Why Is Gamified Travel Information More Effective? An Experimental Investigation

Destination management organizations (DMOs) have used different formats of travel information to create a positive destination image and attract potential tourists. Text-based travel information is the most common format while question-based and gamified versions have become popular in the recent 10 years. Integrating questions or applying gamification is believed to enhance people’s flow experience and result in positive outcomes. However, no known research has empirically investigated the different effects of text-based, question-based, and gamified information in the tourism context. Through an experimental design, this research found that gamified information compared to text-based or question-based significantly enhances people’s flow experience and in turn increases their destination image change, willingness to search for more information, and visit intention. The findings give insights into the effects of different formats of information presentation and have implications for how DMOs could use gamified information to promote destinations and attract potential tourists

Motives to Take a Gamified Trip: An Interpretative Study Using Q Method

Destinations have initiated different gamification practices in the last 10 years. However, there is a lack of understanding of what constitutes gamified trips as well as tourists’ motives to take such a trip. Knowing why tourists would like to engage in a gamified context can help designers create valuable games and offer more memorable experiences. This research sheds light upon the concept and categorization of gamified trips, expands the use of Q method to examine travel motives, and proposes six types of players of gamified trips. Additionally, it provides implications for DMOs on how to apply gamification to attract potential tourists and offer enjoyable tourist experiences for different segment markets

Risk Prediction Using Genome-Wide Association Studies on Type 2 Diabetes

The success of genome-wide association studies (GWASs) has enabled us to improve risk assessment and provide novel genetic variants for diagnosis, prevention, and treatment. However, most variants discovered by GWASs have been reported to have very small effect sizes on complex human diseases, which has been a big hurdle in building risk prediction models. Recently, many statistical approaches based on penalized regression have been developed to solve the “large p and small n” problem. In this report, we evaluated the performance of several statistical methods for predicting a binary trait: stepwise logistic regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN). We first built a prediction model by combining variable selection and prediction methods for type 2 diabetes using Affymetrix Genome-Wide Human SNP Array 5.0 from the Korean Association Resource project. We assessed the risk prediction performance using area under the receiver operating characteristic curve (AUC) for the internal and external validation datasets. In the internal validation, SLR-LASSO and SLR-EN tended to yield more accurate predictions than other combinations. During the external validation, the SLR-SLR and SLR-EN combinations achieved the highest AUC of 0.726. We propose these combinations as a potentially powerful risk prediction model for type 2 diabetes

Prediction of Quantitative Traits Using Common Genetic Variants: Application to Body Mass Index

With the success of the genome-wide association studies (GWASs), many candidate loci for complex human diseases have been reported in the GWAS catalog. Recently, many disease prediction models based on penalized regression or statistical learning methods were proposed using candidate causal variants from significant single-nucleotide polymorphisms of GWASs. However, there have been only a few systematic studies comparing existing methods. In this study, we first constructed risk prediction models, such as stepwise linear regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN), using a GWAS chip and GWAS catalog. We then compared the prediction accuracy by calculating the mean square error (MSE) value on data from the Korea Association Resource (KARE) with body mass index. Our results show that SLR provides a smaller MSE value than the other methods, while the numbers of selected variables in each model were similar

Boundary integral equation method for resonances in gradient index cavities designed by conformal transformation optics

In the case of two-dimensional gradient index cavities designed by the conformal transformation optics, we propose a boundary integral equation method for the calculation of resonant mode functions by employing a fictitious space which is reciprocally equivalent to the physical space. Using the Green's function of the interior region of the uniform index cavity in the fictitious space, resonant mode functions and their far-field distributions in the physical space can be obtained. As a verification, resonant modes in lima\c{c}on-shaped transformation cavities were calculated and mode patterns and far-field intensity distributions were compared with those of the same modes obtained from the finite element method.Comment: 13 pages, 6 figure

Characteristics of a Delayed System with Time-dependent Delay Time

The characteristics of a time-delayed system with time-dependent delay time is investigated. We demonstrate the nonlinearity characteristics of the time-delayed system are significantly changed depending on the properties of time-dependent delay time and especially that the reconstructed phase trajectory of the system is not collapsed into simple manifold, differently from the delayed system with fixed delay time. We discuss the possibility of a phase space reconstruction and its applications.Comment: 4 pages, 6 figures (to be published in Phys. Rev. E

Chaos Synchronization of delayed systems in the presence of delay time modulation

We investigate synchronization in the presence of delay time modulation for application to communication. We have observed that the robust synchronization is established by a common delay signal and its threshold is presented using Lyapunov exponents analysis. The influence of the delay time modulation in chaotic oscillators is also discussed.Comment: 9 pages, 6 figure

The Ability of β-Cells to Compensate for Insulin Resistance is Restored with a Reduction in Excess Growth Hormone in Korean Acromegalic Patients

The aim of this study was to assess the prevalence of diabetes and to study the effects of excess growth hormone (GH) on insulin sensitivity and β-cell function in Korean acromegalic patients. One hundred and eighty-four acromegalic patients were analyzed to assess the prevalence of diabetes, and 52 naïve acromegalic patients were enrolled in order to analyze insulin sensitivity and insulin secretion. Patients underwent a 75 g oral glucose tolerance test with measurements of GH, glucose, insulin, and C-peptide levels. The insulin sensitivity index and β-cell function index were calculated and compared according to glucose status. Changes in the insulin sensitivity index and β-cell function index were evaluated one to two months after surgery. Of the 184 patients, 17.4% were in the normal glucose tolerance (NGT) group, 45.1% were in the pre-diabetic group and 37.5% were in the diabetic group. The insulin sensitivity index (ISI0,120) was significantly higher and the HOMA-IR was lower in the NGT compared to the diabetic group (P = 0.001 and P = 0.037, respectively). The ISI0,120 and disposition index were significantly improved after tumor resection. Our findings suggest that both insulin sensitivity and β-cell function are improved by tumor resection in acromegalic patients