A new theoretical and experimental framework that permits an accurate determination of aggregate-size stability distribution is presented. The size-stability distribution in addition to estimating aggregate-size distribution distinguishes between amounts of stable and unstable macroaggregates (>250 μm). The determination of aggregate-size stability distribution involves the assumptions that soil aggregates can be categorized in terms of their size and water stability (slaking resistance). Experimentally this procedure involves the slaked and capillary-wetted pretreatments; and a subsequent slaking treatment of aggregates >250 μm in size. We also propose the stable aggregates index (SAI) and the stable macroaggregates index (SMaI) for studying soil stability based on aggregate resistance to slaking. These indices account for the total weighted average of stable aggregates and the total weighted average of stable macroaggregates, respectively. Both the SAI and the SMaI indices were shown to be sensitive to the effects of vegetation on soil stability under different riparian buffer communities. The SAI and the SMaI indices were higher in surface soils under coolseason grass than any of the other treatments. These soils samples are well aggregated with SAI = 74% and SMaI = 56% followed by SAI = 55% and SMaI = 37% under existing riparian forest, SAI = 40% and SMaI = 21% under 7-yr switchgrass and SAI = 36% and SMaI = 18% under cropped system. (Kemper and Rosenau, 1986). Several studies have used capillary-wetted and slaked pretreatments (Elliott, 1986; A new theoretical and experimental framework that permits an ABSTRACT

Abstract:We presented a methodology to accurately classify mountainous regions in the tropics. These landscapes are complex in terms of their geology, ecosystems, climate and land use. Obtaining accurate maps to assess land cover change is essential. The objectives of this study were to (1) map vegetation using the Random Forest Classifier (RFC), spectral vegetation index (SVI), and ancillar geographic data (2) identify important variables that help differentiate vegetation cover, and (3) assess the accuracy of the vegetation cover classification in hard-to-reach Ecuadorian mountain region. We used Landsat 7 ETM+ satellite images of the entire scene, a RFC algorithm, and stratified random sampling. The altitude and the two band enhanced vegetation index (EVI2) provide more information on vegetation cover than the traditional and often use normalized difference vegetation index (NDVI) in other settings. We classified the vegetation cover of mountainous areas within the 1016 km 2 area of study, at 30 m spatial resolution, using RFC that yielded a land cover map with an overall accuracy of 95%. The user's accuracy and the half-width of the confidence interval for 95% of the basic map units, forest (FOR), páramo (PAR), crop (CRO) and pasture (PAS) were 95.85% ± 2.86%, 97.64% ± 1.24%, 91.53% ± 3.35% and 82.82% ± 7.74%, respectively. The overall disagreement was 4.47%, which results from adding 0.43% of quantity disagreement and 4.04% of allocation disagreement. The methodological framework presented in this paper and the combined use of SVIs, ancillary geographic data, and the RFC allowed the accurate mapping of hard-to-reach mountain landscapes as well as uncovering the underlying factors that help differentiate vegetation cover in the Ecuadorian mountain geosystem.

The objective of this work was finding out the most advisable testing conditions for an effective and robust characterization of the tensile strength (TS) of concrete disks. The independent variables were the loading geometry, the angle subtended by the contact area, disk diameter and thickness, maximum aggregate size, and the sample compression strength (CS). The effect of the independent variables was studied in a three groups of experiments using a factorial design with two levels and four factors. The likeliest location where failure beginning was calculated using the equations that account for the stress-strain field developed within the disk. The theoretical outcome shows that for failure beginning at the geometric center of the sample, it is necessary for the contact angle in the loading setup to be larger than or equal to a threshold value. Nevertheless, the measured indirect tensile strength must be adjusted to get a close estimate of the uniaxial TS of the material. The correction depends on the loading geometry, and we got their mathematical expression and cross-validated them with the reported in the literature. The experimental results show that a loading geometry with a curved contact area, uniform load distribution over the contact area, loads projected parallel to one another within the disk, and a contact angle bigger of 12°is the most advisable and robust setup for implementation of BT on concrete disks. This work provides a description of the BT carries on concrete disks and put forward a characterization technique to study costly samples of cement based material that have been enabled to display new and improved properties with nanomaterials.