The Gini-Simpson quadratic index is a classic measure of diversity, widely used by ecologists. As shown recently, however, this index is not suitable for the measurement of beta diversity when the number of species is...
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The Gini-Simpson quadratic index is a classic measure of diversity, widely used by ecologists. As shown recently, however, this index is not suitable for the measurement of beta diversity when the number of species is very large. The objective of this paper is to introduce the Rich- Gini-Simpson quadratic index which preserves all the qualities of the classic Gini-Simpson index but behaves very well even when the number of species is very large. The additive partitioning of species diversity using the Rich-Gini- Simpson quadratic index and an application from island biogeography are analyzed.
A controlled quantum system possesses a search landscape defined by the observable value as a functional of the control field. Within the search landscape, there exist level sets of controls giving the same observable...
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A controlled quantum system possesses a search landscape defined by the observable value as a functional of the control field. Within the search landscape, there exist level sets of controls giving the same observable value. This paper focuses on level sets of the transition probability P i¿f . For transition probabilities 0 < P i¿f < 1, a first order diffeomorphic modulation observable response preserving homotopy (D-MORPH) algorithm is utilized to investigate level sets. At the top of the control landscape, P i¿f = 1, a second order D-MORPH algorithm is presented that can explore the perfect control level set. D-MORPH is utilized to identify level set members that exhibit certain desirable secondary characteristics, e.g., minimal pulse fluence. Numerical simulations for finite level systems are presented to illustrate the variety of control behavior found across level set members.
In the first part of this series of two papers [Y. Jiao, F. H. Stillinger, and S. Torquato, Phys. Rev. E 81, 011105 (2010)], we considered the geometrical ambiguity of pair statistics associated with point configurati...
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In the first part of this series of two papers [Y. Jiao, F. H. Stillinger, and S. Torquato, Phys. Rev. E 81, 011105 (2010)], we considered the geometrical ambiguity of pair statistics associated with point configurations. Here we focus on the analogous problem for heterogeneous media (materials). Heterogeneous media are ubiquitous in a host of contexts, including composites and granular media, biological tissues, ecological patterns, and astrophysical structures. The complex structures of heterogeneous media are usually characterized via statistical descriptors, such as the n-point correlation function Sn. An intricate inverse problem of practical importance is to what extent a medium can be reconstructed from the two-point correlation function S2 of a target medium. Recently, general claims of the uniqueness of reconstructions using S2 have been made based on numerical studies, which implies that S2 suffices to uniquely determine the structure of a medium within certain numerical accuracy. In this paper, we provide a systematic approach to characterize the geometrical ambiguity of S2 for both continuous two-phase heterogeneous media and their digitized representations in a mathematically precise way. In particular, we derive the exact conditions for the case where two distinct media possess identical S2, i.e., they form a degenerate pair. The degeneracy conditions are given in terms of integral and algebraic equations for continuous media and their digitized representations, respectively. By examining these equations and constructing their rigorous solutions for specific examples, we conclusively show that in general S2 is indeed not sufficient information to uniquely determine the structure of the medium, which is consistent with the results of our recent study on heterogeneous-media reconstruction [Y. Jiao, F. H. Stillinger, and S. Torquato, Proc. Natl. Acad. Sci. U.S.A. 106, 17634 (2009)]. The analytical examples include complex patterns composed of building blo
Compositional lipid microdomains (“lipid rafts”) in mammalian plasma membranes are believed to facilitate many important cellular processes. While several physically distinct scenarios predicting the presence of fin...
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Compositional lipid microdomains (“lipid rafts”) in mammalian plasma membranes are believed to facilitate many important cellular processes. While several physically distinct scenarios predicting the presence of finite-sized microdomains in vivo have been proposed in the past, direct experimental verification or falsification of model predictions has remained elusive. Herein, we demonstrate that the combination of the spatial correlation and temporal fluctuation spectra of the lipid domains can be employed to unambiguously differentiate between the existing theoretical scenarios. Furthermore, the differentiation of the raft formation mechanisms using this methodology can be achieved by collecting data at physiologically relevant conditions without the need to tune control parameters.
Compositional lipid domains (lipid rafts) in plasma membranes are believed to be important components of many cellular processes. The mechanisms by which cells regulate the sizes, lifetimes, and spatial localization o...
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Compositional lipid domains (lipid rafts) in plasma membranes are believed to be important components of many cellular processes. The mechanisms by which cells regulate the sizes, lifetimes, and spatial localization of these domains are rather poorly understood at the moment. We propose a robust mechanism for the formation of finite-sized lipid raft domains in plasma membranes, the competition between phase separation in an immiscible lipid system and active cellular lipid transport processes naturally leads to the formation of such domains. Simulations of a continuum model reveal that the raft size distribution is broad and the average raft size is strongly dependent on the rates of cellular and interlayer lipid transport processes. We demonstrate that spatiotemporal variations in the recycling may enable the cell to localize larger raft aggregates at specific parts along the membrane. Moreover, we show that membrane compartmentalization may further facilitate spatial localization of the raft domains. Finally, we demonstrate that local interactions with immobile membrane proteins can spatially localize the rafts and lead to further clustering.
We analyze numerically the mechanisms controlling the spacing of chimneys—channels devoid of solid—in two-dimensional mushy layers formed by solidifying a binary alloy. Chimneys are the principal conduits through wh...
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We analyze numerically the mechanisms controlling the spacing of chimneys—channels devoid of solid—in two-dimensional mushy layers formed by solidifying a binary alloy. Chimneys are the principal conduits through which buoyancy effects material transport out of the mushy layer and into the liquid from which it formed. Experiments show a coarsening of chimney spacing; we pursue the hypothesis that the spacing adjusts to optimize material transport and hence maximize the rate of removal of potential energy stored in the mushy layer. The optimal solute flux increases approximately linearly with the mush Rayleigh number. However, for spacings below a critical value, the chimneys collapse and solute fluxes cease, revealing a hysteresis between chimney convection and no flow. The results are consistent with a variational principle controlling the dynamics of this dissipative system.
With the increased availability of rich behavioral data sets, we present a novel combination of tools to analyze to analyze this information. Using criminal offense records as an example, we employ cross-correlation m...
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In this paper, a large scale Medium Voltage DC all-electric ship integrated power system is modeled from the prime mover (gas turbine) to the propulsion load. This system has a three-phase 21MW synchronous machine as ...
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ISBN:
(纸本)9781617387043
In this paper, a large scale Medium Voltage DC all-electric ship integrated power system is modeled from the prime mover (gas turbine) to the propulsion load. This system has a three-phase 21MW synchronous machine as a main generator and a three-phase 19MW induction motor as a main propulsion drive. The influence of propeller emergence on both electrical and mechanical components of the system is investigated.
We consider the problem of tracking the state of a hybrid system capable of performing a bounded number of mode switches. The system is assumed to follow either a nominal or an anomalous model, where the nominal model...
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We consider the problem of tracking the state of a hybrid system capable of performing a bounded number of mode switches. The system is assumed to follow either a nominal or an anomalous model, where the nominal model may stand for, e.g., the non-maneuvering motion regime of a target or the fault-free operation mode of a sensor, and the anomalous model may stand for, e.g., the abrupt evasive maneuvers of a target or the faulty operation of a sensor. As is well known, the optimal algorithm requires implementation of an exponentially growing number of primitive Kalman filters. On the other hand, the system's switching dynamics is not Markov because of the a priori bounded number of model switches, thus ruling out the use of popular estimation schemes such as the interacting multiple model (IMM) and generalized pseudo-Bayesian (GPB) filters. We derive an efficient scheme that uses a number of primitive Kalman filters that is linear in the number of possible maneuvers. The scheme resembles the IMM algorithm in that it uses interaction between some of the primitive filters before every estimation cycle, thus reducing the number of such filters. The algorithm's performance is evaluated via a simulation study, and shown to outperform the state-of-the-art IMM filter in a typical example.
This paper develops a new class of algorithms for signal recovery in the distributed compressive sensing (DCS) framework. DCS exploits both intra-signal and inter-signal correlations through the concept of joint spars...
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ISBN:
(纸本)9781424442959
This paper develops a new class of algorithms for signal recovery in the distributed compressive sensing (DCS) framework. DCS exploits both intra-signal and inter-signal correlations through the concept of joint sparsity to further reduce the number of measurements required for recovery. DCS is well-suited for sensor network applications due to its universality, computational asymmetry, tolerance to quantization and noise, and robustness to measurement loss. In this paper we propose recovery algorithms for the sparse common and innovation joint sparsity model. Our approach leads to a class of efficient algorithms, the Texas Hold 'Em algorithms, which are scalable both in terms of communication bandwidth and computational complexity.
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