The Present work outlines the antibacterial activity of Fe 3 O 4 nanoparticles synthesized through chemical combustion method where ferric nitrate is used as precursor material and urea as fuel with the assistant of Tween 80, a non-ionic surfactant. The obtained Fe 3 O 4 nanoparticles were characterized by X-ray diffraction, differential thermal analysis/thermo gravimetric analysis (DTA/TGA), particle size analyzer, SEM with EDAX and TEM. Various parameters such as dislocation density, micro strain, analysis of weight loss and surface morphological studies were calculated. The particle size was calculated from XRD and it was found to be 33-40 nm. Using well diffusion method antibacterial activity of Fe 3 O 4 nanoparticles was tested against gram-positive and gramnegative Staphylococus aureus, Xanthomonas, Escherichia coli and Proteus vulgaris. Fe 3 O 4 nanoparticles exhibited strong antibacterial activity against bacterial species.

Nanostructured copper particles are synthesized by Garcinia mangostana leaf extract as reducing agent with copper nitrate. X-ray diffraction study confirms the formation of nanocrystalline cubic phase of copper nanoparticles. The micro-structural properties such as grain size, strain, dislocation density and particle size are examined. The lattice constant is calculated using Nelson-Riley function. Physical parameters like lattice constants, stress, strain, dislocation density and size are calculated. Differential thermal analysis (DTA) and thermo gravimetric (TGA) have confirmed that nanoparticles have phase purity and weight loss percentage is 3.328%. The particle size calculated from XRD is 26.51 nm which is in good agreement with the results of W-H plot, SSP methods and particle analyser. The morphology of prepared copper nanoparticles is characterized by scanning electron microscope (SEM) and TEM. These biologically synthesized nanoparticles are highly antibacterial against Escherichia coli and Staphylococcus aureus. ª 2015 Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

In this paper we present the results of an intensive experimental campaign performed at IEIIT-BO/CNR, Bologna, Italy, on an indoor localization system based on wireless sensors network. Received signal strength indications have been measured and collected using real devices. The data serve as an input data-base for an off-line investigation of different localization techniques. This enables us on one side to improve location accuracy through propagation model tuning, on the other side to compare different location algorithms in term of complexity and performance. Results of these optimizations and comparisons are presented in this paper

No abstract

No abstract