An Intercomparison of Rules for Testing the Significance of Coupled Modes of Singular Value Decomposition Analysis

This paper clarifies the essence of the significance test of singular value decomposition analysis （SVD）, and investigates four rules for testing the significance of coupled modes of SVD, including parallel analysis, nonparametric bootstrap, random-phase test, and a new rule named modified parallel analysis. A numerical experiment is conducted to quantitatively compare the performance of the four rules in judging whether a coupled mode of SVD is significant as parameters such as the sample size, the number of grid points, and the signal-to-noise ratio vary. The results show that the four rules perform better with lower ratio of the number of grid points to sample size. Modified parallel analysis and nonparametric bootstrap perform best to abandon the spurious coupled modes, but the latter is better than the former to retain the significant coupled modes when the sample size is not much larger than the number of grid points. Parallel analysis and random-phase test are robust to abandon the spurious coupled modes only when either （1） the observations at the grid points are spatially uncorrelated, or （2） the coupled signal is very strong for parallel analysis and is not weak for random-phase test. The reasons affecting the accuracy of the test rules are discussed.

THE SIGNIFICANCE OF TESTING PREOPERATIVE VISUAL FUNCTION IN CATARACT USING LASER INTERFEROMETRIC VISUAL ACUITY AND ERG

Tests of preoperative visual function and prediction of postoperative E chart visual acuity(ECVA) using laser interferometric visual acuity(LIVA) and electroretinogram(ERG) were performed in 16 cases(19 eyes) of cataract. The results showed that the coincident rate between preoperative LIVA and postoperative ECVA was 63.2%, and there was a parallel correlation between preoperative amplitude of photopic ERG b-wave and postoperative ECVA in 79.0% of the eyes. Comparing these two methods, the test of LIVA ...

A New Method of Significance Testing for Correlation-Coefficient Fields and Its Application

Correlation-coefficient fields are widely used in short-term climate prediction research. The most frequently used significance test method for the correlation-coefficient field was proposed by Livezey, in which the number of significantcorrelation lattice(station) points on the correlation coherence map is used as the statistic. However, the method is based on two assumptions:(1) the spatial distribution of the lattice(station) points is uniform;and(2) there is no correlation between the physical quantities in the correlation-coefficient field. However, in reality, the above two assumptions are not valid.Therefore, we designed a more reasonable method for significance testing of the correlation-coefficient field. Specifically, a new statistic, the significant-correlation area, is introduced to eliminate the inhomogeneity of the grid(station)-point distribution, and an empirical Monte Carlo method is employed to eliminate the spatial correlation of the matrix.Subsequently, the new significance test was used for simultaneous correlation-coefficient fields between intensities of the atmospheric activity center in the Northern Hemisphere and temperature/precipitation in China. The results show that the new method is more reasonable than the Livezey method.

Improved significance testing of wavelet power spectrum near data boundaries as applied to polar research

When one applies the wavelet transform to analyze finite-length time series, discontinuities at the data boundaries will distort its wavelet power spectrum in some regions which are defined as a wavelength-dependent cone of influence （COI）. In the COI, significance tests are unreliable. At the same time, as many time series are short and noisy, the COI is a serious limitation in wavelet analysis of time series. In this paper, we will give a method to reduce boundary effects and discover significant frequencies in the COI. After that, we will apply our method to analyze Greenland winter temperature and Baltic sea ice. The new method makes use of line removal and odd extension of the time series. This causes the derivative of the series to be continuous （unlike the case for other padding methods）. This will give the most reasonable padding methodology if the time series being analyzed has red noise characteristics.

Significant Breakthrough in Industrial Test of the "Methanol to Olefins" Process Developed by Dalian Institute of Chemical Physics,Chinese Academy of Sciences

A process of ＂Methanol or Dimethylether to Olefins＂ developed by Dalian Institute of Chemical Physics （DICP）, designated as the DMTO process, has attained great success in industrial scaling up testing. DICP, by collaborating with the Xinxing Coal Chemical Co., Ltd. of Shaanxi Province and the Luoyang Petrochemical Engineering Co. of the SINOPEC Group, operated successfully a 50t（methanol）/d unit for the conversion of methanol to lower olefins, with a methanol conversion of close to 100%, and a selectivity to lower olefins（ethylene, propylene and butylenes） of higher than 90%. On 23rd August, the industrial test project has passed a state appraisal. The experts of the Appraisal Group, headed by Prof. YUAN Qingtang, academician of Chinese Academy of Engineering, drew the conclusions that the DMTO process, by utilizing a proprietary SAPO-34 catalyst system and a recycling fluidized bed reaction system for the production of lower olefins from methanol, is the first unit in the world having a capacity of producing nearly ten thousand tons lower olefins per year. The technological level of the industrial test is at a leading position internationally. This accomplishment will provide a sound base for the subsequent commercialization of the DMTO process.

Explanatory System of Support Vector Regression and Its Application in QSPR of Surfactants

In order to solve the problem of poor interpretability of support vector re- gression （SVR） applied in quantitative structure-property relationship （QSPR）, a com- plete set of explanatory system for SVR was established based on F-test, The nov- el explanatory system includes significance tests of model and single-descriptor im- portance, single-descriptor effect and sensitivity analysis, and significance tests of interaction between two descriptors, etc. The results of example indicated that the explanatory results of the new system were consistent well with those of stepwise linear regression model and quadratic polynomial stepwise regression model. The explanatory SVR model will play an important role in regression analysis such as QSPR.

Detecting the Relationship Between Summer Rainfall Anomalies in Eastern China and the SSTA in the Global Domain with a New Significance Test Method

It is suggested that the multiple samples in a correlation map or a set of correlation maps should be examined with significance tests as per the Bernoulli probability model. Therefore, both the contemporaneous and lag correlations of summertime precipitation R in any one of the three regions of Northern China （NC）, the Changjiang-Huaihe River Valley （CHRV）, and Southern China （SC） with the SSTA in the global domain have been tested in the present article, using our significance test method and the method proposed by Livezey and Chen （1983） respectively. Our results demonstrate that the contemporaneous correlations of sum- mer R in CHRV with the SSTA are larger than those in NC. Significant correlations of SSTA with CHRV R are found to be in some warm SST regions in the tropics, whereas those of SSTA with NC R, which are opposite in sign as compared to the SSTA-CHRVR correlations, are found to be in some regions where the mean SSTs are low. In comparison with the patterns of the contemporaneous correlations, the 1 to 12 month lag correlations between NC R and SSTA, and those between CHRV summer R and SSTA show similar patterns, including the magnitudes and signs, and the spatial distributions of the coefficients. However, the summer rainfall in SC is not well correlated with the SSTA, no matter how long the lag interval is. The results derived from the observations have set up a relationship frame connecting the precipitation anomalies in NC, CHRV, and SC with the SSTA in the global domain, which is critically useful for our understanding and predicting the climate variabilities in different parts of China. Both NC and CHRV summer R are connected with E1 Nifio events, showing a ‘- -＇pattern in an E1 Nifio year and a‘＋ ＋＇ pattern in the subsequent year. Key words summer precipitation; eastern China; global sea surface

Seasonal variability of the Kuroshio Current at the PN Section in the East China Sea based on in-situ observation from 1987 to 2010

As the spatio-temporal variability of the Kuroshio is highly influenced by mesoscale eddies, representing its seasonal variability characteristics requires sufficiently long term observations to reduce the uncertainties. Geostrophic velocity data estimated from hydrographic observation from 1987 to 2010 and the shipboard ADCP velocity data from 1993 to 2008 at the PN Section in the central East China Sea are collected to view the seasonal variability objectively. From both types of observation, it is found that the seasonal climatology mean of the Kuroshio Current exhibits significant difference in three areas, which are located at the Kuroshio Current core and its two flanks in a shallow layer less than 300 m, with the weakest northeast current at the core in autumn, the strongest counter current on the right flank in spring, and the strongest northeast current on the left flank in autumn, respectively. The seasonal variance of the Kuroshio Current also exhibits significant difference on the off- shore side of the Kuroshio, with larger variance in spring and summer while smaller variance in autumn and winter. For the current parallel to the PN Section, the ratio of the seasonal variability component to the intraseasonal variability component is relatively smaller than that for the current perpendicular to the PN Section. Further analyses indicate that the seasonal variability at the PN Section is tightly linked to the upstream and downstream current variability.

The Relationships between Variations of Sea Surface Temperature Anomalies in the Key Ocean Areas and the Precipitation and Surface Air Temperature in China

The relationships between variations of sea surface temperature anomalies (SSTVA) in the key ocean areas and the precipitation / temperature anomalies in China are studied based on the monthly mean sea surface temperature data from January 1951 to December 1998 and the same stage monthly mean precipitation/ temperature data of 160 stations in China. The purpose of the present study is to discuss whether the relationship between SSTVA and precipitation / temperature is different from that between sea surface temperature anomalies (SSTA) and precipitation/ temperature, and whether the uncertainty of prediction can be reduced by use of SSTVA. The results show that the responses of precipitation anomalies to the two kinds of tendency of SSTA are different. This implies that discussing the effects of two kinds of tendency of SSTA on precipitation anomalies is better than just discussing the effects of SSTA on precipitation anomalies. It helps to reduce the uncertainty of prediction. The temperature anomalies have more identical re-sponses to the two kinds of tendency of SSTA than the precipitation except in the western Pacific Ocean. The response of precipitation anomalies to SSTVA is different from that to SSTA, but there are some similarities. Key words Variations of sea surface temperature anomalies - Precipitation anomalies - Temperature anomalies - Statistical significance test Sponsored jointly by the “ National Key Developing Program for Basic Sciences” (G1998040900) Part I and the Key Program of National Nature Science Foundation of China “ Analyses and Mechanism Study of the Regional Climatic Change in China” under Grant No.49735170.

Analysis of inhibition of concrete steel-rebar corrosion by Na_2Cr_2O_7 concentrations:Implications for conflicting reports on inhibitor effectiveness

Corrosion test data were measured using non-destructive electrochemical techniques and analysed for studying inhibition effectiveness by different concentrations of NazCr207 on the corrosion of concrete steel-rehar in NaC1 and in H2SO4 media. For these, specifications of ASTM G16-95 R04 were combined with the normal and the Gumbel probability density functions as model analytical methods for addressing issues of conflicting reports of inhibitor effectiveness that had generated concerns. Results show that reinforced concrete samples admixed with concentrations having 4 g （0.012 7 tool）, 8 g （0.025 4 mol） and 6 g （0.019 l tool） NaaCr207 exhibited, in that order, high inhibition effectiveness, with respective efficiency, r/, of （90.46±1.30）%, （88.41＋2.24）% and （84.87±4.74）%, in the NaC1 medium. These exhibit good agreements within replicates and statistical methods for the samples. Also, optimal inhibition effectiveness model in the H2SO4 medium was exhibited by 8 g （0.025 4 mol） Na2Cr207 concentration having r/=（78.44±1.10）%. These bear implications for addressing conflicting test data in the study of effective inhibitors for mitigating steel-rebar corrosion in aggressive environments.

Study on Floral and Pollen Characters of Tetraploid Rice

Polyploidization is the evolution trend of many crops, and the yield increased obviously after polyploidization. The polyploidization of rice often brings ＂gigas＂ of both vegetative organs and seeds. Howevere, in rice breeding, it is required for restoring lines to have not only big anthers but also abundant pollens. People often doubt that the enlargement of the floral organ may just be enlargement of cell size in polyploid rice. So, it is of significance to study characteristics of floral organs and pollens of several tetraploid rice varieties or lines. Floral organ and pollen characteristics of Sg99012 and HN2026 were studied comparatively by stages and different ploidy levels, with the materials 9311, HD9802S, and PA64S as the control. The results showed that chromosome doubling had much more influence on floral characteristics of every lines than seeding by stages, and the tetraploids of every lines displayed ＂gigas＂. In correlation analysis, spikelet length, spikelet width, and anther length had significant correlation; spikelet width and anther width had significant correlation, too. Both seeding by stages and chromosome doubling made the correlations of characters between every floral organ changed to some extent. Seeding by stages had little effect on pollen diameter and fertility of HN2026-4X and Sg99012-4X. But chromosome doubling increased pollen size of every lines remarkably, and also increased the pollen quantity of PMeS （polyploid meiosis stability） restoring line HN2026-4X and gene map restoring line 9311-4X remarkably, whereas only had little effect on that of sterile lines. Moreover, chromosome doubling changed pollen fertility and made the number of fertility pollen of 9311 reduced significantly, but the pollen fertility of HN2026 （PMeS restoring line） and PA64S （sterile line） almost had no change after chromosome doubling. The results showed that tetraploid restoring lines had advantage of abundant and big size pollens, and tetraploid sterile lines had the characters of big size pollens, few change of pollen quantity and stable sterile character. These results provided evidence in reproductive biology for utilizing heterosis of polyploid rice by two-line method.

Construct Protein-Protein Interaction Network by Mining Domain-Domain Interactions

Domain-domain interactions are important clues to inferring protein-protein interactions. Although about 8 000 domain-domain interactions are discovered so far,they are just the tip of the iceberg. Because domains are conservative and commonplace in proteins,domain-domain interactions are discovered based on pairs of domains which significantly co-exist in proteins. Meanwhile,it is realized that:( 1) domain-domain interactions may exist within the same proteins or across different proteins;( 2) only the domain-domain interactions across different proteins can mediate interactions between proteins;( 3) domains have biases to interact with other domains. And then,a novel method is put forward to construct protein-protein interaction network by using domain-domain interactions. The method is validated by experiments and compared with the state- of-art methods in the field. The experimental results suggest that the method is reasonable and effectiveness on constructing Protein-protein interactions network.

Construction of Multiple Linear Regression Prediction Model of PRETCO-A Scores and Its Positive Backwash Effect on Teaching

PRETCO-A is a standardized English proficiency test set up to evaluate the English application ability of the students in higher vocational college.In order to improve the passing rate,a multiple linear regression prediction model is constructed in this paper.A significance test was first performed on the regression model and the regression coefficient to verify a high correlation among the variables.The confirmed model was then put into application to predict the students’scores and identify the students who may fail the exam,leading to targeted tutoring assistance given to those students in advance.Finally,60 students with predicted scores lower than 60 points were selected as research samples,and randomly divided into the control group and the experimental group,30 students in each group.Finally,the experimental group students were given 40 teaching hours of precision assistance and targeted training,while the control group did not engage in any teaching intervention.The experimental results indicate that the pass rate of experimental group is 20%higher than the control group,which means the backwash effect of the test prediction is positive.The prediction model is proved to be scientific and reliable for teaching.