This study explores a 2003 Yahoo Anniversary Website-I left my heart in Aegean Sea-built by Justin, a Taiwanese engineer. Justin returns from the romantic Aegean Sea and puts 124 photographs he took onto a website to share with his friends. Unexpectedly, the website becomes a hit and the address achieves wide distribution via various chain e-mails. The site helps to promote tourism to Greece, a destination relatively unknown to most Taiwanese. This investigation explores why the site appeals to so many visitors, impresses them, and even draws them to plan travel to Greece. The article describes the effect of the website by analyzing messages left on the site. The AIDA model is useful for classifying holistic messages. The data demonstrate that the website generates desire and action in over 45% of its readers. These individuals either announce plans to visit Greece immediately or at some time in the foreseeable future. The website thus significantly influences browsers and indirectly promotes Greek tourism. Then, this article describes the key success factors of this popular website. Finally, the article presents suggestions and implications for the tourism industry and for nations seeking to promote tourism.

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Subcellular localization performs an important role in genome analysis as a key functional characteristic of proteins. Therefore, an automatic, reliable and efficient prediction system for protein subcellular localization is needed for large-scale genome analysis. This paper describes a new residue-couple model using a support vector machine to predict the subcellular localization of proteins. This new approach provides better predictions than existing methods. The total prediction accuracies on Reinhardt and Hubbard's dataset reach 92.0% for prokaryotic protein sequences and 86.9% for eukaryotic protein sequences with 5-fold cross validation. For a new dataset with 8304 proteins located in 8 subcellular locations, the total accuracy achieves 88.9%. The model shows robust against N-terminal errors in the sequences. A web server is developed based on the method which was used to predict some new proteins. This paper presents a novel approach combining the residue-couple model and the SVM for subcellular localization prediction. Residue-couples contain information of the amino acid composition and the order of the amino acids in the protein sequences. The information is important for subcellular localization. These residue-couples were used to train the SVM classifiers. By using a 5-fold cross validation test, the overall prediction accuracies reach 86.9% for eukaryotic proteins and 92.1% for prokaryotic proteins. The results show that the prediction accuracy is significantly improved with the novel

Three members of the peroxisome proliferator-activated receptor (PPAR) family, PPARα, PPARγ, and PPARβ/δ, have been investigated widely over the past few decades. Although the roles of these PPARs and their agonists/antagonists were defined in clinical and basic studies, the conflicting results from these studies indicate that more analysis is needed to understand the roles of PPARs. PPARα is a ligand-activated transcription factor that contributes to the regulation of a variety of processes, ranging from inflammation and immunity to nutrient metabolism and energy homeostasis. In this review, we focus on the function and mechanisms of PPARα in the cardiovascular system under various pathological conditions, including vascular and heart injury, blood pressure regulation, and lipid disorder-related cardiovascular injury, as well as its polymorphisms and pharmacogenetic associations with cardiovascular diseases. The anti-inflammatory effect of PPARα in cardiovascular injury is mainly through inhibition of pro-inflammatory signaling pathways and improvement of the lipid profile. Moreover, PPARα also modulates the activity of endothelial nitric oxide synthase and resets the renin-angiotensin system to regulate vascular tone. PPARα gene variants appear to be associated with some cardiovascular risk factors, such as higher plasma lipid levels, cardiac growth, and increased risk of coronary artery disease. Nowadays, novel PPARα drugs with broad safety margins and therapeutic potential for metabolic syndrome and cardiovascular diseases are being developed and applied in the clinical setting. The insights from the current review shed new light on areas of further study and provide a better understanding of the role of PPARα in cardiovascular diseases.

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