Summary

20090506_fidis_D3.12 final 1.0.od

Summary

fidis-wp3-del3.15a.IMS_database_V1.0.do

Soil tripartite interactions between host plants, viruses and the protist vectors Polymyxa

Viral diseases transmitted by Polymyxa involve complex soil-borne pathosystems involving three actors: a plant host, a root obligate endoparasitic protist vector (Polymyxa spp.) and viruses. These pathosystems are spread worldwide, in both temperate and tropical areas. They affect numerous host plants (both monocotyledons and dicotyledons) due to the large diversity of the Polymyxa-virus pathosystems. Our research aims to assess how the host plant,Polymyxa and the viruses they vector interact, mainly focusing on two Polymyxa-virus models for which genomic data are available : (1) the Polymyxa betae – Beet necrotic yellow vein virus (BNYVV) pathosystem on sugar beets and (2) the Polymyxa graminis – Rice stripe necrosis virus (RSNV) pathosystem on rice. Recent genomic and transcriptomic data regarding the vector Polymyxa open new pportunities to understand the nature and specialization of the Polymyxa-host interactions. It allows a better understanding of how Polymyxa manage to bypass host defenses and paves the way for identifying effectors involved in host defenses manipulation. Additionally, the first transcriptomic data of in vivo transmission of virus by Polymyxa clarify how the virus impacts plant defenses and therefore Polymyxa-host interactions. These transcriptomic results also give insight on the specificity Polymyxa-virus interaction

Knowledge and non-knowledge in the liberalization of Belgian network industries: The role of information, egocentrism and self-esteem in policy learning

Policy learning is the mechanism through which actors involved in a policy subsystem revise their beliefs and preferences toward a policy over time – a crucial dynamic of stability or change of public policies. While the social dimension of this dynamic has been extensively researched, the individual psychology of policy learning remains a black box. Yet, this is a key missing link between policy learning and settings or practices that could model it. This paper addresses this research program by looking at two mental constructs susceptible to encourage policy actors to stick to their own point of view rather than to assimilate new policy information: egocentrism and self-esteem. The test of the hypotheses is based on regression analyses of a survey conducted in 2012 among 289 Belgian policy actors who had been involved, during the last two decades, in the European liberalization policy process of two network industries: the rail and electricity sectors. The findings are threefold. First, rational knowledge utilization remains a stronger cognitive dynamic of information processing than egocentrism and self-esteem. Second,still, egocentrism is not only a source of biased assimilation of policy information: it also directly induces a less positive alignment of policy actors’ preferences toward liberalization over time. Third, the results fail to confirm my theoretical expectations about the relation between self-esteem and policy learning. The theoretical and practical implications of these results are discussed

Summary

Usability is an important factor influencing the acceptance of technologyrelated products and subsequently the decision process to use or buy them. For this reason usability has been of interest in market research for many years. However, in the context of user-controlled Identity Management Systems (IMS) hardly any comparative usability studies have been published. This document gives an overview of established evaluation methods and criteria for usability and analyses which methods and criteria are suited for user controlled IMS. The selected methods and criteria are applied to twelve IMS in six functional classes. These classes include user controlled identifier management, policy management, form filling, context monitoring and history management. Nine of these IMS are further analysed in depth and the results of the tests are published in this report

Summary

Deliverable 7.2 represents a genuine attempt to crystallise the multi-disciplinary nature of the FIDIS Network of Excellence in a document assessing the many facets of profiling, with contributions coming from across a wide spectrum of disciplines. Profiling is a powerful, critical and worrying technology because it is probably the only way that massive volumes of data about individual and group behaviour can be mined, whether for nefarious or benign purposes. Ever larger volumes of data have been the holy grail of generations of social scientists, medical researchers and technologists, and with profiling alongside new data-gathering technologies such data is available with the means to mine it for all its value. This deliverable examines how different approaches to profiling are taken, reviewing along the way some of the different technology contexts in which it can be used. Though matters of privacy and security loom behind every corner, the main focus of this deliverable is not on such issues. Subsequent deliverables will move into this. Clearly, with its multiple applications in marketing, law enforcement and surveillance, e-medicine and e-health- to name just some, there exist currently many avenues along which profiling might progress, but unless the consumers and citizens of today and tomorrow have mor