Consumption-Wealth Ratio and Expected Stock Returns: Evidence from Panel Data on G7 Countries

Using the theoretical framework of Lettau and Ludvigson (2001), we perform an empirical investigation on how widespread is the predictability of cay {a modi ed consumption-wealth ratio { once we consider a set of important countries from a global perspective. We chose to work with the set of G7 countries, which represent more than 64% of net global wealth and 46% of global GDP at market exchange rates. We evaluate the forecasting performance of cay using a panel-data approach, since applying cointegration and other time-series techniques is now standard practice in the panel-data literature. Hence, we generalize Lettau and Ludvigson's tests for a panel of important countries. We employ macroeconomic and nancial quarterly data for the group of G7 countries, forming an unbalanced panel. For most countries, data is available from the early 1990s until 2014Q1, but for the U.S. economy it is available from 1981Q1 through 2014Q1. Results of an exhaustive empirical investigation are overwhelmingly in favor of the predictive power of cay in forecasting future stock returns and excess returns.

The history of the introduction of the giant river prawn, Macrobrachium cf. rosenbergii (Decapoda, Palaemonidae), in Brazil: new insights from molecular data

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Performance of advanced generation from a hybrid Japanese cucumber

A endogamia reduz o vigor em plantas pela diminuição da proporção de loci heterozigotos. Entretanto, a influência da endogamia é diferente entre as espécies. O objetivo deste trabalho foi avaliar a depressão causada por endogamia em uma população de pepino do tipo japonês. A partir do intercruzamento entre plantas do híbrido Natsu suzumi foi obtida a geração F2, considerada como população S0. Obtiveram-se progênies S1, S2, S3, S4 e S5, através de autofecundações sucessivas pelo método do SSD ('Single Seed Descent'). Foram sete tratamentos (híbrido Natsu suzumi, populações S0 a S5) e o delineamento experimental foi em blocos ao acaso, com seis repetições e cinco plantas por parcela cultivadas em ambiente protegido de 21/08/2002 à 29/11/2002. Foram avaliados o número de folhas, semanalmente, o número e a massa de frutos, total e comercial, número de nós e porcentagem de nós com brotações laterais. Na comparação entre as populações S0 a S5 não foram observadas diferenças para todas as características avaliadas demonstrando não haver perda de vigor por endogamia nesta população.

Extraction of Building Roof Contours From LiDAR Data Using a Markov-Random-Field-Based Approach

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Mass generation from Lie algebra extensions

Applied to the electroweak interactions, the theory of Lie algebra extensions suggests a mechanism by which the boson masses are generated without resource to spontaneous symmetry breaking. It starts from a gauge theory without any additional scalar field. All the couplings predicted by the Weinberg-Salam theory are present, and a few others which are nevertheless consistent within the model.

Bounds on contact interactions from LEP1 data and high-Q2 HERA events

A contact four-fermion interaction between light quarks and electrons has been evoked as a possible explanation for the excess of events observed by HERA at high-Q2. We explore the 1-loop effects of such interaction in Γ(Z0 → e+e-) measured at LEP and impose strong bounds on the lower limit of the effective scale. Our results are able to discard some of the contact interactions as possible explanation for the HERA events. © 1997 Elsevier Science B.V.

Bounds on Higgs and gauge-boson interactions from LEP2 data

We derive bounds on Higgs and gauge-boson anomalous interactions using the LEP2 data on the production of three photons and photon pairs in association with hadrons. In the framework of SU(2)L ⊗ U(1)Y effective Lagrangians, we examine all dimension-six operators that lead to anomalous Higgs interactions involving γ and Z. The search for Higgs boson decaying to γγ pairs allow us to obtain constrains on these anomalous couplings that are comparable with the ones originating from the analysis of pp̄ collisions at the Tevatron. Our results also show that if the coefficients of all blind operators are assumed to have the same magnitude, the indirect constraints on the anomalous couplings obtained from this analysis, for Higgs masses MH ≲ 140 GeV, are more restrictive than the ones coming from the W+W- production. © 1998 Elsevier Science B.V. All rights reserved.

Integrating open source codes for solid modeling and automatic mesh generation in FEM applications

The applications of the Finite Element Method (FEM) for three-dimensional domains are already well documented in the framework of Computational Electromagnetics. However, despite the power and reliability of this technique for solving partial differential equations, there are only a few examples of open source codes available and dedicated to the solid modeling and automatic constrained tetrahedralization, which are the most time consuming steps in a typical three-dimensional FEM simulation. Besides, these open source codes are usually developed separately by distinct software teams, and even under conflicting specifications. In this paper, we describe an experiment of open source code integration for solid modeling and automatic mesh generation. The integration strategy and techniques are discussed, and examples and performance results are given, specially for complicated and irregular volumes which are not simply connected. © 2011 IEEE.

Building roof contour extraction from LiDAR data

This paper proposes a method for the automatic extraction of building roof contours from a LiDAR-derived digital surface model (DSM). The method is based on two steps. First, to detect aboveground objects (buildings, trees, etc.), the DSM is segmented through a recursive splitting technique followed by a region merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. Preliminary results have shown that the proposed methodology works properly.

Methodology for the measurement of current fertility from population data on young children

Includes bibliography

Latin America: evaluation of the demographic situation in the period 1970-1975. Comparison of previous estimates with those derived from recent data

Includes bibliography

Particle competition and cooperation to prevent error propagation from mislabeled data in semi-supervised learning

Semi-supervised learning is applied to classification problems where only a small portion of the data items is labeled. In these cases, the reliability of the labels is a crucial factor, because mislabeled items may propagate wrong labels to a large portion or even the entire data set. This paper aims to address this problem by presenting a graph-based (network-based) semi-supervised learning method, specifically designed to handle data sets with mislabeled samples. The method uses teams of walking particles, with competitive and cooperative behavior, for label propagation in the network constructed from the input data set. The proposed model is nature-inspired and it incorporates some features to make it robust to a considerable amount of mislabeled data items. Computer simulations show the performance of the method in the presence of different percentage of mislabeled data, in networks of different sizes and average node degree. Importantly, these simulations reveals the existence of the critical points of the mislabeled subset size, below which the network is free of wrong label contamination, but above which the mislabeled samples start to propagate their labels to the rest of the network. Moreover, numerical comparisons have been made among the proposed method and other representative graph-based semi-supervised learning methods using both artificial and real-world data sets. Interestingly, the proposed method has increasing better performance than the others as the percentage of mislabeled samples is getting larger. © 2012 IEEE.

Technology, trade and skills in Brazil: evidence from micro data

Includes bibliography

Simulated annealing for building roof contours identification from lidar data

This paper proposes a method by simulated annealing for building roof contours identification from LiDAR-derived digital elevation model. Our method is based on the concept of first extracting aboveground objects and then identifying those objects that are building roof contours. First, to detect aboveground objects (buildings, trees, etc.), the digital elevation model is segmented through a recursive splitting technique followed by a region merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. The solution of this function is a polygon set corresponding to building roof contours and is found by using a minimization technique, like the Simulated Annealing algorithm. Experiments carried out with laser scanning digital elevation model showed that the methodology works properly, as it provides roof contour information with approximately 90% shape accuracy and no verified false positives.

Are fertility estimates from retrospective data biased by maternal mortality?: an assessment based on parametric models of family size distribution

Includes bibliography