Action of N-bromosuccinimide on sperm whale myoglobin

Previously, it was reported from this laboratory that the heme groups of hemoglobin are “buried” within globin at pH 4.0 and not dissociated, on the basis of the obiligatory requirement of urea for the reaction of N-bromosuccinimide with the heme groups of hemoglobin at pH4.0, and also on the basis of the “normalization” of the spectrum of hemoglobin at this pH in the presence of urea or sucrose. In the present study, it has been shown that the behaviour of sperm whale myoglobin with respect to its reaction with N-bromosuccinimide and with respect to spectral “normalization” in urea or sucrose are essentially similar to that of hemoglobin. It has also been demonstrated that the spectral “normalization” obtained with crystalline hemin is not identical with that obtained with either hemoglobin or myoglobin. The bearing of the results of the present study on the earlier work on hemoglobin is indicated.

Action of N-bromosuccinimide on human hemoglobin and its possible bearing on heme-globin linkage

A reaction of N-bromosuccinimide with the heme groups of hemoglobin has been studied spectrophotometrically. The reaction brings about the disappearance of characteristic absorption peaks of hemoglobin and is accompanied by the release of inorganic iron from the heme groups. Urea is obligatory for the reaction to take place at pH 4.0, while it can occur in the absence of urea at pH 7.0. The spectrum of hemoglobin which does not show any peak in the Soret region at pH 4.0 is “normalized” in the presence of urea or sucrose at the same pH. The effect of “normalization” in 8 M urea is apparent over the pH range 3.0–4.5. From the obligatory requirement of urea and sucrose for “normalization” of spectrum and the dependence of the release of inorganic iron on the concentration of urea, it is suggested that heme groups are “buried” within the globin at pH 4.0 and not dissociated from globin as supposed before.

Studies in sesquiterpenes-XIX. Action of perbenzoic acid on longifolene

Oxidation of longifolene, a mono-olefinic sesquiterpene, with a chloroform solution of perbenzoic acid proceeded to almost two mole consumption of the peracid to furnish a number of products, important ones being an α-ketol, a norketone (longicamphenilone) and the corresponding C14-alcohols. Under certain conditions it has been possible to arrest the reaction at one mole consumption and to isolate longifolene-α-epoxide, which is the major product; some amounts of epimeric longifolaldehydes and longicamphenilone were also formed. Further action of perbenzoic acid on longifolene oxide and longifolaldehydes has been investigated and the results used to interpret the mechanism of abnormal peracid oxidation of longifolene.

Prediction of solid block masonry prism compressive strength using FE model

Masonry strength is dependent upon characteristics of the masonry unit,the mortar and the bond between them. Empirical formulae as well as analytical and finite element (FE) models have been developed to predict structural behaviour of masonry. This paper is focused on developing a three dimensional non-linear FE model based on micro-modelling approach to predict masonry prism compressive strength and crack pattern. The proposed FE model uses multi-linear stress-strain relationships to model the non-linear behaviour of solid masonry unit and the mortar. Willam-Warnke's five parameter failure theory developed for modelling the tri-axial behaviour of concrete has been adopted to model the failure of masonry materials. The post failure regime has been modelled by applying orthotropic constitutive equations based on the smeared crack approach. Compressive strength of the masonry prism predicted by the proposed FE model has been compared with experimental values as well as the values predicted by other failure theories and Eurocode formula. The crack pattern predicted by the FE model shows vertical splitting cracks in the prism. The FE model predicts the ultimate failure compressive stress close to 85 of the mean experimental compressive strength value.

Indoleacetaldoxime hydro-lyase (4.2.1.29). III. Further studies on the nature and mode of action of the enzyme

Further purification of indoleacetaldoxime (IAOX) hydro-lyase from Gibberella fujikuroi by DEAE-cellulose chromatography is described. The purified enzyme was activated by dehydroascorbic acid (DHA), ascorbic acid (AA), and pyridoxal phosphate (PALP) and was inhibited by thiol compounds and thiol reagents including phenylthiocyanate. Ferrous ions but not ferric ions activated the purified enzyme. The enzyme was activated by dihydrofolic acid but inhibited by tetrahydrofolic acid. Phenylacetaldoxime, a competitive inhibitor, afforded partial protection of the enzyme from the action of N-ethylmaleimide suggesting the involvement of a thiol function at the active site or substrate-binding site. The inhibition of the enzyme by 2,3-dimercaptopropanol was reversed by DHA, PALP, or frozen storage. KCN inhibition of the enzyme was reversed by PALP. NaBH4 reduction of the purified enzyme in the presence of PALP gave an active enzyme which was further activated by PALP or DHA but not by ferrous ions. These results suggested a "structural" role for PALP in the activity of IAOX hydro-lyase. Dilute solutions of the purified enzyme, obtained during DEAE-cellulose chromatography and concentrated using sucrose, showed enhanced activity upon frozen storage and thawing. The increase in activity of the enzyme during certain culture conditions, the activation and inhibition of the enzyme by several unrelated compounds, and the effect of freezing indicate that IAOX hydro-lyase is probably a metabolically regulated enzyme with a structure composed of subunits.

Prediction of swelling pressure of soil using artificial intelligence techniques

The swelling pressure of soil depends upon various soil parameters such as mineralogy, clay content, Atterberg's limits, dry density, moisture content, initial degree of saturation, etc. along with structural and environmental factors. It is very difficult to model and analyze swelling pressure effectively taking all the above aspects into consideration. Various statistical/empirical methods have been attempted to predict the swelling pressure based on index properties of soil. In this paper, the computational intelligence techniques artificial neural network and support vector machine have been used to develop models based on the set of available experimental results to predict swelling pressure from the inputs; natural moisture content, dry density, liquid limit, plasticity index, and clay fraction. The generalization of the model to new set of data other than the training set of data is discussed which is required for successful application of a model. A detailed study of the relative performance of the computational intelligence techniques has been carried out based on different statistical performance criteria.

Prediction of swelling pressure of soil using artificial intelligence techniques

The swelling pressure of soil depends upon various soil parameters such as mineralogy, clay content, Atterberg's limits, dry density, moisture content, initial degree of saturation, etc. along with structural and environmental factors. It is very difficult to model and analyze swelling pressure effectively taking all the above aspects into consideration. Various statistical/empirical methods have been attempted to predict the swelling pressure based on index properties of soil. In this paper, the computational intelligence techniques artificial neural network and support vector machine have been used to develop models based on the set of available experimental results to predict swelling pressure from the inputs; natural moisture content, dry density, liquid limit, plasticity index, and clay fraction. The generalization of the model to new set of data other than the training set of data is discussed which is required for successful application of a model. A detailed study of the relative performance of the computational intelligence techniques has been carried out based on different statistical performance criteria.

Framework for enabling highly available distributed applications for utility computing

The move towards IT outsourcing is the first step towards an environment where compute infrastructure is treated as a service. In utility computing this IT service has to honor Service Level Agreements (SLA) in order to meet the desired Quality of Service (QoS) guarantees. Such an environment requires reliable services in order to maximize the utilization of the resources and to decrease the Total Cost of Ownership (TCO). Such reliability cannot come at the cost of resource duplication, since it increases the TCO of the data center and hence the cost per compute unit. We, in this paper, look into aspects of projecting impact of hardware failures on the SLAs and techniques required to take proactive recovery steps in case of a predicted failure. By maintaining health vectors of all hardware and system resources, we predict the failure probability of resources based on observed hardware errors/failure events, at runtime. This inturn influences an availability aware middleware to take proactive action (even before the application is affected in case the system and the application have low recoverability). The proposed framework has been prototyped on a system running HP-UX. Our offline analysis of the prediction system on hardware error logs indicate no more than 10% false positives. This work to the best of our knowledge is the first of its kind to perform an end-to-end analysis of the impact of a hardware fault on application SLAs, in a live system.

Robust prediction of residual velocities and ballistic limits of projectiles for impact on thin aluminium plates

This paper deals with the simulation-driven study of the impact of hardened steel projectiles on thin aluminium target plates using explicit finite element analysis as implemented in LS-DYNA. The evaluation of finite element modelling includes a comprehensive mesh convergence study using shell elements for representing target plates and the solid element-based representation of ogivalnosed projectiles. A user-friendly automatic contact detection algorithm is used for capturing interaction between the projectile and the target plate. It is shown that the proper choice of mesh density and strain rate-dependent material properties is crucial as these parameters significantly affect the computed residual velocity. The efficacy of correlation with experimental data is adjudged in terms of a 'correlation index' defined in the present study for which values close to unity are desirable.By simulating laboratory impact tests on thin aluminium plates carried out by earlier investigators, extremely good prediction of experimental ballistic limits has been observed with correlation indices approaching unity. Additional simulation-based parametric studies have been carried out and results consistent with test data have been obtained. The simulation procedures followed in the present study can be applied with confidence in designing thin aluminium armour plates for protection against low calibre projectiles.

Prediction of inplane damping from deterministic and stochastic models

This paper reviews computational reliability, computer algebra, stochastic stability and rotating frame turbulence (RFT) in the context of predicting the blade inplane mode stability, a mode which is at best weakly damped. Computational reliability can be built into routine Floquet analysis involving trim analysis and eigenanalysis, and a highly portable special purpose processor restricted to rotorcraft dynamics analysis is found to be more economical than a multipurpose processor. While the RFT effects are dominant in turbulence modeling, the finding that turbulence stabilizes the inplane mode is based on the assumption that turbulence is white noise.

Intelligent prediction of the stress-strain response of intact and jointed rocks

An application of Artificial Neural Networks for predicting the stress-strain response of jointed rocks under different confining pressures is presented in this paper. Rocks of different compressive strength with different joint properties (frequency, orientation and strength of joints) are considered in this study. The database for training the neural network is formed from the results of triaxial compression tests on different intact and jointed rocks with different joint properties tested at different confining pressures reported by various researchers in the literature. The network was trained using a three-layered network with the feed-forward back propagation algorithm.About 85% of the data was used for training and the remaining 15% was used for testing the network. Results from the analyses demonstrated that the neural network approach is effective in capturing the stress-strain behaviour of intact rocks and the complex stress-strain behaviour of jointed rocks. A single neural network is demonstrated to be capable of predicting the stress-strain response of different jointed rocks, whose intact strength varies from 11.32 MPa to 123 MPa, spacing of joints varies from 10 cm to 100 cm. and confining pressures range from 0 to 13.8 MPa. (C) 2010 Elsevier Ltd. All rights reserved.

Prediction of breakout noise from an elliptical duct of finite length

This paper describes a predictive model for breakout noise from an elliptical duct or shell of finite length. The transmission mechanism is essentially that of ``mode coupling'', whereby higher structural modes in the duct walls get excited because of non-circularity of the wall. Effect of geometry has been taken care of by evaluating Fourier coefficients of the radius of curvature. The noise radiated from the duct walls is represented by that from a finite vibrating length of a semi infinite cylinder in a free field. Emphasis is on understanding the physics of the problem as well as analytical modeling. The analytical model is validated with 3-D FEM. Effects of the ovality, curvature, and axial terminations of the duct have been demonstrated. (C) 2010 Institute of Noise Control Engineering.