Por qué no les calan? Hugo Chávez’s Re-election in Venezuela and the Decline of Western Hegemony in the Americas

On October 7, 2012, Hugo Chávez was comfortably re-elected president of Venezuela. Just days before the vote the impression given by major international print media was that the vote was a close-run thing, an assessment which proved to be at best optimistic. We argue that Western media coverage of the election in Venezuela was designed to skew the result towards the opposition and that these efforts singularly failed. The conclusions of our analysis are, first, that the “propaganda” model advanced by Chomsky is now faltering in the Americas and, second, that the region is acting in manner that is increasingly free of influence from the US. Venezuela thus stands as a case of the citizenry of a country actively and independently asserting its political agency despite clear attempts to redirect its thinking and decision-making

Anomalous Neutrino Reactions at HERA

We study the sensitivity of HERA to new physics using the helicity suppressed reaction $e_R p \rightarrow \nu X$, where the final neutrino can be a standard model one or a heavy neutrino. The approach is model independent and is based on an effective lagrangian parametrization. It is shown that HERA will put significant bounds on the scale of new physics, though, in general, these are more modest than previously thought. If deviations from the standard model are observed in the above processes, future colliders such as the SSC and LHC will be able to directly probe the physics responsible for these discrepancies}Comment: 11 Pages + 2 figures is TOPDRAWER (included at the end or available by mail). Report UCRHEP-T113 (requires the macropackage PHYZZX). A line in the TeX file requesting an input file has been removed, it caused problem

Aharonov-Bohm Effect and Disclinations in an Elastic Medium

In this work we investigate quasiparticles in the background of defects in solids using the geometric theory of defects. We use the parallel transport matrix to study the Aharonov-Bohm effect in this background. For quasiparticles moving in this effective medium we demonstrate an effect similar to the gravitational Aharonov- Bohm effect. We analyze this effect in an elastic medium with one and $N$ defects.Comment: 6 pages, Revtex

Situationally-sensitive knowledge translation and relational decision making in hyperacute stroke: a qualitive study

Stroke is a leading cause of disability. Early treatment of acute ischaemic stroke with rtPA reduces the risk of longer term dependency but carries an increased risk of causing immediate bleeding complications. To understand the challenges of knowledge translation and decision making about treatment with rtPA in hyperacute stroke and hence to inform development of appropriate decision support we interviewed patients, their family and health professionals. The emergency setting and the symptomatic effects of hyper-acute stroke shaped the form, content and manner of knowledge translation to support decision making. Decision making about rtPA in hyperacute stroke presented three conundrums for patients, family and clinicians. 1) How to allow time for reflection in a severely time-limited setting. 2) How to facilitate knowledge translation regarding important treatment risks and benefits when patient and family capacity is blunted by the effects and shock of stroke. 3) How to ensure patient and family views are taken into account when the situation produces reliance on the expertise of clinicians. Strategies adopted to meet these conundrums were fourfold: face to face communication; shaping decisions; incremental provision of information; and communication tailored to the individual patient. Relational forms of interaction were understood to engender trust and allay anxiety. Shaping decisions with patients was understood as an expression of confidence by clinicians that helped alleviate anxiety and offered hope and reassurance to patients and their family experiencing the shock of the stroke event. Neutral presentations of information and treatment options promoted uncertainty and contributed to anxiety. ‘Drip feeding’ information created moments for reflection: clinicians literally made time. Tailoring information to the particular patient and family situation allowed clinicians to account for social and emotional contexts. The principal responses to the challenges of decision making about rtPA in hyperacute stroke were relational decision support and situationally-sensitive knowledge translation

Tornado Detection with Support Vector Machines

Abstract. The National Weather Service (NWS) Mesocyclone Detec-tion Algorithms (MDA) use empirical rules to process velocity data from the Weather Surveillance Radar 1988 Doppler (WSR-88D). In this study Support Vector Machines (SVM) are applied to mesocyclone detection. Comparison with other classification methods like neural networks and radial basis function networks show that SVM are more effective in meso-cyclone/tornado detection.

Bounds on the electromagnetic interactions of excited spin-3/2 leptons

We discuss possible deviations from QED produced by a virtual excited spin-3/2 lepton in the reaction $e^+e^- \longrightarrow 2\gamma$. Data recorded by the OPAL Collaboration at a c.m. energy $\sqrt{s} = 183 GeV$ are used to establish bounds on the nonstandard-lepton mass and coupling strengths.Comment: Latex, 5 pages, 7 ps figures. To be published in Phys. Rev.

Finding rare objects and building pure samples: Probabilistic quasar classification from low resolution Gaia spectra

We develop and demonstrate a probabilistic method for classifying rare objects in surveys with the particular goal of building very pure samples. It works by modifying the output probabilities from a classifier so as to accommodate our expectation (priors) concerning the relative frequencies of different classes of objects. We demonstrate our method using the Discrete Source Classifier, a supervised classifier currently based on Support Vector Machines, which we are developing in preparation for the Gaia data analysis. DSC classifies objects using their very low resolution optical spectra. We look in detail at the problem of quasar classification, because identification of a pure quasar sample is necessary to define the Gaia astrometric reference frame. By varying a posterior probability threshold in DSC we can trade off sample completeness and contamination. We show, using our simulated data, that it is possible to achieve a pure sample of quasars (upper limit on contamination of 1 in 40,000) with a completeness of 65% at magnitudes of G=18.5, and 50% at G=20.0, even when quasars have a frequency of only 1 in every 2000 objects. The star sample completeness is simultaneously 99% with a contamination of 0.7%. Including parallax and proper motion in the classifier barely changes the results. We further show that not accounting for class priors in the target population leads to serious misclassifications and poor predictions for sample completeness and contamination. (Truncated)Comment: MNRAS accepte

Four-Fermi Effective Operators in Top-Quark Production and Decay

Effects of four-Fermi-type new interactions are studied in top-quark pair production and their subsequent decays at future e^+e^- colliders. Secondary-lepton-energy distributions are calculated for arbitrary longitudinal beam polarizations. An optimal-observables procedure is applied for the determination of new parameters.Comment: Polarized e^- plus unpolarized e^+ collisions were include

Hybrid MM/SVM structural sensors for stochastic sequential data

In this paper we present preliminary results stemming from a novel application of Markov Models and Support Vector Machines to splice site classification of Intron-Exon and Exon-Intron (5' and 3') splice sites. We present the use of Markov based statistical methods, in a log likelihood discriminator framework, to create a non-summed, fixed-length, feature vector for SVM-based classification. We also explore the use of Shannon-entropy based analysis for automated identification of minimal-size models (where smaller models have known information loss according to the specified Shannon entropy representation). We evaluate a variety of kernels and kernel parameters in the classification effort. We present results of the algorithms for splice-site datasets consisting of sequences from a variety of species for comparison

Robust ASR using Support Vector Machines

The improved theoretical properties of Support Vector Machines with respect to other machine learning alternatives due to their max-margin training paradigm have led us to suggest them as a good technique for robust speech recognition. However, important shortcomings have had to be circumvented, the most important being the normalisation of the time duration of different realisations of the acoustic speech units. In this paper, we have compared two approaches in noisy environments: first, a hybrid HMM–SVM solution where a fixed number of frames is selected by means of an HMM segmentation and second, a normalisation kernel called Dynamic Time Alignment Kernel (DTAK) first introduced in Shimodaira et al. [Shimodaira, H., Noma, K., Nakai, M., Sagayama, S., 2001. Support vector machine with dynamic time-alignment kernel for speech recognition. In: Proc. Eurospeech, Aalborg, Denmark, pp. 1841–1844] and based on DTW (Dynamic Time Warping). Special attention has been paid to the adaptation of both alternatives to noisy environments, comparing two types of parameterisations and performing suitable feature normalisation operations. The results show that the DTA Kernel provides important advantages over the baseline HMM system in medium to bad noise conditions, also outperforming the results of the hybrid system.Publicad