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Quantitatively mapping local quality of super-resolution microscopy by rolling Fourier ring correlation

Light(Science & Applications) 2023年第12期12卷 2826-2844页

作者： Weisong Zhao Xiaoshuai Huang Jianyu Yang Liying Qu Guohua Qiu Yue Zhao Xinwei Wang Deer Su Xumin Ding Heng Mao Yaming Jiu Ying Hu Jiubin Tan Shiqun Zhao Leiting Pan Liangyi Chen Haoyu Li innovation Photonics and Imaging center School of Instrumentation Science and EngineeringHarbin Institute of TechnologyHarbinChina Key Laboratory of Ultra-Precision Intelligent Instrumentation of Ministry of Industry and Information Technology Harbin Institute of TechnologyHarbinChina Biomedical Engineering Department International Cancer InstitutePeking University Cancer Hospital and InstituteHealth Science CenterPeking UniversityBeijingChina The Key Laboratory of Weak-Light Nonlinear Photonics of Education Ministry School of Physics and TEDA Institute of Applied PhysicsFrontiers Science Center for Cell ResponsesNankai UniversityTianjinChina State Key Laboratory of Membrane Biology Beijing Key Laboratory of Cardiometabolic Molecular MedicineInstitute of Molecular MedicineNational Biomedical Imaging CenterSchool of Future TechnologyPeking UniversityBeijingChina Department of Control Science and Engineering Harbin Institute of TechnologyHarbinChina School of Mathematical Sciences Peking UniversityBeijingChina Unit of Cell Biology and Imaging Study of Pathogen Host Interaction The Center for MicrobesDevelopment and HealthKey Laboratory of Molecular Virology and ImmunologyShanghai Institute of Immunity and InfectionChinese Academy of SciencesShanghaiChina School of Life Science and Technology Harbin Institute of TechnologyHarbinChina PKU-IDG/McGovern Institute for Brain Research BeijingChina Beijing Academy of Artificial Intelligence BeijingChina Frontiers Science center for Matter Behave in Space Environment Harbin Institute of TechnologyHarbinChina Key Laboratory of Micro-Systems and Micro-Structures Manufacturing of Ministry of Education Harbin Institute of TechnologyHarbinChina

In fluorescence microscopy,computational algorithms have been developed to suppress noise,enhance contrast,and even enable super-resolution(SR).However,the local quality of the images may vary on multiple scales,and these differences can lead to *** mapping methods fail to finely estimate the local quality,challenging to associate the SR scale ***,we develop a rolling Fourier ring correlation(rFRC)method to evaluate the reconstruction uncertainties down to SR *** visually pinpoint regions with low reliability,a filtered rFRC is combined with a modified resolution-scaled error map(RSM),offering a comprehensive and concise map for further *** demonstrate their performances on various SR imaging modalities,and the resulting quantitative maps enable better SR images integrated from different ***,we expect that our framework can become a routinely used tool for biologists in assessing their image datasets in general and inspire further advances in the rapidly developing field of computational imaging.

关键词： resolution local enable

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New Splitting methods for Convection-Dominated Diffusion Problems and Navier-Stokes Equations

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Communications in computational physics 2014年第10期16卷 1239-1262页

作者： Feng Shi Guoping Liang Yubo Zhao Jun Zou School of Mechanical Engineering and Automation Harbin Institute of TechnologyShenzhen Graduate SchoolShenzhen 518055China. Beijing FEGEN software Company Beijing 100190China. Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesShenzhen 518055China. Department of Mathematics The Chinese University of Hong KongShatinNTHong Kong.

We present a new splitting method for time-dependent convention-dominated diffusion *** original convention diffusion system is split into two sub-systems:a pure convection system and a diffusion *** each time step,a convection problem and a diffusion problem are solved successively.A few important features of the scheme lie in the facts that the convection subproblem is solved explicitly and multistep techniques can be used to essentially enlarge the stability region so that the resulting scheme behaves like an unconditionally stable scheme;while the diffusion subproblem is always self-adjoint and coercive so that they can be solved efficiently using many existing optimal preconditioned iterative *** scheme can be extended for solving the Navier-Stokes equations,where the nonlinearity is resolved by a linear explicit multistep scheme at the convection step,while only a generalized Stokes problem is needed to solve at the diffusion step and the major stiffness matrix stays invariant in the time marching *** simulations are presented to demonstrate the stability,convergence and performance of the single-step and multistep variants of the new scheme.

关键词： Convention-dominated diffusion problems Navier-Stokes equations operator splitting finite elements multistep scheme.

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Intermediate polaronic charge transport in organic crystals from a many-body first-principles approach

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npj computational Materials 2022年第1期8卷 630-637页

作者： Benjamin K.Chang Jin-Jian Zhou Nien-En Lee Marco Bernardi Department of Applied physics and Materials Science California Institute of TechnologyPasadenaCA91125USA

Charge transport in organic molecular crystals (OMCs) is conventionally categorized into two limiting regimes − band transport,characterized by weak electron-phonon (e-ph) interactions,and charge hopping due to localized polarons formed by strong e-ph ***,between these two limiting cases there is a less well understood intermediate regime where polarons are present but transport does not occur via *** we show a many-body first-principles approach that can accurately predict the carrier mobility in this intermediate regime and shed light on its microscopic *** approach combines a finite-temperature cumulant method to describe strong e-ph interactions with Green-Kubo transport *** apply this parameter-free framework to naphthalene crystal,demonstrating electron mobility predictions within a factor of 1.5−2 of experiment between 100 and 300 *** analysis reveals the formation of a broad polaron satellite peak in the electron spectral function and the failure of the Boltzmann equation in the intermediate regime.

关键词： polaron charge limiting

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A Survey on Digital Image Copy-Move Forgery Localization Using Passive Techniques

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Journal of New Media 2019年第1期1卷 11-25页

作者： Weijin Tan Yunqing Wu Peng Wu Beijing Chen School of Computer&software Nanjing University of Information Science&TechnologyNanjing210044China Jiangsu Collaborative innovation center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing210044China

Digital images can be tampered easily with simple image editing software ***,image forensic investigation on the authenticity of digital images’content is increasingly ***-move is one of the most common types of image ***,an overview of the traditional and the recent copy-move forgery localization methods using passive techniques is presented in this *** methods are classified into three types:block-based methods,keypoint-based methods,and deep learning-based *** addition,the strengths and weaknesses of these methods are compared and analyzed in robustness and computational ***,further research directions are discussed.

关键词： Image forgery copy-move forgery localization passive techniques

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Map Reconstruction of Radio Observations with Conditional Invertible Neural Networks

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Research in Astronomy and Astrophysics 2023年第7期23卷 126-138页

作者： Haolin Zhang Shifan Zuo Le Zhang School of physics and Astronomy Sun Yat-sen UniversityZhuhai 519082China CSST Science center for the Guangdong-Hong Kong-Macao Greater Bay Area Zhuhai 519082China Department of Astronomy Tsinghua UniversityBeijing 100084China Peng Cheng Laboratory Shenzhen 518000China

In radio astronomy,the challenge of reconstructing a sky map from time ordered data is known as an inverse *** map-making techniques and gridding algorithms are commonly employed to address this problem,each offering its own benefits such as producing minimum-variance ***,these approaches also carry limitations such as computational inefficiency and numerical instability in map-making and the inability to remove beam effects in grid-based *** overcome these challenges,this study proposes a novel solution through the use of the conditional invertible neural network(cINN)for efficient sky map *** the aid of forward modeling,where the simulated time-ordered data(TODs)are generated from a given sky model with a specific observation,the trained neural network can produce accurate reconstructed sky *** the Five-hundred-meter Aperture Spherical radio Telescope as an example,cINN demonstrates remarkable performance in map reconstruction from simulated TODs,achieving a mean squared error of2.29±2.14×10^(-4)K^(2),a structural similarity index of 0.968±0.002,and a peak signal-to-noise ratio of26.13±5.22 at the 1σ***,by sampling in the latent space of cINN,the reconstruction errors for each pixel can be accurately quantified.

关键词： methods:data analysis methods:numerical methods:statistical

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An Intrusion Detection Scheme Based on Federated Learning and Self-Attention Fusion Convolutional Neural Network for IoT

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Journal on Internet of Things 2022年第3期4卷 141-153页

作者： Jie Deng Ran Guo Zilong Jin School of software Nanjing University of Information Science and TechnologyNanjing210044China Cyberspace Institute Advanced Technology Guangzhou UniversityGuangzhou510006China Jiangsu Collaborative innovation center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science and TechnologyNanjing210044China

Traditional based deep learning intrusion detection methods face problems such as insufficient cloud storage,data privacy leaks,high com-munication costs,unsatisfactory detection rates,and false positive *** address existing issues in intrusion detection,this paper presents a novel approach called CS-FL,which combines Federated Learning and a Self-Attention Fusion Convolutional Neural *** Learning is a new distributed computing model that enables individual training of client data without uploading local data to a central *** the same time,local training results are uploaded and integrated across all participating clients to produce a global *** sharing model reduces communication costs,protects data privacy,and solves problems such as insufficient cloud storage and“data islands”for each *** the proposed method,a hybrid model is formed by integrating the self-Attention and similar parts of the Convolutional Neural Network in the local data *** approach not only enhances the performance of the hybrid model but also reduces computational overhead compared to pure hybrid neural *** from experiments on the NSL-KDD dataset show that the proposed method outperforms other intrusion detection techniques,resulting in a significant improvement in *** demonstrates the effectiveness of the proposed approach in improving intrusion detection accuracy.

关键词： Intrusion detection self-attention convolutional neural network federated learning

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Materials structure genealogy and high-throughput topological classification of surfaces and 2D materials

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npj computational Materials 2018年第1期4卷 222-231页

作者： Lauri Himanen Patrick Rinke Adam Stuart Foster Department of Applied physics Aalto UniversityP.O.Box 1110000076 AaltoEspooFinland Graduate School Materials Science in Mainz Staudinger Weg 9Mainz 55128Germany WPI Nano Life Science Institute(WPI-NanoLSI) Kanazawa UniversityKakuma-machiKanazawa 920-1192Japan

Automated and verifiable structural classification for atomistic structures is becoming necessary to cope with the vast amount of information stored in various computational materials *** we present a general recursive scheme for the structural classification of atomistic systems and introduce a structural materials map that can be used to organize the materials structure *** also introduce our implementation for the automatic classification of two-dimensional structures,especially focusing on surfaces and 2D *** classification procedure can automatically determine the dimensionality of a structure,further categorize the structure as a surface or a 2D material,return the underlying unit cell and also identify the outlier atoms,such as *** classification scheme does not require explicit search patterns and works even in the presence of defects and *** classification is tested on a wide variety of atomistic structures and provides a high-accuracy determination for all of the returned structural properties.A software implementation of the classification algorithm is freely available with an opensource license.

关键词： structure return becoming

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An Application of the Level Set Method to Underwater Acoustic Propagation

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Communications in computational physics 2012年第10期12卷 1359-1391页

作者： Sheri L.Martinelli Torpedo Systems Department Naval Undersea Warfare Center1176 Howell StreetNewportRhode Island 02841USA Division of Applied Mathematics Brown UniversityProvidenceRhode Island 02912USA

An algorithm for computing wavefronts,based on the high frequency approximation to the wave equation,is *** technique applies the level set method to underwater acoustic wavefront propagation in the time *** level set method allows for computation of the acoustic phase function using established numerical techniques to solve a first order transport equation to a desired order of *** methods for solving the eikonal equation directly on a fixed grid limit one to only the first arrivals,so these approaches are not useful when multi-path propagation is *** the level set model to the problem allows for the time domain computation of the phase function on a fixed grid,without having to restrict to first arrival *** implementation presented has no restrictions on range dependence or direction of travel,and offers improved efficiency over solving the full wave equation which under the high frequency assumption requires a large number of grid points to resolve the highly oscillatory *** conditions are discussed,and an approach is suggested for producing good results in the presence of boundary *** efficientmethod to compute the amplitude from the level set method solutions is also *** to analytical solutions are presented where available,and numerical results are validated by comparing results with exact solutions where available,a full wave equation solver,and with wavefronts extracted from ray tracing software.

关键词： Geometric acoustics level set method high-frequency acoustic propagation WENO method

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Soliton, breather, and rogue wave solutions for solving the nonlinear Schrodinger equation using a deep learning method with physical constraints

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Chinese physics B 2021年第6期30卷 77-87页

作者： Jun-Cai Pu Jun Li Yong Chen School of Mathematical Sciences Shanghai Key Laboratory of Pure Mathematics and Mathematical Practiceand Shanghai Key Laboratory of Trustworthy ComputingEast China Normal UniversityShanghai 200241China Shanghai Key Laboratory of Trustworthy Computing East China Normal UniversityShanghai 200062China College of Mathematics and Systems Science Shandong University of Science and TechnologyQingdao 266590China Department of physics Zhejiang Normal UniversityJinhua 321004China

The nonlinear Schrodinger equation is a classical integrable equation which contains plenty of significant properties and occurs in many physical ***,due to the difficulty of solving this equation,in particular in high dimensions,lots of methods are proposed to effectively obtain different kinds of solutions,such as neural networks among ***,a method where some underlying physical laws are embeded into a conventional neural network is proposed to uncover the equation’s dynamical behaviors from spatiotemporal data *** with traditional neural networks,this method can obtain remarkably accurate solution with extraordinarily less ***,this method also provides a better physical explanation and *** this paper,based on the above method,we present an improved deep learning method to recover the soliton solutions,breather solution,and rogue wave solutions of the nonlinear Schrodinger *** particular,the dynamical behaviors and error analysis about the one-order and two-order rogue waves of nonlinear integrable equations are revealed by the deep neural network with physical constraints for the first ***,the effects of different numbers of initial points sampled,collocation points sampled,network layers,neurons per hidden layer on the one-order rogue wave dynamics of this equation have been considered with the help of the control variable way under the same initial and boundary *** experiments show that the dynamical behaviors of soliton solutions,breather solution,and rogue wave solutions of the integrable nonlinear Schrodinger equation can be well reconstructed by utilizing this physically-constrained deep learning method.

关键词： deep learning method neural network soliton solutions breather solution rogue wave solutions

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Solving second-order nonlinear evolution partial differential equations using deep learning

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Communications in Theoretical physics 2020年第10期72卷 42-52页

作者： JUN Li Yong Chen Shanghai Key Laboratory of Trustworthy Computing East China Normal UniversityShanghai200062China School of Mathematical Sciences Shanghai Key Laboratory of PMMPShanghai Key Laboratory of Trustworthy ComputingEast China Normal UniversityShanghai200062China College of Mathematics and Systems Science Shandong University of Science and TechnologyQingdao266590China Department of physics Zhejiang Normal UniversityJinhua321004China

Solving nonlinear evolution partial differential equations has been a longstanding computational *** this paper,we present a universal paradigm of learning the system and extracting patterns from data generated from ***,this framework approximates the latent solution with a deep neural network,which is trained with the constraint of underlying physical laws usually expressed by some *** particular,we test the effectiveness of the approach for the Burgers'equation used as an example of second-order nonlinear evolution equations under different initial and boundary *** results also indicate that for soliton solutions,the model training costs significantly less time than other initial conditions.

关键词： deep learning nonlinear evolution equations data-driven solutions solitons nonlinear dynamics

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