Cosmological predictions for a scalar tensor dark energy model by a dedicated Einstein-Boltzmann code

We have extended the Boltzmann code CLASS and studied a specific scalar tensor dark energy model: Induced Gravity

Black hole evaporation and stress tensor correlations

General Relativity is one of the greatest scientific achievementes of the 20th century along with quantum theory. These two theories are extremely beautiful and they are well verified by experiments, but they are apparently incompatible. Hints towards understanding these problems can be derived studying Black Holes, some the most puzzling solutions of General Relativity. The main topic of this Master Thesis is the study of Black Holes, in particular the Physics of Hawking Radiation. After a short review of General Relativity, I study in detail the Schwarzschild solution with particular emphasis on the coordinates systems used and the mathematical proof of the classical laws of Black Hole "Thermodynamics". Then I introduce the theory of Quantum Fields in Curved Spacetime, from Bogolubov transformations to the Schwinger-De Witt expansion, useful for the renormalization of the stress energy tensor. After that I introduce a 2D model of gravitational collapse to study the Hawking radiation phenomenon. Particular emphasis is given to the analysis of the quantum states, from correlations to the physical implication of this quantum effect (e.g. Information Paradox, Black Hole Thermodynamics). Then I introduce the renormalized stress energy tensor. Using the Schwinger-De Witt expansion I renormalize this object and I compute it analytically in the various quantum states of interest. Moreover, I study the correlations between these objects. They are interesting because they are linked to the Hawking radiation experimental search in acoustic Black Hole models. In particular I find that there is a characteristic peak in correlations between points inside and outside the Black Hole region, which correpsonds to entangled excitations inside and outside the Black Hole. These peaks hopefully will be measurable soon in supersonic BEC.

Machine Learning applicato al Web Semantico: Statistical Relational Learning vs Tensor Factorization

Obiettivo della tesi è analizzare e testare i principali approcci di Machine Learning applicabili in contesti semantici, partendo da algoritmi di Statistical Relational Learning, quali Relational Probability Trees, Relational Bayesian Classifiers e Relational Dependency Networks, per poi passare ad approcci basati su fattorizzazione tensori, in particolare CANDECOMP/PARAFAC, Tucker e RESCAL.

String inflationary models with non-monotonic slow-roll and detectable tensor modes

The first chapter of this work has the aim to provide a brief overview of the history of our Universe, in the context of string theory and considering inflation as its possible application to cosmological problems. We then discuss type IIB string compactifications, introducing the study of the inflaton, a scalar field candidated to describe the inflation theory. The Large Volume Scenario (LVS) is studied in the second chapter paying particular attention to the stabilisation of the Kähler moduli which are four-dimensional gravitationally coupled scalar fields which parameterise the size of the extra dimensions. Moduli stabilisation is the process through which these particles acquire a mass and can become promising inflaton candidates. The third chapter is devoted to the study of Fibre Inflation which is an interesting inflationary model derived within the context of LVS compactifications. The fourth chapter tries to extend the zone of slow-roll of the scalar potential by taking larger values of the field φ. Everything is done with the purpose of studying in detail deviations of the cosmological observables, which can better reproduce current experimental data. Finally, we present a slight modification of Fibre Inflation based on a different compactification manifold. This new model produces larger tensor modes with a spectral index in good agreement with the date released in February 2015 by the Planck satellite.

Eye movement and diffusion tensor imaging analysis of treatment effects in a Niemann-Pick Type C patient

New treatment options for Niemann-Pick Type C (NPC) have recently become available. To assess the efficiency and efficacy of these new treatment markers for disease status and progression are needed. Both the diagnosis and the monitoring of disease progression are challenging and mostly rely on clinical impression and functional testing of horizontal eye movements. Diffusion tensor imaging (DTI) provides information about the microintegrity especially of white matter. We show here in a case report how DTI and measures derived from this imaging method can serve as adjunct quantitative markers for disease management in Niemann-Pick Type C. Two approaches are taken--first, we compare the fractional anisotropy (FA) in the white matter globally between a 29-year-old NPC patient and 18 healthy age-matched controls and show the remarkable difference in FA relatively early in the course of the disease. Second, a voxelwise comparison of FA values reveals where white matter integrity is compromised locally and demonstrate an individualized analysis of FA changes before and after 1year of treatment with Miglustat. This method might be useful in future treatment trials for NPC to assess treatment effects.

Forensic application of postmortem diffusion-weighted and diffusion tensor MR imaging of the human brain in situ

DWI and DTI of the brain have proved to be useful in many neurologic disorders and in traumatic brain injury. This prospective study aimed at the evaluation of the influence of the PMI and the cause of death on the ADC and FA for the application of DWI and DTI in forensic radiology.

Groups Acting on Tensor Products

Groups preserving a distributive product are encountered often in algebra. Examples include automorphism groups of associative and nonassociative rings, classical groups, and automorphism groups of p-groups. While the great variety of such products precludes any realistic hope of describing the general structure of the groups that preserve them, it is reasonable to expect that insight may be gained from an examination of the universal distributive products: tensor products. We give a detailed description of the groups preserving tensor products over semisimple and semiprimary rings, and present effective algorithms to construct generators for these groups. We also discuss applications of our methods to algorithmic problems for which all currently known methods require an exponential amount of work. (C) 2013 Elsevier B.V. All rights reserved.

Diffusion tensor imaging in episodic cluster headache

Cluster headache (CH) is a rare headache disorder with severe unilateral headache bouts and autonomic symptoms. The pathophysiology of CH is not completely understood. Using a voxel-based morphometric paradigm or functional imaging, a key role of the hypothalamus and the pain matrix could be demonstrated during CH episodes. However, there are no diffusion tensor imaging (DTI) data investigating the white matter microstructure of the brain in patients with CH. Therefore, we used DTI to delineate microstructural changes in patients with CH in a headache-free state.

Optic radiation fiber tracking using anteriorly angulated diffusion tensor imaging: a tested algorithm for quick application

Fiber tracking (FT) of the optic pathways (OPs) is difficult because there is no standard for the parameters of diffusion tensor imaging (DTI), placement of seed volumes, or interpreting the results.

Spinal Cord Diffusion-Tensor Imaging and Motor-evoked Potentials in Multiple Sclerosis Patients: Microstructural and Functional Asymmetry

Purpose: To assess possible association between intrinsic structural damage and clinical disability by correlating spinal cord diffusion-tensor (DT) imaging data with electrophysiological parameters in patients with a diagnosis of multiple sclerosis (MS). Materials and Methods: This study was approved by the local ethical committee according to the declaration of Helsinki and written informed consent was obtained. DT images and T1- and T2-weighted images of the spinal cord were acquired in 28 healthy volunteers and 41 MS patients. Fractional anisotropy (FA) and apparent diffusion coefficients were evaluated in normal-appearing white matter (NAWM) at the cervical level and were correlated with motor-evoked potentials (n = 34). Asymmetry index was calculated for FA values with corresponding left and right regions of interest as percentage of the absolute difference between these values relative to the sum of the respective FA values. Statistical analysis included Spearman rank correlations, Mann-Whitney test, and reliability analysis. Results: Healthy volunteers had low asymmetry index (1.5%-2.2%). In MS patients, structural abnormalities were reflected by asymmetric decrease of FA (asymmetry index: 3.6%; P = .15). Frequently asymmetrically affected among MS patients was left and right central motor conduction time (CMCT) to abductor digiti minimi muscle (ADMM) (asymmetry index, 15%-16%) and tibialis anterior muscle (TAM) (asymmetry index, 9.5%-14.1%). Statistically significant correlations of functional (ie, electrophysiological) and structural (ie, DT imaging) asymmetries were found (P = .005 for CMCT to ADMM; P = .007 for CMCT to TAM) for the cervical lateral funiculi, which comprise the crossed pyramidal tract. Interobserver reliability for DT imaging measurements was excellent (78%-87%). Conclusion: DT imaging revealed asymmetric anatomic changes in spinal cord NAWM, which corresponded to asymmetric electrophysiological deficits for both arms and legs, and reflected a specific structure-function relationship in the human spinal cord. © RSNA, 2013.

Examining the gateway to the limbic system with diffusion tensor imaging: the perforant pathway in dementia

Current treatments for Alzheimer's disease (AD) are only able to slow the progression of mental deterioration, making early and reliable diagnosis an essential part of any promising therapeutic strategy. In the initial stages of AD, the first neuropathological alterations occur in the perforant pathway (PP), a large neuronal fiber tract located at the entrance to the limbic system. However, to date, there is no sensitive diagnostic tool for performing in vivo assessments of this structure. In the present bimodal magnetic resonance imaging (MRI) study, we examined 10 elderly controls, 10 subjects suffering from mild cognitive impairment (MCI), and 10 AD patients in order to evaluate the sensitivity of diffusion tensor imaging (DTI), a new MRI technique, for detecting changes in the PP. Furthermore, the diagnostic explanatory power of DTI data of the PP should be compared to high-resolution MRI volumetry and intervoxel coherences (COH) of the hippocampus and the entorhinal cortex, two limbic regions also involved in the pathophysiology of early AD. DTI revealed a marked decrease in COH values in the PP region of MCI (right side: 26%, left side: 29%, as compared to controls) and AD patients (right side: 37%, left side: 43%, as compared to controls). Reductions in COH values of the PP region were significantly correlated with cognitive impairment. DTI data of the PP zone were the only parameter differing significantly between control subjects and MCI patients, while the volumetric measures and the COH values of the hippocampus and the entorhinal cortex did not. DTI of medial temporal brain regions is a promising non-invasive tool for the in vivo diagnosis of the early/preclinical stages of AD.

Line-scan diffusion tensor imaging of the posttraumatic brain stem: changes with neuropathologic correlation

Following trauma, imaging of brain stem lesions is often inconclusive. In a man who suffered a lethal accident, postmortem MR diffusion tensor (DT) imaging of the brain and neuropathologic examination were performed. DT imaging showed a disorganization of fibers in the brain stem that was not found in 2 controls and corresponded to changes on neuropathologic correlation. Diffusion tensor imaging provides an insight into the organization of myelinated structures of the CNS, potentially allowing diagnosis of traumatic fiber tract rupture.

Monotone Constrained Tensor-product B-spline with application to screening studies

When different markers are responsive to different aspects of a disease, combination of multiple markers could provide a better screening test for early detection. It is also resonable to assume that the risk of disease changes smoothly as the biomarker values change and the change in risk is monotone with respect to each biomarker. In this paper, we propose a boundary constrained tensor-product B-spline method to estimate the risk of disease by maximizing a penalized likelihood. To choose the optimal amount of smoothing, two scores are proposed which are extensions of the GCV score (O'Sullivan et al. (1986)) and the GACV score (Ziang and Wahba (1996)) to incorporate linear constraints. Simulation studies are carried out to investigate the performance of the proposed estimator and the selection scores. In addidtion, sensitivities and specificities based ona pproximate leave-one-out estimates are proposed to generate more realisitc ROC curves. Data from a pancreatic cancer study is used for illustration.

Cerebral connectivity and psychotic personality traits : A diffusion tensor imaging study

This study aims to investigate the relationship between regional connectivity in the brain white matter and the presence of psychotic personality traits, in healthy subjects with psychotic traits. Thirteen healthy controls were administered the MMPI-2, to assess psychotic traits and, according to MMPI results, a dichotomization into a group of "high-psychotic" and "low-psychotic" was performed. Diffusion tensor imaging (DTI) was used as a non-invasive measure, in order to obtain information about the fractional anisotropy (FA), an intravoxel index of local connectivity and, by means of a voxelwise approach, the between-group differences of the FA values were calculated. The "high-psychotic" group showed higher FA in the left arcuate fasciculus. Subjects with low scores for psychotic traits had significantly higher FA in the corpus callosum, right arcuate fasciculus, and fronto-parietal fibers. In line with previous brain imaging studies of schizophrenia spectrum disorders, our results suggest that psychotic personality traits are related to altered connectivity and brain asymmetry.

Characterization of white matter alterations in phenylketonuria by magnetic resonance relaxometry and diffusion tensor imaging

A multimodal MR study including relaxometry, diffusion tensor imaging (DTI), and MR spectroscopy was performed on patients with classical phenylketonuria (PKU) and matched controls, to improve our understanding of white matter (WM) lesions. Relaxometry yields information on myelin loss or malformation and may substantiate results from DTI attributed to myelin changes. Relaxometry was used to determine four brain compartments in normal-appearing brain tissue (NABT) and in lesions: water in myelin bilayers (myelin water, MW), water in gray matter (GM), water in WM, and water with long relaxation times (cerebrospinal fluid [CSF]-like signals). DTI yielded apparent diffusion coefficients (ADCs) and fractional anisotropies. MW and WM content were reduced in NABT and in lesions of PKU patients, while CSF-like signals were significantly increased. ADC values were reduced in PKU lesions, but also in the corpus callosum. Diffusion anisotropy was reduced in lesions because of a stronger decrease in the longitudinal than in the transverse diffusion. WM content and CSF-like components in lesions correlated with anisotropy and ADC. ADC values in lesions and in the corpus callosum correlated negatively with blood and brain phenylalanine (Phe) concentrations. Intramyelinic edema combined with vacuolization is a likely cause of the WM alterations. Correlations between diffusivity and Phe concentrations confirm vulnerability of WM to high Phe concentrations.