La recepción del léxico de la taxonomía botánica de Linneo en los diccionarios del español / The reception of the lexicon from linnaeus’s botanical taxonomy in spanish language dictionaries

El objetivo de este estudio es describir y analizar la recepción del léxico de la taxonomía botánica de Linneo en los diccionarios de la lengua española de los siglos XVIII y XIX. Para ello, en primer lugar, se ha partido de los términos relativos a clases, órdenes y géneros linneanos presentes en la obra Parte práctica de botánica del caballero Carlos Linneo (1784-1788) de Antoni Palau y Verdera, el asimilador de la obra del botánico sueco al español. En segundo lugar, se han cotejado estos términos en los diccionarios generales del español de los siglos XVIII y XIX para averiguar cuántos de ellos se registraron, cuánto tiempo perduraron en los diccionarios y en cuáles se atestigua su primera documentación lexicográfica. Los resultados obtenidos demuestran que el Diccionario Nacional (1846-1847) de Ramón Joaquín Domínguez fue el primer diccionario en español en incorporar las palabras de la clasificación botánica de Linneo y que, en general, dichas voces se mantuvieron, en mayor o menor proporción, en diferentes diccionarios hasta el Diccionario general y técnico hispano-americano (1918) de Manuel Rodríguez-Navas y Carrasco. La fuente de consulta de Domínguez no fue la obra de Palau (1784-1788) sino el Dictionnaire national (1843) de Louis-Nicolas Bescherelle, diccionario francés del que copia literalmente el lemario y las definiciones. El diccionario de la Real Academia Española apenas se hizo eco de este léxico.(AU)

The aim of this study is to describe and analyze the reception of the lexicon from Linnaeus’s botanical taxonomy in Spanish language dictionaries of the 18th and 19th centuries. Firstly, terms related to linnaean classes, orders, and genera were collected from Parte práctica de botánica del caballero Carlos Linneo (1784-1788), by Antonio Palau y Verdera, the promoter of the Swedish botanist’s work into Spanish. Secondly, these terms were analyzed in general dictionaries of Spanish of 18th and 19th centuries to determine the number of terms registered, time of prevalence in dictionaries, and first lexicographical insertion. Results show that the Diccionario Nacional (1846-1847) by Ramón Joaquín Domínguez was the first dictionary that introduced the Linnaeus’s botanical taxonomy and that terms proposed by Domínguez were generally used in successive dictionaries, including the Diccionario general y técnico hispano-americano (1918), by Manuel Rodríguez-Navas y Carrasco . Domínguez’s source documentation was not Palau y Verdera’s work, but the Dictionnaire national (1843) by Louis-Nicolas Bescherelle, a French dictionary from which Domínguez literally copies lemmas and definitions. The Royal Spanish Academy’s Spanish Dictionary barely registered this lexicon.(AU)

Linguistic effects on news headline success: Evidence from thousands of online field experiments (Registered Report Protocol).

What makes written text appealing? In this registered report protocol, we propose to study the linguistic characteristics of news headline success using a large-scale dataset of field experiments (A/B tests) conducted on the popular website Upworthy comparing multiple headline variants for the same news articles. This unique setup allows us to control for factors that can have crucial confounding effects on headline success. Based on prior literature and a pilot partition of the data, we formulate hypotheses about the linguistic features that are associated with statistically superior headlines. We will test our hypotheses on a much larger partition of the data that will become available after the publication of this registered report protocol. Our results will contribute to resolving competing hypotheses about the linguistic features that affect the success of text and will provide avenues for research into the psychological mechanisms that are activated by those features.

Global Harmonization of Morphological Definitions in Hidradenitis Suppurativa for a Proposed Glossary.

Importance: Standard morphological terminology and definitions are vital for identification of lesion types in the clinical trial setting and communication about the condition. For hidradenitis suppurativa (HS), morphological definitions have been proposed by different groups, representing various regions of the world, but no international consensus has been reached regarding such definitions. A lack of globally harmonized terminology and definitions may contribute to poor-quality data collection in clinical trials as well as poor communication among clinicians, investigators, and patients. Objective: To establish and validate consensus definitions for typical morphological findings for HS lesions. Methods: This study was conducted from August 2019 to August 2020. A Delphi study technique was used to assess agreement and then resolve disagreement on HS terminology among international experts. After an initial preparation phase, the process consisted of 3 rounds. In each round, participants reviewed preliminary definitions and rated them as "keep, with no changes," "keep, with changes," or "remove." Eight HS primary lesions, including papule, pustule, nodule, plaque, ulcer, abscess, comedo, and tunnel, were selected because they are most frequently used in HS clinician-reported outcome measures. The initial definitions were based on extant literature, and modifications were made between rounds based on qualitative thematic analysis of open-ended responses or discussion. Consensus was defined as greater than 70% to accept a definition. Consensus stability across rounds was defined as less than 15% change in agreement. Reliability was evaluated using the Gwet agreement coefficient. Validation was based on assessment of face validity and stability across rounds. Results: A total of 31 experts participated. All 8 HS primary lesion definitions achieved greater than 70% consensus by Delphi round 3. Stability was achieved for papule, pustule, and abscess. The Gwet agreement coefficient increased from 0.49 (95% CI, 0.26-0.71) in round 1 to 0.78 (95% CI, 0.64-0.92) in round 3. Face validity was supported by expert endorsement to keep terms in survey responses. Previously unmeasured variation among clinicians' definition of tunnels was identified, and consensus was achieved. Conclusions and Relevance: An international group of experts agreed on definitions for morphological features of HS lesions frequently included in HS clinical trials. These international consensus terms and definitions are needed to support consistency of lesion identification and quantification in clinical trials.

Locating Nodal Moments Within Psychotherapy Sessions: A Mixed-Methods Study Using a Computerized Measure and Therapist Comments.

A computerized linguistic measure, the Weighted Referential Activity Dictionary (WRAD), was applied to locate nodal turns of speech in psychotherapy, defined here as significant moments of patient emotional communication that are likely to reveal important themes. Two published demonstration sessions conducted by a senior clinician, who made extensive comments on this material, were utilized to illustrate the method. The WRAD, defined in the context of referential process theory, was developed and has been validated as assessing the vividness and immediacy of language. Segments of patient speech (turns of speech) were classified based on WRAD level and sufficient length. The themes of the therapist's clinical comments concerning high WRAD segments were coded using a category system developed for this study, and were compared to themes of comments for the remaining segments. Results showed a significant difference in the therapist's comments between the two groups of segments using Fisher's exact test. In particular, the therapist's comments on the nodal turns showed more focus on the emotional effects of the patient's utterances on him, as well as identification of unexpected disclosures in these utterances. The implications and limitations of this method are discussed.

Co-developing a common glossary with stakeholders for engagement on new genetic approaches for malaria control in a local African setting.

Stakeholder engagement is an essential pillar for the development of innovative public health interventions, including genetic approaches for malaria vector control. Scientific terminologies are mainly lacking in local languages, yet when research activities involve international partnership, the question of technical jargon and its translation is crucial for effective and meaningful communication with stakeholders. Target Malaria, a not-for-profit research consortium developing innovative genetic approaches to malaria vector control, carried out a linguistic exercise in Mali, Burkina Faso and Uganda to establish the appropriate translation of its key terminology to local languages of sites where the teams operate. While reviewing the literature, there was no commonly agreed approach to establish such glossary of technical terms in local languages of the field sites where Target Malaria operates. Because of its commitment to the value of co-development, Target Malaria decided to apply this principle for the linguistic work and to take the opportunity of this process to empower communities to take part in the dialogue on innovative vector control. The project worked with linguists from other institutions (whether public research ones or private language centre) who developed a first potential glossary in the local language after better understanding the project scientific approach. This initial glossary was then tested during focus groups with community members, which significantly improved the proposed translations by making them more appropriate to the local context and cultural understanding. The stepwise process revealed the complexity and importance of elaborating a common language with communities as well as the imbrication of language with cultural aspects. This exercise demonstrated the strength of a co-development approach with communities and language experts as a way to develop knowledge together and to tailor communication to the audience even in the language used.

Development of WRRL: A New Computerized Measure of the Reflecting/Reorganizing Function.

Reflecting/Reorganizing (R/R) is one of the three functions described by Bucci (Overview of the referential process: the operation of language within and between people, 2021a) as part of the referential process. The Weighted Referential Activity Dictionary (WRAD) was previously developed to model the Symbolizing function of the referential process. This paper presents the development of the Weighted Reflecting Reorganizing List (WRRL) as a model of the R/R function. The basic premise of this approach is that by rating segments of text rather than individual words, and using a word by word weighting procedure designed for this purpose, it is possible to identify the nature of the language style that is connected with particular degrees of involvement in the psychological process being modeled. Starting with a brief description of the R/R function, an iterative process was applied that resulted in a clear scoring manual for the R/R function. The method of developing the dictionary is described, a study providing validation for the measure is presented, and the nature of the language style used to express the R/R function is discussed. As was described for the WRAD, the language style of the WRRL was found to involve use of particular function words, applicable across a wide range of contents.

Assessing Key Linguistic Dimensions of Ruptures in the Therapeutic Alliance.

Over the past two decades, therapeutic alliance research has increasingly focused on understanding the process by which the alliance is ruptured and repaired. This paper is the first to explore how alliance rupture segments from psychotherapy sessions differ from non-rupture segments on key dimensions of the referential process. A sample of 27 psychotherapy sessions were scored using a measure designed to identify rupture from non-rupture segments. These segments were then scored for key linguistic dimensions of the referential process. During ruptures patients manifested a referential process marked by a decrease in emotional engagement, an increase in a measure of distancing, and an increase in negation as compared to non-rupture segments. Therapists show similar patterns but, in addition, manifest a language pattern that suggests that during ruptures, therapists are attempting to make sense of, and self-disclose, aspects of their inner experience. Implications for research and clinical work are explored.

El diccionario de especialidad como instrumento de comunicación científica: el ejemplo de la electricidad (1880-1910) / The specialty dictionary as an instrument of scientific communication: the example of electricity (1880-1910)

En este artículo se ofrece un panorama de los diccionarios de electricidad publi-cados en Europa entre 1880 y 1910, etapa en que esta disciplina y sus aplicaciones técnicas e industriales experimentaron un importante desarrollo. En particular, se atiende a los repertorios que circularon en España, tanto en su lengua original como sobre todo traducidos, pues su autoría correspondió mayoritariamente a ingenieros franceses, ingleses y alemanes: Jacquez (1883), Dumont (1889), Houston (1889), Lefèvre (1891), O’Conor Sloane (1892), Hospitalier (1900), Deinhardt y Schlomann (1908), etc. Asimismo, se presta atención a otros diccionarios técnicos de autor español, como los de Clairac (1877-1908) o Camps y Armet (1888), en cuyas páginas está especialmente presente el tecnicismo eléctrico. El acercamiento a este conjunto de diccionarios pone manifiesto el papel que correspondió a los distintos repertorios de espe-cialidad en el proceso de comunicación y divulgación científica de la época, y permite señalar la existencia de discursos complementarios, reflejo de variadas situaciones comunicativas (la que se da en el seno de la comunidad científica, en el mundo técnico e industrial, entre la comunidad técnica y científica y el lector profano...), que hablan asimismo de cómo se resuelve en ellos la tensión entre lengua y ciencia (AU)

Developing and validating the self-transcendent emotion dictionary for text analysis.

Recent years have seen a growing amount of research effort directed toward what positive media psychologists refer to as self-transcendent emotions, such as awe, admiration, elevation, gratitude, inspiration, and hope. While these emotions are invaluable to promote greater human connectedness, prosociality, and human flourishing, researchers are constrained in terms of analyzing self-transcendent emotions as expressed in spoken and written languages. Drawing upon the word-counting approach of the text analysis paradigm, this project aimed at constructing a dictionary tool-Self-Transcendent Emotion Dictionary (STED)-which can be uploaded into mainstream, text analytic software (e.g., LIWC) to identify and analyze self-transcendent emotions in large corpora. This dictionary tool was then refined and validated via three studies, where individual words were first rated with regard to their fitness into the proposed construct (Step 1), and then used to analyze essays written to reflect the corresponding construct (Step 2). Finally, the refined dictionary was applied to examine words used in nearly 4,000 human-coded New York Times articles (Step 3). Results indicated that the final dictionary, consisting of 351 lexicons and phrases, exhibits acceptable face and construct validity, and possesses a reasonable level of external validity and applicability. Despite its shortcoming in accounting for the rhetorical techniques ingrained in natural human language, the STED could be instrumental for social scientific inquiry of positive emotions in textual narratives.

Middle-Level Features for the Explanation of Classification Systems by Sparse Dictionary Methods.

Machine learning (ML) systems are affected by a pervasive lack of transparency. The eXplainable Artificial Intelligence (XAI) research area addresses this problem and the related issue of explaining the behavior of ML systems in terms that are understandable to human beings. In many explanation of XAI approaches, the output of ML systems are explained in terms of low-level features of their inputs. However, these approaches leave a substantive explanatory burden with human users, insofar as the latter are required to map low-level properties into more salient and readily understandable parts of the input. To alleviate this cognitive burden, an alternative model-agnostic framework is proposed here. This framework is instantiated to address explanation problems in the context of ML image classification systems, without relying on pixel relevance maps and other low-level features of the input. More specifically, one obtains sets of middle-level properties of classification inputs that are perceptually salient by applying sparse dictionary learning techniques. These middle-level properties are used as building blocks for explanations of image classifications. The achieved explanations are parsimonious, for their reliance on a limited set of middle-level image properties. And they can be contrastive, because the set of middle-level image properties can be used to explain why the system advanced the proposed classification over other antagonist classifications. In view of its model-agnostic character, the proposed framework is adaptable to a variety of other ML systems and explanation problems.

Exploring the effect of lexical inferencing and dictionary consultation on undergraduate EFL students' vocabulary acquisition.

This study compares how lexical inferencing and dictionary consultation affect L2 vocabulary acquisition. Sixty-one L1 Arabic undergraduates majoring in English language read target words in semi-authentic English reading materials and were either asked to guess their meaning or look it up in a dictionary. A pre- and delayed post-test measured participants' knowledge of target words and overall vocabulary size. The results show a significant and comparable learning effect for both vocabulary learning strategies (VLS), with a higher pre-test vocabulary size related to a larger learning effect for both VLS. In addition, the better participants were at guessing correctly, the better they learned words through inferencing. The results suggest that both VLS are equally effective for our learner group and that learners' overall vocabulary size influences the amount of learning that occurs when using these VLS.

A dictionary-based graph-cut algorithm for MRI reconstruction.

PURPOSE: Compressive sensing (CS)-based image reconstruction methods have proposed random undersampling schemes that produce incoherent, noise-like aliasing artifacts, which are easier to remove. The denoising process is critically assisted by imposing sparsity-enforcing priors. Sparsity is known to be induced if the prior is in the form of the Lp (0 ≤ p ≤ 1) norm. CS methods generally use a convex relaxation of these priors such as the L1 norm, which may not exploit the full power of CS. An efficient, discrete optimization formulation is proposed, which works not only on arbitrary Lp -norm priors as some non-convex CS methods do, but also on highly non-convex truncated penalty functions, resulting in a specific type of edge-preserving prior. These advanced features make the minimization problem highly non-convex, and thus call for more sophisticated minimization routines. THEORY AND METHODS: The work combines edge-preserving priors with random undersampling, and solves the resulting optimization using a set of discrete optimization methods called graph cuts. The resulting optimization problem is solved by applying graph cuts iteratively within a dictionary, defined here as an appropriately constructed set of vectors relevant to brain MRI data used here. RESULTS: Experimental results with in vivo data are presented. CONCLUSION: The proposed algorithm produces better results than regularized SENSE or standard CS for reconstruction of in vivo data.

AANEM - IFCN Glossary of Terms in Neuromuscular Electrodiagnostic Medicine and Ultrasound.

Modern neuromuscular electrodiagnosis (EDX) and neuromuscular ultrasound (NMUS) require a universal language for effective communication in clinical practice and research and, in particular, for teaching young colleagues. Therefore, the AANEM and the IFCN have decided to publish a joint glossary as they feel the need for an updated terminology to support educational activities in neuromuscular EDX and NMUS in all parts of the world. In addition NMUS has been rapidly progressing over the last years and is now widely used in the diagnosis of disorders of nerve and muscle in conjunction with EDX. This glossary has been developed by experts in the field of neuromuscular EDX and NMUS on behalf of the AANEM and the IFCN and has been agreed upon by electronic communication between January and November 2019. It is based on the glossaries of the AANEM from 2015 and of the IFCN from 1999. The EDX and NMUS terms and the explanatory illustrations have been updated and supplemented where necessary. The result is a comprehensive glossary of terms covering all fields of neuromuscular EDX and NMUS. It serves as a standard reference for clinical practice, education and research worldwide. HIGHLIGHTS: Optimal terminology in neuromuscular electrodiagnosis and ultrasound has been revisited. A team of international experts have revised and expanded a standardized glossary. This list of terms serves as standard reference for clinical practice, education and research.

COVID-19 Glosario sobre brotes y epidemias: un recurso para periodistas y comunicadores / COVID-19 Glossary on outbreaks and epidemics: a resource for journalists and communicators

Glosario útil para periodistas y comunicadores sobre términos utilizados durante brotes y epidemias.

Pronouns and Advocacy in Medicine.

In September 2019, a prominent dictionary recognized they as a proper pronoun for nonbinary individuals. This change can be seen as a source of newfound legitimacy for students and trainees self-advocating for nonbinary pronoun recognition in health care practice and training. This article considers one student's experience after coming out as nonbinary and voicing that their pronouns are they/them.

Glosario de IS4H / IS4H Glossary

Este glosario contiene los conceptos básicos para una evaluación eficaz del Modelo de madurez de los IS4H

Development of LactaPedia: A lactation glossary for science and medicine.

During the last decade, there have been several publications highlighting the need for consistent terminology in breastfeeding research. Standard terms and definitions are essential for the comparison and interpretation of scientific studies that, in turn, support evidence-based education, consistency of health care, and breastfeeding policy. Inconsistent advice is commonly reported by mothers to contribute to early weaning. A standard language is the fundamental starting point required for the provision of consistent advice. LactaPedia (www.lactapedia.com) is a comprehensive lactation glossary of over 500 terms and definitions created during the development of LactaMap (www.lactamap.com), an online lactation care support system. This paper describes the development of LactaPedia, a website that is accessible free of charge to anyone with access to the Internet. Multiple methodological frameworks were incorporated in LactaPedia's development in order to meet the needs of a glossary to support both consistent health care and scientific research. The resulting LactaPedia methodology is a six-stage process that was developed inductively and includes framework to guide vetting and extension of its content using public feedback via discussion forums. The discussion forums support ongoing usability and refinement of the glossary. The development of LactaPedia provides a fundamental first step towards improving breastfeeding outcomes that are currently well below World Health Organisation recommendations globally.

Current approaches to identify sections within clinical narratives from electronic health records: a systematic review.

BACKGROUND: The identification of sections in narrative content of Electronic Health Records (EHR) has demonstrated to improve the performance of clinical extraction tasks; however, there is not yet a shared understanding of the concept and its existing methods. The objective is to report the results of a systematic review concerning approaches aimed at identifying sections in narrative content of EHR, using both automatic or semi-automatic methods. METHODS: This review includes articles from the databases: SCOPUS, Web of Science and PubMed (from January 1994 to September 2018). The selection of studies was done using predefined eligibility criteria and applying the PRISMA recommendations. Search criteria were elaborated by using an iterative and collaborative keyword enrichment. RESULTS: Following the eligibility criteria, 39 studies were selected for analysis. The section identification approaches proposed by these studies vary greatly depending on the kind of narrative, the type of section, and the application. We observed that 57% of them proposed formal methods for identifying sections and 43% adapted a previously created method. Seventy-eight percent were intended for English texts and 41% for discharge summaries. Studies that are able to identify explicit (with headings) and implicit sections correspond to 46%. Regarding the level of granularity, 54% of the studies are able to identify sections, but not subsections. From the technical point of view, the methods can be classified into rule-based methods (59%), machine learning methods (22%) and a combination of both (19%). Hybrid methods showed better results than those relying on pure machine learning approaches, but lower than rule-based methods; however, their scope was more ambitious than the latter ones. Despite all the promising performance results, very few studies reported tests under a formal setup. Almost all the studies relied on custom dictionaries; however, they used them in conjunction with a controlled terminology, most commonly the UMLSⓇ metathesaurus. CONCLUSIONS: Identification of sections in EHR narratives is gaining popularity for improving clinical extraction projects. This study enabled the community working on clinical NLP to gain a formal analysis of this task, including the most successful ways to perform it.