• Korean Journal of Soil Science and Fertilizer
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• v.21 no.4
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• pp.386-408
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• 1988

A study was conducted to develop a model for estimating evapotranspiration and yield of Chinese cabbages from meteorological factors from 1981 to 1986 in Suweon, Korea. Lysimeters with water table maintained at 50cm depth were used to measure the potential evapotranspiration and the maximum evapotranspiration in situ. The actual evapotranspiration and the yield were measured in the field plots irrigated with different soil moisture regimes of -0.2, -0.5, and -1.0 bars, respectively. The soil water content throughout the profile was monitored by a neutron moisture depth gauge and the soil water potentials were measured using gypsum block and tensiometer. The fresh weight of Chinese cabbages at harvest was measured as yield. The data collected in situ were analyzed to obtain parameters related to modeling. The results were summarized as followings: 1. The 5-year mean of potential evapotranspiration (PET) gradually increased from 2.38 mm/day in early April to 3.98 mm/day in mid-June, and thereafter, decreased to 1.06 mm/day in mid-November. The estimated PET by Penman, Radiation or Blanney-Criddle methods were overestimated in comparison with the measured PET, while those by Pan-evaporation method were underestimated. The correlation between the estimated and the measured PET, however, showed high significance except for July and August by Blanney-Criddle method, which implied that the coefficients should be adjusted to the Korean conditions. 2. The meteorological factors which showed hgih correlation with the measured PET were temperature, vapour pressure deficit, sunshine hours, solar radiation and pan-evaporation. Several multiple regression equations using meteorological factors were formulated to estimate PET. The equation with pan-evaporation (Eo) was the simplest but highly accurate. PET = 0.712 + 0.705Eo 3. The crop coefficient of Chinese cabbages (Kc), the ratio of the maximum evapotranspiration (ETm) to PET, ranged from 0.5 to 0.7 at early growth stage and from 0.9 to 1.2 at mid and late growth stages. The regression equation with respect to the growth progress degree (G), ranging from 0.0 at transplanting day to 1.0 at the harvesting day, were: $$Kc=0.598+0.959G-0.501G^2$$ for spring cabbages $$Kc=0.402+1.887G-1.432G^2$$ for autumn cabbages 4. The soil factor (Kf), the ratio of the actual evapotranspiration to the maximum evapotranspiration, showed 1.0 when the available soil water fraction (f) was higher than a threshold value (fp) and decreased linearly with decreasing f below fp. The relationships were: Kf=1.0 for $$f{\geq}fp$$ Kf=a+bf for f$$I{\leq}Esm$$ Es = Esm for I > Esm 6. The model for estimating actual evapotranspiration (ETa) was based on the water balance neglecting capillary rise as: ETa=PET. Kc. Kf+Es 7. The model for estimating relative yield (Y/Ym) was selected among the regression equations with the measured ETa as: Y/Ym=a+bln(ETa) The coefficients and b were 0.07 and 0.73 for spring Chinese cabbages and 0.37 and 0.66 for autumn Chinese cabbages, respectively. 8. The estimated ETa and Y/Ym were compared with the measured values to verify the model established above. The estimated ETa showed disparities within 0.29mm/day for spring Chinese cabbages and 0.19mm/day for autumn Chinese cabbages. The average deviation of the estimated relative yield were 0.14 and 0.09, respectively. 9. The deviations between the estimated values by the model and the actual values obtained from three cropping field experiments after the completion of the model calibration were within reasonable confidence range. Therefore, this model was validated to be used in practical purpose.

• Geotechnical Engineering
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• v.14 no.3
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• pp.25-46
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• 1998

This paper shows that there are the results of a series of model tests on the behavior of single pipe pile which is subjected to lateral load in, Nak-dong River sand. The purpose of the present paper is to estimate the effect of Non-homogeneity. constraint condition of pile head, lateral load velocity, relative density, and embedded length of pile on the behavior of single pile. These effects can be quantified only by the results of model tests. Also, these are compared with the results of the numerical methods (p-y method, modified Vlasov method; new ${\gamma}$ parameter, Characteristic Load Method'CLM). In this study, a new ${\gamma}$ parameter equation based on the Vlasov method was developed to calculate the modulus of subgrade reaction (E. : nhz.) proportional to the depth. The p-y method of analysis is characterized by nonlinear behavior. and is an effective method of designing deep foundations subjected to lateral loads. The new method, which is called the characteristic load method (CLM). is simpler than p-y analysis. but its results closely approximates p-y analysis results. The method uses dimensional analysis to characterize the nonlinear behavior of laterally loaded piles with respect to be relationships among dimensionless variables. The modulus of subgrade reaction used in p-y analysis and modified Vlasov method obtained from back analysis using direct shear test (DST) results. The coefficients obtained from DST and the modified ones used for the prediction of lateral behavior of ultimate soil reaction range from 0.014 to 0.05. and from 0.2 to 0.4 respectively. It is shown that the predicted numerical results by the new method (CLM), p-y analysis, and modified Vlasov method (new parameter) agree well with measured results as the relative density increases. Also, the characteristic load method established applicability on the Q-Mnu. relationship below y/D=0.2.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.3 no.4
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• pp.249-260
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• 1998

To understand the attachment of micro algae and their subsequent growths on artificial surfaces immersed in seawater, the relationship between attachment of diatoms on the immersed artificial substrates and species pool in the surrounding water was investigated. We used acryl slides for the study of diatom attachment and examined the surrounding water samples collected in Incheon Harbour from July 1995 to February 1997. Variations of species composition and abundances by exposure time in seawater were investigated during the early phase of biofilm formation on various substrates, e.g. glass, acryl, titanium, copper and antifouling paint-treated slides. Immigration rates of diatoms to acryl slides during spring and winter were significantly correlated with the abundance of benthic diatoms in surrounding water ($r^2$=0.78, p<0.01, n=42), suggesting that immigration rates were affected by variations of benthic diatom abundances in surrounding water. Immigration coefficient of monoraphid diatoms was 5 times higher than that of biraphid diatoms, but relative abundance of monoraphid diatoms was 3 times lower than that of biraphid diatoms on acryl slides in spring. In winter, immigration coefficient and relative abundance of centric diatoms were higher compared to other raphe forms. These results suggest that the attachment of diatoms seems to be caused by the abundance and immigration coefficients of benthic diatoms in surrounding water. Pennate diatoms predominantly attached to all artificial surfaces throughout all experimental periods. Interestingly, centric diatoms predominantly attached to all artificial surfaces in winter. Hantzschia virgata, Licmophora abbreviata and Melosira nummuloides appeared dominantly on antifouling paint-treated slides, probably being tolerant of the antifouling paint. During incubations, the abundance of attached diatoms increased exponentially on glass, titanium and acryl slides with exposure time. The maximum abundance was highest on glass slide, followed by acryl, titanium, copper and antifouling paint-treated slides. The growth rates of attached diatom community on all artificial surfaces were higher at temperature of $24-25^{\circ}C$ than that of $2-3^{\circ}C$. The growth rate of attached diatoms on glass slide was generally higher compared to other slides during the study period. Dominant morphotypes of observed species with exposure time in seawater were prostrate form Amphora coffeaeformis, fan shape Synedra tabulata, stalk type Licmophora paradoxa and chain type M. nummuloides. A micro-succession in the attached microalgal community was observed. The composition of dominant species seems to be the result of species-specific response to gradually limited space with development of microalgal film.

• Magazine of the Korean Society of Agricultural Engineers
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• v.19 no.1
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• pp.4279-4295
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• 1977

Two types of model were established in order to product the soil moisture content by which information on irrigation could be obtained. Model-I was to represent the soil moisture depletion and was established based on the concept of water balance in a given soil profile. Model-II was a mathematical model derived from the analysis of soil moisture variation curves which were drawn from the observed data. In establishing the Model-I, the method and procedure to estimate parameters for the determination of the variables such as evapotranspirations, effective rainfalls, and drainage amounts were discussed. Empirical equations representing soil moisture variation curves were derived from the observed data as the Model-II. The procedure for forecasting timing and amounts of irrigation under the given soil moisture content was discussed. The established models were checked by comparing the observed data with those predicted by the model. Obtained results are summarized as follows: 1. As a water balance model of a given soil profile, the soil moisture depletion D, could be represented as the equation(2). 2. Among the various empirical formulae for potential evapotranspiration (Etp), Penman's formula was best fit to the data observed with the evaporation pans and tanks in Suweon area. High degree of positive correlation between Penman's predicted data and observed data with a large evaporation pan was confirmed. and the regression enquation was Y=0.7436X+17.2918, where Y represents evaporation rate from large evaporation pan, in mm/10days, and X represents potential evapotranspiration rate estimated by use of Penman's formula. 3. Evapotranspiration, Et, could be estimated from the potential evapotranspiration, Etp, by introducing the consumptive use coefficient, Kc, which was repre sensed by the following relationship: Kc=Kco$.$Ka＋Ks‥‥‥(Eq. 6) where Kco : crop coefficient Ka : coefficient depending on the soil moisture content Ks : correction coefficient a. Crop coefficient. Kco. Crop coefficients of barley, bean, and wheat for each growth stage were found to be dependent on the crop. b. Coefficient depending on the soil moisture content, Ka. The values of Ka for clay loam, sandy loam, and loamy sand revealed a similar tendency to those of Pierce type. c. Correction coefficent, Ks. Following relationships were established to estimate Ks values: Ks=Kc-Kco$.$Ka, where Ks=0 if Kc,=Kco$.$K0$\geq$1.0, otherwise Ks=1-Kco$.$Ka 4. Effective rainfall, Re, was estimated by using following relationships : Re=D, if R-D$\geq$0, otherwise, Re=R 5. The difference between rainfall, R, and the soil moisture depletion D, was taken as drainage amount, Wd. {{{{D= SUM from { {i }=1} to n (Et-Re-I+Wd)}}}} if Wd=0, otherwise, {{{{D= SUM from { {i }=tf} to n (Et-Re-I+Wd)}}}} where tf=2∼3 days. 6. The curves and their corresponding empirical equations for the variation of soil moisture depending on the soil types, soil depths are shown on Fig. 8 (a,b.c,d). The general mathematical model on soil moisture variation depending on seasons, weather, and soil types were as follow: {{{{SMC= SUM ( { C}_{i }Exp( { - lambda }_{i } { t}_{i } )+ { Re}_{i } - { Excess}_{i } )}}}} where SMC : soil moisture content C : constant depending on an initial soil moisture content $\lambda$ : constant depending on season t : time Re : effective rainfall Excess : drainage and excess soil moisture other than drainage. The values of $\lambda$ are shown on Table 1. 7. The timing and amount of irrigation could be predicted by the equation (9-a) and (9-b,c), respectively. 8. Under the given conditions, the model for scheduling irrigation was completed. Fig. 9 show computer flow charts of the model. a. To estimate a potential evapotranspiration, Penman's equation was used if a complete observed meteorological data were available, and Jensen-Haise's equation was used if a forecasted meteorological data were available, However none of the observed or forecasted data were available, the equation (15) was used. b. As an input time data, a crop carlender was used, which was made based on the time when the growth stage of the crop shows it's maximum effective leaf coverage. 9. For the purpose of validation of the models, observed data of soil moiture content under various conditions from May, 1975 to July, 1975 were compared to the data predicted by Model-I and Model-II. Model-I shows the relative error of 4.6 to 14.3 percent which is an acceptable range of error in view of engineering purpose. Model-II shows 3 to 16.7 percent of relative error which is a little larger than the one from the Model-I. 10. Comparing two models, the followings are concluded: Model-I established on the theoretical background can predict with a satisfiable reliability far practical use provided that forecasted meteorological data are available. On the other hand, Model-II was superior to Model-I in it's simplicity, but it needs long period and wide scope of observed data to predict acceptable soil moisture content. Further studies are needed on the Model-II to make it acceptable in practical use.

• Progress in Medical Physics
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• v.17 no.1
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• pp.1-5
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• 2006

A parallel plate detector containing PTFE films in FEP film for relative dosimetry was designed to measure the response of detectors to S and 10 MV X-rays from a medical linear accelerator through different thicknesses of lead. The dielectric materials were 100 m thick. The set-up conditions for measurements with this detector were as follows: SSD=100 cm the test detector was at a depth of 5 cm and the reference chamber was at a depth of 10 cm from the phantom surface for 6 and 10 MV X-rays. Lead blocks were designed to cover the irradiated field. They were added to the tray to increase thickness sequentially. We found that the detector response decreased exponentially with the thickness of lead added. The linear attenuation coefficients of the test detector and reference chamber were 0.1414 and 0.541, respectively, for 6 MV X-rays and 0.1358 and 0.5279 for 10 MV X-rays. The test detector response was greater than that of the reference chamber. The response function was calculated from the measured values of the test detector and reference chamber using optimization. These optimized constants for the detector response function were independent of theenergy. As a result of optimizing the response function between detectors, the use of a relative dosimeter was validated, because the response of the test detector was 1% for 6 MV X-rays and 4% for 10 MV X-rays.

• Journal of the Korean earth science society
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• v.40 no.5
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• pp.447-463
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• 2019

Sea surface wind is a fundamental element for understanding the oceanic phenomena and for analyzing changes of the Earth environment caused by global warming. Global research institutes have developed and operated scatterometers to accurately and continuously observe the sea surface wind, with the accuracy of approximately ${\pm}20^{\circ}$ for wind direction and ${\pm}2m\;s^{-1}$ for wind speed. Given that the spatial resolution of the scatterometer is 12.5-25.0 km, the applicability of the data to the coastal area is limited due to complicated coastal lines and many islands around the Korean Peninsula. In contrast, Synthetic Aperture Radar (SAR), one of microwave sensors, is an all-weather instrument, which enables us to retrieve sea surface wind with high resolution (<1 km) and compensate the sparse resolution of the scatterometer. In this study, we investigated the Geophysical Model Functions (GMF), which are the algorithms for retrieval of sea surface wind speed from the SAR data depending on each band such as C-, L-, or X-band radar. We reviewed in the simulation of the backscattering coefficients for relative wind direction, incidence angle, and wind speed by applying LMOD, CMOD, and XMOD model functions, and analyzed the characteristics of each GMF. We investigated previous studies about the validation of wind speed from the SAR data using these GMFs. The accuracy of sea surface wind from SAR data changed with respect to observation mode, GMF type, reference data for validation, preprocessing method, and the method for calculation of relative wind direction. It is expected that this study contributes to the potential users of SAR images who retrieve wind speeds from SAR data at the coastal region around the Korean Peninsula.

• Korean Journal of Ecology and Environment
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• v.54 no.4
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• pp.303-314
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• 2021

To understand how to efficiently observe the biomass and community of phytoplankton, phytoplankton sampling was carried out from June to October 2019 at the Yeongju dam sediment control reservoir(YJ) and Bohyeonsan dam reservoir(BH1 and BH2). The results derived from microscopic observation, such as the conventional phytoplankton qualitative/quantitative analysis, and from the CHEMTAX method based on the pigments, were compared. The relative contribution of phytoplankton, calculated by the microscopy and CHEMTAX methods, showed a significant difference in all four classes: cryptophyta, chlorophyta, cyanobacteria, and diatoms. In addition, the correlation between the two observation methods was poor. This might be caused by methodological differences in microscopy that do not consider the varying cell sizes among phytoplankton species. In this study, by converting the cells into carbon, the slope between both carbon biomasses based on microscopy and CHEMTAX was improved close to the 1 : 1 line, and the y-intercept was closer to 0 for cryptophyta and diatoms. For cyanobacteria, the slope increased, the y-intercept decreased, and the plot approached 1 : 1 although the correlation coefficients were not improved in all classes. The present study suggests that application of CHEMTAX based on pigment analysis could be a possible approach to efficiently determine the relative carbon proportions of individual classes of phytoplankton community composition.

• Journal of the Microelectronics and Packaging Society
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• v.28 no.4
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• pp.11-18
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• 2021

A novel microwave dielectric composite material for ultra-low temperature co-fired ceramics (ULTCC) with (1-x)BaWO₄-xBaV₂O₆ (x=0.54~0.85) composition was prepared by firing a mixture of BaWO₄ and BaV₂O₆. Shrinkage tests showed that the ceramic composite begins to densify at a temperature as low as 550℃ and can be sintered at 650℃ with 98% of relative density under the influence of BaV₂O₆. X-ray diffraction analysis showed that BaWO₄ and BaV₂O₆ coexisted and no secondary phase was detected in the sintered bodies, implying good chemical compatibility between the two phases. Near-zero temperature coefficients of the resonant frequency (𝛕_f) could be achieved by controlling the relative content of the two phases, due to their positive and negative 𝛕_f values, respectively. With increasing BaV₂O₆ (x from 0.53 to 0.85), the 𝛕_f value of the composites increased from -7.54 to 14.49 ppm/℃, ε_r increased from 10.08 to 11.17 and the quality factor (Q×f value) decreased from 47,661 to 37,131 GHz. The best microwave dielectric properties were obtained for x=0.6 samples with ε_r=10.4, Q×f=44,090 GHz, and 𝛕_f=-2.38 ppm/℃. Chemical compatibility experiments showed the developed composites are compatible with aluminum electrode during co-firing process.

• Applied Biological Chemistry
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• v.16 no.2
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• pp.99-111
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• 1973

Percentage recovery or fertilizer nitrogen, phosphorus and potassium by rice plant(Oriza sativa L.) were investigated at 8, 10, 12, 14 kg/10a of N, 6 kg of $P_2O_5$ and 8 kg of $K_2O$ application level in 1967 (51 places) and 1968 (32 places). Two types of nutrient contribution for the yield, that is, P type in which phosphorus firstly increases silicate uptake and secondly silicate increases nitrogen uptake, and K type in which potassium firstly increases P uptake and secondly P increases nitrogen uptake were postulated according to the following results from the correlation analyses (linear) between percentage recovery of fertilizer nutrient and grain or dry matter yields and nutrient uptake. 1. Percentage frequency of minus or zero recovery occurrence was 4% in nitrogen, 48% in phosphorus and 38% in potassium. The frequency distribution of percentage recovery appeared as a normal distribution curve with maximum at 30 to 40 recovery class in nitrogen, but appeared as a show distribution with maximum at below zero class in phosphorus and potassium. 2. Percentage recovery (including only above zero) was 33 in N (above 10kg/10a), 27 in P, 40 in K in 1967 and 40 in N, 20 in P, 46 in Kin 1968. Mean percentage recovery of two years including zero for zero or below zero was 33 in N, 13 in P and 27 in K. 3. Standard deviation of percentage recovery was greater than percentage recovery in P and K and annual variation of CV (coefficient of variation) was greatest in P. 4. The frequency of significant correlation between percentage recovery and grain or dry matter yield was highest in N and lowest in P. Percentage recovery of nitrogen at 10 kg level has significant correlation only with percentage recovery of P in 1967 and only with that of potassium in 1968. 5. The correlation between percentage recovery and dry matter yield of all treatments showed only significant in P in 1967, and only significant in K in 1968, Negative correlation coefficients between percentage recovery and grain or dry matter yield of no or minus fertilizer plots were shown only in K in 1967 and only in P in 1968 indicating that phosphorus fertilizer gave a distinct positive role in 1967 but somewhat' negative role in 1968 while potassium fertilizer worked positively in 1968 but somewhat negatively in 1967. 6. The correlation between percentage recovery of nutrient and grain yield showed similar tendency as with dry matter yield but lower coefficients. Thus the role of nutrients was more precisely expressed through dry matter yield. 7. Percentage recovery of N very frequently had significant correlation with nitrogen uptake of nitrogen applied plot, and significant negative correlation with nitrogen uptake of minus nitrogen plot, and less frequently had significant correlation with P, K and Si uptake of nitrogen applied plot. 8. Percentage recovery of P had significant correlation with Si uptake of all treatments and with N uptake of all treatments except minus phosphorus plot in 1967 indicating that phosphorus application firstly increases Si uptake and secondly silicate increases nitrogen uptake. Percentage recovery of P also frequently had significant correlation with P or K uptake of nitrogen applied plot. 9. Percentage recovery of K had significant correlation with P uptake of all treatments, N uptake of all treatments except minus phosphorus plot, and significant negative correlation with K uptake of minus K plot and with Si uptake of no fertilizer plot or the highest N applied plot in 1968, and negative correlation coefficient with P uptake of no fertilizer or minus nutrient plot in 1967. Percentage recovery of K had higher correlation coefficients with dry matter yield or grain yield than with K uptake. The above facts suggest that K application firstly increases P uptake and secondly phosphorus increases nitrogen uptake for dry matter yied. 10. Percentage recovery of N had significant higher correlation coefficient with grain yield or dry matter yield of minus K plot than with those of minus phosphorus plot, and had higher with those of fertilizer plot than with those of minus K plot. Similar tendency was observed between N uptake and percentage recovery of N among the above treatments. Percentage recovery of K had negative correlation coefficient with grain or-dry matter yield of no fertilizer plot or minus nutrient plot. These facts reveal that phosphorus increases nitrogen uptake and when phosphorus or nitrogen is insufficient potassium competatively inhibits nitrogen uptake. 11. Percentage recovery of N, Pand K had significant negative correlation with relative dry matter yield of minus phosphorus plot (yield of minus plot x 100/yield of complete plot; in 1967 and with relative grain yield of minus K plot in 1968. These results suggest that phosphorus affects tillering or vegetative phase more while potassium affects grain formation or Reproductive phase more, and that clearly show the annual difference of P and K fertilizer effect according to the weather. 12. The correlation between percentage recovery of fertilizer and the relative yield of minus nutrient plat or that of no fertilizer plot to that of minus nutrient plot indicated that nitrogen is the most effective factor for the production even in the minus P or K plot. 13. From the above facts it could be concluded that about 40 to 50 percen of paddy fields do rot require P or K fertilizer and even in the case of need the application amount should be greatly different according to field and weather of the year, especially in phosphorus.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.8 no.2
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• pp.47-60
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• 1975

For the calculation of population parameter and estimation of recruitment of a fish population, an application of multiple regression method was used with some statistical inferences. Then, the differences between the calculated values and the true parameters were discussed. In addition, this method criticized by applying it to the statistical data of a population of bigeye tuna, Thunnus obesus of the Indian Ocean. The method was also applied to the available data of a population of Pacific saury, Cololabis saira, to estimate its recuitments. A stock at t year and t+1 year is, $N_{0,\;t+1}=N_{0,\;t}(1-m_t)-C_t+R_{t+1}$ where $N_0$ is the initial number of fish in a given year; C, number o: fish caught; R, number of recruitment; and M, rate of natural mortality. The foregoing equation is $$\phi_{t+1}=\frac{(1-\varrho^{-z}{t+1})Z_t}{(1-\varrho^{-z}t)Z_{t+1}}-\frac{1-\varrho^{-z}t+1}{Z_{t+1}}\phi_t-a'\frac{1-\varrho^{-z}t+1}{Z_{t+1}}C_t+a'\frac{1-\varrho^{-z}t+1}{Z_{t+1}}R_{t+1}......(1)$$ where $\phi$ is CPUE; a', CPUE $(\phi)$ to average stock $(\bar{N})$ in number; Z, total mortality coefficient; and M, natural mortality coefficient. In the equation (1) , the term $(1-\varrho^{-z}t+1)/Z_{t+1}$s almost constant to the variation of effort (X) there fore coefficients $\phi$ and $C_t$, can be calculated, when R is a constant, by applying the method of multiple regression, where $\phi_{t+1}$ is a dependent variable; $\phi_t$ and $C_t$ are independent variables. The values of Mand a' are calculated from the coefficients of $\phi_t$ and $C_t$; and total mortality coefficient (Z), where Z is a'X+M. By substituting M, a', $Z_t$, and $Z_{t+1}$ to the equation (1) recruitment $(R_{t+1})$ can be calculated. In this precess $\phi$ can be substituted by index of stock in number (N'). This operational procedures of the method of multiple regression can be applicable to the data which satisfy the above assumptions, even though the data were collected from any chosen year with similar recruitments, though it were not collected from the consecutive years. Under the condition of varying effort the data with such variation can be treated effectively by this method. The calculated values of M and a' include some deviation from the population parameters. Therefore, the estimated recruitment (R) is a relative value instead of all absolute one. This method of multiple regression is also applicable to the stock density and yield in weight instead of in number. For the data of the bigeye tuna of the Indian Ocean, the values of estimated recruitment (R) calculated from the parameter which is obtained by the present multiple regression method is proportional with an identical fluctuation pattern to the values of those derived from the parameters M and a', which were calculated by Suda (1970) for the same data. Estimated recruitments of Pacific saury of the eastern coast of Korea were calculated by the present multiple regression method. Not only spring recruitment $(1965\~1974)$ but also fall recruitment $(1964\~1973)$ was found to fluctuate in accordance with the fluctuations of stock densities (CPUE) of the same spring and fall, respectively.