Zhejiang Institute of Communications

The effectiveness of external reinforcement significantly influences the durability and safety of bridges. During construction, prestress is typically applied and controlled using hydraulic jacks. However, long-term service conditions may lead to sectional deterioration or wire fractures in external tendons, which often remain undetected due to the absence of effective monitoring techniques. Since non-destructive methods should be applied to obtain the condition of external tendons for long-term monitoring, and considering the limitations of anchor tendon gauges and vibration-based methods, this research implemented a novel study for long-term monitoring and analysis of tendons in externally prestressed concrete bridges during operation. First, semi-closed elasto-magnetic sensors were deployed on two existing highway viaducts without removing the tendons; Second, prestress loss in bridges with different external prestressing configurations were analyzed using finite element method. Third, data collected over a 12-month period following bridge opening were analyzed under actual traffic loads and with consideration of temperature effects. The results indicate that the prestress values measured by the elasto-magnetic sensors correspond closely with theoretical predictions, demonstrating the suitability of this monitoring approach for practical bridge applications. Furthermore, no significant prestress loss was observed during the monitoring period. • Elasto-magnetic sensors are applied on the steel strand of externally prestressed concrete bridges. • A type of semi-closed elasto-magnetic sensor can be installed in two parts after tensioning and wired together, which significantly reduced the amount of time for sensor production. • Monitoring the long-term changes of the prestress while the bridge is still open to traffic. In-time response can be captured. • Measured results with sensors theoretical results from FEM perform great consistency. • The prestress force in steel strands is analyzed with different temperature and traffic loads during the monitoring period of the bridge.

Aiming at the problems of insufficient target detection accuracy, poor multi-target tracking stability, and rigid traffic signal control in complex environments of urban traffic scenarios, this paper proposes an intelligent traffic management system that integrates improved YOLO series algorithms and multi-modal perception technology. With the DB-YOLOv12 model as the core detector, the system combines the improved DeepSORT tracking algorithm to achieve high-precision recognition and continuous tracking of targets such as vehicles and pedestrians. It also integrates a multi-modal weather recognition module and a dynamic traffic signal control strategy to construct a closed-loop management mechanism of "perception-analysis-decision". Experimental results show that the system achieves a vehicle recognition accuracy of 94.7% in complex environments, a pedestrian detection recall rate of 82.1%, and a foggy weather recognition accuracy of 87.5%, which can improve the traffic efficiency of intersection during peak hours by more than 30%. The research results provide important technical support for the engineering application of intelligent transportation systems.

China's increasingly aging population and relaxed fertility policies have intensified the burden on rural farmers who must support both minors and older adults. This household dependency burden (HDB) constrains farmers' agricultural investments and limits improvements in grain production efficiency. This study examines the impact of the HDB on rice total factor productivity (TFP) growth and its underlying mechanisms. Using farmers' microdata from fixed observation points across rural China, the analysis applies stochastic frontier analysis and a fixed-effects model with robust standard errors. Results show that the HDB reduces farmers' productive investment and land-use expansion, thereby hindering both technical efficiency and technical progress in rice production. Consequently, rice TFP growth is restricted, although this effect can be mitigated through socialized agricultural services. The study offers policy recommendations, including advancing urban–rural integration, easing urban–rural migration restrictions, strengthening rural childcare and eldercare systems, improving agricultural service provision, and fostering innovative production models.

<div class="section abstract"> <div class="htmlview paragraph">Focusing on the deformation warning criteria for a new four-lane tunnel affected by an existing tunnel, this study employs numerical simulation to analyze the ultimate strain of the equivalent rock mass. The results reveal the ultimate shear strain and ultimate tensile strain of Class V surrounding rock, offering critical insights for deformation control and early warning systems. Relying on the Maaoling Tunnel Project, the tunnel planar analysis model is established based on the finite difference FLAC3D software to analyze the deformation and strain distribution pattern of the surrounding rock of the new tunnel under different distances and reduction factors between the new and the existing tunnel. Finally, the tunnel crown settlement as an indicator, the establishment of the Maaoling Tunnel V surrounding rock conditions of different distances construction safety warning standard for the construction of large-span tunnels and early warning provides the basis for the relevant engineering practice has an important reference value.</div> </div>

Interactive installation art provides a distinctive context for examining collective emotion, yet most prior studies have relied on laboratory or longitudinal data that are impractical in public cultural settings. This study applied Hidden Markov Models (HMMs) to self-reported well-being data from HappyHere, a participatory light installation at the National Galleries of Scotland. Despite the cross-sectional design, the HMM framework enabled inference of latent affective states and probabilistic differentiation patterns, stability, and convergence patterns. The results show four key findings. First, three qualitatively distinct latent states were identified: a low/negative cluster (M ≈ 1.5), a moderately positive cluster (M ≈ 3.5), and a ceiling-level, highly positive cluster (all M = 5.0), confirming clear differentiation (H1). Second, positive states proved the most stable, with the highest self-transition probability (0.875) and the longest dwell time (≈ 3.4 steps), supporting H2. Third, neutral states were comparatively unstable, showing the lowest self-transition probability (0.093) and a tendency to shift toward positivity, consistent with H3. Finally, the stationary distribution strongly favored positivity, with positive states Reaching 86.3%, neutral states 7.5%, and negative states 6.2%. Minor diurnal variation was observed, but effect sizes were negligible, confirming the enduring predominance of positivity (H4). The findings demonstrate that even cross-sectional cultural datasets can yield meaningful insights through probabilistic modelling. Positive affect emerged as the most stable and dominant attractor, underscoring the capacity of participatory art to regulate emotion and foster collective well-being.