Diacylglycerol Kinase Is Stimulated by Arachidonic Acid in Neural Membranes.

The effect of arachidonic acid (AA) on the activity of diacylglycerol (DG) kinase in neural membranes was investigated. When rat brain cortical membranes were incubated with 0.5 mM dipalmitin and [gamma-P-32]ATP, formation of phosphatidic acid (PA) was observed. It was linear up to 5 min, and the initial rate was similar to 1.0 nmol/min/mg of protein. The DG kinase activity was stimulated twofold by 0.25 mM AA. The stimulation was apparent at the earliest time point measured (1 min) and with the lowest concentration of AA tested (62.5 mu M). The stimulation was proportional to the concentration of AA up to 250 mu M. AA was the most potent stimulator of DG kinase, and linolenic acid showed similar to 40% stimulation. Oleic acid showed no effect, whereas linoleic and the saturated fatty acids tested were inhibitory. AA stimulation of DG kinase was observed only with membranes of cerebrum, cerebellum, and myelin and not with brain cytosol or liver membranes. AA also stimulated the formation of PA in the absence of added dipalmitin (endogenous activity) with membranes prepared from whole brain. DG kinase of neural membranes was extracted with 2 M NaCl, which on dialysis yielded a precipitate. Both the precipitate and the supernatant showed DG kinase activity, but only the enzyme in the precipitate was stimulated by AA at concentrations as low as 25 mu M. It is suggested that AA, through its effect on DG kinase, regulates the level of DG in neural membranes, which in turn regulates protein kinase C activity.

Digital simulation of galvanostatic current-potential data for gas-diffusion electrodes and estimation of electrodekinetic parameters

A computerized non-linear-least-squares regression procedure to analyse the galvanostatic current-potential data for kinetically hindered reactions on porous gas-diffusion electrodes is reported. The simulated data fit well with the corresponding measured values. The analytical estimates of electrode-kinetic parameters and uncompensated resistance are found to be in good agreement with their respective values obtained from Tafel plots and the current-interrupter method. The procedure circumvents the need to collect the data in the limiting-current region where the polarization values are usually prone to errors. The polarization data for two typical cases, namely, methanol oxidation on a carbon-supported platinum-tin electrode and oxygen reduction on a Nafion-coated platinized carbon electrode, are successfully analysed.

Exact Solution of a One-Dimensional Multicomponent Lattice Gas with Hyperbolic Interaction

We present the exact solution to a one-dimensional multicomponent quantum lattice model interacting by an exchange operator which falls off as the inverse sinh square of the distance. This interaction contains a variable range as a parameter and can thus interpolate between the known solutions for the nearest-neighbor chain and the inverse-square chain. The energy, susceptibility, charge stiffness, and the dispersion relations for low-lying excitations are explicitly calculated for the absolute ground state, as a function of both the range of the interaction and the number of species of fermions.

PVU and wave-particle splitting schemes for Euler equations of gas dynamics

A new way of flux-splitting, termed as the wave-particle splitting is presented for developing upwind methods for solving Euler equations of gas dynamics. Based on this splitting, two new upwind methods termed as Acoustic Flux Vector Splitting (AFVS) and Acoustic Flux Difference Splitting (AFDS) methods are developed. A new Boltzmann scheme, which closely resembles the wave-particle splitting, is developed using the kinetic theory of gases. This method, termed as Peculiar Velocity based Upwind (PVU) method, uses the concept of peculiar velocity for upwinding. A special feature of all these methods that the unidirectional and multidirectional parts of the flux vector are treated separately. Extensive computations done using these schemes demonstrate the soundness of the ideas.

Crossover dynamics at large metastability in gas-liquid nucleation

We have developed an alternate description of dynamics of nucleation in terms of an extended set of order parameters. The order parameters consist of an ordered set of kth largest clusters, ordered such that k = 1 is the largest cluster in the system, k = 2 is the second largest cluster, and so on. We have derived an analytic expression for the free energy for the kth largest cluster, which is in excellent agreement with the simulated results. At large supersaturation, the free energy barrier for the growth of the kth largest cluster disappears and the nucleation becomes barrierless. The major success of this extended theoretical formalism is that it can clearly explain the observed change in mechanism at large metastability P. Bhimalapuram et al., Phys. Rev. Lett. 98, 206104 (2007)] and the associated dynamical crossover. The classical nucleation theory cannot explain this crossover. The crossover from activated to barrierless nucleation is found to occur at a supersaturation where multiple clusters cross the critical size. We attribute the crossover as the onset of the kinetic spinodal. We have derived an expression for the rate of nucleation in the barrierless regime by modeling growth as diffusion on the free energy surface of the largest cluster. The model reproduces the slower increase in the rate of growth as a function of supersaturation, as observed in experiments.

Reaction of normal and pseudo 2-formylbenzenesulfonyl chlorides with amines:experimental and theoretical studies on the structure of 2-formyl benzenesulfonamides in solid, solution and gas phases

The reaction of 2-formylbenzenesulfonyl chloride 1 and its pseudo isomer 2 with primary amines give either the corresponding sulfonamido Schiff bases or the corresponding 2-formylbenzenesulfonamide depending on the concentration of the amine used. The derivatives exist as an equilibrium mixture of the corresponding sulfonamide and 2-alkyl-3-hydroxy(or 3-aminoalkyl)-benzisothiazole-1,1-dioxide. Spectroscopic studies suggest that 2-formylbenzenesulfonamides exist as benzisothiazole-1,1-dioxides in the solid state, as a mixture of 2-formylbenzenesulfonamide and the corresponding benzisothiazole-1,1-dioxide in solution and as 2-formyl-benzenesulfonamides in the gas phase.

Robust/Optimal Temperature Profile Control of a High-Speed Aerospace Vehicle Using Neural Networks

An approximate dynamic programming (ADP)-based suboptimal neurocontroller to obtain desired temperature for a high-speed aerospace vehicle is synthesized in this paper. A I-D distributed parameter model of a fin is developed from basic thermal physics principles. "Snapshot" solutions of the dynamics are generated with a simple dynamic inversion-based feedback controller. Empirical basis functions are designed using the "proper orthogonal decomposition" (POD) technique and the snapshot solutions. A low-order nonlinear lumped parameter system to characterize the infinite dimensional system is obtained by carrying out a Galerkin projection. An ADP-based neurocontroller with a dual heuristic programming (DHP) formulation is obtained with a single-network-adaptive-critic (SNAC) controller for this approximate nonlinear model. Actual control in the original domain is calculated with the same POD basis functions through a reverse mapping. Further contribution of this paper includes development of an online robust neurocontroller to account for unmodeled dynamics and parametric uncertainties inherent in such a complex dynamic system. A neural network (NN) weight update rule that guarantees boundedness of the weights and relaxes the need for persistence of excitation (PE) condition is presented. Simulation studies show that in a fairly extensive but compact domain, any desired temperature profile can be achieved starting from any initial temperature profile. Therefore, the ADP and NN-based controllers appear to have the potential to become controller synthesis tools for nonlinear distributed parameter systems.

Thermal degradation products of poly(styrenesulfides) investigated by direct pyrolysis�mass spectrometry and flash pyrolysis�gas chromatography/mass spectrometry

The thermal degradation products of two sulfur polymers, poly(styrenedisulfide) (PSD) and poly(styrenetetrasulfide) (PST), were investigated in parallel by direct pyrolysis-mass spectrometry (DPMS) and by flash pyrolysis-GC/MS (Py-GC/MS). The time-scale of the two pyrolysis techniques is quite different, and therefore they were able to detect significantly different products in the pyrolysis of PSD and PST because of the thermal lability of sulfur-containing compounds. However, the results obtained are not contradictory, and satisfactory mechanisms for the thermal degradation of PSD and PST have been derived from the overall evidence available. Pyrolysis compounds containing sulfur, styrene, and a number of cyclic styrene sulfides and diphenyldithianes have been observed by DPMS. However, in flash pyrolysis-GC/MS, styrene, sulfur, only one cyclic styrene sulfide, and two isomers of diphenylthiophene have been detected. These thiophene derivatives were indeed absent among the compounds obtained by DPMS because they were the terminal (most thermally stable) species arising from further decomposition of the cyclic styrene sulfides formed in the primary thermal degradation processes of PSD and PST.

Adaptive optimization of continuous bioreactor using neural network model

An adaptive optimization algorithm using backpropogation neural network model for dynamic identification is developed. The algorithm is applied to maximize the cellular productivity of a continuous culture of baker's yeast. The robustness of the algorithm is demonstrated in determining and maintaining the optimal dilution rate of the continuous bioreactor in presence of disturbances in environmental conditions and microbial culture characteristics. The simulation results show that a significant reduction in time required to reach optimal operating levels can be achieved using neural network model compared with the traditional dynamic linear input-output model. The extension of the algorithm for multivariable adaptive optimization of continuous bioreactor is briefly discussed.

A novel neural network design for long range prediction of rainfall pattern

The importance of long-range prediction of rainfall pattern for devising and planning agricultural strategies cannot be overemphasized. However, the prediction of rainfall pattern remains a difficult problem and the desired level of accuracy has not been reached. The conventional methods for prediction of rainfall use either dynamical or statistical modelling. In this article we report the results of a new modelling technique using artificial neural networks. Artificial neural networks are especially useful where the dynamical processes and their interrelations for a given phenomenon are not known with sufficient accuracy. Since conventional neural networks were found to be unsuitable for simulating and predicting rainfall patterns, a generalized structure of a neural network was then explored and found to provide consistent prediction (hindcast) of all-India annual mean rainfall with good accuracy. Performance and consistency of this network are evaluated and compared with those of other (conventional) neural networks. It is shown that the generalized network can make consistently good prediction of annual mean rainfall. Immediate application and potential of such a prediction system are discussed.

A thermodynamic criterion for selection of gas compositions for diamond deposition

Isoactivity lines for carbon with respect to diamond as the standard state have been calculated in the ternary system C-H-O at 1223 K to identify the diamond deposition domain. The gas composition is calculated by suppressing the formation of all condensed forms of carbon using the SOLGASMIX free-energy minimization program. Thirty six gas species were included in the calculation. From the gas composition, isoactivity lines are computed using recent data on the Gibbs energy of diamond. Except for activities less than 0.1, the isoactivity lines are almost linear on the C-H-O ternary diagram. Gas compositions which generate activity of diamond ranging from 1 to 100 at 1223 K fall inside a narrow wedge originating from the point representing CO. This wedge is very similar to the revised lens-shaped diamond growth domain identified by Bachman et al., using inputs from experiment. The small difference between the calculated and observed domains may be attributed to variation in the supersaturation required for diamond deposition with gas composition. The diamond solubility in the gas phase along the isoactivity line for a(di)=100 and P=6.7 kPa exhibits a minimum at 1280 K, which is close to the optimum temperature found experimentally. At higher supersaturations, non-diamond forms of carbon, including amorphous varieties, are expected. The results suggest that thermodynamic calculations can be useful for locating diamond growth domains in more complex CVD systems containing halogens, for which very little experimental data is available.

Gas-liquid nucleation at large metastability: unusual features and a new formalism

Nucleation at large metastability is still largely an unsolved problem, even though it is a problem of tremendous current interest, with wide-ranging practical value, from atmospheric research to materials science. It is now well accepted that the classical nucleation theory (CNT) fails to provide a qualitative picture and gives incorrect quantitative values for such quantities as activation-free energy barrier and supersaturation dependence of nucleation rate, especially at large metastability. In this paper, we present an alternative formalism to treat nucleation at large supersaturation by introducing an extended set of order parameters in terms of the kth largest liquid-like clusters, where k = 1 is the largest cluster in the system, k = 2 is the second largest cluster and so on. At low supersaturation, the size of the largest liquid-like cluster acts as a suitable order parameter. At large supersaturation, the free energy barrier for the largest liquid-like cluster disappears. We identify this supersaturation as the one at the onset of kinetic spinodal. The kinetic spinodal is system-size-dependent. Beyond kinetic spinodal many clusters grow simultaneously and competitively and hence the nucleation and growth become collective. In order to describe collective growth, we need to consider the full set of order parameters. We derive an analytic expression for the free energy of formation of the kth largest cluster. The expression predicts that, at large metastability (beyond kinetic spinodal), the barrier of growth for several largest liquid-like clusters disappears, and all these clusters grow simultaneously. The approach to the critical size occurs by barrierless diffusion in the cluster size space. The expression for the rate of barrier crossing predicts weaker supersaturation dependence than what is predicted by CNT at large metastability. Such a crossover behavior has indeed been observed in recent experiments (but eluded an explanation till now). In order to understand the large numerical discrepancy between simulation predictions and experimental results, we carried out a study of the dependence on the range of intermolecular interactions of both the surface tension of an equilibrium planar gas-liquid interface and the free energy barrier of nucleation. Both are found to depend significantly on the range of interaction for the Lennard-Jones potential, both in two and three dimensions. The value of surface tension and also the free energy difference between the gas and the liquid phase increase significantly and converge only when the range of interaction is extended beyond 6-7 molecular diameters. We find, with the full range of interaction potential, that the surface tension shows only a weak dependence on supersaturation, so the reason for the breakdown of CNT (with simulated values of surface tension and free energy gap) cannot be attributed to the supersaturation dependence of surface tension. This remains an unsettled issue at present because of the use of the value of surface tension obtained at coexistence.

Neural network modeling of associative memory: Beyond the Hopfield model

A number of neural network models, in which fixed-point and limit-cycle attractors of the underlying dynamics are used to store and associatively recall information, are described. In the first class of models, a hierarchical structure is used to store an exponentially large number of strongly correlated memories. The second class of models uses limit cycles to store and retrieve individual memories. A neurobiologically plausible network that generates low-amplitude periodic variations of activity, similar to the oscillations observed in electroencephalographic recordings, is also described. Results obtained from analytic and numerical studies of the properties of these networks are discussed.

Nitrogen Derivatives Of C-60 And C-70 - Interaction Of Fullerenes With Nitrogen In Gas-Phase

Mass spectrometric studies show that contact-arc vaporization of graphite in a partial atmosphere of N2 or NH3 yields nitrogenous products tentatively assigned to species such as C70N2, C59N6, C59N4 and C59N2 involving addition of or substitution by nitrogen along with the species due to C2 and C4 losses. Mass spectrometry and other techniques have been employed to identify products of the nucleophilic addition of aliphatic amines to C60 and C70 in solution phase.