The usefulness of holding in the management of congenital heart disease.

BACKGROUND: In our Pediatric Cardiology Unit we have implemented a number of specific interventions in order to support parents and their children who have congenital heart disease. We paid particular attention about how communicating the diagnosis and how supporting psychologically the parents. METHODS: In order to check the validity of these interventions we used the State-Trait Anxiety Inventory to analyze and compare the anxiety levels of 380 parents of already established patients here in the hospital to the anxiety levels of 240 parents of children seen in our unit for the first time (for screening or evaluating anomalous symptoms). RESULTS: Our analysis shows that during daily life the seriousness of the disease affects parents adversely (the "anxiety trait" in parents of children with cyanotic congenital heart disease has a higher rate than other parents, p < .05). While waiting for medical assessment, the parents of children with a previous diagnosis of congenital heart disease or those with symptomatic children live an increment of the level of anxiety (the "anxiety state" has a higher score than the "anxiety trait", p < .001), but the "anxiety state" of parents of children with congenital heart disease has a lower rate in respect to parents of symptomatic children (p < .001). CONCLUSIONS: Thus adequate interventions, specifically an effective communication in a comfortable environment, can reduce anxiety of parents while waiting for medical assessment. It is very important as the child's psychological wellbeing is very directly related to the emotional state of the parents.

Multiobjective optimization and multivariable control of the beer fermentation process with the use of evolutionary algorithms.

This paper describes empirical research on the model, optimization and supervisory control of beer fermentation. Conditions in the laboratory were made as similar as possible to brewery industry conditions. Since mathematical models that consider realistic industrial conditions were not available, a new mathematical model design involving industrial conditions was first developed. Batch fermentations are multiobjective dynamic processes that must be guided along optimal paths to obtain good results. The paper describes a direct way to apply a Pareto set approach with multiobjective evolutionary algorithms (MOEAs). Successful finding of optimal ways to drive these processes were reported. Once obtained, the mathematical fermentation model was used to optimize the fermentation process by using an intelligent control based on certain rules.