Delay of cortical thinning in very preterm born children

Objective: Cortical gray matter thinning takes place during childhood due to pruning of inefficient synaptic connections and an increase in myelination. Alterations in brain structure occur in very preterm born children with prolonged maturation of the frontal lobes and smaller cortical and white matter volume. These findings give rise to the question if age affects cortical thinning differently in very preterm born children compared to controls. The aim of the present study was to investigate the relationship between age and cortical thickness in very preterm born children when compared to controls. Participants and Methods: Forty-one very preterm born children (<32 weeks gestational age and/or < 1500 gram birth weight) and 30term born controls were included in the study (7-12 years). The automated surface reconstruction software FreeSurfer was applied to obtain measurements of cortical thickness based on T1-weighted MRI images. Results: Cortical thickness was lower in bilateral frontal and left parietal regions and higher in left temporal gyri in very preterm born children compared to controls. However, these differences depended on age. In very preterm born children, age correlated negatively with cortical thickness in right frontal, parietal and inferior temporal regions. Accordingly, cortical thickness was higher in young compared to old very preterm born children in bilateral frontal, parietal and temporal regions. In controls, age was not associated with cortical thickness. Conclusions: In very preterm born children, cortical thinning still occurs between the age of 7 and 12 years, mainly in frontal and parietal areas. In controls, however, a substantial part of cortical thinning appears to be completed in these regions before they reach the age of 7 years. These data indicate a delay in cortical thinning in very preterm born children.

Associating optical measurements and estimating orbits of geocentric objects through population-based meta-heuristic methods

Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. The problem faced in this framework is that of Multiple Target Tracking (MTT). In this context both, the correct associations among the observations and the orbits of the objects have to be determined. The complexity of the MTT problem is defined by its dimension S. The number S corresponds to the number of fences involved in the problem. Each fence consists of a set of observations where each observation belongs to a different object. The S ≥ 3 MTT problem is an NP-hard combinatorial optimization problem. There are two general ways to solve this. One way is to seek the optimum solution, this can be achieved by applying a branch-and- bound algorithm. When using these algorithms the problem has to be greatly simplified to keep the computational cost at a reasonable level. Another option is to approximate the solution by using meta-heuristic methods. These methods aim to efficiently explore the different possible combinations so that a reasonable result can be obtained with a reasonable computational effort. To this end several population-based meta-heuristic methods are implemented and tested on simulated optical measurements. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the correlation and orbit determination problems simultaneously, and is able to efficiently process large data sets with minimal manual intervention.