Anaerobic digestion challenges and resource recovery opportunities from land-based aquaculture waste and seafood processing byproducts: A review.

The unprecedented demand for seafood has resulted in land-based recirculating aquaculture systems (RAS), a highly intensive but sustainable fish farming method. However, intensification also results in concentrated waste streams of fecal matter and uneaten feed. Harvesting and processing vast quantities of fish also leads to the production of byproducts, further creating disposal challenges for fish farms. Recent research indicates that anaerobic digestion (AD), often used for waste treatment in agricultural and wastewater industries, may provide a viable solution. Limited research on AD of freshwater, brackish, and saline wastewater from RAS facilities and co-digestion of seafood byproducts has shown promising results but with considerable operational and process stability issues. This review discusses challenges to AD due to low solid concentrations, salinity, low carbon/nitrogen ratio, and high lipid content in the waste streams. Opportunities for recovering valuable biomolecules and nutrients through microbial treatment, aquaponics, microalgae, and polyhydroxyalkanoate production are also discussed.

Biochar addition with Fe impregnation to reduce H2S production from anaerobic digestion.

Corn stover biochar (CSB) and maple biochar (MB) were added into anaerobic digesters and evaluated for hydrogen sulfide (H2S) reductions. This was the first study to show Fe-impregnated biochar can eliminate H2S production. The novel study evaluated biochar addition on H2S reduction and nutrient concentrations using three experiments to test the effect of: 1) biochar concentration, 2) biochar particle size, and 3) Fe-impregnated biochar using triplicate lab-scale reactors. At the highest biochar dose (1.82 g biochar/g manure TS), H2S production was 90.5% less than the control treatment (351 mL H2S/kg VS). Biochar particle size did not significantly affect H2S concentration. The Fe-impregnated biochar (0.5 g biochar/g manure TS) reactors had no H2S detected in the CSB-Fe system. Methane (CH4) in the biochar and control treatments were not significantly different in all three experiments. The results show that biochar added to digesters can significantly reduce H2S production without affecting CH4 production.

AI in Healthcare: Time-Series Forecasting Using Statistical, Neural, and Ensemble Architectures.

Both statistical and neural methods have been proposed in the literature to predict healthcare expenditures. However, less attention has been given to comparing predictions from both these methods as well as ensemble approaches in the healthcare domain. The primary objective of this paper was to evaluate different statistical, neural, and ensemble techniques in their ability to predict patients' weekly average expenditures on certain pain medications. Two statistical models, persistence (baseline) and autoregressive integrated moving average (ARIMA), a multilayer perceptron (MLP) model, a long short-term memory (LSTM) model, and an ensemble model combining predictions of the ARIMA, MLP, and LSTM models were calibrated to predict the expenditures on two different pain medications. In the MLP and LSTM models, we compared the influence of shuffling of training data and dropout of certain nodes in MLPs and nodes and recurrent connections in LSTMs in layers during training. Results revealed that the ensemble model outperformed the persistence, ARIMA, MLP, and LSTM models across both pain medications. In general, not shuffling the training data and adding the dropout helped the MLP models and shuffling the training data and not adding the dropout helped the LSTM models across both medications. We highlight the implications of using statistical, neural, and ensemble methods for time-series forecasting of outcomes in the healthcare domain.

Effect of electrode surface properties on enhanced electron transfer activity in microbial fuel cells.

The influence of electrode surface chemistry over biofilm growth was evaluated for photo-bioelectrocatalytic fuel cell. A consortium of photosynthetic bacteria was grown onto different electrodes designed with polyethylenimine (PEI) and multiwall carbon nanotubes as hydrophilic and hydrophobic modifier, respectively. The designed electrodes were loaded with 0.08, 0.17, and 0.33 µg/cm2 of PEI to change the hydrophilicity. However, 0.56, 0.72, and 0.83 mg/cm2 of multiwall carbon nanotubes were used to alter the hydrophobicity of the electrodes. The surface chemistry of electrode and bio-interaction was evaluated as a function of contact angle and biofilm formation. The results were compared with those obtained with a carbon paper electrode. The contact angle on the untreated electrode (carbon paper) was 118°, whereas for hydrophobic and hydrophilic electrodes, the maximum and minimum contact angles were 170° and 0°, respectively. Interestingly, the maximum biofilm growth (0.2275 g, wet basis) was observed on highly hydrophobic surface; however, the maximum electrochemical performance (246 mV) was shown by the most hydrophilic electrode surface. PEI-based electrode with good biofilm formation showed comparatively higher electrogenic activity.