Linear matrix inequality-based robust model predictive control for time-delayed systems

This work addresses the solution to the problem of robust model predictive control (MPC) of systems with model uncertainty. The case of zone control of multi-variable stable systems with multiple time delays is considered. The usual approach of dealing with this kind of problem is through the inclusion of non-linear cost constraint in the control problem. The control action is then obtained at each sampling time as the solution to a non-linear programming (NLP) problem that for high-order systems can be computationally expensive. Here, the robust MPC problem is formulated as a linear matrix inequality problem that can be solved in real time with a fraction of the computer effort. The proposed approach is compared with the conventional robust MPC and tested through the simulation of a reactor system of the process industry.

An online data access prediction and optimization approach for distributed systems

Current scientific applications have been producing large amounts of data. The processing, handling and analysis of such data require large-scale computing infrastructures such as clusters and grids. In this area, studies aim at improving the performance of data-intensive applications by optimizing data accesses. In order to achieve this goal, distributed storage systems have been considering techniques of data replication, migration, distribution, and access parallelism. However, the main drawback of those studies is that they do not take into account application behavior to perform data access optimization. This limitation motivated this paper which applies strategies to support the online prediction of application behavior in order to optimize data access operations on distributed systems, without requiring any information on past executions. In order to accomplish such a goal, this approach organizes application behaviors as time series and, then, analyzes and classifies those series according to their properties. By knowing properties, the approach selects modeling techniques to represent series and perform predictions, which are, later on, used to optimize data access operations. This new approach was implemented and evaluated using the OptorSim simulator, sponsored by the LHC-CERN project and widely employed by the scientific community. Experiments confirm this new approach reduces application execution time in about 50 percent, specially when handling large amounts of data.

Real-time PCR quantitation of glucocorticoid receptor alpha isoform

Abstract Background The expression of glucocorticoid-receptor (GR) seems to be a key mechanism in the regulation of glucocorticoid (GC) sensitivity and is potentially involved in cases of GC resistance or hypersensitivity. The aim of this study is to describe a method for quantitation of GR alpha isoform (GRα) expression using real-time PCR (qrt-PCR) with analytical capabilities to monitor patients, offering standard-curve reproducibility as well as intra- and inter-assay precision. Results Standard-curves were constructed by employing standardized Jurkat cell culture procedures, both for GRα and BCR (breakpoint cluster region), as a normalizing gene. We evaluated standard-curves using five different sets of cell culture passages, RNA extraction, reverse transcription, and qrt-PCR quantification. Intra-assay precision was evaluated using 12 replicates of each gene, for 2 patients, in a single experiment. Inter-assay precision was evaluated on 8 experiments, using duplicate tests of each gene for two patients. Standard-curves were reproducible, with CV (coefficient of variation) of less than 11%, and Pearson correlation coefficients above 0,990 for most comparisons. Intra-assay and inter-assay were 2% and 7%, respectively. Conclusion This is the first method for quantitation of GRα expression with technical characteristics that permit patient monitoring, in a fast, simple and robust way.

Value of adenosine infusion for infarct size determination using real-time myocardial contrast echocardiography

Abstract Background Myocardial contrast echocardiography has been used for determination of infarct size (IS) in experimental models. However, with intermittent harmonic imaging, IS seems to be underestimated immediately after reperfusion due to areas with preserved, yet dysfunctional, microvasculature. The use of exogenous vasodilators showed to be useful to unmask these infarcted areas with depressed coronary flow reserve. This study was undertaken to assess the value of adenosine for IS determination in an open-chest canine model of coronary occlusion and reperfusion, using real-time myocardial contrast echocardiography (RTMCE). Methods Nine dogs underwent 180 minutes of coronary occlusion followed by reperfusion. PESDA (Perfluorocarbon-Exposed Sonicated Dextrose Albumin) was used as contrast agent. IS was determined by RTMCE before and during adenosine infusion at a rate of 140 mcg·Kg-1·min-1. Post-mortem necrotic area was determined by triphenyl-tetrazolium chloride (TTC) staining. Results IS determined by RTMCE was 1.98 ± 1.30 cm2 and increased to 2.58 ± 1.53 cm2 during adenosine infusion (p = 0.004), with good correlation between measurements (r = 0.91; p < 0.01). The necrotic area determined by TTC was 2.29 ± 1.36 cm2 and showed no significant difference with IS determined by RTMCE before or during hyperemia. A slight better correlation between RTMCE and TTC measurements was observed during adenosine (r = 0.99; p < 0.001) then before it (r = 0.92; p = 0.0013). Conclusion RTMCE can accurately determine IS in immediate period after acute myocardial infarction. Adenosine infusion results in a slight better detection of actual size of myocardial damage.

Programmable logic design of a compact Genetic Algorithm for phasor estimation in real-time

The main objective of this work is to present an efficient method for phasor estimation based on a compact Genetic Algorithm (cGA) implemented in Field Programmable Gate Array (FPGA). To validate the proposed method, an Electrical Power System (EPS) simulated by the Alternative Transients Program (ATP) provides data to be used by the cGA. This data is as close as possible to the actual data provided by the EPS. Real life situations such as islanding, sudden load increase and permanent faults were considered. The implementation aims to take advantage of the inherent parallelism in Genetic Algorithms in a compact and optimized way, making them an attractive option for practical applications in real-time estimations concerning Phasor Measurement Units (PMUs).