AIMC Topic: Climate Change

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Converging global crises are forcing the rapid adoption of disruptive changes in drug discovery.

Drug discovery today May 18, 2021
Spiralling research costs combined with urgent pressures from the Coronavirus 2019 (COVID-19) pandemic and the consequences of climate disruption are forcing changes in drug discovery. Increasing the predictive power of in vitro human assays and usin...
In Vitro Techniques Humans Data Accuracy Climate Change Machine Learning SARS-CoV-2 COVID-19 Physical Distancing Drug Discovery Artificial Intelligence Disruptive Technology Automation Carbon Footprint Cooperative Behavior
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Experimental support for genomic prediction of climate maladaptation using the machine learning approach Gradient Forests.

Molecular ecology resources Mar 22, 2021
Gradient Forests (GF) is a machine learning algorithm that is gaining in popularity for studying the environmental drivers of genomic variation and for incorporating genomic information into climate change impact assessments. Here we (i) provide the ...
Humans Machine Learning Adaptation, Physiological Climate Change Genomics Genome Polymorphism, Single Nucleotide
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Soft Robots for Ocean Exploration and Offshore Operations: A Perspective.

Soft robotics Jan 15, 2021
The ocean and human activities related to the sea are under increasing pressure due to climate change, widespread pollution, and growth of the offshore energy sector. Data, in under-sampled regions of the ocean and in the offshore patches where the i...
Technology Robotics Humans Oceans and Seas Climate Change Oceanography
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Inter-regional multimedia fate analysis of PAHs and potential risk assessment by integrating deep learning and climate change scenarios.

Journal of hazardous materials Jan 15, 2021
Polycyclic aromatic hydrocarbons (PAHs) are hazardous compounds associated with respiratory disease and lung cancer. Increasing fossil fuel consumption, which causes climate change, has accelerated the emissions of PAHs. However, potential risks by P...
Multimedia Deep Learning China Polycyclic Aromatic Hydrocarbons Climate Change Environmental Monitoring Republic of Korea Risk Assessment
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Analysis of Copernicus' ERA5 Climate Reanalysis Data as a Replacement for Weather Station Temperature Measurements in Machine Learning Models for Olive Phenology Phase Prediction.

Sensors (Basel, Switzerland) Nov 9, 2020
Knowledge of phenological events and their variability can help to determine final yield, plan management approach, tackle climate change, and model crop development. THe timing of phenological stages and phases is known to be highly correlated with ...
Machine Learning Temperature Climate Change Seasons Italy Weather Olea
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Improving area of occupancy estimates for parapatric species using distribution models and support vector machines.

Ecological applications : a publication of the Ecological Society of America Nov 4, 2020
As geographic range estimates for the IUCN Red List guide conservation actions, accuracy and ecological realism are crucial. IUCN's extent of occurrence (EOO) is the general region including the species' range, while area of occupancy (AOO) is the su...
Climate Change Climate Animals Mice Support Vector Machine Ecosystem
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The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems.

Current opinion in biotechnology Oct 7, 2020
Modern agriculture and food production systems are facing increasing pressures from climate change, land and water availability, and, more recently, a pandemic. These factors are threatening the environmental and economic sustainability of current an...
Remote Sensing Technology Climate Change Food Supply Artificial Intelligence Agriculture Humans
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Finding the de-carbonization potentials in the transport sector: application of scenario analysis with a hybrid prediction model.

Environmental science and pollution research international Apr 11, 2020
De-carbonization of the transport sector is an important pathway to climate-change mitigation and presents the potential for future lower emissions. To assess the potential quantitatively under different optimization measures, this paper presents a h...
Climate Change Algorithms Forecasting Neural Networks, Computer Support Vector Machine
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A deep learning approach to conflating heterogeneous geospatial data for corn yield estimation: A case study of the US Corn Belt at the county level.

Global change biology Dec 2, 2019
Understanding large-scale crop growth and its responses to climate change are critical for yield estimation and prediction, especially under the increased frequency of extreme climate and weather events. County-level corn phenology varies spatially a...
Zea mays Seasons Neural Networks, Computer Climate Change Deep Learning
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The effect of climate change on cholera disease: The road ahead using artificial neural network.

PloS one Nov 6, 2019
Climate change has been described to raise outbreaks of water-born infectious diseases and increases public health concerns. This study aimed at finding out these impacts on cholera infections by using Artificial Neural Networks (ANNs) from 2021 to 2...
Seasons Computer Simulation Geography Humans Iran Cholera Climate Change Time Factors Neural Networks, Computer
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