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Tissue tropisms of avian influenza A viruses affect their spillovers from wild bird to domestic swine

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Tissue tropisms of avian influenza A viruses affect their sp...

作者： Xiaojian Zhang Fred L.Cunningham Lei Li Katie Hanson-Dorr Alicia Olivier Liyuan Liu Brandon S.Schmit Minhui Guan Jacqueline M.Nolting Andrew S.Bowman Mia Kim Torchetti Thomas J.DeLiberto Xiu-Feng Wan Missouri University Center for Research on Influenza Systems Biology (CRISB) University of Missouri Bond Life Sciences Center University of Missouri Department of Molecular Microbiology and Immunology School of Medicine University of Missouri Department of Basic Sciences College of Veterinary Medicine Mississippi State University Mississippi Field Station National Wildlife Research Center Wildlife Services Animal and Plant Health Inspection Service U.S. Department of Agriculture Department of Population and Pathobiology College of Veterinary Medicine Mississippi State University National Wildlife Disease Program Wildlife Services Animal and Plant Health Inspection Service U.S. Department of Agriculture Department of Veterinary Preventive Medicine The Ohio State University National Veterinary Services Laboratories Veterinary Services U.S. Department of Agriculture Department of Electrical Engineering & Computer Science College of Engineering University of Missouri Department of Pathobiology College of Veterinary Medicine University of Missouri MU Informatics Institute University of Missouri

Having both avian-like receptors (?±2,3-linked sialic acid, SA2,3Gal) and human-like receptors (?±2,6-linked sialic acid, SA2,6Gal), swine are proposed as??úmixing vessel??ùfor generating influenza pandemic strains. Laboratory experiments suggested all HA subtypes of influenza A virus (IAV) can infect swine. However, only sporadic cases of avian

关键词： Tissue tropisms of avian influenza A viruses affect their spillovers from wild bird to domestic swine

Surgical data science-from concepts toward clinical translation

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arXiv 2020年

作者： Maier-Hein, Lena Eisenmann, Matthias Sarikaya, Duygu März, Keno Collins, Toby Malpani, Anand Fallert, Johannes Feussner, Hubertus Giannarou, Stamatia Mascagni, Pietro Nakawala, Hirenkumar Park, Adrian Pugh, Carla Stoyanov, Danail Vedula, Swaroop S. Cleary, Kevin Fichtinger, Gabor Forestier, Germain Gibaud, Bernard Grantcharov, Teodor Hashizume, Makoto Heckmann-Nötzel, Doreen Kenngott, Hannes G. Kikinis, Ron Mündermann, Lars Navab, Nassir Onogur, Sinan Sznitman, Raphael Taylor, Russell H. Tizabi, Minu D. Wagner, Martin Hager, Gregory D. Neumuth, Thomas Padoy, Nicolas Collins, Justin Gockel, Ines Goedeke, Jan Hashimoto, Daniel A. Joyeux, Luc Lam, Kyle Leff, Daniel R. Madani, Amin Marcus, Hani J. Meireles, Ozanan Seitel, Alexander Teber, Dogu Ückert, Frank Müller-Stich, Beat P. Jannin, Pierre Speidel, Stefanie Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Medical Faculty Heidelberg University Heidelberg Germany Department of Computer Engineering Faculty of Engineering Gazi University Ankara Turkey LTSI Inserm UMR 1099 University of Rennes 1 Rennes France IRCAD Strasbourg France The Malone Center for Engineering in Healthcare The Johns Hopkins University BaltimoreMD United States KARL STORZ SE and Co. KG Tuttlingen Germany Department of Surgery Klinikum Rechts der Isar Technical University of Munich Munich Germany The Hamlyn Centre for Robotic Surgery Imperial College London London United Kingdom ICube University of Strasbourg CNRS France IHU Strasbourg Strasbourg France Altair Robotics Lab University of Verona Verona Italy Department of Surgery Anne Arundel Health System AnnapolisMD United States Johns Hopkins University School of Medicine BaltimoreMD United States Department of Surgery Stanford University School of Medicine StanfordCA United States Wellcome/EPSRC Centre for Interventional and Surgical Sciences University College London London United Kingdom Department for General Visceral and Transplantation Surgery Heidelberg University Hospital Heidelberg Germany The Sheikh Zayed Institute for Pediatric Surgical Innovation Children's National Hospital WashingtonDC United States The Perk Lab Queen's University KingstonON Canada University of Haute-Alsace Mulhouse France Faculty of Information Technology Monash University ClaytonVIC Australia University of Toronto TorontoON Canada The Li Ka Shing Knowledge Institute of St. Michael's Hospital TorontoON Canada Kyushu University Fukuoka Japan Kitakyushu Koga Hospital Fukuoka Japan Department of Radiology Brigham and Women's Hospital Harvard Medical School BostonMA United States Computer Aided Medical Procedures Technical University of Munich Munich Germany Department of Computer Science The Johns Hopkins University Baltim

Recent developments in data science in general and machine learning in particular have transformed the way experts envision the future of surgery. Surgical Data science (SDS) is a new research field that aims to improve the quality of interventional healthcare through the capture, organization, analysis and modeling of data. While an increasing number of data-driven approaches and clinical applications have been studied in the fields of radiological and clinical data science, translational success stories are still lacking in surgery. In this publication, we shed light on the underlying reasons and provide a roadmap for future advances in the field. Based on an international workshop involving leading researchers in the field of SDS, we review current practice, key achievements and initiatives as well as available standards and tools for a number of topics relevant to the field, namely (1) infrastructure for data acquisition, storage and access in the presence of regulatory constraints, (2) data annotation and sharing and (3) data analytics. We further complement this technical perspective with (4) a review of currently available SDS products and the translational progress from academia and (5) a roadmap for faster clinical translation and exploitation of the full potential of SDS, based on an international multi-round Delphi process. © 2020, CC BY.

关键词： Deep learning

Resonant photonic structures in porous silicon for biosensing 9

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Resonant photonic structures in porous silicon for biosensin...

Frontiers in Biological Detection: From Nanosensors to Systems IX

作者： Zhao, Yiliang Rodriguez, Gilberto A. Graham, Yasmin M. Cao, Tengfei Gaur, Girija Weiss, Sharon M. Interdisciplinary Graduate Program in Materials Science Vanderbilt University NashvilleTN37235 United States Department of Electrical Engineering and Computer Science Vanderbilt University NashvilleTN37235 United States Department of Mechanical Engineering University of Maryland Baltimore County BaltimoreMD21250 United States

ISBN: (数字)9781510606043

ISBN: (纸本)9781510606036

The formation of resonant photonic structures in porous silicon leverages the benefit of high surface area for improved molecular capture that is characteristic of porous materials with the advantage of high detection sensitivity that is a feature of resonant optical devices. This review provides an overview of the biosensing capabilities of a variety of resonant porous silicon photonic structures including microcavities, Bloch surface waves, ring resonators, and annular Bragg resonators. Detection sensitivities > 1000 nm/RIU are achieved for small molecule detection. The challenge of detecting molecules that approach and exceed the pore diameter is also addressed. © 2017 SPIE.

关键词： Porous silicon

A phase variable approach for improved rhythmic and non-rhythmic control of a powered knee-ankle prosthesis

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arXiv 2018年

作者： Rezazadeh, Siavash Quintero, David Divekar, Nikhil Reznick, Emma Gray, Leslie Gregg, Robert D. Department of Bioengineering University of Texas at Dallas RichardsonTX75080 United States School of Engineering San Francisco State University San FranciscoCA94132 United States Department of Health Care Sciences University of Texas Southwestern Medical Center DallasTX75390 United States Department of Electrical Engineering and Computer Science Robotics Institute University of Michigan Ann ArborMI48109 United States

Although there has been recent progress in control of multi-joint prosthetic legs for rhythmic tasks such as walking, control of these systems for non-rhythmic motions and general real-world maneuvers is still an open problem. In this article, we develop a new controller that is capable of both rhythmic (constant-speed) walking, transitions between speeds and/or tasks, and some common volitional leg motions. We introduce a new piecewise holonomic phase variable, which, through a finite state machine, forms the basis of our controller. The phase variable is constructed by measuring the thigh angle, and the transitions in the finite state machine are formulated through sensing foot contact along with attributes of a nominal reference gait trajectory. The controller was implemented on a powered knee-ankle prosthesis and tested with a transfemoral amputee subject, who successfully performed a wide range of rhythmic and non-rhythmic tasks, including slow and fast walking, quick start and stop, backward walking, walking over obstacles, and kicking a soccer ball. Use of the powered leg resulted in clinically significant reductions in amputee compensations for rhythmic tasks (including vaulting and hip circumduction) when compared to use of the take-home passive leg. In addition, considerable improvements were also observed in the performance for nonrhythmic tasks. The proposed approach is expected to provide a better understanding of rhythmic and non-rhythmic motions in a unified framework, which in turn can lead to more reliable control of multi-joint prostheses for a wider range of real-world tasks. Copyright © 2018, The Authors. All rights reserved.

关键词： Artificial limbs

NANOROBOTS: Intracellular manipulation and measurement with multipole magnetic tweezers

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science robotics 2019年第28期4卷

作者： Wang, X. Ho, C. Tsatskis, Y. Law, J. Zhang, Z. Zhu, M. Dai, C. Wang, F. Tan, M. Hopyan, S. McNeill, H. Sun, Y. Department of Mechanical and Industrial Engineering University of Toronto TorontoONM5S 3G8 Canada Institute of Biomaterials and Biomedical Engineering TorontoONM5S 3G9 Canada Lunenfeld-Tanenbaum Research Institute Mt. Sinai Hospital TorontoONM5G 1X5 Canada Program in Developmental and Stem Cell Biology Hospital for Sick Children TorontoONM5G 1X8 Canada HRG Central Institute of Robotics HIT Robot Group Harbin Heilongjiang150001 China Institute of Automation Chinese Academy of Sciences Beijing100190 China Division of Orthopaedic Surgery Hospital for Sick Children and University of Toronto TorontoONM5G 1X8 Canada Department of Developmental Biology Washington University School of Medicine St. LouisMO63108 United States Department of Electrical and Computer Engineering University of Toronto TorontoONM5S 3G4 Canada

The capability to directly interrogate intracellular structures inside a single cell for measurement and manipulation is important for understanding subcellular and suborganelle activities, diagnosing diseases, and developing new therapeutic approaches. Compared with measurements of single cells, physical measurement and manipulation of subcellular structures and organelles remain underexplored. To improve intracellular physical measurement and manipulation,we have developed amultipole magnetic tweezers system for micromanipulation involving submicrometer position control and piconewton force control of a submicrometermagnetic bead inside a single cell for measurement in different locations (spatial) and different time points (temporal). The beadwas three-dimensionally positioned in the cell using a generalized predictive controller that addresses the control challenge caused by the low bandwidth of visual feedback from high-resolution confocal imaging. The average positioning error was quantified to be 0.4 mm, slightly larger than the Brownianmotion-imposed constraint (0.31 mm). The system is also capable of applying a force up to 60 pN with a resolution of 4 pN for a period of time longer than 30 min. The measurement results revealed that significantly higher stiffness exists in the nucleus' major axis than in the minor axis. This stiffness polarity is likely attributed to the aligned actin filament. We also showed that the nucleus stiffens upon the application of an intracellularly applied force, which can be attributed to the response of structural protein lamin A/C and the intracellular stress fiber actin filaments. © 2019 The Authors.

关键词： Cells

Recurrent predictive state policy networks

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arXiv 2018年

作者： Hefny, Ahmed Marinho, Zita Sun, Wen Srinivasa, Siddhartha Gordon, Geoffrey Machine Learning Department Carnegie Mellon University Pittsburgh United States Robotics Institute Carnegie Mellon University Pittsburgh United States ISR/IT Instituto Superior Técnico Lisbon Portugal Paul G. Allen School of Computer Science & Engineering University of Washington Seattle United States

We introduce Recurrent Predictive State Policy (RPSP) networks, a recurrent architecture that brings insights from predictive state representations to reinforcement learning in partially observable environments. Predictive state policy networks consist of a recursive filter, which keeps track of a belief about the state of the environment, and a reactive policy that directly maps beliefs to actions, to maximize the cumulative reward. The recursive filter leverages predictive state representations (PSRs) (Rosencrantz & Gordon, 2004;Sun et al., 2016) by modeling predictive state —a prediction of the distribution of future observations conditioned on history and future actions. This representation gives rise to a rich class of statistically consistent algorithms (Hefny et al., 2018) to initialize the recursive filter. Predictive state serves as an equivalent representation of a belief state. Therefore, the policy component of the RPSP-network can be purely reactive, simplifying training while still allowing optimal behaviour. Moreover, we use the PSR interpretation during training as well, by incorporating prediction error in the loss function. The entire network (recursive filter and reactive policy) is still differentiable and can be trained using gradient based methods. We optimize our policy using a combination of policy gradient based on rewards (Williams, 1992) and gradient descent based on prediction error. We show the efficacy of RPSP-networks under partial observability on a set of robotic control tasks from OpenAI Gym. We empirically show that RPSP-networks perform well compared with memory-preserving networks such as GRUs, as well as finite memory models, being the overall Copyright © 2018, The Authors. All rights reserved.

关键词： Gradient methods

Dynamic path planning and replanning for mobile robots using RRT

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arXiv 2017年

作者： Connell, Devin La, Hung Manh Advanced Robotics and Automation Lab Department of Computer Science and Engineering University of Nevada Reno NV89519

It is necessary for a mobile robot to be able to efficiently plan a path from its starting, or current, location to a desired goal location. This is a trivial task when the environment is static. However, the operational environment of the robot is rarely static, and it often has many moving obstacles. The robot may encounter one, or many, of these unknown and unpredictable moving obstacles. The robot will need to decide how to proceed when one of these obstacles is obstructing it's path. A method of dynamic replanning using RRT* is presented. The robot will modify it's current plan when an unknown random moving obstacle obstructs the path. Various experimental results show the effectiveness of the proposed method. Copyright © 2017, The Authors. All rights reserved.

关键词： Mobile robots

The Design of Automatic Bird Data Capture Systems

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The Design of Automatic Bird Data Capture Systems

IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Chia-Yuan Lin Yi-Chun Lin Che-Jui Chang Chi-Feng Chen Ming-Fong Tsai Department of Information Engineering and Computer Science Feng Chia University Taiwan Information and Communications Research Laboratories Industrial Technology Research Institute Taiwan Industrial Ph.D. Program of Internet of Things Feng Chia University Taiwan Departrnent of Electronic Engineering National United University Taiwan

This paper implements an automatic bird data capture system which uploads data captured from social network websites to the server and stores them in the database. When using the Facebook API to capture data of interest, the system needs to filter the captured data to avoid false data storage. This paper takes building an automatic system that includes reinforcing the training database of the bird community as a top priority.

关键词： Birds Databases Facebook Machine learning Servers System implementation

Maximum Willis Coupling in Acoustic Scatterers

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Physical Review Letters 2018年第25期120卷 254301-254301页

作者： Li Quan Younes Ra’di Dimitrios L. Sounas Andrea Alù Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 USA Photonics Initiative Advanced Science Research Center City University of New York New York New York 10031 USA Physics Program Graduate Center City University of New York New York New York 10026 USA Department of Electrical Engineering City College of New York New York New York 10031 USA

Willis coupling in acoustic materials defines the cross-coupling between strain and velocity, analogous to bianisotropic phenomena in electromagnetics. While these phenomena have been garnering significant attention in recent years, to date their effects have been considered mostly perturbative. Here, we derive general bounds on the Willis response of acoustic scatterers, show that these bounds can be reached in suitably designed scatterers, and outline a systematic venue for the realistic implementation of maximally bianisotropic acoustic inclusions. We then employ these inclusions to realize acoustic metasurfaces for bending and steering of sound with unitary efficiency.

关键词： Acoustic metamaterials Acoustic wave phenomena Acoustics Mechanical & acoustical properties