The active living gender's gap challenge: 2013-2017 Eurobarometers physical inactivity data show constant higher prevalence in women with no progress towards global reduction goals

BACKGROUND: The World Health Organization (WHO) considers physical inactivity (PIA) as a critical noncommunicable factor for disease and mortality, affecting more women than men. In 2013, the WHO set a 10% reduction of the PIA prevalence, with the goal to be reached by 2025. Changes in the 2013-2017 period of physical inactivity prevalence in the 28 European Union (EU) countries were evaluated to track the progress in achieving WHO 2025 target. METHODS: In 2013 and 2017 EU Special Eurobarometers, the physical activity levels reported by the International Physical Activity Questionnaire of 53,607 adults were analyzed. Data were considered as a whole sample and country-by-country. A χ2 test was used to analyze the physical inactivity prevalence (%) between countries, analyzing women and men together and separately. Additionally, PIA prevalence was analyzed between years (2013-2017) for the overall EU sample and within-country using a Z-Score for two population proportions. RESULTS: The PIA prevalence increased between 2013 and 2017 for the overall EU sample (p <  0.001), and for women (p = 0.04) and men (p < 0.001) separately. Data showed a higher PIA prevalence in women versus men during both years (p <  0.001). When separately considering changes in PIA by gender, only Belgium's women and Luxembourg's men showed a reduction in PIA prevalence. Increases in PIA prevalence over time were observed in women from Austria, Croatia, Germany, Lithuania, Malta, Portugal, Romania, and Slovakia and in men from Bulgaria, Croatia, Czechia, Germany, Italy, Lithuania, Portugal, Romania, Slovakia, and Spain. CONCLUSIONS: PIA prevalence showed an overall increase across the EU and for both women and men between 2013 and 2017, with higher rates of PIA reported for women versus men during both years. PIA prevalence was reduced in only Belgium's women and Luxembourg's men. Our data indicate a limited gender-sensible approach while tacking PIA prevalence with no progress reaching global voluntary reductions of PIA for 2025

The RFID PIA – developed by industry, agreed by regulators

This chapter discusses the privacy impact assessment (PIA) framework endorsed by the European Commission on February 11th, 2011. This PIA, the first to receive the Commission's endorsement, was developed to deal with privacy challenges associated with the deployment of radio frequency identification (RFID) technology, a key building block of the Internet of Things. The goal of this chapter is to present the methodology and key constructs of the RFID PIA Framework in more detail than was possible in the official text. RFID operators can use this article as a support document when they conduct PIAs and need to interpret the PIA Framework. The chapter begins with a history of why and how the PIA Framework for RFID came about. It then proceeds with a description of the endorsed PIA process for RFID applications and explains in detail how this process is supposed to function. It provides examples discussed during the development of the PIA Framework. These examples reflect the rationale behind and evolution of the text's methods and definitions. The chapter also provides insight into the stakeholder debates and compromises that have important implications for PIAs in general.Series: Working Papers on Information Systems, Information Business and Operation

Phosphorescent perylene imides.

Asymmetrically substituted perylene imide derivatives PIa and PIx display phosphorescence in glassy matrices at 77 K. The lifetime is 49.0 ms for PIa and 13.5 ms for PIx. The triplet energy is 1.79 eV for PIa and 1.68 eV for PIx as confirmed by sensitization experiments of the C60 triplet

PIA : more accurate taxonomic assignment of metagenomic data demonstrated on sedaDNA from the North sea

Assigning metagenomic reads to taxa presents significant challenges. Existing approaches address some issues, but are mostly limited to metabarcoding or optimized for microbial data. We present PIA (Phylogenetic Intersection Analysis): a taxonomic binner that works from standard BLAST output while mitigating key effects of incomplete databases. Benchmarking against MEGAN using sedaDNA suggests that, while PIA is less sensitive, it can be more accurate. We use known sequences to estimate the accuracy of PIA at up to 96% when the real organism is not represented in the database. For ancient DNA, where taxa of interest are frequently over-represented domesticates or absent, poorly-known organisms, more accurate assignment is critical, even at the expense of sensitivity. PIA offers an approach to objectively filter out false positive hits without the need to manually remove taxa and so make presuppositions about past environments and their palaeoecologies

Amorphization induced by pressure: results for zeolites and general implications

We report an {\sl ab initio} study of pressure-induced amorphization (PIA) in zeolites, which are model systems for this phenomenon. We confirm the occurrence of low-density amorphous phases like the one reported by Greaves {\sl et al.} [Science {\bf 308}, 1299 (2005)], which preserves the crystalline topology and might constitute a new type of glass. The role of the zeolite composition regarding PIA is explained. Our results support the correctness of existing models for the basic PIA mechanim, but suggest that energetic, rather than kinetic, factors determine the irreversibility of the transition.Comment: 4 pages with 3 figures embedded. More information at http://www.icmab.es/dmmis/leem/jorg

Testing for Yield Persistency: Is It Skill or is It Luck?

This study uses corn yield data from McLean County, Illinois to test whether farmer skill influences yields. This analysis is conducted by performing persistency tests on unadjusted, soil productivity adjusted (PA), and productivity and input intensity adjusted (PIA) yields. Correlation analysis and winner/loser tables indicate that unadjusted, PA, and PIA yields exhibit persistency across time. PIA yields exhibiting persistency is consistent with farmer skill influencing yield. Hence, our results support the hypothesis that farmer skill influences yields.Crop Production/Industries,