Stochastic particle packing with specified granulometry and porosity

This work presents a technique for particle size generation and placement in arbitrary closed domains. Its main application is the simulation of granular media described by disks. Particle size generation is based on the statistical analysis of granulometric curves which are used as empirical cumulative distribution functions to sample from mixtures of uniform distributions. The desired porosity is attained by selecting a certain number of particles, and their placement is performed by a stochastic point process. We present an application analyzing different types of sand and clay, where we model the grain size with the gamma, lognormal, Weibull and hyperbolic distributions. The parameters from the resulting best fit are used to generate samples from the theoretical distribution, which are used for filling a finite-size area with non-overlapping disks deployed by a Simple Sequential Inhibition stochastic point process. Such filled areas are relevant as plausible inputs for assessing Discrete Element Method and similar techniques

Inflation in Realistic D-Brane Models

We find successful models of D-brane/anti-brane inflation within a string context. We work within the GKP-KKLT class of type IIB string vacua for which many moduli are stabilized through fluxes, as recently modified to include `realistic' orbifold sectors containing standard-model type particles. We allow all moduli to roll when searching for inflationary solutions and find that inflation is not generic inasmuch as special choices must be made for the parameters describing the vacuum. But given these choices inflation can occur for a reasonably wide range of initial conditions for the brane and antibrane. We find that D-terms associated with the orbifold blowing-up modes play an important role in the inflationary dynamics. Since the models contain a standard-model-like sector after inflation, they open up the possibility of addressing reheating issues. We calculate predictions for the CMB temperature fluctuations and find that these can be consistent with observations, but are generically not deep within the scale-invariant regime and so can allow appreciable values for $dn_s/d\ln k$ as well as predicting a potentially observable gravity-wave signal. It is also possible to generate some admixture of isocurvature fluctuations.Comment: 39 pages, 21 figures; added references; identified parameters combining successful inflation with strong warping, as needed for consistency of the approximation

Testing Logselfsimilarity of Soil Particle Size Distribution: Simulation with Minimum Inputs

Particle size distribution (PSD) greatly influences other soil physical properties. A detailed textural analysis is time-consuming and expensive. Soil texture is commonly reported in terms of mass percentages of a small number of size fractions (typically, clay, silt and sand). A method to simulate the PSD from such a poor description or even from the poorest description, consisting in the mass percentages of only two soil size fractions, would be extremly useful for prediction purposes. The goal of this paper is to simulate soil PSDs from the minimum number of inputs, i.e., two and three textural fraction contents, by using a logselfsimilar model and an iterated function system constructed with these data. High quality data on 171 soils are used. Additionally, the characterization of soil texture by entropy-based parameters provided by the model is tested. Results indicate that the logselfsimilar model may be a useful tool to simulate PSD for the construction of pedotransfer functions related to other soil properties when textural information is limited to moderate textural data

Identification of new therapeutic targets for osteoarthritis through genome-wide analyses of UK Biobank data

Osteoarthritis is the most common musculoskeletal disease and the leading cause of disability globally. Here, we performed a genome-wide association study for osteoarthritis (77,052 cases and 378,169 controls), analyzing four phenotypes: knee osteoarthritis, hip osteoarthritis, knee and/or hip osteoarthritis, and any osteoarthritis. We discovered 64 signals, 52 of them novel, more than doubling the number of established disease loci. Six signals fine-mapped to a single variant. We identified putative effector genes by integrating expression quantitative trait loci (eQTL) colocalization, fine-mapping, and human rare-disease, animal-model, and osteoarthritis tissue expression data. We found enrichment for genes underlying monogenic forms of bone development diseases, and for the collagen formation and extracellular matrix organization biological pathways. Ten of the likely effector genes, including TGFB1 (transforming growth factor beta 1), FGF18 (fibroblast growth factor 18), CTSK (cathepsin K), and IL11 (interleukin 11), have therapeutics approved or in clinical trials, with mechanisms of action supportive of evaluation for efficacy in osteoarthritis

Weber and church governance: religious practice and economic activity

The debate about the relationship between religion and economic activity in the wake of Weber has been cast largely in terms of belief and values. This article suggests an alternative focus on practice. It argues that taken for granted practices of church governance formed to-hand resources for the organization of economic activity. The argument is developed through an examination of the historical development of church governance practices in the Presbyterian Church of Scotland, with particular emphasis on the way in which theological belief gave rise to practices of accountability and record keeping. In turn such practices contributed to a ‘culture of organization’ which had implications for economic activity. A focus on governance practices can help to illuminate enduring patterns of difference in the organization of economic activity

Pasture yield and soil physical property responses to soil compaction from treading and grazing - a review

This paper reviews animal treading and the associated effects on soil physical properties and pasture productivity from treading-induced soil compaction and pugging. Response curve relationships between soil physical properties (e.g. macroporosity, air-filled porosity, bulk density) and pasture and crop yield are reviewed. Optimum soil macroporosity for maximum pasture and crop yield ranges from 6 to 17% v/v, but there is a paucity of yield response curves for pastoral systems, particularly critical or optimum values of soil physical properties. There is little information available on the effects of cattle treading on soil physical properties and consequently pasture yield in seasons when soil pugging and poaching is minimised. Such information is needed to provide practical and rigorously tested decision support tools for land managers during grazing seasons. Knowledge of yield response curves, and critical or optimum values of soil physical properties for field pasture-based grazing systems, is required for improved farm-system production and economic decision support

Inter-particle contact heat transfer model: an extension to soils at elevated temperatures

A simple 'inter-particle contact heat transfer' model for predicting effective thermal conductivity of soils at moderate temperatures (0-30degreesC) has been extended up to 90degreesC. The extended model accounts for latent heat transport by water vapour diffusion in soil air above the permanent wilting point; below that point, the soil thermal conductivity is approximated by linear interpolation without latent heat effect. By and large the best results are obtained when the latent heat is used only in the 'self consistent approximation' model with an overall root mean square error of 35% for all soils under consideration or 26% when excluding volcanic soils. This option can also be applied to moderate temperatures at which the enhanced heat transfer is negligibly small. Copyright (C) 2005 John Wiley Sons, Ltd

Comparação de modelos matemáticos para o traçado de curvas granulométricas Comparison of mathematical models for fitting particle-size distribution curves

A distribuição granulométrica de partículas sólidas é essencial para as áreas de material de construção, mecânica dos solos, física dos solos, hidrossedimentologia, entre outras. As técnicas utilizadas na avaliação da distribuição granulométrica de amostras resultam em valores pontuais, dependendo de posterior interpolação para o traçado da curva granulométrica e a obtenção de diâmetros característicos específicos. A transformação de valores pontuais em funções contínuas pode ser realizada por meio de modelos matemáticos. Entretanto, há poucos estudos com a finalidade de determinar o melhor modelo para o ajuste de curvas granulométricas. O objetivo deste trabalho foi testar e comparar 14 diferentes modelos passíveis de utilização no traçado da curva granulométrica de partículas sólidas com base em quatro pontos medidos. O parâmetro de comparação entre os modelos foi a soma de quadrado dos erros entre os valores medidos e calculados. Os modelos mais recomendados no traçado da curva granulométrica, a partir de quatro pontos, são os de Skaggs et al. 3P, Lima & Silva 3P, Weibull 3P e Morgan et al. 3P, todos com três parâmetros de ajuste.<br>Particle-size distribution is fundamental for characterizing construction materials, soil mechanics, soil physics, sediment-flux in rivers, and others. The techniques used to determine the particle-size distribution of a sample are point-wise, demanding posterior interpolation to fit the complete particle-size distribution curve and to obtain values of specific diameters. The transformation of discrete points into continuous functions can be made by mathematical models. However, there are few studies to determine the best model to fit particle-size distribution curves. The objective of this work was to test and compare 14 different models with feasibility to fit the cumulative particle-size distribution curve based on four measured points. The parameter used to compare the models was the sum of the square errors between the measured and calculated values. The most recommendable models to fit the particle-size distribution curve, based on four discrete points, are Skaggs et al. 3P, Lima & Silva 3P, Weibull 3P, and Morgan et al. 3P, all using three fitting parameters