• Genomics & Informatics
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• v.21 no.1
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• pp.3.1-3.10
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• 2023

Characterization as well as prediction of the secondary and tertiary structure of hypothetical proteins from their amino acid sequences uploaded in databases by in silico approach are the critical issues in computational biology. Severe acute respiratory syndrome-associated coronavirus (SARS-CoV), which is responsible for pneumonia alike diseases, possesses a wide range of proteins of which many are still uncharacterized. The current study was conducted to reveal the physicochemical characteristics and structures of an uncharacterized protein Q6S8D9_SARS of SARS-CoV. Following the common flowchart of characterizing a hypothetical protein, several sophisticated computerized tools e.g., ExPASy Protparam, CD Search, SOPMA, PSIPRED, HHpred, etc. were employed to discover the functions and structures of Q6S8D9_SARS. After delineating the secondary and tertiary structures of the protein, some quality evaluating tools e.g., PROCHECK, ProSA-web etc. were performed to assess the structures and later the active site was identified also by CASTp v.3.0. The protein contains more negatively charged residues than positively charged residues and a high aliphatic index value which make the protein more stable. The 2D and 3D structures modeled by several bioinformatics tools ensured that the proteins had domain in it which indicated it was functional protein having the ability to trouble host antiviral inflammatory cytokine and interferon production pathways. Moreover, active site was found in the protein where ligand could bind. The study was aimed to unveil the features and structures of an uncharacterized protein of SARS-CoV which can be a therapeutic target for development of vaccines against the virus. Further research are needed to accomplish the task.

• Genomics & Informatics
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• v.21 no.1
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• pp.9.1-9.13
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• 2023

Matrix metalloproteinase-9 (MMP-9) is a zinc and calcium-dependent proteolytic enzyme involved in extracellular matrix degradation. Overexpression of MMP-9 has been confirmed in several disorders, including cancers, Alzheimer's disease, autoimmune diseases, cardiovascular diseases, and dental caries. Therefore, MMP-9 inhibition is recommended as a therapeutic strategy for combating various diseases. Cinnamic acid derivatives have shown therapeutic effects in different cancers, Alzheimer's disease, cardiovascular diseases, and dental caries. A computational drug discovery approach was performed to evaluate the binding affinity of selected cinnamic acid derivatives to the MMP-9 active site. The stability of docked poses for top-ranked compounds was also examined. Twelve herbal cinnamic acid derivatives were tested for possible MMP-9 inhibition using the AutoDock 4.0 tool. The stability of the docked poses for the most potent MMP-9 inhibitors was assessed by molecular dynamics (MD) in 10 nanosecond simulations. Interactions between the best MMP-9 inhibitors in this study and residues incorporated in the MMP-9 active site were studied before and after MD simulations. Cynarin, chlorogenic acid, and rosmarinic acid revealed a considerable binding affinity to the MMP-9 catalytic domain (ΔG_binding < -10 kcal/ mol). The inhibition constant value for cynarin and chlorogenic acid were calculated at the picomolar scale and assigned as the most potent MMP-9 inhibitor from the cinnamic acid derivatives. The root-mean-square deviations for cynarin and chlorogenic acid were below 2 Å in the 10 ns simulation. Cynarin, chlorogenic acid, and rosmarinic acid might be considered drug candidates for MMP-9 inhibition.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2B
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• pp.121-129
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• 2009

In this study, dam-break flows are simulated numerically by using an efficient and accurate Cartesian cut-cell mesh system. In the system, most of the computational domain is discretized by the Cartesian mesh, while peculiar grids are done by a cutcell mesh system. The governing equations are then solved by the finite volume method. An HLLC approximate Riemann solver and TVD-WAF method are employed to calculation of advection flux of the shallow-water equations. To validate the numerical model, the model is applied to some problems such as a steady flow convergence on an ideal bed, a steady flow over an irregular bathymetry, and a rectangular tank problem. The present model is finally applied to a simulation of dam-break flow on an experimental channel. The predicted water surface elevations are compared with available laboratory measurements. A very reasonable agreement is observed.

• Structural Engineering and Mechanics
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• v.84 no.4
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• pp.489-502
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• 2022

This paper is aimed at developing an optimization-based Finite Element model updating approach for structural damage identification and quantification. A modal flexibility-based error function is introduced, which uses modal assurance criterion to formulate the updating problem as an optimization problem. Because of the inexplicit input/output relationship between the candidate solutions and the error function's output, a robust and efficient optimization algorithm should be employed to evaluate the solution domain and find the global extremum with high speed and accuracy. This paper proposes a new multi-stage Selective Particle Swarm Optimization (SPSO) algorithm to solve the optimization problem. The proposed multi-stage strategy not only fixes the premature convergence of the original Particle Swarm Optimization (PSO) algorithm, but also increases the speed of the search stage and reduces the corresponding computational costs, without changing or adding extra terms to the algorithm's formulation. Solving the introduced objective function with the proposed multi-stage SPSO leads to a smart feedback-wise and self-adjusting damage detection method, which can effectively assess the health of the structural systems. The performance and precision of the proposed method are verified and benchmarked against the original PSO and some of its most popular variants, including SPSO, DPSO, APSO, and MSPSO. For this purpose, two numerical examples of complex civil engineering structures under different damage patterns are studied. Comparative studies are also carried out to evaluate the performance of the proposed method in the presence of measurement errors. Moreover, the robustness and accuracy of the method are validated by assessing the health of a six-story shear-type building structure tested on a shake table. The obtained results introduced the proposed method as an effective and robust damage detection method even if the first few vibration modes are utilized to form the objective function.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.135-146
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• 2023

An effective educational program warrants the inclusion of an innovative construction which enhances the higher education efficacy in such a way that accelerates the achievement of desired results and reduces the risk of failures. Educational Decision Support System (EDSS) has currently been a hot topic in educational systems, facilitating the pupil result monitoring and evaluation to be performed during their development. Insufficient information systems encounter trouble and hurdles in making the sufficient advantage from EDSS owing to the deficit of accuracy, incorrect analysis study of the characteristic, and inadequate database. DMTs (Data Mining Techniques) provide helpful tools in finding the models or forms of data and are extremely useful in the decision-making process. Several researchers have participated in the research involving distributed data mining with multi-agent technology. The rapid growth of network technology and IT use has led to the widespread use of distributed databases. This article explains the available data mining technology and the distributed data mining system framework. Distributed Data Mining approach is utilized for this work so that a classifier capable of predicting the success of students in the economic domain can be constructed. This research also discusses the Intelligent Knowledge Base Distributed Data Mining framework to assess the performance of the students through a mid-term exam and final-term exam employing Multi-agent system-based educational mining techniques. Using single and ensemble-based classifiers, this study intends to investigate the factors that influence student performance in higher education and construct a classification model that can predict academic achievement. We also discussed the importance of multi-agent systems and comparative machine learning approaches in EDSS development.

• Biomolecules & Therapeutics
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• v.32 no.2
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• pp.214-223
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• 2024

Metabolic abnormalities in the liver are closely associated with diverse metabolic diseases such as non-alcoholic fatty liver disease, type 2 diabetes, and obesity. The aim of this study was to evaluate the ameliorating effect of robinetin (RBN) on the significant pathogenic features of metabolic failure in the liver and to identify the underlying molecular mechanism. RBN significantly decreased triglyceride (TG) accumulation by downregulating lipogenesis-related transcription factors in AML-12 murine hepatocyte cell line. In addition, mice fed with Western diet (WD) containing 0.025% or 0.05% RBN showed reduced liver mass and lipid droplet size, as well as improved plasma insulin levels and homeostatic model assessment of insulin resistance (HOMA-IR) values. CD38 was identified as a target of RBN using the BioAssay database, and its expression was increased in OPA-treated AML-12 cells and liver tissues of WD-fed mice. Furthermore, RBN elicited these effects through its anti-histone acetyltransferase (HAT) activity. Computational simulation revealed that RBN can dock into the HAT domain pocket of p300, a histone acetyltransferase, which leads to the abrogation of its catalytic activity. Additionally, knock-down of p300 using siRNA reduced CD38 expression. The chromatin immunoprecipitation (ChIP) assay showed that p300 occupancy on the promoter region of CD38 was significantly decreased, and H3K9 acetylation levels were diminished in lipid-accumulated AML-12 cells treated with RBN. RBN improves the pathogenic features of metabolic failure by suppressing the p300-CD38 axis through its anti-HAT activity, which suggests that RBN can be used as a new phytoceutical candidate for preventing or improving this condition.

• Steel and Composite Structures
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• v.51 no.1
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• pp.73-91
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• 2024

This paper has focused on presenting vibration analysis of trapezoidal sandwich plates with a damaged core and FG wavy CNT-reinforced face sheets. A damage model is introduced to provide an analytical description of an irreversible rheological process that causes the decay of the mechanical properties, in terms of engineering constants. An isotropic damage is considered for the core of the sandwich structure. The classical theory concerning the mechanical efficiency of a matrix embedding finite length fibers has been modified by introducing the tube-to-tube random contact, which explicitly accounts for the progressive reduction of the tubes' effective aspect ratio as the filler content increases. The First-order shear deformation theory of plate is utilized to establish governing partial differential equations and boundary conditions for the trapezoidal plate. The governing equations together with related boundary conditions are discretized using a mapping-generalized differential quadrature (GDQ) method in spatial domain. Then natural frequencies of the trapezoidal sandwich plates are obtained using GDQ method. Validity of the current study is evaluated by comparing its numerical results with those available in the literature. After demonstrating the convergence and accuracy of the method, different parametric studies for laminated trapezoidal structure including carbon nanotubes waviness (0≤w≤1), CNT aspect ratio (0≤AR≤4000), face sheet to core thickness ratio (0.1 ≤ ${\frac{h_f}{h_c}}$ ≤ 0.5), trapezoidal side angles (30° ≤ α, β ≤ 90°) and damaged parameter (0 ≤ D < 1) are carried out. It is explicated that the damaged core and weight fraction, carbon nanotubes (CNTs) waviness and CNT aspect ratio can significantly affect the vibrational behavior of the sandwich structure. Results show that by increasing the values of waviness index (w), normalized natural frequency of the structure decreases, and the straight CNT (w=0) gives the highest frequency. For an overall comprehension on vibration of laminated trapezoidal plates, some selected vibration mode shapes were graphically represented in this study.

• Journal of Educational Research in Mathematics
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• v.20 no.2
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• pp.163-183
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• 2010

It has long been of controversy what the meanings of probability is. And a century has past after the mathematical probability has been at the center of the school curriculum of it. Recently statistical meaning of probability becomes important for various reasons. However the simple modification of its definition is not enough. The computational reasoning of the probability and its practical application needs didactical changes and new instructional transformations along with the modification of it. Most of the current text books introduce probability as a limit of the relative frequencies, a statistical probability. But when the probability computation of the union of two events, or of the simultaneous events is faced on, they use mathematical probability for explanation and practices. Accordingly there is a gap for students in understanding those. Probability is an intuitive concept as far as it belongs to the domain of the experiential frequency. And frequency distribution must be the instructional bases for the (statistical) probability novices. This is what we mean by the probability in accordance with the distribution concepts. First of all, in order to explain the probability of the complementary event we should explain the empirical relative frequency of it first. These are the case for the union of two events and for the simultaneous events. Moreover we need to provide a logic of probabilistic guesses, inferences and decision, which we introduce with the name “the likelihood principle”, the most famous statistical principle. We emphasized this be done through the problems of practical decision making.

• Journal of the Korean Society of Groundwater Environment
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• v.6 no.1
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• pp.23-32
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• 1999

A new numerical method using solution-adaptive grids (SAG) is developed to solve the Richards' equation (RE) for unsaturated flow in porous media. Using a grid generation technique, the SAG method automatically redistributes a fixed number of grid points during the flow process, so that more grid points are clustered in regions of large solution gradients. The method uses the coordinate transformation technique to employ a new transformed RE, which is solved with the standard finite difference method. The movement of grid points is incorporated into the transformed RE, and therefore all computation is performed on fixed grid points of the transformed domain without using any interpolation techniques. Thus, numerical difficulties arising from the movement of the wetting front during the infiltration process have been substantially overcome by the new method. Numerical experiments for an one-dimensional infiltration problem are presented to compare the SAG method to the modified Picard method using a fixed grid. Results show that accuracy of a SAG solution using 41 nodes is comparable with the solution of the fixed grid method using 201 nodes, while it requires only 50% of the CPU time. The global mass balance and the convergence of SAG solutions are strongly affected by the time step size (Δt) and the weighting parameter (${\gamma}$) used for generating solution-adaptive grids. Thus, the method requires automated readjustment of Δt and ${\gamma}$ to yield mass-conservative and convergent solutions, although it may increase computational costs. The method can be effective especially for simulating unsaturated flow and other transport problems involving the propagation of a sharp-front.

• Journal of Navigation and Port Research
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• v.29 no.10 s.106
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• pp.853-858
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• 2005

Recently, various novel numerical models based on Navier-Stokes equation have been developed for calculating wave motions in the sea with coastal or ocean structures. Among those models, Volume Of Fluid (VOF) method might be the most popular one, and it has been used for numerical simulations of wave motions including complicated phenomena of wave breakings. VOF method, however, needs enormous computation time and large computational storage memories in general, thus it is practically difficult to use this method for calculations in the case of random waves because long and stable computation (e.g for more than 100 significant wave periods) is required to obtain statistically meaningful results. On the other hand if the wave motion is potential motion, Boundary Element Method (BEM), which is a much faster and more accurate method than VOF method, can be effectively used. The aim of this study is to develop a new efficient model applicable to calculations of wave motion and/or wave-structure interactions under random waves. To achieve this, a strictly combined BEM-VOF model has been developed by making the best use of both methods' merits; VOF method is used in a restricted fluid domain around a structure where complicated phenomena of wave breakings may exist, and BEM is used in the other domains far from the disturbance where the wave motion may be assumed to be potential. The verification of the model was performed with numerical results for Stokes' 5th order wave propagation and a random wave propagation.