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See detailAlmost global convergence to practical synchronization in the generalized Kuramoto model on networks over the n-sphere
Markdahl, Johan UL; Proverbio, Daniele UL; Mi, La et al

in Communications Physics (2021), 4

From the flashing of fireflies to autonomous robot swarms, synchronization phenomena are ubiquitous in nature and technology. They are commonly described by the Kuramoto model that, in this paper, we ... [more ▼]

From the flashing of fireflies to autonomous robot swarms, synchronization phenomena are ubiquitous in nature and technology. They are commonly described by the Kuramoto model that, in this paper, we generalise to networks over n-dimensional spheres. We show that, for almost all initial conditions, the sphere model converges to a set with small diameter if the model parameters satisfy a given bound. Moreover, for even n, a special case of the generalized model can achieve phase synchronization with nonidentical frequency parameters. These results contrast with the standard n = 1 Kuramoto model, which is multistable (i.e., has multiple equilibria), and converges to phase synchronization only if the frequency parameters are identical. Hence, this paper shows that the generalized network Kuramoto models for n ≥ 2 displays more coherent and predictable behavior than the standard n = 1 model, a desirable property both in flocks of animals and for robot control. [less ▲]

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See detailModelling COVID-19 dynamics and potential for herd immunity by vaccination in Austria, Luxembourg and Sweden
Kemp, Francoise UL; Kemp, Francoise UL; Proverbio, Daniele UL et al

in Modelling COVID-19 dynamics and potential for herd immunity by vaccination in Austria, Luxembourg and Sweden (2021)

Against the COVID-19 pandemic, non-pharmaceutical interventions have been widely applied and vaccinations have taken off. The upcoming question is how the interplay between vaccinations and social ... [more ▼]

Against the COVID-19 pandemic, non-pharmaceutical interventions have been widely applied and vaccinations have taken off. The upcoming question is how the interplay between vaccinations and social measures will shape infections and hospitalizations. Hence, we extend the Susceptible-Exposed-Infectious-Removed (SEIR) model including these elements. We calibrate it to data of Luxembourg, Austria and Sweden until 15 December 2020. Sweden results having the highest fraction of undetected, Luxembourg of infected and all three being far from herd immunity in December. We quantify the level of social interaction, showing that a level around 1/3 of before the pandemic was still required in December to keep the effective reproduction number Refft below 1, for all three countries. Aiming to vaccinate the whole population within 1 year at constant rate would require on average 1,700 fully vaccinated people/day in Luxembourg, 24,000 in Austria and 28,000 in Sweden, and could lead to herd immunity only by mid summer. Herd immunity might not be reached in 2021 if too slow vaccines rollout speeds are employed. The model thus estimates which vaccination rates are too low to allow reaching herd immunity in 2021, depending on social interactions. Vaccination will considerably, but not immediately, help to curb the infection; thus limiting social interactions remains crucial for the months to come. [less ▲]

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See detailDynamical SPQEIR model assesses the effectiveness of non-pharmaceutical interventions against COVID-19 epidemic outbreaks.
Proverbio, Daniele UL; Kemp, Francoise UL; Magni, Stefano UL et al

in PloS one (2021), 16(5), 0252019

Against the current COVID-19 pandemic, governments worldwide have devised a variety of non-pharmaceutical interventions to mitigate it. However, it is generally difficult to estimate the joint impact of ... [more ▼]

Against the current COVID-19 pandemic, governments worldwide have devised a variety of non-pharmaceutical interventions to mitigate it. However, it is generally difficult to estimate the joint impact of different control strategies. In this paper, we tackle this question with an extended epidemic SEIR model, informed by a socio-political classification of different interventions. First, we inquire the conceptual effect of mitigation parameters on the infection curve. Then, we illustrate the potential of our model to reproduce and explain empirical data from a number of countries, to perform cross-country comparisons. This gives information on the best synergies of interventions to control epidemic outbreaks while minimising impact on socio-economic needs. For instance, our results suggest that, while rapid and strong lockdown is an effective pandemic mitigation measure, a combination of social distancing and early contact tracing can achieve similar mitigation synergistically, while keeping lower isolation rates. This quantitative understanding can support the establishment of mid- and long-term interventions, to prepare containment strategies against further outbreaks. This paper also provides an online tool that allows researchers and decision makers to interactively simulate diverse scenarios with our model. [less ▲]

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See detailCOVID-19 Crisis Management in Luxembourg: Insights from an Epidemionomic Approach
Burzynski; Machado, Joel; Aalto, Atte UL et al

in Economics & Human Biology (2020), 43

We develop an epidemionomic model that jointly analyzes the health and economic responses to the COVID-19 crisis and to the related containment and public health policy measures implemented in Luxembourg ... [more ▼]

We develop an epidemionomic model that jointly analyzes the health and economic responses to the COVID-19 crisis and to the related containment and public health policy measures implemented in Luxembourg. The model has been used to produce nowcasts and forecasts at various stages of the crisis. We focus here on two key moments in time, namely the deconfinement period following the first lockdown, and the onset of the second wave. In May 2020, we predicted a high risk of a second wave that was mainly explained by the resumption of social life, low participation in large-scale testing, and reduction in teleworking practices. Simulations conducted 5 months later reveal that managing the second wave with moderately coercive measures has been epidemiologically and economically effective. Assuming a massive third (or fourth) wave will not materialize in 2021, the real GDP loss due to the second wave will be smaller than 0.4 percentage points in 2020 and 2021. [less ▲]

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See detailAssessing the robustness of decentralized gathering: a multi‐agent approach on micro‐biological systems
Proverbio, Daniele UL; Gallo, Luca; Passalacqua, Barbara et al

in Swarm Intelligence (2020), 14

Adopting a multi-agent systems paradigm, we developed, tested and exploited a computational testbed that simulates gathering features of the social amoeba Dictyostelium discoideum. It features a tailored ... [more ▼]

Adopting a multi-agent systems paradigm, we developed, tested and exploited a computational testbed that simulates gathering features of the social amoeba Dictyostelium discoideum. It features a tailored design and implementation to manage discrete simulations with autonomous agents on a microscopic scale, thus focusing on their social behavior and mutual interactions. Hence, we could assess the behavioral conditions under which decentralized gathering could occur. We investigated the dependence of the model dynamics on the main physical variables, namely density and number of amoebas, gaining indications that the process strongly depends on both. This result integrates previous researches, where density is identified as the sole relevant variable. We determined a high-density and high-numerosity region where assuming a scale-free behavior is safe. We also estimated the systematic uncertainties arising from a number of amoebas off the scale-free region, when coping with limited computational resources. Finally, we probed the robustness of the simulated gathering process against both extrinsic and intrinsic noise sources. [less ▲]

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See detailFastField: An Open-Source Toolbox for Efficient Approximation of Deep Brain Stimulation Electric Fields
Baniasadi, Mehri UL; Proverbio, Daniele UL; Goncalves, Jorge UL et al

in NeuroImage (2020)

Deep brain stimulation (DBS) is a surgical therapy to alleviate symptoms of certain brain disorders by electrically modulating neural tissues. Computational models predicting electric fields and volumes ... [more ▼]

Deep brain stimulation (DBS) is a surgical therapy to alleviate symptoms of certain brain disorders by electrically modulating neural tissues. Computational models predicting electric fields and volumes of tissue activated are key for efficient parameter tuning and network analysis. Currently, we lack efficient and flexible software implementations supporting complex electrode geometries and stimulation settings. Available tools are either too slow (e.g. finite element method–FEM), or too simple, with limited applicability to basic use-cases. This paper introduces FastField, an efficient open-source toolbox for DBS electric field and VTA approximations. It computes scalable e-field approximations based on the principle of superposition, and VTA activation models from pulse width and axon diameter. In benchmarks and case studies, FastField is solved in about 0.2s, ~ 1000 times faster than using FEM. Moreover, it is almost as accurate as using FEM: average Dice overlap of 92%, which is around typical noise levels found in clinical data. Hence, FastField has the potential to foster efficient optimization studies and to support clinical applications [less ▲]

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See detailRobust synchronization of heterogeneous robot swarms on the sphere
Markdahl, Johan UL; Proverbio, Daniele UL; Goncalves, Jorge UL

in 2020 59th IEEE Conference on Decision and Control (CDC) (2020)

Synchronization on the sphere is important to certain control applications in swarm robotics. Of recent interest is the Lohe model, which generalizes the Kuramoto model from the circle to the sphere. The ... [more ▼]

Synchronization on the sphere is important to certain control applications in swarm robotics. Of recent interest is the Lohe model, which generalizes the Kuramoto model from the circle to the sphere. The Lohe model is mainly studied in mathematical physics as a toy model of quantum synchronization. The model makes few assumptions, wherefore it is well-suited to represent a swarm. Previous work on this model has focused on the cases of complete and acyclic networks or the homogeneous case where all oscillator frequencies are equal. This paper concerns the case of heterogeneous oscillators connected by a non-trivial network. We show that any undesired equilibrium is exponentially unstable if the frequencies satisfy a given bound. This property can also be interpreted as a robustness result for small model perturbations of the homogeneous case with zero frequencies. As such, the Lohe model is a good choice for control applications in swarm robotics. [less ▲]

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See detailAssessing suppression strategies against epidemicoutbreaks like COVID-19: the SPQEIR model
Proverbio, Daniele UL; Kemp, Francoise UL; Magni, Stefano UL et al

E-print/Working paper (2020)

The current COVID-19 outbreak represents a most serious challenge for societies worldwide. It isendangering the health of millions of people, and resulting in severe socioeconomic challenges dueto lock ... [more ▼]

The current COVID-19 outbreak represents a most serious challenge for societies worldwide. It isendangering the health of millions of people, and resulting in severe socioeconomic challenges dueto lock-down measures. Governments worldwide aim to devise exit strategies to revive the economywhile keeping the pandemic under control. The problem is that the effects of distinct measures arenot well quantified. This paper compares several suppression approaches and potential exit strategiesusing a new extended epidemic SEIR model. It concludes that while rapid and strong lock-down isan effective pandemic suppression measure, a combination of other strategies such as social distanc-ing, active protection and removal can achieve similar suppression synergistically. This quantitativeunderstanding will support the establishment of mid- and long-term interventions. Finally, the paperprovides an online tool that allows researchers and decision makers to interactively simulate diversescenarios with our model. [less ▲]

Detailed reference viewed: 128 (3 UL)
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See detailApproXON: Heuristic Approximation to the E-Field-Threshold for Deep Brain Stimulation Volume-of-Tissue-Activated Estimation
Proverbio, Daniele UL; Husch, Andreas UL

E-print/Working paper (2019)

This paper introduces a heuristic approximation of the e-field threshold used for volume-of-tissue activated computation in deep brain stimulation. Pulse width and axon diameter are used as predictors. An ... [more ▼]

This paper introduces a heuristic approximation of the e-field threshold used for volume-of-tissue activated computation in deep brain stimulation. Pulse width and axon diameter are used as predictors. An open source implementation in MATLAB is provided together with an integration in the open LeadDBS deep brain stimulation research toolbox. [less ▲]

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See detailDynamical strategies for obstacle avoidance during Dictyostelium discoideum aggregation: a Multi-agent system model
Proverbio, Daniele UL; Maggiora, Marco

E-print/Working paper (2019)

Chemotaxis, the movement of an organism in response to a chemical stimulus, is a typical feature of many microbiological systems. In particular, the social amoeba Disctyostelium discoideum is widely used ... [more ▼]

Chemotaxis, the movement of an organism in response to a chemical stimulus, is a typical feature of many microbiological systems. In particular, the social amoeba Disctyostelium discoideum is widely used as a model organism, but it is not still clear how it behaves in heterogeneous environments. A few models focused on mechanical features have already addressed the question; however, we propose that phenomenological models focusing on the dynamics may provide new meaningful data. Consequently, by means of a specific Multi-agent system model, we studied the dynamical features emerging from complex social interactions among individuals belonging to amoeboids colonies. After defining an appropriate metric to perform meaningful measurements, we found that: a) obstacles play the role of local topological perturbation, as they alter the flux of chemical signals; b) that obstacle that physically block the cellular motion as well as the chemicals elicit dynamical evolutions that are not statistically distinguishable from the case where obstacles that do not interfere physically with said motion; c) that fluctuations of the dynamics can lead to better exploration of the physical space, thus preventing multiple stable aggregates. From previous results, we may speculate about the fact that chemotactic cells, in many cases, can avoid obstacles by simply following the altered chemical gradient: social interactions seem to be sufficient to guarantee the aggregation of the whole colony past numerous obstacles. It is then unlikely that cells have developed special mechanisms to cope with the presence of topological perturbation sources. Nevertheless, we suggest that further studies can provide better understanding and that, in order to gain deeper knowledge, mechanical models should be coupled with phenomenological, system-oriented ones. [less ▲]

Detailed reference viewed: 76 (8 UL)