Search Results (6,150)

In the context of global decarbonization and digital transformation, this study investigates whether and how the adoption of artificial intelligence (AI) promotes corporate energy transition, as measured by firms’ total energy consumption, energy intensity, and carbon emission intensity. Drawing on the theories of general-purpose technology (GPT), the resource-based view (RBV), and dynamic capabilities, the paper conceptualizes AI as a production-embedded technological capability that enhances intelligent automation, energy monitoring, and resource coordination within firms. Using panel data on Chinese A-share listed firms from 2012 to 2024, and capturing AI adoption through observable changes in firms’ production-related capital intensity, the analysis employs firm- and year-fixed effects, instrumental variables, and a dynamic event-study design to address endogeneity and temporal dynamics. The results show that AI adoption reduces firms’ energy consumption by approximately 2.0%, energy intensity by 1.8%, and carbon emission intensity by 2.3% within two to three years after adoption. Mechanism tests indicate that green innovation, operational efficiency, and resource allocation efficiency mediate this effect. Heterogeneity analyses reveal more substantial effects among non-state, large-scale, and technology-intensive firms operating in highly marketized regions. The findings broaden understanding of AI as a strategic sustainability technology and provide actionable implications for policymakers to align digital and energy governance to achieve carbon neutrality goals. Full article

Extreme natural disasters raise a fundamental question for biologically rigid food production systems: does post-disaster productivity recovery stem from technological change or from adaptive reorganization within existing constraints? In inland aquaculture, where biological processes, fixed production cycles, and capital requirements severely limit short-run technological upgrading, this distinction is particularly critical. Using two post-earthquake time points (2023 and 2025), the analysis documents productivity and efficiency patterns rather than causal recovery trajectories. Accordingly, the analysis is explicitly descriptive and does not attempt to identify causal recovery mechanisms or long-run productivity dynamics. Adaptive efficiency is not directly measured in this study; rather, the term is used as an interpretative construct to describe efficiency changes that are consistent with adaptive behavior under post-disaster constraints. This study examines productivity patterns observed during the post-earthquake period in inland trout aquaculture following the 6 February 2023 earthquake in Eastern Türkiye, with a particular focus on adaptive efficiency as a recovery-consistent mechanism. Using a balanced panel of 290 inland trout farms observed during the immediate post-earthquake adjustment period (2023) and a subsequent recovery phase (2025), the analysis integrates bias-corrected Data Envelopment Analysis, Malmquist productivity decomposition, and resilience-oriented truncated regression. Recovery dynamics are examined conditional on farm survival, allowing within-farm adaptive adjustment to be distinguished from exit-driven selection effects. The results indicate that productivity recovery was driven predominantly by improvements in technical efficiency, while technological change remained close to unity across provinces, suggesting short-run production frontier stability. This pattern is consistent with delayed or constrained investment behavior under heightened uncertainty rather than with technological stagnation. This interpretation is not unique and should be read as one plausible mechanism among several, rather than as a definitive explanation of observed frontier stability. Farms primarily restored performance through operational reorganization, input coordination, and scale adjustment within existing biological and technological constraints, rather than through innovation. Second-stage results further show that the coefficient on access to liquidity is positive, while higher mortality rates and greater distance to markets are systematically associated with weaker post-disaster adjustment. Overall, the findings indicate that short- to medium-term productivity patterns in biologically rigid inland aquaculture systems are governed primarily by efficiency changes consistent with adaptive efficiency rather than technological change. From a policy perspective, post-disaster aquaculture recovery strategies should prioritize liquidity support, biological continuity, and operational stability over premature technology-push interventions. The analysis is based on two post-disaster observation points (2023 and 2025), which allows identification of short- to medium-term recovery-consistent patterns but does not permit causal or long-run inference. Full article

The evaluation of China’s Low-Carbon City Pilot Policy (LCCP) is critical to understanding its role in mitigating climate challenges associated with carbon emissions. While most existing research has concentrated narrowly on emission reductions within pilot cities, broader improvements in emission performance have often been overlooked. To address this gap, our study employs an integrated methodological framework combining Difference-in-Differences (DID) with Data Envelopment Analysis (DEA), enabling a dual-perspective assessment of policy effectiveness. Baseline regression results confirm that the LCCP has led to a statistically significant decrease in total urban carbon emissions. Pilot cities achieved an average reduction in emission levels that was 4.8 percentage points greater than that of non-pilot cities, underscoring the policy’s tangible impact. Further analysis using DEA reveals a consistent year-on-year enhancement in the dynamic carbon emission performance of these cities. Regionally disaggregated results highlight distinct drivers of low-carbon performance: in low-emission cities such as Huangshan, gains were primarily efficiency-led; in medium-emission cities like Beijing, technological advancement served as the main catalyst; and in high-emission cities including Shanghai, both efficiency gains and technological innovation jointly propelled progress. These findings offer valuable empirical insights for customizing low-carbon transition pathways across cities with varying emission profiles. Full article

This work aims to demonstrate the successful, long-term human use of an automatic scheduling-manual operation (AS-MO) precision irrigation tool by farmers on a medium-scale Jordanian farm. Innovation in low-cost, accessible, and water-efficient irrigation technologies is critical as water resources become scarce, especially on resource-constrained farms in the drought-prone Middle East and North Africa (MENA) region. Prior work has shown that a proposed AS-MO decision support tool could bridge the gap between fully manual irrigation—a common practice on many MENA farms—and existing precision agriculture solutions, which are often too expensive or complex for medium-scale farmers to adopt. Recent developments have also demonstrated that the scheduling theory behind the proposed AS-MO tool uses up to 44% less water compared to fully manual irrigation. However, a functional design of the AS-MO tool has not been realized nor has it been demonstrated on a farm with farmer users. This work documents the detailed design of an AS-MO tool’s human–machine interaction (HMI) and validates the human execution of the tool in context. Through an 11-week case study conducted on a Jordanian farm, we show that farmers used a functional prototype of the AS-MO tool as intended. The functional tool prototype was designed to deliver a long-term AS-MO user experience to study participants. The prototype monitored local weather conditions, generated water-efficient schedules using an existing scheduling theory, and notified users’ phones when they should manually open or close valves. The irrigation practices of participants using the AS-MO prototype were measured, and participants demonstrated successful use of the tool. Users correctly confirmed 93% of the scheduled events using the tool’s HMI. Despite manual operation, a majority of confirmed irrigation event durations fell within 15% of the automatically scheduled durations; relative to the length of scheduled irrigation event durations, the medians of confirmed and scheduled durations were 102% and 88%, respectively. These results demonstrate the success of the tool’s decision support ability. Feedback from study participants can support the AS-MO tool’s next design iteration and can inform the development of other decision support systems designed for resource-constrained, medium-scale farms. This work presents an important step towards developing a precision irrigation tool that, if adopted at scale, could increase the adoption of water-efficient irrigation practices on resource-constrained farms that are not served by existing technology, improving sustainable agriculture in MENA. Full article

The safe and efficient integration of small unmanned aircraft systems (sUAS) into the National Airspace System (NAS) requires a systems-based understanding of the interrelations among human, technological, and regulatory components. Existing Federal Aviation Administration (FAA) guidelines restrict most operations to visual line of sight (VLOS), which constrains operational scalability and underscores the need for system-level innovations supporting beyond-visual-line-of-sight (BVLOS) operations. This study adopted a socio-technical systems approach to evaluate how first-person view (FPV) technologies influence operator workload and situational awareness (SA), key human performance elements within the broader sUAS safety system. Participants meeting FAA Part 107 eligibility criteria were assigned to one of three visual configurations: (a) traditional VLOS, (b) FPV using a 21-inch monitor, or (c) FPV with immersive goggles. Workload was measured with the NASA Task Load Index (NASA-TLX), and Level 1 SA was assessed via post-task recall. ANOVA results revealed no statistically significant differences across visual conditions, indicating no evidence that FPV integration either increased cognitive load or impaired perceptual awareness compared to traditional methods. Complementary analysis of NASA’s Aviation Safety Reporting System (ASRS) identified SA as the most recurrent human-factor issue, suggesting system-level implications for human–machine interaction and training design. These findings contribute to the systemic understanding of human factors in UAS operations, supporting FPV’s potential as a viable subsystem for achieving safe and effective BVLOS integration within complex socio-technical aviation systems. Full article

Marine bioactive substances exhibit structural diversity and function-specific properties, attracting considerable interest in their potential applications in targeted nutritional delivery to the gut and microbiota regulation. These bioactive components, sourced from seaweed, marine crustaceans, and microorganisms, including polysaccharides, polyphenols, and lipids, demonstrate exceptional biocompatibility and specific recognition capabilities. They serve as an optimal carrier matrix and functional core for developing an efficient, precision-targeted intestinal nutrition delivery system. Research findings demonstrate that optimization via innovative delivery technologies, including nanoencapsulation and polymer microsphere encapsulation, enables marine bioactive substances to navigate various physiological barriers in the gastrointestinal tract effectively. This facilitates targeted, sustained release of nutritional components and enhances bioavailability. Simultaneously, these substances may relieve dysbiosis by modulating the composition of the gut microbiota and the quantity and activity of specific metabolic products, thereby reinforcing intestinal barrier integrity. This narrative review systematically examines the sources and functional attributes of marine bioactive compounds, emphasizing their application strategies in developing targeted delivery systems for the gut and their regulatory effects on gut microbiota. It concludes by delineating future research directions in this field, particularly in optimizing carrier functionalities and clarifying action mechanisms. Full article

The increasing demand and production of neodymium-iron-boron-based permanent magnets (NdFeB-PMs) for the electronics, energy sector, and automobile industries led to disposal consequences. The NdFeB-PMs contain a substantial amount of rare earth elements (REEs). Although China is the largest exporter of REEs to the world, it has applied some restrictive policies in terms of supply chain and taxes. To address such issues, this review systematically examines current recycling techniques, including short-loop, hydrometallurgy, pyrometallurgy, and hybrid processes, and the integration of Machine Learning (ML) to the leaching process, with a particular focus on their impact on industrial capability, economic viability, and environmental concerns. However, a comparative study highlights ongoing challenges to large-scale implementation, including fragmented waste sources, gaps between efficient processes and environmental sustainability, and a lack of regulatory and infrastructure support. To address these challenges, technical innovation in automated disassembly systems and selective REE recovery via ML was discussed, along with legislative initiatives such as Extended Producer Responsibility (EPR) and waste monitoring procedures. Furthermore, ecologically and economically feasible solutions were optimized through ML-based recycling procedures to increase the leaching efficiency and the recovery of the REEs. This analysis emphasizes the importance of collective technological, environmental, and policy initiatives to achieve sustainable NdFeB recycling and long-term resource availability. These findings offer important perspectives into developing effective and environmentally friendly NdFeB waste recycling solutions via the integration of ML. Full article

3D-printed hand exoskeletons are important because they enable the creation of affordable, lightweight, and highly customizable assistive and rehabilitation devices tailored to individual patient needs. Their rapid production and design flexibility accelerate innovation, improve access to therapies, and accelerate functional recovery for people with hand impairments. This article discusses the development of a hand exoskeleton using advanced additive manufacturing. It highlights how Industry 4.0 principles such as digital design, automation, and smart manufacturing enable precise prototyping and efficient use of materials. Moving on to Industry 5.0, the study highlights the role of human–machine collaboration, where customization and ergonomics are prioritized to ensure user comfort and rehabilitation effectiveness. The integration of AI-based generative design and digital twins (DTs) is explored as a path to Industry 6.0, where adaptive and self-optimizing systems support continuous improvement. The perspective of personal experience provides insight into practical challenges, including material selection, printing accuracy, and wearability. The results show how technological optimization can be used to reduce costs, improves efficiency and sustainability, and accelerates the personalization of medical devices. The article shows how evolving industrial paradigms are driving the design, manufacture, and refinement of 3D-printed hand exoskeletons, combining technological innovation with human-centered outcomes. Full article

The agri-food sector is a major contributor to global greenhouse gas emissions while facing increasing demand for food production driven by population growth. Transitioning towards sustainable and low-carbon agricultural systems is therefore critical. Green hydrogen, produced from renewable energy sources, holds significant promise as a clean energy carrier and chemical feedstock to decarbonize multiple stages of the agri-food supply chain. This systematic review is based on a structured analysis of peer-reviewed literature retrieved from Web of Science, Scopus, and Google Scholar, covering over 120 academic publications published between 2010 and 2025. This review provides a comprehensive overview of hydrogen’s current and prospective applications across agriculture and the food industry, highlighting opportunities to reduce fossil fuel dependence and greenhouse gas emissions. In agriculture, hydrogen-powered machinery, hydrogen-rich water treatments for crop enhancement, and the use of green hydrogen for sustainable fertilizer production are explored. Innovative waste-to-hydrogen strategies contribute to circular resource utilization within farming systems. In the food industry, hydrogen supports fat hydrogenation and modified atmosphere packaging to extend product shelf life and serves as a sustainable energy source for processing operations. The analysis indicates that near-term opportunities for green hydrogen deployment are concentrated in fertilizer production, food processing, and controlled-environment agriculture, while broader adoption in agricultural machinery remains constrained by cost, storage, and infrastructure limitations. Challenges such as scalability, economic viability, and infrastructure development are also discussed. Future research should prioritize field-scale demonstrations, technology-specific life-cycle and techno-economic assessments, and policy frameworks adapted to decentralized and rural agri-food contexts. The integration of hydrogen technologies offers a promising pathway to achieve carbon-neutral, resilient, and efficient agri-food systems that align with global sustainability goals and climate commitments. Full article

Soil management is crucial for addressing soil-borne pathogens, weeds, and pests, ensuring sustainable crop productivity. Traditional chemical fumigants, such as methyl bromide, have been effective but pose serious environmental risks, including ozone depletion and reduced soil biodiversity. Consequently, attention has shifted toward more sustainable alternatives. Techniques like soil solarization, anaerobic soil disinfestation (ASD), biofumigation, and the use of biological control agents (BCAs) offer environmentally friendly options for managing soil-borne diseases. Steam and microwave disinfestation are also promising techniques; however, further development is required to improve their practical efficiency. Integrated management approaches, which combine multiple interventions, have proven particularly effective, offering flexibility and enhancing control through complementary techniques. Additionally, emerging technologies such as artificial intelligence and hyperspectral imaging provide new opportunities for real-time monitoring and decision-support to optimize the timing and targeting of pest management interventions. This review emphasizes the potential of sustainable soil pest control methods to reduce reliance on chemical fumigants, improve crop yield and quality, and support environmentally responsible farming practices. It also examines the challenges associated with scalability, cost, and variable effectiveness, while outlining the strengths, weaknesses, and mechanisms of each method. Further research on regional adaptation, technological integration, and long-term impacts is essential to fully optimize these innovative solutions for food security and sustainable agriculture. Full article

This study explores how green finance development (GF) promotes forest ecological–economic efficiency (FEEE), and identifies its underlying mechanisms and key determinants. Using panel data for 11 prefecture-level cities in Zhejiang Province from 2011 to 2022, the core area of China’s Green Finance Reform and Innovation Pilot Zone, this study employ mediation, moderation, and panel threshold models to empirically examine the impact and transmission pathways of GF. The results indicate that GF significantly enhances FEEE, mainly through technological progress, industrial structure upgrading (ISU), and industrial structure ecologization (ISE). Environmental regulation (ER) exerts a dominant negative effect on efficiency improvement, while a substitution effect exists between GF and ER. The heterogeneity analysis shows that direct GF plays a more pronounced role in improving efficiency compared with indirect GF. The threshold analysis further reveals that the impact of GF on FEEE is non-linear. Specifically, the marginal effect of GF on FEEE diminishes beyond a certain threshold, while its positive effect strengthens once the levels of ISE and ISU surpass their respective thresholds. These findings contribute to the theoretical understanding and policy design of GF in fostering ecological civilization. Full article

Investigating the impact of factor mobility (FM) on the economic efficiency of marine fisheries (EEMF) holds scientific reference value for promoting the high-quality development of the marine fisheries economy in China’s coastal regions. This study is based on panel data from 11 coastal provinces and municipalities in China, covering the period from 2008 to 2023. Utilizing Tobit models and mediation effect models, it empirically analyzes the direct and indirect impacts of FM on the EEMF, as well as the regional heterogeneity of these effects. Research findings indicate that (1) the level of FM and the EEMF in coastal regions both exhibit fluctuating upward trends, although regional variations exist across different provinces. (2) FM in coastal regions enhances the EEMF. For every additional unit of FM, the EEMF increases by 0.0825 units. (3) Technological innovation levels and industrial structure upgrading serve as key pathways through which FM influences the EEMF, acting as mediating variables. (4) This impact exhibits regional heterogeneity, with the Eastern Marine Economic Circle being the most significantly affected. The research findings expand the scope of studies on FM and the EEMF, providing practical advice for promoting the optimal allocation of factors in coastal regions and enhancing EEMF development. Full article

Phacoemulsification is performed within a highly dynamic intraocular environment, in which fluid exchange, pressure regulation, and tissue biomechanics interact continuously. Although modern cataract surgery is considered safe and efficient, disruption of this delicate intraoperative microenvironment remains a major source of complications. Among fluidics-related events, post-occlusion break surge represents one of the most critical destabilizing factors of the anterior chamber. A surge occurs when the sudden release of an occluded aspiration port generates an abrupt pressure–volume imbalance that cannot be immediately compensated by infusion, leading to a transient collapse of the intraocular environment. This narrative review integrates current experimental and clinical evidence on the pathophysiology, quantification, and technological control of surge, framing it as a model of environmentally driven intraoperative stress. The evolution of phacoemulsification fluidics, from gravity-based systems to active, adaptive, and predictive platforms, is analyzed in relation to their ability to preserve a stable and physiologic intraocular environment. Comparative data from contemporary devices are reviewed, highlighting differences in surge volume, recovery time, and pressure restitution. Special emphasis is placed on the impact of surge on the microenvironments of both the anterior and posterior segments, including endothelial stress, capsular instability, vitreoretinal traction, and macular perfusion. Emerging strategies such as handpiece-integrated pressure sensors, predictive fluidics algorithms, intraoperative imaging, and artificial intelligence are reshaping environmental control during surgery. Despite substantial technological progress, the complete elimination of surge remains an unmet need. Continued innovation, standardized biomechanical models, and robust clinical validation will be essential to further protect the intraoperative intraocular environment and improve long-term visual outcomes. Full article

The incorporation of artificial intelligence (AI) and digital technology in healthcare has revolutionized service delivery, improving diagnostic precision, patient outcomes, and operational efficacy. Nonetheless, despite considerable progress, numerous problems persist that impede the realization of full potential. Current reviews predominantly emphasize the advantages of AI in disease detection and health guidance, neglecting significant concerns such as social opposition, regulatory frameworks, and geographical discrepancies. This SLR, executed in accordance with PRISMA principles, examined 21 publications from 2020 to 2025 to assess the present condition of AI and digital technologies inside Saudi Arabia’s healthcare industry. Initially, 863 publications were obtained, from which 21 were chosen for comprehensive examination. Significant discoveries encompass the extensive utilization of telemedicine, data analytics, mobile health applications, Internet of Things, electronic health records, blockchain technology, online platforms, cloud computing, and encryption methods. These technologies augment diagnostic precision, boost patient outcomes, optimize administrative procedures, and foster preventative medicine, contributing to cost-effectiveness, environmental sustainability, and enduring service provision. Nonetheless, issues include data privacy concerns, elevated implementation expenses, opposition to change, interoperability challenge, and regulatory issues persist as substantial barriers. Subsequent investigations must concentrate on the development of culturally relevant AI algorithms, the enhancement of Arabic natural language processing, and the establishment of AI-driven mental health systems. By confronting these challenges and utilizing emerging technologies, Saudi Arabia has the potential to establish its status as a leading nation in medical services innovation, guaranteeing patient-centered, efficient, and accessible healthcare delivery. Recommendations must include augmenting data privacy and security, minimizing implementation expenses, surmounting resistance to change, enhancing interoperability, fortifying regulatory frameworks, addressing regional inequities, and investing in nascent technologies. Full article

The rapid increase in e-waste has become a significant global concern, influenced by swift technological advancements, shorter product lifecycles, and rising consumer demand. This situation leads to considerable environmental and health hazards, primarily due to the presence of toxic materials, energy demands, and the inadvertent loss of valuable resources when waste is not adequately managed. This review synthesises contemporary theories related to sustainable e-waste management, featuring concepts such as principles of the circular economy, energy efficiency and innovative recycling technologies. The review explores a range of actions, including regulatory strategies, mechanical pre-treatment methods, focusing on reagent-free recovery techniques, and the utilisation of digital solutions to enhance traceability and operational efficiency. The findings indicate substantial improvements in formal e-waste collection rates in areas with strong legislative frameworks, enhanced metal recovery efficiencies through refined hydrometallurgical and pyrometallurgical techniques and minimised environmental footprints through reagent-free and energy-conserving practices. The review emphasises the importance of viewing e-waste recycling not just as a waste management issue but as a fundamental element of resource security and sustainable industrial practices. By assessing recent developments, this work advocates for closed-loop recycling as an essential driver in the global shift towards a resilient, low-carbon, energy-efficient and circular economy. Full article