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A vectorial model for the nonlinear gradient force exerted on metallic Rayleigh nanoparticles

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Chinese Optics Letters 2024年第2期22卷 207-213页

作者：朱政张聿全闵长俊 Aurèle J.LAdam H.Paul Urbach 袁小聪 research Center for Humanoid Sensing Research Institute of Intelligent SensingZhejiang LabHangzhou 311100China Nanophotonics research Center Institute of Microscale Optoelectronics&State Key Laboratory of Radio Frequency Heterogeneous IntegrationShenzhen UniversityShenzhen 518060China Optics research group ImPhys DepartmentFaculty of Applied SciencesDelft University of TechnologyDelft 2628 CJThe Netherlands

Optical tweezers have proved to be a powerful tool with a wide range of *** gradient force plays a vital role in the stable optical trapping of *** scalar method is convenient and effective for analyzing the gradient force in traditional optical ***,when the third-order nonlinear effect of the nano-object is stimulated,the scalar method cannot adequately present the optical response of the metal nanoparticle to the external optical ***,we propose a theoretical model to interpret the nonlinear gradient force using the vector *** combining the optical Kerr effect,the polarizability vector of the metallic nanoparticle is derived.A quantitative analysis is obtained for the gradient force as well as for the optical potential *** vector method yields better agreement with reported experimental *** suggest that this method could lead to a deeper understanding of the physics relevant to nonlinear optical trapping and binding phenomena.

关键词： gradient forces nonlinear effect metallic nanoparticles

Enhancing 3D Reconstruction Accuracy of FIB Tomography Data Using Multi‑voltage Images and Multimodal Machine Learning

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Nanomanufacturing and Metrology 2024年第1期7卷 48-60页

作者： Trushal Sardhara Alexander Shkurmanov Yong Li Lukas Riedel Shan Shi Christian J.Cyron Roland C.Aydin Martin Ritter Institute for Continuum and Material Mechanics Hamburg University of TechnologyHamburgGermany Electron Microscopy Unit Hamburg University of TechnologyHamburgGermany Institute of Materials Physics and Technology Hamburg University of TechnologyHamburgGermany Institute of Materials Mechanics Helmholtz-Zentrum HereonGeesthachtGermany research group of Integrated Metallic Nanomaterials systems Hamburg University of TechnologyHamburgGermany Institute of Material systems Modeling Helmholtz-Zentrum HereonGeesthachtGermany

FIB-SEM tomography is a powerful technique that integrates a focused ion beam(FIB)and a scanning electron microscope(SEM)to capture high-resolution imaging data of *** approach involves collecting in-plane SEM imagesand using FIB to remove material layers for imaging subsequent planes,thereby producing image ***,theseimage stacks in FIB-SEM tomography are subject to the shine-through effect,which makes structures visible from theposterior regions of the current *** artifact introduces an ambiguity between image intensity and structures in thecurrent plane,making conventional segmentation methods such as thresholding or the k-means algorithm *** study,we propose a multimodal machine learning approach that combines intensity information obtained at differentelectron beam accelerating voltages to improve the three-dimensional(3D)reconstruction of *** treatingthe increased shine-through effect at higher accelerating voltages as a form of additional information,the proposed methodsignificantly improves segmentation accuracy and leads to more precise 3D reconstructions for real FIB tomography data.

关键词： Multimodal machine learning Multi-voltage images FIB-SEM Overdeterministic systems 3D reconstruction FIB tomography

Detection of Oscillations in Process Control Loops From Visual Image Space Using Deep Convolutional Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 982-995页

作者： Tao Wang Qiming Chen Xun Lang Lei Xie Peng Li Hongye Su the Department of Electronic Engineering the School of InformationYunnan UniversityKunming 650091China DAMO Academy Alibaba GroupHangzhou 311100China the State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou 310027China

Oscillation detection has been a hot research topic in industries due to the high incidence of oscillation loops and their negative impact on plant *** numerous automatic detection techniques have been proposed,most of them can only address part of the practical *** oscillation is heuristically defined as a visually apparent periodic ***,manual visual inspection is labor-intensive and prone to missed *** neural networks(CNNs),inspired by animal visual systems,have been raised with powerful feature extraction *** this work,an exploration of the typical CNN models for visual oscillation detection is ***,we tested MobileNet-V1,ShuffleNet-V2,Efficient Net-B0,and GhostNet models,and found that such a visual framework is well-suited for oscillation *** feasibility and validity of this framework are verified utilizing extensive numerical and industrial *** with state-of-theart oscillation detectors,the suggested framework is more straightforward and more robust to noise and *** addition,this framework generalizes well and is capable of handling features that are not present in the training data,such as multiple oscillations and outliers.

关键词： Convolutional neural networks(CNNs) deep learning image processing oscillation detection process industries

Localization in modified polar representation: hybrid measurements and closed-form solution

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Journal of systems Engineering and Electronics 2024年第3期35卷 575-588页

作者： CONG Xunchao SUN Yimao YANG Yanbing ZHANG Lei CHEN Liangyin The 10th research Institute of China Electronics Technology group Corporation Chengdu 610036China College of Computer Science and Institute for Industrial Internet research Sichuan UniversityChengdu 610065China

Classical localization methods use Cartesian or Polar coordinates, which require a priori range information to determine whether to estimate position or to only find bearings. The modified polar representation (MPR) unifies near-field and farfield models, alleviating the thresholding effect. Current localization methods in MPR based on the angle of arrival (AOA) and time difference of arrival (TDOA) measurements resort to semidefinite relaxation (SDR) and Gauss-Newton iteration, which are computationally complex and face the possible diverge problem. This paper formulates a pseudo linear equation between the measurements and the unknown MPR position,which leads to a closed-form solution for the hybrid TDOA-AOA localization problem, namely hybrid constrained optimization(HCO). HCO attains Cramér-Rao bound (CRB)-level accuracy for mild Gaussian noise. Compared with the existing closed-form solutions for the hybrid TDOA-AOA case, HCO provides comparable performance to the hybrid generalized trust region subproblem (HGTRS) solution and is better than the hybrid successive unconstrained minimization (HSUM) solution in large noise region. Its computational complexity is lower than that of HGTRS. Simulations validate the performance of HCO achieves the CRB that the maximum likelihood estimator (MLE) attains if the noise is small, but the MLE deviates from CRB earlier.

关键词： localization modified polar representation time difference of arrival(TDOA) angle of arrival(AOA) closed-form solution

Glucagon-like peptide 1 receptor activation:anti-inflammatory effects in the brain

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Neural Regeneration research 2024年第8期19卷 1671-1677页

作者： Yolanda Diz-Chaves Zainab Maastor Carlos Spuch José Antonio Lamas Lucas C.González-Matías Federico Mallo Biomedical research Centre(CINBIO) Laboratory of EndocrinologyUniversity of VigoGalicia Sur Health Research InstituteVigoSpain Translational Neuroscience research group Galicia Sur Health Research InstituteCIBERSAMHospitalÁlvaro CunqueiroSala InvestigaciónEstrada Clara CampoamorVigoSpain Biomedical research Centre(CINBIO) Laboratory of NeuroscienceUniversity of VigoGalicia Sur Health Research InstituteVigoSpain

The glucagon-like peptide 1 is a pleiotropic hormone that has potent insulinotropic effects and is key in treating metabolic diseases such as diabetes and ***-like peptide 1 exerts its effects by activating a membrane receptor identified in many tissues,including diffe rent brain ***-like peptide 1 activates several signaling pathways related to neuroprotection,like the support of cell growth/survival,enhancement promotion of synapse formation,autophagy,and inhibition of the secretion of proinflammatory cytokines,microglial activation,and apoptosis during neural *** glial cells,including astrocytes and microglia,maintain metabolic homeostasis and defe nse against pathogens in the central nervous *** brain insult,microglia are the first cells to respond,followed by reactive *** activated cells produce proinflammato ry mediators like cytokines or chemokines to react to the ***,under these circumstances,mic roglia can become chro nically inflammatory by losing their homeostatic molecular signature and,consequently,their functions during many *** processes promote the development of neurological disorders and influence their pathological evolution:like the formation of protein aggregates,the accumulation of abnormally modified cellular constituents,the formation and release by injured neurons or synapses of molecules that can dampen neural function,and,of critical impo rtance,the dysregulation of inflammato ry control *** glucagonlike peptide 1 receptor agonist emerges as a critical tool in treating brain-related inflammatory pathologies,restoring brain cell homeostasis under inflammatory conditions,modulating mic roglia activity,and decreasing the inflammato ry *** review summarizes recent advances linked to the anti-inflammato ry prope rties of glucagon-like peptide 1 receptor activation in the brain related to multiple sclerosis,Alzheimer’s disease,Parkins

关键词： astrocytes brain glucagon-like peptide 1 receptor inflammation microglia

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 *** 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 *** 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 ***,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 *** 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,*** 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 carri

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

Effect of titanium on the sticking of pellets based on hydrogen metallurgy shaft furnace:Behavior analysis and mechanism evolution

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International Journal of Minerals,Metallurgy and Materials 2024年第2期31卷 282-291页

作者： Jinge Feng Jue Tang Zichuan Zhao Mansheng Chu Aijun Zheng Xiaobing Li Xiao’ai Wang School of Metallurgy Northeastern UniversityShenyang 110819China Institute for Frontier Technologies of Low-carbon Steelmaking Northeastern UniversityShenyang 110819China Liaoning Low-carbon Steelmaking Technology Engineering research Center Northeastern UniversityShenyang 110819China Engineering research Center of Frontier Technologies for Low-carbon Steelmaking(Ministry of Education Shenyang 110819China Zhang Xuan Technology of HBIS group Co. Ltd.Shijiazhuang 050000China Xuanhua Iron and Steel group Co. Ltd.Shijiazhuang 050000China Iron and Steel research Institute of HBIS group Co. Ltd.Shijiazhuang 050000China

Direct reduction based on hydrogen metallurgical gas-based shaft furnace is a promising technology for the efficient and low-carbon smelting of vanadium-titanium ***,in this process,the sticking of pellets occurs due to the aggregation of metal-lic iron between the contact surfaces of adjacent pellets and has a serious negative effect on the continuous *** paper presents a detailed experimental study of the effect of TiO2 on the sticking behavior of pellets during direct reduction under different *** showed that the sticking index(SI)decreased linearly with the increasing TiO2 *** phenomenon can be attributed to the increase in unreduced FeTiO3 during reduction,leading to a decrease in the number and strength of metallic iron interconnections at the sticking *** the TiO2 addition amount was raised from 0 to 15wt%at 1100°C,the SI also increased from 0.71%to 59.91%.The connection of the slag phase could be attributed to the sticking at a low reduction temperature,corresponding to the low sticking ***,the interconnection of metallic iron became the dominant factor,and the SI increased sharply with the increase in re-duction ***2 had a greater effect on SI at a high reduction temperature than at a low reduction temperature.

关键词： titanium sticking index hydrogen metallurgy direct reduction pellets

Fuzzy Difference Equations in Diagnoses of Glaucoma from Retinal Images Using Deep Learning

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 801-816页

作者： D.Dorathy Prema Kavitha L.Francis Raj Sandeep Kautish Abdulaziz S.Almazyad Karam M.Sallam Ali Wagdy Mohamed Department of Mathematics Voorhees CollegeVelloreTamil NaduIndia Chandigarh group of Colleges JhanjeriMohaliPunjabIndia Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Faculty of Science and Technology School of IT and SystemsUniversity of CanberraCanberraAustralia Operations research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science research Center Applied Science Private UniversityAmman11937Jordan

The intuitive fuzzy set has found important application in decision-making and machine *** enrich and utilize the intuitive fuzzy set,this study designed and developed a deep neural network-based glaucoma eye detection using fuzzy difference equations in the domain where the retinal images *** image detections are categorized as normal eye recognition,suspected glaucomatous eye recognition,and glaucomatous eye *** degrees associated with weighted values are calculated to determine the level of concentration between the fuzzy partition and the retinal *** proposed model was used to diagnose glaucoma using retinal images and involved utilizing the Convolutional Neural Network(CNN)and deep learning to identify the fuzzy weighted regularization between *** methodology was used to clarify the input images and make them adequate for the process of glaucoma *** objective of this study was to propose a novel approach to the early diagnosis of glaucoma using the Fuzzy Expert System(FES)and Fuzzy differential equation(FDE).The intensities of the different regions in the images and their respective peak levels were *** the peak regions were identified,the recurrence relationships among those peaks were then *** partitioning was done due to varying degrees of similar and dissimilar concentrations in the *** and dissimilar concentration levels and spatial frequency generated a threshold image from the combined fuzzy matrix and *** distinguished between a normal and abnormal eye condition,thus detecting patients with glaucomatous eyes.

关键词： Convolutional Neural Network(CNN) glaucomatous eyes fuzzy difference equation intuitive fuzzy sets image segmentation retinal images

A Probabilistic Approach for Predicting Vessel Motion

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1877-1879页

作者： Qi Hu Jingyi Liu Zongyu Zuo 7th research Division Beihang University(BUAA)Beijing 100191China 54th research Institute of China Electronics Technology group Corporation Shijiazhuang 050081China

Dear Editor,This letter addresses the challenge of forecasting the motion of real-world vessels over an extended period with a limited amount of available *** employing stochastic differential equation(SDE)modeling,we integrate both deterministic and stochastic components of the available ***,we establish a recursive prediction methodology based on Bayes’rule to update the model state when new measurements are ***,we develop a stochastic model tailored specifically to vessel dynamics and introduce an approximation method to tackle computational ***,we present an application example and conduct a comparative experiment to validate the effectiveness and superiority of the proposed method.

关键词： method stochastic letter