Predictive accuracy determination applied to a linear model phosphorus loading resulting from urban runoff

A case study of the application of an iterative technique for determination of predictive accuracy is presented. The method uses Monte Carlo simulations and split sampling techniques to verify model accuracy. Examination of the ability of a linear parametric runoff loading model's ability to project total phosphorus loadings reveals the sensitivity of the model to calibration procedures. Predictive reliability was found to vary widely as the number of rainfall events considered in the calibration process changed. Predictive reliability was substantially increased by imposing calibration constraints which ensured that a wide distribution of values of the independent variable were presented in the calibration pool.Although the linear model is theoretically weak in its representation of the runoff loading phenomenon, it displays relatively stable predictive capabilities which warrant its consideration for use in management studies. The predictive errors associated with loading projections limit the linear model's value to applications insensitive to errors in the loading projections for individual storm events. This study provides further evidence of the need to consider uncertainties associated with the modelling of water quality phenomena.     

Estimation of the scale parameter of a power law process using power law counts

Analogous to Kingman's Poisson Counts, power law counts are defined. Further, these are used to obtain the maximum likelihood estimator of the scale parameter of a power law process. Comparison of this estimator is done with those obtained by using other sampling schemes. Also, cost comparisons are done under the assumption of equal asymptotic variances under different sampling schemes.Work done while the author was with the Department of Statistics, University of Poona. Current address: Dept. of Mathematics, CME, Pune.     

Percolation and cluster distribution. III. Algorithms for the site-bond problem

Algorithms for estimating the percolation probabilities and cluster size distribution are given in the framework of a Monte Carlo simulation for disordered lattices for the generalized site-bond problem. The site-bond approach is useful when a percolation process cannot be exclusively described in the context of pure site or pure bond percolation. An extended multiple labeling technique (ECMLT) is introduced for the generalized problem. The ECMLT is applied to the site-bond percolation problem for square and triangular lattices. Numerical data are given for lattices containing up to 16 million sites. An application to polymer gelation is suggested.Supported by NSF Grant DMR76-07832 and NIH Grant NS08116-9.     

Protein structure prediction by tempering spatial constraints

Summary The probability to predict correctly a protein structure can be enhanced through introduction of spatial constraints – either from NMR experiments or from homologous structures. However, the additional constraints lead often to new local energy minima and worse sampling efficiency in simulations. In this work, we present a new parallel tempering variant that alleviates the energy barriers resulting from spatial constraints and therefore yields to an enhanced sampling in structure prediction simulations.     

The Cluster Model: A Simulation of the Aerogel Structure as a Hierarchically-Ordered Arrangement of Randomly Packed Spheres

A new structural model based on the premises widely used for describing the structure of aerogels has been introduced. These structures have been described as an assemblage of randomly-packed spheres in several hierarchically-ordered levels. A new algorithm has been developed for constructing our models from these premises using computer simulation. Subsequently, several applications have been simulated to characterize real systems, obtaining textural parameters such as the specific surface area, specific porous volume or the apparent density of the systems, based on the Monte Carlo technique and on geometrical considerations. The object of these is to test the ability of the models to explain the structure of some real aerogels. This Cluster Model has also been applied as an initial approach to the study of the mechanical properties of aerogels. Results support the general conclusion that these models are useful for explaining the structure of aerogels.     

Head space gas chromatography with glass capillaries using an automatic electropneumatic dosing system

Head space GC using a special electropneumatic sampling system works well in combination with glass capillaries. Because a homogenous gas mixture is already present most problems inherent with inlet splitters are thus avoided. In cases where the high vapor pressure of the sample can cause problems with the pressure controlled sampling system, the use of narrow bore glass capillaries provides the necessary inlet pressure. The use of this powerful and convenient analytical tool for water pollution analysis, flavour analysis and the analysis of volatiles in crude oil samples is shown by examples.     

Analysis of Digital Lateral Shearing Interferometer

A new method is proposed for reconstructing wavefront from discretely sampled interferogram data obtained by a digital lateral shearing interferometer. Assumptions applied in the conventional methods are not used and reconstruction error caused by the difference between the amount of shear and the sampling interval can be removed. System error and the influence of the discrete sampling, which limit accuracy of the tested results of the lateral shearing interferometer, are analyzed.     

Simulated annealing for constrained global optimization

Hide-and-Seek is a powerful yet simple and easily implemented continuous simulated annealing algorithm for finding the maximum of a continuous function over an arbitrary closed, bounded and full-dimensional body. The function may be nondifferentiable and the feasible region may be nonconvex or even disconnected. The algorithm begins with any feasible interior point. In each iteration it generates a candidate successor point by generating a uniformly distributed point along a direction chosen at random from the current iteration point. In contrast to the discrete case, a single step of this algorithm may generateany point in the feasible region as a candidate point. The candidate point is then accepted as the next iteration point according to the Metropolis criterion parametrized by anadaptive cooling schedule. Again in contrast to discrete simulated annealing, the sequence of iteration points converges in probability to a global optimum regardless of how rapidly the temperatures converge to zero. Empirical comparisons with other algorithms suggest competitive performance by Hide-and-Seek.This material is based on work supported by a NATO Collaborative Research Grant, no. 0119/89.     

End‐to‐End Distances in Four‐Junction Polymers

The various end‐to‐end distances of four‐junction polymers are investigated. The sizes of the different kinds of equal length branches and the backbone of two different polymers, with either nine or eleven branches, are estimated by means of both renormalization‐group and MC calculations. The comparisons of first‐order ε = 4 − d predictions with the MC results are satisfactory. The same trends are present in both techniques. The excluded‐volume interactions from additional branches further expand the various parts of the chains so that internal branches are larger than external ones. The branch ratios in the eleven‐branch case are expanded even more than the corresponding ratios of the nine‐branch polymer.

     

Macromolecular Crowding and the Sizes of Neutral Flexible Polymer Chains: The Role of Colloids Sizes and Concentrations

In the present work, we revisit the effect of macromolecular crowding on the sizes of flexible neutral polymer chains. Motivated by recent experimental measurements on crowding effects on neutral flexible polymers chains, we perform Monte Carlo simulations on a model system consisting of hard spheres (HS) and a neutral flexible polymer chain. We find that, depending on the ratio of the sizes of the colloidal particles to the sizes of the polymer chain, and thus, on the extent of the colloid partitioning among the chain segments and the solution, the flexible polymeric coil may be either continuously compressed, or initially compressed followed by a reswelling at high enough colloid concentration. The chain behavior is thus nonmonotonic, a point which, apart from the work of Khalatur et al., has not so far been stressed in simulations of flexible polymer chains under crowding conditions. A thermodynamic model for the polymer–colloid interactions based on the Gibbs–Duhem equation and on a “Flory‐type” argument is also presented, emphasizing the indirect influence of macromolecular crowding on the monomers chemical potential. We show explicitly that under crowding conditions, the colloids are driven into the most compact coil states. These analytical results are compared with the results of the potential of mean force between the chain center of mass and the colloids obtained from the Monte Carlo simulations, and a reasonable agreement is found. The implications of the aforementioned results are further discussed in the context of biological systems, specially those for which macromolecular crowding is supposed to play the important role of including preferentially other (charged) macromolecules into the colloid‐compressed polymer phase.