Search Results (1,550)

This study examines how the Central Environmental Protection Inspection (CEPI), a vertical oversight initiative launched in China in 2016, affects corporate ESG performance. While prior studies have documented a positive effect of CEPI on ESG performance, the underlying mechanisms and firm-specific contingencies remain largely unexplored. Treating CEPI as a quasi-natural experiment, we employ a multi-period difference-in-differences design with firm and year fixed effects, using panel data on A-share listed firms from 2011 to 2022. Supported by a battery of robustness checks, the results indicate a positive association between CEPI and corporate ESG performance. Our mediation analysis identifies three distinct transmission channels: government environmental subsidies, green technological innovation, and public environmental concern. Moreover, we find that CEPI’s impact is more pronounced among state-owned enterprises, heavily polluting firms, large firms, and manufacturing firms, and is amplified in highly marketized regions. These findings highlight the importance of vertical regulatory oversight in shaping corporate sustainability and offer practical implications for designing differentiated environmental policies. Full article

Against the backdrop of global forest degradation and timber supply constraints, improving green production efficiency in forestry while securing timber supply is an important challenge for sustainable forest management. Treating China’s National Reserve Forest Policy (NRFP) as a quasi-natural experiment, this study uses panel data for 114 prefecture-level cities from 2011 to 2022, including 67 treated and 47 control cities. We employ a staggered difference-in-differences estimator based on group-time average treatment effects, together with transmission-channel analysis, difference-in-difference-in-differences (DDD), and a spatial difference-in-differences–spatial Durbin model (Spatial DID-SDM). The baseline estimates yield an overall ATT of 0.0149, indicating an average increase of 0.0149 index points in forestry GTFP for treated cities relative to the estimated counterfactual without the NRFP. This effect is approximately 1.49% of the sample mean of forestry GTFP (0.998) and remains stable across multiple robustness and sensitivity checks. NRFP implementation is separately associated with increases in capital deepening (CD) and physical labor productivity (PLP), while the lagged values of CD and PLP are each positively associated with forestry GTFP; these results are consistent with CD and PLP as potential transmission channels. The estimated NRFP effect is significantly weaker in resource-based cities and significantly stronger in economy-efficiency-oriented regions. Spatial effect decomposition shows that both the direct and indirect effects of the NRFP are positive and statistically significant. Under the alternative spatial weight matrix, both effects retain their direction and statistical significance, while the magnitude of the indirect effect remains broadly stable, suggesting that the positive spatial spillover effect of the NRFP on forestry GTFP is reasonably robust to the spatial weight matrix specification. These findings provide city-level empirical evidence for evaluating NRFP performance and informing differentiated policy design. Full article

Amid global economic uncertainty caused by the COVID-19 pandemic and geopolitical conflict, countries worldwide have prioritized urban economic resilience (UER). Using panel data for 283 Chinese cities from 2012 to 2023, this paper applies a difference-in-differences model to estimate the effect of the Pilot Battery Recycling Policy (PBRP) on UER. The results show that: (1) The estimated PBRP coefficient is positive at 0.004 units, equivalent to approximately 4.5% of the sample mean, and the result remains stable across a series of robustness and identification tests. (2) The mechanism and bootstrap mediation analyses provide evidence consistent with three potential city-level transmission channels associated with pilot designation: higher government technology spending, improved energy utilization, and greater total factor productivity. (3) The policy effect is positive and significant in upstream and downstream cities of the Yangtze River Basin, declining resource-based cities, and medium- and small-sized cities; it is negative in regenerative resource-based cities and megacities, while the remaining subgroup estimates are statistically insignificant. The subgroup patterns indicate that industrial foundations, adjustment costs, market capacity, and city scale may help shape policy effectiveness. (4) The Spatial Durbin Model identifies a positive direct effect on pilot cities and a negative indirect effect on neighboring cities under both selected spatial weight matrices. The matrix-specific admissibility and numerical checks confirm the validity of the spatial decomposition. Taken together, the findings point to a positive contribution of pilot designation to local economic resilience. The city-level results point to technological investment, energy-use efficiency, and productivity growth as potential transmission channels, while regional coordination can help manage cross-city competition for recycling resources and capacity. Full article

Natural gas consumption in urban residential buildings is important for household energy affordability and the low-carbon transition of the residential sector. Using panel data from 30 Chinese provinces from 2005 to 2020, this study employs a panel regression model to examine the impact of residential natural gas prices (NPs) on per capita natural gas consumption (NGC) in urban residential buildings. We apply the model to estimate price elasticity and analyze the transmission mechanism of energy consumption intensity (EI), while examining the differentiated characteristics of price effects from both regional and urbanization-stage perspectives. The main findings are as follows: (1) NP shows a significantly negative association with residential NGC, with a price elasticity of −1.182; (2) EI serves as a potential transmission channel between NP and NGC, with its indirect effect offsetting 12.5%; (3) heterogeneity analysis shows that price elasticity is statistically significant only in the western region. Across urbanization quartiles, the absolute magnitude of price elasticity is greatest in Q2. This study provides empirical evidence to optimize tiered natural gas pricing, refine targeted subsidy policies, and inform energy utilization policies in urban residential areas. Full article

Discrete-Variable Quantum Key Distribution (DV-QKD) provides a mechanism for establishing secret keys between legitimate parties using quantum-state transmission and authenticated classical post-processing. In this work, the underlying quantum layer follows a biased-basis decoy-state BB84 model using phase-randomized weak coherent pulses, while additional implementation-level mechanisms are integrated to support Cyber-Physical System (CPS) communication. Exponential Double Delta Encoding-based Merkle Tree (EDDE-MT) is employed as a receiver-side detection-record integrity mechanism for detecting deletion, insertion, reordering, or modification of records relative to an authenticated committed detection-event batch. It does not establish the completeness of the original TCSPC acquisition, detect records omitted before commitment, detect physical photon loss, or increase the information-theoretic secrecy of the QKD key. Time-Correlated Single Photon Counting (TCSPC) is used for detection-event and timing acquisition, while 2’s Complement Cyclic Redundancy Check-based Low-Density Parity Check (2CCRC-LDPC) supports error reconciliation. Following privacy amplification, the legitimate parties retain matching copies of the distilled QKD key locally. Discrete Variable Quantum Mellin Transform Cryptography (DVQMTC) uses fresh, non-reused segments of this privacy-amplified key for application-layer payload protection; the Mellin-transform component is treated only as implementation-level preprocessing and not as a cryptographic key-generation mechanism. Side-channel monitoring is performed using Gini Cramer’s V Correlation-Stationary Wavelet Transform (GCVC-SWT), Helical Valley-Principal Component Analysis (HV-PCA), and an Entmax-based hyperbolic Tangent exponential Linear Unit-Bidirectional Long Short-Term Memory (E-TeLU-Bi-LSTM) classifier. On the AES-HD benchmark, E-TeLU-Bi-LSTM achieved 99.24% classification accuracy; this value represents benchmark-level classification performance and is not interpreted as experimental validation of physical side-channel protection in a deployed DV-QKD system. Frequency Division Multiple Access (FDMA) and the Halton Quasi-Sequence-Invasive Weed Optimization Algorithm (HQS-IWOA) are further incorporated as classical network-resource segmentation and load-management mechanisms and do not modify the composable QKD security bound. The contribution of the work is therefore positioned as a system-level engineering integration of QKD key establishment, detection-record integrity, reconciliation, application-layer data protection, side-channel monitoring, and network-resource management for CPS. The information-theoretic secrecy claim remains restricted to the underlying finite-key decoy-state BB84 procedure under the stated security assumptions; no new QKD security theorem, formally new cryptographic primitive, or experimentally validated physical quantum communication capability is claimed. Full article

Agricultural new quality productive forces (ANQP) provide an important foundation for high-quality agricultural development and sustainable rural transformation. Using panel data for 30 Chinese provinces from 2011 to 2022, this study examines the effect of digital financial inclusion (DFI) on ANQP and the channels through which that effect operates. The results show that DFI is significantly and positively associated with ANQP. A one-standard-deviation increase in DFI is associated with an increase in ANQP equivalent to approximately 64.35% of its sample mean. Green technological innovation serves as a statistically significant transmission channel, although its indirect effect accounts for only 3.31% of the total effect. The relationship between DFI and ANQP exhibits a double-threshold pattern with respect to the level of DFI and a single-threshold pattern with respect to regional economic development, with the estimated coefficients increasing gradually across regimes. Decomposing DFI shows that coverage breadth, usage depth, and digitization all contribute positively to ANQP. Further analysis of the outcome dimensions indicates that DFI is positively associated with agricultural laborers, agricultural labor objects, and agricultural labor resources. The estimated association is also larger in regions with more developed traditional financial systems. These results provide a multidimensional and stage-based understanding of the relationship between digital finance and agricultural productive-capability upgrading. Full article

Vehicular ad hoc networks (VANETs) have become a vital component of intelligent transport systems, with their security concerns increasingly drawing attention. To safeguard user privacy and ensure data authenticity and integrity, researchers have devised numerous certificateless conditional privacy-preserving authentication (CLCPPA) schemes. However, existing schemes generally suffer from insufficient security or high computational and communication overhead. Moreover, most implicitly assume the existence of a secure channel between vehicles and trusted entities during pseudonym generation and transmission, making it difficult to meet the real-time demands and practical deployment requirements of VANETs. To address these issues, this paper constructs a certificateless aggregated conditional privacy-preserving authentication (CL-ACPPA) scheme under elliptic curve cryptography that does not require bilinear operations. Formal security analysis demonstrates that, under the Random Oracle Model and the elliptic curve discrete logarithm problem assumption, the proposed scheme resists adaptive chosen-message attacks from adversaries with varying capabilities. Performance analysis and experimental results demonstrate that, compared with existing schemes, the proposed scheme achieves higher security while maintaining low communication and computational overhead. Full article

In most railway divisions the results of scheduled inspections of automation and telemechanics field devices are still recorded on paper. Such records reach engineering management with a delay, are easy to lose, and are difficult to verify. This paper examines the data transmission core of a digital inspection complex in which passive RFID tags identify both the equipment and the personnel, and the inspection record is delivered to a cloud server over a hybrid cellular architecture combining a failure-prone GSM channel with a reliable CDMA channel. To quantify the stability of such a system, a continuous-time Markov chain model is constructed in which the link is represented as an M/M/2/K queue with one unreliable server: both channels carry traffic in parallel, and during a GSM outage the CDMA channel alone sustains service. Records already admitted are preserved across a channel switch; only records arriving at a full shared buffer are rejected. This residual overflow loss stays below 0.1% at routine load with a buffer of m ≥ 5 and reaches about 2.8% only under post-incident overload. The model parameters were measured on an operating ESP32-based scanner complex piloted at Hamza station on 46 point machines. Calculations for three load scenarios show that increasing the local buffer beyond m = 5 yields diminishing returns while the delay grows, and that resilience is governed primarily by the presence of the redundant channel and adequate buffering, with the primary-channel recovery rate a secondary factor. Full article

This study examines the relationship between financial inclusion and economic growth, focusing specifically on the role of financial sector development in South Asia. The research encompasses annual data from five developing economies in South Asia: Bangladesh, India, Pakistan, Nepal, and Sri Lanka, during the period from 2000 to 2024. Multidimensional indicators of financial inclusion, economic growth, and financial sector development were generated using principal component analysis, while the panel autoregressive distributed lag–pooled mean group technique was applied to evaluate both long-run and short-run dynamics. The findings indicate that growth of the financial sector contributes significantly to economic development, providing its position as a major force behind economic expansion. The results suggest that financial sector development may represent a potential transmission channel linking financial inclusion and economic growth. The study highlights the importance of strengthening inclusive financial systems and financial sector institutions to achieve sustainable economic growth in South Asia, and offers policy recommendations for enhancing financial access, financial literacy, innovation, and financial market efficiency. Full article

Symbiotic radio (SR) has emerged as a spectral-efficient paradigm for Internet-of-Things networks. However, simultaneously optimizing coexisting primary and secondary transmissions remains a challenge. To address this, a joint precoding and RIS phase shift design is proposed to maximize the sum-rate in the reconfigurable intelligent surface (RIS)-aided multiple-input single-output SR system. Specifically, based on an optimization problem that maximizes the sum-rate of primary and secondary data, an iterative algorithm that sequentially updates the precoder and the RIS phase shift matrix is developed. To address practical aspects, channel training overhead and minimum signal-to-interference-plus-noise ratio (SINR) constraints are also considered in the precoder design. Simulation results verify that the precoder design based on perfect successive interference cancellation achieves the highest sum-rate. The results also highlight the necessity of the proposed SINR-constrained precoding schemes in guaranteeing data rates of the primary and secondary links under various channel environments, proving the practical validity of our joint precoder and RIS phase shift design. Full article

Flood forecasting often depends on upstream hydrographs that are unavailable, incomplete, or unreliable. Reverse Flood Routing (RFR) addresses this gap by reconstructing upstream inflows from downstream observations, yet its operational use remains limited by numerical instability, observational uncertainty, and the ill-posed nature of the inverse problem. This review critically synthesizes RFR methodologies across a physics–fidelity continuum, ranging from storage-based and simplified hydraulic models to full hydrodynamic inversions, optimization-based techniques, Bayesian approaches, and emerging data-driven methods. The reviewed approaches are compared in terms of physical realism, numerical stability, computational demand, data requirements, uncertainty treatment, and field applicability. The synthesis indicates that storage-based methods remain attractive for data-limited and computationally constrained applications, whereas full hydrodynamic models are better suited to complex flow conditions involving backwater effects and detailed channel hydraulics. Optimization-based and Bayesian approaches can improve parameter estimation and uncertainty representation, while hybrid AI–physics methods offer promise for computational acceleration but still require stronger physical constraints and broader operational validation. Across all methodological families, error amplification, lateral inflow, transmission losses, and inconsistent benchmarking remain persistent limitations. An integrated framework is therefore proposed to connect observations, model selection, regularization, uncertainty quantification, hybrid computational methods, and operational decision support, providing a roadmap for more reliable and scalable RFR applications. Full article

Magnetic-field coupled wireless power transfer (MC-WPT) systems require reliable power delivery as well as real-time bidirectional data communication. To satisfy this requirement, a simultaneous wireless power and full-duplex data transfer (SWPFDT) system based on a three-coupled bilateral LCC topology is proposed in this paper. In the proposed structure, the power coil, backward-signal coil, and forward-signal coil are implemented as a solenoid-type monopole coil, a solenoid-type bipolar coil, and a DD (double-D) coil, respectively. By utilizing the orthogonal relationship among the magnetic-field distributions of different coils, the desired coupling within each channel and mutual decoupling among the three coil sets are achieved, thereby structurally reducing inter-channel crosstalk. Based on this configuration, an equivalent circuit model of the system is established, through which the constant-current output characteristics, forward and backward signal transmission gains, signal crosstalk, and power-to-signal interference are analytically derived. In addition, the resonant parameters and wave-trapping networks are designed accordingly. A laboratory prototype is developed for experimental verification. Experimental results show that the proposed system can achieve 150 W power transfer with an efficiency of 88.7%. With a 19.2 kbps communication rate, the system can stably realize full-duplex data transmission with limited interference between the forward and backward channels, while maintaining constant-current output and reliable communication under dynamic load switching. Full article

Internet of Things (IoT) devices equipped with electromagnetic sensors, such as millimeter-wave radars, generate massive amounts of computation-intensive and latency-sensitive sensing data. However, their limited computational capability and energy supply hinder real-time local processing. Edge computing can alleviate this limitation by offloading electromagnetic sensing tasks to nearby edge servers. Nevertheless, the broadcast nature of wireless channels exposes sensing data to eavesdropping, while the heterogeneity of multi-source electromagnetic sensing data further complicates sensing-data offloading optimization. To address this issue, this paper develops secure edge-assisted sensing-data offloading framework for heterogeneous electromagnetic sensors deployed on IoT devices. Considering the energy consumed by electromagnetic sensing, wireless transmission, and edge computing, together with the end-to-end latency constraint, a secrecy energy efficiency maximization problem is formulated by jointly optimizing spectrum assignment, transmit power, and computing resource allocation. The simulation results demonstrate that the proposed algorithm improves secrecy energy efficiency at least 31% compared with benchmark schemes within a specific range, demonstrating its effectiveness for secure and energy-efficient electromagnetic sensing-data offloading. Full article

Commercial pacemaker (PCM) analyzers are often expensive, proprietary, and difficult to adapt for experimental biomedical research and educational applications. This work presents a low-cost modular platform for the generation, acquisition, and real-time analysis of pacemaker-related electrical signals. The proposed system consists of two independent printed circuit boards: a digital-to-analog (DAC) board for generation of controlled atrial and ventricular test waveforms and an analog-to-digital (ADC) board for multi-channel signal acquisition and wireless data transmission. A dedicated Qt-based desktop application provides real-time visualization and storage of the acquired signals. Experimental validation was performed using a single commercial dual-chamber pacemaker operating in the DDD mode. For the DAC subsystem, pacing-rate errors remained below 2% over the investigated range of 60–120 BPM, with coefficients of determination exceeding 0.99998 between programmed and measured pacing rates. The ADC subsystem demonstrated relative amplitude errors ranging from 0.96% to 7.19% over the investigated input range of −1000 to −2000 mV. For a programmed atrioventricular delay of 200 ms, the ADC-derived delay was 205.53 ± 1.24 ms, corresponding to a relative error of 2.77%. Combined DAC–ADC operation further demonstrated generation of a controlled atrial test signal, pacemaker sensing and ventricular pacing response, and subsequent acquisition of the response by the ADC subsystem. The developed platform provides a configurable and modular experimental environment in which signal generation and acquisition can be operated either independently or jointly. Its low implementation cost, wireless data transmission, and customizable hardware and software architecture make it suitable for laboratory research, education, and prototype development involving cardiac pacing systems. Full article

Driven by the strategies of high-quality development and manufacturing transformation and upgrading, China’s economy is gradually shifting to an innovation-driven growth model. Empowering firms to lift innovation quality through new-generation artificial intelligence has become a core priority for industrial development and policy support. This paper adopts unbalanced panel data of A-share listed manufacturing firms from 2012 to 2023 and employs the Double Machine Learning model to systematically investigate the impact and transmission mechanisms of new-generation artificial intelligence on manufacturing firms’ innovation quality. The results reveal that new-generation artificial intelligence can significantly boost manufacturing firms’ innovation quality, and this core conclusion remains valid after a series of robustness tests. Mechanism verification confirms that new-generation artificial intelligence promotes the upgrading of firms’ human capital structure, deepens firms’ digital transformation, and raises firms’ R&D investment intensity. These three channels work synergistically to indirectly empower the upgrading of firms’ innovation quality. Heterogeneity analysis verifies that the innovation quality improvement effect of new-generation artificial intelligence exhibits prominent stratified differences across regions, industrial sectors, and environmental regulatory scenarios. Specifically, the empowerment effect of new-generation artificial intelligence (GAI) is significantly stronger for samples from environmental pilot cities, Southern Coastal, Eastern Coastal, and Northern Coastal regions, as well as high-tech manufacturing firms. In contrast, its positive driving effect is weak or insignificant for samples in the middle reaches of the Yellow River and Northwest China, along with non-high-tech industries. This paper improves the theoretical analytical framework for artificial intelligence empowering micro-firm innovation and enriches relevant research on digital technologies and corporate innovation. It provides a theoretical basis and practical implications for China’s manufacturing sector to break through innovation bottlenecks via intelligent technologies and achieve comprehensive high-quality innovative development across the manufacturing industry. Full article