AIMC Topic: Carbon
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Application of nano-carbon and titanium clip combined labeling in robot-assisted laparoscopic transverse colon cancer surgery.
BMC surgery
May 24, 2021
BACKGROUND: Robot-assisted laparoscopic transverse colon tumor surgery requires precise tumor localization. The purpose of this study was to evaluate the safety and efficacy of nano-carbon and titanium clip combination labeling methods in robot-assis...
Prediction of direct carbon emissions of Chinese provinces using artificial neural networks.
PloS one
May 13, 2021
Closely connected to human carbon emissions, global climate change is affecting regional economic and social development, natural ecological environment, food security, water supply, and many other social aspects. In a word, climate change has become...
Machine-Learning-Based Approach to Decode the Influence of Nanomaterial Properties on Their Interaction with Cells.
ACS applied materials & interfaces
Dec 29, 2020
In an nanotoxicity system, cell-nanoparticle (NP) interaction leads to the surface adsorption, uptake, and changes into nuclei/cell phenotype and chemistry, as an indicator of oxidative stress, genotoxicity, and carcinogenicity. Different types of n...
Intuitionistic Fuzzy Hierarchical Multi-Criteria Decision Making for Evaluating Performances of Low-Carbon Tourism Scenic Spots.
International journal of environmental research and public health
Aug 28, 2020
Low-carbon tourism is an effective solution to cope with the goal conflict between developing tourist economy and responding to carbon emission reduction and ecological environment protection. Tourism scenic spots are important carriers of tourist ac...
Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks.
Physical chemistry chemical physics : PCCP
Jun 1, 2020
Chemical representations derived from deep learning are emerging as a powerful tool in areas such as drug discovery and materials innovation. Currently, this methodology has three major limitations - the cost of representation generation, risk of inh...
Dose image prediction for range and width verifications from carbon ion-induced secondary electron bremsstrahlung x-rays using deep learning workflow.
Medical physics
May 25, 2020
PURPOSE: Imaging of the secondary electron bremsstrahlung (SEB) x rays emitted during particle-ion irradiation is a promising method for beam range estimation. However, the SEB x-ray images are not directly correlated to the dose images. In addition,...
The use of artificial neural network (ANN) for modeling adsorption of sunset yellow onto neodymium modified ordered mesoporous carbon.
Chemosphere
May 15, 2020
Discharging coloring products in water bodies has degraded water quality irreversibly over the past several decades. Order mesoporous carbon (OMC) was modified by embedding neodymium(III) chloride on the surface of OMC to enhance the adsorptive remov...
Microbial Decolorization of Triazo Dye, Direct Blue 71: An Optimization Approach Using Response Surface Methodology (RSM) and Artificial Neural Network (ANN).
BioMed research international
Feb 18, 2020
The release of wastewater from textile dyeing industrial sectors is a huge concern with regard to pollution as the treatment of these waters is truly a challenging process. Hence, this study investigates the triazo bond Direct Blue 71 (DB71) dye deco...
Biocompatible liquid-type carbon nanodots (C-paints) as light delivery materials for cell growth and astaxanthin induction of Haematococcus pluvialis.
Materials science & engineering. C, Materials for biological applications
Nov 28, 2019
In this study, we aimed to demonstrate the feasibility of the application of biocompatible liquid type fluorescent carbon nanodots (C-paints) to microalgae by improving microalgae productivity. C-paints were prepared by a simple process of ultrasound...
Machine Learning-Assisted Array-Based Biomolecular Sensing Using Surface-Functionalized Carbon Dots.
ACS sensors
Oct 11, 2019
Fluorescent array-based sensing is an emerging differential sensing platform for sensitive detection of analytes in a complex environment without involving a conventional "lock and key" type-specific interaction. These sensing techniques mainly rely ...
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