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  1. Book ; Online: A data-driven kinetic model for opinion dynamics with social network contacts

    Albi, Giacomo / Calzola, Elisa / Dimarco, Giacomo

    2023  

    Abstract: Opinion dynamics is an important and very active area of research that delves into the complex processes through which individuals form and modify their opinions within a social context. The ability to comprehend and unravel the mechanisms that drive ... ...

    Abstract Opinion dynamics is an important and very active area of research that delves into the complex processes through which individuals form and modify their opinions within a social context. The ability to comprehend and unravel the mechanisms that drive opinion formation is of great significance for predicting a wide range of social phenomena such as political polarization, the diffusion of misinformation, the formation of public consensus, and the emergence of collective behaviors. In this paper, we aim to contribute to that field by introducing a novel mathematical model that specifically accounts for the influence of social media networks on opinion dynamics. With the rise of platforms such as Twitter, Facebook, and Instagram and many others, social networks have become significant arenas where opinions are shared, discussed, and potentially altered. To this aim after an analytical construction of our new model and through incorporation of real-life data from Twitter, we calibrate the model parameters to accurately reflect the dynamics that unfold in social media, showing in particular the role played by the so-called influencers in driving individual opinions towards predetermined directions.
    Keywords Physics - Physics and Society ; Mathematics - Numerical Analysis
    Subject code 612 ; 300
    Publishing date 2023-07-03
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article: Mean-Field Selective Optimal Control via Transient Leadership.

    Albi, Giacomo / Almi, Stefano / Morandotti, Marco / Solombrino, Francesco

    Applied mathematics and optimization

    2022  Volume 85, Issue 2, Page(s) 9

    Abstract: A mean-field selective optimal control problem of multipopulation dynamics via transient leadership is considered. The agents in the system are described by their spatial position and their probability of belonging to a certain population. The dynamics ... ...

    Abstract A mean-field selective optimal control problem of multipopulation dynamics via transient leadership is considered. The agents in the system are described by their spatial position and their probability of belonging to a certain population. The dynamics in the control problem is characterized by the presence of an activation function which tunes the control on each agent according to the membership to a population, which, in turn, evolves according to a Markov-type jump process. In this way, a hypothetical policy maker can select a restricted pool of agents to act upon based, for instance, on their time-dependent influence on the rest of the population. A finite-particle control problem is studied and its mean-field limit is identified via
    Language English
    Publishing date 2022-04-13
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1398298-9
    ISSN 1432-0606 ; 0095-4616
    ISSN (online) 1432-0606
    ISSN 0095-4616
    DOI 10.1007/s00245-022-09837-4
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  3. Article ; Online: Modelling lockdown measures in epidemic outbreaks using selective socio-economic containment with uncertainty.

    Albi, Giacomo / Pareschi, Lorenzo / Zanella, Mattia

    Mathematical biosciences and engineering : MBE

    2021  Volume 18, Issue 6, Page(s) 7161–7190

    Abstract: After the introduction of drastic containment measures aimed at stopping the epidemic contagion from SARS-CoV2, many governments have adopted a strategy based on a periodic relaxation of such measures in the face of a severe economic crisis caused by ... ...

    Abstract After the introduction of drastic containment measures aimed at stopping the epidemic contagion from SARS-CoV2, many governments have adopted a strategy based on a periodic relaxation of such measures in the face of a severe economic crisis caused by lockdowns. Assessing the impact of such openings in relation to the risk of a resumption of the spread of the disease is an extremely difficult problem due to the many unknowns concerning the actual number of people infected, the actual reproduction number and infection fatality rate of the disease. In this work, starting from a SEIRD compartmental model with a social structure based on the age of individuals and stochastic inputs that account for data uncertainty, the effects of containment measures are introduced via an optimal control problem dependent on specific social activities, such as home, work, school, etc. Through a short time horizon approximation, we derive models with multiple feedback controls depending on social activities that allow us to assess the impact of selective relaxation of containment measures in the presence of uncertain data. After analyzing the effects of the various controls, results from different scenarios concerning the first wave of the epidemic in some major countries, including Germany, France, Italy, Spain, the United Kingdom and the United States, are presented and discussed. Specific contact patterns in the home, work, school and other locations have been considered for each country. Numerical simulations show that a careful strategy of progressive relaxation of containment measures, such as that adopted by some governments, may be able to keep the epidemic under control by restarting various productive activities.
    MeSH term(s) COVID-19 ; Communicable Disease Control ; Disease Outbreaks/prevention & control ; Humans ; RNA, Viral ; SARS-CoV-2 ; Socioeconomic Factors ; Uncertainty
    Chemical Substances RNA, Viral
    Language English
    Publishing date 2021-12-09
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2265126-3
    ISSN 1551-0018 ; 1551-0018
    ISSN (online) 1551-0018
    ISSN 1551-0018
    DOI 10.3934/mbe.2021355
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Control with uncertain data of socially structured compartmental epidemic models.

    Albi, Giacomo / Pareschi, Lorenzo / Zanella, Mattia

    Journal of mathematical biology

    2021  Volume 82, Issue 7, Page(s) 63

    Abstract: The adoption of containment measures to reduce the amplitude of the epidemic peak is a key aspect in tackling the rapid spread of an epidemic. Classical compartmental models must be modified and studied to correctly describe the effects of forced ... ...

    Abstract The adoption of containment measures to reduce the amplitude of the epidemic peak is a key aspect in tackling the rapid spread of an epidemic. Classical compartmental models must be modified and studied to correctly describe the effects of forced external actions to reduce the impact of the disease. The importance of social structure, such as the age dependence that proved essential in the recent COVID-19 pandemic, must be considered, and in addition, the available data are often incomplete and heterogeneous, so a high degree of uncertainty must be incorporated into the model from the beginning. In this work we address these aspects, through an optimal control formulation of a socially structured epidemic model in presence of uncertain data. After the introduction of the optimal control problem, we formulate an instantaneous approximation of the control that allows us to derive new feedback controlled compartmental models capable of describing the epidemic peak reduction. The need for long-term interventions shows that alternative actions based on the social structure of the system can be as effective as the more expensive global strategy. The timing and intensity of interventions, however, is particularly relevant in the case of uncertain parameters on the actual number of infected people. Simulations related to data from the first wave of the recent COVID-19 outbreak in Italy are presented and discussed.
    MeSH term(s) COVID-19/epidemiology ; COVID-19/prevention & control ; COVID-19/transmission ; Computer Simulation ; Humans ; Italy/epidemiology ; Models, Statistical ; Pandemics/prevention & control ; Pandemics/statistics & numerical data ; SARS-CoV-2/pathogenicity ; Social Factors ; Uncertainty
    Language English
    Publishing date 2021-05-23
    Publishing country Germany
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 187101-8
    ISSN 1432-1416 ; 0303-6812
    ISSN (online) 1432-1416
    ISSN 0303-6812
    DOI 10.1007/s00285-021-01617-y
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1495: Show issues Location:
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    Jg. 1995 - 2021: Lesesall (1.OG)
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  5. Book: Asymptotic preserving time-discretization of optimal control problems for the Goldstein-Taylor model

    Albi, Giacomo

    (Bericht / Institut für Geometrie und Praktische Mathematik der Rheinisch-Westfälischen Technischen Hochschule Aachen ; Nr. 371)

    2013  

    Institution Technische Hochschule Aachen / Institut für Geometrie und Praktische Mathematik
    Author's details Institut für Geometrie und Praktische Mathematik der RWTH Aachen. Giacomo Albi
    Series title Bericht / Institut für Geometrie und Praktische Mathematik der Rheinisch-Westfälischen Technischen Hochschule Aachen ; Nr. 371
    Language English
    Size 18 S., 30 cm
    Publisher Inst. für Geometrie und Praktische Mathematik
    Publishing place Aachen
    Document type Book
    Database Library catalogue of the German National Library of Science and Technology (TIB), Hannover

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  6. Book ; Online: Gradient-augmented Supervised Learning of Optimal Feedback Laws Using State-dependent Riccati Equations

    Albi, Giacomo / Bicego, Sara / Kalise, Dante

    2021  

    Abstract: A supervised learning approach for the solution of large-scale nonlinear stabilization problems is presented. A stabilizing feedback law is trained from a dataset generated from State-dependent Riccati Equation solves. The training phase is enriched by ... ...

    Abstract A supervised learning approach for the solution of large-scale nonlinear stabilization problems is presented. A stabilizing feedback law is trained from a dataset generated from State-dependent Riccati Equation solves. The training phase is enriched by the use gradient information in the loss function, which is weighted through the use of hyperparameters. High-dimensional nonlinear stabilization tests demonstrate that real-time sequential large-scale Algebraic Riccati Equation solves can be substituted by a suitably trained feedforward neural network.
    Keywords Mathematics - Optimization and Control ; Computer Science - Machine Learning ; Electrical Engineering and Systems Science - Systems and Control
    Publishing date 2021-03-06
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Book ; Online: Efficient stochastic algorithms for agent-based models with predator-prey dynamics

    Albi, Giacomo / Chignola, Roberto / Ferrarese, Federica

    2021  

    Abstract: Experiments in predator-prey systems show the emergence of long-term cycles. Deterministic model typically fails in capturing these behaviors, which emerge from the microscopic interplay of individual based dynamics and stochastic effects. However, ... ...

    Abstract Experiments in predator-prey systems show the emergence of long-term cycles. Deterministic model typically fails in capturing these behaviors, which emerge from the microscopic interplay of individual based dynamics and stochastic effects. However, simulating stochastic individual based models can be extremely demanding, especially when the sample size is large. Hence we propose an alternative simulation approach, whose computation cost is lower than the one of the classic stochastic algorithms. First, we describe how starting from the individual description of predator-prey dynamics, it is possible to derive the mean-field equations for the homogeneous and heterogeneous space cases. Then, we see that the new approach is able to preserve the order and that it converges to the mean-field solutions as the sample size increases. We show how to simulate the dynamics with the new approach, performing different numerical experiments in order to test its efficiency. Finally, we analyze the different nature of oscillations between mean-field and stochastic simulations underling how the new algorithm can be useful also to study the collective behaviours at the population level.
    Keywords Mathematics - Numerical Analysis
    Subject code 612
    Publishing date 2021-07-29
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Book ; Online: Kinetic modelling of epidemic dynamics

    Albi, Giacomo / Bertaglia, Giulia / Boscheri, Walter / Dimarco, Giacomo / Pareschi, Lorenzo / Toscani, Giuseppe / Zanella, Mattia

    social contacts, control with uncertain data, and multiscale spatial dynamics

    2021  

    Abstract: In this survey we report some recent results in the mathematical modeling of epidemic phenomena through the use of kinetic equations. We initially consider models of interaction between agents in which social characteristics play a key role in the spread ...

    Abstract In this survey we report some recent results in the mathematical modeling of epidemic phenomena through the use of kinetic equations. We initially consider models of interaction between agents in which social characteristics play a key role in the spread of an epidemic, such as the age of individuals, the number of social contacts, and their economic wealth. Subsequently, for such models, we discuss the possibility of containing the epidemic through an appropriate optimal control formulation based on the policy maker's perception of the progress of the epidemic. The role of uncertainty in the data is also discussed and addressed. Finally, the kinetic modeling is extended to spatially dependent settings using multiscale transport models that can characterize the impact of movement dynamics on epidemic advancement on both one-dimensional networks and realistic two-dimensional geographic settings.
    Keywords Quantitative Biology - Populations and Evolution ; Mathematics - Optimization and Control ; Nonlinear Sciences - Adaptation and Self-Organizing Systems
    Subject code 612
    Publishing date 2021-10-01
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: Control with uncertain data of socially structured compartmental epidemic models

    Albi, Giacomo / Pareschi, Lorenzo / Zanella, Mattia

    medRxiv

    Abstract: The adoption of containment measures to reduce the amplitude of the epidemic peak is a key aspect in tackling the rapid spread of an epidemic. Classical compartmental models must be modified and studied to correctly describe the effects of forced ... ...

    Abstract The adoption of containment measures to reduce the amplitude of the epidemic peak is a key aspect in tackling the rapid spread of an epidemic. Classical compartmental models must be modified and studied to correctly describe the effects of forced external actions to reduce the impact of the disease. In addition, data are often incomplete and heterogeneous, so a high degree of uncertainty must naturally be incorporated into the models. In this work we address both these aspects, through an optimal control formulation of the epidemiological model in presence of uncertain data. After the introduction of the optimal control problem, we formulate an instantaneous approximation of the control that allows us to derive new feedback controlled compartmental models capable of describing the epidemic peak reduction. The need for long-term interventions shows that alternative actions based on the social structure of the system can be as effective as the more expensive global strategy. The importance of the timing and intensity of interventions is particularly relevant in the case of uncertain parameters on the actual number of infected people. Simulations related to data from the recent COVID-19 outbreak in Italy are presented and discussed.
    Keywords covid19
    Language English
    Publishing date 2020-05-02
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2020.04.27.20081885
    Database COVID19

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  10. Article ; Online: Very-long-chain fatty acid sphingomyelin in nuclear lipid microdomains of hepatocytes and hepatoma cells: can the exchange from C24:0 to C16:0 affect signal proteins and vitamin D receptor?

    Lazzarini, Andrea / Macchiarulo, Antonio / Floridi, Alessandro / Coletti, Alice / Cataldi, Samuela / Codini, Michela / Lazzarini, Remo / Bartoccini, Elisa / Cascianelli, Giacomo / Ambesi-Impiombato, Francesco Saverio / Beccari, Tommaso / Curcio, Francesco / Albi, Elisabetta

    Molecular biology of the cell

    2015  Volume 26, Issue 13, Page(s) 2418–2425

    Abstract: Lipid microdomains localized in the inner nuclear membrane are considered platforms for active chromatin anchoring. Stimuli such as surgery, vitamin D, or glucocorticoid drugs influence their gene expression, DNA duplication, and RNA synthesis. In this ... ...

    Abstract Lipid microdomains localized in the inner nuclear membrane are considered platforms for active chromatin anchoring. Stimuli such as surgery, vitamin D, or glucocorticoid drugs influence their gene expression, DNA duplication, and RNA synthesis. In this study, we used ultrafast liquid chromatography-tandem mass spectrometry to identify sphingomyelin (SM) species coupled with immunoblot analysis to comprehensively map differences in nuclear lipid microdomains (NLMs) purified from hepatocytes and hepatoma cells. We showed that NLMs lost saturated very-long-chain fatty acid (FA; C24:0) SM in cancer cells and became enriched in long-chain FA (C16:0) SM. We also found that signaling proteins, such as STAT3, Raf1, and PKCζ, were increased and vitamin D receptor was reduced in cancer cells. Because recent researches showed a shift in sphingolipid composition from C24:0 to C16:0 in relation to cell life, we performed a comparative analysis of properties among C16:0 SM, C24:0 SM, and cholesterol. Our results led us to hypothesize that the enrichment of C16:0 SM could determine enhanced dynamic properties of NLMs in cancer cells with an increased shuttling of protein signaling molecules.
    MeSH term(s) Animals ; Cholesterol/metabolism ; Fatty Acids/metabolism ; Female ; Hepatocytes/metabolism ; Intracellular Signaling Peptides and Proteins/metabolism ; Lipid Metabolism ; Liver Neoplasms, Experimental/metabolism ; Male ; Membrane Microdomains/metabolism ; Nuclear Envelope/metabolism ; Rats ; Rats, Sprague-Dawley ; Receptors, Calcitriol/metabolism ; Sphingolipids/metabolism ; Sphingomyelins/metabolism
    Chemical Substances Fatty Acids ; Intracellular Signaling Peptides and Proteins ; Receptors, Calcitriol ; Sphingolipids ; Sphingomyelins ; Cholesterol (97C5T2UQ7J)
    Language English
    Publishing date 2015-07-01
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1098979-1
    ISSN 1939-4586 ; 1059-1524
    ISSN (online) 1939-4586
    ISSN 1059-1524
    DOI 10.1091/mbc.E15-04-0229
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 2853: Show issues Location:
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    Zs.MO 410: Show issues

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