A New Approach to Explore the Surface Profile of Clay Soil Using White Light Interferometry.

In order to have a better understanding of the real contact area of granular materials, the white light interference method is applied to explore the real surface morphology of clay soils under high stress. Analysis of the surface profile indicates that there exists a support point height z0 with the highest distribution frequency. A concept of a real contact region (from z0 to z0 + d90; d90 represents the particle size corresponding to 90% of the volume fraction) is proposed by combining a surface profile with the particle size distribution of clay soil. It was found that under the compressive stress of 106 MPa-529 MPa, the actual contact area ratio of clay soil varies between 0.375 and 0.431. This demonstrates an increasing trend with the rise of stress. On the contrary, the apparent porosity decreases with an increasing stress, varying between 0.554 and 0.525. In addition, as the compressive stress increases, the cumulative frequency of apparent profile height (from z0 - d90 to z0 + d90) has a concentrated tendency with a limited value of 0.9.

A mathematical model of mucilage expansion in myxospermous seeds of Capsella bursa-pastoris (shepherd's purse).

BACKGROUND AND AIMS: Myxospermy is a term which describes the ability of a seed to produce mucilage upon hydration. The mucilage is mainly comprised of plant cell-wall polysaccharides which are deposited during development of those cells that comprise the seed coat (testa). Myxospermy is more prevalent among those plant species adapted to surviving on arid sandy soils, though its significance in determining the ecological fitness of plants is unclear. In this study, the first mathematical model of myxospermous seed mucilage expansion is presented based on seeds of the model plant species Capsella bursa-pastoris (shepherd's purse). METHODS: The structures underpinning the expansion process were described using light, electron and time-lapse confocal micrographs. The data and experimental observations were used to create a mathematical model of myxospermous seed mucilage expansion based on diffusion equations. KEY RESULTS: The mucilage expansion was rapid, taking 5 s, during which the cell mucilage volume increased 75-fold. At the level of the seed, this represented a 6-fold increase in seed volume and a 2·5-fold increase in seed surface area. These increases were shown to be a function of water uptake (16 g water g(-1) mucilage dry weight), and relaxation of the polymers which comprised the mucilage. In addition, the osmotic pressure of the seed mucilage, estimated by assessing the mucilage expansion of seeds hydrated in solutions of varying osmotic pressure, was -0·54 MPa (equivalent to 0·11 M or 6·6 g L(-1) NaCl). CONCLUSIONS: The results showed that the mucilage may be characterized as hydrogel and seed-mucilage expansion may be modelled using the diffusion equation described. The potential of myxospermous seeds to affect the ecological services provided by soil is discussed briefly.

A physics-informed statistical learning framework for forecasting local suspended sediment concentrations in marine environment.

An in-situ monitoring of water quality (suspended sediment concentration, SSC) and concurrent hydrodynamics was conducted in the subaqueous Yellow River Delta in China. Empirical mode decomposition and spectral analysis on the SSC time series reveal the different periodicities of each physical mechanism that contribute to the SSC variations. Based on this physical understanding, the decomposed SSC time series were trained separately with a newly-proposed augmented lncosh ridge regression, in which (1) a lncosh function was incorporated in traditional ridge regression for handling outliers in original data, and (2) the temporal auto-correlation in the decomposed SSC series was used for augmented regression. Finally, the trained sub-series were added up as the final prediction. The advantages of this decomposition-ensemble framework is that it depends on SSC only, superior to the normal process-based models which need the concurrent hydrodynamics for estimating bed shear stress. This will not only reduce the measurement uncertainties of the input when training the data-driven model, but also save the prediction cost as no other parameters than SSC need to be measured and input for running the model. The framework realized 6-hour-ahead high-accuracy forecasting with mean relative errors of 5.80-9.44% in the present case study. The proposed framework can be extended to forecast any signal that is superposed by components with various timescales (periodicities) which is common in nature.

Pore Structure of Grain-Size Fractal Granular Material.

Numerous studies have proven that natural particle-packed granular materials, such as soil and rock, are consistent with the grain-size fractal rule. The majority of existing studies have regarded these materials as ideal fractal structures, while few have viewed them as particle-packed materials to study the pore structure. In this study, theoretical analysis, the discrete element method, and digital image processing were used to explore the general rules of the pore structures of grain-size fractal granular materials. The relationship between the porosity and grain-size fractal dimension was determined based on bi-dispersed packing and the geometric packing theory. The pore structure of the grain-size fractal granular material was proven to differ from the ideal fractal structure, such as the Menger sponge. The empirical relationships among the box-counting dimension, lacunarity, succolarity, grain-size fractal dimension, and porosity were provided. A new segmentation method for the pore structure was proposed. Moreover, a general function of the pore size distribution was developed based on the segmentation results, which was verified by the soil-water characteristic curves from the experimental database.

The rheological properties of the seed coat mucilage of Capsella bursa-pastoris L. Medik. (shepherd's purse).

The outer surface of myxospermous seed coats contains mucilage which absorbs large amounts of water relative to its dry weight. Ecologically, the seed mucilage can affect seed germination and dormancy. Upon hydration, a large proportion of the seed mucilage is lost to the soil and the physics of soil-seed mucilage interactions has not been assessed. Towards that end, the dynamic rheological properties of mucilage extracted from Capsella bursa-pastoris L. Medik. (shepherd's purse) seeds were assessed as a function of mucilage concentration (1-10% [w/w]), temperature (0-80°C) and shear frequency (0.1-100 rad s-1). The seed mucilage was shear thinning and was classified as a highly viscous "weak gel". The relationship between the viscoelastic parameters (viscosity, η*, storage and loss modulus, G' and G″, yield and flow stresses, τy and τf) and mucilage concentration were well fitted by power law models. The values of η*, G' and G″ increased as temperature increased above 40°C and were also slightly frequency dependent. The shepherd's purse seed mucilage is more viscous than that from other plant parts, such as fruits and roots. These properties highlight the possibility that seed mucilage may affect soil conditions and therefore present an additional facilitative ecological role (beyond that already reported, which directly affect seed biology); and this is discussed.