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arXiv 2024年

作者： Francisco, Kishi Kobe Yee Apuhin, Andrane Estelle Carnicer Tan, Myles Joshua Toledo Byers, Mickael Cavanaugh Maravilla, Nicholle Mae Amor Tan Karim, Hezerul Abdul AlDahoul, Nouar Biology Program College of Arts and Science University of St. La Salle Negros Occidental Bacolod City Philippines Department of Electrical and Computer Engineering Herbert Wertheim College of Engineering University of Florida GainesvilleFL United States Department of Epidemiology College of Public Health & Health Professions College of Medicine University of Florida GainesvilleFL United States Department of Natural Sciences College of Arts and Science University of St. La Salle Negros Occidental Bacolod City Philippines Department of Chemical Engineering College of Engineering and Technology University of St. La Salle Negros Occidental Bacolod City Philippines Department of Electronics Engineering College of Engineering and Technology University of St. La Salle Negros Occidental Bacolod City Philippines Yo-Vivo Corporation Negros Occidental Bacolod City Philippines Department of Civil and Coastal Engineering Herbert Wertheim College of Engineering University of Florida GainesvilleFL United States Faculty of Engineering Multimedia University Selangor Cyberjaya Malaysia Department of Computer Science Division of Science New York University Abu Dhabi Saadiyat Marina District Abu Dhabi United Arab Emirates

Personalized medicine (PM) promises to transform healthcare by providingtreatments tailored to individual genetic, environmental, and lifestylefactors. However, its high costs and infrastructure demands raise concernsabout exacerbating health disparities, especially between high-income countries(HICs) and low- and middle-income countries (LMICs). While HICs benefit fromadvanced PM applications through AI and genomics, LMICs often lack theresources necessary to adopt these innovations, leading to a wideninghealthcare divide. This paper explores the financial and ethical challenges ofPM implementation, with a focus on ensuring equitable access. It proposesstrategies for global collaboration, infrastructure development, and ethicalframeworks to support LMICs in adopting PM, aiming to prevent furtherdisparities in healthcare accessibility and outcomes. © 2024, CC BY.

关键词： Personalized medicine

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TargetNet: Functional microRNA target prediction with deep neural networks

arXiv

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arXiv 2021年

作者： Min, Seonwoo Lee, Byunghan Yoon, Sungroh Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of LG AI Research Seoul07796 Korea Republic of Department of Electronic and IT Media Engineering Seoul National University of Science and Technology Seoul01811 Korea Republic of Interdisciplinary Program in Artificial Intelligence and Interdisciplinary Program in Bioinformatics Seoul National University Seoul08826 Korea Republic of

Motivation: MicroRNAs (miRNAs) play pivotal roles in gene expression regulation by binding to target sites of messenger RNAs (mRNAs). While identifying functional targets of miRNAs is of utmost importance, their prediction remains a great challenge. Previous computational algorithms have major limitations. They use conservative candidate target site (CTS) selection criteria mainly focusing on canonical site types, rely on laborious and time-consuming manual feature extraction, and do not fully capitalize on the information underlying miRNA-CTS interactions. Results: In this paper, we introduce TargetNet, a novel deep learning-based algorithm for functional miRNA target prediction. To address the limitations of previous approaches, TargetNet has three key components: (1) relaxed CTS selection criteria accommodating irregularities in the seed region, (2) a novel miRNA-CTS sequence encoding scheme incorporating extended seed region alignments, and (3) a deep residual network-based prediction model. The proposed model was trained with miRNA-CTS pair datasets and evaluated with miRNA-mRNA pair datasets. TargetNet advances the previous state-of-theart algorithms used in functional miRNA target classification. Furthermore, it demonstrates great potential for distinguishing high-functional miRNA targets. © 2021, CC BY-NC-ND.

关键词： RNA

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Elastowave: Localized Tactile Feedback in a Soft Haptic Interface via Focused Elastic Waves

Elastowave: Localized Tactile Feedback in a Soft Haptic Inte...

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International Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (HAPTICS)

作者： Gregory Reardon Nikolas Kastor Yitian Shao Yon Visell Media Arts and Technology Program University of California Santa Barbara California California NanoSystems Institute University of California Santa Barbara Santa Barbara California Department of Electrical and Computer Engineering University of Santa Barbara Santa Barbara California

ISBN: (数字)9781728102344

ISBN: (纸本)9781728102351

It is challenging to engineer programmable tactile displays to match human haptic abilities. Such displays are often composed of elements whose stiffness contrasts greatly with the softness of many natural materials. Emerging soft material technologies hold promise for their ability to conform to many objects, including the human body. However, rendering localized feedback from soft haptic devices remains challenging. Here, we present the Elastowave, a soft tactile interface that provides localized tactile feedback via a soft, compliant surface. We achieve this by focusing elastic wave fields generated by a compact array of remotely-positioned actuators. Our method is based on new variations of time-reversal focusing techniques for elastodynamic waves. Our system can provide dynamic, single- or multi-point localized tactile feedback with centimeter-scale resolution across a deformable interface with an area of 175 cm 2 . The sizeable displacements of the focused tactile signals enable them to be easily felt, as our experiments show. This work could enable the design of a multitude of new soft tactile interfaces in areas such as creative computing, product design, and augmented reality.

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Publisher Correction: Battery-free wireless imaging of underwater environments

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Nature communications 2022年第1期13卷 6011页

作者： Sayed Saad Afzal Waleed Akbar Osvy Rodriguez Mario Doumet Unsoo Ha Reza Ghaffarivardavagh Fadel Adib Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA 02139 USA. MIT Media Lab Massachusetts Institute of Technology Cambridge MA 02139 USA. Program in Media Arts and Sciences Massachusetts Institute of Technology Cambridge MA 02139 USA. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA 02139 USA. fadel@mit.edu. MIT Media Lab Massachusetts Institute of Technology Cambridge MA 02139 USA. fadel@mit.edu. Program in Media Arts and Sciences Massachusetts Institute of Technology Cambridge MA 02139 USA. fadel@mit.edu. MIT Sea Grant Massachusetts Institute of Technology Cambridge MA 02139 USA. fadel@mit.edu.

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Neuromuscular fatigue detection by mechanomyography in people with complete spinal cord injury

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Research on Biomedical engineering 2020年第3期36卷 203-212页

作者： Krueger, Eddy Popović-Maneski, Lana Neto, Guilherme Nunes Nogueira Mendonça Scheeren, Eduardo Fiusa, Jessika Mehret Nohama, Percy Neural Engineering and Rehabilitation Laboratory Universidade Estadual de Londrina LondrinaPR Brazil Graduate Program in Rehabilitation Sciences UEL-UNOPAR Campus Universitário s/n zipcode LondrinaPR86051-990 Brazil Institute of Technical Sciences of the Serbian Academy of Sciences and Arts KnezMihailova 35/IV zipcode Belgrade11000 Serbia Graduate Program in Health Technology Pontifícia Universidade Católica do Paraná Rua Imaculada Conceição 1155 Prado Velho zipcode CuritibaPR80215-901 Brazil Graduate Program in Electrical and Computer Engineering Universidade Tecnológica Federal do Paraná Av. Sete de Setembro 3165 zipcode CuritibaPR80230-901 Brazil

Purpose: Functional electrical stimulation (FES) is a method of activating paralyzed muscles. During FES application, fast muscle fatigue can occur (the inability of stimulated muscles to generate force). Therefore, it is beneficial to estimate the muscle fatigue for FES closed-loop control for walking to prevent unexpected muscle collapse and adapt the FES strategy in real time. Mechanomyography (MMG) is a noninvasive technique for registering myofiber vibrations, representing an ideal candidate for the provision of feedback. The hypothesis was that MMG signals could effectively detect muscle fatigue and, thus, provide feedback. Methods: We tested this hypothesis by analyzing the wavelet transform of signals from an MMG sensor positioned over the rectus femoris muscle during electrically evoked contractions in subjects with spinal cord injury (SCI). The signals were collected from a total of 24 lower limb muscles. We investigated both legs of 15 participants with spinal cord injury (male, YOA = 27.13 ± 5.05, M = 75.8 ± 10.35 kg, and H = 1.78 ± 0.07 m, American Spinal Injury Impairment Scale (AIS) A and B). All MMG signals were analyzed in 12 frequency bands from 5 to 53 Hz. Results: We found different trends in the magnitudes in different frequency bands. The magnitude decreased in 13, 16, 20, 25, and 35 Hz bands in correlation with fatigue. The greatest statistical difference was found at 20 Hz and 25 Hz. Conclusion: This result suggests that processed MMG signals indicate muscle fatigue and can, thus, be used as the feedback in FES systems. © 2020, Sociedade Brasileira de Engenharia Biomedica.

关键词： Muscle

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Optical Thouless pumping transport and nonlinear switching in a topological low-dimensional discrete nematic liquid crystal array

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Physical Review A 2022年第1期105卷 013513-013513页

作者： Pawel S. Jung Midya Parto Georgios G. Pyrialakos Hadiseh Nasari Katarzyna Rutkowska Marek Trippenbach Mercedeh Khajavikhan Wieslaw Krolikowski Demetrios N. Christodoulides CREOL The College of Optics and Photonics University of Central Florida Orlando Florida 32816 USA Faculty of Physics Warsaw University of Technology Warsaw Poland Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los Angeles California 90089 USA Faculty of Physics University of Warsaw Warsaw Poland Department of Physics & Astronomy Dornsife College of Letters Arts & Sciences University of Southern California Los Angeles California 90089 USA Laser Physics Centre Research School of Physics Australian National University Canberra ACT 0200 Australia Science Program Texas A&M University at Qatar Doha Qatar

We theoretically investigate a Thouless pumping scheme in the one-dimensional topological Su-Schrieffer-Heeger (SSH) model for single and multiple band-gap systems when implemented in a discrete nematic liquid crystal arrangement. For an electrically controlled SSH waveguide array, we numerically demonstrate edge-to-edge light transport at low power levels. On the other hand, at higher powers, the transport is frustrated by light-induced nonlinear defect states, giving rise to robust all-optical switching.

关键词： Optical solitons Topological insulators Liquid crystals Topological materials

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Non-invasive suppression of essential tremor via phase-locked disruption of its temporal coherence

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Brain Stimulation 2023年第1期16卷 276-277页

作者： Li, Junheng Schreglmann, Sebastian Wang, David Peach, Robert Laurate, Anna Rhodes, Edward Panella, Emanuele Cassara, Antonino Boyden, Edward Barahona, Mauricio Rothwell, John Bhatia, Kailash Grossman, Nir Department of Brain Sciences Imperial College London London UK UK Dementia Research Institute UK Institute of Neurology Department of Clinical and Movement Neuroscience Queen Square University College London (UCL) UK Computer Science and Artificial Intelligence Laboratory Massachussetts Institute of Technology (MIT) USA Department of Brain Sciences Imperial College London UK Department of Mathematics and EPSRC Centre for Mathematics of Precision Healthcare Imperial College London UK Department of Physics Imperial College London London SW7 2AZ UK IT’IS Foundation for Research on Information Technologies in Society Switzerland Department of Media Arts and Sciences MIT USA McGovern Institute for Brain Research MIT USA Howard Hughes Medical Institute Cambridge USA Department of Biological Engineering MIT USA Department of Brain and Cognitive Sciences MIT USA Centre for Neurobiological Engineering MIT USA Koch Institute for Integrative Cancer Research MIT USA Centre for Bio-Inspired Technology Department of Electrical and Electronic Engineering Imperial College London UK Centre for Neurotechnology Imperial College London UK

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Cosmic-CoNN: A Cosmic Ray Detection Deep-Learning Framework, Dataset, and Toolkit

arXiv

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arXiv 2021年

作者： Xu, Chengyuan McCully, Curtis Dong, Boning Howell, D. Andrew Sen, Pradeep Media Arts and Technology University of California Santa BarbaraCA93106 United States Department of Computer Science University of California Santa BarbaraCA93106 United States Las Cumbres Observatory 6740 Cortona Drive Suite 102 GoletaCA93117-5575 United States Department of Electrical and Computer Engineering University of California Santa BarbaraCA93106 United States Department of Physics University of California Santa BarbaraCA93106 United States

Rejecting cosmic rays (CRs) is essential for the scientific interpretation of CCD-captured data, but detecting CRs in single-exposure images has remained challenging. Conventional CR detectors require experimental parameter tuning for different instruments, and recent deep learning methods only produce instrument-specific models that suffer from performance loss on telescopes not included in the training data. We present Cosmic-CoNN, a generic CR detector deployed for 24 telescopes at the Las Cumbres Observatory, which is made possible by the three contributions in this work: 1) We build a large and diverse ground-based CR dataset leveraging thousands of images from a global telescope network. 2) We propose a novel loss function and a neural network optimized for telescope imaging data to train generic CR detection models. At 95% recall, our model achieves a precision of 93.70% on Las Cumbres imaging data and maintains a consistent performance on new ground-based instruments never used for training. Specifically, the Cosmic-CoNN model trained on the Las Cumbres CR dataset maintains high precisions of 92.03% and 96.69% on Gemini GMOS-N/S 1x1 and 2x2 binning images, respectively. 3) We build a suite of tools including an interactive CR mask visualization and editing interface, console commands, and Python APIs to make automatic, robust CR detection widely accessible by the community of astronomers. Our dataset, open-source codebase, and trained models are available at https://***/cy-xu/cosmic-conn. Copyright © 2021, The Authors. All rights reserved.

关键词： Cosmic rays

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Optical Thouless pumping transport and nonlinear switching in a topological low-dimensional discrete nematic liquid crystal array

arXiv

引用

arXiv 2022年

作者： Jung, Pawel S. Parto, Midya Pyrialakos, Georgios G. Nasari, Hadiseh Rutkowska, Katarzyna Trippenbach, Marek Khajavikhan, Mercedeh Krolikowski, Wieslaw Christodoulides, Demetrios N. CREOL The College of Optics and Photonics University of Central Florida OrlandoFL32816 United States Faculty of Physics Warsaw University of Technology Warsaw Poland Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA90089 United States Faculty of Physics University of Warsaw Warsaw Poland Department of Physics & Astronomy Dornsife College of Letters Arts & Sciences University of Southern California Los AngelesCA90089 United States Laser Physics Centre Research School of Physics and Engineering Australian National University CanberraACT0200 Australia Science Program Texas A&M University at Qatar Doha Qatar

We theoretically investigate a Thouless pumping scheme in the 1D topological Su-Schrieffer-Heeger (SSH) model for single and multiple band-gaps systems when implemented in a discrete nematic liquid crystal arrangement. For an electrically controlled SSH waveguide array, we numerically demonstrate edge-to-edge light transport at low power levels. On the other hand, at higher powers, the transport is frustrated by light-induced nonlinear defect states, giving rise to robust all-optical switching. © 2022, CC BY.

关键词： Nematic liquid crystals

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Empowering the Grid: Collaborative Edge Artificial Intelligence for Decentralized Energy Systems

arXiv

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arXiv 2025年

作者： de Paula, Eddie Bunda, Niel Karim, Hezerul Abdul AlDahoul, Nouar Tan, Myles Joshua Toledo Department of Computer Science College of Computing Studies University of St. La Salle Bacolod Philippines Graduate School University of St. La Salle Bacolod Philippines Faculty of Engineering Multimedia University Selangor Cyberjaya Malaysia Department of Computer Science Division of Science New York University Abu Dhabi Abu Dhabi United Arab Emirates Department of Electrical and Computer Engineering Herbert Wertheim College of Engineering University of Florida GainesvilleFL United States Department of Epidemiology College of Public Health and Health Professions College of Medicine University of Florida GainesvilleFL United States Biology Program College of Arts and Sciences University of St. La Salle Bacolod Philippines Department of Natural Sciences College of Arts and Sciences University of St. La Salle Bacolod Philippines Department of Chemical Engineering College of Engineering and Technology University of St. La Salle Bacolod Philippines Department of Electronics Engineering College of Engineering and Technology University of St. La Salle Bacolod Philippines Yo-Vivo Corporation Bacolod Philippines

This paper examines how decentralized energy systems can be enhanced usingcollaborative Edge Artificial Intelligence. Decentralized grids use localrenewable sources to reduce transmission losses and improve energy *** AI enables real-time, privacy-preserving data processing at the networkedge. Techniques such as federated learning and distributed control improvedemand response, equipment maintenance, and energy optimization. The paperdiscusses key challenges including data privacy, scalability, andinteroperability, and suggests solutions such as blockchain integration andadaptive architectures. Examples from virtual power plants and smart gridshighlight the potential of these technologies. The paper calls for increasedinvestment, policy support, and collaboration to advance sustainable energysystems. © 2025, CC BY.

关键词： Smart power grids

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