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Problem structures in the theory and practice of superiorization

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Journal of Applied and Numerical Optimization

Journal of Applied and Numerical Optimization 2020年第1期2卷 71-76页

作者： Herman, Gabor T. Computer Science Ph.D. Program Graduate Center City University of New York New YorkNY10016 United States

The purpose of this short paper is to identify the mathematical essence of the superiorization methodology. This methodology has been developed in recent years while attempting to solve specific application-oriented problems. Consequently, superiorization is often presented using the terminology of such problems. A more general approach is provided here by discussing ideas related to superiorization in terms of an abstract mathematical concept, referred to as a problem structure. © 2020 Journal of Applied and Numerical Optimization.

关键词： Optimization

Transverse acoustic spin and torque from pure spinning of objects

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Physical Review B 2021年第6期104卷 L060104-L060104页

作者： M. Farhat P.-Y. Chen M. Amin A. Alù Y. Wu Computer Electrical and Mathematical Science and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia Department of Electrical and Computer Engineering University of Illinois at Chicago Chicago Illinois 60607 USA College of Engineering Taibah University Madinah 42353 Saudi Arabia Photonics Initiative Advanced Science Research Center City University of New York New York New York 10031 USA Physics Program Graduate Center City University of New York New York New York 10016 USA

Acoustic spin has been recently explored for many applications. In particular, transverse acoustic spin was demonstrated for inhomogeneous acoustic fields. In this Letter, we show the emergence of acoustic spin and torque in rotating acoustic objects of the same physical properties as the surrounding, to single out the effects purely due to rotation. The spinning of a cylindrical column of air or water in the same medium possesses intrinsic spin angular momentum, and we study the torque and force it experiences in evanescent acoustic fields. The resulting discontinuity can thus scatter sound in unusual ways, including a negative radiation force, although it has no imaginary part in its parameters.

关键词： Acoustic interactions Acoustic metamaterials Acoustic wave phenomena Linear acoustics

Observation of Temporal Reflections and Broadband Frequency Translations at Photonic Time-Interfaces

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arXiv 2022年

作者： Moussa, Hady Xu, Gengyu Yin, Shixiong Galiffi, Emanuele Ra'di, Younes Alù, Andrea Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Department of Electric Engineering City College of City University of New York New YorkNY10031 United States Department of Electrical Engineering and Computer Science Syracuse University SyracuseNY13244 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States

Time-reflection is a uniform inversion of the temporal evolution of a signal, which arises when an abrupt change in the properties of the host material occurs uniformly in space.1-3 At such a time-interface, a portion of the input signal is time-reversed, and its frequency spectrum is homogeneously translated while its momentum is conserved, forming the temporal counterpart of a spatial interface. Combinations of time-interfaces, forming time-metamaterials and Floquet matter4, exploit the interference of multiple time-reflections for extreme wave manipulation, leveraging time as a new degree of freedom5. Here, we report the observation of photonic time-reflection and associated broadband frequency translation in a switched transmission-line metamaterial whose effective capacitance is homogeneously and abruptly changed via a synchronized array of switches. A pair of temporal interfaces are combined to demonstrate time-reflection-induced wave interference, realizing the temporal counterpart of a Fabry-Perot cavity6. Our results establish the foundational building blocks to realize time-metamaterials and Floquet photonic crystals, with opportunities for extreme photon manipulation in space and time7-8 © 2022, CC BY.

关键词： Metamaterials

Passive Bias-Free Nonreciprocal Metasurfaces Based on Nonlinear Quasi-Bound States in the Continuum

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arXiv 2022年

作者： Cotrufo, Michele Cordaro, Andrea Sounas, Dimitrios L. Polman, Albert Alù, Andrea Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Van der Waals-Zeeman Institute Institute of Physics University of Amsterdam Science Park 904 Amsterdam1098 XH Netherlands Center for Nanophotonics AMOLF Science Park 104 Amsterdam1098 XG Netherlands Department of Electrical and Computer Engineering Wayne State University DetroitMI48202 United States Physics Program Graduate Center of the City University of New York New YorkNY10016 United States

Nonreciprocal devices – in which light is transmitted with different efficiencies along opposite directions – are key technologies for modern photonic applications, yet their compact and miniaturized implementation remains an open challenge. Among different avenues, nonlinearity-induced nonreciprocity has attracted significant attention due to the absence of external bias and integrability within conventional material platforms. So far, nonlinearity-induced nonreciprocity has been demonstrated only in guided platforms using high-Q resonators. Here, we demonstrate ultrathin optical metasurfaces with large nonreciprocal response for free-space radiation based on silicon third-order nonlinearities. Our metasurfaces combine an out-of-plane asymmetry – necessary to obtain nonreciprocity – with in-plane broken symmetry, which finely tunes the radiative linewidth of quasi-bound states in the continuum (q-BICs). Third-order nonlinearities naturally occurring in silicon, engaged by q-BICs, are shown to enable over 10 dB of nonreciprocal transmission while maintaining less than 3 dB in insertion loss. The demonstrated devices merge the field of nonreciprocity with ultrathin metasurface technologies, offering an exciting functionality for signal processing and routing, communications, and protection of high-power laser cavities. © 2022, CC BY.

关键词： High power lasers

Quantifying U-Net Uncertainty in Multi-Parametric MRI-based Glioma Segmentation by Spherical Image Projection

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arXiv 2022年

作者： Yang, Zhenyu Lafata, Kyle Vaios, Eugene Hu, Zongsheng Mullikin, Trey Yin, Fang-Fang Wang, Chunhao Department of Radiation Oncology Duke University DurhamNC United States Medical Physics Graduate Program Duke Kunshan University Jiangsu Kunshan China Medical Physics Graduate Program Duke University DurhamNC United States Department of Radiology Duke University DurhamNC United States Department of Electrical and Computer Engineering Duke University DurhamNC United States Department of Radiation Physics The University of Texas MD Anderson Cancer Center HoustonTX United States The University of Texas MD Anderson Graduate School of Biomedical Science HoustonTX United States

Background: Uncertainty quantification in deep learning is an important research topic. For medical image segmentation, the uncertainty measurements are usually reported as the likelihood that each pixel belongs to the predicted segmentation region. In potential clinical applications, the uncertainty result reflects the algorithm's robustness and supports the confidence and trust of the segmentation result when the ground-truth result is absent. For commonly studied deep learning models, novel methods for quantifying segmentation uncertainty are in demand. Purpose: To develop a U-Net segmentation uncertainty quantification method based on spherical image projection of multi-parametric MRI (MP-MRI) in glioma segmentation. Methods: The projection of planar MRI data onto a spherical surface is equivalent to a nonlinear image transformation that retains global anatomical information. By incorporating this image transformation process in our proposed spherical projection-based U-Net (SPU-Net) segmentation model design, multiple independent segmentation predictions can be obtained from a single MRI. The final segmentation is the average of all available results, and the variation can be visualized as a pixel-wise uncertainty map. An uncertainty score was introduced to evaluate and compare the performance of uncertainty measurements. The proposed SPU-Net model was implemented on the basis of 369 glioma patients with MP-MRI scans (T1, T1-Ce, T2, and FLAIR). Three SPU-Net models were trained to segment enhancing tumor (ET), tumor core (TC), and whole tumor (WT), respectively. The SPU-Net model was compared with (1) the classic U-Net model with test-time augmentation (TTA) and (2) linear scaling-based U-Net (LSU-Net) segmentation models in terms of both segmentation accuracy (Dice coefficient, sensitivity, specificity, and accuracy) and segmentation uncertainty (uncertainty map and uncertainty score). Results: The developed SPU-Net model successfully achieved low uncertainty

关键词： Tumors

Low Temperature Spin Seebeck Effect in Non-Magnetic Vanadium Dioxide

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arXiv 2023年

作者： Luo, Renjie Legvold, Tanner J. Chen, Liyang Navarro, Henry Basaran, Ali C. Hong, Deshun Liu, Changjiang Bhattacharya, Anand Schuller, Ivan K. Natelson, Douglas Department of Physics and Astronomy Rice University HoustonTX77005 United States Applied Physics Graduate Program Rice Quantum Institute Rice University HoustonTX77005 United States Department of Physics Center for Advanced Nanoscience University of California La Jolla San DiegoCA92093 United States Materials Science Division Argonne National Laboratory LemontIL60439 United States Department of Electrical and Computer Engineering Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States

The spin Seebeck effect (SSE) is sensitive to thermally driven magnetic excitations in magnetic insulators. Vanadium dioxide in its insulating low temperature phase is expected to lack magnetic degrees of freedom, as vanadium atoms are thought to form singlets upon dimerization of the vanadium chains. Instead, we find a paramagnetic SSE response in VO2 films that grows as the temperature decreases below 50 K. The field and temperature dependent SSE voltage is qualitatively consistent with a general model of paramagnetic SSE response and inconsistent with triplet spin transport. Quantitative estimates find a spin Seebeck coefficient comparable in magnitude to that observed in strongly magnetic materials. The microscopic nature of the magnetic excitations in VO2 requires further examination. Copyright © 2023, The Authors. All rights reserved.

关键词： Paramagnetism

CellBiAge: Improved single-cell age classification using data binarization

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Cell Reports 2023年第12期42卷 113500页

作者： Yu, Doudou Li, Manlin Linghu, Guanjie Hu, Yihuan Hajdarovic, Kaitlyn H. Wang, An Singh, Ritambhara Webb, Ashley E. Molecular Biology Cell Biology and Biochemistry Graduate Program Brown University Providence 02912 RI United States Data Science Institute Brown University Providence 02912 RI United States Neuroscience Graduate Program Brown University Providence 02912 RI United States Department of Applied Mathematics & Statistics Johns Hopkins University Baltimore 21218 MD United States Department of Computer Science Brown University Providence 02912 RI United States Center for Computational Molecular Biology Brown University Providence 02912 RI United States Department of Molecular Biology Cell Biology and Biochemistry Brown University Providence 02912 RI United States Center on the Biology of Aging Brown University Providence 02912 RI United States Carney Institute for Brain Science Brown University Providence 02912 RI United States Center for Translational Neuroscience Brown University Providence 02912 RI United States

Aging is a major risk factor for many diseases. Accurate methods for predicting age in specific cell types are essential to understand the heterogeneity of aging and to assess rejuvenation strategies. However, classifying organismal age at single-cell resolution using transcriptomics is challenging due to sparsity and noise. Here, we developed CellBiAge, a robust and easy-to-implement machine learning pipeline, to classify the age of single cells in the mouse brain using single-cell transcriptomics. We show that binarization of gene expression values for the top highly variable genes significantly improved test performance across different models, techniques, sexes, and brain regions, with potential age-related genes identified for model prediction. Additionally, we demonstrate CellBiAge's ability to capture exercise-induced rejuvenation in neural stem cells. This study provides a broadly applicable approach for robust classification of organismal age of single cells in the mouse brain, which may aid in understanding the aging process and evaluating rejuvenation methods. © 2023 The Authors

关键词： aging brain CP: Cell biology hypothalamus machine learning single-cell RNA-seq

Faster GröBner Bases Via Domain-Specific Ordering in Parameter Identifiability of Ode Models

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SSRN

SSRN 2023年

作者： Bessonov, Mariya Ilmer, Ilia Konstantinova, Tatiana Ovchinnikov, Alexey Pogudin, Gleb Soto, Pedro Brookhaven National Laboratory United States Department of Mathematics CUNY NYC College of Technology New YorkNY United States Ph.D. Program in Computer Science CUNY Graduate Center New YorkNY United States Department of Mathematics CUNY Queens College New YorkNY United States LIX CNRS École Polytechnique Institute Polytechnique de Paris Paris France Mathematical Institute University of Oxford Oxford United Kingdom

We consider a specific class of polynomial systems that arise in parameter identifiability problems of models of ordinary differential equations (ODE) and discover a method for speeding up the Gr¨obner basis computation by using specific variable ordering and weights coming from the structure of the ODE model. We provide empirical results that show improvement across different symbolic computing frameworks. © 2023, The Authors. All rights reserved.

关键词： Ordinary differential equations

Learning Vector Quantized Shape Code for Amodal Blastomere Instance Segmentation

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Learning Vector Quantized Shape Code for Amodal Blastomere I...

IEEE International Symposium on Biomedical Imaging

作者： Won-Dong Jang Donglai Wei Xingxuan Zhang Brian Leahy Helen Yang James Tompkin Dalit Ben-Yosef Daniel Needleman Hanspeter Pfister School of Engineering and Applied Sciences Harvard University MA USA Boston College MA USA Department of Molecular and Cellular Biology Harvard University MA USA Harvard Graduate Program in Biophysics Harvard University MA USA Department of Computer Science Brown University RI USA Tel Aviv Sourasky Medical Center Fertility & IVF Institute Israel Dept. of Cell and Developmental Biology Sagol School of Neuroscience Tel Aviv University Israel

Blastomere instance segmentation is important for analyzing embryos’ abnormality. To measure the accurate shapes and sizes of blastomeres, their amodal segmentation is necessary. Amodal instance segmentation aims to recover an object’s complete silhouette even when the object is not fully visible. For each detected object, previous methods directly regress the target mask from input features. However, images of an object under different amounts of occlusion should have the same amodal mask output, making it harder to train the regression model. To alleviate the problem, we propose to classify input features into intermediate shape codes and recover complete object shapes. First, we pre-train the Vector Quantized Variational Autoencoder (VQ-VAE) model to learn these discrete shape codes from ground truth amodal masks. Then, we incorporate the VQ-VAE model into the amodal instance segmentation pipeline with an additional refinement module. We also detect an occlusion map to integrate occlusion information with a backbone feature. As such, our network faithfully detects bounding boxes of amodal objects. On an internal embryo cell image benchmark, the proposed method outperforms previous state-of-the-art methods. To show generalizability, we show segmentation results on the public KINS natural image benchmark. Our method would enable accurate measurement of blastomeres in In Vitro Fertilization (IVF) clinics, potentially increasing the IVF success rate.

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