Digital divide: addressing Internet skills. Educational implications in the validation of a scale

Recent studies indicate that Internet skills have a positive impact on academic achievement. This article presents a national study that seeks to validate an Internet skills scale that was already tested in other EU countries (the Netherlands and the United Kingdom) to understand the competence level of the population as a whole as well as across population sectors. The scale questionnaire was completed by a sample of the Italian population stratified by gender, age and geographical area. The result is globally consistent at the empirical level as well as at the cross-national level. All the five scales showed excellent internal consistency

Predictive performance comparisons of different feature extraction methods in a financial column corpus

Questo contributo riguarda il trattamento di un corpus costituito da una rubrica finanziaria settimanale. In particolare, ci siamo concentrati sull'estrazione di indici a livello di documento e sull'estrazione di variabili testuali. Inoltre, abbiamo confrontato alcuni metodi di estrazione delle variabili per valutare la loro capacità predittiva. I risultati confermano l'ipotesi che i vettori derivati dal word embedding non migliorano la capacità predittiva rispetto ad altri metodi di estrazione delle variabili, ma restano una risorsa fondamentale per cogliere la semantica nei testi.This work concerns the processing of a corpus made up of a financial weekly column. Specifically, we focused on document-level index extraction and textual feature extraction. Moreover, some feature extraction methods had been compared to evaluate their predictive capacity. Results confirm the hypothesis that vectors derived from word embedding do not improve the predictive power compared to other feature extraction methods but remain a fundamental resource for capturing semantics in texts

Role of gelatinases in pathological and physiological processes involving the dystrophin-glycoprotein complex

Dystrophin is a cytosolic protein belonging to a membrane-spanning glycoprotein complex, called dystrophin-glycoprotein complex (DGC), that is expressed in many tissues, especially in skeletal muscle and in the nervous system. The DGC connects the cytoskeleton with the extracellular matrix and, although none of the protein of the DGC displays kinase or phosphatase activity, it is involved in many signal transduction pathways. Mutations in some components of the DGC are linked to many forms of inherited muscular dystrophies. In particular, a mutation hitting the dystrophin gene, leading to a complete loss of the protein, provokes one of the most prominent muscular dystrophy, the Duchenne muscular dystrophy, which affects 1 out of 3500 newborn males. In these circumstances, it can be observed a dramatic alteration of the expression levels of a multitude of metalloproteinases (MMPs), a family of extracellular Zn2+-dependent endopeptidases, especially MMP-2 and MMP-9, also called gelatinases. However, the enzymatic activity of MMP-2 and MMP-9 on dystroglycan, an important member of the DGC, plays an important role also in physiological processes taking place in the central and peripheral nervous system. This mini-review discusses the role of MMP-2 and MMP-9, in physiological as well as pathological processes involving members of the DGC

TextWiller: Collection of functions for text mining, specially devoted to the Italian language

TextWilleris the development version of a R package that collects some text mining utilities intended for the Italian language. It’s available at https://github.com/livioivil/TextWiller. The aim of TextWiller is to help to deal with the pre-processing of a corpus and it also provides some functions about word classification and polarity

The role of citation networks to explain academic promotions: an empirical analysis of the Italian national scientific qualification

The aim of this paper is to study the role of citation network measures in the assessment of scientific maturity. Referring to the case of the Italian national scientific qualification (ASN), we investigate if there is a relationship between citation network indices and the results of the researchers’ evaluation procedures. In particular, we want to understand if network measures can enhance the prediction accuracy of the results of the evaluation procedures beyond basic performance indices. Moreover, we want to highlight which citation network indices prove to be more relevant in explaining the ASN results, and if quantitative indices used in the citation-based disciplines assessment can replace the citation network measures in non-citation-based disciplines. Data concerning Statistics and Computer Science disciplines are collected from different sources (ASN, Italian Ministry of University and Research, and Scopus) and processed in order to calculate the citation-based measures used in this study. Then, we apply logistic regression models to estimate the effects of network variables. We find that network measures are strongly related to the results of the ASN and significantly improve the explanatory power of the models, especially for the research fields of Statistics. Additionally, citation networks in the specific sub-disciplines are far more relevant than those in the general disciplines. Finally, results show that the citation network measures are not a substitute of the citation-based bibliometric indices

WordUp! at VaxxStance 2021: Combining Contextual Information with Textual and Dependency-Based Syntactic Features for Stance Detection.

In this paper we describe the participation of the WordUp! team in the VaxxStance shared task at IberLEF 2021. The goal of the competition is to determine the author's stance from tweets written both in Spanish and Basque on the topic of the Antivaxxers movement. Our approach, in the four different tracks proposed, combines the Logistic Regression classifier with diverse groups of features: stylistic, tweet-based, user-based, lexicon-based, dependency-based, and network-based. The outcomes of our experiments are in line with state-of-the-art results on other languages, proving the efficacy of combining methods derived from NLP and Network Science for detecting stance in Spanish and Basque

The Structure of the N-terminal Region of Murine Skeletal Muscle α-Dystroglycan Discloses a Modular Architecture

Dystroglycan (DG) is a cell surface receptor consisting of two subunits: alpha-dystroglycan, extracellular and highly glycosylated, and beta-dystroglycan, spanning the cell membrane. It is a pivotal member of the dystrophin-glycoprotein complex and is involved in a wide variety of important cellular processes such as the stabilization of the muscle fiber sarcolemma or the clustering of acetylcholine receptors. We report the 2.3-A resolution crystal structure of the murine skeletal muscle N-terminal alpha-DG region, which confirms the presence of two autonomous domains; the first finally identified as an Ig-like and the second resembling ribosomal RNA-binding proteins. Solid-phase laminin binding assays show the occurrence of protein-protein type of interactions involving the Ig-like domain of alpha-DG

Evidence for the production of three massive vectorbosons in pppp collisions with the ATLAS detector

A search for the production of three massive vector bosons in proton--proton collisions is performed using data at s√=13TeV recorded with the ATLAS detector at the Large Hadron Collider in the years 2015--2017, corresponding to an integrated luminosity of 79.8fb−1. Events with two same-sign leptons ℓ (electrons or muons) and at least two reconstructed jets are selected to search for WWW→ℓνℓνqq. Events with three leptons without any same-flavour opposite-sign lepton pairs are used to search for WWW→ℓνℓνℓν, while events with three leptons and at least one same-flavour opposite-sign lepton pair and one or more reconstructed jets are used to search for WWZ→ℓνqqℓℓ. Finally, events with four leptons are analysed to search for WWZ→ℓνℓνℓℓ and WZZ→qqℓℓℓℓ. Evidence for the joint production of three massive vector bosons is observed with a significance of 4.0 standard deviations, where the expectation is 3.1 standard deviations