Clinical research is the study design intended to check the safety and efficacy of drugs through the important phases, generally conducted in human volunteers to provide safe medications that contribute to well being of humanity. Generally a effective clinical trial study follows certain guidelines issued by ICH-GCP policies. These guidelines and policies are designed for protecting the interest of subjects and obtaining valuable information about the drug in clinical trial. Many research designs are implemented to obtain scientific information about the research study since it is tedious and expensive.

The demand for the natural drugs obtained from plant source have been ever increasing due to its negligible side effects. Arjuna scientifically known as Terminalia arjuna belongs to family Combretaceae. Arjuna finds its place in many indigenous systems of medicines like Ayurveda. Cardiovascular diseases have been a major source of death world wide, since then the evolution of many drugs happened to be the cure for cardiovascular diseases. Arjuna bark is found to be one of the potential herb with maximum cardiotonic properties. Several literature reviews confirms its potentiality. The bark of Arjuna is traditionally used in many Ayurvedic formulations for its cardiotonic, styptic, febrifuge and diuretic activities. Arjuna bark is found to contain many bioactive compounds like Gylcosides, tannins, flavonoids possessing active pharmacological actions specially Hypolipidemic activities and Antioxidant activity. The main aim of the study is to focus on the clinical and experimental studies on cardiovascular activities of Arjuna with reference to its phytochemical compounds.

Understanding human emotions is one of the crucial aspects when we are to take action. Our emotions dictate our apparent behaviors. In simple words, what we feel inside can predict things about what we would do. This creates a huge opportunity for government and businesses industry to understand and predict people's behaviors. There has been some really great research done on this with high accuracy. Recently, Covid-19 vaccination process is a challenging task going on all over the world and it is necessary to explore people’s reaction over this for more effective vaccination process spread. In this paper, wetried to understand an event (Covid-19 vaccination) with a relatively simple model with decent accuracy compared to other sophisticated models. We use simple machine learning models to train and deploy it over the network. We have used KNIME Analytical Platform to design and implement our model as it provides end-to-end analytics. We have managed to get 88.67% accuracy and Cohen’s kappa 0.789 with SVM model by tuning some parameters. The model is deployed on Twitter data. This paper shows our efforts trying to make a simple model to analyze an event (Covid-19 vaccination) and understand people's emotions towards the event. The methodology involves identifying important topics (terms) and finding out the sentiment (positive, negative, neutral). This paper tries to find a low-cost solution to analyze an event and provide data-driven insights from it without involving sophisticated algorithms.

Liposomes are spherical vesicles comprises of one or more phospholipid bilayers, which are under substantial research area as drug carriers for enhancing the delivery of drugs, nutritional agents, bioactive agents and many different compounds. The majority of those clinically approved vesicles have diameters of 50–300 nm. Among several new drug delivery systems, liposomes characterize an advanced technology to deliver active molecules to the site of action and decreases undesirable side effects upgrading its in vitro and in vivo activity, as well as reducing the toxicity of the drug and enhancing the efficacy of the encapsulated drug molecule. The present review will briefly explain the characteristics, advantages, scalable techniques based on the type of produced liposomes and potential applications of liposomes in food, cosmetics and pharmaceuticals.