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Advances in Manufacturing 2019年第2期7卷 133-141页

作者： yun-song lian Chen-liang Mu Ming Liu Hui-Feng Chen Bin Yao Department of Mechanical and Electrical Engineering Xiamen University Xiamen 361102 Fujian People's Republic of China

A structural model of a soft/hard compositecoated textured (SHCCT) tool was proposed and substantiated by a three-dimensional numerical simulation. Its dry turning performance as applied to AISI-1045 steel was analyzed via three-factor five-level orthogonal experiments for different coating parameters, including coating thickness, coating material, and thickness ratio of the soft and hard coatings. In addition, the cutting performance of the proposed SHCCT tool was compared with those of uncoated non-textured, coated non?textured, and uncoated textured tools, and its superiority was proved by the significant reductions in the cutting force, and specifically, the cutting temperature. The optimal results were provided by the SHCCT tool with a WS2/ZrN soft/hard composite coating, a 0.9:0.1 thickness ratio of the above ingredients, and a total coating thickness of 0.5 μm.

关键词： Dry cutting performance Soft/hard composite-coated textured (SHCCT) tool Finite element analysis Coating parameters Cemented carbide

XGCN:a library for large-scale graph neural network recommendations

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Frontiers of Computer Science 2024年第3期18卷 247-249页

作者： Xiran song Hong HUANG Jianxun lian Hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Microsoft Research Asia Beijing 100080China

1 Introduction Graph Neural Networks(GNNs)have gained widespread adoption in recommendation systems,and nowadays there is a pressing need to effectively manage large-scale graph data[1].When it comes to large graphs,GNNs may encounter the scalability issue stemming from their multi-layer messagepassing ***,scaling GNNs has emerged as a crucial research area in recent years,with numerous scaling strategies being proposed.

关键词： scaling gained operations

Heuristic Expanding Disconnected Graph:A Rapid Path Planning Method for Mobile Robots

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Chinese Journal of Mechanical Engineering 2024年第2期37卷 68-82页

作者： Yong Tao lian Duan He Gao Yufan Zhang Yian song Tianmiao Wang School of Mechanical Engineering&Automation Beihang UniversityBeijing 100191China Aero-Engine Research Institute Beihang UniversityBeijing 102206China School of Large Aircraft Engineering Beihang UniversityBeijing 100191China

Existing mobile robots mostly use graph search algorithms for path planning,which suffer from relatively low planning efficiency owing to high redundancy and large computational *** to the limitations of the neighborhood search strategy,the robots could hardly obtain the most optimal global path.A global path planning algorithm,denoted as EDG*,is proposed by expanding nodes using a well-designed expanding disconnected graph operator(EDG)in this ***,all obstacles are marked and their corners are located through the map ***,the EDG operator is designed to find points in non-obstruction areas to complete the rapid expansion of disconnected ***,the EDG*heuristic iterative algorithm is *** selects the candidate node through a specific valuation function and realizes the node expansion while avoiding collision with a minimum *** planning experiments were conducted in a typical indoor environment and on the public dataset *** result shows that the proposed EDG*reduced the planning time by more than 90%and total length of paths reduced by more than 4.6%.Compared to A*,Dijkstra and JPS,EDG*does not show an exponential explosion effect in map *** EDG*showed better performance in terms of path smoothness,and collision *** shows that the EDG*algorithm proposed in this paper can improve the efficiency of path planning and enhance path quality.

关键词： Global path planning Mobile robot Expanding disconnected graph Edge node Offset

Comparative analysis of DNA-SIP and magnetic-nanoparticle mediated isolation (MMI) on unraveling dimethoate degraders

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Frontiers of Environmental Science & Engineering 2024年第1期18卷 59-69页

作者： Luning lian Yi Xing Dayi Zhang Longfei Jiang Mengke song Bo Jiang School of Energy and Environmental Engineering University of Science&Technology BeijingBeijing 100083China Beijing Key Laboratory of Resource-oriented Treatment of Industrial Pollutants University of Science&Technology BeijingBeijing 100083China National Environmental and Energy Science and Technology International Cooperation Base University of Science&Technology BeijingBeijing 100083China College of New Energy and Environment Jilin UniversityChangchun 130021China Guangzhou Institute of Geochemistry Chinese Academy of SciencesGuangzhou 510640China College of Natural Resources and Environment South China Agricultural UniversityGuangzhou 510642China National Engineering Laboratory for Site Remediation Technologies Beijing 100015China

Microorganisms are crucial in the bioremediation of organophosphorus pesticides. However, most functional microorganisms (> 99%) are yet to be cultivated. This study applied two cultivation-independent approaches, DNA-SIP and magnetic-nanoparticle mediated isolation (MMI), to identify the functional microorganisms in degrading dimethoate in agricultural soils. MMI identified five dimethoate degraders: Pseudomonas, Bacillus, Ramlibacter, Arthrobacter, and Rhodococcus, whereas DNA-SIP identified three dimethoate degraders: Ramlibacter, Arthrobacter, and Rhodococcus. Also, MMI showed higher resolution than DNA-SIP in identifying functional microorganisms. Two organic phosphohydrolase (OPH) genes: ophC2 and ophB, were involved in dimethoate metabolism, as revealed by DNA-SIP and MMI. The degradation products of dimethoate include omethoate, O,O,S-trimethyl thiophosphorothioate, N-methyl-2-sulfanylacetamide, O,O-diethyl S-hydrogen phosphorodithioate, O,O,O-trimethyl thiophosphate, O,O,S-trimethyl thiophosphorodithioate, and O,O,O-trimethyl phosphoric. This study emphasizes the feasibility of using SIP and MMI to explore the functional dimethoate degraders, expanding our knowledge of microbial resources with cultivation-independent approaches.

关键词： Stable isotope probing(SIP) Magnetic-nanoparticle mediated isolation(MMI) Dimethoate Biodegradation Cultivation-independent approach

Classification of musical hallucinations and the characters along with neural-molecular mechanisms of musical hallucinations associated with psychiatric disorders

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World Journal of Psychiatry 2024年第9期14卷 1386-1396页

作者： Xin lian Wei song Tian-Mei Si Naomi Zheng lian Department of Radiology and Biomedical Imaging Shanxi Bethune HospitalShanxi Academy of Medical SciencesTaiyuan 030032Shanxi ProvinceChina Department of Psychiatry and Behavioral Neurosciences McMaster UniversityHamilton L8S 4L8ONCanada Department of Psychopharmacology Peking University Sixth HospitalBeijing 100191China Department of Psychiatry Hartford HealthCareSt Vincent’s Medical CenterWestportCT 06088United States

BACKGROUND Musical hallucinations(MH)involve the false perception of music in the absence of external stimuli which links with different *** pathomechanisms of MH encompass various *** etiological classification of MH is of particular importance and offers valuable insights to understand MH,and further to develop the effective treatment of *** the recent decades,more MH cases have been reported,revealing newly identified medical and psychiatric causes of *** imaging studies reveal that MH activates a wide array of brain *** up-to-date analysis on MH,especially on MH comorbid psychiatric conditions is *** To propose a new classification of MH;to study the age and gender differences of MH in mental disorders;and neuropathology of *** Literatures searches were conducted using keywords such as“music hallucination,”“music hallucination and mental illness,”“music hallucination and gender difference,”and“music hallucination and psychiatric disease”in the databases of PubMed,Google Scholar,and Web of *** cases were collected and categorized based on their *** t-test and ANOVA were employed(P<0.05)to compare the age differences of MH different etiological *** neuroimaging studies of neural networks regulating MH and their possible molecular mechanisms were *** Among the 357 yielded publications,294 MH cases were *** average age of MH cases was 67.9 years,with a predominance of females(66.8%females vs 33.2%males).MH was classified into eight groups based on their etiological *** analysis of MH cases indicates varying associations with psychiatric *** We carried out a more comprehensive review of MH *** the first time according to our knowledge,we demonstrated the psychiatric conditions linked and/or associated with MH from statistical,biological and molecular point of view.

关键词： Pathomechanism Etiological factors Classification Gender difference Neuropathway Psychotic musical hallucination and non-psychotic musical hallucination Neuropathway Biological and molecular mechanism

Determination of ice jam thickness—A new approach

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Journal of Hydrodynamics 2024年第3期36卷 570-581页

作者： Jun Wang lian-sheng Sang Fei-hu song Tie-jie Cheng Jueyi Sui School of Civil and Water Engineering Hefei University of TechnologyHefei230009China School of Engineering University of Northern British ColumbiaPrince GeorgeCanada

In winter,rivers in cold regions often experience flood disasters resulted from ice jams or ice *** of the variation of ice jam thickness and water level during an ice jammed period are not only a practical need for ice prevention to avoid disaster and plan water resource,but also essential for the development of any mathematical model for predicting the evolution of ice *** far,some equations based on the energy equation have been proposed to describe the relationship between ice jam thickness and water ***,in the derivation of these equations,the local head loss coefficient at the ice jam head and the riverbed slope factor were ***,those reported equations cannot be used to preciously describe the flow energy equation with ice jams and accurately calculate the ice jam thickness and water *** the present study,a more comprehensive theoretical model for hydraulic calculation of ice jam thickness has been derived by considering important and essential factors including riverbed slope and local head loss coefficient at the ice jam ***,based on the data collected from laboratory experiments of ice jam accumulation,the local head loss coefficient at the ice jam head has been calculated,and the empirical equation for calculating the local head loss coefficient has been established by considering flow Froude number and the ratio of ice discharge to flow *** results of this study not only provide a new reference for calculating ice jam thickness and water level,but also present a theoretical basis for accurate CFD simulation of ice jams.

关键词： Energy equation ice jam thickness local head loss coefficient ice jam head riverbed slope

A Novel Fracturing Fluid with High-Temperature Resistance for Ultra-Deep Reservoirs

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Fluid Dynamics & Materials Processing 2024年第5期20卷 975-987页

作者： lian Liu liang Li Kebo Jiao Junwei Fang yun Luo Northwest Oilfield Branch China Petroleum&Chemical CorporationUrumqi830011China Sinopec Key Laboratory for Enhanced Recovery in Fractured and Cavernous Reservoir Urumqi830011China

Ultra-deep reservoirs play an important role at present in fossil energy *** to the related high temperature,high pressure,and high formation fracture pressure,however,methods for oil well stimulation do not produce satisfactory results when conventional fracturing fluids with a low pumping rate are *** response to the above problem,a fracturing fluid with a density of 1.2~1.4 g/cm^(3)was developed by using Potassium formatted,hydroxypropyl guanidine gum and zirconium crosslinking *** fracturing fluid was tested and its ability to maintain a viscosity of 100 mPa.s over more than 60 min was verified under a shear rate of 1701/s and at a temperature of 175℃.This fluid has good sand-carrying performances,a low viscosity after breaking the rubber,and the residue content is less than 200 mg/*** with ordinary reconstruction fluid,it can increase the density by 30%~40%and reduce the wellhead pressure of 8000 m level reconstruction ***,the new fracturing fluid can significantly mitigate safety risks.

关键词： Ultra-deep reservoir high-temperature resistance weighted fracturing fluid guanidine gum potassium formatted

Software Defect Prediction Method Based on Stable Learning

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Computers, Materials & Continua 2024年第1期78卷 65-84页

作者： Xin Fan Jingen Mao liangjue lian Li Yu Wei Zheng yun Ge College of Aerospace Engineering Nanjing University of Aeronautics and AstronauticsNanjing210012China School of Software Nanchang Hangkong UniversityNanchang330029China Software Testing and Evaluation Center Nanchang Hangkong UniversityNanchang330029China

The purpose of software defect prediction is to identify defect-prone code modules to assist software quality assurance teams with the appropriate allocation of resources and *** previous software defect prediction studies,transfer learning was effective in solving the problem of inconsistent project data ***,target projects often lack sufficient data,which affects the performance of the transfer learning *** addition,the presence of uncorrelated features between projects can decrease the prediction accuracy of the transfer learning *** address these problems,this article propose a software defect prediction method based on stable learning(SDP-SL)that combines code visualization techniques and residual *** method first transforms code files into code images using code visualization techniques and then constructs a defect prediction model based on these code *** the model training process,target project data are not required as prior *** the principles of stable learning,this paper dynamically adjusted the weights of source project samples to eliminate dependencies between features,thereby capturing the“invariance mechanism”within the *** approach explores the genuine relationship between code defect features and labels,thereby enhancing defect prediction *** evaluate the performance of SDP-SL,this article conducted comparative experiments on 10 open-source projects in the PROMISE *** experimental results demonstrated that in terms of the F-measure,the proposed SDP-SL method outperformed other within-project defect prediction methods by 2.11%-44.03%.In cross-project defect prediction,the SDP-SL method provided an improvement of 5.89%-25.46% in prediction performance compared to other cross-project defect prediction ***,SDP-SL can effectively enhance within-and cross-project defect predictions.

关键词： Software defect prediction code visualization stable learning sample reweight residual network

Engineering g-C_(3)N_(4)based materials for advanced photocatalysis:Recent advances

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Green Energy & Environment 2024年第2期9卷 166-197页

作者： Xin-lian song Lei Chen Li-Jiao Gao Jin-Tao Ren Zhong-Yong Yuan National Institute for Advanced Materials School of Materials Science and EngineeringSmart Sensing Interdisciplinary Science CenterNankai UniversityTianjin300350China Key Laboratory of Advanced Energy Materials Chemistry(Ministry of Education) Nankai UniversityTianjin300071China

Photocatalysis driven by abundant yet intermittent solar energy has considerable potential in renewable energy generation and environmental *** outstanding electronic structure and physicochemical properties of graphitic carbon nitride(g-C_(3)N_(4)),together with unique metal-free characteristic,make them ideal candidates for advanced photocatalysts *** review summarizes the up-to-date advances on g-C_(3)N_(4)based photocatalysts from ingenious-design strategies and diversified photocatalytic ***,the advantages,fabrication methods and limitations of each design strategy are systemically *** order to deeply comprehend the inner connection of theory–structure–performance upon g-C_(3)N_(4)based photocatalysts,structure/composition designs,corresponding photocatalytic activities and reaction mechanisms are jointly discussed,associated with introducing their photocatalytic applications toward water splitting,carbon dioxide/nitrogen reduction and pollutants degradation,***,the current challenges and future perspectives for g-C_(3)N_(4)based materials for photocatalysis are briefly *** design strategies and limitations are also instructive for constructing g-C_(3)N_(4) based materials in other energy and environment-related applications.

关键词： Graphitic carbon nitride g-C_(3)N_(4) Design strategies Photocatalysis Photocatalysts Reaction mechanism

Identification of carbonate sedimentary facies from well logs with machine learning Author links open overlay panel

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Petroleum Research 2024年第2期9卷 165-175页

作者： Xianmu Hou Peiqing lian Jiuyu Zhao yun Zai Weiyao Zhu Fuyong Wang School of Civil and Resources Engineering University of Science and Technology BeijingBeijing100083China Sinopec Chongqing Fuling Shale Gas Exploration and Development Co. Ltd.Chongqing408000China Sinopec Petroleum Exploration&Production Research Institute SINOPECBeijing100083China National Key Laboratory of Petroleum Resources and Engineering China University of Petroleum(Beijing)Beijing102249China ChinKunlun Digital Technology Co.Ltd. Beijing102206China

Sedimentary facies identification is critical for carbonate oil and gas reservoir *** traditional method of sedimentary facies identification not only be affected by the engineer's experience but also takes a long *** carbonate sedimentary facies based on machine learning is the trend of future development and has the advantages of short time consuming and reliable results without engineers'subjective *** many references reported the application of machine learning to identify lithofacies,but identifying sedimentary facies of carbonate reservoirs is much more challenging due to the complex sedimentary environment and tectonic *** paper compares the performance of the carbonate sedimentary facies identification using four different machine learning models,and the optimal machine learning with the highest prediction accuracy is ***,the carbonate sedimentary facies are classified into the lagoon,shallow sea,shoal,fore-shoal,and inter-shoal five tags based on the well ***,five well log curves including spectral gamma ray(SGR),uranium-free gamma ray(CGR),photoelectric absorption cross-section index(PE),true formation resistivity(RT),shallow lateral resistivity(RS)are used as the input,and the manual identified carbonate sedimentary facies are used as the output of the machine learning *** performance of four different machine learning algorithms,including support vector machine(SVM),deep neural network(DNN),long short-term memory(LSTM)network,and random forest(RF)are *** other two wells are used for model *** research results show that the RF method has the highest accuracy of sedimentary facies prediction,and the average prediction accuracy is 78.81%;the average accuracy of sedimentary facies prediction using SVM is 77.93%.The sedimentary facies predictions using DNN and LSTM are less satisfying compared with RF and SVM,and the average accuracy is 69.94%and 73.05%,respect

关键词： Carbonate Sedimentary facies Well logs Machine learning Deep learning