• Journal of Microbiology and Biotechnology
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• v.25 no.9
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• pp.1401-1409
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• 2015

The aim of this study was to develop a SYBR Green-based real-time PCR assay for the rapid, specific, and sensitive detection of Acidovorax avenae subsp. citrulli, which causes bacterial fruit blotch (BFB), a serious disease of cucurbit plants. The molecular and serological methods currently available for the detection of this pathogen are insufficiently sensitive and specific. Thus, a novel SYBR Green-based real-time PCR assay targeting the YD-repeat protein gene of A. avenae subsp. citrulli was developed. The specificity of the primer set was evaluated using DNA purified from 6 isolates of A. avenae subsp. citrulli, 7 other Acidovorax species, and 22 of non-targeted strains, including pathogens and non-pathogens. The AC158F/R primer set amplified a single band of the expected size from genomic DNA obtained from the A. avenae subsp. citrulli strains but not from the genomic DNA of other Acidovorax species, including that of other bacterial genera. Using this assay, it was possible to detect at least one genomeequivalents of the cloned amplified target DNA using 5 × 10⁰ fg/µl of purified genomic DNA per reaction or using a calibrated cell suspension, with 6.5 colony-forming units per reaction being employed. In addition, this assay is a highly sensitive and reliable method for identifying and quantifying the target pathogen in infected samples that does not require DNA extraction. Therefore, we suggest that this approach is suitable for the rapid and efficient diagnosis of A. avenae subsp. citrulli contaminations of seed lots and plants.

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.282-287
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• 2008

Identification of steady-state is the first step in developing a fault detection and diagnosis (FDD) system. In a complete FDD system, the steady-state detector will be included as a module in a self-learning algorithm which enables the working system's reference model to "tune" itself to its particular installation. In this study, a steady-state detector of a residential air conditioner based on moving windows was designed. Seven representing measurements were selected as key features for steady-state detection. The optimized moving window size and the feature thresholds was suggested through startup transient test and no-fault steady-state test. Performance of the steady-state detector was verified during indoor load change test. From the research, the general methodology to design a moving window steady-state detector was provided for vapor compression applications.

• Journal of Veterinary Science
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• v.23 no.2
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• pp.21.1-21.7
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• 2022

Newcastle disease (ND), infectious laryngotracheitis (ILT) and avian metapneumovirus (aMPV) can be similar making it critical to quickly differentiate them. Herein, we adapted pre-existing molecular-based diagnostic assays for NDV and ILTV, and developed new assays for aMPV A and B, for use under synchronized thermocycling conditions. All assays performed equivalently with linearity over a 5 log₁₀ dynamic range, a reproducible (R² > 0.99) limit of detection of ≥ 10 target copies, and amplification efficiencies between 86.8%-98.2%. Using biological specimens for NDV and ILTV showed 100% specificity. Identical amplification conditions will simplify procedures for detection in diagnostic laboratories.

• Korean Journal of Veterinary Service
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• v.34 no.4
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• pp.321-331
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• 2011

Mycobacterium bovis, a member of the M. tuberculosis complex (MTC), is the causative agent of bovine tuberculosis. Detection of M. bovis and M. tuberculosis using conventional culture- and biochemical-based assays is time-consuming. Therefore, a simple and sensitive molecular assay for rapid detection would be of great help in specific situations such as faster diagnosis of bovine tuberculosis (bTB) infection in the abattoirs. We developed a novel multiplex real-time PCR assay which was applied directly to biological samples with evidence of bTB and it was allowed to differentiate between M. bovis and M. tuberculosis. The primers and TaqMan probes were designed to target the IS1081 gene, the multi-copy insertion element in the MTC and the 12.7-kb fragment which presents in M. tuberculosis, not in the M. bovis genome. The assay was optimized and validated by testing 10 species of mycobacteria including M. bovis and M. tuberculosis, and 10 other bacterial species such as Escherichia coli, and cattle lymph nodes (n=113). The tests identified 96.4% (27/28) as M. bovis from the MTC-positive bTB samples using conventional PCR for specific insertion elements IS1081. And MTC-negative bTB samples (n=85) were tested using conventional PCR and the real-time PCR. When comparative analyses were conducted on all bovine samples, using conventional PCR as the gold standard, the relative accuracy of real-time PCR was 99.1%, the relative specificity was 100%, and the agreement quotient (kappa) was 0.976. The detection limits of the real-time PCR assays for M. bovis and M. tuberculosis genomic DNA were 10 fg and 0.1 pg per PCR reaction, respectively. Consequently, this multiplex real-time PCR assay is a useful diagnotic tool for the identification of MTC and differentiation of M. bovis and M. tuberculosis, as well as the epidemiologic surveillance of animals slaughtered in abattoir.

• The Plant Pathology Journal
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• v.39 no.4
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• pp.309-318
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• 2023

Huanglongbing (HLB) is one of the most destructive diseases in citrus, which imperils the sustainability of citriculture worldwide. The presumed causal agent of HLB, 'Candidatus Liberibacter asiaticus' (CLas) is a non-culturable phloem-limited α-proteobacterium transmitted by Asian citrus psyllids (ACP, Diaphorina citri Kuwayama). A widely adopted method for HLB diagnosis is based on quantitative real-time polymerase chain reaction (qPCR). Although HLB diagnostic qPCR provides high sensitivity and good reproducibility, it is limited by time-consuming DNA preparation from plant tissue or ACP and the requirement of proper lab instruments including a thermal cycler to conduct qPCR. In an attempt to develop a quick assay that can be deployed in the field for CLas detection, we developed a real-time loop-mediated isothermal amplification (rt-LAMP) assay by targeting the CLas five copy nrdB gene. The rt-LAMP assay using various plant sample types and psyllids successfully detected the nrdB target as low as ~2.6 Log10 copies. Although the rt-LAMP assay was less sensitive than laboratory-based qPCR (detection limit ~10 copies), the data obtained with citrus leaf and bark and ACP showed that the rt-LAMP assay has >96% CLas detection rate, compared to that of laboratory-based qPCR. However, the CLas detection rate in fibrous roots was significantly decreased compared to qPCR due to low CLas titer in some root DNA sample. We also demonstrated that the rt-LAMP assay can be used with a crude leaf DNA extract which is fully deployable in the field for quick and reliable HLB screening.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.465-474
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• 2021

Corona-19, a disease caused by 'Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)', was declared a global pandemic by the World Health Organization (WHO) in March 2020, and a real-time polymerase chain reaction test is performed as a diagnostic test for screening and confirmation in most countries. However, not only the target genes and protocols differ by countries, but also the procedures for reading the diagnosis results are diverse, so the criteria for confirmed patients differ by country. Therefore, in this review, we discussed the target genes, test techniques, and diagnostic criteria for each country notified by WHO. And the specificity and sensitivity, limits of detection, positive and negative controls, false positive bacteria candidates, and specimens, and the specifics of the control setting were also described. In addition, the characteristics of Korea's test were compared to each country's one. Finally, in order to obtain the same diagnosis result for SARS-CoV-2 in the future, standardized diagnosis methods and result interpretations for Corona-19 diagnosis were proposed.

• Transactions on Electrical and Electronic Materials
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• v.14 no.2
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• pp.71-77
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• 2013

Advanced semiconductor manufacturing technology requires methods to maximize tool efficiency and improve product quality by reducing process variability. Real-time plasma process monitoring and diagnosis have become crucial for fault detection and classification (FDC) and advanced process control (APC). Additional sensors may increase the accuracy of detection of process anomalies, and optical monitoring methods are non-invasive. In this paper, we propose the use of a chromatic data acquisition system for real-time in-situ plasma process monitoring called the Plasma Eyes Chromatic System (PECS). The proposed system was initially tested in a six-inch research tool, and it was then further evaluated for its potential to detect process anomalies in an eight-inch production tool for etching blanket oxide films. Chromatic representation of the PECS output shows a clear correlation with small changes in process parameters, such as RF power, pressure, and gas flow. We also present how the PECS may be adapted as an in-situ plasma arc detector. The proposed system can provide useful indications of a faulty process in a timely and non-invasive manner for successful run-to-run (R2R) control and FDC.

• Journal of the Korean Chemical Society
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• v.51 no.1
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• pp.36-42
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• 2007

Hepatitis B is a serious public health problem leading to chronic infection and liver cancer. Quantitation of circulating hepatitis B virus (HBV) is important for monitoring disease progression and for assessing the response to antiviral therapy. In this study, by using Real-Time PCR and novel Micro-PCR assay method, we measured HBV concentration in the clinical sample. A total of 120 serum samples from patients with HBV infection collected was in Dankook university hospital to compare the detection limit, sensitivity, specificity and reproducibility of the two assay methods. These findings of this study suggest that Micro-PCR and Real-Time PCR assay methods are comparable to each other in there detection limit, sensitivity, and reproducibility for HBV DNA quantitation. However, Micro-PCR assay is more efficient than Real-Time PCR method, because Real-Time PCR is not so time - consuming, technically easy and need to reagent of a small quantity. It will be useful for rapid and reliable clinical diagnosis of HBV in many countries.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.3
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• pp.150-159
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• 2000

In-process diagnosis of the cutting state is essential for the automation of manufacturing systems. Especially when the cutting process becomes unstable it induces self-exited vibrations a frequent case of poor tool life rough surface finish damage to the workpiece and the machine tool itself and excessive down time. To ensure that the cutting process main-tains stable it is highly desirable to have the capability of real-time. To ensure that the cutting process main-tains stable it is highly desirable to have the capability of real-time monitoring and controlling chatter. This paper describes the detection method of chatter vibration using cutting force in turning process. In order to detect a chatter vibra-tion the dynamic fluctuation of radial force is analyzed since this components is sensitive to the chatter. The envelope sig-nal of radial force has been calculated by the use of FIR Hilbert transformer and it was useful to classify the chatter signal from the dynamically unstable circumstances. It was found that the mode and the mode width were closely correlated with the chatter amplitude was well. Finally back propagation(BP) neural network have been applied to the pattern recognition for the classification of chatter signal in various cutting conditions. The validity of this systed was confirmed by the experiments under the various cutting conditions.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.12
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• pp.643-650
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• 2000

Using neural network approach, the diagnosis of faults in industrial process that requires observing multiple data simultaneously are studied. Two-stage diagnosis is proposed to analyze system faults. By using neural network, the first stage detects the dynamic trend of each normalized date patterns by comparing a proposed pattern. Instead of using neural network, the difference between stored fault pattern and real time data is used for fault diagnosis in the second stage. This method reduces the amount of calculation and saves storing space. Also, we dealt with unknown faults by normalizing the data and calculating the difference between the value of steady state and the data in case of fault. A model of tank reactor is given to verify that the proposed method is useful and effective to noise.