Characteristics of Quantum-Classical Correspondence for Two Interacting Spins

The conditions of quantum-classical correspondence for a system of two interacting spins are investigated. Differences between quantum expectation values and classical Liouville averages are examined for both regular and chaotic dynamics well beyond the short-time regime of narrow states. We find that quantum-classical differences initially grow exponentially with a characteristic exponent consistently larger than the largest Lyapunov exponent. We provide numerical evidence that the time of the break between the quantum and classical predictions scales as log(${\cal J}/ \hbar$), where ${\cal J}$ is a characteristic system action. However, this log break-time rule applies only while the quantum-classical deviations are smaller than order hbar. We find that the quantum observables remain well approximated by classical Liouville averages over long times even for the chaotic motions of a few degree-of-freedom system. To obtain this correspondence it is not necessary to introduce the decoherence effects of a many degree-of-freedom environment.Comment: New introduction, accepted in Phys Rev A (May 2001 issue), 12 latex figures, 3 ps figure

Baryogenesis, Dark Matter and the Pentagon

We present a new mechanism for baryogenesis, which links the baryon asymmetry of the universe to the dark matter density. The mechanism arises naturally in the Pentagon model of TeV scale physics. In that context, it forces a re-evaluation of some of the assumptions of the model, and we detail the changes that are required in order to fit observations.Comment: JHEP3 LaTeX, 15 pages. New version corrects errors in the electroweak baryon violating and matter radiation temperatures, which were pointed out by the referee. Substantial quantitative but no qualitative change to our conclusion

A Generic Agent Organisation Framework For Autonomic Systems

Autonomic computing is being advocated as a tool for managing large, complex computing systems. Specifically, self-organisation provides a suitable approach for developing such autonomic systems by incorporating self-management and adaptation properties into large-scale distributed systems. To aid in this development, this paper details a generic problem-solving agent organisation framework that can act as a modelling and simulation platform for autonomic systems. Our framework describes a set of service-providing agents accomplishing tasks through social interactions in dynamically changing organisations. We particularly focus on the organisational structure as it can be used as the basis for the design, development and evaluation of generic algorithms for self-organisation and other approaches towards autonomic systems

Enough is not enough: Medical students’ knowledge of early warning signs of childhood cancer

Background. The reported incidence of childhood cancer in upper-middle-income South Africa (SA) is much lower than in high-income countries, partly due to under-diagnosis and under-reporting. Documented survival rates are disturbingly low, prompting an analysis of potential factors that may be responsible.Objectives. To determine final-year medical students’ level of knowledge of early warning signs of childhood cancer and whether a correlation existed between test scores and participants’ age, gender and previous exposure to a person with cancer.Methods. A two-part questionnaire based on the Saint Siluan mnemonic, testing both recall and recognition of early warning signs of childhood cancer, was administered. The Mann-Whitney-Wilcoxon test was used to assess differences in continuous and count variables between demographic data, experience and responses, and Fisher’s exact test and Spearman’s rank correlation coefficient were used to determine correlations between demographic data, previous contact with persons with cancer and test scores. A novel equality ratio was calculated to compare the recall and recognition sections and allowed analysis of recall v. recognition.Results. The 84 participants recalled a median of six signs each (interquartile range 4 - 7) and correctly recognised a median of 70% in the recognition section, considered a pass mark. There was no correlation between participants’ age, gender, previous contact with a person with cancer and recognition scores. Students with previous exposure to a person with cancer had higher scores in the recall section, but this did not achieve statistical significance. Students were able to recognise more signs of haematological malignancies than central nervous system (CNS) malignancies.Conclusion. The study demonstrated a marked inconsistency between recall and recognition of signs of childhood cancer, with signs of CNS malignancies being least recognised. However, the majority of students could recognise enough early warning signs to meet the university pass standard. Although this study demonstrated acceptable recognition of early warning signs of childhood cancer at one university, we suggest that long-term recall in medical practitioners is poor, as reflected in the low age-standardised ratios of childhood cancer in SA. We recommend increased ongoing exposure to paediatric oncology in medical school and improved awareness programmes to increase early referrals

A grid-enabled problem solving environment for parallel computational engineering design

This paper describes the development and application of a piece of engineering software that provides a problem solving environment (PSE) capable of launching, and interfacing with, computational jobs executing on remote resources on a computational grid. In particular it is demonstrated how a complex, serial, engineering optimisation code may be efficiently parallelised, grid-enabled and embedded within a PSE. The environment is highly flexible, allowing remote users from different sites to collaborate, and permitting computational tasks to be executed in parallel across multiple grid resources, each of which may be a parallel architecture. A full working prototype has been built and successfully applied to a computationally demanding engineering optimisation problem. This particular problem stems from elastohydrodynamic lubrication and involves optimising the computational model for a lubricant based on the match between simulation results and experimentally observed data

Core Mass Estimates in Strong Lensing Galaxy Clusters: A Comparison between Masses Obtained from Detailed Lens Models, Single-halo Lens Models, and Einstein Radii

The core mass of galaxy clusters is both an important anchor of the radial mass distribution profile and a probe of structure formation. With thousands of strong lensing galaxy clusters being discovered by current and upcoming surveys, timely, efficient, and accurate core mass estimates are needed. We assess the results of two efficient methods to estimate the core mass of strong lensing clusters: the mass enclosed by the Einstein radius (M(<θE), where θE is approximated from arc positions, and a single-halo lens model (MSHM), compared with measurements from publicly available detailed lens models (MDLM) of the same clusters. We use data from the Sloan Giant Arc Survey, the Reionization Lensing Cluster Survey, the Hubble Frontier Fields, and the Cluster Lensing and Supernova Survey with Hubble. We find a scatter of 18.1% (8.2%) with a bias of −7.1% (1.0%) between ${M}_{\mathrm{corr}}\left(\lt {\theta }_{\mathrm{arcs}}\right)$ (MSHM) and MDLM. Last, we compare the statistical uncertainties measured in this work to those from simulations. This work demonstrates the successful application of these methods to observational data. As the effort to efficiently model the mass distribution of strong lensing galaxy clusters continues, we need fast, reliable methods to advance the field

Systematic inference of the long-range dependence and heavy-tail distribution parameters of ARFIMA models

Long-Range Dependence (LRD) and heavy-tailed distributions are ubiquitous in natural and socio-economic data. Such data can be self-similar whereby both LRD and heavy-tailed distributions contribute to the self-similarity as measured by the Hurst exponent. Some methods widely used in the physical sciences separately estimate these two parameters, which can lead to estimation bias. Those which do simultaneous estimation are based on frequentist methods such as Whittle’s approximate maximum likelihood estimator. Here we present a new and systematic Bayesian framework for the simultaneous inference of the LRD and heavy-tailed distribution parameters of a parametric ARFIMA model with non-Gaussian innovations. As innovations we use the α-stable and t-distributions which have power law tails. Our algorithm also provides parameter uncertainty estimates. We test our algorithm using synthetic data, and also data from the Geostationary Operational Environmental Satellite system (GOES) solar X-ray time series. These tests show that our algorithm is able to accurately and robustly estimate the LRD and heavy-tailed distribution parameters

Chaos and Quantum-Classical Correspondence via Phase Space Distribution Functions

Quantum-classical correspondence in conservative chaotic Hamiltonian systems is examined using a uniform structure measure for quantal and classical phase space distribution functions. The similarities and differences between quantum and classical time-evolving distribution functions are exposed by both analytical and numerical means. The quantum-classical correspondence of low-order statistical moments is also studied. The results shed considerable light on quantum-classical correspondence.Comment: 16 pages, 5 figures, to appear in Physical Review

Have we seen the geneticisation of society? Expectations and evidence

Abby Lippman’s geneticization thesis, of the early 1990s, argued and anticipated that with the rise of genetics, increasing areas of social and health related activities would come to be understood and defined in genetic terms leading to major changes in society, medicine and health care. We review the considerable literature on geneticization and consider how the concept stands both theoretically and empirically across scientific, clinical, popular and lay discourse and practice. Social science scholarship indicates that relatively little of the original claim of the geneticization thesis has been realised, highlighting the development of more complex and dynamic accounts of disease in scientific discourse and the complexity of relationships between bioscientific, clinical and lay understandings. This scholarship represents a shift in social science understandings of the processes of sociotechnical change, which have moved from rather simplistic linear models to an appreciation of disease categories as multiply understood. Despite these shifts, we argue that a genetic imaginary persists, which plays a performative role in driving investments in new gene-based developments. Understanding the enduring power of this genetic imaginary and its consequences remains a key task for the social sciences, one which treats ongoing genetic expectations and predictions in a sceptical yet open way

Broad-spectrum in vitro activity of macrophage infectivity potentiator inhibitors against Gram-negative bacteria and Leishmania major

Background The macrophage infectivity potentiator (Mip) protein, which belongs to the immunophilin superfamily, is a peptidyl-prolyl cis/trans isomerase (PPIase) enzyme. Mip has been shown to be important for virulence in a wide range of pathogenic microorganisms. It has previously been demonstrated that small-molecule compounds designed to target Mip from the Gram-negative bacterium Burkholderia pseudomallei bind at the site of enzymatic activity of the protein, inhibiting the in vitro activity of Mip. Objectives In this study, co-crystallography experiments with recombinant B. pseudomallei Mip (BpMip) protein and Mip inhibitors, biochemical analysis and computational modelling were used to predict the efficacy of lead compounds for broad-spectrum activity against other pathogens. Methods Binding activity of three lead compounds targeting BpMip was verified using surface plasmon resonance spectroscopy. The determination of crystal structures of BpMip in complex with these compounds, together with molecular modelling and in vitro assays, was used to determine whether the compounds have broad-spectrum antimicrobial activity against pathogens. Results Of the three lead small-molecule compounds, two were effective in inhibiting the PPIase activity of Mip proteins from Neisseria meningitidis, Klebsiella pneumoniae and Leishmania major. The compounds also reduced the intracellular burden of these pathogens using in vitro cell infection assays. Conclusions These results indicate that Mip is a novel antivirulence target that can be inhibited using small-molecule compounds that prove to be promising broad-spectrum drug candidates in vitro. Further optimization of compounds is required for in vivo evaluation and future clinical applications