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Cluster DetectionMethod of Endogenous Security Abnormal Attack Behavior in Air Traffic Control Network

Computers, Materials & Continua 2024年第5期79卷 2523-2546页

作者： Ruchun Jia Jianwei Zhang yi lin Yunxiang han Feike Yang College of Computer Science Sichuan UniversityChengdu610065China Equipment Management and Unmanned Aerial Vehicle College of Air Force Engineering University Air Force Engineering UniversityXi’an710051China

In order to enhance the accuracy of Air Traffic Control(ATC)cybersecurity attack detection,in this paper,a new clustering detection method is designed for air traffic control network security attacks.The feature set for ATC cybersecurity attacks is constructed by setting the feature states,adding recursive features,and determining the feature criticality.The expected information gain and entropy of the feature data are computed to determine the information gain of the feature data and reduce the interference of similar feature data.An autoencoder is introduced into the AI(artificial intelligence)algorithm to encode and decode the characteristics of ATC network security attack behavior to reduce the dimensionality of the ATC network security attack behavior data.Based on the above processing,an unsupervised learning algorithm for clustering detection of ATC network security attacks is designed.First,determine the distance between the clustering clusters of ATC network security attack behavior characteristics,calculate the clustering threshold,and construct the initial clustering center.Then,the new average value of all feature objects in each cluster is recalculated as the new cluster center.Second,it traverses all objects in a cluster of ATC network security attack behavior feature data.Finally,the cluster detection of ATC network security attack behavior is completed by the computation of objective functions.The experiment took three groups of experimental attack behavior data sets as the test object,and took the detection rate,false detection rate and recall rate as the test indicators,and selected three similar methods for comparative test.The experimental results show that the detection rate of this method is about 98%,the false positive rate is below 1%,and the recall rate is above 97%.Research shows that this method can improve the detection performance of security attacks in air traffic control network.

关键词： Air traffic control network security attack behavior cluster detection behavioral characteristics information gain cluster threshold automatic encoder

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A homopolymolybdate-supported plate-like 2D cobalt network constructed from a new pyrazole-amide-pyridyl ligand: highly electrochemical activity in both capacitive performance and the detection of Cr(Ⅵ)

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Tungsten 2024年第2期6卷 422-427页

作者： Xiu-Li Wang Yong-Zhen Chen Zhi-han Chang Yu-Chun lin Jing-yi Ma College of Chemistry and Materials Engineering Bohai UniversityJinzhou 121013China Professional Technology Innovation Center of Liaoning Province for Conversion Materials of Solar Cell Jinzhou 121013China

By employing a new semi-rigid pyrazole-amide-derived bis(pyridyl)ligand[N,N'-bis(4-picolylamine)-1-hydropyrazole(4-dpap)],a new homopolymolybdate-based two-dimensional(2D)plate-like complex[Co(4-dpap)(H_(2)O)(β-Mo_(8)O_(2)6)1/2](1)has been prepared under solvothermal condition and structurally characterized.Theβ-Mo_(8)anions are fi xed between the 2D metal–organic networks[Co(4-dpap)(H_(2)O)]n 2n+via hydrogen-bonding interaction.Complex 1 possesses satisfactory specifi c capacitance of 1512.4 F·g^(−1)(current density:1 A·g^(−1))and good cycling stability(90.8%after 1000 cycles).Moreover,1 represents a promising amperometric sensor for measurement of Cr(Ⅵ)with low detection limit(0.042μmol·L^(−1))and high durability.The insertion ofβ-Mo_(8)anions between the unique 2D metal−organic networks improves the active area of polyoxometalates,which further promotes electrochemical performance.

关键词： Homopolymolybdate Metal–organic network Pyrazole-amide-derived bis(pyridyl)ligand Supercapacitor Electrochemical sensor

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Crystal phase control and ignition properties of HNS/CL-20 composite microspheres prepared by microfluidics combined with emulsification techniques

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Particuology 2024年第2期85卷 241-251页

作者： yi Liu Yunyan Guo Rui Zhu Jinqiang Zhou Zhengxu lin Kai han Chongwei An Jingyu Wang Bidong Wu School of Environment and Safety Engineering North University of ChinaTaiyuan030051China School of Engineering Beijing Institute of TechnologyBeijing100081China Shanxi Province Ultrafine Powder Engineering Technology Research Center Taiyuan030051China

Improved controllability and energy density of ignition agents are of great significance for the devel-opment of energetic composite materials.In this study,droplet microfluidics and emulsification tech-niques were combined to prepare HNS/CL-20 composite microspheres with polyglycidyl azide polymer(GAP)as the binder.The influence of binder content on the morphology of microspheres was investi-gated,and the microspheres were characterized and tested for particle size,crystal structure,thermal decomposition,dispersibility,mechanical sensitivity,combustion behavior and detonation performance.The results showed that microspheres prepared with a binder content of 3%had higher sphericity and particle size uniformity.The microspheres retained the crystal structure of both HNS and CL-20(ε-type).Compared with raw HNS,the microspheres had higher apparent activation energy,better safety per-formance,and good dispersibility.The ignition experiments and detonation performance tests show that HNS/CL-20 composite microspheres have excellent ignition performance,obvious combustion flame,and significant energy release effects,which are expected to achieve high energy and high-speed response of the igniter,thus improving the ignition reliability in special environments or systems.

关键词： Droplet microfluidics Emulsification technology Energetic materials Composite microspheres Crystal phase control Ignition

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TSC prediction and dynamic control of BOF steelmaking with state-of-the-art machine learning and deep learning methods

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Journal of Iron and Steel Research(International) 2024年第1期31卷 174-194页

作者： Tian-yi Xie Cai-dong Zhang Quan-lin Zhou Zhi-qiang Tian Shuai Liu han-jie Guo Material Technology Research Institute Hesteel GroupShijiazhuang050023HebeiChina Tangsteel Company Hesteel GroupTangshan063611HebeiChina School of Artificial Intelligence Beijing Technology and Business UniversityBeijing100048China School of Metallurgical and Ecological Engineering University of Science and Technology BeijingBeijing100083China

Mathematical(data-driven)models based on state-of-the-art(SOTA)machine learning and deep learning models and data collected from 12,786 heats were established to predict the values of temperature,sample,and carbon(TSC)test,including temperature of molten steel(TSC-Temp),carbon content(TSC-C)and phosphorus content(TSC-P),which made prepa-ration for eliminating the TSC test.To maximize the prediction accuracy of the proposed approach,various models with different inputs were implemented and compared,and the best models were applied to the production process of a Hesteel Group steelmaking plant in China in the field.The number of tabular features(hot metal information,scrap,additives,blowing practices,and preset values)was expanded,and time series(off-gas profiles and blowing practice curves)that could reflect the entire steelmaking process were introduced as inputs.First,the latest machine learning models(LightGBM,CatBoost,TabNet,and NODE)were used to make predictions with tabular features,and the best coefficient of determination R^(2)values obtained for TSC-P,TSC-C and TSC-Temp predictions were 0.435(LightGBM),0.857(Cat-Boost)and 0.678(LightGBM),respectively,which were higher than those of classic models(backpropagation and support vector machine).Then,making predictions was performed by using SOTA time series regression models(SCINet,Dlinear,Informer,and MLSTM-FCN)with original time series,SOTA image regression models(NesT,CaiT,ResNeXt,and GoogLeNet)with resized time series,and the proposed Concatenate-Model and Parallel-Model with both tabular features and time series.Through optimization and comparisons,it was finally determined that the Concatenate-Model with MLSTM-FCN,SCINet and Informer as feature extractors performed the best,and its R^(2)values for predicting TSC-P,TSC-C and TSC-Temp reached 0.470,0.858 and 0.710,respectively.Its field test accuracies for TSC-P,TSC-C and TSC-Temp were 0.459,0.850 and 0.685,respectively.A related importance analysis was carried out,and dynamic control methods based on pred

关键词： BOF steelmaking In-blow prediction TSC test Machine learning Deep learning Field application

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Study on the optimal incident proton energy of ^(7)Li(p,n)^(7)Be neutron source for boron neutron capture therapy

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Nuclear Science and Techniques 2024年第3期35卷 170-180页

作者： yi-Nan Zhu Zuo-Kang lin Hai-Yan Yu Ye Dai Zhi-Min Dai Xiao-han Yu Shanghai Institute of Applied Physics Chinese Academy of SciencesShanghai 201800China University of Chinese Academy of Science Beijing 100049China

Boron neutron capture therapy(BNCT)is recognized as a precise binary targeted radiotherapy technique that effectively eliminates tumors through the^(10)B(n,α)^(7)Li nuclear reaction.Among various neutron sources,accelerator-based sources have emerged as particularly promising for BNCT applications.The^(7)Li(p,n)^(7)Be reaction is highly regarded as a potential neutron source for BNCT,owing to its low threshold energy for the reaction,significant neutron yield,appropriate average neutron energy,and additional benefits.This study utilized Monte Carlo simulations to model the physical interactions within a lithium target subjected to proton bombardment,including neutron moderation by an MgF_(2)moderator and subsequent BNCT dose analysis using a Snyder head phantom.The study focused on calculating the yields of epithermal neutrons for various incident proton energies,finding an optimal energy at 2.7 MeV.Furthermore,the Snyder head phantom was employed in dose simulations to validate the effectiveness of this specific incident energy when utilizing a^(7)Li(p,n)^(7)Be neutron source for BNCT purposes.

关键词： Boron neutron capture therapy ^(7)Li(p,n)7Be neutron source Incident proton energy Monte Carlo simulation

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Development and validation of a prediction model for early screening of people at high risk for colorectal cancer

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World Journal of Gastroenterology 2024年第5期30卷 450-461页

作者： ling-Li Xu yi lin Li-Yuan han Yue Wang Jian-Jiong Li Xiao-Yu Dai Department of General Surgery Ningbo No.2 HospitalNingbo 315000Zhejiang ProvinceChina Center for Health Economics Faculty of Humanities and Social SciencesUniversity of NottinghamNingbo 315100Zhejiang ProvinceChina Department of Global Health Ningbo Institute of Life and Health IndustryUniversity of Chinese Academy of SciencesNingbo 315000Zhejiang ProvinceChina School of Public Health Medical College of Soochow UniversitySuzhou 215123Jiangsu ProvinceChina

BACKGROUND Colorectal cancer(CRC)is a serious threat worldwide.Although early screening is suggested to be the most effective method to prevent and control CRC,the current situation of early screening for CRC is still not optimistic.In China,the incidence of CRC in the Yangtze River Delta region is increasing dramatically,but few studies have been conducted.Therefore,it is necessary to develop a simple and efficient early screening model for CRC.AIM To develop and validate an early-screening nomogram model to identify individuals at high risk of CRC.METHODS Data of 64448 participants obtained from Ningbo Hospital,China between 2014 and 2017 were retrospectively analyzed.The cohort comprised 64448 individuals,of which,530 were excluded due to missing or incorrect data.Of 63918,7607(11.9%)individuals were considered to be high risk for CRC,and 56311(88.1%)were not.The participants were randomly allocated to a training set(44743)or validation set(19175).The discriminatory ability,predictive accuracy,and clinical utility of the model were evaluated by constructing and analyzing receiver operating characteristic(ROC)curves and calibration curves and by decision curve analysis.Finally,the model was validated internally using a bootstrap resampling technique.RESULTS Seven variables,including demographic,lifestyle,and family history information,were examined.Multifactorial logistic regression analysis revealed that age[odds ratio(OR):1.03,95%confidence interval(CI):1.02-1.03,P<0.001],body mass index(BMI)(OR:1.07,95%CI:1.06-1.08,P<0.001),waist circumference(WC)(OR:1.03,95%CI:1.02-1.03 P<0.001),lifestyle(OR:0.45,95%CI:0.42-0.48,P<0.001),and family history(OR:4.28,95%CI:4.04-4.54,P<0.001)were the most significant predictors of high-risk CRC.Healthy lifestyle was a protective factor,whereas family history was the most significant risk factor.The area under the curve was 0.734(95%CI:0.723-0.745)for the final validation set ROC curve and 0.735(95%CI:0.728-0.742)for the training set ROC curve.The calibration curve demonstrated

关键词： Colorectal cancer Early screening model High-risk population Nomogram model Questionnaire survey Dietary habit Living habit

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A Survey on Distributed Network Localization from a Graph Laplacian Perspective

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Journal of Systems Science & Complexity 2024年第1期37卷 273-293页

作者： han Zhimin lin Zhiyun FU Minyue Artificial Intelligence Institute School of AutomationHangzhou Dianzi UniversityHangzhou 310018China Shenzhen Key Laboratory of Control Theory and Intelligent Systems School of System Design and Intelligent ManufacturingSouthern University of Science and TechnologyShenzhen 518055China Peng Cheng Laboratory Shenzhen 518000China

Network localization serves as a fundamental component for enabling various position based operations in multi-agent systems,facilitating tasks like target searching and formation control by providing accurate position information for all nodes in the network.Network localization focuses on the challenge of determining the positions of nodes within a network,relying on the known positions of anchor nodes and internode relative measurements.Over the past few decades,distributed network localization has garnered significant attention from researchers.This paper aims to provide a review of main results and advancements in the field of distributed network localization,with a particular focus on the perspective of graph Laplacian.Owning to its favorable characteristics,graph Laplacian unifies various network localization,even when dealing with diverse types of internode relative measurements,into a unified protocol framework,which can be constructed by a linear method and ensure the global convergence.

关键词： Distributed network localization graph Laplaian sensor network

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Temporal and Spatial Trends in HIV Positivity Rate for VCT Clinics—China,2015–2022

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China CDC weekly 2024年第1期6卷 6-11页

作者： yi Liu Rong Su Dongmin Li Shaorong Wang Mengjie han National Center for AIDS/STD Control and Prevention Chinese Center for Disease Control and PreventionBeijingChina

Introduction:Human immunodeficiency virus(HIV)voluntary counseling and testing(VCT)clinics play a critical role in identifying and diagnosing HIV cases.This study aimed to describe the trend of HIV positivity rate(HPR)among Chinese VCT clinics between 2015 and 2022.Methods:This study utilized data from the China Information System for Disease Control and Prevention to analyze the trend in the HPR for VCT clinics from 2015 to 2022.The HPR was calculated by dividing the number of newly-reported HIV cases by the number of HIV tests,multiplied by 100%.To identify temporal and spatial trends in the HPR,we employed joinpoint regression analysis and the Getis-Ord hotspot analysis.Results:From 2015 to 2022,VCT clinics in China performed a total of 22,075,386 HIV tests,leading to the identification of 260,353 HIV cases,resulting in a HPR of 1.18%.The HPR consistently declined over the study period,with an average annual percent change(AAPC)of−7.5%(95%confidence interval:−12.6%,−2.2%,Plinics in China have played a significant role in identifying HIV cases.The declining HPR observed in these clinics may indicates the progress has been made in some degree in mitigating HIV among high-risk populations.Therefore,it is crucial to further improving the utilization of VCT clinics for HIV testing.

关键词： VCT dividing Spatial

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Epileptic brain network mechanisms and neuroimaging techniques for the brain network

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Neural Regeneration Research 2024年第12期19卷 2637-2648页

作者： yi Guo Zhonghua lin Zhen Fan Xin Tian Department of Neurology Sichuan Provincial People’s HospitalUniversity of Electronic Science and Technology of ChinaChengduSichuan ProvinceChina Sichuan Provincial Center for Mental Health Sichuan Provincial People’s HospitalUniversity of Electronic Science and Technology of ChinaChengduSichuan ProvinceChina Department of Geriatrics Sichuan Provincial People’s HospitalUniversity of Electronic Science and Technology of ChinaChengduSichuan ProvinceChina Department of Neurology Chongqing Key Laboratory of NeurologyThe First Affiliated Hospital of Chongqing Medical UniversityChongqingChina

Epilepsy can be defined as a dysfunction of the brain network,and each type of epilepsy involves different brain-network changes that are implicated diffe rently in the control and propagation of interictal or ictal discharges.Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice.An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tra ctography,diffusion kurtosis imaging-based fiber tractography,fiber ball imagingbased tra ctography,electroencephalography,functional magnetic resonance imaging,magnetoencephalography,positron emission tomography,molecular imaging,and functional ultrasound imaging have been extensively used to delineate epileptic networks.In this review,we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy,and extensively analyze the imaging mechanisms,advantages,limitations,and clinical application ranges of each technique.A greater focus on emerging advanced technologies,new data analysis software,a combination of multiple techniques,and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.

关键词： electrophysiological techniques epilepsy functional brain network functional magnetic resonance imaging functional near-infrared spectroscopy machine leaning molecular imaging neuroimaging techniques structural brain network virtual epileptic models

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Azocalixarenes: a scaffold of universal excipients with high efficiency

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Science China Chemistry 2024年第5期67卷 1697-1706页

作者： Yu-Xin Yue yi-lin lin Meng-Meng Chen han-Wen Tian Rong Ma Ze-han Wang Fang-Yuan Chen Yu-Chen Pan Dong-Sheng Guo College of Chemistry State Key Laboratory of Elemento-Organic ChemistryKey Laboratory of Functional Polymer Materials(Ministry of Education)Frontiers Science Center for New Organic MatterCollaborative Innovation Center of Chemical Science and Engineering(Tianjin)Nankai UniversityTianjin 300071China

Excipients are important components of pharmaceutical preparations that affect their quality, safety, and efficacy. Macrocyclic receptors are a family of supramolecular excipients with several advantages, including molecular-level protection, small sizes,fast kinetics of host-guest recognition, and modular construction. With the continuous advances in the medical field, personalized and precision medicine requires the development of excipients with low dosages, integrated modifying effects, universality,and controlled release. To meet these requirements, we have developed a new family of macrocyclic excipients based on calixarenes by integrating their covalent(broad chemical design space) and noncovalent(wide range of substrates) advantages.Accordingly, azocalixarenes(Azo CAs) were designed, showing high binding affinities to a broad spectrum of active pharmaceutical ingredients(APIs), selectivity to interferents, and responsiveness to hypoxic microenvironments. Due to their highly efficient and controllable recognition, Azo CAs serve as low-dose excipients for 30 APIs. Molecular encapsulation by Azo CAs results in the integrated modification of the physicochemical properties of APIs, including solubility, stability, bioavailability,and biocompatibility. Moreover, Azo CAs can be reduced by azoreductases overexpressed in hypoxic microenvironments,leading to the controlled release of APIs. Collectively, Azo CA excipients have broad application prospects for a series of diseases such as enteritis, arthritis, stroke, cancer, bacterial infection and kidney injury, with diverse therapeutic modalities,including chemotherapy, photodynamic therapy, photothermal therapy, immunotherapy, boron neutron capture therapy, radiotherapy, fluorescence imaging, and their combinations.

关键词： supramolecular chemistry host-guest systems excipient calixarene molecular recognition

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