Experimental Studies of Scale Effect on the Shear Strength of Coarse-Grained Soil

Shear strength is an essential index for the evaluation of soil stability. Test results of the shear strength of scaled coarse-grained soil (CGS for short) are usually not able to accurately reflect the actual properties and behaviors of in situ CGS due to the scale effect. Therefore, this study focuses on the influence of the scale effect on the shear strength of scaled CGS, which has an important theoretical significance and application for the strength estimation of CGS in high earth-rock dam engineering. According to previous studies, the main cause of the scale effect for scaled CGS is the variation of the gradation structure as well as the maximum particle size (dmax), in which the gradation structure as a characteristic parameter can be expressed by the gradation area (S). A total of 24 groups of test soil samples with different gradations were designed by changing the maximum particle size dmax and gradation area S. Direct shear tests were conducted in this study to quantitatively explore the effect of the gradation structure and the maximum particle size on the shear strength of CGS. Test results suggest that the shear strength indexes (i.e., the cohesion and internal friction angle) of CGS present an increasing trend with the improvement of the maximum particle size dmax, and thus a logarithmic function relationship among c, φ, and dmax is presented. Both cohesion (c) and internal friction angle (φ) are negatively related to the gradation area (S) in most cases. As a result, an empirical relationship between c, φ, and S is established based on the test results. Furthermore, a new prediction model of shear strength of CGS considering the scale effect is proposed, and the accuracy of this model is verified through the test results provided by relevant literature. Finally, the applicability of this model to different types of CGS is discussed.

Spurious Correlation Due to Scaling

Scaling is common in empirical accounting research. It is often done to mitigate heteroscedasticity or the influence of firm size on parameter estimates. However, Barth and Clinch conclude that common diagnostic tools are ineffective in detecting various scale effects. Using analytic results and Monte Carlo simulations, we show that common forms of scaling, when misapplied, induce substantial spurious correlation via biased parameter estimates. Researchers, when uncertain about the exact functional form of scale effect, are typically better off dealing with both heteroscedasticity and the influence of larger firms using techniques other than scaling.

Uncertainties in mass balance estimation of the Antarctic Ice Sheet using the input and output method

The input-output method (IOM) is one of the most popular methods of estimating the ice sheet mass balance (MB), with a significant advantage in presenting the dynamics response of ice to climate change. Assessing the uncertainties of the MB estimation using the IOM is crucial to gaining a clear understanding of the Antarctic ice-sheet mass budget. Here, we introduce a framework for assessing the uncertainties in the MB estimation due to the methodological differences in the IOM, the impact of the parameterization and scale effect on the modeled surface mass balance (SMB, input), and the impact of the uncertainties of ice thickness, ice velocity, and grounding line data on ice discharge (D, output). For the assessment of the D’s uncertainty, we present D at a fine scale. Compared with the goal of determining the Antarctic MB within an uncertainty of 15 Gt yr−1, we found that the different strategies employed in the methods cause considerable uncertainties in the annual MB estimation. The uncertainty of the RACMO2.3 SMB caused by its parameterization can reach 20.4 Gt yr−1, while that due to the scale effect is up to 216.7 Gt yr−1. The observation precisions of the MEaSUREs InSAR-based velocity (1–17 m yr−1), the airborne radio-echo sounder thickness (±100 m), and the MEaSUREs InSAR-based grounding line (±100 m) contribute uncertainties of 17.1 Gt yr−1, 10.5 ± 2.7 Gt yr−1 and 8.0~27.8 Gt yr−1 to the D, respectively. However, the D’s uncertainty due to the remarkable ice thickness data gap, which is represented by the thickness difference between the BEDMAP2 and the BedMachine reaches 101.7 Gt yr−1, which indicates its dominant cause of the future D’s uncertainty. In addition, the interannual variability of D caused by the annual changes in the ice velocity and ice thickness are considerable compared with the target uncertainty of 15 Gt yr−1, which cannot be ignored in annual MB estimations.

Trade Openness and Green Total Factor Productivity in China: The Role of ICT-Based Digital Trade

The vigorous development of modern information and communication technology (ICT) has driven the digital trade featured by the ICT technique and industry as the carrier. This study empirically tests the impact of ICT-based digital trade openness on green total factor productivity (GTFP) by selecting ICT as the representative digital trade data of 30 provinces in China over the timespan 2002–2018. We employ the slack-based model and global Malmquist–Luenberger (SBM-GML) estimation method to calculate the provincial GTFP and explore the heterogeneous impact of digital trade openness on GTFP through the scale effect, technology effect, and structure effect. In terms of empirical results, the panel fixed model and panel quantile estimation model both suggest the same findings. With the continuous expansion of the scale of digital trade, its scale effect has a significant inhibitory effect on GTFP, whereas the structure effect combined with human capital and the technology effect correlated with technological research and development (R&D) have a significant promoting effect on GTFP. The panel quantile regression model reveals that the interaction intensity increases gradually from a low quantile to high quantile. Further robustness tests also verify the consistency and stability of the results. Finally, the study puts forward corresponding practical suggestions for the construction of a high-quality open pattern of digital trade and the coordinated development of GTFP. The specific policy implications include the following: (1) Emphasize on the penetration and connection effect of the new generation of ICT, and strengthen the construction of enterprise informatization. (2) Expand digital trade openness and broaden the field of industrial cooperation. (3) Optimize the industrial structure of digital trade, and accelerate the development of core industries of digital trade. (4) Gradually promote the transformation of digital trade from relying on quantity and scale to product quality.