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Cell Nanomechanics Based on Dielectric Elastomer Actuator Device

Nano-Micro Letters 2019年第4期11卷 690-708页

作者： Zhichao Li Chao Gao Sisi Fan Jiang Zou Guoying Gu Mingdong Dong Jie Song Institute of Nano Biomedicine and Engineering Department of Instrument Science and EngineeringSchool of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240People’s Republic of China Shanghai Engineering Research Center of Advanced Dental Technology and Materials Shanghai Ninth People’s HospitalShanghai Jiao Tong UniversityShanghai 200240People’s Republic of China Robotics Institute School of Mechanical EngineeringShanghai Jiao Tong UniversityShanghai 200240People’s Republic of China State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong UniversityShanghai 200240People’s Republic of China Interdisciplinary Nanoscience Center(iNANO) Aarhus UniversityAarhus 8000Denmark

As a frontier of biology,mechanobiology plays an important role in tissue and biomedical *** is a common sense that mechanical cues under extracellular microenvironment affect a lot in regulating the behaviors of cells such as proliferation and gene expression,*** such an interdisciplinary field,engineering methods like the pneumatic and motor-driven devices have been employed for ***,such techniques usually rely on complex structures,which cost much but not so easy to *** elastomer actuators(DEAs)are well known as a kind of soft actuation technology,and their research prospect in biomechanical field is gradually concerned due to their properties just like large deformation(>100%)and fast response(<1 ms).In addition,DEAs are usually optically transparent and can be fabricated into small volume,which make them easy to cooperate with regular microscope to realize real-time dynamic imaging of *** paper first reviews the basic components,principle,and evaluation of DEAs and then overview some corresponding applications of DEAs for cellular mechanobiology *** also provide a comparison between DEA-based bioreactors and current custom-built devices and share some opinions about their potential applications in the future according to widely reported results via other methods.

关键词： Dielectric elastomer actuator Mechanical stimulus Bioreactor Mechanobiology

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An overview of graphite utilization in magnetorheological materials

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AIP Conference Proceedings 2024年第1期3124卷

作者： Nur Alyaa Mohd Nasir Nurhazimah Nazmi Nur Azmah Nordin Saiful Amri Mazlan Mohd Azizi Abdul Rahman Engineering Materials and Structures (eMast) iKohza Malaysia-Japan International Institute of Technology (MJIIT) Universiti Teknologi Malaysia Jalan Sultan Yahya Petra 54100 Kuala Lumpur Malaysia Pattern Recognition & Robotics Automation (PRA) ikohza Malaysia-Japan International Institute of Technology (MJIIT) Universiti Teknologi Malaysia 54100 Kuala Lumpur Malaysia Advanced Vehicle System Research Group Malaysia-Japan International Institute of Technology (MJIIT) Universiti Teknologi Malaysia Jalan Sultan Yahya Petra 54100 Kuala Lumpur Malaysia

Studies on smart materials called Magnetorheological (MR) materials has attracted interest from numerous researchers due to its properties that can be manipulated through applications of magnetic fields. Owing to its wide potential application in various field, improvement on its properties in terms of rheology, tribology, thermal stability as well as electrical conductivity need to be optimized for a material to be possibly applied in real applications. Graphite on other hand is a carbon-allotrope that has been utilized in MR materials which acts as a filler or additives and was reported to significantly improves the distinct properties in different types of MR materials. Therefore, this paper has summarized and discussed the effect of graphite’s addition on the properties of several types of MR materials especially on its electrical conductivity, thermal stability, tribological as well as rheological properties to provides an insight view of graphite as a future potential additives and filler in MR materials for upcoming research.

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Generation of a Compendium of Transcription Factor Cascades and Identification of Potential Therapeutic Targets using Graph Machine Learning

arXiv

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arXiv 2023年

作者： Sivarajkumar, Sonish Tandale, Pratyush Bhardwaj, Ankit Johnson, Kipp W. Titus, Anoop Glicksberg, Benjamin S. Khader, Shameer Yadav, Kamlesh K. Subramanian, Lakshminarayanan Molecular Robotics Kerala India School of Computing and Information University of Pittsburgh Pennsylvania PA United States Health Informatics & Data Science Georgetown University WashingtonDC United States Department of Computer Science Courant Institute of Mathematical Sciences New York University New YorkNY United States Institute for Next Generation Healthcare Mount Sinai Health System New YorkNY United States Department of Preventive Cardiology DeBakey Heart & Vascular Center Houston Methodist HoustonTX United States Hasso Plattner Institute for Digital Health Icahn School of Medicine at Mount Sinai New YorkNY United States Faculty of Medicine Imperial College London London United Kingdom School of Engineering Medicine Texas A&M University HoustonTX United States Department of Translational Medical Sciences Center for Genomic and Precision Medicine Texas A&M University HoustonTX United States

Transcription factors (TFs) play a vital role in the regulation of gene expression thereby making them critical to many cellular processes. In this study, we used graph machine learning methods to create a compendium of TF cascades using data extracted from the STRING database. A TF cascade is a sequence of TFs that regulate each other, forming a directed path in the TF network. We constructed a knowledge graph of 81,488 unique TF cascades, with the longest cascade consisting of 62 TFs. Our results highlight the complex and intricate nature of TF interactions, where multiple TFs work together to regulate gene expression. We also identified 10 TFs with the highest regulatory influence based on centrality measurements, providing valuable information for researchers interested in studying specific TFs. Furthermore, our pathway enrichment analysis revealed significant enrichment of various pathways and functional categories, including those involved in cancer and other diseases, as well as those involved in development, differentiation, and cell signaling. The enriched pathways identified in this study may have potential as targets for therapeutic intervention in diseases associated with dysregulation of transcription factors. We have released the dataset, knowledge graph, and graphML methods for the TF cascades, and created a website to display the results, which can be accessed by researchers interested in using this dataset. Our study provides a valuable resource for understanding the complex network of interactions between TFs and their regulatory roles in cellular processes. Copyright © 2023, The Authors. All rights reserved.

关键词： Transcription factors

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Mechanics of soft-body rolling motion without external torque

arXiv

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arXiv 2024年

作者： Liang, Xudong Ding, Yimiao Yuan, Zihao Jiang, Junqi Xie, Zongling Fei, Peng Sun, Yixuan Gu, Guoying Zhong, Zheng Chen, Feifei Si, Guangwei Gong, Zhefeng School of Science Harbin Institute of Technology Shenzhen518055 China Department of Neurology The Fourth Hospital and School of Brain Science and Brain Medicine Zhejiang University School of Medicine Hangzhou310058 China Liangzhu Laboratory MOE Frontier Science Center for Brain Science and Brain-Machine Integration State Key Laboratory of Brain-Machine Intelligence Zhejiang University 1369 West Wenyi Road Hangzhou311121 China NHC and CAMS Key Laboratory of Medical Neurobiology Zhejiang University Hangzhou310058 China State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai200240 China Robotics Institute School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China State Key Laboratory of Brain and Cognitive Science Institute of Biophysics Chinese Academy of Sciences 15 Datun Road Beijing100101 China University of Chinese Academy of Sciences 19A Yuquan Road Beijing100049 China Huazhong University of Science and Technology Optical and Electronic Information Wuhan430074 China Zhejiang Lab. Hangzhou311121 China

The Drosophila larva, a soft-body animal, can bend its body and roll efficiently to escape danger. However, contrary to common belief, this rolling motion is not driven by the imbalance of gravity and ground reaction forces. Through functional imaging and ablation experiments, we demonstrate that the sequential actuation of axial muscles within an appropriate range of angles is critical for generating rolling. We model the interplay between muscle contraction, hydrostatic skeleton deformation, and body-environment interactions, and systematically explain how sequential muscle actuation generates the rolling motion. Additionally, we constructed a pneumatic soft robot to mimic the larval rolling strategy, successfully validating our model. This mechanics model of soft-body rolling motion not only advances the study of related neural circuits, but also holds potential for applications in soft robotics. © 2024, CC BY.

关键词： Pneumatics

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Care Guide system for Caregivers of People with Dementia*

Care Guide System for Caregivers of People with Dementia*

引用

Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Gyungha Kim Hwawoo Jeon Sungkee Park Yong Suk Choi Yoonseob Lim Research Center for Diagnosis Treatment and Care System of Dementia Korea Institute of Science and Technology Seoul South Korea Research Center for Diagnosis Treatment and Care System of Dementia and the Center for Robotics Research Korea Institute of Science and Technology Seoul South Korea division of computer science and engineering Hanyang University Haengdang-dong Seondong-gu Seoul South Korea

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

In this paper, we introduce a care guide system for caregivers of People with Dementia (PwD) at home or care facility. The system is composed of context data manager, ontological model of caring PwD, and reasoning system that adaptively generates care guides in various circumstances. Caregivers can utilize the proposed system by managing care knowledge through graphical user interface or inquire a care guide through smartphone application for text-based chatting. Knowledge models implemented in the proposed system were evaluated by the experts in caring people with dementia.

关键词： Task analysis Dementia Graphical user interfaces Ontologies Cognition Electronic mail Knowledge management

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Optimal reaction control for the flexible base redundant manipulator system

Optimal reaction control for the flexible base redundant man...

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2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Zhang, Yaowen Liu, Yechao Xie, Zongwu Moallem, Mehrdad Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin Heilongjiang Province150006 China School of Mechatronic Systems Engineering Simon Fraser University VancouverBCV3T 0A3 Canada

ISBN: (纸本)9781728163215

The null space of the Jacobian for the redundant manipulators can be utilized to reach dual control goals and optimal effects. For the flexible base redundant manipulator system, the reaction force from the motion of the manipulator should be carefully handled while the end effector is tracking a desired trajectory. Different optimal goals are discussed, including the minimization of base deflection force/torque and base energy dissipation path. Considering the base reaction dynamic, the reaction force/torque is treated as the input of the base and the deflection energy is treated as the output, an integrated optimal goal is built and solved based on the LQR control to get an optimal feedback for the closed-loop dynamics. We discuss the different optimal goals and implement trough the redefined acceleration. We test the different control laws on the three- link manipulators which mounted on a three-DoF flexible base. Simulation results demonstrate that optimal goal in LQR form can be advantageous in terms of flexible base manipulator. © 2019 IEEE.

关键词： Redundant manipulators

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Design and Evaluation of a Workload-Adaptive Haptic Shared Control Framework for Semi-Autonomous Driving

Design and Evaluation of a Workload-Adaptive Haptic Shared C...

引用

American Control Conference

作者： Yifan Weng Ruikun Luo Paramsothy Jayakumar Mark J. Brudnak Victor Paul Vishnu R. Desaraju Jeffrey L. Stein X. Jessie Yang Tulga Ersal Department of Mechanical Engineering University of Michigan Ann Arbor MI Robotics Institute University of Michigan Ann Arbor MI U.S. Army Ground Vehicles System Center Warren MI Toyota Research Institute Ann Arbor MI Department of Industrial and Operations Engineering University of Michigan Ann Arbor MI

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

Haptic shared control of an autonomy-enabled vehicle is used to manage the control authority allocation between a human and autonomy smoothly. Existing haptic shared control schemes, however, do not take the workload condition of human into account. To fill this research gap, this study develops a novel haptic shared control scheme that adapts to a human operator's workload in a semi-autonomous driving scenario. Human-in-the-loop experiments with 8 participants are reported to evaluate the new scheme. In the experiment, a human operator and an autonomous navigation module shared the steering control of a simulated teleoperated vehicle in a path tracking task while the speed of the vehicle is controlled by autonomy. High and low screen refresh rates were used to create moderate and high workload cases, respectively. Results indicate that adaptive haptic control leads to less driver control effort without sacrificing the path tracking performance when compared with the non-adaptive case.

关键词： Vehicle speed steering control Human vehicle Standing Orders Workload tracking Autonomy driver control

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Comparative study on the machine learning-based techniques for magnetorheological elastomer dynamic properties prediction

引用

AIP Conference Proceedings 2024年第1期3124卷

作者： Kasma Diana Saharuddin Mohd Hatta Mohammed Ariff Irfan Bahiuddin Saiful Amri Mazlan Nurhazimah Nazmi Ubaidillah Ubaidillah Advanced Vehicle System (AVS) Research Group Malaysia Japan International Institute of Technology (MJIIT) Universiti Teknologi Malaysia 54100 Kuala Lumpur Malaysia Department of Mechanical Engineering Vocational College Universitas Gadjah Mada Yogyakarta Indonesia Engineering Materials & Structures (eMast) ikohza Malaysia Japan International Institute of Technology (MJIIT) Universiti Teknologi Malaysia 54100 Kuala Lumpur Malaysia Pattern Recognition and Robotics Automation iKohza Malaysia Japan International Institute of Technology (MJIIT) Universiti Teknologi Malaysia 54100 Kuala Lumpur Malaysia Mechanical Engineering Department Faculty of Engineering Universitas Sebelas Maret JI. Ir. Sutami 36A Kentingan Surakarta 57126 Indonesia

Magnetorheological elastomers (MRE) have gained popularity due to their ability to control viscoelastic properties by varying the strength of the magnetic field. Due to the obvious nonlinear and complex behavior of MRE, machine learning approaches were used to predict the MRE viscoelastic properties, which are storage and loss modulus. In comparison to the traditional viscoelastic model, which is complex in mathematical derivation, machine learning method easily identifies trends and patterns by mapping the input-output relationship. It can also handle nonlinear problems by training on data. Support vector regression (SVR), Gaussian process regression (GPR), Backpropagation neural network (BP-ANN), and Extreme learning machine (ELM) were introduced and compared to simulate the field-dependent viscoelastic behavior of MRE with frequency and magnetic field strength as model input. As a result, the ELM model produced the highest accuracy, with more than 98 percent accuracy on model generalization capability. Therefore, this demonstrates that machine learning can replace traditional modelling approaches and serve as a basis for material and device development.

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SANTIA: a Matlab-based open-source toolbox for artifact detection and removal from extracellular neuronal signals

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Brain Informatics 2021年第1期8卷 1-19页

作者： Fabietti, Marcos Mahmud, Mufti Lotfi, Ahmad Kaiser, M. Shamim Averna, Alberto Guggenmos, David J. Nudo, Randolph J. Chiappalone, Michela Chen, Jianhui Department of Computer Science Nottingham Trent University Clifton Lane NottinghamNG11 8NS United Kingdom Medical Technologies Innovation Facility Nottingham Trent University Clifton Lane NottinghamNG11 8NS United Kingdom Computing and Informatics Research Centre Nottingham Trent University Clifton Lane NottinghamNG11 8NS United Kingdom Institute of Information Technology Jahangirnagar University Savar Dhaka1342 Bangladesh Department of Health Sciences University of Milan Via di Rudinì 8 Milan20142 Italy Department of Physical Medicine and Rehabilitation University of Kansas Medical Center 3901 Rainbow Blvd Kansas City66160 United States Department of informatics Bioengineering Robotics and System Engineering-DIBRIS University of Genova Via All’Opera Pia 13 Genoa16145 Italy Faculty of Information Technology International WIC Institute Beijing University of Technology Beijing100124 China Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing100124 China

Neuronal signals generally represent activation of the neuronal networks and give insights into brain functionalities. They are considered as fingerprints of actions and their processing across different structures of the brain. These recordings generate a large volume of data that are susceptible to noise and artifacts. Therefore, the review of these data to ensure high quality by automatically detecting and removing the artifacts is imperative. Toward this aim, this work proposes a custom-developed automatic artifact removal toolbox named, SANTIA (SigMate Advanced: a Novel Tool for Identification of Artifacts in Neuronal Signals). Developed in Matlab, SANTIA is an open-source toolbox that applies neural network-based machine learning techniques to label and train models to detect artifacts from the invasive neuronal signals known as local field potentials. © 2021, The Author(s).

关键词： Neural networks

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Toward Hazard Reduction of Road Vehicle after Tire Blowout: A Driver Steering Assist Control Strategy

Toward Hazard Reduction of Road Vehicle after Tire Blowout: ...

引用

第三十八届中国控制会议

作者： Lu Yang Ming Yue Hongzhi Zhang Gang Xu School of Automotive Engineering Dalian University of Technology State Key Laboratory of Robotics and System Harbin Institute of Technology

Tire blowout or failure of road vehicle on the expressway has greatly threaten the safety of the passengers and host vehicle as well as surrounding vehicles, and existing studies show that driver improper intervention after tire blowout is one of the principal causes that induce the serious traffic accidents. To such issue, this paper develops a hazard reduction oriented driver steering assist control strategy for road vehicle after tire blowout by introducing a hierarchical closed-loop control architecture for timely assisting driver. Within this strategy, a model predictive control based path tracking controller and an optimal preview acceleration driver model are separately developed for enhancing vehicle lateral stability after tire blowout based upon feedback vehicle attitude information in upper-level. As well, the parameterized driver activity is formulated considering his/her driving action and driving state, upon which a assist determination coefficient is further designed for adaptively allocating intervention level of assist controller. In lower-level, supported by reported burst tire mechanical characteristic and B-class vehicle model sourced from CarSim, a Simulink-CarSim co-simulation platform is constructed, in which tire vertical force redistributions after tire blowout are explicitly considered. In the end, simulations performed on the developed platform validate the effectiveness and efficiency of the assist steering control strategy and methods in improving directional stability and lateral dynamics performance of the vehicle after tire blowout.

关键词： Assist intervention level Co-simulation platform Driver steering assist control Tire blowout

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