Representation through deliberation-The European case

This article shows that the main pattern of European democratization has unfolded along the lines of an EU organized as a multilevel system of representative parliamentary government and not as a system of deliberative governance as the transnationalists propound. But the multilevel EU has developed a structure of representation that is theoretically challenging. In order to come to grips with this we present an institutional variant of deliberative theory, which understands democracy as the combination of a principle of justification and an organizational form. It comes with the following explanatory mechanisms: claimsmaking, justification and learning which in the EU also program institutional copying and emulation mechanisms. We show that the EU has established an incomplete system of representative democracy steeped in a distinct representation-deliberation interface, which has emerged through a particular and distinct configuration of democratization mechanisms

"Europe in Transformation: How to Reconstitute Democracy?"

Europeanization and globalization are frequently held to undermine national democracy; hence raising the democracy in the multi-level constellation that makes up the European Union? We present three models for how democracy can be reconstituted: (a) it can be reconstituted at the national level, as delegated democracy with a concomitant reframing of the EU as a functional regulatory regime; (b) through establishing the EU as a multi-national state based on a common identity(ies) and solidaristic allegiance strong enough to undertake collective action; or (c) through the development of a post-national Union with an explicit cosmopolitan imprint. These are the only viable models of European democracy, as they are the only ones that can ensure equal membership in a self-governing polity. They differ however with regard to both applicability and robustness

Walkabout Activities

Postcard from Samantha O\u27Connor, during the Linfield College Semester Abroad Program at James Cook University in Cairns, Australi

Method of treating endothelial dysfunction comprising administration of a thrombin peptide derivative

Endothelial dysfunction (ED) is associated with a number of diseases and disorders. Agonists of the non-proteolytically activated thrombin receptor can be used in methods to treat ED or ED-related diseases and disorders.Board of Regents, University of Texas Syste

Pytracks: A Tool for Visualizing Fish Movement Tracks on Different Scales

A fundamental problem in conservation biology and fisheries management is the ability to make educated decisions based on the data collected. Fish populations and their spatial distributions need to be represented accurately for conversation efforts and management decisions. Methods such as modeling, surveying, and tracking can all be used to collect data on a particular fishery. To include the movement patterns in conservation and management, one needs to work with and process fish tracking data or data exported from fish movement simulation models. This data can often be difficult to process. This topic is becoming increasingly popular as technology to accurately track and log fish did not exist in the past. With all of this data being generated, real or simulated, tools need to be developed to efficiently process it all, as many do not exist. Pytracks attempts to fill a currently existing gap and help programmers who work with simulated and observed simulation data by allowing them to visualize and analyze their data more efficiently. Pytracks, as presented in this thesis, is a tool written in Python which wraps raw data files from field observations or simulation models with an easy to use API. This allows programmers to spend less time on trivial raw file processing and more time on data visualization and computation. The code to visualize sample data can also be much shorter and easier to interpret. In this thesis, pytracks was used to help solve a problem related to interpreting different movement algorithms. This work has a focus on fish movement models, but can also be relevant for any other type of animal if the data is compatible. Many examples have been included in this thesis to justify the effectiveness of pytracks. Additional online documentation has been written as well to show how to further utilize pytracks

Efficient Fuel Consumption Minimization for Green Vehicle Routing Problems using a Hybrid Neural Network-Optimization Algorithm

Efficient routing optimization yields benefits that extend beyond mere financial gains. In this thesis, we present a methodology that utilizes a graph convolutional neural network to facilitate the development of energy-efficient waste collection routes. Our approach focuses on a Waste company in Tromsø, Remiks, and uses real-life datasets, ensuring practicability and ease of implementation. In particular, we extend the dpdp algorithm introduced by Kool et al. (2021) [1] to minimize fuel consumption and devise routes that account for the impact of elevation and real road distance traveled. Our findings shed light on the potential advantages and enhancements these optimized routes can offer Remiks, including improved effectiveness and cost savings. Additionally, we identify key areas for future research and development