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arXiv 2024年

作者： Bouvet, Pierre Bevilacqua, Carlo Ambekar, Yogeshwari Antonacci, Giuseppe Au, Joshua Caponi, Silvia Chagnon-Lessard, Sophie Czarske, Juergen Dehoux, Thomas Fioretto, Daniele Fu, Yujian Guck, Jochen Hamann, Thorsten Heinemann, Dag Jähnke, Torsten Jean-Ruel, Hubert Kabakova, Irina Koski, Kristie Koukourakis, Nektarios Krause, David La Cavera, Salvatore Landes, Timm Li, Jinhao Margueritat, Jeremie Mattarelli, Maurizio Monaghan, Michael Overby, Darryl R. Perez-Cota, Fernando Pontecorvo, Emanuele Prevedel, Robert Ruocco, Giancarlo Sandercock, John Scarcelli, Giuliano Scarponi, Filippo Testi, Claudia Török, Peter Vovard, Lucie Weninger, Wolfgang Yakovlev, Vladislav Yun, Seok-Hyun Zhang, Jitao Palombo, Francesca Bilenca, Alberto Elsayad, Kareem Center for Anatomy and Cell Biology Medical University of Vienna Austria Cell Biology and Biophysics Unit European Molecular Biology Laboratory Germany Fischell Department of Bioengineering University of Maryland United States Specto Srl. Milan Italy Unità di Perugia Italy LightMachinery Inc. Canada Departement of Electronics Carleton University Canada TU Dresden Germany Cluster of Excellence Physics of Life TU Dresden Germany Competence Center for Biomedical Computational Laser Systems TU Dresden Germany Institut Lumière Matière UMR5306 Université Lyon 1 CNRS Université de Lyon France Dipartimento di Fisica e Geologia Università di Perugia Italy Max Planck Institute for the Science of Light Erlangen Germany Department of Biology Norwegian University of Science and Technology Trondheim Norway Hannover Centre for Optical Technologies Leibniz University Hannover Germany CellSense Technologies GmbH Berlin Germany School of Mathematical and Physical Sciences University of Technology Sydney Australia Department of Chemistry University of California Davis United States Optics & Photonics Group Faculty of Engineering University of Nottingham United Kingdom Discipline of Mechanical Manufacturing & Biomedical Engineering Trinity College Dublin Ireland Department of Bioengineering Imperial College London United Kingdom CREST Optics S.p.A. Rome Italy Heidelberg Germany Center for Life Nano- & Neuro-Science Istituto Italiano di Tecnologia Rome Italy The Table Stable Ltd. Mettmenstetten Switzerland School of Physical & Mathematical Sciences Nanyang Technological University Singapore Nanyang Technological University Singapore Institute for Digital Molecular Analytics & Sciences Nanyang Technological University Singapore Department of Biomedical Engineering Texas A&M University United States Department of Electrical and Computer Engineering Texas A&M University United States Department of Physics and Astronomy Texas A&M University United States Harvard Me

Brillouin Light Scattering (BLS) spectroscopy is a non-invasive, non-contact, label-free optical technique that can provide information on the mechanical properties of a material on the sub-micron scale. Over the last decade it has seen increased applications in the life sciences, driven by the observed significance of mechanical properties in biological processes, the realization of more sensitive BLS spectrometers and its extension to an imaging modality. As with other spectroscopic techniques, BLS measurements not only detect signals characteristic of the investigated sample, but also of the experimental apparatus, and can be significantly affected by measurement conditions. The aim of this consensus statement is to improve the comparability of BLS studies by providing reporting recommendations for the measured parameters and detailing common artifacts. Given that most BLS studies of biological matter are still at proof-of-concept stages and use different-often self-built-spectrometers, a consensus statement is particularly timely to assure unified advancement. © 2024, CC BY.

关键词： Brillouin scattering

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Phase transition in magic with random quantum circuits

arXiv

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arXiv 2023年

作者： Niroula, Pradeep White, Christopher David Wang, Qingfeng Johri, Sonika Zhu, Daiwei Monroe, Christopher Noel, Crystal Gullans, Michael J. Joint Center for Quantum Information and Computer Science University of Maryland and NIST College ParkMD20742 United States Joint Quantum Institute University of Maryland and NIST College ParkMD20742 United States Chemical Physics Program Institute for Physical Science and Technology University of Maryland College ParkMD20742 United States IonQ Inc. College ParkMD20740 United States Duke Quantum Center Department of Electrical & Computer Engineering Department of Physics Duke University DurhamNC27701 United States

Magic is a property of quantum states that enables universal fault-tolerant quantum computing using simple sets of gate operations. Understanding the mechanisms by which magic is created or destroyed is, therefore, a crucial step towards efficient and practical fault-tolerant computation. We observe that a random stabilizer code subject to coherent errors exhibits a phase transition in magic, which we characterize through analytic, numeric and experimental probes. Below a critical error rate, stabilizer syndrome measurements remove the accumulated magic in the circuit, effectively protecting against coherent errors;above the critical error rate syndrome measurements concentrate magic. A better understanding of such rich behavior in the resource theory of magic could shed more light on origins of quantum speedup and pave pathways for more efficient magic state generation. © 2023, CC BY.

关键词： Random errors

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Sag and Flicker Reduction Using Hysteresis-Fuzzy Control-Based SMES Unit

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Canadian Journal of electrical and computer engineering 2019年第1期42卷 52-57页

作者： Yunus, A. M. Shiddiq Habriansyah, Imran Abu-Siada, Ahmed Masoum, Mohammad A.S. Energy Conversion Study Program Mechanical Engineering Department State Polytechnic of Ujung Pandang Makassar90245 Indonesia Mechatronics Study Program Mechanical Engineering Department State Polytechnic of Ujung Pandang Makassar90245 Indonesia Electrical and Computer Engineering Department University of Curtin University BentleyWA6102 United States Department of Engineering Utah Valley University OremUT84058 United States

The issue of power quality is one of the prominent factors in determining the reliability of power systems. It is inevitable to consider power quality issues and include appropriate mitigation techniques in the design of any future power system project construction. Voltage sag and flicker are the two most common short disturbance types of power quality issues that frequently occur in power systems. A widely accepted mitigation strategy to enhance the power quality of disturbed networks is by connecting a flexible ac transmission system. In this paper, a superconducting magnetic energy storage (SMES) unit along with hysteresis-fuzzy controller to suppress the severe impacts of voltage sag and flicker events on the power quality of a power system is proposed, implemented, and tested. The proposed SMES configuration with hysteresis current control and fuzzy logic controller is effective, simple, and easy to implement. Simulation results show the ability of the proposed SMES controller in compensating sag and/or flicker distortions. © 2003-2010 IEEE Canada.

关键词： Power quality

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Dynamic Time-Over-Threshold Readout for Improved Energy Linearity in PET Detectors that Achieve 100 ps CTR

Dynamic Time-Over-Threshold Readout for Improved Energy Line...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Shirin Pourashraf Andrea Gonzalez-Montoro Joshua W. Cates Zhixiang Zhao Jun Yeon Won Jae Sung Lee Craig S. Levin Department of Radiology Stanford University Stanford USA Applied Nuclear Physics Program at Lawrence Berkeley National Laboratory Berkeley USA School of Biomedical Engineering Shanghai Jiao Tong University Shanghai People's Republic of China Department of Nuclear Medicine and Biomedical Sciences Seoul National University Seoul South Korea Departments of Radiology Bioengineering Physics and Electrical Engineering Molecular Imaging Program Stanford University Stanford CA 94305

ISBN: (数字)9781665421133

ISBN: (纸本)9781665421140

We have embedded a dynamic time-over-threshold (DynTOT) block in our scalable TOF-PET detector readout electronics to linearize the multiplexed energy spectra while keeping 100 ps FWHM Coincidence Time Resolution (CTR) performance. This DynTOT block is constructed by off-the-shelve components and consumes only 20 mW power per detector ‘layer’ in our design. Using 3×3×10 mm³ "LGSO" crystals coupled to arrays of 3×3 mm² SiPMs, energy resolution of 13.8±0.1%, 13.9±0.3%, and 17.1±0.6% were experimentally achieved for conventional pulse height, DynTOT, and conventional TOT methods, respectively. Including the DynTOT method, coincidence data were experimentally acquired using a low jitter FPGA-based TDC, and 103.6 ± 1.1 ps FWHM CTR was achieved, demonstrating the robustness of our novel and scalable timing electronic chain.

关键词： Multiplexing Energy resolution Linearity Detectors Crystals Jitter Robustness

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Machine learning full 3-D lower-body kinematics and kinetics on patients with osteoarthritis from electromyography

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biomedical engineering Advances 2023年 5卷

作者： Richard Byfield Matthew Guess Kianoosh Sattari Yunchao Xie Trent Guess Jian Lin Department of Mechanical and Aerospace Engineering George W. Woodruff School of Mechanical Engineering and the Center for Human-Centric Interfaces and Engineering Institute for Electronics and Nanotechnology Georgia Institute of Technology Atlanta USA 30332 Department of Physical Therapy Department of Orthopedic Surgery Department of Electrical Engineering and Computer Science Department of Biomedical Biological and Chemical Engineering University of Missouri Columbia USA 65211

Osteoarthritis (OA) is a degenerative disease that causes severe pain and reduces the range of motion of the joint, decreasing the quality of life for millions of individuals in the United States. Electromyography (EMG) sensors have been widely studied in biomechanics, showing applications in prosthetics, robotics, and control. While complex musculoskeletal models have been well established, the attempt of directly correlating EMG with kinematics and kinetics is still quite limited. Particularly, little work has been conducted on OA patients. In this work, we propose a method for estimating lower body joint angles (JAs) and ground reaction forces (GRFs) from surface-EMG sensors during a step-down task for individuals diagnosed with OA. The JAs and GRFs were measured by a Vicon motion capture system and force plates, respectively. EMG, JAs, and GRFs were used to train an echo state network (ESN) which afforded JAs with relative errors of 3.78% and 3.71% and the GRFs with relative errors of 3.619% and 4.596% for training and testing datasets, respectively. This study suggests the high fidelity of the ESN in automatically predicting full lower body kinematics and kinetics from the EMG signals. The results of this work promote the development of an EMG-controlled lower limb rehabilitation robot system for patients with OA.

关键词： Echo state network Electromyography Kinematics Kinetics Machine learning Osteoarthritis

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Stimulated Raman scattering signal generation in a scattering medium using self-reconstructing Bessel beams

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Photonics Research 2020年第6期8卷 929-939页

作者： XUELI CHEN XINYU WANG LIN WANG PENG LIN YONGHUA ZHAN JI-XIN CHENG Engineering Research Center of Molecular&Neuro Imaging Minitry of EducationXi'an 710126China School of Life Science and Technology Xidian UniversityXi'an 710126China School of Information Sciences and Technology Northwest UniversityXi'an 710127China Department of Electrical and Computer Engineering&Biomedical Engineering Boston UniversityBostonMassachusetts 02215USA

Scattering is a huge challenge for microscopic ***,it is difficult to observe target chemicals in scattering media by means of the current Gaussian beam-based stimulated Raman scattering(SRS)microscopy,since the tight focus of the Gaussian beam is destroyed after propagating through a certain *** beams,featuring self-reconstructing property,may bring a solution to this *** combining Bessel beams with SRS microscopy,we can probe the SRS signal from a scattering *** this paper,using the beam propagation method,we first simulate the propagation of the Bessel beam as well as the generation and self-reconstruction of SRS *** adding glass beads along the beam propagation path in order to simulate scattering,the propagation of the Bessel beams and the generation of the SRS signals will ***,we design a series of simulations to investigate the influence of the size,position,number,and distribution of the added glass beads on the generation of the SRS signals.A preliminary experiment is also carried out to confirm the simulation *** demonstrate that the SRS signals can be generated or be recovered at a certain depth in scattering media,and that such signals are greatly affected by the parameters of the scatters.

关键词： Bessel beads destroyed

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Uncertainty-aware semi-supervised method using large unlabelled and limited labeled COVID-19 data

arXiv

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arXiv 2021年

作者： Alizadehsani, Roohallah Sharifrazi, Danial Izadi, Navid Hoseini Joloudari, Javad Hassannataj Shoeibi, Afshin Gorriz, Juan M. Hussain, Sadiq Arco, Juan E. Sani, Zahra Alizadeh Khozeimeh, Fahime Khosravi, Abbas Nahavandi, Saeid Islam, Sheikh Mohammed Shariful Acharya, U. Rajendra Deakin University Geelong Australia Department of Computer Engineering School of Technical and Engineering Shiraz Branch Islamic Azad University Shiraz Iran Dept. of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran Department of Computer Engineering Faculty of Engineering University of Birjand Birjand Iran Computer Engineering Department Ferdowsi University of Mashhad Mashhad Iran Faculty of Electrical and Computer Engineering Biomedical Data Acquisition Lab K. N. Toosi University of Technology Tehran Iran Department of Signal Theory Networking and Communications Universidad de Granada Spain System Administrator Dibrugarh University Assam786004 India Rajaie Cardiovascular Medical and Research Center Iran University of Medical Sciences Tehran Iran Omid Hospital Iran University of Medical Sciences Tehran Iran Institute for Physical Activity and Nutrition Deakin University Melbourne Australia Cardiovascular Division The George Institute for Global Health Australia Sydney Medical School University of Sydney Australia Department of Electronics and Computer Engineering Ngee Ann Polytechnic Singapore Singapore Department of Biomedical Engineering School of Science and Technology Singapore University of Social Sciences Singapore Singapore Department of Bioinformatics and Medical Engineering Asia University Taiwan

The new coronavirus has caused more than 1 million deaths and continues to spread rapidly. This virus targets the lungs, causing respiratory distress which can be mild or severe. The X-ray or computed tomography (CT) images of lungs can reveal whether the patient is infected with COVID-19 or not. Many researchers are trying to improve COVID-19 detection using artificial intelligence. In this paper, relying on Generative Adversarial Networks (GAN), we propose a Semi-supervised Classification using Limited Labelled Data (SCLLD) for automated COVID-19 detection. Our motivation is to develop learning method which can cope with scenarios that preparing labelled data is time consuming or expensive. We further improved the detection accuracy of the proposed method by applying Sobel edge detection. The GAN discriminator output is a probability value which is used for classification in this work. The proposed system is trained using 10,000 CT scans collected from Omid hospital. Also, we validate our system using the public dataset. The proposed method is compared with other state of the art supervised methods such as Gaussian processes. To the best of our knowledge, this is the first time a COVID-19 semi-supervised detection method is presented. Our method is capable of learning from a mixture of limited labelled and unlabelled data where supervised learners fail due to lack of sufficient amount of labelled data. Our semi-supervised training method significantly outperforms the supervised training of Convolutional Neural Network (CNN) in case labelled training data is scarce. Our method has achieved an accuracy of 99.60%, sensitivity of 99.39%, and specificity of 99.80% where CNN (trained supervised) has achieved an accuracy of 69.87%, sensitivity of 94%, and specificity of 46.40%. Copyright © 2021, The Authors. All rights reserved.

关键词： Generative adversarial networks

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Performance limits due to thermal transport in graphene single-photon bolometers

arXiv

引用

arXiv 2023年

作者： Fried, Caleb Jordan Russell, B. Arnault, Ethan G. Huang, Bevin Lee, Gil-Ho Englund, Dirk Henriksen, Erik A. Fong, Kin Chung Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Earth and Planetary Sciences Harvard University CambridgeMA02138 United States Department of Physics Harvard University CambridgeMA02138 United States Raytheon BBN Quantum Engineering and Computing Group CambridgeMA02138 United States Department of Physics Washington University in St. Louis St. LouisMO United States Intelligence Community Postdoctoral Research Fellowship Program Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics Pohang University of Science and Technology Pohang790-784 Korea Republic of

In high-sensitivity bolometers and calorimeters, the photon absorption often occurs at a finite distance from the temperature sensor to accommodate antennas or avoid the degradation of superconducting circuitry exposed to radiation. As a result, thermal propagation from the input to the temperature readout can critically affect detector performance. In this report we model the performance of a graphene bolometer, accounting for electronic thermal diffusion and dissipation via electron-phonon coupling at low temperatures in three regimes: clean, supercollision, and resonant scattering. Our results affirm the feasibility of a superconducting readout without Cooper-pair breaking by mid- and near-infrared photons, and provide a recipe for designing graphene absorbers for calorimetric single-photon detectors. We investigate the tradeoff between the input-readout distance and detector efficiency, and predict an intrinsic timing jitter of ∼2.7 ps. Based on our result, we propose a spatial-mode-resolving photon detector to increase communication bandwidth. Copyright © 2023, The Authors. All rights reserved.

关键词： Graphene

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A Composite Material Based Neural Network for Tissue Mechanical Properties Estimation Toward Stage Assessment of Infarction

A Composite Material Based Neural Network for Tissue Mechani...

引用

Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Sergio Dempsey Parya Jafari Aaron So Abbas Samani School of Biomedical Engineering at Western University London ON CAN Interaptix Toronto ON CAN Department of Medical Biophysics Imaging Program at Lawson Health Research Institute at Western University London ON CAN Department of Electrical and Computer Engineering Department of Medical Biophysics and The School of Biomedical Engineering Western University London ON CAN

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

Cardiac biomechanical modelling is a promising new tool to be used in prognostic medicine and therapy planning for patients suffering from a variety of cardiovascular diseases and injuries. In order to have an accurate biomechanical model, personalized parameters to define loading, boundary conditions and mechanical properties are required. Achieving personalized modelling parameters often requires inverse optimization which is computationally expensive; hence techniques to reduce the multivariable complexity are in need. Presented in this paper is the fundamental blueprint to create a library of scar tissue mechanical properties to be used in modelling the healing mechanics of hearts that have suffered acute myocardial infarction. This library can be used to reduce the number of variables necessary to capture the scar tissue mechanical properties down to 1. This single parameter also carries information pertaining to staging of the scar tissue healing, predict its rate, and predict its collagen density. This information can be potentially used as valuable biomarkers to adjust existing or develop new treatment plans for patients.

关键词： Mechanical factors Biological system modeling Myocardium Predictive models Neural networks Computational modeling Fibroblasts

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New Closed-form Joint Localization and Synchronization using Sequential One-way TOAs

arXiv

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arXiv 2021年

作者： Guo, Ningyan Zhao, Sihao Zhang, Xiao-Ping Yao, Zheng Cui, Xiaowei Lu, Mingquan The School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China The Department of Electronic Engineering Tsinghua University Beijing100084 China The Department of Electrical Computer and Biomedical Engineering Ryerson University TorontoONM5B 2K3 Canada The Department of Electronic Engineering Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China

It is an essential technique for the moving user nodes (UNs) with clock offset and clock skew to resolve the joint localization and synchronization (JLAS) problem. Existing iterative maximum likelihood methods using sequential one-way time-of-arrival (TOA) measurements from the anchor nodes' (AN) broadcast signals require a good initial guess and have a computational complexity that grows with the number of iterations, given the size of the problem. In this paper, we propose a new closed-form JLAS approach, namely CFJLAS, which achieves the asymptotically optimal solution in one shot without initialization when the noise is small, and has a low computational complexity. After squaring and differencing the sequential TOA measurement equations, we devise two intermediate variables to reparameterize the non-linear problem. In this way, we convert the problem to a simpler one of solving two simultaneous quadratic equations. We then solve the equations analytically to obtain a raw closed-form JLAS estimation. Finally, we apply a weighted least squares (WLS) step to optimize the estimation. We derive the Cramér-Rao lower bound (CRLB), analyze the estimation error, and show that the estimation accuracy of the CFJLAS reaches the CRLB under the small noise condition. The complexity of the new CFJLAS is only determined by the size of the problem, unlike the conventional iterative method, whose complexity is additionally multiplied by the number of iterations. Simulations in a 2D scene verify that the estimation accuracies of the new CFJLAS method in position, velocity, clock offset, and clock skew all reach the CRLB under the small noise condition. Compared with the conventional iterative method, which requires a proper initialization to converge and has a growing complexity with more iterations, the proposed new CFJLAS method does not require initialization, obtains the optimal solution under the small noise condition, and has a low computational complexity. © 2021, CC BY-NC

关键词： Iterative methods

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