Revolutionizing Endovascular Treatment: The Transformative Role of Artificial Intelligence in Healthcare

Artificial Intelligence (AI) has emerged as a revolutionary force in various industries, transforming processes and enhancing outcomes through its advanced capabilities. In the realm of healthcare, AI is making significant strides, particularly in the field of endovascular treatment, a minimally invasive medical procedure conducted within blood vessels. This editorial explores the multifaceted applications of AI in endovascular treatment, shedding light on its pivotal role in improving patient care and procedural efficiency

DNA Computing: A Paradigm Shift from Silicon to Carbon

DNA computing, a fascinating frontier in the realm of biological computing, marks a paradigm shift from traditional silicon-based processing to the innovative realm of carbon-based computation. Rooted in the principles of molecular biology, DNA computing harnesses the inherent parallelism of biological systems, offering a revolutionary approach to data storage, processing, and solving complex problems

Review on DNA Cryptography

Cryptography is the science that secures data and communication over the network by applying mathematics and logic to design strong encryption methods. In the modern era of e-business and e-commerce the protection of confidentiality, integrity and availability (CIA triad) of stored information as well as of transmitted data is very crucial. DNA molecules, having the capacity to store, process and transmit information, inspires the idea of DNA cryptography. This combination of the chemical characteristics of biological DNA sequences and classical cryptography ensures the non-vulnerable transmission of data. In this paper we have reviewed the present state of art of DNA cryptography.Comment: 31 pages, 12 figures, 6 table

DNA Linear Block Codes: Generation, Error-detection and Error-correction of DNA Codeword

In modern age, the increasing complexity of computation and communication technology is leading us towards the necessity of new paradigm. As a result, unconventional approach like DNA coding theory is gaining considerable attention. The storage capacity, information processing and transmission properties of DNA molecules stimulate the notion of DNA coding theory as well as DNA cryptography. In this paper we generate DNA codeword using DNA (n, k) linear block codes which ensures the secure transmission of information. In the proposed code design strategy DNA-based XOR operation (DNAX) is applied for effective construction of DNA codewords which are quadruples generated over the set of alphabets {A,T,G,C}. By worked out examples we explain the use of generator matrix and parity check matrix in encryption and decryption of coded data in the form of short single stranded DNA sequences. The newly developed technique is capable of detecting as well as correcting error in transmission of DNA codewords from sender to the intended receiver.Comment: 23 pages, 1 figure, 5 table

CLASSIFICATION OF SODAR DATA BY DNA COMPUTING

In this paper, we propose a wet lab algorithm for classification of SODAR data by DNA computing. The concept of DNA computing is essentially exploited to generate the classifier algorithm in the wet lab. The classifier is based on a new concept of similarity-based fuzzy reasoning suitable for wet lab implementation. This new concept of similarity-based fuzzy reasoning is different from conventional approach to fuzzy reasoning based on similarity measure and also replaces the logical aspect of classical fuzzy reasoning by DNA chemistry. Thus, we add a new dimension to the existing forms of fuzzy reasoning by bringing it down to nanoscale. We exploit the concept of massive parallelism of DNA computing by designing this new classifier in the wet lab. This newly designed classifier is very much generalized in nature and apart from SODAR data, this methodology can be applied to other types of data also. To achieve our goal we first fuzzify the given SODAR data in a form of synthetic DNA sequence which is called fuzzy DNA and which handles the vague concept of human reasoning. In the present approach, we can avoid the tedious choice of a suitable implication operator (for a particular operation) necessary for the classical approach to fuzzy reasoning based on fuzzy logic. We adopt the basic notion of DNA computing based on standard DNA operations. We consider double stranded DNA sequences, whereas, most of the existing models of DNA computation are based on single stranded DNA sequences. In the present model, we consider double stranded DNA sequences with a specific aim of measuring similarity between two DNA sequences. Such similarity measure is essential for designing the classifier in the wet lab. Note that, we have developed a completely new measure of similarity based on base pair difference which is absolutely different from the existing measure of similarity and which is very much suitable for expert system approach to classifier design, using DNA computing. In the present model of DNA computing, the end result of the wet lab algorithm produces multi valued status which can be linguistically interpreted to match the perception of an expert.Fuzzy set, fuzzy logic, fuzzy reasoning, applicable form of fuzzy reasoning, SODAR data classification, fuzzy DNA, DNA computing