Synthesis and final recommendations on the development of a European Information System for Organic Markets. = Deliverable D6 of the European Project EISfOM QLK5-2002-02400

Executive summary European markets for organic products are growing rapidly, but the market information available in most European countries is woefully inadequate. Often only very basic data such as certified organic holdings and land area are reported, and sometimes not even individual crop areas or livestock numbers. Important market data, such as the amount of production, consumption, international trade or producer and consumer prices, do not exist in most European countries. In some European countries there are only rough estimates of the levels of production and consumption. There is no standardisation and data are seldom comparable. Furthermore, detailed information on specific commodities is missing. Hence, investment decisions are taken under conditions of great uncertainty. Policy evaluation, including periodic monitoring of the European Action Plan for Organic Food and Farming and RDP 2007-2013, will require many other data in addition to those regarding production structures and financial data that are already available, but obtaining this information would require a new EU-wide data collection and processing system (DCPS) to be put in place. The European Information System for Organic Markets (EISfOM) project is an EUfunded Concerted Action which has analysed and documented the current situation and proposed ways in which organic data collection and processing systems (DCPS) can be improved by means of: • improvement in the current situation of data collecting and processing systems for the organic sector • innovation in data collection and processing systems for the organic sector • integration of conventional and organic data collection and processing systems This report summarises the most relevant findings of the EISfOM project, which are analysed in the main project reports: Wolfert, S., Kramer, K. J., Richter, T., Hempfling, G., Lux. S. and Recke, G. (eds.) (2004). Review of data collection and processing systems for organic and conventional markets. EISfOM (QLK5-2002-02400) project deliverable submitted to European Commission. www.eisfom.org/publications. Recke, G., Hamm, U., Lampkin, N., Zanoli, R., Vitulano, S. and Olmos, S. (eds.) (2004a) Report on proposals for the development, harmonisation and quality assurance of organic data collection and processing systems (DCPS). EISfOM (QLK5-2002-02400) project deliverable submitted to European Commission. www.eisfom.org/publications. Recke, G., Willer, H., Lampkin, N. and Vaughan, A. (eds.) (2004b). Development of a European Information System for Organic Markets – Improving the Scope and Quality of Statistical Data. Proceedings of the 1st EISfOM European Seminar, Berlin, Germany, 26-27 April, 2004. Research Institute of Organic Agriculture (FiBL), Frick, Switzerland. www.eisfom.org/publications. Gleirscher, N., Schermer, M., Wroblewska, M. and Zakowska-Biemans, S. (2005) Report on the evaluation of the pilot case studies. EISfOM (QLK5-2002-02400) project deliverable submitted to European Commission. www.eisfom.org/publications. QLK5-2002-02400 European Information System for Organic Markets (EISfOM) D6 final report Rippin, M. and Lampkin, N. (eds.) (2005) Framework for a European Information System for Organic Markets. Unpublished report of the project European Information System for Organic Markets (EISfOM) (QLK5-2002-02400). Rippin, M., Willer, H., Lampkin, N., and Vaughan A. (2006). Towards a European Framework for Organic Market information, Proceedings of the 2nd EISfOM European Seminar, Brussels, November 10 and 11, 2005. Research Institute of Organic Agriculture (FiBL), Frick, Switzerland. www.eisfom.org/publications

An adaptive perception-based image preprocessing method

The aim of this paper is to introduce an adaptive preprocessing procedure based on human perception in order to increase the performance of some standard image processing techniques. Specifically, image frequency content has been weighted by the corresponding value of the contrast sensitivity function, in agreement with the sensitiveness of human eye to the different image frequencies and contrasts. The 2D Rational dilation wavelet transform has been employed for representing image frequencies. In fact, it provides an adaptive and flexible multiresolution framework, enabling an easy and straightforward adaptation to the image frequency content. Preliminary experimental results show that the proposed preprocessing allows us to increase the performance of some standard image enhancement algorithms in terms of visual quality and often also in terms of PSNR

Developmental Trajectories of ADHD Symptoms to Adolescent Substance Use: What Influence Do Peer, Family and Neighborhood Factors Have?

Attention-Deficit/Hyperactivity Disorder (ADHD) has been consistently linked to risk for early substance use. However, the potential mediating mechanisms and moderators of this association remain unclear. The current study examined peer rejection, school bonding and internalizing problems as potential mediators of the association between childhood ADHD symptoms and adolescent substance use in a longitudinal study following children from fourth to ninth grade. Results suggest that ADHD symptoms follow a path to early initiation of tobacco use through the combined effects of peer rejection and internalizing problems as well as through internalizing problems alone. ADHD symptoms did not follow developmental pathways to overall frequency of substance use or initiation of alcohol or marijuana use. Neighborhood problems, family activities and parenting styles did not moderate the developmental pathways from ADHD symptoms to substance use frequency. Results identify important development factors in children with ADHD symptoms that highlight the need for primary prevention and psychological interventions that target these factors and thus minimize substance use during adolescence

Contextual Influences on Associations between Impulsivity and Risk-Taking and Child Delinquency

Previous literature has shown that risk factors for delinquency include individual characteristics of impulsivity and risk-taking as well as contextual influences such as neighborhoods, parenting and engagement in physical activity (e.g., exercise, sports). Theory suggests that individual characteristics interact with contextual factors to influence child development, however evidence is limited. The current study examined the interaction between these individual and contextual risks to influence childhood delinquency in a community sample of 89 children ranging from 9 to 12 years of age (M = 10.4, SD = 1.1). Questionnaire measures showed that both caregiver report of impulsivity and self-reported risk-taking were positively associated with self-reported delinquency, yet no interactions with contextual factors were found. When using computer tasks, neither impulsivity nor risk-taking were significantly associated with delinquency. However, a risk-taking by physical activity interaction was found, such that at low levels of physical activity risk-taking was positively related to delinquency, yet at high levels of physical activity, risk-taking and delinquency were unrelated. Thus, programs that involve physical activity may be useful prevention and intervention strategies for risk-taking children

Report on proposals for the development, harmonisation and quality assurance of organic data collection and processing systems (DCPS)

This report represents the conclusion of the European seminar on development, harmonisation and quality assurance of organic data collection and processing systems (Berlin, April 2004) as well as of the first phase of the EISFOM-project. - In the first chapter the objectives and general approach of this workpackage are described. - Chapter 2 focuses on quality assurance, the main results of WP2 and WP3 and the European Seminar in Berlin (see Recke et al. 2004; https://orgprints.org/2935/. Furthermore, the strengths and weaknesses of organic DCPS (data collection and processing systems) are analysed and the chapter closes with proposals for the development of organic DCPSs. - Chapter 3 focuses on results of expert interviews on the main barriers for the implementation of improved organic statistical data collection and processing systems. - Chapter 4 gives a summary and some general conclusions are drawn. This report provides perspectives on how the above mentioned issues of the European Action Plan might be implemented

Wavelets and partial differential equations for image denoising

In this paper a wavelet based model for image de-noising is presented. Wavelet coefficients are modelled as waves that grow while dilating along scales. The model establishes a precise link between corresponding modulus maxima in the wavelet domain and then allows to predict wavelet coefficients at each scale from the first one. This property combined with the theoretical results about the characterization of singularities in the wavelet domain enables to discard noise. Significant structures of the image are well recovered while some annoying artifacts along image edges are reduced. Some experimental results show that the proposed approach outperforms the most recent and effective wavelet based denoising schemes

Coherence of PRNU weighted estimations for improved source camera identification

This paper presents a method for Photo Response Non Uniformity (PRNU) pattern noise based camera identification. It takes advantage of the coherence between different PRNU estimations restricted to specific image regions. The main idea is based on the following observations: different methods can be used for estimating PRNU contribution in a given image; the estimation has not the same accuracy in the whole image as a more faithful estimation is expected from flat regions. Hence, two different estimations of the reference PRNU have been considered in the classification procedure, and the coherence of the similarity metric between them, when evaluated in three different image regions, is used as classification feature. More coherence is expected in case of matching, i.e. the image has been acquired by the analysed device, than in the opposite case, where similarity metric is almost noisy and then unpredictable. Presented results show that the proposed approach provides comparable and often better classification results of some state of the art methods, showing to be robust to lack of flat field (FF) images availability, devices of the same brand or model, uploading/downloading from social networks

An allelic variant in the intergenic region between ERAP1 and ERAP2 correlates with an inverse expression of the two genes

The Endoplasmatic Reticulum Aminopeptidases ERAP1 and ERAP2 are implicated in a variety of immune and non-immune functions. Most studies however have focused on their role in shaping the HLA class I peptidome by trimming peptides to the optimal size. Genome Wide Association Studies highlighted non-synonymous polymorphisms in their coding regions as associated with several immune mediated diseases. The two genes lie contiguous and oppositely oriented on the 5q15 chromosomal region. Very little is known about the transcriptional regulation and the quantitative variations of these enzymes. Here, we correlated the level of transcripts and proteins of the two aminopeptidases in B-lymphoblastoid cell lines from 44 donors harbouring allelic variants in the intergenic region between ERAP1 and ERAP2. We found that the presence of a G instead of an A at SNP rs75862629 in the ERAP2 gene promoter strongly influences the expression of the two ERAPs with a down-modulation of ERAP2 coupled with a significant higher expression of ERAP1. We therefore show here for the first time a coordinated quantitative regulation of the two ERAP genes, which can be relevant for the setting of specific therapeutic approaches

An MDL-based wavelet scattering features selection for signal classification

Wavelet scattering is a redundant time-frequency transform that was shown to be a powerful tool in signal classification. It shares the convolutional architecture with convolutional neural networks, but it offers some advantages, including faster training and small training sets. However, it introduces some redundancy along the frequency axis, especially for filters that have a high degree of overlap. This naturally leads to a need for dimensionality reduction to further increase its efficiency as a machine learning tool. In this paper, the Minimum Description Length is used to define an automatic procedure for optimizing the selection of the scattering features, even in the frequency domain. The proposed study is limited to the class of uniform sampling models. Experimental results show that the proposed method is able to automatically select the optimal sampling step that guarantees the highest classification accuracy for fixed transform parameters, when applied to audio/sound signals