A review and analysis of the dose response relationship for the probability of acute lethality from prompt or short-term exposure to ionizing radiation is presented. The purpose of this analysis is to provide recommendations concerning estimates of casualties expected from radiation accidents, the use of nuclear weapons, or possible terrorist activities. Previous work on acute ionizing radiation-induced lethality risk together with a collection of dose response relationships are analyzed and presented based on historical case data and expert opinion that have evolved from whole-body radiation therapy experience, radiation exposure accidents, nuclear weapon detonations, and animal experimentation. The nature of the data reviewed ranges from direct individual events to those offered according to collective expert opinion and consensus published as journal articles and in various technical documents and reports. The dose response relationships are expressed as two-parameter (median exposure level and slope) probability distribution models as a function of radiation exposure in terms of a free-in-air dose. Twelve different dose response relationships are presented and discussed, including the impact of some medical care.

Mean, integrated geomagnetic noise power spectra in six octaves between 0.002 and 0.128 Hz from the Air Force Geophysics Laboratory (AFGL) magnetometer network were grouped into seasonal ensembles. We found that the local time variation of the mean logarithm of this ensemble, with respect to both 3‐hr and 8.5‐min time blocks, consistently experienced a 5–10 dB maximum centered around local noon at higher frequencies and near dawn and dusk at lower frequencies, a factor of 3–10 in power. The shape of this trend differed with geomagnetic field component, geomagnetic latitude, and frequency octave. The high‐frequency Pc 3 and 4 waves have a broad maximum in power centered on local noon, but the longer‐period Pc 4 and 5 wave power maximizes away from noon toward dawn for the north‐south geomagnetic field component and toward dusk for the east‐west component. Two years of data did not provide a large enough sample to resolve a significant seasonal variation in the shape of the diurnal trend. These trends changed consistently during periods of enhanced global activity, as measured by the index Ap. These are among the first systematic observations of Pc 5 wave power at low geomagnetic latitudes (40°–55°), indicating that wave energy from the outer magnetosphere is coupling or propagating to low‐latitude locations. This statistical study extends the few previous event studies by providing an explicit parametrization of local time trends in wave power as a function of frequency subband, geographic location, and magnetic activity.

Bioterrorism and emerging infectious diseases such as influenza have spurred research into rapid outbreak detection. One primary thrust of this research has been to identify data sources that provide early indication of a disease outbreak by being leading indicators relative to other established data sources. Researchers tend to rely on the sample cross-correlation function (CCF) to quantify the association between two data sources. There has been, however, little consideration by medical informatics researchers of the influence of methodological choices on the ability of the CCF to identify a lead-lag relationship between time series. We draw on experience from the econometric and environmental health communities, and we use simulation to demonstrate that the sample CCF is highly prone to bias. Specifically, long-scale phenomena tend to overwhelm the CCF, obscuring phenomena at shorter wave lengths. Researchers seeking lead-lag relationships in surveillance data must therefore stipulate the scale length of the features of interest (e.g., short-scale spikes versus long-scale seasonal fluctuations) and then filter the data appropriately--to diminish the influence of other features, which may mask the features of interest. Otherwise, conclusions drawn from the sample CCF of bi-variate time-series data will inevitably be ambiguous and often altogether misleading.

Abstract. This study explores the statistical relationships between 2 years of solar wind data recorded by the IMP 8 spacecraft and data from the Mount Clemens magnetometer station (L = 3) to improve our understanding of possible energy sources of ULF wave activity. Within the four frequency bands, f = 4-8 mHz, 8-16 mHz, 16-32 mHz, and 32-64 mHz, that are studied, two distinct types of waves are found. One is at high frequencies corresponding to Pc3 pulsations, and the other is at low frequencies corresponding to Pc5 and low-frequency Pc4 pulsations. The high-frequency part clearly has an energy source in the upstream foreshock. However, our analysis shows that the magnetospheric cusps do not appear to be the conduit of energy for the wave activity in this low-latitude region. The low-frequency activity occurs most frequently and has greater wave power when the interplanetary magnetic field is southward. This correlation suggests that the major energy source of these low-frequency waves is substorm-related or is related to the reconnection on the dayside magnetopause.

This paper presents calculations of ionospheric electron temperature and density perturbations and ground‐level signal changes produced by intense oblique high‐frequency (HF) radio waves. Our analysis takes into account focusing at caustics, the consequent Joule heating of the surrounding plasma, heat conduction, diffusion, and recombination processes, these being the effects of a powerful oblique “modifying” wave. It neglects whatever plasma instabilities might occur. We then seek effects on a secondary “test” wave that is propagated along the same path as the first. Our calculations predict ground‐level field strength reductions of several decibels in the test wave for modifying waves having effective radiated power (ERP) in the 85‐ to 90‐dBW range. These field strength changes are similar in sign, magnitude, and location to ones measured in Soviet experiments. The location of the signal change is sensitive to the frequency and the model ionosphere assumed; so future experiments should employ the widest possible range of frequencies and propagation conditions. An ERP of 90 dBW seems to be a sort of threshold that, if exceeded, might result in substantial rather than small signal changes. Our conclusions are based solely on Joule heating and subsequent refraction of waves passing through caustic regions.