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Soft,full Wheatstone bridge 3D pressure sensors for cardiovascular monitoring

npj Flexible Electronics 2024年第1期8卷 910-917页

作者： Yoonseok Park Haiwen Luan Kyeongha Kwon Ted S.Chung Seyong Oh Jae-Young Yoo Gooyoon Chung Junha Kim Suhyeon Kim Sung Soo Kwak Junhwan Choi Hoang-Phuong Phan Seonggwang Yoo Hyoyoung Jeong Jaeho Shin Sang Min Won Hong-Joon Yoon Yei Hwan Jung John A.Rogers Department of Advanced Materials Engineering for Information and Electronics Integrated Education Institute for Frontier Science&Technology(BK21 Four)Kyung Hee UniversityYongin-siGyeonggi-do 17104Republic of Korea Department of Mechanical and Aerospace Engineering University of California San DiegoLa JollaCA 92093USA School of Electrical Engineering Korea Advanced Institute of Science and TechnologyDaejeonRepublic of Korea Department of Mechanical Engineering Columbia UniversityNew YorkNYUSA Division of Electrical Engineering Hanyang University ERICAAnsan 15588Republic of Korea Department of Semiconductor Convergence Engineering Sungkyunkwan UniversitySuwonRepublic of Korea Biomedical Research Division Korea Institute of Science and TechnologySeoul 02792Republic of Korea Department of Chemical Engineering Dankook UniversityYonginGyeonggi-do 16890Republic of Korea School of Mechanical and Manufacturing Engineering Tyree Institute of Health EngineeringUniversity of New South WalesSydneyNSW 2052Australia Querrey Simpson Institute for Bioelectronics Northwestern University EvanstonEvanstonIL 60208USA Department of Electrical and Computer Engineering University of California DavisDavisCA 95616USA Department of Electrical and Computer Engineering Sungkyunkwan University2066Seobu-roJangan-guSuwon-siGyeonggi-do 16419Republic of Korea Department of Electronic Engineering Gachon UniversitySeongnamsiGyeonggi-do 13120Republic of Korea Department of Electronic Engineering Hanyang UniversitySeoulRepublic of Korea Department of Materials Science and Engineering Biomedical EngineeringNeurological SurgeryChemistryMechanical EngineeringElectrical Engineering and Computer Science Simpson Querrey Institute and Feinberg Medical SchoolCenter for Bio-Integrated ElectronicsNorthwestern University EvanstonEvanstonIL 60208USA

Variations in parameters associated with the ambient environment can introduce noise in soft,body-worn *** example,many piezoresistive pressure sensors exhibit a high degree of sensitivity to fluctuations in temperature,thereby requiring active compensation *** research presented here addresses this challenge with a multilayered 3D microsystem design that integrates four piezoresistive sensors in a full-Wheatstone bridge *** optimized layout of the sensors relative to the neutral mechanical plane leads to both an insensitivity to temperature and an increased sensitivity to pressure,relative to previously reported devices that rely on similar operating *** this 3D pressure sensor into a soft,flexible electronics platform yields a system capable of real-time,wireless measurements from the surface of the *** above the radial and carotid arteries yields high-quality waveforms associated with pulsatile blood flow,with quantitative correlations to blood *** results establish the materials and engineering aspects of a technology with broad potential in remote health monitoring.

关键词： Wheat bridge thereby

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Thermo-mechanical energy storage technologies:Innovations,challenges and future directions

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能源前沿（英文） 2025年第2期19卷 115-116页

作者： Yao Zhao Mingjia Li Kai Wang Adriano Sciacovelli Chris Qin Steven Lecompte André D.Thess College of Smart Energy Shanghai Jiao Tong UniversityShanghai 200240China Shanghai Non-carbon Energy Conversion and Utilization Institute Shanghai Jiao Tong UniversityShanghai 200240China School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China Institute of Refrigeration and Cryogenics Zhejiang UniversityHangzhou 310027China Key Laboratory of Refrigeration and Cryogenic Technology of Zhejiang Province Zhejiang UniversityHangzhou 310027China Department of Civil and Mechanical Engineering Technical University of DenmarkKongens Lyngby 2800Denmark School of Engineering and Computer Science Washington State UniversityVancouverWA 98686USA Department of Electromechanical Systems and Metal EngineeringGhent UniversityGhent 9000Belgium Institute of Engineering Thermodynamics German Aerospace Center(DLR)Stuttgart 70569Germany University of Stuttgart Stuttgart 70569Germany

Thermo-mechanical energy storage(TMES)technologies are increasingly recognized as essential solutions for enhancing the efficiency and stability of energy systems,particularly in the integration of renewable energy *** technologies leverage the conversion between thermal,electrical and mechanical energy to store and release energy,providing an effective tool to address the intermittency and variability of renewable sources such as wind and *** editorial explores the fundamental principles,innovations,challenges,and future research directions of TMES technologies,with a focus on developments in compressed-air energy storage(CAES),liquid-air energy storage(LAES),Carnot battery/pumped-thermal energy storage(PTES),and carbon dioxide energy storage(CDES).

关键词： technologies future storage energy challenges directions innovations mechanical thermo

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Bacterial population dynamics and biosafety assessment in a closed Bioregenerative Life Support System during the “Lunar Palace 365” experiment

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science China Life sciences 2025年第7期68卷 2137-2149页

作者： Yuming Fu Yueying Lu Jianlou Yang Hong Liu Key Laboratory of Biomechanics and Mechanobiology (Beihang University) Ministry of Education Key Laboratory of Innovation and Transformation of Advanced Medical Devices Ministry of Industry and Information Technology National Medical Innovation Platform for Industry-Education Integration in Advanced Medical Devices (Inte rdiscipline of Medicine and Engineering) School of Biological Science and Medical Engineering Beihang University State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University International Joint Research Center of Aerospace Biotechnology & Medical Engineering Beihang University School of Sport Management Shan Dong Sport University Innovation Center for Medical Engineering & Engineering Medicine Hangzhou International Innovation Institute Beihang University

Our study investigates the dynamic variation of bacterial populations within the Bioregenerative Life Support System(BLSS), a critical component for sustainable habitats in extraterrestrial environments supporting human survival. We utilized the ground-based BLSS test platform, referred to as “Lunar Palace 1”(LP1), to examine bacterial dynamics in an ecosystem integrating plant production, human cultivation, and equipment maintenance. Our findings reveal distinct bacterial compositions among crew members and functional areas within the LP1 system while preserving temporal stability across the 370-day experiment. Importantly, we observed a low abundance of potential pathogens, minimal antibiotic resistance, and negligible impact of the isolated bacterial strains on equipment materials, suggesting favorable biosafety attributed to plant integration. Our work enhances the understanding of microbial communities in BLSS and underscores the importance of incorporating green plants to bolster environmental biosafety and sustainability in long-term space exploration missions.

关键词： bacterial community dynamics Bioregenerative Life Support System biosafety antibiotic resistance genes biodegradation

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Sequence-based Segmentation and Non-Temporal Visualizations for Pilot Performance Assessment

Sequence-based Segmentation and Non-Temporal Visualizations ...

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AIAA science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Sheets, David A. Amiruzzaman, Md Blake Stringer, D. Strzempkowski, Brian Zhao, Ye Department of Computer Science Kent State University 800 E Summit St KentOH44242 United States Department of Computer Science West Chester University 25 University Avenue # 150 West ChesterPA19383 United States Center for Aviation Studies Department of Mechanical & Aerospace Engineering The Ohio State University 228B Bolz Hall 2036 Neil Avenue ColumbusOH43210 United States Center for Aviation Studies College of Engineering College of Education & Human Ecology The Ohio State University 228 Bolz Hall ColumbusOH43210 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

Pilot shortages are predicted to increase over the next decades, resulting in a need to increase the number of qualified pilots. A challenge in meeting this need is maintaining the quality of the training while increasing the throughput. Data-driven approaches, supported by visual analytics techniques, offer a means to meet this challenge and possibly reduce training time and/or improve quality. In this study, we examine the Airman Certification Standards (ACS) and Federal Aviation Administration (FAA) performance maneuvers relevant to initial pilot training. Decomposition methods are applied to the maneuver to establish analyzable components and remove time-related variability. This representation supports a general comparability of maneuver instances, allowing quantification of pilot improvements as well as more direct comparability to gold standards. The decomposition also increases relevance for instructional feedback against individual segments reflecting pilot considerations during the maneuver. Visualizations are applied to further facilitate student-instructor discussion and actionable student feedback. A volume of actual training data is analyzed and explored through user evaluation with aviation experts and students to validate technique applicability. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Students

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Approximating to the Real Translation Quality for Neural Machine Translation via Causal Motivated Methods

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ACM Transactions on Asian and Low-Resource Language Information Processing 2023年第5期22卷 1-26页

作者： Xuewen Shi Heyan Huang Ping Jian Yi-Kun Tang School of Computer Science and Technology Beijing Institute of Technology Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Haidian District Beijing China

It is hard to evaluate translations objectively and accurately, which limits the applications of machine translation. In this article, we assume that the above phenomenon is caused by noise interference during translation evaluation, and we handle the problem through a perspective of causal inference. We assume that the observable translation score is affected by the unobservable true translation quality and some noise simultaneously. If there is a variable that is related to the noise and independent to the true translation quality, the related noise can be eliminated by removing the effect of that variable from the observed score. Based on the above causality hypothesis, this article studies the length bias problem of beam search for neural machine translation (NMT) and the input related noise problem of translation quality estimation (QE). For the NMT length bias problem, we conduct the experiments on four typical NMT tasks (Uyghur–Chinese, Chinese–English, English–German, and English–French) with different scales of datasets. Comparing with previous approaches, the proposed causal motivated method is model-agnostic and does not require supervised training. For QE tasks, we conduct the experiments on the WMT’20 submissions. Experimental results show that the denoised QE results gain better Pearson’s correlation scores with human assessed scores compared to the original submissions. Further analyses on the NMT and QE tasks also demonstrate the rationality of the empirical assumptions made on our methods.

关键词： Neural machine translation causal inference half-sibling regression quality estimation

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An Open-source Hardware/Software Architecture and Supporting Simulation Environment to Perform Human FPV Flight Demonstrations for Unmanned Aerial Vehicle Autonomy

arXiv

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arXiv 2024年

作者： Xiao, Haosong Krisshnakumar, Prajit Pothuri, Jagadeswara P.K.V. Soni, Puru Butcher, Eric Chowdhury, Souma Mechanical and Aerospace Engineering University at Buffalo BuffaloNY United States Mechanical and Aerospace Engineering University at Buffalo BuffaloNY United States Computer Science and Engineering. University at Buffalo BuffaloNY United States Mechanical and Aerospace Engineering Center for Embodied Autonomy and Robotics University at Buffalo United States

Small multi-rotor unmanned aerial vehicles (UAVs), mainly quadcopters, are nowadays ubiquitous in research on aerial autonomy, including serving as scaled-down models for much larger aircraft such as vertical-take-off-and-lift vehicles for urban air mobility. Among the various research use cases, first-person-view (FPV) RC flight experiments allow for collecting data on how human pilots fly such aircraft, which could then be used to compare, contrast, validate, or train (via imitative learning) autonomous flight agents. While this could be uniquely beneficial, especially for studying UAV operation in contextually complex and safety-critical environments such as in human-UAV shared spaces, the lack of inexpensive and open-source hardware/software platforms that offer this capability along with low-level (complete access) to the underlying control software and data remains limited. To address this gap and significantly reduce barriers to human-guided autonomy research with UAVs, this paper presents an open-source software architecture implemented with an inexpensive in-house built quadcopter platform based on the F450 Quadcopter Frame. This setup uses two cameras to provide a dual-view FPV and an open-source flight controller, Pixhawk. The underlying software architecture, developed using the Python-based Kivy library, allows logging telemetry, GPS, control inputs, and camera frame data in a synchronized manner on the ground station computer. Since costs (time) and weather constraints typically limit numbers of physical outdoor flight experiments, this paper also presents a unique AirSim/Unreal Engine based simulation environment and graphical user interface (GUI) – aka digital twin – that provides a Hardware In The Loop (HITL) setup via the Pixhawk flight controller. We demonstrate the usability and reliability of the overall framework through a set of diverse physical FPV flight experiments and corresponding flight tests in the digital twin. Copyright © 2024, The Au

关键词： Graphical user interfaces

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Hydrogen and biomethane pathways to achieve sustainable transportation in circular economic concept: A review

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International Journal of Hydrogen Energy 2025年 143卷 403-419页

作者： Saravanakumar, Ayyadurai Sudha, M.R. Chen, Wei-Hsin Pradeshwaran, Vijayakumar Centre for Research in Environment Sustainability Advocacy and Climate Change Directorate of Research and Virtual Education SRM Institute of Science and Technology Chengalpattu Tamil Nadu Kattankulathur603 203 India Department of Computer Applications College of Science and Humanities SRM Institute of Science and Technology Chengalpattu Tamil Nadu Kattankulathur603 203 India Department of Aeronautics and Astronautics National Cheng Kung University Tainan701 Taiwan Research Center for Smart Sustainable Circular Economy Tunghai University Taichung407 Taiwan Department of Mechanical Engineering National Chin-Yi University of Technology Taichung411 Taiwan Department of Chemistry SRM Institute of Science and Technology Chengalpattu Tamil Nadu Kattankulathur603 203 India

Amidst the imperative need to reduce emissions and the rising demand for transportation, the logistics sector is at a crossroads. On a global scale, where road freight plays a significant role in the economy, the search for environmentally friendly fuel alternatives has led to the emergence of biomethane as a potential solution to assist fleets in decarbonizing their operations in the present day. The reliance of the transportation industry on fossil fuels is a cause for concern due to its environmental consequences and the depletion of resources. This study investigates the feasibility of hydrogen and biomethane as an eco-friendly transportation fuel in a circular economy. The analysis focuses on the production method, environmental advantages, and the role of biomethane in closing resource loops. The study examines constraints such as infrastructural development, feedstock availability, and economic viability. The significant findings on hydrogen suggest its strong potential as a sustainable fuel for long-haul heavy vehicles, showing better climate performance even when fossil electricity is used in production. Furthermore, in a circular economy, hydrogen-powered heavy-duty vehicles could become more advantageous than diesel, particularly as diesel faces reduced acceptance due to environmental issues. © 2025 Hydrogen Energy Publications LLC

关键词： Circular economy

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Towards Automatic Characterization of Nano-Energetic Material Response to Directed Energy 13

Towards Automatic Characterization of Nano-Energetic Materia...

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Energy Harvesting and Storage: Materials, Devices, and applications XIII 2023

作者： Gaines, Timothy Boyle, Camden Hurt, J. Alex Maschmann, Matthew R. Keller, James M. Scott, Grant J. Price, Stanton R. Electrical Engineering and Computer Science Department University of Missouri-Columbia ColumbiaMO65211 United States Mechanical and Aerospace Engineering Department University of Missouri-Columbia ColumbiaMO65211 United States U.S. Army Engineer Research and Development Center VicksburgMS39180 United States

ISBN: (数字)9781510661417

ISBN: (纸本)9781510661400

Nanoenergetic materials offer high-density energy storage that may be reacted to produce heat and release gaseous products. However, the fundamental reaction mechanisms of isolated nanoenergetic fuel particles (typically aluminum - AL) remain poorly understood. In this study, the structure-property relationships of photothermally heated AL nanoparticles are explored using an optical microscope setup and laser-based photothermal heating. Our research explores optical imaging and computer vision techniques to measure distinctive features from images captured before and after directed energy excitation of nanoenergetic particles. These features are used to describe the reactions in the pursuit of creating an automated nanoenergetic material reaction characterization model. Specifically, optical imagery of nano-aluminum particle clusters is taken before and after the reaction is initiated via laser irradiation. Through image preprocessing and registration, we remove untargeted nanoparticle clusters and align the images. We then classify particle reactions into three classes, Spallation, Sintering, or a Combination of both, through an examination of various features derived from our preprocessed imagery. These techniques serve as tools to aid researchers in quantitatively measuring reaction properties, such as loss of mass, and accelerating the search for optimized reaction parameters. © 2023 SPIE.

关键词： Sintering

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Industry 4.0 based Machine Learning Models for Anomalous Product Detection and Classification

Industry 4.0 based Machine Learning Models for Anomalous Pro...

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Emerging Trends in Industry 4.0 (ETI 4.0)

作者： Sourabh Kumar Saroj Kumar Chandra Ram Narayan Shukla Lipismita Panigrahi Center of Excellence in Industry 4.0 Computer Science and Engineering OP Jindal University Raigarh India Department of Computer Applications Kalinga Institute of Industrial Technology Bhubaneswar India

Automation has made tremendous changes in the industries. It has been used to automate the manual processes involved in different physical units of the industries. The purpose was to increase the production in the manufacturing. Now, computers are being used in the industries to monitor functionalities of different production units with the help of artificial intelligence and internet of things (IoT). The IoT has revolutionized the industries. It is an interconnected network system of physical units. The core purpose of it to gather and share information among different physical units. The IoT has great impact on the many areas such as business, industry, medicine, the economy, transport, industrial robots and automation systems. IoT with artificial intelligence has wide range of industrial applications. Industry 4.0 is used in the industries where different industrial units are connected over the internet and interacting to make decisions via machine-to-machine communication. It has increased the benefits of industries in terms of production and supply chain management. Manufacturing industry monitors its production units in every 10 milliseconds to capture features of the product that is being produced. The features generated in this process are huge in amount. Critical observation is performed on the generated features to categorize the product as anomalous or good. Product classification is difficult task in the labeled datasets due to human bias in labeling the final product as anomalous or good. In this work, machine learning models is being used to detect and classify faulty product produced by manufacturing industry. Both qualitative and quantitative study will be carried out to compare various machine learning models.

关键词： Manufacturing industries Biological system modeling Production Fourth Industrial Revolution Decision trees Biomedical monitoring Task analysis

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Projecting infinite time series graphs to finite marginal graphs using number theory

arXiv

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arXiv 2023年

作者： Gerhardus, Andreas Wahl, Jonas Faltenbacher, Sofia Ninad, Urmi Runge, Jakob German Aerospace Center Institute of Data Science Germany Technische Universität Berlin Institute of Computer Engineering and Microelectronics Germany

In recent years, a growing number of method and application works have adapted and applied the causal-graphical-model framework to time series data. Many of these works employ time-resolved causal graphs that extend infinitely into the past and future and whose edges are repetitive in time, thereby reflecting the assumption of stationary causal relationships. However, most results and algorithms from the causal-graphical-model framework are not designed for infinite graphs. In this work, we develop a method for projecting infinite time series graphs with repetitive edges to marginal graphical models on a finite time window. These finite marginal graphs provide the answers to m-separation queries with respect to the infinite graph, a task that was previously unresolved. Moreover, we argue that these marginal graphs are useful for causal discovery and causal effect estimation in time series, effectively enabling to apply results developed for finite graphs to the infinite graphs. The projection procedure relies on finding common ancestors in the to-be-projected graph and is, by itself, not new. However, the projection procedure has not yet been algorithmically implemented for time series graphs since in these infinite graphs there can be infinite sets of paths that might give rise to common ancestors. We solve the search over these possibly infinite sets of paths by an intriguing combination of path-finding techniques for finite directed graphs and solution theory for linear Diophantine equations. By providing an algorithm that carries out the projection, our paper makes an important step towards a theoretically-grounded and method-agnostic generalization of a range of causal inference methods and results to time series. Copyright © 2023, The Authors. All rights reserved.

关键词： Time series

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