Search Results (22,672)

Malaysia has committed to phasing out single-use plastics as part of its national sustainability agenda; however, the specific regulatory guidelines for implementing biodegradable and compostable bioplastics remain underdeveloped. This study aims to formulate practical and scalable guidelines for biodegradable and compostable bioplastic products, with a focus on the Federal Territory of Kuala Lumpur as a pilot case. Using a stakeholder-driven approach, a series of focus group discussions (FGDs) was conducted with key representatives from government bodies and the bioplastics industry. The guideline development process encompassed the identification and standardisation of terminology, definition of scope, certification frameworks, regulatory alignment, implementation strategies, and compliance mechanisms. The findings reveal a consensus among stakeholders on the need for clear and harmonised definitions to prevent ambiguity, as well as for certification protocols and enforcement mechanisms to align with existing legal frameworks. Revisions were proposed to terms, scope, and timelines to ensure legal compatibility and practical enforceability. The proposed guideline framework offers substantial potential for national adoption, contingent on inclusive stakeholder engagement across all Malaysian states to ensure uniformity and contextual relevance in its implementation. This study advances Malaysia’s SDG commitments by promoting sustainable bioplastics guidelines, encouraging national adoption through stakeholder engagement, and emphasising future integration of the life cycle assessment (LCA) to enhance the policy’s impact. Full article

Land is a critical factor of production that contributes significantly to economic growth. However, conventional land use pattern in China has resulted in serious environmental pollution. Now enhancing green land use efficiency (GLUE) has emerged as an effective strategy for improving environmental quality. The development of the digital economy (DE), characterized by low cost and high efficiency, has demonstrated considerable potential in reducing environmental pollutants and enhancing resource allocation. This study employs an extensive analytical framework to analyze the impact of DE development on GLUE across 267 cities in China from 2011 to 2019. The results show that DE exerts a significant effect on improving GLUE, which remains valid after the execution of endogeneity and robustness tests. The research on mechanisms indicates that this promotional effect is primarily achieved through the innovation in green technology and the optimization of industrial structure. Extended empirical tests indicate there is a nonlinear trend, wherein the positive effect increasingly intensifies after green industry innovation and industrial structure optimization exceeds threshold values. There is also a significant short term spillover effect of DE on GLUE, supplemented by long term effects. These findings substantially improve our comprehension of the connection of DE and land use, while providing practical policy recommendations for promoting environmentally sustainable development and land green utilization. Full article

Discrete-event simulation (DES) as an operations research (OR) technique has continued to evolve since its inception in the 1950s. DES evolution mirrors the advances in computer science (hardware and software, processing speed, and advanced information visualization capabilities). DES overcame the initial usability obstacles and lack of efficacy challenges in the early 2000s to remain a popular OR tool of “last resort.” Using bibliographic data from SCOPUS, this study undertakes a science mapping of the DES literature and evaluates its evolution and expansion in the past fifteen years. The results show asymmetrical but positive yearly literature output; broadened DES adoption in diverse fields; and sustained relevance as a potent OR method for tackling old, new, and emerging operations and production issues. The thematic analysis identifies DES as an essential tool that integrates and enhances digital twin technology in Industry 4.0, playing a central role in enabling digital transformation processes that have swept the industrial space in manufacturing, logistics, healthcare, and other sectors. DES integration with generative/artificial intelligence (GenAI/AI) provides a great potential to revolutionize modeling and simulation activities, tasks, and processes. Future studies will explore more ways to integrate GenAI tools in DES. Full article

This research aims to develop a model for cultivating talents in sustainable food literacy education in Taiwan. The project adopts the professional and theoretical axes of the food industry, sustainable development, and food literacy. The research employs a mixed-method approach, combining qualitative and quantitative techniques, to construct sustainable food literacy assessment indicators for Taiwan. In the first year, through literature analysis and qualitative research, the core content of “sustainable food literacy” in Taiwan was extracted, resulting in four major dimensions with 24 indicator items. Then, using the Fuzzy Delphi method, the indicators were constructed, defining the core content and dimension indicators of sustainable food literacy, which include “sustainable agriculture and production”, “healthy diet and culture”, “green environmental protection and consumption”, and “food social responsibility and ethics”, encompassing a total of 20 indicators. In the second year, based on the dimensions identified in the first year, a sustainable food literacy curriculum was developed. A 10-week quasi-experimental teaching curriculum was conducted for students enrolled in the “Vegetable and Fruit Carving” elective course in two classes of the Department of Food and Beverage Management at Jingwen University of Science and Technology. By comparing the pre-test and post-test scores of students’ sustainable food literacy and their sustainable food works, as well as analyzing student learning portfolios and teacher reflections, it was shown that the curriculum developed in this research significantly enhanced students’ sustainable food literacy and their performance. The results of this two-year study can be used for the assessment of sustainable food literacy talents in Taiwan, contributing both academically and practically. Full article

Industrial tree plantations (ITPs) are increasingly recognized as a sustainable response to deforestation and the decline in native wood resources in the Philippines. This study presents LUNTIAN (Labor, UNiversity, Timber Investment, and Agent-based Nexus), an agent-based model that simulates an experimental ITP operation within a mountain forest managed by University of the Philippines Los Baños. The model integrates biophysical processes—such as tree growth, hydrology, and stand dynamics—with socio-economic components such as investment decision making based on risk preferences, employment allocation influenced by local labor availability, and informal harvesting behavior driven by job scarcity. These are complemented by institutional enforcement mechanisms such as forest patrolling, reflecting the complex interplay between financial incentives and rule compliance. To assess the model’s validity, its outputs were compared to those of the 3PG forest growth model, with results demonstrating alignment in growth trends and spatial distributions, thereby supporting LUNTIAN’s potential to represent key ecological dynamics. Sensitivity analysis identified investor earnings share and community member count as significant factors influencing net earnings and management costs. Parameter calibration using the Non-dominated Sorting Genetic Algorithm yielded an optimal configuration that ensured profitability for resource managers, investors, and community-hired laborers while minimizing unauthorized independent harvesting. Notably, even with continuous harvesting during a 17-year rotation, the final tree population increased by 55%. These findings illustrate the potential of LUNTIAN to support the exploration of sustainable ITP management strategies in the Philippines by offering a robust framework for analyzing complex social–ecological interactions. Full article

This study focuses on the removal of arsenic (As) from contaminated water originating from an abandoned mercury mine landfill. To obtain results that more accurately reflect the material’s behavior under real-world conditions, tests were conducted starting with agitation, followed by column tests, and subsequently channel tests. The results demonstrated high efficacy of industrial waste materials (FA, HA, and EA) in adsorbing As, with a significant reduction of this contaminant in the leachates. Practical applications of this methodology include its potential use in large-scale remediation projects, improving water quality in mining-affected areas, and contributing to sustainable waste management practices. Full article

This study investigated the influence of process parameters on the recovery of phenolic compounds and antioxidant activity from pineapple peel using green extraction technologies: ultrasound-assisted extraction (UAE) and microwave-assisted extraction (MAE). A two-level factorial design was used to evaluate the effects of the solvent-to-solid ratio, time, temperature, ethanol concentration, and power on the yield of hydrolyzable and condensed polyphenols. The extracts were characterized using HPLC-MS, and their antioxidant activity was assessed using DPPH, ABTS, and FRAP assays. UAE yielded the highest condensed polyphenol content (323.82 mg/g), while MAE extracts demonstrated superior antioxidant activity (FRAP: 90.40 mgEqTrolox/g). The predominant compound identified using both methods was 1-caffeoylquinic acid. The most influential variable in UAE was the solvent-to-solid ratio, whereas extraction time was the most significant variable in MAE. These findings highlight the potential of pineapple peel valorization through sustainable extraction methods, with UAE favoring phenolic yield and MAE enhancing bioactivity, thereby supporting their application in the food and nutraceutical industries. Full article

The exponential growth in artificial intelligence (AI) and automation technologies is changing industries, creating a niche for a digitally competent workforce. Technical and vocational education (TVET) and training institutions are at the center of this transformational wave, with their role of equipping individuals with the competencies required for the digital era. The integration of AI and automation into the TVET curriculum and practice was explored as a game-changer for vocational education and training. AI-powered tools are used for personalized learning, intelligent tutoring systems, and virtual simulation of hands-on skills acquisition. The challenges and opportunities in using the technologies were explored to mitigate the digital divide, update instructor capabilities, and ensure inclusive access to modern training resources. Based on the results, TVET institutions can educate students, aligning with the need for Industry 4.0/5.0. Strategic frameworks for policy, curriculum design, and industry partnerships must be established to ensure that TVET continues to play a pivotal role in sustainable and equitable digital transformation. Full article

In the current era, Indian agriculture faces a significant demand for increased food production, which has led to the integration of advanced technologies to enhance efficiency and productivity. Drones have emerged as transformative tools for enhancing precision agriculture, reducing costs, and improving sustainability. This study provides a comprehensive review of drone adoption in Indian agriculture by examining its effects on precision farming, crop monitoring, and pesticide application. This research evaluates technological advancements, regulatory frameworks, infrastructure, farmers’ perceptions, and the financial accessibility of drone technology in the Indian agricultural context. Key findings indicate that, while drone adoption enhances efficiency and sustainability, challenges such as high costs, lack of training, and regulatory barriers hinder widespread implementation. This paper also explores the growing market for agricultural drones in India, highlighting key industry players and projected market growth. Furthermore, it addresses regional differences in adoption rates and emphasizes the increasing social acceptance of drones among Indian farmers. To bridge the gap between potential and practice, the study proposes several policy and institutional recommendations, including government-led financial incentives, training programs, and public–private partnerships to facilitate drone integration. Moreover, this review article also highlights technological advancements, such as AI and IoT, in agriculture. Finally, open issues and future research directions for drones are discussed. Full article

This study investigates the Enzyme Biofilm Method (EBM), a biological wastewater treatment technology previously developed by the authors. EBM employs microbial-derived hydrolytic enzyme groups in the initial treatment stage to break down high-molecular-weight organic matter—such as starch, proteins, and fats—into low-molecular-weight compounds. These compounds enhance the growth of native microorganisms, promoting biofilm formation on carriers and improving treatment efficiency. Over the past decade, EBM has been practically applied in food factory wastewater facilities handling high organic loads. The enzyme groups used in EBM are derived from cultures of Bacillus mojavensis, Saccharomyces cariocanus, and Lacticaseibacillus paracasei. To clarify the system’s mechanism and ensure its practical viability, this study focused on starch—a prevalent and recalcitrant component of food wastewater—using two evaluation approaches. Verification 1: Field testing at a starch factory showed that adding enzyme groups to the equalization tank effectively reduced biological oxygen demand (BOD) through starch degradation. Verification 2: Laboratory experiments confirmed that the enzyme groups possess both amylase and maltase activities, sequentially breaking down starch into glucose. The resulting glucose supports microbial growth, facilitating biofilm formation and BOD reduction. These findings confirm EBM’s potential as a sustainable and effective solution for treating high-strength food industry wastewater. Full article

Soil environmental quality in arid oases is crucial for regional ecological security but faces multi-source heavy metal (HM) contamination risks. This study aimed to (1) characterize the spatial distribution of soil HMs (As, Cd, Cr, Cu, Hg, and Zn) in the Ka Shi gar oasis, Xinjiang, (2) quantify the driving effect of irrigation water, and (3) elucidate interactions between HMs, soil properties, and land use types. Using 591 soil and 12 irrigation water samples, spatial patterns were mapped via inverse distance weighting interpolation, with drivers and interactions analyzed through correlation and land use comparisons. Results revealed significant spatial heterogeneity in HMs with no consistent regional trend: As peaked in arable land (5.27–40.20 μg/g) influenced by parent material and agriculture, Cd posed high ecological risk in gardens (max 0.29 μg/g), and Zn reached exceptional levels (412.00 μg/g) in gardens linked to industry/fertilizers. Irrigation water impacts were HM-specific: water contributed to soil As enrichment, whereas high water Cr did not elevate soil Cr (indicating industrial dominance), and Cd/Cu showed no significant link. Interactions with soil properties were regulated by land use: in arable land, As correlated positively with EC/TN and negatively with pH; in gardens, HMs generally decreased with pH, enhancing mobility risk; in forests, SOM adsorption immobilized HMs; in construction land, Hg correlated with SOM/TP, suggesting industrial-organic synergy. This study advances understanding by demonstrating that HM enrichment arises from natural and anthropogenic factors, with the spatial heterogeneity of irrigation water’s driving effect critically regulated by land use type, providing a spatially explicit basis for targeted pollution control and sustainable oasis management. Full article

Longnan is the largest olive cultivation area in China. The unique microclimates in Longnan make it an ideal testing ground for climate-resilient cultivation strategies with broader applications across similar regions, yet predictive models linking weather to oil quality remain scarce. This study establishes a climate suitability evaluation model for olive cultivation in central Longnan based on meteorological data and olive quality data in the Fotanggou planting base. Four key climatic factors are identified: cumulative sunshine hours during the fruit coloring to ripening period, average temperature during the fruit coloring to harvesting period, number of cloudy and rainy days during the harvesting period, and relative humidity during the fruit setting to fruit enlargement period. Olive oil quality is graded into three levels (Excellent III, Good II, Fair I) based on acidity, linoleic acid, and peroxide value using K-means clustering. A climate suitability index is developed by integrating these factors, with weights determined via principal component analysis. The model is validated against an olive quality report from the Dabao planting base, showing an 80% match rate. From 1991 to 2023, 87.9% of years exhibit suitable or moderately suitable conditions, with 100% of years in the past decade (2014–2023) reaching “Good” or “Excellent” levels. This model provides a scientific basis for evaluating and predicting olive oil quality, supporting sustainable olive industry development in Longnan. This model provides policymakers and farmers with actionable insights to ensure the long-term sustainability of olive industry amid climate uncertainty. Full article

This study focuses on realistic modeling of forming load and microstructural evolution during hot metal extrusion, emphasizing the effects of friction models and hydraulic press behavior. Rather than merely predicting load magnitudes, the objective is to replicate actual press operation by integrating a load limit response into finite element modeling (FEM). By applying Coulomb and shear friction models under both constant and hydraulically controlled press conditions, the resulting impact on grain size evolution during deformation is examined. The hydraulic press simulation features a maximum load threshold that dynamically reduces die velocity once the limit is reached, unlike constant presses that sustain velocity regardless of load. P91 steel is used as the material system, and the predicted grain size is validated against experimentally measured data. Incorporating hydraulic control into FEM improves the representativeness of simulation results for industrial-scale extrusion, enhancing microstructural prediction accuracy, and ensuring forming process reliability. Full article

Seeds of Cucurbitaceae crops represent a promising yet underexplored source of bioactive compounds with potential applications beyond nutrition, particularly in the cosmetics industry. This review examines the seeds of Citrullus lanatus (watermelon), Cucumis melo (melon), and Cucurbita pepo (pumpkin), focusing on their biochemical composition and evaluating their functional value in natural cosmetic development. Although these fruits are widely consumed, industrial processing generates substantial seed by-products that are often discarded. These seeds are rich in polyunsaturated fatty acids, proteins, carbohydrates, and phytochemicals, positioning them as sustainable raw materials for value-added applications. The incorporation of seed-derived extracts into cosmetic formulations offers multiple skin and hair benefits, including antioxidant activity, hydration, and support in managing conditions such as hyperpigmentation, acne, and psoriasis. They also contribute to hair care by improving oil balance, reducing frizz, and enhancing strand nourishment. However, challenges such as environmental instability and low dermal permeability of seed oils have prompted interest in nanoencapsulation technologies to improve delivery, stability, and efficacy. This review summarizes current scientific findings and highlights the potential of Cucurbitaceae seeds as innovative and sustainable ingredients for cosmetic and personal care applications. Full article

Digitalization is rapidly reshaping the global construction industry; however, its adoption in developing countries, such as Pakistan, remains limited and uneven. Hence, this study investigates and evaluates the current status of digital technology integration in Pakistan’s construction industry, with a primary focus on key tools, implementation challenges, and necessary policy interventions. Using a three-phase mixed-method approach involving a literature review, expert interviews, and a nationwide survey, this research identifies Building Information Modeling, Geographic Information Systems, and E-Procurement as essential technologies with strong potential to improve transparency, efficiency, and collaboration. However, adoption is hindered by a lack of awareness, limited technical expertise, and the absence of a cohesive national policy. This study also highlights that the private sector shows greater readiness compared to the public sector; however, systemic barriers persist across both sectors. Based on stakeholder insights, a three-part policy strategy was also proposed. This includes establishing a national regulatory framework, investing in capacity-building programs, and providing financial or institutional incentives to encourage the adoption of these measures. The findings emphasize that digitalization is not just a technical upgrade; it represents a pathway to improved governance and more efficient infrastructure delivery. With timely and coordinated policy action, the construction industry in Pakistan can align itself with global innovation trends and move toward a more sustainable and digitally empowered future. Full article