Chemical Aspects of the Synergistic Hypergolic Ignition in Hybrid Systems with N2O4 as Oxidizer

Synergistic hypergolic ignition with nitrogen tetroxide ( N2O4) as oxidizer has been observed in hybrid systems comprising of a mixture of magnesium and Schiff bases as fuels. The ignition delays (IDs) measured using a modified device, have been compared with those of magnesium-Schiff base-WFNA systems under identical conditions. The ID has been found to vary with the nature of the substitution in both the benzene rings. A linear relationship emerges when the ignition delays are plotted against the Hammett substitution constants (σ). The preignition products of the reaction of N2O4 with magnesium and benzylidineaniline have been analysed to be Mg(NO3)2, benzenediazonium salt and benzaldehyde. Based on the preignition products isolated, a probable reaction mechanism has been proposed. The previously proposed preignition mechanism for the Schiff base-magnesium-WFNA system has been further supported from the present ignition delay data.

Structural aspects of high-temperature cuprate superconductors

High-temperature superconductivity constitutes the most sensational discovery of recent times. Since these new superconductors are complex metal oxides, chemistry has had a big role to play in the investigations. For the first time, stoichiometry, structure, bonding, and such chemical factors have formed central themes in superconductivity, an area traditionally dominated by physicists. These oxide superconductors have given a big boost to solid-state chemistry.

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.

Genetic Heterogeneity in Wild Isolates of Cellular Slime Mold Social Groups

This study addresses the issues of spatial distribution, dispersal, and genetic heterogeneity in social groups of the cellular slime molds (CSMs). The CSMs are soil amoebae with an unusual life cycle that consists of alternating solitary and social phases. Because the social phase involves division of labor with what appears to be an extreme form of "altruism", the CSMs raise interesting evolutionary questions regarding the origin and maintenance of sociality. Knowledge of the genetic structure of social groups in the wild is necessary for answering these questions. We confirm that CSMs are widespread in undisturbed forest soil from South India. They are dispersed over long distances via the dung of a variety of large mammals. Consistent with this mode of dispersal, most social groups in the two species examined for detailed study, Dictyostelium giganteum and Dictyostelium purpureum, are multi-clonal.

Non-carboxylate based metal-organic frameworks (MOFs) and related aspects

The metal-organic frameworks, in recent years, show a variety of new developments that includes new methods of preparation, post synthesis modifications and novel class of compounds. Though most of the developments happened in the carboxylate based family of compounds, the other related systems are also equally interesting. In this article,we have highlighted some of the developments that have taken place in the family of non-carboxylate metal-organic frameworks. We have also highlighted some of the recent attempts at modifying the surfaces and pores of the MOFs by careful chemical manipulations. (C) 2009 Elsevier Ltd. All rights reserved.

Optimal reservoir operation for irrigation of multiple crops using genetic algorithms

This paper presents a genetic algorithm (GA) model for obtaining an optimal operating policy and optimal crop water allocations from an irrigation reservoir. The objective is to maximize the sum of the relative yields from all crops in the irrigated area. The model takes into account reservoir inflow, rainfall on the irrigated area, intraseasonal competition for water among multiple crops, the soil moisture dynamics in each cropped area, the heterogeneous nature of soils. and crop response to the level of irrigation applied. The model is applied to the Malaprabha single-purpose irrigation reservoir in Karnataka State, India. The optimal operating policy obtained using the GA is similar to that obtained by linear programming. This model can be used for optimal utilization of the available water resources of any reservoir system to obtain maximum benefits.

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.

Generating artificial chromosomes with probability control in genetic algorithm for machine scheduling problems

In this paper, a novel genetic algorithm is developed by generating artificial chromosomes with probability control to solve the machine scheduling problems. Generating artificial chromosomes for Genetic Algorithm (ACGA) is closely related to Evolutionary Algorithms Based on Probabilistic Models (EAPM). The artificial chromosomes are generated by a probability model that extracts the gene information from current population. ACGA is considered as a hybrid algorithm because both the conventional genetic operators and a probability model are integrated. The ACGA proposed in this paper, further employs the ``evaporation concept'' applied in Ant Colony Optimization (ACO) to solve the permutation flowshop problem. The ``evaporation concept'' is used to reduce the effect of past experience and to explore new alternative solutions. In this paper, we propose three different methods for the probability of evaporation. This probability of evaporation is applied as soon as a job is assigned to a position in the permutation flowshop problem. Experimental results show that our ACGA with the evaporation concept gives better performance than some algorithms in the literature.

Microcycle conidiation and its genetic basis in Neurospora crassa

Some wild isolates of Neurospora show microcycle conidiation in liquid culture under continuous agitation. Macroconidia from agar-grown mycelial cultures germinated in liquid and the germlings spontaneously produced conidia with no intervening mycelial phase. Three types of microcycle conidiation were seen among progeny of N. crassa Vickramam A x N. crassa a wild-type: (1) multinucleate blastoconidia produced by apical budding and septation, (2) multinucleate arthroconidia produced by holothallic septation and disarticulation of cells, and (3) uninucleate microconidia produced directly from conidiogenous cells of the germlings. Two genes were identified which control specific patterns of microcycle conidiogenesis. A single gene mcb in linkage group VR near al-3 (3.2% recombination) controls blastoconidiation. This gene is epistatic to gene mcm located in linkage group IIL, very near ro-7 (1.4%). mcm controls both microconidiation and arthroconidiation depending on temperature. Strains of genotype mcm produce microconidia almost exclusively at 18-22 degrees C, but arthroconidia with few or no microconidia at 30 degrees C. Because they result in rapid and synchronized conidiation in liquid culture, the two genes should be useful for studies of developmental gene regulation. mcm makes it possible to obtain large quantities of pure microconidia rapidly for experimentation.

The 26 July 2005 heavy rainfall event over Mumbai: numerical modeling aspects

The performance of the Advanced Regional Prediction System (ARPS) in simulating an extreme rainfall event is evaluated, and subsequently the physical mechanisms leading to its initiation and sustenance are explored. As a case study, the heavy precipitation event that led to 65 cm of rainfall accumulation in a span of around 6 h (1430 LT-2030 LT) over Santacruz (Mumbai, India), on 26 July, 2005, is selected. Three sets of numerical experiments have been conducted. The first set of experiments (EXP1) consisted of a four-member ensemble, and was carried out in an idealized mode with a model grid spacing of 1 km. In spite of the idealized framework, signatures of heavy rainfall were seen in two of the ensemble members. The second set (EXP2) consisted of a five-member ensemble, with a four-level one-way nested integration and grid spacing of 54, 18, 6 and 1 km. The model was able to simulate a realistic spatial structure with the 54, 18, and 6 km grids; however, with the 1 km grid, the simulations were dominated by the prescribed boundary conditions. The third and final set of experiments (EXP3) consisted of a five-member ensemble, with a four-level one-way nesting and grid spacing of 54, 18, 6, and 2 km. The Scaled Lagged Average Forecasting (SLAF) methodology was employed to construct the ensemble members. The model simulations in this case were closer to observations, as compared to EXP2. Specifically, among all experiments, the timing of maximum rainfall, the abrupt increase in rainfall intensities, which was a major feature of this event, and the rainfall intensities simulated in EXP3 (at 6 km resolution) were closest to observations. Analysis of the physical mechanisms causing the initiation and sustenance of the event reveals some interesting aspects. Deep convection was found to be initiated by mid-tropospheric convergence that extended to lower levels during the later stage. In addition, there was a high negative vertical gradient of equivalent potential temperature suggesting strong atmospheric instability prior to and during the occurrence of the event. Finally, the presence of a conducive vertical wind shear in the lower and mid-troposphere is thought to be one of the major factors influencing the longevity of the event.

Aspects of tautomerism. 7. Study of keto participation in alkaline hydrolysis of normal esters of .gamma.-keto acids

Study of the alkaline hydrolysis of a number of variously substituted normal o-benzoylbenzoic esters has been reported. Although carbonyl-assisted hydrolysis is the general rule, in compounds containing strongly electron-donating groups, the ester function is directly attacked. The cause of rate enhancement in carbonyl-assisted hydrolysis and in greater detail the case of 6-substituted derivatives are discussed. It is shown that the carbonyl-assisted hydrolyses are characterized by decreased sensitivity to leaving-group structure. The implications of this result are pointed out.

Mechanistic Aspects of Nucleophilic Substitution at Half-Sandwich Metal Complexes

The hydrolysis reactions of organometallic ruthenium(II) piano-stool complexes of the type Ru-II(eta(6)-cymene)(L)Cl](0/+) (1-5, where L = kappa(1)- or kappa(2)-1,1-bis(diphenylphosphino)methane,1,1bis-(diphenylphosphino)methane oxide, kappa(1)-mercaptobenzothiazole) have been studied using density functional theory at the B3LYP level. In addition to considering a syn attack in an associative fashion, where the nucleophile approaches from the same side as the leaving group, we have explored alternative paths such as an anti attack in an associative manner, where the nucleophile attacks from the opposite side of the leaving group. During the anti attack, an intermediate is formed and there is a coordination mode change of the arene ring from eta(6) to eta(2) along with its rotation. When the intermediate goes to the product, the arene ring slips back from eta(2) to eta(6) coordination. This coordinated movement of the arene ring makes the associative anti attack an accessible pathway for the substitution process. Our calculations predict very similar activation barriers for both syn and anti attacks. In the dissociative path, the rate-determining step is the generation of a coordinatively unsaturated 16-electron ruthenium species. This turns out to be viable once solvent effects are included. The large size of the ancillary ligands on Ru makes the dissociative process as favorable as the associative process. Activation energy calculations reveal that although the dissociative path is favorable for kappa(1) complexes, both dissociative and associative processes can have significant contribution to the hydrolysis reaction in kappa(2) complexes. Once activated by hydrolysis, these complexes react with guanine and adenine bases of DNA. The thermodynamic stabilities of complexes formed with the nucleobases are also presented.

A Genetic Study of Immunoglobulin E and Atopic Disease Based on Families Ascertained through Asthmatic Children

In order to investigate the modes of inheritance of serum immunoglobulin E (IgE) levels and atopic disease, serum IgE levels and data on allergic disease were obtained from 42 families ascertained through asthmatic children visiting an allergy clinic. Although the mean IgE levels were elevated (mean 637 U/ml), the prevalence of atopic disease in this population was surprisingly low. When the data were analyzed using complex segregation analysis, no major locus could be detected. Moreover, the polygenic heritability was unexpectedly small even though the correlation between serum IgE levels and the liability to atopic disease was around 0.4. Given this unusual set of findings, it is postulated that parasitic infections in this population have (in accordance with well-established results of parasitic disease) caused both elevated levels of serum IgE and a decreased prevalence of allergic disease with the possible masking of the various genetic components of serum IgE levels and atopic disease.