Parallel (k)(k)-Clique Community Detection on Large-Scale Networks

The analysis of real-world complex networks has been the focus of recent research. Detecting communities helps in uncovering their structural and functional organization. Valuable insight can be obtained by analyzing the dense, overlapping, and highly interwoven k-clique communities. However, their detection is challenging due to extensive memory requirements and execution time. In this paper, we present a novel, parallel k-clique community detection method, based on an innovative technique which enables connected components of a network to be obtained from those of its subnetworks. The novel method has an unbounded, user-configurable, and input-independent maximum degree of parallelism, and hence is able to make full use of computational resources. Theoretical tight upper bounds on its worst case time and space complexities are given as well. Experiments on real-world networks such as the Internet and the World Wide Web confirmed the almost optimal use of parallelism (i.e., a linear speedup). Comparisons with other state-of-the-art k-clique community detection methods show dramatic reductions in execution time and memory footprint. An open-source implementation of the method is also made publicly available

Comparison between Artisanal Fishery and Manila Clam Harvesting in the Venice Lagoon by Using Ecosystem Indicators: An Ecological Economics Perspective

Artisanal fishery in the Venice lagoon is a multi-target activity with a long tradition. It was the main fishing activity till the late ’80s when, after the introduction and spread of the Manila clam (Tapes philippinarum), the mechanical clam harvesting started. A mass-balance model of the lagoon ecosystem was developed using the Ecopath with Ecosim software. 73 scenarios, obtained by changing the fishing effort of the two different types of fishery, were used to explore their impact on the ecosystem. A set of indicators was applied in order to compare the two fishing activities. The results obtained showed that the two activities are strongly interlinked, even through they don’t exploit the same resources. The mechanical clam harvesting could reasonably be considered to be the driving force; it is capable of determining the state of lagoon ecosystem. The above mentioned factors create a lot of conflict between the two types of fishery.Artisanal fishery, Indicators, Dynamic model, Venice Lagoon, Fishing impact, Social and economic value

Large-Scale Networks: Algorithms, Complexity and Real Applications

Networks have broad applicability to real-world systems, due to their ability to model and represent complex relationships. The discovery and forecasting of insightful patterns from networks are at the core of analytical intelligence in government, industry, and science. Discoveries and forecasts, especially from large-scale networks commonly available in the big-data era, strongly rely on fast and efficient network algorithms. Algorithms for dealing with large-scale networks are the first topic of research we focus on in this thesis. We design, theoretically analyze and implement efficient algorithms and parallel algorithms, rigorously proving their worst-case time and space complexities. Our main contributions in this area are novel, parallel algorithms to detect k-clique communities, special network groups which are widely used to understand complex phenomena. The proposed algorithms have a space complexity which is the square root of that of the current state-of-the-art. Time complexity achieved is optimal, since it is inversely proportional to the number of processing units available. Extensive experiments were conducted to confirm the efficiency of the proposed algorithms, even in comparison to the state-of-the-art. We experimentally measured a linear speedup, substantiating the optimal performances attained. The second focus of this thesis is the application of networks to discover insights from real-world systems. We introduce novel methodologies to capture cross correlations in evolving networks. We instantiate these methodologies to study the Internet, one of the most, if not the most, pervasive modern technological system. We investigate the dynamics of connectivity among Internet companies, those which interconnect to ensure global Internet access. We then combine connectivity dynamics with historical worldwide stock markets data, and produce graphical representations to visually identify high correlations. We find that geographically close Internet companies offering similar services are driven by common economic factors. We also provide evidence on the existence and nature of hidden factors governing the dynamics of Internet connectivity. Finally, we propose network models to effectively study the Internet Domain Name System (DNS) traffic, and leverage these models to obtain rankings of Internet domains as well as to identify malicious activities

Aging in Financial Market

We analyze the data of the Italian and U.S. futures on the stock markets and we test the validity of the Continuous Time Random Walk assumption for the survival probability of the returns time series via a renewal aging experiment. We also study the survival probability of returns sign and apply a coarse graining procedure to reveal the renewal aspects of the process underlying its dynamics.Comment: To appear in special issue of Chaos, Solitons and Fractal

Combination antifungal therapy and surgery for the treatment of invasive pulmonary aspergillosis after hematopoietic stem cell transplantation

An 8-year old boy, affected by severe aplastic anemia, developed a probable pulmonary invasive aspergillosis (IA) early after a second unrelated allogeneic hematopoietic stem cell transplant (HSCT). He was treated promptly with the combination of liposomal amphotericin B and caspofungin. Despite the initial stabilization, the patient deteriorated and the antifungal therapy was switched to voriconazole and caspofungin. The patient gradually improved and was discharged home on day +29 post-HSCT on oral voriconazole. On day +119, a sudden episode of hemoptysis occurred and a right superior lobectomy was decided to remove the residual aspergilloma. The patient is now alive and well more than 24 months from HSCT. This case demonstrated that antifungal combination therapy and surgery are valid options to cure pulmonary IA even in patients at high-risk and severely immunosuppressed

A random telegraph signal of Mittag-Leffler type

A general method is presented to explicitly compute autocovariance functions for non-Poisson dichotomous noise based on renewal theory. The method is specialized to a random telegraph signal of Mittag-Leffler type. Analytical predictions are compared to Monte Carlo simulations. Non-Poisson dichotomous noise is non-stationary and standard spectral methods fail to describe it properly as they assume stationarity.Comment: 13 pages, 3 figures, submitted to PR

The Influence of Manga on the Graphic Novel

This material has been published in The Cambridge History of the Graphic Novel edited by Jan Baetens, Hugo Frey, Stephen E. Tabachnick. This version is free to view and download for personal use only. Not for re-distribution, re-sale or use in derivative works. © Cambridge University PressProviding a range of cogent examples, this chapter describes the influences of the Manga genre of comics strip on the Graphic Novel genre, over the last 35 years, considering the functions of domestication, foreignisation and transmedia on readers, markets and forms

The Underlying Clustered Structure of Internet: A New Method to Efficiently Extract Communities

Uncovering the underlying clustered structure of Internet is essential to unveil insights into its functional organization. This thesis is focused on discovering such clustered structure in terms of the building blocks it is composed of, building blocks ofter referred to as communities. There have been proposed several definitions of community in the literature and in this work we will try to present some of the most studied and widely used, discussing about their characteristics and properties. Among these definitions, the k-clique community has seemed us the most significant in catching the characteristics cohese groups shoud have. The reasons have driven us to focus on such definition of community will be extensively discussed. Extracting k-clique communities requires a substantial amount of computational load at least for real-world datasets. At the best of our knowledge, no existing software tool has been able to extract these communities from the Internet at the Autonomous System level of abstraction and this has encouraged us in developing a new parallel method that could extract communities efficiently by exploiting a parallel shared memory computing architecture togheter with particular data structures known as disjoint-set data structures. In this thesis the new method will be presented and discussed and experimental results showing the efficiency and the effectivity of this method in extracting communities will be exposed. This work will be concluded with the analysis of the structural properties of the Interent in terms of communities and interconnections between them using both sigle- and multi-criterion scores as meters of the quality of such extracted clusters

Eterno presente.

Analisi dello stato macropolitico e micropolitico dell'Occidente, con particolare riguardo alle inflessioni psicologiche