970 resultados para Covariance estimate


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Reversed-phase high performance liquid chromatography (RP-HPLC) was employed to develop predictive models for fish bioconcentration factors (BCF) of organic compounds. Estimation of BCF from RP-HPLC retention parameters on octadecyl-bonded silica gel (ODS), cyanopropyl-bonded silica gel (CN), and phenyl-bonded silica gel (Ph) columns were investigated. The results show that, for a set of compounds belonging to different chemical classes, the CN stationary phase is the best one among the three columns and better than n-octanol/water model for BCF estimation. A multi-column RP-HPLC model, using the retention parameters on the CN and Ph columns as the variables of multiple linear regression equations, was further evaluated to estimate BCF of organic compounds belonging to different chemical classes, and the results show that the multi-column RP-HPLC model is better than that of any single RP-HPLC column for BCF estimation.

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The algebraic formulas of 1.5 and 2.5 rank are given for four space groups P2(1), Pn, Pna2(1), P2(1)2(1)2(1). It is better that the results of applying them to estimating general type of phases for four correspondent crystal structures. And a method of transforming algebraic formulas from 1.5(2.5) rank is proposed.

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Previously we suggested that four proteins including aldolase and triose phosphate isomerase (TPI) evolved with approximately constant rates over long periods covering the whole animal phyla. The constant rates of aldolase and TPI evolution were reexamined based on three different models for estimating evolutionary distances, It was shown that the evolutionary rates remain essentially unchanged in comparisons not only between different classes of vertebrates but also between vertebrates and arthropods and even between animals and plants, irrespective of the models used, Thus these enzymes might be useful molecular clocks for inferring divergence times of animal phyla, To know the divergence time of Parazoa and Eumetazoa and that of Cephalochordata and Vertebrata, the aldolase cDNAs from Ephydatia fluviatilis, a freshwater sponge, and the TPI cDNAs from Ephydatia fluviatilis and Branchiostoma belcheri an amphioxus, have been cloned and sequenced, Comparisons of the deduced amino acid sequences of aldolase and TPI from the freshwater sponge with known sequences revealed that the Parazoa-Eumetazoa split occurred about 940 million years ago (Ma) as determined by the average of two proteins and three models, Similarly, the aldolase and TPI clocks suggest that vertebrates and amphioxus last shared a common ancestor around 700 Ma and they possibly diverged shortly after the divergence of deuterostomes and protostomes.

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A new model is proposed to estimate the significant wave heights with ERS-1/2 scatterometer data. The results show that the relationship between wave parameters and radar backscattering cross section is similar to that between wind and the radar backscattering cross section. Therefore, the relationship between significant wave height and the radar backscattering cross section is established with a neural network algorithm, which is, if the average wave period is <= 7s, the root mean square of significant wave height retrieved from ERS-1/2 data is 0.51 m, or 0.72 m if it is >7s otherwise.

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数值模式是潮波研究的一种有利手段,但在研究中会面临各种具体问题,包括开边界条件的确定、底摩擦系数和耗散系数的选取等。数据同化是解决这些问题的一种途径,即利用有限数量的潮汐观测资料对潮波进行最优估计,其根本目的是迫使模型预报值逼近观测值,使模式不要偏离实际情况太远。本文采用了一种优化开边界方法,沿着数值模型的开边界优化潮汐水位信息,目的是设法使数值解在动力约束的意义下接近观测值,获得研究区域的潮汐结果。边界值由指定优化问题的解来定,以提高模拟区域的潮汐精度,最优问题的解是基于通过开边界的能量通量的变化,处理开边界处的观测值与计算值之差的最小化。这里提供了辐射型边界条件,由Reid 和Bodine(本文简称为RB)推导,我们将采用的优化后的RB方法(称为ORB)是优化开边界的特殊情况。 本文对理想矩形海域( E- E, N- N, 分辨率 )进行了潮波模拟,有东部开边界,模式采用ECOM3D模式。对数据结果的误差分析采用,振幅平均偏差,平均绝对偏差,平均相对误差和均方根偏差四个值来衡量模拟结果的好坏程度。 需要优化入开边界的解析潮汐值本文采用的解析解由方国洪《海湾的潮汐与潮流》(1966年)方法提供,为验证本文所做的解析解和方文的一致,本文做了其第一个例子的关键值a,b,z,结果与其结果吻合的相当好。但略有差别,分析的可能原因是两法在具体迭代方案和计算机保留小数上有区别造成微小误差。另外,我们取m=20,得到更精确的数值,我们发现对前十项的各项参数值,取m=10,m=20各项参数略有改进。当然我们可以获得m更大的各项参数值。 同时为了检验解析解的正确性讨论m和l变化对边界值的影响,结果指出,增大m,m=20时,u的模最大在本身u1或u2的模的6%;m=100时,u的模最大在本身u1或u2的模的4%;m再增大,m=1000时,u的模最大在本身u1或u2的模的4%,改变不大。当l<1时, =0处u的模最大为2。当l=1时, =0处u的模最大为0.1,当l>1时,l越大,u的模越小,当l=10时,u的模最大为0.001,可以认为为0。 为检验该优化方法的应用情况,我们对理想矩形区域进行模拟,首先将本文所采用的优化开边界方法应用于30m的情况,在开边界优化入开边界得出模式解,所得模拟结果与解析解吻合得相当好,该模式解和解析解在整个区域上,振幅平均绝对偏差为9.9cm,相位平均绝对偏差只有4.0 ,均方根偏差只有13.3cm,说明该优化方法在潮波模型中有效。 为验证该优化方法在各种条件下的模拟结果情况,在下面我们做了三类敏感性试验: 第一类试验:为证明在开边界上使用优化方法相比于没有采用优化方法的模拟解更接近于解析解,我们来比较ORB条件与RB条件的优劣,我们模拟用了两个不同的摩擦系数,k分别为:0,0.00006。 结果显示,针对不同摩擦系数,显示在开边界上使用ORB条件的解比使用RB条件的解无论是振幅还是相位都有显著改善,两个试验均方根偏差优化程度分别为84.3%,83.7%。说明在开边界上使用优化方法相比于没有采用优化方法的模拟解更接近于解析解,大大提高了模拟水平。上述的两个试验得出, k=0.00006优化结果比k=0的好。 第二类试验,使用ORB条件确定优化开边界情况下,在东西边界加入出入流的情况,流考虑线性和非线性情况,结果显示,加入流的情况,潮汐模拟的效果降低不少,流为1Sv的情况要比5Sv的情况均方根偏差相差20cm,而不加流的情况只有0.2cm。线性流和非线性流情况两者模式解相差不大,振幅,相位各项指数都相近, 说明流的线性与否对结果影响不大。 第三类试验,不仅在开边界使用ORB条件,在模式内部也使用ORB条件,比较了内部优化和不优化情况与解析解的偏差。结果显示,选用不同的k,振幅都能得到很好的模拟,而相位相对较差。另外,在内部优化的情况下,考虑不同的k的模式解, 我们选用了与解析解相近的6个模式解的k,结果显示,不同的k,振幅都能得到很好的模拟,而相位较差。 总之,在开边界使用ORB条件比使用RB条件好,振幅相位都有大幅度改进,在加入出入流情况下,流的大小对模拟结果有影响,但线形流和非线性流差别不大。内部优化的结果显示,模式采用不同的k都能很好模拟解析解的振幅。

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The eddy covariance technique provides measurements of net ecosystem exchange (NEE) Of CO2 between the atmosphere and terrestrial ecosystems, which is widely used to estimate ecosystem respiration and gross primary production (GPP) at a number Of CO2 eddy flux tower sites. In this paper, canopy-level maximum light use efficiency, a key parameter in the satellite-based Vegetation Photosynthesis Model (VPM), was estimated by using the observed CO2 flux data and photosynthetically active radiation (PAR) data from eddy flux tower sites in an alpine swamp ecosystem, an alpine shrub ecosystem and an alpine meadow ecosystem in Qinghai-Tibetan Plateau, China. The VPM model uses two improved vegetation indices (Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI)) derived from the Moderate Resolution Imaging Spectral radiometer (MODIS) data and climate data at the flux tower sites, and estimated the seasonal dynamics of GPP of the three alpine grassland ecosystems in Qinghai-Tibetan Plateau. The seasonal dynamics of GPP predicted by the VPM model agreed well with estimated GPP from eddy flux towers. These results demonstrated the potential of the satellite-driven VPM model for scaling-up GPP of alpine grassland ecosystems, a key component for the study of the carbon cycle at regional and global scales. (c) 2006 Elsevier Inc. All rights reserved.

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The soil respiration and net ecosystem productivity of Kobresia littledalei meadow ecosystem was investigated at Dangxiong grassland station, one grassland field station of Lhasa Plateau Ecosystem Research Station. Soil respiration and soil heterotrophic respiration were measured at the same time by using Li6400-09 chamber in growing season of year 2004. The response of soil respiration and its components, i.e. microbial heterotrophic respiration and root respiration to biotic and abiotic factors were addressed. We studied the daily and seasonal variation on Net Ecosystem carbon Exchange (NEE) measured by eddy covariance equipments and then the regression models between the NEE and the soil temperature. Based on the researches, we analyzed the seasonal variation in grass biomass and estimated NEE combined the Net Ecosystem Productivity with heterogeneous respiration and then assessed the whether the area is carbon source or carbon sink. 1.Above-ground biomass was accumulated since the grass growth started from May; On early September the biomass reached maximum and then decreased. The aboveground net primary production (ANPP) was 150.88 g m~" in 2004. The under-ground biomass reached maximum when the aboveground start to die back. Over 80% of the grass root distributed at the soil depth from 0 to 20cm. The underground NPP was 1235.04 g m"2.. Therefore annual NPP wasl.385X103kg ha"1, i.e.6236.6 kg C ha"1. 2. The daily variation of soil respiration showed single peak curve with maximum mostly at noon and minimum 4:00-6:00 am. Daily variations were greater in June, July and August than those in September and October. Soil respiration had strong correlation with soil temperature at 5cm depth while had weaker correlation with soil moisture, air temperature, surface soil temperature, and so on. But since early September the soil respiration had a obviously correlation with soil moisture at 5cm depth. Biomass had a obviously linearity correlation with soil respiration at 30th June, 20th August, and the daytime of 27th September except at 23lh October and at nighttime of 27th September. We established the soil respiration responding to the soil temperature and to estimate the respiration variation during monsoon season (from June through August) and dry season (May, September and October). The regression between soil respiration and 5cm soil temperature were: monsoon season (June through August), Y=0.592expfl()932\ By estimating , the soil daily respiration in monsoon season is 7.798gCO2m"2 and total soil respiration is 717.44 gCC^m" , and the value of Cho is 2.54; dry season (May, September and October), Y=0.34exp°'085\ the soil daily respiration is 3.355gCO2m~2 and total soil respiration is 308.61 gCC^m", and the value of Cho is 2.34. So the total soil respiration in the grown season (From May to October) is 1026.1 g CO2IT1"2. 3. Soil heterogeneous respiration had a strong correlation with soil temperature especially with soil temperature at 5cm depth. The variation range in soil heterogeneous respiration was widely. The regression between soil heterogeneous respiration and 5cm soil temperature is: monsoon season, Y=0.106exp ' 3x; dry season, Y=0.18exp°"0833x.By estimating total soil heterotrophic respiration in monsoon season is 219.6 gCC^m"2, and the value of Cho is 3.78; While total soil heterogeneous respiration in dry season is 286.2 gCCbm"2, and the value of Cho is 2.3. The total soil heterotrophic respiration of the year is 1379.4kg C ha"1. 4. We estimated the root respiration through the balance between soil respiration and the soil heterotrophic respiration. The contribution of root respiration to total respiration was different during different period: re-greening period 48%; growing period 69%; die-back period 48%. 5. The Ecosystem respiration was relatively strong from May to October, and of which the proportion in total was 97.4%.The total respiration of Ecosystem was 369.6 g CO2 m" .we got the model of grass respiration respond to the soil temperature at 5cm depth and then estimated the daytime grass respiration, plus the nighttime NEE and daytime soil respiration. But when we estimated the grass respiration, we found the result was negative, so the estimating value in this way was not close. 6. The estimating of carbon pool or carbon sink. The NPP minus the soil heterogeneous respiration was the NEE, and it was 4857.3kg C o ha"1, which indicated that the area was the carbon sink.

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The Coulomb explosion of ammonia clusters induced by nanosecond laser at 532 not with an intensity of similar to 10(12) Wcm(-2) has been studied by time of flight mass spectrometry. The dominant multiply charged ions are N3+ and N2+ with kinetic energies of 110 and 50 eV respectively. The electrons generated from the multiphoton ionization are heated through inverse bremsstrahlung by the laser field when colliding with neutral or ionic particles. When their energies surpass the corresponding ionization potentials of the molecules or ions, the subsequent electron impact ionization may take place thus resulting in multi-charged nitrogen ions. Covariance analysis is made to study the possible pathways of the Coulomb explosion.

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Estimation of the skeleton of a directed acyclic graph (DAG) is of great importance for understanding the underlying DAG and causal effects can be assessed from the skeleton when the DAG is not identifiable. We propose a novel method named PenPC to estimate the skeleton of a high-dimensional DAG by a two-step approach. We first estimate the nonzero entries of a concentration matrix using penalized regression, and then fix the difference between the concentration matrix and the skeleton by evaluating a set of conditional independence hypotheses. For high-dimensional problems where the number of vertices p is in polynomial or exponential scale of sample size n, we study the asymptotic property of PenPC on two types of graphs: traditional random graphs where all the vertices have the same expected number of neighbors, and scale-free graphs where a few vertices may have a large number of neighbors. As illustrated by extensive simulations and applications on gene expression data of cancer patients, PenPC has higher sensitivity and specificity than the state-of-the-art method, the PC-stable algorithm.

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p.1-16

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p.1-16