8,971 research outputs found
Self-Consistent Thermal Accretion Disk Corona Models for Compact Objects: I. Properties of the Corona and the Spectrum of Escaping Radiation
We present the properties of accretion disk corona (ADC) models, where the
radiation field, the temperature, and the total opacity of the corona are
determined self-consistently. We use a non-linear Monte Carlo code to perform
the calculations. As an example, we discuss models where the corona is situated
above and below a cold accretion disk with a plane-parallel (slab) geometry,
similar to the model of Haardt and Maraschi. By Comptonizing the soft radiation
emitted by the accretion disk, the corona is responsible for producing the
high-energy component of the escaping radiation. Our models include the
reprocessing of radiation in the accretion disk. Here, the photons either are
Compton reflected or photo-absorbed, giving rise to fluorescent line emission
and thermal emission. The self-consistent coronal temperature is determined by
balancing heating (due to viscous energy dissipation) with Compton cooling,
determined using the fully relativistic, angle-dependent cross-sections. The
total opacity is found by balancing pair productions with annihilations. We
find that, for a disk temperature kT_bb \lta 200 eV, these coronae are unable
to have a self-consistent temperature higher than \sim 120 keV if the total
optical depth is \gta 0.2, regardless of the compactness parameter of the
corona and the seed opacity. This limitation corresponds to the angle-averaged
spectrum of escaping radiation having a photon index \gta 1.8 within the 5 keV
- 30 keV band. Finally, all models that have reprocessing features also predict
a large thermal excess at lower energies. These constraints make explaining the
X-ray spectra of persistent black hole candidates with ADC models very
problematic.Comment: 15 pages, Latex, 9 .eps figures, uses emulateapj.sty (included). To
be published in ApJ, October 1, 1997, Vol. 48
Statute of Frauds—Real Estate Brokers\u27 Contracts—Agency
P orally engaged D to sell P\u27s land, for which D was to receive a commission of 10,000, and that D could procure the necessary loan upon paying a bonus of 4,000. P brought an action to recover the $3,000 which D had received and converted to his own use. Held: The oral agreement created an agency relationship which D breached by his misrepresentations, and RCW 19.36.010 (5) [RRS § 5825(5)], which provides that An agreement authorizing or employing an agent or broker to sell or purchase real estate for compensation or commission shall be void unless in writing, is not applicable since it refers only to agreements for the payment of a commission, and does not require that the actual authority to sell or purchase be in writing. Mele v. Cerenzie, 140 Wash. Dec. 115, 241 P. 2d 669 (1952)
Probate—Administration of an Estate Under Absentee Statute
A bank was appointed guardian of N\u27s estate in 1941, N having been adjudged incompetent. In 1942, N disappeared, and was not heard from for over seven years. P, on behalf of N\u27s heirs, petitioned the probate court for appointment as administrator of N\u27s estate. The appointment was made, and the bank appealed. Held: Reversed. Where there is neither allegation nor evidence sufficient to give the probate court jurisdiction to determine that the missing man is dead, his heirs are relegated to the absentee statutes for provisional distribution. In re Nelson\u27s Estate, 37 Wn. 2d 397, 224 P. 2d 347 (1951)
RXTE Observation of Cygnus X-1: II. Timing Analysis
We present timing analysis for a Rossi X-ray Timing Explorer observation of
Cygnus X-1 in its hard/low state. This was the first RXTE observation of Cyg
X-1 taken after it transited back to this state from its soft/high state.
RXTE's large effective area, superior timing capabilities, and ability to
obtain long, uninterrupted observations have allowed us to obtain measurements
of the power spectral density (PSD), coherence function, and Fourier time lags
to a decade lower in frequency and half a decade higher in frequency than
typically was achieved with previous instruments. Notable aspects of our
observations include a weak 0.005 Hz feature in the PSD coincident with a
coherence recovery; a `hardening' of the high-frequency PSD with increasing
energy; a broad frequency range measurement of the coherence function,
revealing rollovers from unity coherence at both low and high frequency; and an
accurate determination of the Fourier time lags over two and a half decades in
frequency. As has been noted in previous similar observations, the time delay
is approximately proportional to f^(-0.7), and at a fixed Fourier frequency the
time delay of the hard X-rays compared to the softest energy channel tends to
increase logarithmically with energy. Curiously, the 0.01-0.2 Hz coherence
between the highest and lowest energy bands is actually slightly greater than
the coherence between the second highest and lowest energy bands. We carefully
describe all of the analysis techniques used in this paper, and we make
comparisons of the data to general theoretical expectations. In a companion
paper, we make specific comparisons to a Compton corona model that we have
successfully used to describe the energy spectral data from this observation.Comment: To Be Published in the Astrophysical Journal. 18 pages. Uses
emulatepaj.st
RXTE Observation of Cygnus X-1: Spectral Analysis
We present the results of the analysis of the broad-band spectrum of Cygnus
X-1 from 3.0 to 200 keV, using data from a 10 ksec observation by the Rossi
X-ray Timing Explorer. The spectrum can be well described phenomenologically by
an exponentially cut-off power law with a photon index Gamma = 1.45 +/- 0.02 (a
value considerably harder than typically found), e-folding energy E_fold = 162
+/- 9 keV, plus a deviation from a power law that formally can be modeled as a
thermal blackbody with temperature kT_bb = 1.2 +/1 0.2 keV. Although the 3 - 30
keV portion of the spectrum can be fit with a reflected power law with Gamma =
1.81 +/- 0.01 and covering fraction f = 0.35 +/- 0.02, the quality of the fit
is significantly reduced when the HEXTE data in the 30 - 100 keV range is
included, as there is no observed hardening in the power law within this energy
range. As a physical description of this system, we apply the accretion disc
corona models of Dove, Wilms & Begelman (1997) --- where the temperature of the
corona is determined self-consistently. A spherical corona with a total optical
depth tau = 1.6 +/- 0.1 and an average temperature kT_c = 87 +/- 5 keV,
surrounded by an exterior cold disc, does provide a good description of the
data (reduced chi-squared = 1.55). These models deviate from the data by up to
7% in the 5 - 10 keV range, and we discuss possible reasons for these
discrepancies. However, considering how successfully the spherical corona
reproduces the 10 - 200 keV data, such ``photon-starved'' coronal geometries
seem very promising for explaining the accretion processes of Cygnus X-1.Comment: Revised version (added content). 8 pages, 6 figures, 1 table.tex
file, latex, uses mn.sty. Accepted for publication in MNRA
Common Grasses of Nebraska: Rangeland Prairie Pasture (Including Grass-Like Plants)
Introduction 3 • Plant Groups 4 • Parts of a Grass Plant 5 • Inflorescence Characteristics 5 • Vegetative Characteristics 5 • Parts of a Grass-Like • Plant 5 • Fruit and Floral Characteristics 5 • Vegetative Characteristics 5 •
Warm-Season • Perennial Grasses • Bermudagrass 14 • Blowoutgrass 15 • bluestems: • Big bluestem 16 • Little bluestem 18 • Sand bluestem 20 • Silver bluestem 21 • Yellow bluestem 22 • Buffalograss 24 • dropseeds: • Alkali sacaton 26 • Prairie dropseed 27 • Sand dropseed 29 • Tall dropseed 30 • Eastern gamagrass 32 • gramas: • Blue grama 33 • Hairy grama 35 • Sideoats grama 36 • Indiangrass 38 • Inland saltgrass 40 • Johnsongrass 41 • lovegrasses: • Purple lovegrass 43 • Sand lovegrass 44 • muhlys: • Marsh muhly 45 • Plains muhly 47 • Sandhill muhly 48 • Scratchgrass 49 • Phragmites 50 • Prairie cordgrass 52 • Prairie sandreed 54 • Purple threeawn 55 • Purpletop 56 • Sand paspalum 58 • Switchgrass 59 • Tumblegrass 61 • Windmillgrass 62
Warm-Season • Annual Grasses • Barnyardgrass 66 • Bearded sprangletop 67 • crabgrasses: • Hairy crabgrass 68 • Smooth crabgrass 69 • Fall panicum 70 • foxtails: • Green foxtail 72 • Hooked foxtail 73 • Yellow foxtail 74 • Goosegrass 76 • Poverty dropseed 77 • Purple sandgrass 78 • Sandbur 79 • Stinkgrass 81 • threeawns: • Forktip threeawn 82 • Prairie threeawn 83 • Witchgrass 84
Cool-Season • Perennial Grasses • bentgrasses: • Redtop bentgrass 88 • Spike bentgrass 89 • Winter bentgrass 90 • bluegrasses: • Bulbous bluegrass 91 • Canada bluegrass 92 • Kentucky bluegrass 94 • Mutton bluegrass 95 • Plains bluegrass 96 • Sandberg bluegrass 98 • Bluejoint reedgrass 99 • bromegrasses: • Meadow brome 101 • Smooth brome 102 • Creeping foxtail 103 • Fowl mannagrass 105 • Foxtail barley 106 • Green needlegrass 108 • Indian ricegrass 109 • Needleandthread 111 • Orchardgrass 112 • Perennial ryegrass 114 • Porcupinegrass 115 • Prairie junegrass 116 • Prairie wedgescale 117 • Quackgrass 119 • Reed canarygrass 120 • rosettegrasses: • Scribner rosettegrass 121 • Wilcox rosettegrass 123 • Squirreltail 124 • Tall fescue 125 • Timothy 127 • Weeping alkaligrass 129 • wheatgrasses: • Crested wheatgrass 130 • Intermediate wheatgrass 132 • Slender wheatgrass 133 • Tall wheatgrass 135 • Western wheatgrass 136 • wildryes: • Canada wildrye 138 • Russian wildrye 139
Cool-Season • Annual Grasses: • American sloughgrass 142 • Annual bluegrass 143 • Cheatgrass 144 • Japanese brome 145 • Little barley 146 • Northern wildrice 148 • Sixweeksgrass 149 •
Grass-Like • Plants: • American bulrush 152 • Field horsetail 153 • Schweinitz flatsedge 154 • sedges: • Nebraska sedge 155 • Needleleaf sedge 156 • Sun sedge 157 • Threadleaf sedge 158 • Yellow nutsedge 160 • Glossary 161 • Ecological Sites 170 • Selected References 173 • Index 17
The Kettleman Hills Landfill Failure: A Retrospective View of the Failure Investigations and Lessons Learned
The sliding stability failure of the Kettleman Hills waste landfill focused attention on several issues related to the safe design and filling of waste repositories, including low strengths between geosynthetic material interfaces in composite liner systems and low interface strength between compacted clay and smooth geomembranes. Waste placement plans must be carefully developed to insure an adequate factor of safety against sliding at all stages of filling. Because of assumptions and uncertainties that remained following the initial failure investigation, model tests, at a scale of 1:150, were done. These tests reproduced the field failure very well and provided insights into the failure mechanisms. A three-dimensional method for stability analysis gave results in close agreement with field observations and the results of a subsequent detailed failure investigation done by others (Byrne et al., 1992). Those special cases of landfill geometry and liner properties for which the 3D stability may be more critical than that computed using usual 2D methods of analysis could then be determined
Distributional Impact of U.S. Farm Commodity Programs: Accounting for Alternative Farm Household Typologies
Agricultural households adjust to policy changes through market mechanisms by altering: their production mix, labor input, and on- and off-farm investments. Because of the significant heterogeneity among farms in the US agricultural sector, various types of farm households respond to the same policy change in significantly different ways. The parameters used to classify farm households into different typologies may also play a significant role in the interpretation of observed effects of policy changes. This paper, using a highly disaggregated U.S. Computable General Equilibrium (CGE) model, analyzes the distributional impacts of policy changes involving price-contingent government payments on alternative U.S. farm household typologies. We find that farm households do vary their responses to an elimination of price-contingent support based on location, production specialty, and farm categorization.Agricultural and Food Policy,
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