Shear behaviour of reinforced cconcrete slab under concentrated load: an investigation through non-linear and sequentially linear analysis

English: The assessment of safety in existing bridges and viaducts led the Ministry of Public Works of the Netherlands to finance a specific campaing aimed at the study of the response of the elements of these infrastructures. Therefore, this activity is focused on the investigation of the behaviour of reinforced concrete slabs under concentrated loads, adopting finite element modeling and comparison with experimental results. These elements are characterized by shear behaviour and crisi, whose modeling is, from a computational point of view, a hard challeng, due to the brittle behavior combined with three-dimensional effects. The numerical modeling of the failure is studied through Sequentially Linear Analysis (SLA), an alternative Finite Element method, with respect to traditional incremental and iterative approaches. The comparison between the two different numerical techniques represents one of the first works and comparisons in a three-dimensional environment. It's carried out adopting one of the experimental test executed on reinforced concrete slabs as well. The advantage of the SLA is to avoid the well known problems of convergence of typical non-linear analysis, by directly specifying a damage increment, in terms of reduction of stiffness and resistance in particular finite element, instead of load or displacement increasing on the whole structure . For the first time, particular attention has been paid to specific aspects of the slabs, like an accurate constraints modeling and sensitivity of the solution with respect to the mesh density. This detailed analysis with respect to the main parameters proofed a strong influence of the tensile fracture energy, mesh density and chosen model on the solution in terms of force-displacement diagram, distribution of the crack patterns and shear failure mode. The SLA showed a great potential, but it requires a further developments for what regards two aspects of modeling: load conditions (constant and proportional loads) and softening behaviour of brittle materials (like concrete) in the three-dimensional field, in order to widen its horizons in these new contexts of study.

Note-taking in consecutive interpretation; advantages and disadvantages of various techniques

The objective of this thesis is to investigate which contexts should be used for different kinds of note-taking and to study the evolution of the various types of note-taking. Moreover, the final aim of this thesis is to understand which method is used most commonly during the interpreting process, with a special focus on consecutive and community interpreting in the sector of public service and healthcare. The belief that stands behind this thesis is that the most complete method is Rozan’s, which is also the most theorized and used by interpreters. Through the analysis of the different rules of this practice, the importance of this method is shown. Moreover, the analysis demonstrates how these techniques can assist the interpreters in their jobs. This thesis starts from an overview of what note-taking means in the different settings of interpreting and a short history of note-taking is presented. The section that follows analyzes three different well-known types of note-taking methods outside the interpreting environment, that is: linear, non-linear and shorthand. Subsequent to the comparison, Rozan’s 7 principles are analyzed. To authenticate this thesis and the hypotheses herein, data was collected through a survey that was conducted on a sample of a group of graduated students in Linguistic and Intercultural Mediation at the University of Bologna “Scuola Superiore di Lingue Moderne per Interpreti e Traduttori”.

Synthetic generation of amyloid PET images by non-linear dimensionality reduction inversion

Privacy issues and data scarcity in PET field call for efficient methods to expand datasets via synthetic generation of new data that cannot be traced back to real patients and that are also realistic. In this thesis, machine learning techniques were applied to 1001 amyloid-beta PET images, which had undergone a diagnosis of Alzheimer’s disease: the evaluations were 540 positive, 457 negative and 4 unknown. Isomap algorithm was used as a manifold learning method to reduce the dimensions of the PET dataset; a numerical scale-free interpolation method was applied to invert the dimensionality reduction map. The interpolant was tested on the PET images via LOOCV, where the removed images were compared with the reconstructed ones with the mean SSIM index (MSSIM = 0.76 ± 0.06). The effectiveness of this measure is questioned, since it indicated slightly higher performance for a method of comparison using PCA (MSSIM = 0.79 ± 0.06), which gave clearly poor quality reconstructed images with respect to those recovered by the numerical inverse mapping. Ten synthetic PET images were generated and, after having been mixed with ten originals, were sent to a team of clinicians for the visual assessment of their realism; no significant agreements were found either between clinicians and the true image labels or among the clinicians, meaning that original and synthetic images were indistinguishable. The future perspective of this thesis points to the improvement of the amyloid-beta PET research field by increasing available data, overcoming the constraints of data acquisition and privacy issues. Potential improvements can be achieved via refinements of the manifold learning and the inverse mapping stages during the PET image analysis, by exploring different combinations in the choice of algorithm parameters and by applying other non-linear dimensionality reduction algorithms. A final prospect of this work is the search for new methods to assess image reconstruction quality.