Multicentre study for a robust protocol in single-voxel spectroscopy: quantification of MRS signals by time-domain fitting algorithms

Magnetic Resonance Spectroscopy (MRS) is an advanced clinical and research application which guarantees a specific biochemical and metabolic characterization of tissues by the detection and quantification of key metabolites for diagnosis and disease staging. The "Associazione Italiana di Fisica Medica (AIFM)" has promoted the activity of the "Interconfronto di spettroscopia in RM" working group. The purpose of the study is to compare and analyze results obtained by perfoming MRS on scanners of different manufacturing in order to compile a robust protocol for spectroscopic examinations in clinical routines. This thesis takes part into this project by using the GE Signa HDxt 1.5 T at the Pavillion no. 11 of the S.Orsola-Malpighi hospital in Bologna. The spectral analyses have been performed with the jMRUI package, which includes a wide range of preprocessing and quantification algorithms for signal analysis in the time domain. After the quality assurance on the scanner with standard and innovative methods, both spectra with and without suppression of the water peak have been acquired on the GE test phantom. The comparison of the ratios of the metabolite amplitudes over Creatine computed by the workstation software, which works on the frequencies, and jMRUI shows good agreement, suggesting that quantifications in both domains may lead to consistent results. The characterization of an in-house phantom provided by the working group has achieved its goal of assessing the solution content and the metabolite concentrations with good accuracy. The goodness of the experimental procedure and data analysis has been demonstrated by the correct estimation of the T2 of water, the observed biexponential relaxation curve of Creatine and the correct TE value at which the modulation by J coupling causes the Lactate doublet to be inverted in the spectrum. The work of this thesis has demonstrated that it is possible to perform measurements and establish protocols for data analysis, based on the physical principles of NMR, which are able to provide robust values for the spectral parameters of clinical use.

Virtual sensing technology applied to a swarm of autonomous robots.

This thesis proposes a novel technology in the field of swarm robotics that allows a swarm of robots to sense a virtual environment through virtual sensors. Virtual sensing is a desirable and helpful technology in swarm robotics research activity, because it allows the researchers to efficiently and quickly perform experiments otherwise more expensive and time consuming, or even impossible. In particular, we envision two useful applications for virtual sensing technology. On the one hand, it is possible to prototype and foresee the effects of a new sensor on a robot swarm, before producing it. On the other hand, thanks to this technology it is possible to study the behaviour of robots operating in environments that are not easily reproducible inside a lab for safety reasons or just because physically infeasible. The use of virtual sensing technology for sensor prototyping aims to foresee the behaviour of the swarm enhanced with new or more powerful sensors, without producing the hardware. Sensor prototyping can be used to tune a new sensor or perform performance comparison tests between alternative types of sensors. This kind of prototyping experiments can be performed through the presented tool, that allows to rapidly develop and test software virtual sensors of different typologies and quality, emulating the behaviour of several hardware real sensors. By investigating on which sensors is better to invest, a researcher can minimize the sensors’ production cost while achieving a given swarm performance. Through augmented reality, it is possible to test the performance of the swarm in a desired virtual environment that cannot be set into the lab for physical, logistic or economical reasons. The virtual environment is sensed by the robots through properly designed virtual sensors. Virtual sensing technology allows a researcher to quickly carry out real robots experiment in challenging scenarios without all the required hardware and environment.

Bottom pressure time series study: the ANTARES deep sea observatory case

Questo elaborato riguarda l'analisi delle variazioni di pressione sul fondale del Mar Mediterraneo. Il primo obiettivo era quello di identificare la variabilità a basse frequenze della pressione sul fondo. I dati osservati sono stati raccolti presso l'osservatorio ANTARES che si trova 40 km al largo di Tolone e ricopre un'area di 180x180 m. Sono state analizzate tre serie temporali, L1, L3, L8, e da esse è stata ricostruita una serie temporale dall'1 gennaio 2009 al 31 dicembre 2013. Sono state applicate delle procedure di despiking, media su 30 minuti e gap-filling. Sono stati proposti due metodi di detiding, una media su tre giorni e il filtro di Doodson. Successivamente è stato eseguito un detrending. Un confronto tra l'analisi armonica e il filtro di Doodson mostra una similarità nei risultati. Per questa ragione, per continuare il lavoro, è stata utilizzata la serie a cui era stato tolto il trend e le maree tramite il filtro di Doodson. Togliere le maree ha reso possibile la rimozione dei segnali ad alta frequenza per potersi focalizzare sui segnali rimasti a bassa frequenza. Uno spettro sulla serie ha mostrato i segnali stagionali dominanti insieme alla cosiddetta Chandler wobble con una frequenza di 14 mesi.