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International Congress on Advanced Electromagnetic Materials in Microwaves and Optics (METAMATERIALS)

作者： D. M. Solís S. Yin E. Galiffi A. Alù N. Engheta Departamento de Tecnología de los Computadores y de las Comunicaciones University of Extremadura Cáceres Spain Photonics Initiative Advanced Science Research Center City University of New York New York USA Physics Program Graduate Center City University of New York New York USA Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia PA USA

ISBN: (数字)9798350373493

ISBN: (纸本)9798350373509

Inspired by the need of recognizing novel mechanisms to engineer time and spacetime inhomogeneities, we theoretically explore the possibilities of inducing fast temporal changes in the structural dispersion of a one-dimensional parallel-plate cavity. In this work, we delve into the variation of interplate distance not by actual motion of the cavity’s metallic boundaries, but through the effective subluminal synthetic motion that emerges from a judicious switching operation in the metallic region, parameterized as a lossless spacetime-varying plasma. We theoretically show how, depending on the nature of this time-dispersive switching process, different boundary conditions apply, providing richer physics than true motion.

关键词： Frequency synthesizers Resonant frequency Switches Boundary conditions Nonhomogeneous media Frequency conversion Metamaterials Plasmas Fabry-Perot Physics

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OXidative Stress PREDictor: A Supervised Learning Approach for Annotating Cellular Oxidative Stress States in Inflammatory Cells

Advanced Intelligent Systems

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Advanced Intelligent systems 2025年第3期7卷

作者： Chen, Po-Yuan Ko, Tai-Ming Institute of Bioinformatics and Systems Biology College of Engineering Bioscience National Yang Ming Chiao Tung University Hsinchu300 Taiwan Bioinformatics Program Institute of Statistical Science Taiwan International Graduate Program Academia Sinica Taipei115 Taiwan Institute of Biomedical Sciences Academia Sinica Taipei115 Taiwan Institute of Statistical Science Academia Sinica Taipei115 Taiwan Department of Biological Science and Technology College of Engineering Bioscience National Yang Ming Chiao Tung University Hsinchu300 Taiwan National Yang Ming Chiao Tung University Hsinchu300 Taiwan School of Pharmacy College of Pharmacy Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung807 Taiwan

Oxidative stress, characterized by an imbalance between reactive oxygen species (ROS) and antioxidants, plays a pivotal role in inflammatory responses associated with both chronic diseases and acute injuries. In this study, OXidative Stress PREDictor (OxSpred), a supervised learning model tailored to accurately annotate the oxidative stress state of innate immune cells at the single-cell level, is introduced. Compared to the traditional gene-set-variation-analysis-based enrichment method, OxSpred demonstrates superior accuracy with an area under the receiver operating characteristic curve of 0.89 and offers interpretable embeddings with significant biological relevance. Using the predicted ROS states, precise elucidation and interpretation of the roles of novel innate immune cell subtypes can be achieved. Overall, OxSpred enhances the utility of single-cell transcriptomic datasets by providing a robust in silico method for determining intracellular oxidative stress states, thereby enriching the understanding of innate immune cell functions during inflammation. © 2024 The Author(s). Advanced Intelligent systems published by Wiley-VCH GmbH.

关键词： Cells

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All-Electric Ship On-Board Continuous Sustainable H2 Generation from Aluminum Scrap and Seawater

All-Electric Ship On-Board Continuous Sustainable H2 Generat...

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IEEE Electric Ship Technologies Symposium, ESTS

作者： Dhyogo M. Taher Wellington Balmant Stephan H. Och Diogo B. Pitz Giuliana S. Venter Lucio C. Filho Lauber S. Martins José V. C. Vargas Juan C. Ordonez Graduate Program in Mechanical Engineering and Sustainable Energy Research and Development Center Federal University of Paraná UFPR Curitiba PR Brazil Department of Chemical Engineering Maringá State University UEM Maringá PR Brazil Department of Health and Biomedical Sciences Advent Health University AHU Orlando FL USA Department of Mechanical Engineering Center for Advanced Power Systems and Energy and Sustainability Center Florida State University FSU Tallahassee FL USA

A mathematical model of a sustainable H2 generation reactor that utilizes aluminum and seawater is introduced. Conservation of species and the kinetics of the H2 production reaction from aluminum and seawater allowed for obtaining the process transient response in a batch reactor. Continuous steady state production was assessed by adding a balance of energy, allowing for reactants inlet mass flow rates, and calculating the outlet H2 mass flow (generation) rate. The theoretical H2 production curve data showed good quantitative and qualitative agreement with experimental data. The validated mathematical model was then used to optimize the continuous reactor. The maximum was sharp, since an 85% variation between the maximum and the smallest H2 generation rate value as a function of the inlet NaOH solution volumetric flow rate tested range was verified. Such fundamental result stresses the importance of operating the system at the optimal condition, no matter how complex the actual reactor design may be. Since aluminum is inexpensive, abundant, and fully recyclable, in situ sustainable H2 production could allow for fuel cell stacks to become all electric ships (AES) power sources.

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Big data in healthcare:Conceptual network structure,key challenges and opportunities

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Digital Communications and Networks 2023年第4期9卷 856-868页

作者： Leonardo B.Furstenaua Pedro Leivas Michele Kremer Sott Michael S.Dohan Jose Ricardo Lopez-Robles Manuel J.Cobo Nicola Luigi Bragazzi Kim-Kwang Raymond Choo Post-Graduate Program in Industrial Engineering Federal University of Rio Grande Do SulPorto Alegre90035-190Brazil University of Santa Cruz Do Sul Av.Independencia 2293Santa Cruz Do SulRSBrazil Business School Unisinos UniversityAv.Dr.Nilo Peçanha 160091330-002Porto AlegreBrazil Faculty of Business Administration Lakehead UniversityThunder BayOntarioCanada Autonomous University of Zacatecas Av.Ramon Lopez Velarde Col.CentroZacatecas98000Mexico Department of Computer Science and Artificial Intelligence Andalusian Research Institute in Data Science and Computational Intelligence(DaSCI)University of GranadaGranada 18071Spain York University ON M3J 1P3Canada Department of Information Systems and Cyber Security University of Texas at San AntonioSan AntonioTX78249USA

Big data is a concept that deals with large or complex data sets by using data analysis tools(e.g.,data mining,machine learning)to analyze information extracted from several sources *** data has attracted wide attention from academia,for example,in supporting patients and health professionals by improving the accuracy of decision-making,diagnosis and disease *** research aimed to perform a Bibliometric Performance and Network Analysis(BPNA)supported by a Scoping Review(SR)to depict the strategic themes,thematic evolution structure,main challenges and opportunities related to the concept of big data applied in the healthcare *** this goal in mind,4857 documents from the Web of Science covering the period between 2009 to June 2020 were analyzed with the support of SciMAT *** bibliometric performance showed the number of publications and citations over time,scientific productivity and the geographic distribution of publications and research *** strategic diagram yielded 20 clusters and their relative importance in terms of centrality and *** thematic evolution structure presented the most important themes and how it changes over ***,we presented the main challenges and future opportunities of big data in healthcare.

关键词： Big data Healthcare digitalization Bibliometric Strategic intelligence Co-word analysis SciMAT

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Terahertz Magnetospectroscopy of Gadolinium Gallium Garnet in Fields up to 25 T

Terahertz Magnetospectroscopy of Gadolinium Gallium Garnet i...

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JSAP-OSA Joint Symposia, JSAP 2021

作者： Bao, J. Peraca, N. Marquez Tay, F. Kritzell, T.E. Li, X. Noe, G.T. Katayama, I. Takeda, J. Nojiri, H. Yamahara, H. Tabata, H. Baydin, A. Kono, J. Department of Physics and Astronomy Rice University HoustonTX United States Department of Electrical and Computer Engineering Rice University HoustonTX United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX United States Department of Physics Graduate School of Engineering Science Yokohama National University Yokohama Japan Institute for Materials Research Tohoku University Sendai Japan Department of Electrical Engineering and Information Systems Graduate School of Engineering University of Tokyo Japan Smalley-Curl Institute Rice University HoustonTX United States Department of Materials Science and NanoEngineering Rice University HoustonTX United States

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Synthesis of zeolites from calcareous waste concrete powder

Results in Materials

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Results in Materials 2022年 13卷

作者： Kanda, Yasuyuki Harada, Satori Mechanical Engineering Program School of Engineering Faculty of Engineering University of the Ryukyus 1 Senbaru Nishihara-cho Nakagami-gun Okinawa 903-0213 Japan Mechanical Systems Engineering Course Graduate School of Engineering and Science University of the Ryukyus 1 Senbaru Nishihara-cho Nakagami-gun Okinawa 903-0213 Japan

In this study, zeolites were synthesized from calcareous waste concrete powder (WCP) using a hydrothermal synthesis method. Effective utilization methods of waste concrete are required worldwide for prolonging the final dumping sites’ lifetime and for promoting a society that recycles. Calcareous concrete, which includes many calcium components, has been widely used. The WCP includes mainly calcite (at 66.9%) and quartz. First, we applied hydrothermal synthesis to raw WCP. However, X-ray diffraction analysis (XRD) revealed no zeolite synthesis. Next, we used the same approach on WCP-HCl (WCP with the calcium component removed by HCl treatment). For WCP-HCl, the synthesis of analcime-type zeolites was confirmed based on XRD and simple absorption tests, in which the WCP-HCl color changed from gray to blue upon its absorption of methylene blue. Finally, to determine the analcime synthesis requirements, we experimentally varied the synthesis. Analcime synthesis was observed at temperatures above 433 K after at least 12 h of heating and for NaOH solution concentrations above 2 mol/L. © 2021 The Authors

关键词： Analcime Hydrothermal synthesis method Recycle Waste concrete Zeolite

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Towards a Predictive Approach for Omni-channel Retailing Supply Chains

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IFAC-PapersOnLine 2019年第13期52卷 844-850页

作者： Pereira, Marina Meireles Frazzon, Enzo Morosini Graduate Program in Production Engineering Industrial and Systems Engineering Department Technology Center Federal University of Santa Catarina Florianópolis Santa Catarina Brazil

The adoption of omni-channel strategy has changed the relation between retailers and customers and brought more complexity to the retailing supply chains. To address the increasing complexity, it is necessary to adopt innovative approaches based on information technologies and intelligent decision methods. The challenges to retailers are improving the accuracy of offline and online channels demand forecasting, better managing offline and online customer's needs, thus reducing the uncertainties of the omni-channel retailing supply chain. In this context, this research paper aims to propose a predictive approach for omni-channel retailing supply chain combining clustering with artificial neural network to handle demand uncertainty. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Neural networks Complex networks Learning systems Sales Supply chain management Channel strategies Clustering Demand forecasting Demand uncertainty Innovative approaches Intelligent decisions Omni channel Retail supply chain

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Diffusion-based Reinforcement Learning for Edge-enabled AI-Generated Content Services

TechRxiv

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TechRxiv 2023年

作者： Du, Hongyang Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Huang, Huawei Mao, Shiwen School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore School of Software Engineering Sun Yat-Sen University Zhuhai China Department of Electrical and Computer Engineering Auburn University Auburn United States

As Metaverse emerges as the next-generation Internet paradigm, the ability to efficiently generate content is paramount. AI-Generated Content (AIGC) emerges as a key solution, yet the resource-intensive nature of large Generative AI (GAI) models presents challenges. To address this issue, we introduce an AIGC-as-a-Service (AaaS) architecture, which deploys AIGC models in wireless edge networks to ensure broad AIGC services accessibility for Metaverse users. Nonetheless, an important aspect of providing personalized user experiences requires carefully selecting AIGC Service Providers (ASPs) capable of effectively executing user tasks, which is complicated by environmental uncertainty and variability. Addressing this gap in current research, we introduce the AI-Generated Optimal Decision (AGOD) algorithm, a diffusion model-based approach for generating the optimal ASP selection decisions. Integrating AGOD with Deep Reinforcement Learning (DRL), we develop the Deep Diffusion Soft Actor-Critic (D2SAC) algorithm, enhancing the efficiency and effectiveness of ASP selection. Our comprehensive experiments demonstrate that D2SAC outperforms seven leading DRL algorithms. Furthermore, the proposed AGOD algorithm has the potential for extension to various optimization problems in wireless networks, positioning it as a promising approach for future research on AIGC-driven services. The implementation of our proposed method is available at: https://***/Lizonghang/AGOD. © 2023, CC BY.

关键词： Reinforcement learning

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Diffusion-based Reinforcement Learning for Edge-enabled AI-Generated Content Services

arXiv

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arXiv 2023年

作者： Du, Hongyang Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Huang, Huawei Mao, Shiwen The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The School of Software Engineering Sun Yat-Sen University Zhuhai China The Department of Electrical and Computer Engineering Auburn University Auburn United States

关键词： Reinforcement learning

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An Analysis Method for Metric-Level Switching in Beat Tracking

arXiv

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arXiv 2022年

作者： Chiu, Ching-Yu Müller, Meinard Davies, Matthew E.P. Su, Alvin Wen-Yu Yang, Yi-Hsuan Graduate Program of Multimedia Systems and Intelligent Computing National Cheng Kung University Academia Sinica Taiwan International Audio Laboratories Erlangen Germany Department of Informatics Engineering Centre for Informatics and Systems The University of Coimbra University of Coimbra Portugal Department of CSIE National Cheng Kung University Taiwan Taiwan AI Labs Taiwan

For expressive music, the tempo may change over time, posing challenges to tracking the beats by an automatic model. The model may first tap to the correct tempo, but then may fail to adapt to a tempo change, or switch between several incorrect but perceptually plausible ones (e.g., half- or double-tempo). Existing evaluation metrics for beat tracking do not reflect such behaviors, as they typically assume a fixed relationship between the reference beats and estimated beats. In this paper, we propose a new performance analysis method, called annotation coverage ratio (ACR), that accounts for a variety of possible metric-level switching behaviors of beat trackers. The idea is to derive sequences of modified reference beats of all metrical levels for every two consecutive reference beats, and compare every sequence of modified reference beats to the subsequences of estimated beats. We show via experiments on three datasets of different genres the usefulness of ACR when being utilized alongside existing metrics, and discuss the new insights that can be gained. © 2022, CC BY.

关键词： Taps

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