Validation of Observed Bedload Transport Pathways Using Morphodynamic Modeling

Phenomena related to braiding, including local scour and fill, channel bar development, migration and avulsion, make numerical morphodynamic modeling of braided rivers challenging. This paper investigates the performance of a Delft3D model, in a 2D depth-averaged formulation, to simulate the morphodynamics of an anabranch of the Rees River (New Zealand). Model performance is evaluated using data from field surveys collected on the falling limb of a major high flow, and using several sediment transport formulas. Initial model results suggest that there is generally good agreement between observed and modeled bed levels. However, some discrepancies in the bed level estimations were noticed, leading to bed level, water depth and water velocity estimation errors

Is there something of the MCT in orientationally disordered crystals ?

Molecular Dynamics simulations have been performed on the orientationally disordered crystal chloroadamantane: a model system where dynamics are almost completely controlled by rotations. A critical temperature T_c = 225 K as predicted by the Mode Coupling Theory can be clearly determined both in the alpha and beta dynamical regimes. This investigation also shows the existence of a second remarkable dynamical crossover at the temperature T_x > T_c consistent with a previous NMR and MD study [1]. This allows us to confirm clearly the existence of a 'landscape-influenced' regime occurring in the temperature range [T_c-T_x] as recently proposed [2,3].Comment: 4 pages, 5 figures, REVTEX

Controlling for transactions bias in regional house price indices

Transactions bias arises when properties that trade are not a random sample of the total housing stock. Price indices are susceptible because they are typically based on transactions data. Existing approaches to this problem rely on Heckman-type correction methods, where a probit regression is used to capture the differences between properties that sell and those that do not sell in a given period. However, this approach can only be applied where there is reliable data on the whole housing stock. In many countries—the UK included—no such data exist and there is little prospect of correcting for transactions bias in any of the regularly updated mainstream house price indices. Thispaper suggests a possible alternative approach, using information at postcode sector level and Fractional Probit Regression to correct for transactions bias in hedonic price indices based on one and a half million house sales from 1996 to 2004, distributed across 1200 postcode sectors in the South East of England

Low Resistance Polycrystalline Diamond Thin Films Deposited by Hot Filament Chemical Vapour Deposition

Polycrystalline diamond thin films with outgrowing diamond (OGD) grains were deposited onto silicon wafers using a hydrocarbon gas (CH4) highly diluted with H2 at low pressure in a hot filament chemical vapour deposition (HFCVD) reactor with a range of gas flow rates. X-ray diffraction (XRD) and SEM showed polycrystalline diamond structure with a random orientation. Polycrystalline diamond films with various textures were grown and (111) facets were dominant with sharp grain boundaries. Outgrowth was observed in flowerish character at high gas flow rates. Isolated single crystals with little openings appeared at various stages at low gas flow rates. Thus, changing gas flow rates had a beneficial influence on the grain size, growth rate and electrical resistivity. CVD diamond films gave an excellent performance for medium film thickness with relatively low electrical resistivity and making them potentially useful in many industrial applications

Landslide Risk Assessment by Using a New Combination Model Based on a Fuzzy Inference System Method

Landslides are one of the most dangerous phenomena that pose widespread damage to property and human lives. Over the recent decades, a large number of models have been developed for landslide risk assessment to prevent the natural hazards. These models provide a systematic approach to assess the risk value of a typical landslide. However, often models only utilize the numerical data to formulate a problem of landslide risk assessment and neglect the valuable information provided by experts’ opinion. This leads to an inherent uncertainty in the process of modelling. On the other hand, fuzzy inference systems are among the most powerful techniques in handling the inherent uncertainty. This paper develops a powerful model based on fuzzy inference system that uses both numerical data and subjective information to formulate the landslide risk more reliable and accurate. The results show that the proposed model is capable of assessing the landslide risk index. Likewise, the performance of the proposed model is better in comparison with that of the conventional techniques