New SST correction method from multi-satellite based on the coefficient of variation

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.

The coefficient of variation representing the non-uniformity of the strain field and its implication to detect earthquake precursor

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.

CLASSICAL LIMITS FOR THE COEFFICIENT OF VARIATION FOR THE NORMAL DISTRIBUTION

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

Intelligent prediction of slope stability based on visual exploratory data analysis of 77 in situ cases

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.

Testing Taylor’s Power Law association of maize interplant variation with mean grain yield

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.

Degree of style coiling is associated with corolla-tube length in the nectarless flowers of Roscoea schneideriana

The plant-pollinator‘arms race’model posits that a major driver of the evolution of elongated corollas in flowers is reciprocal selection for‘morphological fit’between pollinator-tongue length and access distance to nectar(usually corolla-tube length).Evidence for the pollinator-mediated selection on tube length and evolution of multiple,correlated floral traits remains inconclusive.To gain possible insights into the strength of stabilizing selection by assessing standing phenotypic variation,we measured a series of functionally important floral traits,including corolla tube length and‘effective’tube depth and degree of style coiling.We then calculated coefficients of variation(CV)for these traits in three field populations of R.schneideriana.Unlike in most long-tubed flowers,the bottom part of the corolla tube is completely occupied by the style,with no room for nectar.The length of this portion of the corolla tube was more variable(higher CV)than the upper part of the corolla tube,suggesting that functional tube depth was under stronger stabilizing selection.The degree of style coiling was negatively related to the corolla-tube length in all three populations of R.schneideriana,suggesting that there may be conflicting selection acting on style length and corolla-tube length,which are otherwise usually tightly correlated.Given the lack of nectar in the flowers of this species,the long corolla tubes and long styles may represent morphological holdovers from ancestors that were pollinated by long-tongued pollinators,as is still seen in related species in the western Himalayas.

Multi-dimensional size effects and representative elements for nonpersistent fractured rock masses: A perspective of geometric parameter distribution

This study takes a fractured rock mass in the Datengxia Hydropower Station,China as an example to analyze the size effects and determine the representative elementary sizes.A novel method considering geometric parameter distributions is proposed in this work.The proposed method can quickly and simply determine the size effects and representative elementary sizes.Specifically,geometric parameter distributions,including fracture frequency,size and orientation,are generated on the basis of the Bernoulli trial and Monte Carlo simulation.The distributions are assessed using the coefficient of variation(CV),and the acceptable variations for CV(5%,10%and 20%)are used to determine representative elementary sizes.Generally,the representative element of rock masses is the representative elementary volume(REV).The present study extends the representative element to other dimensions,i.e.representative elementary length(REL)and representative elementary area(REA)for one and two dimensions,respectively.REL and REA are useful in studying the size effects of one-(1D)and twodimensional(2D)characteristics of rock masses.The relationships among multi-dimensional representative elementary sizes are established.The representative elementary sizes reduce with the increase in the dimensions,and REA and REV can be deduced by REL.Therefore,the proposed method can quickly and simply determine REL and further estimate REA and REV,which considerably improves the efficiency of rock mass analysis.

Optimizing Optical Attocells Positioning of Indoor Visible Light Communication System

Visible light communication(VLC),which is a prominent emerging solution that complements the radio frequency(RF)technology,exhibits the potential to meet the demands of fifth-generation(5G)and beyond technologies.The random movement of mobile terminals in the indoor environment is a challenge in the VLC system.The model of optical attocells has a critical role in the uniform distribution and the quality of communication links in terms of received power and signal-to-noise ratio(SNR).As such,the optical attocells positions were optimized in this study with a developed try and error(TE)algorithm.The optimized optical attocells were examined and compared with previous models.This novel approach had successfully increased minimum received power from−1.29 to−0.225 dBm,along with enhanced SNR performance by 2.06 dB.The bit error rate(BER)was reduced to 4.42×10−8 and 6.63×10−14 by utilizing OOK-NRZ and BPSK modulation techniques,respectively.The optimized attocells positions displayed better uniform distribution,as both received power and SNR performances improved by 0.45 and 0.026,respectively.As the results of the proposed model are optimal,it is suitable for standard office and room model applications.

Comparative analysis of different static mixers performance by CFD technique:An innovative mixer

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.

Vertical and temporal distribution of nitrogen and phosphorus and relationship with their influencing factors in aquatic-terrestrial ecotone:a case study in Taihu Lake,China

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.

Settlement Prediction of Dredger Fill with the Optimal Combination Model

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.

Spatial Identification of Urban Ecological Function on the North Slope of Qinling Mountains Based on Ecological Sensitivity—A Case Study in Baoji, China

Since the 17th National Congress of the Communist Party of China, ecological civilization has been the key construction goal in China, which has a profound impact on the process of urbanization. In recent years, with the rapid development of urbanization and unreasonable land development and utilization, the ecological environment has deteriorated sharply, and the stability of ecological environment has always been a difficult problem in the process of regional development. The spatial division of urban ecological function can be divided into different types of spatial utilization according to the fragile state of ecological environment, which not only guarantees urban construction but also maintains the ecological environment health, and has great economic benefits and ecological value in formulating regional development strategies and ecological protection. In this paper, from four perspectives of “land, water, human and forest”, eight factors affecting ecological sensitivity were selected, and GIS spatial superposition method was used to conduct qualitative and quantitative analysis on the ecological sensitivity of Baoji City, and the evaluation results of single factor ecological sensitivity and comprehensive ecological sensitivity were obtained. The areas with different ecological sensitivity are divided into extremely sensitive areas, highly sensitive areas, moderately sensitive areas, slightly sensitive areas and non-sensitive areas. The research shows that the proportion of extreme, high, moderate, mild and insensitive areas in Baoji City is 7.32%, 10.57%, 22.25%, 42.91% and 16.95% respectively. Finally, the areas with different sensitivity grades are identified as three types of urban ecological function areas: ecological conservation area, ecological coordinated moderate utilization area and ecological suitable construction area, so as to provide scientific theoretical basis for urban construction and land use optimization in Baoji City.

A Study in Search of Interconnection between Surface Parameters and Surrounding Synoptic And Subsynoptic Features

The paper reveals that the variations in parameters like u *, the scaling velocity and θ*. The scaling temperature during the various phases of monsoon might be linked with subsynoptic features. The rise in u * is mainly connected with the presence of lower tropospheric cyclonic vorticity over a subsynoptic scale of the site. However the variations in θ. is mainly linked with the various phases of monsoon and θ * shows a sharp rise in presence of low level convective cloud.Besides the correlation studies of u and u., θv and θv, θv-θv0 and θv, * are undertaken. The correlation between θv and θv * is poor. In other two cases correlations are good. Besides u / u * has shown good coefficient of variation values within the ξ range.

Determ ination of Even Degree of Animal Population

The even degree of animal population is generlay measured by the coefficient of variation of major economic characters.Facing the coefficient of variation,a statistic with complex properties,we achieved indirectly the determination of confidence interval for even degree of an animal population by analysing the reciprocal of the statistic.The sample size which is suitable to the determination of the even degree of an animal population was probed into within the extent of permissive estimation error.

Effects of Region and Elevation on Adaptation of Leaf Functional Traits of an Invasive Plant Erigeron annuus in China

A key scientific challenge relating to the threat of invasive plants on agriculture at the region level is to understand their adaptation and evolution in functional traits.Leaf functional traits,related to growth and resource utilization,might lead to adaptation of invasive plants to the geographical barriers(region or elevation).In the field experiment,we discussed the effects of region and elevation on leaf functional traits on invasive plant Erigeron annuus in farmland habitats in China.We compared leaf size,coefficient of variation(CV)of leaf traits,and fluctuating asymmetry(FA)of E.annuus from three regions(east vs.center vs.west)and two leaf types(vegetative vs.reproductive leaf),and from nine elevations(980-2100 m)in the west region of China.Our results indicated region and leaf type influenced leaf functional traits,and leaf size was significantly higher and CV of leaf traits and FA in reproductive leaves were significantly lower in the east region than in the west and center regions.Elevation and leaf type affected leaf functional traits,and leaf size was significantly higher and CV of leaf traits in reproductive leaves were significantly lower in moderate elevation.E.annuus has higher leaf size and developmental stability(lower CV and FA)in the eastern region due to the longer adaptation period.Therefore,leaf functional traits play an important role in the adaptation of different longitudes and elevations.It can also facilitate the understanding of the invasiveness and adaptation of leaf traits of invasive plants in the agricultural ecosystem during their spread process in China.

Dynamic Water and Salt Changes in Saline Wasteland on the Lower Edge of Plain Reservoirs in the Desert Oasis Region

In order to reveal the distribution characteristics of water and salt in the non-irrigated saline wasteland and the growth zone of the windbreaks surrounding the plain reservoir,the groundwater and soil monitoring points were set up around the south area of Duolang Reservoir in the desert oasis.Monthly groundwater depth monitoring and soil water content and salt content fixed-point sampling for a period of 2 years were conducted.The results showed that the groundwater depth of salt wasteland in the area around the reservoir area changed slightly during the monitoring period of 2 years,and the average is 1.28 m.The soil moisture content increased with the increase of soil depth,and soil water content of 60-100 cm was larger than that of other soil layers.The salt content of the soil in the salt wasteland varied between 0.48 g/kg and8.86 g/kg in the two years,and the total salt content of different soil decreased with the increase of soil depth.The soil salt content changed greatly in 0-40 cm soil layers,with significant salt accumulation phenomenon.The soil salt content of windbreaks was significantly lower than that of the natural ecological forest.

Income Inequality in Mountain Areas: The Case of Agroforestry Farming Systems in Uluguru Mountains, Tanzania

Land degradation due to use of unsustainable agricultural practices has affected many communities in rural mountain areas rendering them to be more vulnerable to income poverty and inequality. In this case, agroforestry systems promise to offer great solutions as they can be developed in unfavourable conditions where other production systems would either rapidly degrade the land or otherwise would not be possible. However, little is known whether agroforestry can address issues of income inequality in mountain areas. Hence, we conducted a study to investigate the nature and determinants of income inequality in Uluguru Mountains, Tanzania. Specifically, we used the cross-sectional research design and we calculated the income percentile shares, Gini coefficients and the coefficient of variation (CV), to pinpoint the nature of income inequality in the study area. The determinants of income inequality were analysed using the step by step multiple linear model. The results of analysis suggested prevalence of income inequality. Crop production was the main source of income in the agroforestry systems of the study area. Earnings from crops and timber were decreasing income-inequality amongst smallholder farmers. Our disaggregated analysis showed that off-farm income was also decreasing income-inequality for farmers with farmlands located close to homestead, for female-headed households, for farmers who did not access extension services, and those who were members of community-based financial institutions. Estimated incomes increased with household assets, size of farmland, and age of household head. However, the same decreased with household size. We found gender disparity to be one of the key issues that need attention in formulating future policies to reduce inequality. We recommend promotion of livelihood diversification as well as the designing and implementation of tailor-made training and farm financing mechanism to help the less resource-endowed farmers in mountain areas to raise their economic portfolios and social status and combat income poverty and inequality.

Characteristics of soil quality attributes under different agroecosystems and its implications for agriculture in the Choke Mountain watershed in Ethiopia

Awareness of how soil properties vary over agroecosystems(AES) is essential for understanding soil potentials and improving site-specific agricultural management strategies for a sustainable ecosystem. This study examined the characteristics of soil quality attributes and implications for agriculture in the Choke Mountain watershed in Ethiopia. Forty-seven composite soil samples(0–20 cm deep) were collected from lowland and valley fragmented(AES 1),midland plain with black soil(AES 2), midland plain with brown soil(AES 3),sloppy midland land(AES 4), and hilly and mountainous highlands(AES 5).Ten of 15 soil quality properties were significant(P < 0.05 or 0.01), including silt, exchangeable bases, cation exchange capacity, percent base saturation,p H, organic matter, total nitrogen and available phosphorous(P) across the five AES. However, all properties were variable with coefficients of variation from 7%(total porosity) to 169%(available P) across the AES. Although AES 2and 3 are affected by waterlogging and acidity, these two have better prospects for agriculture, but AES 1, 4, and 5 are unsuitable for agriculture because of soil erosion. Therefore, appropriate and applicable soil management strategies, particularly lime application and organic fertilizer, are fundamental to reversing soil acidity and improving soil fertility.

Mapping groundwater dependent ecosystem potential in a semi-arid environment using aremote sensing-based multiple-lines-of-evidence approach

Groundwater dependent ecosystems(GDEs)are vulnerable to groundwater regime changes.However,their protection is often hampered by challenges in their identification.Within is presented a remote sensing-based GDE potential mapping approach based on the persistency of relevant vegetation parameters during prolonged dry periods as an indicator of potential‘consistency’of water supply(e.g.groundwater).The study uses a novel approach to characterising persistency for selected vegetation parameters based on a normalised difference measure and an adaptation of the coefficient of variation statistic.Aggregation of parameters was facilitated through the analytic hierarchy process providing a structured weighting approach to minimise parameter bias.The approach is demonstrated in the semi-arid Flinders Ranges of South Australia where new groundwater resources are being sought to support local domestic and industry needs.Variations in GDE potential were mapped to better target areas where exploration of groundwater should be avoided.Mapping results indicated a high-level of agreement of 77%with an independent springs dataset,along with an 87%agreement with areas coinciding with known phreatophyte species and depths to groundwater.The index-based mapping approach has potential applicability across landscapes,as it normalises for variations in vegetation cover,minimises technical overheads,and employs continental-wide remote sensing data-products.

Inter-annual variations in vegetation and their response to climatic factors in the upper catchments of the Yellow River from 2000 to 2010

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.