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Electrochemical sensor for dopamine detection based on multiwalled carbon nanotube/molybdenum disulfide quantum dots with machine learning integration and anti-interference capability

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Tungsten 2025年第1期7卷 137-151页

作者： Geethukrishnan Onkar Apte Kiran Kumar Tadi Energy Electrodics and Electrocatalysis (EEE) Lab Department of Chemistry School of Advanced Sciences Vellore Institute of Technology School of Computer Science and Engineering Vellore Institute of Technology

The precise detection and measurement of dopamine（DA）,a crucial neurotransmitter in the human body,plays a significant role in diagnosing,preventing,and treating neurological diseases associated with its levels.A highly sensitive DA electrochemical sensor was constructed by combining molybdenum disulfide quantum dots（MSQDs） with multiwalled carbon nanotubes（MWCNTs）.The MSQDs were synthesized using the shear exfoliation *** sensors consist of MSQDs with Mo-S edge catalytic centers for the DA redox reaction,and MWCNTs amplify the sensor *** linearity of the sensor for the detection of DA was tested in the presence of ascorbic acid(AA,50 μmol·L-1) and uric acid(UA,200 μmol·L-1),and exhibited linearity from 2 to 966 μmol·L-1of DA with 0.097 μA(mol·L-1)-1sensitivity and a low limit of detection of0.6 μmol·L-1（the ratio between signal and noise,S/N=3）.Moreover,the sensitivity and selectivity of the sensor were also studied using *** is no increase in amperometric current after adding the most potentially interfering *** sensor was successfully applied to recover DA in human blood sera ***,machine learning algorithms were operated to aid in the near-precise detection of DA in the heterogeneous mixture containing AA and *** algorithms facilitate the identification and quantification of DA amidst coexisting interferents,including AA,that are commonly present in biological matrices.

关键词： Dopamine MoS_2 Biosensor Multiwalled carbon nanotubes Machine learning Complex mixture

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Dis-NDVW: Distributed Network Asset Detection and Vulnerability Warning Platform

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computers, Materials & Continua 2023年第7期76卷 771-791页

作者： Leilei Li Yansong Wang Dongjie Zhu Xiaofang Li Haiwen Du Yixuan Lu Rongning Qu Russell Higgs Artificial Intelligence Academy Wuxi Vocational College of Science and TechnologyWuxi214068China School of Computer Science and Technology Harbin Institute of TechnologyWeihai264209China Department of Mathematics Harbin Institute of TechnologyWeihai264209China School of Astronautics Harbin Institute of TechnologyHarbin150001China School of Mathematics and Statistics University College DublinDublinDO4 V1W8Ireland

With the rapid development of Internet technology,the issues of network asset detection and vulnerability warning have become hot topics of concern in the ***,most existing detection tools operate in a single-node mode and cannot parallelly process large-scale tasks,which cannot meet the current needs of the *** address the above issues,this paper proposes a distributed network asset detection and vulnerability warning platform(Dis-NDVW)based on distributed systems and multiple detection ***,this paper proposes a distributed message sub-scription and publication system based on Zookeeper and Kafka,which endows Dis-NDVW with the ability to parallelly process large-scale ***,Dis-NDVW combines the RangeAssignor,RoundRobinAssignor,and StickyAssignor algorithms to achieve load balancing of task nodes in a distributed detection *** terms of a large-scale task processing strategy,this paper proposes a task partitioning method based on First-In-First-Out(FIFO)*** method realizes the parallel operation of task producers and task consumers by dividing pending tasks into different queues according to task *** ensure the data reliability of the task cluster,Dis-NDVW provides a redundant storage strategy for master-slave partition *** terms of distributed storage,Dis-NDVW utilizes a distributed elastic storage service based on ElasticSearch to achieve distributed storage and efficient retrieval of big *** verification shows that Dis-NDVW can better meet the basic requirements of ultra-large-scale detection tasks.

关键词： Distributed network security network asset detection vulnerability warning

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Correction of the Temperature Effect of Muon Counts Observed at the Guangzhou Station

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Research in Astronomy and Astrophysics 2023年第2期23卷 132-139页

作者： Cao-Long Xu Yang Wang Gang Qin Ping-Bing Zuo School of Science Harbin Institute of TechnologyShenzhenShenzhen 518055China Laboratory for Space Weather Storms Institute of Space Science and Applied TechnologyHarbin Institute of TechnologyShenzhenShenzhen 518055China

Muons are the main component of secondary cosmic rays,and the variation in muon intensity indicates the variation in primary cosmic ray ***,before using muons to study the variation in the intensity of cosmic rays,it is necessary to eliminate the atmospheric effects,such as pressure and temperature *** this work,the temperature effect of the muons is corrected in terms of empirical method by using ground *** temperature correction is applied to the muon data observed at the Guangzhou station during the period2010–2021 after a barometric *** is found that the effect of seasonal variations in temperature on muon counts is greatly eliminated in the corrected ***,the muon data are well correlated with the neutron data in comparison,which verifies the reliability of the corrected muon *** results show that the correction of muon data by using ground temperature is an effective method.

关键词： atmospheric effects-Sun activity-(ISM:)cosmic rays

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Drilling process of indexable drill bit based on Coupled Eulerian-Lagrangian method:A simulation study

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Chinese Journal of Aeronautics 2024年第11期37卷 477-492页

作者： Desheng HU Caixu YUE Xianli LIU Zhipeng JIANG Yongshi XU Junhui LU Steven Y.LIANG Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of EducationHarbin University of Science and TechnologyHarbin 150080China George W.Woodruff School of Mechanical Engineering Georgia Institute of TechnologyAtlanta 30332USA

42CrMo steel has the characteristics of high strength,high wear resistance,high impact resistance,and fatigue ***,drilling 42CrMo steel has always been a challenging *** indexable drill bit has the advantages of high processing efficiency and low processing cost and has been widely used in the field of aerospace hole *** better understand the machining mechanism of the indexable drill bit,this paper uses the Coupled EulerianLagrangian method(CEL)to simulate the three-dimensional drilling model for the first *** simulation results of the drilling force obtained by the CEL method and Lagrangian method are compared with the experimental *** is verified that the CEL method is easy to converge and can avoid the problem of program interruption caused by mesh distortion,and the CEL simulation value is more consistent with the actual ***,the simulation results of cutting force and blade cutting edge node temperature under different process parameters are *** variation of time domain cutting force,frequency domain cutting force and tool temperature with process parameters are *** study provides a new method for the prediction of cutting performance and the optimization of process parameters of indexable drills.

关键词： 42CrMo steel Coupled EulerianLagrangian method Indexable drill bit Drilling force Process parameters

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BaMBNet:A Blur-Aware Multi-Branch Network for Dual-Pixel Defocus Deblurring

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IEEE/CAA Journal of Automatica Sinica 2022年第5期9卷 878-892页

作者： Pengwei Liang Junjun Jiang Xianming Liu Jiayi Ma School of Computer Science and Technology Harbin Institute of TechnologyHarbin 150001China Electronic Information School Wuhan UniversityWuhan 430072China IEEE

Reducing the defocus blur that arises from the finite aperture size and short exposure time is an essential problem in computational *** is very challenging because the blur kernel is spatially varying and difficult to estimate by traditional *** to its great breakthrough in low-level tasks,convolutional neural networks(CNNs)have been introdu-ced to the defocus deblurring problem and achieved significant ***,previous methods apply the same learned kernel for different regions of the defocus blurred images,thus it is difficult to handle nonuniform blurred *** this end,this study designs a novel blur-aware multi-branch network(Ba-MBNet),in which different regions are treated *** particular,we estimate the blur amounts of different regions by the internal geometric constraint of the dual-pixel(DP)data,which measures the defocus disparity between the left and right *** on the assumption that different image regions with different blur amounts have different deblurring difficulties,we leverage different networks with different capacities to treat different image ***,we introduce a meta-learning defocus mask generation algorithm to assign each pixel to a proper *** this way,we can expect to maintain the information of the clear regions well while recovering the missing details of the blurred *** quantitative and qualitative experiments demonstrate that our BaMBNet outperforms the state-of-the-art(SOTA)*** the dual-pixel defocus deblurring(DPD)-blur dataset,the proposed BaMBNet achieves 1.20 dB gain over the previous SOTA method in term of peak signal-to-noise ratio(PSNR)and reduces learnable parameters by 85%.The details of the code and dataset are available at https://***/junjun-jiang/BaMBNet.

关键词： Blur kernel convolutional neural networks(CNNs) defocus deblurring dual-pixel(DP)data meta-learning

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Advanced liquid crystal-based switchable optical devices for light protection applications:principles and strategies

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Light(science & Applications) 2023年第4期12卷 512-541页

作者： Ruicong Zhang Zhibo Zhang Jiecai Han Lei Yang Jiajun li Zicheng Song Tianyu Wang Jiaqi Zhu National Key Laboratory of Science and Technology on Advanced Composites in Special Environments Harbin Institute of TechnologyHarbin 150080China Research Center of Analysis and Measurement Harbin Institute of TechnologyHarbin 150080China School of Energy Science&Engineering Harbin Institute of TechnologyHarbin 150001China Key Laboratory of Micro-systems and Micro-structures Manufacturing Ministry of EducationHarbin 150080China

With the development of optical technologies,transparent materials that provide protection from light have received considerable attention from *** important channels for external light,windows play a vital role in the regulation of light in buildings,vehicles,and *** is a need for windows with switchable optical properties to prevent or attenuate damage or interference to the human eye and light-sensitive instruments by inappropriate optical *** this context,liquid crystals(LCs),owing to their rich responsiveness and unique optical properties,have been considered among the best candidates for advanced light protection *** this review,we provide an overview of advances in research on LC-based methods for protection against ***,we introduce the characteristics of different light sources and their protection ***,we introduce several classes of light modulation principles based on liquid crystal materials and demonstrate the feasibility of using them for light *** addition,we discuss current light protection strategies based on liquid crystal materials for different ***,we discuss the problems and shortcomings of current *** propose several suggestions for the development of liquid crystal materials in the field of light protection.

关键词： optical crystal liquid

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DP-BERT: A pre-trained deep language model for depression prediction using microarray data

DP-BERT: A pre-trained deep language model for depression pr...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Gao, Junyu Zeng, Min Li, Yiming Wang, Fang Zheng, Ruiqing Liu, Jin Guo, Fei Li, Min Central South University School of Computer Science and Engineering Changsha410083 China Harbin Institute of Technology School of Computer Science and Technology Harbin150001 China

ISBN: (纸本)9798350386226

In recent years, the increasing number of individuals diagnosed with depression and the growing awareness of its impact on modern society have highlighted the significance of accurate depression diagnosis. Microarray data has played a crucial role in uncovering the genetic mechanisms underlying depression. However, existing methods for depression prediction using microarray data often rely on the selection of differentially expressed genes. This approach disregards important information from other genes and is susceptible to batch effects, thereby limiting generalizability and model stability. To address these limitations, we propose DP-BERT, a depression prediction model based on Bidirectional Encoder Representations from Transformers (BERT). DP-BERT follows a pre-training and fine-tuning paradigm, leveraging a large amount of unlabeled microarray data from diverse sequencing platforms for pretraining to extract comprehensive genetic-level representations of psychiatric disorders. Subsequently, supervised fine-tuning is performed for depression prediction. Experimental results demonstrate that the pre-trained model achieves superior performance in depression prediction. The source code can be obtained from https://***/CSUBioGroup/DP-BERT. © 2024 IEEE.

关键词： Prediction models

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Research on the variation of dielectric properties of oil-paper insulation for power equipment over a wide temperature range

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High Voltage 2024年第3期9卷 648-658页

作者： Mingze Zhang Muhe Yu Wen Zhou Yilin Liang Shengjie Lei Yunbo Shi Limin Qu Key Laboratory of Engineering Dielectrics and Its Application Ministry of Education Harbin University of Science and TechnologyHarbinChina School of Measurement and Communication Engineering Harbin University of Science and TechnologyHarbinChina Electric Power Research Institute State Grid Heilongjiang Electric Power Company LimitedHarbinChina

The main part of oil-immersed power equipment is oil-paper *** lower ambient temperatures,transformer oil will become *** a result,compared to those at room temperature or operating temperature,the frequency domain dielectric properties of oil-paper insulation at low temperatures are drastically *** evaluating the insulation condition of electrical equipment,it is essential to accurately determine their dielectric *** paper described the FDS test,the DC conductivity test,and the transformer oil viscosity test,which was carried out in a laboratory environment for different ageing of oil-immersed pressboard and transformer oil at 233–373 *** ef-fects of temperature on the dielectric properties at the competing mechanisms of polarisation and conductivity loss were clarified based on variations of the FDS *** the viscosity change of ageing transformer oil at low temperatures,the Arrhenius and VFT viscosity equations were used to achieve a fitting calculation in the different temperature *** on the molecular/ion transition model in the force field and electric field,the characterisation relationships between the dynamic viscosity,DC conductivity,and test temperature of transformer oil were *** limita-tions of conventional transformer oil equivalent dielectric relaxation models over a wide temperature range were finally clarified by combining the test findings of the DC con-ductivity over a wide temperature range with observed and simulated *** paper provides an essential theoretical reference when using the FDS test to diagnose the insulation performance of oil-immersed power equipment in extremely cold regions.

关键词： insulation viscosity immersed

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Multiscale damage and failure behavior of SiCf/SiC composites with initial defects

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Ceramics International 2025年第14期51卷 19366-19381页

作者： Wang, Ben Wang, Jialin Lyu, Qihui Guo, Zaoyang Research Institute of Interdisciplinary Science & School of Materials Science and Engineering Dongguan University of Technology Guangdong Dongguan523808 China School of Science Harbin Institute of Technology Guangdong Shenzhen518055 China

A multiple damage mechanisms-based multiscale model is developed and implemented within a multiscale simulation framework, which incorporates the statistical distributions of SiC fiber strength and SiC matrix microcrack size to capture the mechanical response and defect-induced nonlinear behavior of SiCf/SiC composites. The micro- and mesoscale representative volume element (RVE) models accounting for the initial defects, are established to simulate the key deformation and damage evolution at the fiber bundle and material levels, and whose predictions are in good agreement with the experimental results for SiCf/SiC minicomposites and 2D SiCf/SiC composites. Based on the validated multiscale models, the effects of the multiscale components and defects on the failure envelopes of 2D SiCf/SiC composites under combined loadings are studied. Subsequently, a unified failure criterion with minimal non-physical parameters is formulated. This multiscale modeling strategy provides an effective way to predict the strength of SiCf/SiC composite structures related to the micro-mesoscopic characteristics. © 2025 Elsevier Ltd and Techna Group S.r.l.

关键词： Ceramic matrix composites

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Gaussian process regressions on hot deformation behaviors of FGH98 nickel-based powder superalloy

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Journal of Materials science & technology 2023年第15期146卷 177-185页

作者： Jie Xiong Jian-Chao He Xue-Song Leng Tong-Yi Zhang School of Materials Science and Engineering Harbin Institute of TechnologyShenzhen 518055China Institute of Special Environment Physical Sciences Harbin Institute of TechnologyShenzhen 518055China Hong Kong University of Science and Technology(Guangzhou) Guangzhou 511400China

The hot deformation behaviors of FGH98 nickel-based powder superalloy were experimentally investigated and theoretically analyzed by Arrhenius models and machine learning(ML).Hot compression tests were conducted with a Gleeble-3800 thermo-mechanical simulation machine on the FGH98 superalloy at strain rates of 0.001–1 s–1 and temperatures of 1025–1175℃.The peak stresses under different deformation conditions were analyzed via the Sellars model and an ML-inspired Gaussian process regression(GPR)*** prediction of the GPR model outperformed that from the Sellars *** addition,the stress-strain responses were predicted by the GPR model and tested by experimentally measured stress-strain *** results indicate that the developed GPR model has great power with wide generalization capability in the prediction of hot deformation behaviors of FGH98 superalloy,as evidenced by the R2 value higher than 0.99 on the test dataset.

关键词： Hot compressive deformation Nickel-based powder superalloy Activation energy Gaussian process regression

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