• Food Science of Animal Resources
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• v.42 no.2
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• pp.321-331
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• 2022

Egg yolk is widely used to extract lecithin, which is utilized in the food and cosmetics industry. After lecithin is removed, the rest of egg yolk is generated as a by-product. Thus, it is necessary to properly utilize it. In this study, egg yolk protein extracts were produced using ethanol (EYE-E) and water (EYE-W). Their antioxidant and immunomodulatory effects were then evaluated. Antioxidant activities of EYE-E and EYE-W were determined using cellular antioxidant capacity (CAC) assay and comet assay. EYE-E and EYE-W showed significant (p<0.05) scavenging effects on intracellular reactive oxygen species (ROS) in a dose dependent manner. At a concentration of 50 ㎍/mL, EYE-W showed higher (p<0.05) antioxidant activity than EYE-E. EYE-E and EYE-W also exhibited protective effects against DNA damage caused by oxidative stress. After treatment with EYE-E and EYE-W, DNA damage level of 48.7% due to oxidative stress was decreased to 36.2% and 31.8% levels, respectively. In addition, EYE-E and EYE-W showed immunomodulatory effects by regulating Th1 cytokines (TNF-α and IL-2) and Th2 cytokines (IL-10 and IL-4) in Balb/c mouse splenocytes. These data suggest that EYE-E and EYE-W could be used as functional food ingredients with excellent antioxidant and immunomodulatory activities in the food industry.

• Computers and Concrete
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• v.32 no.1
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• pp.1-13
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• 2023

This paper discusses a framework for predicting the flexural strength of prestressed and non-prestressed FRP reinforced T-shaped concrete beams using soft computing techniques. An analysis of 83 tests performed on T-beams of varying widths has been conducted for this purpose with different widths of compressive face, beam depth, compressive strength of concrete, area of prestressed and non-prestressed FRP bars, elasticity modulus of prestressed and non-prestressed FRP bars, and the ultimate tensile strength of prestressed and non-prestressed FRP bars. By analyzing the data using two soft computing techniques, named artificial neural networks (ANN) and gene expression programming (GEP), the fundamental parameters affecting the flexural performance of prestressed and non-prestressed FRP reinforced T-shaped beams were identified. The results showed that although the proposed ANN model outperformed the GEP model with higher values of R and lower error values, the closed-form equation of the GEP model can provide a simple way to predict the effect of input parameters on flexural strength as the output. The sensitivity analysis results revealed the most influential input parameters in ANN and GEP models are respectively the beam depth and elasticity modulus of FRP bars.

• Computers and Concrete
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• v.32 no.1
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• pp.27-44
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• 2023

The current study targets to apply the adaptive neuro-fuzzy inference system (ANFIS) for the estimation of the shear resistance offered by the externally bonded fiber-reinforced polymer (EB-FRP) U-jackets. A total of 202 groups of data cumulated from previous investigations, were employed for the development and evaluation of the ANFIS model. A relative appraisal between the ANFIS predictions and the results of experiments has shown that the assessments by current ANFIS model are in good concurrence with the latter. In addition, assessment of the accuracy of the ANFIS model was done by relating the ANFIS predictions with the forecasts of eight extensively used design guidelines. Based on the examination of various performance measures, it has been derived that the adequacy of the ANFIS model is better than the available guidelines. A parametric investigation has additionally been done to reconnoiter the influence of individual parameters as well as their combined effects on the shear contribution of EB-FRP. Based on the observations made from the parametric study, it has been witnessed that the ANFIS model has incorporated the effect of different parameters more competently than the considered design guidelines.

• Computers and Concrete
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• v.32 no.1
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• pp.45-60
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• 2023

Concrete in water environment is easily subjected to the attack of leaching, which causes its mechanical reduction and durability deterioration, and the key to improving the leaching resistance of concrete is to increase the compaction of its microstructure formed by the curing. This paper performs a numerical investigation on the intrinsic relationship between microstructures formed by the hydration of cement and slag and leaching resistance of concrete in water environment. Firstly, a shrinking-core hydration model of blended cement and slag is presented, in which the interaction of hydration process of cement and slag is considered and the microstructure composition is characterized by the hydration products, solution composition and pore structure. Secondly, based on Fick's law and mass conservation law, a leaching model of hardened paste is proposed, in which the multi-species ionic diffusion equation and modified Gérard model are established, and the model is numerically solved by applying the finite difference method. Finally, two models are combined by microstructure composition to form an integrated curing-leaching model, and it is used to investigate the relationship between microstructure composition and leaching resistance of slag-blended cement pastes.

• Computers and Concrete
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• v.32 no.1
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• pp.87-97
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• 2023

The bending of a porous FG plate is discussed in this study using a novel higher quasi-3D hyperbolic shear deformation theory with four unknowns. The proposed theory takes into consideration the normal and transverse shear deformation effect and ensures the parabolic distribution of the transverse stresses through the thickness direction with zero-traction at the top and the bottom surfaces of the structure. Innovative porous functionally graded materials (FGM) have through-thickness porosity as a unique attribute that gradually varies with their qualities. An analytical solution of the static response of the perfect and imperfect FG plate was derived based on the virtual work principle and solved using Navier's procedure. The validity and the efficiency of the current model is confirmed by comparing the results with those obtained by others solutions. The comparisons showed that the present model is very efficient and simple in terms of computation time and exactness. The impact of the porosity parameter, aspect ratio, and thickness ratio on the bending of porous FG plate is shown through a discussion of several numerical results.

• Computers and Concrete
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• v.30 no.5
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• pp.323-337
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• 2022

This paper proposes a numerical model to simulate the rotational behavior of steel fiber in fresh cement-based materials in the presence of a magnetic field. The results indicate that as the aspect ratio of fiber increases, the required minimum magnetic field intensity to make fiber rotate in viscous fluid increases. The optimal magnetic field intensity is 0.03 T for aligning steel fiber in fresh cement-based materials to ensure that the applying time of the magnetic field can be conducted concurrently with the vibrating process to increase the aligning efficiency. The orientation factor of steel fiber in cement mortar can exceed 0.85 after aligning by 0.03 T of the uniform magnetic field. When the initial angle of the fiber to the magnetic field direction is less than 10°, the magnetic field less than 0.03 T cannot make the fiber overcome the yield stress of fluid to rotate. The coarse aggregate in steel fiber-reinforced concrete is detrimental to the rotation and alignment of the steel fiber. But the orientation factor of ASFRC under the 0.03T of the magnetic field can also exceed 0.8, while the orientation factor of SFRC without magnetic field application is around 0.6.

• Computers and Concrete
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• v.32 no.4
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• pp.365-371
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• 2023

On the basis of Flügge shell theory, the vibrations of single walled carbon nanotubes (SWCNTs) are investigated. The structure of armchair single walled carbon nanotubes are used here. Influences of length-to-diameter ratios and the two boundary conditions on the natural frequencies of armchair SWCNTs are examined. The Rayleigh-Ritz method is employed to determine eigen frequencies for single walled carbon nanotubes. The solution is obtained using the geometric characteristics and boundary conditions for natural frequencies of SWCNTs. The natural frequencies decrease as ratio of length to diameter increase and the effect of frequencies is less significant and more prominent for long tube. To assess the frequency confirmation carried out in this paper are compared with the earlier computations.

• Computers and Concrete
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• v.32 no.4
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• pp.373-381
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• 2023

Fly ash, granulated blast furnace slag, marble waste powder, etc. are just some of the by-products of other sectors that the construction industry is looking to include into the many types of concrete they produce. This research seeks to use surrogate machine learning methods to forecast the compressive strength of self-compacting concrete. The surrogate models were developed using Gradient Boosting Machine (GBM), Support Vector Machine (SVM), Random Forest (RF), and Gaussian Process Regression (GPR) techniques. Compressive strength is used as the output variable, with nano silica content, cement content, coarse aggregate content, fine aggregate content, superplasticizer, curing duration, and water-binder ratio as input variables. Of the four models, GBM had the highest accuracy in determining the compressive strength of SCC. The concrete's compressive strength is worst predicted by GPR. Compressive strength of SCC with nano silica is found to be most affected by curing time and least by fine aggregate.

• Computers and Concrete
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• v.32 no.4
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• pp.399-410
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• 2023

This study proposes a novel use of backpropagated Levenberg-Marquardt neural networks based on computational intelligence heuristics to comprehend the examination of hybrid nanoparticles on the flow of dusty liquid via stretched cylinder. A two-phase model is employed in the present work to describe the fluid flow. The use of desulphated nanoparticles of silver and molybdenum suspended in water as base fluid. The mathematical model represented in terms of partial differential equations, Implementing similarity transformationsis model is converted to ordinary differential equations for the analysis . By adjusting the particle mass concentration and curvature parameter, a unique technique is utilized to generate a dataset for the proposed Levenberg-Marquardt neural networks in various nanoparticle circumstances on the flow of dusty liquid via stretched cylinder. The intelligent solver Levenberg-Marquardt neural networks is trained, tested and verified to identify the nanoparticles on the flow of dusty liquid solution for various situations. The Levenberg-Marquardt neural networks approach is applied for the solution of the hybrid nanoparticles on the flow of dusty liquid via stretched cylinder model. It is validated by comparison with the standard solution, regression analysis, histograms, and absolute error analysis. Strong agreement between proposed results and reference solutions as well as accuracy provide an evidence of the framework's validity.

• Computers and Concrete
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• v.32 no.4
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• pp.393-398
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• 2023

This paper provides the free vibrations of chiral carbon nanotubes. The governing equations of Flügge theory is considered for vibration frequencies of chiral single walled carbon nanotubes. The solution of frequency equation is obtained from a novel model for better representation of stubby and short vibration characteristics of chiral tubes with clamped-clamped and clamped-simply supported end conditions. For the harmonic response of this tube, the model displacement function is adopted. The variational approach Rayleigh-Ritz method with kinetic and strain energies are used. The Lagragian function is differentiated with respect to unknown functions. The frequency equation is written in compact form to solve with MATLAB software. The frequencies of chiral SWCNTs for first ten aspect ratios as small level are investigated. The results shown as for decreasing the aspect rations, the frequencies are increases. The presented results of this model are verified with experimental and numerical results, which found as an excellent agreement.