Efficient algorithms for computing Reeb graphs

The Reeb graph tracks topology changes in level sets of a scalar function and finds applications in scientific visualization and geometric modeling. We describe an algorithm that constructs the Reeb graph of a Morse function defined on a 3-manifold. Our algorithm maintains connected components of the two dimensional levels sets as a dynamic graph and constructs the Reeb graph in O(nlogn+nlogg(loglogg)3) time, where n is the number of triangles in the tetrahedral mesh representing the 3-manifold and g is the maximum genus over all level sets of the function. We extend this algorithm to construct Reeb graphs of d-manifolds in O(nlogn(loglogn)3) time, where n is the number of triangles in the simplicial complex that represents the d-manifold. Our result is a significant improvement over the previously known O(n2) algorithm. Finally, we present experimental results of our implementation and demonstrate that our algorithm for 3-manifolds performs efficiently in practice.

Exploring profit - Sustainability trade-offs in cropping systems using evolutionary algorithms

Models that implement the bio-physical components of agro-ecosystems are ideally suited for exploring sustainability issues in cropping systems. Sustainability may be represented as a number of objectives to be maximised or minimised. However, the full decision space of these objectives is usually very large and simplifications are necessary to safeguard computational feasibility. Different optimisation approaches have been proposed in the literature, usually based on mathematical programming techniques. Here, we present a search approach based on a multiobjective evaluation technique within an evolutionary algorithm (EA), linked to the APSIM cropping systems model. A simple case study addressing crop choice and sowing rules in North-East Australian cropping systems is used to illustrate the methodology. Sustainability of these systems is evaluated in terms of economic performance and resource use. Due to the limited size of this sample problem, the quality of the EA optimisation can be assessed by comparison to the full problem domain. Results demonstrate that the EA procedure, parameterised with generic parameters from the literature, converges to a useable solution set within a reasonable amount of time. Frontier ‘‘peels’’ or Pareto-optimal solutions as described by the multiobjective evaluation procedure provide useful information for discussion on trade-offs between conflicting objectives.

Fluorescent labelling of strychnine: A novel approach for recognition of strychnine binding sites on neuronal membrane

trychnine was coupled to fluorescein isothiocyanate to mark strychnine binding sites in spinal cord of rat. Specific binding of strychnine could be demonstrated in synaptosomal fraction. Addition of glycine to the strychninised membrane led to a decrease in fluorescence indicating same receptor loci.

The changing face of conveyancing responsibility

In this note the authors examine two cases, one from Australia, the other from New Zealand, both of which explore the responsibility of legal practitioners engaged as professionals in the buying and selling of land. What is shown is that the allocation of risk and responsibility is constantly under scrutiny for those involved in the conveyancing process, something which the nascent Australian electronic conveyancing protocols will only heighten.

Host recognition by a polyphagous lepidopteran (Helicoverpa armigera): Primary host plants, host produced volatiles and neurosensory stimulation

An important question in the host-finding behaviour of a polyphagous insect is whether the insect recognizes a suite or template of chemicals that are common to many plants? To answer this question, headspace volatiles of a subset of commonly used host plants (pigeon pea, tobacco, cotton and bean) and nonhost plants (lantana and oleander) of Helicoverpa armigera Hübner (Lepidoptera: Noctuidae) are screened by gas chromatography (GC) linked to a mated female H. armigera electroantennograph (EAG). In the present study, pigeon pea is postulated to be a primary host plant of the insect, for comparison of the EAG responses across the test plants. EAG responses for pigeon pea volatiles are also compared between females of different physiological status (virgin and mated females) and the sexes. Eight electrophysiologically active compounds in pigeon pea headspace are identified in relatively high concentrations using GC linked to mass spectrometry (GC-MS). These comprised three green leaf volatiles [(2E)-hexenal, (3Z)-hexenylacetate and (3Z)-hexenyl-2-methylbutyrate] and five monoterpenes (α-pinene, β-myrcene, limonene, E-β-ocimene and linalool). Other tested host plants have a smaller subset of these electrophysiologically active compounds and even the nonhost plants contain some of these compounds, all at relatively lower concentrations than pigeon pea. The physiological status or sex of the moths has no effect on the responses for these identified compounds. The present study demonstrates how some host plants can be primary targets for moths that are searching for hosts whereas the other host plants are incidental or secondary targets.

Repeatable Condition-Invariant Visual Odometry for Sequence-Based Place Recognition

This paper describes a vision-only system for place recognition in environments that are tra- versed at different times of day, when chang- ing conditions drastically affect visual appear- ance, and at different speeds, where places aren’t visited at a consistent linear rate. The ma- jor contribution is the removal of wheel-based odometry from the previously presented algo- rithm (SMART), allowing the technique to op- erate on any camera-based device; in our case a mobile phone. While we show that the di- rect application of visual odometry to our night- time datasets does not achieve a level of perfor- mance typically needed, the VO requirements of SMART are orthogonal to typical usage: firstly only the magnitude of the velocity is required, and secondly the calculated velocity signal only needs to be repeatable in any one part of the environment over day and night cycles, but not necessarily globally consistent. Our results show that the smoothing effect of motion constraints is highly beneficial for achieving a locally consis- tent, lighting-independent velocity estimate. We also show that the advantage of our patch-based technique used previously for frame recogni- tion, surprisingly, does not transfer to VO, where SIFT demonstrates equally good performance. Nevertheless, we present the SMART system us- ing only vision, which performs sequence-base place recognition in extreme low-light condi- tions where standard 6-DOF VO fails and that improves place recognition performance over odometry-less benchmarks, approaching that of wheel odometry.

An Adaptive Scheme for Learning the Probability Threshold in Pattern Recognition

The statistical minimum risk pattern recognition problem, when the classification costs are random variables of unknown statistics, is considered. Using medical diagnosis as a possible application, the problem of learning the optimal decision scheme is studied for a two-class twoaction case, as a first step. This reduces to the problem of learning the optimum threshold (for taking appropriate action) on the a posteriori probability of one class. A recursive procedure for updating an estimate of the threshold is proposed. The estimation procedure does not require the knowledge of actual class labels of the sample patterns in the design set. The adaptive scheme of using the present threshold estimate for taking action on the next sample is shown to converge, in probability, to the optimum. The results of a computer simulation study of three learning schemes demonstrate the theoretically predictable salient features of the adaptive scheme.