Tangling and Untangling the Trollopes: A Stylometric Analysis of Frances Milton Trollope, Frances Eleanor Trollope, Anthony Trollope, Thomas Adolphus Trollope, and Charles Dickens

This documentation accompanies 'Tangling and Untangling the Trollopes: A Stylometric Analysis of Frances Milton Trollope, Frances Eleanor Trollope, Anthony Trollope, Thomas Adolphus Trollope, and Charles Dickens', published in Victorian Review. Documentation includes a complete list of texts comprising the corpus, including links to the texts used, and a list of the 1,000 words used in the analysis

Evolution of radiation-induced lattice defects in 20/25 Nb-stabilised austenitic stainless steel during in-situ proton irradiation

We have monitored in situ the lattice defect evolution induced by proton irradiation in 20Cr-25Ni Nb-stabilised stainless steel, used as fuel cladding material in advanced gas-cooled reactors. At 420 °C, the damaged microstructure is mainly characterised by black spots and faulted [Formula presented]〈111〉 Frank loops. Defect saturation is reached at only 0.1dpa. In contrast, at 460 °C and 500 °C proton bombardment induces the formation of a mixture of [Formula presented]〈111〉 Frank loops and perfect [Formula presented]〈110〉 loops. These perfect loops evolve into dislocation lines that form a dense network. This transition coincides with the saturation in the dislocation loop size and number density at 0.8dpa (460 °C) and 0.2dpa (500 °C), respectively. The presence of a high density of dislocation loops and lines at those two temperatures causes a vacancy supersaturation in the matrix, leading to the formation of voids and stacking fault tetrahedra.</p

Enhancing big data warehousing for efficient, integrated and advanced analytics visionary paper

The existing capacity to collect, store, process and analyze huge amounts of data that is rapidly generated, i.e., Big Data, is characterized by fast technological developments and by a limited set of conceptual advances that guide researchers and practitioners in the implementation of Big Data systems. New data stores or processing tools frequently appear, proposing new (and usually more efficient) ways to store and query data (like SQL-on-Hadoop). Although very relevant, the lack of common methodological guidelines or practices has motivated the implementation of Big Data systems based on use-case driven approaches. This is also the case for one of the most valuable organizational data assets, the Data Warehouse, which needs to be rethought in the way it is designed, modeled, implemented, managed and monitored. This paper addresses some of the research challenges in Big Data Warehousing systems, proposing a vision that looks into: (i) the integration of new business processes and data sources; (ii) the proper way to achieve this integration; (iii) the management of these complex data systems and the enhancement of their performance; (iv) the automation of some of their analytical capabilities with Complex Event Processing and Machine Learning; and, (v) the flexible and highly customizable visualization of their data, providing an advanced decision-making support environment.This work has been supported by FCT - Fundacao para a Ciencia e Tecnologia, Projects Scope UID/CEC/00319/2019 and PDE/00040/2013, and the Doctoral scholarships PD/BDE/135100/2017 and PD/BDE/135101/2017. We also thank both the Spanish State Research Agency and the Generalitat Valenciana under the projects DataME TIN2016-80811-P, ACIF/2018/171, and PROMETEO/2018/176. This paper uses icons made by Freepik, from www.flaticon.com