Rainfall spatial predictions: a two-part model and its assessment

Spatial prediction of hourly rainfall via radar calibration is addressed. The change of support problem (COSP), arising when the spatial supports of different data sources do not coincide, is faced in a non-Gaussian setting; in fact, hourly rainfall in Emilia-Romagna region, in Italy, is characterized by abundance of zero values and right-skeweness of the distribution of positive amounts. Rain gauge direct measurements on sparsely distributed locations and hourly cumulated radar grids are provided by the ARPA-SIMC Emilia-Romagna. We propose a three-stage Bayesian hierarchical model for radar calibration, exploiting rain gauges as reference measure. Rain probability and amounts are modeled via linear relationships with radar in the log scale; spatial correlated Gaussian effects capture the residual information. We employ a probit link for rainfall probability and Gamma distribution for rainfall positive amounts; the two steps are joined via a two-part semicontinuous model. Three model specifications differently addressing COSP are presented; in particular, a stochastic weighting of all radar pixels, driven by a latent Gaussian process defined on the grid, is employed. Estimation is performed via MCMC procedures implemented in C, linked to R software. Communication and evaluation of probabilistic, point and interval predictions is investigated. A non-randomized PIT histogram is proposed for correctly assessing calibration and coverage of two-part semicontinuous models. Predictions obtained with the different model specifications are evaluated via graphical tools (Reliability Plot, Sharpness Histogram, PIT Histogram, Brier Score Plot and Quantile Decomposition Plot), proper scoring rules (Brier Score, Continuous Rank Probability Score) and consistent scoring functions (Root Mean Square Error and Mean Absolute Error addressing the predictive mean and median, respectively). Calibration is reached and the inclusion of neighbouring information slightly improves predictions. All specifications outperform a benchmark model with incorrelated effects, confirming the relevance of spatial correlation for modeling rainfall probability and accumulation.

Three-dimensional joint kinematics of swimming using body-worn inertial and magnetic sensors

Wearable inertial and magnetic measurements units (IMMU) are an important tool for underwater motion analysis because they are swimmer-centric, they require only simple measurement set-up and they provide the performance results very quickly. In order to estimate 3D joint kinematics during motion, protocols were developed to transpose the IMMU orientation estimation to a biomechanical model. The aim of the thesis was to validate a protocol originally propositioned to estimate the joint angles of the upper limbs during one-degree-of-freedom movements in dry settings and herein modified to perform 3D kinematics analysis of shoulders, elbows and wrists during swimming. Eight high-level swimmers were assessed in the laboratory by means of an IMMU while simulating the front crawl and breaststroke movements. A stereo-photogrammetric system (SPS) was used as reference. The joint angles (in degrees) of the shoulders (flexion-extension, abduction-adduction and internal-external rotation), the elbows (flexion-extension and pronation-supination), and the wrists (flexion-extension and radial-ulnar deviation) were estimated with the two systems and compared by means of root mean square errors (RMSE), relative RMSE, Pearson’s product-moment coefficient correlation (R) and coefficient of multiple correlation (CMC). Subsequently, the athletes were assessed during pool swimming trials through the IMMU. Considering both swim styles and all joint degrees of freedom modeled, the comparison between the IMMU and the SPS showed median values of RMSE lower than 8°, representing 10% of overall joint range of motion, high median values of CMC (0.97) and R (0.96). These findings suggest that the protocol accurately estimated the 3D orientation of the shoulders, elbows and wrists joint during swimming with accuracy adequate for the purposes of research. In conclusion, the proposed method to evaluate the 3D joint kinematics through IMMU was revealed to be a useful tool for both sport and clinical contexts.

Development and characterisation of a neurogenic model of brain cancer

Primary glioblastoma (GB), the most common and aggressive adult brain tumour, is refractory to conventional therapies and characterised by poor prognosis. GB displays striking cellular heterogeneity, with a sub-population, called Glioblastoma Stem Cells (GSCs), intrinsically resistant to therapy, hence the high rate of recurrence. Alterations of the tumour suppressor gene PTEN are prevalent in primary GBM, resulting in the inhibition of the polarity protein Lgl1 due to aPKC hyperactivation. Dysregulation of this molecular axis is one of the mechanisms involved in GSC maintenance. After demonstrating that the PTEN/aPKC/Lgl axis is conserved in Drosophila, I deregulated it in different cells populations of the nervous system in order to individuate the cells at the root of neurogenic brain cancers. This analysis identified the type II neuroblasts (NBs) as the most sensitive to alterations of this molecular axis. Type II NBs are a sub-population of Drosophila stem cells displaying a lineage similar to that of the mammalian neural stem cells. Following aPKC activation in these stem cells, I obtained an adult brain cancer model in Drosophila that summarises many phenotypic traits of human brain tumours. Fly tumours are indeed characterised by accumulation of highly proliferative immature cells and keep growing in the adult leading the affected animals to premature death. With the aim to understand the role of cell polarity disruption in this tumorigenic process I carried out a molecular characterisation and transcriptome analysis of brain cancers from our fly model. In summary, the model I built and partially characterised in this thesis work may help deepen our knowledge on human brain cancers by investigating many different aspects of this complicate disease.