(2-Chloro-6-methylquinolin-3-yl)methanol

The title compound, C11H10ClNO, is close to being planar (r.m.s deviation for the non-H atoms = 0.026 angstrom). In the crystal,molecules are linked by O-H center dot center dot center dot O hydrogen bonds, generating C(2) chains, and weak C-H center dot center dot center dot pi interactions and aromatic pi-pi stacking interactions [centroid-centroid distance = 3.713 (3) angstrom] help to consolidate the sturcture.

3-[(2-Chloro-6-methylquinolin-3-yl)methyl]quinazolin-4(3H)-one

In the title molecule, C19H14ClN3O, the quinoline and quinazoline ring systems form a dihedral angle of 80.75 (4)degrees. In the crystal, the molecules are linked by pairs of C-H center dot center dot center dot N hydrogen bonds into centrosymmetric dimers, generating R-2(2)(6) ring motifs. The structure is further stabilized by C-H center dot center dot center dot pi interactions and pi-pi stacking interactions [centroid-centroid distances = 3.7869 (8) and 3.8490 (8) angstrom].

Neural network approach for fault location in unbalanced distribution networks with limited measurements

This paper presents an Artificial Neural Network (ANN) approach for locating faults in distribution systems. Different from the traditional Fault Section Estimation methods, the proposed approach uses only limited measurements. Faults are located according to the impedances of their path using a Feed Forward Neural Networks (FFNN). Various practical situations in distribution systems, such as protective devices placed only at the substation, limited measurements available, various types of faults viz., three-phase, line (a, b, c) to ground, line to line (a-b, b-c, c-a) and line to line to ground (a-b-g, b-c-g, c-a-g) faults and a wide range of varying short circuit levels at substation, are considered for studies. A typical IEEE 34 bus practical distribution system with unbalanced loads and with three- and single- phase laterals and a 69 node test feeder with different configurations are considered for studies. The results presented show that the proposed approach of fault location gives close to accurate results in terms of the estimated fault location.

Effect of coordinated ions on structure and flexibility of parallel G-quadruplexes: A molecular dynamics study

ingle tract guanine residues can associate to form stable parallel quadruplex structures in the presence of certain cations. Nanosecond scale molecular dynamics simulations have been performed on fully solvated fibre model of parallel d(G(7)) quadruplex structures with Na+ or K+ ions coordinated in the cavity formed by the O6 atoms of the guanine bases. The AMBER 4.1 force field and Particle Mesh Ewald technique for electrostatic interactions have been used in all simulations. There quadruplex structures are stable during the simulation, with the middle four base tetrads showing root mean square deviation values between 0.5 to 0.8 Angstrom from the initial structure as well the high resolution crystal structure. Even in the absence of any coordinated ion in the initial structure, the G-quadruplex structure remains intact throughout the simulation. During the 1.1 ns MD simulation, one Nai counter ion from the solvent as well as several water molecules enter the central cavity to occupy the empty coordination sites within the parallel quadruplex and help stabilize the structure. Hydrogen bonding pattern depends on the nature of the coordinated ion, with the G-tetrad undergoing local structural variation to accommodate cations of different sizes. in the absence of any coordinated ion. due to strong mutual repulsion, O6 atoms within G-tetrad are forced farther apart from each other, which leads to a considerably different hydrogen bonding scheme within the G-tetrads and very favourable interaction energy between the guanine bases constituting a G-tetrad. However, a coordinated ion between G-tetrads provides extra stacking energy for the G-tetrads and makes the quadruplex structure more rigid. Na+ ions, within the quadruplex cavity, are more mobile than coordinated K+ ions. A number of hydrogen bonded water molecules are observed within the grooves of all quadruplex structures.

Novel Nanocomposites Made of Boron Nitride Nanotubes and a Physical Gel

This article describes successful incorporation of multiwalled boron nitride nanotubes (BNNTs) and various functionalized BNNTs by Lewis bases such as trioctylamine (TOA), tributylamine (TBA), and triphenylphosphine (TPP), etc., in organogels formed by triphenylenevinylene (TPV)-based low molecular weight gelator (LMWG) in toluene and consequent characterization of the resulting gel nanocomposites. Functionalized BNNTs were synthesized first,and the presence of tubular structures with high aspect ratio and increased diameter compared to the starting BNNTs was confirmed by SEM. TEM, and Raman spectroscopy. The micrographs of composites of I and BNNTs showed evidence of wrapping of the gelator molecules on to the BNNT surface presumably brought about by pi-pi stacking and van der Waals interactions, This leads to the formation of densely packed and directionally aligned fibrous networks. Such ``reinforced'' aggregation of the gelator molecules in presence of doped BNNTs led to an increase in the sot-to-gel transition temperature and the solidification temperature of the gel nanocomposites as revealed from differential scanning calorimetry. Rheological investigations of the gel nanocomposites indicate that the flow properties of the resulting materials become resistant to applied stress upon incorporation of even a very low wt % of BNNTs. Finally, the increase in thermal conductivity of the nanocomposite compared to the gelator alone was observed for the temperature range of 0-60 degrees C which may make these composites potentially useful in various applications depending on the choice and the amount of BNNT loading in the composite.

Actuator fault detection and isolation in linear systems

A scheme for the detection and isolation of actuator faults in linear systems is proposed. A bank of unknown input observers is constructed to generate residual signals which will deviate in characteristic ways in the presence of actuator faults. Residual signals are unaffected by the unknown inputs acting on the system and this decreases the false alarm and miss probabilities. The results are illustrated through a simulation study of actuator fault detection and isolation in a pilot plant doubleeffect evaporator.

Interaction of 3-hydroxybenzoate-6-hydroxylase with cibacron blue

Cibacron blue is a potent inhibitor of 3-HBA-6-hydroxylase at a concentration < 1 mu M. Kinetic analyses revealed that at a concentration below 0.5 mu M the dye behaves as an uncompetitive inhibitor with respect to 3-HBA and competes with NADH for the same site on the enzyme. The alteration of the near-UV CD spectrum and quenching of the emission fluorescence of the enzyme by cibacron blue indicates a significant alteration in the environment of aromatic amino acid residues due to a stacking interaction and subtle conformatiodnal changes in the enzyme. The concentration-dependent quenching of the intrinsic fluorescence of the enzyme by cibacron blue was employed to determine the binding parameters such as association constant (K-a) and stoichiometry (r) for the enzyme-dye complex.

Gas turbine diagnostics using a soft computing approach

A fuzzy system is developed using a linearized performance model of the gas turbine engine for performing gas turbine fault isolation from noisy measurements. By using a priori information about measurement uncertainties and through design variable linking, the design of the fuzzy system is posed as an optimization problem with low number of design variables which can be solved using the genetic algorithm in considerably low amount of computer time. The faults modeled are module faults in five modules: fan, low pressure compressor, high pressure compressor, high pressure turbine and low pressure turbine. The measurements used are deviations in exhaust gas temperature, low rotor speed, high rotor speed and fuel flow from a base line 'good engine'. The genetic fuzzy system (GFS) allows rapid development of the rule base if the fault signatures and measurement uncertainties change which happens for different engines and airlines. In addition, the genetic fuzzy system reduces the human effort needed in the trial and error process used to design the fuzzy system and makes the development of such a system easier and faster. A radial basis function neural network (RBFNN) is also used to preprocess the measurements before fault isolation. The RBFNN shows significant noise reduction and when combined with the GFS leads to a diagnostic system that is highly robust to the presence of noise in data. Showing the advantage of using a soft computing approach for gas turbine diagnostics.

Interaction between the Z-type DNA duplex and 1,3-propanediamine:crystal structure of d(CACGTG)(2) at 1.2 angstrom resolution

The crystal structure of a hexamer duplex d(CACGTG)(2) has been determined and refined to an R-factor of 18.3% using X-ray data up to 1.2 angstrom resolution. The sequence crystallizes as a left-handed Z-form double helix with Watson-Crick base pairing. There is one hexamer duplex, a spermine molecule, 71 water molecules, and an unexpected diamine (Z-5, 1,3-propanediamine, C3H10N2)) in the asymmetric unit. This is the high-resolution non-disordered structure of a Z-DNA hexamer containing two AT base pairs in the interior of a duplex with no modifications such as bromination or methylation on cytosine bases. This structure does not possess multivalent cations such as cobalt hexaammine that are known to stabilize Z-DNA. The overall duplex structure and its crystal interactions are similar to those of the pure-spermine form of the d(CGCGCG)(2) structure. The spine of hydration in the minor groove is intact except in the vicinity of the T5A8 base pair. The binding of the Z-5 molecule in the minor grove of the d(CACGTG)(2) duplex appears to have a profound effect in conferring stability to a Z-DNA conformation via electrostatic complementarity and hydrogen bonding interactions. The successive base stacking geometry in d(CACGTG)(2) is similar to the corresponding steps in d(CG)(3). These results suggest that specific polyamines such as Z-5 could serve as powerful inducers of Z-type conformation in unmodified DNA sequences with AT base pairs. This structure provides a molecular basis for stabilizing AT base pairs incorporated into an alternating d(CG) sequence.

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.

Design of crosspoint-irredundant PLAs using minimal number of control inputs

The problem of determining a minimal number of control inputs for converting a programmable logic array (PLA) with undetectable faults to crosspoint-irredundant PLA for testing has been formulated as a nonstandard set covering problem. By representing subsets of sets as cubes, this problem has been reformulated as familiar problems. It is noted that this result has significance because a crosspoint-irredundant PLA can be converted to a completely testable PLA in a straightforward fashion, thus achieving very good fault coverage and easy testability.

Preparation and characterization of rubidium-beta-alumina by the gel-to-crystallite conversion method

Preparation of Rb-beta -alumina was realized by the gel-to-crystallite conversion method. Reaction of hydrated aluminum hydroxide gel with RbOH in ethanol medium gave rise to the Rb+-inserted pseudoboehmite precursor under wet chemical conditions. The thermal decomposition of the precursor yielded Rb-beta -alumina. The Rb2O:Al2O3 ratio of monophasic Rb-beta -alumina ranged from 1:10 to 1:22. The extended stability in the compositional range is due to the fact that the conduction planes containing Rb+ and O2- ions can have lower occupancy of Rb+ ions for larger sized alkali ions, permitting the steric separation of the adjoining spinel blocks. High-resolution electron microscopy revealed that the decreasing occupancy of alkali ions in the conduction plane is balanced by changing widths of spinel blocks arising from the shift of tetrahedral Al3+ ions to octahedral sites and an accompanying increase in stacking defects. (C) 2000 Elsevier Science Ltd. All rights reserved.

Artificial Bee Colony (ABC) for multi-objective design optimization of composite structures

In this paper, we present a generic method/model for multi-objective design optimization of laminated composite components, based on Vector Evaluated Artificial Bee Colony (VEABC) algorithm. VEABC is a parallel vector evaluated type, swarm intelligence multi-objective variant of the Artificial Bee Colony algorithm (ABC). In the current work a modified version of VEABC algorithm for discrete variables has been developed and implemented successfully for the multi-objective design optimization of composites. The problem is formulated with multiple objectives of minimizing weight and the total cost of the composite component to achieve a specified strength. The primary optimization variables are the number of layers, its stacking sequence (the orientation of the layers) and thickness of each layer. The classical lamination theory is utilized to determine the stresses in the component and the design is evaluated based on three failure criteria: failure mechanism based failure criteria, maximum stress failure criteria and the tsai-wu failure criteria. The optimization method is validated for a number of different loading configurations-uniaxial, biaxial and bending loads. The design optimization has been carried for both variable stacking sequences, as well fixed standard stacking schemes and a comparative study of the different design configurations evolved has been presented. Finally the performance is evaluated in comparison with other nature inspired techniques which includes Particle Swarm Optimization (PSO), Artificial Immune System (AIS) and Genetic Algorithm (GA). The performance of ABC is at par with that of PSO, AIS and GA for all the loading configurations. (C) 2009 Elsevier B.V. All rights reserved.

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.

Structure of 2',3'-O-isopropylideneguanosine dimethylsulfoxide solvate

CI3H17N5Os.C2H6OS, Mr=401.23, orthorhombic,P21212 p grown from Me2SO, a = 10.749 (2),b = 13.219 (2), c = 14.056 (2) A, V= 1997-23 A 3, Z =4, D_=1.40, D x=l.335Mgm -3, 2(CuKa)= 1.5418/~', g = 1.694 mm -~, F(000) = 848.00, T=293K, R =0.0538, wR =0.0634 for 2105 unique reflections with F > 3o(F). The asymmetric unit contains one nucleoside molecule with a disordered solvent Me2S_O molecule. The geometry about the C(4')-C(5') bond is gauche-gauche. The guanosine base is in the anti conformation with the furanose ring having C(3')-exo (E 3) puckering. The bases do not show any stacking in contrast to other guanosine-containing structures. The crystal structure is stabilized by N--H...N and N--H...O hydrogen bonding.