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arXiv 2024年

作者： Gao, Shanghua Fang, Ada Huang, Yepeng Giunchiglia, Valentina Noori, Ayush Schwarz, Jonathan Richard Ektefaie, Yasha Kondic, Jovana Zitnik, Marinka Department of Biomedical Informatics Harvard Medical School BostonMA United States Department of Chemistry and Chemical Biology Harvard University CambridgeMA United States Program in Biological and Biomedical Sciences Harvard Medical School BostonMA United States Department of Brain Sciences Imperial College London London United Kingdom Harvard College CambridgeMA United States Program in Biomedical Informatics Harvard Medical School BostonMA United States Department of Electrical Engineering and Computer Science MIT CambridgeMA United States Kempner Institute for the Study of Natural and Artificial Intelligence Harvard University MA United States Broad Institute of MIT and Harvard CambridgeMA United States Harvard Data Science Initiative CambridgeMA United States

We envision "AI scientists" as systems capable of skeptical learning and reasoning that empower biomedical research through collaborative agents that integrate AI models and biomedical tools with experimental platforms. Rather than taking humans out of the discovery process, biomedical AI agents combine human creativity and expertise with AI’s ability to analyze large datasets, navigate hypothesis spaces, and execute repetitive tasks. AI agents are poised to be proficient in various tasks, planning discovery workflows and performing self-assessment to identify and mitigate gaps in their knowledge. These agents use large language models and generative models to feature structured memory for continual learning and use machine learning tools to incorporate scientific knowledge, biological principles, and theories. AI agents can impact areas ranging from virtual cell simulation, programmable control of phenotypes, and the design of cellular circuits to developing new therapies. © 2024, CC BY.

关键词： Adversarial machine learning

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Scaling Limitations of Line TFETs at Sub-8-nm Technology Node

Scaling Limitations of Line TFETs at Sub-8-nm Technology Nod...

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2020 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2020

作者： Thoti, Narasimhulu Li, Yiming Kola, Sekhar Reddy Parallel and Scientific Computing Laboratory Eecs International Graduate Program Institute of Communications Engineering Department of Electrical and Computer Engineering Center for MmWave Smart Radar System and Technologies National Chiao Tung University 1001 Ta-Hsueh Rd Hsinchu300 Taiwan

ISBN: (纸本)9781728142326

The scope of the work is to investigate limitations in device scaling by identifying various parameters of short channel effects (SCEs) in current challenging geometries of the line tunnel field effect transistors (TFETs). Key factors of the considered device, such as the doping and the thickness (tn) of n-epitaxial region, and source-to-drain length (LSDeff) scaling cannot be tuned anymore to boost the device characteristics for the sub-8-nm technology node. The main results of this study indicates that the engineering acceptable performance are achieved at a low doping of 5 1018 cm-3, an optimal tn as low (about 0.5 nm), and a LSDeff greater than 12.5 nm. Hence, the line TFETs below sub-8-nm faces serious bottleneck of scaling and cannot be further scaled with the conventional scaling rule at all. © 2020 IEEE.

关键词： Tunnel field effect transistors

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Multifunctional Microcoaxial Fibers for Electrochemical, Optical and Spectroelectrochemical Sensing

SSRN

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SSRN 2022年

作者： Shi, Yuesong Ward, Spencer Riley, Conor Sirbuly, Donald J. Materials Science and Engineering Program University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States Department of Electrical and Computer Engineering University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States Department of Nanoengineering University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States

Developing microdevices capable of performing multifunctional sensing measurements is of grand importance for various applications including the study of diseases, rapid biomolecular detection, and drug discovery. In this paper, we demonstrate a compact electro-optical multimodal microprobe with a small footprint (~10 µm diameter), low electrical impedance (~ 10 kΩ at 1 kHz), and high optical spatial resolution. The electrical channel is validated by selectively detecting dopamine and serotonin via electrochemistry with a limit of detection of 800 nM and 1.2 μM, respectively. The optical channel is then combined with the adjacent electrical channel to perform localized spectroelectrochemical probing of electrochromic materials including conductive polymers such as poly(3,4-ethylenedioxythiophene) and thiazine dyes such as methylene blue. Due to the size of the probe, dimensional and mechanical tunability, and minimal interference between the co-localized electrical and optical channels, this device architecture shows great promise for in vivo sensing and in situ biomolecular measurements. © 2022, The Authors. All rights reserved.

关键词： Amines

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A novel tri-bandpass filter side-coupled square ring based

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Journal of Microwaves, Optoelectronics and Electromagnetic Applications 2020年第2期19卷 265-275页

作者： Duarte, José Garibaldi Da Silva Neto, Valdemir Praxedes Postgraduate Program in Electrical and Computer Engineering PPGEEC UFRN Natal RN Brazil Communication Engineering Department DCO UFRN Natal RN Brazil

This work presents the design of a tri-bandpass filter based on the side-coupled square ring structure. The modeling is conceived from the classic approach of coupled transmission lines. The geometry consists of a square structure of electrical length equal to twice the wavelength of the main operating frequency, and the laterally coupled lines through which the power supply occurs. Expressions for the admittance and transformation matrix were obtained based on the impedances and admittances that model the geometry. Analyzis were performed from EM simulations. A prototype was built to validate the modeling and adjusted for operation at 0.78, 1.5 and 2.30 GHz. All results are discussed and commented, and the comparisons between simulated and measured results are coherent and in agreement, thus proving the effectiveness of the applied method. © 2020 SBMO/SBMag.

关键词： Electric lines

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Improving STEM education for lower-division college students at HSI by utilizing relevant sociocultural and academic experiences: First year results from ASSURE-US project

Improving STEM education for lower-division college students...

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2020 ASEE Virtual Annual Conference, ASEE 2020

作者： Huang, Jidong Kurwadkar, Sudarshan Bein, Doina Bai, Yu Mayoral, Salvador Department of Electrical Engineering California State University Fullerton FullertonCA United States Department of Civil and Environmental Engineering California State University Fullerton FullertonCA United States Department of Computer Science California State University Fullerton FullertonCA United States Computer Engineering Program California State University Fullerton FullertonCA United States Department of Mechanical Engineering California State University Fullerton FullertonCA United States

Despite national efforts in increasing representation of minority students in STEM disciplines, disparities prevail. Hispanics account for 17.4% of the U.S. population, and nearly 20% of the youth population (21 years and below) in the U.S. is Hispanic, yet they account for just 7% of the STEM workforce. To tackle these challenges, the National Science Foundation (NSF) has granted a 5-year project - ASSURE-US, that seeks to improve undergraduate education in engineering and computer Science (ECS) at California State University, Fullerton. The project seeks to advance student success during the first two years of college for ECS students. Towards that goal, the project incorporates a very diverse set of approaches, such as socio-cultural and academic interventions. Multiple strategies including developing early intervention strategies in gateway STEM courses, creating a nurturing faculty-student interaction and collaborative learning environment, providing relevant, contextual-based learning experiences, integrating project-based learning with engineering design in lower-division courses, exposing lower-division students to research to sustain student interests, and helping students develop career-readiness skills. The project also seeks to develop an understanding of the personal, social, cognitive, and contextual factors contributing to student persistence in STEM learning that can be used by STEM faculty to improve their pedagogical and student-interaction approaches. This paper summarizes the major approaches the ASSURE-US project plans to implement to reduce the achievement gap and motivate ECS students to remain in the program. Preliminary findings from the first-year implementation of the project including pre- and post- data were collected and analyzed from about one hundred freshmen and sophomore ECS students regarding their academic experience in lower-division classes and their feedback for various social support events held by the ASSURE-US project during

关键词： Students

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Spatial atlas of the mouse central nervous system at molecular resolution (vol 622, pg 552, 2023)

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NATURE 2024年第7993期625卷 E6-E6页

作者： Shi, Hailing He, Yichun Zhou, Yiming Huang, Jiahao Maher, Kamal Wang, Brandon Tang, Zefang Luo, Shuchen Tan, Peng Wu, Morgan Lin, Zuwan Ren, Jingyi Thapa, Yaman Tang, Xin Chan, Ken Y. Deverman, Benjamin E. Shen, Hao Liu, Albert Liu, Jia Wang, Xiao Broad Institute of MIT and Harvard Cambridge MA USA Department of Chemistry Massachusetts Institute of Technology Cambridge MA USA John A. Paulson School of Engineering and Applied Sciences Harvard University Boston MA USA Computational and Systems Biology PhD Program Massachusetts Institute of Technology Cambridge MA USA Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA Department of Biology Massachusetts Institute of Technology Cambridge MA USA Klarman Cell Observatory Broad Institute of MIT and Harvard Cambridge MA USA Department of Chemistry and Chemical Biology Harvard University Cambridge MA USA Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard Cambridge MA USA

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Automating the Practice of Science – Opportunities, Challenges, and Implications

arXiv

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arXiv 2024年

作者： Musslick, Sebastian Bartlett, Laura K. Chandramouli, Suyog H. Dubova, Marina Gobet, Fernand Griffiths, Thomas L. Hullman, Jessica King, Ross D. Nathan Kutz, J. Lucas, Christopher G. Mahesh, Suhas Pestilli, Franco Sloman, Sabina J. Holmes, William R. Institute of Cognitive Science Osnabrück University Osnabrück49090 Germany Department of Cognitive Linguistic & Psychological Sciences Brown University ProvidenceRI02912 United States Centre for Philosophy of Natural and Social Science London School of Economics Lakatos Building Houghton Street LondonWC2A 2AE United Kingdom AaltoFI-00076 Finland Department of Computing Science University of Alberta 8900 114 St NW EdmontonABT6G 2S4 Canada Cognitive Science Program Indiana University 1101 E 10th St BloomingtonIN47405 United States School of Psychology University of Roehampton LondonSW15 4JD United Kingdom Departments of Psychology and Computer Science Princeton University PrincetonNJ United States Department of Computer Science Northwestern University IL United States Department of Chemical Engineering and Biotechnology University of Cambridge CambridgeCB3 0AS United Kingdom Department of Computer Science and Engineering Chalmers University of Technology Gothenburg412 96 Sweden Department of Applied Mathematics and Electrical and Computer Engineering University of Washington Seattle98195 United States School of Informatics University of Edinburgh 10 Crichton St. EH8 9AB United Kingdom Department of Materials Science and Engineering University of Toronto Canada Department of Psychology Department of Neuroscience The University of Texas AustinTX United States Department of Computer Science University of Manchester M13 9PL United Kingdom

Automation transformed various aspects of our human civilization, revolutionizing industries and streamlining processes. In the domain of scientific inquiry, automated approaches emerged as powerful tools, holding promise for accelerating discovery, enhancing reproducibility, and overcoming the traditional impediments to scientific progress. This article evaluates the scope of automation within scientific practice and assesses recent approaches. Furthermore, it discusses different perspectives to the following questions: Where do the greatest opportunities lie for automation in scientific practice?;What are the current bottlenecks of automating scientific practice?;and What are significant ethical and practical consequences of automating scientific practice? By discussing the motivations behind automated science, analyzing the hurdles encountered, and examining its implications, this article invites researchers, policymakers, and stakeholders to navigate the rapidly evolving frontier of automated scientific practice. © 2024, CC BY.

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Analyzing Diversity in Healthcare LLM Research: A Scientometric Perspective

arXiv

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arXiv 2024年

作者： Restrepo, David Wu, Chenwei Vásquez-Venegas, Constanza Matos, João Gallifant, Jack Celi, Leo Anthony Bitterman, Danielle S. Nakayama, Luis Filipe Laboratory for Computational Physiology Massachusetts Institute of Technology CambridgeMA United States Departamento de Telematica Universidad del Cauca Cauca Popayán Colombia Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI United States Scientific Image Analysis Lab Faculty of Medicine Universidad de Chile RM Santiago Chile Department of Computer Science Faculty of Engineering Universidad de Concepción Biobio Concepción Chile Department of Biostatistics Harvard TH Chan School of Public Health BostonMA United States Department of Medicine Beth Israel Deaconess Medical Center BostonMA United States Artificial Intelligence in Medicine Program Mass General Brigham Harvard Medical School BostonMA United States Department of Ophthalmology São Paulo Federal University São Paulo São Paulo Brazil

The deployment of large language models (LLMs) in healthcare has demonstrated substantial potential for enhancing clinical decision-making, administrative efficiency, and patient outcomes. However, the underrepresentation of diverse groups in the development and application of these models can perpetuate biases, leading to inequitable healthcare delivery. This paper presents a comprehensive scientometric analysis of LLM research for healthcare, including data from January 1, 2021, to July 1, 2024. By analyzing metadata from PubMed and Dimensions, including author affiliations, countries, and funding sources, we assess the diversity of contributors to LLM research. Our findings highlight significant gender and geographic disparities, with a predominance of male authors and contributions primarily from high-income countries (HICs). We introduce a novel journal diversity index based on Gini diversity to measure the inclusiveness of scientific publications. Our results underscore the necessity for greater representation in order to ensure the equitable application of LLMs in healthcare. We propose actionable strategies to enhance diversity and inclusivity in artificial intelligence research, with the ultimate goal of fostering a more inclusive and equitable future in healthcare innovation. © 2024, CC BY.

关键词： Decision making

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Towards a Prosodic Model for Synthesized Speech of Mathematical Expressions in MathML 2020

Towards a Prosodic Model for Synthesized Speech of Mathemati...

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9th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-exclusion

作者： Adriana Souza Diamantino Freitas Doctoral Program in Digital Media Faculty of Engineering - University of Porto Porto Portugal Bahia Federal Institute of Education Science and Technology Porto Seguro Brazil BR Department of Electrical and Computer EngineeringFaculty of Engineering - University of PortoPorto Portugal PT

ISBN: (纸本)9781450389372

The use of the MathML language made possible to improve the accessibility of mathematics for blind or low-vision persons in digital media. Synthetic speech technologies have advanced significantly using MathML, however, the speech synthesizers' standard reading style is still not suitable for mathematics. Making mathematical reading of the speech synthesizers more natural and expressive is still a challenge. The creation of models to produce the appropriate prosody in the synthesized speech of math content is therefore necessary, as shown in previous research. This article presents a proposal for a model to improve prosody in the synthesized speech of mathematical expressions based on MathML. A corpus of mathematical expressions spoken by Mathematics teachers was created to support the model's development. The Fujisaki intonation model was adopted for intonation control, accent and phrase commands have been extracted from the corpus, and some adjustments have been made to manipulate prosodic parameters in the speech of mathematical expression in correlation with the MathML tree; additionally, a pattern of pauses control is being created.

关键词： Accessibility Mathematics Visual Impairment

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Electron mobility of SnO2 from first principles

arXiv

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arXiv 2024年

作者： Wang, Amanda Bushick, Kyle Pant, Nick Lee, Woncheol Zhang, Xiao Leveillee, Joshua Giustino, Feliciano Poncé, Samuel Kioupakis, Emmanouil Department of Materials Science and Engineering University of Michigan Ann ArborMI48109 United States Applied Physics Program University of Michigan Ann ArborMI48109 United States Department of Electrical and Computer Engineering University of Michigan Ann ArborMI48109 United States Oden Institute for Computational Engineering and Sciences The University of Texas at Austin AustinTX78712 United States Department of Physics The University of Texas at Austin AustinTX78712 United States European Theoretical Spectroscopy Facility Institute of Condensed Matter and Nanosciences Université catholique de Louvain Chemin des Étoiles 8 Louvain-la-NeuveB-1348 Belgium WEL Research Institute Avenue Pasteur 6 Wavre1300 Belgium

The transparent conducting oxide SnO2 is a wide bandgap semiconductor that is easily n-type doped and widely used in various electronic and optoelectronic applications. Experimental reports of the electron mobility of this material vary widely depending on the growth conditions and doping concentrations. In this work, we calculate the electron mobility of SnO2 from first principles to examine the temperature- and doping-concentration dependence, and to elucidate the scattering mechanisms that limit transport. We include both electron-phonon scattering and electron-ionized impurity scattering to accurately model scattering in a doped semiconductor. We find a strongly anisotropic mobility that favors transport in the direction parallel to the c-axis. At room temperature and intrinsic carrier concentrations, the low-energy polar-optical phonon modes dominate scattering, while ionized-impurity scattering dominates above 1018 cm-3 Copyright © 2024, The Authors. All rights reserved.

关键词： Electron mobility

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