FUDMA JOURNAL OF SCIENCES

A COMPARATIVE STUDY OF STENCIL-BASED METHOD OF LINES FOR SOLVING THE BURGERS-HUXLEY EQUATION

2025-07-20T16:43:10+00:00

MATHEMATICAL AND STATISTICAL COMPUTATION OF OPTION PRICING USING THE BLACK-SCHOLES EQUATION

2025-07-20T16:43:10+00:00

This study focuses on the numerical solution of the Black-Scholes model, a key framework in financial mathematics for pricing European-style options. The model describes the behavior of option prices in relation to asset price, volatility, interest rate, and time to maturity. While exact analytical solutions exist for simple cases, numerical methods offer greater adaptability for real-world applications. In this work, we implement an explicit finite difference scheme to approximate the solution of the Black-Scholes partial differential equation. A stability criterion is derived to ensure numerical reliability, and accuracy is measured using the L1-norm by comparing results with the analytical solution. MATLAB simulations are used to compute the price of a European call option with a strike price of $100, a 12% risk-free interest rate, 10% volatility, and a one-year maturity. The generated graph (Figure 1) illustrates how the option value increases as the stock price moves from $70 to $130, notably rising when it exceeds the strike price. A comparative study with a semi-implicit scheme from existing literature confirms the enhanced precision of our explicit approach. These findings demonstrate the accuracy, efficiency, and practical utility of the explicit finite difference method for solving the Black-Scholes model.

EVALUATION OF ELECTRONIC BASED VOTING SYSTEM AND DESIGN OF BLOCK-CHAIN-BASED ELECTRONIC VOTING SYSTEM ENHANCED WITH FINGERPRINT AND FACIAL RECOGNITION TECHNOLOGIES TO ADDRESS IMPERSONATION

2025-07-20T16:43:11+00:00

This study introduces a blockchain-based electronic voting system enhanced with fingerprint and facial recognition to address persistent challenges such as fraud, impersonation, and lack of transparency in electoral processes. Centered on Nigeria's electoral context and supported by data from the 2024 Edo State gubernatorial election, the system utilizes blockchain’s decentralized and tamper-proof ledger for secure vote recording, while multimodal biometrics ensure real-time, accurate voter authentication. Using SWOT analysis and IBM SPSS for statistical evaluation, the framework demonstrates improved security, transparency, and operational efficiency compared to conventional systems. Despite existing challenges related to infrastructure, biometric variability, and data privacy, the model presents a scalable, future-ready solution that can reinforce democratic legitimacy and restore public trust in elections. The findings contribute to advancing research in e-governance, secure computing, and electoral reform, advocating for technology-driven policy changes in emerging democracies.

BREEDING SITES CHARACTERISTICS AND MOSQUITO ABUNDANCE IN SOME SELECTED LOCATIONS WITHIN JIMETA METROPOLIS

2025-07-20T16:43:12+00:00

Samples of water in the service of mosquito’s breeding, in the tropical region supports their resting, swarming and mating activities. Samples were collected from breeding sites within some selected locations from January to June. One thousand, six hundred and twenty-two (1622) mosquito larvae belonging to 3 genera, Anopheles, Culex, and Aedes were collected and seven species of mosquitoes were identified comprising; Culex quinquefasciatus 410 (25.28%), Aedes aegypti 972(48.83%), Culex decens 42 (2.71%), Aedes vittatus 105 (6.56%), Culex tarsalis 44(2.71%), Culex pipiens 30 (1.85%) and Anopheles gambiae 19(1.17%). Aedes aegypti was common in all the locations. Water samples were collected from seven different major breeding sites such as clocked drainage 154(50.82%), abundant tyres 51(16.39%), Rice farms 45 (12.03%), Pools 19 (5.08%) ponds 42(11.23%), Plastic containers 44 (11.76%), and Metallic containers 19 (5.08%) totaling 374 sampled breeding sites. Out of the 374 selected sites, 251 sites were found positive for different species of mosquito larvae. Correlation analysis showed abundance of mosquitoes decreased with increase in physicochemical parameters. In conclusion, the Aedes aegypti was the most prevalent and present in all the breeding sites with the exception of rice fields; while the physico-chemical parameters were all within the favourable limits for mosquito breeding.

EFFECT OF AQUEOUS CRUDE EXTRACT OF TIGER NUT (CYPERUS ESCULENTUS) ON PENILE ERECTION-RELATED BIOCHEMICAL PARAMETERS IN MALE WISTAR RATS

2025-07-20T16:43:13+00:00

There is an increase in the cases of erectile dysfunction and the remedies so far are not without side effects thus, this study is aimed at investigating the influence of aqueous crude extract of tiger nut (Cyperus esculentus) on some important biochemical indices involved in penile erection in male Wistar albino rats. Twenty-four adult male Wistar rats were divided into four (4) groups of five (5) rats each. One group (control) received distilled water, the other groups received 250, 500 and 1000 mg/kg of C. esculentus aqueous crude extract respectively for fourteen (14) days. Administration was done orally (once daily) with the aid of a gavage. At the end of the experimental period, blood samples were collected through the abdominal aorta into plain sample containers to obtain serum for biochemical analysis. Nitric oxide (NO), sex hormones, fasting blood glucose, lipid profile, serum liver enzymes (ALT and AST) and haematological parameters were assayed using standard methods. Body weight of the animals and organs (testis and kidney) were also monitored at intervals of seven (7) days after basal value had been taken. The results showed significant (p<0.05) reduction in body weight in the second week at 500 mg/kg in relation to basal values. Significant decrease and increase were observed in the weight of kidney and testes respectively in some of the groups when compared with the control group. Significant increase was observed in NO levels in the testes. Follicle stimulating hormone and testosterone increased in a non-dose dependent manner. With the exception...

VIRTUAL PROTOTYPING AND IMPLEMENTATION OF A DIGITAL MONITORING SYSTEM FOR FISH DRYING PARAMETERS

2025-07-20T16:43:13+00:00

Heat and moisture transfer occur simultaneously during the fish drying process. Continuous monitoring is necessary to ensure high quality fish drying. In this study, a digital system was designed to monitor parameters (Temperature (-400C±0.50C to 800C±0.50C), Relative Humidity (0 to 100%RH ±2%RH) and smoke concentration (200ppm to 5000ppm)) in the fish drying process in a dryer. A system engineering design approach with the use of Computer Aided Design (CAD) tools was used to establish the basic layout of the different sections of the system using Arduino UNO (based on ATmega328P), sensors, a Liquid Crystal Display (LCD), a micro SD card module and an alarm system. These components were integrated as an embedded system through the use of a compiler; Arduino integrated development environment (Arduino 1.8.7) and Proteus designer suit (Proteus 8.1 professional). The testing was done on the dryer for about 7Hours and 35minutes by monitoring the drying parameters. The results obtained showed that the virtual system modeler software provided a complete embedded digital laboratory for the simulation and implementation of the fish digital monitoring system. The microcontroller drawn is also able to accept, and execute the code produced with Arduino IDE connected to Proteus designer suit. The developed system works effectively in monitoring the drying parameters inside the drying chamber of a fish dryer with the ability to displayed, stored and retrieved the data for future use.

A FRAMEWORK FOR REAL-TIME DATA-DRIVEN DECISION MAKING IN NIGERIAN PUBLIC BASIC SCHOOL SYSTEM

2025-07-20T16:43:14+00:00

This study presents a comprehensive examination of an innovative framework designed to transform data collection and analysis processes within Nigeria's public basic education system through the implementation of real-time Education Management Information Systems (EMIS). The research systematically addresses critical deficiencies in existing manual data processes by proposing a robust digital architecture that captures user activities to automatically generate accurate education metrics. Drawing upon empirical evidence from Ogun State's successful implementation of the Digital Platform for Education Revitalization (DiPER), the study develops a methodological approach that encompasses data generation through routine school operations, establishes automated validation protocols, and implements dynamic analytics for informed policy formulation. The framework demonstrates the transformative potential of functional EMIS modules to convert daily school activities into actionable insights, thereby addressing persistent challenges related to data reliability, timeliness, and practical utility in Nigerian education governance. Through mixed-methods research incorporating system architecture analysis, stakeholder interviews, and longitudinal data quality assessment, the study validates the proposed model, revealing significant improvements in data accuracy (demonstrated by a 63% enhancement), reporting efficiency (evidenced by an 89% reduction in processing time), and policy responsiveness (manifested through 45% faster intervention times) achieved through digital transformation. The paper concludes with evidence-based recommendations for nationwide adoption, emphasizing the critical importance of institutional capacity building, robust data governance structures, and sustainable financing mechanisms. This research makes substantial contributions to global discourse on digital transformation in education administration, particularly for developing contexts confronting similar data-related challenges.

ETHANOL LEAF EXTRACT OF FICUS EXASPERATA ATTENUATES CHANGES IN ELECTROLYTES AND LIPID PROFILES IN A RAT MODEL OF OLANZAPINE-INDUCED OBESITY

2025-07-20T16:43:15+00:00

Obesity is a major public health concern characterized by excessive body fat, which increases the risk of numerous health conditions, including heart disease, diabetes, high blood pressure, and certain cancers. Addressing obesity is crucial for improving overall health and well-being. In this study, thirty female Wistar rats, weighing between 190 and 200 g, were utilized to investigate the effects of Ficus exasperata on olanzapine-induced obesity. After a two-week acclimatization period, obesity was induced in the designated group using olanzapine (4 mg/kg) via oral gavage for 28 days. The rats were then divided into five groups (n = 6): normal control, obese-untreated, non-obese treated with Ficus exasperata (100 mg/kg), obese treated with Ficus exasperata (100 mg/kg), and obese treated with orlistat (100 mg/kg). Treatments were administered orally for 28 days. At the end of the study, the animals were sacrificed, and blood samples were collected for serum analysis. The study demonstrated that Ficus exasperata significantly (P< 0.05) increases bicarbonate and potassium while reducing sodium and calcium (P< 0.05). Ficus exasperata significantly (P< 0.05) reduces HDL with a significant (P< 0.05) increase in TC, TG and LDL. These findings suggest that Ficus exasperata influences both electrolyte balance and lipid metabolism in obese animals.

THERAPEUTIC EFFICACY OF ALLIUM SATIVUM AGAINST SLEEP DEPRIVATION-INDUCED DYSLIPIDEMIA IN ADULT FEMALE WISTAR RATS

2025-07-20T16:43:16+00:00

Sleep deprivation (SD) resulting from unhealthy lifestyle choices poses oxidative challenges and is strongly linked to an increased risk and prevalence of various metabolic disorders. While the negative effects of SD on mental health are well documented, its impact on lipid metabolism remains less explored. Allium sativum (Garlic) has been recognized for its cardioprotective properties in different preclinical models. This study aimed to investigate the cumulative effects of acute SD on lipid metabolism and assess the potential therapeutic benefits of aqueous A. sativum extract using female Wistar rats as the experimental model. The animals (N = 25) were categorized into five groups of five animals each (n = 5): Group I served as the normal control and was administered distilled water (1ml/kg), whereas Group II represented the negative control (sleep-deprived, untreated). Groups III, IV, and V received oral administration of A. sativum extract at doses of 100, 200, and 400 mg/kg, respectively, over three weeks. The study analyzed plasma lipid profiles following treatment and found significant reductions in total cholesterol (T. CHOL), triglycerides (TG), and low-density lipoprotein (LDL) across most treated groups. In contrast, high-density lipoprotein (HDL) levels increased, particularly in treated groups compared to Group II. The decrease in TG and LDL was statistically significant (P 0.05), while HDL showed a notable rise. These results suggest that Allium sativum extract may help regulate lipid metabolism and offer protective benefits against cardiovascular diseases and atherosclerosis. However, the limitation of the study is that the acute SD model may...

MITIGATING PULSE DISTORTION IN OPTICAL FIBERS USING DIGITAL BACKPROPAGATION AND DISPERSION MANAGEMENT

2025-07-20T16:43:17+00:00

This research investigates the propagation effects of optical pulses traveling through fiber links, focusing on phase modulation, nonlinear phase change, and pulse broadening. We analyze these phenomena to enhance the performance of optical communication systems by evaluating key metrics such as nonlinear phase change (in degrees, o) and pulse broadening ratio over propagation distances. Our findings underscore the significant role of nonlinearities in pulse distortion and assess the effectiveness of Digital Backpropagation (DBP) and optimal dispersion techniques in mitigating these impairments. Simulation results demonstrate that DBP is more effective than optimal dispersion management, reducing nonlinear phase change by maintaining it at 15o up to 80 km, compared to optimal dispersion management, which stabilized it to 34o after the initial peaks before the interaction length, defined as the distance over which nonlinear effects manifest. Similarly, DBP achieves complete suppression of pulse broadening, maintaining the ratio at 1:1 up to 80 km. In contrast, optimal dispersion management only achieves lowering the ratio to 40:1. These findings highlight that DBP has superior capability in mitigating both nonlinear phase change and linear pulse broadening, significantly enhancing signal fidelity over long distances and offering valuable insights for the design and optimization of next-generation optical networks.

GROWTH PERFORMANCE AND CARCASS YIELD OF HELMETED GUINEA FOWL (NUMIDA MELEAGRIS) MALE KEETS RAISED IN DIFFERENT HOUSING SYSTEMS OF A TROPICAL ENVIRONMENT

2025-07-20T16:43:18+00:00

This study evaluated the growth performance and carcass yield of male helmeted guinea fowl (Numida meleagris) keets raised under three housing systems: deep litter, battery cage, and deep litter, which run in a tropical environment. The objective was to assess the influence of housing on bird productivity and carcass characteristics to inform best practices for sustainable guinea fowl production. Two hundred sixteen eight-week-old male keets were randomly distributed across the housing systems in a Completely Randomized Design, with feed and water provided ad libitum for 16 weeks. Growth performance was measured weekly, while carcass and gastrointestinal traits were evaluated post-slaughter. Data were analyzed using Analysis of Variance (ANOVA), and significant means were separated using Duncan’s Multiple Range Test at a 5% significance level. Results showed significant differences (p < 0.05) in feed intake and some carcass parameters among housing systems. Deep litter with run birds exhibited a superior dressing percentage (74.25%) and higher ether extract content in thigh meat (5.02%). In contrast, battery cage birds showed higher drumstick meat percentage and crude protein levels. The housing system significantly influenced oesophagus length and selected gastrointestinal segments. It is concluded that deep litter with run offers a favourable environment for improved carcass traits and may enhance nutrient deposition in meat, suggesting it is a viable system in tropical settings. These findings contribute to the knowledge of guinea fowl production and recommend further investigation into the interactive effects of housing and environmental variables on performance outcomes.

ECTO AND ENDOPARASITES OF BATS IN SELECTED AREAS OF LAFIA METROPOLIS, NASARAWA STATE, NIGERIA

2025-07-20T16:43:19+00:00

Bats harbor parasites, increasing disease surveillance. Between November 2022 and January 2023, a survey in Lafia metropolis employed mist nets over 12 nights across six areas to assess bats ecto and endoparasites prevalence. Two hundred and nineteen bats were trapped, belonging to five species: Tadarida brasiliensis (139), Eidolon helvum (32), Afronycteris nanus (16), Scotophilus leucogaster (16), and Rhinolophus lander (16). Ectoparasites comprising four genera: Ixodes, Thaumapsylla, Nycteribia and Demodex; and endoparasites belonging to three groups: Nematodes, Protozoans and Cestodes) showed an overall prevalence (3.65%) and (10.04%) respectively. Locations based prevalence of ecto and endoparasites revealed Phase II recorded the highest prevalence (37.5%), with a significant difference (X² = 0, df = 5, p < 0.001) and Mararaba had the highest prevalence (31.18%), with a very high variation (X² = 36.358, df = 5, p < 0.0001). Prevalence of Ectoparasites, and endoparasites in relation to sex was higher in females (62.5%) than in males (37.5%) with significant difference (X² = 6.25, df = 1, p = 0.01242) and higher in males (63.64%) than in females (36.36%) varied significantly (X² = 7.442, df = 1, p < 0.006372). Ectoparasites of bats in relation to species revealed E. helvum recorded the highest prevalence (50%), with a significant difference (X² = 103.12, df = 4, p < 0.0001), for endoparasites, T. brasiliensis had the highest distribution (50%), with a significant difference (X² = 71.503, df = 4, p < 0.0001). Further research across the state is needed for a better understanding of bats parasites.

ASSESSMENT OF AQUIFER PROTECTIVE CAPACITY AND SOIL CORROSIVITY IN UMUNEDE, DELTA STATE, USING DEPTH PROBING RESISTIVITY INVERSION

2025-07-20T16:43:20+00:00

The protective potential and soil corrosivity of the Umunede village in Ika North East, Delta State, was assessed and the study area has been categorized recently among the oil producing towns in the distinct Niger Delta. Ten (10) Vertical Electric Soundings (VES) were sounded and the areas with low or poor (< 0.1 mho), range of moderate (0.2-0.69 mho) and also good (0.7-4.9 mho) protective capacities were identified by evaluating and ascertaining the area's longitudinal conductance. Aquifers in most areas are shielded (prevented) from oil spills in the event of pollution, according to the study, which rates the protective ability (capacity) of the majority of the just discovered oil community as good and moderate. Conversely, areas with identified weak or poor protection capability (capacity) are vulnerable to groundwater taint (contamination) from observed surface spills and also from other nearby sources. VES data indicates soil corrosivity levels, with mild to moderate corrosivity risking pipeline failure. Environmental management initiatives are needed for storm-proofing and protecting the community's aquifer system. This study simplifies the location and distribution of subsurface aquifers, aiding in exploration projects planning for groundwater-producing wells in the study region.

CORROSION INHIBITION EFFECT OF BALANITE AEGYPTIACA LEAVES EXTRACT ON MILD STEEL IN 5M H2SO4 A GRAVIMETRIC AND THERMOMETRIC STUDY

2025-07-20T16:43:20+00:00

The corrosion inhibition effect of Balanites aegyptiaca leaves extract on mild steel in 5 M sulphuric acid solution has been investigated using gravimetric study and thermometric technique at 40 oC, 50 oC, and 60 oC.

The main aimed of this research is to investigate the potential of Balanite aegyptiaca leaves powder for corrosion inhibitition. The Balanite aegyptiaca fresh leaves was obtained from itas Gadau local government Bauchi and the leaves sample was washed and shade dried for two weeks under room temperature The concentration of the inhibition 0.01, 0.02, 0.03 and 0.04 g/L was prepared and used at temperature of 313 K, 323 K, and 333 K respectively. The inhibition efficiency was found to be highest at 313 K and 0.04 g/l concentration of the extract with IE of 18.48 % and lowest at 333 K and 0.01 g/l concentration with IE of 16.42 %. Therefore the Inhibition efficiency increases with extract concentration but decreases with temperature. The thermodynamic parameters and results from the FTIR (shift from 1208 cm-1 to 1205 cm-1 and 1618 cm-1 to 1611 cm-1 and appearance of new 1016 cm-1, 1676 cm-1, 1834 cm-1, 3905 cm-1 bands,” etc) revealed the adsorption of the inhibitor molecules on mild steel surface as comprehensive adsorption involving physical and chemical adsorption. Results show that Balanites aegyptiaca which is biodegradable, environmentally, and are obtained from a renewable resource with minimal health and safety concerns has the potential to a cost-effective alternative to synthetic corrosion inhibitors

A FRAMEWORK FOR DEVELOPING SMART SOCIAL MEDIA PLATFORMS

2025-07-20T16:43:21+00:00

Social media networks have revolutionized the activities of this age. Larger populations are using social media for education, exchange of ideas, business, marketing, fun, games, commerce and so on. However, there exists a fundamental challenge in this media, which is, the identity insincerity and theft. Users of social media create so many accounts for themselves and use these accounts for frauds. Some use other people information like names, pictures and profile to create multiple accounts for their dubious benefits. This has posed many fears on user not to believe in most media engagements. Connecting and communicating to some people in other locations of the world comes with a lot of doubt, fears and difficulties in exchanging business and expertise ideas which is one of the hallmarks of the social media. In dealing with these challenges, this paper has presented a framework for deploying smart social media platforms for enhanced information security and eliminating multiple opening/using of social media platform by same individual for fraudulent activities. This framework was developed using Object Oriented Methodology and C# was used to implement the prototype platform. Visual Studio was used as the IDE for the developed platform. The platform output shows its viability in preventing multiple account creation by users. The platform performance is shown in the implementation output of the system whereby the system will prevent the creating of multiple accounts and the use of other people information in creating a new account.

DETERMINATION OF POLYCYCLIC AROMATIC HYDROCARBONS AND VOLATILE ORGANIC COMPOUNDS IN SURFACE SOILS OF MECHANIC WORKSHOPS IN AZARE BAUCHI STATE, NIGERIA

2025-07-20T16:43:22+00:00

The study aimed was to determine the organic pollutants in mechanic workshop garages in Azare, Bauchi state, Nigeria. Soil samples were collected after two weeks in a month for three months, making two replicates from three (3) popular auto mechanic workshops using a hand auger. At each location, the surface soil samples was randomly collected from the same depth of 0 – 20 cm to form composite samples. Soil samples are dried to remove moisture, followed by sieving to remove debris the size of the mesh used 2 mm. the soil sample are typically oven dried at 105 oC for a period usually 16-24 hours. The GC-MS concentration of benzene, toluene, ethyl benzene, m,p xylene and o-xylene in site 1, was found to be 12.1±0.31, 9.5±0.02, 8.2±0.02, 7.5±0.01, 6.9±0.01, respectively. Which all are above WHO permissible limits that ranging from 0.01-0.20. Where the mean values of naphthalene, phenanthrene, Anthracene, fluoranthene, and pyrene in site 2, was found to be 6.2±0.01, 5.1±0.01, 5.5±0.01, 4.1±0.1and 3.9±0.01 respectively. Which all are above USEPA limits that ranging from 0.01-0.100. Where the mean values of decane, undecane, dodecane, tridecane, pentadecane in site 3, was found to be 21.9±2.00, 18.5±1.59, 15.2±1.50, 12.9±1.20, 10.5±1.00, respectively which all are above WHO permissible limit that ranging from 0.02-0.07. The GC-MS analysis of three different soil samples from the mechanic garages contained various organic pollutants, including VOCs, PAHs, and aliphatic hydrocarbons. The results highlight the need for proper waste disposal that become crucial for protecting both human health...

HIGH SALT DIET REDUCES OVARIAN, UTERINE WEIGHT, AND FERTILITY INDEX IN FEMALE WISTAR RATS

2025-07-20T16:43:23+00:00

Female reproductive health is highly sensitive to hormonal and environmental factors, and diet is a significant modifiable factor influencing reproductive outcomes. This study aimed to investigate the impact of high-salt diets on the weight and size of the uterus and ovaries in female albino Wistar rats. Forty-four (44) female albino Wistar rats weighing between 200 and 250 g were randomly assigned to four groups comprising 11 albino Wistar rats each. The designated control group was fed with a non-high salt diet ad libitum; the other groups were fed 2.5 %, 3.5 %, and 4.5 % NaCl diets, respectively. All albino Wistar rats in groups 2, 3, and 4 were fed the experimental diet for 6 weeks. The male albino Wistar rats were housed separately before mating and allowed access to rat chow and water. The study showed that a high salt diet resulted in a significant decrease in the weight of the ovaries, the weight of the uterus and the fertility index. These findings show the importance of dietary regulation in preserving reproductive function and mitigating the adverse effects of metabolic disturbances. Thus, a high salt diet could be detrimental to the female reproductive system.

IoT-BASED TELEMEDICINE SYSTEM TO ADDRESS HEALTHCARE ACCESS CHALLENGES IN NIGERIA

2025-07-20T16:43:24+00:00

The Internet of Things (IoT) integrates sensors, software, and connectivity to enable real-time data exchange between devices and systems, playing a transformative role in modern telemedicine. This study presents an IoT-based telemedicine system developed to address healthcare access challenges in Nigeria, especially in rural and underserved areas. The system includes an Android mobile application that uses the smartphone’s camera to capture pulse readings, enabling preliminary assessment of patients' cardiac health. In parallel, a web-based administrative platform allows healthcare administrators to register medical practitioners, assign doctors to patients, schedule consultations, and manage cloud-based patient records. To protect sensitive health data, the system implements the Advanced Encryption Standard (AES) for secure data encryption and decryption. Developed using Flutter SDK, Dart programming language, Visual Studio Code, and Firebase, the application—referred to as the Rim360 Health App—demonstrates how IoT can facilitate real-time, encrypted patient monitoring and doctor-patient interaction. The system holds potential to significantly enhance telemedicine adoption in Nigeria by providing accessible, secure, and scalable healthcare solutions for remote populations.

EFFECT OF DRYING ON THE NUTRITIONAL AND ANTI-NUTRITIONAL COMPOSITION OF SWEET AND BITTER CASSAVA

2025-07-20T16:43:24+00:00

This study investigates the effect of drying on the nutritional and anti-nutritional composition of sweet and bitter cassava (Manihot esculenta). Using standard AOAC methods, four sample types—sweet and bitter cassava in both fresh and dried forms—were analyzed for proximate composition, mineral content, and anti-nutritional factors. The results showed that drying significantly (p < 0.05) reduced moisture (by 69.2% in sweet cassava and 67.4% in bitter cassava), hydrogen cyanide (by 34.9% in sweet cassava and 26.2% in bitter cassava), and oxalate levels (by 23.9% in sweet cassava and 20.6% in bitter cassava), while increasing carbohydrates (by 13.3% in sweet cassava and 14.9% in bitter cassava) and lipids (by 74.4% in sweet cassava and 72.6% in bitter cassava). The reduction in hydrogen cyanide and oxalate was more pronounced in the bitter variety. The reduction in hydrogen cyanide and oxalate was more pronounced in the bitter variety (p<0.05). The hydrogen cyanide reduces from 129.10 ± 6.00 Mg/100g, to 95.30 ± 6.10 Mg/100g and oxalate 79.43 ± 3.41 Mg/100g to 63.03 ± 2.14 Mg/100g in fresh and dried samples respectively. These findings emphasize the importance of drying as a processing method to enhance the safety and nutrient density of cassava consumed in Nigeria.

INFLUENCE OF SOIL PHYSICAL PROPERTIES ON SOIL LOSS DUE TO YAM HARVESTED ON A SANDY LOAM SOIL IN IWO, OSUN STATE, NIGERIA

2025-07-20T16:43:25+00:00

Soil loss due to crop harvesting (SLCH) has been established as an important soil erosion process that has contributed to soil degradation in many countries of the world. However, the quantification of SLCH, particularly concerning yam tubers, remains unstudied globally, despite yam being a crucial staple food in Nigeria. This research examines how soil physical properties affect soil loss during yam harvesting on sandy loam soil in Iwo, Osun State, Nigeria. Manual harvesting of yam tubers was conducted, measuring both their weight and the soil attached to them. The study analyzed the impact of soil properties such as aggregate stability, available water content, bulk density, and texture on soil loss. Results indicated sand content (671.00 g/kg), a bulk density of 1.30 g/cm³, saturated hydraulic conductivity of 7.37 cm/hr, and a moisture content of 15.70%. The infiltration rate averaged 12.5 units in 11 minutes. Manual mound tillage produced the highest soil loss (160.00 kg/ha/harvest), while Zai pit tillage resulted in the least (75.60 kg/ha/harvest). The study highlights the importance of adopting effective soil conservation practices and suggests developing yam harvesters that replicate the hand rubbing technique to reduce soil loss.

CHRONIC KIDNEY DISEASE PREDICTION MODEL USING BAYESIAN OPTIMIZATION AND XGBOOST MACHINE LEARNING ALGORITHM

2025-07-20T16:43:26+00:00

Chronic Kidney Disease or CKD is a global concern that continues to flourish and affect the wellbeing of people and systems across the world. It is defined by the gradual loss of kidney functionality that leads to important issues like cardiovascular disease, renal failure, and increased death rates. Previous researchers has concentrated towards the development of machine learning algorithms Random Forest, K Nearest Neighbour algorithm, Decision Tree and Deep Neural Network for CKD prediction, but higher prediction accuracy and model interpretability has not been achieved. Although some researchers have attempted to shed light on Kidney Disease prediction, the prophecy of Chronic Kidney Disease remains unsolved. For this reason, the main objective of this paper is to integrating some other machine learning algorithms like XGboost along with bayesian optimization for hyper parameter tuning of xgboost and improve CKD prediction along with a large feature set and strong non-linear dependencies within the data. The research derived a dataset from a sonograph showing a hospital from Karaikudi, Tamil Nadu from India. The dataset has 400 samples where 250 samples are positive for CKD and 150 samples are negative. This approach builds upon the previous work of Arumugham et al. (2023) who achieved a remarkable accuracy of 98.75% when using a deep neural network (DNN) model. The findings of this research offer insight into the use of advanced machine learning methods for the better prediction and management of chronic kidney disease.

EVALUATION OF THE EFFICIENCY OF AZADIRACHTA INDICA (NEEM) LEAF POWDER AND ITS ACTIVATED CARBON IN THE ADSORPTION OF BENZENE AND TOLUENE FROM SIMULATED REFINERY WASTE WATER

2025-07-20T16:43:26+00:00

This study assessed the efficiency of Azadirachta indica (Neem) leaf powder (NLP) and its activated carbon (NLAC) as potential adsorbents for the extraction of benzene and toluene from simulated refinery wastewater. The objective is to evaluate the capacity of these materials to enhance the quality of industrial effluents and assist developing nations in attaining the Sustainable Development Goals (SDGs), specifically Goal 6 (Clean water and Sanitation), Goal 12 (Responsible Consumption and Production), and Goal 15 (Life on Land). Azadirachta indica leaf powder and its activated carbon were prepared by air-drying Azadirachta indica leaf in the shade at room temperature (25 °C) for 72 hr, followed by oven drying at 105 °C for 30 min until they were crisp, and chemical activation with phosphoric acid. The adsorbents were assessed by Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR), and Brunauer-Emmett-Teller (BET) analysis. The FTIR analysis identified the functional groups in the adsorbent that are accountable for the adsorption property. The surface presents a fibrous composition including irregular macropores and enlarged cavities that may facilitate the diffusion of adsorbate molecules through the macropores. The batch adsorption process was studied under numerous conditions, encompassing varying concentrations, pH, contact time, adsorbent amount, and temperature. The findings indicated that activated carbon derived from Neem leaf, possessing a surface area of 427.154 m²/g, exhibited substantial adsorption of benzene and toluene, attaining removal efficiency of 74 % and 81 % respectively, under optimal conditions of (pH 10, contact time 75 min, adsorbent dosage 1 g,...

THE ECONOMETRIC IMPACT OF PETROLEUM SUBSIDY REMOVAL ON THE NIGERIAN ECONOMY

2025-07-20T16:43:27+00:00

The removal of petroleum subsidies in Nigeria has sparked considerable debate, with proponents highlighting potential economic gains and critics warning of adverse effects on key economic indicators. This study aims to assess the impact of subsidy removal on major macroeconomic variables, including inflation, GDP growth, government revenue, and fiscal deficit, using econometric techniques. Time-series data from 2000 to 2024 was analysed through regression models to evaluate the causal relationship between subsidy removal and these economic indicators. The findings reveal a positive and significant relationship between subsidy removal and government revenue, with an increase of approximately 112.45 billion NGN, and a reduction in the fiscal deficit by about 5.23 billion NGN. However, the analysis also indicates an initial inflationary spike of 3.56 percentage points and a short-term contraction in GDP growth. In the long term, GDP growth recovers, driven by more efficient resource allocation. These results offer important insights for policymakers, suggesting that while subsidy removal can foster fiscal consolidation, it must be carefully managed to mitigate short-term negative impacts on inflation and economic growth.

EFFECTS OF ORGANO-MINERAL FERTILIZERS ON GROWTH AND YIELD OF FOUR UPLAND RICE CULTIVARS IN TWO LOCATIONS IN TARABA STATE, NIGERIA

2025-07-20T16:43:28+00:00

Field experiments were conducted to evaluate the effects of different rates of organo-mineral fertilizers on the growth and yield of selected rice cultivars at two locations: the Teaching and Research Farm of Taraba State University, Jalingo, and Karim Lamido area of Taraba State, North-East Nigeria, during the 2024 cropping season. The experiment used a factorial (2×4×4) arrangement in a Randomised Complete Block Design (RCBD) with three replications. Treatments comprised four upland rice varieties (Faro 44, Faro 58, Faro 59, and local CP) and four fertilizer regimes: 20 t/ha cow dung (organic, OF), 300 kg/ha N.P.K 20:10:10 (inorganic, IF), a 50% cow dung + 50% N.P.K mixture (MX), and an unfertilized control (CT), resulting in 16 treatment combinations. Each plot measured 3 m × 1.5 m with 20 stands, and seedlings were transplanted at 30 cm × 30 cm spacing. Data were collected on tiller number, leaf area, 1000-seed weight, and grain yield. Results showed location significantly (P<0.05) influenced tiller number and yield: Karim Lamido recorded higher tiller numbers (2.7–10.7) and 26.9% greater 1000-seed weight than Jalingo. The highest grain yield (14.19 t/ha) was obtained with 20 t/ha cow dung at Karim Lamido, followed by the 50% mixture (12.26 t/ha), both significantly outperforming the control (8.11 t/ha). Similar yield trends were observed in Jalingo. Overall, the 20 t/ha organic fertilizer and 50% mixture produced comparable yields at both sites. Therefore, applying a 50% organic and 50% inorganic fertilizer blend is recommended to enhance rice yield in the study areas.

EFFECT OF TEMPERATURE VARIATIONS ON CONDENSATE DROPOUT AND PHASE BEHAVIOR IN GAS CONDENSATE RESERVOIRS

2025-07-20T16:43:29+00:00

Gas condensate reservoirs exhibit complex thermodynamic and phase behavior, where variations in temperature significantly impact condensate dropout and overall hydrocarbon recovery. In these reservoirs, as pressure drops below the dew point, liquid condensate forms in the porous medium, reducing gas relative permeability and impairing well deliverability. Temperature changes influence phase equilibrium, interfacial tension, fluid viscosity, and retrograde condensation, making it essential to incorporate thermal effects in reservoir management and simulation models. This study presents a comprehensive analysis of the impact of temperature variations on condensate dropout and phase behavior using a combination of experimental PVT (Pressure-Volume-Temperature) analysis, numerical simulations, and thermodynamic modeling. The study integrates thermodynamic principles, phase behavior modeling, and reservoir simulation to analyze the effects of temperature fluctuations, particularly due to Joule-Thomson cooling and geothermal gradients, on reservoir performance. Results indicate that temperature variations play a critical role in condensate dropout, fluid distribution, and recovery efficiency. The findings provide valuable insights into optimizing production strategies and mitigating challenges such as condensate blockage in gas condensate reservoirs. This research highlights the importance of incorporating thermal effects in reservoir modeling and offers practical solutions for improving hydrocarbon recovery in gas condensate systems.

EVALUATION OF VIBRATION MAGNITUDE FROM STAGGERED DRILLED HOLE PATTERNS IN A LIMESTONE MINE, OKPELLA, EDO STATE, NIGERIA

2025-07-20T20:25:38+00:00

The evaluation of vibration magnitude created by a staggered drilled holes pattern in a limestone quarry in Okpella, Edo State, Nigeria was investigated. The SLAM STICK X rendered the time spectrum into frequency spectrum which is then converted into velocity to determine the sites constants which are related to the rock geological factor. The generated equation from the site constants is a guide for blasters when using staggered drilled holes pattern in limestone quarry. The study established the specific site constants (k and B) as 721.6 and -1.52 respectively for vibration generated in Okpella limestone mine to predict blast-induced vibration and safe distance. A predictive model developed for the studied quarry based on these constants, gave a safe distance of 102 meter when an explosive weight of 420 kg was exploded. The values generated from the equation generated from the model was compared with the Australian Standards to decide the weight to be used and distance between shot point and observation point to determine the safety of structures.

MITIGATING CLASS IMBALANCE IN TUBERCULOSIS DETECTION: COMBINING SMOTE AND TOMEK LINK WITH MODIFIED FOCAL LOSS AND CLASS WEIGHTING IN A TRANSFER LEARNING FRAMEWORK

2025-07-20T21:13:22+00:00

Tuberculosis (TB) remains a major global health concern, and early detection is crucial for effective treatment. This study addresses the challenge of class imbalance in existing machine learning models for TB prediction, which often leads to biased results. A novel approach combining the hybrid SMOTE-Tomek Links technique, modified focal loss, and class weighting was developed and applied to a dataset of X-ray images categorized into normal and TB classes. The hybrid SMOTE-Tomek Links method generates synthetic samples for the minority class while removing ambiguous samples, ensuring a balanced dataset. The modified focal loss and class weighting help focus on misclassified cases and address class disparities. The model was evaluated against benchmark models, including EfficientNetB3, Random Forest, and XGBoost, with and without SMOTE. The developed model achieved a remarkable accuracy of 99.7%, outperforming the benchmark models (92.72%–99.1%). These results demonstrate the effectiveness of the proposed approach in improving TB prediction accuracy and handling class imbalance. The study's findings provide valuable insights into medical image classification and offer a robust framework for enhancing diagnostic tools, with potential applications beyond TB detection. This research could significantly improve TB management and diagnosis in clinical settings.

PHYSICOCHEMICAL PROPERTIES OF REFINED SOYBEAN OIL AND DEODORIZER DISTILLATE AS BIODIESEL FEEDSTOCKS

2025-07-20T21:47:09+00:00

Biodiesel is an eco-friendly fuel that possesses the right qualities as a renewable source of energy including excellent lubricity, high flash point and biodegradability and this mainly depends on the raw material used. Hence, the physicochemical properties of refined soybean oil and soybean oil deodorizer distillate were determined to compare the most suitable for biodiesel production. The physicochemical parameters of the two oils which include: acid, iodine, saponification, free fatty acid and peroxide value, were determined by the official standard method of the Association of Official Analytical Chemists. The results revealed free fatty acid, peroxide, acid, iodine, and saponification content of soybean oil deodorizer distillate to be: 47.70±1.00 mg KOH/g, 248.55±0.89 meq O2/kg, 115.69±0.85 mg KOH/g, 5.58±0.51 g I2/100 g, and 64.95±0.65 mg KOH/g. While that of refined soybean oil showed the content to be 0.63±0.11 mg KOH/g, 4.08±1.02 meq O2/kg, 10.33±1.53 mg KOH/g, 11.58±0.38 g I2/100 g, and 34.70±1.00 mg KOH/g. These results indicate the free fatty acid, peroxide, acid and saponification content of soybean oil deodorizer distillate to be higher compared to refined soybean oil which suggests that it may require further pretreatment prior to transesterification. Although no transesterification reactions were conducted in this research, the high FFA Content and the origin of soybean oil deodorizer distillate as a byproduct of oil refining suggest its potential as a cost-effective and sustainable feedstock for biodiesel production, particularly within a waste valorization framework.

APPLICATION OF ELZAKI TRANSFORM TO THE ANALYTICAL SOLUTION OF STIFF LINEAR SYSTEMS OF ORDINARY DIFFERENTIAL EQUATIONS

2025-07-20T22:32:14+00:00

Stiff systems of ordinary differential equations (ODEs) are often difficult to solve because of their rapid changes and sensitivity to small variations in conditions. This study explores how the Elzaki transform can be used solve these types of equations analytically, offering an alternative to the traditional matrix method, which usually involves complex operations or exponentiation. By applying the Elzaki transform to the stiff system ODEs, we were able to find exact solutions and compare them with those from the matrix method. The outcome showed that both methods produce the same results, but the Elzaki transform approach is simpler and requires less computation. Elzaki transform proves to be a reliable and efficient method for solving stiff linear ODEs, especially in cases where traditional methods become too complicated or unstable. The Elzaki transform is a relatively new integral transform that is still not widely known, nor used.

FORENSIC ENTOMOTOXICOLOGICAL EVALUATION OF CARRION INSECTS FOUND ON PIGS EUTHANIZED WITH SNIPER INSECTICIDE DICHLORVOS IN IBADAN

2025-07-20T23:04:39+00:00

Dichlorvos is a commonly used suicide agent in Nigeria that needs to be forensically evaluated. A forensic entomotoxicological evaluation of carrion insects found on pigs euthanized with sniper insecticide was carried out at the far backend of the University of Ibadan. Two domestic pigs, Sus scrofa weighing 5.2kg and 10kg were used as surrogate human models for the study. One of the pigs was euthanized with 0.157ml/kg of sniper insecticide while the other was sacrificed without poison and used as the control experiment. Arthropods were collected from the decomposing carrions using a sweep net and were preserved in 70% ethanol for identification. Larvae and pupae were also collected and preserved in 70% ethanol. The families of arthropods namely; Calliphoridae, Muscidae and Dermestidae were found, while five species namely; Chrysomya albiceps, Chrysomya megacephala, Lucilia sericata, Dermestes maculatus and Musca domestica were found. The succession pattern and abundance of the carrion insects, effects of poison and environmental variables such as temperature and humidity on them were studied. The family Calliphoridae were the most abundant and the first to colonize the decomposing carrion. The Calliphoridae had 103 individuals followed by the Muscidae with 17 individuals and the Dermestidae with 4 individuals. It was observed from this study that carrion insects are very important in the decomposition of pig carcass. It was also observed that these insects are of forensic importance and can be used in forensic investigations since pigs are biologically similar to humans, this can be linked to solving human crime cases

IN VITRO ANTIOXIDANT AND ANTIVENOM ACTIVITIES OF AQUEOUS AND CHITOSAN-ENCAPSULATED TAMARINDUS INDICA SEED EXTRACTS AGAINST NAJA NIGRICOLLIS VENOM

2025-07-20T23:24:26+00:00

Snake envenomation is a neglected tropical disease responsible for thousands of mortalities and morbidities annually. Naja nigricollis is one of the venomous snakes of most importance in Nigeria. The enzymatic component of its venom has been associated with devastating complications following envenomation. Hence, this study aimed to evaluate the in vitro antioxidant and antivenom activities of aqueous crude extract and chitosan-encapsulated extract of Tamarindus indica seed. In vitro antioxidant assays; DPPH radical and ferric reducing power assays as well in vitro antivenom activities; phospholipase A2 and proteinases inhibition assays were determined using standard methods. The extracts showed significant DPPH radical-scavenging activities and ferric-reducing powers. However, the encapsulated extract exhibited higher activities with IC50 values of 19.62 µg/mL and 3.67 µg/mL against DPPH radical and FRAP, respectively than crude extract with IC50 values of 33.27 µg/mL and 17.56 µg/mL, respectively. Further, the extracts exerted significant inhibitory effects against the venom enzymes, with the encapsulated extract showing higher inhibitory effects. The IC50 values of the encapsulated extract against the enzymes were 34.58 µg/mL and 45.53 µg/mL against phospholipase A2 and proteinases, respectively, while free extract had IC50 values of 47.42 µg/mL and 62.01 µg/mL, respectively. This is the first study evaluating antivenom potential of chitosan-encapsulated T. indica seed against N. nigricollis. The encapsulated extract showed potential antivenom activities and could serve as a drug lead for the production of herbal therapy against Naja nigricollis venom in order to address antivenom limitations.

TOWARDS SUSTAINABLE SOLAR ENERGY STORAGE: A PATENT ANALYSIS FOR IMPROVING ENERGY DENSITY, CYCLE DURABILITY AND RATE CAPACITY FOR HYBRID LITHIUM-ION BATTERY (LiFePO4)

2025-07-22T02:57:47+00:00

The adoption of renewable energy is accelerating globally in wind and solar energy generation, solar energy particularly provides the promising outlook, its availability and flexibility of use makes it the most acceptable energy source required to achieve high perceptions of intermittent renewable energy. Despite this, solar energy storage capacity is currently underutilized in terms of minutes to hours of output at full power capacity. Although, research efforts and resource planning have begun to forecast on large-scale solar energy storage for a long duration, none has achieved a larger power capacity for a long duration. To this end, we explored the essentials of long-duration energy storage systems by analysing energy density, cycle durability and capacity rating for Hybrid Lithium-ion Battery (LiFePO4). In doing so, major components of potential long-duration storage values and their sensitivity to key parameters were assessed and the resulting indicators compared. The study showed a fast response time with improved energy density leading to a relatively high efficiency of about 42% as compare to the standard roundtrip efficiency of 45%. Cycle durability was highly influenced by depth of discharge (DoD), leading to a relatively short 3.5-hour lifetime for charge management, which is common when considering typical battery behaviour. Thus, strategies identified to improve Li-ion batteries: finding alternative electrode materials to improve energy density, decrease the environmental and societal impact of the raw materials, implementing self-healing mechanisms to improve cycle lifetime, and improving the efficiency to decrease costs.

CRUDE OIL DEGRADATION POTENTIAL BY HYDROCARBON-UTILIZING MICROBES: A REVIEW

2025-07-20T16:43:30+00:00

Globally, environmental pollution by crude oil is one of the most frequently encountered problem faced by the world today as a result of industrial activities, oil spill, and accidental occurrence, among others. Primarily, crude oil are composed of hydrocarbons, which are molecules composed of only carbon and hydrogen atoms. This review aim to present the indispensable role played by hydrocarbon-utilizing microorganisms in the degradation of crude oil, thereby reducing their pollution in the environment. The degradation of hydrocarbon is a complex action primarily mediated by microorganisms that utilize hydrocarbons as carbon sources via employing series of enzymatic pathways to break down these otherwise persistent environmental pollutants. Beyond enzymatic actions, biofilm formation and biosurfactants production are among the mechanisms used in these crude oil degradation. Microorganisms, including Penicillium, Nocardia, Aspergillus, Corynebacterium, Pseudomonas and Bacillus species are among the most frequently reported microorganisms capable of degrading crude oil pollutants. Several factors which influences these microbial action such as pH, inhibitors, nutrients availability, moisture and temperature always limits these degradation process. As reported by many scholars, bioremediation of crude oil by utilizing hydrocarbon degrading microorganisms has now been employed due to their inexpensive and non-toxic nature. Thus, bioremediation of crude oil by the usage of hydrocarbon-utilizing microorganisms represents a wonderful approach for decreasing the environmental impact of crude oil. Therefore parameters such as temperature, nutrient levels and pH should be optimized to enhance biodegradation efficiency.

APPLICATION OF ARTIFICIAL INTELLIGENCE IN MOBILE HEALTH CARE APPLICATIONS: A SCOPING REVIEW

2025-07-20T16:43:30+00:00

The integration of artificial intelligence (AI) with mobile health (mHealth) applications has transformed the healthcare landscape by offering early disease detection, accessible, real-time, and personalized medical support. This review examines the current state and trends of AI-powered mobile health applications, examining their implementation across various medical domains such as mental health, chronic disease management, visual impairment, stroke rehabilitation, and fitness. A comprehensive analysis of peer-reviewed literature from 2015 to 2025 was conducted, focusing on the types of AI algorithms used, their target applications, and overall effectiveness. The findings reveal an increasing trend in scholarly interest, particularly in journal publications, reflecting the demand for validated and reliable AI health solutions. Neural networks and deep learning models dominate the algorithmic landscape due to their effectiveness in handling complex and unstructured health data. This study highlights the growing reception and potential of AI-integrated mHealth apps to revolutionize personal healthcare and surface the way for more intelligent, user-centric solutions.

UNIT PROBABILITY DISTRIBUTIONS: A COMPREHENSIVE REVIEW OF MODELS, PROPERTIES, AND APPLICATIONS

2025-07-20T16:43:31+00:00

Unit probability distributions defined on the standard interval (0, 1) serve as foundational tools for modeling data constrained within this bounded domain. Such data frequently emerge in disciplines where proportions, rates, and probabilities are analyzed, including economics, finance, hydrology, environmental sciences, biomedical research, and reliability engineering. Traditional models such as the Beta and Kumaraswamy distributions have long provided flexible frameworks for these applications. However, the increasing complexity of real-world phenomena has spurred the development of more versatile and specialized unit distributions. This article presents a comprehensive review of the literature on unit probability distributions, encompassing both classical models and recent innovations. Emphasis is placed on transformation techniques used to generate new families, key analytical properties, and a comparative evaluation of estimation methods. A diverse array of real-world applications is examined, highlighting the practical relevance and empirical performance of modern unit distributions across multiple domains. By synthesizing these developments, the review offers a structured resource to support further methodological advancement and informed model selection for bounded data analysis.

PALYNOFACIES ANALYSIS OF PSA-1 WELL SEDIMENTS, NIGER DELTA BASIN: IMPLICATIONS FOR PALEOENVIRONMENTAL RECONSTRUCTION

2025-07-20T16:43:32+00:00

The Niger Delta basin is an important geological region of economic significance, serving as a critical oil and gas exploration area. Hence, there is a need to comprehend the geological history and environmental changes within the basin. Detailed palynofacies analyses, which provide crucial insights into paleoenvironmental conditions and organic matter preservation, are limited in the onshore depobelt. This study addresses this gap by focusing on a detailed palynofacies analysis of the PSA-1 well. Palynofacies analysis was carried out on ninety ditch-cutting samples from the PSA-1 well, located in the onshore Niger Delta Basin, to delineate the paleoenvironment of deposition across depths from 3520–6160ft. Standard acid maceration and microscopic examination were utilized; 200 palynomaceral counts were made per slide to determine the abundance and size fractions of each group. Four lithofacies units were identified through physical examination and textural characteristics, namely: shaly sandstone, clayey sandstone, mudrock, and shale facies. The palynofacies assemblage is quantitatively dominated by medium and small-sized fractions of Palynomaceral-1 (PM1) and Palynomaceral-2 (PM2), moderate amount of Palynomaceral-4 (PM4) with lesser amounts of Palynomaceral-3 (PM3). Moderate records of Structureless Organic Matter (SOM) was also observed. The consistent high percentage of phytoclasts PM1, PM2 and low to moderate percentage of amorphous organic matter (AOM) established a predominantly proximal depositional setting, suggesting a Terrestrial-Brackish swamp environment characterized by fluctuating energy conditions, such as a shifting deltaic or estuarine system.This study contributes to the depositional framework and organic matter distribution within the onshore Niger Delta and beyond.

MACHINE LEARNING APPLICATIONS IN EXOPLANET DETECION: FROM KEPLER TO TESS

2025-07-20T20:07:42+00:00

The detection and classification of exoplanets have undergone a paradigm shift with the advent of space missions like Kepler and TESS, which generate vast volumes of photometric time-series data. Traditional detection techniques, while foundational, struggle with scalability and sensitivity in the face of increased data complexity. This review synthesizes advancements in machine learning (ML) methods applied to exoplanet detection between 2007 and 2023, focusing on data from the Kepler and TESS missions. Key findings reveal that ML models particularly 2D convolutional neural networks (CNNs) applied to phase-folded light curves achieve superior performance (accuracy: 93–98%, AUC: 0.97 for Kepler) compared to traditional pipelines, though mission-specific noise (e.g., TESS’s shorter baselines) degrades performance (AUC: 0.85). Hybrid approaches combining synthetic and real data improve generalizability, while ensemble methods mitigate false positives from stellar variability (e.g., flares). However, challenges persist in interpretability, reproducibility, and cross-mission adaptability. Recommendations include: (1) Standardized benchmarks for ML model evaluation across missions, (2) Integration of noise-invariant architectures (e.g., attention mechanisms) for future surveys like PLATO, and (3) Ethical frameworks to ensure transparency in automated discovery pipelines. ML’s transformative potential is clear, but its integration requires addressing these gaps to fully leverage upcoming exoplanet surveys.

A QUANTILE REGRESSION ANALYSIS OF THE RELATIONSHIP BETWEEN DEMOGRAPHIC FACTORS AND AGE DISTRIBUTION AMONG HIV/AIDS PATIENTS IN JOS, PLATEAU STATE

2025-07-20T22:07:32+00:00

Human Immunodeficiency Virus (HIV) remains a major public health concern in sub-Saharan Africa, with demographic factors influencing both vulnerability and disease progression. This study employs a quantile regression framework to explore how age interacts with gender, educational attainment, marital status, and employment status among HIV-positive patients in Jos, Plateau State, Nigeria. We conducted a retrospective cross-sectional analysis of 667 available patient records from local treatment centres, fitting quantile regression models at the 25th, 50th, 75th, and 90th percentiles ( = 0.25, 0.50, 0.75, 0.90) using R (v4.3.2). Descriptive statistics indicated a right-skewed age distribution (mean = 33.0 years; skewness = 2.28). Normality tests (KolmogorovSmirnov, ShapiroWilk) confirmed significant departures from normality across most subgroups, justifying the quantile approach. Results revealed that female gender is significantly associated with younger age at diagnosis at the 25th75th percentiles (p < 0.01), whereas lower educational status becomes a significant risk factor at the 50th90th percentiles (p < 0.001). In contrast, marital status and employment status exhibited no significant associations with age across any quantiles. These findings show the disproportionate vulnerability of young women (approximately ages 2640) and less-educated adults to HIV infection. Recommendations include gender-targeted prevention strategies, particularly a comprehensive sexual education and empowerment initiatives for young women and broader application of quantile regression methods in epidemiological research to capture distributional heterogeneity.