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22nd International Conference on Miniaturized systems for Chemistry and Life sciences, MicroTAS 2018

作者： Koduri, Manohar Prasad Garden, Tom Hunt, John A. Henstock, James Curran, Judith Tseng, Fan-Gang International Intercollegiate PhD Program NTHU Hsinchu Taiwan Department of Mechanical Materials and Aerospace School of Engineering University of Liverpool United Kingdom School of Science and Technology Nottingham Trent University NottinghamNG11 8NS United Kingdom Institute of Ageing and Chronic Disease William Henry Duncan Building University of Liverpool United Kingdom Engineering and System Science Frontier Research Center on Fundamental and Applied Sciences of Matters National Tsing Hua University Taiwan

ISBN: (纸本)9781510897571

Technologies like additive manufacturing, microfluidics, and electrospray show a possibility of generating a variety of 3-Dimensional structures but seriously suffer in adapting and utilizing the wide variety of available biocompatible materials because of innate diverse physical and chemical properties of biomaterials. It is very important to have a technology which can be viable and dynamically adaptable for different types of materials in generating uniform structures. This work presents a novel cell-laden hydrogel generation using the surface tension phenomenon in controlling the size of the hydrogel. Copyright © (2018) by Chemical and Biological Microsystems Society. All rights reserved.

关键词： Surface tension

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Life cycle costing analysis for poly-silicon photovoltaics production processes in Japan

Life cycle costing analysis for poly-silicon photovoltaics p...

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IEEE International Conference on Industrial engineering and engineering Management, IEEM2010

作者： Inoue, T. Kajikawa, Y. Yamada, K. Department of Mechanical Engineering University of Tokyo Tokyo Japan Center for Low Carbon Society Strategy Japan Science and Technology Agency Tokyo Japan Inovation Policy Research Center University of Tokyo Tokyo Japan Department of Technology Management for Innovation University of Tokyo Tokyo Japan Integrated Research System for Sustainability Science University of Tokyo Tokyo Japan Executive Management Program University of Tokyo Tokyo Japan

ISBN: (纸本)9781424485031

The objective of this study is to identify the key technology with analysis of the cost boundary of future photovoltaics (PV) technologies using life-cycle costing. We estimate the amount cost of photovoltaic system in Japan. It considers material flows over the whole production process starting from silica extraction to the final panel assembling. The comparison of current scenario to the expected future PV technologies focusing on the equipments in each production processes results in factory scale boundaries. ©2010 IEEE.

关键词： Cost reduction

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The impact of active learning during out-of-school time (OST) Energy Clubs on elementary school students

The impact of active learning during out-of-school time (OST...

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2010 ASEE Annual Conference and Exposition

作者： Albers, Lynn Lindsay, Karen Hemric, Janice Tucker, Jade Bottomley, Laura Hollebrands, Karen Parry, Elizabeth Mechanical and Aerospace Engineering Department North Carolina State University United States Wake County Public School System United States Washington Elementary School United States Fuller Elementary School United States College of Engineering North Carolina State University United States Department of Math Science and Technology Education North Carolina State University United States RAMP-UP program United States

Active learning during out-of-school time Energy Clubs, can positively affect students in grades 3-5 by improving their understanding of technology, what engineers do, the engineering design process, and how to improve a windmill. RAMP-UP assessed the impact through a pre- and posttest from the engineering is Elementary workbook, "Catching the Wind."[2] After completing one activity where the students built windmills out of milk cartons, there were positive improvements in their understanding of technology, what engineers do and the engineering design process ranging from 3% to 8%. Significant gains (p

关键词： Students

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mechanical regulation of actin network dynamics in migrating cells

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Journal of Biomechanical science and engineering 2010年第3期5卷 186-207页

作者： Okeyo, Kennedy Omondi Adachi, Taiji Hojo, Masaki Department of Mechanical Engineering and Science Kyoto University Yoshida-Honmachi Sakyo Kyoto 606-8501 Japan Computational Cell Biomechanics Team VCAD System Research Program RIKEN 2-1 Wako 351-0198 Japan

Cell migration is fundamental to various physiological processes, including metastasis, wound healing and tissue development. The complex processes involved in cell migration;polymerization, adhesion, and retraction, are mediated by highly orchestrated structure-function interactions that occur within the actin cytoskeletal structure. Thus understanding how migrating cells regulate the global dynamics of their cytoskeletal components, which result from rather localized protein-protein interactions, is fundamental to elucidating the mechanisms of cell motility. The objective of this review is to explore the mechanical regulation of actin network dynamics in migrating cells, and to discuss its regulatory role in cell migration. Specifically, we examine the various mechanical forces involved in cell migration, and how they couple with biomechanical factors to spatiotemporally regulate the dynamics of the actin cytoskeleton during cell motility. Two aspects of actin network dynamics are addressed, namely, network turnover by polymerization and depolymerization, and network flow resulting from actomyosin activity. We begin by highlighting the fundamental features of actin network dynamics in migrating cells. We then examine the coupling relationship between actin network flow and traction forces, as well as the mechanism underlying the regulation of traction forces by actin network flow. Finally, we integrate the various motility processes into a mechanical pathway in order to elucidate the importance of mechanical regulation of actin network dynamics to cell migration. © 2010 by JSME.

关键词： Cells

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multi-kernel and multi-scale learning based deep ensemble model for predicting recurrence of non-small cell lung cancer

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PeerJ Computer science 2023年 9卷

作者： Kim, Gihyeon Park, Young Mi Yoon, Hyun Jung Choi, Jang-Hwan Department of Computational Medicine Graduate Program in System Health Science and Engineering Ewha Womans University Seoul Korea Republic of Department of Molecular Medicine College of Medicine Ewha Womans University Seoul Korea Republic of Department of Radiology Veterans Health Service Medical Center Seoul Korea Republic of Division of Mechanical and Biomedical Engineering Graduate Program in System Health Science and Engineering Ewha Womans University Seoul Korea Republic of Department of Artificial Intelligence Ewha Womans University Seoul Korea Republic of

Predicting recurrence in patients with non-small cell lung cancer (NSCLC) before treatment is vital for guiding personalized medicine. Deep learning techniques have revolutionized the application of cancer informatics, including lung cancer timeto-event prediction. Most existing convolutional neural network (CNN) models are based on a single two-dimensional (2D) computational tomography (CT) image or three-dimensional (3D) CT volume. However, studies have shown that using multiscale input and fusing multiple networks provide promising performance. This study proposes a deep learning-based ensemble network for recurrence prediction using a dataset of 530 patients with NSCLC. This network assembles 2DCNNmodels of various input slices, scales, and convolutional kernels, using a deep learning-based feature fusion model as an ensemble strategy. The proposed framework is uniquely designed to benefit from (i) multiple 2D in-plane slices to provide more information than a single central slice, (ii) multi-scale networks and multi-kernel networks to capture the local and peritumoral features, (iii) ensemble design to integrate features from various inputs and model architectures for final prediction. The ensemble of five 2D-CNN models, three slices, and two multi-kernel networks, using 5×5 and 6×6 convolutional kernels, achieved the best performance with an accuracy of 69.62%, area under the curve (AUC) of 72.5%, F1 score of 70.12%, and recall of 70.81%. Furthermore, the proposed method achieved competitive results compared with the 2D and 3D-CNN models for cancer outcome prediction in the benchmark studies. Our model is also a potential adjuvant treatment tool for identifying NSCLC patients with a high risk of recurrence. © 2023 Kim et al.

关键词： Neural network models

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Quantifying material stocks in long-lived products: Challenges and improvements for informing sustainable resource use strategies

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Resources, Conservation and Recycling 2025年 221卷

作者： Jan Streeck André Baumgart Helmut Haberl Fridolin Krausmann Bowen Cai Tomer Fishman Maud Lanau Peter Berrill Zhi Cao Sebastiaan Deetman David Frantz Volker Krey Alessio Mastrucci Alessio Miatto Stefan Pauliuk Lola Sylvie Annie Rousseau Shoshanna Saxe Danielle Densley Tingley Gamze Ünlü Dominik Wiedenhofer BOKU University Institute of Social Ecology Department of Economics and Social Sciences Schottenfeldgasse 29 1070 Vienna Austria Wuhan University School of Remote Sensing and Information Engineering Wuhan Hubei Province 430079 China Leiden University Institute of Environmental Sciences (CML) 2333 CC Leiden Netherlands Chalmers University of Technology Department of Architecture and Civil Engineering Research Area Sustainable Built Environments Gothenburg 412 96 Sweden Universität Berlin Sustainability Economics of Human Settlements Berlin 10623 Germany College of Environmental Science and Engineering Nankai University Tianjin 300350 China School of Earth System Science Tianjin University Tianjin 300072 China Trier University Geoinformatics -Spatial Data Science Trier Rhineland-Palatinate 54296 Germany International Institute for Applied Systems Analysis (IIASA) Energy Climate and Environment (ECE) Program Schlossplatz 1 2361 Laxenburg Austria Commonwealth Scientific and Industrial Research Organisation (CSIRO) Canberra 2601 ACT Australia University of Freiburg Faculty of Environment and Natural Resources Freiburg Baden-Wuerttemberg D-79102 Germany Norwegian University of Science and Technology (NTNU) Industrial Ecology Programme Department of Energy and Process Engineering Trondheim 7034 Norway University of Toronto Department of Civil and Mineral Engineering Toronto Ontario M5S 1A1 Canada University of Sheffield School of Mechanical Aerospace and Civil Engineering Mappin Street Sheffield S1 3JD United Kingdom

Material stocks in long-lived products require over half of the annual global resource extraction for their construction and maintenance, and lock in energy use through their technical and geospatial characteristics. A thorough understanding of material stocks is therefore essential to inform sustainable resource use strategies. However, despite substantial advances in material stock research in recent decades, their robust quantification remains challenging and bears considerable uncertainties. We assess the (dis)agreement of material stock estimates from 32 recent studies across global, national, and urban scales, and propose recommendations for future work. Overall, we observe medium to high divergences between studies estimating the same material stocks. For end-use categories that aggregate multiple material stocks (e.g., buildings), most global-level estimates show divergences within 140 %. At the national level, most estimates for the USA diverge by <210 %, while those for China by <550 %. At the urban level, most estimates for Beijing fall within 90 %, and for Vienna, within 70 %. For low-income countries, non-residential buildings, and individual materials, the differences are often substantially higher, highlighting the need for an improved scientific basis for policy and planning. These disparities arise from differences in system boundaries, methodology, data sources, definitions, and lack of data to capture the diversity of material stock types. To robustly inform sustainable resource use strategies, the scientific community and practitioners should systematically assess and report sensitivity and uncertainty, and reduce the latter through transparent documentation, model intercomparisons, consensus and open-access databases, enhanced data collection, and comprehensive quantification of material stocks.

关键词： Material flow analysis Sustainable resource management Uncertainty analysis Socioeconomic metabolism Material stocks

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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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Numerical study on high intensity focused ultrasound therapy using array transducer

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Physics Procedia 2010年第1期3卷 315-322页

作者： Kohei Okita Kazuyasu Sugiyama Kenji Ono Shu Takagi Yoichiro Matsumoto RIKEN CIPS VCAD System Research Program Functionality Simulation and Information Team 2-1 Hirosawa Wako Saitama 351-0198 Japan The University of Tokyo Department of Mechanical Engineering Tokyo Japan RIKEN Computational Science Research Program Integrated Simulation of Living Matter Group Organ and Body Scale Team Saitama Japan

The development of the HIFU therapy for the deeply placed cancer such as the liver cancer and brain cancer has been desired. One problem is the displacement of the focal point due to the reflection and refraction of ultrasound. In the present study, the HIFU therapy for the brain cancer through a skull with a bowl-shape array transducer is performed numerically. Our approach is to solve the mass and momentum equations for mixture with the equation of state of media. The nonlinearity is mainly taken into account through the equation of state of the media. The three-dimensional controllability of the focal point by the array transducer with a phase delay is examined. As the result of the ultrasound propagation through the skull with the phase delay, we obtain a clear focal point where the peak pressure is higher than that without the phase delay. Therefore, the array transducer with the appropriate phase delay enables to assign the focal point to the target adequately, even if the ultrasound propagates through the inhomogeneous medium as a human skull.

关键词： Theraputic ultrasound HIFU Numerical simulation Voxel phantom Array transducer

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Microengineered platforms for characterizing the contractile function of in vitro cardiac models

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Microsystems & Nanoengineering 2022年第1期8卷 29-50页

作者： Wenkun Dou Manpreet Malhi Qili Zhao Li Wang Zongjie Huang Junhui Law Na Liu Craig A.Simmons Jason T.Maynes Yu Sun Department of Mechanical and Industrial Engineering University of TorontoTorontoON M5S 3G8Canada Program in Molecular Medicine The Hospital for Sick ChildrenTorontoON M5G 1X8Canada Department of Biochemistry University of TorontoTorontoON M5S 1A8Canada Institute of Robotics and Automatic Information System and the Tianjin Key Laboratory of Intelligent Robotics Nankai UniversityTianjin 300350China School of Mechanical&Automotive Engineering Qilu University of Technology(Shandong Academy of Sciences)Jinan 250353China School of Mechatronics Engineering and Automation Shanghai UniversityShanghai 200444China Institute of Biomedical Engineering University of TorontoTorontoON M5S 3G9Canada Translational Biology&Engineering Program Ted Rogers Centre for Heart ResearchTorontoON M5G 1M1Canada Department of Anesthesiology and Pain Medicine University of TorontoTorontoON M5S 1A8Canada Department of Anesthesia and Pain Medicine The Hospital for Sick ChildrenTorontoON M5G 1X8Canada Department of Electrical and Computer Engineering University of TorontoTorontoON M5S 3G4Canada Department of Computer Science University of TorontoTorontoON M5T 3A1Canada

Emerging heart-on-a-chip platforms are promising approaches to establish cardiac cell/tissue models in vitro for research on cardiac physiology,disease modeling and drug cardiotoxicity as well as for therapeutic *** still exist in obtaining the complete capability of in situ sensing to fully evaluate the complex functional properties of cardiac cell/tissue *** to contractile strength(contractility)and beating regularity(rhythm)are particularly important to generate accurate,predictive *** new platforms and technologies to assess the contractile functions of in vitro cardiac models is essential to provide information on cell/tissue physiologies,drug-induced inotropic responses,and the mechanisms of cardiac *** this review,we discuss recent advances in biosensing platforms for the measurement of contractile functions of in vitro cardiac models,including single cardiomyocytes,2D monolayers of cardiomyocytes,and 3D cardiac *** characteristics and performance of current platforms are reviewed in terms of sensing principles,measured parameters,performance,cell sources,cell/tissue model configurations,advantages,and *** addition,we highlight applications of these platforms and relevant discoveries in fundamental investigations,drug testing,and disease ***,challenges and future outlooks of heart-on-a-chip platforms for in vitro measurement of cardiac functional properties are discussed.

关键词： cardiac contractile regularity

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Loading Dependent Electrical Properties of Hybrid Perovskite Composite Media

Loading Dependent Electrical Properties of Hybrid Perovskite...

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MRS Advances

作者： Murphy, John P. Andriolo, Jessica M. Sutton, Nathan J. Wyss, Gary Skinner, Jack L. Montana Tech Nanotechology Laboratory 1300 W. Park Street ButteMT59701 United States Materials Science PhD Program Montana State University System United States Individual Interdisiplinary PhD Program University of Montana 32 Campus Drive MissoulaMT59812 United States Mechanical Engineering Department Montana Tech 1300 W. Park Street ButteMT59701 United States Center for Advanced Mineral and Metallurgical Processing Montana Tech ButteMT59701 United States

Hybrid organic-inorganic perovskites (HOIPs) have been previously compounded with hydrophobic polymers in order to improve the resilience of HOIPs in humid environments. In this study HOIP particles were synthesized and dispersed into a polymer solution. The weight loading of the HOIP phase in the composite was increased until an abrupt change in the electrical conduction was observed indicating a percolation threshold was approached. Additionally, the CH3NH3PbI3/ polystyrene composite media was characterized to assess morphology and the effect it has on the observed electrical properties. Copyright © Materials Research Society 2017.

关键词： Perovskite

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