Stress management in mothers of children with Autism Spectrum Disorder : psychological characteristics, coping strategies and biological correlates

Un figlio con un Disturbo dello Spettro Autistico, caratterizzato da gravi difficoltà nelle relazioni, nei comportamenti e nella comunicazione, costringe tutto il sistema familiare a gestire un notevole stress dovuto alla gestione quotidiana di una patologia così complessa. Per questi motivi, i genitori necessitano di un sostegno il più possibile personalizzato rispetto alle caratteristiche del loro contesto familiare. Per fare questo sarebbe importante individuare quali siano i parametri correlati ai livelli di stress nei familiari di pazienti con autismo e che potrebbero avere un’influenza sul benessere familiare. Lo scopo di questo studio è quello di valutare quali caratteristiche di personalità, stili di coping e capacità di gestire le emozioni possano essere in relazione con la reattività individuale alle situazioni di stress, valutata attraverso alcuni correlati biologici, quali il livello di cortisolo (l’ormone dello stress) e la variabilità della frequenza cardiaca. L’ottica di ricerca applicata fa sì che gli obiettivi ultimi di questo lavoro siano anche quelli di diminuire l’accesso ai servizi per questi soggetti, considerando il fatto che progetti individualizzati di sostegno genitoriale costituiscono un fattore protettivo rispetto a conseguenze fisiche e psicologiche di disagio se implementati tenendo conto della variabilità individuale rispetto alle caratteristiche sopra citate.

Advanced receivers for next generation wireless communication systems

Despite extensive progress on the theoretical aspects of spectral efficient communication systems, hardware impairments, such as phase noise, are the key bottlenecks in next generation wireless communication systems. The presence of non-ideal oscillators at the transceiver introduces time varying phase noise and degrades the performance of the communication system. Significant research literature focuses on joint synchronization and decoding based on joint posterior distribution, which incorporate both the channel and code graph. These joint synchronization and decoding approaches operate on well designed sum-product algorithms, which involves calculating probabilistic messages iteratively passed between the channel statistical information and decoding information. Channel statistical information, generally entails a high computational complexity because its probabilistic model may involve continuous random variables. The detailed knowledge about the channel statistics for these algorithms make them an inadequate choice for real world applications due to power and computational limitations. In this thesis, novel phase estimation strategies are proposed, in which soft decision-directed iterative receivers for a separate A Posteriori Probability (APP)-based synchronization and decoding are proposed. These algorithms do not require any a priori statistical characterization of the phase noise process. The proposed approach relies on a Maximum A Posteriori (MAP)-based algorithm to perform phase noise estimation and does not depend on the considered modulation/coding scheme as it only exploits the APPs of the transmitted symbols. Different variants of APP-based phase estimation are considered. The proposed algorithm has significantly lower computational complexity with respect to joint synchronization/decoding approaches at the cost of slight performance degradation. With the aim to improve the robustness of the iterative receiver, we derive a new system model for an oversampled (more than one sample per symbol interval) phase noise channel. We extend the separate APP-based synchronization and decoding algorithm to a multi-sample receiver, which exploits the received information from the channel by exchanging the information in an iterative fashion to achieve robust convergence. Two algorithms based on sliding block-wise processing with soft ISI cancellation and detection are proposed, based on the use of reliable information from the channel decoder. Dually polarized systems provide a cost-and spatial-effective solution to increase spectral efficiency and are competitive candidates for next generation wireless communication systems. A novel soft decision-directed iterative receiver, for separate APP-based synchronization and decoding, is proposed. This algorithm relies on an Minimum Mean Square Error (MMSE)-based cancellation of the cross polarization interference (XPI) followed by phase estimation on the polarization of interest. This iterative receiver structure is motivated from Master/Slave Phase Estimation (M/S-PE), where M-PE corresponds to the polarization of interest. The operational principle of a M/S-PE block is to improve the phase tracking performance of both polarization branches: more precisely, the M-PE block tracks the co-polar phase and the S-PE block reduces the residual phase error on the cross-polar branch. Two variants of MMSE-based phase estimation are considered; BW and PLP.