The mouse secretome: functional classification of the proteins secreted into the extracellular environment

We have developed a computational strategy to identify the set of soluble proteins secreted into the extracellular environment of a cell. Within the protein sequences predominantly derived from the RIKEN representative transcript and protein set, we identified 2033 unique soluble proteins that are potentially secreted from the cell. These proteins contain a signal peptide required for entry into the secretory pathway and lack any transmembrane domains or intracellular localization signals. This class of proteins, which we have termed the mouse secretome, included >500 novel proteins and 92 proteins

The over-production of US sports and the new International Division of Cultural Labor

This article focuses on how US professional sports utilize the New International Division of Cultural Labor to supplement an overly costly local labor pool and over-supplied local market. We argue that while the classic problem of over-production is slowly eroding the sealed-off nature of US culture, the forces of its hyper-protectionist capitalism continue to characterize sports, precluding equal exchange.

Uprootedness and the protection of migrants in the International Law of Human Rights

The article attempt to demonstrate the evolution of international law in connected to the subject of the forced immigrants'. The author supported by several texts, cases and resolutions of the regional level, through interamerican court and European court, and the global level, through the international court. It's shown the evolution that occurred in international law in millennium turn over, which recognize the immigrants' rights. However, it's stressed the necessity of the development of those laws connected to the theme e the recognition, from the States; the importance of law's that effort to ensure the respect to human rights relative to the immigrants and their families.

The international implications of the Chinese model of development in the Global South: Asian Consensus as a network power

This paper analyzes People's Republic of China (PRC) economic and political ascendance in the 21st century focusing on the evolution of the sui generis economic development model and its significances of the evolution of relationship between China and the developing countries in the peripheral "Global South." The objective of this article is to analyze the relationship between China and the Global South (Africa and South America) in the 21st century, characterized as a new Center-periphery global network power based on trade and investment that we call as "Asian Consensus."

International drivers of Brazilian agricultural cooperation in Africa in the post-2008 economic crisis

This text focuses on the major drivers of Brazilian agricultural cooperation in Africa as conceived and pursued from 2004 to 2014, with emphasis on the impacts of political and economic international changes that took place in that period, and particularly the impacts of the 2008 economic crisis, in framing Brazil's foreign policy and development assistance initiatives. It addresses current international forces and developments at the systemic level, but also analyses recent economic domestic developments, in particular those directly related to Brazilian agriculture and those related to the policy framework of its evolving internationalization. Special attention is paid to the dual dimensions of Brazilian agricultural policy and to its projection in agricultural cooperation as pursed in Africa.

Comparison of methods for classification of the coefficient of variation in papaya

ABSTRACT The objective of this work was to study the distribution of values of the coefficient of variation (CV) in the experiments of papaya crop (Carica papaya L.) by proposing ranges to guide researchers in their evaluation for different characters in the field. The data used in this study were obtained by bibliographical review in Brazilian journals, dissertations and thesis. This study considered the following characters: diameter of the stalk, insertion height of the first fruit, plant height, number of fruits per plant, fruit biomass, fruit length, equatorial diameter of the fruit, pulp thickness, fruit firmness, soluble solids and internal cavity diameter, from which, value ranges were obtained for the CV values for each character, based on the methodology proposed by Garcia, Costa and by the standard classification of Pimentel-Gomes. The results obtained in this study indicated that ranges of CV values were different among various characters, presenting a large variation, which justifies the necessity of using specific evaluation range for each character. In addition, the use of classification ranges obtained from methodology of Costa is recommended.

THE INTERNATIONAL GROWTH OF A SOCIAL BUSINESS: A CASE STUDY

ABSTRACTIn developing countries, initiatives have often been undertaken in order to fight social and environmental problems. Since the 1990s, an increase can be seen in corporate social responsibility actions, as well as increasingly strong activities by civil society organizations. Tweenty years ago, companies and civil society organizations stood wide apart from each other, with often conflicting agendas and resistance to mutual collaboration. This reality has changed significantly. Besides the phenomenon of cross-sector partnerships, we can also observe the expansion of a particular organization type, i.e., the social business, which combines two objectives that were previously seen as incompatible: financial sustainability and the generation of social value. This article aims to discuss the factors that influence the results of a social business operating in three countries: Botswana, Brazil and Jordan. The results allow understanding the challenges involved in constructing social businesses in developing countries as well as a better understanding of the very nature of those businesses, considering the social realities where they operate.

Multi-attribute classification of housing conservation status in urban regeneration actions

Urban regeneration is more and more a “universal issue” and a crucial factor in the new trends of urban planning. It is no longer only an area of study and research; it became part of new urban and housing policies. Urban regeneration involves complex decisions as a consequence of the multiple dimensions of the problems that include special technical requirements, safety concerns, socio-economic, environmental, aesthetic, and political impacts, among others. This multi-dimensional nature of urban regeneration projects and their large capital investments justify the development and use of state-of-the-art decision support methodologies to assist decision makers. This research focuses on the development of a multi-attribute approach for the evaluation of building conservation status in urban regeneration projects, thus supporting decision makers in their analysis of the problem and in the definition of strategies and priorities of intervention. The methods presented can be embedded into a Geographical Information System for visualization of results. A real-world case study was used to test the methodology, whose results are also presented.

Statistical classification of road pavements using near field vehicle rolling noise measurements

Low noise surfaces have been increasingly considered as a viable and cost-effective alternative to acoustical barriers. However, road planners and administrators frequently lack information on the correlation between the type of road surface and the resulting noise emission profile. To address this problem, a method to identify and classify different types of road pavements was developed, whereby near field road noise is analyzed using statistical learning methods. The vehicle rolling sound signal near the tires and close to the road surface was acquired by two microphones in a special arrangement which implements the Close-Proximity method. A set of features, characterizing the properties of the road pavement, was extracted from the corresponding sound profiles. A feature selection method was used to automatically select those that are most relevant in predicting the type of pavement, while reducing the computational cost. A set of different types of road pavement segments were tested and the performance of the classifier was evaluated. Results of pavement classification performed during a road journey are presented on a map, together with geographical data. This procedure leads to a considerable improvement in the quality of road pavement noise data, thereby increasing the accuracy of road traffic noise prediction models.

Data mining techniques to support the classification of MV electricity customers

This paper describes a methodology that was developed for the classification of Medium Voltage (MV) electricity customers. Starting from a sample of data bases, resulting from a monitoring campaign, Data Mining (DM) techniques are used in order to discover a set of a MV consumer typical load profile and, therefore, to extract knowledge regarding to the electric energy consumption patterns. In first stage, it was applied several hierarchical clustering algorithms and compared the clustering performance among them using adequacy measures. In second stage, a classification model was developed in order to allow classifying new consumers in one of the obtained clusters that had resulted from the previously process. Finally, the interpretation of the discovered knowledge are presented and discussed.

Contributo para a construção de um code set da classificação internacional de funcionalidade, incapacidade e saúde, para terapeutas ocupacionais, em unidades de cuidados continuados integrados

A CIF é uma ferramenta universal desenvolvida pela OMS que permite a classificação de funcionalidade e incapacidade, através de uma visualização global do que condiciona o desempenho do indivíduo na concretização de atividades e na participação em ocupações. A ideologia da CIF e os seus componentes interrelacionam-se com a essência da TO, indo ao encontro dos modelos da profissão. As UCCI constituem uma atualidade em Portugal e o terapeuta ocupacional é um dos profissionais obrigatórios na equipa multidisciplinar destas unidades. Atendendo à relevância internacional da CIF, à sua ligação com a TO e à necessidade de tornar a CIF operacional na prática clínica diária dado que é uma ferramenta complexa e extensa, é objetivo deste estudo contribuir para a construção de um code set da CIF para terapeutas ocupacionais que exercem funções em UCCI, especificamente em UC, UMDR e ULDM. Para a concretização desta investigação, utilizou-se a técnica de Delphi, que envolveu duas rondas. Na primeira ronda foi possível contar com a participação de 37 terapeutas ocupacionais experientes na área, uma vez que exercem funções em UCCI, e na segunda ronda contou-se com a participação de 20 elementos. Obtiveram consenso na última ronda de Delphi um total de 96 categorias, constituindo esta listagem uma proposta de code set para UCCI. No que se refere às tipologias de unidades, 69 categorias obtiveram consenso em UC, 91 em UMDR e 41 em ULDM. Concluiu-se que a criação de code sets poderá constituir uma mais-valia em contexto de equipa multidisciplinar das UCCI, sendo uma forma de tornar a CIF operacional na prática clínica diária.

Effects of international diffusion of a general purpose technology on wage inequality

This paper studies the effects of the diffusion of a General Purpose Technology (GPT) that spreads first within the developed North country of its origin, and then to a developing South country. In the developed general equilibrium growth model, each final good can be produced by one of two technologies. Each technology is characterized by a specific labor complemented by a specific set of intermediate goods, which are enhanced periodically by Schumpeterian R&D activities. When quality reaches a threshold level, a GPT arises in one of the technologies and spreads first to the other technology within the North. Then, it propagates to the South, following a similar sequence. Since diffusion is not even, neither intra- nor inter-country, the GPT produces successive changes in the direction of technological knowledge and in inter- and intra-country wage inequality. Through this mechanism the different observed paths of wage inequality can be accommodated.

Gender and racial inequalities in trends of oral cancer mortality in Sao Paulo, Brazil

OBJECTIVE:To analyse recent trends in oral cancer mortality, focusing specifically on differences concerning gender and race.METHODS:Official information on deaths and population in the city of Sao Paulo, 2003 to 2009, were used to estimate mortality rates from oral cancer (C00 to C10, International Classification of Diseases, 10th Revision), adjusted for age and stratified by gender (females and males) and race (blacks and whites). The Prais-Winsten auto-regression procedure was used to analyse the time series.RESULTS:During the study period, 8,505 individuals living in the city of Sao Paulo died of oral cancer. Rates increased for females (rate of yearly increase = 4.4%, 95%CI 1.4;7.5), and levelled off for men, which represents an inversion of previous trends among genders in the city. Increases were identified for blacks, with a high rate of yearly increase of 9.1% (95%CI 5.5;12.9), and levelled off for whites. Oral cancer mortality in blacks almost doubled during the study period, and surpassed mortality in whites for almost all categories.CONCLUSIONS:Mortality presented a higher increase among women than in men, and it doubled among backs. The surveillance of trends of oral cancer mortality across gender and racial groups may contribute to implementing socially appropriate health policies, which concurrently reduce the burden of disease and the attenuation of unfair, avoidable and unnecessary inequalities in health.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.