Optimal shrinkage estimation in heteroscedastic hierarchical linear models

Shrinkage estimators have profound impacts in statistics and in scientific and engineering applications. In this article, we consider shrinkage estimation in the presence of linear predictors. We formulate two heteroscedastic hierarchical regression models and study optimal shrinkage estimators in each model. A class of shrinkage estimators, both parametric and semiparametric, based on unbiased risk estimate (URE) is proposed and is shown to be (asymptotically) optimal under mean squared error loss in each model. Simulation study is conducted to compare the performance of the proposed methods with existing shrinkage estimators. We also apply the method to real data and obtain encouraging and interesting results.Comment: 32 pages, 3 figures, contributed to: "Big and Complex Data Analysis: Statistical Methodologies and Applications", Springer, New Yor

Sub-pixel resolving optofluidic microscope for on-chip cell imaging

We report the implementation of a fully on-chip, lensless, sub-pixel resolving optofluidic microscope (SROFM). The device utilizes microfluidic flow to deliver specimens directly across a complementary metal oxide semiconductor (CMOS) sensor to generate a sequence of low-resolution (LR) projection images, where resolution is limited by the sensor's pixel size. This image sequence is then processed with a pixel super-resolution algorithm to reconstruct a single high resolution (HR) image, where features beyond the Nyquist rate of the LR images are resolved. We demonstrate the device's capabilities by imaging microspheres, protist Euglena gracilis, and Entamoeba invadens cysts with sub-cellular resolution and establish that our prototype has a resolution limit of 0.75 microns. Furthermore, we also apply the same pixel super-resolution algorithm to reconstruct HR videos in which the dynamic interaction between the fluid and the sample, including the in-plane and out-of-plane rotation of the sample within the flow, can be monitored in high resolution. We believe that the powerful combination of both the pixel super-resolution and optofluidic microscopy techniques within our SROFM is a significant step forwards toward a simple, cost-effective, high throughput and highly compact imaging solution for biomedical and bioscience needs

Leveraging RFID in hospitals: patient life cycle and mobility perspectives

The application of Radio Frequency Identification (RFID) to patient care in hospitals and healthcare facilities has only just begun to be accepted. This article develops a set of frameworks based on patient life cycle and time-and-motion perspectives for how RFID can be leveraged atop existing information systems to offer many benefits for patient care and hospital operations. It examines how patients are processed from admission to discharge, and considers where RFID can be applied. From a time-and-motion perspective, it shows how hospitals can apply RFID in three ways: fixed RFID readers interrogate mobile objects; mobile, handheld readers interrogate fixed objects; and mobile, handheld readers interrogate mobile objects. Implemented properly, RFID can significantly aid the medical staff in performing their duties. It can greatly reduce the need for manual entry of records, increase security for both patient and hospital, and reduce errors in administering medication. Hospitals are likely to encounter challenges, however, when integrating the technology into their day-to-day operations. What we present here can help hospital administrators determine where RFID can be deployed to add the most value