Sequence Analysis of Rifampicin Resistance Determining Region (RRDR) of Mycobacterium Tuberculosis

Mycobacterium tuberculosis has become the cause for one of the most dreadful disease which the mankind has ever known i.e. Tuberculosis. The organism holds the ability to infect multiple organs at a time resulting in multiple symptomatic presentations in pathogenic condition while in non-pathogenic condition, it can lay dormant and remain asymptomatic. The research work presented here aimed at sequencing of Rifampicin Resistance Determining Region (RRDR) of the rpoB gene present in phenotypically multidrug resistant M. tuberculosis. The findings showed that the major point of mutations to be present within this region was at codon 516, 526, and 531. Early diagnosis of multidrug resistance in any pathogen has become a pre – requisite for proper treatment and efficient elimination of pathogenic organisms from the host with minimal toxicity. Similarly, understanding the mutation dynamics of target genes also help in novel drug design and discovery

Impact of Ground Truth Annotation Quality on Performance of Semantic Image Segmentation of Traffic Conditions

Preparation of high-quality datasets for the urban scene understanding is a labor-intensive task, especially, for datasets designed for the autonomous driving applications. The application of the coarse ground truth (GT) annotations of these datasets without detriment to the accuracy of semantic image segmentation (by the mean intersection over union - mIoU) could simplify and speedup the dataset preparation and model fine tuning before its practical application. Here the results of the comparative analysis for semantic segmentation accuracy obtained by PSPNet deep learning architecture are presented for fine and coarse annotated images from Cityscapes dataset. Two scenarios were investigated: scenario 1 - the fine GT images for training and prediction, and scenario 2 - the fine GT images for training and the coarse GT images for prediction. The obtained results demonstrated that for the most important classes the mean accuracy values of semantic image segmentation for coarse GT annotations are higher than for the fine GT ones, and the standard deviation values are vice versa. It means that for some applications some unimportant classes can be excluded and the model can be tuned further for some classes and specific regions on the coarse GT dataset without loss of the accuracy even. Moreover, this opens the perspectives to use deep neural networks for the preparation of such coarse GT datasets.Comment: 10 pages, 6 figures, 2 tables, The Second International Conference on Computer Science, Engineering and Education Applications (ICCSEEA2019) 26-27 January 2019, Kiev, Ukrain

An improved block matching algorithm for motion estimation in video sequences and application in robotics

Block Matching is one of the most efficient techniques for motion estimation for video sequences. Metaheuristic algorithms have been used effectively for motion estimation. In this paper, we propose two hybrid algorithms: Artificial Bee Colony with Differential Evolution and Harmony Search with Differential Evolution based motion estimation algorithms. Extensive experiments are conducted using four standard video sequences. The video sequences utilized for experimentation have all essential features such as different formats, resolutions and number of frames which are generally required in input video sequences. We compare the performance of the proposed algorithms with other algorithms considering various parameters such as Structural Similarity, Peak Signal to Noise Ratio, Average Number of Search Points etc. The comparative results demonstrate that the proposed algorithms outperformed other algorithms

Comparison of transgenic plant production for bacterial blight resistance in Pakistani local rice (Oryza sativa L.) cultivars

The study was carried out to improve bacterial leaf blight resistance in three rice cultivars (Basmati - 370, DR - 82 and IR - 6) by Agrobacterium mediated transformation system. Three week-old scutellum derived calli were infected with Agrobacterium strain EHA101, containing binary vector pTCL5 which has Xa 21 gene. Different levels of acetosyringone were tested to enhance transformation efficiency. Acetosyringone at 300 ìM showed 56.6% GUS expression with 100 and 200 ìM acetosyringone showing 13.3 and 30.0% GUS expression, respectively. Maximum transformation efficiency was obtained using DR - 82 with calli exposed to 300 ìM acetosyringone for 2 min. Direct hygromycin selection with 48 h ofco-cultivation was superior to pre-selection in all three cultivars. Transient GUS expression was 51.4% while stable GUS expression in calli was 18.8%. PCR analysis confirmed the presence of the Xa 21 gene in transformed regenerated plants. Stable varietal transformation efficiency was DR - 82 > Basmati-370 > IR - 6. Resistance of transgenic plants against Xanthomonas oryzae pathovar oryzae was evaluated with various strains/isolates at the seedling stage. All PCR positive transgenic plants of DR - 82 and Basmati - 370 were resistant with lesion areas less than 5% of the inoculated leaf area. The tested transgenic plants were resistant to all the indigenous and exotic strains tested due to the broad spectrum protection provided by the Xa 21 gene

Fabrication of carbon thin films by pulsed laser deposition in different ambient environments

In this work, carbon thin films are grown in different background environments (Air, Helium and Argon) at different pressures (60, 160, 500 and 1000 mbar) by ablating the graphite target with Nd:YAG laser of wavelength of 1064 nm, pulse energy of 740 mJ and pulse rate of 6 ns. 10,000 laser shots are used to ablate graphite target under different ambient conditions. Grown thin films are analyzed by Atomic Force Microscopy (AFM) to measure thickness, roughness average, maximum profile peak height, average maximum height of profile and spacing ratio of the surface. The obtained results show that the roughness average, thickness of film, maximum profile peak height, average maximum height of profile and spacing ratio of thin films decreases with increase in ambient pressures and shows highest value at low pressure (160 mbar) in helium environment as compared with air and argon

Bronchodilator, spasmolytic and calcium antagonist activities of Nigella sativa seeds (Kalonji): a traditional herbal product with multiple medicinal uses

Objective: The seeds of Nigella sativa locally known as Kalonji has been used in traditional medicine for the treatment of a variety of diseases including diarrhoea and asthma. The crude extract of N. sativa seeds (Ns.Cr) was studied in vitro for its possible spasmolytic and bronchodilator activities to rationalize the folkloric uses.Methods: Isolated rabbit jejunum and guinea-pig tracheal preparations were set up in Tyrode\u27s and Kreb\u27s solutions respectively and aerated with 5% CO2 in oxygen. Isotonic and isometric responses were measured on Bioscience oscillograph and Grass polygraph respectively.Results: The Ns.Cr caused a dose-dependent (0.1-3.0 mg/ml) relaxation of spontaneous contractions in rabbit jejunum. Ns.Cr also inhibited K(+)-induced contractions in a similar dose range, suggestive of calcium channel blockade (CCB). This effect was confirmed when pretreatment of the tissue with Ns.Cr, produced a dose-dependent shift in the Ca++ dose-response curves to the right similar to that of verapamil, a standard calcium channel blocker. In guinea-pig trachea, it caused relaxation of carbachol-, histamine- or K(+)-induced contractions indicating CCB. Activity-directed fractionation revealed that the CCB activity is concentrated in the petroleum ether fraction, which was found to be approximately 10 times more potent than the crude extract both in jejunum and tracheal preparations.Conclusion: These data indicate that the crude extract of Nigella sativa seeds exhibits spasmolytic and bronchodilator activities mediated possibly through calcium channel blockade and this activity is concentrated in the organic fraction. Its usefulness for diarrhoea and asthma in traditional medicine, appears thus to be based on a sound mechanistic background

Effect of different modes of pollination on quantitative and qualitative parameters of Egyptian Clover, Trifolium alexandrinum L.

The effect of different modes of pollination on quantitative and qualitative parameters of Egyptian clover, Trifolium alexandrinum L. was studied at Forage Section, Department of Genetics and Plant Breeding, CCS, Haryana Agricultural University, Hisar during 2012 and 2013. Maximum seed setting (81.5%) was recorded in A. mellifera pollination with an 8 frame colony (BP-8F) followed by 4 frame colony (BP-4F) (75.1%), open pollination (OP) (73.8%) and 2 frame colony (BP-2F) (71.5%). Maximum seed yield (2662.3 seeds) was observed in treatment BP-8F followed by BP-4F (2373.8), OP (2316.3) and BP-2F (2235.5). Still lower yield of 2103.0 seeds was found in hand pollination (HP) treatment that was significantly higher than the without insect pollination (WIP) treatment (1114.2). Minimum 1000-seed weight was observed in WIP (2.64 g). The seed weight of BP-4F (3.30), HP (3.20), BP-2F (3.17) and OP (3.03), the heaviest seeds were recorded in BP-8F (3.62 g/1000 grains) and it was at par with the treatment BP-4F (3.30 g). Highest seed germination per cent was recorded in BP-8F (94.7) followed by OP (90.7%). Lowest germination was found in WIP (84.7%). Though some work has been done on this aspect in India but comprehensive pollination studies has not been worked out

3D Face Reconstruction from Single 2D Image Using Distinctive Features

3D face reconstruction is considered to be a useful computer vision tool, though it is difficult to build. This paper proposes a 3D face reconstruction method, which is easy to implement and computationally efficient. It takes a single 2D image as input, and gives 3D reconstructed images as output. Our method primarily consists of three main steps: feature extraction, depth calculation, and creation of a 3D image from the processed image using a Basel face model (BFM). First, the features of a single 2D image are extracted using a two-step process. Before distinctive-features extraction, a face must be detected to confirm whether one is present in the input image or not. For this purpose, facial features like eyes, nose, and mouth are extracted. Then, distinctive features are mined by using scale-invariant feature transform (SIFT), which will be used for 3D face reconstruction at a later stage. Second step comprises of depth calculation, to assign the image a third dimension. Multivariate Gaussian distribution helps to find the third dimension, which is further tuned using shading cues that are obtained by the shape from shading (SFS) technique. Thirdly, the data obtained from the above two steps will be used to create a 3D image using BFM. The proposed method does not rely on multiple images, lightening the computation burden. Experiments were carried out on different 2D images to validate the proposed method and compared its performance to those of the latest approaches. Experiment results demonstrate that the proposed method is time efficient and robust in nature, and it outperformed all of the tested methods in terms of detail recovery and accuracy