Numerous studies have revealed that artificial light at night alters the natural patterns of light in space and time and may have various ecological impacts at different ecological levels. However, only a few studies have assessed its effect on interactions between organisms in aquatic environments, including predator-prey interactions in lakes. To fill this gap, we performed a preliminary enclosure experiment in which we compared the foraging effect of juvenile perch () on a natural lake zooplankton community in the absence and presence of light of high-pressure sodium (HPS) lamps mimicking artificial light emitted by a boat. The results revealed that even short-lasting exposure to HPS lamps may result in increasing fish predation, which in turn decreased the mean body size in zooplankton populations (e.g. ) and affected the relative proportion between different taxa in zooplankton communities.
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http://dx.doi.org/10.1093/plankt/fbac046 | DOI Listing |
PLoS One
January 2025
Renewable Energy Science and Engineering Department, Faculty of Postgraduate Studies for Advanced Sciences (PSAS), Beni-Suef University, Beni-Suef, Egypt.
This study presents a comprehensive comparative analysis of Machine Learning (ML) and Deep Learning (DL) models for predicting Wind Turbine (WT) power output based on environmental variables such as temperature, humidity, wind speed, and wind direction. Along with Artificial Neural Network (ANN), Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), and Convolutional Neural Network (CNN), the following ML models were looked at: Linear Regression (LR), Support Vector Regressor (SVR), Random Forest (RF), Extra Trees (ET), Adaptive Boosting (AdaBoost), Categorical Boosting (CatBoost), Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM). Using a dataset of 40,000 observations, the models were assessed based on R-squared, Mean Absolute Error (MAE), and Root Mean Square Error (RMSE).
View Article and Find Full Text PDFJ Xenobiot
January 2025
Department of Physics, Novosibirsk State University, 630090 Novosibirsk, Russia.
Engineered light-sensitive molecules offer a sophisticated toolkit for the manipulation of biological systems with both spatial and temporal precision. Notably, artificial "caged" compounds can activate specific receptors solely in response to light exposure. However, the uncaging process can lead to the formation of potentially harmful byproducts.
View Article and Find Full Text PDFFront Plant Sci
January 2025
Department of Computer Science and Engineering, Indian Institute of Information Technology Design and Manufacturing (III TDM), Kurnool, Andhrapradesh, India.
Climate change poses significant challenges to global food security by altering precipitation patterns and increasing the frequency of extreme weather events such as droughts, heatwaves, and floods. These phenomena directly affect agricultural productivity, leading to lower crop yields and economic losses for farmers. This study leverages Artificial Intelligence (AI) and Explainable Artificial Intelligence (XAI) techniques to predict crop yields and assess the impacts of climate change on agriculture, providing a novel approach to understanding complex interactions between climatic and agronomic factors.
View Article and Find Full Text PDFFree Neuropathol
January 2024
Friedman Brain Institute, Departments of Pathology, Neuroscience, and Artificial Intelligence & Human Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Cryopreservation, the preservation of tissues at subzero temperatures, is a mainstay of brain banking that allows for the storage of brain tissue without the use of chemical fixatives. This is particularly important for molecular studies that are incompatible with tissue fixation. However, brain tissue is vulnerable to various forms of damage during the cryopreservation process, in particular due to the phase transition of water from a liquid to a solid state with the formation of ice crystals, which can disrupt cellular morphology.
View Article and Find Full Text PDFRadiologie (Heidelb)
January 2025
Universitätsklinikum Erlangen, Frauenklinik, Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Friedrich-Alexander-Universität Erlangen-Nürnberg, Universitätsstraße 21-23, 91054, Erlangen, Deutschland.
Background: The concept of personalized medicine is becoming increasingly important. The possibilities of diagnostics include not only genetic and molecular tumor profiles, but also the use of precise and individual imaging techniques.
Objectives: The development and implementation of suitable diagnostic procedures with high sensitivity and specificity, which are at the same time tailored to the individual risk factors and biological characteristics of the patient, remain a challenge.
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