Earthworm coelomocytes as nanoscavenger of ZnO NPs

Earthworms can ‘biotransform’ or ‘biodegrade’ chemical contaminants, rendering them harmless in their bodies, and can bioaccumulate them in their tissues. They ‘absorb’ the dissolved chemicals through their moist ‘body wall’ due to the interstitial water and also ingest by ‘mouth’ while soil passes through the gut. Since the advent of the nanotechnology era, the environmental sink has been continuously receiving engineered nanomaterials as well as their derivatives. Our current understanding of the potential impact of nanomaterials and their natural scavenger is limited. In the present investigation, we studied the cellular uptake of ZnO nanoparticles (NPs) by coelomocytes especially by chloragocytes of Eisenia fetida and their role as nanoscavenger. Results from exposure to 100- and 50-nm ZnO NPs indicate that coelomocytes of the earthworm E. fetida show no significant DNA damage at a dose lower than 3 mg/l and have the potential ability to uptake ZnO NPs from the soil ecosystem and transform them into microparticles.     

Coexistence of interfacial stress and charge transfer in graphene oxide-based magnetic nanocomposites

In this paper, the existence of both compressive stress and charge transfer process in hydrothermally synthesized cobalt ferrite–graphene oxide (CoFe₂O₄/GO) nanocomposites has been established. Transmission electron microscopy results reveal the decoration of CoFe₂O₄ nanoparticles on GO sheets. Magnetic response of nanocomposites was confirmed from superconducting quantum interference device magnetometer measurement. Optical properties of these nanocomposites were investigated by Raman spectroscopy. The interfacial compressive stress involved in this system has been evaluated from observed blue shift of characteristic G peak of graphene oxide. Increase in the full-width half-maximum value as well as upshift in D and G peaks is clear indications of involvement of charge transfer process between GO sheets and dispersed magnetic nanoparticles. The effect of charge transfer process is quantified in terms of shifting of Fermi energy level of these nanocomposites. This is evaluated from variation in contact surface potential difference using scanning Kelvin probe microscopy. XRD spectra of CoFe₂O₄/GO confirm the polycrystalline nature of CoFe₂O₄ nanoparticles. Lattice strain estimated from XRD peaks is correlated with the observed Raman shift.     

Buccoadhesive Tablets of Nifedipine: Standardization of A Novel Buccoadhesive-Erodible Carrier

Buccoadhesive tablets of nifedipine were obtained by incorporation of nifedipine in suitable carrier systems standardised based on bioadhesion and dissolution. The carrier systems were formulated using sodium alginate as the bioadhesive. Mannitol, lactose, polyethylene glycol 6000 and polyethylene glycol 4000 were incorporated as solubilisers, singly or in combination. Carrier systems having a diameter of 11 mm and weighing about 200 mg were obtained by standard tabletting techniques using polyvinylpyrolidone as the binder. The systems were evaluated for bioadhesion and dissolution, 'in vitro' and 'in vivo' in seven normal healthy human volunteers. Based on these studies, nifedipine (5 mg) was incorporated in selected carrier systems to obtain buccoadhesive tablets of nifedipine. These tablets exhibited rapid 'in vitro' drug release.     

Corner based statistical modelling in vehicle detection under various condition for traffic surveillance

The paper proposes a robust approach to detect and track the vehicle under various climatic conditions and in the presence of camera shake, shadows, sudden illumination change. Corners have significant features to detect and track the vehicle. Corner points from the vehicular region are segmented from non - vehicular regions based on the statistical background corner point model. The foreground corner points that belong to the vehicular region are grouped using Euclidean distance as they are closely associated with each other. The flickering effects caused by the corner detection algorithm are handled by tracking these corner points. The detection accuracy of the algorithm is 94.32%.

     

What About Spectrum Opportunities in ‘Angle’ Dimension for Dynamic Spectrum Access in Cognitive Radio Network context? A new Paradigm in Spectrum Sensing

The cognitive radio technology is the new paradigm to fulfill ever increasing need of bandwidth ultimately the radio spectrum by accommodating the radio spectrum dynamically to secondary users/unlicensed users without causing the interference. In cognitive radio, the spectrum opportunities have been checked for Space, Time and frequency dimensions but ‘Angle’ dimension has not been explored till now. In this paper we have investigated accuracy of various ‘Angle-of-Arrival (AoA)’ estimation algorithms: ESPRIT, MUSIC, Bartlett, and Capon for opportunistic secondary users’ network under AWGN and time varying fading channels. The improvement in performance of these algorithms has been observed as array elements, signal-to-noise ratio and samples increases. An ‘adaptive thresholding’ technique has been proposed to improve the performance of AoA algorithms. Thus by estimating an ‘Angle-of- Arrival’ of licensed users, the unlicensed users can be accommodated in the same geographical area into the same channel in the same frequency band at the same time by directing unlicensed users’ beam in different direction than the direction of licensed users. Thereby improving spectrum utilization.     

TLC-Digital Image-Based Fluorometric Analysis of Ergosterol and Chitin Content in Food Grains Artificially Infested with <Emphasis Type="Italic">Aspergillus flavus</Emphasis> and <Emphasis Type="Italic">Fusarium verticillioides</Emphasis>

Novel thin-layer chromatography-digital image-based analytical methods were developed for the quantitation of ergosterol and chitin content in six food matrices (rice, wheat, maize, sorghum, groundnut, and sunflower), artificially infested with Aspergillus flavus (MTCC 6513)/Fusarium verticillioides (MRC 826). For ergosterol, single-step method, based on liquid/liquid extraction, was followed by thin-layer chromatography (TLC). Chitin was solubilized using lithium chloride (5%) in dimethyl acetamide and converted to chitosan using 5 N NaOH and subsequently complexed with calcofluor white dye. The absorption and emission maxima of chitosan-calcofluor complex were recorded at λ 350/230 and 430 nm, respectively. The sensitivity based on the limit of detection (LOD) was found to be 100 ng both for ergosterol and chitin analysis. Based on ergosterol and chitin analysis, groundnut and maize were found to be suitable substrates for A. flavus (p?<?0.013 and p?<?0.01), while sorghum followed by groundnut and sunflower were found to be ideal for F. verticillioides (p?<?0.01 and p?<?0.0001) and rice was established as poor substrate as there was no growth on it up to 12 days of incubation. A strong correlation was found between ergosterol and chitin contents with regression (r ²) values of 0.974 and 0.997 in food grains inoculated with A. flavus and F. verticillioides, respectively, during the period of infection. The authenticity of the two methods developed was further confirmed by applying them to commercial food grains and flours. Thus, ergosterol in combination with chitin analysis could be successfully used as an index of fungal contamination employing TLC-digital-based analytical methods.     

A new multi-resolution hybrid wavelet for analysis and image compression

Most of the current image- and video-related applications require higher resolution of images and higher data rates during transmission, better compression techniques are constantly being sought after. This paper proposes a new and unique hybrid wavelet technique which has been used for image analysis and compression. The proposed hybrid wavelet combines the properties of existing orthogonal transforms in the most desirable way and also provides for multi-resolution analysis. These wavelets have unique properties that they can be generated for various sizes and types by using different component transforms and varying the number of components at each level of resolution. These hybrid wavelets have been applied to various standard images like Lena (512 × 512), Cameraman (256 × 256) and the values of peak signal to noise ratio (PSNR) obtained are compared with those obtained using some standard existing compression techniques. Considerable improvement in the values of PSNR, as much as 5.95 dB higher than the standard methods, has been observed, which shows that hybrid wavelet gives better compression. Images of various sizes like Scenery (200 × 200), Fruit (375 × 375) and Barbara (112 × 224) have also been compressed using these wavelets to demonstrate their use for different sizes and shapes.     

Geometric invariant features for the detection and analysis of vehicle

The intelligent traffic management system (ITS) is one of the active research areas. Vehicle detection is a major role in traffic analysis. In the paper, analysis of detecting vehicles is proposed based on the features posed by the vehicle. The foreground pixels from image are extracted by histogram based foreground segmentation. After segmenting, Hu-Moments and Eigen values features are extracted and normalized. The classifiers are trained with the extracted Hu-Moments and Eigen values. The experiments are conducted on different benchmark datasets, and results are analysed considering the overall classification accuracy. Results of the algorithm are satisfactory and acceptable in real time.