• Molecules and Cells
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• v.42 no.7
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• pp.512-522
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• 2019

Chromosomes located in the nucleus form discrete units of genetic material composed of DNA and protein complexes. The genetic information is encoded in linear DNA sequences, but its interpretation requires an understanding of three-dimensional (3D) structure of the chromosome, in which distant DNA sequences can be juxtaposed by highly condensed chromatin packing in the space of nucleus to precisely control gene expression. Recent technological innovations in exploring higher-order chromatin structure have uncovered organizational principles of the 3D genome and its various biological implications. Very recently, it has been reported that large-scale genomic variations may disrupt higher-order chromatin organization and as a consequence, greatly contribute to disease-specific gene regulation for a range of human diseases. Here, we review recent developments in studying the effect of structural variation in gene regulation, and the detection and the interpretation of structural variations in the context of 3D chromatin structure.

• Smart Structures and Systems
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• v.14 no.3
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• pp.347-365
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• 2014

The main objective of this paper is to develop an innovative methodology for the vibration suppression control of the multiple degrees-of-freedom (MDOF) flexible structure. The proposed structure represented in this research as a clamped-free-free-free truss type plate is rotated by motors. The controller has two loops for tracking and vibration suppression. In addition to stabilizing the actual system, the proposed feedback control is based on a genetic algorithm (GA) to seek the primary optimal control gain for tracking and stabilization purposes. Moreover, input shaping is introduced for the control scheme that limits motion-induced elastic vibration by shaping the reference command. Experimental results are presented, demonstrating that, in the control loop, roll and yaw angles track control and elastic mode stabilization. It was also demonstrated that combining the input shaper with the proportional-integral-derivative (PID) feedback method has been shown to yield improved performance in controlling the flexible structure system. The broad range of problems discussed in this research is valuable in civil, mechanical, and aerospace engineering for flexible structures with MDOM motion.

• Journal of the Korean Geotechnical Society
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• v.21 no.9
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• pp.25-34
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• 2005

This paper proposes a selection methodology composed of neural network (NN) and genetic algorithm (GA) to design optimal NN structure. We combine the characteristics of GA and NN to reduce the computational complexity of artificial intelligence applications and increase the precision of NN' prediction in the design of NN structure. Genetic selection approach of design parameters of NN is introduced to obtain optimal NN structure. Analyzed results for geotechnical problems are given to evaluate the performance of the proposed hybrid methodology.

• Structural Engineering and Mechanics
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• v.30 no.2
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• pp.135-146
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• 2008

This study utilizes the fine-tuning and small-digit characteristics of the successive zooming genetic algorithm (SZGA) to propose a method of structural damage detection in a continuum structure, where the differences in the natural frequencies of a structure obtained by experiment and FEM are compared and minimized using an assumed location and extent of structural damage. The final methodology applied to the structural damage detection is a kind of pseudo-discrete-variable-algorithm that counts the soundness variables as one (perfectly sound) if they are above a certain standard, such as 0.99. This methodology is based on the fact that most well-designed structures exhibit failures at some critical point due to manufacturing error, while the remaining region is free of damage. Thus, damage of 1% (depending on the given standard) or less can be neglected, and the search concentrated on finding more serious failures. It is shown that the proposed method can find out the exact structural damage of the monitored structure and reduce the time and amount of computation.

• Smart Structures and Systems
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• v.15 no.1
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• pp.227-244
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• 2015

This study develops a two stage procedure to identify the structural damage based on the optimized artificial neural networks. Initially, the modal strain energy index (MSEI) is established to extract the damaged elements and to reduce the computational time. Then the genetic algorithm (GA) and artificial neural networks (ANNs) are combined to detect the damage severity. The input of the network is modal strain energy index and the output is the flexural stiffness of the beam elements. The principal component analysis (PCA) is utilized to reduce the input variants of the neural network. By using the genetic algorithm to optimize the parameters, the ANNs can significantly improve the accuracy and convergence of the damage identification. The influence of noise on damage identification results is also studied. The simulation and experiment on beam structures shows that the adaptive parameter selection neural network can identify the damage location and severity of beam structures with high accuracy.

• Structural Engineering and Mechanics
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• v.81 no.6
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• pp.677-689
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• 2022

Generally, the goal of seismic retrofit design of an existing structure using energy dissipation devices is to determine the optimum design parameters of a retrofit device to satisfy a specified limit state with minimum cost. However, the presence of multiple parameters to be optimized and the computational complexity of performing non-linear analysis make it difficult to find the optimal design parameters in the realistic 3D structure. In this study, genetic algorithm-based optimal seismic retrofit methods for determining the required number, yield strength, and location of steel slit dampers are proposed to retrofit an asymmetric soft first-story structure. These methods use a multi-objective and single-objective evolutionary algorithms, each of which varies in computational complexity and incorporates nonlinear time-history analysis to determine seismic performance. Pareto-optimal solutions of the multi-objective optimization are found using a non-dominated sorting genetic algorithm (NSGA-II). It is demonstrated that the developed multi-objective optimization methods can determine the optimum number, yield strength, and location of dampers that satisfy the given limit state of a three-dimensional asymmetric soft first-story structure. It is also shown that the single-objective distribution method based on minimizing plan-wise stiffness eccentricity turns out to produce similar number of dampers in optimum locations without time consuming nonlinear dynamic analysis.

• Structural Engineering and Mechanics
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• v.87 no.3
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• pp.211-219
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• 2023

The structural health of a pipeline is usually assessed by visual inspection. In addition to the fact that this method is expensive and time consuming, inspection of the whole structure is not possible due to limited access to some points. Therefore, adopting a damage detection method without the mentioned limitations is important in order to increase the safety of the structure. In recent years, vibration-based methods have been used to detect damage. These methods detect structural defects based on the fact that the dynamic responses of the structure will change due to damage existence. Therefore, the location and extent of damage, before and after the damage, are determined. In this study, fuzzy genetic algorithm has been used to monitor the structural health of the pipeline to create a fuzzy automated system and all kinds of possible failure scenarios that can occur for the structure. For this purpose, the results of an experimental model have been used. Its numerical model is generated in ABAQUS software and the results of the analysis are used in the fuzzy genetic algorithm. Results show that the system is more accurate in detecting high-intensity damages, and the use of higher frequency modes helps to increase accuracy. Moreover, the system considers the damage in symmetric regions with the same degree of membership. To deal with the uncertainties, some error values are added, which are observed to be negligible up to 10% of the error.

• Journal of Microbiology and Biotechnology
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• v.13 no.2
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• pp.182-190
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• 2003

A new phaC gene cluster encoding polyhydroxyalkanoate (PHA) synthase I PHA depolymerase, and PHA synthase II was cloned using the touchdown PCR method, from medium-chain length (mcl-) PHA-producing strain Pseudomonas putida KT2440. The molecular structure of the cloned phaCl gene was analyzed, and the phylogenic relationship was compared with other phaCl genes cloned from Pseudomonas species. The cloned phaCl gene was expressed in a recombinant E. coli to the similar level of PHA synthase in the parent strain P. putida KT2440, but no significant amount of mcl-PHA was accumulated. The isolated phaCl gene was re-introduced into the parent strain P. putida KT2440 to amplify the PHA synthase I activity, and the recombinant P. purida accumulated mcl-PHA more effectively, increasing from 26.6 to $43.5\%$. The monomer compositions of 3-hydroxylalkanoates in mcl-PHA were also modified significantly in the recombinant P. putida enforcing the cloned phaCl gene.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1322-1327
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• 2003

It is important to determine supporting locations for structural stability of a structure under non-uniform load in space interfered by other parts. In this case, There are many local optima with discontinuous design space. Therefore, The traditional optimization methods based on derivative are not suitable. Whereas, Genetic algorithm(GA) based on stochastic search technique is a very robust and general method. This paper has been presented to determine supporting locations of the vertical supports for reducing stress of the KSTAR(Korea super Superconducting Tokamak Advanced Research) IVCC(In-vessel control coil) under non-uniform electromagnetic load and space interfered by other parts using genetic algorithm. For this study, we develop a program combining finite element analysis with a genetic algorithm to perform structural analysis of IVCC. In addition, this paper presents a technique to perform optimization with FEM when design variables are trapped in an incongruent design space.

• Weed & Turfgrass Science
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• v.3 no.3
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• pp.190-195
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• 2014

Echinochloa (L.) P. Beauv. includes some of the noxious weeds, causing a serious yield loss when they are dominant in the fields. Identification of the Echinochloa is very difficult because many interspecific and intraspecific forms of the species are found. However, it is important to identify the species exactly and to know the genetic diversity of the species for effective weed management. This study was conducted to identify and summarize the Echinochloa species by comparing the genetic variation and relationship among Korean Echinochloa species using SSR. The genetic diversity of 107 individuals, including seven species were assessed using five SSR markers. UPGMA dendrogram generated two clades (I and II) and clade II divided again into two subclades (II-1 and II-2) whereas the model based genetic structure proposed four subpopulations. The two subpopulations were corresponded to clades I and II-1 and the other two were arranged to clade II-2 of the UPGMA dendrogram. We have concluded that E. colona and E. glabrescens might have not distributed in Korea. The biological varieties, praticola and echinata, of E. crus-galli should be treated as E. crus-galli. Korean Echinochloa should be summarized with four species, i.e., E. oryzicola, E. crus-galli, E. esculenta, and E. oryzoides.