A Probabilistic Risk Analysis for Taipei Seismic Hazards: An Application of HAZ-Taiwan with its Pre-processor and Post-processor

This paper employs probabilistic risk analysis to estimate exceedance probability curves, average annual loss (AAL) and probable maximum loss (PML) for seismic hazards. It utilizes and event-driven loss estimation model, HAZ-Taiwan, and develops its pre-processing and post-processing software modules. First, the pre-processingmodule establishes a set of hazard-consistent scenarios. Then, the HAZ-Taiwan modelextimates hazards, vulnerabilities and economic losses for each scenario. Finally, the aggregate and occurrence exceedance probability curves for losses and theirconfidence intervals are simulated using the Monte Carlo simulation in thepost-processing module. The methodology is then applied to analyze seismic risks in Taipei. It is found that the exceedance probability of an aggregate loss of NT$40.398 billion is 0.001. This amount of loss is approximately 2.78$37.41-43.12 billion. The average annual loss of buildings in Taipei is NT$1.06 billion r approximately 0.07% of the total stock.probabilistic risk analysis, Hazard analysis, vulnerability analysis, exceedance probability curve, HAZ-Taiwan

On the Mass-Period Distributions and Correlations of Extrasolar Planets

In addition to fitting the data of 233 extra-solar planets with power laws, we construct a correlated mass-period distribution function of extrasolar planets, as the first time in this field. The algorithm to generate a pair of positively correlated beta-distributed random variables is introduced and used for the construction of correlated distribution functions. We investigate the mass-period correlations of extrasolar planets both in the linear and logarithm spaces, determine the confidence intervals of the correlation coefficients, and confirm that there is a positive mass-period correlation for the extrasolar planets. In addition to the paucity of massive close-in planets, which makes the main contribution on this correlation, there are other fine structures for the data in the mass-period plane.Comment: to be published in AJ, tentatively in December 200

An Empirical Study on Consumption Intention of Virtual Tour Streaming

This study employs the social interaction motivation of the audience to explore the social capital dual-model relationship generated by the audience of “Virtual Tour Streaming,” a term that describes virtual tour streaming’s nascent digital economy. This is situated in a virtual tour streaming platform to ascertain how it influences the intention of the audience and to use “Swift Guanxi” as the interaction variable to actual intention behavior. This is done to understand the contributions of virtual tour streaming adoption in a direct dial platform of different audience levels and their consumption behavior. The remaining sections discuss the theoretical and practical implications of the study

MuRAL: Multi-Scale Region-based Active Learning for Object Detection

Obtaining large-scale labeled object detection dataset can be costly and time-consuming, as it involves annotating images with bounding boxes and class labels. Thus, some specialized active learning methods have been proposed to reduce the cost by selecting either coarse-grained samples or fine-grained instances from unlabeled data for labeling. However, the former approaches suffer from redundant labeling, while the latter methods generally lead to training instability and sampling bias. To address these challenges, we propose a novel approach called Multi-scale Region-based Active Learning (MuRAL) for object detection. MuRAL identifies informative regions of various scales to reduce annotation costs for well-learned objects and improve training performance. The informative region score is designed to consider both the predicted confidence of instances and the distribution of each object category, enabling our method to focus more on difficult-to-detect classes. Moreover, MuRAL employs a scale-aware selection strategy that ensures diverse regions are selected from different scales for labeling and downstream finetuning, which enhances training stability. Our proposed method surpasses all existing coarse-grained and fine-grained baselines on Cityscapes and MS COCO datasets, and demonstrates significant improvement in difficult category performance

Construction of Coupled Period-Mass Functions in Extrasolar Planets through the Nonparametric Approach

Using the period and mass data of two hundred and seventy-nine extrasolar planets, we have constructed a coupled period-mass function through the non-parametric approach. This analytic expression of the coupled period-mass function has been obtained for the first time in this field. Moreover, due to a moderate period-mass correlation, the shapes of mass/period functions vary as a function of period/mass. These results of mass and period functions give way to two important implications: (1) the deficit of massive close-in planets is confirmed, and (2) the more massive planets have larger ranges of possible semi-major axes. These interesting statistical results will provide important clues into the theories of planetary formation.Comment: 20 pages, 7 figures, published in AJ, 137, 329 (2009

Optimizing Human Synovial Fluid Preparation for Two-Dimensional Gel Electrophoresis

<p>Abstract</p> <p>Background</p> <p>Proteome analysis is frequently applied in identifying the proteins or biomarkers in knee synovial fluids (SF) that are associated with osteoarthritis and other arthritic disorders. The 2-dimensional gel electrophoresis (2-DE) is the technique of choice in these studies. Disease biomarkers usually appear in low concentrations and may be masked by high abundant proteins. Therefore, the main aim of this study was to find the most suitable sample preparation method that can optimize the expression of proteins on 2-DE gels that can be used to develop a reference proteome picture for non-osteoarthritic knee synovial fluid samples. Proteome pictures obtained from osteoarthritic knee synovial fluids can then be compared with the reference proteome pictures obtained in this study to assist us in identifying the disease biomarkers more correctly.</p> <p>Results</p> <p>The proteomic tool of 2-DE with immobilized pH gradients was applied in this study. A total of 12 2-DE gel images were constructed from SF samples that were free of osteoarthritis. In these samples, 3 were not treated with any sample preparation methods, 3 were treated with acetone, 3 were treated with 2-DE Clean-Up Kit, and 3 were treated with the combination of acetone and 2-D Clean-Up Kit prior to 2-DE analysis. Gel images were analyzed using the PDQuest Basic 8.0.1 Analytical software. Protein spots that were of interest were excised from the gels and sent for identification by mass spectrometry. Total SF total protein concentration was calculated to be 21.98 ± 0.86 mg/mL. The untreated SF samples were detected to have 456 ± 33 protein spots on 2-DE gel images. Acetone treated SF samples were detected to have 320 ± 28 protein spots, 2-D Clean-Up Kit treated SF samples were detected to have 413 ± 31 protein spots, and the combined treatment method of acetone and 2-D Clean-Up Kit was detected to have 278 ± 26 protein spots 2-DE gel images. SF samples treated with 2-D Clean-Up Kit revealed clearer presentation of the isoforms and increased intensities of the less abundant proteins of haptoglobin, apolipoprotein A-IV, prostaglandin-D synthase, alpha-1B-glycoprotein, and alpha-2-HS-glycoprotein on 2-DE gel images as compared with untreated SF samples and SF samples treated with acetone.</p> <p>Conclusions</p> <p>The acetone precipitation method and the combined treatment effect of acetone and 2-DE Clean-Up Kit are not preferred in preparing SF samples for 2-DE analysis as both protein intensities and numbers decrease significantly. On the other hand, 2-D Clean-Up Kit treated SF samples revealed clearer isoforms and higher intensities for the less abundant proteins of haptoglobin, apolipoprotein A-IV, prostaglandin-D synthase, alpha-1B-glycoprotein, and alpha-2-HS-glycoprotein on 2-DE gels. As a result, it is recommended that SF samples should be treated with protein clean up products such as 2-D Clean-Up Kit first before conducting proteomic research in searching for the relevant biomarkers associated with knee osteoarthritis.</p