Search Results (1,702)

Artificial intelligence (AI) is transforming accounting by automating cognitive tasks and redefining mechanisms of governance and risk control. This study examines how AI operates as an intelligent control system—one that substitutes manual accounting procedures while enhancing transparency, internal control, and fraud detection. Integrating the Technology Acceptance Model (TAM) with Organizational Information Processing Theory (OIPT), the research develops a behavioral–organizational framework linking perceived usefulness, ease of use, AI literacy, technology readiness, social influence, and facilitating conditions to AI adoption and perceived substitution benefits. A structured survey was administered to accounting students and practitioners in Northern Italy (n = 185) and analyzed through reliability tests and partial least squares structural equation modeling (PLS-SEM). The results show that AI literacy, facilitating conditions, and social influence significantly drive adoption intention, while perceived substitution benefits fully mediate the relationship between adoption and governance outcomes. The findings demonstrate that AI adoption enhances governance and risk management effectiveness by functioning as an intelligent control mechanism. The study introduces the AI-to-Control (A2C) Blueprint to guide responsible integration of AI into accounting systems, reframing AI adoption as a structural evolution in corporate governance rather than a mere technological upgrade. Full article

With the rapid development of the global urbanization process, the resource utilization of construction waste has become one of the core issues of the development of a circular economy and has been widely concerned by the international community. However, China’s resource utilization efficiency in this field is still in the development stage, and cthere is still a gap with developed countries. It is urgent to systematically solve scientific problems such as low resource utilization efficiency, prominent technical bottlenecks, and imperfect whole process management mechanisms, so as to realize the coordinated high-quality development of the economy, society, and the environment. In order to scientifically predict the generation trend of construction waste and assess the resource potential, this study takes Beijing as the research object. Based on the historical data samples of construction waste in Beijing from 2001 to 2024, the analysis framework of “output estimation—trend prediction—value evaluation” is constructed. The ARIMA model is selected as the core tool of prediction, because it can match the phased change characteristics of construction waste output with the development of the city in time series data processing. Combined with the cost–benefit analysis method, it makes a quantitative analysis of the future production scale of construction waste and the economic benefits of resource utilization in Beijing. The research results show that from 2025 to 2034, the production of construction waste in Beijing will show a trend of first decreasing and then increasing, and it will reach 13.599 million tons by 2034. The resource utilization of construction waste in the next 10 years is expected to bring about USD 2.998 billion of economic benefits. This prediction result may be related to the policy guidance of Beijing’s urban renewal, changes in construction activities, and industrial technology upgrading. Accordingly, this study puts forward countermeasures and suggestions to help the development of industrialization, providing theoretical support and practical references for the sustainable development of the resource utilization of construction waste. Full article

Rapid urban expansion has heightened the demand for accurate, scalable, and real-time methods to assess tree health and the provision of ecosystem services. Urban trees are the major contributors to air-quality improvement and climate change mitigation; however, their monitoring is mostly constrained to inherently subjective and inefficient manual inspections. In order to break this barrier, we put forward a lightweight multimodal deep-learning framework that fuses RGB imagery with environmental and biometric sensor data for a combined evaluation of tree-health condition as well as the estimation of the daily oxygen production and CO₂ absorption. The proposed architecture features an EfficientNet-B0 vision encoder upgraded with Mobile Inverted Bottleneck Convolutions (MBConv) and a squeeze-and-excitation attention mechanism, along with a small multilayer perceptron for sensor processing. A common multimodal representation facilitates a three-task learning set-up, thus allowing simultaneous classification and regression within a single model. Our experiments with a carefully curated dataset of segmented tree images accompanied by synchronized sensor measurements show that our method attains a health-classification accuracy of 92.03% while also lowering the regression error for O₂ (MAE = 1.28) and CO₂ (MAE = 1.70) in comparison with unimodal and multimodal baselines. The proposed architecture, with its 5.4 million parameters and an inference latency of 38 ms, can be readily deployed on edge devices and real-time monitoring platforms. Full article

This study investigates how skilled labor influences the development of the secondary sector in emerging economies, using China as a case study. We focus on the transitional process in which manufacturing growth shifts from labor-intensive expansion toward productivity-driven industrial upgrading. Using provincial-level data from 2000 to 2023, we evaluate the role of skilled labor across different stages of development by applying fixed-effects panel regressions, a difference-in-differences framework, and multiple robustness checks. Our findings reveal that skilled labor does not significantly contribute to secondary sector performance in the early phase, when growth relies primarily on low labor costs and rapid urbanization. However, once regions accumulate sufficient economic capacity and technological readiness, skilled labor becomes an important driver of value added and export performance. Stricter environmental policies further widen regional differences: developed regions benefit from green upgrading supported by skilled workers, while less developed regions face firm exits and weakening industrial output. These results highlight the importance of aligning human capital investments with industrial and environmental policies to promote more balanced and sustainable economic development in emerging markets. Full article

The shipping service industry plays a pivotal role in enhancing port competitiveness and fostering urban economic growth, yet limited studies systematically integrate its spatial temporal dynamics with the processes driving port–city synergy. This study constructs a three-dimensional analytical framework encompassing port operations, urban economic development, and shipping service industry agglomeration. Using data from 13 port cities in Jiangsu Province (2015–2023), we apply the entropy weight method, coupling coordination degree model, relative development model, and panel Tobit regression to evaluate interaction intensity, coordination patterns, and influencing factors. Results reveal a clear spatial gradient in coupling coordination, higher in southern Jiangsu and lower in the north, driven by disparities in economic foundations, port capacities, and service industry structures. In most cities, port operations and urban economies lag behind shipping service industry agglomeration, reflecting the predominance of low- and mid-end services. Port construction level, cargo and container throughput, economic development, openness, fixed asset investment, and population density significantly promote coordination, whereas R&D capacity shows no significant effect. The findings advance understanding of port–city service interlinkages and provide targeted policy recommendations for differentiated regional development, infrastructure enhancement, and upgrading toward high-end shipping services, with implications for maritime regions worldwide. Full article

The global deterioration of water quality due to climate change and industrialization has intensified the need for real-time monitoring systems. In South Korea’s automated water quality monitoring networks, measuring total organic carbon (TOC) and nitrate nitrogen (NO₃-N) as a proxy for total nitrogen (TN) is critical; however, conventional analytical instruments face limitations such as high costs, long analysis times, and the need for chemical reagents. In this study, we developed and evaluated a simultaneous TOC and NO₃-N measurement method using HASM-4000, a domestically developed optical sensor based on ultraviolet (UV) absorption spectroscopy. The sensor measures absorbance at 254 nm (TOC) and 220 nm (NO₃-N) based on the Beer–Lambert law, with signal processing techniques including optical power compensation (OPC) and Binning–Interpolation (BinInterp) applied to enhance measurement accuracy. Calibration using standard solutions demonstrated excellent linear correlations (R² > 0.99) between actual and estimated concentrations for both TOC and NO₃-N, with accuracy and reproducibility validated against standard methods under laboratory conditions. However, performance degradation was observed in turbid mixed samples due to the optical limitations of the 10 mm pathlength, suggesting the need for future improvements such as adopting a 5 mm pathlength and upgrading optical components. The HASM-4000 sensor enables real-time measurement without a reagent, and preliminary testing with river water samples demonstrates its potential to advance Korea’s water quality monitoring infrastructure by reducing dependence on foreign technologies and facilitating network expansion with cost-effective domestic solutions. Full article

At the moment, there are no available data or studies exploring the production of naphtha boiling range hydrocarbons via hydroprocessing of pretreated residual lipids. To that aim, this study targets the production of naphtha, jet and diesel boiling range hydrocarbons via hydroprocessing of refined waste cooking oils utilizing solar hydrogen. The technology was first optimized in a TRL-3 plant. A heteroatom removal catalyst and a saturation catalyst were combined with an isomerization and hydrocracking catalyst to upgrade lipids. The results show that the severity of the process plays an important role in the yields of the fuels. Higher naphtha yields were observed at 663 K, 13.78 MPa and a liquid hourly space velocity of 0.33 h⁻¹, leading to the production of a fuel consisting of 34 wt% naphtha, 23 wt% jet and 42 wt% diesel boiling range hydrocarbons. Subsequently, the technology was validated and demonstrated in an industrially relevant unit (TRL-5). The results from the fuel characterization show that the diesel fraction can be used as a high-quality road transport drop-in fuel, as it is characterized by a high cetane index (~96) and a high flash point (414 K). Although jet and naphtha meet most commercial fuel specifications, further optimization of the process is necessary to meet fuel standards. In conclusion, the current work provides novel data relevant to industrial applications for road, aviation and maritime fuel production via hydroprocessing of refined waste cooking oil. Full article

The energy efficiency of historic buildings is the focus of activities aimed at developing replicable methodologies for implementing innovative technological solutions. In line with this priority, the Sicilian Region has launched a project for the energy retrofitting of 91 heritage sites and buildings across the region. To support the decision-making process, this paper defines criteria and indicators for assessing the compatibility and effectiveness of energy efficiency upgrade solutions for buildings of cultural value. The goal of improving energy performance is framed within broader performance targets, including enhancing user experience, promoting cultural activities for users’ creative growth, and carrying out restoration works to strengthen the identity of the pre-existence. The criteria result from a thorough analysis of the current scientific debate on the energy efficiency of heritage buildings and have been validated through their application to the case study of Palazzo Belmonte-Riso, a listed building in the historical centre of Palermo (Italy). The suggested criteria provide guidance for evaluating implemented projects and developing new design solutions. The research proposes a holistic and multidisciplinary approach aligned with the New European Bauhaus, promoting creative and innovative solutions that embody sustainability, aesthetics, and inclusiveness in addressing key issues on the European Agenda. Full article

Yeast-derived biomolecules are redefining the boundaries of green nanotechnology. Biosurfactants, exopolysaccharides, enzymes, pigments, proteins, and organic acids—when sourced from carbohydrate-rich lignocellulosic hydrolysates—offer a molecular toolbox capable of directing, stabilizing, and functionalizing nanoparticles (NPs) with unprecedented precision. Beyond their structural diversity and intrinsic biocompatibility, these biomolecules anchor a paradigm shift: the convergence of biorefineries with nanotechnology to deliver multifunctional materials for the circular bioeconomy. This review explores: (i) the expanding portfolio of metallic and metal oxide NPs synthesized through yeast biomolecules; (ii) molecular-level mechanisms of reduction, capping, and surface tailoring that dictate NP morphology, stability, and reactivity; (iii) synergistic roles in intensifying lignocellulosic processes—from enhanced hydrolysis to catalytic upgrading; and (iv) frontier applications spanning antimicrobial coatings, regenerative packaging, precision agriculture, and environmental remediation. We highlight structure–function relationships, where amphiphilicity, charge distribution, and redox activity govern resilience under saline, acidic, and thermally harsh industrial matrices. Yet, critical bottlenecks remain: inconsistent yields, limited comparative studies, downstream recovery hurdles, and the absence of comprehensive life-cycle and toxicological evaluations. To bridge this gap, we propose a translational roadmap coupling standardized characterization with real hydrolysate testing, molecular libraries linking biomolecule chemistry to NP performance, and integrated techno-economic and environmental assessments. By aligning yeast biotechnology with nanoscience, we argue that yeast-biomolecule-driven nanoplatforms are not merely sustainable alternatives but transformative solutions for next-generation lignocellulosic biorefineries. Full article

Lignocellulosic biomass wastes are renewable carbon resources that can be available for conversion into biofuels. There is a growing interest in utilizing a broader range of alternative biomass feedstocks such as agri-crop residues aside from the traditional forest-origin wood residues for fuel pellet production. However, crop residues typically have low and inconsistent fuel quality. This paper investigated the effectiveness of the combined steam explosion and water leaching pretreatment techniques to upgrade the fuel properties of wheat straw. The experimental treatments involved auto-catalyzed steam explosion and acid-catalyzed steam with and without subsequent water leaching. Using steam explosion catalyzed by dilute H₂SO₄ at a low concentration of 0.5 wt%, results showed the highest ash, Si, and Ca removal efficiencies of 82.2%, 91.1%, and 74.3%, respectively. Moreover, there was significant improvement in fuel quality in terms of fuel ratio (0.34) and calorific value HHV (21.9 MJ/kg), as well as a pronounced increase in the comprehensive combustibility index at the devolatization stage, indicating better combustion characteristics. Overall, the results demonstrate that with adequate pretreatment, the quality of agri-pellets derived from wheat straw could potentially be on par with wood pellets that are utilized for heat and power generation and residential heating. To mitigate the dry matter loss due to steam explosion, future studies shall consider using the process effluent to produce biofuel. Full article

The treatment of polychlorinated dibenzodioxins and polychlorinated dibenzofurans (PCDD/Fs) in incineration fly ash presents a significant challenge in solid hazardous waste management. This study systematically analyzed the influence mechanisms of multiple factors on the removal efficiency of PCDD/Fs during fly ash pyrolysis. It integrated 4068 datasets conducted between 2010 and 2025 through meta-analysis. Results show that Al₂O₃, CaO, SiO₂, and Cl in fly ash components enhance the removal efficiency by 14.0%, while Fe₂O₃ (Content greater than 5.7%) exhibits inhibitory effects. Cd and Cr demonstrate a bimodal response pattern: low/high concentrations promote removal, while medium concentrations inhibit it. Process optimization identified the optimal parameter combination as pyrolysis temperatures of 500–900 °C, residence time of 50–90 min, and a gas flow rate greater than or equal to 400 mL/min. A significant negative correlation was observed between the initial dioxin concentration and removal efficiency. This study established a structural equation modeling (SEM) model to describe how metallic and nonmetallic components, fly ash components, and pyrolysis conditions determine removal efficiency. Fly ash composition was confirmed as the most influential factor (total effect = 0.3194), with fixed carbon and ash content being the most reliable indicators. Among pyrolysis conditions, gas conditions (flow rate, gas type) also significantly affected removal efficiency (total effect = 0.2357). Conversely, nonmetallic components and excessively prolonged pyrolysis time (beyond the window) consistently reduced removal efficiency. These findings provide theoretical support for upgrading fly ash pyrolysis processes toward low-carbon and resource-efficient operations. Full article

Biogas upgrading and bottling represent essential processes in transforming raw biogas produced via the anaerobic digestion of organic waste into high-purity biomethane (≥95% CH₄), a renewable energy source suitable for applications in cooking, transportation, and electricity generation. Upgrading technologies, such as membrane separation, pressure swing adsorption (PSA), water and chemical scrubbing, and emerging methods, like cryogenic distillation and supersonic separation, play a pivotal role in removing impurities like CO₂, H₂S, and moisture. Membrane and hybrid systems demonstrate high methane recovery (>99.5%) with low energy consumption, whereas chemical scrubbing offers superior gas purity but is limited by high operational complexity and cost. Challenges persist around material selection, safety standards, infrastructure limitations, and environmental impacts, particularly in rural and off-grid contexts. Bottled biogas, also known as bio-compressed natural gas (CNG), presents a clean, portable alternative to fossil fuels, contributing to energy equity, greenhouse gases (GHG) reduction, and rural development. The primary aim of this research is to critically analyze and review the current state of biogas upgrading and bottling systems, assess their technological maturity, identify performance optimization challenges, and evaluate their economic and environmental viability. The research gap identified in this study demonstrates that there is no comprehensive comparison of biogas upgrading technologies in terms of energy efficiency, price, scalability, and environmental impact. Few studies directly compare these technologies across various operational contexts (e.g., rural vs. urban, small vs. large scale). Additionally, the review outlines insights into how biogas can replace fossil fuels in transport, cooking, and electricity generation, contributing to decarbonization goals. Solutions should be promoted that reduce methane emissions, lower operational costs, and optimize resource use, aligning with climate targets. This synthesis highlights the technological diversity, critical barriers to scalability, and the need for robust policy mechanisms to accelerate the deployment of biogas upgrading solutions as a central component of a low-carbon, decentralized energy future. Full article

As an important component of the global fishery economy, the crab breeding and processing industry faces the dual challenges of sustainable development and technological upgrading. This paper first systematically analyzes the regional distribution and core biological characteristics of major global economic crab species, laying a foundation for the targeted design of processing technologies and equipment. Secondly, based on advances in crab processing technology, the industry is categorized into two systems: live crab processing and dead crab processing. Live crab processing has formed a full-chain technological system of “fishing–temporary rearing–depuration–grading–packaging”. Dead crab processing focuses on high-value utilization: high-pressure processing enhances the quality of crab meat; liquid nitrogen quick-freezing combined with modified atmosphere packaging extends shelf life; and biological fermentation and enzymatic hydrolysis facilitate the green extraction of chitin from crab shells. In terms of intelligent equipment application, sensor technology enables full coverage of aquaculture water quality monitoring, precise classification during processing, and vitality monitoring during transportation. Automation technology reduces labor costs, while fuzzy logic algorithms ensure the process stability of crab meat products. The integration of the Internet of Things (IoT) and big data analytics, combined with blockchain technology, enables full-link traceability of the “breeding–processing–transportation” chain. In the future, cross-domain technological integration and multi-equipment collaboration will be the key to promoting the sustainable development of the industry. Additionally, with the support of big data and artificial intelligence, precision management of breeding, processing, logistics, and other links will realize a more efficient and environmentally friendly crab industry model. Full article

Placer deposits constitute important secondary resources for economically valuable minerals, including rare earth elements (REEs) and heavy minerals such as zircon, rutile, and ilmenite. In this study, representative samples from the Hantepe placer deposit (Çanakkale, Türkiye) were processed to investigate the occurrence, distribution, and beneficiation potential of REE-bearing minerals. The ore was subjected to size classification, followed by gravity concentration on a shaking table and subsequent magnetic separation using a low-intensity disc separator. The resulting products were characterized by X-ray diffraction and X-ray fluorescence. The dominant REE-host minerals were identified as titanite, zircon, apatite, monazite and, allanite, accompanied by magnetite, hematite, quartz, and feldspar as gangue constituents. The non-magnetic final concentrate achieved substantial upgrading of critical elements, with Ce increasing from 868 g/t to 5716 g/t, Nd from 308 g/t to 2308 g/t, and Zr from 1435 g/t to 9748 g/t. Additionally, the magnetic concentrate (7.0 wt.%) was strongly enriched in Fe₂O₃ (70.26%) and V (2359 g/t), indicating its potential suitability as an Fe–V source. Overall, the results demonstrate that combined gravity and magnetic separation constitutes an effective beneficiation strategy for critical mineral recovery from placer systems. These findings establish a strong basis for future pilot-scale studies and the techno-economic evaluation of the Hantepe deposit as an emerging source of strategic and industrially relevant heavy minerals. Full article

As a core driver of high-quality and sustainable economic development, the deep integration of the digital economy with foreign trade has emerged as a critical pathway to enhance the resilience of China’s foreign trade while advancing Sustainable Development Goals (SDGs)—particularly those related to decent work and economic growth, industry, innovation and infrastructure, and partnerships. This study employs panel data from 30 Chinese provinces spanning 2012–2021, combined with a two-way fixed effects model, mediating effect model, and threshold panel model, to empirically explore how the digital economy shapes foreign trade resilience and its implications for sustainable development. The findings demonstrate that the digital economy significantly empowers the enhancement of foreign trade resilience, with industrial structure advancement serving as a key mediating channel. This mechanism aligns with sustainable development principles by promoting resource allocation efficiency, reducing environmental footprints through optimized trade processes, and fostering inclusive industrial upgrading. To advance sustainable foreign trade development, policy implications include strengthening digital infrastructure, promoting the integration of digital economy and green industries, and optimizing institutional frameworks for inclusive digital trade. Full article