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Implicit Neural Representations for Deconvolving SAS Images

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Implicit Neural Representations for Deconvolving SAS Images

OCEANS

作者： Albert Reed Thomas Blanford Daniel C. Brown Suren Jayasuriya School of Electrical Computer and Energy Engineering Arizona State University The Applied Research Laboratory Pennsylvania State University Graduate Program in Acoustics Pennsylvania State University

ISBN: (纸本)9781665427883

Synthetic aperture sonar (SAS) image resolution is constrained by waveform bandwidth and array geometry. Specifically, the waveform bandwidth determines a point spread function (PSF) that blurs the locations of point scatterers in the scene. In theory, deconvolving the reconstructed SAS image with the scene PSF restores the original distribution of scatterers and yields sharper reconstructions. However, deconvolution is an ill-posed operation that is highly sensitive to noise. In this work, we leverage implicit neural representations (INRs), shown to be strong priors for the natural image space, to deconvolve SAS images. Importantly, our method does not require training data, as we perform our deconvolution through an analysis-by-synthesis optimization in a self-supervised fashion. We validate our method on simulated SAS data created with a point scattering model and real data captured with an in-air circular SAS. This work is an important first step towards applying neural networks for SAS image deconvolution.

关键词： Deconvolution Oceans Neural networks Training data Scattering Bandwidth Image restoration

Low light quantum phase transition in 1T-TaS2 at room temperature

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Low light quantum phase transition in 1T-TaS2 at room temper...

Conference on Lasers and Electro-Optics (CLEO)

作者： Weijian Li Gururaj V. Naik Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston TX USA Electrical & Computer Engineering Rice University Houston TX USA

Light-matter interaction in quantum materials presents opportunities for discovery. We observe a low-intensity light-induced phase transition in 1T-TaS 2 , a quasi-2D material supporting charge-density-waves (CDW). We... 详细信息

ISBN: (纸本)9781943580910

关键词： Stacking Lighting Lasers and electrooptics Optical materials Laser tuning Laser transitions Laser applications

Bayesian Parameter Inference for Partially Observed Diffusions using Multilevel Stochastic Runge-Kutta Methods

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arXiv 2023年

作者： Moral, Pierre Del Hu, Shulan Jasra, Ajay Ruzayqat, Hamza Wang, Xinyu Institut de Mathematiques de Bordeaux FR Bordeaux33405 France School of Mathematics and Statistics Wenlan School of Business China Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Zhongnan University of Economics and Law CN China

We consider the problem of Bayesian estimation of static parameters associated to a partially and discretely observed diffusion process. We assume that the exact transition dynamics of the diffusion process are unavailable, even up-to an unbiased estimator and that one must time-discretize the diffusion process. In such scenarios it has been shown how one can introduce the multilevel Monte Carlo method to reduce the cost to compute posterior expected values of the parameters for a pre-specified mean square error (MSE);see [12]. These afore-mentioned methods rely on upon the Euler-Maruyama discretization scheme which is well-known in numerical analysis to have slow convergence properties. We adapt stochastic Runge-Kutta (SRK) methods for Bayesian parameter estimation of static parameters for diffusions. This can be implemented in high-dimensions of the diffusion and seemingly under-appreciated in the uncertainty quantification and statistics fields. For a class of diffusions and SRK methods, we consider the estimation of the posterior expectation of the parameters. We prove that to achieve a MSE of O(ϵ2), for ϵ > 0 given, the associated work is O(ϵ−2). Whilst the latter is achievable for the Milstein scheme, this method is often not applicable for diffusions in dimension larger than two. We also illustrate our methodology in several numerical examples. Copyright © 2023, The Authors. All rights reserved.

关键词： Diffusion

Mass Spectra Prediction with Structural Motif-based Graph Neural Networks

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arXiv 2023年

作者： Park, Jiwon Jo, Jeonghee Yoon, Sungroh Interdisciplinary Program in Artificial Intelligence Seoul National University Seoul08826 Korea Republic of LG Chem Seoul07795 Korea Republic of Seoul02456 Korea Republic of Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Artificial Intelligence Institute Seoul National University Seoul08826 Korea Republic of

Mass spectra, which are agglomerations of ionized fragments from targeted molecules, play a crucial role across various fields for the identification of molecular structures. A prevalent analysis method involves spectral library searches, where unknown spectra are cross-referenced with a database. The effectiveness of such search-based approaches, however, is restricted by the scope of the existing mass spectra database, underscoring the need to expand the database via mass spectra prediction. In this research, we propose the Motif-based Mass Spectrum Prediction Network (MoMS-Net), a system that predicts mass spectra using the information derived from structural motifs and the implementation of Graph Neural Networks (GNNs). We have tested our model across diverse mass spectra and have observed its superiority over other existing models. MoMS-Net considers substructure at the graph level, which facilitates the incorporation of long-range dependencies while using less memory compared to the graph transformer model. © 2023, CC BY.

关键词： Molecules

Combining flow virometry with tree-based machine learning models for rapid virus particle estimation in different wastewater matrices

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Water Research 2025年 284卷 123905页

作者： Myshkevych, Yevhen N'Doye, Ibrahima Medina, Julie Sanchez Aljehani, Fahad K. Xiong, Yanghui Laleg-Kirati, Taous-Meriem Hong, Pei-Ying Environmental Science and Engineering Program Division of Biological and Environmental Science and Engineering King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia KAUST Center of Excellence on Smart Health King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia Electrical and Computer Engineering Program Division of Computer Electrical and Mathematical Science and Engineering King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia Paris-Saclay France

Enumerating virus particles (VPs) at different stages of the wastewater treatment process or along the distribution network is essential for ensuring high performance and reducing public health risks. Herein, we aimed to (i) optimize the flow virometry (FVM) protocol for use in wastewater matrices, (ii) correlate FVM data with specific virus genera of interest, and (iii) develop machine learning (ML) models for determining total VP concentration. We identified and tested a comprehensive set of parameters to determine the optimal conditions for wastewater FVM. Specifically, we tested various sample preprocessing steps to enhance FVM detection sensitivity, including the use of different nucleic acid staining dyes, surfactant addition and concentration optimization, glutaraldehyde fixation, and the effect of sample freezing before FVM analysis. Spearman's rank correlation of FVM data with virus genera concentration using a conventional qPCR-based method in 206 samples showed a positive correlation for all five virus genera, ranging from 0.21 to 0.44 (p © 2025 The Author(s)

关键词： Water recycling

Microwave Imaging for Monitoring Patients Post-Radiation Treatment: an initial investigation

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Microwave Imaging for Monitoring Patients Post-Radiation Tre...

European Conference on Antennas and Propagation, EuCAP

作者： Katrin Smith Jeremie Bourqui Petra Grendarova Mark Lesiuk Sarah Quirk Michael Roumeliotis Elise Fear Biomedical Engineering Graduate Program University of Calgary Calgary Canada Electrical and Computer Engineering University of Calgary Calgary Canada University of Calgary Canada Tom Baker Cancer Centre Calgary Canada

In this preliminary study, we investigate how changes in breast tissue due to treatment can be quantified using microwave signals, images, and property estimates. Microwave scans of treated and healthy breasts from a group of cancer patients before and after radiation treatment are compared. Images of the treated breasts generally had an increase in permittivity after treatment, while the healthy breast remained relatively constant over the timeframe. In a case study, the permittivity estimated at various microwave sensor pairs was generally higher for the treated breast compared to the healthy breast, however changes were small in the reported patient. For this example, the signal correlation between scans was high and similar for both the treated and the healthy scan. For the same patient, image correlation highlighted differences between the baseline and follow-up scans, suggesting that image correlation may be a better metric for quantifying changes.

关键词： Microwave antennas Correlation Biomedical applications of radiation Breast tissue Microwave sensors Microwave theory and techniques Permittivity

Single-peak and narrow-band mid-infrared thermal emitters driven by mirror-coupled plasmonic quasi-BIC metasurfaces

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arXiv 2023年

作者： Yang, Sen He, Mingze Hong, Chuchuan Nordlander, Josh Maria, Jon-Paul Caldwell, Joshua D. Ndukaife, Justus C. Department of Electrical and Computer Engineering Vanderbilt University NashvilleTN37235 United States Department of Mechanical Engineering Vanderbilt University NashvilleTN37235 United States Interdisciplinary Materials Science Program Vanderbilt University NashvilleTN37240 United States Department of Materials Science and Engineering The Pennsylvania State University University ParkPA16802 United States Sensorium Technological Labs 6714 Duquaine Ct NashvilleTN37205 United States

Wavelength-selective thermal emitters (WS-EMs) hold considerable appeal due to the scarcity of cost-effective, narrow-band sources in the mid-to-long-wave infrared spectrum. WS-EMs achieved via dielectric materials typically exhibit thermal emission peaks with high quality factors (Q factors), but their optical responses are prone to temperature fluctuations. Metallic EMs, on the other hand, show negligible drifts with temperature changes, but their Q factors usually hover around 10. In this study, we introduce and experimentally verify a novel EM grounded in plasmonic quasi-bound states in the continuum (BICs) within a mirror-coupled system. Our design numerically delivers an ultra-narrowband single peak with a Q factor of approximately 64, and near-unity absorptance that can be freely tuned within an expansive band of more than 10 μm. By introducing air slots symmetrically, the Q factor can be further augmented to around 100. Multipolar analysis and phase diagrams are presented to elucidate the operational principle. Importantly, our infrared spectral measurements affirm the remarkable resilience of our designs’ resonance frequency in the face of temperature fluctuations over 300℃. Additionally, we develop an effective impedance model based on the optical nanoantenna theory to understand how further tuning of the emission properties is achieved through precise engineering of the slot. This research thus heralds the potential of applying plasmonic quasi-BICs in designing ultra-narrowband, temperature-stable thermal emitters in mid-infrared. Moreover, such a concept may be adaptable to other frequency ranges, such as near-infrared, Terahertz, and Gigahertz. Copyright © 2023, The Authors. All rights reserved.

关键词： Mirrors

Linearized frequency domain Landau-Lifshitz-Gilbert equation formulation

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arXiv 2022年

作者： Lin, Zhuonan Lomakin, Vitaliy Department of Electrical and Computer Engineering University of California San Diego La Jolla CA92093 United States Center for Memory and Recording Research La Jolla CA92093 United States Materials Science and Engineering Program University of California San Diego La Jolla CA92093 United States

We present a general finite element linearized Landau-Lifshitz-Gilbert equation (LLGE) solver for magnetic systems under weak time-harmonic excitation field. The linearized LLGE is obtained by assuming a small deviation around the equilibrium state of the magnetic system. Inserting such expansion into LLGE and keeping only first order terms gives the linearized LLGE, which gives a frequency domain solution for the complex magnetization amplitudes under an external time-harmonic applied field of a given frequency. We solve the linear system with an iterative solver using generalized minimal residual method. We construct a preconditioner matrix to effectively solve the linear system. The validity, effectiveness, speed, and scalability of the linear solver are demonstrated via numerical examples. Copyright © 2022, The Authors. All rights reserved.

关键词： Linear systems

Nonsaturated large magnetoresistance and transport dynamics in a n-doped cryogenic WSe2 field-effect device

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Physical Review B 2025年第12期111卷 125307-125307页

作者： Wei-Chen Lin Ching-Chen Yeh Jia-Zhu Zou Nhat Anh Nguyen Phan Inayat Uddin Hai Yen Le Thi Kenji Watanabe Takashi Taniguchi Gil-Ho Kim Department of Engineering and System Science National Tsing Hua University Hsinchu 300 Taiwan Taiwan International Graduate Program Academia Sinica Taipei 115 Taiwan Department of Physics National Taiwan University Taipei 106 Taiwan Department of Electrical and Computer Engineering Sungkyunkwan University (SKKU) Suwon 164 Republic of Korea Sungkyunkwan Advanced Institute of Nano Technology (SAINT) Sungkyunkwan University (SKKU) Suwon 16419 Republic of Korea Research Center for Electronic and Optical Materials National Institute for Materials Science 1-1 Namiki Tsukuba 305-0044 Japan Research Center for Materials Nanoarchitectonics National Institute for Materials Science 1-1 Namiki Tsukuba 305-0044 Japan

Interest in the two-dimensional (2D) semiconducting transition metal dichalcogenides (TMDs) continues to intensify, driven by their suitable band gaps to supplant silicon as next-generation semiconductor materials. Among various TMDs, tungsten diselenide (WSe2) is renowned for its superior electrical properties in carrier density and mobility under ambient conditions. Despite its notable attributes, the behavior of monolayer WSe2 in the electron-doped regime under cryogenic conditions remains largely uncharted, particularly concerning its magnetotransport properties. In this study, we reveal the transport mechanisms of monolayer WSe2 from high temperatures down to the cryogenic regime. As evident by Efros–Shklovskii variable-range hopping (E-S VRH) in the cryogenic regime, strong Coulomb interactions arise between electrons. Above 8 K, an uncommon nonsaturated quadratic large magnetoresistance (MR) can be explained by the wave-function shrinkage model, which is consistent with the E-S VRH transport mechanism. Notably, the nonsaturated quadratic large MR shows a magnitude up to 1740% at 13 T. These findings underscore the potential applications for monolayer WSe2 in cryogenic field-effect devices, magnetic sensors, and memory devices and mark a significant advance in magnetotransport research.

关键词： Monolayers