A machine learning approach to parameter inference in gravitational-wave signal analysis

openGravitational Wave (GW) physics is now in its golden age thanks to modern interferometers. The fourth observing run is now ongoing with two of the four second-generation detectors, collecting GW signals coming from Compact Binary Coalescences (CBCs). These systems are formed by black holes and/or neutron stars which lose energy and angular momentum in favour of GW emission, spiraling toward each other until they merge. The characteristic waveform has a chirping behaviour, with a frequency increasing with time. These GW signals are gold mines of physical information on the emitting system. The data analysis of these signals has two main aspects: detection and parameter estimation. For what concerns detection, two approaches are used right now: matched filtering, which compares numerical waveform with raw interferometers' output to highlight the signal, and the study of bursts, which highlights the coherence of arbitrary signals in different detectors. Both these techniques need to be fast enough to allow for electromagnetic follow-up with a relatively short delay. The offline parameter inference process is based on Bayesian techniques and is rather lengthy (individual processing Markov Chain Monte Carlo runs can take a month or more). My thesis has the goal of introducing a fast parameter estimation for unmodeled (burst) methods which produce only phenomenological, de-noised waveforms with, at best, a rough estimate of only a few parameters. The implementation of an approach for fast parameter inference in this unmodeled analysis, taking as input the reconstructed waveform, could be extremely useful for multimessenger observations. In this context, Keith et al. (2021a) proposed to use Physics Informed Neural Networks (PINNs) in GW data analysis. These PINNs are a machine learning approach which includes physical prior information in the algorithm itself. Taking a clean chirping waveform as input, the algorithm of Keith et al. (2021a) demonstrated a successful application of this concept and was able to reconstruct the compact object's orbits before coalescence with great detail, starting only from a parameterized Post-Newtonian model. The PINN environment could become a key tool to infer parameters from GW signals with a simple physical ansatz. As part of my thesis work, I reviewed in detail GW physics and the PINN environment and I updated the algorithm described in Keith et al. (2021a). Their ground-breaking work introduces PINNs for the first time in the analysis of GW signals, however it does so without considering some important details. In particular, I noted that the algorithm of Keith et al. (2021a) spans a very constrained parameter space. In this thesis I introduce some of the missing details and I recode the algorithm from scratch. My implementation includes the learning of the phenomenological differential equation that describes the frequency evolution over time of the chirping GW, within a different, but more physical, parameter space. As a test, starting from a waveform as training data, and from the Newtonian approximation of the GW chirp, I infer the chirp mass, the GW phase and the frequency exponent in the differential equation. The resulting algorithm is robust and uses realistic physical conditions. This is a necessary first step to realize parameter inference with PINNs on real gravitational wave data

Pancreatic tumors imaging: an update

Currently, ultrasound (US), computed tomography (CT) and Magnetic Resonance imaging (MRI) represent the mainstay in the evaluation of pancreatic solid and cystic tumors affecting pancreas in 80-85% and 10-15% of the cases respectively. Integration of US, CT or MR imaging is essential for an accurate assessment of pancreatic parenchyma, ducts and adjacent soft tissues in order to detect and to stage the tumor, to differentiate solid from cystic lesions and to establish an appropriate treatment. The purpose of this review is to provide an overview of pancreatic tumors and the role of imaging in their diagnosis and management. In order to a prompt and accurate diagnosis and appropriate management of pancreatic lesions, it is crucial for radiologists to know the key findings of the most frequent tumors of the pancreas and the current role of imaging modalities. A multimodality approach is often helpful. If multidetector-row CT (MDCT) is the preferred initial imaging modality in patients with clinical suspicion for pancreatic cancer, multiparametric MRI provides essential information for the detection and characterization of a wide variety of pancreatic lesions and can be used as a problem-solving tool at diagnosis and during follow-up

Identification of markers for the authentication of cranberry extract and cranberry-based food supplements

Due to the high cost of the cranberry extract, there have been several reported cases of adulteration. The aim of our study was to find markers to authenticate extracts or cranberry-based food supplements. Cranberry fruits from 7 countries, 17 cranberry extracts and 10 cranberry-based food supplements were analysed by UPLC-DAD-Orbitrap MS. Procyanidins were assessed by DMAC method. Anthocyanin fingerprint and epicatechin/catechin, procyanidin A2/total procyanidin and procyanidin/anthocyanin ratios were used as markers, and PCA carried out to check for similarity. Approximately 24% and 60% of the extracts and food supplements, respectively, differed significantly from the fruits. One seemed adulterated with Morus nigra and two with Hibiscus extract. Six food supplements were non-compliant and five contained mainly cyanidin-glucoside and cyanidin-rutinoside, suggesting adulteration with M. nigra extract. Only four products contained the procyanidin amount declared on the package, and only one provided the daily dose deemed effective for treating a urinary tract infection

Diagnosis and endovascular treatment of an internal mammary artery injury

Internal mammary artery (IMA) disruption after blunt chest trauma is rare. In some instances, it may occur after mild chest trauma with minor external physical findings. However, prompt diagnosis and treatment are necessary, as it can be associated with vascular and parenchymal injuries. We report a case of blunt chest trauma resulting in a sternal fracture associated with an IMA injury, active anterior mediastinal bleeding, bilateral lung contusions, and a left hemothorax. It was successfully treated by selective embolization to the left IMA branch and chest tube placement

Metabolic syndrome and idiopathic sudden sensori-neural hearing loss

The purpose of this study was to evaluate the association between the presence of Metabolic Syndrome (MetS) and idiopathic sudden sensorineural hearing loss (ISSHL) and the impact of MetS on recovery of patients with ISSHL. 39 Patients with ISSHL and 44 controls were enrolled in this study. Demographic, clinical characteristics and hearing recovery were evaluated. MetS was defined according to the diagnostic criteria of International Diabetes Federation (IDF) consensus definition. Patients affected by ISSHL presented a body mass index (BMI), waist circumference, waist hip ratio (WHR), fasting glucose and blood pressure significantly higher compared to controls. Considering patients with central obesity, 5 controls and 15 ISSHL patients met the criteria of MetS. According to Siegel criteria, a complete or partial recovery was observed in 60% of patients with MetS and in 91,66% of patients without MetS. MetS was associated with ISSHL and this association negatively influenced the hearing recovery of these patients

Mémoire de fille ou la « mémoire pensante » d’Annie Ernaux

The new edition of Annie Ernaux’s writing notebook, L’Atelier noir (Paris: Gallimard 2022), brings unprecedented attention to the almost thirty-year gestation that preceded the publication of the text Mémoire de fille (Paris: Gallimard 2016). Both the content and the form of this text reveal a long reflection on the theme of memory or, rather, on the quality of an impossible remembering. Therefore, the article aims to analyse the 2016 text by means of the considerations on Erinnerung and Gedächtnis common to Paul de Man and Jacques Derrida. The main theoreticalreference will be the text Mémoires pour Paul de Man (1988) and, starting from the reflections on the ‘thinking memory’, an attempt will be made to analyse the narrative outcomes and discursive strategies adopted by Ernaux within this text that stands, perhaps more than any of her others, as the most radical ‘event’ of her writing.La nouvelle édition du journal d’écriture d’Annie Ernaux, L’Atelier noir (Paris : Gallimard, 2022), porte une attention inédite à la gestation de près de trente ans qui a précédé la publication du texte Mémoire de fille (Paris : Gallimard, 2016). Tant le contenu que la forme de ce texte dénoncent une longue réflexion sur la mémoire ou, plutôt, sur la qualité intrinsèque d’un souvenir impossible ; pour cette raison, l’article tentera d’analyser le texte de 2016 au moyen des considérations sur l’Erinnerung et le Gedächtnis communes à Paul de Man et à Jacques Derrida. Le texte théorique de référence sera les Mémoires pour Paul de Man (1988) et, à partir des réflexions sur la « mémoire pensante », on tentera  d’analyser les résultats narratifs et les stratégies discursives adoptées par Ernaux dans ce texte qui, plus que tout autre, semble constituer l’« événement » le plus radical de son écriture