Wind analysis of the Messina Strait Bridge design project proposal with stabilizing cables

A new study on suspension bridges has been prompted by the big disaster of the Tacoma Narrow Bridge at half its design speed. The aerodynamic instability of long-span bridges has been studied using wind tunnel tests. As a result of improved aerodynamic performance from the geometrical configuration of the bridge deck, the aerodynamic criteria for suspension and cable-stayed bridges have become well established in recent years, thereby allowing longer bridge spans to be developed. Although the Messina Strait Bridge has yet to be constructed, we are looking forward to evaluating the impact of different deck cross-sections on both aerodynamic stability and cost reduction. To further improve the aerodynamic characteristics of long-span suspension bridges, an optimized multi-box bridge deck model with two side decks for traffic lanes, two middle railway decks, and three gaps separating them has been proposed aerodynamic performance has been experimentally verified. 1:80 scale wind tunnel tests have been conducted. According to the current MIDAS Model, the first torsional and the first vertical frequency ratios are 1.27787 and 1.36[1] respectively. It is the torsional/vertical frequency ratio, combined with the deck aerodynamic properties, that determines the wind response properties of the bridge for the most dangerous possible form of aeroelastic instability. The classic flutter is caused by the coupling of torsional and vertical modes. Stabilizing cables to the deck could be a solution to this classic flutter by reducing lateral displacement of the deck and increasing frequency ratios. Stabilizing cables will be installed on the deck in three different orientations: vertical, inclined, and horizontal, with diameters of 80 cm, 60 cm, and 40 cm in each orientation respectively. An overview of the research undertaken on this topic will be presented, as well as the most important findings.

Analysis of human posterior EEG alpha frequency as a function of implicit learning of probabilistic lateralized stimuli in a visual detection task

Alpha oscillatory activity has long been associated with perceptual and cognitive processes related to attention control. The aim of this study is to explore the task-dependent role of alpha frequency in a lateralized visuo-spatial detection task. Specifically, the thesis focuses on consolidating the scientific literature's knowledge about the role of alpha frequency in perceptual accuracy, and deepening the understanding of what determines trial-by-trial fluctuations of alpha parameters and how these fluctuations influence overall task performance. The hypotheses, confirmed empirically, were that different implicit strategies are put in place based on the task context, in order to maximize performance with optimal resource distribution (namely alpha frequency, associated positively with performance): “Lateralization” of the attentive resources towards one hemifield should be associated with higher alpha frequency difference between contralateral and ipsilateral hemisphere; “Distribution” of the attentive resources across hemifields should be associated with lower alpha frequency difference between hemispheres; These strategies, used by the participants according to their brain capabilities, have proven themselves adaptive or maladaptive depending on the different tasks to which they have been set: "Distribution" of the attentive resources seemed to be the best strategy when the distribution probability between hemifields was balanced: i.e. the neutral condition task. "Lateralization" of the attentive resources seemed to be more effective when the distribution probability between hemifields was biased towards one hemifield: i.e., the biased condition task.

Analysis of fragmentation cross sections of GSI 2021 data for the FOOT experiment

Hadrontherapy is a medical treatment based on the use of charged particles beams accelerated towards deep-seated tumors on clinical patients. The reason why it is increasingly used is the favorable depth dose profile following the Bragg Peak distribution, where the release of dose is almost sharply focused near the end of the beam path. However, nuclear interactions between the beam and the human body constituents occur, generating nuclear fragments which modify the dose profile. To overcome the lack of experimental data on nuclear fragmentation reactions in the energy range of hadrontherapy interest, the FOOT (FragmentatiOn Of Target) experiment has been conceived with the main aim of measuring differential nuclear fragmentation cross sections with an uncertainty lower than 5\%. The same results are of great interest also in the radioprotection field, studying similar processes. Long-term human missions outside the Earth’s orbit are going to be planned in the next years, among which the NASA foreseen travel to Mars, and it is fundamental to protect astronauts health and electronics from radiation exposure .\\ In this thesis, a first analysis of the data taken at the GSI with a beam of $^{16}O$ at 400 $MeV/u$ impinging on a target of graphite ($C$) will be presented, showing the first preliminary results of elemental cross section and angular differential cross section. A Monte Carlo dataset was first studied to test the performance of the tracking reconstruction algorithm and to check the reliability of the full analysis chain, from hit reconstruction to cross section measurement. An high agreement was found between generated and reconstructed fragments, thus validating the adopted procedure. A preliminary experimental cross section was measured and compared with MC results, highlighting a good consistency for all the fragments.

Introducing CHIMeRA: from the development of a comprehensive biomedical database to the analysis of its sub-components.

In this thesis we discuss the expansion of an existing project, called CHIMeRA, which is a comprehensive biomedical network, and the analysis of its sub-components by using graph theory. We describe how it is structured internally, what are the existing databases from which it retrieves information and what machine learning techniques are used in order to produce new knowledge. We also introduce a new technique for graph exploration that is aimed to speed-up the network cover time under the condition that the analyzed graph is stellar; if this condition is satisfied, the improvement in the performance compared to the conventional exploration technique is extremely appealing. We show that the stellar structure is highly recurrent for sub-networks in CHIMeRA generated by queries, which made this technique even more interesting. Finally, we describe the convenience in using the CHIMeRA network for research purposes and what it could become in a very near future.