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Overview of the activities of the Aviation Laboratory under German rule between 1940 and 1945. Although officially driven by scientific motivation only, the laboratory worked closely with German aviation research and contributed to the German war effort.

Description of the kittajafr-v2-2.0.1; This guide presents KittajaFr-v2. It is a set of free resources and tools frequently used in machine translation, to build a Transformer model to translate from Japanese into French. The corpus contains 2,5M aligned segments. Score BLEU is between 13,5 et 11,5.; Ce guide présente le kit kittajafr-v2baseline. Il s'agit d'un ensemble de ressources et d'outils libres couramment utilisés en traduction automatique, permettant d'entraîner un modèle Transformer de traduction neuronale du japonais vers le français. Le corpus contient 2,5M de segments alignés de qualité variable. La segmentation (sentencePiece) du vocabulaire est fixée à 16K mots pour chaque langue et les embeddings sont de 256. Les scores BLEU se situent vers 13,5 et 11,5 (on dispose aussi des scores chrF). Le kittjafr-v2 fait suite à la version v1, qui permettait de construire un très petit modèle (score BLEU 3 et 7).

The School of Culinary Arts and Food Technology, TU Dublin, Winter Newsletter captured the many events, research, awards, significant contributions, special civic, community and sustainability activities which the students and staff members of the school have successfully completed up to the Winter period of 2021. The successful completion of these activities would not be possible without the active and on-going support of the 'INSPIRED' friends of Culinary Arts (school supporters) and our school's industry association supporters. We thank you all, consider getting involved in our New Campus (Central Quad, Grangegorman, Dublin 7). Take care and stay safe !!

This dataset is intended for training and testing Logical Layout Analysis and recognition system on French historical documents published between 1900 and 1950. The original data is part of the "Fond régional: Franche-Comté", which is curated by Gallica, the digital portal of the Bibliothèque Nationale de France (BnF). It is available on Zenodo at the following adress: https://zenodo.org/record/5752440#.YboX6lPjJhE; This dataset is intended for training and testing Logical Layout Analysis and recognition system on French historical documents published between 1900 and 1950. The original data is part of the "Fond régional: Franche-Comté", which is curated by Gallica, the digital portal of the Bibliothèque Nationale de France (BnF). It is available on Zenodo at the following adress: https://zenodo.org/record/5752440#.YboX6lPjJhE

The Cabeço da Arruda archaeological site, located in the Muge Valley (Central Portugal), is a shell-midden burial site situated in the Mesolithic period (8,500 to 6,900 cal BP). Previous research on the valley has neglected to properly document and systematize the roughly 150 burials recovered from this site which have been curated in the Museo Geológico Museum in Lisbon since the 1930s. My research focused on systematizing the burials at this museum, identifying the individuals whose boney segments preserved in a mud-based cement (breccia), and reconstructing the burial rituals associated with body position and grave environment features using an archaeothanatological method. This allowed me to address the questions: (1) Are there identifiable burial dispositional patterns at Cabeço da Arruda?; and (2) Through comparison of the similarities and differences in dispositional patterns and mortuary practices between the three main sites in the valley (Cabeço da Arruda, Cabeço da Amoreira, and Moita do Sebastião), are there identifiable characteristics throughout the entirety of the Muge Mesolithic? I determined that the most common burial disposition at Cabeço da Arruda was dorsal decubitus with a hyper-flexed lower limb which was positioned over the thorax. The most common grave features were for the body to be interred in an oval, concave pit with lateral space and external wrappings constricting the upper limb and thorax. These patterns constitute burial rituals because their repetition, with minimal individual variation, is indicative of prescribed behaviours occurring during the internment phase. When including osteobiographical data into these interpretations, no statistical pattern was identified for age (neonates, nonadults, adults) or sex (female or male) across the burial ritual data. These interpretations were consistent with the frequencies of previous burial dispositional patterns from the valley indicating that there were consistent rituals within the valley during the Mesolithic.

Introduction: Routinely collected electronic health data (RCEHD), can be comprised of structured, semi-structured, or unstructured information. Electronic medical records (EMRs), one type of RCEHD, often contain unstructured text data (UTD), which are typically prepared for analysis (i.e., preprocessed) and analyzed using natural language processing (NLP) techniques. At present, there are few studies about the specific types of NLP methods used to preprocess UTD to address data quality issues prior to analysis or modelling. Purpose & Objectives: The purpose was to examine preprocessing methods for UTD and evaluate the quality of UTD in EMRs. The objectives were to: 1) systematically document current research and practices for preprocessing UTD to describe or improve its quality, and 2) apply data quality indicators identified from current research and practices to UTD in EMRs from the Manitoba Primary Care Research Network and describe the quality of these data. Methods: Objective 1 involved a scoping review. Scopus, Web of Science, ProQuest, and EBSCOhost were searched for literature on current research and practices to prepare UTD for analysis, up to and including 2021. For objective 2, a case study was undertaken where data quality indicators and preprocessing methods identified in the scoping review were applied to UTD from EMRs. Results: 41 articles were included in the scoping review for objective 1; over 50% were published between 2016 and 2021 and over 90% were empirical research articles. Data quality indicator topics for UTD in EMRs included misspelled words, security, word variability, sources of noise, quality of annotations, ambiguous abbreviations, and manual annotations. For objective 2, we selected 193,206 clinical encounter notes from EMRs between 1985 and 2020. Overall, the clinical encounter notes contained an average (standard deviation [SD]) of 27.3 (27.0) stop words, 25.7 (27.8) punctuation symbols, 12.1 (11.1) spelling errors, and 2.9 (2.6) special characters. The average (SD) length of a clinical encounter note was 555.8 (551.1) characters, and 71.5 (59.7) words. Lexical diversity, had a mean (SD) of 86.2 (11.9). Conclusion: This study identified multiple data quality indicators that have been used to preprocess UTD in published literature and demonstrated their application to real-world data.

The War dummies data set provides structured data on organized armed confrontations with Dutch involvement between 1566 and 1812. The data structure and content align with two well-known data sets with modern (i.e. post 1815) conflict data: the Inter-State War Database of the Correlates of War Project and the Georeferenced Event Dataset (GED) of the Uppsala Conflict Data Program. The War dummies data are based on three volumes of the book series Militaire geschiedenis van Nederland (published under the auspices of the Dutch Institute for Military History – NIMH) that cover the early-modern. They are suited for quantitative analyses of organized armed confrontations with Dutch involvement, and can be readily applied in statistical analyses.

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Las redes sociales son una rica fuente de datos y han sido utilizadas para promover u organizar ciberdelitos que afectan al mundo real. Por ello, las fuerzas del orden se interesan por la información crucial que puede obtenerse de estas fuentes. La cantidad de información y el lenguaje informal que se utiliza para difundir la información hace que el Procesamiento del Lenguaje Natural (PLN) sea una excelente herramienta para realizar análisis sobre las publicaciones en las redes sociales. Por ello, en esta propuesta se integra una arquitectura con tres modelos de PLN para proporcionar un análisis exhaustivo de fuentes abiertas como los medios sociales. Este análisis extrae entidades del texto, identifica clusters de usuarios y su respectiva polaridad, finalmente todos los resultados se relacionan en una base de datos gráfica. Esta arquitectura se puso a prueba utilizando datos de un escenario real para determinar su viabilidad.