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A correction to common advice given to young students

INTERNATIONAL JOURNAL OF electrical engineering EDUCATION 1995年第4期32卷 366-367页

作者： Gluskin, E Department of Electrical and Computer Engineering Ben-Gurion University of the Negev Beer-Sheva Israel and The Electrical Engineering Program The College of Judea and Samaria Ariel Israel

The usual advice given to a first year student is that while the student is reading lectures notes or working with a textbook at home, he has to try to perform the derivations on his own, and even to try to first find his own way to solve the problem example, and only after that to study these details in the source. It is thought, reasonably, that in this way, the study will be effective and the student will acquire good comprehension and obtain new tools which could then be actively used. However, this advice is only a part of more complete and self-consistent advice. This paper presents more complete advice which consists of three parts, of which the first is the advice already considered.

关键词： engineering education

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Impact of Quantum Well Thickness on Efficiency Loss in InGaN/GaN LEDs: Challenges for Thin-Well Designs

arXiv

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arXiv 2025年

作者： Li, Xuefeng Pant, Nick Rahman, Sheikh Ifatur Armitage, Rob Rajan, Siddharth Kioupakis, Emmanouil Feezell, Daniel University of New Mexico AlbuquerqueNM87106 United States Department of Materials Science & Engineering University of Michigan Ann ArborMI48109 United States Applied Physics Program University of Michigan Ann ArborMI48109 United States Department of Electrical and Computer Engineering The Ohio State University ColumbusOH43210 United States Lumileds LLC San JoseCA95131 United States Department of Materials Science and Engineering The Ohio State University ColumbusOH43210 United States

We investigate the impact of quantum well (QW) thickness on efficiency loss in c-plane InGaN/GaN LEDs using a small-signal electroluminescence (SSEL) technique. Multiple mechanisms related to efficiency loss are independently examined, including injection efficiency, carrier density vs. current density relationship, phase space filling (PSF), quantum confined stark effect (QCSE), and Coulomb enhancement. An optimal QW thickness of around 2.7 nm in these InGaN/GaN LEDs was determined for quantum wells having constant In composition. Despite better control of deep-level defects and lower carrier density at a given current density, LEDs with thin QWs still suffer from an imbalance of enhancement effects on the radiative and intrinsic Auger-Meitner recombination coefficients. The imbalance of enhancement effects results in a decline in internal quantum efficiency (IQE) and radiative efficiency with decreasing QW thickness at low current density in LEDs with QW thicknesses below 2.7 nm. We also investigate how LED modulation bandwidth varies with quantum well thickness, identifying the key trends and their implications for device performance. Copyright © 2025, The Authors. All rights reserved.

关键词： Semiconductor quantum wells

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Imaging the evolution of lithium-solid electrolyte interface using operando scanning electron microscopy

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Nature Communications 2025年第1期16卷 1-11页

作者： Zhao, Lihong Feng, Min Wu, Chaoshan Guo, Liqun Chen, Zhaoyang Risal, Samprash Ai, Qing Lou, Jun Fan, Zheng Qi, Yue Yao, Yan Department of Electrical and Computer Engineering and Texas Center for Superconductivity at the University of Houston University of Houston Houston TX United States School of Engineering Brown University Providence RI United States Materials Science and Engineering Program University of Houston Houston TX United States Department of Materials Science and Nanoengineering and the Rice Advanced Materials Institute Rice University Houston TX United States Department of Engineering Technology University of Houston Houston TX United States

The quality of Li–solid electrolyte interface is crucial for the performance of solid-state lithium metal batteries, particularly at low stack pressure, but its dynamics during cell operation remain poorly understood due to a lack of reliable operando characterization techniques. Here, we report the evolution of Li–electrolyte interface with high spatial resolution using operando scanning electron microscopy under realistic operating conditions. By tracking the stripping process of both Li and Li-rich Li-Mg alloy anodes, we show that multiple voids coalesce into a single gap and eventually delaminate the interface in Li, whereas the voids split and collapse to partially recover interfacial contact in Li-Mg. Density functional theory calculations show that the stronger Mg-S interaction at the metal–electrolyte interface attracts Mg toward the interface and repels Li-vacancies into the bulk, resulting in a reduced number of voids. The pressure-dependent voltage profiles of Li and Li-Mg stripping suggest that loss of contact due to void formation, rather than Mg accumulation at the interface, is the origin of high overpotential that limits the utilization of metal anodes. Improved interfacial contact enables stable cycling of all-solid-state lithium full cell at low stack pressure (1 MPa) and moderate rate (2 mA cm⁻²) simultaneously. The real-time visualization of Li–electrolyte interface dynamics provides critical insights into the rational design of solid-state battery interfaces. © The Author(s) 2025.

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Small Polaron-Induced Ultrafast Ferroelectric Restoration in BiFeO3

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Physical Review X 2025年第2期15卷 021046-021046页

作者： Wenfan Chen Tian Wang Chun-Chieh Yu Yuancheng Jing Xiaosong Li Wei Xiong Materials Science and Engineering Program University of California San Diego La Jolla California 92093 USA Department of Chemistry University of Washington Seattle Washington 98195 USA Department of Chemistry University of California San Diego La Jolla California 92093 USA Department of Electrical and Computer Science Engineering University of California San Diego La Jolla California 92093 USA

In this report, we apply a suite of ultrafast spectroscopic techniques and advanced calculations to reveal the interplay between electronic and lattice degrees of freedom in ferroelectric BiFeO3. Using transient sum frequency generation spectroscopy, which is sensitive to electronic polarizations, we observe a transient electronic dipole reduction upon optical excitation which recovers at 0.5 and 10 ps timescale. The time-dependent density functional theory calculation reveals that both ligand-metal charge transfer and local excitation transition occurred upon photo excitation. To reveal the nature of electronic dipole restoration, we employ transient extreme ultraviolet (EUV) spectroscopy—an element-specific ultrafast technique that follows charge dynamics of Bi, Fe, and O altogether. The transient EUV dynamics observed both ultrafast free charge carrier relaxation to excitons, as well as polaron formation. However, a timescale comparison suggests that only the polaron formation is responsible for the 0.5 ps electronic dipole restoration, whereas the faster electronic relaxation does not contribute to the ferroelectric property changes. Multireference configuration interaction calculation further corroborates this result by showing both Fe and Bi atoms shift from the ground state equilibrium—leading to the polaron formation. Our result disentangles the multidegrees of freedom in ultrafast ferroelectric modulation and identifies the pivotal motion—a local polaron formation—for the fast ferroelectric recovery. It provides crucial insights on the specific lattice distortion that could modulate properties or phase transitions of condensed matter materials.

关键词： Light polarization

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ANALYSIS OF A SPECIALLY STRUCTURED DESCRIPTOR-LIKE MODEL

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JOURNAL OF THE FRANKLIN INSTITUTE-engineering AND APPLIED MATHEMATICS 1994年第1期331卷 35-42页

作者： ANSARY, A Electrical and Computer Engineering Program Pennsylvania State University at Harrisburg Middletown PA 17057 U.S.A.

The analysis of a system model with special structured properties is presented in this paper. In particular, the analytical and simulation techniques for computing the system response in the context of a descriptor-like model is developed. In addition, the stability theorems for this model are also developed. This includes the formulation of both the classical and modern stability methods. The latter method leads to a generalized form of the Liapunov equation. The computational saving associated with using the methods developed here is also discussed.

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CHARACTERISTICS OF JUNCTIONS MADE BETWEEN PB AND BI2SR2CACU2O8+X

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IEEE TRANSACTIONS ON MAGNETICS 1991年第2期27卷 935-938页

作者： YANG, YF NORDMAN, JE Materials Science Program Department of Electrical and Computer Engineering University of Wisconsin Madison Madison WI USA

Investigations on the junctions made between Pb and polycrystalline Bi2Sr2CaCu2O8+x (BSCCO) are reported. The BSCCO surfaces were treated with number of methods including mechanically scraping, plasma sputtering, plasma oxidation, and Br etch before junctions were fabricated. The current-voltage characteristics and dynamic resistance (dV/dI) vs voltage have been measured at both 77K and 4.2K. We observed, among other features, a Pb gap structure similar to that seen in Pb/YBa2Cu3O7-delta junctions, a magnetic dependent supercurrent, an asymmetric I-V curve, and narrow resistance peaks. Properties of junctions prepared in different manners are compared. Both XPS and electrical studies indicated that Br etch is not suitable for the BiSrCaCuO system in spite of its successful application in YBa2Cu3O7-delta.

关键词： Plasma measurements Bismuth compounds Plasma applications Plasma properties Strontium Surface resistance Surface treatment Sputtering Oxidation Sputter etching

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Optical implementation of a parallel fuzzy flip-flop

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MICROWAVE AND OPTICAL TECHNOLOGY LETTERS 1997年第1期16卷 44-48页

作者： Zhang, SQ Karim, MA Chen, XW Alam, MF Department of Electrical and Computer Engineering and Electro-Optics Program University of Dayton Dayton Ohio 45469-0226

The concept of an optical fuzzy flip-flop, as an essential and basic component for the effective processing of fuzzy information, is introduced. A design based on the area-encoding technique and a multiple-imaging sys... 详细信息

关键词： optical fuzzy flip-flop area-encoding technique

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Erratum to “MiNuGAN: Dual segmentation of mitoses and nuclei using conditional GANs on multi-center breast H&E images” [Journal of Pathology Informatics Volume 13, 2022, 100002]

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Journal of Pathology Informatics 2025年 17卷 100426-100426页

作者： Salar Razavi Fariba D. Khameneh Hana Nouri Dimitrios Androutsos Susan J. Done April Khademi Electrical Computer and Biomedical Engineering Ryerson University Toronto Ontario Canada Laboratory Medicine Program University Health Network Toronto Ontario Canada

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Enhancing Diagnostic Accuracy for Knee Osteoarthritis Using a Deep Learning Approach

Enhancing Diagnostic Accuracy for Knee Osteoarthritis Using ...

引用

International Symposium on Applied Science 2024, ISAS 2024

作者： Raza, Aquib Ching, Congo Tak Shing Liu, Peng-Ta Phan, Thien-Luan Tran, Ngoc-Luan Nguyen, Ha Anh T. Rameez, Mohammad Li, Hung-Chung Linh, Dao Nguyen Phuong Van Hieu, Nguyen Tran, Trung Nghia National Taiwan University Taipei City10673 Taiwan Research Center for Information Technology Academia Sinica Taipei City11529 Taiwan Graduate Institute of Biomedical Engineering National Chung Hsing University Taichung402 Taiwan Department of Electrical Engineering National Chi Nan University Nantou County Taiwan Advanced Plant and Food Crop Biotechnology Center National Chung Hsing University Taichung402 Taiwan International Doctoral Program in Agriculture National Chung Hsing University Taichung402 Taiwan Fall Prevention Center Department of Physical Medicine & Rehabilitation Changhua Christian Hospital Changhua500 Taiwan Department of Physics and Electronic Engineering University of Science Vietnam National University - Ho Chi Minh City Ho Chi Minh City70000 Viet Nam Department of Computer Science University of York York HeslingtonYO10 5DD United Kingdom Undergraduate Program of Intellectual Creativity Engineering National Chung Hsing University Taichung402 Taiwan Ho Chi Minh City72409 Viet Nam HCMUT Vietnam National University Ho Chi Minh City Thu Duc Ho Chi Minh City71308 Viet Nam

This research introduces a deep learning framework that combines convolutional neural networks with autoencoders to improve the diagnostic accuracy of knee osteoarthritis. The study utilized a publicly available dataset from the Mendeley Data repository, where knee joint images were preprocessed using Contrast Limited Adaptive Histogram Equalization to enhance contrast and ensure consistent image sizing. Initially, an autoencoder was employed in an unsupervised manner to learn compressed representations of the data. These representations were then used to train a CNN to classify knee images into 'healthy' and 'osteoarthritic' categories. The model was trained using an 80:20 split for training and testing data, incorporating early stopping and data augmentation techniques to prevent overfitting and enhance generalization. Performance metrics such as accuracy, precision, recall, and the area under the Receiver Operating Characteristic curve (ROCAUC) were used to evaluate the model, resulting in a high test accuracy of 98.95%. The high precision and recall rates further confirmed the model's robustness in diagnosing KOA. To enhance interpretability, Gradient-weighted Class Activation Mapping (Grad-CAM) was applied to identify critical regions in the images that influenced the model's decisions. Additionally, t-Distributed Stochastic Neighbor Embedding (t-SNE) was used to visualize the high-dimensional encoded features in a two-dimensional space, providing deeper insights into how the model differentiates between classes. The promising results of this deep learning approach suggest its potential for broader applications in medical imaging diagnostics. By providing healthcare professionals with a tool that enhances diagnostic accuracy and operational efficiency, this framework lays the foundation for developing scalable, AI-driven diagnostic systems for various complex medical conditions. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Joints (anatomy)

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BENCHMARKING COMMUNITY DRUG RESPONSE PREDICTION MODELS: DATASETS, MODELS, TOOLS, AND METRICS FOR CROSS-DATASET GENERALIZATION ANALYSIS

arXiv

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arXiv 2025年

作者： Partin, Alexander Vasanthakumari, Priyanka Narykov, Oleksandr Wilke, Andreas Koussa, Natasha Jones, Sara E. Zhu, Yitan Overbeek, Jamie C. Jain, Rajeev Fernando, Gayara Demini Sanchez-Villalobos, Cesar Garcia-Cardona, Cristina Mohd-Yusof, Jamaludin Chia, Nicholas Wozniak, Justin M. Ghosh, Souparno Pal, Ranadip Brettin, Thomas S. Weil, M. Ryan Stevens, Rick L. Division of Data Science and Learning Argonne National Laboratory LemontIL United States Frederick National Laboratory for Cancer Research Cancer Data Science Initiatives Cancer Research Technology Program FrederickMD United States Department of Statistics University of Nebraska–Lincoln LincolnNE United States Department of Electrical & Computer Engineering Texas Tech University LubbockTX United States Division of Computer Computational and Statistical Sciences Los Alamos National Laboratory Los AlamosNM United States Department of Computer Science The University of Chicago ChicagoIL United States

Deep learning (DL) and machine learning (ML) models have shown promise in drug response prediction (DRP), yet their ability to generalize across datasets remains an open question, raising concerns about their real-world applicability. Due to the lack of standardized benchmarking approaches, model evaluations and comparisons often rely on inconsistent datasets and evaluation criteria, making it difficult to assess true predictive capabilities. In this work, we introduce a benchmarking framework for evaluating cross-dataset prediction generalization in DRP models. Our framework incorporates five publicly available drug screening datasets, six standardized DRP models, and a scalable workflow for systematic evaluation. To assess model generalization, we introduce a set of evaluation metrics that quantify both absolute performance (e.g., predictive accuracy across datasets) and relative performance (e.g., performance drop compared to within-dataset results), enabling a more comprehensive assessment of model transferability. Our results reveal substantial performance drops when models are tested on unseen datasets, underscoring the importance of rigorous generalization assessments. While several models demonstrate relatively strong cross-dataset generalization, no single model consistently outperforms across all datasets. Furthermore, we identify CTRPv2 as the most effective source dataset for training, yielding higher generalization scores across target datasets. By sharing this standardized evaluation framework with the community, our study aims to establish a rigorous foundation for model comparison, and accelerate the development of robust DRP models for real-world applications. © 2025, CC BY.

关键词： Prediction models

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