Regional nitrogen cycle: an Indian perspective

During the past century through food and energy production, human activities have altered the world's nitrogen cycle by accelerating the rate of reactive nitrogen creation. India has made impressive strides in the agricultural front, in which N fertilizer plays a major role. There has been a marked change in the supply and use of land, water, fertilizers, seeds and livestock, but the N use efficiency remained at a low level. Exploring the nature of these changes and quantification of the impacts on the N cycle has become essential. Hence we have presented data on various N pools and fluxes based on a conceptual N model. In India, efforts should focus on understanding the fate and consequences of the applied N and to increase the efficiency of N use

Behaviour of a Kinetic Energy Projectile on Angular Impact

Experiments of high velocity impact have been carried out with 30 mm armoured piercing projectiles on 55 mm thick hard steel plate. Angle of impact has been varied from 10" to 90". Damage inflicted on target with varying angle of impact has been reported and discussed in this paper. Comparative behaviour with 20 mm APP shot has also been discussed

Characterizing and predicting the functional and conformational diversity of seven-transmembrane proteins

The activation of seven-transmembrane receptors (7TMRs) allows cells to sense their environment and convert extracellular signals (like hormone binding) into intracellular signals (through G protein-coupled and/or β arrestin-coupled pathways). A single 7TMR is capable of transducing a wide spectrum of physiological responses inside a cell by coupling to these pathways. This intracellular pleiotropic action is enabled by multiple conformations exhibited by these receptors. Developments in membrane protein structure determination technologies have led to a rapid increase in crystal structures for many 7TMRs. Majority of these receptors have been crystallized in their inactive conformation and, for some, one of the many active conformations has also been crystallized. Given the topological constraints of a lipid bilayer that results in a single fold of seven almost parallel TM helices connected by mostly unstructured loops, these structures exhibit a diversity of conformations not only across the receptors but also across the different functional forms for receptors with structures for one of the functionally active conformations. Here we present a method to characterize this conformational diversity in terms of transmembrane helix topology (TMHTOP) parameters and how to use these helix orientation parameters to predict functionally-distinct multiple conformations for these receptors. The TMHTOP parameters enable a quantification of the structural changes that underlie 7TMR activation and also sheds a unique mechanistic light on the pleiotropic nature of these receptors. It provides a common language to describe the 7TMR activation mechanisms as well as differences across many receptors in terms of visually intuitive structural parameters. Protein structure prediction methods can use these parameters to describe 7TMR conformational ensembles, which coupled to experimental data can be used to develop testable hypotheses for the structural basis of 7TMR functions

Scene based Classification of Aerial Images using Convolution Neural Networks

1087-1094The advent of computer vision and evolution of high-end computing in remote sensing images have embellish various researchers for unprecedented development in remotely sensed aerial images. The requirement to extract essential information stimulated anatomization of aerial images for its usefulness. Deep learning provides state of the art solutions for widely explored visual recognition system and has emerged as an evolutionary area, being applicable to large scale image processing applications. Convolutional Neural Networks (CNNs), an essential component of deep learning algorithms consists of increasing the depth and connections in the processing layers to learn various features of data at different abstract levels. In this paper, we present an outlook for classifying and extracting the features of aerial images using CNN. We propose a CNN architecture based on various parameters and layers for classification. CNN has been evaluated on two publicly available aerial data sets: UC Merced Land Use and RSSCN7. Experimental results show that the proposed CNN architecture is competent and efficient in terms of accuracy as performance evaluation parameter in comparison with conventional classifiers like Bag of Visual Words (BOVW)

Nitrate content in wheat leaf blades

This article does not have an abstract

Building inclusive health innovation systems: lessons from India

This article presents an overview of the changes that are taking place within the public and private health innovation systems in India including delivery of medical care, pharmaceutical products, medical devices, and Indian traditional medicine. The nature of the flaws that exist in the health innovation system is pinpointed. The response by the government, the health, technology and medical institutions, and the evolving industry is addressed on a national level. The article also discusses how the alignment of policies and institutions was developed within the scope of national health innovation systems, and how the government and the industry are dealing with the challenges to integrate health system, industry, and social policy development processes

Elucidating glycosaminoglycan–protein–protein interactions using carbohydrate microarray and computational approaches

Glycosaminoglycan polysaccharides play critical roles in many cellular processes, ranging from viral invasion and angiogenesis to spinal cord injury. Their diverse biological activities are derived from an ability to regulate a remarkable number of proteins. However, few methods exist for the rapid identification of glycosaminoglycan–protein interactions and for studying the potential of glycosaminoglycans to assemble multimeric protein complexes. Here, we report a multidisciplinary approach that combines new carbohydrate microarray and computational modeling methodologies to elucidate glycosaminoglycan–protein interactions. The approach was validated through the study of known protein partners for heparan and chondroitin sulfate, including fibroblast growth factor 2 (FGF2) and its receptor FGFR1, the malarial protein VAR2CSA, and tumor necrosis factor-α (TNF-α). We also applied the approach to identify previously undescribed interactions between a specific sulfated epitope on chondroitin sulfate, CS-E, and the neurotrophins, a critical family of growth factors involved in the development, maintenance, and survival of the vertebrate nervous system. Our studies show for the first time that CS is capable of assembling multimeric signaling complexes and modulating neurotrophin signaling pathways. In addition, we identify a contiguous CS-E-binding site by computational modeling that suggests a potential mechanism to explain how CS may promote neurotrophin-tyrosine receptor kinase (Trk) complex formation and neurotrophin signaling. Together, our combined microarray and computational modeling methodologies provide a general, facile means to identify new glycosaminoglycan–protein–protein interactions, as well as a molecular-level understanding of those complexes

Comparative time series RNA-seq analysis of Pigeonpea Root Tissues in response to Fusarium udum infection

Pigeonpea [Cajanus cajan (L.) Millsp.] is an important food legume and is mostly cultivated in tropical and subtropical regions of South Asia, Kenya, Malawi, Bangladesh, and other parts of the world. India is the center of origin and major global producer (66%), consumer, and importer, ahead of production in Africa (14%)..