Valutazione della qualità ed autenticità di prodotti oleari e lattiero caseari mediante metodi fisici di analisi accoppiati a tecniche statistiche multivariate

Questa tesi descrive alcuni studi di messa a punto di metodi di analisi fisici accoppiati con tecniche statistiche multivariate per valutare la qualità e l’autenticità di oli vegetali e prodotti caseari. L’applicazione di strumenti fisici permette di abbattere i costi ed i tempi necessari per le analisi classiche ed allo stesso tempo può fornire un insieme diverso di informazioni che possono riguardare tanto la qualità come l’autenticità di prodotti. Per il buon funzionamento di tali metodi è necessaria la costruzione di modelli statistici robusti che utilizzino set di dati correttamente raccolti e rappresentativi del campo di applicazione. In questo lavoro di tesi sono stati analizzati oli vegetali e alcune tipologie di formaggi (in particolare pecorini per due lavori di ricerca e Parmigiano-Reggiano per un altro). Sono stati utilizzati diversi strumenti di analisi (metodi fisici), in particolare la spettroscopia, l’analisi termica differenziale, il naso elettronico, oltre a metodiche separative tradizionali. I dati ottenuti dalle analisi sono stati trattati mediante diverse tecniche statistiche, soprattutto: minimi quadrati parziali; regressione lineare multipla ed analisi discriminante lineare.

NLGA based Active Control in Aerospace: fault tolerability, disturbance rejection, and parameter estimation

A new control scheme has been presented in this thesis. Based on the NonLinear Geometric Approach, the proposed Active Control System represents a new way to see the reconfigurable controllers for aerospace applications. The presence of the Diagnosis module (providing the estimation of generic signals which, based on the case, can be faults, disturbances or system parameters), mean feature of the depicted Active Control System, is a characteristic shared by three well known control systems: the Active Fault Tolerant Controls, the Indirect Adaptive Controls and the Active Disturbance Rejection Controls. The standard NonLinear Geometric Approach (NLGA) has been accurately investigated and than improved to extend its applicability to more complex models. The standard NLGA procedure has been modified to take account of feasible and estimable sets of unknown signals. Furthermore the application of the Singular Perturbations approximation has led to the solution of Detection and Isolation problems in scenarios too complex to be solved by the standard NLGA. Also the estimation process has been improved, where multiple redundant measuremtent are available, by the introduction of a new algorithm, here called "Least Squares - Sliding Mode". It guarantees optimality, in the sense of the least squares, and finite estimation time, in the sense of the sliding mode. The Active Control System concept has been formalized in two controller: a nonlinear backstepping controller and a nonlinear composite controller. Particularly interesting is the integration, in the controller design, of the estimations coming from the Diagnosis module. Stability proofs are provided for both the control schemes. Finally, different applications in aerospace have been provided to show the applicability and the effectiveness of the proposed NLGA-based Active Control System.

Morphological integration between the cranial base and the face in children and adults

The primary aim of the present study was to assess morphological covariation between the face and the basicranium (midline and lateral), and to evaluate patterns of integration at two specific developmental stages. A group of 71 children (6-10 years) was compared with a group of 71 adults (20-35 years). Lateral cephalometric radiographs were digitized and a total of 28 landmarks were placed on three areas; the midline cranial base, the lateral cranial base and the face. Geometric morphometric methods were applied and partial least squares analysis was used to evaluate correlation between the three shape blocks. Morphological integration was tested both with and without removing the effect of allometry. In children, mainly the midline and, to a lesser extent, the lateral cranial base were moderately correlated to the face. In adults, the correlation between the face and the midline cranial base, which ceases development earlier than the lateral base, was reduced. However, the lateral cranial base retained and even strengthened its correlation to the face. This suggests that the duration of common developmental timing is an important factor that influences integration between craniofacial structures. However, despite the apparent switch of primary roles between the cranial bases during development, the patterns of integration remained stable, thereby supporting the role of genetics over function in the establishment and development of craniofacial shape.

Investigation of different apple cultivars by high resolution magic angle spinning NMR. A feasibility study

(1)H HR-MAS NMR spectroscopy was applied to apple tissue samples deriving from 3 different cultivars. The NMR data were statistically evaluated by analysis of variance (ANOVA), principal component analysis (PCA), and partial least-squares-discriminant analysis (PLS-DA). The intra-apple variability of the compounds was found to be significantly lower than the inter-apple variability within one cultivar. A clear separation of the three different apple cultivars could be obtained by multivariate analysis. Direct comparison of the NMR spectra obtained from apple tissue (with HR-MAS) and juice (with liquid-state HR NMR) showed distinct differences in some metabolites, which are probably due to changes induced by juice preparation. This preliminary study demonstrates the feasibility of (1)H HR-MAS NMR in combination with multivariate analysis as a tool for future chemometric studies applied to intact fruit tissues, e.g. for investigating compositional changes due to physiological disorders, specific growth or storage conditions.

The Incumbent Spending Puzzle

Objective This article seeks to explain the puzzle of why incumbents spend so much on campaigns despite most research finding that their spending has almost no effect on voters. Methods The article uses ordinary least squares, instrumental variables, and fixed-effects regression to estimate the impact of incumbent spending on election outcomes. The estimation includes an interaction term between incumbent and challenger spending to allow the effect of incumbent spending to depend on the level of challenger spending. Results The estimation provides strong evidence that spending by the incumbent has a larger positive impact on votes received the more money the challenger spends. Conclusion Campaign spending by incumbents is most valuable in the races where the incumbent faces a serious challenge. Raising large sums of money to be used in close races is thus a rational choice by incumbents.

Broadband Fourier transform rotational spectroscopy for structure determination: The water heptamer

Over the recent years chirped-pulse, Fourier-transform microwave (CP-FTMW) spectrometers have chan- ged the scope of rotational spectroscopy. The broad frequency and large dynamic range make possible structural determinations in molecular systems of increasingly larger size from measurements of heavy atom (13C, 15N, 18O) isotopes recorded in natural abundance in the same spectrum as that of the parent isotopic species. The design of a broadband spectrometer operating in the 2–8 GHz frequency range with further improvements in sensitivity is presented. The current CP-FTMW spectrometer performance is benchmarked in the analyses of the rotational spectrum of the water heptamer, (H2O)7, in both 2– 8 GHz and 6–18 GHz frequency ranges. Two isomers of the water heptamer have been observed in a pulsed supersonic molecular expansion. High level ab initio structural searches were performed to pro- vide plausible low-energy candidates which were directly compared with accurate structures provided from broadband rotational spectra. The full substitution structure of the most stable species has been obtained through the analysis of all possible singly-substituted isotopologues (H218O and HDO), and a least-squares rm(1) geometry of the oxygen framework determined from 16 different isotopic species compares with the calculated O–O equilibrium distances at the 0.01 Å level.

Broadband Fourier transform rotational spectroscopy for structure determination: The water heptamer

Over the recent years chirped-pulse, Fourier-transform microwave (CP-FTMW) spectrometers have changed the scope of rotational spectroscopy. The broad frequency and large dynamic range make possible structural determinations in molecular systems of increasingly larger size from measurements of heavy atom (C-13, N-15, O-18) isotopes recorded in natural abundance in the same spectrum as that of the parent isotopic species. The design of a broadband spectrometer operating in the 2-8 GHz frequency range with further improvements in sensitivity is presented. The current CP-FTMW spectrometer performance is benchmarked in the analyses of the rotational spectrum of the water heptamer, (H2O)(7), in both 2-8 GHz and 6-18 GHz frequency ranges. Two isomers of the water heptamer have been observed in a pulsed supersonic molecular expansion. High level ab initio structural searches were performed to provide plausible low-energy candidates which were directly compared with accurate structures provided from broadband rotational spectra. The full substitution structure of the most stable species has been obtained through the analysis of all possible singly-substituted isotopologues ((H2O)-O-18 and HDO), and a least-squares r(m)((1)) geometry of the oxygen framework determined from 16 different isotopic species compares with the calculated O-O equilibrium distances at the 0.01 angstrom level. (C) 2013 Elsevier B.V. All rights reserved.

Exploring High-resolution Magic Angle Spinning (HR-MAS) NMR Spectroscopy for Metabonomic Analysis of Apples

Classical liquid-state high-resolution (HR) NMR spectroscopy has proved a powerful tool in the metabonomic analysis of liquid food samples like fruit juices. In this paper the application of (1)H high-resolution magic angle spinning (HR-MAS) NMR spectroscopy to apple tissue is presented probing its potential for metabonomic studies. The (1)H HR-MAS NMR spectra are discussed in terms of the chemical composition of apple tissue and compared to liquid-state NMR spectra of apple juice. Differences indicate that specific metabolic changes are induced by juice preparation. The feasibility of HR-MAS NMR-based multivariate analysis is demonstrated by a study distinguishing three different apple cultivars by principal component analysis (PCA). Preliminary results are shown from subsequent studies comparing three different cultivation methods by means of PCA and partial least squares discriminant analysis (PLS-DA) of the HR-MAS NMR data. The compounds responsible for discriminating organically grown apples are discussed. Finally, an outlook of our ongoing work is given including a longitudinal study on apples.

The Effects of Interstate Speed Limit Increases: Fatality Rates and Traffic Diversion Versus Speed Spillover

This thesis examines two panel data sets of 48 states from 1981 to 2009 and utilizes ordinary least squares (OLS) and fixed effects models to explore the relationship between rural Interstate speed limits and fatality rates and whether rural Interstate speed limits affect non-Interstate safety. Models provide evidence that rural Interstate speed limits higher than 55 MPH lead to higher fatality rates on rural Interstates though this effect is somewhat tempered by reductions in fatality rates for roads other than rural Interstates. These results provide some but not unanimous support for the traffic diversion hypothesis that rural Interstate speed limit increases lead to decreases in fatality rates of other roads. To the author’s knowledge, this paper is the first econometric study to differentiate between the effects of 70 MPH speed limits and speed limits above 70 MPH on fatality rates using a multi-state data set. Considering both rural Interstates and other roads, rural Interstate speed limit increases above 55 MPH are responsible for 39,700 net fatalities, 4.1 percent of total fatalities from 1987, the year limits were first raised, to 2009.

Vibrational Relaxation of 13CO2(v2) by Atomic Oxygen

Carbon dioxide (CO2) has been of recent interest due to the issue of greenhouse cooling in the upper atmosphere by species such as CO2 and NO. In the Earth’s upper atmosphere, between altitudes of 75 and 110 km, a collisional energy exchange occurs between CO2 and atomic oxygen, which promotes a population of ground state CO2 to the bend excited state. The relaxation of CO2 following this excitation is characterized by spontaneous emission of 15-μm. Most of this energy is emitted away from Earth. Due to the low density in the upper atmosphere, most of this energy is not reabsorbed and thus escapes into space, leading to a local cooling effect in the upper atmosphere. To determine the efficiency of the CO2- O atom collisional energy exchange, transient diode laser absorption spectroscopy was used to monitor the population of the first vibrationally excited state, 13CO2(0110) or ν2, as a function of time. The rate coefficient, kO(ν2), for the vibrational relaxation 13CO2 (ν2)-O was determined by fitting laboratory measurements using a home-written linear least squares algorithm. The rate coefficient, kO(ν2), of the vibrational relaxation of 13CO2(ν2), by atomic oxygen at room temperature was determined to be (1.6 ± 0.3 x 10-12 cm3 s-1), which is within the uncertainty of the rate coefficient previously found in this group for 12CO2(ν2) relaxation. The cold temperature kO(ν2) values were determined to be: (2.1 ± 0.8) x 10-12 cm3 s-1 at Tfinal = 274 K, (1.8 ± 0.3) x 10-12 cm3 s-1 at Tfinal = 239 K, (2 ± 1) x 10-12 cm3 s-1 at Tfinal = 208 K, and (1.7 ± 0.3) x 10-12 cm3 s-1 at Tfinal = 186 K. These data did not show a definitive negative temperature dependence comparable to that found for 12CO2 previously.

Assessment of spline-based 2D-3D registration for image-guided spine surgery

2D-3D registration of pre-operative 3D volumetric data with a series of calibrated and undistorted intra-operative 2D projection images has shown great potential in CT-based surgical navigation because it obviates the invasive procedure of the conventional registration methods. In this study, a recently introduced spline-based multi-resolution 2D-3D image registration algorithm has been adapted together with a novel least-squares normalized pattern intensity (LSNPI) similarity measure for image guided minimally invasive spine surgery. A phantom and a cadaver together with their respective ground truths were specially designed to experimentally assess possible factors that may affect the robustness, accuracy, or efficiency of the registration. Our experiments have shown that it is feasible for the assessed 2D-3D registration algorithm to achieve sub-millimeter accuracy in a realistic setup in less than one minute.

Application and comparison of classification algorithms for recognition of Alzheimer's disease in electrical brain activity (EEG)

The early detection of subjects with probable Alzheimer's disease (AD) is crucial for effective appliance of treatment strategies. Here we explored the ability of a multitude of linear and non-linear classification algorithms to discriminate between the electroencephalograms (EEGs) of patients with varying degree of AD and their age-matched control subjects. Absolute and relative spectral power, distribution of spectral power, and measures of spatial synchronization were calculated from recordings of resting eyes-closed continuous EEGs of 45 healthy controls, 116 patients with mild AD and 81 patients with moderate AD, recruited in two different centers (Stockholm, New York). The applied classification algorithms were: principal component linear discriminant analysis (PC LDA), partial least squares LDA (PLS LDA), principal component logistic regression (PC LR), partial least squares logistic regression (PLS LR), bagging, random forest, support vector machines (SVM) and feed-forward neural network. Based on 10-fold cross-validation runs it could be demonstrated that even tough modern computer-intensive classification algorithms such as random forests, SVM and neural networks show a slight superiority, more classical classification algorithms performed nearly equally well. Using random forests classification a considerable sensitivity of up to 85% and a specificity of 78%, respectively for the test of even only mild AD patients has been reached, whereas for the comparison of moderate AD vs. controls, using SVM and neural networks, values of 89% and 88% for sensitivity and specificity were achieved. Such a remarkable performance proves the value of these classification algorithms for clinical diagnostics.

Gauss-Seidel Estimation of Generalized Linear Mixed Models with Application to Poisson Modeling of Spatially Varying Disease Rates

Generalized linear mixed models (GLMMs) provide an elegant framework for the analysis of correlated data. Due to the non-closed form of the likelihood, GLMMs are often fit by computational procedures like penalized quasi-likelihood (PQL). Special cases of these models are generalized linear models (GLMs), which are often fit using algorithms like iterative weighted least squares (IWLS). High computational costs and memory space constraints often make it difficult to apply these iterative procedures to data sets with very large number of cases. This paper proposes a computationally efficient strategy based on the Gauss-Seidel algorithm that iteratively fits sub-models of the GLMM to subsetted versions of the data. Additional gains in efficiency are achieved for Poisson models, commonly used in disease mapping problems, because of their special collapsibility property which allows data reduction through summaries. Convergence of the proposed iterative procedure is guaranteed for canonical link functions. The strategy is applied to investigate the relationship between ischemic heart disease, socioeconomic status and age/gender category in New South Wales, Australia, based on outcome data consisting of approximately 33 million records. A simulation study demonstrates the algorithm's reliability in analyzing a data set with 12 million records for a (non-collapsible) logistic regression model.

Unifying energy minimization and mutual information maximization for robust 2D/3D registration of X-ray and CT images

Similarity measure is one of the main factors that affect the accuracy of intensity-based 2D/3D registration of X-ray fluoroscopy to CT images. Information theory has been used to derive similarity measure for image registration leading to the introduction of mutual information, an accurate similarity measure for multi-modal and mono-modal image registration tasks. However, it is known that the standard mutual information measure only takes intensity values into account without considering spatial information and its robustness is questionable. Previous attempt to incorporate spatial information into mutual information either requires computing the entropy of higher dimensional probability distributions, or is not robust to outliers. In this paper, we show how to incorporate spatial information into mutual information without suffering from these problems. Using a variational approximation derived from the Kullback-Leibler bound, spatial information can be effectively incorporated into mutual information via energy minimization. The resulting similarity measure has a least-squares form and can be effectively minimized by a multi-resolution Levenberg-Marquardt optimizer. Experimental results are presented on datasets of two applications: (a) intra-operative patient pose estimation from a few (e.g. 2) calibrated fluoroscopic images, and (b) post-operative cup alignment estimation from single X-ray radiograph with gonadal shielding.