Anyons in a weakly interacting system

We describe a theoretical proposal for a system whose excitations are anyons with the exchange phase pi/4 and charge -e/2, but, remarkably, can be built by filling a set of single-particle states of essentially noninteracting electrons. The system consists of an artificially structured type-II superconducting film adjacent to a 2D electron gas in the integer quantum Hall regime with unit filling fraction. The proposal rests on the observation that a vacancy in an otherwise periodic vortex lattice in the superconductor creates a bound state in the 2DEG with total charge -e/2. A composite of this fractionally charged hole and the missing flux due to the vacancy behaves as an anyon. The proposed setup allows for manipulation of these anyons and could prove useful in various schemes for fault-tolerant topological quantum computation.Comment: 7 pages with 3 figures. For related work and info visit http://www.physics.ubc.ca/~fran

Conservation must capitalise on climate’s moment

The health of the natural environment has never been a greater concern, but attention to biodiversity loss is being eclipsed by the climate crisis. We argue that conservationists must seize the agenda to put biodiversity at the heart of climate policy

Eliminating the mystery from the concept of emergence

While some branches of complexity theory are advancing rapidly, the same cannot be said for our understanding of emergence. Despite a complete knowledge of the rules underlying the interactions between the parts of many systems, we are often baffled by their sudden transitions from simple to complex. Here I propose a solution to this conceptual problem. Given that emergence is often the result of many interactions occurring simultaneously in time and space, an ability to intuitively grasp it would require the ability to consciously think in parallel. A simple exercise is used to demonstrate that we do not possess this ability. Our surprise at the behaviour of cellular automata models, and the natural cases of pattern formation they mimic, is then explained from this perspective. This work suggests that the cognitive limitations of the mind can be as significant a barrier to scientific progress as the limitations of our senses

Robust Detection of Hierarchical Communities from Escherichia coli Gene Expression Data

Determining the functional structure of biological networks is a central goal of systems biology. One approach is to analyze gene expression data to infer a network of gene interactions on the basis of their correlated responses to environmental and genetic perturbations. The inferred network can then be analyzed to identify functional communities. However, commonly used algorithms can yield unreliable results due to experimental noise, algorithmic stochasticity, and the influence of arbitrarily chosen parameter values. Furthermore, the results obtained typically provide only a simplistic view of the network partitioned into disjoint communities and provide no information of the relationship between communities. Here, we present methods to robustly detect coregulated and functionally enriched gene communities and demonstrate their application and validity for Escherichia coli gene expression data. Applying a recently developed community detection algorithm to the network of interactions identified with the context likelihood of relatedness (CLR) method, we show that a hierarchy of network communities can be identified. These communities significantly enrich for gene ontology (GO) terms, consistent with them representing biologically meaningful groups. Further, analysis of the most significantly enriched communities identified several candidate new regulatory interactions. The robustness of our methods is demonstrated by showing that a core set of functional communities is reliably found when artificial noise, modeling experimental noise, is added to the data. We find that noise mainly acts conservatively, increasing the relatedness required for a network link to be reliably assigned and decreasing the size of the core communities, rather than causing association of genes into new communities.Comment: Due to appear in PLoS Computational Biology. Supplementary Figure S1 was not uploaded but is available by contacting the author. 27 pages, 5 figures, 15 supplementary file

Improved accuracy of multiple ncRNA alignment by incorporating structural information into a MAFFT-based framework

<p>Abstract</p> <p>Background</p> <p>Structural alignment of RNAs is becoming important, since the discovery of functional non-coding RNAs (ncRNAs). Recent studies, mainly based on various approximations of the Sankoff algorithm, have resulted in considerable improvement in the accuracy of pairwise structural alignment. In contrast, for the cases with more than two sequences, the practical merit of structural alignment remains unclear as compared to traditional sequence-based methods, although the importance of multiple structural alignment is widely recognized.</p> <p>Results</p> <p>We took a different approach from a straightforward extension of the Sankoff algorithm to the multiple alignments from the viewpoints of accuracy and time complexity. As a new option of the MAFFT alignment program, we developed a multiple RNA alignment framework, X-INS-i, which builds a multiple alignment with an iterative method incorporating structural information through two components: (1) pairwise structural alignments by an external pairwise alignment method such as SCARNA or LaRA and (2) a new objective function, Four-way Consistency, derived from the base-pairing probability of every sub-aligned group at every multiple alignment stage.</p> <p>Conclusion</p> <p>The BRAliBASE benchmark showed that X-INS-i outperforms other methods currently available in the sum-of-pairs score (SPS) criterion. As a basis for predicting common secondary structure, the accuracy of the present method is comparable to or rather higher than those of the current leading methods such as RNA Sampler. The X-INS-i framework can be used for building a multiple RNA alignment from any combination of algorithms for pairwise RNA alignment and base-pairing probability. The source code is available at the webpage found in the Availability and requirements section.</p

The Challenges, Opportunities, and Imperative of Structured Reporting in Medical Imaging

Despite dramatic innovation in medical imaging and information system technologies, the radiology report has remained stagnant for more than a century. Structured reporting was created in the hopes of addressing well-documented deficiencies in report content and organization but has largely failed in its adoption due to concerns over workflow and productivity. A number of political, economical, and clinical quality-centric initiatives are currently taking place within medicine which will dramatically change the medical landscape including Pay for Performance, Evidence-Based Medicine, and the Physician Quality Reporting Initiative. These will collectively enhance efforts to improve quality in reporting, stimulate new technology development, and counteract the impending threat of commoditization within radiology. Structured reporting offers a number of unique opportunities and advantages over traditional free text reporting and will provide a means for the radiology community to add value to its most important service deliverable the radiology report

The impact of radiotherapy in the treatment of desmoid tumours. An international survey of 110 patients. A study of the Rare Cancer Network

PURPOSE: A multi-centre study to assess the value of combined surgical resection and radiotherapy for the treatment of desmoid tumours. PATIENTS AND METHODS: One hundred and ten patients from several European countries qualified for this study. Pathology slides of all patients were reviewed by an independent pathologist. Sixty-eight patients received post-operative radiotherapy and 42 surgery only. Median follow-up was 6 years (1 to 44). The progression-free survival time (PFS) and prognostic factors were analysed. RESULTS: The combined treatment with radiotherapy showed a significantly longer progression-free survival than surgical resection alone (p smaller than 0.001). Extremities could be preserved in all patients treated with combined surgery and radiotherapy for tumours located in the limb, whereas amputation was necessary for 23% of patients treated with surgery alone. A comparison of PFS for tumour locations proved the abdominal wall to be a positive prognostic factor and a localization in the extremities to be a negative prognostic factor. Additional irradiation, a fraction size larger than or equal to 2 Gy and a total dose larger than 50 Gy to the tumour were found to be positive prognostic factors with a significantly lower risk for a recurrence in the univariate analysis. This analysis revealed radiotherapy at recurrence as a significantly worse prognostic factor compared with adjuvant radiotherapy. The addition of radiotherapy to the treatment concept was a positive prognostic factor in the multivariate analysis. CONCLUSION: Postoperative radiotherapy significantly improved the PFS compared to surgery alone. Therefore it should always be considered after a non-radical tumour resection and should be given preferably in an adjuvant setting. It is effective in limb preservation and for preserving the function of joints in situations where surgery alone would result in deficits, which is especially important in young patients

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

Robustness of Learning That Is Based on Covariance-Driven Synaptic Plasticity

It is widely believed that learning is due, at least in part, to long-lasting modifications of the strengths of synapses in the brain. Theoretical studies have shown that a family of synaptic plasticity rules, in which synaptic changes are driven by covariance, is particularly useful for many forms of learning, including associative memory, gradient estimation, and operant conditioning. Covariance-based plasticity is inherently sensitive. Even a slight mistuning of the parameters of a covariance-based plasticity rule is likely to result in substantial changes in synaptic efficacies. Therefore, the biological relevance of covariance-based plasticity models is questionable. Here, we study the effects of mistuning parameters of the plasticity rule in a decision making model in which synaptic plasticity is driven by the covariance of reward and neural activity. An exact covariance plasticity rule yields Herrnstein's matching law. We show that although the effect of slight mistuning of the plasticity rule on the synaptic efficacies is large, the behavioral effect is small. Thus, matching behavior is robust to mistuning of the parameters of the covariance-based plasticity rule. Furthermore, the mistuned covariance rule results in undermatching, which is consistent with experimentally observed behavior. These results substantiate the hypothesis that approximate covariance-based synaptic plasticity underlies operant conditioning. However, we show that the mistuning of the mean subtraction makes behavior sensitive to the mistuning of the properties of the decision making network. Thus, there is a tradeoff between the robustness of matching behavior to changes in the plasticity rule and its robustness to changes in the properties of the decision making network