12 resultados para Consensus measures

em Chinese Academy of Sciences Institutional Repositories Grid Portal


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It is extremely difficult to explore mRNA folding structure by biological experiments. In this report, we use stochastic sampling and folding simulation to test the existence of the stable secondary structural units of-mRNA, look for the folding units, and explore the probabilistic stabilization of the units. Using this method, We made simulations for all possible local optimum secondary structures of a single strand mRNA within a certain range, and searched for the common parts of the secondary structures. The consensus secondary structure units (CSSUs) extracted from the above method are mainly hairpins, with a few single strands. These CSSUs suggest that the mRNA folding units could be relatively stable and could perform specific biological function. The significance of these observations for the mRNA folding problem in general is also discussed. (c) 2004 Elsevier B.V. All rights reserved.

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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.

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We propose a more general method for detecting a set of entanglement measures, i.e., negativities, in an arbitrary tripartite quantum state by local operations and classical communication. To accomplish the detection task using this method, three observers do not need to perform partial transposition maps by the structural physical approximation; instead, they only need to collectively measure some functions via three local networks supplemented by a classical communication. With these functions, they are able to determine the set of negativities related to the tripartite quantum state.

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Numerous measures are used in the literature to describe the grain-size distribution of sediments. Consideration of these measures indicates that parameters computed from quartiles may not be as significant as those based on more rigorous statistical concepts. In addition, the lack of standardization of descriptive measures has resulted in limited application of the findings from one locality to another. The use of five parameters that serve as approximate graphic analogies to the moment measures commonly employed in statistics is recommended. The parameters are computed from five percentile diameters obtained from the cumulative size-frequency curve of a sediment. They include the mean (or median) diameter, standard deviation, kurtosis, and two measures of skewness, the second measure being sensitive to skew properties of the "tails" of the sediment distribution. If the five descriptive measures are listed for a sediment, it is possible to compute the five percentile diameters on which they are based (phi 5 , phi 16 , phi 50 , phi 84 , and phi 95 ), and hence five significant points on the cumulative carve of the sediment. This increases the value of the data listed for a sediment in a report, and in many cases eliminates the necessity of including the complete mechanical analysis of the sediment. The degree of correlation of the graphic parameters to the corresponding moment measures decreases as the distribution becomes more skew. However, for a fairly wide range of distributions, the first three moment measures can be ascertained from the graphic parameters with about the same degree of accuracy as is obtained by computing rough moment measures.

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National Key Technology RD Program [2006BAD03A02]

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This article assesses the impact of environmental non-tariff measures on China's agricultural exports. It uses two measures to show which countries make most intensive use of environmental non-tariff measures and which agricultural products exported by China are the most affected. Environmental non-tariff measures were most prevalence in Malaysia, Vietnam, Philippines, Mexico, Japan, Russian, USA, Germany, and Netherland. Labor-intensive agricultural products, such as fish, vegetables, and fruit were most seriously affected.

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The identification of near native protein-protein complexes among a set of decoys remains highly challenging. A stategy for improving the success rate of near native detection is to enrich near native docking decoys in a small number of top ranked decoys. Recently, we found that a combination of three scoring functions (energy, conservation, and interface propensity) can predict the location of binding interface regions with reasonable accuracy. Here, these three scoring functions are modified and combined into a consensus scoring function called ENDES for enriching near native docking decoys. We found that all individual scores result in enrichment for the majority of 28 targets in ZDOCK2.3 decoy set and the 22 targets in Benchmark 2.0. Among the three scores, the interface propensity score yields the highest enrichment in both sets of protein complexes. When these scores are combined into the ENDES consensus score, a significant increase in enrichment of near-native structures is found. For example, when 2000 dock decoys are reduced to 200 decoys by ENDES, the fraction of near-native structures in docking decoys increases by a factor of about six in average. ENDES was implemented into a computer program that is available for download at http://sparks.informatics.iupui.edu.