Search Results (4,414)

Insects are increasingly recognized as sustainable protein sources due to their high feed conversion efficiency and low environmental impact. Among them, the superworm, Zophobas morio (Fabricius) (Coleoptera: Tenebrionidae), has strong potential for large-scale production; however, optimized feeding strategies under tropical conditions remain limited. This study aimed (1) to determine the optimal feed formulations and feeding rate using wheat bran supplemented with the KMITL Protein Innovation source (a protein feed ingredient developed by the School of Agricultural Technology, King Mongkut’s Institute of Technology Ladkrabang, KMITL), and (2) evaluate the influence of plant-based supplementary foods on larval performance. In Phase I, larvae were reared on 13 formulations with three protein levels (CP00, CP21, and CP24) and five feeding rates (A–E). Diets CP21–21 and CP24–21 (21 and 24% CP; wheat bran/protein = 2:1) resulted in the highest survival (83.4–84.1%) and the lowest feed conversion ratios (FCR = 2.29–2.34). Moderate feeding rates (C–D; 925–1110 g feed per tray for 50 days) produced the greatest larval weights (700–760 mg), whereas ad libitum feeding provided no additional benefit. In Phase II, larvae reared on CP21–21 with a restricted rate of 1100 g per tray and supplemented with ten plant-derived foods achieved comparable final weights (716–760 mg), but survival varied significantly among treatments. Mulberry leaf yielded the highest survival (95.3%), followed by banana, watermelon rind, winter melon, and jicama (>90%). Pumpkin and jicama accelerated pupation and adult emergence, showing a female-biased sex ratio among emerged adults (59.2–65.5%), suggesting enhanced developmental rates. These results establish a practical framework for cost-effective and sustainable Z. morio production under tropical conditions, contributing to circular bioeconomy strategies and supporting insect-protein innovation. Full article

It is well documented that road construction is a pillar of well-balanced socioeconomic development worldwide. The first decades of the new millennium have witnessed unprecedented development in road construction activities in emerging economies and the Global South. At the same time, the construction industry is widely considered to be a rather conservative one, based on traditional technologies and materials. However, the development of materials science increases the possibilities and volumes of by-products from various technologies, and the selective collection of garbage necessitates innovation in the road construction sphere. The goal of this paper is to provide a broad overview of innovations in road construction. Based on a bibliometric approach, the article analyses the various trends in round construction, where the increasing pressure to reduce costs and the environmental footprint drives deep-rooted innovation through the use of new materials and the optimisation of technologies and management methods. Our results highlight the potential for significant improvements in road construction efficiency, environmental impact, and cost-effectiveness through the adoption of these technologies and methodologies, as well as a trend towards more efficient, sustainable, and technologically advanced road construction practices, with a focus on overcoming traditional inefficiencies and environmental concerns. Future research should continue to focus on addressing these challenges and developing comprehensive, adaptable solutions for the road construction industry, while leveraging the latest findings in this area. Full article

In the context of the ongoing digital revolution in manufacturing and the simultaneous advancement toward dual carbon objectives, this study investigates the role of intelligent technological advancements, particularly industrial robotics, in improving firm-level energy efficiency. Utilizing panel data from Chinese listed companies spanning the period 2012–2023, the research assesses the relationship between exposure to industrial robots and corporate energy efficiency metrics. The empirical analysis demonstrates that greater exposure to industry-level robotization substantially boosts corporate energy performance, verifying that intelligent modernization and green transition can be mutually reinforcing. This positive effect is particularly pronounced among superstar firms, in more competitive industries, and for capital-intensive enterprises. Mechanism analysis reveals that, first, robotization processes generate a scale effect that effectively dilutes the fixed energy consumption per unit of product. Second, the diffusion of robots intensifies market competition, creating a competition effect that compels all firms within the industry to optimize costs and management with a focus on energy conservation. This study demonstrates that enhancing human capital within organizations significantly amplifies the beneficial impact of robotic integration on energy efficiency metrics. By providing empirical data from an emerging market context, this research not only elucidates the role of industrial robots but also offers policy-relevant insights for developed economies navigating the concurrent challenges of industrial modernization and environmental sustainability. Full article

This classroom-based case study examines how an AI-mediated Socratic dialogue, implemented through ChatGPT, can support students’ engagement and perceived learning in undergraduate thermodynamics. Conducted in a first-year engineering physics course at a private university in northern Mexico, the activity invited small student groups to interact with structured prompts designed to promote inquiry, collaboration, and reflective reasoning about the adiabatic process. Rather than functioning as a source of answers, ChatGPT was intentionally positioned as a mediating scaffold for Socratic questioning, prompting students to articulate, examine, and refine their reasoning. A mixed-methods approach was employed, combining a 10-item Likert-scale survey with construct-level statistical analysis of two focal dimensions: perception of learning and engagement, including an exploratory comparison by gender. Results indicated consistently high levels of perceived learning and engagement across the cohort, with average scores above 4.5 out of 5. At the construct level, no statistically significant gender differences were observed, although a single item revealed higher perceived learning among female students. Overall, the findings suggest that the educational value of ChatGPT in this context emerged from its integration within a Socratic, inquiry-oriented pedagogical design, rather than from the technology alone. These results contribute to ongoing discussions on the responsible and pedagogically grounded integration of generative AI in physics education and align with Sustainable Development Goal 4 (Quality Education). Full article

Solar-driven hydrogen production via photocatalytic water splitting represents a promising route toward sustainable and low-carbon energy systems. Among emerging photocatalysts, porphyrin-based framework materials, specifically porphyrinic metal–organic frameworks (PMOFs) and porphyrinic covalent organic frameworks (PCOFs), have attracted increasing attention owing to their strong visible-light absorption, tunable electronic structures, permanent porosity, and well-defined catalytic architectures. In these systems, porphyrins function as versatile photosensitizers whose photophysical properties can be precisely tailored through metalation, peripheral functionalization, and integration into ordered frameworks. This review provides a comprehensive, design-oriented overview of recent advances in PMOFs, PCOFs, and hybrid porphyrinic architectures for photocatalytic H₂ evolution. We discuss key structure–activity relationships governing light harvesting, charge separation, and hydrogen evolution kinetics, with particular emphasis on the roles of porphyrin metal centers, secondary building units, linker functionalization, framework morphology, and cocatalyst integration. Furthermore, we highlight how heterojunction engineering through coupling porphyrinic frameworks with inorganic semiconductors, metal sulfides, or single-atom catalytic sites can overcome intrinsic limitations related to charge recombination and limited spectral response. Current challenges, including long-term stability, reliance on noble metals, and scalability, are critically assessed. Finally, future perspectives are outlined, emphasizing rational molecular design, earth-abundant catalytic motifs, advanced hybrid architectures, and data-driven approaches as key directions for translating porphyrinic frameworks into practical photocatalytic hydrogen-generation technologies. Full article

The continuous detection of emerging pollutants (EPs) in water poses potential threats to aquatic environmental safety and human health, and their efficient removal is a frontier in environmental engineering research. This review systematically summarizes research progress from 2005 to 2025 on the application of activated carbon (AC) and its composites for removing EPs from water and analyzes the development trends in this field using bibliometric methods. The results indicate that research has evolved from the traditional use of AC for adsorption to the design of novel materials through physical and chemical modifications, as well as composites with metal oxides, carbon-based nanomaterials, and other functional components, achieving high adsorption capacity, selective recognition, and catalytic degradation capabilities. Although AC-based materials demonstrate considerable potential, their large-scale application still faces challenges such as cost control, adaptability to complex water matrices, material regeneration, and potential environmental risks. Future research should focus on precise material design, process integration, and comprehensive life-cycle sustainability assessment to advance this technology toward highly efficient, economical, and safe solutions, thereby providing practical strategies for safeguarding water resources. Full article

Sepsis is a life-threatening syndrome characterized by marked clinical heterogeneity and complex host–pathogen interactions. Although traditional mechanistic studies have identified key molecular pathways, they remain insufficient to capture the highly dynamic, multifactorial, and systems-level nature of this condition. The advent of high-throughput omics technologies—particularly integrative multi-omics approaches encompassing genomics, transcriptomics, proteomics, and metabolomics—has profoundly reshaped sepsis research by enabling comprehensive profiling of molecular perturbations across biological layers. However, the unprecedented scale, dimensionality, and heterogeneity of multi-omics datasets exceed the analytical capacity of conventional statistical methods, necessitating more advanced computational strategies to derive biologically meaningful and clinically actionable insights. In this context, artificial intelligence (AI) has emerged as a powerful paradigm for decoding the complexity of sepsis. By leveraging machine learning and deep learning algorithms, AI can efficiently process ultra-high-dimensional and heterogeneous multi-omics data, uncover latent molecular patterns, and integrate multilayered biological information into unified predictive frameworks. These capabilities have driven substantial advances in early sepsis detection, molecular subtyping, prognosis prediction, and therapeutic target identification, thereby narrowing the gap between molecular mechanisms and clinical application. As a result, the convergence of AI and multi-omics is redefining sepsis research, shifting the field from descriptive analyses toward predictive, mechanistic, and precision-oriented medicine. Despite these advances, the clinical translation of AI-driven multi-omics approaches in sepsis remains constrained by several challenges, including limited data availability, cohort heterogeneity, restricted interpretability and causal inference, high computational demands, difficulties in integrating static molecular profiles with dynamic clinical data, ethical and governance concerns, and limited generalizability across populations and platforms. Addressing these barriers will require the establishment of standardized, multicenter datasets, the development of explainable and robust AI frameworks, and sustained interdisciplinary collaboration between computational scientists and clinicians. Through these efforts, AI-enabled multi-omics research may progress toward reproducible, interpretable, and equitable clinical implementation. Ultimately, the synergy between artificial intelligence and multi-omics heralds a new era of intelligent discovery and precision medicine in sepsis, with the potential to transform both research paradigms and bedside practice. Full article

Pathological scars are fibrotic lesions that result from aberrant wound healing following tissue injury, such as burns. They are frequently associated with disfigurement and dysfunction, thereby severely impairing the quality of life of affected patients. Current clinical treatments, including surgery, laser therapy, and corticosteroid injections, are often characterized by limited efficacy, high recurrence rates, and undesirable side effects, including skin atrophy. Furthermore, the dense structure and excessive extracellular matrix (ECM) deposition in scar tissue present a significant barrier to effective drug penetration, thereby further limiting therapeutic efficacy. In recent years, biomaterial-based drug delivery systems, which integrate sustained drug release with minimally invasive transdermal technologies, have emerged as a promising strategy to overcome the limitations of traditional therapies. This review systematically outlines the pathogenesis and molecular mechanisms of pathological scars, summarizes established and emerging treatments, and highlights the application strategies and future prospects of novel biomaterial-based drug delivery systems for managing this condition. Full article

This systematic review article provides a comprehensive and critical analysis of the use of bioinputs in sustainable agriculture, focusing on biosurfactants and absorbent polymers, particularly bacterial cellulose. The article contextualises the growing challenges in agricultural production due to population growth, climate change, and environmental limitations, highlighting the need for alternatives to traditional synthetic inputs that exert negative environmental impacts. The article details functions, types, and benefits, emphasising the ability of bioinputs to improve soil fertility, increase the efficiency of nutrient use, enhance plant resistance to biotic and abiotic stress, and reduce the ecological footprint of agriculture. Emerging biotechnologies are discussed, such as the combined use of biosurfactants with natural polymers to ensure sustainability and efficiency. This article offers an updated description of recent scientific and technological evidence and addresses the potential and limitations of these biological inputs in the global context of modern agriculture. Full article

Aquaculture has grown rapidly worldwide and has become a key source of food and employment opportunities. However, its expansion faces environmental, health, reproductive, and technological challenges that threaten its long-term sustainability. In this context, biologists play a crucial role in promoting sustainable practices and integrated management of aquaculture systems. This article reviews their main contributions to animal health, genetic improvement, assisted reproduction, and resource conservation. They also highlight their leadership in applying advanced technologies, including biotechnology, nanotechnology, and genetic engineering. Moreover, this study explores emerging research trends and emphasizes the importance of interdisciplinary training to address the evolving demands of the sector. This underscores the need to strengthen collaboration between science, technology, and public policy to ensure sustainable aquaculture. Enhancing the role of biologists is essential for overcoming current challenges and advancing efficient, ethical, and environmentally responsible aquaculture systems that meet global demand. Full article

In pursuit of global climate goals and sustainable development, countries have adopted a wide range of environmental policy instruments. This study examines the relationship between environmental policy stringency (EPS) and environmental outcomes, measured by carbon intensity (CI) and renewable energy intensity (REI), in 16 G20 countries from 1990 to 2020. The empirical findings reveal that more stringent environmental policy is a significant predictor of reduced CI and increased REI, although effects vary by policy type, time horizon, and country group. A novel sub-index-level analysis reveals that market-based incentive instruments, particularly trading schemes on CO₂ emissions and renewable energy, as well as technology support instruments, particularly wind and solar initiatives, exhibit the strongest and most robust effects. Emerging economies generally display greater responsiveness to policy interventions than advanced economies. By identifying which specific policy instruments are most effective across different development contexts, this study provides actionable insights for designing targeted climate policies that support both energy transition and sustainable development pathways. Full article

Water wastage management (WWM) in deep-level mines remains a critical challenge, as wastage increases operational costs and threatens sustainability. This study presents a systematic state-of-the-art review of WWM in deep-level mines. Relevant literature was critically assessed to establish current practices, identify limitations, and explore emerging solutions. Five principal approaches were identified: leak detection and repair, pressure control with fixed schedules, network optimisation, accountability measures, and smart management. While each provides benefits, significant challenges persist. Particularly, current pressure control techniques, essential for limiting leakage, rely on static demand profiles that cannot accommodate the stochastic nature of service water demand, often resulting in over- or under-supply. Smart management systems, which have proven effective for managing stochastic utilities in other industries, present a promising alternative. Enabling technologies such as sensors, automated valves, and tracking systems are already widely deployed in mining, underscoring the technical feasibility of such systems. However, no studies have yet examined their development for WWM in deep-level mines. This study recommends a framework for smart water management tailored to mining conditions and highlights three opportunities: developing real-time demand approximation methods, leveraging occupancy data for demand estimation, and integrating these models with mine water supply control infrastructure for implementation and evaluation. Full article

The increasing urgency to mitigate plastic pollution has accelerated the shift from linear manufacturing toward circular systems. This review synthesizes current advances in mechanical, chemical, biological, and upcycling pathways, emphasizing how artificial intelligence (AI) is reshaping decision-making, performance prediction, and system-level optimization. Intelligent sensing technologies—such as FTIR, Raman spectroscopy, hyperspectral imaging, and LIBS—combined with Machine Learning (ML) classifiers have improved material identification, reduced reject rates, and enhanced sorting precision. AI-assisted kinetic modeling, catalyst performance prediction, and enzyme design tools have improved process intensification for pyrolysis, solvolysis, depolymerization, and biocatalysis. Life Cycle Assessment (LCA)-integrated datasets reveal that environmental benefits depend strongly on functional-unit selection, energy decarbonization, and substitution factors rather than mass-based comparisons alone. Case studies across Europe, Latin America, and Asia show that digital traceability, Extended Producer Responsibility (EPR), and full-system costing are pivotal to robust circular outcomes. Upcycling strategies increasingly generate high-value materials and composites, supported by digital twins and surrogate models. Collectively, evidence indicates that AI moves from supportive instrumentation to a structural enabler of transparency, performance assurance, and predictive environmental planning. The convergence of AI-based design, standardized LCA frameworks, and inclusive governance emerges as a necessary foundation for scaling circular plastic systems sustainably. Full article

This review systematically examines the latest research progress and diverse applications of direct evaporative cooling and indirect evaporative cooling across five core sectors: industrial and energy engineering, the built environment, agriculture and food preservation, transportation and aerospace, and emerging interdisciplinary fields. While existing research often focuses on single application silos, this paper distills two common foundational challenges: climate adaptability and water resource management. Quantitative analysis demonstrates significant performance gains. Hybrid systems in data centers increase annual energy-saving potential by 14% to 41%, while precision root-zone cooling in greenhouses boosts crop yields by 13.22%. Additionally, passive cooling blankets reduce post-harvest losses by up to 45%, and integrated desalination cycles achieve 18.64% lower energy consumption compared to conventional systems. Innovative strategies to overcome humidity bottlenecks include vacuum-assisted membranes, advanced porous materials, and hybrid radiative-evaporative systems. The paper also analyzes sustainable water management through rainwater harvesting, seawater utilization, and atmospheric water capture. Collectively, these advancements provide a comprehensive framework to guide the future development and commercialization of sustainable cooling technologies. Full article

The global food industry is undergoing a major shift driven by increasing consumer demand for clean-label and naturally preserved foods. Fresh pasta is highly vulnerable to fungal damage because of its high water activity (a_w > 0.85), typically ranging between 0.92 and 0.97, moderate to near-neutral pH (around 5.0–7.0), and nutrient-rich composition, all of which create favorable conditions for fungal growth during refrigeration, mainly by genera such as Penicillium and Aspergillus. Fungal contamination results in significant economic losses due to reduced product quality and poses potential health risks associated with mycotoxin production. Although conventional chemical preservatives are relatively effective in preventing spoilage, their use conflicts with clean-label trends and faces growing regulatory and consumer scrutiny. In this context, antifungal lactic acid bacteria (LAB) have emerged as a promising natural alternative for biopreservation. Several LAB strains, particularly those isolated from cereal-based environments (e.g., Lactobacillus plantarum and L. amylovorus), produce a broad spectrum of antifungal metabolites, including organic acids, phenylalanine-derived acids, cyclic dipeptides, and volatile compounds. These metabolites act synergistically to inhibit fungal growth through multiple mechanisms, such as cytoplasmic acidification, energy depletion, and membrane disruption. However, the application of LAB in fresh pasta production requires overcoming several challenges, including the scale-up from laboratory to industrial processes, the maintenance of metabolic activity within the complex pasta matrix, and the preservation of desirable sensory attributes. Furthermore, regulatory approval (GRAS/QPS status), economic feasibility, and effective consumer communication are crucial for successful commercial implementation. This review analyzes studies published over the past decade on fresh pasta spoilage and the antifungal activity of lactic acid bacteria (LAB), highlighting the progressive refinement of LAB-based biopreservation strategies. The literature demonstrates a transition from early descriptive studies to recent research focused on strain-specific mechanisms and technological integration. Overall, LAB-mediated biopreservation emerges as a sustainable, clean-label approach for extending the shelf life and safety of fresh pasta, with future developments relying on targeted strain selection and synergistic preservation strategies. Full article