Quantum Arthur-Merlin Games

This paper studies quantum Arthur-Merlin games, which are Arthur-Merlin games in which Arthur and Merlin can perform quantum computations and Merlin can send Arthur quantum information. As in the classical case, messages from Arthur to Merlin are restricted to be strings of uniformly generated random bits. It is proved that for one-message quantum Arthur-Merlin games, which correspond to the complexity class QMA, completeness and soundness errors can be reduced exponentially without increasing the length of Merlin's message. Previous constructions for reducing error required a polynomial increase in the length of Merlin's message. Applications of this fact include a proof that logarithmic length quantum certificates yield no increase in power over BQP and a simple proof that QMA is contained in PP. Other facts that are proved include the equivalence of three (or more) message quantum Arthur-Merlin games with ordinary quantum interactive proof systems and some basic properties concerning two-message quantum Arthur-Merlin games.Comment: 22 page

Non-determinism and quantum information

Bibliography: p. 89-91

Domestication syndrome via indirect selection in simulated cereal grains

Domestication syndrome in cereal grains is commonly thought to be the product of domestication through a combination of direct artificial selection and indirect natural selection by humans. We propose an agent-based model of grain domestication. We simulate cereal grains with four genes that impact their reproductive cycle undergoing harvesting and selective planting by simulated humans. When direct artificial selection is applied to one gene domestication syndrome emerges in the other genes as a result of indirect natural selection. In the absence of direct artificial selection no domestication syndrome emerged, consistent with periods of predomestication cultivation in human history. Domesticated variants are strongest when humans select for traits inconsistent with the wild type traits, and weakest when humans select for traits consistent with the wild type

Checking Memory Safety of Level 1 Safety-Critical Java Programs using Static-Analysis without Annotations

Safety-Critical Java (SCJ) has been designed specifically to ring performance and reliability to the development of safety-critical Java programs. SCJ introduces a novel programming paradigm based on missions and handlers, and has been designed to ease certification. One of the distinguishing features of SCJ is its memory model, which is defined as a hierarchical structure of scoped-based memory areas. Unlike in Java programs, memory management is an important concern under the control of the programmer in SCJ; it is not sufficient to write a program that conforms to the specification as memory safety may still be broken. By using static analysis techniques, it is possible to identify errors in programs before they are executed. Analysing at the source-code level allows for a precise analysis that abstracts away from machine details and unnecessary program details. As the SCJ paradigm is different to that of Java, it is not possible to apply existing tools and techniques for Java programs to SCJ. This thesis describes a new static-checking technique for a comprehensive subset of SCJ programs (comparable to Ravenscar Ada) that automatically checks for memory-safety violations at the source-code level without the need for user-added annotations. An abstract language (SCJ-mSafe) is used to describe the aspects of SCJ programs required to check memory safety, and a set of inference rules define what it means for each aspect to be memory safe. By using a points-to environment and automatically-generated method properties, it is possible to produce a model of the execution of an SCJ program that can identify possible memory-safety violations at each point in the execution. The whole process has been automated with tool support and compared against other techniques. A worst-case analysis is performed that can give false negatives

Development of a prescribing indicator for objective quantification of antibiotic usage in secondary care

Objectives: To compare the recognized defined daily dose per 100 bed-days (DDD/100 bed-days) measure with the defined daily dose per finished consultant episode (DDD/FCE) in a group of hospitals with a variety of medicines management strategies. To compare antibiotic usage using the above indicators in hospitals with and without electronic prescribing systems. Methods: Twelve hospitals were used in the study. Nine hospitals were selected and split into three cohorts (three high-scoring, three medium-scoring and three low-scoring) by their 2001 medicines management self-assessment scores (MMAS). An additional cohort of three electronic prescribing hospitals was included for comparison. MMAS were compared to antibiotic management scores (AMS) developed from a questionnaire relating specifically to control of antibiotics. FCEs and occupied bed-days were obtained from published statistics and statistical analyses of the DDD/100 bed-days and DDD/FCE were carried out using SPSS. Results: The DDD/100 bed-days varied from 81.33 to 189.37 whilst the DDD/FCE varied from 2.88 to 7.43. The two indicators showed a high degree of correlation with r = 0.74. MMAS were from 9 to 22 (possible range 0-23) and the AMS from 2 to 13 (possible range 0-22). The two scores showed a high degree of correlation with r = 0.74. No correlation was established between either indicator and either score. Conclusions: The WHO indicator for medicines utilization, DDD/100 bed-days, exhibited the same level of conformity as that exhibited from the use of the DDD/FCE indicating that the DDD/FCE is a useful additional indicator for identifying hospitals which require further study. The MMAS can be assumed to be an accurate guide to antibiotic medicines management controls. No relationship has been found between a high degree of medicines management control and the quantity of antibiotic prescribed. © The British Society for Antimicrobial Chemotherapy; 2004 all rights reserved

How do red deer react to increased visitor numbers? A case study on human-deer encounter probability and its effect on cortisol stress responses

The numbers of visitors to greenspaces in the United Kingdom has increased over the last few years as the health benefits of spending time in greenspaces have become better known. This has led to problems for conservation ecologists due to increased numbers of reported human-wildlife encounters. Deer are often found in public spaces and are of particular concern. Previous research suggests elevated levels of stress hormones (e.g., cortisol) in deer is a result of increased human activity. This has been linked to several negative effects on the deer’s health. From a practitioner’s point of view, it is therefore important to implement effective management strategies that are based on scientific evidence to help ensure the welfare of managed deer populations. In an effort to identify the impact of visitor numbers on faecal cortisol concentrations, samples from 2 red deer (Cervus elaphus) herds in Lyme Park (Cheshire), United Kingdom, were collected and analysed. A predictive spatial model was developed based on logistic regression to identify areas within the park of low and high human-deer encounter probability. The faecal cortisol levels were found to be significantly higher on days with a high number of visitors. In addition, landscape features such as buildings and roads increased the probability of human-deer encounters, whereas woodland and scrub decreased the probability. However, human-deer encounter probability changed with distance to the features. By providing local park managers with this scientific data, these findings can directly inform current management efforts to reduce deer stress levels in Lyme Park. In addition, the spatial modelling method has the capacity to be implemented in other parks across the country with minimal cost and effort