A composition-dependent ``re-entrant'' crystallographic phase transition in the substitutional metal acetylacetonate complex (Cr1-xGax)(acac)(3)

The formation of a complete solid solution between acetylacetonate (acac) complexes of chromium and gallium, (Cr1-x,Ga-x)(acac)(3) for 0.1 value of x, with thermal analysis confirming each composition to have a congruent melting point, making it a substitutional complex. Whereas the pure complexes (i.e. the end members of the solid solution, x = 0 and x = 1) are both centro-symmetric, a composition-dependent crystallographic phase transition to a non-centrosymmetric structure is found to occur for compositions with 0.4 < x < 0.9. Such a ``re-entrant'' crystallographic transition is interpreted to be due to the drive to overcome the disorder present in certain centrosymmetric chromium-rich compositions, by going over to a non-centrosymmetric structure with a doubling of the unit cell. The substitutional complex is shown to lead to a substitutional oxide with the beta-gallate structure. (C) 2014 Elsevier Ltd. All rights reserved.

High Throughput, Low Latency, Memory Optimized 64K Point FFT Architecture using Novel Radix-4 Butterfly Unit

In this paper we propose a fully parallel 64K point radix-4(4) FFT processor. The radix-4(4) parallel unrolled architecture uses a novel radix-4 butterfly unit which takes all four inputs in parallel and can selectively produce one out of the four outputs. The radix-4(4) block can take all 256 inputs in parallel and can use the select control signals to generate one out of the 256 outputs. The resultant 64K point FFT processor shows significant reduction in intermediate memory but with increased hardware complexity. Compared to the state-of-art implementation 5], our architecture shows reduced latency with comparable throughput and area. The 64K point FFT architecture was synthesized using a 130nm CMOS technology which resulted in a throughput of 1.4 GSPS and latency of 47.7 mu s with a maximum clock frequency of 350MHz. When compared to 5], the latency is reduced by 303 mu s with 50.8% reduction in area.

NaOsO3: A high Neel temperature 5d oxide

The origin of a high Neel temperature in a 5d oxide, NaOsO3, has been analyzed within the mean-field limit of a multiband Hubbard model and compared with the analogous 4d oxide, SrTcO3. Our analysis shows that there are a lot of similarities in both of these oxides on the dependence of the effective exchange interaction strength (J(0)) on the electron-electron interaction strength ( U). However, the relevant value of U in each system puts them in different portions of the parameter space. Although the Neel temperature for NaOsO3 is less than that for SrTcO3, our results suggest that there could be examples among other 5d oxides that have a higher Neel temperature. We have also examined the stability of the G-type antiferromagnetic state found in NaOsO3 as a function of electron doping within GGA + U calculations and find a robust G-type antiferromagnetic metallic state stabilized. The most surprising aspect of the doped results is the rigid bandlike evolution of the electronic structure, which indicates that the magnetism in NaOsO3 is not driven by Fermi surface nesting.

Group behaviour in physical, chemical and biological systems

Groups exhibit properties that either are not perceived to exist, or perhaps cannot exist, at the individual level. Such `emergent' properties depend on how individuals interact, both among themselves and with their surroundings. The world of everyday objects consists of material entities. These are, ultimately, groups of elementary particles that organize themselves into atoms and molecules, occupy space, and so on. It turns out that an explanation of even the most commonplace features of this world requires relativistic quantum field theory and the fact that Planck's constant is discrete, not zero. Groups of molecules in solution, in particular polymers ('sols'), can form viscous clusters that behave like elastic solids ('gels'). Sol-gel transitions are examples of cooperative phenomena. Their occurrence is explained by modelling the statistics of inter-unit interactions: the likelihood of either state varies sharply as a critical parameter crosses a threshold value. Group behaviour among cells or organisms is often heritable and therefore can evolve. This permits an additional, typically biological, explanation for it in terms of reproductive advantage, whether of the individual or of the group. There is no general agreement on the appropriate explanatory framework for understanding group-level phenomena in biology.

Role of Cu2+ ions substitution in magnetic and conductivity behavior of nano-CoFe2O4

Cobalt copper ferrite nanopowders with composition Co1-xCu5Fe2O4 (0.0 <= x <= 0.5) was synthesized by solution combustion method. The powder X-ray diffraction studies reveal the formation of single ferrite phase with particle size of similar to 11-35 nm. Due to increase in electron density with in a material, X-ray density increase with increase of Cu2+ ions concentration. As Cu2+ ions concentration increases, saturation magnetization decreases from 38.5 to 26.7 emu g(-1). Further, the squareness ratio was found to be similar to 0.31-0.46 which was well below the typical value 1, which indicates the existence of single domain isolated ferrimagnetic samples. The dielectric and electrical modulus was studied over a frequency range of 1 Hz to 1 MHz at room temperature using the complex impedance spectroscopy technique. Impedance plots showed only one semi-circle which corresponds to the contributions of grain boundaries. The lower values of dielectric loss at higher frequency region may be quite useful for high frequency applications such as microwave devices. (C) 2014 Elsevier B.V. All rights reserved.

CANDO and the infinite drug discovery frontier

The Computational Analysis of Novel Drug Opportunities (CANDO) platform (http://protinfo.org/cando) uses similarity of compound-proteome interaction signatures to infer homology of compound/drug behavior. We constructed interaction signatures for 3733 human ingestible compounds covering 48,278 protein structures mapping to 2030 indications based on basic science methodologies to predict and analyze protein structure, function, and interactions developed by us and others. Our signature comparison and ranking approach yielded benchmarking accuracies of 12-25% for 1439 indications with at least two approved compounds. We prospectively validated 49/82 `high value' predictions from nine studies covering seven indications, with comparable or better activity to existing drugs, which serve as novel repurposed therapeutics. Our approach may be generalized to compounds beyond those approved by the FDA, and can also consider mutations in protein structures to enable personalization. Our platform provides a holistic multiscale modeling framework of complex atomic, molecular, and physiological systems with broader applications in medicine and engineering.

Discovering Math APIs by Mining Unit Tests

In today's API-rich world, programmer productivity depends heavily on the programmer's ability to discover the required APIs. In this paper, we present a technique and tool, called MATHFINDER, to discover APIs for mathematical computations by mining unit tests of API methods. Given a math expression, MATHFINDER synthesizes pseudo-code to compute the expression by mapping its subexpressions to API method calls. For each subexpression, MATHFINDER searches for a method such that there is a mapping between method inputs and variables of the subexpression. The subexpression, when evaluated on the test inputs of the method under this mapping, should produce results that match the method output on a large number of tests. We implemented MATHFINDER as an Eclipse plugin for discovery of third-party Java APIs and performed a user study to evaluate its effectiveness. In the study, the use of MATHFINDER resulted in a 2x improvement in programmer productivity. In 96% of the subexpressions queried for in the study, MATHFINDER retrieved the desired API methods as the top-most result. The top-most pseudo-code snippet to implement the entire expression was correct in 93% of the cases. Since the number of methods and unit tests to mine could be large in practice, we also implement MATHFINDER in a MapReduce framework and evaluate its scalability and response time.

A constant factor approximation algorithm for boxicity of circular arc graphs

The boxicity (resp. cubicity) of a graph G(V, E) is the minimum integer k such that G can be represented as the intersection graph of axis parallel boxes (resp. cubes) in R-k. Equivalently, it is the minimum number of interval graphs (resp. unit interval graphs) on the vertex set V, such that the intersection of their edge sets is E. The problem of computing boxicity (resp. cubicity) is known to be inapproximable, even for restricted graph classes like bipartite, co-bipartite and split graphs, within an O(n(1-epsilon))-factor for any epsilon > 0 in polynomial time, unless NP = ZPP. For any well known graph class of unbounded boxicity, there is no known approximation algorithm that gives n(1-epsilon)-factor approximation algorithm for computing boxicity in polynomial time, for any epsilon > 0. In this paper, we consider the problem of approximating the boxicity (cubicity) of circular arc graphs intersection graphs of arcs of a circle. Circular arc graphs are known to have unbounded boxicity, which could be as large as Omega(n). We give a (2 + 1/k) -factor (resp. (2 + log n]/k)-factor) polynomial time approximation algorithm for computing the boxicity (resp. cubicity) of any circular arc graph, where k >= 1 is the value of the optimum solution. For normal circular arc (NCA) graphs, with an NCA model given, this can be improved to an additive two approximation algorithm. The time complexity of the algorithms to approximately compute the boxicity (resp. cubicity) is O(mn + n(2)) in both these cases, and in O(mn + kn(2)) = O(n(3)) time we also get their corresponding box (resp. cube) representations, where n is the number of vertices of the graph and m is its number of edges. Our additive two approximation algorithm directly works for any proper circular arc graph, since their NCA models can be computed in polynomial time. (C) 2014 Elsevier B.V. All rights reserved.

A detailed numerical study of NOx kinetics in low calorific value H-2/CO syngas flames

The present study provides an extensive and detailed numerical analysis of NO chemical kinetics in low calorific value H-2/CO syngas flames utilizing predictions by five chemical kinetic mechanisms available out of which four deal with H-2/CO while the fifth mechanism (GRI 3.0) additionally accounts for hydrocarbon chemistry. Comparison of predicted axial NO profiles in premixed flat flames with measurements at 1 bar, 3.05 bar and 9.15 bar shows considerably large quantitative differences among the various mechanisms. However, at each pressure, the quantitative reaction path diagrams show similar NO formation pathways for most of the mechanisms. Interestingly, in counterflow diffusion flames, the quantitative reaction path diagrams and sensitivity analyses using the various mechanisms reveal major differences in the NO formation pathways and reaction rates of important reactions. The NNH and N2O intermediate pathways are found to be the major contributors for NO formation in all the reaction mechanisms except GRI 3.0 in syngas diffusion flames. The GRI 3.0 mechanism is observed to predict prompt NO pathway as the major contributing pathway to NO formation. This is attributed to prediction of a large concentration of CH radical by the GRI 3.0 as opposed to a relatively negligible value predicted by all other mechanisms. Also, the back-conversion of NNH into N2O at lower pressures (2-4 bar) was uniquely observed for one of the five mechanisms. The net reaction rates and peak flame temperatures are used to correlate and explain the differences observed in the peak NO] at different pressures. This study identifies key reactions needing assessment and also highlights the need for experimental data in syngas diffusion flames in order to assess and optimize H-2/CO and nitrogen chemistry. Copyright (C) 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

STM verification of the reduction of the Young's modulus of CdS nanoparticles at smaller sizes

We demonstrate the first STM evaluation of the Young's modulus (E) of nanoparticles (NPs) of different sizes. The sample deformation induced by tip-sample interaction has been determined using current-distance (I-Z) spectroscopy. As a result of tip-sample interaction, and the induced surface deformations, the I-z curves deviates from pure exponential dependence. Normally, in order to analyze the deformation quantitatively, the tip radius must be known. We show, that this necessity is eliminated by measuring the deformation on a substrate with a known Young's modulus (Au(111)) and estimating the tip radius, and afterwards, using the same tip (with a known radius) to measure the (unknown) Young's modulus of another sample (nanoparticles of CdS). The Young's modulus values found for 3 NP's samples of average diameters of 3.7, 6 and 7.5 nm, were E similar to 73%, 78% and 88% of the bulk value, respectively. These results are in a good agreement with the theoretically predicted reduction of the Young's modulus due to the changes in hydrostatic stresses which resulted from surface tension in nanoparticles with different sizes. Our calculation using third order elastic constants gives a reduction of E which scales linearly with 1/r (r is the NP's radius). This demonstrates the applicability of scanning tunneling spectroscopy for local mechanical characterization of nanoobjects. The method does not include a direct measurement of the tip-sample force but is rather based on the study of the relative elastic response. (C) 2014 Elsevier B.V. All rights reserved.

Mining Unit Tests for Discovery and Migration of Math APIs

Today's programming languages are supported by powerful third-party APIs. For a given application domain, it is common to have many competing APIs that provide similar functionality. Programmer productivity therefore depends heavily on the programmer's ability to discover suitable APIs both during an initial coding phase, as well as during software maintenance. The aim of this work is to support the discovery and migration of math APIs. Math APIs are at the heart of many application domains ranging from machine learning to scientific computations. Our approach, called MATHFINDER, combines executable specifications of mathematical computations with unit tests (operational specifications) of API methods. Given a math expression, MATHFINDER synthesizes pseudo-code comprised of API methods to compute the expression by mining unit tests of the API methods. We present a sequential version of our unit test mining algorithm and also design a more scalable data-parallel version. We perform extensive evaluation of MATHFINDER (1) for API discovery, where math algorithms are to be implemented from scratch and (2) for API migration, where client programs utilizing a math API are to be migrated to another API. We evaluated the precision and recall of MATHFINDER on a diverse collection of math expressions, culled from algorithms used in a wide range of application areas such as control systems and structural dynamics. In a user study to evaluate the productivity gains obtained by using MATHFINDER for API discovery, the programmers who used MATHFINDER finished their programming tasks twice as fast as their counterparts who used the usual techniques like web and code search, IDE code completion, and manual inspection of library documentation. For the problem of API migration, as a case study, we used MATHFINDER to migrate Weka, a popular machine learning library. Overall, our evaluation shows that MATHFINDER is easy to use, provides highly precise results across several math APIs and application domains even with a small number of unit tests per method, and scales to large collections of unit tests.

Effect of Groundwater Seepage on Uplift Resistance of Buried Pipelines

The uplift resistance of pipelines buried in sands, in the presence of inclined groundwater flow, considering both upward and downward flow directions, has been determined by using the lower bound finite elements limit analysis in conjunction with nonlinear optimization. A correction factor (f (gamma) ), which needs to be multiplied with the uplift factor (F (gamma) ), has been computed to account for groundwater seepage. The variation of f (gamma) has been obtained as a function of i(gamma (w) /gamma (sub) ) for different horizontal inclinations (theta) of groundwater flow; where i = absolute magnitude of hydraulic gradient along the direction of flow, gamma (w) is the unit weight of water and gamma (sub) is the submerged unit weight of soil mass. For a given magnitude of i, there exists a certain critical value of theta for which the magnitude of f (gamma) becomes the minimum. An example has also been presented to illustrate the application of the results obtained for designing pipelines in presence of groundwater seepage.

Optimal error estimate using mesh equidistribution technique for singularly perturbed system of reaction-diffusion boundary-value problems

In this article, we study the problem of determining an appropriate grading of meshes for a system of coupled singularly perturbed reaction-diffusion problems having diffusion parameters with different magnitudes. The central difference scheme is used to discretize the problem on adaptively generated mesh where the mesh equation is derived using an equidistribution principle. An a priori monitor function is obtained from the error estimate. A suitable a posteriori analogue of this monitor function is also derived for the mesh construction which will lead to an optimal second-order parameter uniform convergence. We present the results of numerical experiments for linear and semilinear reaction-diffusion systems to support the effectiveness of our preferred monitor function obtained from theoretical analysis. (C) 2014 Elsevier Inc. All rights reserved.

High Value of Proton Relaxivity Achieved by Graphene Oxide-Cobalt Ferrite Nanoparticle Composite: A Potential Contrast Agent in Magnetic Resonance Imaging

This work investigates the potential of graphene oxide-cobalt ferrite nanoparticle (GO-CoFe2O4) composite as image contrast enhancing material in Magnetic Resonance Imaging (MRI). In the preset work, GO-CoFe2O4 composites were produced by a two-step synthesis process. In the first step, graphene oxide (GO) was synthesized, and in the second step CoFe2O4 nanoparticles were synthesized in a reaction mixture containing GO to yield graphene GO-CoFe2O4 composite. Proton relaxivity value obtained from the composite was 361 mM(-1)s(-1). This value of proton relaxivity is higher than a majority of reported relaxivity values obtained using several ferrite based contrast agents.

Charge density distribution and electrostatic interactions of ethionamide: an inhibitor of the enoyl acyl carrier protein reductase (inhA) enzyme of Mycobacterium tuberculosis

An experimental charge density analysis of an anti-TB drug ethionamide was carried out from high resolution X-ray diffraction at 100 K to understand its charge density distribution and electrostatic properties. The experimental results were validated from periodic theoretical charge density calculations performed using CRYSTAL09 at the B3LYP/6-31G** level of theory. The electron density rho(bcp)(r) and the Laplacian of electron density del(2)(rho bcp)(r) of the molecule calculated from both the methods display the charge density distribution of the ethionamide molecule in the crystal field. The electrostatic potential map shows a large electropositive region around the pyridine ring and a large electronegative region at the vicinity of the thiol atom. The calculated experimental dipole moment is 10.6D, which is higher than the value calculated from theory (8.2D). The topological properties of C-H center dot center dot center dot S, N-H center dot center dot center dot N and N-H center dot center dot center dot S hydrogen bonds were calculated, revealing their strength. The charge density analysis of the ethionamide molecule determined from both the experiment and theory gives the topological and electrostatic properties of the molecule, which allows to precisely understand the nature of intra and intermolecular interactions.