• The Korea Journal of Herbology
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• v.28 no.5
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• pp.1-6
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• 2013

Objectives : This study was conducted to identify the original Sinomini Caulis et Rhizoma plant among Stephania tetrandra, Cocculus trilobus, and Aristolochiae fangchi to develop the genetic marker for Sinomini Caulis et Rhizoma. Methods : Sinomenium acutum was identified by the classification and identification committee of the National Center for Standardization of Herbal Medicines. The chloroplast ndhF gene was amplified. We performed sequences alignment analysis of Sinomenium acutum, Stephania tetrandra, C. trilobus, and A. fangchi using BioEdit program. The SFR markers designed were consisted of SF01, SR04, and SR05 primers. Results : Many variations of Sinomeni Caulis et Rhizoma are currently commercialized as herbal medicine. We compared the base sequences of the ndhF intergenic space of chloroplast DNA with Sinomenium acutum, Stephania tetrandra, C. trilobus, and A. fangchi. According to the results, it showed that the nucleotide variations were seen in 30 genes of four species. Phylogenetic analysis revealed that 4 species were classified into five groups based on an inter-group divergence in nucleotide sequence of 9%. We developed SFR marker nucleotides enough to authenticate respective species and confirmed its application on the band size at 419 base pair. These sequence differences at corresponding positions were available genetic markers to identity the Sinomeni Caulis et Rhizoma. Conclusions : Base on these results, the ndhF region was effective in distinguishing Sinomini Caulis et Rhizoma The SFR genetic marker was useful for identifying Sinomini Caulis et Rhizoma with other species.

• Genomics & Informatics
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• v.21 no.3
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• pp.36.1-36.19
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• 2023

The LIM domain-containing proteins are dominantly found in plants and play a significant role in various biological processes such as gene transcription as well as actin cytoskeletal organization. Nevertheless, genome-wide identification as well as functional analysis of the LIM gene family have not yet been reported in the economically important plant sorghum (Sorghum bicolor L.). Therefore, we conducted an in silico identification and characterization of LIM genes in S. bicolor genome using integrated bioinformatics approaches. Based on phylogenetic tree analysis and conserved domain, we identified five LIM genes in S. bicolor (SbLIM) genome corresponding to Arabidopsis LIM (AtLIM) genes. The conserved domain, motif as well as gene structure analyses of the SbLIM gene family showed the similarity within the SbLIM and AtLIM members. The gene ontology (GO) enrichment study revealed that the candidate LIM genes are directly involved in cytoskeletal organization and various other important biological as well as molecular pathways. Some important families of regulating transcription factors such as ERF, MYB, WRKY, NAC, bZIP, C2H2, Dof, and G2-like were detected by analyzing their interaction network with identified SbLIM genes. The cis-acting regulatory elements related to predicted SbLIM genes were identified as responsive to light, hormones, stress, and other functions. The present study will provide valuable useful information about LIM genes in sorghum which would pave the way for the future study of functional pathways of candidate SbLIM genes as well as their regulatory factors in wet-lab experiments.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.1
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• pp.49-57
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• 2019

Objective: The first stage in both breeding and programs for the conservation of genetic resources are the identification of genetic diversity in the relevant population. The aim of the present study is to identify genetic diversity of six brown layer pure chicken lines (Rhode Island Red [RIRI, RIRII], Barred Rock [BARI, BARII], Columbian Rock [COL], and line 54 [L-54]) with microsatellite markers. Furthermore, the study aims to employ its findings to discuss the possibilities for the conservation and sustainable use of these lines that have been bred as closed populations for a long time. Methods: In the present study, a total number of 180 samples belonging to RIRI (n = 30), RIRII (n = 30), BARI (n = 30), BARII (n = 30), L-54 (n = 30), and COL (n = 30) lines were genotyped using 22 microsatellite loci. Microsatellite markers are extremely useful tools in the identification of genetic diversity since they are distributed throughout the eukaryotic genome in multitudes, demonstrate co-dominant inheritance and they feature a high rate of polymorphism and repeatability. Results: In this study, we found all loci to be polymorphic and identified the average number of alleles per locus to be in the range between 4.41 (BARI) and 5.45 (RIRI); the observed heterozygosity to be in the range between 0.31 (RIRII) and 0.50 (BARII); and $F_{IS}$ (inbreeding coefficient) values in the range between 0.16 (L-54) and 0.46 (RIRII). The $F_{IS}$ values obtained in this context points out to a deviation from Hardy-Weinberg equilibrium due to heterozygote deficiency in six different populations. The Neighbour-Joining tree, Factorial Correspondence Analysis and STRUCTURE clustering analyzes showed that six brown layer lines were separated according to their genetic origins. Conclusion: The results obtained from the study indicate a medium level of genetic diversity, high level inbreeding in chicken lines and high level genetic differentiation between chicken lines.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.11 no.sup2
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• pp.59-66
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• 2008

Genome-wide association studies using large case-control samples and several hundred thousand genetic markers efficiently and powerfully assay common genetic variations. The application of these studies to inflammatory bowel disease has led to the identification of susceptibility genes and affirmed the importance of innate and adaptive immunity in the pathogenesis of disease. Efforts directed towards the identification of environmental factors have implicated commensal bacteria as determinants of dysregulated immunity and inflammatory bowel disease. Host genetic polymorphisms most likely interact with functional bacterial changes to stimulate aggressive immune responses that lead to chronic tissue injury.

• Clinical and Experimental Pediatrics
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• v.56 no.2
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• pp.52-59
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• 2013

Cardiomyopathy (CMP) is a heterogeneous disease caused by a functional abnormality of the cardiac muscle. CMP is of 2 major types, dilated and hypertrophic, and is further classified as either primary or secondary. Secondary CMP is caused by extrinsic factors, including infection, ischemia, hypertension, and metabolic disorders. Primary CMP is diagnosed when the extrinsic factors of secondary CMP are absent. Furthermore, the World Health Organization, American Heart Association, and European Cardiology Association have different systems for clinically classifying primary CMP. Primary CMP is rare and associated with a family history of the disease, implying that genetic factors might affect its incidence. In addition, the incidence of CMP varies widely according to patient ethnicity. Genetic testing plays an important role in the care of patients with CMP and their families because it confirms diagnosis, determines the appropriate care for the patient, and possibly affects patient prognosis. The diagnosis and genetic identification of CMP in patients' families allow the possibility to identify novel genes that may lead to new treatments. This review focuses on the epidemiology, pathophysiology, diagnosis, and treatment of CMP, with the aim of providing pediatricians with insights that may be helpful in the early identification and management of idiopathic CMP in children.

• Journal of Advanced Marine Engineering and Technology
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• v.31 no.5
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• pp.599-605
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• 2007

This paper presents a method for identifying various systems based on input-output data and a real-coded genetic algorithm(RCGA). The advantages of this technique are, first, it is not dependent on the deterministic or stochastic nature of the systems and, second, the globally optimized models for the original systems can be identified without the need of a differentiable measure function of linearly separable parameters. Under suitable hypotheses, the estimation error is shown to converge in probability to zero. The performance of the proposed algorithm is demonstrated through several simulations.

• Communications for Statistical Applications and Methods
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• v.31 no.3
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• pp.279-289
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• 2024

Familial searching is a useful technique in a forensic investigation. Using genetic information, it is possible to identify individuals, determine familial relationships, and obtain racial/ethnic information. The total number of shared alleles (TNSA) and likelihood ratio (LR) methods have traditionally been used, and novel data-mining classification methods have recently been applied here as well. However, it is difficult to apply these methods to identify familial relationships above the third degree (e.g., uncle-nephew and first cousins). Therefore, we propose to apply a stacking ensemble machine learning algorithm to improve the accuracy of familial relationship identification. Using real data analysis, we obtain superior relationship identification results when applying meta-classifiers with a stacking algorithm rather than applying traditional TNSA or LR methods and data mining techniques.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2600-2605
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• 2003

The PBL (Poly-butadiene Latex) production process is a typical batch process. Changes of the reactor characteristics due to the accumulated scaling with the increase of batch cycles require adaptive tuning of the PID controller being used. In this work we propose a tuning method for PID controllers based on the closed-loop identification and the genetic algorithm (GA) and apply it to control the PBL process. An approximated process transfer function for the PBL reactor is obtained from the closed-loop data using a suitable closed-loop identification method. Tuning is performed by GA optimization in which the objective function is given by ITAE for the setpoint change. The proposed tuning method showed good control performance in actual operations.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.1-6
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• 1993

This report proposes a novel method of identification of continuous time-delay systems from sampled input-output data. By the aid of a digital pre-filter, an approximated discrete-time estimation model is first derived, in which the system parameters remain in their original form and the time delay need not be an integral multiple of th sampling period. Then an identification method combining the common linear least squares(LS) method or the instrumental variable(IV) method with the genetic algorithm(GA) is proposed. That is, the time-delay is selected by the GA, and the system parameters are estimated by the LS or IV method. Furthermore, the proposed method is extended to the case of multi-input multi-output systems where the time-delays in the individual input channels may differ each other. Simulation resutls show that our method yields consistent estimates even in the presence of high measurement noises.

• Journal of Power System Engineering
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• v.13 no.4
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• pp.68-73
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• 2009

The mathematical model has a different response character with the real system because this mathematical model has the modeling errors and the imprecise value of system's parameters. Therefore to find the value of system parameters as possible as near by real value in the model is necessary to design the controlled system. This study concern about the identification method to estimate the parameter for the magnetic bearing system with RCGA(Real Coded Genetic Algorithm). Firstly, we will get the mathematical model from the current amplifier circuit and the magnetic bearing system. Secondly we will get the step response data in this circuit and system. Finally, we will estimate the unknown parameter's value from the data.