Competition policies in emerging economies: lessons and challenges from Central America and Mexico

Incluye Bibliografía

Models of privatization and development of competition in telecommunications in Central America and Mexico

Incluye Bibliografía

Competition and regulation in the banking system of Central America and Mexico: a comparative study

Incluye Bibliografía

Advantages and limitations of Costa Rica's experience in competition policy. A benchmark for the rest of the countries in the Central American region

Incluye Bibliografía

Banking competition in Mexico

Incluye Bibliografía

Cooperation on competition policy in Latin American and Caribbean bilateral trade agreements

Incluye Bibliografía

Legal and economic interfaces between antidumping and competition policy

Includes bibliography

Multilateral rules on competition policy: an overview of the debate

Includes bibliography

Policy competition for foreign direct investment in the Caribbean Basin: Costa Rica, the Dominican Republic and Jamaica

Includes bibliography

The effectiveness of technical assistance, socio-economic development and the absorptive capacity of competition authorities

Includes bibliography

Best practices in defence of competition in Argentina and Brazil: useful aspects for Central America

Includes bibliography

Efeitos de diferentes tipos de poda nos teores de nutrients emflores e frutos de goiabeira

A better understanding of the differences between the levels of nutrients, depending on the type of pruning used in the cultivation of the guava tree, may allow a more adequate understanding of the physiological processes of this fruit. The analysis of flowers is a tool that can be used to assist in assessing the nutritional status of crops, especially perennials. We evaluated the effects of different types of pruning on nutrient concentrations in flowers and fruit, at different developmental stages and in different parts of the fruit. The study was carried out in Vista Alegre do Alto, in orchards of guava variety Paluma. Flowers and fruit were collected in orchards, one under heavy pruning and the other with continuous pruning. The fruit were collected in two stages (two millimeters length and mature) and divided into basal part and apex, with the top toward the stalk. Flowers were collected in the same orchards as the fruits, sampling the basal part and apex of the flowers. F tests were performed and, when necessary, the Scott-Knott test at α= 5%. Overall, there were nutritional differences among flowers and fruits in relation to the type of pruning employed; drastic pruning provided higher levels of nutrients compared with continuous pruning. In relation to the portion of the samples, especially for fruit, there were differences between the apex and base, as well as between different stages of fruit collection.

Competition, oligopoly and technological change in the construction industry: the Argentine case

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.

MERCOSUR: its challenges to small and medium-sized industrial enterprises in terms of competition

Includes bibliography