Topological features of massive bosons on two dimensional Einstein space-time

In this paper we tackle the problem of constructing explicit examples of topological cocycles of Roberts' net cohomology, as defined abstractly by Brunetti and Ruzzi. We consider the simple case of massive bosonic quantum field theory on the two dimensional Einstein cylinder. After deriving some crucial results of the algebraic framework of quantization, we address the problem of the construction of the topological cocycles. All constructed cocycles lead to unitarily equivalent representations of the fundamental group of the circle (seen as a diffeomorphic image of all possible Cauchy surfaces). The construction is carried out using only Cauchy data and related net of local algebras on the circle.Comment: 41 pages, title changed, minor changes, typos corrected, references added. Accepted for publication in Ann. Henri Poincare

Desengaño del abuso de la sangria y purga compuesto por ... Lorenço Romeo ...

BHR/A-012-339(BIB LVL) w-FONDO ANTIGUO(ES-GrU)b13642881-34cbua_ugr(OCoLC)915446024UGRALARomeo, LorenzoDesengaño del abuso de la sangria y purga compuesto por ... Lorenço Romeo ...Impresso en Tarragona[8], 165, [2] h.Colofó

Fault plane orientations of microearthquakes at Mt. Etna from theinversion of P-wave rise times

A crucial point in the analysis of tectonic earthquakes occurring in a volcanic area is the inference of the orientation of the structures along which the ruptures occur. These structures represent zones of weakness which could favor the migration of melt toward the surface and the assessment of their geometry is a fundamental step toward efficient evaluation of volcanic risk. We analyzed a high-quality dataset of 171 lowmagnitude, tectonic earthquakes that occurred at Mt. Etna during the 2002–2003 eruption. We applied a recently developed technique aimed at inferring the source parameters (source size, dip and strike fault) and the intrinsic quality factor Qp of P waves from the inversion of rise times. The technique is based on numerically calibrated relationships among the rise time of first P waves and the source parameters for a circular crack rupturing at a constant velocity. For the most of the events the directivity source effect did not allow us to constrain the fault plane orientation. For a subset of 45 events with well constrained focal mechanisms we were able to constrain the “true” fault plane orientation. The level of resolution of the fault planes was assessed through a non linear analysis based on the random deviates technique. The significance of the retrieved fault plane solutions and the fit of the assumed source model to data were assessed through a χ-square test. Most of the retrieved fault plane solutions agree with the geometrical trend of known surface faults. The inferred source parameters and Qp are in agreement with the results of previous studie

differential diagnosis of benign and malignant vertebral compression fractures using conventional and advanced mri techniques

Atraumatic vertebral compression fractures (VCFs) are commonly encountered in clinical practice and often represent a diagnostic challenge. MRI plays a major role in the differential diagnosis of benign and malignant VCFs, due to its high contrast resolution and the possibility to obtain quantitative and functional data with the employment of advanced sequences. Computer-aided diagnosis systems are also applied on MRI images for this purpose, showing promising results. In this setting, aim of this pictorial review is to elucidate the role of MRI in the differential diagnosis of VCFs with a specific focus on advanced and post-processing imaging techniques

Artificial intelligence applied to neuroimaging data in Parkinsonian syndromes: Actuality and expectations

Idiopathic Parkinson's Disease (iPD) is a common motor neurodegenerative disorder. It affects more frequently the elderly population, causing a significant emotional burden both for the patient and caregivers, due to the disease-related onset of motor and cognitive disabilities. iPD's clinical hallmark is the onset of cardinal motor symptoms such as bradykinesia, rest tremor, rigidity, and postural instability. However, these symptoms appear when the neurodegenerative process is already in an advanced stage. Furthermore, the greatest challenge is to distinguish iPD from other similar neurodegenerative disorders, "atypical parkinsonisms", such as Multisystem Atrophy, Progressive Supranuclear Palsy and Cortical Basal Degeneration, since they share many phenotypic manifestations, especially in the early stages. The diagnosis of these neurodegenerative motor disorders is essentially clinical. Consequently, the diagnostic accuracy mainly depends on the professional knowledge and experience of the physician. Recent advances in artificial intelligence have made it possible to analyze the large amount of clinical and instrumental information in the medical field. The application machine learning algorithms to the analysis of neuroimaging data appear to be a promising tool for identifying microstructural alterations related to the pathological process in order to explain the onset of symptoms and the spread of the neurodegenerative process. In this context, the search for quantitative biomarkers capable of identifying parkinsonian patients in the prodromal phases of the disease, of correctly distinguishing them from atypical parkinsonisms and of predicting clinical evolution and response to therapy represent the main goal of most current clinical research studies. Our aim was to review the recent literature and describe the current knowledge about the contribution given by machine learning applications to research and clinical management of parkinsonian syndromes

A first look at the Gargano (southern Italy) seismicity as seen by the local scale OTRIONS seismic network

OnApril 2013,alocal scale seismic network,namedOTRIONS, composed of twelve short period (1 Hz) three component seismometers, has been located in the northern part of the Apulia (Southern Italy). At each station, the acquisition systemallows the recording of data in situ and their real time transfer toa seismic laboratory located at the Dipartimento di Scienze della Terra e Geoambientali of Università di Bari "Aldo Moro". The preliminary real time detection and localization of the events is automatically realized by using the SeisComp3 software. In the first two months of data acquisition, the network recorded about one hundred low magnitude (ML<2) earthquakes. In that follows,wepresent the results of a study aimed at investigating the crustal structure of the Gargano promontory. To this aimweanalyzed the seismic events recorded in the area by the “Istituto Nazionale di Geofisica e Vulcanologia” (INGV) in the period 2006-2012 and the seismic events recorded by the OTRIONS network in the first two months of acquisition (march and april 2013). From the inversion of P and S travel times of INGV events we inferred a preliminary 3-layer Vp velocity model. The Moho is located at a depth of 27-30 km, in agreement with previous studies. A linearized inversion scheme that uses Velest (Kissling et al., 1994), allowed us to infer a 1D velocity model from the joint inversion of INGV and OTRIONS datasets of P and S travel times. On the whole, the number of earthquakes recorded by the OTRIONS seismic network is higher than 1200 in the period april,2013-march,2014

A first look at the Gargano (southern Italy) seismicity as seen by the local scale OTRIONS seismic network

On April 2013, a local scale seismic network, named OTRIONS, composed of twelve short period (1 Hz) three component seismometers, has been located in the northern part of the Apulia (southern Italy). In the first two months of data acquisition, the network recorded about one hundred very small (ML<2) magnitude earthquakes. A three-layer 1D VP velocity model was preliminarily computed, using the recordings of earthquakes occurred in the area in the period 2006-2012 and recorded by the national seismic network of INGV (Istituto Nazionale di Geofisica e Vulcanologia). This model was calibrated by means of a multi-scale approach, based on a global search of the minimum misfit between observed and theoretical travel times. At each step of the inversion, a grid-search technique was implemented to infer the elastic properties of the layers, by using HYPO71 to compute the forward models. In a further step, we used P and S travel times of both INGV and OTRIONS events to infer a minimum 1D VP velocity model, using a classical linearized inversion approach. Owing to the relatively small number of data and poor coverage of the area, in the inversion procedure, the VP/VS ratio was fixed to 1.82, as inferred from a modified Wadati diagram. The final 1D velocity model was obtained by averaging the inversion results arising from nine different initial velocity models. The inferred VP velocity model shows a gradual increase of P wave velocity with increasing the depth. The model is well constrained by data until to a depth of about 25-30 km

QR code and the wine sector: What contents? an exploratory research study on the wine industry

This paper presents an explorative analysis of the contents shared through QR codes as a tool of proximity marketing. The aim of the research is to identify the most common links shared through the QR code technology, in order to investigate the use of this tool from a marketing point of view. Moreover, the research explores the main aspects of the communications related to the contents shared through QR codes. Specifically, the authors focus on hedonic aspects and functional ones. Finally, the research aims at identifying preliminary best practices in the use of QR code technology. Due to the widespread use of this tool in the sector, the research focuses on the wine industry, as one of the most involved with QR code practices. The study adopts a qualitative approach based on a content analysis of 91 wine labels. Considering the importance of this integrated communication, the purpose of this explorative analysis is to deduce implications that enable managers to master the use of this tool, exploiting all its potential

Oncologic Imaging and Radiomics: A Walkthrough Review of Methodological Challenges

Imaging plays a crucial role in the management of oncologic patients, from the initial diagnosis to staging and treatment response monitoring. Recently, it has been suggested that its importance could be further increased by accessing a new layer of previously hidden quantitative data at the pixel level. Using a multi-step process, radiomics extracts potential biomarkers from medical images that could power decision support tools. Despite the growing interest and rising number of research articles being published, radiomics is still far from fulfilling its promise of guiding oncologic imaging toward personalized medicine. This is, at least partly, due to the heterogeneous methodological quality in radiomic research, caused by the complexity of the analysis pipelines. In this review, we aim to disentangle this complexity with a stepwise approach. Specifically, we focus on challenges to face during image preprocessing and segmentation, how to handle imbalanced classes and avoid information leaks, as well as strategies for the proper validation of findings