Factors influencing biodeposit production by the New Zealand freshwater mussel Echyridella menziesii

Laboratory experiments on the New Zealand freshwater mussel Echyridella menziesii were used to investigate the short-term effects (7–8 days) of food type on rates of biodeposition and benthic substrate respiration. Post-feeding biodeposition rates ranged from 0.34 to 1.52?mg?g^?1?h^?1 (mean?=?0.50?mg g^?1?h^?1) and were unaffected by the addition of toxin-producing Microcystis. Addition of suspended sediment (30?mg?L^?1) visibly altered substrate composition, and increased total and inorganic biodeposit production rates by 24–33% compared to mussels fed commercial phytoplankton stock. Biodeposition rates of mussels in lake bed substrates were 38% higher than those in silica sand for identical feeding regimes, suggesting that a significant proportion of material produced in this experiment could have been derived from feeding on organic matter in the lake bed sediments. Respiration rates were higher in treatments with Microcystis but were unaffected by the presence of mussels. This laboratory study suggests that biodeposition by E. menziesii is resilient to short-term exposure to Microcystis, and highlights the ability of mussels to alter benthic substrate composition by incorporating suspended sediment into substrates.     

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.     

Application of micropolar plasticity to post failure analysis in geomechanics

A micropolar elastoplastic model for soils is formulated and a series of finite element analyses are employed to demonstrate the use of a micropolar continuum in overcoming the numerical difficulties encountered in application of finite element method in standard Cauchy–Boltzmann continuum. Three examples of failure analysis involving a deep excavation, shallow foundation, and a retaining wall are presented. In all these cases, it is observed that the length scale introduced in the polar continuum regularizes the incremental boundary value problem and allows the numerical simulation to be continued until a clear collapse mechanism is achieved. The issue of grain size effect is also discussed. Copyright © 2004 John Wiley & Sons, Ltd.     

An explicit representation of steady state response of a beam on an elastic foundation to moving harmonic line loads

A closed‐form deflection response of a beam rest is presented in this paper using the integral transform method. The theory of linear partial differential equations is used to represent the deflection of beam subjected to a moving harmonic line load in integration form. The solution is finally carried out using the inverse Fourier transform. To evaluate the integration analytically, poles of the integrand are identified with the help of algebraic equation theory. Residue theorem is then utilized to represent the integration as a contour integral in the complex plane. Closed‐form deflections and numerical results are provided for different combinations of load frequency and velocity. Copyright © 2002 John Wiley & Sons, Ltd.     

Variations in the natural abundance of 15N in estuarine suspended particulate matter: A specific indicator of biological processing

In this study, the ¹⁴N:¹⁵N ratio of suspended particulate material collected from the Tamar river estuary, south-west England, is described. Three populations of particles, distinguishable by their ¹⁵N content, were observed. This investigation has shown that populations of estuarine particles are generated by biological transformations in situ and that the ¹⁵N content of estuarine particles does not merely reflect hydrodynamic mixing of the freshwater and seawater source particulate material.     

THE CHARACTERISTIC OF MARINE ENVIRONMENT IN LINGDINGYANG ESTUARY

1 HYDROLOGIC FEATURES Lingdingyang Estuary, located at the middle south of Guangdong Province, is a bell-shaped estuary with a north-south direction. Its area is about 2100km2. The north of Qi′ao Island and Inner-Lingding Island, and the south of Humen are grouped as Neilingdingyang Estuary, having an area of 1041km2. Affected by topography, runoff and tide, its dynamic condition is very complicated. Different water areas have different hydrologic features. The topography under …     

基于统一强度理论的地基临界荷载公式

基于统一强度理论,按照临界荷载公式的推导方法,得到地基临界荷载的统一解公式。Mohr-Coulomb强度理论计算的结果为其特例。把计算结果与《建筑地基基础设计规范》中的结果进行了对比分析,认为当不同程度地考虑中间主应力σ2的影响时,可以有效地发挥地基的强度潜能。并通过实例计算了统一强度理论参数b取不同值时地基承载力特征值,并进行了对比分析。     

基于负反馈的网络负载调度算法

提出一种基于负反馈权值的动态网络负载调度算法。算法主要用在多出口路由器上，其执行效率高，开销小。基于算法的多出口路由器不仅能够很好的保持出口间的负载均衡。还具有良好的出口容错性能。     

MONITORING THE DIFFUSION OF SUSPENDED SEDIMENTS AND STABILITY OF TIDAL RADIAL SAND RIDGES AREA USING MULTI-SATELLITE REMOTE SENSING DATA

Nine Landsat TM tapes and images and MSS images, 10 NOAA tapes and images and 1 SAR image from 1973 to 1997 were used to analyse the diffusion of suspended sediments and the change of tidal radial sand ridges in the northern part of the Changjiang River delta, the South Yellow Sea. The results showed that the diffusion of suspended sediments was controlled by the tide, net current, and submarine topography in this area. The distribution of suspended sediments had close relationship with thesubmarine topography. The old Huanghe River delta and the Changjiang River comprise the main sediment supply for the formation of radial sand ridges, whose evolution can be divided into three stages since the Huangbe River changed its course and flowed northward into the Bohai Sea.     

Discriminating between pore‐filling load and bed‐structure load: a new porosity‐based method,exemplified for the river Rhine

Sediments contained in the river bed do not necessarily contribute to morphological change. The finest part of the sediment mixture often fills the pores between the larger grains and can be removed without causing a drop in bed level. The discrimination between pore‐filling load and bed‐structure load, therefore, is of practical importance for morphological predictions. In this study, a new method is proposed to estimate the cut‐off grain size that forms the boundary between pore‐filling load and bed‐structure load. The method evaluates the pore structure of the river bed geometrically. Only detailed grain‐size distributions of the river bed are required as input to the method. A preliminary validation shows that the calculated porosity and cut‐off size values agree well with experimental data. Application of the new cut‐off size method to the river Rhine demonstrates that the estimated cut‐off size decreases in a downstream direction from about 2 to 0·05 mm, covariant with the downstream fining of bed sediments. Grain size fractions that are pore‐filling load in the upstream part of the river thus gradually become bed‐structure load in the downstream part. The estimated (mass) percentage of pore‐filling load in the river bed ranges from 0% in areas with a unimodal river bed, to about 22% in reaches with a bimodal sand‐gravel bed. The estimated bed porosity varies between 0·15 and 0·35, which is considerably less than the often‐used standard value of 0·40. The predicted cut‐off size between pore‐filling load and bed‐structure load (D_c,p) is fundamentally different from the cut‐off size between wash‐load and bed‐material load (D_c,w), irrespective of the method used to determine D_c,p or D_c,w. D_c,w values are in the order of 10^?1 mm and mainly dependent on the flow characteristics, whereas D_c,p values are generally much larger (about 10⁰ mm in gravel‐bed rivers) and dependent on the bed composition. Knowledge of D_c,w is important for the prediction of the total sediment transport in a river (including suspended fines that do not interact with the bed), whereas knowledge of D_c,p helps to improve morphological predictions, especially if spatial variations in D_c,p are taken into account. An alternative to using a spatially variable value of D_c,p in morphological models is to use a spatially variable bed porosity, which can also be predicted with the new method. In addition to the morphological benefits, the new method also has sedimentological applications. The possibility to determine quickly whether a sediment mixture is clast‐supported or matrix‐supported may help to better understand downstream fining trends, sediment entrainment thresholds and variations in hydraulic conductivity.