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Supporting continuous sensing applications on mobile phones is challenging because of the resource demands of long-term sensing, inference and communication algorithms. We present the design, implementation and evaluation of the <i>Jigsaw continuous sensing engine</i>, which balances the performance needs of the application and the resource demands of(More)
We present Darwin, an enabling technology for mobile phone sensing that combines collaborative sensing and classification techniques to reason about human behavior and context on mobile phones. Darwin advances mobile phone sensing through the deployment of efficient but sophisticated machine learning techniques specifically designed to run directly on(More)
BACKGROUND Rheumatoid arthritis (RA) is a very complicated autoimmune disease with apparent synovial hyperplasia and cartilage and bone destruction. AIMS In the present study, we aimed to determine whether the pathogenesis of RA correlates with food allergy and which allergen(s) are relevant. MATERIALS AND METHODS We used type-II collagen (CII) to(More)
BACKGROUND Mesenchymal stem cells (MSCs) hold great promise for the treatment of difficult diseases. As MSCs represent a rare cell population, ex vivo expansion of MSCs is indispensable to obtain sufficient amounts of cells for therapies and tissue engineering. However, spontaneous differentiation and aging of MSCs occur during expansion and the molecular(More)
With increasingly powerful mobile devices, user context information can be derived from a variety of sensing components embedded inside, such as accelerometer, GPS, microphone, Bluetooth, camera, etc. Mobile phones can build continuous sensing systems that are able to collect sensor data important to a user's daily life, namely, what is the user doing,(More)