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Prediction Models of P-Glycoprotein Substrates Using Simple 2D and 3D Descriptors by a Recursive Partitioning Approach

  • Joung, Jong-Young;Kim, Hyoung-Joon;Kim, Hwan-Mook;Ahn, Soon-Kil;Nam, Ky-Youb;No, Kyoung-Tai
    • Bulletin of the Korean Chemical Society
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    • v.33 no.4
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    • pp.1123-1127
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    • 2012
  • P-gp (P-glycoprotein) is a member of the ATP binding cassette (ABC) family of transporters. It transports many kinds of anticancer drugs out of the cell. It plays a major role as a cause of multidrug resistance (MDR). MDR function may be a cause of the failure of chemotherapy in cancer and influence pharmacokinetic properties of many drugs. Hence classification of candidate drugs as substrates or nonsubstrate of the P-gp is important in drug development. Therefore to identify whether a compound is a P-gp substrate or not, in silico method is promising. Recursive Partitioning (RP) method was explored for prediction of P-gp substrate. A set of 261 compounds, including 146 substrates and 115 nonsubstrates of P-gp, was used to training and validation. Using molecular descriptors that we can interpret their own meaning, we have established two models for prediction of P-gp substrates. In the first model, we chose only 6 descriptors which have simple physical meaning. In the training set, the overall predictability of our model is 78.95%. In case of test set, overall predictability is 69.23%. Second model with 2D and 3D descriptors shows a little better predictability (overall predictability of training set is 79.29%, test set is 79.37%), the second model with 2D and 3D descriptors shows better discriminating power than first model with only 2D descriptors. This approach will be used to reduce the number of compounds required to be run in the P-gp efflux assay.

Characterization of Korean Archaeological Artifacts by Neutron Activation Analysis (II). Multivariate Classification of Korean Ancient Glass Pieces (중성자 방사화분석에 의한 한국산 고고학적 유물의 특성화 연구 (II). 다변량 해석법에 의한 고대 유리제품의 분류 연구)

  • Chul Lee;Oh Cheun Kwun;Ihn Chong Lee;Nak Bae Kim
    • Journal of the Korean Chemical Society
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    • v.31 no.6
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    • pp.567-575
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    • 1987
  • Fourty five ancient Korean glass pieces have been determined for 19 elements such as Ag, As, Br, Ce, Co, Cr, Eu, Fe, Hf, K, La, Lu, Na, Ru, Sb, Sc, Sm, Th and Zn, and for one such as Pb by instrumental neutron activation analysis and by atomic absorption spectrometry, respectively. The multivariate data have been analyzed for the relation among elemental contents through the variance-covariance matrix. The data have been further analyzed by a principal component mapping method. As the results training set of 5 class have been chosen, based on the spread of sample points in an eigen vector plot and archaeological data. The 5 training set consisting of 36 species and a test set consisting of 9 species bave finally been analyzed for the assignment to certain classes or outliers through the statistical isolinear multiple component analysis (SIMCA). The results have showed the whole species for 5 training set and 3 species in the test set are assigned appropriately and these are in accord with the results by principal component mapping.

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Stability evaluation model for loess deposits based on PCA-PNN

  • Li, Guangkun;Su, Maoxin;Xue, Yiguo;Song, Qian;Qiu, Daohong;Fu, Kang;Wang, Peng
    • Geomechanics and Engineering
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    • v.27 no.6
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    • pp.551-560
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    • 2021
  • Due to the low strength and high compressibility characteristics, the loess deposits tunnels are prone to large deformations and collapse. An accurate stability evaluation for loess deposits is of considerable significance in deformation control and safety work during tunnel construction. 37 groups of representative data based on real loess deposits cases were adopted to establish the stability evaluation model for the tunnel project in Yan'an, China. Physical and mechanical indices, including water content, cohesion, internal friction angle, elastic modulus, and poisson ratio are selected as index system on the stability level of loess. The data set is randomly divided into 80% as the training set and 20% as the test set. Firstly, principal component analysis (PCA) is used to convert the five index system to three linearly independent principal components X1, X2 and X3. Then, the principal components were used as input vectors for probabilistic neural network (PNN) to map the nonlinear relationship between the index system and stability level of loess. Furthermore, Leave-One-Out cross validation was applied for the training set to find the suitable smoothing factor. At last, the established model with the target smoothing factor 0.04 was applied for the test set, and a 100% prediction accuracy rate was obtained. This intelligent classification method for loess deposits can be easily conducted, which has wide potential applications in evaluating loess deposits.

Predicting the CPT-based pile set-up parameters using HHO-RF and PSO-RF hybrid models

  • Yun Dawei;Zheng Bing;Gu Bingbing;Gao Xibo;Behnaz Razzaghzadeh
    • Structural Engineering and Mechanics
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    • v.86 no.5
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    • pp.673-686
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    • 2023
  • Determining the properties of pile from cone penetration test (CPT) is costly, and need several in-situ tests. At the present study, two novel hybrid learning models, namely PSO-RF and HHO-RF, which are an amalgamation of random forest (RF) with particle swarm optimization (PSO) and Harris hawks optimization (HHO) were developed and applied to predict the pile set-up parameter "A" from CPT for the design aim of the projects. To forecast the "A," CPT data along were collected from different sites in Louisiana, where the selected variables as input were plasticity index (PI), undrained shear strength (Su), and over consolidation ratio (OCR). Results show that both PSO-RF and HHO-RF models have acceptable performance in predicting the set-up parameter "A," with R2 larger than 0.9094, representing the admissible correlation between observed and predicted values. HHO-RF has better proficiency than the PSO-RF model, with R2 and RMSE equal to 0.9328 and 0.0292 for the training phase and 0.9729 and 0.024 for testing data, respectively. Moreover, PI and OBJ indices are considered, in which the HHO-RF model has lower results which leads to outperforming this hybrid algorithm with respect to PSO-RF for predicting the pile set-up parameter "A," consequently being specified as the proposed model. Therefore, the results demonstrate the ability of the HHO algorithm in determining the optimal value of RF hyperparameters than PSO.

Predicting Recurrence-Free Survival After Upfront Surgery in Resectable Pancreatic Ductal Adenocarcinoma: A Preoperative Risk Score Based on CA 19-9, CT, and 18F-FDG PET/CT

  • Boryeong Jeong;Minyoung Oh;Seung Soo Lee;Nayoung Kim;Jae Seung Kim;Woohyung Lee;Song Cheol Kim;Hyoung Jung Kim;Jin Hee Kim;Jae Ho Byun
    • Korean Journal of Radiology
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    • v.25 no.7
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    • pp.644-655
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    • 2024
  • Objective: To develop and validate a preoperative risk score incorporating carbohydrate antigen (CA) 19-9, CT, and fluorine18-fluorodeoxyglucose (18F-FDG) PET/CT variables to predict recurrence-free survival (RFS) after upfront surgery in patients with resectable pancreatic ductal adenocarcinoma (PDAC). Materials and Methods: Patients with resectable PDAC who underwent upfront surgery between 2014 and 2017 (development set) or between 2018 and 2019 (test set) were retrospectively evaluated. In the development set, a risk-scoring system was developed using the multivariable Cox proportional hazards model, including variables associated with RFS. In the test set, the performance of the risk score was evaluated using the Harrell C-index and compared with that of the postoperative pathological tumor stage. Results: A total of 529 patients, including 335 (198 male; mean age ± standard deviation, 64 ± 9 years) and 194 (103 male; mean age, 66 ± 9 years) patients in the development and test sets, respectively, were evaluated. The risk score included five variables predicting RFS: tumor size (hazard ratio [HR], 1.29 per 1 cm increment; P < 0.001), maximal standardized uptake values of tumor ≥ 5.2 (HR, 1.29; P = 0.06), suspicious regional lymph nodes (HR, 1.43; P = 0.02), possible distant metastasis on 18F-FDG PET/CT (HR, 2.32; P = 0.03), and CA 19-9 (HR, 1.02 per 100 U/mL increment; P = 0.002). In the test set, the risk score showed good performance in predicting RFS (C-index, 0.61), similar to that of the pathologic tumor stage (C-index, 0.64; P = 0.17). Conclusion: The proposed risk score based on preoperative CA 19-9, CT, and 18F-FDG PET/CT variables may have clinical utility in selecting high-risk patients with resectable PDAC.

Development of an In Planta Molecular Marker for the Detection of Chinese Cabbage (Brassica campestris ssp. pekinensis) Club Root Pathogen Plasmodiophora brassicae

  • Kim, Hee-Jong;Lee, Youn-Su
    • Journal of Microbiology
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    • v.39 no.1
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    • pp.56-61
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    • 2001
  • Plasmodiophora brassicae is an obligate parasite, a causal organism of clubroot disease in crucifers that can survive in the soil as resting spores for many years. P. brassicae causes great losses in susceptible varieties of crucifers throughout the world. In this present study, an in planta molecular marker for the detection of P. bassicae was developed using an oligonucleotide primer set foam the small subunit gene (18S like) and internal transcribed spacer (ITS) region of rDNA. The specific primer sequences determined were TCAGCTTGAATGCTAATGTG (ITS5) and CTACCTCATTTGAGATCCTTTGA (PB-2). This primer set was used to specifically detect p. bassicae in planta. The amplicon using the specific primer set was about 1,000 bp. However, the test plant and other soil-borne fungi including Fusarium spp. and Rhizoctonia app., as well as bacteria such as Pseudomonas app. and Erwinia sup. did not show any reaction with the primer set.

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A MULTIPHASE LEVEL SET FRAMEWORK FOR IMAGE SEGMENTATION USING GLOBAL AND LOCAL IMAGE FITTING ENERGY

  • TERBISH, DULTUYA;ADIYA, ENKHBOLOR;KANG, MYUNGJOO
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.21 no.2
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    • pp.63-73
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    • 2017
  • Segmenting the image into multiple regions is at the core of image processing. Many segmentation formulations of an images with multiple regions have been suggested over the years. We consider segmentation algorithm based on the multi-phase level set method in this work. Proposed method gives the best result upon other methods found in the references. Moreover it can segment images with intensity inhomogeneity and have multiple junction. We extend our method (GLIF) in [T. Dultuya, and M. Kang, Segmentation with shape prior using global and local image fitting energy, J.KSIAM Vol.18, No.3, 225-244, 2014.] using a multiphase level set formulation to segment images with multiple regions and junction. We test our method on different images and compare the method to other existing methods.

An Interconnection Model of ISP Networks (ISP 네트워크간 상호접속 모델)

  • Choi Eunjeong;Tcha Dong-Wan
    • Journal of the Korean Operations Research and Management Science Society
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    • v.30 no.4
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    • pp.151-161
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    • 2005
  • For Internet service providers (ISPs), there are three common types of interconnection agreements : private peering, public peering and transit. One of the most important problems for a single ISP is to determine which other ISPs to interconnect with, and under which agreements. The problem can be then to find a set of private peering providers, transit providers and Internet exchanges (IXs) when the following input data are assumed to be given : a set of BGP addresses with traffic demands, and a set of potential service providers (Private peering/transit providers and IXs) with routing information, cost functions and capacities. The objective is to minimize the total interconnection cost. We show that the problem is NP-hard, give a mixed-integer programming model, and propose a heuristic algorithm. Computational experience with a set of test instances shows the remarkable performance of the proposed algorithm of rapidly generating near-optimal solutions.

A study on the design optimization of baseframe to avoid resonance of diesel generator set (발전기세트 공진 회피를 위한 베이스프레임 최적설계에 관한 연구)

  • Jeong, S.H.;Kwak, Y.S.;Kim, W.H.
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2012.04a
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    • pp.157-162
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    • 2012
  • A structural modification of baseframe is an effective method to avoid resonance in marine diesel generator (D/G) set which consists of diesel engine, generator and baseframe. However the reinforcement with thick plates or additional parts to increase the natural frequency can be less effective because of increased weight. Especially fine control of target mode based on the experience is difficult because the weight and interference of system have to be considered. In this paper, the design optimization of baseframe was performed to reduce the resonant vibration using a gradient descent method. The design parameters such as thickness, shape and location of baseframe parts are optimized to increase the torsional natural frequency of D/G set. From the actual test, the new designed baseframe reduced the vibration level in resonance by 55% without any increase of weight and interference. interference.

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Flexural Toughness and Fatigue Behavior of Steel Fiber Reinforced Rapid-set Cement Concrete (강섬유보강 초속경시멘트 콘크리트의 휨인성 및 피로거동)

  • Lee, Bong-Hak;Hong, Chang-Woo;Kim, Dong-Ho
    • Journal of Industrial Technology
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    • v.19
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    • pp.163-172
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    • 1999
  • This study is conducted on the flexural toughness and flexural fatigue test to fine the mechanical properties of steel fiber reinforced rapid-set cement concrete. Experimental investigation is examined according to fiber contents(0, 0.4, 0.7, 1.0, 1.5%), fiber aspect ratio(58, 60, 83), fiber type (hooked, crimped fiber), and cement type (normal portland & rapid-set cement). The principal results obtained through this study are as follows; toughness and fatigue resistance tend to considerably increase with fiber contents, fiber aspect ration. And hooked fiber is improved better than crimped fiber. Concrete using rapid set cement is increased strength properties compared with concrete using normal portland cement, but relative strength properties behavior and fatigue resistance show a tendency to decrease a little.

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