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Are facilities to support alternative modes effective in reducing congestion?: Modeling the effect of heterogeneous traffic conditions on vehicle delay at intersections

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Multimodal Transportation 2023年第1期2卷

作者： Kodupuganti, Swapneel R. Pulugurtha, Srinivas S. Ph.D. Graduate of Infrastructure and Environmental Systems (INES) Program The University of North Carolina at Charlotte 9201 University City Boulevard Charlotte 28223-0001 NC United States Professor & Research Director of Civil & Environmental Engineering Department Director of Infrastructure Design Environment and Sustainability (IDEAS) Center The University of North Carolina at Charlotte 9201 University City Boulevard Charlotte 28223-0001 NC United States

Multimodal facilities are being built in a majority of urban areas to accommodate both motorized and non-motorized traffic. The resulting transportation system is susceptible to complex interactions between different modes and users. These complex interactions are hard to quantify and capture on a regular basis. There is a need to rely on a microsimulation platform to replicate such real-world scenarios and forecast future conditions. This study focuses on assessing the effect of heterogeneous traffic conditions involving multiple modes like light rail transit (LRT), walking, bicycling, and motorized traffic on vehicle delay at intersections using Vissim traffic simulation software. A 2.5-mile urban arterial corridor comprising of seven at-grade and two grade-separated signalized intersections along US-29 route in the city of Charlotte, NC, USA was chosen for analysis and modeling. Base simulation model was developed by replicating the traffic scenario for the year 2018 (without LRT and non-motorized traffic). External controllers like VisVAP and Viswalk were used to assign signal priority and model heterogenous traffic conditions. The vehicle operational performance of the corridor improved along the major street after the addition of the LRT. An increase in vehicle delay on the major street was observed with an increase in the non-motorized traffic. Contrarily, the operational performance of the cross-streets at at-grade intersections did not see any significant change due to the addition of non-motorized traffic. The proposed framework assists planners to assess the impact of adding a new transit system like LRT and associated non-motorized traffic on the urban corridor. © 2022

关键词： Bicyclist Light rail transit LRT Operational performance Pedestrian Vehicle delay

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Development of a Bioactive, Piezoelectric PVDF-TrFE Scaffold to Modulate Wound Response in the Peripheral Nervous System

SSRN

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SSRN 2024年

作者： Bryan, Andrew E. Krutko, Maksym Rebholz, Sandra Marquez, Lindsey E. Busch, Emma Dong, Kevin Pixley, Sarah K. Cushion, Melanie T. Esfandiari, Leyla Harris, Greg M. Department of Chemical and Environmental Engineering University of Cincinnati CincinnatiOH45221 United States Department of Biomedical Engineering University of Cincinnati CincinnatiOH45221 United States Department of Internal Medicine University of Cincinnati College of Medicine CincinnatiOH45267 United States Medical Research Service Cincinnati Veterans Affairs Medical Center CincinnatiOH45220 United States Department of Pharmacology and Systems Physiology University of Cincinnati College of Medicine CincinnatiOH45267 United States Department of Electrical Engineering University of Cincinnati CincinnatiOH45221 United States Department of Environmental & Public Health Sciences University of Cincinnati College of Medicine CincinnatiOH45267 United States Neuroscience Graduate Program University of Cincinnati College of Medicine CincinnatiOH45267 United States

To address current limitations in biomaterials for peripheral nerve repair regarding a lack of physiologically relevant signaling and immune response following implantation, this study evaluated the development and feasibility of a multi-cue biomaterial with physiologically relevant chemical, electrical, and physical signaling. To accomplish this, a bulk-functionalized poly(vinylidene fluoride-trifluoroethylene) (PVDF-TrFE) scaffold was fabricated using blend electrospinning to incorporate decellularized extracellular matrix (dECM) to mediate the foreign body response in vivo and promote enhanced wound healing. Decellularized ECM was secreted and assembled by fibroblast cells and incorporated into the electrospinning solution with concentration values ranging from 0% to 0.4% (m/v). Physical, chemical, and electrical properties of the scaffold were analyzed by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), Fourier-transform infrared spectroscopy (FTIR), X-ray diffractometry (XRD), mechanical tensile testing, and voltage readings for piezoelectricity. Blended scaffolds were evaluated in vitro for analysis of cell-material interactions in the context of peripheral nerve injury (PNI) repair and in vivo for immune response. In vitro work demonstrated increased cell metabolism and elongated, repair-like morphologies in Schwann cells on scaffolds with higher dECM concentrations. Subcutaneous implantation of blended scaffolds in rats at 7 days revealed limited multi-nucleated giant cell formation. Following 28 days in vivo, regenerative characteristics of the proliferative phase of wound healing were present with enhanced nerve growth and vasculature to scaffold. Overall, blend-electrospun scaffolds with native dECM showed promise in mitigating pro-inflammatory responses and promote advanced regenerative behaviors, thereby providing an implantable biomaterial with the necessary physical, chemical, and electrical characteristics desired for c

关键词： Fourier transform infrared spectroscopy

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Improved multiobjective differential evolution with spherical pruning algorithm for optimizing 3D printing technology parametrization process

Research Square

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Research Square 2021年

作者： Cruz, Luciano Ferreira Pinto, Flavia Bernardo Camilotti, Lucas Santanna, Angelo Marcio Oliveira Freire, Roberto Zanetti Coelho, Leandro dos Santos Volvo of Brazil Vehicles Juscelino Kubitschek de Oliveira 2600 Curitiba81260-900 Brazil Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Imaculada Conceição 1155 Curitiba80215-901 Brazil Industrial Engineering Graduate Program Federal University of Bahia prof. Aristides Novis 2 Salvador41250-360 Brazil Department of Electrical Engineering Federal University of Paraná Cel. Francisco Heráclito dos Santos 100 Curitiba81531-980 Brazil

Multiobjective optimization approaches have allowed the improvement of technical features in industrial processes, focusing on more accurate approaches for solving complex engineering problems and support decision-making. This paper proposes a hybrid approach to optimize the 3D printing technology parameters, integrating the design of experiments and multiobjective optimization methods, as an alternative to classical parametrization design used in machining processes. Alongside the approach, a multiobjective differential evolution with uniform spherical pruning (usp-MODE) algorithm is proposed to serve as an optimization tool. The parametrization design problem considered in this research has the following three objectives: to minimize both surface roughness and dimensional accuracy while maximizing the mechanical resistance of the prototype. A benchmark with nondominated sorting genetic algorithm II (NSGA-II) and with the classical sp-MODE is used to evaluate the performance of the proposed algorithm. With the increasing complexity of engineering problems and advances in 3D printing technology, this study demonstrates the applicability of the proposed hybrid approach, finding optimal combinations for the machining process among conflicting objectives regardless of the number of decision variables and goals involved. To measure the performance and to compare the results of metaheuristics used in this study, three Pareto comparison metrics have been utilized to evaluate both the convergence and diversity of the obtained Pareto approximations for each algorithm: hyper-volume (H), g-Indicator (G), and inverted generational distance (IGD). To all of them, ups-MODE outperformed, with significant figures, the results reached by NSGA-II and sp-MODE algorithms. © 2021, CC BY.

关键词： Multiobjective optimization

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Optimal Indirect Power Predictive Controller in the Alpha-Beta Reference Frame for Grid-Connected Converters

Optimal Indirect Power Predictive Controller in the Alpha-Be...

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2019 FISE-IEEE/CIGRE Conference - Living the Energy Transition, FISE/CIGRE 2019

作者： Murillo-Yarce, D. Marulanda-Durango, J.J. Mejía, A. Escobar Alzatc-Gómez, A. Engineering Systems Faculty of Engineering Universidad de Talca Curicó Chile Electrical Engineering Graduate and Undergraduate Program Universidad Tecnológica de Pereira Pereira Colombia

ISBN: (纸本)9781728142302

This article presents an indirect power predictive optimal controller applicable to grid-connected converters. The VSI converter is used as an interface between distributed generators, energy storage systems and the ac-grid. The objective of the research project is to develop a controller with high static and dynamic features, that performs with low computational burden and low switching stress. The first step to develop the controller is to select the appropiate reference frame. The αβ frame is used for its simple structure and easy implementation. Then, the proposed methodology consider the controller performance to define the sampling period, the prediction horizon and the switching pattern. Results show that an increment in the sampling period results in a major harmonic content, and if the prediction horizon increases, the number of calculations is higher without improving the controller performance. The main features of the proposed controller are: low sampling times and a two-steps prediction horizon. With these features the VSI efficiency rises, while the systems's losses and harmonic distortion are reduced. © 2019 IEEE.

关键词： Controllers

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Membrane Protein Modification Modulates Big and Small Extracellular Vesicle Biodistribution and Tumorigenic Potential in Breast Cancers In Vivo

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Advanced Materials 2023年第13期35卷 e2208966页

作者： Magoling, Bryan John Abel Wu, Anthony Yan-Tang Chen, Yen-Ju Wong, Wendy Wan-Ting Chuo, Steven Ting-Yu Huang, Hsi-Chien Sung, Yun-Chieh Hsieh, Hsin Tzu Huang, Poya Lee, Kang-Zhang Huang, Kuan-Wei Chen, Ruey-Hwa Chen, Yunching Lai, Charles Pin-Kuang Institute of Atomic and Molecular Sciences Academia Sinica Taipei10617 Taiwan Graduate Institute of Biochemical Sciences National Taiwan University Taipei10617 Taiwan Chemical Biology and Molecular Biophysics Program TIGP Academia Sinica Taipei11529 Taiwan Department of Pharmacology College of Medicine National Taiwan University Taipei100233 Taiwan Institute of Biomedical Engineering and Frontier Research Center on Fundamental and Applied Sciences of Matters National Tsing Hua University Hsinchu30013 Taiwan Department of Chemical Engineering National Tsing Hua University Hsinchu30013 Taiwan Institute of Biological Chemistry Academia Sinica Taipei11529 Taiwan Genome and Systems Biology Degree Program National Taiwan University Taipei10617 Taiwan

Extracellular vesicles (EVs) are released by cells to mediate intercellular communication under pathological and physiological conditions. While small EVs (sEVs;200 nm, microvesicles) are less well explored. Here, bEVs and sEVs are identified as distinct EV populations, and it is determined that bEVs are released in a greater bEV:sEV ratio in the aggressive human triple-negative breast cancer (TNBC) subtype. PalmGRET, bioluminescence-resonance-energy-transfer (BRET)-based EV reporter, reveals dose-dependent EV biodistribution at nonlethal and physiological EV dosages, as compared to lipophilic fluorescent dyes. Remarkably, the bEVs and sEVs exhibit unique biodistribution profiles, yet individually promote in vivo tumor growth in a syngeneic immunocompetent TNBC breast tumor murine model. The bEVs and sEVs share mass-spectrometry-identified tumor-progression-associated EV surface membrane proteins (tpEVSurfMEMs), which include solute carrier family 29 member 1, Cd9, and Cd44. tpEVSurfMEM depletion attenuates EV lung organotropism, alters biodistribution, and reduces protumorigenic potential. This study identifies distinct in vivo property and function of bEVs and sEVs in breast cancer, which suggest the significant role of bEVs in diseases, diagnostic and therapeutic applications. © 2023 The Authors. Advanced Materials published by Wiley-VCH GmbH.

关键词： Mass spectrometry

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Evaluation of using WGS/WES to characterize ACMG actionable genes in genetic testing reports

Evaluation of using WGS/WES to characterize ACMG actionable ...

引用

2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

作者： Yang, Wen-Tse Wu, Dong-Chi Liu, Jen-Feng Hong, Jin-Bon Wu, June-Tai Chen, Pei-Lung Chen, Chien-Yu National Taiwan University Department of Biomechatronics Engineering Taipei Taiwan National Taiwan University and Academia Sinica Genome and Systems Biology Degree Program Taipei Taiwan Institute of Molecular Medicine National Taiwan University College of Medicine Taipei Taiwan National Taiwan University Hospital Department of Dermatology Taipei Taiwan Graduate Institute of Medical Genomics and Proteomics National Taiwan University College of Medicine Taipei Taiwan

ISBN: (纸本)9781665401265

Since the American College of Medical Genetics and Genomics (ACMG) published recommendations for reporting incidental findings in clinical exome and genome sequencing in 2013, the list of suggested actionable genes appear more and more frequently in the reports of genetic testing. However, the existence of low-coverage regions, no matter happening systematically or randomly, in whole genome sequencing (WGS) or whole exome sequencing (WES) raise the chances of false negatives when reporting pathogenicity in variant discovery. To evaluate the effectivity of different sequencing methods, this study developed a workflow to examine low-coverage regions in ACMG actionable genes (version 2 contains 59 genes) on three groups of sequencing data, including 5 samples of 30X WGS, 41 samples of 40X WGS, and 11 samples of WES. By extracting the ACMG regions of the alignment files, we first found that per-base mean coverage in WES is significantly higher in some chromosomes (2, 5, 6, 9, 13, 14, 17, 18) than the others, and the overall average (44.5) is higher than 30X WGS (32.4) and 40X WGS (36.2). However, the total length of the low-coverage regions in ACMG actionable genes is higher in WES samples: 23 times higher than 40X WGS, and 8 times higher than 30X WGS. When looking into ClinVar significance of pathogenic/likely pathogenic (P/LP) variants (the 2020/03/16 release contains 21,388 P/LP variants falling in the 59 actionable genes), 100% (11/11) WES samples and 80% (4/5) 30X WGS samples have more than 20 P/LP variants in the low-coverage regions, while only 2.4% (1/41) 40X WGS samples have such a risk of missing >20 P/LP variants. We conclude that in order to reduce the possibility of missing clinically significant variants, 40X WGS are more recommended than 30X WGS and WES to achieve satisfied quality of characterizing ACMG actionable genes in genetic testing. © 2021 IEEE.

关键词： Genome

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A model for renewable energy symbiosis networks in eco-industrial parks

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IFAC-PapersOnLine 2020年第2期53卷 13137-13142页

作者： Maria Angela Butturi Miguel A. Sellitto Francesco Lolli Elia Balugani Alessandro Neri Department of Sciences and Methods for Engineering University of Modena and Reggio Emilia 42100 Reggio Emilia Italy Production and Systems Engineering Graduate Program Universidade do Vale do Rio dos Sinos 93.022-000 Brazil

Renewable energy technologies integration within industrial districts can boost carbon emissions reduction in the industry sector. The eco-industrial parks model promotes the sustainable use of energy and the application of energy synergies and energy exchanges that can include renewable sources of energy. This paper presents an optimization methodology based on a multi-stakeholder perspective to evaluate energy symbiosis including the integration of renewable energy sources within the parks. The study results in three scenarios providing to managers of single firms and parks relevant information for supporting decision making regarding the economic sustainability and the environmental impacts of the energy synergies. The results show that the optimization of the collective point of view ensures more efficient management of the energy supplied by renewables as well as by firms that can provide an energy surplus.

关键词： Renewable energy systems Decision making Models Environment Energy dependence Energy management system Industrial production systems

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cytoNet: Spatiotemporal network analysis of cell communities (vol 18, e1009846, 2022)

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PLOS COMPUTATIONAL BIOLOGY 2022年第11期18卷 e1009846页

作者： Mahadevan, A. S. Long, B. L. Hu, C. W. Ryan, D. T. Grandel, N. E. Department of Bioengineering University of Pennsylvania Philadelphia Pennsylvania United States of America. Department of Bioengineering Rice University Houston Texas United States of America. Systems Synthetic and Physical Biology Program Rice University Houston Texas United States of America. Department of Biomedical Engineering University of Texas at San Antonio San Antonio Texas United States of America. Biophysics Graduate Program University of California Berkeley California United States of America. Department of Oral & Maxillofacial Surgery University of Texas Health Science Center at San Antonio San Antonio Texas United States of America. Department of Electrical and Computer Engineering Rice University Houston Texas United States of America.

We introduce cytoNet, a cloud-based tool to characterize cell populations from microscopy images. cytoNet quantifies spatial topology and functional relationships in cell communities using principles of network science. Capturing multicellular dynamics through graph features, cytoNet also evaluates the effect of cell-cell interactions on individual cell phenotypes. We demonstrate cytoNet's capabilities in four case studies: 1) characterizing the temporal dynamics of neural progenitor cell communities during neural differentiation, 2) identifying communities of pain-sensing neurons in vivo, 3) capturing the effect of cell community on endothelial cell morphology, and 4) investigating the effect of laminin α4 on perivascular niches in adipose tissue. The analytical framework introduced here can be used to study the dynamics of complex cell communities in a quantitative manner, leading to a deeper understanding of environmental effects on cellular behavior. The versatile, cloud-based format of cytoNet makes the image analysis framework accessible to researchers across domains.

关键词： Calcium imaging Fluorescence imaging Growth factors Centrality Cell cycle and cell division Endothelial cells Network analysis Stem cells

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Economics of Semantic Communication System: An Auction Approach

arXiv

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arXiv 2022年

作者： Liew, Zi Qin Du, Hongyang Yang, Wei Lim, Bryan Xiong, Zehui Niyato, Dusit Miao, Chunyan Kim, Dong In Alibaba-NTU Singapore Joint Research Institute Nanyang Technological Univerity Singapore The School of Computer Science and Engineering The Energy Research Institute NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The School of Computer Science and Engineering Nanyang Technological University Singapore The School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore Nanyang Technological University Singapore639798 Singapore The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Semantic communication technologies enable wireless edge devices to communicate effectively by transmitting semantic meaning of data. Edge components, such as vehicles in next-generation intelligent transport systems, use well-trained semantic models to encode and decode semantic information extracted from raw and sensor data. However, the limitation in computing resources makes it difficult to support the training process of accurate semantic models on edge devices. As such, edge devices can buy the pretrained semantic models from semantic model providers, which is called "semantic model trading". Upon collecting semantic information with the semantic models, the edge devices can then sell the extracted semantic information, e.g., information about urban road conditions or traffic signs, to the interested buyers for profit, which is called "semantic information trading". To facilitate both types of the trades, effective incentive mechanisms should be designed. Thus, in this paper, we propose a hierarchical trading system to support both semantic model trading and semantic information trading jointly. The proposed incentive mechanism helps to maximize the revenue of semantic model providers in the semantic model trading, and effectively incentivizes model providers to participate in the development of semantic communication systems. For semantic information trading, our designed auction approach can support the trading between multiple semantic information sellers and buyers, while ensuring individual rationality, incentive compatibility, and budget balance, and moreover, allowing them achieve higher utilities than the baseline method. Copyright © 2022, The Authors. All rights reserved.

关键词： Commerce

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Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization

arXiv

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arXiv 2023年

作者： Du, Hongyang Zhang, Ruichen Liu, Yinqiu Wang, Jiacheng Lin, Yijing Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Cui, Shuguang Ai, Bo Zhou, Haibo Kim, Dong In The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Computer Science and Engineering Nanyang Technological University Singapore The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications China 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 Shenzhen China The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China School of Electronic Science and Engineering Nanjing University Jiangsu Nanjing210093 China The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across various applications. The ability to model complex data distributions and generate high-quality samples has made GDMs particularly effective in tasks such as image generation and reinforcement learning. Furthermore, their iterative nature, which involves a series of noise addition and denoising steps, is a powerful and unique approach to learning and generating data. This paper serves as a comprehensive tutorial on applying GDMs in network optimization tasks. We delve into the strengths of GDMs, emphasizing their wide applicability across various domains, such as vision, text, and audio generation. We detail how GDMs can be effectively harnessed to solve complex optimization problems inherent in networks. The paper first provides a basic background of GDMs and their applications in network optimization. This is followed by a series of case studies, showcasing the integration of GDMs with Deep Reinforcement Learning (DRL), incentive mechanism design, Semantic Communications (SemCom), Internet of Vehicles (IoV) networks, etc. These case studies underscore the practicality and efficacy of GDMs in real-world scenarios, offering insights into network design. We conclude with a discussion on potential future directions for GDM research and applications, providing major insights into how they can continue to shape the future of network optimization. © 2023, CC BY.

关键词： Reinforcement learning

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