Silicon Mitigates Drought Stress in Wheat (Triticum aestivum L.) Through Improving Photosynthetic Pigments,Biochemical and Yield Characters

Silicon - Feeling prone to stress differs with plant production stage, water scarcity near commencement of grain filling phase has a significant reduced grain yield through fewer endosperm and sink...     

Comparison of γ-aminobutyric acid accumulation capability in different mung bean (Vigna radiata L.) varieties under heat and relative humidity treatment,and its correlation with endogenous amino acids and polyamines

In this study, the accumulation of GABA and its inherent factors across different varieties of mung bean (Vigna radiata L.) in response to heat and relative humidity (HRH) were investigated. Results showed the average GABA content in mung bean varieties was increased 7.52 times following HRH treatment, and the black mung bean variety (A8) exhibited the highest GABA accumulation capability (1.76–84.57 mg per 100 g DW). From the perspective of GABA shunt metabolites, the free glutamic acid content of mung beans significantly decreased (P < 0.05) after HRH treatment and presented a significant correlation (P < 0.05) with GABA content. In polyamine degradation pathway, although the average levels of spermine and spermidine of mung bean varieties significantly decreased (P < 0.05) after HRH treatment, no significant correlation with GABA content was identified. Hence, the GABA accumulation was predominantly attributed to GABA shunt. Besides, free amino acids including glutamic acid, serine, ornithine, arginine and glycine in mung beans showed a significant positive correlation (P < 0.05) with GABA content and increment following HRH treatment, which suggested that mung beans enriched in these free amino acids might accumulate higher amounts of GABA after HRH treatment and be useful for industrial applications.     

Analysis of postbuckling of graded porous GPL-reinforced beams with geometrical imperfection

This research is concerned with the analysis of post-buckling of a nano-composite beam reinforced by graphene plateletes (GPLs) having geometrical imperfection. GPLs are uniformly and nonuniformly distributed thorough the thickness direction. Different porosity distributions are considered. The elastic properties of the nanocomposite are obtained by employing Halpin-Tsai micromechanics model. The postbuckling load-deflection relation is obtained by solving the governing equations having cubic nonlinearity applying Galerkin's method needless of any iteration process. New results show the importance of porosity coefficient, porosity distribution, GPL distribution, GPL weight fraction, geometrical imperfection, and foundation parameters on nonlinear buckling behavior of porous nanoscale beams. Specially, porosities and GPL reinforcement have a great impact on postbuckling configuration of both ideal and imperfect nanocomposite beams.     

Modified three-phase-lag Green–Naghdi models for thermomechanical waves in an axisymmetric annular disk

Abstract

A novel modification for Green and Naghdi thermoelasticity model of type III is proposed in this article. This model is joined to other ones to treat a thermoelastic wave propagation problem in an annular disk. The closed-form solution of thermoelastic analysis of the annular disks has been presented to deduce temperature, radial displacement, dilatation and stresses. Results are illustrated and reported to compare the simple Green–Naghdi II and III and their modified single-, dual- and three-phase-lag models. Concluding remarks are added.     

A comprehensive study on the size-dependent hygrothermal analysis of exponentially graded microplates on elastic foundations

Abstract

In this paper, the effects of hygrothermal conditions on various behaviors, such as bending, free vibration, mechanical and thermal buckling, of exponentially graded microplates lying on two-parameter elastic foundations are investigated. The trigonometric four-variable plate theory incorporated to the modified couple stress theory (MCST) is employed to derive the equations of motion. The present MCST contains an internal material length scale parameter, thus it can capture the size effect. The microplate is assumed to be subjected to a temperature rise and moisture concentration which are varied linearly through the thickness of the plate. Based on an exponential law, the material properties of the microplate are graded only in z direction. The equations of motion are solved analytically to obtain the displacements, stresses, eigenfrequencies and critical buckling load and temperature of the microplates. The present results are validated by comparing them with those previously published. The numerical examples reveal that considering the size effect and/or the elastic foundations leads to an increment in plate stiffness and thereby leads to a decrement in the deflection and an increment in eigenfrequency and buckling loads. It is also shown that the size effect is negligible for the thicker plate.     

Role of Conducting Polymers in Enhancing TiO2-based Photocatalytic Dye Degradation: A Short Review

Research in the field of TiO₂-based photocatalysis has gained wide attention to address important energy and environmental problem. Lately, the use of conducting polymers as photosensitizers has proven to immensely enhance photodegradation by exhibiting excellent photocatalytic activity under both ultraviolet light and natural sunlight irradiation which is not possible using semiconductors alone. Considering the unique performance of conducting polymer-based nanocomposites in photocatalysis, the present review provides the recent advances in the development of ultraviolet and visible light-responsive conducting polymer-based TiO₂ nanocomposites for their potential application in environmental remediation. This review ends with a summary focusing on the challenges and new dimensions in this still emerging area of research.     

Group Decision Making by Using Incomplete Fuzzy Preference Relations Based on T‐Consistency and the Order Consistency

The existing group decision making techniques may not satisfy the order consistency for aggregation in some cases. The algorithm proposed in this paper overcomes the weaknesses of the existing techniques. The method determines the unknown preferences for group decision making in such a manner that the resulting matrix is T‐consistent and order consistent simultaneously.     

Artificial Neural Networks for Prediction of COVID-19 in Saudi Arabia

In this study, we have proposed an artificial neural network (ANN) model to estimate and forecast the number of confirmed and recovered cases of COVID-19 in the upcoming days until September 17, 2020. The proposed model is based on the existing data (training data) published in the Saudi Arabia Coronavirus disease (COVID-19) situation—Demographics. The Prey-Predator algorithm is employed for the training. Multilayer perceptron neural network (MLPNN) is used in this study. To improve the performance of MLPNN, we determined the parameters of MLPNN using the prey-predator algorithm (PPA). The proposed model is called the MLPNN–PPA. The performance of the proposed model has been analyzed by the root mean squared error (RMSE) function, and correlation coefficient (R). Furthermore, we tested the proposed model using other existing data recorded in Saudi Arabia (testing data). It is demonstrated that the MLPNN-PPA model has the highest performance in predicting the number of infected and recovering in Saudi Arabia. The results reveal that the number of infected persons will increase in the coming days and become a minimum of 9789. The number of recoveries will be 2000 to 4000 per day.