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SSRN 2025年

作者： Li, Ziqian Liu, Hong Xiao, Yunmu Min, Ke Pan, Yuliang Li, Yong Yan, Wende National Engineering Laboratory of Applied Technology for Forestry & Ecology in South China the Laboratory of Urban Forest Ecology of Hunan Province Department of Life and Environmental Science Central South University of Forestry and Technology Hunan Province Changsha410004 China State Key Laboratory of Environmental Chemistry and Ecotoxicology Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing100085 China Hunan Normal University China

This study systematically investigates the phytotoxic mechanisms of lead-based perovskite solar cells (Pb-PSCs), an emerging energy nanomaterial, using the deep-rooted leguminous crop Arachis hypogaea L. (peanut) as a model system. Multi-scale analyses integrating physiological, spatial elemental imaging, and omics approaches revealed that Pb-PSC exposure induced significant morphological impairments, including root morphogenesis inhibition and stem elongation reduction. Spatial imaging techniques revealed the Pb uptake and transport through apoplast pathway and active transport pathway in root tissue. The internalized Pb element accumulated as salt precipitation around the root epidermis and cortex nearby endodermis, resulting in compression distortion of cell structures. Meanwhile, Pb PSC exposure induced an inhibition of Ca and Cu upward transport, causing nutrient deficiency in plants. Omics analysis indicated the enhancement of Salicylic Acid (SA) signaling pathways in defense response, and the metabolic hyperactivity led to poor root growth and development. This work pioneers the elucidation of absorption dynamics, spatial distribution patterns, and molecular toxicity cascades of Pb-PSCs in plants, providing critical insights for ecological risk mitigation and sustainable nanomaterial design. © 2025, The Authors. All rights reserved.

关键词： Brain

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The concentration-dependent physiological damage, oxidative stress, and DNA lesions in Caenorhabditis elegans by subacute exposure to landfill leachate

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Chemosphere 2023年第1期339卷 139544页

作者： Zhu, Manman Zhang, Meng Tang, Mingqi Wang, Jun Liu, Lili Wang, Zhiping State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process School of Resource and Environmental Engineering East China University of Science and Technology Shanghai200237 China Institute of Applied Ecology Chinese Academy of Sciences Shenyang110016 China School of Environment Science and Technology Shanghai Jiao Tong University Shanghai200240 China

The leakage of landfill leachate (LL) into environmental media would be happened even in the sanitary/controlled landfill, due to the deterioration of geomembrane and the blockage of drainage system after long-term operation. Considering the complex composition and high concentration of pollutants in LL, its toxicity assessment should be conducted as a whole liquid contaminant. Therefore, the impacts of LL on Caenorhabditis elegans (C. elegans) were investigated under the condition of different exposure time and exposure volume fraction (EVF). The stimulating effects on locomotion behavior and growth of C. elegans were observed after acute (24 h) exposure to LL, which were increased firstly and then decreased with the increase of EVF. Meanwhile, the intestinal barrier was not affected by LL, and levels of reactive oxygen species (ROS) and cell apoptosis significantly decreased. However, stimulation and inhibition effects on locomotion behavior and growth of C. elegans were observed when subacute (72 h) exposure to 0.25%–0.5% and 1%–4% of LL, respectively. The intestinal injury index and levels of ROS and cell apoptosis significantly increased when EVF were 2% and 4%. Although the acute exposure of LL had resulted in obviously biological adaptability and antioxidant defense in C. elegans, the protective mechanisms failed to be induced as the exposure time increased (subacute exposure). The toxic effects were confirmed by the down-regulation of genes associated with antioxidant defense and neurobehavior, accompanied by the up-regulation of intestinal injury and cell apoptosis related genes. Moreover, the disturbance of metabolic pathways that associated with locomotion behaviors, growth, and antioxidant defense provided good supplementary evidence for the confirmation of oxidative stress in C. elegans. The research results verified the potential of C. elegans as model organism to determine the complex toxic effects of LL. © 2023 Elsevier Ltd

关键词： Deterioration

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Harmonic response analysis for ball grid array package using computer finite element simulation 3

Harmonic response analysis for ball grid array package using...

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3rd International Conference on Electrical, Communication and Computer engineering, ICECCE 2021

作者： Su, Wei Luo, Wenhao Dong, Xianshan Chen, Si Tomar, Agam Science and Technology on Reliability Physics and Application Technology of Electronic Component Laboratory China Electronic Product Reliability and Environmental Testing Research Institute Guangzhou China MOE Key Lab of Disaster Forecast and Control in Engineering Guangzhou China School of Mechanics and Construction Engineering Jinan University Guangzhou China Faculty of Engineering and Mathematical Sciences University of Western Australia Australia

BGA package is selected as the research object in this paper. Workbench (finite elemental analysis tool in ANSYS) is used for harmonic response analysis. The author lays several paper sheets on the sample and builds the finite element model of clamp, ceramic and metal plate. Then, the model analysis is carried out. Based on this, it is converted to harmonic response analysis. According to the results, the author has found that there is no relation between the number of paper sheets and acceleration-frequency result. It promotes the development of electronic packaging reliability. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Finite element method

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Health-oriented strategies are needed to optimize China’s 2025 clean air action plan

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science Bulletin 2024年第13期69卷 2007-2008页

作者： Tao Xue Ning Kang Wei Wan Tong Zhu Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics/Ministry of Education Key Laboratory of Epidemiology of Major Diseases(PKU) School of Public HealthPeking University Health Science CentreBeijing 100191China State Environmental Protection Key Laboratory of Atmospheric Exposure and Health Risk Management Center for Environment and HealthPeking UniversityBeijing 100871China Advanced Institute of Information Technology Peking UniversityHangzhou 311215China Clean Air Asia Beijing 100600China College of Environmental Sciences and Engineering Peking UniversityBeijing 100871China

Recently,China’s state Council issued the Continuous Improvement of Air Quality Action Plan(hereafter,the third action plan),which follows the Air Pollution Prevention and Control Action Plan(2013–2017)(hereafter,the first action plan)and the Three-Year Action Plan for Winning the Blue Sky defense Battle(2018–2020)(hereafter the second action plan).The first two action plans yielded nationwide health benefits[1–3],from improving lung function[4]to saving medical expenditures[5].Based on our previous estimates[6],due to reductions in the fine particulate matter(PM2.5)level,implementation of the first and second action plans was expected to increase life expectancy by 2.11 and 3.68 months.

关键词： action hereafter nationwide

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Integration method of multi-source accelerated degradation testing data considering epistemic uncertainties and stress dependency 29

Integration method of multi-source accelerated degradation t...

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29th European Safety and reliability Conference, ESREL 2019

作者： Chen, Wen-Bin Li, Xiao-Yang Kang, Rui Hu, Yu-Qing Science and Technology on Reliability and Environmental Engineering Laboratory School of Reliability and Systems Engineering Beihang University Beijing100191 China Aerospace Science and Industry Corp Defense Technology R&T Center Beijing100854 China

ISBN: (纸本)9789811127243

Accelerated degradation testing (ADT) is commonly used to evaluate product reliability. Due to the fact that the test resources in conducting ADTs are usually limited, the collected degradation data are scarce, which brings epistemic uncertainties in reliability evaluation. Herein, the multi-source ADT data are usually integrated to decrease such uncertainties and achieve high accurate reliability assessments. However, the stress type sets of multiple ADTs are usually dependent, which makes it more difficult for the integration and is seldom taken into consideration in the state of art methods. In this paper, a novel integration method of multi-source ADT data are proposed to address such issues based on uncertainty theory and mutually exclusive set (MES) theory. First, the weight assignments for ADT datasets are given based on the union of the MESs of the accelerated stress types. Then, the uncertainty theory is introduced to model the degradation process of product, and the integration model of multi-source ADT datasets with assigned weights is proposed. A simulation study of the integration of two ADT datasets with different accelerated stress type sets is applied to verify the effectiveness of the proposed method. © 2019 European Safety and reliability Association. Published by Research Publishing, Singapore.

关键词： Integration testing

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Real-time Accident Anticipation for Autonomous Driving Through Monocular Depth-Enhanced 3D Modeling

arXiv

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arXiv 2024年

作者： Liao, Haicheng Li, Yongkang Wang, Chengyue Lai, Songning Li, Zhenning Bian, Zilin Lee, Jaeyoung Cui, Zhiyong Zhang, Guohui Xu, Chengzhong State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science University of Macau China Department of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China State Key Laboratory of Internet of Things for Smart City University of Macau China State Key Laboratory of Internet of Things for Smart City Departments of Civil and Environmental Engineering and Computer and Information Science University of Macau China Guangzhou China Transportation Planning and Engineering The Department of Civil and Urban Engineering New York University New York United States School of Traffic and Transportation Engineering Central South University Changsha China School of Transportation Science and Engineering Beihang University Beijing China Department of Civil and Environmental Engineering University of Hawaii HonoluluHI United States

The primary goal of traffic accident anticipation is to foresee potential accidents in real time using dashcam videos, a task that is pivotal for enhancing the safety and reliability of autonomous driving technologies. In this study, we introduce an innovative framework, AccNet, which significantly advances the prediction capabilities beyond the current state-of-the-art 2D-based methods by incorporating monocular depth cues for sophisticated 3D scene modeling. Addressing the prevalent challenge of skewed data distribution in traffic accident datasets, we propose the Binary Adaptive Loss for Early Anticipation (BA-LEA). This novel loss function, together with a multi-task learning strategy, shifts the focus of the predictive model towards the critical moments preceding an accident. We rigorously evaluate the performance of our framework on three benchmark datasets—Dashcam Accident Dataset (DAD), Car Crash Dataset (CCD), and AnAn Accident Detection (A3D), and DADA-2000 Dataset—demonstrating its superior predictive accuracy through key metrics such as Average Precision (AP) and mean Time-To-Accident (mTTA). Copyright © 2024, The Authors. All rights reserved.

关键词： Multi-task learning

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Pyrolyzed Iron–Nitrogen–Carbon Hybrids Enable Efficient Periodate Activation Toward Contaminant Decomposition: Active Site, Degradation Mechanism, and Influential Factors

SSRN

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SSRN 2023年

作者： Long, Yangke Huang, Shixin Zhao, Shiyin Xiao, Guicong Sun, Jianlin Peng, Dan Department of Transportation and Environment Shenzhen Institute of Information Technology Shenzhen518172 China Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control School of Environmental Science and Engineering Southern University of Science and Technology Shenzhen518055 China College of Science National University of Defense Technology Changsha410073 China

To incorporate periodate-based advanced oxidation technologies (PI-AOTs) into practical wastewater treatment, there is a need for efficient and affordable activators. Pyrolyzed Fe–N/C materials are candidates for this purpose, but their actual active sites and associated activation mechanisms remain unclear. Herein, a series of Fe–N/C samples (denoted as Fe@NC-X) with differing structures and iron components was delicately synthesized. Experimental studies of the structure–activity relationship and density functional theory (DFT) computations revealed that Fe–Nx species dominated as the active site responsible for periodate activation, while the inactive iron-based particles (i.e., Fe0 and Fe3C) optimized the binding affinity of their surrounding carbon layers toward periodate to confer enhanced activity. In-depth exploration of the oxidative mechanism revealed that Fe@NC-X activated periodate through an electron transfer regime. We also showed that the optimal Fe@NC-0.2/periodate system exhibited superior activity for 4-CP oxidation with a high apparent rate constant of 0.38 min-1, which exceeded that of many reported activators. Moreover, Fe@NC-0.2/periodate is effective for eliminating miscellaneous organic pollutants and is strongly resistant to environmental interference. These findings provide an indispensable foundation for the rational development of advanced Fe–N/C activators and offer vital insights into the underlying mechanism underlying pollutant destruction through PI-AOTs. © 2023, The Authors. All rights reserved.

关键词： Wastewater treatment

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Fault Assessment of Hydraulic System Based on Gaussian Mixture Model

Fault Assessment of Hydraulic System Based on Gaussian Mixtu...

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2020 Global reliability and Prognostics and Health Management, PHM-Shanghai 2020

作者： Wang, Zhaobing Tang, Jian Jiang, Xin Wang, Yi Ma, Jian Chen, Yu COMAC Beijing Aircraft Technology Research Institute Beijing China School of Reliability and Systems Engineering National Key Laboratory of Science and Technology on Reliability and Environmental Engineering Beihang University Beijing China

ISBN: (纸本)9781728159454

Based on the civil aircraft hydraulic system, the typical slow-change fault injection is carried out in hydraulic system MWorks model, and the fault state assessment technology based on Gaussian mixture model is studied. The results show that the health curve of the Gaussian mixture model can truly reflect the system pressure abnormal deviation process, and the health confidence value obtained by the inverse tangent function normalization is more sensitive to the early failure process of the fault, which can better support the predictive maintenance. © 2020 IEEE.

关键词： Gaussian distribution

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VCAT: Vulnerability-aware and Curiosity-driven Adversarial Training for Enhancing Autonomous Vehicle Robustness

arXiv

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arXiv 2024年

作者： Cai, Xuan Cui, Zhiyong Bai, Xuesong Ke, Ruimin Ma, Zhenshu Yu, Haiyang Ren, Yilong State Key Laboratory of Intelligent Transportation Systems School of Transportation Science and Technology Beihang University Beijing100191 China Department of Civil and Environmental Engineering Rensselaer Polytechnic Institute TroyNY12180 United States Zhongguancun Laboratory Beijing100191 China

Autonomous vehicles (AVs) face significant threats to their safe operation in complex traffic environments. Adversarial training has emerged as an effective method of enabling AVs to preemptively fortify their robustness against malicious attacks. Train an attacker using an adversarial policy, allowing the AV to learn robust driving through interaction with this attacker. However, adversarial policies in existing methodologies often get stuck in a loop of overexploiting established vulnerabilities, resulting in poor improvement for AVs. To overcome the limitations, we introduce a pioneering framework termed Vulnerability-aware and Curiosity-driven Adversarial Training (VCAT). Specifically, during the traffic vehicle attacker training phase, a surrogate network is employed to fit the value function of the AV victim, providing dense information about the victim’s inherent vulnerabilities. Subsequently, random network distillation is used to characterize the novelty of the environment, constructing an intrinsic reward to guide the attacker in exploring unexplored territories. In the victim defense training phase, the AV is trained in critical scenarios in which the pretrained attacker is positioned around the victim to generate attack behaviors. Experimental results revealed that the training methodology provided by VCAT significantly improved the robust control capabilities of learning-based AVs, outperforming both conventional training modalities and alternative reinforcement learning counterparts, with a marked reduction in crash rates. The code is available at https://***/caixxuan/VCAT. © 2024, CC BY.

关键词： Adversarial machine learning

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An object tracking method to track maintenance objects by object detection based on deep learning in induced maintenance environment 30th

An object tracking method to track maintenance objects by ob...

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30th European Safety and reliability Conference, ESREL 2020 and 15th Probabilistic Safety Assessment and Management Conference, PSAM15 2020

作者： Liang, Chuansheng Lv, Chuan State Key Laboratory of Virtual Reality Technology and Systems 37 Xueyuan Road Beijing China School of Reliability and Systems Engineering Beihang University 37 Xueyuan Road Beijing China State Key Science and Technology Laboratory on Reliability and Environmental Engineering 37 Xueyuan Road Beijing China

ISBN: (纸本)9789811485930

Induced maintenance means that the surrounding scene and the maintenance object state change are perceived through natural interaction means, and the digital maintenance instruction information is superimposed on the physical object and the process in real time so that the person can obtain the operation guidance. However, in the augmented reality environment, there are few researches on application object detection technology in the field of induced maintenance. Therefore, this paper proposes a process for object detection and localization of induced maintenance based on the yolov3(you only look once)-slim model. For the problem that the deep convolutional neural network is deployed on the mobile side and the cost is too high, a pruning method for the batch normalization layer is adopted(Zoph et al. 2019). After the object is recognized, it can only obtain the two-dimensional coordinate information in the image. The coordinates obtained in the two-dimensional pixel coordinate system are then converted into three-dimensional coordinates in the camera coordinate system through the method of solving the PNP(Perspective N Points) problem(Moreno-Noguer, Lepetit, and Fua 2007). The experimental results show that the recognition rate of the repair parts based on the deep neural network can reach 90% of the mean average precision. The average recognition speed is less than 300 millisecond per frame, meeting the accuracy and interactivity requirements of the AR-induced maintenance system. © ESREL2020-PSAM15 *** by Research Publishing, Singapore.

关键词： Object detection

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