Evaluation of reproductive success and conservation strategies for Senecio coincyi (Asteraceae), a narrow and threatened species.

enecio coincyi is a threatened endemic plant of central western Spain, with a very narrow extent of occurrence. The reproductive success and germination behaviour of this species were studied. The area of occupancy, habitat types and size of 13 known subpopulations of S. coincyi were evaluated. The number of individuals that form all these subpopulations was counted. In addition, the number of flowers and cypselas per fruit head and the number of fruit heads per individual plant were recorded in a subset of subpopulations. Germination tests were carried out to evaluate the effect of temperature and light regimes on, and possible intraspecific variation in, cypsela germination. Cypselas reached very high germination percentages (90?100%) from 15°C to 30°C. However, the germination decreased (19%) at 10°C. The light conditions assayed (16-h light photoperiod and complete darkness) did not significantly affect cypsela germination. In general, there was no intraspecific variability in germination patterns of S. coincyi cypselas. Livestock is the most important factor that can be a threat for this species. S. coincyi showed high reproductive success and, therefore, its conservation problems are not due to agents related to its reproduction, but rather to other factors such as alteration of its habitat caused by the presence of livestock.

Dental Implants Success Prediction: Tomography Based and Data Mining Based Approach.

There are a number of factors that contribute to the success of dental implant operations. Among others, is the choice of location in which the prosthetic tooth is to be implanted. This project offers a new approach to analyse jaw tissue for the purpose of selecting suitable locations for teeth implant operations. The application developed takes as input jaw computed tomography stack of slices and trims data outside the jaw area, which is the point of interest. It then reconstructs a three dimensional model of the jaw highlighting points of interest on the reconstructed model. On another hand, data mining techniques have been utilised in order to construct a prediction model based on an information dataset of previous dental implant operations with observed stability values. The goal is to find patterns within the dataset that would help predicting the success likelihood of an implant.