Science World Journal

Evaluating sustainable features of selected university female hostels in Kaduna State, Nigeria

2025-02-12T10:58:55+00:00

This research investigates the sustainable design features of selected female university hostels in Kaduna state, Nigeria, with a focus on identifying strengths and weaknesses in their current sustainability practices. The objectives are to analyse selected existing female hostels in Kaduna, Nigeria, and develop design recommendations to improve their sustainability. The study employs a case study research design, collecting data through field observations and architectural assessments. Findings reveal that while the buildings are strategically oriented along the north-south axis to optimize natural light and energy efficiency, there is significant untapped potential for renewable energy integration. Additionally, Waste management practices are inadequate, with improper disposal observed on or near the sites. Although natural ventilation and daylighting strategies, such as window openings and courtyards, were successfully implemented, the hostels lack appropriate landscaping. Thermal comfort is generally well-managed, but noise control measures are absent. The construction relied solely on concrete blocks, which offer high thermal mass, yet no recycled materials were utilized, and water management practices were not implemented. While most building materials were locally sourced, the absence of modular coordination indicates inefficiencies in design. The study underscores the need for a more integrated approach to sustainable design in university hostels, offering targeted recommendations that prioritize environmental responsibility while addressing the specific needs of female students in Kaduna state, Nigeria.

A Stackelberg game-theoretic trade credit model with credit response time length through credit function

2025-02-12T11:03:17+00:00

The nature and effect of credit period CP has been one of the major focuses and concerns in modelling TC settings. Only very little has been done on the distance in time between credit periods of channel members, which can be referred to as credit response time length. This work considers a supplier-retailer supply channel in which the supplier provides trade credit to the retailer, and allows a delayed repayment time. The retailer in-turn allows a delayed repayment time, and also aids sales by engaging in product promotion. It models the channel members’ payoff using credit function, and explores two channel structures: a situation involving TC, and another without TC. It obtains a closed-form optimal promotion effort, credit period and Stackelberg equilibrium solutions for the payoffs. The work examines the effect of the supplier’s CP and credit response time length on promotion and payoffs. It shows that while large credit period provision from the supplier will translate into large promotion effort, a large credit response time length – early repayment – requires a large promotion effort. It further shows that both players’ payoffs continuously increase with credit period, with the supplier benefiting more from the increase. On the other hand while the supplier’s payoff continuously reduces with increasing credit response time length, the reverse is the case with the retailer. Being the channel leader, the supplier’s interest, can lead to making policies that can constrain the retailer to delay repayment until his optimal profit is achieved. In general the players perform better with credit scenario than no-credit scenario. Further, the supplier can opt for very early repayment provided he has a favourable agreement which will earn him larger payoff than what obtains in the other scenarios since the channel payoff in this situation is larger.

Assessment of heavy metals contamination: A study in the industrial tannery waste disposal site of national institute of leather and science technology (NILEST), Zaria

2025-02-12T11:06:45+00:00

Heavy metals, such as chromium, cadmium, lead cupper and others, pose significant environmental risks. Elevated levels of these metals can result in soil and water contamination, adversely affecting both ecosystems and human health. This study aims at investigating the presence and distribution of heavy metal contamination in leather research tannery disposal site, to identify its sources and propose effective remediation strategies to mitigate environmental and health risks. A total of five locations within the sites were chosen. The samples were collected at depth of about 15-20cm below the earth surface and thoroughly mixed to form a composite into polyethylene bags. Analytes in solids samples were transferred into solution employing mechanical sample preparation. Elemental determination of analytes was carried out using acid digestion procedures and Nitrichydrochloric acid (HNO3-HCl) at the ratio of 3:1. Heavy metals; (Cr, Pb, Co, Cd, Cu, Ni, Fe, Mn, and Zn) presence were identify in the samples and their concentrations determined using Buck Scientific model 210 VGP Atomic Absorption Spectrophotometer with deuterium background correction lamp. This result revealed the following heavy metal concentrations; Cr, Pb, Co, Cd, Cu, Ni, Fe, Mn, and Zn in the studied area and identified significant levels of heavy metals contamination in the tannery waste disposal site Cr, Pb, Co, Cd, Cu, Ni, Fe, Mn, and Zn, with Chromium, Iron, Manganese and Zinc showing notable amount ranging from 14.3-1249.3 mg/Kg These findings present a genuine environmental concern, contributing a valuable insight to the understanding of heavy metal contamination and provides a baseline for informed decision-making in environmental management.

Efficacy of honey against clinical isolates of Staphylococcus aureus and Pseudomonas aeruginosa

2025-02-12T11:09:39+00:00

Skin serves as the first line of defense of the body against invading microorganisms. When it becomes compromised due to a cut or a burn, infections may set into the wound. Honey produced by bees can serve as an alternative treatment to available antibiotics to which microorganisms are already becoming resistant to. This study was undertaken to evaluate the efficacy of honey sold in Samaru, Zaria against bacterial wound isolates. Proximate compositions of two honey samples were determined. Pure isolates of P. aeruginosa and S. aureus were challenged against a pool of the two honey samples that passed sterility test using agar well diffusion method. The MIC and MBC of the honey were determined using tube dilution method. The honey samples had a mean pH of 4.93, with composition of 76.23% carbohydrate, 0.16% ash, 2.23% lipid and 3.45% protein. The honey demonstrated its highest activity against P. aeruginosa (20.0 mm), than S. aureus (16.0 mm) at a concentration of 100%v/v. Activity of the honey reduced with reducing concentration, until no activity was recorded at a concentration of 25%v/v. The MIC of the honey was 25%v/v against S. aureus and 12.5%v/v against P. aeruginosa. However, the MBC of the honey against S. aureus and P. aeruginosa was 25%v/v each. This study confirms that honey sold in Zaria possess antibacterial activity against wound pathogens.

New records of fungal endophytes from Unilorin Sugarcane plantation using internal transcribed spacer gene sequences

2025-02-12T11:15:51+00:00

Fungal endophytes are beneficial microbes that confer an added advantage to plants by colonizing their intercellular spaces without causing any harm. Instead, they produce secondary metabolites that play a considerable role in improving the medicinal qualities and protection of the host plants. There are several reports on fungal endophytes isolated from different plants but no report yet on fungal endophytes of Blighia sapida and Euphorbia heterophylla. These two plants were found growing in the Unilorin Sugarcane plantation as weeds. Leaf samples were collected from the plants, sterilized, and cultured on potato dextrose agar (PDA) for seven days. Emerging fungal mycelia from the leaves were subcultured to obtain pure culture and used for DNA extraction. We used the Internal Transcribed Spacer (ITS) region gene sequence analysis of fungi DNA for the identification of two new records of isolated fungal endophytes of these two plants. The extracted DNA was amplified using Polymerase Chain Reaction (PCR), sequenced and analyzed using the computer softwares; AliView and MEGAX. Molecular phylogeny inferred using maximum likelihood phylogenetic tree based on the ITS DNA sequences showed the relationship between the isolated fungal endophyte and the closest identified relatives from NCBI GenBank. Fungal endophyte isolated from B. sapida had the highest sequence similarity to Curvularia lunata, and isolate from E. heterophylla had the highest similarity to Chaetomium globosum. These two results represent the first reports of the fungal isolates as new records of endophytes from their respective host plant. The implications of these new records are fully discussed.

Comparative study of heavy metals in wild catfish (Clarias gariepinus) from Jabi Lake and cultured catfish from Gwagwalada fish market Abuja

2025-02-12T11:23:49+00:00

Pollution of heavy metals affect aquatic environments due to rise in natural processes and anthropogenic activities. The aim of the study was to analyse heavy metals in wild catfish from Jabi Lake and cultured catfish (Clarias gariepinus) from Gwagwalada fish market in Abuja. The specific objectives were to compare the presence of heavy metals (Cr, Cu, Fe, Pb, and Cd) in wild and cultured Clarias gariepinus. A total of 80 Clarias gariepinus were used for the study. Forty (40) fish from each group were purchased from Jabi Lake and Gwagwalada fish market respectively. The fish samples were prepared and digested using nitric acid and Sulphuric acid in a ratio of 3:1 for about 1 hour using a hot plate. The digested solution was taken to the fully automated PC-controlled double-beam iCE 300 Atomic Absorption Spectrophotometer for analysis. The result showed the presence of the five heavy metals. The mean levels of lead (Pb) and Cd in the cultured fish were (2.929 ±0.707) and Cd (0.1867 ±0.508) respectively. The result of the lake wild cat fish showed Pb > Fe > Cr > Cd > Cu while that of the catfish cultured in Gwagwalada market showed Pb > Fe > Cr > Cd > Cu. The study's finding showed that wild catfish had greater concentrations of heavy metals than cultured fish.

Assessment of contractile effect of Trema orientale (Cannabaceae) root bark extracted with methanol on uterus of non-pregnant rat

2025-02-12T11:28:11+00:00

Charcoal-tree, Trema orientale (L.) Blume (Cannabaceae) (syn. T. orientalis) has a range of uses in African traditional medicine such as the treatment of respiratory ailments, gonorrhea, yellow fever, and toothache, while the root bark is used traditionally to induce labour. This study evaluated the possible contractile effect of methanol (MeOH) crude extract of the root bark of T. orientale on the isolated uterus of oestrogenised non-pregnant female rats suspended in physiological salt solution (PSS). The effect of MeOH extract (0.2-4.0 mg/mL) on spontaneous uterine tissue contraction in physiological salt solution (PSS) was determined. Similarly, 1.0 mg/mL extract was tested on uterine tissues pre-contracted with oxytocin (6.7 μg/mL) in PSS and in the calcium-free medium. Finally, tissue was precontracted with high KCL concentration (80 mM, 1 mg/mL) followed by adding extract (10 mg/mL). Amplitude and frequency of contraction were measured in all cases. Extract elicited dose-dependent increases in amplitude (0.347 – 1.252 gr) and frequency (8 – 19 peaks/min) of spontaneous uterine contraction. For the oxytocin pre-contracted uteri in normal PSS and calcium-free-PSS, as well as high KCL concentration-induced contraction, decreases in amplitude and frequency of contractions were recorded, suggesting the plant did not potentiate the effects of these agonists. Trema orientale root bark methanol extract demonstrated tocolytic properties on a preliminary basis, not contractile.

Reliability of supervised topic models over unsupervised topic models for the prediction task

2025-02-12T11:31:02+00:00

The study investigated the depth of machine learning's capacity to perform prediction tasks. The study used textual data, specifically the daily actions of cryptocurrency (Bitcoin) dealers, which were found in news articles. The data was employed merely because it produced crowd knowledge of trade from News articles that affected the market price trend. For the goal of making predictions, 4073 pre-processed, scraped news articles from CNBC's market section website were analysed using the Latent Dirichlet Allocation (LDA) model and its variation, the Supervised Latent Dirichlet Allocation Model (sLDA). The document-term matrix and "k" with different values ranging from 3 to 200 were used to train and test the models. The study used four metrics for evaluation because of our multinomial classification method: mean absolute percentage error (MAPE), mean absolute error (MAE), root mean square error (RMSE), and R2. The outcome demonstrated that for label prediction for unlabeled new documents, the sLDA model performed better than the LDA model plus (classification or regression model). The response variable, which was tagged "users' or traders' interest," was the daily closing price of each corresponding document.

Machine learning prediction models of birth weight of new born babies in FCT Abuja, Nigeria

2025-02-12T11:35:11+00:00

This research aimed at creating a machine learning model for predicting birth weight using the maternal risk factors that have been found to be associated with low birth weight. The data covered a period of ten years from 2010 to 2019 was utilized where the variables were extracted from the births recorded file. The study population included mothers between the age of 15 to 49 years. The machine learning algorithms employed were logistic regression, Decision trees, Random Forest, Support Vector Machines, Gradient Boosting and K -Nearest Neighbors, Neural Network, Gradient boosting and Linear Regression. The metrics used for classification method were Accuracy, Sensitivity, Specificity and Kappa. In terms of accuracy, the best machine learning model was the Decision tree with an accuracy of 0.9823. The other five models produced an accuracy that ranged between 0.9806 to 0.9822. Based on the kappa, decision tree again emerged to be the best with a value of 09631. The rest of the models had a kappa that ranged from 0.8859 to 0.9592. Sensitivity was also evaluated and Neural Network and support vector machine had the same sensitivity value of 0.9941 whereas the other models managed a recall score ranging from 0.9501 to 0.9853. Moreover, Specificity was also examined. Logistic Regression model had the best specificity value of 0.9908. The rest of the models ranged from 0.9378 to 0.9778. Furthermore, the ROC curves of all the tested models were plotted and the area under the curved evaluated. The decision tree had the highest area under the curve of 0.9896. The AUC of the other models ranged from 0.9440 to 0.9816. Therefore, from these results based on the performance metrics and ROC-AUC, decision tree emerged to be the most robust model for classification method. Furthermore, the ROC-AUC was used to test the classification ability of the models to differentiate between the low-birth-weight cases and the cases without low birth weight.

A hybrid transfer learning model with optimized SVM using honey badger optimization algorithm for multi-class lung cancer classification

2025-02-12T11:39:00+00:00

Lung cancer is a fatal disease with a high mortality rate in patience. Early and accurate detection of this disease plays a crucial role in improving a patient's chances of survival. Traditional methods, such as Computed Tomography (CT) scans, have historically been employed for tumor localization and assessing cancer severity. However, these methods are time-consuming and may pose risks, including patient mortality before tumor identification. Given the challenges associated with lung cancer classification and the limitations of existing practices, there is a pressing need for innovative clinical data assessment tools to complement biopsies and offer a more precise characterization of the disease. Recent literature suggests the application of deep learning techniques for lung cancer detection. However, efficient training of deep learning models requires a substantial amount of data, and the availability of annotated data for lung cancer detection is often constrained, potentially resulting in overfitting or under-fitting issues and inaccurate predictions. To address these challenges, this dissertation proposes a novel deep learning architecture based on the hybridization of three pre-trained models with a support vector machine (SVM) optimized using the honey badger optimization algorithm (HBA). The process involves pre-processing the input images to ensure compatibility with pre-trained models, implementing augmentation techniques to expand the dataset and prevent overfitting, and employing a hybrid model consisting of AlexNet, VGG16, and GoogleNet for feature extraction. The extracted features are combined to generate hybrid features, which are then fed into a multi-class SVM optimized with HBA for classification. The proposed model was trained and tested using a lung cancer dataset from Iraq-Oncology Teaching Hospital and the National Centre for Cancer Diseases (IQ-OTH/NCCD), comprising 1190 images across three categories: normal, benign, and malignant. The model underwent validation and was compared with existing literature works. The results demonstrated superior performance, achieving an overall accuracy of 98% in accurately detecting different categories of lung cancer. This result demonstrates the capability of the proposed model compared to other existing models from the literature.

Production and characterization of Zeolite-A nanoparticles for the treatment of pharmaceutical wastewater

2025-02-12T11:42:08+00:00

This study investigated the production and characterization of Zeolite-A nanoparticles for treating pharmaceutical wastewater. The Zeolite-A exhibited a surface area of 17.06 m²/g, pore size of 9.206 nm, and pore volume of 0.1946 cc/g, highlighting its suitability for adsorption. The adsorption efficiency was evaluated based on contact time, dosage, and temperature. Significant adsorption occurred within the first 20 minutes for chromium (Cr), iron (Fe), and copper (Cu), with concentrations reaching near saturation, followed by minor declines. For Cr, concentrations peaked at 52.6 μg/g, Fe at 48.32 μg/g, and Cu at 42.31 μg/g, before slightly decreasing. The effect of adsorbent dosage showed that increasing the dosage from 0.4 g to 1.2 g significantly enhanced metal removal, with Cu rising from 34.62 μg/g to 96.12 μg/g, Fe from 41.83 μg/g to 92.15 μg/g, and Cr from 43.51 μg/g to 94.16 μg/g. Temperature analysis revealed improved adsorption at higher temperatures, with Cu increasing from 29.1 μg/g at 30°C to 62.15 μg/g at 70°C, Fe from 26.16 μg/g to 55.9 μg/g, and Cr from 28.16 μg/g to 73.7 μg/g. These findings suggest that Zeolite-A nanoparticles effectively remove toxic metals from pharmaceutical wastewater, offering the potential for large-scale wastewater treatment.

Numerical solutions of fractional conformable derivative using a generalized Kudryashov method

2025-02-12T11:46:58+00:00

This paper addresses the numerical solutions of fractional differential equations (FDEs) using the Generalized Kudryashov Method (GKM) in the context of the conformable fractional derivative. Fractional calculus, particularly the conformable derivative, provides a versatile framework for modeling systems exhibiting memory and hereditary properties commonly found in complex physical phenomena. Traditional integer-order derivatives lack the capability to accurately represent such dynamics, which fractional derivatives effectively handle. The conformable derivative, a recent addition to fractional calculus, retains many advantageous properties of integer-order differentiation, such as the chain rule, while extending to non-integer orders. The Generalized Kudryashov Method, initially developed for solving nonlinear ordinary differential equations, is adapted here to address nonlinear FDEs involving conformable derivatives. By employing a traveling wave transformation, the study converts fractional partial differential equations into ordinary differential equations, facilitating the application of GKM. Through this approach, the study derives numerical solutions, demonstrating the method’s ability to capture complex dynamics in nonlinear fractional systems. The results indicate that GKM, in conjunction with the conformable derivative, offers a robust tool for accurately approximating solutions of FDEs, with potential applications across fields such as fluid mechanics, quantum mechanics, and anomalous diffusion.

Enhancing code generation accuracy using fine-tuning and task-adaptive pretraining with domain-specific data augmentation

2025-02-12T12:13:50+00:00

Recent advancements in deep learning, particularly through Transformer architectures, have significantly improved code generation tasks. However, current pre-trained language models still encounter limitations when applied to code generation. The Improved RoBERTaMarian model, built upon the Marian neural machine translation framework, addresses these limitations by fine-tuning on natural language descriptions to generate code. The model was trained and tested on Django and CoNaLa datasets. The results in the CoNaLa dataset, was BLEU score of 36.834, Exact Match Accuracy of 15.300%, SacreBLEU score of 34.215, and ROUGE score of 49.827, reflecting its ability to generate accurate and semantically aligned code. Similarly, when evaluated on the Django dataset, the Improved RoBERTaMarian model outperformed BERTMarian, ELECTRAMarian, LUKEMarian, MarianCG and RoBERTaMarian models with a BLEU score of 91.230, Exact Match Accuracy of 83.676%, SacreBLEU score of 75.984, and ROUGE score of 95.210. These results indicate that the Improved RoBERTaMarian model excels in both syntactic and semantic code generation, making it a robust solution for applications requiring precise, contextually relevant code generation. Its high performance suggests significant potential for use in automated code synthesis and language model-based code assistants in software engineering tasks.

Preparation and characterization of MoO₃ nanoparticles for the photocatalytic degradation of dyeing wastewater

2025-02-12T12:17:17+00:00

This study focuses on the preparation and characterization of MoO₃ nanoparticles for the photocatalytic degradation of dyeing wastewater. The XRD pattern of MoO₃ shows distinct peaks at 2θ values of 12.8°, 23.4°, 25.7°, 27.3°, and 39.0°, corresponding to specific crystal planes and confirming its α-MoO₃ phase, validated against JCPDS card number 05-0508. The morphology reveals stacked or crumpled particles with a high surface area conducive to catalytic activities. EDX analysis identifies molybdenum (Mo) and oxygen (O) with characteristic peaks at 2.29 keV (Mo Lα), 17.48 keV (Mo Kα), 19.63 keV (Mo Kβ), and 0.52 keV (O Kα), confirming the material's composition. MoO₃’s layered structure, influenced by van der Waals forces, offers unique interlayer spacing advantageous for photocatalytic processes. Photodegradation experiments showed progressive efficiency: at 10 minutes, MoO₃ achieved 8.58%; by 40 minutes, it increased to 30.42%, and at 50 minutes, reached 42.3%. Efficiency peaked at 60 minutes with 50.52%, progressing to 60.8% at 70 minutes and 71.03% at 90 minutes, finally achieving 75.25% at 100 minutes. These results demonstrate MoO₃ nanoparticles' effectiveness in degrading dye pollutants, highlighting their potential for sustainable wastewater treatment applications.

Assessment of bacterial contamination of irrigated vegetables cultivated along the Kubanni irrigation site in Zaria, Nigeria

2025-02-12T12:21:17+00:00

Bacterial contamination of vegetables becomes a significant health challenge. This study identified and categorized bacterial contaminants in vegetables cultivated along the Kubanni irrigation area in order to inform consumers about their safety and quality. Aerobic Colony Count, Gram Stain and Biochemical test was conducted on five vegetables which include cabbage, lettuce, spinach, onion and tomatoes. Samples were obtained from 25 farmlands within the study area. A total of 175 samples of vegetables, soil and irrigation water were analyzed. Result shows that all the vegetables were contaminated with bacteria above the WHO limits of 102. Spinach, cabbage, lettuce, onion and tomatoes recorded 5.1 x 10⁶, 5.7 x 10⁶, 5.2 x 10⁶, 4.8 x 10⁶, and 4.6 x 10⁶ respectively. Cabbage had the highest ACC while tomatoes had the lowest. ACC for the Kubanni River is 4.7 x 10⁶ against the WHO limit of <500. Soil recorded highest ACC (6.1 x 10⁶) than irrigation water (4.7 x 10⁶). Correlation analysis shows that bacteria in all the vegetables and that of soils are positively related except lettuce and tomatoes. It also shows a positive relationship between bacteria in irrigation water and all vegetables except onion and tomatoes. Bacillus is the most prevalence gram positive bacteria with 57 (45%) while Citrobacter and salmonella are the most prevalent gram negative bacteria in vegetables with 38 (30.4%) and 28%. Vegetables should be properly cleaned before consumption.

Influence of land use and land cover changes on flood susceptibility in Karadua River Basin, Katsina State, Nigeria

2025-02-12T12:25:41+00:00

This study examines land use and land cover (LULC) changes and their impacts on flood susceptibility in the Karadua River Basin, Katsina State, Nigeria, between 2017 and 2023. Supervised classification of Landsat imagery was conducted, with spatial integration and extraction by polygon. Weighted and decomposition analyses were applied to deduce the influence of LULC on flood susceptibility in the study area. The results revealed that the classified LULC achieved high classification accuracy (overall accuracy > 84%, Kappa coefficient > 0.81). Additionally, agricultural land was identified as the dominant LULC type, covering over 98% of the area, though it declined slightly (-0.20%). Built-up areas increased significantly (118.06%), indicating rapid growth, while vegetation and water bodies declined by 50.40% and 26.47%, respectively. The decomposed weighted analysis of the Soil Conservation Service Curve Number (SCS-CN) method and LULC highlighted changes in infiltration and runoff across different LULC classes and soil types, with the growth of built-up areas and vegetation loss contributing to increased flood susceptibility. These trends underscore the need for sustainable land-use practices to mitigate environmental degradation and reduce flood risks in the basin.

Effects of soil salinity on sustainability of crop production in Gusau Local Government Area, Zamfara State, Nigeria

2025-02-12T12:29:34+00:00

The sustainability of agricultural production on the soils in the Sudano-Sahelian agroecological zone needs current information on the salinity status for appropriate management practices. This paper assessed the effects of soil salinity on the sustainability of crop production in Gusau, Local Government Area, Zamfara State. Soils were sampled from a polygon layer of grid stratification map of Gusau LGA at 0 - 20cm depth, a total of 8 polygon layers with over 50% proportion were selected for the collection of samples. Three soil samples were collected purposively at three different locations to produce eight composite soil samples. Soil parameters that were analyzed include Electrical Conductivity (EC) and Total Dissolved Solids (TDS) which are crucial in determining salinity level. Classification chart was used to classify the soils based on various degree of salinity. The results of the soil samples were interpolated using Inverse Distant Weight (IDW) to create maps of the spatial distribution of salinity level across the study area. Modis 13Q1 NDVI data of the study area from 2000 to 2020 were acquired from LP DAAC. The Area of Interest (AOI) and data attributes were selected. The data was used to show the vegetation responsive changes from salinity, which serves as an indirect method of detecting salinity. The EC values shows non salinity (0 to 2 dS/m), low salinity (2 to 4 dS/m) and mild salinity (4 to 5.7 dS/m). TDS ranged from non-hazard (140 ppm) to high hazard (465 ppm). Non-hazard class ranged (< 150 ppm), low hazard (150 to 250 ppm), medium hazard TDS (250 to 300 ppm) and high hazard (300 to 500 ppm) were found spatially distributed in different parts of the study area. A sustainability map of the study area from the severity of soil salinity which determined different management practices shows three sustainability classes of soils, very sustainable soils, sustainable soils and less sustainable soil. The study concludes that soils in Gusau ranges from moderate salinity towards the North and Central part of the study area and low in the Southern part. By implication, the soils in the North and Central areas can only sustain crops that are not sensitive to salinity. It is recommended that farmers should review their farm management strategies on soils with risk of salinity in order to reduce the rate and implications in the area.

Mathematical modelling and simulation of effective production of non-isothermal transient hydrogen natural gas mixture using FVSM

2025-02-12T12:33:50+00:00

Mathematical modelling and simulation of effective production of non-isothermal transient Hydrogen Natural Gas mixture is an important phenomena in gas producing industries. Gas mixture production is a production of natural gas mixed with hydrogen which remain a problem to gas producing industries. During production transient pressure is usually generated by rapid and sudden closure of shut-off valve at wellhead and the flow environment. Many authors in gas producing industries consider gas as a single substances and does not consider the production of natural gas mixed with hydrogen. In this work a one-dimensional transient compressible model comprising conservation of mass, momentum and energy which incorporate hydrogen natural gas mixture equation with the properties of flow environment has been developed with the aim of determining the effect of the mixture on the flow parameters. The model was solved using flux vector splitting method (FVSM). The effect of body force on transient pressure and sound wave due to the well flow geometry including the effect of hydrogen mass ratio has also been discussed. The results obtained when considering isothermal flow in a well of 700 ft deep using different wellbore diameter 0.073 m, 0.088m different time and different thermal conductivities shows good agreement with published results. For non-isothermal flow, the pressure and sound wave are observed to be increasing when the hydrogen mass ratio are increased. The heat exchange between the flowing fluid and the well flow environment increase the temperature of the flowing fluid. The result of this work reflect gas flow law and has provide a technical way forward for production of hydrogen natural gas mixture to all gas producing industries.

Mathematical modelling and simulation of pressure, temperature, and velocity distribution of two-phase flow in a producing gas well

2025-02-12T12:46:05+00:00

Mathematical modelling of pressure, temperature, and velocity distribution of two-phase flow in a producing gas well is an important phenomena in the management, design, and dynamic analysis of the wells. Many studies in producing gas wells focuses mostly on single phase gas flow during production but pressure traverses in two-phase flow differs from single phase due to the differential flow rates of the different phases and using single phase model may result to insufficient prediction leading to premature closure of wells. This work considered a one-dimensional time-dependent homogeneous model which represents a system of partial differential equations to describe mathematically the transient two-phase gas-liquid mixture flow in a producing well. The numerical solution of the mathematical model, which consists conservation of mass, momentum, and energy equations based on finite difference technique in the implicit scheme has been applied. PVT correlation is used in estimating the thermodynamic and transport properties of the fluids. From the results obtained, it was observed that Joule-Thomson affect sensitively in the prediction of pressure and other flow parameters which agreed with existing work. The curves obtained reflect the gas flowing law which can provide technical reliance and dynamic analysis of multiphase producing gas wells.

Adsorptive kinetic mechanisms of bromocresol green dye removal from wastewater using modified groundnut shell adsorbent

2025-02-12T12:50:35+00:00

This study explores the production and application of modified groundnut shell (MGNS) adsorbent to remove Bromocresol Green Dye (BCGD) from wastewater as an alternative to cost intensive wastewater treatment technologies. The adsorbent was characterized for physicochemical properties, and by employing Scanning Electron Microscope (SEM), Fourier Transform Infrared (FTIR) and Energy dispersive X-ray spectrometers (EDX) as characterization tools respectively. The effects of contact time on the percentage of dye recovery were evaluated. The kinetic data were fitted to kinetic models such as Brouers Weron Sotolongo-Coasta (BWS), Fractal Pseudo-second-order (FPSO), Pseudo-First-Order (PFO), Pseudo-second-order (PSO) models using a non-linear form of the equations. The results revealed that the biomass has a pH (6.60), moisture content (14.20) %, volatile matter, (10.20) %, Ash content (8.10) %, fixed carbon (65.50) %, bulk density (0.440) g/cm³, surface area (690) m²/g and particle size (250) μm. The adsorbent possesses high carbon content and a well-developed pore structure. The adsorbent percentage dye removal efficiency (% R) was time-dependent (30 min). The adsorbent has maximum percentage dye removal of 84% at the optimum time. The kinetic data that best described the removal of BCGD from wastewater was BWS (R² = 0.9644). Overall, the prepared adsorbent from MGNS was efficient, eco-friendly and economically viable in treating dye polluted wastewater, ensuring regulatory compliance and facilitating water reuse.

Effects of sun-dried cassava peels on growth performance in Red Sokoto does (Capra aegagrus hircus) during gestation

2025-02-13T05:48:30+00:00

This study was conducted to evaluate the potentials of graded levels of sun-dried cassava peels as alternatural energy source to replace maize offal in supplement diets for pregnant Red Sokoto (Maradi) does. Five (5) supplementary diets were formulated to contain Sun-Dried Cassava Peels (SDCP) at levels of 0, 18.5, 37.0, 55.5 and 74.0%. A sixth diet contained Cotton Seed Cake (CSC) without maize offal, and SDCP. Treatment 1 and 6 containing 0% supplementation of SDCP served as the control diets. The diets were iso-calorific and iso-nitrogenous. Thirty (30) pregnant Red Sokoto does aged between 1.5-2.0 years were weighed and equally allotted to six (6) treatments at a means of 26.1-26.6kg in a Randomize Complete Block Design. The goats were fed at 1.5% weekly live weight. After supplementation for two hours (8:00-10:00am) each morning, they were released to graze on natural pasture within a specified paddock. Results obtained showed that the daily dry matter intake (DMI/head) in treatment 6 was significantly higher than Treatments 1 and 5. Although, the supplementation of SDCP recorded low CPI compared to the two controls, their increasing levels of supplementations also showed a decreasing tendency on CPI. There were no significant differences between Treatments 3 and 4 for crude protein intake (CPI), although Treatment 1, 2, 5 and 6 differ significantly (P<0.05) for CPI. Treatment 6 recorded higher CPI (103.1 g) while Treatment 5 was lower (43.1 g). The efficiency of dry matter utilization (EDMU) and efficiency of crude protein utilization (ECPU) were not significantly (P>0.05) different for all treatments. The higher average daily gain (ADG) 67.4 g was obtained in Treatment 3 and the least (14.3 g) in Treatment 4. The results obtained for ADG in Treatment 3 was significantly higher than Treatment 4 only (P<0.05). the higher final mean live weight of 32.2kg was obtained for Treatments 3 and 6. Treatments 1, 2, 4 and 5 were not significantly (P>0.05) different. Based on the results of this study, Maize offal can be replaced with up to 74% Sun dried Cassava peels in the diet of Red Sokoto Does grazed on natural pasture during gestation without adverse effect on growth performance.

Climate change-resilience farming model for enhanced food security and sustainable development in Sub-Saharan Africa

2025-02-13T05:52:27+00:00

The devastating impact of climate change on the agricultural sector threatens farmers' livelihood, food security, and environmental sustainability. This study identified trends in crop production reports, harvest reports, and climate change trends to provide critical information necessary to tackle chronic food insecurity and enhance environmental sustainability in West Africa. A systematic search of national and international organizations' databases, Google Scholar, Scopus, AgEcon Search, and Web of Science for peer-reviewed publications from 2010 to 2024 on Climate-smart agriculture practices in Sub-Sahara Africa was carried out. The results showed that Rwanda had the highest percentage of banana production (80.46 %) while Benin had the lowest (0.84 %). Nigeria had the highest Cassava production (67.65 %) while Burkina Faso recorded the lowest (0.02 %). On trends in yield harvested, Senegal had the highest banana yield (100 kg/ha), while Benin had the lowest (4.26 kg/ha). Overall, there was low yields and disruptive food production systems in West African countries. To curb with this challenge, there is a need for increased sensitization and awareness among farmers to adopt the climate-smart agriculture model, provide incentives and markets to help reduce chronic food insecurity and ensure environmental sustainability.

Magnetohydrodynamic flow of third-grade nanofluid with convective boundary conditions

2025-02-13T05:54:56+00:00

The research focuses on boundary layer flow of an incompressible third grade nanofluid over a stretching surface under impact of convective boundary condition with presence of thermophoresis, Brownian motion, Newtonian heating, viscous dissipation and chemical reaction. Governing nonlinear equation of velocity, temperature and nanoparticle concentration modelled the problems are solved via shooting method and sixth-order Runge-Kutta. Results of velocity, temperature and nanoparticle concentration profiles are plotted and discussed for various values of fluid parameters such as Prandtl number, Lewis number, thermal biot parameter, chemical reaction parameter, Eckert number and thermophoresis and Brownian motion parameters. Numerical computations are performed. The results show that the change in temperature and nanoparticle concentration distribution functions is similar when we use higher values of material parameters. It is seen that the temperature and thermal boundary layer thickness are increasing functions of chemical reaction parameter Kr. An increase in thermophoresis and Brownian motion parameters tends to an enhancement in the temperature. Also increase in Eckert number resulted to rise in fluid temperature

Geospatial quantification of the polycyclic aromatic hydrocarons (PAHs) in the wetlands of Kolokolo and environs (oil bearing communities), Warri North, Delta, Nigeria

2025-02-13T05:59:51+00:00

This study was an ex-port factor research that investigated the content of PAHs in the wetlands in Kolokolo and environs. The study answered 5 research questions and tested a hypothesis. To achieve these, the wetlands in the 5 settlements were mapped into 5 sampling grids of 50 meters apart and water samples were collected from 5 spots with 125mL plastic sampling bottles at 10cm depth and covered sub surface. The samples from each grid were bulked, composites drawn and fixed with HNO3 and stored in ice cooled flasks for analysis. The analytical standard adopted was EU 1881/2014 while the instrument of determination deployed was Agilent GC/MS Triple Quadruple model 7000. The mean result obtained were; pyrene 1.02 ± 0.01μg/l, chrysene, 1.02±0.01 μg/l, BaP; 1.03 ± 0.01μg/l BaA; 1.02 ±0.02ug/l and BbF, 1.03 ± 0.02μg/l. The mean results were subjected to test of significance with ANOVA using SPSS IBM model 29 at 0.05 level of significance and the p value was 0.042 thus rejecting Ho. The study concluded that the wetlands are contaminated with PAHs above EU 1881/2014 MPC for wetlands thus the produce are not fit for human and animal consumption. They are equally not exportable. The study recommended that the oil companies should be compelled to adopt world best practices in their operational activities, the monitoring agencies NESREA and NOSDRA should scale up their surveillance and the impacted ecosystem should be remediated and restored.

Assessment of Per- and Polyfluoroalkyl Substances (PFAS) in drinking water sources in Abakaliki, Nigeria

2025-02-13T06:05:44+00:00

The drinking water sources in Abakaliki, Nigeria were investigated for PFAS concentration. PFAS has been known for its bioaccumulation in the food chain, causing a detrimental health effect to humans when contaminated food is ingested. 13 targeted PFAS were analyzed using a Gas Chromatography-Mass Spectrometry (GC-MS) technique. This method allowed for the identification and quantification of specific PFAS compounds present in the sample. Perfluorohexanoate (PFHX1), N-methylperfluorooctanesulfonamide (MeFOSA), and N-ethylperfluorooctanesulfonamides (ETFOSA) were the only perfluoroakyl substances found others were fluorotelomers which are polyfluoroalkyl substance and there were the predominant PFAS obtained in this study. The mean sum of the targeted PFAS (⅀PFAS) across all the samples analyzed ranged from 0.22±0.06 mg/L (sample A3) to 7.20±1.82 mg/L (sample C4). The mean value of the PFAS obtained in samples A1 to A5 ranged from 0.22±0.06 mg/L (samples A3) to 0.59±0.12 mg/L (sample A1) while the mean values of samples B1-B5, C1-C5, and D1-D5 ranged from 0.35±0.08 mg/L (B1) to 1.14±0.21 mg/L (B5), 0.64±0.04 mg/L (C3) to7.20±1.82 mg/L (C4) and 0.63±0.04 mg/L (D1) to 3.61±1.08 mg/L (D4) respectively. PFAS are contaminants of emerging concern whose toxicity is of environmental and health concern. However, the detection of PFAS in water is gradually decreasing because of the restriction of PFAS and its industrial applications, which result from environmental and health-associated problems.

In vitro protective effect of Telfairai occidentalis (fluted pumpkin) leaves against oxidative DNA damage induced by reactive oxygen species

2025-02-13T06:08:53+00:00

Oxidative DNA damage is an inevitable consequence of cellular metabolism leading to reactive products that cause cellular damage. Telfairai occidentalis is a tropical vine grown in West Africa as a vegetable and for its edible seeds. This study aimed to evaluate the in vitro protective effect of T. occidentalis leaves extract against DNA damage induced by Fenton’s system. T. occidentalis leaves were extracted using three solvents; water, n-butanol (n-BuOH) and ethyl acetate (EtOAc). pVax plasmid DNA (476 ng) was incubated with Fenton’s system (FeSO4/H2O2) in the presence/varying concentrations of the extract (10 mg/mL, 5 mg/mL and 1 mg/mL) at 37°C for 30 minutes while the control was devoid of extract. The incubate were analysed in 0.8 % agarose gel. The ethyl acetate and the butanolic extract were subjected to GC-MS analysis. The protective effect of T. occidentalis leaves extracts demonstrated an effective protective activity against oxidative stress-induced DNA damage and was dose-dependent with higher dose being most protective. Oleic acid and 3-hydroxy benzoic acid were found to be most likely the bioactive components of the butanolic and the ethyl acetate extract respectively.

Incidence of multidrug resistant bacteria in selected sachet water sold in Malete, Nigeria

2025-02-13T06:14:04+00:00

The proliferation of packaged water in rural communities has been exacerbated by the increasing demand for safe and potable water in areas where access to clean water sources remains a significant challenge. Unfortunately, non- compliance of some sachet water producers to adhere the standards regulations exposes the consumers to potential risks of waterborne diseases. Therefore, this study investigated the susceptibility profile of bacteria isolated from selected sachet water sold in Malete. Ten different brands of sachet water (B1- B10 NAFDAC registered) were randomly purchased from retailers in Moro LGA, Malete, Nigeria to assess their physicochemical, bacteriological quality and their susceptibility to antibiotics. Bacteriological analyses were carried out using membrane filtration technique. Identification of the isolates and susceptibility were done using standard methods. Physicochemical parameters measured included pH (7.01 - 7.50), electrical conductivity (12.3 - 199.3 μs/cm), alkalinity (42.67 - 73.04 mg/L), total dissolved solids (10.0 – 130.0 mg/L), turbidity (0.62 - 1.08 NTU), and hardness (54.36 - 84.22 mg/L).The total bacterial count in CFU/100mL of the sachet water sample ranged from 1.0 x10¹ - 4.7 x10¹, B4 and B1 have the lowest and the highest values respectively. The total coliform counts ranged from the lowest value of 0 CFU /100mL to the highest value of 12.0 ×10¹ CFU/100mL, no coliforms were detected in B2, B4 and B6 while B8 has the highest number of coliforms. Faecal coliforms were not detected in all the samples tested. Twenty two (22) bacterial isolates were identified phenotypically; Staphylococcus aureus, Bacillus spp., Streptococcus spp., Micrococcus spp. and Enterobacter spp. Bacillus spp. had the highest frequency of 7 (33 %) followed by Micrococcus sp. with a frequency of 6 and a percentage frequency of 29 %. Staphylococcus aureus also have a frequency of 4 and a percentage frequency of 19% while Enterobacter sp. and Streptococcus sp had 10 % and 9 % respectively. All the Gram positive bacteria obtained were resistant to amoxicillin and zinnacef and at least one other antibiotic while Enterobacter sp., the only Gram negative was resistant 4 different antibiotics; amoxicillin, augmentin and two others. This finding highlights the need for regular microbiological monitoring so as to ensure public health safety.

Phytochemical assay and antibacterial appraisal of methanolic leaf extracts of Borreria verticillate and Ageratum conyzoides against MDR nosocomial pathogens

2025-02-13T06:32:04+00:00

In a bid to find solution to the global menace of antibiotic resistance, the current work attempts to explore the phytochemical composition and validate the antibacterial potential of methanolic leaf extracts of B. verticillata and A. conyzoides against nosocomial pathogens. The test organisms namely Klebsiella pneumoniae, Acinetobacter baumannii and Enterococcus faecalis were collected from Microbiology laboratory, Nigerian Navy Reference Hospital, Calabar, Nigeria. The bacteria were authenticated by standard microbiological methods. Multi-drug resistance attribute of the organisms was determined by Kirby Bauer disc diffusion technique. Methanol was used as solvent for plants’ extraction by the aid of Soxhlet apparatus. Phytochemical evaluation was carried out using standard protocol and subjected to GC-MS analysis. The in vitro antibacterial potentials of the plants’ extracts were investigated against the bacterial isolates using agar well diffusion technique. Results revealed the presence of saponins, alkaloids, cardiac glycosides, flavonoids, steroids, tannins, phenols and volatile oils in the methanolic leaf extract of B. verticillata. Also, extract of A. conyzoides indicated the presence of alkaloids, cardiac glycosides, saponins, flavonoids, phenols, volatile oils and tannins. GC-MS investigation showed the detection of hexadecenoic acid, methyl ester, 11-0ctadecanoic acid, methyl stearate, 9-octadecanamide, 1,2-benzenedicarboxylic acid and butyl-2-ethylhexyl ester in A. conyzoides. The major components detected in B. verticillata leaf extract were 1.2-15,16-dieoxyhexadecane, 1,2-benzenedicarboxylic acid, butyl 2-ethyhexyl ester, hexadecenoic acid, 2,3-bis (trimethyl islyl) oxyl propyl ester, 9-octadecenamide, 2-ethylbutyric acid and eicosyl ester, 3-tetradecanol. It was observed that K. pneumoniae was resistant to amoxicillin, ofloxacin and clindamycin with a percentage drug resistance rate of 3(21.43%). A. baumannii was resistant to eight (8) antibiotics including vancomycin, amoxicillin+clavulanic acid and had percentage drug resistance rate of 8(53.43%). E. faecalis was resistant to five (5) antibiotics including vancomycin, amoxillicin and ciprofloxacin while the percentage drug resistance rate was 5(35.71%). The results established the fact that the bacterial isolates exhibited multidrug-resistance. B. verticillata leaf extract inhibited bacterial growth producing zone sizes ranging from 7.7 to 17.4mm. Antibacterial activity of A. conyzoides against the organisms revealed lesser zone sizes (9.6 to 14.1mm) with A. baumannii having the least zone size (12.6mm) at 100% concentration. Therefore, it can be concluded that B. verticillata and A. conyzoides present remarkable potential of producing significant plant-derived pharmaceuticals against multidrug-resistant nosocomial pathogens.

Detection of mec(a) gene in cefoxitin and oxacillin (methicillin) resistant Staphylococcus aureus isolated from ready-to-eat foods in Jos, Plateau State, Nigeria

2025-02-13T06:37:41+00:00

Staphylococcus aureus is a significant foodborne pathogen that can cause serious infections in humans, and its resistance to commonly used antibiotics poses a major public health threat. This study determined the prevalence of the mecA gene in methicillin-resistant S. aureus isolated from ready-to-eat foods sold in Jos, Nigeria. A total of 120 food samples were evaluated for bacterial load, Antibiotic susceptibility using the disc diffusion method and detection of methicillin resistance through PCR amplification of the mecA gene. The results indicate substantial bacterial contamination of the foods, with TBC ranging from 1.60 × 106 to 1.04 × 107 CFU/g and TSC ranging from 1.57 × 10⁵ to 6.15 × 10⁵ CFU/g. Among the food types, ‘suya’ showed the highest mean TBC (1.04 × 107 CFU/g) and jollof rice the lowest (1.60 × 106 CFU/g). The overall detection rate of S. aureus was 30.83%, with the highest occurrence in jollof rice (50.00%). Antibiotic susceptibility profiles revealed high resistance to oxacillin (81.9%) and cefoxitin (70.3%), confirming the circulation of MRSA in the food chain. Gentamicin (78.4%) and vancomycin (73.0%) were the most effective antibiotics, while notable resistance was found against trimethoprim (64.9%). Of 37 isolates, 26 (70.30%) were mecA carriers, with a 21.67% prevalence in the RTE foods. The Jollof rice exhibited the highest mecA occurrence (80.00%), while other popular dishes showed 50% to 70% positivity. The polymerase chain reaction amplification revealed a distinct band of the mecA genes at 533 base pairs on the agarose gel, providing strong evidence for the presence of methicillin-resistant S. aureus (MRSA) in the tested food samples. This study underscores the need for monitoring and control measures regarding MRSA in food products to protect public health.

Mathematical modelling of COVID-19 transmission dynamics in Kaduna State, Nigeria

2025-02-13T13:03:38+00:00

This study developed a mathematical model of COVID-19 infection transmission dynamics incorporating asymptomatically and symptomatically-infectious individuals, the vital dynamics such as birth rate and mortality rate, face-mask use, diagnosis of asymptomatic infectious individuals, and isolation of infected individuals as control strategy are also incorporated. The model is shown to have two unique equilibrium states, namely: the disease-free and endemic equilibrium states, and the basic reproduction number was computed using the next generation matrix operator. The results obtained from the normalised forward sensitivity index show that the contact rate, face-mask efficacy and compliance, and isolation rate are the most influential factors on the spread of COVID-19 infectious disease. Numerical simulations show that, decreasing the infection transmission parameter will also reduce the size of the infective population. From the numerical simulations and results, it is recommended that a combination of decreasing contact rate, increasing face mask compliance and efficacy, clinical diagnosis of asymptomatic individuals, and isolation of symptomatic individuals is vital to public health strategy in eradicating COVID-19 infection and death in the shortest possible time.

Advanced bagging ensemble technique for multi-crop predictive modeling to enhance agricultural decision-making

2025-02-13T13:09:38+00:00

Crop production is a cornerstone of agriculture, significantly influencing economies and farmers' livelihoods. However, fluctuating environmental conditions complicate the selection of suitable crops, requiring expertise in factors such as soil type, climate, humidity, rainfall, and temperature. Existing crop recommendation models primarily focus on a limited range of crops, such as rice, maize, and wheat, which restricts their utility across varied agricultural settings. Additionally, these models often exhibit inconsistent accuracy and high false-positive rates, undermining their reliability for practical use. To overcome these challenges, this study proposes a Bagging-based ensemble model that integrates seven machine-learning algorithms: Decision Tree, Support Vector Machine, Logistic Regression, Naive Bayes, Random Forest, K-Nearest Neighbor, and XGBoost. Leveraging a dataset enriched with diverse environmental and soil features—using soil type encoding and feature normalization—the model captures complex relationships that influence crop suitability. The ensemble model demonstrates an outstanding 99.9% accuracy, with macro-average precision, recall, and F1 scores of 99%, surpassing traditional models in performance. This advanced predictive tool offers a robust and versatile solution, enabling accurate and adaptable crop recommendations to support farmers and agricultural stakeholders in diverse environmental conditions.

Economic order quantity (EOQ) for items exhibiting delay in deterioration with price, stock, and reliability demand under partial backlogging

2025-02-13T13:13:30+00:00

The study explored an advanced EOQ model tailored for items that delay deterioration, such as perishable goods. This model incorporates price, stock level, and reliability as variables affecting demand to optimize profit per unit time under partial backlogging conditions. Differential equations that capture inventory dynamics across stages of no deterioration, active deterioration, and shortage are presented. Numerical simulations using Excel and Maple validate the model, revealing that higher stock-dependent consumption parameters and reliability increase demand and profitability. Results indicate that deterioration negatively impacts profit by reducing product quality, while longer replenishment cycles decrease profitability due to increased spoilage. Enhanced backordering boosts profit by reducing holding costs. This study highlights the importance of integrating price, stock, and reliability in EOQ models for strategic inventory management, balancing costs to maximize operational gains.

Modified Laplace-variational iteration method for solving linear and nonlinear Volterra integro-differential equations

2025-02-13T13:21:55+00:00

This study presents a modified Laplace-variational iteration method (MLVIM) designed to solve linear and nonlinear Volterra integro-differential equations (VIDEs) with specified initial conditions. The MLVIM is a hybrid approach that integrates the strengths of the Laplace transform and the variation iteration method (VIM), effectively enhancing the overall solution process by improving both the efficiency and convergence rate. Specifically, the method refines the correction functional and optimizes the handling of the integral term, which directly leads to a reduction in the number of iterations needed and decreases the associated computational complexity. To demonstrate the effectiveness of MLVIM, the study applies it to two illustrative examples involving both linear and nonlinear VIDEs, with initial conditions. The results are then compared to those obtained using the Adomian decomposition method (ADM) and the fourth-order Runge-Kutta (RK4) algorithm. The findings show that MLVIM consistently exhibits a faster convergence rate and higher accuracy compared to both ADM and RK4 in all the examples presented. The MLVIM can be applied to a broad range of linear and nonlinear VIDEs. This makes it a valuable tool with potential applications in various scientific and engineering fields, where integro-differential equations frequently arise in modeling complex systems and processes.

Energy dispersive X-ray Fluoresence Spectrometry evaluation of rock minerals in Gujeni and Tsohon Birnin Gwari Local Government Areas, Kaduna State, Nigeria

2025-02-14T06:36:13+00:00

The elemental evaluation was carried out by Energy Dispersive X-ray Fluorescence Spectrometry. The Gujeni iron ore contained Fe (76.07%), Cu(0.039%), S(1.10%), Zn(0.061%), Au(5 x10-5%), Hg(0.0012%), Ga(0.01%), As(0.0082%), Bi(0.058%), Si (20.05%) and Al(2.60%) and Tsohon Birnin Gwari gold ore contained Au(0.009%), Pb(0.045%), Ag(0.019%), Zn(0.053%), S(0.56%), Fe(90.44%), Cu(0.014%),Ga(0.043), As(0.202%), Bi(0.25%), Hg(0.27%), Si(7.0%) and Al(0.25%). The results of the analysis showed a high percentage contents of Fe in both samples but low percentage of gold. The low percentage of gold might be due to interlocking of the gold with aluminiumsilicate phase which require high pressure and temperature to release the gold metal. The results also provide baseline information on anthropogenic impact on environmental information on the mining community and the basis for planning strategy by regulated bodies for better quality environment.

Determination of Mean Sea Level from 1980 to 2018 using tidal observation data, Bonny Primary Port, Nigeria

2025-02-14T06:46:24+00:00

Mean Sea Level (MSL) is the average height of the sea for all stages of tide over 19 years; and it is obtained through tidal analysis. This research work aims at determination and assessment of the MSL for the Bonny port. Tidal data of 1980, 1994 and 2018 years of observation were employed using the Least Squares Adjustment method with MATLAB programming codes for data processing. The results of the monthly analysis were compared and subjected to statistical analysis (Mean, standard deviation, t-test and Analysis of variance (ANOVA). The difference between the computed 1980 yearly mean and that of 1994 is 3.0 mm; while that of 1994 and 2018 is 5.1 mm. The yearly variation for 1980 to 1994 is (3.0/14) mm = 0.20 mm; and for 1994 to 2018 is (5.1/24) mm = 0.21 mm. The variation for 1980 to 2018 is (0.20-0.21) mm. The results show gradual rise in MSL for the period of 1980 to 2018 as further explained by the month and the year variables. Therefore, it can be concluded that there is a gradual rise in sea level of about 0.01 mm for the period of study in Bonny which does not take into consideration the subsidence phenomenon. Although, the rate is low, however, the results suggest that the relative sea level could be much higher because there is a lot of fluid extraction.

Evaluating the quality and sensory characteristics of watermelon and apple juice blends

2025-02-14T06:49:15+00:00

The fruit juice industry is a growing globally and the practice of mixing different fruits to make a juice blend is a recent trend being exploited in the industry. Little has been done to maximize the nutrients and sweetening content. This study evaluated the quality and sensory properties of the watermelon/apple juice blend. The watermelon and apples were obtained in the ripe stages, they were washed and chopped into smaller sizes and then blended separately. The design for the study was a Completely Randomized Design (CRD). Data collection and analysis were performed on pH, Total Titratable Acidity, Total Soluble Solids, protein, ash, crude fibre, potassium, potassium, calcium, iron, copper and zinc. The study revealed that 66.67% watermelon and 33.33% apple blend (W4AM) as well as the 25% watermelon and 75% apple blend (W5AM) recorded the highest value for total soluble solids (12.167 °Brix, 12.333 °Brix) and titratable acidity (0.034%, 0.034%) respectively. W5AM blend also recorded the highest vitamin C content (9.983 mg/100 g). Generally, the proximate composition of the blends had improved nutritional components as compared to the individual juices. The results showed significant differences between the blends (p<0.01) where the sensory evaluation showed that W5AM was mostly preferred amongst the blends for parameters like appearance, odour, taste and mouthfeel. However, the 50% watermelon and 50% apple blend (W6AM) were preferred in terms of overall acceptability. Furthermore, the 100% apple gave highly acidic drink. It was concluded that to obtain high nutritional and sensory quality drink, the 25% watermelon and 75% apple blend (W5AM) should be considered.

Assessment of radioactivity and radiological hazards associated with clay bricks in Jalingo City and its metropolis, North-Eastern Nigeria

2025-02-14T06:52:33+00:00

This study estimates the radiation safety of soils used in making clay bricks, a common building material in Jalingo City and its surrounding areas. The activity concentration of the natural radioactive elements 238U, 232Th, and 40K in the soils was measured using a gamma-ray spectrometer equipped with a 905-3 NaI (TI) crystal detector and a high photomultiplier measuring 7.62 cm by 7.62 cm. The average activity concentrations of 238U, 232Th, and 40K in the soils were 12.5±1.3, 26.7±1.7, and 65.1±5.2 Bqkg^-1 respectively, all of which were lower than the global average concentrations. The research also assessed the Radium equivalent activity, absorbed dose rates, and other radiological hazard parameters relevant to building materials. The mean Radium equivalent activity was 55.69 Bqkg^-1, below the safety limit of 370 Bqkg^-1. Additionally, the mean outdoor absorbed dose rate was 24.64 nGyh^-1, below the safety limit of 59.00 nGyh^-1, and the mean indoor absorbed dose rate was 46.08 nGyh-¹, below the safety limit of 84.00 nGyh^-1. All assessed hazard parameters, including annual effective dose rates (indoor and outdoor), lifetime cancer risk, annual gonadal effective dose, representative level index, and both external and internal hazard indices, were well below the established global safety limits. The activity concentration of the primordial radionuclides and the radiological hazard parameters were also lower compared to other parts of Nigeria and the world. As a result, the study concluded that the soils and the buildings constructed with them are radiologically safe and pose no hazard threats to the occupants.

Bioinformatics-driven analysis and antibiotic resistance profiling of Enterobacter species isolated from acne lesions

2025-02-14T07:01:14+00:00

This study characterised Enterobacter sp. isolated from individuals with acne, focusing on their biochemical, antibiotic resistance, and molecular profiles. Using standard morphological, biochemical, and molecular methods, the isolates exhibited typical Enterobacter traits, including rod-shaped morphology and positive to catalase and oxidase reactions. The isolates were highly resistant to beta-lactam antibiotics, particularly ampicillin (85%) and ceftazidime (76.7%); while susceptibility to ciprofloxacin remained high (87.3%). Molecular identification using 16S rRNA sequencing, confirmed two isolates as Enterobacter hormaechei. Phylogenetic analysis of the isolates using MEGA software indicated a close relationship with clinical strains, suggesting clinical reservoirs of resistant bacteria. RAST subsystem analysis revealed the presence of multiple resistance genes, including those for beta-lactamases (CTX-M, OXA, AmpC) and fluoroquinolone resistance (gyrA, parC). These findings highlight the multidrug-resistant nature of Enterobacter hormaechei, emphasizing their role in the spread of antimicrobial resistance in the clinical settings and underscoring the need for ongoing surveillance and management.

Exploring the anti-inflammatory properties of bromelain in the management of some skin conditions

2025-02-14T07:06:03+00:00

Bromelain is an enzyme obtained from pineapple with reported anti-inflammatory characteristics that could be explored in managing skin disorders such as acne, eczema and rosacea. The study aims to analyse bromelain’s effectiveness in decreasing skin redness, enhancing the skin’s quality and determining the side effects of bromelain when treating skin disorders. This research involved a randomized, double-blind placebo controlled clinical intervention involving 40 participants for 12 weeks. Patients were randomly assigned to experimental group using (1.0mg/cm² of bromelain) and control group using a non-active cream in the affected area twice daily. Redness and inflammation were measured using a standard dermatological grading scale, with scores ranging from 0 (no inflammation) to 10 (severe inflammation). Skin quality of the was assessed using participants diary, scaled questionnaire and dermatologist assessment. Baseline measurements of skin inflammation were taken; repeated measurements were obtained once a week. The overall findings revealed a decrease in redness and skin inflammation in the experimental group compared to control group (p < 0.001) that was consistent as the week progressed. The participants in the experimental group also had a significant enhancement of skin texture (p < 0.01) quality and decrease in acne compared to the control group. The participants in the experimental group had 15% mild irritation, 10% itching and 0% severe irritation. Participant compliance was found to be high during the trial while most of the participant showed enhanced benefit by the end of the trial. The findings support the use of bromelain as a natural supplement in management of inflammatory skin diseases.

Antimicrobial activities, GC-Ms composition and proximate analysis of volatile oil extract from tumeric rhizomes (Curcuma longa)

2025-02-14T07:13:10+00:00

This research investigated the antimicrobial activity, GC-MS, and proximate composition of turmeric rhizomes (Curcuma longa) using standard methods. The results showed turmeric contained crude protein (8.12%), lipid (5.75%), fiber (5.00%), ash (6.50%), moisture (10.20%), and carbohydrate (64.43%). Oil was extracted via the AOAC method using n-hexane. FTIR analysis identified functional groups, including OH, CH3, C=O, and C=C, within a wavenumber range of 4000–650 cm⁻¹. UV-Visible analysis revealed a peak at 415 nm, indicating conjugated systems and aromatic compounds. GC-MS identified 19 compounds, with turmerone and curlone being prominent, known for antibacterial, antioxidant, anti-inflammatory, and anti-cancer properties. Antimicrobial testing showed turmeric oil's significant effectiveness against Staphylococcus aureus, Pseudomonas sp., and Aspergillus sp. at varying concentrations.

Biodecolourization of textile effluent using biosurfactant produced by Pseudomonas aeruginosa and Bacillus subtilis isolated from engine oil contaminated soil

2025-02-14T07:18:34+00:00

Biosurfactants can be characterized according to their chemical composition, molecular weight, physicochemical properties, mode of action and microbial origin. Microbial decolorization and degradation is an environment friendly and cost-competitive alternative to chemical decomposition processes. This study therefore was carried to with the aim to produce and characterized biosurfactants produced by Pseudomonas and Bacillus species for the decolorization of textile effluents. Bacteria from oil polluted soil was isolated by standard spread plate technique using nutrient agar. Extraction of biosurfactant was done using the acid precipitation method and the weight of the biosurfactant was determined. GCMS and FTIR analysis of the biosurfactant were carried out according to standard method, and the extent of decolourization caused by the biosurfactant was estimated and expressed as percentage (%) decolourization. The result indicated that the dry weight of biosurfactant produced by Pseudomonas aeruginosa was estimated to be (1.2±0.03), while Bacillus subtilis was 1.38±0.02. The GC/MS analysis of the biosurfactant produced by Pseudomonas aeruginosa was a rhamnolipid and detected 12 compounds present in the biosurfactant while the biosurfactant produced by Bacillus subtilis was glycolipid and the constituents present in the extract where 17 in numbers. Biosurfactants produced by Bacillus subtilis decolorized textile effluent by 67.7%; on the other hand, biosurfactant produced by Pseudomonas aeruginosa decolorized textile effluent by 13.7%. Bacillus subtilis and Pseudomonas aeruginosa proved to be good biosurfactant producers and hence good in decolorization of textile dyes and effluents.

Screening of mutant fungi isolated from Romi River for potential to degrade refinery effluent

2025-02-14T07:21:42+00:00

Environmental pollution implies any alterations in the surroundings; but it is restricted in use, especially to mean any deterioration in physical, chemical and biological qualities of the environment. This present study was carried out with the aim to screen and mutate fungi consortia isolated from Romi river for potential to degrade refinery effluent. Refinery effluent samples were collected aseptically into sterile bottles from under the storage tank in Kaduna Refining and Petrochemical Company (KRPC) Kaduna State, Nigeria using aseptic technique into sterile bottles. Physicochemical analysis was carried out using standard methods. Mycological analyses of the samples including the mutation of the fungal isolates were carried out using standard techniques. Identification of the mutated fungi isolated was achieved using both conventional and molecular technique. Results of the physicochemical properties of the samples indicated that most of the parameters were within the acceptable limit set by standard organizations, and parameters supported the survival and proliferation of the fungi. It was observed that Aspergillus niger had the highest percentage occurrence across the sampling sites (29.55%), followed by Aspergillus quadrilineatus (27.77%), Aspergillus fumigatus (22.73%), and Aspergillus versicolor (20.45%). In this study, A. versicolor and A. quadrilineatus were sensitive to UV radiation. There was moderate to maximum growth observed after eight days of screening.

Determination of the phytochemical properties of ethanolic and aqueous plant extracts of Euphorbia hirta towards the inhibition of dermatophytes

2025-02-14T07:25:06+00:00

Medicinal plants have evolved as essential preventive and therapeutic aids for various ailments. Approximately 2.5 million species of higher plants remain unexplored for their pharmacological activities. This study was aimed at screening of phytochemical properties of ethanolic and aqueous extracts of leaves, stem, flower, and whole parts of Euphorbia hirta extract. Fresh leaves, stem, flower and the whole plant of Euphorbia hirta were collected from the Centenary Park, opposite 44 Reference Army Hospital, Kaduna North, Kaduna, Nigeria. The entire plant was identified and authenticated by a Botanist from the department of Biological Sciences, NDA. The collected plant parts were processed in the laboratory using standard procedure. Qualitative and quantitative analyses of the phytochemical properties of the leaves stem, and flower of Euphorbia hirta was carried out using standard method. Results obtained from this study indicated that aqueous extracts yielded mean values of 7.93 mg/g for flowers, 8.18 mg/g for leaves, 8.65 mg/g for stems, and 6.3 mg/g for the whole plant. For the ethanolic extracts, the highest value was observed in the stem with 5.8 mg/g, followed by the whole plant with 6.43 mg/g, the leaves with 5.35 mg/g, and the flowers with the lowest value at 0.84 mg/g. Phytochemical properties of E. hirta could be employ in the pharmacological studies as these compounds have been known to possess antimicrobial properties..

Physicochemical and sensory properties of locally produced digestive biscuit from two varieties of wheat (Triticum spp)

2025-02-14T07:27:19+00:00

Digestive biscuits were produced from two varieties of wheat grain (Reyna-28 and Norman). The grains were processed into whole wheat flour at 100% (g) each with commercial digestive biscuit (Mcvities digestive biscuit) used as control and analyzed for physical properties, functional properties, mineral composition and sensory evaluation using standard methods. Other ingredients such as; margarine, egg, milk, baking powder, and sugar were added. Data obtained were analyzed using Analysis of variance (ANOVA) using Statistical Package for the Social Sciences. Results showed that the digestive biscuits gave good physical properties in terms of weight, height, diameter, thickness and spread ratio. Functional properties ranged from 0.59-0.72g/m3 for bulk density, Sample B2 exhibited the highest bulk density (0.72), 30.32-34.31g/g for water absorption capacity, with B2 having the highest value (34.31), 4.95-10.12% solubility index. The sodium, potassium, iron and zinc content ranged from 60.23±4.93-71.21±6.18, 91.55±6.00-96.00±5.16, 2.46±0.05-6.74±0.02, 1.43±0.03-2.34±0.05mg/100g respectively. Digestive biscuit from sample B2 had the highest mineral composition. The digestive biscuits produced gave good physical properties in terms of weight, height, diameter, thickness and spread ratio. Sensory properties revealed that there were no significant differences in color, odor, texture, taste between digestive biscuits produced from processed 100% Reyna-28 wheat flour (B2) and the commercial control. In conclusion, digestive biscuits from sample B2 was most preferred than digestive biscuits produced from sample B1, B3 and B4 and was comparable to the commercial control.

Toxicity and modulating effect of Olax subscorpiodea oliv. aqueous root extract on clonidine-induced sexual dysfunction in male Wistar rats

2025-02-14T07:30:17+00:00

This study examined the effects of aqueous root extract of O. subscorpioidea Oliv. (AREOS) on liver function, male sexual hormones and nitric oxide in normal and clonidine-treated Wistar rats. Thirty rats were divided into six groups to assess sexual function parameters, including a control group, a clonidine hydrochloride-only group, and groups receiving clonidine plus Adam’s desire or varying doses of AREOS (250, 500, 1000 mg/kg body weight). After seven days of treatment, blood and testicular samples were analyzed for testosterone (TT), serum testosterone (ST), luteinizing hormone (LH), follicle-stimulating hormone (FSH), dihydrotestosterone (DHT), and nitric oxide (NO). Toxicity study was also conducted on 20 male rats treated with different doses of AREOS to analyze liver enzymes and serum proteins. Phytochemical analysis revealed bioactive compounds like saponins, flavonoids, and amino acids. Clonidine treatment increased TT, ST, and DHT but decreased LH and FSH. AREOS reduced TT, ST, DHT, and NO levels but increased LH, compared to the clonidine only-treated group. AREOS had no significant effects on liver function markers but significantly lowered serum alanine aminotransferase (ALT) activity. Overall, AREOS was not hepatotoxic and showed potential to normalize hormone imbalances, supporting its traditional use in treating male sexual dysfunctions.

Effect of co-administration of metformin and aqueous leaf extract of Bryophyllum pinnatum on kidney function indices in diabetic rats

2025-02-14T07:33:25+00:00

The aim of this study was to evaluate the effect of co-administration of metformin and Bryophyllum pinnatum (BP) on kidney function parameters in diabetic rats. Forty male Wistar rats were randomly divided into 5 groups with 8 rats each namely; A (Control), B (Diabetic untreated), C (120 mg/kg b. wt Metformin only), D (400 mg/kg b. wt. BP only), and E (400 mg/kg b. wt. BP and 120 mg/kg b. wt. Metformin). Results showed urea, BUN and serum ALP significantly increased (p < 0.05) while Na⁺, K+, Ca²⁺, PO₄^3-, Cl- and kidney ALP decreased significantly (p < 0.05) in group B but were not altered in groups C, D and E when compared with A. However, Ca²⁺ level was significantly reduced (p < 0.05) in group E compared with groups A, C and D. Kidney sections for groups A, B, C, D and E showed renal tissue with preserved architecture. There are no vascular lesions seen and no features of acute or chronic damage. In conclusion, co-administration of metformin and B. pinnatum in diabetic rats reversed diabetes-induced alterations in selected kidney function parameters in experimental rats.

An improved diabetes mellitus prediction model through ensemble learning and Gini Index-based feature selection

2025-02-14T07:40:01+00:00

Diabetes Mellitus (DM) is a condition where the body cannot regulate blood sugar due to improper insulin production or use, posing a significant global health burden. Traditional detection methods rely on clinical assessments and basic lab tests, but recent technological advancements suggest that Machine Learning (ML) algorithms can predict DM more effectively and efficiently. However, current ML models face challenges like feature redundancy, irrelevancy, and dataset imbalance, which can reduce accuracy and interpretability, ultimately affecting patient outcomes. This paper aims to address these challenges by developing an enhanced ML-based DM prediction model. The proposed model leverages an ensemble soft voting classifier, integrating the Random Forest, Logistic Regression, and Naïve Bayes algorithms. Feature importance determination is facilitated by the Gini Index Random Forest (GI-RF) algorithm. Additionally, three data imbalance handling techniques random oversampling (ROS), random undersampling (RUS), and the synthetic minority oversampling technique (SMOTE) are employed to mitigate biased model development. Initially, the GI-RF algorithm identifies the top 5 most informative features from the PIMA Indians Diabetes Dataset, originally comprising 8 features. Subsequently, the dataset is subjected to each of the three imbalance handling techniques. The performance of each model variation, incorporating different imbalance handling techniques is then extensively compared. The results demonstrate that ROS notably outperforms RUS and SMOTE across multiple metrics, including accuracy, F1 score, recall, and AUC. A comparative analysis with existing studies reveals the proposed method's notable improvements across all metrics, with increases of 5% in accuracy, 8% in precision, 13% in F1 score, 18% in recall, and 4% in AUC. This demonstrates the proposed model's overall robustness and effectiveness in predictive modeling, contributing to more accurate diagnosis and treatment of DM.

Investigation of panel modelling techniques in the presence of collinearity regressors

2025-02-14T07:43:14+00:00

In order to estimate the presence of collinearity, this study used the fixed effect model, pooled effect model, and random effect model in the presence of collinearity regressors. In respond one, data were simulated under several types of collinearity verifiable at varying sample sizes (-0.1, -0.5, -0.9, 0.1, 0.5, and 0.9) in the Monte Carlo simulation. For the models estimators, two regressor estimators were used. Simulations were run at various panel structures and collinearity regressors in the Monte Carlo study. The trial was conducted ten thousand times (10000), and the accuracy of the model estimation was assessed using the Root Mean Square Error (RMSE). The results of the study showed that the estimation of the small sample panel structure model. While following time series lengths (5, 10, 10, 30, 60, and 60) have 10,000 repetitions of the experiment conducted in the R environment. The Root Mean Square Error (RMSE) was used to assess the models. The RMSE values for the fixed and random model are fluctuated as the collinearity levels grew in all of the scenarios that were taken into consideration. Based on the analysis, the Fixed Effects (FE) Model is the best-performing model, particularly in larger datasets, as it minimizes both bias and RMSE. The Random Effects (RE) Model can also be effective, especially when collinearity is moderate and when the assumptions of random effects hold true. However, for datasets where collinearity is high, or where individual-specific effects are crucial, the Fixed Effects Model provides more reliable estimate. The Pooled Regression Model should generally be avoided in cases where collinearity or panel-specific heterogeneity is significant, as it produces the least stable and least reliable results across different collinearity levels