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The Multi-parameter Test of Gravitational Wave Dispersion with Principal Component Analysis

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Research in Astronomy and Astrophysics 2024年第5期24卷 140-150页

作者： zhi-Chu Ma Rui niu Wen Zhao CAS Key Laboratory for Research in Galaxies and Cosmology Department of AstronomyUniversity of Science and Technology of ChinaHefei 230026China School of Astronomy and Space Sciences University of Science and Technology of ChinaHefei 230026China

In this work, we consider a conventional test of gravitational wave(GW) propagation which is based on the phenomenological parameterized dispersion relation to describe potential departures from General Relativity(GR)along the propagation of GWs. But different from tests conventionally performed previously, we vary multiple deformation coefficients simultaneously and employ the principal component analysis(PCA) method to remedy the strong degeneracy among deformation coefficients and obtain informative posteriors. The dominant PCA components can be better measured and constrained, and thus are expected to be more sensitive to potential departures from the waveform model. Using this method we analyze ten selected events and get the result that the combined posteriors of the dominant PCA parameters are consistent with GR within 99.7% credible intervals. The standard deviation of the first dominant PCA parameter is three times smaller than that of the original dispersion parameter of the leading order. However, the multi-parameter test with PCA is more sensitive to not only potential deviations from GR but also systematic errors of waveform models. The difference in results obtained by using different waveform templates hints that the demands of waveform accuracy are higher to perform the multiparameter test with PCA. Whereas, it cannot be strictly proven that the deviation is indeed and only induced by systematic errors. It requires more thorough research in the future to exclude other possible reasons in parameter estimation and data processing.

关键词： gravitational waves-gravitation-black hole physics

Smart Cutting Tools and Smart Machining: Development Approaches, and Their Implementation and Application Perspectives

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Chinese Journal of Mechanical Engineering 2017年第5期30卷 1162-1176页

作者： Kai Cheng zhi-chao niu Robin C.Wang Richard Rakowski Richard Bateman College of Engineering Design and Physical SciencesBrunel University London

Smart machining has tremendous potential and is becoming one of new generation high value precision manufacturing technologies in line with the advance of Industry 4.0 concepts. This paper presents some innovative design concepts and, in particular, the development of four types of smart cutting tools, including a force-based smart cutting tool, a temperature-based internally-cooled cutting tool, a fast tool servo （FTS） and smart collets for ultra- precision and micro manufacturing purposes. Implemen- tation and application perspectives of these smart cutting tools are explored and discussed particularly for smart machining against a number of industrial application requirements. They are contamination-free machining, machining of tool-wear-prone Si-based infra-red devices and medical applications, high speed micro milling and micro drilling, etc. Furthermore, implementation tech- niques are presented focusing on：（a） plug-and-produce design principle and the associated smart control algo- rithms, （b） piezoelectric film and surface acoustic wave transducers to measure cutting forces in process, （c） critical cutting temperature control in real-time machining, （d） in- process calibration through machining trials, （e） FE-based design and analysis of smart cutting tools, and （f） applica- tion exemplars on adaptive smart machining.

关键词： Smart cutting tool Smart machining Fast toolservo (FFS) Precision machining Micro manufacturing Smart tooling

An advanced 2D/3D g-C_(3)N_(4)/TiO_(2)@MnO_(2) multifunctional membrane for sunlight-driven sustainable water purification

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Nano Research 2024年第4期17卷 2368-2380页

作者： Fan Yu Chunjia Luo Xiaohan niu Min chao Pengfei Zhang Luke Yan Polymer Materials&Engineering Department School of Materials Science&EngineeringChang’an UniversityXi’an 710064China Key Laboratory of Road Construction Technology and Equipment MOEChang’an UniversityXi’an 710064China School of Textile Science and Engineering Xi’an Polytechnic UniversityXi’an 710064China

Graphitic carbon nitride(g-C_(3)N_(4))nanosheets have attracted widespread interest in the construction of advanced separation ***,dense stacking and a single functionality have limited the membrane ***,an advanced two-/three-dimensional(2D/3D)g-C_(3)N_(4)/TiO_(2)@MnO_(2) membrane is constructed by intercalating 3D TiO_(2)@MnO_(2) nanostructures into g-C_(3)N_(4) *** 3D flower-like nanostructures broaden the transport channels of the composite *** membrane can effectively separate five oil-in-water(O/W)emulsions,with a maximum flux of 3265.67±15.01 L·m^(-2)·h^(-1)·bar^(-1) and a maximum efficiency of 99.69%±0.45%for toluene-in-water emulsion(T/W).Meanwhile,the TiO_(2)@MnO_(2) acts as an excellent electron acceptor and provides positive spatial separation of electrons–holes(e^(-)–h^(+)).The formation of 2D/3D heterojunctions allows the material with wider light absorption and smaller bandgap(2.10 eV).These photoelectric properties give the membrane good degradation of three different pollutants,with about 100%degradation for methylene blue(MB)and malachite green(MG).The photocatalytic antibacterial efficiency of the membrane is also about 100%.After cyclic experiment,the membrane maintains its original separation and photocatalytic *** remarkable multifunctional and self-cleaning properties of the g-C_(3)N_(4) based membrane represent its potential value for complex wastewater treatment.

关键词： graphitic carbon nitride(g-C_(3)N_(4))based membrane three-dimensional(3D)nanostructures self-cleaning multifunction

A survey on the network models applied in the industrial network optimization

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Science China(Information Sciences) 2024年第2期67卷 85-103页

作者： chao DONG Xiaoxiong XIONG Qiulin XUE Zhengzhen ZHANG Kai niu Ping ZHANG Key Laboratory of Universal Wireless Communications Ministry of EducationBeijing University of Posts and Telecommunications Smart City College Beijing Union University

Network architecture design is critical for optimizing industrial networks. Network architectures can be classified into small-scale networks and large-scale networks based on scale. Graph theory is an efficient mathematical tool for network topology modeling. For small-scale networks, their structure often has regular topology. For large-scale ones, the current body of work mainly focuses on random characteristics of network nodes and edges. Recently, widely used models include random networks, small-world networks,and scale-free networks. In this study, starting from the scale of the network, network modeling methods based on graph theory as well as their industrial applications, are summarized and analyzed. Moreover, a novel network performance metric, called system entropy, is proposed. From the perspective of mathematical properties, an analysis of its non-negativity and concavity is performed. The advantage of system entropy is that it can cover the existing regular networks, random networks, small-world networks, and scale-free networks, and has strong generality. The simulation results reveal that this proposed metric can achieve the comparison of various industrial networks under different models.

关键词： industrial network small-scale network large-scale network graph theory system entropy

Patterns and drivers of avian taxonomic and phylogenetic beta diversity in China vary across geographical backgrounds and dispersal abilities

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Zoological Research 2024年第1期45卷 125-135页

作者： Jian-chao Liang zhi-Feng Ding Chun-Lin Li Yi-Ming Hu zhi-Xin Zhou Gan-Wen Lie Xiao-Nan niu Wen-Bin Huang Hui-Jian Hu Xing-Feng Si Guangdong Key Laboratory of Animal Conservation and Resource Utilization Guangdong Public Laboratory of Wild Animal Conservation and UtilizationInstitute of ZoologyGuangdong Academy of SciencesGuangzhouGuangdong 510260China School of Resources and Environmental Engineering Anhui UniversityHefeiAnhui 230601China Guangdong Eco-Engineering Polytechnic GuangzhouGuangdong 510520China Huizhou Institute of Forestry(Huizhou Botanical Garden Management Service Center) HuizhouGuangdong 516001China Administration of National Nature Reserve for Marine Ecology of Guangdong Nanpeng Islands ShantouGuangdong 515900China Zhejiang Zhoushan Archipelago Observation and Research Station Institute of Eco-ChongmingZhejiang Tiantong Forest Ecosystem National Observation and Research StationSchool of Ecological and Environmental SciencesEast China Normal UniversityShanghai 200241China

Geographical background and dispersal ability may strongly influence assemblage dissimilarity;however,these aspects have generally been overlooked in previous large-scale beta diversity ***,we examined whether the patterns and drivers of taxonomic beta diversity(TBD)and phylogenetic beta diversity(PBD)of breeding birds in China vary across(1)regions on both sides of the Hu Line,which demarcates China’s topographical,climatic,economic,and social patterns,and(2)species with different dispersal *** and PBD were calculated and partitioned into turnover and nestedness components using a moving window *** representing climate,habitat heterogeneity,and habitat quality were employed to evaluate the effects of environmental *** distance was considered to assess the impact of dispersal *** partitioning analysis was applied to assess the relative roles of these *** general,the values of TBD and PBD were high in mountainous areas and were largely determined by environmental ***,different dominant environmental filters on either side of the Hu Line led to divergent beta diversity ***,climate-driven species turnover and habitat heterogeneity-related species nestedness dominated the regions east and west of the line,***,bird species with stronger dispersal ability were more susceptible to environmental filtering,resulting in more homogeneous *** results indicated that regions with distinctive geographical backgrounds may present different ecological factors that lead to divergent assemblage dissimilarity patterns,and dispersal ability determines the response of assemblages to these ecological *** a single universal explanation for the observed pattern without considering these aspects may lead to simplistic or incomplete ***,a comprehensive understanding of large-scale beta diversity patterns and effective pla

关键词： Beta diversity Environmental filtering Dispersal limitation Hu Line Species dispersal ability Breeding birds

Green synthesis of luminescent La-MOF nanoparticle from waste poly(ethylene terephthalate) for high-performance in Fe(Ⅲ) detection

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Rare Metals 2024年第8期43卷 3833-3843页

作者： zhi Gong zhi-Kui Dai zhi-Yue Dong Qiu-Xuan Liu Valentin A.Milichko Hua-Jian Liu Jie Liu Ran niu Jiang Gong Key Laboratory of Material Chemistry for Energy Conversion and Storage Hubei Key Laboratory of Material Chemistry and Service FailureHubei Engineering Research Center for Biomaterials and Medical Protective MaterialsSemiconductor Chemistry CenterSchool of Chemistry and Chemical EngineeringMinistry of EducationHuazhong University of Science and TechnologyWuhan 430074China School of Chemical Engineering and Pharmacy Wuhan Institute of TechnologyWuhan 430073China Collaborative Innovation Center for Advanced Organic Chemical Materials Co-constructed by the Province and Ministry Ministry of Education Key Laboratory for the Synthesis and Application of Organic Functional Molecules and College of Chemistry and Chemical EngineeringHubei UniversityWuhan 430062China School of Physics and Engineering ITMO UniversitySt.Petersburg197101Russia School of Materials Science and Engineering Hubei UniversityWuhan430062China Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing School of Mechanical and Automotive EngineeringKey Laboratory of Polymer Processing EngineeringMinistry of EducationSouth China University of TechnologyGuangzhou 510641China

Developing luminescent metal-organic frameworks(MOFs) capable of high-efficiency Fe^(3+)sensing has aroused great attraction in the fields of biology,chemistry,***,previous solvothermal methods are limited by organic solvent usage,time consuming,high pressure,and high-energy ***,we propose the waste-toMOF strategy towards the scale-up production of La-MOF nanoparticles through the ball milling of recycled poly(-ethylene terephthalate)(PET) bottles and La(NO_(3))_(3)·_(6)H_(2)*** goes on alkaline hydrolysis to form 1,4-benzenedicarboxylic acid sodium salt(Na_(2)BDC) and ethylene glycol by ball ***,BDC reacts with La^(3+)to form *** as-prepared La-MOF crystal nanoparticles possess a rod-like morphology with the size of few hundred ***,La-MOF nanoparticles display high selectivity and sensitivity for Fe^(3+)*** quenching constant and limit of detection are 5.29×10^(3)(mol·L^(-1))^(-1) and 0.147 μmol·L^(-1),respectively,thus surpassing many advanced Fe^(3+) *** to the result of density functional theory,the high Fe^(3+) detection performance of La-MOF is related to the complexing of Fe^(3+)with La-MOF,which leads to the gradual dissociation of the coordination bond between terephthalic acid and La^(3+).It is anticipated that the mechanochemistry milling-based wasteto-MOF strategy provides a new platform for the massive production of functional MOFs in a green manner.

关键词： Metal-organic framework Waste polyester Mechanochemistry milling Fluorescence sensor

A data-driven approach to RUL prediction of tools

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Advances in Manufacturing 2024年第1期12卷 6-18页

作者： Wei Li Liang-Chi Zhang Chu-Han Wu Yan Wang Zhen-Xiang Cui chao niu Department of Mechanical Engineering University College LondonLondonWC1E 7JEUK Shenzhen Key Laboratory of Cross-Scale Manufacturing Mechanics Southern University of Science and TechnologyShenzhen518055GuangdongPeople’s Republic of China SUSTech Institute for Manufacturing Innovation Southern University of Science and TechnologyShenzhen518055GuangdongPeople’s Republic of China Department of Mechanics and Aerospace Engineering Southern University of Science and TechnologyShenzhen518055GuangdongPeople’s Republic of China School of Mechanical and Manufacturing Engineering The University of New South WalesKensingtonNSW2052Australia Baoshan Iron&Steel Co. Ltd.Shanghai200941People’s Republic of China

An effective and reliable prediction of the remaining useful life(RUL)of a tool is important to a metal forming process because it can significantly reduce unexpected maintenance,avoid machine shutdowns and increase system *** study proposes a new data-driven approach to the RUL prediction for metal forming processes under multiple contact sliding *** data-driven approach took advantage of bidirectional long short-term memory(BLSTM)and convolutional neural networks(CNN).A pre-trained lightweight CNN-based network,WearNet,was re-trained to classify the wear states of workpiece surfaces with a high accuracy,then the classification results were passed into a BLSTM-based regression model as inputs for RUL *** experimental results demonstrated that this approach was able to predict the RUL values with a small error(below 5%)and a low root mean square error(RMSE)(around 1.5),which was more superior and robust than the other state-of-the-art methods.

关键词： Remaining useful life(RUL) Bidirectional long short-term memory(BLSTM) Data-driven approach Metal forming

Pathogenic Surveillance of Foodborne Illness-Related Diarrhea—Beijing Municipality,China,2013-2023

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China CDC weekly 2024年第24期6卷 568-573页

作者： chao Wang Tongyu Wang Yanlin niu Yangbo Wu Jinru Jiang Xiaochen Ma Institute for Nutrition and Food Hygiene Beijing Center for Disease Prevention and ControlBeijingChina

Summary What is already known about this topic?Foodborne diseases present a significant public health concern,particularly in China,where they represent a significant food safety ***,there is a need for a thorough and systematic analysis of the extended epidemiological patterns of foodborne diseases in Beijing *** is added by this report?

关键词： Beijing safety borne

Application of machine learning models in groundwater quality assessment and prediction:progress and challenges

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Frontiers of Environmental Science & Engineering 2024年第3期18卷 25-55页

作者： Yanpeng Huang chao Wang Yuanhao Wang Guangfeng Lyu Sijie Lin Weijiang Liu Haobo niu Qing Hu School of Environment Harbin Institute of TechnologyHarbin 150090China School of Environmental Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Engineering Innovation Center of SUSTech(Beijing) Southern University of Science and TechnologyBeijing 100083China Technical Center for Soil Agriculture and Rural Ecology and EnvironmentMinistry of Ecology and EnvironmentBeijing 100012China Chinese Academy of Environmental Planning Beijing 100043China

Groundwater quality assessment and prediction(GQAP)is vital for protecting groundwater *** GQAP methods can not adequately capture the complex relationships among attributes and have the disadvantage of being computationally ***,the application of machine learning(ML)in GAQP(GQAPxML)has been widely studied due to ML’s reliability and *** many GQAPxML publications exist,a thorough review is *** review provides a comprehensive summary of the development of ML applications in the field of ***,the workflow of ML modeling is briefly introduced,as are data preparation,model development,model evaluation,and model ***,299 publications related to the topic are filtered,mainly through ML ***,many aspects of GQAPxML,such as publication trends,the spatial distribution of study areas,the size of data sets,and ML algorithms,are discussed from a bibliometric *** addition,we review in detail the well-established applications and recent findings for several subtopics,including groundwater quality assessment,groundwater quality modeling using groundwater quality parameters,groundwater quality spatial mapping,probability estimation of exceeding the groundwater quality threshold,groundwater quality temporal prediction,and the hybrid use of ML and physics-based ***,the development of GQAPxML is explored from three perspectives:data collection and preprocessing,model building and evaluation,and the broadening of model *** review provides a reference for environmental scientists to better understand GQAPxML and promotes the development of innovative methods and improvements in modeling quality.

关键词： Groundwater quality assessment Groundwater quality prediction Machine learning Groundwater modeling