Review of trend detection methods and their application to detect temperature changes in India

Present study performs the spatial and temporal trend analysis of annual, monthly and seasonal maximum and minimum temperatures (t(max), t(min)) in India. Recent trends in annual, monthly, winter, pre-monsoon, monsoon and post-monsoon extreme temperatures (t(max), t(min)) have been analyzed for three time slots viz. 1901-2003,1948-2003 and 1970-2003. For this purpose, time series of extreme temperatures of India as a whole and seven homogeneous regions, viz. Western Himalaya (WH), Northwest (NW), Northeast (NE), North Central (NC), East coast (EC), West coast (WC) and Interior Peninsula (IP) are considered. Rigorous trend detection analysis has been exercised using variety of non-parametric methods which consider the effect of serial correlation during analysis. During the last three decades minimum temperature trend is present in All India as well as in all temperature homogeneous regions of India either at annual or at any seasonal level (winter, pre-monsoon, monsoon, post-monsoon). Results agree with the earlier observation that the trend in minimum temperature is significant in the last three decades over India (Kothawale et al., 2010). Sequential MK test reveals that most of the trend both in maximum and minimum temperature began after 1970 either in annual or seasonal levels. (C) 2012 Elsevier B.V. All rights reserved.

Trends and Variability of AVHRR-Derived NPP in India

In this paper, we estimate the trends and variability in Advanced Very High Resolution Radiometer (AVHRR)-derived terrestrial net primary productivity (NPP) over India for the period 1982-2006. We find an increasing trend of 3.9% per decade (r = 0.78, R-2 = 0.61) during the analysis period. A multivariate linear regression of NPP with temperature, precipitation, atmospheric CO2 concentration, soil water and surface solar radiation (r = 0.80, R-2 = 0.65) indicates that the increasing trend is partly driven by increasing atmospheric CO2 concentration and the consequent CO2 fertilization of the ecosystems. However, human interventions may have also played a key role in the NPP increase: non-forest NPP growth is largely driven by increases in irrigated area and fertilizer use, while forest NPP is influenced by plantation and forest conservation programs. A similar multivariate regression of interannual NPP anomalies with temperature, precipitation, soil water, solar radiation and CO2 anomalies suggests that the interannual variability in NPP is primarily driven by precipitation and temperature variability. Mean seasonal NPP is largest during post-monsoon and lowest during the pre-monsoon period, thereby indicating the importance of soil moisture for vegetation productivity.

Farmers' vulnerability to climate variability in Dimapur district of Nagaland, India

Certain parts of the State of Nagaland situated in the northeastern region of India have been experiencing rainfall deficit over the past few years leading to severe drought-like conditions, which is likely to be aggravated under a climate change scenario. The state has already incurred considerable losses in the agricultural sector. Regional vulnerability assessments need to be carried out in order to help policy makers and planners formulate and implement effective drought management strategies. The present study uses an 'index-based approach' to quantify the climate variability-induced vulnerability of farmers in five villages of Dimapur district, Nagaland. Indicators, which are reflective of the exposure, sensitivity and adaptive capacity of the farmers to drought, were quantified on the basis of primary data generated through household surveys and participatory rural appraisal supplemented by secondary data in order to calculate a composite vulnerability index. The composite vulnerability index of village New Showba was found to be the least, while Zutovi, the highest. The overall results reveal that biophysical characteristics contribute the most to overall vulnerability. Some potential adaptation strategies were also identified based on observations and discussions with the villagers.

Regionalization of precipitation in India-a review

Regionalization of precipitation refers to delineation of rain gauges in an area into homogeneous groups (clusters or regions). Various regionalization procedures are employed by researchers in hydrometeorology for addressing a wide spectrum of problems. This paper provides an overview of underlying concepts as well as advantages and limitations of procedures that have been developed over the past six decades. Emphasis is given to studies that have been carried out in India. Following this, gaps where more research needs to be focussed are highlighted, and challenges for regionalization in a climate change scenario are discussed.

Seasonal variability of rainfall recorded in growth bands of the Giant African Land Snail Lissachatina fulica (Bowdich) from India

Seasonal rainfall patterns in Bangalore, India, have been reconstructed using stable isotopic ratios in the growth bands of Giant African Land Snail shells. The present study was conducted at Bangalore, India which receives rain during the summer months. The oxygen isotopic record in the rainwater samples collected during different months covering the period of the summer monsoon of the year 2008 is compared with the isotopic ratio in the gastropod growth bands deposited simultaneously. The chronology of the shell growth band is independently established assuming the growth rate observed in a chamber experiment maintaining similar relative humidity and temperature conditions. A consistent pattern observed in the isotopic ratio in the gastropod growth bands and rainwater is demonstrated and provides a novel approach for precipitation reconstruction at seasonal and weekly time scales. This approach of using isotopic ratios in the gastropod growth bands for rainfall can serve as a substitute for filling gaps in rainfall data and for cases where no rain records are available. In addition, they can be used to determine the frequencies and magnitudes of dry spells from the past records. (C) 2013 Elsevier B.V. All rights reserved.

Variation at Diabetes- and Obesity-Associated Loci May Mirror Neutral Patterns of Human Population Diversity and Diabetes Prevalence in India

South Asian populations harbor a high degree of genetic diversity, due in part to demographic history. Two studies on genome-wide variation in Indian populations have shown that most Indian populations show varying degrees of admixture between ancestral north Indian and ancestral south Indian components. As a result of this structure, genetic variation in India appears to follow a geographic cline. Similarly, Indian populations seem to show detectable differences in diabetes and obesity prevalence between different geographic regions of the country. We tested the hypothesis that genetic variation at diabetes-and obesity-associated loci may be potentially related to different genetic ancestries. We genotyped 2977 individuals from 61 populations across India for 18 SNPs in genes implicated in T2D and obesity. We examined patterns of variation in allele frequency across different geographical gradients and considered state of origin and language affiliation. Our results show that most of the 18 SNPs show no significant correlation with latitude, the geographic cline reported in previous studies, or by language family. Exceptions include KCNQ1 with latitude and THADA and JAK1 with language, which suggests that genetic variation at previously ascertained diabetes-associated loci may only partly mirror geographic patterns of genome-wide diversity in Indian populations.

THE LEGACY OF GN RAMACHANDRAN AND THE DEVELOPMENT OF STRUCTURAL BIOLOGY IN INDIA

G.N. Ramachandran is among the founding fathers of structural molecular biology. He made pioneering contributions in computational biology, modelling and what we now call bioinformatics. The triple helical coiled coil structure of collagen proposed by him forms the basis of much of collagen research at the molecular level. The Ramachandran map remains the simplest descriptor and tool for validation of protein structures. He has left his imprint on almost all aspects of biomolecular conformation. His contributions in the area of theoretical crystallography have been outstanding. His legacy has provided inspiration for the further development of structural biology in India. After a pause, computational biology and bioinformatics are in a resurgent phase. One of the two schools established by Ramachandran pioneered the development of macromolecular crystallography, which has now grown into an important component of modern biological research in India. Macromolecular NMR studies in the country are presently gathering momentum. Structural biology in India is now poised to again approach heights of the kind that Ramachandran conquered more than a generation ago.

Breeding in bamboo: a novel anuran reproductive strategy discovered in Rhacophorid frogs of the Western Ghats, India

Amphibians exhibit extraordinarily diverse sets of reproductive strategies among vertebrates. Understanding life history strategies in an evolutionary framework is lacking for many amphibian species in the tropics. Here, we report a novel reproductive mode where adult frogs enter hollow internodes of bamboo via a small opening, deposit direct developing eggs, and provide parental care. This behaviour is observed in two species of the frog genus Raorchestes. The first description of this unique life history and details of nest site characteristics and embryo development are provided along with ecological comparisons. Evolution of novel reproductive modes and parental care are discussed in context of natural selection. Dearth of natural history information on amphibians in the Western Ghats and much of the South-East Asian region is highlighted with suggestions for further studies.(c) 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 114, 1-11.

Embodied energy assessment of building materials in India using process and input-output analysis

Growing demand for urban built spaces has resulted in unprecedented exponential rise in production and consumption of building materials in construction. Production of materials requires significant energy and contributes to pollution and green house gas (GHG) emissions. Efforts aimed at reducing energy consumption and pollution involved with the production of materials fundamentally requires their quantification. Embodied energy (EE) of building materials comprises the total energy expenditure involved in the material production including all upstream processes such as raw material extraction and transportation. The current paper deals with EE of a few common building materials consumed in bulk in Indian construction industry. These values have been assessed based on actual industrial survey data. Current studies on EE of building materials lack agreement primarily with regard to method of assessment and energy supply assumptions (whether expressed in terms of end use energy or primary energy). The current paper examines the suitability of two basic methods; process analysis and input-output method and identifies process analysis as appropriate for EE assessment in the Indian context. A comparison of EE values of building materials in terms of the two energy supply assumptions has also been carried out to investigate the associated discrepancy. The results revealed significant difference in EE of materials whose production involves significant electrical energy expenditure relative to thermal energy use. (C) 2014 Elsevier B.V. All rights reserved.

What Drives Venture Capital Fundraising in India: An Empirical Analysis of Systematic and Non-Systematic Factors

In this paper, we develop a consolidated Supply-Demand framework of the Venture Capital (VC) ecosystem for India. Further, we empirically analyze the supply side of this ecosystem to ascertain the influence of systematic (macro) and non-systematic (micro) factors on VC fundraising. At the macro level, our results indicate that relatively strong fundamentals of the Indian economy in the past decade as compared with the severe recessionary tendencies in the developed economies have been critical in determining the aggregate volume of VC fundraising. Among the micro factors, past performance and reputation of the individual fund managers have been instrumental in determining their fund raising potential.

GHG footprint of major cities in India

Concentration of greenhouse gases (GHG) in the atmosphere has been increasing rapidly during the last century due to ever increasing anthropogenic activities resulting in significant increases in the temperature of the Earth causing global warming. Major sources of GHG are forests (due to human induced land cover changes leading to deforestation), power generation (burning of fossil fuels), transportation (burning fossil fuel), agriculture (livestock, farming, rice cultivation and burning of crop residues), water bodies (wetlands), industry and urban activities (building, construction, transport, solid and liquid waste). Aggregation of GHG (CO2 and non-CO2 gases), in terms of Carbon dioxide equivalent (CO(2)e), indicate the GHG footprint. GHG footprint is thus a measure of the impact of human activities on the environment in terms of the amount of greenhouse gases produced. This study focuses on accounting of the amount of three important greenhouses gases namely carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) and thereby developing GHG footprint of the major cities in India. National GHG inventories have been used for quantification of sector-wise greenhouse gas emissions. Country specific emission factors are used where all the emission factors are available. Default emission factors from IPCC guidelines are used when there are no country specific emission factors. Emission of each greenhouse gas is estimated by multiplying fuel consumption by the corresponding emission factor. The current study estimates GHG footprint or GHG emissions (in terms of CO2 equivalent) for Indian major cities and explores the linkages with the population and GDP. GHG footprint (Aggregation of Carbon dioxide equivalent emissions of GHG's) of Delhi, Greater Mumbai, Kolkata, Chennai, Greater Bangalore, Hyderabad and Ahmedabad are found to be 38,633.2 Gg, 22,783.08 Gg, 14,812.10 Gg, 22,090.55 Gg, 19,796.5 Gg, 13,734.59 Gg and 91,24.45 Gg CO2 eq., respectively. The major contributors sectors are transportation sector (contributing 32%, 17.4%, 13.3%, 19.5%, 43.5%, 56.86% and 25%), domestic sector (contributing 30.26%, 37.2%, 42.78%, 39%, 21.6%, 17.05% and 27.9%) and industrial sector (contributing 7.9%, 7.9%, 17.66%, 20.25%, 1231%, 11.38% and 22.41%) of the total emissions in Delhi, Greater Mumbai, Kolkata, Chennai, Greater Bangalore, Hyderabad and Ahmedabad, respectively. Chennai emits 4.79 t of CO2 equivalent emissions per capita, the highest among all the cities followed by Kolkata which emits 3.29 t of CO2 equivalent emissions per capita. Also Chennai emits the highest CO2 equivalent emissions per GDP (2.55 t CO2 eq./Lakh Rs.) followed by Greater Bangalore which emits 2.18 t CO2 eq./Lakh Rs. (C) 2015 Elsevier Ltd. All rights reserved.

History of Computing in India: 1955-2010

The history of computing in India is inextricably intertwined with two interacting forces: the political climate determined by the political party in power) and the government policies mainly driven by the technocrats and bureaucrats who acted within the boundaries drawn by the political party in power. There were four break points (which occurred in 1970, 1978, 1991 and 1998) that changed the direction of the development of computers and their applications. This article explains why these breaks occurred and how they affected the history of computing in India.

Regionalization of extreme rainfall in India

Regionalization of extreme rainfall is useful for various applications in hydro-meteorology. There is dearth of regionalization studies on extreme rainfall in India. In this perspective, a set of 25 regions that are homogeneous in 1-, 2-, 3-, 4- and 5-day extreme rainfall is delineated based on seasonality measure of extreme rainfall and location indicators (latitude, longitude and altitude) by using global fuzzy c-means (GFCM) cluster analysis. The regions are validated for homogeneity in L-moment framework. One of the applications of the regions is in arriving at quantile estimates of extreme rainfall at sparsely gauged/ungauged locations using options such as regional frequency analysis (RFA). The RFA involves use of rainfall-related information from gauged sites in a region as the basis to estimate quantiles of extreme rainfall for target locations that resemble the region in terms of rainfall characteristics. A procedure for RFA based on GFCM-delineated regions is presented and its effectiveness is evaluated by leave-one-out cross validation. Error in quantile estimates for ungauged sites is compared with that resulting from the use of region-of-influence (ROI) approach that forms site-specific regions exclusively for quantile estimation. Results indicate that error in quantile estimates based on GFCM regions and ROI are fairly close, and neither of them is consistent in yielding the least error over all the sites. The cluster analysis approach was effective in reducing the number of regions to be delineated for RFA.