Towards Deep Semantic Analysis Of Hashtags

Hashtags are semantico-syntactic constructs used across various social networking and microblogging platforms to enable users to start a topic specific discussion or classify a post into a desired category. Segmenting and linking the entities present within the hashtags could therefore help in better understanding and extraction of information shared across the social media. However, due to lack of space delimiters in the hashtags (e.g #nsavssnowden), the segmentation of hashtags into constituent entities ("NSA" and "Edward Snowden" in this case) is not a trivial task. Most of the current state-of-the-art social media analytics systems like Sentiment Analysis and Entity Linking tend to either ignore hashtags, or treat them as a single word. In this paper, we present a context aware approach to segment and link entities in the hashtags to a knowledge base (KB) entry, based on the context within the tweet. Our approach segments and links the entities in hashtags such that the coherence between hashtag semantics and the tweet is maximized. To the best of our knowledge, no existing study addresses the issue of linking entities in hashtags for extracting semantic information. We evaluate our method on two different datasets, and demonstrate the effectiveness of our technique in improving the overall entity linking in tweets via additional semantic information provided by segmenting and linking entities in a hashtag.Comment: To Appear in 37th European Conference on Information Retrieva

ATLAS Sensitivity to Leptoquarks, W_R and Heavy Majorana Neutrinos in Final States with High-pt Dileptons and Jets with Early LHC Data at 14 TeV proton-proton collisions

Dilepton-jet final states are used to study physical phenomena not predicted by the standard model. The ATLAS discovery potential for leptoquarks and Majorana Neutrinos is presented using a full simulation of the ATLAS detector at the Large Hadron Collider. The study is motivated by the role of the leptoquark in the Grand Unification of fundamental forces and the see-saw mechanism that could explain the masses of the observed neutrinos. The analysis algorithms are presented, background sources are discussed and estimates of sensitivity and the discovery potential for these processes are reported.Comment: 6 pages, 16 figures, To be published in the proceedings of DPF-2009, Detroit, MI, July 2009, eConf C09072

Philip Morris USA v. Williams: A Confusing Distinction

In Philip Morris USA v. Williams, the United States Supreme Court held 5-4 that it is unconstitutional under the Due Process Clause of the Constitution for a jury to award punitive damages for harm caused to individuals other than the plaintiff. Thus, the Court concluded that, under the Constitution, a trial court could not levy punitive damages out of a desire to punish a company for injuries it inflicts upon others who are essentially, strangers to the litigation. However, the Court confusingly drew a narrow and arguably contradictory distinction to justify its holding. Under Philip Morris USA, a jury may not use punitive damages to punish a defendant directly on account of harms it is alleged to have visited on nonparties, but a jury is still permitted to consider the harm to third parties to determine the reprehensibility of the defendant\u27s conduct, one of the three factors in assessing the constitutionality of punitive damages. Justice Ginsburg in her dissent wrote that the distinction slips from my grasp

A computational method for estimating the PCR duplication rate in DNA and RNA-seq experiments.

BackgroundPCR amplification is an important step in the preparation of DNA sequencing libraries prior to high-throughput sequencing. PCR amplification introduces redundant reads in the sequence data and estimating the PCR duplication rate is important to assess the frequency of such reads. Existing computational methods do not distinguish PCR duplicates from "natural" read duplicates that represent independent DNA fragments and therefore, over-estimate the PCR duplication rate for DNA-seq and RNA-seq experiments.ResultsIn this paper, we present a computational method to estimate the average PCR duplication rate of high-throughput sequence datasets that accounts for natural read duplicates by leveraging heterozygous variants in an individual genome. Analysis of simulated data and exome sequence data from the 1000 Genomes project demonstrated that our method can accurately estimate the PCR duplication rate on paired-end as well as single-end read datasets which contain a high proportion of natural read duplicates. Further, analysis of exome datasets prepared using the Nextera library preparation method indicated that 45-50% of read duplicates correspond to natural read duplicates likely due to fragmentation bias. Finally, analysis of RNA-seq datasets from individuals in the 1000 Genomes project demonstrated that 70-95% of read duplicates observed in such datasets correspond to natural duplicates sampled from genes with high expression and identified outlier samples with a 2-fold greater PCR duplication rate than other samples.ConclusionsThe method described here is a useful tool for estimating the PCR duplication rate of high-throughput sequence datasets and for assessing the fraction of read duplicates that correspond to natural read duplicates. An implementation of the method is available at https://github.com/vibansal/PCRduplicates

Sum rules for isospin centroids in pick-up reactions on general multishell target states

Sum Rules equations for pick-up reactions are presented for the first time for the energy centroids of states both for the isospin T_< (\equiv T_0 - 1 \over 2) and T_> (\equiv T_0 + {1 \over 2}) of the final nucleus when a nucleon is picked up from a general multishell target state with isospin T_0. These equations contain two-body correlation terms, , which, at the present moment, are difficult to handle analytically. These terms are managed by combining these equations with the known stripping reactions equations. Sample applications of these equations to experimental data are presented.Comment: 11 pages, LaTe