Determination of the chromospheric quiet network element area index and its variation during 2008-2011

Generally it has been considered that the plages and sunspots are the main contributors to the solar irradiance. There are small scale structures on the sun with intermediate magnetic fields that could also contribute to the solar irradiance. It has not yet been quantified how much of these small scale structures contribute to the solar irradiance and how much it varies over the solar cycle. In this paper, we used Ca II K images obtained from the telescope installed at Kodaikanal observatory. We report a method to separate the network elements from the background structure and plage regions. We compute the changes in the network element area index during the minimum phase of solar cycle and part of the ascending phase of cycle 24. The measured area occupied by the network elements is about 30% and plages less than 1% of the solar disk during the observation period from February 2008-2011. During the extended period of minimum activity it is observed that the network element area index decreases by about 7% compared to the area occupied by the network elements in 2008. A long term study of network element area index is required to understand the variations over the solar cycle.Comment: 12 pages, 9 Figures, Accepted for publication in RA

Lithological Discrimination of Anorthosite using ASTER data in Oddanchatram Area, Dindigul district, Tamil Nadu, India

The present study applies with hyperspectral remote sensing techniques to map the lithology of the Oddanchatram anorthosite. The hyperspectral data were subjected to Principal Component Analysis (PCA), Independent Component Analysis (ICA) and Minimum Noise Fraction (MNF), Pixel Purity Index (PPI) and n-Dimensional Visualization for better lithology mapping. The proposed study area has various typical rock types. The PCA, ICA and MNF have been proposed best band combination for effectiveness of lithological mapping such as PCA (R: G: B=2:1:3), MNF (R: G: B=4:3:2) and ICA (R: G: B=3:1:2). The derived lithological map has compared with published geological map from Geological Survey of India and validated with field investigation. Therefore, ASTER data based lithological mapping are fast, cost-effective and more accurate

Biogenic silver nanoparticles mediated by Broussonetia papyrifera: anticancer and antimicrobial activity against pathogenic organisms

Objective: To evaluate the potential aspects of biologically synthesized silver nanoparticles mediated by Broussonetia papyrifera against the human pathogens. The same is acknowledged to have high efficiency in the field of Pharmaceutical industry.Methods: The 1Mm of AgNO3 is prepared and mixed with appropriate volume of plant extract and reaction volume was made up to 100 ml. the physical   characterization of AgNPs was done. The anti-microbial activity was done against dread pathogens. Cytotoxic activity of the AgNPs was investigated against breast and lung cancer cell lines.Results: The FESEM and EDAX of the microscopic level showed the particle surface measurements around 44 nm to 50 nm. The XRD investigations are being an evidence for the crystalline structure of the AgNPs with 30 nm. The bacterial pathogen Rhodococcus rhodochrous showed the maximum zone of inhibition (11.8±0.447). The A549 human lung cancer cell line and MCF-7 human breast cancer cell line were tested against the toxicity of AgNPs. The toxicity of AgNPs was valued and corresponding IC50 for Lung cancer (A549) is 12.95± 0.05 µg/mL and Breast cancer (MCF-7) is 10.75± 0.05 µg/mL respectively.Conclusion: The present research denotes that biomolecules derived AgNPs have larger impact as antimicrobials in the biomedical field. Since the aggressive chemicals are not involved AgNPs production, these bio-substances can of alternative medicine to resistant once. The in-vitro experiments exhibits the therapeutic effect of this AgNPs based on the ambient concentration on the process.Â

Virtual screening, identification and experimental testing of novel inhibitors of PBEF1/Visfatin/NMPRTase for glioma therapy

Background: Pre-B-cell colony enhancing factor 1 gene (PBEF1) encodes nicotinamide phosphoribosyltransferase (NMPRTase), which catalyses the rate limiting step in the salvage pathway of NAD+ metabolism in mammalian cells. PBEF1 transcript and protein levels have been shown to be elevated in glioblastoma and a chemical inhibitor of NMPRTase has been shown to specifically inhibit cancer cells. Methods: Virtual screening using docking was used to screen a library of more than 13,000 chemical compounds. A shortlisted set of compounds were tested for their inhibition activity in vitro by an NMPRTase enzyme assay. Further, the ability of the compounds to inhibit glioma cell proliferation was carried out. Results: Virtual screening resulted in short listing of 34 possible ligands, of which six were tested experimentally, using the NMPRTase enzyme inhibition assay and further with the glioma cell viability assays. Of these, two compounds were found to be significantly efficacious in inhibiting the conversion of nicotinamide to NAD+, and out of which, one compound, 3-amino-2-benzyl-7-nitro-4-(2-quinolyl-)-1,2-dihydroisoquinolin-1-one, was found to inhibit the growth of a PBEF1 over expressing glioma derived cell line U87 as well. Conclusions: Thus, a novel inhibitor has been identified through a structure based drug discovery approach and is further supported by experimental evidence

Risk factors for relapse in childhood steroid sensitive nephrotic syndrome

Background: Nephrotic syndrome (NS) generally tends to follow a benign and chronic relapsing course. Relapses are a major problem in children with steroid sensitive NS (SSNS). Objective: To identify the risk factors for frequent relapse (FR) in the first episode childhood SSNS. Methods: This prospective study was conducted in the Government Dharmapuri Medical College Hospital, Tamil Nadu, between July 2013 and January 2016. Children aged 9 months - 12 years with a diagnosis of SSNS (first episode) who came for follow-up for at least 12 months in the pediatric nephrology clinic were included. The enrolled cases were divided into 2 groups: (1) frequent relapser (FR) and (2) infrequent relapser (IFR). 9 factors were studied as possible risk factorsfor relapse. The data collected were analyzed using Chi-square test and Student’s t-test. Results: Of 160 SSNS children, there were 92 (57.5%) cases of IFR and 68 (42.5%) cases of FR. There were 97 males (60.6%) and 63 females (39.4%) with a male to female ratio of 1.5:1. The mean age of presentation was 4.37±2.32 years. The mean time taken to achieve remission during the first episode was 1.94±1.04 weeks. The interval between remission and first relapse was 5.56±4.51 months. Incidence of infection and hypertension was 31.9% and 37.5%, respectively. Risk factors significantly associated with FR were: Time taken to achieveremission during the first episode (>14 days) (p<0.0001), mean duration of interval between remission and first relapse (within 6 months) (p<0.0001), associated infections (p<0.0001) and hypertension (p<0.0001). Age at onset, sex, serum albumin, 24 h urine protein, and azotemia did not influence the FR in our study. Conclusion: More than 14 days to achieve remission during the first episode, relapse within first 6 months, associated infections and hypertension were the factors associated with FRs

Human milk banking: One year experience from a tertiary care centre

Introduction: A human milk bank (HMB) systematically collects, screens, processes, and dispenses excess milk donated by healthy nursing mothers. First HMB of Asia was established in the year 1989 in Mumbai, but there are still insufficient milk banks in India. Objective: This study aimed to provide our experience in the past 1 year. Methods: This retrospective descriptive study was conducted in the HMB of a tertiary care institution. The data were collected from donor forms and other milk bank records in the milk bank. All the demographic details and bacteriological data were collected. Results: There were 1168 donors with no extramural donors. Of these, 882 donors had term babies and 286 had preterm babies. The mean age of the donor population was 23.53±3.27 years. On the analysis of the volume of milk donated, the mean volume was 77.62±51.26 ml. A total of 90,660 ml of human milk was collected during the study period of 1 year. The bacteriological culture of the donor milk showed growth in 42 (3.6%) samples and was discarded. Klebsiella (2.39%) was the most common organism followed by Escherichia coli (0.44%) and Staphylococcus (0.35%). There were 1424 recipients and about 74% of them, were preterm babies. There were no extramural recipients. Conclusion: For a large number of preterm babies and the neonates without breast milk in India, pasteurized donor human milk will be the best source of nutrition. Hence, number of HMBs will improve the neonatal survival and reduce the morbidity

Comparative Analysis of advanced Face Recognition Techniques

ABSTRACT: This project entitled "Comparative analysis of advanced Face Recognition Techniques", it is based on fuzzy c means clustering and associated sub neural network. It deals with the face is a complex multidimensional visual model and developing a computational model for face recognition is difficult. In this paper, it represents a method for face recognition base on similar neural networks. Neural networks (NNs) have been widely used in various fields. However, the computing effectiveness decreases rapidly if the scale of the NN increases. In this paper, a new method of face recognition based on fuzzy clustering and parallel NNs is proposed. The face patterns are divided into several small-scale neural networks based on fuzzy clustering and they are combine to obtain the recognition result. The facial feature vector was compared by PCA and LDA methods. In particular, the proposed method achieved 98.75% recognition accuracy for 240 patterns of 20 registrants and a 99.58% rejection rate for 240 patterns of 20 nonregistrants. Experimental results show that the performance of our new face-recognition method is better than those of the LDA based face recognition system

Tibia Fracture Healing Prediction Using First-Order Mathematical Model

The prediction of healing period of a tibia fracture in humans across limb using first-order mathematical model is demonstrated. At present, fracture healing is diagnosed using X-rays. Recent studies have demonstrated electric stimulation as a diagnostic tool in fracture healing. A DC electric voltage of 0.7 V was applied across the fracture and stabilized with Teflon coated carbon rings and the data was recorded at different time intervals until the fracture heals. The experimental data fitted a first-order plus dead time zero model (FOPDTZ) that coincided with the mathematical model of electrical simulated tibia fracture limb. Fracture healing diagnosis was proposed using model parameter process gain. Current stabilization in terms of process gain parameter becoming constant indicates that the healing of fracture is a new finding in the work. An error analysis was performed and it was observed that the measured data correlated to the FOPDTZ model with an error of less than 2 percent. Prediction of fracture healing period was done by one of the identified model parameters, namely, process gain. Moreover, mathematically, it is justified that once the fracture is completely united there is no capacitance present across the fracture site, which is a novelty of the work.</jats:p

Review of Topology Optimisation Refinement Processes for Sheet Metal Manufacturing in the Automotive Industry

Topology optimisation is a process that is becoming increasingly reliable and necessary in the pursuit of highly efficient components comprising of low mass with a high structural performance. These components are typically mass-produced on a large-scale in automotive sectors for instance, where components are usually metallic and pressed. The ability to maximise a component’s structural characteristics has yielded many variations of computational topological solvers over the years. Over time many different methodologies have been used to generate suitable manufacturable solutions. Despite this, a gap between the generation of topology optimisation solutions and the creation of ready-to-manufacture solutions still exists today. This review paper outlines existing methods for computational topology optimisation and addresses any refinement methods used to generate a manufacturable solution, particularly focussing on methodologies used in automotive sheet metal forming. These methods are scrutinised in regards to the level of manual user input needed to create a Computer Aided Design (CAD) model representation of the manufacturable solution. Suggestions are also made to highlight further work to improve these techniques for large-scale industry-standard product development

Efficient Low-Frequency SSVEP Detection with Wearable EEG Using Normalized Canonical Correlation Analysis

Recent studies show that the integrity of core perceptual and cognitive functions may be tested in a short time with Steady-State Visual Evoked Potentials (SSVEP) with low stimulation frequencies, between 1 and 10 Hz. Wearable EEG systems provide unique opportunities to test these brain functions on diverse populations in out-of-the-lab conditions. However, they also pose significant challenges as the number of EEG channels is typically limited, and the recording conditions might induce high noise levels, particularly for low frequencies. Here we tested the performance of Normalized Canonical Correlation Analysis (NCCA), a frequency-normalized version of CCA, to quantify SSVEP from wearable EEG data with stimulation frequencies ranging from 1 to 10 Hz. We validated NCCA on data collected with an 8-channel wearable wireless EEG system based on BioWolf, a compact, ultra-light, ultra-low-power recording platform. The results show that NCCA correctly and rapidly detects SSVEP at the stimulation frequency within a few cycles of stimulation, even at the lowest frequency (4 s recordings are sufficient for a stimulation frequency of 1 Hz), outperforming a state-of-the-art normalized power spectral measure. Importantly, no preliminary artifact correction or channel selection was required. Potential applications of these results to research and clinical studies are discussed