Canonical formalism for compact sources

This thesis aims to describe the ADM formalism of General Relativity and to use the latter to describe a spherical compact source consisting of a perfect fluid. With two different choices for three-dimensional metric on hypersurfaces, we analyze the constraints of the system in the non-static case and the resulting equations of motion, both for canonical gravitational variables and those of matter. After examining some special cases, we also show that it is possible, in the case of static nature, to obtain the value of the Misner-Sharp mass from the Hamiltonian constraint, while near the trapping surfaces we obtain a relationship between the density of matter and the dynamic variables of the metric. Finally we propose a possible method for quantizing the constraints using the procedure that in the vacuum leads to the Wheeler-DeWitt equations

Disease Progression Modeling and Prediction through Random Effect Gaussian Processes and Time Transformation

The development of statistical approaches for the joint modelling of the temporal changes of imaging, biochemical, and clinical biomarkers is of paramount importance for improving the understanding of neurodegenerative disorders, and for providing a reference for the prediction and quantification of the pathology in unseen individuals. Nonetheless, the use of disease progression models for probabilistic predictions still requires investigation, for example for accounting for missing observations in clinical data, and for accurate uncertainty quantification. We tackle this problem by proposing a novel Gaussian process-based method for the joint modeling of imaging and clinical biomarker progressions from time series of individual observations. The model is formulated to account for individual random effects and time reparameterization, allowing non-parametric estimates of the biomarker evolution, as well as high flexibility in specifying correlation structure, and time transformation models. Thanks to the Bayesian formulation, the model naturally accounts for missing data, and allows for uncertainty quantification in the estimate of evolutions, as well as for probabilistic prediction of disease staging in unseen patients. The experimental results show that the proposed model provides a biologically plausible description of the evolution of Alzheimer's pathology across the whole disease time-span as well as remarkable predictive performance when tested on a large clinical cohort with missing observations.Comment: 13 pages, 2 figure

Visualizing Convolutional Networks for MRI-based Diagnosis of Alzheimer's Disease

Visualizing and interpreting convolutional neural networks (CNNs) is an important task to increase trust in automatic medical decision making systems. In this study, we train a 3D CNN to detect Alzheimer's disease based on structural MRI scans of the brain. Then, we apply four different gradient-based and occlusion-based visualization methods that explain the network's classification decisions by highlighting relevant areas in the input image. We compare the methods qualitatively and quantitatively. We find that all four methods focus on brain regions known to be involved in Alzheimer's disease, such as inferior and middle temporal gyrus. While the occlusion-based methods focus more on specific regions, the gradient-based methods pick up distributed relevance patterns. Additionally, we find that the distribution of relevance varies across patients, with some having a stronger focus on the temporal lobe, whereas for others more cortical areas are relevant. In summary, we show that applying different visualization methods is important to understand the decisions of a CNN, a step that is crucial to increase clinical impact and trust in computer-based decision support systems.Comment: MLCN 201

How-To compute EPRL spin foam amplitudes

Spin foam theory is a concrete framework for quantum gravity where numerical calculations of transition amplitudes are possible. Recently, the field became very active, but the entry barrier is steep, mainly because of its unusual language and notions scattered around the literature. This paper is a pedagogical guide to spin foam transition amplitude calculations. We show how to write an EPRL-FK transition amplitude, from the definition of the 2-complex to its numerical implementation using \texttt{sl2cfoam-next}. We guide the reader using an explicit example balancing mathematical rigor with a practical approach. We discuss the advantages and disadvantages of this approach and provide a novel look at a recently proposed approximation scheme.Comment: 28 pages with many colored figures. Paper published in the special issue "Probing the Quantum Space-Time" of Universe. v-2 Added introductory section. Matching published versio

Validation of the BUGJEFF311.BOLIB, BUGENDF70.BOLIB and BUGLE-B7 broad-group libraries on the PCA-Replica (H2O/Fe) neutron shielding benchmark experiment

The PCA-Replica 12/13 (H2 O/Fe) neutron shielding benchmark experiment was analysed using the TORT-3.2 3D SN code. PCA-Replica reproduces a PWR ex-core radial geometry with alternate layers of water and steel including a pressure vessel simulator. Three broad-group coupled neutron/photon working cross section libraries in FIDO-ANISN format with the same energy group structure (47 n + 20 γ) and based on different nuclear data were alternatively used: the ENEA BUGJEFF311.BOLIB (JEFF-3.1.1) and UGENDF70.BOLIB (ENDF/B-VII.0) libraries and the ORNL BUGLE-B7 (ENDF/B-VII.0) library. Dosimeter cross sections derived from the IAEA IRDF-2002 dosimetry file were employed. The calculated reaction rates for the Rh-103(n,n′)Rh-103m, In-115(n,n′)In-115m and S-32(n,p)P-32 threshold activation dosimeters and the calculated neutron spectra are compared with the corresponding experimental results

Text-to-Text Extraction and Verbalization of Biomedical Event Graphs

Biomedical events represent complex, graphical, and semantically rich interactions expressed in the scientific literature. Almost all contributions in the event realm orbit around semantic parsing, usually employing discriminative architectures and cumbersome multi-step pipelines limited to a small number of target interaction types. We present the first lightweight framework to solve both event extraction and event verbalization with a unified text-to-text approach, allowing us to fuse all the resources so far designed for different tasks. To this end, we present a new event graph linearization technique and release highly comprehensive event-text paired datasets, covering more than 150 event types from multiple biology subareas (English language). By streamlining parsing and generation to translations, we propose baseline transformer model results according to multiple biomedical text mining benchmarks and NLG metrics. Our extractive models achieve greater state-of-the-art performance than single-task competitors and show promising capabilities for the controlled generation of coherent natural language utterances from structured data

Radiative corrections to the Lorentzian EPRL spin foam propagator

We numerically estimate the divergence of several two-vertex diagrams that contribute to the radiative corrections for the Lorentzian EPRL spin foam propagator. We compute the amplitudes as functions of a homogeneous cutoff over the bulk quantum numbers, fixed boundary data, and different Immirzi parameters, and find that for a class of two-vertex diagrams, those with fewer than six internal faces are convergent. The calculations are done with the numerical framework sl2cfoam-next.Comment: 20 pages, 11 figure

Expressions biogéologiques du confinement dans une lagune méditerranéenne : le lac Melah (Algérie)

Le lac Melah est un bassin paralique relativement profond communiquant avec la mer par un chenal étroit de faible profondeur. Ces caractéristiques ont pour conséquences la stratification des eaux et un fort confinement de l'ensemble du bassin qui engendre une biomasse phytoplanctonique élevée. Celle-ci est peu consommée par une macrofaune dense mais de faible biomasse et se dépose massivement sous la lentille d'eau inférieure anoxique. Le lac Melah apparaît ainsi comme un modèle actuel de bassin producteur de roches-mères d'hydrocarbures. En revanche, ses potentialités aquacoles sont limitées. (Résumé d'auteur

Enhancing Biomedical Scientific Reviews Summarization with Graph-based Factual Evidence Extracted from Papers

Combining structured knowledge and neural language models to tackle natural language processing tasks is a recent research trend that catalyzes community attention. This integration holds a lot of potential in document summarization, especially in the biomedical domain, where the jargon and the complex facts make the overarching information truly hard to interpret. In this context, graph construction via semantic parsing plays a crucial role in unambiguously capturing the most relevant parts of a document. However, current works are limited to extracting open-domain triples, failing to model real-world n-ary and nested biomedical interactions accurately. To alleviate this issue, we present EASumm, the first framework for biomedical abstractive summarization enhanced by event graph extraction (i.e., graphical representations of medical evidence learned from scientific text), relying on dual text-graph encoders. Extensive evaluations on the CDSR dataset corroborate the importance of explicit event structures, with better or comparable performance than previous state-of-the-art systems. Finally, we offer some hints to guide future research in the field