Local Estimates for the Koornwinder Jacobi-Type Polynomials

In this paper we give some local estimates for the Koornwinder Jacobi-type polynomials by using asymptotic properties of Jacobi orthogonal polynomials

Molecular Model of Dynamic Social Network Based on E-mail communication

In this work we consider an application of physically inspired sociodynamical model to the modelling of the evolution of email-based social network. Contrary to the standard approach of sociodynamics, which assumes expressing of system dynamics with heuristically defined simple rules, we postulate the inference of these rules from the real data and their application within a dynamic molecular model. We present how to embed the n-dimensional social space in Euclidean one. Then, inspired by the Lennard-Jones potential, we define a data-driven social potential function and apply the resultant force to a real e-mail communication network in a course of a molecular simulation, with network nodes taking on the role of interacting particles. We discuss all steps of the modelling process, from data preparation, through embedding and the molecular simulation itself, to transformation from the embedding space back to a graph structure. The conclusions, drawn from examining the resultant networks in stable, minimum-energy states, emphasize the role of the embedding process projecting the non–metric social graph into the Euclidean space, the significance of the unavoidable loss of information connected with this procedure and the resultant preservation of global rather than local properties of the initial network. We also argue applicability of our method to some classes of problems, while also signalling the areas which require further research in order to expand this applicability domain

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

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

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

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

Effects of cadmium and phenanthrene mixtures on aquatic fungi and microbially mediated leaf litter decomposition

This version does not correspond to the published one. To access the final version go to: http://www.springerlink.com/content/t8t302617003m078/Urbanization and industrial activities have contributed to widespread contamination by metals and polycyclic aromatic hydrocarbons, but the combined effects of these toxics on aquatic biota and processes are poorly understood. We examined the effects of cadmium (Cd) and phenanthrene on the activity and diversity of fungi associated with decomposing leaf litter in streams. Leaves of Alnus glutinosa were immersed for 10 days in an unpolluted low-order stream in northwest Portugal to allow microbial colonization. Leaves were then exposed in microcosms for 14 days to Cd (0.06–4.5 mg L−1) and phenanthrene (0.2 mg L−1) either alone or in mixture. A total of 19 aquatic hyphomycete species were found sporulating on leaves during the whole study. The dominant species was Articulospora tetracladia, followed by Alatospora pulchella, Clavatospora longibrachiata, and Tetrachaetum elegans. Exposure to Cd and phenanthrene decreased the contribution of A. tetracladia to the total conidial production, whereas it increased that of A. pulchella. Fungal diversity, assessed as denaturing gradient gel electrophoresis fingerprinting or conidial morphology, was decreased by the exposure to Cd and/or phenanthrene. Moreover, increased Cd concentrations decreased leaf decomposition and fungal reproduction but did not inhibit fungal biomass production. Exposure to phenanthrene potentiated the negative effects of Cd on fungal diversity and activity, suggesting that the co-occurrence of these stressors may pose additional risk to aquatic biodiversity and stream ecosystem functioning.The Portuguese Foundation for the Science and Technology supported this work (POCI/MAR/56964/2004) and S. Duarte (SFRH/BPD/47574/2008