Special Issue on Spatial Moment Techniques for Modelling Biological Processes

Over the last two decades, there has been an increasing awareness of, and interest in, the use of spatial moment techniques to provide insight into a range of biological and ecological processes. Models that incorporate spatial moments can be viewed as extensions of mean-field models. These mean-field models often consist of systems of classical ordinary differential equations and partial differential equations, whose derivation, at some point, hinges on the simplifying assumption that individuals in the underlying stochastic process encounter each other at a rate that is proportional to the average abundance of individuals. This assumption has several implications, the most striking of which is that mean-field models essentially neglect any impact of the spatial structure of individuals in the system. Moment dynamics models extend traditional mean-field descriptions by accounting for the dynamics of pairs, triples and higher n-tuples of individuals. This means that moment dynamics models can, to some extent, account for how the spatial structure affects the dynamics of the system in question.

Modelling the movement of interacting cell populations: A moment dynamics approach

Mathematical models describing the movement of multiple interacting subpopulations are relevant to many biological and ecological processes. Standard mean-field partial differential equation descriptions of these processes suffer from the limitation that they implicitly neglect to incorporate the impact of spatial correlations and clustering. To overcome this, we derive a moment dynamics description of a discrete stochastic process which describes the spreading of distinct interacting subpopulations. In particular, we motivate our model by mimicking the geometry of two typical cell biology experiments. Comparing the performance of the moment dynamics model with a traditional mean-field model confirms that the moment dynamics approach always outperforms the traditional mean-field approach. To provide more general insight we summarise the performance of the moment dynamics model and the traditional mean-field model over a wide range of parameter regimes. These results help distinguish between those situations where spatial correlation effects are sufficiently strong, such that a moment dynamics model is required, from other situations where spatial correlation effects are sufficiently weak, such that a traditional mean-field model is adequate.

Photos of Gomez coat of arms and other Gomez items

Digital image

Platinum dendritic nanoparticles with magnetic behavior

Magnetic nanoparticles have attracted increasing attention for biomedical applications in magnetic resonance imaging, high frequency magnetic field hyperthermia therapies, and magnetic-field-gradient-targeted drug delivery. In this study, three-dimensional (3D) platinum nanostructures with large surface area that features magnetic behavior have been demonstrated. The well-developed 3D nanodendrites consist of plentiful interconnected nano-arms ∼4 nm in size. The magnetic behavior of the 3D dendritic Pt nanoparticles is contributed by the localization of surface electrons due to strongly bonded oxygen/Pluronic F127 and the local magnetic moment induced by oxygen vacancies on the neighboring Pt and O atoms. The magnetization of the nanoparticles exhibits a mixed paramagnetic and ferromagnetic state, originating from the core and surface, respectively. The 3D nanodendrite structure is suitable for surface modification and high amounts of drug loading if the transition temperature was enhanced to room temperature properly.

Localization of handwritten text in documents using moment invariants and Delaunay triangulation

This paper describes an approach based on Zernike moments and Delaunay triangulation for localization of hand-written text in machine printed text documents. The Zernike moments of the image are first evaluated and we classify the text as hand-written using the nearest neighbor classifier. These features are independent of size, slant, orientation, translation and other variations in handwritten text. We then use Delaunay triangulation to reclassify the misclassified text regions. When imposing Delaunay triangulation on the centroid points of the connected components, we extract features based on the triangles and reclassify the text. We remove the noise components in the document as part of the preprocessing step so this method works well on noisy documents. The success rate of the method is found to be 86%. Also for specific hand-written elements such as signatures or similar text the accuracy is found to be even higher at 93%.

Moment methods and "restricted variation" in kinetic theory

It is shown that there is a strict one-to-one correspondence between results obtained by the use of "restricted" variational principles and those obtained by a moment method of the Mott-Smith type for shock structure.

Charge distribution, dipole moment and molecular structure of silyl compounds

The formal charge distribution and hence the electric moments of a number of halosilanes and their methyl derivatives have been calculated by the method of Image and Image . The difference between the observed and the calculated values in simple halosilanes is attributed to a change in the hybridization of the terminal halogen atom and in methyl halosilanes to the enhanced electron release of the methyl group towards silicon compared with carbon.

Moment-Matched Lognormal Modeling of Uplink Interference with Power Control and Cell Selection

We develop an alternate characterization of the statistical distribution of the inter-cell interference power observed in the uplink of CDMA systems. We show that the lognormal distribution better matches the cumulative distribution and complementary cumulative distribution functions of the uplink interference than the conventionally assumed Gaussian distribution and variants based on it. This is in spite of the fact that many users together contribute to uplink interference, with the number of users and their locations both being random. Our observations hold even in the presence of power control and cell selection, which have hitherto been used to justify the Gaussian distribution approximation. The parameters of the lognormal are obtained by matching moments, for which detailed analytical expressions that incorporate wireless propagation, cellular layout, power control, and cell selection parameters are developed. The moment-matched lognormal model, while not perfect, is an order of magnitude better in modeling the interference power distribution.

Probabilistic Analysis of Cracking Moment of Reinforced Concrete Beams

Probabilistic analysis of cracking moment from 22 simply supported reinforced concrete beams is performed. When the basic variables follow the distribution considered in this study, the cracking moment of a beam is found to follow a normal distribution. An expression is derived, for characteristic cracking moment, which will be useful in examining reinforced concrete beams for a limit state of cracking.

Therapeutic work with the present moment: A conversation analytical study of guidance into immediacy

Therapeutic work with the client’s present moment experience in existential therapy was studied by means of conversation analysis. Using publicly available video recordings of therapy sessions as data, an existential therapist’s practice of guiding a client into immediacy, or refocusing the talk on a client’s immediate experience, was described and compared with a therapist’s corresponding action in cognitive therapy. The study contributes to the description of interactional practice of existential therapy, and involves the first application of conversation analysis to a comparative study of psychotherapy process. The potential utility of this approach and the clinical and empirical implications of the present findings are discussed.

Attitude estimation using moment invariants

The problem of estimating the three-dimensional rotational parameters of a rigid body from its monocular image data has been considered using the method of moment invariants. Second- and third-order moment invariants are used to construct the feature vector for the scale and orientation independent identification of the camera view axis direction in the body-fixed reference frame. The camera rotation angle about the view axis is derived from second-order central moments. The relative attitude of the rigid body is then expressed in terms of quaternion parameters to model the outputs of a video sensor in attitude control simulations. Experimental results and simulation outputs are presented using the mathematical model of a spacecraft.

Investigation on the Magnetic Anomaly and the Role of Orbital Moment on the Magnetic Properties of LaMn0.5Co0.5O3

Two distinct ferromagnetic phases are present in LaMn0.5Co0.5O3 for which the spin-only magnetic moment calculated from the high temperature dc susceptibility is found to be unusually high. Such a high moment can only be accounted for by assigning the valence state of the cations to Mn2+-Co4+. This is unrealistic as the earlier report based on X-ray absorption spectroscopy (XAS) has suggested the valence state to be mainly Mn4+-Co2+ with traces of Co3+. Also from our studies using XAS, it is found that the valence state is mainly Mn4+-Co2+. In addition, no notable difference is observed in the minor Co3+ present in both phases. Our results based on X-ray magnetic circular dichroism studies (XMCD) reveal the presence of ``distinct'' high orbital moment associated with Co2+ for both phases. Thus it is found that the distinctness of the orbital moment also plays a vital role in determining the magnetic moment and T-c of both phases of LaMn0.5Co0.5O3. By considering the orbital moment obtained from XMCD, the anomaly in the paramagnetic susceptibility is resolved and thus we are able to assign the valence state to Mn4+-Co2+ configuration. The difference in the magnitude of orbital moment in both phases is believed to be due to the crystal field effects.

Assessment of conditional moment closure models of turbulent autoignition using DNS data

A systematic assessment of the submodels of conditional moment closure (CMC) formalism for the autoignition problem is carried out using direct numerical simulation (DNS) data. An initially non-premixed, n-heptane/air system, subjected to a three-dimensional, homogeneous, isotropic, and decaying turbulence, is considered. Two kinetic schemes, (1) a one-step and (2) a reduced four-step reaction mechanism, are considered for chemistry An alternative formulation is developed for closure of the mean chemical source term , based on the condition that the instantaneous fluctuation of excess temperature is small. With this model, it is shown that the CMC equations describe the autoignition process all the way up to near the equilibrium limit. The effect of second-order terms (namely, conditional variance of temperature excess sigma(2) and conditional correlations of species q(ij)) in modeling is examined. Comparison with DNS data shows that sigma(2) has little effect on the predicted conditional mean temperature evolution, if the average conditional scalar dissipation rate is properly modeled. Using DNS data, a correction factor is introduced in the modeling of nonlinear terms to include the effect of species fluctuations. Computations including such a correction factor show that the species conditional correlations q(ij) have little effect on model predictions with a one-step reaction, but those q(ij) involving intermediate species are found to be crucial when four-step reduced kinetics is considered. The "most reactive mixture fraction" is found to vary with time when a four-step kinetics is considered. First-order CMC results are found to be qualitatively wrong if the conditional mean scalar dissipation rate is not modeled properly. The autoignition delay time predicted by the CMC model compares excellently with DNS results and shows a trend similar to experimental data over a range of initial temperatures.

An adaptive cascade compensator for a wide class of stable minimum or nonminimum phase plants through time moment estimation

Model Reference Adaptive Control (MRAC) of a wide repertoire of stable Linear Time Invariant (LTI) systems is addressed here. Even an upper bound on the order of the finite-dimensional system is unavailable. Further, the unknown plant is permitted to have both minimum phase and nonminimum phase zeros. Model following with reference to a completely specified reference model excited by a class of piecewise continuous bounded signals is the goal. The problem is approached by taking recourse to the time moments representation of an LTI system. The treatment here is confined to Single-Input Single-Output (SISO) systems. The adaptive controller is built upon an on-line scheme for time moment estimation of a system given no more than its input and output. As a first step, a cascade compensator is devised. The primary contribution lies in developing a unified framework to eventually address with more finesse the problem of adaptive control of a large family of plants allowed to be minimum or nonminimum phase. Thus, the scheme presented in this paper is confined to lay the basis for more refined compensators-cascade, feedback and both-initially for SISO systems and progressively for Multi-Input Multi-Output (MIMO) systems. Simulations are presented.