FUDMA JOURNAL OF SCIENCES

DESIGN AND SIMULATION OF A HIGH-GAIN DUAL-BAND MICROSTRIP PATCH ANTENNA ARRAY FOR 26/28 GHz 5G APPLICATIONS

Muhammad A. Yusuf, Mutari Hajara Ali — Mon, 31 Mar 2025 00:00:00 +0000

This paper presents a high-gain dual-band microstrip patch antenna array design and simulation for 26/28 GHz 5G applications. The 26 and 28 GHz bands are particularly notable among the existing bands for millimeter-wave applications due to their wide bandwidth and lower absorption rates. The antenna is developed in the CST simulation environment on a Rogers RT5880 substrate with a thickness of 0.508 mm, a relative dielectric permittivity of 2.2, and a loss tangent of 0.0009. The Rogers RT substrate is chosen for its low dielectric loss, controlled dielectric constant, environmental stability, ease of fabrication, and high reliability, making it ideal for high-frequency and high-performance applications. The transmission line model method is used to calculate the antenna dimensions designed to resonate at 26/28 GHz. To achieve high gain and wide bandwidth, arraying and slotting techniques are applied to rectangular patch antennas, as these methods significantly enhance gain, bandwidth, directivity, and radiation pattern control, making them suitable for advanced communication applications. The proposed 1×2 patch antenna array, with dimensions of 33.4 × 21.6 × 0.508 mm³, is designed using a tapered feedline. The antenna array resonates at 26.27 GHz and 28.0 GHz, achieving return losses of -16.55 dB and -31.78 dB, bandwidths of 0.58 GHz and 1.54 GHz, VSWR values of 1.35 and 1.05, gains of 9.12 dB and 12.43 dB, and directivities of 9.77 dBi and 13.05 dBi, respectively. The antenna exhibits higher gain and directivity compared to existing array designs in the literature. This cost-effective and compact antenna array is...

EFFECTS OF AGROCHEMICALS AND THEIR IMPACT ON SOIL QUALITY IN PART OF SUDAN SAVANNAH ZONE OF NORTHWESTERN NIGERIA

Isah Usman Hassan, Yusuf Idris Garba, Ahmad Hussain — Mon, 31 Mar 2025 00:00:00 +0000

The use of agrochemicals causes a number of environmental issues, including harm to human health, contamination of groundwater and other aquatic habitats, and soil degradation that lowers soil quality and turns many formerly productive agricultural lands into unproductive ones. This study assessed the effect of agrochemicals on soil quality in the area. A survey was conducted among 331 farmers from seven villages in Bunkure Local Government Area Kano State. Soil samples were also collected and analyzed to determine various soil parameters (OC, P, N, CEC, Ca2+, Na2+, Mg2+ and K2+). Questionnaire was used to obtain information on the farmers knowledge and perception regarding agrochemical application and impact to soil quality. The results revealed that a majority (78%) of the farmers had been using agrochemicals for more than four years, with most (76%) applying those more than twice per year. Furthermore, a significant proportion (61%) indicated awareness of the impact of agrochemicals on soil quality. In addition, findings indicated that 94% of the respondents believed that the use of agrochemicals affected soil quality. Among them, 83% reported a positive effect on soil quality, while 10% observed a negative effect. Only 4% perceived no effect of agrochemicals on soil quality. The amount of Organic Carbon, Phosphate, Nitrogen, and Cation Exchange Capacity (CEC) were found to be within the permissible limits set by the World Health Organization (WHO) with exception of phosphate. Additionally, the cation distribution in the soil profile followed the order: Ca2+ > Na2+ > Mg2+ > K2+. The average concentrations...

COMPARATIVE ANALYSIS OF THE RATE OF VITAMIN C DEGRADATION IN LETTUCE (LACTUCA SATIVA) TREATED WITH VARIOUS PRETREATMENT SOLUTIONS

Emenike Fidelis Awagu, Chinedu Henry Okoroafor — Mon, 31 Mar 2025 00:00:00 +0000

Lettuce is a highly perishable leafy vegetable that faces significant postharvest challenges, including water loss, browning, microbial contamination, and ethylene sensitivity. These issues lead to reduced shelf life, economic losses, and food waste, affecting both farmers and consumers. This study aimed to establish a kinetic model for the breakdown of ascorbic acid in lettuce via computer simulations. The vegetable samples were examined using high-performance liquid chromatography (HPLC) to assess the ascorbic acid (AA) content of the vegetables after they were dipped at various time intervals. This consists of an isocratic elution procedure with ultraviolet-visible detection at 245 nm. The average coefficient of determination (R²-value), was greater than 0.9088, indicating that the AA degradation in the experiment followed a first-order kinetic model. Using the integrated law approach, rate constants of 0.0135, 0.0460, and 0.0341 k (min^-1) and half-lives of 51.3442, 15.0684, and 20.3269 minutes for lettuce dipped in NaCl, SB, and SM, respectively were determined. The Arrhenius equation was used to calculate the activation energies of 161.5341, 84.2009, and 48.6334 kcal/mol. Time series analysis was used to predict the amount of vitamin C at point "70" (Y-INTERCEPT), which was 2.3167, 0.1438, and 0.9561 mg/100 g. In(C): 6.800551, 6.570627, and 6.630127 were obtained when the kinetic models were constructed using the expected initial concentration, processing time, and observed contents respectively. This suggests that In(C) is directly influenced by the initial vitamin C concentration, with an In(C_o) concentration of 898.41 mg/100 g, a rate constant, and time. The best result was obtained by...

CURRENT INCIDENCE OF ANTIBIOTIC RESISTANT BACTERIA OF UROLOGIC BACTERIA FROM PATIENTS WITH URINARY TRACT INFECTION AT A HEALTHCARE FACILITY IN SOUTHWEST NIGERIA.

Mon, 31 Mar 2025 00:00:00 +0000

Uropathogenic bacteria are known to be significant pathogens responsible for urinary tract infections (UTIs). UTIs are among the most prevalent infectious diseases, affecting millions of people worldwide, and are a significant healthcare burden. The study determined the antibiotic susceptibility patterns of uropathogenic bacterial isolates obtained from UTIs at a study location in Ekiti-State, Nigeria. Fifty Gram-negative (8 E. coli, 25 K. pneumoniae and 17 P. aeruginosa) and 6 Gram-positive (6 S. aureus) bacterial isolates were obtained from patients referred to the laboratory. Each isolate was identified accordingly using conventional biochemical test. All bacteria recovered were subjected to antibiotic susceptibility tests using the agar disk diffusion method. The bacteria were further tested presumptively for the formation of biofilms. All the Gram-negative bacteria were resistant to ceftazidime 50(100.0%). Furthermore, the Gram-negative bacteria showed the least resistance to chloramphenicol 17(34%) and ciprofloxine 23(46%). All the S. aureus strains showed elevated resistance against the antibiotics tested. Thirty five multiple antibiotic resistance patterns were observed among the isolates and the most prominent patterns were observed as Crx-Van-Ctr-Ctx-Cpz-Tet-Gen-Mem-Cot-Amk, Crx-Van-Ctr-Ctx-Cpz-Tet-Cot-Gen-Mem-Cip-Amk and Crx-Van-Chl-Ctr-Ctx-Cpz-Tet-Cot-Gen-Mem-Cip-Amk. The research has shown that multidrug resistant bacteria in UTI is a serious healthcare problem and efforts must be made to enforce strict antibiotic treatment regimen to prevent the emergence and spread of antibiotic resistant bacteria in clinical settings.

INCIDENCE OF Echinococcucus granulosus IN OWNED DOGS IN LOKOJA METROPOLITAN, KOGI STATE. NIGERIA

Mon, 31 Mar 2025 00:00:00 +0000

Echinococcosis is a zoonotic disease affecting both animals and human with significant health hazard and economic impacts. A study to evaluate the incidence of E. granulosus was carried out on dogs from six study sites in Lokoja, Kogi State. Faecal samples from 300 dogs were collected and examined for the presence of E. granulosus cyst microscopically. A designed questionnaire was used to obtain both extrinsic and intrinsic information on the sampled dogs from their owners. Out of the 300 dog faecal samples screened, 59 had E. granulosus eggs with overall prevalence of 19.66%. Otokiti study unit had highest prevalence of 28.57%, GRA had the lowest prevalence (4.76%). With regards to sex, male and female dogs had a prevalence of 19.20% and 20.33% respectively. In terms of season, highest prevalence of 19.05% and lowest prevalence of 0.00% was recorded during rainy and dry season respectively. The incidence infection rate showed statistical significance with a (P< 0.05) relation to season. Free-range dogs recorded a prevalence of 22.69% while a prevalence of 8.06% was recorded in dogs reared under intensive condition (P< 0.05). The result from this study revealed the presence of E.granulosus in the study area. Therefore, appropriate and regular deworming of dogs should be undertaken as well as awareness campaigns to educate the masses on the preventive measures is highly recommended to reduce risk of E. granulosus transmission to humans.

BIODEGRADATION POTENTIAL OF INDIGENOUS FUNGI ISOLATES FROM WASTE ENGINE OIL CONTAMINATED SOIL

Kingsley E. Enerijiofi, Abigeal A. Enitan — Mon, 31 Mar 2025 00:00:00 +0000

The anthropogenic release of waste engine oil in the environment causes environmental and public health risks. This study aimed at determining the biodegradation potentials of indigenous fungi isolates on waste engine oil. Waste engine oil tainted soils were taken from five different automobile workshops in Benin City. They were analysed using standard laboratory methods. Five fungi isolates; Penicillium, Fusarium, Aspergillus, Trichoderma and Geotrichum species were isolated and screened for their potential to use engine oil as carbon source. Penicillium sp., Fusarium sp. and Aspergillus sp. had the highest and were used for the bioremediation studies. The pH, electrical conductivity, total nitrogen, total hydrocarbon content and optical density were recorded for 25 days at 5 days interval with different oil concentrations (10%, 20%, 30%, and 40%) to monitor the process. The results obtained showed that pH and total hydrocarbon content values were decreasing with increasing incubation time. Penicillium sp. gave the highest electrical conductivity value of 501 us/cm at 30% contamination level at day 25 while Fusarium sp. had the lowest, 239 us/cm at 40% contamination level at day 5. The electrical conductivity and optical density values were increasing with increased incubation days. Penicillium sp. gave the highest increase in the nitrogen content of 0.91mg/l at 30% contamination level. The study showed that Penicillium sp., Fusarium sp. and Aspergillus sp. were able to biodegrade waste engine oil and therefore recommends that they be used to clean up waste engine oil.

SYNTHESIS, CHARACTERIZATION AND ANTI-MICROBIAL ACTIVITIES OF SCHIFF BASE DERIVED FROM 2-AMINOBENZENETHIOL AND 4-NITROBENZALDEHYDE AND ITS Mn(II), Fe(II) AND Co(II) COMPLEXES

Alkasim Alhassan Umar, Safiyanu Adamu Lame, Aminu Abdulkarim — Mon, 31 Mar 2025 00:00:00 +0000

A Schiff base was prepared by the condensation of 2-aminobenzenethiol and 4-nitrobenzaldehyde. Metal (II) chlorides were refluxed with the prepared Schiff base affording the corresponding metal(II) complexes. The synthesized compounds were characterized based on T-IR, solubility test, melting point/decomposition temperature, molar conductance, magnetic susceptibility, UV-visible spectroscopy and elemental analysis. IR spectra of the Schiff base indicated the azomethine (-C=N-) peak at 1596cm-1, which is shifted in the spectra of the complexes. The Schiff base melts at 160oC, whereas the chelate decomposes within the range of (220oC -232oC). The Elemental analysis revealed the metal to ligand ratio as 1:2. Molar conductance values (11.03 -1cm2mol-1 15.93 -1cm2mol-1) showed non- electrolytic nature of the complexes, magnetic susceptibility values of the complexes were recorded at the range (4.51BM -5.85BM). The synthesized Schiff base and their respective complexes were screened for their anti-microbial activities against some selected pathogenic bacteria (Staphylococcus aureus, and Escherichia coli) and fungi (Aspergillus niger and Candida albicans), the Schiff base shows moderate activity at 6 -15mm zone of inhibition, while the metal(II) complexes show higher activity with the increased in concentration. Moreover, antifungal data revealed an appreciated activity (6 18) mm zone of inhibition against all fungal isolates, which is lower than the standard.

ASSESSMENT OF RADON CONCENTRATION AND EXCESS LIFE CANCER RISK FOR WATER SAMPLES IN FEDERAL UNIVERSITY DUTSE (FUD), JIGAWA STATE, NIGERIA

Mon, 31 Mar 2025 00:00:00 +0000

Radon, a major cause of lung cancer, can be found in groundwater as it emanates from rocks and soil. The risk increases by 16% for every 100 Bq/m³ rise in long-term exposure. Even low radon levels, particularly from groundwater, pose health risks. The WHO estimates radon causes 3% to 14% of lung cancers, with risk rising proportionally to exposure. Six underground water samples (borehole) from within and outside FUD were analyzed using a Liquid Scintillation Counter at CERT in Zaria. Samples were collected from the Senate Building and student hostels. The mean radon concentration was 21.723 Bq/L, below the WHO (2017) and UNSCEAR (2020) limit of 100 Bq/L but above recommended levels of 10-11.1 Bq/L. Annual effective doses for inhalation and ingestion were 0.055, 0.161, 0.237, and 0.278 mSv/year for adults, children, and infants, with ingestion doses exceeding WHO limits. The cancer risk from ingestion exceeded the WHO standard of 2.9E-4, suggesting the water is not safe for drinking without treatment.

BANDWIDTH ENHANCEMENT IN DOHERTY POWER AMPLIFIERS: A COMPARISON OF CONVENTIONAL AND INVERTED ARCHITECTURES

Mon, 31 Mar 2025 00:00:00 +0000

Conventional Doherty power amplifiers (DPAs) face bandwidth issues due to poor impedance matching and input phase design. This paper explores ways to enhance DPA performance in frequency response. The study focuses on optimizing output matching network parameters and the input phase slope between main and auxiliary amplifiers to improve bandwidth efficiency, especially for mobile wireless applications.We calculate the voltage standing wave ratio (VSWR) for each DPA amplification stage at different power levels using MATLAB. We examine conventional and inverted DPA configurations at 2.5 GHz within the 2 GHz to 3 GHz range, utilizing an NXP GaN-based FET transistor model. The two-stage architectures include main amplifiers in Class B and auxiliary in Class C modes, analyzed at peak and back-off levels. Our results indicate that the inverted Doherty amplifier achieves a 40% fractional bandwidth compared to the 8% of the conventional DPA at a VSWR of 1.2, showing better performance due to greater parameter flexibility. These findings are significant for improving RF efficiency in 5G base stations and future wireless networks.

GENETIC ANALYSIS OF SEED SIZE AND SEED RELATED TRAITS IN SELECTED GROUNDNUT (Arachis hypogaea L.) GENOTYPES

Mon, 31 Mar 2025 00:00:00 +0000

Breeding groundnut genotypes with larger seed size enhances consumer appeal. This study investigated the genetic variability, inheritance, and relationships of seed size and yield-related traits in Arachis hypogaea L. using a five-parameter genetic model and correlation analysis. Two crosses, ICGV 188105 × Samnut 24 (Cross 1) and its reciprocal (Cross 2), were evaluated to F3 generations at Institute for Agricultural Research (IAR), Samaru, during the 2021/2022 season. Significant variation was observed for seed size (SS1.506 mm), seed length (SL; 11.187 mm), seed width (SW; 7.409 mm), pod length (PL; 26.978 mm), hundred seed weight (100-SW; 42.705 g), and hundred pod weight (100-PW; 93.238 g). High broad-sense heritability (H² > 70%) and moderate to high phenotypic (PCV: 6.33%–38.36%) and genotypic coefficients of variation (GCV: 5.89%–38.79%) suggest strong potential for genetic improvement, particularly in Cross 2. Additive, dominance, and epistatic effects were significant for seed size and related traits, indicating complex genetic control. Strong positive correlations (p < 0.001) were observed between SS and SL (r = 0.87–0.90), SW (r = 0.85–0.91), 100-SW (r = 0.81–0.83), and 100-PW (r = 0.69–0.93), while flowering time showed weak, non-significant associations. These findings highlight promising opportunities for selecting larger seeds and related traits while allowing independent manipulation of flowering time. We recommend implementing recurrent selection to capitalize on additive effects while maintaining heterozygosity, with Cross 2 showing superior potential for developing varieties with larger seeds and higher yield simultaneously.

A STUDY OF HYBRID FIXED POINTS ON SEMIGROUPS OF TRANSFORMATION

Abubakar Abdulkarim, A. A. Muhammad, A. Abdullahi — Mon, 31 Mar 2025 00:00:00 +0000

Fixed point theory plays a fundamental role in mathematical analysis, algebra, and topology, with applications spanning differential equations, game theory, and computer science. This study extends classical fixed point results by exploring hybrid fixed points within semigroups of transformation. Hybrid fixed points generalize standard fixed points by incorporating auxiliary functions, allowing for broader applications in iterative methods and computational mathematics. We establish key results on hybrid fixed points by considering contractive and nonexpansive mappings in semigroups. Using Banach’s contraction principle and related fixed point theorems, we prove the existence and uniqueness of hybrid fixed points under suitable conditions. Notable results include hybrid contractions, asymptotic regularity, and their implications in complete and compact metric spaces. Examples illustrate the theoretical findings, demonstrating hybrid fixed points in transformation semigroups.

DESIGN OF AN EFFICIENT POWER MANAGEMENT SYSTEM FOR SOLAR-POWERED UAVS: A SYSTEMATIC APPROACH

K. P. Ter, M. S. Yakubu, Muyideen O. Momoh, G. E. Abbe, T. E. Agov, O. C. Alioke — Mon, 31 Mar 2025 00:00:00 +0000

As the demand for sustainable and efficient energy sources increases, integrating solar power into UAV operations presents a viable solution. Conventional MPPT controllers for solar-powered UAVs suffer from slow response times and inefficiencies under dynamic environmental conditions. This study proposes an enhanced power management system integrating FLC with MPPT for superior energy efficiency. The proposed power management design is achieved with the implementation of the Perturb and Observe (P and O) algorithm coupled with a Proportional-Integral (PI) controller to achieve Maximum Power Point Tracking (MPPT). The P&O algorithm was chosen for its simplicity and widespread adoption in MPPT applications, while PI control ensures stable convergence to the MPP. The integration of FLC further improves adaptability in fluctuating irradiance conditions. This approach ensures that the UAV operates at optimal power output levels under varying environmental conditions, specifically temperature solar irradiance. Additionally, a Fuzzy Logic Control (FLC) mechanism is employed to dynamically adjust the power output based on real-time data, ensuring optimal performance and stability. The results gotten from the simulations show that the FLC and the PI based on P & O algorithm returned a settling time of 0.01 seconds and 0.45 seconds respectively. The result showed that the fuzzy logic controller achieved a settling time 97% faster than the PI based on P & O algorithm. This research contributes to the development of more sustainable UAV technologies, paving the way for broader applications in various fields, including environmental monitoring and disaster response.

ASSESSMENT OF GEOMETRIC CONSISTENCY OF THE NIGERIAN ADMINISTRATIVE BOUNDARIES DATASETS FROM DIFFERENT SOURCES: THE NEED FOR DATA HARMONY AND STANDARDIZATION

Peter Emmanjay Adaviruku — Mon, 31 Mar 2025 00:00:00 +0000

Precise administrative boundaries demarcation facilitates effective governance, policy making, resource allocation and the delivery of public services. The delineation of administrative boundaries in Nigeria has been an ongoing challenge, with several disputes and boundary adjustments over the years. Different sources of datasets on Nigerian administrative boundaries exhibit inconsistencies, leading to discrepancies and misalignment. The aim of this study therefore is to assess the geometric consistency of the Nigerian administrative boundaries datasets from different sources. The datasets were sourced from the Office of Surveyor General of Federation (OSGoF), Geo-Referenced Infrastructure and Demographic Data for Development (GRID3), Global Administrative Areas (GADM) and Divas GIS. These datasets were analyzed in ArcGIS 10.8 for alignment and discrepancy. The findings revealed that the Global Administrative Areas datasets showed general good alignment for the Nigerian national boundary. On the contrary, the datasets from GRID3 and Divas GIS have gross misalignment. Furthermore, the misalignment observed in the datasets is generally prominent in the eastern part where Nigeria shares border with Cameroon. Significant discrepancies were observed between the datasets at all level of boundaries from the various sources compared. The result also revealed that the Nigerian national boundary from the Office of Surveyor General of Federation is 912,153.24 km² in area, while datasets from Divas GIS is -1,991.09 km² (-0.22%) smaller, GADM is -1,991.09 km² (-0.22%) lower and GRID3 is 2,330.75 km² (0.26%) higher than OSGoF dataset. The study therefore concluded that these discrepancies could have a significant impact on spatial analysis, resource allocation, and decision-making processes.

EVIDENCE OF ANOPHELES RESISTANCE TO PYRETHROID PESTICIDES: REPORT FROM GADAU KATAGUM ENDEMIC REGION BAUCHI STATE, NIGERIA

Mon, 31 Mar 2025 00:00:00 +0000

Malaria continues to pose a significant health issue negatively. The high number of cases requires prevention, including controlling the Anopheles gambiae s.l., mosquito. One of the control methods is the use of insecticides containing pyrethrin. WHO tube Bioassays in Anopheles gambiae s.l., to determine resistance from pyrethroids expose in F1 adult mosquitoes to insecticides and a sensitivity test to temephos, measuring the activity of non-specific alpha and beta esterase enzymes. This study determined Anopheles gambiae s.l., resistance from larvae to adult. The bioassay was used for the temephos sensitivity of Anopheles larvae. The LC99 value was analyzed using probit and compared with the diagnostic. WHO susceptibility test was conducted to determine pyrethroid resistance from adult mosquitoes. A mortality of less than 90% was declared as resistant. Measurement of alpha and beta esterase levels used Lee's microplate assay technique based on visual identification and absorbance value. Anopheles gambiae s.l., were resistant to both class of pyrethroids. Adult mosquitoes have recorded resistant to both class of type i and ii pyrethroid with increase in time reaching about 60% with cypermethrin. At 24 hours Mortality Rates showed Cypermethrin with the highest at 90% followed by Permethrin (80%), Deltamethrin (75%), and Tetramethrin (70%). Based on the alpha esterase activity test, it was found that most of the mosquitoes showed very sensitive meanwhile, most of the mosquitoes were moderate resistance. This study suggests that Anopheles gambiae s.l., the population from the endemic region in Bauchi, Nigeria are indicated to develop resistance to the pyrethroids insecticides.

CONCURRENT PREDICTION OF DIABETES AND HYPERTENSION USING DEEP LEARNING

Abubakar Bello Bada, Ahmad Baita Garko, Danlami Gabi, Musa S. Argungu — Mon, 31 Mar 2025 00:00:00 +0000

Early detection of diabetes and hypertension is essential in preventing severe complications caused by the diseases. This study developed a prediction model using Feed-Forward Deep Neural Network architecture to predict the diseases. A custom dataset generated by combining features from PIMA Indian dataset and PPG-BP dataset is used in training the model. It achieved 93% accuracy in predicting the diseases. Precision and recall scores were also noteworthy, with 95.5% and 94% for concurrent prediction respectively. These results highlight the model’s balanced performance and reliability in real-world healthcare applications. The study addressed limitations in existing single-disease prediction models by focusing on concurrent prediction, which captures the interrelated nature of diabetes and hypertension. Transfer learning played a crucial role in enhancing the model’s performance, taking advantage of pre-training of models to overcome challenges like limited labelled datasets and help in making the concurrent prediction possible by sensitizing the model with features relevant for individual disease. This approach reduced computational overhead and improved generalization, making the model practical for deployment in resource-constrained healthcare settings. Feature selection and engineering, driven by Recursive Feature Elimination (RFE) and domain knowledge, ensured the inclusion of the most relevant attributes, further optimizing the model’s predictive accuracy.

INTEGRATED GEOPHYSICAL METHOD FOR GOLD EXPLORATION IN BIRNIN GWARI, KADUNA STATE NIGERIA

Olanrewaju C. Alaba, Musiliu Adebanji Gbolagade, Victor Abioye Akinbinu — Mon, 31 Mar 2025 00:00:00 +0000

Birin Gwari is well recognised for having a wealth of minerals, particularly gold deposits, but its exploration efforts based on the use of single method have resulted to inaccurate results when it comes to detecting mineralisation zones and target accuracy. This problem was addressed by combining induced polarisation (IP) and electrical resistivity imaging (ERI) surveys techniques to further investigate the interpreted aeromagnetic data of the study. This combined technique improved subsurface characterization of the identified gold-mineralized zones with detail geological information. The study adopted GDD IP and electrical resistivity imaging survey equipment to probe further the selected nine IP profiles of delineated anomalous from the aeromagnetic survey. The results from the 2-D inverted IP - resistivity models revealed that 30 out of 34 of the anomalous zone with high chargeability and high to average resistivity were identified. Also, 33 of the IP profiles were highly charged, and their chargeability increased with depth. Meanwhile, 29 of the delineated anomalous has a width length less than 10 m while 5 has greater than 10 m. However, the depth to top length of the 34 anomalies varied from 5 to 81 m. Therefore, the study came to the conclusion that the geophysical parameters of each of the identified anomalous and the maps of mineral prospective priority targets should be served as a reference for core drilling of the suggested anomalous points.

NUMERICAL SOLUTION OF FIRST AND SECOND ORDER DIFFERENTIAL EQUATIONS USING THE TAU METHOD WITH AN ESTIMATION OF THE ERROR

Samuel Adeleye Egbetade, Abimbola Latifat Adebisi — Mon, 31 Mar 2025 00:00:00 +0000

The Subject of Numerical methods is an important aspect of ordinary differential equations. It is useful in providing solutions to a wide variety of complex differential equations arising from engineering, physical and biological sciences, health and other allied disciplines which are difficult to tackle by exact methods. Numerical approximations of differential equations of one and higher order have been provided using Euler Method, Tau Method, Runge-Kutta Method, Adams-Bashforth Method, Milne Simpson predictor-corrector Method, Adams-Moulton linear multistep method and a host of others. In this paper, we discussed the application of tau method for solving first and second order initial value problems of ordinary differential equations. Numerical examples are given for the sake of illustration of the method. To validate the accuracy of the method, we compare the approximate solutions obtained with exact solutions. By estimating the error, it is observed that the error decreases as the order of Tau approximations increases. This showed the performance and computational efficiencies of tau method.

IN VITRO AMELIORATIVE POTENTIAL OF SOME ORGANIC ACID IDENTIFIED FROM BOSWELLIA DALZIELII STEM BARK EXTRACT AGAINST FREE RADICALS

Musa Bashir, Usman Mohammed Jajere, Shade Omolabi — Mon, 31 Mar 2025 00:00:00 +0000

Due to their safety and availability, medicinal plants are natural alternatives to orthodox medicines in health management, particularly in developing countries. One such plant is Boswellia dalzielii, a renowned tree in northern Nigeria that is extensively used due to its ethnomedicinal history. This study aimed to evaluate the antioxidant of some organic acids identified in the stem bark extract of B. dalzielii by Liquid Chromatography Mass Spectrometer (LCMS). The stem bark was extracted with ethanol using the cold maceration method. Antioxidant assay using 2,2-Diphenyl 1-Picryl-Hydrazyl-hydrate (DPPH), Ferric Reducing Antioxidant Property (FRAP), and Hydrogen Peroxide (H₂O₂₎ methods were used, and the results showed the highest antioxidant activity with higher concentrations of the extract; 49.580% ± 0.214, 3.540 ± 0.022 and 45.145% ± 0.234 for DPPH, FRAP and H₂O₂ respectively. And significantly lower than the standard (Ascorbic acid) used, 95.01 ± 0.001, 3.540 ± 0.120, and 91.390%± 0.022 respectively. the LCMS profile revealed the presence of many organic acids and other metabolites; Malonamic acid, D-pyroglutamic acid, Maleamic acid, Benzohydroxamic acid, 2-bromo-1,10-phenanthroline, p-tropoquinone (Quinone derivatives) among others. Therefore, the stem bark of B. dalzielii extract possesses antioxidant potential and could be due to its organic acid presence, it can be concluded that the stem bark of this plant may perhaps be useful in health management.

HEAVY METAL SEASONAL VARIATION IN IRRIGATION WATER ALONG JAKARA RIVER, KANO STATE, NIGERIA

Mon, 31 Mar 2025 00:00:00 +0000

The water in the Jakara River is a blend of domestic sewage from the north and central parts of the Kano metropolis and industrial effluent from the Bompai Industrial Estate. The wastewater in the river is the main source of irrigation water used by urban farmers in the city. Wastewater contaminated with heavy metals can be of public health concern when used for irrigation. The increasing concentration of several metals in soil and waters due to the Industrial Revolution has created an alarming situation for human life and aquatic biota. The study aims to determine the effect of season and location on the concentrations of Pb, Cd, Ni, Co, Cr and Hg in the irrigation water from the Jakara River. Water samples were collected from three locations monthly for 12 months from January to December 2022. The water samples were digested and subjected to heavy metals analysis using an atomic absorption spectrophotometer. Results of irrigation water analysis show that Pb and Cr are present in all the 36 samples taken during the study period. Co and Hg were not detected in all the samples taken during this period. Cd and Ni were not detected during September sampling, additionally, the concentrations of Pb and Cr detected in September were also the lowest. The highest concentrations were found in samples collected from Jaba and Kumantaka. It is only Pb concentration that exceeded the FAO/WHO permissible limit. Water samples collected in September at Airport Road possess the lowest heavy metals contamination...

SOFTWARE DEFECT PREDICTION MODELS FOR MITIGATING THE RISK OF BUG RECURRENCE IN LINES OF CODES: A SYSTEMATIC REVIEW

Mon, 31 Mar 2025 00:00:00 +0000

The custom of recent research in the field of software defect prediction is to display frameworks that provide software quality assurance teams with the ability to concentrate purely on software defect-prone codes. This has enabled software development time and maintenance activities to be managed more efficiently. Previous studies involved intricate software defect prediction datasets and methods. However, more detailed and inclusive insight into the state-of-the-art software defect prediction research method is needed. This systematic literature review aimed at evaluating the trends in the research field, the algorithms deployed, the methods utilised, the datasets used, the feature selection techniques mostly applied, the software metrics used, and the evaluation measures used in software defect prediction studies between 2017 and June 2023. Upon the application of selection and rejection criteria, 104 studies published on software defect prediction from January 2017 to June 2023 were evaluated. It was shown that 82 published articles on software defect prediction applied classification techniques, or about 78% of the total study. Meanwhile, the estimation algorithm accounts for 3% of the published articles on software defect prediction. Association methods have 2%. Clustering methods have four total published articles, with 4%. Finally, data processing has 14 published articles, resulting in 13%. The distribution of datasets used in software defect prediction found that 21 published articles utilised private datasets, a result of about 40%. Public datasets have a total of 32 published articles on software defect prediction, which resulted in 60%. Additionally, it was found that Naïve Bayes dominates the most...

IMPLEMENTATION AND COMPARISON OF SOFTWARE-DEFINED NETWORK CONTROLLERS IN VARIOUS SIMULATED NETWORK ENVIRONMENTS

Mon, 31 Mar 2025 00:00:00 +0000

In today's ever-evolving networking landscape, Software Defined Networking (SDN) has emerged as a paradigm-shifting technology that promises greater flexibility, agility, and control over network infrastructures. However, how easy are the configuration, extensibility, and programmability of these SDN controllers, considering the practical implications for network administrators and developers? Despite the growing adoption of SDN, there is limited research on the comparative performance of controllers across multiple simulation environments. This study aims to explore the practical implementation and comparative evaluation of different SDN Controllers within diverse simulated network environments. Prominent controllers such as POX and Faucet are meticulously configured and deployed in simulated network environments created using GNS3 (Graphical Network Simulator-3), OPNET (Optimized Network Engineering Tools), NS3 (Network Simulator-3), OMNET++ (Objective Modular Network Testbed in C++) and MININET platforms. Furthermore. the study employs a range of performance metrics like controller latency, network throughput, packet loss, CPU (Central Processing Unit) and memory utilization to assess the efficacy and efficiency of each SDN Controller. The Results indicated that Mininet provided the lowest latency, whereas OPNET demonstrated better scalability for large-scale networks. NS3, though useful for SDN network design and visualization, exhibited higher CPU and memory utilization that might limit its scalability for large-scale SDN controller simulations. While GNS3 offered a balanced performance and resource utilization, making it a suitable choice for SDN controller simulation that prioritizes realistic network modelling, OMNET++, on the other hand, exhibited moderate performance metrics with efficient resource utilization, making it suitable for SDN controller simulations requiring a balance between performance...

A SURVEY OF HEALTHCARE ACCESS AND UTILIZATION IN SELECTED RURAL AND URBAN SETTLEMENT OF PLATEAU STATE, NIGERIA

Daniel Fom Fulus — Mon, 31 Mar 2025 00:00:00 +0000

This study examines disparities in healthcare access and utilization between rural and urban communities in Plateau State, Nigeria. Using a cross-sectional survey design, data were collected from 384 respondents across six selected local government areas (LGAs). Fisher’s Discriminant Analysis was employed to identify significant factors influencing healthcare access. The results demonstrate that rural residents face greater challenges, including long travel distances to health facilities, inadequate transportation, financial constraints, and low health insurance coverage. Maternal and child healthcare utilization is also lower in rural areas, contributing to higher under-five mortality rates. The study finds that educational status and proximity to health facilities are critical determinants of healthcare access. The use of Fisher’s Discriminant Analysis proves appropriate, as it effectively differentiates between rural and urban healthcare accessibility based on key variables, achieving a classification accuracy of 67.7%. This validates its suitability in modelling healthcare disparities. The study highlights the need for strategic policy interventions, including expanding rural healthcare infrastructure, subsidizing healthcare costs, and increasing health awareness programs. Addressing these disparities is essential to achieving universal health coverage and improving public health outcomes in Plateau State.

ADVANCED SURVIVAL MODELING OF TUBERCULOSIS PATIENTS: INSIGHTS FROM EXPONENTIAL AND WEIBULL AFT MODELS

Mon, 31 Mar 2025 00:00:00 +0000

Tuberculosis is a significant public health issue in high-burden countries like Nigeria, causing increased disability and claiming many lives. The Cox Proportional Hazards model is commonly used in survival studies, but it fails to define the distribution of survival time. This study uses data from the National Tuberculosis and Leprosy Center (NTLC), Zaria, Kaduna State, Nigeria, to determine Tuberculosis survival and compare alternative parametric survival models. The objectives include determining predictors of TB mortality, evaluating the effect of these predictors on survival probability, and comparing Exponential and Weibull AFT models on NTLC Zaria TB survival data. The results show that the Weibull AFT model is most effective in modelling TB survival rates, with the lowest AIC score of 485.1 and the highest log likelihood of -228.6. Major factors associated with mortality include age over 55 years, pulmonary tuberculosis, family history of tuberculosis, alcohol and smoking history, and BMI less than 18.5 kgs/m2. The study emphasizes the need for region-specific survival models to reveal major directions for successful interventions and TB policies. Future studies should consider translating the highly-parametric approach into next-generation non-parametric models/machine learning for more accurate prognoses for implementing state-of-the-art public health interventions.

ASSESSMENT OF INFANT AND YOUNG CHILD FEEDING PRACTICES OF CAREGIVERS IN IHIMA DISTRICT, OKEHI LOCAL GOVERNMENT AREA, KOGI STATE

Elizabeth Funmilola Audu, Shehu Mohammed Hassan — Mon, 31 Mar 2025 00:00:00 +0000

Optimal infant and young child feeding practices are crucial for improving health outcomes and reducing mortality rates among children under the age of two. However, inadequate nutrition during this critical period remains a leading cause of global malnutrition. This study assessed key indicators of infant and young child feeding practices in Ihima District, Okehi Local Government Area, Kogi State. A cross-sectional study was conducted among mothers and caregivers in Ihima District. Respondents were recruited using convenience sampling method. Data was collected on assessment of Infant and young child feeding practice using a validated semi-structured questionnaire. The interviewer-administered questionnaire obtained information on demographic characteristics, breastfeeding practices and complementary feeding practices based on WHO guidelines. Data was analyzed using descriptive statistics and Chi-square on SPSS version 21, the p-values <0.05 was considered statistically significant. Among the 116 children studied, 75% were breastfed within one hour of birth, 74.14% were exclusively breastfed, and 48.28% received pre lacteal feeding. Additionally, 32.61% of mothers of children aged 12–23 months continued breastfeeding until the child was two years old. Timely introduction of complementary foods was observed in 66.67% of children aged 6–8 months. Of the 83 children within the 6–23 months age group, 43.37% were fed from four or more food groups. Minimum meal frequency (MMF) was adequate in 57.83%, while the minimum acceptable diet (MAD) was met by 43.37% of children. This study reported good early initiation of breastfeeding and exclusive breastfeeding practices, however complementary feeding practice was sub-optimal.

TEMPERATURE DEPENDENCE OF LUMINESCENCE LIFETIMES OF A-AL2O3:C USING TIME-RESOLVED OPTICAL STIMULATION

Solomon Akpore Uriri, Sunday Edewor Unuafe, Sandra Malumi — Mon, 31 Mar 2025 00:00:00 +0000

This study reported the performance of a newly developed time-resolved pulsing system by investigating the components of time-resolved optically stimulated luminescence (TR-OSL) signal from carbon-doped aluminium oxide, -Al2O3:C, a material of interest in dosimetry. The study demonstrates time-resolved optical stimulation (TR-OSL) measurements under a brief light-pulse LEDs stimulation. TR-OSL is a technique that separates in time the stimulation and emission of luminescence. In this work, we report the influence of measurement temperature on luminescence lifetimes in -Al2O3:C obtained using a new pulsing system. Luminescence lifetimes were measured from 20C to 140C using a pulsed LED system with a 17 ms stimulation duration. Despite extensive studies on the luminescence properties of -AlO:C, the precise influence of temperature on time-resolved optical stimulation luminescence lifetimes remains insufficiently characterized. Here, we designed and developed a new cost-effective time-resolved pulsing system based on blue LEDs. The measured luminescence lifetimes decreased from 36.8 0.1 ms at 20 0C to 28.0 0.6 ms at 140 0C. Luminescence lifetimes in -AlO:C exhibited thermal quenching at elevated temperatures, attributed to increased non-radiative transitions. The value of the activation energy for thermal quenching for -Al2O3:C was evaluated as 1.02 0.01 eV. The measured activation energy of 1.02 0.01 eV agrees with earlier findings 1.075 1.0 eV reported by Pagonis et al. (Pagonis et al., 2013), 0.96 0.005 eV reported by Ogundare et al. (Ogundare, 2012) and 0.95 0.04 eV by Chithambo et al. (Chithambo, 2014), confirming the thermal quenching model.

MICROBIOLOGICAL EVALUATION OF READY-TO-EAT FOODS SOLD AROUND SA'ADU ZUNGUR UNIVERSITY GADAU, BAUCHI, NIGERIA: IMPLICATIONS FOR FOOD SAFETY AND PUBLIC HEALTH

Mon, 31 Mar 2025 00:00:00 +0000

Food safety remains a global public health concern, and the eruption of diseases caused by food contamination occurs in places where sanitation and hygiene conditions are generally poor. This study evaluated the microbiological quality and safety of ready-to-eat foods (Awara, Akara, and Masa) sold around Sa'adu Zungur University, Gadau Campus, Bauchi, Nigeria. A total of 27 samples were randomly collected from the cafeteria, Gadau Market, and off-campus sites over one month. Samples were immediately analyzed using standard microbiological assays, including serial dilution, inoculation, incubation, microscopy, and biochemical tests to identify and confirm microbial contaminants. A total of four pathogenic bacteria were isolated: Staphylococcus aureus (51.9 %), Escherichia coli (25.9 %), Salmonella species (18.5 %), and Pseudomonas species (3.7 %). Awara sample had the highest total aerobic bacteria count of 9.33 ± 0.37 x 10⁵ cfu/g, with total coliform count (TCC) obtained ranging from 4.07 ± 2.8 x 10⁵ to 7.20 ± 0.23 x 10⁵ cfu/g. Akara sample has the highest TCC (7.20 ± 0.23 x10⁵cfu/g), and Staphylococcus count (TSC) of 5.40 ± 0.31 x 10⁵cfu/g, while Masa samples have the lowest TSC of 1.13 ± 0.03 x 10⁵cfu/g. The findings reveal poor hygiene among food vendors, likely due to inadequate food safety knowledge, posing health risks. Mandatory health certification, regular renewal, and food hygiene training are recommended to enhance safety and protect consumer health.

ENHANCED PREDICTION OF CORONARY ARTERY DISEASE USING LOGISTIC REGRESSION

Mon, 31 Mar 2025 00:00:00 +0000

Coronary Artery Disease (CAD) remains a leading cause of global morbidity and mortality, emphasizing the urgent need for accurate and interpretable prediction models to facilitate timely interventions and improve patient outcomes. This study investigates the application of Logistic Regression for CAD prediction, leveraging a dataset of 303 patients and 13 clinical features obtained from the UCI Machine Learning Repository. Recognizing the limitations of traditional risk assessment methods, this research explores the potential of Logistic Regression to enhance CAD prediction accuracy through a streamlined and easily implementable approach. The dataset, which encompasses demographic factors, clinical measurements, and lifestyle indicators, was subjected to rigorous analysis to evaluate the model's performance. A Logistic Regression model was developed using Python's scikit-learn library and assessed using a comprehensive set of evaluation metrics, including accuracy, precision, recall, F1-score, and the Area Under the Receiver Operating Characteristic curve (AUC-ROC). On a test set of 61 instances, the model achieved an overall accuracy of 82%, demonstrating its ability to correctly classify individuals with and without CAD. The precision and recall scores for Class 0 (absence of CAD) were 79% and 82%, respectively, while for Class 1 (presence of CAD), the precision and recall scores were 84% and 82%, respectively, indicating balanced performance across both classes. The model exhibited an AUC-ROC of 0.89, signifying strong discriminatory ability. These findings suggest that Logistic Regression can serve as a valuable tool for CAD risk assessment, providing a foundation for more advanced predictive models and contributing to improved cardiovascular health management...

QUANTIFICATION OF QUININE IN MEDICINAL PLANTS FROM EDE, NIGERIA USING HPLC

Mon, 31 Mar 2025 00:00:00 +0000

Nigeria, a West African country, is rich in medicinal plants traditionally used to manage various ailments. Quinine, a well-established antimalarial drug, has been widely used as a chemotherapeutic agent for treating malaria. This study aimed to develop and validate a rapid, simple, accurate and precise high-performance liquid chromatography (HPLC) method for the quantitatively determine the quinine content in three selected medicinal plants – Azadirachtai ndica (neem), Citrus aurantii folia (lime), and Mangifera indica (mango). Cold extraction method with vortex agitator was employed to obtain plant extracts. The separation and quantification of quinine were performed using an Agilent 1260 Infinity HPLC system equipped with a diode-array detector (DAD). Separation of quinine from extract was achieved on a Phenomenex Gemini C18 column in less than 2 minutes using an isocratic mobile phase of 30% acetonitrile and 70% double-distilled water and a flow rate of 1.0 mL/min at 254 nm. The standard calibration curve obtained was found to be linear R² = 0.9975. The analytical figures of merits were also evaluated for the percentage extraction recovery of quinine was 99.5%, the intraday precision as percent relative standard deviation was 1.14, it proved excellent % RSD which is less than 2 and of limits of detection (LOD) and limits of quantification (LOQ) were found to be 0.14µg/mL and 0.42µg/mL respectively. This study showed that, with the use of HPLC, quinine levels in these plants were accurately measured, thus, the method used was highly reliable, with excellent accuracy and precision. This study helps confirm whether...

GENETIC VARIABILITY AND MULTI-TRAIT SELECTION FOR SUPERIOR TRAITS IN WILD YAM HYBRIDS

Mon, 31 Mar 2025 00:00:00 +0000

The interspecific breeding of yams (Dioscorea spp.) for superior traits is hindered by the dioecious nature of their flowers and low flowering frequency, despite the potential of wild yams to improve related cultivated varieties. However, the genetic variability of these wild yam species has yet to be fully explored. This study investigated the genetic variability and heritability estimates for multi-trait selection of hybrids derived from crosses between two wild yam species, Dioscorea abyssinica and Dioscorea praehensilis. Field experiment was conducted on 65 hybrids using a partially replicated block design. With standard descriptors, data were collected on phenotypic traits, including stem length, internode, plant vigour, tuber length, tuber weight, tuber width, tuber thorniness, and tuber surface cracks. Heritability, genetic advance and variance components were estimated to quantify the genetic contribution to trait variability. Analysis of variance identified significant differences (p=0.00) among hybrids and high genetic variability was observed in phenotypic traits assessed, with tuber weight showing the highest genotypic (104%) and phenotypic (127%) variances. Heritability estimates suggested strong selection potential for stem length (74%), tuber weight (67%) and tuber hairiness (65%), while tuber shape (7%) and tuber width (9%) showed low genetic potential. Multi-trait Genotype Ideotype Distance Index (MGIDI) analysis further identified 8 high-performing wild yam hybrid accessions (TDabp2101010, TDabp2101013, TDabp2101030, TDabp2101042, TDabp2101046, TDabp2101050, TDabp2101052, and TDabp2101055). These findings demonstrate the potential of wild yam hybrids for trait introgression, thereby paving way for the development of new yam cultivars and providing valuable insights for yam improvement programs.

EFFECTS OF DATA DELETION AND WEIGHTING ON FISHER’S LINEAR CLASSIFICATION METHOD: A ROBUSTIFICATION APPROACH

Friday Zinzendoff Okwonu, Aishah Nor Ahad — Mon, 31 Mar 2025 00:00:00 +0000

The classical supervised classification model's performance is hampered by the effects of influential observations (IOs). The influential observations(IO’s) when deleted, weighted,Winsorized, truncated and retained have enormous effects in making replicative inferences in different classification models. Due to the influence of IO’s on classical supervised classification models, different methods such as IO deletion or weighting have been introduced to reduce the influence of IO’s. Some of these influential observations reduction or deletion methods have resulted in information loss of various degrees. In this study, we investigated the effects of IOs deletion and weighting using the Mahalanobis distance as a plug in to enhance the robustness of the Fisher linear classification method (FLCM). We proposed an F-weight plug in method to robustify the FLCM. We compared the performance of these methods to determine whether IO deletion or IO weighting retards or enhances the classification accuracy of the FLCM. The study affirmed that IO weighting using the F-weight minimizes information loss more than the IO deletion using the Mahalanobis distance. This study concludes that the variant of FLCM based on the F-weight method showed improved classification accuracy, and efficiency more than the Mahalanobis distance based FLCM.

APPLICATION OF MODIFIED SEQUENTIAL PROBABILITY RATIO TEST CUM-MAXWELL DISTRIBUTION ON KIDNEY DIAGNOSIS

G. I. Onwuka, W. B. Babayemi, Ibrahim Sylvester, Tolulope O. James — Mon, 31 Mar 2025 00:00:00 +0000

The early diagnosis of Chronic Kidney Disease (CKD) remains a crucial challenge in medical research. This study investigates the robustness of the Modified Sequential Probability Ratio Test (MSPRT) in kidney diagnosis, focusing on its response to non-normality and outliers. Additionally, the study evaluates the diagnostic performance of MSPRT by analyzing the average sample size and the operating characteristics curve (OC) in conjunction with the Receiver Operating Characteristic (ROC) curve and the Maxwell-Boltzmann Distribution (MBD). Using patient data from the University of Maiduguri Teaching Hospital (UMTH), the study applies these statistical methods to assess their effectiveness in CKD classification. The results demonstrate the adaptability of MSPRT in non-ideal data conditions and its efficiency in minimizing sample size while maintaining high diagnostic accuracy. The findings recommend the importance of integrating statistical models such as MBD in refining diagnostic decision-making processes for CKD.

AN ENHANCED CLASSIFICATION AND REGRESSION TREE ALGORITHM USING GINI EXPONENTIAL

Mon, 31 Mar 2025 00:00:00 +0000

Decision tree algorithms, particularly Classification and Regression Trees (CART), are widely used in machine learning for their simplicity, interpretability, and ability to handle both categorical and numerical data. However, traditional decision trees often encounter limitations when dealing with complex, high-dimensional, or imbalanced datasets, as conventional impurity measures such as the Gini Index and Information Gain may fail to capture subtle variations in the data effectively. This study enhances the traditional Classification and Regression Trees (CART) model by introducing the Gini Exponential Criterion, which incorporates an exponential weighting factor into the split point calculation process. This novel approach amplifies the influence of highly discriminative features, resulting in more refined splits and improved decision boundaries. The enhanced CART model was evaluated on two benchmark datasets: the wine quality dataset and the hypothyroid dataset, with preprocessing steps like feature scaling and SMOTE for class imbalance, and hyperparameter tuning via Bayesian Optimization. On the wine quality dataset, the enhanced model improved accuracy from 57% (traditional CART) to 86%, while on the hypothyroid dataset, it achieved an impressive accuracy of 98%. These results highlight the model's ability to handle complex and imbalanced data effectively. Feature importance analysis and decision tree visualization further demonstrated the model's interpretability. The study concludes that the Gini Exponential Criterion significantly improves CART's performance, offering better generalization and clearer decision boundaries. This advancement is particularly valuable for applications requiring precise and interpretable predictions, such as healthcare diagnostics and quality assessment. Future work could explore integrating this criterion into ensemble methods and...

STUDY OF THE ADSORPTION OF Cr, Ni, AND Pb FROM TANNERY WASTEWATER USING MODIFIED RICE HUSK AND CASSAVA PEEL POWDER

Timothy Ojoarome Yahaya, Umar Alfa Abubakar, Baraudeen Salauwa Sani — Mon, 31 Mar 2025 00:00:00 +0000

Over the years, water pollution due primarily to the discharge of toxic heavy metals from industrial activities has served as a major challenge in the quest to provide a safe environment. Key among the technologies used for the treatment of wastewater contaminated with heavy metals is adsorption. In this study, mixed rice husk and cassava peel powder were used to develop microporous adsorbent with chemical modification by Sulphuric acid (H₂SO₄) for the batch adsorption of hexavalent chromium [Cr (VI)], Nickel(Ni), and Lead(Pb). Using adsorption equilibrium isotherms and adsorption kinetic study, a positive correlations (better fit) was obtained for Redlich-Peterson isotherm and Pseudo second order kinetic models. A maximum adsorption capacity of 139.18 mg/g, 3.66mg/g, and 5.58mg/g and a maximium removal of 93.60%, 98.20% and 93.80% were obtained for Chromium, Nickel, and Lead respectively. Therefore, rice husk and cassava peel usage were found to has a high chance of reducing solid waste management problems as well as having the potential to be effective in the removal of heavy metals from industrial effluents.

COMBATTING BANKING MALWARE THREATS: EVALUATING THE EFFICACY OF HYBRID AND SINGLE-CLASSIFICATION ALGORITHMS

Mon, 31 Mar 2025 00:00:00 +0000

The increasing sophistication and prevalence of banking malware pose significant challenges to cybersecurity, threatening the confidentiality, integrity, and availability of financial systems and user data. This study evaluates the efficacy of hybrid and single-classification algorithms in detecting banking malware, addressing a critical gap in existing research. A total of eight classification algorithms were analyzed, including three hybrid models—Stacked Ensemble with Gradient Boosting, AdaBoost, and Stacking with Decision Trees and Random Forest. Additionally, five single classifiers—Support Vector Machine (SVM), Decision Tree, k-NN, Random Forest and Logistic Regression were assessed. The research methodology incorporated principal component analysis (PCA) for feature selection and techniques like Adasyn and Tomek Link to address data imbalance. Classification performance was evaluated using key metrics: accuracy, precision, recall, and F1-score. Results demonstrated that hybrid models, particularly an ensemble combining Random Forest and Decision Tree, outperformed other classifiers, achieving superior accuracy (0.98), precision, and recall. While Gradient Boosting and AdaBoost also exhibited robust performance, Logistic Regression showed room for improvement in precision and recall metrics. This research highlights the effectiveness of hybrid classification models in enhancing the detection of banking malware and underscores their potential for strengthening cybersecurity defenses in financial systems. The study contributes to the growing literature on machine learning applications in malware detection and provides insights into the strengths and limitations of diverse classification algorithms.

SPECTRAL ANALYSIS AND STABILITY OF WAVE EQUATIONS WITH DISPERSIVE NONLINEARITY

Umar Muhammad Dauda, Lawal Ja’afaru — Mon, 31 Mar 2025 00:00:00 +0000

This study employs spectral methods to capture the behaviour of wave equation with dispersive-nonlinearity. We describe the evolution of hump initial data and track the conservation of the mass and energy functionals. The dispersive-nonlinearity results to solution in an extended Schwartz space via analytic approach. We construct numerical schemes based on spectral methods to simulate soliton interactions under Schwartzian initial data. The computational analysis includes validation of energy and mass conservation to ensure numerical accuracy. Results show that initial data from the Schwartz space decompose into smaller wave-packets due to the weaker dispersive-nonlinearity but leads to wave collapse as a result of stronger dispersive-nonlinearity. We conjecture that the hyperbolic equation with a positive nonlinearity and exponent admits global solutions, while lower exponents lead to localized solutions. A stability analysis of solitonic solutions of the equation is provided via the perturbation approach.

MATHEMATICAL ANALYSIS OF A RISK STRUCTURED LISTERIOSIS DYNAMICS MODEL

M. Alkali, Musa Abdullahi, A. Alhassan, S. Muhammad, H. Zailani — Mon, 31 Mar 2025 00:00:00 +0000

A foodborne disease called listeriosis is brought on by the bacteria Listeria monocytogenes which typically infects people after consuming contaminated food. Listeriosis mostly affects people with weakened immune systems, pregnant women and newborns. In this paper, we developed and analyzed a risk-structured mathematical model describing the dynamics of Listeriosis using ordinary differential equations. Three equilibrium points were obtained, viz; disease free equilibrium point, , bacteria free equilibrium point, , and endemic equilibrium point, . Contaminated food threshold was established as . The disease-free equilibrium and Bacteria-free equilibrium points are found to be locally asymptotically stable whenever the contaminated food threshold is less than unity (). Also, the endemic equilibrium point is found to be locally asymptotically stable using the Routh-Hurwitz criterion whenever the food safety index is less than unity (). Global stability analysis of the disease-free equilibrium point using Castillo-Chavez method revealed that the disease-free equilibrium point, is globally asymptotically stable.

ASSESSMENT OF KEEPING QUALITY AND MICROBIAL LOAD OF Staphylococcus aureus IN CATTLE MILK, PROCESSING FACILITIES, AND ENVIRONMENT IN NORTHERN OYO STATE, NIGERIA

Mon, 31 Mar 2025 00:00:00 +0000

Milk is a vital nutritional resource but is highly perishable and prone to contamination by pathogens like Staphylococcus aureus, posing significant public health risks. In Northern Oyo State, where dairy production is predominantly traditional, poor hygiene practices and limited sanitation infrastructure exacerbate these risks. This study addresses gaps in understanding the keeping quality and microbial contamination of raw milk in the region, providing data to improve safety standards. A cross-sectional study was conducted from August 2023 to January 2024, collecting 1,200 samples from five Local Government Areas (LGAs). These samples included raw milk, swabs from milk handlers, and environmental sources. The keeping quality of milk was assessed using the methylene blue reduction test (MBRT) and total bacterial count (TBC) was used to determine microbial load. S. aureus was isolated using standard culture methods. Results revealed that 81.4% of raw milk samples demonstrated “very good” keeping quality, while 4.8% were categorized as “very bad.” TBCs across all samples exceeded international safety standards, indicating significant microbial contamination. The prevalence of S. aureus was 2.7%, with most isolates originating from milk handlers, emphasizing poor hygiene practices as a critical factor. These findings highlighted the urgent need for improved sanitation, handler training, and proper milk storage protocols to enhance dairy safety and protect public health. This study provides foundational data to guide interventions aimed at reducing microbial contamination in Nigeria’s dairy sector.

IMPACTS OF HOME MOSQUITO VECTOR CONTROL AND INSECTICIDE TREATED NETS ON MALARIA STATUS AMONG PREGNANT WOMEN ATTENDING ANTENATAL CARE AT POLICE HOSPITAL, DUTSE, JIGAWA STATE

Mon, 31 Mar 2025 00:00:00 +0000

Malaria remains a critical public health challenge, particularly among vulnerable populations such as pregnant women in endemic regions. This study investigated the impact of home mosquito vector control and insecticide-treated nets (ITNs) on malaria prevalence among 50 pregnant women attending antenatal care at the Police Hospital, Dutse, Jigawa State, Nigeria. Participants' demographic characteristics, knowledge, attitudes, and practices regarding mosquito control were assessed, alongside malaria prevalence across age, marital, trimester, educational, and occupational categories. Findings revealed a malaria prevalence of 46%, with younger participants (18–24 years) and unemployed individuals showing higher rates, though statistical associations were insignificant (p > 0.05). Knowledge of malaria transmission was universal (100%), and ITN ownership was high (94%), yet only 86% reported consistent nightly use. Despite positive perceptions of ITNs, gaps in equitable distribution and consistent usage were identified, with 60% of ITNs purchased rather than obtained through free programs. Additionally, while 70% of participants engaged in regular mosquito control practices, community-based programs were limited, with only 18% reporting active initiatives in their areas. The study underscores the need for strengthened malaria prevention strategies, emphasizing universal access to ITNs, community-driven mosquito control programs, and targeted health education campaigns. Comprehensive approaches integrating antenatal care services and public health outreach can enhance protective measures for pregnant women, mitigating malaria's impact on maternal and fetal health.

EFFECT OF MEDIUM CHAIN TRIGLYCERIDE-KETOGENIC DIET ON THE LUNGS OF TYPE 2 DIABETIC MALE NEW ZEALAND RABBITS

Mon, 31 Mar 2025 00:00:00 +0000

Type 2 diabetes mellitus is a metabolic disorder that results in impairment of the lungs, associated with both structural and functional alterations. Ketogenic diet is a high-fat, moderate-protein and low-carbohydrate dietary regimen, with the potential of ameliorating diabetic lung complications. This study evaluated the effects of medium chain triglyceride-ketogenic diet (MCT-KD) on the lungs of type 2 diabetic male New Zealand rabbits. Type 2 diabetes was induced by feeding the rabbits formulated high fat diet for ten weeks. Twenty rabbits were divided into five groups of four rabbits each: Group I was a normoglycemic group fed with normal diet; Group II was a normoglycemic group fed with a MCT-KD; Group III was a diabetic group fed with normal diet; Group IV was a diabetic group fed with MCT-KD while Group V was a diabetic group fed with normal diet and oral administration of 4 mg/kg pioglitazone. There was a significant increase (p < 0.05) in cellular infiltration of total white blood cells, lymphocytes, neutrophils and macrophages into the bronchoalveolar lavage fluid of diabetic lungs. However, feeding with MCT-KD and administration of 4 mg/kg pioglitazone significantly decreased (p < 0.05) total white blood cells and the differential components in the diabetic lungs. The MCT-KD was observed to reduce the lung weight of the diabetic rabbits, however, no change was observed in the relative lung weight. Cellular infiltration, reduced alveolar spaces, distorted bronchial epithelium and oedema were observed in the lungs. These were observed to be alleviated after feeding with MCT-KD.

STUDY ON THE EFFECT OF TEMPERATURE ON BIO-ETHANOL PRODUCTION FROM CASSAVA FLOUR AND CASSAVA PEELS: AN INSIGHT INTO BIO-ENERGY PROCESSES

Mon, 31 Mar 2025 00:00:00 +0000

Knowledge of fermentation parameters with respect to temperature is necessary in bio-ethanol production; as an important process in bio-energy applications for green energy utilization. Bio-ethanol provides an alternative clean energy source that can be obtained from biomass, thereby mitigating pollution problems associated with using environmentally unfriendly energy sources. A study into the effect of temperature on bio-ethanol production from cassava flour and cassava peels was investigated. Temperature was varied between 30-60^oC at 5^oC intervals and the volume of bio-ethanol produced was examined using optical density measurement. An increase in substrate concentration led to a proportionate increase in the volume of bio-ethanol produced at an optimal temperature of 30^oC. However, a gradual decrease in bio-ethanol production was observed beyond 30^oC (35-60^oC), which shows the effect of temperature on bio-ethanol production from cassava flour and cassava peels, with the yeast activity optimum at 30°C using 80 grams of substrate. The optical density measurements provided a reliable indication of optimum microbial activity and bio-ethanol production. Bio-ethanol yield was higher in cassava flour than in cassava peels at the same concentration, indicating higher carbohydrate content in cassava flour. The findings show a significant temperature influence on the activity of the yeast efficiency in bio-ethanol production. Cassava and its peel are important for the production of bio-ethanol because it holds potential as a valuable feedstock for bio-ethanol production, offering a sustainable solution to waste management and clean energy; therefore, knowledge of the optimal fermentation temperature is an important information in bio-ethanol production from cassava precursors.

FFECTIVE RETRIEVAL OF RELEVANT WEB DOCUMENTS: A QUERY EXPANSION APPROACH USING FORMAL CONCEPT ANALYSIS

Abdullahi Bn Umar — Mon, 31 Mar 2025 00:00:00 +0000

In information retrieval, vocabulary mismatch between the search vocabulary and documents vocabulary has been a common challenge for web users, hindering information access and retrieval. This issue is often attributed to the ambiguous representation of user information needs as queries, leading to the retrieval of many irrelevant documents, particularly for non-skilled web users. This paper aims to improve user query representation for effective retrieval of relevant documents from the web. To achieve this, a query expansion strategy was employed to identify terms with similar meanings to the user’s initial query term. The similarities between the expanded terms and the initial user query term were determined by calculating the cosine angle between the vector resenting document vocabulary and the vector representing query term. Thereafter, Formal Concept Analysis (FCA) was employed to analyze and present the results. Findings from the analysis revealed that concatenating similar terms with the initial user query terms resulted in a 0.16% improvement, as evident in the retrieval precision of 0.64% with the initial query and 0.80% with the expanded query terms.

MITIGATION OF COPPER-INDUCED TOXICITY IN WISTAR RATS' SERUM BIOCHEMICAL PROFILE BY CANNABIS LEAF EXTRACT

Mon, 31 Mar 2025 00:00:00 +0000

Copper serves as an integral part of specialized cuproproteins responsible for normal growth and development of the body, and excess accumulation in the body has a detrimental effect. Anthropogenic influences and an increased number of vehicles coupled with intensive urban and rural infrastructure result in the accumulation of heavy metals in the soil and plants, which are subsequently transmitted to humans via the food chain. The study was designed to provide positive effects of cannabis, establish a means of preventing copper exposure, and devise a means of preventing them. The aim of the study was to determine the therapeutic effect of cannabis leaf extract on copper-induced toxicity and serum biochemical profile changes. The experimental study was carried out using 20 Wistar rats allocated into 4 groups containing 5 rats each: group A (negative control), group B (copper only), group C (cannabis only), and group D (copper then treated with cannabis). The results showed decreased serum electrolytes (urea, bicarbonate, creatinine, total protein, albumin, bilirubin, AST, and ALP) and increased serum ALT and erythropoietin, which were later reversed after treatment with cannabis. In conclusion, cannabis leaf extract has therapeutic effects on copper toxicity.

ISOLATION AND CHARACTERIZATION OF PYOCIN S2-PRODUCING LOCAL STRAINS OF Pseudomonas aeruginosa

Gladys Aribi Sika, Samson Baranzan Wayah, Peter Maitalata Waziri — Mon, 31 Mar 2025 00:00:00 +0000

Antibiotic resistance is responsible for 1.27 million deaths globally. Pyocin, from Pseudomonas aeruginosa is a promising candidate against antibiotic-resistant infections. This study aims at isolating pyocin S2-producing local strains of Pseudomonas aeruginosa and investigating the antimicrobial activity of pyocin S2 against Staphylococcus aureus, Staphylococcus sp., Escherichia coli, Salmonella sp., Streptococcus pneumoniae, and Vibrio cholerae. Pseudomonas aeruginosa was isolated from environmental and clinical samples by inoculation on cetrimide agar plates and incubating at 37⁰C for 24 hours. To detect the presence of pyocin S2 gene in the isolates: DNA extraction, polymerase chain reaction (PCR) using primers specific to pyocin S2 gene, and agarose gel electrophoresis was conducted. Using agar well diffusion assay, the antimicrobial activity of pyocin S2-containing Pseudomonas aeruginosa against the aforementioned target pathogens was evaluated. Out of 20 Pseudomonas aeruginosa isolates subjected to PCR, 11 contained pyocin S2 gene. Pyocin S2 from Pseudomonas aeruginosa A1, B2, CL2, CL8 and C11 produced zone of inhibition (ZOI) when tested against Escherichia coli (ZOI = 23.5mm, 17.5mm, 26.0mm, 21.5mm, 29.0mm respectively). However, pyocin S2 from Pseudomonas aeruginosa B3, B10, CL3, B19, CL9 and CL6 did not inhibit Escherichia coli but suppressed the growth of Staphylococcus sp. (ZOI = 21.0mm, 18.5mm, 28.5mm, 23.7mm, 24.5mm and 23.5mm respectively). Also, Pyocin S2 from Pseudomonas aeruginosa C11 suppressed the growth of Vibrio cholerae (ZOI = 30.7mm), but not the other strains. In conclusion, pyocin S2 from indigenous strains of Pseudomonas aeruginosa inhibited the target pathogens. These findings will foster further evaluation of pyocin S2’s antimicrobial potential.

PHYTOCHEMICALS AND GAS CHROMATOGRAPHY-MASS SPECTROMETRY (GC-MS) ANALYSIS OF Rauvolfia vomitoria Afzel COLD AND HOT WATER LEAVES EXTRACT

Mon, 31 Mar 2025 00:00:00 +0000

Phytochemicals, which are bioactive compounds found in medicinal plants, have been attributed to the therapeutic properties of these plants. Qualitative and quantitative phytochemicals of cold and hot leaf extracts of Rauvolfia vomitoria Afzel were determined using standard methods and GC-MS technique was used to examine specific bioactive constituents. The qualitative results showed the presence of of cardiac glycosides, alkaloids, terpenes, flavonoids, phenols, and tannins whereas phlobatannins, thiols and steroids were absent in the cold and hot leaf extracts. The extract from hot water had a significantly higher (p < 0.05) value in phytochemical content than the cold water in all total phytochemicals determined with flavonoids (4.808 ± 0.099, 2.596 ± 0.045) having the highest concentration in the hot and cold water extract respectively while phenol (1.382 ± 0.010, 1.356 ± 0.002) had the least concentration in the hot and cold water extract respectively. The GC-MS result showed the following: n-Hexadecanoic acid, 9,12-Octadecadienoic acid, methyl ester, (E, E), 11-Octadecenoic acid, methyl ester, Octadecanoic acid, methyl ester, 2-hydroxy-1,3-propanediyl ester, 9-Octadecenamide, (Z), 9-Tetradecenal, (Z), 9-Octadecenoyl chloride, (Z), Tridecanoic acid, methyl ester, n-Hexadecanoic acid, 9,12-Octadecadienoic acid, methyl ester, (E, E), 9-Octadecenoic acid, Octadecanoic acid, methyl ester, etc. The following are a few of the phytochemicals' pharmacological characteristics: antioxidant, antiviral, anticarcinogenic, antimicrobial, antibiotic, antiallergic and anti-inflammatory. The results of this investigation provide insight into the plant's medicinal usefulness, especially the hot extract, which had higher levels of phytochemicals. Hence, R. vomitoria plant may be a true source of medicinal agents to manage and treat diseases.

DEVELOPMENT AND TESTING OF A SOLAR ADSORPTION REFRIGERATOR UNDER HAZY CONDITION

Mon, 31 Mar 2025 00:00:00 +0000

ASSESSMENT OF EFFECTS OF BANDITRY ON MAIZE FARMERS IN LERE LOCAL GOVERNMENT AREA OF KADUNA STATE, NIGERIA

Zando B. Agyo, David T. Wake — Mon, 31 Mar 2025 00:00:00 +0000

This study examined Effects of banditry on maize farmers in Lere Local Government Area of Kaduna State. One of the major threats to the agricultural sector in Nigeria is insecurity from bandits. The sustained terrorist and banditry activities have had negative impacts on agricultural activities and farming system which led to loss of lives and economic losses. Descriptive survey design was used to collect and analyzed data which consists maize farmers in Lere Local Government Area, questionnaire was used to collect information from the respondents. Based on the result, most of the respondents are male. Most of the respondent (60 %) strongly agreed that bandits often target farms to steal valuable crops leading to significant financial losses which is positive. 51 % respondents strongly agreed that bandit attacks often result in the destruction of farm infrastructure, including barns, storage facilities, and equipment. Majority (65 %) of the respondents strongly agreed that presence of banditry forces farmers to invest in security measures such as hiring guards, installing fencing, and using surveillance equipment. 74 % of the respondents strongly agreed that frequent bandit attacks disrupt the supply chain, making it difficult for farmers to transport their goods to market. 48 respondents representing 48 % strongly agreed that banditry fosters an atmosphere of fear and mistrust within rural communities. Bases on the study it was recommended that community or people of the area should try as much as possible to assist in strengthen the security system in the area, the community leader should...

TOWARDS SMARTER CYBER DEFENSE: LEVERAGING DEEP LEARNING FOR THREAT IDENTIFICATION AND PREVENTION

Mon, 31 Mar 2025 00:00:00 +0000

The increasing sophistication of cyber threats has rendered traditional security measures inadequate, necessitating the adoption of deep learning-based techniques for enhanced threat detection and prevention. This study develops a Sequential Neural Network (SNN) model to improve cybersecurity defenses by identifying malicious activities with greater accuracy. The model is trained on the CERT Insider Threat v6.2 datasets, utilizing user activity modeling to detect anomalous behavior effectively. Performance evaluation reveals that the model achieved an accuracy of 67%, with precision, recall, and F1-score all at 0.67, indicating a balanced but moderate classification capability. The AUC-ROC score of 0.67 further suggests that while the model surpasses random classification, refinements are necessary for practical deployment. The confusion matrix analysis highlights challenges in distinguishing between certain cyber threats, resulting in misclassifications and false positives. Despite these challenges, the proposed deep learning approach demonstrates the potential of SNNs in cybersecurity by detecting complex attack patterns that traditional methods often fail to recognize. However, issues such as class imbalance, interpretability, and computational overhead must be addressed to improve model robustness. Future research will focus on enhancing model architectures, optimizing hyperparameters, and integrating explainable AI techniques to improve detection accuracy and reduce false positive rates. By leveraging deep learning, this study contributes to the development of smarter and more adaptive cybersecurity solutions, capable of responding to evolving threats in real time.

THE IMPACT OF ARBUSCULAR MYCORRHIZAL FUNGAL INOCULANTS ON GROWTH, NUTRIENTS, AND YIELD OF VEGETABLE PLANTS: A REVIEW

Umma Abdurrahman Yakasai, Safianu Rabiu — Mon, 31 Mar 2025 00:00:00 +0000

Arbuscular mycorrhizal fungi (AMF), belonging to the phylum Glomeromycota, establish symbiotic associations with plant roots, enhancing nutrient uptake through extensive hyphal networks. These networks facilitate the acquisition of essential nutrients, particularly phosphorus, while the host plants supply the fungi with photosynthates. This review examines the impact of AMF inoculation on onion, tomato, cucumber, and pepper. The findings highlight the numerous benefits conferred by AMF symbiosis, which includes significant enhancements in plant growth and development. AMF inoculation has been shown to improve photosynthetic efficiency, increase plant height, leaf area, root length, and both fresh and dry biomass, as well as boost fruit yield in terms of number, size, and weight. Furthermore, AMF contribute to improved nutrient and water absorption by extending their hyphae into deeper soil layers, thereby enhancing resource availability for plants. Additionally, AMF inoculation plays a crucial role in mitigating biotic and abiotic stresses in vegetable crops while also improving soil stability by reducing leaching and erosion.

EVALUATION OF PHOTODEGRADATION BEHAVIOR OF POLYPROPYLENE/GRAPHITE PARTICULATE COMPOSITE FOR ROOFING APPLICATION

Mon, 31 Mar 2025 00:00:00 +0000

Polypropylene employed in plastic roofing sheets production is vulnerable to UV light irradiation, causing it to degrade. This study investigates the effect of graphite (Foreign and Nigerian) as fillers and UV stabilizers on the mechanical properties of Polypropylene subjected to UV irradiation. Polypropylene composite was prepared with varying proportions of graphite (10% to 60%). The hardness, impact strength, and tensile strength were tested before and after 48 hours of UV exposure. The results indicate that tensile strength generally decreases with increasing filler loading and UV exposure-time, though the tensile strength of Polypropylene/FGP composites at 20% filler-loading was insignificantly affected by the UV-light with its tensile-strength slightly dropping from 32.71 MPa to 31.88 MPa. Tensile strength of Polypropylene/NGP composites at 40% slightly dropped from 41.78 MPa to 37.42 MPa, likewise that of Polypropylene/NGP composites at a 90/10 proportion dropped more (33.77 MPa to 26.62 MPa) compared with that of its counterpart. The Impact strength increases with an increase in the filler-loading up to 20%, and at 30% of the filler, the materials gained more resistance to degradation by UV light. Hardness results showed that both foreign and local graphite fillers increased the material's hardness, with PP/FGP exhibiting more consistent performance after UV exposure. The hardness value of the materials produced with 10% of the filler slightly dropped from 12.3 HRF to 11.85 after exposure. In conclusion, the composites produced offer superior resistance to degradation by UV light pertinent to Impact strength, tensile strength and Hardness of the composite compared with Polypropylene.

EFFECT OF LOW-TEMPERATURE CARBURIZATION TREATMENT ON THE HARDNESS BEHAVIOR OF Alsl316 AUSTENITIC STAINLESS STEEL

Mon, 31 Mar 2025 00:00:00 +0000

There has been significant progress in the surface modification of stainless steel in order to enhance its surface hardness without major loss in other important properties. In this work, the possibility of enhancing the hardness property of austenitic stainless steel through a low-temperature pack carburization process was explored and investigated. Taguchi approach with L9 orthogonal array was used to optimize the hardness property of the carburized steel via the manipulation of the process parameters viz: carburizing temperature (350, 450, 550 ^oC), carburizing time (8,16, 24hrs) and carburizer/energizer ratio (90:10, 80:20,70:30). The surface hardness profiles of the carburized layer were investigated. Taguchi analysis result shows that optimal hardness of 407Hv was achieved. The optimization of the carburized surface properties revealed that the carburizing temperature of 550 ^oC, carburizing time of 24hrs and carburizer/energizer ratio of 90:10 are the prominent factors and levels for achieving optimal condition respectively. The models for optimal conditions were validated and the prediction adequacy are found to be within the limit of 2-6% prediction error, indicating the models are accurate and adequate to predict the responses. Optical microscope micrographs and morphologies indicates that the modified steel layer obtained at the optimal condition shows mild deeper case profile compared to non-treated stainless-steel samples. Equivalent of 104% improvement in the case hardness was achieved for the samples investigated with optimized condition. The level of improvement attained in the hardness therefore suggest that the ultimate objective of surface modification of austenitic stainless steel investigated in this study has been achieved.