AIMC Topic: Carbon

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Machine Learning Tools to Assist the Synthesis of Antibacterial Carbon Dots.

International journal of nanomedicine
INTRODUCTION: The emergence and rapid spread of multidrug-resistant bacteria (MRB) caused by the excessive use of antibiotics and the development of biofilms have been a growing threat to global public health. Nanoparticles as substitutes for antibio...

Carbon-based molecular properties efficiently predicted by deep learning-based quantum chemical simulation with large language models.

Computers in biology and medicine
The prediction of thermodynamic properties of carbon-based molecules based on their geometrical conformation using fluctuation and density functional theories has achieved great success in the field of energy chemistry, while the excessive computatio...

Paper-based fluorescence sensor array with functionalized carbon quantum dots for bacterial discrimination using a machine learning algorithm.

Analytical and bioanalytical chemistry
The rapid discrimination of bacteria is currently an emerging trend in the fields of food safety, medical detection, and environmental observation. Traditional methods often require lengthy culturing processes, specialized analytical equipment, and b...

Machine learning-assisted chromium speciation using a single-well ratiometric fluorescent nanoprobe.

Chemosphere
Chromium is widely recognized as a significant pollutant discharged into the environment by various industrial activities. The toxicity of this element is dependent on its oxidation state, making speciation analysis crucial for monitoring the quality...

Exploring optical descriptors for rapid estimation of coastal sediment organic carbon and nearby land-use classifications via machine learning models.

Marine pollution bulletin
This study utilizes ultraviolet and fluorescence spectroscopic indices of dissolved organic matter (DOM) from sediments, combined with machine learning (ML) models, to develop an optimized predictive model for estimating sediment total organic carbon...

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...