A Universal Model of Global Civil Unrest

Civil unrest is a powerful form of collective human dynamics, which has led to major transitions of societies in modern history. The study of collective human dynamics, including collective aggression, has been the focus of much discussion in the context of modeling and identification of universal patterns of behavior. In contrast, the possibility that civil unrest activities, across countries and over long time periods, are governed by universal mechanisms has not been explored. Here, we analyze records of civil unrest of 170 countries during the period 1919-2008. We demonstrate that the distributions of the number of unrest events per year are robustly reproduced by a nonlinear, spatially extended dynamical model, which reflects the spread of civil disorder between geographic regions connected through social and communication networks. The results also expose the similarity between global social instability and the dynamics of natural hazards and epidemics.Comment: 8 pages, 3 figure

Dynamical Patterns of Cattle Trade Movements

Despite their importance for the spread of zoonotic diseases, our understanding of the dynamical aspects characterizing the movements of farmed animal populations remains limited as these systems are traditionally studied as static objects and through simplified approximations. By leveraging on the network science approach, here we are able for the first time to fully analyze the longitudinal dataset of Italian cattle movements that reports the mobility of individual animals among farms on a daily basis. The complexity and inter-relations between topology, function and dynamical nature of the system are characterized at different spatial and time resolutions, in order to uncover patterns and vulnerabilities fundamental for the definition of targeted prevention and control measures for zoonotic diseases. Results show how the stationarity of statistical distributions coexists with a strong and non-trivial evolutionary dynamics at the node and link levels, on all timescales. Traditional static views of the displacement network hide important patterns of structural changes affecting nodes' centrality and farms' spreading potential, thus limiting the efficiency of interventions based on partial longitudinal information. By fully taking into account the longitudinal dimension, we propose a novel definition of dynamical motifs that is able to uncover the presence of a temporal arrow describing the evolution of the system and the causality patterns of its displacements, shedding light on mechanisms that may play a crucial role in the definition of preventive actions

Dynamical Patterns of Cattle Trade Movements

Despite their importance for the spread of zoonotic diseases, our understanding of the dynamical aspects characterizing the movements of farmed animal populations remains limited as these systems are traditionally studied as static objects and through simplified approximations. By leveraging on the network science approach, here we are able for the first time to fully analyze the longitudinal dataset of Italian cattle movements that reports the mobility of individual animals among farms on a daily basis. The complexity and inter-relations between topology, function and dynamical nature of the system are characterized at different spatial and time resolutions, in order to uncover patterns and vulnerabilities fundamental for the definition of targeted prevention and control measures for zoonotic diseases. Results show how the stationarity of statistical distributions coexists with a strong and non-trivial evolutionary dynamics at the node and link levels, on all timescales. Traditional static views of the displacement network hide important patterns of structural changes affecting nodes' centrality and farms' spreading potential, thus limiting the efficiency of interventions based on partial longitudinal information. By fully taking into account the longitudinal dimension, we propose a novel definition of dynamical motifs that is able to uncover the presence of a temporal arrow describing the evolution of the system and the causality patterns of its displacements, shedding light on mechanisms that may play a crucial role in the definition of preventive actions

Validating a test to measure the awareness and expression of anger

[xii], 96, [86] leaves ; 28 cm.Bibliography: leaves 89-96.Experimental, physiological, and theoretical literature on anger is reviewed briefly. It is concluded that there is a lack of consensus on standard definitions of anger, or on the nature of anger. The Buss-Durkee Hostility Inventory, The Oken Scale, The Gottschalk-Gleser Content Analysis Scales, and, The Reaction Inventory are reviewed and dismissed as adequate instruments for the measurement of the awareness and expression of anger. The awareness and Expression of Anger Indicator (AEAI) is presented as a test which purports to measure different dimensions of anger. Existing psychometric data on the AEAI is reviewed and it is concluded that further psychometric study on the reliability and validity of the AEAI is needed. The results indicate that the AEAI demonstrates 1. adequate internal reliability; 2. a factor structure which supports a distinction between non-induced awareness, expression and induced awareness of anger, 3. that there is some evidence of convergence between AEAI awareness measures and other awareness of anger measures, but no evidence of convergence between AEAI expression of anger measures and other measures of the same trait; and, 4. that AEAI scores show no positive relationship to scores on the social desirability sale but correlate positively with a measure of subjects' beliefs about the consequences of expressing anger. Discussion focuses on the effects of a weighting system on AEAI scores, the multidimensional nature of anger, and on more general issues in testing

Self-Organizing Networks in Complex Infrastructure Projects

While significant importance is given to establishing formal organizational and contractual hierarchies, existing project management techniques neglect the management of self-organizing networks in large-infrastructure projects. We offer a case-specific illustration of self-organization using network theory as an investigative lens. The findings have shown that these networks exhibit a high degree of sparseness, short path lengths, and clustering in dense “functional” communities around highly connected actors, thus demonstrating the small-world topology observed in diverse real-world self-organized networks. The study underlines the need for these non-contractual functions and roles to be identified and sponsored, allowing the self-organizing network the space and capacity to evolve

A dynamic model of time-dependent complex networks

The characterization of the "most connected" nodes in static or slowly evolving complex networks has helped in understanding and predicting the behavior of social, biological, and technological networked systems, including their robustness against failures, vulnerability to deliberate attacks, and diffusion properties. However, recent empirical research of large dynamic networks (characterized by connections that are irregular and evolve rapidly) has demonstrated that there is little continuity in degree centrality of nodes over time, even when their degree distributions follow a power law. This unexpected dynamic centrality suggests that the connections in these systems are not driven by preferential attachment or other known mechanisms. We present a novel approach to explain real-world dynamic networks and qualitatively reproduce these dynamic centrality phenomena. This approach is based on a dynamic preferential attachment mechanism, which exhibits a sharp transition from a base pure random walk scheme.Comment: 8 pages, 6 figures; This is a substantial revision of the previous versio

10 Years of C-K Theory: A Survey on the Academic and Industrial Impacts of a Design Theory.

The goal of our research1 was to understand what is expected today from a design theory and what types of impact such type of scientific proposition may reach. To answer these questions with a grounded approach we chosed to study the developement of C-K theory as phenomenon per se that can inform our research work. C-K theory is clearly recognized as a design theory and it is a good representative of the level of generality and abstraction of contemporary design theory. Indeed, the validity of the theory as such has already been documented (e.g. Hatchuel & Weil 2002, 2003, 2008, 2009; Kazakçi 2009; Reich et al 2010; Le Masson et al 2010; Ullah et al 2012). Instead the current work sets out to understand the dissemination and the impact of the theory in both academic and industrial fields. The data collection overlooks the literature on C-K theory in English and in French, and includes interviews and feedbacks of students and industrial partners who applied C-K methodologies and tools. This research confirms the rapid diffusion and multiples impact of C-K theory. Beyond, such study signals that there are important expectations and potential impacts of a Design Theory within the field of knowledge at large. However there are strong conditions to meet these expectations: generality, generativity, and relatedness to contemporary sciences. A similar research could be done on Nam Suh's axiomatic approach to further test these conditions. It is impossible to say what will be the next generations of Design theory but it is sure that they should progress on these directions