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

作者： Loreto Rojas Sandoval René Araya Ulloa Ana Karoline Almeida Da Silva Gustavo Adolfo Marcelino de Almeida Nunes Rafael Mendes Faria José Parra Sepúlveda Lindemberg Barreto Mota Da Costa Luca Rubilar Acevedo Mário Fabrício Fleury Rosa Esteban J. Pino Suélia de Siqueira Rodrigues Fleury Rosa Electrical Engineering Department Universidad de Concepción Chile Mechanical Engineering Department University of Brasilia Brasilia Brazil Postgraduate Program in Biomedical Engineering University of Brasilia Brasilia Brazil

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Coronary artery stenosis is characterized by the obstruction or narrowing of coronary arteries, impairing blood flow to the cardiac muscle. Cardiovascular diseases rank among the leading global causes of death. Understanding the mechanisms, risk factors, and impacts of coronary artery stenosis (CAD) is essential for developing effective strategies for prevention, early diagnosis, and treatment, aiming to enhance cardiovascular health and reduce adverse consequences associated with this condition. Previous studies explore the potential of acoustic devices in non-invasive CAD detection through the analysis of cardiac sounds. A theoretical model utilized a cardiac microphone and signal processing to generate sounds in partially obstructed coronary arteries. Emphasizing the model’s sensitivity to geometric and dynamic parameters, this article integrates Bond Graph (BG) models into the analog sound circuit, aiming to develop a dynamic representation of biological processes in complex systems like coronary arteries. This research seeks to construct a comprehensive mathematical model using a state-space approach to enhance understanding, diagnostics, and interventions in cardiovascular conditions. The utilization of BG demonstrated notable similarity to the pathology of the disease, providing an accurate representation of its effects. The model’s sensitivity to geometric and dynamic parameters allowed an in-depth understanding of the specific physiological characteristics of the disease, highlighting its ability to reproduce patterns observed in patients with CAD.

关键词： Solid modeling Analytical models Pathology Sensitivity Biological system modeling Prevention and mitigation Signal processing Predictive models Mathematical models Arteries

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Accurate prediction of oxygen vacancy concentration with disordered A-site cations in high-entropy perovskite oxides

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npj Computational Materials 2023年第1期9卷 2053-2065页

作者： Jiyun Park Boyuan Xu Jie Pan Dawei Zhang Stephan Lany Xingbo Liu Jian Luo Yue Qi School of Engineering Brown UniversityProvidenceRI 02912USA Department of Physics Brown UniversityProvidenceRI 02912USA Department of Chemical Engineering and Materials Science Michigan State UniversityEast LansingMI 48824USA Program of Materials Science and Engineering University of California San DiegoLa JollaCA 92093USA Materials Science Center National Renewable Energy LaboratoryGoldenCO 80401USA Department of Mechanical and Aerospace Engineering Benjamin M.Statler College of Engineering and Mineral ResourcesWest Virginia UniversityMorgantownWV 26506USA Department of NanoEngineering University of California San DiegoLa JollaCA 92093USA

Entropic stabilized ABO_(3) perovskite oxides promise many applications,including the two-step solar thermochemical hydrogen(STCH)*** binary and quaternary A-site mixed{A}FeO_(3) as a model system,we reveal that as more cation types,especially above four,are mixed on the A-site,the cell lattice becomes more cubic-like but the local Fe–O octahedrons are more *** comparing four different Density Functional Theory-informed statistical models with experiments,we show that the oxygen vacancy formation energies(E^(f)_(V))distribution and the vacancy interactions must be considered to predict the oxygen non-stoichiometry(δ)*** STCH applications,the E^(f)_(V) distribution,including both the average and the spread,can be optimized jointly to improveΔδ(difference ofδbetween the two-step conditions)in some hydrogen production *** model can be used to predict the range of water splitting that can be thermodynamically improved by mixing cations in{A}FeO_(3) perovskites.

关键词： perovskite vacancy oxides

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Device for monitoring the vital functions of athletes using Arduino UNO development board

Device for monitoring the vital functions of athletes using ...

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International Symposium on Applied Machine Intelligence and Informatics (SAMI)

作者： Adriána Špaková Norbert Ferenčík Veronika Sedláková Petra Kolembusová William Steingartner Radovan Hudák Department of Biomedical Engineering Faculty of Mechanical Engineering Technical University of Kosice Kosice Slovakia

This document outlines a proposal for the development of a device dedicated to monitoring the health and physical activity of athletes. The realization of this device leveraged the Arduino UNO microcontroller, and empirical trials have yielded encouraging results. The device was meticulously engineered with the primary objective of scrutinizing vital functions, encompassing heart rate, blood oxygen saturation, body temperature, lung capacity, and electromyography (EMG) for a comprehensive assessment of muscle activity. Furthermore, spirometry has been integrated to quantify lung vital capacity. This endeavor heralds pioneering prospects in the realm of health and fitness surveillance, proffering potential advantages not only to athletes but also to the broader populace.

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Enhancing Agricultural Efficiency and Sustainability Through Smart Direct Couple Motor Operated Valve: A Technological Innovation for Automated Irrigation and Fertilization

SSRN

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SSRN 2024年

作者： Nugraha, Muhamad Hanhan Hanhan Rabbika, Anes Inda Rusdja, Andy Permana Bustomi, Ahmad Mechanical Engineering Study Program Mechanical Engineering Department State Polytechnic of Jakarta Depok16425 Indonesia Manufacturing Engineering Technology Study Program Mechanical Engineering Department State Polytechnic of Jakarta Depok16425 Indonesia Mechanical Engineering Study Program Faculty of Engineering Mayasari Bakti University Tasikmalaya46196 Indonesia

This research introduces the Smart Direct Couple Motor Operated Valve (SDCMOV), designed to enhance agricultural efficiency and sustainability. SDCMOV automates the distribution of water and fertilizers in vegetable farming, reducing labor intensity and inefficiencies. The system addresses key issues such as minimizing musculoskeletal disorders (MSDs) among farmers and ensuring consistent nutrient delivery for optimal plant growth. Energy-efficient, environmentally friendly, and remotely controllable via mobile devices, SDCMOV significantly improves irrigation and fertilization processes. Experimental results suggest that SDCMOV is a viable solution for sustainable and modern agricultural practices, particularly in developing countries. © 2024, The Authors. All rights reserved.

关键词： Irrigation

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EDNCL: An Efficient Deep Learning Approach to Identify Cardiovascular Diseases Based on Enhanced Deep Neural Classifier Logic

EDNCL: An Efficient Deep Learning Approach to Identify Cardi...

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2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2024

作者： Sabarivani, A. Arulmozhiselvan, L. Nirmala, P. Dhanalakshmi, G. Alok, N. Al-Safarini, M.Y. Sathyabama Institute of Science and Technology Department of Biomedical Engineering Chennai India Meenakshi Sundararajan Engineering College Department of Information Technology Chennai India Hindustan College of Arts & Science Department of Microbiology Padur Chennai India Panimalar Engineering College Department of Information Technology Chennai India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India Zarqa University Department of Computer Science Zarqa Jordan University of Business and Technology Jeddah21448 Saudi Arabia

ISBN: (纸本)9798331543617

In light of the detrimental consequences of heart disease on society, there has been a concerted effort to improve its diagnosis and treatment. Data mining and the storage of medical information can enhance patient management opportunities as technology and medical diagnostics become more synergistic. Consequently, it is imperative to investigate the interdependence of the risk factors in patients' medical histories and to understand their respective contributions to the prognosis of cardiac disease. The objective of this research is to conduct an analysis of the numerous components in patient data in order to accurately predict cardiac disease. The proposed model, which is referred to as Enhanced Deep Neural Classifier Logic (EDNCL), has been employed to identify the most critical attributes for the prediction of heart disease. This model is designed to accurately predict cardiovascular disease using deep learning principles. It is necessary to cross-validate the suggested scheme with the more traditional Random Forest Classifier (RFC) learning strategy in order to determine its effectiveness. The efficacy of vision transformer models is contrasted to the state-of-the-art methodology RFC in order to illustrate the framework's contribution. The proposed framework demonstrates notable classification results, as evidenced by the experiment results. The potential of this methodology to accurately detect cardiac disease from acoustic signals is illustrated in this study. These discoveries offer promising prospects for improving patient care and medical diagnosis. © 2024 IEEE.

关键词： Cardiovascular Disease Deep Learning Deep Neural Classifier EDNCL Random Forest Classifier RFC

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Assessment of Changes in Zebrafish Embryo Biomechanical Properties Due to Cold Treatment Using High-Resolution Brillouin Microscopy 12

Assessment of Changes in Zebrafish Embryo Biomechanical Prop...

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Optical Elastography and Tissue Biomechanics XII 2025

作者： Fard, Sajede Saeidi Singh, Manmohan Schill, Alexander W. Aglyamov, Salavat R. Nijem, Nadine Scarcelli, Giuliano Lekven, Arne Larin, Kirill V. Department of Biomedical Engineering University of Houston HoustonTX United States Department of Mechanical and Aerospace Engineering University of Houston HoustonTX United States Department of Biology and Biochemistry University of Houston HoustonTX United States Fischell Departement of Bioengineering University of Maryland MD United States

ISBN: (纸本)9781510683907

The assessment of microscale biomechanical characteristics provides crucial information about the interplay between forces and tissue stiffness during development. These forces can regulate tissue dynamics and organogenesis. Many methods such as atomic force microscopy, optical tweezers, and optical coherence elastography have been utilized to extract mechanical parameters. However, these techniques often lack sufficient resolution or require external forces that involve contract, which can disrupt mechanosensitive cells and tissues. In this study, we have used a high-resolution Brillouin microscopy system enabling mapping of the stiffness of zebrafish embryos at cleavage periods 1 hour post fertilization (hpf), 1.75 hpf, and 2.25 hpf before and after a 1-hour cold treatment at 5℃. The axial and transverse resolution of Brillouin system was 2.3 and 1.8 µm, respectively, enabling cellular-level imaging of the zebrafish embryo mechanical properties. The results show that zebrafish embryo anomalies caused by the cold treatment were correlated to changes in the Brillouin frequency. The results show that the longitudinal modulus across the yolk has increased, and two various layers with different Brillouin frequency shifts at the blastomere are clearly observable. Furthermore, the results show an increasing stiffness at the interface of the blastomere and yolk regions, where the yolk syncytial layer (YSL) forms during early cleavage stages between the ninth and tenth cleavages, which is when the embryo has 512-1024 cells. © 2025 SPIE.

关键词： Invertebrates

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Spatially strain-induced and selective preparation of Mo_(x)N(x=1,2)as a highly effective nanoarchitectonic catalyst for hydrogen evolution reaction in a wide pH range

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Rare Metals 2023年第5期42卷 1446-1452页

作者： Chao Huang Xiao-Lin Zhang Jing Tang Dan Li Qing-Dong Ruan Liang-Liang Liu Fang-Yu Xiong Bin Wang Yue Xu Sui-Han Cui Yang Luo Qing-Wei Li Paul K.Chu Department of Physics Department of Materials Science and EngineeringCity University of Hong KongHong Kong999077China Department of Biomedical Engineering City University of Hong KongHong Kong999077China State Key Laboratory of Powder Metallurgy Central South UniversityChangsha410011China School of Mechanical Engineering Liaoning Petrochemical UniversityFushun113001China Advanced Research Institute for Multidisciplinary Science Qilu University of Technology(Shandong Academy of Sciences)Jinan250307China

Developing highly efficient catalysts for the hydrogen evolution reaction(HER)is crucial to commercial water splitting in the global efforts to mitigate fossil fuel combustion and combat global climate *** nitrides(Mo... 详细信息

关键词： catalyst splitting preparation

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Long-term monitoring of indoor carbon monoxide levels in disproportionately impacted neighborhoods in Denver 18

Long-term monitoring of indoor carbon monoxide levels in dis...

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18th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2024

作者： Sankhyan, Sumit Hollo, Aniya K. Gonzalez-Beltran, Dulce Clements, Nicholas Miller, Shelly L. Paul M. Rady Department of Mechanical Engineering University of Colorado Boulder 1111 Engineering Drive BoulderCO80309 United States Environmental Engineering Program University of Colorado Boulder 4001 Discovery Drive BoulderCO80302 United States

ISBN: (纸本)9798331306816

In this study we monitored indoor carbon monoxide (CO) levels for ~50 homes over two seasons in the Denver metropolitan area as part of the Social, Justice, and Environmental Quality-Denver initiative (SJEQ-D). These homes were chosen from disproportionately impacted neighborhoods and were impacted by a major freeway construction upgrade in close proximity to these neighborhoods. The results from the suggest that ~10% of the homes in each cohort had consistently low levels of CO (daily averaged values above 3.5 ppm) and ~20% of the homes also consistently showed episodic peaks above 9 ppm throughout this yearlong study spanning three different seasons. The results from this study underline the need for increasing awareness regarding the prevalence of low levels of CO exposures at homes since concentration at these levels could impact the overall health of residents especially pregnant women and sensitive populations. © 2024 18th Conference of the International Society of Indoor Air Quality and Climate, INDOOR AIR 2024 - Conference program and Proceedings. All rights reserved.

关键词： Indoor air pollution

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Targeting glial metabolism in neurodegenerative diseases:detail matters

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Neural Regeneration Research 2023年第11期18卷 2393-2394页

作者： Ruqayya Afridi Kyoungho Suk Department of Pharmacology School of MedicineKyungpook National UniversityDaeguSouth Korea Department of Biomedical Sciences BK21 PLUS KNU Biomedical Convergence ProgramSchool of MedicineKyungpook National UniversityDaeguSouth Korea Brain Science and Engineering Institute Kyungpook National UniversityDaeguSouth Korea

Neurodegenerative diseases,a group of disorders associated with advanced age,are typified by the disease-specific accumulation of mutant proteins and *** decades,treatment modalities for these disorders have focused on addressing neuronal malfu nction,which has resulted in the failure of *** studies have identified the crucial role of glial cells in exacerbating neurodegenerative processes via the release of neuroinflammatory ***,the major immune component of the central nervous system (CNS),undergo numerous phenotypic transitions and regulate the outcomes of various pathologies (Afridi et al.,2022).

关键词： degenerative metabolism diseases

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Risk Allocation Preferences in Indonesian Electricity Public-Private Partnership Projects: A Conjoint Analysis

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IEEE engineering Management Review 2021年第3期49卷 154-174页

作者： Hartono, Budi Ghifari, M. Dzaki Agung Dianita, Orchida Industrial Engineering Program Mechanical and Industrial Engineering Department Faculty of Engineering Universitas Gadjah Mada Yogyakarta5528 Indonesia

This article investigates the risk allocation preferences of Indonesian government agents within a public-private partnership scheme in electricity infrastructure projects. A full-factorial conjoint analysis is employed by introducing three groups of risk factors, namely, 'Policy,' 'Legal,' and 'Project residual' risks, to form eight distinctive scenarios. A total of 37 respondents from a government agency and other public agencies participated in the experiment, and two distinct clusters within a single party (public entity/government) emerged. The two clusters agree on the order of importance of risk preferences but disagree on nearly everything else. The clusters diverge in the magnitude of risk importance, risk preference scores, profiles, and the most preferred scenarios. This article also determines that the risk preference profiles of both clusters do not consistently follow the optimum risk-sharing principles. Moreover, this article elaborates on the scientific contributions and practical implications of the findings. Results provide essential insights into the risk allocation preferences of the public agents. The findings contribute to the development of mutual understanding between the public and private entities. © 1973-2011 IEEE.

关键词： Risk perception

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