• Nutrition Research and Practice
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• v.13 no.4
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• pp.333-343
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• 2019

BACKGROUND/OBJECTIVES: To compare five indices of adherence to the Mediterranean Diet (MD) among adults living in the Mediterranean region. SUBJECTS/METHODS: A total of 100 healthy Lebanese adults aged between 18 and 65 years. Face-to-face interviews to collect sociodemographic and medical information, to take anthropometric measurements, and to fill a validated, culturally adapted, food frequency questionnaire (FFQ). The score for each item was calculated following the recommendations for each corresponding index. The five MD indices were Mediterranean Diet Scale (MDScale), Mediterranean Food Pattern (MFP), MD Score (MDS), Short Mediterranean Diet Questionnaire (SMDQ), and the MedDiet score. RESULTS: Significant correlations were detected between items with P-values < 0.001. Minimal agreement was seen between MDScale and MedDiet score and maximal agreement between MDS and MedDiet score. Univariate and multivariate analyses showed that MDS and MedDiet scores had significant correlations with fiber and olive oil intake, main components of the MD. MDScale showed a significant correlation with waist-to-hip ratio and with total energy intake but none of the five indices was correlated to body mass index (BMI). CONCLUSIONS: The indices that showed the highest correlation with variables related to the MD are the MDScale and the MedDiet score; therefore, they can be used to assess our future study populations. Based on the current results, more than half of the study population was non-adherent to the MD and adherence to this diet did not appear to protect against being overweight ($BMI{\geq}30$).

• Geomechanics and Engineering
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• v.31 no.6
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• pp.545-556
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• 2022

Evaluation and optimization of tunnel wall convergence (TWC) plays a vital role in preventing potential problems during tunnel construction and utilization stage. When convergence occurs at a high rate, it can lead to significant problems such as reducing the advance rate and safety, which in turn increases operating costs. In order to design an effective solution, it is important to accurately predict the degree of TWC; this can reduce the level of concern and have a positive effect on the design. With the development of soft computing methods, the use of deep learning algorithms and neural networks in tunnel construction has expanded in recent years. The current study aims to employ the long-short-term memory (LSTM) deep neural network predictor model to predict the TWC, based on 550 data points of observed parameters developed by collecting required data from different tunnelling projects. Among the data collected during the pre-construction and construction phases of the project, 80% is randomly used to train the model and the rest is used to test the model. Several loss functions including root mean square error (RMSE) and coefficient of determination (R²) were used to assess the performance and precision of the applied method. The results of the proposed models indicate an acceptable and reliable accuracy. In fact, the results show that the predicted values are in good agreement with the observed actual data. The proposed model can be considered for use in similar ground and tunneling conditions. It is important to note that this work has the potential to reduce the tunneling uncertainties significantly and make deep learning a valuable tool for planning tunnels.

• Steel and Composite Structures
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• v.47 no.2
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• pp.147-165
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• 2023

The paper contrasts conventional seismic design with a design that incorporates buckling-restrained bracing in three-dimensional reinforced concrete buildings (BRBs). The suboptimal structures may be found using the multi-objective chimp optimization algorithm (MEN-ChOA). Given the constraints and dimensions, ChOA suffers from a slow convergence rate and tends to become stuck in local minima. Therefore, the ChOA is improved by niching and evolutionary operators to overcome the aforementioned problems. In addition, a new technique is presented to compute seismic and dead loads that include all of a structure's parts in an algorithm for three-dimensional frame design rather than only using structural elements. The performance of the constructed multi-objective model is evaluated using 12 standard multi-objective benchmarks proposed in IEEE congress on evolutionary computation. Second, MEN-ChOA is employed in constructing several reinforced concrete structures by the Mexico City building code. The variety of Pareto optimum fronts of these criteria enables a thorough performance examination of the MEN-ChOA. The results also reveal that BRB frames with comparable structural performance to conventional moment-resistant reinforced concrete framed buildings are more cost-effective when reinforced concrete building height rises. Structural performance and building cost may improve by using a nature-inspired strategy based on MEN-ChOA in structural design work.

• Geomechanics and Engineering
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• v.30 no.6
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• pp.489-502
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• 2022

In this study, a Gaussian process regression (GPR) model as well as six GPR-based metaheuristic optimization models, including GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, and GPR-SSO, were developed to predict fly-rock distance in the blasting operation of open pit mines. These models included GPR-SCA, GPR-SSO, GPR-MVO, and GPR. In the models that were obtained from the Soungun copper mine in Iran, a total of 300 datasets were used. These datasets included six input parameters and one output parameter (fly-rock). In order to conduct the assessment of the prediction outcomes, many statistical evaluation indices were used. In the end, it was determined that the performance prediction of the ML models to predict the fly-rock from high to low is GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, GPR-SSO, and GPR with ranking scores of 66, 60, 54, 46, 43, 38, and 30 (for 5-fold method), respectively. These scores correspond in conclusion, the GPR-PSO model generated the most accurate findings, hence it was suggested that this model be used to forecast the fly-rock. In addition, the mutual information test, also known as MIT, was used in order to investigate the influence that each input parameter had on the fly-rock. In the end, it was determined that the stemming (T) parameter was the most effective of all the parameters on the fly-rock.

• Wind and Structures
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• v.34 no.2
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• pp.231-257
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• 2022

Transmission lines systems are important components of the electrical power infrastructure. However, these systems are vulnerable to damage from high wind events such as hurricanes. This study presents the results from a 1:50 scale aeroelastic model of a multi-span transmission lines system subjected to simulated hurricane winds. The transmission lines system considered in this study consists of three lattice towers, four spans of conductors and two end-frames. The aeroelastic tests were conducted at the NSF NHERI Wall of Wind Experimental Facility (WOW EF) at the Florida International University (FIU). A horizontal distortion scaling technique was used in order to fit the entire model on the WOW turntable. The system was tested at various wind speeds ranging from 35 m/s to 78 m/s (equivalent full-scale speeds) for varying wind directions. A system identification (SID) technique was used to evaluate experimental-based along-wind aerodynamic damping coefficients and compare with their theoretical counterparts. Comparisons were done for two aeroelastic models: (i) a self-supported lattice tower, and (ii) a multi-span transmission lines system. A buffeting analysis was conducted to estimate the response of the conductors and compare it to measured experimental values. The responses of the single lattice tower and the multi-span transmission lines system were compared. The coupling effects seem to drastically change the aerodynamic damping of the system, compared to the single lattice tower case. The estimation of the drag forces on the conductors are in good agreement with their experimental counterparts. The incorporation of the change in turbulence intensity along the height of the towers appears to better estimate the response of the transmission tower, in comparison with previous methods which assumed constant turbulence intensity. Dynamic amplification factors and gust effect factors were computed, and comparisons were made with code specific values. The resonance contribution is shown to reach a maximum of 18% and 30% of the peak response of the stand-alone tower and entire system, respectively.

• Anatomy and Cell Biology
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• v.56 no.2
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• pp.219-227
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• 2023

Adult neurogenesis has been reported in the hypothalamus, subventricular zone and subgranular zone in the hippocamp. Recent studies indicated that new cells in the hypothalamus are affected by diet. We previously showed beneficial effects of safflower seed oil (SSO), a rich source of linoleic acid (LA; 74%), on proliferation and differentiation of neural stem cells (NSCs) in vitro. In this study, the effect of SSO on hypothalamic neurogenesis was investigated in vivo, in comparison to synthetic LA. Adult mice were treated with SSO (400 mg/kg) and pure synthetic LA (300 mg/kg), at similar concentrations of LA, for 8 weeks and then hypothalamic NSCs were cultured and subsequently used for Neurosphere-forming assay. In addition, serum levels of brain-derived neurotrophic factor (BNDF) were measured using enzyme-linked immunosorbent assay. Administration of SSO for 8 weeks in adult mice promoted the proliferation of NSCs isolated from SSO-treated mice. Immunofluorescence staining of the hypothalamus showed that the frequency of astrocytes (glial fibrillary acidic protein⁺ cells) are not affected by LA or SSO. However, the frequency of immature (doublecortin⁺ cells) and mature (neuronal nuclei⁺ cells) neurons significantly increased in LA- and SSO-treated mice, compared to vehicle. Furthermore, both LA and SSO caused a significant increase in the serum levels of BDNF. Importantly, SSO acted more potently than LA in all experiments. The presence of other fatty acids in SSO, such as oleic acid and palmitic acid, suggests that they could be responsible for SSO positive effect on hypothalamic proliferation and neurogenesis, compared to synthetic LA at similar concentrations.

• Advances in nano research
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• v.16 no.5
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• pp.509-519
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• 2024

In this study, the static analysis of carbon nanotube-reinforced composites (CNTRC) beams resting on a Winkler-Pasternak elastic foundation is presented. The developed theories account for higher-order variation of transverse shear strain through the depth of the beam and satisfy the stress-free boundary conditions on the top and bottom surfaces of the beam. To study the effect of carbon nanotubes distribution in functionally graded (FG-CNT), we introduce in the equation of CNT volume fraction a new exponent equation. The SWCNTs are assumed to be aligned and distributed in the polymeric matrix with different patterns of reinforcement. The rule of mixture is used to describe the material properties of the CNTRC beams. The governing equations were derived by employing Hamilton's principle. The models presented in this work are numerically provided to verify the accuracy of the present theory. The analytical solutions are presented, and the obtained results are compared with the existing solutions to verify the validity of the developed theories. Many parameters are investigated, such as the Pasternak shear modulus parameter, the Winkler modulus parameter, the volume fraction, and the order of the exponent in the volume fraction equation. New results obtained from bending and stresses are presented and discussed in detail. From the obtained results, it became clear the influence of the exponential CNTs distribution and Winkler-Pasternak model improved the mechanical properties of the CNTRC beams.

• Structural Engineering and Mechanics
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• v.90 no.3
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• pp.233-252
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• 2024

This research explores a new finite element model for the free vibration analysis of bi-directional functionally graded (BDFG) beams. The model is based on an efficient higher-order shear deformation beam theory that incorporates a trigonometric warping function for both transverse shear deformation and stress to guarantee traction-free boundary conditions without the necessity of shear correction factors. The proposed two-node beam element has three degrees of freedom per node, and the inter-element continuity is retained using both C1 and C0 continuities for kinematics variables. In addition, the mechanical properties of the (BDFG) beam vary gradually and smoothly in both the in-plane and out-of-plane beam's directions according to an exponential power-law distribution. The highly elevated performance of the developed model is shown by comparing it to conceptual frameworks and solution procedures. Detailed numerical investigations are also conducted to examine the impact of boundary conditions, the bi-directional gradient indices, and the slenderness ratio on the free vibration response of BDFG beams. The suggested finite element beam model is an excellent potential tool for the design and the mechanical behavior estimation of BDFG structures.

• Geomechanics and Engineering
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• v.37 no.5
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• pp.453-465
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• 2024

This paper presents a logarithmic shear deformation theory to study the thermal buckling response of power-law FG one-dimensional structures in thermal conditions with different boundary conditions. It is assumed that the functionally graded material and thermal properties are supposed to vary smoothly according to a contentious function across the vertical direction of the beams. A P-FG type function is employed to describe the volume fraction of material and thermal properties of the graded (1D) beam. The Ritz model is employed to solve the thermal buckling problems in immovable boundary conditions. The outcomes of the stability analysis of FG beams with temperature-dependent and independent properties are presented. The effects of the thermal loading are considered with three forms of rising: nonlinear, linear and uniform. Numerical results are obtained employing the present logarithmic theory and are verified by comparisons with the other models to check the accuracy of the developed theory. A parametric study was conducted to investigate the effects of various parameters on the critical thermal stability of P-FG beams. These parameters included support type, temperature fields, material distributions, side-to-thickness ratios, and temperature dependency.

• Structural Engineering and Mechanics
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• v.91 no.1
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• pp.1-23
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• 2024

This paper formulates a new integral shear deformation shell theory to investigate the free vibration response of carbon nanotube (CNT) reinforced structures with only four independent variables, unlike existing shell theories, which invariably and implicitly induce a host of unknowns. This approach guarantees traction-free boundary conditions without shear correction factors, using a non-polynomial hyperbolic warping function for transverse shear deformation and stress. By introducing undetermined integral terms, it will be possible to derive the motion equations with a low order of differentiation, which can facilitate a closed-form solution in conjunction with Navier's procedure. The mechanical properties of the CNT reinforcements are modeled to vary smoothly and gradually through the thickness coordinate, exhibiting different distribution patterns. A comparison study is performed to prove the efficacy of the formulated shell theory via obtained results from existing literature. Further numerical investigations are current and comprehensive in detailing the effects of CNT distribution patterns, volume fractions, and geometrical configurations on the fundamental frequencies of CNT-reinforced nanocomposite shells present here. The current shell theory is assumed to serve as a potent conceptual framework for designing reinforced structures and assessing their mechanical behavior.