Search Results (1,475)

This study focuses on the impact of China’s digital economy on sustainable modernization from 2011 to 2021, using provincial panel data for empirical analysis. By applying threshold and mediation models, we find that the digital economy promotes modernization through industrial upgrading (with a mediating effect of 38%) and trade openness (coefficient = 0.234). The research reveals “U-shaped” nonlinear threshold effects at specific levels of digital development (2.218), market efficiency (9.212), and technological progress (12.224). Eastern provinces benefit significantly (coefficient ranging from 0.12 to 0.15 ***), while western regions initially experience some inhibition (coefficient = −0.08 *). Industrial digitalization (coefficient = 0.13 ***) and innovation ecosystems (coefficient = 0.09 ***) play crucial roles in driving eco-efficiency and equity, in line with Sustainable Development Goals 9 and 13. Meanwhile, the impacts of infrastructure (coefficient = 0.07) and industrialization (coefficient = 0.085) are delayed. Economic modernization improves (coefficient = 0.37 ***), yet social modernization declines (coefficient = −0.12 *). This study not only enriches economic theory but also extends the environmental Kuznets curve to the digital economy domain. We propose tiered policy recommendations, including the construction of green digital infrastructure, carbon pricing, and rural digital transformation, which are applicable to China and offer valuable references for emerging economies aiming to achieve inclusive low-carbon growth in the digital era. Future research could further explore the differentiated mechanisms of various digital technologies in the modernization process across different regions and how to optimize policy combinations to better balance digital innovation with sustainable development goals. Full article

Against the backdrop of digital transformation, this study constructs an analytical framework for the influence mechanism of the data-driven dynamic capabilities of foreign trade SMEs from the perspective of digital intelligence immunity, aiming to clarify the complex relationships among influencing factors and multi-combination paths for capability improvement. The research employs the fuzzy AHP-DEMATEL method to quantify the complex influence relationships among factors and uses fsQCA to analyze the configuration paths of high-level data-driven dynamic capabilities. Results show that digital intelligence management and analysis, digital intelligence supervision and early warning, and digital intelligence ecosystem are key drivers of data-driven dynamic capabilities, with digital intelligence talents serving as a guarantee and digital foundation as a foundation. The study identifies the following two core paths for forming high-level capabilities: “management–talent–ecology collaboration” and “early warning–technology–mechanism enhancement.” It concludes that foreign trade SMEs should strengthen digital intelligence management and ecological construction, improve early warning mechanisms, and adopt multi-pronged approaches to build data-driven dynamic capabilities, providing a theoretical basis for their digital transformation and capability upgrading. Full article

Since the early 21st century, urban shrinkage has become a significant global phenomenon. Dongguan, in Guangdong Province, China, is known as a “world factory”. It experienced notable urban shrinkage following the 2008 financial crisis. However, the city demonstrated remarkable recovery and ongoing development in subsequent years. On that basis, this study focuses on the following three points: (1) identifying the spatiotemporal factors contributing to the growth and shrinkage of manufacturing cities, taking Dongguan as an example; (2) explaining the influencing factors of the growth and shrinkage of Dongguan City during three critical periods, 2008–2014 (post-crisis), 2015–2019 (as machinery replaced human work), and 2020–2023 (the COVID-19 pandemic and recovery); and (3) selecting representative towns and streets for on-site observation and investigation, analyzing the measures they have taken to cope with growth and shrinkage during different periods. The key findings include the following: (1) The spatial dynamics of growth and shrinkage in Dongguan show significant temporal patterns, with traditional manufacturing areas shrinking from 2008 to 2014, central urban areas recovering from 2015 to 2019, and renewed shrinkage from 2020 to 2023. However, some regions maintained stability through strategic innovations. (2) Various factors, particularly industrial upgrading and technological innovation, drove the urban dynamics, enhancing economic resilience. (3) The case study of Houjie Town revealed successful adaptive mechanisms supported by policy while facing challenges like labor mismatches and inadequate R&D investment. This research offers insights for improving urban resilience and promoting sustainable development in Dongguan. Full article

The integration of financial technology expenditures and green total factor productivity (GTFP) constitutes a critical impetus for sustainable economic advancement. This study employs provincial panel data from China (2012–2020) and uses the SBM model with undesirable outputs, the PVAR model, moderation effect analysis, and threshold regression to investigate the underlying mechanisms and threshold effects of financial technology expenditure on GTFP. The results show that (1) financial technology expenditure has a significant promoting effect on the growth of GTFP, with a coefficient of 0.614 (p < 0.05), indicating the need for further increases in fiscal investment in science and technology; (2) the effect of financial technology expenditure on GTFP varies across the eastern, central, and western regions of China, with stronger effects observed in the eastern region, suggesting that the government should formulate differentiated financial technology expenditure policies on the basis of local conditions; and (3) that educational investment and industrial upgrading play strong moderating roles in the impact of financial technology expenditure on GTFP, with interaction term coefficients of 0.059 (p < 0.05) and 0.206 (p < 0.1), respectively. Threshold analysis further reveals that the positive effect strengthens significantly once educational investment surpasses a log value of 9.3674 and industrial upgrading exceeds a ratio of 0.0814. However, currently, China’s education investment and industrial structure upgrading are still insufficient, necessitating further increases in education investment and promoting the transformation and upgrading of the industrial structure. Full article

The air quality within urban public transport is a critical determinant of passenger health. In the crowded and poorly ventilated cabins of Almaty’s metro, buses, and trolleybuses, concentrations of CO₂ and PM_2.5 often accumulate, elevating the risk of respiratory and cardiovascular diseases. This study investigates the air quality along three of the city’s busiest transport corridors, analyzing how the concentrations of CO₂, PM_2.5, and PM₁₀, as well as the temperature and relative humidity, fluctuate with the passenger density and time of day. Continuous measurements were collected using the Tynys mobile IoT device, which was bench-calibrated against a commercial reference sensor. Several machine learning models (logistic regression, decision tree, XGBoost, and random forest) were trained on synchronized environmental and occupancy data, with the XGBoost model achieving the highest predictive accuracy at 91.25%. Our analysis confirms that passenger occupancy is the primary driver of in-cabin pollution and that these machine learning models effectively capture the nonlinear relationships among environmental variables. Since the surveyed routes serve Almaty’s most densely populated districts, improving the ventilation on these lines is of immediate importance to public health. Furthermore, the high-temporal-resolution data revealed short-term pollution spikes that correspond with peak ridership, advancing the current understanding of exposure risks in transit. These findings highlight the urgent need to combine real-time monitoring with ventilation upgrades. They also demonstrate the practical value of using low-cost IoT technologies and data-driven analytics to safeguard public health in urban mobility systems. Full article

Nearly zero-energy buildings (nZEBs) are central to global carbon reduction strategies, and Taiwan is actively promoting their adoption through building energy performance labeling, particularly in the retrofit of existing buildings. Under Taiwan’s nZEB framework, qualification requires both an A⁺ energy performance label and over 50% energy savings from retrofit technologies. This study proposes an integrated assessment framework for retrofitting small- to medium-sized office buildings into nZEBs, incorporating diagnostics, technical evaluation, policy alignment, and resource integration. A case study of a bank branch in Kaohsiung involved on-site energy monitoring and EnergyPlus V22.2 simulations to calibrate and assess the retrofit impacts. Lighting improvements and two HVAC scenarios—upgrading the existing fan coil unit (FCU) system and adopting a completely new variable refrigerant flow (VRF) system—were evaluated. The FCU and VRF scenarios reduced the energy use intensity from 141.3 to 82.9 and 72.9 kWh/m²·yr, respectively. Combined with rooftop photovoltaics and green power procurement, both scenarios met Taiwan’s nZEB criteria. The proposed framework demonstrates practical and scalable strategies for decarbonizing existing office buildings, supporting Taiwan’s 2050 net-zero target. Full article

ComPair, a prototype of the All-sky Medium Energy Gamma-ray Observatory (AMEGO), completed a short-duration high-altitude balloon campaign on 27 August 2023 from Fort Sumner, New Mexico, USA. The goal of the balloon flight was to demonstrate ComPair as both a Compton and Pair telescope in flight, reject the charged particle background, and measure the background $\gamma$-ray spectrum. This analysis compares measurements from the balloon flight with Monte Carlo simulations to benchmark the instrument. The comparison finds good agreement between the measurements and simulations and supports the conclusion that ComPair accomplished its goals for the balloon campaign. Additionally, two charged particle background rejection schemes are discussed: a soft ACD veto that records a higher charged particle event rate but with less risk of event loss, and a hard ACD veto that limits the charged particle event rate on board. There was little difference in the measured spectra from the soft and hard ACD veto schemes, indicating that the hard ACD veto could be used for future flights. The successes of ComPair’s engineering flight will inform the development of the next generation of ComPair with upgraded detector technology and larger active area. Full article

With an economic model characterized by high energy consumption and low efficiency, China is facing serious energy shortages and environmental problems. However, education, as the cornerstone of social progress, has been overlooked in its role in improving energy efficiency. This study aims to enhance our understanding of the impact of educational competitiveness on urban green total factor energy efficiency (GTFEE), helping policymakers to achieve sustainable urban development. This study utilizes panel data from 20 major Chinese cities spanning from 2012 to 2022 and applies a two-way fixed effects model to investigate the relationship and pathways of educational competitiveness (Ec) on GTFEE. Our results show that the Ec index can enhance the major urban GTFEE. Among them, educational resource competitiveness, input competitiveness, efficiency competitiveness, and sustainable competitiveness can all enhance urban GTFEE, but the coefficient of the educational scale is not significant. In addition, Ec can effectively improve GTFEE by promoting green technological innovation, alleviating human resource mismatch, and driving industrial structure upgrading. Furthermore, the impact of Ec on GTFEE shows significant regional heterogeneity, with its effect weakening from the eastern coastal areas to the western inland regions. Full article

The equitable allocation of clean energy access across towns–rural divides is a critical benchmark of modernization in developing economies. This is because it is intricately linked to the realization of strategic goals such as shared prosperity, ecological civilization advancement, and national energy security reinforcement. This research examines the impact of China’s digital village (DV) construction in reducing the urban–rural disparity in household clean energy access, evaluates the effect on towns–rural clean energy consumption inequality (CEI), explores the mediating mechanisms, and considers regional heterogeneity. It is an innovative approach to test the influence of digital village construction on clean energy consumption inequality between urban and rural areas, beyond which conventional research is limited to infrastructure investment and policy considerations. We can reach the following three results: (1) With the continuous improvement of digital village construction, CEI between towns and rural areas shows an “inverted U-shaped” change. (2) From the perspective of the intermediary mechanism, agricultural technological progress (ATP) and industrial structure upgrading (IND) can facilitate digital village construction and reduce the disparity in clean energy consumption between towns and rural regions. (3) From the perspective of heterogeneity analysis, digital village construction in areas with low urbanization levels, high terrain undulation, and non-clean energy demonstration provinces can significantly alleviate CEI. It is on this basis that the present paper proposes a policy recommendation for the Chinese government to effectively reduce the gap between towns and rural clean energy consumption in the process of digital village construction. Full article

Lignin, the most abundant renewable aromatic biopolymer on Earth, is rapidly emerging as a powerful enabler of next-generation sustainable technologies. This review shifts the focus to the latest industrial breakthroughs that exploit lignin’s multifunctional properties across energy, agriculture, healthcare, and environmental sectors. Lignin-derived carbon materials are offering scalable, low-cost alternatives to critical raw materials in batteries and supercapacitors. In agriculture, lignin-based biostimulants and controlled-release fertilizers support resilient, low-impact food systems. Cosmetic and pharmaceutical industries are leveraging lignin’s antioxidant, UV-protective, and antimicrobial properties to create bio-based, clean-label products. In water purification, lignin-based adsorbents are enabling efficient and biodegradable solutions for persistent pollutants. These technological leaps are not merely incremental, they represent a paradigm shift toward a materials economy powered by renewable carbon. Backed by global sustainability roadmaps like the European Green Deal and China’s 14th Five-Year Plan, lignin is moving from industrial residue to strategic asset, driven by unprecedented investment and cross-sector collaboration. Breakthroughs in lignin upgrading, smart formulation, and application-driven design are dismantling long-standing barriers to scale, performance, and standardization. As showcased in this review, lignin is no longer just a promising biopolymer, it is a catalytic force accelerating the global transition toward circularity, climate resilience, and green industrial transformation. The future of sustainable innovation is lignin-enabled. Full article

In recent years, 3D pixel sensors have been a topic of increasing interest within the High Energy Physics community. Due to their inherent radiation hardness, demonstrated up to a fluence of $3\times {10}^{16}$ 1 MeV equivalent neutrons per square centimeter, 3D pixel sensors have been used to equip the innermost tracking layers of the ATLAS and CMS detector upgrades at the High-Luminosity Large Hadron Collider. Additionally, the next generation of vertex detectors calls for precise measurement of charged particle timing at the pixel level. Owing to their fast response times, 3D sensors present themselves as a viable technology for these challenging applications. Nevertheless, both radiation hardness and fast timing require 3D sensors to be operated with high bias voltages on the order of ∼150 V and beyond. Special attention should therefore be devoted to avoiding problems that could cause premature electrical breakdown, which could limit sensor performance. In this paper, TCAD simulations are used to gain deep insight into the impact of surface isolation layers (i.e., p-stop and p-spray) used by different vendors on the high-voltage tolerance of small-pitch 3D sensors. Results relevant to different geometrical configurations and irradiation scenarios are presented. The advantages and disadvantages of the available technologies are discussed, offering guidance for design optimization. Experimentalmeasurements from existing samples based on both isolation techniques show good agreement with simulated breakdown voltages, thereby validating the simulation approach. Full article

In recent years, with the development of science and technology and the transformation of economic structures, rubidium and cesium have gradually become indispensable rare metal resources as important materials for high-tech industries. However, the relationship between supply and demand of resources is unbalanced, industrial demand is much higher than production, and the rubidium and cesium resources in hard rock minerals such as traditional pegmatite minerals are no longer enough to support global scientific and technological upgrading. There is therefore an urgent need to expand sources of resource extraction and recovery to meet market demand. This paper summarizes the current feasible technologies for extracting rubidium and cesium from pegmatite minerals, silicate minerals, salt lake brines and other potential resources. Full article

While electric unmanned aerial vehicles (UAVs) offer advantages in noise reduction, safety, and operational efficiency, their endurance is limited by current battery technology. Extending flight autonomy without compromising performance is a critical challenge in UAV system development. Previous studies introduced hybrid micro-turbogenerator architectures, but limitations in control stability and output power constrained their practical implementation. This study aimed to finalize the design and experimental validation of an optimized hybrid power system featuring a micro-turboprop engine mechanically coupled to an upgraded electric generator. A fuzzy logic-based control algorithm was implemented on a single-board computer to enable autonomous voltage regulation. The test bench architecture was reinforced and instrumented to allow stable multi-stage testing across increasing power levels. Results demonstrated stable voltage control at 48 VDC and electrical power outputs up to 3 kW, with an estimated maximum of 3.5 kW at full throttle. Efficiency was calculated at approximately 67%, and analysis of the generator’s KV constant revealed that using a lower KV variant (KV80) could reduce required rotational speed (RPM) and improve performance. These findings underscore the value of adaptive hybridization in UAVs and suggest that tuning generator electromechanical parameters can significantly enhance overall energy efficiency and platform autonomy. Full article

In recent years, passive acoustic monitoring (PAM) technology has significantly contributed to advancements in aquaculture techniques, system iterations, and increased production yields within intelligent feeding systems for Penaeus vannamei. However, current PAM-based intelligent feeding systems do not incorporate environmental factors into the decision process, limiting the improvement of monitoring accuracy in complex environments such as ponds. To establish a connection between environmental factors and the feeding acoustics of P. vannamei, this study utilized PAM technology combined with video analysis to investigate the effects of three key environmental factors—temperature, ammonia nitrogen, and nitrite nitrogen—on the feeding behavioral characteristics of shrimp, with a specific focus on acoustic signals “clicks”. The results demonstrated a significant correlation between the number of clicks and feed consumption in shrimp across different treatments, establishing this stable relationship as a reliable indicator for assessing shrimp feeding status. When water temperature increased from 20 °C to 32 °C, shrimp feed consumption showed an elevation from 0.46 g to 0.95 g per 30 min, with the average number of clicks increasing from 388 to 2947.58 and sound pressure levels rising accordingly. Conversely, ammonia nitrogen at 12 mg/L reduced feed consumption by 0.15 g and decreased click counts by 911.75 pulses compared to controls, while nitrite nitrogen at 40 mg/L similarly suppressed feed consumption by 0.15 g and the average number of clicks by 304.75. A rise in water temperature stimulated shrimp behaviors such as feeding, swimming, and foraging, while elevated concentrations of ammonia nitrogen and nitrite nitrogen significantly inhibited shrimp activity. Redundancy analysis revealed that temperature was the most prominent factor among the three environmental factors influencing shrimp feeding. This study is the first to quantify the specific effects of common environmental factors on the acoustic feeding signals and feeding behavior of P. vannamei using PAM technology. It confirms the feasibility of using PAM technology to assess shrimp feeding conditions under diverse environmental conditions and the necessity of integrating environmental monitoring modules into future feeding systems. This study provides behavioral evidence for the development of precise feeding technologies and the upgrade of intelligent feeding systems for P. vannamei. Full article

Chemical products, including cleaning agents, disinfectants, stain removers, and cosmetics, release harmful chemicals that pose a risk to human health and the environment, necessitating alternative sources. The objective of this research was to identify the most effective phytoextract from food production waste for use in sustainable aerosol hygiene technology as an electrostatic bio-disinfectant. The investigation was performed through wipe tests and airborne microbial collection techniques. The upgraded coffee silverskin phytoextract demonstrated superior disinfection potential for various surfaces and airborne microbes compared to the hot trub phytoextract, with an industrial disinfectant serving as the control. Log reduction analyses revealed a more significant killing efficacy (p ≤ 0.05, using the ANOVA test) against Gram-positive organisms (Bacillus subtilis and Listeria monocytogenes) than against Gram-negative organisms (Escherichia coli and Vibrio parahaemolyticus), with the log reductions ranging from 3.08 to 5.56 and 3.72 to 5.81, respectively. Chemical characterization by LC-ESI-QTOF-MS, ¹H NMR, and FTIR showed that CGAs and chalcones are the most bioactive compounds in CSS and HT, respectively. The innovation in this work involves an integrated approach that combines waste-derived phytoextracts, advanced chemical profiling, and scalable aerosol disinfection. Furthermore, this research offers a greener, cost-effective, and industrially relevant alternative to synthetic chemical disinfectants. The interdisciplinary approach contributes to the development of bio-based disinfectants for use in the food industry, hospitals, and public health settings. This investigation supports a paradigm shift toward sustainable disinfection practices, thereby improving food and environmental safety. Full article