Encapsulation of Orange Essential Oil Using Cross-linked Electrospun Gelatin Nanofibers

The aim of this study was to prepare electrospun gelatin (G) and gelatin-cross-linked tannic acid (GT) nanofibers loaded with orange essential oil. Four G/GT-to-orange essential oil ratios (1:0.25, 1:0.5, 1:0.74, and 1:1) were used to prepare orange oil-loaded nanofibers. The best encapsulation efficiency (69 and 52.6%) and oil content (34.45 and 26.26%) were observed at the ratio of 1:1 for both G and GT, respectively. The morphology and thermal properties of the electrospun fibers as well as the release and storage stability of loaded orange essential oil were investigated at the selected ratio. The results indicated that the fibrous structure of the orange essential oil-loaded samples was maintained. It is found that both G and GT provided suitable controlled release of orange essential oil and were successful in improving its storage stability.     

Accurate estimation of CO2 adsorption on activated carbon with multi-layer feed-forward neural network (MLFNN) algorithm

Global warming due to greenhouse effect has been considered as a serious problem for many years around the world. Among the different gases which cause greenhouse gas effect, carbon dioxide is of great difficulty by entering into the surrounding atmosphere. So CO₂ capturing and separation especially by adsorption is one of the most interesting approaches because of the low equipment cost, ease of operation, simplicity of design, and low energy consumption.In this study, experimental results are presented for the adsorption equilibria of carbon dioxide on activated carbon. The adsorption equilibrium data for carbon dioxide were predicted with two commonly used isotherm models in order to compare with multi-layer feed-forward neural network (MLFNN) algorithm for a wide range of partial pressure. As a result, the ANN-based algorithm shows much better efficiency and accuracy than the Sips and Langmuir isotherms. In addition, the applicability of the Sips and Langmuir models are limited to isothermal conditions, even though the ANN-based algorithm is not restricted to the constant temperature condition. Consequently, it is proved that MLFNN algorithm is a promising model for calculation of CO₂ adsorption density on activated carbon.     

Galerkin’s approach for buckling analysis of functionally graded anisotropic nanoplates/different boundary conditions

Engineering with Computers - For the first time, buckling behavior of functionally graded (FG) nanoplates made of anisotropic material (beryllium crystal as a hexagonal material) is investigated....     

A blind video watermarking algorithm robust to lossy video compression attacks based on generalized Newton complex map and contourlet transform

Multimedia Tools and Applications - The rapid growth of fast communication networks for digital video transmission has created a need to copyright protection for these media. Digital video can be...     

Optimisation of experimental conditions for binding of divalent iron to bioactive casein phosphopeptides

Casein phosphopeptides (CPPs) are mineral‐binding bioactive peptides derived from enzymatic digestion of casein. They have been shown to increase iron bioavailability due to increasing iron solubility at the alkaline pH of the intestine. Thus, they are potentially applicable as an advantageous preparation for iron fortification of food. This study aimed to characterise a commercially available CPP and determines optimum experimental conditions for binding it with ferrous iron. The effect of three variables – pH (5–7.5), mass ratio of iron to CPP (MR) (0.04–0.16) and holding time (40–80 min) – on the CPP's iron content was investigated using the central composite design (CCD) in response surface methodology (RSM), and a quadratic model was developed. The optimisation in this survey was based on the maximum response. Among all the regression's terms, the main and quadratic effects of pH represented the most significant influences on the iron content (P‐value <0.05). The obtained optimum conditions were as follows: pH 6.5, MR 0.14 and holding time 72 min, resulting in binding 68.66 mg iron per gram of the CPP. The quantity of iron bound to the CPP depended considerably on the experimental conditions and proved the importance of optimisation.     

Formulation of soil angle of shearing resistance using a hybrid GP and OLS method

In the present study, a prediction model was derived for the effective angle of shearing resistance (?′) of soils using a novel hybrid method coupling genetic programming (GP) and orthogonal least squares algorithm (OLS). The proposed nonlinear model relates ?′ to the basic soil physical properties. A comprehensive experimental database of consolidated-drained triaxial tests was used to develop the model. Traditional GP and least square regression analyses were performed to benchmark the GP/OLS model against classical approaches. Validity of the model was verified using a part of laboratory data that were not involved in the calibration process. The statistical measures of correlation coefficient, root mean squared error, and mean absolute percent error were used to evaluate the performance of the models. Sensitivity and parametric analyses were conducted and discussed. The GP/OLS-based formula precisely estimates the ?′ values for a number of soil samples. The proposed model provides a better prediction performance than the traditional GP and regression models.