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.

Inter-subband redundancy prediction using neural network for video coding

High performance video codec is mandatory for multimedia applications such as video-on-demand and video conferencing. Recent research has proposed numerous video coding techniques to meet the requirement in bandwidth, delay, loss and Quality-of-Service (QoS). In this paper, we present our investigations on inter-subband self-similarity within the wavelet-decomposed video frames using neural networks, and study the performance of applying the spatial network model to all video frames over time. The goal of our proposed method is to restore the highest perceptual quality for video transmitted over a highly congested network. Our contributions in this paper are: (1) A new coding model with neural network based, inter-subband redundancy (ISR) prediction for video coding using wavelet (2) The performance of 1D and 2D ISR prediction, including multiple levels of wavelet decompositions. Our result shows a short-term quality enhancement may be obtained using both 1D and 2D ISR prediction.

Debt Maturity: Is Long-Term Debt Optimal?

We model and calibrate the arguments in favor and against short-term and long-term debt. These arguments broadly include: maturity premium, sustainability, and service smoothing. We use a dynamic-equilibrium model with tax distortions and government outlays uncertainty, and model maturity as the fraction of debt that needs to be rolled over every period. In the model, the benefits of defaulting are tempered by higher future interest rates. We then calibrate our artificial economy and solve for the optimal debt maturity for Brazil as an example of a developing country and the US as an example of a mature economy. We obtain that the calibrated costs from defaulting on long-term debt more than offset costs associated with short-term debt. Therefore, short-term debt implies higher welfare levels.

Optimal reserve management and sovereign debt

Most models currently used to determine optimal foreign reserve holdings take the level of international debt as given. However, given the sovereign`s willingness-to-pay incentive problems, reserve accumulation may reduce sustainable debt levels. In addition, assuming constant debt levels does not allow addressing one of the puzzles behind using reserves as a means to avoid the negative effects of crisis: why do not sovereign countries reduce their sovereign debt instead? To study the joint decision of holding sovereign debt and reserves, we construct a stochastic dynamic equilibrium model calibrated to a sample of emerging markets. We obtain that the reserve accumulation does not play a quantitatively important role in this model. In fact, we find the optimal policy is not to hold reserves at all. This finding is robust to considering interest rate shocks, sudden stops, contingent reserves and reserve dependent output costs. (c) 2008 Elsevier B.V. All rights reserved.

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.

Effects of Optimal Medical Treatment With or Without Coronary Revascularization on Angina and Subsequent Revascularizations in Patients With Type 2 Diabetes Mellitus and Stable Ischemic Heart Disease

Background-In the Bypass Angioplasty Revascularization Investigation 2 Diabetes (BARI 2D) trial, an initial strategy of coronary revascularization and optimal medical treatment (REV) compared with an initial optimal medical treatment with the option of subsequent revascularization (MED) did not reduce all-cause mortality or the composite of cardiovascular death, myocardial infarction, and stroke in patients with type 2 diabetes mellitus and stable ischemic heart disease. In the same population, we tested whether the REV strategy was superior to the MED strategy in preventing worsening and new angina and subsequent coronary revascularizations. Methods and Results-Among the 2364 men and women (mean age, 62.4 years) with type 2 diabetes mellitus, documented coronary artery disease, and myocardial ischemia, 1191 were randomized to the MED and 1173 to the REV strategy preselected in the percutaneous coronary intervention (796) and coronary artery bypass graft (377) strata. Compared with the MED strategy, the REV strategy at the 3-year follow-up had a lower rate of worsening angina (8% versus 13%; P < 0.001), new angina (37% versus 51%; P = 0.001), and subsequent coronary revascularizations (18% versus 33%; P < 0.001) and a higher rate of angina-free status (66% versus 58%; P = 0.003). The coronary artery bypass graft stratum patients were at higher risk than those in the percutaneous coronary intervention stratum, and had the greatest benefits from REV. Conclusions-In these patients, the REV strategy reduced the occurrence of worsening angina, new angina, and subsequent coronary revascularizations more than the MED strategy. The symptomatic benefits were observed particularly for high-risk patients.

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.

A Bayesian approach to fuzzy hypotheses testing for the estimation of optimal age for vaccination against measles

Fuzzy Bayesian tests were performed to evaluate whether the mother`s seroprevalence and children`s seroconversion to measles vaccine could be considered as ""high"" or ""low"". The results of the tests were aggregated into a fuzzy rule-based model structure, which would allow an expert to influence the model results. The linguistic model was developed considering four input variables. As the model output, we obtain the recommended age-specific vaccine coverage. The inputs of the fuzzy rules are fuzzy sets and the outputs are constant functions, performing the simplest Takagi-Sugeno-Kang model. This fuzzy approach is compared to a classical one, where the classical Bayes test was performed. Although the fuzzy and classical performances were similar, the fuzzy approach was more detailed and revealed important differences. In addition to taking into account subjective information in the form of fuzzy hypotheses it can be intuitively grasped by the decision maker. Finally, we show that the Bayesian test of fuzzy hypotheses is an interesting approach from the theoretical point of view, in the sense that it combines two complementary areas of investigation, normally seen as competitive. (C) 2007 IMACS. Published by Elsevier B.V. All rights reserved.