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Daniel B. Oerther

Researcher at Missouri University of Science and Technology

Publications -  143
Citations -  3292

Daniel B. Oerther is an academic researcher from Missouri University of Science and Technology. The author has contributed to research in topics: Activated sludge & Population. The author has an hindex of 23, co-authored 133 publications receiving 3011 citations. Previous affiliations of Daniel B. Oerther include University of Illinois at Urbana–Champaign & University of South Florida.

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The Academy, the Association, and the Society Advancing Environmental Engineering Training and Credentialing

TL;DR: As the lead society for environmental engineering and similarly named programs accredited by ABET (formerly the Accreditation Board of Engineering and Technology, Inc.), the American Academy of Env... as mentioned in this paper.
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Developing rapid detection of mycobacteria using microwaves

TL;DR: By combing the semi-selective paraffin surface of the biochip with the microorganism-specific response to the microwaves, an improved analytical system with the potential to rapidly identify and enumerate mycobacteria in environmental samples in as little as 2 h is developed.
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Review of Recent Research about Parenting Generation Z Pre-Teen Children.

TL;DR: A scoping review of available research describing parents' perspectives of parenting pre-teen children of Generation Z (born 1997 through 2012) is presented in this article, where the authors provide a timely update.

Disseminating Molecular Biology For Environmental Engineers With Nsf Ccli Support

TL;DR: For the past five years, more than fifty undergraduate and graduate students at the University of Cincinnati have participated in a term-length course, CEE69 Molecular Biology for Environmental Systems as mentioned in this paper.
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16S Ribosomal RNA Tools Identify an Unexpected Predominance of Paenibacillus-Like Bacteria in an Industrial Activated Sludge System Suffering from Poor Biosolids Separation

TL;DR: It is demonstrated that the full‐cycle 16S rRNA approach can be used to identify candidate bacterial populations that may be responsible for operational upsets in full‐scale activated sludge systems without prior information from cultivation or microscopic analyses.