Advanced Thermo-Exergo-Economic Optimization of Regenerative Dual-Turbine Gas Turbine Cycles under Tropical Operating Conditions

Gas turbine power plants operating in tropical regions experience persistent performance degradation due to high ambient temperatures, increased compressor work, and intensified thermodynamic irreversibilities, collectively reducing efficiency and increasing operating costs. While conventional energy-based analyses indicate that cycle modifications can enhance performance, they do not adequately identify the sources of inefficiency or their economic consequences. This study presents a comprehensive thermos-exergo-economic optimization of a real industrial gas turbine power plant operating under sustained tropical conditions. Five years of operational data from the Omotosho gas turbine power plant in Nigeria were used to develop and validate detailed ASPEN HYSYS models for a conventional Brayton cycle and three advanced retrofit configurations incorporating inlet air cooling, regeneration, heat- recovery steam generation, steam injection, dual combustion chambers, and staged turbine expansion. Component-level exergy and exergoeconomic analyses were conducted, followed by multi-objective optimization using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to maximize exergetic efficiency and minimize the cost of exergy destruction. The results show that the configuration combining inlet air cooling, regeneration, steam injection, and dual turbine expansion achieves the lowest exergy destruction and the highest exergetic efficiency, improving second-law efficiency by more than 40% relative to the conventional cycle. A well-defined Pareto-optimal operating region with exergetic efficiencies above 45% is identified without excessive economic penalties, providing practical guidance for gas turbine retrofits in hot-climate power systems

Marxist Critique of Trade Unionism in Colonial Africa: Nigerian Experience

The central theme of this study was to critically examine the nature, origin, role and development of the social movement and institution of trade unionism in colonial Africa from the Marxian perspective. It determined the question whether the role Marxism proposed for unionism had been accomplished and whether it was applicable to colonial Nigeria and by extension, Africa. This study adopted the doctrinal method. It critically analyzed the views of text writers and colonial officials. It examined colonial records and events involving governments, unionists and unionism. It found and held the view that trade union developed with the rise of industrialization but that political unionism was the genre that suited its analysis and critique as against the enterprise or the business union in colonial Africa. The study concluded that trade unionism played a crucial role in the industrial relations atmosphere of colonial Africa and the agitations and struggles leading to the independence of African states including Nigeria

Detailed Molecular Interaction Analysis at the DPP-4 Active Site of Aromatic Compounds from Cinnamon Bark (Cinnamomum Cassia): Binding Mechanisms and Comparison with the Gliptin Class

This study presents a detailed residue-level interaction analysis at the active site of Dipeptidyl peptidase- 4 (DPP-4) for 13 aromatic compounds isolated from cinnamon bark (Cinnamomum cassia), integrating previously published molecular docking results with comprehensive profiling using the Protein-Ligand Interaction Profiler (PLIP). Interaction patterns — including hydrophobic contacts, hydrogen bonds, π- stacking, and salt bridges — were systematically extracted, mapped onto key active-site residues, and comparatively evaluated against six synthetic DPP-4 inhibitors of the gliptin class. The analysis demonstrates that the S1 subsite (Tyr631, Val656, Trp659, Tyr662, Tyr666, Val711) is the preferred binding locus for 12 out of 13 aromatic compounds, whereas 4-hydroxybenzaldehyde exhibits a distinctive binding mode that preferentially targets the S2 subsite and the catalytic triad. Among the natural ligands, three compounds emerged as the most promising candidates: benzyl benzoate (−7.4 kcal/mol, 9 interactions), 1-naphthalenol (−6.352 kcal/mol, 11 interactions), and 1-phenyl-1,2- propanedione (−6.086 kcal/mol, 6 interactions), with 1-naphthalenol displaying a multi-point interaction profile that simultaneously engages S1, S2, and catalytic residues via a combination of hydrophobic contacts and hydrogen bonds. Comparative profiling with the gliptins reveals that the aromatic compounds excel in hydrophobic contacts within S1 but generally lack interactions with S2 and the catalytic triad — a key distinction that largely accounts for their lower binding affinity and selectivity. Structure-activity relationship (SAR) analysis suggests that combining aromatic hydrophobic scaffolds with appropriately oriented hydrogen-bond donors/acceptors directed toward S2 and the catalytic triad constitutes a rational strategy for optimizing natural-origin DPP-4 inhibitors. Collectively, these findings provide a robust mechanistic framework for the design and development of cinnamon-derived DPP-4 inhibitor candidates as potential therapeutics for type 2 diabetes mellitus

A Hybrid AHP–WSM–TOPSIS Decision Framework for Optimal Gas Turbine Retrofit Selection under Conflicting Thermo-Economic Objectives

Gas turbine retrofit planning involves complex trade-offs among thermodynamic performance, economic viability, and environmental impact, given conflicting objectives. Conventional retrofit studies often emphasize isolated performance indicators or rely on deterministic decision frameworks, limiting their applicability to real-world investment and operational planning. This study presents an integrated thermo-economic and multi-criteria decision-making (MCDM) framework for optimal selection of gas turbine retrofits, using the Omotosho gas turbine power plant as a real-world case study. Three advanced retrofit configurations—incorporating inlet air cooling, exhaust gas regeneration, heat- recovery steam generation (HRSG)-based steam injection, additional turbine stages, and dual combustion chambers — are modelled and evaluated against the baseline simple-cycle plant. Detailed thermodynamic simulations are performed using ASPEN HYSYS, while long-term economic performance is assessed over a 20-year operating horizon. To address conflicting objectives, the Analytic Hierarchy Process (AHP) is used to determine criterion weights, which are integrated into the Weighted Sum Method (WSM) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for retrofit ranking. Results indicate that all retrofit configurations significantly outperform the baseline plant. The MGTP-1 configuration consistently demonstrates superior performance, achieving the highest thermal efficiency (47.44%), the most excellent net power output (157.08 MW), the lowest specific fuel consumption, and the highest net economic benefit. Both WSM and TOPSIS rank MGTP-1 as the optimal retrofit option, with sensitivity analysis confirming its robustness across varying operating conditions. The proposed framework provides a transparent, data-driven decision-support tool for identifying economically viable and environmentally sustainable gas turbine retrofit strategies

The Impact of Environmental Factors on the Development of Antibiotic Resistance in Environmental Systems

The pressure of climate change and human actions on the ecosystems are unprecedented, so our analysis should be conducted in parallel regarding their independent and combined consequences on the ecosystem stability. The climate dynamics are highly controlling in that they have direct effect on species, population, community and biogeochemical processes within various systems including terrestrial ecosystems, freshwater ecosystems, marine ecosystems and coastal ecosystems. Manmade activities, both in land-use change, pollution and greenhouse-gas emission, equally encroach on many climate and environmental drivers, impacting organisms and processes in all ecosystems. In the present climate- change era, the anthropogenic perturbations affect the resilience and stability by changing the ecosystem responses and vary the interaction between climate and environmental drivers. Little formal modelling of the interactions between human activities and climate change has been done. Nonetheless, the recent data on cases of such interactions in diverse ecological settings depicts the interactions as well as their ecological impacts on the stability of ecosystems. A single study of a dryland stream showed that an increase in temperature and reduction in precipitation interact to cause macroinvertebrate communities to become more unstable and sensitive; as warming and drought become more severe, the cascading processes destroy former stabilizing processes and interacting climatic and anthropogenic drivers. Likewise, the shift of tropical waters to a turbid condition of underwarming and nutrient enrichment is an example of a tipping point and alterations in fire, great storms and pest outbreaks are evidence of changes in disturbance regime

From Compliance to Culture: Reconstructing Academic Integrity Education in Emerging Higher Education Systems in the Digital and AI Era

In the context of rapid digital transformation and the proliferation of artificial intelligence (AI), academic integrity has emerged as a systemic challenge for higher education, particularly in emerging systems. This paper argues that traditional compliance-based approaches–centered on detection and punishment–are increasingly inadequate for sustaining academic standards. Drawing on a systematic literature review and conceptual analysis, the study proposes a paradigm shift toward a culture-based approach in which academic integrity is internalized as a core value. The study integrates three theoretical strands–academic integrity, information and copyright literacy, and digital ethics–to develop an “academic integrity ecosystem” framework comprising four interconnected dimensions: policy, pedagogy, infrastructure, and culture. The findings highlight three key issues: the structural limitations of compliance-based models, the transformative impact of AI in blurring the boundaries of academic misconduct, and the emerging role of academic libraries as central actors in fostering ethical knowledge practices. The paper argues that academic libraries should be repositioned as institutional hubs that bridge policy and practice through the development of information literacy, ethical awareness, and responsible AI use. By shifting from behavioral control to value cultivation, the proposed framework offers both theoretical and practical implications for higher education systems seeking to build sustainable and adaptive academic environments in the digital and AI era

Environmental Governance in Bangladesh’s Textile Industry for Sustainable Development: Issues and Challenges

Environmental governance is a key concept within political ecology and environmental policy that emphasizes sustainability, or sustainable development, as the foremost priority in guiding political, social, and economic activities. In Bangladesh, environmental governance holds considerable importance in confronting various environmental issues. It includes legal structures, policy measures, and institutional mechanisms designed to encourage sustainable practices and reduce environmental damage. This study offers a comprehensive and systematic analysis of environmental legislation and policy frameworks in Bangladesh. It aims to critically examine the conceptual foundations of environment and sustainable development and to establish their interrelationship within the broader context of the country’s development priorities. The paper evaluates the prevailing environmental conditions in Bangladesh, identifying the principal causes and consequences of environmental degradation, which emerge from the complex interaction between anthropogenic activities and natural processes. Furthermore, it investigates the extent to which development programs contribute to, or are affected by, environmental decline. The study also assesses the initiatives and policy responses undertaken to address environmental challenges and disasters in Bangladesh. Finally, it proposes a set of policy recommendations advocating for an integrated and holistic approach to achieving long-term sustainable development. For analytical rigor, the research concentrates on selected environmental issues that collectively represent the overall environmental status of the country

Atomic-Scale Interfacial Characterization and Circular Economy Assessment of Sustainable Concrete Incorporating DCFRP, GBFS, and Oyster Shell Waste

Mitigating the carbon footprint of cementitious composites while sustaining mechanical performance remains a critical challenge in modern construction. This study investigates the atomic-scale origins of strength in a sustainable ternary waste valorization system incorporating Discarded Carbon Fibre Reinforced Polymer (DCFRP) fibres, S105 Granulated Blast Furnace Slag (GBFS), and Oyster Shell Powder (OSP). While previous research established the macroscopic viability of this composite, demonstrating a 22.4% increase in compressive strength the physicochemical mechanisms governing its performance remained unexplored. Employing X-ray Photoelectron Spectroscopy (XPS), this research reveals that the optimal mix (10% GBFS and 5% OSP) achieves a surface Calcium-to-Silicon (Ca/Si) atomic ratio of 0.47. Although lower than typical bulk C-S-H values reported in the literature (Ca/Si ≈ 0.8–1.7), this reduced ratio reflects a silica-enriched surface environment in the slag-blended system, consistent with enhanced silicate polymerization and surface-modified C-(A)-S-H chemistry. High-resolution Si2p spectra at 102.6 eV confirm enhanced silicate polymerization driven by the latent hydraulic activity of GBFS. XPS analysis indicates the presence of carbonate–aluminate interactions consistent with potential heterogeneous nucleation mechanisms at the OSP surface. While XPS does not provide spatial resolution of the ITZ, the observed chemical signatures support a chemically favourable environment for interfacial densification. Conversely, a chemical "dilution threshold" is identified at 15% OSP replacement, where unreacted calcite phases act as stress concentrators. These findings bridge the gap between phenomenological testing and molecular chemistry, establishing a scientific framework for a Circular Economy model that enables a 10% reduction in clinker consumption and the effective valorization of industrial and marine waste streams

Chemical Methods of Water Purification in Uzbekistan

Uzbekistan faces a serious environmental problem of water pollution due to intensive industrial activity, exacerbated by outdated water treatment infrastructure and poorly coordinated water resource management. Industrial and domestic wastewater often contains a mixture of chemical contaminants, including suspended solids, heavy metals, and organic compounds, posing a significant risk to the quality of surface and groundwater. The solution to these problems lies in technological modernization and the scientifically sound application of chemical water treatment methods, based on the experience of other countries. International experience from countries with similar problems will help Uzbekistan develop its own comprehensive approach to addressing water pollution using chemical methods. The study is based on a qualitative analysis of scientific literature, official documents, and case studies from Uzbekistan and selected countries with advanced water treatment systems. The international experience of Germany, Singapore, and Japan is analyzed to assess the effectiveness of integrating chemical treatment methods into regulated water resource management systems in Uzbekistan. This study examines key chemical water treatment methods widely used in Uzbekistan, including chemical softening, chlorination, and activated carbon adsorption. The results show that although many chemical water treatment methods in Uzbekistan are scientifically sound, their effectiveness is limited by fragmented application, insufficient monitoring, and poor integration into multi-stage treatment schemes. The study concludes that implementing international practices could significantly improve water quality and promote sustainable water resource management in Uzbekistan

A Graph Neural Network-Based Framework for Reliability Prediction of Automated Carotid Intima-Media Thickness Segmentation

Cardiovascular diseases remain the leading cause of global mortality. Carotid intima-media thickness (CIMT) is a well-established surrogate biomarker for early atherosclerosis detection. Manual CIMT ultrasound segmentations are more time-consuming and prone to error than automated CIMT ultrasound segmentations. This study presents a two-stage framework that integrates metric-based evaluation with Graph Neural Network (GNN)-based learning for automated CIMT segmentation evaluation and reliability prediction. In the first stage, segmentation performance was evaluated using overlap-based metrics, including the Dice Similarity Coefficient (DSC) and Jaccard Index (JI), together with the distance- based Point-to-Distance Metric (PDM). In the second stage, a GNN was trained on a patient similarity graph constructed from aggregated clinical features and segmentation-derived metrics for patient-level segmentation reliability prediction. The metric-based evaluation yielded a mean DSC of 0.915 ± 0.143, a mean JI of 0.863 ± 0.158, and PDM values of 0.239 ± 0.070 mm and 0.236 ± 0.067 mm for the Lumen– Intima and Media–Adventitia boundaries, respectively, indicating close agreement between automated and manual segmentations. The GNN-based learning achieved a Pearson’s correlation coefficient (r) of 0.972 with a Mean Absolute Error (MAE) of 0.017 for mean DSC and an r of 0.946 with an MAE of 0.015 for mean JI, indicating high consistency between predicted and true values. The proposed framework reduces reliance on manual segmentations by demonstrating robust performance of automated segmentations and enabling patient-level segmentation reliability prediction