Assessing Destination Competitiveness: An Application to the Hot Springs Tourism Sector

This paper proposes a model to identify the factors determining the competitiveness of the hot springs tourism sector, with particular application to Taiwan. The proposed conceptual framework brings together two approaches, namely the theories of industry organization (10) and the resource-based view (RBV). The proposition underlying this framework is that destination competitiveness is achieved by the adoption of policies and strategies aligned with market opportunities, drawing upon the unique or distinctive tourism features offered by the destination. It is proposed that three major influences are evident in the case of hot springs tourism, namely Tourism Destination Resources and Attractors, Tourism Destination Strategies and Tourism Destination Environments. An evaluation is provided of the administration of a three-round Delphi survey, which was intended to validate the determinants of destination competitiveness that were derived from the literature. Drawing upon the results of the pilot study it is concluded that the development of a sector-specific model of destination competitiveness is capable of capturing the nature and characteristics of the hot springs tourism sector

Skeletal Rigidity of Phylogenetic Trees

Motivated by geometric origami and the straight skeleton construction, we outline a map between spaces of phylogenetic trees and spaces of planar polygons. The limitations of this map is studied through explicit examples, culminating in proving a structural rigidity result.Comment: 17 pages, 12 figure

Mapping Topographic Structure in White Matter Pathways with Level Set Trees

Fiber tractography on diffusion imaging data offers rich potential for describing white matter pathways in the human brain, but characterizing the spatial organization in these large and complex data sets remains a challenge. We show that level set trees---which provide a concise representation of the hierarchical mode structure of probability density functions---offer a statistically-principled framework for visualizing and analyzing topography in fiber streamlines. Using diffusion spectrum imaging data collected on neurologically healthy controls (N=30), we mapped white matter pathways from the cortex into the striatum using a deterministic tractography algorithm that estimates fiber bundles as dimensionless streamlines. Level set trees were used for interactive exploration of patterns in the endpoint distributions of the mapped fiber tracks and an efficient segmentation of the tracks that has empirical accuracy comparable to standard nonparametric clustering methods. We show that level set trees can also be generalized to model pseudo-density functions in order to analyze a broader array of data types, including entire fiber streamlines. Finally, resampling methods show the reliability of the level set tree as a descriptive measure of topographic structure, illustrating its potential as a statistical descriptor in brain imaging analysis. These results highlight the broad applicability of level set trees for visualizing and analyzing high-dimensional data like fiber tractography output

GECKA3D: A 3D Game Engine for Commonsense Knowledge Acquisition

Commonsense knowledge representation and reasoning is key for tasks such as artificial intelligence and natural language understanding. Since commonsense consists of information that humans take for granted, gathering it is an extremely difficult task. In this paper, we introduce a novel 3D game engine for commonsense knowledge acquisition (GECKA3D) which aims to collect commonsense from game designers through the development of serious games. GECKA3D integrates the potential of serious games and games with a purpose. This provides a platform for the acquisition of re-usable and multi-purpose knowledge, and also enables the development of games that can provide entertainment value and teach players something meaningful about the actual world they live in

Teaching the Basics of Reactive Oxygen Species and their Relevance to Cancer Biology: Mitochondrial Reactive Oxygen Species Detection, Redox Signaling, and Targeted Therapies

Reactive oxygen species (ROS) have been implicated in tumorigenesis (tumor initiation, tumor progression, and metastasis). Of the many cellular sources of ROS generation, the mitochondria and the NADPH oxidase family of enzymes are possibly the most prevalent intracellular sources. In this article, we discuss the methodologies to detect mitochondria-derived superoxide and hydrogen peroxide using conventional probes as well as newly developed assays and probes, and the necessity of characterizing the diagnostic marker products with HPLC and LC-MS in order to rigorously identify the oxidizing species. The redox signaling roles of mitochondrial ROS, mitochondrial thiolperoxidases, and transcription factors in response to mitochondria-targeted drugs are highlighted. ROS generation and ROS detoxification in drug-resistant cancer cells and the relationship to metabolic reprogramming are discussed. Understanding the subtle role of ROS in redox signaling and in tumor proliferation, progression, and metastasis as well as the molecular and cellular mechanisms (e.g., autophagy) could help in the development of combination therapies. The paradoxical aspects of antioxidants in cancer treatment are highlighted in relation to the ROS mechanisms in normal and cancer cells. Finally, the potential uses of newly synthesized exomarker probes for in vivo superoxide and hydrogen peroxide detection and the low-temperature electron paramagnetic resonance technique for monitoring oxidant production in tumor tissues are discussed

Sonochemical Degradation of Perfluorooctane Sulfonate (PFOS) and Perfluorooctanoate (PFOA) in Landfill Groundwater: Environmental Matrix Effects

Perfluorinated chemicals such as perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) are environmentally persistent and recalcitrant to most conventional chemical and microbial treatment technologies. In this paper, we show that sonolysis is able to decompose PFOS and PFOA present in groundwater beneath a landfill. However, the pseudo first-order rate constant for the sonochemical degradation in the landfill groundwater is reduced by 61 and 56% relative to MilliQ water for PFOS and PFOA, respectively, primarily due to the presence of other organic constituents. In this study, we evaluate the effect of various organic compounds on the sonochemical decomposition rates of PFOS and PFOA. Organic components in environmental matrices may reduce the sonochemical degradation rates of PFOS and PFOA by competitive adsorption onto the bubble−water interface or by lowering the average interfacial temperatures during transient bubble collapse events. The effect of individual organic compounds depends on the Langmuir adsorption constant, the Henry’s law constant, the specific heat capacity, and the overall endothermic heat of dissociation. Volatile organic compounds (VOCs) are identified as the primary cause of the sonochemical rate reduction for PFOS and PFOA in landfill groundwater, whereas the effect of dissolved natural organic matter (DOM) is not significant. Finally, a combined process of ozonation and sonolysis is shown to substantially recover the rate loss for PFOS and PFOA in landfill groundwater