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Particuology 2022年第6期20卷 32-38页

作者： Paul Git Matthias Hofmeister robert f.singer Carolin Körner Chair of Materials Science and Engineering for Metals(WTM) Friedrich-Alexander UniversitätErlangen-Nürnberg(FAU)Martensstr.591058 ErlangenGermany

fluidized Carbon Bed Cooling(fCBC)is an innovative investment casting process for directional solidification of superalloy *** takes advantage of a fluidized bed with a base of small glassy carbon beads for cooling and other low-density particles that form an insulating layer by floating to the bed *** so-called“Dynamic Baffle”protects the fluidized bed from the direct heat input from the high-temperature heating zone and provides the basis for an improved bed *** prerequisites for a stable casting process are stable fluidization conditions where neither collapse of the bed nor particle blow out at excessive bubble formation *** work aimed to investigate the fluidization behavior of spherical carbon bed material in argon and air at temperatures between 20 to 350℃.Systematic studies at reduced pressures using the fCBC prototype device were performed to understand the stable fluidization conditions at all stages of the investment casting *** particle shape factor and size distribution characterization and the measurement of the powder’s minimum fluidization velocity and bed voidage show that this material can be fully utilized as a cooling and buoyancy medium during the fCBC process.

关键词： Gas-solid fluidization Glassy carbon Reduced pressure Increased temperature fluidized carbon bed

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

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

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

Climate Change:No Going Back

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China Today 2025年第1期74卷 42-44页

作者： robert WALKER Beijing Normal University Royal Society of Arts Academy of Social Sciences in the U.K

With a commitment to reduce emissions,and its investment in green technology bringing down global costs,China is emerging as the leader in fighting climate *** knows that our world is getting *** also know *** out po... 详细信息

关键词： investment bringing fighting

New guidance for using t-SNE:Alternative defaults,hyperparameter selection automation,and comparative evaluation

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Visual Informatics 2022年第2期6卷 87-97页

作者： robert Gove Lucas Cadalzo Nicholas Leiby Jedediah M.singer Alexander Zaitzeff Two Six Technologies USA

We present new guidelines for choosing hyperparameters for t-SNE and an evaluation comparing these guidelines to current *** guidelines include a proposed empirically optimum guideline derived from a t-SNE hyperparameter grid search over a large collection of data *** also introduce a new method to featurize data sets using graph-based metrics called scagnostics;we use these features to train a neural network that predicts optimal t-SNE hyperparameters for the respective data *** neural network has the potential to simplify the use of t-SNE by removing guesswork about which hyperparameters will produce the best *** evaluate and compare our neural network-derived and empirically optimum hyperparameters to several other t-SNE hyperparameter guidelines from the literature on 68 data *** hyperparameters predicted by our neural network yield embeddings with similar accuracy as the best current t-SNE *** our empirically optimum hyperparameters is simpler than following previously published guidelines but yields more accurate embeddings,in some cases by a statistically significant *** find that the useful ranges for t-SNE hyperparameters are narrower and include smaller values than previously reported in the ***,we also quantify the potential for future improvements in this area:using data from a grid search of t-SNE hyperparameters we find that an optimal selection method could improve embedding accuracy by up to two percentage points over the methods examined in this paper.

关键词： Dimensionality reduction Machine learning t-SNE

Anosov and expanding attractors

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Science China Mathematics 2020年第9期63卷 1929-1934页

作者： robert f.Williams Department of Mathematics University of Texas at AustinAustinTX 78705USA Institute for Advanced Study PrincetonNJ 08540USA

An earlier conjecture is settled with an immersion of a 2-dimensional branched *** obstructions in linear algebra and tiling theory are studied rst.

关键词： Anosov expanding attractor Cantor set ber bundle

Predicting global landslide spatiotemporal distribution:Integrating landslide susceptibility zoning techniques and real-time satellite rainfall estimates

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International Journal of Sediment Research 2008年第3期23卷 249-257页

作者： robert f. ADLER Senior Research Scientist Code 613.1 Laboratory for Atmospheres NASA/Goddard Space Flight Center Greenbelt MD 20771 U. S. ADr.

Landslides triggered by rainfall can possibly be foreseen in real time by jointly using rainfall intensity-duration thresholds and information related to land surface susceptibility. However, no system exists at either a national or a global scale to monitor or detect rainfall conditions that may trigger landslides due to the lack of sufficient ground-based observing network in many parts of the world. Recent advances in satellite remote sensing technology and increasing availability of high-resolution geospatial products around the globe have provided an unprecedented opportunity for such a study. In this paper, a framework for developing a preliminary real-time prediction system to identify where rainfall-triggered landslides will occur is proposed by combining two necessary components: surface landslide susceptibility and a real-time space-based rainfall analysis system (http://***). first, a global landslide susceptibility map is derived from a combination of semi-static global surface characteristics (digital elevation topography, slope, soil types, soil texture, land cover classification, etc.) using a GIS weighted linear combination approach. Second, an adjusted empirical relationship between rainfall intensity-duration and landslide occurrence is used to assess landslide hazards at areas with high susceptibility. A major outcome of this work is the availability for the first time of a global assessment of landslide hazards, which is only possible because of the utilization of global satellite remote sensing products. This preliminary system can be updated continuously using the new satellite remote sensing products. This proposed system, if pursued through wide interdisciplinary efforts as recommended herein, bears the promise to grow many local landslide hazard analyses into a global decision-making support system for landslide disaster preparedness and mitigation activities across the world.

关键词： Landslide Natural disasters Satellite remote sensing Real-time precipitation analysis Landslide susceptibility