Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians

This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of finite mixture models, conjugate families and factorization. Both the joint probability density of the variables and the likelihood function of the (objective or subjective) observation are approximated by a special mixture model, in such a way that any desired conditional distribution can be directly obtained without numerical integration. We have developed an extended version of the expectation maximization (EM) algorithm to estimate the parameters of mixture models from uncertain training examples (indirect observations). As a consequence, any piece of exact or uncertain information about both input and output values is consistently handled in the inference and learning stages. This ability, extremely useful in certain situations, is not found in most alternative methods. The proposed framework is formally justified from standard probabilistic principles and illustrative examples are provided in the fields of nonparametric pattern classification, nonlinear regression and pattern completion. Finally, experiments on a real application and comparative results over standard databases provide empirical evidence of the utility of the method in a wide range of applications

Extreme speech, hate crimes and freedom of expression: A difficult balance

Este trabajo afronta la necesidad de conseguir una definición legal más clara y restrictiva del discurso del odio y se plantea los límites de la libertad de expresión ante discursos intolerantes. Asimismo, estudia las distintas respuestas que ofrece el ordenamiento jurídico y en particular el impacto de las redes sociales y de InternetThis paper addresses the need to a more defined and restrictive legal definition of hate speech and displays the limits on freedom of expression related to extreme speech. Moreover, it studies the different responses offered by the legal system and the impact of social networks and the Interne

Revision of the genus \u3cem\u3eTityopsis\u3c/em\u3e Armas, 1974 (Scorpiones: Buthidae). Part 1. General updates and description of four new species

The buthid scorpion genus Tityopsis Armas, 1974, endemic to western Cuba, is herein revised. In total, 428 specimens were examined from 127 localities, including the primary types of the two species currently recognized as valid; this led to realize that several populations actually represent taxa new to science. Four of them are described in the present paper: a presumed troglobite and three others from epigean habitats. A thorough photographic complement and data on natural history are given for each species and for the genus in general, for which known geographical distribution is verified and updated. With this contribution, the scorpion fauna of Cuba reaches now 61 species, with 56 of them (92%) being endemic to this Caribbean archipelago

The missing piece of the puzzle solved: \u3cem\u3eHeteronebo\u3c/em\u3e Pocock, 1899 (Scorpiones: Scorpionidae) occurs at Isla de Pinos, Cuba

The diplocentrine scorpion genus Heteronebo Pocock, 1899 is recorded herein for the first time from Isla de Pinos, southwestern Cuba. A total of 15 specimens of Heteronebo bermudezi (Moreno, 1938) were collected in two nearby localities of the southern coast of the island, where it occurs in exactly the same habitat previously known for this species in Guanahacabibes Peninsula and two cays of Canarreos Archipelago. The allegedly polytypic status of this species is also revised and full species rank is restored to the subspecies Heteronebo bermudezi morenoi (Armas, 1973). An updated distribution map of H. bermudezi is provided

The economic reaction to non-pharmaceutical interventions during Covid-19

Policy makers have implemented a set of non-pharmaceutical interventions (NPIs) to contain the spread of Covid-19 and reduce the burden on health systems. These restrictive measures have had adverse effects on economic activity; however, these negative impacts differ with respect to each country. Based on daily data, this article studies governmental economic responses to the application of NPIs for 59 countries. Furthermore, we assess if these economic responses differ according to the economic and sectoral context of the countries. By applying a counting model to the economic support intensity, our results quantify the average reaction of governments in counterbalancing the imposition of NPIs. We further re-estimate the base model by dividing the countries according to their GDP per capita, the intensity of their service sectors, and the expenditure by tourists. Our results show how each NPI implied a different level of economic support and how the structural characteristics considered were relevant to the decision-making process