A resampling-based test to detect person-to-person transmission of infectious disease

Early detection of person-to-person transmission of emerging infectious diseases such as avian influenza is crucial for containing pandemics. We developed a simple permutation test and its refined version for this purpose. A simulation study shows that the refined permutation test is as powerful as or outcompetes the conventional test built on asymptotic theory, especially when the sample size is small. In addition, our resampling methods can be applied to a broad range of problems where an asymptotic test is not available or fails. We also found that decent statistical power could be attained with just a small number of cases, if the disease is moderately transmissible between humans.Comment: Published at http://dx.doi.org/10.1214/07-AOAS105 in the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

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

Accurate molecular polarizabilities with coupled-cluster theory and machine learning

The molecular polarizability describes the tendency of a molecule to deform or polarize in response to an applied electric field. As such, this quantity governs key intra- and inter-molecular interactions such as induction and dispersion, plays a key role in determining the spectroscopic signatures of molecules, and is an essential ingredient in polarizable force fields and other empirical models for collective interactions. Compared to other ground-state properties, an accurate and reliable prediction of the molecular polarizability is considerably more difficult as this response quantity is quite sensitive to the description of the underlying molecular electronic structure. In this work, we present state-of-the-art quantum mechanical calculations of the static dipole polarizability tensors of 7,211 small organic molecules computed using linear-response coupled-cluster singles and doubles theory (LR-CCSD). Using a symmetry-adapted machine-learning based approach, we demonstrate that it is possible to predict the molecular polarizability with LR-CCSD accuracy at a negligible computational cost. The employed model is quite robust and transferable, yielding molecular polarizabilities for a diverse set of 52 larger molecules (which includes challenging conjugated systems, carbohydrates, small drugs, amino acids, nucleobases, and hydrocarbon isomers) at an accuracy that exceeds that of hybrid density functional theory (DFT). The atom-centered decomposition implicit in our machine-learning approach offers some insight into the shortcomings of DFT in the prediction of this fundamental quantity of interest

Reaction Mechanisms for Long-Life Rechargeable Zn/MnO 2 Batteries

Rechargeable aqueous Zn-ion batteries (ZIBs) are very promising for large-scale grid energy storage applications owing to their low cost, environmentally benign constituents, excellent safety, and relatively high energy density. Their usage, however, is largely hampered by the fast capacity fade. The complexity of the reactions has resulted in long-standing ambiguities of the chemical pathways of Zn/MnO 2 system. In this study, we find that both H + /Zn 2+ intercalation and conversion reactions occur at different voltages and that the rapid capacity fading can clearly be ascribed to the rate-limiting and irreversible conversion reactions at a lower voltage. By limiting the irreversible conversion reactions at â1.26 V, we successfully demonstrate ultrahigh power and long life that are superior to most of the reported ZIBs or even some lithium-ion batteries

Dynamics of moving bubbles in single and binary component systems

Dynamics of a single bubble moving in a quiescent liquid is analyzed for single and binary component systems. The transport of energy and/or mass at thermodynamic-phase equilibrium governs the dynamics of the bubble at its interface