Immune cognition, social justice and asthma: structured stress and the developing immune system

We explore the implications of IR Cohen's work on immune cognition for understanding rising rates of asthma morbidity and mortality in the US. Immune cognition is conjoined with central nervous system cognition, and with the cognitive function of the embedding sociocultural networks by which individuals are acculturated and through which they work with others to meet challenges of threat and opportunity. Using a mathematical model, we find that externally- imposed patterns of 'structured stress' can, through their effect on a child's socioculture, become synergistic with the development of immune cognition, triggering the persistence of an atopic Th2 phenotype, a necessary precursor to asthma and other immune disease. Reversal of the rising tide of asthma and related chronic diseases in the US thus seems unlikely without a 21st Century version of the earlier Great Urban Reforms which ended the scourge of infectious diseases

A Study of Differences in Calculated Capacity when Using Single-, Mixed- or Multiple-Bounce GSCM Schemes

The paper looks for differences in MIMO system capacity when using either single-, mixed-, or multiple-bounce geometry based stochastic channel models (GSCMs). The investigation considers Saleh-Valenzuela temporal indoor model, expanded for angular domain. In the model omnidirectional and idealized sector antennas were used as array elements. The single-bounce assumption, combination of single and multiple bounces, and pure random multiple bounces assumption were compared within “temporally identical” environment regarding the overall MIMO capacity. Assumption of clustered scatterers/reflectors is used in all three cases. The comparison is performed in statistical sense, using a large number of stochastically generated temporal models. The model is two- dimensional, i.e. neither elevation angle nor polarization/ depolarization was considered

About Dynamical Systems Appearing in the Microscopic Traffic Modeling

Motivated by microscopic traffic modeling, we analyze dynamical systems which have a piecewise linear concave dynamics not necessarily monotonic. We introduce a deterministic Petri net extension where edges may have negative weights. The dynamics of these Petri nets are well-defined and may be described by a generalized matrix with a submatrix in the standard algebra with possibly negative entries, and another submatrix in the minplus algebra. When the dynamics is additively homogeneous, a generalized additive eigenvalue may be introduced, and the ergodic theory may be used to define a growth rate under additional technical assumptions. In the traffic example of two roads with one junction, we compute explicitly the eigenvalue and we show, by numerical simulations, that these two quantities (the additive eigenvalue and the growth rate) are not equal, but are close to each other. With this result, we are able to extend the well-studied notion of fundamental traffic diagram (the average flow as a function of the car density on a road) to the case of two roads with one junction and give a very simple analytic approximation of this diagram where four phases appear with clear traffic interpretations. Simulations show that the fundamental diagram shape obtained is also valid for systems with many junctions. To simulate these systems, we have to compute their dynamics, which are not quite simple. For building them in a modular way, we introduce generalized parallel, series and feedback compositions of piecewise linear concave dynamics.Comment: PDF 38 page

Maps of random walks on complex networks reveal community structure

To comprehend the multipartite organization of large-scale biological and social systems, we introduce a new information theoretic approach that reveals community structure in weighted and directed networks. The method decomposes a network into modules by optimally compressing a description of information flows on the network. The result is a map that both simplifies and highlights the regularities in the structure and their relationships. We illustrate the method by making a map of scientific communication as captured in the citation patterns of more than 6000 journals. We discover a multicentric organization with fields that vary dramatically in size and degree of integration into the network of science. Along the backbone of the network -- including physics, chemistry, molecular biology, and medicine -- information flows bidirectionally, but the map reveals a directional pattern of citation from the applied fields to the basic sciences.Comment: 7 pages and 4 figures plus supporting material. For associated source code, see http://www.tp.umu.se/~rosvall

Long-run urban dynamics: understanding local housing market change in London

Recently, a literature has emerged using empirical techniques to study the evolution of international cities over many centuries; however, few studies examine long-run change within cities. Conventional models and concepts are not always appropriate and data issues make long-run neighbourhood analysis particularly problematic. This paper addresses some of these points. First, it discusses why the analysis of long-run urban change is important for modern urban policy and considers the most important concepts. Second, it constructs a novel data set at the micro level, which allows consistent comparisons of London neighbourhoods in 1881 and 2001. Third, the paper models some of the key factors that affected long-run change, including the role of housing. There is evidence that the relative social positions of local urban areas persist over time but, nevertheless, at fine spatial scales, local areas still exhibit change, arising from aggregate population dynamics, from advances in technology, and also from the effects of shocks, such as wars. In general, where small areas are considered, long-run changes are likely to be greater, because individuals are more mobile over short than long distances. Finally, the paper considers the implications for policy

The Traffic Phases of Road Networks

We study the relation between the average traffic flow and the vehicle density on road networks that we call 2D-traffic fundamental diagram. We show that this diagram presents mainly four phases. We analyze different cases. First, the case of a junction managed with a priority rule is presented, four traffic phases are identified and described, and a good analytic approximation of the fundamental diagram is obtained by computing a generalized eigenvalue of the dynamics of the system. Then, the model is extended to the case of two junctions, and finally to a regular city. The system still presents mainly four phases. The role of a critical circuit of non-priority roads appears clearly in the two junctions case. In Section 4, we use traffic light controls to improve the traffic diagram. We present the improvements obtained by open-loop, local feedback, and global feedback strategies. A comparison based on the response times to reach the stationary regime is also given. Finally, we show the importance of the design of the junction. It appears that if the junction is enough large, the traffic is almost not slowed down by the junction.Comment: 37 page

Characterization of MIMO channel capacity in urban microcellular environment

The research work in this thesis consists of several investigations of multiple-input multiple-output (MIMO) wireless channel capacity in urban microcellular environment. The investigations can be categorized into three groups, 1)- model-based investigations, 2)- measurement-based investigations, and 3)- theoretical investigations. Utilizing three dimensional (3D) channel models the influence of environment physical parameters and antenna array configuration on MIMO channel capacity are investigated. In terms of environment influence, parameters such as street width, wall relative permittivity and multipath richness are considered. In terms of antenna array configuration, the effect of array geometry and uniform linear array (ULA) azimuthal orientation are considered. It is shown that the effect of these parameters on MIMO channel capacity is significant. Based on field measurements, the effect of spatial smoothing on the accuracy of a widely used stochastic narrowband MIMO radio channel model, namely, the Kronecker model, and the impact of temporal signal to noise ratio (SNR) variations on MIMO channel capacity are investigated. Results from non-line of sight (NLOS) and line of sight (LOS) propagation scenarios are analyzed. While under NLOS conditions spatial smoothing significantly enhances the applicability of the Kronecker structure, under LOS conditions spatial smoothing does not help to improve the accuracy of the Kronecker model. It is also noticed that while the temporal SNR variation has significant impact on the capacity of MIMO wireless channel in a NLOS propagation scenario, the influence is smaller under LOS conditions. Theoretical investigation of antenna mutual coupling (MC) on the capacity of MIMO wireless channels is presented with particular emphasis on the case of high SNR scenario. It is shown that the effect of MC on MIMO channel capacity can be positive or negative depending on the spatial correlation properties of the propagation environment and the characteristics of the two ends MC matrices. The impact of phase noise (PN) on the accuracy of measured MIMO channel capacity is studied by considering its effect on both the spatial multiplexing gain and the power gain. It is shown that in the case of a low rank physical channel matrix the PN impact is more pronounced on the spatial multiplexing gain than on the power gain. Based on that an eigenvalue filtering (EVF) technique is proposed to improve the accuracy of the measured MIMO channel capacity.reviewe