811 research outputs found

    img2net: Automated network-based analysis of imaged phenotypes

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    Automated analysis of imaged phenotypes enables fast and reproducible quantification of biologically relevant features. Despite recent developments, recordings of complex, networked structures, such as: leaf venation patterns, cytoskeletal structures, or traffic networks, remain challenging to analyze. Here we illustrate the applicability of img2net to automatedly analyze such structures by reconstructing the underlying network, computing relevant network properties, and statistically comparing networks of different types or under different conditions. The software can be readily used for analyzing image data of arbitrary 2D and 3D network-like structures. img2net is open-source software under the GPL and can be downloaded from http://mathbiol.mpimp-golm.mpg.de/img2net/, where supplementary information and data sets for testing are provided.Comment: Bioinformatics, 2014, btu50

    Statistical physics of neural systems with non-additive dendritic coupling

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    How neurons process their inputs crucially determines the dynamics of biological and artificial neural networks. In such neural and neural-like systems, synaptic input is typically considered to be merely transmitted linearly or sublinearly by the dendritic compartments. Yet, single-neuron experiments report pronounced supralinear dendritic summation of sufficiently synchronous and spatially close-by inputs. Here, we provide a statistical physics approach to study the impact of such non-additive dendritic processing on single neuron responses and the performance of associative memory tasks in artificial neural networks. First, we compute the effect of random input to a neuron incorporating nonlinear dendrites. This approach is independent of the details of the neuronal dynamics. Second, we use those results to study the impact of dendritic nonlinearities on the network dynamics in a paradigmatic model for associative memory, both numerically and analytically. We find that dendritic nonlinearities maintain network convergence and increase the robustness of memory performance against noise. Interestingly, an intermediate number of dendritic branches is optimal for memory functionality

    Reduced density matrix hybrid approach: Application to electronic energy transfer

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    Electronic energy transfer in the condensed phase, such as that occurring in photosynthetic complexes, frequently occurs in regimes where the energy scales of the system and environment are similar. This situation provides a challenge to theoretical investigation since most approaches are accurate only when a certain energetic parameter is small compared to others in the problem. Here we show that in these difficult regimes, the Ehrenfest approach provides a good starting point for a dynamical description of the energy transfer process due to its ability to accurately treat coupling to slow environmental modes. To further improve on the accuracy of the Ehrenfest approach, we use our reduced density matrix hybrid framework to treat the faster environmental modes quantum mechanically, at the level of a perturbative master equation. This combined approach is shown to provide an efficient and quantitative description of electronic energy transfer in a model dimer and the Fenna-Matthews-Olson complex and is used to investigate the effect of environmental preparation on the resulting dynamics.Comment: 11 pages, 8 figure

    Sector skills insights : construction

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    The UK Commission for Employment and Skills is a social partnership, led by Commissioners from large and small employers, trade unions and the voluntary sector. Our mission is to raise skill levels to help drive enterprise, create more and better jobs and promote economic growth. Our strategic objectives are to: • Provide outstanding labour market intelligence which helps businesses and people make the best choices for them; • Work with businesses to develop the best market solutions which leverage greater investment in skills; • Maximise the impact of employment and skills policies and employer behaviour to support jobs and growth and secure an internationally competitive skills base. These strategic objectives are supported by a research programme that provides a robust evidence base for our insights and actions and which draws on good practice and the most innovative thinking. The research programme is underpinned by a number of core principles including the importance of: ensuring ‘relevance ’ to our most pressing strategic priorities; ‘salience ’ and effectively translating and sharing the key insights we find; internationa

    Area law for fixed points of rapidly mixing dissipative quantum systems

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    We prove an area law with a logarithmic correction for the mutual information for fixed points of local dissipative quantum system satisfying a rapid mixing condition, under either of the following assumptions: the fixed point is pure, or the system is frustration free.Comment: 17 pages, 1 figure. Final versio

    Bloch-Redfield equations for modeling light-harvesting complexes

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    We challenge the misconception that Bloch-Redfield equations are a less powerful tool than phenomenological Lindblad equations for modeling exciton transport in photosynthetic complexes. This view predominantly originates from an indiscriminate use of the secular approximation. We provide a detailed description of how to model both coherent oscillations and several types of noise, giving explicit examples. All issues with non-positivity are overcome by a consistent straightforward physical noise model. Herein also lies the strength of the Bloch-Redfield approach because it facilitates the analysis of noise-effects by linking them back to physical parameters of the noise environment. This includes temporal and spatial correlations and the strength and type of interaction between the noise and the system of interest. Finally we analyze a prototypical dimer system as well as a 7-site Fenna-Matthews-Olson (FMO) complex in regards to spatial correlation length of the noise, noise strength, temperature and their connection to the transfer time and transfer

    Constraining a complex biogeochemical model for COâ‚‚ and Nâ‚‚O emission simulations from various land uses by model-data fusion

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    This study presents the results of a combined measurement and modelling strategy to analyse N₂O and CO₂ emissions from adjacent arable land, forest and grassland sites in Hesse, Germany. The measured emissions reveal seasonal patterns and management effects, including fertilizer application, tillage, harvest and grazing. The measured annual N₂O fluxes are 4.5, 0.4 and 0.1 kg N ha−1^{-1} a−1^{-1}, and the CO₂ fluxes are 20.0, 12.2 and 3.0 t C ha−1^{-1} a−1^{-1} for the arable land, grassland and forest sites, respectively. An innovative model–data fusion concept based on a multicriteria evaluation (soil moisture at different depths, yield, CO₂ and N₂O emissions) is used to rigorously test the LandscapeDNDC biogeochemical model. The model is run in a Latin-hypercube-based uncertainty analysis framework to constrain model parameter uncertainty and derive behavioural model runs. The results indicate that the model is generally capable of predicting trace gas emissions, as evaluated with RMSE as the objective function. The model shows a reasonable performance in simulating the ecosystem C and N balances. The model–data fusion concept helps to detect remaining model errors, such as missing (e.g. freeze–thaw cycling) or incomplete model processes (e.g. respiration rates after harvest). This concept further elucidates the identification of missing model input sources (e.g. the uptake of N through shallow groundwater on grassland during the vegetation period) and uncertainty in the measured validation data (e.g. forest N₂O emissions in winter months). Guidance is provided to improve the model structure and field measurements to further advance landscape-scale model predictions

    A review of volatiles in the Martian interior

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    Multiple observations from missions to Mars have revealed compelling evidence for a volatile-rich Martian crust. A leading theory contends that eruption of basaltic magmas was the ultimate mechanism of transfer of volatiles from the mantle toward the surface after an initial outgassing related to the crystallization of a magma ocean. However, the concentrations of volatile species in ascending magmas and in their mantle source regions are highly uncertain. This work and this special issue of Meteoritics & Planetary Science summarize the key findings of the workshop on Volatiles in the Martian Interior (Nov. 3–4, 2014), the primary open questions related to volatiles in Martian magmas and their source regions, and the suggestions of the community at the workshop to address these open questions
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