic matter contents of 1.84-3.92%. Post-harvest soils recorded 11.33 ± 2.51 mg/kg higher concentrations of Zn and 4.64 ± 0.69 mg/kg of Cu compared to control soils, while Fe decreased to 735.47 ± 73.20 mg/kg. Cadmium was detected in one soil sample (1.14 mg/kg) and in T. occidentalis (0.02-2.03 mg/kg), but was not detected in D. bulbifera and Z. mays. Pollution indices revealed high Cd contamination with enrichment factor (EF > 10), geoaccumulation index (Igeo > 2), contamination factor (CF > 6), and a pollution load index (PLI) of 1.65. The bioconcentration factor (BCF) of Zn in T. occidentalis was 3.98 with a translocation factor (TF) of 1.87, showing strong accumulation. Estimated daily intake (EDI) and total hazard index (THI) for adults were low (0.00042-0.00057), while children showed high THI values of 4.28 for Z. mays and 4.54 for D. bulbifera. Structural equation modeling indicated that soil pH (? = -0.62) influenced Cd mobility and its accumulation in T. occidentalis (? = 0.58), contributing to child-specific health risk (? = 0.79). These results highlight the need for risk control measures, including regulated ash application and crop-specific monitoring in waste-affected farmlands.
Copyright (c) 2025 Emmanuel Agboeze, Henry Okechukwu Agboeze, Theresa Orieji Uchechukwu, Anayo Vitus Ofordile, Chukwuebuka Gabriel Eze (Author) https://creativecommons.org/licenses/by/4.0
Evaluation of radiation shielding and mechanical properties of palm nut shell ash modernized concrete: a comparative analysis
Gamma radiation poses health and environmental risks, creating the need for sustainable, low-cost, and eco-friendly shielding materials. In this study, we modified ordinary concrete with palm nut shell ash (PNSA) to examine its mechanical, physical, and gamma ray shielding performance. The adopted W/C (water-to-cement) ratio was 0.5 for the entire mixtures and the ratio of the samples’ masses to their respective volumes gives the densities of our samples. The results reported that, as PNSA advances from 0 to 0.15 kg, the concrete density decreased from 2.40 to 2.25 g/cm3, accompanied by a rise in porosity from 14.5% to 21.5% as well as an increase in water absorption from 6.8% to 8.6%, 6.4% to 8%, and 5% to 7% respectively for 7, 14, and 28 curing days. The mechanical characteristics decrease as PNSA is added to the concrete matrix. The Monte Carlo N-Particle (MCNP) and Phy-X/PSD simulation results showed that CPNSA2 had superior linear attenuation coefficient (LAC), confirming higher gamma ray attenuation ability. Generally, this work displayed the prospect of adding PNSA for the purpose of shielding against the low and intermediate gamma-ray energy. This study contributes by introducing palm nut shell ash as a sustainable cement substitute, demonstrating improved gamma-ray attenuation with CPNSA2, and reducing reliance on costly and toxic conventional shielding materials.
Copyright (c) 2025 U. Rilwan, M. I. Sayyed, K. A. Mahmoud, S. Muhammad, A. Alkasim, S. I. Ikpughul, S. J. Iwa, Jibrin Ahmed Guto, O. A. Adeyeba, M. W. Marashdeh (Author) https://creativecommons.org/licenses/by/4.0
Integrated data-driven credit default prediction in Uganda using machine learning models
The prediction of credit facility defaulters is quite a challenge in Uganda, particularly for those without a formal banking history. Existing prediction models cater for prediction using conventional banking records which is not sufficient. The use of integrated data to cater for the unbanked population is required to further enhance financial inclusivity and stability in Uganda’s financial landscape. This study therefore aims at filling this gap by using machine learning techniques on a rich blend of financial data, including mobile money and Fintech (Financial Technology) services, as well as traditional banking records. Several machine learning algorithms used for loan default prediction were compared, such as Random Forest, Logistic Regression, Support Vector Machines (SVM), and Extreme Gradient Boosting (XGBoost). Random Forest Model showed 96.66% accuracy, 79.65% recall, 96.52% precision and 0.85 AUC. XGBoost model was found to have an accuracy of 95.23%; recall, 73.32%; precision, 94.11%; and Area Under the Curve (AUC) of 0.81. However, Random Forest performed best by all metrics with XGBoost following slightly. Logistic Regression showed 89.53% accuracy but had a very low recall at 43.24% and precision at 66.59%. SVM performed averagely with 93.21% accuracy and 62.80% recall all falling below that of XGBoost and Random Forest. Thus, the study revealed the significance of machine learning models like Random Forest and XGBoost for credit scoring prediction. Overall, it will improve the ability of institutions and policymakers to identify potential default borrowers so as to mitigate loan default rates and ensure economic growth in underserved communities through more accurate and inclusive credit evaluation tools.
Copyright (c) 2025 George Muddu, Shefiu Olusegun Ganiyu, Adekunle Olugbenga Ejidokun, Yusuf Abass Aleshinloye (Author) https://creativecommons.org/licenses/by/4.0
Computational optimization of auctioneer revenue in modified discrete Dutch auctions with cara risk preferences
This research presents a computational optimization framework designed to maximize auctioneer revenue in modified discrete Dutch auctions by explicitly incorporating bidders’ risk preferences---modeled independently of wealth through the Constant Absolute Risk Aversion (CARA) utility function---thus enabling the analysis of risk-averse, risk-neutral, and risk-loving behaviors within the auction context. The study models bidders with three distinct risk profiles--risk-loving, risk-neutral, and risk-averse--employing nonlinear programming techniques to optimize expected revenues for the discrete bid levels. Discrete optimization methods are applied to analyze the impact of varying risk preferences, revealing that auctioneer revenue grows nonlinearly with bidder participation. For risk-neutral bidders (\alpha -> 0), revenue increases sharply from \mathscr{R}* = 0.3849 for n=2 to \mathscr{R}* = 0.8179 for n = 20 (a 112.5% increase), but the rate of growth declines significantly beyond n=30, with revenue plateauing near \mathscr{R}* = 0.9454 for n = 100 (a mere 9.5\% increase from n = 30 to n = 100). Similar patterns hold for risk-averse (\alpha > 0) and risk-loving (\alpha < 0) bidders, though the magnitudes differ. Moreover, risk-loving bidders (for \alpha = -0.5) yield \mathscr{R}* = 1.2122 for n = 100, a 28\% higher revenue than risk-neutral case with \mathscr{R}*= 0.9454 and a 61% higher than risk-averse case (for \alpha = 0.5) with \mathscr{R}*=0.7519. This nonlinearity suggests diminishing marginal returns to additional bidders, a critical insight for auction design. The findings suggest that for larger bidder groups, fewer bid levels are sufficient for revenue maximization, with risk-averse behavior decreasing expected returns and risk-loving behavior amplifying them. This computational approach highlights the critical role of risk preferences in auction design, offering a robust mathematical model that can be adapted for broader applications in algorithmic auction mechanisms.
Copyright (c) 2025 Raja Aqib Shamim, Majid Khan Majahar Ali, Mohamed Farouk Haashir bin Hamdullah (Author) https://creativecommons.org/licenses/by/4.0
Corrosion inhibition of carbon steel XC70 in 1M HCl solution using Balanite Aegyptiaca extracts as an eco-friendly inhibitor
The corrosion inhibition effect of Balanites aegyptiaca leaves extracts on carbon steel XC70 in 1 M hydrochloric acid solution has been studied using gravimetric study and Potentiodynamic polarization method. The plant extracts has proven its ability to stabilize metal corrosion, as FTIR curves confirm that extracts has compounds rich in oxygen atom and aromatic compounds. The results show that the inhibition efficiency increases with increase in extract concentration and decreases with rise in temperature. The inhibition efficiency from weight loss studies was found to be more than 90 % at 50 % volumic concentration while this inhibition efficiency was obtained from Potentiodynamic polarization studies at 150 ppm. We also investigated the effect of temperature on corrosion with and without the optimal concentration in the temperature range of 293 to 373 K and calculated the activation energy, enthalpy, and entropy. The thermodynamic results showed that the plant extract particle’s adsorption process on the steel’s surface was endothermic and physical in nature. Tafel curve analysis revealed that our green inhibitor worked as a mixed-type inhibitor, bottled up the corrosion processes of steel X70 in hydrochloric acid, and their adsorption was found to follow the Langmuir and Temkin models.
Copyright (c) 2025 nedjimi mohammed said, Yazid amri, belalem Mohammed Abdelkader, Guerguer Louiza, tlili salah (Author) https://creativecommons.org/licenses/by/4.0
Assessment of the nutritional and phytochemical composition of selected mushroom species grown in Southern Nigeria
Mushrooms are increasingly gaining attention for their nutritional and therapeutic benefits due to their rich composition of essential nutrients and bioactive compounds. However, all-encompassing integrative data on Calocybe indica, Ganoderma lucidum, and Pleurotus djamor grown in southern Nigeria is lacking. This study aims to provide a detailed, parallel evaluation of the nutritional and phytochemical composition of these mushroom species through a multidimensional analysis. The proximate, mineral, and phytochemical contents of the mushrooms were determined following standard analytical methods, while the metabolites were identified using gas chromatography-mass spectrometry (GC-MS). The phytochemical, terpenoid, was of the highest level (2.25 ± 0.05 % to 15.91 ± 0.41 %), with Ganoderma lucidum having the highest value. In the GC-MS chromatograms of the methanol extracts of the mushrooms, the most prominent bioactive metabolites were cis–vaccenic acid (31.32 %) and n-hexadecenoic acid (27.75 %), ergosterol (28.02 %), and linoelaidic acid (37.83 %) for Calocybe indica, Ganoderma lucidum, and Pleurotus djamor, respectively. High amounts of carbohydrates, protein, fiber, and ash were recorded for all the species, with Ganoderma lucidum having the highest fiber content of 34.85 ± 0.74 %. Mg, Ca, and Fe were significantly higher in Ganoderma lucidum, while K is at the highest level in Calocybe indica (30119.05 mg/kg). These findings suggest that these mushrooms are potent sources of vital nutrients, with Ganoderma lucidum having superior antioxidant relevance. This research provides an indispensable basis for mushroom choice, formulation of functional foods and nutraceuticals, and optimization of health-promoting characteristics of the studied mushrooms.
Copyright (c) 2025 Bethel Onyeka Ekute, Muluh Emmanuel Khan, Aloysius Akaangee Pam, Jude Ehwevwerhere Emurotu (Author) https://creativecommons.org/licenses/by/4.0
Isolation and investigation of the structure of silicon quantum dots from rice husk ultrafine silica for possible applications in nanoelectromechanical systems
Silicon quantum dots (SiQDs) are nanostructure semiconducting crystalline particles of silicon, usually less than 10 nm in size. Usually, silicon is extracted from its oxide through a carbothermic process using electric submerged arc furnaces at temperatures exceeding 2000 ºC, a highly energy-intensive method and detrimental to silicon oxide's structural properties, resulting in carbon dioxide emissions. In this work, we propose a two-step green approach involving sol-gel synthesis and solid state magnesiothermic reduction at 700 ºC to produce silicon quantum dots from rice husk ash. This method prevents strain, fracture, and vaporization associated with direct reduction methods at higher temperatures, which emit greenhouse gases and vaporize silicon. The produced silicon quantum dots were characterized using Energy Dispersive Spectroscopy (EDS), Transmission Electron Microscopy (TEM), and X-ray Diffraction (XRD) techniques. A total total yield of 77.76% silicon, with average particle and crystallite sizes of 2.51 nm and 2.69 nm, respectively was observed. The material exhibited a dislocation density of 0.14 (14 %) lines/nm2, strain of 0.0467 (4.67%), stress of 7.94 GPa, Young modulus of 170 GPa, and energy density of 32.50 GJm-3. These indicate robust mechanical properties that suitable for nanoelectromechanical systems(NEMS) fabrication. In addition, this eco-friendly method used in this work utilizes rice husk silica which prevent the use of synthetic and harmful silica precursors. Thus, enhances sustainability and cost-effectiveness in accordance with green synthesis principles and the use of local resources.
Copyright (c) 2025 K. M. Omatola, A. D. Onojah, R. Larayetan, A. O. Ohiani, I. I. Oshatuyi, M. B. Ochang, O. Anawo, P. Abraham (Author) https://creativecommons.org/licenses/by/4.0
Optimizing initial chlorine dosage at an injection point along a water distribution pipe
This study proposed a gradient-based optimization framework for determining the optimal initial chlorine dosage at an injection point along a water distribution pipe, with the aim of ensuring microbial safety and regulatory compliance while minimizing chlorine overuse and associated costs. Leveraging the SNOPT (Sparse Nonlinear Optimizer) algorithm integrated within the COMSOL Multiphysics environment, the approach systematically refined dosing strategies based on temperature-dependent chlorine decay dynamics. Prior to optimization, a uniform dosage of 1 mg/L yielded suboptimal outlet residuals; 0.30 mg/L, 0.23 mg/L, and 0.17 mg/L at 290K, 300K, and 310K, respectively. Post-optimization, precise dosing of 0.66 mg/L, 0.87 mg/L, and 1.16 mg/L achieved the target residual concentration of 0.2 mg/L across the same temperature conditions, enhancing disinfection control by 13-17%. The results demonstrate that this method delivers accurate, adaptive chlorine dosing, reducing the risk of harmful disinfection byproducts (DBPs), improving cost efficiency, and supporting sustainable water quality management. The proposed model is suitable for real-time integration into supervisory control systems, offering a practical pathway for advancing water safety, operational effectiveness, and environmental stewardship.
Copyright (c) 2025 John Tulirinya, Mathew Kinyanju, Samuel Mutua, Asaph Muhumuza (Author) https://creativecommons.org/licenses/by/4.0
Deep neural network model for vertical total electron content prediction at a single low latitude station
Modeling ionospheric parameters at low and equatorial stations is quite challenging due to the nature of the variation in the region. In this study, a Deep Neural Network (DNN) was configured via optimization of its hyperparameters and then trained to predict vertical Total Electron Content (vTEC) at a single low latitude location. Input parameters to the model are universal time, day of the year and solar activity index (EUV / ), while the target parameter is vTEC at a single location. EUV and values were used separately as the solar ionizing index leading to two trained models. The data used for training were for the solar cycle 24 and the data were split into 75 % for training and 25 % for validation. The training process was completed by the number of iterations. In addition, the derived model was also validated using data for the whole of 2000 and 2021 which are years outside the solar cycle 24. For completeness, the two models were also compared with NeQuick 2 model which is a global empirical model. The results obtained showed that the DNN models were able to predict reasonably well within the solar cycle 24 and slightly outperformed NeQuick 2 model. Similar results were obtained when the models were validated in 2021 with DNN slightly performed better that NeQuick 2 model. However, large deviation was recorded in 2000 – the DNN and NeQuick 2 models underestimated vTEC.
Copyright (c) 2025 F. U. Salifu, O. A. Oladipo, E. O. Ebock, B. Nava (Author) https://creativecommons.org/licenses/by/4.0
Eigensolutions and thermodynamic properties constrained by magnetic field of cyclotron frequency
The present work investigates the influence of cyclotron frequency on the energy spectrum and thermodynamic properties of a quantum system. The energy as a function of the quantum number unveils an increase in the system's energy due to the presence of cyclotron frequency, making it open-ended by curtailing its negativity. The screening parameter significantly shapes the system’s energy, increasing at the initial point due to Landau quantization and then monotonically decreasing as a result of weakness of Coulomb interaction. The study also revealed that the parameter a and b impacted the energy differently as the cyclotron frequency altering the system’s confinement behaviours. Similarly, the partition function (Z) and some thermodynamic properties (TP), are analyzed under varying temperatures and parameter conditions. The presence of the cyclotron frequency (CF) reduces the Z and the TP due to Zeeman effect. The TP (H and S) exhibited similar characteristics. Thus, the presence of CF affects the stability of the system. This study finds applications in quantum wells and dots, fusion energy, magnetic quantum computing, and quantum statistical mechanics.
Copyright (c) 2025 C. A. Onate, S. O. Mobolaji, J. A. Akinpelu (Author) https://creativecommons.org/licenses/by/4.0
A hybrid IFR-IDY conjugate gradient algorithm for unconstrained optimization and its application in portfolio selection
This study introduces the Improved Fletcher-Reeves (IFR)-Improved Dai-Yuan (IDY) hybrid conjugate gradient method, which combines the strengths of the IFR and IDY parameters through a minimum-operator strategy to enhance robustness in unconstrained optimization. The method is shown to satisfy descent and global convergence properties under the strong Wolfe line search. Numerical experiments on 134 benchmark functions demonstrate that IFR-IDY achieves superior performance, solving 98 problems more than IFR and IDY and exhibiting faster CPU times and fewer iterations in most cases. The method is also used to solve an IDX30 portfolio optimization problem, which results in an optimal allocation with an expected return of 0.00042 and a risk of 0.000050545. These results highlight the efficiency of IFR-IDY and its practical applicability in real-world decision-making.
Copyright (c) 2025 Diva Marchandra Mulansari, Maulana Malik, Sindy Devila, Ibrahim Mohammed Sulaiman, Dian Lestari, Fevi Novkaniza, Fida Fathiyah Addini (Author) https://creativecommons.org/licenses/by/4.0
Modeling the dynamics of pertussis to assess the influence of timely awareness with optimal control analysis
Pertussis, also known as whooping cough, is a very infectious respiratory disease that can be easily avoided with vaccination. For newborns, whooping cough poses an especially serious risk. In addition to a ”whoop”-like cough, other symptoms include sneezing, nasal congestion, and a runny nose. The bacteria that cause pertussis are called Bordetella pertussis. The upper respiratory system is the main target of the disease, and it is extremely contagious. In this work, a system of nonlinear ordinary differential equations of pertussis has been formulated to examine the impact of early treatment. Through theoretical examination, the positivity and boundlessness of the solution are confirmed. Furthermore, the local stability has been examined using the Jacobian matrix, and the equilibrium points for the system are derived for both the free and the endemic instances, and global asymptotic stability of disease-free equilibrium have been ascertained using the comparison method, which shows that the disease-free equilibrium is globally asymptotically stable if the control reproduction number is less than one. Furthermore, the global asymptotic stability of the endemic equilibrium point was determined using the Lyapunov function of the Goh-Volterra type, which shows that the endemic equilibrium point is globally asymptotically stable if the control reproduction number is greater than one. Numerical experiments are performed to validate the theoretical conclusions. The suggested model has been fitted to real Austrian pertussis data, demonstrating that it is appropriate for the data. The control reproduction number was also used to test the sensitivity analysis of all of the parameters of the proposed model. The results indicate that the effective contact rate is the parameter that is more sensitive to increasing the control reproduction number. In contrast, the awareness rate is the parameter that is most sensitive to decreasing the number of control reproductions, and optimal control analysis has also been performed in this work. Numerical simulation reveals that awareness is the most influential parameter in reducing infection in the population. Moreover, vaccination and treatment are also very important in controlling pertussis in society.
Bio-Maths, Applied maths, Mathematical Epidemiology
Copyright (c) 2025 J. Andrawus, J. Y. Musa, S. Babuba, A. Yusuf, S. Qureshi, U. T. Mustapha, A. Oghenefejiro, I. S. Mamba (Author) https://creativecommons.org/licenses/by/4.0
Analytical resolution of nonlinear fractional equations using the GERDFM method: Application to nonlinear Schrödinger and truncated Boussinesq-Burgers equations
In this paper we develop the Generalized Exponential Rational Differential Function Method (GERDFM) for analytically solving complex nonlinear fractional partial differential equations, with application to the fractional nonlinear Schr¨odinger equation (NLSE) and the M-fractional truncated Boussinesq-Burgers equation. Our approach transforms these PDEs into adapted ordinary differential equations (ODEs), generating exact solutions for various nonlinear laws (Kerr, power, double power, parabolic) while explicitly incorporating the fractional Caputo derivatives of order M ? [0, 1]. The solitonic profiles obtained, illustrated by 2D/3D visualizations, reveal the crucial impact of non-linearity and fractional order on their dynamics, particularly in long memory optical systems and viscoelastic media. A rigorous numerical validation combining a fractional Runge-Kutta method and an L1 scheme confirms the superiority of our solutions, with a relative error < 10?8 (error < 2% near the solitonic peak) and a reduced computation time compared to conventional methods (Tanh-Coth, Sine-Cosine). These results open up concrete prospects for controlling solitons in anomalous dispersion optical fibers and modelling extreme waves in coastal hydrodynamics, while suggesting promising extensions to coupled and stochastic systems in nonlinear optics, fluid dynamics and plasma physics. This work provides significant advances in modeling wave propagation in complex media with memory effects. The GERDFM method’s ability to handle diverse nonlinearities while maintaining computational efficiency makes it particularly valuable for designing optical communication systems and predicting extreme wave phenomena in coastal engineering. Our analytical framework bridges a critical gap between classical soliton theory and fractional calculus applications.
Copyright (c) 2025 Rachid El chaal, Hamid Dalhi, Otmane Darbal, Omar Boughaleb (Author) https://creativecommons.org/licenses/by/4.0
Relativistic correction on bottomia within the gaussian basis function method
In this theoretical research to describe the latest experimental results from the Large Hadron Collider, Belle II, and heavy-ion collisions obtained in high-energy hadronic physics, we include relativistic corrections to improve predictions of the mass spectra of Bottomia resonance states using the Gaussian basis function within the tanh-shaped hyperbolic plus a linear confinement potential in the framework of nonrelativistic and relativistic quantum mechanics under the Schrödinger equation. The relativistic effects of bound states in high energy physics must be described within the framework of approximations or perturbation methods and specific relativistic equations, but in this paper, we provided a mathematically relativistic correction on the bound states mass spectrum; and considering the applied relativistic corrections to the Schrödinger equation using quantum mechanics and quantum field theory principles and high energy approximation. Also, we have helped predict and solve one of the most critical issues of resonance states in particle physics. Current theoretical work is focused on studying this problem for the mass spectra of Bottomia within the refined hybrid potential and based on the modified Schrödinger equation. The mass spectra results agree closely with the experimental and other theoretical data.
Bottomia, Bound state, Hyperbolic potential, Relativistic mass, Schrödinger equation.
Copyright (c) 2025 Arezu Jahanshir, Jalil Naji (Author) https://creativecommons.org/licenses/by/4.0
Appraising raw exhaust pollutant gases emissions from industrial generators using statistics and machine learning approaches
Industrial generators, widely used for backup power generation, emit significant levels of pollutant gases such as carbon monoxide (CO), carbon dioxide (CO2), hydrocarbons (HC), and nitrogen oxides (NOx). These emissions exacerbate air pollution and climate change, while their inhalation adversely impacts human health, leading to respiratory/cardiovascular diseases and increased mortality rates. Raw exhausts of CO, CO2, HC, NOx, and O2 from industrial generators were assessed using a portable analyser. Thereafter, the obtained dataset was analysed using multiple linear regression and Pearson’s correlation to quantify the synergistic impact of generator characteristics, while the study equally trained 70% of the dataset using machine learning (ML) classification models. The result showed that generators’ age and capacity impacted considerably on exhaust concentrations as the diesel-powered generators exhibited higher CO2 and NOx emissions at 76.1% and 7393ppm, respectively, compared to gas-powered generators. For diesel-powered generators, there was a moderate negative correlation at -0.49142 and p-value of 0.03281 for CO and NOx. For the gas-powered generators, the correlation is statistically significant for CO and HC, while there was an inverse association between NOx and O2. The employed ML models achieved high prediction accuracy range of 80.6?93.5 % for exhaust pollutant gases for OGEPA classification status. Based on this study, policy frameworks should be implemented up to impose stringent generator emissions standards to reduce air pollution, invest in expanding/upgrading the national electricity grid to reduce reliance, provide low-interest green loans to finance renewable energy systems, as well as access climate finance mechanisms to subsidise clean energy projects.
Copyright (c) 2025 O. Oderinde, C. O. Ajanaku, C. A. Mgbechidimma, O. A. Orelaja, O. O. Olaide, A. O. Ogundiran, A. A. Ajayi, A. O. Agbeja, C. L. Mgbechidinma, K. D. Oyeyemi (Author) https://creativecommons.org/licenses/by/4.0
Zinc oxide nanoparticles and nanorods: advanced sunscreen ingredients for enhanced UV protection and radiation filtration
Due to its high ability to absorb ultraviolet rays in a wide spectrum, zinc oxide has emerged as the most important element used in the manufacture of sunscreens and cosmetics. This study aimed to determine the composition of zinc oxide nanorods and nanoparticles, as well as their impact on UV ray absorption. This was done by using Field Emission Scanning Electron Microscopy (FESEM-EDS) and Ultra Violet (UV-Visible) spectroscopy to look at sunscreen samples that had different amounts of zinc oxide added to them. We prepared two types of commercial zinc oxide powder using a chemical bath deposition method. After characterizing samples of the two powders using FESEM-EDS spectroscopy, various shapes emerged, with rods dominating in both powders. The length of the structure was 224.7 nm, 9.443 ?m, and the diameter was 75.65 nm, 859.9 nm, respectively. The sun protection factor and the critical wavelength for the prepared samples were calculated using UV-Visible spectroscopy to measure the absorbance. An increasing zinc oxide to a certain extent led to an increase in UV ray absorption in all regions of the UV ray wavelength, with the ideal zinc oxide ratio being. The sunscreen had a concentration of 27.5%, and the use of zinc oxide provided broad protection from ultraviolet rays in all samples at the critical wavelength. In conclusion, increasing zinc oxide concentration in sunscreen increased the sun protection factor, critical wavelength, and UV ray protection.
Copyright (c) 2025 Ammar A. Oglat, Abdallah Al Said, Naser M. Ahmed, Mohammed Dawood Salman https://creativecommons.org/licenses/by/4.0
Response of the magnetospheric convection electric field (MCEF) to geomagnetic storms during the solar cycle 24 declining phase
This article examines the magnetospheric convection electric field (MCEF) fluctuations during seven moderate to severe storms in the declining phase of solar cycle 24. The storms induced by ICMEs were selected based on specific conditions. The primary aim of this study is to assess the influence of geoeffective ICMEs on the MCEF. We conducted a cross-correlation analysis to examine the temporal delays between MCEF fluctuations and geomagnetic indices (Sym-H and AE), as well as the IMF Bz. A linear regression was employed to assess MCEF fluctuations in relation to variations in Sym-H, AE, and Bz. A strong correlation (R = 0.81) was seen between the average transit speed of ICMEs and MCEF fluctuations in the initial phase, underscoring the direct influence of ICMEs on the MCEF. ICMEs with speeds >= 800 km/s cause substantial MCEF variations during the storm's initial phase, with a variation of 0.08 mV/m for every one nT change in IMF Bz. During the complete evolution of the examined storms, fluctuations in the AE index precede those of the MCEF, with time delays between 21 and 44 minutes. MCEF variations exhibit a delay relative to Sym-H index fluctuations, with estimated intervals ranging from 60 to 306 minutes.
Geoeffective interplanetary coronal mass ejections
Magnetospheric convection electric field
Copyright (c) 2025 Nongobsom Bazié, Christian Zoundi, M'BI Kaboré, Alfred Jean Stéphane Dama, Frédéric Ouattara (Author) https://creativecommons.org/licenses/by/4.0
Development of internet of things-based petroleum pipeline topology leak monitoring and detection system using sensors
Transportation of crude oil by pipelines is the safest mode of oil transportation. In Nigeria, over 90\% of oil transported by federally regulated pipelines arrives safely every year. The flow starts from oil fields to flow stations to refineries and export tankers and finally, from refineries to depots. Notably, the transportation of oil by pipeline suffers challenges. The challenges range from natural disasters to attacks and activities carried out by vandals. These activities pose a serious threat to Flora and Fauna and have caused devastating effects on the environment, with remarkable destruction of vegetation cover, water bodies, and arable land. In this study, an Internet of Things (IoT)-Based Petroleum Pipeline Topology Leak Detection and Monitoring System (IoT-BPTLDMS) that is capable of monitoring, detecting, and reporting pipeline topology leakage and reports same to the control room before it graduates to spillage has been developed. This was done by strategically mounting pressure-change detecting sensors along the pipelines which are capable of detecting leakages through changes in fluid pressure and results transmitted with the aid of a Long-Range Wireless Area Network (LoRaWAN) module. The transmitted data captures the date, time, event, and geo-location of the leak site. This data is received in a computer and an Android phone. A prototype was used to study the setup's workings. The prototype controller was programmed using C++ with the Arduino Integrated Development Environment (IDE). The Android Application was assembled with Basic4Andriod. The captured result shows consistency with the area of leakage against the geo-location reported. This shows that this method would be effective in checking and detecting petroleum pipeline leakage, and as such, can solve the problem of quick response to pipeline vandalisation and oil spillage in Nigeria or generally.
Copyright (c) 2025 Paul Tawo Bukie, Idongesit E. Eteng, Eyo E. Essien (Author) https://creativecommons.org/licenses/by/4.0
Hydrodynamic Casson hybrid nanofluid flow across a stretching sheet in the regime of velocity slip and temperature jump,including viscous dissipation, melting, Soret and Dufour effects
This work explores the magnetohydrodynamics (MHD) viscous, incompressible, Casson hybrid nanofluid over a stretched sheet which is a well-known non-Newtonian fluid. The analysis incorporates the effects of viscous dissipation, melting, Soret and Dufour effects, within the frameworks of velocity slip and temperature jump boundary conditions. Copper (Cu) and alumina oxide (Al2 O3 ) have been employed as nanoparticles, while water (H2 O) has been considered as the base fluid. This mixture is used to increase the fluid’s thermal characteristics for better heat transfer efficiency. To simplify the complex governing partial differential equations describing the flow and heat transfer characteristics, similarity transformations were employed, which reduced the system to a set of coupled, ordinary differential equations that are nonlinear. The bvp4c function in MATLAB was used to solve these modified equations numerically. The study looks into the effects of various parameters on flow and heat transfer characteristics, such as the volume fractions of alumina and copper, the Prandtl Number, the Radiation parameter, the Darcy permeability, the Magnetic field parameter, the heat source/sink parameter, melting parameter, the Eckert Number, the Soret number, and the Dufour number. Results indicate that the alumina volume fraction influences the velocity, temperature and concentration profiles. Specifically, the aluminium oxide volume fraction parameter causes increases in profiles of temperature, velocity and concentration. With suction and the Casson parameter, the mass transfer rate increases while the heat transfer rate decreases.
Copyright (c) 2025 B. Laxmi, K. Chand, P. Thakur (Author) https://creativecommons.org/licenses/by/4.0
Contamination levels, occurrence pattern and associated risk of organophosphate pesticide residues in spices and herbs sold in southern Nigeria
This study investigated the contamination levels, occurrence pattern and associated health risks of organophosphate pesticide residues in spices and herbs sold in southern Nigeria. Fifty-two samples of commonly consumed spices and herbs were purchased from multiple locations in southern Nigeria and subjected to extraction using dichloromethane/n-hexane (1:1, v/v). Thereafter, the extracts were analysed for 14 OPPs on gas chromatograph-mass spectrometry. The contamination levels of the$\mathrm{\sum}$14 OPPs in the spices and herbs ranged between 4.96 and 795 ng/g. The average OPP concentrations in the spices and herbs were in the order of diazinone > chlorpyriphos methyl > pyrazophos > isazophos > quinalphos > phosalone > pirimiphos methyl > chlorpyrifos > azinphos ethyl > pirimiphos ethyl > EPN > fenitrothion > pyraclofos > triphenyl phosphate. The OPPs concentrations in the spices and herbs were below the maximum residue limits (MRLs) established by FAO/WHO. The risk estimated using hazard index indicated the absence of non-carcinogenic risk from the intake of these spices and herbs except for seven samples in the case of children intake. Although the findings suggest minimal health risks from OPPs through intake of these spices and herbs, we recommended that there is need for continuous monitoring of spices and herbs sold generally in Nigeria markets for pesticides contamination and the appropriate regulators should establish MRLs for OPPs in foodstuffs in Nigeria and ensure strict compliance with the MRLs of contaminants in food and drugs.
Copyright (c) 2025 Duke Okoro, Oghenenyerhovwo E. Ididama, Godswill O. Tesi, Jude C. Ossai (Author) https://creativecommons.org/licenses/by/4.0