Mendeley Data Showcase

This dataset compiles bibliographic information from peer-reviewed studies applying the Revised Universal Soil Loss Equation (RUSLE) and its parameters (R, K, LS, C, and P), along with the Sediment Delivery Ratio (SDR), for soil erosion and sediment yield estimation.

manuscript data

The core hypothesis of this study was that short-term biochar amendment would, contrary to its long-term benefits, exacerbate rill erosion risk in loess soils by increasing soil detachment capacity (Dc) and rill erodibility (Kr), with this effect being significantly modulated by soil texture.To test this hypothesis, a dataset was established through flume experiments and soil physicochemical analyses. The first part comprises raw data from flume scour experiments. The experiments were conducted in a recirculating flume under controlled hydrodynamic conditions, combining two slope gradients (15° and 25°) with three flow discharge rates (12, 24, and 36 L min⁻¹). All experimental runs were performed following a 2-week incubation period after biochar application, during which both amended and control soils were maintained under identical open-air conditions. A total of 240 experimental runs were performed, covering five loess soils of distinct textures (from Yangling, Changwu, Ansai, Dingbian, and Shenmu) each under two treatments: untreated control and amended with 3% corn straw biochar. For each run, primary data on hydraulic parameters (flow velocity, temperature) and erosion response (dry weight of collected sediment and corresponding scouring duration) were recorded directly. These primary measurements were then used to calculate key hydrodynamic stress indicators—including shear stress, stream power, and unit stream power—applying standard hydraulic formulas. The fundamental response variable, soil detachment capacity (Dc), was subsequently determined from these calculations. The second part is the supporting soil physicochemical property dataset. This component involves standardized laboratory analyses performed on all soil samples used in the flume experiments (both control and biochar-amended). This dataset is intended to elucidate the controlling mechanisms of intrinsic soil properties on the erosion process. The dataset clearly reveals several key findings. Firstly, the data directly demonstrates that short-term biochar amendment consistently and significantly increased soil detachment capacity (Dc) across all tested soil textures and hydrodynamic conditions, and generally raised rill erodibility (Kr). Secondly, data analysis indicates that the finest-textured clay loess was the most sensitive to this biochar-induced erosion exacerbation. Most critically, the data identifies soil organic carbon (SOC) as the dominant factor controlling Dc and Kr. Finally, the data confirms that stream power (ω) serves as the optimal hydrodynamic predictor for Dc. This foundation successfully supported the development of high-fidelity multivariate predictive models that integrate hydraulic forcing (stream power) with key soil attributes (e.g., SOC, MWD, porosity).

The geochemical data generated in the study entitled “Geochemical Analysis of Diachronous V-Shaped Ridges and Troughs Flanking the Reykjanes Ridge South of Iceland.”

This dataset has been used for TS-ABS in "A Two-Stage Adaptive Beam Search Algorithm for the Hybrid-Class Timetabling Problem".

The data of Zhisheng Zhang

SCB pretreatment with varying NaOH conc, Temp, and time (based on CCD) maps to solid recovery, delignification, and sugar yield from the treated biomass. The dataset was augmented with Gaussian noise, and three different ML models were developed for three responses. Multi-objective optimization was adopted using GA - the pareto optimal solution was screened based on TOPSIS method.

The data set describes two phase flow characterisation in L shaped pipe.

This dataset includes a total of 797 freshman preservice teachers' responses across 21 teacher education programs in different regions of Türkiye by employing non-random sampling approach. Data was collected with an online form given the widespread geographical location of 21 teacher education programs. (Respondents are 632 female, 158 male whereas seven participants chose not to disclose their gender). The average age for participants was 20,75 (SD=3,35).