Numerical Cytotaxonomic Studies of Hemerocallis (Liliaceae) from China

Comparative studies of karyotypes in Hemerocallis from China have been carried out using numerical techniques. Taxa studied are as follows: Hemerocallis citrina, H. dumortieri , H. esculenta , H. forrestii , di- and triploid H. fulva , H. lilioasphodelus , H. middendorffii, H. minor, H. multiflora and H. plicata. The results show that variation in speciation has taken place at chromosomal level, and that karyotype variations have largely paralleled the morphological ones. Taxonomic proposals are given to treat H. citrina and H. minor as subspecies of H. lilioasphodelus, and H. esculenta as a variety of H. dumortieri. The results are not in favour of considering H. middendorffii as a variety ofH. dumortieri, and H. multiflora closely related to H. plicata.     

Numerical simulation of birch pollen dispersion with an operational weather forecast system

We included a parameterisation of the emissions of pollen grains into the comprehensive model system COSMO-ART. In addition, a detailed density distribution of birch trees within Switzerland was derived. Based on these new developments, we carried out numerical simulations of the dispersion of pollen grains for an episode that occurred in April 2006 over Switzerland and the adjacent regions. Since COSMO-ART is based on the operational forecast model of the German Weather Service, we are presenting a feasibility study of daily pollen forecast based on methods which have been developed during the last two decades for the treatment of anthropogenic aerosol. A comparison of the model results and very detailed pollen counts documents the current possibilities and the shortcomings of the method and gives hints for necessary improvements.     

Response of eutrophication in the eastern Gulf of Finland to nutrient load reduction scenarios

The trophic status of the eastern Gulf of Finland, where the largest Baltic metropolis St. Petersburg sits at the mouth of the largest Baltic river Neva, is elevated but existing recommendations on water protection measures are controversial. In this study, the effects of nutrient load reductions on this ecosystem were estimated with the aid of a three-dimensional coupled hydrodynamic-biogeochemical model. As a reference, the contemporary seasonal dynamics were simulated with nutrient inputs corresponding to the recent estimates of point and riverine sources. In order to eliminate the effects of natural inter-annual variations, the computations were run under recurrent annual forcing for 3 years, until quasi steady-state seasonal dynamics were reached. Reasonable comparability of simulated concentrations and biogeochemical fluxes to available field estimates provides credibility to scenario simulations. These simulations show that substantial reductions of nutrient point sources in St. Petersburg would affect only the Neva Bay as the immediate receptor of treated sewage waters, where primary production could decrease by up to 20%. Eutrophication in the other parts of the Neva Estuary and in the entire eastern Gulf of Finland would change insignificantly owing to increased nutrient import from the offshore waters. Therefore, more significant changes can occur only via a reduction in nutrient pools in the open Gulf of Finland and the Baltic Proper, which would require a longer time. Guest editors: J. H. Andersen & D. J. Conley Eutrophication in Coastal Ecosystems: Selected papers from the Second International Symposium on Research and Management of Eutrophication in Coastal Ecosystems, 20–23 June 2006, Nyborg, Denmark     

Human erythrocyte flickering: temperature,ATP concentration,water transport,and cell aging,plus a computer simulation

Images of human erythrocytes from a healthy donor were recorded under differential interference contrast (DIC) microscopy; they were acquired rapidly (~336 Hz) and the intensity of the centermost pixel of each cell was recorded for ~60 s (20,000 values). Various techniques were used to analyze the data, including detrended fluctuation analysis (DFA) and multiscale entropy (MSE); however, power spectrum analysis was deemed the most appropriate for metrifying and comparing results. This analysis was used to compare cells from young and old populations, and after perturbing normal conditions, with changes in temperature, adenosine triphosphate (ATP) concentration (using NaF, an inhibitor of glycolysis, and α-toxin, a pore-forming molecule used to permeabilize red cells to ATP), and water transport rates [using glycerol, and p-chloromercuriphenylsulfonic acid (pCMBS) to inhibit aquaporins, AQPs]. There were measurable differences in the membrane fluctuation characteristics in populations of young and old cells, but there was no significant change in the flickering time series on changing the temperature of an individual cell, by depleting it of ATP, or by competing with the minor water exchange pathway via AQP3 using glycerol. However, pCMBS, which inhibits AQP1, the major water exchange pathway, inhibited flickering in all cells, and yet it was restored by the membrane intercalating species dibutyl phthalate (DBP). We developed a computer model to simulate acquired displacement spectral time courses and to evaluate various methods of data analysis, and showed how the flexibility of the membrane, as defined in the model, affects the flickering time course.     

A finite volume method for stochastic integrate-and-fire models

The stochastic integrate and fire neuron is one of the most commonly used stochastic models in neuroscience. Although some cases are analytically tractable, a full analysis typically calls for numerical simulations. We present a fast and accurate finite volume method to approximate the solution of the associated Fokker-Planck equation. The discretization of the boundary conditions offers a particular challenge, as standard operator splitting approaches cannot be applied without modification. We demonstrate the method using stationary and time dependent inputs, and compare them with Monte Carlo simulations. Such simulations are relatively easy to implement, but can suffer from convergence difficulties and long run times. In comparison, our method offers improved accuracy, and decreases computation times by several orders of magnitude. The method can easily be extended to two and three dimensional Fokker-Planck equations.

Spiking neural network simulation: numerical integration with the Parker-Sochacki method

Mathematical neuronal models are normally expressed using differential equations. The Parker-Sochacki method is a new technique for the numerical integration of differential equations applicable to many neuronal models. Using this method, the solution order can be adapted according to the local conditions at each time step, enabling adaptive error control without changing the integration timestep. The method has been limited to polynomial equations, but we present division and power operations that expand its scope. We apply the Parker-Sochacki method to the Izhikevich ‘simple’ model and a Hodgkin-Huxley type neuron, comparing the results with those obtained using the Runge-Kutta and Bulirsch-Stoer methods. Benchmark simulations demonstrate an improved speed/accuracy trade-off for the method relative to these established techniques.

具有社会行为的HIV传播模型

考虑到HIV传播的社会行为的影响,建立了一个HIV传播的偏微分方程系统.利用预测校正方法我们给出了系统的数值解法,由此说明人的行为在HIV传播中的重要作用.     

Limiting the sedimentation coefficient for sedimentation velocity data analysis: partial boundary modeling and g(s) approaches revisited

Brown and coworkers (Eur. Biophys. J. 38 (2009) 1079–1099) introduced partial boundary modeling (PBM) to simplify sedimentation velocity data analysis by excluding species outside the range of interest (e.g., aggregates, impurities) via restricting the sedimentation coefficient range being fitted. They strongly criticized the alternate approach of fitting g(s^∗) distributions using similar range limits, arguing that (i) it produces “nonoptimal fits in the original data space” and (ii) the g(s^∗) data transformations lead to gross underestimates of the parameter confidence intervals. It is shown here that neither of those criticisms is valid. These two approaches are not truly fitting the same data or in equivalent ways; thus, they should not actually give the same best-fit parameters. The confidence limits for g(s^∗) fits derived using F statistics, bootstrap, or a new Monte Carlo algorithm are in good agreement and show no evidence for significant statistical distortion. Here 15 g(s^∗) measurements on monoclonal antibody samples gave monomer mass estimates with experimental standard deviations of less than 1%, close to the confidence limit estimates. Tests on both real and simulated data help to clarify the strengths and drawbacks of both approaches. New algorithms for computing g(s^∗) and a scan-differencing approach for PBM are introduced.