Asian Journal of Advanced Research and Reports
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Exploration of Priestia flexa for the Biosynthesis of Polyhydroxybutyrate (PHB) and Comprehensive Evaluation of its Biodegradation Potential under Different Environmental Conditions
No full textBiodegradable alternatives are required due to the increasing environmental impact of synthetic polymers. Although production costs and yields limit its industrial use, polyhydroxybutyrate (PHB), a microbial polyester with thermoplastic and biocompatible qualities, is a viable possibility. In this study, resilient PHB-producing bacteria were isolated from industrial soils, the biodegradation capability of PHB was assessed, and cultural conditions were optimized for improved PHB synthesis. Soil samples from the industrial region of Goraguntepalya, Bangalore, were processed via serial dilution, yielding four isolates. PHB 2 showed the largest intracellular concentration among the two PHB-positive strains found by Sudan Black B staining. 16S rRNA sequencing, morphological analysis, and biochemistry all confirmed that PHB 2 was Priestia flexa (GenBank accession: OR462711.1). 1.13 g of PHB per 300 mL of broth was the greatest amount of PHB that could be produced using the following conditions: 48 hours of incubation, pH 7.0, 35 °C, 0.5% NaCl, 1% sucrose, and 1% peptone. The typical absorption peak at 250 nm in UV-visible spectroscopy verified PHB. Biodegradation assays demonstrated weight loss of 0.08% after 5 days in rhizosphere soil, confirming PHB’s microbial degradability. These results highlight P. flexa as a promising bioplastic producer with potential for sustainable applications. Using agro-industrial wastes as carbon substrates, enhancing yields through metabolic engineering, and carrying out extended biodegradation experiments in various environments are some future objectives. When combined, these tactics have the potential to hasten PHB\u27s shift to environmentally benign, scalable plastic replacements
Human Factors Engineering and AI for Optimizing Human-machine Interaction in Industrial Systems
No full textThe convergence of Artificial Intelligence (AI) and Human Factors Engineering (HFE) is the latest revolutionary method to maximize human-machine interaction (HMI) in industrial systems, and efficiency, safety, and reliability are continually the highest drivers of performance. The paper discusses how adaptive interfaces facilitated by AI, grounded on human factors design principles, enhance operator performance, reduce cognitive workload, and deliver automation confidence boost. Mixed-method design was employed with quantitative experiments on 60 industrial operators and qualitative interviews on 20 participants. Quantitative analysis was utilized to compare task performance, error rate, cognitive workload (NASA-TLX), and trust in automation of a baseline HMI (Group A) with an AI-HFE optimized HMI (Group B). Outcomes indicated shorter task completion times for operators using the AI-HFE interface to complete the task, error rates were reduced, ratings of workload were decreased, and trust levels were higher (p < .001). Trust and cognitive workload were also found to be predictors of performance on the task by regression analysis and explained 61% of the variance. Complementary qualitative findings highlighted trends of increased trust, reduced cognitive load, alignment with ergonomics, and training needs. Participants also expressed resistance in the form of concerns about skill loss and dependence on AI. Integrated analysis suggested that AI-HFE systems not only impact enhanced objective measures of performance but also influence subjective perceptions of interaction, with implications for user experience design as well as organizational support. This research adds to the emerging area of intelligent ergonomics by introducing an optimization framework for industrial HMI and with practical guidelines for system designers, engineers, and policy makers. Overall, AI application from a human factors perspective is an approach to improve industrial systems to be safer, more robust, and more human-centered
From Data Lakes to Decision-making: Leveraging Artificial Intelligence for Enterprise Governance, Risk Management, and Strategic Value Creation in the Digital Economy
No full textThe emergence of data lakes and artificial intelligence (AI) represents one of the most significant innovations at this intersection, enabling firms to translate raw, unstructured information into actionable insights that support governance, risk management, and strategic value creation. The rapid evolution of the digital economy has transformed how enterprises collect, store, and leverage data for governance, risk management, and strategic value creation. Central to this transformation is the emergence of data lakes and artificial intelligence (AI) technologies, which provide unprecedented opportunities for organisations to integrate vast, unstructured datasets into meaningful insights that drive decision-making. This paper employed a narrative-conceptual review design. The review was based on a structured process of identifying, selecting, analysing, and synthesising relevant literature. This paper explores the intersection of data lakes and AI, emphasising their role in enhancing enterprise governance structures, mitigating risks, and creating sustainable competitive advantage. Data lakes, by design, offer a scalable and flexible repository for heterogeneous data sources, while AI algorithms enable pattern recognition, predictive modelling, and real-time analytics. Together, they facilitate evidence-based decision-making, streamline compliance processes, and strengthen resilience against dynamic market uncertainties. The study highlights three critical dimensions. First, the governance perspective demonstrates how AI-enabled data management systems ensure accountability, transparency, and alignment with regulatory requirements. Second, the risk management perspective underscores the capacity of AI to identify vulnerabilities, forecast potential disruptions, and optimise mitigation strategies across financial, operational, and reputational domains. Third, the strategic value creation perspective explores how AI-driven insights contribute to innovation, agility, and long-term enterprise growth. By synthesising literature across management, information systems, and risk studies, this paper provides a conceptual framework that positions AI and data lakes as integral to enterprise digital transformation. The findings suggest that organisations that strategically invest in data infrastructure and AI capabilities can achieve superior decision-making, improved governance outcomes, and enhanced competitive positioning in the digital economy. Overall, the results of this study and the supporting literature converge on a central conclusion: AI, when integrated with robust governance and risk management frameworks, transcends its role as a technical tool to become a strategic enabler of organisational resilience, ethical compliance, and long-term value creation
Enhancing Smart Urban Mobility through Digital Twin-driven Autonomous Transportation and Predictive Maintenance
No full textThe research formulates a digital twin-focused autonomous transport system with a double functionality of predictive maintenance and traffic control. Through a simulation-based approach, real-time traffic flow data and vehicle health data were consolidated into a digital twin platform for autonomous transport in a Lagos urban transport model. Artificial intelligence software, including anomaly detection, predictive repair, and reinforcement learning, as well as adaptive traffic management, was incorporated into the digital twin platform. Results indicate that the framework achieved a 27% decline in vehicle downtime, an 18% increase in component lifespan, and a 22% decline in maintenance expenditures. Concomitantly, traffic optimization results achieved a 31% decline in congestion and a 24% average improvement in travel time in the simulated urban corridors. The results support the capacity of digital twin technology to achieve real-time decision-making, increase operating reliability, and facilitate sustainable mobility in future urban environments. The study emphasizes the potential of digital twins as a new technology for future autonomous transportation systems
Evaluating Conflict Resolution Mechanisms and Their Impact on Employment Relations in Public Institutions: A Case Study of the Greater Accra Region, Ghana
No full textThe study investigated conflict resolution mechanisms in employment relations within selected public institutions in the Greater Accra Region of Ghana, focusing on the causes of workplace disputes, the mechanisms used to address them, and their implications for organizational performance. Conflicts were found to arise mainly from communication breakdowns, role ambiguities, favoritism in promotions, and resource constraints. The study examined the use of negotiation, mediation, arbitration, collective bargaining, and formal grievance handling as key resolution mechanisms. The study employed a descriptive case study design with a mixed-methods approach, combining both qualitative and quantitative techniques. The study population comprised employees, HR personnel, and management staff from ministries, state-owned enterprises and public universities. The sample size for the study was 126 participants. Data were collected through structured questionnaires to obtain quantitative information while semi-structured and key informant interviews provided qualitative information. Quantitative data were analyzed using statistical software, including descriptive statistics, SPSS, and regression analysis, while qualitative data were subjected to thematic analysis. The study found that although institutional policies provided structured avenues for dispute resolution, their effectiveness was undermined by bureaucratic delays, inadequate training of human resource officers, and perceptions of bias, which reduced employee trust in the system. Additionally, the study revealed that where conflict resolution processes were timely, impartial, and participatory, they significantly improved employee–employer relationships, boosted job satisfaction, and enhanced institutional productivity. The study therefore recommends that public institutions prioritize the establishment of transparent, well-resourced, and professionally managed conflict resolution frameworks that emphasize fairness, neutrality, and participatory dialogue in order to sustain industrial harmony and improve organizational effectiveness
A Note on Dual Generalized Adrien Numbers
No full textIn this study, we introduce and develop the concept of Dual Adrien numbers, with particular emphasis on two fundamental cases: the Dual Adrien sequence and the Dual Adrien–Lucas sequence. We conduct a systematic investigation of their structural and analytical properties, encompassing algebraic identities, matrix representations, recurrence relations, Binet-type formulas, generating functions, exponential expressions, Simson-type identities, and summation formulas. By establishing these results, we aim to construct a coherent and mathematically rigorous framework for the study of Dual Adrien numbers. Furthermore, we highlight their intrinsic connections with classical recurrence families, thereby situating them within the broader landscape of hypercomplex sequence analysis. This work not only extends the theory of generalized number sequences into the dual-number algebraic setting but also provides new tools and perspectives that may inspire further research in recurrence relations, combinatorial identities, and hypercomplex algebraic structures
Assessing the Ecological Impact of Excreta Disposal on Lagos Lagoon, Nigeria
No full textThe dumping of raw faecal waste at Iddo Jetty poses serious environmental and public health issues for the Lagos Lagoon. The effects of these behaviors on the health of communities, fish safety, and the quality of water are examined in this study. The study is to evaluate how lagoon water usage is affected by the dumping of faeces, how common waterborne illnesses are among residents and waste handlers, and to offer practical suggestions for better cleanliness.Surveys and interviews were conducted with 163 respondents and 33 garbage handlers to gather field data. Both quantitative and qualitative analyses were performed on observations about lagoon water utilization, sanitation procedures, and health outcomes. The results showed that, despite serious contamination, 74.2% of respondents depend on the lagoon for fishing, and 2.5% drink the water. Residents reported 13.5% typhoid, 16.6% cholera, and 23.9% dysentery. Waste handlers who came into touch with raw faecal effluent reported getting typhoid (12.1%) and diarrhea (18.1%). Furthermore, 23.3% of those surveyed said that fish from the lagoon were unfit for human eating due to faecal pollution. The investigation comes to the conclusion that Iddo Jetty\u27s poor waste management and sanitation seriously endanger the community\u27s health and harm the lagoon ecology. To guarantee the lagoon\u27s sustainable use, immediate actions include installing centralized sewage systems, building adequate sanitary facilities, raising public knowledge of health hazards, and upholding environmental protection laws
Strategic Framework for Medical Technology Management in Healthcare Institutions: Enhancing Planning and Efficiency
No full textToday, the provision and management of healthcare services is becoming increasingly complex, and technology has a major impact on change and development in this field. The study can cover various aspects such as the role, processes, challenges and opportunities of technology planning in the organization of healthcare services. In addition, how healthcare organizations accept, implement and manage technology can also be investigated. It covers issues such as the inability to properly formulate technology investments and budget strategies in healthcare organizations, the difficulties and obstacles encountered in the technology planning process, and the effectiveness of technology use in healthcare services. The aim of the study is to create a framework model for understanding, evaluating and improving the planning process related to the use of technology in healthcare services. It allows us to determine how healthcare organizations organize technological infrastructure and processes, how they plan technology investments and how to improve the quality, access and effectiveness of healthcare services. The general objectives of the study can be stated as investigating the technological planning process, evaluating technology investments, investigating effective technology use, identifying obstacles and problems in the strategic technology planning process, and creating future strategies. In the research, strategic plans were developed based on the life cycles of medical technology products used in healthcare institutions. Then, a strategic technology framework model was proposed to improve the technological planning process in healthcare organizations and ensure the impact of future technological developments on improving the quality of healthcare services. This research develops a specific framework model for strategic planning in medical technology management in healthcare institutions, introducing innovative approaches to technology management. Unlike other studies, this model integrates both managerial and technical perspectives by considering the economic efficiency, operational effectiveness, and long-term sustainability of technologies. This approach offers comprehensive and sustainable solutions to support decision-making for healthcare managers
Strategic Leadership in Multigenerational Workforces: Bridging Generational Divides for Enhanced Engagement
No full textThis review examines the management of a multigenerational workforce, focusing on Baby Boomers, Generation X, Millennials, and Generation Z, and is underpinned by Upper Echelons Theory, which highlights how leaders\u27 experiences and values influence organizational outcomes. The study explores strategies like customized communication, mentorship, flexible work options, and tailored development programs, with the aim of enhancing engagement, collaboration, and productivity across generational lines. Using a qualitative approach, the review synthesizes findings from recent empirical studies and reports to identify key challenges and opportunities for managing a diverse workforce. Among the key challenges include different communication preferences across generations and varying work values and expectations. The conclusion emphasizes the need for adaptable leadership that recognizes and addresses the distinct values and expectations of each generation. Its significance lies in offering actionable recommendations for organizations and policymakers to create inclusive environments that cater to generational diversity, fostering employee engagement, satisfaction, and retention. The review also advocates for investment in mentorship programs, flexible work arrangements, and personalized career development, while urging policymakers to implement supportive policies that enhance generational collaboration and contribute to long-term organizational success
Diameter Distribution Models and Carbon Sequestration Potential of Afi Forest Reserve, Cross River State, Nigeria
No full textForest managers can make well-informed judgments, including prescribing silvicultural treatments, by being able to forecast the distribution of diameters in a stand. This study calculated the carbon potential of the Afi River Forest in Cross River State, Nigeria, and created and verified models for diameter distribution. For this investigation, two transects totaling 1500 meters in length were used, separated by 500 meters. There were ten sample plots per 1500m transect, or a total of 20 sample plots in the study area, with 50m x 50m sample plots spaced 100m apart throughout each transect. Measurements were made of the diameter at the breast height, the diameters at the base, middle, and top, and the overall height of 1368 individual tree species, distributed among 23 species from 18 distinct tree families. The average tree volume and biomass were found to be 12.01 m3 and 80.72 kg, respectively, while the mean diameter at breast height (dbh) and total height were measured to be 25.8 cm and 18.5 m, respectively. At stand level, mean basal area of 48.95m2ha-1 was attained with a mean volume of 244.561m3 ha-1and mean green biomass was 448.860ton ha-1with a dry biomass of 325.423ton ha-1. Diameter Distribution models were created using the Easy Fit program. Three diameter distribution models were validated for the reserve based on their post-development rankings. Nevertheless, among the chosen diameter models in the reserve, the Log-Logistic (3P) distribution model was determined to have the best fit. Since none of the chosen models was statistically significant, the diameter distribution of the study region can be modeled using all three of the fitted and validated models