Протеом липопротеинов высокой плотности

БЕЛКИЛИПОПРОТЕИНЫ, ЛВППРОТЕО

Extension of the Measurement Capabilities of the Quadrupole Resonator

The Quadrupole Resonator, designed to measure the surface resistance of superconducting samples at 400 MHz has been refurbished. The accuracy of its RF-DC compensation measurement technique is tested by an independent method. It is shown that the device enables also measurements at 800 and 1200 MHz and is capable to probe the critical RF magnetic field. The electric and magnetic field configuration of the Quadrupole Resonator are dependent on the excited mode. It is shown how this can be used to distinguish between electric and magnetic losses.Comment: 6 pages, g figure

Linking Physics and Algorithms in the Random-Field Ising Model

The energy landscape for the random-field Ising model (RFIM) is complex, yet algorithms such as the push-relabel algorithm exist for computing the exact ground state of an RFIM sample in time polynomial in the sample volume. Simulations were carried out to investigate the scaling properties of the push-relabel algorithm. The time evolution of the algorithm was studied along with the statistics of an auxiliary potential field. At very small random fields, the algorithm dynamics are closely related to the dynamics of two-species annihilation, consistent with fractal statistics for the distribution of minima in the potential (``height\u27\u27). For $d=1,2$, a correlation length diverging at zero disorder sets a cutoff scale for the magnitude of the height field; our results are most consistent with a power-law correction to the exponential scaling of the correlation length with disorder in $d=2$. Near the ferromagnetic-paramagnetic transition in $d=3$, the time to find a solution diverges with a dynamic critical exponent of $z=0.93\pm0.06$ for a priority queue version and $z=0.43\pm0.06$ for a first-in first-out queue version of the algorithm. The links between the evolution of auxiliary fields in algorithmic time and the static physical properties of the RFIM ground state provide insight into the physics of the RFIM and a better understanding of how the algorithm functions

Isotropic-medium three-dimensional cloaks for acoustic and electromagnetic waves

We propose a generalization of the two-dimensional eikonal-limit cloak derived from a conformal transformation to three dimensions. The proposed cloak is a spherical shell composed of only isotropic media; it operates in the transmission mode and requires no mirror or ground plane. Unlike the well-known omnidirectional spherical cloaks, it may reduce visibility of an arbitrary object only for a very limited range of observation angles. In the short-wavelength limit, this cloaking structure restores not only the trajectories of incident rays, but also their phase, which is a necessary ingredient to complete invisibility. Both scalar-wave (acoustic) and transverse vector-wave (electromagnetic) versions are presented.Comment: 17 pages, 12 figure

Probabilistic methods for seasonal forecasting in a changing climate: Cox-type regression models.

For climate risk management, cumulative distribution functions (CDFs) are an important source of information. They are ideally suited to compare probabilistic forecasts of primary (e.g. rainfall) or secondary data (e.g. crop yields). Summarised as CDFs, such forecasts allow an easy quantitative assessment of possible, alternative actions. Although the degree of uncertainty associated with CDF estimation could influence decisions, such information is rarely provided. Hence, we propose Cox-type regression models (CRMs) as a statistical framework for making inferences on CDFs in climate science. CRMs were designed for modelling probability distributions rather than just mean or median values. This makes the approach appealing for risk assessments where probabilities of extremes are often more informative than central tendency measures. CRMs are semi-parametric approaches originally designed for modelling risks arising from time-to-event data. Here we extend this original concept beyond time-dependent measures to other variables of interest. We also provide tools for estimating CDFs and surrounding uncertainty envelopes from empirical data. These statistical techniques intrinsically account for non-stationarities in time series that might be the result of climate change. This feature makes CRMs attractive candidates to investigate the feasibility of developing rigorous global circulation model (GCM)-CRM interfaces for provision of user-relevant forecasts. To demonstrate the applicability of CRMs, we present two examples for El Ni ? no/Southern Oscillation (ENSO)-based forecasts: the onset date of the wet season (Cairns, Australia) and total wet season rainfall (Quixeramobim, Brazil). This study emphasises the methodological aspects of CRMs rather than discussing merits or limitations of the ENSO-based predictors

Event frequency and severity of sorghum ergot in Australia

The temporal and regional distribution of the severity and potential number of events of sorghum ergot on grain sorghum in Australia were analysed using daily climatic data from 1957 to 1998. This analysis was conducted using both a rule-based method and a regression model. Between December and March, the main flowering period for most commercial grain sorghum crops, we found a likely increase of ergot events in eastern Australia from south to north as well as from west to east. When crops flowered in April or May the number of potential monthly events increased, particularly in the southern areas. The smallest number of events occurred when flowering occurred between September and December. The temporal and geographic distribution of the number of events and severity of sorghum ergot is closely related to relative humidity during the flowering period. The analysis indicates that grain sorghum crops flowering between early December and February are unlikely to be severely infected with sorghum ergot. Late flowering sorghum has increased risk to severe infection, especially in the coastal regions