Genetic transformation of Vitreoscilla sp

Of all the methods customarily used to transform E. coli we found only electroporation to be effective for transformation of the Gram-negative bacterium Vitreoscilla, yielding 5.10(5) transformants/microgram of plasmid DNA. The conditions used were close to those described for E. coli E. coli plasmids are stably maintained in Vitreoscilla. This is the first report of exogenous DNA transfer in Vitreoscilla which opens the way for the application of recombinant-DNA techniques to study this unique group of organisms.     

A study on measuring surface deformation of the L’Aquila region using the StaMPS technique

This research compares two time-series interferometric synthetic aperture radar (InSAR) methods, namely persistent scatterer SAR interferometry (PS-InSAR) and small baseline subset (SBAS) to retrieve the deformation signal from pixels with different scattering characteristics. These approaches are used to estimate the surface deformation in the L’Aquila region in Central Italy where an earthquake of magnitude Mw 6.3 occurred on 6 April 2009. Fourteen Environmental Satellite (ENVISAT) C-band Advanced Synthetic Aperture Radar (ASAR) images, covering the pre-seismic, co-seismic, and post-seismic period, are used for the study. Both the approaches effectively extract measurement pixels and show a similar deformation pattern in which the north-west and south-east regions with respect to the earthquake epicentre show movement in opposite directions. The analysis has revealed that the PS-InSAR method extracted more number of measurement points (21,103 pixels) as compared to the SBAS method (4886 pixels). A comparison of velocity estimates shows that out of 833 common pixels in both the methods, about 62% (517 pixels) have the mean velocity difference below 3 mm year^?1 and nearly 66% pixels have difference below 5 mm year^?1. It is concluded that StaMPS-based PS-InSAR method performs better in terms of extracting more number of measurement pixels and in the estimation of mean line of sight (LOS) velocity as compared to SBAS method.     

Comparison of predicted vehicular pollution concentration with air quality standards for different time periods

Air pollution is caused by variety of sources such as industries, vehicles, cremation, bakeries, and open burning. These sources have variation in emission with different time scales. Industry and bakeries have variation in emission with day or week, rest of the sources like vehicles and domestic sector have variation with time in a day. In fact, vehicles have a large variation in emission with time period of the day. The average concentration of 24 h is much less than hourly concentration of peak time when there is heavy vehicular emissions. The hourly concentration of off-peak time or lean time is very low due to low emission for that period. The air quality standards of India are prescribed for 24-h average concentration with which the predicted average concentration from models is compared. However, the peak time concentration may be much higher than the standard. In the peak time, outdoor concentration is more and since a large proportion of the population is out the exposure is also very high and can cause severe health effect. In this paper, vehicular pollution modeling has been carried out using AERMOD with simulated meteorology by Weather Research and Forecasting model. NO_x and PM concentrations were 3.6 and 1.45 times higher in peak time than off-peak and evening peak, respectively. Lean time has higher concentration for both NO_x and PM than off-peak and evening peak. It shows the misleading concept of comparing average predicted concentration of 24 h with standards for vehicles.

     

Cedrus oil—A promising storage fungitoxicant

Seeds of two spices Coriandrum sativum and Foeniculum vulgare, were dressed separately with essential oil of Cedrus deodara as well as with five synthetic fungicides viz., phenylmercury acetate, 2-methoxyethyl mercury chloride, copper oxychloride, mancozeb and wettable sulphur. Treated seeds were stored in polythene bags for 12 months. On mycofloral analysis, the oil had checked the appearance of ten fungi, Absidia sp., Alternaria alternata, Aspergillus flavus, A. fumigatus, A. niger, A. ruber, A. versicolor, Cladosporium cladosporioides, Curvularia lunata, and Paecilomyces variotii on the seeds of C. sativum, and seven fungi, Absidia sp., A. flavus, A. fumigatus, A. niger, A. ruber, A. versicolor, and Rhizopus spp., on the seeds of F. vulgare. The oil proved to be more effective than the synthetic fungicides. Further, the oil did not show any adverse effect on seed germination and seedling growth of both spices.     

Chatter and dynamic cutting force prediction in high-speed ball end milling

Machine tool chatter is a serious problem which deteriorates surface quality of machined parts and increases tool wear, noise, and even causes tool failure. In the present paper, machine tool chatter has been studied and a stability lobe diagram (SLD) has been developed for a two degrees of freedom system to identify stable and unstable zones using zeroth order approximation method. A dynamic cutting force model has been modeled in tangential and radial directions using regenerative uncut chip thickness. Uncut chip thickness has been modeled using trochoidal path traced by the cutting edge of the tool. Dynamic cutting force coefficients have been determined based on the average force method. Several experiments have been performed at different feed rates and axial depths of cut to determine the dynamic cutting force coefficients and have been used for predicting SLD. Several other experiments have been performed to validate the feasibility and effectiveness of the developed SLD. It is found that the proposed method is quite efficient in predicting the SLD. The cutting forces in stable and unstable cutting zone are in well agreement with the experimental cutting forces.     

Performance evaluation of ProJet multi-material jetting 3D printer

The purpose of this paper is to quantitatively evaluate the performance of a multi-material jetting 3D printer, ProJet 5500X, especially the capability for micro manufacturing. Unlike other single material 3D printer, ProJet 5500X uses photopolymers as the build material and wax as the support material. The building performance was evaluated by building a modified version of the standard benchmark model with a high-resolution printing mode. The dimensional error, forming quality and surface roughness of the printed parts have been measured and analysed using a microscope, a 3D coordinate measuring machine and a surface profilometer. Using wax as the support material, fine features as small as 0.25?mm, lateral features and sharper edges could all be properly built, despite the rough side surfaces observed in the printed part. Identical features (3?mm pins) were precisely built with an accuracy of 15?µm. The research provides first-hand detailed performance knowledge in the ProJet system for understanding the working principle and comparison with other 3D printing systems.     

Interferon-inducer polyriboinosinic-polyribocytidylic acid: a potent anti-gastric ulcer agent and inhibitor of the gastric proton pump in rats

Obesity was defined by a body mass index more than 30 kg/m2. Many risks were related to this pathology, and sometimes, menstrual disorders or infertility. In order to obtain an adequate response to ovarian stimulation during IVF cycles, higher doses of menotropins are necessary in the group of obese patients. The mechanism of this phenomenon is still unclear. Leptin is one of the main hypothesis, and could act on obesity and reproductive system simultaneously. The likelihood to have an ongoing pregnancy after IVF treatment is less in the group of obese patients because of the increased risk of miscarriage and obstetrical complications. Weight loss prior IVF remains the main advice in order to decrease the risks of the procedure and to treat successfully these patients.     

Optimal estimation of interferometric phase for measuring surface deformation

In recent times, time-series interferometric synthetic aperture radar (InSAR) methods are developed to retrieve the deformation signal in non-urban areas from distributed scatterers (DS). Phase triangulation algorithm (PTA), an important step in these methods for filtering decorrelation noise from DS, aims at optimal estimation of the filtered wrapped interferometric phase values using InSAR data stack. The uniqueness of this research work lies in the incorporation of one such PTA only to provide an optimal set of wrapped interferometric phase values before phase unwrapping in the open source StaMPS processing environment. The proposed methodology, when adapted to measure surface deformation in Tehri reservoir rim region, Uttarakhand, India using Environmental Satellite (Envisat) C-band advanced synthetic aperture radar images, works efficiently and has enhanced the spatial coverage of measurement pixels compared to standalone PS-InSAR processing. It is also revealed from the one-dimension-line of sight velocity map that resulted velocity estimates are congruent with standalone PS-InSAR processing.     

Hyperspectral image classification based on morphological profiles and decision fusion

Extended morphological profile (EMP) is an important mathematical tool for extracting structural information from the hyperspectral images. However, the accuracy of the EMP-based classification is greatly influenced by the choice of structuring element (SE). In this article, two supervised classification frameworks multiclassifier system with morphological profiles (MCSMP) and MCSMP2 are proposed that exploit rich spectral and structural information of hyperspectral images using EMPs and multiclassifier system for better classification than conventional methods. The EMPs with SEs of multiple shapes are used instead of one particular shape to better detect the response from the structures in the image. The EMPs created from SEs of different shapes are independently classified followed by decision fusion to generate final classification map. The classification results are compared with the conventional pixelwise and other EMP-based methods. The experimental results from three different types of hyperspectral data sets demonstrate that the proposed methods have significantly improved the spectral approach and outperformed the other studied methods in terms of classification accuracy. The new methods are more robust to the noise and produce good classification accuracy with very limited training samples. Various decision fusion techniques are evaluated, which performed differently in tested scenarios. Two different classifiers, Support Vector Machine (SVM) and random forest, are used in the experiments. It is shown that the proposed methods perform better with random forest classifier.