Dicopper(II) complexes showing DNA hydrolase activity and monomeric adduct formation with bis(4-nitrophenyl)phosphate

Ferromagnetic dicopper(II) complexes [Cu(2)(mu-O(2)CCH(3))(mu-OH)(L)(2)(mu-L(1))](PF(6))(2), where L = 1,10-phenanthroline (phen), L(1) = H(2)O in 1 and L = dipyrido[3,2-d:2',3'-f]quinoxaline (dpq), L(1) = CH(3)CN in 2, are prepared and structurally characterized. Crystals of 1 and 2 belong to the monoclinic space group of P2(1)/n and P2(1)/m, respectively. The copper(II) centers display distorted square-pyramidal geometry having a phenanthroline base and two oxygen atoms of the bridging hydroxo and acetate group in the basal plane. The fifth coordination site has weak axially bound bridging solvent molecule H(2)O in 1 and CH(3)CN in 2. The Cu center dot center dot center dot Cu distances are 3.034 and 3.046 angstrom in 1 and 2, respectively. The complexes show efficient hydrolytic cleavage of supercoiled pUC19 DNA as evidenced from the mechanistic studies that include T4 DNA ligase experiments. The binuclear complexes form monomeric copper(II) adducts [Cu(L)(2)(BNPP)](PF(6)) (L = phen, 3; dpq, 4) with bis(4-nitrophenyl)phosphate (BNPP) as a model phosphodiester. The crystal structures of 3 and 4 reveal distorted trigonal bipyramidal geometry in which BNPP binds through the oxygen atom of the phosphate. The kinetic data of the DNA cleavage reactions of the binuclear complexes under pseudo- and true-Michaelis-Menten conditions indicate remarkable enhancement in the DNA hydrolysis rate in comparison to the control data. (C) 2011 Elsevier B.V. All rights reserved.

Regimes of spray formation in gas-centered swirl coaxial atomizers

Spray formation in ambient atmosphere from gas-centered swirl coaxial atomizers is described by carrying out experiments in a spray test facility. The atomizer discharges a circular air jet and an axisymmetric swirling water sheet from its coaxially arranged inner and outer orifices. A high-speed digital imaging system along with a backlight illumination arrangement is employed to record the details of liquid sheet breakup and spray development. Spray regimes exhibiting different sheet breakup mechanisms are identified and their characteristic features presented. The identified spray regimes are wave-assisted sheet breakup, perforated sheet breakup, segmented sheet breakup, and pulsation spray regime. In the regime of wave-assisted sheet breakup, the sheet breakup shows features similar to the breakup of two-dimensional planar air-blasted liquid sheets. At high air-to-liquid momentum ratios, the interaction process between the axisymmetric swirling liquid sheet and the circular air jet develops spray processes which are more specific to the atomizer studied here. The spray exhibits a periodic ejection of liquid masses whose features are dominantly controlled by the central air jet.

Volume Change behaviour in Calcitic Soil influenced with Sulphuric Acid using Artificial Neural Networks

This paper elucidates the methodology of applying artificial neural network model (ANNM) to predict the percent swell of calcitic soil in sulphuric acid solutions, a complex phenomenon involving many parameters. Swell data required for modelling is experimentally obtained using conventional oedometer tests under nominal surcharge. The phases in ANN include optimal design of architecture, operation and training of architecture. The designed optimal neural model (3-5-1) is a fully connected three layer feed forward network with symmetric sigmoid activation function and trained by the back propagation algorithm to minimize a quadratic error criterion.The used model requires parameters such as duration of interaction, calcite mineral content and acid concentration for prediction of swell. The observed strong correlation coefficient (R2 = 0.9979) between the values determined by the experiment and predicted using the developed model demonstrates that the network can provide answers to complex problems in geotechnical engineering.

Stress-Strain Prediction of Jointed Rocks using Artificial Neural Networks

The applicability of Artificial Neural Networks for predicting the stress-strain response of jointed rocks at varied confining pressures, strength properties and joint properties (frequency, orientation and strength of joints) has been studied in the present paper. The database is formed from the triaxial compression tests on different jointed rocks with different confining pressures and different joint properties reported by various researchers. This input data covers a wide range of rock strengths, varying from very soft to very hard. The network was trained using a 3 layered network with feed forward back propagation algorithm. About 85% of the data was used for training and remaining15% for testing the predicting capabilities of the network. Results from the analyses were very encouraging and demonstrated that the neural network approach is efficient in capturing 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 rocks, whose intact strength vary from 11.32 MPa to 123 MPa and spacing of joints vary from 10 cm to 100 cm for confining pressures ranging from 0 to 13.8 MPa.

Electrochemical phase formation. Time-dependent nucleation and growth rates

The theory of phase formation is generalised for any arbitrary time dependence of nucleation and growth rates. Some sources of this time dependence are time-dependent potential inputs, ohmic drop and the ingestion effect. Particular cases, such as potentiostatic and, especially, linear potential sweep, are worked out for the two limiting cases of nucleation, namely instantaneous and progressive. The ohmic drop is discussed and a procedure for this correction is indicated. Recent results of Angerstein-Kozlowska, Conway and Klinger are critically investigated. Several earlier results are deduced as special cases. Evans' overlap formula is generalised for the time-dependent case and the equivalence between Avrami's and Evans' equations established.

A Shapley Value Analysis to Coordinate the Formation of Procurement Networks

In this paper we address the problem of forming procurement networks for items with value adding stages that are linearly arranged. Formation of such procurement networks involves a bottom-up assembly of complex production, assembly, and exchange relationships through supplier selection and contracting decisions. Research in supply chain management has emphasized that such decisions need to take into account the fact that suppliers and buyers are intelligent and rational agents who act strategically. In this paper, we view the problem of procurement network formation (PNF) for multiple units of a single item as a cooperative game where agents cooperate to form a surplus maximizing procurement network and then share the surplus in a fair manner. We study the implications of using the Shapley value as a solution concept for forming such procurement networks. We also present a protocol, based on the extensive form game realization of the Shapley value, for forming these networks.

Surface effects on stacking fault and twin formation in fcc nanofilms: A first-principles study

The free surface effects on stacking fault and twin formation in fcc metals (Al, Cu, and Ni) were examined by first-principles calculations based on density functional theory (DFT). It is found that the generalized planar fault (GPF) energies of Ni are much larger than bulk Ni with respect to Al and Cu. The discrepancy is attributed to the localized relaxation of Ni nanofilm to accommodate the large expansion of the inter-planar separation induced at the fault plane. The localized relaxation can be coupled to the electronic structure of Ni nanofilms. (C) 2011 Elsevier B.V. All rights reserved.