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Artificial photosynthesis for high-value hydrogen peroxide (H2O2) through a two-electron reduction reaction is a green and sustainable strategy. However, the development of highly active H2O2 photocatalysts is impeded by severe carrier recombination, ineffective active sites, and low surface reaction efficiency. We developed a dual optimization strategy to load dense Ni nanoparticles onto ultrathin porous graphitic carbon nitride (Ni-UPGCN). In the absence and presence of sacrificial agents, Ni-UPGCN achieved H2O2 production rates of 169 and 4116 µmol g-1 h-1 with AQY (apparent quantum efficiency) at 420 nm of 3.14% and 17.71%. Forming a Schottky junction, the surface-modified Ni nanoparticles broaden the light absorption boundary and facilitate charge separation, which act as active sites, promoting O2 adsorption and reducing the formation energy of *OOH (reaction intermediate). This results in a substantial improvement in both H2O2 generation activity and selectivity. The Schottky junction of dual modulation strategy provides novel insights into the advancement of highly effective photocatalytic agents for the photosynthesis of H2O2.
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Converting CO2 to olefins is an ideal route to achieve carbon neutrality. However, selective hydrogenation to light olefins, especially single-component olefin, while reducing CH4 formation remains a great challenge. Herein, we developed ZnZrOx /SSZ-13 tandem catalyst for the highly selective hydrogenation of CO2 to light olefins. This catalyst shows C2 = -C4 = and propylene selectivity up to 89.4 % and 52 %, respectively, while CH4 is suppressed down to 2 %, and there is no obvious deactivation. It is demonstrated that the isolated moderate Brønsted acid sites (BAS) of SSZ-13 promotes the rapid conversion of intermediate species derived from ZnZrOx , thereby enhancing the kinetic coupling of the reactions and inhibit the formation of alkanes and improve the light olefins selectivity. Besides, the weaker BAS of SSZ-13 promote the conversion of intermediates into aromatics with 4-6 methyl groups, which is conducive to the aromatics cycle. Accordingly, more propene can be obtained by elevating the Si/Al ratio of SSZ-13. This provides an efficient strategy for CO2 hydrogenation to light olefins with high selectivity.
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INTRODUCTION: Citri Sarcodactylis Fructus (CSF) is widely used as a food ingredient and a traditional Chinese medicine. In China, CSF is cultivated in many places, including Sichuan, Guangdong, Zhejiang, and Fujian provinces. The types and chemical contents of CSF from different origins may vary greatly due to the difference in climate and environmental conditions. Therefore, comparing the chemical composition of CSF from various places is vital. OBJECTIVE: To rapidly select potential characteristic compounds for differentiating CSF from different origins. MATERIAL AND METHODS: Thirty-one batches of CSF samples from different regions were analysed using ultra-performance liquid chromatography with hybrid quadrupole-orbitrap high-resolution mass spectrometry. Thereafter, chemometric methods, including principal component analysis (PCA) and orthogonal partial least squares discrimination analysis (OPLS-DA), were employed to find differential metabolites among the CSF samples from various origins. RESULTS: PCA revealed 77.9% of the total variance and divided all CSF samples into three categories corresponding to their origins. OPLS-DA displayed better discrimination of CSF from different sources, with R2 X, R2 Y, and Q2 of 0.801, 0.985, and 0.849, respectively. Finally, 203 differential metabolites were obtained from CSF from different origins using the variable importance in projection of the OPLS-DA model, 30 of which were identified, and five coumarin compounds were selected as marker compounds discriminating CSF from different origins. CONCLUSION: This work provides a practical strategy for classifying CSF from different origins and offers a research foundation for the quality control of CSF.
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Citrus/química , Medicamentos de Ervas Chinesas , Cromatografia Líquida de Alta Pressão , Medicamentos de Ervas Chinesas/análise , Frutas , Geografia , Espectrometria de Massas , Medicina Tradicional Chinesa , Análise de Componente PrincipalRESUMO
As a promising metal-free photocatalyst, graphitic carbon nitride (g-C3N4) is still limited by insufficient visible light absorption and rapid recombination of photogenerated carriers, resulting in low photocatalytic activity. Here, we adjusted the microstructure of the pristine bulk-g-C3N4 (PCN) and further loaded silver (Ag) nanoparticles. Abundant Ag nanoparticles were grown on the thin-layer g-C3N4 nanosheets (CNNS), and the Ag nanoparticles decorated g-C3N4 nanosheets (Ag@CNNS) were successfully synthesized. The thin-layer nanosheet-like structure was not only beneficial for the loading of Ag nanoparticles but also for the adsorption and activation of reactants via exposing more active sites. Moreover, the surface plasmon resonance (SPR) effect induced by Ag nanoparticles enhanced the absorption of visible light by narrowing the band gap of the substrate. Meanwhile, the composite band structure effectively promoted the separation and transfer of carriers. Benefiting from these merits, the Ag@CNNS reached a superior hydrogen peroxide (H2O2) yield of 120.53 µmol/g/h under visible light irradiation in pure water (about 8.0 times higher than that of PCN), significantly surpassing most previous reports. The design method of manipulating the microstructure of the catalyst combined with the modification of metal nanoparticles provides a new idea for the rational development and application of efficient photocatalysts.
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It is commonly believed that the Hamiltonian approach applies only to linear systems, or nonlinear systems with proper linearization procedures. In this Letter, we show that the Hamiltonian approach based on linear coupled-mode theory applies very well for cross-mode modulation, i.e., field variation of the probe light induced by a strong co-propagating pump light in a degenerate mode group. By deriving eigenvalues and eigenvectors of the nonlinear system, evolution of the probe light can be obtained, which agrees with numerical simulations of multimode nonlinear Schrödinger equations. Using the Hamiltonian approach, a simple approach for determining the pump mode for realizing arbitrary mode conversion is discussed. Two concrete scenarios of the optically induced vector mode conversions within the LP11-mode group are further exemplified.
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The prospect of Line-of-Business Services (LoBSs) for infrastructure of Emerging Sensor Networks (ESNs) is exciting. Access control remains a top challenge in this scenario as the service provider's server contains a lot of valuable resources. LoBSs' users are very diverse as they may come from a wide range of locations with vastly different characteristics. Cost of joining could be low and in many cases, intruders are eligible users conducting malicious actions. As a result, user access should be adjusted dynamically. Assessing LoBSs' risk dynamically based on both frequency and threat degree of malicious operations is therefore necessary. In this paper, we proposed a Quantitative Risk Assessment Model (QRAM) involving frequency and threat degree based on value at risk. To quantify the threat degree as an elementary intrusion effort, we amend the influence coefficient of risk indexes in the network security situation assessment model. To quantify threat frequency as intrusion trace effort, we make use of multiple behavior information fusion. Under the influence of intrusion trace, we adapt the historical simulation method of value at risk to dynamically access LoBSs' risk. Simulation based on existing data is used to select appropriate parameters for QRAM. Our simulation results show that the duration influence on elementary intrusion effort is reasonable when the normalized parameter is 1000. Likewise, the time window of intrusion trace and the weight between objective risk and subjective risk can be set to 10 s and 0.5, respectively. While our focus is to develop QRAM for assessing the risk of LoBSs for infrastructure of ESNs dynamically involving frequency and threat degree, we believe it is also appropriate for other scenarios in cloud computing.
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Polybrominated diphenyl ethers (PBDEs) are widespread in marine ecosystems, despite the limits placed on several congeners, and pose a threat to marine organisms. Many coexisting factors, especially dissolved organic matter (DOM), affect the environmental behavior and ecological risk of PBDEs. Since blooms frequently occur in coastal waters, we used algogenic DOM (A-DOM) from the diatom Skeletonem costatum and examined the interaction of A-DOM with 2,2',4,4'-tetrabromodiphenyl ether (BDE-47). Moreover, their combined effect on the rotifer Brachionus plicatilis was analyzed. During the stationary period, A-DOM had more proteins than polysaccharides, and 7 extracellular proteins were identified. A-DOM fluorescence was statically quenched by BDE-47, and amide, carbonyl, and hydroxyl groups in A-DOM were involved. Molecular docking analysis showed that all 5 selected proteins of A-DOM could spontaneously bind with BDE-47 and that hydrophobic interactions, van der Waals forces and pi-bond interactions existed. The reproductive damage, oxidative stress and inhibition of mitochondrial activity induced by BDE-47 in rotifers were relieved by A-DOM addition. Transcriptomic analysis further showed that A-DOM could activate energy metabolic pathways in rotifers and upregulate genes encoding metabolic detoxification proteins and DNA repair. Moreover, A-DOM alleviated the interference effect of BDE-47 on lysosomes, the extracellular matrix pathway and the calcium signaling system. Alcian blue staining and scanning electron microscopy showed that A-DOM aggregates were mainly stuck to the corona and cuticular surface of the rotifers; this mechanism, rather than a real increase in uptake, was the reason for enhanced bioconcentration. This study reveals the complex role of marine A-DOM in PBDEs bioavailability and enhances the knowledge related to risk assessments of PBDE-like contaminants in marine environments.
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Rotíferos , Poluentes Químicos da Água , Animais , Zooplâncton/metabolismo , Éteres Difenil Halogenados/análise , Ecossistema , Matéria Orgânica Dissolvida , Simulação de Acoplamento Molecular , Poluentes Químicos da Água/análise , Rotíferos/fisiologiaRESUMO
High concentrations of organic aerosol (OA) occur in Asian countries, leading to great health burdens. Clean air actions have resulted in significant emission reductions of air pollutants in China. However, long-term nation-wide trends in OA and their causes remain unknown. Here, we present both observational and model evidence demonstrating widespread decreases with a greater reduction in primary OA than in secondary OA (SOA) in China during the period of 2013 to 2020. Most of the decline is attributed to reduced residential fuel burning while the interannual variability in SOA may have been driven by meteorological variations. We find contrasting effects of reducing NOx and SO2 on SOA production which may have led to slight overall increases in SOA. Our findings highlight the importance of clean energy replacements in multiple sectors on achieving air-quality targets because of high OA precursor emissions and fluctuating chemical and meteorological conditions.
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ZnZrO/Mg-Si-ZSM-5 tandem catalysts enable CO2 hydrogenation to para-xylene (PX) with PX selectivity up to 28% and a proportion of PX in xylene up to 84%. SiO2 and MgO modification increases the PX selectivity by reducing the Brønsted acid sites and reducing the pore size of the zeolite.
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Dióxido de Carbono , Dióxido de Silício , Xilenos , HidrogenaçãoRESUMO
Preciously assessing the creep mechanical response of sand-geomembrane interfaces is vital for the design of relevant engineering applications, which is inevitable to be influenced by temperature and stress statuses. In this paper, based on the self-developed temperature-controlled large interface shear apparatus, a series of long-term creep shear tests on textured geomembrane-silica sand interfaces in different temperatures, normal pressure, and creep shear pressure were conducted, and a database compiled from the physical creep shear test results is constructed. By adopting the database, three disparate machine learning algorithms of the Back Propagation Artificial Neural Network (BPANN), the Support Vector Machine (SVM) and the Extreme Learning Machine (ELM) were adopted to assess the long-term creep mechanical properties of sand-geomembrane interfaces while also considering the influence of temperature. Then, the forecasting results of the different algorithms was compared and analyzed. Furthermore, by using the optimal machine learning model, sensitivity analysis was carried out. The research indicated that the BPANN model has the best forecasting performance according to the statistics criteria of the Root-Mean-Square Error, the Correlation Coefficient, Wilmot's Index of Agreement, and the Mean Absolute Percentage Error among the developed models. Temperature is the most important influence factor on the creep interface mechanical properties, followed with time. The research findings can support the operating safety of the related engineering facilities installed with the geomembrane.
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Organophosphorus flame retardants (OPFRs) are frequently detected in aquatic environments and can potentially amplify the food chain, posing a potential risk to organisms. Marine invertebrates have primitive nervous systems to regulate behavior, but how they respond to OPFRs that are potentially neurotoxic substances is unclear. This study assessed changes in the feeding behavior of rotifer Brachionus plicatilis exposed to alkyl OPFRs tributyl phosphate (TnBP) (0.376 nM, 3.76 and 22.53 µM) to elucidate the mechanism of behavioral toxicity. TnBP at 22.53 µM reduced the ingestion and filtration rates of rotifers for Chlorella vulgaris and Phaeocystis globosa in a 24-h test and altered rotifer-P. globosa population dynamics in 15-d coculture. Ciliary beat frequency was also reduced, and the expression of genes encoding the cilia axoneme was downregulated. TnBP could inhibit rotifer acetylcholinesterase activity by binding this protein and reduce the expression of the exocytotic membrane protein syntaxin-4, suggesting a disorder in nervous regulation of cilia beat. Moreover, TnBP induced abnormal shape and dysfunction of mitochondria, which caused insufficient energy required for ciliary movement. This study revealed diverse neurotoxicity mechanisms of TnBP, particularly as a potentially competing acetylcholinesterase ligand for aquatic invertebrates. Our research also provides a meaningful reference for OPFR-induced behavioral toxicity assessments.
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Chlorella vulgaris , Retardadores de Chama , Rotíferos , Animais , Acetilcolinesterase/metabolismo , Cílios/metabolismo , Chlorella vulgaris/metabolismo , Axonema/metabolismo , Rotíferos/metabolismo , Organofosfatos , Comportamento Alimentar , Compostos OrganofosforadosRESUMO
Pharmaceuticals derived from the raw materials of Periplanattica americana have been applied for wound healing, liver disease treatment, and antitumor therapy. However, the resulting residues of P. americana have not been well exploited. We found that P. americana residues comprised high amounts of chitin (PC) and polysaccharides (PAP) exhibit good biological activity. Compared to shrimp-derived chitin, PC has a smaller molecular weight (Mv), lower crystallinity, and looser molecular structure, demonstrating stronger antioxidant activity and degradability. After adding the PAP, the PC solution rapidly lost fluidity and formed a hydrogel (P/PCGEL) that had antioxidation, biodegradability, and injectability properties and exhibited rapid coagulation, good water absorption and retention, and a low hemolysis rate (HR). In vivo studies reported that the P/PCGEL reduced edema during burns, accelerated collagen synthesis and deposition, reduced reactive oxygen species (ROS) levels, and increased superoxide dismutase (SOD) levels, thereby reducing the inflammatory response, avoiding oxidative stress, and effectively promoting wound healing. Furthermore, the P/PCGEL demonstrated good biocompatibility, rapid biodegradation, and injectability, thereby reducing the risk of trauma and infection engendered by repeated wound opening and dressing changes. These properties also demonstrated the potential application for this hydrogel in preparing injectable hydrogel excipients. Hence, this study provided a hydrogel-formed wound dressing comprising pure natural ingredients and offering convenient administration, economic availability, and strong tissue repair ability.
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Quitina , Hidrogéis , Hidrogéis/química , Antioxidantes/farmacologia , Cicatrização , Bandagens , Polissacarídeos , AntibacterianosRESUMO
Aims: The current guidelines recommend aortic valve intervention in patients with severe aortic regurgitation (AR) with the onset of symptoms, left ventricular enlargement, or systolic dysfunction. Recent studies have suggested that we might be missing the window of early intervention in a significant number of patients by following the guidelines. Methods and results: The overarching goal was to determine if machine learning (ML)-based algorithms could be trained to identify patients at risk for death from AR independent of aortic valve replacement (AVR). Models were trained with five-fold cross-validation on a dataset of 1035 patients, and performance was reported on an independent dataset of 207 patients. Optimal predictive performance was observed with a conditional random survival forest model. A subset of 19/41 variables was selected for inclusion in the final model. Variable selection was performed with 10-fold cross-validation using random survival forest model. The top variables included were age, body surface area, body mass index, diastolic blood pressure, New York Heart Association class, AVR, comorbidities, ejection fraction, end-diastolic volume, and end-systolic dimension, and the relative variable importance averaged across five splits of cross-validation in each repeat were evaluated. The concordance index for predicting survival of the best-performing model was 0.84 at 1 year, 0.86 at 2 years, and 0.87 overall, respectively. Conclusion: Using common echocardiographic parameters and patient characteristics, we successfully trained multiple ML models to predict survival in patients with severe AR. This technique could be applied to identify high-risk patients who would benefit from early intervention, thereby improving patient outcomes.
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Photocatalytic two-electron oxygen reduction to produce high-value hydrogen peroxide (H2O2) is gaining popularity as a promising avenue of research. However, structural evolution mechanisms of catalytically active sites in the entire photosynthetic H2O2 system remains unclear and seriously hinders the development of highly-active and stable H2O2 photocatalysts. Herein, we report a high-loading Ni single-atom photocatalyst for efficient H2O2 synthesis in pure water, achieving an apparent quantum yield of 10.9% at 420 nm and a solar-to-chemical conversion efficiency of 0.82%. Importantly, using in situ synchrotron X-ray absorption spectroscopy and Raman spectroscopy we directly observe that initial Ni-N3 sites dynamically transform into high-valent O1-Ni-N2 sites after O2 adsorption and further evolve to form a key *OOH intermediate before finally forming HOO-Ni-N2. Theoretical calculations and experiments further reveal that the evolution of the active sites structure reduces the formation energy barrier of *OOH and suppresses the O=O bond dissociation, leading to improved H2O2 production activity and selectivity.
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A coupled linear ultrasonic motor (LUSM) based on an eccentric constraint was proposed. Two pieces of oblique piezoelectric ceramics were arranged at each end of the elastomer, and the polarization direction of the ceramics was vertically upward. Using the tilting characteristics of the piezoelectric ceramics, the two ends of the fixed piezoelectric ceramics formed an eccentric restraint on the motor, providing conditions for the motor to generate coupled modes. When the elastomer of the motor generated the coupling vibration, the motion trajectories of the driving feet ends were oblique straight lines, and the oblique straight-line motion trajectories of the upper and lower driving feet ends were in opposite directions, driving the upper and lower sliders to run simultaneously. The stator parameters were optimized by using ANSYS to obtain larger amplitudes for the ends of the driving feet in both X and Z directions. The structure and operation principle of the motor are explained in detail. A prototype was fabricated to study the arrangement scheme with fixed constraints at the ends of the motor. The frequency-velocity characteristics, voltage-velocity characteristics, and mechanical characteristics of the motor were tested. The no-load speed and maximum output power were measured to be 45.9 mm/s and 3.24 mW.
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OBJECTIVE: This study aimed to establish a deep learning method based on convolutional networks for the preliminary study of the pathological diagnosis of prosthetic joint infections (PJI). METHODS: We enrolled 20 revision patients after joint replacement from the Department of Orthopedics, the First Medical Center, General Hospital of the People's Liberation Army, from January 2021 to January 2022 (10 of whom were confirmed to be infected against 2018 ICM criteria, and the remaining 10 were verified to be non-infected), and classified high-power field images according to 2018 ICM criteria. Then, we inputted 576 positive images and 576 negative images into a neural network by employing a resNET model, used to select 461 positive images and 461 negative images as training sets, 57 positive images and 31 negative images as internal verification sets, 115 positive images and 115 negative images as external test sets. RESULTS: The resNET model classification was used to analyze the pathological sections of PJI patients under high magnification fields. The results of internal validation set showed a positive accuracy of 96.49%, a negative accuracy of 87.09%, an average accuracy of 93.22%, an average recall rate 96.49%, and an F1 of 0.9482. The accuracy of external test results was 97.39% positive, 93.04% negative, the average accuracy of external test set was 93.33%, the average recall rate was 97.39%, with an F1 of 0.9482. The AUC area of the intelligent image-reading diagnosis system was 0.8136. CONCLUSIONS: This study used the convolutional neural network deep learning to identify high-magnification images from pathological sections of soft tissues around joints, against the diagnostic criteria for acute infection, and a high precision and a high recall rate were accomplished. The results of this technique confirmed that better results could be achieved by comparing the new method with the standard strategies in terms of diagnostic accuracy. Continuous upgrading of extended training sets is needed to improve the diagnostic accuracy of the convolutional network deep learning before it is applied to clinical practice.
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Phase transition is a physical phenomenon that attracts great interest of researchers. Although the theory of second-order phase transitions is well-established, their atomic-scale dynamics in polycrystalline materials remains elusive. In this work, second-order phase transitions in polycrystalline Cu2 Se at the transition temperature are directly observed by in situ aberration-corrected transmission electron microscopy. Phase transitions in microcrystalline Cu2 Se start at the grain boundaries and extend inside the grains. This phenomenon is more pronounced in nanosized grains. Analysis of phase transitions in nanocrystalline Cu2 Se with different grain boundaries demonstrates that grain boundary energy dominates unsynchronized phase transition behavior. This suggests that the energy of grain boundaries is the key factor influencing the energetic barrier for initiation of phase transition. The findings advance atomic-scale understanding of second-order phase transitions, which is crucial for the control of this process in polycrystalline materials.
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Information capacity of single-mode fiber communication systems face fundamental limitations imposed by optical nonlinearities. Spatial division multiplexing (SDM) offers a new dimension for upgrading fiber communication systems. Many enabling integrated devices, such as mode multiplexers and multimode bending with low crosstalk, have been developed. On the other hand, all-optical signal processing (AOSP) can avoid optical to electrical to optical (O-E-O) conversion, which may potentially allow for a low cost and green operation for large-scale signal processing applications. In this paper, we show that the system performance of AOSP can be pushed further by benefiting from the existing technologies developed in spatial mode multiplexing (SDM). By identifying key technologies to balance the impacts from mode-dependent loss, crosstalk and nonlinearities, three-channel 40 Gbit/s optical logic operations are demonstrated using the first three spatial modes in a single multimode waveguide. The fabricated device has a broadband four-wave mixing operation bandwidth (>20 nm) as well as high conversion efficiency (>-20 dB) for all spatial modes, showing the potential for a large-scale signal processing capacity with the combination of wavelength division multiplexing (WDM) and SDM in the future.
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A novel macro-architectures material Fe3O4-N-GO@sodium alginate (SA) gel film was successfully produced, which was used to remove series azo dye wastewater. The optimal adsorption rates were attained, which achieved the maximum removal efficiency of 74.22%, 45.72%, 37.75% for Congo Red, Acid Orange 7 and Amino Black 10B respectively, under the condition that the mass ratio of Fe3O4-N-GO to sodium alginate was 0.11. The optimal adsorption temperature for three dyes was 30 â and the adsorption equilibrium was reached at 150 min. The adsorption kinetic model of Fe3O4-N-GO@SA for the three azo dyes conformed to the quasi-second-order reaction model, and the adsorption isotherm was more in line with the Freundlich adsorption. The adsorption mechanism was multi-layer heterogeneous adsorption under the combined action of physical adsorption and chemisorption, and chemisorption was the main step of controlling the speed. The study would provide theoretical basis for the application of macro-architectures material in environment.
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Águas Residuárias , Poluentes Químicos da Água , Adsorção , Compostos Azo , Corantes , Vermelho Congo , Concentração de Íons de Hidrogênio , CinéticaRESUMO
This work studied bacterial community structure and gene function prediction in long-term running of dual graphene modified bioelectrode bioelectrochemical systems (LT D-GM-BE BES, 2 year). The maximum power density of LT D-GM-BE BES was 99.03 ± 3.64 mW/m2, which was 3.66 times of dual control BES (D-C-BE BES), and the transfer resistance of LT GM-BE was just approximately 1/4 of control bioelectrode (C-BE). Proteobacteria and Firmicutes were dominant bacteria in long-term modified bioanode (LT GM-BA, 30.03% and 45.64%), and in long-term modified biocathode (LT GM-BC) was Armatimonadetes (47.14%) in phylum level. The dominant bacteria in LT GM-BA was Clostridium (30.56%), in GM-BC was Chthonomonas (47.14%) in genus level. Gene function related with substrate, energy metabolism and environmental adaptation were enriched. LT GM-BE was tended to enrich dominant bacteria and enrich gene to adapt to micro-environmental changes. This study would provide metagenomics information for long-term running of BES in future.