We measured the partial pressure of oxygen (PO2) in the interstitial gas surrounding the sand-swimming Namib moleEremitalpa granti namibensis. At a sand temperature of 26 °C, which produced a nearly maximal rate of oxygen consumption, thePO2near the noses of the animals averaged only 0·9 kPa (6·7 Torr) below the level in the free atmosphere. High oxygen availability was a result of the notably low metabolic rate in the 20 g mammals and the dry, porous and metabolically inactive nature of dune sand. A mathematical model indicated that normal mammals weighing 200 g or more could comfortably exist completely encased in dune sand. We concluded that the moles' small size and low metabolic rate are not adaptations to hypoxia or hypercapnia underground but are probably related to low food availability and the energetic cost of foraging in their desert environment. 相似文献
This paper presents a fundamental study on the effect of the relative humidity on the rockfill crushing strength. This aspect plays an important role in the mechanical behaviour of rockfill, and it is known that certain characteristics of the granular materials, such as compressibility and shear strength, depend on the confining stress, which is a function of the particles crushing. An increased interest has been observed regarding the effect of the relative humidity in the mechanical behaviour of rockfill. Unfortunately, limited research has been conducted until now regarding the study of individual particle crushing. Therefore, this paper thoroughly investigated particle crushing, by performing single-particle crushing tests on rockfill particles divided into four size ranges, under different relative humidity conditions. The experimental results reveal a considerable influence of the relative humidity in the studied rockfill particles, whose strength of the particles with the greatest dimensions in saturated conditions was reduced by half. Consistent macro-mechanical evidence demonstrates that particle’s size and relative humidity conditions depict the most important factors that influence particle crushing strength.
Histograms of observations from spatial phenomena are often found to be more heavy-tailed than Gaussian distributions, which
makes the Gaussian random field model unsuited. A T-distributed random field model with heavy-tailed marginal probability density functions is defined. The model is a generalization
of the familiar Student-T distribution, and it may be given a Bayesian interpretation. The increased variability appears cross-realizations, contrary
to in-realizations, since all realizations are Gaussian-like with varying variance between realizations. The T-distributed random field model is analytically tractable and the conditional model is developed, which provides algorithms
for conditional simulation and prediction, so-called T-kriging. The model compares favourably with most previously defined random field models. The Gaussian random field model
appears as a special, limiting case of the T-distributed random field model. The model is particularly useful whenever multiple, sparsely sampled realizations of the
random field are available, and is clearly favourable to the Gaussian model in this case. The properties of the T-distributed random field model is demonstrated on well log observations from the Gullfaks field in the North Sea. The predictions
correspond to traditional kriging predictions, while the associated prediction variances are more representative, as they
are layer specific and include uncertainty caused by using variance estimates. 相似文献
The present work provides a new methodology to determine onset dates of the rainy season (ONR) in central Amazon (CAM) using the antisymmetric in relation to the equator outgoing longwave radiation (OLR) (AOLR) data, for the 1979–2006 period. Spatial averages of the AOLR ($\overline {AOLR} $) over the CAM for the ONR periods are obtained. These periods correspond to 25 pentads centered on the mean pentad for the ONR. The sign changes from positive to negative of the $\overline {AOLR} $ for the ONR periods indicate the transition from dry to wet season. Composites of several variables are done for pentads before and after the ONR dates. These composites show physically consistent features. The potential of the $\overline {AOLR} $ time series as an index for monitoring tasks is analyzed. The results here show that the $\overline {AOLR} $ for the ONR period captures the transition from dry to wet conditions in the CAM area during 2006. The advantages of this method are discussed. The new simple method proposed here seems to be efficient in determining the ONR in the CAM. 相似文献