A new approach using polyvinylidene fluoride immobilised calf-intestinal alkaline phosphatase for uranium bioprecipitation     

P. Venu-Babu  Gouri Chaudhuri  W. Richard Thilagaraj 《International Journal of Environmental Science and Technology》2018,15(3):599-606

Uranium is a predominant radionuclide arising out of operations of mining, milling and fuel fabrication for nuclear power plants. While chemical and biological methods using several micro-organisms have been employed for the remediation of uranium from such effluents, use of immobilised enzymes for the purpose has not been reported. The current investigation deals with a purified calf-intestinal alkaline phosphatase which is capable of driving uranium precipitation in the presence of a phosphate-containing substrate. The enzyme, both in free form and in an immobilised form on polyvinylidene fluoride membrane, was investigated for the precipitation of uranium using para-nitrophenyl phosphate as substrate. The results indicated that while the enzyme in free form could precipitate most of the uranium within 6 h, the immobilised enzyme could achieve the same in 24 h. There was a spurt in the precipitation of uranium by the immobilised enzyme during the initial period of 3 h followed by a linear increase for the remaining period. The immobilised enzyme was found to be stable and catalytically active for 3 years in precipitating uranium. The results obtained offer polyvinylidene fluoride immobilised alkaline phosphatase from calf intestine as a new tool for the remediation of uranium from effluents. Further, evidence has been also shown that no requirement for any cellular architecture/scaffolding exists for uranium mineralisation to occur.  相似文献   

Generalized Potential Temperature in a Diagnostic Study of High Impact Weather over an Urban Station of India     

Sutapa Chaudhuri  Debashree Dutta 《Pure and Applied Geophysics》2014,171(8):2013-2021

The tropospheric atmosphere is neither absolutely dry nor completely saturated. It is, in general, moist. The purpose of the present study is to reveal the role of generalized potential temperature (GPT) in describing the humid state of the real moist atmosphere pertaining to understanding the prevalence of high impact weather systems over an urban station, Kolkata (22°32′N; 88°20′E), of India. A comparative study among GPT, equivalent potential temperature (EPT), potential temperature and relative humidity to reveal the significance of GPT in a precise understanding of the high impact weather of Kolkata is carried out. To attain the objectives, 50 cases of thunderstorms, 15 cases of tropical cyclones and 15 heavy rainfall days are selected during the pre-monsoon season (April–May) over Kolkata (22°32′N; 88°20′E), India. The condition—decision support system of rough set theory is adopted as the methodology. The result of the study reveals that GPT is the most pertinent convective parameter in estimating the prevalence of the high impact weather of Kolkata during the pre-monsoon season and is observed to be better than RH. The results, thus, show that the moist air is capable of describing the distribution of water vapour and thermodynamic properties of the real atmosphere more precisely than an absolutely dry and completely saturated state of the atmosphere.  相似文献   

Shelf water entrainment by Gulf Stream warm-core rings between 75°W and 50°W during 1978–1999     

Ayan H. Chaudhuri  James J. BisagniAvijit Gangopadhyay 《Continental Shelf Research》2009

Previous work concerning Gulf Stream warm-core rings (WCRs) and their associated shelf water entrainments have been based upon single surveys or time series from individual WCRs. To date, estimates of annual shelf water volume entrained into the Slope Sea by WCRs and its interannual variability have not been made. Using a long time series of satellite-derived sea surface temperature (SST) observations of Slope Sea WCRs, we have completed an analysis of 22 years of WCR data (1978–1999) between 75°W and 50°W to understand the interannual variability of WCRs and their role in entraining shelf water. Satellite-derived SST data digitized at Bedford Institute of Oceanography are analyzed using an ellipse-fitting feature model to determine key WCR characteristics including WCR center position, radius and orientation. Key characteristics are then used to compute WCR swirl velocity by finite-differencing WCR orientations (θ) obtained from the feature model time series. Global mean WCR-edge swirl velocity calculated from all observations is 105.72±10.7 km day⁻¹ (122.36±12.4 cm s⁻¹), and global mean WCR radius is 64.8±6.2 km. Primary and derived WCR data are incorporated into a two-dimensional ring entrainment model (RM) using the quasi-geostrophic approximation of the potential vorticity equation. The RM defines ambient water as entrained by a WCR only if the gradient of relative vorticity term (horizontal shear) dominates the potential vorticity. Proximity of a WCR to the position of the shelf-slope front (SSF) is then used to determine whether the ambient water is entrained from the outer continental shelf. WCR-induced shelf entrainment derived from the RM displays considerable spatial variability, with maximum entrainment occurring offshore of Georges Bank, advecting a mean total annual shelf water volume of 7500 km³ year⁻¹ from the region. Estimates of shelf water fluxes display significant interannual variability, which may be in part due to the observed covariance between WCR occurrences and the state of the North Atlantic Oscillation (NAO). Increased (decreased) occurrences of WCRs are evidenced during positive (negative) phases of the NAO. The total mean annual shelf-wide WCR-induced shelf water transport is estimated to be 23,700 km³ year⁻¹ (0.75 Sv), accounting for nearly 25% of the total transport in the Slope Sea region neighboring the outer continental shelf.  相似文献   

Empirical approaches in prediction of reservoir sediment distribution——An experience of 57 reservoirs in the USA and India     

Dipankar Chaudhuri 《国际泥沙研究》2017,32(2)

An accurate prediction of sediment distribution may minimize economic losses through proper and timely planning of the functional activities of a reservoir.This study assesses different temporal and spatial factors that affect for sediment deposition in a reservoir and its distribution.This study also focuses on evaluation of two popular distribution prediction methodologies,Area Increment and Empirical Area Reduction,based on experience with sediment distribution in 57 reservoirs in the USA and India.A non-iterative processed empirical distribution model(NPEDM) and a linear regression trend model(LRTM) are proposed to predict sediment distribution.Silt contributing area and inflow entering a reservoir are found to be the most significant factors affecting in reservoir sediment deposition.Compared to the Empirical Area Reduction method,the Area Increment method provided better prediction.The reservoir classification approach and empirical design distribution type curves given by Borland and Miller(1960) are found to be rational.Shape factor values for different periods indicate that reservoir shape(type) changes with time.Thus,long term prediction is not desirable in Type-Ⅱ Ⅲ reservoirs using the Empirical Area Reduction method.Newly developed the NPEDM shows reasonably good prediction of sediment distribution.The NPEDM is very easy to apply and can be used in any reservoir of any size.Extrapolation of the trend of sediment distribution obtained from the LRTM indicates an accurate short term prediction in a few reservoirs as causes of temporal and spatial variations of sediment distribution including the factors of uncertainties of sediment deposition are implicit within the methodology.  相似文献   

Nowcasting visibility during wintertime fog over the airport of a metropolis of India: decision tree algorithm and artificial neural network approach     

Dutta  Debashree  Chaudhuri  Sutapa 《Natural Hazards》2015,78(2):1349-1367

Natural Hazards - The endeavor of the present research is to nowcast the spatial visibility during fog over the airport of Kolkata (22.6°N; 88.4°E), India, with artificial neural network...  相似文献   

Predictability of landfall location and surge height of tropical cyclones over North Indian Ocean (NIO)     

Chaudhuri  Sutapa  Goswami  Sayantika  Middey  Anirban  Das  Debanjana  Chowdhury  S. 《Natural Hazards》2015,78(2):1369-1385

Natural Hazards - Forecasting, with precision, the location of landfall and the height of surge of cyclonic storms prevailing over any ocean basin is very important to cope with the associated...  相似文献   

Effect of suspended sediment concentration on local scour around cylinder for clay–sand mixed sediment beds     

Koustuv Debnath  Susanta Chaudhuri 《Engineering Geology》2011,117(3-4):236-245

Suspended sediments present in the flow are known to affect the flow resistance, velocity distribution and turbulent characteristics. Experiments were conducted in the laboratory flume to see the effect of suspended sediment concentration (SSC) on local scour around a cylindrical pier for a wide range of clay–sand mixed sediment beds for SSC up to 2700 mg/L. It has been observed that the effect of SSC on equilibrium scour hole parameters such as maximum equilibrium scour depth, and longitudinal and transverse extent of scour hole can be significant. Present data showed that the presence of SSC in the range 993–1332 mg/L can increase maximum equilibrium scour depth as much as 1.54 times compared to the clear water case. However, tests made for SSC in the range 2456–2700 mg/L showed that the maximum equilibrium scour depth reduced compared to that for SSC in the range 993–1332 mg/L, but these maximum equilibrium scour depths were still larger than that obtained for clear water. The effect of SSC on time variation of scour and equilibrium scour hole geometry was further investigated.  相似文献   

Adaptive neuro-fuzzy inference system to forecast peak gust speed during thunderstorms     

Sutapa Chaudhuri  Anirban Middey 《Meteorology and Atmospheric Physics》2011,114(3-4):139-149

The aim of the present study is to develop an adaptive neuro-fuzzy inference system (ANFIS) to forecast the peak gust speed associated with thunderstorms during the pre-monsoon season (April?CMay) over Kolkata (22°32??N, 88°20??E), India. The pre-monsoon thunderstorms during 1997?C2008 are considered in this study to train the model. The input parameters are selected from various stability indices using statistical skill score analysis. The most useful and relevant stability indices are taken to form the input matrix of the model. The forecast through the hybrid ANFIS model is compared with non-hybrid radial basis function network (RBFN), multi layer perceptron (MLP) and multiple linear regression (MLR) models. The forecast error analyses of the models in the test cases reveal that ANFIS provides the best forecast of the peak gust speed with 3.52% error, whereas the errors with RBFN, MLP, and MLR models are 10.48, 11.57, and 12.51%, respectively. During the validation with the 2009 observations of the India Meteorological Department (IMD), the ANFIS model confirms its superiority over other comparative models. The forecast error during the validation of the ANFIS model is observed to be 3.69%, with a lead time of <12?h, whereas the errors with RBFN, MLP, and MLR are 12.25, 13.19, and 14.86%, respectively. The ANFIS model may, therefore, be used as an operational model for forecasting the peak gust speed associated with thunderstorms over Kolkata during the pre-monsoon season.  相似文献   

Long-range forecast of all India summer monsoon rainfall using adaptive neuro-fuzzy inference system: skill comparison with CFSv2 model simulation and real-time forecast for the year 2015     

S. Chaudhuri  D. Das  S. Goswami  S. K. Das 《Climate Dynamics》2016,47(9-10):3319-3333

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Implementation of Sugeno: ANFIS for forecasting the seismic moment of large earthquakes over Indo-Himalayan region     

Sutapa Chaudhuri  Arumita Roy Chowdhury  Payel Das 《Natural Hazards》2018,90(1):391-405

The earthquake is known to be an unpredictable geophysical phenomenon. Only few seismic indicators and assumptions of earthquakes can be predicted with probable certainty. This study attempts to analyze the earthquakes over the Indo-Himalayan Border region including Bhutan, Bangladesh, Nepal, China and India during the period from 1995 to 2015. Bangladesh, Bhutan and China borders experience fewer earthquakes than Nepal and India border regions. However, Indo-China rim has inconsistency and vast range in its magnitude. Bangladesh though is a small country with respect to others, but it experiences earthquakes comparable to Bhutan. Nepal experiences highest number of earthquakes. In the last 20 years around 800 records have been observed with moment magnitude > 4.0 Richter scale, while very few records (around 10–12) have been observed for large earthquakes having moment magnitude > 6.0 Richter scale over the region. In this study adaptive neuro-fuzzy inference system has been implemented to assess the predictability of seismic moment associated with large earthquakes having the moment magnitude between 6.0 and 8.0 Richter scales using different combination of epochs, technique and membership functions. The Gaussian membership function with hybrid technique and 40 epochs is observed to be the reasonable model on the basis of the selected spatial and temporal scale. The forecast error in terms of root-mean-square error with the stopping criterion 0.001 has been observed to be 0.006 in case of large earthquakes (> 6.5 Richter scale), that is, forecast accuracy of 99.4%. The model bias of 0.6% may be due to inadequate number of large earthquakes having moment magnitude > 6.5 Richter scale over the region.  相似文献