Event-assisted Blurriness Representation Learning for Blurry Image Unfolding.

The goal of blurry image deblurring and unfolding task is to recover a single sharp frame or a sequence from a blurry one. Recently, its performance is greatly improved with introduction of a bio-inspired visual sensor, event camera. Most existing event-assisted deblurring methods focus on the design of powerful network architectures and effective training strategy, while ignoring the role of blur modeling in removing various blur in dynamic scenes. In this work, we propose to implicitly model blur in an image by computing blurriness representation with an event-assisted blurriness encoder. The learning of blurriness representation is formulated as a ranking problem based on specially synthesized pairs. Blurriness-aware image unfolding is achieved by integrating blur relevant information contained in the representation into a base unfolding network. The integration is mainly realized by the proposed blurriness-guided modulation and multi-scale aggregation modules. Experiments on GOPRO and HQF datasets show favorable performance of the proposed method against state-of-the-art approaches. More results on real-world data validate its effectiveness in recovering a sequence of latent sharp frames from a blurry image.

Network model with internal complexity bridges artificial intelligence and neuroscience.

Artificial intelligence (AI) researchers currently believe that the main approach to building more general model problems is the big AI model, where existing neural networks are becoming deeper, larger and wider. We term this the big model with external complexity approach. In this work we argue that there is another approach called small model with internal complexity, which can be used to find a suitable path of incorporating rich properties into neurons to construct larger and more efficient AI models. We uncover that one has to increase the scale of the network externally to stimulate the same dynamical properties. To illustrate this, we build a Hodgkin-Huxley (HH) network with rich internal complexity, where each neuron is an HH model, and prove that the dynamical properties and performance of the HH network can be equivalent to a bigger leaky integrate-and-fire (LIF) network, where each neuron is a LIF neuron with simple internal complexity.

Sorting Out the Latest Advances in Separators and Pilot-Scale Microbial Electrochemical Systems for Wastewater Treatment: Concomitant Development, Practical Application, and Future Perspective.

To date, dozens of pilot-scale microbial fuel cell (MFC) devices have been successfully developed worldwide for treating various types of wastewater. The availability and configurations of separators are determining factors for the economic feasibility, efficiency, sustainability, and operability of these devices. Thus, the concomitant advances between the separators and pilot-scale MFC configurations deserve further clarification. The analysis of separator configurations has shown that their evolution proceeds as follows: from ion-selective to ion-non-selective, from nonpermeable to permeable, and from abiotic to biotic. Meanwhile, their cost is decreasing and their availability is increasing. Notably, the novel MFCs configured with biotic separators are superior to those configured with abiotic separators in terms of wastewater treatment efficiency and capital cost. Herein, a highly comprehensive review of pilot-scale MFCs (>100 L) has been conducted, and we conclude that the intensive stack of the liquid cathode configuration is more advantageous when wastewater treatment is the highest priority. The use of permeable biotic separators ensures hydrodynamic continuity within the MFCs and simplifies reactor configuration and operation. In addition, a systemic comparison is conducted between pilot-scale MFC devices and conventional decentralized wastewater treatment processes. MFCs showed comparable cost, higher efficiency, long-term stability, and significant superiority in carbon emission reduction. The development of separators has greatly contributed to the availability and usability of MFCs, which will play an important role in various wastewater treatment scenarios in the future.

Multi-scale full spike pattern for semantic segmentation.

Spiking neural networks (SNNs), as the brain-inspired neural networks, encode information in spatio-temporal dynamics. They have the potential to serve as low-power alternatives to artificial neural networks (ANNs) due to their sparse and event-driven nature. However, existing SNN-based models for pixel-level semantic segmentation tasks suffer from poor performance and high memory overhead, failing to fully exploit the computational effectiveness and efficiency of SNNs. To address these challenges, we propose the multi-scale and full spike segmentation network (MFS-Seg), which is based on the deep direct trained SNN and represents the first attempt to train a deep SNN with surrogate gradients for semantic segmentation. Specifically, we design an efficient fully-spike residual block (EFS-Res) to alleviate representation issues caused by spiking noise on different channels. EFS-Res utilizes depthwise separable convolution to improve the distributions of spiking feature maps. The visualization shows that our model can effectively extract the edge features of segmented objects. Furthermore, it can significantly reduce the memory overhead and energy consumption of the network. In addition, we theoretically analyze and prove that EFS-Res can avoid the degradation problem based on block dynamical isometry theory. Experimental results on the Camvid dataset, the DDD17 dataset, and the DSEC-Semantic dataset show that our model achieves comparable performance to the mainstream UNet network with up to 31× fewer parameters, while significantly reducing power consumption by over 13×. Overall, our MFS-Seg model demonstrates promising results in terms of performance, memory efficiency, and energy consumption, showcasing the potential of deep SNNs for semantic segmentation tasks. Our code is available in https://github.com/BICLab/MFS-Seg.

Potential Toxicity and Mechanisms of T-2 and HT-2 Individually or in Combination on the Intestinal Barrier Function of Porcine Small Intestinal Epithelial Cells.

Under natural conditions, T-2 toxin can be easily metabolized to HT-2 toxin by deacetylation, and T-2 and HT-2 are usually co-contaminated in grain and feed at a high detected rate. Our previous information indicated that T-2 toxin could injure the function of the intestinal barrier, but the combined toxicity and mechanism of T-2 and HT-2 on the intestinal cells of porcines are still unknown. Therefore, we aimed to explore T-2 and HT-2 individually and combined on cellular viability, cell membrane integrity, the expression of tight junction-related proteins, and the generation of inflammatory factors in porcine intestinal epithelial cells (IPEC-J2). The results showed that T-2 and HT-2, individually or in combination, could induce a decrease in cell viability, an increase in LDH release and IL-1, IL-6, and TNF-α generation, and a decrease in the anti-inflammatory factor IL-10. Based on the analysis of immunofluorescence staining, real-time PCR, and western blotting, the tight junction protein expressions of Claudin-1, Occludin, and ZO-1 were significantly decreased in the T-2 and HT-2 individual or combination treated groups compared with the control. Furthermore, all the parameter changes in the T-2 + HT-2 combination group were much more serious than those in the individual dose groups. These results suggest that T-2 and HT-2, individually and in combination, could induce an intestinal function injury related to an inflammatory response and damage to the intestinal barrier function in porcine intestinal epithelial cells. Additionally, T-2 and HT-2 in combination showed a synergistic toxic effect, which will provide a theoretical basis to assess the risk of T-2 + HT-2 co-contamination in porcine feed.

Triple strategy-enhanced immunochromatographic assay based on APCB and AIEFM for the ultrasensitive detection of AFM1.

Aflatoxin M1 (AFM1) is highly toxic, widely distributed, and difficult to monitor, posing a serious threat to human health. Therefore, a highly sensitive, rapid, convenient, and low-cost detection method must be urgently established. In this study, a triple strategy-enhanced immunochromatographic assay (ICA) was developed to satisfy these detection requirements. First, a turn-on signal output mode of the fluorescence quenching ICA substituted the turn-off mode of the traditional ICA for sensitive response to trace AFM1, with the limit of detection (LOD) reduced by approximately 4.9-fold. Then, a novel Au and polydopamine (PDA) cogrowth chrysanthemum-like blackbody was prepared as the quenching probe to reduce the background signal. This probe combined the excellent properties of Au nanoparticles with PDA. Thus, its fluorescence quenching constant was higher than that of single Au and PDA nanoparticles by 25.8- and 4.9-fold, respectively. Furthermore, an aggregation-induced emission fluorescence microsphere with a 5.7-fold higher relative quantum yield than a commercial fluorescence microsphere was selected as the signal output carrier to improve the signal-to-noise ratio. The integration of the above triple strategies established a 53.4-fold sensitivity-enhanced fluorescence quenching ICA (LOD = 0.9 pg/mL) for detecting AFM1 in milk, providing a strong technical guarantee for the safety monitoring of milk products.

The restricted mass transfer inside the anode pore channel affects the electroactive biofilms formation, community composition and the power production in microbial electrochemical systems.

Porous anodes improve system performance in microbial electrochemical systems by increasing the specific surface area for electroactive bacteria. In this study, multilayer anodes with different pore diameters were constructed to assess the impact of pore size and depth on anode performance. This layered structure makes detecting electroactive biofilms more accessible layer by layer, which is the first study to examine electroactive biofilms' molecular biology and electrochemical properties at different depths in pores with varied pore sizes. The millimeter-scale pores inside the bioanode have a limited effect in increasing power. The larger the pore diameter, the higher the maximum power density (Pmax) obtained. The Pmax of anodes with 4 mm pore (1.91 ± 0.15 W m-2) was 1.4 times higher than that of the non-perforated (1.37 ± 0.07 W m-2) and 0.5 mm pore anodes (1.39 ± 0.04 W m-2). Electricigens can colonize into pore channels for at least 10 mm with a pore diameter ≥3 mm and current densities >0.05 A m-2. However, in the pores channel with 0.5 mm diameter, electricigens can only colonize to a depth of 2 mm. The biofilm thickness, electricity output, metabolic activity, and biocommunity changed with pore depth and were restricted by the limited mass transfer. The Geobacter sp. was the dominant species in inter-pore biofilms, with 43.8 %-78.6 % in abundance and decreased in quantity as pore depth increased. The inter-pore biofilms on the outer layer contributed a current density of 0.17 ± 0.003 A m-2, while that of the inner layer was only 0.02 ± 0.01 A m-2. Further studies found that the pore edge mass transfer effect can contribute up to 75 % of the current. The mass transfer process at the pore edge region could be a multidirectional mass transfer rather than a pore channel mass transfer.

Impedance-Based Multimodal Electrical-Mechanical Intrinsic Flow Cytometry.

Reflecting various physiological states and phenotypes of single cells, intrinsic biophysical characteristics (e.g., mechanical and electrical properties) are reliable and important, label-free biomarkers for characterizing single cells. However, single-modal mechanical or electrical properties alone are not specific enough to characterize single cells accurately, and it has been long and challenging to couple the conventionally image-based mechanical characterization and impedance-based electrical characterization. In this work, the spatial-temporal characteristics of impedance sensing signal are leveraged, and an impedance-based multimodal electrical-mechanical flow cytometry framework for on-the-fly high-dimensional intrinsic measurement is proposed, that is, Young's modulus E, fluidity ß, radius r, cytoplasm conductivity σi , and specific membrane capacitance Csm , of single cells. With multimodal high-dimensional characterization, the electrical-mechanical flow cytometry can better reveal the difference in cell types, demonstrated by the experimental results with three types of cancer cells (HepG2, MCF-7, and MDA-MB-468) with 93.4% classification accuracy and pharmacological perturbations of the cytoskeleton (fixed and Cytochalasin B treated cells) with 95.1% classification accuracy. It is envisioned that multimodal electrical-mechanical flow cytometry provides a new perspective for accurate label-free single-cell intrinsic characterization.

High-flux smartphone-integrated lateral flow assay based on chrysanthemum-like Au@polydopamine for sensitive detection of enrofloxacin in milk.

Lateral flow assays (LFAs) are widely used in screening analysis. However, the detection flux and sensitivity of LFAs are unsatisfactory because of the 'one-to-one' read mode and the ordinary performance conventional probe. In this work, a high-flux smartphone-integrated LFA (sLFA) based on chrysanthemum-like Au@polydopamine (AuNC@PDA) for the detection of enrofloxacin (ENR) in milk was established. The smartphone-integrated device was developed and applied in the LFA, giving rise to a reading maximum of 64 samples with only two photos in less than 2 min compared to a 'one-to-one' read mode of a conventional LFA in more than 14 min with a 36.4% deviation. For ENR detection, the limits of detection of sLFA based on AuNC@PDA (33.78 pg mL-1) had 5.0-fold and 6.4-fold reduction compared with those based on AuNP (169.99 pg mL-1, conventional probe) and vvAuNP (216.47 pg mL-1, commercial probe), respectively. This study provides an effective technical means for screening ENR in large quantities of milk samples.

Liquid-gas phase transition enables microbial electrolysis and H2-based membrane biofilm hybrid system to degrade organic pollution and achieve effective hydrogenotrophic denitrification of groundwater.

Electron-donor Lacking was the limiting factor for the denitrification of oligotrophic groundwater and hydrogenotrophic denitrification provided an efficient approach without secondary pollution. In this study, a hybrid system with microbial electrolysis cell (MEC) assisted hydrogen-based membrane biofilm reactor (MBfR) was established for advanced groundwater denitrification. The liquid-gas phase transition prevented the potential pollution from organic wastes in MEC to groundwater, while the bubble-free diffusion of MBfR promoted hydrogen utilization efficiency. The negative-pressure extraction from MEC and the positive pressure for gas supply into MBfR increased the hydrogen proportion and current density of MEC, and improved the kinetic constant K of the denitrification reaction in MBfR. With actual groundwater, the MEC-MBfR hybrid system achieved a nitrate reduction of 97.8% with an effluent NO3--N of 2.2 ± 1.0 mg L-1. The hydrogenotrophic denitrifiers of Thauera, Pannonibacter, and Azonexus, dominated the denitrification biofilm on the membrane and elastic filler in MBfR.

Bi(â ¢) and Ce(â £) functionalized carbon nitride photocatalyst for antibiotic degradation: Synthesis, toxicity, and mechanism investigations.

Graphite-phase carbon nitride (g-C3N4) has shown great potential for antibiotic wastewater treatment due to its unique electronic structure and corresponding to visible light. In this study, a series of Bi/Ce/g-C3N4 photocatalysts with different doping amount were developed by direct calcination method for Rhodamine B and sulfamethoxazole photocatalytic degradation. The experiment result shows that the photocatalytic performance of Bi/Ce/g-C3N4 catalysts were better than that of single component samples. Under the optimal experimental conditions, the degradation rates of RhB (20 min) and SMX (120 min) by 3Bi/Ce/g-C3N4 reached 98.3% and 70.5%, respectively. The theoretical calculation results of DFT show that after Bi and Ce doping modification, the band-gap width of g-C3N4 is reduced to 1.215 eV and carrier migration rate is greatly improved. The enhanced photocatalytic activity was mainly attributed to the capture of electrons after doping modification, which inhibition of photogenerated carriers recombination and reduced the gap width. The cyclic treatment experiment of sulfamethoxazole showed that Bi/Ce/g-C3N4 catalysts had good stability. Ecosar evaluation and leaching toxicity test showed that Bi/Ce/g-C3N4 can be safely used for wastewater treatment. This study provides a perfect strategy for modifying g-C3N4 and a new way to improve the photocatalytic performance.

Lignocellulose reconstituted shape-controllable self-supporting carbonaceous capacitance-anodes with high electron transfer rates for high-performance microbial electrochemical system.

Natural biomass is a promising candidate for manufacturing an efficient anode in the microbial electrochemical system (MES) for its abundance and low cost. However, the structure and performance of the electrode highly depend on the biomass species. A simple and sustainable method for creating a self-supporting electrode is proposed by freeze-drying and carbonizing a blend of cellulose, lignin, and hemicellulose. This strategy leads to a cork-like structure and improved mechanical strength of the lignocellulose carbon. A power density of 4780 ± 260 mW m-2 (CLX-800) was achieved, which was the highest record for unmodified lignocellulose-based anodes in the microbial fuel cells. The morphological as lamellar multilayer and rich in hydrophilic functional groups could facilitate the formation of thick electroactive biofilms and enrich Geobacter with the highest abundance of 92.3%. The CLX material is expected to be the ideal electrode for high performance and functionally controllability.

Event-based Semantic Segmentation with Posterior Attention.

In the past years, attention-based Transformers have swept across the field of computer vision, starting a new stage of backbones in semantic segmentation. Nevertheless, semantic segmentation under poor light conditions remains an open problem. Moreover, most papers about semantic segmentation work on images produced by commodity frame-based cameras with a limited framerate, hindering their deployment to auto-driving systems that require instant perception and response at milliseconds. An event camera is a new sensor that generates event data at microseconds and can work in poor light conditions with a high dynamic range. It looks promising to leverage event cameras to enable perception where commodity cameras are incompetent, but algorithms for event data are far from mature. Pioneering researchers stack event data as frames so that event-based segmentation is converted to framebased segmentation, but characteristics of event data are not explored. Noticing that event data naturally highlight moving objects, we propose a posterior attention module that adjusts the standard attention by the prior knowledge provided by event data. The posterior attention module can be readily plugged into many segmentation backbones. Plugging the posterior attention module into a recently proposed SegFormer network, we get EvSegFormer (the event-based version of SegFormer) with state-of-the-art performance in two datasets (MVSEC and DDD-17) collected for event-based segmentation. Code is available at https://github.com/zexiJia/EvSegFormer to facilitate research on event-based vision.

Polyethyleneimine-induced fluorescence enhancement strategy for AIEgen: the mechanism and application.

Aggregation-induced emission luminogens (AIEgens) are attracting extensive research attention in the biosensor fields. Herein, we report a new polyethyleneimine (PEI)-induced strategy for enhancing luminescence of TCBPE (an AIEgen) to promote its development in biosensor. The copolymer dots (TCBPE-PEI) with high quantum yield (39.7%) and outstanding stability were synthesized via a one-pot method. The fluorescence enhancement mechanism based on the PEI strategy originated from the restriction of intramolecular motions of TCBPEs and the form of donor-acceptor structures to decrease the inherent energy bandgap. Benefiting from chelating property of TCBPE-PEI by Cu2+, a fluorescence-quenching sensor for Cu2+ detection was developed based on the fluorescence quenching of the electron transfer effect. Especially, a good linear range of 10-250 nM with a low limit of detection 1.1 nM was achieved, and it was further applied in samples successfully. The current work provides a novel approach to fabricate AIEgen biosensors and shows great potential in Cu2+ detection.

Migration electric-field assisted electrocoagulation with sponge biochar capacitive electrode for advanced wastewater phosphorus removal.

Migrating electric field-assisted electrocoagulation (MEAEC) is a three-electrode electrochemical system, including waste flour-derived sponge biochar (SBC) as an adsorption electrode for efficient phosphorus removal from wastewater. The SBC was applied in the MEAEC system as a pseudo capacitance electrode with low energy consumption and reached an excellent effluent level (0.12 mg/L) with a 200-s treatment time in 1 mg/L phosphate synthetic wastewater. The SBC adsorption electrode had a total charge capacitance of 1.14 F/g with abundant micropores. Continuous charging and discharging at a constant voltage over 100 cycles demonstrated the excellent durability of the biochar electrodes. The energy demand of SBC-MEAEC was only 0.0058 kWh/m3 for 90% phosphate removal, which was 65% less than that of the control. The use of SBC in the MEAEC system greatly enhanced phosphate removal at low concentrations. In the SBC-MEAEC system, the electro-desorption synchronous electrocoagulation process demonstrated efficient concentration and release of ions after electro-adsorption. These results indicate that MEAEC with an SBC electrode could achieve a high level of phosphate removal with a much lower energy consumption than in previous studies. The recovered concentrated phosphorus flocs also contained fewer metal impurities than those in previous electrochemical approaches. The proposed desorption synchronous electrocoagulation utilizing waste-derived SBC electrodes provides a cost-effective pathway to treat low phosphorous-containing wastewater.

A three-dimensional phenolic-based carbon anode for microbial electrochemical system with customized macroscopic pore structure to promote interior bacteria colonization.

Microbial electrochemical system (MES) is an emerging wastewater treatment technology that compensates the energy demands of containments removal by in situ converting the chemical energy of organic pollutants. As the structure for exoelectrogens and the reaction site of extracellular electron transfer (EET), the anode is essential for MES. The future commercial application of MES requires efficiency and large-scale fabrication available anode. In this study, a 3D anode with millimeter-scale pores (3D-MPA) was successfully constructed by sacrificial template method, with low-cost phenolic resin as carbon precursor and polymethyl methacrylate (PMMA) pellets as template. With customized and ordered pore of 1 mm, the 3D-MPAs allowed the microorganisms to colonize inside, improving anodic space utilization efficiency. Different carbonization temperature in tested range from 700 °C to 1000 °C regulated the micrometer-scale convex structures and surface roughness of 3D-MPAs, causing electrochemical performance changes. The 3D-MPA-900 obtained the largest electroactive surface area (102 ± 4.1 cm2) and smallest ohmic resistance (1.8 ± 0.09 Ω). Equipped with MES, 3D-MPA-900 reached the highest power density and current density (2590 ± 25 mW m-2 and 5.20 ± 0.07 A m-2). Among tested 3D-MPA, the excellent performance of 3D-MPA-900 might be attributed by its convex structures with suitable size and surface coverage. The surface roughness of 3D-MPA-900 enhanced the microorganism adherence, which then promoted EET on anode surface. Generally, phenolic-based 3D-MPA made of sacrificial-template method had controllable porous structure, large-scale fabrication availability, high chemical stability and excellent mechanical property, which could be promising for the commercial application of MES.

Enhanced electricity generation and storage by nitrogen-doped hierarchically porous carbon modification of the capacitive bioanode in microbial fuel cells.

Microbial fuel cells (MFCs) can potentially be utilized for power generation, but their low power density and low energy storage capabilities remain major bottlenecks for their large-scale development. In this research, a simplistic nitrogen-doped hierarchically porous carbon material (HPC-A) was developed through a one-step carbonization and activation process and was successfully hot-pressed on the carbon cloth (CC) substrate. This process fabricates capacitive bioanodes (HPC-A-CC) that can enhance electricity generation and storage in MFCs. The as-prepared HPC-A-CC anode delivered a power density of 2043.6 mW·m-2 and a cumulative total charge (Qm) of 426.4 ± 13.4C·m-2 at each cycle, which was 2.1 and 34.8 times higher than that of the plain CC anode, respectively. This was a result of the hierarchical and interconnected porous structure, improved hydrophilic surface, and increased number of active centers which host the bacteria for enhanced electron transfer. Electrochemical measurements indicated the superior electrochemical activity and capacitive behavior of the HPC-A-CC anode. Furthermore, biofilm analysis revealed that the HPC-A-CC biofilm exhibited higher cell viability and a more uniform spatial distribution. These findings not only demonstrate the potential of HPC-A-CC for power enhancement in MFCs but also provide a feasible solution to the problem of power generation and demand mismatch in MFC applications.

Possible Toxic Mechanisms of Deoxynivalenol (DON) Exposure to Intestinal Barrier Damage and Dysbiosis of the Gut Microbiota in Laying Hens.

Deoxynivalenol is one the of most common mycotoxins in cereals and grains and causes a serious health threat to poultry and farm animals. Our previous study found that DON decreased the production performance of laying hens. It has been reported that DON could exert significant toxic effects on the intestinal barrier and microbiota. However, whether the decline of laying performance is related to intestinal barrier damage, and the underlying mechanisms of DON induced intestine function injury remain largely unclear in laying hens. In this study, 80 Hy-line brown laying hens at 26 weeks were randomly divided into 0, 1, 5 and 10 mg/kg.bw (body weight) DON daily for 6 weeks. The morphology of the duodenum, the expression of inflammation factors and tight junction proteins, and the diversity and abundance of microbiota were analyzed in different levels of DON treated to laying hens. The results demonstrated that the mucosal detachment and reduction of the villi number were presented in different DON treated groups with a dose-effect manner. Additionally, the genes expression of pro-inflammatory factors IL-1ß, IL-8, TNF-α and anti-inflammatory factors IL-10 were increased or decreased at 5 and 10 mg/kg.bw DON groups, respectively. The levels of ZO-1 and claudin-1 expression were significantly decreased in 5 and 10 mg/kg.bw DON groups. Moreover, the alpha diversity including Chao, ACE and Shannon indices were all reduced in DON treated groups. At the phylum level, Firmicutes and Actinobacteria and Bacteroidetes, Proteobacteria, and Spirochaetes were decreased and increased in 10 mg/kg.bw DON group, respectively. At the genus levels, the relative abundance of Clostridium and Lactobacillus in 5 and 10 mg/kg.bw DON groups, and Alkanindiges and Spirochaeta in the 10 mg/kg.bw DON were significantly decreased and increased, respectively. Moreover, there were significant correlation between the expression of tight junction proteins and the relative abundance of Lactobacillus and Succinispira. These results indicated that DON exposure to the laying hens can induce the inflammation and disrupt intestinal tight junctions, suggesting that DON can directly damage barrier function, which may be closely related to the dysbiosis of intestinal microbiota.

Electron-pool promotes interfacial electron transfer efficiency between pyrogenic carbon and anodic microbes.

Relying on surface functional groups and graphitized structure, pyrogenic carbon (PC) was reported to facilitate microbial extracellular electron transfer (EET), which plays a crucial role in diverse biogeochemical reactions. However, little is known about the role of electrical capacitance on EET between microbes and PCs. Here, PCs were obtained from fermented steam bread after carbonization at different temperatures from 700 °C to 1100 °C. PC-900 exhibited the lowest charge transfer resistance and highest electrical capacitance, ascribed to combined effects of graphitic structure and hierarchical porous structure. The interfacial EET was further investigated by enriching electroactive biofilms on PC surface. Faster interfacial EET was demonstrated in PC-900. Maximum power density was proportional to electrical capacitance rather than conductivity. PC-900 enriched the most Geobacter sp., which was positively correlated with electrical capacitance according to the distance-based redundancy analysis. Electrical capacitance was suggested to act as electron pool to facilitate interfacial EET efficiency.

High concentration of ammonia sensitizes the response of microbial electrolysis cells to tetracycline.

Microbial electrolysis cell (MEC) is a promising technology for effective energy conversion of wastewater organics to biogas. Yet, in swine wastewater treatment, the complex contaminants including antibiotics may affect MEC performance, while the high ammonia concentration might increase this risk by increasing cell membrane permeability. In this work, the responses of MECs on tetracycline (TC) with low and high ammonia loadings (80 and 1000 mg L-1) were fully investigated. The TC of 0 to 1 mg L-1 slightly improved MEC performance in current production and electrochemical characteristics with low ammonia loading, while TC ≥ 4 mg L-1 started to show negative effects. Generally, the high ammonia loading sensitized MECs to TC concentration, inducing the current and COD removal of MECs to sharply decline with TC ≥ 0.5 mg L-1. The positive effect of high ammonia loading on MEC due to conductivity increase was counteracted with TC ≥ 1 mg L-1. The co-contamination of TC and ammonia significantly decreased the bioactivity and biomass of anode biofilm. Although the high concentration of co-existing TC and ammonia inhibited MEC performance, the reactors still obtained positive energy feedback. The network analyses indicated that the effluent suspension contributed much to antibiotic resistance gene (ARG) transmission, while the microplastics (MPs) in wastewater greatly raised the risks of ARGs spreading. This work systematically examined the synergetic effects of TC and ammonia and the transmission of ARGs in MEC operation, which is conducive to expediting the application of MECs in swine wastewater treatment.