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Structural effects of sulfonamides on the proliferation dynamics of sulfonamide resistance genes in the sequencing batch reactors and the mechanism

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Journal of Environmental sciences 2024年第1期135卷 161-173页

作者： Ligui Wu Mingyu Wang Lingling Rong Wenbiao Wang Linwei Chen Qiaofeng Wu Haoyu Sun Xiangfeng Huang Xiaoming Zou College of Environmental science and engineering Tongji UniversityShanghai 200092China School of Life science Jinggangshan UniversityJi’an 343009China Key Laboratory of Organic Compound Pollution control engineering(MOE) School of Environmental and Chemical EngineeringShanghai UniversityShanghai 200444China Fuzhou Urban and Rural Construction Group Co.Ltd. Fuzhou 350007China

Antibiotic resistance genes(ARGs)can be easily promoted by antibiotics,however,the structural effects of antibiotics on the proliferation of ARGs dynamic and the associated mechanisms remain obscure in,especially,activated sludge sequencing batch reactors.In the present study,the effects of 9 sulfonamides(SAs)with different structures on the proliferation dynamic of sulfonamide resistance genes(Suls)in the activated sludge sequencing batch reactors and the corresponding mechanisms were determined(30 days),and the results showed that the largest proliferation value(ΔA^(R))of Suls dynamic for SAs(sulfachloropyridazine)was approximately 2.9 times than that of the smallest one(sulfadiazine).The proliferation of Suls was significantly related to the structural features(minHBint6,SssNH,SHBd and SpMax2_Bhm)that represent the biological activity of SAs.To interpret the phenomenon,a mechanistic model was developed and the results indicated that the biodegradation of SAs(T_(1/2))rather than conjugative transfer frequency or mutation frequency tends to be the key process for affecting Suls proliferation.T_(1/2)was proved to be dependent on the interactions between SAs and receptors(E_(binding)),the cleavage mode(bond dissociation energy),and the site of nucleophilic assault.Besides,the metagenomic analysis showed that SAs posed significant effect on antibiotic resistome and Tnp31 played a vital role in the proliferation of Suls.Overall,our findings provide important insight into a theoretical basis for understanding the structural effects of SAs on the proliferation of ARGs in SBR systems.

关键词： Activated sludge Sulfonamides Suls Proliferation Mechanism

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Categorizing methods for integrating machine learning with executable specifications

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science China(Information sciences) 2024年第1期67卷 5-19页

作者： David HAREL Raz YERUSHALMI Assaf MARRON Achiya ELYASAF department of Computer science and Applied Mathematics Weizmann Institute of Science department of Software and Information Systems engineering Ben-Gurion University of the Negev

Deep learning(DL),which includes deep reinforcement learning(DRL),holds great promise for carrying out real-world tasks that human minds seem to cope with quite readily.That promise is already delivering extremely impressive results in a variety of areas.However,while DL-enabled systems achieve excellent performance,they are far from perfect.It has been demonstrated,in several domains,that DL systems can err when they encounter cases they had not hitherto encountered.Furthermore,the opacity of the produced agents makes it difficult to explain their behavior and ensure that they adhere to various requirements posed by human engineers.At the other end of the software development spectrum of methods,behavioral programming(BP) facilitates orderly system development using self-standing executable modules aligned with how humans intuitively describe desired system behavior.In this paper,we elaborate on different approaches for combining DRL with BP and,more generally,machine learning(ML) with executable specifications(ES).We begin by defining a framework for studying the various approaches,which can also be used to study new emerging approaches not covered here.We then briefly review state-of-the-art approaches to integrating ML with ES,continue with a focus on DRL,and then present the merits of integrating ML with BP.We conclude with guidelines on how this categorization can be used in decision making in system development,and outline future research challenges.

关键词： machine learning artificial intelligence grey box learning domain knowledge rules behavioral programming deep reinforcement learning survey

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Molecular Generation and Optimization of Molecular Properties Using a Transformer Model

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Big Data Mining and Analytics 2024年第1期7卷 142-155页

作者： Zhongyin Xu Xiujuan Lei Mei Ma Yi Pan School of Computer science Shaanxi Normal UniversityXi'an 710119China Faculty of Computer science and control engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China

Generating novel molecules to satisfy specific properties is a challenging task in modern drug discovery,which requires the optimization of a specific objective based on satisfying chemical rules.Herein,we aim to optimize the properties of a specific molecule to satisfy the specific properties of the generated molecule.The Matched Molecular Pairs(MMPs),which contain the source and target molecules,are used herein,and logD and solubility are selected as the optimization properties.The main innovative work lies in the calculation related to a specific transformer from the perspective of a matrix dimension.Threshold intervals and state changes are then used to encode logD and solubility for subsequent tests.During the experiments,we screen the data based on the proportion of heavy atoms to all atoms in the groups and select 12365,1503,and 1570 MMPs as the training,validation,and test sets,respectively.Transformer models are compared with the baseline models with respect to their abilities to generate molecules with specific properties.Results show that the transformer model can accurately optimize the source molecules to satisfy specific properties.

关键词： molecular optimization transformer Matched Molecular Pairs(MMPs) logD solubility

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Multi-time Collaborative Restoration for Integrated Electrical-gas Distribution Systems Based on Rolling Optimization

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 660-671页

作者： Jingyang Yun Zheng Yan Yun Zhou Peichao Zhang Weidong Hu Key Laboratory of control of Power Transmission and Conversion of Ministry of Education Department of Electrical EngineeringShanghai Jiao Tong University

This paper proposes a multi-time collaborative restoration model for integrated electricity-gas distribution sys-tems(IEGDSs)considering multiple resources after extreme weather events.Based on the linearized power flow constraints of the unbalanced electrical distribution system(EDS)and gas distribution system(GDS),this problem can be formulated as a mixed-integer linear programming(MILP)model.To improve the efficiency and veracity of the solution,a rolling optimiza-tion based two-stage method is developed with the first stage solved by a linear approximation model,and the second stage solved by real-time updated rolling optimization.By solving the MILP problem using rolling optimization,the proposed model and solution method achieve efficient and reliable collaborative restoration of IEGDS considering multiple resources and unbal-anced operation characteristics of EDS.The effectiveness of the proposed model and method is validated by using an IEGDS made of a 37-bus unbalanced EDS and 11-node GDS.Index Terms-Electricity-gas system,mix-integer linear programming,power system restoration.

关键词： Electricity-gas system mix-integer linear programming power system restoration

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Neural Dynamics for Cooperative Motion control of Omnidirectional Mobile Manipulators in the Presence of Noises: A Distributed Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1605-1620页

作者： Yufeng Lian Xingtian Xiao Jiliang Zhang Long Jin Junzhi Yu Zhongbo Sun the department of control engineering Changchun University of TechnologyChangchun 130012China IEEE the College of Information science and engineering Northeastern UniversityShenyang 110819 the National Mobile Communications Research Laboratory Southeast UniversityNanjing 210096China the School of Information science and engineering Lanzhou UniversityLanzhou 730000China the State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and RoboticsCollege of EngineeringPeking UniversityBeijing 100871China

This paper presents a distributed scheme with limited communications, aiming to achieve cooperative motion control for multiple omnidirectional mobile manipulators(MOMMs).The proposed scheme extends the existing single-agent motion control to cater to scenarios involving the cooperative operation of MOMMs. Specifically, squeeze-free cooperative load transportation is achieved for the end-effectors of MOMMs by incorporating cooperative repetitive motion planning(CRMP), while guiding each individual to desired poses. Then, the distributed scheme is formulated as a time-varying quadratic programming(QP) and solved online utilizing a noise-tolerant zeroing neural network(NTZNN). Theoretical analysis shows that the NTZNN model converges globally to the optimal solution of QP in the presence of noise. Finally, the effectiveness of the control design is demonstrated by numerical simulations and physical platform experiments.

关键词： Cooperative motion control noise-tolerant zeroing neural network(NTZNN) omnidirectional mobile manipulator(OMM) repetitive motion planning

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High-temperature Oxidation Behavior of Barrel Materials

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Binggong Xuebao/Acta Armamentarii 2024年第4期45卷 1354-1362页

作者： Zhang, Cheng Zhang, Yuqi Wen, Xiangli Bai, Pengpeng Meng, Yonggang Ma, Liran Tian, Yu State Key Laboratory of Tribology Department of Mechanical Engineering Tsinghua University Beijing 100084 China National Joint engineering Research Center forAbrasion control and Molding of Metal Materials School of Materials Science and Engineering Henan University of Science and Technology Henan Luoyang 471003 China

With the increase in firepower strike requirements and the development of high-powered artillery, the high-temperature oxidation of barrel materials is becoming more and more serious, which seriously affects the performance of weapon and even leads to the scrapping of weapon. However, there is little research on the anti-oxidation performance of barrel materials at present. In this paper, the oxidation resistances and oxidation mechanisms of three barrel materials, i. e.,PCrNi3MoVA steel. 30SiMn2MoVA steel and MPS700 steel, at 600 ℃ in airare investigated. The cross-sectional morphology and phases of the oxide layers are analyzed by scanning electron microscopy, energy spectroscopy and X-ray diffractometry. The oxidation kinetics of three barrrel materials were analyzed. The results show that the oxide film thicknesses of the three steels gradually thicken and the rate of increaseinthickness gradually decreaseswith the increase in oxidation time. The oxidation kinetics curves of the three barrel materials are consistent with the parabolic growth kinetics law of oxide film. At 600 ℃, the internal oxide layer of PCrNi3MoVA steel forms an adhesive layer of a network structure consisting mainlyof Ni and Cr-richspinel oxides but theadhesive layerdoes not act as a barrier against oxidation. The inner layer of oxide layer of 30SiMn2MoVA steel is a porous aggregation zone of Si element oxide with a loose structure and relatively serious oxide flaking. The internal oxide layer of MPS700 steel forms a protective Cr-rich oxide layer that effectively prevents further oxidation. At the same time, Mo element stabilises the passivation film and indirectly improves oxidation resistance. Compared with PCrNi3MoVA steel and 30SiMn2MoVA steel, MPS700 steel can better form a dense oxidized layer under high temperature condition, so as to reduce the high temperature oxidation and wear degree of the matrix under high temperature conditions. MPS700 steel is more suitable for the preparation of long life and high reliability barrel. © 20

关键词： Alloying elements

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Research progress on metal-organic framework compounds(MOFs)in electrocatalysis

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Journal of Environmental sciences 2024年第7期141卷 261-276页

作者： Yutong Guo Shunzheng Zhao Xiaolong Tang Honghong Yi department of Environmental science and engineering School of Energy and Environmental EngineeringUniversity of Science and Technology BeijingBeijing 100083China Beijing Key Laboratory of Resource-oriented Treatment of Industrial Pollutants Beijing 100083China

Metal-organic frameworks(MOFs)have favorable characteristics such as large specific surface area,high porosity,structural diversity,and pore surface modification,giving them great potential for development and attractive prospects in the research area of modern materials electrocatalysis.However,unsatisfactory catalytic activity and poor electronic conductivity are the main challenges facing MOFs.This review focuses on MOF-based materials used in electrocatalysis,based on the types of catalytic reactions that have used MOF-based materials in recent years along with their applications,and also looks at some new electrocatalytic materials and their future development prospects.

关键词： Metal-organic frame compounds Electrocatalysis Oxidation-reduction Nitrogen fixation to synthesize ammonia Carbon dioxide reduction

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A Novel Eccentric Intrusion Detection Model Based on Recurrent Neural Networks with Leveraging LSTM

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Computers, Materials & Continua 2024年第3期78卷 3089-3127页

作者： Navaneetha Krishnan Muthunambu Senthil Prabakaran Balasubramanian Prabhu Kavin Kishore Senthil Siruvangur Kavitha Chinnadurai Jehad Ali department of Computer Applications Karpagam College of EngineeringCoimbatore641032India department of Computer science and engineering Karpagam College of EngineeringCoimbatore641032India department of Data science and Business Systems College of Engineering and TechnologySRM Institute of Science and TechnologyKattankulathur603203India department of Computer science and engineering Sathyabama Institute of Science and TechnologyJeppiaar NagarRajiv Gandhi SalaiChennai600119India department of AI Convergence Network Ajou UniversitySuwon16499Korea

The extensive utilization of the Internet in everyday life can be attributed to the substantial accessibility of online services and the growing significance of the data transmitted via the Internet.Regrettably,this development has expanded the potential targets that hackers might exploit.Without adequate safeguards,data transmitted on the internet is significantly more susceptible to unauthorized access,theft,or alteration.The identification of unauthorised access attempts is a critical component of cybersecurity as it aids in the detection and prevention of malicious attacks.This research paper introduces a novel intrusion detection framework that utilizes Recurrent Neural Networks(RNN)integrated with Long Short-Term Memory(LSTM)units.The proposed model can identify various types of cyberattacks,including conventional and distinctive forms.Recurrent networks,a specific kind of feedforward neural networks,possess an intrinsic memory component.Recurrent Neural Networks(RNNs)incorporating Long Short-Term Memory(LSTM)mechanisms have demonstrated greater capabilities in retaining and utilizing data dependencies over extended periods.Metrics such as data types,training duration,accuracy,number of false positives,and number of false negatives are among the parameters employed to assess the effectiveness of these models in identifying both common and unusual cyberattacks.RNNs are utilised in conjunction with LSTM to support human analysts in identifying possible intrusion events,hence enhancing their decision-making capabilities.A potential solution to address the limitations of Shallow learning is the introduction of the Eccentric Intrusion Detection Model.This model utilises Recurrent Neural Networks,specifically exploiting LSTM techniques.The proposed model achieves detection accuracy(99.5%),generalisation(99%),and false-positive rate(0.72%),the parameters findings reveal that it is superior to state-of-the-art techniques.

关键词： Cybersecurity intrusion detection machine learning leveraging long short-term memory(LLSTM) CICIDS2019 dataset innovative cyberattacks

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A Railway Fastener Inspection Method Based on Abnormal Sample Generation

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Computer Modeling in engineering & sciences 2024年第4期139卷 565-592页

作者： Shubin Zheng Yue Wang Liming Li Xieqi Chen Lele Peng Zhanhao Shang Higher Vocational and Technical College Shanghai University of Engineering ScienceShanghai200437China School of Urban Railway Transportation Shanghai University of Engineering ScienceShanghai201620China Shanghai engineering Research Centre of Vibration and Noise control Technologies for Rail Transit Shanghai University of Engineering ScienceShanghai201620China

Regular fastener detection is necessary to ensure the safety of railways.However,the number of abnormal fasteners is significantly lower than the number of normal fasteners in real railways.Existing supervised inspectionmethods have insufficient detection ability in cases of imbalanced samples.To solve this problem,we propose an approach based on deep convolutional neural networks(DCNNs),which consists of three stages:fastener localization,abnormal fastener sample generation based on saliency detection,and fastener state inspection.First,a lightweight YOLOv5s is designed to achieve fast and precise localization of fastener regions.Then,the foreground clip region of a fastener image is extracted by the designed fastener saliency detection network(F-SDNet),combined with data augmentation to generate a large number of abnormal fastener samples and balance the number of abnormal and normal samples.Finally,a fastener inspection model called Fastener ResNet-8 is constructed by being trained with the augmented fastener dataset.Results show the effectiveness of our proposed method in solving the problem of sample imbalance in fastener detection.Qualitative and quantitative comparisons show that the proposed F-SDNet outperforms other state-of-the-art methods in clip region extraction,reaching MAE and max F-measure of 0.0215 and 0.9635,respectively.In addition,the FPS of the fastener state inspection model reached 86.2,and the average accuracy reached 98.7%on 614 augmented fastener test sets and 99.9%on 7505 real fastener datasets.

关键词： Railway fastener sample generation inspection model deep learning

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Photodegradation of xylene isomers:Kinetics,mechanism,secondary pollutant formation potential and health risk evaluation

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Journal of Environmental sciences 2024年第2期136卷 658-669页

作者： Xiaoyan Chen Weikun Zhu Sufen Feng Jiangyao Chen Guangdong Key Laboratory of Environmental Catalysis and Health Risk control Guangdong Technology Research Center for Photocatalytic Technology Integration and Equipment EngineeringInstitute of Environmental Health and Pollution ControlGuangdong University of TechnologyGuangzhou 510006China Guangzhou Key Laboratory of Environmental Catalysis and Pollution control Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and HealthSchool of Environmental Science and EngineeringGuangdong University of TechnologyGuangzhou 510006China

Photodegradation technology has been widely applied in the purification of industrial aromatic hydrocarbons.However,whether this technology efficiently removes the pollutants to prevent secondary pollution and health risk is still unclear.Here,the photodegradation processes of three xylenes were compared under designed reaction atmospheres and light sources.Xe lamp showed poor photodegradation ability toward xylenes,no matter in N_(2) or N_(2)+O_(2)system,while much higher photodegradation performance of xylenes were obtained under ultraviolet(UV)and vacuum ultraviolet(VUV)irradiation,especially in N_(2)+O_(2)+VUV system,where 97.9%of m-xylene,99.0%of o-xylene or 87.5%of p-xylene with the initial concentration of 860 mg/m^(3) was removed within 240 min.The xylenes underwent three processes of photo-isomerization,photodecomposition and photo-oxidation to produce intermediates of aromatics,alkanes and carbonyls.Among them,the photo-isomerization products showed the highest concentration percentage(e.g.,≥50%in o-xylene system),confirming that photo-isomerization reaction was the dominated photodegradation process of xylenes.Moreover,these isomerized products not only contributed about 97%and91%to the formation potential of O3(OFP)and secondary organic aerosols(SOAFP),but also displayed obvious non-carcinogenic risk,although one of photodecomposition product—benzene showed the highest occupational exposure risk.Therefore,the secondary pollution and health risks of photodegradation products of xylenes were non-ignorable,although the OFP,SOAFP and health risks of the generated products reduced at least 4.5 times in comparison with that of the degraded xylenes.The findings are helpful for the appropriate application of this technology in the purification of industrial organic waste gas.

关键词： Isomer aromatics Photodegradation Ozone formation Secondary organic aerosols Health risk

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