Percolative fragmentation of char particles during gasification

Percolative fragmentation was confirmed to occur during gasification of three microporous coal chars. Indirect evidence obtained by the variation of electrical resistivity (ER) with conversion was supported by direct observation of numerous fragments during gasification. The resistivity increases slowly at low conversions and then sharply after a certain conversion value, which is a typical percolation phenomenon suggesting the occurrence of internal fragmentation at high conversion. Two percolation models are applied to interpret the experimental data and determine the percolation threshold. A percolation threshold of 0.02-0.07 was found, corresponding to a critical conversion of 92-96% for fragmentation. The electrical resistivity variation at high conversions is found to be very sensitive to diffusional effects during gasification. Partially burnt samples with a narrow initial particle size range were also observed microscopically, and found to yield a large number of small fragments even when the particles showed no disintegration and chemical control prevailed. It is proposed that this is due to the separation of isolated clusters from the particle surface. The particle size distribution of the fragments was essentially independent of the reaction conditions and the char type, and supported the prediction by percolation theory that the number fraction distribution varies linearly with mass in a log-log plot. The results imply that perimeter fragmentation would occur in practical combustion systems in which the reactions are strongly diffusion affected.

The clinical value compass: Achieving benchmarking and quality improvement in aged care

Quality measurement and benchmarking in aged cave presents several challenges. A model which addresses this by linking four dimensions of outcomes has been developed - the Clinical Value Compass (CVC). A CVC was developed for stroke rehabilitation and measured across four sites. The CVC teas well accepted by the treatment teams and proved practical to measure. The results revealed differences in practices and client groups that led to a closer analysis of process and subsequent changes in these processes. Remeasuring of the CVC is required to demonstrate improved outcomes arising from these process changes.

Long range forecasts of the numbers of Helicoverpa punctigera and H-armigera (Lepidoptera : Noctuidae) in Australia using the Southern Oscillation Index and the Sea Surface Temperature

The use of long-term forecasts of pest pressure is central to better pest management. We relate the Southern Oscillation Index (SOI) and the Sea Surface Temperature (SST) to long-term light-trap catches of the two key moth pests of Australian agriculture, Helicoverpa punctigera (Wallengren) and H. armigera (Hubner), at Narrabri, New South Wales over 11 years, and for H. punctigera only at Turretfield, South Australia over 22 years. At Narrabri, the size of the first spring generation of both species was significantly correlated with the SOI in certain months, sometimes up to 15 months before the date of trapping. Differences in the SOI and SST between significant months were used to build composite variables in multiple regressions which gave fitted values of the trap catches to less than 25% of the observed values. The regressions suggested that useful forecasts of both species could be made 6-15 months ahead. The influence of the two weather variables on trap catches of H. punctigera at Turretfield were not as strong as at Narrabri, probably because the SOI was not as strongly related to rainfall in southern Australia as it is in eastern Australia. The best fits were again given by multiple regressions with SOI plus SST variables, to within 40% of the observed values. The reliability of both variables as predictors of moth numbers may be limited by the lack of stability in the SOI-rainfall correlation over the historical record. As no other data set is available to test the regressions, they can only be tested by future use. The use of long-term forecasts in pest management is discussed, and preliminary analyses of other long sets of insect numbers suggest that the Southern Oscillation Index may be a useful predictor of insect numbers in other parts of the world.

Evaluation of a new bioelectrical impedance instrument for the prediction of body cell mass independently of height or weight

The objective of the present study was to evaluate the performance of a new bioelectrical impedance instrument, the Soft Tissue Analyzer (STA), which predicts a subject's body composition. A cross-sectional population study in which the impedance of 205 healthy adult subjects was measured using the STA. Extracellular water (ECW) volume (as a percentage of total body water, TBW) and fat-free mass (FFM) were predicted by both the STA and a compartmental model, and compared according to correlation and limits of agreement analysis, with the equivalent data obtained by independent reference methods of measurement (TBW measured by D2O dilution, and FFM measured by dual-energy X-ray absorptiometry). There was a small (2.0 kg) but significant (P < 0.02) difference in mean FFM predicted by the STA, compared with the reference technique in the males, but not in the females (-0.4 kg) or in the combined group (0.8 kg). Both methods were highly correlated. Similarly, small but significant differences for predicted mean ECW volume were observed. The limits of agreement for FFM and ECW were -7.5-9.9 and -4.1-3.0 kg, respectively. Both FFM and ECW (as a percentage of TBW) are well predicted by the STA on a population basis, but the magnitude of the limits of agreement with reference methods may preclude its usefulness for predicting body composition in an individual. In addition, the theoretical basis of an impedance method that does not include a measure of conductor length requires further validation. (C) Elsevier Science Inc. 2000.

Soil carbon determination by high temperature combustion - A comparison with dichromate oxidation procedures and the influence of charcoal and carbonate carbon on the measured value

The measurement of organic carbon in soils has traditionally used dichromate oxidation procedures including the Wakley and Black and the Heanes methods. The measurement of carbon in soils by high temperature combustion is now widely used providing a rapid automated procedure without the use of toxic chemicals. This procedure however measures total carbon thus requiring some means of correction for soil samples containing carbonate and charcoal forms of carbon. This paper examines the effects of known additions of charcoal to a range of soil types on the results obtained by the Walkley and Black, Heanes and combustion methods. The results show, that while the charcoal carbon does not react under Walkley and Black conditions, some proportion does so with the Heanes method. A comparison of six Australian Soil and Plant Analysis Council reference soil samples by the three methods showed good agreement between the Heanes method, the combustion method and only slightly lower recoveries by the Walkley and Black procedure. Carbonate carbon will cause an overestimation of soil organic carbon by the combustion method thus requiring a separate determination of carbonate carbon to be applied as a correction. This work shows that a suitable acid pre-treatment of alkaline soils in the sample boats followed by a drying step eliminates the carbonate carbon prior to combustion and the need for an additional measurement. The measurement of carbon in soils by high temperature combustion in an oxygen atmosphere has been shown to be a rapid and reliable method capable of producing results in good agreement with one of the established dichromate oxidation procedures.

Prediction of rock alteration patterns: a potential tool in mineral exploration

Hydrothermal alteration of a quartz-K-feldspar rock is simulated numerically by coupling fluid flow and chemical reactions. Introduction of CO2 gas generates an acidic fluid and produces secondary quartz, muscovite and/or pyrophyllite at constant temperature and pressure of 300 degrees C and 200 MPa. The precipitation and/or dissolution of the secondary minerals is controlled by either mass-action relations or rate laws. In our simulations the mass of the primary elements are conserved and the mass-balance equations are solved sequentially using an implicit scheme in a finite-element code. The pore-fluid velocity is assumed to be constant. The change of rock volume due to the dissolution or precipitation of the minerals, which is directly related to their molar volume, is taken into account. Feedback into the rock porosity and the reaction rates is included in the model. The model produces zones of pyrophyllite quartz and muscovite due to the dissolution of K-feldspar. Our model simulates, in a simplified way, the acid-induced alteration assemblages observed in various guises in many significant mineral deposits. The particular aluminosilicate minerals produced in these experiments are associated with the gold deposits of the Witwatersrand Basin.

The role of cognitive vulnerability and stress in the prediction of postpartum depressive symptomatology

Objectives. The present study was designed to test the diathesis-stress components of Beck's cognitive theory of depression and the reformulated learned helplessness model of depression in the prediction of postpartum depressive symptomatology. Design and methods. The research used a two-wave longitudinal design-data were collected from 65 primiparous women during their third trimester of pregnancy and then 6 weeks after the birth. Cognitive vulnerability and initial depressive symptomatology were assessed at Time 1, whereas stress and postpartum depressive symptomatology were assessed at Time 2. Results. There was some support for the diathesis-stress component of Beck's cognitive theory, to the extent that the negative relationship between both general and maternal-specific dysfunctional attitudes associated with performance evaluation and Time 2 depressive symptomatology was strongest for women who reported high levels of parental stress. In a similar vein, the effects of dysfunctional attitudes (general and maternal-specific) associated with performance evaluation and need for approval (general measure only) on partner ratings of emotional distress were evident only among those women whose infants were rated as being temperamentally difficult. Conclusion. There was no support for the diathesis-stress component of the reformulated learned helplessness model of depression; however, there was some support for the diathesis-stress component of Beck's cognitive theory.

An object-oriented neural network approach to short-term traffic forecasting

This paper discusses an object-oriented neural network model that was developed for predicting short-term traffic conditions on a section of the Pacific Highway between Brisbane and the Gold Coast in Queensland, Australia. The feasibility of this approach is demonstrated through a time-lag recurrent network (TLRN) which was developed for predicting speed data up to 15 minutes into the future. The results obtained indicate that the TLRN is capable of predicting speed up to 5 minutes into the future with a high degree of accuracy (90-94%). Similar models, which were developed for predicting freeway travel times on the same facility, were successful in predicting travel times up to 15 minutes into the future with a similar degree of accuracy (93-95%). These results represent substantial improvements on conventional model performance and clearly demonstrate the feasibility of using the object-oriented approach for short-term traffic prediction. (C) 2001 Elsevier Science B.V. All rights reserved.

Stochastic structure and individual-tree growth models

The majority of past and current individual-tree growth modelling methodologies have failed to characterise and incorporate structured stochastic components. Rather, they have relied on deterministic predictions or have added an unstructured random component to predictions. In particular, spatial stochastic structure has been neglected, despite being present in most applications of individual-tree growth models. Spatial stochastic structure (also called spatial dependence or spatial autocorrelation) eventuates when spatial influences such as competition and micro-site effects are not fully captured in models. Temporal stochastic structure (also called temporal dependence or temporal autocorrelation) eventuates when a sequence of measurements is taken on an individual-tree over time, and variables explaining temporal variation in these measurements are not included in the model. Nested stochastic structure eventuates when measurements are combined across sampling units and differences among the sampling units are not fully captured in the model. This review examines spatial, temporal, and nested stochastic structure and instances where each has been characterised in the forest biometry and statistical literature. Methodologies for incorporating stochastic structure in growth model estimation and prediction are described. Benefits from incorporation of stochastic structure include valid statistical inference, improved estimation efficiency, and more realistic and theoretically sound predictions. It is proposed in this review that individual-tree modelling methodologies need to characterise and include structured stochasticity. Possibilities for future research are discussed. (C) 2001 Elsevier Science B.V. All rights reserved.

Prediction of promiscuous peptides that bind HLA class I molecules

Promiscuous T-cell epitopes make ideal targets for vaccine development. We report here a computational system, multipred, for the prediction of peptide binding to the HLA-A2 supertype. It combines a novel representation of peptide/MHC interactions with a hidden Markov model as the prediction algorithm. multipred is both sensitive and specific, and demonstrates high accuracy of peptide-binding predictions for HLA-A*0201, *0204, and *0205 alleles, good accuracy for *0206 allele, and marginal accuracy for *0203 allele. multipred replaces earlier requirements for individual prediction models for each HLA allelic variant and simplifies computational aspects of peptide-binding prediction. Preliminary testing indicates that multipred can predict peptide binding to HLA-A2 supertype molecules with high accuracy, including those allelic variants for which no experimental binding data are currently available.

Methods for prediction of peptide binding to MHC molecules: A comparative study

Background: A variety of methods for prediction of peptide binding to major histocompatibility complex (MHC) have been proposed. These methods are based on binding motifs, binding matrices, hidden Markov models (HMM), or artificial neural networks (ANN). There has been little prior work on the comparative analysis of these methods. Materials and Methods: We performed a comparison of the performance of six methods applied to the prediction of two human MHC class I molecules, including binding matrices and motifs, ANNs, and HMMs. Results: The selection of the optimal prediction method depends on the amount of available data (the number of peptides of known binding affinity to the MHC molecule of interest), the biases in the data set and the intended purpose of the prediction (screening of a single protein versus mass screening). When little or no peptide data are available, binding motifs are the most useful alternative to random guessing or use of a complete overlapping set of peptides for selection of candidate binders. As the number of known peptide binders increases, binding matrices and HMM become more useful predictors. ANN and HMM are the predictive methods of choice for MHC alleles with more than 100 known binding peptides. Conclusion: The ability of bioinformatic methods to reliably predict MHC binding peptides, and thereby potential T-cell epitopes, has major implications for clinical immunology, particularly in the area of vaccine design.

Effects of alkalis, oxidants and urea on the nutritive value of rhodes grass (Chloris gayana cv. Callide)

Two in sacco experiments were conducted to evaluate the impact on the nutritive value of rhodes grass hay (Chloris gayana cv. Callide) of treatment with alkalis or oxidants. In Experiment 1, three alkalis (Ca(OH)(2), NaOH, CaO) and two oxidants (NaOCl and H2O2) were applied at levels of 0, 20, 40, 60 or 80 g/kg of dry matter (DM). NaOH, Ca(OH)(2) and CaO had negative linear effects (P < 0.05) on the neutral detergent fibre (NDF) content and positive linear effects (P < 0.05) on the 48 h in sacco disappearances of DM, organic matter (OM), NDF and acid detergent fibre (ADF). NaOCl reduced (P < 0.05) NDF content but had no effect (P > 0.05) on the in sacco disappearances. H2O2 had no effect (P > 0.05) on the composition or digestibility of rhodes grass hay. In Experiment 2, effects of urea (0, 20, 40, 60 and 80 g urea/kg DM) and water (250, 500 and 750 g/kg DM) treatment of rhodes grass hay were examined in a 5 x 3 factorial experiment. Significant interactions between water and urea (P < 0.05) occurred for concentrations of crude protein (CP) and NDF, and 48 h in sacco disappearances of DM, OM (OMD) and NDE The combinations of water (g/kg DM) and urea (g/kg DM) that resulted in the highest concentrations of CP (281 g/kg DM) and OMD (747 g/kg DM) were 250 + 80 and 500 + 80, respectively. NaOH, Ca(OH)(2), CaO and urea significantly alter the NDF content and digestibility of rhodes grass hay, and urea also increases its CP content. Overall, NaOH was the most efficacious, followed by Ca(OH)(2), CaO, urea, NaOCl and H2O2. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.