Expert perspectives on the future of the organic food market: results of a Pan-European Delphi study

A Delphi Inquiry was carried out to assess the prospect and conditions affecting the overall growth in the European Market for organic products in the coming decade, and to provide support for research. Countries were classified as established, growing and emerging, according to the state of development of their organic market. The survey confirmed the importance of factors influencing the development of the organic food market: the supply base, the role of supermarkets as sales channels and of government support. Organic Producer Initiatives were seen as important in securing a fair deal for organic producers but managerial capacity and professionalism are key challenges for such organizations

Sequential Complexity as a Descriptor for Musical Similarity

We propose string compressibility as a descriptor of temporal structure in audio, for the purpose of determining musical similarity. Our descriptors are based on computing track-wise compression rates of quantised audio features, using multiple temporal resolutions and quantisation granularities. To verify that our descriptors capture musically relevant information, we incorporate our descriptors into similarity rating prediction and song year prediction tasks. We base our evaluation on a dataset of 15500 track excerpts of Western popular music, for which we obtain 7800 web-sourced pairwise similarity ratings. To assess the agreement among similarity ratings, we perform an evaluation under controlled conditions, obtaining a rank correlation of 0.33 between intersected sets of ratings. Combined with bag-of-features descriptors, we obtain performance gains of 31.1% and 10.9% for similarity rating prediction and song year prediction. For both tasks, analysis of selected descriptors reveals that representing features at multiple time scales benefits prediction accuracy.Comment: 13 pages, 9 figures, 8 tables. Accepted versio

Identifying Cover Songs Using Information-Theoretic Measures of Similarity

This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/This paper investigates methods for quantifying similarity between audio signals, specifically for the task of cover song detection. We consider an information-theoretic approach, where we compute pairwise measures of predictability between time series. We compare discrete-valued approaches operating on quantized audio features, to continuous-valued approaches. In the discrete case, we propose a method for computing the normalized compression distance, where we account for correlation between time series. In the continuous case, we propose to compute information-based measures of similarity as statistics of the prediction error between time series. We evaluate our methods on two cover song identification tasks using a data set comprised of 300 Jazz standards and using the Million Song Dataset. For both datasets, we observe that continuous-valued approaches outperform discrete-valued approaches. We consider approaches to estimating the normalized compression distance (NCD) based on string compression and prediction, where we observe that our proposed normalized compression distance with alignment (NCDA) improves average performance over NCD, for sequential compression algorithms. Finally, we demonstrate that continuous-valued distances may be combined to improve performance with respect to baseline approaches. Using a large-scale filter-and-refine approach, we demonstrate state-of-the-art performance for cover song identification using the Million Song Dataset.The work of P. Foster was supported by an Engineering and Physical Sciences Research Council Doctoral Training Account studentship

IDENTIFICATION OF COVER SONGS USING INFORMATION THEORETIC MEASURES OF SIMILARITY

13 pages, 5 figures, 4 tables. v3: Accepted version13 pages, 5 figures, 4 tables. v3: Accepted version13 pages, 5 figures, 4 tables. v3: Accepted versio

Single polymer gating of channels under a solvent gradient

We study the effect of a gradient of solvent quality on the coil-globule transition for a polymer in a narrow pore. A simple self-attracting self-avoiding walk model of a polymer in solution shows that the variation in the strength of interaction across the pore leads the system to go from one regime (good solvent) to the other (poor solvent) across the channel. This may be thought analogous to thermophoresis, where the polymer goes from the hot region to the cold region under the temperature gradient. The behavior of short chains is studied using exact enumeration whilst the behavior of long chains is studied using transfer matrix techniques. The distribution of the monomer density across the layer suggests that a gate-like effect can be created, with potential applications as a sensor.Comment: 5 Pages, 7 Figures, Accepted in Phys. Rev. E (2013

The Policy and Regulatory Environment for Organic Farming in Europe

Organic Farming is one of the key issues in reshaping European agricultural policy. This book clarifies the policy and regulatory environment within which organic farming currently operates in all EU-15 member states and in three non-EU countries (Norway, Switzerland and the Czech Republic). European and national regulations and their implementation are reviewed. Focus is led on agri-environmental and mainstream agricultural support measures, marketing and regional development programmes, certification systems and organic farming support in the form of advice, training and research. The book aims at policy makers, the private sector, researchers and students in the field of economics and politics of organic farming

Universality of collapsing two-dimensional self-avoiding trails

Results of a numerically exact transfer matrix calculation for the model of Interacting Self-Avoiding Trails are presented. The results lead to the conclusion that, at the collapse transition, Self-Avoiding Trails are in the same universality class as the O(n=0) model of Blote and Nienhuis (or vertex-interacting self-avoiding walk), which has thermal exponent $\nu=12/23$, contrary to previous conjectures.Comment: Final version, accepted for publication in Journal of Physics A; 9 pages; 3 figure

A back to back multilevel converter for driving low inductance brushless AC machines

Traditionally, multilevel converters are utilised in medium voltage applications, allowing the DC-link voltage to exceed the switch maximum blocking voltage. Here, their application to control high- efficiency brushless permanent magnet synchronous machines exhibiting low phase inductance is explored, the relative advantages being shown to include reduced current ripple and improved harmonic spectrum. A cost benefit analysis is included along with experimental results from a prototype 5-level back-to-back converter

SCREENING FOR HEPATITIS C Response from Hepatitis C Trust, BASL, BIA, BVHG, BSG, and BHIVA to article asking whether widespread screening for hepatitis C is justified

This is the peer reviewed published version of the following article: Response from Hepatitis C Trust, BASL, BIA, BVHG, BSG, and BHIVA to article asking whether widespread screening for hepatitis C is justified, which has been published in final form at 10.1136/bmj.h998. This article may be used for non-commercial purposes in accordance with BMJ's Terms and Conditions for Self-Archiving.This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/ by/4.0

Corner transfer matrix renormalization group method for two-dimensional self-avoiding walks and other O(n) models

We present an extension of the corner transfer matrix renormalisation group (CTMRG) method to O(n) invariant models, with particular interest in the self-avoiding walk class of models (O(n=0)). The method is illustrated using an interacting self-avoiding walk model. Based on the efficiency and versatility when compared to other available numerical methods, we present CTMRG as the method of choice for two-dimensional self-avoiding walk problems.Comment: 4 pages 7 figures Substantial rewrite of previous version to include calculations of critical points and exponents. Final version accepted for publication in PRE (Rapid Communications