Scientific Mobility, Training and Entrepreneurial Skills in Health Sciences: The Spanish Case.

The activity of scientists promotes medical research in health services. However, on many occasions, these professionals do not know how to transfer their research results to the market. Therefore, it is worth providing data on aspects such as training in entrepreneurship and scientific mobility to foster knowledge transfer. This paper discusses data on the Spanish case in Health Sciences to devise effective policies in these areas. To this end, following the methodology of the Global Entrepreneurship Monitor report and the existing scientific literature, 291 researchers involved in scientific mobility in Spain have been interviewed. Of these, 90 belonged to health areas: Spanish scientists abroad (37), Scientists returned to Spain (16), and Young researchers in Spain (37). The results show that the mobile scientists in this area have more entrepreneurial and intrapreneurial intentions, have acquired more entrepreneurial skills, and have received more training in these subjects. Furthermore, there are few permanent positions for all these groups whose mobility decisions fundamentally depend on job opportunities, so the health authorities can intensify these measures to promote knowledge transfer.

Synthetic Data Generation for End-to-End Thermal Infrared Tracking.

The usage of both off-the-shelf and end-to-end trained deep networks have significantly improved the performance of visual tracking on RGB videos. However, the lack of large labeled datasets hampers the usage of convolutional neural networks for tracking in thermal infrared (TIR) images. Therefore, most state-of-the-art methods on tracking for TIR data are still based on handcrafted features. To address this problem, we propose to use image-to-image translation models. These models allow us to translate the abundantly available labeled RGB data to synthetic TIR data. We explore both the usage of paired and unpaired image translation models for this purpose. These methods provide us with a large labeled dataset of synthetic TIR sequences, on which we can train end-to-end optimal features for tracking. To the best of our knowledge, we are the first to train end-to-end features for TIR tracking. We perform extensive experiments on the VOT-TIR2017 dataset. We show that a network trained on a large dataset of synthetic TIR data obtains better performance than one trained on the available real TIR data. Combining both data sources leads to further improvement. In addition, when we combine the network with motion features, we outperform the state of the art with a relative gain of over 10%, clearly showing the efficiency of using synthetic data to train end-to-end TIR trackers.

Entrepreneurship, intrapreneurship and scientific mobility: The Spanish case.

Scientific mobility can stimulate entrepreneurship and intrapreneurship, acting as a catalyst for reducing imbalances between local and global science and the resulting socio-economic damage. This study evaluates both whether scientific mobility effectively promotes these concepts and the fundamental reasons to articulate effective policies for scientific mobility. Toward this end, a survey has been prepared following the methodology of Global Entrepreneurship Monitor (GEM) and current scientific literature. A total of 364 researchers involved in Spanish scientific mobility took part in the study: Spanish scientists abroad (135) and scientists returned to Spain (52), as mobile groups, and young researchers in Spain (177), as a group of scientists who could go abroad, but that have not yet begun to leave. The results demonstrate that scientific mobility does promote entrepreneurship and, especially intrapreneurship. Moreover, since permanent positions are scarce for these groups and their mobility decisions largely depend on job opportunities, the involved Spanish authorities and agents can improve scientific mobility by means suitable policies that make the most of this potential to the benefit of economic growth and job creation.