Procedures of quality control and data analysis of multi-site ground-based observations for the absolute flux calibration of Gaia

The Gaia space mission is a major project for the European astronomical community. As challenging as it is, the processing and analysis of the huge data-flow incoming from Gaia is the subject of thorough study and preparatory work by the DPAC (Data Processing and Analysis Consortium), in charge of all aspects of the Gaia data reduction. This PhD Thesis was carried out in the framework of the DPAC, within the team based in Bologna. The task of the Bologna team is to define the calibration model and to build a grid of spectro-photometric standard stars (SPSS) suitable for the absolute flux calibration of the Gaia G-band photometry and the BP/RP spectrophotometry. Such a flux calibration can be performed by repeatedly observing each SPSS during the life-time of the Gaia mission and by comparing the observed Gaia spectra to the spectra obtained by our ground-based observations. Due to both the different observing sites involved and the huge amount of frames expected (≃100000), it is essential to maintain the maximum homogeneity in data quality, acquisition and treatment, and a particular care has to be used to test the capabilities of each telescope/instrument combination (through the “instrument familiarization plan”), to devise methods to keep under control, and eventually to correct for, the typical instrumental effects that can affect the high precision required for the Gaia SPSS grid (a few % with respect to Vega). I contributed to the ground-based survey of Gaia SPSS in many respects: with the observations, the instrument familiarization plan, the data reduction and analysis activities (both photometry and spectroscopy), and to the maintenance of the data archives. However, the field I was personally responsible for was photometry and in particular relative photometry for the production of short-term light curves. In this context I defined and tested a semi-automated pipeline which allows for the pre-reduction of imaging SPSS data and the production of aperture photometry catalogues ready to be used for further analysis. A series of semi-automated quality control criteria are included in the pipeline at various levels, from pre-reduction, to aperture photometry, to light curves production and analysis.

Tools and methods for the quality assurance of force platforms in human movement analysis

The human movement analysis (HMA) aims to measure the abilities of a subject to stand or to walk. In the field of HMA, tests are daily performed in research laboratories, hospitals and clinics, aiming to diagnose a disease, distinguish between disease entities, monitor the progress of a treatment and predict the outcome of an intervention [Brand and Crowninshield, 1981; Brand, 1987; Baker, 2006]. To achieve these purposes, clinicians and researchers use measurement devices, like force platforms, stereophotogrammetric systems, accelerometers, baropodometric insoles, etc. This thesis focus on the force platform (FP) and in particular on the quality assessment of the FP data. The principal objective of our work was the design and the experimental validation of a portable system for the in situ calibration of FPs. The thesis is structured as follows: Chapter 1. Description of the physical principles used for the functioning of a FP: how these principles are used to create force transducers, such as strain gauges and piezoelectrics transducers. Then, description of the two category of FPs, three- and six-component, the signals acquisition (hardware structure), and the signals calibration. Finally, a brief description of the use of FPs in HMA, for balance or gait analysis. Chapter 2. Description of the inverse dynamics, the most common method used in the field of HMA. This method uses the signals measured by a FP to estimate kinetic quantities, such as joint forces and moments. The measures of these variables can not be taken directly, unless very invasive techniques; consequently these variables can only be estimated using indirect techniques, as the inverse dynamics. Finally, a brief description of the sources of error, present in the gait analysis. Chapter 3. State of the art in the FP calibration. The selected literature is divided in sections, each section describes: systems for the periodic control of the FP accuracy; systems for the error reduction in the FP signals; systems and procedures for the construction of a FP. In particular is detailed described a calibration system designed by our group, based on the theoretical method proposed by ?. This system was the “starting point” for the new system presented in this thesis. Chapter 4. Description of the new system, divided in its parts: 1) the algorithm; 2) the device; and 3) the calibration procedure, for the correct performing of the calibration process. The algorithm characteristics were optimized by a simulation approach, the results are here presented. In addiction, the different versions of the device are described. Chapter 5. Experimental validation of the new system, achieved by testing it on 4 commercial FPs. The effectiveness of the calibration was verified by measuring, before and after calibration, the accuracy of the FPs in measuring the center of pressure of an applied force. The new system can estimate local and global calibration matrices; by local and global calibration matrices, the non–linearity of the FPs was quantified and locally compensated. Further, a non–linear calibration is proposed. This calibration compensates the non– linear effect in the FP functioning, due to the bending of its upper plate. The experimental results are presented. Chapter 6. Influence of the FP calibration on the estimation of kinetic quantities, with the inverse dynamics approach. Chapter 7. The conclusions of this thesis are presented: need of a calibration of FPs and consequential enhancement in the kinetic data quality. Appendix: Calibration of the LC used in the presented system. Different calibration set–up of a 3D force transducer are presented, and is proposed the optimal set–up, with particular attention to the compensation of non–linearities. The optimal set–up is verified by experimental results.

Kernel Methods for Tree Structured Data

Machine learning comprises a series of techniques for automatic extraction of meaningful information from large collections of noisy data. In many real world applications, data is naturally represented in structured form. Since traditional methods in machine learning deal with vectorial information, they require an a priori form of preprocessing. Among all the learning techniques for dealing with structured data, kernel methods are recognized to have a strong theoretical background and to be effective approaches. They do not require an explicit vectorial representation of the data in terms of features, but rely on a measure of similarity between any pair of objects of a domain, the kernel function. Designing fast and good kernel functions is a challenging problem. In the case of tree structured data two issues become relevant: kernel for trees should not be sparse and should be fast to compute. The sparsity problem arises when, given a dataset and a kernel function, most structures of the dataset are completely dissimilar to one another. In those cases the classifier has too few information for making correct predictions on unseen data. In fact, it tends to produce a discriminating function behaving as the nearest neighbour rule. Sparsity is likely to arise for some standard tree kernel functions, such as the subtree and subset tree kernel, when they are applied to datasets with node labels belonging to a large domain. A second drawback of using tree kernels is the time complexity required both in learning and classification phases. Such a complexity can sometimes prevents the kernel application in scenarios involving large amount of data. This thesis proposes three contributions for resolving the above issues of kernel for trees. A first contribution aims at creating kernel functions which adapt to the statistical properties of the dataset, thus reducing its sparsity with respect to traditional tree kernel functions. Specifically, we propose to encode the input trees by an algorithm able to project the data onto a lower dimensional space with the property that similar structures are mapped similarly. By building kernel functions on the lower dimensional representation, we are able to perform inexact matchings between different inputs in the original space. A second contribution is the proposal of a novel kernel function based on the convolution kernel framework. Convolution kernel measures the similarity of two objects in terms of the similarities of their subparts. Most convolution kernels are based on counting the number of shared substructures, partially discarding information about their position in the original structure. The kernel function we propose is, instead, especially focused on this aspect. A third contribution is devoted at reducing the computational burden related to the calculation of a kernel function between a tree and a forest of trees, which is a typical operation in the classification phase and, for some algorithms, also in the learning phase. We propose a general methodology applicable to convolution kernels. Moreover, we show an instantiation of our technique when kernels such as the subtree and subset tree kernels are employed. In those cases, Direct Acyclic Graphs can be used to compactly represent shared substructures in different trees, thus reducing the computational burden and storage requirements.

Application of FTIR microscopy to cultural heritage materials

Research in art conservation has been developed from the early 1950s, giving a significant contribution to the conservation-restoration of cultural heritage artefacts. In fact, only through a profound knowledge about the nature and conditions of constituent materials, suitable decisions on the conservation and restoration measures can thus be adopted and preservation practices enhanced. The study of ancient artworks is particularly challenging as they can be considered as heterogeneous and multilayered systems where numerous interactions between the different components as well as degradation and ageing phenomena take place. However, difficulties to physically separate the different layers due to their thickness (1-200 µm) can result in the inaccurate attribution of the identified compounds to a specific layer. Therefore, details can only be analysed when the sample preparation method leaves the layer structure intact, as for example the preparation of embedding cross sections in synthetic resins. Hence, spatially resolved analytical techniques are required not only to exactly characterize the nature of the compounds but also to obtain precise chemical and physical information about ongoing changes. This thesis focuses on the application of FTIR microspectroscopic techniques for cultural heritage materials. The first section is aimed at introducing the use of FTIR microscopy in conservation science with a particular attention to the sampling criteria and sample preparation methods. The second section is aimed at evaluating and validating the use of different FTIR microscopic analytical methods applied to the study of different art conservation issues which may be encountered dealing with cultural heritage artefacts: the characterisation of the artistic execution technique (chapter II-1), the studies on degradation phenomena (chapter II-2) and finally the evaluation of protective treatments (chapter II-3). The third and last section is divided into three chapters which underline recent developments in FTIR spectroscopy for the characterisation of paint cross sections and in particular thin organic layers: a newly developed preparation method with embedding systems in infrared transparent salts (chapter III-1), the new opportunities offered by macro-ATR imaging spectroscopy (chapter III-2) and the possibilities achieved with the different FTIR microspectroscopic techniques nowadays available (chapter III-3). In chapter II-1, FTIR microspectroscopy as molecular analysis, is presented in an integrated approach with other analytical techniques. The proposed sequence is optimized in function of the limited quantity of sample available and this methodology permits to identify the painting materials and characterise the adopted execution technique and state of conservation. Chapter II-2 describes the characterisation of the degradation products with FTIR microscopy since the investigation on the ageing processes encountered in old artefacts represents one of the most important issues in conservation research. Metal carboxylates resulting from the interaction between pigments and binding media are characterized using synthesised metal palmitates and their production is detected on copper-, zinc-, manganese- and lead- (associated with lead carbonate) based pigments dispersed either in oil or egg tempera. Moreover, significant effects seem to be obtained with iron and cobalt (acceleration of the triglycerides hydrolysis). For the first time on sienna and umber paints, manganese carboxylates are also observed. Finally in chapter II-3, FTIR microscopy is combined with further elemental analyses to characterise and estimate the performances and stability of newly developed treatments, which should better fit conservation-restoration problems. In the second part, in chapter III-1, an innovative embedding system in potassium bromide is reported focusing on the characterisation and localisation of organic substances in cross sections. Not only the identification but also the distribution of proteinaceous, lipidic or resinaceous materials, are evidenced directly on different paint cross sections, especially in thin layers of the order of 10 µm. Chapter III-2 describes the use of a conventional diamond ATR accessory coupled with a focal plane array to obtain chemical images of multi-layered paint cross sections. A rapid and simple identification of the different compounds is achieved without the use of any infrared microscope objectives. Finally, the latest FTIR techniques available are highlighted in chapter III-3 in a comparative study for the characterisation of paint cross sections. Results in terms of spatial resolution, data quality and chemical information obtained are presented and in particular, a new FTIR microscope equipped with a linear array detector, which permits reducing the spatial resolution limit to approximately 5 µm, provides very promising results and may represent a good alternative to either mapping or imaging systems.

Three dimensional seismic imaging and earthquake locations in a complex, segmented fault region in Southern Apennines (Italy)

The southern Apennines of Italy have been experienced several destructive earthquakes both in historic and recent times. The present day seismicity, characterized by small-to-moderate magnitude earthquakes, was used like a probe to obatin a deeper knowledge of the fault structures where the largest earthquakes occurred in the past. With the aim to infer a three dimensional seismic image both the problem of data quality and the selection of a reliable and robust tomographic inversion strategy have been faced. The data quality has been obtained to develop optimized procedures for the measurements of P- and S-wave arrival times, through the use of polarization filtering and to the application of a refined re-picking technique based on cross-correlation of waveforms. A technique of iterative tomographic inversion, linearized, damped combined with a strategy of multiscale inversion type has been adopted. The retrieved P-wave velocity model indicates the presence of a strong velocity variation along a direction orthogonal to the Apenninic chain. This variation defines two domains which are characterized by a relatively low and high velocity values. From the comparison between the inferred P-wave velocity model with a portion of a structural section available in literature, the high velocity body was correlated with the Apulia carbonatic platforms whereas the low velocity bodies was associated to the basinal deposits. The deduced Vp/Vs ratio shows that the ratio is lower than 1.8 in the shallower part of the model, while for depths ranging between 5 km and 12 km the ratio increases up to 2.1 in correspondence to the area of higher seismicity. This confirms that areas characterized by higher values are more prone to generate earthquakes as a response to the presence of fluids and higher pore-pressures.

Measurement of K(892)*0 resonance production in Pb-Pb collisions with the ALICE experiment at the LHC

The analysis of the K(892)*0 resonance production in Pb–Pb collisions at √sNN = 2.76 TeV with the ALICE detector at the LHC is presented. The analysis is motivated by the interest in the measurement of short-lived resonances production that can provide insights on the properties of the medium produced in heavy-ion collisions both during its partonic (Quark-Gluon Plasma) and hadronic phase. This particular analysis exploits particle identification of the ALICE Time-Of-Flight detector. The ALICE experiment is presented, with focus on the performance of the Time-Of-Flight system. The aspects of calibration and data quality controls are discussed in detail, while illustrating the excellent and very stable performance of the system in different collision environments at the LHC. A full analysis of the K*0 resonance production is presented: from the resonance reconstruction to the determination of the efficiency and the systematic uncertainty. The results show that the analysis strategy discussed is a valid tool to measure the K∗0 up to intermediate momenta. Preliminary results on K*0 resonance production at the LHC are presented and confirmed to be a powerful tool to study the physics of ultra-relativistic heavy-ion collisions.

Radar based improvements and diagnosis of the convective capabilities of the cosmo-2 model

In the last few years the resolution of numerical weather prediction (nwp) became higher and higher with the progresses of technology and knowledge. As a consequence, a great number of initial data became fundamental for a correct initialization of the models. The potential of radar observations has long been recognized for improving the initial conditions of high-resolution nwp models, while operational application becomes more frequent. The fact that many nwp centres have recently taken into operations convection-permitting forecast models, many of which assimilate radar data, emphasizes the need for an approach to providing quality information which is needed in order to avoid that radar errors degrade the model's initial conditions and, therefore, its forecasts. Environmental risks can can be related with various causes: meteorological, seismical, hydrological/hydraulic. Flash floods have horizontal dimension of 1-20 Km and can be inserted in mesoscale gamma subscale, this scale can be modeled only with nwp model with the highest resolution as the COSMO-2 model. One of the problems of modeling extreme convective events is related with the atmospheric initial conditions, in fact the scale dimension for the assimilation of atmospheric condition in an high resolution model is about 10 Km, a value too high for a correct representation of convection initial conditions. Assimilation of radar data with his resolution of about of Km every 5 or 10 minutes can be a solution for this problem. In this contribution a pragmatic and empirical approach to deriving a radar data quality description is proposed to be used in radar data assimilation and more specifically for the latent heat nudging (lhn) scheme. Later the the nvective capabilities of the cosmo-2 model are investigated through some case studies. Finally, this work shows some preliminary experiments of coupling of a high resolution meteorological model with an Hydrological one.