Exact fundamental solutions of linear parabolic equations with spatially varying coefficients

The exact general solution is obtained to a linear second order ordinary differential equation which has quite general coefficients depending on an arbitrary function of the independent variable. From this, the exact fundamental solution is derived for the corresponding linear parabolic partial differential equation with coefficients depending on the single space coordinate. In a special case this latter equation reduces to one of the Fokker-Planck type. These coefficients are then generalised and the appropriate fundamental solution is obtained. Extensions are given to linear parabolic equations in two andn space dimensions. The paper provides a collection of basic examples which illustrate and develop the theory for the generation of the exact fundamental solutions. Reduction to, and the corresponding fundamental solutions of the Fokker-Planck equations is presented, where appropriate.     

Modeling the Role of Diffusion Coefficients on Turing Instability in a Reaction-diffusion Prey-predator System

The paper is concerned with the effect of variable dispersal rates on Turing instability of a non-Lotka-Volterra reaction-diffusion system. In ecological applications, the dispersal rates of different species tends to oscillate in time. This oscillation is modeled by temporal variation in the diffusion coefficient with large as well as small periodicity. The case of large periodicity is analyzed using the theory of Floquet multipliers and that of the small periodicity by using Hill's equation. The effect of such variation on the resulting Turing space is studied. A comparative analysis of the Turing spaces with constant diffusivity and variable diffusivities is performed. Numerical simulations are carried out to support analytical findings.     

Determination of local brain blood flow by means of switched heating]

It is demonstrated by model experiments that the determination of stationary and instationary data (amplitude and shape of the heating signal) allows the two components of local brain perfusion (flow rate and volume flux) to be measured separately. Since perfusion and temperature are measured at the same site, the convection data are free of variations of the local brain temperature. The dependence of the amplitude of the heating signal on the flow rate is described by the equation Ao = a - e-bv + c, with the parameters a, b, c being represented as a function of the convection-free space around the sensing probe. It is shown by animal-experimental data that the magnitude of the convection-free space around the sensing probe is variable. A tentative algorithm is proposed for practical application of the method.     

Fast adaptive formation of orthogonalizing filters and associative memory in recurrent networks of neuron-like elements

A demonstration is given that an orthogonalizing filter for patterns is formed adaptively and very rapidly in a network of neuron-like elements with internal feedback connections. It is here assumed that the feedback gain is variable, and proportional to the correlation matrix of the output pattern vectors. The time-dependent signal transfer properties of the complete system are described by a system matrix which satisfies a matrix Bernoulli differential equation; solutions of this equation are outlined. The asymptotic value of the system matrix is shown to correspond to the orthogonal projection operator on the space that is complementary to the space spanned by all of the earlier input pattern vectors. Such a system then acts as a filter, which optimally extracts the amount that is new in an input pattern with respect to all old patterns. It also has features that are directly attributable to a distributed associative memory that is optimally selective.     

结构方程混合模型在SNP分析中的应用

采用结构方程混合模型(SEMM)对实际SNP数据进行分析,为遗传统计学提供一种新的有效的分析方法。本研究的数据是由GAW17提供的,包含697个个体的22条常染色体的上万个SNP和根据这些SNP所模拟的697个个体的性状特点。随机挑选了1号染色体上的4个SNP和3个定量性状作为研究变量,分别进行潜在类别分析和结构方程混合模型分析。根据4个SNP数据,人群被分为3个潜在类别,概率分别为0.53,0.34,0.13。潜在类别1、2和3中的因子均值Q分别为-4.029、-2.052和0,潜在类别1、2的因子均值均低于3(<0.001)。研究表明:结构方程混合模型(SEMM)综合了结构方程模型和潜在类别模型的思想,形成了自己的优势,可用于处理同时包含分类潜变量和连续潜变量的数据。     

Some mathematical aspects of chemotherapy: I. One-organ models

A model of the processes occuring in the exchange of a drug between capillary plasma, extracellular space and intracellular space is developed. This leads to an interesting set of differential differences equations, one of which is an integrodifferential equation, another a partial differential equation. Under certain conditions, these may be simplified to a set of ordinary differential equations. The application of Laplace transform techniques to the solution of these equations is discussed.     

MICROSPECTROPHOTOMETRIC INVESTIGATIONS OF FREE SPACE IN PLANT CELL WALLS

Two equations were proposed for the determination of free space in plant cell walls. Solution of the equations required microspectrophotometric measurements of cell walls after introduction of a chromophore. A periodic acid-Schiff test was developed for this purpose and a statistical analysis of the error terms was used to evaluate the discriminatory capacity of the system. Bouguer's law was tested directly and found to hold for the tissue thicknesses and wavelengths used. Because concentration was unknown, Beer's law could not be tested directly, but a new method based on the logarithmic transformation of the optical densities and statistical correlation of curve shape was used to predict the wavelength interval in which Beer's law held. Calculations by a newly derived extinction-ratio equation (AE/E) were essentially invariant over the predicted range and variable outside of this wavelength interval. Free space in hydrated S₂ layers of tracheid cell walls of Pinus resinosa Ait. was calculated to be about 25%. The magnitude of free space at various stages of hydration was also tabulated. Considerable free space was found to exist in plant cell walls after prolonged exposure to anhydrous ethyl alcohol; however, after complete dehydration there was little evidence of residual free space.     

Comparison of spatially implicit and explicit approaches to model plant infestation by insect pests

Spatial heterogeneities have been explored in many different ways in population dynamic models. We investigate here the way in which space should be considered in the dynamics of an aphid–parasitoid system in a melon greenhouse, in order to plan a biological control program at a wide scale. By comparing a non-spatial model with a spatially explicit model (a lattice one), we show a strong difference between predictions and we thus confirm that it is essential to take space into account in such closed and structured environments when describing the spatial heterogeneities observed in the field. The way in which space should be considered in such system is tested by comparing the spatially explicit model with a new implicit approach, which describes the level of plant infestation by a continuous variable corresponding to the number of plants with a given density of pests at a given time. When the explicit model needs as many equations as plants in the greenhouse, our novel approach has only a partial differential equation. We infer from the comparisons between the two spatial models that the predicted host–parasitoid dynamics are similar under most conditions. Some differences occur when local dispersal (considered only in the explicit model) is high and it can have a strong impact on population dynamics but does not change the conclusions for crop protection. We conclude that the new spatially implicit model thus generate relevant predictions with a more synthetic formalism than the common plant-by-plant model and it will thus be more adapted to test biological control strategies at a higher scale than the greenhouse.     

A Maximum Likelihood Estimator for Shape Parameters of S‐Distributions

The S‐distribution is a four‐parameter distribution that is defined in terms of a differential equation, in which the cumulative is represented as the dependent variable: The article proposes a maximum likelihood estimator for the shape parameters of this distribution.     

Outline of a matrix calculus for neural nets

The activity of a neural net is represented in terms of a matrix vector equation with a normalizing operator in which the matrix represents only the complete structure of the net, and the normalized vector-matrix product represents the activity of all the non-afferent neurons. The activity vectors are functions of a quantized time variable whose elements are zero (no activity) or one (activity). Certain properties of the structure matrix are discussed and the computational procedure which results from the matrix vector equation is illustrated by a specific example.     

Models of Darwinian processes and evolutionary principles

Evolutionary processes are described as stochastic motions in a genotype space (set of sequences with a Hamming distance) and a phenotype space (vector space of phenotypic properties). Real value functions are introduced which form a landscape over these spaces; smoothness postulates are formulated. Evolution is considered as a kind of hill climbing on these adaptive landscapes. A rather simple diffusion approximation for the phenotypic processes is proposed which leads to similar mathematical problems as the Schrödinger equation for disordered potential distributions.     

On the theory of diffusion of electrolytes

In the theory of diffusion of electrolytes the following assumptions are frequently made: (i) the electrolytic solution is electrically neutral everywhere, (ii) the ionic concentrations and the electric potential all depend on a single Cartesian coordinate as the only space variable. Often the electric potential of the solution is determined on the basis of the Poisson equation alone, disregarding any other relation between this potential and the ionic concentrations. Since the Poisson equation only represents a condition which the potential fulfills, the use of this equation alone may lead to error unless the explicit relation for the potential involving a space integration of ionic concentrations is also taken into account. But if this relation is used the Poisson equation becomes redundant and, more important, assumptions (i) and (ii) appear unacceptable, the former because it leads to a zero electric potential everywhere, the latter because it is mathematically incorrect. The present paper is based on general equations of diffusion of ions, excluding the Poisson equation. These equations form a system of nonlinear integrodifferential quations whose number equals the number of ionic species present in the solution. It appears that when all ions are distributed symmetrically around a point all functions related to the above system of equations can be made dependent on a single space coordinate: the distance from the center of symmetry. Two methods of successive approximations are given for the solution of the equations in the case of spherical symmetry with limitation to the steady state. These methods are then applied to the study of the distribution of ionic concentrations and electrical potentials inside a cell of spherical shape in equilibrium with its surroundings. These methods are rapidly convergent; exact theoretical values of the electric potential are calculable on the boundary of the cell. It appears that the potential at the center of the cell is not more than ∼50% higher than at its boundary and that variation of concentration inside the cell is not very large. For instance, with 100 mV on the boundary the ionic concentration there is about four times higher than at the center. Calculations show that extremely small amounts of electricity are sufficient to account for the electric potentials currently observed. In a cell of 100 micra diameter an average concentration of only 10⁻¹⁴ mole/cm³ of a monovalent ion would be sufficient to give 1 millivolt on the boundary. This concentration is directly proportional to the voltage and inversely proportional to the square of the cell diameter. Most of the numerical results given above are obtained by considering only those ions whose electrical charge is not compensated for by ions of an opposite sign. The total concentrations may be much higher than those quoted. The theory does not take into account possible effects of structural heterogeneities which may exist in the cell, particularly of various phase boundaries. An incidental result shows that the Boltzmann distribution function in the form employed in modern theory of electrolytes is fundamentally a consequence of the mathematical theory of diffusion alone. It is pointed out, however, that Boltzmann distribution is not always compatible with the definition of the electric potential.     

Nonlinear feedforward control of bioreactors with input multiplicities

A steady-state nonlinear feedforward controller (FFC) for measurable disturbances is designed for a continuous bioreactor, which is represented by Hammerstein type nonlinear model wherein the nonlinearity is a polynomial with input multiplicities. The manipulated variable is the feed substrate concentration (S_f) and the disturbance variable is the dilution rate (D). The productivity (Q=DP) is considered as the controlled variable. The desired value of Q=3.73 gives two values of feed substrate concentration. The nonlinearity in the gain is considered for relating output to the manipulated variable and separately for the relation between output to disturbance variable. The FFC is also designed for the overall linearized system. The performance of the FFC is evaluated on the nonlinear differential equation model. The FFC is also designed for the model based on a single nonlinear steady-state equation containing both D and S_f. This nonlinear FFC gives the best performance. The nonlinear FFC is also designed by using only linear gain for the disturbance and nonlinear gain for the manipulated variable. Similarly, nonlinear FFC is also designed by using linear gain for the manipulated variable and the nonlinear gain for the disturbance variable. The performances of these FFC schemes are compared.     

A Generalized Simplest Equation Method and Its Application to the Boussinesq-Burgers Equation

In this paper, a generalized simplest equation method is proposed to seek exact solutions of nonlinear evolution equations (NLEEs). In the method, we chose a solution expression with a variable coefficient and a variable coefficient ordinary differential auxiliary equation. This method can yield a Bäcklund transformation between NLEEs and a related constraint equation. By dealing with the constraint equation, we can derive infinite number of exact solutions for NLEEs. These solutions include the traveling wave solutions, non-traveling wave solutions, multi-soliton solutions, rational solutions, and other types of solutions. As applications, we obtained wide classes of exact solutions for the Boussinesq-Burgers equation by using the generalized simplest equation method.     

Exact solutions to the continuous-quality equation for soil organic matter turnover

All living systems depend on transformations of elements between different states. In particular, the transformation of dead organic matter in the soil (SOM) by decomposers (microbes) releases elements incorporated in SOM and makes the elements available anew to plants. A major problem in analysing and describing this process is that SOM, as the result of the decomposer activity, is a mixture of a very large number of molecules with widely differing chemical and physical properties. The continuous-quality equation (CQE) is a general equation describing this complexity by assigning a continuous-quality variable to each carbon atom in SOM. The use of CQE has been impeded by its complicated mathematics. Here, we show by deriving exact solutions that, at least for some specific cases, there exist solutions to CQE. These exact solutions show that previous approximations have overestimated the rate by which litter decomposes and as a consequence underestimated steady state SOM amounts. The exact and approximate solutions also differ with respect to the parameter space in which they yield finite steady-state SOM amounts. The latter point is important because temperature is one of the parameters and climatic change may move the solution from a region of the parameter space with infinite steady-state SOM to a region of finite steady-state SOM, with potentially large changes in soil carbon stores. We also show that the solution satisfies the Chapman-Kolmogorov theorem. The importance of this is that it provides efficient algorithms for numerical solutions.     

Study of kinetic effects arising in simulations of Farley-Buneman instability

The Farley-Buneman instability, which has been observed in the E region of the Earth’s ionosphere, is studied using fluid equations for electrons, a four-dimensional (in coordinate-velocity space) kinetic equation for ions, and Poisson’s equation. Numerical simulations with allowance for Landau damping show that the Farley-Buneman instability results in anisotropy of the ion velocity distribution function.     

The kinetics of protein salting-Out: Precipitation of yeast enzymes by ammonium sulfate

Protein solubility can be adequately represented by the classical Cohn equation for the salting-out of alcohol dehydrogenase and fumarase from clarified yeast homogenate with ammonium sulfate. However, the constant β in this equation is a function of the contacting procedure employed. The kinetics of continuous salting-out were similar for alcohol dehydrogenase and fumarase. The overall rate equation for precipitation had a variable order which was high initially, up to 3.1, but approached unity on completion of precipitation. This was followed by a partial resolution stage which was first order with respect to the concentration driving force. Precipitate particle size was estimated as 0.5 to 5 μm with continuous flow precipitation producing the largest particles.     

Dynamics of sexual populations structured by a space variable and a phenotypical trait

We study sexual populations structured by a phenotypic trait and a space variable, in a non-homogeneous environment. Departing from an infinitesimal model, we perform an asymptotic limit to derive the system introduced in Kirkpatrick and Barton (1997). We then perform a further simplification to obtain a simple model. Thanks to this simpler equation, we can describe rigorously the dynamics of the population. In particular, we provide an explicit estimate of the invasion speed, or extinction speed of the species. Numerical computations show that this simple model provides a good approximation of the original infinitesimal model, and in particular describes quite well the evolution of the species’ range.