• CELLMED
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• v.4 no.1
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• pp.6.1-6.12
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• 2014

Anthrax is the deadly disease for human being caused by Bacillus anthracis. Instantaneous research work on the mode of infection of the organism revealed that different proteases are involved in different steps of pathogenesis. Present study reports the in silico characterization and the detection of pathogenic proteases involved in anthrax infection through protein-protein interaction. A total of 13 acid, 9 neutral, and 1 alkaline protease of Bacillus anthracis were selected for analysing the physicochemical parameter, the protein superfamily and family search, multiple sequence alignment, phylogenetic tree construction, protein-protein interactions and motif finding. Among the 13 acid proteases, 10 were found as extracellular enzymes that interact with immune inhibitor A (InhA) and help the organism to cross the blood brain barrier during the process of infection. Multiple sequence alignment of above acid proteases revealed the position 368, 489, and 498-contained 100% conserved amino acids which could be used to deactivate the protease. Among the groups analyzed, only acid protease were found to interact with InhA, which indicated that metalloproteases of acid protease group have the capability to develop pathogenesis during B. anthracis infection. Deactivation of conserved amino acid position of germination protease can stop the sporulation and germination of B anthracis cell. The detailed interaction study of neutral and alkaline proteases could also be helpful to design the interaction network for the better understanding of anthrax disease.

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.2
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• pp.181-186
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• 2013

We present nondestructive characterization for remanent life of advanced ferritic steels, next-gen energy facility materials by reversible permeability. The reversible permeability is based on the theory that the value of reversible permeability is the same differential of the hysteresis loop. The measurement principle is based on the foundation of harmonics voltage induced in a sensing coil using a lock-in amplifier tuned to the frequency of the exciting one. The peak interval of reversible permeability(PIRP), Vickers hardness, and tensile strength(TS) of the aged samples decreased with aging time. We could estimate the remanent life of advanced ferritic steel by using the relationship between the peak interval of reversible permeability and Larson-Miller parameter(LMP), non-destructively.

• Biomaterials and Biomechanics in Bioengineering
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• v.2 no.3
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• pp.127-141
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• 2015

Silver-based systems activated by low intensity direct current continue to be investigated as an alternative antimicrobial for infection prophylaxis and treatment. However there has been limited research on the quantitative characterization of the antimicrobial efficacy of such systems. The objective of this study was to develop a semi-mechanistic pharmacokinetic/pharmacodynamic (PK/PD) model providing the quantitative relationship between the critical system parameters and the degree of antimicrobial efficacy. First, time-kill curves were experimentally established for a strain of Staphylococcus aureus in a nutrientrich fluid environment over 48 hours. Based on these curves, a modified PK/PD model was developed with two components: a growing silver-susceptible bacterial population and a depreciating bactericidal process. The test of goodness-of-fit showed that the model was robust and had good predictability ($R^2>0.7$). The model demonstrated that the current intensity was positively correlated to the initial killing rate and the bactericidal fatigue rate of the system while the anode surface area was negatively correlated to the fatigue rate. The model also allowed the determination of the effective range of these two parameters within which the system has significant antimicrobial efficacy. In conclusion, the modified PK/PD model successfully described bacterial growth and killing kinetics when the bacteria were exposed to the electrically activated silver-titanium implant system. This modeling approach as well as the model itself can also potentially contribute to the development of optimal design strategies for other similar antimicrobial systems.

• Journal of the Korean Wood Science and Technology
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• v.31 no.6
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• pp.31-39
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• 2003

The enzymatic isolation of residual lignins obtained from spruce and beech pulps (obtained by sulfite, kraft, ASAM and soda/AQ/MeOH pulping processes) and their characterization was described in previous publications. Here, the residual lignins have been submitted to potassium permanganate oxidation (KMnO₄ degradation), and 9 aromatic carboxylic acids (3 of them are dimeric) were identified after methylation with diazomethane by GC/MS. The analytical challenge during qantification by the internal standard methods was the partly high protein content of the samples, which resulted in elevated anisic acid yields in the degradation mixture of sulfite residual lignins. The results are compared with the KMnO₄ degradation of the corresponding MWLs and discussed in terms of S/G ratios and degrees of condensation. The latter was calculated as a quotient between the aromatic carboxylic acids derived from condensed and non-condensed lignin structures. Typical degradation patterns for the various processes have been observed. Among other parameter, the relative compositions between iso-hemipinic acid (which is for condensation in pos. 5 of the aromatic ring) and meta-hemipinic acid and 3,4,5-trimethoxyphthalic acid (both are for condensation in pos. 6 of the aromatic ring) was found to be process specific. Kraft and soda/AQ/MeOH residual lignins yielded higher amounts of iso-hemipinic acid. In contrast, the relative yields of meta-hemipinic acid and 3,4,5-trimethoxyphthalic acid (the latter in beech lignins) are higher in sulfite and particularly in ASAM residual lignin. In case of beech residual lignins the amount of acids originated from non-condensed syringyl type lignin units was surprisingly high. The condensation degree of residual lignins was shown to be generally higher than that of MWLs. This was especially true for the G units. ASAM residual lignin exhibited very high S/G ratios and degrees of polymerization. Causality between condensation degree and total yield of degradation products was demonstrated.

• The Journal of Engineering Geology
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• v.6 no.1
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• pp.1-13
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• 1996

The fracture transmissivity($T_f$) is the most important parameter of fracture in assessing groundwater flow in fractured rock masses by using the DFN(Discrete Fracture Network) modeling. $T_f$, the most sensitive parameter m DFN modeling, is dependent upon aperture, size and filling characteristics of each fracture set. In the field test, the accuracy of $T_f$ can be increased with Borehole Acoustic Scanning (Televiewer) and Fixed Interval Length(FIL) test in constant head. $T_f$ values measured from FIL test was modified and estimated by each fracture set on the basis of the Cubic Law and the information of aperture and filling characteristics obtained from Televiewer. The modified $T_f$ results in the increase of confidence and reliability of modeling results including the amount of tunnel inflow.And, this approach would reduce the uncertaintity of the assessment for groundwater flow in fractured rock masses using the DFN modeling.

• Journal of the Mineralogical Society of Korea
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• v.16 no.2
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• pp.125-133
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• 2003

Saponite was synthesized from talc by hydrothermal method. The starting material was prepared by adding ($NO_3$)$Al_3$$.$$9H_2$O and Mg($NO_3$)$_2$$.$$6H_2$O solution to the talc powder. which was previously activated in air at 800 $^{\circ}C$ together with $Na_2$$CO_3$. The alkalinity of the solution was controlled by $NH_4$OH solution. The autoclaving was carried out in the closed stainless steel vessel (about 1 liter) for 40 hours under the pressure of 25 kgf/$\textrm{cm}^2$ at $ 230^{\circ}C$ The characterization of the reaction product shows that saponite was crystallized successfully. After the experimental results, pressure was not sensitive parameter in the range of 25 ∼ 75 kgf/$\textrm{cm}^2$, but longer reaction time results in better crystallinity.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.10
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• pp.1139-1145
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• 2014

Creation of a human skeleton model and characterization of the variation in the bone shape are fundamentally important in many applications of biomechanics. In this paper, we present a parametric shape modeling method for femurs that is based on extracting the main parameter of variations of the femur shape from a 3D model database by using statistical shape analysis. For this shape analysis, principal component analysis (PCA) is used. Application of the PCA to 3D data requires bringing all the models in correspondence to each other. For this reason, anatomical landmarks are used for guiding the deformation of the template model to fit the 3D model data. After subsequent application of PCA to a set of femur models, we calculate the correlation between the dominant components of shape variability for a target population and the anatomical parameters of the femur shape. Finally, we provide tools for visualizing and creating the femur shape using the main parameter of femur shape variation.

• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.7
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• pp.297-300
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• 2015

In medical ultrasonography, transit time and contrast enhancement patterns are considered as important parameters to analyze liver diseases. In many recent researches, time-intensity curves(TIC) have been used for calculating the transit time of the contrast agents. However, the intensity curve may include the variations which are caused by the micro-bubble effect of contrast agents. In this paper, we propose a complementary approach to diagnostic parameter extraction which utilizes a density information as well as the intensity data. The proposed technique improves the accuracy in extraction of the transit time and velocity of contrast agents for detection and characterization of focal liver lesions. Through the experiments using a set of clinical data, we show that the proposed methods can improve the reliability of the parametric image data.

• Environmental Engineering Research
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• v.19 no.3
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• pp.247-253
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• 2014

The aim of this study was to characterize quintinite in fluoride removal from aqueous solutions, using batch experiments. Experimental results showed that the maximum adsorption capacity of fluoride to quintinite was 7.71 mg/g. The adsorption of fluoride to quintinite was not changed at pH 5-9, but decreased considerably in highly acidic (pH < 3) and alkaline (pH > 11) solution conditions. Kinetic model analysis showed that among the three models (pseudo-first-order, pseudo-second-order, and Elovich), the pseudo-second-order model was the most suitable for describing the kinetic data. From the nonlinear regression analysis, the pseudo-second-order parameter values were determined to be $q_e=0.18mg/g$ and $k_2=28.80g/mg/hr$. Equilibrium isotherm model analysis demonstrated that among the three models (Langmuir, Freundlich, and Redlich-Peterson), both the Freundlich and Redlich-Peterson models were suitable for describing the equilibrium data. The model analysis superimposed the Redlich-Peterson model fit on the Freundlich fit. The Freundlich model parameter values were determined from the nonlinear regression to be $K_F=0.20L/g$ and 1/n=0.51. This study demonstrated that quintinite could be used as an adsorbent for the removal of fluoride from aqueous solutions.