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Distillation optimization: Parameterized relationship between feed flow rate of a steady-state distillation column and heat duties of reboiler and condenser

Distillation optimization: Parameterized relationship betwee...

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作者： Sukin, Ivan Tsirlin, Anatoly Balunov, Alexander Starodumov, Ilya Complex Systems Department Ailamazyan Program Systems Institute of Russian Academy of Sciences Yaroslavl Oblast Russia Cybernetics Department Yaroslavl State Technical University Yaroslavl Russia Department of Theoretical and Mathematical Physics Laboratory of Multi-Scale Mathematical Modeling Ural Federal University Ekaterinburg Russia

The paper considers the problem of maximum efficiency for the system of distillation columns. Columns in such systems are connected in parallel or sequential way. The mixture being separated is assumed to be close to ideal one. Authors parameterize the relationship between feed flow rate and heat duties of a steady-state binary distillation column using two parameters: the reversible efficiency and the irreversibility coefficient. This relationship is later being used to solve the problems of optimal distribution of heat and feed flows within the system. The results obtained allow one to estimate minimum heat energy demand for distillation of the given feed flow, maximum performance, and efficiency of the system. © 2022 John Wiley & Sons, Ltd.

关键词： Distillation columns

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The context-specificity of virulence evolution revealed through evolutionary invasion analysis

arXiv

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arXiv 2023年

作者： Surasinghe, Sudam Kabengele, Ketty Turner, Paul E. Brandon Ogbunugafor, C. Department of Ecology and Evolutionary Biology Yale University New HavenCT06520 United States Public Health Modeling Unit Yale School of Public Health New HavenCT06510 United States Microbiology Program Yale School of Medicine New HavenCT06510 United States Santa Fe Institute Santa FeNM87501 United States Vermont Complex Systems Center University of Vermont BurlingtonVT05405 United States

Models are often employed to integrate knowledge about epidemics across scales and simulate disease dynamics. While these approaches have played a central role in studying the mechanics underlying epidemics, we lack ways to reliably predict how the relationship between virulence (the harm to hosts caused by an infection) and transmission will evolve in certain virus-host contexts. In this study, we invoke evolutionary invasion analysis-a method used to identify the evolution of uninvadable strategies in dynamical systems-to examine how the virulence-transmission dichotomy can evolve in models of virus infections defined by different natural histories. We reveal that peculiar ecologies drive different evolved relationships between virulence and transmission. Specifically, we discover patterns of virulence evolution between epidemics of various kinds (SARS-CoV-2 and hepatitis C virus) and that varying definitions of virulence alter our predictions for how viruses will evolve. We discuss the findings in light of contemporary conversations in the public health sector around the possibility of predicting virus evolution and in more extensive theoretical discussions involving virulence evolution in emerging infectious diseases. © 2023, CC BY-NC-ND.

关键词： Transmissions

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Taming cluster synchronization

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Chaos, Solitons & Fractals 2025年 199卷

作者： Cinzia Tomaselli Lucia Valentina Gambuzza Gui-Quan Sun Stefano Boccaletti Mattia Frasca Modeling and Engineering Risk and Complexity Program Scuola Superiore Meridionale Naples 80138 Italy Department of Electrical Electronics and Computer Science Engineering University of Catania Catania 95125 Italy Complex Systems Research Center Shanxi University Shanxi Taiyuan 030006 China Sino-Europe Complex Science Center North University of China Shanxi Taiyuan 030051 China Institute of Interdisciplinary Intelligent Science Ningbo Univ. of Technology Ningbo China CNR - Institute of Complex Systems Sesto Fiorentino I-50019 Italy

Synchronization is a widespread phenomenon observed across natural and artificial networked systems. It often manifests itself by clusters of units exhibiting coincident dynamics. These clusters are a direct consequence of the organization of the Laplacian matrix eigenvalues into spectral localized blocks. We show how the concept of spectral blocks can be leveraged to design straightforward yet powerful controllers able to fully manipulate cluster synchronization of a generic network, thus shaping at will its parallel functioning. Specifically, we demonstrate how to induce the formation of spectral blocks in networks where such structures would not exist, and how to achieve precise mastering over the synchronizability of individual clusters by dictating the sequence in which each of them enters or exits the synchronization stability region as the coupling strength varies. Our results underscore the pivotal role of cluster synchronization control in shaping the parallel operation of networked systems, thereby enhancing their efficiency and adaptability across diverse applications.

关键词： complex networks Dynamical systems Cluster synchronization Control Spectral blocks

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First principles investigations of the electronic and magnetic properties of RVO3 (R = Er, Ho, Y, Lu) vanadates

arXiv

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arXiv 2022年

作者： Jmal, Sohail Ait Balli, Sohail Ait Bouhani, Hamza Mounkachi, Omar AMEEC Team LERMA International University of Rabat Parc Technopolis Rocade de Rabat- Salé 11100 Morocco Complex Systems and Interactions Ecole Centrale Casablanca Morocco Laboratory of Condensed Matter and Interdisciplinary Sciences Department of Physics Faculty of Sciences Mohammed V University in Rabat PO Box 1014 Rabat Morocco Modeling Simulation & Data Analysis Program Mohammed VI Polytechnic University Ben Guerir43150 Morocco

In this paper, we investigate the influence of the rare earth element (R) on the physical properties of RVO3 (R = Er, Ho, Y, Lu). For this purpose, a theoretical work is reported in this study using ab initio method with the intent of enhancing our knowledge of the electronic, and magnetic properties of RVO3 (R = Er, Ho, Y, Lu) compounds. The electronic properties of these materials show the presence of Jahn-Teller effect, with a band gap of approximately 0.58eV, 1.57eV, 1.12eV, 1.28eV, for ErVO3, HoVO3, YVO3, LuVO3, respectively. The magnetic contribution of Ho, Er, and V atoms in HoVO3, and ErVO3 compounds was disentangled using X-ray magnetic circular dichroism (XMCD). The magnetic anisotropies of RVO3 with (R = Er, Ho, Y, Lu) are studied and analyzed using spin orbit coupling. We noticed an easy axis of magnetization along the c-direction with strong magneto-crystalline anisotropy energies for the non-magnetic rare earth elements (R = Lu, Y)VO3. For the magnetic rare earth elements, the easy and hard magnetization direction were found to be along b-axis and c-axis, and a- axis and c-axis for HoVO3, and ErVO3, respectively. This means that instead of the standard magnetization demagnetization process, large thermal effects can be obtained by spinning their single crystals in constant magnetic fields. The exchange coupling between (Ho-V) is also found to be greater than the other exchange interactions in HoVO3. Accordingly, a large conventional magnetocaloric effect could be created in HoVO3, since the Ho Ising moments experience a metamagnetic transition. However, the magnetocaloric effect (MCE) is expected to be lower in ErVO3 due to the weak (Er-V) exchange coupling. © 2022, CC BY.

关键词： Holmium compounds

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Impact of inter-city interactions on disease scaling

arXiv

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arXiv 2025年

作者： Loureiro, Nathalia A. Neto, Camilo R. Sutton, Jack Perc, Matjaž Ribeiro, Haroldo V. Complex Systems Modeling Program School of Arts Sciences and Humanities University of São Paulo São Paulo Brazil College of Science and Engineering University of Derby Markeaton Street DerbyDE22 3AW United Kingdom Faculty of Natural Sciences and Mathematics University of Maribor Koroška cesta 160 Maribor2000 Slovenia Community Healthcare Center Dr. Adolf Drolc Maribor Vošnjakova ulica 2 Maribor2000 Slovenia Complexity Science Hub Vienna Josefstädterstraße 39 Vienna1080 Austria Department of Physics Kyung Hee University 26 Kyungheedae-ro Dongdaemun-gu Seoul Korea Republic of Departamento de Física Universidade Estadual de Maringá PR Maringá87020-900 Brazil

Inter-city interactions are critical for the transmission of infectious diseases, yet their effects on the scaling of disease cases remain largely underexplored. Here, we use the commuting network as a proxy for inter-city interactions, integrating it with a general scaling framework to describe the incidence of seven infectious diseases across Brazilian cities as a function of population size and the number of commuters. Our models significantly outperform traditional urban scaling approaches, revealing that the relationship between disease cases and a combination of population and commuters varies across diseases and is influenced by both factors. Although most cities exhibit a less-than-proportional increase in disease cases with changes in population and commuters, more-than-proportional responses are also observed across all diseases. Notably, in some small and isolated cities, proportional rises in population and commuters correlate with a reduction in disease cases. These findings suggest that such towns may experience improved health outcomes and socioeconomic conditions as they grow and become more connected. However, as growth and connectivity continue, these gains diminish, eventually giving way to challenges typical of larger urban areas - such as socioeconomic inequality and overcrowding - that facilitate the spread of infectious diseases. Our study underscores the interconnected roles of population size and commuter dynamics in disease incidence while highlighting that changes in population size exert a greater influence on disease cases than variations in the number of commuters. Copyright © 2025, The Authors. All rights reserved.

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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A novel algorithm for describing population level trends in body weight

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Health 2012年第12期4卷 1514-1521页

作者： Azadeh Alimadad Carrie Matteson Warren L. Hare Ozge Karanfil Diane T. Finegood Department of Biomedical Physiology & Kinesiology Simon Fraser University Burnaby Canada Faculty of Health Sciences Simon Fraser University Burnaby Canada Modeling of Complex Social Systems Program Simon Fraser University Burnaby Canada Sloan School of Management MIT Cambridge USA

modeling population trends and predicting the impact of interventions to address obesity requires algorithms for predicting body weight status in the future. Predictions can be based on statistical consideration of different risk factors, or be an extrapolation of past and current trends. Despite the well known correlation between previous and future weight, individual weight history has not been used to predict future trends. We developed a novel population-level model to examine trends of different classes of body weight considering individual body weight histories from the National Longitudinal Survey of Youth (NLSY79). A subset of data used to assess the predictive ability of our proposed model with actual data. Our results confirm the importance of weight history in determining future weight status. Over 80% of individuals in a specific weight category (normal, overweight, obese) will stay in the same weight category after two years (except overweight females). The length of body weight stability was also found to be important. The probability of remaining normal weight increased with longer prior periods of being at a normal weight over 18 years (0.834 to 0.893). We demonstrate that an individual’s most probable weight class in the future is consistent with their maximal historical weight class.

关键词： Body Weight modeling Obesity

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