AIMC Topic: Environment

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Environmental adaptations in metagenomes revealed by deep learning.

BMC biology Aug 11, 2025
BACKGROUND: Deep learning has emerged as a powerful tool in the analysis of biological data, including the analysis of large metagenome data. However, its application remains limited due to high computational costs, model complexity, and difficulty e...
Adaptation, Physiological Environment Metagenome Deep Learning
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Machine learning models highlight environmental and genetic factors associated with the Arabidopsis circadian clock.

Nature communications Aug 5, 2025
The circadian clock of plants contributes to their survival and fitness. However, understanding clock function at the transcriptome level and its response to the environment requires assaying across high resolution time-course experiments. Generating...
Machine Learning Environment Gene Expression Regulation, Plant Arabidopsis Arabidopsis Proteins Gene Expression Profiling Circadian Rhythm Transcriptome Circadian Clocks
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Strategic forecasting of renewable energy production for sustainable electricity supply: A machine learning approach considering environmental, economic, and oil factors in Türkiye.

PloS one Aug 5, 2025
Providing electricity needs from renewable energy sources is an important issue in the energy policies of countries. Especially changes in energy usage rates make it necessary to use renewable energy resources to be sustainable. The electricity usage...
Electricity Environment Machine Learning Algorithms Forecasting Renewable Energy
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Considering the Social and Economic Sustainability of AI.

Science and engineering ethics Jul 24, 2025
In recent years, the notion of 'sustainable AI' has emerged as a new topic within the wider debate on artificial intelligence (AI). Although sustainability is usually understood as having three dimensions - the environment, society, and the economy -...
Environment Sustainable Development Conservation of Natural Resources Artificial Intelligence Economics Humans
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Optimization of a multi-environmental detection model for tomato growth point buds based on multi-strategy improved YOLOv8.

Scientific reports Jul 16, 2025
Tomato growing points and flower buds serve as vital physiological indicators influencing yield quality, yet their detection remains challenging in complex facility environments. This study develops an improved YOLOv8 model for robust flower bud dete...
Flowers Environment Agriculture Algorithms Solanum lycopersicum
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Pollen morphology, deep learning, phylogenetics, and the evolution of environmental adaptations in Podocarpus.

The New phytologist Jun 3, 2025
Podocarpus pollen morphology is shaped by both phylogenetic history and the environment. We analyzed the relationship between pollen traits quantified using deep learning and environmental factors within a comparative phylogenetic framework. We inves...
Pollen Fossils Environment Biological Evolution Phylogeny Deep Learning Altitude Adaptation, Physiological Temperature
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Egocentric value maps of the near-body environment.

Nature neuroscience Jun 2, 2025
Body-part-centered response fields are pervasive in single neurons, functional magnetic resonance imaging, electroencephalography and behavior, but there is no unifying formal explanation of their origins and role. In the present study, we used reinf...
Brain Mapping Reward Space Perception Reinforcement, Psychology Humans Environment Neural Networks, Computer Magnetic Resonance Imaging Personal Space Animals Models, Neurological Male
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Use of robotics in broiler production systems: a relationship between technology, environment and production.

Tropical animal health and production Mar 29, 2025
In poultry farming, robotics is represented by robotic models which perform different functions. Among these functions, ambience is one of the most critical, as the aviary is an artificial environment which needs to present all the necessary conditio...
Housing, Animal Environment Chickens Animals Robotics Animal Husbandry
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Leveraging Automated Machine Learning for Environmental Data-Driven Genetic Analysis and Genomic Prediction in Maize Hybrids.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Mar 6, 2025
Genotype, environment, and genotype-by-environment (G×E) interactions play a critical role in shaping crop phenotypes. Here, a large-scale, multi-environment hybrid maize dataset is used to construct and validate an automated machine learning framewo...
Genotype Zea mays Gene-Environment Interaction Genome-Wide Association Study Machine Learning Environment Genomics Phenotype Genome, Plant
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A systematic review of plastic recycling: technology, environmental impact and economic evaluation.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA Jan 18, 2025
In this systematic review, advancements in plastic recycling technologies, including mechanical, thermolysis, chemical and biological methods, are examined. Comparisons among recycling technologies have identified current research trends, including a...
Waste Management Environment Plastics Recycling
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