Travel preferences of the residents of Guimarães: a revised model of push and pull motives

The historic center of the Portuguese city of Guimarães is a world heritage site (UNESCO) since 2001, having hosted the European Capital of Culture (ECOC) in 2012. In this sense, Guimarães has made a major effort in promoting tourism, positioning itself as an urban and cultural tourism destination. The present paper has two objectives. The first, to examine if an existing push and pull motivation model finds statistical support with regard to the population of the municipality of Guimarães, a cultural tourism destination. The second, to study the role that important socio-demographic variables, such as gender, age, and education, play in determining travel motivations of residents from this municipality. Insight on tourism motivation may be an important policy tool for tourism planners and managers in the development of products and marketing strategies. The empirical analysis is undertaken based on questionnaires administered in 2012 to residents of Guimarães. The present study shows that gender, age and education make a difference with regard to travel motivations.

Automatic segmentation and 3D feature extraction of protein aggregates in Caenorhabditis Elegans

In the last years, it has become increasingly clear that neurodegenerative diseases involve protein aggregation, a process often used as disease progression readout and to develop therapeutic strategies. This work presents an image processing tool to automatic segment, classify and quantify these aggregates and the whole 3D body of the nematode Caenorhabditis Elegans. A total of 150 data set images, containing different slices, were captured with a confocal microscope from animals of distinct genetic conditions. Because of the animals’ transparency, most of the slices pixels appeared dark, hampering their body volume direct reconstruction. Therefore, for each data set, all slices were stacked in one single 2D image in order to determine a volume approximation. The gradient of this image was input to an anisotropic diffusion algorithm that uses the Tukey’s biweight as edge-stopping function. The image histogram median of this outcome was used to dynamically determine a thresholding level, which allows the determination of a smoothed exterior contour of the worm and the medial axis of the worm body from thinning its skeleton. Based on this exterior contour diameter and the medial animal axis, random 3D points were then calculated to produce a volume mesh approximation. The protein aggregations were subsequently segmented based on an iso-value and blended with the resulting volume mesh. The results obtained were consistent with qualitative observations in literature, allowing non-biased, reliable and high throughput protein aggregates quantification. This may lead to a significant improvement on neurodegenerative diseases treatment planning and interventions prevention