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The methods for improving the biodegradability of oily sludge: a critical review

Environmental science and Pollution research 2024年第29期31卷 41844-41853页

作者： Yan, Yuhao Tong, Kun Li, Chengtao Pan, Lifang State Key Laboratory of Petroleum Pollution Control Beijing102206 China CNPC Research Institute of Safety and Environmental Technology Beijing102206 China College of Environmental Science and Engineering Shaanxi University of Science & ampTechnology Xi’an710021 China

Biological degradation method, as an environmentally friendly, low-carbon, and clean pollution treatment technology, is widely used for the harmless disposal of oily sludge. The biodegradability of oily sludge with stable emulsification system, high oil, and water content is poor. Therefore, it is necessary to pre-treat the oily sludge to improve its biodegradability, including recover the petroleum resources and remove heavy metals and bio-toxic organic matters. This review systematically summarizes five oily sludge treatment methods and their influences on sludge biodegradability, including pyrolysis, chemical hot washing, solvent extraction, chemical oxidation, and hydrothermal. Pyrolysis at temperatures above 750 °C produces high molecular weight polycyclic aromatic hydrocarbons, chemical hot washing and chemical oxidation would cause secondary pollution, solvent extraction method could not be applied due to the high cost and high toxicity of the extractant, and the oil removal of hydrothermal method is inefficient. Additionally, the principles, advantages, and disadvantages of those treatments and the factors affecting microbial degradation were analyzed, which provide the development direction of pretreatment technology to improve the biodegradability of oily sludge. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Heavy metals

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A Joint Estimation Method of SOC and SOH for Lithium-ion Battery Considering Cyber-Attacks Based on GA-BP

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Computers, Materials & Continua 2024年第9期80卷 4497-4512页

作者： Tianqing Yuan Na Li Hao Sun Sen Tan Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin132012China Department of Electrical Engineering Northeast Electric Power UniversityJilin132012China College of Information and Control Engineering Jilin Institute of Chemical TechnologyJilin132022China Center for Research on Microgrids Department of EnergyAalborg UniversityAalborg9220Denmark

To improve the estimation accuracy of state of charge(SOC)and state of health(SOH)for lithium-ion batteries,in this paper,a joint estimation method of SOC and SOH at charging cut-off voltage based on genetic algorithm(GA)combined with back propagation(BP)neural network is proposed,the research addresses the issue of data manipulation resulting ***,anomalous data stemming fromcyber-attacks are identified and eliminated using the isolated forest algorithm,followed by data ***,the incremental capacity(IC)curve is derived fromthe restored data using theKalman filtering algorithm,with the peak of the ICcurve(ICP)and its corresponding voltage serving as the health factor(HF).Thirdly,the GA-BP neural network is applied to map the relationship between HF,constant current charging time,and SOH,facilitating the estimation of SOH based on ***,SOC estimation at the charging cut-off voltage is calculated by inputting the SOH estimation value into the trained model to determine the constant current charging time,and by updating the maximum available *** show that the root mean squared error of the joint estimation results does not exceed 1%,which proves that the proposed method can estimate the SOC and SOH accurately and stably even in the presence of false data injection attacks.

关键词： Lithium-ion batteries state of charge state of health cyber-attacks genetic algorithm back propagation neural network

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Features of Building Automated Educational Systems with Virtual and Augmented Reality Technologies 1

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7th Computational Methods in Systems and Software, CoMeSySo 2023

作者： Slavin, Oleg Federal Research Center «Computer Science and Control» of the Russian Academy of Sciences 44 Building 2 Vavylova Street Moscow119333 Russia

ISBN: (数字)9783031548208

ISBN: (纸本)9783031548192

The features of the construction of automated educational systems with technologies of virtual and augmented reality are outlined in terms of the specifics of the implementation of the current control of the level of knowledge of students using the test control system. For automated correction of the information model of the learning environment in order to form the required learning trajectory, taking into account the specifics of learning and the individual abilities of the student, it is proposed to use automated learning diagrams. The accumulated practical experience convincingly indicates that the implementation of the above approaches allows to reduce the time and improve the quality of trainees’ professional training through adaptive personalized management of trainees’ training by optimizing the typical training structure for each trainee, taking into account the individual characteristics of mastering the educational material. The general tasks of implementing automated learning with the use of virtual and augmented reality technologies that need to be solved are identified. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Students

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Toxicological responses of A549 and HCE-T cells exposed to fine particulate matter at the air–liquid interface

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Environmental science and Pollution research 2024年第18期31卷 27375-27387页

作者： Chen, Wankang Ge, Pengxiang Deng, Minjun Liu, Xiaoming Lu, Zhenyu Yan, Zhansheng Chen, Mindong Wang, Junfeng Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science & ampTechnology Nanjing210044 China Ningxia Meteorological Service Center Yinchuan750002 China

Fine particulate matter (PM2.5) can enter the human body in various ways and have adverse effects on human health. Human lungs and eyes are exposed to the air for a long time and are the first to be exposed to PM2.5. The "liquid immersion exposure method" has some limitations that prevent it from fully reflecting the toxic effects of particulate matter on the human body. In this study, the collected PM2.5 samples were chemically analyzed. An air–liquid interface (ALI) model with a high correlation to the in vivo environment was established based on human lung epithelial cells (A549) and immortalized human corneal epithelial cells (HCE-T). The VITROCELL Cloud 12 system was used to distribute PM2.5 on the cells evenly. After exposure for 6 h and 24 h, cell viability, apoptosis rate, reactive oxygen species (ROS) level, expression of inflammatory factors, and deoxyribonucleic acid (DNA) damage were measured. The results demonstrated significant dose- and time-dependent effects of PM2.5 on cell viability, cell apoptosis, ROS generation, and DNA damage at the ALI, while the inflammatory factors showed dose-dependent effects only. It should be noted that even short exposure to low doses of PM2.5 can cause cell DNA double-strand breaks and increased expression of γ-H2AX, indicating significant genotoxicity of PM2.5. Increased abundance of ROS in cells plays a crucial role in the cytotoxicity induced by PM2.5 exposure These findings emphasize the significant cellular damage and genotoxicity that may result from short-term exposure to low levels of PM2.5. © The Author(s) 2024.

关键词： Cell death

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Constructing high-biosecurity MoS_(2)-based anodes for rapid and efficient lithium storage

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Nano research 2025年第2期18卷 358-366页

作者： Yixin Wang Ruxia Qiao Xueying Zheng Wangyan Wu Hao Yang Stephanie Ling Jie Lee Jian Peng Jinyu Rong Wei Luo Sijie Lin College of Environmental Science and Engineering Biomedical Multidisciplinary Innovation Research InstituteShanghai East HospitalTongji UniversityShanghai 200092China Key Laboratory of Yangtze River Water Environment Shanghai Institute of Pollution Control and Ecological SecurityTongji UniversityShanghai 200092China Institute of New Energy for Vehicles School of Materials Science and EngineeringTongji UniversityShanghai 201804China

Lithium-ion batteries that integrate electrochemical performance and safety considerations offer advantages to curb the reliance on fossil fuels while minimizing the potential environmental *** metal disulfides and metal oxides with high specific capacity are promising candidates as anodes for lithium ***,neither the layered structure of MoS_(2) nor the powder form of In_(2)O_(3) is ideal for battery prolonged ***,we demonstrated a low-toxicity anode designed with hollow fibers to regulate the MoS_(2) contact surface,significantly reducing biotoxicity and enhancing Lit *** functional theory(DFT)calculations revealed that the interactions among MoS_(2),In_(2)O_(3),and the hollow structure lowered the Li-ion migration energy barrier hence fastening the ***,the MoS_(2)-containing fiber showed significantly decreased toxicity in zebrafish embryos compared to MoS_(2) alone,demonstrating a proof-of-principle of integrating functional nanomaterials into flexible fiber structures to improve both electrochemical performance and safety.

关键词： electrospun fibers Li-ion battery MoS_(2) In_(2)O_(3) hollow fiber low-toxicity anode

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Multiagent Consensus over Time-Invariant and Time-Varying Signed Digraphs via Eventual Positivity

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IEEE Transactions on Automatic control 2023年第9期68卷 5429-5444页

作者： Fontan, Angela Wang, Lingfei Hong, Yiguang Shi, Guodong Altafini, Claudio Linköping University Division of Automatic Control Department of Electrical Engineering LinköpingSE-58183 Sweden KTH Royal Institute of Technology Division of Decision and Control Systems StockholmSE-10044 Sweden Chinese Academy of Sciences Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing100190 China University of Chinese Academy of Sciences Beijing100190 China Tongji University Department of Control Science and Engineering Shanghai201804 China University of Sydney Australian Center for Field Robotics School of Aerospace Mechanical and Mechatronic Engineering SydneyNSW2008 Australia

Laplacian dynamics on signed digraphs have a richer behavior than those on nonnegative digraphs. In particular, for the so-called 'repelling' signed Laplacians, the marginal stability property (needed to achieve consensus) is not guaranteed a priori and, even when it holds, it does not automatically lead to consensus, as these signed Laplacians may lose rank even in strongly connected digraphs. Furthermore, in the time-varying case, instability can occur even when switching in a family of systems each of which corresponds to a marginally stable signed Laplacian with the correct corank. In this article, we present novel conditions for achieving consensus on signed digraphs based on the property of eventual positivity, a Perron-Frobenius (PF) type of property for signed matrices. The conditions we develop cover both time-invariant and time-varying cases. A particularly simple sufficient condition, valid in both cases, is that the Laplacians are normal matrices. Such condition can be relaxed in several ways. For instance, in the time-invariant case it is enough that the Laplacian has this PF property on the right side, but not on the left side (i.e., on the transpose). For the time-varying case, convergence to consensus can be guaranteed by the existence of a common Lyapunov function for all the signed Laplacians. All conditions can be easily extended to bipartite consensus. © 1963-2012 IEEE.

关键词： Lyapunov functions

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Attention-Modulated Feature Fusion Neural Network for Inverse Modeling of Microwave Filters

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IEEE Microwave and Wireless Technology Letters 2025年第4期35卷 376-379页

作者： Guo, Linwei Cao, Weihua Hu, Wenkai Lu, Zhengyang Wu, Min China University of Geosciences School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

Inverse modeling is extensively applied in the design and tuning of microwave filters (MFs). Inverse models (IMs) take the features extracted from the high-dimensional electromagnetic parameters as input. How to make full use of features from multiple perspective is a critical issue for improving model accuracy. To solve it, this letter proposes an attention-modulated feature fusion neural network (AMFFNN). AMFFNN achieves multiperspective feature fusion (MPFF) at the input side and independent feature fusion (IFF) at the output side. In addition, feature fusion in AMFFNN is enhanced by attention modules to dynamically identify the importance of each feature. Statistical and comparative results of simulations demonstrate that AMFFNN outperforms existing methods in terms of accuracy, stability, and generalization. © 2023 IEEE.

关键词： Inverse problems

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Prediction of single cell mechanical properties in microchannels based on deep learning

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Applied Mathematics and Mechanics(English Edition) 2024年第11期45卷 1857-1874页

作者： Jiajie GONG Xinyue LIU Yancong ZHANG Fengping ZHU Guohui HU Shanghai Institute of Applied Mathematics and Mechanics School of Mechanics and Engineering ScienceShanghai Frontier Science Center of MechanoinformaticsShanghai Key Laboratory of Mechanics in Energy EngineeringShanghai UniversityShanghai200072China Shanghai Institute of Aircraft Mechanics and Control Shanghai200092China Department of Neurosurgery Huashan HospitalShanghai Medical CollegeFudan UniversityShanghai200040China

Traditional methods for measuring single-cell mechanical characteristics face several challenges,including lengthy measurement times,low throughput,and a requirement for advanced technical *** overcome these challenges,a novel machine learning(ML)approach is implemented based on the convolutional neural networks(CNNs),aiming at predicting cells'elastic modulus and constitutive equations from their deformations while passing through micro-constriction *** the present study,the computational fluid dynamics technology is used to generate a dataset within the range of the cell elastic modulus,incorporating three widely-used constitutive models that characterize the cellular mechanical behavior,i.e.,the Mooney-Rivlin(M-R),Neo-Hookean(N-H),and Kelvin-Voigt(K-V)*** this dataset,a multi-input convolutional neural network(MI-CNN)algorithm is developed by incorporating cellular deformation data as well as the time and positional *** approach accurately predicts the cell elastic modulus,with a coefficient of determination R^(2)of 0.999,a root mean square error of 0.218,and a mean absolute percentage error of 1.089%.The model consistently achieves high-precision predictions of the cellular elastic modulus with a maximum R^(2)of 0.99,even when the stochastic noise is added to the simulated *** significant feature of the present model is that it has the ability to effectively classify the three types of constitutive equations we *** model accurately and reliably predicts single-cell mechanical properties,showcasing a robust ability to *** demonstrate that incorporating deformation features at multiple time points can enhance the algorithm's accuracy and *** algorithm presents a possibility for high-throughput,highly automated,real-time,and precise characterization of single-cell mechanical properties.

关键词： cell deformation single-cell mechanics machine learning(ML) constitutive law convolutional neural network(CNN)

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Indoor Uncertain Semantic Trajectory Similarity Join

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Journal of Computer science & Technology 2024年第6期39卷 1441-1465页

作者： Hong-Bo Yin Dong-Hua Yang Kai-Qi Zhang Hong Gao Jian-Zhong Li Faculty of Computing Harbin Institute of TechnologyHarbin 150001China Center of Analysis Measurement and ComputingHarbin Institute of TechnologyHarbin 150001China Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China

With the widespread deployment of indoor positioning systems, an unprecedented scale of indoor trajectories is being produced. By considering the inherent uncertainties and the text information contained in such an indoor trajectory, a new definition named Indoor Uncertain Semantic Trajectory is defined in this paper. In this paper, we focus on a new primitive, yet quite essential query named Indoor Uncertain Semantic Trajectory Similarity Join (IUST-Join for short), which is to match all similar pairs of indoor uncertain semantic trajectories from two sets. IUST-Join targets a number of essential indoor applications. With these applications in mind, we provide a purposeful definition of an indoor uncertain semantic trajectory similarity metric named IUS. To process IUST-Join more efficiently, both an inverted index on indoor uncertain semantic trajectories named 3IST and the first acceleration strategy are proposed to form a filtering-and-verification framework, where most invalid pairs of indoor uncertain semantic trajectories are pruned at quite low computation cost. And based on this filtering-and-verification framework, we present a highly-efficient algorithm named Indoor Uncertain Semantic Trajectory Similarity Join Processing (USP for short). In addition, lots of novel and effective acceleration strategies are proposed and embedded in the USP algorithm. Thanks to these techniques, both the time complexity and the time overhead of the USP algorithm are further reduced. The results of extensive experiments demonstrate the superior performance of the proposed work.

关键词： filtering-and-verification framework indoor uncertain semantic trajectory inverted index trajectory similarity join

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Numerical Simulation of Pressure Fluctuations on a Plate behind a Transverse Recess in a Supersonic Flow

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Mathematical Models and Computer Simulations 2024年第6期16卷 861-869页

作者： Savel’ev, A.D. Savel’ev, I.A. Federal Research Center “Computer Science and Control ” Russian Academy of Sciences Moscow 119333 Russian Federation Lomonosov Moscow State University Moscow Russian Federation

Abstract: The flow around a flat transverse recess on a flat plate by a supersonic viscous gas flow is numerically simulated. The flow inside the recess and the pressure fluctuations in the wake behind it are studied at the Mach numbers of the incoming flow ranging from 2 to 8 and the laminar boundary layer. High-order difference schemes are used in the calculations. © Pleiades Publishing, Ltd. 2024.

关键词： high-order composite compact schemes Navier–Stokes equations numerical modeling supersonic unsteady viscous gas flows

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