• Asian-Australasian Journal of Animal Sciences
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• v.20 no.5
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• pp.761-767
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• 2007

This study was conducted to determine the effects of exogenous zinc-metallothionein (Zn-MT) on anti-oxidative function and pork quality. After feeding a corn-soybean meal-based diet for two weeks, 48 pigs ($Duroc{\times}Landrace{\times}Chinese\;Black Pig$) were assigned randomly to four groups. Pigs in Group 1 were maintained under non-stress conditions, whereas pigs in Groups 2, 3 and 4 were aggressively handled for 25 min to produce stress. Pigs in Groups 1, 2, 3, and 4 received intramuscular administration of saline (control group; CON), 0 (negative control group; NCON), 0.8 (low dose group; LOW), and 1.6 (high dose group; HIGH) mg rabbit liver Zn-MT per kg body weight, respectively. Pigs were slaughtered at 3 and 6 h post-injection. Zn-MT treatment increased (p<0.05) the activities of superoxide dismutase (SOD) and glutathione-peroxidase (GSH-PX) while decreasing the concentration of malondialdehyde (MDA) in liver. These responses were greater (p<0.05) at 6 h than at 3 h post Zn-MT injection. Zn-MT treatment increased (p<0.05) hepatic SOD mRNA levels in a time and dose-dependent manner and decreased (p<0.05) serum glutamate-pyruvate transaminase and lactate dehydrogenase activities (indicators of tissue integrity). Zn-MT administration decreased (p<0.05) lactate concentration and increased (p<0.05) pH and water-holding capacity in the longissimus thorasis meat. Collectively, our results indicate that intramuscular administration of Zn-MT to pre-slaughter stressed pigs improved tissue anti-oxidative ability and meat quality.

• Journal of Nutrition and Health
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• v.53 no.4
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• pp.390-405
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• 2020

Purpose: The effect of prebiotics intake after administration of a synbiotics mixture (a probiotic, Bifidobacterium longum, and a prebiotic, xylooligosaccharide containing sugar [XOS]) on human intestinal microflora and defecation characteristics was investigated in a randomized controlled trial. Methods: Twenty-five healthy young volunteers (11 males and 14 females) were randomly assigned to 2 groups (BL2XO2 and BL2XO6). The synbiotics mixture was orally administered to both groups for 2 weeks, and the prebiotics were subsequently administered to the BL2XO6 group for 4 additional weeks. The daily dose of the synbiotics mixture comprised 10¹⁰ colony-forming unit of Bifidobacterium longum and 10 g of XOS, and during the prebiotics period, the daily dose of prebiotics comprised only 10 g of XOS. The fecal pH, microflora, and defecation characteristics were analyzed at baseline and at weeks 1, 2, 4, and 6. Results: The counts of B. longum and Bifidobacterium spp. in the BL2XO6 group exhibited a steady, increasing trend during the synbiotics and prebiotics periods, whereas those of the BL2XO2 group exhibited considerable variation in each week of the study period. Although there was no significant difference, the counts of fecal Bifidobacterium in the BL2XO6 group tended to be higher than those of the BL2XO2 group at week 6. The growth of Lactobacillus spp. exhibited a time-dependent variation, peaking at week 6 in both groups. Low counts of Clostridium spp. were observed after treatment with the synbiotics and prebiotics in the BL2XO6 group (p < 0.05) throughout the study, whereas the inhibitory effect on Clostridium spp. was maintained only during the synbiotics period in the BL2XO2 group. The defecation characteristics did not differ between the two groups. Conclusion: Administration of XOS after a synbiotics mixture containing B. longum and XOS can exert a prebiotic effect in healthy young volunteers by stimulating Bifidobacteriun spp. growth and inhibiting growth of Clostridium spp.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.19-47
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• 2015

In this era of knowledge economy, a variety of virtual communities are proliferating for the purpose of knowledge creation and utilization. Since the voluntary contributions of members are the essential source of knowledge, member turnover can have significant implications on the survival and success of virtual communities. However, there is a dearth of research on the effect of membership turnover and even the method of measurement for membership turnover is left unclear in virtual communities. In a traditional context, membership turnover is calculated as the ratio of the number of departing members to the average number of members for a given time period. In virtual communities, while the influx of newcomers can be clearly measured, the magnitude of departure is elusive since explicit withdrawals are seldom executed. In addition, there doesn't exist a common way to determine the average number of community members who return and contribute intermittently at will. This study initially examines the limitations in applying the concept of traditional turnover to virtual communities, and proposes five membership fluidity measures based on a preliminary analysis of editing behaviors of 2,978 featured articles in English Wikipedia. Subsequently, this work investigates the relationships between three selected membership fluidity measures and group collaboration performance, reflecting a moderating effect dependent on work characteristic. We obtained the following results: First, membership turnover relates to collaboration efficiency in a right-shortened U-shaped manner, with a moderating effect from work characteristic; given the same turnover rate, the promotion likelihood for a more professional task is lower than that for a less professional task, and the likelihood difference diminishes as the turnover rate increases. Second, contribution period relates to collaboration efficiency in a left-shortened U-shaped manner, with a moderating effect from work characteristic; the marginal performance change per unit change of contribution period is greater for a less professional task. Third, the number of new participants per month relates to collaboration efficiency in a left-shortened reversed U-shaped manner, for which the moderating effect from work characteristic appears to be insignificant.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.305-316
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• 2011

Recommender system is the system which, by using automated information filtering technology, recommends products or services to the customers who are likely to be interested in. Those systems are widely used in many different Web retailers such as Amazon.com, Netfix.com, and CDNow.com. Various recommender systems have been developed. Among them, Collaborative Filtering (CF) has been known as the most successful and commonly used approach. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. However, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting in advance whether the performance of CF recommender system is acceptable or not is practically important and needed. In this study, we propose a decision making guideline which helps decide whether CF is adoptable for a given application with certain transaction data characteristics. Several previous studies reported that sparsity, gray sheep, cold-start, coverage, and serendipity could affect the performance of CF, but the theoretical and empirical justification of such factors is lacking. Recently there are many studies paying attention to Social Network Analysis (SNA) as a method to analyze social relationships among people. SNA is a method to measure and visualize the linkage structure and status focusing on interaction among objects within communication group. CF analyzes the similarity among previous ratings or purchases of each customer, finds the relationships among the customers who have similarities, and then uses the relationships for recommendations. Thus CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. Under the assumption that SNA could facilitate an exploration of the topological properties of the network structure that are implicit in transaction data for CF recommendations, we focus on density, clustering coefficient, and centralization which are ones of the most commonly used measures to capture topological properties of the social network structure. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. We explore how these SNA measures affect the performance of CF performance and how they interact to each other. Our experiments used sales transaction data from H department store, one of the well?known department stores in Korea. Total 396 data set were sampled to construct various types of social networks. The dependant variable measuring process consists of three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used UCINET 6.0 for SNA. The experiments conducted the 3-way ANOVA which employs three SNA measures as dependant variables, and the recommendation accuracy measured by F1-measure as an independent variable. The experiments report that 1) each of three SNA measures affects the recommendation accuracy, 2) the density's effect to the performance overrides those of clustering coefficient and centralization (i.e., CF adoption is not a good decision if the density is low), and 3) however though the density is low, the performance of CF is comparatively good when the clustering coefficient is low. We expect that these experiment results help firms decide whether CF recommender system is adoptable for their business domain with certain transaction data characteristics.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Journal of Nutrition and Health
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• v.49 no.1
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• pp.18-27
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• 2016

Purpose: Our previous study demonstrated the hypoglycemic effects of mulberry (Morus alba L.) leaf and the underlying mechanisms. Here we explored the potency of mulberry twigs (TW) and root barks (RB) in postprandial hypoglycemic effects in vitro and in vivo. Methods: The major components of TW and RB were determined by high performance liquid chromatography (HPLC). Alpha-glucosidase inhibition and glucose/fructose uptake inhibition in Caco-2 cells were determined for TW, RB, and their major components, followed by an oral sugar tolerance test (OSTT) in streptozotocin-induced diabetic rats. Male Wistar rats were fed a high-fat diet for 2 weeks and then a single dose of streptozotocin (35 mg/kg B.W) was administered by intraperitoneal injection. Rats with fasting blood glucose levels above 126 mg/dL were randomly divided into 5 groups (n = 8/group) for the following treatments by gavage for 4 weeks: vehicle (normal control and diabetic control), 200 mg/kg B.W of TW or RB or 100 mg/kg B.W of oxyresveratrol (OXY). Results: OXY and mulberroside A were identified as the major components of TW and OXY, mongolicin, and kuwanon H for RB. A significant inhibitory activity on ${\alpha}-glucosidase$ was found for TW, RB, and OXY (p = 0.0099). There was a dose-dependent inhibition of TW and RB on the intestinal sugar uptakes in Caco-2 cells, showing a greater impact on fructose compared to glucose. The OSTT showed that TW and RB significantly delayed time to maximal concentration (p = 0.0088) and decreased maximal concentration (p = 0.0043) compared to the control group. Conclusion: These results suggest that TW and RB may have a postprandial hypoglycemic effect, particularly in the case of high fructose or sucrose intake. OXY was suggested as a contributor to the hypoglycemic effect of TW and RB. Further studies are needed for the systemic effect of TW and RB in circulation.

• Journal of Chest Surgery
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• v.32 no.6
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• pp.510-517
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• 1999

Background: Total anomalous pulmonary venous connection (TAPVC) is still one of the more challenging congenital heart defects in newborns and young infants. The purpose of the study is to evaluate the early and midterm results of the surgical corrections for patients in early infancy with isolated TAPVC. Material and Method: Hospital records of 15 consecutive patients in early infancy (January 1993 to August 1998) were retrospectively reviewed. There were 8 boys and 7 girls whose ages ranged from 4 days to 3.5 months (median age 22 days). Their body weight ranged from 1.75 kg to 4.9 kg (mean 3.54 kg). The abnormal anatomical connections were supracardiac in 11, cardiac in 3, and infracardiac in 1. In 6 patients (40%), the pulmonary venous drainage was obstructive. Total circulatory arrest was used in 13 patients. Anastomosis between the common pulmonary vein and the left atrium was performed with a continuous suture technique using a fine nonabsorbable polypropylene suture through a lateral approach behind the right atrium. Result: There was one hospital death (6.5%) caused by a sepsis 17 days after the operation in a neonate who had supracardiac drainage and was dependent on a ventilator preoperatively. There were 2 late deaths. One died sudde`nly of an unknown cause at home 2.5 years after the operation and the other died of a recurrent pulmonary hypertension 3 months after the reoperation due to pulmonary venous obstruction (PVO). Two patients required reoperations because of PVO 5 months and 10 months respectively after the initial operation. Of these patients, one patient is alive at the present time with persistent pulmonary hypertension. All survivors without postoperative PVO (78.6%) were in NYHA functional class I at mean follow-up of 25.8 months (0.5∼67 months). Conclusion: Surgical correction of TAPVC in early infancy can be performed at low risk. However, there were 2 postoperative PVOs (14.3%) which had bad results. The survivors without postoperative PVO had excellent functional status.

• Journal of the Korean Geotechnical Society
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• v.28 no.5
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• pp.13-25
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• 2012

Ground anchor method is one of the most popular reinforcing technology for slope in Korea. For the health monitoring of slope which is reinforced by permanent anchor for a long period, monitoring of the tension force of ground anchor is very important. However, since electromechanical sensors such as strain gauge and V/W type load cell are also subject to long-term risk as well as suffering from noise during long distance transmission and immunity to electromagnetic interference (EMI), optical FBG sensors embedded tendon was developed to measure strain of 7-wire strand by embedding FBG sensor into the center king cable of 7-wire strand. This FBG sensors embedded tendon has been successfully applied to measuring the short-term anchor force. But to adopt this tendon to long-term monitoring, temperature compensation of the FBG sensors embedded tendon should be done. In this paper, we described how to compensate the effect in compliance with the change of underground temperature during long-term tension force monitoring of ground anchors by using optical fiber sensors (FBG: Fiber Bragg Grating). The model test was carried out to determine the temperature sensitivity coefficient (${\beta}^{\prime}$) of FBG sensors embedded tendon. The determined temperature sensitivity coefficient ${\beta}^{\prime}=2.0{\times}10^{-5}/^{\circ}C$ was verified by comparing the ground temperatures predicted from the proposed sensor using ${\beta}^{\prime}$ with ground temperatures measured from ground thermometer. Finally, temperature compensations were carried out based on ${\beta}^{\prime}$ value and ground temperature measurement from KMA for the tension force monitoring results of tension type and compression type anchors, which had been installed more than 1 year before at the test site. Temperature compensated tension forces are compared with those measured from conventional load cell during the same measuring time. Test results show that determined temperature sensitivity coefficient (${\beta}^{\prime}$) of FBG sensors embedded tendon is valid and proposed temperature compensation method is also appropriate from the fact that the temperature compensated tension forces are not dependent on the change of ground temperature and are consistent with the tension forces measured from the conventional load cell.

• Journal of the korean academy of Pediatric Dentistry
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• v.31 no.1
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• pp.98-107
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• 2004

Proper finishing/polishing of dental restorations are critical clinical procedures that enhance both esthetics and longevity of restored teeth. This study was to compare the effects of immediate and delayed finishing/polishing procedures on the surface roughness and surface hardness of tooth-colored restoratives including two microfilled composite resins, such as Filtek A110 and Silux Plus, two hybrid composite resins, such as Revolution formular2 and Palfique Estelite. A total of 48 specimens were made for each material. The first 16 specimens served as the control group and the remaining 32 specimens were randomly divided into two equal groups. The control group was stored in distilled water at $37^{\circ}C$ for 1 week after light polymerization against the Mylar sheet. The first experimental group was finished/polished immediately after light polymerization and stored for 1 week in distilled water at $37^{\circ}C$, whereas the while the second group was finished/polished 1 week after light polymerization and stored in distilled water at $37^{\circ}C$. The results were as follows: 1. The smoothest surface was produced by Mylar sheet and finishing/polishing procedure increased the surface roughness. However, the surface roughness of composite resins were not influenced by the finishing/polishing timing. 2. There were significant differences about surface roughness between Revolution formular 2 and Silux Plus, regarding immediate finishing/polishing, and between Palfique Estelite and Silux Plus regarding delayed finishing/polishing(p<0.05). 3. The sequence of the surface hardness was ascending order by Revolution formular 2, Silux Plus, Filtek A110 and Palfique Estelite. However there were no significant differences about hardness among the control group and two finishing/polishing timing groups. 4. The effects of finishing/polishing time on surface roughness and hardness appeared to be material-dependent.

• Tuberculosis and Respiratory Diseases
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• v.67 no.2
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• pp.95-104
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• 2009

Background: The pathophysiologic mechanisms of early acute lung injury (ALI) differ according to the type of primary insult. It is important to differentiate between direct and indirect pathophysiologic pathways, and this may influence the approach to treatment strategies. NF-$\kappa$B decoy oligodeoxynucleotide (ODN) is a useful tool for the blockade of the expression of NF-$\kappa$B-dependent proinflammatory mediators and has been reported to be effective in indirect ALI. The purpose of this study was to investigate the effect of NF-$\kappa$B decoy ODN in the lipopolysaccharide (LPS)-induced direct ALI model. Methods: Five-week-old specific pathogen-free male BALB/c mice were used for the experiment. In the preliminary studies, tumor necrosis factor (TNF)-$\alpha$, interleukine (IL)-6 and NF-$\kappa$B activity peaked at 6 hours after LPS administration. Myeloperoxidase (MPO) activity and ALI score were highest at 36 and 48 hours, respectively. Therefore, it was decided to measure each parameter at the time of its highest level. The study mice were randomly divided into three experimental groups: (1) control group which was administered 50 ${\mu}L$ of saline and treated with intratracheal administration of 200 ${\mu}L$ DW containing only hemagglutinating virus of Japan (HVJ) vector (n=24); (2) LPS group in which LPS-induced ALI mice were treated with intratracheal administration of 200 ${\mu}L$ DW containing only HVJ vector (n=24); (3) LPS+ODN group in which LPS-induced ALI mice were treated with intratracheal administration of 200 ${\mu}L$ DW containing 160 ${\mu}g$ of NF-$\kappa$B decoy ODN and HVJ vector (n=24). Each group was subdivided into four experimental subgroups: (1) tissue subgroup for histopathological examination for ALI at 48 hours (n=6); (2) 6-hour bronchoalveolar lavage (BAL) subgroup for measurement of TNF-$\alpha$ and IL-6 in BAL fluid (BALF) (n=6); (3) 36-hour BAL subgroup for MPO activity assays in BALF (n=6); and (4) tissue homogenate subgroup for measurement of NF-$\kappa$B activity in lung tissue homogenates at 6 hours (n=6). Results: NF-$\kappa$B decoy ODN treatment significantly decreased NF-$\kappa$B activity in lung tissues. However, it failed to improve the parameters of LPS-induced direct ALI, including the concentrations of tumor necrosis factor-$\alpha$ and interleukin-6 in BALF, myeloperoxidase activity in BALF and histopathologic changes measured by the ALI score. Conclusion: NF-$\kappa$B decoy ODN, which has been proven to be effective in indirect models, had no effect in the direct ALI model.