A Novel Image Encryption Scheme Based on Walsh Compressed Quantum Spinning Chaotic Lorenz System

In today’s era, a fascinating discipline is immensely influencing a wide miscellany in different fields of science and technology known as quantum cryptography. The amalgamation of different unconventional themes of information security and fast computing have appended inventiveness and creativity into the performance of quantum systems which exhibits astonishing outcomes surprisingly for the most complicated nonlinear models. The exploitation of chaos theory at quantum scale is a dynamical new approach towards the system of information security. Regarding this a novel image encryption approach based on modern standards of chaos, fast computing and quantum encryption has been proposed in this article. In the designed scheme, Walsh transformation is exploited to get standard image compression as to reduce data being processed resulting in fast computing. Quantum spinning and rotation operators leading new protocols, compressed data is encrypted using quantum spinning and rotation operators. For adding more confusion capability in contemplated algorithm discrete fractional chaotic Lorenz system is also accomplished. The proposed system has been validated through statistical analysis, the assessments accordingly by statistical analysis tests clearly emphasis that proposed scheme of encryption is comparatively equitable for the digital images security.

     

Compressible pulsating convection through regular and random porous media: the thermoacoustic case

The effects of material, geometry, length and position of the porous channels on energy transfer in air-filled enclosures carrying a compressible pulsating wave are investigated. The pulsating fluid motion is created by an acoustic driver in a resonant chamber. Three different porous materials (Corning Celcor, Reticulated Vitreous Carbon (RVC), and Mylar plastic), three different geometries (square, open foam, and circular cross-section), six different lengths, “L” (varying between 1 and 6.5 cm, L = 0.01–0.068 λ, where λ is the wavelength of the fundamental acoustic mode), and eight different positions (hot end of the channel, varying between 0.5 and 8 cm) of the channels from the pressure anti-node is experimentally measured. The surface temperature distribution on the channel wall and temperature difference generated across the channel walls are measured while energy flow along the channel walls is calculated analytically. The experimental results are compared with a 1-D numerical code and found excellent agreement. The material, geometry, length, and position of the porous channel strongly affect the energy interactions between the porous channel and the working fluid. The temperature difference generated across the porous RVC channel increases as the porosity increases form 20 to 80 PPI; but decreases if the porosity increases further. Corning Celcor shows improved temperature difference generated across the channel as the length of the channel increases; but then decreases if the length is further increased. The results of this study are applicable to the design of thermoacoustic devices.     

Influence of non-proportional loading on ratcheting responses and simulations by two recent cyclic plasticity models

Aubin and her coworkers conducted a unique set of experiments demonstrating the influence of loading non-proportionality on ratcheting responses of duplex stainless steel. In order to further explore their new observation, a set of experiments was conducted on stainless steel (SS) 304L under various biaxial stress-controlled non-proportional histories. This new set of data reiterated Aubin and her coworkers’ observation and illustrated many new responses critical to model development and validation. Two recent and different classes of cyclic plasticity models, the modified Chaboche model proposed by Bari and Hassan and the version of the multi-mechanism model proposed by Taleb and Cailletaud, are evaluated in terms of their simulations of the SS304L non-proportional ratcheting responses. A modeling scheme for non-proportional ratcheting responses using the kinematic hardening rule parameters in addition to the conventionally used isotropic hardening rule parameter (yield surface size change) in the modified Chaboche model is evaluated. Strengths and weaknesses of the models in simulating the non-proportional ratcheting responses are identified. Further improvements of these models needed for improving the non-proportional ratcheting simulations are suggested in the paper.     

Heat transfer mechanisms in poplar wood undergoing torrefaction

Torrefaction, a thermal treatment process of biomass, has been proved to improve biomass combustible properties. Torrefaction is defined as a thermochemical process in reduced oxygen condition and at temperature range from 200 to 300 °C for shorter residence time whereby energy yield is maximized, can be a bridging technology that can lead the conventional system (e.g. coal-fired plants) towards a sustainable energy system. In efforts to develop a commercial operable torrefaction reactor, the present study examines the minimum input condition at which biomass is torrefied and explores the heat transfer mechanisms during torrefaction in poplar wood samples. The heat transfer through the wood sample is numerically modeled and analyzed. Each poplar wood is torrefied at temperature of 250, 270, and 300 °C. The experimental study shows that the 270 °C-treatment can be deduced as the optimal input condition for torrefaction of poplar wood. A good understanding of heat transfer mechanisms can facilitate the upscaling and downscaling of torrefaction process equipment to fit the feedstock input criteria and can help to develop treatment input specifications that can maximize process efficiency.     

Detection of cancer affected cell using Sagnac interferometer based photonic crystal fiber refractive index sensor

Optical and Quantum Electronics - A complex studies of optoelectronics, non-linear optical and laser stimulated piezoelectric features of chalcogenide powder-like chalcogenide crystals pure and...     

Design,synthesis and liquid crystalline behavior of ethyl 4-((4-alkoxyphenyl)diazenyl)benzoates

A series of ethyl 4-((4-alkoxyphenyl)diazenyl)benzoate is synthesized and the liquid crystalline behavior studied. Synthesized compounds are characterized by FTIR, ¹H-NMR, Mass and single crystal XRD. Differential scanning calorimetry was carried out to study the phase transitions and enthalpy changes. Polarizing optical microscopy revealed the mesogenic properties. These techniques revealed that three compounds (2a, 2b, 2f) exhibit liquid crystalline properties in the range of 80–104°C. POM exhibiting focal conical fan like texture which revealed the presence of smectic phases suggestive of their use in LCD and temperature sensing devices, besides 2c can be used as green emitter in OLEDs.     

Discovery of Phenylcarbamoylazinane-1,2,4-Triazole Amides Derivatives as the Potential Inhibitors of Aldo-Keto Reductases (AKR1B1 & AKRB10): Potential Lead Molecules for Treatment of Colon Cancer

Both members of the aldo-keto reductases (AKRs) family, AKR1B1 and AKR1B10, are over-expressed in various type of cancer, making them potential targets for inflammation-mediated cancers such as colon, lung, breast, and prostate cancers. This is the first comprehensive study which focused on the identification of phenylcarbamoylazinane-1, 2,4-triazole amides (7a–o) as the inhibitors of aldo-keto reductases (AKR1B1, AKR1B10) via detailed computational analysis. Firstly, the stability and reactivity of compounds were determined by using the Guassian09 programme in which the density functional theory (DFT) calculations were performed by using the B3LYP/SVP level. Among all the derivatives, the 7d, 7e, 7f, 7h, 7j, 7k, and 7m were found chemically reactive. Then the binding interactions of the optimized compounds within the active pocket of the selected targets were carried out by using molecular docking software: AutoDock tools and Molecular operation environment (MOE) software, and during analysis, the Autodock (academic software) results were found to be reproducible, suggesting this software is best over the MOE (commercial software). The results were found in correlation with the DFT results, suggesting 7d as the best inhibitor of AKR1B1 with the energy value of −49.40 kJ/mol and 7f as the best inhibitor of AKR1B10 with the energy value of −52.84 kJ/mol. The other potent compounds also showed comparable binding energies. The best inhibitors of both targets were validated by the molecular dynamics simulation studies where the root mean square value of <2 along with the other physicochemical properties, hydrogen bond interactions, and binding energies were observed. Furthermore, the anticancer potential of the potent compounds was confirmed by cell viability (MTT) assay. The studied compounds fall into the category of drug-like properties and also supported by physicochemical and pharmacological ADMET properties. It can be suggested that the further synthesis of derivatives of 7d and 7f may lead to the potential drug-like molecules for the treatment of colon cancer associated with the aberrant expression of either AKR1B1 or AKR1B10 and other associated malignancies.     

Deep Learning and Structure-Based Virtual Screening for Drug Discovery against NEK7: A Novel Target for the Treatment of Cancer

NIMA-related kinase7 (NEK7) plays a multifunctional role in cell division and NLRP3 inflammasone activation. A typical expression or any mutation in the genetic makeup of NEK7 leads to the development of cancer malignancies and fatal inflammatory disease, i.e., breast cancer, non-small cell lung cancer, gout, rheumatoid arthritis, and liver cirrhosis. Therefore, NEK7 is a promising target for drug development against various cancer malignancies. The combination of drug repurposing and structure-based virtual screening of large libraries of compounds has dramatically improved the development of anticancer drugs. The current study focused on the virtual screening of 1200 benzene sulphonamide derivatives retrieved from the PubChem database by selecting and docking validation of the crystal structure of NEK7 protein (PDB ID: 2WQN). The compounds library was subjected to virtual screening using Auto Dock Vina. The binding energies of screened compounds were compared to standard Dabrafenib. In particular, compound 762 exhibited excellent binding energy of −42.67 kJ/mol, better than Dabrafenib (−33.89 kJ/mol). Selected drug candidates showed a reactive profile that was comparable to standard Dabrafenib. To characterize the stability of protein–ligand complexes, molecular dynamic simulations were performed, providing insight into the molecular interactions. The NEK7–Dabrafenib complex showed stability throughout the simulated trajectory. In addition, binding affinities, pIC50, and ADMET profiles of drug candidates were predicted using deep learning models. Deep learning models predicted the binding affinity of compound 762 best among all derivatives, which supports the findings of virtual screening. These findings suggest that top hits can serve as potential inhibitors of NEK7. Moreover, it is recommended to explore the inhibitory potential of identified hits compounds through in-vitro and in-vivo approaches.     

Development of oxidative sample preparation for the analysis of forensic soil samples with near‐IR Raman spectroscopy

Forensic soil samples have been traditionally analysed via examinations of colour, texture and mineral content by physical or chemical methods. These methods leave any organic or water‐soluble fractions unexamined. A range of analytical techniques have been applied in this area and these procedures have been reviewed recently. This study uses Raman Spectroscopy to assess both the mineralogical and the water‐soluble organic fractions in soil samples. Soil samples were collected from both urban and rural environments comprising the city of Bradford, England, and an arable farming district in Lincolnshire. This study demonstrates how, with the use of oxidative preparation methods, Raman spectroscopy can be used to successfully discriminate between soil types using mineralogy as well as the organic and water‐soluble fractions of soils. Copyright © 2011 John Wiley & Sons, Ltd.