Modelling bank lending in the euro area: A non-linear approach

This paper investigates possible non-linearities in the response of bank lending to monetary policy shocks in the euro area. The credit market is modelled over the period 1985-2005 by means of an Asymmetric Vector Error Correction Model (AVECM) involving four endogenous variables (loans to the private sector, real GDP, lending rate, and consumer price index) and one exogenous variable (money market rate). The main features of the model are the existence of two co-integrating equations representing the long-run credit demand and supply and the possibility for loading and lagged-term coefficients to assume different values depending on the monetary policy regime (easing or tightening). The paper finds that the effect on credit, GDP, and prices of a monetary policy tightening is larger than the effect of a monetary policy easing. This result supports the existence of an asymmetric broad credit channel in the euro area.monetary policy transmission, credit market, credit view, asymmetries

Flexible oxide thin film transistors: fabrication and photoresponse

Gli ossidi amorfi semiconduttori (AOS) sono nuovi candidati per l’elettronica flessibile e su grandi aree: grazie ai loro legami prevalentemente ionici hanno una mobilità relativamente alta (µ > 10cm^2/Vs) anche nella fase amorfa. Transistor a film sottile (TFT) basati sugli AOS saranno quindi più performanti di tecnologie a base di a-Si e più economici di quelle a base di silicio policristallino. Essendo amorfi, possono essere depositati a basse temperature e su substrati polimerici, caratteristica chiave per l’elettronica flessibile e su grandi aree. Per questa tesi, diversi TFT sono stati fabbricati e caratterizzati nei laboratori del CENIMAT all’Università Nova di Lisbona sotto la supervisione del Prof. P. Barquinha. Questi dispositivi sono composti di contatti in molibdeno, un canale semiconduttivo di ossido di zinco, gallio e indio (IGZO) e un dielettrico composto da 7 strati alternati di SiO2 e SiO2+Ta2O5. Tutti i dispositivi sono stati depositati mediante sputtering su sostrati flessibili (fogli di PEN). Le misure tensione-corrente mostrano che i dispositivi mantengono alte mobilità (decine di 10cm^2/Vs) anche quando fabbricati a temperature inferiori a 200°C. Si è analizzato il funzionamento dei dispositivi come fototransistor rilevando la risposta alla luce ultravioletta e in particolare la loro responsività e spostamento della tensione di soglia in funzione della lunghezza d’onda incidente. Questi risultati consentono di formulare ipotesi sul comportamento dei dispositivi alla scala microscopica. In particolare, indicano che i) la mobilità del canale non è influenzata dall’illuminazione, ii) sia l'IGZO sia il Ta2O5 contribuiscono al processo di fotoconduttività e iii) il processo di fotogenerazione non è adiabatico. La tesi contiene inoltre una descrizione del processo di ricombinazione e presenta un’applicazione pratica di tali dispositivi in un circuito per RFID. Infine, esplora la possibilità di migliorarne la flessibilità e le prestazioni

Status of the ATLAS detector and first measurements at the LHC

The status of the ATLAS detector is presented together with the first results on proton-proton collisions at the Large Hadron Collider (LHC). Measurements of kinematical variables and multiplicities of charged particle produced in 900 GeV collisions are presented together with some relevant commissioning studies. Preliminary results on 7TeV collisions are also presented including twoW-decay candidates

Complejidad y emergencia de la organización política. La polis griega en el pensamiento de Aristóteles como sistema complejo

El propósito del artículo es contribuir al desarrollo de una teoría política interdisciplinaria a través de una vinculación conceptual de la filosofía política de Aristóteles con la teoría de los sistemas complejos. El trabajo relaciona la tesis aristotélica de la sabiduría colectiva con el concepto de emergencia desarrollado por la teoría de los sistemas complejos. Se analiza la politeia o república como un régimen político ascendente, que extrae su inteligencia de la base. Postula que el encuentro y la deliberación entre ciudadanos virtualmente libres e iguales permiten la aparición de una conducta emergente, la sabiduría colectiva como propiedad agregada macro-individual. Se afirma que la ciudad puede concebirse como un problema de complejidad organizada, donde las acciones, percepciones e interacciones locales producen un comportamiento emergente, al mismo tiempo que la organización del todo condiciona la conducta de las partes. La ciudad es por lo tanto una unidad compleja que se constituye como physis política a través de un proceso organizativo que entraña una dialógica (lógica complementaria y antagonista) entre el todo y las partes. La conclusión central es que el desarrollo de conceptos capaces de viajar a través de las fronteras disciplinarias puede contribuir a la comprensión de la complejidad sociopolítica

UniParma at SemEval-2021 Task 5: Toxic Spans Detection Using CharacterBERT and Bag-of-Words Model

With the ever-increasing availability of digital information, toxic content is also on the rise. Therefore, the detection of this type of language is of paramount importance. We tackle this problem utilizing a combination of a state-of-the-art pre-trained language model (CharacterBERT) and a traditional bag-of-words technique. Since the content is full of toxic words that have not been written according to their dictionary spelling, attendance to individual characters is crucial. Therefore, we use CharacterBERT to extract features based on the word characters. It consists of a CharacterCNN module that learns character embeddings from the context. These are, then, fed into the well-known BERT architecture. The bag-of-words method, on the other hand, further improves upon that by making sure that some frequently used toxic words get labeled accordingly. With a 4 percent difference from the first team, our system ranked 36th in the competition. The code is available for further re-search and reproduction of the results

Improving BERT Performance for Aspect-Based Sentiment Analysis

Aspect-Based Sentiment Analysis (ABSA) studies the consumer opinion on the market products. It involves examining the type of sentiments as well as sentiment targets expressed in product reviews. Analyzing the language used in a review is a difficult task that requires a deep understanding of the language. In recent years, deep language models, such as BERT \cite{devlin2019bert}, have shown great progress in this regard. In this work, we propose two simple modules called Parallel Aggregation and Hierarchical Aggregation to be utilized on top of BERT for two main ABSA tasks namely Aspect Extraction (AE) and Aspect Sentiment Classification (ASC) in order to improve the model's performance. We show that applying the proposed models eliminates the need for further training of the BERT model. The source code is available on the Web for further research and reproduction of the results

A novel Region of Interest Extraction Layer for Instance Segmentation

Given the wide diffusion of deep neural network architectures for computer vision tasks, several new applications are nowadays more and more feasible. Among them, a particular attention has been recently given to instance segmentation, by exploiting the results achievable by two-stage networks (such as Mask R-CNN or Faster R-CNN), derived from R-CNN. In these complex architectures, a crucial role is played by the Region of Interest (RoI) extraction layer, devoted to extracting a coherent subset of features from a single Feature Pyramid Network (FPN) layer attached on top of a backbone. This paper is motivated by the need to overcome the limitations of existing RoI extractors which select only one (the best) layer from FPN. Our intuition is that all the layers of FPN retain useful information. Therefore, the proposed layer (called Generic RoI Extractor - GRoIE) introduces non-local building blocks and attention mechanisms to boost the performance. A comprehensive ablation study at component level is conducted to find the best set of algorithms and parameters for the GRoIE layer. Moreover, GRoIE can be integrated seamlessly with every two-stage architecture for both object detection and instance segmentation tasks. Therefore, the improvements brought about by the use of GRoIE in different state-of-the-art architectures are also evaluated. The proposed layer leads up to gain a 1.1% AP improvement on bounding box detection and 1.7% AP improvement on instance segmentation. The code is publicly available on GitHub repository at https://github.com/IMPLabUniPr/mmdetection/tree/groie_de

Towards Model-Driven Dashboard Generation for Systems-of-Systems

Configuring and evolving dashboards in complex and large-scale Systems-of-Systems (SoS) can be an expensive and cumbersome task due to the many Key Performance Indicators (KPIs) that are usually collected and have to be arranged in a number of visualizations. Unfortunately, setting up dashboards is still a largely manual and error-prone task requiring extensive human intervention. This short paper describes emerging results about the definition of a model-driven technology-agnostic approach that can automatically transform a simple list of KPIs into a dashboard model, and then translate the model into an actual dashboard for a target dashboard technology. Dashboard customization can be efficiently obtained by solely modifying the abstract model representation, freeing operators from expensive interactions with actual dashboards