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Global Scholarship, Curated with Rigor

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Padang City faces serious waste problems, including a 500-ton increase in daily waste generation to 500 tons and an annual accumulation of 236,296 tons (2023). Waste from the Final Processing Site is predicted to exceed its maximum limit by 2026; waste composition mainly comprises organic materials (62.53%) and plastics (13.6%), which have not been sufficiently managed through the Reduce, Reuse, and Recycle (3R) paradigm. This study analyzes the institutional, technical, regulatory, financial, and participatory barriers to waste management in Padang, as well as the policy implications from collaborative governance and circular economy perspectives. Using qualitative-descriptive methodology, with document analysis and policy evaluation, this study offers a unique contribution by combining polycentric governance defined as multi-level coordination and activity among government, private sector, and community actors with responsive regulation that situates punitive enforcement in the context of observed social behaviour and institutional capacity. The results indicate that institution fragmentation, under-enforcement of established laws, unsustainable funding mechanisms, and low community participation undermine the waste management practices in Padang. Integrated Waste Processing Place 3R and waste banks have, so far, not achieved optimal scale in terms of effectiveness. Contextualizing these outcomes through the lenses of polycentric governance, responsive regulation, circular economy, and community-based social marketing shows the role that cross-sectoral collaboration, participatory mechanisms, and adaptive regulatory tools played in building resilient urban waste systems. Theoretically, this study contributes to environmental governance scholarship by integrating governance design and regulatory innovation in the Global South context, while offering practical recommendations for performance contracts among stakeholders, as well as the adoption of Extended Producer Responsibility (EPR), decentralized technologies for organic waste, and digital-based incentives at the community level. Therefore, this study not only highlights the need for structural reforms but also contributes to establishing inclusive, adaptive, and sustainable waste management systems in Indonesia’s urban areas.

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Kerosene pollution, stemming from its widespread use as a fuel and solvent, poses significant health and environmental risks. This study aimed to isolate biosurfactant-producing Klebsiella pneumoniae from petroleum-contaminated soil and apply the biosurfactant to enhance kerosene biodegradation. Among twelve isolates screened, seven produced biosurfactants, with K. pneumoniae S9 exhibiting the highest emulsification index (E24 = 45%). The biosurfactant was extracted, purified, and characterized as a lipopeptide via Thin-Layer Chromatography (TLC) and Fourier Transform Infrared (FT-IR) spectroscopy. Supplementation with the biosurfactant significantly accelerated kerosene degradation, achieving 64% efficiency within an 11-day incubation period. These results demonstrate the potential of this biosurfactant as an effective agent for the bioremediation of kerosene-contaminated environments.

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Lakes in mining areas face serious ecological degradation due to complex interactions between human activities, land use change, and industrial pressures. Globally, approximately 46.7% of lakes have lost their ecosystem resilience, with impacts such as declining water quality, sedimentation, heavy metal pollution, and biodiversity loss. While previous studies have mostly focused on post-mining pit lakes, limited attention has been given to conservation in active mining areas, leaving a critical research gap. This study aims to identify the factors influencing lake water resource conservation in mining regions, analyze the interrelationships among these factors, develop a conceptual model, and propose contextual strategies for sustainable conservation. A systematic literature review was conducted following the PRISMA 2020 protocol, using searches on Scopus and Web of Science for English-language publications from 2015 to 2025. Inclusion criteria emphasized empirical studies addressing lake conservation in mining areas. Study quality was assessed using the Mixed Methods Appraisal Tool (MMAT) version 2018, and data synthesis employed thematic analysis with NVivo 14 to identify key themes, factor relationships, and model design. From an initial 642 articles, 114 studies met the criteria. The analysis identified 13 key factors, with three dominant determinants: human–environment interaction, eco-friendly technology and innovation, and socio-economic pressures. Factor relationships included direct pathways such as institutional capacity and social capital, mediating roles such as environmental education and leadership, and negative moderation through economic pressures. The resulting conceptual model emphasizes integrating technological interventions, social capacity building, and environmental value internalization. Priority strategies include environmental education, institutional strengthening, community participation, and adoption of mitigation technologies. Overall, lake conservation in mining contexts requires an integrative social–ecological systems approach that balances technical innovation, social interventions, and mitigation of economic drivers.

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Sustainable logistics hub planning in emerging economies is often challenged by high levels of uncertainty, limited data availability, and the need to balance economic, environmental, and social objectives. Supporting consistent and transparent decision-making under such conditions remains a key issue in infrastructure planning. To address this, the present study develops an intelligent decision-support framework for prioritizing logistics hubs in complex and uncertain environments. The proposed framework combines $q$-rung orthopair fuzzy sets with the ordinal priority approach, enabling the representation of imprecise expert judgments alongside ordinal preference information within a unified multi-criteria structure. The approach is applied to the case of Kenya, where logistics development involves multiple and often conflicting criteria. A comprehensive evaluation system is established, and expert assessments are incorporated to derive priority rankings. The results show that operational efficiency and economic considerations play a dominant role in the decision process, while environmental and social factors receive comparatively lower weights. Sensitivity and comparative analyses confirm the stability and reliability of the findings. The study provides a structured and uncertainty-aware decision-support tool that can assist infrastructure planning and offers practical insights for policy and managerial decision-making in logistics systems.

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Remediating hydrocarbon-contaminated soils in rainforest ecosystems poses complex challenges, requiring strategies that balance ecological restoration with long-term sustainability. This study aimed to analyze stakeholder dynamics and identify collaborative approaches to support sustainable remediation in the Taman Hutan Raya Sultan Syarif Hasyim (TAHURA SSH) area in Sumatra. The Matrix of Alliances and Conflicts: Tactics, Objectives, and Recommendations (MACTOR) method was applied to examine interactions among eleven stakeholder groups. Data were collected through purposive interviews and focus group discussions to evaluate influence, dependence, and consensus across these groups. The findings revealed that Pertamina Hulu Rokan (PHR) and contractors function as central actors with the highest influence in advancing remediation practices. Conversely, local communities exhibited limited influence, suggesting their potential marginalization in decision-making processes. Although strong consensus was observed on ecological priorities—such as ecosystem restoration, long-term sustainability, and minimizing environmental impact—significant divergence regarding cost-effectiveness exposed underlying tensions between economic efficiency and environmental objectives. Sustainable remediation in rainforest ecosystems requires collaborative and inclusive strategies that foster partnerships among the private sector, government institutions, and local communities. These results provide practical implications for policymakers to develop environmentally responsible and socially equitable remediation frameworks in fragile ecosystems.

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To respond to global climate change, promote climate governance, and develop a master plan for sustainable development, carbon neutrality has become a common goal and vision of both developed and developing countries. In view of this objective, the interaction among energy transition, energy intensity, economic growth, and financial development is considered an important tool to harmonize economic development and environmental governance. This study aims to investigate the impacts of these four variables on Vietnam’s carbon neutrality objective during the period of 1995–2022. The Johansen cointegration analysis and a Vector Error Correction Model (VECM) were employed to disentangle short- and long-run relationships among the variables; the results of these analyses revealed asymmetric temporal effects. Energy transition and economic growth were found to increase CO₂ emissions in both the short and long run, hence suggesting that expansion of renewable energy could not effectively substitute fossil fuels and that economic growth remains energy intensive. In contrast, energy intensity and financial development reduced CO₂ emissions in the short run but contributed to rising emissions in the long run. This indicates the presence of rebound effects and scale-driven financial expansion without green investment target. It was concluded that Vietnam should plan and implement appropriate low carbon-intensive policies to achieve its carbon neutrality objective in the years ahead.

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Compliance management in business operations is often addressed through fragmented procedures that are difficult to coordinate and evaluate in a consistent manner. This study develops a structured compliance management framework grounded in a system engineering perspective, with the aim of linking regulatory requirements to operational processes in a coherent way. The framework is constructed by organizing compliance activities into a set of interrelated components, including regulatory interpretation, process integration, monitoring mechanisms, and feedback loops. On this basis, an evaluation scheme is established to examine the consistency and effectiveness of compliance implementation across operational stages. Particular attention is given to the identification of critical control points and the interaction between compliance measures and routine business processes. The proposed framework is examined through its application to typical organizational settings, where it allows a more transparent mapping between compliance requirements and operational execution. The analysis shows that a system-based structure supports clearer identification of process dependencies and facilitates more consistent evaluation outcomes. The study provides a structured basis for understanding compliance as an integrated operational system rather than a set of isolated practices, and offers a foundation for more informed decision-making in compliance management.

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Automated grading has become an important component of digital transformation in K-12 education, yet the structured recognition of handwritten responses on answer sheets remains a practical challenge. General-purpose vision-language models often show limited robustness when applied directly to school assessment materials, particularly in the presence of fixed answer regions, mixed Chinese-English content, and diverse handwriting styles. To address this issue, this study develops a task-oriented fine-tuning framework for automated recognition of handwritten answer sheets in K-12 educational settings. A multimodal dataset was constructed from Chinese and English answer sheets, with region-level annotations designed to support structured text extraction. Based on this dataset, the Qwen2.5-VL-7B-Instruct model was adapted through LoRA-based fine-tuning under a dual-A16 GPU environment to reduce computational cost while preserving practical deployment feasibility. An end-to-end workflow covering data preparation, model training, weight merging, and inference was then established for structured JSON output. Experimental results show that the fine-tuned model achieved stable convergence in both small-sample and medium-sample settings and improved the extraction quality of handwritten responses within predefined answer regions. The proposed framework provides a practical and reproducible solution for deploying vision-language models in school grading scenarios with limited computing resources. The study also offers an application-oriented reference for the integration of multimodal large models into educational assessment systems.

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This study aimed to demonstrate the application of environmental activity-based costing (EABC) and its impact on supporting environmental sustainability, in accordance with ISO 14001 and 14051 standards for material flow cost accounting (MFCA) and GRI 300 standards for materials, energy, water, compliance, waste, and environmental performance improvement. EABC is an environmental accounting tool that identifies activities and allocates environmental costs to those activities, then to products, thereby assigning each product its actual costs and providing more accurate data. The research was conducted at the General Company for Fertilizer Industries in the Southern Region of Basra, Iraq. The researcher employed a practical approach by comparing the system implemented in the company under study with EABC. The main reason for using this technique is the inefficient use of resources and the resulting environmental pollution and fines imposed for exceeding permissible pollution limits. These costs have come to constitute a large percentage of the company’s total costs, thus impacting its profitability. The research contributed to identifying areas of waste resulting from the inefficient use of available resources and assisted management in making sound and accurate decisions related to environmental and economic aspects. It also helped improve environmental performance and enable the allocation of environmental costs to products based on their resource consumption. This, in turn, leads to the sustainability of resources through optimal use, thus achieving environmental sustainability. The study concluded that adopting cash flow statements helps improve various administrative decision-making processes, including pricing decisions, by allocating environmental costs to products and the activities that generate them. Furthermore, some reasons for waste in raw materials are attributed to the poor quality of those materials and the manual addition of materials. Therefore, the model directs management’s attention and efforts towards purchasing less environmentally damaging materials and using a pump for material application.

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