• Journal of Soil and Groundwater Environment
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• v.13 no.5
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• pp.57-73
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• 2008

Nitrate concentrations were measured up to 49 mg/L (as $NO_3$-N) and 22% of the samples exceeded drinking water standard in shallow and bedrock groundwater of the northern Nonsan area. Nitrate concentrations showed a significant difference among land use groups. To predict nitrate concentration in groundwater, multiple regression analysis was carried out using hydrogeologic parameters of soil media, topography and land use which were categorized as several groups, well depth and altitude, and field parameters of temperature, pH, DO and EC. Hydrogeologic parameters were quantified as area proportions of each category within circular buffers centering at wells. Regression was performed to all the combination of variables and the most relevant model was selected based on adjusted coefficient of determination (Adj. $R^2$). Regression using hydrogelogic parameters with varying buffer radii show highest Adj. $R^2$ at 50m and 300m for shallow and bedrock groundwater, respectively. Shallow groundwater has higher Adj. $R^2$ than bedrock groundwater indicating higher susceptibility to hydrogeologic properties of surface environment near the well. Land use and soil media was major explanatory variables for shallow and bedrock groundwater, respectively and residential area was a major variable in both shallow and bedrock groundwater. Regression involving hydrogeologic parameters and field parameters showed that EC, paddy and pH were major variables in shallow groundwater whereas DO, EC and natural area were in bedrock groundwater. Field parameters have much higher explanatory power over the hydrogeologic parameters suggesting field parameters which are routinely measured can provide important information on each well in assessment of nitrate contamination. The most relevant buffer radii can be applied to estimation of travel time of contaminants in surface environment to wells.

• Information Systems Review
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• v.14 no.3
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• pp.25-51
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• 2012

The purpose of this study is to analyze the key factors affecting satisfaction of the visually impaired SNS users so that they may use SNS more effectively in the future. This study has used three factors such as the information factor, the relationship factor and the speed factor and the usability as independent variables. The social presence factor was used as a parameter and the SNS user satisfaction as a dependent variable. For the research, 195 visually impaired SNS users have participated in this survey. The major findings of this study are that the relationship factor has strong effects on the self-identification factor, the social presence factor and the SNS usage satisfaction among the factors affecting the visually impaired users to be satisfied with SNS. On the other hand, the information factor and usage factor have no effects on the self-identification factor and the social presence factor. However, they have effects on the SNS usage satisfaction. Additionally, the self-identification factor has no effect on the SNS usage satisfaction, but the social presence factor has effect. Based on the above study results, this paper proposed for the government to enhance the educational program on the use of SNS for the visually impaired and to increase its financial and political support on this subject. Additionally, technical supports on SNS service accessibility and usage by the government are vital for the visually impaired. Academically, this study provides a concrete groundwork for the research on the use of SNS by the visually impaired by providing a solid research direction for further study on this subject. Socially, this study helps the visually impaired use SNS more effectively by increasing the general public awareness of the importance of SNS usages by the visually impaired so that the information gap of the society may be diminished in the future.

• Investigative Magnetic Resonance Imaging
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• v.18 no.2
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• pp.120-132
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• 2014

Purpose : To compare dynamic susceptibility contrast imaging, diffusion-weighted imaging, and susceptibility-weighted imaging (SWI) for the differentiation of tumor recurrence and delayed radiation therapy (RT)-related changes in patients treated with RT for primary brain tumors. Materials and Methods: We enrolled 24 patients treated with RT for various primary brain tumors, who showed newly appearing enhancing lesions more than one year after completion of RT on follow-up MRI. The enhancing-lesions were confirmed as recurrences (n=14) or RT-changes (n=10). We calculated the mean values of normalized cerebral blood volume (nCBV), apparent diffusion coefficient (ADC), and proportion of dark signal intensity on SWI (proSWI) for the enhancing-lesions. All the values between the two groups were compared using t-test. A multivariable logistic regression model was used to determine the best predictor of differential diagnosis. The cutoff value of the best predictor obtained from receiver-operating characteristic curve analysis was applied to calculate the sensitivity, specificity, and accuracy for the diagnosis. Results: The mean nCBV value was significantly higher in the recurrence group than in the RT-change group (P=.004), and the mean proSWI was significantly lower in the recurrence group (P<.001). However, no significant difference was observed in the mean ADC values between the two groups. A multivariable logistic regression analysis showed that proSWI was the only independent variable for the differentiation; the sensitivity, specificity, and accuracy were 78.6% (11 of 14), 100% (10 of 10), and 87.5% (21 of 24), respectively. Conclusion: The proSWI was the most promising parameter for the differentiation of newly developed enhancing-lesions more than one year after RT completion in brain tumor patients.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.139-155
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• 2009

For the last few decades, many studies have tried to explore and unveil venture companies' success factors and unique features in order to identify the sources of such companies' competitive advantages over their rivals. Such venture companies have shown tendency to give high returns for investors generally making the best use of information technology. For this reason, many venture companies are keen on attracting avid investors' attention. Investors generally make their investment decisions by carefully examining the evaluation criteria of the alternatives. To them, credit rating information provided by international rating agencies, such as Standard and Poor's, Moody's and Fitch is crucial source as to such pivotal concerns as companies stability, growth, and risk status. But these types of information are generated only for the companies issuing corporate bonds, not venture companies. Therefore, this study proposes a method for evaluating venture businesses by presenting our recent empirical results using financial data of Korean venture companies listed on KOSDAQ in Korea exchange. In addition, this paper used multi-class SVM for the prediction of DEA-based efficiency rating for venture businesses, which was derived from our proposed method. Our approach sheds light on ways to locate efficient companies generating high level of profits. Above all, in determining effective ways to evaluate a venture firm's efficiency, it is important to understand the major contributing factors of such efficiency. Therefore, this paper is constructed on the basis of following two ideas to classify which companies are more efficient venture companies: i) making DEA based multi-class rating for sample companies and ii) developing multi-class SVM-based efficiency prediction model for classifying all companies. First, the Data Envelopment Analysis(DEA) is a non-parametric multiple input-output efficiency technique that measures the relative efficiency of decision making units(DMUs) using a linear programming based model. It is non-parametric because it requires no assumption on the shape or parameters of the underlying production function. DEA has been already widely applied for evaluating the relative efficiency of DMUs. Recently, a number of DEA based studies have evaluated the efficiency of various types of companies, such as internet companies and venture companies. It has been also applied to corporate credit ratings. In this study we utilized DEA for sorting venture companies by efficiency based ratings. The Support Vector Machine(SVM), on the other hand, is a popular technique for solving data classification problems. In this paper, we employed SVM to classify the efficiency ratings in IT venture companies according to the results of DEA. The SVM method was first developed by Vapnik (1995). As one of many machine learning techniques, SVM is based on a statistical theory. Thus far, the method has shown good performances especially in generalizing capacity in classification tasks, resulting in numerous applications in many areas of business, SVM is basically the algorithm that finds the maximum margin hyperplane, which is the maximum separation between classes. According to this method, support vectors are the closest to the maximum margin hyperplane. If it is impossible to classify, we can use the kernel function. In the case of nonlinear class boundaries, we can transform the inputs into a high-dimensional feature space, This is the original input space and is mapped into a high-dimensional dot-product space. Many studies applied SVM to the prediction of bankruptcy, the forecast a financial time series, and the problem of estimating credit rating, In this study we employed SVM for developing data mining-based efficiency prediction model. We used the Gaussian radial function as a kernel function of SVM. In multi-class SVM, we adopted one-against-one approach between binary classification method and two all-together methods, proposed by Weston and Watkins(1999) and Crammer and Singer(2000), respectively. In this research, we used corporate information of 154 companies listed on KOSDAQ market in Korea exchange. We obtained companies' financial information of 2005 from the KIS(Korea Information Service, Inc.). Using this data, we made multi-class rating with DEA efficiency and built multi-class prediction model based data mining. Among three manners of multi-classification, the hit ratio of the Weston and Watkins method is the best in the test data set. In multi classification problems as efficiency ratings of venture business, it is very useful for investors to know the class with errors, one class difference, when it is difficult to find out the accurate class in the actual market. So we presented accuracy results within 1-class errors, and the Weston and Watkins method showed 85.7% accuracy in our test samples. We conclude that the DEA based multi-class approach in venture business generates more information than the binary classification problem, notwithstanding its efficiency level. We believe this model can help investors in decision making as it provides a reliably tool to evaluate venture companies in the financial domain. For the future research, we perceive the need to enhance such areas as the variable selection process, the parameter selection of kernel function, the generalization, and the sample size of multi-class.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.46-46
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• 2011

Severe sediment erosion during floods occur disaster and economic losses, but general sediment erosion is basic mechanism to move sediment from upstream to downstream river. In addition, it is important process to change river form. Check dam, which is constructed in mountain stream, play a vital role such as control of sudden debris flow, but it has negative aspects to river ecosystem. Now a day, check dam of open type is an alternative plan to recover river biological diversity and ecosystem through sediment transport while maintaining the function of disaster control. The purpose of this paper is to verify sediment erosion progress of river bottom and bank as first step for river restoration after dam slit by cross-sectional shear stress and critical shear stress. Study area is upstream reach of slit check dam in mountain stream, named Wasada, in Japan. The check dam was slit with two passages in August, 2010. The transects were surveyed for four upstream cross-sections, 7.4 m, 34 m, 86 m, and 150 m distance from dam in October 2010. Sediment size was surveyed at river bottom and bank. Sediment of cobble size was found at the wetted bottom, and small size particles of sand to medium gravel composed river bank. Discharge was $2.5\;m^3/s$ and bottom slope was 0.027 m/m. Excess shear stress (${\tau}_{ex}$) was calculated for hydraulic erosion by subtracting the values of critical shear stress (${\tau}_{c}$) from the value of shear stress (${\tau}$) at river bottom and bank (${\tau}_{ex}=\tau-{\tau}_c$). Shear stress of river bottom (${\tau}_{bottom}$) was calculated using the cross-sectional shear stress, and bank shear stress (${\tau}_{bank}$) was calculated from the method of Flintham and Carling (1988). $${\tau}_{bank}={\tau}^*SF_{bank}((B+P_{bed})/(2^*P_{bank}))$$ where $SF_{bank}=1.77(P_{bed}/p_{bank}+1.5)^{-1.4}$, B is the water surface width, $P_{bed}$ and $P_{bank}$ are wetted parameter of the bed and bank. Estimated values for ${\tau}_{bottom}$ for a flow of $2.5\;m^3/s$ were lower as 25.0 (7.5 m cross-section), 25.7 (34 m), 21.3 (86 m) and 19.8 (150 m), in N/$m^2$, than critical shear stress (${\tau}_c=62.1\;N/m^2$) with cobble of 64 mm. The values were insufficient to erode cobble sediment. In contrast, even if the values of ${\tau}_{bank}$ were lower than the values for ${\tau}_{bottom}$ as 18.7 (7.5 m), 19.3 (34 m), 16.1 (86 m) and 14.7 (150 m), in N/$m^2$, excess shear stresses were calculated at the three cross-sections of 7.5 m, 34 m, and 86 m distances compare with ${\tau}_c$ is 15.5 N/$m^2$ of 16mm gravel. Bank shear stresses were sufficient for erosion of the medium gravel to sand. Therefore there is potential to erode lateral bank than downward erosion in a flow of $2.5\;m^3/s$. Undercutting of the wetted bank can causes bank scour or collapse, therefore this channel has potential to become wider at the same time. This research is about a potential of sediment erosion, and the result could not verify with real data. Therefore it need next step for verification. In addition an erosion mechanism for river restoration is not simple because discharge distribution is variable by snow-melting or rainy season, and a function for disaster control will recover by big precipitation event. Therefore it needs to consider the relationship between continuous discharge change and sediment erosion.

• Tuberculosis and Respiratory Diseases
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• v.45 no.1
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• pp.116-127
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• 1998

Background: The natural course of sarcoidosis is variable from spontaneous remission to significant morbidity or death. So the assessment of disease activity is important but no single parameter was generally accepted as a good marker. Recently several studies suggested that adhesion molecules, especially ICAM-1 can be a marker, but there are some controversies. And only few data are available about the relationship of ICAM-1 with clinical follow-up course. Methods: We measured the expression of adhesion molecules on BAL cells by flow cytometry and the level of soluble ICAM-1(sICAM-1) in serum and BALF at the time of diagnosis in 12 patients with active disease and 7 inactive sarcoidosis(5 male, 14 female, mean age: $39.4{\pm}10.7$ years, mean follow-up : $20{\pm}15$ months). Follow-up clinical course were compared with the changes in serum sICAMA-1 level and the adhesion molecule on BAL cells. Results: In the patients with active disease, the ICAM-1 on AM(RMFI: $3.68{\pm}1.71$) and sICAM-1 level in serum($582{\pm}193$ng/ml) and BAL fluid($47.8{\pm}16.5$ng/ml) were all higher than those of 7 inactive disease(RMFI: $1.89{\pm}0.75$, p=0.0298, serum: $294{\pm}117$ ng/ml, p=0.0049, BALF: $20.9{\pm}8.3$ ng/ml). In the active sarcoidosis, ICAM-1 on AM(RMFI : $1.51{\pm}0.84$) and serum sICAM-1 were decreased after the therapy($250{\pm}147$ ng/ml) but no significant change was noted in inactive disease. Also we found the initial ICAM-1 on AM and serum sICAM-1 had a significant correlation with the degree of improvement in PFT after the therapy. During the follow-up, the disease relapsed in 4 patients after the discontinuation of steroid and the serum sICAM-1 level went-up again at the time of relapse. Conclusion: Our data suggest that the serum sICAM-1 level and the ICAM-1 expression on AM can be a good marker of disease activity and also a predictor of outcome in sarcoidosis.

• Korean journal of applied entomology
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• v.25 no.4 s.69
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• pp.221-228
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• 1986

An empirical model to predict initial disease occurrence and subsequent progress of Alternaria leaf spot was constructed based on the modified degree day temperature and frequency of rainfall in three years field experiments. Climatic factors were analized 10-day bases, beginning April 20 to the end of August, and were used as variables for model construction. Cumulative degree portion (CDP) that is over $10^{\circ}C$ in the daily average temperature was used as a parameter to determine the relationship between temperature and initial disease occurrence. Around one hundred and sixty of CDP was needed to initiate disease incidence. This value was considered as temperature threshhold. After reaching 160 CDP, time of initial occurrence was determined by frequency of rainfall. At least four times of rainfall were necessary to be accumulated for initial occurrence of the disease after passing temperature threshhold. Disease progress after initial incidence generally followed the pattern of frequency of rainfall accumulated in those periods. Apparent infection rate (r) in the general differential equation dx/dt=xr(1-x) for individual epidemics when x is disease proportion and t is time, was a linear function of accumulation rate of rainfall frequency (Rc) and was able to be directly estimated based on the equation r=1.06Rc-0.11($R^2=0.993$). Disease severity (x) after t time could be predicted using exponential equation $[x/(1-x)]=[x_0/(1-x)]e^{(b_0+b_1R_c)t}$ derived from the differential equation, when $x_0$ is initial disease, $b_0\;and\;b_1$ are constants. There was a significant linear relationship between disease progress and cumulative number of air-borne conidia of Alternaria mali. When the cumulative number of air-borne conidia was used as an independent variable to predict disease severity, accuracy of prediction was poor with $R^2=0.3328$.

• Progress in Medical Physics
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• v.15 no.4
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• pp.202-209
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• 2004

Flat panel based digital radiography (DR) systems have recently become useful and important in the field of diagnostic radiology. For DRs with amorphous silicon photosensors, CsI(TI) is normally used as the scintillator, which produces visible light corresponding to the absorbed radiation energy. The visible light photons are converted into electric signal in the amorphous silicon photodiodes which constitute a two dimensional array. In order to produce good quality images, detailed behaviors of DR detectors to radiation must be studied. The relationship between air exposure and the DR outputs has been investigated in many studies. But this relationship was investigated under the condition of the fixed tube voltage. In this study, we investigated the relationship between the DR outputs and X-ray in terms of the absorbed energy in the detector rather than the air exposure using SPEC-l8, an X-ray energy spectrum model. Measured exposure was compared with calculated exposure for obtaining the inherent filtration that is a important input variable of SPEC-l8. The absorbed energy in the detector was calculated using algorithm of calculating the absorbed energy in the material and pixel values of real images under various conditions was obtained. The characteristic curve was obtained using the relationship of two parameter and the results were verified using phantoms made of water and aluminum. The pixel values of the phantom image were estimated and compared with the characteristic curve under various conditions. It was found that the relationship between the DR outputs and the absorbed energy in the detector was almost linear. In a experiment using the phantoms, the estimated pixel values agreed with the characteristic curve, although the effect of scattered photons introduced some errors. However, effect of a scattered X-ray must be studied because it was not included in the calculation algorithm. The result of this study can provide useful information about a pre-processing of digital radiography.

• Korean Journal of Environmental Biology
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• v.36 no.4
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• pp.479-487
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• 2018

The purpose of this study is to analyze photochemical activity of nursery seedlings under drought stress, using chlorophyll fluorescence reaction analysis. Young nursery seedlings of tomato (Lycopersicon esculentum Mill.) and cucumber (Cucumis sativa L.), were grown under drought stress for 8 days. Analysis of chlorophyll fluorescence reaction (OJIP) and parameters, were performed to evaluate photochemical fluctuation in nursery seedlings under drought stress. Chlorophyll fluorescence reaction analysis showed maximal recorded fluorescence (P) decreased from the 5 day after treatment in tomato seedlings, while an amount of chlorophyll fluorescence increased at the J-I step. Thus, physiological activity was reduced. In cucumber seedlings, maximal recorded fluorescence (P) and maximal variable fluorescence ($F_V$) lowered from the 4 day after treatment, and chlorophyll fluorescence intensity of J-I step increased. Chlorophyll fluorescence parameter analysis showed electron transfer efficiency of PSII and PSI were significantly inhibited with decreasing $ET2_O/RC$ and $RE1_O/RC$ from the 5 day after treatment, in tomato seedlings and from the 4 day after treatment, in cucumber seedlings. $ET2_O/RC$ and $PI_{ABS}$ significantly changed. In conclusion, 6 indices such as $F_V/F_M$, $DI_O/RC$, $ET2_O/RC$, $RE1_O/RC$, $PI_{ABS}$ and $PI_{TOTAL}ABS$ were selected for determining drought stress in nursery seedlings. Drought stress factor index (DFI) was used to evaluate whether the crop was healthy or not, under drought stress. Cucumber seedlings were less resistant to drought stress than tomato seedlings, in the process of drought stress.

• Tuberculosis and Respiratory Diseases
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• v.46 no.2
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• pp.215-228
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• 1999

Background: Sarcoidosis is a chronic granulomatous inflammatory disease of unknown etiology often involving the lungs and intrathoracic lymph nodes. The natural course of sarcoidosis is variable from spontaneous remission to significant morbidity or death. But, the mechanisms causing the variable clinical outcomes or any single parameter to predict the prognosis was not known. In sarcoidosis, the number and the activity of CD4 + lymphocytes are significantly increased at the loci of disease and their oligoclonality suggests that the CD4 + lymphocytes hyperreactivity may be caused by persistent antigenic stimulus. Recently, it has been known that CD4+ lymphocytes can be subdivided into 2 distinct population(Th1 and Th2) defined by the spectrum of cytokines produced by these cells. Th1 cells promote cellular immunity associated with delayed type hypersensitivity reactions by generating IL-2 and IFN-$\gamma$. Th2 cells playa role in allergic responses and immediate hypersensitivity reactions by secreting IL-4, IL-5, and IL-10. CD4+ lymphocytes in pulmonary sarcoidosis were reported to be mainly Th1 cells. IL-12 has been known to play an important role in differentiation of undifferentiated naive T cells to Th1 cells. And, Moller et al. observed increased IL-12 in bronchoalveolar lavage fluid(BALF) in patients with sarcoidosis. So it is possible that the elevated level of IL-12 is necessary for the continuous progression of the disease in active sarcoidosis. This study was performed to test the assumption that IL-12 can be a marker of active pulmonary sarcoidosis. Methods: We measured the concentration of IL-12 in BALF and in conditioned medium of alveolar macrophage(AM) using ELISA(enzyme-linked immunosorbent assay) method in 26 patients with pulmonary sarcoidosis(10 males, 16 females, mean age: $39.8{\pm}2.1$ years) and 11 normal control. Clinically, 14 patients had active sarcoidosis and 12 patients had inactive. Results: Total cells counts, percentage and number of lymhocytes, number of AM and CD4/CD8 lymphocyte ratio in BALF were significantly higher in patients with sarcoidosis than in control group. But none of these parameters could differentiate active sarcoidosis from inactive disease. The concentration of IL-12 in BALF was significantly increased in sarcoidosis patients ($49.3{\pm}9.2$ pg/ml) than in normal control ($2.5{\pm}0.4$ pg/ml) (p<0.001). Moreover it was significantly higher in patients with active sarcoidosis ($70.3{\pm}14.8$ pg/ml) than in inactive disease ($24.8{\pm}3.l$ pg/ml) (p=0.001). Also, the concentration of IL-12 in BALF showed significant correlation with the percentage of AM(p<0.001), percentage(p<0.001) and number of lymphocyte(p<0.001) in BALF, suggesting the close relationship between the level of IL-12 in BALF and the inflammatory cell infiltration in the lungs. Furthermore, we found a significant correlation between the level of IL-12 and the concentration of soluble ICAM-1 : in serum(p<0.001) and BALF (p=0.001), and also between IL-12 level and ICAM-1 expression of AM(p<0.001). The AM from patients with pulmonary sarcoidosis secreted significantly larger amount of IL-12 ($206.2{\pm}61.9$ pg/ml) than those of control ($68.3{\pm}43.7$ pg/ml) (p<0.008), but, there was no difference between inactive and active disease group. Conclusion : Our data suggest that the BALF IL-12 level can be used as a marker of the activity of pulmonary sarcoidosis.