Characterizing Distances of Networks on the Tensor Manifold

At the core of understanding dynamical systems is the ability to maintain and control the systems behavior that includes notions of robustness, heterogeneity, or regime-shift detection. Recently, to explore such functional properties, a convenient representation has been to model such dynamical systems as a weighted graph consisting of a finite, but very large number of interacting agents. This said, there exists very limited relevant statistical theory that is able cope with real-life data, i.e., how does perform analysis and/or statistics over a family of networks as opposed to a specific network or network-to-network variation. Here, we are interested in the analysis of network families whereby each network represents a point on an underlying statistical manifold. To do so, we explore the Riemannian structure of the tensor manifold developed by Pennec previously applied to Diffusion Tensor Imaging (DTI) towards the problem of network analysis. In particular, while this note focuses on Pennec definition of geodesics amongst a family of networks, we show how it lays the foundation for future work for developing measures of network robustness for regime-shift detection. We conclude with experiments highlighting the proposed distance on synthetic networks and an application towards biological (stem-cell) systems.Comment: This paper is accepted at 8th International Conference on Complex Networks 201

Nuclear Diacylglycerol Produced by Phosphoinositide-specific Phospholipase C Is Responsible for Nuclear Translocation of Protein Kinase C-α

It is well established that an independent inositide cycle is present within the nucleus, where it is involved in the control of cell proliferation and differentiation. Previous results have shown that when Swiss 3T3 cells are treated with insulin-like growth factor-I (IGF-I) a rapid and sustained increase in mass of diacylglycerol (DAG) occurs within the nuclei, accompanied by a decrease in the levels of both phosphatidylinositol 4-phosphate and phosphatidylinositol 4,5-bisphosphate. However, it is unclear whether or not other lipids could contribute to this prolonged rise in DAG levels. We now report that the IGF-I-dependent increase in nuclear DAG production can be inhibited by the specific phosphatidylinositol phospholipase C inhibitor 1-O-octadeyl-2-O-methyl-sn-glycero-3-phosphocholine or by neomycin sulfate but not by the purported phosphatidylcholine-phospholipase C specific inhibitor D609 or by inhibitors of phospholipase D-mediated DAG generation. Treatment of cells with 1-O-octadeyl-2-O-methyl-sn-glycero-3-phosphocholine or neomycin sulfate inhibited translocation of protein kinase C-alpha to the nucleus. Moreover, exposure of cells to 1-O-octadeyl-2-O-methyl-sn-glycero-3-phosphocholine, but not to D609, dramatically reduced the number of cells entering S-phase upon stimulation with IGF-I. These results suggest that the only phospholipase responsible for generation of nuclear DAG after IGF-I stimulation of 3T3 cells is PI-PLC. When this activity is inhibited, neither DAG rise is seen nor PKC-alpha translocation to the nucleus occurs. Furthermore, this PI-PLC activity appears to be essential for the G0/G1 to S-phase transition

Home-based cognitive training in pediatric patients with acquired brain injury: preliminary results on efficacy of a randomized clinical trial

Cognitive rehabilitation may compensate for cognitive deficits of children with acquired brain injury (ABI), capitalizing on the use-dependent plasticity of a developing brain. Remote computerized cognitive training (CCT) may be delivered to patients in ecological settings, ensuring rehabilitation continuity. This work evaluated cognitive and psychological adjustment outcomes of an 8-week multi-domain, home-based CCT (Lumosity Cognitive Training) in a sample of patients with ABI aged 11–16 years. Two groups of patients were engaged in five CCT sessions per week for eight weeks (40 sessions). According to a stepped-wedge research design, one group (Training-first Group) started the CCT immediately, whereas the other group (Waiting-first Group) started the CCT after a comparable time of waiting list. Changes after the training and after the waiting period were compared in the two groups. Both groups improved in visual-spatial working memory more after the training than after the waiting-list period. The Training-first group improved also in arithmetic calculation speed. Findings indicate that a multi-domain CCT can produce benefits in visual-spatial working memory, probably because, in accordance with previous research, computer games heavily tax visuo-spatial abilities. This suggests that the prolonged stimulation of the same cognitive ability may generate the greatest benefits in children with ABI

Are your students safe to learn? The role of lecturer’s authentic leadership in the creation of psychologically safe environments and their impact on academic performance:The role of teacher's authentic leadership on the creation of psychologically safe environments and their impact on academic performance

As the role of students and lecturers in higher education changes, several questions emerge about the role of each of them on students? academic performance. This includes questions regarding the impact of the relationships between students, lecturer?s characteristics and the social environment on students? performance. To address these questions, this article reports a study of the impact of lecturer authentic leadership, psychological safety and network density on academic performance. It explores the relationship between network density, psychological safety and lecturer authentic leadership. A questionnaire was distributed to undergraduate students. A positive impact of lecturer authentic leadership and psychological safety on academic performance was found. Students from high-density groups tended to show better academic performance, higher psychological safety and tended to see their lecturers as being more authentic. A reflection on the role of the lecturer in higher education settings is presented. It also presents some recommendations on how student academic performance can be improved by the adoption of specific behaviours by their lecturer

Percolation theory applied to measures of fragmentation in social networks

We apply percolation theory to a recently proposed measure of fragmentation $F$ for social networks. The measure $F$ is defined as the ratio between the number of pairs of nodes that are not connected in the fragmented network after removing a fraction $q$ of nodes and the total number of pairs in the original fully connected network. We compare $F$ with the traditional measure used in percolation theory, $P_{\infty}$, the fraction of nodes in the largest cluster relative to the total number of nodes. Using both analytical and numerical methods from percolation, we study Erd\H{o}s-R\'{e}nyi (ER) and scale-free (SF) networks under various types of node removal strategies. The removal strategies are: random removal, high degree removal and high betweenness centrality removal. We find that for a network obtained after removal (all strategies) of a fraction $q$ of nodes above percolation threshold, $P_{\infty}\approx (1-F)^{1/2}$. For fixed $P_{\infty}$ and close to percolation threshold ($q=q_c$), we show that $1-F$ better reflects the actual fragmentation. Close to $q_c$, for a given $P_{\infty}$, $1-F$ has a broad distribution and it is thus possible to improve the fragmentation of the network. We also study and compare the fragmentation measure $F$ and the percolation measure $P_{\infty}$ for a real social network of workplaces linked by the households of the employees and find similar results.Comment: submitted to PR

Finding the Needle in a Haystack: Who are the Most Central Authors Within a Domain?

The speed at which new scientific papers are published has increased dramatically, while the process of tracking the most recent publications having a high impact has become more and more cumbersome. In order to support learners and researchers in retrieving relevant articles and identifying the most central researchers within a domain, we propose a novel 2-mode multilayered graph derived from Cohesion Network Analysis (CNA). The resulting extended CNA graph integrates both authors and papers, as well as three principal link types: coauthorship, co-citation, and semantic similarity among the contents of the papers. Our rankings do not rely on the number of published documents, but on their global impact based on links between authors, citations, and semantic relatedness to similar articles. As a preliminary validation, we have built a network based on the 2013 LAK dataset in order to reveal the most central authors within the emerging Learning Analytics domain.This study is part of the RAGE project. The RAGE project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains

El perfil de las revistas españolas de comunicación (2007-2008)

La evolución de los parámetros de publicación científi ca y de las exigencias de la carrera académica en España ha provocado cambios en las revistas científi cas y, entre ellas, las de comunicación. Este artículo caracteriza las revistas nucleares españolas en el ámbito de la comunicación a través de variables como el volumen de artículos publicados, el idioma empleado, la procedencia y las redes de colaboración de sus autores o los patrones de citación en el período 2007-2008. Mediante técnicas bibliométricas y el análisis de redes sociales se obtiene un perfi l que muestra las similitudes y las diferencias entre las diferentes revistas y el perfi l del conjunto del sistema.The evolution of parameters for scholarly publications and of academic requirements in Spain has resulted in changes to scholarly journals, among others, those in the fi eld of communication sciences. This article characterizes the core Spanish communication journals according to variables such as the number of published articles, language, author institution and collaboration networks, and citation patterns during 2007-2008. By applying bibliometric techniques and social network analysis, a profile showing similarities and differences among the journals is obtained, as well as a profile of the overall system

The impact of partially missing communities~on the reliability of centrality measures

Network data is usually not error-free, and the absence of some nodes is a very common type of measurement error. Studies have shown that the reliability of centrality measures is severely affected by missing nodes. This paper investigates the reliability of centrality measures when missing nodes are likely to belong to the same community. We study the behavior of five commonly used centrality measures in uniform and scale-free networks in various error scenarios. We find that centrality measures are generally more reliable when missing nodes are likely to belong to the same community than in cases in which nodes are missing uniformly at random. In scale-free networks, the betweenness centrality becomes, however, less reliable when missing nodes are more likely to belong to the same community. Moreover, centrality measures in scale-free networks are more reliable in networks with stronger community structure. In contrast, we do not observe this effect for uniform networks. Our observations suggest that the impact of missing nodes on the reliability of centrality measures might not be as severe as the literature suggests