Sungkyunkwan University

About: Sungkyunkwan University is a education organization based out in Seoul, South Korea. It is known for research contribution in the topics: Graphene & Thin film. The organization has 28229 authors who have published 56428 publications receiving 1352733 citations. The organization is also known as: 성균관대학교.

Optimal Contract Design for Mixed Channels Under Information Asymmetry

Abstract: The mixed-channel model is becoming increasingly popular in the marketplace. In this model, a firm selling through the traditional supply chain of wholesaler and retailer opens a direct channel to the customer through Internet sales. Because both channels have their respective advantages, the manufacturer is attracted to this business model. However, it also leads to channel conflict, with the retailer feeling threatened by direct competition. One way of eliminating the possibility of this channel conflict, where the retailer is allowed to add value to the product to differentiate its offering to the customers, is proposed in this paper. The retailer is also given full authority to make pricing decisions. This paper presents a model, under this scenario, of obtaining optimum pricing decisions by both parties, the amount of value added by the retailer, and the manufacturer's wholesale price to the retailer. Our model incorporates information asymmetry, where the manufacturer has incomplete information about the retailer's cost of adding value. We obtain closed-form contracts with incomplete information and compare them with those with complete channel coordination. We also develop a number of managerial guidelines and identify future research topics.

Insulin resistance and C-reactive protein as independent risk factors for non-alcoholic fatty liver disease in non-obese Asian men.

Abstract: Background and Aim: Although insulin resistance is often considered the link between obesity and non-alcoholic fatty liver disease (NAFLD), the role of insulin resistance, independent of obesity, as a NAFLD risk factor in non-obese men has been less well established. Systemic inflammation may be accompanied by insulin resistance in healthy subjects. The goal of the present study was to examine if insulin resistance and systemic inflammatory markers are independent predictors of NAFLD in non-obese men. Methods: The authors conducted a cross-sectional survey of 120 patients with NAFLD and 240 controls matched by age and body mass index. Controls had no evidence of alcohol abuse, hepatitis B or C, obesity, or previous history of diabetes, fasting hyperglycemia or hypertension. Diagnosis of NAFLD was based on an elevated alanine aminotransferase level and sonographic evidence of a fatty liver. Insulin resistance was determined using a homeostasis model assessment (HOMA-IR). Results: The age-adjusted risk of developing NAFLD was strongly associated with the elevated levels in measurements of uric acid, fasting blood sugar, triglycerides, apolipoprotein B, C-reactive protein (CRP) and HOMA-IR, and decreased levels of high density lipoprotein cholesterol and apolipoprotein A-I. Multivariate analysis based on univariate analysis indicated that an increase in CRP (odds ratio [OR] = 1.37; 95% confidence interval [CI]: 1.06–1.77) per 1 SD (1.48 mg/L) and HOMA-IR (OR = 2.28; 95% CI: 1.67–3.11) per 1 SD (0.63) were independent risk factors for NAFLD. Conclusion: Insulin resistance and systemic inflammatory response are of key importance for inducing NAFLD, particularly in apparently healthy non-obese men.

Learning styles diagnosis based on user interface behaviors for the customization of learning interfaces in an intelligent tutoring system

Abstract: Each learner has different preferences and needs. Therefore, it is very crucial to provide the different styles of learners with different learning environments that are more preferred and more efficient to them. This paper reports a study of the intelligent learning environment where the learner's preferences are diagnosed, and then user interfaces are customized in an adaptive manner to accommodate the preferences. A learning system with a specific interface has been devised based on the learning-style model by Felder & Silverman, so that different learner preferences are revealed through user interactions with the system. Using this interface, learning styles are diagnosed from learner behavior patterns on the interface using Decision Tree and Hidden Markov Model approaches.

A phylogenetic analysis of Prunus and the Amygdaloideae (Rosaceae) using ITS sequences of nuclear ribosomal DNA.

Abstract: The economically important plum or cherry genus (Prunus) and the subfamily Amygdaloideae of the Rosaceae have a controversial taxonomic history due to the lack of a phylogenetic framework. Phylogenetic analysis using the ITS sequences of nuclear ribosomal DNA (nrDNA) was conducted to construct the evolutionary history and evaluate the historical classifications of Prunus and the Amygdaloideae. The analyses suggest two major groups within the Amygdaloideae: (1) Prunus s.l. (sensu lato) and Maddenia, and (2) Exochorda, Oemleria, and Prinsepia. The ITS phylogeny supports the recent treatment of including Exochorda (formerly in the Spiraeoideae) in the Amygdaloideae. Maddenia is found to be nested within Prunus s.l. in the parsimony and distance analyses, but basal to Prunus s.l. in the maximum likelihood analysis. Within Prunus, two major groups are recognizable: (1) the Amygdalus‐Prunus group, and (2) the Cerasus‐Laurocerasus‐Padus group. The clades in the ITS phylogeny are not congruent with most subgeneric groups in the widely used classification of Prunus by Rehder. A broadly definedPrunus is supported.