How Porosity and Permeability Vary Spatially With Grain Size, Sorting, Cement Volume, and Mineral Dissolution In Fluvial Triassic Sandstones: The Value of Geostatistics and Local Regression

Although it is well known that sandstone porosity and permeability are controlled by a range of parameters such as grain size and sorting, amount, type, and location of diagenetic cements, extent and type of compaction, and the generation of intergranular and intragranular secondary porosity, it is less constrained how these controlling parameters link up in rock volumes (within and between beds) and how they spatially interact to determine porosity and permeability. To address these unknowns, this study examined Triassic fluvial sandstone outcrops from the UK using field logging, probe permeametry of 200 points, and sampling at 100 points on a gridded rock surface. These field observations were supplemented by laser particle-size analysis, thin-section point-count analysis of primary and diagenetic mineralogy, quantitiative XRD mineral analysis, and SEM/EDAX analysis of all 100 samples. These data were analyzed using global regression, variography, kriging, conditional simulation, and geographically weighted regression to examine the spatial relationships between porosity and permeability and their potential controls. The results of bivariate analysis (global regression) of the entire outcrop dataset indicate only a weak correlation between both permeability porosity and their diagenetic and depositional controls and provide very limited information on the role of primary textural structures such as grain size and sorting. Subdividing the dataset further by bedding unit revealed details of more local controls on porosity and permeability. An alternative geostatistical approach combined with a local modelling technique (geographically weighted regression; GWR) subsequently was used to examine the spatial variability of porosity and permeability and their controls. The use of GWR does not require prior knowledge of divisions between bedding units, but the results from GWR broadly concur with results of regression analysis by bedding unit and provide much greater clarity of how porosity and permeability and their controls vary laterally and vertically. The close relationship between depositional lithofacies in each bed, diagenesis, and permeability, porosity demonstrates that each influences the other, and in turn how understanding of reservoir properties is enhanced by integration of paleoenvironmental reconstruction, stratigraphy, mineralogy, and geostatistics.

Increasing the accuracy of Nitrogen Dioxide (NO2) pollution mapping using geographically weighted regression (GWR) and geostatistics.

Nitrogen Dioxide (NO2) is known to act as an environmental trigger for many respiratory illnesses. As a pollutant it is difficult to map accurately, as concentrations can vary greatly over small distances. In this study three geostatistical techniques were compared, producing maps of NO2 concentrations in the United Kingdom (UK). The primary data source for each technique was NO2 point data, generated from background automatic monitoring and background diffusion tubes, which are analysed by different laboratories on behalf of local councils and authorities in the UK. The techniques used were simple kriging (SK), ordinary kriging (OK) and simple kriging with a locally varying mean (SKlm). SK and OK make use of the primary variable only. SKlm differs in that it utilises additional data to inform prediction, and hence potentially reduces uncertainty. The secondary data source was Oxides of Nitrogen (NOx) derived from dispersion modelling outputs, at 1km x 1km resolution for the UK. These data were used to define the locally varying mean in SKlm, using two regression approaches: (i) global regression (GR) and (ii) geographically weighted regression (GWR). Based upon summary statistics and cross-validation prediction errors, SKlm using GWR derived local means produced the most accurate predictions. Therefore, using GWR to inform SKlm was beneficial in this study.

Study of ground-state titanium ion velocity distributions in laser-produced plasma plumes

The velocity distribution of ground-state titanium ions within a low-temperature plasma resulting from the laser ablation of a titanium target has been investigated. A KrF excimer laser was focused onto the target at moderate fluences (

DNA double-strand break distributions in X-ray and alpha-particle irradiated V79 cells: Evidence for non-random breakage

Many studies have shown that with increasing LET of ionizing radiation the RBE (relative biological effectiveness) for dsb (double strand breaks) induction remains around 1.0 despite the increase in the RBE for cell killing. This has been attributed to an increase in the complexity of lesions, classified as dsb with current techniques, at multiply damaged sites. This study determines the molecular weight distributions of DNA from Chinese hamster V79 cells irradiated with X-rays or 110 keV/mu m alpha-particles. Two running conditions for pulsed-field gel-electrophoresis were chosen to give optimal separation of fragments either in the 225 kbp-5.7 Mbp range or the 0.3 kbp to 225 kbp range. Taking the total fraction of DNA migrating into the gel as a measure of fragmentation, the RBE for dsb induction was less than 1.0 for both molecular weight regions studied. The total yields of dsb were 8.2 x 10(-9) dsb/Gy/bp for X-rays and 7.8 x 10(-9) dsb/Gy/bp for a-particles, measured using a random breakage model. Analysis of the RBE of alpha-particles versus molecular weight gave a different response. In the 0.4 Mbp-57 Mbp region the RBE was less than 1.0; however, below 0.4 Mbp the RBE increased above 1.0. The frequency distributions of fragment sizes were found to differ from those predicted by a model assuming random breakage along the length of the DNA and the differences were greater for alpha-particles than for X-rays. An excess of fragments induced by a single-hit mechanism was found in the 8-300 kbp region and for X-rays and alpha-particles these corresponded to an extra 0.8 x 10(-9) and 3.4 x 10(-9) dsb/bp/Gy, respectively. Thus for every alpha-particle track that induces a dsb there is a 44% probability of inducing a second break within 300 kbp and for electron tracks the probability is 10%. This study shows that the distribution of damage from a high LET alpha-particle track is significantly different from that observed with low LET X-rays. In particular, it suggests that the fragmentation patterns of irradiated DNA may be related to the higher-order chromatin repealing structures found in intact cells.

A study of DNA fragmentation patterns in cells irradiated with charged particles: evidence for non-random distributions

Many studies have shown that the effectiveness of radiations of varying LET is similar when yields of dsb have been measured, despite large differences in biological response. Recent evidence has suggested however, that current techniques underestimate the yields of dsb. By monitoring the fragmentation of DNA over a wide range of fragment sizes ( 6 Mbp) by pulsed field electrophoresis, RBE values greater than 1.0 for radiations of around 100 keV/mm have been determined. The data provide evidence for the production of correlated breaks produced within cells as particle tracks traverse the nucleus. The highly ordered structure of DNA within mammalian cells may lead to clustering of breaks over distances related to the repeating unit structures of the chromatin. As well as these regionally damaged sites, a major contributor to radiation effectiveness will be the localised clustering of damage in the 1 - 20 bp region. A major effort is required to elucidate the relative importance of these levels of clustering and their importance in biological response.

Energy distributions of copper ions and atoms sputtered by atomic and molecular ions

Non-resonant multiphoton ionization combined with quadrupole and time-of-flight analysis has been used to study sputtering by both atomic and molecular ion beams. The mass spectra and energy distributions of both sputtered atoms and secondary ions produced by 3.6 keV Ar+, N+, N-2(+), CF2+ and CF3+ ion bombardment at 45 degrees to a polycrystalline copper target have been measured. The energy distributions of the copper ions and atoms are found to be different and quite complex. The ion distributions can generally be described by a linear collision cascade model, with possible evidence for a knock-on contribution. The sputtered atom distributions are partially described by a combination of linear collision cascade and dense cascade (thermal spike) models. This is interpreted as support for a time-evolving sputtering mechanism.

Computational learning of the conditional phase-type (C-Ph) distribution: Learning C-Ph distributions

This paper presents a new algorithm for learning the structure of a special type of Bayesian network. The conditional phase-type (C-Ph) distribution is a Bayesian network that models the probabilistic causal relationships between a skewed continuous variable, modelled by the Coxian phase-type distribution, a special type of Markov model, and a set of interacting discrete variables. The algorithm takes a dataset as input and produces the structure, parameters and graphical representations of the fit of the C-Ph distribution as output.The algorithm, which uses a greedy-search technique and has been implemented in MATLAB, is evaluated using a simulated data set consisting of 20,000 cases. The results show that the original C-Ph distribution is recaptured and the fit of the network to the data is discussed.

Non-competitive phenotypic differences can have a strong effect on ideal free distributions

1. We present a model of the ideal free distribution (IFD) where differences between phenotypes other than those involved in direct competition for resources are considered. We show that these post-acquisitional differences can have a dramatic impact on the predicted distributions of individuals.

2. Specifically, we predict that, when the relative abilities of phenotypes are independent of location, there will be a continuum of mixed evolutionarily stable strategy (ESS) distributions (where all phenotypes are present in all patches).

3, When the relative strengths of the post-acquisitional trait in the two phenotypes differ between patches, however, we predict only a single ESS at equilibrium. Further, this distribution may be fully or partially segregated (with the distribution of at least one phenotype being spatially restricted) but it will never be mixed.

4, Our results for post-acquisitional traits mirror those of Parker (1982) for direct competitive traits. This comparison illustrates that it does not matter whether individual differences are expressed before or after competition for resources, they will still exert considerable influence on the distribution of the individuals concerned.

How do grazers achieve their distribution? A continuum of models from random diffusion to the ideal free distribution using biased random walks

A conceptual model is described for generating distributions of grazing animals, according to their searching behavior, to investigate the mechanisms animals may use to achieve their distributions. The model simulates behaviors ranging from random diffusion, through taxis and cognitively aided navigation (i.e., using memory), to the optimization extreme of the Ideal Free Distribution. These behaviors are generated from simulation of biased diffusion that operates at multiple scales simultaneously, formalizing ideas of multiple-scale foraging behavior. It uses probabilistic bias to represent decisions, allowing multiple search goals to be combined (e.g., foraging and social goals) and the representation of suboptimal behavior. By allowing bias to arise at multiple scales within the environment, each weighted relative to the others, the model can represent different scales of simultaneous decision-making and scale-dependent behavior. The model also allows different constraints to be applied to the animal's ability (e.g., applying food-patch accessibility and information limits). Simulations show that foraging-decision randomness and spatial scale of decision bias have potentially profound effects on both animal intake rate and the distribution of resources in the environment. Spatial variograms show that foraging strategies can differentially change the spatial pattern of resource abundance in the environment to one characteristic of the foraging strategy.</

Investigating the efficiency of fitting Coxian phase-type distributions to health care data

Coxian phase-type distributions are becoming a popular means of representing survival times within a health care environment. They are favoured as they show a distribution as a system of phases and can allow for an easy visual representation of the rate of flow of patients through a system. Difficulties arise, however, in determining the parameter estimates of the Coxian phase-type distribution. This paper examines ways of making the fitting of the Coxian phase-type distribution less cumbersome by outlining different software packages and algorithms available to perform the fit and assessing their capabilities through a number of performance measures. The performance measures rate each of the methods and help in identifying the more efficient. Conclusions drawn from these performance measures suggest SAS to be the most robust package. It has a high rate of convergence in each of the four example model fits considered, short computational times, detailed output, convergence criteria options, along with a succinct ability to switch between different algorithms.