Geoscientists have extensively used machine learning for geological mapping and exploring the mineral prospect of a province. However, the interpretation of results becomes challenging due to the complexity of machine learning models. This study uses a convolutional neural network (CNN) and Shapley additive explanation (SHAP) to estimate potential locations for gold mineralisation in Rengali Province, a tectonised mosaic of volcano-sedimentary sequences juxtaposed at the interface of the Archaean cratonic segment in the north and the Proterozoic granulite provinces of the Eastern Ghats Belt in Eastern India. The objective is to integrate multi-thematic data involving geological, geophysical, mineralogical and geochemical surveys on a 1:50 K scale with the aim of prognosticating gold mineralisation. The available data utilised during the integration include aero-geophysical (aeromagnetic and aerospectrometric), geochemical (national geochemical mapping), ground geophysical (gravity), satellite gravity, remote sensing (multispectral) and National Geomorphology and Lineament Project structural lineament maps obtained from the Geological Survey of India Database. The CNN model has an overall accuracy of 90%. The SHAP values demonstrate that the major contributing factors are, in sequential order, antimony, clay, lead, arsenic content and a magnetic anomaly in CNN modelling. Geochemical pathfinders, including geophysical factors, have high importance, followed by the shear zones in mineralisation mapping. According to the results, the central parts of the study area, including the river valley, have higher gold prospects than the surrounding areas. Gold mineralisation is possibly associated with intermediate metavolcanics along the shear zone, which is later intruded by quartz veins in the northern part of the Rengali Province. This work intends to model known occurrences with respect to multiple themes so that the results can be replicated in surrounding areas.
The survival and growth rate of the Indian freshwater mussel, Lamellidens marginalis, (Lamarck) was ascertained in cultivation by using certain drugs in CIFA, fish farm, BBSR (India) during June 1998 to February 1999. Two sets of experiments were carried out to evaluate the effects of drugs like Betamethasone, Calcium, Azathioprine, Stanazolol, and Folic acid. Chloramphenicol was added with each treatment as prophylaxis to prevent the bacterial growth. In the first set, the inactiveness and mortality of the mussels in different drugs were studied through two different dosages and in subsequent tests the fixation of dosage was employed. The study in the second set was regarding the survival, increment of shell length, its thickness, and wet weight in response to different drugs therapy. The drugs were administered parenterally in "fixed dosage" at a regular interval of 21-23 days. The survival rate was good with Betamethasone and Azathioprine that is 75%, whereas it was 16.66% in Folic acid treatment. But the mussels originating from the control site had the significant survival rate though the growth rate was average. Calcium treatment had shown a marked increment of shell thickness and luster. The culture was lasted for 160 days. The wet weight gain of mussels in all the treatments were significant, p<0.0001 whereas increment of shell thickness was significant only in treatment B (Calcium) and treatment D (Azathioprine), p<0.0001 but with regard to the increment of length of mussel, treatment E (Stanazolol) was not significant, p>0.05. The regression analysis was adopted to find out the coefficient of determination (R(2)=0.90, being the best) from the relationship between length and weight of mussels and to establish the LWR equation with condition factor k=W/L(b).
Sea Surface Temperature (SST) derived from the NOAA AVHRR satellite data were used to generate the Degree of Heating Weeks (DHW) and Hot Spot (HS) products. Combination of the cumulative temperature anomalies and the thermal stress studies were yielded to synoptically identify the probable areas of bleaching. The bleaching status of the Andaman region was assessed based on the DHW and HS for the bleaching event occurred in the Andaman region in April/May 2005. The bleaching status up to Alert Level-1 was recorded with the maximum HS of 3 o C and DHW 6 o C-week. Simultaneous in-situ reef observations conducted in the Andaman Sea confirmed the coral bleaching event. The maximum mortality in the region due to coral bleaching was shown by the Acropora species (43%) followed by Montipora species (22%) and Porites species (14%). This study focused on detection of coral bleaching warning based on the SST in compliment with the in-situ observations.
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