Search Results (8,539)

As a cornerstone of China’s energy infrastructure, the coal mining industry relies heavily on the stability of its underground roadways, where the support of soft rock formations presents a critical and persistent technological challenge. This challenge arises primarily from the high content of expansive clay minerals and well-developed micro-fractures within soft rock, which collectively undermine the effectiveness of conventional support methods. To address the soft rock control problem in China’s Longdong Mining Area, an integrated material–structure control approach is developed and validated in this study. Based on the engineering context of the 3205 material gateway in Xin’an Coal Mine, the research employs a combined methodology of micro-mesoscopic characterization (SEM, XRD), theoretical analysis, and field testing. The results identify the intrinsic instability mechanism, which stems from micron-scale fractures (0.89–20.41 μm) and a high clay mineral content (kaolinite and illite totaling 58.1%) that promote water infiltration, swelling, and strength degradation. In response, a novel synergistic technology was developed, featuring a high-performance grouting material modified with redispersible latex powder and a tiered thick anchoring system. This technology achieves microscale fracture sealing and self-stress cementation while constructing a continuous macroscopic load-bearing structure. Field verification confirms its superior performance: roof subsidence and rib convergence in the test section were reduced to approximately 10 mm and 52 mm, respectively, with grouting effectively sealing fractures to depths of 1.71–3.92 m, as validated by multi-parameter monitoring. By integrating microscale material modification with macroscale structural optimization, this study provides a systematic and replicable solution for enhancing the stability of soft rock roadways under demanding geo-environmental conditions. Soft rock roadways, due to their characteristics of being rich in expansive clay minerals and having well-developed microfractures, make traditional support difficult to ensure roadway stability, so there is an urgent need to develop new active control technologies. This paper takes the 3205 Material Drift in Xin’an Coal Mine as the engineering background and adopts an integrated method combining micro-mesoscopic experiments, theoretical analysis, and field tests. The soft rock instability mechanism is revealed through micro-mesoscopic experiments; a high-performance grouting material added with redispersible latex powder is developed, and a “material–structure” synergistic tiered thick anchoring reinforced load-bearing technology is proposed; the technical effectiveness is verified through roadway surface displacement monitoring, anchor cable axial force monitoring, and borehole televiewer. The study found that micron-scale fractures of 0.89–20.41 μm develop inside the soft rock, and the total content of kaolinite and illite reaches 58.1%, which is the intrinsic root cause of macroscopic instability. In the test area of the new support scheme, the roof subsidence is about 10 mm and the rib convergence is about 52 mm, which are significantly reduced compared with traditional support; grouting effectively seals rock mass fractures in the range of 1.71–3.92 m. This synergistic control technology achieves systematic control from micro-mesoscopic improvement to macroscopic stability by actively modifying the surrounding rock and optimizing the support structure, significantly improving the stability of soft rock roadways. Full article

Water quality monitoring faces increasing challenges due to accelerating industrialization and urbanization, demanding accurate, real-time, and reliable prediction technologies. This study presents a novel ensemble learning framework integrating Gaussian Process Regression, Support Vector Regression, and Random Forest algorithms for high-precision water quality pH prediction. The research utilized a comprehensive spatiotemporal dataset, comprising 11 water quality parameters from 37 monitoring stations across Georgia, USA, spanning 705 days from January 2016 to January 2018. The ensemble model employed a dynamic weight allocation strategy based on cross-validation error performance, assigning optimal weights of 34.27% to Random Forest, 33.26% to Support Vector Regression, and 32.47% to Gaussian Process Regression. The integrated approach achieved superior predictive performance, with a mean absolute error of 0.0062 and coefficient of determination of 0.8533, outperforming individual base learners across multiple evaluation metrics. Statistical significance testing using Wilcoxon signed-rank tests with a Bonferroni correction confirmed that the ensemble significantly outperforms all individual models (p < 0.001). Comparison with state-of-the-art models (LightGBM, XGBoost, TabNet) demonstrated competitive or superior ensemble performance. Comprehensive ablation experiments revealed that Random Forest removal causes the largest performance degradation (+4.43% MAE increase). Feature importance analysis revealed the dissolved oxygen maximum and conductance mean as the most influential predictors, contributing 22.1% and 17.5%, respectively. Cross-validation results demonstrated robust model stability with a mean absolute error of 0.0053 ± 0.0002, while bootstrap confidence intervals confirmed narrow uncertainty bounds of 0.0060 to 0.0066. Spatiotemporal analysis identified station-specific performance variations ranging from 0.0036 to 0.0150 MAE. High-error stations (12, 29, 33) were analyzed to distinguish characteristics, including higher pH variability and potential upstream pollution influences. An integrated software platform was developed featuring intuitive interface, real-time prediction, and comprehensive visualization tools for environmental monitoring applications. Full article

The application of bioactive nanoemulsions in the meat industry has attracted great interest due to their ability to improve the stability, bioavailability, and functionality of bioactive compounds, contributing to the extension of the shelf-life of highly perishable products, such as sausages and meat patties. Thus, this review provides a critical analysis of the application of nanoemulsions in sausages and meat patties, with emphasis on their mechanisms of action, formulation strategies, and performance in improving oxidative stability and microbial safety. Nanoemulsions, typically characterized by droplet sizes below 200 nm, increase interfacial area and penetration into meat matrices, resulting in reductions of 30–60% in lipid oxidation markers and decreases of 1–2 log CFU/g in spoilage and pathogenic microorganisms. Preparation and stabilization approaches, including high-energy and low-energy methods, are summarized, and the influence of nanoemulsion characteristics on texture, color, pH, and sensory perception is discussed. Particular attention is given to technological barriers, such as scale-up feasibility, stability during processing and storage, interactions with meat proteins, as well as regulatory and labeling considerations related to nano-enabled foods. Overall, the current evidence indicates that NEs represent a viable strategy to replace synthetic preservatives while supporting clean-label product development; however, further research on safety assessment, optimal dosing, and consumer acceptance is still required for broader industrial implementation. Full article

Shipping is a high-energy-intensive sector and a major source of climate-relevant and harmful air pollutant emissions. In response to growing environmental concerns, the sector has been subject to increasingly stringent regulations, promoting the uptake of alternative fuels and emission control technologies. Accurate and diverse emission factors (EFs) are critical for quantifying shipping’s contribution to current emission inventories and projecting future developments under different policy scenarios. This study advances the development of load-dependent EFs for ships by incorporating alternative fuels, biofuels and emission control technologies. The methodology combines statistical analysis of data from an extensive literature review with newly acquired on-board emission measurements, including two-stroke propulsion engines and four-stroke auxiliary units. To ensure broad applicability, the updated EFs are expressed as functions of engine load and are categorized by engine and fuel type, covering conventional marine fuels, liquified natural gas, methanol, ammonia and biofuels. The results provide improved resolution of shipping emissions and insights into the role of emission control technologies, supporting robust, up-to-date emission models and inventories. This work contributes to the development of effective strategies for sustainable maritime transport and supports both policymakers and industry stakeholders in their decarbonization efforts. Full article

Monoacylglycerols (MAGs) are significant intermediate byproducts in the hydrolysis of oils and fats. The accumulation of MAGs not only reduces the quality and purity of the final products in biodiesel production and edible oil refining but also poses challenges for downstream separation processes. Therefore, the development of efficient biocatalysts for the specific MAG conversion is of great industrial importance. The lipase from Aspergillus oryzae (AOL) has shown potential for lipid modification; however, the wild-type enzyme (WT) suffers from poor solubility, tendency to aggregate, and low specific activity towards MAGs in aqueous systems, which severely restricts its practical application. In this study, a combinatorial protein engineering strategy was employed to overcome these limitations. We integrated fusion protein technology with rational design to enhance both the functional expression and catalytic efficiency of AOL. Firstly, the superfolder green fluorescent protein (sfGFP) was fused to the N-terminus of AOL. The results indicated that the sfGFP fusion tag significantly improved the solubility and stability of the enzyme, preventing the formation of inclusion bodies. The fusion protein sfGFP-AOL exhibited a MAG conversion rate of approximately 65%, confirming the positive impact of the fusion tag on enzyme developability. To further boost catalytic performance, site-directed mutagenesis was performed based on structural analysis. Among the variants, the mutant sfGFP-Y92Q emerged as the most potent candidate. In the MAG conversion, sfGFP-Y92Q achieved a conversion rate of 98%, which was not only significantly higher than that of sfGFP-AOL but also outperformed the widely used commercial immobilized lipase, Novozym 435 (~54%). Structural modeling and docking analysis revealed that the Y92Q mutation optimized the geometry of the active site. The substitution of Tyrosine with Glutamine at position 92 likely enlarged the substrate-binding pocket and altered the local electrostatic environment, thereby relieving steric hindrance and facilitating the access of the bulky MAG substrate to the catalytic center. In conclusion, this work demonstrates that the synergistic application of sfGFP fusion and rational point mutation (Y92Q) can dramatically transform the catalytic properties of AOL. The engineered sfGFP-Y92Q variant serves as a robust and highly efficient biocatalyst for MAG degradation. Its superior performance compared to commercial standards suggests immense potential for cost-effective applications in the bio-manufacturing of high-purity fatty acids and biodiesel, offering a greener alternative to traditional chemical processes. Full article

In the context of the “Dual Carbon” goals, achieving synergistic development between digitalization and green transformation in the coal power industry is essential for ensuring a just and sustainable energy transition. The core scientific problem addressed is the lack of a robust quantitative tool to evaluate the comprehensive performance of diverse transition scenarios in a complex environment characterized by multi-objective trade-offs and high uncertainty. This study establishes a sustainability-oriented four-dimensional performance evaluation system encompassing 22 indicators, covering Synergistic Economic Performance, Green-Digital Strategy, Synergistic Governance, and Technology Performance. Based on this framework, a Fuzzy DEMATEL–MultiMOORA–Borda integrated decision model is proposed to evaluate seven transition scenarios. The computational framework utilizes the Interval Type-2 Fuzzy DEMATEL (IT2FS-DEMATEL) method for robust causal analysis and weight determination, addressing the inherent subjectivity and vagueness in expert judgments. The model integrates MultiMOORA with Borda Count aggregation for enhanced ranking stability. All model calculations were implemented using Matlab R2022a. Results reveal that Carbon Price and Digital Hedging Capability (C13) and Digital-Driven Operational Efficiency (C43) are the primary drivers of synergistic performance. Among the scenarios, P3 (Digital Twin Empowerment and New Energy Co-integration) achieves the best overall performance (score: 0.5641), representing the most viable pathway for balancing industrial efficiency and environmental stewardship. Robustness tests demonstrate that the proposed model significantly outperforms conventional approaches such as Fuzzy AHP (Analytic Hierarchy Process) and TOPSIS under weight perturbations. Sensitivity analysis further identifies Financial Return (C44) and Green Transformation Marginal Economy (C11) as critical factors for long-term policy effectiveness. This study provides a data-driven framework and a robust decision-support tool for advancing the coal power industry’s low-carbon, intelligent, and resilient transition in alignment with global sustainability targets. Full article

As a natural refrigerant, CO₂ shows significant potential in sustainable thermal engineering due to its environmental safety and economic viability. While the transcritical CO₂ cycle demonstrates strong performance in heating, low-temperature applications, and integration with renewable energy sources, its widespread adoption is hindered by key challenges at the application level. These include: high sensitivity of system efficiency to operating conditions, which creates an “efficiency hump” and narrows the optimal operating window; increased component costs and technical challenges for key devices such as multi-channel valves due to high-pressure requirements; and complex system control with limited intelligent solutions currently integrated. Despite these challenges, the transcritical CO₂ cycle holds unique value in enabling synergistic energy conversion. Its ability to efficiently match and cascade different energy grades makes it particularly suitable for data center cooling, industrial combined cooling and heating, and solar–thermal hybrid systems, positioning it as an indispensable technology in future low-carbon energy systems. To fully realize its potential, development efforts must focus on high-value applications and key technological breakthroughs. Priority should be given to demonstrating its use in fields where it holds a distinct advantage, such as low-temperature refrigeration and high-temperature industrial heat pumps, to establish commercially viable models. Concurrently, core technologies—including adaptive intelligent control algorithms, high-efficiency expanders, and cost-effective pressure-resistant components—must be advanced. Supportive policies, encompassing energy efficiency standards, safety regulations, and fiscal incentives, will be essential to facilitate the transition from demonstration projects to widespread industrial adoption. Full article

Urban agglomerations are concentrated production areas of new-quality productivity (NQP), and developing NQP is an inevitable requirement and obligation to promote the high-quality development of urban agglomerations. It is of great concern whether green finance (GF) can serve as a catalyst in promoting the formation and development of NQP in urban agglomerations. This study selects panel data from 41 cities in the Yangtze River Delta urban agglomeration spanning 2011–2023 to construct a comprehensive indicator system for NQP based on the composition, quality, and function of productive factors in the urban agglomeration, and explores the impact effects, mechanisms of action, spatial spillover effects, and heterogeneity of GF on the development of NQP using a two-way fixed-effects model, an intermediary effect model, and a spatial Durbin model (SDM). The empirical results indicate the following: (1) GF can significantly promote the development of NQP in the Yangtze River Delta urban agglomeration, and there is a significant positive spatial spillover effect. The above conclusions remain valid after a series of robustness tests and endogeneity treatments. (2) The mechanism tests find that industrial structure upgrading and environmental regulation play positive mediating roles in GF’s promotion of NQP development in urban agglomerations. (3) The impact of GF on NQP exhibits significant heterogeneity. In regions with higher levels of economic and financial development, as well as a higher degree of marketization, the promotional effect of GF on NQP is more pronounced. In terms of city size and geographical location, the empowering effect and spatial spillover effect of GF on NQP are more evident in prefecture-level cities and the northern plain area of the Yangtze River Delta. Therefore, it is recommended to implement differentiated GF policies to promote the development of NQP in the Yangtze River Delta urban agglomeration through regional cooperation, green technology innovation, industrial transformation and upgrading, and environmental regulation. Full article

Megacity clusters are the key battlegrounds for carbon emission reduction in China, and the polycentric spatial structure of these clusters has a profound impact on their carbon emission intensity. This paper focuses on five major megacity clusters: the Beijing–Tianjin–Hebei (BTH), Yangtze River Delta (YRD), Pearl River Delta (PRD), the middle reaches of the Yangtze River (MRYR), and the Chengdu–Chongqing (CY) City Clusters. We construct an inter-period panel dataset spanning from 2002 to 2023 and utilize an index of polycentric spatial structure, which equally considers both morphology and functionality. A fixed-effects model is employed, and the Lind–Mehlum U-shape test is applied to identify the nonlinear relationship. Additionally, a two-step approach is used to examine the mediating effect of industrial agglomeration, while interaction terms help identify the moderating effects of technological innovation and transport infrastructure. The results indicate a significant U-shaped relationship between the polycentric structure of megacity clusters and carbon emission intensity. When the polycentric spatial structure index reaches a specific threshold, carbon emission intensity is minimized, suggesting that a moderate degree of polycentricity is most conducive to carbon reduction. Mechanism analysis reveals that industrial agglomeration functions as a significant mediator, whereas technological innovation and transport infrastructure serve as critical moderators in this relationship. Based on these findings, we propose several policy recommendations: to guide the moderate adjustment of the polycentric structure of city clusters with stage-specific targets, optimize the mechanism of industrial synergy and transfer, differentiate the allocation of innovation resources, and achieve a fine-tuned alignment between the transport system and spatial structure. These measures will support the high-quality, low-carbon transformation of city clusters. Full article

Digitalization is widely heralded as a catalyst for growth, yet its role in achieving the United Nations’ Sustainable Development Goal 10 (Reduced Inequalities) remains deeply contested. Moving beyond linear assumptions of “digital dividends,” this study adopts a complex socio-technical systems perspective to unravel the configurational pathways linking digitalization to national income inequality. We analyze a high-quality balanced panel of 56 major economies from 2012 to 2022. Employing Panel Fuzzy-Set Qualitative Comparative Analysis (Panel fsQCA) and Necessary Condition Analysis (NCA), this study proposes an evidence-based typology of digitalization-inequality pathways. We reveal that the impact of digital transformation is asymmetric and contingent on geo-economic contexts. NCA identifies Digital Infrastructure, Innovation, and Governance as necessary “bottlenecks” for social equity. Sufficiency analysis uncovers three distinct sustainable development modes: an “Open Innovation Mode” in affluent small economies, driven by global integration and technological frontiers; a “Governance-Regulated Industry Mode” in major economies, where strong state capacity regulates digital industrial scale; and an “Open Niche Mode” for transition economies, leveraging openness to bypass domestic structural deficits. Conversely, we identify a critical “Hollow Governance Trap” in the Global South, where digital governance efforts fail to reduce inequality in the absence of real industrial and infrastructural foundations. These findings challenge one-size-fits-all policies, suggesting that bridging the global digital divide requires context-specific strategies—ranging from synergistic integration to asymmetric breakthroughs—that align digital investments with institutional capacity. Full article

Rare-earth fluoride nanocrystals have emerged as promising scintillator materials due to their excellent optical properties, environmental stability, and ease of fabrication into flexible screens. However, their practical application is often hindered by persistent afterglow, a phenomenon caused by deep trap states that capture and slowly release charge carriers after X-ray excitation, which leads to signal overlap and image artifacts in dynamic imaging scenarios. This study addresses this critical challenge by developing Ce³⁺/Tb³⁺ co-doped NaLuF₄ nanoscintillators with suppressed afterglow. By introducing Ce³⁺ions as dopants into the Tb³⁺-activated NaLuF₄ host, we successfully quenched the characteristic long afterglow without compromising the intrinsic radioluminescence efficiency of the Tb³⁺ centers. The optimized nanocrystals were subsequently incorporated into a poly (vinyl alcohol) matrix to fabricate transparent, high-loading composite scintillator films. The resulting films exhibit negligible afterglow, maintain high spatial resolution, and demonstrate excellent radiation stability. This work presents an effective strategy for suppressing afterglow in rare-earth fluoride scintillators through targeted ion doping, which paves the way for their application in real-time, high-quality X-ray imaging technologies such as medical diagnostics and industrial inspection. 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

The global clean energy transition requires power conversion technologies that combine high efficiency, operational flexibility, and reduced environmental impact over their entire service life. Solid-state transformers (SSTs) have emerged as a promising alternative to conventional line-frequency transformers, offering bidirectional power flow, high-frequency isolation, and advanced control capabilities that support renewable integration and electrified infrastructures. This paper presents a comparative life cycle assessment (LCA) of conventional transformers and SSTs across representative power-system applications, including residential and industrial distribution networks, electric vehicle fast-charging infrastructure, and transmission–distribution interface substations. The analysis follows a cradle-to-grave approach and is based on literature-derived LCA data, manufacturer specifications, and harmonized engineering assumptions applied consistently across all case studies. The results show that, under identical assumptions, SST-based solutions are associated with indicative lifecycle CO₂ emission reductions of approximately 10–30% compared to conventional transformers, depending on power rating and operating profile (≈90–1000 t CO₂ over 25 years across the four cases). These reductions are primarily driven by lower operational losses and reduced material intensity, while additional system-level benefits arise from enhanced controllability and compatibility with renewable-rich and hybrid AC/DC grids. The study also identifies key challenges that influence the sustainability performance of SSTs, including higher capital cost, thermal management requirements, and the long-term reliability of power-electronic components. Overall, the results indicate that SSTs represent a relevant enabling technology for future low-carbon power systems, while highlighting the importance of transparent assumptions and lifecycle-oriented evaluation when comparing emerging grid technologies. Full article

Enzyme technology, characterized by high efficiency, environmental compatibility, and precise controllability, has become a pivotal biocatalytic approach for quality enhancement and nutritional improvement in modern food industries. This review summarizes recent advances and underlying mechanisms of enzyme applications in food processing optimization, nutritional enhancement, and functional food development. In terms of process optimization, enzymes such as transglutaminase, laccase, and peroxidase enhance protein crosslinking, thereby markedly improving the texture and stability of dairy products, meat products, and plant-based protein systems. Proteases and lipases play essential roles in flavor development, maturation, and modulation of sensory attributes. From a nutritional perspective, enzymatic hydrolysis significantly improves the bioavailability of proteins, minerals, and dietary fibers, while simultaneously degrading antinutritional factors and harmful compounds, including phytic acid, tannins, food allergens, and acrylamide, thus contributing to improved food safety and nutritional balance. With respect to functional innovation, enzyme-directed production of bioactive peptides has demonstrated notable antihypertensive, antioxidant, and immunomodulatory activities. In addition, enzymatic synthesis of functional oligosaccharides and rare sugars, glycosylation-based modification of polyphenols, and enzyme-assisted extraction of plant bioactive compounds provide novel strategies and technological support for the development of functional foods. Owing to their high specificity and eco-friendly nature, enzyme technologies are driving food and nutrition sciences toward more precise, personalized, and sustainable development pathways. Despite these advances, critical research gaps remain, particularly in the limited mechanistic understanding of enzyme behavior in complex food matrices, the insufficient integration of multi-omics data with enzymatic process design, and the challenges associated with translating laboratory-scale enzymatic strategies into robust, data-driven, and scalable industrial applications. Full article

The automotive industry’s shift to a Circular Economy for global sustainability is vital, but it faces challenges when establishing efficient Reverse Supply Chains. Reverse Supply Chain implementation is dependent on multiple barriers and enablers, including eco-nomic, managerial, technological, regulatory, and social domains, thus making single-factor solutions ineffective. The purpose of this review is to conduct a systematic literature review to understand how these interconnected barriers and enablers can collectively shape Reverse Supply Chain implementation and performance, specifically within the automotive sector, which remains little known. The PRISMA framework was utilised, which resulted in 129 peer-reviewed articles being selected for review. Findings showed that the literature focuses primarily on Electric Vehicle batteries within developing economies, particularly China. Reverse Supply Chain implementation is governed not only by isolated barriers but by complex systemic interdependencies between enablers as well. This complex inter-relationship between barriers and enablers can be categorised into five key dimensions: economic and financial; managerial and organisational; technological and infrastructural; policy and regulatory; and market and social. The study reveals two systemic patterns driving the transition: technology–policy interdependence and the conflicting relationship between large-scale production and value extraction. Our findings also presented a research agenda focusing on strategic value creation through material streams of automotive electronics, plastic, and composites with high potential value, and further insights are needed in regions such as the Middle East, Oceania, and the Americas. Organisations should consider Reverse Supply Chain as a strategic approach for securing critical material supplies, while policymakers could leverage the use of digital tools as the foundational infrastructure for subsidies allocation and prevent fraud. Full article