UNDERSTANDING THE LIGHTNING DISCHARGE WITHSTAND AND BREAKDOWN CHARACTERISTICS OF NANO SiO2 MODIFIED MINERAL OIL FOR TRANSFORMER APPLICATIONS

The successful operation of electrical power system network depends on the performance of insulation provided in the high voltage power transformers. Recent output of many research works confirm that the nano modified insulation system provides enhanced dielectric and thermal characteristics when compared with conventional system. Now a days nano modified mineral oils are considered as an alternative to conventional mineral oils as a dielectric insulation fluid in power transformers, leading to the improved dielectric strength of apparatus with further reduction in the size and manufacturing cost. Since distribution transformers are mainly used in outdoor applications, understanding its lightning discharge withstand and breakdown characteristics of nano modified insulating fluid is a vital issue. In this paper laboratory experimental works are performed to understand the lightning discharge performance of mineral oil along with SiO2 nanofiller at different %wt concentration such as 0.01%, 0.05% and 0.1%. Standard lightning impulse voltage of 1.2/50 µs time period with both positive and negative polarity is used in the experiments. Results illustrate that the nano modified mineral oil significantly improves the lightning impulse withstand and breakdown strength of insulation system.Â

A review on marine based nanoparticles and their potential applications

The increasing demands on nanoparticles have wide pertinent in almost all the fields. Marine ecosystem has variety of living resources, which includes prokaryotes like microorganism to eukaryotic organism like higher plants and animals. The present review dealt with the application of marine organisms in nanotechnology. Our discussion mainly focused on what the marine organisms are involved in and what type of nanoparticles is synthesized, including size and, medical and medicinal applications. Based on our observation through this review, it will be a good reference document for the further research on marine ecosystem to develop drug from sea. Keywords: Nanomaterial, marine animals, mangroves, marine microbe

Occurrence of Uranium in Groundwater from Cuddalore District Tamil Nadu Aided by Geospatial and Statistical Techniques

An attempt has been made to examine uranium distribution in groundwater from Cuddalore district, Tamil Nadu, India. Groundwater occurs under porous sedimentary, fractured, and weathered hard rock formations ranging in age from recent sediments to the oldest Archean formations. A total of 186 groundwater samples were collected during Pre- Monsoon (May) and Post-monsoon (January) and analyzed for major cations, anions, and uranium using standard procedures. Major anions and cations follow the order Cl- >H4SiO4>HCO3- >NO3- > Na+> Ca2+> Mg2+>K+>SO42- > F-> PO43- irrespective of seasons. Uranium in groundwater ranges from 0.1 micro gram per liter (µg/l ) to 24.67 µg/l with average 1.82 µg/l. The spatial representation maps isolated areas of higher and lower uranium and statistical analysis inferred uranium sources to the groundwater environment

An Efficient Comparative Analysis of CNN-based Image Classification in the Jupyter Tool Using Multi-Stage Techniques

The main process of this image classification with a convolution neural network using deep learning model was performed in the programming language Python code in the Jupyter tool, mainly using the data set of IRS P-6 LISS IV from an Indian remote sensing satellite with a high resolution multi-spectral camera with around 5.8m from an 817 km altitude Delhi image. To classify the areas within the cropped image required to apply enhancement techniques, the image size was 1000 mb. To view this image file required high-end software for opening. For that, initially, ERDAS imaging software viewer was used for cropping into correct resolution pixels. based on that cropped image used for image classification with preprocessing for applying filters for enhancement. And with the convolution neural network model, required to train the sample images of the same pixels, was collected from the group of objects that were cropped. Then we needed to use image sample areas to train the model with learning rate and epoch rate to improve object detection accuracy using the Jupyter notebook tool with tensorflow and machine learning model produce the accuracy rate of 90.78%

Review of Hybrid Wind-Solar PV Technology in the Generation of Electricity

Achieving sustainability by utilizing alternative energy sources viable technological possibilities for creating sustainable energy, the sun, biomass, wind, geothermal resources, hydropower, and ocean resources are considered. Despite the fact that the total amount of energy produced by PV cells and wind turbines is still far less than that of fossil fuels, their ability to generate electricity has significantly expanded in recent years. This article provides an overview of the Solar-Wind hybrid power system, which generates electricity by combining the Sun and Wind, two renewable energy sources. Microcontrollers are widely used in the field of system management. We can maximize the utilization of those resources by employing this strategy, which takes into account the distinct production processes of each resource. Furthermore, it increases dependability and decreases reliance on any single input. This hybrid solar-wind power generation system is suitable for both industrial and residential applications

Investigations on the age, growth and mortality parameters of Kawakawa, Euthynnus affinis (Cantor, 1849) from the North west coast of India

Kawakawa, Euthynnus affinis contributes to the tune of 35,466 tonnes forming 1% to the total marine fish landings of India. Investigations on growth and mortality were of this species carried out based on the length frequency data during 2008-2012. The length-weight relationship for the pooled samples were derived for intercept a=0.0286, slope b=2.857 and coefficient of determination r2=0.917. The values obtained for growth parameters of L∞ was 67.86 cm, for growth coefficient (K) 0.70 and for to -0.26y-1. The natural, total and fishing mortalities recorded as 0.86, 1.48 and 0.62 y-1,respectively. The exploitation ratio (F/Z) was observed as 0.42. The M/K ratio was estimated at 1.23. The average fork length of 46 cm and weight of 2024 g were estimated in the samples collected. The length at the end of 1st year to 5th year was observed to be 33, 52, 64, 70 and 75 cm, respectively. The fishing mortality derived in this study is more than the optimum and limit value indicated the sign of overexploitation

Metabolic Disorder Dysfunction in Parkinson’s Disease: Bioenergetics, Redox Homeostasis and Central Carbon Metabolism

The loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc) and the accumulation of protein inclusions (Lewy bodies) are the pathological hallmarks of Parkinson’s disease (PD). PD is triggered by genetic alterations, environmental/occupational exposures and aging. However, the exact molecular mechanisms linking these PD risk factors to neuronal dysfunction are still unclear. Alterations in redox homeostasis and bioenergetics (energy failure) are thought to be central components of neurodegeneration that contribute to the impairment of important homeostatic processes in dopaminergic cells such as protein quality control mechanisms, neurotransmitter release/metabolism, axonal transport of vesicles and cell survival. Importantly, both bioenergetics and redox homeostasis are coupled to neuro-glial central carbon metabolism. We and others have recently established a link between the alterations in central carbon metabolism induced by PD risk factors, redox homeostasis and bioenergetics and their contribution to the survival/death of dopaminergic cells. In this review, we focus on the link between metabolic dysfunction, energy failure and redox imbalance in PD, making an emphasis in the contribution of central carbon (glucose) metabolism. The evidence summarized here strongly supports the consideration of PD as a disorder of cell metabolism

A glossy mutant in onion (Allium cepa L.) shows decreased expression of wax biosynthesis genes

Cuticular wax is a characteristic feature of land plants that provides protection against both biotic and abiotic stresses. In this study, a glossy mutant lacking an epicuticular wax layer was identified in the γ-irradiated M2 mutant population of the onion cultivar Bhima Super. The inheritance of the mutant’s glossy phenotype was determined to be recessive and single locus. Scanning electron microscopy analysis showed poor accumulation of wax crystals in the glossy mutant, concentrated near the stomata. The plant height, number of leaves per plant, and stomatal parameters of the mutant were similar to the wild-type. RNA-seq was used to comprehend the expression variations of waxy cuticle-related genes in the glossy mutant and its wild-type waxy cultivars. Differential gene expression analysis of the RNA-seq data revealed that the genes involved in wax biosynthesis, such as AcCER1, AcCER26, AcMAH1, and AcWSD1, were downregulated by 2.72, 1.74, 2.59 and 2.12-fold, respectively, in the glossy mutant respectively. The expression patterns of these four unigenes were validated using semi-quantitative RT-PCR. The glossy mutant displayed a substantial 3.5-fold reduction in cuticular wax load compared to the wild-type due to the significant downregulation of these wax biosynthesis genes. These findings represent early advancements in understanding the molecular mechanisms of wax biosynthesis in onions. Furthermore, they provide a foundation for utilizing the glossy mutant trait in breeding programmes to enhance stress and pest resilience

Assessment of genetic variability and diversity analysis in medium duration rice accessions

A total of 64 medium duration rice accessions were evaluated for their genetic variability and genetic divergence during Rabi season 2020 at Pandit Jawaharlal Nehru College of Agriculture and Research Institute, Karaikal. Analysis of variance revealed significant differences for all the traits considered for the study. The traits spikelets per panicle and filled grains per panicle recorded high GCV as well as PCV thereby indicating that these traits would be improved effectively through selection. Other yield component traits viz., plant height, productive tillers per plant, spikelets per panicle, filled grains per panicle, fertility per cent, grain weight and single plant yield revealed high heritability coupled with high genetic advance, indicating that simple selection could be effective for improving these characters. The D2 values and hierarchical clustering analysis grouped the 64 germplasm into seven clusters. In both the clustering methods, the genotype Gold 44 was grouped under separate clusters indicating that, this is a diverse genotype among all the genotypes taken for study. Further, genotype AD 16124 was grouped under the same cluster in both the clustering methods with the highest cluster mean for grain yield per plant. Hence, this genotype could be efficiently utilized for the yield improvement programme in rice