13C NMR of a single molecule magnet: analysis of pseudocontact shifts and residual dipolar couplings

Paramagnetic triple decker complexes of lanthanides are promising Single Molecule Magnets (SMMs), with many potential uses. Some of them show preferable relaxation behavior, which enables the recording of well resolved NMR spectra. These axially symmetric complexes are also strongly magnetically anisotropic, and this property can be described with the axial component of the magnetic susceptibility tensor, χa. For triple decker complexes with phthalocyanine based ligands, the Fermi˗contact contribution is small. Hence, together with the axial symmetry, the experimental chemical shifts in 1H and 13C NMR spectra can be modeled easily by considering pseudocontact and orbital shifts alone. This results in the determination of the χa value, which is also responsible for molecular alignment and consequently for the observation of residual dipolar couplings (RDCs). A detailed analysis of the experimental 1H-13C and 1H-1H couplings revealed that contributions from RDCs (positive and negative) and from dynamic frequency shifts (negative for all observed couplings) have to be considered. Whilst the pseudocontact shifts depend on the average positions of 1H and 13C nuclei relative to the lanthanide ions, the RDCs are related to the mobility of nuclei they correspond to. This phenomenon allows for the measurement of the internal mobility of the various groups in the SMMs.

Twitter data analysis for financial markets

Over the time, Twitter has become a fundamental source of information for news. As a one step forward, researchers have tried to analyse if the tweets contain predictive power. In the past, in financial field, a lot of research has been done to propose a function which takes as input all the tweets for a particular stock or index s, analyse them and predict the stock or index price of s. In this work, we take an alternative approach: using the stock price and tweet information, we investigate following questions. 1. Is there any relation between the amount of tweets being generated and the stocks being exchanged? 2. Is there any relation between the sentiment of the tweets and stock prices? 3. What is the structure of the graph that describes the relationships between users?

UWB radar sensor networks: Detection algorithms design and experimental analysis

In the last years radar sensor networks for localization and tracking in indoor environment have generated more and more interest, especially for anti-intrusion security systems. These networks often use Ultra Wide Band (UWB) technology, which consists in sending very short (few nanoseconds) impulse signals. This approach guarantees high resolution and accuracy and also other advantages such as low price, low power consumption and narrow-band interference (jamming) robustness. In this thesis the overall data processing (done in MATLAB environment) is discussed, starting from experimental measures from sensor devices, ending with the 2D visualization of targets movements over time and focusing mainly on detection and localization algorithms. Moreover, two different scenarios and both single and multiple target tracking are analyzed.