Deployment strategy for controlled morphologies in sessile, mixed colloidal droplets

Colloidal systems offer an effective medium to micro-engineer complex structures without involving sophisticated fabrication procedures. This article presents a deployment strategy of multiple droplets of different colloidal composition and utilizes the inherent capillary flow driven self assembly of nanoparticles to construct stacks of multiple materials on a given glass substrate. Here we used aqueous nano-crystalline titania and nano-amorphous silica solutions as the two materials. Initially, a pure nanotitania (nanosilica) droplet is deployed and allowed to dry partially. Subsequently, a second droplet of pure nanosilica (nanotitania) is deployed co-axially on the partially dried precipitate. The proposed deployment strategy allowed significant morphological differences when the deployment order of nanosilica and nanotitania were interchanged. Compositional analysis performed using EDX (Energy Dispersive X-ray spectroscopy) showed preferential deposition of nanosilica and nanotitania along the radial as well as the axial plane of the final deposit pattern. The underlying mechanism for such a phenomenon could be attributed to the contact line dynamics of a sessile double droplet. We also observe heteroaggregation of the nanosilica-nanotitania interaction along a narrow interface which resulted in nanotitania particles clustering into isolated islands embedded into a matrix of nanosilica particles. Overall, this work elucidates the evaporation driven dynamics of a mixed colloidal system which displays both macroscopic as well as microscopic phenomena. Such a system could be used to generate ordered arrays of functional materials with engineered micro to nano-scale properties.

Improved recognition of aged Kannada documents by effective segmentation of merged characters

In optical character recognition of very old books, the recognition accuracy drops mainly due to the merging or breaking of characters. In this paper, we propose the first algorithm to segment merged Kannada characters by using a hypothesis to select the positions to be cut. This method searches for the best possible positions to segment, by taking into account the support vector machine classifier's recognition score and the validity of the aspect ratio (width to height ratio) of the segments between every pair of cut positions. The hypothesis to select the cut position is based on the fact that a concave surface exists above and below the touching portion. These concave surfaces are noted down by tracing the valleys in the top contour of the image and similarly doing it for the image rotated upside-down. The cut positions are then derived as closely matching valleys of the original and the rotated images. Our proposed segmentation algorithm works well for different font styles, shapes and sizes better than the existing vertical projection profile based segmentation. The proposed algorithm has been tested on 1125 different word images, each containing multiple merged characters, from an old Kannada book and 89.6% correct segmentation is achieved and the character recognition accuracy of merged words is 91.2%. A few points of merge are still missed due to the absence of a matched valley due to the specific shapes of the particular characters meeting at the merges.

Immune responses against hepatitis C virus genotype 3a virus-like particles in mice: A novel VLP prime-adenovirus boost strategy

Chronic hepatitis C virus (HCV) infection represents a major health threat to global population. In India, approximately 15-20% of cases of chronic liver diseases are caused by HCV infection. Although, new drug treatments hold great promise for HCV eradication in infected individuals, the treatments are highly expensive. A vaccine for preventing or treating HCV infection would be of great value, particularly in developing countries. Several preclinical trials of virus-like particle (VLP) based vaccine strategies are in progress throughout the world. Previously, using baculovirus based system, we have reported the production of hepatitis C virus-like particles (HCV-LPs) encoding structural proteins for genotype 3a, which is prevalent in India. In the present study, we have generated HCV-LPs using adenovirus based system and tried different immunization strategies by using combinations of both kinds of HCV-LPs with other genotype 3a-based immunogens. HCV-LPs and peptides based ELISAs were used to evaluate antibody responses generated by these combinations. Cell-mediated immune responses were measured by using T-cell proliferation assay and intracellular cytokine staining. We observed that administration of recombinant adenoviruses expressing HCV structural proteins as final booster enhances both antibody as well as T-cell responses. Additionally, reduction of binding of VLP and JFH1 virus to human hepatocellular carcinoma cells demonstrated the presence of neutralizing antibodies in immunized sera. Taken together, our results suggest that the combined regimen of VLP followed by recombinant adenovirus could more effectively inhibit HCV infection, endorsing the novel vaccine strategy. (C) 2015 Elsevier Ltd. All rights reserved.

A strategy to achieve enhanced electromagnetic interference shielding at ultra-low concentration of multiwall carbon nanotubes in P alpha MSAN/PMMA blends in the presence of a random copolymer PS-r-PMMA

A unique strategy was adopted to achieve an ultra-low electrical percolation threshold of multiwall carbon nanotubes (MWNTs) (0.25 wt%) in a classical partially miscible blend of poly-alpha-methylstyrene-co-acrylonitrile and poly(methyl methacrylate) (P alpha MSAN/PMMA), with a lower critical solution temperature. The polymer blend nanocomposite was prepared by standard melt-mixing followed by annealing above the phase separation temperature. In a two-step mixing protocol, MWNTs were initially melt-mixed with a random PS-r-PMMA copolymer and subsequently diluted with 85/15 P alpha MSAN/PMMA blends in the next mixing step. Mediated by the PS-r-PMMA, the MWNTs were mostly localized at the interface and bridged the PMMA droplets. This strategy led to enhanced electromagnetic interference (EMI) shielding effectiveness at 0.25 wt% MWNTs through multiple scattering from MWNT-covered droplets, as compared to the blends without the copolymer, which were transparent to electromagnetic radiation.

Stabilization of a Tetrahedral (Mn5+O4) Chromophore in Ternary Barium Oxides as a Strategy toward Development of New Turquoise/Green-Colored Pigments

An experimental investigation of the stabilization of the turquoise-colored chrornophore (Mn5+O4) in various oxide hosts, viz., A(3)(VO4)(2) (A = Ba, Sr, Ca), YVO4, and Ba2MO4 (M = Ti, Si), has been carried out. The results reveal that substitution of Mn5+O4 occurs in Ba-3(VO4)(2) forming the entire solid solution series Ba-3(V1-x MnxO4)(2) (0 < x <= 1.0), while with the corresponding strontium derivative, only up to about 10% of Mn5+O4 substitution is possible. Ca-3(VO4)(2) and YVO4 do not stabilize Mn5+O4 at all. With Ba2MO4 (M = Ti, Si), we could prepare only partially substituted materials, Ba2M1-xMn5+O4+x/2 for x up to 0.15, that are turquoise-colored. We rationalize the results that a large stabilization of the O 2p-valence band states occurs in the presence of the electropositive barium that renders the Mn5+ oxidation state accessible in oxoanion compounds containing PO43-, VO43-, etc. By way of proof-of-concept, we synthesized new turquoise-colored Mn5+O4 materials, Ba-5(BO3)(MnO4)(2)Cl and Ba-5(BO3)(PO4)(MnO4)Cl, based on the apatite-Ba-5(PO4)(3)Cl-structure.

CROWD FLOW SEGMENTATION IN COMPRESSED DOMAIN USING CRF

Crowd flow segmentation is an important step in many video surveillance tasks. In this work, we propose an algorithm for segmenting flows in H.264 compressed videos in a completely unsupervised manner. Our algorithm works on motion vectors which can be obtained by partially decoding the compressed video without extracting any additional features. Our approach is based on modelling the motion vector field as a Conditional Random Field (CRF) and obtaining oriented motion segments by finding the optimal labelling which minimises the global energy of CRF. These oriented motion segments are recursively merged based on gradient across their boundaries to obtain the final flow segments. This work in compressed domain can be easily extended to pixel domain by substituting motion vectors with motion based features like optical flow. The proposed algorithm is experimentally evaluated on a standard crowd flow dataset and its superior performance in both accuracy and computational time are demonstrated through quantitative results.