Search Results (6,793)

ESG (Environmental, Social, and Governance) performance is increasingly viewed as a strategic factor shaping firms’ innovation activities. However, existing studies have largely examined green innovation as a whole, with limited attention to low-carbon technological innovation as a distinct domain and insufficient understanding of its driving mechanisms and conditional heterogeneity. Using panel data on Chinese A-share listed companies from 2009 to 2024, this study employs a two-way fixed-effects framework to examine the effect of ESG performance on low-carbon technological innovation, and further investigates the underlying transmission mechanisms and heterogeneous effects. The results show that ESG significantly promotes low-carbon technological innovation, with a notably stronger effect on substantive innovation than on strategic innovation, indicating that ESG drives genuine technological advancement rather than superficial patent accumulation. Mechanism tests reveal that ESG facilitates innovation by easing financing constraints and enhancing government support. At the dimensional level, the environmental and social pillars exert significant positive effects, whereas the governance pillar does not. Heterogeneity analyses demonstrate that the promotional effect is more pronounced in state-owned enterprises, large firms, heavily polluting industries, and non-technology-intensive firms, revealing structural variation across firm characteristics. By isolating low-carbon innovation from the broader green innovation concept and identifying dual transmission channels, this study extends the literature on the economic consequences of ESG and provides evidence for designing differentiated green governance policies. Full article

Sargassum biomass has attracted increasing attention due to its massive accumulation along the Mexican Caribbean coast (Riviera Maya) and its potential role in carbon cycling. Although previous studies have reported calcium carbonate formation associated with Sargassum, the crystallographic nature of these biomineralized phases and the possible incorporation of Mg into the carbonate lattice remain poorly understood. In this study, carbonate phases associated with Sargassum collected from the Mexican Caribbean were investigated using X-ray diffraction (XRD), Rietveld refinement, Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy coupled with energy-dispersive spectroscopy (SEM-EDS), and transmission electron microscopy (TEM). Structural, morphological, and compositional analyses consistently revealed calcite as the dominant carbonate phase, exhibiting lattice modifications associated with Mg incorporation. Rietveld refinement identified crystallographic changes consistent with Mg substitution within the calcite lattice, while complementary characterization confirmed Mg-bearing carbonate domains and local structural distortions characteristic of high-Mg calcite (HMC). The combined results provide strong evidence for the formation of HMC associated with Sargassum, demonstrating that Mg incorporation occurs within the carbonate structures of a non-calcifying brown macroalga, a process previously reported predominantly in calcifying organisms and calcareous algae. These findings expand the current understanding of biomineralization pathways in marine ecosystems and suggest that Sargassum can promote the transformation of dissolved inorganic carbon into carbonate minerals. The occurrence of HMC highlights the potential role of Sargassum as a natural bioremediator and a contributor to transient carbon fixation through carbonate formation, providing new insights into the role of brown macroalgae in carbonate production and carbon cycling. Full article

Landslides are among the most common and destructive geological hazards and pose a significant threat to the long-term stability of infrastructure systems. In particular, long-distance power transmission corridors often traverse mountainous and forested regions, where landslides can endanger tower foundations and transmission line safety. Such landslides predominantly occur in sloped forested areas, where dense vegetation causes severe occlusion that blurs landslide boundaries and creates strong visual similarity with surrounding land covers. Consequently, accurate and efficient landslide identification from remote sensing imagery remains a significant challenge. To address these challenges, we propose a structural constrained contrastive learning network (SC-Net) for reliable landslide extraction from remote sensing images. First, a multi-structural feature extraction module is designed to capture landslide-specific geometric characteristics. These features are further enhanced by fusing multi-scale semantic representations extracted from a pretrained backbone network through an attention-based adaptive feature fusion module. Additionally, a mask-constrained object-level contrastive learning strategy is introduced to enforce global structural consistency at the landslide object-level, thereby improving the discriminability between landslide and non-landslide regions. Extensive experiments conducted on the publicly available CAS landslide dataset demonstrate the effectiveness of the proposed method. The proposed SC-Net achieves IoU scores of 89.89% and 79.76% on the CAS-UAV and CAS-SAT datasets, respectively, outperforming the best-performing baseline by 2.09% and 0.46%. The proposed method provides an effective solution for large-scale landslide monitoring and demonstrates potential for applications in power transmission corridor inspection and infrastructure safety assessment. Full article

When a short-circuit fault occurs along the transmission line of a modular multilevel converter high-voltage direct-current (MMC-HVDC) grid, the sub-module capacitors discharge, causing the fault current to rapidly rise, posing a threat to the safe operation of the system. Therefore, this paper proposes a novel fault location method based on the Gram Angle Difference Field (GADF). The column corresponding to the maximum differential value in a sliding window is used to identify the fault moment and locate faults in MMC-HVDC transmission lines. In order to effectively distinguish normal fluctuations from fault mutations and avoid false alarms, a dynamic threshold is set based on the statistical characteristics of normal data. This method utilizes the unique feature extraction capability of the GADF matrix, the adaptive mechanism of the dynamic threshold, and the stability of line-mode voltage to achieve fast and accurate fault location. Finally, this method is validated using a simulation model. The results show that the proposed method can accurately locate faults in different conditions. Full article

In this study, the seismic vulnerability of the Ferdowsi School building in Tabriz is investigated. The research began with comprehensive fieldwork, during which exploratory surveys and in-depth technical inspections of all structural components were performed. Experimental testing of prismatic masonry specimens was carried out to evaluate their mechanical characteristics, and the resulting properties were then incorporated as input parameters into the numerical model. The seismic vulnerability assessment was then carried out using nonlinear static (pushover) analysis, applying a lateral load pattern proportional to the first vibration mode of the structure. For numerical simulation, the building was modeled in the ABAQUS finite element software using the macro-modeling technique. The results of the nonlinear static analysis indicated that the building does not possess sufficient load-bearing capacity at the target displacement. Damage was primarily concentrated in the form of cracking in the masonry walls as well as in the dome-shaped sections of the roof, requiring the implementation of a seismic retrofitting scheme to enhance the structure’s seismic performance. To rehabilitate the structure, horizontal and vertical reinforced concrete beams were introduced as confining elements for the masonry walls and subsequently applied in the strengthening project. Furthermore, due to the presence of a domed roof at the first-floor level, it was strengthened using FRP composite materials to enhance tensile capacity and ductility. At the second-floor level, where the roof structure is made of timber elements, a steel cable system was employed to improve its strength and diaphragm action. As for the third-floor timber truss roof, the connections were upgraded and reinforced to provide reliable force transmission and to maintain the overall integrity of the structural system. Following the implementation of the retrofitting measures, the structural model was re-analyzed using nonlinear static analysis. The results demonstrated that the proposed strengthening scheme successfully increased the structural capacity up to the target displacement level and satisfied the intended performance requirements. In the final section of the paper, the implementation details of the retrofitting interventions, as well as the practical experiences gained during the implementation process, are presented and discussed. Full article

To address the stringent demands of intelligent connected vehicles for high bandwidth, low latency, and highly reliable communication, this paper systematically summarizes the semantic communication technology of the Internet of Vehicles (IoV) based on information “meaning” transmission, covering basic theory, key technologies, application practice and challenge and trends. First, the paper expounds the knowledge driven and task oriented paradigm characteristics of semantic communication and its efficiency advantages in the IoV. Second, in terms of key technologies, semantic extraction achieves efficient feature compression through multimodal fusion and Generative Artificial Intelligence (GAI); semantic coding employs hierarchical codebooks and adaptive strategies to optimize transmission efficiency; semantic transmission leverages deep reinforcement learning for the joint scheduling of resources such as spectrum and power; and semantic decoding utilizes reconstruction networks and GAI to enhance resilience against impairments. Application practices demonstrate that semantic communication can significantly compress image data transmission volume for autonomous driving collaborative perception while maintaining high-fidelity reconstruction under adverse channel conditions. It significantly reduces the communication load and improves the system utility in vehicle-to-infrastructure coordination and in-vehicle service. Despite facing technical challenges such as semantic consistency, dynamic adaptability, and security trustworthiness, future semantic communication will evolve towards deep integration with distributed collaborative knowledge networks, lightweight real-time decision-making agents, and integrated “communication, sensing, and computing” architectures, positioning itself as a key enabling technology for empowering Sixth Generation mobile communication (6G) of intelligent vehicular networks. Full article

This study investigates the transient mode-locking dynamics and parameter-sensitive pulse evolution in a ytterbium-doped mode-locked fiber laser under near-zero net-dispersion conditions. The influence of gain saturation energy E_s, modulation depth T₀, saturation power P_sat, and non-saturable loss P_ns on transient pulse evolution and mode-locking buildup is comparatively analyzed using the complex Ginzburg–Landau equation. Numerical results indicate that increasing the gain saturation energy E_s weakens the gain saturation effect and prolongs the transient buildup process of stable mode locking, while simultaneously promoting intracavity energy accumulation and spectral broadening through enhanced nonlinear phase evolution. Increasing the modulation depth T₀ accelerates mode-locking initiation through enhanced nonlinear transmission contrast, whereas saturation power P_sat mainly affects the transient intracavity energy accumulation process during pulse evolution. Increasing the non-saturable loss P_ns suppresses low-intensity fluctuations during pulse buildup and contributes to faster gain–loss stabilization inside the laser cavity. Under near-zero net-dispersion conditions, stable picosecond pulse evolution with consistent spectral and temporal characteristics is numerically obtained. The present results provide useful physical insight into gain–loss interaction mechanisms and transient dissipative-soliton dynamics in ultrafast fiber lasers. Full article

Background/Objectives: African Union (AU) guidance identifies decentralized diagnostics as central to epidemic preparedness. However, the epidemiological role of self-testing across epidemic-prone diseases remains underexplored. Drivers for the potential impact of self-testing were examined conceptually using a transmission model. Methods: A deterministic SEIR model compared standard-of-care testing with additional self-testing. Global sensitivity analysis using Latin Hypercube sampling and partial rank correlation coefficients (PRCCs) examined parameters influencing reductions in peak disease prevalence (mitigation). Dynamics were illustrated using AU pathogen archetypes (Ebola, Influenza A, Cholera, Coronavirus, and Mpox), estimating the number needed to self-test (NNST) to avert one death. Results: Epidemic mitigation was minimal (median 1.9%; IQR: 0.4–5.8%); this correlated with isolation adherence (PRCC = 0.784), self-testing intensity (PRCC = 0.617), lower R₀ (basic reproductive number; PRCC = −0.607) and greater duration of infectiousness (PRCC = 0.370). Conditional scenario exploration indicated 34 self-tests per 10,000 people per day to achieve a 10% reduction in peak prevalence at R₀ = 1.1, assuming self-test sensitivity 78.7%, specificity 99.3%. This exceeded the WHO Afro COVID-19 operational benchmark of 10 per 10,000 per week. High-mortality, moderate-transmission archetypes (e.g., Ebola) were most responsive to mortality reductions (median 1512 NNST/death averted) compared to Mpox (median 355,708 NNST/death averted). Adherence to post-test isolation exerted greater epidemiological impact than diagnostic accuracy. Conclusions: The epidemiological value of untargeted self-testing depends on pathogen characteristics and post-test behavioral adherence. Epidemic mitigation effects were limited under constrained health-system capacity. Future studies evaluating early decentralized self-testing deployment during Ebola-archetype outbreaks may identify operationally feasible deployment strategies to support mitigation and mortality reduction. Full article

Reducing emissions is increasingly critical for mitigating the environmental impact of the iron and steel industry. Achieving this transition requires an accurate evaluation of carbon emission intensity for steel production, which relies on an in-depth analysis of carbon metabolism mechanisms across the entire steel production chain. Existing approaches predominantly focus on carbon tracing within material flows, which cannot deeply integrate carbon migration pathways with energy flows and thus fail to reveal the actual sources and transmission mechanisms of carbon emissions. To address this gap, this study develops a carbon metabolism simulation model of the steel manufacturing process that considers the coupling of material production with the energy network. The differentiated carbon metabolism patterns are characterized in terms of carbon fixation, migration, and dissipation to support more accurate carbon emission accounting and enable the formulation of targeted decarbonization strategies. The results show that the coking process fixes 72.51% of its carbon input. The sintering and pelletizing process shows typical carbon dissipation characteristics, with nearly 100% of input carbon discharged. Carbon emissions from steelmaking and the rolling process are mainly induced by indirect energy consumption. The total carbon dissipation of integrated steel production system is 440.62 kg-C/t-CS, with the ironmaking process contributing the largest share of 33.92%. Full article

The global outbreak of monkeypox virus (MPXV) demonstrated qualitatively new epidemiological characteristics of the infection, significantly different from previous outbreaks, mainly limited to the regions of Central and West Africa. The scale and speed of the spread of the virus necessitated a revision of existing ideas about the transmission routes of MPXV and its epidemiological potential. Human-to-human transmission of MPXV has traditionally been considered to be limited and self-extinguishing. However, the data obtained during the 2022 outbreak indicate the formation of stable transmission chains and an increase in the effectiveness of anthroponotic spread. This work is devoted to an analysis of the dynamics of transmission of MPXV with an emphasis on its potential to spread to Kazakhstan from neighboring countries and an evaluation of preparedness, eventually aiming to raise awareness in the scientific community of Central Asia. Full article

This paper presents the development and experimental validation of a Wi-Fi-based distributed system for structural health monitoring of building structures. The proposed system employs a hybrid mesh/ad hoc architecture, enabling autonomous sensor nodes to communicate via IEEE 802.11 without requiring a centralized wired infrastructure. A distributed monitoring architecture, a data transmission algorithm, and a multi-sensor platform integrating distance, magnetometric, and environmental sensors were developed. A mathematical network model was established to analyze the communication characteristics and ensure reliable data exchange in the distributed system. The proposed approach was validated through 500 consecutive experimental measurements and a comparative analysis of wired and wireless data acquisition. The results demonstrated reliable wireless communication without data loss while preserving the temporal characteristics of the measured signals. The distance sensors and the DHT22 temperature sensor achieved the highest agreement with the wired reference based on the MAE and RMSE metrics, whereas the magnetometric sensors and humidity measurements exhibited moderate variability associated with sensor sensitivity and transmission conditions. The obtained results confirm that the proposed Wi-Fi-based distributed architecture provides a stable, scalable, and fault-tolerant solution for structural health monitoring. The developed system can also be adapted for environmental monitoring, energy systems, and other smart infrastructure applications. Full article

“Song-style 宋風 stone lions” is a term commonly seen in scholarly literature on medieval Japanese stone carvings. It refers primarily to the Chinese stone lions imported into Japan from around 1200 to the turn of the 14th and 15th centuries, as well as to stone lion figures carved by Southern Song stonemasons in Japan. Like other Song-style stone carvings such as Satsuma pagodas 薩摩塔, they are important remains of cultural exchange along the Sino-Japanese maritime Silk Road. Through comparative analysis of their morphological features, it is possible to trace the evolutionary lineage of the extant Song-style stone lions in Japan. The imported examples can be divided into two main types, A and B. Type A can be further subdivided into three sequential subtypes (I, II, III). All stone lions of Subtypes I and II of Type A and the earliest ones of Subtype III, together with Type B examples, generally date from around 1200 to the Song-Yuan transitional period, and can therefore be considered “Song-style” stone lions in the strict sense. The lion figures left by Southern Song stonemasons in Japan, which are mainly works of the late 12th to early 13th century, share morphological characteristics with the early imported Song-style stone lions—namely, Subtype I of Type A. The analysis of stone material sources suggests that most of the extant imported Song-style stone lions in Japan might have come from the Jiangsu-Zhejiang 江浙 region, China. In fact, the lineage of Song-style stone lions outlined on the basis of the Japanese examples is equally applicable to the study of contemporaneous stone lions found in the Jiangsu-Zhejiang region. Moreover, it should also be noted that the transmission of Song-style stone lions and their craftsmanship to Japan occurred in the context of the prosperity of the Sino-Japanese maritime Silk Road and the eastward spread of Song-style Buddhist culture. The production, importation, placement and preservation of most Song-style stone lions in medieval Japan are closely tied to Sino-Japanese Buddhist cultural exchanges. Full article

This study investigates the long-run and short-run relationships between capital market development, foreign direct investment, trade openness, and real GDP per capita in Romania over 2003–2024, employing the Autoregressive Distributed Lag (ARDL) bound testing approach, complemented by lag-augmented VAR Granger-causality analysis and a comprehensive set of diagnostic and stability tests. The bounds tests strongly reject the null of no cointegration, confirming a long-run relationship that remains robust under finite-sample critical values. The causality analysis demonstrates a supply-leading mechanism from the equity market to real economic activity, while economic growth in turn Granger-causes both market liquidity and trade openness, pointing to demand-following dynamics for these channels. The analysis shows that foreign direct investment, market liquidity, and trade openness exert positive and significant short-run effects; yet their long-run coefficients are negative, significantly for FDI (foreign direct investments), capturing an asymmetry between immediate output gains and durable structural contribution that is characteristic of emerging European economies. The error-correction term is positive, demonstrating that real GDP (gross domestic product) per capita does not adjust back toward the long-run relationship in the conventional sense, but, instead, it behaves as a forcing variable that leads the financial and trade channels rather than being led by them. All in all, the findings describe an economy with functional short-run transmission channels, but limited long-run structural anchoring, with direct relevance for Sustainable Development Goals 8 and 17 and Romania’s ongoing OECD accession. Full article

Tendon-driven bipedal robots exhibit complex time-varying dynamics due to elastic deformations, multi-joint coupling, and transmission delays. These characteristics lead to significant sim-to-real discrepancies and limit the robot’s performance in complex terrains. To address this issue, we propose a two-stage locomotion control training framework based on Real2Sim2Real (RSR). In the first stage, joint motion data collected from the real robot are used to train a torque refinement policy in simulation, implicitly modeling the time-varying dynamics of the tendon-driven system and reducing the body dynamics gap during sim-to-real transfer. In the second stage, we introduce a reinforcement learning approach that integrates explicit estimation with implicit representation. By explicitly estimating body linear velocity and local terrain information under the feet, and simultaneously learning task-relevant latent features through implicit representation, the robot’s adaptability to complex terrains is enhanced. Experimental results show that, for a forward velocity tracking task of 2.5 m/s, the proposed explicit–implicit learning method achieves a 15.9% reduction in velocity tracking error compared to the purely implicit representation baseline (IWM). When further combined with the torque refinement policy (RSR), the tracking error is further reduced by 86.4% compared to the explicit–implicit baseline (EIWM). Moreover, the proposed method enables stable locomotion across various complex terrains, demonstrating its effectiveness in improving sim-to-real transfer performance and terrain adaptability. Full article

To address the issue of transmission performance degradation caused by misalignment between the transmitting and receiving coils in wireless power transfer (WPT) systems, the optimal design for a bipolar reverse-wound magnetic coupler is proposed in this paper, considering both misalignment tolerance and wire consumption. Firstly, a bipolar reverse-wound magnetic coupler employing two concentric circular coils connected in reverse series is introduced. The calculation method for the mutual inductance between the transmitter and receiver coils of the proposed mechanism is investigated. Secondly, a circuit model for the WPT system based on this magnetic coupler is established. Subsequently, considering the mutual inductance variation characteristics and coil wire consumption, the design method based on particle swarm optimization for the bipolar reverse-wound magnetic coupler is proposed to enhance its misalignment tolerance. Simulation and experimental results demonstrate that, with the proposed optimization method, the receiving coil is permitted to misalign within a range covering 60% of the transmitter radius while maintaining mutual inductance fluctuations below ±5%. Compared to the conventional single circular transmitter, the proposed magnetic coupler achieves an approximately 20% improvement in misalignment tolerance under similar transmitter coil wire consumption conditions. The maximum receiving power of the experimental prototype is 203.67 W, while the DC-DC efficiency is 89.33%. Full article