Curvature singularity and film-skating during drop impact

We study the influence of the surrounding gas in the dynamics of drop impact on a smooth surface. We use an axisymmetric 3D model for which both the gas and the liquid are incompressible; lubrication regime applies for the gas film dynamics and the liquid viscosity is neglected. In the absence of surface tension a finite time singularity whose properties are analysed is formed and the liquid touches the solid on a circle. When surface tension is taken into account, a thin jet emerges from the zone of impact, skating above a thin gas layer. The thickness of the air film underneath this jet is always smaller than the mean free path in the gas suggesting that the liquid film eventually wets the surface. We finally suggest an aerodynamical instability mechanism for the splash.Comment: 5 figure

Contact and cooperation in the Belgian fertility and family survey.

Cooperation; Fertility and family survey;

Robust estimators for the fixed effects panel data model.

The presence of outlying observations in panel data can affect the classical estimates in a dramatic way. Nevertheless the common practice seems to disregard the problem. The aim of this work is to study robust regression techniques in the fixed effects linear panel data framework. Robustness of the procedures is investigated by means of breakdown point computations and simulation experiments. A distinction between outlying blocks and cells in a panel is made. To show the potential of robust panel data methods an empirical example on the response of the private sector behavior to fiscal policy is presented.Breakdown point; Data; Effects; Estimator; Fixed effects model; Framework; Linear regression; Methods; Model; Panel data; Policy; Private sector; Regression; Robust regression; Robustness; Simulation; Studies;

Performance of likelihood-based estimation methods for multilevel binary regression models.

By means of a fractional factorial simulation experiment, we. compare the performance of penalised quasi-likelihood (PQL), non-adaptive Gaussian quadrature and adaptive Gaussian quadrature in estimating parameters for multilevel logistic regression models. The comparison is done in terms of bias, mean-squared error (MSE), numerical convergence and computational efficiency. It turns out that in terms of MSE, standard versions of the quadrature methods per-form relatively poorly in comparison with PQL.Bias; Binary regression; Convergence; Efficiency; Factorial; Fractional factorial experiment; Gaussian quadrature; Logistic regression; Methods; Model; Models; Monte Carlo simulation; Multilevel analysis; Parameters; Penalised quasi-likelihood; Performance; Regression; Simulation;