465,657 research outputs found

    Video Conferencing Tool

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    Video Conferencing Tool (VCT) is a web-based video chat application that allows users anywhere in the world to join real-time streaming video chat rooms. This product is similar to social networking sites that allow web-based video conferencing. The main advantage of VCT compared to existing tools is that it is easy to use and does not require users to download and set up additional hardware. Since this product is a browser-based solution, it allows users from multiple platforms like Windows, Linux, or Mac to join a chat room. My VCT allows users to create new public or private chat rooms or enter into existing chat rooms with the click of a button. VCT allows users to share their live audio and video to all users in the chat room. It also allows users to see the list of attendees in the chat room. VCT users can invite their friends to join video chat rooms by sending a link to their email. Friends can click the link and directly enter chat room without creating an account in VCT. The users also have the option of sending video messages to other users. Adobe Flash Media Server is used as the back end for developing this web site

    Cell type-specific regulation of choline acetyltransferase gene expression - Role of the neuron-restrictive silencer element and cholinergic-specific enhancer

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    This study demonstrates the presence of positive and negative regulatory elements within a 2336-base pair-long region of the rat choline acetyltransferase (ChAT) gene promoter that cooperate to direct cell type-specific expression in cholinergic cells. A 21-base pair-long neuron-restrictive silencer element (NRSE) was identified in the proximal part of this region. This element was recognized by the neuron-restrictive silencer factor (NRSF), previously shown to regulate expression of other neuron-specific genes. The ChAT NRSE was inactive in both cholinergic and non-cholinergic neuronal cells, but repressed expression from a heterologous promoter in non-neuronal cells. Specific deletion of this element allowed ChAT gene promoter activity in non-neuronal cells, and overexpression of NRSF repressed ChAT gene promoter activity in cholinergic cells. The distal part of the ChAT gene promoter showed cholinergic-specific enhancing activity, which stimulated promoter activity in cholinergic cells, but was inactive in non-cholinergic neuronal and non-neuronal cells. This enhancer region suppressed the activity of the ChAT NRSE in cholinergic cells, even after NRSF overexpression. Thus, at least two kinds of regulatory elements cooperate to direct ChAT gene expression to cholinergic neurons, namely a neuron-restrictive silencer element and a cholinergic-specific enhancer

    Rationale in Development Chat Messages: An Exploratory Study

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    Chat messages of development teams play an increasingly significant role in software development, having replaced emails in some cases. Chat messages contain information about discussed issues, considered alternatives and argumentation leading to the decisions made during software development. These elements, defined as rationale, are invaluable during software evolution for documenting and reusing development knowledge. Rationale is also essential for coping with changes and for effective maintenance of the software system. However, exploiting the rationale hidden in the chat messages is challenging due to the high volume of unstructured messages covering a wide range of topics. This work presents the results of an exploratory study examining the frequency of rationale in chat messages, the completeness of the available rationale and the potential of automatic techniques for rationale extraction. For this purpose, we apply content analysis and machine learning techniques on more than 8,700 chat messages from three software development projects. Our results show that chat messages are a rich source of rationale and that machine learning is a promising technique for detecting rationale and identifying different rationale elements.Comment: 11 pages, 6 figures. The 14th International Conference on Mining Software Repositories (MSR'17

    The Q-CHAT (Quantitative CHecklist for Autism in Toddlers): A Normally Distributed Quantitative Measure of Autistic Traits at 18‚Äď24 Months of Age: Preliminary Report

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    We report a major revision of the CHecklist for Autism in Toddlers (CHAT). This quantitative CHAT (Q-CHAT) contains 25 items, scored on a 5 point scale (0-4). The QCHAT was completed by parents of n = 779 unselected toddlers (mean age 21 months) and n = 160 toddlers and preschoolers (mean age 44 months) with an Autism Spectrum Condition (ASC). The ASC group (mean (SD) = 51.8 (14.3)) scored higher on the QCHAT than controls (26.7 (7.8)). Boys in the control group (27.5 (7.8)) scored higher than girls (25.8 (7.7)). The intraclass correlation for test-retest reliability was 0.82 (n=330). The distribution in the control group was close to normal. Full examination of the clinical validity of the Q-CHAT and test properties is underway

    Working with the CHILDES tools : transcription, coding and analysis

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    The Child Language Data Exchange System (CHILDES) consists of Codes for the Human Analysis of Transcripts (CHAT), Computerized Language Analysis (CLAN), and a database. There is also an online manual which includes the CHILDES bibliography, the database, and the CHAT conventions as well as the CLAN instructions. The first three parts of this paper concern the CHAT format of transcription, grammatical coding, and analyzing transcripts by using the CLAN programs. The fourth part shows examples of transcribed and coded data

    The CHAT Dataset

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    This note accompanies the Cross?country Historical Adoption of Technology (CHAT) dataset. CHAT is an unbalanced panel dataset with information on the adoption of over 100 technologies in more than 150 countries since 1800. The data is available for download at: http://www.nber.org/data/chat. We discuss the main aim of CHAT, its scope and limitations, as well as several ways in which we have used the data so far and ways to potentially use the data for other research. Suggested acknowledgment: If you use the CHAT dataset for your research, please include the following citation: "Our technology measures come from the CHAT data set which is an extension of the data set described in Comin and Hobijn (2004)"
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