Expansive clayey soils at the subgrade level of roads and highways in different cities can affect the performance and durability of pavements. This increases the need for maintenance and conservation work, leading to higher operating costs. Traditionally, clayey soils are stabilised by adding lime or cement. However, the handling and use of these materials are restricted in some Latin American countries due to illegal drug production, and obtaining high-quality materials from distant sources can be impractical. The goal of this study is to determine the effectiveness of incorporating fibres in improving the performance of expansive clayey subgrade soils. To achieve this goal, resilient modulus tests and measurements of compacted soil expansion were performed. Two types of fibres were selected for this study: natural Ichu fibre, which is common in the Peruvian Andes, and polypropylene fib...

An accurate land-cover segmentation of very-high-resolution aerial images is essential for a wide range of applications, including urban planning and natural resource management. However, the automation of this process remains a challenge owing to the complexity of images, variability in land surface features, and noise. In this study, a method for training convolutional neural networks and transformers to perform land-cover segmentation on very-high-resolution aerial images in a regional context was proposed. We assessed the U-Net-scSE, FT-U-NetFormer, and DC-Swin architectures, incorporating transfer learning and active contour loss functions to improve performance on semantic segmentation tasks. Our experiments conducted using the OpenEarthMap dataset, which includes images from 44 countries, demonstrate the superior performance of U-Net-scSE models with the EfficientNet-V2-XL and MiT...