Zhejiang Institute of Science and Technology Information

Little is known about whether childhood exposure to parental mental health problems, a significant stressor in early life, influences an individual’s memory trajectories in mid- and later life. Drawing on data from four waves (2011–2018) of the China Health and Retirement Longitudinal Study (CHARLS) and its supplement, the 2014 Life History Survey, we used the latent growth curve modeling technique to investigate whether exposure to parental depression in childhood is associated with memory trajectories of Chinese older adults. Our analytic sample included 7,097 respondents aged 50 and above who were raised by both parents. Results show that individuals who recalled having both parents depressed during their childhood had lower memory scores at baseline compared to their non-exposed counterparts, even after controlling for childhood socioeconomic status and health. These differences remained stable over the 7-year follow-up. Educational attainment and adult health—particularly depressive symptoms—explained the lower episodic memory scores observed in individuals who experienced both parents’ depression during childhood. Surprisingly, individuals who reported having only one parent (either mother or father) depressed during their childhood did not show significantly different memory trajectories compared to their non-exposed counterparts. The findings underscore the long arm of parental mental health on cognitive function in later life and highlight the importance of preventing and treating parental depression through a child’s formative years.

Abstract Hazardous chemical storage tanks are vital to production and societal safety as critical energy storage equipment in petrochemical plants. This paper addresses the technical challenges of inspecting these tanks in service and describes breakthroughs in key technologies for detecting delamination in multilayer structures using low-frequency ultrasonic phased array testing. It also describes the development of phased array ultrasonic probes and scanning devices that are specifically designed for use with these tanks. Three distinct scenarios were first defined based on the relationship between plate thickness and the probe’s near-field zone. Iterative fitting was then used to examine the relationship between plate thickness and the amplitude of interfacial and bottom waves in each scenario. Next, the ratio of interfacial wave amplitude to bottom wave amplitude after mapping was adopted as an evaluation metric for bonding quality. Finally, tank test specimens were inspected using a magnetic-adhesion crawler-type rapid ultrasonic inspection device developed in-house. The results demonstrate that the proposed method effectively detects debonding defects and that the self-developed scanning device significantly enhances inspection efficiency.

Torque sensors are critical perception components in robot joints, providing essential feedback for precise motion control and operational safety. To ensure their reliability, a comprehensive metrological evaluation, including uncertainty assessment, is imperative. This paper establishes a measurement and analysis methodology based on the deadweight torque standard machine, following the national verification regulation JJG 995-2005. The indication error of a torque sensor is measured, and the primary sources of measurement uncertainty—including repeatability, the standard machine's inherent uncertainty, and the sensor indicator's resolution—are quantitatively analyzed. The combined standard uncertainty and expanded uncertainty (with a coverage factor k=2) are calculated. For a 10 Newton-meter (Nm) measurement point, the relative expanded uncertainty is determined to be 0.08%. The results confirm the sensor's compliance with specifications and provide a validated framework for the uncertainty assessment of torque sensors in robotic applications, thereby supporting the pursuit of higher-precision robot control. This study not only demonstrates the practical application of uncertainty evaluation in torque sensors for robotics but also offers a methodological reference for manufacturers and researchers to enhance the accuracy and reliability of torque sensing systems in advanced robotic applications. The findings contribute to the development of more precise and safer robotic systems, particularly in fields such as medical robotics and high-precision assembly.

Within the areas of bridge engineering, scour is an important factor contributing to structural vulnerability. To mitigate the local scour of the sea-crossing bridge foundation, systematic experimental and numerical investigations into the scour protection effect of pile groups were conducted. In this paper, through numerical simulation of 11 pile groups for scour protection, the effects of the geometry of the riprap layer under the action of wave–current coupling were explored. Based on the above laws, two protection methods were proposed: multi-layer riprap and sacrificial pile + riprap. The effectiveness of five different protection methods under an actual engineering background was studied through seven sets of physical tests. The results show that, in numerical simulations, the square riprap provides better scour protection than the elliptical riprap; the 2-m-thick square riprap can effectively reduce the maximum scour depth by 89%. In physical scale tests, the unprotected experimental results are consistent with the numerical simulations and standard formulas; riprap protection can reduce the scour equilibrium time, and the square riprap provides better scour protection; finally, the 2-m-thick multi-layer riprap not only minimizes the maximum scour depth within the pile group, but also maintains the stability of the protective structure. The research results can provide a reference for practical projects considering scour protection under wave–current coupling.

Performance and durability of proton-conducting solid oxide cells (P–SOCs) are primarily governed by the properties of their air electrodes. While PrBaCo 2 O 6-δ (PBC) has emerged as a widely utilized P–SOC air electrode, owing to its superior electrochemical characteristics, its application is hindered by issues related to poor durability and inadequate thermal compatibility. To overcome these limitations, this study explores a Fe/Nb co-doping strategy. This approach significantly elevates the oxygen vacancy concentration, oxygen ion conductivity, and oxygen surface exchange coefficient, while concurrently reducing the thermal expansion coefficient. These changes collectively result in notable improvements in both performance and durability. Cells with PrBaCoFe 0.9 Nb 0.1 O 6-δ (PBCFN) air electrode achieve a peak power density of 1.23 W cm −2 and a current density of 1.74 A cm −2 (1.3 V) at 650 °C. Additionally, the voltage decay rate for this cell is reduced to just 0.25 %/100 h, further underscoring the remarkable durability of PBCFN. In conclusion, we have successfully developed an air electrode that offers both exceptional electrocatalytic performance and durability. This Fe/Nb co-doping strategy not only addresses the stability challenges of traditional PBC air electrodes but also provides valuable insights into the design of advanced air electrodes for next-generation P–SOCs. • DRM catalytic activities of BZYNi x with different Ni doping content was explored. • A Ba 0.9 (Zr 0.8 Y 0.2 ) 0.8 Ni 0.2 O 6-δ reforming layer was added outside the anode support. • Enhanced performance and durability of RSC were observed when fueled with CH 4 –CO 2 .

With the rapid development of mobile edge computing (MEC) and unmanned aerial vehicle (UAV) communication networks, UAV-assisted edge computing has emerged as a promising paradigm for low-latency and energy-efficient computation. However, the time-varying nature of air-to-ground channels and the coupling between UAV trajectories and computation offloading decisions significantly increase system complexity. To address these challenges, this paper proposes an Adaptive UAV Edge Intelligence Framework (AUEIF) for joint UAV computation offloading and trajectory optimization under dynamic channels. Specifically, a dynamic graph-based system model is constructed to characterize the spatio-temporal correlation between UAV motion and channel variations. A hierarchical reinforcement learning-based optimization framework is developed, in which a high-level actor–critic module is responsible for generating coarse-grained UAV flight trajectories, while a low-level deep Q-network performs fine-grained optimization of task offloading ratios and computational resource allocation in real time. In addition, an adaptive channel prediction module leveraging long short-term memory (LSTM) networks is integrated to model temporal channel state transitions and to assist policy learning and updates. Extensive simulation results demonstrate that the proposed AUEIF achieves significant improvements in end-to-end latency, energy efficiency, and overall system stability compared with conventional deep reinforcement learning approaches and heuristic-based schemes while exhibiting strong robustness against dynamic and fluctuating wireless channel conditions.

Robust, national-scale quantification of soil organic carbon (SOC) dynamics in China’s paddy fields has been hindered by widely divergent estimates and a lack of comprehensive driver attribution. To address this, we developed a new empirical model from a comprehensive database of 746 long-term field observations (125 sites) to identify predominant drivers and quantify national-scale SOC stock dynamics from 1980 to 2018. The model explained 43% of the variance in topsoil SOC change. Organic matter input was the dominant driver (21.83% variance), with livestock manure demonstrating the highest C sequestration efficiency, followed by green manure and straw. Soil pH, latitude (as a climate proxy), and initial SOC content were also critical controllers. We estimate that China’s paddy topsoils (0–20 cm) acted as a significant C sink from 1980 to 2018, accumulating 242.51 ± 85.80 Tg C (an average rate of 6.65 Tg C yr−1), bringing the 2018 national stock to 1220.48 ± 85.80 Tg C. Spatially, sequestration was highest in central (e.g., Hunan) and northeastern (e.g., Heilongjiang) China, while Chongqing experienced a net SOC loss. Crucially, our study provides a new long-term benchmark that reconciles previous, higher estimates from shorter timeframes, empirically demonstrating that sequestration rates are non-linear and diminish over time. These findings confirm that the C sequestration potential of paddy soils, while substantial, is finite and requires spatially targeted management of organic inputs and soil pH to maintain.