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With the increasing availability of large-area graphene, the ability to rapidly and accurately assess the quality of the electrical properties has become critically important. For practical applications, spatial variability in carrier density and carrier mobility must be controlled and minimized. We present a simple framework for assessing the quality and homogeneity of large-area graphene devices. The field effect in both exfoliated graphene devices encapsulated in hexagonal boron nitride and chemical vapor-deposited （CVD） devices was measured in dual current-voltage configurations and used to derive a single, gate-dependent effective shape factor, t, for each device, β is a sensitive indicator of spatial homogeneity that can be obtained from samples of arbitrary shape. All 50 devices investigated in this study show a variation （up to tenfold） in β as a function of the gate bias. Finite element simulations suggest that spatial doping inhomogeneity, rather than mobility inhomogeneity, is the primary cause of the gate dependence of β, and that measurable variations of β can be caused by doping variations as small as 10^10 cm^-2. Our results suggest that local variations in the position of the Dirac point alter the current flow and thus the effective sample shape as a function of the gate bias. We also found that such variations lead to systematic errors in carrier mobility calculations, which can be revealed by inspecting the corresponding β factor.

As the offshore engineering moving from shallow to deep waters, the foundation types for fixed and floating platforms have been gradually evolving to minimize engineering costs and structural risks in the harsh offshore environments. Particular focus of this paper is on the foundation instability and its failure mechanisms as well as the relevant theory advances for the prevail- ing foundation types in both shallow and deep water depths. Piles, spudcans, gravity bases, suction caissons, and plate anchors are detailed in this paper. The failure phenomena and mechanisms for each type of foundations are identified and summarized, respectively. The theoretical approaches along with sophisticated empirical solutions for the bearing capacity problems are then presented. The major challenges are from flow-structure-soil coupling processes, rigorous constitutive modeling of cyclic behaviors of marine sediments, and the spatial variability of soil properties for large-spreading structures. Further researches are suggested to reveal the instability mechanisms for underpinning the evolution of offshore foundations.

Soil carbon to nitrogen（C/N） ratio is one of the most important variables reflecting soil quality and ecological function,and an indicator for assessing carbon and nitrogen nutrition balance of soils.Its variation reflects the carbon and nitrogen cycling of soils.In order to explore the spatial variability of soil C/N ratio and its controlling factors of the Ili River valley in Xinjiang Uygur Autonomous Region,Northwest China,the traditional statistical methods,including correlation analysis,geostatistic alanalys and multiple regression analysis were used.The statistical results showed that the soil C/N ratio varied from 7.00 to 23.11,with a mean value of 10.92,and the coefficient of variation was 31.3%.Correlation analysis showed that longitude,altitude,precipitation,soil water,organic carbon,and total nitrogen were positively correlated with the soil C/N ratio（P 〈 0.01）,whereas negative correlations were found between the soil C/N ratio and latitude,temperature,soil bulk density and soil p H.Ordinary Cokriging interpolation showed that r and ME were 0.73 and 0.57,respectively,indicating that the prediction accuracy was high.The spatial autocorrelation of the soil C/N ratio was 6.4 km,and the nugget effect of the soil C/N ratio was 10% with a patchy distribution,in which the area with high value（12.00–20.41） accounted for 22.6% of the total area.Land uses changed the soil C/N ratio with the order of cultivated land 〉 grass land 〉 forest land 〉 garden.Multiple regression analysis showed that geographical and climatic factors,and soil physical and chemical properties could independently explain 26.8%and 55.4% of the spatial features of soil C/N ratio,while human activities could independently explain 5.4% of the spatial features only.The spatial distribution of soil C/N ratio in the study has important reference value for managing soil carbon and nitrogen,and for improving ecological function to similar regions.

The estimation of precipitation quantiles has always been an area of great importance to meteorologists, hydrologists, planners and managers of hydrotechnical infrastructures. In many cases, it is necessary to estimate the values relating to extreme events for the sites where there is little or no measurement, as well as their return periods. A statistical approach is the most used in such cases. It aims to find the probability distribution that best fits the maximum daily rainfall values. In our study, 231 rainfall stations were used to regionalize and find the best distribution for modeling the maximum daily rainfall in Northern Algeria. The L-moments method was used to perform a regionalization based on discordance criteria and homogeneity test. It gave rise to twelve homogeneous regions in terms of LCoefficient of variation（L-CV）, L-Skewness（L-CS） and L-Kurtosis（L-CK）. This same technique allowed us to select the regional probability distribution for each group using the Z statistic. The generalized extreme values distribution（GEV） was selected to model the maximum daily rainfall of 10 groups located in the north of the steppe region and the generalized logistic distribution（GLO） for groups representing the steppes of Central and Western Algeria. The study of uncertainty by the bias and RMSE showed that the regional approach is acceptable. We have also developed maximum daily rainfall maps for 2, 5, 10, 20, 50 and 100 years return periods. We relied on a network of 255 rainfall stations. The spatial variability of quantiles was evaluated by semi-variograms. All rainfall frequency models have a spatial dependence with an exponential model adjusted to the experimental semi-variograms. The parameters of the fitted semi-variogram for different return periods are similar, throughout, while the nugget is more important for high return periods. Maximum daily rainfall increases from South to North and from West to East, and is more significant in the coastal areas of eastern Algeria where it exceeds 170 mm for a return period of 100 years. However, it does not exceed 50 mm in the highlands of the west.

Accessibility to organic carbon（OC） budget is required for sustainable agricultural development and ecosystem preservation and restoration. Using geostatistical models to describe and demonstrate the spatial variability of soil organic carbon（SOC） will lead to a greater understanding of this dynamics. The aim of this paper is to present the relationships between the spatial variability of SOC and the topographic features by using geostatistical methods on a loess mountain-slope in Toshan region, Golestan Province, northern Iran. Hence, 234 soil samples were collected in a regular grid that covered different parts of the slope. The results showed that such factors as silt, clay, saturated moisture content, mean weighted diameter（MWD） and bulk density were all correlated to the OC content in different slope positions, and the spatial variability of SOC more to slope positions and elevations. The coefficient of variation（CV） indicated that the variability of SOC was moderate in different slope positions and for the mountain-slope as a whole. However, the higher variability of SOC（CV = 45.6%） was shown in the back-slope positions. Also, the ordinary cokriging method for clay as covariant gave better results in evaluating SOC for the whole slope with the RMSE value 0.2552 in comparison with the kriging and the inverse distance weighted（IDW） methods. The interpolation map of OC for the slope under investigation showed lowering SOC concentrations versus increasing elevation and slope gradient. The spatial correlation ratio was different between various slope positions and related to the topographic texture.

In areas with topographic heterogeneity, land use change is spatially variable and influenced by climate, soil properties, and topography. To better understand this variability in the high-sediment region of the Loess Plateau in which soil loss is most severe and sediment diameter is larger than in other regions of the plateau, this study builds some indicators to identify the characteristics of land use change and then analyze the spatial variability as it is affected by climate, soil property, and topography. We build two indicators, a land use change intensity index and a vegetation change index, to characterize the intensity of land use change, and the degree of vegetation restoration, respectively. Based on a subsection mean method, the two indicators are then used to assess the spatial variability of land use change affected by climatic, edaphic, and topographic elements. The results indicate that： 1） Land use changed significantly in the period 1998-2010. The total area experiencing land use change was 42,302 km2, accounting for 22.57%of the study area. High-coverage grassland, other woodland, and forest increased significantly, while low-coverage grassland and farmland decreased in 2010 compared with 1998.2） Land use change occurred primarily west of the Yellow River, between 35 and 38 degrees north latitude. The four transformation types, including （a） low-coverage grassland to medium-coverage grassland, （b） medium-coverage grassland to high-coverage grassland, （c） farmland to other woodland, and （d） farmland to medium-coverage grassland, were the primary types of land use change, together constituting 60% of the area experiencing land use change. 3） The spatial variability of land use change was significantly affected by properties of dryness/wetness, soil conditions and slope gradient. In general, land use changed dramatically in semi-arid regions, remained relatively stable in arid regions, changed significantly in clay-rich soil, remained relatively stable in clay-poor soil, changed dramatically in steeper slopes, and remained relatively stable in tablelands and low-lying regions. The increase in vegetation coincided with increasing changes in land use for each physical element. These findings allow for an evaluation of the effect of the Grain to Green Program, and are applicable to the design of soil and water conservation projects on the Loess Plateau of China.

Understanding the spatial variability of house- hold carbon emissions is necessary for formulating sustainable and low-carbon energy policy. However, data on household carbon emissions is limited in China, the world＇s largest greenhouse gases emitter. This study quantifies and maps household carbon emissions in Shanghai using a city-wide household survey. The findings reveal substantial spatial variability in household carbon emissions, especially in transport-related emissions. Low emission clusters are founded in Hongkou, Xuhui, Luwan, Jinshan, and Fengxian. High emission clusters are located in Jiading and Pudong. Overall, the spatial pattern of household carbon emissions in Shanghai is donut-shaped： lowest in the urban core, increasing in the surrounding suburban areas, and declining again in the urban fringe and rural regions. The household emissions are correlated with a number of housing and socioeconomic factors, including car ownership, type of dwelling, size of dwelling, age of dwelling, and income. The findings underscore the importance of a localized approach to low-carbon policy- making and implementation.

Rank Histograms are suitable tools to assess the quality of ensembles within an ensemble prediction system or framework. By counting the rank of a given variable in the ensemble, we are basically making a sample analysis, which does not allow us to distinguish if the origin of its variability is external noise or comes from chaotic sources. The recently introduced Mean to Variance Logarithmic （MVL） Diagram accounts for the spatial variability, being very sensitive to the spatial localization produced by infinitesimal perturbations of spatiotemporal chaotic systems. By using as a benchmark a simple model subject to noise, we show the distinct information given by Rank Histograms and MVL Diagrams. Hence, the main effects of the external noise can be visualized in a graphic. From the MVL diagram we clearly observe a reduction of the amplitude growth rate and of the spatial localization （chaos suppression）, while from the Rank Histogram we observe changes in the reliability of the ensemble. We conclude that in a complex framework including spatiotemporal chaos and noise, both provide a more complete forecasting picture.

Increasing shortages of fresh water has led to greater use of treated wastewater for irrigation of crops. This study evaluates the spatial variability of soil proper- ties after irrigation with wastewater and freshwater. Geostatistical techniques were used to identify the variability of soil properties at the different sites. A set of physical and chemical soil properties were measured including total nitrogen （TN）, total phosphorus （TP）, organic matter （OM） and soil moisture. The TN concen- tration levels varied from 567 to 700 mg. kg-1, while OC levels ranged from 7.3 to 16.3 mg.kg-1 in wastewater- irrigated zones. The concentration levels of TP were between 371.53 and 402.88 mg-kg-1 for the wastewater- irrigated sites. Wastewater irrigation resulted in higher TN, TP and OM concentrations by 18.4%, 8% and 25%, respectively. The highest TN and OM occurred along the wastewater trunk. It was also observed that nitrogen concentrations correlate with the soil＇s organic matter. The increase of salinity may be associated with the increase of pH, which might suggest that a reduction of pH will be beneficial for plant growth due to the decrease of salinity. The average concentrations of nitrogen in topsoil were higher than those in subsurface soils in irrigated areas. Such differences of the N profile might be due to variations in organic matter content and microbial populations. Consistent with TN and OM, soil C：N decreased significantly with an increase of depth. This phenomenon possibly reflects a greater degree of breakdown and the older age of humus stored in the deeper soil layers. The analysis of pH levels at different depths for the three sites showed that pH values for wastewater irrigation were slightly lower than the controlled sites at the same depths.

The spatial variations of phytoplankton community structure in the Xiamen Western Bay during the summer and autumn cruises in 2001 were investigated based on HPLC analysis of photosynthetic pigments in algal cells and CHEMTAX processing of pigment data. The Chl a concentration reached 18.9 μg/L in the summer and declined to 0.28–2.17 in the autumn, respectively, consistent with the observation of diatom blooms in June. Among the accessory pigments, fucoxanthin was consistently the most abundant, ranging from 0.172 to 8.46 μg/L, with the maximum concentrations in June. 19’- hexfucoxanthin and alloxanthin were the other two abundant pigments in the summer and autumn. In addition, 19’-butanoyloxyfucoxanthin or peridinin was also important in late autumn. Generally the biomass of all the phytoplankton or each group was higher in the inner part than the mouth of this bay, represented by Chl a. CHEMTAX processing revealed the dominance of diatoms with their contribution of 14.6%–52.5% to the total Chl a, but its importance decreased in the autumn. Cryptophytes and Haptophytes, with an average contribution of 16.9%–31.4% and 12.1%–26.3%, were the other two important groups, especially in the autumn. On the contrary, Dinoflagellates and Chlorophytes were the minor groups, but the former became important sporadically in the autumn. It was suggested that there was distinctive variation in both the phytoplankton community structure and biomass between summer and autumn in the Xiamen Western Bay and the latter was coupled to the changes in temperature and dissolved oxygen. However, the spatial variation of the phytoplankton community structure was not as clear as the trend in the biomass of phytoplankton among all the sites in this bay.