Institutional Investment in REITs: Evidence and Implications

It has been documented that institutional investors did not participate actively in the real estate investment trust (REIT) stock market prior to 1990 and that the percentage of institutional holdings of a REIT stock is positively correlated with the performance of the REIT stock. This article documents a reversal in trend in institutional investors’ preference for investing in REIT stocks and in other stocks. The study shows that prior to 1990, institutional investors invested more of their funds in other stocks than in REITs, whereas after 1990 they invest more of their funds in REITs than in other stocks in the market. The strategies of institutional investors investing in REITs are also analyzed. The findings of the study have implications for the agency and corporate control issues prevailing in the REIT stock market.

E/B Separation in CMB Interferometry

We study the problem of separating E and B modes in interferometric observations of the polarization of the cosmic microwave background. The E and B band powers and their mixings are measured from both single-dish and interferometric mock observations using the quadratic estimator of the maximum likelihood analysis. We find that the interferometer can separate E and B modes in a single-pointing measurement and is thus well suited for detecting the faint lensing induced and gravity-wave induced B modes. In mosaicking observation, compared to the single dish, the interferometer is in general more efficient in separating E and B modes, and for high signal-to-noise per pixel it needs about three times fewer pixels to measure extremely blue polarization power spectra.Comment: 21 pages, 11 figures, ApJ in pres

Mobility-Induced Service Migration in Mobile Micro-Clouds

Mobile micro-cloud is an emerging technology in distributed computing, which is aimed at providing seamless computing/data access to the edge of the network when a centralized service may suffer from poor connectivity and long latency. Different from the traditional cloud, a mobile micro-cloud is smaller and deployed closer to users, typically attached to a cellular basestation or wireless network access point. Due to the relatively small coverage area of each basestation or access point, when a user moves across areas covered by different basestations or access points which are attached to different micro-clouds, issues of service performance and service migration become important. In this paper, we consider such migration issues. We model the general problem as a Markov decision process (MDP), and show that, in the special case where the mobile user follows a one-dimensional asymmetric random walk mobility model, the optimal policy for service migration is a threshold policy. We obtain the analytical solution for the cost resulting from arbitrary thresholds, and then propose an algorithm for finding the optimal thresholds. The proposed algorithm is more efficient than standard mechanisms for solving MDPs.Comment: in Proc. of IEEE MILCOM 2014, Oct. 201

A convex analysis based criterion for blind separation of non-negative sources

[[abstract]]In this paper, we apply convex analysis to the problem of blind source separation (BSS) of non-negative signals. Under realistic assumptions applicable to many real-world problems such as multichannel biomedical imaging, we formulate a new BSS criterion that does not require statistical source independence, a fundamental assumption to many existing BSS approaches. The new criterion guarantees perfect separation (in the absence of noise), by constructing a convex set from the observations and then finding the extreme points of the convex set. Some experimental results are provided to demonstrate the efficacy of the proposed method. © 2007 IEEE.[[fileno]]2030157030001[[department]]電機工程學

Novel algorithms and high-performance cloud computing enable efficient fully quantum mechanical protein-ligand scoring

Ranking the binding of small molecules to protein receptors through physics-based computation remains challenging. Though inroads have been made using free energy methods, these fail when the underlying classical mechanical force fields are insufficient. In principle, a more accurate approach is provided by quantum mechanical density functional theory (DFT) scoring, but even with approximations, this has yet to become practical on drug discovery-relevant timescales and resources. Here, we describe how to overcome this barrier using algorithms for DFT calculations that scale on widely available cloud architectures, enabling full density functional theory, without approximations, to be applied to protein-ligand complexes with approximately 2500 atoms in tens of minutes. Applying this to a realistic example of 22 ligands binding to MCL1 reveals that density functional scoring outperforms classical free energy perturbation theory for this system. This raises the possibility of broadly applying fully quantum mechanical scoring to real-world drug discovery pipelines.Comment: 15 pages, 5 figures, 1 tabl