Synthesis, characterization and bactericidal activity of silica/silver core-shell nanoparticles

Silica/silver core-shell nanoparticles (NPs) were synthesized by coating silver NPs on silica core particles (size ~300 ± 10 nm) via electro less reduction method. The core-shell NPs were characterized for their structural, morphological, compositional and optical behavior using X-ray diffraction, scanning electron microscopy, energy dispersive X-ray analysis and UV-Visible spectroscopy, respectively. The size (16-35 nm) and loaded amount of silver NPs on the silica core were found to be dependent upon reaction time and activation method of silica. The bactericidal activity of the NPs was tested by broth micro dilution method against both Bacillus subtilis (gram positive) and Escherichia coli ATCC25922 (gram negative) bacterium. The bactericidal activity of silica/silver core-shell NPS is more against E. coli ATCC25922, when compared to B. subtilis. The minimal inhibitory concentration of the core-shell NPs ranged from 7.8 to 250 μg/mL and is found to be dependent upon the amount of silver on silica, the core. These results suggest that silica/silver core-shell NPs can be utilized as a strong substitutional candidate to control pathogenic bacterium, which are otherwise resistant to antibiotics, making them applicable in diverse medical device

Efficient technique for rice grain classification using back‐propagation neural network and wavelet decomposition

This study describes the classification of four varieties of bulk rice grain images using back‐propagation neural network (BPNN). Eighteen colour features, 27 texture features using grey‐level co‐occurrence matrix, 24 wavelet features and 45 combined features (combination of colour and texture) were extracted from the colour images of bulk rice grains. Classification was carried out on three different data set of images under different environmental conditions. It is seen that BPNN is able to classify faithfully the four varieties of rice grain even with a poor image quality. It is also found that classification based on reduced wavelet features outperform the classification using all other features (such as colour, texture features taken separately) for two data set of images with minimum resolution. The authors have further compared the proposed BPNN technique with other classifiers such as support vector machine, k‐nearest neighbour and naive Bayes classifier on all the three data sets. It is found that the average classification accuracy of more than 96% was able to achieve using BPNN consistently on all different features for each data set

My privacy policy: Exploring end-user specification of free-form location access rules

The increasing inclusion of location and other contextual information in social media applications requires users to be more aware of what their location disclosures reveal. As such, it is important to consider whether existing access-control mechanisms for managing location sharing meet the needs of today's users. We report on a questionnaire (N=103) in which respondents were asked to specify location access control rules using free-form everyday language. Respondents also rated and ranked the importance of a variety of contextual factors that could influence their decisions for allowing or disallowing access to their location. Our findings validate some prior results (e.g., the recipient was the most highly rated and ranked factor and appeared most often in free-form rules) while challenging others (e.g., time-based constraints were deemed relatively less important, despite being features of multiple location-sharing services). We also identified several themes in the free-form rules (e.g., special rules for emergency situations). Our findings can inform the design of tools to empower end users to articulate and capture their access-control preferences more effectively. © 2012 Springer-Verlag