Prospects of banana waste utilization in wastewater treatment: A review.

This review article explores utilization of banana waste (fruit peels, pseudo-stem, trunks, and leaves) as precursor materials to produce an adsorbent, and its application against environmental pollutants such as heavy metals, dyes, organic pollutants, pesticides, and various other gaseous pollutants. In recent past, quite a good number of research articles have been published on the utilization of low-cost adsorbents derived from biomass wastes. The literature survey on banana waste derived adsorbents shown that due to the abundance of banana waste worldwide, it also considered as low-cost adsorbents with promising future application against various environmental pollutants.

Effect of different stent configurations using Lattice Boltzmann method and particles image velocimetry on artery bifurcation aneurysm problem.

Proper design of stent for application at specific aneurysm effect arteries could help to reduce the issues with thrombosis and aneurysm. In this paper, four types of stent configuration namely half-Y (6 mm), half-Y (4 mm), cross-bar, and full-Y configuration will implanted on real 3D artery bifurcation aneurysm effected arteries. Comparisons were then conducted based on the flow patterns after stent placement using both LBM-based solver and PIV experimental findings.

Degradation of 17α-ethinylestradiol by nano zero valent iron under different pH and dissolved oxygen levels.

The catalytic properties of nanoparticles (e.g., nano zero valent iron, nZVI) have been used to effectively treat a wide range of environmental contaminants.

Physico-mechanical, thermal and morphological properties of furfuryl alcohol/2-ethylhexyl methacrylate/halloysite nanoclay wood polymer nanocomposites (WPNCs).

In this study, the physical, morphological, mechanical and thermal properties of furfuryl alcohol/2-ethylhexyl methacrylate/halloysite nanoclay wood polymer nanocomposites (FA-co-EHMA-HNC WPNCs) were investigated. FA-co-EHMA-HNC WPNCs were prepared an impregnation method and the properties of the nanocomposites were characterized through the weight percent gain, Fourier transform infrared (FT-IR) spectroscopy, scanning electron microscopy (SEM), three-point flexural test, dynamic mechanical thermal analysis (DMTA), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) analysis and moisture absorption test. The weight percent gain in the 50:50 FA-co-EHMA-HNC WPNC was the highest compared with the raw wood (RW) and other WPNCs.

Piezoresistive Effect in Plasma-Doping of Graphene Sheet for High-Performance Flexible Pressure Sensing Application.

This paper presents a straightforward plasma treatment modification of graphene with an enhanced piezoresistive effect for the realization of a high-performance pressure sensor. The changes in the graphene in terms of its morphology, structure, chemical composition, and electrical properties after the NH/Ar plasma treatment were investigated in detail. Through a sufficient plasma treatment condition, our studies demonstrated that plasma-treated graphene sheet exhibits a significant increase in sensitivity by one order of magnitude compared to that of the unmodified graphene sheet.

Piezoresistive effects in controllable defective HFTCVD graphene-based flexible pressure sensor.

In this work, the piezoresistive effects of defective graphene used on a flexible pressure sensor are demonstrated. The graphene used was deposited at substrate temperatures of 750, 850 and 1000 °C using the hot-filament thermal chemical vapor deposition method in which the resultant graphene had different defect densities. Incorporation of the graphene as the sensing materials in sensor device showed that a linear variation in the resistance change with the applied gas pressure was obtained in the range of 0 to 50 kPa.

Technologies for Assessment of Motor Disorders in Parkinson's Disease: A Review.

Parkinson's Disease (PD) is characterized as the commonest neurodegenerative illness that gradually degenerates the central nervous system. The goal of this review is to come out with a summary of the recent progress of numerous forms of sensors and systems that are related to diagnosis of PD in the past decades. The paper reviews the substantial researches on the application of technological tools (objective techniques) in the PD field applying different types of sensors proposed by previous researchers.

Locality sensitivity discriminant analysis-based feature ranking of human emotion actions recognition.

[Purpose] Computational intelligence similar to pattern recognition is frequently confronted with high-dimensional data. Therefore, the reduction of the dimensionality is critical to make the manifold features amenable. Procedures that are analytically or computationally manageable in smaller amounts of data and low-dimensional space can become important to produce a better classification performance.

Particle swarm optimization based feature enhancement and feature selection for improved emotion recognition in speech and glottal signals.

In the recent years, many research works have been published using speech related features for speech emotion recognition, however, recent studies show that there is a strong correlation between emotional states and glottal features. In this work, Mel-frequency cepstralcoefficients (MFCCs), linear predictive cepstral coefficients (LPCCs), perceptual linear predictive (PLP) features, gammatone filter outputs, timbral texture features, stationary wavelet transform based timbral texture features and relative wavelet packet energy and entropy features were extracted from the emotional speech (ES) signals and its glottal waveforms(GW). Particle swarm optimization based clustering (PSOC) and wrapper based particle swarm optimization (WPSO) were proposed to enhance the discerning ability of the features and to select the discriminating features respectively.