• Bulletin of the Korean Space Science Society
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• 2007.04a
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• pp.52-52
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• 2007

• Analytical Science and Technology
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• v.24 no.6
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• pp.533-543
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• 2011

The hERG (human ether-a-go-go related gene) ion channel is a main factor for cardiac repolarization, and the blockade of this channel could induce arrhythmia and sudden death. Therefore, potential hERG ion channel inhibitors are now a primary concern in the drug discovery process, and lots of efforts are focused on the minimizing the cardiotoxic side effect. In this study, $IC_{50}$ data of 202 organic compounds in HEK (human embryonic kidney) cell from literatures were used to develop predictive 2D-QSAR model. Multiple linear regression (MLR), Support Vector Machine (SVM), and artificial neural network (ANN) were utilized to predict inhibition concentration of hERG ion channel as machine learning methods. Population based-forward selection method with cross-validation procedure was combined with each learning method and used to select best subset descriptors for each learning algorithm. The best model was ANN model based on 14 descriptors ($R^2_{CV}$=0.617, RMSECV=0.762, MAECV=0.583) and the MLR model could describe the structural characteristics of inhibitors and interaction with hERG receptors. The validation of QSAR models was evaluated through the 5-fold cross-validation and Y-scrambling test.

• Analytical Science and Technology
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• v.29 no.5
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• pp.234-241
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• 2016

The approach presented in this article refers to the bioanalytical method validation for the detection and quantitative determination of arsenic species including arsenite (As(III)), arsenate (As(V)), dimethylarsinic acid (DMA) and monomethylarsonic acid (MMA) in dog plasma by high-performance liquid chromatography inductively coupled plasma mass spectrometry (HPLC-ICP/MS). The arsenic species were separated using an agilent As speciation column by a mobile phase of 2 mM sodium phosphate monobasic, 0.2 mM ethylenediaminetetraacetic acid disodium salt dehydrate, 10 mM sodium acetate, 3 mM sodium nitrate and 1 % ethyl alcohol at pH 11 (adjusted with 1M NaOH). The method validation experiment was obtained selectivity, linearity, accuracy, precision, matrix effect, recovery, system suitability, dilution integrity and various stabilities. All calibration curves showed good linearity (R²>0.999) within test ranges. The lower limit of quantitation (LLOQ) was 5 ng/mL for As(III), As(V) and DMA, and 20 ng/mL for MMA. The system suitability and dilution values were within 6.5 % and 7.7 %. Subsequently, the developed and validated HPLC-ICP/MS method was also successfully applied to determine the arsenic speciation in dog plasma samples, and the recoveries for the spiked samples were in the range of 91.5–102.2 %. Therefore, this method could be applied to the evaluation of arsenic exposure, health effect assessment and other bio-monitoring studies in biological samples.

• Computers and Concrete
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• v.15 no.5
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• pp.807-831
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• 2015

In the previous analytical studies on 2D reinforced concrete (RC) beam-column joints, the modified compression field theory (MCFT) and the strut-and-tie method (STM) are usually employed. In this paper, the limitations of these analytical models for RC joint applications are reviewed. Essentially for predictions of RC joint shear behaviour, the MCFT is not applicable, while the STM can only predict the ultimate shear strength. To eliminate these limitations, an improved STM is derived and applied to some commonly encountered 2D joints, viz., interior and exterior joints, subjected to monotonic loading. Compared with the other STMs, the most attracting novelty of the proposed improved STM is that all critical stages of the shear stress-strain relationships for RC joints can be predicted, which cover the stages characterized by concrete cracking, transverse reinforcement yielding and concrete strut crushing. For validation and demonstration of superiority, the shear stress-strain relationships of interior and exterior RC beam-column joints from published experimental studies are employed and compared with the predictions by the proposed improved STM and other widely-used analytical models, such as the MCFT and STM.

• Structural Engineering and Mechanics
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• v.64 no.3
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• pp.311-321
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• 2017

This paper presents the details of analytical studies carried out towards the prediction of flexural capacity and load-deflection behaviour of Laced Steel-Concrete Composite (LSCC) beams. Analytical expressions for flexural capacity of the beams are derived in accordance with the basic principles of conventional Reinforced Concrete (RC) beams, but incorporated with relevant modifications to account for the composite nature of the cross-section. The ultimate flexural capacity of the two LSCC beams predicted using the derived expressions is found to be approximately 20% lower than those obtained due to measurement from experiments. Further to these, two simple methods are also proposed on the basis of unit load method and equivalent steel beam method to determine the non-linear load-deflection response of the LSCC beams for monotonic loading. Upon validation of the proposed methods by comparing the predicted responses with those of experiments and finite element analysis, it is found that the methods are useful to find nonlinear response of such composite beams.

• Mass Spectrometry Letters
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• v.6 no.3
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• pp.75-79
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• 2015

Suitable analytical procedures for the bulk analysis of ultra-trace amounts of uranium and plutonium have been developed using multi-collector inductively coupled mass spectrometry (MC-ICP-MS). The quantification and determination of the isotopic ratios of uranium and plutonium in three simulated swipe samples, a swipe blank, and a process blank were performed to validate the analytical performance. The analytical results for the simulated swipe samples were in good agreement with the certified values, based on the measurement quality goals for the analysis of bulk environmental samples recommended by the International Atomic Energy Agency (IAEA)

• Structural Engineering and Mechanics
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• v.72 no.1
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• pp.31-41
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• 2019

Structural integrity assessment of piping components is of paramount important for remaining life prediction, residual strength evaluation and for in-service inspection planning. For accurate prediction of these, a reliable fracture parameter is essential. One of the fracture parameters is stress intensity factor (SIF), which is generally preferred for high strength materials, can be evaluated by using linear elastic fracture mechanics principles. To employ available analytical and numerical procedures for fracture analysis of piping components, it takes considerable amount of time and effort. In view of this, an alternative approach to analytical and finite element analysis, a model based on relevance vector machine (RVM) is developed to predict SIF of part through crack of a piping component under fatigue loading. RVM is based on probabilistic approach and regression and it is established based on Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. Model for SIF prediction is developed by using MATLAB software wherein 70% of the data has been used for the development of RVM model and rest of the data is used for validation. The predicted SIF is found to be in good agreement with the corresponding analytical solution, and can be used for damage tolerant analysis of structural components.

• Smart Structures and Systems
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• v.5 no.6
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• pp.613-632
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• 2009

The present paper is concerned with the design of a proper patch actuator network in order to track a desired displacement of the sidewalls of a one-storey frame structure; both, for the static and the dynamic case. Weights for each patch of the actuator network found in our previous work were based on beam theory; in the present paper a refinement of these weights by modeling the sidewalls of the frame structure as thin plates is presented. For the sake of calculating the refined weights approximate solutions of the plate equations are calculated by an extended Galerkin method. The solutions based on the analytical plate model are compared with three-dimensional Finite Element results computed in the commercially available code ANSYS. The patch actuator network is put into practice by means of four piezoelectric patches attached to each of the two sidewalls of the frame structures, to which electric voltages proportional to the analytically refined patch weights are applied. Analytical and numerical results coincide very well over a broad frequency range.

• Nuclear Engineering and Technology
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• v.49 no.3
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• pp.562-568
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• 2017

Background: The chemical characterization of metallic alloys and oxides is conventionally carried out by wet chemical analytical methods and/or instrumental methods. Instrumental neutron activation analysis (INAA) is capable of analyzing samples nondestructively. As a part of a chemical quality control exercise, Zircaloys 2 and 4, nimonic alloy, and zirconium oxide samples were analyzed by two INAA methods. The samples of alloys and oxides were also analyzed by inductively coupled plasma optical emission spectroscopy (ICP-OES) and direct current Arc OES methods, respectively, for quality assurance purposes. The samples are important in various fields including nuclear technology. Methods: Samples were neutron irradiated using nuclear reactors, and the radioactive assay was carried out using high-resolution gamma-ray spectrometry. Major to trace mass fractions were determined using both relative and internal monostandard (IM) NAA methods as well as OES methods. Results: In the case of alloys, compositional analyses as well as concentrations of some trace elements were determined, whereas in the case of zirconium oxides, six trace elements were determined. For method validation, British Chemical Standard (BCS)-certified reference material 310/1 (a nimonic alloy) was analyzed using both relative INAA and IM-NAA methods. Conclusion: The results showed that IM-NAA and relative INAA methods can be used for nondestructive chemical quality control of alloys and oxide samples.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.3114-3114
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• 2001

During the last years phytochemistry and phytopharmaceutical applications have developed rapidly and so there exists a high demand for faster and more efficient analysis techniques. Therefore we have established a near infrared transflectance spectroscopy (NIRS) method that allows a qualitative and quantitative determination of new polyphenolic pharmacological active leading compounds within a few seconds. As the NIR spectrometer has to be calibrated the compound of interest has at first to be characterized by using one or other a combination of chromatographic or electrophoretic separation techniques such as thin layer chromatography (TLC), high performance liquid chromatography (HPLC), capillary electrophoresis (CE), gas chromatography (GC) and capillary electrochromatography (CEC). Both structural elucidation and quantitative analysis of the phenolic compound is possible by direct coupling of the mentioned separation methods with a mass spectrometer (GC-MS, LC-MS/MS, CE-MS, CEC-MS) and a NMR spectrometer (LC-NMR). Furthermore the compound has to be isolated (NPLC, MPLC, prep. TLC, prep. HPLC) and its structure elucidated by spectroscopic techniques (UV, IR, HR-MS, NMR) and chemical synthesis. After that HPLC can be used to provide the reference data for the calibration step of the near infrared spectrometer. The NIRS calibration step is time consuming, which is compensated by short analysis times. After validation of the established NIRS method it is possible to determine the polyphenolic compound within seconds which allows to raise the efficiency in quality control and to reduce costs especially in the phytopharmaceutical industry.