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Climate Change

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A hybrid machine-learning model to map glacier-related debris flow susceptibility along Gyirong Zangbo watershed under the changing climate.

The Science of the total environment
Gyirong serves as an important channel to Chine-Nepal Economic Corridor, which is also the only land route for China-Nepal trade since the 2015 earthquake. However, the Gyirong corridor suffers from glacier-related debris flow from every April to Sep...

Combining novel technologies with interdisciplinary basic research to enhance horticultural crops.

The Plant journal : for cell and molecular biology
Horticultural crops mainly include fruits, vegetables, ornamental trees and flowers, and tea trees (Melaleuca alternifolia). They produce a variety of nutrients for the daily human diet in addition to the nutrition provided by staple crops, and some ...

BERTtoCNN: Similarity-preserving enhanced knowledge distillation for stance detection.

PloS one
In recent years, text sentiment analysis has attracted wide attention, and promoted the rise and development of stance detection research. The purpose of stance detection is to determine the author's stance (favor or against) towards a specific targe...

Interpretable and explainable AI (XAI) model for spatial drought prediction.

The Science of the total environment
Accurate prediction of any type of natural hazard is a challenging task. Of all the various hazards, drought prediction is challenging as it lacks a universal definition and is getting adverse with climate change impacting drought events both spatial...

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

Drug discovery today
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...

Experimental support for genomic prediction of climate maladaptation using the machine learning approach Gradient Forests.

Molecular ecology resources
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 ...

Soft Robots for Ocean Exploration and Offshore Operations: A Perspective.

Soft robotics
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...

Inter-regional multimedia fate analysis of PAHs and potential risk assessment by integrating deep learning and climate change scenarios.

Journal of hazardous materials
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...

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)
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 ...

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
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...