Metodologia della valutazione cognitiva

Guidare l\u2019automobile \ue8 un\u2019attivit\ue0 indispensabile nella vita quotidiana di milioni di persone in tutto il mondo, ma \ue8 anche un compito complesso e cognitivamente impegnativo. Per questo motivo oggi \ue8 sempre pi\uf9 frequente che le commissioni mediche di competenza richiedano valutazioni per verificare l\u2019esistenza dei prerequisiti cognitivi per la guida sicura. \uc8 dunque indispensabile avere linee-guida ben definite e condivise. Il volume affronta gli aspetti clinico-giuridici di base, fornendo considerazioni tecniche e metodologiche utili a medici e psicologi che operano in questo ambito

L'idoneit\ue0 alla guida

Guidare l\u2019automobile \ue8 un\u2019attivit\ue0 indispensabile nella vita quotidiana di milioni di persone in tutto il mondo, ma \ue8 anche un compito complesso e cognitivamente impegnativo. Per questo motivo oggi \ue8 sempre pi\uf9 frequente che le commissioni mediche di competenza richiedano valutazioni per verificare l\u2019esistenza dei prerequisiti cognitivi per la guida sicura. \uc8 dunque indispensabile avere linee-guida ben definite e condivise. Il volume affronta gli aspetti clinico-giuridici di base, fornendo considerazioni tecniche e metodologiche utili a medici e psicologi che operano in questo ambito

Automatic Detection of Cross-language Verbal Deception

The assessment of how a deceptive message is produced in dif-ferent languages has received little attention, with the majorityof studies focused on the English language. Moreover, thereis no agreement about the stability of linguistic clues of deceitacross different languages. In this paper, we address this issueby analysing both theory-driven linguistic markers of decep-tion (cognitive load hypothesis) and standard text categorisa-tion features. After compiling a multilingual corpus of bothhonest and deceitful first-person opinions regarding five differ-ent topics, we assessed the cross-language applicability of fourdifferent features sets in within-topic, cross-topic and cross-language binary classification experiments. Results showedpromising classification performances in all the three experi-ments with few exceptions. Interestingly, linguistic markersof deceit linked to the cognitive load hypothesis exhibited thesame trend in the two languages under investigation and thecross-language evaluation highlighted their usefulness in spot-ting deceit between different languages

Automatic Detection of Cross-language Verbal Deception

The assessment of how a deceptive message is produced in different languages has received little attention, with the majority of studies focused on the English language. Moreover, there is no agreement about the stability of linguistic clues of deceit across different languages. In this paper, we address this issue by analysing both theory-driven linguistic markers of deception (cognitive load hypothesis) and standard text categorisation features. After compiling a multilingual corpus of both honest and deceitful first-person opinions regarding five different topics, we assessed the cross-language applicability of four different features sets in within-topic, cross-topic and cross-language binary classification experiments. Results showed promising classification performances in all the three experiments with few exceptions. Interestingly, linguistic markers of deceit linked to the cognitive load hypothesis exhibited the same trend in the two languages under investigation and the cross-language evaluation highlighted their usefulness in spotting deceit between different languages

DecOp: A Multilingual and Multi-domain Corpus For Detecting Deception In Typed Text

In recent years, the increasing interest in the development of automatic approaches for unmasking deception in online sources led to promising results. Nonetheless, among the others, two major issues remain still unsolved: the stability of classifiers performances across different domains and languages. Tackling these issues is challenging since labelled corpora involving multiple domains and compiled in more than one language are few in the scientific literature. For filling this gap, in this paper we introduce DecOp (Deceptive Opinions), a new language resource developed for automatic deception detection in cross-domain and cross-language scenarios. DecOp is composed of 5000 examples of both truthful and deceitful first-person opinions balanced both across five different domains and two languages and, to the best of our knowledge, is the largest corpus allowing cross-domain and cross-language comparisons in deceit detection tasks. In this paper, we describe the collection procedure of the DecOp corpus and his main characteristics. Moreover, the human performance on the DecOp test-set and preliminary experiments by means of machine learning models based on Transformer architecture are shown

Verbal lie detection using Large Language Models

Abstract Human accuracy in detecting deception with intuitive judgments has been proven to not go above the chance level. Therefore, several automatized verbal lie detection techniques employing Machine Learning and Transformer models have been developed to reach higher levels of accuracy. This study is the first to explore the performance of a Large Language Model, FLAN-T5 (small and base sizes), in a lie-detection classification task in three English-language datasets encompassing personal opinions, autobiographical memories, and future intentions. After performing stylometric analysis to describe linguistic differences in the three datasets, we tested the small- and base-sized FLAN-T5 in three Scenarios using 10-fold cross-validation: one with train and test set coming from the same single dataset, one with train set coming from two datasets and the test set coming from the third remaining dataset, one with train and test set coming from all the three datasets. We reached state-of-the-art results in Scenarios 1 and 3, outperforming previous benchmarks. The results revealed also that model performance depended on model size, with larger models exhibiting higher performance. Furthermore, stylometric analysis was performed to carry out explainability analysis, finding that linguistic features associated with the Cognitive Load framework may influence the model’s predictions

Verbal cues to deceit when lying through omitting information

Background Lying through omitting information has been neglected in verbal lie detection research. The task is challenging: Can we decipher from the truthful information a lie teller provides that s/he is hiding something? We expected this to be the case because of lie tellers\u2019 inclination to keep their stories simple. We predicted lie tellers to provide fewer details and fewer complications than truth tellers, the latter particularly after exposure to a Model Statement. Method A total of 44 truth tellers and 41 lie tellers were interviewed about a conversation (debriefing interview) they had taken part in earlier. Lie tellers were asked not to discuss one aspect of that debriefing interview. Results Results showed that truth tellers reported more complications than lie tellers after exposure to a Model Statement. Conclusion Ideas about future research in lying through omissions are discussed

L’ingegnerizzazione tissutale delle cellule paratiroidee

Background. L’ipoparatiroidismo postchirurgico rappresenta un’evenienza tutt’altro che rara dopo intervento di tiroidectomia totale e/o paratiroidectomia totale. I tentativi di trapiantare tessuto paratiroideo sono iniziati nel 1975 con Wells ed i risultati ancora oggi sono alquanto deludenti. Negli ultimi anni grazie a tecniche di ingegneria tissutale si cerca di costruire paratiroidi artificiali,capaci di secernere paratormone, disponibili per il trapianto in pazienti affetti da ipoparatiroidismo iatrogeno. Pazienti e metodi. I paratireociti sono stati ottenuti da paratiroidi di tre pazienti, uremici cronici in emodialisi, operati per iperparatiroidismo secondario. Le colture cellulari ottenute in RPMI sono state successivamente seminate sugli scaffold di collagene (supporti tridimensionali a lenta biodegradazione). Il collagene rappresenta la componente maggioritaria della matrice extracellulare e quindi costituisce un buon substrato su cui le cellule aderiscono e crescono. I terreni di coltura adeguatamente supplementati contenevano bassa concentrazione di calcio e quindi stimolavano in maniera fisiologica i paratireociti a produrre paratormone in maniera costante. Le colture cellulari sono state osservate in microscopia ottica ed in ESEM e sono state sottoposte al test di vitalità MTT fino alla decima settimana. Inoltre è stata misurata la concentrazione di paratormone nel liquido colturale a varie settimane. Risultati. Dopo 24 ore di coltura in RPMI le cellule estratte dalle paratiroidi umane erano quasi tutte adese e raggruppate in clusters tra di loro, a ricordare l’organizzazione ghiandolare. La popolazione cellulare era costituita prevalentemente da paratireociti (90-95%). Seminate sugli scaffold collagenici, a 10 settimane le cellule mantengono una morfologia epithelial-like, arrivando a colonizzare la superficie dello scaffold, conservano una buona progressione proliferativa, associata alla produzione di paratormone. Conclusioni. La scelta di utilizzare paratireociti di pazienti affetti da iperparatiroidismo secondario ha certamente contribuito ad ottenere questi risultati, che, seppur parziali ed in vitro, vanno sperimentati in vivo su modello animale. Il costrutto bioingegnerizzato in scaffold impiantabile nel sottocutaneo può evitare la temuta dispersione delle cellule paratiroidee impiantate e dunque favore la loro agevole rimozione in caso di complicanze. La nostra ricerca ha avuto come obiettivi innanzitutto la realizzazione di colture cellulari di paratireociti umani e successivamente la ingegnerizzazione in vitro di paratiroidi umane all’interno di scaffold tridimensionali collagenici