Biochemical changes in cerebrospinal fluid associated with the neurotoxic action of HIV-1]

Different intravascular ultrasound (IVUS) systems vary in their image presentation. The purpose of this study was to compare four IVUS systems in vitro to determine the accuracy of tissue characterization of atherosclerotic plaque compared with histology. Ninety-eight plaque segments from 23 formalin-fixed human iliac arteries were imaged in saline at room temperature with four different IVUS systems. To assess the accuracy of IVUS in describing plaque, three types of analysis were performed: (1) the ability to identify the presence and extent of lumen or plaque boundary; (2) sensitivity, specificity, and interobserver variability of IVUS in qualitatively identifying plaque components compared with histology; and (3) quantification of calcification. The synthetic aperture device had a lower sensitivity in identifying lumen and plaque boundaries (87%, 38% respectively) compared with other machines (96%-100%, 95%-100%). All three mechanically rotating systems had fair to good sensitivities for identifying calcification (57%-73%) or lipid filled areas (50%-83%). The sensitivity of discriminating fibrous tissue from fatty areas was low (39%-52%). The synthetic aperture system had a significantly lower sensitivity for identifying all three tissue types (4%-21%). There was significant interobserver variability (kappa value = 0.47-0.68) as well as machine to machine variability (kappa value = 0.52) for tissue characterization. Calcified areas were underestimated by System 1 (p < .05) and System 4 (p < .01) because of weaker echo reflections or poor image quality. There are significant differences in image representation among these four IVUS systems in the diagnosis of tissue components of complex atherosclerotic plaque. These variabilities should be considered when interpreting studies performed with different machines.     

Testing of the multi-application small light water reactor (MASLWR) passive safety systems

Experimental thermal hydraulic research has been conducted at Oregon State University for the purpose of assessing the performance of a new reactor design concept, the multi-application small light water reactor (MASLWR). The MASLWR is a pressurized light water reactor design with a net output of 35 MWe that uses natural circulation in both normal and transient operation. Due to its small size, portability and modularity, the MASLWR design is well suited to help fill the potential need for grid appropriate reactor designs for smaller electricity grids as may be found in developing or remote regions. The purpose of the OSU MASLWR test facility is to assess the operation of the MASLWR under normal full operating pressure and full temperature conditions and to assess the passive safety systems under transient conditions. The data generated by the testing program will be used to assess computer code calculations and to provide a better understanding of the thermal-hydraulic phenomena in the design of the MASLWR NSSS. During this testing program, four tests were conducted at the OSU MASLWR test facility. These tests included one design basis accident and one beyond design basis accident. During the performance of these tests, plant operations to include start up, normal operation and shut down evolutions were demonstrated successfully.     

Synthesis of distillation trains by thermodynamic analysis

Thermodynamic principles, involving mainly: (1) minimum reversible work of separation and (2) second-law analysis that accounts for irreversibility, are used to synthesize separation trains. These principles lead to a development and classification into two groups of many of the heuristics appearing in the literature. An efficient algorithm based on reversible thermodynamics leads to optimal structures for simple acyclic trains. Complex structures are efficiently synthesized by algorithms using reversible thermodynamics and second-law analysis. The procedures presented are depth-first algorithms. The optimal structures developed are shown to be strongly influenced by feed and product compositions.     

STATISTICAL ANALYSIS ON COKE YIELDS IN VACUUM RESIDS AS A FUNCTION OF COMPOUND CLASSES AND ELEMENTAL ANALYSIS

This paper describes the statistical analysis of data on coke formation (measured by microcarbon residue) in five resids, as a function of compound classes, in order to identify variables wiih a significant effect on the former. In this sense, the SAS VARCLUS and Principal Component Analysis were used. The analysis carried out leads to a lineal combination of the H/C ratio, vanadium and nitrogen content as a model to explain coke yield, under non-catalytic conditions, as determined by MCR. Of all these factors, the H/C ratio has the most important contribution.     

Passive internet-based crane teleoperation with haptic aids

Crane operation is a challenging task, due to the combined problem of obstacle avoidance and load swing suppression in underactuated conditions. This paper presents a human-machine interface that increases the operator’s perception of a gantry crane’s workspace. With this aim, a virtual environment resembling the workspace is connected with a haptic device. This allows the user to receive not only visual but also tactile feedback, thus increasing maneuvering safety. Additionally, this capability is integrated in a teleoperation setup, adopting a passivity-based control approach that guarantees overall stability. This includes also the design of controllers by means of the IDA-PBC method. Experimental results carried out with a laboratory crane show its feasibility for internet-based teleoperation and demonstrate the improvements on the system performance.     

Adsorption isotherms of sesame oil in a concentrated miscella system

The adsorption of peroxides, unsaturated carbonyls, free fatty acids and carotenoids from unrefined sesame oil on vegetable carbon (5%, w/w) in a miscella system was studied. Three different solvent conditions (hexane/ethanol, 100:0, 95:5 and 75:25, vol/vol), combined in a factorial design with five levels of solvent (0, 10, 20, 30 and 40%, w/w), were used to develop the miscella. Equilibrium adsorption was not achieved during the 100 min of adsorption, mainly because the oil components were involved in oxidation reactions during the adsorption process. However, for a given solvent concentration, adsorption of the oil components showed a significant linear regression on their respective initial concentration in the miscella (C_i). Peroxides and carbonyls showed, at all solvent levels investigated, an affinity for the carbon more independent of their C_i than free fatty acids and carotenoids. In general, at the same C_i, a higher adsorption was achieved as solvent concentration increased. The results indicated that free fatty acid adsorption may depend on competitive adsorption based on molecule hydrophobicity. However, in spite of the higher hydrophobicity of carotenoids, compared with free fatty acids, they might not be competing for the same adsorbing sites. Ethanol showed a prooxidant effect that increased peroxide production during adsorption but did not affect the reaction involved in carbonyl production.     

Fast training procedure for Viola–Jones type object detectors using Laplacian clutter models

This paper presents a fast training strategy for the Viola–Jones (VJ) type object-detection systems. The VJ object- detection system, popular for its high accuracy at real-time testing speeds, has a drawback that it is slow to train. A face detector, for example, can take days to train. In content-based image retrieval (CBIR), where search needs to be performed instantaneously, VJ’s long training time is not affordable. Therefore, VJ’s method is hardly used for such applications. This paper proposes two modifications to the training algorithm of VJ-type object detection systems which reduces the training time to the order of seconds. Firstly, Laplacian clutter (non-object) models are used to train the weak classifier, thus eliminating the need to read and evaluate thousands of clutter images. Secondly, the training procedure is simplified by removing the time-consuming AdaBoost-based feature selection procedure. An object detector, trained with 500 images, approximately takes 2 s for training in a conventional 3 GHz machine. Our results show that the accuracy of the detector, built with the proposed approach, is inferior to that of VJ for difficult object class such as frontal faces. However, for objects with lesser degree of intra-class variations such as hearts, state-of-the-art accuracy can be obtained. Importantly, for CBIR applications, the fast testing speed of the VJ type object detector is maintained.     

One-shot methods in function space for PDE-constrained optimal control problems

We state and analyse one-shot methods in function space for the optimal control of nonlinear partial differential equations (PDEs) that can be formulated in terms of a fixed-point operator. A general convergence theorem is proved by generalizing the previously obtained results in finite dimensions. As application examples we consider two nonlinear elliptic model problems: the stationary solid fuel ignition model and the stationary viscous Burgers equation. For these problems we present a more detailed convergence analysis of the method. The resulting algorithms are computationally implemented in combination with an adaptive mesh refinement strategy, which leads to an improvement in the performance of the one-shot approach.     

Performance modeling and analysis of message-oriented event-driven systems

Message-oriented event-driven systems are becoming increasingly ubiquitous in many industry domains including telecommunications, transportation and supply chain management. Applications in these areas typically have stringent requirements for performance and scalability. To guarantee adequate quality-of-service, systems must be subjected to a rigorous performance and scalability analysis before they are put into production. In this paper, we present a comprehensive modeling methodology for message-oriented event-driven systems in the context of a case study of a representative application in the supply chain management domain. The methodology, which is based on queueing Petri nets, provides a basis for performance analysis and capacity planning. We study a deployment of the SPECjms2007 standard benchmark on a leading commercial middleware platform. A detailed system model is built in a step-by-step fashion and then used to predict the system performance under various workload and configuration scenarios. After the case study, we present a set of generic performance modeling patterns that can be used as building blocks when modeling message-oriented event-driven systems. The results demonstrate the effectiveness, practicality and accuracy of the proposed modeling and prediction approach.     

Enacting agent-based services for automated procurement

Negotiation events in industrial procurement involving multiple, highly customisable goods pose serious challenges to buying agents when trying to determine the best set of providing agents’ offers. Typically, a buying agent's decision involves a large variety of constraints that may involve attributes of a very same item as well as attributes of different, multiple items. In this paper we present iBundler, an agent-aware service offered to buying agents to help them determine the optimal bundle of received offers based on their business rules. In this way, buying agents are relieved with the burden of solving too hard a problem and concentrate on strategic issues. iBundler is intended as a negotiation service for buying agents and as a winner determination service for reverse combinatorial auctions with side constraints. Furthermore, we assess the computational cost added by employing agent technology in the development of iBundler to characterise the type of negotiation scenarios that it can acceptably handle.