Green synthesised zinc oxide nanostructures through Periploca aphylla extract shows tremendous antibacterial potential against multidrug resistant pathogens

To grapple with multidrug resistant bacterial infections, implementations of antibacterial nanomedicines have gained prime attention of the researchers across the globe. Nowadays, zinc oxide (ZnO) at nano‐scale has emerged as a promising antibacterial therapeutic agent. Keeping this in view, ZnO nanostructures (ZnO‐NS) have been synthesised through reduction by P. aphylla aqueous extract without the utilisation of any acid or base. Structural examinations via scanning electron microscopy (SEM) and X‐ray diffraction have revealed pure phase morphology with highly homogenised average particle size of 18 nm. SEM findings were further supplemented by transmission electron microscopy examinations. The characteristic Zn–O peak has been observed around 363 nm using ultra‐violet–visible spectroscopy. Fourier‐transform infrared spectroscopy examination has also confirmed the formation of ZnO‐NS through detection of Zn–O bond vibration frequencies. To check the superior antibacterial activity of ZnO‐NS, the authors'' team has performed disc diffusion assay and colony forming unit testing against multidrug resistant E. coli, S. marcescens and E. cloacae. Furthermore, protein kinase inhibition assay and cytotoxicity examinations have revealed that green fabricated ZnO‐NS are non‐hazardous, economical, environmental friendly and possess tremendous potential to treat lethal infections caused by multidrug resistant pathogens.Inspec keywords: nanomedicine, zinc compounds, II‐VI semiconductors, wide band gap semiconductors, nanoparticles, scanning electron microscopy, X‐ray diffraction, antibacterial activity, transmission electron microscopy, particle size, Fourier transform infrared spectra, ultraviolet spectra, visible spectra, enzymes, biochemistry, molecular biophysics, microorganisms, drugs, toxicology, bonds (chemical), semiconductor growth, nanofabrication, vibrational modesOther keywords: green synthesised zinc oxide nanostructures, Periploca aphylla extract, antibacterial potential, multidrug resistant pathogens, multidrug resistant bacterial infections, antibacterial nanomedicines, P. aphylla aqueous extract, structural examinations, scanning electron microscopy, X‐ray diffraction, pure phase morphology, homogenised average particle size, SEM, transmission electron microscopy, Fourier‐transform infrared spectroscopy, bond vibration frequency, antibacterial activity, disc diffusion assay, colony forming unit testing, S. marcescens, E. cloacae, E. coli, ultraviolet‐visible spectroscopy, protein kinase inhibition assay, cytotoxicity, lethal infections, ZnO     

VARIATION OF PRESSURE WITH RAM SPEED AND DIE PROFILE IN HOT EXTRUSION OF ALUMINUM-6063

Prediction of extrusion pressure, especially in the case of complex die geometries, is an area of continued research interest. Die complexity, usually defined by “shape factor” (the ratio of the perimeter to the cross-sectional area of the profile), critically affects the flow of metal and the pressure required to extrude a given product. Applied strain rate (related directly to the ram speed of the extrusion press) also alters the product quality significantly. The current paper presents results of an ongoing study about effects of ram speed and die profile on extrusion pressure. Experiments were conducted using dies of different complexity to track the effects of ram speed variation and changing die profiles on extrusion pressure. Al-6063, the most popular commercial variety of structural aluminum, was used as the billet material for all experiments.     

Analysis of Silver Nanoparticles in Engine Oil: Atangana–Baleanu Fractional Model

The present article aims to examine the heat and mass distribution in a free convection flow of electrically conducted, generalized Jeffrey nanofluid in a heated rotatory system. The flow analysis is considered in the presence of thermal radiation and the transverse magnetic field of strength B₀. The medium is porous accepting generalized Darcy’s law. The motion of the fluid is due to the cosine oscillations of the plate. Nanofluid has been formed by the uniform dispersing of the Silver nanoparticles in regular engine oil. The problem has been modeled in the form of classical partial differential equations and then generalized by replacing time derivative with Atangana–Baleanu (AB) time-fractional derivative. Upon taking the Laplace transform technique (LTT) and using physical boundary conditions, exact expressions have been obtained for momentum, energy, and concentration distributions. The impact of a number of parameters on fluid flow is shown graphically. The numerical tables have been computed for variation in the rate of heat and mass transfer with respect to rooted parameters. Finally, the classical solution is recovered by taking the fractional parameter approaching unity. It is worth noting that by adding silver nanoparticles in regular engine oil, its heat transfer rate increased by 14.59%, which will improve the life and workability of the engine.     

Nonconvulsive status epilepticus: high incidence in dialysis-dependent patients

Nonconvulsive status epilepticus is defined as a mental status change from baseline of at least a 30-min duration associated with constant or near-continuous ictal discharges on an electroencephalogram (EEG). Nonconvulsive status epilepticus is an often-overlooked diagnosis as a cause of acute confusional state. There are few case reports in dialysis patients. We are reporting 5 patients on chronic dialysis treatment who presented with an acute confusional state. Nonconvulsive status epilepticus was diagnosed by EEG and response to intravenous benzodiazepines. We recommend early EEG to be considered in the evaluation of dialysis patients with an acute confusional state.     

Emotion Recognition from Occluded Facial Images Using Deep EnsembleModel

Facial expression recognition has been a hot topic for decades, but high intraclass variation makes it challenging. To overcome intraclass variation for visual recognition, we introduce a novel fusion methodology, in which the proposed model first extract features followed by feature fusion. Specifically, RestNet-50, VGG-19, and Inception-V3 is used to ensure feature learning followed by feature fusion. Finally, the three feature extraction models are utilized using Ensemble Learning techniques for final expression classification. The representation learnt by the proposed methodology is robust to occlusions and pose variations and offers promising accuracy. To evaluate the efficiency of the proposed model, we use two wild benchmark datasets Real-world Affective Faces Database (RAF-DB) and AffectNet for facial expression recognition. The proposed model classifies the emotions into seven different categories namely: happiness, anger, fear, disgust, sadness, surprise, and neutral. Furthermore, the performance of the proposed model is also compared with other algorithms focusing on the analysis of computational cost, convergence and accuracy based on a standard problem specific to classification applications.     

Stability Analysis of Laminated Soft Core Sandwich Plates Using Higher Order Zig-Zag Plate Theory

C₀ finite element model based on higher order zig-zag plate theory is used to study the stability analysis of laminated sandwich plates. The in-plane displacement field is obtained by superposing a global cubically varying displacement field on a zig-zag linearly varying displacement field with different slope in each layer. The transverse displacement assumes to have a quadratic variation within the core and constant in the faces. The conditions regarding transverse shear stress at layer interfaces and top and bottom are satisfied. Numerical examples covering different features of laminated sandwich plates are presented to illustrate the accuracy of the model.     

Effect of size and shape of metal particles to improve hardness and electrical properties of carbon nanotube reinforced copper and copper alloy composites

Utilizing the extra-ordinary properties of carbon nanotube (CNT) in metal matrix composite (MMC) for macroscopic applications is still a big challenge for science and technology. Very few successful attempts have been made for commercial applications due to the difficulties incorporating CNTs in metals with up-scalable processes. CNT reinforced copper and copper alloy (bronze) composites have been fabricated by well-established hot-press sintering method of powder metallurgy. The parameters of CNT–metal powder mixing and hot-press sintering have been optimized and the matrix materials of the mixed powders and composites have been evaluated. However, the effect of shape and size of metal particles as well as selection of carbon nanotubes has significant influence on the mechanical and electrical properties of the composites. The hardness of copper matrix composite has improved up to 47% compared to that of pure copper, while the electrical conductivity of bronze composite has improved up to 20% compared to that of the pure alloy. Thus carbon nanotube can improve the mechanical properties of highly-conductive low-strength copper metals, whereas in low-conductivity high-strength copper alloys the electrical conductivity can be improved.     

Simple and Sensitive HPLC Method with Fluorescence Detection for the Measurement of Ibuprofen in Rat Plasma: Application to a Long-Lasting Dosage Form

A simple and sensitive high-performance liquid chromatography (HPLC) assay applied to the measurement of ibuprofen in rat plasma has been developed. Two parameters have been investigated to improve ibuprofen detectability using fluorescence detection: variation of mobile phase pH and the use of β-cyclodextrin (β-CD). Increasing the pH value from 2.5 to 6.5 and adding 5 mM β-CD enhanced the fluorescence signal (λ_exc = 224 nm; λ_em = 290 nm) by 2.5 and 1.3-fold, respectively, when using standards. In the case of plasma samples, only pH variation significantly lowered detection and quantification limits, down to 10 and 35 ng/mL, respectively. Full selectivity was obtained with a single step for plasma treatment, that is, protein precipitation with acidified acetonitrile. The validated method was applied to a pharmacokinetic study of ibuprofen encapsulated in microspheres and subcutaneously administered to rats.