Capillary network models for transport in packed beds: Considerations of pore aspect ratio

The conventional analysis for the estimation of the tortuosity factor for transport in porous media is modified here to account for the effect of pore aspect ratio. Structural models of the porous medium are also constructed for calculating the aspect ratio as a function of porosity. Comparison of the model predictions with the extensive data of Currie (1960) for the effective diffusivity of hydrogen in packed beds shows good agreement with a network model of randomly oriented intersecting pores for porosities upto about 50 percent, which is the region of practical interest. The predictions based on this network model are also found to be in better agreement with the data of Currie than earlier expressions developed for unconsolidated and grainy media.

Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network

Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.

Relationship between peptide selectivities of human transporters associated with antigen processing and HLA class I molecules

Efficiency of presentation of a peptide epitope by a MHC class I molecule depends on two parameters: its binding to the MHC molecule and its generation by intracellular Ag processing. In contrast to the former parameter, the mechanisms underlying peptide selection in Ag processing are poorly understood. Peptide translocation by the TAP transporter is required for presentation of most epitopes and may modulate peptide supply to MHC class I molecules. To study the role of human TAP for peptide presentation by individual HLA class I molecules, we generated artificial neural networks capable of predicting the affinity of TAP for random sequence 9-mer peptides. Using neural network-based predictions of TAP affinity, we found that peptides eluted from three different HLA class I molecules had higher TAP affinities than control peptides with equal binding affinities for the same HLA class I molecules, suggesting that human TAP may contribute to epitope selection. In simulated TAP binding experiments with 408 HLA class I binding peptides, HLA class I molecules differed significantly with respect to TAP affinities of their ligands, As a result, some class I molecules, especially HLA-B27, may be particularly efficient in presentation of cytosolic peptides with low concentrations, while most class I molecules may predominantly present abundant cytosolic peptides.

Modeling the fluid-flow-induced stress and collapse in a dendritic network

An analytical approach to the stress development in the coherent dendritic network during solidification is proposed. Under the assumption that stresses are developed in the network as a result of the friction resisting shrinkage-induced interdendritic fluid flow, the model predicts the stresses in the solid. The calculations reflect the expected effects of postponed dendrite coherency, slower solidification conditions, and variations of eutectic volume fraction and shrinkage. Comparing the calculated stresses to the measured shear strength of equiaxed mushy zones shows that it is possible for the stresses to exceed the strength, thereby resulting in reorientation or collapse of the dendritic network.

Control of fed-batch fermentations

Fed-batch fermentation is used to prevent or reduce substrate-associated growth inhibition by controlling nutrient supply. Here we review the advances in control of fed-batch fermentations. Simple exponential feeding and inferential methods are examined, as are newer methods based on fuzzy control and neural networks. Considerable interest has developed in these more advanced methods that hold promise for optimizing fed-batch techniques for complex fermentation systems. (C) 1999 Elsevier Science Inc. All rights reserved.

Molecular cloning and chromosomal mapping of the human homologue of MYB binding protein (P160) 1A (MYBBP1A) to 17p13.3

We have previously isolated and characterized murine MYB binding protein (p160) 1a, a protein that specifically interacts with the leucine zipper motif within the negative regulatory domain of the c-Myb proto-oncoprotein, We now describe the molecular cloning of the human MYBBP1A cDNA and chromosomal localization to 17p13.3 by fluorescence in situ hybridization analysis, Given the likely presence of a tumor suppressor gene (or genes) within this region of chromosome 17, the position of MYBBP1A was further mapped by radiation hybrid analysis and was found to lie between markers D17S1828 and D17S938. A P1 artificial chromosome clone containing the 5' region of MYBBP1A was isolated and indicates a physical linkage between MYBBP1A and the 15-lipoxygenase gene (ALOX15), A novel, polymorphic (CA)(25) dinucleotide repeat was also isolated from this PAC and may serve as a useful marker for MYBBP1A and this region of chromosome 17. (C) 1999 Academic Press.

Impact of increasing the re-supply interval on the seasonality of subsidised prescription use in Australia

Objective: To evaluate the impact of increasing the minimum resupply period for prescriptions on the Pharmaceutical Benefits Scheme (PBS) in November 1994. The intervention was designed to reduce the stockpiling of medicines used for chronic medical conditions under the PBS safety net. Methods: Interrupted times series regression analyses were performed on 114 months of PBS drug utilisation data from January 1991 to June 2000. These analyses assessed whether there had been a significant interaction between the onset of the intervention in November 1994 and the extreme levels of drug utilisation in the months of December (peak utilisation) and January (lowest utilisation) respectively. Both serial and 12-month lag autocorrelations were controlled for. Results: The onset of the intervention was associated with a significant reduction in the December peak in drug utilisation; after the introduction of the policy there were 1,150,196 fewer proscriptions on average or that month (95% Cl 708,333-1,592,059). There was, however, no significant change in the low level of utilisation in January. The effect of the policy appears to be decreasing across successive postintervention years. though the odds of a prescription being dispensed in December remained significantly lower in 1999 compared to each of the pre-intervention years (11% vs. 14%) Conclusion: Analysis of the impact of increasing the re-supply period for PBS prescriptions showed that the magnitude of peak utilisation in December had been markedly reduced by the policy, though this effect appears to be decreasing over time. Continued monitoring and policy review is warranted in order to ensure that the initial effect of the intervention be maintained.

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.

Ecological interface design for pasteurizer II: A process description of semantic mapping

Ecological interface design (EID) is proving to be a promising approach to the design of interfaces for complex dynamic systems. Although the principles of EID and examples of its effective use are widely available, few readily available examples exist of how the individual displays that constitute an ecological interface are developed. This paper presents the semantic mapping process within EID in the context of prior theoretical work in this area. The semantic mapping process that was used in developing an ecological interface for the Pasteurizer II microworld is outlined, and the results of an evaluation of the ecological interface against a more conventional interface are briefly presented. Subjective reports indicate features of the ecological interface that made it particularly valuable for participants. Finally, we outline the steps of an analytic process for using EID. The findings presented here can be applied in the design of ecological interfaces or of configural displays for dynamic processes.

Inter-subband redundancy prediction using neural network for video coding

High performance video codec is mandatory for multimedia applications such as video-on-demand and video conferencing. Recent research has proposed numerous video coding techniques to meet the requirement in bandwidth, delay, loss and Quality-of-Service (QoS). In this paper, we present our investigations on inter-subband self-similarity within the wavelet-decomposed video frames using neural networks, and study the performance of applying the spatial network model to all video frames over time. The goal of our proposed method is to restore the highest perceptual quality for video transmitted over a highly congested network. Our contributions in this paper are: (1) A new coding model with neural network based, inter-subband redundancy (ISR) prediction for video coding using wavelet (2) The performance of 1D and 2D ISR prediction, including multiple levels of wavelet decompositions. Our result shows a short-term quality enhancement may be obtained using both 1D and 2D ISR prediction.

Image calibration to like-values in mapping shallow water quality from multitemporal data

The applicability of image calibration to like-values in mapping water quality parameters from multitemporal images is explored, Six sets of water samples were collected at satellite overpasses over Moreton Bay, Brisbane, Australia. Analysis of these samples reveals that waters in this shallow bay are mostly TSS-dominated, even though they are occasionally dominated by chlorophyll as well. Three of the images were calibrated to a reference image based on invariant targets. Predictive models constructed from the reference image were applied to estimating total suspended sediment (TSS) and Secchi depth from another image at a discrepancy of around 35 percent. Application of the predictive model for TSS concentration to another image acquired at a time of different water types resulted in a discrepancy of 152 percent. Therefore, image calibration to like-values could be used to reliably map certain water quality parameters from multitemporal TM images so long as the water type under study remains unchanged. This method is limited in that the mapped results could be rather inaccurate if the water type under study has changed considerably. Thus, the approach needs to be refined in shallow water from multitemporal satellite imagery.