A ranking of the value of patents granted by legal protection

This paper aims at ranking the value of legal patent protection among countries, using the real options approach. In particular, we manage to overcome the problem of the lack of data for those countries that do not collect patent renewal data. The econometric technique we propose is well grounded in economic theory, specifically in the real options literature. Following this estimation strategy, we rank the value of legal patent protection for seventeen countries, closely reproducing other rankings based on surveys, for instance the PatVal survey by the EU Commission (2006), but relying on macro data publicly available and easy to access.Legal protection, intellectual property, real option, value of patent.

Estimates of the Sticky-Information Phillips Curve for the USA with the General to Specific Method

This paper tests for the time series properties of the variables in the sticky information Phillips curve and estimates it for the US with the general to specific method (GETS). Our results show that the estimates of the stickiness parameter range from 0.25 to 0.42.Sticky information Phillips curve, General to specific method, Stickiness parameter

The Euro Changeover and Price Adjustments in Italy

By estimating a staggered price model over the period 1980q1-2010q2, this paper documents that, after the euro changeover, Italian retailers have increased the number of price adjustments, which has translated into a higher inflation rate, with a detrimental effect on the competitiveness of the Italian economy.Euro changeover, staggered price adjustments, inflation

The Euro Changeover and Price Adjustments in Italy

By estimating a staggered price model over the period 1980q1-2010q2, this paper documents that, after the euro changeover, Italian retailers have increased the number of price adjustments, which has translated into a higher inflation rate, with a detrimental effect on the competitiveness of the Italian economyEuro changeover, staggered price adjustments, inflation

Robustness-Driven Resilience Evaluation of Self-Adaptive Software Systems

An increasingly important requirement for certain classes of software-intensive systems is the ability to self-adapt their structure and behavior at run-time when reacting to changes that may occur to the system, its environment, or its goals. A major challenge related to self-adaptive software systems is the ability to provide assurances of their resilience when facing changes. Since in these systems, the components that act as controllers of a target system incorporate highly complex software, there is the need to analyze the impact that controller failures might have on the services delivered by the system. In this paper, we present a novel approach for evaluating the resilience of self-adaptive software systems by applying robustness testing techniques to the controller to uncover failures that can affect system resilience. The approach for evaluating resilience, which is based on probabilistic model checking, quantifies the probability of satisfaction of system properties when the target system is subject to controller failures. The feasibility of the proposed approach is evaluated in the context of an industrial middleware system used to monitor and manage highly populated networks of devices, which was implemented using the Rainbow framework for architecture-based self-adaptation

Mota-Engil : equity valuation

The purpose of this thesis is to obtain the value of an equity investment through a deep study of the company and industry fundamentals. The selection of the firm was based on my big interest in the construction industry, which I developed from my work experience in a real estate company, as an intern. Particularly, Mota-Engil’s impressive position among the top European players captured my attention leading to the choice of developing a broad analysis of its past and future performance. The valuation methodology results from the analyzed literature review on the topic of equity valuation conciliating the theory and the practice. According to the chosen company specificities, several methods were selected and resulted in an extensive equity valuation project. With this work it has been possible to reach the conclusion that Mota-Engil’s stocks are undervalued in the market with an upside potential of 18% resulting from the obtained price per share of 1,6€. This information can be translated into a Buy recommendation. This is the mirror of the company’s strong international presence in emerging markets and its diversification policy that allows attractive profitability levels

Training neural networks with structured noise improves classification and generalization

The beneficial role of noise in learning is nowadays a consolidated concept in the field of artificial neural networks, suggesting that even biological systems might take advantage of similar mechanisms to maximize their performance. The training-with-noise algorithm proposed by Gardner and collaborators is an emblematic example of a noise injection procedure in recurrent networks, which are usually employed to model real neural systems. We show how adding structure into noisy training data can substantially improve the algorithm performance, allowing to approach perfect classification and maximal basins of attraction. We also prove that the so-called Hebbian unlearning rule coincides with the training-with-noise algorithm when noise is maximal and data are fixed points of the network dynamics. A sampling scheme for optimal noisy data is eventually proposed and implemented to outperform both the training-with-noise and the Hebbian unlearning procedures.Comment: 21 pages, 17 figures, main text and appendice

Magnesium isotopes: a tool to understand self-enrichment in Globular Clusters

A critical issue in the asymptotic giant branch (AGB) self-enrichment scenario for the formation of multiple populations in Globular Clusters (GCs) is the inability to reproduce the magnesium isotopic ratios, despite the model in principle can account for the depletion of magnesium. In this work we analyze how the uncertainties on the various p-capture cross sections affect the results related to the magnesium content of the ejecta of AGB stars. The observed distribution of the magnesium isotopes and of the overall Mg-Al trend in M13 and NGC 6752 are successfully reproduced when the proton-capture rate by 25Mg at the temperatures 100 MK, in particular the 25Mg(p, gamma)26Alm channel, is enhanced by a factor 3 with respect to the most recent experimental determinations. This assumption also allows to reproduce the full extent of the Mg spread and the Mg-Si anticorrelation observed in NGC 2419. The uncertainties in the rate of the 25Mg(p,gamma)26Alm reaction at the temperatures of interest here leave space for our assumption and we suggest that new experimental measurements are needed to settle this problem. We also discuss the competitive model based on the super massive star nucleosynthesis.Comment: accepted for publication on MNRA