Comparing Emotional Communities: Moravians, Methodists and Halle Pietists

In this paper I will lay out the framework for comparing emotional vocabularies, using two corpora of first-person narratives from the Moravian Church and the Methodist Church from the mid-18th century. The Moravian texts are from the Fetter Lane congregation in London and the majority of the manuscripts are to be found at Moravian Church House. These texts have been transcribed, encoded and published on the Moravian Lives website. The Methodist corpus is compiled from a project housed at the Rylands Library in Manchester, which contains letters of petition to Charles Wesley tranbscribed by volunteers and available online at (https://www.library.manchester.ac.uk/services/digitisation-services/projects/rapture-and-reason/) As McGuire and I have shown in our previous study (Faull and McGuire 2022), applying computational analysis to text corpora can help to identify emotional communities in which common patterns and sentiment lexica can be found. This paper will begin to address these questions by: a) identifying the emotional vocabularies or sentiment dictionaries of personal narratives of members of the Methodist and Moravian churches in Northern England in the eighteenth century; b) exploring a methodology for measuring those sentiments and offer alternate methods for analysis and interpretation c) asking whether such a comparative perspective could be applied to the personal papers of Halle Pietists. I make this claim based on Hindmarsh\u27s argument that, Zinzendorf’s dispute with the Halle pietists on the necessity of the Busskampf as proof of conversion in 1740 is simultaneous with the contact with the Wesleys and Methodism. In Hindmarsh’s eyes, this meant that the Moravians and their followers were able to distinguish their own piety from that of the Methodists in the same way: Methodism was Hallensian Pietism redivivus (Hindmarsh 165

Collaborating on Machine Reading: Training Algorithms to Read Complex Collections

Interdisciplinary collaboration between two faculty members in the humanities and computer science, a research librarian, and an undergraduate student has led to remarkable results in an ongoing international DH research project that has at its core 18th century manuscripts. The corpus stems from a vast collection of archival materials held by the Moravian Church in the UK, Germany, and the US. The number of pages to be transcribed, differences in handwriting styles, paper quality, and original language pose enormous problems for the feasibility of human transcription. This presentation will review the hypothesis, process, and findings of a summer research project that builds upon the Transkribus (Transkribus.eu) platform and seeks to refine the process for creating handwriting training recognition (HTR) models to further improve accuracy. An undergraduate student working with a faculty member in computer science developed a deep learning model to help overcome challenges of accuracy in computer transcription

Diagnostic accuracy and predictive value in differentiating the severity of dengue infection

Objective: To review the diagnostic test accuracy and predictive value of statistical models in differentiating the severity of dengue infection. Methods: Electronic searches were conducted in the Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, MEDLINE (complete), PubMed and Scopus. Eligible studies to be included in this review were cohort studies with participants confirmed by laboratory test for dengue infection and comparison among the different severity of dengue infection by using statistical models. The methodological quality of the paper was assessed by independent reviewers using QUADAS-2. Results: Twenty-six studies published from 1994 to 2017 were included. Most diagnostic models produced an accuracy of 75% to 80% except one with 86%. Two models predicting severe dengue according to the WHO 2009 classification have 86% accuracy. Both of these logistic regression models were applied during the first three days of illness, and their sensitivity and specificity were 91-100% and 79.3-86%, respectively. Another model which evaluated the 30-day mortality of dengue infection had an accuracy of 98.5%. Conclusion: Although there are several potential predictive or diagnostic models for dengue infection, their limitations could affect their validity. It is recommended that these models be revalidated in other clinical settings and their methods be improved and standardised in future

Translation Control of Swarming Proficiency in \u3cem\u3eBacillus subtilis\u3c/em\u3e by 5-amino-pentanolylated Elongation Factor P

Elongation factor P (EF-P) accelerates diprolyl synthesis and requires a posttranslational modification to maintain proteostasis. Two phylogenetically distinct EF-P modification pathways have been described and are encoded in the majority of Gram-negative bacteria, but neither is present in Gram-positive bacteria. Prior work suggested that the EF-P-encoding gene (efp) primarily supports Bacillus subtilis swarming differentiation, whereas EF-P in Gram-negative bacteria has a more global housekeeping role, prompting our investigation to determine whether EF-P is modified and how it impacts gene expression in motile cells. We identified a 5-aminopentanol moiety attached to Lys32 of B. subtilis EF-P that is required for swarming motility. A fluorescent in vivo B. subtilis reporter system identified peptide motifs whose efficient synthesis was most dependent on 5-aminopentanol EF-P. Examination of the B. subtilis genome sequence showed that these EF-P-dependent peptide motifs were represented in flagellar genes. Taken together, these data show that, in B. subtilis, a previously uncharacterized posttranslational modification of EF-P can modulate the synthesis of specific diprolyl motifs present in proteins required for swarming motility