Developing New Drug Antagonist for Alpha Adrenergic Receptors for Hypertension Diseases

Alpha-adrenergic receptors play a vital role in the regulation of blood pressure(BP). Hypertension referred as blood pressure above the normal range. hyper tension can cause severe complications such as stroke, coronary heart disease and kidney failure. Phentolamine is a potential antagonist for a. Alpha-adrenergic receptor. New phentolamine derivatives will be developed through FEP (Free Energy perturbation) methods. AMBER Force fields will apply for energy Calculation. Molecular modeling includes energy minimization, molecular dynamics, mounte-carlo simulations and QSAR properties will be performed for all phentolamine analogs. The interactions studies between alpha - adrenergic Receptor and Phentolamine analogs in solvent mode and protein complex mode will be performed. The best antagonist for alpha-Adrenergic Receptor will be identified

Novel Advent For Add-On Security By Magic Square Intrication

The efficiency of a cryptographic algorithm is based on its time taken for encryption / decryption and the way it produces diverse cipher text from a clear text. The RSA, the extensively used public key algorithm and other public key algorithms may not guarantee that the cipher text is copiously secured. As an alternative approach to handling ASCII characters in the cryptosystems, a magic square implementation is deliberated of in this work. It attempts to augment the efficiency by providing add-on security to the cryptosystem. This approach will boost the security due to its complexity in encryption because it deals with the magic square. Here, encryption / decryption is based on numerals generated by magic square rather than ASCII values. In this, we add the ASCII value and the numeral in the consequent magic square. Because to encrypt the plaintext characters, their ASCII values are taken and if a character occurs in numerous places in a plaintext there is a possibility of same cipher text is produced. To surmount the problem, this paper attempts to develop a technique in which a constant is added for the recurring character

A Novel Approach for Management Zone Delineation by Classifying Spatial Multivariate Data and Analyzing Maps of Crop Yield

Precision farming has been playing a distinguished role over last few years. It encompasses the techniques of Data Mining and Information Technology into agricultural process. The acute task in classic agriculture is fertilization, which makes minerals available for crops. Site specific methods result in imbalanced management within fields which affects the crop yield. Treating the whole field as uniform area is merely heedless as it forces the farmers to use costly resources like fertilizers, pesticides etc., at greater expenses. As the field is heterogeneous, the critical task is to identify which part of the field should be considered and the percentage of fertilizer or pesticide required. In order to increase the yield productivity, concept of Management Zone Delineation (MZD) has to be adopted, which divides the agricultural field into homogeneous subfields, or zones based on the soil parameters. Precision Agriculture focuses on the utilization of Management zones (MZs). In this paper, we have collected huge data of Davanagere agricultural jurisdiction during standard farming operations which reflects the heterogeneity of agricultural field. We base our work on a new Data Mining technique called Kriging, which interpolates soil sample values for the specific region, which in turn helps in converting heterogeneous zones to homogeneous subfields