1,431 research outputs found

    Geospatial Distribution of Age-Adjusted Incidence of the Three Major Types of Pediatric Cancers and Waterborne Agrichemicals in Nebraska

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    This study was conducted to examine, at the county level, the relationship between pediatric cancer incidence rate and atrazine and nitrate mean concentrations in surface and groundwater. A negative binomial regression analysis was performed to investigate the association between central nervous system (CNS) tumors, leukemia, lymphoma, and atrazine and nitrate mean concentrations in groundwater. The age-adjusted brain and other CNS cancer incidence was higher than the national average in 63% of the Nebraska counties. After controlling for the counties socio-economic status and nitrate concentrations in groundwater, counties with groundwater atrazine concentrations above 0.0002 μg/L had a higher incidence rate for pediatric cancers (brain and other CNS, leukemia, and lymphoma) compared to counties with groundwater atrazine concentrations in the reference group (0.0000–0.0002 μg/L). Additionally, compared to counties with groundwater nitrate concentrations between 0 and 2 mg/L (reference group), counties with groundwater nitrate concentrations between 2.1 and 5 mg/L (group 2) had a higher incidence rate for pediatric brain and other CNS cancers (IRR = 8.39; 95% CI: 8.24–8.54), leukemia (IRR = 7.35; 95% CI: 7.22–7.48), and lymphoma (IRR = 5.59; CI: 5.48–5.69) after adjusting for atrazine groundwater concentration and the county socioeconomic status. While these findings do not indicate a causal relationship, because other contaminants or cancer risk factors have not been accounted for, they suggest that atrazine and nitrate may pose a risk relative to the genesis of pediatric brain and CNS cancers, leukemia, and lymphoma

    Quantum state preparation and macroscopic entanglement in gravitational-wave detectors

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    Long-baseline laser-interferometer gravitational-wave detectors are operating at a factor of 10 (in amplitude) above the standard quantum limit (SQL) within a broad frequency band. Such a low classical noise budget has already allowed the creation of a controlled 2.7 kg macroscopic oscillator with an effective eigenfrequency of 150 Hz and an occupation number of 200. This result, along with the prospect for further improvements, heralds the new possibility of experimentally probing macroscopic quantum mechanics (MQM) - quantum mechanical behavior of objects in the realm of everyday experience - using gravitational-wave detectors. In this paper, we provide the mathematical foundation for the first step of a MQM experiment: the preparation of a macroscopic test mass into a nearly minimum-Heisenberg-limited Gaussian quantum state, which is possible if the interferometer's classical noise beats the SQL in a broad frequency band. Our formalism, based on Wiener filtering, allows a straightforward conversion from the classical noise budget of a laser interferometer, in terms of noise spectra, into the strategy for quantum state preparation, and the quality of the prepared state. Using this formalism, we consider how Gaussian entanglement can be built among two macroscopic test masses, and the performance of the planned Advanced LIGO interferometers in quantum-state preparation

    Searching for a Stochastic Background of Gravitational Waves with LIGO

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    The Laser Interferometer Gravitational-wave Observatory (LIGO) has performed the fourth science run, S4, with significantly improved interferometer sensitivities with respect to previous runs. Using data acquired during this science run, we place a limit on the amplitude of a stochastic background of gravitational waves. For a frequency independent spectrum, the new limit is ΩGW<6.5×105\Omega_{\rm GW} < 6.5 \times 10^{-5}. This is currently the most sensitive result in the frequency range 51-150 Hz, with a factor of 13 improvement over the previous LIGO result. We discuss complementarity of the new result with other constraints on a stochastic background of gravitational waves, and we investigate implications of the new result for different models of this background.Comment: 37 pages, 16 figure

    Compressed representation of a partially defined integer function over multiple arguments

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    In OLAP (OnLine Analitical Processing) data are analysed in an n-dimensional cube. The cube may be represented as a partially defined function over n arguments. Considering that often the function is not defined everywhere, we ask: is there a known way of representing the function or the points in which it is defined, in a more compact manner than the trivial one
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