AIMC Topic: Carbon

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How does the robot adoption promote carbon reduction?: spatial correlation and heterogeneity analysis.

Environmental science and pollution research international
Along with the continuous improvement of industrial intelligence, robots are widely used in various aspects of production and life, playing an essential role in achieving carbon reduction targets. However, the existing research on the carbon reductio...

Application of artificial intelligence in quantifying lung deposition dose of black carbon in people with exposure to ambient combustion particles.

Journal of exposure science & environmental epidemiology
BACKGROUND: Understanding lung deposition dose of black carbon is critical to fully reconcile epidemiological evidence of combustion particles induced health effects and inform the development of air quality metrics concerning black carbon. Macrophag...

Artificial intelligence, industrial structure optimization, and CO emissions.

Environmental science and pollution research international
The carbon-reducing effects of artificial intelligence (AI) will be a critical means of achieving carbon peak and carbon neutrality in China. However, in order to efficiently harness the power of AI, the relationship between AI and carbon reduction n...

Do industrial robots reduce carbon intensity? The role of natural resource rents and corruption control.

Environmental science and pollution research international
Although the research on the impact of robotics on carbon emissions is increasing, there are still relatively few studies on the impact of robots on carbon intensity from the perspective of natural resources and corruption. In order to fill in the re...

Optimization of biogas production from straw wastes by different pretreatments: Progress, challenges, and prospects.

The Science of the total environment
Lignocellulosic biomass (LCB) presents a promising feedstock for carbon management due to enormous potential for achieving carbon neutrality and delivering substantial environmental and economic benefit. Bioenergy derived from LCB accounts for about ...

Deep learning-based fast denoising of Monte Carlo dose calculation in carbon ion radiotherapy.

Medical physics
BACKGROUND: Plan verification is one of the important steps of quality assurance (QA) in carbon ion radiotherapy. Conventional methods of plan verification are based on phantom measurement, which is labor-intensive and time-consuming. Although the pl...

Spatial differentiation of carbon emissions from energy consumption based on machine learning algorithm: A case study during 2015-2020 in Shaanxi, China.

Journal of environmental sciences (China)
Carbon emissions resulting from energy consumption have become a pressing issue for governments worldwide. Accurate estimation of carbon emissions using satellite remote sensing data has become a crucial research problem. Previous studies relied on s...

Self-removal of catheter after robot-assisted radical prostatectomy: a feasibility study.

Journal of robotic surgery
Self-removal of urinary catheter as an option after robot-assisted radical prostatectomy (RARP) has never been explored in literature. We report the feasibility and outcome of the first study of this novel concept in our hospital. We conducted a pros...

Spatiotemporal characteristics of carbon emissions in Shaanxi, China, during 2012-2019: a machine learning method with multiple variables.

Environmental science and pollution research international
Global warming attributed to the emission of greenhouse gases has caused unprecedented extreme weather events, such as excessive heatwave and rainfall, posing enormous threats to human life and sustainable development. China, as the toppest CO emitte...

Can the application of artificial intelligence in industry cut China's industrial carbon intensity?

Environmental science and pollution research international
As an emerging technology, industrial intelligence focus on the integration of artificial intelligence and production, which creates a new access to achieve the goal of carbon emissions reduction. Using data on provincial panel data from 2006 to 2019...