A compiled computer program for assisting the diagnosis of gastrointestinal helminths of humans and animals.

A compiled computer program for assisting the diagnosis of gastrointestinal helminths in fecal examinations of humans and animals is described. The characteristics of this program which distinguish it from previous similar programs are that it does not require specific software, it does not need a lot of computer memory, and it covers both humans and animals, making it easier to use.     

Analysis of the biomechanical behaviour of gastrointestinal regions adopting an experimental and computational approach

An integrated experimental and computational procedure is provided for the evaluation of the biomechanical behaviour that characterizes the pressure–volume response of gastrointestinal regions. The experimental activity pertains to inflation tests performed on specific gastrointestinal conduct segments. Different inflation processes are performed according to progressively increasing volumes. Each inflation test is performed by a rapid liquid in-flaw, up to a prescribed volume, which is held constant for about 300 s to allow the development of relaxation processes. The different tests are interspersed by 600 s of rest to allow the recovery of the specimen mechanical condition. A physio-mechanical model is developed to interpret both the elastic behaviour of the sample, as the pressure–volume trend during the rapid liquid in-flaw, and the time-dependent response, as the pressure drop during the relaxation processes. The minimization of discrepancy between experimental data and model results entails the identification of the parameters that characterize the viscoelastic model adopted for the definition of the behaviour of the gastrointestinal regions. The reliability of the procedure is assessed by the characterization of the response of samples from rat small intestine.     

Probabilistic model identification of uncertainties in computational models for dynamical systems and experimental validation

We present a methodology to perform the identification and validation of complex uncertain dynamical systems using experimental data, for which uncertainties are taken into account by using the nonparametric probabilistic approach. Such a probabilistic model of uncertainties allows both model uncertainties and parameter uncertainties to be addressed by using only a small number of unknown identification parameters. Consequently, the optimization problem which has to be solved in order to identify the unknown identification parameters from experiments is feasible. Two formulations are proposed. The first one is the mean-square method for which a usual differentiable objective function and an unusual non-differentiable objective function are proposed. The second one is the maximum likelihood method coupling with a statistical reduction which leads us to a considerable improvement of the method. Three applications with experimental validations are presented in the area of structural vibrations and vibroacoustics.