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arXiv 2022年

作者： Ni, Xiang Yves, Simon Krasnok, Alex Alu, Andrea Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Department of Electrical and Computer Engineering Florida International University MiamiFL33174 United States Department of Electrical Engineering City College The City University of New York 160 Convent Avenue New York10031 United States Physics Program The Graduate Center The City University of New York 365 Fifth Avenue New York10016 United States

Unlike geometrical features, such as shape or volume, the topological properties of an object do not change continuously, but only due to abrupt transitions associated with a change in the integer quantities that describe these properties - known as topological invariants. In turn, this resilience of topological features is associated with intrinsic robustness. For example, the topological invariant known as the Chern number, associated with the quantization of the Hall conductance in a two-dimensional electron gas, supports disorder-immune electron transport at the surface of topological insulators (TIs). One of the most significant breakthroughs in physics of the last decade has been the discovery that materials with non-trivial topological properties for electronic, electromagnetic, acoustic and mechanical responses can be designed and manufactured at our will through engineered metamaterials (MMs). Here, we review the foundation and the state-of-the-art advances of topological photonics, acoustics and mechanical MMs. We discuss how topological MMs enable nontrivial wave phenomena in physics, engineering, of great interest for a broad range of interdisciplinary science disciplines such as classical and quantum chemistry. We first introduce the foundations of topological materials and the main concepts behind their peculiar features, including the concepts of topological charge and geometric phase. We then discuss the topology of electronic band structures in natural topological materials, like topological insulators and gapless Dirac and Weyl semimetals. Based on these concepts, we review the concept, design and response of topologically nontrivial MMs in photonics and phononics, including topological phases in 2D MMs with and without time-reversal symmetry, Floquet TIs based on spatial and temporal modulation, topological phases in 3D MMs, higher-order topological phases in MMs, non-Hermitian and nonlinear topological MMs and the topological features of scatteri

关键词： Metamaterials

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Beyond Bounds on Light Scattering with Complex Frequency Excitations

arXiv

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arXiv 2022年

作者： Kim, Seunghwi Lepeshov, Sergey Krasnok, Alex Alù, Andrea Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States DTU Electro Department of Electrical and Photonics Engineering Technical University of Denmark Ørsteds Plads 343 Kgs. LyngbyDK-2800 Denmark Department of Electrical and Computer Engineering Florida International University MiamiFL33174 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States

Light scattering is one of the most established wave phenomena in optics, lying at the heart of light-matter interactions and of crucial importance for nanophotonic applications. Passivity, causality and energy conservation imply strict bounds on the degree of control over scattering from small particles, with implications on the performance of many optical devices. Here, we demonstrate that these bounds can be surpassed by considering excitations at complex frequencies, yielding extreme scattering responses as tailored nanoparticles reach a quasi-steady-state regime. These mechanisms can be used to engineer light scattering of nanostructures beyond conventional limits for noninvasive sensing, imaging, and nanoscale light manipulation. Copyright © 2022, The Authors. All rights reserved.

关键词： Light scattering

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A Hybrid Particle Swarm Optimization with Crossover and Mutation of Genetic Algorithm for Solving the Wide Constraint Problem

A Hybrid Particle Swarm Optimization with Crossover and Muta...

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2019 International Congress on Applied Information Technology, AIT 2019

作者： Herlawati, H. Heryadi, Yaya Lukas, L. BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Cognitive Engineering Research Group Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta12930 Indonesia

ISBN: (纸本)9781728158624

When optimizing the spatial data, a lot of constraints should be handled. Some constraints might be too wide for a metaheuristic algorithm, e.g. particle swarm optimization, to allocate the candidate locations outside a wide constraint. However, particle swarm optimization notably has fast computation characteristic and many researchers used this method for optimizing their spatial data. In the other hand, genetic algorithm has not only better exploitation-characteristic performance in searching but also has mutation and crossover that was proven in this study can be overcome the wide constraint problem. To minimize the drawback of genetic algorithm, i.e. need many computation resources, the hybrid particle swarm optimization with genetic algorithm through the use of crossover and mutation was used. Half of lower fitness values from particle swarm optimization were optimized using crossover and mutation in genetic algorithm. After merging the results of both methods, the optimum location showed that the proposed method was able to allocate the land use in a case study area outside the wide constraint. © 2019 IEEE.

关键词： Genetic algorithms

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Radar Occupancy Prediction with Lidar Supervision while Preserving Long-Range Sensing and Penetrating Capabilities

arXiv

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arXiv 2021年

作者： Kung, Pou-Chun Wang, Chieh-Chih Lin, Wen-Chieh The Graduate Degree Program of Robotics National Yang Ming Chiao Tung University Hsinchu Taiwan The Department of Electrical and Computer Engineering National Yang Ming Chiao Tung University Taiwan The Mechanical and Mechatronics Systems Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan The Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan

Radar shows great potential for autonomous driving by accomplishing long-range sensing under diverse weather conditions. But radar is also a particularly challenging sensing modality due to the radar noises. Recent works have made enormous progress in classifying free and occupied spaces in radar images by leveraging lidar label supervision. However, there are still several unsolved issues. Firstly, the sensing distance of the results is limited by the sensing range of lidar. Secondly, the performance of the results is degenerated by lidar due to the physical sensing discrepancies between the two sensors. For example, some objects visible to lidar are invisible to radar, and some objects occluded in lidar scans are visible in radar images because of the radar's penetrating capability. These sensing differences cause false positive and penetrating capability degeneration, respectively. In this paper, we propose training data preprocessing and polar sliding window inference to solve the issues. The data preprocessing aims to reduce the effect caused by radar-invisible measurements in lidar scans. The polar sliding window inference aims to solve the limited sensing range issue by applying a near-range trained network to the long-range region. Instead of using common Cartesian representation, we propose to use polar representation to reduce the shape dissimilarity between long-range and near-range data. We find that extending a near-range trained network to long-range region inference in the polar space has 4.2 times better IoU than in Cartesian space. Besides, the polar sliding window inference can preserve the radar penetrating capability by changing the viewpoint of the inference region, which makes some occluded measurements seem non-occluded for a pretrained network. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical radar

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Neural population dynamics in songbird RA and HVC during learned motor-vocal behavior

arXiv

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arXiv 2024年

作者： Tostado-Marcos, Pablo Arneodo, Ezequiel M. Ostrowski, Lauren Brown, Daril E. Perez, Xavier A. Kadwory, Adam Stanwicks, Lauren L. Alothman, Abdullah Gentner, Timothy Q. Gilja, Vikash Department of Bioengineering University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States Department of Electrical and Computer Engineering University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States Department of Psychology University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States Department of Neurobiology University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States Neurosciences Graduate Program University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States

Complex, learned motor behaviors involve the coordination of large-scale neural activity across multiple brain regions, but our understanding of the population-level dynamics within different regions tied to the same behavior remains limited. Here, we investigate the neural population dynamics underlying learned vocal production in awake-singing songbirds. We use Neuropixels probes to record the simultaneous extracellular activity of populations of neurons in two regions of the vocal motor pathway. In line with observations made in non-human primates during limb-based motor tasks, we show that the population-level activity in both the premotor nucleus HVC and the motor nucleus RA is organized on low-dimensional neural manifolds upon which coordinated neural activity is well described by temporally structured trajectories during singing behavior. Both the HVC and RA latent trajectories provide relevant information to predict vocal sequence transitions between song syllables. However, the dynamics of these latent trajectories differ between regions. Our state-space models suggest a unique and continuous-over-time correspondence between the latent space of RA and vocal output, whereas the corresponding relationship for HVC exhibits a higher degree of neural variability. We then demonstrate that comparable high-fidelity reconstruction of continuous vocal outputs can be achieved from HVC and RA neural latents and spiking activity. Unlike those that use spiking activity, however, decoding models using neural latents generalize to novel sub-populations in each region, consistent with the existence of preserved manifolds that confine vocal-motor activity in HVC and RA. © 2024, CC BY.

关键词： Dynamics

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A Neural Ordinary Differential Equation Model for Visualizing Deep Neural Network Behaviors in Multi-Parametric MRI based Glioma Segmentation

arXiv

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arXiv 2022年

作者： Yang, Zhenyu Hu, Zongsheng Ji, Hangjie Lafata, Kyle Floyd, Scott Yin, Fang-Fang Wang, Chunhao Deparment of Radiation Oncology Duke University DurhamNC27710 United States Medical Physics Graduate Program Duke Kunshan University Jiangsu Kunshan215316 China Department of Mathematics North Carolina State University RaleighNC27695 United States Department of Radiology Duke University DurhamNC27710 United States Department of Electrical and Computer Engineering Duke University DurhamNC27710 United States

Purpose: To develop a neural ordinary differential equation (ODE) model for visualizing deep neural network behavior during multi-parametric MRI (mp-MRI) based glioma segmentation as a method to enhance deep learning explainability. Methods: By hypothesizing that deep feature extraction can be modeled as a spatiotemporally continuous process, we designed a novel deep learning model, neural ODE, in which deep feature extraction was governed by an ODE without explicit expression. The dynamics of 1) MR images after interactions with the deep neural network and 2) segmentation formation can thus be visualized after solving ODE. An accumulative contribution curve (ACC) was designed to quantitatively evaluate each MR image's utilization by the deep neural network towards the final segmentation results. The proposed neural ODE model was demonstrated using 369 glioma patients with a 4-modality mp-MRI protocol: T1, contrast-enhanced T1 (T1-Ce), T2, and FLAIR. Three neural ODE models were trained to segment enhancing tumor (ET), tumor core (TC), and whole tumor (WT), respectively. The key MR modalities with significant utilization by deep neural network were identified based on ACC analysis. Segmentation results by deep neural networks using only the key MR modalities were compared to the ones using all 4 MR modalities in terms of Dice coefficient, accuracy, sensitivity, and specificity. Results: All neural ODE models successfully illustrated image dynamics as expected. ACC analysis identified T1-Ce as the only key modality in ET and TC segmentations, while both FLAIR and T2 were key modalities in WT segmentation. Compared to the U-Net results using all 4 MR modalities, Dice coefficient of ET (0.784→0.775), TC (0.760→0.758), and WT (0.841→0.837) using the key modalities only had minimal differences without significance. Accuracy, sensitivity, and specificity results demonstrated the same patterns. Conclusion: The neural ODE model offers a new tool for optimizing the deep lear

关键词： Tumors

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Thermalization of fluorescent protein exciton-polaritons at room temperature

arXiv

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arXiv 2022年

作者： Satapathy, Sitakanta Liu, Bin Deshmukh, Prathmesh Molinaro, Paul M. Dirnberger, Florian Khatoniar, Mandeep Koder, Ronald L. Menon, Vinod M. Department of Physics Center for Discovery and Innovation The City College of New York 85 St. Nicholas Terrace New YorkNY10031 United States The PhD Program in Physics The Graduate Center of the City University of New York 365 5th Ave New YorkNY10016 United States Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109 United States

Fluorescent proteins (FPs) have recently emerged as a serious contender for realizing ultra-low threshold room temperature exciton-polariton condensation and lasing. Our contribution investigates the thermalization of FP microcavity exciton-polaritons upon optical pumping under ambient conditions. We realize polariton cooling using a new FP molecule, called mScarlet, coupled strongly to the optical modes in a Fabry-Pérot cavity. Interestingly, at the threshold excitation energy (fluence) of ~9 nJ/pulse (15.6 mJ/cm2), we observe an effective temperature, Teff ~350 ± 35 K close to the lattice temperature indicative of strongly thermalized exciton-polaritons at equilibrium. This efficient thermalization results from the interplay of radiative pumping facilitated by the energetics of the lower polariton branch and the cavity Qfactor. Direct evidence for dramatic switching from an equilibrium state into a metastable state is observed for the organic cavity polariton device at room temperature via deviation from the Maxwell-Boltzmann statistics at k1 = 0 above the threshold. Thermalized polariton gases in organic systems at equilibrium hold substantial promise for designing room temperature polaritonic circuits, switches, and lattices for analog simulation. © 2022, CC BY-NC-SA.

关键词： Polariton

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ZETA: a library for Zonotope-based EsTimation and fAult diagnosis of discrete-time systems

arXiv

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arXiv 2025年

作者： Rego, Brenner S. Scott, Joseph K. Raimondo, Davide M. Terra, Marco H. Raffo, Guilherme V. Department of Electrical and Computer Engineering University of São Paulo SP São Carlos13566-590 Brazil Department of Chemical and Biomolecular Engineering Georgia Institute of Technology 311 Ferst Dr. AtlantaGA30318 United States Department of Engineering and Architecture University of Trieste Trieste34127 Italy Department of Electronics Engineering Graduate Program in Electrical Engineering Federal University of Minas Gerais MG Belo Horizonte31270-901 Brazil

This paper introduces ZETA, a new MATLAB library for Zonotope-based EsTimation and fAult diagnosis of discrete-time systems. It features user-friendly implementations of set representations based on zonotopes, namely zonotopes, constrained zonotopes, and line zonotopes, in addition to a basic implementation of interval arithmetic. This library has capabilities starting from the basic set operations with these sets, including propagations through nonlinear functions using various approximation methods. The features of ZETA allow for reachability analysis and state estimation of discrete-time linear, nonlinear, and descriptor systems, in addition to active fault diagnosis of linear systems. Efficient order reduction methods are also implemented for the respective set representations. Some examples are presented in order to illustrate the functionalities of the new library. © 2025, CC BY.

关键词： Digital arithmetic

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Spatiotemporal dynamics of NF-κB/Dorsal inhibitor IκBα/Cactus in Drosophila blastoderm embryos

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iScience 2025年

作者： Allison E. Schloop Sharva V. Hiremath Razeen Shaikh Sadia Siddika Dima Leslie Lizardo Amrit Bhakta Cranos M. Williams Gregory T. Reeves Graduate Program in Genetics North Carolina State University Raleigh NC 27606 Department of Electrical and Computer Engineering North Carolina State University Raleigh NC 27606 North Carolina Plant Sciences Initiative North Carolina State University Raleigh NC 27606 Department of Chemical Engineering Texas A&M University College Station TX 77843 Program in Genetics and Genomics Texas A&M University College Station TX 77843

The NF-κB/IκBα pathway regulates key cellular processes, including development, immunity, and inflammation. In Drosophila, the homologous Dorsal/Cactus system patterns the dorsoventral axis of the blastoderm embryo. While the inhibitor Cactus has been suggested to play multiple roles in regulating Dorsal, direct visualization of Cactus is challenging due to its rapid turnover. To overcome this challenge, we endogenously tagged Cactus with a nanobody against GFP and quantitatively imaged Cactus distribution in live embryos. We found that, like Dorsal, Cactus undergoes nuclear-cycle-driven dynamics and nucleocytoplasmic shuttling. Using a mathematical model constrained by our data, we estimated Cactus nuclear and cytoplasmic concentration. Our results imply that the Dorsal gradient has increased spatial range, robustness, and precision due to the presence of Cactus in the nucleus uniformly throughout the embryo. This study provides insights into NF-κB regulation in Drosophila embryos and highlights the need for similar quantitative studies in other biological systems.

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Monitoring and Analysis of Compensatory Trunk Movements with RGB-D Camera and Wireless System for Rehabilitation of Upper Limbs

Monitoring and Analysis of Compensatory Trunk Movements with...

引用

IEEE Latin American Robotics Symposium, LARS

作者： Alice T. Garcia André L. S. da Kelbouscas Sibyla A. V. e Silva Leonardo L. Guimarães Vinícius M. de Oliveira Graduate Student in Computer Engineering Graduate Program at the Federal University of Rio Grande (FURG) Rio Grande RS Brazil Associate Professor at Federal University of Rio Grande (FURG) Rio Grande RS Brazil

ISBN: (数字)9780738111537

ISBN: (纸本)9781665419857

Assistive Robotics has been shown to be an important tool in the patient rehabilitation process. The rehabilitation of patients with traditional therapeutic approaches has not achieved results, making therapeutic approaches that use robotics gain more and more strength. With this, a series of new ones can be used in order to assist in the rehabilitation of patients with limited restrictions, especially those who have suffered post-stroke trauma. Stroke patients often use the trunk to compensate for impaired upper limb motor function during upper limb rehabilitation training, or that results in a reduced effect of rehabilitation training. Detecting trunk displacements can improve the effect of rehabilitation training. Therefore, this study aims to use an RGB-D camera to analyze the movement behavior of the trunk of five volunteers, who do not have any type of restriction, in the execution of four predefined movements. The objective is to verify that, even without any type of restriction, the process of executing movements of the trunk to execute movements. In addition, this study proposes a methodology to perform kinematic tracking of trunk movement compensation through the use of a wireless system. The results obtained with the use of the RGB-D camera were satisfactory and were able to prove the existence of compensatory movements even in patients who do not have any type of restriction.

关键词： Cameras Monitoring Wireless communication Training Tools Stroke (medical condition) Biomedical monitoring

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