Impatti dell'automazione sul mercato del lavoro. Prime stime per il caso italiano.

The causes of the present decline of demand in labor markets in developed countries are subject to considerable theoretical debate. More specifically, according to some authors, globalization and offshoring together with technological innovation, could lead to further negative impacts on real employment. Some studies estimate that the contribution of automation is the actual cause of job loss: in the US the introduction of robots by 2021 could lead to a cut of more than 6% of the workforce (FORRESTER 2016), and as much as 54% in Europe in the coming decades (Bowles 2014), although the greatest impact would occur in developing countries, where automation could weaken the traditional comparative advantages in terms of labor costs (UN 2016). The Italian case is particularly interesting, as the automation was introduced in large enterprises over three decades ago, determining a deep impact in terms of loss for low skilled jobs. This paper aims to provide a first quantification of the impacts on Italian labor market determined by the spread of latest technological innovations, both in terms of employment levels and social/territorial mobility, by differentiating its effects per macro-geographical breakdown of the country

Una tecnica di disaggregazione fuzzy

Nei problemi di decisione statistica l’incertezza è comunemente rappresentata tramite misure di probabilità. Tale schema, tuttavia, in presenza di un information set limitato, potrebbe rivelarsi inappropriato (Krätschmer 2003). Da un punto di vista generale sarebbe quindi auspicabile adottare procedure più flessibili. Le misure del grado di incertezza, in altri termini, dovrebbero in alcuni casi soddisfare soltanto alcune proprietà generali. Un’importante classe di misure è quella delle c.d. misure fuzzy, caratterizzate da monotonicità e da alcune condizioni di normalizzazione. I concetti di misura ed integrale fuzzy generalizzano la definizione comune di misura sostituendo la proprietà di additività con un requisito più debole, la monotonicità rispetto alla funzione d’insieme, strettamente legata alla nozione di capacità introdotta da Choquet (1954). Nell’approccio di Walley (1991) l’incertezza è rappresentata da previsioni minime, intese come funzionali in ? e di cui le misure fuzzy rappresentano un caso particolare. Uno dei concetti chiave nella teoria delle previsioni minime è quello di coerenza, che esprime un requisito minimo di consistenza e la cui formulazione si deve originariamente a De Finetti (1974) che, come è noto, introduce il concetto di coerenza per fornire un fondamento comportamentale alla teoria della probabilità. Per garantire la proprietà di coerenza delle misure fuzzy Walley introduce il concetto di estensione naturale, che rappresenta una previsione minima coerente. Sotto certe condizioni l’estensione naturale è rappresentabile in termini di integrale di Choquet e la misura fuzzy assume un contenuto probabilistico. L’articolo esamina un problema di disaggregazione di serie storiche in presenza di estesi lack informativi. In contesti di questo tipo è impossibile mantenere gli assunti che giustificano l’applicazione di metodologie tradizionali, quali quelle derivate dall’algoritmo di Chow e Lin, basate sulle consuete ipotesi di normalità. In termini generali, in presenza di information set limitati, il riferimento a misure probabilistiche potrebbe rivelarsi inappropriato e appare opportuno adottare misure del grado di incertezza che soddisfino soltanto alcune proprietà generali, quali ad esempio le c.d. misure fuzzy. Dopo un esame sommario delle proprietà dei principali operatori di aggregazione, è quindi presentata una procedura di disaggregazione di informazioni in presenza di lack informativi, basata sulla nozione di integrale di Choquet, caratterizzata da coerenza nel senso di De Finetti

Using stop words in text mining: Immigration and the election campaigns.

In order to understand immigration sentiment and its relationship to other concepts in the Italian general election campaign of 2018 and the European election campaign of 2019, we collected in two corpora all the tweets in the Italian language containing the word “immigration” in the period preceding the vote. Both corpora underwent a sentiment analysis and a stop word analysis using two textual software packages: Linguistic Inquiry and Word Count (LIWC) (Pennebaker et al., 2015) and WORDij. LIWC was originally designed by James Pennebaker to understand how some patients recover from traumatic experiences by writing about those experiences and the emotions associated with it then and afterwards. LIWC consists of a dictionary of words which assesses the percent that they occur in a given text. LIWC analysis provides a measure of positive and negative emotion in the immigration text over time. WORDij is a text analysis program that can compute a Z-Score or the relative proportional test of difference between words and words pairs in two sets of texts. Using an include list of stop words we can determine how these relational words change over time with an emotional valence and Z-score to assess the immigration political debate over time. The paper represents a focus on stop-words, which have been an aspect of textual analysis that is often dismissed yet can be very important to our understanding of relational powe

Deep reinforcement learning control of white-light continuum generation

White-light continuum (WLC) generation in bulk media finds numerous applications in ultrafast optics and spectroscopy. Due to the complexity of the underlying spatiotemporal dynamics, WLC optimization typically follows empirical procedures. Deep reinforcement learning (RL) is a branch of machine learning dealing with the control of automated systems using deep neural networks. In this Letter, we demonstrate the capability of a deep RL agent to generate a long-term-stable WLC from a bulk medium without any previous knowledge of the system dynamics or functioning. This work demonstrates that RL can be exploited effectively to control complex nonlinear optical experiments

Adult Spinal Deformity in the Elderly. Preliminary Clinical and Radiological Results in 22 Patients Treated by a Two Times Minimally Invasive Spine Surgery

IntroductionThe adult spinal deformity (ASD) seems, in the last years, in a progressive increment. It should be in relation to the aging of the population. This trend leads to a progression of the ..

Text mining e social media: Anatomia di una crisi di governo

In August 2019, when Matteo Salvini asked to return to the ballot box, the Italian government entered into crisis. This generated a large debate that also took place on social media – particularly on Twitter, which has now become increasingly important as a place for political debate. This study presents the analysis of the Twitter discourse related to government crisis, in the period following the resignation of the Prime Minister. Text mining and social network analysis techniques have been integrated to study the positioning of political leaders and the topics of major interest. In particular, we used the Emotional Text Mining (ETM) and Semantic Brand Score (SBS) techniques. The SBS served as an indicator of the most relevant topics in the discourse. It was used to determine the importance of the themes emerging from the EMT. This importance was measured along the three dimensions of prevalence, diversity, and connectivity – considering textual association patterns and cooccurrence networks. The integration of the two procedures allowed to describe the public perception of the crisis and to identify the symbolic-cultural matrix and the sentiment related to each discourse topic

Artificial Intelligence in Classical and Quantum Photonics

The last decades saw a huge rise of artificial intelligence (AI) as a powerful tool to boost industrial and scientific research in a broad range of fields. AI and photonics are developing a promising two-way synergy: on the one hand, AI approaches can be used to control a number of complex linear and nonlinear photonic processes, both in the classical and quantum regimes; on the other hand, photonics can pave the way for a new class of platforms to accelerate AI-tasks. This review provides the reader with the fundamental notions of machine learning (ML) and neural networks (NNs) and presents the main AI applications in the fields of spectroscopy and chemometrics, computational imaging (CI), wavefront shaping and quantum optics. The review concludes with an overview of future developments of the promising synergy between AI and photonics

The use of surgical sealants in the repair of dural tears during non-instrumented spinal surgery

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Evaluation of Trichoderma atroviride endophytes with growth-promoting activities on tomato plants and antagonistic action on Fusarium oxysporum

In Brazil, tomato is one of the most consumed vegetables and the fungus Fusarium oxysporum is one of the most important phytopathogen of tomato plants (Lycopersicon esculentum Mill.). Thus, the search of beneficial microorganisms with growth-promoting and/or biological control properties represent an important tool for agricultural biotechnology. Herein, two Trichoderma endophytes (strains 36b and 164b) associated with Coffea arabica were investigated on their growth-promoting activities on plants and their antagonist effects and interactions against F. oxysporum. Molecular multigene (ITS- TEF-TUB-CAL) identification and phylogenetic analysis allowed the identification of these endophytes as belonging to Trichoderma atroviride species. When inoculated with the endophytic strain 36b, tomato plants reached the highest speed of seedling emergence (83.3%), but both endophytes increased the number of leaves, root length and dry biomass of treated plants. Regarding the in vitro antagonism assay, reduced phytopathogen growth by approximately 70 (strain 36b) and 52% (strain 164b) which indicates a partial replacement of endophytes after initial deadlock with mycelial contact. Scanning electron microscopy allowed to observe the presence of Fusarium macroconidia between endophytic hyphae and conidia, with the helicoidization of endophytic hyphae, which wrapped around the pathogen hyphae, suggesting a mechanical inhibition by strangulation