The penetration of technology & media advances into football has improved referees’ choices on contestable objectives. This paper analyzes the reception of Video Assistant Referees (VAR) and Goal Line Technology (GLT), and how the understanding of the correspondence between arbitrators influences the result of the games. In this study, we take a few examples of use cases where VAR has given major yet confusing decisions that drastically affected the match’s outcome. This investigation is planned for investigating the informative frame of reference for off-field and on-field referees. Decision-making is a critical aspect of soccer. As small as a third division match to as big as a world cup final, one wrong decision on the part of the on-field referee can change the match’s outcome. Therefore, this exploration attempts to build up whether the dissemination of computerized media innovation into football administering has to ban human mistakes and goofs imagined in simple pitch and officials, subsequently setting the glue for negligible blunders in the present-day period advanced and digital officiating.

Aim: To study the comparative molecular interactions of Quercetin and Imatinib with the active sites of Breakpoint Cluster Region (BCR)-Abelson (ABL) fusion protein using molecular docking analysis for the selective anti-Chronic myeloid leukemia (CML) activity. Materials and Methods: In this study, Group 1 is binding affinity of Imatinib with BCR-ABL Fusion Protein and Group 2 is binding affinity of Quercetin with BCR-ABL Fusion Protein. The sample size was calculated with pretest power 80%. The sample size per group is 10 and total sample size is 20. The protein structure of BCR-ABL fusion protein was collected from the protein data bank (PDB) website and the ligand structures were collected from the NCBI-PUBCHEM website. The binding energy (kcal/mol) was calculated using Autodock Vina Software. The non-covalent protein ligand interactions were detected using protein–ligand interaction profiler (PLIP) webserver. Results: The mean binding affinity of Imatinib (-10.34 kcal/mol) was significantly (p=<0.001, p<0.001, 2-tailed t-test) higher than Quercetin (-8.8 kcal/mol) towards the active sites of BCR-ABL fusion protein. Conclusion: In Spite of lesser binding affinity of Quercetin compared to Imatinib, Quercetin can make strong hydrogen bond and hydrophobic interactions with the aminoacid residues at the active sites of BCR-ABL fusion protein. It suggests that, Quercetin may bind selectively to the cells of CML and inhibit their proliferation and can act as novel Anti-CML agent.

During a pandemic, the most affected aspects are the business economy and other sectors and areas globally. This research analyses the IT sector’s condition during COVID-19 by taking a sample of four companies, analyzing the stock market and financial records of the previous few months, and predicting future stock market value to see the stock market graph. Random function and MS excel used for prediction of future stock market and records of the previous financial year to conclude status of the company with graphs. After analyzing a four-sample company, a conclusion for the sector is provided. Research analysis found most companies are stable even though they are going through certain losses because of their existing assets, fluctuating financial records, and stock market graphs. Sample companies can easily recover losses and still showing a bullish graph successfully. Even though suffering a percentage of error with the actual stock market price, it successfully portrayed the IT industry scenario in this uncertain situation. However, the magnitude of the impact has never been precisely calculated. This thesis suggests a COVID-19 impact calculation model. Assets gains in the COVID-19 timeframe are weighted means of prior COVID-19 standard yields and COVID-19-induced returns in the proposed model. The COVID-19-generated gains are negatively auto-correlated and extremely unpredictable, and they substitute the prior COVID-19 standard gains. During the COVID-19 era, the COVID-19-generated gains are unique natural gains.

Alcoholism affects both adults and children, and it is a major medical issue. A high predominance of ailment, insufficiencies, and fatalities has been associated to alcoholism. It tends to be influenced by hereditary, psychological, social, and other elements. Misuse of alcohol is a main source of non-communicable diseases and mental illnesses and its all add weight to the alcohol-related disease. With regard to alcohol-related issues, medicine and public health face a conundrum. Early detection is critical for effective analysis and management of patients, hence primary prevention should be emphasized in medical care administrations.

The purpose of this study is to determine the influence of Covid-19 on the intention to purchase online fashion clothing. A structured questionnaire was used to collect data from 231 customers in an online survey. The researchers utilised exploratory factor analysis to uncover the most important elements that influence customer behaviour while purchasing online fashion items. Multiple regression study revealed that situational variables, practical motive, and safety and precaution had a positive and substantial influence on customers’ online buy intention for fashion items. Hedonic incentive, on the other hand, had a minor impact, despite being beneficial on purpose. A structured questionnaire was shared with the respondents for data collection. The Questionnaire was floated between individuals who purchase fashion apparel online. The questions assessing the four predictors were first subjected to an exploratory factor analysis. Second, multiple regression was used to determine the influence of these variables on online purchase intentions among customers.

COVID-19 crisis has changed the way we work. Work-fromhome, which was a possibility in some sectors, has become a compulsion for all, which has affected the work-life balance of working professionals. Depending on where the employees are working, the office hours have noticeably increased by one to five hours longer as this supplementary time is spent in conferences and follow-ups, or an endeavor to improve productivity, or just being unaware of the time as there is no clear boundary that exists between work and life now. During this unprecedented time, the augmented center of attention should be towards the welfare of the employees and the acknowledgment, recognition, and acceptance of the fact that work and personal/ family needs will overlap. This paper intends to investigate the various factors impacting work-life balance during the lockdown imposed by the government in light of the coronavirus, which is spreading at a rapid pace. Key insights were obtained by conducting a factor analysis and extracting four main factors, which have been explained further below. Data was collected from 225 employees across India belonging to various sectors. The findings of this study can be a crucial contributor to organizations by taking inputs. Then this prescience will help organizations to be prepared during unforeseen events by further refining their policies to benefit their employees.

Wireless Body Area Network (WBAN) is several wearable sensor nodes with unstable sensing, storage, computation, and communication capabilities. Heart infection is an essential origin of death internationally, and early recognition is vital in avoiding the development of the infection. This article presents an Ensemble Learning (EL) method for improving the Healthcare Internet of Things (IoT) System. This approach aims to forecast the risk of heart infection. This method involves dividing the dataset into subgroups at random using a mean-based split. The data is then divided into multiple groups using a classification and regression tree. A weighted aging classifier ensemble is used to create an ensemble from the many trees used for classification and regression. It makes sure an optimal function is reached. The experimental outcomes on the datasets reached better classification accuracies that outperformed other machine learning algorithms like Artificial Neural Network, Naıve Bayes, and Support Vector Machine. The outcomes demonstrate that the risk of heart infection can be forecasted efficiently through ensemble learning.

Depending on technology is a surprisingly easy task for a person since the course of parameter change can be calculated intuitively by the consistency of the solution. However, manual parameter modification in many situations is varied. It becomes unworkable when specific parameters occur in a crisis. The model’s performance was evaluated using generalized data throughout the testing step. According to cross-validation studies, a 5-fold method might successfully hamper the overfitting problem. This paper aims to overcome this issue and create a system that changes its parameters automatically in the way humans do. This concept can be illustrated as an optimization-based iterative CT reconstruction model using a pixel-savvy regularisation term. A network of parameter-tuned policies maps an Image data patch to an output defining the position and amplitude of the patch center’s parameter is also setup. The PTPN is designed for a complete strengthening phase. It can be proved that replicated ct images achieve comparable quality or good performance to those reconstructed with electronic parameters under the guidance of the professional PTPN.

Diabetes Mellitus is one of the most serious health problem that arise from poor sleep quality. Objectives of the study were to assess the level of sleep quality and glycemic control among patients with diabetes mellitus. To establish a relationship between sleep quality and glycemic control among patients with diabetes mellitus and to associate the level of sleep quality and glycemic control among patients with their selected demographic variables.A descriptive study was conducted among 100 diabetic patients at SMCH, Thandalam Chennai. Subjects were selected using purposive sampling. Data were collected by using Tool 1: Structured Questionnaire and Tool 2: Pittsburgh Sleep Quality Index and Tool 3: Recent HbA1C Scoring. The result of the study found that there is a borderline significance in the mean score of HbA1c was 6.02±0.92 and the mean score of sleep quality was 9.32±3.68. The calculated Karl Pearson’s Correlation value of r = 0.416 shows a moderate positive correlation between HbA1c and sleep quality which was found to be statistically significant at p<0.001 level. This clearly infers that when HbA1c increases among increases then the sleep disturbances among patients with diabetes mellitus also increases.

Aim- The current study sought to assess the fracture strength of thin monolithic zirconia crowns of varying thickness and finish line configuration. Study design- The current study was carried out to evaluate and compare the fracture strength of monolithic zirconia crowns with chamfers and radial shoulder finish lines of 0.5, 0.8, and 1.1 mm thickness. Result- Monolithic zirconia crowns with merely 0.5 mm reduction demonstrated adequate strength for use in posterior areas. On evaluation and comparison it was observed that no statistically significant difference was found in the fracture strength of monolithic zirconia crowns with different thicknesses and finish lines was investigated. Conclusion- The 0.5 mm thickness of monolithic zirconia crowns demonstrated significant fracture resistance to withstand physiological performance, regardless of finish line type.