Chiral Bosons as solutions of the BV master equation 2D chiral gauge theories

We construct the chiral Wess-Zumino term as a solution for the Batalin-Vilkovisky master equation for anomalous two-dimensional gauge theories, working in an extended field-antifield space, where the gauge group elements are introduced as additional degrees of freedom. We analyze the Abelian and the non-Abelian cases, calculating in both cases the BRST generator in order to show the physical equivalence between this chiral solution for the master equation and the usual (non-chiral) one.Comment: 11 pages, TEX dialet, IF/UFRJ-94-

Smuggler's Blues at the Central Bank: Lessons from Sudan

The ineffectiveness of real devaluation as stabilization policy does not imply that the nominal exchange rate should be held constant in the face of a domestic inflation. In this circumstance, import duties and export subsidies would have to be escalated to counter the potential erosion of the trade balance. This escalation of trade barriers generates a rising black market premium and offers increasing incentives to smuggling, already a pervasive problem in the African countries. As a consequence, the central bank would find it more and more difficult to hold the nominal exchange rate constant. This leads us to consider a passive exchange rate policy of stabilizing the exchange rate by moving the nominal rate in line with domestic inflation. If such passive policy is not accompanied by the elimination of trade barriers, however, the black market premium will not disappear. Unless exchange rate policy and trade policy are consistent with each other, the smuggler's blues will reach the central bank. Indeed, this is not just a theoretical possibility, it is the major lesson from the recent experience of Sudan.

Axial Anomaly from the BPHZ regularized BV master equation

A BPHZ renormalized form for the master equation of the field antifiled (or BV) quantization has recently been proposed by De Jonghe, Paris and Troost. This framework was shown to be very powerful in calculating gauge anomalies. We show here that this equation can also be applied in order to calculate a global anomaly (anomalous divergence of a classically conserved Noether current), considering the case of QED. This way, the fundamental result about the anomalous contribution to the Axial Ward identity in standard QED (where there is no gauge anomaly) is reproduced in this BPHZ regularized BV framework.Comment: 10 pages, Latex, minor changes in the reference

Vector meson quasinormal modes in a finite-temperature AdS/QCD model

We study the spectrum of vector mesons in a finite temperature plasma. The plasma is holographically described by a black hole AdS/QCD model. We compute the boundary retarded Green's function using AdS/CFT prescriptions. The corresponding thermal spectral functions show quasiparticle peaks at low temperatures. Then we calculate the quasinormal modes of vector mesons in the soft-wall black hole geometry and analyse their temperature and momentum dependences.Comment: 27 pages, 9 figure

Early Identification of Violent Criminal Gang Members

Gang violence is a major problem in the United States accounting for a large fraction of homicides and other violent crime. In this paper, we study the problem of early identification of violent gang members. Our approach relies on modified centrality measures that take into account additional data of the individuals in the social network of co-arrestees which together with other arrest metadata provide a rich set of features for a classification algorithm. We show our approach obtains high precision and recall (0.89 and 0.78 respectively) in the case where the entire network is known and out-performs current approaches used by law-enforcement to the problem in the case where the network is discovered overtime by virtue of new arrests - mimicking real-world law-enforcement operations. Operational issues are also discussed as we are preparing to leverage this method in an operational environment.Comment: SIGKDD 201

A Semi-Supervised Self-Organizing Map for Clustering and Classification

There has been an increasing interest in semi-supervised learning in the recent years because of the great number of datasets with a large number of unlabeled data but only a few labeled samples. Semi-supervised learning algorithms can work with both types of data, combining them to obtain better performance for both clustering and classification. Also, these datasets commonly have a high number of dimensions. This article presents a new semi-supervised method based on self-organizing maps (SOMs) for clustering and classification, called Semi-Supervised Self-Organizing Map (SS-SOM). The method can dynamically switch between supervised and unsupervised learning during the training according to the availability of the class labels for each pattern. Our results show that the SS-SOM outperforms other semi-supervised methods in conditions in which there is a low amount of labeled samples, also achieving good results when all samples are labeled