Safety of chia seeds (Salvia hispanica L.) powders, as novel foods, pursuant to Regulation (EU) 2015/2283

Following a request from the European Commission, the EFSA Panel on Nutrition, Novel foods and Food Allergens (NDA) was asked to deliver an opinion on chia seeds (Salvia hispanica L.) powders as novel foods (NFs) pursuant to Regulation (EU) 2015/2283. The NFs are partially defatted chia seed powders, obtained by extrusion of whole seeds of S. hispanica L. with the main differences between two powders in particle sizes and the content of some macronutrients. The information provided on the production processes, composition, batch-to-batch variability, stability and specifications of the NFs is sufficient and does not raise safety concerns. The applicant proposed to market the NFs as food supplements and as ingredients in a variety of foods. The target population for the NFs is the general population. Noting that no hazard raising safety concerns (except for allergenicity) could be identified from the information available on the source (i.e. chia seeds), the production processes, composition, specifications and proposed uses of the NFs, irrespectively of the maximum use levels at the proposed uses, the Panel considers that intake estimates and additional toxicological data for the NFs are not needed for this assessment. The Panel concludes that the NFs, partially defatted powders of whole chia seeds, are safe under the assessed conditions of use. (C) 2019 European Food Safety Authority. EFSA Journal published by John Wiley and Sons Ltd on behalf of European Food Safety Authority.Peer reviewe

Data-driven Soft Sensors in the Process Industry

In the last two decades Soft Sensors established themselves as a valuable alternative to the traditional means for the acquisition of critical process variables, process monitoring and other tasks which are related to process control. This paper discusses characteristics of the process industry data which are critical for the development of data-driven Soft Sensors. These characteristics are common to a large number of process industry fields, like the chemical industry, bioprocess industry, steel industry, etc. The focus of this work is put on the data-driven Soft Sensors because of their growing popularity, already demonstrated usefulness and huge, though yet not completely realised, potential. A comprehensive selection of case studies covering the three most important Soft Sensor application fields, a general introduction to the most popular Soft Sensor modelling techniques as well as a discussion of some open issues in the Soft Sensor development and maintenance and their possible solutions are the main contributions of this work

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This paper discusses the use of e-Science Grid in providing computational resources for modern international High Energy Physics (HEP) experiments. We investigate the suitability of the current generation of Grid software to provide the necessary resources to perform large-scale simulation of the experiment and analysis of data in the context of multinational collaboration