Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

Expression of drug resistance markers by spheroplasts ofMycobacterium smegmatis after fusion

Mycobacterial spheroplasts were prepared by treatment of the glycinesensitized cells with a combination of lipase and lysozyme. They were stable for several hours at room temperature but were lysed on treatment with 0.1% sodium dodecyl sulfate. The spheroplasts could be regenerated on a suitable medium. Fusion and regeneration of the spheroplasts were attempted using drug resistant mutant strains ofM. smegmalis. Recombinants were obtained from spheroplast fusion mediated by polyethylene glycol and dimethyl sulfoxide. Simultaneous expression of rccombinant properties was observed only after an initial lag in the isolated clones. This has been explained as due to “chromosome inactivation” in the fused product.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

Mechanism of interaction of the antileukemic drug cytosine arabinoside with aromatic peptides : role of sugar conformation and peptide backbone

Interaction of the antileukemic drugs, cytosine-arabinoside (Ara-C) and adenosine-arabinoside (Ara-A) and a structural analogue, cytidine, with aromatic dipeptides has been studied by fluorescence and NMR spectroscopy. Ara-C and cytidine bind tryptophanyl and histidyl dipeptides but not tyrosyl dipeptides, while Ara-A does not bind to any of them. Both studies indicate association involving stacking of aromatic moieties. NMR spectra also indicate a protonation of the histidine moiety by Ara-C. In case of cytidine, the chemical shifts observed on binding to His-Phe imply that the backbone protons of the dipeptide participate in the binding. The conformation of the sugar and the base seem to play a very important role in the binding phenomenon as three similar molecules, Ara-C, Ara-A and cytidine bind in totally different ways.

Steric and rotational constraints in the X-ray structure of the animalarial drug amodiaquine

In the crystal structure of the antimalarial drug amodiaquine, the bonds linking the quinoline and the phenyl groups show partial double-bond character. The partial double-bond character of the two exocyclic bonds, together with stereochemical constraints, reduce flexibility of the two ring systems of the molecule. The dihedral angle between the two ring planes is lowest compared to those in the antileukaemic drug amsacrine and its derivatives. CPK-modelling studies suggest the way amodiaquine can bind to DNA. Stacking interaction between the quinoline and phenyl groups of independent molecules and the hydrogen-bond network stabilize the crystal structure.

Poly propyl ether imine (PETIM) dendrimer: A novel non-toxic dendrimer for sustained drug delivery

In the present study, an attempt was made to study the acute and sub-acute toxicity profile of G3-COOH Poly (propyl ether imine) PETIM] dendrimer and its use as a carrier for sustained delivery of model drug ketoprofen. Drug-dendrimer complex was prepared and characterized by FTIR, solubility and in vitro drug release study. PETIM dendrimer was found to have significantly less toxicity in A541 cells compared to Poly amido amine (PAMAM) dendrimer. Further, acute and 28 days sub-acute toxicity measurement in mice showed no mortality, hematological, biochemical or histopathological changes up to 80 mg/kg dose of PETIM dendrimer. The results of study demonstrated that G3-COOH PETIM dendrimer can be used as a safe and efficient vehicle for sustained drug delivery. (C) 2010 Elsevier Masson SAS. All rights reserved.

Heat Shock Protein 90 as a Drug Target against Protozoan Infections Biochemical characterization of HSP90 From plasmodium falciparum and trypanosoma evansi and evaluation of its inhibitor as a candidate drug

Using a pharmacological inhibitor of Hsp90 in cultured malarial parasite, we have previously implicated Plasmodium falciparum Hsp90 (PfHsp90) as a drug target against malaria. In this study, we have biochemically characterized PfHsp90 in terms of its ATPase activity and interaction with its inhibitor geldanamycin (GA) and evaluated its potential as a drug target in a preclinical mouse model of malaria. In addition, we have explored the potential of Hsp90 inhibitors as drugs for the treatment of Trypanosoma infection in animals. Our studies with full-length PfHsp90 showed it to have the highest ATPase activity of all known Hsp90s; its ATPase activity was 6 times higher than that of human Hsp90. Also, GA brought about more robust inhibition of PfHsp90 ATPase activity as compared with human Hsp90. Mass spectrometric analysis of PfHsp90 expressed in P. falciparum identified a site of acetylation that overlapped with Aha1 and p23 binding domain, suggesting its role in modulating Hsp90 multichaperone complex assembly. Indeed, treatment of P. falciparum cultures with a histone deacetylase inhibitor resulted in a partial dissociation of PfHsp90 complex. Furthermore, we found a well known, semisynthetic Hsp90 inhibitor, namely 17-(allylamino)-17-demethoxygeldanamycin, to be effective in attenuating parasite growth and prolonging survival in a mouse model of malaria. We also characterized GA binding to Hsp90 from another protozoan parasite, namely Trypanosoma evansi. We found 17-(allylamino)-17-demethoxygeldanamycin to potently inhibit T. evansi growth in a mouse model of trypanosomiasis. In all, our biochemical characterization, drug interaction, and animal studies supported Hsp90 as a drug target and its inhibitor as a potential drug against protozoan diseases.

Impaired conflict monitoring in Parkinson's disease patients during an oculomotor redirect task

Fallibility is inherent in human cognition and so a system that will monitor performance is indispensable. While behavioral evidence for such a system derives from the finding that subjects slow down after trials that are likely to produce errors, the neural and behavioral characterization that enables such control is incomplete. Here, we report a specific role for dopamine/basal ganglia in response conflict by accessing deficits in performance monitoring in patients with Parkinson's disease. To characterize such a deficit, we used a modification of the oculomotor countermanding task to show that slowing down of responses that generate robust response conflict, and not post-error per se, is deficient in Parkinson's disease patients. Poor performance adjustment could be either due to impaired ability to slow RT subsequent to conflicts or due to impaired response conflict recognition. If the latter hypothesis was true, then PD subjects should show evidence of impaired error detection/correction, which was found to be the case. These results make a strong case for impaired performance monitoring in Parkinson's patients.

Monitoring Fatigue Crack Propagation in Compact Tension Specimens via Remote Sensing of Back Face Strain

Back face strain (BFS) measurement is now well-established as an indirect technique to monitor crack length in compact tension (CT) fracture specimens [1,2]. Previous work [2] developed empirical relations between fatigue crack propagation (FCP) parameters. BFS, and number of cycles for CT specimens subjected to constant amplitude fatigue loading. These predictions are experimentally validated in terms of the variations of mean values of BFS and load as a function of crack length. Another issue raised by this study concerns the validity of assigning fixed values for the Paris parameters C and n to describe FCP in realistic materials.

Ring Resonators and Micro Fluidics: Novel Design for Drug/Disease Detection

MEMS systems are technologically developed from integrated circuit industry to create miniature sensors and actuators. Originally these semiconductor processes and materials were used to build electrical and mechanical systems, but expanded to include biological, optical fluidic magnetic and other systems 12]. Here a novel approach is suggested where in two different fields are integrated via moems, micro fluidics and ring resonators. It is well known at any preliminary stage of disease onset, many physiological changes occur in the body fluids like saliva, blood, urine etc. The drawback till now was that current calibrations are not sensitive enough to detect the minor physiological changes. This is overcome using optical detector techniques 1]. The basic concepts of ring resonators, with slight variations can be used for optical detection of these minute disease markers. A well known fact of ring resonators is that a change in refractive index will trigger a shift in the resonant wavelength 5]. The trigger for the wavelength shift in the case discussed will be the presence of disease agents. To trap the disease agents specific antibody has to be used (e. g. BSA).

Fiber Bragg Grating Sensors for Real Time Monitoring of Evacuation Process

Fiber bragg grating (FBG) sensors have been widely used for number of sensing applications like temperature, pressure, acousto-ultrasonic, static and dynamic strain, refractive index change measurements and so on. Present work demonstrates the use of FBG sensors in in-situ measurement of vacuum process with simultaneous leak detection capability. Experiments were conducted in a bell jar vacuum chamber facilitated with conventional Pirani gauge for vacuum measurement. Three different experiments have been conducted to validate the performance of FBG sensor in monitoring vacuum creating process and air bleeding. The preliminary results of FBG sensors in vacuum monitoring have been compared with that of commercial Pirani gauge sensor. This novel technique offers a simple alternative to conventional method for real time monitoring of evacuation process. Proposed FBG based vacuum sensor has potential applications in vacuum systems involving hazardous environment such as chemical and gas plants, automobile industries, aeronautical establishments and leak monitoring in process industries, where the electrical or MEMS based sensors are prone to explosion and corrosion.

Composite material and piezoelectric coefficient uncertainty effects on structural health monitoring using feedback control gains as damage indicators

This article addresses uncertainty effect on the health monitoring of a smart structure using control gain shifts as damage indicators. A finite element model of the smart composite plate with surface-bonded piezoelectric sensors and actuators is formulated using first-order shear deformation theory and a matrix crack model is integrated into the finite element model. A constant gain velocity/position feedback control algorithm is used to provide active damping to the structure. Numerical results show that the response of the structure is changed due to matrix cracks and this change can be compensated by actively tuning the feedback controller. This change in control gain can be used as a damage indicator for structural health monitoring. Monte Carlo simulation is conducted to study the effect of material uncertainty on the damage indicator by considering composite material properties and piezoelectric coefficients as independent random variables. It is found that the change in position feedback control gain is a robust damage indicator.

Effective drug dosage design for treatment of infectious diseases using dynamic inversion

A generic nonlinear mathematical model describing the human immunological dynamics is used to design an effective automatic drug administration scheme. Even though the model describes the effects of various drugs on the dynamic system, this work is confined to the drugs that kill the invading pathogen and heal the affected organ. From a system theoretic point of view, the drug inputs can be interpreted as control inputs, which can be designed based on control theoretic concepts. The controller is designed based on the principle of dynamic inversion and is found to be effective in curing the �nominal model patient� by killing the invading microbes and healing the damaged organ. A major advantage of this technique is that it leads to a closed-form state feedback form of control. It is also proved from a rigorous mathematical analysis that the internal dynamics of the system remains stable when the proposed controller is applied. A robustness study is also carried out for testing the effectiveness of the drug administration scheme for parameter uncertainties. It is observed from simulation studies that the technique has adequate robustness for many �realistic model patients� having off-nominal parameter values as well.

Comparison of electrical resistivity by geophysical method and neutron probe logging for soil moisture monitoring in a forested watershed

Geophysical methods are becoming more popular nowadays in the field of hydrology due to their time and space efficiency. So an attempt has been made here to relate electrical resistivity with soil moisture content in the field. The experiments were carried out in an experimental watershed `Mulehole' in southern India, which is a forested watershed with approximately 80% red soil. Five auger holes were drilled to perform the soil moisture and electrical resistivity measurements in a toposequence having red and black soils, with sandy weathered soil at the bottom. Soil moisture was measured using neutron probe and electrical resistivity was measured using electrical logging tool. The results indicate that electrical resistivity measurements can be used to measure soil moisture content for red soils only.