AIMC Topic: Carbon

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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 Feb 19, 2024
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...
Cell Membrane Artificial Intelligence Carbon Blood Proteins Biological Transport
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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 Feb 15, 2024
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...
Neural Networks, Computer Deep Learning China Machine Learning Forecasting Carbon Models, Econometric
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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 Feb 6, 2024
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...
China Carbon Entropy Investments Forecasting Deep Learning
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Monitoring carbon emissions using deep learning and statistical process control: a strategy for impact assessment of governments' carbon reduction policies.

Environmental monitoring and assessment Feb 3, 2024
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 ...
Policy Deep Learning Humans Artificial Intelligence Air Pollutants Carbon Dioxide Government Environmental Monitoring Carbon
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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 Jan 23, 2024
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...
Industry China Carbon Forecasting Reproducibility of Results Deep Learning
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Municipal solid waste management for low-carbon transition: A systematic review of artificial neural network applications for trend prediction.

Environmental pollution (Barking, Essex : 1987) Jan 17, 2024
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...
Refuse Disposal Waste Management Greenhouse Gases Machine Learning Carbon Air Pollutants Solid Waste Neural Networks, Computer
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Taxonomy, biological characterization and fungicide sensitivity assays of Hypomyces cornea sp. nov. causing cobweb disease on Auricularia cornea.

Fungal biology Dec 31, 2023
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...
Hypocreales Agaricales Nitrogen Auricularia Carbon Cornea Fungicides, Industrial Phylogeny
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Waste-to-energy incineration site selection framework based on heterogeneous fuzzy regret-PROMETHEE model considering life-cycle carbon emissions.

Environmental science and pollution research international Dec 13, 2023
Waste incineration technology has received extensive attention for its advantages of being harmless, reducing, and recycling. However, the waste-to-energy incineration project confronts significant "not-in-my-backyard (NIMBY) concerns," and irrationa...
Carbon Decision Making Uncertainty Incineration Fuzzy Logic Emotions
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Toward a comprehensive understanding of alicyclic compounds: Bio-effects perspective and deep learning approach.

The Science of the total environment Nov 30, 2023
The escalating use of alicyclic compounds in modern industrial production has led to a rapid increase of these substances in the environment, posing significant health hazards. Addressing this challenge necessitates a comprehensive understanding of t...
Organic Chemicals Carbon Industry Neural Networks, Computer Deep Learning
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Emerging Directions for Carbon Capture Technologies: A Synergy of High-Throughput Theoretical Calculations and Machine Learning.

Environmental science & technology Nov 2, 2023
As the world grapples with the challenges of energy transition and industrial decarbonization, the development of carbon capture technologies presents a promising solution. The Scalable Modeling, Artificial Intelligence (AI), and Rapid Theoretical ca...
Carbon Industry Machine Learning Artificial Intelligence Technology
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