77 research outputs found

    Context-sensitive user Interfaces for semantic services

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    Service-centric solutions usually require rich context to fully deliver and better reflect on the underlying applications. We present a novel use of context in the form of customized user interface services with the concept of User Interface as a Service (UIaaS). UIaaS takes user profiles as input to generate context-aware interface services. Such interface services can be used as context to augment semantic services with contextual information leading to UIaaS as a Context (UIaaSaaC). The added serendipitous benefit of the proposed concept is that the composition of a customized user interface with the requested service is performed by the service composition engine, as is the case with any other services. We use a special-purpose language (called User Interface Description Language (UIDL)) to model and realize user interfaces as services. We use a real-life e-government application, human services delivery for the citizens, as a proof-of-concept. We also present a comprehensive evaluation of the proposed approach using a functional evaluation and a nonfunctional evaluation consisting of an end user usability test and expert usability reviews

    Expressing Trust with Temporal Frequency of User Interaction in Online Communities

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    Reputation systems concern soft security dynamics in diverse areas. Trust dynamics in a reputation system should be stable and adaptable at the same time to serve the purpose. Many reputation mechanisms have been proposed and tested over time. However, the main drawback of reputation management is that users need to share private information to gain trust in a system such as phone numbers, reviews, and ratings. Recently, a novel model that tries to overcome this issue was presented: the Dynamic Interaction-based Reputation Model (DIBRM). This approach to trust considers only implicit information automatically deduced from the interactions of users within an online community. In this primary research study, the Reddit and MathOverflow online social communities have been selected for testing DIBRM. Results show how this novel approach to trust can mimic behaviors of the selected reputation systems, namely Reddit and MathOverflow, only with temporal information

    Online change detection for energy-efficient mobilec crowdsensing

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    Mobile crowdsensing is power hungry since it requires continuously and simultaneously sensing, processing and uploading fused data from various sensor types including motion sensors and environment sensors. Realizing that being able to pinpoint change points of contexts enables energy-efficient mobile crowdsensing, we modify histogram-based techniques to efficiently detect changes, which has less computational complexity and performs better than the conventional techniques. To evaluate our proposed technique, we conducted experiments on real audio databases comprising 200 sound tracks. We also compare our change detection with multivariate normal distribution and one-class support vector machine. The results show that our proposed technique is more practical for mobile crowdsensing. For example, we show that it is possible to save 80% resource compared to standard continuous sensing while remaining detection sensitivity above 95%. This work enables energy-efficient mobile crowdsensing applications by adapting to contexts

    Crotalus atrox venom preconditioning increases plasma fibrinogen and reduces perioperative hemorrhage in a rat model of surgical brain injury.

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    Perioperative bleeding is a potentially devastating complication in neurosurgical patients, and plasma fibrinogen concentration has been identified as a potential modifiable risk factor for perioperative bleeding. The aim of this study was to evaluate preconditioning with Crotalus atrox venom (Cv-PC) as potential preventive therapy for reducing perioperative hemorrhage in the rodent model of surgical brain injury (SBI). C. atrox venom contains snake venom metalloproteinases that cleave fibrinogen into fibrin split products without inducing clotting. Separately, fibrinogen split products induce fibrinogen production, thereby elevating plasma fibrinogen levels. Thus, the hypothesis was that preconditioning with C. atrox venom will produce fibrinogen spilt products, thereby upregulating fibrinogen levels, ultimately improving perioperative hemostasis during SBI. We observed that Cv-PC SBI animals had significantly reduced intraoperative hemorrhage and postoperative hematoma volumes compared to those of vehicle preconditioned SBI animals. Cv-PC animals were also found to have higher levels of plasma fibrinogen at the time of surgery, with unchanged prothrombin time. Cv-PC studies with fractions of C. atrox venom suggest that snake venom metalloproteinases are largely responsible for the improved hemostasis by Cv-PC. Our findings indicate that Cv-PC increases plasma fibrinogen levels and may provide a promising therapy for reducing perioperative hemorrhage in elective surgeries

    A unique view of SARS-COV-2 through the lens of ORF8 protein

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    Immune evasion is one of the unique characteristics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) attributed to its ORF8 protein. This protein modulates the adaptive host immunity through down-regulation of MHC-1 (Major Histocompatibility Complex) molecules and innate immune responses by surpassing the host\u27s interferon-mediated antiviral response. To understand the host\u27s immune perspective in reference to the ORF8 protein, a comprehensive study of the ORF8 protein and mutations possessed by it have been performed. Chemical and structural properties of ORF8 proteins from different hosts, such as human, bat, and pangolin, suggest that the ORF8 of SARS-CoV-2 is much closer to ORF8 of Bat RaTG13-CoV than to that of Pangolin-CoV. Eighty-seven mutations across unique variants of ORF8 in SARS-CoV-2 can be grouped into four classes based on their predicted effects (Hussain et al., 2021) [1]. Based on the geo-locations and timescale of sample collection, a possible flow of mutations was built. Furthermore, conclusive flows of amalgamation of mutations were found upon sequence similarity analyses and consideration of the amino acid conservation phylogenies. Therefore, this study seeks to highlight the uniqueness of the rapidly evolving SARS-CoV-2 through the ORF8

    Minimizing errors in RT-PCR detection and quantification of SARS-CoV-2 RNA for wastewater surveillance

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    Wastewater surveillance for pathogens using reverse transcription-polymerase chain reaction (RT-PCR) is an effective and resource-efficient tool for gathering community-level public health information, including the incidence of coronavirus disease-19 (COVID-19). Surveillance of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in wastewater can potentially provide an early warning signal of COVID-19 infections in a community. The capacity of the world's environmental microbiology and virology laboratories for SARS-CoV-2 RNA characterization in wastewater is increasing rapidly. However, there are no standardized protocols or harmonized quality assurance and quality control (QA/QC) procedures for SARS-CoV-2 wastewater surveillance. This paper is a technical review of factors that can cause false-positive and false-negative errors in the surveillance of SARS-CoV-2 RNA in wastewater, culminating in recommended strategies that can be implemented to identify and mitigate some of these errors. Recommendations include stringent QA/QC measures, representative sampling approaches, effective virus concentration and efficient RNA extraction, PCR inhibition assessment, inclusion of sample processing controls, and considerations for RT-PCR assay selection and data interpretation. Clear data interpretation guidelines (e.g., determination of positive and negative samples) are critical, particularly when the incidence of SARS-CoV-2 in wastewater is low. Corrective and confirmatory actions must be in place for inconclusive results or results diverging from current trends (e.g., initial onset or reemergence of COVID-19 in a community). It is also prudent to perform interlaboratory comparisons to ensure results' reliability and interpretability for prospective and retrospective analyses. The strategies that are recommended in this review aim to improve SARS-CoV-2 characterization and detection for wastewater surveillance applications. A silver lining of the COVID-19 pandemic is that the efficacy of wastewater surveillance continues to be demonstrated during this global crisis. In the future, wastewater should also play an important role in the surveillance of a range of other communicable diseases

    Quantifying Direct Trust for Private Information Sharing in an Online Social Network

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