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Correction: Materials laboratories of the future for alloys, amorphous, and composite materials (MRS Bulletin, (2025), 50, 2, (190-207), 10.1557/s43577-024-00846-y)

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MRS Bulletin 2025年 1-2页

作者： Banerjee, Sarbajit Meng, Y. Shirley Minor, Andrew M. Zhang, Minghao Zaluzec, Nestor J. Chan, Maria K.Y. Seidler, Gerald McComb, David W. Agar, Joshua Mukherjee, Partha P. Melot, Brent Chapman, Karena Guiton, Beth S. Klie, Robert F. McCue, Ian D. Voyles, Paul M. Robertson, Ian Li, Ling Chi, Miaofang Destino, Joel F. Devaraj, Arun Marquis, Emmanuelle A. Segre, Carlo U. Liu, Huinan H. Yang, Judith C. Momeni, Kasra Misra, Amit Abdolrahim, Niaz Medvedeva, Julia E. Cai, Wenjun Sehirlioglu, Alp Dizbay-Onat, Melike Mehta, Apurva Graham-Brady, Lori Maruyama, Benji Rajan, Krishna Warner, Jamie H. Taheri, Mitra L. Kalinin, Sergei V. Reeja-Jayan, B. Schwarz, Udo D. Simon, Sindee L. Brown, Craig M. Department of Chemistry and Department of Materials Science & Engineering Texas A & M University College Station United States Pritzker School of Molecular Engineering The University of Chicago Chicago United States Department of Materials Science & Engineering University of California Berkeley Berkeley United States National Center for Electron Microscopy Molecular Foundry Lawrence Berkeley National Laboratory Berkeley United States Center for Nanoscale Materials Argonne National Laboratory Lemont United States Department of Physics University of Washington Seattle United States Department of Materials Science & Engineering The Ohio State University Columbus United States Department of Mechanical Engineering and Mechanics Drexel University Philadelphia United States School of Mechanical Engineering Purdue University West Lafayette United States Department of Chemistry University of Southern California Los Angeles United States Department of Chemistry Stony Brook University The State University of New York Stony Brook United States Department of Chemistry University of Kentucky Lexington United States Department of Physics University of Illinois at Chicago Chicago United States Department of Materials Science & Engineering Northwestern University Evanston Bangladesh Department of Materials Science & Engineering University of Wisconsin–Madison Madison United States Department of Materials Science and Engineering University of Pennsylvania Philadelphia United States Department of Mechanical Engineering and Materials Science Duke University Durham United States Department of Chemistry Creighton University Omaha United States Physical and Computational Sciences Directorate Pacific Northwest National Laboratory Richland United States Department of Materials Science & Engineering University of Michigan–Ann Arbor Ann Arbor United States Department of Physics Illinois Institute of Technology Chicago United States Department of Bioengineering and the Mater

This article was updated to correct Minghao Zhang’s affiliation from "Pritzker School of Molecular engineering, The University of Chicago, Chicago, USA" to "Pritzker School of Molecular engineering, The University of Chicago, Chicago, USA;Argonne National Laboratory, Lemont, USA." Argonne National Laboratory was left off the original publication. © The Author(s) 2025.

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Humans vs. ChatGPT: Evaluating Annotation Methods for Financial Corpora

Humans vs. ChatGPT: Evaluating Annotation Methods for Financ...

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IEEE International Conference on Big Data

作者： Jamshed Kaikaus Haoen Li Robert J. Brunner Informatics Program University of Illinois Urbana-Champaign Urbana Illinois USA Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh Pennsylvania USA Department of Accountancy University of Illinois Urbana-Champaign Urbana Illinois USA

Given the vast amount of unstructured financial text data available today, there is a high demand for reliable, quality annotations to facilitate robust model development. However, traditional methods can often be expensive and time-inefficient. In this study, we investigate annotations for emotion, sentiment, and cognitive dissonance generated by the large language models (LLMs), GPT-3.5 and GPT-4, for quarterly earnings conference calls and compare them against human annotations obtained via traditional methods. We also investigate different prompt engineering choices on LLM annotation quality, experimenting with 4 styles of prompts centered around varying the amount of contextual information given and how it is presented to the models. Our results show the GPT models are not only more consistent and reliable than human annotators, but also provide annotations in a more cost- and time-efficient manner.

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Chiral exceptional point enhanced active tuning and nonreciprocity in micro-resonators

arXiv

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arXiv 2024年

作者： Lee, Hwaseob Chang, Lorry Kecebas, Ali Mao, Dun Xiao, Yahui Li, Tiantian Alù, Andrea Özdemir, Sahin K. Gu, Tingyi Department of Electrical and Computer Engineering University of Delaware NewarkDE19716 United States Department of Engineering Science and Mechanics Pennsylvania State University University ParkPA16802 United States Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States Department of Electrical and Computer Engineering Saint Louis University Saint LouisMO63103 United States

Exceptional points (EPs) have been extensively explored in mechanical, acoustic, plasmonic, and photonic systems. However, little is known about the role of EPs in tailoring the dynamic tunability of optical devices. A specific type of EPs known as chiral EPs has recently attracted much attention for controlling the flow of light and for building sensors with better responsivity. A recently demonstrated route to chiral EPs via lithographically defined symmetric Mie scatterers on the rim of resonators has not only provided the much-needed mechanical stability for studying chiral EPs, but also helped reduce losses originating from nanofabrication imperfections, facilitating the insitu study of chiral EPs and their contribution to the dynamics and tunability of resonators. Here, we use asymmetric Mie scatterers to break the rotational symmetry of a microresonator, to demonstrate deterministic thermal tuning across a chiral EP, and to demonstrate EP-mediated chiral optical nonlinear response and efficient electro-optic tuning. Our results indicate asymmetric electro-optic modulation with up to 17dB contrast at GHz and CMOS-compatible voltage levels. Such wafer-scale nano-manufacturing of chiral electro-optic modulators and the chiral EP-tailored tunning may facilitate new micro-resonator functionalities in quantum information processing, electromagnetic wave control, and optical interconnects. © 2024, CC BY.

关键词： Microresonators

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MathSpeech: Leveraging Small LMs for Accurate Conversion in Mathematical Speech-to-Formula 39

MathSpeech: Leveraging Small LMs for Accurate Conversion in ...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Hyeon, Sieun Jung, Kyudan Won, Jaehee Kim, Nam-Joon Ryu, Hyun Gon Lee, Hyuk-Jae Do, Jaeyoung Department of Electrical and Computer Engineering Seoul National University Korea Republic of Department of Mathematics Chung-Ang University Korea Republic of College of Liberal Studies Seoul National University Korea Republic of NVIDIA United States Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of

ISBN: (纸本)157735897X

In various academic and professional settings, such as mathematics lectures or research presentations, it is often necessary to convey mathematical expressions orally. However, reading mathematical expressions aloud without accompanying visuals can significantly hinder comprehension, especially for those who are hearing-impaired or rely on subtitles due to language barriers. For instance, when a presenter reads Euler's Formula, current Automatic Speech Recognition (ASR) models often produce a verbose and error-prone textual description (e.g., e to the power of i x equals cosine of x plus i side of x), instead of the concise LATEX format (i.e., eix = cos(x) + isin(x)), which hampers clear understanding and communication. To address this issue, we introduce MathSpeech, a novel pipeline that integrates ASR models with small Language Models (sLMs) to correct errors in mathematical expressions and accurately convert spoken expressions into structured LATEX representations. Evaluated on a new dataset derived from lecture recordings, MathSpeech demonstrates LATEX generation capabilities comparable to leading commercial Large Language Models (LLMs), while leveraging fine-tuned small language models of only 120M parameters. Specifically, in terms of CER, BLEU, and ROUGE scores for LATEX translation, MathSpeech demonstrated significantly superior capabilities compared to GPT-4o. We observed a decrease in CER from 0.390 to 0.298, and higher ROUGE/BLEU scores compared to GPT-4o. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

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Testbed Demonstration of a Microgrid Building Block Prototype

Testbed Demonstration of a Microgrid Building Block Prototyp...

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Annual Conference of Industrial Electronics Society

作者： Baza Somda Akshay Kumar Jain Haris Bin Ashraf Chen-Ching Liu Richard Zhang Alok Kumar Bharati Francis Tuffner Kevin Schneider Dan Ton Bradley Department of Electrical and Computer Engineering Virginia Tech Blacksburg Virginia Pacific Northwest National Laboratory Energy and Environment Directorate Richland Washington U.S. Department of Energy (DOE) Office of Electricity (OE) Microgrid R&D Program Washington DC

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

With the adoption of ambitious climate action goals, the penetration level of distributed energy resources (DERs) is rapidly increasing. Microgrids are an efficient way to integrate these DERs, facilitating their operation and control. Additionally, microgrids enhance the overall resilience of the distribution system by serving critical loads both within and outside their boundaries. However, the need for substantial customized engineering leads to a high cost of development, installation and maintenance of microgrids. To address this challenge, Microgrid Building Blocks (MBB) are proposed to reduce the deployment cost of microgrids through modular, standardized design and implementation. This work presents a testbed demonstrating the integrated power conversion, control, and communication functionalities of an MBB. The testbed is formed by a real-time electromagnetic transient (EMT) simulation combined with a hardware and software prototype of MBB. The use cases supported by the MBB testbed are enumerated. The islanded operation, voltage regulation, and optimal dispatch capabilities of an MBB-based microgrid controller are validated through a case study.

关键词： Costs Refining Prototypes Microgrids Software Real-time systems Power conversion Voltage control Testing Resilience

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Cylindrical-Lens-Embedded Photonic Crystal Based on Self-Collimation 5

Cylindrical-Lens-Embedded Photonic Crystal Based on Self-Col...

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5th IEEE Research and Applications of Photonics in Defense Conference, RAPID 2022

作者： Xia, Chun Gutierrez, Jesus J. Kuebler, Stephen M. Rumpf, Raymond C. Touma, Jimmy University of Central Florida The College of Optics and Photonics Creol OrlandoFL32816 United States University of Texas at El Paso Em Lab Department of Electrical and Computer Engineering El PasoTX79968 United States Materials Science and Engineering University of Central Florida Creol The College of Optics and Photonics Chemistry Department OrlandoFL32816 United States Computational Science Program University of Texas at El Paso Em Lab Department of Electrical and Computer Engineering El PasoTX79968 United States Eglin Afb AFRL/Munitions Directorate Integrated Sensing and Processing Branch FL32542 United States

Independent optical power and phase control is experimentally demonstrated in a self-collimating PC based on rod-into-wall unit cell and fabricated in a low-refractive-index medium by multiphoton lithography. © 2... 详细信息

ISBN: (数字)9781665402231

ISBN: (纸本)9781665402231

关键词： Refractive index

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Impact of High-k Materials and Tube Numbers on CNFET Gate’s Performances

Impact of High-k Materials and Tube Numbers on CNFET Gate’s...

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International Conference on Smart Systems and Inventive Technology (ICSSIT)

作者： Christofer Yalung Doldet Tantraviwat Sermsak Uatrongjit Wittawat Yamwong Philosophy Program in Nanoscience and Nanotechnology (International Program/Interdisciplinary) Chiang Mai University Chiang Mai Thailand Department of Electrical Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand Thai Microelectronics Center (TMEC) National Electronics and Computer Technology Center (NECTEC) Chachoengsao Thailand

Carbon nanotube field effect transistor (CNFET) performance is primarily influenced by a variety of characteristics, such as nanotube diameter, operating voltage, pitch, the number of tubes, dielectric constant, and contact materials. In this study, the dielectric constant and the number of carbon nanotubes (CNTs) were emphasized to analyze the propagation delay and average power dissipation of basic logic gates. Zirconium dioxide (ZrO 2 ), hafnium oxide (HfO 2 ), and silicon dioxide (SiO 2 ) were used as dielectric materials. In this experiment, the Stanford CNFET model was utilized, and variable factors such as the number of CNTs and the dielectric constant $(K_{ox})$ accumulated on the nanotube gate's surface were diversified. The correlation coefficients of the delay, the average power, and the CNT numbers were also presented. Furthermore, the multi-objective genetic algorithm and the Rmethod were utilized to find the optimal K ox and the number of CNTs for minimizing the average dissipation power and the propagation delay of some logic gates designed with CNFET. For all the gates considered, the optimal number of CNTs is 4 while the dielectric constant is within the ranges of 19 to 24.

关键词： Silicon compounds Dielectric constant Correlation Logic gates CNTFETs Power dissipation Electron tubes

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Deep-Learning–Based Screening and Ancillary Testing for Thyroid Cytopathology

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American Journal of Pathology 2023年第9期193卷 1185-1194页

作者： Dov, David Elliott Range, Danielle Cohen, Jonathan Bell, Jonathan Rocke, Daniel J. Kahmke, Russel R. Weiss-Meilik, Ahuva Lee, Walter T. Henao, Ricardo Carin, Lawrence Kovalsky, Shahar Z. I-Medata AI Center Tel Aviv Sourasky Medical Center Tel Aviv-Yafo Israel Department of Pathology Duke University Medical Center Durham NC United States Department of Head and Neck Surgery & Communication Sciences Duke University Medical Center Durham NC United States Department of Head and Neck Surgery Kaplan Medical Center Rehovot Israel Biological Environmental Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia Department of Biostatistics and Bioinformatics Duke University Durham NC United States Computer Science Program Computer Electrical and Mathematical Sciences and Engineering (CEMSE) Division King Abdullah University of Science and Technology Thuwal Saudi Arabia Department of Mathematics University of North Carolina at Chapel Hill Chapel Hill NC United States

Thyroid cancer is the most common malignant endocrine tumor. The key test to assess preoperative risk of malignancy is cytologic evaluation of fine-needle aspiration biopsies (FNABs). The evaluation findings can often be indeterminate, leading to unnecessary surgery for benign post-surgical diagnoses. We have developed a deep-learning algorithm to analyze thyroid FNAB whole-slide images (WSIs). We show, on the largest reported data set of thyroid FNAB WSIs, clinical-grade performance in the screening of determinate cases and indications for its use as an ancillary test to disambiguate indeterminate cases. The algorithm screened and definitively classified 45.1% (130/288) of the WSIs as either benign or malignant with risk of malignancy rates of 2.7% and 94.7%, respectively. It reduced the number of indeterminate cases (N = 108) by reclassifying 21.3% (N = 23) as benign with a resultant risk of malignancy rate of 1.8%. Similar results were reproduced using a data set of consecutive FNABs collected during an entire calendar year, achieving clinically acceptable margins of error for thyroid FNAB classification. © 2023 American Society for Investigative Pathology

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Multi-Level Branched Regularization for Federated Learning

arXiv

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arXiv 2022年

作者： Kim, Jinkyu Kim, Geeho Han, Bohyung Computer Vision Laboratory Department of Electrical and Computer Engineering & ASRI Seoul National University Korea Republic of Interdisciplinary Program of Artificial Intelligence Seoul National University Korea Republic of

A critical challenge of federated learning is data heterogeneity and imbalance across clients, which leads to inconsistency between local networks and unstable convergence of global models. To alleviate the limitations, we propose a novel architectural regularization technique that constructs multiple auxiliary branches in each local model by grafting local and global subnetworks at several different levels and that learns the representations of the main pathway in the local model congruent to the auxiliary hybrid pathways via online knowledge distillation. The proposed technique is effective to robustify the global model even in the non-iid setting and is applicable to various federated learning frameworks conveniently without incurring extra communication costs. We perform comprehensive empirical studies and demonstrate remarkable performance gains in terms of accuracy and efficiency compared to existing methods. The source code is available in our project page1 Copyright © 2022, The Authors. All rights reserved.

关键词： Distillation

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Minimizing File Transfer Time in Opportunistic Spectrum Access Model

arXiv

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arXiv 2022年

作者： Hu, Jie Doshi, Vishwaraj Eun, Do Young Department of Electrical and Computer Engineering United States Operations Research Graduate Program North Carolina State University RaleighNC United States

We study the file transfer problem in opportunistic spectrum access (OSA) model, which has been widely studied in throughput-oriented applications for max-throughput strategies and in delay-related works that commonly assume identical channel rates and fixed file sizes. Our work explicitly considers minimizing the file transfer time for a given file in a set of heterogeneous-rate Bernoulli channels, showing that max-throughput policy doesn’t minimize file transfer time in general. We formulate a mathematical framework for static extend to dynamic policies by mapping our file transfer problem to a stochastic shortest path problem. We analyze the performance of our proposed static and dynamic optimal policies over the max-throughput policy. We propose a mixed-integer programming formulation as an efficient alternative way to obtain the dynamic optimal policy and show a huge reduction in computation time. Then, we propose a heuristic policy that takes into account the performance-complexity tradeoff and consider the online implementation with unknown channel parameters. Furthermore, we present numerical simulations to support our analytical results and discuss the effect of switching delay on different policies. Finally, we extend the file transfer problem to Markovian channels and demonstrate the impact of the correlation of each channel. Copyright © 2022, The Authors. All rights reserved.

关键词： Stochastic systems

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