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arXiv 2020年

作者： Ling, Yuye Wang, Mengyuan Gan, Yu Yao, Xinwen Schmetterer, Leopold Zhou, Chuanqing Su, Yikai John Hopcroft Center for Computer Science Shanghai Jiao Tong University Shanghai China Department of Electrical and Computer Engineering University of Alabama AL United States Singapore Institute for Health Technologies Nanyang Technological University Singapore Singapore Eye Research Institute Singapore National Eye Centre Singapore School of Chemical and Biomedical Engineering Nanyang Technological University Singapore Institute of Biomedical Engineering Shenzhen Bay Lab Shenzhen China School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China State Key Lab of Advanced Optical Communication Systems and Networks Department of Electronic Engineering Shanghai Jiao Tong University Shanghai China

Optical coherence tomography (OCT) is a volumetric imaging modality that empowers clinicians and scientists to noninvasively visualize and examine the microscopic cross-sectional architectures of biological samples. By taking advantage of the coherence gating, OCT could achieve micrometer-level axial sectioning with high sensitivity. In the past decade, substantial efforts have been made to push the axial resolution of Fourier-domain OCT (FD-OCT) further into the sub-micron regime by physically extending the system's spectral bandwidth. Here, we offer a new perspective on this problem with the help of a new theoretical framework. We identified a key limitation on the reconstruction's axial resolution, which is induced by the Fourier transform-based reconstruction algorithm. To break this limit, we presented a novel optimization-based algorithm to recover the super-resolution image from ordinary FD-OCT measurements with proper physical assumptions. To prove the concept, we retrieved images at a resolution higher than the theoretical prediction in both phantoms and biological samples. Copyright © 2020, The Authors. All rights reserved.

关键词： Optical tomography

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Towards new forms of particle sensing and manipulation and 3D imaging on a smartphone for healthcare applications

arXiv

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arXiv 2020年

作者： Zhu, Jinlong Zhao, Ni Zhou, Renjie Photonic Systems Laboratory Holonyak Micro and Nanotechnology Laboratory Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Electronic Engineering Chinese University of Hong Kong Shatin New Territories Hong Kong Department of Biomedical Engineering Chinese University of Hong Kong Shatin New Territories Hong Kong Shun Hing Institute of Advanced Engineering Chinese University of Hong Kong Shatin New Territories Hong Kong

Close to half of the world population have smartphones, while a typical flagship smartphone today has been integrated with more than 20 smart components and sensors, making a smartphone a highly integrated platform that can potentially mimic the five senses of humans. Recent advancement in achieving high compactness, high performance computing, high flexibility, and multiplexed functionality in smartphones have enabled them for many cutting-edge healthcare applications, such as single-molecule imaging, medical diagnosis, and biosensing, which were conventionally done with bulky and sophisticated devices. Most of the current healthcare applications are developed based on using the photon-sensitive components, such as CMOS sensors, flash & fill lights, lens modules, and LED lights in the screen, leaving the rest of the smart and high-performance sensors rarely explored. In this Perspective, we review recent progresses in advanced sensors in modern smartphones and discuss how those sensors have great, as yet unmet, promise to offer widespread and easy-to-implement solutions to many emerging healthcare applications, including nanoscale sensing, point-of-care testing, pollution monitoring, *** Codes 7811(Primary), 9201(Secondary) © 2020, CC-BY-NC-SA.

关键词： Smartphones

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Bit-Interleaved Coded OCDM with Nonlinear Equalization

Bit-Interleaved Coded OCDM with Nonlinear Equalization

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Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Xing Ouyang Giuseppe Talli Mark Power Mingwei Yang Ivan Djordjevic Paul Townsend Photonic Systems Group Tyndall National Institute Cork City Centre Ireland Department of Electrical and Computer Engineering The University of Arizona Tucson USA

We propose a bit-interleaved coded OCDM with nonlinear IB-DFE for IM/DD systems, and for the first time experimentally demonstrate a 31-Gbit/s KP4-coded OCDM signal over 50-km S-SMF achieving additional 5-dB coding ga... 详细信息

ISBN: (纸本)9781943580705

关键词： Capacity limits Optical communications Optical networks Optical signals Signal processing Variable optical attenuators

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TCAD model for TeraFET detectors operating in a large dynamic range

arXiv

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arXiv 2019年

作者： Liu, Xueqing Shur, Michael S. Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute 110 8th Street TroyNY12180 United States

We present technology computer-aided design (TCAD) models for AlGaAs/InGaAs and AlGaN/GaN and silicon TeraFETs, plasmonic field effect transistors (FETs), for terahertz (THz) detection validated over a wide dynamic range. The modeling results are in good agreement with the experimental data for the AlGaAs/InGaAs heterostructure FETs (HFETs) and, to the low end of the dynamic range, with the analytical theory of the TeraFET detectors. The models incorporate the response saturation effect at high intensities of the THz radiation observed in experiments and reveal the physics of the response saturation associated with different mechanisms for different material systems. These mechanisms include the gate leakage, the velocity saturation and the avalanche effect. Copyright © 2019, The Authors. All rights reserved.

关键词： Electronic design automation

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On diffusive non-reciprocity and thermal diode

arXiv

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arXiv 2019年

作者： Li, Ying Li, Jiaxin Qiu, Cheng-Wei Department of Electrical and Computer Engineering National University of Singapore Kent Ridge17583 Singapore State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China

Wave propagation and diffusion in linear materials preserve local reciprocity in terms of a symmetric Green's function. For wave propagations, people usually focus on the signals entering and leaving a system, and do not need detailed information about the fields inside it. In such cases, the global reciprocity of the scattering off a system through several ports is more important, which is defined as the symmetric transmission between the scattering channels. When a two-port system supports non-reciprocal (electromagnetic, acoustic) wave propagation, it is a (optical, phonon) diode directly following the definition. However, to date no clear definition or discussion has been made on the global reciprocity of diffusive processes through a system. It thus remains a question whether diffusive non-reciprocity is related with diode for diffusive fields, say, a thermal diode. Here, we provide theoretical analysis based on local reciprocity and define the global reciprocity of diffusion through a two-port system. We further prove the equivalence between a non-reciprocal heat transfer system and a thermal diode, and discuss some methods to realize it. Our results set a general background for future studies on symmetric and asymmetric diffusive processes. Copyright © 2019, The Authors. All rights reserved.

关键词： Acoustic wave propagation

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Modeling and Analysis of Data Center Power System Stability by Impedance Methods

Modeling and Analysis of Data Center Power System Stability ...

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IEEE Energy Conversion Congress and Exposition

作者： Jian Sun Mingchun Xu Mauricio Cespedes David Wong Mike Kauffman Department of Electrical Computer & Systems Engineering Rensselaer Polytechnic Institute Troy NY USA Facebook Inc. Menlo Park CA USA

This paper presents a study of recently experienced power system instability and resonance problems in large data centers using impedance modeling and analysis. The approach developed to analyze the problem consists of 1) modeling each power supply unit (PSU) by its input impedance and the power distribution network by an equivalent source impedance;2) converting the 3-phase system impedance model into separate positive-, negative-, and zero-sequence impedance models by ignoring asymmetries in the network impedance;3) determining system stability in each sequence based on the Nyquist criterion;and 4) applying matrix perturbation theory and eigenvalue analysis to account for network asymmetries. Inclusion of the zero-sequence model is necessary because of the use of a three-phase, four-wire distribution system and single-phase power supplies operating between phase and neutral. The analyses presented in the paper identifies zero sequence as the weakest link in which instability occurs first. The simplified system model and analysis also lead to new specs and design guidelines for data center power systems to assure stability. Laboratory and field measurements are presented to demonstrate the nature of this new problem and to validate the proposed method.

关键词： data center power systems power system stability impedance-based stability analysis impedance specifications

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Integrative characterization of MYC RNA-binding function

Cell Genomics

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Cell Genomics 2025年 100878页

作者： Li, Sihan Wang, Zehua Wang, Xiaofei Wang, Yifei Pattarayan, Dhamotharan Zhang, Yu Nguyen, Phuong Bhuniya, Avishek Chen, Yuang Huang, Haozhe Huang, Yixian Wang, Luxuan Wang, Junmei Li, Song Zhang, Min Liu, Yang Lee, Nara Yang, Da Center for Pharmacogenetics and Department of Pharmaceutical Sciences University of Pittsburgh Pittsburgh PA United States Department of Medicine University of Pittsburgh Pittsburgh PA United States UPMC Hillman Cancer Center University of Pittsburgh Pittsburgh PA United States Department of Bioengineering Department of Electrical and Computer Engineering Cancer Center at Illinois Beckman Institute for Advanced Science and Technology University of Illinois Urbana-Champaign Urbana IL United States Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center School of Pharmacy University of Pittsburgh Pittsburgh PA United States Department of Microbiology and Molecular Genetics University of Pittsburgh Pittsburgh PA United States Department of Computational and Systems Biology University of Pittsburgh Pittsburgh PA United States

Emerging evidence suggests that MYC interacts with RNAs. Here, we performed an integrative characterization of MYC as an RNA-binding protein in six cell lines. We found that MYC binds to a myriad of RNAs with high affinity for guanosine-rich RNAs. Global and specific depletion of RNAs reduces MYC chromatin occupancy. Mechanistically, two highly conserved sequences, amino acids 355–357 KRR and 364–367 RQRR, within the basic region of MYC are necessary for its RNA binding. Notably, alanine substitution of KRR abolishes MYC's RNA-binding ability both in vitro and in vivo, without affecting its ability to bind E-box DNA as part of the MYC:MAX dimer in vitro. The loss of RNA-binding function decreases MYC chromatin binding in vivo and attenuates its ability to promote gene expression, cell-cycle progression, and proliferation. Our study lays a foundation for future investigation into the role of RNAs in MYC-mediated transcriptional activation and oncogenic functions. © 2025 The Author(s)

关键词： arginine-rich motif CRISPR-Display eCLIP enhancer RNA gene regulation guanosine-rich RNA MYC rChIP RNA-binding protein (RBP) TF RNA binding

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Retraction notice to "A strategic review on sustainable approaches in municipal solid waste management and energy recovery: Role of artificial intelligence, economic stability and life cycle assessment" [Bioresour. Technol. 379 (2023) 129044]

引用

Bioresource technology 2025年 421卷 132185页

作者： Rajendiran Naveenkumar Jayaraj Iyyappan Ravichandran Pravin Seifedine Kadry Jeehoon Han Raveendran Sindhu Mukesh Kumar Awasthi Samuel Lalthazuala Rokhum Gurunathan Baskar Biological Systems Engineering University of Wisconsin-Madison Madison WI 53706 United States Forest Products Laboratory USDA Forest Service Madison WI 53726 United States. Department of Biotechnology Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Thandalam Chennai 602107 India. Department of Biotechnology St. Joseph's College of Engineering Chennai 600119 India. Department of Applied Data Science Noroff University College Kristiansand Norway Artificial Intelligence Research Center (AIRC) Ajman University Ajman 346 United Arab Emirates Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon. Department of Chemical Engineering Pohang University of Science and Technology Pohang 37673 Republic of Korea. Department of Food Technology TKM Institute of Technology Kollam Kerala India. College of Natural Resources and Environment Northwest A&F University Yangling Shaanxi Province 712100 China. Department of Chemistry National Institute of Technology Silchar 788010 Assam India. Department of Biotechnology St. Joseph's College of Engineering Chennai 600119 India Department of Applied Data Science Noroff University College Kristiansand Norway. Electronic address: basg2002@***.

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A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises

arXiv

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arXiv 2020年

作者： Zhou, S. Kevin Greenspan, Hayit Davatzikos, Christos Duncan, James S. van Ginneken, Bram Madabhushi, Anant Prince, Jerry L. Rueckert, Daniel Summers, Ronald M. School of Biomedical Engineering University of Science and Technology of China Institute of Computing Technology Chinese Academy of Sciences China Biomedical Engineering Department Tel-Aviv University Israel Radiology Department Electrical and Systems Engineering Department University of Pennsylvania United States The Departments of Biomedical Engineering and Radiology & Biomedical Imaging Yale University United States Radboud University Medical Center Netherlands The Department of Biomedical Engineering Case Western Reserve University Louis Stokes Cleveland Veterans Administration Medical Center United States Electrical and Computer Engineering Department Johns Hopkins University United States Klinikum rechts der Isar TU Munich Germany Department of Computing Imperial College United Kingdom National Institute of Health Clinical Center United States

Since its renaissance, deep learning has been widely used in various medical imaging tasks and has achieved remarkable success in many medical imaging applications, thereby propelling us into the so-called artificial intelligence (AI) era. It is known that the success of AI is mostly attributed to the availability of big data with annotations for a single task and the advances in high performance computing. However, medical imaging presents unique challenges that confront deep learning approaches. In this survey paper, we first present traits of medical imaging, highlight both clinical needs and technical challenges in medical imaging, and describe how emerging trends in deep learning are addressing these issues. We cover the topics of network architecture, sparse and noisy labels, federating learning, interpretability, uncertainty quantification, etc. Then, we present several case studies that are commonly found in clinical practice, including digital pathology and chest, brain, cardiovascular, and abdominal imaging. Rather than presenting an exhaustive literature survey, we instead describe some prominent research highlights related to these case study applications. We conclude with a discussion and presentation of promising future directions. Copyright © 2020, The Authors. All rights reserved.

关键词： Surveys

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Blockchain-based solution for COVID-19 digital medical passports and immunity certificates

TechRxiv

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TechRxiv 2020年

作者： Hasan, Haya R. Salah, Khaled Jayaraman, Raja Arshad, Junaid Yaqoob, Ibrar Omar, Mohammed Ellahham, Samer Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi127788 United Arab Emirates Department of Industrial and Systems Engineering Khalifa University Abu Dhabi127788 United Arab Emirates School of Computing and Digital Technology Birmingham City University Birmingham United Kingdom Heart & Vascular Institute Cleveland Clinic Abu Dhabi Abu Dhabi United Arab Emirates

COVID-19 has emerged as a highly contagious disease which has caused a devastating impact across the world with a very large number of infections and deaths. Timely and accurate testing is paramount to an effective response to this pandemic as it helps identify infections and therefore mitigate (isolate/cure) them. In this paper, we investigate this challenge and contribute by presenting a blockchain-based solution that incorporates self-sovereign identity, re-encryption proxies, and decentralized storage, such as the interplanetary file systems (IPFS). Our solution implements digital medical passports (DMP) and immunity certificates for COVID-19 test-takers. We present smart contracts based on the Ethereum blockchain written and tested successfully to maintain a digital medical identity for test-takers that help in a prompt trusted response directly by the relevant medical authorities. We reduce the response time of the medical facilities, alleviate the spread of false information by using immutable trusted blockchain, and curb the spread of the disease through DMP. We present a detailed description of the system design, development, and evaluation (cost and security analysis) for the proposed solution. Since our code leverages the use of the on-chain events, the cost of our design is almost negligible. We have made our smart contract codes publicly available on Github. © 2020, CC BY.

关键词： COVID-19

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