Comparing knowledge sources for nominal anaphora resolution

We compare two ways of obtaining lexical knowledge for antecedent selection in other-anaphora and definite noun phrase coreference. Specifically, we compare an algorithm that relies on links encoded in the manually created lexical hierarchy WordNet and an algorithm that mines corpora by means of shallow lexico-semantic patterns. As corpora we use the British National Corpus (BNC), as well as the Web, which has not been previously used for this task. Our results show that (a) the knowledge encoded in WordNet is often insufficient, especially for anaphor-antecedent relations that exploit subjective or context-dependent knowledge; (b) for other-anaphora, the Web-based method outperforms the WordNet-based method; (c) for definite NP coreference, the Web-based method yields results comparable to those obtained using WordNet over the whole dataset and outperforms the WordNet-based method on subsets of the dataset; (d) in both case studies, the BNC-based method is worse than the other methods because of data sparseness. Thus, in our studies, the Web-based method alleviated the lexical knowledge gap often encountered in anaphora resolution, and handled examples with context-dependent relations between anaphor and antecedent. Because it is inexpensive and needs no hand-modelling of lexical knowledge, it is a promising knowledge source to integrate in anaphora resolution systems

Lambda(1520) production in d+Au collisions at RHIC

Recent results of $\Lambda$(1520) resonance production in d+Au collisions at $\sqrt{s_{\rm NN}} =$ 200 GeV are presented and discussed in terms of the evolution and freeze-out conditions of a hot and dense fireball medium. Yields and spectra are compared to results from p+p and Au+Au collisions. The $\Lambda$(1520)/$\Lambda$ ratio in d+Au collisions ratio is consistent with the ratio in p+p collisions. This suggests a short time for elastic interactions between chemical and thermal freeze-out. One can conclude that the interaction volume in d+Au collisions is small.Comment: 4 Pages, 3 figures, conference proceedings Quark Matter 200

Serine biosynthesis with one carbon catabolism represents a novel pathway for ATP generation in cells using alternative glycolysis with zero net ATP production

Recent experimental evidence indicates that some cancer cells have an alternative glycolysis pathway with net zero ATP production, implying that upregulation of glycolysis in these cells may not be related to the generation of ATP. Here we use a genome-scale model of human cell metabolism to investigate the potential metabolic alterations in cells using net zero ATP glycolysis. We uncover a novel pathway for ATP generation that involves reactions from the serine biosynthesis and one-carbon metabolism pathways. This pathway has a predicted two-fold higher flux rate in cells using net zero ATP glycolysis than those using standard glycolysis and generates twice as much ATP with significantly lower rate of lactate- but higher rate of alanine secretion. Thus, in cells using the standard- or the net zero ATP glycolysis pathways a significant portion of the glycolysis flux is always associated with ATP generation, and the ratio between the flux rates of the two pathways determines the rate of ATP generation and lactate and alanine secretion during glycolysis

Resonance production from jet fragmentation

Short lived resonances are sensitive to the medium properties in heavy-ion collisions. Heavy hadrons have larger probability to be produced within the quark gluon plasma phase due to their short formation times. Therefore heavy mass resonances are more likely to be affected by the medium, and the identification of early produced resonances from jet fragmentation might be a viable option to study chirality. The high momentum resonances on the away-side of a triggered di-jet are likely to be the most modified by the partonic or early hadronic medium. We will discuss first results of triggered hadron-resonance correlations in Cu+Cu heavy ion collisions.Comment: Hot Quarks Colorado 2008 Proceedings, 4 pages 5 figure

Demonstration of Self-Updating Landslide Hazard Maps with Dynamic Crowd-Sourced Data in Rwanda

No abstract availabl

Automatic Extraction of News Values from Headline Text

Headlines play a crucial role in attracting audiences’ attention to online artefacts (e.g. news articles, videos, blogs). The ability to carry out an automatic, largescale analysis of headlines is critical to facilitate the selection and prioritisation of a large volume of digital content. In journalism studies news content has been extensively studied using manually annotated news values – factors used implicitly and explicitly when making decisions on the selection and prioritisation of news items. This paper presents the first attempt at a fully automatic extraction of news values from headline text. The news values extraction methods are applied on a large headlines corpus collected from The Guardian, and evaluated by comparing it with a manually annotated gold standard. A crowdsourcing survey indicates that news values affect people’s decisions to click on a headline, supporting the need for an automatic news values detection

Cancer metabolism at a glance

A defining hallmark of cancer is uncontrolled cell proliferation. This is initiated once cells have accumulated alterations in signaling pathways that control metabolism and proliferation, wherein the metabolic alterations provide the energetic and anabolic demands of enhanced cell proliferation. How these metabolic requirements are satisfied depends, in part, on the tumor microenvironment, which determines the availability of nutrients and oxygen. In this Cell Science at a Glance paper and the accompanying poster, we summarize our current understanding of cancer metabolism, emphasizing pathways of nutrient utilization and metabolism that either appear or have been proven essential for cancer cells. We also review how this knowledge has contributed to the development of anticancer therapies that target cancer metabolism

Crowdsourcing for web genre annotation

Recently, genre collection and automatic genre identification for the web has attracted much attention. However, currently there is no genre-annotated corpus of web pages where inter-annotator reliability has been established, i.e. the corpora are either not tested for inter-annotator reliability or exhibit low inter-coder agreement. Annotation has also mostly been carried out by a small number of experts, leading to concerns with regard to scalability of these annotation efforts and transferability of the schemes to annotators outside these small expert groups. In this paper, we tackle these problems by using crowd-sourcing for genre annotation, leading to the Leeds Web Genre Corpus—the first web corpus which is, demonstrably reliably annotated for genre and which can be easily and cost-effectively expanded using naive annotators. We also show that the corpus is source and topic diverse

Headlines data for social media popularity prediction

This dataset is part of a larger project on using headlines to predict the social media popularity of news articles. The dataset consists of two headlines corpora -- The Guardian and New York Times -- collected in 2014 using news outlet APIs. Each corpus includes a unique headline identifier (to enable recreating the corpus by querying the relevant API), the extracted features (news values, style, metadata), and the corresponding popularity on Twitter and Facebook