647 research outputs found

    ¿Cómo influyen las limitaciones geométricas en las pautas de migración?

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    Null models exclusively invoking geometric constraints have recently been demonstrated to provide new insight as to what explains geographic patterns of species richness and range size distribution. Analyses of migration patterns have traditionally been conducted in the absence of appropriate simulations and analytical models. Here we present a null model exclusively invoking geometric constraints and a more advanced analytical model incorporating spread along a migration direction that allow investigation of the influence of physiographical and physiological boundaries for terrestria taxa, with ocean and sea as geometric constraints, in relation to observed patterns of migration. Our models take into account the low recovery probability of terrestrial taxa over sea. The null model was not found to explain any of the directional variation in the ring–recoveries, but when comparing the distribution of data modeled using a simple clock–and–compass model with distributions of ring–recoveries, geometric constraints were found to explain up to 22% of the variation in ring–recoveries. However, the assumed directional concentrations per step used in the model were much higher than expected, and the qualitative fit of the model was rather poor even when non–terrestrial sites of recoveries were excluded.Recientemente se ha demostrado que los modelos nulos que recurren exclusivamente a las limitaciones geométricas proporcionan nuevas aportaciones para explicar las pautas geográficas que definen la riqueza de las especies y la distribución por tamaños según el rango. Tradicionalmente, los análisis de pautas de migración se han realizado sin emplear simulaciones ni modelos analíticos apropiados. En este estudio presentamos un modelo nulo que se basa exclusivamente en limitaciones geométricas, así como un modelo analítico más avanzado que incorpora la dispersión y una dirección de migración, lo que permite investigar la influencia de los límites fisiográficos y fisiológicos en los taxones terrestres, tomando el océano y el mar como limitaciones geométricas, con relación a las pautas de migración observadas. Los modelos que hemos empleado tienen en cuenta la baja probabilidad de recuperación de los taxones terrestres en el mar. El modelo nulo no pudo explicar ninguna de las variaciones direccionales en las recuperaciones de anillas; sin embargo, al comparar la distribución de los datos modelados utilizando un modelo simple de reloj y brújula con distribuciones de recuperaciones de anillas, se constató que las limitaciones geométricas podían explicar hasta el 22% de la variación en las recuperaciones de anillas. Pese a ello, las concentraciones direccionales por pasos que se presupusieron en el modelo fueron muy superiores a lo previsto, y el ajuste cualitativo del mismo resultó bastante deficiente cuando se excluyeron los emplazamientos de recuperaciones no terrestres

    Development and critical evaluation of a generic 2-D agro-hydrological model (SMCR_N) for the responses of crop yield and nitrogen composition to nitrogen fertilizer

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    Models play an important role in optimizing fertilizer use in agriculture to maintain sustainable crop production and to minimize the risk to the environment. In this study, we present a new Simulation Model for Crop Response to Nitrogen fertilizer (SMCR_N). The SMCR_N model, based on the recently developed model EU-Rotate_N for the N-economies of a wide range of crops and cropping systems, includes new modules for the estimation of N in the roots and an associated treatment of the recovery of soil mineral N by crops, for the reduction of growth rates by excessive fertilizer-N, and for the N mineralization from soil organic matter. The validity of the model was tested against the results from 32 multi-level fertilizer experiments on 16 different crop species. For this exercise none of the coefficients or parameters in the model was adjusted to improve the agreement between measurement and simulation. Over the practical range of fertilizer-N levels model predictions were, with few exceptions, in good agreement with measurements of crop dry weight (excluding fibrous roots) and its %N. The model considered that the entire reduction of soil inorganic N during growth was due to the sum of nitrate leaching, retention of N in fibrous roots and N uptake by the rest of the plant. The good agreement between the measured and simulated uptakes suggests that in this arable soil, losses of N from other soil processes were small. At high levels of fertilizer-N yields were dominated by the negative osmotic effect of fertilizer-N and model predictions for some crops were poor. However, the predictions were significantly improved by using a different value for the coefficient defining the osmotic effect for saline sensitive crops. The developed model SMCR_N uses generally readily available inputs, and is more mechanistic than most agronomic models and thus has the potential to be used as a tool for optimizing fertilizer practice

    Efficient algorithms for tensor scaling, quantum marginals and moment polytopes

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    We present a polynomial time algorithm to approximately scale tensors of any format to arbitrary prescribed marginals (whenever possible). This unifies and generalizes a sequence of past works on matrix, operator and tensor scaling. Our algorithm provides an efficient weak membership oracle for the associated moment polytopes, an important family of implicitly-defined convex polytopes with exponentially many facets and a wide range of applications. These include the entanglement polytopes from quantum information theory (in particular, we obtain an efficient solution to the notorious one-body quantum marginal problem) and the Kronecker polytopes from representation theory (which capture the asymptotic support of Kronecker coefficients). Our algorithm can be applied to succinct descriptions of the input tensor whenever the marginals can be efficiently computed, as in the important case of matrix product states or tensor-train decompositions, widely used in computational physics and numerical mathematics. We strengthen and generalize the alternating minimization approach of previous papers by introducing the theory of highest weight vectors from representation theory into the numerical optimization framework. We show that highest weight vectors are natural potential functions for scaling algorithms and prove new bounds on their evaluations to obtain polynomial-time convergence. Our techniques are general and we believe that they will be instrumental to obtain efficient algorithms for moment polytopes beyond the ones consider here, and more broadly, for other optimization problems possessing natural symmetries

    Decremental All-Pairs ALL Shortest Paths and Betweenness Centrality

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    We consider the all pairs all shortest paths (APASP) problem, which maintains the shortest path dag rooted at every vertex in a directed graph G=(V,E) with positive edge weights. For this problem we present a decremental algorithm (that supports the deletion of a vertex, or weight increases on edges incident to a vertex). Our algorithm runs in amortized O(\vstar^2 \cdot \log n) time per update, where n=|V|, and \vstar bounds the number of edges that lie on shortest paths through any given vertex. Our APASP algorithm can be used for the decremental computation of betweenness centrality (BC), a graph parameter that is widely used in the analysis of large complex networks. No nontrivial decremental algorithm for either problem was known prior to our work. Our method is a generalization of the decremental algorithm of Demetrescu and Italiano [DI04] for unique shortest paths, and for graphs with \vstar =O(n), we match the bound in [DI04]. Thus for graphs with a constant number of shortest paths between any pair of vertices, our algorithm maintains APASP and BC scores in amortized time O(n^2 \log n) under decremental updates, regardless of the number of edges in the graph.Comment: An extended abstract of this paper will appear in Proc. ISAAC 201

    Sparse Fault-Tolerant BFS Trees

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    This paper addresses the problem of designing a sparse {\em fault-tolerant} BFS tree, or {\em FT-BFS tree} for short, namely, a sparse subgraph TT of the given network GG such that subsequent to the failure of a single edge or vertex, the surviving part TT' of TT still contains a BFS spanning tree for (the surviving part of) GG. Our main results are as follows. We present an algorithm that for every nn-vertex graph GG and source node ss constructs a (single edge failure) FT-BFS tree rooted at ss with O(n \cdot \min\{\Depth(s), \sqrt{n}\}) edges, where \Depth(s) is the depth of the BFS tree rooted at ss. This result is complemented by a matching lower bound, showing that there exist nn-vertex graphs with a source node ss for which any edge (or vertex) FT-BFS tree rooted at ss has Ω(n3/2)\Omega(n^{3/2}) edges. We then consider {\em fault-tolerant multi-source BFS trees}, or {\em FT-MBFS trees} for short, aiming to provide (following a failure) a BFS tree rooted at each source sSs\in S for some subset of sources SVS\subseteq V. Again, tight bounds are provided, showing that there exists a poly-time algorithm that for every nn-vertex graph and source set SVS \subseteq V of size σ\sigma constructs a (single failure) FT-MBFS tree T(S)T^*(S) from each source siSs_i \in S, with O(σn3/2)O(\sqrt{\sigma} \cdot n^{3/2}) edges, and on the other hand there exist nn-vertex graphs with source sets SVS \subseteq V of cardinality σ\sigma, on which any FT-MBFS tree from SS has Ω(σn3/2)\Omega(\sqrt{\sigma}\cdot n^{3/2}) edges. Finally, we propose an O(logn)O(\log n) approximation algorithm for constructing FT-BFS and FT-MBFS structures. The latter is complemented by a hardness result stating that there exists no Ω(logn)\Omega(\log n) approximation algorithm for these problems under standard complexity assumptions

    Who are the cable bacteria?

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    Speeding up shortest path algorithms

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    Given an arbitrary, non-negatively weighted, directed graph G=(V,E)G=(V,E) we present an algorithm that computes all pairs shortest paths in time O(mn+mlgn+nTψ(m,n))\mathcal{O}(m^* n + m \lg n + nT_\psi(m^*, n)), where mm^* is the number of different edges contained in shortest paths and Tψ(m,n)T_\psi(m^*, n) is a running time of an algorithm to solve a single-source shortest path problem (SSSP). This is a substantial improvement over a trivial nn times application of ψ\psi that runs in O(nTψ(m,n))\mathcal{O}(nT_\psi(m,n)). In our algorithm we use ψ\psi as a black box and hence any improvement on ψ\psi results also in improvement of our algorithm. Furthermore, a combination of our method, Johnson's reweighting technique and topological sorting results in an O(mn+mlgn)\mathcal{O}(m^*n + m \lg n) all-pairs shortest path algorithm for arbitrarily-weighted directed acyclic graphs. In addition, we also point out a connection between the complexity of a certain sorting problem defined on shortest paths and SSSP.Comment: 10 page

    EU-Rotate_N – a decision support system – to predict environmental and economic consequences of the management of nitrogen fertiliser in crop rotations

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    A model has been developed which assesses the economic and environmental performance of crop rotations, in both conventional and organic cropping, for over 70 arable and horticultural crops, and a wide range of growing conditions in Europe. The model, though originally based on the N_ABLE model, has been completely rewritten and contains new routines to simulate root development, the mineralisation and release of nitrogen (N) from soil organic matter and crop residues, and water dynamics in soil. New routines have been added to estimate the effects of sub-optimal rates of N and spacing on the marketable outputs and gross margins. The model provides a mechanism for generating scenarios to represent a range of differing crop and fertiliser management strategies which can be used to evaluate their effects on yield, gross margin and losses of nitrogen through leaching. Such testing has revealed that nitrogen management can be improved and that there is potential to increase gross margins whilst reducing nitrogen losses

    Evaluation of a method for determining binaural sensitivity to temporal fine structure (TFS-AF test) for older listeners with normal and impaired low-frequency hearing

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    The ability to process binaural temporal fine structure (TFS) information was assessed using the TFS-AF test (where AF stands for adaptive frequency) for 26 listeners aged 60 years or more with normal or elevated low-frequency audiometric thresholds. The test estimates the highest frequency at which a fixed interaural phase difference (IPD) of ϕ (varied here between 30° and 180°) can be discriminated from an IPD of 0°, with higher thresholds indicating better performance. A sensation level of 30 dB was used. All listeners were able to perform the task reliably, giving thresholds well above the lowest allowed frequency of 30 Hz. The duration of a run averaged 5 min. Repeated testing of the normal-hearing listeners showed no significant practice effects. Thresholds varied markedly across listeners, but their ranking was fairly consistent across values of ϕ. Thresholds decreased (worsened) with decreasing ϕ and were lower than for a group of young listeners tested in an earlier study. There were weak to moderate, negative correlations between TFS-AF thresholds and audiometric thresholds at low frequencies (125–1000 Hz) but not at high frequencies (4000–8000 Hz). In conclusion, the TFS-AF test yielded a graded measure of binaural TFS sensitivity for all listeners. This contrasts with the TFS-LF (low-frequency) test, which measures the smallest detectable shift in IPD for a fixed frequency. The absence of practice effects and a reasonably short administration time make the TFS-AF test a good candidate for the assessment of sensitivity to changes in binaural TFS for older listeners without or with hearing loss

    Search in Complex Networks : a New Method of Naming

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    We suggest a method for routing when the source does not posses full information about the shortest path to the destination. The method is particularly useful for scale-free networks, and exploits its unique characteristics. By assigning new (short) names to nodes (aka labelling) we are able to reduce significantly the memory requirement at the routers, yet we succeed in routing with high probability through paths very close in distance to the shortest ones.Comment: 5 pages, 4 figure
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