Morphometric analysis of a population of diplopods of the genus Rhinocricus Karsch, 1881

Diplopods belonging to the subclass Helminthomorpha may present one or both leg pairs of the seventh diplosegment modified into structures that aid copulation, called gonopods. These structures are used as a taxonomic trait for the description of most species. In the genus Rhinocricus these structures are closely similar, so that it is difficult to distinguish species only on the basis of this trait. Two species, R. padbergi and R. varians, are found in the same habitat and present gonopods practically identical in shape; together they present a broad colour gradient, ranging from dark brown to light beige. Morphometric data for individuals of the experimental group were submitted to ANOVA and MANOVA, using Hotelling-Lawley Trace and generalized Mahalanobis distances (D 2) tests. The results demonstrated a relationship between size and colour, with darker individuals being larger. On the basis of this preliminary analysis, we may suggest that the two species are distinct since dark individuals are distant from medium- and light-coloured individuals according to the D 2 values. This seems to indicate a possible polymorphism of individuals belonging to R. padbergi which present close proximity in the values obtained. In all analyses, we observed that the main variables were diameter, length and telson size.

An intelligent system to detect drilling problems through drilled cuttings return analysis

Cuttings return analysis is an important tool to detect and prevent problems during the petroleum well drilling process. Several measurements and tools have been developed for drilling problems detection, including mud logging, PWD and downhole torque information. Cuttings flow meters were developed in the past to provide information regarding cuttings return at the shale shakers. Their use, however, significantly impact the operation including rig space issues, interferences in geological analysis besides, additional personel required. This article proposes a non intrusive system to analyze the cuttings concentration at the shale shakers, which can indicate problems during drilling process, such as landslide, the collapse of the well borehole walls. Cuttings images are acquired by a high definition camera installed above the shakers and sent to a computer coupled with a data analysis system which aims the quantification and closure of a cuttings material balance in the well surface system domain. No additional people at the rigsite are required to operate the system. Modern Artificial intelligence techniques are used for pattern recognition and data analysis. Techniques include the Optimum-Path Forest (OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC). Field test results conducted on offshore floating vessels are presented. Results show the robustness of the proposed system, which can be also integrated with other data to improve the efficiency of drilling problems detection. Copyright 2010, IADC/SPE Drilling Conference and Exhibition.

Agricultural incentives, growth and poverty in Latin America and the Caribbean: cross-country evidence for the period 1960-2005. Did trade liberalization increase the incomes of the poorest?

Includes bibliography

Ex-post evaluation of the employment effects of a preferential trade agreement: methodological issues, illustrated with a reference to Chile

Includes bibliography

Estimating the effects of United States food safety and agricultural health standards on agro-food exports from Latin America and the Caribbean

Includes bibliography

Risk-adjusted poverty in Argentina: measurement and determinants

Includes bibliography

Peru: integration, sectoral specialization and synchronization with international gross domestic product cycles

Includes bibliography

An Integrative Genomic and Transcriptomic Analysis Reveals Potential Targets Associated with Cell Proliferation in Uterine Leiomyomas

Background: Uterine Leiomyomas (ULs) are the most common benign tumours affecting women of reproductive age. ULs represent a major problem in public health, as they are the main indication for hysterectomy. Approximately 40-50% of ULs have non-random cytogenetic abnormalities, and half of ULs may have copy number alterations (CNAs). Gene expression microarrays studies have demonstrated that cell proliferation genes act in response to growth factors and steroids. However, only a few genes mapping to CNAs regions were found to be associated with ULs. Methodology: We applied an integrative analysis using genomic and transcriptomic data to identify the pathways and molecular markers associated with ULs. Fifty-one fresh frozen specimens were evaluated by array CGH (JISTIC) and gene expression microarrays (SAM). The CONEXIC algorithm was applied to integrate the data. Principal Findings: The integrated analysis identified the top 30 significant genes (P<0.01), which comprised genes associated with cancer, whereas the protein-protein interaction analysis indicated a strong association between FANCA and BRCA1. Functional in silico analysis revealed target molecules for drugs involved in cell proliferation, including FGFR1 and IGFBP5. Transcriptional and protein analyses showed that FGFR1 (P = 0.006 and P<0.01, respectively) and IGFBP5 (P = 0.0002 and P = 0.006, respectively) were up-regulated in the tumours when compared with the adjacent normal myometrium. Conclusions: The integrative genomic and transcriptomic approach indicated that FGFR1 and IGFBP5 amplification, as well as the consequent up-regulation of the protein products, plays an important role in the aetiology of ULs and thus provides data for potential drug therapies development to target genes associated with cellular proliferation in ULs. © 2013 Cirilo et al.

Stress analysis in bone tissue around single implants with different diameters and veneering materials: A 3-D finite element study

The aimof this study was to evaluate the stress distribution on bone tissue with a single prosthesis supported by implants of large and conventional diameter and presenting different veneering materials using the 3-D finite elementmethod. Sixteenmodels were fabricated to reproduce a bone block with implants, using two diameters (3.75 × 10 mmand 5.00 × 10 mm), four different veneering materials (composite resin, acrylic resin, porcelain, and NiCr crown), and two loads (axial (200 N) and oblique (100 N)). For data analysis, the maximum principal stress and vonMises criterion were used. For the axial load, the cortical bone in allmodels did not exhibit significant differences, and the trabecular bone presented higher tensile stresswith reduced implant diameter. For the oblique load, the cortical bone presented a significant increase in tensile stress on the same side as the loading for smaller implant diameters. The trabecular bone showed a similar but more discreet trend. There was no difference in bone tissue with different veneering materials. The veneering material did not influence the stress distribution in the supporting tissues of single implant-supported prostheses. The large-diameter implants improved the transference of occlusal loads to bone tissue and decreased stress mainly under oblique loads.Oblique loading was more detrimental to distribution stresses than axial loading. © 2013 Elsevier B.V. All rights reserved.

O impacto da qualificação da mão-de-obra no desempenho comercial do Brasil

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Mexico: Combining monthly inflation predictions from surveys

We examine the problem of combining Mexican inflation predictions or projections provided by a biweekly survey of professional forecasters. Consumer price inflation in Mexico is measured twice a month. We consider several combining methods and advocate the use of dimension reduction techniques whose performance is compared with different benchmark methods, including the simplest average prediction. Missing values in the database are imputed by two different databased methods. The results obtained are basically robust to the choice of the imputation method. A preliminary analysis of the data was based on its panel data structure and showed the potential usefulness of using dimension reduction techniques to combine the experts' predictions. The main findings are: the first monthly predictions are best combined by way of the first principal component of the predictions available; the best second monthly prediction is obtained by calculating the median prediction and is more accurate than the first one.

Relação entre governança corporativa e gerenciamento de resultados: um estudo em empresas brasileiras listadas na BM&FBOVESPA

The objective of this work was to identify a possible relation between corporate governance, through the structure of the boards of directors and the levels of earnings management of Brazilian public companies. The study is characterized as a descriptive, of a hypothetical-deductive nature, with quantitative approach guided by the estimation model proposed by Kang and Sivaramakrishnan (1995). The sample was comprised by 56 companies, analyzed in the period from 2011 to 2014. The information on the companies were extracted from Economatica databank. For the data analysis, we used multivariate techniques, such as Pearson correlation and panel data in POLS, Fixed Effects and Random Effects approaches. Furthermore, we applied the mean comparison test ANOVA. The results obtained show that, generally, the organizations tend to follow the profile of boards of directors recommended by the codes of corporative governance. However, the characteristics of the composition of the board, regarding its size and the duality of positions that are not yet sufficient to be considered capable of inhibiting the discretionary practice of the studied companies. Relative the control variables, only size and return on equity presented no significant relation with result management. It is important to highlight that literature point many factors that explain the different impacts caused by the formation of the administration board in different regions or countries. Among the factors pointed, we highlight the legal system of the country, the economic and political development, the importance of the capital market, and the level of accounting education.

The impact of climate change on the tourism sector in the Caribbean

The main aim of this study is to estimate the economic impact of climate change on nine countries in the Caribbean basin: Aruba, Barbados, Dominican Republic, Guyana, Jamaica, Montserrat, Netherlands Antilles, Saint Lucia and Trinidad and Tobago. A typical tourism demand function, with tourist arrivals as the dependent variable, is used in the analysis. To establish the baseline, the period under analysis is 1989-2007 and the independent variables are destination country GDP per capita and consumer price index, source country GDP, oil prices to proxy transportation costs between source and destination countries. At this preliminary stage the climate variables are used separately to augment the tourism demand function to establish a relationship, if any, among the variables. Various econometric models (single OLS models for each country, pooled regression, GMM estimation and random effects panel models) were considered in an attempt to find the best way to model the data. The best fit for the data (1989-2007) is the random effects panel data model augmented by both climate variables, i.e. temperature and precipitation. Projections of all variables in the model for the 2008-2100 period were done using forecasting techniques. Projections for the climate variables were undertaken by INSMET. The cost of climate change to the tourism sector was estimated under three scenarios: A2, B2 and BAU (the mid-point of the A2 and B2 scenarios). The estimated costs to tourism for the Caribbean subregion under the three scenarios are all very high and ranges from US$43.9 billion under the B2 scenario to US$46.3 billion under the BAU scenario.

The impact of climate change on the macroeconomy in the Caribbean

In this study, an attempt is made to assess the economic impact of climate change on nine countries in the Caribbean basin: Aruba, Barbados, Dominican Republic, Guyana, Jamaica, Montserrat, Netherlands Antilles, Saint Lucia and Trinidad and Tobago. A methodological approach proposed by Dell et al. (2008) is used in preference to the traditional Integrated Assessment Models. The evolution of climate variables and of the macroeconomy of each of the nine countries over the period 1970 to 2006 is analyzed and preliminary evidence of a relationship between the macroeconomy and climate change is examined. The preliminary investigation uses correlation, Granger causality and simple regression methods. The preliminary evidence suggests that there is some relationship but that the direction of causation between the macroeconomy and the climate variables is indeterminate. The main analysis involves the use of a panel data (random effects) model which fits the historical data (1971-2007) very well. Projections of economic growth from 2008 to 2099 are done on the basis of four climate scenarios: the International Panel on Climate Change A2, B2, a hybrid A2B2 (the mid-point of A2 and B2), and a ‘baseline’ or ‘Business as Usual’ scenario, which assumes that the growth rate in the period 2008-2099 is the same as the average growth rate over the period 1971-2007. The best average growth rate is under the B2 scenario, followed by the hybrid A2B2 and A2 scenarios, in that order. Although negative growth rates eventually dominate, they are largely positive for a long time. The projections all display long-run secular decline in growth rates notwithstanding short-run upward trends, including some very sharp ones, moving eventually from declining positive rates to negative ones. The costs associated with the various scenarios are all quite high, rising to as high as a present value (2007 base year) of US$14 billion in 2099 (constant 1990 prices) for the B2 scenario and US$21 billion for the BAU scenario. These costs were calculated on the basis of very conservative estimates of the cost of environmental degradation. Mitigation and adaptation costs are likely to be quite high though a small fraction of projected total investment costs.

Ambiente data cleaning: suporte extensível, semântico e automático para análise e transformação de dados

Pós-graduação em Ciência da Computação - IBILCE