Improved spectral algorithm for the detection of network communities

We review and improve a recently introduced method for the detection of communities in complex networks. This method combines spectral properties of some matrices encoding the network topology, with well known hierarchical clustering techniques, and the use of the modularity parameter to quantify the goodness of any possible community subdivision. This provides one of the best available methods for the detection of community structures in complex systems.Comment: 4 pages, 1 fugure; to appear in the Proceedings of the 8th Granada Seminar - Computational and Statistical Physic

Network synchronization: Optimal and Pessimal Scale-Free Topologies

By employing a recently introduced optimization algorithm we explicitely design optimally synchronizable (unweighted) networks for any given scale-free degree distribution. We explore how the optimization process affects degree-degree correlations and observe a generic tendency towards disassortativity. Still, we show that there is not a one-to-one correspondence between synchronizability and disassortativity. On the other hand, we study the nature of optimally un-synchronizable networks, that is, networks whose topology minimizes the range of stability of the synchronous state. The resulting ``pessimal networks'' turn out to have a highly assortative string-like structure. We also derive a rigorous lower bound for the Laplacian eigenvalue ratio controlling synchronizability, which helps understanding the impact of degree correlations on network synchronizability.Comment: 11 pages, 4 figs, submitted to J. Phys. A (proceedings of Complex Networks 2007

Innovation, the game and the smart city

At our times the gap between opportunities and practical applications of the “Smart City Concept” is very large, and the risk for Administrations is to exceed in pilots primoted by large Public Companies in order to promote their products and services regardless of the local identity and social capital. “Connected City Council” is a project of a real/virtual platform created with the goal of encouraging the promotion of the “genius loci” and the increase of “quality of life” in urban centers as a certification of “smartness”. The basic idea is to tie innovative academic research, the IT industry, SMEs and practitioners of innovation in the creation of a number of tools to be used (remotely or in presence) for the assessment and the definition of different future scenarios related to every City as a Smart City . “Connected City Council” is an online platform providing: The design of a Method of assessment for Governement, Utilities, and Organisations, according to Qualitative Criteria, based on the Gamification and Serious Game principles. A Method of Scenarios Planning, aimed to identify the development prospects for the urban areas becoming “smart”; The development of a online tool allowing stakeholders to evaluate their behaviour and their governement paths in a simple but effective methods, providing a preliminary representation of their situation. The opening of “territorial meetings” designed to meet and dialogue with stakeholders in order to share both the expressed and the latent needs, spreading the culture of smart city as a value fot the territories. The creation of an analysis tool that allows the collection of data and API in order to assess the evolution of the model. The goal is to create a network of Cities sharing their experience, reuse projects and tools, and to innovate business models related to the public administration, multi-utilities and all public and private entities lifes, creating tools that can provide a set of tools, with basic services free of charge. The aim is to enable them to have a representation of their condition compared to the theme of smartness and its sustainability. Connecting City Council is now in a beta version, www.connectedicitycouncil.com, realized by 3 Italian SMEs, with the cooperation of hepia.ge and funded by Lombardy Region. The project aims to be in an european scale in 2015

Probability of graphs with large spectral gap by multicanonical Monte Carlo

Graphs with large spectral gap are important in various fields such as biology, sociology and computer science. In designing such graphs, an important question is how the probability of graphs with large spectral gap behaves. A method based on multicanonical Monte Carlo is introduced to quantify the behavior of this probability, which enables us to calculate extreme tails of the distribution. The proposed method is successfully applied to random 3-regular graphs and large deviation probability is estimated.Comment: 3pages 4figure

The spectral dimension of random trees

We present a simple yet rigorous approach to the determination of the spectral dimension of random trees, based on the study of the massless limit of the Gaussian model on such trees. As a byproduct, we obtain evidence in favor of a new scaling hypothesis for the Gaussian model on generic bounded graphs and in favor of a previously conjectured exact relation between spectral and connectivity dimensions on more general tree-like structures.Comment: 14 pages, 2 eps figures, revtex4. Revised version: changes in section I

Dose Delivery Concept and Instrumentation

Radiation therapy aims to deliver the prescribed amount of dose to a tumour at the same time as sparing the surrounding tissues as much as possible. In charged particle therapy, delivering the prescribed dose is equivalent to delivering the prescribed number of ions of a given energy at each position of the irradiation field. The accurate delivery is committed to a dose delivery (DD) system that shapes, guides and controls the beam before the patient entrance. Most of the early DD systems provided uniform lateral dose profiles by using different devices, mainly patient-specific, placed in the beam line to shape the three-dimensional final target dose. More recently, systems that provide highly conformal dose distributions using thousands of narrow beams at well-defined energy were developed which feature advanced scanning magnets and real-time beam monitors, without patient-specific hardware. This lecture will cover the general dose delivery concept as well as the different DD instrumentations depending mainly on the beam delivery technique and on the particle and accelerator types. Some characteristic worldwide DD and beam monitor systems will be mentioned.Comment: presented at the CAS- CERN Accelerator School on Accelerators for Medical Application, V\"osendorf, Austria, 26 May - 5 June, 201

Community detection in complex networks using Extremal Optimization

We propose a novel method to find the community structure in complex networks based on an extremal optimization of the value of modularity. The method outperforms the optimal modularity found by the existing algorithms in the literature. We present the results of the algorithm for computer simulated and real networks and compare them with other approaches. The efficiency and accuracy of the method make it feasible to be used for the accurate identification of community structure in large complex networks.Comment: 4 pages, 4 figure