Linear models of simple cells: Correspondence to real cell responses and space spanning properties

Despite their limitations, linear filter models continue to be used to simulate the receptive field properties of cortical simple cells. For theoreticians interested in large scale models of visual cortex, a family of self-similar filters represents a convenient way in which to characterise simple cells in one basic model. This paper reviews research on the suitability of such models, and goes on to advance biologically motivated reasons for adopting a particular group of models in preference to all others. In particular, the paper describes why the Gabor model, so often used in network simulations, should be dropped in favour of a Cauchy model, both on the grounds of frequency response and mutual filter orthogonality.

Addressing shortcomings in the Household Responsibility System - Empirical analysis of the Two-Farmland System in Shandong Province

Despite apparent overwhelming benefits, implementation of the Household Responsibility System (HRS) in China contained a number of flaws. The Two-Farmland System (TFS), which originated in Pingdu City in Shandong Province, sought to address the twin problems of land fragmentation and economies of size. A stochastic frontier production function analysis that isolates the impacts of land allocation reforms suggests that the TFS increased efficiency by around 7%. This article highlights the need for empirical analysis to assess objectively the merits or otherwise of particular reforms. (C) 2002 Elsevier Science Inc. All rights reserved.

How should pathogen transmission be modelled?

Host-pathogen models are essential for designing strategies for managing disease threats to humans, wild animals and domestic animals. The behaviour of these models is greatly affected by the way in which transmission between infected and susceptible hosts is modelled. Since host-pathogen models were first developed at the beginning of the 20th century, the 'mass action' assumption has almost always been used for transmission. Recently, however, it has been suggested that mass action has often been modelled wrongly. Alternative models of transmission are beginning to appear, as are empirical tests of transmission dynamics.

Discrimination of adsorption kinetic models for the description of hydrocarbon adsorption in activated carbon

Five kinetic models for adsorption of hydrocarbons on activated carbon are compared and investigated in this study. These models assume different mass transfer mechanisms within the porous carbon particle. They are: (a) dual pore and surface diffusion (MSD), (b) macropore, surface, and micropore diffusion (MSMD), (c) macropore, surface and finite mass exchange (FK), (d) finite mass exchange (LK), and (e) macropore, micropore diffusion (BM) models. These models are discriminated using the single component kinetic data of ethane and propane as well as the multicomponent kinetics data of their binary mixtures measured on two commercial activated carbon samples (Ajax and Norit) under various conditions. The adsorption energetic heterogeneity is considered for all models to account for the system. It is found that, in general, the models assuming diffusion flux of adsorbed phase along the particle scale give better description of the kinetic data.

Power of the joint segregation analysis method for testing mixed major-gene and polygene inheritance models of quantitative traits

Understanding the genetic architecture of quantitative traits can greatly assist the design of strategies for their manipulation in plant-breeding programs. For a number of traits, genetic variation can be the result of segregation of a few major genes and many polygenes (minor genes). The joint segregation analysis (JSA) is a maximum-likelihood approach for fitting segregation models through the simultaneous use of phenotypic information from multiple generations. Our objective in this paper was to use computer simulation to quantify the power of the JSA method for testing the mixed-inheritance model for quantitative traits when it was applied to the six basic generations: both parents (P-1 and P-2), F-1, F-2, and both backcross generations (B-1 and B-2) derived from crossing the F-1 to each parent. A total of 1968 genetic model-experiment scenarios were considered in the simulation study to quantify the power of the method. Factors that interacted to influence the power of the JSA method to correctly detect genetic models were: (1) whether there were one or two major genes in combination with polygenes, (2) the heritability of the major genes and polygenes, (3) the level of dispersion of the major genes and polygenes between the two parents, and (4) the number of individuals examined in each generation (population size). The greatest levels of power were observed for the genetic models defined with simple inheritance; e.g., the power was greater than 90% for the one major gene model, regardless of the population size and major-gene heritability. Lower levels of power were observed for the genetic models with complex inheritance (major genes and polygenes), low heritability, small population sizes and a large dispersion of favourable genes among the two parents; e.g., the power was less than 5% for the two major-gene model with a heritability value of 0.3 and population sizes of 100 individuals. The JSA methodology was then applied to a previously studied sorghum data-set to investigate the genetic control of the putative drought resistance-trait osmotic adjustment in three crosses. The previous study concluded that there were two major genes segregating for osmotic adjustment in the three crosses. Application of the JSA method resulted in a change in the proposed genetic model. The presence of the two major genes was confirmed with the addition of an unspecified number of polygenes.

Nucleation, growth and breakage phenomena in agitated wet granulation processes: a review

Wet agglomeration processes have traditionally been considered an empirical art, with great difficulties in predicting and explaining observed behaviour. Industry has faced a range of problems including large recycle ratios, poor product quality control, surging and even the total failure of scale up from laboratory to full scale production. However, in recent years there has been a rapid advancement in our understanding of the fundamental processes that control granulation behaviour and product properties. This review critically evaluates the current understanding of the three key areas of wet granulation processes: wetting and nucleation, consolidation and growth, and breakage and attrition. Particular emphasis is placed on the fact that there now exist theoretical models which predict or explain the majority of experimentally observed behaviour. Provided that the correct material properties and operating parameters are known, it is now possible to make useful predictions about how a material will granulate. The challenge that now faces us is to transfer these theoretical developments into industrial practice. Standard, reliable methods need to be developed to measure the formulation properties that control granulation behaviour, such as contact angle and dynamic yield strength. There also needs to be a better understanding of the flow patterns, mixing behaviour and impact velocities in different types of granulation equipment. (C) 2001 Elsevier Science B.V. All rights reserved.

Immune responses to ISCOM (R) formulations in animal and primate models

ISCOMs(R) are typically 40 nm cage-like structures comprising antigen, saponin, cholesterol and phospholipid. ISCOMs(R) have been shown to induce antibody responses and activate T helper cells and cyrolytic T lymphocytes in a number of animal species, including non-human primates. Recent clinical studies have demonstrated that ISCOMs(R) are also able to induce antibody and cellular immune responses in humans. This review describes the current understanding of the ability of ISCOMs(R) to induce immune responses and the mechanisms underlying this property. Recent progress in the characterisation and manufacture of ISCOMs(R) will also be discussed. (C) 2001 Elsevier Science Ltd. All rights reserved.

Hemoglobin-degrading, aspartic proteases of blood-feeding parasites - Substrate specificity revealed by homology models

Blood-feeding parasites, including schistosomes, hookworms, and malaria parasites, employ aspartic proteases to make initial or early cleavages in ingested host hemoglobin. To better understand the substrate affinity of these aspartic proteases, sequences were aligned with and/or three-dimensional, molecular models were constructed of the cathepsin D-like aspartic proteases of schistosomes and hookworms and of plasmepsins of Plasmodium falciparum and Plasmodium vivax, using the structure of human cathepsin D bound to the inhibitor pepstatin as the template. The catalytic subsites S5 through S4' were determined for the modeled parasite proteases. Subsequently, the crystal structure of mouse renin complexed with the nonapeptidyl inhibitor t-butyl-CO-His-Pro-Phe-His-Leu [CHOHCH2]Leu-Tyr-Tyr-Ser-NH2 (CH-66) was used to build homology models of the hemoglobin-degrading peptidases docked with a series of octapeptide substrates. The modeled octapeptides included representative sites in hemoglobin known to be cleaved by both Schistosoma japonicum cathepsin D and human cathepsin D, as well as sites cleaved by one but not the other of these enzymes. The peptidase-octapeptide substrate models revealed that differences in cleavage sites were generally attributable to the influence of a single amino acid change among the P5 to P4' residues that would either enhance or diminish the enzymatic affinity. The difference in cleavage sites appeared to be more profound than might be expected from sequence differences in the enzymes and hemoglobins. The findings support the notion that selective inhibitors of the hemoglobin-degrading peptidases of blood-feeding parasites at large could be developed as novel anti-parasitic agents.

The plausibility of long-wavelength stress correlation or stress magnitude as a mechanism for precursory seismicity: Results from two simple elastic models

Observations of accelerating seismic activity prior to large earthquakes in natural fault systems have raised hopes for intermediate-term eartquake forecasting. If this phenomena does exist, then what causes it to occur? Recent theoretical work suggests that the accelerating seismic release sequence is a symptom of increasing long-wavelength stress correlation in the fault region. A more traditional explanation, based on Reid's elastic rebound theory, argues that an accelerating sequence of seismic energy release could be a consequence of increasing stress in a fault system whose stress moment release is dominated by large events. Both of these theories are examined using two discrete models of seismicity: a Burridge-Knopoff block-slider model and an elastic continuum based model. Both models display an accelerating release of seismic energy prior to large simulated earthquakes. In both models there is a correlation between the rate of seismic energy release with the total root-mean-squared stress and the level of long-wavelength stress correlation. Furthermore, both models exhibit a systematic increase in the number of large events at high stress and high long-wavelength stress correlation levels. These results suggest that either explanation is plausible for the accelerating moment release in the models examined. A statistical model based on the Burridge-Knopoff block-slider is constructed which indicates that stress alone is sufficient to produce accelerating release of seismic energy with time prior to a large earthquake.

An aggregate sales model for consumer durables incorporating a time-varying mean replacement age

Forecasting category or industry sales is a vital component of a company's planning and control activities. Sales for most mature durable product categories are dominated by replacement purchases. Previous sales models which explicitly incorporate a component of sales due to replacement assume there is an age distribution for replacements of existing units which remains constant over time. However, there is evidence that changes in factors such as product reliability/durability, price, repair costs, scrapping values, styling and economic conditions will result in changes in the mean replacement age of units. This paper develops a model for such time-varying replacement behaviour and empirically tests it in the Australian automotive industry. Both longitudinal census data and the empirical analysis of the replacement sales model confirm that there has been a substantial increase in the average aggregate replacement age for motor vehicles over the past 20 years. Further, much of this variation could be explained by real price increases and a linear temporal trend. Consequently, the time-varying model significantly outperformed previous models both in terms of fitting and forecasting the sales data. Copyright (C) 2001 John Wiley & Sons, Ltd.