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arXiv 2024年

作者： Ding, Tong Wagner, Sophia J. Song, Andrew H. Chen, Richard J. Lu, Ming Y. Zhang, Andrew Vaidya, Anurag J. Jaume, Guillaume Shaban, Muhammad Kim, Ahrong Williamson, Drew F.K. Chen, Bowen Almagro-Perez, Cristina Doucet, Paul Sahai, Sharifa Chen, Chengkuan Komura, Daisuke Kawabe, Akihiro Ishikawa, Shumpei Gerber, Georg Peng, Tingying Le, Long Phi Mahmood, Faisal Department of Pathology Mass General Brigham Harvard Medical School BostonMA United States Data Science Program Dana-Farber Cancer Institute BostonMA United States Cancer Program Broad Institute of Harvard and MIT CambridgeMA United States John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA United States Helmholtz Munich German Research Center for Environment and Health Munich Germany School of Computation Information and Technology Technical University of Munich Munich Germany Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States Harvard-MIT Division of Health Sciences and Technology Massachusetts Institute of Technology CambridgeMA United States Department of Pathology Pusan National University Busan Korea Republic of Department of Pathology and Laboratory Medicine Emory University School of Medicine AtlantaGA United States Harvard Data Science Initiative Harvard University CambridgeMA United States Department of Systems Biology Harvard Medical School BostonMA United States Department of Preventive Medicine Graduate School of Medicine The University of Tokyo Tokyo Japan Division of Pathology National Cancer Center Exploratory Oncology Research & Clinical Trial Center Chiba Japan

The field of computational pathology has been transformed with recent advances in foundation models that encode histopathology region-of-interests (ROIs) into versatile and transferable feature representations via self-supervised learning (SSL). However, translating these advancements to address complex clinical challenges at the patient and slide level remains constrained by limited clinical data in disease-specific cohorts, especially for rare clinical conditions. We propose TITAN, a multimodal whole slide foundation model pretrained using 335,645 WSIs via visual self-supervised learning and vision-language alignment with corresponding pathology reports and 423,122 synthetic captions generated from a multimodal generative AI copilot for pathology. Without any finetuning or requiring clinical labels, TITAN can extract general-purpose slide representations and generate pathology reports that generalize to resource-limited clinical scenarios such as rare disease retrieval and cancer prognosis. We evaluate TITAN on diverse clinical tasks and find that TITAN outperforms both ROI and slide foundation models across machine learning settings such as linear probing, few-shot and zero-shot classification, rare cancer retrieval and cross-modal retrieval, and pathology report generation. The model is publicly accessible at https://***/mahmoodlab/TITAN © 2024, CC BY-NC-ND.

关键词： Self-supervised learning

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On sparse identification of complex dynamical systems: a study on discovering influential reactions in chemical reaction networks

arXiv

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arXiv 2020年

作者： Harirchi, Farshad Kim, Doohyun Khalil, Omar Liu, Sijia Elvati, Paolo Baranwal, Mayank Hero, Alfred Violi, Angela Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109–2125 United States Department of Mechanical Engineering University of Michigan Ann ArborMI48109–2125 United States Departments of Chemical Engineering Biomedical Engineering Macromolecular Science and Engineering Biophysics Program University of Michigan Ann ArborMI48109–2125 United States

A wide variety of real life complex networks are prohibitively large for modeling, analysis and control. Understanding the structure and dynamics of such networks entails creating a smaller representative network that preserves its relevant topological and dynamical properties. While modern machine learning methods have enabled identification of governing laws for complex dynamical systems, their inability to produce white-box models with sufficient physical interpretation renders such methods undesirable to domain experts. In this paper, we introduce a hybrid black-box, white-box approach for the sparse identification of the governing laws for complex, highly coupled dynamical systems with particular emphasis on finding the influential reactions in chemical reaction networks for combustion applications, using a data-driven sparse-learning technique. The proposed approach identifies a set of influential reactions using species concentrations and reaction rates, with minimal computational cost without requiring additional data or simulations. The new approach is applied to analyze the combustion chemistry of H2 and C3H8 in a constant-volume homogeneous reactor. The influential reactions determined by the sparse-learning method are consistent with the current kinetics knowledge of chemical mechanisms. Additionally, we show that a reduced version of the parent mechanism can be generated as a combination of the significantly reduced influential reactions identified at different times and conditions and that for both H2 and C3H8 fuel, the reduced mechanisms perform closely to the parent mechanisms as a function of the ignition delay time over a wide range of conditions. Our results demonstrate the potential of the sparse-learning approach as an effective and efficient tool for dynamical system analysis and reduction. The uniqueness of this approach as applied to combustion systems lies in the ability to identify influential reactions in specified conditions and times dur

关键词： Learning systems

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Efficient Focusing with Large Numerical Aperture Using a Hybrid Metalens

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Physical Review Applied 2020年第4期13卷 044016-044016页

作者： Ming Kang Younes Ra'di Diego Farfan Andrea Alù Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 USA Photonics Initiative Advanced Science Research Center City University of New York New York 10031 USA Physics Program Graduate Center City University of New York New York 10016 USA Department of Electrical Engineering City College of The City University of New York New York 10031 USA

Focusing light using electrically thin layers is of paramount importance in several applications, from integrated optics to microwave engineering and sensing. Recently, gradient metasurfaces, which are electrically thin arrays of densely located polarizable particles, have been employed to perform different wave-front transformations, including focusing. In comparison to a bulk lens, these designs provide ultrathin geometries, but they suffer from fundamental limitations on their overall efficiency and achievable numerical aperture. Metagratings offer a solution for efficient beam steering at large angles, but it is challenging to utilize them in the small-angle limit. Here, we introduce a hybrid metalens design, which provides dramatic enhancement in lensing performance compared with that of state-of-the-art metasurfaces, combining metagratings and conventional gradient approaches. Our experimental prototype enables microwave focusing with large efficiency (η=0.479) and near-unity numerical aperture (NA=0.98), yielding a sharp focal point at the diffraction limit in the far field (FWHM=0.332λ). We propose a hybrid metalens design with exceptional performance in terms of efficiency and numerical aperture, opening up opportunities for high-throughput optical lithography, high-density data recording, focal plane arrays, radar, and communication systems.

关键词： Classical optics Integrated optics Metamaterials Optical & microwave phenomena Devices Surfaces

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Transient thermo-mechanical analysis for bimorph soft robot based on thermally responsive liquid crystal elastomers

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Applied Mathematics and Mechanics(English Edition) 2019年第7期40卷 943-952页

作者： Yun CUI Yafei YIN Chengjun WANG K. SIM Yuhang LI Cunjiang YU Jizhou SONG Institute of Solid Mechanics Beihang University Beijing 100191 China Department of Engineering Mechanics Soft Matter Research Center Key Laboratory of Soft Machines and Smart Devices of Zhejiang Province Zhejiang University Hangzhou 310027 China Materials Science and Engineering Program University of Houston Houston TX 77204 U. S.A. State Key Laboratory of Strength and Vibration of Mechanical Structures School of Aerospace Engineering Xi’an Jiaotong University Xi’an 710049 China Department of Mechanical Engineering University of Houston Houston TX 77204 U. S.A. Department of Electrical and Computer Engineering University of Houston Houston TX 77204 U. S.A. Department of Biomedical Engineering Texas Center for Superconductivity University of Houston Houston TX 77204 U. S.A.

Thermally responsive liquid crystal elastomers (LCEs) hold great promise in applications of soft robots and actuators because of the induced size and shape change with temperature. Experiments have successfully demonstrated that the LCE based bimorphs can be effective soft robots once integrated with soft sensors and thermal actuators. Here, we present an analytical transient thermo-mechanical model for a bimorph structure based soft robot, which consists of a strip of LCE and a thermal inert polymer actuated by an ultra-thin stretchable open-mesh shaped heater to mimic the unique locomotion behaviors of an inchworm. The coupled mechanical and thermal analysis based on the thermo-mechanical theory is carried out to underpin the transient bending behavior, and a systematic understanding is therefore achieved. The key analytical results reveal that the thickness and the modulus ratio of the LCE and the inert polymer layer dominate the transient bending deformation. The analytical results will not only render fundamental understanding of the actuation of bimorph structures, but also facilitate the rational design of soft robotics.

关键词： transient thermo-mechanical analysis soft robot thermal-responsive liq- uid crystal elastomer (LCE)

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Reply to “Comment on ‘Scattering Cancellation-Based Cloaking for the Maxwell-Cattaneo Heat Waves’”

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Physical Review Applied 2021年第5期15卷 058002-058002页

作者： M. Farhat S. Guenneau P.-Y. Chen A. Alù K.N. Salama Computer Electrical and Mathematical Science and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia UMI 2004 Abraham de Moivre-CNRS Imperial College London London SW7 2AZ United Kingdom Department of Electrical and Computer Engineering University of Illinois at Chicago Chicago Illinois 60607 USA 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

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Magnetic Control of Soft Chiral Phonons in PbTe

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Physical Review Letters 2022年第7期128卷 075901-075901页

作者： Andrey Baydin Felix G. G. Hernandez Martin Rodriguez-Vega Anderson K. Okazaki Fuyang Tay G. Timothy Noe, II Ikufumi Katayama Jun Takeda Hiroyuki Nojiri Paulo H. O. Rappl Eduardo Abramof Gregory A. Fiete Junichiro Kono Department of Electrical and Computer Engineering Rice University Houston Texas 77005 USA Smalley-Curl Institute Rice University Houston Texas 77005 USA Instituto de Física Universidade de São Paulo São Paulo São Paulo 05508-090 Brazil Theoretical Division Los Alamos National Laboratory Los Alamos New Mexico 87545 USA Laboratório Associado de Sensores e Materiais Instituto Nacional de Pesquisas Espaciais São José dos Campos São Paulo 12201-970 Brazil Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston Texas 77005 USA Department of Physics Graduate School of Engineering Science Yokohama National University Yokohama 240-8501 Japan Institute for Materials Research Tohoku University Sendai 980-8577 Japan Department of Physics Northeastern University Boston Massachusetts 02115 USA Department of Physics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Physics and Astronomy Rice University Houston Texas 77005 USA Department of Material Science and NanoEngineering Rice University Houston Texas 77005 USA

PbTe crystals have a soft transverse optical phonon mode in the terahertz frequency range, which is known to efficiently decay into heat-carrying acoustic phonons, resulting in anomalously low thermal conductivity. Here, we studied this phonon via polarization-dependent terahertz spectroscopy. We observed softening of this mode with decreasing temperature, indicative of incipient ferroelectricity, which we explain through a model including strong anharmonicity with a quartic displacement term. In magnetic fields up to 25 T, the phonon mode splits into two modes with opposite handedness, exhibiting circular dichroism. Their frequencies display Zeeman splitting together with an overall diamagnetic shift with increasing magnetic field. Using a group-theoretical approach, we demonstrate that these observations are the result of magnetic field-induced morphic changes in the crystal symmetries through the Lorentz force exerted on the lattice ions. Thus, our Letter reveals a novel process of controlling phonon properties in a soft ionic lattice by a strong magnetic field.

关键词： Chirality Diamagnetism Magneto-dielectric effect Optical phonons Thermal conductivity Zeeman effect Terahertz time-domain spectroscopy

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Spectral DiffuserCam: lensless snapshot hyperspectral imaging with a spectral filter array

arXiv

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arXiv 2020年

作者： Monakhova, Kristina Yanny, Kyrollos Aggarwal, Neerja Waller, Laura Department of Electrical Engineering & Computer Sciences University of California BerkeleyCA94720 United States UCB/UCSF Joint Graduate Program in Bioengineering University of California BerkeleyCA94720 United States

Hyperspectral imaging is useful for applications ranging from medical diagnostics to crop monitoring;however, traditional scanning hyperspectral imagers are prohibitively slow and expensive for widespread adoption. Snapshot techniques exist but are often confined to bulky bench-top setups or have low spatio-spectral resolution. In this paper, we propose a novel, compact, and inexpensive computational camera for snapshot hyperspectral imaging. Our system consists of a repeated spectral filter array placed directly on the image sensor and a diffuser placed close to the sensor. Each point in the world maps to a unique pseudorandom pattern on the spectral filter array, which encodes multiplexed spatio-spectral information. A sparsity-constrained inverse problem solver then recovers the hyperspectral volume with good spatio-spectral resolution. By using a spectral filter array, our hyperspectral imaging framework is flexible and can be designed with contiguous or non-contiguous spectral filters that can be chosen for a given application. We provide theory for system design, demonstrate a prototype device, and present experimental results with high spatio-spectral resolution. © 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement Copyright © 2020, The Authors. All rights reserved.

关键词： Spectroscopy

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Bulk-plasmon-mediated free-electron radiation beyond the conventional formation time

arXiv

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arXiv 2022年

作者： Tay, Fuyang Lin, Xiao Shi, Xihang Chen, Hongsheng Kaminer, Ido Zhang, Baile Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation ZJUHangzhou Global Science and Technology Innovation Center College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley–Curl Institute Rice University HoustonTX77005 United States International Joint Innovation Center The Electromagnetics Academy Zhejiang University Zhejiang University Haining314400 China Department of Electrical Engineering Technion-Israel Institute of Technology Haifa32000 Israel Jinhua Institute of Zhejiang University Zhejiang University Jinhua321099 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 637371 Singapore Centre for Disruptive Photonic Technologies Nanyang Technological University 637371 Singapore

Free-electron radiation is a fundamental photon emission process that is induced by fast-moving electrons interacting with optical media. Historically, it has been understood that, just like any other photon emission process, free-electron radiation must be constrained within a finite time interval known as the "formation time", whose concept is applicable to both Cherenkov radiation and transition radiation, the two basic mechanisms describing radiation from a bulk medium and from an interface, respectively. Here we reveal an alternative mechanism of free-electron radiation far beyond the previously defined formation time. It occurs when a fast electron crosses the interface between vacuum and a plasmonic medium supporting bulk plasmons. While emitted continuously from the crossing point on the interface — thus consistent with the features of transition radiation — the extra radiation beyond the conventional formation time is supported by a long tail of bulk plasmons following the electron’s trajectory deep into the plasmonic medium. Such a plasmonic tail mixes surface and bulk effects, and provides a sustained channel for electron-interface interaction. These results also settle the historical debate in Ferrell radiation, regarding whether it is a surface or bulk effect, from transition radiation or plasmonic oscillation. Copyright © 2022, The Authors. All rights reserved.

关键词： Plasmonics

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Detection of hard exudates in fundus images using convolutional neural networks 7

Detection of hard exudates in fundus images using convolutio...

引用

7th International Conference on Green and Human Information Technology, ICGHIT 2019

作者： Poonkasem, Ittided Theera-Umpon, Nipon Auephanwiriyakul, Sansanee Patikulsila, Direk Biomedical Engineering Institute Chiang Mai University Chiang Mai Thailand Graduate School Chiang Mai University Chiang Mai Thailand Department of Electrical Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand Department of Computer Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand Department of Ophthalmology Faculty of Medicine Chiang Mai University Chiang Mai Thailand

ISBN: (纸本)9781728106274

The patients with diabetes have a chance to have blindness. An impairment of metabolism can cause a high glucose level in blood vessel leading to an abnormality called hard exudates. Hard exudates are often arranged in clumps or circinate rings and located in the outer layer of the retina. The aim of this research is to detect hard exudates by applying image processing techniques and classify them by using convolutional neuron network (CNN). DIARETDB1 dataset is used in the experiments. The proposed method achieves the area under the curve (AUC) of 0.97 and 0.95 on the training and validation sets, respectively, of 10-fold cross validation experiment. These show that the combination of image processing techniques, three channels of fundus images, and CNN can perform as a promising classification tool in hard exudates detection system. © 2019 IEEE.

关键词： Blood vessels

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Persistent flat band splitting and strong selective band renormalization in a kagome magnet thin film

arXiv

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arXiv 2024年

作者： Ren, Zheng Huang, Jianwei Tan, Hengxin Biswas, Ananya Pulkkinen, Aki Zhang, Yichen Xie, Yaofeng Yue, Ziqin Chen, Lei Xie, Fang Allen, Kevin Wu, Han Ren, Qirui Rajapitamahuni, Anil Kundu, Asish K. Vescovo, Elio Kono, Junichiro Morosan, Emilia Dai, Pengcheng Zhu, Jian-Xin Si, Qimiao Minár, Ján Yan, Binghai Yi, Ming Department of Physics and Astronomy Rice University HoustonTX77005 United States Department of Condensed Matter Physics Weizmann Institute of Science Rehovot Israel New Technologies-Research Center University of West Bohemia Plzeň301 00 Czech Republic Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States National Synchrotron Light Source II Brookhaven National Lab UptonNY United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Chemistry Rice University HoustonTX77005 United States Theoretical Division Center for Integrated Nanotechnologies Los Alamos National Laboratory Los AlamosNM United States

Magnetic kagome materials provide a fascinating playground for exploring the interplay of magnetism, correlation and topology. Many magnetic kagome systems have been reported including the binary FemXn (X=Sn, Ge;m:n = 3:1, 3:2, 1:1) family and the rare earth RMn6Sn6 (R = rare earth) family, where their kagome flat bands are calculated to be near the Fermi level in the paramagnetic phase. While partially filling a kagome flat band is predicted to give rise to a Stoner-type ferromagnetism, experimental visualization of the magnetic splitting across the ordering temperature has not been reported for any of these systems due to the high ordering temperatures, hence leaving the nature of magnetism in kagome magnets an open question. Here, we probe the electronic structure with angle-resolved photoemission spectroscopy in a kagome magnet thin film FeSn synthesized using molecular beam epitaxy. We identify the exchange-split kagome flat bands, whose splitting persists above the magnetic ordering temperature, indicative of a local moment picture. Such local moments in the presence of the topological flat band are consistent with the compact molecular orbitals predicted in theory. We further observe a large spin-orbital selective band renormalization in the Fe dxy+dx2-y2spin majority channel reminiscent of the orbital selective correlation effects in the iron-based superconductors. Our discovery of the coexistence of local moments with topological flat bands in a kagome system echoes similar findings in magic-angle twisted bilayer graphene, and provides a basis for theoretical effort towards modeling correlation effects in magnetic flat band systems. © 2024, CC BY.

关键词： Iron-based Superconductors

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