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People are quick to form impressions of others’ social class, and likely adjust their behavior accordingly. If social class is linked to prosociality, as literature suggests, then an interaction partner’s class should affect prosocial behavior, especially when costs or investments are low. We test this expectation using social mindfulness (SoMi) and dictator games (DG) as complementary measures of prosociality. We manipulate target class by providing information regarding a target’s (a) position on a social class ladder, and (b) family background. Three studies using laboratory and online approaches ( Noverall = 557) in two nations (the Netherlands [NL], the UK), featuring actual and hypothetical exchanges, reveal that lower class targets are met with greater prosociality than higher class targets, even when based on information about the targets’ parents (Study 3). The effect of target class was partially mediated by compassion (Studies 2 and 3) and perceived deservingness of the target (Study 3). Implications and limitations are discussed.

The applicability of two alternative spectroscopic techniques (i.e., 1 H NMR and NIR) for the quantitative characterization of gasoline was compared in this work. The chemometric approach followed to build the regression models was support vector regression, and two distinct kernel functions were tested: Gaussian and linear. Additionally, a significance test was performed on test set predictions to determine if the difference between the estimations of 1 H NMR and NIR-based models is statistically significant. According to the performance indexes of the developed models, NIR spectroscopy is preferable over 1 H NMR for the prediction of most gasoline physical−chemical properties. Still, for most of the cases, it was also demonstrated that the estimations resulting from both spectroscopic techniques are not significantly different from each other. The accuracy level attained with the support vector regression models is adequate and enables the replacement of the standard methods of analysis for at least 10 different gasoline quality parameters.

OBJETIVO: verificar a importância da comunicação não-verbal do professor no exercício de sua atividade profissional. MÉTODOS: a presente pesquisa foi realizada no período de março a maio de 2008. A população de estudo foi composta por alunos de dois cursos de graduação (Ciências Biológicas e de Fonoaudiologia). Foram escolhidos, aleatoriamente, alunos de cada turma, independente de sexo ou idade, compondo um total de 63 alunos. RESULTADOS: os dados obtidos mostraram que, independente da sua formação (se fonoaudiólogo ou não), todos consideraram que a comunicação não-verbal do professor é um importante fator na transmissão das mensagens. CONCLUSÃO: a pesquisa mostrou que os entrevistados avaliaram a comunicação não-verbal como importante para a efetividade da interação, podendo interferir no desempenho do docente em sala de aula.

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Commercial gasoline must satisfy several product specifications before trading.In the present work, repeated double cross validation using partial least squares regression was applied to create reliable prediction models for 13 physicochemical parameters (eg, density, vapour pressure, evaporate at 70 C, evaporate at 100 C, evaporate at 150 C, final boiling point, research octane number, motor octane number, aromatic content, olefinic content, benzene content, oxygen content, and methyl tert-butyl ether content) of gasoline produced in Matosinhos' refinery. The input variables for the regression are the 1 H NMR spectral intensities of a total of 448 samples, which were recorded using a pico-Spin NMR spectrometer operating at 80 MHz. The output variables are the corresponding property values, which were also measured according to ISO standard methods. A spectral feature elimination before multivariate analysis was done to remove noise and speed up the chemometric analysis. The optimum complexity of each model was achieved by repeated double crossvalidation strategy, consisting of 100 repetitions of two nested cross-validation loops. Quantitative partial least squares yielded accurate predictions of 11 of 13 properties within the reproducibility of ISO standards. The methodology presented in this work has been proven effective in property estimation and enables a significant reduction in the total time of gasoline quality control.