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 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.

Tooth Tissue Engineering: Optimal Dental Stem Cell Harvest Based on Tooth Development

Our long-term objective is to devise reliable methods to generate biological replacement teeth exhibiting the physical properties and functions of naturally formed human teeth. Previously, we demonstrated the successful use of tissue engineering approaches to generate small, bioengineered tooth crowns from harvested pig and rat postnatal dental stem cells (DSCs). To facilitate characterizations of human DSCs, we have developed a novel radiographic staging system to accurately correlate human third molar tooth developmental stage with anticipated harvested DSC yield. Our results demonstrated that DSC yields were higher in less developed teeth (Stages 1 and 2), and lower in more developed teeth (Stages 3, 4, and 5). The greatest cell yields and colony-forming units (CFUs) capability was obtained from Stages 1 and 2 tooth dental pulp. We conclude that radiographic developmental staging can be used to accurately assess the utility of harvested human teeth for future dental tissue engineering applications.

The effect of resource aggregation at different scales: Optimal foraging behavior of Cotesia rubecula

Resources can be aggregated both within and between patches. In this article, we examine how aggregation at these different scales influences the behavior and performance of foragers. We developed an optimal foraging model of the foraging behavior of the parasitoid wasp Cotesia rubecula parasitizing the larvae of the cabbage butterfly Pieris rapae. The optimal behavior was found using stochastic dynamic programming. The most interesting and novel result is that the effect of resource aggregation within and between patches depends on the degree of aggregation both within and between patches as well as on the local host density in the occupied patch, but lifetime reproductive success depends only on aggregation within patches. Our findings have profound implications for the way in which we measure heterogeneity at different scales and model the response of organisms to spatial heterogeneity.

Optimal patch-leaving behaviour: a case study using the parasitoid Cotesia rubecular

1. Parasitoids are predicted to spend longer in patches with more hosts, but previous work on Cotesia rubecula (Marshall) has not upheld this prediction, Tests of theoretical predictions may be affected by the definition of patch leaving behaviour, which is often ambiguous. 2. In this study whole plants were considered as patches and assumed that wasps move within patches by means of walking or flying. Within-patch and between-patch flights were distinguished based on flight distance. The quality of this classification was tested statistically by examination of log-survivor curves of flight times. 3. Wasps remained longer in patches with higher host densities, which is consistent with predictions of the marginal value theorem (Charnov 1976). tinder the assumption that each flight indicates a patch departure, there is no relationship between host density and leaving tendency. 4. Oviposition influences the patch leaving behaviour of wasps in a count down fashion (Driessen et al. 1995), as predicted by an optimal foraging model (Tenhumberg, Keller & Possingham 2001). 5. Wasps spend significantly longer in the first patch encountered following release, resulting in an increased rate of superparasitism.

The investigation of optimal bombardment parameters for transient and stable transgene expression in sorghum

This report outlines the development of optimized particle inflow gun (PIG) parameters for producing transgenic sorghum (Sorghum bicolor (L.) Moench). Both transient and stable expression were examined when determining these parameters. The uidA reporter gene (GUS) encoding beta -glucuronidase was used in transient experiments and the green fluorescent protein (GFP) used to monitor stable expression. Initially, optimization was conducted using leaf segments, as the generation of sorghum callus in sufficiently large quantities is time-consuming. Following leaf optimization, experiments were conducted using callus, identifying a high similarity between the two tissue types (r(s) = 0.83). High levels of GUS expression were observed in both leaf and callus material when most distant from the DNA expulsion point, and using a pressure greater than 1800 kPa. A higher level of expression was also observed when the aperture of the helium inlet valve was constricted. Using the optimized conditions (pressure of 2200 kPa, distance to target tissue of 15 cm from the expulsion point, and the aperture of the helium inlet valve at one full turn), three promoters (Ubiquitin, Actin1 and CaMV 35S) were evaluated over a 72-h period using GUS as the reporter gene. A significantly higher number of GUS foci were counted with the Ubiquitin construct over this period, compared to the Actin1 and CaMV 35S constructs. Stable callus sectors (on 2 mg l(-1) bialaphos) with GFP expression were visualized for as long as 6 wk post-bombardment. Using this optimized protocol, several plants were regenerated after having been bombarded with the pAHC20 construct (containing the bar gene), with molecular evidence confirming integration.

The use of stochastic dynamic programming in optimal landscape reconstruction for metapopulations

A decision theory framework can be a powerful technique to derive optimal management decisions for endangered species. We built a spatially realistic stochastic metapopulation model for the Mount Lofty Ranges Southern Emu-wren (Stipiturus malachurus intermedius), a critically endangered Australian bird. Using diserete-time Markov,chains to describe the dynamics of a metapopulation and stochastic dynamic programming (SDP) to find optimal solutions, we evaluated the following different management decisions: enlarging existing patches, linking patches via corridors, and creating a new patch. This is the first application of SDP to optimal landscape reconstruction and one of the few times that landscape reconstruction dynamics have been integrated with population dynamics. SDP is a powerful tool that has advantages over standard Monte Carlo simulation methods because it can give the exact optimal strategy for every landscape configuration (combination of patch areas and presence of corridors) and pattern of metapopulation occupancy, as well as a trajectory of strategies. It is useful when a sequence of management actions can be performed over a given time horizon, as is the case for many endangered species recovery programs, where only fixed amounts of resources are available in each time step. However, it is generally limited by computational constraints to rather small networks of patches. The model shows that optimal metapopulation, management decisions depend greatly on the current state of the metapopulation,. and there is no strategy that is universally the best. The extinction probability over 30 yr for the optimal state-dependent management actions is 50-80% better than no management, whereas the best fixed state-independent sets of strategies are only 30% better than no management. This highlights the advantages of using a decision theory tool to investigate conservation strategies for metapopulations. It is clear from these results that the sequence of management actions is critical, and this can only be effectively derived from stochastic dynamic programming. The model illustrates the underlying difficulty in determining simple rules of thumb for the sequence of management actions for a metapopulation. This use of a decision theory framework extends the capacity of population viability analysis (PVA) to manage threatened species.