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Multi-Scale Dilated Convolution Network for SPECT-MPI Cardiovascular Disease Classification with Adaptive Denoising and Attenuation Correction

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 299-327页

作者： A.robert Singh Suganya Athisayamani Gyanendra Prasad Joshi Bhanu Shrestha Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203Tamil NaduIndia School of Computing Sastra Deemed to be UniversityThanjavur613401Tamil NaduIndia Department of Artificial Intelligence&Software Kangwon National UniversitySamcheok25913Republic of Korea Department of Information Convergence System Graduate School of Smart ConvergenceKwangwoon UniversitySeoul01897Republic of Korea

Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronary artery disease(CAD).The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks(CNNs).This paper uses a SPECT classification framework with three steps:1)Image denoising,2)Attenuation correction,and 3)Image *** denoising is done by a U-Net architecture that ensures effective image *** correction is implemented by a convolution neural network model that can remove the attenuation that affects the feature extraction process of ***,a novel multi-scale diluted convolution(MSDC)network is *** merges the features extracted in different scales and makes the model learn the features more *** scales of filters with size 3×3 are used to extract *** three steps are compared with state-of-the-art *** proposed denoising architecture ensures a high-quality image with the highest peak signal-to-noise ratio(PSNR)value of *** proposed classification method is compared with the five different CNN models,and the proposed method ensures better classification with an accuracy of 96%,precision of 87%,sensitivity of 87%,specificity of 89%,and F1-score of 87%.To demonstrate the importance of preprocessing,the classification model was analyzed without denoising and attenuation correction.

关键词： SPECT-MPI CAD MSDC denoising attenuation correction classification

Three-Stage Transfer Learning with AlexNet50 for MRI Image Multi-Class Classification with Optimal Learning Rate

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 155-183页

作者： Suganya Athisayamani A.robert Singh Gyanendra Prasad Joshi Woong Cho School of Computing Sastra Deemed to be UniversityThanjavur613401India Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203India Department of AI and Software Engineering Kangwon National UniversitySamcheok25913Republic of Korea Department of Electronics Information and Communication EngineeringKangwon National UniversitySamcheok25913Republic of Korea

In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological *** is particularly effective for detecting soft tissue ***,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of *** address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI *** manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning *** are three stages for learning;in the first stage,the whole dataset is used to learn the *** the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented *** method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the School of Biomedical Engineering of Southern Medical University(SMU-dataset),and The National Institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for *** hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning ***-dataset registers maximum classification *** evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.

关键词： MRI tumors classification AlexNet50 transfer learning hyperparameter tuning optimizer

Human endogenous retrovirus type-W and multiple sclerosis–related smoldering neuroinflammation

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Neural Regeneration Research 2025年第3期20卷 813-814页

作者： Joel Gruchot Laura Reiche Andrew Chan robert Hoepner Patrick Küry Department of Neurology Medical Faculty and University Hospital DüsseldorfHeinrich Heine University DüsseldorfDüsseldorfGermany Department of Neurology InselspitalBern University Hospital and University of BernBernSwitzerland

Introduction to human endogenous retrovirus type-W(HERV-W): Genomic inheritance from the past includes retroviral sequences that have been stably incorporated into our genomes and account for up to 8% of human DNA.

关键词： endogenous inflammation Human

Lipid droplets in the nervous system:involvement in cell metabolic homeostasis

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Neural Regeneration Research 2025年第3期20卷 740-750页

作者： Yuchen Zhang Yiqing Chen Cheng Zhuang Jingxuan Qi robert Chunhua Zhao Jiao Wang School of Life Sciences Shanghai UniversityShanghaiChina School of Medicine Shanghai UniversityShanghaiChina Institute of Basic Medical Sciences Chinese Academy of Medical Sciences School of Basic MedicinePeking Union Medical CollegeBeijingChina Center of Excellence in Tissue Engineering Chinese Academy of Medical SciencesBeijingChina Beijing Key Laboratory of New Drug Development and Clinical Trial of Stem Cell Therapy BeijingChina

Lipid droplets serve as primary storage organelles for neutral lipids in neurons,glial cells,and other cells in the nervous *** droplet formation begins with the synthesis of neutral lipids in the endoplasmic ***,lipid droplets were recognized for their role in maintaining lipid metabolism and energy homeostasis;however,recent research has shown that lipid droplets are highly adaptive organelles with diverse functions in the nervous *** addition to their role in regulating cell metabolism,lipid droplets play a protective role in various cellular stress ***,lipid droplets exhibit specific functions in neurons and glial *** of lipid droplet formation leads to cellular dysfunction,metabolic abnormalities,and nervous system *** review aims to provide an overview of the role of lipid droplets in the nervous system,covering topics such as biogenesis,cellular specificity,and ***,it will explore the association between lipid droplets and neurodegenerative *** the involvement of lipid droplets in cell metabolic homeostasis related to the nervous system is crucial to determine the underlying causes and in exploring potential therapeutic approaches for these diseases.

关键词： Alzheimer's disease lipid droplet biogenesis lipid droplets lipid metabolism nervous system neurodegenerative disorders oxidative stress Parkinson's disease

Sleep as a window to understand and regulate Alzheimer's disease:emerging roles of thalamic reticular nucleus

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Neural Regeneration Research 2025年第6期20卷 1711-1712页

作者： Haoqi Sun Shiqian Shen robert J.Thomas M.Brandon Westover Can Zhang Department of Neurology Beth Israel Deaconess Medical CenterHarvard Medical SchoolBostonMAUSA Center for Translational Pain Research Department of AnesthesiaCritical Care and Pain MedicineMassachusetis General HospitalHarvard Medical SchoolBostonMAUSA Division of Pulmonary Critical Care and Sleep MedicineDepartment of MedicineBeth Israel Deaconess Medical CenterHarvard Medical SchoolBostonMAUSA Genetics and Aging Research Unit McCance Center for Brain HealthMass General Institute for Neurodegenerative DiseaseDepartment of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMAUSA

Introduction:Alzheimer 's disease(AD) is a common neurodegenerative disorder and the primary cause of dementia. Considerable evidence supports the “amyloid hypothesis,” stating that the pathogenesis of AD is primarily caused by the deposition of amyloid-β(Aβ), which drives tau phosphorylation, neuroinflammation, and neurodegeneration in the brain. The amyloid hypothesis is strengthened by the significant and moderate benefit of lecanemab, a humanized antibody through an anti-amyloid mechanism,showing slowed clinical decline(van Dyck et al.,2023). The recent positive results of anti-amyloid trials have brought back focus on the amyloid hypothesis through biochemical, genetic, and pharmacological approaches(Zhang, 2023).

关键词： Alzheimer inflammation hypothesis

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Interview of robert ***

Science China Chemistry 2011年第12期54卷 2018-2020页

作者： Xue, Ziling Grubbs, robert H. Univ Tennessee Knoxville TN 37996 USA CALTECH Pasadena CA 91125 USA Stanford Univ Stanford CA 94305 USA

robert H. Grubbs is a Nobel Laureate and the Victor and Eliza-beth Atkins Professor of Chemistry at the California Institute of Technology, USA. He grew up in the State of Kentucky,

关键词：诺贝尔奖获得者采访加州理工学院肯塔基州

Prof. robert S. Warren: come early, stay late and listen

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Hepatobiliary Surgery and Nutrition 2020年第1期9卷 122-123页

作者：无 robert S.Warre HBSN the University of California School of Medicine

Expert’s introduction robert ***,MD(Figure 1)is a Professor of Surgery in the University of California School of Medicine and a specialist in gastrointestinal and liver *** earned a medical degree at the University of Minnesota,where he completed a general surgery *** completing an oncology research fellowship at Memorial Sloan-Kettering Cancer Center in New York,***,joined UCSF Medical Center in 1988.A board-certified surgeon,he later became the Chief of Surgical Oncology at *** respected by his peers,*** was named to the list of ***"America’s Top Doctors",a distinction reserved for the top 1%of physicians in the nation for a given *** research focuses on the biology of colorectal cancer(CRC)and how it spreads.

关键词： Surgery Figure Warren

Magnetic Flux Controllers for Induction Heating Applications

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材料热处理学报 2004年第5期25卷 567-572页

作者： Valentin Nemkov robert Goldstein robert Ruffini FluxtroUCentre for Induction Technology USAFluxtroUCentre for Induction Technology USAFluxtroUCentre for Induction Technology USA

Application of magnetic flux controllers/concentrators to induction heating coils can drastically improve the process efficiency and heat pattern control. Presentation includes: benefits provided by flux controllers, materials available for controllers, application techniques, computer assisted design of induction coils with concentrators, examples of applications. Depending on induction system design, magnetic flux controllers can concentrate heating in a specified area, change heat source distribution and shield a particular part zone or external area preventing unintended eddy current heating. Besides of the coil efficiency improvement and optimal power distribution, magnetic flux controllers reduce the coil current demand from a supplying circuitry thus strongly reducing losses in busswork, cables, transformers and inverter components. Improvement that can be achieved due to magnetic flux controllers is case dependable. 2D and 3D computer simulation allows the designer to predict accurately effect of controllers on the coil parameters and temperature distribution and optimize the whole electromagnetic system. Special attention in presentation is paid to new magnetodielectric materials optimized for induction heating conditions. These materials have high magnetic permeability and saturation flux density, excellent machinability, good chemical and temperature resistance. Concentrators from these materials can work in a wide range of frequencies and specific powers. Examples of magnetic flux controller application include surface hardening of shafts and gears, induction surface hardfacing and brazing.

关键词：热处理感应器磁通量计算机模拟

Multi-stream join answering for mining significant cross-stream correlations

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Frontiers of Computer Science 2012年第2期6卷 131-142页

作者： robert GWADERA IBM Zurich Research Laboratory Säumerstrasse 4CH-8803 RüschlikonSwitzerland

Sliding-window multi-stream join （SWMJ） is a fundamental operation for correlating information from dif- ferent streams. We provide a solution to the problem of as- sessing significance of the SWMJ result by focusing on the relative frequency of windows satisfying a given equijoin predicate as the most important parameter of the SWMJ re- suit. In particular, we derive a formula for computing the expected relative frequency of windows satisfying a given equijoin predicate that can be. evaluated in quadratic time in the window size given a proposed probabilistic model of the multi-stream. In experiments conducted on a daily rain- fall data set we demonstrate the remarkable accuracy of our method, which confirms our theoretical analysis.

关键词： probabilistic data streams stream summariza-tion stream sketch window aggregate queries