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Employment Factors Associated With Long Working Hours in France
Niedhammer Isabelle,Pineau Elodie,Bertrais Sandrine 한국산업안전보건공단 산업안전보건연구원 2023 Safety and health at work Vol.14 No.4
The objectives of the study were to explore the employment factors associated with long working hours, known as a risk factor for various health outcomes. The study relied on the national representative data of the 2013 French working conditions survey and a study sample of 23,378 full-time employees. Long working hours were defined by the threshold of 48 hours a week following the European Working Time Directive. The prevalence of long working hours was higher among men (13.5%) than among women (8.5%). Employees of the private sector, with permanent work contract, in small companies, and men in the services had a higher prevalence of exposure. This prevalence increased with educational and occupational levels. Our findings may help decision-makers to define preventive strategies. More research is needed to improve our knowledge of the employment factors associated with long working hours, as there may be strong differences between countries.
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Current situation and future prospects for beef production in Europe - A review
Hocquette, Jean-Francois,Ellies-Oury, Marie-Pierre,Lherm, Michel,Pineau, Christele,Deblitz, Claus,Farmer, Linda Asian Australasian Association of Animal Productio 2018 Animal Bioscience Vol.31 No.7
The European Union (EU) is the world's third largest producer of beef. This contributes to the economy, rural development, social life, culture and gastronomy of Europe. The diversity of breeds, animal types (cows, bulls, steers, heifers) and farming systems (intensive, extensive on permanent or temporary pastures, mixed, breeders, feeders, etc) is a strength, and a weakness as the industry is often fragmented and poorly connected. There are also societal concerns regarding animal welfare and environmental issues, despite some positive environmental impacts of farming systems. The EU is amongst the most efficient for beef production as demonstrated by a relative low production of greenhouse gases. Due to regional differences in terms of climate, pasture availability, livestock practices and farms characteristics, productivity and incomes of beef producers vary widely across regions, being among the lowest of the agricultural systems. The beef industry is facing unprecedented challenges related to animal welfare, environmental impact, origin, authenticity, nutritional benefits and eating quality of beef. These may affect the whole industry, especially its farmers. It is therefore essential to bring the beef industry together to spread best practice and better exploit research to maintain and develop an economically viable and sustainable beef industry. Meeting consumers' expectations may be achieved by a better prediction of beef palatability using a modelling approach, such as in Australia. There is a need for accurate information and dissemination on the benefits and issues of beef for human health and for environmental impact. A better objective description of goods and services derived from livestock farming is also required. Putting into practice "agroecology" and organic farming principles are other potential avenues for the future. Different future scenarios can be written depending on the major driving forces, notably meat consumption, climate change, environmental policies and future organization of the supply chain.
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Human Proteome Project Mass Spectrometry Data Interpretation Guidelines 3.0
Deutsch, Eric W.,Lane, Lydie,Overall, Christopher M.,Bandeira, Nuno,Baker, Mark S.,Pineau, Charles,Moritz, Robert L.,Corrales, Fernando,Orchard, Sandra,Van Eyk, Jennifer E.,Paik, Young-Ki,Weintraub, S American Chemical Society 2019 JOURNAL OF PROTEOME RESEARCH Vol.18 No.12
<P>The Human Proteome Organization’s (HUPO) Human Proteome Project (HPP) developed Mass Spectrometry (MS) Data Interpretation Guidelines that have been applied since 2016. These guidelines have helped ensure that the emerging draft of the complete human proteome is highly accurate and with low numbers of false-positive protein identifications. Here, we describe an update to these guidelines based on consensus-reaching discussions with the wider HPP community over the past year. The revised 3.0 guidelines address several major and minor identified gaps. We have added guidelines for emerging data independent acquisition (DIA) MS workflows and for use of the new Universal Spectrum Identifier (USI) system being developed by the HUPO Proteomics Standards Initiative (PSI). In addition, we discuss updates to the standard HPP pipeline for collecting MS evidence for all proteins in the HPP, including refinements to minimum evidence. We present a new plan for incorporating MassIVE-KB into the HPP pipeline for the next (HPP 2020) cycle in order to obtain more comprehensive coverage of public MS data sets. The main checklist has been reorganized under headings and subitems, and related guidelines have been grouped. In sum, Version 2.1 of the HPP MS Data Interpretation Guidelines has served well, and this timely update to version 3.0 will aid the HPP as it approaches its goal of collecting and curating MS evidence of translation and expression for all predicted ∼20 000 human proteins encoded by the human genome.</P> [FIG OMISSION]</BR>
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