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A I I E Transactions 2024年第7期56卷

作者： Xiaoyan Xu Suresh P. Sethi Sai-Ho Chung Tsan-Ming Choi a Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong b Jindal School of Management The University of Texas at Dallas Richardson TX USA c Centre for Supply Chain Research University of Liverpool Management School Liverpool UK

In the digital age, operations can be improved by a wise use of information and technological tools. During the COVID-19 pandemic, governments faced various choices of vaccines possessing different efficacy and availability levels at different time points. In this article, we consider a two-stage vaccine ordering problem of a government from a first and only supplier in the first stage, and either the same supplier or a new second supplier in the second stage. Between the two stages, potential demand information for the vaccine is collected to update the forecast. Using dynamic programming, we derive the government’s optimal vaccine ordering policy. We find that the government should select its vaccine supplier based on the disease’s infection rate in the society. When the infection rate is low, the government should order nothing at the first stage and order from the supplier with a higher efficacy level at the second stage. When the disease’s infection rate is high, the government should order vaccines at the first stage and switch to the other supplier with a lower efficacy level at the second stage. We extend our model to examine (i) the value of blockchain adoption and (ii) the impact of vaccines’ side effects.

关键词： Vaccine supply chain two-stage ordering information updating social welfare blockchain COVID-19

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Dramatic effect of extreme rainfall event and storm on microbial community dynamics in a subtropical coastal region

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Science of the Total Environment 2025年 964卷 178560页

作者： Olivia, Madeline Annabel, Clara Natalie Chen, Patrichka Wei-Yi Hsieh, Chih-hao Chang, Feng-Hsun Ho, Pei-Chi Chien, Chia-Te Chao, Chien-Fu Mukhanov, Vladimir Tsai, An-Yi Institute of Marine Environment and Ecology National Taiwan Ocean University Keelung202-24 Taiwan Doctoral Degree Program in Ocean Resource and Environmental Changes National Taiwan Ocean University Keelung202-24 Taiwan Center of Excellence for the Oceans National Taiwan Ocean University Keelung202-24 Taiwan Institute of Oceanography National Taiwan University Taipei10617 Taiwan Department of Bioenvironmental Systems Engineering National Taiwan University Taipei10617 Taiwan A.O. Kovalevsky Institute of Biology of the Southern Seas Russian Academy of Sciences Sevastopol299011 Russia Laboratory of Marine Ecosystems Institute for Advanced Research Sevastopol State University Sevastopol299053 Russia

Extreme weather events, such as heavy rainfall and typhoons, are becoming more frequent due to climate change and can significantly impact coastal microbial communities. This study examines the short-term alterations in microbial food webs—viruses, bacteria, picophytoplankton, nanoflagellates, ciliates, and diatom—following Typhoon Krathon in Taiwan's coastal waters in October 2024. Daily in situ sampling revealed a significant post-typhoon increased in viral, nanoflagellate, and Synechococcus spp. abundance. Furthermore, viral, Synechococcus spp., and nanoflagellate abundance increased by approximately 4.2 to 12.8-fold, 33.3 to 160 fold, and 0.5 to 9.4 fold in response to these weather events, compared to periods pre-typhoon, respectively. Modified dilution experiments showed that, before the typhoon, nanoflagellate grazing was the major cause of bacterial mortality, while viral lysis was the main cause of Synechococcus spp. mortality. Post-typhoon, there was a notable shift, with nanoflagellate grazing increasing mortality rates of bacteria and Synechococcus spp., suggesting that grazing became the dominant top-down control mechanism after the disturbance. Our findings suggest that extreme weather events shift microbial mortality dynamics, increasing the role of grazing in controlling microbial populations, with potential implications for carbon cycling in coastal ecosystems. © 2025 Elsevier B.V.

关键词： Tropical cyclone

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DTCMS: Dynamic traffic congestion management in Social Internet of Vehicles (SIoV)

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Internet of Things (Netherlands) 2021年 16卷

作者： Roopa, M.S. Ayesha Siddiq, S. Buyya, Rajkumar Venugopal, K.R. Iyengar, S.S. Patnaik, L.M. Department of Computer Science and Engineering University Visvesvaraya College of Engineering Bangalore University Bengaluru 560-001 India Cloud Computing and Distributed Systems Laboratory School of Computing and Information Systems University of Melbourne Melbourne 3053 VIC Australia Bangalore University Bengaluru 560-001 India Department of Computer Science and Engineering Florida International University Miami 33199 FL United States Consciousness Studies Program National Institute of Advanced Studies Indian Institute of Science Bengaluru 560-012 India

With the augmentation of traffic exponentially, we observe that traffic congestion does not guarantee road safety or enhance the driving experience. In the recent past, Social Internet of Vehicles (SIoV), a social network paradigm permits social relationships among every vehicle in the network or with any road infrastructure to render a radically useful environment. SIoV is beneficial for the drivers, in improving road safety, avoiding mishaps, and providing a friendly-driving experience. In this paper, we propose a traffic scheduling algorithm to gain the maximum throughput for the flow of vehicles at a road intersection with the formation of social relationships among the vehicles and with the Road Side Units (RSUs). The algorithm estimates the flow rate of vehicles for lanes at the intersections exploiting the volume of traffic moving through the given road. A condition matrix is designed for the consistent movement of traffic considering different routes on the road segments. Social relationships are devised on various aspects of travel needs for a safe, agile, and better driving experience. Simulation results illustrate the efficacy of the proposed scheme with high traffic throughput, service rate and reduce the total travelling time, delay time, and average waiting time in comparison with Dynamic Throughput Maximization Framework and Adaptive Traffic Control Algorithm. © 2020 Elsevier B.V.

关键词： Dynamic traffic control Social Internet of Vehicles (SIoV) Social relationships Traffic congestion management

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How Microbes Shape Their Communities? A Microbial Community Model Based on Functional Genes

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Genomics, Proteomics & Bioinformatics 2019年第1期17卷 91-105页

作者： Xiaoqing Jiang Xin Li Longshu Yang Chunhong Liu Qi Wang Weilai Chi Huaiqiu Zhu State Key Laboratory for Turbulence and Complex Systems Department of Biomedical Engineering College of Engineering Peking University Center for Quantitative Biology Peking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Biological (PTN) PhD Program and College of Life Sciences Peking University Center for Protein Science Peking University

Exploring the mechanisms of maintaining microbial community structure is important to understand biofilm development or microbiota dysbiosis. In this paper, we propose a functional gene-based composition prediction(FCP) model to predict the population structure composition within a microbial community. The model predicts the community composition well in both a low-complexity community as acid mine drainage(AMD) microbiota, and a complex community as human gut microbiota. Furthermore, we define community structure shaping(CSS) genes as functional genes crucial for shaping the microbial community. We have identified CSS genes in AMD and human gut microbiota samples with FCP model and find that CSS genes change with the conditions. Compared to essential genes for microbes, CSS genes are significantly enriched in the genes involved in mobile genetic elements, cell motility, and defense mechanisms, indicating that the functions of CSS genes are focused on communication and strategies in response to the environment factors. We further find that it is the minority, rather than the majority, which contributes to maintaining community structure. Compared to health control samples, we find that some functional genes associated with metabolism of amino acids, nucleotides, and lipopolysaccharide are more likely to be CSS genes in the disease group. CSS genes may help us to understand critical cellular processes and be useful in seeking addable gene circuitries to maintain artificial self-sustainable communities. Our study suggests that functional genes are important to the assembly of microbial communities.

关键词： Metagenomics Dynamics model Community structure Acid mine drainage Human gut microbiota

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Identification of reference multi criteria domain model -Production line optimization case study 24

Identification of reference multi criteria domain model -Pro...

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24th KES International Conference on Knowledge-Based and Intelligent Information and engineering systems, KES 2020

作者： Rymaszewski, Szymon Watróbski, Jaroslaw Karczmarczyk, Artur Department of Information Systems Engineering Faculty of Economics Finance and Management University of Szczecin Mickiewicza 64 Szczecin71-101 Poland Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Zolnierska 49 Szczecin71-210 Poland

The methods of multi-criteria decision analysis are widely used for problems of selecting the best solution or ordering their sets. In the vast majority of cases, solving multi-criteria decision-making problems focuses on finding solutions for a given set of alternatives. When, for one or more decisional variants, the values of their attributes change, or a new alternative for assessment appears, the problem occurs. Therefore, in this paper, we focus on identifying the full decision-making model in the issue related to the study case of production line optimization. In this work, the Characteristic Objects METhod (COMET) has been applied. In effect, it identifies the full decision-making model. The decision problem has been identified, taking into account six decision criteria, and its operation has been used in organizing four decision alternatives. © 2020 The Authors. Published by Elsevier B.V.

关键词： Decision making

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Inertial Microfluidic-Assisted Rapid Detection of Chemical Contaminant in Foods Using Quantum Dots-Based Molecular Imprinting Sensor

SSRN

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SSRN 2023年

作者： Feng, Shaolong Lin, Yang Xu, Jie Lu, Xiaonan Food Nutrition and Health Program Faculty of Land and Food Systems The University of British Columbia VancouverBCV6T 1Z4 Canada Department of Food Science and Agricultural Chemistry McGill University Macdonald Campus 21111 Lakeshore Road Sainte-Anne-de-BellevueQCH9X 3V9 Canada Department of Mechanical and Industrial Engineering University of Illinois at Chicago ChicagoIL60607 United States University of Rhode Island United States

Integration of sample pretreatment, separation and detection in simple steps for food chemical contaminant analysis is challenging due to the complexity of food matrices. A novel analytical approach of using quantum dots-based molecular imprinting fluorescence sensor (QDs@MIPs) combined with inertial separation microfluidic device for separation and detection of enrofloxacin is presented in this study. The microfluidic device was designed based on laminar flow principle combined with Dean-coupled inertial migration of particles in spiral microchannels. Micron-sized QDs@MIPs sensing particles were synthesized for selective separation and sensitive detection of enrofloxacin. Separation of QDs@MIPs was achieved via parallel migration from the original suspension solution to another buffer solution in the same spiral microchannel with a high separation efficiency of 97.7±1.6%. Fluorescence intensity of QDs@MIPs was quenched in the presence of enrofloxacin and showed a linearity in the range of 0.1-50 µg/mL with limit of detection of 0.059 µg/mL. On-chip analyses were performed to detect enrofloxacin in both standard samples and contaminated swine muscle. This microfluidic-assisted fluorescence sensing system provides a solution to integrate sample pretreatment, separation and detection together to realize rapid analysis of food contaminants with high selectivity and sensitivity. © 2023, The Authors. All rights reserved.

关键词： Microchannels

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Entropy-Based Characterization of Influence Pathways in Traditional and Social Media

Entropy-Based Characterization of Influence Pathways in Trad...

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International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom)

作者： Ozlem Ozmen Garibay Niloofar Yousefi Kevin Aslett Jacopo Baggio Erik Hemberg Chathura Jayalath Alexander Mantzaris Bruce Miller Una-May O’Reilly William Rand Chathurani Senevirathna Ivan Garibay Industrial Engineering & Management Systems University of Central Florida Orlando FL USA School of Politics Security and International Affairs University of Central Florida Orlando FL USA Computer Science & Artificial Intelligence Lab Massachusetts Institute of Technology Cambridge MA USA Statistics & Data Science Department University of Central Florida Orlando FL USA Poole School of Management North Carolina State University Raleigh NC USA

Despite much work on social media, analysis of individual influence campaigns, messages, and platforms, we lack the tools and techniques and fundamental research to effectively understand the information flows and their effects on the dynamics of the entire information ecosystem. For example, how information is amplified or dampened as it moves from one online community to another, how information is spinned or framed into narratives that favor or malign viewpoints organically or by foreign actors, how disinformation flows from fringe to mainstream communities, etc. We postulate that the information ecosystem is an attention economy, and that influence-the ability to gather attention towards a particular message or messages- is its currency. As a result, we model the information ecosystem as a complex network of influences flowing between actors, communities and platforms. This paper advocate for the use of information-theoretic entropic methods to model and characterize this complex network of influences over time: Influence Cascades Ecosystem (ICE). We envision leveraging the concept of influence cascades in conjunction with a novel geopolitical news-centric model of the information ecosystem in order to better understand the influence pathways by which various types of information (new articles from trusted, untrusted, fringe or mainstream sources) propagate across the social and traditional hybrid media environment.

关键词： Social networking (online) Ecosystems Collaboration Complex networks Media Internet Currencies

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A multiagent framework for coordinating industrial symbiotic networks 21

A multiagent framework for coordinating industrial symbiotic...

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21st Workshop "From Objects to Agents", WOA 2020

作者： Yazdanpanah, Vahid Yazan, Devrim M. Zijm, Henk M. Research Group School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom Department Industrial Engineering and Business Information Systems Faculty of Behavioural Management and Social Sciences University of Twente Enschede7500 AE Netherlands

We present a formal multiagent framework for coordinating a class of collaborative industrial practices called "Industrial Symbiotic Networks (ISNs)" as cooperative games. The game-theoretic formulation of ISNs enables systematic reasoning about what we call the ISN implementation problem. Specifically, the characteristics of ISNs may lead to the inapplicability of standard fair and stable benefit allocation methods. Inspired by realistic ISN scenarios and following the literature on normative multiagent systems, we consider regulations and normative socio-economic policies as coordination instruments that in combination with ISN games resolve the situation. In this multiagent system, employing Marginal Contribution Nets (MC-Nets) as rule-based cooperative game representations foster the combination of regulations and ISN games with no loss in expressiveness. We develop algorithmic methods for generating regulations that ensure the implementability of ISNs and as a policy support, present the policy requirements that guarantee the implementability of desired ISNs in a balanced-budget way. © 2020 Copyright for this paper by its authors.

关键词： Multi agent systems

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Genome and clonal hematopoiesis stability contrasts with immune,cfDNA,mitochondrial,and telomere length changes during short duration spaceflight

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Precision Clinical Medicine 2024年第1期7卷 1-13页

作者： J.Sebastian Garcia-Medina Karolina Sienkiewicz S.Anand Narayanan Eliah G.Overbey Kirill Grigorev Krista A.Ryon Marissa Burke Jacqueline Proszynski Braden Tierney Caleb M.Schmidt Nuria Mencia-Trinchant Remi Klotz Veronica Ortiz Jonathan Foox Christopher Chin Deena Najjar Irina Matei Irenaeus Chan Carlos Cruchaga Ashley Kleinman JangKeun Kim Alexander Lucaci Conor Loy Omary Mzava Iwijn De Vlaminck Anvita Singaraju Lynn E.Taylor Julian C.Schmidt Michael A.Schmidt Kelly Blease Juan Moreno Andrew Boddicker Junhua Zhao Bryan Lajoie Andrew Altomare Semyon Kruglyak Shawn Levy Min Yu Duane C.Hassane Susan M.Bailey Kelly Bolton Jaime Mateus Christopher E.Mason Department of Physiology and Biophysics Weill Cornell MedicineCornell UniversityNew YorkNY 10021USA The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine Weill Cornell MedicineNew YorkNY 10021USA Department of Immunology Weill Cornell MedicineCornell UniversityNew YorkNY 10021USA Department of Stem Cell Biology and Regenerative Medicine Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCA 90033USA Space Exploration Technologies Corporation HawthomeCA 90250USA Sovaris Aerospace BoulderCO 80302USA Advanced Pattern Analysis&Human Performance Group BoulderCO 80302USA Children's Cancer and Blood Foundation Laboratories Departments of Pediatrics and Cell and Developmental BiologyDrukier Institute for Children's HealthMeyer Cancer CenterWeill Cornell MedicineNew YorkNY 10021USA Meyer Cancer Center Weill Cornell MedicineNew YorkNY 10065USA Department of Nutrition and Integrative Physiology Florida State UniversityTallahasseeFL 32306USA Department of Systems Engineering Colorado State UniversityFort CollinsCO 80523USA Element Biosciences San DiegoCA 10055USA Department of Environmental and Radiological Health Sciences Colorado State UniversityFort CollinsCO 80523USA Cell and Molecular Biology Program Colorado State UniversityFort CollinsCO 80523USA BioAstra Inc New YorkNYUSA Washington University St Louis Oncology Division St.LouisMO 63100USA Meinig School of Biomedical Engineering Cornell UniversityIthacaNY 14853USA The Feil Family Brain and Mind Research Institute Weill Cornell MedicineNY 10021USA WorldQuant Initiative for Quantitative Prediction Weill Cornell MedicineNew YorkNY 10021USA

Background The Inspiration4(I4)mission,the first all-civilian orbital flight mission,investigated the physiological effects of short-duration spaceflight through a multi-omic *** advances,there remains much to learn about human adaptation to spaceflight's unique challenges,including microgravity,immune system perturbations,and radiation *** To provide a detailed genetics analysis of the mission,we collected dried blood spots pre-,during,and post-flight for DNA *** length was measured by quantitative PCR,while whole genome and cfDNA sequencing provided insight into genomic stability and immune adaptations.A robust bioinformatic pipeline was used for data analysis,including variant calling to assess mutational *** Telomere elongation occurred during spaceflight and shortened after return to ***-free DNA analysis revealed increased immune cell signatures *** significant clonal hematopoiesis of indeterminate potential(CHIP)or whole-genome instability was *** long-term gene expression changes across immune cells suggested cellular adaptations to the space environment persisting months *** Our findings provide valuable insights into the physiological consequences of short-duration spaceflight,with telomere dynamics and immune cell gene expression adapting to spaceflight and persisting after return to *** sequencing data will serve as a reference point for studying the early development of CHIP in astronauts,an understudied phenomenon as previous studies have focused on career *** study will serve as a reference point for future commercial and non-commercial spaceflight,low Earth orbit(LEO)missions,and deep-space exploration.

关键词： genomes clonal hematopoiesis stability immune mitochondria ribosomes spaceflight

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Improving the performance of AgCdF 3 -based perovskite solar cells using machine learning-driven adjustment of active layer and charge transport materials with SCAPS-1D

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Inorganic Chemistry Communications 2025年

作者： Avijit Ghosh Al Shahriar Zishan Mahbuba Moumita Yedluri Anil Kumar Anup Kumar Roy Siful Islam Shahan Ahmed Hasanur Zaman Anonto Asma Tabassum Happy Md. Shameem Ahsan H.A. Alrafai Abeer A. Hassan Department of Electrical and Electronic Engineering Begum Rokeya University Rangpur 5400 Bangladesh Department of Electrical and Electronics Engineering American International University – Bangladesh 408/1 Kuratoli Road Kuril Dhaka 1229 Bangladesh Department of Mathematics Lamar University Beaumont TX 77705 USA Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai 602105 Tamil Nadu India Phillip M. Drayer Department of Electrical and Computer Engineering Lamar University TX USA Master of Science in Management Information Systems College of Business Lamar University TX USA Master of Arts in Social Research & Data Analysis Montclair State University NJ USA Department of Industrial and Systems Engineering Lamar University Beaumont TX 77710 USA Department of Chemistry Faculty of Science King Khalid University PO Box 9004 Abha 61413 Saudi Arabia

This study investigates the possibility of combining inorganic substances—which act as absorbers, HTLs) in order to produce stable, effective PSCs. A ZnSe ETL, HTLs (MoS 2 , MoTe 2 , and CuI), and an AgCdF 3 perovskite absorber, comprise the suggested architecture for this study. This study examines the impact of metal contacts, doping density, interface defect densities, absorber thickness, HTL and ETL layers, and defect density on the output of a solar device using the SCAPS-1D model. The investigation of how temperature impacts the performance of the proposed PSC is another important aspect of the study. By integrating the MoS 2 /MoTe 2 /CuI layers as an HTL with the studied structure of Al/FTO/ZnSe/AgCdF 3 /HTL/Ni, the V OC climbed to 0.834/0.910/0.969 V, the J SC to 42.122/42.862/42.885 mA cm −2 , the PCE to 30.31/34.05/36.06 %, and the FF to 86.21/87.23/86.69 %. A machine learning model was created to forecast the solar cells’ performance metrics. The model precisely evaluates the importance of each parameter by utilizing SHAP values, providing important insights into their contributions. With an accuracy rate of around 83.75 %, machine learning predicted the performance matrix of the optimal solar cell under investigation. An affordable AgCdF 3 solar cell may be developed as a result of this study’s significant findings and practical design.

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