A new monetary aggregates measurement: Application to Taiwanese data

This paper compares the different dynamics of simple sum monetary aggregates and PLS indexes over the business cycle, which have turning points at economic expansion and recession phases. We also investigates the long run relationship between monetary aggregates and GDP, to utilize the data in the most efficient manner via the nonparametric rank test of cointegration analysis proposed by Breitung (2001), and the impulse response functions to find the response of GDP to innovations in PLS and simple sum aggregates from 1969Q1 to 2010Q3.monetary aggregates, PLS, business cycle, cointegration, impulse response functions

Discovery of a Proto-cluster Associated with a Ly-α\alpha Blob Pair at z=2.3

Bright Ly-$\alpha$ blobs (LABs) --- extended nebulae with sizes of $\sim$100kpc and Ly-$\alpha$ luminosities of $\sim$10$^{44}$erg s$^{-1}$ --- often reside in overdensities of compact Ly-$\alpha$ emitters (LAEs) that may be galaxy protoclusters. The number density, variance, and internal kinematics of LABs suggest that they themselves trace group-like halos. Here we test this hierarchical picture, presenting deep, wide-field Ly-$\alpha$ narrowband imaging of a 1$^\circ$ $\times$ 0.5$^\circ$ region around a LAB pair at $z$ = 2.3 discovered previously by a blind survey. We find 183 Ly-$\alpha$ emitters, including the original LAB pair and three new LABs with Ly-$\alpha$ luminosities of (0.9--1.3)$\times$10$^{43}$erg s$^{-1}$ and isophotal areas of 16--24 arcsec$^2$. Using the LAEs as tracers and a new kernel density estimation method, we discover a large-scale overdensity (Bo{\"o}tes J1430+3522) with a surface density contrast of $\delta_{\Sigma}$ = 2.7, a volume density contrast of $\delta$ $\sim$ 10.4, and a projected diameter of $\approx$ 20 comoving Mpc. Comparing with cosmological simulations, we conclude that this LAE overdensity will evolve into a present-day Coma-like cluster with $\log{(M/M_\odot)}$ $\sim$ $15.1\pm0.2$. In this and three other wide-field LAE surveys re-analyzed here, the extents and peak amplitudes of the largest LAE overdensities are similar, not increasing with survey size, implying that they were indeed the largest structures then and do evolve into rich clusters today. Intriguingly, LABs favor the outskirts of the densest LAE concentrations, i.e., intermediate LAE overdensities of $\delta_\Sigma = 1 - 2$. We speculate that these LABs mark infalling proto-groups being accreted by the more massive protocluster

A Simplified Crossing Fiber Model in Diffusion Weighted Imaging

Diffusion MRI (dMRI) is a vital source of imaging data for identifying anatomical connections in the living human brain that form the substrate for information transfer between brain regions. dMRI can thus play a central role toward our understanding of brain function. The quantitative modeling and analysis of dMRI data deduces the features of neural fibers at the voxel level, such as direction and density. The modeling methods that have been developed range from deterministic to probabilistic approaches. Currently, the Ball-and-Stick model serves as a widely implemented probabilistic approach in the tractography toolbox of the popular FSL software package and FreeSurfer/TRACULA software package. However, estimation of the features of neural fibers is complex under the scenario of two crossing neural fibers, which occurs in a sizeable proportion of voxels within the brain. A Bayesian non-linear regression is adopted, comprised of a mixture of multiple non-linear components. Such models can pose a difficult statistical estimation problem computationally. To make the approach of Ball-and-Stick model more feasible and accurate, we propose a simplified version of Ball-and-Stick model that reduces parameter space dimensionality. This simplified model is vastly more efficient in the terms of computation time required in estimating parameters pertaining to two crossing neural fibers through Bayesian simulation approaches. Moreover, the performance of this new model is comparable or better in terms of bias and estimation variance as compared to existing models

The ciliary GTPase Arl13b regulates cell migration and cell cycle progression

Acknowledgments We acknowledge Prof. Tamara Caspary from Emory University for kindly providing the cell lines, Linda Duncan from the University of Aberdeen Ian Fraser Cytometry Center for help with flow cytometry. MP was funded by the Scottish Universities Life Science Alliance (SULSA) and the University of Aberdeen. Funding This work was supported by grants from British Council China (Sino-UK higher Education for PhD studies) to YD and CM, The Carnegie Trust for the Universities of Scotland (70190) and The NHS Grampian Endowment Funds (14/09) to BL, and National Natural Science Foundation of China (31528011) to BL and YD.Peer reviewedPostprin