Volume 8 | Issue 8 |

 Abstract

Sthanika Chikitsa plays an important role in the management of many Yonivyapadas. In Ayurveda, given equal importance to Abhyantara as well as Sthanika Chikitsa. In the context of yonivyapada Chikitsa , it is mentioned that the local treatment should be done and must be followed by shodhana therapy (panchkarma).1 Sthanika Chikitsa in Streeroga includes yoni pichu, yoni dhavana, yoni dhoopan, yoni varti, yoni pooran, yoni lepana, Yoni Parishek, kshara karma and agni karma. In the present study all these local therapies are explained in brief and in simpler way.

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Ayurveda, Sthanika Chikitsa, local therapies in Streeroga, yonivyapada.

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Production of bulky silk is the need of the hour as the same is required for weft in the production of silk sarees. So far raw silk produced in charkha reeling device was used for the purpose. But due to non-availability of skilled labourers and improper working atmosphere in charkha reeling sector, alternative methods of production of bulky raw silk were thought off. In this context, introducing PVA yarn in the process of silk reeling has been developed by CSTRI by modifying the multiend reeling machine for the production of bulky void raw silk. The bivoltine cocoons along with Indian PVA yarn is used for the production of bulky silk. Using the Box and Behnken design of experiments the process variables viz., Number of cocoons, croissure length, reeling basin water temperature and reel speed have been standardized with 27 combinations of experiments. The study indicates that process variables significantly influence the reeling performance and quality of bulky void raw silk produced viz., reelability, non-broken filament length, single cocoon filament denier, raw silk percentage, average denier, cross section view of bulky void raw silk. Based on the response optimization in statistical analysis, it was observed that 20 bivoltine cocoons reeled per end along with Indian PVA yarn with 6 mm croissure length, 50�C basin temperature and reel speed of 100 m/min is ideal for the production of bulky void raw silk on modified CSTRI multiend reeling machine. The bulky void raw silk is quite useful as weft in the production of silk sarees with unique surface characteristics.

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Bulky void raw silk, Indian PVA yarn, Croissure length, Basin temperature and Reel speed

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The present study deals with the cluster, discriminant and principal component analysis. The data for the present study was collected. Data on different morphological and seedling characters, namely tree height (m), tree diameter (cm), crown spread E-W (m), crown spread N-S (m), fruit weight (g), leaf length(cm), internodal length(cm), collar diameter (mm), number of branches per plant and leaf petiole (cm) were considered from five different districts comprising of ten seed sources. Two seed sources were considered from each district viz; Narag and Neripul from Sirmour district, Waknaghat and Sadhupul from Solan district, Sundernagar and Rewalsar from Mandi district, Mohal and Banjar from Kullu district, Basantpur and Sunni from Shimla district. Different morphological and seedling characteristics of ten seed sources were evaluated. Cluster analysis was performed and the seed sources were grouped into three clusters. Discriminant analysis was carried out to categorize the seed sources into high and low yielders. Tree diameter, Tree height and crown spread E-W are the most important characters that discriminate the two groups. Six seed sources from Mandi, Kullu and Shimla district were high yielder whereas other four seed sources were low yielder. Three principal components (PCS) were extracted out of ten which explained 34.675, 23.002, and 11.587 per cent of the total variation respectively amounting to 69.26 per cent of total variation.

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Principle component analysis, cluster analysis, discriminant analysis, Punica granatum L, Wild Pomegranate

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In this paper software-defined network (SDN) approach used to provide a set of deliberate active allocators for virtual machines (VMs) in the cloud data center (DC). Each VM request has four parameters: CPU, RAM, disk, or memory. Virtual machine allocation is one of the challenges in cloud computing environments, especially for private cloud design. In this environment, each virtual machine is assigned to a physical host based on the resources available on the host. Specifically, in the case of different performance indicators and system requirements, quantifying the performance of scheduling and allocation strategies in the cloud infrastructure for different applications and service models is a very challenging and difficult solution.

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Cloud Computing, Network, Storage, VM, IT resources.

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Nowadays, there are numerous causes for visual impairment. Eye diseases which are evident in the retina can be spotted through a systematic and structured ophthalmologic examination. Subsequent rise of the patients with these diseases due to population growth, aging made the number of Ophthalmologists a controlling factor. Glaucoma is a type of deep-rooted disease which leads to vision loss thus making it irreparable. Therefore, this disease has to be detected at an early or intermediate stage for timely treatment. Various models have been developed based on image processing or deep learning to detect Glaucoma but the systems have either been computationally complex or of insufficient accuracy. In the proposed system, structured learning which makes use of the edge information of the fundus image is used for OD detection. Finally, the convolutional neural network (CNN) is used to check if it is glaucoma affected eye or not. Thus detecting Glaucoma at early stage with system producing the increased accuracy, specificity and sensitivity.

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Convolutional Neural Network, Hough Transform, Optic Cup, Optic disk, Principal Component Analysis, Watershed Segmentation

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BIM

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Insurance industry provides enormous opportunities to the domestic as well as foreign investors. India has a great potential in this sector. This industry contributes a huge amount to country�s GDP and economic development. This remarkable development in the insurance sector attracted foreign investors in India also. This present study considered two important factors insurance density and insurance penetration. For analyzing the data last 15 years� (2004-2018) insurance density and penetration of life, non-life and industry sector have been considered and different statistical tools have been used to judge the relationship between industry insurance sector with life and non-life insurance sector, significance difference between life and non-life insurance sector, breakpoint during this study period, normality of data, heteroscedasticity and auto-correlation between the 2 models. For this researchers used Multiple Linear Regression Model, ANOVA, Bai-Perron and Residual test. This study also identified the future scope of research and constructive conclusion a feasible recommendation for growth of the industry.

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Economic Development, GDP, Insurance Density, Insurance Penetration, Investors

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The aim of the article is to provide variant calling workflow and analysis protocol for comparing results of the two using two variant calling platforms. Variant calling pipelines used here are predominantly used for calling variants in human whole exome data and whole genome data. The result of a variant calling pipeline is a set of variants( SNPS, insertions, deletions etc) present in the sequencing data. Each pipeline is capable of calling its certain intersecting and certain unique variants. The intersecting and unique variants can further be distinguished on the basis of their reference SNP ID and grouped on the basis of its annotation. The number of variants called can be humongous depending upon the size and complexity of the data. R programming packages and ubuntu command shell can be used to differentiate and analyse the variants called by each type of pipeline.

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Whole Exome Sequencing, Variant Calling, Sequencing data, R programming

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Assam, one among the eight sisters in the North-Eastern region has been playing a vital role over the years in establishing a unique identity for India in the world scenario through its contribution in the production of tea. Although Assam was annexed into the British Empire in 1826, the British had made several detailed enquiries starting from 1778 about the resources of the region. The Britishers were keen to start tea cultivation so that they could compete with China which was the major explorer of tea during that period. In this context, the colonial government found the province of Assam the most suitable region to start the commercial cultivation of tea. As the tea plantations were highly labour intensive, the issues relating to labour gained high attention during that period. In due course of time, such requirement of labourers caused migration of labourers transforming the demographic structure of the whole society of Assam. Hence, through this paper an attempt has been made to study about the recruitment of tea garden labourers and how it led to the migration of labourers in colonial Assam. The current paper is basically a qualitative one based on secondary sources. Due to the laziness for working in the tea gardens by the local Assamese people and shortage of adult population, the tea plantations had to face the problem of shortage of labour. It is in this context that the colonial state provided a patronage and the migration of the black tribals i.e. the Adivasis started. The labourers were appointed mainly through two systems, i.e. Contractor system and Sardari system both of which proved to be brutal and inhumane. Moreover, inhumane practices were used in the whole process of transportation of labourers. After they reached the tea estates, the planters did not made proper arrangements for their living. Even after 72 years of independence, there is no marked improvement in the living standard of the tea garden labourers in Assam. The government, trade unions, media as well as the elite ones within the community have to play a positive role towards uplifting the condition of these people.

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 Keywords

Assam, Community, Labour Recruitment, Migration, Tea Industry.

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Abstract: The Corporate houses and different Non-Governmental Organizations (NGOs) have been constantly engaging in combating the COVID-19 pandemic situation in India. As a part of the CSR (Corporate Social Responsibilities) activity, several Indian corporate houses like the Mc Donald�s, the Audi, the Coca-Cola, the Volkswagen and many more Indian origin companies like the Infosys Foundation, the ITC Ltd, the TCS, the Reliance Industries Ltd etc. are trying to contribute money, foods, necessary commodities to the part of society where it requires the most and trying to make people aware about basic hygiene. Other than that the companies have taken precautionary measures for most of their employees to Work from Home and other flexibilities. Along with the corporate houses, the NGOs have been untiringly trying to help migrant labourers and other affected poor people in their own way apart from governmental measures. The Ministry of Home Affairs (MHA) of India has already issued instruction to all states to utilize the services of NGOs to provide food and shelter to the migrant workers. NGOs like the MCKS Food for the Hungry Foundation, the Zomato Feeding India, the Give India, the SEEDS, the Uday Foundation, and the Khushiyaan Foundation etc. have been proving free foods or ration and shelters for migrant labourers and distributing free soaps, sanitizers & masks, medicines etc. to those who are not capable to buy. NGOs are also helping to those elderly persons who are abandoned by their families and friends. They are also collecting donations from the middle class and rich people who want to become a part of this philanthropic activity. All of them are trying to make India unite, hunger less and working with government to help those who needs it the most. The aim of this article is to focus on the role of the corporate houses and the NGOs in combating the pandemic situation caused by the COVID-19 pandemic in India.

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 Keywords

COVID-19, Corporate, NGOs, economic insecurity, livelihood

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