Distributed phase-covariant cloning with atomic ensembles via quantum Zeno dynamics

We propose an interesting scheme for distributed orbital state quantum cloning with atomic ensembles based on the quantum Zeno dynamics. These atomic ensembles which consist of identical three-level atoms are trapped in distant cavities connected by a single-mode integrated optical star coupler. These qubits can be manipulated through appropriate modulation of the coupling constants between atomic ensemble and classical field, and the cavity decay can be largely suppressed as the number of atoms in the ensemble qubits increases. The fidelity of each cloned qubit can be obtained with analytic result. The present scheme provides a new way to construct the quantum communication network.Comment: 5 pages, 4 figure

Theoretical Evaluation of the Detectability of Random Lesions in Bayesian Emission Reconstruction

Detecting cancerous lesion is an important task in positron emission tomography (PET). Bayesian methods based on the maximum a posteriori principle (also called penalized maximum likelihood methods) have been developed to deal with the low signal to noise ratio in the emission data. Similar to the filter cut-off frequency in the filtered backprojection method, the prior parameters in Bayesian reconstruction control the resolution and noise trade-off and hence affect detectability of lesions in reconstructed images. Bayesian reconstructions are difficult to analyze because the resolution and noise properties are nonlinear and object-dependent. Most research has been based on Monte Carlo simulations, which are very time consuming. Building on the recent progress on the theoretical analysis of image properties of statistical reconstructions and the development of numerical observers, here we develop a theoretical approach for fast computation of lesion detectability in Bayesian reconstruction. The results can be used to choose the optimum hyperparameter for the maximum lesion detectability. New in this work is the use of theoretical expressions that explicitly model the statistical variation of the lesion and background without assuming that the object variation is (locally) stationary. The theoretical results are validated using Monte Carlo simulations. The comparisons show good agreement between the theoretical predications and the Monte Carlo results

Invasive species control: incorporating demographic data and seed dispersal into a management model for Rhododendron ponticum

Rhododendron ponticum is a serious invasive alien plant in the British Isles and is of significant conservation and economic concern. Here, we integrate information on both the life-history and spatial dynamics of this species within an individual-based, spatially-explicit model and investigate the effectiveness of different control strategies. Importantly, we simulate seed movement and dispersal using a mechanistic seed dispersal model. We investigate the effectiveness of initiating control at the edge versus the core of the infestation, with and without returning each year to remove seedlings. We compare these results to an age-dependent strategy whereby the oldest plants are removed each year. Age-dependent control, in which the oldest plants were removed first, was the most effective strategy investigated, both in terms of the probability of successful eradication and the number of years taken to control. We demonstrate that this is because the older (and taller) plants towards the core produce more seeds that, on average, travel further. Indeed, our results suggest that the expansion of the invading front is actually driven as much by seeds that disperse long distances from these larger plants as by the seed rain from recently matured plants located much closer to the front. Finally, we investigate the potential use of ‘quarantine lines’ - corridors of unsuitable habitat that are sufficiently wide to contain an infestation, preventing spread to vulnerable areas. This study has provided generic insights into best practice for management based on the current understanding of the biology and ecology of this pernicious, invasive plant

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

A theoretical framework and research agenda for studying team attributions in sport

The attributions made for group outcomes have attracted a great deal of interest in recent years. In this article we bring together much of the current research on attribution theory in sport and outline a new conceptual framework and research agenda for investigating the attributions of team members. The proposed framework draws on multiple conceptual approaches including models of attribution, group dynamics and stress responses to provide a detailed hypothetical description of athletes' physiological, cognitive and affective responses to group competition. In describing this model we outline important antecedents of team attributions before hypothesising how attributions can impact hormonal and cardiovascular responses of athletes, together with cognitive (goals, choices, expectations), affective (self-esteem, emotions), and behavioural (approach-avoidance actions) responses of groups and group members. We conclude by outlining important methodological considerations and implications for structured context specific attribution-based interventions

FANCJ coordinates two pathways that maintain epigenetic stability at G-quadruplex DNA

We have previously reported that DT40 cells deficient in the Y-family polymerase REV1 are defective in replicating G-quadruplex DNA. In vivo this leads to uncoupling of DNA synthesis from redeposition of histones displaced ahead of the replication fork, which in turn leads to loss of transcriptional repression due to failure to recycle pre-existing repressive histone post-translational modifications. Here we report that a similar process can also affect transcriptionally active genes, leading to their deactivation. We use this finding to develop an assay based on loss of expression of a cell surface marker to monitor epigenetic instability at the level of single cells. This assay allows us to demonstrate G4 DNA motif-associated epigenetic instability in mutants of three helicases previously implicated in the unwinding of G-quadruplex structures, FANCJ, WRN and BLM. Transcriptional profiling of DT40 mutants reveals that FANCJ coordinates two independent mechanisms to maintain epigenetic stability near G4 DNA motifs that are dependent on either REV1 or on the WRN and BLM helicases, suggesting a model in which efficient in vivo replication of G-quadruplexes often requires the established 5′–3′-helicase activity of FANCJ acting in concert with either a specialized polymerase or helicase operating in the opposite polarity

Geography, institutions and development: a review ofthe long-run impacts of climate change

The links between climate change, economic growth and economic development have gained increasing attention over recent years in both the academic and policy literature. However, most of the existing literature has tended to focus on direct, short run effects of climate change on the economy, for example due to extreme weather events and changes in agricultural growing conditions. In this paper we review potential effects of climate change on the prospects for long-run economic development. These effects might operate directly, via the role of geography (including climate) as a fundamental determinant of relative prosperity, or indirectly by modifying the environmental context in which political and economic institutions evolve. We consider potential mechanisms from climate change to long-run economic development that have been relatively neglected to date, including, for instance, effects on the distribution of income and political power. We conclude with some suggestions for areas of future research

RANTES/CCL5 and risk for coronary events: Results from the MONICA/KORA Augsburg case-cohort, Athero-express and CARDIoGRAM studies

Background: The chemokine RANTES (regulated on activation, normal T-cell expressed and secreted)/CCL5 is involved in the pathogenesis of cardiovascular disease in mice, whereas less is known in humans. We hypothesised that its relevance for atherosclerosis should be reflected by associations between CCL5 gene variants, RANTES serum concentrations and protein levels in atherosclerotic plaques and risk for coronary events. Methods and Findings: We conducted a case-cohort study within the population-based MONICA/KORA Augsburg studies. Baseline RANTES serum levels were measured in 363 individuals with incident coronary events and 1,908 non-cases (mean follow-up: 10.2±