No abstract

Due to the high redox activity of Fe(II) and its abundance in natural waters, the electro-oxidation of Fe(II) can be found in many air-cathode fuel cell systems, such as acid mine drainage fuel cells and sediment microbial fuel cells. To deeply understand these iron-related systems, it is essential to elucidate the kinetics and mechanisms involved in the electro-oxidation of Fe(II). This work aims to develop a kinetic model that adequately describes the electro-oxidation process of Fe(II) in air-cathode fuel cells. The speciation of Fe(II) is incorporated into the model, and contributions of individual Fe(II) species to the overall Fe(II) oxidation rate are quantitatively evaluated. The results show that the kinetic model can accurately predict the electro-oxidation rate of Fe(II) in air-cathode fuel cells. FeCO3, Fe(OH)2, and Fe(CO3)2(2-) are the most important species determining the electro-oxidation kinetics of Fe(II). The Fe(II) oxidation rate is primarily controlled by the oxidation of FeCO3 species at low pH, whereas at high pH Fe(OH)2 and Fe(CO3)2(2-) are the dominant species. Solution pH, carbonate concentration, and solution salinity are able to influence the electro-oxidation kinetics of Fe(II) through changing both distribution and kinetic activity of Fe(II) species.

This is a PDF file of a peer-reviewed, preliminarily formatted and unedited paper that has been accepted for publication in Diagnostic and Interventional Radiology. Copyediting of the text and figures and proof review of the the paper will be finished before the paper is published in its final form. Please note that errors may be discovered which could affect the content of the paper during the production process. All legal disclaimers apply. u n c o r r e c t e d p r o o f ABSTRACT PURPOSE: This study aimed to develop a diagnostic model combining computed tomography (CT) images and radiomic features to differentiate indeterminate small (5-20 mm) solid pulmonary nodules (SSPNs).METHODS: This study retrospectively enrolled 413 patients with SSPNs surgically removed and histologically confirmed from 2017 to 2019. The SSPNs included solid malignant pulmonary nodules (n=210) and benign pulmonary nodules (n=203). The least absolute shrinkage and selection operator (LASSO) was used for radiomic feature selection, and random forest (RF) algorithms were used for radiomic model construction. The clinical model and nomogram were established using univariate and multivariable logistic regression analyses combined with clinical symptoms, subjective CT findings and radiomic features. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of the models. RESULTS:The AUC for the clinical model was 0.77 in the training cohort (n=289; 95% confidence interval [CI]: 0.71-0.82; p = 0.001) and 0.75 in the validation cohort (n=124; 95% CI: 0.66-0.83; p = 0.016); the AUCs for the nomogram were 0.92 (95% CI: 0.89-0.95;p < 0.001) and 0.85 (95% CI: 0.78-0.91;p < 0.001), respectively. The Radscore, sex, pleural indentation and age were found independent predictors and were used to build the nomogram. CONCLUSIONS: The radiomic nomogram derived from clinical features, subjective CT signs and the radiomic score can potentially identify the risk of indeterminate SSPNs and aid in the patient's preoperative diagnosis.

No abstract

The water-soluble polyacrylamide (PAM) can accumulate in ecosystems and cause serious environmental pollution. Biological approach achieves poor PAM degradation efficiency, due to the extreme resistance of PAM to the microbial metabolism. In the present work, the potential of bioelectrochemical system (BES) as an effective tool to degrade the PAM is adequately evaluated. The closed-circuit operation of BES obtains COD removal efficiencies of 29.2 and 33.6 % for the PAM and polyacrylic acid (PAA), respectively. In comparison, 4.3 and 2.7 % of COD are removed after the PAM and PAA are treated in the open-circuit BES, and 7.3 and 6.6 % are removed in the aerobic BES. These results suggest the bioelectricity generation is crucial to trigger the activity of bioanode for the effective degradation of PAM. Bioelectricity generation not only favors the decomposition of carbon backbone but also facilitates the hydrolysis of amide group in the side-chain of PAM. Microbial attack on the carbon backbone of PAM is proposed to initiate at the head-to-head linkage, resulting in the formation of ether bond within the shortened carbon chain. The Ignavibacterium sp. and phenotypically uncharacterized bacteria are classified as the dominant species on the anode of PAM-fed BES.