Design and characterization of PNVCL-based nanofibers and evaluation of their potential applications as scaffolds for surface drug delivery of hydrophobic drugs

In this work, nanofiber scaffolds for surface drug delivery applications were obtained by electrospinning poly(N-vinylcaprolactam) (PNVCL) and its blends with poly(ε-caprolactone) and poly(N-vinylcaprolactam)-b-poly(ε-caprolactone). The process parameters to obtain smooth and beadless PNVCL fibers were optimized. The average fibers diameter was less than 1 μm, and it was determined by scanning electron microscopy analyses. Their affinity toward water was evaluated by measuring the contact angle with water. The ketoprofen release behavior from the fibers was analyzed using independent and model-dependent approaches. The low values of the release exponent (n < 0.5) obtained for 20 and 42 °C, indicating a Fickian diffusion mechanism for all formulations. Dissolution efficiencies (DEs) revealed the effect of polymer composition, methodology used in the electrospinning process, and temperature on the release rate of ketoprofen. PNVCL/poly(N-vinylcaprolactam)-b-poly(ε-caprolactone)-based nanofibers showed greater ability to control the in vitro release of ketoprofen, in view of reduced kinetic constant and DE, making this material promising system for controlling release of hydrophobic drugs. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48472.     

Boosting the activity of FeOOH via integration of ZIF-12 and graphene to efficiently catalyze the oxygen evolution reaction

Transition metal oxyhydroxides have been used as promising electrocatalysts for water splitting however, their catalytic activity is restricted due to low surface area and poor conductivity. Herein, we report novel composite FeOOH@ZIF-12/graphene composite as electrocatalyst for water oxidation, whereby ZIF-12 provide extra surface for the FeOOH dispersion whilst graphene act as excellent electron mediator. The composite shows a low overpotential value of 291 mV to attain a current density of 10 mA cm^?2 and a low Tafel slope value of 78 mV dec^?1. The catalyst offers a maximum current density of 101 mA cm^?2, while it gives a turnover frequency (TOF) value of 0.031 s^?1 at an overpotential of 291 mV only. The excellent activity and remarkable stability of composite is attributed to highly conductive and porous support.     

Characterization of Failure Mechanisms of Duplex and Graded Thermal Barrier Coatings Exposed to Thermal Shock Test

The beginning of failure of a (ZrO2-7%Y2O3)/(Ni-22%Co-17%Cr-12.5%Al-0.6%Y) duplex andgraded coating systems on lnconel 617 and IN738LC in burner rig tests has been characterized.The test conditions are 40 s heating up to 75O℃ substrate temperature followed by 80 s aircooling. Failure is considered at the appearance of the first bright spot during heating period.Stresses due to thermal expansion mismatch strains on cooling are the probable cause of life-limiting in this conditions of testing.     

Study of Lateral Spread of Ions Emitted from 2.3 kJ Plasma Focus with Hydrogen and Nitrogen Gases

The characteristics of ion beams of hydrogen and nitrogen with different filling pressures emitted from the plasma focus device of 2.3 kJ energy are investigated. CR-39 SSNTDs are employed for the registration of tracks of ions. The exposed detectors are etched in 6N NaOH solution at 70°C and then examined with an optical microscope. The ion flux is estimated to be of the order of 10^5–6 tracks/cm². The flux with the radial position does not exhibit any regular pattern of variation.     

Effect of Zn and Pb as alloying elements on the electrochemical behavior of brass in NaCl solutions

The electrochemical behavior of brasses with various Zn content (5.5–38 mass%) and brass (Cu–38Zn) with different Pb contents (1–3.4 mass%) in 0.6 M NaCl was investigated. The effects of temperature, immersion time, and concentration of chloride ions on the behavior of the different alloys were studied. The pitting corrosion behavior of Cu–Zn alloys and leaded–brass alloys in 0.6 M NaCl solution was also investigated. Open-circuit potential measurements (OCP), polarization techniques and electrochemical impedance spectroscopy (EIS) were used. The results show that the increase in the Zn content increases the corrosion rate of the brass alloys in chloride solutions, while the increase of Pb content in Cu–38Zn–Pb decreases the corrosion rate of the alloy. Long immersion time of the alloys in the aqueous electrolyte improves their stability due to the formation of passive film on the alloy surface. The breakdown potential is shifted to more negative direction with increasing the Zn content, whereas it shifts towards positive values with increasing Pb content. Equivalent circuit model for the electrode/electrolyte interface under different conditions was proposed to illustrate the electrochemical processes taking place at the interface. The electrochemical behavior of the different alloys was discussed in view of the fitting results.     

Corrosion control of Cu-Ni alloys in neutral chloride solutions by amino acids

The corrosion inhibition of Cu-Ni alloys was investigated in aqueous chloride solutions using amino acids as environmentally safe materials. The corrosion rate was calculated in absence and presence of the corrosion inhibitor using polarization and impedance techniques. The inhibition efficiency of the different amino acids was also calculated.The experimental results have shown that a simple amino acid like glycine can be used as efficient corrosion inhibitor for the Cu-Ni alloys in neutral chloride solutions. An inhibition efficiency of about 85% could be achieved at very low concentrations of the amino acid (0.1 mM). For low Ni content alloy (Cu-5Ni), 2.0 mM cysteine shows a remarkable high (∼96%) corrosion inhibition efficiency. The experimental impedance data were fitted to theoretical data according to a proposed equivalent circuit model for the electrode/electrolyte interface, and the mechanism of the corrosion inhibition process was suggested. Different adsorption isotherms were tested and the corrosion inhibition process was found to depend on the adsorption of the amino acid molecules and/or the deposition of corrosion products on the alloy surface. The adsorption free energy of cysteine on Cu-5Ni (−37.81 kJ mol⁻¹) reveals a strong physical adsorption of the inhibitor on the alloy surface.     

Speech enhancement with an adaptive Wiener filter

This paper proposes an adaptive Wiener filtering method for speech enhancement. This method depends on the adaptation of the filter transfer function from sample to sample based on the speech signal statistics; the local mean and the local variance. It is implemented in the time domain rather than in the frequency domain to accommodate for the time-varying nature of the speech signals. The proposed method is compared to the traditional frequency-domain Wiener filtering, spectral subtraction and wavelet denoising methods using different speech quality metrics. The simulation results reveal the superiority of the proposed Wiener filtering method in the case of Additive White Gaussian Noise (AWGN) as well as colored noise.     

Optimal Deep Learning Model Enabled Secure UAV Classification forIndustry 4.0

Emerging technologies such as edge computing, Internet of Things (IoT), 5G networks, big data, Artificial Intelligence (AI), and Unmanned Aerial Vehicles (UAVs) empower, Industry 4.0, with a progressive production methodology that shows attention to the interaction between machine and human beings. In the literature, various authors have focused on resolving security problems in UAV communication to provide safety for vital applications. The current research article presents a Circle Search Optimization with Deep Learning Enabled Secure UAV Classification (CSODL-SUAVC) model for Industry 4.0 environment. The suggested CSODL-SUAVC methodology is aimed at accomplishing two core objectives such as secure communication via image steganography and image classification. Primarily, the proposed CSODL-SUAVC method involves the following methods such as Multi-Level Discrete Wavelet Transformation (ML-DWT), CSO-related Optimal Pixel Selection (CSO-OPS), and signcryption-based encryption. The proposed model deploys the CSO-OPS technique to select the optimal pixel points in cover images. The secret images, encrypted by signcryption technique, are embedded into cover images. Besides, the image classification process includes three components namely, Super-Resolution using Convolution Neural Network (SRCNN), Adam optimizer, and softmax classifier. The integration of the CSO-OPS algorithm and Adam optimizer helps in achieving the maximum performance upon UAV communication. The proposed CSODL-SUAVC model was experimentally validated using benchmark datasets and the outcomes were evaluated under distinct aspects. The simulation outcomes established the supreme better performance of the CSODL-SUAVC model over recent approaches.