Regional-scale investigation of the spatial distribution and origin of soluble salts in central north Queensland

A method for regional assessment of the distribution of saline outbreaks is demonstrated for a large area (68 000 km(2)) in north Queensland, Australia. Soil samples were used in conjunction with a digital elevation model and a map of potentially saline discharge zones to examine the landscape distribution of soluble salts in the region. The hypothesis of atmospheric accession of salt was tested for the topographically defined catchment regions feeding into each potentially saline discharge area. Most catchments showed a salt distribution consistent with this hypothesis, i.e. %TSS was large near the discharge areas and decreased rapidly with distance uphill from the discharge areas. In some catchments, however, local saline outbreaks were apparent at significant distances uphill from discharge areas. The possibility of geological sources of this salt was examined by comparing random point distributions with the location of saline points with distance downhill from geological units (excluding points near discharge zones). The distribution of some saline outbreaks was consistent with the occurrence of Cambro-Ordovician metasediments, Devonian limestone, Upper Devonian-Lower Carboniferous volcanics, and Triassic sediments. Copyright (C) 2000 John Wiley & Sons, Ltd.

Characterization of pore size distributions of mesoporous materials from adsorption isotherms

In this article, a new hybrid model for estimating the pore size distribution of micro- and mesoporous materials is developed, and tested with the adsorption data of nitrogen, oxygen, and argon on ordered mesoporous materials reported in the literature. For the micropore region, the model uses the Dubinin-Rudushkevich (DR) isotherm with the Chen-Yang modification. A recent isotherm model of the authors for nonporous materials, which uses a continuum-mechanical model for the multilayer region and the Unilan model for the submonolayer region, has been extended for adsorption in mesopores. The experimental data is inverted using regularization to obtain the pore size distribution. The present model was found to be successful in predicting the pore size distribution of pure as well as binary physical mixtures of MCM-41 synthesized with different templates, with results in agreement with those from the XRD method and nonlocal density functional theory. It was found that various other recent methods, as well as the classical Broekhoff and de Beer method, underpredict the pore diameter of MCM-41. The present model has been successfully applied to MCM-48, SBA's, CMK, KIT, HMS, FSM, MTS, mesoporous fly ash, and a large number of other regular mesoporous materials.

Microscopic origin of non-Gaussian distributions of financial returns

In this paper we study the possible microscopic origin of heavy-tailed probability density distributions for the price variation of financial instruments. We extend the standard log-normal process to include another random component in the so-called stochastic volatility models. We study these models under an assumption, akin to the Born-Oppenheimer approximation, in which the volatility has already relaxed to its equilibrium distribution and acts as a background to the evolution of the price process. In this approximation, we show that all models of stochastic volatility should exhibit a scaling relation in the time lag of zero-drift modified log-returns. We verify that the Dow-Jones Industrial Average index indeed follows this scaling. We then focus on two popular stochastic volatility models, the Heston and Hull-White models. In particular, we show that in the Hull-White model the resulting probability distribution of log-returns in this approximation corresponds to the Tsallis (t-Student) distribution. The Tsallis parameters are given in terms of the microscopic stochastic volatility model. Finally, we show that the log-returns for 30 years Dow Jones index data is well fitted by a Tsallis distribution, obtaining the relevant parameters. (c) 2007 Elsevier B.V. All rights reserved.

Scale-up of mixer granulators for effective liquid distribution

There is considerable anecdotal evidence from industry that poor wetting and liquid distribution can lead to broad granule size distributions in mixer granulators. Current scale-up scenarios lead to poor liquid distribution and a wider product size distribution. There are two issues to consider when scaling up: the size and nature of the spray zone and the powder flow patterns as a function of granulator scale. Short, nucleation-only experiments in a 25L PMA Fielder mixer using lactose powder with water and HPC solutions demonstrated the existence of different nucleation regimes depending on the spray flux Psi(a)-from drop-controlled nucleation to caking. In the drop-controlled regime at low Psi(a) values. each drop forms a single nucleus and the nuclei distribution is controlled by the spray droplet size distribution. As Psi(a) increases, the distribution broadens rapidly as the droplets overlap and coalesce in the spray zone. The results are in excellent agreement with previous experiments and confirm that for drop-controlled nucleation. Psi(a) should be less than 0.1. Granulator flow studies showed that there are two powder flow regimes-bumping and roping. The powder flow goes through a transition from bumping to roping as impeller speed is increased. The roping regime gives good bed turn over and stable flow patterns. This regime is recommended for good liquid distribution and nucleation. Powder surface velocities as a function of impeller speed were measured using high-speed video equipment and MetaMorph image analysis software, Powder surface velocities were 0.2 to 1 ms(-1)-an order of magnitude lower than the impeller tip speed. Assuming geometrically similar granulators, impeller speed should be set to maintain constant Froude number during scale-up rather than constant tip speed to ensure operation in the roping regime. (C) 2002 Published by Elsevier Science B.V.

Modelling High-Dimensional Data by Mixtures of Factor Analyzers

We focus on mixtures of factor analyzers from the perspective of a method for model-based density estimation from high-dimensional data, and hence for the clustering of such data. This approach enables a normal mixture model to be fitted to a sample of n data points of dimension p, where p is large relative to n. The number of free parameters is controlled through the dimension of the latent factor space. By working in this reduced space, it allows a model for each component-covariance matrix with complexity lying between that of the isotropic and full covariance structure models. We shall illustrate the use of mixtures of factor analyzers in a practical example that considers the clustering of cell lines on the basis of gene expressions from microarray experiments. (C) 2002 Elsevier Science B.V. All rights reserved.

Time-frequency and time-scale characterisation of the beat-by-beat high-resolution electrocardiogram

Proceedings of the Sixth Portuguese Conference on Bioemedical Engineering faro, Portugal

Mathematical modelling of shallow flows: closure models drawn from grain-scale mechanics of sediment transport and flow hydrodynamics

Canadian Journal of Civil Engineering 36(10) 1605–16

Analysis of metabolic flux distributions in relation to the extracellular environment in Avian cells

Continuous cell lines that proliferate in chemically defined and simple media have been highly regarded as suitable alternatives for vaccine production. One such cell line is the AG1.CR.pIX avian cell line developed by PROBIOGEN. This cell line can be cultivated in a fully scalable suspension culture and adapted to grow in chemically defined, calf serum free, medium [1]–[5]. The medium composition and cultivation strategy are important factors for reaching high virus titers. In this project, a series of computational methods was used to simulate the cell’s response to different environments. The study is based on the metabolic model of the central metabolism proposed in [1]. In a first step, Metabolic Flux Analysis (MFA) was used along with measured uptake and secretion fluxes to estimate intracellular flux values. The network and data were found to be consistent. In a second step, Flux Balance Analysis (FBA) was performed to access the cell’s biological objective. The objective that resulted in the best predicted results fit to the experimental data was the minimization of oxidative phosphorylation. Employing this objective, in the next step Flux Variability Analysis (FVA) was used to characterize the flux solution space. Furthermore, various scenarios, where a reaction deletion (elimination of the compound from the media) was simulated, were performed and the flux solution space for each scenario was calculated. Growth restrictions caused by essential and non-essential amino acids were accurately predicted. Fluxes related to the essential amino acids uptake and catabolism, the lipid synthesis and ATP production via TCA were found to be essential to exponential growth. Finally, the data gathered during the previous steps were analyzed using principal component analysis (PCA), in order to assess potential changes in the physiological state of the cell. Three metabolic states were found, which correspond to zero, partial and maximum biomass growth rate. Elimination of non-essential amino acids or pyruvate from the media showed no impact on the cell’s assumed normal metabolic state.

Identification of tumor-associated antigens by large-scale analysis of genes expressed in human colorectal cancer.

Despite the high prevalence of colon cancer in the world and the great interest in targeted anti-cancer therapy, only few tumor-specific gene products have been identified that could serve as targets for the immunological treatment of colorectal cancers. The aim of our study was therefore to identify frequently expressed colon cancer-specific antigens. We performed a large-scale analysis of genes expressed in normal colon and colon cancer tissues isolated from colorectal cancer patients using massively parallel signal sequencing (MPSS). Candidates were additionally subjected to experimental evaluation by semi-quantitative RT-PCR on a cohort of colorectal cancer patients. From a pool of more than 6000 genes identified unambiguously in the analysis, we found 2124 genes that were selectively expressed in colon cancer tissue and 147 genes that were differentially expressed to a significant degree between normal and cancer cells. Differential expression of many genes was confirmed by RT-PCR on a cohort of patients. Despite the fact that deregulated genes were involved in many different cellular pathways, we found that genes expressed in the extracellular space were significantly over-represented in colorectal cancer. Strikingly, we identified a transcript from a chromosome X-linked member of the human endogenous retrovirus (HERV) H family that was frequently and selectively expressed in colon cancer but not in normal tissues. Our data suggest that this sequence should be considered as a target of immunological interventions against colorectal cancer.

Evaluation of genetic mixtures of sorghum lines for anthracnose resistance management

The main objective of this work was to evaluate the diversification of sorghum (Sorghum bicolor) populations as a way to manage resistance to the sorghum anthracnose fungus Colletotrichum graminicola. A total of 18 three-way hybrids were obtained by crossing six single cross male-sterile F1 hybrids, derived by crossing A (non restorer sterile cytoplasm) and B (non restorer normal cytoplasm) lines, with three fertile R (restorer) lines, previously evaluated for their differential reaction to the pathogen. Variation in the level of resistance was observed, as indicated by the values of the area under the disease progress curve (AUDPC) obtained for each hybrid. Lines contributed differently to the level of resistance of each hybrid. All hybrids in which CMSXS169R was the male progenitor were classified as highly resistant. Some hybrids had a level of resistance superior to the maximum levels of each line component individually.

A SAXS study of the structure of gels formed by mixtures of polyoxyalkylene triblock copolymers

Small-angle X-ray scattering was used to characterise aqueous micellar gels of triblock copolymers E137S18E137, E82S9E82, E76S5E76, E62P39E62, and of two mixtures: E137S18E137 and E62P39E62 (Mix 1) and ES2S9E82 and E62P39E62 (Mix 2), each 50/50 wt%. E = oxyethylene, CH2CH2O; S = oxyphenylethylene, OCH2CH(C6H5); and P = oxypropylene, OCH2CH(CH3)- Within the concentration and temperature ranges investigated (30-40 wt% copolymer, 20-80 degrees C), spherical micelles of copolymers E137S18E137, E82S9ES2 and E62P39E62 packed into bodycentred cubic (BCC) structures. Gels of E76S5E76 were stable only at high concentrations and low temperatures, and a 70 wt/o copolymer solution at T = 30 degrees C formed a hexagonal gel consistent with cylindrical micelles. It is likely that the mixed copolymers would form two distributions of micelles, and more complex structures were expected. However, gels of Mix 2 had well-ordered BCC structures, while the less ordered gels of Mix 1 were also best characterised as BCC. (c) 2006 Society of Chemical Industry.

Self-organisation in the assembly of gels from mixtures of different dendritic peptide building blocks

This paper investigates dendritic peptides capable of assembling into nanostructured gels, and explores the effect on self-assembly of mixing different molecular building blocks. Thermal measurements, small angle Xray scattering (SAXS) and circular dichroism (CD) spectroscopy are used to probe these materials on macroscopic, nanoscopic and molecular length scales. The results from these investigations demonstrate that in this case, systems with different "size" and "chirality" factors can self-organise, whilst systems with different "shape" factors cannot. The "size" and "chirality" factors are directly connected with the molecular information programmed into the dendritic peptides, whilst the shape factor depends on the group linking these peptides together-this is consistent with molecular recognition hydrogen bond pathways between the peptidic building blocks controlling the ability of these systems to self-recognise. These results demonstrate that mixtures of relatively complex peptides, with only subtle differences on the molecular scale, can self-organise into nanoscale structures, an important step in the spontaneous assembly of ordered systems from complex mixtures.

Diversity for resilience : multi-scale application of agro-ecology

The integration of ecological principles into agricultural systems presents major opportunities for spreading risk at the crop and farm scale. This paper presents mechanisms by which diversity at several scales within the farming system can increase the stability of production. Diversity of above- and below-ground biota, but also genetic and phenotypic diversity within crops, has an essential role in safeguarding farm production. Novel mixtures of legume-grass leys have been shown to potentially provide significant benefits for pollinator and decomposer ecosystem services but to realise the greatest improvements carefully tailored farm management is needed such as mowing or grazing time, and the type and depth of cutivation. Complex farmland landscapes such as agroforestry systems have the potential to support pollinator abundance and diversity and spread risk across production enterprises. At the crop level, early results indicate that the vulnerability of pollen development, flowering and early grain set to abiotic stress can be ameliorated by managing flowering time through genotypic selection, and through the buffering effects of pollinators. Finally, the risk of sub-optimal quality in cereals can be mitigated through integration of near isogenic lines selected to escape specific abiotic stress events. We conclude that genotypic, phenotypic and community diversity can all be increased at multiple scales to enhance resilience in agricultural systems.

On the Skew-Normal-Cauchy Distribution

In this article, we study further properties of a skew normal distribution, called the skew-normal-Cauchy (SNC) distribution by Nadarajah and Kotz (2003). A stochastic representation is obtained which allows alternative derivations for moments, moments generating function, and skewness and kurtosis coefficients. Issues related to singularity of the Fisher information matrix are investigated.

On the skew-normal calibration model

In this article, we present the EM-algorithm for performing maximum likelihood estimation of an asymmetric linear calibration model with the assumption of skew-normally distributed error. A simulation study is conducted for evaluating the performance of the calibration estimator with interpolation and extrapolation situations. As one application in a real data set, we fitted the model studied in a dimensional measurement method used for calculating the testicular volume through a caliper and its calibration by using ultrasonography as the standard method. By applying this methodology, we do not need to transform the variables to have symmetrical errors. Another interesting aspect of the approach is that the developed transformation to make the information matrix nonsingular, when the skewness parameter is near zero, leaves the parameter of interest unchanged. Model fitting is implemented and the best choice between the usual calibration model and the model proposed in this article was evaluated by developing the Akaike information criterion, Schwarz`s Bayesian information criterion and Hannan-Quinn criterion.