Aging and percolation dynamics in a Non-Poissonian temporal network model

We present an exhaustive mathematical analysis of the recently proposed Non-Poissonian Ac- tivity Driven (NoPAD) model [Moinet et al. Phys. Rev. Lett., 114 (2015)], a temporal network model incorporating the empirically observed bursty nature of social interactions. We focus on the aging effects emerging from the Non-Poissonian dynamics of link activation, and on their effects on the topological properties of time-integrated networks, such as the degree distribution. Analytic expressions for the degree distribution of integrated networks as a function of time are derived, ex- ploring both limits of vanishing and strong aging. We also address the percolation process occurring on these temporal networks, by computing the threshold for the emergence of a giant connected component, highlighting the aging dependence. Our analytic predictions are checked by means of extensive numerical simulations of the NoPAD model

Effect of risk perception on epidemic spreading in temporal networks

Many progresses in the understanding of epidemic spreading models have been obtained thanks to numerous modeling efforts and analytical and numerical studies, considering host populations with very different structures and properties, including complex and temporal interaction networks. Moreover, a number of recent studies have started to go beyond the assumption of an absence of coupling between the spread of a disease and the structure of the contacts on which it unfolds. Models including awareness of the spread have been proposed, to mimic possible precautionary measures taken by individuals that decrease their risk of infection, but have mostly considered static networks. Here, we adapt such a framework to the more realistic case of temporal networks of interactions between individuals. We study the resulting model by analytical and numerical means on both simple models of temporal networks and empirical time-resolved contact data. Analytical results show that the epidemic threshold is not affected by the awareness but that the prevalence can be significantly decreased. Numerical studies highlight however the presence of very strong finite-size effects, in particular for the more realistic synthetic temporal networks, resulting in a significant shift of the effective epidemic threshold in the presence of risk awareness. For empirical contact networks, the awareness mechanism leads as well to a shift in the effective threshold and to a strong reduction of the epidemic prevalence

Random walks in non-Poissoinan activity driven temporal networks

The interest in non-Markovian dynamics within the complex systems community has recently blossomed, due to a new wealth of time-resolved data pointing out the bursty dynamics of many natural and human interactions, manifested in an inter-event time between consecutive interactions showing a heavy-tailed distribution. In particular, empirical data has shown that the bursty dynamics of temporal networks can have deep consequences on the behavior of the dynamical processes running on top of them. Here, we study the case of random walks, as a paradigm of diffusive processes, unfolding on temporal networks generated by a non-Poissonian activity driven dynamics. We derive analytic expressions for the steady state occupation probability and first passage time distribution in the infinite network size and strong aging limits, showing that the random walk dynamics on non-Markovian networks are fundamentally different from what is observed in Markovian networks. We found a particularly surprising behavior in the limit of diverging average inter-event time, in which the random walker feels the network as homogeneous, even though the activation probability of nodes is heterogeneously distributed. Our results are supported by extensive numerical simulations. We anticipate that our findings may be of interest among the researchers studying non-Markovian dynamics on time-evolving complex topologies.Postprint (published version

Invoice from Charles Moinet to Ogden Goelet

https://digitalcommons.salve.edu/goelet-personal-expenses/1110/thumbnail.jp

Temperature sensitivity of decomposition: Discrepancy between field and laboratory estimates is not due to sieving the soil

© 2020 The Authors Is persistent soil organic matter (SOM), characterised by an old age and long-turnover time, more or less sensitive to changes in temperature than fast-cycling, recent SOM? Largely due to our limited understanding of the mechanisms of SOM formation, this question remains controversial. Laboratory incubation studies, through sieving the soil, may create conditions in which substrate accessibility is modified. The recent recognition of SOM accessibility as a defining factor of SOM persistency calls into question conclusions from these studies. Previously, in a study using root exclusion plots of increasing age, we showed in the field that the temperature sensitivity of SOM decomposition decreased with increasing persistence of SOM (Moinet et al., 2020), in opposition to many laboratory incubation studies. Here we sampled soils from the same root exclusion plots and conducted a laboratory incubation experiment to test the hypotheses that (i) the relationship between temperature sensitivity and SOM persistence is inverted as compared to the field, and (ii) the discrepancy is due to sieving the soil. We showed that, in the laboratory, the relationship was indeed inverted, with the temperature sensitivity being higher for the old root exclusion plots. However, sieving the soil at 2 mm did not affect estimates of the temperature sensitivity of SOM decomposition, suggesting that discrepancies between field and laboratory estimates are unlikely to stem from artificially modified substrate accessibility due to sieving

Defining tools to address over-constrained geometric problems

International audienceThis paper proposes a new tool for decision support to address geometric over-constrained problems in Computer Aided Design (CAD). It concerns the declarative modeling of geometrical problems. The core of the coordinate free solver used to solve the Geometric Constraint Satisfaction Problem (GCSP) was developed previously by the authors. This research proposes a methodology based on Michelucci's witness method to determine whether the structure of the problem is over-constrained. In this case, the authors propose a tool for assisting the designer in solving the over-constrained problem by ensuring the consistency of the specifications. An application of the methodology and tool is presented in an academic example