Reflection and transmission coefficient of yttrium iron garnet filled polyvinylidene fluoride composite using rectangular waveguide at microwave frequencies.

The sol-gel method was carried out to synthesize nanosized Yttrium Iron Garnet (YIG). The nanomaterials with ferrite structure were heat-treated at different temperatures from 500 to 1000 °C. The phase identification, morphology and functional groups of the prepared samples were characterized by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FT-IR), respectively. The YIG ferrite nanopowder was composited with polyvinylidene fluoride (PVDF) by a solution casting method. The magnitudes of reflection and transmission coefficients of PVDF/YIG containing 6, 10 and 13% YIG, respectively, were measured using rectangular waveguide in conjunction with a microwave vector network analyzer (VNA) in X-band frequencies. The results indicate that the presence of YIG in polymer composites causes an increase in reflection coefficient and decrease in transmission coefficient of the polymer.

Synthesis and characterization of polyethylene glycol mediated silver nanoparticles by the green method.

The roles of green chemistry in nanotechnology and nanoscience fields are very significant in the synthesis of diverse nanomaterials. Herein, we report a green chemistry method for synthesized colloidal silver nanoparticles (Ag NPs) in polymeric media. The colloidal Ag NPs were synthesized in an aqueous solution using silver nitrate, polyethylene glycol (PEG), and ß-D-glucose as a silver precursor, stabilizer, and reducing agent, respectively. The properties of synthesized colloidal Ag NPs were studied at different reaction times. The ultraviolet-visible spectra were in excellent agreement with the obtained nanostructure studies performed by transmission electron microscopy (TEM) and their size distributions. The Ag NPs were characterized by utilizing X-ray diffraction (XRD), zeta potential measurements and Fourier transform infrared (FT-IR). The use of green chemistry reagents, such as glucose, provides green and economic features to this work.

Green biosynthesis of silver nanoparticles using Callicarpa maingayi stem bark extraction.

Different biological methods are gaining recognition for the production of silver nanoparticles (Ag-NPs) due to their multiple applications. The use of plants in the green synthesis of nanoparticles emerges as a cost effective and eco-friendly approach. In this study the green biosynthesis of silver nanoparticles using Callicarpa maingayi stem bark extract has been reported. Characterizations of nanoparticles were done using different methods, which include; ultraviolet-visible spectroscopy (UV-Vis), powder X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy dispersive X-ray fluorescence (EDXF) spectrometry, zeta potential measurements and Fourier transform infrared (FT-IR) spectroscopy. UV-visible spectrum of the aqueous medium containing silver nanoparticles showed absorption peak at around 456 nm. The TEM study showed that mean diameter and standard deviation for the formation of silver nanoparticles were 12.40 ± 3.27 nm. The XRD study showed that the particles are crystalline in nature, with a face centered cubic (fcc) structure. The most needed outcome of this work will be the development of value added products from Callicarpa maingayi for biomedical and nanotechnology based industries.

Novel trajectory clustering method based on distance dependent Chinese restaurant process.

Trajectory clustering and path modelling are two core tasks in intelligent transport systems with a wide range of applications, from modeling drivers' behavior to traffic monitoring of road intersections. Traditional trajectory analysis considers them as separate tasks, where the system first clusters the trajectories into a known number of clusters and then the path taken in each cluster is modelled. However, such a hierarchy does not allow the knowledge of the path model to be used to improve the performance of trajectory clustering. Based on the distance dependent Chinese restaurant process (DDCRP), a trajectory analysis system that simultaneously performs trajectory clustering and path modelling was proposed. Unlike most traditional approaches where the number of clusters should be known, the proposed method decides the number of clusters automatically. The proposed algorithm was tested on two publicly available trajectory datasets, and the experimental results recorded better performance and considerable improvement in both datasets for the task of trajectory clustering compared to traditional approaches. The study proved that the proposed method is an appropriate candidate to be used for trajectory clustering and path modelling.

An Efficient Optimization Method for Solving Unsupervised Data Classification Problems.

Unsupervised data classification (or clustering) analysis is one of the most useful tools and a descriptive task in data mining that seeks to classify homogeneous groups of objects based on similarity and is used in many medical disciplines and various applications. In general, there is no single algorithm that is suitable for all types of data, conditions, and applications. Each algorithm has its own advantages, limitations, and deficiencies. Hence, research for novel and effective approaches for unsupervised data classification is still active. In this paper a heuristic algorithm, Biogeography-Based Optimization (BBO) algorithm, was adapted for data clustering problems by modifying the main operators of BBO algorithm, which is inspired from the natural biogeography distribution of different species. Similar to other population-based algorithms, BBO algorithm starts with an initial population of candidate solutions to an optimization problem and an objective function that is calculated for them. To evaluate the performance of the proposed algorithm assessment was carried on six medical and real life datasets and was compared with eight well known and recent unsupervised data classification algorithms. Numerical results demonstrate that the proposed evolutionary optimization algorithm is efficient for unsupervised data classification.

Green biosynthesis of silver nanoparticles using Curcuma longa tuber powder.

Green synthesis of noble metal nanoparticles is a vastly developing area of research. Metallic nanoparticles have received great attention from chemists, physicists, biologists, and engineers who wish to use them for the development of a new-generation of nanodevices. In this study, silver nanoparticles were biosynthesized from aqueous silver nitrate through a simple and eco-friendly route using Curcuma longa tuber-powder extracts, which acted as a reductant and stabilizer simultaneously. Characterizations of nanoparticles were done using different methods, which included ultraviolet-visible spectroscopy, powder X-ray diffraction, transmission electron microscopy, scanning electron microscopy, energy-dispersive X-ray fluorescence spectrometry, and Fourier-transform infrared spectroscopy. The ultraviolet-visible spectrum of the aqueous medium containing silver nanoparticles showed an absorption peak at around 415 nm. Transmission electron microscopy showed that mean diameter and standard deviation for the formation of silver nanoparticles was 6.30 ± 2.64 nm. Powder X-ray diffraction showed that the particles are crystalline in nature, with a face-centered cubic structure. The most needed outcome of this work will be the development of value-added products from C. longa for biomedical and nanotechnology-based industries.

Investigation of antibacterial properties silver nanoparticles prepared via green method.

BACKGROUND: This study aims to investigate the influence of different stirring times on antibacterial activity of silver nanoparticles in polyethylene glycol (PEG) suspension. The silver nanoparticles (Ag-NPs) were prepared by green synthesis method using green agents, polyethylene glycol (PEG) under moderate temperature at different stirring times. Silver nitrate (AgNO3) was taken as the metal precursor while PEG was used as the solid support and polymeric stabilizer. The antibacterial activity of different sizes of nanosilver was investigated against Gram-positive [Staphylococcus aureus] and Gram-negative bacteria [Salmonella typhimurium SL1344] by the disk diffusion method using Müeller-Hinton Agar. RESULTS: Formation of Ag-NPs was determined by UV-vis spectroscopy where surface plasmon absorption maxima can be observed at 412-437 nm from the UV-vis spectrum. The synthesized nanoparticles were also characterized by X-ray diffraction (XRD). The peaks in the XRD pattern confirmed that the Ag-NPs possessed a face-centered cubic and peaks of contaminated crystalline phases were unable to be located. Transmission electron microscopy (TEM) revealed that Ag-NPs synthesized were in spherical shape. The optimum stirring time to synthesize smallest particle size was 6 hours with mean diameter of 11.23 nm. Zeta potential results indicate that the stability of the Ag-NPs is increases at the 6 h stirring time of reaction. The Fourier transform infrared (FT-IR) spectrum suggested the complexation present between PEG and Ag-NPs. The Ag-NPs in PEG were effective against all bacteria tested. Higher antibacterial activity was observed for Ag-NPs with smaller size. These suggest that Ag-NPs can be employed as an effective bacteria inhibitor and can be applied in medical field. CONCLUSIONS: Ag-NPs were successfully synthesized in PEG suspension under moderate temperature at different stirring times. The study clearly showed that the Ag-NPs with different stirring times exhibit inhibition towards the tested gram-positive and gram-negative bacteria.

Synthesis and characterization of silver/montmorillonite/chitosan bionanocomposites by chemical reduction method and their antibacterial activity.

Silver nanoparticles (AgNPs) of a small size were successfully synthesized using the wet chemical reduction method into the lamellar space layer of montmorillonite/chitosan (MMT/Cts) as an organomodified mineral solid support in the absence of any heat treatment. AgNO3, MMT, Cts, and NaBH4 were used as the silver precursor, the solid support, the natural polymeric stabilizer, and the chemical reduction agent, respectively. MMT was suspended in aqueous AgNO3/Cts solution. The interlamellar space limits were changed (d-spacing = 1.24-1.54 nm); therefore, AgNPs formed on the interlayer and external surface of MMT/Cts with d-average = 6.28-9.84 nm diameter. Characterizations were done using different methods, ie, ultraviolet-visible spectroscopy, powder X-ray diffraction, transmission electron microscopy, scanning electron microscopy, energy dispersive X-ray fluorescence spectrometry, and Fourier transform infrared spectroscopy. Silver/montmorillonite/chitosan bionanocomposite (Ag/MMT/Cts BNC) systems were examined. The antibacterial activity of AgNPs in MMT/Cts was investigated against Gram-positive bacteria, ie, Staphylococcus aureus and methicillin-resistant S. aureus and Gram-negative bacteria, ie, Escherichia coli, E. coli O157:H7, and Pseudomonas aeruginosa by the disc diffusion method using Mueller Hinton agar at different sizes of AgNPs. All of the synthesized Ag/MMT/Cts BNCs were found to have high antibacterial activity. These results show that Ag/MMT/Cts BNCs can be useful in different biological research and biomedical applications, including surgical devices and drug delivery vehicles.