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 Physics , 2012, DOI: 10.1371/journal.pcbi.1002974 Abstract: Empirical studies suggest that contact patterns follow heterogeneous inter-event times, meaning that intervals of high activity are followed by periods of inactivity. Combined with birth and death of individuals, these temporal constraints affect the spread of infections in a non-trivial way and are dependent on the particular contact dynamics. We propose a stochastic model to generate temporal networks where vertices make instantaneous contacts following heterogeneous inter-event times, and leave and enter the system at fixed rates. We study how these temporal properties affect the prevalence of an infection and estimate R0, the number of secondary infections, by modeling simulated infections (SIR, SI and SIS) co-evolving with the network structure. We find that heterogeneous contact patterns cause earlier and larger epidemics on the SIR model in comparison to homogeneous scenarios. In case of SI and SIS, the epidemics is faster in the early stages (up to 90% of prevalence) followed by a slowdown in the asymptotic limit in case of heterogeneous patterns. In the presence of birth and death, heterogeneous patterns always cause higher prevalence in comparison to homogeneous scenarios with same average inter-event times. Our results suggest that R0 may be underestimated if temporal heterogeneities are not taken into account in the modeling of epidemics.
 Physics , 2008, DOI: 10.1209/0295-5075/86/66004 Abstract: Using molecular dynamics simulation, we study structural and dynamical heterogeneities at melting in two-dimensional one-component systems with 36000 particles. Between crystal and liquid we find intermediate hexatic states, where the density fluctuations are enhanced at small wave number k as well as those of the six-fold orientational order parameter. Their structure factors both grow up to the smallest wave number equal to the inverse system length. The intermediate scattering function of the density S(k,t) is found to relax exponentially with decay rate Gamma_k ~ k^z with z~2.6 at small k in the hexatic phase.
 Physics , 1998, DOI: 10.1209/epl/i1998-00339-6 Abstract: We present the first experimental characterization in molecular fragile glassformers of a 'prepeak that appears significantly below the main peak of the static structure factor. The temperature and density dependences of this prepeak are studied via elastic neutron scattering experiments under high pressure (up to 300 MPa) in m-toluidine and m-fluoroaniline. The prepeak intensity increases with decreasing temperature, but it remains constant with increasing pressure while its position and width stay roughly the same. These features are opposite to those observed for the 'first sharp diffraction peak' of network glasses. The origin of the phenomenon is analyzed with the help of Monte Carlo simulations. We associate the prepeak to hydrogen-bond-induced heterogeneities (or clusters) whose limited size results from exclusion effect between benzene rings that prevents the extension of a hydrogen-bond network. Implications for the dynamics of the liquid close to the glass transition are finally considered.
 Computer Science , 2013, Abstract: This paper introduces the concept of adaptive temporal compressive sensing (CS) for video. We propose a CS algorithm to adapt the compression ratio based on the scene's temporal complexity, computed from the compressed data, without compromising the quality of the reconstructed video. The temporal adaptivity is manifested by manipulating the integration time of the camera, opening the possibility to real-time implementation. The proposed algorithm is a generalized temporal CS approach that can be incorporated with a diverse set of existing hardware systems.
 Physics , 2009, DOI: 10.1039/C0SM00756K Abstract: We study concentrated binary colloidal suspensions, a model system which has a glass transition as the volume fraction $\phi$ of particles is increased. We use confocal microscopy to directly observe particle motion within dense samples with $\phi$ ranging from 0.4 to 0.7. Our binary mixtures have a particle diameter ratio $d_S/d_L=1/1.3$ and particle number ratio $N_S/N_L=1.56$, which are chosen to inhibit crystallization and enable long-time observations. Near the glass transition we find that particle dynamics are heterogeneous in both space and time. The most mobile particles occur in spatially localized groups. The length scales characterizing these mobile regions grow slightly as the glass transition is approached, with the largest length scales seen being $\sim 4$ small particle diameters. We also study temporal fluctuations using the dynamic susceptibility $\chi_4$, and find that the fluctuations grow as the glass transition is approached. Analysis of both spatial and temporal dynamical heterogeneity show that the smaller species play an important role in facilitating particle rearrangements. The glass transition in our sample occurs at $\phi_g \approx 0.58$, with characteristic signs of aging observed for all samples with $\phi>\phi_g$.
 PLOS ONE , 2014, DOI: 10.1371/journal.pone.0091170 Abstract: Following the 2006 Chikungunya disease in La Reunion, questions were raised concerning the monitoring survey of Aedes albopictus populations and the entomological indexes used to evaluate population abundance. The objectives of the present study were to determine reliable productivity indexes using a quantitative method to improve entomological surveys and mosquito control measures on Aedes albopictus. Between 2007 and 2011, 4 intervention districts, 24 cities, 990 areas and over 850,000 houses were used to fulfil those objectives. Four indexes including the classical Stegomyia index (House Index, Container Index, Breteau Index) plus an Infested Receptacle Index were studied in order to determine whether temporal (year, month, week) and/or spatial (districts, cities, areas) heterogeneities existed. Temporal variations have been observed with an increase of Ae. albopictus population density over the years, and a seasonality effect with a highest population during the hot and wet season. Spatial clustering was observed at several scales with an important autocorrelation at the area scale. Moreover, the combination among these results and the breeding site productivity obtained during these 5 years allowed us to propose recommendations to monitor Aedes albopictus by eliminating not the most finding sites but the most productive ones. As the other strategies failed in La Reunion, this new approach should should work better.
 Computer Science , 2012, Abstract: One of the major task of sensor nodes in wireless sensor networks is to transmit a subset of sensor readings to the sink node estimating a desired data accuracy. Therefore in this paper, we propose an accuracy model using Steepest Decent method called Adaptive Data Accuracy (ADA) model which doesn't require any a priori information of input signal statistics to select an optimal set of sensor nodes in the network. Moreover we develop another model using LMS filter called Spatio-Temporal Data Prediction (STDP) model which captures the spatial and temporal correlation of sensing data to reduce the communication overhead under data reduction strategies. Finally using STDP model, we illustrate a mechanism to trace the malicious nodes in the network under extreme physical environment. Computer simulations illustrate the performance of ADA and STDP models respectively.
 Computer Science , 2014, DOI: 10.1103/PhysRevE.90.042805 Abstract: Empirical temporal networks display strong heterogeneities in their dynamics, which profoundly affect processes taking place on these networks, such as rumor and epidemic spreading. Despite the recent wealth of data on temporal networks, little work has been devoted to the understanding of how such heterogeneities can emerge from microscopic mechanisms at the level of nodes and links. Here we show that long-term memory effects are present in the creation and disappearance of links in empirical networks. We thus consider a simple generative modeling framework for temporal networks able to incorporate these memory mechanisms. This allows us to study separately the role of each of these mechanisms in the emergence of heterogeneous network dynamics. In particular, we show analytically and numerically how heterogeneous distributions of contact durations, of inter-contact durations and of numbers of contacts per link emerge. We also study the individual effect of heterogeneities on dynamical processes, such as the paradigmatic Susceptible-Infected epidemic spreading model. Our results confirm in particular the crucial role of the distributions of inter-contact durations and of the numbers of contacts per link.
 Computer Science , 2014, Abstract: Interactions in time-varying complex systems are often very heterogeneous at the topological level (who interacts with whom) and at the temporal level (when interactions occur and how often). While it is known that temporal heterogeneities often have strong effects on dynamical processes, e.g. the burstiness of contact sequences is associated with slower spreading dynamics, the picture is far from complete. In this paper, we show that temporal heterogeneities result in temporal sparsity} at the time scale of average inter-event times, and that temporal sparsity determines the amount of slowdown of Susceptible-Infectious (SI) spreading dynamics on temporal networks. This result is based on the analysis of several empirical temporal network data sets. An approximate solution for a simple network model confirms the association between temporal sparsity and slowdown of SI spreading dynamics. Since deterministic SI spreading always follows the fastest temporal paths, our results generalize -- paths are slower to traverse because of temporal sparsity, and therefore all dynamical processes are slower as well.
 PLOS ONE , 2014, DOI: 10.1371/journal.pone.0094998 Abstract: Temporal networks are such networks where nodes and interactions may appear and disappear at various time scales. With the evidence of ubiquity of temporal networks in our economy, nature and society, it's urgent and significant to focus on its structural controllability as well as the corresponding characteristics, which nowadays is still an untouched topic. We develop graphic tools to study the structural controllability as well as its characteristics, identifying the intrinsic mechanism of the ability of individuals in controlling a dynamic and large-scale temporal network. Classifying temporal trees of a temporal network into different types, we give (both upper and lower) analytical bounds of the controlling centrality, which are verified by numerical simulations of both artificial and empirical temporal networks. We find that the positive relationship between aggregated degree and controlling centrality as well as the scale-free distribution of node's controlling centrality are virtually independent of the time scale and types of datasets, meaning the inherent robustness and heterogeneity of the controlling centrality of nodes within temporal networks.
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