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Effect of Biochar Type and Bradyrhizobium japonicum Seed Inoculation on Soybean growth, Nodulation and Yield in a Tropical Ferric Acrisol

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Agricultural Sciences 2024年第6期15卷 635-675页

作者： g.adebo monday elebiyo Robert Thomas Bachmann Department of Crop and Soil Sciences Kwame Nkrumah University of Science and Technology Kumasi Ghana Branch Campus Malaysian Institute of Chemical and Bio-Engineering Technology Green Chemistry and Sustainable Engineering Technology Cluster Universiti Kuala Lumpur Alor Gajah Malaysia

In tropical environments, most soybean growth studies have utilized rice husk biochar (RHB) in soil, even though it is low in nitrogen, potassium, and phosphorous. This may not give short-term agronomic performance relative to enriched biochar. Moreover, the impact of inoculating soybean seeds with atmospheric nitrogen-fixing bacterium Bradyrhizobium japonicum on nodulation and grain yield has produced inconclusive findings in the literature. This research therefore aims to assess the effect of poultry manure (PM), poultry manure biochar (PMB) and RHB alone and in combinations on grain yield, dry shoot and root biomass of soybeans in the semi-deciduous agro-ecological zone. In addition, the effect of B. japonicum inoculated and non-inoculated soybean seeds on nodulation and grain yield was also investigated. The treatments followed a split plot design studying inoculation and non-inoculation, soil amendments (eight), and control subplot factors, respectively. The results show that the amendment of a ferric acrisol with 4 Mg∙ha−1 PM, 10 Mg∙ha−1 RHB + 2 Mg∙ha−1 PM, and 5 Mg∙ha−1 RHB + 4 Mg∙ha−1 PMB with B. japonicum inoculated seed produced significantly greater grain yield (p = 0.05). PM treatment had a significant (p B. japonicum-inoculated soybean seeds significantly (p = 0.014) increased soybean nodulation. This study suggests that RHB combined with PM or PMB provides a beneficial source of N, P, and K, resulting in improved soybean yield and nodulation in a tropical ferric acrisol.

关键词： Biochar Poultry Manure Soil Fertility Soil Microorganism Soybean Production

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Machine Learning Models for Heterogenous Network Security Anomaly Detection

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Journal of Computer and Communications 2024年第6期12卷 38-58页

作者： Mercy Diligence Ogah Joe Essien Martin Ogharandukun monday Abdullahi Department of Computer Science Veritas University Abuja Nigeria Department of Pure and Applied Physics Veritas University Abuja Nigeria Department of Computer Science Air Force Institute of Technology Kaduna Nigeria

The increasing amount and intricacy of network traffic in the modern digital era have worsened the difficulty of identifying abnormal behaviours that may indicate potential security breaches or operational interruptions. Conventional detection approaches face challenges in keeping up with the ever-changing strategies of cyber-attacks, resulting in heightened susceptibility and significant harm to network infrastructures. In order to tackle this urgent issue, this project focused on developing an effective anomaly detection system that utilizes Machine Learning technology. The suggested model utilizes contemporary machine learning algorithms and frameworks to autonomously detect deviations from typical network behaviour. It promptly identifies anomalous activities that may indicate security breaches or performance difficulties. The solution entails a multi-faceted approach encompassing data collection, preprocessing, feature engineering, model training, and evaluation. By utilizing machine learning methods, the model is trained on a wide range of datasets that include both regular and abnormal network traffic patterns. This training ensures that the model can adapt to numerous scenarios. The main priority is to ensure that the system is functional and efficient, with a particular emphasis on reducing false positives to avoid unwanted alerts. Additionally, efforts are directed on improving anomaly detection accuracy so that the model can consistently distinguish between potentially harmful and benign activity. This project aims to greatly strengthen network security by addressing emerging cyber threats and improving their resilience and reliability.

关键词： Cyber-Security Network Anomaly Detection Machine Learning Random Forest Decision Tree gaussian Naive Bayes

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Application of Machine Learning for Flood Prediction and Evaluation in Southern Nigeria

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Atmospheric and Climate Sciences 2024年第3期14卷 299-316页

作者： Emeka Bright Ogbuene Chukwumeuche Ambrose Eze Obianuju getrude Aloh Andrew monday Oroke Damian Onuora Udegbunam Josiah Chukwuemeka Ogbuka Fred Emeka Achoru Vivian Amarachi Ozorme Obianuju Anwara Ikechukwu Chukwunonyelum Anthonia Nneka Nebo Obiageli Jacinta Okolo Centre for Environmental Management and Control (CEMAC) University of Nigeria Enugu Nigeria Department of geography Enugu State University of Science and Technology ESUT Enugu Nigeria School of Civil Engineering Newcastle University Newcastle upon Tyne UK

This study explored the application of machine learning techniques for flood prediction and analysis in southern Nigeria. Machine learning is an artificial intelligence technique that uses computer-based instructions to analyze and transform data into useful information to enable systems to make predictions. Traditional methods of flood prediction and analysis often fall short of providing accurate and timely information for effective disaster management. More so, numerical forecasting of flood disasters in the 19th century is not very accurate due to its inability to simplify complex atmospheric dynamics into simple equations. Here, we used Machine learning (ML) techniques including Random Forest (RF), Logistic Regression (LR), Naïve Bayes (NB), Support Vector Machine (SVM), and Neural Networks (NN) to model the complex physical processes that cause floods. The dataset contains 59 cases with the goal feature “Event-Type”, including 39 cases of floods and 20 cases of flood/rainstorms. Based on comparison of assessment metrics from models created using historical records, the result shows that NB performed better than all other techniques, followed by RF. The developed model can be used to predict the frequency of flood incidents. The majority of flood scenarios demonstrate that the event poses a significant risk to people’s lives. Therefore, each of the emergency response elements requires adequate knowledge of the flood incidences, continuous early warning service and accurate prediction model. This study can expand knowledge and research on flood predictive modeling in vulnerable areas to inform effective and sustainable contingency planning, policy, and management actions on flood disaster incidents, especially in other technologically underdeveloped settings.

关键词： Machine Learning Flood Prediction Evaluation Southern Nigeria

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Adsorption of Natural Surfactant on Sandstone in Enhanced Oil Recovery: Isotherms and Kinetics Studies

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Open Journal of Applied Sciences 2023年第7期13卷 1119-1144页

作者： monday Obekpa Michael Department of Petroleum Engineering Khazar University Baku Azerbaijan

In chemical enhanced oil recovery, surfactants are injected into the reservoir with the intention to lower interfacial tension (IFT) between the water and oil phases, and thereby bring about efficient displacement of oil. However, the adsorption of the surfactants to reservoir rock surfaces leads to the loss and reduction in concentration of the surfactants, which in turn reduces the overall efficiency of the oil recovery process, with attendant financial losses. In this work, the adsorption of Quillaja Saponaria (QS), a novel, natural, non-ionic surfactant, on crushed sandstone reservoir rock is investigated. X-ray diffraction (XRD) study of clean sandstone particles has been undertaken to determine the main components present in the sand particles. The conductivity method was used to measure CMC and the surfactant concentrations in aqueous solutions. Batch adsorption experiments were used to determine the amount of QS adsorbed on rock surface. Equilibrium conditions were reached after almost 5 days. From the results of the study, the Langmuir isotherm model is more suited for predicting the adsorption behaviour of QS on sandstone. The kinetic adsorption of QS obeys the pseudo-second order model. This study is particularly relevant in surfactant selection for chemical EOR processes.

关键词： Enhanced Oil Recovery Critical Micelle Concentration Interfacial Tension Adsorption Kinetics Surfactant Saponin

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Autonomous Unbiased Study group Formation Algorithm for Rapid Knowledge Propagation

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Computer Systems Science & Engineering 2022年第7期42卷 15-31页

作者： monday Eze Charles Okunbor Solomon Esomu Nneka Richard-Nnabu Kayode Oladapo Oghenetega Avwokuruaye Abisola Olayiwola Akpovi Ominike godwin Odulaja Oluwatobi Akinmerese Department of Computer Science Babcock UniversityOgunNigeria Department of Computer Science Admiralty UniversityDeltaNigeria Department of Computer Science National Open UniversityNigeria Department of Computer Science and Informatics Alex-Ekwueme Federal UniversityEbonyiNigeria Department of Cyber Security Admiralty UniversityDeltaNigeria Department of Computer Science Caleb UniversityImotaLagosNigeria Department of Computer Science and Information Technology Petroleum Training InstituteDeltaNigeria Department of Computer Science Tai Solarin University of EducationOgunNigeria

Knowledge propagation is a necessity,both in academics and in the *** focus of this work is on how to achieve rapid knowledge propaga-tion using collaborative study *** practice of knowledge sharing in study groupsﬁnds relevance in conferences,workshops,and class ***-nately,there appears to be only few researches on empirical best practices and techniques on study groups formation,especially for achieving rapid knowledge *** work bridges this gap by presenting a workﬂow driven compu-tational algorithm for autonomous and unbiased formation of study *** system workﬂow consists of a chronology of stages,each made of distinct *** of the most important steps,subsumed within the algorithmic stage,are the algorithms that resolve the decisional problem of number of study groups to be formed,as well as the most effective permutation of the study group participants to form collaborative *** work contributes a number of new algorithmic concepts,such as autonomous and unbiased matching,exhaustive multiplication technique,twisted round-robin transversal,equilibrium summation,among *** concept of autonomous and unbiased matching is centered on the constitution of study groups and pairs purely based on the participants’performances in an examination,rather than through any external *** part of practical demon-stration of this work,study group formation as well as unbiased pairing were fully demonstrated for a collaborative learning size of forty(40)participants,and partially for study groups of 50,60 and 80 *** quantitative proof of this work was done through the technique called equilibrium summation,as well as the calculation of inter-study group Pearson Correlation Coefﬁcients,which resulted in values higher than 0.9 in all *** life experimentation was carried out while teaching Object-Oriented Programming to forty(40)under-graduates between February and May *** result showed

关键词： Knowledge propagation collaborative study group unbiased matching twisted round robin exhaustive multiplication

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graphics Evolutionary Computations in Higher Order Parametric Bezier Curves

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Computer Systems Science & Engineering 2022年第5期41卷 595-609页

作者： monday Eze Charles Okunbor Deborah Aleburu Olubukola Adekola Ibrahim Ramon Nneka Richard-Nnabu Oghenetega Avwokuruaye Abisola Olayiwola Rume Yoro Esomu Solomon Department of Computer Science Babcock UniversityOgunNigeria Department of Computer Science Admiralty UniversityDeltaNigeria Department of Computer Science Caleb UniversityImotaLagosNigeria Department of Computer Science Education Federal College of Education(Tech)AkokaLagosNigeria Department of Computer Science Alex Ekwueme Federal UniversityEbonyiNigeria Department of Cyber Security Admiralty UniversityDeltaNigeria Department of Computer Science School of ICTDelta State PolytechnicOgwashi-UkuDeltaNigeria Department of Computer Science National Open UniversityNigeria

This work demonstrates in practical terms the evolutionary concepts and computational applications of Parametric *** cases were drawn from higher order parametric Bezier curves of degrees 2 and *** curves find real life applications in diverse areas of Engineering and Computer Science,such as computer graphics,robotics,animations,virtual reality,among *** of the evolutionary issues explored in this work are in the areas of parametric equations derivations,proof of related theorems,first and second order calculus related computations,among others.A Practical case is demonstrated using a graphical design,physical hand sketching,and programmatic implementation of two opposite-faced handless cups,all evolved using quadratic Bezier *** actual drawing was realized using web graphics canvas programming based on HTML 5 and *** work will no doubt find relevance in computational researches in the areas of graphics,web programming,automated theorem proofs,robotic motions,among others.

关键词： Parametric curve computer graphics bezier curve blending function robotics

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Psychological Issues among Women Undergoing Fertility Treatment in a Specialist Fertility Hospital, South East Nigeria

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Open Journal of Obstetrics and gynecology 2023年第4期13卷 681-692页

作者： Johnson Akuma Obuna monday Nwite Igwe Department of Obstetrics and gynaecology Ebonyi State University Abakaliki Nigeria National Obstetric Fistula Centre Abakaliki Nigeria Department of Psychological Medicine Ebonyi State University Abakaliki Nigeria Federal Neuropsychiatric Hospital Enugu Nigeria

Introduction: In Nigeria, a major reason for marriage is procreation and married couples look forward to having children within a year or two of marriage. The inability to achieve conception and subsequently have a child among couples may lead to psychological complications. Objective: This study assessed the psychological impact of infertility and its management on women receiving treatment at a Fertility Specialist Hospital in a poor resource setting. Methods: This was a cross-sectional study of 376 consenting married women who sought and received fertility treatment at a private Fertility Specialist Hospital, located at Abakaliki, South-East Nigeria between May 1, 2017 and May 31, 2022. Socio-demographic and Structured questionnaires were administered to the participants over a 5-year period. Results: The mean age of the women at presentation was 36.9 (±7.2 SD) years. The majority of the women (227) presented with secondary infertility accounting for 60.4%, while the rest had primary infertility (χ2 = 16.18, P = 0.001). Male-only factor infertility accounted for 22.9% of all the infertility cases, female-only factor 21.3% while both (male and female factors co-existing) accounted for 52.7% of all the cases. The commonest cause of infertility in the study was poor sperm parameters (176) accounting for 46.8% of cases, tubal factor 19.1% and anovulatory factor 22.3% (χ2 = 214.21, P = 0.001). Three hundred and thirty four (88.8%) felt depressed, 266 (70.7%) felt guilty about the past, and 222 (59.0%) had suicidal tendencies because of the infertility ordeal. Two hundred and fifty one (66.8%) felt inferior, 237 (63.0%) cried often and 174 (46.3%) were socially withdrawn. However, 10.4% of the women felt satisfied and well. These negative psychological feelings were statistically significant. Concerning the effect on marriage, the closeness of couples was reduced significantly in 57.7%, 62.8% had reduced coital intimacy, 79.3% had frequent quarrel

关键词： Infertility Psychological Issues Fertility Treatment Fertility Hospital Nigeria

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Discrete Event Simulation-Based Evaluation of a Single-Lane Synchronized Dual-Traffic Light Intersections

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Journal of Computer and Communications 2023年第10期11卷 82-100页

作者： Chimezie Calistus Ogharandukun Martin Abdullahi monday Essien Joe Department of Electrical/Electronic and Computer Engineering Veritas University Abuja Nigeria Department of Pure and Applied Physics Veritas University Abuja Nigeria Department of Computer Science Air Force Institute of Technology Kaduna Nigeria Department of Computer and Information Technology Veritas University Abuja Nigeria

This research involved an exploratory evaluation of the dynamics of vehicular traffic on a road network across two traffic light-controlled junctions. The study uses the case study of a one-kilometer road system modelled on Anylogic version 8.8.4. Anylogic is a multi-paradigm simulation tool that supports three main simulation methodologies: discrete event simulation, agent-based modeling, and system dynamics modeling. The system is used to evaluate the implication of stochastic time-based vehicle variables on the general efficiency of road use. Road use efficiency as reflected in this model is based on the percentage of entry vehicles to exit the model within a one-hour simulation period. The study deduced that for the model under review, an increase in entry point time delay has a domineering influence on the efficiency of road use far beyond any other consideration. This study therefore presents a novel approach that leverages Discrete Events Simulation to facilitate efficient road management with a focus on optimum road use efficiency. The study also determined that the inclusion of appropriate random parameters to reflect road use activities at critical event points in a simulation can help in the effective representation of authentic traffic models. The Anylogic simulation software leverages the Classic DEVS and Parallel DEVS formalisms to achieve these objectives.

关键词： Multi-Core Processing Distributed Computing Event-Driven Modelling Discrete Event Simulation Data Analysis and Visualization

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The new WHO guideline for control and elimination of human schistosomiasis:implications for the Schistosomiasis Elimination Programme in Nigeria

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Infectious Diseases of Poverty 2022年第5期11卷 87-89页

作者： Akinola Stephen Oluwole Uwem Friday Ekpo Obiageli Josephine Nebe Nse Michael Akpan Solomon monday Jacob Uche Veronica Amazigo John Russell Stothard Department of Pure and Applied Zoology Federal University of AgricultureAbeokutaOgun StateNigeria Neglected Tropical Disease Control Division Department of Public HealthFederal Ministry of HealthAbujaNigeria Pan-African Community Initiative on Education and Health(PACIEH) EnuguNigeria Department of Tropical Disease Biology Liverpool School of Tropical MedicineLiverpool L35QAUK.

Background With some 134,073,166 people living in endemic communities at risk of infection[1],Nigeria is the most endemic country in Africa and requires preventive chemotherapy(PC)for a total of 26.3 million persons[2].The National Schistosomiasis Elimination Programme(NSCHEP),with the support of international partners,has been implementing PC in Nigeria since 2009 and most recently will need to revise its current strategy(Additional file 1).For example,the new World Health Organization(WHO)guideline has six key recommendations that will dramatically change the implementation of schistosomiasis elimination in endemic countries[3].However,its impact and programmatic implications will vary from country to country,hence the need for a country-specific analysis.

关键词： schistosomiasis Schistosomiasis Nigeria

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gender Perspectives of Vulnerability to Climate Change: A Descriptive Evidence from Farming Households at Ikpayongo Community in gwer Lga, Benue State, Nigeria

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American Journal of Climate Change 2023年第1期12卷 116-139页

作者： monday Akpegi Onah Elizabeth Jeiyol Odeh Adimanyi Chiviter Ukange Department of geography Benue State University Makurdi Nigeria gender and Environmental Risk Reduction Initiative (gERI) Makurdi Nigeria

Climate change impact and risks on agricultural livelihood affect women and men disproportionately and often to the disadvantage of women and girls. Consequently, this study assessed gender perspectives of vulnerability to climate change of farming households at Ikpayongo community in gwer local government area, Benue State, Nigeria using descriptive approach. The study identified a total of 120 male-headed and female-headed farming households across four neighbourhoods and administered structured questionnaire on them using simple random sampling method, while data analysis was done using descriptive statistics. The results indicate lower education and income status among female-headed households, though male-headed households have high household size. Both sexes have relatively equal access to land for farming, however men have large farm size compared to women. The major crops cultivated by men were rice and yam, while women cultivated largely groundnut and cassava. Women are more exposed and sensitive to climate-related hazards such as floods and heat stress due to the location of their farms. The result further shows that males possess better adaptive capacity given their higher incomes, social networks and more access to training/capacity building programmes and credit facilities. The study concludes that female-headed farming households are more vulnerable to climate change and variability than male-headed farming households due to higher exposure and a lower adaptive capacity. Programme and policies to improve women access to credit facilities and relevant training to boost their adaptive capacity and build resilience are highly recommended. This would also limit exposure with attendant reduction in vulnerability.

关键词： Climate Change gender Farming Households Vulnerability Adaptive Capacity

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