Effects of damming on population sustainability of Chinese sturgeon, Acipenser sinensis: evaluation of optimal conservation measures

The numbers of spawning sites for Chinese sturgeon have been drastically reduced since the construction of the Gezhouba Dam across the Yangtze River. This dam has blocked migration of Chinese sturgeon to their historic spawning ground causing a significant decline of the Chinese sturgeon population. We conducted a VORTEX population viability analysis to estimate the sustainability of the population and to quantify the efficiency of current and alternative conservation procedures. The model predicted the observed decline of Chinese sturgeon, resulting from the effect of the Gezhouba Dam. These simulations demonstrated the potential interest of two conservation measures: increasing spawning area and reducing predation on sturgeon eggs. The simulations also demonstrated that the actual restocking program is not sufficient to sustain sturgeon population as the artificial reproduction program induce the loss of more wild mature adults that the recruitment expected by the artificial reproduction.

Optimal displacement mechanisms beneath shallow foundations on linear-elastic perfectly plastic soil

An energy method for a linear-elastic perfectly plastic method utilising the von Mises yield criterion with associated flow developed in 2013 by McMahon and co-workers is used to compare the ellipsoidal cavity-expansion mechanism, from the same work, and the displacement fields of other research by Levin, in 1995, and Osman and Bolton, in 2005, which utilise the Hill and Prandtl mechanisms respectively. The energy method was also used with a mechanism produced by performing a linear-elastic finite-element analysis in Abaqus. At small values of settlement and soil rigidity the elastic mechanism provides the lowest upper-bound solution, and matches well with finite-element analysis results published in the literature. At typical footing working loads and settlements the cavity-expansion mechanism produces a more optimal solution than the displacement fields within the Hill and Prandtl mechanisms, and also matches well with the published finite-element analysis results in this range. Beyond these loads, at greater footing settlements, or soil rigidity, the Prandtl mechanism is shown to be the most appropriate.

Optimal data fitting on lie groups: A coset approach

This work considers the problem of fitting data on a Lie group by a coset of a compact subgroup. This problem can be seen as an extension of the problem of fitting affine subspaces in n to data which can be solved using principal component analysis. We show how the fitting problem can be reduced for biinvariant distances to a generalized mean calculation on an homogeneous space. For biinvariant Riemannian distances we provide an algorithm based on the Karcher mean gradient algorithm. We illustrate our approach by some examples on SO(n). © 2010 Springer -Verlag Berlin Heidelberg.

High-performance bowing machine tests of bowed-string transients

The development is described of a computer-controlled bowing machine that can bow a string with a range of gestures that match or exceed the capabilities of a human violinist. Example measurements of string vibration under controlled bowing conditions are shown, including a Schelleng diagram and a set of Guettler diagrams, for the open D string of a cello. For some results a rosin-coated rod was used in place of a conventional bow, to provide quantitative data for comparison with theoretical predictions. The results show qualitative consistency with the predictions of Schelleng and Guettler, but details are revealed that go beyond the limitations of existing models. © S. Hirzel Verlag · EAA.

Optimal recall from bounded metaplastic synapses: predicting functional adaptations in hippocampal area CA3.

A venerable history of classical work on autoassociative memory has significantly shaped our understanding of several features of the hippocampus, and most prominently of its CA3 area, in relation to memory storage and retrieval. However, existing theories of hippocampal memory processing ignore a key biological constraint affecting memory storage in neural circuits: the bounded dynamical range of synapses. Recent treatments based on the notion of metaplasticity provide a powerful model for individual bounded synapses; however, their implications for the ability of the hippocampus to retrieve memories well and the dynamics of neurons associated with that retrieval are both unknown. Here, we develop a theoretical framework for memory storage and recall with bounded synapses. We formulate the recall of a previously stored pattern from a noisy recall cue and limited-capacity (and therefore lossy) synapses as a probabilistic inference problem, and derive neural dynamics that implement approximate inference algorithms to solve this problem efficiently. In particular, for binary synapses with metaplastic states, we demonstrate for the first time that memories can be efficiently read out with biologically plausible network dynamics that are completely constrained by the synaptic plasticity rule, and the statistics of the stored patterns and of the recall cue. Our theory organises into a coherent framework a wide range of existing data about the regulation of excitability, feedback inhibition, and network oscillations in area CA3, and makes novel and directly testable predictions that can guide future experiments.

Optimal teleportation via thermal entangled states of a two-qubit Heisenberg chain

We study the optimal teleportation based on Bell measurements via the thermal states of a two-qubit Heisenberg XXX chain in the presence of the Dzyaloshinsky-Moriya (DM) anisotropic antisymmetric interaction and obtain an optimal unitary transformation. The explicit expressions of the output state and the teleportation fidelity are presented and compared with those of the standard protocol. It is shown that in this protocol the teleportation fidelity is always larger and the unit fidelity is achieved at zero temperature. The DM interaction can enhance the teleportation fidelity at finite temperatures, as opposed to the effect of the interaction in the standard protocol. Cases with other types of anisotropies are also discussed. Copyright (C) EPLA, 2009

Optimal distance from high power laser diode to cylindrical microlens in a coupling system

In a practical coupling system, a cylindrical microlens is used to collimate the emission of a high powerlaser diode (LD) in the dimension perpendicular to the junction plane. Using passive alignment, the LD isplaced in the focus of the cylindrical microlens generally, regardless of the performance of the multimodeoptical fiber and the LD. In this paper, a more complete analysis is arrived at by ray-tracing technique,by which the angle θ of the ray after refraction is computed as a function of the angle θo of the ray beforerefraction. The focus of the cylindrical microlens is not always the optimal position of the LD. In fact, inorder to achieve a higher coupling efficiency, the optimal distance from the LD to the cylindrical microlensis dependent on not only the radius R and the index of refraction n of the cylindrical microlens, but alsothe divergence angle of the LD in the dimension perpendicular to the junction plane and the numericalaperture (NA) of the multimode optical fiber. The results of this discussion are in good agreement withexperimental results.

Biomimetic (topological) pattern recognition - A new model of pattern recognition theory and its application

A new theoretical model of Pattern Recognition principles was proposed, which is based on "matter cognition" instead of "matter classification" in traditional statistical Pattern Recognition. This new model is closer to the function of human being, rather than traditional statistical Pattern Recognition using "optimal separating" as its main principle. So the new model of Pattern Recognition is called the Biomimetic Pattern Recognition (BPR)(1). Its mathematical basis is placed on topological analysis of the sample set in the high dimensional feature space. Therefore, it is also called the Topological Pattern Recognition (TPR). The fundamental idea of this model is based on the fact of the continuity in the feature space of any one of the certain kinds of samples. We experimented with the Biomimetic Pattern Recognition (BPR) by using artificial neural networks, which act through covering the high dimensional geometrical distribution of the sample set in the feature space. Onmidirectionally cognitive tests were done on various kinds of animal and vehicle models of rather similar shapes. For the total 8800 tests, the correct recognition rate is 99.87%. The rejection rate is 0.13% and on the condition of zero error rates, the correct rate of BPR was much better than that of RBF-SVM.

Intelligent control of avalanched photodiode to get optimal state

To improve the sensitivity of our laser radar system, we provided a set of control method for APDs (Avalanched Photodiodes) based on single-chip computer together with the circuits dealing with noise and temperature. It adjusts the voltages intelligently and maintains the APD's optimal working status.