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The effect of hydrostatic pressure on the nitrogen removal potential at the sediment water interface of reservoirs

Zhongguo Huanjing Kexue/China Environmental science 2024年第4期44卷 2119-2129页

作者： Li, Yu-Mei Chen, Kai He, Li-Xin Chai, Bei-Bei Zhuo, Tian-Yu Yu, Ke-Hong Zhang, Jin-Nan Lei, Xiao-Hui School of Water Conservancy and Hydroelectric Power Hebei University of Engineering Handan056038 China School of Water Conservancy and Hydroelectric Hebei University of Engineering Collaborative Innovation Center for Intelligent Regulation and Comprehensive Management of Water Resources Handan056038 China Hebei Key Laboratory of Intelligent Water Conservancy Handan056038 China Handan Key Laboratory of Low-Carbon Energy Handan056038 China Tianjin Water Group Binhai Water Co. Ltd. Tianjin300308 China School of Energy and Environmental Engineering Hebei University of Engineering Handan056038 China School of Architecture and Civil Engineering Xi’an University of Science and Technology Xi′an710054 China State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin China Institute of Water Resources and Hydropower Research Beijing100038 China

The effects of different hydrostatic conditions (atmospheric pressure, 0.2MPa, 0.5MPa and 0.7MPa) on microbial community structure, nitrogen cycling function genes and metabolic pathways at the sediment-water interface of reservoir were studied through microcosmic simulation experiments and metagenomics. The results showed that the number of microbial species involved in nitrogen cycling increased first to 1227 and then decreased to 1199 with the increase of hydrostatic pressure. The relative abundances of archaea and fungi increased by 0.002% and 0.0006% with the increase of hydrostatic pressure, while the proportion of bacteria decreased. High hydrostatic pressure fostered closer ecological network connections, intricate interspecific interactions, and enhanced system stability compared to low pressure. Furthermore, increased hydrostatic pressure facilitated denitrification and repressed dissimilatory nitrate reduction by augmenting the abundance of functional genes such as nxrB and narH, alongside the participating microorganism abundance. Moreover, piezophilic taxa (e.g., Proteobacteria, Chloroflexi, Bacteroidetes) and genes (e.g., ompH, asd) were identified among nitrogen-cycling microorganisms, with a predominant presence in Proteobacteria. Their abundance initially grew and then declined with rising pressure. Hydrostatic pressure can improve the nitrogen removal potential of reservoir sediments by altering the microbial population structure, related functional gene abundance, and metabolic pathways involved in the nitrogen cycle at the sediment-water interface, thereby mitigating reservoir eutrophication. © 2024 Chinese Society for Environmental sciences. All rights reserved.

关键词： Microorganisms

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Identification of important precursors and theoretical toxicity evaluation of byproducts driving cytotoxicity and genotoxicity in chlorination

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Frontiers of Environmental science & Engineering 2020年第2期14卷 125-137页

作者： Qian-Yuan Wu Yi-Jun Yan Yao Lu Ye Du Zi-Fan Liang Hong-Ying Hu Key Laboratory of Microorganism Application and Risk Control of Shenzhen Guangdong Provincial Engineering Research Center for Urban Water Recycling and Environmental SafetyGraduate School at ShenzhenTsinghua UniversityShenzhen 518055China Shenzhen Environmental Science and New Energy Technology Engineering Laboratory Tsinghua-Berkeley Shenzhen InstituteShenzhen 518055China Environmental Simulation and Pollution Control State Key Joint Laboratory State Environmental Protection Key Laboratory of Microorganism Application and Risk Control(SMARC)School of EnvironmentTsinghua UniversityBeijing 100084China

Chlorination,the most widely used disinfection process for water treatment,is unfortunately always accompanied with the formation of hazardous disinfection byproducts(DBPs).Various organic matter species,like natural organic matter(NOM)and amino acids,can serve as precursors of DBPs during chlorination but it is not clear what types of organic matter have higher potential *** regulation of DBPs such as trihalomethanes has received much attention,further investigation of the DBPs driving toxicity is *** study aimed to identify the important precursors of chlorination by measuring DBP formation from NOM and amino acids,and to determine the main DBPs driving toxicity using a theoretical toxicity evaluation of contributions to the cytotoxicity index(CTI)and genotoxicity index(GTI).The results showed that NOM mainly formed carbonaceous DBPs(CDBPs),such as trichloromethane,while amino acids mainly formed nitrogenous DBPs(N-DBPs),such as dichloroacetonitrile(DCAN).Among the DBPs,DCAN had the largest contribution to the toxicity index and might be the main driver of *** the precursors,aspartic acid and asparagine gave the highest DCAN concentration(200 g/L)and the highest CTI and ***,aspartic acid and asparagine are important precursors for toxicity and their concentrations should be reduced as much as possible before chlorination to minimize the formation of *** chlorination of NOM,tryptophan,and asparagine solutions with different chlorine doses and reaction times,changes in the CTI and GTI were consistent with changes in the DCAN concentration.

关键词： Chlorination Dichloroacetonitrile Aspartic acid Asparagine Toxicity index

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Neural architecture search for fault diagnosis

arXiv

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arXiv 2020年

作者： Li, Xudong Hu, Yang Zheng, Jianhua Li, Mingtao National Space Science Center. CAS University of Chinese Academy of Sciences Beijing China Science and Technology on Complex Aviation System Simulation Laboratory 9236 mailbox Beijing China

Data-driven methods has made great progress in fault diagnosis, especially deep learning method. Deep learning is suitable for processing big data, and has a strong feature extraction ability to realize end-to-end fault diagnosis systems. Due to the complexity and variability of experimental data, some deep learning models are designed to be complex. However, designing neural network architecture requires rich professional knowledge and debugging experience, and a lot of experiments are needed to screen models and hyperparameters, increasing the difficulty of developing deep learning models. Fortunately, neural architecture search (NAS) is developing rapidly, and is becoming one of the next directions for deep learning. Given a search space, NAS can automatically search for the optimal network architecture. In this paper, we proposed a NAS method for fault diagnosis using reinforcement learning. A recurrent neural network is used as an agent to generate the network architecture. The accuracy of the generated network on the validation dataset is fed back to the agent as a reward, and the parameters of the agent are updated through the strategy gradient algorithm. In order to speed up the search process, parameters sharing method is adopted in this paper. We use PHM 2009 Data Challeng gearbox dataset to prove the effectiveness of propsed method, and obtain state-of-the-art results compared with other artificial designed network structures. To authors best knowledge, its the first time that NAS has been applied in fault diagnosis. Copyright © 2020, The Authors. All rights reserved.

关键词： Failure analysis

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Climatic and Biotic Controls of Evapotranspiration Across Grassland Ecosystems on Tibetan Plateau

SSRN

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SSRN 2024年

作者： Peng, Siyuan Yang, Yue Luo, Dengnan Zeng, Xiang Liang, Minqi Tao, Long Zhang, Guangru Li, Pan Liao, Weijie Guo, Qun Cao, Ruochen Li, Yuzhe Zhang, Weirong Hu, Zhongmin School of Geography South China Normal University Shipai Campus Guangzhou510631 China Hainan Baoting Tropical Rainforest Ecosystem Observation and Research Station School of Ecology Hainan University Haikou570228 China Facility of Geographical Science Beijing Normal University Beijing100875 China Zhuhai Branch State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Zhuhai519087 China School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat-sen University Guangdong Zhuhai510245 China Key Lab of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing101408 China International Institute for Earth System Sciences Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing University Jiangsu 210023 China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications Ministry of Natural Resources School of Geography and Ocean Science Nanjing University Jiangsu 210023 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China

Comprehending the spatial variations of evapotranspiration (ET) and its components on Tibetan Plateau (TP) is crucial for grasping the dynamics of the regional water cycle and energy balance. However, the influence of various environmental factors on ET and its components remains unclear. This study addresses this gap by utilizing observational data from 14 sites and employing the Shuttleworth-Wallace-Hu (SWH) model to examine the spatial relationships between ET, its components, and influencing factors. The SWH model parameters were optimized using the Monte Carlo method, achieving a satisfactory simulation performance with an average R2 value of 0.75. Our analysis indicates that in alpine meadow, the ratio of transpiration to ET is generally higher (0.55) compared to alpine steppe (0.39). In terms of spatial distribution, both precipitation and leaf area index significantly impact ET and transpiration. Precipitation emerges as the primary driver of interannual spatial variations in ET, while leaf area index plays a pivotal role in regulating proportion of transpiration. Furthermore, our results reveal a transition from water-dominated to energy-dominated in TP grassland ecosystem at an aridity index of 0.73. This finding is significant as it challenges the common application of an aridity index of 0.65 to distinguish arid from humid regions. It suggests that TP grassland, within the 0.65-0.73 range, remain primarily water-driven. These findings enhance our comprehension of the intricate interactions within the water cycle. © 2024, The Authors. All rights reserved.

关键词： Evapotranspiration

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Climatic and Biotic Controls of Evapotranspiration Across Grassland Ecosystems on the Tibetan Plateau

SSRN

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SSRN 2024年

作者： Peng, Siyuan Yang, Yue Luo, Dengnan Zeng, Xiang Liang, Minqi Tao, Long Zhang, Guangru Li, Pan Liao, Weijie Guo, Qun Cao, Ruochen Li, Yuzhe Zhang, Weirong Hu, Zhongmin School of Geography South China Normal University Shipai Campus Guangzhou510631 China Hainan Baoting Tropical Rainforest Ecosystem Observation and Research Station School of Ecology Hainan University Haikou570228 China Facility of Geographical Science Beijing Normal University Beijing100875 China Zhuhai Branch of State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Zhuhai519087 China School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat-sen University Guangdong Zhuhai510245 China Key Lab of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing101408 China International Institute for Earth System Sciences Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing University Jiangsu210023 China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources School of Geography and Ocean Science Nanjing University Jiangsu210023 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China

Study region: The Tibetan Plateau in China, the Third Pole of the *** focus: Accurate descriptions of spatial variation in evapotranspiration (ET) and its components on the Tibetan Plateau (TP) are crucial for understanding the dynamics of the regional water cycle and energy balance. However, how various environmental factors affect ET and its components remains unclear. This study addresses this gap using observational data from 14 sites and employing the Shuttleworth-Wallace-Hu (SWH) model to examine the spatial relationships between ET, its components, and underlying *** hydrological insights for the region: The SWH model parameters were optimized using the Monte Carlo method, achieving a satisfactory model performance with an average R² of 0.75. The ratio of transpiration to ET was generally higher in alpine meadows (0.55) than alpine steppes (0.39). Across the TP, precipitation and the leaf area index together shaped spatial variation in ET and transpiration. Precipitation emerged as the primary driver of interannual variation in ET, while the leaf area index strongly regulated the proportion of ET accounted for by transpiration. Furthermore, above aridity index values of 0.73, grassland ecosystems transitioned from water to energy. This finding is significant as it challenges the common application of an aridity index value of 0.65 to distinguish arid from humid regions. It suggests that TP grasslands, with an AI of 0.65-0.73, remain primarily water-limited. © 2024, The Authors. All rights reserved.

关键词： Biotic

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A Microservices Oriented Edge Computing Framework for LVC simulation in the IoT Era

A Microservices Oriented Edge Computing Framework for LVC Si...

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2019第十一届计算机建模与仿真国际会议

作者： Wenxin Sun Yanlong Zhai Tianhong Bao Muhammad Mudassar Jun Shen Kai Yang School of Computer Science Beijing Institute of Technology School of Computing & Information Technology University of Wollongong Science and Technology on Special System Simulation Laboratory Beijing Simulation Center

Modeling and simulation are essential methods to better understand a complex system in the real world. Many simulation systems have strong demand for involving physical devices or equipment in the system to improve the fidelity. But most of the current cloud based simulation systems are designed for equipment with adequate resources and suffering from high latency for their centralized communication. Edge computing is getting much attention as a new paradigm for distributed systems involving heterogeneous devices and requiring real-time communication. However, edge computing is still in its initial stage and there is no consensus on the edge framework and implementation. To the best of our knowledge, no detailed studies have explored the edge-side simulation and modeling. In this paper, we study and design an edge-side simulation framework, which exploits light-weight microservices architecture to build scalable and real-time LVC(Live, Virtual and Constructive) simulations. Specifically, the application model is designed to illustrate how LVC simulation integrates with edge computing and cloud computing. The autonomous negotiation service and time synchronization services are discussed in details. Though it is a preliminary edge computing framework for LVC simulation, no similar research has been conducted for modeling and simulation using edge computing.

关键词： Edge-side simulation microservices LVC simulation IoT

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Pilot-scale experiments on multilevel contact oxidation treatment of poultry farm wastewater using saran lock carriers under different operation model

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Journal of Environmental sciences 2019年第3期31卷 336-345页

作者： Tianlong Zheng Peng Li Xiaoyu Ma Xiaohong Sun Chuanfu Wu Qunhui Wang Ming Gao State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Department of Environmental Engineering University of Science and Technology Beijing Xinkai Water Environmental Investment Co.Ltd Beijing Agro-Biotechnology Research Center Beijing Academy of Agriculture and Forestry Sciences

A pilot-scale multilevel contact oxidation reactors system, coupled with saran lock carriers,was applied for the treatment of poultry farm wastewater. The removal efficiencies of CODcr, ammonia, and the total nitrogen as well as the elimination performance of CODcr and total nitrogen along the three-level contact oxidation tanks under six designed operational models were investigated. Based on the performance of the nitrogen removal of the saran lock carriers and the distribution of anoxic–aerobic interspace under the suitable operation model, the mechanism of nitrogen removal of the system was also explored. The results revealed that the intermittent aeration under parallel model is the most suitable operation model, while the removal efficiencies of CODcr, ammonia, and the total nitrogen were 86.86%, 84.04%, and 80.96%, respectively. The effluent concentration of CODcr,ammonia, and the total nitrogen were 55.6 mg/L, 8.3 mg/L, and 12.0 mg/L, which satisfy both the discharge standard of pollutants for livestock and poultry breeding industry(GB18596–2001) and the first grade of the integrated wastewater discharge standard(GB 8978–1996). Moreover, the mechanism for the nitrogen removal should be attributed to the plenty of anoxic–aerobic interspaces of the biofilm and the three-dimensional spiral structure of the saran lock carriers, where the oxygen-deficient distribution was suitable for the happening of the simultaneous nitrification and denitrification process. Therefore, the multilevel contact oxidation tanks system is an effective pathway for the treatment of the poultry farm wastewater on the strength of a suitable operation model and novel carriers.

关键词： Multilevel contact oxidation tanks Nitrogen removal Mechanism Operation model Poultry farm wastewater Saran lock carriers

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Method for constructing multi-dimensional feature map of malicious code

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Journal of Physics: Conference Series 2021年第4期1748卷

作者： Haocong Ma Ji Zhang Junhua Zhou Xiang Zhai Junjie Xue Hang Ji State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing 100854 China Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing simulation Center Beijing 100854 China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center Beijing 100854 China School of Computer Science and Technology Beijing Institute of Technology Beijing 100081 China

Malicious code is characterized by a large number of types, rapid increase in number, continuous update of transmission routes, and continuous enhancement of back analysis and back detection methods. Therefore, how to effectively detect and analyze malicious code has been a problem of great concern. This paper studies the features of binary file and disassembly file of malicious code, introduces the concept of information gain, and proposes a method to construct the multi-dimensional characteristic graph of malicious code. Finally, the convolutional neural network is used to classify the multi-dimensional feature graph of malicious code, which provides a new idea for the feature extraction of malicious code.

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Climatic and Biotic Controls of Evapotranspiration Across Grassland Ecosystems on Tibetan Plateau

SSRN

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SSRN 2024年

作者： Peng, Siyuan Yang, Yue Luo, Dengnan Zeng, Xiang Liang, Minqi Tao, Long Zhang, Guangru Li, Pan Liao, Weijie Guo, Qun Cao, Ruochen Li, Yuzhe Zhang, Weirong Hu, Zhongmin School of Geography South China Normal University Shipai Campus Guangzhou510631 China Hainan Baoting Tropical Rainforest Ecosystem Observation and Research Station Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation School of Ecology and Environment Hainan University Haikou570228 China Center for Eco-Environment Restoration Engineering of Hainan Province Hainan University Haikou570228 China Facility of Geographical Science Beijing Normal University Beijing100875 China Zhuhai Branch of State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Zhuhai519087 China School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat-sen University Guangdong Zhuhai510245 China Key Lab of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing101408 China International Institute for Earth System Sciences Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing University Jiangsu210023 China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources School of Geography and Ocean Science Nanjing University Jiangsu210023 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China

Understanding the spatial variations of evapotranspiration (ET) and its components on Tibetan Plateau (TP) is pivotal for grasping the regional water cycle and energy balance dynamics. Yet it is unclear how the changes of the intricate synergy among diverse environment factors significantly impacts the patterns of ET and its transformation state. Addressing this gap, this study employed observational data from 14 sites, utilizing the Shuttleworth-Wallace-Hu (SWH) model to investigate the spatial relationships between ET, its components, and influencing factors. Model parameters of SWH were optimized by Monte Carlo method, achieving a commendable simulation performance with a mean R2 value of 0.75. Our analysis reveals that in alpine meadow, the ratio of transpiration (T) to ET (T/ET) is generally higher (0.55) compared to alpine steppe (0.39). The T/ET values for hover around or below 0.5, indicating a balanced contribution of various ET components. Spatially, both PPT and LAI have an impact on ET and T/ET. PPT emerges as the primary driver of interannual spatial variations in ET, while LAI plays a crucial role in regulating T/ET. Our results further demonstrate that a transition from water-dominated to energy-dominated systems in TP grassland ecosystem at an approximately aridity index of 0.73. This is noteworthy considering the general application of an aridity index of 0.65 to delineate arid from humid regions. It implies that TP grasslands, within the 0.65-0.73 range, remain primarily water-driven. This insight holds substantial implications for comprehending water-energy dynamics in similar ecosystems, challenging the conventional binary categorization of arid and humid areas. Such findings are of immense significance in enhancing understanding of the intricate interactions of the water cycle between land and the atmosphere. © 2024, The Authors. All rights reserved.

关键词： Water supply

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Climatic and Biotic Controls of Evapotranspiration Across Grassland Ecosystems on the Tibetan Plateau

SSRN

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SSRN 2025年

作者： Peng, Siyuan Yang, Yue Luo, Dengnan Zeng, Xiang Liang, Minqi Tao, Long Zhang, Guangru Li, Pan Liao, Weijie Guo, Qun Cao, Ruochen Li, Yuzhe Zhang, Weirong Hu, Zhongmin Hainan Baoting Tropical Rainforest Ecosystem Observation and Research Station School of Ecology Hainan University Haikou570228 China Department of Geography Faculty of Arts and Sciences Beijing Normal University Zhuhai519087 China Facility of Geographical Science Beijing Normal University Beijing100875 China Zhuhai Branch of State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Zhuhai519087 China School of Geography South China Normal University Shipai Campus Guangzhou510631 China School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat-sen University Guangdong Zhuhai510245 China Key Lab of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing101408 China International Institute for Earth System Sciences Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing University Jiangsu210023 China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources School of Geography and Ocean Science Nanjing University Jiangsu210023 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China

关键词： Monte Carlo methods

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