865 resultados para Pseudo-population bootstrap approach


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Horseshoe crab (Limulus polyphemus) is harvested commercially, used by the biomedical industry, and provides food for migrating shorebirds, particularly in Delaware Bay. Recently, decreasing crab population trends in this region have raised concerns that the stock may be insufficient to fulfill the needs of these diverse user groups. To assess the Delaware Bay horseshoe crab population, we used surplus production models (programmed in ASPIC), which incorporated data from fishery-independent surveys, fishery-dependent catch-per-unit-of-effort data, and regional harvest. Results showed a depleted population (B2003/=0.03−0.71) BMSY and high relative fishing mortality /FMSY=0.9−9.5). Future harvest (F2002strategies for a 15-year period were evaluated by using population projections with ASPICP software. Under 2003 harvest levels (1356 t), population recovery to BMSY would take at least four years, and four of the seven models predicted that the population would not reach BMSY within the 15year period. Production models for horseshoe crab assessment provided management benchmarks for a species with limited data and no prior stock assessment

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The influence of laser-field parameters, such as intensity and pulse width, on the population of molecular excited state is investigated by using the time-dependent wavepacket method. For a two-state system in intense laser fields, the populations in the upper and lower states are given by the wavefunctions obtained by solving the Schrodinger equation through split-operator scheme. The calculation shows that both the laser intensity and the pulse width have a strong effect on the population in molecular excited state, and that as the common feature of light-matter interaction (LMI), the periodic changing of the population with the evolution time in each state can be interpreted by Rabi oscillation and area-theorem. The results illustrate that by controlling these two parameters, the needed population in excited state of interest can be obtained, which provides the foundation of light manipulation of molecular processes. (C) 2005 Elsevier B.V. All rights reserved.

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Based on our previous work in deformable shape model-based object detection, a new method is proposed that uses index trees for organizing shape features to support content-based retrieval applications. In the proposed strategy, different shape feature sets can be used in index trees constructed for object detection and shape similarity comparison respectively. There is a direct correspondence between the two shape feature sets. As a result, application-specific features can be obtained efficiently for shape-based retrieval after object detection. A novel approach is proposed that allows retrieval of images based on the population distribution of deformed shapes in each image. Experiments testing these new approaches have been conducted using an image database that contains blood cell micrographs. The precision vs. recall performance measure shows that our method is superior to previous methods.

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Gene flow in macroalgal populations can be strongly influenced by spore or gamete dispersal. This, in turn, is influenced by a convolution of the effects of current flow and specific plant reproductive strategies. Although several studies have demonstrated genetic variability in macroalgal populations over a wide range of spatial scales, the associated current data have generally been poorly resolved spatially and temporally. In this study, we used a combination of population genetic analyses and high-resolution hydrodynamic modelling to investigate potential connectivity between populations of the kelp Laminaria digitata in the Strangford Narrows, a narrow channel characterized by strong currents linking the large semi-enclosed sea lough, Strangford Lough, to the Irish Sea. Levels of genetic structuring based on six microsatellite markers were very low, indicating high levels of gene flow and a pattern of isolation-by-distance, where populations are more likely to exchange migrants with geographically proximal populations, but with occasional long-distance dispersal. This was confirmed by the particle tracking model, which showed that, while the majority of spores settle near the release site, there is potential for dispersal over several kilometres. This combined population genetic and modelling approach suggests that the complex hydrodynamic environment at the entrance to Strangford Lough can facilitate dispersal on a scale exceeding that proposed for L. digitata in particular, and the majority of macroalgae in general. The study demonstrates the potential of integrated physical–biological approaches for the prediction of ecological changes resulting from factors such as anthropogenically induced coastal zone changes.

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OBJECTIVES: Sphingosine kinase 1 (SphK1) phosphorylates the membrane sphingolipid, sphingosine, to sphingosine-1-phosphate (S1P), an oncogenic mediator, which drives tumor cell growth and survival. Although SphK1 has gained increasing prominence as an oncogenic determinant in several cancers, its potential as a therapeutic target in colon cancer remains uncertain. We investigated the clinical relevance of SphK1 expression in colon cancer as well as its inhibitory effects in vitro.

METHODS: SphK1 expression in human colon tumor tissues was determined by immunohistochemistry and its clinicopathological significance was ascertained in 303 colon cancer cases. The effects of SphK1 inhibition on colon cancer cell viability and the phosphoinositide 3-kinase (PI3K)/Akt cell survival pathway were investigated using a SphK1-selective inhibitor-compound 5c (5c). The cytotoxicity of a novel combination using SphK1 inhibition with the chemotherapeutic drug, 5-fluorouracil (5-FU), was also determined.

RESULTS: High SphK1 expression correlated with advanced tumor stages (AJCC classification). Using a competing risk analysis model to take into account disease recurrence, we found that SphK1 is a significant independent predictor for mortality in colon cancer patients. In vitro, the inhibition of SphK1 induced cell death in colon cancer cell lines and attenuated the serum-dependent PI3K/Akt signaling. Inhibition of SphK1 also enhanced the sensitivity of colon cancer cells to 5-FU.

CONCLUSION: Our findings highlight the impact of SphK1 in colon cancer progression and patient survival, and provide evidence supportive of further development in combination strategies that incorporate SphK1 inhibition with current chemotherapeutic agents to improve colon cancer outcomes.

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BACKGROUND: Previous observations found a high prevalence of obstructive sleep apnea (OSA) in the hemodialysis population, but the best diagnostic approach remains undefined. We assessed OSA prevalence and performance of available screening tools to propose a specific diagnostic algorithm. METHODS: 104 patients from 6 Swiss hemodialysis centers underwent polygraphy and completed 3 OSA screening scores: STOP-BANG, Berlin's Questionnaire, and Adjusted Neck Circumference. The OSA predictors were identified on a derivation population and used to develop the diagnostic algorithm, which was validated on an independent population. RESULTS: We found 56% OSA prevalence (AHI ≥ 15/h), which was largely underdiagnosed. Screening scores showed poor performance for OSA screening (ROC areas 0.538 [SE 0.093] to 0.655 [SE 0.083]). Age, neck circumference, and time on renal replacement therapy were the best predictors of OSA and were used to develop a screening algorithm, with higher discriminatory performance than classical screening tools (ROC area 0.831 [0.066]). CONCLUSIONS: Our study confirms the high OSA prevalence and highlights the low diagnosis rate of this treatable cardiovascular risk factor in the hemodialysis population. Considering the poor performance of OSA screening tools, we propose and validate a specific algorithm to identify hemodialysis patients at risk for OSA for whom further sleep investigations should be considered.

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This paper examines several families of population principles in the light of a set of axioms. In addition to the critical-level utilitarian, number-sensitive critical-level utilitarian and number-dampened families and their generalized counterparts, we consider the restricted number-dampened family (suggested by Hurka) and introduce two new families : the restricted critical-level and restricted number-dependent critical-level families. Subsets of the restricted families have nonnegative critical levels and avoid both the repugnant and sadistic conclusions but fail to satisfy an important independence condition. We defend the critical-level principles with positive critical levels.

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This paper provides new versions of Harsanyi’s social aggregation theorem that are formulated in terms of prospects rather than lotteries. Strengthening an earlier result, fixed-population ex-ante utilitarianism is characterized in a multi-profile setting with fixed probabilities. In addition, we extend the social aggregation theorem to social-evaluation problems under uncertainty with a variable population and generalize our approach to uncertain alternatives, which consist of compound vectors of probability distributions and prospects.

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Inferring population admixture from genetic data and quantifying it is a difficult but crucial task in evolutionary and conservation biology. Unfortunately state-of-the-art probabilistic approaches are computationally demanding. Effectively exploiting the computational power of modern multiprocessor systems can thus have a positive impact to Monte Carlo-based simulation of admixture modeling. A novel parallel approach is briefly described and promising results on its message passing interface (MPI)-based C implementation are reported.

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Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC.