3 documents found, page 1 of 1
Small concentrations, big results: μM addition of photoactive iron oxides with ...
Jia, Jialin; Minella, Marco; Ruiz, Mercedes Cid; Decker, Jeremie; Li, Dong; Gonçalves, Nuno P. F.; Prevot, Alessandra Bianco; Lin, TaoThe photo-Fenton process is effective for pathogen removal, and its low-cost versions can be applied in resource-poor contexts. Herein, a photo-Fenton-like system was proposed using low concentrations of iron oxides (hematite and magnetite) and persulfates (peroxymonosulfate - PMS, and peroxydisulfate - PDS), which exhibited excellent inactivation performance towards MS2 bacteriophages. In the presence of bacte...
From rust to robust disinfectants: How do iron oxides and inorganic oxidants sy...
Jia, Jialin; Minella, Marco; Del Castillo González, Isabel; Lehmann, Aurelio Hernández; Li, Dong; Gonçalves, Nuno P. F.; Prevot, Alessandra BiancoPathogens in drinking water remain a challenge for human health, photo-Fenton process is a promising technique for pathogen inactivation, herein, two common iron oxides, hematite and magnetite mediate persulfate (peroxymonosulfate-PMS - and peroxydisulfate-PDS) involved photo-Fenton-like processes were constructed for E. coli inactivation, and the inactivation performance was investigated and compared with the ...
A deep learning approach to improving spectral analysis of fruit quality under ...
Yang, Jie; Luo, Xuan; Zhang, Xiaolei; Passos, Dário; Xie, Lijuan; Rao, Xiuqin; Xu, Huirong; Ting, K.C.; Lin, Tao; Ying, YibinModel updating for developed calibrations is critical for robust spectral analysis in fruit quality control. Existing methods have limitations that usually need sufficient samples for model recalibration and are mainly designed for conventional linear models. This study proposes a model fine-tuning approach to update nonlinear deep learning models using limited sample sizes for fruit detection under interseason...