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The aim of this article is to offer a systematic review of digital studies that provide new research perspectives on ancient classical theatre. The undeniable progress in the field of computational analysis in the service of traditional textual interpretation is helping to study in greater depth and to interpret in greater detail the classical linguistic corpora that have come down to us through the manuscript tradition. The new model of digital research is integrated not only in the field of information technologies, but also in the field of e-learning, where we can already observe the implementation of a new educational model. Based on the digital processing of data on Greco-Roman theatre, a systematic review is presented, following the methodological principles of the PRISMA statement [ Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2009 (2020)]. [ABSTRACT FROM AUTHOR]

This research focuses on classifying translated and non-translated Chinese texts by analyzing syntactic rule features, using an integrated approach of machine learning and entropy analysis. The methodology employs information entropy to gauge the complexity of syntactic rules in both text types. The methodology is based on the concept of information entropy, which serves as a quantitative measure for the complexity inherent in syntactic rules as manifested from tree-based annotations. The goal of the study is to explore whether translated Chinese texts demonstrate syntactic characteristics that are significantly different from those of non-translated texts, thereby permitting a reliable classification between the two. To do this, the research calculates information entropy values for syntactic rules in two comparable corpora, one of translated and the other of non-translated Chinese texts. Then, various machine learning models are applied to these entropy metrics to identify any significant differences between the two groups. The results show significant differences in the syntactic structures. Translated texts have a higher degree of entropy, indicating more complex syntactic constructs compared to non-translated texts. These findings contribute to our understanding of the effect of translation on language syntax, with implications for text classification and translation studies. [ABSTRACT FROM AUTHOR]

This article will analyze the use of the noun nafs ‘soul’ with the firstperson possessive pronominal suffix, through the corpus of Andalusi texts gathered in Nafḥ al-ṭīb by the North-African author Shihāb al-Dīn al-Maqqarī (d. 1632). The aim is threefold: one, to identify patterns of the use of nafsī in the Nafḥ, their semantic performance, and diachronic evolution; two, to compare the use of the term in this corpus with its use in lists of collocates in the macro corpora KSUCCA and arTenTen of Classical and Modern Standard Arabic; and three, to show that linguistically systematizing self-expression is adequate for the identification of highly subjective texts in a corpus. Analysis will show that the notions of the ‘divided self’, sacrificing oneself, and yearning change towards a closer relationship between the subject and the self over time. [ABSTRACT FROM AUTHOR]

The launch of the FrameNet project in 1997 was both a crystallisation point of decades worth of theoretical investigations into lexical meaning by Charles J. Fillmore and colleagues, as well as the seed of an ongoing line of corpus-based and computational research that seeks to implement Fillmore's theory of Frame Semantics in a way that both provides an interesting model relevant for further theorising and also is applicable practically for semantic analysis, lexicology, and lexicography. At the occasion of FrameNet's 25th birthday, we want to introduce the project to a new generation of researchers but also take stock of, and report on, what has been achieved. We revisit the origins of the FrameNet project, assess its development and various changes in the years since it was first reported on in a special issue in the pages of this journal twenty years ago. [ABSTRACT FROM AUTHOR]

Motivation Biomedical entity linking (BEL) is the task of grounding entity mentions to a given knowledge base (KB). Recently, neural name-based methods, system identifying the most appropriate name in the KB for a given mention using neural network (either via dense retrieval or autoregressive modeling), achieved remarkable results for the task, without requiring manual tuning or definition of domain/entity-specific rules. However, as name-based methods directly return KB names, they cannot cope with homonyms, i.e. different KB entities sharing the exact same name. This significantly affects their performance for KBs where homonyms account for a large amount of entity mentions (e.g. UMLS and NCBI Gene). Results We present BELHD (Biomedical Entity Linking with Homonym Disambiguation), a new name-based method that copes with this challenge. BELHD builds upon the BioSyn model with two crucial extensions. First, it performs pre-processing of the KB, during which it expands homonyms with a specifically constructed disambiguating string, thus enforcing unique linking decisions. Second, it introduces candidate sharing, a novel strategy that strengthens the overall training signal by including similar mentions from the same document as positive or negative examples, according to their corresponding KB identifier. Experiments with 10 corpora and 5 entity types show that BELHD improves upon current neural state-of-the-art approaches, achieving the best results in 6 out of 10 corpora with an average improvement of 4.55pp recall@1. Furthermore, the KB preprocessing is orthogonal to the prediction model and thus can also improve other neural methods, which we exemplify for GenBioEL, a generative name-based BEL approach. Availability and implementation The code to reproduce our experiments can be found at: https://github.com/sg-wbi/belhd. [ABSTRACT FROM AUTHOR]

Cambridge, Corpus Christi College, MS 402 uniquely transmits the authorial revision of the central Middle English spiritual text, Ancrene Riwle/Ancrene Wisse. The first leaf includes a note of the book's donation to the Augustinian abbey at Wigmore (Herefs) around 1300. This note investigates the donor and the circumstances that may have prompted both the book's production and the abbey precentor's request for its donation. [ABSTRACT FROM AUTHOR]

Amidst ongoing global debate about reproductive rights, questions have emerged about the role of language in reinforcing stigma around termination. Amongst some 'pro-choice' groups, the use of pro-life is discouraged, and anti-abortion is recommended. In UK official documents, termination of pregnancy is generally used, and abortion is avoided. Lack of empirical research focused on lexis means it is difficult to draw conclusions about the role language plays in this polarized debate, however. This paper, therefore, explores whether the stigma associated with abortion may reflect negative semantic prosody. Synthesizing quantitative corpus linguistic methods and qualitative discourse analysis, it presents findings that indicate that abortion has unfavourable semantic prosody in a corpus of contemporary internet English. These findings are considered in relation to discursive salience, offering a theoretical framework and operationalization of this theory. Through this lens, the paper considers whether the discursive salience of extreme anti-abortion discourses may strengthen the negative semantic prosody of abortion. It, therefore, combines a contribution to theory around semantic prosody with a caution to those using abortion whilst unaware of its possibly unfavourable semantic prosody. [ABSTRACT FROM AUTHOR]

Contemporary Japanese given names exhibit great variety and have minimal formal restrictions in their formation. It is often possible, however, to determine the gender of the name's bearer from its phonological and/or graphic form. In this article, various features, including name length, syllables, and characters at particular positions within a name and the choice of script, are statistically analyzed to determine whether they are significantly associated with male or female names and which of them contribute the most to the expression of gender. The findings of this study verify the empirical knowledge of the gender-markedness of some of the features and establish a solid foundation for future feature-based gender prediction algorithms. The expression of gender in currently bestowed names is discussed in the context of major changes in naming practices and name choices toward the end of the 20th century. [ABSTRACT FROM AUTHOR]

Although the idea of the Anthropocene originated in the earth sciences, there have been increasing calls for questions about the Anthropocene to be addressed by pan-disciplinary groups of researchers from across the natural sciences, social sciences, and humanities. We use data analysis techniques from corpus linguistics to examine academic texts about the Anthropocene from these disciplinary families. We read the data to suggest that barriers to a broadly interdisciplinary study of the Anthropocene are high, but we are also able to identify some areas of common ground that could serve as interdisciplinary bridges. [ABSTRACT FROM AUTHOR]

Though best known for his extensive and often transformative writings on lexicography and corpus linguistics, Patrick Hanks was also a career lexicographer with a strong track record of managing a string of groundbreaking dictionaries. His experience at the lexicographic coalface led him to question dictionary conventions, especially when the corpus data seemed to be at odds with traditional approaches to identifying and explaining meanings. His ideas about meaning potentials, his focus on 'the probable not the possible', and his Theory of Norms and Exploitations all arose directly from the experience of analysing corpus data in order to describe how words behave and combine. He was involved in almost every major development in our field over the last 50 years, and his influence will continue to be felt for as long as people are analysing language and making dictionaries. [ABSTRACT FROM AUTHOR]

We describe an efficient pipeline for morpho-syntactically annotating an ancient language corpus which takes advantage of bootstrapping techniques. This pipeline is designed for ancient language scholars looking to jump-start their own treebank projects, which can in turn serve further pedagogical research projects in the target language. We situate our work in the field of similar ancient language treebank projects, arguing that our approach shows that individual humanities scholars can leverage current machine-learning tools to produce their own richly annotated corpora. We illustrate this pipeline by producing a new Akkadian-language treebank based on two volumes from the online editions of the State Archives of Assyria project hosted on Oracc, as well as a spaCy language model named AkkParser trained on that treebank. Both of these are made publicly available for annotating other Akkadian corpora. In addition, we discuss linguistic issues particular to the Neo-Assyrian letter corpus and data-encoding complications of cuneiform texts in Oracc. The strategies, language models, and processing scripts we developed to handle both linguistic and data-encoding issues in this project will be of special interest to scholars seeking to develop their own cuneiform treebanks. [ABSTRACT FROM AUTHOR]

The analysis of co-citations, which occurs when two publications or authors are mentioned together in the same text, has long been established as a practice within scientometrics, particularly in the field of "science mapping". However, historiography has shown less openness to utilizing co-citation analysis for distant reading purposes. To address this gap, this article presents a comprehensive methodology for applying co-citation analysis to extensive collections of historical documents, specifically 17th-century letters indexed in the ePistolarium database. In science mapping, co-citation serves as an indicator for tracking the development of scientific fields. Similarly, I employ co-citation to map the Dutch socio-intellectual landscape during the Scientific Revolution period (1623–87) and evaluate the strengths and limitations of this approach. [ABSTRACT FROM AUTHOR]

This article introduces and explores the 3.5-million-word Victorian Anti-Vaccination Discourse Corpus (VicVaDis). The corpus is intended to provide a (freely accessible) historical resource for the investigation of the earliest public concerns and arguments against vaccination in England, which revolved around compulsory vaccination against smallpox in the second half of the 19th century. It consists of 133 anti-vaccination pamphlets and publications gathered from 1854 to 1906, a span of 53 years that loosely coincides with the Victorian era (1837–1901). This timeframe was chosen to capture the period between the 1853 Vaccination Act, which made smallpox vaccination for babies compulsory, and the 1907 Act that effectively ended the mandatory nature of vaccination. After an overview of the historical background, this article describes the rationale, design and construction of the corpus, and then demonstrates how it can be exploited to investigate the main arguments against compulsory vaccination by means of widely accessible corpus linguistic tools. Where appropriate, parallels are drawn between Victorian and 21st-century vaccine-hesitant attitudes and arguments. Overall, this article demonstrates the potential of corpus analysis to add to our understanding of historical concerns about vaccination. [ABSTRACT FROM AUTHOR]

The year 1993 represents a momentous milestone in the not-so-long history of translation and interpreting studies (TIS). The foundational paper published by Mona Baker entitled 'Corpus linguistics and translation studies: Implications and applications' in 1993 has signalled a defining moment in the application of digital humanities (DH) approaches in TIS. Since then, corpus-based TIS, as a most visible manifestation of DH in TIS, has come into being and is now gradually entering into maturity. Compared with the previously largely anecdotal, impressionist, and prescriptivist accounts of translation and interpreting, the incorporation of DH tools (e.g. CL) has significantly enriched TIS with new perspectives. This makes it possible for researchers to explore the various aspects of translation and interpreting in a more objective and systematic way, drawing on real-world data. Now one-third of a century has passed since the publication of Baker's seminal paper, DH-inspired studies of translation and interpreting are in full swing. As we are reaching the 30-year mark of the influential publication, it is important for us to take stock of the previous achievements and look to the future both with pride and a cool head. In this article, we trace the developments of a DH approach to TIS and present the state of the art, before discussing some of the limitations and pitfalls and the road ahead going forward. [ABSTRACT FROM AUTHOR]

Many theoretical conclusions core to the study of international politics rely on having access to, and understanding, the rhetoric of international actors. One important development in advancing the empirical study of international relations (IR) theory, therefore, is the availability of machine-analyzable speech data. A collection of fine-grained textual representations of states' speeches in the context of an important international organization, such as the United Nations General Assembly (UNGA), is needed to understand the ideas, preferences, and values that states put forth in their statements. An especially promising use for such a corpus of texts would be to measure states' preferences based on their statements. In an effort to add to the burgeoning field of text-as-data in IR, I present the UNGA Speech Corpus, a collection of over 34,000 speeches delivered by states in the UNGA from 1993 to 2018. I use it to improve on recent work that links text to preferences in IR by combining a structural topic model with locally trained word embeddings to estimate the policy positions of states on specific topics. I then show how these "topic scores" can help scholars to improve their analyses of exigent international issues, such as global climate change governance. [ABSTRACT FROM AUTHOR]

With the rapid growth of online content written in the Kurdish language, there is an increasing need to make it machine-readable and processable. Part of speech (POS) tagging is a critical aspect of natural language processing (NLP), playing a significant role in applications such as speech recognition, natural language parsing, information retrieval, and multiword term extraction. This study details the creation of the DASTAN corpus, the first POS-annotated corpus for the Sorani Kurdish dialect. The corpus, containing 74,258 words and thirty-eight tags, employs a hybrid approach utilizing the bigram hidden Markov model in combination with the Kurdish rule-based approach to POS tagging. This approach addresses two key problems that arise with rule-based approaches, namely misclassified words and ambiguity-related unanalyzed words. The proposed approach's accuracy was assessed by training and testing it on the DASTAN corpus, yielding a 96% accuracy rate. Overall, this study's findings demonstrate the effectiveness of the proposed hybrid approach and its potential to enhance NLP applications for Sorani Kurdish. [ABSTRACT FROM AUTHOR]

This article presents a method of emotion analysis for German drama from the 17th to the 19th century that significantly goes beyond previous research approaches in computational literary studies. It is based on annotations of 17 dramatic texts resulting in 11,939 annotations which were used as training material to fine-tune a German language BERT model that achieves an average accuracy of 73% for the single-label emotion classification of fourteen emotion types in cross-validation. We apply the emotion classification on a corpus of 141 comedies and 92 tragedies to compare these genres. For tragedies, the mean proportion percentages of 'suffering' and 'abhorrence' are higher than for comedies. Inversely, mean percentages of 'anger' and 'joy' are higher for comedies than for tragedies. A new finding is the surprisingly high proportion of 'anger' in comedies. Emotion distribution of the last scenes in dramatic texts also proves the quality of the classified data in terms of literary studies. In addition, the emotion distribution for several subgenres of comedy is investigated including non-canonical works of wide circulation which reached the recipients directly through the depicted emotions in the Kasperl Plays. Comedies from 1740 to 1770 are characterized by a pairing of higher amounts of 'friendship' and 'love'. Satirical comedies from the same period stand out due to high rates of 'anger' as well as 'suffering'. The very successful Kasperl plays turn out to be characterized by a comparatively large percentage of 'schadenfreude' and 'joy'. [ABSTRACT FROM AUTHOR]

Motivation The recognition of mentions of species names in text is a critically important task for biomedical text mining. While deep learning-based methods have made great advances in many named entity recognition tasks, results for species name recognition remain poor. We hypothesize that this is primarily due to the lack of appropriate corpora. Results We introduce the S1000 corpus, a comprehensive manual re-annotation and extension of the S800 corpus. We demonstrate that S1000 makes highly accurate recognition of species names possible (F -score =93.1%), both for deep learning and dictionary-based methods. Availability and implementation All resources introduced in this study are available under open licenses from https://jensenlab.org/resources/s1000/. The webpage contains links to a Zenodo project and three GitHub repositories associated with the study. [ABSTRACT FROM AUTHOR]

The fact is now accepted that specialised discourses do not deviate from the rules of language: variation in all its forms emerges from corpora. One of the questions that now arises is that of "implementing" socioterminological data in terminological resources: how can sociolinguistic diversity be integrated into a descriptive program? After reviewing the types of variation, this article explores an approach to integrating some of these data into a terminographic ressource. This will provide an opportunity to discuss the question of the interface with the corpus, which is no longer confined to a descriptive objective, but is likely to become a pivotal element of a database. [ABSTRACT FROM AUTHOR]

Bertalign is designed to improve sentence alignment accuracy for Chinese–English parallel corpora of literary texts. Aligning bilingual literary texts is not trivial, since most of the translation is interpretative and not based on 1-to-1 mappings between source and target sentences. Existing alignment methods highlight 1-to-1 links while having difficulty coping with 1-to-many and many-to-many alignments that are common in literary texts. To overcome the weaknesses of current approaches, we propose a novel two-step algorithm for bilingual sentence alignment. The first step finds the optimal paths for 1-to-1 alignments based on the top- k most semantically similar target sentences for each source sentence using the bidirectional encoder representations from transformer-based cross-lingual word embeddings. The second step relies on search paths found in the previous step to recover all valid alignments with more than one sentence on each side of the bilingual text. A comprehensive experiment was conducted on a newly built Chinese–English literary parallel corpus and a large-scale publicly available bilingual corpus of the Bible to compare the performance of Bertalign with five baseline systems: Gale-Church, Hunalign, Bleualign, Bleurtalign, and Vecalign. The results show that Bertalign achieves the highest accuracy in terms of F 1 score on the two evaluation datasets than previous methods. [ABSTRACT FROM AUTHOR]

The availability of large digital archives of historical newspaper content has transformed the historical sciences. However, the scale of these archives can limit the direct application of advanced text processing methods. Even if it is computationally feasible to apply sophisticated language processing to an entire digital archive, if the material of interest is a small fraction of the archive, the results are unlikely to be useful. Methods for generating smaller specialized corpora from large archives are required to solve this problem. This article presents such a method for historical newspaper archives digitized using the METS/ALTO XML standard (Veridian Software, n.d.). The method is an 'iterative bootstrapping' approach in which candidate corpora are evaluated using text mining techniques, items are manually labelled, and Naïve Bayes text classifiers are trained and applied in order to produce new candidate corpora. The method is illustrated by a case study that investigates philosophical content, broadly construed, in pre-1900 English-language New Zealand newspapers. Extensive code is provided in Supplementary Materials. [ABSTRACT FROM AUTHOR]

The aim of this study was to verify the possibility of Sor Juana Inés de la Cruz authoring the anonymous part of the baroque play La Segunda Celestina , commissioned to Agustín de Salazar, and left unfinished after his death. This is a first systematic stylometric study on this problem and a baroque hispanoamerican text. In our study, we faced building a balanced corpus from few available resources, and took extensive evaluation measures to deal with unclear stylometric signals. We use a variety of established attribution and verification methods, and introduce a novel evaluation procedure of examining historic texts with scarce corpora. The results support Sor Juana's authorship, and unravel new connections between her and other authors of the time, showing, still undermined, powerful impact of her works on the epoch. The solutions adopted in solving methodological problems of such a complex task show how stylometry can overcome similar challenges. [ABSTRACT FROM AUTHOR]

We present the result of a corpus study on the difference between quelques 'a few' and plusieurs 'several'. On this basis, we propose a categorization of the nouns significantly attracted by quelques and argue for an understanding of the distinction in topological terms (Grimm, 2012a , 2012b ; Wągiel, 2018 , 2019). A series of observations, focusing successively on the aggregate nouns (pomme de terre 'potato'), a sub-class of 'fence' nouns (gribouillis 'scrawl') and the mass plurals (victuailles 'victuals') leads us to argue that quelques Npl 'a few Npl' is a 'clustered' plural, which is true of a (more or less) cohesive set of connected entities, while plusieurs 'several' quantifies over sets of maximally strongly self-connected (mssc) entities. We will show that this principle can also be generalized to the temporal domain. We shall see that this distinction between the two determiners has numerous consequences on atomicity, the mass-count distinction, the possibility of counting individuals, and especially, on the existence of an individuation scale in the nominal domain. [ABSTRACT FROM AUTHOR]

Motivation: Relation extraction (RE) is a crucial process to deal with the amount of text published daily, e.g. to find missing associations in a database. RE is a text mining task for which the state-of-the-art approaches use bidirectional encoders, namely, BERT. However, state-of-the-art performance may be limited by the lack of efficient external knowledge injection approaches, with a larger impact in the biomedical area given the widespread usage and high quality of biomedical ontologies. This knowledge can propel these systems forward by aiding them in predicting more explainable biomedical associations. With this in mind, we developed K-RET, a novel, knowledgeable biomedical RE system that, for the first time, injects knowledge by handling different types of associations, multiple sources and where to apply it, and multi-token entities. Results: We tested K-RET on three independent and open-access corpora (DDI, BC5CDR, and PGR) using four biomedical ontologies handling different entities. K-RET improved state-of-the-art results by 2.68% on average, with the DDI Corpus yielding the most significant boost in performance, from 79.30% to 87.19% in F-measure, representing a P-value of 2.91 × 10 − 12 . Availability and implementation: https://github.com/lasigeBioTM/K-RET. [ABSTRACT FROM AUTHOR]

This paper investigates the phenomenon of greeting in English, which can be surprisingly challenging for speakers of other languages, such as Chinese. By 'greeting' we mean the seemingly 'simple' act of choosing conventionalized expressions at the opening of an encounter. Following pilot interviews with Chinese learners of English who reported puzzlement concerning greeting in English, we pursue a two-fold approach to explore conventions of greeting in English and Chinese. First, we use corpora to investigate pragmatic differences and similarities between conventionalized uses of English and Chinese comparable Greet expressions, examining them separately and then conducting a contrastive analysis. This step helps us capture the contextual spread of Greet expressions in English and Chinese. Second, we elicit production data from speakers of English and Chinese to investigate their behaviour in the broader opening phase of an interaction across various contexts. The results of the study help us understand in a differentiated way the puzzlement that certain groups of learners of English feel when it comes to greeting. [ABSTRACT FROM AUTHOR]

This article introduces the 'Environmental Scan' as answer to the question of hidden biases in digital heritage collections. Its substantive focus is digitized nineteenth-century British provincial newspapers, and in particular the JISC corpus, a popular, publicly-funded resource for scholars. While multiple papers have meticulously investigated the genesis of such newspaper collections, in the process highlighting the often unacknowledged politics of collection, preservation and dissemination via microfilm and now digitization, our aim is to explore questions of representativeness and bias in new ways by enriching computational analysis of digital corpora with the historical insights that can be derived from a contemporaneous reference source: namely, the Victorian newspaper press directories. [ABSTRACT FROM AUTHOR]

Given the growing expansion in the development and use of computational methods in humanities research, it is necessary to propose methodologies that properly explore the questions posed by different disciplines, considering the locality of both data and the process behind its generation. In the present work, we explore the problem of automatically identifying the main topics in collections of Nahua discourses known as huehuetlahtollis. Each document in the collections is introduced through an extended title, and it is a natural question if enhancing the role of title terms during the unsupervised learning process could enrich results. Aiming at explainability, we consider a model based on nonnegative matrix factorizations (NMF). An overview of the historical process behind the composition of the explored corpora suggests that titles reflect the point of view of the collection's compiler in manners that justify viewing the paratext as a supplementary source on the material. Therefore, we propose a bi-objective NMF scheme that appropriately reflects the a priori knowledge on the corpus, linking and combining the information of titles and content to improve the accuracy in identifying topic groups and relevant terms within a corpus. By comparing three different schemes against the labels assigned by an expert, we show that our model better reflects the nature of data, translating into higher accuracy. Finally, we present some insights on the studied corpora derived from our analysis of identified relevant terms. [ABSTRACT FROM AUTHOR]

A distant-reading task in literary corpus analysis is to group stylometrically similar texts. Since there are many ways to define writing style, the result not only depends on the clustering method but even more so on the measure of similarity. With authorship attribution, the predominant application of stylometry, as its benchmark much research has addressed the utility of methods for measuring similarity. We use a corpus of German-language novellas to demonstrate that one may be interested in very different meaningful groups of texts simultaneously, and that these can be recovered from stylometric clustering if the measure is chosen accordingly. As can be expected, different measures do better at recovering groups associated with, for instance, subgenre, author gender, or narrative perspective. As a consequence, it is suggested that corpus analyses should not be based on what is currently considered the most refined measure of stylometric similarity, but rather break down the decisions that yield a specific measure and provide substantively justified arguments for them. [ABSTRACT FROM AUTHOR]

Introduction Patients with a prostatectomy are at high risk of developing erectile dysfunction (ED) that is refractory to phosphodiesterase type 5 inhibitors. The cavernous nerve (CN) is frequently damaged during prostatectomy, causing loss of innervation to the penis. This initiates corpora cavernosal remodeling (apoptosis and fibrosis) and results in ED. Aim To aid in the development of novel ED therapies, the current aim was to obtain a global understanding of how signaling mechanisms alter in the corpora cavernosa with loss of CN innervation that results in ED. Methods Microarray and pathway analysis were performed on the corpora cavernosal tissue of patients with a prostatectomy (n = 3) or Peyronie disease (control, n = 3). Results were compared with an analysis of a Sprague-Dawley rat CN injury model (n = 10). RNA was extracted by TRIzol, DNase treated, and purified by a Qiagen Mini Kit. Microarray was performed with the Human Gene 2.0 ST Array and the RU34 rat array. Differentially expressed genes were identified through several analytic tools (ShinyGO, Ingenuity, WebGestalt) and databases (GO, Reactome). A 2-fold change was used as the threshold for differential expression. Outcomes Pathways that were altered (up- or downregulated) in response to CN injury in the prostatectomy patients and a rat CN injury model were determined. Results Microarray identified 197 differentially expressed protein-coding genes in the corpora cavernosa from the prostatectomy cohort, with 100 genes upregulated and 97 genes downregulated. Altered signaling pathways that were identified that affect tissue morphology included the following: neurologic disease, cell death and survival, tissue and cellular development, skeletal and muscle development and disorders, connective tissue development and function, tissue morphology, embryonic development, growth and proliferation, cell-to-cell signaling, and cell function and maintenance. These human pathways have high similarity to those observed in the CN-injured rat ED model. Clinical Implications Significant penile remodeling continues in patients long after the acute surgical injury to the CN takes place, offering the opportunity for clinical intervention to reverse penile remodeling and improve erectile function. Strengths and Limitations Understanding how signaling pathways change in response to CN injury and how these changes translate to altered morphology of the corpora cavernosa and ensuing ED is critical to identify strategic targets for therapy development. Conclusion Altered signaling in pathways that regulate tissue homeostasis, morphogenesis, and development was identified in penes of patients with a prostatectomy, and competitive forces of apoptosis and proliferation/regeneration were found to compete to establish dominance after CN injury. How these pathways interact to regulate penis tissue homeostasis is a complex process that requires further investigation. [ABSTRACT FROM AUTHOR]

Our article reports on the emerging Corpus of Contemporary Czech Poetry and the possibilities for its use. We describe the genesis of the idea of creating a specific corpus that combines the principles of synchronicity and genre instead of relying on the presence of poetry in the general corpus of contemporary Czech. We also characterize the structure of our corpus, which is designed to cover both of the basic media areas in which contemporary poetry is published and distributed: either in books or through open publishing platforms on the Internet (literary forums). We additionally describe the functionalities of the tools for mining the corpus data, which are designed to easily serve comparative analyses across media (print/web). We suggest how useful quantitative data analysis can be in the first phase of language-oriented literary research; or rather we point out the necessity of combining quantitative and qualitative approaches. Only the researcher's interpretative proficiency can decide on the boundaries of the field under study and the meaning of the elements present in it. In text-centred analyses, language corpora should start to play a similar role as other tools of scientific infrastructure, such as bibliographic databases. [ABSTRACT FROM AUTHOR]

Until now, there has been very little unified analysis of metadiscourse across speech and writing. Drawing on a reflexive metadiscourse model, this article conducts a multidimensional analysis of metadiscourse across 10 spoken and written registers in a corpus of 626 texts. Two metadiscourse dimensions, participants' interaction and discourse presentation, are identified. The more interactive registers are more prominently marked by participants' interaction, and the more informational registers by discourse presentation. Along metadiscourse dimensions, the 10 registers are lumped into 6 clusters: 'discussion broadcasts and public conversations', 'scripted speeches and unscripted speeches', 'general prose and nondiscussion broadcasts', 'press and fiction', 'casual conversations', and 'academic prose'. Metadiscourse markers of both dimensions are frequently used in registers of the first two clusters which are highly interactive and informational, while they rarely occur in registers of the next two clusters which have low interactive or informational focuses. Metadiscourse markers of participants' interaction are pervasive in the highly interactive register (casual conversations), and those of discourse presentation in the highly informational register (academic prose). [ABSTRACT FROM AUTHOR]

We examine the evolution of the form of the first movement in the eighteenth-century concerto from the Baroque ritornello plan to the eighteenth-century Classical concerto by means of a statistical corpus study. Our data yields a more nuanced understanding of several key characteristics of this evolution, characteristics that have been observed by both contemporary and present-day theorists. We demonstrate how the rise in both quantity and thematic quality of the soloist's part enabled the convergence of ritornello practices with sonata-form features. We conclude with analytical case studies of works by C. P. E. Bach and Josef Mysliveček, showing how their formal solutions fit within this evolutionary process. [ABSTRACT FROM AUTHOR]

The study examined contemporary Chinese novels that depicted the social changes in rural and urban areas. We analyzed the texts using several quantitative methods of stylometry (lexical richness, activity, descriptivity, nominality, cluster analysis of the most frequent words) and corpus linguistics (keywords). We focused on the differences (both in style and in content) between contemporary fiction depicting life in Chinese rural and urban areas. The results revealed that rural stories are more dynamic (active), focusing more on the plot with a simpler description and a smaller vocabulary. [ABSTRACT FROM AUTHOR]

This study examines the consistency of medieval abbreviation practices in a parallel corpus consisting of Latin and Middle English copies of a plague treatise attributed to John of Burgundy (JB). Focusing on different versions of the treatise enables us to maximize textual and lexical overlap, comparing differences caused by text type, word type, and language. We examine how the following variables affect the consistency of abbreviating across manuscript witnesses: A language: Latin versus English; B text type: recipes versus running text; C word type: lexical versus function words; and D: the number of characters in a word. Variables A–D are compared using a parallel corpus of automatically aligned rich TEI P5 XML-tagged transcriptions of six manuscript witnesses to the JB treatise. The alignment process is based on computer–human collaboration and custom-built alignment tool which uses sections tagged in the TEI XML file and word division. The results reveal that abbreviation was overwhelmingly more consistent in Latin than in the Middle English and somewhat more consistent in recipes. High token counts of frequent lexical items had a major effect on the results. Word length worked better than division into lexical and function words. [ABSTRACT FROM AUTHOR]

Current approaches to the expansion of semantic lexicons for corpus annotation are somewhat ad hoc in nature and do not generally offer a systematic means of identifying areas for development within one's lexicon. The present paper sets forward a domain based approach to semantic lexicon expansion, targeting UCREL's Semantic Analysis System (USAS). First, an updated version of the lexicon is compared to representative corpora to ascertain areas of underrepresentation in a novel method which we call K-FLUX analysis. Second, an example set of underrepresented types are targeted for development using domain specific corpora. Collectively, the results show that some corpora are more successful than others in supplementing the existing USAS lexicon. The paper discusses the various factors that should be borne in mind when utilising the proposed method before concluding with how findings might inform future developments of the lexicon, and crucially, the semantic system on which it is based. [ABSTRACT FROM AUTHOR]

Introduction: Severe corporeal fibrosis presents significant challenges in penile implant insertion. LISWT studies in rats and humans have suggested its ability to rejuvenate cavernous bodies through various mechanisms and growth factors. Objective: This prompted our evaluation of LISWT's effectiveness in facilitating prosthesis implantation in patients with penile fibrosis, which are typically considered difficult cases. Methods: A 34-year-old male smoker with a history of sickle cell disease, bilateral hip replacements, and splenectomy due to sickle cell crisis sought penile prosthesis implantation. He presented with severe erectile dysfunction and corporeal fibrosis following two ischemic priapism episodes caused by sickle cell disease, which were treated with distal shunts 4 and 1 years prior, respectively (Fig. 1). After obtaining consent, the patient underwent four cycles of LISWT, spaced one month apart. Each cycle consisted of four weekly sessions using the PiezoWave2 device from Richard WOLF with settings of 0.16mj/mm2 energy flux density, 6Hz frequency, and 10mm wave focus penetration depth. In each session, the patient received a total of 6000 shocks, distributed between the perineum, dorsum penis, and the lateral aspect of the penis. Results: A month post-LISWT, the patient's Erection Hardness Score (EHS) improved from 0 to 1 following an intracavernous injection of 20 mcg of alprostadil (Fig. 2). Subsequently, he underwent a malleable penile implant procedure through the penoscrotal approach. Cavernosal dilation was successful up to 10mm using a Hegar dilator, with bilateral corporal measurements of 8cm proximally and 9cm distally. A Tactra malleable penile prosthesis (9.5mm girth and 17cm length) from Boston Scientific was implanted without complications (Fig. 3.A.B) Conclusions: In cases of severe corporeal fibrosis, pre-treatment with LISWT may aid in the dilation of the corpora during penile prosthesis implantation, potentially reducing complications. Randomized studies are warranted to validate this indication Disclosure: No. [ABSTRACT FROM AUTHOR]

Introduction: One of the most difficult challenges in prosthetic urology is the insertion of penile implants into corpora scarred from an episode of priapism. In cases of scarred penile cavernosal bodies, surgery becomes challenging even for experienced surgeons, as it can be very difficult to dilate the corpora. Objective: Usually, the initial insertion of a malleable device is used as a temporary measure, to maintain the penile length and simplify the subsequent insertion of an inflatable one. So our objective is to decrease the number of surgeries from 2 to 1. Methods: In this case, we dilated the corpora cavernosa initially with Metzenbaum scissors thoroughly and carefully. We placed the tip of the scissors at the outer side of each cavernous body (away from the urethra) and advanced it to the tip of the corpus cavernosum. Then, we used the cavernotomes Results: Till now the prostheses are functional. We do believe that in certain cases, with the right choice of the patient, the implant of the IPP after priapism is a viable solution Conclusions: Cavernotomes are a good option for dilating the fibrotic corpora. And it is safe Disclosure: No. [ABSTRACT FROM AUTHOR]

Cavernous nerve (CN) injury causes penile remodeling, including smooth muscle apoptosis and increased collagen, which results in erectile dysfunction (ED), and prevention of this remodeling is critical for novel ED therapy development. We developed 2 peptide amphiphile (PA) hydrogel delivery vehicles for Sonic hedgehog (SHH) protein to the penis and CN, which effectively suppress penile distrophic remodeling (apoptosis and fibrosis), in vivo in a rat CN injury model, and the aim of this study is to determine if SHH PA can be used to regenerate human corpora cavernosal smooth muscle deriving from multiple ED origins. Corpora cavernosal tissue was obtained from prostatectomy, diabetic, hypertension, cardiovascular disease and Peyronie's (control) patients (n = 21). Primary cultures (n = 21) were established, and corpora cavernosal cells were treated with SHH protein, MSA (control), 5E1 SHH inhibitor, and PBS (control). Growth was quantified by counting the number of cells at 3–4 days. Statistics were performed by ANOVA with Scheffe's post hoc test. Concentration of SHH protein for maximal growth was optimized, and a more active SHH protein examined. Cultures were characterized by immunohistochemical analysis with ACTA2, CD31, nNOS and P4HB, and smooth muscle was quantified in comparison to DAPI. Cultures established were >97% smooth muscle. SHH protein increased growth of smooth muscle cells from prostatectomy, diabetic, and Peyronie's patients in a similar manner (49%–51%), and SHH inhibition decreased growth (20%–33%). There was no difference in growth using 25 ug and 10 ug SHH protein, suggesting a threshold concentration of SHH protein above which smooth muscle growth is enhanced. A more active lipid modified SHH peptide further enhanced growth (15%), indicating a more robust growth response. SHH increased growth in smooth muscle cells from hypertension (37%) and cardiovascular disease (32%) patients. SHH protein increased growth under normal and high glucose conditions, suggesting that high glucose conditions that may be present in under controlled diabetic patients would not detract from SHH regenerative capacity. SHH PA would be beneficial to enhance smooth muscle regeneration in patients with ED of multiple etiologies. Understanding how human corpora cavernosal tissue responds to SHH treatment is critical for clinical translation of SHH PA to ED patients. Corpora cavernosal smooth muscle from all ED patients responded to SHH treatment with increased growth. Stupp, SI. Sonic Hedgehog Signaling in Primary Culture of Human Corpora Cavernosal Tissue From Prostatectomy, Diabetic, and Peyronie's Patients. J Sex Med 2022;19:1228–1242. [ABSTRACT FROM AUTHOR]

The commonly used categorical system for conditionals (zero, first, second, and third) has been repeatedly demonstrated to be inadequate because it is unable to account for many conditional types attested in actual usage. ELT coursebooks and pedagogic grammars are criticized for ignoring the evidence and persisting with its use, but the reality appears to be that, from the point of view of syllabus designers and materials writers, the usefulness and practicality that the system offers outweighs any concerns related to its accuracy. This paper attempts to resolve this tension by showing how the existing system can be improved rather than simply abandoned. It proposes a revised categorization system that better reflects the reality of conditional usage and takes into account evidence on how learners' knowledge of conditional forms expands and develops as they progress through proficiency levels, but that nonetheless can be practically employed in multi-level teaching materials and courses. [ABSTRACT FROM AUTHOR]

This article presents the elaboration of a morphosyntactically annotated diachronic corpus of Basque, and the first results obtained in the processing of historical varieties of this language with computational techniques. The corpus size is around one million words, expanding from the 15th to the mid-18th century and encompassing the most significant written production in all historical dialects. Morphosyntactic tagging allows for systematic searches at different levels of complexity; additionally, a rich set of metadata enables searches based on sociohistorical criteria too. This is not only the first tagged corpus of historical Basque but also a means to improve language processing tools by analyzing historical varieties more or less distant from the present-day standard language. Moreover, this project aims to set a model for further works in the historical corpora of Basque and inform similar projects on other languages. [ABSTRACT FROM AUTHOR]

Following the findings of two prior publications this supplement makes use of the General Imposters (GI) method which largely confirms previous results, namely that the Marlowe corpus is stylistically inhomogeneous. The two Tamburlaines match each other in style, but the remaining corpus has hardly any stylistic similarity with them. Instead, there are strong indications of Shakespeare's involvement in nominal Marlowe plays which becomes most obvious in The Jew of Malta. In terms of methodology, GI turns out to be an additional verification system, at its best when the training set consists of the texts of only two authors. [ABSTRACT FROM AUTHOR]

In this article, we argue for the benefits of combining large-scale analyses of visual materials currently pursued within digital humanities with insights from multimodality research, which is an emerging discipline that studies how human communication relies on appropriate combinations of expressive resources. We show that concepts developed within the field of multimodality research provide appropriate metadata schemes for various modes of expression in large corpora and datasets. We illustrate the proposed approach using a common mode of expression, diagrams, and analyse two recent multimodal diagram corpora using statistical and computational methods. Our results suggest that multimodally-motivated metadata schemes can provide a robust foundation for computational analyses of large corpora and datasets. Even if a corpus or dataset is not designed to support full-blown analyses of multimodal communication, our results imply that multimodality theory can still be used to impose tighter analytical control over a variety of visual materials. [ABSTRACT FROM AUTHOR]

This article discusses Wouter J. Hanegraaff's book on "Hermetic spirituality" and its implications for understanding spiritual practices reflected in the Hermetic corpus and related texts. The book explores the historical imagination and the use of altered states of consciousness in late antiquity, suggesting that psychoactive substances may have been used in Hermetic rituals. The article highlights the structure of the book, which includes chapters on topics such as healing the soul, the path of reverence, and the nature of language. While the book raises some speculative and anachronistic issues, it offers valuable insights into Hermetic spirituality and visionary practices from late antiquity. [Extracted from the article]

The article focuses on the analysis of the user as an aesthetic category and proposes a methodology for evaluating user response within a framework that combines theoretical background from different areas, the theory of aesthetic response, psycholinguistics, appraisal theory, dialogism, and affective stylistics, with the application of digital tools for corpus linguistics and sentiment analysis. Four user types were derived from the corpus linguistics analysis referred to as immersed, distant, sceptical, and enthusiastic users. Each type may encompass a certain degree of intentionality and convey an attitude, implying features such as commitment and honesty, objectivity and engagement with the audience, critical reflection and circumspection, openness to technological novelty, and enjoyment. This assumes that the users involved in usability testing are not neutral or undifferentiated informational entities placed in an experimental context but individuals that respond to the same stimuli and express themselves differently in light of psycholinguistic factors and rules of social interaction. On the other hand, the results of sentiment analysis showed that an experiential analysis, centred not only on the artefact but also on the response and the experience it generates, may enable understanding the user as involved in a hermeneutic process of interpretation during his/her interaction with the studied artefact. Given the small scale of the analysed data, the study does not intend to provide evidence for general or definitive statements but formulates and illustrates a set of interpretative hypotheses and methodological directions for further enquiry aiming at developing an 'aesthetics' of user response. [ABSTRACT FROM AUTHOR]

This article aims to analyse aboutness in a corpus of videos posted by Brazilian female transsexual influencers. The analysis is based on Corpus Linguistics, machine learning techniques, and automated lexical mapping techniques, especially Topic Modelling. This technique served as a starting point for establishing four main topics: Relationship and Social Events, Gender, Beauty, and Transition. These topics had their statistically relevant lexis qualitatively analysed by concordance. This study used tools written in R and Python programming languages, made freely available to the community. The results show that the topics are qualitatively and quantitatively consistent, and the approach adopted was fruitful for text analysis. [ABSTRACT FROM AUTHOR]

Motivation Information about bacteria biotopes (BB) is important for fundamental research and applications in microbiology. BB task at BioNLP-OST 2019 focuses on the extraction of locations and phenotypes of microorganisms from PubMed abstracts and full-text excerpts. The subtask BB-rel+ner aims to recognize relevant entities and extract interrelationships about BBs. The corresponding corpus owns some distinctive features (e.g. nested entities) which are challenging to deal with. Therefore, previous methods achieved low performance on entity and relation extraction and limited the mutual effect between named entity recognition and relation extraction. There is still much room for improvement. Results We propose a span-based model to extract entities and relations jointly from biomedical text regarding the BBs. For alleviating the problem of annotated data deficiency in domain-specific task, we employ a BERT (Bidirectional Encoder Representations from Transformers) model pre-trained on the domain-specific corpus to encode sentences. Our model considers all spans in a sentence as potential entity mentions and computes relation scores between the most confident entity spans based on representations of spans and contexts between spans. Experiments on the BB-rel+ner 2019 corpus demonstrate that our model achieves significantly better performance than the state-of-the-art method, with a reduction of 21.6% slot error rate (SER) for extracting relations. Our model is also effective in recognizing nested entities. Furthermore, the model can be applied to the CHEMPROT corpus for joint extraction of chemical–protein entities and relations, achieving state-of-the-art performance. Availability and implementation Our source code is available at https://github.com/zmmzGitHub/SpanMB%5fBERT. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

In the last decades, a great amount of work has been done in predictive modeling of issues related to human and environmental health. Resolution of issues related to healthcare is made possible by the existence of several biomedical vocabularies and standards, which play a crucial role in understanding the health information, together with a large amount of health-related data. However, despite a large number of available resources and work done in the health and environmental domains, there is a lack of semantic resources that can be utilized in the food and nutrition domain, as well as their interconnections. For this purpose, in a European Food Safety Authority–funded project CAFETERIA, we have developed the first annotated corpus of 500 scientific abstracts that consists of 6407 annotated food entities with regard to Hansard taxonomy, 4299 for FoodOn and 3623 for SNOMED-CT. The CafeteriaSA corpus will enable the further development of natural language processing methods for food information extraction from textual data that will allow extracting food information from scientific textual data. Database URL : https://zenodo.org/record/6683798#.Y49wIezMJJF [ABSTRACT FROM AUTHOR]

TopEx is a natural language processing application developed to facilitate the exploration of topics and key words in a set of texts through a user interface that requires no programming or natural language processing knowledge, thus enhancing the ability of nontechnical researchers to explore and analyze textual data. The underlying algorithm groups semantically similar sentences together followed by a topic analysis on each group to identify the key topics discussed in a collection of texts. Implementation is achieved via a Python library back end and a web application front end built with React and D3.js for visualizations. TopEx has been successfully used to identify themes, topics and key words in a variety of corpora, including Coronavirus disease 2019 (COVID-19) discharge summaries and tweets. Feedback from the BioCreative VII Challenge Track 4 concludes that TopEx is a useful tool for text exploration for a variety of users and tasks. Databse URL http://topex.cctr.vcu.edu [ABSTRACT FROM AUTHOR]