Biological Characteristics and Thermal Requirements of the Biological Control Agent Telenomus remus (Hymenoptera: Platygastridae) Reared on Eggs of Different Species of the Genus Spodoptera (Lepidoptera: Noctuidae)

The biological characteristics of Telenomus remus Nixon, 1937 (Hymenoptera: Platygastridae) on eggs of Spodoptera albula (Walker, 1857); S. cosmioides Walker 1858, S. eridania (Cramer, 1782); and S. frugiperda (Smith, 1797) (Lepidoptera: Noctuidae) were evaluated under different temperatures (19, 22, 25, 28, 31, and 34 degrees C +/- 1 degrees C). The duration of the T remus egg-to-adult period on eggs of all four Spodoptera species and the longevity of adults of T. remus were both inversely proportional to the increase in temperature. Parasitoid emergence was higher than 80% at temperatures from 19 to 28 degrees C when the parasitoid was reared on eggs of S. eridania and S. frugiperda. Differently, when the parasitoid was reared on eggs of S. albula and S. cosmioides, T. remus emergence at rates of 80% or higher just occurred from 22 to 25 degrees C and at 22 degrees C, respectively. At 34 degrees C, this parameter was lower than 30% for T reams reared in all hosts. The sex ratio was 64-86% females, except for T. remus in S. cosmioides eggs at 34 C, in which temperature it was 39%. The estimated thermal requirements of T. remus, for the thermal constant (K) and the base temperature (T(base)), were: 125.39 DD and 15.139 degrees C; 125.56 DD and 14.912 degrees C; 142.98 DD and 14.197 degrees C; and 149.16 DD and 13.846 degrees C, for S. cosmioides, S. frugiperda, S. albula, and S. eridania, respectively. In general, T. remus showed good parasitism potential on all the hosts, although eggs of S. frugiperda, S. eridania, and S. albula proved to be the most suitable for mass rearing of T reams in the laboratory. Eggs of S. cosmioides are less suitable because of the lower parasitoid emergence observed at most of the temperatures with exception of 22 degrees C.

Rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART): Study protocol for a randomized controlled trial

Background: Acute respiratory distress syndrome (ARDS) is associated with high in-hospital mortality. Alveolar recruitment followed by ventilation at optimal titrated PEEP may reduce ventilator-induced lung injury and improve oxygenation in patients with ARDS, but the effects on mortality and other clinical outcomes remain unknown. This article reports the rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART). Methods/Design: ART is a pragmatic, multicenter, randomized (concealed), controlled trial, which aims to determine if maximum stepwise alveolar recruitment associated with PEEP titration is able to increase 28-day survival in patients with ARDS compared to conventional treatment (ARDSNet strategy). We will enroll adult patients with ARDS of less than 72 h duration. The intervention group will receive an alveolar recruitment maneuver, with stepwise increases of PEEP achieving 45 cmH(2)O and peak pressure of 60 cmH2O, followed by ventilation with optimal PEEP titrated according to the static compliance of the respiratory system. In the control group, mechanical ventilation will follow a conventional protocol (ARDSNet). In both groups, we will use controlled volume mode with low tidal volumes (4 to 6 mL/kg of predicted body weight) and targeting plateau pressure <= 30 cmH2O. The primary outcome is 28-day survival, and the secondary outcomes are: length of ICU stay; length of hospital stay; pneumothorax requiring chest tube during first 7 days; barotrauma during first 7 days; mechanical ventilation-free days from days 1 to 28; ICU, in-hospital, and 6-month survival. ART is an event-guided trial planned to last until 520 events (deaths within 28 days) are observed. These events allow detection of a hazard ratio of 0.75, with 90% power and two-tailed type I error of 5%. All analysis will follow the intention-to-treat principle. Discussion: If the ART strategy with maximum recruitment and PEEP titration improves 28-day survival, this will represent a notable advance to the care of ARDS patients. Conversely, if the ART strategy is similar or inferior to the current evidence-based strategy (ARDSNet), this should also change current practice as many institutions routinely employ recruitment maneuvers and set PEEP levels according to some titration method.

Transverse single-spin asymmetry and cross section for pi(0) and eta mesons at large Feynman x in p(up arrow) + p collisions at root s=200 GeV

Measurements of the differential cross section and the transverse single-spin asymmetry, A(N), vs x(F) for pi(0) and eta mesons are reported for 0.4 < x(F) < 0.75 at an average pseudorapidity of 3.68. A data sample of approximately 6.3 pb(-1) was analyzed, which was recorded during p(up arrow) + p collisions at root s = 200 GeV by the STAR experiment at RHIC. The average transverse beam polarization was 56%. The cross section for pi(0), including the previously unmeasured region of x(F) > 0.55, is consistent with a perturbative QCD prediction, and the eta/pi(0) cross-section ratio agrees with existing midrapidity measurements. For 0.55 < x(F) < 0.75, the average A(N) for eta is 0.210 +/- 0.056, and that for pi(0) is 0.081 +/- 0.016. The probability that these two asymmetries are equal is similar to 3%.

On the impact of disproportional samples in credit scoring models: An application to a Brazilian bank data

Statistical methods have been widely employed to assess the capabilities of credit scoring classification models in order to reduce the risk of wrong decisions when granting credit facilities to clients. The predictive quality of a classification model can be evaluated based on measures such as sensitivity, specificity, predictive values, accuracy, correlation coefficients and information theoretical measures, such as relative entropy and mutual information. In this paper we analyze the performance of a naive logistic regression model (Hosmer & Lemeshow, 1989) and a logistic regression with state-dependent sample selection model (Cramer, 2004) applied to simulated data. Also, as a case study, the methodology is illustrated on a data set extracted from a Brazilian bank portfolio. Our simulation results so far revealed that there is no statistically significant difference in terms of predictive capacity between the naive logistic regression models and the logistic regression with state-dependent sample selection models. However, there is strong difference between the distributions of the estimated default probabilities from these two statistical modeling techniques, with the naive logistic regression models always underestimating such probabilities, particularly in the presence of balanced samples. (C) 2012 Elsevier Ltd. All rights reserved.