13,848 research outputs found
Spray-on technique simplifies fabrication of complex thermal insulation blanket
Spray-on process constructs molds used in forming sections of thermal insulation blankets. The process simplifies the fabrication of blankets by eliminating much of the equipment formerly required and decreasing the time involved
Signal-to-Noise Eigenmode Analysis of the Two-Year COBE Maps
To test a theory of cosmic microwave background fluctuations, it is natural
to expand an anisotropy map in an uncorrelated basis of linear combinations of
pixel amplitudes --- statistically-independent for both the noise and the
signal. These -eigenmodes are indispensible for rapid Bayesian analyses of
anisotropy experiments, applied here to the recently-released two-year COBE
{\it dmr} maps and the {\it firs} map. A 2-parameter model with an overall
band-power and a spectral tilt describes well inflation-based
theories. The band-powers for {\it all} the {\it dmr} + GHz
and {\it firs} 170 GHz maps agree, , and
are largely independent of tilt and degree of (sharp) -filtering. Further,
after optimal -filtering, the {\it dmr} maps reveal the same
tilt-independent large scale features and correlation function. The unfiltered
{\it dmr} + index is ; increasing the
-filtering gives a broad region at (1.0--1.2)0.5, a jump to
(1.4--1.6)0.5, then a drop to 0.8, the higher values clearly seen to be
driven by -power spectrum data points that do not fit single-tilt models.
These indices are nicely compatible with inflation values (0.8--1.2), but
not overwhelmingly so.Comment: submitted to Phys.Rev.Letters, 4 pages, uuencoded compressed
PostScript; also bdmr2.ps.Z, via anonymous ftp to ftp.cita.utoronto.ca, cd to
/pub/dick/yukawa; CITA-94-2
Knowledge development for organic systems: An example of weed management
Despite the large amount information on weed biology and specific weed control measures produced by researchers, organic farmers still prioritise weeds as an important area for further research. A recent project investigating weed management in organic farming systems has established that knowledge and learning are key requirements for this to be effective. Development of relevant, practically useful knowledge depends on access to information generated ‘scientifically’ by researchers and also to knowledge generated as a result of farmer experience with weeds. This requires that farmers, advisors and researchers take a participatory approach to collecting and processing information on weed management, using it to develop new and relevant knowledge. The appropriate framework for knowledge development is thus a collegiate one in which all stakeholders’ value and learn from the observations and experience of others. These findings have implications for the way in which research is conducted and funded
Application of XFaster power spectrum and likelihood estimator to Planck
We develop the XFaster Cosmic Microwave Background (CMB) temperature and
polarization anisotropy power spectrum and likelihood technique for the Planck
CMB satellite mission. We give an overview of this estimator and its current
implementation and present the results of applying this algorithm to simulated
Planck data. We show that it can accurately extract the power spectrum of
Planck data for the high-l multipoles range. We compare the XFaster
approximation for the likelihood to other high-l likelihood approximations such
as Gaussian and Offset Lognormal and a low-l pixel-based likelihood. We show
that the XFaster likelihood is not only accurate at high-l, but also performs
well at moderately low multipoles. We also present results for cosmological
parameter Markov Chain Monte Carlo estimation with the XFaster likelihood. As
long as the low-l polarization and temperature power are properly accounted
for, e.g., by adding an adequate low-l likelihood ingredient, the input
parameters are recovered to a high level of accuracy.Comment: 25 pages, 20 figures, updated to reflect published version: slightly
extended account of XFaster technique, added improved plots and minor
corrections. Accepted for publication in MNRA
Arkansas Corn and Grain Sorghum Peformance Tests 2017
Corn and grain sorghum performance tests are conducted each year in Arkansas by the University of Arkansas System Division of Agriculture. The tests provide information to companies marketing seed within the state, and aid the Arkansas Cooperative Extension Service in formulating recommendations for producers
Arkansas Corn and Grain Sorghum Performance Tests 2014
Corn and grain sorghum performance tests are conducted each year in Arkansas by the University of Arkansas System Division of Agriculture. The tests provide information to companies marketing seed within the state, and aid the Arkansas Cooperative Extension Service in formulating recommendations for producers
Arkansas Soybean Performance Tests 2015
Soybean variety and strain performance tests are conducted each year in Arkansas by the University of Arkansas System Division of Agriculture’s Arkansas Crop Variety Improvement Program. The tests provide information to companies developing varieties and/or marketing seed within the State, and aid the Arkansas Cooperative Extension Service in formulating variety recommendations for soybean producers
Arkansas Soybean Performance Tests 2008
Soybean cultivar performance tests are conducted each year in Arkansas by the University of Arkansas Division of Agriculture. The tests provide information to companies developing cultivars and/or marketing seed within the state, and aid the Arkansas Cooperative Extension Service in formulating cultivar recommendations for soybean producer
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