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Chlorine

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Evaluation of Free Available Chlorine of Sodium Hypochlorite When Admixed with 0.2% Chitosan: A Preliminary Study.

The journal of contemporary dental practice
AIM AND OBJECTIVE: The aim of the study was to evaluate the changes in free available chlorine (FAC) when 6% sodium hypochlorite (NaOCl) is admixed with irrigants 17% ethylenediaminetetraacetic acid (EDTA), 2% chlorhexidine (CHX), and 0.2% chitosan i...

Sanitation of tomatoes based on a combined approach of washing process and pulsed light in conjunction with selected disinfectants.

Food research international (Ottawa, Ont.)
In this study, we evaluated the performance of a large-scale decontamination system based on a washing process in combination with pulsed light (PL) exposure and HO/chlorine. In order to identify optimum processing condition, we first evaluated the e...

Designing and executing a functional exercise to test a novel informatics tool for mass casualty triage.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The testing of informatics tools designed for use during mass casualty incidents presents a unique problem as there is no readily available population of victims or identical exposure setting. The purpose of this article is to describe the...

Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks.

Physical chemistry chemical physics : PCCP
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...

Multiple Statistical Model Ensemble Predictions of Residual Chlorine in Drinking Water: Applications of Various Deep Learning and Machine Learning Algorithms.

Journal of environmental and public health
Applicability of statistical models in predicting chlorine decay remains minimally explored. This study predicted residual chlorine using six deep learning and nine machine learning techniques. Suitability of multimodel ensembles (MMEs) including ari...

Implementation of an early warning system with hyperspectral imaging combined with deep learning model for chlorine in refuse derived fuels.

Waste management (New York, N.Y.)
Chlorine content is one of the most important parameters in Refuse Derived Fuels (RDFs) used as a fuel in cement kilns. The main problem with the use of RDF is that chlorine in the waste weakens the cement, increases the risk of corrosion in the kiln...

Development of benchmark datasets for text mining and sentiment analysis to accelerate regulatory literature review.

Regulatory toxicology and pharmacology : RTP
In the field of regulatory science, reviewing literature is an essential and important step, which most of the time is conducted by manually reading hundreds of articles. Although this process is highly time-consuming and labor-intensive, most output...

The insightful water quality analysis and predictive model establishment via machine learning in dual-source drinking water distribution system.

Environmental research
Dual-source drinking water distribution systems (DWDS) over single-source water supply systems are becoming more practical in providing water for megacities. However, the more complex water supply problems are also generated, especially at the hydrau...

Enhancing long-term water quality modeling by addressing base demand, demand patterns, and temperature uncertainty using unsupervised machine learning techniques.

Water research
Water quality modelling in Water Distribution systems (WDS) is frequently affected by uncertainties in input variables such as base demand and decay constants. When utilizing simulation tools like EPANET, which necessitate exact numerical inputs, the...

Prediction of chlorination degradation rate of emerging contaminants based on machine learning models.

Environmental pollution (Barking, Essex : 1987)
Assessing the degradation of emerging contaminants in water through chlorination is crucial for regulatory monitoring of these contaminants. In this study, we developed a machine learning model to predict the apparent second-order reaction rate const...