A Resource for Detecting Misspellings and Denoising Medical Text Data

In this paper we propose a method for collecting a dictionary to deal with noisy medical text documents. The quality of such Italian Emergency Room Reports is so poor that in most cases these can be hardly automatically elaborated; this also holds for other languages (e.g., English), with the notable difference that no Italian dictionary has been proposed to deal with this jargon. In this work we introduce and evaluate a resource designed to fill this gap.In questo lavoro illustriamo un metodo per la costruzione di un dizionario dedicato all’elaborazione di documenti medici, la porzione delle cartelle cliniche annotata nei reparti di pronto soccorso. Questo tipo di documenti è così rumoroso che in genere le cartelle cliniche difficilmente posono essere direttamente elaborate in maniera automatica. Pur essendo il problema di ripulire questo tipo di documenti un problema rilevante e diffuso, non esisteva un dizionario completo per trattare questo linguaggio settoriale. In questo lavoro proponiamo e valutiamo una risorsa finalizzata a condurre questo tipo di elaborazione sulle cartelle cliniche

Genuinely Ferroelectric Sub-1-Volt-Switchable Nanodomains in HfₓZr₍₁₋ₓ₎ O₂ Ultrathin Capacitors

The new class of fully silicon-compatible hafnia-based ferroelectrics with high switchable polarization and good endurance and thickness scalability shows a strong promise for new generations of logic and memory devices. Among other factors, their competitiveness depends on the power efficiency that requires reliable low-voltage operation. Here, we show genuine ferroelectric switching in HfₓZr₍₁₋ₓ₎ O₂ (HZO) layers in the application-relevant capacitor geometry, for driving signals as low as 800 mV and coercive voltage below 500 mV. Enhanced piezoresponse force microscopy with sub-picometer sensitivity allowed for probing individual polarization domains under the top electrode and performing a detailed analysis of hysteretic switching. The authentic local piezoelectric loops and domain wall movement under bias attest to the true ferroelectric nature of the detected nanodomains. The systematic analysis of local piezoresponse loop arrays reveals a totally unexpected thickness dependence of the coercive fields in HZO capacitors. The thickness decrease from 10 to 7 nm is associated with a remarkably strong decrease of the coercive field, with about 50% of the capacitor area switched at coercive voltages ≤0.5 V. Our explanation consistent with the experimental data involves a change of mechanism of nuclei-assisted switching when the thickness decreases below 10 nm. The practical implication of this effect is a robust ferroelectric switching under the millivolt-range driving signal, which is not expected for the standard coercive voltage scaling law. These results demonstrate a strong potential for further aggressive thickness reduction of HZO layers for low-power electronics

Conceptual Abstractness: from Nouns to Verbs

Investigating lexical access, representation and processing involves dealing with conceptual abstractness: abstract concepts are known to be more quickly and easily delivered in human communications than abstract meanings (Binder et al., 2005). Although these aspects have long been left unexplored, they are relevant: abstract terms are widespread in ordinary language, as they contribute to the realisation of various sorts of figurative language (metaphors, metonymies, hyperboles, etc.). Abstractness is therefore an issue for computational linguistics, as well. In this paper we illustrate how to characterise verbs with abstractness information. We provide an experimental evaluation of the presented approach on the largest existing corpus annotated with abstraction scores: our results exhibit good correlation with human ratings, and point out some open issues that will be addressed in future work.In questo lavoro presentiamo il tema dell’astrattezza come una caratteristica diffusa del linguaggio, e un nodo cruciale nell’elaborazione automatica del linguaggio. In particolare illustriamo un metodo per la stima dell’astrattezza che caratterizza i verbi a partire dalla composizione dei punteggi di astrattezza degli argomenti dei verbi utilizzando la risorsa Abs-COVER

A computational analysis of transcribed speech of people living with dementia: The Anchise 2022 Corpus

Introduction: Automatic linguistic analysis can provide cost-effective, valuable clues to the diag­ nosis of cognitive difficulties and to therapeutic practice, and hence impact positively on well­ being. In this work, we analyzed transcribed conversations between elderly individuals living with dementia and healthcare professionals. The material came from the Anchise 2022 Corpus, a large collection of transcripts of conversations in Italian recorded in naturalistic conditions. The aim of the work was to test the effectiveness of a number of automatic analyzes in finding cor­ relations with the progression of dementia in individuals with cognitive decline as measured by the Mini-Mental State Examination (MMSE) score, which is the only psychometric-clinical in­ formation available on the participants in the conversations. Healthy controls (HC) were not considered in this study, nor does the corpus itself include HCs. The main innovation and strength of the work consists in the high ecological validity of the language analyzed (most of the literature to date concerns controlled language experiments); in the use of Italian (there is little corpora for Italian); in the size of the analyzed data (more than 200 conversations were considered); in the adoption of a wide range of NLP methods, that span from traditional morphosyntactic investi­ gation to deep linguistic models for conducting analyzes such as through perplexity, sentiment (polarity) and emotions. Methods: Analyzing real-world interactions not designed with computational analysis in mind, such as is the case of the Anchise Corpus, is particularly challenging. To achieve the research goals, a wide variety of tools were employed. These included traditional morphosyntactic analysis based on digital linguistic biomarkers (DLBs), transformer-based language models, sentiment and emotion analysis, and perplexity metrics. Analyzes were conducted both on the continuous range of MMSE values and on the severe/moderate/mild categorization suggested by AIFA (Italian Medicines Agency) guidelines, based on MMSE threshold values. Results and discussion: Correlations between MMSE and individual DLBs were weak, up to 0.19 for positive, and -0.21 for negative correlation values. Nevertheless, some correlations were statis­ tically significant and consistent with the literature, suggesting that people with a greater degree of impairment tend to show a reduced vocabulary, to have anomia, to adopt a more informal linguist register, and to display a simplified use of verbs, with a decrease in the use of participles, gerunds, subjunctive moods, modal verbs, as well as a flattening in the use of the tenses towards the present to the detriment of the past. The -0.26 inverse correlation between perplexity and MMSE suggests that perplexity captures slightly more specific linguistic information, which can complement the MMSE scores. In the categorization tasks, the classifier based on DLBs achieved an F1 score of 0.79 for binary classification between SEVERE and MILD, and 0.61 for multi-label categorization. Sentiment and emotion analyzes showed inverse trends for joy while MMSE scores suggested that less impaired individuals were less joyful, or more “negative”, than others. Considering the real-world context, this is consistent with the hypothesis of a gradual reduction in awareness in individuals affected by dementia. Finally, integrating various profiles of analysis has been proved to be effective in offering a wider picture of linguistic and communication deficits, as well as more precise data regarding the progression of dementia

Position Control of Piezoelectric Actuators by Thick-Film Piezoresistive Elements

Precise control of actuator position can be achieved by using thick-film resistors (TFRs) for piezoresistive position feedback