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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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Intrinsic Exciton-Phonon Coupling and Tuning in ZnTe Nanowires Probed by Resonant Raman Scattering

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Physical Review applied 2020年第1期13卷 011001-011001页

作者： Yingyan Yi Jason K. Marmon Yuanping Chen Fan Zhang Tao Sheng Priyalal S. Wijewarnasuriya Haitao Zhang Yong Zhang Department of Electrical and Computer Engineering University of North Carolina at Charlotte Charlotte North Carolina 28223 USA School of Science Wuhan University of Technology Wuhan Hubei 430070 China Nanoscale Science Graduate Program University of North Carolina at Charlotte Charlotte North Carolina 28223 USA US Army Research Laboratory Adelphi Maryland 20783 USA Optical Science and Engineering Graduate Program University of North Carolina at Charlotte Charlotte North Carolina 28223 USA Department of Mechanical Engineering and Engineering Science University of North Carolina at Charlotte Charlotte North Carolina 28223 USA

We show in ZnTe that the 2LO to 1LO resonant Raman intensity ratio, a measure of electron-phonon coupling (EPC), exhibits a much larger intrinsic value than that previously reported and minimal change from bulk to 30 nm nanowires. However, the ratio can be tuned extrinsically over one order in magnitude controllably either during or after growth, and thus, allows for the programing of EPC or quantum information in nanoscale devices. This work helps to understand a matter of controversy in the literature for more than three decades, regarding the EPC size dependence in nanostructures, and provides unambiguous experimental results for validating EPC theories with reduced dimensionality.

关键词： Crystal defects Electron-phonon coupling Excitons Optoelectronics Nanowires Semiconductor compounds Photoluminescence Raman spectroscopy

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Observation of the dual quantum spin Hall insulator by density-tuned correlations in a van der Waals monolayer

arXiv

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arXiv 2024年

作者： Tang, Jian Ding, Thomas Siyuan Chen, Hongyu Gao, Anyuan Qian, Tiema Huang, Zumeng Sun, Zhe Han, Xin Strasser, Alex Li, Jiangxu Geiwitz, Michael Shehabeldin, Mohamed Belosevich, Vsevolod Wang, Zihan Wang, Yiping Watanabe, Kenji Taniguchi, Takashi Bell, David C. Wang, Ziqiang Fu, Liang Zhang, Yang Qian, Xiaofeng Burch, Kenneth S. Shi, Youguo Ni, Ni Chang, Guoqing Xu, Su-Yang Ma, Qiong Department of Physics Boston College Chestnut HillMA United States Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore Singapore Department of Chemistry and Chemical Biology Harvard University CambridgeMA United States Department of Physics and Astronomy and California NanoSystems Institute University of California Los Angeles Los AngelesCA United States Beijing National Laboratory for Condensed Matter Physics Institute of Physics Chinese Academy of Sciences Beijing China Department of Materials Science and Engineering Texas A&M University College StationTX United States Department of Physics and Astronomy University of Tennessee KnoxvilleTN United States Min H. Kao Department of Electrical Engineering and Computer Science University of Tennessee KnoxvilleTN United States Research Center for Electronic and Optical Materials National Institute for Materials Science Tsukuba Japan Research Center for Materials Nanoarchitectonics National Institute for Materials Science Tsukuba Japan Harvard John A. Paulson School of Engineering and Applied Sciences The Center for Nanoscale system Harvard University CambridgeMA United States Department of Physics Massachusetts Institute of Technology CambridgeMA United States CIFAR Azrieli Global Scholars program CIFAR Toronto Canada

The convergence of topology and correlations represents a highly coveted realm in the pursuit of novel quantum states of matter [1, 2]. Introducing electron correlations to a quantum spin Hall (QSH) insulator can lead to the emergence of a fractional topological insulator and other exotic time-reversal-symmetric topological order [3- 10], not possible in quantum Hall and Chern insulator systems. However, the QSH insulator with quantized edge conductance remains rare, let alone that with significant correlations. In this work, we report a novel dual QSH insulator within the intrinsic monolayer crystal of TaIrTe4, arising from the interplay of its single-particle topology and density-tuned electron correlations. At charge neutrality, monolayer TaIrTe4 demonstrates the QSH insulator that aligns with single-particle band structure calculations, manifesting enhanced nonlocal transport and quantized helical edge conductance. Interestingly, upon introducing electrons from charge neutrality, TaIrTe4 only shows metallic behavior in a small range of charge densities but quickly goes into a new insulating state, entirely unexpected based on TaIrTe4's single-particle band structure. This insulating state could arise from a strong electronic instability near the van Hove singularities (VHS), likely leading to a charge density wave (CDW). Remarkably, within this correlated insulating gap, we observe a resurgence of the QSH state, marked by the revival of nonlocal transport and quantized helical edge conduction. Our observation of helical edge conduction in a CDW gap could bridge spin physics and charge orders. The discovery of a dual QSH insulator introduces a new method for creating topological flat minibands via CDW superlattices, which offer a promising platform for exploring time-reversal-symmetric fractional phases and electromagnetism [3-5, 11, 12]. Copyright © 2024, The Authors. All rights reserved.

关键词： Charge density waves

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Decision Making using Internet of Things and Machine Learning: A bibliometric approach to tracking main research themes

Decision Making using Internet of Things and Machine Learnin...

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2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy, ICDABI 2020

作者： Gamboa-Rosales, N.K. Castorena-Robles, A. Casas-Valadez, M.A. Cobo, M.J. Castaneda-Miranda, R. Lopez-Robles, J.R. CONACYT-Autonomous University of Zacatecas Academic Unit of Electrical Engineering Zacatecas Mexico Monterrey Institute of Technology and Higher Education Biotechnology Engineering Queretaro Mexico Autonomous University of Zacatecas Academic Unit of Accounting and Administration Zacatecas Mexico University of Cadiz Department of Computer Science and Engineering Cadiz Spain Autonomous University of Zacatecas Post. Program of Eng. and Applied Tech. National Lab. CONACYT-SEDEAM Zacatecas Mexico

ISBN: (纸本)9781728196756

The internet has become an integral part of our life, we connect daily for informational, social, entertainment and even work and economic purposes. Therefore, it is completely normal to connect to the internet;But it is not only people, also these everyday objects or things in our environment who connect to the network to take advantage of its benefits. This next stage in the evolution of the internet, in which connectivity extends to the objects which surround us, is known as the Internet of Things. Sensors, Machines, Devices, Wearables are part of the Internet of Things and these can be identified to be recognized and interact without the need for a human being. With the Internet of Things, the connection extends to any type of object. All these interconnected devices and people produce an immense amount of data, when analyzed, they become a tool that allows organizations to make wise decisions in real time by having information on various market situations and ensuring a better understanding of behavior and consumer preferences. One of the disciplines of Artificial Intelligence responsible for analyzing this large amount of data is Machine Learning, whose sole purpose is to improve the Decision-Making process. To understand the relationship between Internet of Things, application of Machine Learning and the Decision Making process, a bibliometric analysis is carried out from 2013 to 2020 to know its evolution, trends, research areas, authors and other aspects using Scopus. © 2020 IEEE.

关键词： Decision making

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Response to Comment on (Novel two-dimensional porous graphitic carbon nitride C6N7 monolayer: A First-principle calculations [Appl. Phys. Lett. 2021, 119, 142102])

arXiv

引用

arXiv 2022年

作者： Bafekry, Asadollah Faraji, Mehrdad Fadlallah, Mohamed M. Sarsari, I. Abdolhosseini Jappor, Hamad R. Fazeli, Sara Ghergherehchi, Mitra Department of Radiation Application Shahid Beheshti University Tehran Iran Micro and Nanotechnology Graduate Program TOBB University of Economics and Technology Sogutozu Caddesi No 43 Sogutozu Ankara06560 Turkey Department of Physics Faculty of Science Benha University Benha13518 Egypt Department of Physics Isfahan University of Technology Isfahan84156-83111 Iran Department of Physics College of Education for Pure Sciences University of Babylon Hilla Iraq Department of Material Science and Engineering Sharif University of Technology PO Box 11155-9466 Tehran Iran Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Recently, reported a comments on the our paper [Appl. Phys. Lett. 119, 142102(2021)]. With our response, the APL journal rejected their non scientificcomments. There are some ambiguities about their claim: 1-They can check thephonon dispersion of their structure to see ZA out-of-plane mode. 2-They reportthe uniaxial stress-strain responses in Fig 2., which is unrelated to ourpaper. For a more helpful understanding of the mechanical properties of thenovel C6N7 monolayer, they can publish a paper. 3-They mentioned: Using the DFTmethod and with assuming a thickness of 3.35 A for the C6N7 monolayer based ongraphene thickness. Why did they choose this thickness while we know our C6N7monolayer is at without buckling? The distance of ZA out-of-plane movement ofions in C6N7 is different from Graphene. © 2022, CC BY.

关键词： Monolayers

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Electrostatic Properties and Ions Elimination Effect of Polyvinyl Chloride (PVC) Adhesive Tape Manufacturing

Electrostatic Properties and Ions Elimination Effect of Poly...

引用

International electrical engineering Congress (iEECON)

作者： Tatsanee Jenbanphue Komsan Hongesombut Kulsawasd Jitkajornwanich Siwapon Srisonphan Graduate program in safety engineering Kasetsart University Bangkok Thailand Department of Electrical Engineering Kasetsart University Bangkok Thailand Department of Computer Science King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand

ISBN: (数字)9781728130767

ISBN: (纸本)9781728130774

Electrostatic discharges (ESD) can release large amounts of energy to products and humans, causing product failure and pain, respectively. In this research, we elucidate the electrostatic charge generation, and discharge phenomena in real polyvinyl chloride (PVC) based electrical tape factory, which is primarily operated by the roll to roll manufacturing process. We perform the electrostatic potential measurement to identify the critical process of charge generation and to eliminate static charge at the source in order to prevent incidents caused by electrostatic discharge to operators or staff in the winding process. We also perform a numerical simulation-based finite element method (FEM) that provides modeling of an induced electric field, allowing the electrostatic discharge. The maximum potential is ~20 kV measured at 25 mm, indicating that the meter was induced by the electric field approximately ~0.8 MV/m, corresponding to surface charges density is ~ 10 μC/m 2 . Therefore, we introduced the ionization emitter bar in this case because it is feasible to install to the current infrastructure of the tested factory. The ionization emitter appears to reduce the electrostatic charge deposited on the PVC surface ~ 30% of the original charges. Therefore, installing a charge-dissipation technology at a proper location or combining with other methods, the electrostatic charge generation can be minimized even in roll to roll process.

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Big Data Governance for Building A Smart Cities 10

Big Data Governance for Building A Smart Cities

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10th International Conference on ICT for Smart Society, ICISS 2019

作者： Zulkarnain, Novan Kosala, Raymond Ranti, Benny Supangkat, Suhono Harso Bina Nusantara University Computer Science Department BINUS Graduate Program Doctor of Computer Science Information Systems Department Jakarta11480 Indonesia Universitas Indonesia Computer Science Department Depok16424 Indonesia Institute of Technology Bandung School of Electrical and Informatics Engineering Bandung40132 Indonesia

ISBN: (纸本)9781728148809

There have been many studies conducted related to Smart City, IT Governance and Big Data. In this study aims to find out how the relationship between the three and how to form a framework to explain it. The methodology used is qualitative by looking for some literature on smart city framework, IT Governance framework, and a Big Data framework. From these results, an overall picture of the relationship between the three is concluded, where Big Data has a role in IT Governance. and also the relationship of IT Governance to the realization of Smart City. And the final results of this study produce a framework to explain the relationship between Smart City, IT Governance and Big Data. © 2019 IEEE.

关键词： Big data

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Roadmap for phase change materials in photonics and beyond (vol 26, 107946, 2023)

引用

Iscience 2023年第12期26卷 107946页

作者： Prabhathan, Patinharekandy Sreekanth, Kandammathe Valiyaveedu Teng, Jinghua Ko, Joo Hwan Yoo, Young Jin Jeong, Hyeon-Ho Lee, Yubin Zhang, Shoujun Cao, Tun Popescu, Cosmin-Constantin Mills, Brian Gu, Tian Fang, Zhuoran Chen, Rui Tong, Hao Wang, Yi He, Qiang Lu, Yitao Liu, Zhiyuan Yu, Han Mandal, Avik Cui, Yihao Ansari, Abbas Sheikh Bhingardive, Viraj Kang, Myungkoo Lai, Choon Kong Merklein, Moritz Mueller, Maximilian J. Song, Young Min Tian, Zhen Hu, Juejun Losurdo, Maria Majumdar, Arka Miao, Xiangshui Chen, Xiao Gholipour, Behrad Richardson, Kathleen A. Eggleton, Benjamin J. Sharda, Kanudha Wuttig, Matthias Singh, Ranjan Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 21 Nanyang Link Singapore 637371 Singapore Centre for Disruptive Photonic Technologies The Photonic Institute 50 Nanyang Avenue Singapore 639798 Singapore Institute of Materials Research and Engineering (IMRE) Agency for Science Technology and Research (A∗STAR) 2 Fusionopolis Way Innovis #08-03 Singapore 138634 Republic of Singapore School of Electrical Engineering and Computer Science Gwangju Institute of Science and Technology Gwangju 61005 Republic of Korea School of Materials Science and Engineering Gwangju Institute of Science and Technology Gwangju 61005 Republic of Korea DELL Center for Terahertz Waves and College of Precision Instrument and Optoelectronics Engineering Key Laboratory of Optoelectronic Information Technology (Ministry of Education of China) Tianjin University Tianjin 300072 China DELL School of Optoelectronic Engineering and Instrumentation Science Dalian University of Technology Dalian 116024 China Department of Materials Science &amp Engineering Massachusetts Institute of Technology Cambridge MA USA Materials Research Laboratory Massachusetts Institute of Technology Cambridge MA USA Department of Electrical &amp Computer Engineering University of Washington Washington Seattle USA Wuhan National Research Center for Optoelectronics School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan China Institute of Advanced Materials Beijing Normal University Beijing 100875 China Nanoscale Optics Lab ECE Department University of Alberta Edmonton Canada CREOL College of Optics and Photonics University of Central Florida Orlando FL USA Institute of Photonics and Optical Science (IPOS) School of Physics The University of Sydney New South Wales NSW 2006 Australia The University of Sydney Nano Institute (Sydney Nano) The University of Sydney New South Wales NSW 2006 Australia Insti

Phase Change Materials (PCMs) have demonstrated tremendous potential as a platform for achieving diverse functionalities in active and reconfigurable micro-nanophotonic devices across the electromagnetic spectrum, ranging from terahertz to visible frequencies. This comprehensive roadmap reviews the material and device aspects of PCMs, and their diverse applications in active and reconfigurable micro-nanophotonic devices across the electromagnetic spectrum. It discusses various device configurations and optimization techniques, including deep learning-based metasurface design. The integration of PCMs with Photonic Integrated Circuits and advanced electric-driven PCMs are explored. PCMs hold great promise for multifunctional device development, including applications in non-volatile memory, optical data storage, photonics, energy harvesting, biomedical technology, neuromorphic computing, thermal management, and flexible electronics.

关键词： Physics applied physics Materials application

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Spatiotemporally controlled room temperature exciton transport under dynamic pressure

arXiv

引用

arXiv 2021年

作者： Datta, Kanak Lyu, Zhengyang Li, Zidong Taniguchi, Takashi Watanabe, Kenji Deotare, Parag B. Department of Electrical and Computer Engineering College of Engineering University of Michigan Ann ArborMI48109 United States Applied Physics Program College of Literature Science and Arts University of Michigan Ann ArborMI48109 United States International Center for Materials Nanoarchitectonics National Institute for Materials Science 1-1 Namiki Ibaraki305-0044 Japan Research Center for Functional Materials National Institute for Materials Science 1-1 Namiki Tsukuba305-0044 Japan

Two-dimensional transition metal dichalcogenides (TMDs) provide an attractive platform for studying strain dependent exciton transport at room temperature due to large exciton binding energy and strong bandgap sensitivity to mechanical stimuli. Here, we use Rayleigh type surface acoustic wave (SAW) to demonstrate controlled and directional exciton transport under weak coupling regime at room temperature. We screen the in-plane piezoelectric field using photogenerated carriers to study transport under type-I bandgap modulation and measure a maximum exciton drift velocity of 600 m/s. Furthermore, we demonstrate precise steering of exciton flux by controlling the relative phase between the input RF excitation and exciton photogenerations. The results provide important insight into the weak coupling regime between dynamic strain wave and room temperature excitons in a 2D semiconductor system and pave way to exciting applications of excitonic devices in data communication and processing, sensing and energy conversion. Copyright © 2021, The Authors. All rights reserved.

关键词： Excitons

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Iterative quantum optimization of spin glass problems with rapidly oscillating transverse fields

arXiv

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arXiv 2024年

作者： Barton, Brandon Sagal, Jacob Feeney, Sean Grattan, George Patnaik, Pratik Oganesyan, Vadim Carr, Lincoln D. Kapit, Eliot Quantum Engineering Program Colorado School of Mines 1523 Illinois St GoldenCO80401 United States Department of Applied Mathematics and Statistics Colorado School of Mines 1500 Illinois St GoldenCO80401 United States Center for Computational Quantum Physics Flatiron Institute 162 5th Avenue New YorkNY10010 United States Department of Physics Colorado School of Mines 1523 Illinois St GoldenCO80401 United States Department of Computer Science Colorado School of Mines 1500 Illinois St GoldenCO80401 United States Department of Physics and Astronomy College of Staten Island City University of New York Staten IslandNY10314 United States Physics program and Initiative for the Theoretical Sciences The Graduate Center City University of New York New YorkNY10016 United States

In this work, we introduce a new iterative quantum algorithm, called Iterative Symphonic Tunneling for Satisfiability problems (IST-SAT), which solves quantum spin glass optimization problems using high-frequency oscillating transverse fields. IST-SAT operates as a sequence of iterations, in which bitstrings returned from one iteration are used to set spin-dependent phases in oscillating transverse fields in the next iteration. Over several iterations, the novel mechanism of the algorithm steers the system toward the problem ground state. We benchmark IST-SAT on sets of hard MAX-3-XORSAT problem instances with exact state vector simulation, and report polynomial speedups over trotterized adiabatic quantum computation (TAQC) and the best known semi-greedy classical algorithm. When IST-SAT is seeded with a sufficiently good initial approximation, the algorithm converges to exact solution(s) in a polynomial number of iterations. Our numerical results identify a critial Hamming radius(CHR), or quality of initial approximation, where the time-to-solution crosses from exponential to polynomial scaling in problem size. By combining IST-SAT with future classical or quantum approximation algorithms, larger gains may be achieved. The mechanism we present in this work thus presents a new path toward achieving quantum advantage in optimization. © 2024, CC BY.

关键词： Combinatorial optimization

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