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5th International Conference on Geoscience and Remote Sensing Mapping, ICGRSM 2023

作者： Hou, Shengshan Chen, Liang Feng, Zhen Liu, Mingxue Li, Ang Wang, Lichao Cao, Peng Liu, Junyou Beijing100081 China Observation and Research Station of Geological Hazard in Sichuan Yaan Ministry of Natural Resources Sichuan Ya'an625099 China Technology Innovation Center for Geohazard Monitoring and Risk Early Warning Ministry of Natural Resources Beijing100081 China Tianjin Geological Engineering Survey and Design Institute Co. Ltd Tianjin300191 China North China Engineering Investigation Institute Co. Ltd. Hebei Shijiazhuang050021 China

ISBN: (纸本)9781510672789

Geohazard is a serious problem in Minxian County of Gansu Province, northwest China. A mid-sized landslide was selected for universal monitoring construction. Crack-meter, GNSS monitoring, soil moisture monitoring, real-time rain-gauge and alarm apparatus were used in the landslide monitoring network. Power supply of landslide monitoring instruments is from Li-ion battery and solar panels, providing sufficient power for 24h-per-day working. Data transmission of real-time data is based on near field communication and 2/3/4G mobile communication, with increasing reliability and cost reduction. monitoring data were transmitted to national platform and provincial platform simultaneously, providing real-time data for both platforms. The monitoring data were analyzed automatically, using multi-module for landslide prediction and warning. When abnormal data were discriminated, SMS messages were delivered automatically to designated personnels for further processing. Based on the monitoring network and intelligent data platform, the landslide was under the inspection of instruments. On Sept. 16, 2021, the active trend was identified before the main sliding. Yellow, orange, and red alerts were sent to the professional staff, government officers and residents in the threat zone. People under risk were evacuated before sliding. Through the implementation of landslide universal monitoring projects, on the one hand, real-time monitoring of landslide deformation and environmental factors is realized, and a reference solution is provided for regions with similar problems. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Lithium-ion batteries

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A novel fast response and high precision water temperature sensor based on Fiber Bragg Grating

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Optik 2023年第1期289卷

作者： Liu, Feng Wei, Shaopeng Li, Bin Tan, Yuxin Guo, Xuan Fu, Xinghu College of Information Science and Engineering Yanshan University Qinhuangdao066004 China Hebei Provincial Key Laboratory of Specialty Optical Fiber and Optical Fiber Sensing Qinhuangdao066004 China Intelligent Sensing Technology and Equipment for Offshore seawater Quality Monitoring Engineering Research Center of Hebei Province Qinhuangdao066004 China

A novel fast response and high precision water temperature sensor scheme based on gallium alloy sensitivity enhanced Fiber Bragg Grating(FBG) is proposed and experimentally demonstrated. In order to achieve faster temperature response speed of the sensor, a fiber Bragg grating is encapsulated in a single-end sealed metal tube which is filled with liquid gallium alloy. The very high thermal conductivity of the liquid gallium alloy that is filled in the metal tube gives rise to an experimental sensitivity of 30 pm/℃. Thanks to accurate and optimal design of metal tube structure parameters, the sensor exhibits an excellent response speed of 43 ms/℃ in water. Very good linearity between center wavelength of FBG and temperature is also achieved in the experiment. The research result of this paper is especially useful for applications where rapid temperature response and high precision are required at the same time, such as ocean CTD(Conductivity Temperature Depth) measuring equipment, ocean hydrology and underwater submersible. © 2023 Elsevier GmbH

关键词： Fiber Bragg gratings

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Selenium and Bacillus proteolyticus SES increased Cu-Cd-Cr uptake by ryegrass: highlighting the significance of key taxa and soil enzyme activity

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Environmental Science and Pollution research 2024年第20期31卷 29113-29131页

作者： Zhang, Huan Nie, Min Du, Xiaoping Chen, Suhua Liu, Hanliang Wu, Chihhung Tang, Yanni Lei, Zheng Shi, Guangyu Zhao, Xiaohu College of Resources and Environment Huazhong Agricultural University / Research Center of Trace Elements Wuhan430070 China Key Laboratory of Se-Enriched Products Development and Quality Control Ministry of Agriculture and Rural Affairs/ National-Local Joint Engineering Laboratory of Se-Enriched Food Development Ankang725000 China Nanchang330063 China Key Laboratory of Geochemical Exploration Institute of Geophysical and Geochemical Exploration CAGS Hebei Langfang065000 China Fujian Provincial Key Laboratory of Resources and Environment Monitoring & amp Sustainable Management and Utilization Sanming University Sanming365004 China School of Environmental Science and Engineering Suzhou University of Science and Technology Suzhou215009 China

Many studies have focused their attention on strategies to improve soil phytoremediation efficiency. In this study, a pot experiment was carried out to investigate whether Se and Bacillus proteolyticus SES promote Cu-Cd-Cr uptake by ryegrass. To explore the effect mechanism of Se and Bacillus proteolyticus SES, rhizosphere soil physiochemical properties and rhizosphere soil bacterial properties were determined further. The findings showed that Se and Bacillus proteolyticus SES reduced 23.04% Cu, 36.85% Cd, and 9.85% Cr from the rhizosphere soil of ryegrass. Further analysis revealed that soil pH, organic matter, soil enzyme activities, and soil microbial properties were changed with Se and Bacillus proteolyticus SES application. Notably, rhizosphere key taxa (Bacteroidetes, Actinobacteria, Firmicutes, Patescibacteria, Verrucomicrobia, Chloroflexi, etc.) were significantly enriched in rhizosphere soil of ryegrass, and those taxa abundance were positively correlated with soil heavy metal contents (P © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Soils

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Exhaust and Evaporative Volatile Organic Compounds Emissions from Vehicles Fueled with Ethanol-Blended-Gasoline

SSRN

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SSRN 2024年

作者： Li, Ruikang Zhong, Chongzhi Xu, Ruiguang Liu, Yan Song, Pengfei Zhang, Taiyu Ning, Yang Mao, Hongjun Tianjin Key Laboratory of Urban Transport Emission Research College of Environmental Science and Engineering Nankai University Tianjin300071 China China Automotive Technology & Research Center Co. Ltd Tianjin300071 China Tianjin Eco-Environmental Monitoring Center Tianjin300192 China Hebei University of Engineering Handan056009 China

By 2020, China has implemented the use of 10% ethanol-blended-gasoline (E10), which is expected to notably impact vehicular volatile organic compounds (VOCs) emissions. The adoption of E10 reduced certain emissions but raised concerns with about more reactive oxygenated volatile organic compounds (OVOCs). This study aimed to evaluate the impact of E10 on the total VOCs emissions from both exhaust and evaporative emissions by conducting tests on CHINA V and VI light-duty gasoline vehicles (LDGVs) using 0% ethanol blended gasoline (E0) and E10. E10 reduces VOCs emissions in the exhaust, as evidenced by the lower emission factors (EFs) in CHINA V and VI vehicles. Evaporative emissions showed differences in emitted VOCs, with lower EFs for CHINA V vehicles fueled with E10. The CHINA VI vehicles also exhibited reduced EFs. These findings highlight the environmental benefits of E10 in CHINA VI-compliant LDGVs;however, the effectiveness of earlier CHINA V standard vehicles requires further evaluation. © 2024, The Authors. All rights reserved.

关键词： Volatile organic compounds

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Highly Sensitive Fiber Optic Spr Sensor Based on Chitosan for the Detection of Trace Cu2+ Ion in Aqueous Solution

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SSRN 2024年

作者： Guo, Xuan Wang, Rui Liu, Feng Ma, Yunjie Fu, Xinghu Yu, Li School of Information Science and Engineering Yanshan University Qinhuangdao066004 China Hebei Provincial Key Laboratory of Specialty Optical Fiber and Optical Fiber Sensing Qinhuangdao066004 China Intelligent Sensing Technology and Equipment for Offshore Seawater Quality Monitoring Engineering Research Center of Hebei Province Yanshan University Qinhuangdao066004 China

In this paper, a highly sensitive fiber-optic sensor was proposed for the detection of Cu2+ traces in aqueous solution which has a nonnegligible impact on human health. Based on the principle of SPR, a uniform chitosan (CS) material was coated on a multimode fiber-single mode fiber-multimode fiber (MSM) structure with silver layer by glutaraldehyde (GLA) and graphene oxide modification. The amino and hydroxyl groups in the material have a recognition function for Cu2+, which can chelate with Cu2+ and change the ambient layer refractive index of the sensor leading to a shift in the SPR spectrum. Trace Cu2+ can be detected by monitoring the shift in the resonance wavelength of the SPR spectrum. The results illustrate that within the range of 0.1~1 mg/L Cu2+ concentration, as the Cu2+ concentration increasing, the SPR spectrum undergoes a red shift and the maximum detection sensitivity of Cu2+ ions achieves 49.4661 nm/(mg/L), with a good linearity of 0.996. The temperature experimental results indicate that the sensor has good stability at room temperature (25-35 °C). The stability and repeatability characteristics of the system are also investigated. The good performance provides a new method in trace Cu2+ in-situ detection. © 2024, The Authors. All rights reserved.

关键词： Refractive index

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A physics-informed data-driven model for landslide susceptibility assessment in the Three Gorges Reservoir area

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Geoscience Frontiers 2023年第5期14卷 1-16页

作者： Songlin Liu Luqi Wang Wengang Zhang Weixin Sun Jie Fu Ting Xiao Zhenwei Dai School of Civil Engineering Chongqing UniversityChongqing 400045China Key Laboratory of New Technology for Construction of Cities in Mountain Area Chongqing UniversityMinistry of EducationChongqing 400045China National Joint Engineering Research Center of Geohazards Prevention in the Reservoir Areas Chongqing UniversityChongqing 400045China Chongqing Field Scientific Observation Station for Landslide Hazards in Three Gorges Reservoir Area Chongqing UniversityChongqing 400045China Center for Hydrogeology and Environmental Geology CGSBaoding Hebei 071051China Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring Ministry of EducationSchool of Geosciences and Info-PhysicsCentral South UniversityChangsha 410083China Central South China Innovation Center for Geosciences Wuhan Centre of China Geological SurveyWuhan 430205China

Landslide susceptibility mapping is a crucial tool for analyzing geohazards in a *** publications have popularized data-driven models,particularly machine learning-based methods,owing to their strong capability in dealing with complex nonlinear ***,a significant proportion of these models have neglected qualitative aspects during analysis,resulting in a lack of interpretability throughout the process and causing inaccuracies in the negative sample *** this study,Scoops 3D was employed as a physics-informed tool to qualitatively assess slope stability in the study area(the Hubei Province section of the Three Gorges Reservoir Area).The non-landslide samples were extracted based on the calculated factor of safety(FS).Subsequently,the random forest algorithm was employed for data-driven landslide susceptibility analysis,with the area under the receiver operating characteristic curve(AUC)serving as the model evaluation *** to the benchmark model(i.e.,the standard method of utilizing the pure random forest algorithm),the proposed method’s AUC value improved by 20.1%,validating the effectiveness of the dual-driven method(physics-informed data-driven).

关键词： Machine Learning Physics-informed Negative sample extraction Interpretability Dual-driven

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Study of UAV Application in Wireless Sensor Networks 3

Study of UAV Application in Wireless Sensor Networks

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3rd International Conference on Mechanical, Electronics, Computer, and Industrial technology, MECnIT 2020

作者： Zhang, Fan Liu, Huidan Ma, Zigian Yang, Yi Wan, Xuefen Donghua University College of Information Science and Technology Shanghai2181287 China North China Institute of Science and Technology College of Computer Hebei IoT Monitoring Engineering Technology Research Center Langfang China

ISBN: (纸本)9781728174037

In order to improve the performance of wireless sensor networks, unmanned aerial vehicles (UAVs) are introduced as an auxiliary tool. This paper reviews the main applications of UAVs in wireless sensor networks today. These applications are divided to three categories: auxiliary wireless sensor network data gathering, collaborative sensing and autonomous deployment nodes. For these three types of applications, detailed discussions are made in combination with their engineering application examples. In addition, based on the existing research, the development trend of the future hybrid system composed of UAV and wireless sensor network is analyzed. The research results show that the introduction of UAVs in wireless sensor networks can not only effectively enhance their sensing capabilities, communication capabilities, and deployment capabilities, but also hope to obtain new service methods, thereby realizing an air-ground hybrid networking information service system © 2020 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Temporal variations and source apportionment of volatile organic compounds at an urban site in Shijiazhuang, China

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Journal of Environmental Sciences 2020年第11期32卷 25-34页

作者： Yanan Guan Lei Wang Shujuan Wang Yihao Zhang Jieying Xiao Xiaoli Wang Erhong Duan Li'an Hou School of Environmental Science and Engineering Hebei University of Science and TechnologyShijiazhuang 050018China National and Local Joint Engineering Center of Volatile Organic Compounds&Odorous Pollution Control Technology Shijiazhuang 050018China Hebei Province Environmental Monitoring Center Shijiazhuang 050018China Hebei Province Environmental Emergency and Heavy Pollution Weather Warning Center Shijiazhuang 050018China Logistics Science and Technology Research Institute of Rocket Army Beijing 100011China

Shijiazhuang,the city with the worst air quality in China,is suffering from severe ozone pollution in *** the key precursors of ozone generation,it is necessary to control the Volatile Organic Compounds(VOCs)*** have a better understanding of the pollution status and source contribution,the concentrations of 117 ambient VOCs were analyzed from April to August 2018 in an urban site in *** showed that the monthly average concentration of total VOCs was 66.27 ppbv,in which,the oxygenated VOCs(37.89%),alkanes(33.89%),and halogenated hydrocarbons(13.31%)were the main composite *** major sources were identified using Positive Matrix Factorization modeling with an accurate VOCs emission inventory as inter-complementary methods revealed that the petrochemical industry(26.24%),other industrial sources(15.19%),and traffic source(12.24%)were the major sources for ambient VOCs in *** spatial distributions of major industrial activities emissions were identified by using geographic information statistics system,which illustrated the VOCs was mainly from the north and southeast of *** inverse trajectory analysis using Hybrid Single-Particle Lagrangian Integrated Trajectory(HYSPLIT)and Potential Source Contribution Function(PSCF)clearly demonstrated the features of pollutant transport to *** findings can provide references for local governments regarding control strategies to reduce VOCs emissions.

关键词： VOCs Source analysis Positive Matrix Factorization(PMF) modeling GIS Inverse trajectory Shijiazhuang

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Recognition of Maize Seedling Under Weed Disturbance Using Deep Learning Algorithms

SSRN

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SSRN 2023年

作者： Tang, Boyi Gu, Xiaohe Zhao, Chunjiang Li, Xuguang Zhou, Jingping Qu, Xuzhou Pan, Yuchun Cui, Yanglin Liu, Chang College of Information Engineering Northwest A&F University Yangling712100 China Information Technology Research Center Beijing Academy of Agriculture and Forestry Sciences Beijing100097 China HeBei Provincial Cultivated Land Quality Monitoring and Protection Center China

Using UAV-based RGB images to recognize maize seedlings is of great significant for precise weed control, efficient water and fertilizer management. However, the presence of weeds with morphological resemblances at the maize seedling stage affects the recognition of maize seedlings. This research employs UAV RGB images and deep learning algorithms to achieve accurate recognition of maize seedlings under weed disturbance. Firstly, the adaptive anchor frame algorithm is employed to intelligently select optimal anchor frame sizes suited for the maize seedling from UAV images. This strategic selection minimizes time and computational demands associated with multiple anchor frame sampling. Subsequently, the Global Attention Mechanism (GAM) is introduced, bolstering feature extraction capabilities. A range of deep learning models, including YOLOv3 and YOLOv5, are applied for maize seedling recognition, culminating in the identification of an optimal model. To account for real-world scenarios, we investigate the influences of UAV flight altitude and weed disturbance on maize seedling recognition. The results indicate a multi-class Average Precision (mAP) of 94.5% and 88.2% for detecting maize seedlings at flight altitudes of 15m and 30m, respectively. This emphasizes the efficacy of the improved YOLOv5 deep learning model in recognizing maize seedlings under weed disturbance using UAV RGB images. © 2023, The Authors. All rights reserved.

关键词： Object detection

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Improved Extraction Performance of Sno2 Etl for Perovskite Solar Cells by a Combined Hydrolysis Oxidation and Sol-Gel Method

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SSRN 2023年

作者： Zhao, Hang Cheng, Zetong Lv, Kuanxin Yuan, Shiyu Chen, Zeli Yang, Yuyun Huang, Xing Li, Zhenzhen College of Metallurgy and Energy North China University of Science and Technology Hebei Tangshan063210 China Research and Monitoring Division Municipal Engineering Design and Research Institute Changchun130000 China Municipal Facilities Maintenance and Management Center Changchun130000 China

Tin dioxide (SnO2) is widely used in perovskite solar cells due to its high electron mobility, suitable conduction band and low-temperature preparation characteristics. Currently, the two most commonly used methods for preparing SnO2 are SnCl2 hydrolysis oxidation or SnO2 sol-gel preparation. However, although SnCl2 hydrolysis oxidation can produce well-crystallized SnO2, its controllability is poor, resulting in low device performance repeatability. On the other hand, the devices based on SnO2 electronic transport layer prepared by the sol-gel method have good repeatability, but usually have poor crystallinity, leading to a decrease in electron transport performance. In this study, a combination of hydrolysis oxidation and sol-gel methods was used to prepare SnO2 electronic transport layers. The results of the study demonstrate that using SnCl2 hydrolysis oxidation to prepare high-quality SnO2 crystalline layers can serve as a pre-growth template to improve the crystalline quality of sol-gel generated SnO2. Additionally, covering the hydrolysis oxidation-based SnO2 layer with sol-gel prepared SnO2 crystalline layer can improves the repeatability of device preparation. The electron transport layers prepared by this method can effectively enhance the quality of thin film crystal growth and charge extraction capability, ultimately contributing to improving the efficiency, stability, and reducing hysteresis of the devices. © 2023, The Authors. All rights reserved.

关键词： Sol-gel process

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