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An analysis of farmers-herdsmen conflict and the resolution mechanisms in Benue State, Nigeria.
No full textThe study examines the causes of conflicts between farmers and herdsmen in Benue State. It also assesses the various steps taken to resolve the conflict. The study notes that farmers-herdsmen conflict has long historical roots that span through the pre-colonial and colonial to the post-colonial times. It is qualitative in nature and relies on qualitative data to evaluate the causes and consequences of the conflict. The study discovered that farmers-herdsmen conflict is caused by overgrazing, destruction of farm crops, killing of herdsmen cattle, climate change, environmental degradation, resource scarcity and identity discrimination among others. The study uses environmental/resource scarcity theory and identity construction theory to explain the causes of farmers-herdsmen conflict and dual concern theory to underscore its resolution. Drawing lessons from the various factors that escalates farmers-herdsmen conflict and its social, economic, political, and humanitarian consequences on vulnerable groups in Benue State, the study concludes that farmers and herdsmen have been exposed to humanitarian and socio-economic consequences that affected their individual well-being. The frequent escalation of conflict between farmers and herdsmen reflects the failure of traditional, conventional and dual concern approaches to resolving the conflict. My study recommends the need to promote inclusiveness in citizenship culture, compensation and dialogue between farmers and herdsmen as pathways to strengthening the relationship between farmers and herdsmen in Benue State, Nigeria
Sentiment analysis of electronic word of mouth (E-WoM) on e-learning.
Get PDFThe proliferation of social media and the internet has given people many opportunities to air their views and to be at liberty to say what they feel without hindrance. This is beneficial to commercial organizations and the general well-being of the populace. However, the cost of this freedom is that spamming is practiced with little or no control. This chapter focuses on the electronic word of mouth (eWOM) of opinion holders and the sentiments expressed in eWOM. One of the areas of life impacted by sentiment is electronic learning because it has become a prevalent mode of learning. The study aims to analyze eWOM on e-learning which can help in identifying learners' sentiments. Findings from three thousand tweets show more neutral sentiments, followed by positive sentiments. Suggestions and recommendations as well as the future directions for sentiment analysis of eWOM on e-learning are also discussed in this chapter
Trust declarations and creditor protection in insolvency: lessons from Wade and Anor v Singh and Ors.
Get PDFThe High Court case Amanda Wade and Nicholas Nicholson (Joint Liquidators of Msd Cash and Carry Plc (In Liquidation)) v Mohinder Singh, Surjit Singh Deol, Raminder Kaur Deol, the Estate of Bakshish Kaur (Deceased) ('Wade and Anor v Singh and Ors') examined the validity of a Declaration of Trust and enforcement of charging orders in a corporate insolvency. Involving a property owned by family members of a liquidated company, the case explored the intersection of trust law, property rights and creditor protection. The court invalidated the Declaration as an attempt to defraud creditors under the Insolvency Act 1986. This case emphasises the importance of clear intent in trust declarations and reinforces creditor rights protection in insolvency proceedings. The case underscores the need for specialist legal advice in property and trust matters, particularly when creditor claims may arise
Wear-resistant and stable low-friction nanodiamond composite superhard coatings against Al2O3 counter-body in dry condition.
Get PDFConventional machining lubricants pose environmental hazards and increase production costs. This study addresses this challenge by investigating nanodiamond composite (NDC) coatings deposited on WC–Co substrates as a lubricant-free alternative for sustainable machining. The NDC films show superior hardness (65 GPa) compared to the substrate (22 GPa) and enhanced adhesion (HF2). The NDC's unique self-lubrication results in a low and stable friction coefficient (COF ≤ 0.095) and exceptional wear resistance (7.45 x 10−8 mm3/N·m) in dry tesing against Al2O3 counter-body. Compared to CVD diamond, NDC coatings show a 47.8 % reduction in COF and a 31.65 % enhancement in wear resistance, promoting environmentally friendly machining practices
Assessing the research scene of green AI via bibliometric analysis.
No full textThe environmental impact of artificial intelligence (AI) continues to rise as more people embrace the technology. The optimization of AI models to be more efficient, use less energy, and emit low carbon is essential. This bibliometric study presents an overview of literature published on Green AI research worldwide, with a particular focus on Africa. This study investigates the current state of research on Green AI, to learn about the most influential contributors, institutions, countries, journal outlets, and partnerships in Green AI research, and to assess their influence. Bibliometric information for the analysis was retrieved from the Web of Science database. Over 385 articles from 2016 to 2024 were obtained and analyzed with the aid of Microsoft Excel and VOSviewer, a bibliometric visualization network tool. The results showed that there has been a growth in Green AI research since the year 2020. A closer look at the data showed that the USA outperformed all other countries in terms of research output and collaboration. The dominant themes recorded in the study include energy efficiency, carbon footprint reduction, and the development of sustainable AI models. The results are noteworthy for the academic community because they provide current and emerging trends in Green AI research
Embedding sustainable development goals (SDGs) into the curricula using an interdisciplinary design thinking approach.
Get PDFEmbedding sustainability into curricula has been a challenge many universities have been facing for a while. The nature of the topic could be classified as "dry" when taught through a legislative lens, but a creative, impactful method is required to enhance student engagement. One approach developed at a Scottish university is via the use of Design Thinking pedagogy in the context of a Collaborative Online International Learning (COIL) hybrid workshop, where fashion management students and fashion and textile design students from the Scottish university partnered virtually with fashion students from Cape Peninsula University of Technology (CPUT). This case study will demonstrate the power of bringing together students from other cultures and slightly different disciplines (with one being management-based and the other being practice-based) to successfully demonstrate the use of an innovative method of delivery, which enhances students' Sustainable Development Goals (SDGs) knowledge with impact
Towards the underwater internet of things for subsea oil and gas monitoring.
No full textThe oil and gas industry (O&G) is at the forefront of significant social change as the world aligns itself with the 2050 Net Zero agenda. The Underwater Internet of Things (UIoT) will inevitably be part of this process across a broad range of applications from monitoring pollutant emissions to enabling proactive maintenance of pipelines through robotics. The goal of this survey is to discuss the current and future technologies of UIoT regarding communications, networking, sensing and computational technologies and how it will address challenges that the O&G is facing. Firstly, a brief discussion on subsea assets is carried out. After, the propagation and physical characteristics of common underwater communications technologies are discussed in depth and how they relate to effective transmission of data. Additionally, this discussion of communication is followed by another on networking through analysis of the three layers of the protocol stack most affected by the change in transmission media, the physical, datalink and network layers. After this discussion, an example investigation is presented on a simulated network to support O&G UIoT with a proceeding introduction to the available simulation tools for designing subsea networks. then, research challenges of the UIoT in the O&G are identified. Finally, the trends in UIoT research are discussed regarding their relevance to O&G as well as concluding remarks
Collaborative Online International Learning (COIL) for sustainable development. [Dataset]
No full textThis questionnaire aims to gather insights and experiences from students participating in a COIL project. The focus is on understanding cross-cultural collaboration, knowledge of sustainable building materials, and the impact of the project on participants' learning
An ethnobotanical survey and pharmacological and toxicity review of medicinal plants used in the management of obesity in the North Central Zone of Nigeria.
Get PDFObesity is increasing worldwide. Due to the unavailability of affordable obesity drugs in most parts of Nigeria, many overweight and obese people rely on medicinal plants to manage obesity. Thus, the aim of this study is to document medicinal plants traditionally used in the treatment and management of obesity in the North Central Zone of Nigeria, determine the plants to which pharmacological assessment of their use in obesity management has not been reported, and assess their toxicity based on the literature. Semistructured questionnaires and interviews were used to assess sociodemographic information of the 700 herb sellers/practitioners (100 for each state) who consented to participate in the study. Information gathered on plants that are traditionally used in the management of obesity included administration/dosage, method of preparation, plant part used, method of growth, and plant type. The field study was conducted over a one-year period, from March 2018 to March 2019. Reports of pharmacological activity pertaining to obesity as well as toxicity of the plants were obtained from the literature via scientific databases (Scopus, Web of Science, PubMed, Google Scholar, SciFinder, AJOL, PubChem, and other web sources) after the field survey. A total of 39 families and 70 plant species were used to treat or manage obesity. The majority of plant species used resulted in the family Leguminosae. The relative frequency of citation (RFC) and percentage values for the five most frequently used plants were as follows: Citrus aurantifolia (0.0500; 3.56%), Citrus limon (0.0457; 3.26%), Garcinia kola (0.0429; 3.05%), Zingiber officinale (0.0429; 3.05%), and Allium sativum (0.0414; 2.95%). The majority of the medications were prepared as decoctions (50.5%), and cultivated plants (62.86%) were in the majority of plants used. Results showed that 23 plants have no pharmacological report for antiobesity activities while among the five frequently used plants, only Garcinia kola was reported toxic in preclinical models. This paper provides a valuable compilation of the plants used in obesity treatment in the study area by indigenous healers, highlights plants with no reported pharmacological activity pertaining to obesity, and indicates the toxicity profile of used plants. However, further studies on the mechanism of action are warranted, especially where no reports were obtained
Towards explainable metaheuristics: feature mining of search trajectories through principal component projection.
Get PDFWhile population-based metaheuristics have proven useful for refining and improving explainable AI systems, they are seldom the focus of explanatory approaches themselves. This stems from their inherently stochastic, population-driven searches, which complicate the use of standard explainability techniques. In this paper, we present a method to identify which decision variables have the greatest impact during an algorithm's trajectory from random initialization to convergence. We apply Principal Component Analysis to project each population onto a lower-dimensional space, then introduce two metrics—Mean Variable Contribution and Proportion of Aligned Variables—to identify the variables most responsible for guiding the search. Using four different population-based methods (Particle Swarm Optimisation, Genetic Algorithm, Differential Evolution, and Covariance Matrix Adaptation Evolution Strategy) on 24 BBOB benchmark functions in 10 dimensions, we find that these metrics highlight meaningful variable relationships and provide a window into each method's search dynamics. By comparing the features extracted across algorithms and problems, we illustrate how certain variable subsets consistently drive major improvements in solution quality. In doing so, new evolutionary algorithm variants can be designed to take advantage of these influential variables, while also identifying underutilised variables that may benefit alternative search strategies
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