An Economy-wide Analysis of Impacts of WTO Tiered Formula for Tariff Reduction on Taiwan

In this study we use Taiwan as a case study to provide an economy-wide analysis of impacts on Taiwan of WTO tariff reduction schemes with different combinations of thresholds and reduction rates. The model we utilized in this study is Taiwan General Equilibrium Model with a WTO module (TAIGEM-WTO, hereafter) that is a multi-sectoral computable general equilibrium (CGE) model of the Taiwan's economy derived from Australian ORANI model (Dixon, Parmenter, Sutton and Vincent, 1982). Simulation results show that results are more sensitive to the scheme of tariff-reduction (i.e., Category 1, 2, and 3) than the tiered levels (i.e., A, B, C, and D) and as a strategy we should pay more attention to the arguments related to the amounts of tariff-reduction. Moreover, changes in nominal average tariff rates are more sensitive and shocks to the economy are more severe when we change the tariff reduction categories rather than the tiered levels. This conclusion also applies to the tiered reduction case when only sensitive products are considered. Finally, simulations with sector's bound rate calculated using arithmetic means have bigger effects than those using import values as weights. Therefore, sector's bound rate using import values as weights would be preferred.International Relations/Trade,

Signal Normalization among Multiple Optical Coherence Tomography Devices

Optical coherence tomography (OCT) has become a clinical standard in ophthalmology because it has the ability to provide in vivo cross-sectional images of ocular tissues with microscopic resolution in a non-contact and non-invasive manner. More and more manufacturers are getting involved in the race of instrument design and the development of the spectral-domain OCT (SD-OCT). Various light sources, optical designs, and image acquisition settings were employed by different manufacturers to stand out among competitors. This provides a wide variety of options in terms of scanning protocol, image processing, and presentation. However, the diversity also reflects in the variability in the OCT signal characteristics. The variability of OCT signal characteristics not only results in systematic differences in OCT measurement data, such as the retinal nerve fiber layer (RNFL) thickness and total retinal thickness, but also induces discrepancies in OCT image appearance. Those differences cause serious clinical challenges when comparing OCT images from different OCT devices, or recruiting multiple OCT devices in one study. To solve this problem, a novel signal normalization method was developed in this dissertation. The signal normalization was developed in a stepwise fashion to resolve all factors contributing to the systematic differences among various OCT devices, including axial sampling density, the amount of speckle noise, intensity dynamic range, and image quality. Quantitative analyses and qualitative assessments were conducted to evaluate the proposed signal normalization method. For the quantitative analyses, engineering and clinical validations were performed via measuring the absolute differences in A-scan profile intensity and comparing the systematic RNFL thickness differences before and after signal normalization. For the qualitative assessment, subjective evaluation of the similarity of OCT image appearance through a questionnaire was performed. Statistically significant reduction in both the absolute difference in A-scan profile and the systematic differences among SD-OCT devices were observed after signal normalization. Statistically significant improvements of image similarity between OCT image pairs were also found after the processing. With the proposed signal normalization method, quantitative analysis as well as qualitative assessment among OCT devices will become directly comparable, which would broaden the use of OCT technology in both clinical and research applications

Quantitative inference of dynamic regulatory pathways via microarray data

BACKGROUND: The cellular signaling pathway (network) is one of the main topics of organismic investigations. The intracellular interactions between genes in a signaling pathway are considered as the foundation of functional genomics. Thus, what genes and how much they influence each other through transcriptional binding or physical interactions are essential problems. Under the synchronous measures of gene expression via a microarray chip, an amount of dynamic information is embedded and remains to be discovered. Using a systematically dynamic modeling approach, we explore the causal relationship among genes in cellular signaling pathways from the system biology approach. RESULTS: In this study, a second-order dynamic model is developed to describe the regulatory mechanism of a target gene from the upstream causality point of view. From the expression profile and dynamic model of a target gene, we can estimate its upstream regulatory function. According to this upstream regulatory function, we would deduce the upstream regulatory genes with their regulatory abilities and activation delays, and then link up a regulatory pathway. Iteratively, these regulatory genes are considered as target genes to trace back their upstream regulatory genes. Then we could construct the regulatory pathway (or network) to the genome wide. In short, we can infer the genetic regulatory pathways from gene-expression profiles quantitatively, which can confirm some doubted paths or seek some unknown paths in a regulatory pathway (network). Finally, the proposed approach is validated by randomly reshuffling the time order of microarray data. CONCLUSION: We focus our algorithm on the inference of regulatory abilities of the identified causal genes, and how much delay before they regulate the downstream genes. With this information, a regulatory pathway would be built up using microarray data. In the present study, two signaling pathways, i.e. circadian regulatory pathway in Arabidopsis thaliana and metabolic shift pathway from fermentation to respiration in yeast Saccharomyces cerevisiae, are reconstructed using microarray data to evaluate the performance of our proposed method. In the circadian regulatory pathway, we identified mainly the interactions between the biological clock and the photoperiodic genes consistent with the known regulatory mechanisms. We also discovered the now less-known regulations between crytochrome and phytochrome. In the metabolic shift pathway, the casual relationship of enzymatic genes could be detected properly