Vector-borne diseases of man and their socio-economic impact

Vector-borne diseases such as malaria, lymphatic filariases, schistosomiasis, leishmaniasis, onchocerciasis, trypanosomiasis, dengue and dengue haemorrhagic fever (DHF), yellow fever and Japanese encephalitis, globally account for suffering amongst more than one billion people, mostly from the developing world. Geographical distribution and prevalence of these diseases have been discussed. In addition to the mortality caused by these diseases, millions of people lead a hopeless life and are socially unable to achieve self-realization and be economically productive, as a result of these diseases. Examples of such economic impact and the costs of these diseases and methods of control have been given. Economic benefits of control of some of these diseases have been discussed. These concepts are of utility when resource allocation for control of these diseases is under consideratio

Aerosol Characteristics at a high-altitude station Nainital during the ISRO-GBP Land Campaign-II

During the second land campaign (LC-II) organised by ISRO-GBP, extensive ground-based measurements of aerosol characteristics were carried out over Manora Peak (29.4oN; 79.5oE; 1951 metres above mean sea level), Nainital (a high altitude station located in the Shivalik ranges of Central Himalayas) during the dry, winter season (December) of 2004. These measurements included the spectral aerosol optical depths (AOD), columnar water vapour content (W), Total Columnar Ozone (TCO), total number concentration (NT) of near surface aerosols, mass concentration of black carbon (MB), aerosol mass loading (MT), and Global Solar Radiation. Based on these measured parameters, we present the results on the near-surface and columnar properties of atmospheric aerosols at Nainital.Comment: Published in the Proceedings of the ISRO-GBP Land-Campaign-II meeting, Physical Research Laboratory, Ahmadabad (Inida), March 200

Application of Molecular Pathology Techniques to Understand Mechanisms of Disease in Smallmouth Bass

In the Chesapeake Bay drainage, smallmouth bass Micropterus dolomieu are used as an indicator species of estrogenic contaminant exposure and have been implicated in fish kills and disease since 2005. In the Potomac River drainage, adult smallmouth bass have experienced mortality and disease and males have a high prevalence of intersex (testicular oocytes). Conversely, in the Susquehanna River drainage mortalities and disease of young-of-the-year smallmouth bass (YOY SMB) have occurred and resulted in a population shift to older and larger fish. The exact cause of these events remains unknown; however, factors such as poor water quality, contaminants, pathogens and parasites, increased temperatures, and nutrification have been assessed. In order to address this issue, the USGS Fish Health Branch, Leetown Science Center, and West Virginia Cooperative Fish and Wildlife Research Unit have ongoing assessment and monitoring projects throughout the Chesapeake Bay watershed. The use of routine histopathology has provided guidance for further research with molecular endpoints that may help explain the mechanisms involved in disease in smallmouth bass. The purpose of this dissertation research was to: 1.) Identify the prevalence of coinfections and risk factors of disease in YOY SMB; 2.) Use in situ hybridization to identify coinfections of bacteria with the myxozoan parasite Myxobolus inornatus in YOY smallmouth bass; 3.) Model liver helminths and coinfections of YOY SMB with land use at two spatial scales; 4.) Develop laser capture microdissection methods for nucleic acid extractions which could be used with smallmouth bass tissues; and 5.) Utilize Next-Generation Sequencing to develop a partial testes transcriptome to identify molecular markers that may help explain intersex development in male smallmouth bass

Retrieval of columnar aerosol size distributions from spectral attenuation measurements over Central Himalayas

Extensive measurements of spectral aerosol optical depths (AODs) were made at Manora Peak, Nainital (29.4°N, 79.5°E, ~1958 m above mean sea level) in the central Himalayas, using a ten channel multi-wavelength solar radiometer during January 2002 to December 2005. Using these spectral AOD values, the columnar size distribution [CSD; nc(r)] function of aerosols have been derived. The CSD, retrieved from spectral AODs are, in general, bimodal (combination of power law and unimodal log normal distribution) with a prominent secondary (or coarse) mode occurring at a fairly large value of radius (r >0.5 µm), while the primary (or fine) mode either does not appear explicitly or perhaps occurs below the radius ≅ 0.1 µm. The bimodal nature of CSDs indicates the presence of fine as well as coarse mode aerosols over the observational site. The effective radius, total aerosol number content and columnar mass loading computed from deduced CSD shows minimum values during winter (November to February) and maximum during summer (March to June) months. The share of sub micron and super micron aerosols to the total aerosol number concentration (Nt) indicates the dominance of sub micron aerosols to the Nt and it accounts for > 90% during the study period

Sulphur Mustard Induced Toxicity, Mechanism of Action and Current Medical Management

Sulphur mustard (SM), chemically, bis (2-chloroethyl) sulphide is a bifunctional alkylating agent that causes cutaneous blisters in human or animals. It was first used in the World War I. Since then, there have been 11 conflicts where SM allegedely had caused mass distruction. Additionally, discarded weapons and stockpiles periodically come to surface during agricultural or fishing activities leading to serious injury. Concerns for threat to modern societies by the serious effects of SM, agreements to ban its production and the use has been made as per 1993 chemical weapons convention (CWC) and agent destruction programs. This short review attempts to discuss the histroy, chemical nature, mechanism of toxicity, toxicokinetics, animal models used for SM induced skin and systemic lesions, pathogenesis of SM induced lesions including medical countermeasures for SM toxicity

Simulating Burr Type VII Distributions through the Method of L-moments and L-correlations

Burr Type VII, a one-parameter non-normal distribution, is among the less studied distributions, especially, in the contexts of statistical modeling and simulation studies. The main purpose of this study is to introduce a methodology for simulating univariate and multivariate Burr Type VII distributions through the method of L-moments and L-correlations. The methodology can be applied in statistical modeling of events in a variety of applied mathematical contexts and Monte Carlo simulation studies. Numerical examples are provided to demonstrate that L-moment-based Burr Type VII distributions are superior to their conventional moment-based analogs in terms of distribution fitting and estimation. Simulation results presented in this study also demonstrate that the estimates of L-skew, L-kurtosis, and L-correlation are substantially superior to their conventional product-moment based counterparts of skew, kurtosis, and Pearson correlation in terms of relative bias and relative efficiency when distributions with greater departure from normality are used

A Doubling Technique for the Power Method Transformations

Power method polynomials are used for simulating non-normal distributions with specified product moments or L-moments. The power method is capable of producing distributions with extreme values of skew (L-skew) and kurtosis (L-kurtosis). However, these distributions can be extremely peaked and thus not representative of real-world data. To obviate this problem, two families of distributions are introduced based on a doubling technique with symmetric standard normal and logistic power method distributions. The primary focus of the methodology is in the context of L-moment theory. As such, L-moment based systems of equations are derived for simulating univariate and multivariate non-normal distributions with specified values of L-skew, L-kurtosis, and L-correlation. Evaluation of the proposed doubling technique indicates that estimates of L-skew, L-kurtosis, and L-correlation are superior to conventional product-moments in terms of relative bias and relative efficiency when extreme non-normal distributions are of concern

An L-Moment Based Characterization of the Family of Dagum Distributions

This paper introduces a method for simulating univariate and multivariate Dagum distributions through the method of L-moments and L-correlation. A method is developed for characterizing non-normal Dagum distributions with controlled degrees of L-skew, L-kurtosis, and L-correlations. The procedure can be applied in a variety of contexts such as statistical modeling (e.g., income distribution, personal wealth distributions, etc.) and Monte Carlo or simulation studies. Numerical examples are provided to demonstrate that -moment-based Dagum distributions are superior to their conventional moment-based analogs in terms of estimation and distribution fitting. Evaluation of the proposed method also demonstrates that the estimates of L-skew, L-kurtosis, and L-correlation are substantially superior to their conventional product-moment based counterparts of skew, kurtosis, and Pearson correlation in terms of relative bias and relative efficiency–most notably in the context of heavy-tailed distributions

Uniform-based and triangular-based third-order power method distributions using a doubling technique distributions

Power method (PM) polynomials have been used for simulating non-normal distributions in a variety of settings such as toxicology research, price risk, business-cycle features, microarray analysis, computer adaptive testing, and structural equation modeling. A majority of the applications associated with the PM polynomials are based on the method of matching conventional moments (e.g., skew and kurtosis). However, estimators of skew and kurtosis can be (a) substantially biased, (b) highly dispersed, or (c) influenced by outliers. To address this limitation, two families of third-order PM distributions are developed through the method of -moments (Hosking, 1990) using a doubling technique (Morgenthaler & Tukey, 2000) and contrasted with the method of moments in the contexts of estimation of parameters. The methodology is based on simulating uniform- and triangular-based third-order PM distributions with specified values of -skew and - kurtosis. Monte Carlo simulation results indicate that the estimators based on method of Lmoments are superior to their conventional moment-based counterparts