The current popular methods for decision making and project optimisation in mine ventilation contain a number of deficiencies as they are solely based on either subjective knowledge or objective information.This paper...The current popular methods for decision making and project optimisation in mine ventilation contain a number of deficiencies as they are solely based on either subjective knowledge or objective information.This paper presents a new approach to rank the alternatives by G1-coefficient of variation method.The focus of this approach is the use of the combination weighing,which is able to compensate for the deficiencies in the method of evaluation index single weighing.In the case study,an appropriate evaluation index system was established to determine the evaluation value of each ventilation mode.Then the proposed approach was used to select the best development face ventilation mode.The result shows that the proposed approach is able to rank the alternative development face ventilation mode reasonably,the combination weighing method had the advantages of both subjective and objective weighing methods in that it took into consideration of both the experience and wisdom of experts,and the new changes in objective conditions.This approach provides a more reasonable and reliable procedure to analyse and evaluate different ventilation modes.展开更多
In order to shorten the difference between the raw silk size grading standards of the world and that of China, to quicken the step of the electronic raw silk testing process, the distribution of the coefficient of var...In order to shorten the difference between the raw silk size grading standards of the world and that of China, to quicken the step of the electronic raw silk testing process, the distribution of the coefficient of variation (CV50m%) of the raw silk size in the electronic testing and the development of the new standards are studied according to the sampling and grading theory. By the theoretical deduction and the simulating experiments, the distribution of the coefficient of variation of the raw silk size is given, and the grading scheme whose quality index is the coefficient of variation(CV50m%)of the raw silk size and the grading precisions of all grades are proposed. Moreover, the rightness and the feasibility of the grading scheme are testified by the sampling and grading simulation.展开更多
In remote sensing sea surface temperature （SST）, the traditional fusion method is used to compute the dot product of a subjective weight vector with a satellite measurement vector, while the result requires validati...In remote sensing sea surface temperature （SST）, the traditional fusion method is used to compute the dot product of a subjective weight vector with a satellite measurement vector, while the result requires validation by field measurement. However, field measurement that relative to the satellite measurement is very sparse, many information may not be verified. A relative objective weight vector is constructed by using the limited field measurement, which is based on coefficient of variation method. And then it make an application of the data fusion by the weighted average method in the SST data. fuse SST data with the weighted average method. In this way, some posteriori information can be added to the fusion process. The model reduces the dependence on verification, and some of the satellite measurement can be handled without corresponding to the field measurement, and the fusion result matches transfer errors theory.展开更多
The Coefficient of Variation(CV)of hectometer yarn's weight is one of the guidelines to evaluate its intrinsic quality.In the spinning manufacturing,the control of cotton yarn's weight unevenness is accomplish...The Coefficient of Variation(CV)of hectometer yarn's weight is one of the guidelines to evaluate its intrinsic quality.In the spinning manufacturing,the control of cotton yarn's weight unevenness is accomplished mainly in terms of a spot-check on semi-product and a succedent adjust in process parameters during spinning based on technicians' experience.However,it is theoretically believed among manufacturers that with fixed technical levels and parameters in the spinning process,the quality parameters of assorted cotton have a certain influence on the CV.In order to find out a rule of the influence that assorted cotton has on the CV,a GM(1,N)model,correlated raw cotton's quality parameter with the CV,has firstly been developed according to the modeling theory of grey system,and then been applied in the designing step to predict the CV.It has been approved by practical modeling and validation that the model could fit preferably an accrual CV value,and provide a method of quantitative predicting analysis for textile manufacturers to design cotton yarn's quality.展开更多
Before the major earthquake or rock damage occurs,it is often accompanied by a sudden change in the degree of non-uniformity of the strain field.In order to find a stronger non-uniformity signal before the rock failur...Before the major earthquake or rock damage occurs,it is often accompanied by a sudden change in the degree of non-uniformity of the strain field.In order to find a stronger non-uniformity signal before the rock failure,the coefficient of variation(Cv)is examined and reformed in this study.We test the Cv calculation way of the"normal-abnormal"model proposed in the previous studies.Based on the analysis of the physical process of rock failure and its relationship to the shear strain field,we construct a new way to calculate the Cv value.The variation of shear strain field on rock sample with the increase of stress is obtained by the digital speckle correlation method(DSCM).The new Cv value calculation way is used to study the non-uniformity of the spatial distribution for the shear strain field.The results show that this Cv calculation way can get more obvious abnormal signals.When the number of observation points are limited,the specific distribution of points can increase the signal strength,which may provide reference for the research on precursor detection of earthquakes.展开更多
The exact classical limits for the coefficient of variation c for the normal distribution are derived. The hand-calculating approximated classical limits for c having high accuracy are given to meet practical engineer...The exact classical limits for the coefficient of variation c for the normal distribution are derived. The hand-calculating approximated classical limits for c having high accuracy are given to meet practical engineering needs. Using Odeh and Owen's computational method and Brent's algorithm, the tables for the r-upper exact classical limits of coefficient of variation for normal distribution are calculated for the different confidence coefficient y, the sample size n=1(1)30,40,60,120, the sample coefficient of variation c=0.01(0.01)0.20. It is shown that if n<8,c<0.20, then the V -upper exact classical limits cu for c are slightly higher than the exact fiducial limits cu,F for c if. n>8, c<0.02,then cu-cu,f<5x10-6展开更多
Accurate estimation of Weibull parameters is an important issue for the characterization of the strength variability of brittle ceramics with Weibull statistics.In this paper,a simple method was established for the de...Accurate estimation of Weibull parameters is an important issue for the characterization of the strength variability of brittle ceramics with Weibull statistics.In this paper,a simple method was established for the determination of the Weibull parameters,Weibull modulus m and scale parameter σ0,based on Monte Carlo simulation.It was shown that an unbiased estimation for Weibull modulus can be yielded directly from the coefficient of variation of the considered strength sample.Furthermore,using the yielded Weibull estimator and the mean value of the strength in the considered sample,the scale parameter σ0 can also be estimated accurately.展开更多
To understand the variations in vegetation and their correlation with climate factors in the upper catchments of the Yellow River, China, Normalized Difference Vegetation Index（NDVI） time series data from 2000 to 20...To understand the variations in vegetation and their correlation with climate factors in the upper catchments of the Yellow River, China, Normalized Difference Vegetation Index（NDVI） time series data from 2000 to 2010 were collected based on the MOD13Q1 product. The coefficient of variation, Theil–Sen median trend analysis and the Mann–Kendall test were combined to investigate the volatility characteristic and trend characteristic of the vegetation. Climate data sets were then used to analyze the correlation between variations in vegetation and climate change. In terms of the temporal variations, the vegetation in this study area improved slightly from 2000 to 2010, although the volatility characteristic was larger in 2000–2005 than in 2006–2010. In terms of the spatial variation, vegetation which is relatively stable and has a significantly increasing trend accounts for the largest part of the study area. Its spatial distribution is highly correlated with altitude, which ranges from about 2000 to 3000 m in this area. Highly fluctuating vegetation and vegetation which showed a significantly decreasing trend were mostly distributed around the reservoirs and in the reaches of the river with hydropower developments. Vegetation with a relatively stable and significantly decreasing trend and vegetation with a highly fluctuating and significantly increasing trend are widely dispersed. With respect to the response of vegetation to climate change, about 20–30% of the vegetation has a significant correlation with climatic factors and the correlations in most areas are positive： regions with precipitation as the key influencing factor account for more than 10% of the area; regions with temperature as the key influencing factor account for less than 10% of the area; and regions with precipitation and temperature as the key influencing factors together account for about 5% of the total area. More than 70% of the vegetation has an insignificant correlation with climatic factors.展开更多
Plant-to-plant variability is a crop stability component.The objective of this study in maize(Zea mays L.)was to test the validity of the theoretical background of the hypothesis that the coefficient of variation(CV)f...Plant-to-plant variability is a crop stability component.The objective of this study in maize(Zea mays L.)was to test the validity of the theoretical background of the hypothesis that the coefficient of variation(CV)for grain yield per plant and mean yield are connected exponentially,following the Taylor’s Power Law(TPL)Model.Field experimentation was conducted across two sites,two seasons,and two planting densities.Densities were the main plots,corresponding to the typical practice of 8.89 plants m–2(TCD)and the low-input optimal of 5.33 plants m–2(LCD),while hybrids were the subplots.Data from 26 subplots in the first site averaged CV values of 22.6%at the TCD and 21.9%at the LCD,and mean yields of 19.1 and 13.9 t ha–1,respectively,following the TPL Model.The same was true for the second site,with average CVs and means of 41.5%and 14.3 t ha–1 at the TCD and 36.8%and 11.5 t ha–1 at the LCD.A test was performed on the simple correlation between the logarithms of variances and their respective means to investigate whether there is a systematic variance dependence on mean,thus questioning the reliability of TPL.The validity of TPL was verified in the first site.Nevertheless,there was a systematic dependence of yield variance on mean yield in the second site,implying that the CV-yield correlation might be not biologically meaningful.Conversion of the variance to remove its dependence on the mean did not validate the CV-yield negative relationship,meaning that caution is needed when interpreting the CV as a stability index for intra-crop variation.Whether the determinant factor of invalidity of TPL was the extensive intra-crop variation in the lower yielding second site can be assessed in future research.展开更多
Paleoearthquake research represents an essential method for determining recurrence intervals oflarge earthquakes.Reasonable determination of the average recurrence interval and coefficient of variationprovides a cruci...Paleoearthquake research represents an essential method for determining recurrence intervals oflarge earthquakes.Reasonable determination of the average recurrence interval and coefficient of variationprovides a crucial basis for the analysis of the recurrence characteristics of strong earthquakes on intraplatefaults in Chinese mainland.Paleoearthquake data from 145 fault segments of 93 well-studied faults in MainlandChina were collected,organized,and analyzed to discuss the rational estimation of the average recurrenceinterval and coefficient of variation of a strong earthquake occurrence probability model.First,differencesin structural environments were used as a basis to investigate the spatial distribution characteristics of theaverage recurrence intervals of strong earthquakes.The results indicate significant variations in the recurrenceperiods of strong earthquakes in the Sichuan–Yunnan,Xinjiang,North China,and northeastern Qinghai-Tibet Plateau structure zones.The Sichuan–Yunnan structure zone exhibited the shortest average recurrence intervalfor strong earthquakes,which was mainly distributed between 100 and 2000 years,and a relatively high sliprate.The Xinjiang structure zone attained a relatively balanced recurrence interval frequency distribution of1000–4500 years and a moderate slip rate.The North China structure zone showed the lowest slip rate,withthe strong earthquake recurrence interval mainly concentrated between 1000 and 4000 years.The northeastern Qinghai-Tibet Plateau structure zone presented two main frequency peaks in the strong earthquake recurrenceintervals between 1000–3000 years and 3000–5000 years and a relatively high slip rate.The slip rate is a keyfactor influencing the recurrence interval of strong earthquakes,and active faults with high slip rates showshort recurrence intervals.Furthermore,the relationship between fault slip rate,fault type,and the averagerecurrence interval of strong earthquakes was examined.The results indicate a good logarithmic linearrelationship between the fault slip rate and the average recurrence interval of large earthquakes—the higherthe slip rate,the shorter the recurrence interval of strong earthquakes.Fault type also showed a relation to theaverage recurrence interval,with the intervals for various types of active faults gradually increasing in theorder of strike-slip,normal,reverse strike-slip,reverse,and normal strike-slip faults.Second,we calculated theproportions of active faults and various fault types in each structure zone that had a coefficient of variation inrecurrence intervals less than 0.4.The findings reveal that the occurrence of strong earthquakes on most activefaults in Chinese mainland satisfies a quasiperiodic model.The general coefficient of variation across differentstructure zones and fault types ranges between 0.36 and 0.44,which indicates the nonsignificant difference inthe degree of variability in the periodicity of strong earthquake occurrence across various structural zones andfault types.展开更多
To identify the root causes of heavy metal contamination in soils as well as prevent and control such contamination from its sources,this study explored the accumulation patterns and ecological risks of heavy metals l...To identify the root causes of heavy metal contamination in soils as well as prevent and control such contamination from its sources,this study explored the accumulation patterns and ecological risks of heavy metals like Cd and Pb in solid waste in mining areas and across the water body,sediment,soil and agricultural product ecosystem surrounding the mining areas.Focusing on the residual solid waste samples in lead-zinc deposits in a certain area of Guizhou Province,along with samples of topsoils,irrigation water,river sediments,and crops from surrounding areas.This study analyzed the distributions of eight heavy metals,i.e.,Cd,As,Cr,Hg,Pb,Zn,Cu,and Ni,in the samples through field surveys and sample tests.Furthermore,this study assessed the contamination levels and ecological risks of heavy metals in soils,sediments,and agricultural products using methods such as the single-factor index,Nemerow composite index,and potential ecological risk assessment.The results indicate that heavy metals in the solid waste samples all exhibited concentrations exceeding their risk screening values,with 60%greater than their risk intervention values.The soils and sediments demonstrate slight and moderate comprehensive ecological risks of heavy metals.The single-factor potential ecological risks of heavy metals in both the soil and sediment samples decreased in the order of Hg,Cd,Pb,As,Cu,Zn,Cr,and Ni,suggesting the same sources of heavy metals in the soils and sediments.Most of the agricultural product samples exhibited over-limit concentrations of heavy metals dominated by Cd,Pb,Ni,and Cr,excluding Hg and As.The agricultural product assessment using the Nemerow composite index reveals that 35%of the agricultural product samples reached the heavy metal contamination level,implying that the agricultural products from farmland around the solid waste dumps have been contaminated with heavy metals.The eight heavy metals in the soil,sediment,and agricultural product samples manifested high coefficients of variation(CVs),indicating pronounced spatial variability.This suggests that their concentrations in soils,sediments,and agricultural products are significantly influenced by human mining activities.Additionally,the agricultural products exhibit strong transport and accumulation capacities for Cd,Cu,and Zn.展开更多
Spatial variability of soil organic carbon (SOC) of different land use patterns and soil types was examined in a county-wide red soil region of South China,using six sampling densities,14,34,68,130,255,and 525 samples...Spatial variability of soil organic carbon (SOC) of different land use patterns and soil types was examined in a county-wide red soil region of South China,using six sampling densities,14,34,68,130,255,and 525 samples designed by the method of grid sampling in 6 different grid sizes,labeled as D14,D34,D68,D130,D255,and D525,respectively.The results showed that the coefficients of variation (CVs) of SOC decreased gradually from 62.8% to 47.4% with the increase in soil sampling densities.The SOC CVs in the paddy field change slightly from 30.8% to 28.7%,while those of the dry farmland and forest land decreased remarkably from 58.1% to 48.7% and from 99.3% to 64.4%,respectively.The SOC CVs of the paddy soil change slightly,while those of red soil decreased remarkably from 82.8% to 63.9%.About 604,500,and 353 (P < 0.05) samples would be needed a number of years later if the SOC change was supposedly 1.52 g kg-1,based on the CVs of SOC acquired from the present sampling densities of D14,D68,and D525,respectively.Moreover,based on the same SOC change and the present time CVs at D255,the ratio of samples needed for paddy field,dry farmland,and forest land should be 1:0.81:3.33,while the actual corresponding ratio in an equal interval grid sampling was 1:0.74:0.46.These indicated that the sampling density had important effect on the detection of SOC variability in the county-wide region,the equal interval grid sampling was not efficient enough,and the respective CV of each land use or soil type should be fully considered when determining the sampling number in the future.展开更多
The flow and mixing behavior of two miscible liquids has been studied in an innovative static mixer by using CFD,with Reynolds numbers ranging from 20 to 160.The performance of the new mixer is compared with those of ...The flow and mixing behavior of two miscible liquids has been studied in an innovative static mixer by using CFD,with Reynolds numbers ranging from 20 to 160.The performance of the new mixer is compared with those of Kenics,SMX,and Komax static mixers.The pressure drop ratio(Z-factor),coefficient of variation(CoV),and extensional efficiency(α)features have been used to evaluate power consumption,distributive mixing,and dispersive mixing performances,respectively,in all mixers.The model is firstly validated based on experimental data measured for the pressure drop ratio and the coefficient of variation.CFD results are consistent with measured data and those obtained by available correlations in the literature.The new mixer shows a superior mixing performance compared to the other mixers.展开更多
Fuzzy similarity measures, which are used to judge the closeness of two fuzzy sets, are presented to evaluate the water quality of the Haihe River. Based on the membership functions and coefficient of variation as the...Fuzzy similarity measures, which are used to judge the closeness of two fuzzy sets, are presented to evaluate the water quality of the Haihe River. Based on the membership functions and coefficient of variation as the weights, four fuzzy similarity measures （including Lattice similarity measure, Hamming similarity measure, Euclidean similarity measure and the max-min similarity measure） are used to classify the 299 samples into the proper water quality standard ranks. The results are compared with the traditional distance discriminant methods. The calculation of two traditional distance discriminant methods （both Euclidean distance and absolute value distance） is also based on the use of coefficients of variation as the weights. Without the Lattice similarity measure, for this method loses some information, the correct assignment of samples classified into the same water quality ranks is 75.92% with the other three similarity measures and two distance discriminant methods. This result shows the reliability of the five methods. Only considering the three similarity measures, there were only 1.01% of the samples that did not classify to the same ranks, while the corresponding ratio of the two distance discriminant methods was 5.69%. The results of leave-one-out cross validation show that more than 88% of the samples are classified to the proper ranks, which demonstrates that the similarity measures are suitable to evaluate the water quality of the Haihe River.展开更多
Slope stability prediction research is a complex non-linear system problem.In carrying out slope stability prediction work,it often encounters low accuracy of prediction models and blind data preprocessing.Based on 77...Slope stability prediction research is a complex non-linear system problem.In carrying out slope stability prediction work,it often encounters low accuracy of prediction models and blind data preprocessing.Based on 77 field cases,5 quantitative indicators are selected to improve the accuracy of prediction models for slope stability.These indicators include slope angle,slope height,internal friction angle,cohesion and unit weight of rock and soil.Potential data aggregation in the prediction of slope stability is analyzed and visualized based on Six-dimension reduction methods,namely principal components analysis(PCA),Kernel PCA,factor analysis(FA),independent component analysis(ICA),non-negative matrix factorization(NMF)and t-SNE(stochastic neighbor embedding).Combined with classic machine learning methods,7 prediction models for slope stability are established and their reliabilities are examined by random cross validation.Besides,the significance of each indicator in the prediction of slope stability is discussed using the coefficient of variation method.The research results show that dimension reduction is unnecessary for the data processing of prediction models established in this paper of slope stability.Random forest(RF),support vector machine(SVM)and k-nearest neighbour(KNN)achieve the best prediction accuracy,which is higher than 90%.The decision tree(DT)has better accuracy which is 86%.The most important factor influencing slope stability is slope height,while unit weight of rock and soil is the least significant.RF and SVM models have the best accuracy and superiority in slope stability prediction.The results provide a new approach toward slope stability prediction in geotechnical engineering.展开更多
Vertical and temporal distributions of N and P in soil solution in aquatic-terrestrial ecotone （ATE） of Taihu Lake were investigated, and the relations among N, P, ORP （oxidation reduction potential）, TOC, root sy...Vertical and temporal distributions of N and P in soil solution in aquatic-terrestrial ecotone （ATE） of Taihu Lake were investigated, and the relations among N, P, ORP （oxidation reduction potential）, TOC, root system biomass and microorganism were studied. As a whole, significant declines in TN, NO3^--N, DON （dissolved organic nitrogen） and TP concentration in soil solution have occurred with increase of the depth, and reached their minima at 60 cm depth, except for NH4^＋-N, which increased with depth. The concentration of TP increased gradually from spring to winter in the topsoil, the maximum 0.08 mg/L presented in the winter while the minimum 0.03 mg/L in spring. In the deeper layer, the concentration value of TP fluctuated little. As for the NO3^--N, its seasonal variation was significant at 20 cm depth, its concentration increased gradually from spring to autumn, and decreased markedly in winter. Vertical and temporal distribution of DON is contrary to that of NO3^--N. The results also show that the variation of N and P in the percolate between adjacent layers is obviously different. The vertical variation ofTN, TP, NO3^--N, NH4^＋-N and DON is significant, of which the variation coefficient of NO3^--N along the depth reaches 100.23%, the highest; while the variation coefficient of DON is 41.14%, the smallest. The results of correlation analysis show that the concentration of nitrogen and phosphorus correlate significantly with TOC, ORP, root biomass and counts of nitrifying bacteria. Most nutrients altered much from 20 to 40 cm along the depth. However, DON changed more between 60 and 80 cm. Results show that soil of 0-60 cm depth is active rhizoplane, with strong capability to remove the nitrogen and phosphorus in ATE. It may suggest that there exists the optimum ecological efficiency in the depth of above 60 cm in reed wetland. This will be very significant for ecological restoration and reestablishment.展开更多
The exceptionally large individual growth variation has been previously recognized in several sea cucumber cohorts. However, there is a lack of information regarding the mechanism of such individual differences. In th...The exceptionally large individual growth variation has been previously recognized in several sea cucumber cohorts. However, there is a lack of information regarding the mechanism of such individual differences. In this study, the sea cucumber Apostichopusjaponicus （Selenka） was reared individually in order to eliminate possible effects of social interaction, stocking density, etc. The results showed that there were substantial differences in growth among the sea cucumber individuals during the 100-day experiment. The special growth rate of the sea cucumber individuals differed by up to three folds （from 0.40% to 1.01%）, and the coefficient of variation in body weight increased from 12.04% to 40.51%. The final wet body weight, food intake and food conversion efficiency for each sea cucumber were generally positively correlated with their initial wet body weight （P〈0.05）. Energy budget of the animals showed that the food energy spent on respiration was much greater （about four folds） but energy deposited for growth was much less for （initially） smaller than for larger A. japonicus. The present result implies that there are obvious genetic differences among the sea cucumber individuals, largely accounting for the individual growth variation of the cohort sea cucumber. These results will provide some basic data for promoting selective breeding and fanning of the sea cucumber.展开更多
Located in the inland arid area of central Asia, salt-affected farmlands take up one third of the total irrigated land area in Xinjiang of Northwest China. Spatio-temporal variability of soil salinity and the underlyi...Located in the inland arid area of central Asia, salt-affected farmlands take up one third of the total irrigated land area in Xinjiang of Northwest China. Spatio-temporal variability of soil salinity and the underlying mechanism are fundamental problems challenging the sustainability of oasis agriculture in China. In this study, the data of total dissolved solids(TDS) measured for soil samples collected from 27 representative study areas in the oasis areas of Xinjiang were analyzed and the coefficient of variation(CV) and stratification ratio(SR) of TDS were used to describe the lateral and vertical soil salinity variations, respectively. Weekly, monthly,and annual changes in soil salinity were also summarized. Results showed that the top(0–20 cm) soil salinity was highly variable(CV> 75%) for most studied areas. Lateral variation of soil salinity was significantly correlated with the sampling interval; as a result, a maximum sampling interval of 0.9 m was found for reducing evaluation uncertainty. The top 0–20 cm soil salt accounted for about25.2% of the total salt in the 0–100 cm soil profile. The stratification ratio values(the ratio of TDS at the 20–40 cm depth to that at the 0–20 cm depth) were mostly smaller than 1 and on average 0.92, illustrating that the top 0–20 cm soil contained slightly more salt and a considerable amount of salt still existed in subsurface and deep horizons. Irrigation reduced top soil salinity by 0.52 g kg-1, or14.6%, within the first week. On average, the relative range of soil salinity, calculated to indicate monthly changes in soil salinity, was58.2% from May to September. A 27-year experiment indicated that cultivation increased soil salinity by 44.4% at a rate of 0.14 g kg-1year-1. At small spatio-temporal scales, soil salinity variation was mainly affected by anthropogenic factors, such as irrigation and land use. However, natural factors, including groundwater, topography, and climate conditions, mainly influenced soil salinity variation at large spatio-temporal scales. This study displayed the highly variable nature of soil salinity in space and time. Those driving factors identified in this study could provide guidelines for developing sustainable agriculture in the oasis areas and combating salinization in arid regions of China.展开更多
Functional traits, specifically leaf functional traits, are core-topics to explore importance to the invasion success of invasive plant species. This study aims to address the differences in leaf functional traits and...Functional traits, specifically leaf functional traits, are core-topics to explore importance to the invasion success of invasive plant species. This study aims to address the differences in leaf functional traits and their corresponding variability of the invasive tree staghorn sumac Rhus typhina L. with different invasion success, including lower and higher invasion success, in two climatic regions in North China, including a warm temperate region and a cold temperate region. No significant differences were found for leaf functional traits of staghorn sumac across different invasion success. However, the variability of leaf chlorophyll and nitrogen concentrations of staghorn sumac under higher invasion success were approximately 66.023% and 68.615% higher than those under lower invasion success, respectively. The leaf chlorophyll and nitrogen concentrations of staghorn sumac in the warm temperate region were approximately 18.432% and 16.337% higher than those in cold temperate region, respectively. The variability of specific leaf area of staghorn sumac in warm temperate region was approximately 59.802% higher than that in cold temperate region. Accordingly, leaf chlorophyll and N concentrations as well as specific leaf area of staghorn sumac and their corresponding variability may play an essential role in shaping ecological success of studied invader along a climatic gradient.展开更多
Post-construction settlement has gained increasing attention because it frequently causes engineering problems. A combined model is a commonly used prediction model that overcomes the difficulty of a single model( i. ...Post-construction settlement has gained increasing attention because it frequently causes engineering problems. A combined model is a commonly used prediction model that overcomes the difficulty of a single model( i. e., cannot reflect various regulations of settlement at some stages or the entire process). In this study,the correlation coefficient,maximum error values,and other values were obtained according to the fitting and predicted results of a single model. The coefficient of variation was then introduced to determine the weight of each model forming the combination. The proposed model was used to fit and predict for settlement and overcome the issue of utilizing a single model while determining the weight. The fitting predictive effect was also analyzed using the settlement fitting precision results. The fitting precision of optimizing the combination model is high. The predicted data of the post-construction settlement are closer to the calculated value of the settlement monitoring data. Moreover,the proposed model has good practicability,does not require the interval data of settlement,and restricts the model number. Thus,this model can be applied in the engineering field.展开更多
基金Projects(51504286,51374242)supported by the National Natural Science Foundation of ChinaProject(2015M572270)supported by China Postdoctoral Science FoundationProject(2015RS4004)supported by the Science and Technology Plan of Hunan Province,China
文摘The current popular methods for decision making and project optimisation in mine ventilation contain a number of deficiencies as they are solely based on either subjective knowledge or objective information.This paper presents a new approach to rank the alternatives by G1-coefficient of variation method.The focus of this approach is the use of the combination weighing,which is able to compensate for the deficiencies in the method of evaluation index single weighing.In the case study,an appropriate evaluation index system was established to determine the evaluation value of each ventilation mode.Then the proposed approach was used to select the best development face ventilation mode.The result shows that the proposed approach is able to rank the alternative development face ventilation mode reasonably,the combination weighing method had the advantages of both subjective and objective weighing methods in that it took into consideration of both the experience and wisdom of experts,and the new changes in objective conditions.This approach provides a more reasonable and reliable procedure to analyse and evaluate different ventilation modes.
基金Research Foundation of Ministry of Education for Doctoral Program(No.20040285008)
文摘In order to shorten the difference between the raw silk size grading standards of the world and that of China, to quicken the step of the electronic raw silk testing process, the distribution of the coefficient of variation (CV50m%) of the raw silk size in the electronic testing and the development of the new standards are studied according to the sampling and grading theory. By the theoretical deduction and the simulating experiments, the distribution of the coefficient of variation of the raw silk size is given, and the grading scheme whose quality index is the coefficient of variation(CV50m%)of the raw silk size and the grading precisions of all grades are proposed. Moreover, the rightness and the feasibility of the grading scheme are testified by the sampling and grading simulation.
基金Project supported by the National Natural Science Foundation of China(Grant No.40976108)the Shanghai Leading Academic Discipline Project(Grant No.J50103)
文摘In remote sensing sea surface temperature （SST）, the traditional fusion method is used to compute the dot product of a subjective weight vector with a satellite measurement vector, while the result requires validation by field measurement. However, field measurement that relative to the satellite measurement is very sparse, many information may not be verified. A relative objective weight vector is constructed by using the limited field measurement, which is based on coefficient of variation method. And then it make an application of the data fusion by the weighted average method in the SST data. fuse SST data with the weighted average method. In this way, some posteriori information can be added to the fusion process. The model reduces the dependence on verification, and some of the satellite measurement can be handled without corresponding to the field measurement, and the fusion result matches transfer errors theory.
基金Hunan Provincial Basic Science Foundation of China(No.2007FJ3046)Key Scientific Research Fundof Hunan Provincial Education Department,China(No.07A048)
文摘The Coefficient of Variation(CV)of hectometer yarn's weight is one of the guidelines to evaluate its intrinsic quality.In the spinning manufacturing,the control of cotton yarn's weight unevenness is accomplished mainly in terms of a spot-check on semi-product and a succedent adjust in process parameters during spinning based on technicians' experience.However,it is theoretically believed among manufacturers that with fixed technical levels and parameters in the spinning process,the quality parameters of assorted cotton have a certain influence on the CV.In order to find out a rule of the influence that assorted cotton has on the CV,a GM(1,N)model,correlated raw cotton's quality parameter with the CV,has firstly been developed according to the modeling theory of grey system,and then been applied in the designing step to predict the CV.It has been approved by practical modeling and validation that the model could fit preferably an accrual CV value,and provide a method of quantitative predicting analysis for textile manufacturers to design cotton yarn's quality.
基金jointly supported by the China Postdoctoral Science Foundation(No.2018M630028)the National Natural Science Foundation of China(Nos.41274094,40821062 and 40872133).
文摘Before the major earthquake or rock damage occurs,it is often accompanied by a sudden change in the degree of non-uniformity of the strain field.In order to find a stronger non-uniformity signal before the rock failure,the coefficient of variation(Cv)is examined and reformed in this study.We test the Cv calculation way of the"normal-abnormal"model proposed in the previous studies.Based on the analysis of the physical process of rock failure and its relationship to the shear strain field,we construct a new way to calculate the Cv value.The variation of shear strain field on rock sample with the increase of stress is obtained by the digital speckle correlation method(DSCM).The new Cv value calculation way is used to study the non-uniformity of the spatial distribution for the shear strain field.The results show that this Cv calculation way can get more obvious abnormal signals.When the number of observation points are limited,the specific distribution of points can increase the signal strength,which may provide reference for the research on precursor detection of earthquakes.
文摘The exact classical limits for the coefficient of variation c for the normal distribution are derived. The hand-calculating approximated classical limits for c having high accuracy are given to meet practical engineering needs. Using Odeh and Owen's computational method and Brent's algorithm, the tables for the r-upper exact classical limits of coefficient of variation for normal distribution are calculated for the different confidence coefficient y, the sample size n=1(1)30,40,60,120, the sample coefficient of variation c=0.01(0.01)0.20. It is shown that if n<8,c<0.20, then the V -upper exact classical limits cu for c are slightly higher than the exact fiducial limits cu,F for c if. n>8, c<0.02,then cu-cu,f<5x10-6
文摘Accurate estimation of Weibull parameters is an important issue for the characterization of the strength variability of brittle ceramics with Weibull statistics.In this paper,a simple method was established for the determination of the Weibull parameters,Weibull modulus m and scale parameter σ0,based on Monte Carlo simulation.It was shown that an unbiased estimation for Weibull modulus can be yielded directly from the coefficient of variation of the considered strength sample.Furthermore,using the yielded Weibull estimator and the mean value of the strength in the considered sample,the scale parameter σ0 can also be estimated accurately.
基金National Natural Science Foundation of China,No.41171318 National Key Technology Support Program,No.2012BAH32B03+1 种基金No.2012BAH33B05 The Remote Sensing Investigation and Assessment Project for Decade-Change of the National Ecological Environment（2000–2010）
文摘To understand the variations in vegetation and their correlation with climate factors in the upper catchments of the Yellow River, China, Normalized Difference Vegetation Index（NDVI） time series data from 2000 to 2010 were collected based on the MOD13Q1 product. The coefficient of variation, Theil–Sen median trend analysis and the Mann–Kendall test were combined to investigate the volatility characteristic and trend characteristic of the vegetation. Climate data sets were then used to analyze the correlation between variations in vegetation and climate change. In terms of the temporal variations, the vegetation in this study area improved slightly from 2000 to 2010, although the volatility characteristic was larger in 2000–2005 than in 2006–2010. In terms of the spatial variation, vegetation which is relatively stable and has a significantly increasing trend accounts for the largest part of the study area. Its spatial distribution is highly correlated with altitude, which ranges from about 2000 to 3000 m in this area. Highly fluctuating vegetation and vegetation which showed a significantly decreasing trend were mostly distributed around the reservoirs and in the reaches of the river with hydropower developments. Vegetation with a relatively stable and significantly decreasing trend and vegetation with a highly fluctuating and significantly increasing trend are widely dispersed. With respect to the response of vegetation to climate change, about 20–30% of the vegetation has a significant correlation with climatic factors and the correlations in most areas are positive： regions with precipitation as the key influencing factor account for more than 10% of the area; regions with temperature as the key influencing factor account for less than 10% of the area; and regions with precipitation and temperature as the key influencing factors together account for about 5% of the total area. More than 70% of the vegetation has an insignificant correlation with climatic factors.
基金the European Union and Greek National Funds through the Operational Program Competitiveness,Entrepreneurship and Innovation,under the Call Research-Create-Innovate(Project Code:T1EDK-00739).
文摘Plant-to-plant variability is a crop stability component.The objective of this study in maize(Zea mays L.)was to test the validity of the theoretical background of the hypothesis that the coefficient of variation(CV)for grain yield per plant and mean yield are connected exponentially,following the Taylor’s Power Law(TPL)Model.Field experimentation was conducted across two sites,two seasons,and two planting densities.Densities were the main plots,corresponding to the typical practice of 8.89 plants m–2(TCD)and the low-input optimal of 5.33 plants m–2(LCD),while hybrids were the subplots.Data from 26 subplots in the first site averaged CV values of 22.6%at the TCD and 21.9%at the LCD,and mean yields of 19.1 and 13.9 t ha–1,respectively,following the TPL Model.The same was true for the second site,with average CVs and means of 41.5%and 14.3 t ha–1 at the TCD and 36.8%and 11.5 t ha–1 at the LCD.A test was performed on the simple correlation between the logarithms of variances and their respective means to investigate whether there is a systematic variance dependence on mean,thus questioning the reliability of TPL.The validity of TPL was verified in the first site.Nevertheless,there was a systematic dependence of yield variance on mean yield in the second site,implying that the CV-yield correlation might be not biologically meaningful.Conversion of the variance to remove its dependence on the mean did not validate the CV-yield negative relationship,meaning that caution is needed when interpreting the CV as a stability index for intra-crop variation.Whether the determinant factor of invalidity of TPL was the extensive intra-crop variation in the lower yielding second site can be assessed in future research.
基金Funded by the National Key Research and Development Program(2022YFC3003502).
文摘Paleoearthquake research represents an essential method for determining recurrence intervals oflarge earthquakes.Reasonable determination of the average recurrence interval and coefficient of variationprovides a crucial basis for the analysis of the recurrence characteristics of strong earthquakes on intraplatefaults in Chinese mainland.Paleoearthquake data from 145 fault segments of 93 well-studied faults in MainlandChina were collected,organized,and analyzed to discuss the rational estimation of the average recurrenceinterval and coefficient of variation of a strong earthquake occurrence probability model.First,differencesin structural environments were used as a basis to investigate the spatial distribution characteristics of theaverage recurrence intervals of strong earthquakes.The results indicate significant variations in the recurrenceperiods of strong earthquakes in the Sichuan–Yunnan,Xinjiang,North China,and northeastern Qinghai-Tibet Plateau structure zones.The Sichuan–Yunnan structure zone exhibited the shortest average recurrence intervalfor strong earthquakes,which was mainly distributed between 100 and 2000 years,and a relatively high sliprate.The Xinjiang structure zone attained a relatively balanced recurrence interval frequency distribution of1000–4500 years and a moderate slip rate.The North China structure zone showed the lowest slip rate,withthe strong earthquake recurrence interval mainly concentrated between 1000 and 4000 years.The northeastern Qinghai-Tibet Plateau structure zone presented two main frequency peaks in the strong earthquake recurrenceintervals between 1000–3000 years and 3000–5000 years and a relatively high slip rate.The slip rate is a keyfactor influencing the recurrence interval of strong earthquakes,and active faults with high slip rates showshort recurrence intervals.Furthermore,the relationship between fault slip rate,fault type,and the averagerecurrence interval of strong earthquakes was examined.The results indicate a good logarithmic linearrelationship between the fault slip rate and the average recurrence interval of large earthquakes—the higherthe slip rate,the shorter the recurrence interval of strong earthquakes.Fault type also showed a relation to theaverage recurrence interval,with the intervals for various types of active faults gradually increasing in theorder of strike-slip,normal,reverse strike-slip,reverse,and normal strike-slip faults.Second,we calculated theproportions of active faults and various fault types in each structure zone that had a coefficient of variation inrecurrence intervals less than 0.4.The findings reveal that the occurrence of strong earthquakes on most activefaults in Chinese mainland satisfies a quasiperiodic model.The general coefficient of variation across differentstructure zones and fault types ranges between 0.36 and 0.44,which indicates the nonsignificant difference inthe degree of variability in the periodicity of strong earthquake occurrence across various structural zones andfault types.
文摘To identify the root causes of heavy metal contamination in soils as well as prevent and control such contamination from its sources,this study explored the accumulation patterns and ecological risks of heavy metals like Cd and Pb in solid waste in mining areas and across the water body,sediment,soil and agricultural product ecosystem surrounding the mining areas.Focusing on the residual solid waste samples in lead-zinc deposits in a certain area of Guizhou Province,along with samples of topsoils,irrigation water,river sediments,and crops from surrounding areas.This study analyzed the distributions of eight heavy metals,i.e.,Cd,As,Cr,Hg,Pb,Zn,Cu,and Ni,in the samples through field surveys and sample tests.Furthermore,this study assessed the contamination levels and ecological risks of heavy metals in soils,sediments,and agricultural products using methods such as the single-factor index,Nemerow composite index,and potential ecological risk assessment.The results indicate that heavy metals in the solid waste samples all exhibited concentrations exceeding their risk screening values,with 60%greater than their risk intervention values.The soils and sediments demonstrate slight and moderate comprehensive ecological risks of heavy metals.The single-factor potential ecological risks of heavy metals in both the soil and sediment samples decreased in the order of Hg,Cd,Pb,As,Cu,Zn,Cr,and Ni,suggesting the same sources of heavy metals in the soils and sediments.Most of the agricultural product samples exhibited over-limit concentrations of heavy metals dominated by Cd,Pb,Ni,and Cr,excluding Hg and As.The agricultural product assessment using the Nemerow composite index reveals that 35%of the agricultural product samples reached the heavy metal contamination level,implying that the agricultural products from farmland around the solid waste dumps have been contaminated with heavy metals.The eight heavy metals in the soil,sediment,and agricultural product samples manifested high coefficients of variation(CVs),indicating pronounced spatial variability.This suggests that their concentrations in soils,sediments,and agricultural products are significantly influenced by human mining activities.Additionally,the agricultural products exhibit strong transport and accumulation capacities for Cd,Cu,and Zn.
基金Supported by the National Natural Science Foundation of China (Nos. 40921061 and 40701070)the Knowledge Innovation Program of the Chinese Academy of Sciences (Nos. KSCX1-YW-09-02,KZCX2-YW-Q1-07,and KZCX2-YW-Q1-15)
文摘Spatial variability of soil organic carbon (SOC) of different land use patterns and soil types was examined in a county-wide red soil region of South China,using six sampling densities,14,34,68,130,255,and 525 samples designed by the method of grid sampling in 6 different grid sizes,labeled as D14,D34,D68,D130,D255,and D525,respectively.The results showed that the coefficients of variation (CVs) of SOC decreased gradually from 62.8% to 47.4% with the increase in soil sampling densities.The SOC CVs in the paddy field change slightly from 30.8% to 28.7%,while those of the dry farmland and forest land decreased remarkably from 58.1% to 48.7% and from 99.3% to 64.4%,respectively.The SOC CVs of the paddy soil change slightly,while those of red soil decreased remarkably from 82.8% to 63.9%.About 604,500,and 353 (P < 0.05) samples would be needed a number of years later if the SOC change was supposedly 1.52 g kg-1,based on the CVs of SOC acquired from the present sampling densities of D14,D68,and D525,respectively.Moreover,based on the same SOC change and the present time CVs at D255,the ratio of samples needed for paddy field,dry farmland,and forest land should be 1:0.81:3.33,while the actual corresponding ratio in an equal interval grid sampling was 1:0.74:0.46.These indicated that the sampling density had important effect on the detection of SOC variability in the county-wide region,the equal interval grid sampling was not efficient enough,and the respective CV of each land use or soil type should be fully considered when determining the sampling number in the future.
文摘The flow and mixing behavior of two miscible liquids has been studied in an innovative static mixer by using CFD,with Reynolds numbers ranging from 20 to 160.The performance of the new mixer is compared with those of Kenics,SMX,and Komax static mixers.The pressure drop ratio(Z-factor),coefficient of variation(CoV),and extensional efficiency(α)features have been used to evaluate power consumption,distributive mixing,and dispersive mixing performances,respectively,in all mixers.The model is firstly validated based on experimental data measured for the pressure drop ratio and the coefficient of variation.CFD results are consistent with measured data and those obtained by available correlations in the literature.The new mixer shows a superior mixing performance compared to the other mixers.
基金supported by the National Natural Science Foundation of China (No.51178018,71031001)
文摘Fuzzy similarity measures, which are used to judge the closeness of two fuzzy sets, are presented to evaluate the water quality of the Haihe River. Based on the membership functions and coefficient of variation as the weights, four fuzzy similarity measures （including Lattice similarity measure, Hamming similarity measure, Euclidean similarity measure and the max-min similarity measure） are used to classify the 299 samples into the proper water quality standard ranks. The results are compared with the traditional distance discriminant methods. The calculation of two traditional distance discriminant methods （both Euclidean distance and absolute value distance） is also based on the use of coefficients of variation as the weights. Without the Lattice similarity measure, for this method loses some information, the correct assignment of samples classified into the same water quality ranks is 75.92% with the other three similarity measures and two distance discriminant methods. This result shows the reliability of the five methods. Only considering the three similarity measures, there were only 1.01% of the samples that did not classify to the same ranks, while the corresponding ratio of the two distance discriminant methods was 5.69%. The results of leave-one-out cross validation show that more than 88% of the samples are classified to the proper ranks, which demonstrates that the similarity measures are suitable to evaluate the water quality of the Haihe River.
基金by the National Natural Science Foundation of China(No.52174114)the State Key Laboratory of Hydroscience and Engineering of Tsinghua University(No.61010101218).
文摘Slope stability prediction research is a complex non-linear system problem.In carrying out slope stability prediction work,it often encounters low accuracy of prediction models and blind data preprocessing.Based on 77 field cases,5 quantitative indicators are selected to improve the accuracy of prediction models for slope stability.These indicators include slope angle,slope height,internal friction angle,cohesion and unit weight of rock and soil.Potential data aggregation in the prediction of slope stability is analyzed and visualized based on Six-dimension reduction methods,namely principal components analysis(PCA),Kernel PCA,factor analysis(FA),independent component analysis(ICA),non-negative matrix factorization(NMF)and t-SNE(stochastic neighbor embedding).Combined with classic machine learning methods,7 prediction models for slope stability are established and their reliabilities are examined by random cross validation.Besides,the significance of each indicator in the prediction of slope stability is discussed using the coefficient of variation method.The research results show that dimension reduction is unnecessary for the data processing of prediction models established in this paper of slope stability.Random forest(RF),support vector machine(SVM)and k-nearest neighbour(KNN)achieve the best prediction accuracy,which is higher than 90%.The decision tree(DT)has better accuracy which is 86%.The most important factor influencing slope stability is slope height,while unit weight of rock and soil is the least significant.RF and SVM models have the best accuracy and superiority in slope stability prediction.The results provide a new approach toward slope stability prediction in geotechnical engineering.
基金Project supported by the Hi-Tech Research and Development Program (863) of China(No.2002AA601013).
文摘Vertical and temporal distributions of N and P in soil solution in aquatic-terrestrial ecotone （ATE） of Taihu Lake were investigated, and the relations among N, P, ORP （oxidation reduction potential）, TOC, root system biomass and microorganism were studied. As a whole, significant declines in TN, NO3^--N, DON （dissolved organic nitrogen） and TP concentration in soil solution have occurred with increase of the depth, and reached their minima at 60 cm depth, except for NH4^＋-N, which increased with depth. The concentration of TP increased gradually from spring to winter in the topsoil, the maximum 0.08 mg/L presented in the winter while the minimum 0.03 mg/L in spring. In the deeper layer, the concentration value of TP fluctuated little. As for the NO3^--N, its seasonal variation was significant at 20 cm depth, its concentration increased gradually from spring to autumn, and decreased markedly in winter. Vertical and temporal distribution of DON is contrary to that of NO3^--N. The results also show that the variation of N and P in the percolate between adjacent layers is obviously different. The vertical variation ofTN, TP, NO3^--N, NH4^＋-N and DON is significant, of which the variation coefficient of NO3^--N along the depth reaches 100.23%, the highest; while the variation coefficient of DON is 41.14%, the smallest. The results of correlation analysis show that the concentration of nitrogen and phosphorus correlate significantly with TOC, ORP, root biomass and counts of nitrifying bacteria. Most nutrients altered much from 20 to 40 cm along the depth. However, DON changed more between 60 and 80 cm. Results show that soil of 0-60 cm depth is active rhizoplane, with strong capability to remove the nitrogen and phosphorus in ATE. It may suggest that there exists the optimum ecological efficiency in the depth of above 60 cm in reed wetland. This will be very significant for ecological restoration and reestablishment.
基金supported by the Ministry of Science and Technology of China (2006BAD09A01, 200905020)the National Natural Science Fundation of China (30771661the 111 Project of China (B08049)
文摘The exceptionally large individual growth variation has been previously recognized in several sea cucumber cohorts. However, there is a lack of information regarding the mechanism of such individual differences. In this study, the sea cucumber Apostichopusjaponicus （Selenka） was reared individually in order to eliminate possible effects of social interaction, stocking density, etc. The results showed that there were substantial differences in growth among the sea cucumber individuals during the 100-day experiment. The special growth rate of the sea cucumber individuals differed by up to three folds （from 0.40% to 1.01%）, and the coefficient of variation in body weight increased from 12.04% to 40.51%. The final wet body weight, food intake and food conversion efficiency for each sea cucumber were generally positively correlated with their initial wet body weight （P〈0.05）. Energy budget of the animals showed that the food energy spent on respiration was much greater （about four folds） but energy deposited for growth was much less for （initially） smaller than for larger A. japonicus. The present result implies that there are obvious genetic differences among the sea cucumber individuals, largely accounting for the individual growth variation of the cohort sea cucumber. These results will provide some basic data for promoting selective breeding and fanning of the sea cucumber.
基金Supported by the Special Fund for Agro-scientific Research in the Public Interest of China(No.200903001-3)the National Natural Science Foundation of China(No.41301231)the Recruitment Program of High-Level Talents of Xinjiang,China
文摘Located in the inland arid area of central Asia, salt-affected farmlands take up one third of the total irrigated land area in Xinjiang of Northwest China. Spatio-temporal variability of soil salinity and the underlying mechanism are fundamental problems challenging the sustainability of oasis agriculture in China. In this study, the data of total dissolved solids(TDS) measured for soil samples collected from 27 representative study areas in the oasis areas of Xinjiang were analyzed and the coefficient of variation(CV) and stratification ratio(SR) of TDS were used to describe the lateral and vertical soil salinity variations, respectively. Weekly, monthly,and annual changes in soil salinity were also summarized. Results showed that the top(0–20 cm) soil salinity was highly variable(CV> 75%) for most studied areas. Lateral variation of soil salinity was significantly correlated with the sampling interval; as a result, a maximum sampling interval of 0.9 m was found for reducing evaluation uncertainty. The top 0–20 cm soil salt accounted for about25.2% of the total salt in the 0–100 cm soil profile. The stratification ratio values(the ratio of TDS at the 20–40 cm depth to that at the 0–20 cm depth) were mostly smaller than 1 and on average 0.92, illustrating that the top 0–20 cm soil contained slightly more salt and a considerable amount of salt still existed in subsurface and deep horizons. Irrigation reduced top soil salinity by 0.52 g kg-1, or14.6%, within the first week. On average, the relative range of soil salinity, calculated to indicate monthly changes in soil salinity, was58.2% from May to September. A 27-year experiment indicated that cultivation increased soil salinity by 44.4% at a rate of 0.14 g kg-1year-1. At small spatio-temporal scales, soil salinity variation was mainly affected by anthropogenic factors, such as irrigation and land use. However, natural factors, including groundwater, topography, and climate conditions, mainly influenced soil salinity variation at large spatio-temporal scales. This study displayed the highly variable nature of soil salinity in space and time. Those driving factors identified in this study could provide guidelines for developing sustainable agriculture in the oasis areas and combating salinization in arid regions of China.
基金Project(31300343)supported by the National Natural Science Foundation of ChinaProject(Y20160023)supported by Open Science Research Fund of State Key Laboratory of Soil and Sustainable Agriculture,Institute of Soil Science,Chinese Academy of Sciences,China+1 种基金Project supported by Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD),ChinaProject supported by Jiangsu Collaborative Innovation Center of Technology and Material of Water Treatment
文摘Functional traits, specifically leaf functional traits, are core-topics to explore importance to the invasion success of invasive plant species. This study aims to address the differences in leaf functional traits and their corresponding variability of the invasive tree staghorn sumac Rhus typhina L. with different invasion success, including lower and higher invasion success, in two climatic regions in North China, including a warm temperate region and a cold temperate region. No significant differences were found for leaf functional traits of staghorn sumac across different invasion success. However, the variability of leaf chlorophyll and nitrogen concentrations of staghorn sumac under higher invasion success were approximately 66.023% and 68.615% higher than those under lower invasion success, respectively. The leaf chlorophyll and nitrogen concentrations of staghorn sumac in the warm temperate region were approximately 18.432% and 16.337% higher than those in cold temperate region, respectively. The variability of specific leaf area of staghorn sumac in warm temperate region was approximately 59.802% higher than that in cold temperate region. Accordingly, leaf chlorophyll and N concentrations as well as specific leaf area of staghorn sumac and their corresponding variability may play an essential role in shaping ecological success of studied invader along a climatic gradient.
基金National Natural Science Foundations of China(Nos.41172236,41402243,and 40911120044)Basic Research Project of Jilin University,China(No.450060491448)
文摘Post-construction settlement has gained increasing attention because it frequently causes engineering problems. A combined model is a commonly used prediction model that overcomes the difficulty of a single model( i. e., cannot reflect various regulations of settlement at some stages or the entire process). In this study,the correlation coefficient,maximum error values,and other values were obtained according to the fitting and predicted results of a single model. The coefficient of variation was then introduced to determine the weight of each model forming the combination. The proposed model was used to fit and predict for settlement and overcome the issue of utilizing a single model while determining the weight. The fitting predictive effect was also analyzed using the settlement fitting precision results. The fitting precision of optimizing the combination model is high. The predicted data of the post-construction settlement are closer to the calculated value of the settlement monitoring data. Moreover,the proposed model has good practicability,does not require the interval data of settlement,and restricts the model number. Thus,this model can be applied in the engineering field.
