The prediction of community evolution events in dynamic social networks is of great importance for network security alerts. Currently, most of the common prediction models use a fixed timeframe ...division strategy to divide the dynamic social network, such as the disjoint timeframe division strategy and overlapping timeframe division strategy. However, these frameworks cannot change once they are selected, and are not suitable for the prediction of network evolution with strong variability in real-world applications. In this paper, a new community evolution model is developed from the perspective of the universality of the timeframe, and a new optimized timeframe partitioning algorithm is proposed. Compared with the traditional fixed timeframe partitioning algorithm, this method adaptively adjusts the size and number of time windows according to the information fluctuations of the specific network at an acceptable extra computational cost. Based on the analysis of several real-world networks, we found that the proposed self-adaptive timeframe partitioning algorithm improved the quality of community tracking of the network and ensured the accuracy of prediction events.
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•Selective Na+ stress improved protease activity and promoted DOMs biodegradation.•Na+ stress induced bacteria screening with reduced species richness and diversity.•Selective Na+ ...stress facilitated “SCFAs-producing” microbial community formation.•Salt-tolerant acidogens were enriched and vulnerable methanogens were inhibited.•Na+ stress is prime inducement to modify microbial community for SCFAs accumulation.
The short-chain fatty acids (SCFAs) production was facilitated in Na+ assistant anaerobic fermentation of waste activated sludge, whereas the relevant micro-ecosystem characteristics were unclear. This work explored the microbial community and hydrolases shifts under Na+ stress. It demonstrated that the selective Na+ stress increased protease activities to 126–160% while inhibiting α-glucosidase activities to 83.1–91.3%. Correspondingly, the biodegradation rates of protein and glucose were improved from 25.6% and 45.8% to 39.0% and 55.2%, respectively. Furthermore, the microbial species richness and biodiversity gradually decreased, attributing to Na+-induced cell lysis. Selective Na+ stress was the prime inducement for microbial community evolution and promoted “SCFAs-producing” bacterial community formation by “bacteria-screening” roles. Overall, the hydrolytic bacteria and acidogens became dominant bacteria, which were resistive to Na+ stress, while the SCFAs consumers were restrained as they are salinity-sensitive. Such microbial community shift modified functional metabolisms for enhancing anaerobic fermentation performance. The pathways for metabolism and genetic information processing were improved, positively relating to the facilitated catabolism of fermentation substrates. Consequently, the mechanism of maximized SCFAs accumulation by selective Na+ stress was proposed, i.e. microbial modification of fermentation ecosystem for facilitating sludge hydrolysis and acidification with impeded methanogenesis.
•Establish a connection between the evolution of social networks and real social events.•Capture the “impact” of social events on social networks through the change point detection model on temporal ...networks.•Reveal the microstructure evolution mechanism implicit in social events through the evolution of communities.•Explain the patterns of human behavior behind social events in two real social network cases.
The social network is closely related to people’s lives. And social events are the products of the human subjective initiative during the evolution of networks. Therefore, there is a close correlation between social events and network evolution. This paper studies the characteristics of network evolution corresponding to social events from the perspective of temporal networks. The change point detection method is applied to capture the “shocks” of social events on the network structure. Then, the patterns of structural changes are analyzed based on the theory of community evolution. Experiments on two cases illustrate that social events are significant milestones to promote the development of social networks. And the mesostructure is the intermediary connecting evolving network and social events.
Intra-urban origin-destination (OD) network communities evolve throughout the day, indicating changing groups of closely connected regions. Under such variation, groups of regions with high ...consistency of community affiliation characterize the temporally stable structure of the evolution process, supporting comprehending urban dynamics. However, how to quantify this consistency and identify the associated region groups are open questions. In this study, we introduce the consensus OD network to quantify the consistency of community affiliation among regions. Furthermore, the temporally stable community decomposition method is proposed to identify groups of regions with high internal and low external consistency (named “stable groups”), where each group consists of temporally stable cores and attaching peripheries. Wuhan taxi data is used to verify our methods. On the hourly time scale, eleven stable groups containing 82.9 % of regions are identified. This high percentage suggests that dynamic communities can be well organized via cores. Moreover, stable groups are spatially closed and more likely to distribute within a single district and separated by water bodies. Cores exhibit higher point of interest (POI) entropy and more healthcare and shopping services than peripheries. Our methods and empirical findings contribute to some practical issues, such as urban area division, polycentric evaluation and construction, and infectious disease control.
•Community evolution throughout the day is analyzed from the stability perspective•Consensus origin-destination network is introduced to quantify the consistency of community affiliation among regions•Region groups with high internal and low external consistency are detected, each comprising cores and peripheries•Groups are more likely to distribute within a single district and separated by water bodies•Cores have a higher point of interest entropy and the number of shopping and healthcare services than peripheries.
•Anammox granules were fast-transformed using a nitrification-denitrification sludge.•Maximum nitrogen removal rate of the EGSB reactor reached 7.25±0.16 gN/L/d.•Candidatus Brocadia and Candidatus ...Kuenenia were enriched in the sludge.•Anammox bacteria abundance increased from 2.5% to 29.0% after 300 days.
A lengthy start-up period has been one of the key obstacles limiting the application of the anammox process. In this investigation, a nitrification-denitrification sludge was used to start-up the anammox EGSB process. The transformation process from nitrification-denitrification sludge to anammox granule sludge was explored through the aspects of nitrogen removal performance, granule properties, microbial community structure, and evolution route. A successful start-up of the anammox process was achieved after 94 days of reactor operation. The highest nitrogen removal rate (NRR) obtained was 7.25±0.16 gN/L/d at a nitrogen loading rate (NLR) of 8.0 gN/L/d, and the corresponding nitrogen removal efficiency was a high 90.61±1.99%. The results of the microbial analysis revealed significant changes in anammox bacteria, nitrifying bacteria, and denitrifying bacteria in the sludge. Notably, the anammox bacteria abundance increased from 2.5% to 29.0% during the operation, and Candidatus Kuenenia and Candidatus Brocadia were the dominant genera. Distinct-different successions on Candidatus Brocadia and Candidatus Kuenenia were also observed over the long-term period. In addition, the settling performance, anammox activity and biomass retention capacity of the granules were significantly enhanced during this process, and the corresponding granule evolution route was also proposed. The results in this study indicate the feasibility of using available seed sludge source for the fast-transformation of anammox granules, it is beneficial to the large-scale application of anammox process and the utilization of excess sludge.
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•Similar influents in varied processes lead to similar sludge microbial community.•HGT might mainly occur in an aeration tank rather than the anaerobic/anoxic tank.•Higher ...co-occurrence of potential pathogens and ARGs in wastewater than in sludge.•Microbial biomass mainly drive ARGs in wastewater, while MGEs drive ARGs in sludge.•Enhancement in nutrients removal and tertiary treatment would benefit ARGs removal.
The evolution of microbial community and the fate of ARGs along different full-scale wastewater treatment processes (i.e., Anaerobic-Anoxic-Oxic, Oxidation Ditch, and Cyclic Activated Sludge System) were investigated in this study. We found that the sludges of bioreactors treating similar influent showed the similar microbial communities, independent of the treatment technologies. The horizontal gene transfer (HGT) mainly occurred in aeration tank rather that anaerobic/anoxic tank. More co-occurrence of potential pathogens and ARGs was found in wastewater than in sludge. Microbial biomass was the key driver for the fate of ARGs in wastewater, while mobile genetic elements (MGEs) was the key factor for the fate of ARGs in sludge. Combination of wastewater characteristics, microbial diversity, microbial biomass, and MGEs contributed to the variation of ARGs. Finally, it was found that enhanced nutrients removal process and tertiary treatment would benefit ARGs removal.
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•Solar intermittent-powered electromethanogenesis achieved efficient CO2 reduction.•Higher bicarbonate loading promoted the redox activity of electrode biofilms.•Increased HCO3− ...facilitated electron transfer and lowered charge transfer resistance.•More functional mcrA genes were upregulated with elevated bicarbonates.•Basophilic Methanobacterium alcaliphilum occupied predominated at the biocathode.
Microbial electromethanogenesis (EM), as a sustainable bioderived carbon-neutrality catalyzing platform, can be accelerated and regulated by weak power input for carbon fixation into value-added bioenergy. Solar electricity as a day-night intermittent renewable resource has been verified to effectively drive microbes to capture carbon dioxide (CO2). However, understanding the influence mechanisms of higher CO2 loading on EM is of intrinsic significance yet lacking. Herein, natural solar-powered bioelectrocatalytic CO2 reduction to methane (CH4) under increasing bicarbonate concentrations was investigated. CH4 recovery for the long-term measurement showed that CH4 production rate positively responded to improved bicarbonate concentrations from 2.5 to 10.0 g HCO3−·L−1, exhibiting a robust and potent competence in CH4 yield compared to reported EM. Whereas exceed bicarbonate mainly contributed to raised pH in the solution resulting in the proton limitation despite the intermittent driven-mode could mitigate pH shock. Electrochemistry results demonstrated that higher bicarbonate concentrations promoted the redox activity of electrode biofilm and lowered the system resistances, especially the charge transfer resistance. Adequately improving CO2 loading can dynamically optimize the structure of anodic electroactive microorganisms and facilitate electron transfer. Furthermore, more functional cathodic mcrA genes were upregulated with elevated bicarbonates and the species of basophilic Methanobacterium alcaliphilum occupied predominated at the cathode. These findings open up a perspective avenue to carbon reduction using natural solar intermittent-powered EM.
Microbial biodegradation plays a key role in determining the fate of estrogens and can be affected by the background nutrients in natural environments. However, information on how microbial community ...and nutrient conditions influence estrogen biodegradation is very limited. In this study, 13C-17β-estradiol (13C-E2) was supplied to sediments from the Central Area (CA), Gonghu (GH), Meiliang (ML), and Zhushan (ZS) Bays of Taihu Lake to investigate shifts in bacterial community structure associated with 13C-E2 mineralization over a 30-day incubation period, and the relationships between the background nutrients and cumulative 13C-E2 mineralization rates. The cumulative 13C-E2 mineralization rate for ZS Bay was 87.40% on Day 30, which was significantly greater (P < 0.05) than the rates for ML Bay (67.74%), GH Bay (62.79%), and the CA (52.60%). A correlation analysis suggested that the cumulative 13C-E2 mineralization rate was significantly and positively related to the concentrations of total organic carbon (P < 0.01), nitrate-nitrogen (P < 0.05), ammonia-nitrogen (P < 0.001), and dissolved phosphorus (P < 0.001) in the sediments. Although the highest relative abundances of Proteobacteria, Actinobacteria, Bacteroidetes, and Firmicutes (contain most estrogen-degrading bacteria) were not initially in the ZS Bay sediment, the addition of 13C-E2 stimulated their growth in all sediments, with the greatest increases observed for ZS Bay. At the genus level, the cumulative increases of seven genera (Nitrosomonas, Bacillus, Pseudomonas, Sphingomonas, Novosphingobium, Alcaligenes and Mycobacterium) considered to be associated with E2 degradation were also highest for ZS Bay (80.2 times), followed by ML Bay (39.8 times), GH Bay (28.1 times), and CA (19.0 times). Besides the higher nutrient concentrations, the responses of bacteria to 13C-E2 addition in ZS Bay could also explain it having the highest cumulative 13C-E2 mineralization rate. These results indicate both the background nutrients and bacterial community evolution in the sediments determined the 13C-E2 mineralization rates.
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•13C-E2 mineralization rate varied significantly among the four sediments.•13C-E2 mineralization rate was positively related to nutrient concentrations.•The addition of 13C-E2 exerted a selective pressure on certain bacterial groups.•Bacterial community evolution was responsible for the E2 mineralization.
This paper presents a survey of previous studies done on the problem of tracking community evolution over time in dynamic social networks. This problem is of crucial importance in the field of social ...network analysis. The goal of our paper is to classify existing methods dealing with the issue. We propose a classification of various methods for tracking community evolution in dynamic social networks into four main approaches using as a criterion the functioning principle: the first one is based on independent successive static detection and matching; the second is based on dependent successive static detection; the third is based on simultaneous study of all stages of community evolution; finally, the fourth and last one concerns methods working directly on temporal networks. Our paper starts by giving basic concepts about social networks, community structure and strategies for evaluating community detection methods. Then, it describes the different approaches, and exposes the strengths as well as the weaknesses of each.
Bio-hydrogen production based on lignocellulosic biomass provide clean and neutral route for bio-fuels production with promising prospective. In this work, we used a hydrogen-producing enriched ...consortium and explored a syntrophic co-fermentation model to evaluate microbial community evolution and carbon transfer route of co-fermentation system with lignocellulosic biomass for hydrogen production. Maximum hydrogen production levels of 165.4 mL/g with mean hydrogen concentrations of 52.3% were recorded. Community evolution analysis revealed that the main contributor to hydrogen production was photosynthetic bacterium with about 70% contribution. Anaerobic bacteria were involved in lignocellulosic degradation and carbon transfer processes. In addition, some non-hydrogen producing microbes perform beneficial effects of metabolic adjustment by consuming accumulative organic acids to maintain stable hydrogen production. This study shows that the syntrophic co-fermentation system has the potential for clean energy production with sustainable supply prospective.
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•A syntrophic cofermentation model for bio-hydrogen production was explored.•Abundant microbial community support the high rate of hydrogen production.•The predominant microorganisms exhibit stable abundance and play a key role in hydrogen production.•Community evolution help to release organic acid stress and enhance hydrogen production.
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