Characterization of soluble and bound EPS obtained from 2 submerged membrane bioreactors by 3D-EEM and HPSEC

This research study deals with the quantification and characterization of the EPS obtained from two 25 L bench scale membrane bioreactors (MBRs) with micro-(MF-MBR) and ultrafiltration (UF-MBR) submerged membranes. Both reactors were fed with synthetic water and operated for 168 days without sludge extraction, increasing their mixed liquor suspended solid (MLSS) concentration during the experimentation time. The characterization of soluble EPS (EPSs) was achieved by the centrifugation of mixed liquor and bound EPS (EPSb) by extraction using a cationic resin exchange (CER). EPS characterization was carried out by applying the 3-dimensional excitation–emission matrix fluorescence spectroscopy (3D-EEM) and high-performance size exclusion chromatography (HPSEC) with the aim of obtaining structural and functional information thereof. With regard to the 3D-EEM analysis, fluorescence spectra of EPSb and EPSs showed 2 peaks in both MBRs at all the MLSS concentrations studied. The peaks obtained for EPSb were associated to soluble microbial by-product-like (predominantly protein-derived compounds) and to aromatic protein. For EPSs, the peaks were associated with humic and fulvic acids. In both MBRs, the fluorescence intensity (FI) of the peaks increased as MLSS and protein concentrations increased. The FI of the EPSs peaks was much lower than for EPSb. It was verified that the evolution of the FI clearly depends on the concentration of protein and humic acids for EPSb and EPSs, respectively. Chromatographic analysis showed that the intensity of the EPSb peak increased while the concentrations of MLSS did. Additionally, the mean MW calculated was always higher the higher the MLSS concentrations in the reactors. MW was higher for the MF-MBR than for the UF-MBR for the same MLSS concentrations demonstrating that the filtration carried out with a UF membrane lead to retentions of lower MW particles.

Local job descriptions for two establishments in the malt liquor manufacturing industry : Malting Branch and Brewery Branch /

At head of title: Preliminary job study no. 5-113.

Knowledge acquisition through conceptual clustering : a theoretical framework and an algorithm for partitioning data into conjunctive concepts /

"May 1980."

Science and technology; a purchase guide for branch and small public libraries.

Accompanied by "Supplement 1963." (42 L.) Published: [Pittsburgh, Carnegie Library of Pittsburgh, 1964?]

Rules and regulations of Plant Pest Control Branch and Plant Quarantine Branch. Title 7, Chapter III, of the Code of Federal Regulations.

Amendments [issued by Plant Quarantine Division or Plant Pest Control Division.] (1 v. loose-leaf)

Stray subjects, arrested and bound over. Being the fugitive offspring of the "old 'un" and the "young 'un," that have been "lying round loose," and are now "tied up" for fast keeping.

"Hamilton 645 (2)"

The Vaughn Branch and Old Edwardsville Road sites : late Stirling and early Moorehead phase Mississippian occupations in the northern American Bottom /

Includes bibliographical references (p. 413-431).

Collected and bound

Mode of access: Internet.

Working agreement - woods between Weyerhauser Timber Company, Longview Branch, and Lumber and Sawmill Workers, Local union No. 2642, April l5, 1937.

Mode of access: Internet.

Optimization and Machine Learning Frameworks for Complex Network Analysis

Thesis (Ph.D.)--University of Washington, 2016-06

Investigating the performance analysis of EASI algorithm and EKENS algorithm in nonlinear model

This paper investigates the performance of EASI algorithm and the proposed EKENS algorithm for linear and nonlinear mixtures. The proposed EKENS algorithm is based on the modified equivariant algorithm and kernel density estimation. Theory and characteristic of both the algorithms are discussed for blind source separation model. The separation structure of nonlinear mixtures is based on a nonlinear stage followed by a linear stage. Simulations with artificial and natural data demonstrate the feasibility and good performance of the proposed EKENS algorithm.