Growth hormone-binding protein in normal and pathologic gestation: Correlations with maternal diabetes and fetal growth

To date, measurements of GH-binding protein (GHBP) during human pregnancy have been carried out using;assays susceptible to interference by the elevated levels of human placental GH typical of late gestation. We recruited a large cohort of pregnant women (n = 140) for serial measurements of GHBP and used the ligand immunofunctional assay for GHBP. For normal gravidas, GHBP levels fell throughout gestation. Mean levels were 1.07 nmol/L (SE = 0.18) in the first trimester, 0.90 nmol/L (SE = 0.08) at 18-20 weeks, 0.73 nmol/L (SE = 0.05) at 28-30 weeks, and 0.62 nmol/L (SE = 0.06) at 36-38 weeks. GHBP levels in the first trimester correlated significantly with maternal body mass index (r = 0.58; P < 0.01). GHBP levels in pregnancies complicated by noninsulin-dependent diabetes mellitus (NIDDM) were substantially elevated at all gestational ages. The mean value in the first quarter (2.29 nmol/L) was more than double the normal mean (P < 0.01). In contrast, patients with insulin-dependent diabetes mellitus (IDDM) showed reduced GHBP concentrations at 36-38 weeks. The correlation between body mass index and GHBP is consistent with a metabolic role for GHBP during pregnancy, as is the dramatic elevation in GHBP observed in cases of NIDDM. At 36 weeks gestation, GHBP was significantly elevated (P < 0.01) in those women whose neonates had low birth weight (

A continuum model for periodic two-dimensional block structures

A continuum model for regular block structures is derived by replacing the difference quotients of the discrete equations by corresponding differential quotients. The homogenization procedure leads to an anisotropic Cosserat Continuum. For elastic block interactions the dispersion relations of the discrete and the continuous models are derived and compared. Yield criteria for block tilting and sliding are formulated. An extension of the theory for large deformation is proposed. (C) 1997 by John Wiley & Sons, Ltd.

A two-dimensional fuzzy random model of soil pore structure

A new conceptual model for soil pore-solid structure is formalized. Soil pore-solid structure is proposed to comprise spatially abutting elements each with a value which is its membership to the fuzzy set ''pore,'' termed porosity. These values have a range between zero (all solid) and unity (all pore). Images are used to represent structures in which the elements are pixels and the value of each is a porosity. Two-dimensional random fields are generated by allocating each pixel a porosity by independently sampling a statistical distribution. These random fields are reorganized into other pore-solid structural types by selecting parent points which have a specified local region of influence. Pixels of larger or smaller porosity are aggregated about the parent points and within the region of interest by controlled swapping of pixels in the image. This creates local regions of homogeneity within the random field. This is similar to the process known as simulated annealing. The resulting structures are characterized using one-and two-dimensional variograms and functions describing their connectivity. A variety of examples of structures created by the model is presented and compared. Extension to three dimensions presents no theoretical difficulties and is currently under development.

Rapid computation of static fields produced by thick circular solenoids

A straightforward method is proposed for computing the magnetic field produced by a circular coil that contains a large number of turns wound onto a solenoid of rectangular cross section. The coil is thus approximated by a circular ring containing a continuous constant current density, which is very close to the real situation when sire of rectangular cross section is used. All that is required is to evaluate two functions, which are defined as integrals of periodic quantities; this is done accurately and efficiently using trapezoidal-rule quadrature. The solution can be obtained so rapidly that this procedure is ideally suited for use in stochastic optimization, An example is given, in which this approach is combined with a simulated annealing routine to optimize shielded profile coils for NMR.

Optimal quantum trajectories for discrete measurements

Using the method of quantum trajectories we show that a known pure state can be optimally monitored through time when subject to a sequence of discrete measurements. By modifying the way that we extract information from the measurement apparatus we can minimize the average algorithmic information of the measurement record, without changing the unconditional evolution of the measured system. We define an optimal measurement scheme as one which has the lowest average algorithmic information allowed. We also show how it is possible to extract information about system operator averages from the measurement records and their probabilities. The optimal measurement scheme, in the limit of weak coupling, determines the statistics of the variance of the measured variable directly. We discuss the relevance of such measurements for recent experiments in quantum optics.

Anisotropy-based performance analysis of linear discrete time invariant control systems

The anisotropic norm of a linear discrete-time-invariant system measures system output sensitivity to stationary Gaussian input disturbances of bounded mean anisotropy. Mean anisotropy characterizes the degree of predictability (or colouredness) and spatial non-roundness of the noise. The anisotropic norm falls between the H-2 and H-infinity norms and accommodates their loss of performance when the probability structure of input disturbances is not exactly known. This paper develops a method for numerical computation of the anisotropic norm which involves linked Riccati and Lyapunov equations and an associated special type equation.