Downscaling of surface moisture flux and precipitation in the Ebro Valley (Spain) using analogues and analogues followed by random forests and multiple linear regression

In this paper, reanalysis fields from the ECMWF have been statistically downscaled to predict from large-scale atmospheric fields, surface moisture flux and daily precipitation at two observatories (Zaragoza and Tortosa, Ebro Valley, Spain) during the 1961-2001 period. Three types of downscaling models have been built: (i) analogues, (ii) analogues followed by random forests and (iii) analogues followed by multiple linear regression. The inputs consist of data (predictor fields) taken from the ERA-40 reanalysis. The predicted fields are precipitation and surface moisture flux as measured at the two observatories. With the aim to reduce the dimensionality of the problem, the ERA-40 fields have been decomposed using empirical orthogonal functions. Available daily data has been divided into two parts: a training period used to find a group of about 300 analogues to build the downscaling model (1961-1996) and a test period (19972001), where models' performance has been assessed using independent data. In the case of surface moisture flux, the models based on analogues followed by random forests do not clearly outperform those built on analogues plus multiple linear regression, while simple averages calculated from the nearest analogues found in the training period, yielded only slightly worse results. In the case of precipitation, the three types of model performed equally. These results suggest that most of the models' downscaling capabilities can be attributed to the analogues-calculation stage.

Adsorption of formaldehyde molecule on the intrinsic and Al-doped graphene: a first principle study

To search for a high sensitivity sensor for formaldehyde (H2CO), We investigated the adsorption of H2CO on the intrinsic and Al-doped graphene sheets using density functional theory (DFT) calculations. Compared with the intrinsic graphene, the Al-doped graphene system has high binding energy value and short connecting distance, which are caused by the chemisorption of H2CO molecule. Furthermore, the density of states (DOS) results show that orbital hybridization could be seen between H2CO and Al-doped graphene sheet, while there is no evidence for hybridization between the H2CO molecule and the intrinsic graphene sheet. Therefore, Al-doped graphene is expected to be a novel chemical sensor for H2CO gas. We hope our calculations are useful for the application of graphene in chemical sensor.

Efficient learning of decomposable models with a bounded clique size

The learning of probability distributions from data is a ubiquitous problem in the fields of Statistics and Artificial Intelligence. During the last decades several learning algorithms have been proposed to learn probability distributions based on decomposable models due to their advantageous theoretical properties. Some of these algorithms can be used to search for a maximum likelihood decomposable model with a given maximum clique size, k, which controls the complexity of the model. Unfortunately, the problem of learning a maximum likelihood decomposable model given a maximum clique size is NP-hard for k > 2. In this work, we propose a family of algorithms which approximates this problem with a computational complexity of O(k · n^2 log n) in the worst case, where n is the number of implied random variables. The structures of the decomposable models that solve the maximum likelihood problem are called maximal k-order decomposable graphs. Our proposals, called fractal trees, construct a sequence of maximal i-order decomposable graphs, for i = 2, ..., k, in k − 1 steps. At each step, the algorithms follow a divide-and-conquer strategy based on the particular features of this type of structures. Additionally, we propose a prune-and-graft procedure which transforms a maximal k-order decomposable graph into another one, increasing its likelihood. We have implemented two particular fractal tree algorithms called parallel fractal tree and sequential fractal tree. These algorithms can be considered a natural extension of Chow and Liu’s algorithm, from k = 2 to arbitrary values of k. Both algorithms have been compared against other efficient approaches in artificial and real domains, and they have shown a competitive behavior to deal with the maximum likelihood problem. Due to their low computational complexity they are especially recommended to deal with high dimensional domains.

Direct observation of adsorption sites of protein impurities and their effects on step advancement of protein crystals

We measured noninvasively step velocities of elementary two-dimensional (2D) islands on {110} faces of tetragonal lysozyme crystals, under various supersaturations, by laser confocal microscopy combined with differential interference contrast microscopy. We studied the correlation between the effects of protein impurities on the growth of elementary steps and their adsorption sites on a crystal surface, using three kinds of proteins: fluorescent-labeled lysozyme (F-lysozyme), covalently bonded dimers of lysozyme (dimer), and a 18 kDa polypeptide (18 kDa). These three protein impurities suppressed the advancement of the steps. However, they exhibited different supersaturation dependencies of the suppression of the step velocities. To clarify the cause of this difference, we observed in situ the adsorption sites of individual molecules of F-lysozyme and fluorescent-labeled dimer (F-dimer) on the crystal surface by single-molecule visualization. We found that F-lysozyme adsorbed preferentially on steps (i.e., kinks), whereas F-dimer adsorbed randomly on terraces. Taking into account the different adsorption sites of F-lysozyme and F-dimer, we could successfully explain the different effects of the impurities on the step velocities. These observations strongly suggest that 18 kDa also adsorbs randomly on terraces. Seikagaku lysozyme exhibited a complex effect that could not alone be explained by the two major impurities (dimer and 18 kDa) present in Seikagaku lysozyme, indicating that trace amounts of other impurities significantly affect the step advancement.

The adsorption of protein molecules at a crystal/solution interface observed by an improved TIRFM

We have improved the ordinary total internal reflection fluorescence microscopy (TIRFM). Two improvements have been achieved, one is the interface between opaque material and solution can be observed, another is the interface far away (usually several ten micro meters) the objective lens can be observed. By this improved TIRFM, the adsorption of protein molecules at a crystal/solution interface had been successfully observed. We have obtained the results of relationship between the amount of adsorbed protein molecules on bunched steps and the height of bunched steps of a protein crystal.

Random response of nonlinear continuous systems

This thesis presents a technique for obtaining the stochastic response of a nonlinear continuous system. First, the general method of nonstationary continuous equivalent linearization is developed. This technique allows replacement of the original nonlinear system with a time-varying linear continuous system. Next, a numerical implementation is described which allows solution of complex problems on a digital computer. In this procedure, the linear replacement system is discretized by the finite element method. Application of this method to systems satisfying the one-dimensional wave equation with two different types of constitutive nonlinearities is described. Results are discussed for nonlinear stress-strain laws of both hardening and softening types.

Absolute measurement of roughness and lateral-correlation length of random surfaces by use of the simplified model of image-speckle contrast

We present a method of image-speckle contrast for the nonprecalibration measurement of the root-mean-square roughness and the lateral-correlation length of random surfaces with Gaussian correlation. We use the simplified model of the speckle fields produced by the weak scattering object in the theoretical analysis. The explicit mathematical relation shows that the saturation value of the image-speckle contrast at a large aperture radius determines the roughness, while the variation of the contrast with the aperture radius determines the lateral-correlation length. In the experimental performance, we specially fabricate the random surface samples with Gaussian correlation. The square of the image-speckle contrast is measured versus the radius of the aperture in the 4f system, and the roughness and the lateral-correlation length are extracted by fitting the theoretical result to the experimental data. Comparison of the measurement with that by an atomic force microscope shows our method has a satisfying accuracy. (C) 2002 Optical Society of America.