Membrane technology has revolutionized the dairy sector. Different types of membranes are used in the industry for various purposes like extending the shelf life of milk without exposure to heat treatment, standardization of the major components of milk for tailoring new products as well increasing yield and quality of the dairy products, and concentrating, fractionation and purification of milk components especially valuable milk proteins in their natural state. In the cheese industry, membranes increase the yield and quality of cheese and control the whey volume, by concentrating the cheese milk. With the advancement of newer technology in membrane processes, it is possible to recover growth factor from whey. With the introduction of superior quality membranes as well as newer technology, the major limitation of membranes, fouling or blockage has been overcome to a greater extent.

This study focuses on understanding the growth and control of nanostructures using reverse micelles. It has been earlier realized that parameters like surfactant, cosurfactant, and aqueous content influence the size and shape of the nanostructures obtained using reverse micelles. However, a concerted effort to understand the role of these factors on the growth of a specific nanomaterial is missing. In this study we have focused on one nanomaterial (copper oxalate monohydrate) and determined how the above-mentioned factors control the size, shape, aspect ratio, and growth of these nanostructures. Our results show that cationic surfactants (CTAB, TTAB, and CPB) favor the formation of nanorods of copper oxalate. The aspect ratio of these rods could be controlled to obtain nanocubes (approximately 80-100 nm) and nanoparticles (approximately 8-10 nm) in the CTAB system using longer chain cosurfactants like 1-octanol and 1-decanol, respectively. Nanocubes of approximately 50-60 and approximately 60-80 nm were obtained using nonionic surfactants Triton X-100 and Tergitol, respectively. The size of the nanostructures could also be controlled by varying the molar ratio of water to surfactant (W0) by using a nonionic (Triton X-100)-based reverse micellar system. The study espouses the versatility of the microemulsion method to realize a variety of nanostructures of copper oxalate monohydrate. Our results will be of use in extending these ideas to other nanomaterials.

No abstract

Abstract. Remote sensing and hydrological models are one of the foremost tools for rapid and comprehensive study of flood hazards and disasters in any parts of the world. Current study is focused on severe 2018 Kerala flood, and is done using various remote sensing data, geospatial tools and combination of hydrological/hydrodynamic/topographical models. Flood mapping is done with pre and post floods remote sensing datasets. For pre-Flood analysis, Normalized Difference Water Index (NDWI) map was prepared on Google Earth Engine (GEE), using Sentinel-2 images for the period of Feb. 2017 to identify permanent water bodies. For post-Flood analysis, GEE was used to download the pre-processed and thermal noise removed Sentinel-1 SAR image for Aug. 9, 2018, Aug. 14 and Aug. 21, 2018 and flood maps were generated using this data. In addition to SAR data, probable flood inundation areas using topography-based flood inundation tool HAND (Height Above Nearest Drainage tool) was also utilized. Hydrological simulation was carried out for all 12 major river sub-basins of Kerala, where floods are reported. Indian Meteorological Department-Global Precipitation Measurement (IMD-GPM) gridded daily data is used as input meteorological data for hydrological simulations. The hydrological simulations results were verified using published Central Water Commission (CWC) reports and reservoirs data for India-WRIS. The hydrodynamic simulation was also performed for simulating the Idukki dam release data and flood condition in downstream areas. Overall, an integrated study and developed approach can be utilized by state and central water and disaster management agencies to develop flood early warning systems.

No abstract

No abstract

No abstract

No abstract