• Title/Summary/Keyword: SCC model

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Near Infrared Spectroscopy for Diagnosis: Influence of Mammary Gland Inflammation on Cow´s Milk Composition Measurement

  • Roumiana Tsenkova;Stefka Atanassova;Kiyohiko Toyoda
    • Near Infrared Analysis
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    • v.2 no.1
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    • pp.59-66
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    • 2001
  • Nowadays, medical diagnostics is efficiently supported by clinical chemistry and near infrared spectroscopy is becoming a new dimension, which has shown high potential to provide valuable information for diagnosis. The investigation was carried out to study the influence of mammary gland inflammation, called mastitis, on cow´s milk spectra and milk composition measured by near infrared spectroscopy (NIRS). Milk somatic cell counts (SCC) in milk were used as a measure of mammary gland inflammation. Naturally occurred variations with milk composition within lactation and in the process of milking were included in the experimental design of this study. Time series of unhomogenized, raw milk spectral data were collected from 3 cow along morning and evening milking, for 5 consecutive months, within their second lactation. In the time of the trial, the investigated cows had periods with mammary gland inflammation. Transmittance spectra of 258 milk samples were obtained by NIRSystem 6500 spectrophotometer in 1100-2400 nm region. Calibration equations for the examined milk components were developed by PLS regression using 3 different sets of samples: samples with low somatic cell count (SCC), samples with high SCC and combined data set. The NIR calibration and prediction of individual cow´s milk fat, protein, and lactose were highly influenced by the presence of mil samples from animals with mammary gland inflammation in the data set. The best accuracy of prediction (i.e. the lower SEP and the higher correlation coefficient) for fat, protein and lactose was obtained for equations, developed when using only “healthy” samples, with low SCC. The standard error of prediction increased and correlation coefficient decreased significantly when equations for low SCC milk were used to predict examined components in “mastitis” samples with high SCC, and vice versa. Combined data set that included samples from healthy and mastitis animals could be used to build up regression models for screening. Further use of separate model for healthy samples improved milk composition measurement. Regression vectors for NIR mild protein measurement obtained for “healthy” and “mastitic” group were compared and revealed differences in 1390-1450 nm, 1500-1740 nm and 1900-2200 nm regions and thus illustrated post-secretory breakdown of milk proteins by hydrolytic enzymes that occurred with mastitis. For the first time it has been found that monitoring the spectral differences in water bands at 1440 nm and 1912 nm could provide valuable information for inflammation diagnosis.

An Adaptive Synthetic Control Chart for Detecting Shifts in the Process Mean (공정평균 이동을 탐지하기 위한 적응 합성 관리도)

  • Lim Taejin
    • Journal of Korean Society for Quality Management
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    • v.32 no.4
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    • pp.169-183
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    • 2004
  • The synthetic control chart (SCC) proposed by Wu and Spedding (2000) is to detect shifts in the process mean. The performance was re-evaluated by Davis and Woodall (2002), and the steady-state average run length (ARL) performance was shown to be inferior to cumulative sum (CUSUM) or exponentially weighted moving average (EWMA) chart This paper proposes a simple adaptive scheme to improve the performance of the synthetic control chart. That is, once a non-conforming (NC) sample occurs, we investigate the next L-consecutive samples with larger sample sizes and shorter sampling intervals. We employ a Markov chain model to derive the ARL and the average time to s19na1 (ATS). We also propose a statistical design procedure for determining decision variables. Comprehensive comparative study shows that the proposed control chart is uniformly superior to the original SCC or double sampling (DS) Χ chart and comparable to the EWMA chart in ATS performance.

DISEASE DIAGNOSED AND DESCRIBED BY NIRS

  • Tsenkova, Roumiana N.
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1031-1031
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    • 2001
  • The mammary gland is made up of remarkably sensitive tissue, which has the capability of producing a large volume of secretion, milk, under normal or healthy conditions. When bacteria enter the gland and establish an infection (mastitis), inflammation is initiated accompanied by an influx of white cells from the blood stream, by altered secretory function, and changes in the volume and composition of secretion. Cell numbers in milk are closely associated with inflammation and udder health. These somatic cell counts (SCC) are accepted as the international standard measurement of milk quality in dairy and for mastitis diagnosis. NIR Spectra of unhomogenized composite milk samples from 14 cows (healthy and mastitic), 7days after parturition and during the next 30 days of lactation were measured. Different multivariate analysis techniques were used to diagnose the disease at very early stage and determine how the spectral properties of milk vary with its composition and animal health. PLS model for prediction of somatic cell count (SCC) based on NIR milk spectra was made. The best accuracy of determination for the 1100-2500nm range was found using smoothed absorbance data and 10 PLS factors. The standard error of prediction for independent validation set of samples was 0.382, correlation coefficient 0.854 and the variation coefficient 7.63%. It has been found that SCC determination by NIR milk spectra was indirect and based on the related changes in milk composition. From the spectral changes, we learned that when mastitis occurred, the most significant factors that simultaneously influenced milk spectra were alteration of milk proteins and changes in ionic concentration of milk. It was consistent with the results we obtained further when applied 2DCOS. Two-dimensional correlation analysis of NIR milk spectra was done to assess the changes in milk composition, which occur when somatic cell count (SCC) levels vary. The synchronous correlation map revealed that when SCC increases, protein levels increase while water and lactose levels decrease. Results from the analysis of the asynchronous plot indicated that changes in water and fat absorptions occur before other milk components. In addition, the technique was used to assess the changes in milk during a period when SCC levels do not vary appreciably. Results indicated that milk components are in equilibrium and no appreciable change in a given component was seen with respect to another. This was found in both healthy and mastitic animals. However, milk components were found to vary with SCC content regardless of the range considered. This important finding demonstrates that 2-D correlation analysis may be used to track even subtle changes in milk composition in individual cows. To find out the right threshold for SCC when used for mastitis diagnosis at cow level, classification of milk samples was performed using soft independent modeling of class analogy (SIMCA) and different spectral data pretreatment. Two levels of SCC - 200 000 cells/$m\ell$ and 300 000 cells/$m\ell$, respectively, were set up and compared as thresholds to discriminate between healthy and mastitic cows. The best detection accuracy was found with 200 000 cells/$m\ell$ as threshold for mastitis and smoothed absorbance data: - 98% of the milk samples in the calibration set and 87% of the samples in the independent test set were correctly classified. When the spectral information was studied it was found that the successful mastitis diagnosis was based on reviling the spectral changes related to the corresponding changes in milk composition. NIRS combined with different ways of spectral data ruining can provide faster and nondestructive alternative to current methods for mastitis diagnosis and a new inside into disease understanding at molecular level.

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An Analysis of Prognostic Factors in the Uterine Cervical Cancer Patients (자궁경부암 환자의 예후인자에 관한 분석)

  • Yang, Dae-Sik;Yoon, Won-Sub;Kim, Tae-Hyun;Kim, Chul-Yong;Choi, Myung-Sun
    • Radiation Oncology Journal
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    • v.18 no.4
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    • pp.300-308
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    • 2000
  • Purpose :The aim of this study is to analysis of suwival and recurrence rates of the uterine cervical carcinoma patients whom received the radiation therapy respectively. The prognostic factors, such as Papanicolaou (Pap) smear, carcinoembriogenic antigen (CEA) and squamous cell carcinoma (SCC) antigen has been studied. Methods and Materials : From January 1981 to December 1998, eight-hundred twenty-seven uterine carvical cancer patients were treat with radiation therapy. All of the patients were divided into two groups : the radiation therapy only (S2l patients) group and the postoperative radiation therapy (326 patients) group. The age, treatment modality, clinical stage, histopathology, recurrence, follow-up Pap smears, CEA and SCC antigen were used as parameters for the evaluation. The prognostic factors such as survival and recurrence rates were peformed with the Kaplan-Meier method and the Cox hazard model, respectively. Median rollow-up was 38.6 months. Results :On the radiation therapy only group, 314 patients (60$\%$) achieved complete response (CR), 47 patients (9$\%$) showed local recurrence (LR), 78 patients (15$\%$) developed distant metastasis (DM). On the Postoperative radiation therapy group, showed 276 Patients (85$\%$) CR, 8 Patients (2$\%$) LR, 37 Patients (11$\%$) DM. The 5-year survival and recurrence rates was evaluated for all parameters. The statistically significant factors for the survival rate in univariate analysis were clinical stage (p=0.0001), treatment modality (p=0.0010), recurrence (p=0.0001), Pap smear (p=0.0329), CEA (p=0.0001) and SCC antigen (p=0.0001). Conclusion: This study indicated that after treatment, the follow-up studies of Pap smear, CEA and SCC antigen were significant parameter and prediction factors for the survival and recurrence of the uterine cervical carcinoma.

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Prediction of the compressive strength of self-compacting concrete using surrogate models

  • Asteris, Panagiotis G.;Ashrafian, Ali;Rezaie-Balf, Mohammad
    • Computers and Concrete
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    • v.24 no.2
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    • pp.137-150
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    • 2019
  • In this paper, surrogate models such as multivariate adaptive regression splines (MARS) and M5P model tree (M5P MT) methods have been investigated in order to propose a new formulation for the 28-days compressive strength of self-compacting concrete (SCC) incorporating metakaolin as a supplementary cementitious materials. A database comprising experimental data has been assembled from several published papers in the literature and the data have been used for training and testing. In particular, the data are arranged in a format of seven input parameters covering contents of cement, coarse aggregate to fine aggregate ratio, water, metakaolin, super plasticizer, largest maximum size and binder as well as one output parameter, which is the 28-days compressive strength. The efficiency of the proposed techniques has been demonstrated by means of certain statistical criteria. The findings have been compared to experimental results and their comparisons shows that the MARS and M5P MT approaches predict the compressive strength of SCC incorporating metakaolin with great precision. The performed sensitivity analysis to assign effective parameters on 28-days compressive strength indicates that cementitious binder content is the most effective variable in the mixture.

Performance Analysis of Sensor Network Real-Time Traffic for Factory Automation in Intranet Environment (인트라넷 환경에서의 공장자동화를 위한 센서 망 실시간 트래픽 성능 평가)

  • Song, Myoung-Gyu;Choo, Young-Yeol
    • Journal of Korea Multimedia Society
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    • v.11 no.7
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    • pp.1007-1015
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    • 2008
  • In order to provide real-time data from sensors and instruments at manufacturing processes on web, we proposed a communication service model based on XML(eXtensible Markup Language). HTML(Hyper Text Markup Language) is inadequate for describing real-time data from manufacturing plants while it is suitable for display of non-real-time multimedia data on web. For applying XML-based web service of process data in Intranet environment, real-time performance of communication services was evaluated to provide the system design criteria. XML schema for the data presentation was proposed and its communication performance was evaluated by simulation in terms of transmission delay due to increased message length and processing delay for transformation of raw data into defined format. For transformation of raw data into XML format, we proposed two structures: one is the scheme where transformation is done at an SCC(Supervisory Control Computer) after receiving real-time data from instruments. the other is the scheme where transformation is carried out at instruments before the data are transmitted to the SCC. Performances of two structures were evaluated on a testbed under various conditions such as six packet sizes and offered loads of 20%, 50% and 80%, respectively. Test results show that proposed schemes are applicable to the systems in Ethernet 100BaseT network if total message traffic is less than 7 Mbps.

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MAKING IN VIVO MODEL TO STUDY ABOUT HUMAN ORAL CANCER (I) (구강암 연구를 위한 동물실험모델의 개발(I))

  • Park, Hyung-Kook;Kim, Yong-Kack
    • Maxillofacial Plastic and Reconstructive Surgery
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    • v.19 no.3
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    • pp.300-310
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    • 1997
  • In order to make in vivo model of human oral squamous cell cancer, we brought up BALB/C nude mice in specially designed housystem, and maintained some kind of human oral squamous cancer cell lines ; KB, SCC-4, SCC-9, SCC-15, SCC-25. Various concentration of cancer cells were inoculated subcutaneouly into flank area of nude mice. We observed each nude mouse more than 5 weeks after tumor inoculation. We appraised the results, measured the tumor size, and calculated the growing tumor volumes after tumor inoculation according to cancer cell line and concentration of cancer cells in media. Some cancer cell lines were rapidly growing in nude mice, but some cancer cell line couldn't grow in nude mice and resorbed completely. And in some cancer cell line, some nude mice showed continuously growing tumor, but other didn't show any tumor growing. And as a new try, we implanted specially disigned caps on the back of nude mice, and cancer cell lines were brought into the caps with media. We removed the cap after 1 week, and observed over 4 weeks. The shape and size of growing tumor were observed.

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Predictions of PD-L1 Expression Based on CT Imaging Features in Lung Squamous Cell Carcinoma (편평세포폐암에서 CT 영상 소견을 이용한 PD-L1 발현 예측)

  • Seong Hee Yeo;Hyun Jung Yoon;Injoong Kim;Yeo Jin Kim;Young Lee;Yoon Ki Cha;So Hyeon Bak
    • Journal of the Korean Society of Radiology
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    • v.85 no.2
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    • pp.394-408
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    • 2024
  • Purpose To develop models to predict programmed death ligand 1 (PD-L1) expression in pulmonary squamous cell carcinoma (SCC) using CT. Materials and Methods A total of 97 patients diagnosed with SCC who underwent PD-L1 expression assay were included in this study. We performed a CT analysis of the tumors using pretreatment CT images. Multiple logistic regression models were constructed to predict PD-L1 positivity in the total patient group and in the 40 advanced-stage (≥ stage IIIB) patients. The area under the receiver operating characteristic curve (AUC) was calculated for each model. Results For the total patient group, the AUC of the 'total significant features model' (tumor stage, tumor size, pleural nodularity, and lung metastasis) was 0.652, and that of the 'selected feature model' (pleural nodularity) was 0.556. For advanced-stage patients, the AUC of the 'selected feature model' (tumor size, pleural nodularity, pulmonary oligometastases, and absence of interstitial lung disease) was 0.897. Among these factors, pleural nodularity and pulmonary oligometastases had the highest odds ratios (8.78 and 16.35, respectively). Conclusion Our model could predict PD-L1 expression in patients with lung SCC, and pleural nodularity and pulmonary oligometastases were notable predictive CT features of PD-L1.

Comparative Evaluation on Collision and Particle Separation Efficiency between CO2 Bubbles and Air Bubbles Using Contact Zone Model of Flotation Process (부상분리 공정의 접촉영역 모델을 이용한 이산화탄소와 공기 기포의 충돌 및 입자 분리효율 비교 평가)

  • Yang, Jong-Won;Choi, Yong-Ho;Chae, In-Seok;Kim, Mi-Sug;Jeong, Yong-Hoon;Kim, Tae-Geum;Kwak, Dong-Heui
    • Journal of Korean Society on Water Environment
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    • v.35 no.1
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    • pp.64-71
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    • 2019
  • In recent years, carbon dioxide ($CO_2$) bubbles emerged as the most widely applied material with the recycling of sequestrated storage to decrease global warming. Flotation using $CO_2$ as an alternative to air could be effective in overcoming the high power consumption in the dissolved air flotation (DAF) process. The comparison of DAF and DCF system indicated that, the carbon dioxide flotation (DCF) system with pressurized $CO_2$ only requires 1.5 ~ 2.0 atm, while the DAF system requires 3.0 ~ 6.0 atm. In a bid to understand the characteristics of particle separation, the single collector collision (SCC) model was used and a series of simulations were conducted to compare the differences of collision and flotation between $CO_2$ bubbles and air bubbles. In addition, laboratory experiments were sequentially done to verify the simulation results of the SCC model. Based on the simulation results, surfactant injection, which is known to decrease bubble size, cloud improved the collision efficiency of $CO_2$ bubbles similar to that of air bubbles. Furthermore, the results of the flotation experiments showed similar results with the simulation of the SCC model under anionic surfactant injection. The findings led us to conclude that $CO_2$ bubbles can be an alternative to air bubbles and a promising material as a collector to separate particles in the water and wastewater.

Effect of Lymphangiogenic Factors on Survival in a Murine Model of Oral Squamous Cell Carcinoma (구강암 마우스모델에서 림프관형성 인자가 생존율에 미치는 영향)

  • Park, Young-Wook;Cho, Ju-Won
    • Maxillofacial Plastic and Reconstructive Surgery
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    • v.35 no.1
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    • pp.1-12
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    • 2013
  • Purpose: Vascular endothelial growth factor (VEGF)-C and its tyrosine kinase receptor, VEGF receptor (VEGFR)-3 are recently known to have lymphangiogenic activities in various tumor types. In this study, we determined whether the expression of lymphangiogenic factors correlate with nodal metastasis or survival in a nude mouse model of oral squamous cell carcinoma (OSCC). Methods: Three OSCC cells (KB, SCC4, SCC9) were xenografted into the right mandibular gland of athymic nude mice. The mice were followed for tumor development and growth, and the mice were sacrificed when they had lost more than 20% of their initial body weight, or the diameter of the induced tumor exceeds 20 mm. After necropsy, the murine tumors were examined histologically and radiologically (micro-positron emission tomography computed tomography) for regional or distant metastasis. We performed immunohistochemical assays with anti-VEGF-C, VEGFR-3, CD105, and D2-40 antibodies. Immunofluorescence double staining for LYVE-1/CD31 was also performed. To quantify the VEGF-C and VEGFR-3 level in the cancer tissue, Western blotting was performed. Finally, we determined the correlation between the degree of expression of VEGF-C/VEGFR-3 and the mean survival time. Results: OSCC tumor cells into the mandibular gland of the nude mice successfully resulted in the formation of recapitulating orthotopic tumor. Tumor cells of the induced tumor did not express VEGF-C. VEGF-C/VEGFR-3 expression was mainly distributed in the endothelial cells of the stromal area. There were no correlation between the degree of expression of VEGF-C/VEGFR-3 and the mean survival time of mice injected with different OSCC cell lines. Conclusion: An recapitulating orthotopic model of OSCC in nude mice was established, which copies the cervical nodal metastasis of human OSCC. Overexpression of lymphangiogenic factors seems to have no effect on survival of hosts in this in vivo experiment.