Measuring E. coli and bacteriophage DNA in cell sonicates to evaluate the CAL1 reaction as a synthetic biology standard for qPCR

Templar, Alexander; Schofield, Desmond M.; Nesbeth, Darren N.

doi:10.1016/j.bdq.2016.12.001

Cited by 1 publication

(1 citation statement)

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“…Culture-based methods of analyzing FIB concentrations usually take up to 18-96 h, which is ineffective at keeping up with the change in temporal variations in FIB concentrations. Another method that has been introduced in recent years is the rapid instrumental method, such as the quantitative polymerase chain reaction (qPCR) (Dorevitch et al 2011;Templar et al 2017). The process for rapid detection methods may take up to 2-4 h, which shows some promise in addressing the temporal variation that limits the use of culture-based methods.…”

Section: Introductionmentioning

confidence: 99%

Modeling Fecal Indicator Bacteria in Urban Waterways Using Artificial Neural Networks

et al. 2018

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Fecal indicator bacteria (FIB) are used as proxies to measure the microbial water quality of aquatic ecosystems. Methods of modeling FIB have evolved in order to provide accurate and timely prediction to inform decisions by governing authorities to prevent risks to public health. A predictive model to forecast the FIB concentrations of an urban waterway, the Chicago River, utilizing the artificial neural network (ANN) method was developed. To address tuning of hyperparameters of the ANN model, an exhaustive testing was performed to select optimal hyperparameters. The root-mean-square propagation (RMSprop) optimizer performed better than the stochastic gradient descent (SGD) and adaptive moment estimation (Adam) optimizers in this study. Eight input variables were eventually selected from 10 initially proposed variables: water temperature; turbidity; daily, 2-day, and 7-day cumulative rainfall; river flow discharge; distance from the upstream water reclamation plant; and number of upstream combined sewer outfalls. Water reclamation plants and combined sewer overflows were found to be critical contributors of microbial pollution in this urban waterway and should be considered in the ANN model. The developed model has an accuracy of 86.5% to predict whether fecal coliform concentration is above or below a regulatory threshold. individual papers. This paper is part of the Journal of Environmental Engineering, © ASCE, ISSN 0733-9372. © ASCE 05018003-1 J. Environ. Eng. J. Environ. Eng., 2018, 144(6): 05018003 Downloaded from ascelibrary.org by Zhenduo Zhu on 04/06/18. Copyright ASCE. For personal use only; all rights reserved. Batch size 8, 16, 32, 64, 128 32 Activation function ELU, ReLU, and Tanh ReLU Optimizer SGD, RMSprop, and Adam RMSprop © ASCE 05018003-5 J. Environ. Eng.

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Section: Introductionmentioning

confidence: 99%