Design and fabrication of an automated temperature programmed reaction system to evaluate 3-way catalysts Ce1-x-y(La/Y)(x)PtyO2-delta

A completely automated temperature-programmed reaction (TPR) system for carrying out gas-solid catalytic reactions under atmospheric flow conditions is fabricated to study CO and hydrocarbon oxidation, and NO reduction. The system consists of an all-stainless steel UHV system, quadrupole mass spectrometer SX200 (VG Scientific), a tubular furnace and micro-reactor, a temperature controller, a versatile gas handling system, and a data acquisition and analysis system. The performance of the system has been tested under standard experimental conditions for CO oxidation over well-characterized Ce1-x-y(La/Y)(y)O2-delta catalysts. Testing of 3-way catalysis with CO, NO and C2H2 to convert to CO2, N-2 and H2O is done with this catalyst which shows complete removal of pollutants below 325 degrees C. Fixed oxide-ion defects in Pt substituted Ce1-y(La/Y)(y)O2-y/2 show higher catalytic activity than Pt ion-substituted CeO2.

An automated thermal relaxation calorimeter for operation at low temperature (0.5 K

We describe an automated calorimeter for measurement of specific heat in the temperature range 10 K>T>0.5 K. It uses sample of moderate size (100–1000 mg), has a moderate precision and accuracy (2%–5%), is easy to operate and the measurements can be done quickly with He4 economy. The accuracy of this calorimeter was checked by measurement of specific heat of copper and that of aluminium near its superconducting transition temperature.

Design and fabrication of an automated thermal desorption gas-solid reaction system: Oxidation of ammonia and methanol over YBa2Cu3O7−δ(123) oxide systems

A fully automated, versatile Temperature Programmed Desorption (TDP), Temperature Programmed Reaction (TPR) and Evolved Gas Analysis (EGA) system has been designed and fabricated. The system consists of a micro-reactor which can be evacuated to 10−6 torr and can be heated from 30 to 750°C at a rate of 5 to 30°C per minute. The gas evolved from the reactor is analysed by a quadrupole mass spectrometer (1–300 amu). Data on each of the mass scans and the temperature at a given time are acquired by a PC/AT system to generate thermograms. The functioning of the system is exemplified by the temperature programmed desorption (TPD) of oxygen from YBa2Cu3−xCoxO7 ± δ, catalytic ammonia oxidation to NO over YBa2Cu3O7−δ and anaerobic oxidation of methanol to CO2, CO and H2O over YBa2Cu3O7−δ (Y123) and PrBa2Cu3O7−δ (Pr123) systems.

The use of murine polyclonal anti-idiotypic antibodies as surrogate allergens in the diagnosis of Parthenium hypersensitivity

Background: Anti-idiotypic antibodies (Ab-2), which are the mirror images of idiotypic antibodies (Ab-1), may be useful as diagnostic reagents and for use as immunogen to induce antigen-specific immune responses. Methods and Results: To explore the biologic potential of Ab-2 as diagnostic reagents in allergic diseases, murine mouse (m) Ab-2 were raised by immunizing Balb/c mice with affinity purified rabbit (r) Ab-1 specific for the pollen of Parthenium hysterophorus, an allergenic weed that grows wild on the Indian subcontinent and in Australia, Mexico, and the southern United States. Affinity purified Parthenium-specific human (h)AB-1 could successfully inhibit the binding of mAb-2 to immobilized rAb-1. Further, Balb/c mice immunized with mAb-2 induced Parthenium-specific anti-anti-idiotypic IgE and IgG antibodies. Specificity of the Ab-2 was confirmed by the ability of Parthenium pollen extracts to inhibit the binding of allergen-specific IgE and IgG Ab-1 in the sera of patients with rhinitis to immobilized mAb-2. Parthenium-sensitive patients with rhinitis who had positive results on skin prick tests to Parthenium pollen extracts also responded with a positive skin reaction to mAb-2. Conclusion: Our data demonstrate that Parthenium-specific mAb-2 may be of value as surrogate allergens in allergen standardization and for in vitro diagnosis.

Performability of automated manufacturing systems with centralized material handling

We present a framework for performance evaluation of manufacturing systems subject to failure and repair. In particular, we determine the mean and variance of accumulated production over a specified time frame and show the usefulness of these results in system design and in evaluating operational policies for manufacturing systems. We extend this analysis for lead time as well. A detailed performability study is carried out for the generic model of a manufacturing system with centralized material handling. Several numerical results are presented, and the relevance of performability analysis in resolving system design issues is highlighted. Specific problems addressed include computing the distribution of total production over a shift period, determining the shift length necessary to deliver a given production target with a desired probability, and obtaining the distribution of Manufacturing Lead Time, all in the face of potential subsystem failures.

Automated Multi-Agent Search Using Centroidal Voronoi Configuration

This paper addresses the problem of automated multiagent search in an unknown environment. Autonomous agents equipped with sensors carry out a search operation in a search space, where the uncertainty, or lack of information about the environment, is known a priori as an uncertainty density distribution function. The agents are deployed in the search space to maximize single step search effectiveness. The centroidal Voronoi configuration, which achieves a locally optimal deployment, forms the basis for the proposed sequential deploy and search strategy. It is shown that with the proposed control law the agent trajectories converge in a globally asymptotic manner to the centroidal Voronoi configuration. Simulation experiments are provided to validate the strategy. Note to Practitioners-In this paper, searching an unknown region to gather information about it is modeled as a problem of using search as a means of reducing information uncertainty about the region. Moreover, multiple automated searchers or agents are used to carry out this operation optimally. This problem has many applications in search and surveillance operations using several autonomous UAVs or mobile robots. The concept of agents converging to the centroid of their Voronoi cells, weighted with the uncertainty density, is used to design a search strategy named as sequential deploy and search. Finally, the performance of the strategy is validated using simulations.

Antigen detection assay with parasite specific monoclonal antibodies for diagnosis of lymphatic filariasis

Background: Lymphatic filariasis is a painful and profoundly disfiguring disease. Infection is usually acquired in childhood but its visible manifestations occur later in life, causing temporary or permanent disability. The importance of developing effective assays to diagnose, monitor and evaluate human lymphatic filariasis has been emphasized by the WHO. Methods: High-affinity monoclonal antibodies (mAbs) specific for recombinant filarial antigen WbSXP-1 were developed. An ELISA based capture assay using monoclonal and polyclonal antibodies for WbSXP-1 was used for detection of circulating filarial antigen. Results: High-affinity monoclonal antibodies (mAbs) were developed that specifically binds both W. bancrofti and B. malayi mf antigens. Two mAbs (1F6H3 and 2E12E3) of subclass IgG2a and IgM showed high affinity, avidity and reactivity to recombinant and mf native antigen. Both the mAbs were used in combination as capture antibodies and polyclonal as detection antibody to develop the assay. The assay showed very high sensitivity towards W. bancrofti mf positive samples compared to endemic normal samples (P<0.0001). Conclusion: A capture assay using high-affinity monoclonal antibodies for WbSXP-1 was developed for the detection of filarial circulating antigen in clinical samples from bancroftian infection. Besides, this would also help in epidemiological studies in endemic areas of filarial infections. (C) 2011 Elsevier B.V. All rights reserved.

Coloured Petri net models for automated manufacturing systems

In this paper, we propose an approach, using Coloured Petri Nets (CPN) for modelling flexible manufacturing systems. We illustrate our methodology for a Flexible Manufacturing Cell (FMC) with three machines and three robots. We also consider the analysis of the FMC for deadlocks using the invariant analysis of CPNs.

mRegistry: a registry representation for fault diagnosis

Microsoft Windows uses the notion of registry to store all configuration information. The registry entries have associations and dependencies. For example, the paths to executables may be relative to some home directories. The registry being designed with faster access as one of the objectives does not explicitly capture these relations. In this paper, we explore a representation that captures the dependencies more explicitly using shared and unifying variables. This representation, called mRegistry exploits the tree-structured hierarchical nature of the registry, is concept-based and obtained in multiple stages. mRegistry captures intra-block, inter-block and ancestor-children dependencies (all leaf entries of a parent key in a registry put together as an entity constitute a block thereby making the block as the only child of the parent). In addition, it learns the generalized concepts of dependencies in the form of rules. We show that mRegistry has several applications: fault diagnosis, prediction, comparison, compression etc.

Intelligent Approach for Fault Diagnosis in Power Transmission Systems Using Support Vector Machines

This paper presents an approach for identifying the faulted line section and fault location on transmission systems using support vector machines (SVMs) for diagnosis/post-fault analysis purpose. Power system disturbances are often caused by faults on transmission lines. When fault occurs on a transmission system, the protective relay detects the fault and initiates the tripping operation, which isolates the affected part from the rest of the power system. Based on the fault section identified, rapid and corrective restoration procedures can thus be taken to minimize the power interruption and limit the impact of outage on the system. The approach is particularly important for post-fault diagnosis of any mal-operation of relays following a disturbance in the neighboring line connected to the same substation. This may help in improving the fault monitoring/diagnosis process, thus assuring secure operation of the power systems. In this paper we compare SVMs with radial basis function neural networks (RBFNN) in data sets corresponding to different faults on a transmission system. Classification and regression accuracy is reported for both strategies. Studies on a practical 24-Bus equivalent EHV transmission system of the Indian Southern region is presented for indicating the improved generalization with the large margin classifiers in enhancing the efficacy of the chosen model.

Active-contour-based automated image quantitation techniques for Western Blot analysis

Western Blot analysis is an analytical technique used in Molecular Biology, Biochemistry, Immunogenetics and other Molecular Biology studies to separate proteins by electrophoresis. The procedure results in images containing nearly rectangular-shaped blots. In this paper, we address the problem of quantitation of the blots using automated image processing techniques. We formulate a special active contour (or snake) called Oblong, which locks on to rectangular shaped objects. Oblongs depend on five free parameters, which is also the minimum number of parameters required for a unique characterization. Unlike many snake formulations, Oblongs do not require explicit gradient computations and therefore the optimization is carried out fast. The performance of Oblongs is assessed on synthesized data and Western Blot Analysis images.

A LSQR-type method provides a computationally efficient automated optimal choice of regularization parameter in diffuse optical tomography

Purpose: Developing a computationally efficient automated method for the optimal choice of regularization parameter in diffuse optical tomography. Methods: The least-squares QR (LSQR)-type method that uses Lanczos bidiagonalization is known to be computationally efficient in performing the reconstruction procedure in diffuse optical tomography. The same is effectively deployed via an optimization procedure that uses the simplex method to find the optimal regularization parameter. The proposed LSQR-type method is compared with the traditional methods such as L-curve, generalized cross-validation (GCV), and recently proposed minimal residual method (MRM)-based choice of regularization parameter using numerical and experimental phantom data. Results: The results indicate that the proposed LSQR-type and MRM-based methods performance in terms of reconstructed image quality is similar and superior compared to L-curve and GCV-based methods. The proposed method computational complexity is at least five times lower compared to MRM-based method, making it an optimal technique. Conclusions: The LSQR-type method was able to overcome the inherent limitation of computationally expensive nature of MRM-based automated way finding the optimal regularization parameter in diffuse optical tomographic imaging, making this method more suitable to be deployed in real-time. (C) 2013 American Association of Physicists in Medicine. http://dx.doi.org/10.1118/1.4792459]

An automated approach to network features of protein structure ensembles

Network theory applied to protein structures provides insights into numerous problems of biological relevance. The explosion in structural data available from PDB and simulations establishes a need to introduce a standalone-efficient program that assembles network concepts/parameters under one hood in an automated manner. Herein, we discuss the development/application of an exhaustive, user-friendly, standalone program package named PSN-Ensemble, which can handle structural ensembles generated through molecular dynamics (MD) simulation/NMR studies or from multiple X-ray structures. The novelty in network construction lies in the explicit consideration of side-chain interactions among amino acids. The program evaluates network parameters dealing with topological organization and long-range allosteric communication. The introduction of a flexible weighing scheme in terms of residue pairwise cross-correlation/interaction energy in PSN-Ensemble brings in dynamical/chemical knowledge into the network representation. Also, the results are mapped on a graphical display of the structure, allowing an easy access of network analysis to a general biological community. The potential of PSN-Ensemble toward examining structural ensemble is exemplified using MD trajectories of an ubiquitin-conjugating enzyme (UbcH5b). Furthermore, insights derived from network parameters evaluated using PSN-Ensemble for single-static structures of active/inactive states of 2-adrenergic receptor and the ternary tRNA complexes of tyrosyl tRNA synthetases (from organisms across kingdoms) are discussed. PSN-Ensemble is freely available from http://vishgraph.mbu.iisc.ernet.in/PSN-Ensemble/psn_index.html.