Statistical simulation analysis of the correlation between the annual estimated key regions with a certain seismic risk and the earthquakes in China

We have analyzed the correlation of the annual key regions with a certain seismic risk and the earthquakes in China from 1990-1997 by the statistical simulation analysis method. The statistical simulation analysis method is effective to deal with space-time heterogeneity of earthquakes and risk regions, the values of simulating random prediction probability have been got after 105 count, the objective results have been got by comparing average probability between the simulating prediction and the practical prediction. The results show: (1) average probability of the practical prediction for the annual seismic key risk regions in China from 1990-1997 is higher than that of the simulating prediction by 0.037 19 using the method of pure random simulating risk regions; (2) average probability of the practical prediction is higher than that of the simulation prediction by 0.021 83 using the method of simulating risk regions with the different probability based on the earthquake activity; (3) average probability of the practical prediction is much higher than that of the simulating prediction by 0.209 62 in West Xinjiang region using the method of dividing the Chinese Continent into the three regions: West Xinjiang region, Southwest region of China and the other region.

Applications of the representative points in statistical simulations

The paper gives a new approach to statistical simulation and resampling by the use of numbertheoretic methods and representative points. Resempling techniques take samples from an approximate population. The bootstrap suggests to use a random sample to form an approximate population. We propose to construct some approximate population distribution by the use of two kinds of representative points, and samples are taken from these approximate distributions. The statistical inference is based on those samples. The statistical inference in this paper involves estimation of mean, variance, skewness, kurtosis, quantile and density of the population distribution. Our results show that the new method can significantly improve the results by the use of Monte Carlo methods.

Classifying the sedimentary environments of the Xincun Lagoon,Hainan Island,by system cluster and principal component analyses

An understanding of the sedimentary environment in relation to its controlling factors is of great importance in coastal geomorphology,ecology,tourism and aquaculture studies.We attempt to deal with this issue,using a case study from the Xincun Lagoon,Hainan Island in southern China.For the study,surficial sediment samples were collected,together with hydrodynamic and bathymetric surveys,during August 2013.Numerical simulation was carried out to obtain high-spatial resolution tidal current data.The sediment samples were analyzed to derive mean grain size,sorting coefficient,skewness and kurtosis,together with the sand,silt and clay contents.The modern sedimentary environments were classified using system cluster and principal component analyses.Grain size analysis reveals that the sediments are characterized by extremely slightly sandy silty mud（ESSSM） and slightly silty sand（SSS）,which are distributed in the central lagoon and near-shore shallow water areas,respectively.Mean grain size varies from 0 to 8.0Ф,with an average of 4.6Ф.The silt content is the highest,i.e.,52% on average,with the average contents of sand and clay being 43% and 5%,respectively.There exists a significant correlation between mean size and water depth,suggesting that the surficial sediments become finer with increasing water depth.Cluster analyses reveals two groups of samples.The first group is characterized by mean grain size of more than 5.5Ф,whilst the second group has mean grain size of below 3.5Ф.Further,these groups also have different correlations between mean grain size and the other grain size parameters.In terms of the tidal current,the average values of the root mean square velocity（RMSV） are 7.5 cm/s and 6.9 cm/s on springs and neaps,respectively.For the RMSVs that are higher than 4 cm/s,a significant positive correlation is found between the content of the 63–125 μm fraction and the RMSV,suggesting that the RMSV determines the variability of the very fine sand fraction.Based on system cluster and principal component analyses（PCA）,the modern sedimentary environments are classified into three types according to the grain size parameters,RMSVs and water depth data.The results suggest the importance of grain size parameters and high-spatial resolution hydrodynamic data in differentiating the coastal sedimentary environments.

Equation oriented method for Rectisol wash modeling and analysis

Rectisol process is more efficient in comparison with other physical or chemical absorption methods for gas purification. To implement a real time simulation of Rectisol process, thermodynamic model and simulation strategy are needed. In this paper, a method of modified statistical associated fluid theory with perturbation theory is used to predict thermodynamic behavior of process. As Rectisol process is a highly heat-integrated process with many loops, a method of equation oriented strategy, sequential quadratic programming, is used as the solver and the process converges perfectly. Then analyses are conducted with this simulator.

A Fault Sample Simulation Approach for Virtual Testability Demonstration Test

Virtual testability demonstration test has many advantages,such as low cost,high efficiency,low risk and few restrictions.It brings new requirements to the fault sample generation.A fault sample simulation approach for virtual testability demonstration test based on stochastic process theory is proposed.First,the similarities and differences of fault sample generation between physical testability demonstration test and virtual testability demonstration test are discussed.Second,it is pointed out that the fault occurrence process subject to perfect repair is renewal process.Third,the interarrival time distribution function of the next fault event is given.Steps and flowcharts of fault sample generation are introduced.The number of faults and their occurrence time are obtained by statistical simulation.Finally,experiments are carried out on a stable tracking platform.Because a variety of types of life distributions and maintenance modes are considered and some assumptions are removed,the sample size and structure of fault sample simulation results are more similar to the actual results and more reasonable.The proposed method can effectively guide the fault injection in virtual testability demonstration test.

Adapting Nanotech Research as Nano-Micro Hybrids Approach Biological Complexity,A Review

Today＇s emergence of nano-micro hybrid structures with almost biological complexity is of fundamental interest. Our ability to adapt intelligently to the challenges has ramifications all the way from fundamentally changing research itself, over applications critical to future survival, to posing globally existential dangers. Touching on specific issues such as how complexity relates to the catalytic prowess of multi-metal compounds, we discuss the increasingly urgent issues in nanotechnology also very generally and guided by the motto ＇Bio Is Nature＇s Nanotech＇. Technology belongs to macro-evolution; for example integration with artificial intelligence （AI） is inevitable. Darwinian adaptation manifests as integration of complexity, and awareness of this helps in developing adaptable research methods that can find use across a wide range of research. The second half of this work reviews a diverse range of projects which all benefited from ＇playful＇ programming aimed at dealing with complexity. The main purpose of reviewing them is to show how such projects benefit from and fit in with the general, philosophical approach, proving the relevance of the ＇big picture＇ where it is usually disregarded.