The analysis of solvation in ionic liquids and organic solvents using the Abraham linear free energy relationship

The contentions made in an earlier paper [J Chem Technol Biotechnol 80 : 133–137 (2005)] that the coefficients of the Abraham solvation equation do not provide meaningful information on the molecular properties of ionic liquid solvents is refuted. The objections noted in the earlier paper disappear when the solvation equation model is correctly applied to the experimental data. It is further shown that the coefficients of the Abraham solvation equations can be used to characterize ionic liquids and can be used to select solvents for the solubility of gaseous solutes. Copyright © 2006 Society of Chemical Industry     

Assessing the relative priority of projects

Where there are a large number of projects competing for a limited pool of resources, projects have to be assigned priorities to determine which should proceed and which should be curtailed. The traditional economic procedures for assessing the relative priority of projects are reviewed, and alternative methods of ranking projects are suggested, with particular emphasis on methods that are inexpensive and easy to use.     

Using rainbow net simulation to measure fault tolerance in a multiprocessor

The Rainbow net simulation technique is applied to modelling the impact of system load and fault handling on the availability of a fault-tolerant multiprocessor architecture. Rainbow nets are described along with the motivation for creating this modelling technique. A Rainbow net fault-handling model is created for the fault-tolerant multiprocessor architecture and the topology is shown to remain constant in size, independent of the number of processor, memory and I/O elements configured in the system. Simulation is performed with a varying load in terms of the number of active jobs the system must support. Results are given showing how the fault-tolerant capability varies with load. Two new metrics for evaluating fault tolerance are introduced; namely full fault-tolerability and partial fault-tolerability. They are based on simple observations in the model.     

Targets and methods for the detection of processed animal proteins in animal feedstuffs

Bovine spongiform encephalopathy (BSE), or ‘mad cow disease’, is one of several transmissable spongiform encephalopathies (TSEs) known to affect certain mammals and is spread through the ingestion of infected animal tissue. It is believed that the inadvertent contamination of meat and bone meal (MBM) with infected animal tissue and the subsequent use of this material as a feed supplement contributed to the spread of the disease in cattle. As a result, the use of processed animal proteins (PAPs) in animal feeds is regulated in many parts of the world. Although feed testing is the only definitive means to certify compliance, regulatory compliance often relies solely on paper certification. Recently, rapid methods have become available that can be used by regulators to determine compliance during routine inspections. We describe a rapid, immunochromatographic strip test that can detect 0.1% MBM in animal feed. The test takes 15 min to perform and large numbers of samples can be screened for PAPs simultaneously.     

Enhancing cognitive radio systems with robust reasoning

Cognitive radio systems dynamically reconfigure the algorithms and parameters they use, in order to adapt to the changing environment conditions. However, reaching proper reconfiguration decisions presupposes a way of knowing, with high enough assurance, the capabilities of the alternate configurations, especially in terms of achievable transmission capacity and coverage. The present paper addresses this problem, firstly, by specifying a complete process for extracting estimations of the capabilities of candidate configurations, in terms of transmission capacity and coverage, and, secondly, by enhancing these estimations with the employment of a machine learning technique. The technique is based on the use of Bayesian Networks, in conjunction with an effective learning and adaptation strategy, and aims at extracting and exploiting knowledge and experience, in order to reach robust (i.e. stable and reliable) estimations of the configurations' capabilities. Comprehensive results of the proposed method are presented, in order to validate its functionality. Copyright © 2007 John Wiley & Sons, Ltd.     

Sheet molding compound characterization using spiral flow

Sheet molding compound (SMC) is a fiber‐reinforced polymeric composite. It is often used in automotive, marine, and industrial applications over other materials because of its high strength to density ratio, resistance to corrosion, and low cost. There is a demand in the SMC industry to be able to characterize SMC processability. This is particularly true for heavy truck body panels, one of the fastest growing applications of SMC. Because of their large size and high strength requirement, the molding forces have a major influence in the molding cycle. Also because of the long flow paths involved, the ability of the paste to carry glass needs to be properly characterized when developing new SMC materials. In this article, we demonstrate the benefits of using spiral flow as a processability tester. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Microstructured and Electro-Assisted High-Temperature Wettability of MgO in Contact with a Silicate Slag-Based on Fayalite

In this work, MgO samples have been microstructured by laser treatment and surfaces with a controlled stripe design have been manufactured. Sessile drop wetting measurements were performed in a special heating microscope by determining horizontal contact angles as well as contact angles as a function of surface inclination angles. In a further step, voltage was applied to ground MgO surfaces and the wetting behavior was registered as a function of the voltage level. Activation energy analysis was conducted for all the experiments.     

Computer aided kinetic modeling with KMT and KME

The complexity of many chemical and refining reaction systems and the thus-derived tedious and time-consuming process of building the associated kinetic models have been major obstacles in the use of fundamental kinetics in the solution of chemical engineering problems. This review summarizes work aimed at removing theses obstacles. Our recent work that has led to the enhancement of the Kinetic Modeler's Toolbox (KMT) and the development of the Kinetic Model Editor (KME) presents an end-to-end solution to the kinetic modeling process, including automated feedstock modeling, reaction network construction, kinetic rate estimation, model programming, process system configurations, model customizations, compilations, model execution and results analysis.