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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

Applying mobility business intelligence concept in analyzing oil palm plantation productivity

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AIP Conference Proceedings 2024年第1期3026卷

作者： Andreas Wahyu Krisdiarto Irya Wisnubhadra Anzaludin Samsinga Perbangsa Teddy Suparyanto Bens Pardamean Faculty of Agricultural Technology STIPER Institute of Agriculture Yogyakarta Indonesia Informatics Engineering Department Atma Jaya Yogyakarta University Yogyakarta Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia BDSRC Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia

The palm oil business employs almost 20 million people, generates USD 21 billion in revenue, and plays a vital role in Indonesia’s social economy. The Fresh Fruit Bunches (FFB) to Palm Oil Mills (POM) distribution system is one important aspect of fruit quality. Three steps are involved in getting Oil Palm FFB from the plantation to the POM. The first part of the procedure involves cutting FFB from the tree, the second stage involves gathering the fruit at a fruit collection point (FCP), and the third stage involves transporting the fruit to the palm oil mill (POM). As of now, the cost of the FFB transportation is still considerable, accounting for roughly 15% to 20% of the FFB pricing. The use of the Business Intelligence (BI) idea in the oil palm harvesting system is presented in this study as a foundation for creating web-based applications.

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A radiomics-boosted deep-learning model for COVID-19 and non-COVID-19 pneumonia classification using chest X-ray image

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arXiv 2021年

作者： Hu, Zongsheng Yang, Zhenyu Lafata, Kyle J. Yin, Fang-Fang Wang, Chunhao Medical Physics Graduate Program Duke Kunshan University Jiangsu Kunshan215316 China Department of Radiation Oncology Duke University DurhamNC27710 United States Department of Radiology Duke University DurhamNC27710 United States Department of Electrical and Computer Engineering Duke University DurhamNC27710 United States

Purpose: To develop a deep-learning model that integrates radiomics analysis for enhanced performance of COVID-19 and Non-COVID-19 pneumonia detection using chest X-ray image. Methods: Based on a pre-trained VGG-16 architecture, the deep-learning design consisted of a 5-Dense layer neural network with varying sizes, while the last three convolutional layers were set as free parameters for training. In radiomics analysis, a 2D sliding kernel was implemented to map the impulse response of radiomic features throughout the entire X-ray image;thus, each feature is rendered as a 2D map in the same dimension as X-ray image. For comparison purpose, a pilot model was trained using X-ray image only. Subsequently, 2 radiomic feature maps (RFMs) were selected based on cross-correlation analysis in reference to the pilot model saliency map results. The radiomics-boosted model was then trained based on the same deep-learning design using X-ray image plus the selected RFMs as input. Both models were developed using 812 chest X-ray images with 262/288/262 COVID-19/Non-COVID-19 pneumonia/healthy cases, and 649/163 cases were assigned as training-validation/independent test sets. For each model, 50 versions were trained with random assignments of training/validation cases following 7:1 ratio in the training-validation set. Sensitivity, specificity, accuracy, and ROC curves together with Area-Under-the-Curve (AUC) were compared between the two models. Results: The performance of detecting COVID-19 vs Non-COVID-19 pneumonia in the pilot model using X-ray image only were:1) sensitivity 0.90±0.07 vs 0.78±0.09, 2) specificity 0.94±0.04 vs 0.94±0.04, 3) accuracy 0.93±0.03 vs 0.89±0.03, and 4) ROC AUC 0.96±0.02 vs 0.92±0.04. Entropy and Short-Run-Emphasize were selected based on their high correlations with pilot model saliency map results. In the radiomics-boosted model, the corresponding results demonstrated significant improvements (p © 2021, CC BY-NC-ND.

关键词： Impulse response

Automated extraction of sentencing decisions from court cases in the Hebrew language

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arXiv 2021年

作者： Wenger, Mohr Kalir, Tom Berger, Noga Chalamish, Carmit Klar Keydar, Renana Stanovsky, Gabriel School of Computer Science and Engineering The Hebrew University of Jerusalem Jerusalem Israel Faculty of Law The Hebrew University of Jerusalem Jerusalem Israel Digital Humanities The Hebrew University of Jerusalem Jerusalem Israel The Association of Rape Crisis Centers Israel Department of Criminology Conflict Resolution Management & Negotiation Graduate Program Bar-Ilan University Israel

We present the task of Automated Punishment Extraction (APE) in sentencing decisions from criminal court cases in Hebrew. Addressing APE will enable the identification of sentencing patterns and constitute an important stepping stone for many follow up legal NLP applications in Hebrew, including the prediction of sentencing decisions. We curate a dataset of sexual assault sentencing decisions and a manually-annotated evaluation dataset, and implement rule-based and supervised models. We find that while supervised models can identify the sentence containing the punishment with good accuracy, rule-based approaches outperform them on the full APE task. We conclude by presenting a first analysis of sentencing patterns in our dataset and analyze common models’ errors, indicating avenues for future work, such as distinguishing between probation and actual imprisonment punishment. We will make all our resources available upon request, including data, annotation, and first benchmark models. Copyright © 2021, The Authors. All rights reserved.

关键词： Extraction

Topological Surface State Evolution in Bi2Se3 via Surface Etching

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arXiv 2024年

作者： Yue, Ziqin Huang, Jianwei Wang, Ruohan Li, Jia-Wan Rong, Hongtao Guo, Yucheng Wu, Han Zhang, Yichen Kono, Junichiro Zhou, Xingjiang Hou, Yusheng Wu, Ruqian Yi, Ming Department of Physics and Astronomy Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Guangdong Provincial Key Laboratory of Magnetoelectric Physics and Devices Center for Neutron Science and Technology School of Physics Sun Yat-Sen University Guangzhou510275 China Institute of Physics Chinese Academy of Sciences Beijing100190 China Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States Department of Physics and Astronomy University of California Irvine IrvineCA92697 United States

Topological insulators are materials with an insulating bulk interior while maintaining gapless boundary states against back scattering. Bi2Se3 is a prototypical topological insulator with a Dirac-cone surface state around Γ. Here, we present a controlled methodology to gradually remove Se atoms from the surface Se-Bi-Se-Bi-Se quintuple layers, eventually forming bilayer-Bi on top of the quintuple bulk. Our method allows us to track the topological surface state and confirm its robustness throughout the surface modification. Importantly, we report a relocation of the topological Dirac cone in both real space and momentum space, as the top surface layer transitions from quintuple Se-Bi-Se-Bi-Se to bilayer-Bi. Additionally, charge transfer among different surface layers is identified. Our study provides a precise method to manipulate surface configurations, allowing for the fine-tuning of the topological surface states in Bi2Se3, which represents a significant advancement towards nano-engineering of topological states. Copyright © 2024, The Authors. All rights reserved.

关键词： Topological insulators

Structural and performance comparison between SU-8 microfabricated and 3D-printed microneedle electrodes

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Journal of 3D Printing in Medicine 2020年第1期4卷 29-44页

作者： Soltanzadeh, Ramin Afsharipour, Elnaz Anssari, Neda Mansouri, Behzad Shafai, Cyrus Biomedical Graduate Studies Program University of Manitoba Winnipeg R3T 5V6 MB Canada Electrical and Computer Engineering Department University of Manitoba Winnipeg R3T 5V6 MB Canada Department of Internal Medicine (Neurology) University of Manitoba Winnipeg R3A 1R9 MB Canada

Aim: This study is aimed to compare the structure and performance of 3D-printed and microfabricated microneedle arrays (MNAs). Materials & methods: MNAs were produced using either stereolithography printing or were micro-fabricated using SU-8 polymer. The structure of both MNA types were tested and compared through scanning electron microscopy. MNA performance was also evaluated through electrical impedence spectroscopy and nerve conduction velocity testing. Results & conclusion: The 3D-printed MNAs were shown to have higher gain than microfabricated MNAs at high frequencies. However, the selectivity of the microfabricated MNAs is more than 3D-printed MNAs. Scanning electron microscopy image comparison also showed significant differences between the output of the 3D-printed MNAs and the microfabricated MNAs. It was understood that the microfabricated MNAs' geometries are closer to the primary design than the 3D-printed MNAs. © 2020 Future Medicine Ltd.

关键词： 3D printing microfabrication microneedle array performance difference strucutral difference

Deep-Strong Coupling between Cavity Photons and Terahertz TO Phonons in PbTe

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Deep-Strong Coupling between Cavity Photons and Terahertz TO...

2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Baydin, Andrey Manjappa, Manukumara Mishra, Sobhan Subhra Xu, Hongjing Tay, Fuyang Kim, Dasom Hernandez, Felix G.G. Rappl, Paulo H.O. Abramof, Eduardo Singh, Ranjan Kono, Junichiro Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Smalley-Curl Institute Rice University HoustonTX77005 United States Instrumentation and Applied Physics Department Indian Institute of Science Bangalore560012 India Center for Disruptive Photonic Technologies The Photonics Institute Nanyang Technological University 639798 Singapore Department of Physics and Astronomy Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Instituto de Física Universidade de Sao Paulo SP Sao Paulo05508-090 Brazil Laboratorio Associado de Sensores e Materiais Instituto Nacional de Pesquisas Espaciais SP Sao Jose dos Campos12201-970 Brazil Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 637371 Singapore Department of Material Science and NanoEngineering Rice University HoustonTX77005 United States

We have investigated the resonant coupling of photons with TO phonons in lead telluride in small-mode-volume terahertz cavities, observing a giant vacuum Rabi splitting on the order of the bare cavity-phonon frequency... 详细信息

ISBN: (纸本)9781957171258

关键词： Photons

CNN-based cardiac motion extraction to generate deformable geometric left ventricle myocardial models from Cine MRI

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arXiv 2021年

作者： Upendra, Roshan Reddy Wentz, Brian Jamison Simon, Richard Shontz, Suzanne M. Linte, Cristian A. Center for Imaging Science Rochester Institute of Technology RochesterNY United States Biomedical Engineering Rochester Institute of Technology RochesterNY United States Bioengineering Graduate Program University of Kansas LawrenceKS United States Electrical Engineering and Computer Science University of Kansas LawrenceKS United States Information and Telecommunication Technology Center University of Kansas LawrenceKS United States

Patient-specific left ventricle (LV) myocardial models have the potential to be used in a variety of clinical scenarios for improved diagnosis and treatment plans. Cine cardiac magnetic resonance (MR) imaging provides high resolution images to reconstruct patient-specific geometric models of the LV myocardium. With the advent of deep learning, accurate segmentation of cardiac chambers from cine cardiac MR images and unsupervised learning for image registration for cardiac motion estimation on a large number of image datasets is attainable. Here, we propose a deep leaning-based framework for the development of patient-specific geometric models of LV myocardium from cine cardiac MR images, using the Automated Cardiac Diagnosis Challenge (ACDC) dataset. We use the deformation field estimated from the VoxelMorph-based convolutional neural network (CNN) to propagate the isosurface mesh and volume mesh of the end-diastole (ED) frame to the subsequent frames of the cardiac cycle. We assess the CNN-based propagated models against segmented models at each cardiac phase, as well as models propagated using another traditional nonrigid image registration technique. © 2021, CC BY.

关键词： Image registration

A Scenario-Based Branch-and-Bound Approach for Mes Scheduling In Urban Buildings

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arXiv 2020年

作者： Dan, Mainak Srinivasan, Seshadhri Sundaram, Suresh Easwaran, Arvind Glielmo, Luigi Interdisciplinary Graduate Program Nanyang Technological University Singapore Singapore Department of Aerospace Engineering Indian Institute of Science Bangalore India School of Computer Science and Engineering Nanyang Technological University Singapore Singapore Department of Engineering University of Sannio Benevento Italy

This paper presents a novel solution technique for scheduling multi-energy system (MES) in a commercial urban building to perform price-based demand response and reduce energy costs. The MES scheduling problem is formulated as a mixed integer nonlinear program (MINLP), a non-convex NP-hard problem with uncertainties due to renewable generation and demand. A model predictive control approach is used to handle the uncertainties and price variations. This in-turn requires solving a time-coupled multi-time step MINLP during each time-epoch which is computationally intensive. This investigation proposes an approach called the Scenario-Based Branch-and-Bound (SB3), a light-weight solver to reduce the computational complexity. It combines the simplicity of convex programs with the ability of meta-heuristic techniques to handle complex nonlinear problems. The performance of the SB3 solver is validated in the Cleantech building, Singapore and the results demonstrate that the proposed algorithm reduces energy cost by about 17.26% and 22.46% as against solving a multi-time step heuristic optimization model. Copyright © 2020, The Authors. All rights reserved.

关键词： Nonlinear programming