Statistical methodology for classification of partially observed functional data

This thesis is devoted to the development of new methodologies for the classication of partially observed functional data. Functional Data Analysis is nowadays one of the most active area of research in statistics. It deals mostly with data coming from technical machineries and digital instruments, treating data as functions. Classication of this kind of data is still an open problem and there are several available methods in the literature. Unfortunately, none of these methods is directly applicable when the data are partially observed, i.e. exhibit some missing parts. The aim of this work is to provide new insights and proposals for discrimination of functional fragments. The theory we develop is strongly supported by extensive simulations and all the methods are illustrated on a real medical dataset called Aneurisk, on which we outperform previous classication performance

Multiscale stick-breaking mixture models

We introduce a family of multiscale stick-breaking mixture models for Bayesian nonparametric density estimation. The Bayesian nonparametric literature is dominated by single scale methods, exception made for P\`olya trees and allied approaches. Our proposal is based on a mixture specification exploiting an infinitely-deep binary tree of random weights that grows according to a multiscale generalization of a large class of stick-breaking processes; this multiscale stick-breaking is paired with specific stochastic processes generating sequences of parameters that induce stochastically ordered kernel functions. Properties of this family of multiscale stick-breaking mixtures are described. Focusing on a Gaussian specification, a Markov Chain Montecarlo algorithm for posterior computation is introduced. The performance of the method is illustrated analyzing both synthetic and real data sets. The method is well-suited for data living in $\mathbb{R}$ and is able to detect densities with varying degree of smoothness and local features

Analyzing Cause-Specific Mortality Trends using Compositional Functional Data Analysis

We study the dynamics of cause--specific mortality rates among countries by considering them as compositions of functions. We develop a novel framework for such data structure, with particular attention to functional PCA. The application of this method to a subset of the WHO mortality database reveals the main modes of variation of cause--specific rates over years for men and women and enables us to perform clustering in the projected subspace. The results give many insights of the ongoing trends, only partially explained by past literature, that the considered countries are undergoing. We are also able to show the different evolution of cause of death undergone by men and women: for example, we can see that while lung cancer incidence is stabilizing for men, it is still increasing for women

An adaptive functional regression framework for spatially heterogeneous signals in spectroscopy

The attention towards food products characteristics, such as nutritional properties and traceability, has risen substantially in the recent years. Consequently, we are witnessing an increased demand for the development of modern tools to monitor, analyse and assess food quality and authenticity. Within this framework, an essential set of data collection techniques is provided by vibrational spectroscopy. In fact, methods such as Fourier near infrared and mid infrared spectroscopy have been often exploited to analyze different foodstuffs. Nonetheless, existing statistical methods often struggle to deal with the challenges presented by spectral data, such as their high dimensionality, paired with strong relationships among the wavelengths. Therefore, the definition of proper statistical procedures accounting for the peculiarities of spectroscopy data is paramount. In this work, motivated by two dairy science applications, we propose an adaptive functional regression framework for spectroscopy data. The method stems from the trend filtering literature, allowing the definition of a highly flexible and adaptive estimator able to handle different degrees of smoothness. We provide a fast optimization procedure that is suitable for both Gaussian and non Gaussian scalar responses, and allows for the inclusion of scalar covariates. Moreover, we develop inferential procedures for both the functional and the scalar component thus enhancing not only the interpretability of the results, but also their usability in real world scenarios. The method is applied to two sets of MIR spectroscopy data, providing excellent results when predicting milk chemical composition and cows' dietary treatments. Moreover, the developed inferential routine provides relevant insights, potentially paving the way for a richer interpretation and a better understanding of the impact of specific wavelengths on milk features.Comment: 20 pages, 3 figure

Functional concurrent regression with compositional covariates and its application to the time-varying effect of causes of death on human longevity

Multivariate functional data that are cross-sectionally compositional data are attracting increasing interest in the statistical modeling literature, a major example being trajectories over time of compositions derived from cause-specific mortality rates. In this work, we develop a novel functional concurrent regression model in which independent variables are functional compositions. This allows us to investigate the relationship over time between life expectancy at birth and compositions derived from cause-specific mortality rates of four distinct age classes, namely 0--4, 5--39, 40--64 and 65+. A penalized approach is developed to estimate the regression coefficients and select the relevant variables. Then an efficient computational strategy based on an augmented Lagrangian algorithm is derived to solve the resulting optimization problem. The good performances of the model in predicting the response function and estimating the unknown functional coefficients are shown in a simulation study. The results on real data confirm the important role of neoplasms and cardiovascular diseases in determining life expectancy emerged in other studies and reveal several other contributions not yet observed

The potential of eupraxia@sparc_lab for radiation based techniques

A proposal for building a Free Electron Laser, EuPRAXIA@SPARC_LAB, at the Laboratori Nazionali di Frascati, is at present under consideration. This FEL facility will provide a unique combination of a high brightness GeV-range electron beam generated in a X-band RF linac, a 0.5 PW-class laser system and the first FEL source driven by a plasma accelerator. The FEL will produce ultra-bright pulses, with up to 1012 photons/pulse, femtosecond timescale and wavelength down to 3 nm, which lies in the so called “water window”. The experimental activity will be focused on the realization of a plasma driven short wavelength FEL able to provide high-quality photons for a user beamline. In this paper, we describe the main classes of experiments that will be performed at the facility, including coherent diffraction imaging, soft X-ray absorption spectroscopy, Raman spectroscopy, Resonant Inelastic X-ray Scattering and photofragmentation measurements. These techniques will allow studying a variety of samples, both biological and inorganic, providing information about their structure and dynamical behavior. In this context, the possibility of inducing changes in samples via pump pulses leading to the stimulation of chemical reactions or the generation of coherent excitations would tremendously benefit from pulses in the soft X-ray region. High power synchronized optical lasers and a TeraHertz radiation source will indeed be made available for THz and pump–probe experiments and a split-and-delay station will allow performing XUV-XUV pump–probe experiments.Fil: Balerna, Antonella. Istituto Nazionale Di Fisica Nucleare.; ItaliaFil: Bartocci, Samanta. Università degli studi di Sassari; ItaliaFil: Batignani, Giovanni. Università degli studi di Roma "La Sapienza"; ItaliaFil: Cianchi, Alessandro. Universita Tor Vergata; Italia. Istituto Nazionale Di Fisica Nucleare.; ItaliaFil: Chiadroni, Enrica. Istituto Nazionale Di Fisica Nucleare.; ItaliaFil: Coreno, Marcello. Istituto Nazionale Di Fisica Nucleare.; Italia. Istituto di Struttura della Materia; ItaliaFil: Cricenti, Antonio. Istituto di Struttura della Materia; ItaliaFil: Dabagov, Sultan. Istituto Nazionale Di Fisica Nucleare.; Italia. National Research Nuclear University; Rusia. Lebedev Physical Institute; RusiaFil: Di Cicco, Andrea. Universita Degli Di Camerino; ItaliaFil: Faiferri, Massimo. Università degli studi di Sassari; ItaliaFil: Ferrante, Carino. Università degli studi di Roma “La Sapienza”; Italia. Center for Life Nano Science @Sapienza; ItaliaFil: Ferrario, Massimo. Istituto Nazionale Di Fisica Nucleare.; ItaliaFil: Fumero, Giuseppe. Università degli studi di Roma “La Sapienza”; ItaliaFil: Giannessi, Luca. Elettra-Sincrotrone Trieste; Italia. ENEA C.R. Frascati; ItaliaFil: Gunnella, Roberto. Universita Degli Di Camerino; ItaliaFil: Leani, Juan Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; ArgentinaFil: Lupi, Stefano. Università degli studi di Roma “La Sapienza”; Italia. Istituto Nazionale di Fisica Nucleare (INFN) Sezione di Roma La Sapienza; ItaliaFil: Macis, Salvatore. Università degli Studi di Roma Tor Vergata; Italia. Istituto Nazionale di Fisica Nucleare (INFN) Sezione di Roma Tor Vergata; ItaliaFil: Manca, Rosa. Università degli studi di Sassari; ItaliaFil: Marcelli, Augusto. Istituto Nazionale Di Fisica Nucleare.; Italia. Consiglio Nazionale delle Ricerche; ItaliaFil: Masciovecchio, Claudio. Elettra-Sincrotrone Trieste; ItaliaFil: Minicucci, Marco. Universita Degli Di Camerino; ItaliaFil: Morante, Silvia. Universita Tor Vergata; Italia. Istituto Nazionale Di Fisica Nucleare.; ItaliaFil: Perfetto, Enrico. Universita Tor Vergata; Italia. Consiglio Nazionale delle Ricerche; ItaliaFil: Petrarca, Massimo. Università degli studi di Roma "La Sapienza"; Italia. Istituto Nazionale Di Fisica Nucleare.; ItaliaFil: Pusceddu, Fabrizio. Università degli studi di Sassari; ItaliaFil: Rezvani, Javad. Istituto Nazionale Di Fisica Nucleare.; ItaliaFil: Robledo, José Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; ArgentinaFil: Rossi, Giancarlo. Centro Fermi—Museo Storico della Fisica e Centro Studi e Ricerche “Enrico Fermi”; Italia. Istituto Nazionale Di Fisica Nucleare.; Italia. Universita Tor Vergata; ItaliaFil: Sanchez, Hector Jorge. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; ArgentinaFil: Scopigno, Tullio. Center for Life Nano Science @Sapienza; Italia. Università degli studi di Roma "La Sapienza"; ItaliaFil: Stefanucci, Gianluca. Universita Tor Vergata; Italia. Istituto Nazionale Di Fisica Nucleare.; ItaliaFil: Stellato, Francesco. Universita Tor Vergata; Italia. Istituto Nazionale Di Fisica Nucleare.; ItaliaFil: Trapananti, Angela. Universita Degli Di Camerino; ItaliaFil: Villa, Fabio. Istituto Nazionale Di Fisica Nucleare.; Itali

Altered TMPRSS2 usage by SARS-CoV-2 Omicron impacts infectivity and fusogenicity

The SARS-CoV-2 Omicron BA.1 variant emerged in 20211 and has multiple mutations in its spike protein2. Here we show that the spike protein of Omicron has a higher affinity for ACE2 compared with Delta, and a marked change in its antigenicity increases Omicron’s evasion of therapeutic monoclonal and vaccine-elicited polyclonal neutralizing antibodies after two doses. mRNA vaccination as a third vaccine dose rescues and broadens neutralization. Importantly, the antiviral drugs remdesivir and molnupiravir retain efficacy against Omicron BA.1. Replication was similar for Omicron and Delta virus isolates in human nasal epithelial cultures. However, in lung cells and gut cells, Omicron demonstrated lower replication. Omicron spike protein was less efficiently cleaved compared with Delta. The differences in replication were mapped to the entry efficiency of the virus on the basis of spike-pseudotyped virus assays. The defect in entry of Omicron pseudotyped virus to specific cell types effectively correlated with higher cellular RNA expression of TMPRSS2, and deletion of TMPRSS2 affected Delta entry to a greater extent than Omicron. Furthermore, drug inhibitors targeting specific entry pathways3 demonstrated that the Omicron spike inefficiently uses the cellular protease TMPRSS2, which promotes cell entry through plasma membrane fusion, with greater dependency on cell entry through the endocytic pathway. Consistent with suboptimal S1/S2 cleavage and inability to use TMPRSS2, syncytium formation by the Omicron spike was substantially impaired compared with the Delta spike. The less efficient spike cleavage of Omicron at S1/S2 is associated with a shift in cellular tropism away from TMPRSS2-expressing cells, with implications for altered pathogenesis

Altered TMPRSS2 usage by SARS-CoV-2 Omicron impacts infectivity and fusogenicity

The SARS-CoV-2 Omicron BA.1 variant emerged in 20211 and has multiple mutations in its spike protein2. Here we show that the spike protein of Omicron has a higher affinity for ACE2 compared with Delta, and a marked change in its antigenicity increases Omicron’s evasion of therapeutic monoclonal and vaccine-elicited polyclonal neutralizing antibodies after two doses. mRNA vaccination as a third vaccine dose rescues and broadens neutralization. Importantly, the antiviral drugs remdesivir and molnupiravir retain efficacy against Omicron BA.1. Replication was similar for Omicron and Delta virus isolates in human nasal epithelial cultures. However, in lung cells and gut cells, Omicron demonstrated lower replication. Omicron spike protein was less efficiently cleaved compared with Delta. The differences in replication were mapped to the entry efficiency of the virus on the basis of spike-pseudotyped virus assays. The defect in entry of Omicron pseudotyped virus to specific cell types effectively correlated with higher cellular RNA expression of TMPRSS2, and deletion of TMPRSS2 affected Delta entry to a greater extent than Omicron. Furthermore, drug inhibitors targeting specific entry pathways3 demonstrated that the Omicron spike inefficiently uses the cellular protease TMPRSS2, which promotes cell entry through plasma membrane fusion, with greater dependency on cell entry through the endocytic pathway. Consistent with suboptimal S1/S2 cleavage and inability to use TMPRSS2, syncytium formation by the Omicron spike was substantially impaired compared with the Delta spike. The less efficient spike cleavage of Omicron at S1/S2 is associated with a shift in cellular tropism away from TMPRSS2-expressing cells, with implications for altered pathogenesis