AIMC Topic: Metals

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Anthropogenic activities impact on atmospheric environmental quality in a gas-flaring community: application of fuzzy logic modelling concept.

Environmental science and pollution research international
We present a modelling concept for evaluating the impacts of anthropogenic activities suspected to be from gas flaring on the quality of the atmosphere using domestic roof-harvested rainwater (DRHRW) as indicator. We analysed seven metals (Cu, Cd, Pb...

Antifungal activities against toxigenic Fusarium specie and deoxynivalenol adsorption capacity of ion-exchanged zeolites.

Journal of environmental science and health. Part. B, Pesticides, food contaminants, and agricultural wastes
Zeolites are often used as adsorbents materials and their loaded cations can be exchanged with metal ions in order to add antimicrobial properties. The aim of this study was to use the 4A zeolite and its derived ion-exchanged forms with Zn, Li, Cu an...

Evaluation of a peroxygen-based disinfectant for inactivation of porcine epidemic diarrhea virus at low temperatures on metal surfaces.

Veterinary microbiology
Porcine epidemic diarrhea virus (PEDV) spread rapidly across the United States in part due to contaminated livestock trailers. The objective of this study was to test a peroxygen-based disinfectant for the ability to inactivate PEDV on aluminum surfa...

Microwave-assisted digestion using diluted HNO and HO for macro and microelements determination in guarana samples by ICP OES.

Food chemistry
A microwave-assisted digestion procedure using diluted HNO and HO was developed for multi-element determination in guarana samples by ICP OES. Optimization step was performed employing a mixture design with pseudocomponents using HNO, HO and HO. The ...

How Well Does Dual-energy CT with Fast Kilovoltage Switching Quantify CT Number and Iodine and Calcium Concentrations?

Academic radiology
RATIONALE AND OBJECTIVES: Because it is imperative for understanding the performance of dual-energy computed tomography scanner to determine clinical diagnosis, we aimed to assess the accuracy of quantitative measurements using dual-energy computed t...

Metal-free virucidal effects induced by g-CN under visible light irradiation: Statistical analysis and parameter optimization.

Chemosphere
Waterborne viruses with a low infectious dose and a high pathogenic potential pose a serious risk for humans all over the world, calling for a cost-effective and environmentally-friendly inactivation method. Optimizing operational parameters during t...

Spiking Neural Classifier with Lumped Dendritic Nonlinearity and Binary Synapses: A Current Mode VLSI Implementation and Analysis.

Neural computation
We present a neuromorphic current mode implementation of a spiking neural classifier with lumped square law dendritic nonlinearity. It has been shown previously in software simulations that such a system with binary synapses can be trained with struc...

Manipulation of Biomolecule-Modified Liquid-Metal Blobs.

Angewandte Chemie (International ed. in English)
Soft and deformable liquid metals (LMs) are building components in various systems related to uncertain and dynamic task environments. Herein we describe the development of a biomolecule-triggered external-manipulation method involving LM conjugates ...

Construction of environmental risk score beyond standard linear models using machine learning methods: application to metal mixtures, oxidative stress and cardiovascular disease in NHANES.

Environmental health : a global access science source
BACKGROUND: There is growing concern of health effects of exposure to pollutant mixtures. We initially proposed an Environmental Risk Score (ERS) as a summary measure to examine the risk of exposure to multi-pollutants in epidemiologic research consi...

Machine Learning Using Combined Structural and Chemical Descriptors for Prediction of Methane Adsorption Performance of Metal Organic Frameworks (MOFs).

ACS combinatorial science
Using molecular simulation for adsorbent screening is computationally expensive and thus prohibitive to materials discovery. Machine learning (ML) algorithms trained on fundamental material properties can potentially provide quick and accurate method...