Vignan University

About: Vignan University is a education organization based out in Guntur, Andhra Pradesh, India. It is known for research contribution in the topics: Computer science & Control theory. The organization has 1138 authors who have published 1381 publications receiving 7798 citations.

Robotics in Healthcare: An Internet of Medical Robotic Things (IoMRT) Perspective

Abstract: Robotics is one of the most advanced and emerging technologies in the field of medicine. Electronic sensors incorporated with combination of control into mechanical systems greatly enhance the performance and flexibility of systems. The robotic technology used for movement of arms were not accurate and unable to send the exact sensory feedback, exact movement, and positioning. With the advances in hardware, software, and control programming systems, extensive automation is being utilized to operate with more degree of freedom than humans under an extensive array of conditions. Currently, robotic innovations are introduced in numerous areas that specifically influence the understanding and consideration of patient care. Robotics technology in medicine is the prime focus of the healthcare services in ICUs, general rooms, and surgery room which reduces risks for patients, doctors and it is also utilized in laboratories to collect the samples followed by transportation of samples if required, analyzing, and preserving them for long-term storage. The healthcare services provided by robotics become complex and critical pertaining to sharing of information, data communication and distribution of the sensors data. The Internet of Medical Robotics Things (IoMRT) approaches incorporated robots as a “thing” and buildup connections with new communication such as Li-Fi technology and information technology on web. This chapter demonstrates the overview of robotics in performing surgeries, other healthcare services and it also emphasizes on long-term benefits for human beings using robotics with IoMT-based new communication (Li-Fi) technology. Also the limitations and future challenges associated with this technology are described in detail.

Feature and Subfeature Selection for Classification Using Correlation Coefficient and Fuzzy Model

Abstract: This article presents an analysis of data extraction for classification using correlation coefficient and fuzzy model. Several traditional methods of data extraction are used for classification that could not provide sufficient information for further step of data analysis on class. It needs refinement of features data to distinguish a class that differs from a traditional class. Thus, it proposes the feature tiny data (subfeature data) to find distinguish class from a traditional class using two methods such as correlation coefficient and fuzzy model to select features as well as subfeature for distinguishing class. In the first approach, the correlation coefficient methods with gradient descent technique are used to select features from the dataset and in the second approach, the fuzzy model with supreme of minimum value is considered to get subfeature data. As per the proposed model, some features (i.e., three features from the acoustic dataset, two features from the QCM dataset, and eight features from the audit dataset, etc.) and subfeatures (as per threshold value like 20 for acoustic; 10 for QCM, and 20 for audit, etc.) are selected based on correlation coefficient as well as fuzzy methods, respectively. Further, the probability approach is used to find the association and availability of subfeature data from the dimensional reduced database. The experimental results show the proposed framework identifies and selects both feature and subfeature data with the effectiveness of the new class. The comparison results of several classifiers on several datasets are explained in the experimental section.

Acute toxicity of cyanide in aerobic respiration: Theoretical and experimental support for murburn explanation.

Abstract: The inefficiency of cyanide/HCN (CN) binding with heme proteins (under physiological regimes) is demonstrated with an assessment of thermodynamics, kinetics, and inhibition constants. The acute onset of toxicity and CN's mg/Kg LD50 (μM lethal concentration) suggests that the classical hemeFe binding-based inhibition rationale is untenable to account for the toxicity of CN. In vitro mechanistic probing of CN-mediated inhibition of hemeFe reductionist systems was explored as a murburn model for mitochondrial oxidative phosphorylation (mOxPhos). The effect of CN in haloperoxidase catalyzed chlorine moiety transfer to small organics was considered as an analogous probe for phosphate group transfer in mOxPhos. Similarly, inclusion of CN in peroxidase-catalase mediated one-electron oxidation of small organics was used to explore electron transfer outcomes in mOxPhos, leading to water formation. The free energy correlations from a Hammett study and IC50/Hill slopes analyses and comparison with ligands ( CO/ H 2 S/ N 3 - ) $\left( {\text{CO}}/{{{{\text{H}}_{2}}\text{S}}/{\text{N}_{3}^{\text{-}}}\;}\; \right)$ provide insights into the involvement of diffusible radicals and proton-equilibriums, explaining analogous outcomes in mOxPhos chemistry. Further, we demonstrate that superoxide (diffusible reactive oxygen species, DROS) enables in vitro ATP synthesis from ADP+phosphate, and show that this reaction is inhibited by CN. Therefore, practically instantaneous CN ion-radical interactions with DROS in matrix catalytically disrupt mOxPhos, explaining the acute lethal effect of CN.