Debabrata Datta

Bio: Debabrata Datta is an academic researcher from Bhabha Atomic Research Centre. The author has contributed to research in topics: Fuzzy number & Uncertainty analysis. The author has an hindex of 15, co-authored 154 publications receiving 885 citations. Previous affiliations of Debabrata Datta include Tripura Institute of Technology & Homi Bhabha National Institute.

Chronic oral arsenic intoxication as a possible aetiological factor in idiopathic portal hypertension (non-cirrhotic portal fibrosis) in India.

Abstract: Estimates were made of the arsenic concentration in liver specimens from nine patients having idiopathic portal hypertension (IP), and in four livers these were found to be significantly higher than those in patients with cirrhosis and in control subjects. The splenovenogram revealed extensive portosystemic collateral circulation. Corrected sinusoidal pressure and blood flow studies showed higher levels in four patients than in normal subjects. Microscopic examination of liver tissues revealed periportal fibrosis. The higher hepatic arsenic levels that were found were due to the inadvertent drinking of water contaminated with arsenic, adulterated opium, and indigenous medicines. A history of opium intake was not forthcoming but two patients had drunk water contaminated with arsenic and two others had taken bhasams (Ayurvedic medicines prepared by repeated oxidation of ores). Though the aetiology of idiopathic portal hypertension is not known, it is possible that arsenic intake may be one of the factors.

Quantification of tolerance limits of engineering system using uncertainty modeling for sustainable energy

Abstract: Measurements always associate a certain degree of uncertainty. In order to achieve high precision measurement in presence of uncertainty an efficient computation is desired. Statistical definition of precision of any measurement is defined as one standard deviation divided by the square root of the sample size taken for measurements. Accordingly, tolerance limits are statistical in nature. Therefore, measurements are required to repeat large number of times to obtain better precision. Hence, the target is to establish the tolerance limits in presence of uncertainty in computer and communication systems. Nonparametric method is applied to establish the tolerance limits when uncertainty is present in measurements. The basic aim of the present paper is to explore order statistics based nonparametric method to estimate the appropriate number of samples required to generate the realizations of the uncertain random parameters which further will facilitate user to establish the tolerance limits. A case study of solute transport model is experimented where tolerance limits of solute concentration at any spatial location at any temporal moment is shown. Results obtained based on the nonparametric simulation are compared with the results obtained by executing traditional method of setting tolerance limits using Monte Carlo simulations using computer and communication systems.

Assessment of Multiple Tolerance Indices for Salinity Stress in Bread Wheat (Triticum aestivum L.)

Abstract: Salinity is one of the major factors reducing plant growth and productivity worldwide and affects about 7% of world’s total land area. In India about 6.73 million hectare of land area is salt affected. Wheat is the second most important crop after rice in India and occupies approximately 28.5 million hectare area. Several tolerance indices comprising of mean productivity (MP), geometric mean productivity (GMP), stress tolerance index (STI), stress stability index (SSI), tolerance index (TOL), yield index (YI) and yield stability index (YSI) were calculated in this investigation for salinity and its ability to understand which one or more predictor among studied indices based on correlation, principal component analysis and cluster analysis. Ten wheat genotypes were evaluated in two successive growing seasons (2012-2014), with complete randomized design with three replications under both salinity stress and non-salinity to identify salt tolerant genotypes to the target environment. Multiple indices for salt tolerance were calculated based on the potential yield (Yp) under non-stress and yield (Ys) under stress conditions. The Ys and Yp showed highest significant and positive correlations with GMP, MP and STI among indices studied. Therefore, these indices were considered as a better predictor of Ys and Yp than TOL, SSI and YSI. Principal component analysis classified the genotypes into two groups. The first two PCs with eigen values >1 contributed 99.74% of the variability amongst genotypes. PC1 accounted for about 5.24% of the variation in salt tolerance indices and PC2 for 3.74%. The first PC was related to Ys, Yp, MP, GMP, STI and YI whereas the second PC related to Yp, TOL and SSI. The cluster analysis sequestrated ten genotypes into two clusters based on Ward’s method. According to results, salinity significantly reduced the yield of some genotypes while some were found tolerant to stress indicating sufficient genetic variability for salinity tolerance among the studied genotypes. It could be implicated in selection of salinity tolerant wheat genotypes for the development of bread wheat varieties.

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Nuclear reactor analysis

Abstract: This is cne of the r-are text books written in the discipline of Nuclear Reactor Analysis, where the author has considered the interests of both scientists and practising engineers, in addition to serving the needs of the academia. The most attractive feature of this book is a balanced treatment of theory and practice of the subject matter. The theoretical foundations of the reactor design methods are explained with simplified definitions and relevant practical illustrations. The author scans through quickly the traditional aspects of the so-called reactor physics and takes the reader through the details of the analytical aspects in a conventional manner. Hcwever, there is a definite departure from the classical method of approach in order to avoid lengthy and repetitive discussions, that are available in many standard text books on reactor physics. The chief departure fran tradition is the priority accorded to the treatment of the energy part of the problems as opposed to the spatial Dart normally devoted to by other authors . A similar unorthodox approach has been applied while dealing with the solution of the various equations by giving priority to computer oriented mrethods as opposed to the classical solutions.

Diabetes Mellitus Associated with Arsenic Exposure in Bangladesh

Abstract: The objective of this study was to assess whether arsenic exposure is a risk factor for diabetes mellitus as indicated in a few earlier studies. Arsenic in drinking water is known to occur in western Bangladesh, and in 1996, two of the authors conducted a survey of the prevalence of diabetes mellitus among 163 subjects with keratosis taken as exposed to arsenic and 854 unexposed individuals. Diabetes mellitus was determined by history of symptoms, previously diagnosed diabetes, glucosuria, and blood sugar level after glucose intake. The crude prevalence ratio for diabetes mellitus among keratotic subjects exposed to arsenic was 4.4 (95% confidence interval 2.5-7.7) and increased to 5.2 (95% confidence interval 2.5-10.5) after adjustment for age, sex, and body mass index. On the basis of a few earlier measurements of arsenic concentrations in drinking water by the authorities in Bangladesh and another 20 new ad hoc analyses, approximate time-weighted exposure levels to arsenic in drinking water could be estimated for each subject. Three time-weighted average exposure categories were created, i.e., less than 0.5, 0.5-1.0, and more than 1.0 mg/liter. For the unexposed subjects, the corresponding prevalence ratios were 1.0, 2.6, 3.9, and 8.8, representing a significant trend in risk (p < 0.001). The result corroborates earlier studies and suggests that arsenic exposure is a risk factor for diabetes mellitus.