The rotational shear layer inside the early red-giant star KIC 4448777

We present the asteroseismic study of the early red-giant star KIC 4448777, complementing and integrating a previous work (Di Mauro et al. 2016), aimed at characterizing the dynamics of its interior by analyzing the overall set of data collected by the {\it Kepler} satellite during the four years of its first nominal mission. We adopted the Bayesian inference code DIAMOND (Corsaro \& De Ridder 2014) for the peak bagging analysis and asteroseismic splitting inversion methods to derive the internal rotational profile of the star. The detection of new splittings of mixed modes, more concentrated in the very inner part of the helium core, allowed us to reconstruct the angular velocity profile deeper into the interior of the star and to disentangle the details better than in Paper I: the helium core rotates almost rigidly about 6 times faster than the convective envelope, while part of the hydrogen shell seems to rotate at a constant velocity about 1.15 times lower than the He core. In particular, we studied the internal shear layer between the fast-rotating radiative interior and the slow convective zone and we found that it lies partially inside the hydrogen shell above $r \simeq 0.05R$ and extends across the core-envelope boundary. Finally, we theoretically explored the possibility for the future to sound the convective envelope in the red-giant stars and we concluded that the inversion of a set of splittings with only low-harmonic degree $l\leq 3$, even supposing a very large number of modes, will not allow to resolve the rotational profile of this region in detail.Comment: accepted for publication on Ap

Forecasting loss given default with the nearest neighbor algorithm

Mestrado em Matemática FinanceiraNos últimos anos, a previsão do Loss Given Default (LGD) tem sido um dos principais desafios no âmbito da gestão do risco de crédito. Investigadores académicos e profissionais da indústria bancária têm-se dedicado ao estudo deste parâmetro de risco em particular. Apesar de todas as diferentes abordagens já desenvolvidas e publicadas até hoje, a previsão do LGD continua a ser um tema de estudo académico intenso e sobre o qual ainda não existe um "consenso" metodológico na banca. Este trabalho apresenta uma abordagem alternativa para a previsão do LGD baseada na utilização de um simples, mas intuitivo, algoritmo de Machine Learning: o algoritmo nearest neighbor. De forma a avaliar a perfomance desta técnica não paramétrica na previsão do LGD, são utilizadas determinadas métricas de avaliação que permitem a comparação com um modelo paramétrico mais convencional e com a utilização do LGD médio histórico.In recent years, forecasting Loss Given Default (LGD) has been a major challenge in the field of credit risk management. Practitioners and academic researchers have focused on the study of this particular risk dimension. Despite all different approaches that have been developed and published so far, it remains an area of intense academic study and with lack of consensual solutions in the banking industry. This paper presents an LGD forecasting approach based on a simple and intuitive Machine Learning algorithm: the nearest neighbor algorithm. In order to evaluate the performance of this non parametric technique, some proper evaluation metrics are used to compare it to a more ?classical? parametric model and to the use of historical recovery rates to predict LGD

Effects of Knife Jointing and Wear on the Planed Surface Quality of Northern Red Oak Wood

Jointing is a technique to obtain the same cutting circle for all knives mounted in a cutterhead of a peripheral knife planer. Initially the jointed land at the cutting edge has a 0 degree clearance angle that becomes negative with workpiece motion relative to the cutterhead and as the cutting edge wears. Jointed knives may crush cells on the planed surface and affect the quality and performance of wood for end uses. We evaluated the gluing properties of northern red oak planed surfaces that had been planed using one of three jointed land widths, over four levels of knife wear. Under these cutting conditions, surface roughness significantly influenced gluability more than cellular damage. In sum, gluing performance was positively affected by knife wear, and no variation in gluing performance among the jointed land widths studied existed. In samples after accelerated aging, the effects of wear on gluing were more pronounced, with an improvement in gluing performance, associated with an increase in surface roughness and permeability with increased knife wear. These results suggest a jointed land of 1.2 mm as the maximum allowable width for planing red oak wood prior to gluing. Also, the planed surface gluability of this wood may be enhanced using a knife with the rake face recession of 332 μm and the clearance face recession of 438 μm, which results in a surface roughness of 40 μm Rmax

Equity research - Spotify Technology S.A.

Mestrado em FinançasEste projeto consiste numa avaliação do preço por ação da Spotify Technology S.A. para o final do ano de 2020, de acordo com o Mestrado em Finance do ISEG. Este relatório segue o formato aconselhado pelo CFA Institute (Pinto, Henry, Robison e Stowe, 2010), e reflete a informação pública da empresa até 24 de maio de 2019. Consequentemente, qualquer evento após esta data não foi considerado nesta análise. O preço sugerido para o final do ano de 2020 é de $145.21 por ação e quando comparado com o preço de 23 de maio de 2019 representa um potencial de valorização de 19.44Os principais riscos associados à nossa recomendação são a taxa de crescimento de utilizadores premium, a taxa de crescimento em perpetuidade, as taxas de retorno sem rico, entre outras variáveis. Estas variáveis são testadas através de análises de sensibilidade e através da simulação de Monte Carlo para prever o impacto das mesmas na nossa recomendação.This project consists on an Equity Research of Spotify Technology S.A. for the year end of 2020, according to ISEG?s Master Final Work in Finance. This report follows the format suggested by the CFA Institute (Pinto, Henry, Robison, and Stowe, 2010), and it reflects the public information of the company published until 24th of May of 2019. Consequently, any event following this date was not considered in this analysis. Our target price for the year end of 2020 is of$145.21 per share and when compared to the closing price of $121.58/share at 23rd of May of 2019 represents an upside potential of 19.44%. Our recommendation stands for a HOLD recommendation with a high risk associated. The main risks for this recommendation are growth rate of premium users, perpetual growth rate, unlevered beta, market risk premium, the risk-free rates and the overall WACC rate. Additionally, these variables are tested under sensitivity and Monte Carlo analysis to evaluate how changes in certain variables and assumptions would impact our final recommendation.info:eu-repo/semantics/publishedVersio

Export performance : the case of the exports of cork stoppers from Portugal to emergent economies

Export performance has always been a non-consensual topic in the field of International Business, despite being one of the most researched areas. This dissertation starts aiming at understanding the influence of internal factors to the firm, export market characteristics and export marketing strategy in the export venture of a firm. After presenting a literature review, it was explained the research questions, and a conceptual framework was presented. This dissertation’s methodology has been that of a case study, where exports of cork stoppers from Portugal to emergent economies were studied. The results support the contention that commitment with export activity, contribution of firm’s resources to the success of the venture, international business knowledge, export market characteristics, and export venture marketing strategy adaptation (influenced by the factors previously mentioned) are key factors to a successful export venture performance. Then theoretical and managerial findings are discussed and directions for further research are given

Delocalization and wave-packet dynamics in one-dimensional diluted Anderson models

We study the nature of one-electron eigen-states in a one-dimensional diluted Anderson model where every Anderson impurity is diluted by a periodic function $f(l)$ . Using renormalization group and transfer matrix techniques, we provide accurate estimates of the extended states which appear in this model, whose number depends on the symmetry of the diluting function $f(l)$. The density of states (DOS) for this model is also numerically obtained and its main features are related to the symmetries of the diluting function $f(l)$. Further, we show that the emergence of extended states promotes a sub-diffusive spread of an initially localized wave-packet.Comment: 6 pages, 6 figures, to appear in EPJ

Genetic diversity in a germplasm bank of Oenocarpus mapora (Arecaceae).

Oenocarpus mapora is an Amazonian palm species commonly used by native populations for food and in folk medicine. We measured genetic variability, using RAPD markers, of material kept in a germplasm bank composed of accessions sampled from the Brazilian Amazon. These included 74 individuals from 23 accessions sampled from 9 localities in three States of the Brazilian Amazon. Jaccard genetic similarities were calculated based on 137 polymorphic bands, amplified by 15 primers. Dendrograms constructed based on the genetic similarities among individuals and sample localities demonstrated genetic separation of Acre State from the States of Amazonas and Pará. Two models in three hierarchical levels were considered for AMOVA: one considering the grouping of sampling sites in each state, and the other considering sampling sites in each subgroup formed by the dendrograms. The first model showed no significant genetic variation among states. On the other hand, genetic variation among subgroups was significant. In this model, the within-sample-site genetic diversity was 47.15%, which is considered to be low, since O. mapora is allogamous. By means of Bayesian analysis, the sample sites were clustered into five groups, and their distribution was similar to what we found in the dendrograms based on genetic similarity