Externalities in economics and finance:Essays on spillover effects and economic decisions

This dissertation includes three chapters that empirically investigate the role of externalities in financial markets (Chapter 2 and 3), and in society during a health crisis (Chapter 4). More specifically, in Chapter 2 I explore how the risk of future collateral fire sales affects lending decisions. In Chapter 3, I examine how technology can make the collateral liquidation process more efficient, as well as the indirect consequences it may have on other assets. In Chapter 4, I study the effectiveness of government interventions in containing negative externalities during the COVID-19 outbreak in Italy. Final remarks conclude in Chapter 5

Externalities in economics and finance:Essays on spillover effects and economic decisions

This dissertation includes three chapters that empirically investigate the role of externalities in financial markets (Chapter 2 and 3), and in society during a health crisis (Chapter 4). More specifically, in Chapter 2 I explore how the risk of future collateral fire sales affects lending decisions. In Chapter 3, I examine how technology can make the collateral liquidation process more efficient, as well as the indirect consequences it may have on other assets. In Chapter 4, I study the effectiveness of government interventions in containing negative externalities during the COVID-19 outbreak in Italy. Final remarks conclude in Chapter 5

Macroprudential tax on debt

With the aim of testing macroprudential policies’ effectiveness, this research models a rich and open economy hit by future news shocks about fundamentals and regime switches in global liquidity. Agents take excessive debt to finance current consumption, making the economy more vulnerable to financial crises. Quantitative findings of the simulation shows that a tax on debt, optimally set by a social planner, increases total welfare and decreases the probability and the magnitude of financial crisis. However, it is shown that if news precision increases too much, a tax on debt may be even deleterious because it reduces economic growth

Analysis of the variability of cutting processes when many factors are perturbed.

Since the knowledge of industrial processes is mainly based on virtualisation, it is fundamental to develop a better understanding of the real processes performing analysis from an industrial point of view. Every analysis must use tools and solutions that could be really useful for industries, and become improvement keys for success. This paper shows a structured analysis of a turning process, to gain useful information, to evaluate experimental data and to define some improvement guidelines. On the basis of an excellent dataset, the main objective is to perform statistical analyses to estimate the influence of critical factors on response variables

Schede per la flora ornamentale siciliana. 61-67

With the aim to improve the knowledge of the ornamental flora of Sicily, a series of reports on the most rare and significant species found in the historic or public gardens and parks has been started since 2001. The plants taken in consideration are examined as far as taxonomy, geographical origin, biology, ecology are concerned, also taking into account their condition in Sicily with respect to introduction, sanitary status, occurrence, etc... Furthermore, germplasm conservation is, when possible, provided in the Botanical Garden of Palermo. Each taxon is treated in a single report. Here the reports 61-67, by F. Argento, M.R. Cucco, E. Di Gristina & R. Oliveri, are presented. These concern Araucaria bidwillii Hook., Araucaria cunninghamii Sweet, Cordia myxa L., Decaisnea fargesii Franch., Ficus benjamina L., Ficus elastica var. decora Guillaumin e Kleinia neriifolia Haw

Shared perception is different from individual perception: a new look on context dependency

Human perception is based on unconscious inference, where sensory input integrates with prior information. This phenomenon, known as context dependency, helps in facing the uncertainty of the external world with predictions built upon previous experience. On the other hand, human perceptual processes are inherently shaped by social interactions. However, how the mechanisms of context dependency are affected is to date unknown. If using previous experience - priors - is beneficial in individual settings, it could represent a problem in social scenarios where other agents might not have the same priors, causing a perceptual misalignment on the shared environment. The present study addresses this question. We studied context dependency in an interactive setting with a humanoid robot iCub that acted as a stimuli demonstrator. Participants reproduced the lengths shown by the robot in two conditions: one with iCub behaving socially and another with iCub acting as a mechanical arm. The different behavior of the robot significantly affected the use of prior in perception. Moreover, the social robot positively impacted perceptual performances by enhancing accuracy and reducing participants overall perceptual errors. Finally, the observed phenomenon has been modelled following a Bayesian approach to deepen and explore a new concept of shared perception.Comment: 14 pages, 9 figures, 1 table. IEEE Transactions on Cognitive and Developmental Systems, 202

A new species of Smyrnium (Apiaceae) related to S. perfoliatum

On the basis of plant collections recently carried out in Sicily as well as the study of the herbarium material kept in PAL and PAL-Gr, a new species of Smyrnium (Apiaceae) is described here. This new taxon, named Smyrnium dimartinoi, is related to S. perfoliatum and is presently known from Sicily, Crete and realistically elsewhere in the Mediterranean. In such range it occurs in open woods and clearings of the Mediterranean-temperate and submontane belt

Automating the simulation of SME processes through a discrete event parametric model

At the factory level, the manufacturing system can be described as a group of processes governed by complex weaves of engineering strategies and technologies. Decision- making processes involve a lot of information, driven by managerial strategies, technological implications and layout constraints. Many factors affect decisions, and their combination must be carefully managed to determine the best solutions to optimize performances. In this way, advanced simulation tools could support the decisional process of many SMEs. The accessibility of these tools is limited by knowledge, cost, data availability and development time. These tools should be used to support strategic decisions rather than specific situations. In this paper, a novel approach is proposed that aims to facilitate the simulation of manufacturing processes by fast modelling and evaluation. The idea is to realize a model that is able to be automatically adapted to the user’s specific needs. The model must be characterized by a high degree of flexibility, configurability and adaptability in order to automatically simulate multiple/heterogeneous industrial scenarios. In this way, even a SME can easily access a complex tool, perform thorough analyses and be supported in taking strategic decisions. The parametric DES model is part of a greater software platform developed during COPERNICO EU funded project

Names of Italian vascular plants published by Michele Lojacono Pojero

Michele Lojacono Pojero (1853-1919) is among the most prolific Italian authors of plant names of his era. A list is presented of the names of 581 new Italian (almost invariably Sicilian) vascular plant taxa he published (303 species, 272 varieties, 6 formae), with reference to existing lectotype designations

To Whom are You Talking? A Deep Learning Model to Endow Social Robots with Addressee Estimation Skills

Communicating shapes our social word. For a robot to be considered social and being consequently integrated in our social environment it is fundamental to understand some of the dynamics that rule human-human communication. In this work, we tackle the problem of Addressee Estimation, the ability to understand an utterance's addressee, by interpreting and exploiting non-verbal bodily cues from the speaker. We do so by implementing an hybrid deep learning model composed of convolutional layers and LSTM cells taking as input images portraying the face of the speaker and 2D vectors of the speaker's body posture. Our implementation choices were guided by the aim to develop a model that could be deployed on social robots and be efficient in ecological scenarios. We demonstrate that our model is able to solve the Addressee Estimation problem in terms of addressee localisation in space, from a robot ego-centric point of view.Comment: Accepted version of a paper published at 2023 International Joint Conference on Neural Networks (IJCNN). Please find the published version and info to cite the paper at https://doi.org/10.1109/IJCNN54540.2023.10191452 . 10 pages, 8 Figures, 3 Table