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Reservoirs are aquatic resources with the potential to increase India's fish production through inland fisheries. Thippagondanahalli is a medium-size reservoir on Arkavathy River, a tributary of the Cauvery. It is located in Bangalore rural district of Karnataka (12°58’24” to 12°96'49" N 77°20’33” to 77°35’63” E) and has a water surface area of 1162 ha at full reservoir level and 784.55 m at full supply level. Fish diversity studies were conducted to examine the spatial and temporal variations in fish diversity in relation to habitat parameters. A taxonomic abundance of 25 fish species (80% of them native) belonging to 14 families and 4 orders was recorded. A range of statistical estimators such as Chao 1, Jack 1, and Bootstrap were used to assess the expected species richness. The Jack 1 method showed the highest abundance with 28 species. The littoral zone, dominated by small indigenous species, was found to have relatively higher fish diversity (Shannon index-1.86) compared to the limnetic zone of the reservoir. Shannon diversity was higher in the monsoon season (1.76) compared to other seasons. Physico-chemical parameters revealed that this waterbody is highly eutrophic. Canonical correspondence analysis between seasonal habitat characteristics and seasonal species abundance showed the abundance of the small indigenous fish Amblypharyngodon mola during the post-monsoon season, the bottom feeder Cirrhinus mrigala and the surface feeder Rasbora daniconius during the monsoon season, and the carnivores Mystus malabaricus and Channa orientalis as well as the planktivore Puntius sarana during the pre-monsoon season. This study suggests the use of fisheries management and conservation measures such as fish-aggregating devices, stocking of certified seed, and impact assessment of exotic species.

The pattern of a fish assemblage of a large reservoir, Stanley (also called as Mettur) in Peninsular India was studied to derive various management protocols, specifically fish enhancement. The investigation was carried out in the spatial and temporal scale of the reservoir during 2017–2019. A total of 52 species belonging to 35 genera were recorded indicating high species richness. Simpson (0.17), Shannon (0.17), dominance (0.104), and evenness (0.52) indices did not show significant differences among zones whereas there was a significant difference during different seasons. On a temporal scale, maximum species were recorded in monsoon (47) followed by post-monsoon (43) and pre-monsoon season (33). On a spatial scale, it represented that riverine (47) and transitional zone (37) showed more species richness compared to lacustrine zone (30). Based on the catch structure of this reservoir, it is evident that exotic fishes play a major role in the recent past. One species under critically endangered and endangered, three species under near threatened, and two under vulnerable species were observed in the catch during this study period. The trophic guild of fishes showed the dominancy of planktivores. Abiotic factors such as temperature, pH, and chlorophyll were found directly influencing the species abundance. The study suggested management measures, including observation of closed fishing season, protection of breeding grounds, use of fish aggregating devices, mesh size regulation, and fish seed stocking in the reservoir.

Availability of off-the-shelf infrared sensors combined with high definition visible cameras has made possible the construction of a Software Defined Multi-Spectral Imager (SDMSI) combining long-wave, near-infrared and visible imaging. The SDMSI requires a real-time embedded processor to fuse images and to create real-time depth maps for opportunistic uplink in sensor networks. Researchers at Embry Riddle Aeronautical University working with University of Alaska Anchorage at the Arctic Domain Awareness Center and the University of Colorado Boulder have built several versions of a low-cost drop-in-place SDMSI to test alternatives for power efficient image fusion. The SDMSI is intended for use in field applications including marine security, search and rescue operations and environmental surveys in the Arctic region. Based on Arctic marine sensor network mission goals, the team has designed the SDMSI to include features to rank images based on saliency and to provide on camera fusion and depth mapping. A major challenge has been the design of the camera computing system to operate within a 10 to 20 Watt power budget. This paper presents a power analysis of three options: 1) multi-core, 2) field programmable gate array with multi-core, and 3) graphics processing units with multi-core. For each test, power consumed for common fusion workloads has been measured at a range of frame rates and resolutions. Detailed analyses from our power efficiency comparison for workloads specific to stereo depth mapping and sensor fusion are summarized. Preliminary mission feasibility results from testing with off-the-shelf long-wave infrared and visible cameras in Alaska and Arizona are also summarized to demonstrate the value of the SDMSI for applications such as ice tracking, ocean color, soil moisture, animal and marine vessel detection and tracking. The goal is to select the most power efficient solution for the SDMSI for use on UAVs (Unoccupied Aerial Vehicles) and other drop-in-place installations in the Arctic. The prototype selected will be field tested in Alaska in the summer of 2016.

A simple, precise, rapid, selective, and economic high performance thin-layer chromatography method has been established for simultaneous analysis of atorvastatin (ATV) and ezetimibe (EZE) in tablet dosage forms. The chromatography separation was performed on precoated silica gel 60 GF254 plates with toluene–ethyl acetate–methanol 12:5:3 (v/v/v) as mobile phase. The plate was developed to a distance of 8.0 cm at ambient temperature. The retention factors for ATV and EZE were 0.31 and 0.57, respectively. The detection band was carried out at 254 nm. The calibration curve was linear in the concentration range of 200–1200 ng/spot for both ATV and EZE. For ATV, the recovery study results ranged from 99.44 to 99.54% with RSD value ranging from 0.067 to 0.107%. For EZE, the recovery results ranged from 98.88 to 99.00% with RSD value ranging from 0.154 to 1.756%. The assay was 99.89% for ATV and 99.84% for EZE. The calibration plots revealed a good linear relationship with r 2 = 0.9991 for ATV and 0.9992 for EZE. Both ATV and EZE were subjected to different stress conditions—acid, alkaline hydrolysis, oxidation, photo degradation, dry, and wet heat treatment—as prescribed by ICH. The degradation products were well resolved from the pure drug with significantly different R f values. The method was validated for precision, accuracy, specificity, ruggedness, and robustness.