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Carbon

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Learning vs. understanding: When does artificial intelligence outperform process-based modeling in soil organic carbon prediction?

New biotechnology
In recent years, machine learning (ML) algorithms have gained substantial recognition for ecological modeling across various temporal and spatial scales. However, little evaluation has been conducted for the prediction of soil organic carbon (SOC) on...

Comparison of sexual function after robot-assisted radical prostatectomy and carbon-ion radiotherapy for Japanese prostate cancer patients using propensity score matching.

BMC cancer
BACKGROUND: The quality of life of patients is an important consideration when selecting treatments for localized prostate cancer (PCa). We retrospectively compared sexual function after robot-assisted radical prostatectomy (RARP) and carbon-ion radi...

Ocean carbon emission prediction and management measures based on artificial intelligence remote sensing estimation in the context of carbon neutrality.

Environmental research
With rapid economic development, the gradual deterioration of the natural environment has posed unprecedented challenges to human social civilization. The marine economy, as an important part of economic development, is the breakthrough of economic t...

Nanoinformatics based insights into the interaction of blood plasma proteins with carbon based nanomaterials: Implications for biomedical applications.

Advances in protein chemistry and structural biology
In the past three decades, interest in using carbon-based nanomaterials (CBNs) in biomedical application has witnessed remarkable growth. Despite the rapid advancement, the translation of laboratory experimentation to clinical applications of nanomat...

Which model is more efficient in carbon emission prediction research? A comparative study of deep learning models, machine learning models, and econometric models.

Environmental science and pollution research international
Accurately predicting future carbon emissions is of great significance for the government to scientifically promote carbon emission reduction policies. Among the current technologies for forecasting carbon emissions, the most prominent ones are econo...

Forecasting China carbon price using an error-corrected secondary decomposition hybrid model integrated fuzzy dispersion entropy and deep learning paradigm.

Environmental science and pollution research international
Forecasting China's carbon price accurately can encourage investors and manufacturing industries to take quantitative investments and emission reduction decisions effectively. The inspiration for this paper is developing an error-corrected carbon pri...

Monitoring carbon emissions using deep learning and statistical process control: a strategy for impact assessment of governments' carbon reduction policies.

Environmental monitoring and assessment
Across the globe, governments are developing policies and strategies to reduce carbon emissions to address climate change. Monitoring the impact of governments' carbon reduction policies can significantly enhance our ability to combat climate change ...

A CNN-LSTM based deep learning model with high accuracy and robustness for carbon price forecasting: A case of Shenzhen's carbon market in China.

Journal of environmental management
Accurately predicting carbon trading prices using deep learning models can help enterprises understand the operational mechanisms and regulations of the carbon market. This is crucial for expanding the industries covered by the carbon market and ensu...

Municipal solid waste management for low-carbon transition: A systematic review of artificial neural network applications for trend prediction.

Environmental pollution (Barking, Essex : 1987)
Improper municipal solid waste (MSW) management contributes to greenhouse gas emissions, necessitating emissions reduction strategies such as waste reduction, recycling, and composting to move towards a more sustainable, low-carbon future. Machine le...

Taxonomy, biological characterization and fungicide sensitivity assays of Hypomyces cornea sp. nov. causing cobweb disease on Auricularia cornea.

Fungal biology
Auricularia cornea is an important edible mushroom crop in China but the occurrence of cobweb disease has cause significance economic loss in its production. The rate of disease occurrence is 16.65% all over the country. In the present study, a new p...