El marc jurídic : dret comparat

A partir d'una primera aproximació a les dades socioeconòmiques sobre la mediació als Estats Units, Austràlia, Nova Zelanda, Llatinoamèrica, Àsia i Europa, i després d'una anàlisi de les previsions normatives en matèria de mediació existents a l'actualitat, s'ha procedit a la identificació de certs principis i estàndards que han permès una delimitació progressiva del concepte de mediació desenvolupat en l'experiència estrangera dels diferents estats nacionals i dels organismes supranacionals i internacionals. Delimitat el concepte, l'estudi aborda una segona etapa, consistent en la comprensió del fenomen mediador en el context de les diverses cultures i tradicions jurídiques, així com en els diversos contextos socioeconòmics en els quals la mediació es desenvolupa principalment, tot identificant els àmbits d'aplicació materials i orgànics. Finalment, després d'una atenta identificació del concepte i descripció legal de la mediació existent a Espanya i Catalunya, el present estudi es conclou amb un exercici de contrast, a fi d'identificar els aspectes transversals i transnacionals que puguin resultar aplicables en una futura regulació de la mediació a Catalunya

Multivariate side-band subtraction using probabilistic event weights

A common situation in experimental physics is to have a signal which can not be separated from a non-interfering background through the use of any cut. In this paper, we describe a procedure for determining, on an event-by-event basis, a quality factor ($Q$-factor) that a given event originated from the signal distribution. This procedure generalizes the "side-band" subtraction method to higher dimensions without requiring the data to be divided into bins. The $Q$-factors can then be used as event weights in subsequent analysis procedures, allowing one to more directly access the true spectrum of the signal.Comment: 17 pages, 9 figure

Exploring the spectroscopic diversity of type Ia supernovae with DRACULA: a machine learning approach

The existence of multiple subclasses of type Ia supernovae (SNeIa) has been the subject of great debate in the last decade. One major challenge inevitably met when trying to infer the existence of one or more subclasses is the time consuming, and subjective, process of subclass definition. In this work, we show how machine learning tools facilitate identification of subtypes of SNeIa through the establishment of a hierarchical group structure in the continuous space of spectral diversity formed by these objects. Using Deep Learning, we were capable of performing such identification in a 4 dimensional feature space (+1 for time evolution), while the standard Principal Component Analysis barely achieves similar results using 15 principal components. This is evidence that the progenitor system and the explosion mechanism can be described by a small number of initial physical parameters. As a proof of concept, we show that our results are in close agreement with a previously suggested classification scheme and that our proposed method can grasp the main spectral features behind the definition of such subtypes. This allows the confirmation of the velocity of lines as a first order effect in the determination of SNIa subtypes, followed by 91bg-like events. Given the expected data deluge in the forthcoming years, our proposed approach is essential to allow a quick and statistically coherent identification of SNeIa subtypes (and outliers). All tools used in this work were made publicly available in the Python package Dimensionality Reduction And Clustering for Unsupervised Learning in Astronomy (DRACULA) and can be found within COINtoolbox (https://github.com/COINtoolbox/DRACULA).Comment: 16 pages, 12 figures, accepted for publication in MNRA

Enabling Network Slicing Across a Disaggregated Optical Transport Network

We propose and implement a network virtualization architecture for open optical (partially) disaggregated networks, based on a device hypervisor and OpenConfig and OpenROADM data models, in support of 5G network slicing over interconnected NFVI-PoPs

Porcine reproductive and respiratory syndrome prevalence and processing fluids use for diagnosis in United States breeding herds

Processing fluids have been recently adopted by the U.S. swine industry as a breeding herd PRRS monitoring tool due to their increased representativeness of animals within the herd. Here, we use the Morrison Swine Health Monitoring Project (MSHMP) database, representative of ~50% of the U.S. swine breeding herd, to describe processing fluids submissions for PRRS diagnosis and their relation to PRRS prevalence and time to stability over time between 2009 and 2020.info:eu-repo/semantics/publishedVersio