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Conference on Lasers and Electro-Optics (CLEO)

作者： Roman Adam Genyu Chen Daniel E. Bürgler Derang Cao Sarah Heidtfeld Debamitra Chakraborty Jing Cheng Ivan Komissarov Hilde Hardtdegen Martin Mikulics Claus M. Schneider Roman Sobolewski Research Centre Jülich Peter Grünberg Institute (PGI-6) Jülich Germany Materials Science Graduate Program University of Rochester Rochester New York USA Laboratory for Laser Energetics University of Rochester Rochester New York USA College of Physics Center for Marine Observation and Communications Qingdao University Qingdao China Department of Electrical and Computer Engineering University of Rochester Rochester New York USA Research Centre Jülich Ernst Ruska Centre for Microscopy and Spectroscopy with Electrons Jülich Germany Department of Physics University of California Davis Davis California USA

We report an additional degree of control of THz transients in Fe/X spintronic emitters grown on GaAs(001). We ascribe the field-independent enhancement of the THz amplitude to specific chemical bonding at the epitaxi... 详细信息

ISBN: (纸本)9781943580910

关键词： Electromagnetic radiation Free electron lasers Gallium arsenide Magnetic fields Terahertz generation Ultrafast lasers

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Stratifying vascular disease patients into homogeneous subgroups using machine learning and FLAIR MRI biomarkers

Npj imaging

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Npj imaging 2024年第1期2卷 56页

作者： Karissa Chan Corinne Fischer Pejman Jabehdar Maralani Sandra E Black Alan R Moody April Khademi Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University Toronto ON Canada. Institute for Biomedical Engineering Science Tech (iBEST) a Partnership between St. Michael's Hospital and Toronto Metropolitan University Toronto ON Canada. Keenan Research Center for Biomedical Science St. Michael's Hospital Unity Health Network Toronto ON Canada. Department of Medical Imaging University of Toronto Toronto ON Canada. Institute of Medical Science University of Toronto Toronto ON Canada. Horvitz Brain Sciences Research Program Sunnybrook Research Institute Toronto ON Canada. Division of Neurology Department of Medicine Sunnybrook Health Sciences Centre Toronto ON Canada. L.C. Campbell Cognitive Neurology Research Unit Sunnybrook Health Sciences Centre Toronto ON Canada. Vector Institute for Artificial Intelligence Toronto ON Canada.

This study proposes a framework to stratify vascular disease patients based on brain health and cerebrovascular disease (CVD) risk using regional FLAIR biomarkers. Intensity and texture biomarkers were extracted from FLAIR volumes of 379 atherosclerosis patients. K-Means clustering identified five homogeneous subgroups. The 15 most important biomarkers for subgroup differentiation, identified via Random Forest classification, were used to generate biomarker profiles. ANOVA tests showed age and white matter lesion volume were significantly ( < 0.05) different across subgroups, while Fisher's tests revealed significant ( < 0.05) differences in the prevalence of several vascular risk factors across subgroup. Based on biomarker and clinical profiles, Subgroup 4 was characterized with neurodegeneration unrelated to CVD, Subgroup 3 identified patients with high CVD risk requiring aggressive intervention, and Subgroups 1, 2, and 5 identified patients with varying levels of moderate risk, suitable for long-term lifestyle interventions. This study supports personalized treatment and risk stratification based on FLAIR biomarkers.

关键词： Brain imaging Image processing

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Deep Learning Based Method for computer Aided Diagnosis of Diabetic Retinopathy

Deep Learning Based Method for Computer Aided Diagnosis of D...

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IEEE International Workshop on Imaging Systems and Techniques (IST)

作者： Omar Dekhil Ahmed Naglah Mohamed Shaban Mohammed Ghazal Fatma Taher Ayman Elbaz Department of Bioengineering at University of Louisville Louisville United States Department of Computer Science at Southern Arkansas University Magnolia United States Department of Electrical and Computer Engineering at Abu Dhabi University Abu Dhabi UAE College of Technological Innovation at Zayed University Abu Dhabi UAE

ISBN: (数字)9781728138688

ISBN: (纸本)9781728138695

Diabetic retinopathy (DR) is a retinal disease caused by the high blood sugar levels that may damage and block the blood vessels feeding the retina. In the early stages of DR, the disease is asymptomatic; however, as the disease advances, a possible sudden loss of vision and blindness may occur. Therefore, an early diagnosis and staging of the disease is required to possibly slow down the progression of the disease and improve control of the symptoms. In response to the previous challenge, we introduce a computer aided diagnosis tool based on convolutional neural networks (CNN) to classify fundus images into one of the five stages of DR. The proposed CNN consists of a preprocessing stage, five stage convolutional, rectified linear and pooling layers followed by three fully connected layers. Transfer learning was adopted to minimize overfitting by training the model on a larger dataset of 3.2 million images (i.e. ImageNet) prior to the use of the model on the APTOS 2019 Kaggle DR dataset. The proposed approach has achieved a testing accuracy of 77% and a quadratic weighted kappa score of 78%, offering a promising solution for a successful early diagnose and staging of DR in an automated fashion.

关键词： Diabetes Retinopathy Convolutional neural networks Training Biomedical imaging Retina

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Student Space Missions – Facilitating Pathways to Success for Next Generation Professionals in Space

Student Space Missions – Facilitating Pathways to Success f...

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IAF Space Education and Outreach Symposium 2021 at the 72nd International Astronautical Congress, IAC 2021

作者： Bering, Edgar A. Khan, Shuhab Moges, Mequanint Hampton, Donald Mölders, Nicole Thorsen, Denise Dunbar, Bonnie J. Lefer, Barry L. Gamblin, Rachel B. Greer, Michael Greer, Presley Gunawan, Bryan Hernandez, Elizabeth Lehnen, Jamie Nguyencuu, Andy Piña, Megan Porat, Itay Prince, John R. Pessoa, Ana Gabriela Simmons, James Tovar, Chloe Ulinski, Alexandra Departments of Physics and Electrical Engineering University of Houston 3507 Cullen Blvd. #617 HoustonTX77204-5005 United States Department of Earth and Atmospheric Sciences University of Houston 3507 Cullen Blvd. #312 HoustonTX77204-5007 United States Department of Engineering Technology 4730 Calhoun Road #304 HoustonTX77204-4020 United States Geophysical Institute University of Alaska Fairbanks 2156 Koyukuk Drive FairbanksAK99775 United States Department of Aerospace Engineering Texas A&M University 701 H.R. Bright Bldg. #609B College StationTX77843-3141 United States Tropospheric Composition Program Earth Sciences Division NASA Headquarters 300 E St SW WashingtonDC20024 United States NASA Johnson Space Center Cimarron Software Services Inc. 2101 NASA Parkway HoustonTX77058 United States Alumni University of Houston 3507 Cullen Blvd. HoustonTX77204 United States UT Southwestern Medical Center 5323 Harry Hines Blvd DallasTX75390 United States Department of Computer Science University of Houston 3551 Cullen Blvd. #501 HoustonTX77204-3010 United States University of Pennsylvania School of Design 210 S. 34th St. PhiladelphiaPA19104 United States

ISBN: (纸本)9781713843177

The Undergraduate Student Instrumentation Project (USIP) was a NASA program created to engage undergraduate students in rigorous scientific research for the purposes of innovation and developing the next generation of professionals in space research. It is now run by the University of Houston using local resources. This student-led project, based on the 5E instructional model, is executed by the students from initial ideation of research objectives to the design, testing, and deployment of scientific payloads. The 5E Instructional model places the student at the center of knowledge building, while instructors facilitate interaction with content and guide the inquiry process. Since 2013, this project has been not only an effective vehicle for delivering STEM education but is also effective in increasing classroom engagement and interest in space. Space research is inherently interdisciplinary and crosscuts Geoscience, engineering, and Technology. The project is designed to integrate engineering, technology, physics, material science, and earth and atmospheric sciences as an important opportunity for the students to gain access to cross-disciplinary experiential research. In addition to classroom engagement, the students build their own payloads and ground instruments. This project increases students’ command of essential skills such as teamwork, collaboration, problem solving, technology, communication, innovation, and leadership. For the faculty, the project was an extended exercise in professional development, learning how to implement project level inquiry-based education on this scale. For the students, this formative experience continues to encourage the development of a much broader range of technical skills than is typically offered within an undergraduate degree. Furthermore, the extensive time and energy that students commit to this project promotes a strong sense of personal and professional responsibility and emphasizes the necessity of coherent teamwork.

关键词： Students

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Revamping robotics education to meet 21st century workforce needs- years 1-2 progress reports

Revamping robotics education to meet 21st century workforce ...

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2018 ASEE Conference for Industry and Education Collaboration, CIEC 2018

作者： Sergeyev, Aleksandr Alaraje, Nasser Kuhl, Scott Hooker, Joshua Druschke, Vincent Kinney, Mark Highum, Mark Electrical and Computer Engineering Program School of Technology Computer Science Department Michigan Technological University HoughtonMI49931 United States Bay de Noc Community College

The interdisciplinary nature of robots makes robotics a valuable STEM pedagogical tool. Robots are increasingly used across industry sectors to improve production throughputs while maintaining product quality. The benefits of robotics, however, depend on workers with up-to-date knowledge and skills to maintain and use existing robots, enhance future technologies, and educate users. It is critical that education institutions respond to the demand for robotics specialists by offering courses and professional certification in robotics and automation. This NSF sponsored project introduces a new approach for Industrial Robotics in electrical engineering technology (EET) programs at Michigan Tech and bay de Noc Community College. The curriculum and software developed by this collaboration of two- and four-year institutions match industry needs and provide a replicable model for programs around the US. The project also addresses the need for certified robotic training centers (CRTCs) and provides curriculum and training opportunities for students from other institutions, industry representatives, and displaced workers. In this article, authors report on Year 2 project progress, including the achievements in the developing "RobotRun" robotic simulation software, professional development opportunities for the faculty members from the other institutions, training workshops for K-12 teachers, and robotic one-day camps for high school students. Copyright © 2018, American Society for engineering Education.

关键词： Curricula

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Interference mitigation of adjacent radio frequency signals on a flexible software-defined radio testbed platform 55

Interference mitigation of adjacent radio frequency signals ...

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55th Annual International Telemetering Conference: Cultivating the Next Generation of Range Engineers, ITC 2019

作者： Elahi, Mirza M. Sandoval, Jose C. Gonzalez, Virgilio Corral, Pabel Yasuda, Susumu Gonzalez, Virgilio Computational Science Program University of Texas at El Paso El PasoTX79968 United States Department of Electrical and Computer Engineering University of Texas at El Paso El PasoTX79968 United States U.S. Army Test and Evaluation Command White Sands Missile Range White SandsNM United States

ISBN: (纸本)9781713801887

The radio frequency (RF) spectrum is crowded with users and adjacent frequency users are facing an increase in interference from each other. The spectrum governing body Federal Communications Commission (FCC) has the difficult task of allocating spectral bands for new users for mobile devices using 4G LTE technology. Telemetry (TM) is affected by the adjacent band 4G LTE users in terms of signal degradation. To minimize the interference between adjacent frequency users, several methods can be used. A common but inefficient method separates adjacent band frequencies using guard bands which leaves a big portion of the spectrum unused. Alternatively, adjacent RF signals can be separated using digital filtering techniques with the signal of interest being unharmed and reducing the signal power of the interfering signal. A digital filtering technique includes bandpass filter (BPF) rejection, which has the ability to filter out adjacent interfering signals. This is accomplished by designing bandpass digital filters where the passband and stopband frequencies are adjusted to achieve maximum signal power and reject the interfering signal by reducing its power. A flexible software-defined radio testbed is set up to experiment and analyze this scenario with ease and effective measures. © 2019 International Foundation for Telemetering. All rights reserved.

关键词： Bandpass filters

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Detailed profiling of carbon fixation of in silico synthetic autotrophy with reductive tricarboxylic acid cycle and Calvin-Benson-Bassham cycle in Esherichia coli using hydrogen as an energy source

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Synthetic and Systems Biotechnology 2019年第3期4卷 165-172页

作者： Hsieh-Ting-Yang Cheng Shou-Chen Lo Chieh-Chen Huang Tsung-Yi Ho Ya-Tang Yang Department of Computer Science National Tsing Hua UniversityHsinchu30013TaiwanR.O.C Department of Life Sciences National Chung-Hsing UniveristyTaichungTaiwanR.O.C Department of Electrical Engineering National Tsing Hua UniversityHsinchu30013TaiwanR.O.C Program in Microbial Genomics National Chung Hsing UniversityTaichungTaiwanR.O.C Innovation and Development Center of Sustainable Agriculture National Chung Hsing UniversityTaichungTaiwanR.O.C

Carbon fixation is the main route of inorganic carbon in the form of CO2 into the *** nature,RuBisCO is the most abundant protein that photosynthetic organisms use to fix CO2 from the atmosphere through the Calvin-Benson-Bassham(CBB)***,the CBB cycle is limited by its low catalytic rate and low energy *** this work,we attempt to integrate the reductive tricarboxylic acid and CBB cycles in silico to further improve carbon fixation *** heterologous enzymes,mostly carboxylating enzymes,are inserted into the Esherichia coli core metabolic network to assimilate CO2 into biomass using hydrogen as energy ***,such a strain shows enhanced growth yield with simultaneous running of dual carbon fixation *** key results include the following.(i)We identified two main growth states:carbon-limited and hydrogenlimited;(ii)we identified a hierarchy of carbon fixation usage when hydrogen supply is limited;and(iii)we identified the alternative sub-optimal growth mode while performing genetic *** results and modeling approach can guide bioengineering projects toward optimal production using such a strain as a microbial cell factory.

关键词： Reductive tricarboxylic acid cycle Calvin-Benson-Bassham cycle Carbon fixation Metabolism

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Phonon and thermal properties of quasi-two-dimensional FePS3 and MnPS3 antiferromagnetic semiconductor materials

arXiv

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arXiv 2019年

作者： Kargar, Fariborz Aytan, Ece Ghosh, Subhajit Lee, Jonathan Gomez, Michael Liu, Yuhang Magana, Andres Sanchez Beiranvand, Zahra Barani Debnath, Bishwajit Wilson, Richard Lake, Roger K. Balandin, Alexander A. Center Department of Electrical and Computer Engineering University of California RiversideCA92521 United States Mechanical Engineering Department and Materials Science and Engineering Program University of California RiversideCA92521 United States Department of Electrical and Computer Engineering University of California RiversideCA92521 United States Center University of California RiversideCA92521 United States

We report results of investigation of the phonon and thermal properties of the exfoliated films of layered single crystals of antiferromagnetic FePS3 and MnPS3 semiconductors. The Raman spectroscopy was conducted using three different excitation lasers with the wavelengths of 325 nm (UV), 488 nm (blue), and 633 nm (red). The resonant UV-Raman spectroscopy reveals new spectral features, which are not detectable via visible Raman light scattering. The thermal conductivity of FePS3 and MnPS3 thin films was measured by two different techniques: the steady-state Raman optothermal and transient time-resolved magneto-optical Kerr effect. The Raman optothermal measurements provided the orientation-average thermal conductivity of FePS3 to be 1.35 ± 0.32 Wm−1K−1 at room temperature. The transient measurements revealed that the through-plane and in-plane thermal conductivity of FePS3 is 0.85 ± 0.15 Wm−1K−1 and 2.7 ± 0.3 Wm−1K−1, respectively. The films of MnPS3 have higher thermal conductivity of 1.1 ± 0.2 Wm−1K−1 through-plane and 6.3 ± 1.7 Wm−1K−1 in-plane. The data obtained by both techniques reveal strong thermal anisotropy of the films and the dominant contribution of phonons to heat conduction. Our results are important for the proposed applications of the antiferromagnetic semiconductor thin films in spintronic devices. Copyright © 2019, The Authors. All rights reserved.

关键词： Raman spectroscopy

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DeePMD-kit v2: A software package for Deep Potential models

arXiv

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arXiv 2023年

作者： Zeng, Jinzhe Zhang, Duo Lu, Denghui Mo, Pinghui Li, Zeyu Chen, Yixiao Rynik, Marián Huang, Li'ang Li, Ziyao Shi, Shaochen Wang, Yingze Ye, Haotian Tuo, Ping Yang, Jiabin Ding, Ye Li, Yifan Tisi, Davide Zeng, Qiyu Bao, Han Xia, Yu Huang, Jiameng Muraoka, Koki Wang, Yibo Chang, Junhan Yuan, Fengbo Bore, Sigbjørn Løland Cai, Chun Lin, Yinnian Wang, Bo Xu, Jiayan Zhu, Jia-Xin Luo, Chenxing Zhang, Yuzhi Goodall, Rhys E.A. Liang, Wenshuo Singh, Anurag Kumar Yao, Sikai Zhang, Jingchao Wentzcovitch, Renata Han, Jiequn Liu, Jie Jia, Weile York, Darrin M. Weinan, E. Car, Roberto Zhang, Linfeng Wang, Han Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine Department of Chemistry and Chemical Biology Rutgers University PiscatawayNJ08854 United States AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China HEDPS CAPT College of Engineering Peking University Beijing100871 China College of Electrical and Information Engineering Hunan University Changsha China Yuanpei College Peking University Beijing100871 China Program in Applied and Computational Mathematics Princeton University PrincetonNJ08540 United States Department of Experimental Physics Comenius University Mlynská Dolina F2 Bratislava842 48 Slovakia Center for Quantum Information Institute for Interdisciplinary Information Sciences Tsinghua University Beijing100084 China Center for Data Science Peking University Beijing100871 China ByteDance Research Zhonghang Plaza No. 43 North 3rd Ring West Road Haidian District Beijing China College of Chemistry and Molecular Engineering Peking University Beijing100871 China Baidu Inc. Beijing China Key Laboratory of Structural Biology of Zhejiang Province School of Life Sciences Westlake University Zhejiang Hangzhou China Westlake AI Therapeutics Lab Westlake Laboratory of Life Sciences and Biomedicine Zhejiang Hangzhou China Department of Chemistry Princeton University PrincetonNJ08544 United States SISSA Scuola Internazionale Superiore di Studi Avanzati Trieste34136 Italy Laboratory of Computational Science and Modeling Institute of Materials École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Department of Physics National University of Defense Technology Hunan Changsha410073 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China School of Electronics Engineerin

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, Deep Potential - Range Correction (DPRc), Deep Potential Long Range (DPLR), GPU support for customized operators, model compression, non-von Neumann molecular dynamics (NVNMD), and improved usability, including documentation, compiled binary packages, graphical user interfaces (GUI), and application programming interfaces (API). This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, the article benchmarks the accuracy and efficiency of different models and discusses ongoing developments. © 2023, CC BY-NC-ND.

关键词： Molecular dynamics

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Exciton transport under periodic potential in MoSe2/WSe2 heterostructures

arXiv

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arXiv 2020年

作者： Li, Zidong Lu, Xiaobo Cordovilla Leon, Darwin F. Hou, Jize Lu, Yanzhao Kaczmarek, Austin Lyu, Zhengyang Taniguchi, Takashi Watanabe, Kenji Zhao, Liuyan Yang, Li Deotare, Parag B. Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109 United States Department of Physics Washington University in St. Louis St. LouisMO63130 United States Applied Physics Program University of Michigan Ann ArborMI48109 United States Department of Physics University of Michigan Ann ArborMI48109 United States National Institute for Materials Science Tsukuba Japan Institute of Materials Science and Engineering Washington University in St. Louis St. LouisMO63130 United States

The predicted formation of moiré superlattices leading to confined excitonic states in heterostructures formed by stacking two lattice mismatched transition metal dichalcogenide (TMD) monolayers was recently experimentally confirmed. Such periodic potential in TMD heterostructure functions as a diffusion barrier that affects the energy transport and dynamics of interlayer excitons (electron and hole spatially concentrated in different monolayers). Understanding the transport of excitons under such condition is essential to establish the material system as a next generation device platform. In this work, we experimentally quantify the diffusion barrier experienced by the interlayer excitons in a hexagonal boron nitride (h-BN) – encapsulated, molybdenum diselenide/tungsten diselenide (MoSe2/WSe2) heterostructure by studying the exciton transport at various temperatures. Copyright © 2020, The Authors. All rights reserved.

关键词： Selenium compounds

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