Advanced mobile devices and global internet services have enhanced the usage of smartphones in the education sector and their potential for fulfilling teaching and learning objectives. The current ...study is an attempt to assess the factors affecting mobile learning acceptance by Saudi university students. A theoretical model of mobile learning acceptance was developed based on the technology acceptance model (TAM) and the unified theory of acceptance and use of technology (UTAUT) model. Theoretically, five independent constructs were identified as most contributory towards the use of mobile learning and tested empirically. Data were collected through an online survey and analyzed using SmartPLS. The results of the study indicate that four constructs were significantly associated with mobile learning acceptance: perceived usefulness (β = 0.085, t = 2.201, and p = 0.028), perceived ease of use (β = 0.031, t = 1.688, and p = 0.013), attitude (β = 0.100, t = 3.771, and p = 0.037), and facilitating conditions (β = 0.765, t = 4.319, and p = 0.001). On the other hand, social influence was insignificant (β = −0.061, t = 0.136, and p = 0.256) for mobile learning acceptance. The contribution of social influence towards the use of mobile learning was negative and insignificant; hence, it was neglected. Thus, finally, four constructs (perceived usefulness, perceived ease of use, attitude, and facilitating conditions) were considered as important determinants of mobile learning acceptance by university students.
Nanofluid is treated as a smart fluid that is useful for heat and mass transfer enhancement, which is paramount in several electronics, biomedical, transportation as well as industrial applications. ...In view of this, in the current analysis we scrutinize the flow of nanofluid over a curved stretching sheet. The noted novelty of this work is to discuss the heat and mass transfer in nanofluid flow along with the activation energy. Further, CuO with water-based nanofluid is considered in the modelling. The viscosity and effective thermal conductivity of fluid flow suspended by nanoparticles are scrutinized by Koo–Kleinstreuer–Li (KKL) model. By employing suitable similarity transformations, the governing equations of momentum, thermal and concentration of nanoparticle are converted into ordinary differential equations and then they are solved with Runge–Kutta-Fehlberg-45 (RKF-45) process along with shooting method. The impact of pertinent non-dimensional parameters is attained and illustrated with the help of graphs. The results reveal that, the heightening of Biot number and curvature parameter heightens the thermal gradient. The mass transfer decreases as the Schmidt number and chemical reaction rate parameter increases. The upsurge in activation energy parameter declines the mass transfer.
Abstract
In various machinery engines, the engine oil is utilized as a lubricant. Heat transportation rate and to saving the energy dissipated due to higher temperature are the basic goals of all ...thermal systems. Thus, current work is mainly focused to develop a model for the Marangoni flow of nanofluids (NFs) with viscous dissipation. The considered NFs are made of nanoparticles (NPs) i.e.
$${\text{CoCr}}_{20} {\text{W}}_{15} {\text{N}}$$
CoCr
20
W
15
N
and base fluid (BF) as Engine Oil (EO). Darcy Forchheimer (DF) law which leads to porous medium is implemented in the model to investigate the variations of NF velocity and temperature. The governing flow expressions are simplified through similarity variables. The obtained expressions are solved numerically via an effective technique known as the NDSolve algorithm. The consequences of pertinent variables on temperature, velocity and Nusselt number are designed through tables and graphs. The obtained results reveal that velocity rises for higher Marangoni number, Darcy Forchheimer (DF) parameter whereas it shows decaying behavior against nanoparticles volume fraction.
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•High frequency (20 kHz) ultrasonic probe was used to extract flavonoids in 45-different origin fenugreek seed samples.•Green and short UHPLC-DAD method was developed for simultaneous ...flavonoids analysis of RT, QT, LT, and KF.•The effect of individual solvent upon the extract yeild and flavonoids qauntitiy was evaluated.•The developed and validated methods were applied on large scale to determine the quality of fenugreek.•High yield for RT and QT was noticed in these samples.
This study, for the first time, reports a simultaneous determination of flavonoids; rutin (RT), quercetin (QT), luteolin (LT), and kaempferol (KF) in different origins of fenugreek seeds samples (N = 45) using a green UHPLC-DAD analysis
Ultrasound-assisted extraction (UAE) was employed to extract fenugreek flavonoids using different polarity solvents of n-hexane (n-hex), dichloromethane (DCM), and methanol (MeOH)
The extract yield on an individual basis was observed in the range of 1.03–17.29 mg, with the highest yield (mg/sample) for the Egyptian sample (17.29 mg). The highest total extract yield (mg/origin) was observed for the Iranian sample (82.28 ± 5.38). The solvent with the highest extract yield (mg) was n-hex 169.35 ± 13.47, followed by MeOH 114.39 ± 12.27. The validated green UHPLC-DAD method resulted in a short runtime (9 min) with an accuracy of 97.86(±12.32)-101.37(±5.91), r2-values = 0.993–0.999, LOD = 2.09–4.48 ppm, and LOQ = 6.33–13.57 ppm for flavonoids analysis within the linearity range of 1–500 ppm. The general yield for flavonoids exhibited a descending order (ppm): RT (2924.55 ± 143.84) > QT (457.05 ± 34.07) > LT (82.37 ± 3.27) > KF (4.54 ± 0.00). The yield (ppm) for the flavonoids was more in MeOH solvent (3424.81 ± 235.44) constructing a descending order of MeOH > n-hex > DCM. For an individual flavonoid yield; MeOH was seen with an order of RT > QT > LT, n-hex (LT > QT), and DCM (RT > LT > QT). The statistical analysis of PCA (principle component analysis) revealed a widespread distribution of flavonoids in fenugreek seeds with a variance of 35.93% (PC1). Moreover, flavonoids extraction was prone to the nature and specificity of the solvent used (PC2: 33.34%) rather than the amount of the extract yield (P = 0.00). The K-mean cluster analysis showed the origins with higher flavonoids yield in appropriate solvent as I3M (Indian accession # 3 MeOH extract) with more QT amount, IR2M (Iranian accession # 2 MeOH extract) with more LT amount along with I2M (Indian accession # 2 MeOH extract) and Q2M (Qassim Saudi Arabia accession # 2 MeOH extract) containing high amount of RT. The outcomes are supported by KMO (Kaiser-Meyer-Olkin) and Bartlett’s test value of 0.56 with X2-value of 191.87 (P = 0.00)
The samples were effectively evaluated and standardized in terms of flavonoid amount suggesting a significant variation in fenugreek quality.
The current study provides the numerical performances of the fractional kind of breast cancer (FKBC) model, which are based on five different classes including cancer stem cells, healthy cells, tumor ...cells, excess estrogen, and immune cells. The motive to introduce the fractional order derivatives is to present more precise solutions as compared to integer order. A stochastic computing reliable scheme based on the Levenberg Marquardt backpropagation neural networks (LMBNNS) is proposed to solve three different cases of the fractional order values of the FKBC model. A designed dataset is constructed by using the Adam solver in order to reduce the mean square error by taking the data performances as 9% for both testing and validation, while 82% is used for training. The correctness of the solver is approved through the negligible absolute error and matching of the solutions for each model's case. To validates the accuracy, and consistency of the solver, the performances based on the error histogram, transition state, and regression for solving the FKBC model.
The fins performance under natural convection is essential to make it more functional for large scale applications more specifically in thermal engineering. For this, it is important to introduce new ...techniques to enhance the fins performance instead of traditional way. Thus, this study introduces a new way to make the fin more efficient using ternary nanomaterial under nanoparticles shape factor. The annular fin significantly contributes in electronics to exhaust the hot air, injector pumps and applied thermal engineering.
and Methodology: This work focuses on the fin energy model using shape factors. Therefore, the ternary nanofluid, natural convection, thermal radiation and magnetic field used to develop the model. Then, the RKF-45 implemented to investigate physical results.
Keen analysis of the physical results reveal that the coefficient of thermal conductivity ranging from 0.0% < α1 < 3.0% and natural convection have major role in the fins energy performance. Induction of magnetic field and thermal radiation Rd are reliable for the fin cooling and, heating source Q1 = 0.2,0.4,0.6,0.8 promote the fin energy capability in the existence of (Al2O3–CuO–Cu) ternary nanomaterial with concentration factor up to 2%. On the comparative basis, ternary nanomaterial makes the fin more efficient than hybrid nanomaterial.
The aim of the current analysis is to evaluate the significances of magnetic dipole and heat transmission through ternary hybrid Carreau Yasuda nanoliquid flow across a vertical stretching sheet. The ...ternary compositions of Al
O
, SiO
, and TiO
nanoparticles (nps) in the Carreau Yasuda fluid are used to prepare the ternary hybrid nanofluid (Thnf). The heat transfer and velocity are observed in context of heat source/sink and Darcy Forchhemier effect. Mathematically, the flow scenario has been expressed in form of the nonlinear system of PDEs for fluid velocity and energy propagation. The obtained set of PDEs are transform into ODEs through suitable replacements. The obtained dimensionless equations are computationally solved with the help of the parametric continuation method. It has been observed that the accumulation of Al
O
, SiO
and TiO
-nps to the engine oil, improves the energy and momentum profiles. Furthermore, as compared to nanofluid and hybrid nanofluid, ternary hybrid nanofluid have a greater tendency to boost the thermal energy transfer. The fluid velocity lowers with the outcome of the ferrohydrodynamic interaction term, while enhances with the inclusion of nano particulates (Al
O
, SiO
and TiO
).
The COVID-19 outbreak continues to spread worldwide at a rapid rate. Currently, the absence of any effective antiviral treatment is the major concern for the global population. The reports of the ...occurrence of various point mutations within the important therapeutic target protein of SARS-CoV-2 has elevated the problem. The SARS-CoV-2 main protease (Mpro) is a major therapeutic target for new antiviral designs. In this study, the efficacy of PF-00835231 was investigated (a Mpro inhibitor under clinical trials) against the Mpro and their reported mutants. Various in silico approaches were used to investigate and compare the efficacy of PF-00835231 and five drugs previously documented to inhibit the Mpro. Our study shows that PF-00835231 is not only effective against the wild type but demonstrates a high affinity against the studied mutants as well.
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