Informatics Publishing Limited

J. Karthick ¹, P. K. Praveen Kumar ¹

Affiliations
1 Department of Biotechnology, Sri Venkateswara College of Engineering, Sriperumbudur, IN

Abstract

The Present Study is to analyse the targeted delivery of Ursodiol, a drug used in the treatment of Primary Sclerosing Cholangitis (PSC) using Lipid Bilayer Nano-Particles or Solid Lipid Nano Particles(SLNPs) which is taken for insilico binding studies with various 4 different liver receptors. 3 Solid Lipid Nano Particles are chosen and Binding Efficiency of the Drug with Solid Lipid Nano Particles are Studied Using DFT Analysis and FEM Analysis. It was seen that the complete drug binding is seen in Small Unilamellar Vessicle (SUV). Chosen Liver Receptors with Ursodiol of the SUV are checked for binding studies using AutoDock 4. The Study revealed that Liver X Receptor has a greater efficiency in binding with the Solid Lipid Nano Particles.

Keywords

Ursodiol, Solid Lipid Nano Particles, Small Unilamellar Vessicle, Liver Receptors.

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J. Karthick ¹, P. K. Praveen Kumar ¹, P. L. Sujatha Loganathan ²

Affiliations
1 Department of Biotechnology, Sri Venkateswara College of Engineering, Sriperumbudur, Chennai, IN
2 Department of Bioinformatics and ARIS Cell, Madras Veterinary College, Chennai, IN

Abstract

Liver diseases are the second most predominant diseases next to diabetes. Treatment of most of the liver diseases involves liver transplantation, which is not feasible due to lack of sufficient donors. Most of the drugs prescribed are random and doesn't involve proper action in the patient. Hence targeted delivery of the drug is the most viable and affordable solution for treating liver diseases. Despite many available carriers like viral vectors, metallic vectors etc, liposomes are the most suitable drug carrier molecules and they are more advantageous than other materials. Targeted delivery experiments involve much tedious experimental procedures and complex biological pathway study. Developing and analysing these nano scale compounds are also much difficult and hence for the ease of work, tools of Bioinformatics are used to analyse and interpret the results. Hence in-Silico analysis are commonly used for analysing their pathway before carrying out the in-Vitro and in-Vivo experiments. This review article emphasis on the various procedures and software used in targeted delivery experiments.

Keywords

Drug Delivery, Liposomes, Nanoparticles, System Biology, Computational Biology.

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J. Karthick ¹, Mohemmed Yousuf ¹

Affiliations
1 Department of Computer Science and Engineering, MVJ College of Engineering, Bangalore –560067, Karnataka, IN

Abstract

Objective: The main objective of the paper is to evaluate the performance level of an employee using Predictive Analytics. Human capital is a major concern for an organization as they want to hire most qualified one who will perform well. This human resource can be used to find the future of the organization. Method: The advanced branch of data engineering is Predictive Analytics is used for this purpose. Generally, these analytics predicts some occurrence or probability based on data. The future occurrence or events, were predicted by analyzing the historical data. Finding: With the help of the rules generated by the decision tree classifier, performance of an employee were found by testing with the attributes. This paper concentrates on gathering information about the employees from the organizational database, based on the analysis of historical data generates an decision tree, validating the attributes of the employee with decision tree. With the latest prediction algorithm, we will predict employees’ performance more efficiently than the existing system.

Keywords

Data Mining, Decision Tree, Employee Performance, Prediction, Regression.

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J. Karthick ¹, K. Suguna ¹, P. N. Raghunath ¹

Affiliations
1 Department of Civil and Structural Engineering, Annamalai University, Chidambaram - 608002, Tamil Nadu, IN

Abstract

Objectives: An attempt has been made to suggest regression model for evaluating concrete beams with externally bonded hybrid FRP reinforcement using OriginPro-8.5 software. Methods: Fourteen beam specimens were subjected to monotonic and cyclic loading. The mechanical and geometrical properties of constituent materials such as thickness, tensile strength and elasticity modulus of FRP laminates, and characteristic strength of concrete and characteristic strength of steel were considered as independent variables. The performance parameters such as strength, deformation, ductility, crack history and number of cycles were considered as dependent variables. Findings: After conducting the multivariate linear regression analysis, a fitness of 0.192 to 0.850 and a ischolar_main mean square error of 0.201 to 8.311 were observed while predicting the performance parameters of test beams under static loading condition. A fitness of 0.477 and a ischolar_main mean square error of 1.702 were observed while evaluating the test beam specimens under cyclic loading condition. This observation clearly shows the validity of the proposed regression equations for evaluating the test beam specimens under monotonic and cyclic loading. The predicted results and the test results were compared through scatter plots. The predicted results have also been validated with other researcher’s experimental data. Applications: By using this regression equation, the performance of the both unstrengthened and strengthened beams can be assessed without any experimental work.

Keywords

GFRP; hybrid FRP; linear regression; strengthening.

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