珊瑚中微量铀的ID-ICP-MS 高精度测定及其在珊瑚U/Ca 温度计研究中的应用

建立了同位素稀释技术与IC-MS 相结合的ID-ICP-MS 分析方法, 成功测量了取自南海北部的滨珊瑚样品中的微量铀, 获得0.5% 左右的精度。并以此建立南海北部近岸海域的珊瑚U/Ca 温度计, 其温度精度可达士0.5 ℃。ID-ICP-MS, an analytical method that combines isotope dilution technique and ICP-MS method had been developed in our laboratory. Trace uranium of the coral samples from the northern area of the South China Sea had been measured to an accuracy of 0.5%. Depended on these results, a high resolution coral U/Ca thermometer for thes area was established. Monthly average SSTs with a precision of ±0.5℃ were attainable by this U/Ca thermometer.published_or_final_versio

Zone center phonons of the orthorhombic RMnO3 (R = Pr, Eu, Tb, Dy, Ho) perovskites

A short range force constant model (SRFCM) has been applied for the first time to investigate the phonons in RMnO3 (R = Pr, Eu, Tb, Dy, Ho) perovskites in their orthorhombic phase. The calculations with 17 stretching and bending force constants provide good agreement for the observed Raman frequencies. The infrared frequencies have been assigned for the first time. PACS Codes: 36.20.Ng, 33.20.Fb, 34.20.CfComment: 8 pages, 1 figur

Region-based and pathway-based QTL mapping using a p-value combination method

Quantitative trait locus (QTL) mapping using deep DNA sequencing data is a challenging task. In this study we performed region-based and pathway-based QTL mappings using a p-value combination method to analyze the simulated quantitative traits Q1 and Q4 and the exome sequencing data. The aims were to evaluate the performance of the QTL mapping approaches that were used and to suggest plausible strategies for QTL mapping of DNA sequencing data. We conducted single-locus QTL mappings using a linear regression model with adjustments for age and smoking status, and we also conducted region-based and pathway-based QTL mappings using a truncated product method for combining p-values from the single-locus QTL mapping. To account for the features of rare variants and common single-nucleotide polymorphisms (SNPs), we considered independently rare-variant-only, common-SNP-only, and combined analyses. An analysis of 200 simulated replications showed that the three region-based methods reasonably controlled type I error, whereas the combined analysis yielded the greatest statistical power. Rare-variant-only, common-SNP-only, and combined analyses were also applied to pathway-based QTL mappings. We found that pathway-based QTL mappings had a power of approximately 100% when the significance of the vascular endothelial growth factor pathway was evaluated, but type I errors were slightly inflated. Our approach complements single-locus QTL mapping. An integrated approach using single-locus, combined region-based, and combined pathway-based analyses should yield promising results for QTL mapping of DNA sequencing data

ITPKC Single Nucleotide Polymorphism Associated with the Kawasaki Disease in a Taiwanese Population

Kawasaki disease (KD) is characterized by systemic vasculitis with unknown etiology. Previous studies from Japan indicated that a gene polymorphism of ITPKC (rs28493229) is responsible for susceptibility to KD. We collected DNA samples from 1,531 Taiwanese subjects (341 KD patients and 1,190 controls) for genotyping ITPKC. In this study, no significant association was noted for the ITPKC polymorphism (rs28493229) between the controls and KD patients, although the CC genotype was overrepresented. We further combined our data with previously published case/control KD studies in the Taiwanese population and performed a meta-analysis. A significant association between rs28493229 and KD was found (Odds Ratio:1.36, 95% Confidence Interval 1.12–1.66). Importantly, a significant association was obtained between rs28493229 and KD patients with aneurysm formation (P = 0.001, under the recessive model). Taken together, our results indicated that C-allele of ITPKC SNP rs28493229 is associated with the susceptibility and aneurysm formation in KD patients in a Taiwanese population

Interferometric time-stretch microscopy for ultrafast quantitative cellular and tissue imaging at 1 μm

Quantitative phase imaging (QPI) has been proven to be a powerful tool for label-free characterization of biological specimens. However, the imaging speed, largely limited by the image sensor technology, impedes its utility in applications where high-throughput screening and efficient big-data analysis are mandated. We here demonstrate interferometric time-stretch (iTS) microscopy for delivering ultrafast quantitative phase cellular and tissue imaging at an imaging line-scan rate >20 MHz-orders-of-magnitude faster than conventional QPI. Enabling an efficient time-stretch operation in the 1-mum wavelength window, we present an iTS microscope system for practical ultrafast QPI of fixed cells and tissue sections, as well as ultrafast flowing cells (at a flow speed of up to 8 ms). To the best of our knowledge, this is the first time that time-stretch imaging could reveal quantitative morphological information of cells and tissues with nanometer precision. As many parameters can be further extracted from the phase and can serve as the intrinsic biomarkers for disease diagnosis, iTS microscopy could find its niche in high-throughput and high-content cellular assays (e.g., imaging flow cytometry) as well as tissue refractometric imaging (e.g., whole-slide imaging for digital pathology).published_or_final_versio

The US stock market leads the Federal funds rate and Treasury bond yields

Using a recently introduced method to quantify the time varying lead-lag dependencies between pairs of economic time series (the thermal optimal path method), we test two fundamental tenets of the theory of fixed income: (i) the stock market variations and the yield changes should be anti-correlated; (ii) the change in central bank rates, as a proxy of the monetary policy of the central bank, should be a predictor of the future stock market direction. Using both monthly and weekly data, we found very similar lead-lag dependence between the S&P500 stock market index and the yields of bonds inside two groups: bond yields of short-term maturities (Federal funds rate (FFR), 3M, 6M, 1Y, 2Y, and 3Y) and bond yields of long-term maturities (5Y, 7Y, 10Y, and 20Y). In all cases, we observe the opposite of (i) and (ii). First, the stock market and yields move in the same direction. Second, the stock market leads the yields, including and especially the FFR. Moreover, we find that the short-term yields in the first group lead the long-term yields in the second group before the financial crisis that started mid-2007 and the inverse relationship holds afterwards. These results suggest that the Federal Reserve is increasingly mindful of the stock market behavior, seen at key to the recovery and health of the economy. Long-term investors seem also to have been more reactive and mindful of the signals provided by the financial stock markets than the Federal Reserve itself after the start of the financial crisis. The lead of the S&P500 stock market index over the bond yields of all maturities is confirmed by the traditional lagged cross-correlation analysis.Comment: 12 pages, 7 figures, 1 tabl

Deep Lesion Graphs in the Wild: Relationship Learning and Organization of Significant Radiology Image Findings in a Diverse Large-scale Lesion Database

Radiologists in their daily work routinely find and annotate significant abnormalities on a large number of radiology images. Such abnormalities, or lesions, have collected over years and stored in hospitals' picture archiving and communication systems. However, they are basically unsorted and lack semantic annotations like type and location. In this paper, we aim to organize and explore them by learning a deep feature representation for each lesion. A large-scale and comprehensive dataset, DeepLesion, is introduced for this task. DeepLesion contains bounding boxes and size measurements of over 32K lesions. To model their similarity relationship, we leverage multiple supervision information including types, self-supervised location coordinates and sizes. They require little manual annotation effort but describe useful attributes of the lesions. Then, a triplet network is utilized to learn lesion embeddings with a sequential sampling strategy to depict their hierarchical similarity structure. Experiments show promising qualitative and quantitative results on lesion retrieval, clustering, and classification. The learned embeddings can be further employed to build a lesion graph for various clinically useful applications. We propose algorithms for intra-patient lesion matching and missing annotation mining. Experimental results validate their effectiveness.Comment: Accepted by CVPR2018. DeepLesion url adde

Ultrafast Laser-Scanning Time-Stretch Imaging at Visible Wavelengths

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Asymmetric-detection time-stretch optical microscopy (ATOM) for ultrafast high-contrast cellular imaging in flow

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