Volume 9 | Issue 8 |

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Education, Reflection, Enlightenment, Innovative practices

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Creative Commons Attribution 4.0 and The Open Definition

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The purpose of this study is to understand the factors influencing the consumer attitude about green products. From this research it is found that attitude and personal norms are positively influencing consumer purchase intention and attitude towards green products. This study helps the marketers to design strategies for sustaining in the green products. The structured questionnaire was used collect primary data and analyzed using software package. This study aims to investigate the effect of demographic factors towards consumer attitude about green products. A total of 150 completed questionnaires were collected via convenience sampling from customers in Tirupur City. Eight demographic variables were used in this study including gender, age, educational qualification, employment status, monthly income, marital status, number of family members and type of family. The findings of the present study showed that the most used statistical techniques were Descriptive Analysis and Chi-Square Test. Based on the findings of the present study, several environmental and non-environmental predictors of green marketing strategies have been identified. The present study has also provided directions for future research on consumer attitude.

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Creative Commons Attribution 4.0 and The Open Definition

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Mandna is an excellent example of rajasthani traditional folk art. This artform has been preserved especially by rural women from centuries. This art uses geometrical forms of various types i.e circle, triangle etc. This artform transpires aesthetic beauty, celebration of festivals and religious traditions.

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Creative Commons Attribution 4.0 and The Open Definition

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rajasthan, mandna, folk art, traditions

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Creative Commons Attribution 4.0 and The Open Definition

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VYANGY - EK KALATMAK ABHIVYAKTI

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VYANGY - EK KALATMAK ABHIVYAKTI

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Abstract: Background: Stomal recurrence means a recurrence experienced by patients with laryngeal carcinoma after total laryngectomy with a high mortality rate. It is essential to identify the risk factors to predict stomal recurrence. However, factors contributing to stomal recurrence indicate controversial results. Tumor expansion, thyroid nodules, and free margins become the risk factors that are easily identified. The objective: This study aims to describe the correlation between tumor expansion, thyroid nodules, and free margins with stomal recurrence after total laryngectomy. Methods: This study applied an analytical observational study with retrospective cohort studies by employing secondary data. The samples included patients who had experienced a total laryngectomy from January 1, 2015, to December 31, 2019, and those who met the study criteria. The samples were divided into groups of T3 and T4 tumor expansion, groups of N1 and N2+ thyroid nodules, as well as groups of positive and negative free margins. These samples were associated with the stomal recurrence and categorized into yes and no accordingly. The Chi-Square Test was employed for correlation analysis and followed by multiple logistic regression. The results were considered correlated if the P-value was less than 0.05. Results: This study obtained 92 patients with 87 males and 5 females. The analysis of the correlation between tumor expansion and stomal recurrence suggested a P-value of 0.770, which was greater than 0.05. Meanwhile, the correlation between thyroid nodules and free margins with stomal recurrence indicated a P-value of 0.068 and 0.147, greater than 0.05. Conclusion: There was no significant correlation between tumor expansion, thyroid nodules, and free margins with stomal recurrence after a total laryngectomy.

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Creative Commons Attribution 4.0 and The Open Definition

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total laryngectomy, tumor expansion, thyroid nodules, free margin, stomal recurrence.

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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Stress, Coping, Student, Nursing

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Creative Commons Attribution 4.0 and The Open Definition

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Aim: The purpose of the present experimental study was to find out the best walking intervention protocol which would have significant effect on health related physical fitness of the middle aged people. Methodology: Total 32 subjects have been selected purposively and divided randomly in equal numbers in four groups. Three experimental groups namely Experimental Group 1 (EG -1), Experimental Group 2 (EG -2), and Experimental Group 3 (EG -3), have gone through three different walking protocol for 12 weeks designed with different intensity and volume of walking; whereas the Control Group (CG) did not get any training. Three components of health related physical fitness namely cardio-respiratory endurance, muscular strength and endurance and body fat percentage has been tested through 12 Minute walk/run, one minute bent knee sit ups and skinfold measurement respectively. ANCOVA has been applied to find out the differences among the groups at 0.05 level of significance. LSD test has been applied to find out the best walking protocol. Result & Conclusion: The statistical findings of mean score of pre and post test mean scores have revealed the fact that all the three walking protocol has significantly improved the selected health related physical fitness components. The walking protocol III has been proved to be best protocol may be because of its gradual increase of intensity of speed with fixed distance covered in lesser duration after every four weeks of training.

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Module, Intervention, Protocol, Health-related fitness.

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ABSTRACT: Over 2.52Cr covid-19 cases in India. Using data and algorithm route block rapid progress of covid-19.AI & ML to solve real world problem like the corona virus outbreal.AI used powerful complex algorithm with them process data which them immolated human cognation to interpretation and compression of complicated medical and health care data for any artificial intelligence, need to be big data needed. This paper mostly focuses on how to manage spread of infection using Artificial Intelligence. Also focuses on the topic and the challenges a developing country such as India faces and overcome. The condition is troubling and new scientific, environmental and infrastructure needs to play a crucial role in removing this important problem globally (including India). It focused in this report on how India, a developing country is trying to stop corona spreading, and how artificial intelligence (AI) plays an essential role in controlling and monitoring the disease.

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Artificial Intelligence(AI), Data Science, PCR, Drone, Aarogya setu App, Robert,RT-PCR,Mylab ,Google AI

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The COVID-19 pandemic has led to the dramatic destruction of human life worldwide and presents an unprecedented hurdle to public health, livelyhood and the world of work. The social and economical disruption caused by the pandemic is devastating. The outbreak first appeared in to spotlight in December 2019 in Wuhan, China. This was declared as a pandemic by the World Health Organization on 11th March 2020. This article analyses how people react to a pandemic outbreak, how much they are aware of the disease and its symptoms, what preventive measures they are taking, whether people are following government guidelines, etc. The experiments have been conducted on the collected data related to COVID-19 tweets from all over the world. This study was conducted to understand how people from different infected countries cope with the situation

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nlp, sentiment analysis,

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Creative Commons Attribution 4.0 and The Open Definition

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Neural networks have become increasingly popular for the task of language modeling. Whereas feed-forward networks only exploit a fixed context length to predict the next word of a sequence, conceptually, standard recurrent neural networks can take into account all of the predecessor words. On the other hand, it is well known that recurrent networks are difficult to train and therefore are unlikely to show the full potential of recurrent models. These problems are addressed by the Long Short-Term Memory neural network architecture. In this work, we analyze this type of network on an English and a large French language modeling task. Experiments show improvements of about 8% relative in perplexity over standard

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Creative Commons Attribution 4.0 and The Open Definition

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WORD BASED PREDICTION USING LSTM NEURAL NETWORKS FOR LANGUAGE MODELING

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Creative Commons Attribution 4.0 and The Open Definition