Search Results (171)

The growing demand for air connectivity, coupled with the forecasted increase in passengers by 2040, implies an exigency in the aviation sector to adopt sustainable approaches for net zero emission by 2050. Sustainable Aviation Fuel (SAF) is currently the most promising short-term solution; however, ensuring its overall sustainability depends on reducing the life cycle carbon footprints. A key challenge prevails in hydrogen usage as a reactant for the approved ASTM routes of SAF. The processing, conversion and refinement of feed entailing hydrodeoxygenation (HDO), decarboxylation, hydrogenation, isomerisation and hydrocracking requires substantial hydrogen input. This hydrogen is sourced either in situ or ex situ, with the supply chain encompassing renewables or non-renewables origins. Addressing this hydrogen usage and recognising the emission implications thereof has therefore become a novel research priority. Aside from the preferred adoption of renewable water electrolysis to generate hydrogen, other promising pathways encompass hydrothermal gasification, biomass gasification (with or without carbon capture) and biomethane with steam methane reforming (with or without carbon capture) owing to the lower greenhouse emissions, the convincing status of the technology readiness level and the lower acidification potential. Equally imperative are measures for reducing hydrogen demand in SAF pathways. Strategies involve identifying the appropriate catalyst (monometallic and bimetallic sulphide catalyst), increasing the catalyst life in the deoxygenation process, deploying low-cost iso-propanol (hydrogen donor), developing the aerobic fermentation of sugar to 1,4 dimethyl cyclooctane with the intermediate formation of isoprene and advancing aqueous phase reforming or single-stage hydro processing. Other supportive alternatives include implementing the catalytic and co-pyrolysis of waste oil with solid feedstocks and selecting highly saturated feedstock. Thus, future progress demands coordinated innovation and research endeavours to bolster the seamless integration of the cutting-edge hydrogen production processes with the SAF infrastructure. Rigorous techno-economic and life cycle assessments, alongside technological breakthroughs and biomass characterisation, are indispensable for ensuring scalability and sustainability. Full article

Water loss during storage is a major cause of postharvest quality deterioration in cucumber, yet existing methods to monitor hydration are often destructive or require expensive instrumentation. We developed a low-cost, non-destructive approach for estimating fruit relative water content (RWC) using visible-light color imaging combined with an ensemble machine-learning model (Random Forest). A total of 1200 fruits were greenhouse-grown, harvested at market maturity, and equally divided between optimal and ambient storage temperature (10 and 25 °C, respectively). Digital images were acquired at harvest and at 7 d intervals during storage, and color parameters from four standard color systems (RGB, CMYK, CIELAB, HSV) were extracted separately for the neck, mid, and blossom regions as well as for the whole fruit. During storage, fruit RWC decreased from 100% (fully hydrated condition) to 15.3%, providing a broad dynamic range for assessing color–hydration relationships. Among the 16 color features evaluated, the mean cyan component (μC) of the CMYK space showed the strongest relationship with measured RWC (R² up to 0.70 for whole-fruit averages), reflecting the cyan region’s heightened sensitivity to dehydration-induced changes in pigments, cuticle properties and surface scattering. The Random Forest regression model trained on these features achieved a higher predictive accuracy (R² = 0.89). Predictive accuracy was also consistently higher when μC was calculated over the entire fruit surface rather than for individual anatomical regions, indicating that whole-fruit color information provides a more robust hydration signal than region-specific measurements. Our findings demonstrate that simple visible-range imaging coupled with ensemble learning can provide a cost-effective, non-invasive tool for monitoring postharvest hydration of cucumber fruit, with direct applications in quality control, shelf-life prediction and waste reduction across the fresh-produce supply chain. Full article

Technological decoupling, geopolitical tensions, and carbon neutrality pressures have created systemic risks, making supply chain security a global concern. Digital-driven new quality productivity (NQP), as a key driver of supply chain upgrading, plays a crucial role in restructuring modern supply chain systems and enhancing resilience. Based on data from Chinese supply chain data from listed companies (2012–2023), this study integrates enterprise-level NQP and applies complex network methods and the Hadamard product model to analyze how NQP regulates supply chain resilience. The results show that NQP affects network resilience through three nonlinear coupling mechanisms: strengthening defense at fixed points, promoting recovery through chain reinforcement, and enhancing sustainability via network expansion. Its impact is stage-dependent—showing partial vulnerability during early technology diffusion but significantly improving overall resilience at maturity, with structural imbalance remaining a potential risk. This study provides theoretical and practical insights for optimizing supply chain structures and improving risk prevention and collaborative capabilities. Full article

The spread of epidemic-associated panic information through online social platforms, as well as the allocation and utilization of therapeutic defensive resources in reality, directly influences the transmission of infectious diseases. Moreover, how to reasonably allocate resources to effectively suppress epidemic spread remains a problem that requires further investigation. To address this, we construct a coupled three-layer network framework to explore the complex co-evolutionary mechanisms among false panic information, therapeutic defensive resource transmission, and disease propagation. In the model, individuals can obtain therapeutic defensive resources either through centralized distribution by government agencies or through interpersonal assistance, while the presence of false panic information reduces the willingness of neighbors to share resources. Using the microscopic Markov chain approach, we formulate the dynamical equations of the system and analyze the epidemic threshold. Furthermore, systematic simulation analyses are carried out to evaluate how panic information, resource-sharing willingness, centralized distribution strategies, and resource effectiveness affect epidemic prevalence and threshold levels. For example, under a representative parameter setting, the infection prevalence decreases from 0.18 under the random allocation strategy to 0.03 when resources are allocated exclusively to infected individuals. Moreover, increasing the total supply of resources under high treatment efficiency raises the epidemic threshold by approximately 2.5 times, effectively delaying the outbreak. These quantitative results highlight the significant role of allocation strategies, resource supply, and treatment efficiency in suppressing epidemic transmission. Full article

The unimolecular alkene elimination reaction class of fatty acid alkyl esters (FAAEs) is a crucial component in the low-temperature combustion mechanism for biodiesel fuels. However, thermo-kinetic parameters for this reaction class are scarce, particularly for the large-size molecules over four carbon atoms and intricate branched-chain configurations. Thermo-kinetic parameters are essential for constructing a reaction mechanism, which can be used to clarify the chemical nature of combustion for biodiesel fuels. In this paper, the B3LYP method, in conjunction with the 6-311G(d,p) basis set, is used to carry out geometry optimization of the species participating in the reactions. Frequency calculations are further executed at the same level of theory. Additionally, coupled with the 6-311G(d,p) basis set, the B3LYP method acts as the low-level ab initio approach, while the Gaussian-4 (G4) composite method serves as the high-level ab initio approach within the isodesmic reaction correction scheme. The CCSD(T) approach is employed to verify the consistency of the electronic energy ascertained through the G4 method. The isodesmic reaction method (IRM) is used to obtain the energy barriers and reaction enthalpies for unimolecular alkene elimination reaction class of FAAEs. Based on the reaction class transition state theory (RC-TST), high-pressure-limit rate coefficients were computed, with asymmetric Eckart tunneling corrections applied across 500~2000 K temperature range. Rate rules at the high-pressure-limit are obtained through the averaging of rate coefficients from a representative collection of reactions, which incorporate substituent groups and carbon chains with different sizes and lengths. Ultimately, the energy barriers, reaction enthalpies, and rate rules at the high-pressure-limit and kinetic parameters expressed as (A, n, E) are supplied for developing the low-temperature combustion mechanism of biodiesel fuels. Full article

As native bovine whey (WHEY) poses environmental concerns as a high-water-content by-product, this trial aimed at assessing the effectiveness of a thermal–mechanical microparticulation coupled with a fermentative process to concentrate it into a high-protein soft dairy cream. Compared to native whey, in microparticulated (MPW) and fermented (FMPW) matrices, there was a significant increase in proteins (from 0.7 to 8.8%) and lipids (from 0.3 to 1.3%), and a more brilliant yellowness colour. A factorial discriminant analysis (FDA) showed that FMPW had a higher content of saturated fatty acid (SFA) and some specific polyunsaturated fatty acid (PUFA) n-6, and also identified C14:0, C18:1, C18:1 t-11, C18:2 n-6, and C18:3 n-6 as informative biomarkers of microparticulation and fermentative treatments. The SDS-PAGE indicated no effects on the protein profile but indicated its rearrangement into high molecular weight aggregates. Z-sizer and transmission electron microscopy analyses confirmed a different supramolecular structure corresponding to a higher variability and greater incidence of very large molecular aggregates, suggesting that MPW could be accounted as a colloidal matrix that may have similar ball-bearing lubrication properties. Microparticulation of whey could facilitate its circularity into the dairy supply chain through its re-generation from a waste into a high-value fat replacer for dairy-based food production. Full article

This study examines industrial digitalization, with a particular focus on the transformation from Industry 4.0 to Industry 5.0. The research is based on a database of 1441 Scopus-indexed articles, which forms the basis of a systematic literature review and bibliometric network analysis. The articles were ranked using Global Citation Score (GCS), followed by Co-Coupling Network (CCN) within VosViewer, the method to create arrays. The arrays were analyzed based on the connection strengths of the citations in them. Next, we performed Burst Detection using the CiteSpace app. Finally, the most relevant keywords, determined in the Burst Detection, were used for Co-Occurrence Network (CONK), with which we could create new arrays and analyze them. By connecting the various, fragmented scientific findings, our results highlight that digital twins, artificial intelligence, supply chain resilience and the Internet of Things are the focus of Industry 4.0, i.e., the technological side is dominant. In contrast, Industry 5.0 places employees at the center. It also emphasizes the analysis of human–machine interaction and the importance of green digital sustainability. The results provide a comprehensive picture of how decision-makers, researchers, and professionals can interpret a changing mindset and apply it as practical advice. Full article

This study examines the impact of corporate social responsibility (CSR) decoupling on investment efficiency through the lens of systems thinking, using 34,143 firm-year observations from Chinese listed firms between 2009 and 2022. CSR decoupling is conceptualized as a systemic misalignment between two interrelated governance subsystems: the externally facing legitimacy subsystem and the internally embedded strategic action subsystem. Drawing on legitimacy theory and systems thinking, we find that CSR decoupling significantly reduces investment efficiency, primarily through overinvestment, with no consistent evidence of underinvestment. Furthermore, this effect is amplified in tightly coupled supply chain systems and is especially pronounced in foreign-owned firms. The findings contribute to the integration of systems thinking into CSR and corporate governance research, emphasizing the role of structural coupling strength in shaping the consequences of symbolic–substantive misalignment. The study also offers managerial and policy implications for improving the alignment between external CSR communication and internal strategic execution to enhance investment discipline and long-term value creation. Full article

Biomass is a key renewable resource for advancing sustainable and circular energy systems. In contrast to prior reviews that predominantly emphasized well-established biomass types and conventional conversion technologies, this work offers a comparative synthesis that underscores underutilized feedstocks and emerging valorization pathways, providing a strategic perspective for sustainable process development. This review critically examines the current state of high-value-added bioproducts derived from biomass, focusing on their relevance to climate mitigation and resource efficiency. It explores sustainable process design strategies that enhance the environmental and economic performance of biomass conversion. Particular attention is given to recent advances in process intensification, including novel reactor configurations and heat integration techniques. The integration of sustainability assessment tools and multi-objective optimization approaches is analyzed to support data-driven decision-making. Multi-product biorefineries are discussed as central platforms for valorizing diverse feedstocks, supported by emerging models for supply chain integration. Present limitations such as feedstock heterogeneity, infrastructure constraints, and energy coupling challenges are reviewed, along with new opportunities in digitalization, modularization, and policy support. The novelty of this work lies in its cross-sectional synthesis of technologies, methodologies, and system-level strategies, offering a unified framework to unlock the full potential of biomass as a strategic vector for sustainable process development. Full article

Vertical alliances within agricultural supply chains serve as critical institutional vehicles for deepening triple-sector integration (primary–secondary–tertiary) in rural economies, driving agricultural modernization, and advancing rural revitalization. However, sustaining alliance stability constitutes a complex dynamic process wherein inadequate stakeholder engagement and collaborative failures frequently precipitate alliance instability or even dissolution. Existing scholarship exhibits limited systematic examination of the micro-mechanisms and regulatory pathways through which multi-agent strategic interactions affect alliance stability from a dynamic evolutionary perspective. To address this gap, this research focuses on China’s core agricultural innovation vehicle—the Agricultural Industrialization Consortium—and examines the tripartite structure of “Leading Enterprise–Family Farm–Integrated Agricultural Service Providers.” We construct a tripartite evolutionary game model to systematically analyze (1) the influence mechanisms governing cooperative strategy selection, and (2) the regulatory effects of key parameters on consortium stability through strategic stability analysis and multi-scenario simulations. Our key findings are as follows: Four strategic equilibrium scenarios emerge under specific conditions, with synergistic parameter optimization constituting the fundamental driver of alliance stability. Specific mechanisms are as follows: (i) compensation mechanisms effectively mobilize leading enterprises under widespread defection, though excessive penalties erode reciprocity principles; (ii) strategic reductions in benefit sharing ratios coupled with moderate factor value-added coefficients are critical for reversing leading enterprises’ defection; (iii) dual adjustment of cost sharing and benefit sharing coefficients is necessary to resolve bilateral defection dilemmas; and (iv) synchronized optimization of compensation, cost sharing, benefit sharing, and value-added parameters represents the sole pathway to achieving stable (1,1,1) full-cooperation equilibrium. Critical barriers include threshold effects in benefit sharing ratios (defection triggers when shared benefits > cooperative benefits) and the inherent trade-off between penalty intensity and alliance resilience. Consequently, policy interventions must balance immediate constraints with long-term cooperative sustainability. This study extends the application of evolutionary game theory in agricultural organization research by revealing the micro-level mechanisms underlying alliance stability and providing a novel analytical framework for addressing the ‘strategy–equilibrium’ paradox in multi-agent cooperation. Our work not only offers new theoretical perspectives and methodological support for understanding the dynamic stability mechanisms of agricultural vertical alliances but also establishes a substantive theoretical foundation for optimizing consortium governance and promoting long-term alliance stability. Full article

The mutagenic potential of coffee by-products, including Coffea leaves, blossoms, cherries, and silverskin, was studied using thin-layer chromatography (TLC) coupled with the recent planar Ames bioassay via pH indicator endpoint. The 2LabsToGo-Eco allowed for the separation and detection of mutagens in complex samples. Hot water was the most effective extraction solvent in terms of yield and closely simulated the typical human consumption of coffee by-products. Separation was performed on TLC plates with a mixture of ethyl acetate, n-propanol, and water, followed by bioassay detection. The positive control 4-nitroquinoline 1-oxide exhibited clear mutagenic responses, confirming the proper bioassay performance. In the Ames bioautogram, none of the tested coffee by-products showed mutagenic zones, suggesting the absence of strongly acting, acute mutagens under the applied test conditions; however, given the only 5 h short incubation and the use of TA98 strain only, a longer incubation time and testing with additional Salmonella strains is recommended. The results provide new safety data for Coffea leaves and blossoms and are consistent with some previous studies demonstrating the safety of coffee by-products. However, further improvements in the sensitivity and selectivity of the planar Ames bioassay are demanded, and further in vivo and long-term safety studies are recommended. Considering natural variability, the different uses of pesticides and treatments, and the fluctuating supply chains, coffee by-products may differ highly. The planar bioassay technology using the affordable 2LabsToGo-Eco is a powerful toxicological screening option for the coffee industry, considering the increasing interest in utilizing coffee by-products. Full article

Urban lifeline Natech events are coupled systems composed of multiple risks and entities with complex dynamic transmission chains. Predicting risk evolution probabilities is the core task for achieving the safety management of urban lifeline Natech events. First, the risk evolution mechanism is analyzed, where urban lifeline Natech events exhibit spatial evolution characteristics, which involves dissecting the parallel and synergistic effects of risk evolution in spatial dimensions. Next, based on fitting marginal probability distribution functions for natural hazard and urban lifeline risk evolution, a Multi-dimensional Copula (MdC) function for the joint probability distribution of urban lifeline Natech event risk evolution is constructed. Building upon the MdC function, a Markov Chain Monte Carlo (MCMC) model for predicting risk evolution probabilities of urban lifeline Natech events is developed using the Metropolis–Hastings (M-H) algorithm and Gibbs sampling. Finally, taking the 2021 Zhengzhou ‘7·20’ catastrophic rainstorm as a case study, joint probability distribution functions for risk evolution under Rainfall-Wind speed scenarios are fitted for traffic, electric, communication, water supply, and drainage systems (including different risk transmission chains). Numerical simulations of joint probability distributions for risk evolution are conducted, and visualizations of joint probability predictions for risk evolution are generated. Full article

As manufacturing and logistics-oriented supply chains continue to expand in scale and complexity, and the coupling between their physical execution layers and information–decision layers deepens, the resulting high interdependence within the system significantly increases overall fragility. Driven by key technological barriers, economies of scale, and the trend toward resource centralization, supply chains have increasingly evolved into centralized structures, with critical functions such as decision-making highly concentrated in a few focal firms. While this configuration may enhance coordination under normal conditions, it also significantly increases dependency on focal nodes. Once a focal node is disrupted, the intense task, information, and risk loads it carries cannot be effectively dispersed across the network, thereby amplifying load spillovers, coordination imbalances, and information delays, and ultimately triggering large-scale cascading failures. To capture this phenomenon, this study develops a coupled network model comprising a Physical Network and an Information and Decision Risk Network. The Physical Network incorporates a tri-load coordination mechanism that distinguishes among theoretical operational load (capacity), actual production load (production output), and actual delivery load (order fulfillment), using a load sensitivity coefficient to describe the asymmetric propagation among them. The Information and Decision Risk Network is further divided into a communication subnetwork, which represents transmission efficiency and delay, and a decision risk subnetwork, which reflects the diffusion of uncertainty and risk contagion caused by information delays. A discrete-event simulation approach is employed to evaluate system resilience under various failure modes and parametric conditions. The results reveal the following: (1) under a centralized structure, poorly allocated redundancy can worsen local imbalances and amplify disruptions; (2) the failure of a focal firm is more likely to cause a full network collapse; and (3) node failures in the Communication System Network have a greater destabilizing effect than those in the Physical Network. Full article

This study addresses the critical challenge of emergency material distribution during atypical public health crises, using the COVID-19 pandemic in Hubei Province as a representative case. An innovative internal–external coupled dispatching framework is proposed by integrating regional medical resource allocation with cross-regional supply chain networks. Our methodology employs the SEIR epidemiological model to forecast infection rates and corresponding material demands, then incorporates bidirectional dispatching efficiency as a key determinant of demand urgency. Through systematic risk stratification of affected areas, we develop a dual-objective optimization model that simultaneously minimizes logistical time and cost, solved by the NSGA-II algorithm. The results demonstrate that the internal–external coupled emergency material dispatching approach significantly enhances demand satisfaction in affected regions and improves overall dispatching effectiveness. This study offers practical recommendations and valuable references for emergency material dispatching during public health crises. Full article

Understanding the coupling mechanism and coordinated development between digital transformation and operational efficiency in logistics enterprises is vital for optimizing resource allocation and promoting high-quality, sustainable growth in the logistics industry. This study analyzes panel data from 52 listed logistics enterprises in China from 2014 to 2023. It constructs evaluation index systems for digital transformation and operational efficiency and applies an integrated methodology comprising the super-efficiency SBM model, coupling coordination degree model, and random forest regression model to evaluate efficiency, assess coupling dynamics, and forecast future trends. The main findings are as follows: (1) Overall operational efficiency has shown a pattern of fluctuating growth, increasing from 0.520 to 0.585. Road transport consistently outperformed other sectors, water transport maintained steady growth, and air transport exhibited significant volatility, particularly during the COVID-19 pandemic. (2) The coupling coordination degree remains in the initial coordination stage (0.642–0.677), with road transport achieving intermediate-level coordination (0.718) by 2021. Water transport showed gradual but stable improvement, and air transport remained unstable due to external shocks. (3) Road transport leads in overall industry performance, while water transport exhibits stable progress, and air transport is hindered by international supply chain disruptions and technological adoption challenges. (4) Projections for 2024–2026 suggest an average annual growth rate of 0.31% in coupling coordination across all subsectors, although inter-sectoral synergistic mechanisms require further enhancement. Based on these findings, this study proposes targeted recommendations: increasing comprehensive investments in digital technologies across the entire supply chain, cultivating interdisciplinary talent, optimizing risk management frameworks, and refining policy support. These measures aim to strengthen the integration of digital transformation and operational efficiency, contributing to the sustainable development of the logistics industry. Full article