The roles of olfaction and vision in host-plant finding by the diamondback moth, Plutella xylostella

The relative roles of olfaction and vision in the crepuscular host-finding process of a major lepidopteran pest of cruciferous crops, the diamondback moth Plutella xylostella are investigated in a series of laboratory and semi-field experiments. Flying female moths use volatile plant chemical cues to locate and to promote landing on their host, even in complex mixed-crop environments in large cages. Multiple regression analysis shows that both the plant position (front, middle or back rows) and the type of plant (host plant, nonhost plant) are needed to explain the distribution of insects in such a mixed-crop situation. This strong plant position effect indicates that, when host plants are present in a mixture, foraging P. xylostella are more likely to alight on the first row of the plants. The findings are discussed with regard to current theories of host-plant location by phytophagous insects and the possible implications for integrated pest management.

Finding the smallest eigenvalue by the inverse Monte Carlo method with refinement

Finding the smallest eigenvalue of a given square matrix A of order n is computationally very intensive problem. The most popular method for this problem is the Inverse Power Method which uses LU-decomposition and forward and backward solving of the factored system at every iteration step. An alternative to this method is the Resolvent Monte Carlo method which uses representation of the resolvent matrix [I -qA](-m) as a series and then performs Monte Carlo iterations (random walks) on the elements of the matrix. This leads to great savings in computations, but the method has many restrictions and a very slow convergence. In this paper we propose a method that includes fast Monte Carlo procedure for finding the inverse matrix, refinement procedure to improve approximation of the inverse if necessary, and Monte Carlo power iterations to compute the smallest eigenvalue. We provide not only theoretical estimations about accuracy and convergence but also results from numerical tests performed on a number of test matrices.

Use of auditory cues for wayfinding assistance in virtual environment: music aids route decision

This paper addresses the crucial problem of wayfinding assistance in the Virtual Environments (VEs). A number of navigation aids such as maps, agents, trails and acoustic landmarks are available to support the user for navigation in VEs, however it is evident that most of the aids are visually dominated. This work-in-progress describes a sound based approach that intends to assist the task of 'route decision' during navigation in a VE using music. Furthermore, with use of musical sounds it aims to reduce the cognitive load associated with other visually as well as physically dominated tasks. To achieve these goals, the approach exploits the benefits provided by music to ease and enhance the task of wayfinding, whilst making the user experience in the VE smooth and enjoyable.

Finding the point on Bezier Curves with the normal vector passing an external point

Two algorithms for finding the point on non-rational/rational Bezier curves of which the normal vector passes through a given external point are presented. The algorithms are based on Bezier curves generation algorithms of de Casteljau's algorithm for non-rational Bezier curve or Farin's recursion for rational Bezier curve, respectively. Orthogonal projections from the external point are used to guide the directional search used in the proposed iterative algorithms. Using Lyapunov's method, it is shown that each algorithm is able to converge to a local minimum for each case of non-rational/rational Bezier curves. It is also shown that on convergence the distance between the point on curves to the external point reaches a local minimum for both approaches. Illustrative examples are included to demonstrate the effectiveness of the proposed approaches.

Adaptive designs for Phase I dose-finding studies

Improving methodology for Phase I dose-finding studies is currently of great interest in pharmaceutical and medical research. This article discusses the current atmosphere and attitude towards adaptive designs and focuses on the influence of Bayesian approaches.

Benchmarking and valuation issues in measuring depreciation for European office markets

Purpose – The paper addresses the practical problems which emerge when attempting to apply longitudinal approaches to the assessment of property depreciation using valuation-based data. These problems relate to inconsistent valuation regimes and the difficulties in finding appropriate benchmarks. Design/methodology/approach – The paper adopts a case study of seven major office locations around Europe and attempts to determine ten-year rental value depreciation rates based on a longitudinal approach using IPD, CBRE and BNP Paribas datasets. Findings – The depreciation rates range from a 5 per cent PA depreciation rate in Frankfurt to a 2 per cent appreciation rate in Stockholm. The results are discussed in the context of the difficulties in applying this method with inconsistent data. Research limitations/implications – The paper has methodological implications for measuring property investment depreciation and provides an example of the problems in adopting theoretically sound approaches with inconsistent information. Practical implications – Valuations play an important role in performance measurement and cross border investment decision making and, therefore, knowledge of inconsistency of valuation practice aids decision making and informs any application of valuation-based data in the attainment of depreciation rates. Originality/value – The paper provides new insights into the use of property market valuation data in a cross-border context, insights that previously had been anecdotal and unproven in nature.