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By considering the current regulatory requirement for an analytical method development, a reversed phase high performance liquid chromatographic method for routine analysis of pregabalin and Methylcobalamin has been developed . The optimized method was achieved using unisol C-18 (3 μm, 4.6 ×150 mm) column with mobile phase consisting of mixture of water and methanol (40: 60 v/v) with a flow rate of 0.6ml/min at 210 nm. The optimized method was then validated according to the ICH guidelines. The developed method was found linear over the concentration range of 50-150 μg/ml for pregabalin and 5-15 μg/ml for Methylcobalamin and the detection and quantitation limit was found to be 2.69μg/ml ,8.18 μg/ml for pregabalin and 1.74μg/ml, 5.27μg/ml for Methylcobalamin respectively. Therefore, a sensitive, robust, accurate method was developed with high degree of practical utility.

Garbage management is essential in today’s society. Due to the increase in population, the waste generation is getting doubled day by day. Therefore, it is imperative that we examine the process of garbage collection, segregation, and automation for better management of the garbage materials. This project provides a solution that can detect, identify and segregate waste objects into Bio-Degradable and Non-Biodegradable garbage classification. This work is an integration of machine learning concepts using. Numbers of ways have been proposed to solve this challenge; a new concept uses a conveyor belt and a camera module that can sort garbage objects at the initial stage of segregation. The segregating module is DC geared motors sorts these garbage objects into two different categories, namely Bio-Degradable and Non-Biodegradable garbage. Our main aim is to segregate the collected garbage objects into two categories of bio-degradable wastes and non-biodegradable wastes. So, when the unwanted garbage is discarded in two different dustbins at the source itself which in turn allows effective treatment and disposal. So, Efficient garbage management administration makes the garbage collection productive.

In modern times, disposal of garbage has turn out a huge cause for concern in the world. A comprehensive amount of waste that is generated is not disposed properly and in turn have a harmful effect on the habitat. The most commonly used method for disposal of the waste is by random and unscientifically dumping garbage at landfill sites, which is creating problems to public health and the environment. Garbage disposal is an emerging environmental and public health issue. Waste production has been doubled over a period of past 20 years and the efficiency in manual segregation is very low. Thus, a practicable answer to this problem is by segregating waste at the root stage. The paper briefs to classify the waste into basic categories that is bio-degradable and non – biodegradable wastes. The wastes are detected and dropped into the respective bins allocated to each category where these classified wastes can be taken ahead for efficient recycling. The whole system is designed to get maximum efficiency of work and make our environment safer.

The brown planthopper (BPH)

DRR17A is a stable wild-abortive cytoplasmic male sterile line with medium-slender grain type. DRR17A and its maintainer line DRR17B are highly susceptible to two of the major rice diseases, bacterial blight (BB) and blast. To improve DRR17B for resistance against BB and blast, we have introgressed a major dominant gene each conferring resistance against BB (Xa21) and blast (Pi54) into the maintainer line through marker-assisted backcross breeding using RP-Bio-Patho-2 (a near-isogenic line of Samba Mahsuri possessing Xa21 and Pi54) as the donor parent. PCR-based molecular markers tightly linked to Xa21 and Pi54 were used for foreground selection of the resistance plants at each backcross generation, while molecular markers tightly linked to the major fertility restorer genes, Rf3 and Rf4, were used for negative selection (i.e. selection of plants possessing non-fertility-restoring alleles at the two loci) at BC1 generation. After foreground selection for the target genes at each backcross generation, the ‘positive’ plants were screened with parental polymorphic markers for identifying backcross plants possessing maximum recovery of DRR17B genome. Marker-assisted backcrossing was continued till BC3 generation, and a single BC3F1 plant possessing the target genes with ~94 % recovery of recurrent parent genome was identified and selfed to generate BC3F2s. A total of six homozygous BC3F2 plants were identified and advanced. At BC3F5, six promising, stable, backcross-derived lines possessing high level of resistance against BB and blast, high yield, short plant stature, fine-grain type, have been identified; their maintenance ability and heterotic potential validated through test crosses and these lines are being converted to CMS lines through marker-assisted breeding.