Enriching Knowledge Bases with Counting Quantifiers

Information extraction traditionally focuses on extracting relations between identifiable entities, such as . Yet, texts often also contain Counting information, stating that a subject is in a specific relation with a number of objects, without mentioning the objects themselves, for example, "California is divided into 58 counties". Such counting quantifiers can help in a variety of tasks such as query answering or knowledge base curation, but are neglected by prior work. This paper develops the first full-fledged system for extracting counting information from text, called CINEX. We employ distant supervision using fact counts from a knowledge base as training seeds, and develop novel techniques for dealing with several challenges: (i) non-maximal training seeds due to the incompleteness of knowledge bases, (ii) sparse and skewed observations in text sources, and (iii) high diversity of linguistic patterns. Experiments with five human-evaluated relations show that CINEX can achieve 60% average precision for extracting counting information. In a large-scale experiment, we demonstrate the potential for knowledge base enrichment by applying CINEX to 2,474 frequent relations in Wikidata. CINEX can assert the existence of 2.5M facts for 110 distinct relations, which is 28% more than the existing Wikidata facts for these relations.Comment: 16 pages, The 17th International Semantic Web Conference (ISWC 2018

Similarity-aware deep attentive model for clickbait detection

© Springer Nature Switzerland AG 2019. Clickbait is a type of web content advertisements designed to entice readers into clicking accompanying links. Usually, such links will lead to articles that are either misleading or non-informative, making the detection of clickbait essential for our daily lives. Automated clickbait detection is a relatively new research topic. Most recent work handles the clickbait detection problem with deep learning approaches to extract features from the meta-data of content. However, little attention has been paid to the relationship between the misleading titles and the target content, which we found to be an important clue for enhancing clickbait detection. In this work, we propose a deep similarity-aware attentive model to capture and represent such similarities with better expressiveness. In particular, we present the ways of either using similarity only or integrating it with other available quality features for the clickbait detection. We evaluate our model on two benchmark datasets, and the experimental results demonstrate the effectiveness of our approach by outperforming a series of competitive state-of-the-arts and baseline methods

A phase 1b study evaluating the safety and preliminary efficacy of berzosertib in combination with gemcitabine in patients with advanced non-small cell lung cancer

OBJECTIVES: Berzosertib (formerly M6620, VX-970) is an intravenous, highly potent and selective, first-in-class ataxia telangiectasia and Rad3-related (ATR) protein kinase inhibitor. We assessed the safety, tolerability, preliminary efficacy, and pharmacokinetics (PK) of berzosertib plus gemcitabine in an expansion cohort of patients with advanced non-small cell lung cancer (NSCLC). The association of efficacy with TP53 status and other tumor markers was also explored. MATERIALS AND METHODS: Adult patients with advanced histologically confirmed NSCLC received berzosertib 210 mg/m2 (days 2 and 9) and gemcitabine 1000 mg/m2 (days 1 and 8) at the recommended phase 2 dose established in the dose escalation part of the study. RESULTS: Thirty-eight patients received at least one dose of study treatment. The most common treatment-emergent adverse events were fatigue (55.3%), anemia (52.6%), and nausea (39.5%). Gemcitabine had no apparent effect on the PK of berzosertib. The objective response rate (ORR) was 10.5% (4/38, 90% confidence interval [CI]: 3.7–22.5%). In the exploratory analysis, the ORR was 30.0% (3/10, 90% CI: 9.0–61.0%) in patients with high loss of heterozygosity (LOH) and 11.0% (1/9, 90% CI: 1.0–43.0%) in patients with low LOH. The ORR was 33.0% (2/6, 90% CI: 6.0–73.0%) in patients with high tumor mutational burden (TMB), 12.5% (2/16, 90% CI: 2.0–34.0%) in patients with intermediate TMB, and 0% (0/3, 90% CI: 0.0–53.6%) in patients with low TMB. CONCLUSIONS: Berzosertib plus gemcitabine was well tolerated in patients with advanced, pre-treated NSCLC. Based on the observed clinical efficacy, future clinical trials should involve genomically selected patients

Feature fusion based deep spatiotemporal model for violence detection in videos

© Springer Nature Switzerland AG 2019. It is essential for public monitoring and security to detect violent behavior in surveillance videos. However, it requires constant human observation and attention, which is a challenging task. Autonomous detection of violent activities is essential for continuous, uninterrupted video surveillance systems. This paper proposed a novel method to detect violent activities in videos, using fused spatial feature maps, based on Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) units. The spatial features are extracted through CNN, and multi-level spatial features fusion method is used to combine the spatial features maps from two equally spaced sequential input video frames to incorporate motion characteristics. The additional residual layer blocks are used to further learn these fused spatial features to increase the classification accuracy of the network. The combined spatial features of input frames are then fed to LSTM units to learn the global temporal information. The output of this network classifies the violent or non-violent category present in the input video frame. Experimental results on three different standard benchmark datasets: Hockey Fight, Crowd Violence and BEHAVE show that the proposed algorithm provides better ability to recognize violent actions in different scenarios and results in improved performance compared to the state-of-the-art methods

Endothelial nitric oxide pathways in the pathophysiology of dengue: a prospective observational study.

Background: Dengue can cause increased vascular permeability that may lead to hypovolemic shock. Endothelial dysfunction may underlie this; however the association of endothelial nitric oxide pathways with disease severity is unknown. Methods: We performed a prospective observational study in two Vietnamese hospitals, assessing patients presenting early (<72 hours fever) and patients hospitalized with warning signs or severe dengue. The reactive hyperaemic index (RHI), which measures endothelium-dependent vasodilation and is a surrogate marker of endothelial function and NO bioavailability was evaluated using peripheral artery tonometry (EndoPAT) and plasma levels of L-arginine, Arginase-1 and ADMA were measured at serial time-points. The main outcome of interest was plasma leakage severity. Results: 314 patients were enrolled, median age of the participants was 21 (IQR 13-30) years. No difference was found in the endothelial parameters between dengue and other febrile illness (OFI). Considering dengue patients, the RHI was significantly lower for patients with severe plasma leakage compared to those with no leakage (1.46 vs. 2.00, P<0.001), over acute time-points, apparent already in the early febrile phase (1.29 vs. 1.75, P=0.012). RHI correlated negatively with arginase-1, and positively with L-arginine (P=0.001). Endothelial dysfunction/NO bioavailability is associated with worse plasma leakage, occurs early in dengue illness and correlates with hypoargininaemia and high arginase-1 levels

Modulating signaling networks by CRISPR/Cas9-mediated transposable element insertion

In a recent past, transposable elements (TEs) were referred to as selfish genetic components only capable of copying themselves with the aim of increasing the odds of being inherited. Nonetheless, TEs have been initially proposed as positive control elements acting in synergy with the host. Nowadays, it is well known that TE movement into host genome comprises an important evolutionary mechanism capable of increasing the adaptive fitness. As insights into TE functioning are increasing day to day, the manipulation of transposition has raised an interesting possibility of setting the host functions, although the lack of appropriate genome engineering tools has unpaved it. Fortunately, the emergence of genome editing technologies based on programmable nucleases, and especially the arrival of a multipurpose RNA-guided Cas9 endonuclease system, has made it possible to reconsider this challenge. For such purpose, a particular type of transposons referred to as miniature inverted-repeat transposable elements (MITEs) has shown a series of interesting characteristics for designing functional drivers. Here, recent insights into MITE elements and versatile RNA-guided CRISPR/Cas9 genome engineering system are given to understand how to deploy the potential of TEs for control of the host transcriptional activity.Fil: Vaschetto, Luis Maria Benjamin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Diversidad y Ecología Animal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto de Diversidad y Ecología Animal; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Cátedra de Diversidad Animal I; Argentin

Split-based computation of majority-rule supertrees

<p>Abstract</p> <p>Background</p> <p>Supertree methods combine overlapping input trees into a larger supertree. Here, I consider split-based supertree methods that first extract the split information of the input trees and subsequently combine this split information into a phylogeny. Well known split-based supertree methods are matrix representation with parsimony and matrix representation with compatibility. Combining input trees on the same taxon set, as in the consensus setting, is a well-studied task and it is thus desirable to generalize consensus methods to supertree methods.</p> <p>Results</p> <p>Here, three variants of majority-rule (MR) supertrees that generalize majority-rule consensus trees are investigated. I provide simple formulas for computing the respective score for bifurcating input- and supertrees. These score computations, together with a heuristic tree search minmizing the scores, were implemented in the python program PluMiST (Plus- and Minus SuperTrees) available from <url>http://www.cibiv.at/software/plumist</url>. The different MR methods were tested by simulation and on real data sets. The search heuristic was successful in combining compatible input trees. When combining incompatible input trees, especially one variant, MR(-) supertrees, performed well.</p> <p>Conclusions</p> <p>The presented framework allows for an efficient score computation of three majority-rule supertree variants and input trees. I combined the score computation with a heuristic search over the supertree space. The implementation was tested by simulation and on real data sets and showed promising results. Especially the MR(-) variant seems to be a reasonable score for supertree reconstruction. Generalizing these computations to multifurcating trees is an open problem, which may be tackled using this framework.</p

Expression of CD82 in Human Trophoblast and Its Role in Trophoblast Invasion

BACKGROUND: Well-controlled trophoblast invasion at maternal-fetal interface is a critical event for the normal development of placenta. CD82 is a member of transmembrane 4 superfamily, which showed important role in inhibiting tumor cell invasion and migration. We surmised that CD82 are participates in trophoblast differentiation during placenta development. METHODOLOGY/PRINCIPAL FINDINGS: CD82 was found to be strongly expressed in human first trimester placental villous and extravillous trophoblast cells as well as in trophoblast cell lines. To investigate whether CD82 plays a role in trophoblast invasion and migration, we further utilized human villous explants culture model on matrigel and invasion/migration assay of trophoblast cell line HTR8/SVneo. CD82 siRNA significantly promoted outgrowth of villous explants in vitro (P<0.01), as well as invasion and migration of HTR8/SVneo cells (P<0.05), whereas the trophoblast proliferation was not affected. The enhanced effect of CD82 siRNA on invasion and migration of trophoblast cells was found associated with increased gelatinolytic activities of matrix metalloproteinase MMP9 while over-expression of CD82 markedly decreased trphoblast cell invasion and migration as well as MMP9 activities. CONCLUSIONS/SIGNIFICANCE: These findings suggest that CD82 is an important negative regulator at maternal-fetal interface during early pregnancy, inhibiting human trophoblast invasion and migration