FUDMA JOURNAL OF SCIENCES

ASSESSMENT OF CARBON SEQUESTRATION POTENTIAL OF TREES IN ADEOYO GENERAL HOSPITAL PREMISES, IBADAN, OYO STATE

2025-01-04T05:25:58+00:00

This study assessed the carbon sequestration of trees around healthcare facilities at Adeoyo General Hospital, Adeoyo, Ibadan. Total enumeration of all the trees in the study areas was carried out. Data were collected on dbh (cm) and total height (m) and these parameters were used to compute basal area (m²), volume (m³) and Carbon sequestered (ton). The parameters measured from the study area tree include: diameter at breast height (DBH), total height (H), basal area (B.A), Total volume (V). Trees species of 10cm Dbh and above were measured and enumerated. The carbon sequestration of 64 trees belonging to 13 species, 8 families was estimated using allometric equations. The results showed the growth characteristics of various tree species. Azadirachta indica dominated constituting 42.2% of the total population. Terminalia catappa and Gliricidia sepium are also significant. Mean diameter, height, basal area, and volume suggest a diverse forest with a wide range of tree sizes. The total carbon sequestered by these trees was 194425.2tCwith the average carbon sequestered of the trees as 3037.8947tC. The highest average of 8880.9tC sequestration was observed in Delonix regia and the lowest (44.1tC) in Ficus capensis. Delonix regia showed the highest DBH and more carbon sequestration potential, whereas Newbouldia laevis showed the minimum in both DBH and carbon sequestration potential.

A TWO-STEP AUTHENTICATION FACIAL RECOGNITION SYSTEM FOR AUTOMATED ATTENDANCE TRACKING

2025-01-04T05:25:58+00:00

This study addresses the need for efficient, automated attendance systems through the design of a facial recognition application. Manual attendance systems are slow, error-prone and the retrieval of old records can be tedious. Universally assessable technological developments such as facial recognition software can easily solve these problems. However, the vast amount of computational resources required for its implementation has posed a limitation to its wide adoption. This study presents a two-step approach to resolve these challenges. By leveraging a faster, less-powerful model, as the first step, the workload of facial recognition can be distributed to save time and computational cost. A more powerful machine learning model is applied as the second step, deployed for tasks that are too complex for the first model to handle. The two-step authentication process will also reduce the occurrences of false negatives. Face_recognition, a python library is used for detection and encoding of face images read using python’s opencv library from an IP webcam. A flask application demonstrates this facial recognition functionality. The database connection and communication are accomplished using flask_sqlalchemy. A graphical user interface (web application) is used to interact with users on a high level, showing saved images of logged personnel and their times of entry. The system has a maximum accuracy of 98.78% and precision of 98.82% from tests. This shows its potential for application on a wider scale, with some added improvements such as cloud deployment and larger datasets.

ANTICONVULSANT ACTIVITY OF METHANOL LEAF FRACTIONS OF LAGGERA AURITA LINN (ASTERACEAE) IN LABORATORY ANIMALS

2025-01-04T05:25:57+00:00

The Plant Laggera aurita Linn, a widely used medicinal plant in Africa, in the treatment of many medical conditions. This study was conducted to evaluate the anticonvulsant effects of solvents fractions of methanol leaf extract of Laggera aurita in laboratory animals. Phytochemical screening and acute toxicity studies was carried out using standard protocols. The fractions were evaluated against electrically-induced seizures in chicks, pentylenetetrazole induced seizures in mice and pentylenetetrazole kindling in rats. The analysis of the solvents fractions of Laggera aurita revealed alkaloids, flavonoids, tannins, steroids, terpenoids and cardiac glycosides. The i.p median lethal dose values in mice for NHF were found to be 1264mg/kg, 2154mg/kg for EAF and 3807mg/kg for RAF. The maximal electroshock induced seizure model of solvents fractions did not protect the animals against tonic hind limb extension (THLE), however it increases the mean recovery time of the convulsed chicks at all doses tested. In the subcutaneous pentylenetetrazole-induced seizure model, the NHF protected the mice against seizure at all doses tested, up to 50% at 200mg/kg and 400mg/kg, while the EAF and RAF confers no protection against seizures at all doses tested (150mg/kg, 300mg/kg, 600mg/kg for EAF and 250mg/kg, 500mg/kg and 1000mg/kg for RAF). The NHF produced significant protection against subcutaneous pentylenetetrazole (40mg/kg) induced kindling in rats at all the doses tested, while the EAF and RAF shows no protection. The study therefore suggests the presence of bioactive compounds in the plant that posses’ anticonvulsant activity and may be of pharmacological benefit in the management of epilepsy.

EFFECTS OF VARYING LEVELS OF UREA SUPPLEMENTATIONS ON HAEMATO-BIOCHEMICAL INDICES OF YANKASA RAMS FED ENSILED CRUSHED GROUNDNUT SHELL, AFRICAN LOCUST BEAN PULP AND POULTRY LITTER

2025-01-04T05:25:58+00:00

A study was carried out to assess the effects of varying levels of urea supplementations on haemato-biochemical indices of growing Yankasa rams fed ensiled crushed groundnut shell, African locust bean pulp and poultry litter. The study was carried out at Abubakar Tafawa Balewa University Teaching and Research Farm, Bauchi. Twenty (20) growing Yankasa rams were fed five supplemental diets plus a basal diet. A complete randomized design (CRD) was use to allocate the treatment with each treatment replicated four times. Groundnut shell (GNS) and African locust bean pulp (ALBP) were ensiled with poultry litter as basal diet, Maize bran (MB), cotton seed cake (CSC), groundnut cake (GNC), groundnut haulms (GNH) and urea were used as supplements at various proportions. The basal diet and water were offered ad libitum, three hundred grams (300g) of the supplements were offered before the basal diet to each animal first thing in the morning. Blood samples were collected from ten rams (two animals per treatment), the animals were properly restrained and 5mls of blood was collected through the Jugular veins using syringe and needles, to analyse for various parameters. The results showed that Haematological parameters affected were packed cell volume (PCV) and red blood cell (RBC) at (P<0.05) level of significance, while alanine aminotransferase (ALT) and creatinine were also affected (P<0.05) by dietary treatments. It was concluded that ensiled crushed groundnut shell, African locust bean pulp and poultry litter fed to Yankasa rams with various supplementations has significant effects on PCV, and RBC however, they...

PROBATION OF THE SOIL FROM CALEB UNIVERSITY, IMOTA LAGOS, NIGERIA AS A SOURCE OF ANTIBIOTIC-PRODUCING BACTERIA

2025-01-08T13:46:16+00:00

The importance of antibiotics in treating bacterial diseases cannot be overstated. However, the excessive use of antibiotics has led to the development of resistance in many bacteria, making the treatment of bacterial infections challenging. Therefore, it is essential to search for new strains of bacteria in different habitats that produce novel antibiotics. The aim of this study was to investigate the soil from Caleb University for antibiotic-producing bacteria. Soil samples were collected from seven locations within Caleb University, including Joshua Hall (J), Cafeteria (C), Dump site (DS), Lab garden (LAB G), Last Garden (LG), and School Inner Garden (SID). The samples were diluted, and standard procedures were followed for all experiments. The results of this study indicate that the isolated species did not show significant inhibitory activity against the test bacteria and were unable to produce antimicrobial compound. Therefore, it can be concluded that the species found in the soil samples from Caleb University are not effective in stopping bacterial growth.

INFLUENCE OF TEMPERATURE DEPENDENT VISCOSITY, VISCOUS DISSIPATION AND JOULE HEATING ON MHD NATURAL CONVECTION FLOW: A SEMI ANALYTICAL APPROACH

2025-01-05T05:25:57+00:00

This paper investigates influences of temperature dependent viscosity, viscous dissipation and Joule heating on method MHD natural convection flow through a vertical porous channel. The equations representing the flow formation are of highest complexity as such their solutions are difficult to obtain through any analytical means. To achieve the solution, the use of Adomian decomposition of solution (ADM) is therefore deployed. The method of ADM is a semi-analytic method which is a powerful tool capable of decoupling the complexity into series form upon which a computer algebra package can be used for the final solution. This investigation may have application in the context of refining of crude oil as its components are separated under changing temperatures.

ADVANCED ENCRYPTION STANDARD (AES) IMPLEMENTATION EFFICIENCY USING JAVA AND NODE.JS PLATFORMS

2025-01-08T05:27:34+00:00

The rapid advancement of communication technologies, such as satellite networks, mobile, internet, and terrestrial communications, has created an urgent need to protect sensitive data from potential attacks. This is particularly crucial as photos transmitted through unreliable channels may contain sensitive or confidential information. This study evaluates the effectiveness of the Advanced Encryption Standard (AES) algorithm implemented in Java and Node.js, focusing on their performance in data encryption and decryption. The research employs AES in Cipher Block Chaining (CBC) mode, using 128-bit keys for Java and 256-bit keys for Node.js. It utilizes the Java Cryptography Architecture (JCA) and Java Cryptography Extension (JCE) to create an optimized runtime environment with advanced cryptographic libraries. The result indicate that Java's AES-128 implementation is more efficient than Node.js's AES-256, particularly in terms of speed and data processing capabilities as seen in figure 11 taking Java 2.00ns to encrypt and decrypt before the Node.js algorithm that couldn’t complete the process but remain at 0.75ns. Suggesting that specific use case and requirements should be considered when choosing between the two platforms for AES encryption. Java generally outperforms Node.js in efficiency, but Node.js provides essential cryptographic functions through its built-in 'crypto' module. Overall, the research underscores the advantages of using the AES algorithm across these platforms while demonstrating the varying performance characteristics between them.

RUMEN pH AND MICROBIAL POPULATION OF YANKASA RAMS FED ENSILED SUGARCANE WASTE FORTIFIED WITH POULTRY LITTER

2025-01-08T05:27:37+00:00

Rumen contents may be observed for physical aspects (color, odor, consistency, sedimentation) and the chemical characteristics (pH, glucose, fermentation, nitrate reduction and methylene blue reduction test) and biological parameters (bacteria, protozoa and fungi) (Donato et al., 1999). The study was conducted to evaluate the effects of feeding ensiled sugarcane waste (ESCW) fortified with poultry litter (PL) to Yankasa rams on rumen fluid characteristics using 16 rams (mean initial BW 28.94 ± 5.77 kg; aged 12 to 18 months). Sugarcane waste was mixed with poultry litter in 3:1 and ensiled for 21 days, then use compound a complete diet. The rams were allocated to four groups on the basis of body weights into control group without ESCW (CG) as treatment groups (T₁), 15% (T₂), 30% (T₃) and 45% (T₄) in a Completely Randomized Design (CRD) and fed ad libtum for 84 days. At the end of the experiment, ten (10) ml of rumen fluid was drawn from individual experimental animal before feeding at 0 hr and 3 hrs and 6 hrs after meal. Parameters observed were pH, rumen bacteria and fungi biomass. The results showed that rumen bacteria and fungi counts were significantly (P<0.05) affected by sampling time. Significant (P<0.05) differences were observed in the counts between different sampling times. In conclusion, the ESCW had positive effects on the rumen fluid of the rams by improving rumen pH and microbial activity (bacteria and fungi). It is recommended that rumen fluid could be sampled at 3 hours after feeding for higher bacteria...

SYNTHESIS, CHARACTERIZATION AND APPLICATIONS OF MODIFIED NANOCLAY SUSPENSION FROM KAKURI VILLAGE

2025-01-24T15:00:20+00:00

In this study, the preparation of modified nanoclay using different amino acids has been investigated. The modified and unmodified nanoclay sample has been characterized using X- Ray Diffraction (XRD), Brunauer-Emmett Teller (BET), Particle Size and Scanning Electron Microscopy (SEM). The XRD results suggest that the interlayer spacing of modified nanoclay increases with the intercalation of the modifiers. BET showed that nanoclay was successfully synthesized as revealed by the pore width and volume in the range of 2.647-45.23nm and 11.08-862.6cm³/g, with a BET surface area of 262.1m²/g for the control (CTL). Whereas, Arginine, Tyrosine and Aspartic acid modified nanoclay had 1.847-6.503nm, 2.647-45.23nm and 2.647-45.23nm each with a BET SA of 533.9, 325.4 and 356.3m²/g respectively. Study revealed that the clay deposits were composed of a mixture of clay minerals (Quartz, Anorthite, Kaolinite, Montmorillonite, Orthoclase and Muscovite). Particle size shows that unmodified nanoclay had particle diameter in the range of 0.88-68.71nm, Whereas, modified nanoclay sample had particle size value of 0.88-60.52nm for TYS, ASP and ARG respective. SEM images revealed the presence of varying pore sizes distribution across the surface area of both the modified and unmodified nanoclay samples.

EVALUATION OF THE GROUNDWATER QUALITY IN GISHIRI VILLAGE – KATAMPE, ABUJA USING WATER QUALITY INDEX

2025-01-14T20:50:09+00:00

Water quality is inherently linked with human health, poverty reduction, food security, livelihoods, preservation of ecosystems, economic growth, and social development of societies. This study evaluated the groundwater quality of Gishiri-Katampe, Abuja-Nigeria using statistical and geospatial techniques for water quality indexing. The study also used hydro-chemical parameters, geographical information, and statistical analysis to assess groundwater pollution potential; identify the most vulnerable areas, and generate a groundwater quality map. The Canadian Water Quality Index, the GIS mapping of the water quality of Gishiri indicates that the Water Quality Index is within the range of 76.87 to 92.53. Similarly, the WQI is predominantly good (62%), indicating a minor degree of threat. However, 38% of the area is occasionally threatened (fair) on the Canadian scale. However, some areas are occasionally threatened (fair) with the corresponding WQI of 28% within the study area. Moreover, out of the 11 water quality parameters analyzed, 6 parameters (dissolved oxygen DO, turbidity, chemical oxygen demand COD, NO₃, Na, and biological oxygen demand BOD) were identified as significant parameters as indicated by the correlation and regression analysis. This suggested that they strongly influenced the variability of the water quality.

STACKING ENSEMBLE-BASED PREDICTIVE SYSTEM FOR CROP RECOMMENDATION

2025-01-08T05:27:36+00:00

Agricultural sustainability relies on crop production, but the task of choosing appropriate crops for certain places is difficult owing to the ever-changing environmental circumstances. Traditional approaches are often limited in scope, failing to adapt to diverse soil types and environmental parameters. This study introduces a novel prediction method that utilizes a machine-learning model with ensemble approaches to provide recommendations for crops. The system was developed using a Design Science Research (DSR) methodology. The proposed model incorporates a wide array of machine-learning techniques, including K-Nearest Neighbors, Decision Trees, Support Vector Machines, Naive Bayes, Logistic Regression, and Extreme Gradient Boosting. The integration utilizes the Random Forest meta-model. The model was trained and validated using a large dataset gathered from Kaggle, which consisted of a wide variety of crops and environmental characteristics. The model's performance was evaluated using metrics such as Accuracy, Recall, F1-Score, and Precision. It exhibited outstanding accuracy of 99.8%, along with superior recall, precision, and F1 scores, outperforming previous research by a significant margin. Furthermore, data flow diagrams illustrate the data processing flow within the system. The implementation was carried out using the Python programming language, with MongoDB employed for database development. The resulting proof-of-concept system demonstrates the practical applicability of the model by providing reliable crop recommendations based on environmental data. This research marks a substantial advancement in optimizing crop management strategies through advanced predictive modeling, offering a robust tool to aid farmers in making informed decisions, ultimately enhancing agricultural productivity and sustainability.

MAXIMIZING PROFIT POTENTIAL IN SUPPLY CHAIN FROM SUPPLIER-RETAILER INVENTORY REPLENISHMENT IN RURAL AREAS

2025-01-16T19:34:05+00:00

Successful collaborative relationship enhances profitability in the delivery of products or services to customers in a supply. This study focuses on the impact of successful relationships in supply chain management on customer exploration and profitability. By implementing a strong strategy, more customers can be brought into the supply chain, leading to increased productivity and ultimately, higher profitability. The main objective is to determine the optimal quantity levels in supplier relationships that minimize long-term costs in the supply chain. A mathematical model incorporating shipment consolidation was utilized to derive the profit function. Numerical examples were then employed to illustrate the developed models. The results demonstrate variations in total quantity and relevant costs based on factors such as retailer input, supplier replenishment quantities, optimal order quantities, and total relevant costs within the supply chain, ultimately contributing to enhanced profitability. Our result shows that. there is an increase in the supply chain profitability when the retailer orders greater number of items from the supplier.

PROFITABILITY AND CONSTRAINTS OF AGRICULTURAL COMMERCIALIZATION AMONG SMALLHOLDER RICE FARMERS IN NASARAWA STATE, NIGERIA

2025-01-16T05:29:02+00:00

This study analysed the profitability of smallholder rice farmers in Nasarawa State, Nigeria. Multistage sampling technique was used to select 300 rice farmers for the study. The primary data utilized for the study were collected using structured questionnaires. The data were analysed using descriptive statistics and farm budgetary techniques. The result of the study revealed that rice production in the study area is profitable with gross margin of N103, 876.17/ha. The most important problems identified were inadequate supportive institutions, poor access to credit, and poor rural infrastructure. Based on the findings of the study, it was recommended that provision of adequate and improved agricultural supportive institutions such as research, financial and marketing as well as extension services should be strengthened in order to improve smallholder rice profitability in the study area.

HYDROGEOCHEMICAL INVESTIGATION OF SURFACE AND GROUNDWATER QUALITY OF PAGO, NORTH CENTRAL NIGERIA

2025-01-16T05:28:59+00:00

This study investigated the hydrogeochemical characteristics of surface and groundwater in Pago, North Central Nigeria, a region characterized by Precambian Basement Complex rocks. Water samples collected from wells and streams were analysed using Atomic Absorption Spectrometer (AAS) to analyse for major ions and heavy metals in the water samples. The water quality of the study region was evaluated using hydrogeochemical indices. The hydrogechemical analysis shows that most of the analysed parameters fell within WHO permissible limits, elevated COD levels in some samples indicate potential organic pollution, which may pose risks to human health and aquatic ecosystems. The CF shows low concentrations (<1) of SO, Cl, Ca, Mg, Pb and Zn, and high concentrations (>1) of COD. The values of PLI were generally low, indicating minimal pollution. The WQI showed samples with excellent (<50) ratings. These results underscore the new regular water quality monitoring and targeted remediation strategies to ensure the safety of surface and groundwater in the region. The assessment indicates that the water in the study area is generally safe for drinking and other domestic purposes.

IMPROVING BIOENERGY PRODUCTION FROM ANAEROBIC CO-DIGESTION OF PAPER WASTE AND CHICKEN MANURE USING COCONUT SHELL BIOCHAR

2025-01-16T05:29:00+00:00

CONTRIBUTION OF NON-TIMBER FOREST PRODUCTS (NTFPs) TO HOUSEHOLDS’ DIETARY REQUIREMENT IN KAJOLA LOCAL GOVERNMENT AREA OF OYO STATE, NIGERIA

2025-01-16T05:29:01+00:00

Non-Timber Forest Products (NTFPs) contributes to dietary requirement of the households during economic shocks through food and income provisions. This study investigates the contribution of NTFPs to the dietary requirement of households in Kajola Local Government Area of Oyo State, Nigeria. Data from 120 sampled respondents were generated via a simple random sampling technique and interview schedule using a well-structured questionnaire. Descriptive statistics and inferential analytical tool (multiple regression) were used for the analysis. From the results, (60.0%) of the respondents were female. Majority (64.2%) respondents were within their youthful age group of 18-40 years. Also, majority (61.7%) of them were married. Good number (41.6%) of respondents attained secondary education qualification. Majority (38.3%)of the sampled respondents had not more than 5 household size. Equally, (77.5%) of t respondents earned between N20,000- N60,000 monthly from NTFPs sales. Wild fruits (29.2%) and Honey (28.3%) and firewood/charcoal (20.0%) are the most available and exploited NTFPs for dietary requirement by the respondents. Likewise, majority (51.7%) of the respondents sold only NTFPs to contribute to their household’s dietary requirement. explicitly, (89.3%) of the NTFPs harvested were sold by the respondents’ households while only (10.7%) of the NTFPs harvested were consumed. Meanwhile, variable such as respondents age, respondents’ gender, family status, academic level, core occupation and households’ size were all significant at 5% probability level and positively impacted NTFPs contribution to households’ dietary requirement. Hence, the need for strategies and investment in NTFPs value addition for all year round dietary availability to households, and a means...

ISOLATION AND IDENTIFICATION OF PLANT PARASITIC NEMATODES AFFECTING TOMATO (SOLANUM LYCOPERSICUM, LINN.) IN GIWA LOCAL GOVERNMENT AREA, KADUNA, NIGERIA

2025-01-16T05:29:02+00:00

Plant-parasitic nematodes are the major biotic stressor in crop cultivation. They are recognized as one of the greatest threats to crops worldwide. The study evaluated nematodes that affect tomato in Giwa Local Government area, Kaduna State, Nigeria. Samples were collected from two selected farms each from seven locations. The tomato samples were classified as diseased and healthy based on the appearance of the plants. In each farm, four samples were taken during the growing season; two from diseased plants and two from apparently healthy looking plants. Similarly, soil samples from diseased and apparently healthy soil were collected. The soil and tomato samples were extracted using Cobb-Sieving and Decanting method. Descriptive statistics, students t-test and species diversity were used to analyze the data. Nineteen (19) genera of plant parasitic nematodes were isolated and identified, with 18 genera each in diseased soil and root samples, 12 and 9 genera from apparently healthy soil and roots respectively. Scutellonema spp. (1121) had the highest number of nematodes genera while Tetylenchus (20) had the lowest, in diseased soil samples. In diseased root samples, Meloidogyne (415) had the highest nematodes while Tetylenchus (10) had the lowest number of nematodes. In apparently healthy soil samples, Scutellonema (522) had the highest number of collection, while Tylenchorynchus (20) had the least. In apparently healthy root samples, Pratylenchus (415) had the highest and Hoplolaimus (10) had the lowest number of collection across all the locations. There was no significant difference (p > 0.05) in the presence of nematodes in the...

EFFICACY AND RESISTANCE PATTERN OF SOME COMMONLY USED INSECTICIDES AGAINST ANOPHELES MOSQUITOES IN SIX LOCAL GOVERNMENT AREAS OF ADAMAWA STATE, NORTHEASTERN NIGERIA

2025-01-24T14:36:39+00:00

The global effort to control malaria vectors has been halted due to resistance mechanisms developed against various insecticides and their associated effects. This study evaluates the efficacy and resistance pattern of some commonly used insecticides against Anopheles mosquitoes using various insecticide concentrates. A ladle was used to collect Anopheles mosquito larvae in the study areas. The collected larvae were transferred to a plastic container and transported to the Institute of Infectious Diseases of Poverty (IIDP) laboratory in Modibbo Adama University, Yola, where the samples were reared to adulthood. Four separate batches of twenty-five (25) female Anopheles mosquitoes were subjected to the test papers of each impregnated insecticide for 1 hour at 27± 1°C and 80± 2% relative humidity. Similar batches were subjected to the non-impregnated insecticide paper as a control. After one hour of subjection, they were conveyed into a holding tube furnished with cotton drenched with a 10% sugar solution. Following 24 hours, mortality and susceptibility were observed and recorded. The findings showed that propoxur, bendiocarb, and pirimiphos-methyl showed 100% susceptibility across all Local Government Areas studied. In contrast, permethrin, deltamethrin, and DDT showed resistance across the Local Government Areas suggesting varying significant resistance levels. These findings outrageously emphasize the significance of ongoing surveillance, resistance management, and context-specific development for vector control strategies to combat malaria effectively in Adamawa state.

PREVALENCE OF GASTROINTESTINAL HELMINTH PARASITE OF PARACHANNA OBSCURA AND HETEROTIS NILOTICUS AT RIVER ANAMBRA, ANAMBRA STATE

2025-01-17T05:29:03+00:00

Parasitic infections are one of the factors limiting fish in the wild for sustainable productivity. The study was carried out to determine the gastrointestinal helminth parasite associated with Parachanna obscura and Heterotis niloticus and their prevalence concerning sex and size (length and weight). Sixty (60) fishes (30 H. niloticus and 30 P. obscura) were bought from fishmongers from the Anambra River. They were examined through dissection and observation of the alimentary canal under the microscope's objective lens. The overall prevalence of the parasites in Heterotis niloticus was 83.33%. The parasites recovered were Tenuisentis niloticus 16 (53.33%), Sandonella sandoni 8 (26.67%) and Capillaria species 1 (3.33%). There was no significant difference in the prevalence of gastrointestinal helminth among the sexes (p> 0.05). However, the parasite species had a significant difference in prevalence (p< 0.05). In P. obscura, the overall prevalence of the parasite was 73.33% and only one parasite species, Procamallanus species was recovered. There was no significant difference in the prevalence of gastrointestinal helminth among sexes (p= 0.096, p>0.05) and fish size. Further studies are required to consider the probable zoonotic transmission of parasitic diseases from fish. It concluded that the prevalence of gastrointestinal helminth parasites of these species is high and this may affect the fish quality.

GC-MS ANALYSIS, QUALITATIVE AND QUANTITATIVE PHYTOCHEMICAL COMPOSITION OF Boerhavia diffusa (Linn.) LEAF EXTRACT CHARACTERIZING ITS MEDICINAL USE

2025-01-17T05:29:00+00:00

Boerhavia diffusa Linn., commonly known as punarnava, is a perennial herb of the Nyctaginaceae family, renowned for its medicinal significance in traditional medicine, particularly in India. The leaves of Boerhavia diffusa were extracted using a Soxhlet extractor, and the resulting ethanolic extract was subjected to qualitative and quantitative phytochemical analysis. Qualitative screening revealed the presence of phenols, tannins, alkaloids, saponins, flavonoids, terpenoids, steroids, and cardiac glycosides. Quantitative analysis demonstrated significant concentrations of phenols (344.97 mg/100g), flavonoids (67.72 mg/100g), and tannins (84.33 mg/100g). Advance GC-MS profiling identified 16 bioactive compounds, including benzofuran, stigmasterol, pentadecanoic acid, and phytol, which exhibit diverse pharmacological activities such as antioxidant, anti-inflammatory, and antimicrobial effects. The study highlights the potential of Boerhavia diffusa as a source of novel therapeutic agents, bridging traditional knowledge with modern scientific techniques. Further research is recommended to explore the synergistic effects, pharmacokinetics, and bioavailability of its phytochemicals to validate its clinical applications. This investigation substantiates the medicinal value of Boerhavia diffusa and advocates for its integration into contemporary medicine, offering a promising avenue for the advancement of herbal medicine.

ASSESSMENT OF HEAVY METAL CONCENTRATIONS AND PHYSICOCHEMICAL PARAMETERS IN SOILS OF SELECTED REFUSE DUMPSITES IN FIVE GEOGRAPHICAL ZONES OF LAFIA METROPOLIS, NIGERIA

2025-01-17T05:29:03+00:00

The disposal of solid wastes has become a very serious problem particularly in most Nigerian cities due to rapid population explosion and commercial activities. Lafia metropolis, the capital city of Nasarawa State, Nigeria is experiencing rapid urbanization as a result of population growth, and unplanned development accompanied by indiscriminate waste disposal. In this study, concentrations of heavy metals and physicochemical parameters from 20 soil samples each from selected refuse dumpsites in wet and dry seasons were determined using Atomic Absorption Spectrophotometer and Association of Official Analytical Chemists (AOAC) standard methods. The results showed that during the wet season the concentration of heavy metals; Hg (0.100 mg/kg – 0.367 mg/kg), Cr (0.117 mg/kg – 0.926 mg/kg), and Mn (0.480 mg/kg – 1.385 mg/kg) were above the maximum permissible limits (0.04 mg/kg), (0.2 mg/kg), (0.1 mg/kg) of World Health Organisation (WHO), and (0.0005 mg/kg for Hg) of National Environmental Standards Regulations Enforcement Agency (NESREA), while that of Pb, As, Fe, Zn, Cu and Ni were below the tolerable limits. In the dry season, the levels of concentrations of Hg (0.123 mg/kg - 0.345 mg/kg), Cr (0.067 mg/kg – 2.833 mg/kg), and Mn (0.702 mg/kg – 3.091 mg/kg) across the locations were also found to be above the tolerable limits. Except for nitrates in wet season (131.36 mg/L – 1,312.15 mg/L), phosphates (0.12 mg/L – 7.86 mg/L) and organic matter (2.19% w/w – 3.24 % w/w), dry season for nitrates (176.84 mg/L – 1,755.21 mg/L), phosphates (0.26 mg/L – 14.39 mg/L), organic matter...

CREDIT RISK ANALYSIS: AN ASSESSMENT OF THE PERFORMANCE OF SIX MACHINE LEARNING TECHNIQUES IN CREDIT SCORING MODELLING

2025-01-17T05:29:01+00:00

This study checked the credit risk analysis domain, concentrating on assessing the efficacy of six distinct credit scoring methodologies: linear discriminant analysis, logistic regression, artificial neural networks, support vector machine, decision tree and, K-nearest neighbour on microcredit applicant’s data. Two performance metrics were used: Area under the receiver operative characteristic curve and, Precision. The results obtained from the experimentation phase reveal distinct performance levels for each technique. Specifically, K-nearest neighbour and artificial neural networks showcase exceptional prowess, yielding an AUC of 0.9833 and 0.9062 and, an impressive precision score of 0.8065 and 1 respectively. In contrast, logistic regression and support vector machine demonstrate a good performance with an area under the curve value of 0.8537 and 0.8532 respectively, on precision metric score, support vector machine showed impressive high performance while logistic regression performed poorly. Linear discriminant analysis and Decision tree exhibit comparatively moderate accuracy scores and achieved an AUC of 0.8494318 and 0.7524 respectively. Thus, we underscore the potential of K-nearest neighbour and Artificial neural networks as a superior method for credit risk analysis, supported by robust performance metrics. Although, all techniques achieve significantly good discriminative power and good precision. The findings advocate for the adoption of modern techniques in credit scoring modelling, positioning K-nearest neighbour and Artificial neural networks as a valuable tool in financial institutions’ risk assessment processes.

PROVENANCE AND COMPOSITION OF THE BIMA GROUP EXPOSED AROUND WUYO VILLAGE, UPPER BENUE TROUGH N.E. NIGERIA

2025-01-17T05:29:01+00:00

Provenance study of Bima group of the Upper Benue Trough around Wuyo village was carried out on fresh representative samples. The petrographic results suggest the sandstones to be arkosic arenites, the average composition of the three rock forming minerals as observed are; 40% quartz, 46% feldspar and 3% rock fragments. The higher percentage of feldspar, the sphericity of the grain sizes which are largely sub-angular to sub-rounded and the poorly sorted nature of the sandstones as well as ZTR index of 60.3% from the heavy minerals analysis suggest immature sediments, they are deposited close to their source area. The coarse grain Sandstone in the study area were deposited by fluviatile system while the fine grain sandstone and clay were deposited in a lacustrine environment. The dominance of monocrystalline quartz as well as the Microscopic examination of the heavy minerals contained in the sandstones of the study area revealed that the sediments originated from dominantly granitic source and deposited by a moderate to high energy level shallow water continental conditions. The sutured contact, polycrystalline quartz crystals and the undulose extinction exhibited by some of the few quartz crystals in the petrographic studies is as a result of stress the sediment went through after deposition.

A MULTIFACETED SENTIMENT ANALYSIS APPROACH TO THE ESTIMATION OF THE STRENGTH OF ONLINE SUPPORT FOR POLITICAL CANDIDATES IN NIGERIA'S ELECTIONS

2025-01-17T05:29:02+00:00

The strength of online support for political candidates in an election is crucial to their victory at the polls, particularly in countries with advanced digital infrastructure and culture. In modern times, social media is one free space where residents express, and are persuaded to, support or show disdain for political candidates prior to an election. This has resulted in the opinion mining of political tweets to predict electoral victories at the polls. However, this is usually done by adopting a single sentiment analysis model and scraping tool. Ordinarily, no sentiment analysis model or scraping tool is a silver bullet – each has strengths and weaknesses. Thus, this study employed two contemporary scraping tools and adopted three contemporary sentiment analysis models. The models were then exposed to the scrapped political tweets of the top contestants for the Nigeria 2023 presidential election, validated with another set of political tweets of the top contestants for the 2024 Edo State governorship election, and, after that, used to predict the online support strength of the top contestants for the 2024 Ondo State governorship election. Only tweets from within the geopolitical space of elections were scrapped. A notable finding of this study is that no two sentiment analysis models estimate the same online support strength for selected candidates, even with the same set of tweets. Overall, the study holds that online support strength is necessary but insufficient to guarantee victory at the polls in Nigeria's elections.

INFLUENCE OF DIETARY INCORPORATION OF MORINGA (MORINGA OLEIFERA) LEAF MEAL IN DIETS OF BROILER CHICKENS ON GROWTH PERFORMANCE AND ECONOMIC BENEFITS

2025-01-17T05:29:02+00:00

Consuming enough high-quality protein is essential for a long and healthy life. Because of their high-quality protein content, broiler chickens are a valuable food source that can support optimum growth and development and assist in address dietary deficiencies in Nigeria. The experiment was carried out at Adamawa State University Teaching and Research Farm, Mubi to evaluate the effects of diets containing varying levels of moringa (Moringa oleifera) leaf meal (MoLM) on growth performance and cost benefits fed to broiler chickens. The broiler chicks were purchased and maintained on a deep-litter system throughout the study. Fresh Moringa oleifera leaves were shed-dried and pulverised into fine particles. The powder was incorporated into the diets at 0, 0.5, 1, 1.5 and 2 g/kg denoted as control, 0.5MoLM, 1MoLM, 1.5MoLM and 2MoLM, respectively. The birds were randomly allotted to the different diets in a completely randomised design. Data collected during the study were: weight gain, feed intake, feed conversion ratio and the cost benefits of feeding MoLM-based diets. Significant (p<0.05) results were observed for most growth performance parameters. Weight gain and feed intake were high in the control followed by 2MoLM (1023.00 and 2825.80 g, respectively). The FCR was least for 1.5MoLM (2.37) compared to the control diet. The 1.5MoLM ensured a higher cost saving amongst the other diets. Mortality was reduced with increased levels of MoLM. It can therefore be agreed from this study that the inclusion of 1.5 g/kg MoLM in broiler chicken diets promoted better feed efficiency and more cost saving.

OPTIMIZING HEATED AIR CIRCULATION IN SILO/BIN DESIGN: A PARAMETRIC APPROACH

2025-01-18T05:29:09+00:00

Aeration is one of the most essential processes after harvest in guaranteeing food security since it is often employed for grain cooling while the physical qualities of the stored grains are sustained. Aiming to address issues of storage inefficiencies, the research reviewed “Optimization of Heated Air Circulation in Silo/Bin Design: A Parametric Approach.” The method adopted for the study was systematic review of journal articles, conference proceedings, books and other relevant materials. Furthermore, the main method used to find relevant publications for the study was keyword searches in electronic databases such as Research Gate, Web of Science, Google Scholar and Scopus. Hence, the study ascertained that at an optimal temperature range between 10 - 15°C, grain storage facilities can effectively mitigate the risks of moisture accumulation, insect infestation, and microbial growth. More so, the study revealed that the rate of airflow ranging from 0.05 to 0.1 m³ min^-1 t^-1 are usually utilized in tall steel bins and concrete silos containing small grains, again measurements ranges from 0.1 to 0.2 meter cubed per minute per tonne were suggested for horizontal storage for huge grains. However, the study suggests that SSR model seems to be the most suitable model for optimization of heated air circulation in silo/bin among all the reviewed models because it is capable of describing nearly all the systems’ dynamics.

A TREATMENT OF A MULTISTEP COLLOCATION METHOD FOR THE DIRECT SOLUTION OF SECOND-ORDER ORDINARY DIFFERENTIAL EQUATIONS

2025-01-20T05:29:58+00:00

A research has been conducted at the Department of Mathematics, Faculty of Science, Federal University, Gashua, Yobe State to study the treatment of multistep collocation method for the direct solution of second order ordinary differential equations using a class of modified Backward Differentiation Formular (BDF)-type with one super-future point. The research has proposed the construction of a new method of solving second-order initial valued problem of ordinary differential equation. A step-number, , a number of discrete members are obtained and used in block through multi-step collocation approach. The stability properties of the newly constructed methods are investigated using written computer codes and its convergence are established. The numerical efficiency of the method has been tested on some treated second-order initial valued problems, in order to ascertain its suitability. The solutions of the problems are compared with the corresponding exact solutions and the associated absolute errors are presented. Tables and graph have been adopted in the presentation of results, and they have shown the efficiency of the new method for solving solution of second order ordinary differential equations.

BUCCAL CELL STAINING EFFECT OF LAWSONIA INERMIS AQUEOUS LEAF EXTRACT

2025-01-20T05:29:58+00:00

Lawsonia inermis (henna) is a perennial shrub or plant belonging to the Lythraceae family. Hands, nails, fingers, and even hair can be dyed using henna plants, which are a natural colour. The study aims to examine the use of Lawsonia inermis aqueous extract (local stain) as a substitute for methylene blue in the demonstration of buccal swabs in people. Twelve volunteers offered their time to help gather buccal mucosa samples. The volunteers used tap water and normal saline to rinse their mouths. A wooden spatula was used to scrape the cheeks' buccal surface. Each was applied on a glass slide after being diluted with regular saline. 70% alcohol was used to fix the smear, and it was then let to dry. Methylene blue and Lawsonia inermis aqueous extract were used to stain the smears. Squamous epithelial cells' cytoplasm and nucleus were visible on methylene blue-stained slides. There was no nuclear staining in the squamous epithelial cell stained with Lawsonia inermis aqueous extract. Nevertheless, it stained the nucleus when counterstained with hematoxylin. Lawsonia inermis plus hematoxylin-stained buccal smear present a better result compared to the Lawsonia inermis plus eosin-stained slides. Hence, it can be counterstained with hematoxylin to demonstrate buccal cells.

ANTIBACTERIAL STUDIES OF ESSENTIAL OIL FROM THE FRESH LEAF OF LEMON GRASS CYMBOPOGON CITRATUS

2025-01-20T05:29:58+00:00

Cymbopogon citratus, belongs to Gramineae family. This study used a microwave-assisted hydro-distillation process to extract lemongrass essential oil and examined its antimicrobial qualities. Physical characteristics of the essential oils included a yellow color, a yield percentage of 4.67%, solubility in trichloromethane, and a lemony aroma. The disc diffusion method was used to assess the oil's effectiveness. Pseudomonas aeruginosa, Klebsiella oxytoca, Staphylococcus aureus, and Escherichia coli were all susceptible to the oil's concentration-dependent antibacterial qualities. 5.72 mmL/disc was the oil's most effective concentration against E. coli, while 1.43 mmL/disc was its least effective. The zone of inhibition shrank as the concentration of oil per disc dropped, indicating that the oil's activity against all species was concentration-dependent. At concentrations of 5.72 mmL/disc, 2.86 mmL/disc, and 1.43 mmL/disc, respectively, the zone of inhibition for E. coli was 24, 11.3, and 7.7 mm. For other creatures, the pattern is the same. Pseudomonas aeruginosa had the smallest zone of inhibition, measuring 7.0, 7.0, and 5.7 mm at concentrations of 5.72 mmL/disc, 2.86 mmL/disc, and 1.43 mmL/disc, respectively. Staphylococcus aureus was 13.3, 10.3, and 9.0 mm at concentrations of 5.72 mmL/disc, 2.86 mmL/disc, and 1.43 mmL/disc, while Klebsiella oxytoca was 11.3, 9.7, and 9.0 mm at concentrations of 5.72 mmL/disc, 2.86 mmL/disc, and 1.43 mmL/disc, respectively. These results imply that lemongrass essential oil may be a viable natural substitute for synthetic antibiotics, with potential uses in medical and food preservation. It is advised that additional bioassays be conducted and contrasted with the results obtained from alternative...

INFLUENCE OF GOAT DUNG ON SOIL PROPERTIES, GROWTH AND YIELD OF MAIZE IN GWAGWALADA, FCT, NIGERIA

2025-01-21T05:30:23+00:00

Farmers in the Guinea Savannah region of Nigeria rely on inorganic fertilizer to mitigate yield reduction caused by low soil fertility. Unfortunately, high purchasing cost and harmful residual effect of chemical fertilizers render them unsustainable. However, goat dung, which is an animal waste, can be harnessed as organic amendment. Therefore, a field experiment was conducted at the Teaching and Research Farm, Faculty of Agriculture, University of Abuja, Nigeria to evaluate growth and yield response of maize to goat dung amended soils. Three levels of goat dung (0 kg, 1.8 kg, and 2.7 kg of goat dung) were incorporated into the soil during land preparation. A Randomized Complete Block Design (RCBD) was used for arranging the treatments, which were replicated three times. Vegetative components: plant height, leaf area, number of leaves, as well as yield parameters: cob length, cob diameter, cob weight, number of seeds/cob, 1000 seed weight and seed yield were evaluated and subjected to Analysis of Variance (ANOVA) using GenStat statistical software (17th Edition). Significantly different means were separated using Duncan New Multiple Range Test (DNMRT) at 5% level of significance. Result showed that application of goat dung increased soil properties (pH, organic matter content, total N, available P, CEC, exchangeable K, Na, Ca, Mg) and improved growth and yield of maize; however, increments were not significant. Thus, further trials are recommended using higher quantities of goat dung.

EFFICACY OF CHICKEN MANURE AND PLANTS SPACING ON THE GROWTH AND YIELD OF GARDEN HUCKLEBERRY (Solanum scabrum) IN SARDAUNA LOCAL GOVERNMENT AREA, TARABA STATE

2025-01-21T05:30:24+00:00

Garden Huckleberry is an edible form of the common nightshade weed plant belonging to the family Solanaceae. The research was conducted in Sardauna Local Government, Taraba State. The objectives of the study were to determine the fertilizer (chicken manure) rate and spacing adequate for garden huckleberry cultivation. The experiment consists of three rate of chicken manure (0t/ha, 15t/ha and 20t/ha) with two spacing of 10cm×15cm and 15cm×20cm, with plots size of 0.75m² which was laid out in a randomized complete block design (RCBD) with three replications. The data were analyzed and presented using Figureical presentation. The result shows that chicken manure rate of 20t/ha, and 15×20cm spacing produced Huckleberry with highest number of leaves at 6 weeks after sowing among others. The researcher therefore, recommended that poultry manure at the rate of 20t/ha and the spacing of 15×20cm to be use by the farmers in huckleberry production for maximum yield.

AN ENHANCED MODEL FOR PREMIUM MOTOR SPIRIT (PMS) PRICE PREDICTION AND MANAGEMENT IN NIGERIA USING MACHINE LEARNING

2025-01-22T05:30:26+00:00

Forecasting Premium Motor Spirit (PMS) prices accurately is crucial for economic stability and effective decision-making in Nigeria. Premium Motor Spirit (PMS), which is also known as petrol or fuel, plays a pivotal role in the country's economy, impacting transportation costs, inflation rates, and overall economic growth. However, the unpredictability of PMS prices prediction and management is influenced by factors like government policies, international oil markets, supply chain disruptions, stakeholders and interested cartels amongst others. This has created a constant price fluctuation, poor price control and management which eventually lead to fuel scarcity and high cost of fuel. The price control mechanism remains a contentious issue, with debates over its impact on the economy, government spending, and the welfare of ordinary Nigerians. This article presents an enhanced model for Premium Motor Spirit (PMS) price prediction and management in Nigeria using machine learning that will improve the price prediction and management system that will produce high degree of accuracy. The system was developed using visual studio C#, ML.Net model and Microsoft SQL server for its backend database. This model identifies key factors impacting PMS prices prediction and management that is used to forecast PMS prices over a specified time horizon such as daily, weekly, or monthly thereby enhancing economic planning and stability in Nigeria.

EFFECTS OF DICHLOROMETHANE FRACTION OF ETHANOL EXTRACT OF PHYLLANTHUS AMARUS LEAF ON 1, 2-DIMETHYLHYDRAZINE INDUCED HEPATO-RENAL DYSFUNCTION IN SWISS ALBINO MICE

2025-01-22T05:30:27+00:00

The objective of this study was to assess the impact of the Dichloromethane (DCM) fraction of the ethanol extract from Phyllanthus amarus leaves on hepato-renal toxicity induced by 1,2-dimethylhydrazine (DMH) in Swiss albino mice. A total of twenty-five male Swiss albino mice, each weighing between 21-25g, were used in a 90-day (12-week) experiment. The mice were divided into five groups: Group 1 (Control), Group 2 (25 mg/kg DMH + 250 mg/kg DCM fraction of P. amarus), Group 3 (25 mg/kg DMH + 350 mg/kg DCM fraction of P. amarus), Group 4 (25 mg/kg DMH + 450 mg/kg DCM fraction of P. amarus), and Group 5 (25 mg/kg DMH). Each cage, made of mental steel, housed five animals. The mice had free access to food and clean water and were kept under a 12-hour light/dark cycle. DMH was administered orally at a dose of 25 mg/kg body weight using a dolphin gavage, three times a week for a duration of eight weeks. Following the end of DMH treatment, the DCM fraction of the ethanol extract of P. amarus leaves was administered orally for an additional four weeks. The animals were fasted overnight and were sacrificed after being anesthetized using urethane. Blood was collected into plain and EDTA containers for biochemical investigation. Liver and kidneys were excised and homogenized for the assay of some antioxidant biomarkers. Liver function indices were assayed as well as kidney function biomarkers. Portions of the liver and kidney were used for histological analysis Results obtained showed that...

PREDICTION ACCURACY ANALYSIS OF MACHINE LEARNING CLASSIFIERS ON STUDENT COURSE ASSESSMENT METHODS

2025-01-22T05:30:26+00:00

There is growing need to improve the quality of education through an effective service delivery from educators. Also, educational institutions are searching for ways to reduce student failure rate. The rapid growth in size and availability of student data and robust algorithms to generate machine learning models, more accurate predictions and tailored learning interventions can be factored. The research investigates the prediction accuracy of machine learning algorithms, including Logistic Regression, Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Naive Bayes, XGBoost, and Gradient Boosting, applied to student learning attributes and course assessment. The aim is to evaluate the effectiveness of these algorithms in predicting student performance on various metrics. A dataset encompassing student learning attributes and assessment modes were analyzed. Each algorithm's predictive capabilities was assessed using accuracy, precision, recall and F1-score metrics. Logistic regression had the highest accuracy score of 0.93, SVM and XGBoost both achieved an accuracy 0f 0.90 while Random Forest, KNN and Naive Bayes achieved same accuracy score of 0.88 while Gradient Boosting achieved an accuracy score of 0.85 each which was the lowest. RF, SVM, KNN got the same F-score, recall and precision of 0.93, 0.97 and 0.90 respectively while Naive Bayes, XGBoost, and Gradient Boosting achieved the same recall of 0.94 while KNN had a recall of 0.97. Gradient Boosting had a precision of 0.89, and an F-score of 0.92, the F-score of Naïve Bayes was 0.93. This research underscores the potential of advanced machine learning techniques in enhancing educational outcomes.

COMPARATIVE STUDY ON THE FUNGI DETERMINANTS IN LOCUST BEANS (IRU) PRODUCED FROM PARKIA BIGLOBOSA AND PROSOPIS AFRICANA

2025-01-22T05:30:27+00:00

Iru, a traditional fermented condiment widely consumed in West Africa, is produced from the seeds of Parkia biglobosa (African locust bean) and Prosopis Africana (Mesquite/Okpehe). The quality and safety of Iru can be significantly affected by fungal contaminants during processing and storage. This study aims to compare the fungal contaminants present in Iru produced from Parkia biglobosa and Prosopis Africana, examining their impact on the nutritional and microbial quality of the final product. Standard mycological techniques were used to isolate and identify fungal species using Potato dextrose agar (PDA). The microbial load, proximate composition, and physicochemical properties of the samples were analysed to assess the quality and safety of the fermented products. Results showed that Parkia biglobosa Iru exhibited a higher diversity of fungal species compared to Prosopis Africana Iru. Aspergillus niger and Sacharomyces cerevisiae were the most prevalent with (23.81%) each while Penicillium chrysogenum has the least prevalence (1.0%). This diversity poses a greater risk of mycotoxin contamination in Iru from Parkia biglobosa. Both Prosopis Africana and Parkia bioglobosa offers significant nutritional benefits but Parkia generally has higher moisture content, protein and fat content while Prosopis contains higher fibre, ash content and carbohydrates which aids metabolic process overall nutritional value and energy source respectively.

MONTE CARLO EVALUATION OF WHITE'S TEST FOR DETECTING HETEROSCEDASTICITY IN GENERALIZED LINEAR MODELS

2025-01-22T05:30:28+00:00

Heteroscedasticity in regression analysis occurs when the variance of the error term changes across different levels of the independent variable(s), leading to inefficient estimates and incorrect inference. In Generalized Linear Models (GLMs), heteroscedasticity significantly impacts prediction and inference accuracy. This study evaluates White's test for detecting heteroscedasticity in GLMs through Monte Carlo simulations. We investigate the test's power, Type II errors, and Type I errors at different sample sizes (100, 250, and 500). Our findings reveal that White test performs well in detecting strong heteroscedasticity, particularly for exponential heteroscedasticity structures (EHS), but poorly for weaker forms like linear heteroscedasticity structures (LHS) and square root heteroscedasticity structures (SQRTHS). While increased sample size enhances performance, the test remains susceptible to over-rejection of homoscedasticity. We recommend cautious use, especially with weaker heteroscedasticity or specific structures. For improved performance, use the test with moderate to high sample sizes (e.g., n = 500), particularly for EHS and quadratic heteroscedasticity structures (QHS). Alternative tests may be considered for researchers with limited sample sizes or dealing with LHS and SQRTHS. Finally, we emphasize the importance of assessing the underlying structure of heteroscedasticity in the dataset to choose the most suitable test and interpretation.

EVALUATING THE RELATIONSHIP BETWEEN VARIABLES: A CANONICAL CORRELATION ANALYSIS OF ACADEMIC PERFORMANCE IN NIGER STATE POLYTECHNIC, ZUNGERU

2025-01-22T05:30:29+00:00

Canonical Correlation Analysis (CCA) is a statistical technique used to investigate the relationship between two set of variables. CCA is particularly useful when dealing with multiple outcome variables that are intercorrelated. In situations where multiple regression analysis would be applicable, but there are multiple correlated dependent variables, CCA provides a more suitable approach. In this research, we used Canonical Correlation Analysis to investigate the level of correlation between some departmental and non-departmental courses, taken ND1 Estate Management and Valuation department, Niger State Polytechnic, Zungeru, 2022/2023 session as case study. Slovin’s formula was used to determine the appropriate sample size to be used in this study. The researchers sampled 48 from the population in ND1 class. The analysis carried out using the SPSS package. Results obtained from the analysis shows that the correlation of (EST111 on EST114) is 0.708. Also, the correlation of (GNS111 on EST114) is 0.552. Y variables are the results of GNS101 and GNS111 and also represented by and respectively. X variables are the results for EST111 and EST114 and represented as and respectively. The extent to which departmental courses correlate with non-departmental courses is stronger than how non-departmental courses correlate with departmental courses this is in line with the outcome of the analysis. Based on the results obtained, it was recommended that there should be more efforts by the lecturers teaching non-departmental courses in the department concerned and the institution entirely.

COMPARATIVE ANALYSIS OF GASTROINTESTINAL PARASITES IN FISH FROM KADUNA RIVER AND SELECTED DOMESTIC PONDS IN KADUNA METROPOLIS

2025-01-22T05:30:29+00:00

Fish is a source of livelihood for fishermen and fish farmers especially in Nigeria and other developing countries. Fish from river and domestic ponds are widely consumed today, hence the need to conduct this study to enable monitoring and adopting control measures of parasites. The aim of this research to analyze the gastrointestinal parasites in fish from Kaduna River and selected domestic ponds in Kaduna metropolis. Results showed that 197 fishes out of the 350 examined were infected, giving an overall prevalence (56.3%) in fish from Kaduna River and selected domestic ponds. Infection was significantly higher in fishes from Kaduna River (68.0%) than in those from selected domestic ponds (27.0%). The male was 68.3% significantly higher (p < 0.05) than that of the female (23.1%) and there was significant association (p < 0.05) in the prevalence of gastrointestinal parasites and weight of fish sampled from Kaduna River and selected domestic ponds. Intestines harboured the highest number of parasites (168) than stomach and parasites identified comprised of three taxonomic groups, the nematodes were Capillaria species, Paracamallanus species, Contracaecum species and Camallanus species respectively. Cestode was Diphyllobothrium latum and Trematode was Clinostomum species. There was no significant difference (p > 0.05) of intensity and parasite load to the fish species of parasites identified from River Kaduna and selected domestic ponds. The study has revealed that different parasites in fresh water fish from Kaduna River constitutes a major threat to fish productivity than the selected domestic ponds. It is recommended that...

NEXUS OF WIREFRAMES, 3D MODEL, AND SIMULATION FOR THE DEVELOPMENT OF AN INTELLIGENT WASTE MANAGEMENT SYSTEM

2025-01-22T05:30:28+00:00

The exponential growth in urban population has intensified the challenges of municipal waste management, necessitating innovative technological solutions. This research presents an integrated approach to developing a smart waste management system by integrating wireframes, 3D modeling, and simulation technologies. The study employs a three-phase methodology: utilizing wireframe prototyping for user interface design, enabling iterative development based on stakeholder feedback, implementing detailed 3D modeling of smart waste bins to visualize and optimize waste flow dynamics, and conducting comprehensive simulations to evaluate system performance under various scenarios. The simulation analysis compared multiple routing algorithms while monitoring real-time bin capacity through virtual sensors. Results demonstrate a 25% improvement in collection efficiency using dynamic routing compared to traditional fixed routes and a 30% reduction in overflow incidents through predictive capacity monitoring. The user-centered design approach, validated through wireframe testing with 50 participants, showed a 40% increase in system engagement compared to conventional waste management interfaces. Additionally, the 3D modeling phase identified critical design modifications that improved bin accessibility by 35% and reduced maintenance requirements by 20%. This research contributes to the growing knowledge of smart city solutions while providing practical insights for municipalities seeking to modernize their waste management. infrastructure. The proposed system offers a scalable, efficient approach to addressing urban waste challenges while promoting environmental sustainability. A limitation of the study is its reliance on simulation-based testing, which may not fully represent real-world operational complexities. A major challenge is implementation dependency on continuous stakeholder engagement and high reliance on technological infrastructures.

COMPARATIVE EFFECT OF ORGANIC AND INORGANIC FERTILIZER ON GROWTH AND YIELD OF TOMATO GENOTYPES, LYCOPERSICON ESCULENTUM (MILL.)

2025-01-22T05:30:30+00:00

This research was carried out to determine and to compare the effect of moringa leaf extract, poultry manure and NPK fertilizer on the growth rate and yield of the tomato genotypes. The 10 tomato genotypes utilized for this study were obtained from the tomato germplasm collection at the National Center for Genetic Resources and Biotechnology (NACGRAB), Department of Plant Genetic Resources, Ibadan, Oyo state, Nigeria. The experiment was a potted and factorial experiment whereby the tomato genotypes were subjected to 4 treatments which comprises Treatment 1 (no fertilizer), Treatment 2 (moringa leaf extract), Treatment 3 (poultry manure), Treatment 4 (NPK fertilizer). The experiment was carried out at the Teaching and Research Farm, Federal University of Technology, Akure. Data were collected on 13 agronomic characters. The application of NPK 15:15:15 fertilizer was found to greatly influence the rate of growth and yield of the tomato genotypes followed by Poultry manure and Moringa leaf extract for all the characters studied. Genotypes NGB00724, NGB00711 and NGB00695 were found outstanding among the tomato genotypes in terms of number of fruits, number of clusters, individual fruit weight and yield per plant irrespective of the type of fertilizer applied.Hence, these tomato genotypes could be improved upon and released as high yielding tomato varieties to farmers. The use of moringa leaf extract and poultry manure to produce tomato is a worthwhile alternative in place of NPK fertilizer.

FORECASTING PERFORMANCE OF SOME GARCH MODELS ON HOLIDAY-INDUCED VOLATILITY IN NIGERIA STOCK EXCHANGE PRICE RETURNS UNDER DIFFERENT ERROR DISTRIBUTIONS

2025-01-23T05:30:29+00:00

Time series data occasionally depend on factors among which are holidays (such as Mother’s days, Children’s days, Democracy days, Independent Days, Valentine’s days to mention but few) which number of researchers did not put into consideration. This paper aimed at evaluating the forecast performance of some asymmetry GARCH models (EGARCH, GJR-GARCH, and APARCH) on holiday-induced volatility in Nigeria stock exchange price returns under three different error distributions of innovation: Normal, Skewed student’s t, and Generalized Error Distribution (GED). Based on minimum value of Root Mean Square Error (RMSE), EGARCH (1,1) model under Skewed student’s t is found to be the best model. In addition, there exists consequences of all the holiday’s that falls on Thursday’s (with effect 0.002803; indicating that for any unit of holiday on Thursday(s), the volatility of NSE price series returns will significantly increase by 0.002803). Volatility clustering and persistence are found in the models. More so, leverage effect is found in EGARCH model under the three error distributions of innovation.

PREDICTIVE MODEL FOR HEALTH INSURANCE COST USING SELF-ORGANIZING MAPS AND XGBOOST

2025-01-23T05:30:29+00:00

Machine Learning (ML) techniques are gaining more adoption in every sector in order to improve their services. The healthcare industry is not left behind in this development of adopting ML predictive model to increase their efficiency and productivity.The paper developed a predictive healthcare insurance cost Model using Self-Organizing Maps (SOM) and XGBoost models. In this study, two models, SOM and XGBoost were deployed for medical insurance cost prediction using the dataset from KAGGLE’s repository which consists of 1338 instances and 7 predicting parameters. The dataset were preprocessed and thereafter divided into 80% for training and 20% for testing. The comparative result from the prediction showed that the two models achieved impressive outcomes, and whereas the XGBoost model achieved the results of MAE score of 2432.04, MSE of 18030522.49 and RMSE of 4246.24. The SOM model achieved result of MAE score of 3978.29, MSE of 32775593.13 and RMSE of 5724.997216804203. The quantization error of 0.5135462765843376 and topographic error of 0.9730941704035875 generated for SOM model developed. The study concluded that XGBoost outperformed SOM for the insurance predictive model developed and the model is recommended for healthcare sectors to assist in decision making as regard to health insurance cost. More future works can be done using more predicting factors in the dataset and other machine learning algorithms can be employed.

INVESTIGATION OF THE DIAGNOSTIC ACCURACY OF MALARIA RAPID DIAGNOSTIC TEST IN PATIENTS WITH RECURRING MALARIA SYMPTOMS

2025-01-23T05:30:29+00:00

Accurate diagnosis and proper treatment are central to breaking malaria transmission cycle and eradication of malaria especially in an endemic country as Nigeria Malaria rapid diagnostic test RDT is a simple and effective diagnostic tool There is rise in the use of RDT in malaria diagnosis in Nigeria however its accuracy in patients with recurring malaria symptoms is unclear This study evaluated the efficacy of Plasmodium falciparum histidinerich protein 2 based rapid diagnostic test RDT in the diagnosis of malaria in patients with recurring malaria symptoms Microscopy was used as the reference method for diagnosis Giemsa and Field stained thick and thin smear were used to count and detect malaria parasite The results showed that out of 100 participants examined a total prevalence of 85 percent Giemsa stain 83 percent Fields stain was recorded for microscopy while and 36 percent was recorded for RDT Additionally we observed that there was no significant difference p005 in the parasite density observed in both Giemsa and Fields staining technique Conclusively our study revealed that RDT is not effective in diagnostic tool in patients with recurring malaria symptoms therefore microscopy is still the gold standard for malaria diagnosis

NIGERIAN ETHNICITY CLASSIFICATION THROUGH FUSED FEATURES FROM MOBILENET-V2 AND LOCAL BINARY PATTERN GUIDED BY ATTENTION MECHANISM

2025-01-23T05:30:28+00:00

Our face plays a vital role in many human-to-human encounters and is closely linked to our identity. Significant promise exists for the automatic recognition of facial features, opening the door to hands-free alternatives and innovative uses in computer-human digital interactions. Deep learning techniques have led to a notable increase in interest in the field of face picture analysis in recent years, especially in applications like biometrics, security, and surveillance. Due to feature overlaps and dataset under-representation, ethnicity classification in computer vision is still a difficult task, particularly for African populations. This study explores Nigerian ethnicity classification, focusing on the three major groups—Hausa, Igbo, and Yoruba—using a hybrid model that integrates MobileNetV2, Local Binary Patterns (LBP), and an Attention Mechanism. The hybrid model achieved an overall classification accuracy of 87%, significantly outperforming benchmarks, particularly in Igbo and Yoruba classifications. While the Yoruba group demonstrated the highest accuracy, overlaps between Hausa and Igbo highlight areas for refinement. This research advances the field by addressing dataset imbalances, incorporating innovative feature fusion, and improving the inclusivity of computer vision models. It has practical implications for identity verification, security, and demographic research while emphasizing the importance of culturally sensitive AI systems tailored to underrepresented populations. Future work includes expanding datasets, enhancing model architectures, and exploring interdisciplinary approaches to further refine ethnicity classification.

INVESTIGATION ON THE COMPARATIVE PROXIMATE AND ELEMENTAL COMPOSITIONS OF THE FRUIT AND LEAF OF SOLANUM AETHIOPICUM CULTIVATED IN JOS

2025-01-23T08:00:33+00:00

Solanum aethiopicum, commonly referred to as the African eggplant, is one of the commonly consumed vegetables in Nigeria and other African countries because of its nutritional value and health benefits. Despite its pervasiveness, limited studies have focused on the proximate and elemental compositions of this species, especially in Jos, Nigeria. The study conducted a comprehensive proximate and elemental analysis of the fruit and leaf extracts of S. aethiopicum using n-hexane, acetone, and ethanol for maceration. Proximate and elemental analyses were conducted on fruit and leaf extracts of Solanum aethiopicum, using n-hexane, acetone, and ethanol for maceration. The results showed that fruit extracts had higher moisture, crude fat, fiber, and total protein compared to leaf extracts. However, leaf extracts had slightly higher total carbohydrates and total ash. Specifically, the moisture content for n-hexane fruit extract was 61.04 ± 0.47, while for leaf extract was 59.75 ± 0.64. Total protein in n-hexane fruit extract was 1.74 ± 0.04 compared to 1.55 ± 0.25 in leaf extract. Fiber content was 5.57 ± 0.11 in fruit and 3.54 ± 0.04 in leaf extracts. Crude fat was 5.70 ± 0.45 in fruit and 6.23 ± 0.13 in leaf extracts. Total carbohydrates was 10.24 ± 0.37 in fruit and 11.40 ± 0.09 in leaf extracts, while total ash was 15.71 ± 1.24 in fruit and 17.52 ± 1.17 in leaf extracts. Elemental analyses revealed that magnesium (Mg) was 183.06 ± 2.56 in fruit and 165.60 ± 0.29 in leaf extracts; iron (Fe) was 68.17 ± 0.28...

AMELIORATIVE POTENTIALS OF Trigonella foenum-graecum (FENUGREEK) SEEDS ON PROTEIN-ENERGY MALNOURISHED RATS

2025-01-23T08:54:50+00:00

HIERARCHICAL MODELS OF FISH ABUNDANCE AND OCCURRENCES IN SOUTHERN BASIN OF KAINJI LAKE NIGERIA

2025-01-24T05:30:46+00:00

Fish abundance is directly linked to species diversity, indicating the importance of maintaining rich fish communities for ecosystem stability and productivity. The aim of the study is to fit hierarchical models to modelled fish abundance through the following objectives: Evaluate fish abundance and occurrences using abundance formulae and their diversity index, fit hierarchical models, Investigate the variability of fish abundance and occurrences in different fishing locations and to identify the consequences of location specific management actions. Shannon weinner and Sampson diversity index reveals that Monai fishing location has the highest percentage of catch ranging to 30%. Cast net is found to be the most efficient method with highest count value of 1.9457, Poisson and negative binomial models reveal that, the locations have no significant difference and there is variability among fish catch over the years. Negative binomial reveals that Monai has the highest fish in abundance having the fish count value of 1.067 with a decrease in fish population by 7%. These results indicate significant variations in fish abundance and occurrence across the locations, years and methods. From the comparative regression and negative binomial model. Negative binomial model has the lowest log like hood of 7855874.07, with a deviance of 434.34. This infers that the negative binomial regression performs better than the Poisson regression in modelling fish abundance and occurrence. This study contributes valuable knowledge about dynamics of fish populations and basis for informed decision making in fisheries management and conservation.

QUANTITATIVE TRAIT LOCI (QTL) MAPPING FOR DROUGHT TOLERANCE AND YIELD IN NIGERIAN GROUNDNUT (ARACHIS HYPOGAEA) VARIETIES

2025-01-23T13:50:55+00:00

This study investigates the genetic basis of drought tolerance and yield in Nigerian groundnut (Arachis hypogaea) varieties through Quantitative Trait Loci (QTL) mapping and phenotypic analysis. Addressing the critical need for improved drought tolerance, it employs modern molecular breeding techniques to identify key genomic regions associated with resilience and productivity under water stress, supporting sustainable agriculture in Nigeria's challenging climatic conditions. A diverse panel of groundnut genotypes was evaluated under drought-stressed and well-watered conditions across multiple locations in Nigeria. Significant differences were observed in wilting scores, root lengths, and pod yields among the genotypes, with local landrace G3 and improved variety V2 demonstrating superior drought tolerance. Specifically, G3 maintained a pod yield of 3200 kg/ha under drought stress, while the exotic variety E1 yielded only 1900 kg/ha. QTL mapping identified four major QTLs significantly associated with drought tolerance traits: qDT1 (root length), qDT2 (stomatal conductance), and qYLD1 (pod yield under drought), explaining 35%, 28%, and 40% of the phenotypic variance, respectively. High heritability estimates for root length (0.75), wilting score (0.68), and pod yield under drought (0.62) suggest that these traits can be effectively improved through selection. The positive correlations between root length and pod yield (r = 0.58) and relative water content (RWC) with stomatal conductance (r = 0.62) further indicate that selecting for these traits could enhance yield stability under drought conditions. These findings underscore the potential of utilizing QTL mapping and marker-assisted selection to develop drought-resistant, high-yielding groundnut varieties tailored to Nigeria's diverse agro-climatic conditions, contributing to...

NHANCING NETWORK SECURITY THROUGH INTEGRATED DEEP LEARNING ARCHITECTURES AND ATTENTION MECHANISMS

2025-01-24T04:57:53+00:00

With the widespread integration of the Internet into our daily life, ensuring network security has become crucial for applications like online retail, auctions, and file processing. By examining network process logs, intrusion detection and classification are crucial for spotting threats. The issue of network infiltration is made worse by the increasing volume and complexity of contemporary network traffic data, making traditional intrusion prevention methods insufficient. Therefore, low false alarm rates and effective intrusion detection systems are essential. In order to increase efficacy and efficiency, the model uses Convolution Neural Network-Long Short Time Memory (CNN-LSTM) for feature extraction and classification. The attention mechanism is used to choose the most discriminative features. Metrics including accuracy, precision, recall, and the F1-score are used to assess the model's performance. These metrics reveal how well the model detects intrusions (true positives), prevents harmful traffic from being mistakenly labelled as normal (true negatives), and classifies data overall. About 99.9% accuracy is attained by the model, with a precision of 0.98, recall of 1.0, and F1-score of 0.99. These results reflect its ability to effectively identify both normal traffic and intrusion attempts. The high accuracy underscores the model’s strong performance in distinguishing malicious from benign activities. This work contributed to cybersecurity by presenting an innovative solution to intrusion detection challenges. It highlights the importance of balanced datasets and advanced deep learning architectures to improve detection capabilities. The results highlight how well the model can handle the intricacies of contemporary network security risks.

ESTIMATION OF SEDIMENTARY AQUIFER’S PARAMETERS WITHIN IDAH AND ENVIRONS, PART OF NORTHERN ANAMBRA BASIN, NIGERIA

2025-01-24T05:30:45+00:00

A BLOCKCHAIN-DRIVEN VAT COMPLIANCE MODEL USING HYPERLEDGER FABRIC AND MONTE CARLO SIMULATIONS

2025-01-24T05:30:45+00:00

This paper presents the development and evaluation of a VAT compliance model utilizing Hyperledger Fabric blockchain technology integrated with Monte Carlo simulations. The model aims to address the pervasive issue of VAT non-compliance by providing real-time monitoring and automated compliance checks. By simulating 10,000 VAT-related transactions under various compliance scenarios, the study assesses the model's performance in detecting both compliant and non-compliant transactions based on product registration and VAT rate application. The Monte Carlo simulations generate diverse transaction scenarios, while the blockchain provides a secure, immutable ledger for tracking each transaction's compliance status. The model is tested on a system simulating real-world conditions, focusing on key metrics such as transaction throughput, latency, accuracy, sensitivity, precision, and specificity. The results demonstrate that the model achieves 100% accuracy in identifying non-compliant transactions, with a transaction throughput of 1,200 transactions per second and an average latency of 0.83 milliseconds. This study highlights the potential of blockchain technology to revolutionize VAT administration by reducing non-compliance, enhancing transparency, and streamlining tax enforcement processes.

PREVALENCE OF OVERWEIGHT AND OBESITY AND THEIR CORRELATION WITH FASTING BLOOD GLUCOSE AND BLOOD PRESSURE AMONG FEMALE SECONDARY SCHOOL STUDENTS IN KANO, NIGERIA

2025-01-23T21:30:58+00:00

Childhood obesity has been linked with adverse cardiometabolic risk. Multiple indices have been used to assess obesity and associated cardiovascular risk. However, relationship between these indices and markers of cardiovascular risk has been inconsistent. This study aimed to determine prevalence of overweight and obesity and their correlation with fasting blood glucose (FBG) and measures of blood pressure among female secondary school students in Kano, Nigeria. One hundred and fifty female students were recruited. Fasting blood glucose was measured using glucose oxidase method. Anthropometric indices and blood pressure measurements were by standard protocols. Mean age of the participants was 15.67 ± 1.30 years (13 – 18 years). Mean systolic, diastolic, and arterial blood pressure were: 115.38 ± 7.62, 71.01 ± 8.34, and 85.65 ± 6.58 mmHg respectively. Mean anthropometric indices were: weight - 48.30 ± 8.85 kg, height - 1.58 ± 0.07 m, BMI - 19.43 ± 3.82 kg/m²hip circumference (HC) - 71.69 ± 15.14 cm, waist circumference (WC) - 62.05 ± 10.34 cm, waist to height ratio (WHtR) - 0.40 ± 0.07, and waist-to-hip ratio (WHC) - 0.88 ± 0.28, respectively. Mean FBG was 4.55 ± 0.28 mmol/l. Prevalence of overweight and obesity were: 6.0% and 5.3% respectively. None of the anthropometric indices correlated with FBG or blood pressure. Prevalence of overweight and obesity in adolescent female students in this environment are low and is not correlated with fasting blood glucose or blood pressure.

DEVELOPMENT OF MATHEMATICAL MODEL FOR OPTIMAL RICE PRODUCTION IN NIGER STATE, NIGERIA

2025-01-25T05:30:55+00:00

Rice is a staple food and a critical crop for food security and economic stability in Niger State, Nigeria. However, achieving optimal production levels is challenged by various factors, including environmental variability, land use inefficiency, and rising production costs. Mathematical modeling offers a systematic approach to understanding and optimizing these factors to enhance yields and promote sustainable agricultural practices. A mathematical model to optimize rice production by integrating key agronomic, environmental, and economic factors were formulated. This research paper aims to predict optimal rice yields based on input variables such as rainfall, temperature, humidity, land area use and production cost using a multivariate linear regression (MLR) method. The developed model is validated with real-world data from agricultural research stations. It was observed from the analysis that predicted values were not significantly different from the observed values. The results show that R-square, Mean Square Error (MSE) and Root Mean Square Errors (RMSE) values were 0.96345, 0.0249 and 0.1578 respectively; indicating that approximately 96.35% of the variance in rice production can be explained by the independent variables. Due to its high level of accuracy in predicting rice yield; it can be concluded that the model can be used to determine optimum rice production in Niger state, Nigeria and provide a decision-support tool for farmers and policymakers.

PRODUCTION AND CHARACTERIZATION OF ANTI-DIABETIC GOLD NANOPARTICLES USING THE LEAF EXTRACT OF MANGIFERA INDICA

2025-01-25T05:30:54+00:00

Diabetes has continued to affect the well-being of millions of individuals all over the world. More than seventy percent of Africans have undiagnosed diabetes mellitus, with Nigeria among the list of the African countries recording most undiagnosed cases. Biologically synthesized gold nanoparticles using the extracts of plants have continued to gain grounds in the treatment of diabetes. In the present research, a straightforward green method was used to form gold nanoparticles (AuNPs) from Mangifera indica leaf extract. Transmission electron microscopy (TEM), dynamic light scattering (DLS), ultraviolet visible spectroscopy (UV-Vis), X-ray diffraction (XRD), and selected area electron diffraction (SAED) were used to characterize the nanoparticles. Using XRD and SAED, the AuNPs' crystallinity was ascertained. The TEM revealed particles of various morphologies, and the UV-Vis revealed a surface plasmon resonance (SPR) at 539 nm. The stability of the colloidal suspension was implied by the DLS measurement, which revealed a hydrodynamic size of 31.74 nm and a zeta potential of -23.7 mV. With percentage inhibitions that were about equivalent to that of acarbose, the conventional medication, the AuNPs demonstrated strong antidiabetic efficacy against the alpha-glucosidase and alpha-amylase enzymes. The research revealed the potential of Mangifera indica leaf extract-mediated gold nanoparticles in treatment of diabetes.

EULER POLYNOMIALS COLLOCATION METHOD FOR SOLVING LANE-EMDEN EQUATIONS

2025-01-25T05:30:58+00:00

In this paper, Euler polynomials were utilized to formulate a collocation method for approximating Lane-Emden equations. The approximation formulations were initialized producing truncation function. The residual functions were constructed by using the truncation function. The collocation points were substituted into the residual function to form system of equations and were solved by Matlab application fsolve or Newton-Raphson methods. The results were tabulated and compared with the Herodt (2004) results for absolute error. It was observed that the Euler polynomial is very accurate and converges faster producing zero error as compared. The study recommended in solving Lane-Emden and higher order equations.

JOB SATISFACTION SCALE FOR TECH WORKERS: IMPLEMENTATION COMPASS

2025-01-25T05:30:55+00:00

Tech workers are not just employees but ubiquitous architects and drivers of the imminent digitalized future. Tech worker’s wellbeing is, therefore, crucial for global prosperity – necessitating their continuous monitoring and management in the workplace. Although a cross-cultural job satisfaction scale has been specifically developed and validated to help gauge the wellbeing of tech workers, christened JSST, it lacked an implementation guideline. This lack of implementation guidelines for the JSST questionnaire can stifle its practicality and, by extension, the wellbeing of Tech workers. The aim of this study, therefore, is to design an implementation guideline for JSST. The implementation guideline was designed using descriptive statistics and algorithmic specification. Adopting a self-assessment online survey on the original Five-point Likert JSST Questionnaire, this study also demonstrated the implementation of the guideline. 276 valid Tech workers’ job satisfaction self-assessment data solicited globally using the JSST questionnaire was employed to demonstrate the guideline’s feasibility. Overall, the job satisfaction index of the global tech workers has been estimated to fall into the third quartile of satisfaction, Q3, which is low. This low satisfaction index may account for the high turnover and turn-away in the global Tech industry. A notable outcome of this study is the seamless JSST implementation scheme, which is not only effective but also highly adaptable. This scheme can be tailored for the implementation of any multi-faceted psychometric scale, making it a versatile tool for assessing employee wellbeing. The automation for web accessibility of the JSST implementation scheme is encouraged.

ESTIMATION OF THE RELATIONSHIP BETWEEN SOLAR RADIATION, RELATIVE HUMIDITY, AND TEMPERATURE IN UGWOLAWO USING LINEAR REGRESSION ANALYSIS

2025-01-25T05:30:59+00:00

The radiation of the sun has a critical climatic influence on solar energy generation, ecology and crop production. Consequently, it is important to know how solar radiation interacts with other climate variables such as temperature and relative humidity towards developing better designs of solar arrays and mitigate the impact of climate variability. In this study, we have explored the impacts of relative humidity and temperature on the sun’s radiation. The statistical data for this work was collected from the trustworthy National Aeronautics and Space Administration (NASA) power archive. Shortwave solar radiation, relative humidity and temperature readings from January 1991 to December 2020 were retrieved and evaluated to establish average values. The results showed that the annual relative humidity ranged from 77.25% to 83.94%, while the annual temperature fluctuated between 24.86°C and 26.58°C, and the radiation from sun varied from 4.72 to 5.40 kW-hr/m². Both graphical and statistical analyses using a simple regression model indicated a slightly direct correlation between solar radiation and relative humidity while data regarding temperatures and solar radiation during the analysis period demonstrated an inverse relationship.

EXPLOITATION OF IRVINGIA WOMBOLU (OGBONO) BY RURAL WOMEN IN ETSAKO CENTRAL LOCAL GOVERNMENT AREA OF EDO STATE

2025-01-24T17:48:30+00:00

Exploitation of Irvingia wombolu constitutes a good source of livelihood and earnings for women in local communities. The study assessed rural women involvements in the exploitation of Irvingia wombolu popularly known as Ogbono in Etsako central local government area of Edo state, Nigeria. The study employed multi-stage random sampling and analyzed the data collected from 120 sampled respondents using SPSS to generate the descriptive statistics and principal component analysis (factor analysis) in line with the study objectives. The results showed that majority (53.3%) are within their active age group of 31-40years. Majority (63.3%) of the sampled respondents were married. Majority of them had not more than 5 household size members. Most of them earn average of NGN30,000 – NGN40,000 monthly from Irvingia wombolu exploitation. Similarly, majority of them were into Irvingia wombolu business as their main occupation on forest land size of between 2-4 acres and farming experience of 10 years or below. In addition, homestead garden was mostly used (70.8%) for the cultivation of Irvingia wombolu tree by the respondents in the study area. Also, quite a number of them asserted that the exploitation of Irvingia wombolu had increased their earnings and benefitted their households’ needs. However, the respondents noted that they had major challenge of inadequate finance for their business. Lastly, spoilage due to poor storage was a major factor (-0.778) limiting their involvement in exploitation of Irvingia wombolu in the study area. On this note, priority should be given to investment in storage facilities in order to...

ANALYSIS FROM 1980 TO 2018 OF TIDAL OBSERVATION DATA FOR ASSESSING THE STABILITY OF TIDAL CONSTANTS FOR PRIMARY PORT

2025-01-25T05:30:58+00:00

Tidal analysis involves the computation of tidal constants (phase lag (g) and amplitude (H)) of tidal constituents at a location. This study focuses on the assessment of the stability of g and H for the Bonny port which is the only standard tidal port in Nigeria. Monthly analysis of tidal observations was carried out with 1980, 1994 and 2018 year’s data using Least Squares Method (LSM) of Harmonic Analysis with MATLAB programming codes. The observation equation technique of LSM is adopted; the dimension of the Normal (N) matrix equations obtained for the monthly analysis is 72 56 i.e. 72 rows, and 56 columns. The N matrix is inverted and gave results for mean sea level (MSL) and g and H of 28 primary constituents of tide. Four major constituents of tide (M₂, S₂, K₁ and O₁) remain stable throughout the analysis. The mean of g and H obtained for each year was observed to be almost equal to the mean obtained from the three-year data. The maximum residuals and spreads of the computed g and H over the period of study show that g and H at Bonny are stable and that results from accurately analyze one-month data observation can be employed for tidal prediction for several years. Therefore, it can be concluded that the g and H for M₂, S₂, K₁ and O₁ are stable and that the type of tide (F) at Bonny port is semidiurnal since the computed F is 0.16 which is 0.25.

THE ODD RAYLEIGH-G FAMILY OF DISTRIBUTION: PROPERTIES, APPLICATIONS, AND PERFORMANCE COMPARISONS

2025-01-25T05:30:57+00:00

This study introduces the Odd Rayleigh-G (OR-G) family of distribution and explores its mathematical properties, applications, and performance comparisons. The Odd Rayleigh-Weibull distribution (ORWD) is developed by incorporating the "Odd" transformation into the Rayleigh and Weibull distribution, resulting in a flexible model suitable for various real-life and survival data applications. The probability density function (PDF), cumulative distribution function (CDF), hazard function, and survival function of the ORWD are derived and analyzed. Parameter estimation is performed using the Maximum Likelihood Estimation (MLE) method, and the performance of the ORWD is assessed through simulation studies. The simulations for parameter estimates at 100 sample sizes were conducted and the plot of the simulated data on the PDF, CDF, survival and hazard function demonstrate a comprehensive view of the characteristics of the Odd Rayleigh Weibull distribution. This information is useful for understanding the behaviour of the distribution and for applications in reliability analysis and survival studies. The results demonstrate the consistency and efficiency of the MLE method for the ORWD. The ORWD is compared with other distributions, including the Weibull, Power Rayleigh, and Rayleigh distributions, using goodness-of-fit measures such as the Akaike Information Criterion (AIC = 111.0238 and 87.4294), Bayesian Information Criterion (BIC = 117.2564 and 96.0320), and Kolmogorov-Smirnov (KS = 0.9559 and 0.9889) test with p-values (p-val = 7.772e-16 and 2.2e-16). The ORWD shows superior performance in fitting the mortality dataset and the Reddit advertisement dataset, highlighting its potential for modelling complex data structures. Overall, this study provides a comprehensive framework for the...

GEOCHEMISTRY OF THE UPPER CRETACEOUS SHALES FROM GOMBE FORMATION, GONGOLA BASIN, UPPER BENUE TROUGH, NIGERIA: IMPLICATIONS FOR PROVENANCE AND TECTONIC EVOLUTION

2025-01-25T05:30:58+00:00

The Gombe Formation, situated in the northeastern region of Nigeria, contains shales in addition to various sedimentary lithologies such as sandstones, mudstones, and coals. Nonetheless, the comprehensive geochemical analyses of the major oxides of these shales remain inadequately documented to date. The current study aimed to elucidate the geochemical significance of major oxides of the shales from the Gombe Formation in the Upper Benue Trough, Nigeria, using x-ray fluorescence spectrometry (XRF) within the context of provenance, tectonic settings, and paleosalinity. The average concentration of the major oxides ranged from 0.02 to 34.93 % in the shales. Among the twenty-four (24) major oxides detected, the shales exhibit elevated concentrations of SiO₂, with Al₂O₃>Fe₂O₃>SO₃>MgO>CaO>SrO>BaO>K₂O>TiO₂>Sb₂O₃>CeO₂>MnO, whereas the remaining oxides exhibited low concentrations. This observation implies that the shales were predominantly composed of quartz minerals and deposited in marine environments. The relatively high concentrations of Fe₂O₃ (with an average value of 3.36 %) and MgO (with an average value of 2.48 %) in the samples suggest that the source rocks were likely of a mafic to ultramafic nature. The values of Al₂O₃/TiO₂ and SiO₂/Al₂O₃ in the shales ranged from 1.75 to 11.02 and 6.95 to 38.44, respectively. These values indicated their derivation from a mixture of felsic igneous and mafic igneous rocks and mixed compositional maturity in proximity to the active continental margin. This study demonstrated that major oxides serve as a robust tool for assessing the provenance and tectonic characteristics of the shales from the Gombe Formation within the Gongola Basin, Nigeria.

LITHOLOGICAL DEDUCTIONS AND THE EVALUATION OF GROUNDWATER POTENTIALS FROM GEO-ELECTRICAL SOUNDINGS IN THE BENDE-AMEKI FORMATION OF EHIME-MBANO AREA, SOUTHERN NIGERIA

2025-01-25T09:30:34+00:00

Lithological deductions and evaluation of groundwater potentials from Geo-electrical soundings in the Bende-Ameki Formation of Ehime-Mbano Area, Southern Nigeria, was carried out by imploring the vertical electrical sounding (VES) technique. A total of nine VES points were obtained using the ABEM SAS 1000 Terrameter. The study reveals that the depth of the shallow wells in the area (upper aquifer) ranges from 12-22m and falls within the 3rd and 4th geo-electric layers with resistivity values ranging from 240m - 2500m; while the 2nd aquifer ranges from 34-45m and with range of resistivity values of 190m - 300m. The depth to the 3rd aquifer ranges from 70 120m, while that of the 4th aquifer is 130-300m. The data obtained after partial curve matching and computer iteration indicates a total of 8 - 10 geoelectric layers with inferred lithologies namely: silt, clay, fine-grained sand, medium-grained sand, coarse-grained sand and sandstone. Results show that most of the aquifers are hosted within the silts and fine-grained sands with the exception of a few locations with medium-grained and coarse-grained sands. By using the Dar-Zarrouk parameters, the overburden protective capacities of the aquifers in the study area were evaluated as poor, weak and moderate in some locations. It was concluded that in the area, sand mining (excavation) is a potential economic source except in the vicinity of VES 9.

THE IMPACT OF COAL MINING ON WATER AROUND OKOBO AND ODAGBO AREA, ANKPA, NORTH-CENTRAL NIGERIA

2025-01-25T10:01:39+00:00

This study evaluates how mining operations affect the Okobo and Odagbo populations' main sources of water in Kogi State, Nigeria. High turbidity levels were found in water samples taken from the streams, which serve as these communities' primary water sources. This impedes photosynthesis and endangers aquatic life. The elevated quantities of heavy metals, particularly iron and lead found in the water samples, exceeded the Nigerian Industrial Standard and the World Health Organisation's permissible limits for human consumption. The research draws attention to the possible health hazards connected to extended exposure to these tainted water sources. Isolating mine water runoff, putting water treatment technology into place, sprinkling water to minimise dust, and requiring mining corporations to enforce land reclamation rules are some of the recommendations for reducing pollution. This study emphasises the urgent need for comprehensive environmental impact assessments and the implementation of stricter regulations to safeguard water resources and the overall well-being of the affected communities.

ORGANIC FERTILIZER PRODUCTION USING BANANA PEEL, EGGSHELLS, AND YEAST: EFFECTS ON AMARANTHUS GROWTH

2025-01-25T10:24:36+00:00

The use of organic fertilizers as an alternative to inorganic fertilizers is one way to reduce the use of inorganic fertilizers, which have negative effects when used for a long time. Banana Peels, Egg Shells, and Yeast were utilized to generate an organic fertilizer in this study. Banana peel is high in biomass fibre, nitrogen, potassium, and phosphorus, all of which are essential components of organic fertilizer. Phosphate and calcium, which are essential for plant growth, are found in eggshells, while yeast serves as a catalyst in nutrient cycling and organic matter decomposition. This study used a Randomized Completely Block Design (RCBD), which consisted of 3 treatments with 3 replications. To evaluate the yield and growth performance of Amaranthus under different organic fertilizer combinations using Banana Peels, Eggshells, and Yeast. A multi-factor Duncan Multiple Range Test (DMRT) was applied after ANOVA to determine significant differences in treatments. The results indicate that the combination of Banana Peels, Eggshells, and Yeast significantly improved yield compared to the combination without Yeast. Treatment A (Banana Peels, Eggshells, and Yeast) consistently outperformed other treatments. After four weeks, Treatment A in Combination 1 (Banana Peels, Eggshells, and Yeast) achieved a mean leaf count of 32, compared to 26.33 in Treatment B (Banana Peels and Eggshells) and 15.00 in the untreated control (Treatment C). This represents a 62% higher yield compared to the corresponding treatment in Combination 2, which did not include Yeast. The addition of Yeast was crucial in boosting Amaranthus growth, contributing to improved nutrient...

ISOLATION, MOLECULAR CHARACTERIZATION AND APPLICATION OF PENICILLIUM CITRINUM AS BIOFERTILIZER POTENTIALS TO ENHANCE COWPEA GROWTH

2025-01-25T11:17:16+00:00

Chemical fertilizers are linked to a persistent decline in soil fertility, posing health hazards. This study investigated P. citrinum as a biofertilizer for cowpea (Vigna unguiculata growth. The test fungus was identified using molecular techniques from alligator pepper. Using a pot experimental method, an in-situ experiment was conducted on cowpea (TVX-3236) in the greenhouse to screen for the isolate's mycofertilizer potential. For six weeks, the cowpea was planted in six replicates in loamy soil. P. citrinum treatment was applied to the cowpea leaves in the following amounts 20 ml, 35 ml, 50 ml, 65 ml and 80 ml per bucket at a concentration of 0.08 spores per milliliter (mL) with no inoculation on the control. P. citrinum was applied on the second week and data was collected for agronomic traits (plant height, leaf number, leaf area, and root length) and leaf color. The impact of P. citrinum on cowpea height, leaf number, leaf area, and root length revealed that these agronomic parameters rose with increasing P. citrinum concentration. The cowpea in the pot that received the 80 ml P. citrinum inoculation performed the best, indicating that the plant benefited from this treatment. The experiment's results suggest that the isolate can be utilized as a mycofertilizer to promote cowpea growth. For that reason, this study offers some initial data for further investigation into the application of P. citrinum as a biofertilizer in agriculture. This fungus strain's capacity to stimulate plant development may aid in the preservation and revegetation of some vegetations.

A COMPARATIVE ANALYSIS OF THE ANTIFUNGAL EFFECTS OF YEAST AND BACILLUS SUBTILIS IN THE CONTROL OF BLUE EYE MOLD DISEASE OF MAIZE AND RICE

2025-01-25T11:39:38+00:00

Blue eye mold disease cause significant post harvest losses of grains in storage. The need to control the plant disease with the use of bio friendly agents is of paramount importance. This research assessed the antifungal effect of Bacillus subtilis and Yeast (Saccharomyces cerevisiae) in the control of blue eye mold disease that affects maize and Rice grains in storage. The diseased grains were gotten from two storage barns which were Bukuru and Katako market storage barns of Jos Metropolis and the ability of these organisms to inhibit the growth of the pathogenic fungi (Aspergillus glaucus) found in Maize and Rice grain. The research work was carried out at African Center for Phyto medicine and Research University of Jos, Plateau State. The pathogenic organism was isolated by culturing it on the SDA Media in an aseptic condition. Several other subcultures were carried out in order to get the pure isolates of the fungi. Organisms which served as biocontrol were gotten from National Veterinary Research Institute Vom (NVRI), these organisms were incubated on the same plate with the pathogenic fungi. For Bacillus subtilis, it was incubated at 25°C while that of the Yeast was incubated at 30°C. Results showed that Bacillus subtilis inhibited at 59.40% while Yeast inhibited at 95.84%in maize grains from Bukuru while Bacillus subtilis inhibited at 64.80% and yeast at 69.70%. For Katako market B. subtilis inhibited at 57.48% while yeast inhibited at 64.84% for maize grains while for Rice grains B. subtilis inhibited at 48.93% and Yeast...

POLYCHLORINATED BIPHENYLS IN FISH (HETEROTIS NILOTICUS) IN IGBOKODA RIVER, ONDO STATE NIGERIA

2025-01-16T05:29:01+00:00

Polychlorinated biphenyls are composed of 209 possible chlorinated compounds or congeners with lipophilic properties. They are bioaccumulative, persistent pollutants that have been related to a variety of negative human health effects, including cancer. Humans can be exposed to PCBs by eating contaminated foods such as fish, pig, and dairy products. The purpose of this study was to quantify PCB contents in heterotis niloticus using an electron capture detector in gas chromatography (GC-ECD). The presence of PCBs in the fish's head, tail, and centre was determined. The average total PCB concentration was 4.27g/g in the centre, 6.43g/g in the tail, and 2.42g/g in the head. PCBs 8, 18, 28, 44, 156, and 170 were discovered in the fish's head, middle, and tail, except for PCB 8, which was not found in either the head or the tail. The concentration of PCBs in this study found that, except for the middle, which had a mean value of 0.01, there was no PCB8 in the fish's head or tail. The least amount of total PCB was found in the fish head, while the highest concentration was detected in the tail. Except for PCB8, which was not calculated since it only occurred in one location of the fish, the various PCB homologs showed statistical spatial variations. According to the distribution of PCB homologs in fish samples, triPCBs were present in the majority of fish components, whereas tetraPCBs were found in the middle and tail at low levels.

COMMUNICATION MODELS IN AGRICULTURAL EXTENSION FOR SUSTAINABLE DEVELOPMENT IN NIGERIA

2025-01-19T05:29:18+00:00

This paper reviewed suitable communication models that bring about the changes in farmers’ behavior and farming practices for increase in the social economic status and livelihoods of farm families. The main focus of agricultural extension includes transferring knowledge from researchers, advising farmers on decision-making and educating farm families on how to make accurate decisions which will enable them clarify goals and stimulate desirable agricultural development. Disseminating innovations and technologies through extension education using various communication models involves agricultural and non-agricultural issues in the immediate environment and so the wellbeing of inhabitants in a particular area should be considered when using communication models. Advantages and disadvantages of these models are highlighted to show the relevance of communication models in agricultural extension and advisory services. The study highlights the implications of communication models in communicating agricultural and non-agricultural issues to farmers which is pertinent to agricultural productivity. It is recommended that competent extension agents properly trained in Information Communication Technologies (ICTs) extension approaches and the appropriate communication models educate farmers. Extension agents should also work with more contact farmers in various communities to have result oriented extension service delivery in Nigeria.

ANTIBIOTIC RESISTANCE GENES IN FRESHWATER ENVIRONMENT: SOURCES, FATE, ECOLOGICAL IMPACT AND CLINICAL RELEVANCE

2025-01-19T05:29:19+00:00

Global public health is seriously threatened by antibiotic resistance, making the identification of environmental reservoirs of antibiotic resistance genes (ARGs) a crucial area of study. Freshwater ecosystems are particularly important for the spread of ARGs because of the intricate interactions between diverse microbial populations, human activities, and various antibiotic contamination sources. This review aims to offer a thorough understanding of the origin, progression, environmental impact, and medical significance of ARGs in freshwater environment. ARGs enter freshwater systems through various means, including the release of treated and untreated wastewater, agricultural drainage, and discharge of antibiotics and their byproducts. Once introduced, ARGs can endure freshwater environments through processes, such as horizontal gene transfer, co-selection, and biofilm formation. Moreover, the presence of ARGs in freshwater ecosystems has significant ecological consequences, affecting microbial diversity, ecosystem functions, and biogeochemical processes. The clinical relevance of ARGs in freshwater environments is a matter of concern. These genes can be transmitted to disease-causing bacteria, resulting in treatment failure and proliferation of infections that are resistant to multiple drugs. Additionally, the potential for ARGs to contaminate drinking water supplies raises concerns regarding human health. To develop effective strategies for combating the proliferation of antibiotic resistance, it is crucial to understand the behavior of ARGs in freshwater ecosystems. This review emphasizes the necessity of enhanced wastewater treatment technologies, responsible antibiotic usage, and sustainable farming practices to decrease the release and persistence of ARGs in freshwater ecosystems, ultimately protecting public health and maintaining the ecological balance of these vital habitats.

BLOCKCHAIN TECHNOLOGY FOR LAND REGISTRATION IN NIGERIA: A REVIEW OF OPPORTUNITIES AND CHALLENGES

2025-01-21T05:30:23+00:00

Land registration is critical for ensuring legal certainty and economic stability, yet Nigeria's system is plagued by inefficiencies, corruption, and inadequate technical infrastructure. These challenges result in prolonged processing times, high registration costs, insufficient technical skills, unqualified staff, excessive land charges, and an unclear legal framework. Additionally, institutional inefficiencies, ignorance among landowners regarding the importance of registration, multiple sales, unofficial charges, and lack of transparency exacerbate the problem. This study examines the potential of blockchain technology to address these systemic issues. Blockchain's decentralized and secure framework offers transformative potential by enhancing transparency, reducing fraud, and streamlining land registration processes. Drawing from global applications, the paper highlights blockchain's ability to create tamper-proof records, minimize human errors, and build public trust in land transactions. However, significant challenges to adoption in Nigeria include technical and infrastructural limitations, regulatory challenges, political resistance, and the need to train stakeholders. The study proposes a strategic framework focused on private permissioned blockchains, smart contracts, and integration with existing land records to ensure gradual implementation. Adopting blockchain could significantly reduce registration timelines, lower costs, improve transparency, and foster economic growth through a reliable and secure land tenure system. This research highlights blockchain's potential to modernize land administration in Nigeria while addressing critical challenges and enabling equitable access to land rights.

AN OVERVIEW OF KEY SAFETY CONCERNS AND SUSTAINABILITY OF CNG RETROFITTED VEHICLES IN NIGERIA

2025-01-21T05:30:24+00:00

Compressed natural gas (CNG) is increasingly being advocated and adopted as an alternative fuel for vehicles in Nigeria due to its economic and environmental benefits. However, the retrofitting of vehicles to use CNG has raised safety concerns, particularly in a country like Nigeria where regulatory standards, enforcement, and public awareness may not be fully developed. An assessment of the key safety and sustainability of retrofitted CNG vehicles (CNGVs) focusing on factors such as the quality and durability of conversion kits and tanks, proper installation procedures, CNG storage, and refuelling are considered. While CNG is generally safer than traditional fuels like gasoline and diesel—requiring higher ignition temperatures and presenting less fire risk during leaks, the fear of regulatory oversight, inadequate safety standards, and limited technical expertise in vehicle retrofitting may pose significant challenges. Stronger regulations, public awareness campaigns, and technician training programs are advocated to ensure safe CNGV operations in Nigeria.

MODELLING STUDENTS’ ACADEMIC PERFORMANCE AND PROGRESS: A DISCRETE-TIME MARKOV CHAIN APPROACH

2025-01-24T05:30:46+00:00

Predicting students' performance has become increasingly challenging due to the large volume of data in educational databases. Academic achievement reflects learning effectiveness and serves as a key indicator of teaching quality, institutional standards, and overall student development. Higher education systems operate hierarchically, with students progressing through academic levels annually or exiting as graduates or dropouts. Understanding and evaluating student progression is vital amidst evolving educational dynamics. This study models students’ academic performance and progression using a discrete-time Markov chain approach to predict future outcomes. Data on students’ enrollment and performance for five(5) sessions were collected from the Department of Statistics, Federal University of Technology, Minna. The Markov chain model was constructed for different academic levels and their absorbing states. Key metrics, including expected time spent at each level, absorption probabilities, and graduation or withdrawal likelihoods, were estimated. The findings show that 100-level entrants have an 80.5% chance of graduating and a 19.5% risk of withdrawal, with graduation likelihoods increasing with progression—reaching 99.4% at 500-level. The forecasts from the constructed Markov chain models showed that 100-level entrants are 99.4% likely to graduate after five sessions, 200-level entrants after three sessions, and 300-level entrants after one session. The study shows that while attrition rates are higher in the early stages, students advancing beyond the 200-level exhibit strong prospects for completion. These findings underscore the university’s effective programs and support systems, particularly in retaining and advancing students beyond the critical early stages.

MACHINE LEARNING-BASED FORECASTING OF BIOACCUMULATION AND HISTOPATHOLOGICAL EFFECTS IN AQUATIC ORGANISMS

2025-01-25T05:30:56+00:00

Heavy metal contamination in freshwater environments poses significant risks to aquatic organisms and human health, as these heavy metals enter freshwater systems through various sources, including industrial waste, agricultural runoff, mining and atmospheric deposition. Efforts to develop efficient methods for removing heavy metals from wastewater have gained momentum in recent years. This study focuses on machine learning (ML) models for predicting the bioaccumulation and histopathological effects of heavy metal pollutants on aquatic life under various climate change scenarios. The ML models have shown promise in forecasting the impacts of heavy metal pollution on freshwater ecosystems and informing conservation strategies. It is crucial to understand the complex interactions between environmental factors, climate change and ecosystem health. This study discusses the importance of incorporating diverse species and environmental factors in these models and acknowledges potential challenges, such as inaccuracies and data misinterpretation. Enhancing the predictive capabilities of ML models is essential for better environmental management and conservation practices via refinement and validation of models using updated data and advanced methodologies. This study also emphasizes the broad potential of ML in environmental research, improvement of model capabilities and challenges posed by heavy metal pollution and climate change.