Review of Recent Tevatron Jet, W/Z+Jet and Heavy-flavor Production Results

This document reviews several recent measurements at the Fermilab Tevatron, including the cross sections of inclusive jet, dijet production, the cross sections of electroweak boson (W or Z) production in association with inclusive or heavy-flavor (b or c) jets, and b-jet shapes. In addition, searches for new physics using the dijet angular distributions are discussed. These analyses are based on integrated luminosities of 0.3--2.5/fb of p-pbar collisions at \sqrt{s}=1.96 TeV, collected with the CDF and D0 detectors. The results directly test the leading order and next-to leading order calculations of perturbative quantum chromodynamics and provide constraints on the parton distribution functions, gluon-splitting contribution, and physics beyond the standard model.Comment: 10 pages, 7 figures, Proceedings for Photon 200

Market Shares, Consumer Ignorance and the Reciprocal Termination Charges

The aim of this paper is to study different regulatory effects on termination charges and social welfare. We employ a framework with a fixed network and two mobile networks competing in a market to study the following regulatory regimes: collusive and social welfaremaximising reciprocity, uniform termination charge, asymmetric regulation, and direct calling price. We incorporate the idea of partial consumer ignorance when calling to a mobile user and allow the network operator to discriminate between on-net and off-net calls by setting differential calling prices. Compared to the uniform termination charge and asymmetric regulation, it is shown in this paper that the regulator can improve social welfare, without too much intervention, by imposing reciprocity on termination charges. We also find that with stronger consumer ignorance the regulator is more capable of improving social welfare. Further we show that, depending upon the extent of consumer ignorance, direct regulation of calling prices may be a welfare-improving alternative over regulation of termination charges.Telecommunications; Consumer ignorance; Termination Charges, Regulation

Multi-turn Inference Matching Network for Natural Language Inference

Natural Language Inference (NLI) is a fundamental and challenging task in Natural Language Processing (NLP). Most existing methods only apply one-pass inference process on a mixed matching feature, which is a concatenation of different matching features between a premise and a hypothesis. In this paper, we propose a new model called Multi-turn Inference Matching Network (MIMN) to perform multi-turn inference on different matching features. In each turn, the model focuses on one particular matching feature instead of the mixed matching feature. To enhance the interaction between different matching features, a memory component is employed to store the history inference information. The inference of each turn is performed on the current matching feature and the memory. We conduct experiments on three different NLI datasets. The experimental results show that our model outperforms or achieves the state-of-the-art performance on all the three datasets