引入圈闭加合法的多统计法联合计算油气资源量探讨

区带油气资源量计算常用到统计法，主要包括规模序列法、发现过程模型法、广义帕莱托法等，但这3种方法在油气资源评价过程中均存在油气藏数量难以确定的问题。为了更精确、合理地计算区带油气资源量，首先通过圈闭加合法分析和预测区带中未发现的大—中型油气藏，然后根据已发现与未发现大—中型油气藏的储量规模序列计算区带油气藏数量，最后根据已确定的油气藏数量采用多统计法联合计算区带油气资源量。通过使用圈闭加合法分析大—中型油气藏储量规模，并计算得出区带油气藏数量，解决了油气藏数量确定这一关键问题，而多统计法的联合使用更进一步提高了油气资源量计算结果的准确性。

Macrobenthic community structure and species composition in the Yellow Sea and East China Sea in jellyfi sh bloom

To understand the characteristics of macrobenthic structures and the relationship between environment and benthic assemblages in jellyfish bloom, we studied the macrobenthos and related environmental factors in the coastal waters of the Yellow Sea and East China Sea. Data were collected during two seasonal cruises in April and August of 2011, and analyzed with multivariate statistical methods. Up to 306 macrobenthic species were registered from the research areas, including 115 species of Polychaeta, 78 of Crustacea, 61 of Mollusca, 30 of Echinodermata, and 22 of other groups. Nine polychaete species occurred at frequencies higher than 25% from the sampling stations： Lumbrineris longifolia, Notomastus latericeus, Nin6e palmata, Ophelina acuminata, Nephtys oligobranchia, Onuphis geophiliformis, Glycera chirori, Terebellides stroemii, and Aricidea fragilis. Both the average biomass and abundance of macrobenthos are higher in August （23.8 g/m^2 and 237.7 ind./m^2） than those in April （11.3 g/m^2 and 128 ind./m^2）; the dissimilarity ofmacrobenthic structures among stations is as high as 70%. In terms of the dissimilarity values, we divided the stations into four clusters in spring and eight in summer. The ABC curve shows that the macrofauna communities in high jellyfish abundance were not changed. Canonical correspondence analysis showed that depth, temperature, median grain size, total organic carbon of sediment and total nitrogen in sediment were important factors affecting the macrozoobenthic community in the study area.

Application of Kernel Independent Component Analysis for Multivariate Statistical Process Monitoring

In this research, a new fault detection method based on kernel independent component analysis （kernel ICA） is developed. Kernel ICA is an improvement of independent component analysis （ICA）, and is different from kernel principal component analysis （KPCA） proposed for nonlinear process monitoring. The basic idea of our approach is to use the kernel ICA to extract independent components efficiently and to combine the selected essential independent components with process monitoring techniques. 12 （the sum of the squared independent scores） and squared prediction error （SPE） charts are adopted as statistical quantities. The proposed monitoring method is applied to Tennessee Eastman process, and the simulation results clearly show the advantages of kernel ICA monitoring in comparison to ICA monitoring.

The Common Principal Component Analyses of Multi-RCMs

Based on a 10-year simulation of six Regional Climate Models(RCMs) in phase II of the Regional Climate Model Inter-Comparison Project(RMIP) for Asia,the multivariate statistical method of common principal components(CPCs) is used to analyze and compare the spatiotemporal characteristics of temperature and precipitation simulated by multi-RCMs over China,including the mean climate states and their seasonal transition,the spatial distribution of interannual variability,and the interannual variation.CPC is an effective statistical tool for analyzing the results of different models.Compared with traditional statistical methods,CPC analyses provide a more complete statistical picture for observation and simulation results.The results of CPC analyses show that the climatological means and the characteristics of seasonal transition over China can be accurately simulated by RCMs.However,large biases exist in the interannual variation in certain years or for individual models.

Joint Network and Fountain Codes Design for RelayAssisted Multi-User System

In relay-assisted multi-user system, relay coding is important to enhance the robustness and reliability of cooperative transmission. For better adaptability and efficiency, two joint network and fountain coding(JNFC) schemes are proposed. When the condition of all direct channels is worse, JNFC scheme based on distributed LT(DLT) codes is used. Otherwise, JNFC scheme based on multi-dimensional LT(MD-LT) codes is suited. For both two above-mentioned schemes, the united degree distribution design method for short-length fountain codes is proposed. For the latter scheme, MD-LT codes are proposed for equal error protection(EEP) of each user. Simulation results and analysis show that the united degree distribution need less decoding overhead compared with other degree distribution for short-length fountain codes. And then, all users are protected equally in despite of asymmetric uplinks.

Physical design method of MPSoC

Floorplan, clock network and power plan are crucial steps in deep sub-micron system-on-chip design. A novel di- agonal floorplan is integrated to enhance the data sharing between different cores in system-on-chip. Custom clock network con- taining hand-adjusted buffers and variable routing rules is constructed to realize balanced synchronization. Effective power plan considering both IR drop and electromigration achieves high utilization and maintains power integrity in our MediaSoC. Using such methods, deep sub-micron design challenges are managed under a fast prototyping methodology, which greatly shortens the design cycle.

Evaluation of Gold Geochemical Anomalies in the Liaodong Paleorift

89 Au geochemical anomalies are delineated by using 1/200000 regional geochemical exploration data. By researching regional geochemical characteristics and the relationship with the geological background, the author points out that： the main factors causing high background of Au geochemical anomalies are Gaixian and Dashiqiao formation of Liaohe group, intrusions of Mesozoic intermediate-acid intrusive rocks. The elements combination types of typical anomalies are determined by using factorial analysis,cluster analysis and other mathematical methods with the combination of elements association in typical anomalies：the composite anomaly of Baiyun gold deposits is Au-As-Sb, Maoling gold deposit is Au-As- Bi-Mo, Wulong gold deposits is Au-As-Bi-W, Xiaotongjiapuzi gold deposit is Au-As-Bi-Mo-Sb. By using multivariate statistical analysis method,62 ore-caused anomaly are preferred in 89 Au geochemical anomalies delineated. On this basis, the 62 anomalies are divided into 4 kinds of anomaly types reference to elements combination types of typical anomalies,the classification results of ore-caused anomalies are： 4 geochemical anomalies of Baiyun type,36 geochemical anomalies of Maoling type,11 geochemical anomalies of Wulong type, 11 geochemical anomalies of Xiaotongjapuzi type. According to the results, the prospecting direction is provided for the futme of gold exploration.

Sorting Data Elements by SOCD Using Centralized Diamond Architecture

Several parallel sorting techniques on different architectures have been studied for many years. Due to the need for faster systems in today＇s world, parallelism can be used to accelerate applications. Nowadays, parallel operations are used to solve computer problems such as sort and search, which result in a reasonable speed. Sorting is one of the most important operations in computing world. The authors always try to find the best in different areas which the premier is speedup. In this paper, the authors issued a sort with O（logn） time complexity on PRAM EREW （Parallel Random Access Machine Exclusive Read Exclusive Write）. The algorithm is designed in a manner that keeps the tradeoff between the number of processor elements in the architecture and execution time. The simulation of the algorithm proves the theoretical analysis of the algorithm. The results of this research can be utilized in developing faster embedded systems. Sorting on Centralized Diamond （SOCD） algorithm is issued on the novel Centralized Diamond architecture which takes the advantages of Single Instruction Multiple Data （SIMD） architecture. This architecture and the sort on it are intuitive and optimal.

Economic Consequences of Gender Equality in Europe

This paper shows influence of gender equality on economy where it analyzed how gender equality in Europe has affected on the development of the frozen food industry and services related to childcare. The development of these industries has given a positive impulse to the development of the whole economy. In this analysis, it is used multiple regressions as one of the most important statistical methods. In the first part of this paper, it shows the connection among the growth of female employment, growth in frozen food expenditure and growth of GDP in United Kingdom. In the second part of paper, it shows the relationship among the growth of labor force participation of women, growth of number of kindergarten and growth of GDP in Hungary. To proof these relationships, it used a multiple regression model. This statistical model was tested by using the T schedule which showed that the model in both the analyses is correct. At the end of the paper, it presents that employment rate and GDP behaves in the same way in European Union. These analyses show that it is necessary to continue to strengthen gender equality if the policy makers want to achieve even greater economic growth. The issue of gender equality is a very important factor in creating employment policy, and statisticians should be more involved in process of employment policy and gender equality

Analysis on the risk factors of second fracture in osteoporosis-related fractures

Objective： To explore the clinical characteristics and risk factors of refracture in patients suffering from osteoporosis-related fractures as well as effective interventions. Methods： From January 2006 to January 2008, both out-patients and in-patients in our hospital who were over 50 years old and suffered from osteoporosis-related fractures were selected for this research. They were divided into fracture group and refracture group. The refracture rate was followed up for 2 years, during which 11 patients developed refracture, thus were included in the refracture group. Therefore, 273 patients, 225 first-fracture cases, aged （67.7± 8.5） years, and 48 refracture cases, aged （72.7±9.5） years, were included in this study. General data including age and sex, fracture types, femoral neck bone mineral density （BMD） T-scores tested by dual-energy X-rays absorptiometry （DEXA）, Charlson index, time-frame between two fractures as well as mobility skill assessment were collected and analyzed by single-factor and multivariate statistical methods. Results： Females accounted for 70.2% of the fracture group and 77.1% of the refracture group. The most common refracture type was vertebral fracture for the first time and femoral neck fracture for the second time during the followup. The second fracture happened 3.7 years after the first one on average. The refracture rate was 2.12% within one year, and 4.66% within two years. Risk factors for a second fracture in osteoporotic fracture patients included age （〉75 years, HR=1.23, 95%CI 1.18-1.29; 〉85 years, HR=1.68, 95% CI 1.60-1.76）, female sex （HR=1.36, 95%CI 1.32-1.40）, prior vertebral fractures （HR= 1.62, 95%CI 1.01-2.07）, prior hip fractures （HR=1.27, 95%CI 0.89-2.42）, BMD T-score〈-3.5 （HR-1.38, 95%CI 1.17-1.72） and weakened motor skills （HR=1.27, 95%CI 1.09-1.40）. Conclusions： The risks of second fracture among patients with initial brittle fracture are substantial. There is adequate time between the first and second fractures for interventions to reduce the risks of refracture, especially for the old women with a vertebral or hip fracture. Medication, motor functional rehabilitation and fall-down prevention training are helpful.

Chemical deception among ant social parasites

Deception is widespread throughout the animal kingdom and various deceptive strategies are exemplified by social parasites. These are species of ants, bees and wasps that have evolved to invade, survive and reproduce within a host colony of another social species. This is achieved principally by chemical deception that tricks the host workers into treating the invading parasite as their own kin. Achieving levels of acceptance into typically hostile host colonies requires an amazing level of decep- tion as social insects have evolved complex species- and colony-specific recognition systems. This allows the detection of for- eigners, both hetero- and con-specific. Therefore, social parasitic ants not only have to overcome the unique species recognition profiles that each ant species produces, but also the subtle variations in theses profiles which generate the colony-specific profiles We present data on the level of chemical similarity between social parasites and their hosts in four different systems and then discuss these data in the wider context with previous studies, especially in respect to using multivariate statistical methods when looking for differences in these systems.

Risk Assessment of Metal Contamination in Soil and Groundwater in Asia： A Review of Recent Trends as well as Existing Environmental Laws and Regulations

Asia is experiencing a more rapid economic growth compared to any other regions. The contamination of soil and groundwater with metals can mainly be attributed to human activities; therefore, risk assessments to characterize the nature and magnitude of risks to humans and ecological receptors from contaminants are important. Risk assessments are often iterative processes, which involve identification and filling data gap. Experimental samplings, geostatistical and multivariate statistical methods as well as multimedia risk assessment modeling are the three major methodologies used in the assessment of metal contamination in soil and groundwater.This review highlights a number of measurements for improving risk calculation methods and expounds scientific approaches that involve the identification of the major source of contamination, exposure pathways and bioavailability of metals. In general, risk assessments of metals in soil and groundwater worldwide are mainly focused on the levels of contamination, identification of exposure pathways, and prediction of the probability of contamination. To date, very limited studies have reported the development of relevant environmental laws and policies in the regulation of soil and groundwater contamination in Asia. The development, variations and limitations in the regulations of soil and groundwater contamination among developed countries may provide helpful guidance for the developing countries in Asia.

Risk Assessment of Heavy Metal Pollution in Sediments of the Fenghe River by the Fuzzy Synthetic Evaluation Model and Multivariate Statistical Methods

Concentrations of heavy metals in 74 sediment samples from the Fenghe River, which originates from the north of the Qinling Mountains and flows through Xi'an, Shaanxi Province, China, were characterized by employing geographic information system(GIS)mapping, fuzzy synthetic assessment, and multivariate statistical analysis to determine the enrichment characteristics of heavy metals as well as their potential risks of pollution to sediments. Al, Cd, and Co were the major pollutants, with a high enrichment factor(EF) value. Heavy metal concentrations from samples near the paper plant were maintained at a high level. Significant enrichment of Al, Ba, Cr, Ni, Pb, and Co was found in the midstream and downstream, while high concentration of Cu occurred in the headwater stream. Based on the cluster and principal component analyses, sediment metals mainly came from the paper plants, agronomic practices, natural sources, and tourism, with a contribution of 51.59%, 23.01%, 14.21%, and 9.88%, respectively. Sediment pollution assessment explored using fuzzy theory based on the entropy method and toxicity coefficient showed that 26, 32, and 11 sites fell into Class III(slightly polluted), Class IV(moderately polluted), and Class V(heavily polluted), respectively, and their scores of membership degree in the polluted level were on the rise, suggesting a relatively high degree of sediment metal pollution in the study area. Closely related to the excessive industrial and agricultural applications, metal pollution in sediment is necessary to be addressed in the Fenghe River.

Using DGT to Assess Cadmium Bioavailability to Ryegrass as Influenced by Soil Properties

A generally accepted method for predicting the bioavailability and transfer of cadmium(Cd) from soil to plants has not yet been established. In this study, the diffusive gradients in thin films(DGT) and conventional extraction methods for metal fractions were used to investigate how effective these methods were at predicting Cd bioavailability to ryegrass(Lolium perenne) and to assess whether these holistic variables were independent of the soil property variables. The influences of soil properties on the predictive capabilities of the different methods were evaluated using multivariate statistics. The Cd concentrations in the shoots and roots of ryegrass correlated more closely with the effective Cd concentration measured by DGT(CE), compared with those with soil total Cd, pore water Cd, and ethylenediaminetetraacetic acid disodium salt(Na2EDTA)- and acetic acid(HOAc)-extractable Cd. When soil properties were included in a stepwise multiple linear regression, Cd transfer to L. perenne was negatively influenced by p H and positively influenced by organic matter(OM). The multivariate statistics showed that the adjusted correlation coefficients for the plots involving soil total Cd, pore water Cd, and Na2EDTA- and HOAc-extractable Cd had been significantly improved after considering the influences of soil properties, which suggested that these methods were p H and OM dependent. For CE, the relationship was p H independent or only dependent in strongly acidic soils. These results suggested that the main soil factors affecting bioavailability had the lowest impact on the DGT technique. Therefore, the DGT technique provided significant advantages over conventional methods when assessing Cd bioavailability.

A novel stochastic collocation method for uncertainty propagation in complex mechanical systems

This paper presents a novel stochastic collocation method based on the equivalent weak form of multivariate function integral to quantify and manage uncertainties in complex mechanical systems. The proposed method, which combines the advantages of the response surface method and the traditional stochastic collocation method, only sets integral points at the guide lines of the response surface. The statistics, in an engineering problem with many uncertain parameters, are then transformed into a linear combination of simple functions' statistics. Furthermore, the issue of determining a simple method to solve the weight-factor sets is discussed in detail. The weight-factor sets of two commonly used probabilistic distribution types are given in table form. Studies on the computational accuracy and efforts show that a good balance in computer capacity is achieved at present. It should be noted that it's a non-gradient and non-intrusive algorithm with strong portability. For the sake of validating the procedure, three numerical examples concerning a mathematical function with analytical expression, structural design of a straight wing, and flutter analysis of a composite wing are used to show the effectiveness of the guided stochastic collocation method.

Physical statistical algorithm for precipitable water vapor inversion on land surface based on multi-source remotely sensed data

Water vapor plays a crucial role in atmospheric processes that act over a wide range of temporal and spatial scales, from global climate to micrometeorology. The determination of water vapor distribution in the atmosphere and its changing pattern is very important. Although atmospheric scientists have developed a variety of means to measure precipitable water vapor(PWV) using remote sensing data that have been widely used, there are some limitations in using one kind satellite measurements for PWV retrieval over land. In this paper, a new algorithm is proposed for retrieving PWV over land by combining different kinds of remote sensing data and it would work well under the cloud weather conditions. The PWV retrieval algorithm based on near infrared data is more suitable to clear sky conditions with high precision. The 23.5 GHz microwave remote sensing data is sensitive to water vapor and powerful in cloud-covered areas because of its longer wavelengths that permit viewing into and through the atmosphere. Therefore, the PWV retrieval results from near infrared data and the indices combined by microwave bands remote sensing data which are sensitive to water vapor will be regressed to generate the equation for PWV retrieval under cloud covered areas. The algorithm developed in this paper has the potential to detect PWV under all weather conditions and makes an excellent complement to PWV retrieved by near infrared data. Different types of surface exert different depolarization effects on surface emissions, which would increase the complexity of the algorithm. In this paper, MODIS surface classification data was used to consider this influence. Compared with the GPS results, the root mean square error of our algorithm is 8 mm for cloud covered area. Regional consistency was found between the results from MODIS and our algorithm. Our algorithm can yield reasonable results on the surfaces covered by cloud where MODIS cannot be used to retrieve PWV.

Multi-objective robust design optimization of a novel negative Poisson's ratio bumper system

Negative Poisson's ratio(NPR) structure has outstanding performances in lightweight and energy absorption, and it can be widely applied in automotive industries. By combining the front anti-collision beam, crash box and NPR structure, a novel NPR bumper system for improving the crashworthiness is first proposed in the work. The performances of the NPR bumper system are detailed studied by comparing to traditional bumper system and aluminum foam filled bumper system. To achieve the rapid design while considering perturbation induced by parameter uncertainties, a multi-objective robust design optimization method of the NPR bumper system is also proposed. The parametric model of the bumper system is constructed by combining the full parametric model of the traditional bumper system and the parametric model of the NPR structure. Optimal Latin hypercube sampling technique and dual response surface method are combined to construct the surrogate models. The multi-objective robust optimization results of the NPR bumper system are then obtained by applying the multi-objective particle swarm optimization algorithm and six sigma criteria. The results yielded from the optimizations indicate that the energy absorption capacity is improved significantly by the NPR bumper system and its performances are further optimized efficiently by the multi-objective robust design optimization method.

Testing against second-order stochastic dominance of multiple distributions

Second-order stochastic dominance plays an important role in reliability and various branches of economics such as finance and decision-making under risk, and statistical testing for the stochastic dominance is often useful in practice. In this paper, we present a test of stochastic equality under the constraint of second-order stochastic dominance based on the theory of empirical processes. The asymptotic distribution of the test statistic is obtained, and a simple method to compute the critical value is derived. Simulation results and real data examples are presented to illustrate the proposed test method.