Spectral Modes of Network Dynamics Reveal Increased Informational Complexity Near Criticality

What does the informational complexity of dynamical networked systems tell us about intrinsic mechanisms and functions of these complex systems? Recent complexity measures such as integrated information have sought to operationalize this problem taking a whole-versus-parts perspective, wherein one explicitly computes the amount of information generated by a network as a whole over and above that generated by the sum of its parts during state transitions. While several numerical schemes for estimating network integrated information exist, it is instructive to pursue an analytic approach that computes integrated information as a function of network weights. Our formulation of integrated information uses a Kullback-Leibler divergence between the multi-variate distribution on the set of network states versus the corresponding factorized distribution over its parts. Implementing stochastic Gaussian dynamics, we perform computations for several prototypical network topologies. Our findings show increased informational complexity near criticality, which remains consistent across network topologies. Spectral decomposition of the system's dynamics reveals how informational complexity is governed by eigenmodes of both, the network's covariance and adjacency matrices. We find that as the dynamics of the system approach criticality, high integrated information is exclusively driven by the eigenmode corresponding to the leading eigenvalue of the covariance matrix, while sub-leading modes get suppressed. The implication of this result is that it might be favorable for complex dynamical networked systems such as the human brain or communication systems to operate near criticality so that efficient information integration might be achieved

Locating the Source of Diffusion in Large-Scale Networks

How can we localize the source of diffusion in a complex network? Due to the tremendous size of many real networks--such as the Internet or the human social graph--it is usually infeasible to observe the state of all nodes in a network. We show that it is fundamentally possible to estimate the location of the source from measurements collected by sparsely-placed observers. We present a strategy that is optimal for arbitrary trees, achieving maximum probability of correct localization. We describe efficient implementations with complexity O(N^{\alpha}), where \alpha=1 for arbitrary trees, and \alpha=3 for arbitrary graphs. In the context of several case studies, we determine how localization accuracy is affected by various system parameters, including the structure of the network, the density of observers, and the number of observed cascades.Comment: To appear in Physical Review Letters. Includes pre-print of main paper, and supplementary materia

Bars and Cold Dark Matter Halos

The central part of a dark matter halo reacts to the presence and evolution of a bar. Not only does the halo absorb angular momentum from the disk, it can also be compressed and have its shape modified. We study these issues in a series of cosmologically motivated, highly resolved N-body simulations of barred galaxies run under different initial conditions. In all models we find that the inner halo's central density increases. We model this density increase using the standard adiabatic approximation and the modified formula by Gnedin et al. and find that halo mass profiles are better reproduced by this latter. In models with a strong bar, the dark matter in the central region forms a bar-like structure (``dark matter bar''), which rotates together with the normal bar formed by the stellar component (``stellar bar''). The minor-to-major axial ratio of a halo bar changes with radius with a typical value 0.7 in the central disk region. DM bar amplitude is mostly a function of the stellar bar strength. Models in which the bar amplitude increases or stays roughly constant with time, initially large (40%-60%) misalignment between the halo and disk bars quickly decreases with time as the bar grows. The halo bar is nearly aligned with the stellar bar (~10 degrees lag for the halo) after ~2 Gyr. The torque, which the halo bar exerts on the stellar bar, can serve as a mechanism to regulate the angular momentum transfer from the disk to the halo.Comment: Modified version after referee's suggestions. 17 pages, 12 figures, accepted by Ap

Medium materials for improving frost detection on a resistive sensor

Reducing food waste demands improvements in refrigeration systems. Furthermore, the rise of temperatures worldwide demands more capable and efficient refrigeration equipment. One of the problems that affects refrigeration equipment is the accumulation of frost in the heat exchanger that reduces efficiency, and in extreme cases, blocks the air flow. Usually, defrosting is timed for the worst-case scenario, which results in many unnecessary defrosting operations that compromise the efficiency, and temperature stability in the refrigerated environment. This paper presents a low-cost resistive sensor’s reliability case studies, using several materials and configurations.This study is within the activities of project “Pack2Life – High performance packaging”, project IDT in consortium n.o 33792, call n.o 03/SI/2017, Ref. POCI-01-0247-FEDER-033792, promoted by COMPETE 2020 and co-funded by FEDER within Portugal 2020. This work has was supported by the project Centro-01-0145-FEDER000017 - EMaDeS - Energy, Materials and Sustainable Development, co-funded by the Portugal 2020 Program (PT 2020), within the Regional Operational Program of the Center (CENTRO 2020) and the EU through the European Regional Development Fund (ERDF). The authors thank the opportunity and financial support to carry on this project to Fundação para a Ciência e Tecnologia (FCT) and R&D Unit “Centre for Mechanical and Aerospace Science and Technologies” (C-MAST), under project UIDB/00151/2020. The authors also thank Cláudia Monteiro for her assistance in the production of the ceramic samples.info:eu-repo/semantics/publishedVersio

J Regularization Improves Imbalanced Multiclass Segmentation

We propose a new loss formulation to further advance the multiclass segmentation of cluttered cells under weakly supervised conditions. When adding a Youden's J statistic regularization term to the cross entropy loss we improve the separation of touching and immediate cells, obtaining sharp segmentation boundaries with high adequacy. This regularization intrinsically supports class imbalance thus eliminating the necessity of explicitly using weights to balance training. Simulations demonstrate this capability and show how the regularization leads to correct results by helping advancing the optimization when cross entropy stagnates. We build upon our previous work on multiclass segmentation by adding yet another training class representing gaps between adjacent cells. This addition helps the classifier identify narrow gaps as background and no longer as touching regions. We present results of our methods for 2D and 3D images, from bright field images to confocal stacks containing different types of cells, and we show that they accurately segment individual cells after training with a limited number of images, some of which are poorly annotated

The Kumaraswamy-G Poisson Family of Distributions

For any baseline continuous G distribution, we propose a new generalized family called the Kumaraswamy-G Poisson (denoted with the prefix “Kw-GP”) with three extra positive parameters. Some special distributions in the new family such as the Kw-Weibull Poisson, Kw-gamma Poisson and Kw-beta Poisson distributions are introduced. We derive some mathematical properties of the new family including the ordinary moments, generating function and order statistics. The method of maximum likelihood is used to fit the distributions in the new family. We illustrate its potentiality by means of an application to a real data set

International business tourism : a growth rate model

The aim of this paper is to understand the factors influencing business tourism on a global scale, in order to assess the competence of the countries in this tourism segment and prescribe them guidelines for action. For the development of data analysis, a growth rate model was estimated and a sample of 136 countries for the years 2005 and 2009 was collected. Results reveal that, for the development of policies to stimulate the growth in the business tourism segment, countries should develop measures that encourage capital investment in tourism, leisure tourism and trade openness.8316-FD77-85EB | Pedro Miguel Fonseca Moreira de CarvalhoN/