FENDL: A library for fusion research and applications

The Fusion Evaluated Nuclear Data Library (FENDL) is a comprehensive and validated collection of nuclear cross section data coordinated by the International Atomic Energy Agency (IAEA) Nuclear Data Section (NDS). FENDL assembles the best nuclear data for fusion applications selected from available nuclear data libraries and has been under development for decades. FENDL contains sub-libraries for incident neutron, proton, and deuteron cross sections including general purpose and activation files used for particle transport and nuclide inventory calculations. We describe the history, selection of evaluations for the various sub-libraries (neutron, proton, deuteron) with the focus on transport and reactor dosimetry applications, the processing of the nuclear data for application codes, and the development of the TENDL-2017 library which is the currently recommended activation library for FENDL. We briefly describe the IAEA IRDFF library as the recommended library for dosimetry fusion applications. We also present work on validation of the neutron sub-library using a variety of fusion relevant computational and experimental benchmarks. A variety of cross section libraries are used for the validation work including FENDL-2.1, FENDL-3.1d, FENDL-3.2, ENDF/B-VIII.0, and JEFF-3.2 with the emphasis on the FENDL libraries. The results of the experimental validation showed that the performance of FENDL-3.2b is at least as good and in most cases better than FENDL-2.1. Future work will consider improved evaluations developed by the International Nuclear Data Evaluation Network (INDEN). Additional work will be needed to investigate differences in gas production in structural materials. Covariance matrices need to be updated to support the development of fusion technology. Additional validation work for high-energy neutrons, protons and deuterons, and the activation library will be needed.Comment: 81 pages, 114 figure

The use of sensor technology and genomics to breed for laying hens that show less damaging behaviour

The European COST Action GroupHouseNet aims to provide synergy for preventing damaging behaviour in group-housed pigs and laying hens. One area of focus of this network is how genetic and genomic tools can be used to breed animals that are less likely to develop damaging behaviour to their pen-mates. When focussing on laying hens, one of the main problems is that feather pecking (FP) occurs in large groups, making it difficult to identify birds performing damaging behaviour. We propose a combination of sensor technology and genomic methods to solve this issue. Research on genetic lines selected divergently on high and low FP as well as on a F2 cross established from these lines has pointed to mechanisms that may underlie this behaviour, revealing relationships between FP, fearfulness and activity levels and locating genomic markers related with FP. Birds selected for high FP were found to be less fearful and highly active in a range of tests and home pen situations. This knowledge may be used to automatically detect high feather-pecking individuals in a group setting. Research on using novel methods such as ultra-wideband tracking to detect phenotypic differences between individuals in a group is ongoing. First results confirm previously found line differences in fearfulness and activity. Future work will focus on exploring potential of other sensor-based methods to accurately measure individual phenotypes, and linking this information to genomic markers. This should lead to the development of novel breeding methods to select against damaging behaviour in laying hens

The use of sensor technology and genomics to breed for laying hens that show less damaging behaviour

The European COST Action GroupHouseNet aims to provide synergy for preventing damaging behaviour in group-housed pigs and laying hens. One area of focus of this network is how genetic and genomic tools can be used to breed animals that are less likely to develop damaging behaviour to their pen-mates. When focussing on laying hens, one of the main problems is that feather pecking (FP) occurs in large groups, making it difficult to identify birds performing damaging behaviour. We propose a combination of sensor technology and genomic methods to solve this issue. Research on genetic lines selected divergently on high and low FP as well as on a F2 cross established from these lines has pointed to mechanisms that may underlie this behaviour, revealing relationships between FP, fearfulness and activity levels and locating genomic markers related with FP. Birds selected for high FP were found to be less fearful and highly active in a range of tests and home pen situations. This knowledge may be used to automatically detect high feather-pecking individuals in a group setting. Research on using novel methods such as ultra-wideband tracking to detect phenotypic differences between individuals in a group is ongoing. First results confirm previously found line differences in fearfulness and activity. Future work will focus on exploring potential of other sensor-based methods to accurately measure individual phenotypes, and linking this information to genomic markers. This should lead to the development of novel breeding methods to select against damaging behaviour in laying hens.</p

Developing sensor technologies to inform breeding approaches to reduce damaging behaviour in laying hens and pigs: The GroupHouseNet approach

The European COST Action GroupHouseNet aims to provide synergy for preventing damaging behaviour in group-housed pigs and laying hens. One area of focus of this network is how genetic and genomic tools can be used to breed animals that are less likely to develop damaging behaviour directed at their pen-mates. Reducing damaging behaviour in large groups is a challenge, because it is difficult to identify and monitor individual animals. With the current developments in sensor technologies and animal breeding, there is the possibility to identify individual animals, monitor individual behaviour, and link this information to the genotype. Using a combination of sensor technologies and genomics enables us to select against damaging behaviour in pigs and laying hens.</p

Developing sensor technologies to inform breeding approaches to reduce damaging behaviour in laying hens and pigs: The GroupHouseNet approach

The European COST Action GroupHouseNet aims to provide synergy for preventing damaging behaviour in group-housed pigs and laying hens. One area of focus of this network is how genetic and genomic tools can be used to breed animals that are less likely to develop damaging behaviour directed at their pen-mates. Reducing damaging behaviour in large groups is a challenge, because it is difficult to identify and monitor individual animals. With the current developments in sensor technologies and animal breeding, there is the possibility to identify individual animals, monitor individual behaviour, and link this information to the genotype. Using a combination of sensor technologies and genomics enables us to select against damaging behaviour in pigs and laying hens.</p

A global look at time: a 24-country study of the equivalence of the Zimbardo time perspective inventory

In this article, we assess the structural equivalence of the Zimbardo Time Perspective Inventory (ZTPI) across 26 samples from 24 countries (N = 12,200). The ZTPI is proven to be a valid and reliable index of individual differences in time perspective across five temporal categories: Past Negative, Past Positive, Present Fatalistic, Present Hedonistic, and Future. We obtained evidence for invariance of 36 items (out of 56) and also the five-factor structure of ZTPI across 23 countries. The short ZTPI scales are reliable for country-level analysis, whereas we recommend the use of the full scales for individual-level analysis. The short version of ZTPI will further promote integration of research in the time perspective domain in relation to many different psycho-social processes