Analysis of CT Brain Images using Radial Basis Function Neural Network

Medical image processing and analysis is the tool to assist radiologists in the diagnosis process to obtain a moreaccurate and faster diagnosis. In this work, we have developed a neural network to classify the computer tomography(CT) brain tumor image for automatic diagnosis. This system is divided into four steps namely enhancement, segmentation, feature extraction and classification. In the first phase, an edge-based selective median filter is usedto improve the visibility of the loss of the gray-white matter interface in CT brain tumor images. Second phaseuses a modified version of shift genetic algorithm for the segmentation. Next phase extracts the textural featuresusing statistical texture analysis method. These features are fed into classifiers like BPN, Fuzzy k-NN, and radialbasis function network. The performances of these classifiers are analyzed in the final phase with receiver operating characteristic and precision-recall curve. The result shows that the CAD system is only to develop the tool for braintumor and proposed method is very accurate and computationally more efficient and less time consuming.Defence Science Journal, 2012, 62(4), pp.212-218, DOI:http://dx.doi.org/10.14429/dsj.62.183

Characterization and Evaluation of a Rare Orchid Renanthera imschootiana Rolfe from Manipur & Nagaland

The orchid Renanthera imschootiana Rolfe is the only species under the genus available in India at Manipur and Nagaland, which is a part of Indo-Burma mega diversity hot-spot. The only collection, NRCO-Coll-77 (1998)/IC 566525 of this species available with us was evaluated and characterized as per 'Common Descriptors of Orchids' developed at this center. Monopodial nature in habit, un-branched raceme with a length of 32.2 cm having attractive dominant red-purple (RHS-60A) flowers and petals coloured grayed orange (RHS-164C) with shade is typical of this species. Broad, lateral sepals with attractive dominant crimson/red purple colour flower having medium-range vase life of 23.7 days, imparts high breeding value to this species for developing new hybrid derivatives

Interspecific Hybrid Developed in Epidendrum Orchid from the Cross E. radicans Pav. Ex. Lindl. X E. xanthinum Lindl.

An interspecific Epidendrum hybrid was developed using E. radicans (known as 'fire star orchid', 'ground-rooted orchid') as female parent and E. xanthinum known as 'yellow orchid' as male parent. The selected line (NRCO Epidendrum cross/2005-01) was characterized for morphological and floral traits. Flower size (3.5 cm x 3.4 cm) of selected line was bigger than both parents, with bright saffron-orange colour (RHS 44A). Dorsal sepal size (1.8 cm x 0.6 cm), lateral sepal size (1.9 cm x 0.7 cm), petal size (1.8 cm x 0.6 cm), lip size (2.3 cm x 2 cm) and column size (1.1 cm x 0.2 cm) were bigger than in parents. Shape and fimbriated side lobes of lip with deep cleft of anterior margins was similar to the male parent (E. xanthinum), except colour. The F1progeny of 'NRCO-Epidendrum cross/2005-01' flowered with different red-orange to yellow shades is categorized broadly into three types: Red-orange, Orangeyellow and Yellow. Epidendrums are popularly known as 'Crucifix orchid' and 'Poor man's orchid', have a long flowering period with 2-3 flowerings in a year, and are easy to multiply. These attributes are ideal for popularizing this plant in India as a potted plant as well garden plant

Effect of stripe rust on the yield response of wheat to nitrogen

Nitrogen (N) is the most important fertiliser element determining the productivity of wheat. N nutrition is known to affect the level of stripe rust infection, with higher N associated with increased disease severity. Stripe rust, caused by Puccinia striiformis f. sp. tritici, is a major yield-limiting disease of wheat in Australia. This paper describes experiments designed to investigate the agronomic response to the interaction of various levels of N application and stripe rust severity in wheat varieties differing in response. Experimental plots were established in crop seasons 2006 and 2007 on the Liverpool Plains of northern NSW, Australia. Yield, biomass, grain protein content (GPC) and harvest index (HI) data were recorded. Increased rates of N increased the severity of stripe rust during grain filling. N application also increased yield and GPC in all varieties in both years. Stripe rust reduced the yield of the rust-susceptible wheat varieties, and GPC and proportion of added N recovered in the grain were also reduced in one year but not the other. It was evident from our experiment that stripe rust caused yield loss accompanied by either no change or reduction in GPC, indicating that the total amount of N entering the grain was reduced by stripe rust. The effects of stripe rust on N yield are most likely associated with reduced uptake of N during grain filling

Prevalence of hypertension and its association with obesity in children of selected schools of Bengaluru city

Background: Childhood hypertension and its association with obesity are becoming important issues worldwide. The prevalence of hypertension and obesity are increasing in both developed and developing countries. Objectives: To determine the prevalence of hypertension among school-aged children in Bengaluru and to determine whether or not obesity is associated with hypertension. Materials and Methods: Six schools were selected at random from an area in Bengaluru. A total of 3,000 students studying from 1 to 10 grades were included in the study. The students were visited at school, and their weights, heights, and blood pressures (BP)were measured. The World Health Organization’s references were used to determine the prevalence of overweight, obesity, and hypertension. Results: The prevalence of hypertension and obesity were 3.5% (n=106) and 8.2% (n=247), respectively. Sex and obesity were found to be positively associated with hypertension. Conclusion: The prevalence of obesity and hypertension are high among school children of 6-15 years of age in Bengaluru. Obesity is positively associated with hypertension. BP measurements should be part of routine school health examination, especially in obese children

Diverse sensitivity of winter crops over the growing season to climate and land surface temperature across the rainfed cropland-belt of eastern Australia

© 2017 Elsevier B.V. The rainfed cropland belt in Australia is of great importance to the world grain market but has the highest climate variability of all such regions globally. However, the spatial-temporal impacts of climate variability on crops during different crop growth stages across broadacre farming systems are largely unknown. This study aims to quantify the contributions of climate and Land Surface Temperature (LST) variations to the variability of the Enhanced Vegetation Index (EVI) by using remote sensing methods. The datasets were analyzed at an 8-day time-scale across the rainfed cropland of eastern Australia. First, we found that EVI values were more variable during the crop reproductive growth stages than at any other crop life stage within a calendar year, but nevertheless had the highest correlation with crop grain yield (t ha−1). Second, climate factors and LST during the crop reproductive growth stages showed the largest variability and followed a typical east-west gradient of rainfall and a north-south temperature gradient across the study area during the crop growing season. Last, we identified two critical 8-day periods, beginning on day of the year (DoY) 257 and 289, as the key ‘windows’ of crop growth variation that arose from the variability in climate and LST. Our results show that the sum of the variability of the climate components within these two 8-day ‘windows’ explained >88% of the variability in the EVI, with LST being the dominant factor. This study offers a fresh understanding of the spatial-temporal climate-crop relationships in rainfed cropland and can serve as an early warning system for agricultural adaptation in broadacre rainfed cropping practices in Australia and worldwide

Estimating net primary productivity of croplands in Indo-Gangetic Plains using GOME-2 sun-induced fluorescence and MODIS NDVI

© 2018 Current Science Association, Bengaluru. Recently evolved satellite-based sun-induced fluorescence (SIF) spectroscopy is considered as a direct measure of photosynthetic activity of vegetation. We have used monthly averages of satellite-based SIF retrievals for three agricultural year cycles, i.e. May to April for each of the three years, viz. 2007-08, 2008-09 and 2009-10 to assess comparative performance of SIF and normalized difference vegetation index (NDVI) for predicting net primary productivity (NPP) over the Indo-Gangetic Plains, India. Results show that SIF values for C4 crop-dominated districts were higher than C3 crop-dominated districts during summer and low during winter for all three years. SIF explained more or less above 70% of variance in NPP. The variance explained by integrated NDVI ranged from 60% to 67%. Thus the present study has shown the potential of SIF data for improved modelling of agricultural productivity at a regional scale

Chemoenzymatic Labeling of Proteins for Imaging in Bacterial Cells

Reliable methods to determine the subcellular localization of bacterial proteins are needed for the study of prokaryotic cell biology. We describe here a simple and general technique for imaging of bacterial proteins in situ by fluorescence microscopy. The method uses the eukaryotic enzyme N-myristoyltransferase to modify the N-terminus of the protein of interest with an azido fatty acid. Subsequent strain-promoted azide–alkyne cycloaddition allows conjugation of dyes and imaging of tagged proteins by confocal fluorescence microscopy. We demonstrate the method by labeling the chemotaxis proteins Tar and CheA and the cell division proteins FtsZ and FtsA in Escherichia coli. We observe distinct spatial patterns for each of these proteins in both fixed and live cells. The method should prove broadly useful for protein imaging in bacteria

The Façade Wall: a Focus on the Green Architecture of Laurie Baker’s Houses

I would like to thank architect Sajan for his support and putting me in touch with the three houseowners and for his suggestion to study on Baker’s use of pattern in his building vocabulary. Architect Sajan was trained under Laurie Baker and continues his work under the aegis of Costford. I would like to thank the three houseowners – Mrs Narayanan, Mr George and Mrs Subrahmaniam – for their support and giving me their valuable time. I would like to thank Mr Anil Kumar of Laurie Baker Centre for giving me permission to use images from the book Untold Stories published by Laurie Baker Centre.This paper is an attempt to illustrate ‘green’ strategies Laurie Baker uses, in particular with respect to passive design principles as applied to houses. Green architecture is holistic and socially sensitive as it, in addition to being environmentally conscious, addresses the well-being of its users. This paper will focus on the method of harvesting ‘green’ ideals with respect to the architecture of the façade wall in Laurie Baker’s houses. Three houses designed by Baker in the 1990s in Trivandrum, Kerala will be studied. The discussion will show that Baker’s façade design strategies represent innovative solutions for facade designs built on low technology with derivations from the local vernacular in a contemporary architectural language. In the larger context of architecture of sustainability and green architecture, Baker’s approach, it will be shown, is essentially humanist and presents a way forward to establishing identity through place and an understanding of culture. In a digital era, which challenges identity and encourages notions of connectivity in a global sense, Baker’s architecture, it will be proposed, promotes green principles in making significant the value of the local and in the credence it gives to the end user and the craftsman in a singularly unique architectural language

Land surface phenological response to decadal climate variability across Australia using satellite remote sensing

© 2014 Author(s). Land surface phenological cycles of vegetation greening and browning are influenced by variability in climatic forcing. Quantitative spatial information on phenological cycles and their variability is important for agricultural applications, wildfire fuel accumulation, land management, land surface modeling, and climate change studies. Most phenology studies have focused on temperature-driven Northern Hemisphere systems, where phenology shows annually recurring patterns. However, precipitation-driven non-annual phenology of arid and semi-arid systems (i.e., drylands) received much less attention, despite the fact that they cover more than 30% of the global land surface. Here, we focused on Australia, a continent with one of the most variable rainfall climates in the world and vast areas of dryland systems, where a detailed phenological investigation and a characterization of the relationship between phenology and climate variability are missing. To fill this knowledge gap, we developed an algorithm to characterize phenological cycles, and analyzed geographic and climate-driven variability in phenology from 2000 to 2013, which included extreme drought and wet years. We linked derived phenological metrics to rainfall and the Southern Oscillation Index (SOI). We conducted a continent-wide investigation and a more detailed investigation over the Murray-Darling Basin (MDB), the primary agricultural area and largest river catchment of Australia. Results showed high inter-and intra-annual variability in phenological cycles across Australia. The peak of phenological cycles occurred not only during the austral summer, but also at any time of the year, and their timing varied by more than a month in the interior of the continent. The magnitude of the phenological cycle peak and the integrated greenness were most significantly correlated with monthly SOI within the preceding 12 months. Correlation patterns occurred primarily over northeastern Australia and within the MDB, predominantly over natural land cover and particularly in floodplain and wetland areas. Integrated greenness of the phenological cycles (surrogate of vegetation productivity) showed positive anomalies of more than 2 standard deviations over most of eastern Australia in 2009-2010, which coincided with the transition from the El Niño-induced decadal droughts to flooding caused by La Niña