Search Results - "Meyer, Hanna"
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Machine learning-based global maps of ecological variables and the challenge of assessing them
Published in Nature communications (22-04-2022)“…The recent wave of published global maps of ecological variables has caused as much excitement as it has received criticism. Here we look into the data and…”
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Soil respiration and its temperature sensitivity (Q10): Rapid acquisition using mid-infrared spectroscopy
Published in Geoderma (01-08-2018)“…Spatial patterns of soil respiration (SR) and its sensitivity to temperature (Q10) are one of the key uncertainties in climate change research but since their…”
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Hyperspectral Data Analysis in R : The hsdar Package
Published in Journal of statistical software (01-05-2019)“…Hyperspectral remote sensing is a promising tool for a variety of applications including ecology, geology, analytical chemistry and medical research. This…”
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High-resolution soil temperature and soil moisture patterns in space, depth and time: An interpretable machine learning modelling approach
Published in Geoderma (01-11-2024)“…Soil temperature and soil moisture are key drivers of various soil ecological processes, which implies a significant importance of datasets including their…”
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Using GEDI as training data for an ongoing mapping of landscape-scale dynamics of the plant area index
Published in Environmental research letters (01-07-2023)“…Abstract Leaf or plant area index (LAI, PAI) information is frequently used to describe vegetation structure in environmental science. While field measurements…”
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A Machine Learning Based Downscaling Approach to Produce High Spatio-Temporal Resolution Land Surface Temperature of the Antarctic Dry Valleys from MODIS Data
Published in Remote sensing (Basel, Switzerland) (01-11-2021)“…To monitor environmental and biological processes, Land Surface Temperature (LST) is a central variable, which is highly variable in space and time. This…”
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Antarctic daily mesoscale air temperature dataset derived from MODIS land and ice surface temperature
Published in Scientific data (27-11-2023)“…Knowledge about local air temperature variations and extremes in Antarctica is of large interest to many polar disciplines such as climatology, glaciology,…”
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Mapping Daily Air Temperature for Antarctica Based on MODIS LST
Published in Remote sensing (Basel, Switzerland) (01-09-2016)“…Spatial predictions of near-surface air temperature ( T a i r ) in Antarctica are required as baseline information for a variety of research disciplines. Since…”
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Unbiased Area Estimation Using Copernicus High Resolution Layers and Reference Data
Published in Remote sensing (Basel, Switzerland) (01-10-2022)“…Land cover area estimates can be derived via design-based approaches using a probability (random) reference sample. The collection of samples is usually costly…”
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Novel Class of Potent and Cellularly Active Inhibitors Devalidates MTH1 as Broad-Spectrum Cancer Target
Published in ACS chemical biology (18-08-2017)“…MTH1 is a hydrolase responsible for sanitization of oxidized purine nucleoside triphosphates to prevent their incorporation into replicating DNA. Early tool…”
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Stress responses of the industrial workhorse Bacillus licheniformis to osmotic challenges
Published in PloS one (15-11-2013)“…The Gram-positive endospore-forming bacterium Bacillus licheniformis can be found widely in nature and it is exploited in industrial processes for the…”
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Predicting into unknown space? Estimating the area of applicability of spatial prediction models
Published in Methods in ecology and evolution (01-09-2021)“…Machine learning algorithms have become very popular for spatial mapping of the environment due to their ability to fit nonlinear and complex relationships…”
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13
Identification of Small Molecules that Modulate Mutant p53 Condensation
Published in iScience (25-09-2020)“…Structural mutants of p53 induce global p53 protein destabilization and misfolding, followed by p53 protein aggregation. First evidence indicates that p53 can…”
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High Throughput FISH Screening Identifies Small Molecules That Modulate Oncogenic lncRNA MALAT1 via GSK3B and hnRNPs
Published in Non-coding RNA (03-01-2023)“…Traditionally, small molecule-based drug discovery has mainly focused on proteins as the drug target. Opening RNA as an additional target space for small…”
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A time resolved metabolomics study: the influence of different carbon sources during growth and starvation of Bacillus subtilis
Published in Molecular bioSystems (01-01-2014)“…In its natural environment, the soil, the Gram-positive model bacterium Bacillus subtilis frequently encounters nutrient limitation and other stress factors…”
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Biomechanical Properties of a Novel Biodegradable Magnesium-Based Interference Screw
Published in Orthopedic Reviews (27-06-2016)“…Magnesium-based interference screws may be an alternative in anterior/posterior cruciate ligament reconstruction. The well-known osteoconductive effects of…”
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Importance of spatial predictor variable selection in machine learning applications – Moving from data reproduction to spatial prediction
Published in Ecological modelling (01-11-2019)“…[Display omitted] •Spatial cross-validation is crucial for reliable error estimates of predictions.•Geolocation as predictor variable can lead to overfitting…”
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Improving performance of spatio-temporal machine learning models using forward feature selection and target-oriented validation
Published in Environmental modelling & software : with environment data news (01-03-2018)“…Importance of target-oriented validation strategies for spatio-temporal prediction models is illustrated using two case studies: (1) modelling of air…”
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Nearest neighbour distance matching Leave‐One‐Out Cross‐Validation for map validation
Published in Methods in ecology and evolution (01-06-2022)“…Several spatial and non‐spatial Cross‐Validation (CV) methods have been used to perform map validation when additional sampling for validation purposes is not…”
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Comparison of four machine learning algorithms for their applicability in satellite-based optical rainfall retrievals
Published in Atmospheric research (01-03-2016)“…Machine learning (ML) algorithms have successfully been demonstrated to be valuable tools in satellite-based rainfall retrievals which show the practicability…”
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