Search Results (168)

Against intensifying climate risks, a paradox persists in green finance: high corporate awareness yet low green bond issuance. This study examines the impact of climate risk on green bond issuance using a final sample of 5958 bond issuances, which were issued by 469 unique A-share non-financial listed companies in China between 2016 and 2023. By integrating the Fogg Behavior Model (FBM) into a Motivation–Capability–Triggers framework and employing Logit and Karlson–Holm–Breen (KHB) methods, we investigate the underlying mechanisms. The baseline results show a positive link between climate risk and issuance likelihood, confirming a motivation-incentive effect. Mechanism analyses reveal significant negative mediation through financing constraints, green innovation, and environmental reputation, highlighting a capability-constraint effect. Heterogeneity analysis finds a stronger effect in non-state-owned firms, non-heavily polluting industries, and firms in pilot zones or central/western China, indicating that policy signals and resource endowments act as key triggers to synergize motivation and capability. Our findings offer valuable insights for policymakers in designing motivation-stimulating and capability-compensating intervention strategies to help firms balance economic and environmental objectives. Full article

This study investigates the synergistic influence of multi-walled carbon nanotubes (MWC-NTs), nanosilica powder (NSP), and polypropylene fiber waste (PFW) on the mechanical performance of mortar incorporating demolished concrete waste aggregates (DCWA). The replacement of natural aggregates with DCWA typically results in strength reductions and weak interfacial transition zones; therefore, the combined use of nanomaterials and microfibers is proposed as a mitigation strategy. A Taguchi Design of Experiments (DOE) approach was employed to optimize mix parameters, including MWCNT dosage, NSP content, PFW volume fraction, and DCWA replacement level. Mortar mixtures were prepared with MWCNTs (0–0.1% by binder weight), NSP (0–2% by binder weight), PFW (0–0.3% by volume), and DCWA (0–20% replacement of fine sand). Mechanical performance was assessed through compressive and flexural strength tests. A combined statistical approach using the Pareto chart and ANOVA identified the most influential parameters and their respective contributions to the response variable. The innovative aspect of this research lies in the synergistic integration of MWCNTs, NSP, demolished concrete waste, and polypropylene fiber waste within the mortar matrix, with the incorporation of nanomaterials specifically intended to compensate for the strength reduction typically induced by the use of demolition concrete waste aggregates. Although a potential nano-scale synergy between MWCNTs and NSP was initially considered, the experimental results indicated that the most relevant synergistic effects occurred among broader mix parameters rather than specifically between the two nanomaterials. Even so, when assessed individually, both nanomaterials contributed to improving the mechanical characteristics of the mortar—particularly nanosilica, which demonstrated a more pronounced effect—yet these individual enhancements did not translate into a distinct synergistic interaction between MWCNTs and NSP. The Taguchi DOE proved to be an efficient tool for multiple factor analysis, enabling reliable identification of the most influential parameters with a minimum number of tests. Its application facilitated the development of mortar mixtures that effectively integrate demolition waste while achieving enhanced mechanical performance through nano- and micro-scale reinforcement. Full article

This paper focuses on addressing the finite-time tracking problem of a class of multi-agent systems (MASs) under specific perturbations. Each agent is modeled with general linear dynamics, and an undirected interconnected communication topology is assumed among the agents. A key technical innovation lies in the proposed adaptive rule, which dynamically tunes two critical elements: the parameters of the nonlinear compensation term in the reference input and the coupling weights between neighboring agents. By integrating this adaptive mechanism into a sliding mode control framework, rigorous theoretical analysis confirms that under suitable conditions, the controlled system can converge to an innovative desired switching surface within finite time, thereby further guaranteeing the MASs achieve finite-time bounded (FTB) tracking. The convergence time is elaborated in detail in the subsequent proof. Finally, numerical examples are presented to experimentally substantiate the effectiveness of the proposed approach. Full article

To address the key challenges of non-uniform energy distribution, local overheating, and unstable electromagnetic–thermal coupling in multi-source microwave heating systems, this paper proposes a distributed optimisation cooperative method based on phase–power coordinated control and consensus-feedback constraints. A two-stage multi-agent control mechanism, described as “phase leading, power following”, is constructed within a hierarchical architecture to achieve spatiotemporal collaborative optimisation from the perspectives of electromagnetic interference-field shaping and thermal feedback regulation. In the phase-regulation stage (Innovation 1), adaptive reconstruction of the interference field is achieved through relative phase specification and a two-level scanning mechanism, rapidly shaping the spatial energy distribution and enhancing the absorption efficiency of incident electromagnetic energy in the cavity–material system. In the power-regulation stage (Innovation 2), amplitude correction is performed under a stabilised interference-field background, and a consensus-feedback constrained regional energy collaboration network is established to ensure that regional energy states converge within the convex hull of the leader reference set. Power redistribution is driven by the target–region energy deviation and neighbourhood consistency relationships, enabling spatial reverse balancing of energy density, suppressing excessive heating in high-energy regions, and enhancing compensation in low-energy regions. Furthermore, a spatiotemporal dual-scale coupling consensus-optimisation framework (Innovation 3) is developed to form a cooperative loop between fast electromagnetic-field reconstruction and slow thermal-field dynamics, achieving synchronous improvement in energy utilisation efficiency and temperature-field uniformity with stable convergence. Simulation results demonstrate that, compared with conventional constant-power, single-phase, and single-power control strategies, the proposed method improves heating efficiency by 16.62–44.74%, and enhances temperature uniformity in vertical and horizontal sections by 8.84–55.87% and 11.41–40.54%, respectively. Full article

This paper examines how air pollution affects the distribution of labor income within firms. We build a within-firm incentive model and show that air pollution, treated as an exogenous shock, reduces production efficiency and increases operating uncertainty. In response, firms compress both employee and executive compensation. Because executive pay carries a larger weight on performance- and equity-based components and is therefore more sensitive to profit volatility, it declines by more, mechanically narrowing within-firm pay dispersion. At the same time, rank-and-file wages display downward rigidity. The result is a “synchronized decline with sharper cuts at the top,” a form of spurious equality. Using 2014–2022 data on non-financial A-share listed firms in China, we find that a 1% increase in air pollution is associated with a 0.37% average decline in labor income. Effects are stronger in labor-intensive firms and in firms with weaker unions. Two-stage least squares estimates indicate real consequences: talent outflows and reduced innovation. By linking air quality to wage setting, human capital, and innovation, our results reveal a sustainability channel through which pollution undermines decent work and inclusive growth—issues of global relevance for urban economies. The mechanisms we document are likely to generalize beyond China and inform integrated policies that combine environmental regulation with labor-market and innovation policy to support a just and sustainable transition. Full article

The accurate determination of an object’s centroid is a critical requirement in fields such as aerospace engineering and advanced manufacturing, where it is essential for quality control and system performance. Traditional methods, such as multi-point weighing, are often limited by restricted measurement ranges, inaccuracies from mechanical alignment tolerances, and susceptibility to lateral force interference from uneven platforms, which collectively constrain measurement precision. To address these challenges, a novel measurement framework is proposed that synergizes high-precision 3D scanning with Hooke’s law-based mechanical sensing. This methodology eliminates dependencies on mechanical positioning and offers enhanced compatibility with various object geometries through its non-contact 3D scanning. The system also integrates linear spring-based force transduction for enhanced load adaptability and incorporates active anti-tilt compensation using 3D scanning and motor leveling. Experimental validation demonstrated sub-millimeter accuracy compared to the multi-point weighing method, with measured centroid deviations of 0.01 mm (X-axis), 0.06 mm (Y-axis), and 0.03 mm (Z-axis), achieving a composite spatial precision of 0.07 mm. This methodological innovation not only expands the operational envelope of centroid measurement systems but also provides new theoretical insights and a robust methodology for measuring complex parts and systems. Full article

Drawing on an annual dataset of Chinese Shanghai and Shenzhen A-share listed companies covering the years 2011 to 2023, this study employs multiple regression analysis to investigate the impact of ESG information disclosure on corporate environmental performance and its underlying mechanisms. The results indicate that ESG disclosure significantly enhances environmental performance, a relationship mediated by green innovation, media attention, and executive compensation. Furthermore, heterogeneity analysis reveals that this positive effect is more pronounced in state-owned enterprises, firms with high-quality internal controls, and environmentally sensitive industries. This large-sample study provides a new perspective on how ESG disclosure bolsters corporate green competitiveness and long-term value, offering theoretical support for improving environmental governance and informing policy to promote sustainable economic development in China. Full article

Background: In China, a paradox has emerged: while the digital access gap narrows, a pronounced digital gradient—a sequential decline in outcomes from urban to county to township students—persists in innovation and entrepreneurship. This study investigates the hidden, cognitive mechanisms behind this enduring gradient inequality. Methods: Analyzing a national survey of 31,779 students, we employed statistical models designed to trace sequential pathways and account for institutional influences. Results: We found a clear urban > county > township gradient in students’ digital literacy, information perception, and innovation capabilities. The disparity is primarily driven by a cognitive mediation chain: rural students’ lower digital literacy inhibits their ability to perceive and evaluate information effectively, which in turn suppresses their innovation and entrepreneurial potential. This “digital literacy → information perception” pathway explains over 80% of the gap in entrepreneurial intention and one-third of the gap in innovation capacity. Crucially, elite “Double First-Class” universities mitigate this gradient; their robust offline support systems compensate for deficits in students’ digital literacy, reducing its necessity for entrepreneurial success. Conclusions: The contemporary digital divide is fundamentally a cognitive gradient. Moving forward, policy must look beyond infrastructure to foster a cognitive capacity to transform digital access into innovation capability, rather than merely expanding digital access. Our findings affirm that universities can act as powerful institutional compensators. A dual strategy that combines cognitive empowerment with targeted institutional support is essential to bridge the digital gradient and close the innovation gap across urban, county, and township student populations. Full article

Antimicrobial resistance (AMR) is a present, pressing global public health crisis associated with rising morbidity and mortality rates due to previously curable infectious disease. Targeted drug delivery is an important approach to address AMR due to its ability to improve the therapeutic performance of antibiotics without leading to any adverse effects or organ toxicities. In this review we explore molecular mechanisms of AMR and drawbacks of conventional antibiotic therapies and discuss unique drug delivery approaches to compensate these. Nanoparticulate carrier systems, stimuli-responsive systems, antibody–drug conjugates, and CRISPR-Cas systems are some of the carrier method designs that are promising for tackling hard to treat infections related to pathogenic strains and biofilms due to their features. Many of these are among the most significant advances in the field. However, there are many challenges to be overcome, with biological limitations, scaling and regulatory challenges, etc., before they can be employed in commercial applications. Materials are being developed, and an approach standardized and applicable to future work is in development to improve the efficiency of targeted delivery systems. Controlled drug delivery, which could be the answer to an increasing AMR problem, will not only help in alerting awareness among individuals but will also help in prolonging the activity of antibiotics by providing synergistic interdisciplinary solutions. This review emphasizes the complementary role of targeted drug delivery in transitioning from laboratory investigations to clinical therapy. It addresses underrepresented aspects, including new materials, scalability, regulatory considerations, and ethical implications, while offering a roadmap for translating innovations into next-generation antimicrobials. Full article

The growing environmental concern over waste tire accumulation necessitates innovative recycling strategies in construction materials. Therefore, this study aims to develop and evaluate sustainable concrete by integrating waste tire rubber (WTR) aggregates of different sizes and recycled waste tire steel fibers (WTSFs), assessing their combined effects on the mechanical and microstructural performance of concrete through experimental and analytical approaches. WTR aggregates, consisting of fine (0–4 mm), small coarse (5–8 mm), and large coarse (11–22 mm) particles, were used at substitution rates of 0–20%; WTSF was used at volumetric dosages of 0–2%, resulting in a total of 40 mixtures. Mechanical performance was evaluated using density and pressure resistance tests, while microstructural properties were assessed using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS). The findings indicate systematic decreases in density and compressive strength with increasing WTR ratio; the average strength losses were approximately 12%, 20%, and 31% at 5%, 10%, and 20% for WTR substitution, respectively. Among the WTR types, the most negative effect occurred in fine particles (FWTR), while the least negative effect occurred in coarse particles (LCWTR). The addition of WTSF compensated for losses at low/medium dosages (0.5–1.0%) and increased strength by 2–10%. However, high dosages (2.0%) reduced strength by 20–40% due to workability issues, fiber clumping, and void formation. The highest strength was achieved in the 5LCWTR–1WTSF mixture at 36.98 MPa (≈6% increase compared to the reference/control concrete), while the lowest strength was measured at 16.72 MPa in the 20FWTR–2WTSF mixture (≈52% decrease compared to the reference/control). A strong positive correlation was found between density and strength (r, Pearson correlation coefficient, ≈0.77). SEM and EDX analyses confirmed the weak matrix–rubber interface and the crack-bridging effect of steel fibers in mixtures containing fine WTR. Additionally, a hybrid prediction model combining physics-informed neural networks (PINNs) and CatBoost, supported by data augmentation strategies, accurately estimated compressive strength. Overall, the results highlight that optimized integration of WTR and WTSF enables sustainable concrete production with acceptable mechanical and microstructural performance. Full article

With the continuous advancement of urban construction, inertial sensors are increasingly used in the detection of underground pipelines. However, inertial measurement units (IMUs) are susceptible to a variety of error sources, leading to the accumulation of position estimation errors over time, which severely restricts their positioning accuracy. This paper provides a systematic review of IMU calibration and drift suppression error compensation methods applicable to underground pipeline environments. Building upon this foundation, it innovatively proposes a three-tiered review framework based on “error characteristics–compensation mechanisms–application scenarios”. The framework begins with the characterization of error factors, maps them to corresponding compensation mechanisms, and then applies them to specific operating conditions. It identifies current research limitations in real-time performance, robustness, experimental validation, and standardized evaluation. Future efforts should focus on designing lightweight fusion algorithms, integrating deep learning with sensor fusion, and establishing standardized testing platforms. This paper aims to summarize the current state and development trends of inertial sensor error compensation methods, providing a reference for advancing related technologies while offering beginners a clear and systematic learning path. Full article

Using economic and water consumption data from Inner Mongolia and its 12 cities (2004–2023), this study employs the Tapio decoupling model to investigate the relationship between water consumption and economic growth. The results show a general shift from weak to strong decoupling across the region, with extreme events such as the 2020–2021 pandemic period (decoupling index, DI = 10.31) causing clear disruptions. Regional disparities followed a triple pattern: industrial areas (e.g., Ordos, Baotou) achieved strong decoupling via innovation; agricultural regions (e.g., Tongliao, Bayannur) remained in weak negative decoupling modes due to rigid water demand; and ecologically vulnerable areas (e.g., Alxa League, Xilin Gol) saw high volatility and unsustainable policy effects. Our interpretation of the three patterns highlights the need for region-specific governance. The driving mechanisms mainly include uneven adoption of water-saving technology (e.g., low drip irrigation rates in agriculture), virtual water trade shifting pressures across regions, and climate extremes worsening imbalances. Based on these findings, we recommend differentiated subsidies, regional compensation mechanisms, and adaptive policies to support sustainable water–economy coordination in arid regions. Full article

High-quality corporate innovation serves as a critical driver for achieving corporate sustainable development. This study bridges the gap between macroeconomic fiscal sustainability and microeconomic innovation quality. Specifically, this paper investigates the influence of local fiscal sustainability on high-quality corporate innovation, examining the underlying mechanisms and heterogeneous effects. Methodologically, data were collected using Python-based retrieval and web-scraping techniques. A multi-dimensional index of local fiscal sustainability was constructed, comprising five key dimensions to quantitatively map provincial fiscal sustainability across China. Corporate innovation quality was measured using patent citation metrics. Employing panel data from A-share listed companies over the 2015–2023 period, we implemented a two-way fixed-effects model for rigorous empirical econometric analysis. The findings indicate a significant positive relationship between local fiscal sustainability and high-quality corporate innovation. This result remains robust after a battery of robustness tests, including the use of instrumental variable (IV) methods. Mechanism analysis reveals that the resource compensation effect is the primary channel. Furthermore, our analysis identifies heterogeneity across varying innovation environments, economic regions, and industry characteristics. The positive influence is particularly pronounced in provinces with stronger intellectual property protection, firms located in the eastern regions, and High-Tech Enterprises. Collectively, the conclusions drawn from this research offer valuable policy implications for strengthening local fiscal sustainability and enhancing high-quality corporate innovation. Full article

Against the backdrop of intensifying global technological competition and the deepening of the national innovation-driven strategy, private technology enterprises, as the core entities of technological innovation, have their sustainable innovation dynamics profoundly influenced by the strategic interactions among multiple parties such as the government, enterprises, and users. Based on evolutionary game theory, this paper constructs a tripartite evolutionary game model involving the government, private technology enterprises, and market users in the Chinese context. Through theoretical deduction and multi-scenario numerical simulation using Matlab, it systematically analyzes the logic of strategic choices and the laws of dynamic equilibrium of the three parties in the process of sustainable innovation. The research shows that the strategic evolution of multiple entities presents multiple equilibrium states. There exist critical thresholds for the intensity of policy support, the concentration of market competition, and users’ willingness to choose innovative products; beyond these thresholds, the marginal impact on sustainable innovation dynamics increases significantly. Further research finds that the government and enterprises need to compensate for the profit gap between users’ choice of innovative products and traditional products through a subsidy mechanism to form a positive cycle of “active innovation–market recognition–profit improvement”. This study enriches the theoretical system of multi-entity innovation dynamics by incorporating user behavior and provides a decision-making reference for optimizing innovation governance and fostering the development of sustainable innovation dynamics in private enterprises in China and other similar economies. Full article

As regional integration accelerates globally, green development has emerged as a pivotal imperative for reconciling economic growth with environmental sustainability. This study employs a Difference-in-Differences framework incorporating city and year fixed effects to examine the impact of regional integration on green development efficiency in China’s Yangtze River Delta. The empirical findings reveal that regional integration significantly undermines green development efficiency, a conclusion corroborated by rigorous robustness checks including parallel trends and placebo tests. Mechanism analysis demonstrates that trade openness and digital economy development function as partial mediating channels that modestly attenuate the direct adverse effect of regional integration, whereas the decline in secondary industry agglomeration amplifies the negative impact. Notably, innovation capability has yet to fully unlock its potential for green transformation, it intensifies the negative effects of regional integration across all three mediating mechanisms. Building on these findings, this study proposes policy recommendations including strengthening multi-level green governance frameworks, integrating ecological compensation and carbon trading systems, advancing low-carbon trade structures, promoting the synergistic development of digitalization and green transformation, facilitating the green transition of secondary industries, and reinforcing green technology innovation. These insights provide empirical evidence and policy references for achieving coherence between regional integration and sustainable development objectives. Full article