393,022 research outputs found

    Transport of measures on networks

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    In this paper we formulate a theory of measure-valued linear transport equations on networks. The building block of our approach is the initial/boundary-value problem for the measure-valued linear transport equation on a bounded interval, which is the prototype of an arc of the network. For this problem we give an explicit representation formula of the solution, which also considers the total mass flowing out of the interval. Then we construct the global solution on the network by gluing all the measure-valued solutions on the arcs by means of appropriate distribution rules at the vertexes. The measure-valued approach makes our framework suitable to deal with multiscale flows on networks, with the microscopic and macroscopic phases represented by Lebesgue-singular and Lebesgue-absolutely continuous measures, respectively, in time and space

    Topology and energy transport in networks of interacting photosynthetic complexes

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    We address the role of topology in the energy transport process that occurs in networks of photosynthetic complexes. We take inspiration from light harvesting networks present in purple bacteria and simulate an incoherent dissipative energy transport process on more general and abstract networks, considering both regular structures (Cayley trees and hyperbranched fractals) and randomly-generated ones. We focus on the the two primary light harvesting complexes of purple bacteria, i.e., the LH1 and LH2, and we use network-theoretical centrality measures in order to select different LH1 arrangements. We show that different choices cause significant differences in the transport efficiencies, and that for regular networks centrality measures allow to identify arrangements that ensure transport efficiencies which are better than those obtained with a random disposition of the complexes. The optimal arrangements strongly depend on the dissipative nature of the dynamics and on the topological properties of the networks considered, and depending on the latter they are achieved by using global vs. local centrality measures. For randomly-generated networks a random arrangement of the complexes already provides efficient transport, and this suggests the process is strong with respect to limited amount of control in the structure design and to the disorder inherent in the construction of randomly-assembled structures. Finally, we compare the networks considered with the real biological networks and find that the latter have in general better performances, due to their higher connectivity, but the former with optimal arrangements can mimic the real networks' behaviour for a specific range of transport parameters. These results show that the use of network-theoretical concepts can be crucial for the characterization and design of efficient artificial energy transport networks.Comment: 14 pages, 16 figures, revised versio

    Supporting policy packages: the future of road pricing in the UK

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    Transport is already a large component of our economy and society. Historically, transport programmes were substantially about developing basic infrastructure networks. Now the emphasis is on the active management of systems and operating them to maximum advantage in the face of growing travel demand and capacity limitations. Combined developments in technology and the world economy have accelerated change to almost unpredictable levels. The change affects many areas and transport is not an exception. With new vehicle technologies, radical policies and the persistent growth in private and commercial vehicles, a new changing transport landscape is emerging. One of these changes comes in the form of sustainable transport management - managing the demand of existing infrastructure networks. The role of demand management has been illustrated in many reports and papers and it seems that governments are becoming more aware of it. This paper focuses on one particular demand management policy that is often regarded as radical and generally unacceptable. Road pricing often gets delayed or abandoned due to controversy, disagreements, unanticipated problems and a whole host of other delaying factors. There are complex interactions in transport management - there is a need for cooperation between networks, stakeholders and different authorities. Single measures that focus on 'sustainable transport' usually address a limited set of objectives and are not usually combined with other policy measures. When combined, it is sometimes unclear whether the multiple interactions between policy tools and implementation networks have been considered. An emerging case of implementation of a policy package in the UK is the support of road pricing initiatives combined with public transport improvements by the Transport Innovation Fund. The paper will present a review of the UK road pricing situation along with key implementation factors that show firstly the importance of combining policy tools and secondly the necessity in creating and maintaining strong implementation networks

    Transport on weighted Networks: when correlations are independent of degree

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    Most real-world networks are weighted graphs with the weight of the edges reflecting the relative importance of the connections. In this work, we study non degree dependent correlations between edge weights, generalizing thus the correlations beyond the degree dependent case. We propose a simple method to introduce weight-weight correlations in topologically uncorrelated graphs. This allows us to test different measures to discriminate between the different correlation types and to quantify their intensity. We also discuss here the effect of weight correlations on the transport properties of the networks, showing that positive correlations dramatically improve transport. Finally, we give two examples of real-world networks (social and transport graphs) in which weight-weight correlations are present.Comment: 8 pages, 8 figure

    Threshold-activated transport stabilizes chaotic populations to steady states

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    We explore Random Scale-Free networks of populations, modelled by chaotic Ricker maps, connected by transport that is triggered when population density in a patch is in excess of a critical threshold level. Our central result is that threshold-activated dispersal leads to stable fixed populations, for a wide range of threshold levels. Further, suppression of chaos is facilitated when the threshold-activated migration is more rapid than the intrinsic population dynamics of a patch. Additionally, networks with large number of nodes open to the environment, readily yield stable steady states. Lastly we demonstrate that in networks with very few open nodes, the degree and betweeness centrality of the node open to the environment has a pronounced influence on control. All qualitative trends are corroborated by quantitative measures, reflecting the efficiency of control, and the width of the steady state window
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