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IEEE Electron Device Letters 2025年第5期46卷 705-708页

作者： Chen, Yi-Ho Chu, Fu-Chuan Aslam, Muhammad Lee, Yao-Jen Li, Yiming Samukawa, Seiji National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Graduate Degree Program of College of Electrical and Computer Engineering Hsinchu300093 Taiwan National Chung-Shan Institute of Science and Technology Solid State Devices Section Electronic System Research Division Taoyuan325 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Institute of Communications Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Communications Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan

Recess gate etching is a critical technique for achieving enhancement-mode (E-mode) AlGaN/GaN high-electron mobility transistors (HEMTs) because the interface is susceptible to the etching damage. This study fabricates recess gates using the neutral beam etching (NBE) technique. By adjusting the aperture thickness in the NBE apparatus, we simulate both NB-mode and plasma-mode etching. The electrical characteristics of E-mode HEMTs fabricated using these two modes are analyzed and compared through DC, noise, and pulsed IV measurements. The results demonstrate that NB-recessed HEMTs exhibit superior performance. © 1980-2012 IEEE.

关键词： Aluminum gallium nitride

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An Ultra-high Sensitivity Sensing Collimation Imager: Design, Modelling, and Assessment

An Ultra-high Sensitivity Sensing Collimation Imager: Design...

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Medical Imaging 2025: Physics of Medical Imaging

作者： Cai, Ling Aggarwal, Samarth Enninful, Kweku Chen, Yunlai Komarov, Sergey Thorek, Daniel Jha, Abhinav K. Tai, Yuan-Chuan Imaging Science Doctoral Program Washington University in St. Louis St. LouisMO United States Department of Biomedical Engineering Washington University in St. Louis St. LouisMO United States Mallinckrodt Institute of Radiology Washington University St. Louis United States

ISBN: (纸本)9781510685888

In this work, we discuss the design and development of an ultra-high sensitivity imaging system, Sensing Collimation Imager (SCI), dedicated to guide and optimize application of alpha particle-emitting radiopharmaceutical therapy (αRPT). Alpha particles are highly potent and unlike conventional external beam therapy can be used in metastatic settings. Currently, the lack of information of radionuclide distribution hinders estimated internal absorbed dose from αRPT, which calls for ultrasensitive SPECT technologies that can report reliable activity distribution under ultra-low count rate imaging conditions. The proposed SCI-SPECT is based on an innovative design that incorporates the geometry of both conventional pinhole collimator and coded aperture. Aimed to decouple the dependence of resolution and sensitivity, the heavy metal collimator is replaced by scintillator crystals to serve dual purposes of increasing detected events and providing spatial information. The detector module consists of an 8×8 array of crystal elements. Each crystal presents an alternating pattern of GAGG scintillator and acrylic. The depth of interaction (DOI) information is obtained through dual-ended readout system. Our experimental results are based on a working prototype SCI module that is fully functional under a broad range of energy (70 keV - more than 511 keV), which is well-suited for alpha particle emitter imaging applications. Furthermore, we modeled the system response function based on analytical derivation and validated it by comparing with Monte Carlo simulations. We carried out a preliminary imaging study of three rod sources filled with Tc99m. The image was successfully reconstructed with the derived system matrix, and the rods at different locations can be clearly resolved. We also compared the performance with Siemens Symbia Intevo scanner for high γ-ray energy imaging with Cu-64, the reconstructed image shows better resolution while potentially achieving 2 orders of magni

关键词： Alpha particles

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Speech Abusive Language Detection System Using MFCC Speech Feature Extraction and Convolutional Neural Network

Speech Abusive Language Detection System Using MFCC Speech F...

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Consumer Technology (ICCT-Pacific), International Conference on

作者： Yi-Chang Zhu Ying-Hsiu Hung Yen-Ching Chang Jhen-Kai Tang Wen-Kai Tsai Shin-Chi Lai The Doctoral Degree Program in Smart Industry Technology Research and Development National Formosa University Huwei Taiwan Dept. Electronics Engineering National Yunlin University of Science and Technology Douliu Taiwan Doctoral Degree Program in Smart Industry Technology Research and Development National Formosa University Huwei Taiwan Department of Electrical Engineering Master's Program National Formosa University Huwei Taiwan Dept. Electrical Engineering National Formosa University Huwei Taiwan Dept. Automation Engineering & Smart Machinery and Intelligent Manufacturing Research Center National Formosa University Huwei Taiwan

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

As bullying rapidly spreads in schools, many parents are becoming increasingly concerned about their children being subjected to bullying by peers, which could negatively impact their physical and mental health. This paper proposes an abusive language detection system that combines Mel-frequency Cepstrum Coefficients (MFCC) speech features with a Convolutional Neural Network (CNN). Audio files which contain daily abusive phrases in the Minnan dialect are initially preprocesses to eliminate non-speech interference. Subsequently, the MFCC algorithm is applied to extract speech features that closely capture auditory characteristics. The CNN classification model is trained to learn the MFCC features and classify the phrases into their respective categories. Experimental results indicate that the CNN model achieves an average recognition accuracy of 91.9%. Finally, the CNN model was deployed on an embedded platform, where it achieves an average recognition time of 0.54 seconds per phrase and an average recognition accuracy of 86.25%.

关键词： Pediatrics Accuracy Semantics Speech recognition Mental health Speech enhancement Feature extraction Convolutional neural networks Mel frequency cepstral coefficient Optimization

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Enhancing Diagnostic Accuracy for Knee Osteoarthritis Using a Deep Learning Approach

Enhancing Diagnostic Accuracy for Knee Osteoarthritis Using ...

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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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Harnessing the bishomolithocholic acid scaffold for selective sialyltransferase inhibition: A targeted approach to suppress breast cancer metastasis

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European Journal of Medicinal Chemistry 2025年 292卷 117674页

作者： Perez, Ser John Lynon P. Hsu, Zih-Fan Chang, Tzu-Ting Chen, Chia-Ling Li, Wen-Shan Institute of Chemistry Academia Sinica Taipei 115 Taiwan Department of Applied Chemistry National Yang Ming Chiao Tung University Hsinchu 300 Taiwan Sustainable Chemical Science and Technology Taiwan International Graduate Program Academia Sinica Taipei 115 Taiwan Biomedical Translation Research Center Academia Sinica Taipei 115 Taiwan Department of Chemistry National Taiwan Normal University Taipei 116 Taiwan Department of Medicinal and Applied Chemistry College of Life Science Kaohsiung Medical University Kaohsiung 807 Taiwan Ph.D. Program in Drug Discovery and Development Industry College of Pharmacy Taipei Medical University Taipei 110 Taiwan Doctoral Degree Program in Marine Biotechnology National Sun Yat-Sen University Kaohsiung 804 Taiwan

ST6GAL1 plays a crucial role in the progression of triple-negative breast cancer (TNBC), highlighting its potential as a therapeutic target for this aggressive cancer subtype. Due to the high metastatic potential of TNBC and the limitations of current therapies, selective and potent ST6GAL1 inhibitors are urgently needed. In this study, a scaffold-hopping approach from lithocholic acid to bishomolithocholic acid successfully led to the discovery of novel ST6GAL1 inhibitors, SPP-037 and HZF01, with enhanced biological activity and selectivity. Both compounds significantly inhibited MDA-MB-231 cell migration, HUVEC tube formation, tumor growth, and metastasis in vitro and in vivo. Molecular docking studies revealed key interactions between the ST inhibitors and ST6GAL1, supporting their enhanced selectivity and binding affinity. Additionally, SPP-037 and HZF01 were found to block integrin α2,6-sialylation, disrupting integrin activation and downstream signaling pathways involving the phosphorylation of focal adhesion kinase (FAK) and paxillin, which are critical for cell migration. These results underscore the potential of targeting ST6GAL1 to suppress tumor progression and metastasis, offering a promising avenue for treating aggressive breast cancer. © 2025 Elsevier Masson SAS

关键词： Bishomolithocholic acid Breast cancer metastasis Integrin-FAK-Paxillin axis N-glycan sialylation Sialyltransferase inhibitor ST6GAL1

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Enhancing safety with an AI-empowered assessment and monitoring system for BSL-3 facilities

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Heliyon 2025年第1期11卷 e40855页

作者： Fan, Yi-Ling Hsu, Ching-Han Wu, Ju-Yu Tsai, Ying-Ying Chen, Wei J. Lee, Min-Shi Hsu, Fang-Rong Liao, Lun-De Institute of Biomedical Engineering and Nanomedicine National Health Research Institutes 35 Keyan Road Miaoli County Zhunan Town 350 Taiwan Department of Biomedical Engineering & Environmental Sciences National Tsing-Hua University Hsinchu Taiwan Doctoral Program in Tissue Engineering and Regenerative Medicine National Chung Hsing University Taichung Taiwan Center for Neuropsychiatric Research National Health Research Institutes 35 Keyan Road Miaoli County Zhunan Town 350 Taiwan National Institute of Infectious Diseases and Vaccinology National Health Research Institutes 35 Keyan Road Miaoli County Zhunan Town 350 Taiwan Department of Information Engineering and Computer Science Feng Chia University Taichung 407 Taiwan

Introduction: The COVID-19 pandemic has created an urgent demand for research, which has spurred the development of enhanced biosafety protocols in biosafety level (BSL)-3 laboratories to safeguard against the risks associated with handling highly contagious pathogens. Laboratory management failures can pose significant hazards. Methods: An external system captured images of personnel entering a laboratory, which were then analyzed by an AI-based system to verify their compliance with personal protective equipment (PPE) regulations, thereby introducing an additional layer of protection. A deep learning model was trained to detect the presence of essential PPE items, such as clothing, masks, hoods, double-layer gloves, shoe covers, and respirators, ensuring adherence to World Health Organization (WHO) standards. The internal laboratory management system used a deep learning model to delineate alert zones and monitor compliance with the imposed safety protocols. Results: The external detection system was trained on a dataset consisting of 4112 images divided into 15 PPE compliance classes. The model achieved an accuracy of 97.52 % and a recall of 97.03 %. The identification results were presented in real time via a visual interface and simultaneously stored on the administrator's dashboard for future reference. We trained the internal management system on 3347 images, achieving 90 % accuracy and 85 % recall. The results were transmitted in JSON format to the internal monitoring system, which triggered alerts in response to violations of safe practices or alert zones. Real-time notifications were sent to the administrators when the safety thresholds were met. Conclusion: The BSL-3 laboratory monitoring system significantly reduces the risk of exposure to pathogens for personnel during laboratory operations. By ensuring the correct use of PPE and enhancing adherence to the imposed safety protocols, this system contributes to maintaining the integrity of BSL-3 facilities

关键词： Bioengineering biomedical instrumentation biomedical laboratory safety Biosafety level-3 laboratory

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Fabrication of versatile poly(xylitol sebacate)-co-poly(ethylene glycol) hydrogels through multifunctional crosslinkers and dynamic bonds for wound healing

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Acta Biomaterialia 2023年 170卷 344-359页

作者： Yeh, Ying-Yu Lin, Yi-Yun Wang, Ting-Teng Yeh, Yu-Jia Chiu, Ting-Hsiang Wang, Reuben Bai, Meng-Yi Yeh, Yi-Cheun Institute of Polymer Science and Engineering National Taiwan University Taipei Taiwan Institute of Biomedical Engineering National Taiwan University Taipei Taiwan Biomedical Engineering Program Graduate Institute of Applied Science and Technology National Taiwan University of Science and Technology Taipei Taiwan Institute of Food Safety and Health National Taiwan University Taipei Taiwan Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan Adjunct Appointment to the Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan Program National Taiwan University Taipei Taiwan GIP-TRIAD Master's Degree in Agro-Biomedical Science National Taiwan University Taipei Taiwan

Poly(polyol sebacate) (PPS) polymer family has been recognized as promising biomaterials for biomedical applications with their characteristics of easy production, elasticity, biodegradation, and cytocompatibility. Poly(xylitol sebacate)-co-poly(ethylene glycol) (PXS-co-PEG) has been developed to fabricate PPS-based hydrogels;however, current PXS-co-PEG hydrogels presented limited properties and functions due to the limitations of the crosslinkers and crosslinking chemistry used in the hydrogel formation. Here, we fabricate a new type of PXS-co-PEG hydrogels through the use of multifunctional crosslinkers as well as dynamic bonds. In our design, polyethyleneimine-polydopamine (PEI-PDA) macromers are utilized to crosslink aldehyde-functionalized PXS-co-PEG (APP) through imine bonds and hydrogen bonds. PEI-PDA/APP hydrogels present multiple functional properties (e.g., fluorescent, elastomeric, biodegradable, self-healing, bioadhesive, antioxidant, and antibacterial behaviors). These properties of PEI-PDA/APP hydrogels can be fine-tuned by changing the PDA grafting degrees in the PEI-PDA crosslinkers. Most importantly, PEI-PDA/APP hydrogels are considered promising wound dressings to promote tissue remodeling and prevent bacterial infection in vivo. Taken together, PEI-PDA/APP hydrogels have been demonstrated as versatile biomaterials to provide multiple tailorable properties and desirable functions to expand the utility of PPS-based hydrogels for advanced biomedical applications. Statement of significance: Various strategies have been developed to fabricate poly(polyol sebacate) (PPS)-based hydrogels. However, current PPS-based hydrogels present limited properties and functions due to the limitations of the crosslinkers and crosslinking chemistry used in the hydrogel formation. This work describes that co-engineering crosslinkers and interfacial crosslinking is a promising approach to synthesizing a new type of poly(xylitol sebacate)-co-poly(ethylene glycol) (PXS-co-

关键词： Polyols

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Transient analysis of an advanced static Var compensator using quad-series voltage-source PAM inverters

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ELECTRICAL engineering IN JAPAN 1996年第2期117卷 93-106页

作者： Tominaga, S Fujita, H Akagi, H Okayama University [?]Received his Master's degree in Electrical and Electronic Engineering in 1995 from the Engineering Research Division of the Graduate School Okayama University. He is currently in the doctoral program in system science at the Natural Sciences Research Division of the Graduate School of the same university. He is engaged in research on reactive power compensators.

This paper deals with an advanced static Var compensator (ASVC) using quad-series voltage-source PAM inverters. The ASVC consists of four three-phase voltage-source inverters with a common de capacitor and four three-phase transformers, each primary winding of which is connected in series with each other. Each inverter outputs a square-wave voltage, while the synthesized output voltage of the ASVC has a 24-step wave shape. This results not only in a great reduction of harmonic currents and de voltage ripples but also in fewer switching and snubbing losses. In this paper, transient analysis is performed with the focus on the response of reactive power and the resonance between the de capacitor and ac reactors. Experimental results obtained from a small-rated laboratory model of 10 kVA are also shown to verify analytical results based on the p-q transformation. The analytical results help in the design of system parameters such as the capacity of the de capacitor and feedback gains.

关键词： reactive power compensator voltage-source inverter PAM higher harmonics power system stabilization

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Ultrasonic interfacial crosslinking of TiO2-based nanocomposite hydrogels through thiol-norbornene reactions for sonodynamic antibacterial treatment

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Biomaterials science 2023年第12期11卷 4184-4199页

作者： Yang, Su-Rung Wang, Reuben Yan, Chen-Jie Lin, Yi-Yun Yeh, Yu-Jia Yeh, Ying-Yu Yeh, Yi-Cheun Institute of Polymer Science and Engineering National Taiwan University Taipei Taiwan Institute of Food Safety and Health National Taiwan University Taipei Taiwan Master of Public Health Program National Taiwan University Taipei Taiwan GIP-TRIAD Master's Degree in Agro-Biomedical Science National Taiwan University Taipei Taiwan

Nanocomposite (NC) hydrogels used for sonodynamic therapy (SDT) face challenges such as lacking interfacial interactions between the polymers and nanomaterials as well as presenting uneven dispersion of nanomaterials in the hydrogel network, reducing their mechanical properties and treatment efficiency. Here, we demonstrate a promising approach of co-engineering nanomaterials and interfacial crosslinking to expand the materials construction and biomedical applications of NC hydrogels in SDT. In this work, mesoporous silica-coated titanium dioxide nanoparticles with thiolated surface functionalization (TiO2@MS-SH) are utilized as crosslinkers to react with norbornene-functionalized dextran (Nor-Dex) through ultrasound-triggered thiol-norbornene reactions, forming TiO2@MS-SH/Nor-Dex NC hydrogels. The TiO2@MS-SH nanoparticles act not only as multivalent crosslinkers to improve the mechanical properties of hydrogels under ultrasound irradiation but also as reactive oxygen species (ROS) generators to allow the use of TiO2@MS-SH/Nor-Dex NC hydrogels in SDT applications. Particularly, the TiO2@MS-SH/Nor-Dex NC hydrogels present tailorable microstructures, properties, and sonodynamic killing of bacteria through the modulation of the ultrasound frequency. Taken together, a versatile TiO2-based NC hydrogel platform prepared under ultrasonic interfacial crosslinking reactions is developed for advancing the applications in SDT. © 2023 The Royal Society of Chemistry.

关键词： Titanium dioxide

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ROI detection of reading process using ANFIS method

ROI detection of reading process using ANFIS method

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4th biomedical engineering International Conference, BMEiCON-2011

作者： Pongpanitanont, Pongphan Sittiprapaporn, Wichian Prasertsakul, Thunyanoot Charoensuk, Warakorn Department of Biomedical Engineering Faculty of Engineering Mahidol University Nakorn Pathom Thailand Office of the Doctoral Degree Program Studies in Education Mahasarakham University Faculty of Education Nakhonsawan Rd. Talad Sub-district Muang District Mahasarakham 44000 Thailand Department of Electrical Engineering Faculty of Engineering Mahidol University Nakorn Pathom Thailand

ISBN: (纸本)9781457721908

This paper studies the application of the adaptive neuro-fuzzy inference system (ANFIS). We propose the ANFIS used for region of interest (ROI) detection in brain fMRI images. The ROI is used for estimating the tissue activity by Blood-Oxygen Level Dependent technique (BOLD). The result shows the ANFIS model can be used to fit the image time-intensity data. A 3 Gaussian membership functions were proposed to estimate the time-intensity relation. The result shows the rate of time-intensity relation to determine the tissue activity. The tissue activity should be determined the normal pattern of reading process. © 2011 IEEE.

关键词： Tissue

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