Synthesis and characterization of novel curcumin based polyurethanes varying diisocyanates structure

In this research work, novel polyurethanes (PUs) based on blends of curcumin/1,4-butane diol (BDO) by varying the structure of diisocyanates were prepared following step growth polymerization. Structural study of blends and various diisocyanates based PU through Fourier Transform Infrared (FTIR) spectroscopy confirmed the incorporation of curcumin into the backbone of the PU. The scanning electron microscopic (SEM) study confirmed the well dispersion of incorporated curcumin and homogeneity of surface of synthesized samples. The SEM results also indicated that surface morphology of synthesized samples much dependent on diisocynates structure. Moreover SEM images inferred that phase separation is more pronounced in aromatic diisocyanate based PU. The anti-bacterial and anti-fungal tests were performed against different strains in order to determine the biocompatibility of the curcumin based PU. The antimicrobial activity results revealed that the material having aromatic diisocyanate are more biocompatible than the aliphatic diisocyanates in the PU structure. On the whole, this work is actually a step towards the generation of novel biocompatible materials preferably useful for biomedical applications.     

Exploration of connectivity with SEM: An fMRI study of resting state

In this era, the neuroscientists get attention to find a network of brain which is activated in resting state of mind. It is challenging for any analytical technique to find out the connectivity among Brodmann areas of brain in resting state. To find network, a study was conducted in which brains are scan by functional magnetic resonance imaging of four healthy right handed individuals. Exploratory factor analysis was used to explore that which Brodmann areas are related to each other and then structural equation model has applied on explored factors (lobes) to find a network of activated brain in resting state. © 2016 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 26, 264–269, 2016     

Structural,mechanical, and electrical properties of carbon nanoparticles synthesized from diesel

We studied the elemental analysis, structural morphology, mechanical, and electrical properties of carbon nanoparticles synthesized from diesel. The spherical carbon particle size in the range of about 10 to 80 nm in diameter was observed in scanning electron microscope (SEM) studies that were identified by Atomic force microscopy (AFM) study as an aggregation of carbon particles of average size 2.5 nm. The surface rms of carbon nanoparticle thin film (CNTF) was measured directly by AFM and found 0.22 nm. The Derjaguin–Muller–Toporov (DMT) elastic modulus of carbon nanoparticles (CNPs) was measured by PeakForce QNM mode of AFM. The minimum and maximum elastic modulus was measured of 0.40 GPa and 43.89 GPa, respectively. The resistivity, conductivity, magneto resistance, mobility, and average Hall co-efficient were measured by “Ecopia Hall-effect measurement system” by four-point Van der Pauw approach at ambient condition. We demonstrated I–V characteristic at the Indium/CNTF thin film interface, which is accompanied by rectifying behavior.     

Low Temperature Hall Effect Investigation of Conducting Polymer-Carbon Nanotubes Composite Network

Polypyrrole (PPy) and polypyrrole-carboxylic functionalized multi wall carbon nanotube composites (PPy/f-MWCNT) were synthesized by in situ chemical oxidative polymerization of pyrrole on the carbon nanotubes (CNTs). The structure of the resulting complex nanotubes was characterized by transmission electron microscopy (TEM) and X-ray diffraction (XRD). The effects of f-MWCNT concentration on the electrical properties of the resulting composites were studied at temperatures between 100 K and 300 K. The Hall mobility and Hall coefficient of PPy and PPy/f-MWCNT composite samples with different concentrations of f-MWCNT were measured using the van der Pauw technique. The mobility decreased slightly with increasing temperature, while the conductivity was dominated by the gradually increasing carrier density.     

One-Step Quenching and Partitioning Heat Treatment of Medium Carbon Low Alloy Steel

This paper presents the results of novel one-step quenching and partitioning (Q&P) heat treatment conducted on medium carbon low alloy steel sheet. Samples were austenitised at 1193 K followed by interrupted quenching at 473 K for different partitioning times and finally they were quenched in water. Dilatometry was employed for selection of treatment temperatures. Optical and scanning electron microscopy was carried out to examine the microstructural changes. Volume fraction of retained austenite was measured by x-ray diffraction technique. Resulting microstructures were correlated with the mechanical properties such hardness, tensile strength, elongation, impact absorbed energy, etc. The notch tensile and fracture toughness properties of Q&P steels are still lacking therefore notch tensile strength and plain strain fracture toughness tests were conducted and results are reported here. Results of Q&P treatments were also compared with the properties obtained by conventional Quenching and Tempering (Q&T) and normalizing treatments. Optimum strength-ductility balance of about 2000 MPa tensile strength with 11% elongation was achieved in samples quenched at 473 K and isothermally partitioned for 100 s. Higher ductility of Q&P steel was attributed to the presence of 6.8% film-type interlath retained austenite. Fine-grained martensitic structure with high density of interphase boundaries imparted ultrahigh strength. It was further noted that the impact toughness, notch tensile strength and fracture toughness of 1000 s partitioned samples was higher than 100 s partitioned samples. Possible reasons for high toughness are synergetic effect of recovery of dislocations, partial loss of martensite tetragonality and precipitation of fine transition carbides.     

Automated detection of exudates and macula for grading of diabetic macular edema

Medical systems based on state of the art image processing and pattern recognition techniques are very common now a day. These systems are of prime interest to provide basic health care facilities to patients and support to doctors. Diabetic macular edema is one of the retinal abnormalities in which diabetic patient suffers from severe vision loss due to affected macula. It affects the central vision of the person and causes total blindness in severe cases. In this article, we propose an intelligent system for detection and grading of macular edema to assist the ophthalmologists in early and automated detection of the disease. The proposed system consists of a novel method for accurate detection of macula using a detailed feature set and Gaussian mixtures model based classifier. We also present a new hybrid classifier as an ensemble of Gaussian mixture model and support vector machine for improved exudate detection even in the presence of other bright lesions which eventually leads to reliable classification of input retinal image in different stages of macular edema. The statistical analysis and comparative evaluation of proposed system with existing methods are performed on publicly available standard retinal image databases. The proposed system has achieved average value of 97.3%, 95.9% and 96.8% for sensitivity, specificity and accuracy respectively on both databases.     

A music symbols recognition method using pattern matching along with integrated projection and morphological operation techniques

Multimedia Tools and Applications - Optical Music Recognition (OMR) can be divided into three main phases: (i) staff line detection and removal. The goal of this phase is to detect and to remove...