29,125 research outputs found
Differentially altered social dominance- and cooperative-like behaviors in Shank2- and Shank3-mutant mice
No full textBackground: Recent progress in genomics has contributed to the identification of a large number of autism spectrum disorder (ASD) risk genes, many of which encode synaptic proteins. Our understanding of ASDs has advanced rapidly, partly owing to the development of numerous animal models. Extensive characterizations using a variety of behavioral batteries that analyze social behaviors have shown that a subset of engineered mice that model mutations in genes encoding Shanks, a family of excitatory postsynaptic scaffolding proteins, exhibit autism-like behaviors. Although these behavioral assays have been useful in identifying deficits in simple social behaviors, alterations in complex social behaviors remain largely untested. Methods: Two syndromic ASD mouse models—Shank2 constitutive knockout [KO] mice and Shank3 constitutive KO mice—were examined for alterations in social dominance and social cooperative behaviors using tube tests and automated cooperation tests. Upon naïve and salient behavioral experience, expression levels of c-Fos were analyzed as a proxy for neural activity across diverse brain areas, including the medial prefrontal cortex (mPFC) and a number of subcortical structures. Findings: As previously reported, Shank2 KO mice showed deficits in sociability, with intact social recognition memory, whereas Shank3 KO mice displayed no overt phenotypes. Strikingly, the two Shank KO mouse models exhibited diametrically opposed alterations in social dominance and cooperative behaviors. After a specific social behavioral experience, Shank mutant mice exhibited distinct changes in number of c-Fos+ neurons in the number of cortical and subcortical brain regions. Conclusions: Our results underscore the heterogeneity of social behavioral alterations in different ASD mouse models and highlight the utility of testing complex social behaviors in validating neurodevelopmental and neuropsychiatric disorder models. In addition, neural activities at distinct brain regions are likely collectively involved in eliciting complex social behaviors, which are differentially altered in ASD mouse models. © 2020, The Author(s).1
Generation of Semantic Clouds based on Linked Data for Efficient Multimedia Semantic Annotations
No full textThe major drawback of existing semantic annotation methods is that they are not intuitive enough for users to easily resolve semantic ambiguities while associating semantic meaning to a chosen keyword. We have developed a semantic-cloud-based annotation scheme in which users can use semantic clouds as the primary interface for semantic annotation, and choose the most appropriate concept among the candidate semantic clouds. The most critical element of this semantic-cloud-based annotation scheme is the method of generating efficient semantic clouds that make users intuitively recognize candidate concepts to be annotated without having any semantic ambiguity. We propose a semantic cloud generation approach that locates essential points to start searching for relevant concepts in Linked Data and then iteratively analyze potential merges of different semantic data. We focus on reducing the complexity of handling a large amount of Linked Data by providing context sensitive traversal of such data. We demonstrate the quality of semantic clouds generated by the proposed approach with a case study
TurboGraph++: A Scalable and Fast Graph Analytics System
No full textExisting distributed graph analytics systems are categorized into two main groups: those that focus on efficiency with a risk of out-of-memory error and those that focus on scale-up with a fixed memory budget and a sacrifice in performance. While the former group keeps a partitioned graph resident in memory of each machine and uses an in-memory processing technique, the latter stores the partitioned graph in external memory of each machine and exploits a streaming processing technique. Gemini and Chaos are the state-of-the-art distributed graph systems in each group, respectively.
We present TurboGraph++, a scalable and fast graph analytics system which efficiently processes large graphs by exploiting external memory for scale-up without compromising efficiency. First, TurboGraph++ provides a new graph processing abstraction for efficiently supporting neighborhood analytics that requires processing multi-hop neighborhoods of vertices, such as triangle counting and local clustering coefficient computation, with a fixed memory budget. Second, TurboGraph++ provides a balanced and buffer-aware partitioning scheme for ensuring balanced workloads across machines with reasonable cost. Lastly, TurboGraph++ leverages three-level parallel and overlapping processing for fully utilizing three hardware resources, CPU, disk, and network, in a cluster. Extensive experiments show that TurboGraph++ is designed to scale well to very large graphs, like Chaos, while its performance is comparable to Gemini.110Nsciescopu
Pollutant removals of an urban riparian artificial wetland and its reconstruction in Taipei Basin after Typhoon Aere.
No full textA community recommendation method based on social networks for web 2.0-based IPTV
No full textWeb 2.0-based IPTV is a new Internet Protocol Television (IPTV) infrastructure that allows users to participate in content creation and consumption through Web-based communities that are formed based on user interests. However, there are some limitations in making users actively participate in creating and utilizing communities. First, users need to explicitly create and manage their communities. In addition, it is difficult for users to identify and join communities that meet their needs. This paper proposes a method to identify and recommend potential IPTV communities for users by using their social relationships and preferences. The main goal of this method is to motivate users to actively participate in creating and sharing their contents through recommended communities. We have implemented a prototype of Web 2.0-based IPTV that allows users to share their contents and build relevant knowledge regarding the contents through blogs and Wiki-based communities.This work was supported by the IT R&D program of MKE/IITA. [AI 100-0801-3015, Development of OpenIPTV Technologies for Wired and Wireless Networks
A Deputy Object based Presentation Sematnics Split Application Model for Synchronous Collaboration in Ubiquitous computing Environments
No full textRu-catalyzed hydroamidation of alkenes and cooperative aminocarboxylation procedure with chelating formamide
No full textA strategy of chelation-assisted activation of formamide was employed to achieve hydroamidation of alkenes to generate one-carbon-elongated amides in moderate to good selectivity and yields. Also reported is the two-metal-catalyzed cooperative aminocarboxylation of aryl iodides, in which Ru is presumed to catalyze decarbonylation of formamide to release carbon monoxide and amine for the subsequent Pd-catalyzed aminocarboxylation routes, thus enabling the net transformation to be performed in the absence of external CO pressure
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