International Journal of Research -GRANTHAALAYAH

EFFECT OF CALCINATION TEMPERATURE VARIATION ON GREEN SYNTHESIS OF CADMIUM SULFIDE FOR CIPROFLOXACIN PHOTODEGRADATION

Aminatul Haq Faizah, Gunawan, Khabibi, Roni Adi Wijaya — Sun, 30 Jun 2024 00:00:00 +0000

The green synthesis method has been successfully carried out to CdS with tea leaf extract and calcination temperature variation for the application of photocatalytic degradation of ciprofloxacin antibiotic. Variations in calcination at temperatures of 500, 600, and 700 ℃ were carried out to determine the effect of temperature on morphology and elemental composition, crystal structure and size, functional groups, and band gap energy by SEM-EDX, XRD, FTIR, and UV-DRS Spectrophotometer. The SEM-EDX image of the synthesized CdS is smooth and spherical and there is agglomeration with an even distribution of elements. The results of XRD and FTIR characterization showed the CdS peaks. The size of the CdS crystal increased with increasing temperature, namely CdS-600 at 64 nm and CdS-700 at 81.58 nm. The band gap energy value is influenced by the calcination temperature during synthesis with the band gap energy values of CdS-600 2.3 eV and CdS-700 2.38 eV. The percentage of CdS effectiveness with variations in calcination temperature in ciprofloxacin photodegradation is CdS-500 at 32.18%, CdS-600 at 48.72%, and CdS-700 at 8.73%. The optimum condition of CdS synthesis in degrading ciprofloxacin by photocatalytic process occurs at a temperature of 600℃ with a photocatalytic irradiation time under visible light for 120 minutes, a CdS mass of 10 mg, and an initial concentration of ciprofloxacin of 25 ppm. This result demonstrates the potential of an environmentally friendly method that can be applied in wastewater treatment.

KNOWLEDGE AND ASSOCIATED FACTORS FOR USE OF CONTRACEPTIVES AMONG MARRIED WOMEN OF WEST BENGAL, INDIA

Moumita Mondal — Sun, 30 Jun 2024 00:00:00 +0000

Use of contraceptive and family planning methods are help in fertility pattern and also helps to improve reproductive health. It is important to have proper knowledge about the contraceptives and identified the associated factor for the use of contraceptives by the married women. A study was conducted to assess the knowledge and the associated factor for the use of contraceptives among married women in the selected rural community of West Bengal. Non-probability purposive technique was used to collect data from 162 married women residing at the selected rural community. It was collected by using structured knowledge questionnaire and structured questionnaire for identify associated factor. The study revealed that 16.67% married women’s had poor knowledge, 12.34% married women’s had good knowledge. It observed that 48.76% married women belonged to the married life of 5-10 years. 72.22 % married women got contraceptives from Subcenter.38.89 % married women used Oral contraceptives pill.83.34 % married women’s were using contraceptives by couple choice.74.70 % married women’s advice taken from Health worker.42.85 % married women used Oral contraceptives pill because of Decision of couple.92.60 % women used Condoms because of because of Decision of couple.65.62% women used Injectables because of easily available .52.5 % married women used CU-T because of easily available. There was statistically significant association between knowledge of contraceptives and their demographic variables like, the religion, marital age.

PREDICTIVE ANALYSIS IN MEDICAL HEALTHCARE: A META-ANALYSIS

Sun, 30 Jun 2024 00:00:00 +0000

Predictive analytics is a subfield of advanced analytics that uses historical data along with statistical modelling, data mining, and machine learning to forecast future events. Businesses use predictive analytics to look for trends in this data to pinpoint possibilities and dangers. This meta-analysis explores the landscape of predictive analysis within medical healthcare, examining methodologies, applications, challenges, and future directions. By synthesizing existing literature, this study offers insights into the effectiveness, limitations, and potential advancements in predictive analytics within the healthcare domain. This meta-analysis aims to provide a comprehensive overview of the state of predictive analysis in medical healthcare, highlighting key methodologies, applications, challenges, and future directions. To conduct this meta-analysis, a systematic approach was employed. Inclusion criteria encompassed studies focusing on predictive analysis in medical healthcare published in peer-reviewed journals. Databases such as PubMed, IEEE Xplore, and Scopus were searched using relevant keywords. Data extraction involved identifying key methodologies, applications, and challenges discussed in each study. Quality assessment was performed to ensure the reliability of included studies and minimize bias.