The development of a physiologically-based pharmacokinetic model using the distribution of 2,3,7,8-tetrachlorodibenzo-p-dioxin in the tissues of the eastern oyster (Crassostrea virginica)

A physiologically-based pharmacokinetic model (PBPK) was developed to describe the kinetics of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in the eastern oyster (Crassostrea virginica). The estimated t(1/2) of elimination for a bolus dose of TCDD in C. virginica is approximately 14-24 days based on both the experimental data and the PBPK model. The highest dioxin concentration reached during 28-days was in the digestive gland followed by the mantle, gonad, hemolymph, gill, adductor muscle, and the kidney/heart. A binding protein for 2,3,7,8-TCDD had been reported in the literature for both the digestive gland and gonad. Incorporating a binding component in the model resulted in a better fit for the data. The PBPK model predicted the distribution and the elimination concentrations for 2,3,7,8-TCDD within each of the tissue compartments. This model will serve as a useful tool for predicting the kinetics of other persistent organic pollutants as well as, allow for a more refined ecological risk assessment by estimating dioxin concentrations in sensitive tissues such as the gonad.     

Hyperspectral Remote Sensing of Forests: Technological advancements,Opportunities and Challenges

In real world what we are able to see is just because of light or energy reflected or emitted from the viewing object is falling upon retina of human eye. The variations in intensity of light reflected back from any object in different wavelengths are sensed and provide ability of discriminating different objects having similar size and shape. In the same way, in spectroscopy we sense the reflected light through artificial sensors and record as image (in airborne and satellite spectroscopy) or as spectrum (in field spectroscopy). In remote sensing discrimination of different object mainly depends on difference in reflection of energy in different wavelength region of light. Considering this behaviour of light, in hyperspectral remote sensing the reflected light coming from object is split into multiple continuous and small-small wavelength bands and are sensed in each wave band separately. Therefore we are having reflection response of object in multiple and narrow wavelength regions, which can be used in discrimination of different objects that are not separable in multispectral remote sensing due to less number of broad range wave bands. Collection of data is one aspect of the technology but as soon as these data are collected, a question arises how to and where to use this data? To answer where to use, a list of applications like discrimination, mapping and monitoring of different features and process of landforms in ecosystem have been reported, and forestry is one of them. And question of how to use these data in each applications involve converting the raw data into useful information using a multistep process of atmospheric, radiometric and geometric correction, removal of bad data and data redundancy, transformation and extraction of most useful data, data segmentation and extraction of useful information. For this purpose variety of data processing techniques, algorithms, concepts and schemes have been reported from time to time. In this review article we have summarized the available technical developments in hyperspectral remote sensing during the last three decades and tried to discuss the opportunities and challenges in hyperspectral remote sensing applications in the forestry sector.     

Spitze Angle Changes during Rapid Geomagnetic Core Field Variation

Geomagnetism and Aeronomy - The spitze phenomenon is an outstanding feature of electromagnetic wave propagation through the ionosphere. It consists in a ray path cusp that occurs between vertical...     

Study of spectral signatures for exploration of Bauxite ore deposits in Panchpatmali,India

Spectral analysis technique has been utilized to identify the Bauxite mineral occurrences in Panchpatmali, Orissa, India. Spectral processing of Landsat ETM+ data has been carried out by converting the digital data from quantized and calibrated values to reflectance values. Minimum noise fraction transformation is used to determine the inherent dimensionality of reflected Landsat ETM+ data, to segregate noise in the data, and to reduce the computational requirements for subsequent processing and interactively to locate pure pixels within the data-set, projecting n-dimensional scatterplots. Spectral processing results are displayed in the form of images corresponding to each group of pixels (endmembers). Mixed tune matched filtering method has been applied on Landsat ETM+ images which gave three score (abundance) images for three different classes (endmembers) such as Bauxite, vegetation and soil. Further, mineralized zones are identified using image fusion of ERS-2 SAR and Landsat ETM+ data using intensity-hue-saturation technique.     

Geomorphic investigation of the Late-Quaternary landforms in the southern Zanskar Valley,NW Himalaya

The Suru, Doda and Zanskar river valleys in the semi-arid region of Southern Zanskar Ranges (SZR) preserve a rich repository of the glacial and fluvial landforms, alluvial fans, and lacustrine deposits. Based on detailed field observations, geomorphic mapping and limited optical ages, we suggest four glaciations of decreasing magnitude in the SZR. The oldest Southern Zanskar Glaciation Stage (SZS-4) is inferred from glacially polished bedrock and tillite pinnacles. The SZS-4 is ascribed to the Marine Isotopic Stage (MIS)-4/3. The subsequent SZS-3 is represented by obliterated and dissected moraines, and is assigned to MIS-2/Last Glacial Maximum. The multiple recessional moraines of SZS-2 glaciation are assigned the early to mid Holocene age whereas, the youngest SZS-1 moraines were deposited during the Little Ice Age. We suggest that during the SZS-2 glaciation, the Drang-Drung glacier shifted its course from Suru Valley (west) to the Doda Valley (east). The study area has preserved three generations of outwash gravel terraces, which broadly correlate with the phases of deglaciation associated with SZS-3, 2, and 1. The alluvial fan aggradation, lacustrine sedimentation, and loess deposition occurred during the mid-to-late Holocene. We suggest that glaciation was driven by a combination of the mid-latitude westerlies and the Indian Summer Monsoon during periods of cooler temperature, while phases of deglaciation occurred during enhanced temperature.     

Shoreline change analysis and its application to prediction: A remote sensing and statistics based approach

Shoreline change analysis and prediction are important for integrated coastal zone management, and are conventionally performed by field and aerial surveys. This paper discusses an alternative cost-effective methodology involving satellite remote sensing images and statistics. Multi-date satellite images have been used to demarcate shoreline positions, from which shoreline change rates have been estimated using linear regression. Shoreline interpretation error, uncertainty in shoreline change rate, and cross-validation of the calculated past shorelines have been performed using the statistical methods, namely, Regression coefficient (R²) and Root Mean Square Error (RMSE). This study has been carried out along 113.5 km of coast adjoining Bay of Bengal in eastern India, over the time interval 1973 to 2003. The study area has been subdivided into seven littoral cells, and transects at uniform interval have been chosen within each cell. The past and future shoreline positions have been estimated over two time periods of short and long terms in three modes, viz., transect-wise, littoral cell-wise and regionally.The result shows that 39% of transects have uncertainties in shoreline change rate estimations, which are usually nearer to cell boundaries. On the other hand, 69% of transects exhibit lower RMSE values for the short-term period, indicating better agreement between the estimated and satellite based shoreline positions. It is also found that cells dominated by natural processes have lower RMSE, when considered for long term period, while cells affected by anthropogenic interventions show better agreement for the short-term period. However, on regional considerations, there is not much difference in the RMSE values for the two periods. Geomorphological evidence corroborates the results. The present study demonstrates that combined use of satellite imagery and statistical methods can be a reliable method for shoreline related studies.     

Google Earth Engine for concurrent flood monitoring in the lower basin of Indo-Gangetic-Brahmaputra plains

Natural Hazards - The present study focused on the recent flood inundation (July 2020) that occurred in the lower Indo-Gangetic-Brahmaputra plains (IGBP) using concurrent C-band Sentinel-1A...