Research on the vocal culture of Orcinus orca in the Loro Parque, Tenerife: a pilot study

This research is focussed on the study of Orcinus orca's communication system. The analysis of vocalizations emitted by marine mammals has started in the '80s and most studies have been carried out in the wild. In this regard the most studied animal has been common dolphin (Tursiops truncatus) as the numerous presence of captive individuals worldwide made researches easier to be carried out. Studies about Orcinus orca's vocalizations have mainly been carried out in the wild (most in British Columbia) because its maintenance in a controlled environment results to be very difficult, only 17 among parks and oceanaria worldwide have some Orcinus orca (45 overall among which 64% born in captivity). These researches showed that Orcinus orca emit three main different types of sounds, classified as: whistles, clicks and calls. Besides, it was discovered that different groups (pods) produce sounds belonging only to the relevant pod (dialects). It is rare to find two pods sharing some calls. The two pods usually live in adjacent areas and can form a clan. This study was carried out in a controlled environment in the Orca ocean structure (Loro Parque, Tenerife, Spain) where, at the moment (March 2012) 6 individuals are hosted. Here it was developed an automatic sound recording system. Thanks to the use of suitable mathematical algorithms that allow to isolate only "interesting" sound events that differ from the "background noise", it was possible to create a database. The visualization of the sound events collected in the database is carried out with the use of a software. By looking at this output and at the observation register we could match the animal to the sound produced. Three situations were detected and studied: 1) Chosen alone: the animal chooses to go to the recording pool but it is free to move to another pool with other individuals. 2) Put alone: the animal is put alone in the recording pool. 3) With other orcas: more animals are together in the recording pool. The statistic analysis show that animals emit more vocalizations when they are in the situation "Chosen alone". The research will continue in order to observe eventual differences in the individual repertoire of each Orcinus orca.

Near Real-Time Detection Of Pipe Bursts in Water Distribution Systems

The research work presented in the thesis describes a new methodology for the automated near real-time detection of pipe bursts in Water Distribution Systems (WDSs). The methodology analyses the pressure/flow data gathered by means of SCADA systems in order to extract useful informations that go beyond the simple and usual monitoring type activities and/or regulatory reporting , enabling the water company to proactively manage the WDSs sections. The work has an interdisciplinary nature covering AI techniques and WDSs management processes such as data collection, manipulation and analysis for event detection. Indeed, the methodology makes use of (i) Artificial Neural Network (ANN) for the short-term forecasting of future pressure/flow signal values and (ii) Rule-based Model for bursts detection at sensor and district level. The results of applying the new methodology to a District Metered Area in Emilia- Romagna’s region, Italy have also been reported in the thesis. The results gathered illustrate how the methodology is capable to detect the aforementioned failure events in fast and reliable manner. The methodology guarantees the water companies to save water, energy, money and therefore enhance them to achieve higher levels of operational efficiency, a compliance with the current regulations and, last but not least, an improvement of customer service.

Assessing model credibility of CT-Based finite element model to predict bone strength

Osteoporosis is one of the major causes of mortality among the elderly. Nowadays, areal bone mineral density (aBMD) is used as diagnostic criteria for osteoporosis; however, this is a moderate predictor of the femur fracture risk and does not capture the effect of some anatomical and physiological properties on the bone strength estimation. Data from past research suggest that most fragility femur fractures occur in patients with aBMD values outside the pathological range. Subject-specific finite element models derived from computed tomography data are considered better tools to non-invasively assess hip fracture risk. In particular, the Bologna Biomechanical Computed Tomography (BBCT) is an In Silico methodology that uses a subject specific FE model to predict bone strength. Different studies demonstrated that the modeling pipeline can increase predictive accuracy of osteoporosis detection and assess the efficacy of new antiresorptive drugs. However, one critical aspect that must be properly addressed before using the technology in the clinical practice, is the assessment of the model credibility. The aim of this study was to define and perform verification and uncertainty quantification analyses on the BBCT methodology following the risk-based credibility assessment framework recently proposed in the VV-40 standard. The analyses focused on the main verification tests used in computational solid mechanics: force and moment equilibrium check, mesh convergence analyses, mesh quality metrics study, evaluation of the uncertainties associated to the definition of the boundary conditions and material properties mapping. Results of these analyses showed that the FE model is correctly implemented and solved. The operation that mostly affect the model results is the material properties mapping step. This work represents an important step that, together with the ongoing clinical validation activities, will contribute to demonstrate the credibility of the BBCT methodology.