• Applied Biological Chemistry
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• v.23 no.1
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• pp.23-30
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• 1980

Labelling of chromatin proteins with 32P was observed after incubating isolated liver nuclei with $[{\gamma}-32P]$ ATP for 5 minutes at $37^{\circ}C$. The pattern of labelling with 32P was examined on SDS polyacrylamide gel electrophoresis with nuclei from rats maintained in a starvation state for 48 hours, following refeeding for 12 hours; and from fed streptozotocin-diabetic rats with insulin injection 6 hours before sacrifice. With 48h starved rat liver nuclei the level of phosphorylation for 0.14M NaCl soluble proteins was decreased in the molecular weights between 41,000 and 200,000 daltons relative to normal controls. Refeeding the starved rats reversed the change of phosphorylation pattern over 12 hour The level of phosphorylation for five phenol soluble non-histone proteins with molecular weights above 59,000 daltons was somewhat decreased with 48h starved rat liver nuclei as compared with that of normal controls. Starvation also decreased the phosphorylation level of major histones in relation to normal controls. The experiment with insulin injection into fed streptozotocin-diabetic rats showed the tendency to increase phosphorylation of 0.14M NaCl soluble proteins (130,000 dalton protein) and phenol soluble non-histone proteins (155,000 dalton protein). The phosphorylation level of histones appeared to be invariant under the experimental conditoins employed here. These results suggest the possibility that the phosphorylation and dephosphorylation of 0.14M NaCl soluble proteins and $H_1$ histone precede those of other chromatin associated nuclear proteins, It is of interest to find that insulin signal was correlated to phosphorylation of nuclear proteins while glucagon signet dephosphorylated nuclear proteins.

• Restorative Dentistry and Endodontics
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• v.24 no.4
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• pp.560-569
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• 1999

Blood supply rather than nerve supply implies pulp vitality. To evaluate pulp vitality clinically, electric pulp test and thermal test which are based on sensory nerve response have been used in addition to many auxiliary data such as past dental history, visual inspection, radiographic examination, percussion, palpation and transillumination test. However, reactivity of the nerves to the stimulation is not synonymous with normalcy. Therefore measurement of pulpal blood flow using a laser Doppler flowmeter became a new trial to test the pulp vitality. The purpose of the present study was to evaluate normal pulpal blood flow level of maxillary teeth in adult to provide a guideline in determining the vitality of dental pulp. Pulpal blood flow was measured in maxillary central and lateral incisors, canines, first and second premolars and first molars of seventy nine adults of 22 - 30 years old using a laser Doppler flowmeter (PeriFlux 4001, Perimed Co., Stockholm, Sweden, 780 nm infrared laser, 1mW). For directly-made splints, silicone rubber impressions were taken directly from the mouth. For indirectly-made splints, alginate impressions were taken from the mouth and stone cast were made. After making depressions on the buccal surfaces of the cast teeth to indicate the hole positions, second impressions with vinyl polysyloxane putty were taken from the cast. Holes for the laser probes were made at the putty impressions 4mm above the gingival level. Laser probe (PF416 dental probe, 1.5mm) was inserted in the prepared hole and the splint was set in the mouth. After 10 minutes of patient relaxing, pulpal blood flow was recorded for 5 minutes on each tooth. The recorded flow was saved in the computer and calculated with a software 'Perisoft' version 5.1. Pulpal blood flow was also recorded in six teeth of five individuals with no response to electric pulp test and cold test, with periapical radiolucency, or with history of root canal treatment to compare with nonvital teeth. The difference between the mean flow values of each group of teeth were analyzed using one-way ANOVA and Duncan's Multiple Range test. The results were as follows: 1. The average pulpal blood flow values of all the tested teeth of each location were between 9 - 16 Perfusion Unit. Pulpal blood flow value was highest in maxillary lateral incisors, followed by first premolars, second premolars, canines, central incisors, and then first molars (p<0.01). 2. In six anterior teeth, indirectly-made splint group showed higher pulpal blood flow values than directly-made splint group (p<0.01). In posterior teeth, however, there was no significant flow value difference between directly-made splint group and indirectly-made splint one (p>0.05). 3. Teeth with vital pulps showed higher signal values than teeth with nonvital pulps (p<0.01), and the flow photographs showed heartbeat-synchronous fluctuations and vasomotions, while those were absent in non vital tooth.

• Journal of Plant Biotechnology
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• v.50
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• pp.1-10
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• 2023

Sweet potato (Ipomoea batatas L. Lam) is an economically important root crop and a valuable source of nutrients, processed foods, animal feeds, and pigment materials. However, during post-harvest storage, storage roots of sweet potatoes are susceptible to decay caused by various microorganisms and diseases. Post-harvest curing is the most effective means of healing wounds and preventing spoilage by microorganisms during storage. In this study, we aimed to identify proteins involved in the molecular mechanisms related to curing and study proteomic changes during the post-curing storage period. For this purpose, changes in protein spots were analyzed through 2D-electrophoresis after treatment at 33℃ (curing) and 15℃ (control) for three days, followed by a storage period of eight weeks. As a result, we observed 31 differentially expressed protein spots between curing and control groups, among which 15 were identified. Among the identified proteins, the expression level of 'alpha-amylase (spot 1)' increased only after the curing treatment, whereas the expression levels of 'probable aldo-keto reductase 2-like (spot 3)' and 'hypothetical protein CHGG_01724 (spot 4)' increased in both the curing and control groups. However, the expression level of 'sporamin A (spot 10)' decreased in both the curing and control treatments. In the control treatment, the expression level of 'enolase (spot 14)' increased, but the expression levels of 'chain A of actinidin-E-64 complex+ (spot 19)', 'ascorbate peroxidase (spot 22)', and several 'sporamin proteins (spot 20, 21, 23, 24, 27, 29, 30, and 31)' decreased. These results are expected to help identify proteins related to the curing process in sweet potato storage roots, understand the mechanisms related to disease resistance during post-harvest storage, and derive candidate genes to develop new varieties with improved low-temperature storage capabilities in the future.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

• Korean small business review
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• v.31 no.4
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• pp.67-93
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• 2009

The purpose of this paper is to explore the relations between financial constraints and dividend smoothing of innovative small and medium sized enterprises(SMEs) listed on Korea Securities Market and Kosdaq Market of Korea Exchange. The innovative SMEs is defined as the firms with high level of R&D intensity which is measured by (R&D investment/total sales) ratio, according to Chauvin and Hirschey (1993). The R&D investment plays an important role as the innovative driver that can increase the future growth opportunity and profitability of the firms. Therefore, the R&D investment have large, positive, and consistent influences on the market value of the firm. In this point of view, we expect that the innovative SMEs can adjust dividend payment faster than the noninnovative SMEs, on the ground of their future growth opportunity and profitability. And also, we expect that the financial unconstrained firms can adjust dividend payment faster than the financial constrained firms, on the ground of their financing ability of investment funds through the market accessibility. Aivazian et al.(2006) exert that the financial unconstrained firms with the high accessibility to capital market can adjust dividend payment faster than the financial constrained firms. We collect the sample firms among the total SMEs listed on Korea Securities Market and Kosdaq Market of Korea Exchange during the periods from January 1999 to December 2007 from the KIS Value Library database. The total number of firm-year observations of the total sample firms throughout the entire period is 5,544, the number of firm-year observations of the dividend firms is 2,919, and the number of firm-year observations of the non-dividend firms is 2,625. About 53%(or 2,919) of these total 5,544 observations involve firms that make a dividend payment. The dividend firms are divided into two groups according to the R&D intensity, such as the innovative SMEs with larger than median of R&D intensity and the noninnovative SMEs with smaller than median of R&D intensity. The number of firm-year observations of the innovative SMEs is 1,506, and the number of firm-year observations of the noninnovative SMEs is 1,413. Furthermore, the innovative SMEs are divided into two groups according to level of financial constraints, such as the financial unconstrained firms and the financial constrained firms. The number of firm-year observations of the former is 894, and the number of firm-year observations of the latter is 612. Although all available firm-year observations of the dividend firms are collected, deletions are made in the case of financial industries such as banks, securities company, insurance company, and other financial services company, because their capital structure and business style are widely different from the general manufacturing firms. The stock repurchase was involved in dividend payment because Grullon and Michaely (2002) examined the substitution hypothesis between dividends and stock repurchases. However, our data structure is an unbalanced panel data since there is no requirement that the firm-year observations data are all available for each firms during the entire periods from January 1999 to December 2007 from the KIS Value Library database. We firstly estimate the classic Lintner(1956) dividend adjustment model, where the decision to smooth dividend or to adopt a residual dividend policy depends on financial constraints measured by market accessibility. Lintner model indicates that firms maintain stable and long run target payout ratio, and that firms adjust partially the gap between current payout rato and target payout ratio each year. In the Lintner model, dependent variable is the current dividend per share(DPS_t), and independent variables are the past dividend per share(DPS_t-1) and the current earnings per share(EPS_t). We hypothesized that firms adjust partially the gap between the current dividend per share(DPS_t) and the target payout ratio(Ω) each year, when the past dividend per share(DPS_t-1) deviate from the target payout ratio(Ω). We secondly estimate the expansion model that extend the Lintner model by including the determinants suggested by the major theories of dividend, namely, residual dividend theory, dividend signaling theory, agency theory, catering theory, and transactions cost theory. In the expansion model, dependent variable is the current dividend per share(DPS_t), explanatory variables are the past dividend per share(DPS_t-1) and the current earnings per share(EPS_t), and control variables are the current capital expenditure ratio(CEA_t), the current leverage ratio(LEV_t), the current operating return on assets(ROA_t), the current business risk(RISK_t), the current trading volume turnover ratio(TURN_t), and the current dividend premium(DPREM_t). In these control variables, CEA_t, LEV_t, and ROA_t are the determinants suggested by the residual dividend theory and the agency theory, ROA_t and RISK_t are the determinants suggested by the dividend signaling theory, TURN_t is the determinant suggested by the transactions cost theory, and DPREM_t is the determinant suggested by the catering theory. Furthermore, we thirdly estimate the Lintner model and the expansion model by using the panel data of the financial unconstrained firms and the financial constrained firms, that are divided into two groups according to level of financial constraints. We expect that the financial unconstrained firms can adjust dividend payment faster than the financial constrained firms, because the former can finance more easily the investment funds through the market accessibility than the latter. We analyzed descriptive statistics such as mean, standard deviation, and median to delete the outliers from the panel data, conducted one way analysis of variance to check up the industry-specfic effects, and conducted difference test of firms characteristic variables between innovative SMEs and noninnovative SMEs as well as difference test of firms characteristic variables between financial unconstrained firms and financial constrained firms. We also conducted the correlation analysis and the variance inflation factors analysis to detect any multicollinearity among the independent variables. Both of the correlation coefficients and the variance inflation factors are roughly low to the extent that may be ignored the multicollinearity among the independent variables. Furthermore, we estimate both of the Lintner model and the expansion model using the panel regression analysis. We firstly test the time-specific effects and the firm-specific effects may be involved in our panel data through the Lagrange multiplier test that was proposed by Breusch and Pagan(1980), and secondly conduct Hausman test to prove that fixed effect model is fitter with our panel data than the random effect model. The main results of this study can be summarized as follows. The determinants suggested by the major theories of dividend, namely, residual dividend theory, dividend signaling theory, agency theory, catering theory, and transactions cost theory explain significantly the dividend policy of the innovative SMEs. Lintner model indicates that firms maintain stable and long run target payout ratio, and that firms adjust partially the gap between the current payout ratio and the target payout ratio each year. In the core variables of Lintner model, the past dividend per share has more effects to dividend smoothing than the current earnings per share. These results suggest that the innovative SMEs maintain stable and long run dividend policy which sustains the past dividend per share level without corporate special reasons. The main results show that dividend adjustment speed of the innovative SMEs is faster than that of the noninnovative SMEs. This means that the innovative SMEs with high level of R&D intensity can adjust dividend payment faster than the noninnovative SMEs, on the ground of their future growth opportunity and profitability. The other main results show that dividend adjustment speed of the financial unconstrained SMEs is faster than that of the financial constrained SMEs. This means that the financial unconstrained firms with high accessibility to capital market can adjust dividend payment faster than the financial constrained firms, on the ground of their financing ability of investment funds through the market accessibility. Futhermore, the other additional results show that dividend adjustment speed of the innovative SMEs classified by the Small and Medium Business Administration is faster than that of the unclassified SMEs. They are linked with various financial policies and services such as credit guaranteed service, policy fund for SMEs, venture investment fund, insurance program, and so on. In conclusion, the past dividend per share and the current earnings per share suggested by the Lintner model explain mainly dividend adjustment speed of the innovative SMEs, and also the financial constraints explain partially. Therefore, if managers can properly understand of the relations between financial constraints and dividend smoothing of innovative SMEs, they can maintain stable and long run dividend policy of the innovative SMEs through dividend smoothing. These are encouraging results for Korea government, that is, the Small and Medium Business Administration as it has implemented many policies to commit to the innovative SMEs. This paper may have a few limitations because it may be only early study about the relations between financial constraints and dividend smoothing of the innovative SMEs. Specifically, this paper may not adequately capture all of the subtle features of the innovative SMEs and the financial unconstrained SMEs. Therefore, we think that it is necessary to expand sample firms and control variables, and use more elaborate analysis methods in the future studies.