Connections between cosmic-ray physics, gamma-ray data analysis and Dark Matter detection

Cosmic-ray (CR) physics has been a prolific field of research for over a century. The open problems related to CR acceleration, transport and modulation are deeply connected with the indirect searches for particle dark matter (DM). In particular, the high-quality gamma-ray data released by Fermi-LAT are under the spotlight in the scientific community because of a recent claim about a inner Galaxy anomaly: The necessity to disentangle the astrophysical emission due to CR interactions from a possible DM signal is therefore compelling and requires a deep knowledge of several non-trivial aspects regarding CR physics. I review all these connections in this contribution. In the first part, I present a detailed overview on recent results regarding modeling of cosmic-ray (CR) production and propagation: I focus on the necessity to go beyond the standard and simplified picture of uniform and homogeneous diffusion, showing that gamma-ray data point towards different transport regimes in different regions of the Galaxy; I sketch the impact of large-scale structure on CR observables, and -- concerning the interaction with the Heliosphere -- I mention the necessity to consider a charge-dependent modulation scenario. In the second part, all these aspects are linked to the DM problem. I analyze the claim of a inner Galaxy excess and discuss the impact of the non-trivial aspects presented in the first part on our understanding of this anomaly.Comment: 16 pages, 8 figures. Proceeding of the ICRC 201

The politics of policy resistance: reconstructing higher education in Kosovo

This article considers attempts to incorporate lessons and transfer policies from Britain in the reconstruction of Higher Education in Kosovo after 1999. In doing so, it employs aspects of the lesson-drawing framework developed by Rose (1991 and 2001) and the related concepts of policy transfer and policy diffusion. Drawing on contributions from anthropology and democratization studies, we suggest development of the public policy frameworks for lesson drawing and policy transfer in circumstances characterised by asymmetric interdependence, in which the tactics and strategies of policy resistance by ‘subordinate’ recipient actors can be crucial. This article details the nature of policy resistance and sets out hypotheses for future research

Interests Diffusion in Social Networks

Understanding cultural phenomena on Social Networks (SNs) and exploiting the implicit knowledge about their members is attracting the interest of different research communities both from the academic and the business side. The community of complexity science is devoting significant efforts to define laws, models, and theories, which, based on acquired knowledge, are able to predict future observations (e.g. success of a product). In the mean time, the semantic web community aims at engineering a new generation of advanced services by defining constructs, models and methods, adding a semantic layer to SNs. In this context, a leapfrog is expected to come from a hybrid approach merging the disciplines above. Along this line, this work focuses on the propagation of individual interests in social networks. The proposed framework consists of the following main components: a method to gather information about the members of the social networks; methods to perform some semantic analysis of the Domain of Interest; a procedure to infer members' interests; and an interests evolution theory to predict how the interests propagate in the network. As a result, one achieves an analytic tool to measure individual features, such as members' susceptibilities and authorities. Although the approach applies to any type of social network, here it is has been tested against the computer science research community. The DBLP (Digital Bibliography and Library Project) database has been elected as test-case since it provides the most comprehensive list of scientific production in this field.Comment: 30 pages 13 figs 4 table

What Have We Learned from Policy Transfer Research? Dolowitz and Marsh Revisited

Over the last decade, policy transfer has emerged as an important concept within public policy analysis, guiding both theoretical and empirical research spanning many venues and issue areas. Using Dolowitz and Marsh's 1996 stocktake as its starting point, this article reviews what has been learned by whom and for what purpose. It finds that the literature has evolved from its rather narrow, state-centred roots to cover many more actors and venues. While policy transfer still represents a niche topic for some researchers, an increasing number have successfully assimilated it into wider debates on topics such as globalisation, Europeanisation and policy innovation. This article assesses the concept's position in the overall ‘tool-kit’ of policy analysis, examines some possible future directions and reflects on their associated risks and opportunities

Together we stand, Together we fall, Together we win: Dynamic Team Formation in Massive Open Online Courses

Massive Open Online Courses (MOOCs) offer a new scalable paradigm for e-learning by providing students with global exposure and opportunities for connecting and interacting with millions of people all around the world. Very often, students work as teams to effectively accomplish course related tasks. However, due to lack of face to face interaction, it becomes difficult for MOOC students to collaborate. Additionally, the instructor also faces challenges in manually organizing students into teams because students flock to these MOOCs in huge numbers. Thus, the proposed research is aimed at developing a robust methodology for dynamic team formation in MOOCs, the theoretical framework for which is grounded at the confluence of organizational team theory, social network analysis and machine learning. A prerequisite for such an undertaking is that we understand the fact that, each and every informal tie established among students offers the opportunities to influence and be influenced. Therefore, we aim to extract value from the inherent connectedness of students in the MOOC. These connections carry with them radical implications for the way students understand each other in the networked learning community. Our approach will enable course instructors to automatically group students in teams that have fairly balanced social connections with their peers, well defined in terms of appropriately selected qualitative and quantitative network metrics.Comment: In Proceedings of 5th IEEE International Conference on Application of Digital Information & Web Technologies (ICADIWT), India, February 2014 (6 pages, 3 figures

Dynamic Monopolies in Colored Tori

The {\em information diffusion} has been modeled as the spread of an information within a group through a process of social influence, where the diffusion is driven by the so called {\em influential network}. Such a process, which has been intensively studied under the name of {\em viral marketing}, has the goal to select an initial good set of individuals that will promote a new idea (or message) by spreading the "rumor" within the entire social network through the word-of-mouth. Several studies used the {\em linear threshold model} where the group is represented by a graph, nodes have two possible states (active, non-active), and the threshold triggering the adoption (activation) of a new idea to a node is given by the number of the active neighbors. The problem of detecting in a graph the presence of the minimal number of nodes that will be able to activate the entire network is called {\em target set selection} (TSS). In this paper we extend TSS by allowing nodes to have more than two colors. The multicolored version of the TSS can be described as follows: let $G$ be a torus where every node is assigned a color from a finite set of colors. At each local time step, each node can recolor itself, depending on the local configurations, with the color held by the majority of its neighbors. We study the initial distributions of colors leading the system to a monochromatic configuration of color $k$, focusing on the minimum number of initial $k$-colored nodes. We conclude the paper by providing the time complexity to achieve the monochromatic configuration

BOUNDARY ORGANIZATIONS: AN EFFICIENT STRUCTURE FOR MANAGING KNOWLEDGE IN DECISION-MAKING UNDER UNCERTAINTY

Modern environmental issues imply that decision-makers take into account opinions from experts of different spheres. Boundary organizations are institutions able to cross the gap between different areas of expertise and to act beyond the boundaries while remaining accountable to each side: by encouraging a flow of useful information, they permit an exchange to take place while maintaining the authority of each side, in order to provide a better knowledge and understanding of a situation characterized by uncertainty. Though never formally proved, this hypothesis is widely accepted based on the observation of existing boundary organizations. Through a multi-agent simulation, it is possible to assess their impact on the diffusion of opinions among experts. This virtual interaction of heterogeneous agents based on a model of continuous opinion dynamics over two dimensions, shows that boundary organizations have a significant quantitative impact on the diversity of opinions expressed and the number of experts agreeing to each emerging position.boundary organization, opinion, knowledge diffusion, multi-agent system, Agribusiness, Labor and Human Capital, Public Economics,