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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yiwen Ruan Rui Jin Zhaorui Liu Caishan Wang Lei Zhang Tao Peng School of Future Science and Engineering Soochow University Suzhou China Department of Ultrasound Second Affiliated Hospital of Soochow University Suzhou China Graduate Program of Medical Physics and Data Science Research Center Duke Kunshan University Kunshan Jiangsu China Department of Radiation Oncology UT Southwestern Medical Center Dallas Texas USA

Delineation of prostate cancer (PCa) on ultrasound images has become an essential technique for early PCa treatment, which still faces several challenges, such as low image contrast and blurred organ boundaries. Facing the aforementioned issues, a novel coarse-fine segmentation framework method is adopted in this work. First, a deep learning algorithm is used for positioning the region of interest (ROI); then, the principal curve-related technique is adopted to fine-tune initial results. Thirdly, an enhanced quantum evolutionary algorithm is used to hunt for the optimal initialization of the backpropagation neural network. Finally, an interpretable mathematical model is introduced for representing the ROI contour by using the parameters of the neural network. A comprehensive evaluation using the clinical data proves the superiority of our method, with Dice similarity coefficient (DSC) of 83.48+3.44%, Jaccard similarity coefficient (Ω) of 82.25+4.12%, and accuracy (ACC) of 83.4+3.57%, respectively.

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Design and fabrication of a metalens with a hexagonal array of intersecting-wall meta-atoms for operation in the near-infrared 5

Design and fabrication of a metalens with a hexagonal array ...

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5th IEEE Research and Applications of Photonics in Defense Conference, RAPID 2022

作者： Horton, Chad L. Kuebler, Stephen M. Martinez, Manuel Bustamante, Edgar Rumpf, Raymond C. Touma, Jimmy University of Central Florida Chemistry Department OrlandoFL32816 United States Creol The College of Optics and Photonics Chemistry Department University of Central Florida Department of Materials Science and Engineering OrlandoFL32816 United States University of Texas at El Paso Em Lab Department of Electrical and Computer Engineering El PasoTX79968 United States University of Texas at El Paso Em Lab Department of Electrical and Computer Engineering Computational Science Program El PasoTX79968 United States AFRL/Munitions Directorate Integrated Sensing and Processing Branch Eglin AFB FL32542 United States

A metalens with a hexagonal array of intersecting-wall meta-atoms was designed for operation at a wavelength of 1.550 μm with a new meta-optics design tool (MODT) and fabricated in the photopolymer IP-Dip by multi-ph... 详细信息

ISBN: (数字)9781665402231

ISBN: (纸本)9781665402231

关键词： Photons

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New connections between brand and environmentally sustainable businesses in the Amazon forest and local business owner’s perception

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Sustainable Earth Reviews 2023年第1期6卷 1-17页

作者： Luiz Diego Vidal Santos Francisco Sandro Rodrigues Holanda Pedro Vinícius Bertulino de Menezes Ana Paula Schervinski Villwock Alceu Pedrotti Catuxe Varjão de Santana Oliveira Graduate Program in Intellectual Property Science Universidade Federal de Sergipe-UFS São Cristóvão Sergipe Brasil Agronomy Engineering Department Universidade Federal de Sergipe-UFS São Cristóvão Sergipe Brasil Computer Science Department Instituto Federal de Sergipe-UFS Lagarto Sergipe Brasil

The debate surrounding entrepreneurship in the Amazon rainforest region highlights the importance of sustainable actions developed by local brands. However, limited attention has been given to entrepreneur's perspectives regarding the outcome of their applied practices. The objective of this study was to understand the entrepreneurs’ perception based on their business models concerning the connection to the Amazon brand and the aspects of sustainable use of its natural resources. The study was performed through semi-structured interviews with seven Amazonian product brands entrepreneurs utilizing Grounded Theory. The results demonstrate that entrepreneurs understand that reaching the social dimension relies on the articulation of three main factors: entrepreneurs, the native people, and the shared traditional knowledge and culture. It is observed that the political dimension is still underdeveloped in the region with limited application of its effects on products. Additionally, the economic dimension is not significantly favored by the utilization of environmentally sustainable brands. Lastly, the territorial dimension depends on the establishment of permanent protection areas, as well as agroforestry systems.

关键词： Brand Environmental sustainability Marketing Entrepreneur behavior Traditional communities

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Jing-Si Herbal Tea Suppresses H2O2-Instigated Inflammation and Apoptosis by Inhibiting Bax and Mitochondrial Cytochrome C Release in HIG-82 Synoviocytes

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Environmental Toxicology 2024年第12期39卷 5347-5356页

作者： Kao, Shih-Wen Chang, Yu-Chun Lin, Feng-Huei Huang, Tai-Lung Chen, Tung-Sheng Lin, Shinn-Zong Lin, Kuan-Ho Kuo, Wei-Wen Ho, Tsung-Jung Huang, Chih-Yang Graduate Institute of Aging Medicine China Medical University Taichung Taiwan Department of Orthopedic Surgery Chung-Shan Medical University Hospital Taichung Taiwan Department of Biological Science and Technology College of Life Sciences China Medical University Taichung Taiwan Cardiovascular and Mitochondrial Related Disease Research Center Hualien Tzu Chi Hospital Buddhist Tzu Chi Medical Foundation Hualien Taiwan Institute of Biomedical Engineering College of Medicine and College of Engineering National Taiwan University Taipei Taiwan Division of Biomedical Engineering and Nanomedicine Research National Health Research Institute Miaoli Taiwan Department of Orthopedics Chung-Kang Branch Cheng Ching General Hospital Taichung Taiwan School of Life Science National Taiwan Normal University Taipei Taiwan Department of Neurosurgery Hualien Tzu Chi Hospital Buddhist Tzu Chi Medical Foundation Hualien Taiwan Bioinnovation Center Buddhist Tzu Chi Medical Foundation Hualien Taiwan Department of Emergency Medicine China Medical University Hospital Taichung Taiwan College of Medicine China Medical University Taichung Taiwan Ph.D. Program for Biotechnology Industry China Medical University Taichung Taiwan School of Pharmacy China Medical University Taichung Taiwan School of Post-Baccalaureate Chinese Medicine College of Medicine Tzu chi University Hualien Taiwan Department of Chinese Medicine Hualien Tzu Chi Hospital Buddhist Tzu Chi Medical Foundation Tzu Chi University Hualien Taiwan Integration Center of Traditional Chinese and Modern Medicine Hualien Tzu Chi Hospital Buddhist Tzu Chi Medical Foundation Hualien Taiwan Graduate Institute of Biomedical Sciences China Medical University Taichung Taiwan Department of Medical Laboratory Science and Biotechnology Asia University Taichung Taiwan

Inflammation is an intrinsic protective mechanism against various forms of cellular injuries in humans;however, its undesired activation results in tissue damage and cell death. The onset of chronic inflammation and oxidative stress are the key characteristics of autoimmune inflammatory diseases such as rheumatoid arthritis (RA), for which an effective treatment is yet to be developed. Therefore, in this study, we investigated the protective effects and molecular mechanisms of a novel herbal preparation, Jing-Si herbal tea (JS), against H2O2-induced inflammation and cellular damage in HIG-82 synoviocytes. We found that JS did not show any significant alterations in cell viability at 2O2-induced pathological oxidative stress (ROS) in HIG-82 cells. Interestingly, JS treatment not only reduced the ROS levels but also significantly repressed the protein expressions of collagen degrading proteases in a dose-dependent manner. Treatment with JS showed enhanced cell viability against H2O2-induced toxic ROS levels. The expressions of cell protective aggrecan, Collagen II, and Bcl-2 were increased, whereas MMP-13, ADAMTS-2, Cytochrome C, and cleaved Caspase 3 were decreased by JS under inflammatory agents H2O2, MIA, LPS, and TNF-α treatment, respectively, in HIG-82 cells. Interestingly, the cytoprotective effect of JS treatment was attributed to a decreased mitochondrial localization of Bax and a reduction of Cytochrome C release into the cytoplasm of H2O2-treated HIG-82 cells. Collectively, our results suggest a novel protective mechanism of JS for RA treatment, which could be potentially applied as a complementary treatment or as an alternative therapeutic approach to mitigate inflammatory diseases. © 2024 Wiley Periodicals LLC.

关键词： Cell death

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Deep Brain Optoacoustic Stimulation Enabled by a Multifunctional Fiber-based Optoacoustic Emitter

Deep Brain Optoacoustic Stimulation Enabled by a Multifuncti...

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Optics and the Brain, BRAIN 2022

作者： Zheng, Nan Jiang, Ying Jiang, Shan Li, Yueming Jia, Xiaoting Yang, Chen Cheng, Ji-Xin Division of Materials Science and Engineering Boston University BostonMA02215 United States Graduate Program for Neuroscience Boston University BostonMA02215 United States Photonics Center Boston University BostonMA02215 United States Department of Mechanical Engineering Boston University BostonMA02215 United States Department of Biomedical Engineering Boston University BostonMA02215 United States Department of Chemistry BostonMA02215 United States

Optoacoustic neurostimulation is a non-genetic light-mediated technique allows high precise control of neural activities. Here, we combined optoacoustic stimulation and electrophysiological recording to achieve bidire... 详细信息

ISBN: (纸本)9781957171036

关键词： Electrophysiology

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Beyond Visual Image: Automated Diagnosis of Pigmented Skin Lesions Combining Clinical Image Features with Patient Data

arXiv

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arXiv 2022年

作者： Esgario, José G.M. Krohling, Renato A. Federal University of Espírito Santo ES Vitória Brazil PPGI - Graduate Program in Computer Science LABCIN Production Engineering Department

Skin cancer is considered one of the most common type of cancer in several countries. Due to the difficulty and subjectivity in the clinical diagnosis of skin lesions, Computer-Aided Diagnosis systems are being developed for assist experts to perform more reliable diagnosis. The clinical analysis and diagnosis of skin lesions relies not only on the visual information but also on the context information provided by the patient. This work addresses the problem of pigmented skin lesions detection from smartphones captured images. In addition to the features extracted from images, patient context information was collected to provide a more accurate diagnosis. The experiments showed that the combination of visual features with context information improved final results. Experimental results are very promising and comparable to experts. © 2022, CC BY.

关键词： Computer aided diagnosis

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Sentiment Analysis of User Review on Indonesian Food and Beverage Group using Machine Learning Techniques

Sentiment Analysis of User Review on Indonesian Food and Bev...

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Creative Communication and Innovative Technology (ICCIT), IEEE

作者： Yanfi Yanfi Yaya Heryadi Lukas Lukas Wayan Suparta Yulyani Arifin Computer Science Department BINUS Graduate Program Computer Science School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

A vast number of technologies based on Artificial Intelligence (AI) have proliferated into various application domains. As part of its objectives to develop agents which can behave and think like humans, some branches of AI have focused on developing various algorithms that can learn from input data without explicitly being programmed. In the food industry, notably in restaurants, smartphone technology is typically used to collect data from customers efficiently such as orders or feedback toward the services provided. The use of smartphones by some restaurants is motivated by their convenience and efficiency. Furthermore, various promotions, discounts, and membership benefits offered by cellular service providers have attracted the use of smartphones as devices for improving restaurant services to their customers. This study aimed to conduct a sentiment analysis related to multi-brand restaurants in Indonesia based on customer feedback. The data retrieved from the Google Play Store consists of 756 reviews from Boga, Champs, Hangry, Ismaya, Kulo, and Union groups. In this study, TF-IDF was used as a vectorizer to represent customer feedback as numeric vectors. The polarity sentiment of customer feedback was recognized using classifier models based on machine learning such as Logistic Regression, Naive Bayes (NB), Random Forest, and Support Vector Machine (SVM) as the classifier. The empirical results showed that SVM has the best accuracy of 93.10 % average accuracy followed by Logistic Regression with 92.41 %, Random Forest with 84.14 % average accuracy, and Naive Bayes with 76.55 % average accuracy.

关键词： Support vector machines Sentiment analysis Analytical models Machine learning algorithms Food industry Companies Classification algorithms

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Classifying Tweet Sentiment Analysis on Airlines using Random Forest Classifier, Naïve Bayes Classifier and K-Nearest Neighbors Classifier Algorithm

Classifying Tweet Sentiment Analysis on Airlines using Rando...

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Artificial Intelligence Robotics, Signal and Image Processing (AIRoSIP), International Conference on

作者： Ivan Alexander Yaya Heryadi Lukas Wayan Suparta Ilvico Sonata Computer Science Departement Binus Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

ISBN: (数字)9798350327472

ISBN: (纸本)9798350327489

Opinion has always affected businesses and individuals especially from the Public. People react through social media and spread it incompletely. The situation was then accepted as public opinion. There are three categories of opinion i.e., positive, negative, and neutral. To investigate public opinion on a particular issue of interest, sentiment analysis might be employed. By offering a solution to the text classification challenge, this experiment focuses on the perception of airline tweets among the American public. We offer a method to classify tweets as positive, negative, or neutral using three machine learning classifiers: Random Forest Classifier, Naive Bayes Classifier, and K-Nearest Neighbors Classifier. We examined the performance of three machine learning classifiers in terms of accuracy, average precision, average recall, and average f-1 score. The results demonstrate that the Random Forest Classifier, which produces 82% accuracy, 80% average precision, 82% average recall, and 80% average f1-score, performs the best among the machine learning classifiers.

关键词： Training Sentiment analysis Accuracy Social networking (online) Text categorization Nearest neighbor methods Naive Bayes methods Random forests Robots Airline industry

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Innovative High Step-Up Converter for Improved Photovoltaic Efficiency

Innovative High Step-Up Converter for Improved Photovoltaic ...

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IEEE Annual Southern Power Electronics Conference (SPEC)

作者： Chun-Hsin Chang Hwa-Dong Liu Chang-Hua Lin Rashid Ahmed Khan Yi-Jie Zeng Undergraduate Program of Vehicle and Energy Engineering National Taiwan Normal University Taipei City Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei City Taiwan Graduate Institute of Green Energy and Sustainable Technology National Taiwan Normal University Taipei City Taiwan

ISBN: (数字)9798350351156

ISBN: (纸本)9798350351163

This study introduces an innovative high step-up (HSU) converter designed for solar photovoltaic systems equipped with a maximum power point (MPP) tracker. This converter efficiently increases the output voltage while maintaining low voltage stress on its components, thanks to a novel combination of primary boost cells, switched capacitors, and voltage multiplier cells. A clamping circuit minimizes leakage energy, enhancing overall efficiency. Testing of a prototype confirmed its effective MPP tracking and high efficiency, with a conversion rate of 20 V-40 V to 380 V at 150 W and efficiencies between 90 % and 96 %.

关键词： Photovoltaic systems Electric potential Renewable energy sources Capacitors Prototypes Voltage Switches Power electronics Stress Testing

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Downstream Task Performance of Pre-Trained Model For Outdoor Audio Event Classification

Downstream Task Performance of Pre-Trained Model For Outdoor...

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International Conference of Signal Processing and Intelligent Systems (ICSPIS)

作者： Theresia Herlina Rochadiani Yaya Heryadi Ilvico Sonata Lukas Wawan Suparta BINUS Graduate Program- Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

Our surroundings’ auditory landscapes are a wealth of knowledge, providing insights into a range of outdoor pursuits. The automatic classification of these actions using audio event detection and classification (AEDC) systems has a great deal of potential applications in environmental monitoring, security, surveillance, and driverless cars. Even though AEDC has advanced significantly in indoor settings, difficulties still exist outside because of the variable and changing acoustic conditions brought on by elements like the weather, different sound sources, and ambient noise from traffic and industry. This study suggests an outdoor audio event categorization model based on convolutional neural networks (CNNs). The suggested model shows passable accuracy by utilizing adaptation to the downstream task using the ESC-50 dataset and transfer learning from a pre-trained model. The effectiveness of multi-class audio classification models in downstream tasks is analyzed in this paper, with an emphasis on the effect of an increasing number of output classes on accuracy. Three models—three, four, and five classes—with different output class configurations are used in the study, and their training and validation accuracies are assessed. Although the accuracy scores above 80% are commendable, the data show a discernible reduction in performance as the number of classes rises. Notably, the three-class model attains a validation accuracy exceeding 90%, whereas the four-class and five-class models exhibit reduced accuracies, falling below 90% and 85%, respectively.

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