Hybrid Materials Combining Photoactive 2,3-Didecyloxy Anthracene Physical Gels and Gold Nanoparticles

Organic/inorganic hybrid gels have been developed in order to control the three-dimensional structure of photoactive nanofibers and metallic nanoparticles (NPs). These materials are prepared by simultaneous self-assembly of the 2,3-didecyloxyanthracene (DDOA) gelator and of thiol-capped gold nanoparticles (AuNPs). TEM and fluorescence measurements show that alkane-thiol capped AuNPs are homogeneously dispersed and tightly attached to the thermoreversible fibrillar network formed by the organogelator in n-butanol or n-decanol. Rheology and thermal stability measurements reveal moreover that the mechanical and thermal stabilities of the DDOA organogels are not significantly altered and that they remain strong, viscoelastic materials. The hybrid materials display a variable absorbance in the visible range because of the AuNPs, whereas the strong luminescence of the DDOA nanofibers is efficiently quenched by micromolar amounts of AuNPs. Besides, we obtained hybrid aerogels using supercritical CO2. These arc very low-density porous materials showing fibrillar networks oil which fluorinated gold NPs arc dispersed. These hybrid materials are of high interest because of their tunable optical properties and are under investigation for efficient light scattering.

Topography of the combining region of a Thomsen-Friedenreich-antigen-specific lectin jacalin (Artocarpus integrifolia agglutinin). A thermodynamic and circular-dichroism spectroscopic study

Thermodynamic analysis of carbohydrate binding by Artocarpus integrifolia (jackfruit) agglutinin (jacalin) shows that, among monosaccharides, Me alpha GalNAc (methyl-alpha-N-acetylgalactosamine) is the strongest binding ligand. Despite its strong affinity for Me alpha GalNAc and Me alpha Gal, the lectin binds very poorly when Gal and GalNAc are in alpha-linkage with other sugars such as in A- and B-blood-group trisaccharides, Gal alpha 1-3Gal and Gal alpha 1-4Gal. These binding properties are explained by considering the thermodynamic parameters in conjunction with the minimum energy conformations of these sugars. It binds to Gal beta 1-3GalNAc alpha Me with 2800-fold stronger affinity over Gal beta 1-3GalNAc beta Me. It does not bind to asialo-GM1 (monosialoganglioside) oligosaccharide. Moreover, it binds to Gal beta 1-3GalNAc alpha Ser, the authentic T (Thomsen-Friedenreich)-antigen, with about 2.5-fold greater affinity as compared with Gal beta 1-3GalNAc. Asialoglycophorin A was found to be about 169,333 times stronger an inhibitor than Gal beta 1-3GalNAc. The present study thus reveals the exquisite specificity of A. integrifolia lectin for the T-antigen. Appreciable binding of disaccharides Glc beta 1-3GalNAc and GlcNAc beta 1-3Gal and the very poor binding of beta-linked disaccharides, which instead of Gal and GalNAc contain other sugars at the reducing end, underscore the important contribution made by Gal and GalNAc at the reducing end for recognition by the lectin. The ligand-structure-dependent alterations of the c.d. spectrum in the tertiary structural region of the protein allows the placement of various sugar units in the combining region of the lectin. These studies suggest that the primary subsite (subsite A) can accommodate only Gal or GalNAc or alpha-linked Gal or GalNAc, whereas the secondary subsite (subsite B) can associate either with GalNAc beta Me or Gal beta Me. Considering these factors a likely arrangement for various disaccharides in the binding site of the lectin is proposed. Its exquisite specificity for the authentic T-antigen, Gal beta 1-3GalNAc alpha Ser, together with its virtual non-binding to A- and B-blood-group antigens, Gal beta 1-3GalNAc beta Me and asialo-GM1 should make A. integrifolia lectin a valuable probe for monitoring the expression of T-antigen on cell surfaces.

Combining Bayes Classification and Point Group Symmetry under Boolean Framework for Enhanced Protein Quaternary Structure Inference

Our ability to infer the protein quaternary structure automatically from atom and lattice information is inadequate, especially for weak complexes, and heteromeric quaternary structures. Several approaches exist, but they have limited performance. Here, we present a new scheme to infer protein quaternary structure from lattice and protein information, with all-around coverage for strong, weak and very weak affinity homomeric and heteromeric complexes. The scheme combines naive Bayes classifier and point group symmetry under Boolean framework to detect quaternary structures in crystal lattice. It consistently produces >= 90% coverage across diverse benchmarking data sets, including a notably superior 95% coverage for recognition heteromeric complexes, compared with 53% on the same data set by current state-of-the-art method. The detailed study of a limited number of prediction-failed cases offers interesting insights into the intriguing nature of protein contacts in lattice. The findings have implications for accurate inference of quaternary states of proteins, especially weak affinity complexes.

Performance analysis of TCM with generalized selection combining on Rayleigh fading channels

We derive the computational cutoff rate, R-o, for coherent trellis-coded modulation (TCM) schemes on independent indentically distributed (i.i.d.) Rayleigh fading channels with (K, L) generalized selection combining (GSC) diversity, which combines the K paths with the largest instantaneous signal-to-noise ratios (SNRs) among the L available diversity paths. The cutoff rate is shown to be a simple function of the moment generating function (MGF) of the SNR at the output of the (K, L) GSC receiver. We also derive the union bound on the bit error probability of TCM schemes with (K, L) GSC in the form of a simple, finite integral. The effectiveness of this bound is verified through simulations.

Combining adiabatic and Hartmann-Hahn cross-polarization for sensitivity enhancement in solid state separated local field 2D-NMR experiments of partially ordered systems

In this Letter, we examine magnetization in double- and zero-quantum reservoirs of an ensemble of spin-1/2 nuclei and describe their role in determining the sensitivity of a class of separated local field NMR experiments based on Hartmann-Hahn cross-polarization. We observe that for the liquid crystal system studied, a large dilute spin-polarization, obtained initially by the use of adiabatic cross-polarization, can enhance the sensitivity of the above experiment. The signal enhancement factors, however, are found to vary and depend on the local dynamics. The experimental results have been utilized to obtain the local order-parameters of the system. (C) 2012 Elsevier B. V. All rights reserved.

Parameter estimation of a two-horizon soil profile by combining crop canopy and surface soil moisture observations using GLUE

Estimation of soil parameters by inverse modeling using observations on either surface soil moisture or crop variables has been successfully attempted in many studies, but difficulties to estimate root zone properties arise when heterogeneous layered soils are considered. The objective of this study was to explore the potential of combining observations on surface soil moisture and crop variables - leaf area index (LAI) and above-ground biomass for estimating soil parameters (water holding capacity and soil depth) in a two-layered soil system using inversion of the crop model STICS. This was performed using GLUE method on a synthetic data set on varying soil types and on a data set from a field experiment carried out in two maize plots in South India. The main results were (i) combination of surface soil moisture and above-ground biomass provided consistently good estimates with small uncertainity of soil properties for the two soil layers, for a wide range of soil paramater values, both in the synthetic and the field experiment, (ii) above-ground biomass was found to give relatively better estimates and lower uncertainty than LAI when combined with surface soil moisture, especially for estimation of soil depth, (iii) surface soil moisture data, either alone or combined with crop variables, provided a very good estimate of the water holding capacity of the upper soil layer with very small uncertainty whereas using the surface soil moisture alone gave very poor estimates of the soil properties of the deeper layer, and (iv) using crop variables alone (else above-ground biomass or LAI) provided reasonable estimates of the deeper layer properties depending on the soil type but provided poor estimates of the first layer properties. The robustness of combining observations of the surface soil moisture and the above-ground biomass for estimating two layer soil properties, which was demonstrated using both synthetic and field experiments in this study, needs now to be tested for a broader range of climatic conditions and crop types, to assess its potential for spatial applications. (C) 2012 Elsevier B.V. All rights reserved.

Combining heterogeneous classifiers for relational databases

Practical usage of machine learning is gaining strategic importance in enterprises looking for business intelligence. However, most enterprise data is distributed in multiple relational databases with expert-designed schema. Using traditional single-table machine learning techniques over such data not only incur a computational penalty for converting to a flat form (mega-join), even the human-specified semantic information present in the relations is lost. In this paper, we present a practical, two-phase hierarchical meta-classification algorithm for relational databases with a semantic divide and conquer approach. We propose a recursive, prediction aggregation technique over heterogeneous classifiers applied on individual database tables. The proposed algorithm was evaluated on three diverse datasets. namely TPCH, PKDD and UCI benchmarks and showed considerable reduction in classification time without any loss of prediction accuracy. (C) 2012 Elsevier Ltd. All rights reserved.

Combining product information and process information to build virtual assembly situations for knowledge acquisition

Assembly is an important part of the product development process. To avoid potential issues during assembly in specialized domains such as aircraft assembly, expert knowledge to predict such issues is helpful. Knowledge based systems can act as virtual experts to provide assistance. Knowledge acquisition for such systems however, is a challenge, and this paper describes one part of an ongoing research to acquire knowledge through a dialog between an expert and a knowledge acquisition system. In particular this paper discusses the use of a situation model for assemblies to present experts with a virtual assembly and help them locate the specific context of the knowledge they provide to the system.

Combining indentation and diffusion couple techniques for combinatorial discovery of high temperature shape memory alloys

We demonstrate the possibility of accelerated identification of potential compositions for high-temperature shape memory alloys (SMAs) through a combinatorial material synthesis and analysis approach, wherein we employ the combination of diffusion couple and indentation techniques. The former was utilized to generate smooth and compositionally graded inter-diffusion zones (IDZs) in the Ni-Ti-Pd ternary alloy system of varying IDZ thickness, depending on the annealing time at high temperature. The IDZs thus produced were then impressed with an indenter with a spherical tip so as to inscribe a predetermined indentation strain. Subsequent annealing of the indented samples at various elevated temperatures, T-a, ranging between 150 and 550 degrees C allows for partial to full relaxation of the strain imposed due to the shape memory effect. If T-a is above the austenite finish temperature, A(f), the relaxation will be complete. By measuring the depth recovery, which serves as a proxy for the shape recovery characteristic of the SMA, a three-dimensional map in the recovery temperature composition space is constructed. A comparison of the published Af data for different compositions with the Ta data shows good agreement when the depth recovery is between 70% and 80%, indicating that the methodology proposed in this paper can be utilized for the identification of promising compositions. Advantages and further possibilities of this methodology are discussed.

Electromagnetic jigsaw: metal-cutting by combining electromagnetic and mechanical Forces

The magnetic saw effect, induced by the Lorentz force generated due to the application of a series of electromagnetic ( EM) pulses, can be utilized to cut a metallic component containing a pre-existing cut or crack. By combining a mechanical force with the Lorentz force, the cut can be propagated along any arbitrary direction in a controlled fashion, thus producing an `electromagnetic jigsaw', yielding a novel tool-less, free-formed manufacturing process, particularly suitable for hard-to-cut metals. This paper presents validation of the above concept based on a simple analytical model, along with experiments on two materials - Pb foil and steel plate. (C) 2013 The Authors. Published by Elsevier B.V. Selection and/or peer-review under responsibility of Professor Bert Lauwers

Combining ``chimie douce'' and green principles for the developing world: Improving industrial viability of photocatalytic water remediation

We highlight the need for a comprehensive, multi-disciplinary approach for the development of cost-effective water remediation methods. Combining ``chimie douce'' and green chemical principles seems essential for making these technologies economically viable and socially relevant (especially in the developing world). A comprehensive approach to water remediation will take into account issues such as nanotoxicity, chemical yield, cost, and ease of deployment in reactors. By considering technological challenges that lie ahead, we will attempt to identify directions that are likely to make photocatalytic water remediation a more global technology than it currently is. (C) 2013 Elsevier Ltd. All rights reserved

Bit Error Probability Analysis of SSK in DF Relaying with Threshold-Based Best Relay Selection and Selection Combining

In this letter, we analyze the end-to-end average bit error probability (ABEP) of space shift keying (SSK) in cooperative relaying with decode-and-forward (DF) protocol, considering multiple relays with a threshold based best relay selection, and selection combining of direct and relayed paths at the destination. We derive an exact analytical expression for the end-to-end ABEP in closed-form for binary SSK, where analytical results agree with simulation results. For non-binary SSK, approximate analytical and simulation results are presented.

Efficient simulation of unitary operators by combining two numerical algorithms: An NMR simulation of the mirror-inversion propagator of an XY spin chain

Precise experimental implementation of unitary operators is one of the most important tasks for quantum information processing. Numerical optimization techniques are widely used to find optimized control fields to realize a desired unitary operator. However, finding high-fidelity control pulses to realize an arbitrary unitary operator in larger spin systems is still a difficult task. In this work, we demonstrate that a combination of the GRAPE algorithm, which is a numerical pulse optimization technique, and a unitary operator decomposition algorithm Ajoy et al., Phys. Rev. A 85, 030303 (2012)] can realize unitary operators with high experimental fidelity. This is illustrated by simulating the mirror-inversion propagator of an XY spin chain in a five-spin dipolar coupled nuclear spin system. Further, this simulation has been used to demonstrate the transfer of entangled states from one end of the spin chain to the other end.