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16th IEEE International Conference on Nano/Molecular Medicine and engineering, NANOMED 2023

作者： Liao, Hao-Yen Chu, Cheng-Shane Wu, Yang-Shun Lin, Sheng-Chieh Lin, Chia-Tsai Hung, Kuo-Yung Ming Chi University of Technology Dept. of Intl. Ph.D Program in Innovative Technology of Biomedical Engineering and Medical Devices Taiwan Ming Chi University of Technology Department of Mechanical Engineering Taiwan Ming Chi University of Technology Research Center for Intelligent Medical Devices Taiwan

ISBN: (纸本)9798350343700

This study aims to reduce the risk of aerosol infection in patients and healthcare workers by establishing a portable negative pressure filtering chest drainage system (PNPFCDS) that filters aerosols and microparticles. By controlling the negative pressure precisely, the system can prevent aerosol transmission under different air leaks. By using a respiratory pressure simulation platform (RPSP), it has been demonstrated that the negative pressure filtering chest drainage system can achieve a minimum measured pressure error of 1.6% without simulated intrapleural pressure changes when the air leak flow rises to 800 ml/min. When the target pressure is -1.5 kPa under simulated intrapleural pressure changes with air leak of 500 ml/min, the measured pressure change rate ranges from -16.7 % to +22.7%. When the target pressure is -9 kPa, the measured pressure change rates ranges from -2% to +6.7%. According to ISO 10079-1, this study provides a model of a negative pressure filtering chest drainage system that is effective and safe. © 2023 IEEE.

关键词： Aerosols

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Composite Distributed Learning and Synchronization of Nonlinear Multi-Agent Systems with Complete Uncertain Dynamics

Composite Distributed Learning and Synchronization of Nonlin...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Emadodin Jandaghi Dalton L. Stein Adam Hoburg Paolo Stegagno Mingxi Zhou Chengzhi Yuan Department of Mechanical Industrial and Systems Engineering Kingston RI USA Department of Electrical Computer and Biomedical Engineering Kingston RI USA Graduate School of Oceanography Kingston RI USA

ISBN: (数字)9798350355369

ISBN: (纸本)9798350355376

This paper addresses the problem of composite synchronization and learning control in a network of multiagent robotic manipulator systems with heterogeneous nonlinear uncertainties under a leader-follower framework. A novel two-layer distributed adaptive learning control strategy is introduced, comprising a first-layer distributed cooperative estimator and a second-layer decentralized deterministic learning controller. The first layer is to facilitate each robotic agent’s estimation of the leader’s information. The second layer is responsible for both controlling individual robot agents to track desired reference trajectories and accurately identifying/learning their nonlinear uncertain dynamics. The proposed distributed learning control scheme represents an advancement in the existing literature due to its ability to manage robotic agents with completely uncertain dynamics including uncertain mass matrices. This allows the robotic control to be environment-independent which can be used in various settings, from underwater to space where identifying system dynamics parameters is challenging. The stability and parameter convergence of the closed-loop system are rigorously analyzed using the Lyapunov method. Numerical simulations validate the effectiveness of the proposed scheme.

关键词： Adaptive learning Computer aided instruction Uncertainty System dynamics Distance learning Aerospace electronics Nonlinear dynamical systems

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Mannoside-Functionalized Silica Nanocomposite-Encapsulated Doxorubicin for MDA-MB-231 Cancer Cell Targeting and Delivery

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ACS Applied Nano Materials 2023年第6期6卷 4957-4968页

作者： Su, Yu-Han Lin, Han-Chen Li, Hsing-Yen Lien, Chih-Hsuan Shih, Yao-Hsiang Lai, Chian-Hui Graduate Institute of Biomedical Engineering National Chung Hsing University Taichung402 Taiwan Department of Anatomy School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung807 Taiwan Department of Medical Research Kaohsiung Medical University Hospital Kaohsiung807 Taiwan Department of Medicinal and Applied Chemistry Kaohsiung Medical University Kaohsiung807 Taiwan

The purpose of this study was to develop a carbohydrate silica nanocomposite, M-mDOX@SiO2, that can specifically target cancer cells and release the drug doxorubicin (DOX) specifically in an acidic tumor microenvironment (TME). First, DOX@SiO2 was prepared using the Stöber method to encapsulate DOX within silica nanoparticles (NPs). DOX@SiO2 was then immersed in acidic PBS (pH 5) to obtain mesoporous silica-based NPs, termed mDOX@SiO2. Through mannoside and galactoside surface silane modification of mDOX@SiO2, we obtained M-mDOX@SiO2 (specifically targeting the MDA-MB-231 cell surface receptor) and G-mDOX@SiO2 (a nontargeting control), respectively. The synthesized silica NPs were characterized through ultraviolet-visible (UV-vis) spectrophotometry, fluorescence spectrometry, dynamic light scattering, and transmission electron microscopy. The anthrone-sulfuric acid method was used to measure the NP surface sugar content, and thermogravimetric analysis was applied to estimate the content of DOX loaded inside the NPs. The drug release profiles of M-mDOX@SiO2 in different pH buffer solutions demonstrated that M-mDOX@SiO2 can effectively release DOX in an environment with a pH of 5;moreover, the drug release rate increased as pH decreased. Fluorescence spectrometry and confocal microscopy were used to image MDA-MB-231 cells specifically targeted by M-mDOX@SiO2. The MTT assay results revealed that M-mDOX@SiO2 resulted in efficient cell growth inhibition. Finally, our animal experiments revealed that M-mDOX@SiO2 demonstrated high antitumor efficacy. In conclusion, M-mDOX@SiO2 has great potential as a drug delivery carrier. © 2023 American Chemical Society.

关键词： Carbohydrates

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Pipeline System for Versatile Medical Image Processing

Pipeline System for Versatile Medical Image Processing

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2023 IEEE EMBS Special Topic Conference on Data Science and engineering in Healthcare, Medicine and Biology, IEEECONF 2023

作者： Rodríguez-Carpio, A.B. Bojorges-Valdez, E. Yáñez-Suarez, O. Biomedical Engineering Program Universidad Iberoamericana Ciudad de México CDMX01219 Mexico Universidad Iberoamericana Ciudad de México CDMX01219 Mexico Universidad Autónoma Metropolitana Iztapalapa CDMX09340 Mexico

ISBN: (纸本)9798350383386

Machine learning (ML) algorithms are valuable for various clinical imaging tasks, including organ and lesion segmentation and diagnostic support. This paper suggests a versatile system architecture that follows a standard pipeline of capture, processing, and display and a manager that evaluates input image and performs user-selected tasks over it. This architecture can perform three distinct tasks: detecting specific images in a scene, segmenting based on imaging modality, and classifying images related to pathology. The system was evaluated using Dice index (DI) in segmentation tasks such as lung from CT and transmission radiography (DI: 0.956 ± 0.015, DI: 0.8013 ± 0.277 respectively), heart from CT (DI: 0.8396 ± 0.2188), and optic disc from slit lamps (DI: 0.9134 ± 0.079). In diagnostic tasks, accuracy was evaluated for five-class fundus pathology classification (0.854 ± 0.015) and six class thoracic radiography classification (0.972 ± 0.0069). The real time operation of the system depends on the active mode: detection and segmentation are performed at 23 frames per second (fps), detection and diagnostic 3 fps, all modes at once 2 fps. These values show the viability of the architecture presented here as proof of *** Relevance: The presented project aims to build a versatile visualization assistance system for medical staff, that allows three operation modes by an easy change of internal ML model. © 2023 IEEE.

关键词： Pipelines

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An interdisciplinary approach to high school curriculum development: Swarming Powered by Neuroscience 12

An interdisciplinary approach to high school curriculum deve...

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12th IEEE Integrated STEM Education Conference, ISEC 2022

作者： Buckley, Elise Monaco, Joseph D. Schultz, Kevin M. Chalmers, Robert W. Hadzic, Armin Zhang, Kechen Hwang, Grace M. Carr, M. Dwight United States Department of Biomedical Engineering School of Medicine JHU United States Jhuapl United States Computer Vision Researcher Formerly Jhuapl United States Biomedical Engineering School of Medicine Jhu United States Jhuapl Johns Hopkins University Kavli Neuroscience Discovery Institute United States Program Manager Stem Program Management Office Jhuapl United States

ISBN: (纸本)9781665484299

This article discusses how to create an interactive virtual training program at the intersection of neuroscience, robotics, and computer science for high school students with equity of access. A four-day microseminar, titled Swarming Powered by Neuroscience (SPN), was conducted virtually through a combination of presentations and interactive computer game simulations. The SPN microseminar was delivered by subject matter experts in neuroscience, mathematics, multi-agent swarm robotics, and education. The objective of this research was to determine if taking an interdisciplinary approach to high school education would enhance the students learning experiences in fields such as neuroscience, robotics, or computer science. This study found an improvement in student engagement for neuroscience by 16.6%, while interest in robotics and computer science improved respectively by 2.7% and 1.8%. The majority of students (64%) strongly agreed that they enjoyed learning from an interdisciplinary team of experts and 70% strongly agreed that the microseminar emphasized the need to have instruction teams with diverse disciplinary backgrounds. The curriculum materials, developed for the SPN microseminar, can be used by high school teachers to further evaluate interdisciplinary instructions across life and physical sciences and computer science. © 2022 IEEE.

关键词： Curricula

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Synthetic Data-Empowered Supervised Machine Learning Modeling for a Binary Fracture Risk Assessment from 2D-DXA Analysis

SSRN

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SSRN 2023年

作者： Choi, Heesun Quagliato, Luca Chung, Yoon-Sok Lee, Taeyong Division of Mechanical and Biomedical Engineering Ewha Womans University Seoul03760 Korea Republic of Division of Mechanical and Biomedical Engineering Graduate Program in System Health Science and Engineering Ewha Womans University Seoul03760 Korea Republic of Department of Endocrinology and Metabolism Ajou University School of Medicine Suwon16499 Korea Republic of

Background and Objectives: Bone fracture risk assessment for osteopenia and osteoporotic patients is essential for the adoption of early countermeasures and avoiding discomfort and hospitalization. Currently employed methodologies, such as FRAX®, provides a risk assessment over a five to ten years period without showing the main variables influencing the prediction nor how they can be targeted in the short term. Thus, a lesser black-box approach where the fracture risk can be assessed in real-time from a commonly employed analysis, id est the dual-energy X-ray absorptiometry (2D-DXA), would be of help to clinicians and patients alike. Accordingly, this study presents three real-time machine learning (ML) assessment models, with distinct complexity, architectures, and performances, capable of predicting a binary fracture risk based on a femur head-hip joint 2D-DXA scan. Methods: A ~10,000 adult Korean gathered between 2017 and 2021 and composed of ~90% female and ~10% male ranging from 50 to 99 years of age was considered. 10% of the data is relevant to subjects who experienced skeletal fractures, among which 245 cases are femur fractures. The 2D-DXA analyses of the femur head-hip joint region carried out on patients allowed collecting 23 parameters, including the patient’s age, BMI, and gender, associated with one binary variable, defined in terms of non-fracture (NFX) or fracture (FX), to be employed as the training dataset for the three ML models employed and optimized in this research. The 2D-DXA results’ database (DB) was employed to train three ML classifiers with a binary (NFX/FX) output layer, namely the Extreme Gradient Boosting (XGB), the K-Nearest Neighbor (KNN), and Deep Neural Network (DNN). To avoid overfitting due to the higher number of NFX data with respect to FX one, two features augmentation techniques based on the Synthetic Minority Over-sampling Technique (SMOTE) and Oversample using Adaptive Synthetic (ADASYN) oversamplers were employed. For all

关键词： Fracture

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Design and Evaluation of an Immersive Virtual Reality Game for the Treatment of Attention Deficit and Hiperactivity Disorder in Adults

SSRN

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SSRN 2023年

作者： Alvarez-Suarez, Ana Caldas, Oscar I. Biomedical Engineering Program Faculty of Engineering Universidad Militar Nueva Granada Km 2 Via Cajica-Zipaquira Cajica250247 Colombia

Attention deficit hyperactivity disorder (ADHD) is one of the most common psychological pathologies worldwide. Despite mostly occurring in childhood, it could lead to difficulties in adults, mainly on social relations, personal life and performance in work or *** present, novel technological approaches, such as interactive tools in mixed and virtual reality (VR), have proven to enhance the traditional therapies to reduce the observation dependency and subjectivity. However, usage is still not widespread due to higher costs, field implementation difficulties (e.g., electroencephalography or electrooculography), or being only pediatric-oriented. Therefore, the following research aimed to design and evaluate an immersive Virtual Reality game based on the psychological evaluation of the Continuous Performance Test (CPT) to quantify and supervise the ADHD symptoms, and test any *** game design methodology, measuring techniques and data analysis are presented. A controlled experiment was carried out with 37 participants randomly assigned to two immersion groups: a VR version developed in Unity vs Real version of a custom-made table tennis game, designed to assess nine ADHD-related symptom indicators. All participants performed the activity three times (once per week) to test the individual effect of time and its interaction with the level of immersion. Results suggested greater impulsivity and cognitive flexibility when performing the therapy in VR than in real table tennis, whereas no significant differences were found between the three weekly sessions. © 2023, The Authors. All rights reserved.

关键词： Virtual reality

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Rapid Escherichia coli Cloned DNA Detection in Serum Using an Electrical Double Layer-Gated Field-Effect Transistor-Based DNA Sensor

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Analytical Chemistry 2023年第17期95卷 6871-6878页

作者： Paulose, Akhil K. Hou, Yueh-Ju Huang, Yu-Shan Chakkalaparambil Dileep, Navyamol Chiu, Chia-Lin Pal, Arnab Kalaimani, Vishal Mani Lin, Zong-Hong Chang, Chuang-Rung Chen, Cheng-Pin Lin, Yi-Chun Cheng, Chien-Yu Cheng, Shu-Hsing Cheng, Chao-Min Wang, Yu-Lin Institute of Nanoengineering and Microsystems National Tsing Hua University Hsinchu30013 Taiwan Department of Power Mechanical Engineering National Tsing Hua University Hsinchu30013 Taiwan College of Semiconductor Research National Tsing Hua University Hsinchu30013 Taiwan Department of Life Sciences National University of Kaohsiung Kaohsiung811726 Taiwan Department of Biomedical Engineering National Taiwan University Taipei10617 Taiwan Institute of Biotechnology National Tsing Hua University Hsinchu30013 Taiwan Department of Infectious Diseases Taoyuan General Hospital Ministry of Health and Welfare Taoyuan32748 Taiwan Institute of Biomedical Engineering National Tsing Hua University Hsinchu30013 Taiwan International Intercollegiate PhD Program National Tsing Hua University Hsinchu30013 Taiwan

In this study, a rapid diagnosis platform was developed for the detection of Escherichia coli O157:H7. An electrical double layer (EDL)-gated field-effect transistor-based biosensor (BioFET) as a point-of-care testing device is demonstrated with its high sensitivity, portability, high selectivity, quick response, and ease of use. The specially designed ssDNA probe was immobilized on the extended gate electrode to bind the target complementary DNA segment of E. coli, resulting in a sharp drain current change within minutes. The limit of detection for target DNA is validated to a concentration of 1 fM in buffer solution and serum. Meanwhile, the results of a Kelvin probe force microscope were shown to have reduced surface potential of the DNA immobilized sensors before and after the cDNA detection, which is consistent with the decreased drain current of the BioFET. A 1.2 kb E. coli duplex DNA synthesized in plasmid was sonicated and detected in serum samples with the sensor array. Gel electrophoresis was used to confirm the efficiency of sonication by elucidating the length of DNA. Those results show that the EDL-gated BioFET system is a promising platform for rapid identification of pathogens for future clinical needs. © 2023 American Chemical Society

关键词： DNA

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Computerized Classification Method for Molecular Subtypes in Glioma with Multi-Scale 3D-Attention Branch Networks Analyzing Multi-Sequence Brain MRI Images

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and Systems 2023年第5期143卷 539-545页

作者： Tanaka, Daiki Hizukuri, Akiyoshi Nakayama, Ryohei Kusuda, Kaori Masamune, Ken Muragaki, Yoshihiro Graduate School of Science and Engineering Ritsumeikan University 1-1-1 Nojihigashi Kusatsu Shiga525-8577 Japan Division of Healthcare Informatics Tokyo Healthcare Universtiy 3-11-3 Setagaya Setagaya-ku Tokyo154-8568 Japan Faculty of Advanced Techno-Surgery Institute of Advanced Biomedical Engineering and Science Tokyo Women’s Medical University 8-1 Kawada-cho Shinjuku-ku Tokyo162-8666 Japan

The purpose of this study was to develop a computerized classification method for molecular subtypes in low-grade gliomas (LGGs) with multi-scale 3D-attention branch networks analyzing multi-sequence brain MRI images. Our dataset consisted of brain T1-weighted and T2-weighted MRI images for 217 patients (58 Astrocytoma IDH-mutant, 49 Astrocytoma IDH-wildtype, and 110 Oligodendroglioma). The proposed method was constructed from a feature extractor, an attention branch, and a perception branch. In the feature extractor, the feature maps were extracted from brain T1-weighted and T2-weighted MRI images, respectively. The attention branch focused on a tumor region and generated the attention maps normalized to 0.0 – 1.0. The feature maps were then multiplied by the attention maps to weight features on LGG in the feature maps. The molecular subtype in LGG was evaluated in the perception branch. The classification accuracy for the proposed method was 63.6%, showing an improvement when compared with the conventional method using only single sequence (T2-weighted) MRI images (59.9%). © 2023 The Institute of Electrical Engineers of Japan.

关键词： Tumors

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Comparison of Precision Grasping Performance between Artificial Fingers With and Without Nails 4

Comparison of Precision Grasping Performance between Artific...

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4th IEEE Global Conference on Life Sciences and Technologies, LifeTech 2022

作者： Kumagai, Ayane Obata, Yoshinobu Yabuki, Yoshiko Jiang, Yinlai Yokoi, Hiroshi Togo, Shunta The University of Electro-Communications Graduate School of Informatics and Engineering Department of Mechanical and Intelligent System Engineering Tokyo Japan The University of Electro-Communications Center for Neuroscience and Biomedical Engineering Tokyo Japan Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing China

ISBN: (纸本)9781665419048

In this study, we investigated the effect of the presence or absence of fingernails on precision grasping using artificial anthropomimetic fingers. We hypothesized that fingernails improve precision grasping performance by increasing the friction coefficient while suppressing fingertip deformation. To test our hypothesis, we developed artificial fingertips, each composed of bone, nail, skin, and soft tissue, and fabricated three types of artificial fingers with different skin softness grades and artificial fingers without nails as the control condition. Pull-out experiments of cylindrical objects and T-shaped blocks were conducted using the developed artificial fingertips with and without nails, and the pull-out resistance forces were compared. The nail contributed to object grasping stability because the pull-out resistance force was significantly increased by the presence of the nail in the artificial fingertip with soft skin. The rate of increase in the resistance force of the T-shaped block was more significant than that of the cylindrical object because the finger pulp deformation was suppressed by the nail, and the form closure, that is, geometric constraint, was formed for the grasping object. These results suggest that the human nail improves precision grasping performance by forming geometric constraints on the grasped object, suppressing finger pulp deformation. © 2022 IEEE.

关键词： Deformation

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