Pore structure characterisation of pillared clays using a modified MP method

The data of nitrogen adsorption on pillared clays (PILC) are converted to comparison plots (t-plots) to derive their pore size distribution (PSD). As in the MP method, the surface area of a group of pores having similar pore sizes is calculated from the slopes of tangent lines at two succeeding points on a comparison plot. By the modified MP method in this work, the tangent line is extrapolated to the adsorption axis on the t-plot, and the difference between intercepts is used to obtain the volume of the group of pores. From the information of surface area and pore volume, the average width of the pore group can be calculated and hence the PSDs of PILCs are obtained by carrying out such calculation procedures from high to low t. With this method, PSDs of several pillared clays are calculated over a wide pore size range, from micropores to mesopores. It is found that the modified MP method could result in the underestimation of the width of ultramicropores due to the enhancement in adsorption energy in these pores. Nevertheless, the method can be very useful in calculating the surface area and pore volume, as well as a mean width of these pores. For super-micropores and mesopores, pore size can also be underestimated, due to deviation of the pore shape from a slit. The principles of the improved MP method, as well as problems associated with it are thoroughly discussed in this paper. In general, this modified method provides practically meaningful results which are consistent with the pore dimension obtained from powder X-ray diffraction measurements, but involves no complicated theoretical treatment or assumptions.

Robust algorithms for solving stochastic partial differential equations

A robust semi-implicit central partial difference algorithm for the numerical solution of coupled stochastic parabolic partial differential equations (PDEs) is described. This can be used for calculating correlation functions of systems of interacting stochastic fields. Such field equations can arise in the description of Hamiltonian and open systems in the physics of nonlinear processes, and may include multiplicative noise sources. The algorithm can be used for studying the properties of nonlinear quantum or classical field theories. The general approach is outlined and applied to a specific example, namely the quantum statistical fluctuations of ultra-short optical pulses in chi((2)) parametric waveguides. This example uses a non-diagonal coherent state representation, and correctly predicts the sub-shot noise level spectral fluctuations observed in homodyne detection measurements. It is expected that the methods used wilt be applicable for higher-order correlation functions and other physical problems as well. A stochastic differencing technique for reducing sampling errors is also introduced. This involves solving nonlinear stochastic parabolic PDEs in combination with a reference process, which uses the Wigner representation in the example presented here. A computer implementation on MIMD parallel architectures is discussed. (C) 1997 Academic Press.

Genetic algorithms for continuous optimization problems - a concept of parameter-space size adjustment

The concept of parameter-space size adjustment is pn,posed in order to enable successful application of genetic algorithms to continuous optimization problems. Performance of genetic algorithms with six different combinations of selection and reproduction mechanisms, with and without parameter-space size adjustment, were severely tested on eleven multiminima test functions. An algorithm with the best performance was employed for the determination of the model parameters of the optical constants of Pt, Ni and Cr.

Concurreny based transition refinement for the verification of distributed algorithms

We suggest a new notion of behaviour preserving transition refinement based on partial order semantics. This notion is called transition refinement. We introduced transition refinement for elementary (low-level) Petri Nets earlier. For modelling and verifying complex distributed algorithms, high-level (Algebraic) Petri nets are usually used. In this paper, we define transition refinement for Algebraic Petri Nets. This notion is more powerful than transition refinement for elementary Petri nets because it corresponds to the simultaneous refinement of several transitions in an elementary Petri net. Transition refinement is particularly suitable for refinement steps that increase the degree of distribution of an algorithm, e.g. when synchronous communication is replaced by asynchronous message passing. We study how to prove that a replacement of a transition is a transition refinement.

Robust parameter settings of evolutionary algorithms for the optimisation of agricultural systems models

Numerical optimisation methods are being more commonly applied to agricultural systems models, to identify the most profitable management strategies. The available optimisation algorithms are reviewed and compared, with literature and our studies identifying evolutionary algorithms (including genetic algorithms) as superior in this regard to simulated annealing, tabu search, hill-climbing, and direct-search methods. Results of a complex beef property optimisation, using a real-value genetic algorithm, are presented. The relative contributions of the range of operational options and parameters of this method are discussed, and general recommendations listed to assist practitioners applying evolutionary algorithms to the solution of agricultural systems. (C) 2001 Elsevier Science Ltd. All rights reserved.

Increase of fat oxidation and weight loss in obese mice caused by chronic treatment with human growth hormone or a modified C-terminal fragment

OBJECTIVE: To observe the chronic effects of human growth hormone (hGH) and AOD9604 (a C-terminal fragment of hGH) on body weight, energy balance, and substrate oxidation rates in obese (ob/ob) and lean C57BL/6Jmice. In vitro assays were used to confirm whether the effects of AOD9604 are mediated through the hGH receptor, and if this peptide is capable of cell proliferation via the hGH receptor. METHOD: Obese and lean mice were treated with hGH, AOD or saline for 14 days using mini-osmotic pumps. Body weight, caloric intake, resting energy expenditure, fat oxidation, glucose oxidation, and plasma glucose, insulin and glycerol were measured before and after treatment. BaF-BO3 cells transfected with the hGH receptor were used to measure in Vitro I-125-hGH receptor binding and cell proliferation. RESULTS: Both hGH and AOD significantly reduced body weight gain in obese mice. This was associated with increased in vivo fat oxidation and increased plasma glycerol levels (an index of lipolysis). Unlike hGH, however, AOD9604 did not induce hyperglycaemia or reduce insulin secretion. AOD9604 does not compete for the hGH receptor and nor does it induce cell proliferation, unlike hGH. CONCLUSIONS: Both hGH and its C-terminal fragment reduce body weight gain, increase fat oxidation, and stimulate lipolysis in obese mice, yet AOD9604 does not interact with the hGH receptor. Thus, the concept of hGH behaving as a pro-hormone is further confirmed. This data shows that fragments of hGH can act in a manner novel to traditional hGH-stimulated pathways.