"Ain schone kunstliche underweisung": Modelling German lute tablature in MEI

Abstract: https://teimec2023.uni-paderborn.de/contributions/188.htm

Crafting TabMEI, a Module for Encoding Instrumental Tablatures

In this progress report, we describe the issues encountered during the design and implementation of TabMEI, a new MEI module for encoding instrumental tablatures. We discuss the main challenges faced and lay out our workflow for implementing the TabMEI module. In addition, we present a number of example encodings, and we describe anticipated applications of the module

A Large-Scale Semantic Library of MIDI Linked Data

Over recent decades, the natural sciences have moved from formulating hypotheses through the observation of phenomena to generating them automatically through the analysis of large cross-disciplinary datasets, collected and maintained within large collaborative projects. Recently, it was suggested that musicology should embrace the same paradigm shift, and move to a more collaborative and data-oriented culture. In this paper, we describe the MIDI Linked Data Cloud, an RDF graph of 10 billion MIDI statements linked to contextual metadata. We show examples of its potential application for digital libraries for musicology, and we argue that the use of Linked Data for integrating symbolic music notations and contextual metadata constitutes technical foundations for Web-scale musicology projects

The MIDI Linked Data Cloud

The study of music is highly interdisciplinary, and thus requires the combination of datasets from multiple musical domains, such as catalog metadata (authors, song titles, dates), industrial records (labels, producers, sales), and music notation (scores). While today an abundance of music metadata exists on the Linked Open Data cloud, linked datasets containing interoperable symbolic descriptions of music itself, i.e. music notation with note and instrument level information, are scarce. In this paper, we describe the MIDI Linked Data Cloud dataset, which represents multiple collections of digital music in the MIDI standard format as Linked Data using the novel midi2rdf algorithm. At the time of writing, our proposed dataset comprises 10,215,557,355 triples of 308,443 interconnected MIDI files, and provides Web-compatible descriptions of their MIDI events. We provide a comprehensive description of the dataset, and reflect on its applications for research in the Semantic Web and Music Information Retrieval communities

Curating and Archiving Linked Data Datasets from the Humanities - From Data of the Present to Data of the Future

Abstract of paper 0652 presented at the Digital Humanities Conference 2019 (DH2019), Utrecht , the Netherlands 9-12 July, 2019

Cardiac inflammation and microvascular procoagulant changes are decreased in second wave compared to first wave deceased COVID-19 patients.

BACKGROUND Compelling evidence has shown cardiac involvement in COVID-19 patients. However, the overall majority of these studies use data obtained during the first wave of the pandemic, while recently differences have been reported in disease course and mortality between first- and second wave COVID-19 patients. The aim of this study was to analyze and compare cardiac pathology between first- and second wave COVID-19 patients. METHODS Autopsied hearts from first- (n = 15) and second wave (n = 10) COVID-19 patients and from 18 non-COVID-19 control patients were (immuno)histochemically analyzed. CD45+ leukocyte, CD68+ macrophage and CD3+ T lymphocyte infiltration, cardiomyocyte necrosis and microvascular thrombosis were quantified. In addition, the procoagulant factors Tissue Factor (TF), Factor VII (FVII), Factor XII (FXII), the anticoagulant protein Dipeptidyl Peptidase 4 (DPP4) and the advanced glycation end-product N(ε)-Carboxymethyllysine (CML), as markers of microvascular thrombogenicity and dysfunction, were quantified. RESULTS Cardiac inflammation was significantly decreased in second wave compared to first wave COVID-19 patients, predominantly related to a decrease in infiltrated lymphocytes and the occurrence of lymphocytic myocarditis. This was accompanied by significant decreases in cardiomyocyte injury and microvascular thrombosis. Moreover, microvascular deposits of FVII and CML were significantly lower in second wave compared to first wave COVID-19 patients. CONCLUSIONS These results show that in our cohort of fatal COVID-19 cases cardiac inflammation, cardiomyocyte injury and microvascular thrombogenicity were markedly decreased in second wave compared to first wave patients. This may reflect advances in COVID-19 treatment related to an increased use of steroids in the second COVID-19 wave