R-U-In?-Exploiting Rich Presence and Converged Communications for Next-Generation Activity-Oriented Social Networking

With the growing popularity of social networking, traditional Internet Service Providers (ISPs) and telecom operators have both started exploring new opportunities to boost their revenue streams. The efforts have facilitated consumers to stay connected to their favorite social networks,be it from an ISP portal or a mobile device. The use of Web 2.0 technologies and converged communication tools has further led to a rise in both user-generated content as well as contextual information (i.e. rich presence) about users - including their current location, availability, interests and moods. In this evolving landscape, social networking players need to innovate for value-centric usage models that increase customer stickiness,along with business models to monetize the social media. To this end, we present R-U-In? - an activity-oriented social networking system for users to collaborate and participate in activities of mutual interest. Activities can be initiated and scheduled on-demand and be as ephemeral as the user interests themselves. R-U-In? leverages contextual modeling and reasoning techniques to enable "social search" based on real-time user interests and finds potential matches for the proposed activity. Further, it exploits next-generation presence and communication technologies to manage the entire activity lifecycle in real-time. Initial survey results, based on a prototype implementation of R-U-In?, attest to the promise of realtime activity-oriented social networking - both in terms of an effective collaboration tool for value-oriented social networking users and an enhanced end-user experience.Upprättat; 2009; 20130423 (saguna

Ebola Virus Glycoprotein Induces an Innate Immune Response In vivo via TLR4

Ebola virus (EBOV), a member of the Filoviridae family, causes the most severe form of viral hemorrhagic fever. Although no FDA licensed vaccine or treatment against Ebola virus disease (EVD) is currently available, Ebola virus glycoprotein (GP) is the major antigen used in all candidate Ebola vaccines. Recent reports of protection as quickly as within 6 days of administration of the rVSV-based vaccine expressing EBOV GP before robust humoral responses were generated suggests that the innate immune responses elicited early after vaccination may contribute to the protection. However, the innate immune responses induced by EBOV GP in the absence of viral vectors or adjuvants have not been fully characterized in vivo. Our recent studies demonstrated that immunization with highly purified recombinant GP in the absence of adjuvants induced a robust IgG response and partial protection against EBOV infection suggesting that GP alone can induce protective immunity. In this study we investigated the early immune response to purified EBOV GP alone in vitro and in vivo. We show that GP was efficiently internalized by antigen presenting cells and subsequently induced production of key inflammatory cytokines. In vivo, immunization of mice with EBOV GP triggered the production of key Th1 and Th2 innate immune cytokines and chemokines, which directly governed the recruitment of CD11b+ macrophages and CD11c+ dendritic cells to the draining lymph nodes (DLNs). Pre-treatment of mice with a TLR4 antagonist inhibited GP-induced cytokine production and recruitment of immune cells to the DLN. EBOV GP also upregulated the expression of costimulatory molecules in bone marrow derived macrophages suggesting its ability to enhance APC stimulatory capacity, which is critical for the induction of effective antigen-specific adaptive immunity. Collectively, these results provide the first in vivo evidence that early innate immune responses to EBOV GP are mediated via the TLR4 pathway and are able to modulate the innate-adaptive interface. These mechanistic insights into the adjuvant-like property of EBOV GP may help to develop a better understanding of how optimal prophylactic efficacy of EBOV vaccines can be achieved as well as further explore the potential post-exposure use of vaccines to prevent filoviral disease

Complex activity recognition using context driven activity theory in home environments

This paper proposes a context driven activity theory (CDAT) and reasoning approach for recognition of concurrent and interleaved complex activities of daily living (ADL) which involves no training and minimal annotation during the setup phase. We develop and validate our CDAT using the novel complex activity recognition algorithm on two users for three weeks. The algorithm accuracy reaches 88.5% for concurrent and interleaved activities. The inferencing of complex activities is performed online and mapped onto situations in near real-time mode. The developed systems performance is analyzed and its behavior evaluatedValiderad; 2011; 20111116 (andbra