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  1. Free, publicly-accessible full text available April 4, 2024
  2. Free, publicly-accessible full text available April 4, 2024
  3. In this article the recent developments of the open-source OpenMolcas chemistry software environment, since spring 2020, are described, with the main focus on novel functionalities that are accessible in the stable branch of the package and/or via interfaces with other packages. These community developments span a wide range of topics in computational chemistry, and are presented in thematic sections associated with electronic structure theory, electronic spectroscopy simulations, analytic gradients and molecular structure optimizations, ab initio molecular dynamics, and other new features. This report represents a useful summary of these developments, and it offers a solid overview of the chemical phenomena and processes that OpenMolcas can address, while showing that OpenMolcas is an attractive platform for state-of-the-art atomistic computer simulations. 
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    Free, publicly-accessible full text available July 1, 2024
  4. Water plays a critical role in our living and manufacturing activities. The continuously growing exploitation of water over the aquifer poses a risk for over-extraction and pollution, leading to many negative effects on land irrigation. Therefore, predicting aquifer water levels accurately is urgently important, which can help us prepare water demands ahead of time. In this study, we employ the Long-Short Term Memory (LSTM) model to predict the saturated thickness of an aquifer in the Southern High Plains Aquifer System in Texas and exploit TensorBoard as a guide for model configurations. The Root Mean Squared Error of this study shows that the LSTM model can provide a good prediction capability using multiple data sources, and provides a good visualization tool to help us understand and evaluate the model configuration. 
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  5. Loess covers large areas around the earth. Loess deposits are typically composed of silt with clay and fine sand particles and it is usually distributed with a few meters thick. Literature review shows that, the thermal conductivity of loess varies in a relatively large range from 0.2 to 2 W/(mK), depending on the particle composition, texture and moisture content of soil. In this study, loess samples were taken at shallow depth from the Northern France. Suction, volumetric moisture content and thermal conductivity of soil were measured simultaneously while wetting/drying cycles were applied to the sample. The results show that, the degree of saturation significantly affects the thermal conductivity of the soil. The relationship between these two parameters is reversible under wetting/drying cycles while hysteresis can be observed while plotting the thermal conductivity versus suction. 
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  6. Free, publicly-accessible full text available November 1, 2024
  7. Free, publicly-accessible full text available November 1, 2024