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.
The Editor and Publisher of the Journal of the Nigerian Society of Physical Sciences hereby issue this formal retraction notice for the article titled “Fractional-order modeling of visceral leishmaniasis disease transmission dynamics: strategies in eastern Sudan” by Ghada A. Ahmed, published in Journal of the Nigerian Society of Physical Sciences, Volume 5, 2023, Article ID 1693, DOI: https://doi.org/10.46481/jnsps.2023.1693. The article has been retracted due to errors in the calculations reported in the manuscript. Since the calculations form the basis of the fractional-order mathematical modelling, disease transmission analysis, and resulting conclusions, the identified errors affect the reliability of the findings presented in the article. The retraction decision had previously been reflected on the article page; however, a separate formal retraction notice was not published at that time. This notice is therefore being published now to correct that omission, improve transparency, and ensure that the retraction is properly visible to readers, indexing services, and metadata platforms. The original article should be regarded as retracted and should not be cited as reliable scientific evidence except in discussions relating to the retraction itself. Retracted article: Ghada A. Ahmed, “Fractional-order modeling of visceral leishmaniasis disease transmission dynamics: strategies in eastern Sudan,” Journal of the Nigerian Society of Physical Sciences 5 (2023) 1693. https://doi.org/10.46481/jnsps.2023.1693 Retraction decision date: 06-12-2023 Retraction notice publication date: 26-04-2026
Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0
The Editor and Publisher of the Journal of the Nigerian Society of Physical Sciences hereby issue this formal retraction notice for the article titled “Preparation and Characterization of High Performance Dye Sensitized Solar Cells with Silver Nanoparticles in nanocomposite Photoanode” by Eli Danladi, Jamila Tasiu, and Lucky Endas, published in Journal of the Nigerian Society of Physical Sciences, Volume 2, Issue 1, February 2020, pages 7–11, DOI: 10.46481/jnsps.2020.24 [1]. The article was retracted after the authors notified the journal of an incorrect report of the X-ray diffraction analysis. Since the X-ray diffraction result formed part of the material characterization presented in the article, the reported error affected the reliability of the relevant findings and conclusions. Following the authors’ notification and editorial assessment, the article was retracted to maintain the accuracy and integrity of the scholarly record. The retraction decision had previously been reflected on the article page; however, a separate formal retraction notice was not published at the time. This notice is therefore being published now to correct that omission, improve transparency, and ensure that the retraction is properly visible to readers, indexing services, and metadata platforms. The original article should be regarded as retracted and should not be cited as reliable scientific evidence except in discussions relating to the retraction itself. Retraction notice publication date: 26-04-2026
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
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
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
A novel mathematical model for transmission dynamics of HPV and cervical cancer progression with cancer-reliant awareness
Human papillomavirus (HPV) is a global health problem that causes the vast majority of cervical cancers. { A novel mathematical model for HPV, as it progresses to cervical cancer, was formulated using a system of six ordinary differential equations that incorporates behavioural dynamics in the description of some control measures. In particular, this study introduces a novel chained dependency framework where the awareness parameter depends on Cancer burden, and the screening rate is a function of awareness}. The essential epidemiological features of the model, such as the positivity and boundedness of the model, the basic reproduction number $\mathcal{R}_0$, the disease-free equilibrium, and the endemic equilibrium, are derived. The disease-free equilibrium is shown to be locally and globally asymptotically stable when $\mathcal{R}_0 < 1$. The endemic level of infection is expressed in terms of $\mathcal{R}_0$, and deductions are made from their relationship. Sensitivity analysis is conducted to determine which parameters are of utmost importance using a global sensitivity analysis method called the Partial Rank Correlation Coefficient (PRCC) method. Parameters are set from the literature, and simulation is carried out using the Runge--Kutta 4th order (RK4) method to explore the impact of various parameters on model dynamics. { The results of the analyses not only reveal the impact of awareness campaigns, routine screening programmes, and vaccination in reducing HPV and cervical cancer, but also demonstrate how improved disease outcomes are directly linked to the chained awareness screening structure rather than the usual epidemic dynamics.
Bio-Maths, Applied maths, Mathematical Epidemiology
Basic reproduction number, Local stability, numerical simulation
Numerical Simulation and Mathematical Computation
Copyright (c) 2026 Ogechi Regina Amanso, Jeconia Okelo Abonyo, Phineas Roy Kiogora, Obiora Cornelius Collins (Author) https://creativecommons.org/licenses/by/4.0
Existence and uniqueness results for double jump fractional uncertain differential equations
Fractional uncertain differential equations have been used to model random processes in economics and other fields that exhibit jumps, dependency, and nonlinearities, and which possess uncertainties due to limited data and inadequate models. In this paper, a double V-jump fractional uncertain differential equation (DV-FUDE) is presented as a $\theta^{th}$-order Riemann-Liouville or Caputo fractional uncertain differential equation with the addition of two V-jump independent processes on different filtrations. The equation models systems possessing two sources of uncertain shocks attributed to internal and external factors, respectively. Exact solutions in the case of time-dependent coefficients are given in terms of the Mittag-Leffler function. Sample continuity, existence, and uniqueness for the general Riemann-Liouville and Caputo DV-FUDE are established using the Banach Fixed Point Theorem, under global Lipschitz and linear growth conditions on the coefficients. Some extensions and possible areas of application are highlighted for future research.
Fractional uncertain differential equation
fractional uncertain differential equation.
Fractional Uncertain Differential Equations
Copyright (c) 2026 Philip Ajibola Bankole, Mabel Eruore Adeosun, Sunday Emmanuel Fadugba, Tolulope Fadina, Christopher Thron (Author) https://creativecommons.org/licenses/by/4.0
Numerical solution of fractional advection-diffusion equation with generalized Caputo derivative using shifted ultraspherical collocation method
In this article, we develop an approximate technique for solving a fractional advection-diffusion equation with a generalized Caputo derivative via a finite difference scheme. This technique employed the properties of shifted ultraspherical polynomials, which combine the finite difference scheme for the temporal discretization derivative and express the approximate solution in terms of shifted ultraspherical polynomials. The convergence and the stability of the proposed technique are proved. Numerical examples are considered, and the obtained results are compared with the analytical results and those obtained in the literature to establish the accuracy of the technique. The proposed techniques, based on the generalized Caputo derivative and the properties of shifted ultraspherical polynomials, produce robust results and encompass those obtained using several other families of orthogonal polynomials as demonstrated in the results of the examples considered.
Generalized Caputo Fractional Derivative (GCFD)
Copyright (c) 2026 K. Issa, A. T. AbdulKareem, A D. Adeshola, R. A. Bello (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
Analysis of love-type surface waves in an isotropic thermoelastic layer over a non-homogeneous elastic half-space with interface irregularity
This study explores the dispersion characteristics of Love-type surface waves in a composite elastic media consisting of an isotropic thermoelastic layer resting over nonhomogeneous elastic half-space. A rectangular-shaped irregularity at the interface between the two media is introduced to simulate a geometric discontinuity, which represents more realistic subsurface features. The present work simultaneously incorporates material inhomogeneity, thermoelastic effects, and interface irregularity within a unified analytical framework. The governing equations have been taken using theory of elasticity and solved analytically using Fourier and inverse Fourier transformations. Perturbation method is then applied to derive the dispersion equation for the propagation of Love waves. This dispersion equation is graphically analysed using MATLAB to observe how the dimensionless phase velocity changes with dimensionless wave number for different values of the inhomogeneity parameter and various values of the ratio of irregularity depth to layer height. The obtained results show that both rectangular-shaped interface irregularity and inhomogeneity significantly affect phase velocity, particularly at the lower wave numbers. This study enhances the understanding of surface wave behaviour in complex elastic structures and provides practical implications for subsurface imaging, seismic hazard assessment, and material characterization in civil engineering and geotechnical applications.
Love waves, interface irregularity, thermoelastic layer, dispersion equation, non-homogeneous half-space
Department of Mathematics, University Institute of Sciences, Chandigarh University, Mohali-140413, Punjab, India
Copyright (c) 2026 Suraj Sharma, Ravinder Kumar (Author) https://creativecommons.org/licenses/by/4.0
Mathematical model analysis for maize yield under co-infection of maize streak virus and maize stripe virus diseases with control measures
Maize is a staple food for billions of human globally. It is a very important food crop for sustaining global food security, livelihoods, and economic development. Despite the valuable advantages of maize, its optimal production is affected by several challenges, such as climate change, socio-economic factors, sustainable practices, pests, and diseases. A mathematical epidemiological model for maize yield that takes into account the major factors influencing maize yield, such as co-infection of maize streak virus and maize stripe virus, is developed. The essential dynamical features of the model, such as the basic reproduction number, disease-free and endemic equilibria, are determined and analysed. The model is used to investigate how to improve maize yield under several challenging factors, using Nigeria as a case study. By fitting the model to real data on maize yield in Nigeria, possible long-term model predictions on maize yield in Nigeria were obtained, and parameters of the model were also estimated. Numerical simulations using the estimated parameters illustrated how various control interventions, such as the use of modern technologies, controlling of insect vectors etc can improve maize yield significantly. The results of this study are expected to aid farmers and policy-makers to adopt best farming practices that will improve maize yield and consequently assist in achieving food security globally.
Copyright (c) 2026 Obiora Cornelius Collins (Author) https://creativecommons.org/licenses/by/4.0
Hydrophobicity of golden-phase leaves coated with zinc oxide-based nanocomposite for decorative local products
Golden-phase leaves are widely used in decorative crafts and heritage products, yet their susceptibility to moisture limits long-term durability, especially in humid environments. This study investigates the wetting behaviour of zinc oxide (ZnO)-based nanocomposite coatings designed to preserve the hydrophobicity and service life of golden-phase leaves. The uncoated leaf exhibits strong intrinsic water repellency, with a water contact angle of 151°, attributed to hierarchical surface roughness that supports a Cassie–Baxter-like wetting regime. However, probe liquids with lower surface tension show reduced contact angles, indicating partial transitions toward Wenzel-like wetting. To compare three coating formulations, ZnO/chitosan (brush), ZnO/polyvinyl alcohol (PVA) (spray), and ZnO/chitosan/PVA (spray) were prepared and evaluated. The binary coatings decreased water contact angles to below 85° due to the hydrophilicity of chitosan and PVA. In contrast, the ternary ZnO/chitosan/PVA coating produced a high water contact angle of 136° and an exceptionally low surface free energy of 2.4 mN/m, tend to suppress liquid infiltration. The results demonstrate that the ZnO/chitosan/PVA coating applied by a simple spray process, alters the apparent wetting behavior of a naturally hierarchical biological substrate. This experimental observation of wettability enhancement on a natural surface complex morphology-dominated is relevant to preservation of decorative natural materials.
Copyright (c) 2025 Patchara Pholnak, Ratchaneewan Siri, Palakorn Boonsai, Autthaphol Theppaya, Chitnarong Sirisathitkul (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
Factors influencing the thermal stability of HEMA polymer gel dosimeters for clinical radiotherapy
Thermal stability is an essential feature required for practical applicability of gel dosimeters in radiation therapy planning system (TPS). This study pioneers a comprehensive experimental study of various factors that influence thermal stability of Polymer Gel Dosimeters (PGDs) by investigating the impact of gelatin source and its weight fraction (WF), type and WF of antioxidant, presence of maltose as a disaccharide additive, and the storage time post manufacturing, on the thermal properties of 2-hydroxymethyl methacrylate (HEMA) PGD. Results show that in terms of fast gelation and gel strength, gelatin from bovine skin outperforms gelatin from cold water fish, withstanding temperature up to 11 ?C aboves its Tm, and tetrakis(hydroxymethyl)phosphonium chloride (THPC) outperforms ascorbic acid (AscA), and sample with maltose additive outperforms sample without maltose. The melting rate (Rm) increases with the temperature difference above Tm, and storage time post manufacturing, improves the thermal stability. These findings contribute to the identification of the causes of gel instability and propose the possible solutions that could lead to more accurate assessments and maintenance of dose distribution in three-dimension (3D), and to extend the shelf life of PGDs.
Copyright (c) 2026 Muhammad Alhassan, Azhar Abdul Rahman, Iskandar Shahrim Mustafa, Kabiru Alhaji Bala (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
Dynamics of the Earth’s magnetopause’s subsolar location during solar cycle 24 in relation to the phases of geomagnetic storms of CME origin
This article analyses the response of the subsolar position (Ro) of the Earth’s magnetopause to geo-effective ICME storms in solar cycle 24, ranging from minor to extreme intensity, based on the model developed by Shue et al. (1998) and 1-minute OMNI data. The study combines a phase analysis of representative storms with an analysis of the influence of Ro variability on solar wind parameters, without phase distinction (correlations, time lags, Granger causality, and adjustments). The results show that the dynamics of Ro are driven almost exclusively by Pd in the minor and moderate storms studied, while a synergistic shift appears in strong and extreme storms, where magnetic reconnection or even magnetopause erosion becomes decisive. The crossing of the magnetopause at the subsolar point of the geosynchronous orbit (<6.6 Re) is a signature of the main phase of the storm on 22 June 2015 (strong) and the initial and main phase of the storm on 17 March 2015 (extreme). The autocorrelation correction confirms the robustness of the high correlations observed. The relationships between Ro and Pd remain linear except for the extreme event, while Bz requires polynomial adjustments in most of the events studied. Variations in Pd and N precede those in Ro by 1 min to 3 min and significantly influence those in Ro, with a maximum effect at lag = 0 min in almost all events. The predominant response of Ro to the magnetic constraint imposed by B is delayed, with lag varying from 30 min to 7 min depending on the event, except in the extreme case where lag = 0 min, controlled by the structure of the magnetosphere, and Bz plays a secondary role except in the extreme case where it contributes to magnetic reconnection and magnetopause erosion.
Copyright (c) 2025 Boukary DAMIBA, Christian ZOUNDI, Abdoul Kader SEGDA (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
An inverse physics-informed neural network (I-PINN) framework for parameter estimation in mixed convection and melting effects
An inverse physics-informed neural network (I-PINN) framework is developed for joint parameter estimation and field reconstruction in steady mixed convection with melting in a porous medium. Focusing on the laminar boundary layer of an Al2 O3 –Cu/water hybrid nanofluid over a vertical melting surface, the approach treats the mixed-convection parameter ? and the melting parameter M as trainable variables and fits sparse, noisy temperature measurements while satisfying the coupled similarity ODEs and boundary conditions. A robust training strategy combining data-guided curriculum learning, self-adaptive loss weighting, gradient clipping, and a hybrid Adam–L-BFGS optimization achieves accurate recovery and robust uncertainty quantification on synthetic benchmark data. The dominant parameter lambda is identified with below 0.5% relative error even with as few as eight sensors. The reconstructed temperature and velocity fields remain smooth and physically consistent across unmeasured regions. Notably, the method remains stable in the challenging opposing-flow regime near separation (lambda = -1.354, M = -0.4), demonstrating the promise of I-PINNs for parameter discovery, model calibration, and digital-twin development under limited data.
Copyright (c) 2026 Majid Khan Bin Majahar Ali, Shahida Shahnawaz (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
A fluorescent copper(II) complex based on 4,4-oxybisbenzoic acid and benzimidazole for selective detection of nitroaromatic compounds
Nitroaromatic compounds (NACs) are electron-deficient aromatic molecules extensively used in explosives, dyes, and pesticides, and their high toxicity and environmental persistence pose serious risks to human health and ecological systems. Consequently, the development of sensitive, selective, and portable sensing platforms for NAC detection is of significant importance. In this work, a copper-based coordination complex, [Cu(Oba)2(Beim)(H2O)] (1) (H2Oba = 4,4’-oxybisbenzoic acid; Beim = benzimidazole), was synthesized via a conventional method and fully characterized using standard instrumental techniques. Infrared spectroscopy confirmed the coordination environment, with characteristic bands observed at 1666 cm-1 (vC = O), 1243 cm-1 (vC - - N), and 3061 cm-1 (vN --H). The complex exhibits strong fluorescence emission at 490 nm and good thermal stability. Fluorescence sensing studies revealed a significant quenching response in the presence of NACs, particularly 4-nitroaniline. The sensor demonstrated a low limit of detection (LOD) of 1.46 ppm and a high Stern–Volmer quenching constant (KSV = 9.16 × 104 M-1) towards 4-nitroaniline, indicating excellent sensitivity and selectivity. Furthermore, recyclability experiments showed that the complex could be reused for up to four sensing cycles without significant loss of performance. These results highlight the potential of the copper coordination complex as an efficient and reusable fluorescent sensor for nitroaromatic compounds.
Copyright (c) 2026 Victoria T. Olayemi, Adetola C. Oladipo, Vincent O. Adimula, Ayobami C. David, John O. Abedoh, Basheer A. Jaji, Adedibu C. Tella (Author) https://creativecommons.org/licenses/by/4.0