Publications by authors named "M E Larcher"

Article Synopsis
  • Climate data is essential for managing water resources and is utilized in various hydrological analyses beyond just climate change studies.
  • Though climate models are becoming more accurate over time, their outputs often require adjustments to be applicable for local contexts.
  • This study evaluates various statistical and machine learning methods for bias correction of climate data at different time scales, revealing distinct performance trends for correcting precipitation and temperature data.
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Medulloblastoma (MB) is the most prevalent brain cancer in children. Four subgroups of MB have been identified; of these, Group 3 is the most metastatic. Its genetics and biology remain less clear than the other groups, and it has a poor prognosis and few effective treatments available.

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We study the (1:s+1) success rule for controlling the population size of the (1,λ)- EA. It was shown by Hevia Fajardo and Sudholt that this parameter control mechanism can run into problems for large s if the fitness landscape is too easy. They conjectured that this problem is worst for the ONEMAX benchmark, since in some well-established sense ONEMAX is known to be the easiest fitness landscape.

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This data collection presents a comprehensive five-year monitoring record from a historic building located in Settequerce, South Tyrol (Italy). The 17th-century building, characterized by a stone masonry, was subject to a retrofit in 2017 that introduced a wood fiber insulation panel to the inner side of the building's walls. As part of the renovation process, a monitoring system was installed.

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The dataset provided in this paper refers to an experimental campaign conducted in Laboratory of Fluid Dynamics (LTDF) of the Free University of Bozen-Bolzano at NOI Techpark aiming to understand the movement of granular material in fluids of low viscosity and density exhibited in debris flows. One experimental test was performed consisting of 31 repetitions. In detail, a three-litre volume of granular material ( = 1.

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