Automatic generation of data representations for construction applications

This paper presents an argument for automating data representations within the construction sector. It questions whether full automation and integration is feasible and achievable considering the complexity of the industry and supply chain problems. The paper starts by reviewing the research in the area of information automation, modelling and integration. A research prototype, GALLICON, is used as an example to demonstrate the levels of integration and automation that may be achieved with the current generation of technology

Simple and statistically sound recommendations for analysing physical theories

Physical theories that depend on many parameters or are tested against data from many different experiments pose unique challenges to statistical inference. Many models in particle physics, astrophysics and cosmology fall into one or both of these categories. These issues are often sidestepped with statistically unsound ad hoc methods, involving intersection of parameter intervals estimated by multiple experiments, and random or grid sampling of model parameters.Whilst these methods are easy to apply, they exhibit pathologies even in low-dimensional parameter spaces, and quickly become problematic to use and interpret in higher dimensions. In this article we give clear guidance for going beyond these procedures, suggesting where possible simple methods for performing statistically sound inference, and recommendations of readily-available software tools and standards that can assist in doing so. Our aim is to provide any physicists lacking comprehensive statistical training with recommendations for reaching correct scientific conclusions, with only a modest increase in analysis burden. Our examples can be reproduced with the code publicly available at Zenodo.Shehu S AbdusSalam, Fruzsina J Agocs, Benjamin C Allanach, Peter Athron, Csaba Balázs, Emanuele Bagnaschi, Philip Bechtle, Oliver Buchmueller, Ankit Beniwal, Jihyun Bhom, Sanjay Bloor, Torsten Bringmann, Andy Buckley, Anja Butter, Jos, e Eliel Camargo-Molina, Marcin Chrzaszcz, Jan Conrad, Jonathan M Cornell, Matthias Danninger, Jorge de Blas, AlbertDeRoeck, Klaus Desch, MatthewDolan, Herbert Dreiner, Otto Eberhardt, John Ellis, Ben Farmer, Marco Fedele, Henning Flächer, Andrew Fowlie, Tomás E Gonzalo, Philip Grace, Matthias Hamer, Will Handley, JuliaHarz, Sven Heinemeyer, Sebastian Hoof, Selim Hotinli, Paul Jackson, Felix Kahlhoefer, Kamila Kowalska, Michael Krämer, Anders Kvellestad, Miriam Lucio Martinez, Farvah Mahmoudi, Diego Martinez Santos, Gregory D Martinez, Satoshi Mishima, KeithOlive, Ayan Paul, Markus Tobias Prim, Werner Porod, Are Raklev, JaninaJRenk, Christopher Rogan, Leszek Roszkowski, Roberto Ruiz de Austri, Kazuki Sakurai, Andre Scaffidi, PatScott, Enrico Maria Sessolo, Tim Stefaniak, Patrick Stöcker, Wei Su, Sebastian Trojanowski, Roberto Trotta, Yue-Lin Sming Tsai, Jeriek Van den Abeele, MauroValli, Aaron C Vincent, Georg Weiglein, MartinWhite, Peter Wienemann, LeiWu, and Yang Zhan

The Phenylpropanoid Pathway in Arabidopsis

The phenylpropanoid pathway serves as a rich source of metabolites in plants, being required for the biosynthesis of lignin, and serving as a starting point for the production of many other important compounds, such as the flavonoids, coumarins, and lignans. In spite of the fact that the phenylpropanoids and their derivatives are sometimes classified as secondary metabolites, their relevance to plant survival has been made clear via the study of Arabidopsis and other plant species. As a model system, Arabidopsis has helped to elucidate many details of the phenylpropanoid pathway, its enzymes and intermediates, and the interconnectedness of the pathway with plant metabolism as a whole. These advances in our understanding have been made possible in large part by the relative ease with which mutations can be generated, identified, and studied in Arabidopsis. Herein, we provide an overview of the research progress that has been made in recent years, emphasizing both the genes (and gene families) associated with the phenylpropanoid pathway in Arabidopsis, and the end products that have contributed to the identification of many mutants deficient in the phenylpropanoid metabolism: the sinapate esters