Component-based software structuring principles are now commonplace at the application level; but componentization is far less established when it comes to building low-level systems software. Although there have been pioneering efforts in applying componentization to systems-building, these efforts have tended to target specific application domains (e.g., embedded systems, operating systems, communications systems, programmable networking environments, or middleware platforms). They also tend to be targeted at specific deployment environments (e.g., standard personal computer (PC) environments, network processors, or microcontrollers). The disadvantage of this narrow targeting is that it fails to maximize the genericity and abstraction potential of the component approach. In this article, we argue for the benefits and feasibility of a generic yet tailorable approach to component-based systems-building that offers a uniform programming model that is applicable in a wide range of systems-oriented target domains and deployment environments. The component model, called OpenCom , is supported by a reflective runtime architecture that is itself built from components. After describing OpenCom and evaluating its performance and overhead characteristics, we present and evaluate two case studies of systems we have built using OpenCom technology, thus illustrating its benefits and its general applicability.

Sensor networks provide a method of collecting environmental data for use in a variety of distributed applications. However, to date, limited support has been provided for the development of integrated environmental monitoring and modeling applications. Specifically, environmental dynamism makes it difficult to provide computational resources that are sufficient to deal with changing environmental conditions. This paper argues that the Cloud Computing model is a good fit with the dynamic computational requirements of environmental monitoring and modeling. We demonstrate that Amazon EC2 can meet the dynamic computational needs of environmental applications. We also demonstrate that EC2 can be integrated with existing sensor network technologies to offer an end-to-end environmental monitoring and modeling solution.

Suppression of β-catenin/TCF transcriptional activity and colon tumor cell growth by dual inhibition of PDE5 and 10

Advances in natural language understanding have facilitated the development of Virtual Standardized Patients (VSPs) that may soon rival human patients in conversational ability. We describe herein ...

A novel approach of design of experiment (DoE) is developed for the optimization of key substrates of the culture medium, amino acids, and sugars, by utilizing perfusion microbioreactors with 2 mL working volume, operated in high cell density continuous mode, to explore the design space. A mixture DoE based on a simplex‐centroid is proposed to test multiple medium blends in parallel perfusion runs, where the amino acids concentrations are selected based on the culture behavior in presence of different amino acid mixtures, and using targeted specific consumption rates. An optimized medium is identified with models predicting the culture parameters and product quality attributes (G0 and G1 level N‐glycans) as a function of the medium composition. It is then validated in runs performed in perfusion microbioreactor in comparison with stirred‐tank bioreactors equipped with alternating tangential flow filtration (ATF) or with tangential flow filtration (TFF) for cell separation, showing overall a similar process performance and N‐glycosylation profile of the produced antibody. These results demonstrate that the present development strategy generates a perfusion medium with optimized performance for stable Chinese hamster ovary (CHO) cell cultures operated with very high cell densities of 60 × 10⁶ and 120 × 10⁶ cells/mL and a low cell‐specific perfusion rate of 17 pL/cell/day, which is among the lowest reported and is in line with the framework recently published by the industry.

The pervasiveness of social media and user-generated content has triggered an exponential increase in global data. However, due to collection and extraction challenges, data in embedded comments, reviews and testimonials are largely inaccessible to a knowledge management system. This article describes a KM framework for the end-to-end knowledge management and value extraction from such content. This framework embodies solutions to unlock the potential of UGC as a rich, real-time data source. Three contributions are described in this article. First, a method for automatically navigating webpages to expose UGC for collection is presented. This is evaluated using browser emulation integrated with automated collection. Second, a method for collecting data without any a priori knowledge of the sites is introduced. Finally, a new testbed is developed to reflect the current state of internet sites and shared publicly to encourage future research. The discussion benchmarks the new algorithm alongside existing techniques, providing evidence of the increased amount of UGC data extracted.