Conservation of water resources problems of small rivers in Russia

Translated from Gidrotekhnicheskoe Stroitel'stvo, No. 8, pp. 1–5, August, 1994.     

Synthesizing plans that contain actions with context-dependent effects1

This paper presents a method of solving planning problems that involve actions whose effects change according to the situations in which they are performed. The approach is an extension of the conventional planning methodology in which plans are constructed through an iterative process of scanning for goals that are not yet satisfied, inserting actions to achieve them, and introducing subgoals to these actions. This methodology was originally developed under the assumption that one would be dealing exclusively with actions that produce the same effects in every situation. The extension involves introducing additional subgoals to actions above and beyond the preconditions of execution normally introduced. These additional subgoals, called secondary preconditions, ensure that the actions are performed in contexts conducive to producing the effects we desire. This paper defines and analyzes secondary preconditions from a mathematically rigorous standpoint and demonstrates how they can be derived from regression operators.     

A Microscopic study of the transformation of sphalerite particles during the roasting of zinc concentrate

The formation of zinc ferrite (ZnFe₂O₄) during the roasting of iron-bearing zinc concentrates requires substantial additional processing to recover the zinc from this compound by leaching and to eliminate the iron from the leachate. The phase changes that occur in the particles of a typical industrial zinc sulfide concentrate during roasting in a fluidized bed at 1223 K were investigated by the use of light microscopy, electron microprobe analysis, and SEM with EDS. The processes which the iron undergoes during its eventual transformation into ferrite have been clarified by examination of the phases and the morphology of partially roasted marmatitic sphalerite particles (Zn, Fe)S, and by reference to the known phase equilibria involved in the Zn-Fe-S-0 system. The oxidation of ironbearing sphalerite occurs in three stages. The first involves the selective diffusion of most of the iron to the particle surface resulting in the formation of an iron oxide shell enclosing a largely unreacted zinc sulfide kernel. In the second stage, this kernel is oxidized to form a solid solution of zinc oxide and iron oxide. The iron is initially present in the ferrous state but, with the disappearance of the sulfide kernel, is oxidized to ferric iron. In the final stage, this dissolved iron oxide and the iron oxide shell react with the surrounding zinc oxide to form the refractory spinel zinc ferrite.     

Long-term low-dose calcitriol treatment in predialysis chronic renal failure: can it prevent hyperparathyroid bone disease?

In an uncontrolled open study 13 patients with moderate to preterminal renal failure were treated with low doses (average 0.36 micrograms/day) of calcitriol up to the time of renal transplantation, which was performed before dialysis had been initiated. A transiliac bone biopsy was obtained both at the start and at the end of the treatment period, the latter coinciding with renal transplantation. All patients who started calcitriol treatment at a creatinine clearance (Ccr) above 30 ml/min had normal bone histology at the time of transplantation, but this was not observed when calcitriol treatment was started at Ccr below 30 ml/min. The study suggests that full benefit of calcitriol at the bone level is obtained only if prophylactic administration is started early in the course of renal failure.     

Determining hearing threshold from brain stem evoked potentials.Optimizing a neural network to improve classification performance

Feed-forward neural networks in conjunction with back-propagation are an effective tool to automate the classification of biomedical signals. Most of the neural network research to date has been done with a view to accelerate learning speed. In the medical context, however, generalisation may be more important than learning speed. With the brain stem auditory evoked potential classification task described in this study, the authors found that parameter values that gave fastest learning could result in poor generalisation. In order to achieve maximum generalisation, it was necessary to fine tune the neural net for gain, momentum, batch size, and hidden layer size. Although this maximization could be time consuming, especially with larger training sets, the authors' results suggest that fine tuning parameters can have important clinical consequences, which justifies the time involved. In the authors' case, fine tuning parameters for high generalisation had the additional effect of reducing false negative classifications, with only a small sacrifice in learning speed     

Scanning probe microscopy: Materials analysis with an added dimension

Encompassing such versatile analytical techniques as scanning tunneling microscopy and atomic (or scanning) force microscopy, scanning probe microscopes produce high-resolution three-dimensional images. Because of their power as quantitative tools for three-dimensional surface measurement and analysis, the techniques are being used in materials science and engineering for the study of a variety of advanced materials and for investigations into numerous phenomena, including reaction chemistry, crystallinity, kinetics, equilibrium processes, tribology, and conductivity.     

Bioprocess applications of model-based estimation techniques

The last decade has seen the development of a number of approaches for estimating those variables which are difficult to measure on-line in industrial process situations. Whilst a range of techniques is available, a common element is the use of process knowledge in the form of a system model. In the case of bioprocess systems, although a large range of models has been presented in the literature, their use in estimation schemes on an industrial scale has been limited. A number of reasons can be identified for their low level of utilisation. Of particular significance is the uncertainty which exists in quantifying system performance and the process-model mismatch which inevitably results. The level of ‘pre-defined model’ uncertainty, together with the knowledge gained during the course of the fermentation, serves to dictate estimator structure. The paper considers a range of estimation strategies and contrasts, through industrial applications, their performance characteristics and utility.