Probability distribution of the four-phase structure invariants of isomorphously related structure factors and its applications

The probability distribution of the four-phase structure invariants (4PSIs) involving four pairs of structure factors is derived by integrating the direct methods with isomorphous replacement (IR). A simple expression of the reliability parameter for 16 types of invariant is given in the case of a native protein and a heavy-atom derivative. Test calculations on a protein and its heavy-atom derivative using experimental diffraction data show that the reliability for 4PSI estimates is comparable with that for the three-phase structure invariants (3PSIs), and that a large-modulus invariants method can be used to improve the accuracy.

Laser light scattering studies of soluble high-performance polyimides: Solution properties and molar mass distributions

Two soluble high-performance polyimides, poly(BCPOBDA/DMMDA) and poly(ODPA/DMMDA), in CHCl3 at 25 degrees C have been studied using laser light scattering. We found that the z-average radius of gyration ([R(g)]) can be scaled to the weight-average molecular weight (M(w)) as [R(g)] (nm) = 4.95 x 10(-2)M(w)(0.52) and [R(g)] (nm) = 1.25 x 10(-2)M(w)(0.66) respectively for poly(BCPOBDA/DMMDA) and poly(ODPA/DMMDA), indicating that poly(ODPA/DMMDA) in CHCl3 at 25 degrees C has a more extended chain conformation than poly(BCPOBDA/DMMDA). Using the wormlike chain model approach, we found that the Flory characteristic ratios (C*) of poly(BCPOBDA/DMMDA) and poly(ODPA/DMMDA) are similar to 20 and similar to 31, respectively, indicating that both of them have a slightly extended chain conformation in comparison with typical flexible polymer chains, such as polystyrene, whose C-infinity is similar to 10. A combination of the weight-average molar mass (M(w)) with the translational diffusion coefficient distributions (G(D)) has led to D (cm(2)/s) = 3.53 x 10(-4)M(-0.579) and D (cm(2)/s) = 4.30 x 10(-4)M(-0.613) respectively for two soluble high-performance polyimides, poly(BCPOBDA/DMMDA) and poly(ODPA/DMMTA), in CHCl3 at 25 degrees C. Using these two calibrations, we have successfully characterized the molar mass distributions of the two polyimides from their corresponding G(D)s. The exponents of these two calibrations further confirm that both of the polyimides have a slightly extended coil chain conformation in CHCl3. The chain flexibility difference between these two polyimides has also been discussed.

RELATIONSHIP OF THE SEQUENCE DISTRIBUTION OF A POLYMER TO THE CATALYTIC ACTIVITY OF ITS ND COMPLEX

The sequence distribution of the monomeric units in the styrene-acrylic acid copolymer has been obtained by calculation. The probability of long sequences of styrene increases with an increase in the content of the monomer in the copolymer. The highest distribution of short sequences of styrene takes place for the copolymer containing equimolecular amounts of styrene and acrylic acid. The copolymer which has this latter structure is inadequate for the synthesis of highly active supported complexes. When the distributions of long and short sequences of styrene are approximately equal, the activity of the Nd and Fe prepared polymer complexes is higher.

Clay mineral distributions in the southern Yellow Sea and their significance

To better understand the characteristics of the clay minerals in the southern Yellow Sea, the X-ray quantitative determinations have been carried out for the surface samples obtained from the Yellow Sea. With newly compiled clay mineral synoptic maps, the depositional processes were described for four main clay minerals (illite, chlorite, kaolinite and smectite). The analysis shows that most clay minerals are of terrigenous source with the Huanghe River acting as the major sediment supplier. Besides, the source of muddy sediments in the Yellow Sea was also discussed. As for the central Yellow Sea mud (CYSM), the sediments in its northern part mainly come from the Huanghe River, and those in the rest are of multi-origin. Very similarly, a large amount of sediments in the northern part of the southeastern Yellow Sea Mud (SEYSM) derive from the Keum River and Yeong-san River, while those in the southern part are of multi-origin.

Distribution of the nonlinear random ocean wave period

Because of the intrinsic difficulty in determining distributions for wave periods, previous studies on wave period distribution models have not taken nonlinearity into account and have not performed well in terms of describing and statistically analyzing the probability density distribution of ocean waves. In this study, a statistical model of random waves is developed using Stokes wave theory of water wave dynamics. In addition, a new nonlinear probability distribution function for the wave period is presented with the parameters of spectral density width and nonlinear wave steepness, which is more reasonable as a physical mechanism. The magnitude of wave steepness determines the intensity of the nonlinear effect, while the spectral width only changes the energy distribution. The wave steepness is found to be an important parameter in terms of not only dynamics but also statistics. The value of wave steepness reflects the degree that the wave period distribution skews from the Cauchy distribution, and it also describes the variation in the distribution function, which resembles that of the wave surface elevation distribution and wave height distribution. We found that the distribution curves skew leftward and upward as the wave steepness increases. The wave period observations for the SZFII-1 buoy, made off the coast of Weihai (37A degrees 27.6' N, 122A degrees 15.1' E), China, are used to verify the new distribution. The coefficient of the correlation between the new distribution and the buoy data at different spectral widths (nu=0.3-0.5) is within the range of 0.968 6 to 0.991 7. In addition, the Longuet-Higgins (1975) and Sun (1988) distributions and the new distribution presented in this work are compared. The validations and comparisons indicate that the new nonlinear probability density distribution fits the buoy measurements better than the Longuet-Higgins and Sun distributions do. We believe that adoption of the new wave period distribution would improve traditional statistical wave theory.

中国近海和西北太平洋温跃层时空变化分析、模拟及预报

温度跃层是反映海洋温度场的重要物理特性指标，对水下通讯、潜艇活动及渔业养殖、捕捞等有重要影响。本文利用中国科学院海洋研究所“中国海洋科学数据库”在中国近海及西北太平洋（110ºE-140ºE,10ºN-40ºN）的多年历史资料（1930-2002年，510143站次），基于一种改进的温跃层判定方法，分析了该海域温跃层特征量的时空分布状况。同时利用Princeton Ocean Model(POM)，对中国近海，特别是东南沿海的水文结构进行了模拟，研究了海洋水文环境对逆温跃层的影响。最后根据历史海温观测资料，利用EOF分解统计技术，提出了一种适于我国近海及毗邻海域，基于现场有限层实测海温数据，快速重构海洋水温垂直结构的统计预报方法，以达到对现场温跃层的快速估计。 历史资料分析结果表明，受太阳辐射和风应力的影响，20°N以北研究海域，温跃层季节变化明显，夏季温跃层最浅、最强，冬季相反，温跃层厚度的相位明显滞后于其他变量，其在春季最薄、秋季最厚。12月份到翌年3月份，渤、黄及东海西岸，呈无跃层结构，西北太平洋部分海域从1月到3月份，也基本无跃层结构。在黄海西和东岸以及台湾海峡附近的浅滩海域，由于风力搅拌和潮混合作用，温跃层出现概率常年较低。夏季，海水层化现象在近海陆架海域得到了加强，陆架海域温跃层强度季节性变化幅度(0.31°C/m)明显大于深水区(约0.05°C/m)，而前者温跃层深度和厚度的季节性变化幅度小于后者。20°N以南研究海域，温跃层季节变化不明显。逆温跃层主要出现在冬、春季节（10月-翌年5月）。受长江冲淡水和台湾暖流的影响，东南沿海区域逆温跃层持续时间最长，出现概率最大，而在山东半岛北及东沿岸、朝鲜半岛西及北岸，逆温跃层消长过程似乎和黄海暖流有关。多温跃层结构常年出现于北赤道流及对马暖流区。在黑潮入侵黄、东、南海的区域，多温跃层呈现明显不同的季节变化。在黄海中部，春季多温跃层发生概率高于夏季和秋季，在东海西部，多跃层主要出现在夏季，在南海北部，冬季和春季多温跃层发生概率大于夏季和秋季。这些变化可能主要受海表面温度变化和风力驱动的表层流的影响。 利用Princeton Ocean Model(POM)，对中国东南沿海逆温跃层结构进行了模拟，模拟结果显示，长江冲淡水的季节性变化以及夏季转向与实际结果符合较好，基本再现了渤、黄、东海海域主要的环流、温盐场以及逆温跃层的分布特征和季节变化。通过数值实验发现，若无长江、黄河淡水输入，则在整个研究海域基本无逆温跃层出现，因此陆源淡水可能是河口附近逆温跃层出现的基本因素之一。长江以及暖流（黑潮和台湾暖流）流量的增加，均可在不同程度上使逆温跃层出现概率及强度、深度和厚度增加，且暖流的影响更加明显。长江对东南沿海逆温跃层的出现，特别是秋季到冬季初期，有明显的影响，使长江口海域逆温跃层位置偏向东南。暖流对于中国东南沿海的逆温跃层结构，特别是初春时期，有较大影响，使长江口海域的逆温跃层位置向东北偏移。 通过对温跃层长期变化分析得出，黄海冷水团区域，夏季温跃层强度存在3.8年左右的年际变化及18.9年左右的年代际变化，此变化可能主要表现为对当年夏季和前冬东亚地区大气气温的热力响应。东海冷涡区域，夏季温跃层强度存在3.7年的年际变化，在El Nino年为正的强度异常，其可能主要受局地气旋式大气环流变异所影响。谱分析同时表明，该海域夏季温跃层强度还存在33.2年的年代际变化，上世纪70年代中期，温跃层强度由弱转强，而此变化可能与黑潮流量的年代际变化有关。 海洋水温垂直结构的统计预报结果显示，EOF分解的前四个主分量即能够解释原空间点温度距平总方差的95%以上，以海洋表层附近观测资料求解的特征系数推断温度垂直结构分布的结果最稳定。利用东海陆架区、南海深水区和台湾周边海域三个不同区域的实测CTD样本廓线资料，对重构模型的检验结果表明，重构与实测廓线的相关程度超过95%的置信水平。三个区重构与实测温度廓线值的平均误差分别为0.69℃，0.52℃，1.18℃，平均重构廓线误差小于平均气候偏差，统计模式可以很好的估算温度廓线垂直结构。东海陆架海区温度垂直重构廓线与CTD观测廓线获得的温跃层结果对比表明，重构温跃层上界、下界深度和强度的平均绝对误差分别为1.51m、1.36m和0.17℃/m，它们的平均相对误差分别为24.7%、8.9%和22.6%，虽然温跃层深度和强度的平均相对误差较大，但其绝对误差量值较小。而在南海海区，模型重构温跃层上界、下界和强度的平均绝对预报误差分别为4.1m、27.7m和0.007℃/m，它们的平均相对误差分别为16.1%、16.8%和9.5%，重构温跃层各特征值的平均相对误差都在20%以内。虽然南海区温跃层下界深度平均绝对预报误差较大，但相对于温跃层下界深度的空间尺度变化而言（平均温跃层下界深度为168m），平均相对误差仅为16.8%。因此说模型重构的温度廓线可以达到对我国陆架海域、深水区温跃层的较好估算。 基于对历史水文温度廓线观测资料的分析及自主温跃层统计预报模型，研制了实时可利用微机简单、快捷地进行温跃层估算及查询的可视化系统，这是迄今进行大范围海域温跃层统计与实时预报研究的较系统成果。

Spatial distributions and seasonal variations of particulate phosphorus in the Jiaozhou Bay in North China

Based oil the measurements of particulate phosphorus (PP) in the Jiaozhou Bay front May 2003 to April 2004, the spatial distribution, seasonal variation and biogeochemical characteristics of PP Were investigated to Understand the fates and roles of phosphorus in the Jiaozhou Bay ecosystem. The Concentration of the total PP ranged from 0. 07 to 2. 09 mu mol/dm(3). The concentration of POP was from 0. 01 to 1. 83 mu mol/dm(3), with all average of with all average of 0. 33 mu mol/dm(3), which accounted for 50. 4% in total PP. In general, file concentrations of IT in surface water show obvious seasonal variations in the Jiaozhou Bay. POP was the highest in spring, which derived front the accumulation of phyto-detritus and was the lowest ill autumn, which was decomposed into seawaters to participate the recycle of phosphorus. PIP was the highest in spring and summer and Was the lowest in autumn and winter. PLP Was Mainly influenced by river input in the inner bay lint POP derived front autochthonous source in the outer bay. Overkill, the concentrations of IT in the inner bay were higher than those in mouth and the Older bay. In the inner bay. the concentrations of IT with the area near the shore were higher than those in the center of the bay. Totally PP showed the decreasing trend with depth especially in spring and winter. The high value of PP emerged in 20 and 10 in Corresponding to summer and autumn, respectively. The changes of POP showed hysteretic effect compared with the changes of Chl a in the investigated year. However, according to the Change of Chl a, the second high value of POP which should be emerged ill October was missing due to the remineralization of POP and participation in the recycle of phosphorus, which lead to the high concentration of orthophosphate in seawaters.

Phytoplankton distributions and their relationship with the environment in the Changjiang Estuary, China

This study was carried out in the Changjiang Estuary from 19 to 26 May 2003. Based on the data collected from 29 stations, including two anchor stations, phytoplankton taxonomic composition, abundance, diurnal variability and spatial distribution were examined. Eighty-seven species, including 54 species of diatoms and 16 red tide causative species, were identified. Average diversity index (H') and evenness (J) values were 1.04 and 0.40, respectively. A bloom in abundance of certain phytoplankton species, especially Prorocentrum dentatum and Skeletoneina costatum, was thought to be the cause of the low diversity index and evenness values. Total phytoplankton abundance averaged 6.75 x 10(5) cells 1(-1), and was much higher than previous investigation carried out in the same month in 1986. Abundance increased seaward showing a distinct spatial difference, and the dominant species varied with salinity. Correlation between phosphorus and abundance further supported the former conclusion that phosphorus is the controlling factor in phytoplankton growth in the Changjiang Estuary where light is not limiting. Based on the relationship between DO, pH and abundance, it is likely that the bloom was caused by rapid in situ growth of phytoplankton with high nutrients and sufficient light. The data also indicated that the duration of the bloom was not long and

Size dependence of biomass spectra and abundance spectra: the optimal distributions

Based on the hypothesis of self-optimization, we derive four models of biomass spectra and abundance spectra in communities with size-dependent metabolic rates. In Models 1 and 2, the maximum diversity of population abundance in different size classes subject to the constraints of constant mean body mass and constant mean respiration rate is assumed to be the strategy for ecosystems to organize their size structure. In Models 3 and 4, the organizing strategy is defined as the maximum diversity of biomass in different size classes without constraints on mean body mass and subject to the constant mean specific respiration rate of all individuals, i.e. the average specific respiration rate over all individuals of a community or group, which characterizes the mean rate of energy consumption in a community. Models 1 and 2 generate peaked distributions of biomass spectral density whereas Model 3 generates a fiat distribution. In Model 4, the distributions of biomass spectral density and of abundance spectral density depend on the Lagrangian multipler (lambda (2)). When lambda (2) tends to zero or equals zero, the distributions of biomass spectral density and of abundance spectral density correspond to those from Model 3. When lambda (2) has a large negative value, the biomass spectrum is similar to the empirical fiat biomass spectrum organized in logarithmic size intervals. When lambda (2) > 0, the biomass spectral density increases with body mass and the distribution of abundance spectral density is an unimodal curve. (C) 2001 Elsevier Science B.V. All rights reserved.

Summertime ciliate and copepod nauplii distributions and micro-zooplankton herbivorous activity in the Laizhou Bay, Bohai Sea, China

The abundance and biomass of ciliated protozoa and copepod nauplii were investigated at 21 grid stations and two anchored stations in the Laizhou Bay, Bohai Sea, China in June 1998. Dilution incubations were carried out to investigate micro-zooplankton grazing pressure at the anchored stations during spring tide and neap tide. The dominant species were Tintinnopsis amoyensis, T. chinglanensis, T. pallida and aloricate ciliates. A total of 13 species of tintinnids were found. The total abundance of ciliates and nauplii ranged from 30 to 2390 ind l(-1) at grid stations. Tintinnopsis amoyensis was the only ciliate found at the anchored stations and in concentrations which varied from 0 to 6700 ind l(-1). The spatial distribution of ciliates was patchy. Tintinnopsis amoyensis and T. pallida were distributed in the Weihe River mouth and Xiaoqinghe River mouth respectively. The aloricate ciliates, T. chinglanensis and Codonellopsis ostenfeldi dominated offshore in sequence. The water mixing process may affect the spatial pattern of the dominant ciliate species. The abundance and biomass of copepod nauplii were in the range of 0-140 ind l(-1) and 0-7 mu g C l(-1) respectively, with the peak appearing at grid station 15. The total biomass of ciliates and copepod nauplii was in the range of 1(.)5-25 mu g C l(-1). Water column biomass of ciliates and nauplii varied from 2(.)37 to 52(.)3 mg C m(-2). At the anchored stations, the phytoplankton growth rates ranged from undetectable to 0 21 d(-1) and micro-zooplankton grazing rates from 0 13 to 0(.)57 d(-1). The grazing pressure of micro-zooplankton were 12 to 43% of the chlorophyll standing stock and 84 to 267% of the chlorophyll (C) 2000 Academic Press.

Effects of azadirachtin on six inorganic cation distributions in Ostrinia furnacalis (G.)

Azadirachtin (Az), as a botanical insecticide, is relatively safe and biodegradable. It affects a wide vaariety of biological processes, including the reduction of feeding, suspension of molting, death of larvae and pupae, and sterility of emerged adults in a dose-dependent manner. However, the mode of action of this toxin remains obscure. By using ion chromatography, we analyzed changes in six inorganic cation (Li+, Na+, NH4+, K+, Mg2+, and Ca2+) distributions of the whole body and hemolymph in Ostrinia furnacalis (G.) after exposure to sublethal doses of Az. The results showed that Az dramatically interfered with Na+, NH4+, K+, Mg2+, and Ca2+ distributions in hemolymph of O. furnacalis (G.) and concentrations of these five cations dramatically increased. However, in the whole body, the levels of K+, Mg2+, and Ca2+ significantly, decreased after exposure to Az, except that Na+ and NH4+ remained constant. Li+ was undetected in both the control and treated groups in the whole body and hemolymph. It is suggested that Az exerts its insecticidal effects on O. furnacalis (G.) by interfering with the inorganic cation distributions related to ion channels.

基于MRF模型的油气储层属性随机建模方法研究

Stochastic reservoir modeling is a technique used in reservoir describing. Through this technique, multiple data sources with different scales can be integrated into the reservoir model and its uncertainty can be conveyed to researchers and supervisors. Stochastic reservoir modeling, for its digital models, its changeable scales, its honoring known information and data and its conveying uncertainty in models, provides a mathematical framework or platform for researchers to integrate multiple data sources and information with different scales into their prediction models. As a fresher method, stochastic reservoir modeling is on the upswing. Based on related works, this paper, starting with Markov property in reservoir, illustrates how to constitute spatial models for catalogued variables and continuum variables by use of Markov random fields. In order to explore reservoir properties, researchers should study the properties of rocks embedded in reservoirs. Apart from methods used in laboratories, geophysical means and subsequent interpretations may be the main sources for information and data used in petroleum exploration and exploitation. How to build a model for flow simulations based on incomplete information is to predict the spatial distributions of different reservoir variables. Considering data source, digital extent and methods, reservoir modeling can be catalogued into four sorts: reservoir sedimentology based method, reservoir seismic prediction, kriging and stochastic reservoir modeling. The application of Markov chain models in the analogue of sedimentary strata is introduced in the third of the paper. The concept of Markov chain model, N-step transition probability matrix, stationary distribution, the estimation of transition probability matrix, the testing of Markov property, 2 means for organizing sections-method based on equal intervals and based on rock facies, embedded Markov matrix, semi-Markov chain model, hidden Markov chain model, etc, are presented in this part. Based on 1-D Markov chain model, conditional 1-D Markov chain model is discussed in the fourth part. By extending 1-D Markov chain model to 2-D, 3-D situations, conditional 2-D, 3-D Markov chain models are presented. This part also discusses the estimation of vertical transition probability, lateral transition probability and the initialization of the top boundary. Corresponding digital models are used to specify, or testify related discussions. The fifth part, based on the fourth part and the application of MRF in image analysis, discusses MRF based method to simulate the spatial distribution of catalogued reservoir variables. In the part, the probability of a special catalogued variable mass, the definition of energy function for catalogued variable mass as a Markov random field, Strauss model, estimation of components in energy function are presented. Corresponding digital models are used to specify, or testify, related discussions. As for the simulation of the spatial distribution of continuum reservoir variables, the sixth part mainly explores 2 methods. The first is pure GMRF based method. Related contents include GMRF model and its neighborhood, parameters estimation, and MCMC iteration method. A digital example illustrates the corresponding method. The second is two-stage models method. Based on the results of catalogued variables distribution simulation, this method, taking GMRF as the prior distribution for continuum variables, taking the relationship between catalogued variables such as rock facies, continuum variables such as porosity, permeability, fluid saturation, can bring a series of stochastic images for the spatial distribution of continuum variables. Integrating multiple data sources into the reservoir model is one of the merits of stochastic reservoir modeling. After discussing how to model spatial distributions of catalogued reservoir variables, continuum reservoir variables, the paper explores how to combine conceptual depositional models, well logs, cores, seismic attributes production history.