The effect of high-pass filtering on TEOAE in 2-month-old infants

The aim of the present study was to investigate the effect of high-pass filtering on TEOAE obtained from 2-month-old infants as a function of filter cut-off frequency, activity states and pass/fail status of infants. Two experiments were performed. In Experiment 1, 100 2-month-old infants (200 ears) in five activity states (asleep, awake but peaceful, sucking a pacifier, feeding, restless) were tested by use of TEOAE technology. Five different filter conditions were applied to the TEOAE responses post hoc. The filter conditions were set at 781 Hz (default setting), 1.0, 1.2, 1.4 and 1.6 kHz. Results from this experiment showed that TEOAE parameters, such as whole-wave reproducibility (WR) and signal-to-noise ratio (SNR) at 0.8 kHz and 1.6 kHz, changed as a function of the cut-off frequency. The findings suggest that the 1.6 kHz and 1.2 kHz filter conditions are optimal for WR and SNR pass/fail criteria, respectively. Although all infant recordings appeared to benefit from the filtering, infants in the noisy states seemed to benefit the most. In Experiment 2, the high-pass filtering technique was applied to 23 infants (35 ears) who apparently failed the TEOAE tests on initial screening but were subsequently awarded a pass status based on the results from a follow-up auditory brainstem response (ABR) assessment. The findings showed a significant decrease in noise contamination of the TEOAE with a corresponding significant increase in WR. With high-pass filtering at 1.6 kHz, 21/35 ears could be reclassified into the pass category.

Generalized optimal lattice covering of finite-dimensional Euclidean space

A generalization of the classical problem of optimal lattice covering of R-n is considered. Solutions to this generalized problem are found in two specific classes of lattices. The global optimal solution of the generalization is found for R-2. (C) 1998 Elsevier Science Inc. All rights reserved.

The nurse lecturer role in clinical practice conceptualized: helping clinical teachers provide optimal student learning

Despite the fairly wide reporting in the literature of the ma ny roles of clinical supervision by the nursing teacher, little attention has been given to conceptualizing the relative priorities these roles take during the process of supervising nursing students in clinical practice. The purpose of this paper is to consider the manifestations and implications of conflicting roles when nurse lecturers undertake clinical supervision. Previously published research will provide working examples of issues in a conceptual framework for clinical teaching.

The influence of supra-optimal root-zone temperatures on growth and stomatal conductance in Capsicum annuum L.

Pepper (Capsicum annuum L.) plants were grown aeroponically in a Singapore greenhouse under natural diurnally fluctuating ambient shoot temperatures, but at two different root-zone temperatures (RZTs): a constant 20 +/- 2 degrees C RZT and a diurnally fluctuating ambient (A) (25-40 degrees C) RZT, Plants grown at 20-RZT had more leaves, greater leaf area and dry weight than A-RZT plants. Reciprocal transfer experiments were conducted between RZTs to investigate the effect on plant growth, stomatal conductance (g(s)) and water relations. Transfer of plants from A-RZT to 20-RZT increased plant dry weight, leaf area, number of leaves, shoot water potential (Psi(shoot)), and g(s); while transfer of plants from 20-RZT to A-RZT decreased these parameters. Root hydraulic conductivity was measured in the latter transfer and decreased by 80% after 23 d at A-RZT. Transfer of plants from 20-RZT to A-RZT had no effect on xylem ABA concentration or xylem nitrate concentration, but reduced xylem sap pH by 0.2 units. At both RZTs, g(s) measured in the youngest fully expanded leaves increased with plant development. In plants with the same number of leaves, A-RZT plants had a higher g(s) than 20-RZT plants, but only under high atmospheric vapour pressure deficit. The roles of chemical signals and hydraulic factors in controlling g(s) of aeroponically grown Capsicum plants at different RZTs are discussed.

Optimal release strategies for biological control agents: an application of stochastic dynamic programming to population management

1. Establishing biological control agents in the field is a major step in any classical biocontrol programme, yet there are few general guidelines to help the practitioner decide what factors might enhance the establishment of such agents. 2. A stochastic dynamic programming (SDP) approach, linked to a metapopulation model, was used to find optimal release strategies (number and size of releases), given constraints on time and the number of biocontrol agents available. By modelling within a decision-making framework we derived rules of thumb that will enable biocontrol workers to choose between management options, depending on the current state of the system. 3. When there are few well-established sites, making a few large releases is the optimal strategy. For other states of the system, the optimal strategy ranges from a few large releases, through a mixed strategy (a variety of release sizes), to many small releases, as the probability of establishment of smaller inocula increases. 4. Given that the probability of establishment is rarely a known entity, we also strongly recommend a mixed strategy in the early stages of a release programme, to accelerate learning and improve the chances of finding the optimal approach.

Using stochastic dynamic programming to determine optimal fire management for Banksia ornata

1. A model of the population dynamics of Banksia ornata was developed, using stochastic dynamic programming (a state-dependent decision-making tool), to determine optimal fire management strategies that incorporate trade-offs between biodiversity conservation and fuel reduction. 2. The modelled population of B. ornata was described by its age and density, and was exposed to the risk of unplanned fires and stochastic variation in germination success. 3. For a given population in each year, three management strategies were considered: (i) lighting a prescribed fire; (ii) controlling the incidence of unplanned fire; (iii) doing nothing. 4. The optimal management strategy depended on the state of the B. ornata population, with the time since the last fire (age of the population) being the most important variable. Lighting a prescribed fire at an age of less than 30 years was only optimal when the density of seedlings after a fire was low (< 100 plants ha(-1)) or when there were benefits of maintaining a low fuel load by using more frequent fire. 5. Because the cost of management was assumed to be negligible (relative to the value of the persistence of the population), the do-nothing option was never the optimal strategy, although lighting prescribed fires had only marginal benefits when the mean interval between unplanned fires was less than 20-30 years.

Modelling socially optimal land allocations for sugar cane growing in North Queensland: a linked mathematical programming and choice modelling study

A modelling framework is developed to determine the joint economic and environmental net benefits of alternative land allocation strategies. Estimates of community preferences for preservation of natural land, derived from a choice modelling study, are used as input to a model of agricultural production in an optimisation framework. The trade-offs between agricultural production and environmental protection are analysed using the sugar industry of the Herbert River district of north Queensland as an example. Spatially-differentiated resource attributes and the opportunity costs of natural land determine the optimal tradeoffs between production and conservation for a range of sugar prices.

Fast-convergent iterative scheme for filtering velocity signals and finding Kolmogorov scales

The present fundamental knowledge of fluid turbulence has been established primarily from hot- and cold-wire measurements. Unfortunately, however, these measurements necessarily suffer from contamination by noise since no certain method has previously been available to optimally filter noise from the measured signals. This limitation has impeded our progress of understanding turbulence profoundly. We address this limitation by presenting a simple, fast-convergent iterative scheme to digitally filter signals optimally and find Kolmogorov scales definitely. The great efficacy of the scheme is demonstrated by its application to the instantaneous velocity measured in a turbulent jet.

Optimal estimation of one-parameter quantum channels

We explore the task of optimal quantum channel identification and in particular, the estimation of a general one-parameter quantum process. We derive new characterizations of optimality and apply the results to several examples including the qubit depolarizing channel and the harmonic oscillator damping channel. We also discuss the geometry of the problem and illustrate the usefulness of using entanglement in process estimation.

Optimal quantum measurements for phase-shift estimation in optical interferometry

Quantum information theory, applied to optical interferometry, yields a 1/n scaling of phase uncertainty Delta phi independent of the applied phase shift phi, where n is the number of photons in the interferometer. This 1/n scaling is achieved provided that the output state is subjected to an optimal phase measurement. We establish this scaling law for both passive (linear) and active (nonlinear) interferometers and identify the coefficient of proportionality. Whereas a highly nonclassical state is required to achieve optimal scaling for passive interferometry, a classical input state yields a 1/n scaling of phase uncertainty for active interferometry.

Optimal quantum trajectories for discrete measurements

Using the method of quantum trajectories we show that a known pure state can be optimally monitored through time when subject to a sequence of discrete measurements. By modifying the way that we extract information from the measurement apparatus we can minimize the average algorithmic information of the measurement record, without changing the unconditional evolution of the measured system. We define an optimal measurement scheme as one which has the lowest average algorithmic information allowed. We also show how it is possible to extract information about system operator averages from the measurement records and their probabilities. The optimal measurement scheme, in the limit of weak coupling, determines the statistics of the variance of the measured variable directly. We discuss the relevance of such measurements for recent experiments in quantum optics.