Topworking of 'Bengal' lychee trees in the state of São Paulo, Brazil

This study aimed to evaluate the performance of 'Feizixiao', 'Nuomici', 'Heiye', 'Kway May Pink' and 'Bengal' lychee cultivars topworked onto bearing 'Bengal' trees. The experiments were carried out in commercial orchard at Rio das Pedras Farm in Jundiaí, state of São Paulo. The experimental design consisted of randomized blocks in a subdivided parcel arrangement, in which the parcel consisted of five cultivars and the sub-parcel consisted of six evaluation periods. Five replicates of three plants per parcel and six grafts per plant, (with two grafts per main branch) were used. The trees were approximately 10 years old propagated by air layering and planted with 6 x 4 m (416 plants/ha) spacing. The following characteristics were evaluated: success rate of the grafts, number of shoots, shoot length, number of nodes, number of leaves and chlorophyll content (SPAD). The control ('Bengal'/'Bengal') had the highest grafting success rate with 89.9%. On the other hand, 'Heiye', 'Feizixião', 'Nuomici' and 'Kway May Pink' had, respectively, 60.6, 55.0, 52.6 and 47.0% grafting success rates. All of the shoot grafts had normal growth with no signs of incompatibility. Therefore, the cultivars studied are compatible with 'Bengal' and may be used on commercial orchards.

Systematic analysis of factors associated with progression and regression of ulcerative colitis in 918 patients.

BACKGROUND: Studies that systematically assess change in ulcerative colitis (UC) extent over time in adult patients are scarce. AIM: To assess changes in disease extent over time and to evaluate clinical parameters associated with this change. METHODS: Data from the Swiss IBD cohort study were analysed. We used logistic regression modelling to identify factors associated with a change in disease extent. RESULTS: A total of 918 UC patients (45.3% females) were included. At diagnosis, UC patients presented with the following disease extent: proctitis [199 patients (21.7%)], left-sided colitis [338 patients (36.8%)] and extensive colitis/pancolitis [381 (41.5%)]. During a median disease duration of 9 [4-16] years, progression and regression was documented in 145 patients (15.8%) and 149 patients (16.2%) respectively. In addition, 624 patients (68.0%) had a stable disease extent. The following factors were identified to be associated with disease progression: treatment with systemic glucocorticoids [odds ratio (OR) 1.704, P = 0.025] and calcineurin inhibitors (OR: 2.716, P = 0.005). No specific factors were found to be associated with disease regression. CONCLUSIONS: Over a median disease duration of 9 [4-16] years, about two-thirds of UC patients maintained the initial disease extent; the remaining one-third had experienced either progression or regression of the disease extent.

ICA as a preprocessing technique for classification

In this paper we propose the use of the independent component analysis (ICA) [1] technique for improving the classification rate of decision trees and multilayer perceptrons [2], [3]. The use of an ICA for the preprocessing stage, makes the structure of both classifiers simpler, and therefore improves the generalization properties. The hypothesis behind the proposed preprocessing is that an ICA analysis will transform the feature space into a space where the components are independent, and aligned to the axes and therefore will be more adapted to the way that a decision tree is constructed. Also the inference of the weights of a multilayer perceptron will be much easier because the gradient search in the weight space will follow independent trajectories. The result is that classifiers are less complex and on some databases the error rate is lower. This idea is also applicable to regression

Regression-based techniques for statistical decision making in single-case designs

The present study evaluates the performance of four methods for estimating regression coefficients used to make statistical decisions regarding intervention effectiveness in single-case designs. Ordinary least squares estimation is compared to two correction techniques dealing with general trend and one eliminating autocorrelation whenever it is present. Type I error rates and statistical power are studied for experimental conditions defined by the presence or absence of treatment effect (change in level or in slope), general trend, and serial dependence. The results show that empirical Type I error rates do not approximate the nominal ones in presence of autocorrelation or general trend when ordinary and generalized least squares are applied. The techniques controlling trend show lower false alarm rates, but prove to be insufficiently sensitive to existing treatment effects. Consequently, the use of the statistical significance of the regression coefficients for detecting treatment effects is not recommended for short data series.

Abacavir/Lamivudine Versus Tenofovir/Emtricitabine in Virologically Suppressed Patients Switching from Ritonavir-Boosted Protease Inhibitors to Raltegravir

There are few clinical data on the combination abacavir/lamivudine plus raltegravir. We compared the outcomes of patients from the SPIRAL trial receiving either abacavir/lamivudine or tenofovir/emtricitabine at baseline who had taken at least one dose of either raltegravir or ritonavir-boosted protease inhibitors. For the purpose of this analysis, treatment failure was defined as virological failure (confirmed HIV-1 RNA ≥50 copies/ml) or discontinuation of abacavir/lamivudine or tenofovir/emtricitabine because of adverse events, consent withdrawal, or lost to follow-up. There were 143 (72.59%) patients with tenofovir/emtricitabine and 54 (27.41%) with abacavir/lamivudine. In the raltegravir group, there were three (11.11%) treatment failures with abacavir/lamivudine and eight (10.96%) with tenofovir/emtricitabine (estimated difference 0.15%; 95% CI -17.90 to 11.6). In the ritonavir-boosted protease inhibitor group, there were four (14.81%) treatment failures with abacavir/lamivudine and 12 (17.14%) with tenofovir/emtricitabine (estimated difference -2.33%; 95% CI -16.10 to 16.70). Triglycerides decreased and HDL cholesterol increased through the study more pronouncedly with abacavir/lamivudine than with tenofovir/emtricitabine and differences in the total-to-HDL cholesterol ratio between both combinations of nucleoside reverse transcriptase inhibitors (NRTIs) tended to be higher in the raltegravir group, although differences at 48 weeks were not significant. While no patient discontinued abacavir/lamivudine due to adverse events, four (2.80%) patients (all in the ritonavir-boosted protease inhibitor group) discontinued tenofovir/emtricitabine because of adverse events (p=0.2744). The results of this analysis do not suggest that outcomes of abacavir/lamivudine are worse than those of tenofovir/emtricitabine when combined with raltegravir in virologically suppressed HIV-infected adults.

Effects of unit - based pricing on the waste collection demand : a meta - regression analysis

We perform a meta - analysis of 21 studies that estimate the elasticity of the price of waste collection demand upon waste quantities, a prior literature review having revealed that the price elasticity differs markedly. Based on a meta - regression with a total of 65 observations, we find no indication that municipal data give higher estimates for price elasticities than those associated with household data. Furthermore, there is no evidence that treating prices as exogenous underestimates the price elasticity. We find that much of the variation can be explained by sample size, the use of a weight - based as opposed to a volume - based pricing system, and the pricing of compostable waste. We also show that price elasticities determined in the USA and point estimations of elasticities are more elastic, but these effects are not robust to the changing of model specifications. Finally, our tests show that there is no evidence of publication bias while there is some evidence of the existence of genuine empirical effect.

The environmental effects of changing speed limits: a quantile regression approach

Two speed management policies were implemented in the metropolitan area of Barcelona aimed at reducing air pollution concentration levels. In 2008, the maximum speed limit was reduced to 80 km/h and, in 2009, a variable speed system was introduced on some metropolitan motorways. This paper evaluates whether such policies have been successful in promoting cleaner air, not only in terms of mean pollutant levels but also during high and low pollution episodes. We use a quantile regression approach for fixed effect panel data. We find that the variable speed system improves air quality with regard to the two pollutants considered here, being most effective when nitrogen oxide levels are not too low and when particulate matter concentrations are below extremely high levels. However, reducing the maximum speed limit from 120/100 km/h to 80 km/h has no effect – or even a slightly increasing effect –on the two pollutants, depending on the pollution scenario. Length: 32 pages

A Hierarchical Approach for Multi-task Logistic Regression

Peer-reviewed

Regression analysis of compositional data when both the dependent variable and independent variable are components

It is well known that regression analyses involving compositional data need special attention because the data are not of full rank. For a regression analysis where both the dependent and independent variable are components we propose a transformation of the components emphasizing their role as dependent and independent variables. A simple linear regression can be performed on the transformed components. The regression line can be depicted in a ternary diagram facilitating the interpretation of the analysis in terms of components. An exemple with time-budgets illustrates the method and the graphical features

The causal factors of international inequality in CO2 emissions per capita: a regression-based inequality decomposition analysis

This paper uses the possibilities provided by the regression-based inequality decomposition (Fields, 2003) to explore the contribution of different explanatory factors to international inequality in CO2 emissions per capita. In contrast to previous emissions inequality decompositions, which were based on identity relationships (Duro and Padilla, 2006), this methodology does not impose any a priori specific relationship. Thus, it allows an assessment of the contribution to inequality of different relevant variables. In short, the paper appraises the relative contributions of affluence, sectoral composition, demographic factors and climate. The analysis is applied to selected years of the period 1993–2007. The results show the important (though decreasing) share of the contribution of demographic factors, as well as a significant contribution of affluence and sectoral composition.

Optimization of wood flour acetylation by factorial design and partial least squares regression

Acetylation was performed to reduce the polarity of wood and increase its compatibility with polymer matrices for the production of composites. These reactions were performed first as a function of acetic acid and anhydride concentration in a mixture catalyzed by sulfuric acid. A concentration of 50%/50% (v/v) of acetic acid and anhydride was found to produced the highest conversion rate between the functional groups. After these reactions, the kinetics were investigated by varying times and temperatures using a 3² factorial design, and showed time was the most relevant parameter in determining the conversion of hydroxyl into carbonyl groups.