Linear minimum mean square error estimation for discrete-timeMarkovian jump linear systems

The linear minimum mean square error estimator (LMMSE) for discrete-time linear systems subject to abrupt changes in the parameters modeled by a Markov chain &thetas;(k)ϵ{1...,N} is considered. The filter equations are derived from geometric arguments in a recursive form, resulting in an on-line algorithm suitable for computer implementation. The author's approach is based on estimating x(k)1/sub {&thetas;(k/=i}) instead of estimating directly x(k). The uncertainty introduced by the Markovian jumps increases the dimension of the filter to N(n+1), where n is the dimension of the state variable. An example where the dimension of the filter can be reduced to n is presented, as well as a numerical comparison with the IMM filter     

Analysis and design of I/O based variable structure adaptivecontrol

This paper presents an overview of a technique for the design of variable structure model reference adaptive control (VS-MRAC) systems, using only input-output data. The main ideas underlying the design and the analysis, as well as the main properties of the controller, are described having as point of departure a well known parameter adaptive MRAC scheme. Then, asymptotic properties of the VS-MRAC system are established taking into account the effect of the averaging filters necessary to implement some equivalent control signals. In particular, global exponential stability of the associated error system with respect to a small residual set is demonstrated. The effect of linear zones in the relay functions is assessed showing that they can alleviate the chattering phenomena. This is related with the fact that the VS-MRAC has a high-gain stability property. A procedure for noise sensitivity reduction is also proposed. Simulations illustrate the very satisfactory performance of the VS-MRAC in adverse operating conditions     

The molecular biology of breast cancer: accelerating clinical applications

Recent advances in basic science have led to a better understanding of the molecular events important in the pathogenesis of breast cancer. Very little of this new knowledge, however, has had a significant impact on improving the diagnosis and therapy of breast cancer. We review many of the molecular events important in the pathogenesis of breast cancer, including inherited abnormalities in BRCA-1 and BRCA-2, p53, ATM, and PTEN and sporadic alterations in growth factors and their receptors, signal transduction, cell cycle control, DNA repair, cell death, angiogenesis, and invasion and metastasis. We suggest ways to speed up clinical applications of the new molecular knowledge base through the use of preclinical disease models, development of high throughput sample analysis and infrastructure programs to facilitate translational research, implementation of practice guidelines, and development of regional oncology networks. Only through the implementation of such a deliberate, multifaceted strategy will the gap between the research laboratory and the clinic be closed.     

Urinary albumin excretion rate and glomerular filtration rate in single-kidney type 2 diabetic patients

OBJECTIVE: To evaluate the urinary albumin excretion rate (UAER) and the glomerular filtration rate (GFR) of single-kidney type 2 diabetic patients (SKD) and of single-kidney non-diabetic patients (SKN). RESEARCH DESIGN AND METHODS: Patients who had only one kidney for at least 5 years, with no renal disease or hypertension at the time of the nephrectomy and with no calculus or systemic disease at the time of the evaluation, were included in this controlled cross-sectional study A total of 20 SKD (8 men, age 62 +/- 9 years; diabetes duration 8.5 +/- 7 years), 17 SKN (2 men, age 57 +/- 13 years), and 184 type 2 diabetic patients who were matched to the single-kidney diabetic group for age, sex, and BMI were studied. UAER was measured by immunoturbidimetry in timed 24-h sterile urine, and GFR was determined by the 51Cr-EDTA single-injection method. RESULTS: SKD patients presented a higher proportion (8 of 20, 40%) of microalbuminuria (UAER 20-200 microg/min) than SKN patients (3 of 17, 17.6%) and type 2 diabetic patients (37 of 184, 20%). SKD patients presented a higher proportion of macroalbuminuria (UAER >200 microg/min; 6 of 20, 30%) than SKN patients (1 of 17, 6%) but were similar to type 2 diabetic patients (43 of 184, 23%). The GFRs of normoalbuminuric SKN (71.7 +/- 21.4 ml x min(-1) x 1.73 m(-2)) and SKD patients (73.0 +/- 21.5 ml x min(-1) x 1.73 m(-2)) were similar but higher than the one-kidney GFR (GFR / 2) of the age-, sex-, and BMI-matched normal individuals (50.5 +/- 9.0 ml x min(-1) x 1.73 m(-2)) and normoalbuminuric type 2 diabetic patients (54.0 +/- 11.6 ml x min(-1) x 1.73 m(-2)). CONCLUSIONS: Increased GFR related to single-kidney status confers an increased risk of developing renal disease in the presence of diabetes.     

Determination of the roots of the characteristic equation forcorrugated and dielectric loaded circular waveguides

An algorithm is developed for the numerical determination of the roots of the characteristic equation for corrugated and dielectric loaded circular waveguides. The algorithm, based on geometrical properties of the characteristic equation and on the identification of the interval of existence of each root, assures a fast and precise determination of all the roots, real or complex, in a given interval     

Production of organic solvent tolerant lipase by Staphylococcus caseolyticus EX17 using raw glycerol as substrate

BACKGROUND: In this work we used Plackett–Burman statistical design and central composite design in order to optimize culture conditions for lipase production by Staphylococcus caseolyticus strain EX17 growing on raw glycerol, which was obtained as a by‐product of the enzymatic synthesis of biodiesel. The stability of lipase was verified over several organic solvents, such as methanol, ethanol and n‐hexane. RESULTS: Optimal culture conditions for lipase production were found to be 36 °C, initial pH 8.12, glycerol 30 g L^?1, olive oil 3.0 g L^?1, and soybean oil 2.5 g L^?1, with 145.8 U L^?1 of enzyme activity. When commercial glycerol was substituted by the raw glycerol from biodiesel synthesis, lipolytic activity was 127.3 U L^?1. Experimental validation of enzyme production matched values predicted by the mathematical model, which was 138.3 U L^?1. Stability tests showed that lipase from S. caseolyticus EX17 was stable in methanol, ethanol, and n‐hexane. CONCLUSIONS: Results obtained in this work suggest that raw glycerol can be used for lipase production by S. caseolyticus EX17 and that this enzyme has a potential application in the synthesis of biodiesel. Copyright © 2008 Society of Chemical Industry     

2, 5-Diketopiperazines (Cyclic Dipeptides) in Beef: Identification, Synthesis, and Sensory Evaluation

ABSTRACT:  Stewed beef and grilled dry aged beef were analyzed as part of an in-depth analytical program, with the aim of creating new flavors incorporating only compounds identified in the target foods and identifying new synthesis targets. In-house GC-MS analyses of several types of cooked beef have identified over 1000 volatile and semivolatile components; many for the 1st time. Among the semivolatiles detected were ten 2, 5-diketopiperazines (cyclic dipeptides) previously unreported in beef. These cyclic dipeptides are cis -cyclo( l -Ile- l -Pro), cis -cyclo( l -Leu- l -Pro), cis -cyclo( l -Pro- l -Pro), cis -cyclo( l -Pro- l -Val), cis -cyclo( l -Ala- l -Pro), cyclo(Gly- l -Pro), cyclo(Gly- l -Leu), cis -cyclo( l -Met- l -Pro), cis -cyclo( l -Phe- l -Pro), and cis- cyclo( l -Phe- l -Val). All 10 cyclic dipeptides were synthesized and evaluated organoleptically. Among them cis -cyclo( l -Leu- l -Pro), cis -cyclo( l -Met- l -Pro), and cis -cyclo( l -Phe- l -Pro) were found to be of particular organoleptic interest.     

Failure Mechanisms in Sand over a Deep Active Trapdoor

An experimental testing program was undertaken to investigate failure mechanisms induced by the active movement of a deep rectangular trapdoor underlying a granular soil. Reduced-scale models were tested under normal gravity as well as under an increased gravitational field using a centrifuge facility. Some models were used to evaluate the performance of both flexible and rigid pipes undergoing a localized loss of support. Failure mechanisms in the longitudinal direction of the models were characterized by a single, well-defined failure surface that developed within the limits of the trapdoor. However, failure mechanisms in the transverse direction of the models were characterized by multiple failure surfaces extending outside the limits of the trapdoor. Significant dilation of the soil located immediately above the trapdoor was identified in the failure of the models. The pattern of the failure mechanisms was found to be affected by the stress level and backfill density. Higher stress levels were found to lead to well-developed failure zones. The influence of backfill density was found to be more relevant in models involving flexible pipes. Pipes embedded within loose backfill were severely damaged after loss of support, while pipes embedded in dense backfill experienced negligible deformations. These results indicate that damage to pipelines caused by ground loss of support can be significantly minimized by controlling the compaction of the fill.     

Stochastic analysis of the filtered-X LMS algorithm in systems withnonlinear secondary paths

This paper presents a statistical analysis of the filtered-X LMS algorithm behavior when the secondary path (output of the adaptive filter) includes a nonlinear element. This system is of special interest for active acoustic noise and vibration control, where a saturation nonlinearity models the nonlinear distortion introduced by the power amplifiers and transducers. Deterministic nonlinear recursions are derived for Gaussian inputs for the transient mean weight, mean square error, and cross-covariance matrix of the adaptive weight vector at different times. The cross-covariance results provide improved steady-state predictions (as compared with previous results) for moderate to large step sizes. Monte Carlo simulations show excellent agreement with the behavior predicted by the theoretical models. The analytical and simulation results show that a small nonlinearity can have a significant impact on the adaptive filter behavior