Incorporation of pyridinic and graphitic N to Ni@CNTs: As a competent electrocatalyst for hydrogen evolution reaction

Cheap production of hydrogen (H₂) from eco-friendly routes is preeminent for solving future energy challenges. This study explores the hydrogen evolution reaction (HER) activity of nickel (Ni) nanoparticles and nitrogen doped carbon nanotubes (NiNCNTs), which are fabricated by a cheap and one-step pyrolysis method. The most active catalyst synthesized at 800°C exhibits an overpotential of 0.244 V to reach a current density of 10 mA cm⁻², Tafel slope of 93.3 mV dec⁻¹ and a satisfactory 10 hours stability. Low resistance and large ECSA value of the sample also favor the competent response for HER in alkaline media. The robust HER activity of the catalyst is as a result of the nickel nanoparticles which are the active spots of reaction; while the presence of well-developed nitrogen containing carbon nanotubes with large content of pyridinic and graphitic nitrogen may provide high-electron density and feasible routes for its transportation to deliver an outstanding HER performance.     

Fabrication and simulation studies on D-shaped optical fiber sensor via surface plasmon resonance

This paper describes simulation and experimental methods for designing a D-shaped surface plasmon resonance (SPR) fibre sensor. The sensor consists of two set-up approaches. Finite element method is used in simulation on the fibre sensor device. Two experimental methods for detecting relative intensity are used by varying the wavelength of the optical signal sources and the thickness of gold layer coated on the D-shaped fibre. In the first method, the sensor device works by detecting the relative intensity of two optical signal sources having different wavelengths. In the second set-up, the relative intensity between two D-shaped fibres coated with different thicknesses of gold is measured when a single signal source is launched at the input. The difference in intensities of the signal outputs is used to estimate the refractive index at the sensing region. A prototype SPR D-shaped fibre sensor has been fabricated and the experimental results show good agreement with simulation.     

Adaptive Fuzzy Logic Controller for Harmonics Mitigation Using Particle Swarm Optimization

An excessive use of non-linear devices in industry results in current harmonics that degrades the power quality with an unfavorable effect on power system performance. In this research, a novel control technique-based Hybrid-Active Power-Filter (HAPF) is implemented for reactive power compensation and harmonic current component for balanced load by improving the Power-Factor (PF) and Total–Hormonic Distortion (THD) and the performance of a system. This work proposed a soft-computing technique based on Particle Swarm-Optimization (PSO) and Adaptive Fuzzy technique to avoid the phase delays caused by conventional control methods. Moreover, the control algorithms are implemented for an instantaneous reactive and active current (I_d-I_q) and power theory (Pq0) in SIMULINK. To prevent the degradation effect of disturbances on the system's performance, PS0-PI is applied in the inner loop which generate a required dc link-voltage. Additionally, a comparative analysis of both techniques has been presented to evaluate and validate the performance under balanced load conditions. The presented result concludes that the Adaptive Fuzzy PI controller performs better due to the non-linearity and robustness of the system. Therefore, the gains taken from a tuning of the PSO based PI controller optimized with Fuzzy Logic Controller (FLC) are optimal that will detect reactive power and harmonics much faster and accurately. The proposed hybrid technique minimizes distortion by selecting appropriate switching pulses for VSI (Voltage Source Inverter), and thus the simulation has been taken in SIMULINK/MATLAB. The proposed technique gives better tracking performance and robustness for reactive power compensation and harmonics mitigation. As a result of the comparison, it can be concluded that the PSO-based Adaptive Fuzzy PI system produces accurate results with the lower THD and a power factor closer to unity than other techniques.     

Robust and High Accuracy Algorithm for Detection of Pupil Images

Recently, many researchers have tried to develop a robust, fast, and accurate algorithm. This algorithm is for eye-tracking and detecting pupil position in many applications such as head-mounted eye tracking, gaze-based human-computer interaction, medical applications (such as deaf and diabetes patients), and attention analysis. Many real-world conditions challenge the eye appearance, such as illumination, reflections, and occasions. On the other hand, individual differences in eye physiology and other sources of noise, such as contact lenses or make-up. The present work introduces a robust pupil detection algorithm with and higher accuracy than the previous attempts for real-time analytics applications. The proposed circular hough transform with morphing canny edge detection for Pupillometery (CHMCEP) algorithm can detect even the blurred or noisy images by using different filtering methods in the pre-processing or start phase to remove the blur and noise and finally the second filtering process before the circular Hough transform for the center fitting to make sure better accuracy. The performance of the proposed CHMCEP algorithm was tested against recent pupil detection methods. Simulations and results show that the proposed CHMCEP algorithm achieved detection rates of 87.11, 78.54, 58, and 78 according to Świrski, ExCuSe, Else, and labeled pupils in the wild (LPW) data sets, respectively. These results show that the proposed approach performs better than the other pupil detection methods by a large margin by providing exact and robust pupil positions on challenging ordinary eye pictures.     

Synthesis,Characterization, and Applications of Some New Trimeric‐Type Cationic Surfactants

In recent years, trimeric surfactants have created excitement in the surfactant field because of their properties, which have been found to be better than monomeric or dimeric homologues. Only a limited number of trimeric surfactants have been synthesized and studied so far, probably owing to the difficulty in synthesis. In this article, we synthesized some novel star‐shaped trimeric cationic surfactants based on the alkylation of the 3 hydroxyl groups of the phloroglucinol nuclei as a core (i.e., spacer) with 3 dodecyl or 3 octyl groups (as tails) for the surfactant. The chemical structures were confirmed by nuclear magnetic resonance, Fourier transform infrared, mass spectrometry, and elemental analysis; also the critical micelle concentration was determined by electrical conductivity measurements. These surfactants were used in the synthesis of mesoporous silica nanoparticles by the sol–gel method. The silica particles shape and size were determined using field emission scanning electron microscopy and high‐resolution transmission electron microscopy images. Furthermore, the corrosion inhibitor capability of these surfactants was investigated by monitoring the corrosion rate of iron sheets in 0.5 M hydrochloric acid in the presence and in the absence of different surfactants at 45°C based on the weight loss method. We have used cetyltrimethylammonium bromide (CTAB) as a positive control, the obtained results showed a high inhibition efficiency at very low concentrations, and the prepared trimeric surfactants exhibited a higher anticorrosion efficiency than the CTAB surfactants.     

Entropy with Local Binary Patterns for Efficient Iris Liveness Detection

Iris anti-spoofing is one of the most important topics, in which the development is increasing rapidly. This paper introduces an efficient system for detecting iris attacks. The system avoids the segmentation and the normalization stages employed traditionally in fake detection systems. Wavelet packets (WPs) are used to decompose the original image into wavelet approximation and detail channels. Entropy values are extracted from the wavelet channels, and also from the local binary pattern (LBP) images of the channels. These features are used for discriminating between real and fake iris images. Support vector machines are used for the classification purpose. The aim is to contribute for improved classification accuracy with less computational complexity and reduced processing time. Entropy of the WP channels gives 99.9237% classification accuracy, and the entropy of the LBP images yields 99.781%, using ATVS-FIr-DB. Fusion of these features yields 100% classification accuracy. Entropy of the wavelet channels is sufficient to obtain 100% accuracy using CASIA-Iris-Syn database, without fusion. All images in both databases are used, without the need to discard images with unsuccessful segmentation. Segmented images from both databases are used for comparison. Results show that more discriminative features can be obtained using the proposed algorithm. System complexity and processing time are reduced noticeably, and the system is robust to different types of fakes.     

Progressive Compression of 3D Mesh Geometry Using Sparse Approximations from Redundant Frame Dictionaries

In this paper, we present a new approach for the progressive compression of three‐dimensional (3D) mesh geometry using redundant frame dictionaries and sparse approximation techniques. We construct the proposed frames from redundant linear combinations of the eigenvectors of a combinatorial mesh Laplacian matrix. We achieve a sparse synthesis of the mesh geometry by selecting atoms from a frame using matching pursuit. Experimental results show that the resulting rate‐distortion performance compares favorably with other progressive mesh compression algorithms in the same category, even when a very simple, sub‐optimal encoding strategy is used for the transmitted data. The proposed frames also have the desirable property of being able to be applied directly to a manifold mesh having arbitrary topology and connectivity types; thus, no initial remeshing is required and the original mesh connectivity is preserved.     

Synthesis,Characterization and Immunological Evaluation of Self‐Adjuvanting Group A Streptococcal Vaccine Candidates Bearing Various Lipidic Adjuvanting Moieties

Four group A streptococcal glycolipopeptide vaccine candidates with different lipidic adjuvanting moieties were prepared and characterized. The immunogenicity of the compounds was evaluated by macrophage and dendritic cell uptake studies and by in vivo quantification of systemic IgG antibody by ELISA. Three of the candidates showed significant induction of the IgG response.     

Development and Evaluation of Repurposed Etoricoxib Loaded Nanoemulsion for Improving Anticancer Activities against Lung Cancer Cells

In the present work, novel modality for lung cancer intervention has been explored. Primary literature has established the potential role of cyclooxygenase-2 (COX-2) inhibitor in regression of multiple forms of carcinomas. To overcome its poor water solubility and boost anticancer activity, etoricoxib (ETO) was chosen as a therapeutic candidate for repurposing and formulated into a nanoemulsion (NE). The prepared ETO loaded NE was characterized for the surface charge, droplet size, surface morphology, and in vitro release. The optimized ETO loaded NE was then investigated for its anticancer potential employing A549 lung cancer cell line via cytotoxicity, apoptotic activity, mitochondrial membrane potential activity, cell migration assay, cell cycle analysis, Caspase-3, 9, and p53 activity by ELISA and molecular biomarker analysis through RT-PCR test. The developed ETO-NE formulation showed adequate homogeneity in the droplet size distribution with polydispersity index (PDI) of (0.2 ± 0.03) and had the lowest possible droplet size (124 ± 2.91 nm) and optimal negative surface charge (−8.19 ± 1.51 mV) indicative of colloidal stability. The MTT assay results demonstrated that ETO-NE exhibited substantial anticancer activity compared to the free drug. The ETO-NE showed a substantially potent cytotoxic effect against lung cancer cells, as was evident from the commencement of apoptosis/necrotic cell death and S-phase cell cycle arrests in A549 cells. The study on these molecules through RT-PCR confirmed that ETO-NE is significantly efficacious in mitigating the abundance of IL-B, IL-6, TNF, COX-2, and NF-kB as compared to the free ETO and control group. The current study demonstrates that ETO-NE represents a feasible approach that could provide clinical benefits for lung cancer patients in the future.