Entropic dynamics of networks

Here we present the entropic dynamics formalism for networks. That is, a framework for the dynamics of graphs meant to represent a network derived from the principle of maximum entropy and the rate of transition is obtained taking into account the natural information geometry of probability distributions. We apply this framework to the Gibbs distribution of random graphs obtained with constraints on the node connectivity. The information geometry for this graph ensemble is calculated and the dynamical process is obtained as a diffusion equation. We compare the steady state of this dynamics to degree distributions found on real-world networks

Bioceramic Cements in Endodontics

New bioceramic calcium silicate endodontic cements have been recently introduced in the market. They are biocompatible materials that stimulate mineralization. Its dimensional stability is similar to the Fillapex MTA with greater thickness and solubility than AH Plus (Dentsply, DeTrey, Konstanz, Germany) as it is water based. Stored in dispensed syringe, it has a pre-mixed consistency. They are used with the single cone obturation technique because they have properties that are changed when heated. They were developed by inducing bioactivity on the surface of the material when in contact with tissue fluids. An improvement in the osteoblastic differentiation of the cells of the periodontal ligament, induction of remineralization of the dentin, and excellent antimicrobial properties have also been associated with these cements. These properties make these cements an excellent alternative in the attempt to obtain a three-dimensional obturation of the Root Canal System (SCR)

Optimization model for bandwidth allocation in a network virtualization environment

Bandwidth allocation is one of the main problems in network virtualization. Mechanisms to allocate bandwidth may avoid bottlenecked virtual links. This paper proposes a model based on optimization theory, to distribute the bandwidth among virtual links looking for the minimization of the spare bandwidth in the substrate network.Postprint (published version

CellSim: a validated modular heterogeneous multiprocessor simulator

As the number of transistors on a chip continues increasing the power consumption has become the most important constraint in processors design. Therefore, to increase performance, computer architects have decided to use multiprocessors. Moreover, recent studies have shown that heterogeneous chip multiprocessors have greater potential than homogeneous ones. We have built a modular simulator for heterogeneous multiprocessors that can be configure to model IBM's Cell Processor. The simulator has been validated against the real machine to be used as a research tool.Peer ReviewedPostprint (published version

Dynamic Conditional Correlation GARCH: A Multivariate Time Series Novel using a Bayesian Approach

The Dynamic Conditional Correlation GARCH (DCC-GARCH) mutation model is considered using a Monte Carlo approach via Markov chains in the estimation of parameters, time-dependence variation is visually demonstrated. Fifteen indices were analyzed from the main financial markets of developed and developing countries from different continents. The performances of indices are similar, with a joint evolution. Most index returns, especially SPX and NDX, evolve over time with a higher positive correlation

The Neumann problem for the fractional Laplacian: regularity up to the boundary

We study the regularity up to the boundary of solutions to the Neumann problem for the fractional Laplacian. We prove that if u is a weak solution of . Å/su D f in and Nsu D 0 in c, then u is C ̨ up to the boundary for some ̨>0. Moreover, in case s > 1 2 , we show that u 2 C2s 1C ̨. /. To prove these results we need, among other things, a delicate Moser iteration on the boundary with some logarithmic corrections. Our methods allow us to treat as well the Neumann problem for the regional fractional Laplacian, and we establish the same boundary regularity result. Prior to our results, the interior regularity for these Neumann problems was well understood, but near the boundary even the continuity of solutions was open

A divide and conquer approach to cope with uncertainty, human health risk, and decision making in contaminant hydrology

Assessing health risk in hydrological systems is an interdisciplinary field. It relies on the expertise in the fields of hydrology and public health and needs powerful translation concepts to provide decision support and policy making. Reliable health risk estimates need to account for the uncertainties and variabilities present in hydrological, physiological, and human behavioral parameters. Despite significant theoretical advancements in stochastic hydrology, there is still a dire need to further propagate these concepts to practical problems and to society in general. Following a recent line of work, we use fault trees to address the task of probabilistic risk analysis and to support related decision and management problems. Fault trees allow us to decompose the assessment of health risk into individual manageable modules, thus tackling a complex system by a structural divide and conquer approach. The complexity within each module can be chosen individually according to data availability, parsimony, relative importance, and stage of analysis. Three differences are highlighted in this paper when compared to previous works: (1) The fault tree proposed here accounts for the uncertainty in both hydrological and health components, (2) system failure within the fault tree is defined in terms of risk being above a threshold value, whereas previous studies that used fault trees used auxiliary events such as exceedance of critical concentration levels, and (3) we introduce a new form of stochastic fault tree that allows us to weaken the assumption of independent subsystems that is required by a classical fault tree approach. We illustrate our concept in a simple groundwater‐related settin

Semi-metric topology characterizes epidemic spreading on complex networks

Network sparsification represents an essential tool to extract the core of interactions sustaining both networks dynamics and their connectedness. In the case of infectious diseases, network sparsification methods remove irrelevant connections to unveil the primary subgraph driving the unfolding of epidemic outbreaks in real networks. In this paper, we explore the features determining whether the metric backbone, a subgraph capturing the structure of shortest paths across a network, allows reconstructing epidemic outbreaks. We find that both the relative size of the metric backbone, capturing the fraction of edges kept in such structure, and the distortion of semi-metric edges, quantifying how far those edges not included in the metric backbone are from their associated shortest path, shape the retrieval of Susceptible-Infected (SI) dynamics. We propose a new method to progressively dismantle networks relying on the semi-metric edge distortion, removing first those connections farther from those included in the metric backbone, i.e. those with highest semi-metric distortion values. We apply our method in both synthetic and real networks, finding that semi-metric distortion provides solid ground to preserve spreading dynamics and connectedness while sparsifying networks.Comment: 11 pages, 4 figures. Supplementary Text: 6 pages, 1 table, 5 figure