The Blue Bond Proposal

Soaring debt levels and the crisis in Greece has sharpened the focus on fiscal sustainability among eurozone members. The European Union has to tackle high debt levels in vulnerable states which are compounded by a hike in risk premiums on government bonds leading to a debt trap, while designing ways to efficiently finance debt. Furthermore, European solidarity with weaker states should not undermine incentives for individual members to pursue fiscally sustainable policies. This Policy Brief proposes a Blue Bond to resolve these challenges. The authors, Bruegel Non-resident Fellow Jakob von Weizsäcker and Jacques Delpla from Conseil d'Analyse �conomique, Paris, explain the economics behind their proposal, its institutional underpinnings and the implication of it on various participating countries.

Vulnerability as potential: the search for agency in Deborah Levy’s _Hot Milk_ (2016)

Departing from Agamben’s idea of potentiality, I propose to explore this notion in connection to the critical term of vulnerability, to show that they are not that different as one could think at first. In order to do so, I will analyse the portrayal of vulnerability and potential in the contemporary novel _Hot Milk_ written by the Britisth author Deborah Levy and published in 2016.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Unsupervised Action Proposal Ranking through Proposal Recombination

Recently, action proposal methods have played an important role in action recognition tasks, as they reduce the search space dramatically. Most unsupervised action proposal methods tend to generate hundreds of action proposals which include many noisy, inconsistent, and unranked action proposals, while supervised action proposal methods take advantage of predefined object detectors (e.g., human detector) to refine and score the action proposals, but they require thousands of manual annotations to train. Given the action proposals in a video, the goal of the proposed work is to generate a few better action proposals that are ranked properly. In our approach, we first divide action proposal into sub-proposal and then use Dynamic Programming based graph optimization scheme to select the optimal combinations of sub-proposals from different proposals and assign each new proposal a score. We propose a new unsupervised image-based actioness detector that leverages web images and employs it as one of the node scores in our graph formulation. Moreover, we capture motion information by estimating the number of motion contours within each action proposal patch. The proposed method is an unsupervised method that neither needs bounding box annotations nor video level labels, which is desirable with the current explosion of large-scale action datasets. Our approach is generic and does not depend on a specific action proposal method. We evaluate our approach on several publicly available trimmed and un-trimmed datasets and obtain better performance compared to several proposal ranking methods. In addition, we demonstrate that properly ranked proposals produce significantly better action detection as compared to state-of-the-art proposal based methods

Proposal Flow

Finding image correspondences remains a challenging problem in the presence of intra-class variations and large changes in scene layout.~Semantic flow methods are designed to handle images depicting different instances of the same object or scene category. We introduce a novel approach to semantic flow, dubbed proposal flow, that establishes reliable correspondences using object proposals. Unlike prevailing semantic flow approaches that operate on pixels or regularly sampled local regions, proposal flow benefits from the characteristics of modern object proposals, that exhibit high repeatability at multiple scales, and can take advantage of both local and geometric consistency constraints among proposals. We also show that proposal flow can effectively be transformed into a conventional dense flow field. We introduce a new dataset that can be used to evaluate both general semantic flow techniques and region-based approaches such as proposal flow. We use this benchmark to compare different matching algorithms, object proposals, and region features within proposal flow, to the state of the art in semantic flow. This comparison, along with experiments on standard datasets, demonstrates that proposal flow significantly outperforms existing semantic flow methods in various settings

A Proposal for Semantic Map Representation and Evaluation

Semantic mapping is the incremental process of “mapping” relevant information of the world (i.e., spatial information, temporal events, agents and actions) to a formal description supported by a reasoning engine. Current research focuses on learning the semantic of environments based on their spatial location, geometry and appearance. Many methods to tackle this problem have been proposed, but the lack of a uniform representation, as well as standard benchmarking suites, prevents their direct comparison. In this paper, we propose a standardization in the representation of semantic maps, by defining an easily extensible formalism to be used on top of metric maps of the environments. Based on this, we describe the procedure to build a dataset (based on real sensor data) for benchmarking semantic mapping techniques, also hypothesizing some possible evaluation metrics. Nevertheless, by providing a tool for the construction of a semantic map ground truth, we aim at the contribution of the scientific community in acquiring data for populating the dataset

MEG Upgrade Proposal

We propose the continuation of the MEG experiment to search for the charged lepton flavour violating decay (cLFV) \mu \to e \gamma, based on an upgrade of the experiment, which aims for a sensitivity enhancement of one order of magnitude compared to the final MEG result, down to the $6 \times 10^{-14}$ level. The key features of this new MEG upgrade are an increased rate capability of all detectors to enable running at the intensity frontier and improved energy, angular and timing resolutions, for both the positron and photon arms of the detector. On the positron-side a new low-mass, single volume, high granularity tracker is envisaged, in combination with a new highly segmented, fast timing counter array, to track positron from a thinner stopping target. The photon-arm, with the largest liquid xenon (LXe) detector in the world, totalling 900 l, will also be improved by increasing the granularity at the incident face, by replacing the current photomultiplier tubes (PMTs) with a larger number of smaller photosensors and optimizing the photosensor layout also on the lateral faces. A new DAQ scheme involving the implementation of a new combined readout board capable of integrating the diverse functions of digitization, trigger capability and splitter functionality into one condensed unit, is also under development. We describe here the status of the MEG experiment, the scientific merits of the upgrade and the experimental methods we plan to use.Comment: A. M. Baldini and T. Mori Spokespersons. Research proposal submitted to the Paul Scherrer Institute Research Committee for Particle Physics at the Ring Cyclotron. 131 Page