AIMC Topic: Copper
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Machine Learning Allowed Interpreting Toxicity of a Fe-Doped CuO NM Library Large Data Set─An Environmental In Vivo Case Study.
ACS applied materials & interfaces
Aug 1, 2024
The wide variation of nanomaterial (NM) characters (size, shape, and properties) and the related impacts on living organisms make it virtually impossible to assess their safety; the need for modeling has been urged for long. We here investigate the c...
Machine learning trained poly (3,4-ethylenedioxythiophene) functionalized carbon matrix suspended Cu nanoparticles for precise monitoring of nitrite from pickled vegetables.
Food chemistry
Jul 17, 2024
Precise monitoring of nitrite from real samples has gained significant attention due to its detrimental impact on human health. Herein, we have fabricated poly(3,4-ethylenedioxythiophene) functionalized carbon matrix suspended Cu nanoparticles (PEDOT...
Radiological characterization of the tailings of an abandoned copper mine using a neural network and geostatistical analysis through the Co-Kriging method.
Environmental geochemistry and health
Jul 9, 2024
The radiological characterization of soil contaminated with natural radionuclides enables the classification of the area under investigation, the optimization of laboratory measurements, and informed decision-making on potential site remediation. Neu...
Identification and validation of cuproptosis-related genes in acetaminophen-induced liver injury using bioinformatics analysis and machine learning.
Frontiers in immunology
Jun 27, 2024
BACKGROUND: Acetaminophen (APAP) is commonly used as an antipyretic analgesic. However, acetaminophen overdose may contribute to liver injury and even liver failure. Acetaminophen-induced liver injury (AILI) is closely related to mitochondrial oxidat...
Evaluation of a Voltametric E-Tongue Combined with Data Preprocessing for Fast and Effective Machine Learning-Based Classification of Tomato Purées by Cultivar.
Sensors (Basel, Switzerland)
Jun 2, 2024
The potential of a voltametric E-tongue coupled with a custom data pre-processing stage to improve the performance of machine learning techniques for rapid discrimination of tomato purées between cultivars of different economic value has been investi...
Machine-learning developed an iron, copper, and sulfur-metabolism associated signature predicts lung adenocarcinoma prognosis and therapy response.
Respiratory research
May 14, 2024
BACKGROUND: Previous studies have largely neglected the role of sulfur metabolism in LUAD, and no study has combine iron, copper, and sulfur-metabolism associated genes together to create prognostic signatures.
Prediction models for bioavailability of Cu and Zn during composting: Insights into machine learning.
Journal of hazardous materials
Apr 23, 2024
Bioavailability assessment of heavy metals in compost products is crucial for evaluating associated environmental risks. However, existing experimental methods are time-consuming and inefficient. The machine learning (ML) method has demonstrated exce...
Predictive modeling of copper (II) adsorption from aqueous solutions by sawdust: a comparative analysis of adaptive neuro-fuzzy interference system (ANFIS) and artificial neural network (ANN) approaches.
Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
Apr 12, 2024
Heavy metal ions are considered to be the most prevalent and toxic water contaminants. The objective of thois work was to investigate the effectiveness of employing the adsorption technique in a laboratory-size reactor to remove copper (II) ions from...
Fast real-time monitoring of meat freshness based on fluorescent sensing array and deep learning: From development to deployment.
Food chemistry
Mar 21, 2024
A fluorescent sensor array (FSA) combined with deep learning (DL) techniques was developed for meat freshness real-time monitoring from development to deployment. The array was made up of copper metal nanoclusters (CuNCs) and fluorescent dyes, having...
Mn-Triggered Swing-Arm Robot Strategy Using Anemone-Like Thi@AuPd@Cu-MOFs as Signaling Probes for the Detection of T-2 Toxin.
Analytical chemistry
Dec 18, 2023
Herein, we synthesized anemone-like copper-based metal-organic frameworks (MOFs) loaded with gold-palladium nanoparticles (AuPd@Cu-MOFs) and polyethylenimine-reduced graphene oxide/gold-silver nanosheet composites (PEI-rGO/AuAg NSs) for the first tim...
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