AC Potential-Dependent Concentration Variation and Domain Wall Pinning in Co1−x Zn x (x=0.4−0.5) Nanorods

The Co_1?x Zn _x (x=0.4?0.5) nanorods were synthesized via an AC electrochemical deposition method into anodized aluminum oxide (AAO) templates at different voltages ranging from 10 to 18 V, and nanorods of varying concentrations of Co and Zn were obtained. The characterization tools were used to examine different aspects of nanorods, e.g., shape, size, morphology, chemical composition, and magnetic behavior. Scanning electron microscope (SEM) images show that CoZn nanorods have length L=1μm and diameter d=50 nm. The grain size was calculated to be 25.4 nm using an X-ray diffraction (XRD) technique. The XRD also shows some other phases of ZnCoO. The M?H loops measured by a vibrating sample magnetometer (VSM) at room temperature show pure ferromagnetic behavior at all AC potentials. The nanorods show magnetic isotropic behavior due to strong magnetic interactions and presence of random nanorods. The potential-dependent coercivity H _c and saturation magnetization M _s show a non-linear curve which is explained on the basis of magnetic islands and domain wall pinning. This study is useful to tune the magnetic properties of nanorods by a simple and low-cost technique.     

A new rectangular window based image cropping method for generalization of brain neoplasm classification systems

Classification of brain neoplasm images is one of the most challenging research areas in the field of medical image processing. The main objective of this study is to design a brain neoplasm classification system that can be trained using multiple various sized MR images of different institutions. The proposed method is a generalized classification system; it can be used in a single institute or in a number of institutions at the same time, without any restriction on image size. The generalization and unbiased capability of the proposed method can bring researchers on a single platform to work on some standard forms of computer aided diagnosis system with more efficient diagnostic capabilities. In this study, a suitable size of moveable rectangular window is used between segmentation and feature extraction stages. A semiautomatic, localized region based active contour method is used for segmentation of brain neoplasm region. Discrete wavelet transform for feature extraction, principal component analysis for feature selection and support vector machine is used as classifier. For the first time MR images of 2 sizes and from different institutions are used in training and testing of brain neoplasm classifier. Three glioma grades were classified using 92 MR images. The proposed method achieved the highest accuracy of 88.26%, the highest sensitivity of 92.23% and the maximum specificity of 93.93%. In addition, the proposed method is computationally less complex, requires shorter processing time and is more efficient in terms of storage capacity.     

Fabrication of silver monoliths using Brij 52 surfactant and TiO2 nanoparticles and their applications to reduce Fast Sulphon Black F dye and sensor against Pb2+

Journal of Materials Science: Materials in Electronics - Silver monoliths were prepared using Brij 52 as surfactant with and without dextran and reinforcing agents TiO2NPs by modified sol–gel...     

Antimicrobial Peptides from Plants: A cDNA-Library Based Isolation,Purification, Characterization Approach and Elucidating Their Modes of Action

Even in a natural ecosystem, plants are continuously threatened by various microbial diseases. To save themselves from these diverse infections, plants build a robust, multilayered immune system through their natural chemical compounds. Among the several crucial bioactive compounds possessed by plants’ immune systems, antimicrobial peptides (AMPs) rank in the first tier. These AMPs are environmentally friendly, anti-pathogenic, and do not bring harm to humans. Antimicrobial peptides can be isolated in several ways, but recombinant protein production has become increasingly popular in recent years, with the Escherichia coli expression system being the most widely used. However, the efficacy of this expression system is compromised due to the difficulty of removing endotoxin from its system. Therefore, this review suggests a high-throughput cDNA library-based plant-derived AMP isolation technique using the Bacillus subtilis expression system. This method can be performed for large-scale screening of plant sources to classify unique or homologous AMPs for the agronomic and applied field of plant studies. Furthermore, this review also focuses on the efficacy of plant AMPs, which are dependent on their numerous modes of action and exceptional structural stability to function against a wide range of invaders. To conclude, the findings from this study will be useful in investigating how novel AMPs are distributed among plants and provide detailed guidelines for an effective screening strategy of AMPs.     

Carburization of Si microwires by chemical vapour deposition

We report the elaboration of silicon carbide (SiC) nanostructures thanks to the carburization of silicon microwires (MWs) under methane at high temperature. The produced SiC nanostructures display a tubular shape and are polycrystalline. The as-prepared silicon carbide microtubes (MTs) were characterized and studied by scanning electron microscopy (SEM), dual focused ion beam-scanning electron microscope (FIB-SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD) and Raman spectroscopy. The formation of microtubes can be explained by the out-diffusion of Si through the SiC during the carburization process.     

Effect of temperature and thermodynamic quality of solvent over unperturbed chain dimensions of nylon 6

A nylon 6 sample having average molecular mass 4.825 × 10⁵ g mol^?1 was fractionated into five different fractions with respect to molecular mass, which ranged from 3691 to 999,000 g mol^?1. The light scattering and intrinsic viscosity measurements were made in m‐cresol and its mixture with 1,4‐dioxane. The second virial coefficient, radius of gyration and Mark Houwink's constant and unperturbed chain dimensions were determined by light scattering and viscosity measurement. It has been observed that all these parameters are composition of solvent and temperature dependent. The solvent having composition of 97% m‐cresol and 3% dioxane, was best and it deteriorated with the increase/decrease in percentage of 1,4‐dioxane in m‐cresol. However, its thermodynamic quality was enhanced with the temperature. Such variation in quality of solvent was reflected in all the estimated parameters and showed maxima at this composition of solvent. The unperturbed dimensions obtained by different methods though, differed in values but showed same trend and NA‐MKB method gave close results to the one obtained through [η_o]. A new expression has also been proposed relating k_o to solvent quality and temperature and the data obtained by us for nylon‐6 and the one obtained from the literature for dextran obeyed this expression up to large extent irrespective of the solvent composition and temperature. The proposed equations have also been applied to dextran/methoxy ethylene and dextran/ethylene glycol systems and worked well. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011.     

Wavelength Dependence of the Aerosol Angstrom Exponent and Its Implications Over Delhi,India

The aerosol optical depth (AOD), Angstrom coefficients (α and β), and the second-order Angstrom exponent (α′) obtained by Microtops-II sun photometer have been analyzed in the spectral range 0.34–0.87 μm over the urban polluted city of Delhi, India for the period 2007–2008, aiming at investigating the physical and optical properties of aerosols. The average values of AOD at 500 nm, α and β (in the range 340–870 nm) are found to be 0.78 ± 0.32, 0.78 ± 0.28, and 0.45 ± 0.21, respectively, for the entire period of observations. The AOD data show significant curvature in the lnτ versus lnλ relationship suggesting different dominant aerosol types depending on season. In order to analyze further the curvature effect and the relative dominance of aerosol size, α has been calculated in three wavelength bands, i.e., shorter (0.34–0.50 μm), longer (0.675–0.87 μm), and broad (0.34–0.87 μm) during four seasons, summer (April–June), monsoon (July–September), winter (October–January), and spring (February–March) accompanied with calculations of α′, which quantifies the deviation of logarithmic behavior of AOD with lnλ. The α′ values are found to be positive and higher in the months of October–December and mostly negative in February and March, while close to zero values of α′ are found in April–August. These results indicate that winter season exhibits dominance of fine-mode aerosols while summer relatively higher concentration of coarse-mode particles. On the other hand, monsoon and spring seasons revealed the presence of mixed type, both fine- and coarse-mode aerosols over Delhi.     

Probabilistic Design space determination in pharmaceutical product development: A Bayesian/latent variable approach

To find the design space (DS) of a pharmaceutical process, quantification of the “assurance of quality” for the product under development is required. In this study, latent‐variable modeling is combined with multivariate Bayesian regression to identify a subset of input combinations (process operating conditions and raw materials properties) within which the DS of the product will lie at a probability equal to, or greater than, an assigned threshold. Partial least‐squares regression is used to obtain a linear transformation between the original multidimensional input space and a low‐dimensional latent space. The input domain is then discretized on its lower dimensional representation and a Bayesian posterior predictive approach is used to quantify the probability that the critical quality attributes of the product will meet their specifications for each discretization point. The methodology is tested on two case studies taken from the literature, one of which involving experimental data. The ability of the proposed approach to obtain a probabilistic identification of the DS, while simultaneously reducing the computational burden for the discretization of the input domain and providing a simple graphical representation of the DS, is shown. © 2018 American Institute of Chemical Engineers AIChE J, 64: 2438–2449, 2018