Generic dialogue modeling for multi-application dialogue systems

We present a novel approach to developing interfaces for multi-application dialogue systems. The targeted interfaces allow transparent switching between a large number of applications within one system. The approach, based on the Rapid Dialogue Prototyping Methodology (RDPM) and the Vector Space model techniques from Information Retrieval, is composed of three main steps: (1) producing finalized dia logue models for applications using the RDPM, (2) designing an application interaction hierarchy, and (3) navigating between the applications based on the user's application of interest

Extracting collective trends from Twitter using social-based data mining

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-40495-5_62Proceedings 5th International Conference, ICCCI 2013, Craiova, Romania, September 11-13, 2013,Social Networks have become an important environment for Collective Trends extraction. The interactions amongst users provide information of their preferences and relationships. This information can be used to measure the influence of ideas, or opinions, and how they are spread within the Network. Currently, one of the most relevant and popular Social Network is Twitter. This Social Network was created to share comments and opinions. The information provided by users is specially useful in different fields and research areas such as marketing. This data is presented as short text strings containing different ideas expressed by real people. With this representation, different Data Mining and Text Mining techniques (such as classification and clustering) might be used for knowledge extraction trying to distinguish the meaning of the opinions. This work is focused on the analysis about how these techniques can interpret these opinions within the Social Network using information related to IKEA® company.The preparation of this manuscript has been supported by the Spanish Ministry of Science and Innovation under the following projects: TIN2010-19872, ECO2011-30105 (National Plan for Research, Development and Innovation) and the Multidisciplinary Project of Universidad Aut´onoma de Madrid (CEMU-2012-034

Single-tube multiplex-PCR screen for common deletional determinants of α-thalassemia

Blood951360-362BLOO

Simplified multiplex-PCR diagnosis of common Southeast Asian deletional determinants of α-Thalassemia

Clinical Chemistry46101692-1695CLCH

Autonomous and non-autonomous regulation of mammalian neurite development by Notch1 and Delta1

AbstractBackground: On the basis of experiments suggesting that Notch and Delta have a role in axonal development in Drosophila neurons, we studied the ability of components of the Notch signaling pathway to modulate neurite formation in mammalian neuroblastoma cells in vitro.Results: We observed that N2a neuroblastoma cells expressing an activated form of Notch, Notch1IC, produced shorter neurites compared with controls, whereas N2a cell lines expressing a dominant-negative Notch1 or a dominant-negative Delta1 construct extended longer neurites with a greater number of primary neurites. We then compared the effects on neurites of contacting Delta1 on another cell and of overexpression of Delta1 in the neurite-extending cell itself. We found that N2a cells co-cultured with Delta1-expressing quail cells produced fewer and shorter neuritic processes. On the other hand, high levels of Delta1 expressed in the N2a cells themselves stimulated neurite extension, increased numbers of primary neurites and induced expression of Jagged1 and Notch1.Conclusions:These studies show that Notch signals can antagonize neurite outgrowth and that repressing endogenous Notch signals enhances neurite outgrowth in neuroblastoma cells. Notch signals therefore act as regulators of neuritic extension in neuroblastoma cells. The response of neuritic processes to Delta1 expressed in the neurite was opposite to that to Delta1 contacted on another cell, however. These results suggest a model in which developing neurons determine their extent of process outgrowth on the basis of the opposing influences on Notch signals of ligands contacted on another cell and ligands expressed in the same cell

Text Document Topical Recursive Clustering and Automatic Labeling of a Hierarchy of Document Clusters

Abstract. The overwhelming amount of textual documents available nowadays highlights the need for information organization and discovery. Effectively organizing documents into a hierarchy of topics and subtopics makes it easier for users to browse the documents. This paper borrows community mining from social network analysis to generate a hierarchy of topically coherent document clusters. It focuses on giving the document clusters descriptive labels. We propose to use betweenness centrality measure in networks of co-occurring terms to label the clusters. We also incorporate keyphrase extraction and automatic titling in cluster labeling. The results show that the cluster labeling method utilizing KEA to extract keyphrases from the documents generates the best labels overall comparing to other methods and baselines

Evaluation of Text Clustering Algorithms with N-Gram-Based Document Fingerprints

Abstract. This paper presents a new approach designed to reduce the computational load of the existing clustering algorithms by trimming down the documents size using fingerprinting methods. Thorough evaluation was performed over three different collections and considering four different metrics. The presented approach to document clustering achieved good values of effectiveness with considerable save in memory space and computation time.

Genetic heterogeneity of HIV type 1 subtypes in Kimpese, rural democratic republic of congo

A relatively low and stable seroprevalence of HIV-1 was previously reported among pregnant women attending for antenatal care between 1988 and 1993 in Kimpese, a rural town in the Democratic Republic of Congo (DRC, formerly Zaire). To characterize the HIV-1 subtypes circulating in this area, we have examined a 330-bp fragment of the p17 region of the gag gene of HIV- 1 strains obtained from 70 patients (55 mothers, 15 children), of whom 61 were epidemiologically unlinked. Phylogenetic analyses revealed the existence of at least seven HIV-1 subtypes within the Kimpese region. Among the 61 epidemiologically unlinked patients, subtype A was predominant and found in 29 (47.5%) individuals. Other subtypes cocirculating in this rural part of DRC include subtypes C (1.6%), D (9.8%), F (3.2%), G (6.5%), H (21.3%), and J (4.9%). Sequences from four patients did not cluster with any of the currently documented HIV-1 subtypes, in analyses of fragments of both the gag (247 to 330 bp, 197 bp, and 310 bp) and env (340 bp) genes. Overall, comparisons of the gag(p17) gene regions revealed high pairwise divergences (mean, 19.9%; range, 1 to 46%). This level of gag(p17) gene variation in the DRC is considerably greater than previously appreciated. These results are relevant for the molecular epidemiology of HIV-1 in Africa and for the design of a future vaccine against HIV1 in this region