Analyzing seasonality of tuberculosis across Indian states and union territories.

A significant seasonal variation in tuberculosis (TB) is observed in north India during 2006-2011, particularly in states like Himachal Pradesh, Haryana and Rajasthan. To quantify the seasonal variation, we measure average amplitude (peak to trough distance) across seasons in smear positive cases of TB and observe that it is maximum for Himachal Pradesh (40.01%) and minimum for Maharashtra (3.87%). In north India, smear positive cases peak in second quarter (April-June) and reach a trough in fourth quarter (October-December), however low seasonal variation is observed in southern region of the country. The significant correlations as 0.64 (p-value<0.001), 0.54 (p-value<0.01) and 0.42 (p-value<0.05) are observed between minimum temperature and seasonality of TB at lag-1 in north, central and northeast India respectively. However, in south India, this correlation is not significant

A quantitative assessment on 26/11 Mumbai attack using social network analysis

This paper analyses, the terror attacks in Mumbai on November 26, 2008, popularly known as 26/11 terror attacks, as per a mathematical technique known as Social Network Analysis (SNA). This analysis of the behaviour of the ten attackers and their telephonic communications with their handlers in Pakistan even as the attacks were in progress is based on the open source information. Using the SNA technique, we identify the key members, sub-groups, and the interaction among the various members of the group. The analysis gives useful insights into the modus operandi of the terrorists. We have found that a star-type structure of hierarchy prevailed during the attack which means terrorists were well connected through a central node.Publisher PD

CMIP5 Projected Changes in the Annual Cycle of Indian Monsoon Rainfall

The annual cycle of Indian monsoon rainfall plays a critical role in the agricultural as well as the industrial sector. Thus, it is necessary to evaluate the behaviour of the monsoon annual cycle in a warming climate. There are several studies on the variability and uncertainty of the Indian monsoon. This study, examines the impact of climate change on the annual cycle of monsoon rainfall in India from 1871–2100 by applying 20 model simulations designed by the World Climate Research Programme (WCRP) coupled with the model inter-comparison Project 5 (CMIP5). It is found that the models MPI-ESM-LR, INM-CM4 and MRI-CGCM3 best capture the spatial patterns of the monsoon rainfall peak month (MRPM) of the winter monsoon compared to observations, whereas HadGEM2-AO and MIROC-ESM-CHEM best capture the MRPM of the summer monsoon. The MIROC, MIROC-ESM, and MIROC-ESM-CHEM models best capture the average rainfall intensity as well as the MRPM of all-India rainfall. This paper examines the future spatial distribution of the MRPM for meteorological sub-divisions of India, that can have crucial implications for water resources and management. Although the future projections as per the CMIP5 models indicate no changes in the MRPM of the all-India rainfall, a reduction in average intensity can be expected. The projections indicate a shift in the MRPM in some meteorological sub-divisions, particularly with regard to the summer monsoon but no significant change has been projected for the winter monsoon. For example, the summer monsoon MRPM is projected to move from July to August in northern and central India

Statistical Selection of the Optimum Models in the CMIP5 Dataset for Climate Change Projections of Indian Monsoon Rainfall

Monsoons are the life and soul of India’s financial aspects, especially that of agribusiness in deciding cropping patterns. Around 80% of the yearly precipitation occurs from June to September amid monsoon season across India. Thus, its seasonal mean precipitation is crucial for agriculture and the national water supply. From the start of the 19th century, several studies have been conducted on the possible increments in Indian summer monsoon precipitation in the future. Unfortunately, none of them has endeavoured to discover the models whose yield give the best fit to the observed data. Here some statistical tests are performed to quantify the models of Coupled Model Inter-comparison Project 5 (CMIP5). Then, after, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is used to select optimum models. It shows that four models, CCSM4, CESM1-CAM5, GFDL-CM3, and GFDL-ESM2G, best capture the pattern in Indian summer monsoon rainfall over the historical period (1871–2005). Further, Student’s t-test is utilized to estimate the significant changes in meteorological subdivisions of selected optimum models. Also, our results reveal the Indian meteorological subdivisions which are liable to encounter significant changes in mean at confidence levels that differ from 80% to 99%

Periodicities in Indian monsoon rainfall over spectrally homogeneous regions

This work presents results of a sharper search for significant periodicities in Indian monsoon rainfall, based on the recognition of the area's meteorological heterogeneity. Towards this end, a quantitative definition of spectral homogeneity is proposed, and the concept is used to classify India into distinct spectrally homogeneous regions (SHR) by two independent methods. The analysis is then carried out for each of the 10 SHRs, which may cut across or be subsets of homogeneous-rainfall zones defined earlier by various workers based on different criteria. A particularly interesting region is SHR7, the largest spectrally homogeneous cluster identified by both methods, which includes sub-divisions from west central and peninsular India. The spectrum here shows a significant dip in the frequency band 0.2-0.31 per year, flanked on either side by a rich structure characterised by nearly coincident spectral peaks in all the seven sub-divisions constituting the region. The significant peaks (confidence level = 99%) in SHR7 are 3.0, 5.7, 10.9, 13.3, 24.0, 30.3 and 60.6 years. The spectral dip is conjectured to be associated with the ENSO (EI Niño-Southern Oscillation) phenomenon, which occurs on the period scales of 3-5 years and is known to be anti-correlated with monsoon rainfall

A wavelet based significance test for periodicities in Indian monsoon rainfall

This paper is a sequel to a recent study of the authors' that uses a combination of multiresolution analysis (MRA) and classical Fourier spectral methods, to identify 17 peaks in the power spectral density of the Homogeneous Indian Monsoon (HIM) rainfall time series constructed in Ref. 1. Here we propose a new procedure for testing the statistical significance of these peaks. In this procedure, using MRA the stationary component of the rainfall time series is first identified. Then (partially) reconstructed time series are derived over each scale band in the stationary component. For each of these time series an appropriately colored reference spectrum is derived. The significance of the detected peaks is then determined using a Χ<SUP>2</SUP> test against the reference spectra, which together represent a noise process spectrally close to rainfall. It is concluded that HIM rainfall exhibits 10 statistically significant periodicities at a confidence level of 99.9%

Multiresolution analysis for separating closely spaced frequencies with an application to Indian monsoon rainfall data

In this paper we make use of the multiresolution properties of discrete wavelets, including their ability to remove interference, to reveal closely spaced spectral peaks. We propose a procedure which we first verify on two test signals, and then apply it to the time series of homogeneous Indian monsoon rainfall annual data. We show that, compared to empirical mode decomposition, discrete wavelet analysis is more effective in identifying closely spaced frequencies if used in combination with classical power spectral analysis of wavelet-based partially reconstructed time series. An effective criterion based on better localization of specific frequency components and accurate estimation of their amplitudes is used to select an appropriate wavelet. It is shown here that the discrete Meyer wavelet has the best frequency properties among the wavelet families considered (Haar, Daubechies, Coiflet and Symlet). In rainfall data, the present analysis reveals two additional spectral peaks besides the fifteen found by classical spectral analysis. Moreover, these two new peaks have been found to be statistically significant, although a detailed discussion of testing for significance is being presented elsewhere

South Asian consensus statement on women\u27s health and Ramadan

Fasting during Ramadan, the holy month of Islam, is mandatory for all healthy adult Muslims. It is estimated that there are 1.1-1.5 billion Muslims worldwide, comprising 18-25% of the world population. About 62% of the world\u27s Muslim population resides in Asia. Women comprise approximately 50% of this population. There is great religious fervor and enthusiasm in the majority of Muslims the world over for observing the religious fasting. Many of the Muslim women perhaps due to the family and societal pressures or lack of proper information hesitate and fail to avail themselves of the generous provisions of temporary or permanent exemptions from fasting available in Islam. It is therefore important that medical professionals as well as the general population be aware of potential risks that may be associated with fasting during Ramadan. This familiarity and knowledge is as important in South Asia and the Middle East as it is in Europe, North America, New Zealand, and Australia. There has not yet been any statement of consensus regarding women\u27s health issues during Ramadan, namely menstruation, sexual obligations of married life, pregnancy, and lactation. This document aims to put forward some of the general guidelines for these issues especially for the South Asian Muslim wome

South Asian consensus statement on women′s health and Ramadan

Fasting during Ramadan, the holy month of Islam, is mandatory for all healthy adult Muslims. It is estimated that there are 1.1-1.5 billion Muslims worldwide, comprising 18-25% of the world population. About 62% of the world′s Muslim population resides in Asia. Women comprise approximately 50% of this population. There is great religious fervor and enthusiasm in the majority of Muslims the world over for observing the religious fasting. Many of the Muslim women perhaps due to the family and societal pressures or lack of proper information hesitate and fail to avail themselves of the generous provisions of temporary or permanent exemptions from fasting available in Islam. It is therefore important that medical professionals as well as the general population be aware of potential risks that may be associated with fasting during Ramadan. This familiarity and knowledge is as important in South Asia and the Middle East as it is in Europe, North America, New Zealand, and Australia. There has not yet been any statement of consensus regarding women′s health issues during Ramadan, namely menstruation, sexual obligations of married life, pregnancy, and lactation. This document aims to put forward some of the general guidelines for these issues especially for the South Asian Muslim women