Length scales of dynamic heterogeneities of low and high molecular weight glass formers from multidimensional NMR

Das Ziel der vorliegenden Arbeit ist die Untersuchung der räumlichen und zeitlichen Aspekte der heterogenen Dynamik in Modellglasbildnern. Dabei wird vor allem die langsame alpha-Relaxationsdynamik oberhalb des Glasüberganges Tg untersucht. Die nukleare Magnetresonanz zeigt ihre einmalige Vielseitigkeit bei der Untersuchung molekularer Dynamik, wenn die angewandten Techniken und Experimente durch Simulationen unterstützt werden. Die räumliche Aspekt dynamischer Heterogenitäten wird untersucht durch ein reduziertes vierdimensionales Spindiffusionsexperiment (4D3CP), ein Experiment, das Reorientierungsraten örtlich korreliert. Eine Simulation dieses Experimentes an einem System harter Kugeln liefert wertvolle Informationen über die Auswertemethode des 4D3CP Experiments. Glycerol und o-terphenyl werden durch das 4D3CP Experiment untersucht. Die erhaltenen Resultate werden mit bereits publizierten Daten des polymeren Glasbildners PVAc verglichen. Während PVAc und o-terphenyl eine Längenskale von 3.7 nm bzw. 2.9 nm aufweisen, ist die Längenskale von Glycerol signifikant kleiner bei 1.1 nm. Ein neues Experiment, welches sensitiv auf Translationsbewegung reagiert, wird vorgestellt. Durch Verwendung eines pi-Impulszuges kann eine separate Evolution unter dem Hamiltonian der dipolaren Kopplung und der chemischen Verschiebungsanisotropie erreicht werden.

Assessing poverty with survey data. Uni-dimensional, multidimensional and resilience poverty analysis in Kenya

Traditionally Poverty has been measured by a unique indicator, income, assuming this was the most relevant dimension of poverty. Sen’s approach has dramatically changed this idea shedding light over the existence of many more dimensions and over the multifaceted nature of poverty; poverty cannot be represented by a unique indicator that only can evaluate a specific aspect of poverty. This thesis tracks an ideal path along with the evolution of the poverty analysis. Starting from the unidimensional analysis based on income and consumptions, this research enter the world of multidimensional analysis. After reviewing the principal approaches, the Foster and Alkire method is critically analyzed and implemented over data from Kenya. A step further is moved in the third part of the thesis, introducing a new approach to multidimensional poverty assessment: the resilience analysis.

Multidimensional project control system: applicazione di verifica della qualità dei progetti in Despar Italia c.r.l.

La dissertazione affronterà il tema del controllo qualità nei progetti, applicando conoscenze, tecniche e strumenti propri del Project e del Multiproject Management. L’analisi partirà svolgendo, nel primo capitolo, considerazioni introduttive riguardo le due discipline citate. Lo scopo ultimo sarà quello di elaborare un sistema di controllo integrato della qualità, indirizzato principalmente al Project Management che è presente in una qualsiasi organizzazione che opera per progetti. Nel secondo capitolo verrà illustrato il metodo denominato Multidimensional Project control System sul quale il modello sviluppato in seguito si basa. La progettazione di un sistema di controllo è una parte importante dello sforzo di gestione di un progetto. Tale sistema è basato su una serie di obiettivi di progetto e sulla loro importanza relativa e fonda la sua natura su una sistematica valutazione in corso d’opera dello stato di conformità del progetto, sia a livello di processo che a livello di output. Nel capitolo conclusivo si affronta l’obiettivo principale di questo elaborato. Sono stati forniti dati e documenti dall’azienda Despar Italia c.r.l. ed è stato chiesto di sviluppare un metodo di controllo che il Project Management potesse utilizzare per implementare un processo di verifica della qualità di progetto. Viene quindi descritta l’azienda, come il Management pianifica, gestisce e controlla i progetti e quali necessità devono essere soddisfatte. Si procede poi con l’illustrazione e spiegazione del metodo sviluppato, chiarito da un esempio esplicativo. L’elaborato si concluderà con delle riflessioni finali, proponendo critiche e spunti per eventuali sviluppi futuri.

Multidimensional Measures of Firm Competitiveness: a Model-Based Approach

The concept of competitiveness, for a long time considered as strictly connected to economic and financial performances, evolved, above all in recent years, toward new, wider interpretations disclosing its multidimensional nature. The shift to a multidimensional view of the phenomenon has excited an intense debate involving theoretical reflections on the features characterizing it, as well as methodological considerations on its assessment and measurement. The present research has a twofold objective: going in depth with the study of tangible and intangible aspect characterizing multidimensional competitive phenomena by assuming a micro-level point of view, and measuring competitiveness through a model-based approach. Specifically, we propose a non-parametric approach to Structural Equation Models techniques for the computation of multidimensional composite measures. Structural Equation Models tools will be used for the development of the empirical application on the italian case: a model based micro-level competitiveness indicator for the measurement of the phenomenon on a large sample of Italian small and medium enterprises will be constructed.

Multidimensional analysis of complex networks

Complex Networks analysis turn out to be a very promising field of research, testified by many research projects and works that span different fields. Those analysis have been usually focused on characterize a single aspect of the system and a study that considers many informative axes along with a network evolve is lacking. We propose a new multidimensional analysis that is able to inspect networks in the two most important dimensions, space and time. To achieve this goal, we studied them singularly and investigated how the variation of the constituting parameters drives changes to the network as a whole. By focusing on space dimension, we characterized spatial alteration in terms of abstraction levels. We proposed a novel algorithm that, by applying a fuzziness function, can reconstruct networks under different level of details. We verified that statistical indicators depend strongly on the granularity with which a system is described and on the class of networks. We keep fixed the space axes and we isolated the dynamics behind networks evolution process. We detected new instincts that trigger social networks utilization and spread the adoption of novel communities. We formalized this enhanced social network evolution by adopting special nodes (called sirens) that, thanks to their ability to attract new links, were able to construct efficient connection patterns. We simulated the dynamics of the system by considering three well-known growth models. Applying this framework to real and synthetic networks, we showed that the sirens, even when used for a limited time span, effectively shrink the time needed to get a network in mature state. In order to provide a concrete context of our findings, we formalized the cost of setting up such enhancement and provided the best combinations of system's parameters, such as number of sirens, time span of utilization and attractiveness.

Multidimensional item response theory models with general and specific latent traits for ordinal data

The aim of the thesis is to propose a Bayesian estimation through Markov chain Monte Carlo of multidimensional item response theory models for graded responses with complex structures and correlated traits. In particular, this work focuses on the multiunidimensional and the additive underlying latent structures, considering that the first one is widely used and represents a classical approach in multidimensional item response analysis, while the second one is able to reflect the complexity of real interactions between items and respondents. A simulation study is conducted to evaluate the parameter recovery for the proposed models under different conditions (sample size, test and subtest length, number of response categories, and correlation structure). The results show that the parameter recovery is particularly sensitive to the sample size, due to the model complexity and the high number of parameters to be estimated. For a sufficiently large sample size the parameters of the multiunidimensional and additive graded response models are well reproduced. The results are also affected by the trade-off between the number of items constituting the test and the number of item categories. An application of the proposed models on response data collected to investigate Romagna and San Marino residents' perceptions and attitudes towards the tourism industry is also presented.

Enhanced Sensitivity by Nonuniform Sampling Enables Multidimensional MAS NMR Spectroscopy of Protein Assemblies

We report dramatic sensitivity enhancements in multidimensional MAS NMR spectra by the use of nonuniform sampling (NUS) and introduce maximum entropy interpolation (MINT) processing that assures the linearity between the time and frequency domains of the NUS acquired data sets. A systematic analysis of sensitivity and resolution in 2D and 3D NUS spectra reveals that with NUS, at least 1.5- to 2-fold sensitivity enhancement can be attained in each indirect dimension without compromising the spectral resolution. These enhancements are similar to or higher than those attained by the newest-generation commercial cryogenic probes. We explore the benefits of this NUS/MaxEnt approach in proteins and protein assemblies using 1-73-(U-C-13,N-15)/74-108-(U-N-15) Escherichia coil thioredoxin reassembly. We demonstrate that in thioredoxin reassembly, NUS permits acquisition of high-quality 3D-NCACX spectra, which are inaccessible with conventional sampling due to prohibitively long experiment times. Of critical importance, issues that hinder NUS-based SNR enhancement in 3D-NMR of liquids are mitigated in the study of solid samples in which theoretical enhancements on the order of 3-4 fold are accessible by compounding the NUS-based SNR enhancement of each indirect dimension. NUS/MINT is anticipated to be widely applicable and advantageous for multidimensional heteronuclear MAS NMR spectroscopy of proteins, protein assemblies, and other biological systems.

Parallel vector processing of multidimensional orthogonal transforms for digital signal processing applications

The performance of the parallel vector implementation of the one- and two-dimensional orthogonal transforms is evaluated. The orthogonal transforms are computed using actual or modified fast Fourier transform (FFT) kernels. The factors considered in comparing the speed-up of these vectorized digital signal processing algorithms are discussed and it is shown that the traditional way of comparing th execution speed of digital signal processing algorithms by the ratios of the number of multiplications and additions is no longer effective for vector implementation; the structure of the algorithm must also be considered as a factor when comparing the execution speed of vectorized digital signal processing algorithms. Simulation results on the Cray X/MP with the following orthogonal transforms are presented: discrete Fourier transform (DFT), discrete cosine transform (DCT), discrete sine transform (DST), discrete Hartley transform (DHT), discrete Walsh transform (DWHT), and discrete Hadamard transform (DHDT). A comparison between the DHT and the fast Hartley transform is also included.(34 refs)

Evaluation of multidimensional geriatric assessment as a predictor of mortality and cardiovascular events after transcatheter aortic valve implantation

This study evaluated Multidimensional Geriatric Assessment (MGA) as predictor of mortality and major adverse cardiovascular and cerebral events (MACCE) after transcatheter aortic valve implantation (TAVI).