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Aline Thaís Bruni

Researcher at Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto

Publications -  41
Citations -  344

Aline Thaís Bruni is an academic researcher from Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto. The author has contributed to research in topics: Chemistry & Chemical oxygen demand. The author has an hindex of 10, co-authored 32 publications receiving 274 citations. Previous affiliations of Aline Thaís Bruni include Sao Paulo State University & State University of Campinas.

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A structure–activity relationship study of quinone compounds with trypanocidal activity

TL;DR: The prediction study was done with a set of three new compounds by using the PCA, HCA, SDA, KNN and SIMCA methods and two of them were predicted as active against the Trypanosoma cruzi.
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Leachate/domestic wastewater aerobic co-treatment: A pilot-scale study using multivariate analysis.

TL;DR: Principal component analysis (PCA) and partial least squares (PLS) indicated that the data dimension could be reduced and that TAN, SCOD, DOC and nitrification efficiency were the main variables that affected the performance of the AS reactors.
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Analyzing the effect of homogeneous frustration in protein folding.

TL;DR: A simple theoretical model is proposed as a useful tool for experimentalists to predict the limits of improvements in real proteins, and its findings strongly correlate with the protein free‐energy folding barrier and the absolute contact order parameters.
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Performance of an Anaerobic Baffled Reactor (ABR) in treatment of cassava wastewater.

TL;DR: The performance of an anaerobic baffled reactor (ABR) was evaluated in the treatment of cassava wastewater, a pollutant residue, and showed buffering ability as acidity decreased along compartments while alkalinity and pH values were increased.
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A partial least squares regression study with antioxidant flavonoid compounds

TL;DR: In this paper, the quantitative structure-activity relationship of a set of 19 flavonoid compounds presenting antioxidant activity was studied by means of PLS (Partial Least Squares) regression.