Investigation of Anti-Cancer Drug Nimustine Interaction with Calf Thymus DNA

Nimustine, a chloroethyl nitrosourea derivative (CENU), is an antineoplastic agent, which is used for the treatment of various types of cancer. The present study focuses on the prediction and investigation of binding properties of nimustine with DNA using molecular modeling and UV–Visible spectroscopic technique. The docking study show that nimustine plausibly binds within the major groove of DNA. Further analysis of docking suggests direct interaction of nimustine with the moieties of heterocyclic nitrogenous bases of DNA. The free binding energy value of the best nimustine-DNA docked conformer is predicted as ?4.31 kcal/mol using docking results.The molecular modeling study also reveals that the interaction between nimustine and DNA is majorly governed by van der Waals forces, hydrogen bonding and hydrophobic interactions, whereas the contribution of electrostatic forces stands negligible. Further, UV–Visible spectra of free calf thymus DNA and its complexes with varying concentration of nimustine indicate the binding constant (K _a ) value as 3.27 × 10³ M^?1, which suggests moderate interaction of nimustine with DNA. The spectroscopic results are further used to calculate the binding free energy of the complex using the relation ΔG = ?RT ln (K _a ). This accounts for a value of ?4.79 kcal/mol. It corroborates well with the docking outcomes. The results of present study may help in designing and synthesis of new chloroethyl nitrosourea derivatives with improved efficacy and specificity for the target molecules.     

Analysing stable feature selection through an augmented marine predator algorithm based on opposition-based learning

Retrieving the relevant information from the high-dimensional dataset enhances the classification accuracy of a predictive model. This research critique has devised an improved marine predator algorithm based on opposition learning for stable feature selection to overcome the problem of high-dimensionality. Marine predator algorithm is a population-based meta-heuristics optimization algorithm that works on the ‘survival-of-the-fittest’ theory. Classical marine predator algorithm explores the search space merely in one direction, affecting its converging capacity while being responsible for stagnation at local minima. The proposed opposition-based learning nuances enhance the exploration capacity of marine predator algorithm and productively converges the model to global optima. The proposed OBL-based marine predator algorithm selects stable, substantial elements from six different high-dimensional microarray datasets. The performance of the proposed method is investigated using five predominantly used classifiers. From the result, it is understood that the proposed approach outperforms other conventional feature selection techniques in terms of converging capability, classification accuracy, and stable feature selection.     

Isomers of monoethylenic fatty acids in some partially hydrogenated marine oils

An analytical study of the monoethylenic isomers in commercial samples of partially hydrogenated herring, whale and seal oils is presented. The results show that with hydrogenated herring oil there is a slight decline in monoenetrans content from 37% in C₁₆ through to 32% in C₂₂. With both whale and seal oils, monoenetrans contents were constant at 54% and 59%, respectively, throughout all chain lengths. In general thecis andtrans positional isomers from hydrogenated whale and seal oils were more scattered than those from hydrogenated herring oil; however in each oil the majorcis isomers of each chainlength were indicative of originalcis fatty acid isomers in the raw oils.     

CLA-Rich Soy Oil Margarine Production and Characterization

A heterogeneous catalysis method to produce 20 % conjugated linoleic acid (CLA)-rich food-grade soy oil in 2 h without solvents or gases was recently developed. The objective of this study was to produce and characterize CLA-rich soy oil margarine relative to a soy oil control and commercial margarine. CLA-rich soy oil was used to prepare margarine. The samples were characterized for firmness, rheology, thermal behavior, solid fat content (SFC) and microstructure and compared with a soy oil control and commercial margarine. The CLA-rich oil margarine firmness and rheological properties were similar to commercial margarine and provided a better texture relative to the soy oil control margarine. However, SFC, droplet size distribution and melting behavior of CLA-rich oil margarine were similar to control soy oil margarine and dissimilar to the commercial product. This suggests that hardness and rheological properties of margarine are not solely dependent on SFC and melting behavior. Lipid composition, polymorphism and microstructure differences in CLA-rich oil margarine may play an important role on the texture and rheological properties. A 7-g typical serving of the CLA-rich oil margarine will provide 0.6 g CLA. Thus five servings will provide 3.2 g/day of CLA and 185 calories/day, which is well within the maximum recommended 700–980 fat calories/day.     

Bit error rate and reliability analysis of cooperative communication in free-space optical systems

We have investigated the performance and reliability improvement of cooperative free-space optical (FSO) communication over single input single output (SISO) system in this paper. The bit error rate (BER) analysis with quadrature phase shift keying (QPSK), gamma–gamma channel model and pointing error has been demonstrated for SISO and cooperative system. The performance improvement with different combining techniques in cooperative system for different channel environments has been shown in the paper. Markov models for reliability analysis of FSO systems in SISO and cooperative communication have been developed. We have obtained significant increase in availability and mean time between failures with cooperative communication over SISO model.     

Machine Learning and Deep Learning powered satellite communications: Enabling technologies,applications, open challenges,and future research directions

The recent wave of creating an interconnected world through satellites has renewed interest in satellite communications. Private and government-funded space agencies are making advancements in the creation of satellite constellations, and the introduction of 5G has brought a new focus to a fully connected world. Satellites are the proposed solutions for establishing high throughput and low latency links to remote, hard-to-reach areas. This has caused the injection of many satellites in Earth's orbit, which has caused many discrepancies. There is a need to establish highly adaptive and flexible satellite systems to overcome this. Machine Learning (ML) and Deep Learning (DL) have gained much popularity when it comes to communication systems. This review extensively provides insight into ML and DL's utilization in satellite communications. This review covers how satellite communication subsystems and other satellite system applications can be implemented through Artificial Intelligence (AI) and the ongoing open challenges and future directions.     

Performance evaluation of the augmented data vortex switch fabric: An all-optical packet switched interconnection network

Modern high-performance computing systems require networks with high capacity, extremely high throughput and low latency in order to pass messages between thousands of processors and memory elements. Optical Interconnection Networks (OIN) offer a potentially viable solution to this requirement. An all-optical packet switched interconnection network called a Data Vortex (DV) switch has already been proposed by Yang et al. for the purpose of large scale photonic interconnections. For any interconnection network, fault tolerance and reliability are crucial issues, evaluation of which lacked attention for the case of the DV switch. In our earlier work we therefore presented the results for fault tolerance and reliability analysis of the primary DV switch. We also proposed a new Augmented Data Vortex (ADV) switch fabric, to improve the fault tolerance of the primary DV switch. The performance as regards fault tolerance of the ADV switch was computed and detailed results were obtained. In this paper, performance of ADV is investigated with reference to parameters such as latency and injection ratio (throughput) by means of numerical simulations. A uniform random traffic model has been used for the performance evaluation. The results obtained are compared with the results reported for the DV switch. The results show that the ADV switch with enhanced fault tolerance also improves the performance regarding latency. For same switch sizes (i.e. the same number of angles A, and height H) the injection ratios (throughput) for the DV and the ADV switches are comparable. Hence it can serve as a suitable candidate for high performance computing.     

Shielded edge-coupled coplanar waveguide structures: Modes and field configurations

In this article we present the dispersion characteristics as well as frequency-dependent field configuration and characteristic impedance for edge-coupled, shielded, coplanar waveguide structures. The structures studied include conductor-backed and suspended configurations. Phenomena such as mode conversion and dispersion of the dominant modes are explained. The characteristic impedance behavior is shown to be directly related to the phenomenon of mode conversion. The analysis uses the method of lines. © 1996 John Wiley & Sons, Inc.     

Common-path optical coherence tomography with side-viewing bare fiber probe for endoscopic optical coherence tomography

All-fiber-optic common-path optical coherence tomography (OCT) using a side-viewing bare fiber probe has been demonstrated and analyzed. A bare single mode fiber tip is angle cleaved at approximately 49 degrees to enable side illumination due to total internal reflection. The bare fiber probe was inserted in an arterial tissue and a circumferential OCT scan was obtained. The research is aimed at realizing highly miniaturized monolithic probes for possible applications in miniature endoscopic OCT or intravascular OCT. The effects of the angle of the cleaved fiber on reference reflection and the sensitivity of the common-path OCT system have been studied theoretically. The angle cleaved fiber probe is also used in series with a microlens to analyze and optimize its performance in a common-path OCT system. Our research aims to explore the combined advantages of common-path OCT and extremely simplified miniature probe design and to discuss how it may greatly simplify the endoscopic OCT instrumentation eventually.