Characterization of substrate UpA binding to RNase A--computer modelling and energetics approach.

In the past two decades RNase A has been the focus of diverse investigations in order to understand the nature of substrate binding and to know the mechanism of enzyme action. Although this system is reasonably well characterized from the view point of some of the binding sites, the details of interactions in the second base binding (B2) site is insufficient. Further, the nature of ligand-protein interaction is elucidated generally by studies on RNase A-substrate analog complexes (mainly with the help of X-ray crystallography). Hence, the details of interactions at atomic level arising due to substrates are inferred indirectly. In the present paper, the dinucleotide substrate UpA is fitted into the active site of RNase A Several possible substrate conformations are investigated and the binding modes have been selected based on Contact Criteria. Thus identified RNase A-UpA complexes are energy minimized in coordinate space and are analysed in terms of conformations, energetics and interactions. The best possible ligand conformations for binding to RNase A are identified by experimentally known interactions and by the energetics. Upon binding of UpA to RNase A the changes associated,with protein back bone, Side chains in general and at the binding sites in particular are described. Further, the detailed interactions between UpA and RNase A are characterized in terms of hydrogen bonds and energetics. An extensive study has helped in interpreting the diverse results obtained from a number of experiments and also in evaluating the extent of changes the protein and the substrate undergo in order to maximize their interactions.

Modelling of a batch sonochemical reactor

Ultrasonication of aqueous KI solution is known to yield I2 due to reaction of iodide ions with hydroxyl radicals, which in turn are generated due to cavitation. Based on this conceptual framework, a model has been developed to predict the rate of iodine formation for KI solutions of various concentrations under different gas atmospheres. The model follows the growth and collapse of a gas—vapour cavity using the Rayleigh—Plesset bubble dynamics equation. The bubble is assumed to behave isothermally during its growth phase and a part of the collapse phase. Thereafter it is assumed to collapse adiabatically, yielding high temperatures and pressures. Thermodynamic equilibrium is assumed in the bubble at the end of collapse phase. The contents of the bubble are assumed to mix with the liquid, and the reactor contents are assumed to be well stirred. The model has been verified by conducting experiments with KI solutions of different concentrations and using different gas atmospheres. The model not only explains these results but also the existence of a maximum when Ar---O2 mixtures of different compositions are employed.

Modelling of a batch sonochemical reactor

Ultrasonication of aqueous KI solution is known to yield I2 due to reaction of iodide ions with hydroxyl radicals, which in turn are generated due to cavitation. Based on this conceptual framework, a model has been developed to predict the rate of iodine formation for KI solutions of various concentrations under different gas atmospheres. The model follows the growth and collapse of a gas-vapour cavity using the Rayleigh-Plesset bubble dynamics equation. The bubble is assumed to behave isothermally during its growth phase and a part of the collapse phase. Thereafter it is assumed to collapse adiabatically, yielding high temperatures and pressures. Thermodynamic equilibrium is assumed in the bubble at the end of collapse phase. The contents of the bubble are assumed to mix with the liquid, and the reactor contents are assumed to be well stirred. The model has been verified by conducting experiments with KI solutions of different concentrations and using different gas atmospheres. The model not only explains these results but also the existence of a maximum when Ar-O2 mixtures of different compositions are employed.

Reactions of palladium chloride with amino spirocyclic cyclotriphosphazenes: Isolation and Crystal Structures of Novel Mono- and Bimetallic Complexes Formed by the Hydrolysis of a .lambda.5-Diazaphospholane Ring

The reaction of the amino spirocyclic cyclotriphosphazene N3P3(NMe2)4(NHCH2CH2CH2NH) (2) with palladium chloride gives the stable chelate complex [PdCl2.2] (4). An X-ray crystallographic study reveals that one of the nitrogen atoms of the diaminoalkane moiety and an adjacent phosphazene ring nitrogen atom are bonded to the metal. An analogous reaction with the phosphazene N3P3(NMe2)4(NHCH2CH2NH) (1) gives initially a similar complex which undergoes facile hydrolysis to give the novel monometallic and bimetallic complexes [PdCl2.HN3P3(O)(NMe2)4(NHCH2CH2NH2)] (5) and [PdCl{N3P3(NMe2)4(NCH2CH2NH2)}]2(O) (6), which have been structurally characterized; in the former, an (oxophosphazadienyl)ethylenediamine is chelated to the metal whereas, in the latter, an oxobridged bis(cyclotriphosphazene) acts as a hexadentate nitrogen donor ligand in its dianionic form. Crystal data for 4 : a = 14.137(1) angstrom, b = 8.3332(5) angstrom, c = 19.205(2) angstrom, beta = 96.108(7)degrees, P2(1)/c, Z = 4, R = 0.027 with 3090 reflections (F > 5sigma(F)). Crystal data for 5 : a = 8.368(2) angstrom, b = 16.841(4) A, c = 16.092(5) angstrom, beta = 98.31(2)degrees, P2(1)/n, Z = 4, R = 0.049 with 3519 reflections (F > 5sigma(F)). Crystal data for 6 : a = 22.455(6) angstrom, b = 14.882(3) angstrom, c = 13.026(5) angstrom, 6 = 98.55(2)degrees, C2/c, Z = 4, R = 0.038 with 3023 reflections (F > 5sigma(F)).

Machine learning modelling for predicting soil liquefaction susceptibility

This study describes two machine learning techniques applied to predict liquefaction susceptibility of soil based on the standard penetration test (SPT) data from the 1999 Chi-Chi, Taiwan earthquake. The first machine learning technique which uses Artificial Neural Network (ANN) based on multi-layer perceptions (MLP) that are trained with Levenberg-Marquardt backpropagation algorithm. The second machine learning technique uses the Support Vector machine (SVM) that is firmly based on the theory of statistical learning theory, uses classification technique. ANN and SVM have been developed to predict liquefaction susceptibility using corrected SPT (N-1)(60)] and cyclic stress ratio (CSR). Further, an attempt has been made to simplify the models, requiring only the two parameters (N-1)(60) and peck ground acceleration (a(max)/g)], for the prediction of liquefaction susceptibility. The developed ANN and SVM models have also been applied to different case histories available globally. The paper also highlights the capability of the SVM over the ANN models.

Joining of dissimilar metals: issues and modelling techniques

Joining of dissimilar metals involves a number of scientific issues, the modelling of which offers unique challenges. This review discusses the complexities in different joining processes and dissimilar combinations, and the corresponding computational techniques that have the potential to address the same. Future directions in modelling at both macroscopic and microscopic scales are also suggested.

Stochastic modelling of flexible manufacturing systems

Mathematical modelling plays a vital role in the design, planning and operation of flexible manufacturing systems (FMSs). In this paper, attention is focused on stochastic modelling of FMSs using Markov chains, queueing networks, and stochastic Petri nets. We bring out the role of these modelling tools in FMS performance evaluation through several illustrative examples and provide a critical comparative evaluation. We also include a discussion on the modelling of deadlocks which constitute an important source of performance degradation in fully automated FMSs.

Thermal expansion of irradiated polyvinyl chloride from 10 K to 340 K

The coefficient of thermal expansion is measured for irradiated Polyvinyl Chloride (PVC) from 10K to 340K. The samples of PVC are irradiated, up to 500 Mrad in steps of 100 Mrad, in air at room temperature by using Co gamma rays with a dose rate of 0.3 Mrad/h. The PVC is an amorphous sample which is confirmed by X-ray diffraction. The coefficient of thermal expansion is found to decrease with radiation dose from 10K to 110K and it increaseswith radiation dose from 110K to 340K. The results are explained on the basis of radiation induced degradation of the sample.

Thermodynamic modelling of absorption-resorption heating cycles with some new working pairs

This paper presents the results of a thermodynamic cycle analysis of single stage resorption heat pump (RHP) and resorption heat transformer (RHT) cycles with the new working pairs R22-NMP and R22-DMA. The coefficients of performance (COP) are correlated with the low grade source temperature, temperature at which useful heat is obtained and ambient temperature. The COPs are in the range 1.20–1.60 for the RHP mode and 0.25–0.45 for the RHT mode. Absorber temperatures (useful temperatures) as high as 50°C in the RHP mode and 87°C in the RHT mode have been obtained. It is observed that absorption-resorption systems are inflexible in their range of operating temperature and necessitate a higher pump work as compared with simple single-stage absorption heating systems. However, single stage RHTs show higher temperature boosts than simple absorption heat transformers.

Mathematical modelling of neurons and neural networks

The basic concepts and techniques involved in the development and analysis of mathematical models for individual neurons and networks of neurons are reviewed. Some of the interesting results obtained from recent work in this field are described. The current status of research in this field in India is discussed

Modelling plane mixing layers using vortex points and sheets

We present here a critical assessment of two vortex approaches (both two-dimensional) to the modelling of turbulent mixing layers. In the first approach the flow is represented by point vortices, and in the second it is simulated as the evolution of a continuous vortex sheet composed of short linear elements or ''panels''. The comparison is based on fresh simulations using approximately the same number of elements in either model, paying due attention in both to the boundary conditions far downstream as well as those on the splitter plate from which the mixing layer issues. The comparisons show that, while both models satisfy the well-known invariants of vortex dynamics approximately to the same accuracy, the vortex panel model, although ultimately not convergent, leads to smoother roll-up and values of stresses and moments that are in closer agreement with the experiment, and has a higher computational efficiency for a given degree of convergence on moments. The point vortex model, while faster for a given number of elements, produces an unsatisfactory roll-up which (for the number of elements used) is rendered worse by the incorporation of the Van der Vooren correction for sheet curvature.

Mathematical modelling of divided blast cupola

A pseudo 2-D mathematical model has been developed to simulate a cupola with one row and two rows of tuyere. The simulation results predicted higher spout temperature and combustion ratio for cupola with two rows of tuyere compared to that with one row. Further, the model has been used to study the effect of the distance of separation between the two rows of tuyere on cupola performance. The computed results shows that the spout temperature increases with tuyere level separation and attains the maximum at an optimum distance of separation between two rows of tuyere. Above the optimum, the spout temperature starts decreasing. The exit gas temperature and combustion ratio increases monotonously with the increase in tuyere level separation. These results agree well with the reported experimental observations. The mechanism behind the improved cupola performance with two rows of tuyere has been deduced from the computed temperature and composition profiles inside the cupola.

Modelling transport processes during microwave heating: A review

The review is concerned with models that analyze transport:processes that occur during microwave heating. Early models on microwave. heating used Lambert's law to describe the microwave power absorption. Over the last decade, models for transport processes have been developed with the microwave power derived from Maxwell's equations. Those models, primarily based on plane waves, have been used for analyzing microwave heating of solids, liquids, emulsions, microwave thawing and drying. The models illustrate phenomena such a resonances, hot spots, edge and runaway heating. The literature on microwave sintering, susceptor heating and microwave assisted synthesis is largely experimental in nature and only key issues are highlighted. To fully appreciate the models for microwave heating, a section on the theory of electromagnetic wave propagation is included, where expressions for the electric field in dielectric slabs and cylinders are presented.

A molecular dynamics study and molecular level explanation of pressure dependence of ionic conductivity of potassium chloride in water

Experimental ionic conductivity of different alkali ions in water shows markedly different dependences on pressure. Existing theories such as that of Hubbard-Onsager are unable to explain these dependences on pressure of the ionic conductivity for all ions. We report molecular dynamics investigation of potassium chloride solution at low dilution in water at several pressures between 1 bar and 2 kbar. Two different potential models have been employed. One of the models successfully reproduces the experimentally observed trend in ionic conductivity of K+ ions in water over the 0.001-2 kbar range. We also propose a theoretical explanation, albeit at a qualitative level, to account for the dependence of ionic conductivity on pressure in terms of the previously studied Levitation Effect. It also provides a microscopic picture in terms of the pore network in liquid water.