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Water pollution has recently become a serious global problem and hence researchers were focusing to develop innovative methods for the purification of water and then getting access to purified water by reducing pollution. As a result, the current study concentrated on synthesizing cobalt-doped zinc oxide nanoparticles by accumulating cobalt ions on Pistia (Pistiastratiotes L.) plant tissue and combining them with zinc acetate precursor. Further, the synthesized particles were analyzed for their efficiency in photo-desulphurization of organo sulphur compounds such as Dibenzothiophene and 2,5-dimethyl thiophene. Various characterization studies proved that the nanoparticles were oval in shape and had particle sizes of 8-34 nm and the particles were distributed with less aggregation. The particles have 47 % of zinc element and 21% cobalt with hexagonal (wurtzite) crystalline structure. The synthesized Co-doped ZnO nanoparticles were utilized for the desulfurization of Sulphur containing pollutants such as dibenzothiophene and 2,5-dimethyl thiophene. The results proved that rapid desulfurization was observed during the initial time of the study. The % desulfurization of 14.36±0.136 and 19.63±0.201% was observed within 5 min of the study for dibenzothiophene and 2,5-dimethyl thiophene. Whereas the high % desulfurization was noticed within less time of 25 min wherein the % desulfurization was observed to be 95.61±0.279 and 93.66±0.137 for dibenzothiophene and 2,5-dimethyl thiophene respectively. The removal of harmful heavy metals utilizing the Pistia plant and recycling in the wastewater treatment process may therefore be inferred as being highly valued. Additionally, the Co-doped ZnO photocatalysts might improve photocatalytic activity owing to the catalysts' porosity and the hole recombination and electron suppression. [ABSTRACT FROM AUTHOR]

Perpendicular Magnetic Anisotropy-based Magnetic Tunnel Junction (PMA-MTJ) and Spin Transfer Torque Magnetic Random-Access Memory (STT-MRAM) have attracted wide attention among the next-generation Non-Volatile Memory (NVM) technologies due to low leakage and high-density characteristics for embedded memory architectures. However, STT-MRAM-based memory cells are not energy efficient with CMOS scaling at scaled supply voltages. This paper presents a novel energy-efficient Hybrid TFET (1 T: Hetero-junction TFET, 1 T: Homo-junction TFET)/STT-MRAM cell that explores p-i-n forward current of Tunnel FET. The proposed hybrid memory cell demonstrates ~27.3% energy efficiency over equivalent 1 T FinFET/STT-MRAM cell, 16.75% energy efficiency over equivalent 1 T Homo-junction TFET/STT-MRAM cell and 24.3% energy efficiency over equivalent 1 T Hetero-junction TFET/STT-MRAM cell at VDD = 0.5 V. [ABSTRACT FROM AUTHOR]

A novel simple, rapid, sensitive and stability-indicating RP-HPLC method was developed and validated for the determination of azelnidipine (ALDP) and its impurities 1 and 2. Resolution of drug, its potential impurities and degradation products were achieved by RP-HPLC on was performed on Prontosil ODS C18 column (250 mm x 4.6 mm, 5µ) using a mobile phase consisting of methanol and 0.1M sodium acetate 40: 60 (v/v) at a flow rate of 1 ml/min and 231 nm of UV detector. Validation of the method was performed along with formulation analysis and forced degradation studies. The calibration curves of ALDP were linear over a concentration range of 50-300 µg/mL. The method was rapid with a retention time of the impurity 2, impurity and ALDP observed at 3.60, 5.15 and 6.90 min, respectively. The method was applied for the impurities determination in drug tablets and for degradation products determination in a stability study of ALDP. The impurity content in the tablets was quantified as 0.1% of total drug. The method can also be used for rapid and accurate quantification of ALDP in its tablets during stability testing. [ABSTRACT FROM AUTHOR]

The necessity of recognizing a person from a low-resolution non-frontal image is a challenging problem in video surveillance. In order to alleviate the problem of recognition in the low-resolution image, the literature presents different techniques for face recognition after converting the low-resolution image to high resolution. Accordingly, this paper presents a technique for multi-view face video super resolution using the tangential and exponential kernel weighted regression model. In this paper, a new hybrid kernel is proposed to perform non-parametric kernel regression model for estimation of a neighbor pixel in the super resolution after the face detection is performed using Viola-Jones algorithm. The experimentation is performed with the UCSD face video databases, and the quantitative results are analyzed using the SDME with the existing techniques. From the resulting outcome, we prove that the maximum SDME of 77.3db is obtained for the proposed technique as compared to the existing techniques like nearest interpolation, bicubic interpolation, and bilinear interpolation. [ABSTRACT FROM AUTHOR]

In this work, we propose NRDPF-VQA (No Reference Distortion Patch Features Video Quality Assessment) model aims to use to measure the video quality assessment for H.264/AVC (Advanced Video Coding). The proposed method takes advantage of the contrast changes in the video quality by luminance changes. The proposed quality metric was tested by using LIVE video database. The experimental results show that the new index performance compared with the other NR-VQA models that require training on LIVE video databases, CSIQ video database, and VQEG HDTV video database. The values are compared with human score index analysis of DMOS. [ABSTRACT FROM AUTHOR]

In this work, a No-Reference objective image quality assessment based on NRDPF-IQA metric and classification based metric are tested using LIVE database, which consisting of Gaussian white noise, Gaussian blur, Rayleigh fast fading channel, JPEG compressed images, JPEG2000 images. We plot the Spearman's Rank Order Correlation Coefficient [SROCC] between each of these features and human DMOS from the LIVE-IQA database using our proposed method to ascertain how well the features correlate with human judgement quality. The analysis of the testing and training is done by SVM model. The proposed method shows better results compared with the earlier methods. Finally, the results are generated by using MATLAB. [ABSTRACT FROM AUTHOR]

A simple, rapid and precise Reversed phase high performance liquid chromatography method was developed for the analysis of Eletriptan. Chromatographic separation of Eletriptan is performed by using a Phenomenex Chromosil C18 (250 x 4.6mm, 5 µm) column as stationary phase. A mobile phase comprising of Acetonitrile, Triethylamine (TEA) and Tetrahydrofuran (THF) in the ratio of 50:25:25(v/v/v) (pH is adjusted to 6.3 with 1% ortho phosphoric acid) at a flow rate of 1.0ml/min and UV detection at 228 nm. The method is validated as per ICH and FDA guidelines. Linearity was observed in the range of 30-100 µg/ml. Recovery values are found to be 99.04 to 101.99%. The % RSD values for method precision and system precision are found to be less than 2%. The limit of detection and limit of quantification of method was found to be 0.8µg/ml and 2.5µg/ml respectively. The method was able to determine the stability of drug from pharmaceutical dosage form exposed to various stress conditions such as acidic, basic, photolytic oxidative, hydrolytic, and thermal degradation. Well-separated degrading peaks of Eletriptan are observed from the chromatograms of the samples subjected to stability studies. [ABSTRACT FROM AUTHOR]

Image registration and segmentation are the two important processes that are frequently used in medical image processing and computer vision applications. In traditional medical image applications both the techniques are applied independently even though the solution to one impacts the solution of the other. Currently medical image segmentation is very complex task due to the lack of sufficient contrast, SNR, and volume averages caused due to the non-uniform magnetic field. The problem is still high with MRI scans rather than other scans due to lack of real boundary. Availability of sophisticated diagnostic methods in the medical domain, demands the fusion of information from different sources for the better analysis. Similarity is enhanced by performing the non-rigid registration, where the local registration highly depends on segmentation of objects. This paper deals with the Atlas-based segmentation technique requires that the given atlas image is to be registered with the target image to find the desired shape segmentation in the target image. This paper discus the joint registration and segmentation process is achieved through highly accurate variational cost effective Distance Regularized Level Set Evolution (DRLSE) method for medical scan images. The key features of this algorithm are, it can accurately converge towards sharp object boundary corners due to forward and backward diffusion and also applied for small and large deformations. It uses less computational cost due to large time steps. [ABSTRACT FROM AUTHOR]

A 35-year-old, human immunodeficiency virus sero-positive male presented with huge mediastinal mass for evaluation. After contrast enhanced computed tomography (CECT) angiogram, aneurysm of arch of aorta was diagnosed. The patient also proved to be co-infected with syphilis, which is the aetiological cause of aneurysm in this case. The present report highlights the need to suspect, diagnose and treat dual infections in individuals with high risk behaviour.