Simulative Investigation on the Electronic, Vibrational and Optical Properties of the Ge2Sb2Te5 Chalcogenide

Chalcogenides are chemical compounds with at least one of the following three chemical elements: Sulfur (S), Selenium (Sn), and Tellurium (Te). As opposed to other materials, chalcogenide atomic arrangement can quickly and reversibly inter-change between crystalline, amorphous and liquid phases. Therefore they are also called phase change materials. As a results, chalcogenide thermal, optical, structural, electronic, electrical properties change pronouncedly and significantly with the phase they are in, leading to a host of different applications in different areas. The noticeable optical reflectivity difference between crystalline and amorphous phases has allowed optical storage devices to be made. Their very high thermal conductivity and heat fusion provided remarkable benefits in the frame of thermal energy storage for heating and cooling in residential and commercial buildings. The outstanding resistivity difference between crystalline and amorphous phases led to a significant improvement of solid state storage devices from the power consumption to the re-writability to say nothing of the shrinkability. This work focuses on a better understanding from a simulative stand point of the electronic, vibrational and optical properties for the crystalline phases (hexagonal and faced-centered cubic). The electronic properties are calculated implementing the density functional theory combined with pseudo-potentials, plane waves and the local density approximation. The phonon properties are computed using the density functional perturbation theory. The phonon dispersion and spectrum are calculated using the density functional perturbation theory. As it relates to the optical constants, the real part dielectric function is calculated through the Drude-Lorentz expression. The imaginary part results from the real part through the Kramers-Kronig transformation. The refractive index, the extinctive and absorption coefficients are analytically calculated from the dielectric function. The transmission and reflection coefficients are calculated using the Fresnel equations. All calculated optical constants compare well the experimental ones.

Variability analysis of discrete event series and wavefront patterns in surface electrocardiogram: contributions to psychophysiological and clinical research

The surface electrocardiogram (ECG) is an established diagnostic tool for the detection of abnormalities in the electrical activity of the heart. The interest of the ECG, however, extends beyond the diagnostic purpose. In recent years, studies in cognitive psychophysiology have related heart rate variability (HRV) to memory performance and mental workload. The aim of this thesis was to analyze the variability of surface ECG derived rhythms, at two different time scales: the discrete-event time scale, typical of beat-related features (Objective I), and the “continuous” time scale of separated sources in the ECG (Objective II), in selected scenarios relevant to psychophysiological and clinical research, respectively. Objective I) Joint time-frequency and non-linear analysis of HRV was carried out, with the goal of assessing psychophysiological workload (PPW) in response to working memory engaging tasks. Results from fourteen healthy young subjects suggest the potential use of the proposed indices in discriminating PPW levels in response to varying memory-search task difficulty. Objective II) A novel source-cancellation method based on morphology clustering was proposed for the estimation of the atrial wavefront in atrial fibrillation (AF) from body surface potential maps. Strong direct correlation between spectral concentration (SC) of atrial wavefront and temporal variability of the spectral distribution was shown in persistent AF patients, suggesting that with higher SC, shorter observation time is required to collect spectral distribution, from which the fibrillatory rate is estimated. This could be time and cost effective in clinical decision-making. The results held for reduced leads sets, suggesting that a simplified setup could also be considered, further reducing the costs. In designing the methods of this thesis, an online signal processing approach was kept, with the goal of contributing to real-world applicability. An algorithm for automatic assessment of ambulatory ECG quality, and an automatic ECG delineation algorithm were designed and validated.

Social learning and action understanding in human observers: contributions of sensori-motor constraints and prior information

The aim of this thesis was to investigate the respective contribution of prior information and sensorimotor constraints to action understanding, and to estimate their consequences on the evolution of human social learning. Even though a huge amount of literature is dedicated to the study of action understanding and its role in social learning, these issues are still largely debated. Here, I critically describe two main perspectives. The first perspective interprets faithful social learning as an outcome of a fine-grained representation of others’ actions and intentions that requires sophisticated socio-cognitive skills. In contrast, the second perspective highlights the role of simpler decision heuristics, the recruitment of which is determined by individual and ecological constraints. The present thesis aims to show, through four experimental works, that these two contributions are not mutually exclusive. A first study investigates the role of the inferior frontal cortex (IFC), the anterior intraparietal area (AIP) and the primary somatosensory cortex (S1) in the recognition of other people’s actions, using a transcranial magnetic stimulation adaptation paradigm (TMSA). The second work studies whether, and how, higher-order and lower-order prior information (acquired from the probabilistic sampling of past events vs. derived from an estimation of biomechanical constraints of observed actions) interacts during the prediction of other people’s intentions. Using a single-pulse TMS procedure, the third study investigates whether the interaction between these two classes of priors modulates the motor system activity. The fourth study tests the extent to which behavioral and ecological constraints influence the emergence of faithful social learning strategies at a population level. The collected data contribute to elucidate how higher-order and lower-order prior expectations interact during action prediction, and clarify the neural mechanisms underlying such interaction. Finally, these works provide/open promising perspectives for a better understanding of social learning, with possible extensions to animal models.