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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Qian Dong Brian J. Lee Chen-Ming Chang Ilaria Sacco Ronald D. Watkins Peter Fischer Emily Anaya Craig S. Levin Departments of Electrical Engineering and Radiology Stanford University Stanford CA USA Departments of Mechanical Engineering and Radiology Stanford University Stanford CA USA Departments of Applied Physics and Radiology Stanford University Stanford CA USA Department of Radiology Stanford University Stanford CA USA Department of Computer Science Heidelberg University Mannheim Germany Departments of Radiology Electrical Engineering Bioengineering and Physics Stanford University and Molecular Imaging Program at Stanford (MIPS) Stanford CA USA

ISBN: (数字)9781728141640

ISBN: (纸本)9781728141657

Simultaneous PET/MRI combines two powerful and complementary modalities, providing multiparametric information to assess the anatomic as well as biochemical basis of disease. However, the high cost of the current commercial integrated PET/MRI systems limit the long-term potential, accessibility, and availability of PET/MRI. A portable PET insert provides a cost- effective alternative to achieve simultaneous PET/MRI for the sites that are already equipped with MR systems. Therefore, we are developing a radiofrequency (RF)-penetrable MR-compatible time-of-flight (TOF)-PET insert that can acquire simultaneous PET/MR data using the MR systems built-in body coil for RF transmission. In this study, we characterized performance of two detector modules in the MR bore under four different MRI conditions: B 0 only, echo planar imaging (EPI), gradient echo (GRE), and fast spin echo (FSE), each running for 15 minutes. The one-hour study results for coincidence timing resolution, energy resolution, coincidence count rate and ASIC chip temperature of two detector modules demonstrate the PET performance stability as well as the MR compatibility of the PET detectors under different MRI sequences. The global coincidence timing and energy resolution achieved was 264.21 ± 4.82 ps FWHM and 13.66 ± 0.08 % FWHM, respectively.

关键词： Detectors Clocks Energy resolution Magnetic resonance imaging Timing Positron emission tomography Radio frequency

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Prosthetic hand signals

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Significance 2018年第4期15卷 30-35页

作者： Mike Wininger Reva Johnson PhD has faculty appointments at the University of Hartford (Prosthetics Program) and Yale University (Department of Biostatistics) and is a statistician of clinical trials with the Department of Veterans Affairs. PhD is a professor in the Department of Mechanical Engineering and Bioengineering at Valparaiso University.

How Bayesian inference can decode movement intentions and control the next generation of powered prostheses. By Mike Wininger and Reva Johnson

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Considering discrepancy when calibrating a mechanistic electrophysiology model

arXiv

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arXiv 2020年

作者： Lei, Chon Lok Ghosh, Sanmitra Whittaker, Dominic G. Aboelkassem, Yasser Beattie, Kylie A. Cantwell, Chris D. Delhaas, Tammo Houston, Charles Novaes, Gustavo Montes Panfilov, Alexander V. Pathmanathan, Pras Riabiz, Marina Weber dos Santos, Rodrigo Worden, Keith Mirams, Gary R. Wilkinson, Richard D. Computational Biology & Health Informatics Dept. of Computer Science University of Oxford United Kingdom MRC Biostatistics Unit University of Cambridge United Kingdom Centre for Mathematical Medicine & Biology School of Mathematical Sciences University of Nottingham United Kingdom Department of Bioengineering University of California San Diego United States Systems Modeling and Translational Biology GlaxoSmithKline R&D Stevenage United Kingdom ElectroCardioMaths Programme Centre for Cardiac Engineering Imperial College London United Kingdom CARIM School for Cardiovascular Diseases Maastricht University Netherlands Graduate Program in Computational Modeling Universidade Federal de Juiz de Fora Brazil Department of Physics and Astronomy Ghent University Belgium Laboratory of Computational Biology and Medicine Ural Federal University Ekaterinburg Russia U.S. Food and Drug Administration Center for Devices and Radiological Health Office of Science and Engineering Laboratories United States Department of Biomedical Engineering King’s College London Alan Turing Institute United Kingdom Dynamics Research Group Department of Mechanical Engineering University of Sheffield United Kingdom School of Mathematics and Statistics University of Sheffield United Kingdom

Uncertainty quantification (UQ) is a vital step in using mathematical models and simulations to take decisions. The field of cardiac simulation has begun to explore and adopt UQ methods to characterise uncertainty in model inputs and how that propagates through to outputs or predictions. In this perspective piece we draw attention to an important and under-addressed source of uncertainty in our predictions — that of uncertainty in the model structure or the equations themselves. The difference between imperfect models and reality is termed model discrepancy, and we are often uncertain as to the size and consequences of this discrepancy. Here we provide two examples of the consequences of discrepancy when calibrating models at the ion channel and action potential scales. Furthermore, we attempt to account for this discrepancy when calibrating and validating an ion channel model using different methods, based on modelling the discrepancy using Gaussian processes (GPs) and autoregressive-moving-average (ARMA) models, then highlight the advantages and shortcomings of each approach. Finally, suggestions and lines of enquiry for future work are provided. Copyright © 2020, The Authors. All rights reserved.

关键词： Uncertainty analysis

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Nanostethoscopy: Atomic force microscopy probe contact force versus measured amplitude of cardiomyocytic contractions

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Journal of Bionanoscience 2017年第4期11卷 319-322页

作者： Vyas, Varun Nagarajan, Neerajha Zorlutuna, Pinar Huey, Bryan D. Institute of Materials Science University of Connecticut StorrsCT06269 United States Department of Aerospace and Mechanical Engineering Bioengineering Graduate Program University of Notre Dame Notre DameIN46556 United States

Cardiomyocytes are one of the most active cells in the human body. Understanding their mechanical contractions via nanostethoscopy has given us better insight into the subtleties of contractions. There is extensive data available on the temporal behavior of contraction in a cardiomyocytes but little is known about how contact force of the AFM probe influences the measurement force of contractions i.e., mean beat force. This investigation suggests that in order to accurately measure mean beat force nanostethoscopy data should be analyzed from the lowest to the highest contact force. In this study optimal contact force was varied from 10 nN to 500 nN and it was observed that the maximum contraction i.e., mean beat force was highest at contact force of 250 nN. © 2017 American Scientific Publishers.

关键词： Atomic force microscopy

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The control of brain network dynamics across diverse scales of space and time

arXiv

引用

arXiv 2019年

作者： Tang, Evelyn Baum, Graham L. Roalf, David R. Satterthwaite, Theodore D. Pasqualetti, Fabio Bassett, Danielle S. Department of Bioengineering School of Engineering & Applied Science University of Pennsylvania PA19104 United States Max Planck Institute for Dynamics and Self-Organization Göttingen37079 Germany Neuroscience Graduate Program Perelman School of Medicine University of Pennsylvania PA19104 United States Department of Psychiatry Perelman School of Medicine University of Pennsylvania PA19104 United States Department of Mechanical Engineering University of California Riverside RiversideCA92521 United States Department of Physics & Astronomy College of Arts & Sciences University of Pennsylvania PA19104 United States Department of Electrical & Systems Engineering School of Engineering & Applied Science University of Pennsylvania PA19104 United States Department of Neurology Perelman School of Medicine University of Pennsylvania PA19104 United States

The human brain is composed of distinct regions that are each associated with particular functions and distinct propensities for the control of neural dynamics. However, the relation between these functions and control profiles is poorly understood, as is the variation in this relation across diverse scales of space and time. Here we probe the relation between control and dynamics in brain networks constructed from diffusion tensor imaging data in a large community based sample of young adults. Specifically, we probe the control properties of each brain region and investigate their relationship with dynamics across various spatial scales using the Laplacian eigenspectrum. In addition, through analysis of regional modal controllability and partitioning of modes, we determine whether the associated dynamics are fast or slow, as well as whether they are alternating or monotone. We find that brain regions that facilitate the control of energetically easy transitions are associated with activity on short length scales and slow time scales. Conversely, brain regions that facilitate control of difficult transitions are associated with activity on long length scales and fast time scales. Built on linear dynamical models, our results offer parsimonious explanations for the activity propagation and network control profiles supported by regions of differing neuroanatomical structure. Copyright © 2019, The Authors. All rights reserved.

关键词： Brain

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Analysis of Bone Remodeling Under Piezoelectricity Effects Using Boundary Elements

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Journal of Bionic engineering 2017年第4期14卷 659-671页

作者： Miguel Cerrolaza Vannessa Duarte Diego Garzon-Alvarado National Institute of Bioengineering Central University of Venezuela Caracas Venezuela International Center for Numerical Methods in Engineering ( CIMNE) Polytechnic University of Catalonia Barcelona Spain Virtual Rooms Program ( CIMNE) Polytechnic University of Catalonia Barcelona Spain Laboratory of Biomimetics Group of Mechanobiology of Organs and Tissues Biotechnology Institute Department of Mechanical Engineering and Mechatronics National University of Colombia Bogota Colombia

Piezoelectric materials exhibit a response to mechanical-electrical coupling, which represents an important contribution to the electrical-mechanical interaction in bone remodeling process. Therefore, the study of the piezoelectric effect on bone re- modeling has high interest in applied biomechanics. The effects of mechano-regulation and electrical stimulation on bone healing are explained. The Boundary Element Method （BEM） is used to simulate piezoelectric effects on bones when shearing forces are applied to collagen fibers to make them slip past each other. The piezoelectric fundamental solutions are obtained by using the Radon transform. The Dual Reciprocity Method （DRM） is used to simulate the particular solutions in time-dependent problems. BEM analysis showed the strong influence of electrical stimulation on bone remodeling. The examples discussed in this work showed that, as expected, the electrically loaded bone surfaces improved the bone deposition. BEM results confirmed previous findings obtained by using the Finite Element Method （FEM）. This work opens very promising doors in biomechanics research, showing that mechanical loads can be replaced, in part, by electrical charges that stimulate strengthening bone density. The obtained results herein are in good agreement with those found in literature from experimental testing and/or other simu- lation approaches.

关键词： bone remodeling numerical methods piezoelectricity boundary element anisotropy

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Self-learning how to swim at low Reynolds number

arXiv

引用

arXiv 2018年

作者： Tsang, Alan Cheng Hou Tong, Pun Wai Nallan, Shreyes Pak, On Shun Department of Bioengineering Stanford University StanfordCA94305 United States Clinical Genomics Program Stanford Health Care StanfordCA94305 United States Department of Mechanical Engineering Santa Clara University Santa ClaraCA95053 United States

Synthetic microswimmers show great promise in biomedical applications such as drug delivery and microsurgery. Their locomotion, however, is subject to stringent constraints due to the dominance of viscous over inertial forces at low Reynolds number (Re) in the microscopic world. Furthermore, locomotory gaits designed for one medium may become ineffective in a different medium. Successful biomedical applications of synthetic microswimmers rely on their ability to traverse biological environments with vastly different properties. Here we leverage the prowess of machine learning to present an alternative approach to designing low Re swimmers. Instead of specifying any locomotory gaits a priori, here a swimmer develops its own propulsion strategy based on its interactions with the surrounding medium via reinforcement learning. This self-learning capability enables the swimmer to modify its propulsion strategy in response to different environments. We illustrate this new approach using a minimal example that integrates a standard reinforcement learning algorithm (Q-learning) into the locomotion of a swimmer consisting of an assembly of spheres connected by extensible rods. We showcase theoretically that this first self-learning swimmer can recover a previously known propulsion strategy without prior knowledge in low Re locomotion, identify more effective locomotory gaits when the number of spheres increases, and adapt its locomotory gaits in different media. These results represent initial steps towards the design of a new class of self-learning, adaptive (or "smart") swimmers with robust locomotive capabilities to traverse complex biological environments. Copyright © 2018, The Authors. All rights reserved.

关键词： Propulsion

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Cytocompatible magnetostrictive microstructures for nano- A nd microparticle manipulation on linear strain response piezoelectrics

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Multifunctional Materials 2018年第1期1卷

作者： Xiao, Zhuyun Khojah, Reem Chooljian, Marc Conte, Roberto Lo Schneider, Joseph D. Fitzell, Kevin Chopdekar, Rajesh V. Wang, Yilian Scholl, Andreas Chang, Jane Carman, Gregory P. Bokor, Jeffrey Carlo, Dino Di Candler, Rob N. Department of Electrical and Computer Engineering University of California Los Angeles United States Department of Bioengineering University of California Los Angeles United States University of California Berkeley UCSF Graduate Program in Bioengineering Berkeley United States Department of Electrical Engineering and Computer Sciences University of California Berkeley United States Department of Mechanical and Aerospace Engineering University of California Los Angeles United States Department of Chemical and Biomolecular Engineering University of California Los Angeles United States Advanced Light Source Lawrence Berkeley National Laboratory Berkeley United States California Nanosystems Institute Los Angeles United States

In this work, we investigate polycrystalline Ni and FeGamagnetostrictivemicrostructures on prepoled (011)-cut single crystal [Pb(Mg1/3Nb2/3)O3]1-x-[PbTiO3]x (PMN-PT, x ≈ 0.31) with linear strain profile versus applied electric field. Magnetostrictive microstructure arrays with various geometries are patterned on PMN-PT. Functionalizedmagnetic beads are trapped by localized stray fields originating fromthe microstructures. With an applied electric field, themagnetic domains are actuated, inducing the motion of the coupled particles with sub-micrometer precision. This work shows promise of using energy-efficient electric-field-controlled magnetostrictivemicro- A nd nanostructures formanipulatingmagnetic beads via a linear strain response. The work also demonstrates the viability of cells suspended in solution on these structures when subject to applied electric fields, proving the cytocompatibility of the platform for live cell sorting applications. © 2018 IOP Publishing Ltd.

关键词： Electric fields

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A metasurface-inspired focusing collector for concentrated solar power applications

A metasurface-inspired focusing collector for concentrated s...

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Frontiers in Optics, FIO 2018

作者： Ding, Qing Barna, Shama Jacobs, Kyle Choubal, Aakash Mensing, Glennys Zhang, Zhong Yamada, Kaito Tirawat, Robert Kincaid, Nicholas Zhu, Guangdong Wendelin, Tim Guo, L. Jay Ferreira, Placid Toussaint, Kimani C. University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Mechanical Science and Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109-2102 United States Applied Physics Program University of Michigan Ann ArborMI48109 United States National Renewable Energy Lab. GoldenCO80401 United States Solar Dynamics LLC United States Department of Bioengineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States

We present a simple metasurface-inspired planar focusing collector for concentrated solar power. Fabrication is achieved using two-photon lithography, and subsequent nanoimprint lithography tests for scalability. Opti... 详细信息

ISBN: (纸本)9781943580460

关键词： Solar energy

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Drug Delivery: Injectable Drug‐Releasing Microporous Annealed Particle Scaffolds for Treating Myocardial Infarction (Adv. Funct. Mater. 43/2020)

引用

Advanced Functional Materials 2020年第43期30卷

作者： Jun Fang Jaekyung Koh Qizhi Fang Huiliang Qiu Maani M. Archang Mohammad Mahdi Hasani‐Sadrabadi Hiromi Miwa Xintong Zhong Richard Sievers Dong‐Wei Gao Randall Lee Dino Di Carlo Song Li Department of Bioengineering University of California Los Angeles CA 90095 USA Department of Medicine University of California Los Angeles CA 90095 USA Department of Medicine Cardiovascular Research Institute and Institute for Regeneration Medicine University of California San Francisco CA 94143 USA California NanoSystems Institute (CNSI) University of California Los Angeles CA 90095 USA UC Berkeley‐UCSF Graduate Program in Bioengineering University of California San Francisco San Francisco CA 94158 USA Department of Mechanical and Aerospace Engineering University of California Los Angeles CA 90095 USA Jonsson Comprehensive Cancer Centre University of California Los Angeles CA 90024 USA

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