Modelling of health monitoring signals and detection areas for aerospace structures

This paper is focused on Structural Health Monitoring (SHM) for aerospace use. It analyses the performance of commercially available finite element (FE) software packages for the simulation of propagation of ultrasonic guided waves (UGW) in typical aerospace structures. The purpose of the research is to support activities leading to the introduction of UGW based health monitoring on aerospace structures, as well as to support the design of future structures with integrated health monitoring. Activities are demonstrated on panels with growing complexity (adding different materials, sensors, damage types etc.). FE simulations are used to identify “detection areas” of UGW sensors. This output can be directly applied to the design of future aerospace structures with an integrated SHM system (to ensure the proper planning of the placement of UGW sensors)

GWAS in practical cattle breeding in Czech Republic, single step method, genetic progress

Development of genetic evaluation of animals is permanent process. It was going from estimated breeding value (EBV) calculated by CC-test, across a BLUP – animal model and RR-TDM, to the genomic enhanced breeding value (GEBV) using genetic markers. Methods of genetic evaluation become a part of marketing strategies of insemination companies. Therefore all countries and association of breeders seek to be compatible with others. Now we are in a period of massive global implementation of genomic evaluation, which combines traditional BLUP with huge quantity of genetic SNP markers. Multi-step procedures are now usual in practice, which work with deregressed proofs. Development of methods attained to the single-step procedure (ssGBLUP) which overcomes some difficulties of previous methods, improves reliabilities of evaluation and compares all animals, genotyped and ungenotyped, in entire nation-wide population. Genomic evaluation influence above all young genotyped animals. In Czech Republic single-step procedure is routinely used for national evaluation of milk, linear type traits, reproduction and longevity. GEBVs are accompanied by genomic reliabilities. Genetic trends over last 20 years are in some traits different for genomic evaluation compared to traditional BLUP evaluation, although input data and genetic parameters (heritability) are the same and genotyped animals were only small proportion from entire evaluated population. Differences in genetic trends increase mainly in new batches of animals. Reason of it could be in the changed variability of breeding values and “genomic correction” of relationship between animals, which is expanded from genotyped animals to others individuals in a population. Keywords: genomic breeding value, single-step, genomic relationship, genetic trend, SNP ReferencesBauer, J. et al. (2014) Approximation of the reliability of single-step genomic breeding values for dairy cattle in the Czech Republic. Anim. Sci. Papers and Reports, 32, pp. 301-306.Bauer, J., Přibyl, J. and Vostrý, L. (2015) Contribution of domestic production records and Interbull EBV on approximate reliabilities of single-step genomic breeding values in dairy cattle. Czech J. Anim. Sci., 60, 263-267.Candrák, J., Kadlečík O. and Schaeffer L.R. (1997) The use of test-day model for Slovak cattle populations. In: Proc. 48th Annual Meeting of the European Association for Animal Production, Vienna, Austria, August 25–28.Christensen,  O.F. and Lund, M.S. (2010) Genomic prediction when some animals are not genotyped. Genet.Sel.Evol. 42, pp. 2.Fisher, R.A. (1918) The correlation between relatives in the supposition of Mendelianinheritance. Trans. Roy. Soc. Edinb. 52, pp. 399-433.            Fragomeni, B.O. et al. (2015) Hot topic: Use of genomic recursions in single-step genomic best linear unbiased predictor (BLUP) with a large number of genotypes. J. Dairy Sci., 98, pp. 4090-4094.Gao, H. et al. (2012) Comparison on genomic predictions using three GBLUP methods and two single step blending methods in the Nordic Holstein population. Genet. Sel.Evol. 44, pp. 8.Legarra A., Aguilar I. and Misztal, I. (2009) A relationship matrix including full pedigree and genomic information. J. Dairy Sci., 92, pp. 4656-4663.Masuda, Y. et al. (2016) Implementation of genomic recursions in single-step genomic best linear unbiased predictor for US Holsteins with a large number of genotyped animals. J. Dairy Sci., 99, pp. 1968-1974.Mendel, G.J. (1866) Versuche über Pflanzen-Hybriden. Verh. Naturforsch. Ver. Brünn 4, pp. 3–47 (1901, J. R. Hortic. Soc. 26, pp. 1–32).Meuwissen, T.H.E., Hayes, B.J. and Goddard, M.E. (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics, 157, pp. 1819–1829.Misztal, I., Legarra A. and Aguilar, I. (2009) Computing procedures for genetic evaluation including phenotypic, full pedigree, and genomic information. J. Dairy Sci., 92, pp. 4648–4655.Misztal, I. et al. (2013) Methods to approximate reliabilities in single-step genomic evaluation. J. Dairy Sci., 96, pp. 647-654.Pešek, P., Přibyl, J. and Vostrý, L. (2015) Genetic variances of SNP loci for milk yield in dairy cattle. J. Appl. Genet., 56, pp. 339-347.Přibyl, J. et al. (2014) Domestic and Interbull information in the single step genomic evaluation of Holstein milk production.  Czech J. Anim. Sci., 59, pp. 409-415.Přibyl, J. et al. (2015) Domestic estimated breeding values and genomic enhanced breeding values of bulls in comparison with their foreign genomic enhanced breeding values. Animal, 9, pp. 1635-1642.VanRaden, P.M. (2008) Efficient methods to compute genomic predictions. J. Dairy Sci., 91, pp. 4414–4423.VanRaden, P.M. et al. (2011) Genomic evaluations with many more genotypes. Genet. Sel.Evol. 43, pp. 10.Wright, S. (1921) Systems of mating. Genetics. 6, pp. 111-178.Zavadilová, L. et al. (2014) Single-step genomic evaluation for linear type traits of Holstein cows in Czech Republic. Anim. Sci. Papers and Reports vol. 32, pp. 201-208.

Modelling of health monitoring signals and detection areas for aerospace structures

This paper is focused on Structural Health Monitoring (SHM) for aerospace use. It analyses the performance of commercially available finite element (FE) software packages for the simulation of propagation of ultrasonic guided waves (UGW) in typical aerospace structures. The purpose of the research is to support activities leading to the introduction of UGW based health monitoring on aerospace structures, as well as to support the design of future structures with integrated health monitoring. Activities are demonstrated on panels with growing complexity (adding different materials, sensors, damage types etc.). FE simulations are used to identify “detection areas” of UGW sensors. This output can be directly applied to the design of future aerospace structures with an integrated SHM system (to ensure the proper planning of the placement of UGW sensors)

Semi and Fully-probabilistic Nonlinear Analyses of Post-tensioned Concrete Bridge Made of KT-24 Girders

This paper deals with the assessment of the design resistance of an existing railway bridge made of KT-24 precast post-tensioned concrete girders. The load-bearing capacity of the structure is determined us- ing probabilistic nonlinear analysis by the finite element method. Load-bearing capacity is determined for the ultimate and serviceability limit states. A fully proba- bilistic approach is compared to selected recommended semi-probabilistic methods, which can greatly reduce the number of nonlinear calculations needed to estimate the design value of resistance. Two stochastic mod- els are compared, reflecting the level of knowledge of actual material properties from the diagnostic survey. The results are compared and discussed with respect to accuracy and required computational time, which is a critical issue when performing a global nonlinear anal- ysis of a complex structure

Genetic Parameters for a Weighted Analysis of Survivability in Dairy Cattle

The genetic parameters for the survival of Holstein cows, analysed in nine consecutive time periods during the first three calving intervals, were estimated. The earlier the animals are culled, the more they are informationally underestimated. This undervaluing can be remedied by using a weighted analysis that balances the amount of information. If the method of estimating breeding values changes, the genetic parameters will also change. The Holstein cattle dataset from 2005 to 2017 used in this study included 1,813,636 survival records from 298,290 cows. The pedigree with three generations of ancestors included 660,476 individuals. Linear repeatability models estimated genetic parameters for overall and functional survivability. Due to weights, heritability increased from 0.013 to 0.057. Repeatability with weights was 0.505. The standard deviations of breeding values were 1.75 and 2.18 without weights and 6.04 and 6.20 with weights. Including weights in the calculation increased the additive variance proportion and the breeding values’ reliabilities. We conclude that the main contribution of the weighted method we have presented is to compensate for the lack of records in culled individuals with a positive impact on the reliability of the breeding value

Comparison of genomic breeding values of Holstein in Czech Republic

Genomic evaluation by single-step procedure allows efficient implanting of genetic SNP markers into complicated procedure of random regression test-day-model of milk traits. Test-day records and pedigree files on nation-wide scale are combined with genomic relationship into common evaluation of both genotyped and ungenotyped animals. Due to strong import of foreign sperm into small national populations is the reliability of evaluation of young animals low. This is particularly seen in evaluation of young bulls, which frequently have both parents foreign. Genomic evaluation helps and notably improves reliability of evaluation. ssGBLUP procedure is advantageous especially for small populations. Domestic genomic evaluation of young animals has medium to high correlation with foreign Interbull values. Interbull conversion of values of bulls according MACE, which works with progeny tested bulls, is more reliable than conversion according GMACE procedure, which works with genomic evaluation of young animals.  Keywords: genomic breeding value, ssGBLUP, test day model, MACE, GMACEReferencesBauer, J. et al. (2014) Approximation of the reliability of single-step genomic breeding values for dairy cattle in the Czech Republic. Anim. Sci. Papers and Reports, 32, pp. 301-306.Bauer, J., Přibyl, J. and Vostrý, L. (2015) Contribution of domestic production records and Interbull EBV on approximate reliabilities of single-step genomic breeding values in dairy cattle. Czech J. Anim. Sci., 60, 263-267.Christensen,  O.F. and Lund, M.S. (2010) Genomic prediction when some animals are not genotyped. Genet.Sel.Evol. 42, pp. 2.Forni, S., Aguilar I. and Misztal, I. (2011) Different genomic relationship matrices for single step analysis using phenotypic, pedigree and genomic information. Genet. Sel. Evol., 43, pp. 1.Legarra A., Aguilar I. and Misztal, I. (2009) A relationship matrix including full pedigree and genomic information. J. Dairy Sci., 92, pp. 4656-4663.Meuwissen, T.H.E., Hayes, B.J. and Goddard, M.E. (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics, 157, pp. 1819–1829.Misztal, I., Legarra A. and Aguilar, I. (2009) Computing procedures for genetic evaluation including phenotypic, full pedigree, and genomic information. J. Dairy Sci., 92, pp. 4648–4655.Pešek, P., Přibyl, J. and Vostrý, L. (2015) Genetic variances of SNP loci for milk yield in dairy cattle. J. Appl. Genet., 56, pp. 339-347.Plemdat, (2015) Descriptions of Breeding values Evaluation.  Retrieved on 10th June 2015 From www.plemdat.cz.Přibyl, J. et al. (2014) Domestic and Interbull information in the single step genomic evaluation of Holstein milk production.  Czech J. Anim. Sci., 59, pp. 409-415.Přibyl, J. et al. (2015) Domestic estimated breeding values and genomic enhanced breeding values of bulls in comparison with their foreign genomic enhanced breeding values. Animal, 9, pp. 1635-1642.Vitezica, Z.G. et al. (2011) Bias in genomic predictions for populations under selection. Genet. Res. (Camb), 93, pp. 357-366.Zavadilová, L., Jamrozik, J. and Schaeffer, L.R. (2005a) Genetic parameters for test-day model with random regressions for production traits of Czech Holstein cattle. Czech J. Anim. Sci., 50, pp. 142-154.Zavadilová, L., Němcová, E. and Wolf, J. (2005b) Definition of subgroups for fixedregression in the test-day animal model for milk production of Holstein cattle in the CzechRepublic. Czech J. Anim. Sci., 50, pp. 7-13.Zavadilová, L. et al. (2014) Single-step genomic evaluation for linear type traits of Holstein cows in Czech Republic. Anim. Sci. Papers and Reports vol. 32, pp. 201-208

Hub4Everybody - New Collaborative Environment for Sharing

Hub4Everybody is a one-of-a-kind solution for publishing, sharing and cooperative management of geographical datasets, such as professional data and measuring, results of research projects or student papers, educational materials, emotional maps, visualization of in-field research and other maps, tables, or databases. You can easily upload or update your data as well as adjust the parameters of sharing among different audiences. Hub4Everybody is an alternative tool combining online office software with an editorial system for spatial data. It is also an Open-Source alternative to already existing commercial solutions, while offering additional extending options. Hub4Everybody offers all usual functions of geoportals (working with a map, linking of external data and services) but on top of that it offers a possibility to link desktop and mobile solutions for geographical data processing, data visualisation in form of storyboard and communication components via social networks. The solution is scalable and fully adaptable to the end-user needs. You can store your data directly on Hub4Everybody cloud or in your own infrastructure. All technologies used for Hub4Everybody are open source, which enables you to communicate with all kinds of users all over the world while no costs are necessary. The paper describes not only the current system, but also the history of development and potential utilization. An intensive testing and development using a series of INSPIRE Hackathons are an important part of development