¿De los nuevos medios a las hipermediaciones?

El nombre que le he dado a este artículo recoge la apuesta de Scolari: actualizar el trabajo de Martin-Barbero. Sin duda, la propuesta es audaz desde el punto de vista de la variable tecnológica (habla de hipermediaciones); lamentablemente en el trabajo se pierde el fondo: no aparece el aparato crítico ni la lectura encarnada en la realidad socio-política de América Latina. En varios autores y autoras citados aparece reiteradamente la categoría convergencia: la destacaré como lo merece.-La interactividad. -Caracterización del Nuevo Medio. -Aproximación a una taxonomía de los NM. -Lista de referencias

Tensorial analisis of the superposed deformation in the easthern border of the Madrid basin

An analysis of Neogene brittle deformation using fault populatíon analysis methods has been carried out between the SW border of the Iberian Range and Altomira Range. Two main paleostress fields have been established: 1) N70E - N120E compression (Altomira paleostress field) ofLate Oligocene - Early Miocene age that induced the formation of the SW border of Iberian Range and Altomira - Pareja thrust belts with reverse and strike-slip faults. 2) N140-N160E compression (Guadarrama paleostress field) of Middle Aragonian - early Pleistocene age that reactivated previous faults with strikeslip movement along the Iberian Range. A superposition of two regional stress fields (Iberian and Guadarrama) is proposed to explain E-W compression that formed Altomira Range. Stress tensorial additions have been realized to check this hypothesis

Quantifying offshore fore-arc deformation and splay-fault slip using drowned Pleistocene shorelines, Arauco Bay, Chile

Indexación: Web of Science; Scopus.Most of the deformation associated with the seismic cycle in subduction zones occurs offshore and has been therefore difficult to quantify with direct observations at millennial timescales. Here we study millennial deformation associated with an active splay-fault system in the Arauco Bay area off south central Chile. We describe hitherto unrecognized drowned shorelines using high-resolution multibeam bathymetry, geomorphic, sedimentologic, and paleontologic observations and quantify uplift rates using a Landscape Evolution Model. Along a margin-normal profile, uplift rates are 1.3 m/ka near the edge of the continental shelf, 1.5 m/ka at the emerged Santa María Island, −0.1 m/ka at the center of the Arauco Bay, and 0.3 m/ka in the mainland. The bathymetry images a complex pattern of folds and faults representing the surface expression of the crustal-scale Santa María splay-fault system. We modeled surface deformation using two different structural scenarios: deep-reaching normal faults and deep-reaching reverse faults with shallow extensional structures. Our preferred model comprises a blind reverse fault extending from 3 km depth down to the plate interface at 16 km that slips at a rate between 3.0 and 3.7 m/ka. If all the splay-fault slip occurs during every great megathrust earthquake, with a recurrence of ~150–200 years, the fault would slip ~0.5 m per event, equivalent to a magnitude ~6.4 earthquake. However, if the splay-fault slips only with a megathrust earthquake every ~1000 years, the fault would slip ~3.7 m per event, equivalent to a magnitude ~7.5 earthquake. ©2017. American Geophysical Union.http://onlinelibrary.wiley.com/doi/10.1002/2016JB013339/epd

Detection of Adversarial Training Examples in Poisoning Attacks through Anomaly Detection

Machine learning has become an important component for many systems and applications including computer vision, spam filtering, malware and network intrusion detection, among others. Despite the capabilities of machine learning algorithms to extract valuable information from data and produce accurate predictions, it has been shown that these algorithms are vulnerable to attacks. Data poisoning is one of the most relevant security threats against machine learning systems, where attackers can subvert the learning process by injecting malicious samples in the training data. Recent work in adversarial machine learning has shown that the so-called optimal attack strategies can successfully poison linear classifiers, degrading the performance of the system dramatically after compromising a small fraction of the training dataset. In this paper we propose a defence mechanism to mitigate the effect of these optimal poisoning attacks based on outlier detection. We show empirically that the adversarial examples generated by these attack strategies are quite different from genuine points, as no detectability constrains are considered to craft the attack. Hence, they can be detected with an appropriate pre-filtering of the training dataset

Síntesis estratigráfica del Terciario del borde Sur de la Cuenca del Ebro: unidades genéticas

In the southern margin of the Ebro Basin eigth Tectosedimentary Units (TSU) have been defined by means of the application of tectosedimentary analysis. These units are limited by sedimentary breaks which can be recognized in the whole studied area. The sedimentary breaks are genetically related to diastrophic evolution, and they are shown as angular or syntectonic unconformities at the basin margins. Each TSU has aparticular sequential evolution, generally complex, but with a similar trend in the entire area. For each unit the litologic composition, evolution, boundaries and chronostratigraphy are established. The three first units are placed in the Palaeogene, the fourth one includes the Palaeogene-Neogene boundary and the four last ones are Neogene in age. The chronostratigraphic interval of each one is, respectively: Thanetian-Bartonian, Bartonian-Priabonian, Priabonian-Lower Oligocene, Upper Oligocene-Agenian, Agenim-Middle Aragonian, Middle Aragonim-Upper Aragonian, Upper Aragonian-Upper Vallesian, and Turolian. Finally the equivalences between the Tectosedimentary Units and the cartographic units defiiied by other authors have been establised

Engineering and harnessing giant atoms in high-dimensional baths: a cold atoms' implementation

Emitters coupled simultaneously to distant positions of a photonic bath, the so-called giant atoms, represent a new paradigm in quantum optics. When coupled to one-dimensional baths, as recently implemented with transmission lines or SAW waveguides, they lead to striking effects such as chiral emission or decoherence-free atomic interactions. Here, we show how to create giant atoms in dynamical state-dependent optical lattices, which offers the possibility of coupling them to structured baths in arbitrary dimensions. This opens up new avenues to a variety of phenomena and opportunities for quantum simulation. In particular, we show how to engineer unconventional radiation patterns, like multi-directional chiral emission, as well as collective interactions that can be used to simulate non-equilibrium many-body dynamics with no analogue in other setups. Besides, the recipes we provide to harness giant atoms in high dimensions can be exported to other platforms where such non-local couplings can be engineered.Comment: 9 pages, 5 figures. Title changed to accommodate to the new focus of the main text. Several typos correcte

Linking ecosystem health indicators and collaborative management: A systematic framework to evaluate ecological and social outcomes

Collaborative management has gained popularity across the United States as a means of addressing the sustainability of mixed-ownership landscapes and resolving persistent conflicts in public lands management. At the same time, it has generated skepticism because its ecological and social outcomes are seldom measured. Evaluating the success of collaborative efforts is difficult because frameworks to assess on-the-ground outcomes are poorly developed or altogether lacking. Ecosystem health indicators are valuable tools for evaluating site-specific outcomes of collaboration based on the effects of collaboration on ecological and socioeconomic conditions. We present the holistic ecosystem health indicator, a promising framework for evaluating the outcomes of collaborative processes, which uses ecological, social, and interactive indicators to monitor conditions through time. Finally, we draw upon our experience working with the Diablo Trust, a community-based collaborative group in northern Arizona, USA, to illustrate the development of an indicator selection model generated through a stakeholder-driven process