A logical foundation for the case‐based reasoning cycle

Case‐based reasoning (CBR) has drawn considerable attention in artificial intelligence (AI) fields with many successful applications in systems such as e‐commerce and multiagent systems. For the moment, research and development of CBR basically follows the traditional process model of CBR, i.e., the R⁴ model and problem space model introduced in 1994 and 1996, respectively. However, there has been no logical analysis for this popular CBR model. This article will fill this gap by providing a unified logical foundation for the CBR cycle. The proposed approach is based on an integration of traditional mathematical logic, fuzzy logic, and similarity‐based reasoning. At the same time, we examine the CBR cycle from the knowledge‐based (KB) viewpoint. The proposed logical approach can facilitate research and development of CBR. © 2003 Wiley Periodicals, Inc.     

Applications of percolation theory to fungal spread with synergy

There is increasing interest in the use of the percolation paradigm to analyse and predict the progress of disease spreading in spatially structured populations of animals and plants. The wider utility of the approach has been limited, however, by several restrictive assumptions, foremost of which is a strict requirement for simple nearest-neighbour transmission, in which the disease history of an individual is influenced only by that of its neighbours. In a recent paper, the percolation paradigm has been generalized to incorporate synergistic interactions in host infectivity and susceptibility, and the impact of these interactions on the invasive dynamics of an epidemic has been demonstrated. In the current paper, we elicit evidence that such synergistic interactions may underlie transmission dynamics in real-world systems by first formulating a model for the spread of a ubiquitous parasitic and saprotrophic fungus through replicated populations of nutrient sites and subsequently fitting and testing the model using data from experimental microcosms. Using Bayesian computational methods for model fitting, we demonstrate that synergistic interactions are necessary to explain the dynamics observed in the replicate experiments. The broader implications of this work in identifying disease-control strategies that deflect epidemics from invasive to non-invasive regimes are discussed.     

Probing the Substrate Promiscuity of Isopentenyl Phosphate Kinase as a Platform for Hemiterpene Analogue Production

Isoprenoids are a large class of natural products with wide-ranging applications. Synthetic biology approaches to the manufacture of isoprenoids and their new-to-nature derivatives are limited due to the provision in nature of just two hemiterpene building blocks for isoprenoid biosynthesis. To address this limitation, artificial chemo-enzymatic pathways such as the alcohol-dependent hemiterpene (ADH) pathway serve to leverage consecutive kinases to convert exogenous alcohols into pyrophosphates that could be coupled to downstream isoprenoid biosynthesis. To be successful, each kinase in this pathway should be permissive of a broad range of substrates. For the first time, we have probed the promiscuity of the second enzyme in the ADH pathway—isopentenyl phosphate kinase from Thermoplasma acidophilum—towards a broad range of acceptor monophosphates. Subsequently, we evaluate the suitability of this enzyme to provide unnatural pyrophosphates and provide a critical first step in characterizing the rate-limiting steps in the artificial ADH pathway.     

Accuracy and optimal sampling in Monte Carlo solution of population balance equations

Implementation of a Monte Carlo simulation for the solution of population balance equations (PBEs) requires choice of initial sample number (N₀), number of replicates (M), and number of bins for probability distribution reconstruction (n). It is found that Squared Hellinger Distance, H², is a useful measurement of the accuracy of Monte Carlo (MC) simulation, and can be related directly to N₀, M, and n. Asymptotic approximations of H² are deduced and tested for both one‐dimensional (1‐D) and 2‐D PBEs with coalescence. The central processing unit (CPU) cost, C, is found in a power‐law relationship, , with the CPU cost index, b, indicating the weighting of N₀ in the total CPU cost. n must be chosen to balance accuracy and resolution. For fixed n, M × N₀ determines the accuracy of MC prediction; if b > 1, then the optimal solution strategy uses multiple replications and small sample size. Conversely, if 0 < b < 1, one replicate and a large initial sample size is preferred. © 2015 American Institute of Chemical Engineers AIChE J, 61: 2394–2402, 2015     

Australia,uranium and nuclear power

The nuclear debate in Australia is shaped by the nation's substantial base of energy resources, including its large reserves of uranium and recent rises in the market price of uranium. But the debate also echoes Australia's past in the development of programs for nuclear weapons. The proposals include uranium enrichment, the storage of nuclear waste in Australia, and the introduction of nuclear reactors. A national inquiry has been instituted by the government. These developments, stemming from a range of factors, have revived the opposition to uranium mining and nuclear power which has for two decades held a dominant role in Australian politics. The issue of what should be Australia's energy path in a time of climate change is beginning to be examined. The importance of the decisions, whether to be a player in the nuclear club with its attendant multiple hazards, or to play a quite different leadership role in the development and adoption of sustainable energy strategies and technologies, cannot be exaggerated.     

Long-Run Trends in Victorian Housing Affordability and First Transition into Homeownership

Over the past two decades housing pathways have become increasingly differentiated between generations, particularly in advanced societies dominated by owner-occupied tenure systems. Demographic transformations caused by aging and falling fertility rates, along with a more volatile economy and a neo-liberal reorientation of governance have combined to restructure housing conditions. Drawing on empirical research in Japan, this paper illustrates the social origins and impact of generation-based differentiations in housing patterns in that country. It considers the housing experiences of three cohorts: baby-boomers, baby-busters and the ‘lost generation’. The contrast of housing pathways between these generations in Japan illustrates the contemporary dynamics of housing and social processes in homeowner societies.     

Self Organising Maps for variable selection: Application to human saliva analysed by nuclear magnetic resonance spectroscopy to investigate the effect of an oral healthcare product

SOMs (Self Organising Maps) are derived from the machine learning literature and serve as a valuable method for representing data. In this paper, the use of SOMs as a technique for determining the most significant variables (or markers) in a dataset is described. The method is applied to the NMR spectra of 96 human saliva samples, half of which have been treated with an oral rinse formulation and half of which are controls, and 49 variables consisting of bucketed intensities. In addition, three simulations, two of which consist of the same number of samples and variables as the experimental dataset and a third that contains a much larger number of variables, are described. Two of the simulations contain known discriminatory variables, and the remaining is treated as a null dataset without any specific discriminatory variables added. The described SOM method is contrasted to Partial Least Squares Discriminant Analysis, and a list of the markers determined to be most significant using both approaches was obtained and the differences arising are discussed. A SOM Discrimination Index (SOMDI) is defined, whose magnitude relates to how strongly a variable is considered to be a discriminator. In order to ensure that the model is stable and not dependent on the random starting point of the SOM, one hundred iterations were performed and variables that were consistently of high rank were selected. A variety of approaches for data representation are illustrated, and the main theoretical principles of employing SOMs for determining which variables are most significant are outlined. Software used in this paper was written in-house, allowing greater flexibility over existing packages, and tailored for the specific application in hand.