Effect of proton pump inhibitor on microbial community, function, and kinetics in anaerobic digestion with ammonia stress

The proton pump is a convincing mechanism for ammonia inhibition in anaerobic digestion, which explained how the ammonia accumulated intercellularly due to diffusion of free ammonia. Proton pump inhibitor (PPI) was dosed for mitigating the accumulation in anaerobic digestion with ammonia stress, with respect to kinetics. Results show PPI inhibited beta-oxidation of fatty acids by targeting ATPase in anaerobic digestion with ammonia stress. Alternatively, PPI stimulated syntrophic acetate oxidization. Random forest located key genera as syntrophic consortia. Methane increased 18.72 +/- 7.39% with 20 mg/L PPI at the first peak, consistent with microbial results. The deterministic Gompertz kinetics and stochastic Gaussian processes contributed 97.63 +/- 8.93% and 2.37 +/- 8.93% in accumulated methane production, respectively. Thus, the use of PPI for anaerobic digestion allowed mitigate ammonia inhibition based on the mechanism of proton pump, facilitate intercellularly ammonia accumulation, stimulate syntrophic consortia, and eliminate uncertainty of process failure, which resulted in efficient methane production under ammonia stress

New Insights into the Microbial Diversity of Cake Layer in Yttria Composite Ceramic Tubular Membrane in an Anaerobic Membrane Bioreactor (AnMBR)

Cake layer formation is an inevitable challenge in membrane bioreactor (MBR) operation. The investigations on the cake layer microbial community are essential to control biofouling. This work studied the bacterial and archaeal communities in the cake layer, the anaerobic sludge, and the membrane cleaning solutions of anaerobic membrane bioreactor (AnMBR) with yttria-based ceramic tubular membrane by polymerase chain reaction (PCR) amplification of 16S rRNA genes. The cake layer resistance was 69% of the total membrane resistance. Proteins and soluble microbial by-products (SMPs) were the dominant foulants in the cake layer. The pioneering archaeal and bacteria in the cake layer were mostly similar to those in the anaerobic bulk sludge. The dominant biofouling bacteria were Proteobacteria, Bacteroidetes, Firmicutes, and Chloroflexi and the dominant archaeal were Methanosaetacea and Methanobacteriacea at family level. This finding may help to develop antifouling membranes for AnMBR treating domestic wastewater

Applying novel self‐supervised learning for early detection of retinopathy of prematurity

Abstract Retinopathy of prematurity (ROP) mainly occurs in premature infants with low birth weight, and it is the leading cause of childhood blindness. Early and accurate ROP diagnosis is imperative for appropriate treatment. However, less research concentrates on early‐stage ROP diagnosis based on limited‐labelled images in an imbalanced dataset. To address the dilemma, this study proposed a novel self‐supervised network, MOCO‐MIM, for early ROP grading. The proposed classification network was evaluated on a total of 553 labelled fundus images from 89 preterm infants. The trained network achieved a test accuracy of 98.29% and an AUC score of 97.6% for three stages of grading. The adopted method is verified that the proposed method can be detected early stages of ROP more efficiently and grade the severity more accurately based on limited‐labelled fundus images, which is superior to the existing state‐of‐the‐art methods

Effects of mixed-liquor rheology on vibration of hollow-fiber membrane via particle image velocimetry and computational fluid dynamics

Although vortex-induced vibration is widely observed, not only its characteristics but also its manipulation remains ambiguous. The effects of mixed-liquor rheology on vortex-induced vibration are investigated in a hollow-fiber MBR using particle image velocimetry (PIV) for observation and computational fluid dynamics (CFD) for modeling. Ply shows the vibration in the form of the Karmen vortex with amplify similar diameter. Further, CFD shows a lower Strouhal number (St, 0.149) at the optimized MISS 6305 mg.L-1 resulting similar vibration frequencies 1.89 +/- 0.20 Hz in 78.7% tank volume. The lower St 0.151 +/- 0.002 therefore increases resonance probability. The resonance doubled the shear force without extra energy input. A full scale MBR's permeability was used to test the assumption of optimizing shear force by vibration in rheology optimized mixed-liquor. The theoretically optimized MLSS 6305 mg.L-1 (5615 mgL(-1), practically) achieved the highest permeability. The accordance suggested that optimized MISS doubled the shear force by resonance of vortexinduced vibration within proper mixed-liquor rheology. The MBR's permeability is nearly doubled to 1.84 +/- 0.70 L m(-2) h(-1) kPa(-1) at the optimized MISS, and sustained longer period (similar to 3 months)

Prediction of the Long-Term Effect of Iron on Methane Yield in an Anaerobic Membrane Bioreactor Using Bayesian Network Meta-Analysis

A method for predicting the long-term effects of ferric on methane production was developed in an anaerobic membrane bioreactor treating food processing wastewater to provide management tools for maximizing methane recovery using ferric based on a batch test. The results demonstrated the accuracy of the predictions for both batch and long-term continuous operations using a Bayesian network meta-analysis based on the Gompertz model. The prediction bias of methane production for batch and continuous operations was minimized, from 11~19% to less than 0.5%. A biochemical methane potential-based Bayesian network meta-analysis suggested a maximum 2.55% ± 0.42% enhancement for Fe2.25. An anaerobic membrane bioreactor improved the methane yield by 2.27% and loading rate by 4.57% for Fe2.25, operating in the sequenced batch mode. The method allowed for a predictable methane yield enhancement based on the biochemical methane potential. Ferric enhanced the biochemical methane potential in batch tests and the methane yield in a continuously operated reactor by a maximum of 8.20% and 7.61% for Fe2.25, respectively. Copper demonstrated a higher methane (18.91%) and sludge yield (17.22%) in batch but faded in the continuous operation (0.32% of methane yield). The enhancement was primarily due to changing the kinetic patterns for the last period, i.e., increasing the second methane production peak (k71), bringing forward the second peak (λ7, λ8), and prolonging the second period (k62). The dual exponential function demonstrated a better fit in the last three stages (after the first peak), which implied that syntrophic methanogenesis with a ferric shuttle played a primary role in the last three methane production periods, in which long-term effects were sustained, as the Bayesian network meta-analysis predicted