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Method development and validation for the simultaneous estimation of Atenolol, Hydrochlorothiazide, and Losartan potassium by using RP-HPLC

A simple, precise, rapid, and accurate RP-HPLC method was developed for the simultaneous estimation of Atenolol, Hydrochlorothiazide, and Losartan Potassium in pharmaceutical bulk drugs and tablet dosage forms. The method was developed by using HPLC (Shimadzu LC2010-CHT) with UV detector and Symmetry C18 (4.5 x 100mm, 5µm, make: waters) at 1.2 ml/min flow, column temperature – 27°C and a mixture of Methanol and water in the ratio of 65: 35 v/v as Mobile phase and diluent at 225nm wavelength, injection volume of 20µl with Isocratic flow for 10minutes run time. The accuracy studies show that % recovery for Atenolol, Hydrochlorothiazide, and Losartan Potassium at 50%, 100%, and 150% were found to be within 98-102%. Retention times were found to be 1.467 min, 2.208 min and 3.292 min for Atenolol, Hydrochlorothiazide and Losartan Potassium respectively.

Published by: Saithangpuia, Dr. Mohd. Omar

Author: Saithangpuia

Paper ID: V7I6-1191

Paper Status: published

Published: November 12, 2021

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Research Paper

Dietary fat intake pattern of adults during the COVID-19 pandemic in the City of Mumbai, India

Obesity is a growing public health issue across the globe and in India, which is increasing the risk of other chronic diseases. A high quantity of fats and an imbalance of fatty acids contribute to inflammation and faster disease progression. To study the food-based dietary fat intake patterns of adults during the COVID-19 outbreak in the city of Mumbai, India. Adults (n=103), both males and females (30-60 years of age) were selected from one of the cities in India, Mumbai, by purposive sampling, meeting the inclusion and exclusion criteria. In this survey, a KAP questionnaire was administered to understand the fat intake patterns. The data was analyzed by SPSS 26 to obtain mean and SD, frequencies, and percentages. The majority of the participants (60.2%) reported being overweight, while only 27.2% of the participants reported with normal BMI. Sixty-six percent of the participants reported ‘not checking’ the nutrition labels before purchasing any packaged food items; 32% showed to be never changing their cooking oils, and 51.5% of them reported to be re-heating the oil. The present study had the majority of the participants leading a sedentary lifestyle due to pandemic situations and nationwide lockdown. It also covers various aspects of lifestyle behaviors and eating habits, particularly of dietary fats which contribute as major risk factors to develop non-communicable diseases (NCDs).

Published by: Sweta Sharma, Dr. Monal Velangi

Author: Sweta Sharma

Paper ID: V7I6-1186

Paper Status: published

Published: November 12, 2021

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Research Paper

Expanded Polystyrene (EPS) waste: An Emerging monster in Lagos municipal solid waste

Expanded Polystyrene (EPS) also referred to as Styrofoam, is a form of plastic frequently use for food packaging. This research focuses on the generation, disposal, and negative effects of waste EPS in Lagos Municipal Solid Waste (MSW). Studies from some specific locations in five Local Government Areas (LGAs) of Lagos showed daily usage of EPS (as food package) by street food vendors and its negative impact on the environment and human life. Qualitative analysis of these locations of Lagos state has shown how several factors including the properties of EPS such as low cost, light weight, versatility, low recycle value and non biodegradability has contributed to the surge of EPS waste in Lagos state. This paper shows how street food vendors and consumers’ attitudes have contributed to defacing the aesthetic quality of Lagos state.

Published by: Aeneas U. Nebert, Oluwatoyin E. Taiwo, Jane Adamma Chukwudebelu, Nwauzor Onyinyechi Gloria, Ugo Uchechi, Ogbonna Sylvanus Orji, Okuneye Josephine Olayinka, Anozia Euphemia Chibuzor, Obuene Udoka Shedrack

Author: Aeneas U. Nebert

Paper ID: V7I6-1181

Paper Status: published

Published: November 12, 2021

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Review Paper

A critical review of alternative raw materials that can be used in the production of lyocell to make it cost competitive

The textile industry is one of the largest contributors to the looming climate crisis. Cotton, the most popular fabric, severely harms the environment because of its high water and carbon footprint. In current times, achieving sustainability is of utmost importance. Lyocell, a regenerated cellulosic fiber, is an eco-friendly alternative that offers similar benefits as cotton. However, due to the use of hardwood as a raw material in commercial production, it is twice as expensive and hence not widely adopted. This literature review evaluates the use of other raw materials that can be substituted into the conventional lyocell production process. The cost-effectiveness, time needed for implementation, and environmental impact of the method of generating the dissolving pulp and additional steps required for each alternative have been compared. After a critical evaluation, it was concluded that polycotton waste would be the most suitable alternative raw material as it will not harm the environment while also reducing pollution and offering a solution to recycle textiles and PET plastic, hence promoting sustainability and restoring the environment.

Published by: Ankita Agrawal

Author: Ankita Agrawal

Paper ID: V7I6-1170

Paper Status: published

Published: November 12, 2021

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Research Paper

Real Estate Price Prediction using Ensemble Methods

Real estate is one of the popular fields in current society. Customers should be very careful when they are buying or selling the property. There exist several reasons for increasing in the demand of land and houses. The factors like locality of house, the rooms it consists of and cost of living at that particular place plays an important role for deciding the value of house. Automated house price prediction can be done using linear regression, random forest and linear classification methods which are also termed as Ensemble methods. In the system, the data will be cleaned initially like removal and detection of extreme data from datasets and then the algorithms be applied.

Published by: Nidamaneni Rajyalakshmi, Sai Pavan Kumar Kokkiri, Chandra Shekar V., Dr. B. Srinivas Rao

Author: Nidamaneni Rajyalakshmi

Paper ID: V7I6-1168

Paper Status: published

Published: November 8, 2021

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Case Study

HR Analytics Using Tableau

1) The dataset deals with employee details like age, travel profile, department, designation, monthly income, marital status, salary hike, involvement etc in the company and also attrition rate of the employees in the company 2) We need to determine the attrition of employees in the company 3) We also determine the major causes of attrition of employees in the company and to address it.

Published by: G. Raghav

Author: G. Raghav

Paper ID: V7I6-1156

Paper Status: published

Published: November 8, 2021

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