Modelling and analysis of thin-walled beams in the context of the Generalized Beam Theory

In this work, the Generalized Beam Theory (GBT) is used as the main tool to analyze the mechanics of thin-walled beams. After an introduction to the subject and a quick review of some of the most well-known approaches to describe the behaviour of thin-walled beams, a novel formulation of the GBT is presented. This formulation contains the classic shear-deformable GBT available in the literature and contributes an additional description of cross-section warping that is variable along the wall thickness besides along the wall midline. Shear deformation is introduced in such a way that the classical shear strain components of the Timoshenko beam theory are recovered exactly. According to the new kinematics proposed, a reviewed form of the cross-section analysis procedure is devised, based on a unique modal decomposition. Later, a procedure for a posteriori reconstruction of all the three-dimensional stress components in the finite element analysis of thin-walled beams using the GBT is presented. The reconstruction is simple and based on the use of three-dimensional equilibrium equations and of the RCP procedure. Finally, once the stress reconstruction procedure is presented, a study of several existing issues on the constitutive relations in the GBT is carried out. Specifically, a constitutive law based on mirroring the kinematic constraints of the GBT model into a specific stress field assumption is proposed. It is shown that this method is equally valid for isotropic and orthotropic beams and coincides with the conventional GBT approach available in the literature. Later on, an analogous procedure is presented for the case of laminated beams. Lastly, as a way to improve an inherently poor description of shear deformability in the GBT, the introduction of shear correction factors is proposed. Throughout this work, numerous examples are provided to determine the validity of all the proposed contributions to the field.

Computational methods for the analysis of protein structure and function

The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.

The assessment of change in rural landscape and the analysis of the driving forces. Proposal of a spatial model for the rural built environment

The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.

Technical innovations for the diagnosis and the rehabilitation of motor and perceptive impairments of the child with Cerebral Palsy

The treatment of the Cerebral Palsy (CP) is considered as the “core problem” for the whole field of the pediatric rehabilitation. The reason why this pathology has such a primary role, can be ascribed to two main aspects. First of all CP is the form of disability most frequent in childhood (one new case per 500 birth alive, (1)), secondarily the functional recovery of the “spastic” child is, historically, the clinical field in which the majority of the therapeutic methods and techniques (physiotherapy, orthotic, pharmacologic, orthopedic-surgical, neurosurgical) were first applied and tested. The currently accepted definition of CP – Group of disorders of the development of movement and posture causing activity limitation (2) – is the result of a recent update by the World Health Organization to the language of the International Classification of Functioning Disability and Health, from the original proposal of Ingram – A persistent but not unchangeable disorder of posture and movement – dated 1955 (3). This definition considers CP as a permanent ailment, i.e. a “fixed” condition, that however can be modified both functionally and structurally by means of child spontaneous evolution and treatments carried out during childhood. The lesion that causes the palsy, happens in a structurally immature brain in the pre-, peri- or post-birth period (but only during the firsts months of life). The most frequent causes of CP are: prematurity, insufficient cerebral perfusion, arterial haemorrhage, venous infarction, hypoxia caused by various origin (for example from the ingestion of amniotic liquid), malnutrition, infection and maternal or fetal poisoning. In addition to these causes, traumas and malformations have to be included. The lesion, whether focused or spread over the nervous system, impairs the whole functioning of the Central Nervous System (CNS). As a consequence, they affect the construction of the adaptive functions (4), first of all posture control, locomotion and manipulation. The palsy itself does not vary over time, however it assumes an unavoidable “evolutionary” feature when during growth the child is requested to meet new and different needs through the construction of new and different functions. It is essential to consider that clinically CP is not only a direct expression of structural impairment, that is of etiology, pathogenesis and lesion timing, but it is mainly the manifestation of the path followed by the CNS to “re”-construct the adaptive functions “despite” the presence of the damage. “Palsy” is “the form of the function that is implemented by an individual whose CNS has been damaged in order to satisfy the demands coming from the environment” (4). Therefore it is only possible to establish general relations between lesion site, nature and size, and palsy and recovery processes. It is quite common to observe that children with very similar neuroimaging can have very different clinical manifestations of CP and, on the other hand, children with very similar motor behaviors can have completely different lesion histories. A very clear example of this is represented by hemiplegic forms, which show bilateral hemispheric lesions in a high percentage of cases. The first section of this thesis is aimed at guiding the interpretation of CP. First of all the issue of the detection of the palsy is treated from historical viewpoint. Consequently, an extended analysis of the current definition of CP, as internationally accepted, is provided. The definition is then outlined in terms of a space dimension and then of a time dimension, hence it is highlighted where this definition is unacceptably lacking. The last part of the first section further stresses the importance of shifting from the traditional concept of CP as a palsy of development (defect analysis) towards the notion of development of palsy, i.e., as the product of the relationship that the individual however tries to dynamically build with the surrounding environment (resource semeiotics) starting and growing from a different availability of resources, needs, dreams, rights and duties (4). In the scientific and clinic community no common classification system of CP has so far been universally accepted. Besides, no standard operative method or technique have been acknowledged to effectively assess the different disabilities and impairments exhibited by children with CP. CP is still “an artificial concept, comprising several causes and clinical syndromes that have been grouped together for a convenience of management” (5). The lack of standard and common protocols able to effectively diagnose the palsy, and as a consequence to establish specific treatments and prognosis, is mainly because of the difficulty to elevate this field to a level based on scientific evidence. A solution aimed at overcoming the current incomplete treatment of CP children is represented by the clinical systematic adoption of objective tools able to measure motor defects and movement impairments. A widespread application of reliable instruments and techniques able to objectively evaluate both the form of the palsy (diagnosis) and the efficacy of the treatments provided (prognosis), constitutes a valuable method able to validate care protocols, establish the efficacy of classification systems and assess the validity of definitions. Since the ‘80s, instruments specifically oriented to the analysis of the human movement have been advantageously designed and applied in the context of CP with the aim of measuring motor deficits and, especially, gait deviations. The gait analysis (GA) technique has been increasingly used over the years to assess, analyze, classify, and support the process of clinical decisions making, allowing for a complete investigation of gait with an increased temporal and spatial resolution. GA has provided a basis for improving the outcome of surgical and nonsurgical treatments and for introducing a new modus operandi in the identification of defects and functional adaptations to the musculoskeletal disorders. Historically, the first laboratories set up for gait analysis developed their own protocol (set of procedures for data collection and for data reduction) independently, according to performances of the technologies available at that time. In particular, the stereophotogrammetric systems mainly based on optoelectronic technology, soon became a gold-standard for motion analysis. They have been successfully applied especially for scientific purposes. Nowadays the optoelectronic systems have significantly improved their performances in term of spatial and temporal resolution, however many laboratories continue to use the protocols designed on the technology available in the ‘70s and now out-of-date. Furthermore, these protocols are not coherent both for the biomechanical models and for the adopted collection procedures. In spite of these differences, GA data are shared, exchanged and interpreted irrespectively to the adopted protocol without a full awareness to what extent these protocols are compatible and comparable with each other. Following the extraordinary advances in computer science and electronics, new systems for GA no longer based on optoelectronic technology, are now becoming available. They are the Inertial and Magnetic Measurement Systems (IMMSs), based on miniature MEMS (Microelectromechanical systems) inertial sensor technology. These systems are cost effective, wearable and fully portable motion analysis systems, these features gives IMMSs the potential to be used both outside specialized laboratories and to consecutive collect series of tens of gait cycles. The recognition and selection of the most representative gait cycle is then easier and more reliable especially in CP children, considering their relevant gait cycle variability. The second section of this thesis is focused on GA. In particular, it is firstly aimed at examining the differences among five most representative GA protocols in order to assess the state of the art with respect to the inter-protocol variability. The design of a new protocol is then proposed and presented with the aim of achieving gait analysis on CP children by means of IMMS. The protocol, named ‘Outwalk’, contains original and innovative solutions oriented at obtaining joint kinematic with calibration procedures extremely comfortable for the patients. The results of a first in-vivo validation of Outwalk on healthy subjects are then provided. In particular, this study was carried out by comparing Outwalk used in combination with an IMMS with respect to a reference protocol and an optoelectronic system. In order to set a more accurate and precise comparison of the systems and the protocols, ad hoc methods were designed and an original formulation of the statistical parameter coefficient of multiple correlation was developed and effectively applied. On the basis of the experimental design proposed for the validation on healthy subjects, a first assessment of Outwalk, together with an IMMS, was also carried out on CP children. The third section of this thesis is dedicated to the treatment of walking in CP children. Commonly prescribed treatments in addressing gait abnormalities in CP children include physical therapy, surgery (orthopedic and rhizotomy), and orthoses. The orthotic approach is conservative, being reversible, and widespread in many therapeutic regimes. Orthoses are used to improve the gait of children with CP, by preventing deformities, controlling joint position, and offering an effective lever for the ankle joint. Orthoses are prescribed for the additional aims of increasing walking speed, improving stability, preventing stumbling, and decreasing muscular fatigue. The ankle-foot orthosis (AFO), with a rigid ankle, are primarily designed to prevent equinus and other foot deformities with a positive effect also on more proximal joints. However, AFOs prevent the natural excursion of the tibio-tarsic joint during the second rocker, hence hampering the natural leaning progression of the whole body under the effect of the inertia (6). A new modular (submalleolar) astragalus-calcanear orthosis, named OMAC, has recently been proposed with the intention of substituting the prescription of AFOs in those CP children exhibiting a flat and valgus-pronated foot. The aim of this section is thus to present the mechanical and technical features of the OMAC by means of an accurate description of the device. In particular, the integral document of the deposited Italian patent, is provided. A preliminary validation of OMAC with respect to AFO is also reported as resulted from an experimental campaign on diplegic CP children, during a three month period, aimed at quantitatively assessing the benefit provided by the two orthoses on walking and at qualitatively evaluating the changes in the quality of life and motor abilities. As already stated, CP is universally considered as a persistent but not unchangeable disorder of posture and movement. Conversely to this definition, some clinicians (4) have recently pointed out that movement disorders may be primarily caused by the presence of perceptive disorders, where perception is not merely the acquisition of sensory information, but an active process aimed at guiding the execution of movements through the integration of sensory information properly representing the state of one’s body and of the environment. Children with perceptive impairments show an overall fear of moving and the onset of strongly unnatural walking schemes directly caused by the presence of perceptive system disorders. The fourth section of the thesis thus deals with accurately defining the perceptive impairment exhibited by diplegic CP children. A detailed description of the clinical signs revealing the presence of the perceptive impairment, and a classification scheme of the clinical aspects of perceptual disorders is provided. In the end, a functional reaching test is proposed as an instrumental test able to disclosure the perceptive impairment. References 1. Prevalence and characteristics of children with cerebral palsy in Europe. Dev Med Child Neurol. 2002 Set;44(9):633-640. 2. Bax M, Goldstein M, Rosenbaum P, Leviton A, Paneth N, Dan B, et al. Proposed definition and classification of cerebral palsy, April 2005. Dev Med Child Neurol. 2005 Ago;47(8):571-576. 3. Ingram TT. A study of cerebral palsy in the childhood population of Edinburgh. Arch. Dis. Child. 1955 Apr;30(150):85-98. 4. Ferrari A, Cioni G. The spastic forms of cerebral palsy : a guide to the assessment of adaptive functions. Milan: Springer; 2009. 5. Olney SJ, Wright MJ. Cerebral Palsy. Campbell S et al. Physical Therapy for Children. 2nd Ed. Philadelphia: Saunders. 2000;:533-570. 6. Desloovere K, Molenaers G, Van Gestel L, Huenaerts C, Van Campenhout A, Callewaert B, et al. How can push-off be preserved during use of an ankle foot orthosis in children with hemiplegia? A prospective controlled study. Gait Posture. 2006 Ott;24(2):142-151.

Mixed Mode Fracture Behaviour of Piezoelectric Materials

Piezoelectrics present an interactive electromechanical behaviour that, especially in recent years, has generated much interest since it renders these materials adapt for use in a variety of electronic and industrial applications like sensors, actuators, transducers, smart structures. Both mechanical and electric loads are generally applied on these devices and can cause high concentrations of stress, particularly in proximity of defects or inhomogeneities, such as flaws, cavities or included particles. A thorough understanding of their fracture behaviour is crucial in order to improve their performances and avoid unexpected failures. Therefore, a considerable number of research works have addressed this topic in the last decades. Most of the theoretical studies on this subject find their analytical background in the complex variable formulation of plane anisotropic elasticity. This theoretical approach bases its main origins in the pioneering works of Muskelishvili and Lekhnitskii who obtained the solution of the elastic problem in terms of independent analytic functions of complex variables. In the present work, the expressions of stresses and elastic and electric displacements are obtained as functions of complex potentials through an analytical formulation which is the application to the piezoelectric static case of an approach introduced for orthotropic materials to solve elastodynamics problems. This method can be considered an alternative to other formalisms currently used, like the Stroh’s formalism. The equilibrium equations are reduced to a first order system involving a six-dimensional vector field. After that, a similarity transformation is induced to reach three independent Cauchy-Riemann systems, so justifying the introduction of the complex variable notation. Closed form expressions of near tip stress and displacement fields are therefore obtained. In the theoretical study of cracked piezoelectric bodies, the issue of assigning consistent electric boundary conditions on the crack faces is of central importance and has been addressed by many researchers. Three different boundary conditions are commonly accepted in literature: the permeable, the impermeable and the semipermeable (“exact”) crack model. This thesis takes into considerations all the three models, comparing the results obtained and analysing the effects of the boundary condition choice on the solution. The influence of load biaxiality and of the application of a remote electric field has been studied, pointing out that both can affect to a various extent the stress fields and the angle of initial crack extension, especially when non-singular terms are retained in the expressions of the electro-elastic solution. Furthermore, two different fracture criteria are applied to the piezoelectric case, and their outcomes are compared and discussed. The work is organized as follows: Chapter 1 briefly introduces the fundamental concepts of Fracture Mechanics. Chapter 2 describes plane elasticity formalisms for an anisotropic continuum (Eshelby-Read-Shockley and Stroh) and introduces for the simplified orthotropic case the alternative formalism we want to propose. Chapter 3 outlines the Linear Theory of Piezoelectricity, its basic relations and electro-elastic equations. Chapter 4 introduces the proposed method for obtaining the expressions of stresses and elastic and electric displacements, given as functions of complex potentials. The solution is obtained in close form and non-singular terms are retained as well. Chapter 5 presents several numerical applications aimed at estimating the effect of load biaxiality, electric field, considered permittivity of the crack. Through the application of fracture criteria the influence of the above listed conditions on the response of the system and in particular on the direction of crack branching is thoroughly discussed.

Exploring novel targeted therapeutic strategies against Acute Myeloid Leukemia cells based on inhibition of bromodomain proteins and CDC20 activity

Acute myeloid leukemia (AML) is a haematological malignancies arising from the accumulation of undifferentiated myeloid progenitors with an uncontrolled proliferation. The genomic landscape of AML revealed that the disease is characterized by high level of heterogeneity and is subjected to clonal evolution driven by selective pressure of chemotherapy. In this study, we investigated the therapeutic effects of the inhibition of BRD4 and CDC20 in vitro and ex vivo. We demonstrated that inhibition of BRD4 with GSK1215101A in AML cell lines was effective under hypoxia. It induced the activation of antioxidant response both, at transcriptomic and metabolomic levels, driven by enrichment of NRF2 pathway under normoxic and hypoxic condition. Moreover, the combined treatment with Omaveloxolone, a drug inducing NRF2 activation and NF-κB inhibition, potentiated the effects on apoptosis and colony forming capacity of stem progenitor cells. Lastly, gene expression profiling data revealed that combination treatment induced major changes in genes related to cell cycle, together with enrichment of cell differentiation pathways and negative regulation of WNT, in normoxia and hypoxia. Regarding CDC20, we observed its up-regulation in AML patients. Treatment with two different inhibitors, Apcin and proTAME, was effective in primary AML cells and in AML cell lines, through induction of apoptosis and mitotic arrest. The lack of correlation between proliferation markers and CDC20 levels in AML cell subpopulations supports the idea of alternative CDC20 functions, independent from its essential role during mitosis. CDC20-KD experiments conducted in AML cell lines revealed a mild effect on apoptosis induction, but no significant change in cell cycle progression. In summary, these results allowed the identification of a new strategy combination to improve the effects of BRD4 inhibition on LSC residing in the BM hypoxic niche, and provide some new evidence regarding the potential role of CDC20 as a new target for AML treatment.

Assessing the fit of unidimensional IRT models for binary data under model misspecification

Model misspecification affects the classical test statistics used to assess the fit of the Item Response Theory (IRT) models. Robust tests have been derived under model misspecification, as the Generalized Lagrange Multiplier and Hausman tests, but their use has not been largely explored in the IRT framework. In the first part of the thesis, we introduce the Generalized Lagrange Multiplier test to detect differential item response functioning in IRT models for binary data under model misspecification. By means of a simulation study and a real data analysis, we compare its performance with the classical Lagrange Multiplier test, computed using the Hessian and the cross-product matrix, and the Generalized Jackknife Score test. The power of these tests is computed empirically and asymptotically. The misspecifications considered are local dependence among items and non-normal distribution of the latent variable. The results highlight that, under mild model misspecification, all tests have good performance while, under strong model misspecification, the performance of the tests deteriorates. None of the tests considered show an overall superior performance than the others. In the second part of the thesis, we extend the Generalized Hausman test to detect non-normality of the latent variable distribution. To build the test, we consider a seminonparametric-IRT model, that assumes a more flexible latent variable distribution. By means of a simulation study and two real applications, we compare the performance of the Generalized Hausman test with the M2 limited information goodness-of-fit test and the Likelihood-Ratio test. Additionally, the information criteria are computed. The Generalized Hausman test has a better performance than the Likelihood-Ratio test in terms of Type I error rates and the M2 test in terms of power. The performance of the Generalized Hausman test and the information criteria deteriorates when the sample size is small and with a few items.

Deploying and processing neural representations of signals

Neural representations (NR) have emerged in the last few years as a powerful tool to represent signals from several domains, such as images, 3D shapes, or audio. Indeed, deep neural networks have been shown capable of approximating continuous functions that describe a given signal with theoretical infinite resolution. This finding allows obtaining representations whose memory footprint is fixed and decoupled from the resolution at which the underlying signal can be sampled, something that is not possible with traditional discrete representations, e.g., grids of pixels for images or voxels for 3D shapes. During the last two years, many techniques have been proposed to improve the capability of NR to approximate high-frequency details and to make the optimization procedures required to obtain NR less demanding both in terms of time and data requirements, motivating many researchers to deploy NR as the main form of data representation for complex pipelines. Following this line of research, we first show that NR can approximate precisely Unsigned Distance Functions, providing an effective way to represent garments that feature open 3D surfaces and unknown topology. Then, we present a pipeline to obtain in a few minutes a compact Neural Twin® for a given object, by exploiting the recent advances in modeling neural radiance fields. Furthermore, we move a step in the direction of adopting NR as a standalone representation, by considering the possibility of performing downstream tasks by processing directly the NR weights. We first show that deep neural networks can be compressed into compact latent codes. Then, we show how this technique can be exploited to perform deep learning on implicit neural representations (INR) of 3D shapes, by only looking at the weights of the networks.

Modelling and classification with quantile-based distributions

In this work, we explore and demonstrate the potential for modeling and classification using quantile-based distributions, which are random variables defined by their quantile function. In the first part we formalize a least squares estimation framework for the class of linear quantile functions, leading to unbiased and asymptotically normal estimators. Among the distributions with a linear quantile function, we focus on the flattened generalized logistic distribution (fgld), which offers a wide range of distributional shapes. A novel naïve-Bayes classifier is proposed that utilizes the fgld estimated via least squares, and through simulations and applications, we demonstrate its competitiveness against state-of-the-art alternatives. In the second part we consider the Bayesian estimation of quantile-based distributions. We introduce a factor model with independent latent variables, which are distributed according to the fgld. Similar to the independent factor analysis model, this approach accommodates flexible factor distributions while using fewer parameters. The model is presented within a Bayesian framework, an MCMC algorithm for its estimation is developed, and its effectiveness is illustrated with data coming from the European Social Survey. The third part focuses on depth functions, which extend the concept of quantiles to multivariate data by imposing a center-outward ordering in the multivariate space. We investigate the recently introduced integrated rank-weighted (IRW) depth function, which is based on the distribution of random spherical projections of the multivariate data. This depth function proves to be computationally efficient and to increase its flexibility we propose different methods to explicitly model the projected univariate distributions. Its usefulness is shown in classification tasks: the maximum depth classifier based on the IRW depth is proven to be asymptotically optimal under certain conditions, and classifiers based on the IRW depth are shown to perform well in simulated and real data experiments.