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The development of technology and the recent Covid-19 has moved a substantial part of education into online environments, and video-based learning has become a common format of online learning. An alternative to enhance the co-learning experience in video-based online learning is to make use of immersive virtual reality (VR) technology. The current study focused on how to build a sense of being together in an immersive VR classroom for video-based learning, when individual learners can schedule and pace their learning on their own. Two alternative in-class interaction mechanisms for video-based learning were proposed (i.e., real-time interaction and timeline-anchored interaction). The impact of in-class interaction design was investigated, together with the impact of different styles of visual embodiment of learners (i.e., realistic and cartoon-styled), through a laboratory experiment involving 48 participants, and the influences on learners' immersion in a VR classroom, identification with the avatars, perceived social presence of peer learners, and learning outcomes were analyzed. The results showed that enabling in-class interaction with peer learners in VR classrooms enhances immersion in the learning environment and their identification of peer avatars, as well as helping learners to develop a stronger co-presence and more intimate perception of peers. Whereas real-time interaction improves perceived social presence the most, the reduced learning outcome suggests that it may distract learners from the video. The timeline-anchored interaction, on the other hand, improves social presence at no cost of learning performance. Appearance style, however, has no significant influence on learning experiences and outcomes. [ABSTRACT FROM AUTHOR]

Urban-rural integration is the critical process of urbanization, while during this process there are various corresponding problems generated, safety is the most important one, especially at urban-rural fringe areas due to mixed traffic flow and complicated land use. This study intended to investigate the injury severity interaction between urban area and urban-rural fringe area, and explore the correlation within injury severity levels and heterogeneity attributed to unobserved factors. To address the correlation and heterogeneity issues, a grouped random parameters seemingly unrelated bivariate (SUB) probit model was proposed, in which the SUB probit model addressed the correlation of residuals, while the random parameters model accommodated the heterogeneity due to unobserved factors. By comparing the pooled with random parameters models, the results showed that random parameters SUB probit model performed better than the pooled one, and the dataset collected from 2013 to 2017 in Chengdu, China was adopted to illustrate the proposed model. It is found that crash location, speed limit and age of person injured are significant for injury severity in urban and urban-rural fringe areas, but crash form plays a significant role in urban area while number of persons involved should be paid more attention due to injury severity in urban-rural fringe area. Some empirical suggestions are presented to improve the safety in urban and urban-rural fringe areas. [ABSTRACT FROM AUTHOR]

The discrete outcome model is an important method for analyzing the factors affecting crash outcomes. However, the lack of effective approaches for discretizing continuous variables and mining interaction terms are two important problems confronted by such models. To address the above issues, this paper proposes a hybrid approach combining machine learning and econometric modelling to investigate fatal crash types in Shenzhen, China. First, the fatal crash data were collected from 2014 to 2016 in Shenzhen. Second, the minimum description length principle (MDLP), an outstanding representative of supervised discretization algorithms, was used for the discretization of continuous variables in the data. This algorithm selects the proper cut-point through the minimization of the entropy for the given interval. Subsequently, the feature subset selection algorithm based on association rule mining (FEAST), which has advantages over other interaction-mining algorithms in terms of structure freedom and the global search capability, was employed to mine the interaction effects between variables. Finally, the discretized continuous variables and the interaction terms were incorporated into the random parameters logit (RPL) model. Results reveal that the goodness of fit of the MDLP-FEAST-RPL model proposed in this paper is significantly better than that of the equal width discretization (EWD)-RPL, MDLP-RPL, and EWD-FEAST-RPL models. In addition, a total of eleven factors and interaction terms are associated with urban fatal crash types. These findings will facilitate the development of cost-effective policies or countermeasures for targeted crash types in large cities of developing countries. [ABSTRACT FROM AUTHOR]

We provide a novel method to analytically calculate the high-order origin moments of a hypergeometric distribution, that is, the expectation identity method. First, the expectation identity of the hypergeometric distribution is discovered and summarized in a theorem. After that, we analytically calculate the first four origin moments of the hypergeometric distribution by using the expectation identity. Furthermore, we analytically calculate the general kth ( k = 1 , 2 , ... ) origin moment of the hypergeometric distribution by using the expectation identity, and the results are summarized in a theorem. Moreover, we use the general kth origin moment to validate the first four origin moments of the hypergeometric distribution. Next, the coefficients of the first ten origin moments of the hypergeometric distribution are summarized in a table containing Stirling numbers of the second kind. Moreover, the general kth origin moment of the hypergeometric distribution by using the expectation identity is restated by another theorem involving Stirling numbers of the second kind. Finally, we provide some numerical and theoretical results. [ABSTRACT FROM AUTHOR]

This paper develops a multivariate spatial model for the joint analysis of daytime and nighttime crash frequencies by injury severity in traffic analysis zones (TAZs). The model specification allows for spatial correlation across TAZs, heterogeneous effects specific to crash time and severity, and correlations across response types under a Bayesian multivariate conditional autoregressive framework. One hundred and thirty one TAZs in Hong Kong, China, with traffic crash, traffic flow, roadway network, and land use data for a one-year period are selected to calibrate the advocated model. Considerable spatial and heterogeneous effects are found for each type crash frequency. Significant correlations exist in the heterogeneous effects for various severity levels and those for daytime and nighttime. The Bayesian estimates of the regression coefficients reveal that there are significant inconsistencies in the set of factors contributing to zonal daytime and nighttime crashes at various severity levels. [ABSTRACT FROM AUTHOR]

In recent years the pedestrian deaths have been declining, but the pedestrian–vehicle death rate in Croatia is still pretty high. This study intended to investigate the injury severity of pedestrian–vehicle crashes and identify the influencing factors. To achieve this goal, the dataset was firstly collected from Traffic Accident Database System maintained by the Ministry of the Interior, Republic of Croatia from 2015 to 2019, and then latent cluster analysis was employed to identify homogenous clusters from heterogeneous dataset. Based on the classified dataset, unbalanced panel mixed ordered probit model was proposed. By analyzing the classes with different vehicles, the proposed model revealed a more complete understanding of significant variables and showed beneficial performance from the goodness-of-fit, while capturing the impact of exogenous variables to vary among different places, as well as accommodating the heterogeneity issue due to unobserved effects. Findings revealed that the proposed model can be considered as an alternative to determine the factors of injury severity and to deal with the heterogeneity issue. The results may provide potential insights for reducing the injury severity of pedestrian-vehicle crashes. [ABSTRACT FROM AUTHOR]

This study explored the deformation mechanisms and, in particular, the features of particle pair motions in response to shearing. A specially designed biaxial testing system with a flexible boundary equipped with an image system was set up for experimental tests. The whole testing system was modified from a CKC triaxial testing system. The particle image velocimetry (PIV) technique and close-range photogrammetry were used together to help with the investigation. The test samples TA and TB were made of randomly packed 3 D printed elliptical rods with different particle eccentricities e = 0.1, 0.2, respectively. In the examinations, the motion of a particle pair was divided into three modes, i.e. the contact deformation, the Type 4 rolling and the rigid body motion. It is found that each mode of the motion has different contributions to the sample deformation at different strain levels. The normal component of contact deformation dominates volumetric contraction at small strains and dilation at larger strains. The rigid body rotation only induces a slight dilation in sample TA and even leads to contraction in sample TB as the particles used in TB assembly become more elongated. For the sample distortion, it is mainly due to the rigid body rotation while the normal component of contact deformation makes a second contribution. The tangential component of contact deformation and the Type 4 rolling have relatively small contributions to both volumetric strain and sample distortion. The local volumetric strains arising from the contact deformation (including normal and tangential components) and Type 4 rolling mainly take place at the interfaces between moving particle clusters and vortices, also at the boundaries of micro bands or shear bands. The associated local volumetric strain due to the rigid body rotation mainly occurs inside the shear band. [ABSTRACT FROM AUTHOR]

Understanding the characteristics of passenger vehicle use is the prerequisite for effective urban management. However, it has been challenging in the existing literature due to the lack of continuously observed data on passenger vehicle use. Thanks to the advances in data collection and processing techniques, multi-day vehicle trajectory data generated from volunteered passenger cars provide new opportunities for examining in depth how people travel in regular patterns. In this paper, based on a week's operation data of 6600 passenger cars in Shanghai, we develop a systematic approach for identifying trips and travel purposes, and classify vehicles into four categories using a Gaussian-Mixed-Model. A new method is proposed to identify vehicle travel regularities and we use the Z Test to explore differences in travel time and route choices between four types of vehicles. We find that commercially used vehicles present high travel intensity in temporal and spatial aspects and the use intensity in elevated roads is higher for household-used commuting vehicles than semi-commercially used vehicles. The methodologies and conclusions of this paper may provide not only theoretical support for future urban traffic prediction, but also guidance for employing customized active traffic demand management measures to alleviate traffic congestion. [ABSTRACT FROM AUTHOR]

This study provides experimental evidence of the correlation between different fabric tensors in 2D granular assemblies subjected to shearing. Two testing assemblies with different elliptical rods were used and the shearing tests were conducted in a tailor-made biaxial cell. Both the rods and cell were produced using the 3D printing technique. Throughout the shearing, three fabric tensors, i.e., the particle orientation-based, the contact normal-based and the void-based fabric tensors, were studied. In particular, to obtain the void-based fabric tensor, the best-fit ellipse method was used, which can better describe the irregular void geometric information compared with the conventional methods described in the literature. In both samples, a strong linear relationship between the anisotropy intensity factors of the three fabric tensors was found. However, such a correlation was not identified when the void-based fabric tensor was quantified using the conventional methods. The discrepancy demonstrates the importance of properly quantifying the fabric tensor, and by using the best-fit ellipse method, the correlation between the fabric tensors can be better observed, which is crucial to understand the constitutive relationship in granules. [ABSTRACT FROM AUTHOR]

Given the potential difference in drivers' route familiarity, this study aims to investigate the respective factors contributing to local-vehicle and non-local-vehicle crashes on freeway. Crash data from Kaiyang Freeway in Guangdong Province, China in 2014 are collected for the investigation, where the crashes with all involved vehicles registered in the province are labeled as local-vehicle crashes while others are labeled as non-local-vehicle crashes. Bayesian spatial models are developed to build local-vehicle and non-local-vehicle crash frequencies' relationships with traffic characteristics, roadway design, and weather condition. The parameter estimation results indicate that the factors including daily vehicle kilometers traveled, vertical grade, air temperature, and precipitation, impact local-vehicle and non-local-vehicle crash frequencies in the same directions. The proportion of vehicles in Class 1 (e.g., passenger car) impacts the two type crash frequencies in different directions. The proportion of vehicles in Class 3 (e.g., medium-sized bus and truck) and horizontal curvature have significant effects on local-vehicle crashes only. The results are indicative of developing countermeasures from the perspectives of roadway geometry design and driving assistance apps, which aims to reduce freeway crash occurrence. [ABSTRACT FROM AUTHOR]

HBV pol plays a critical role in the replication of hepatitis B virus (HBV). Previous studies conducted on HBV pol have produced limited evidence on HBV pol expression due to the lack of effective detection methods. The present study used the HBV pol (159–406 aa) protein as a target to screen for specific monoclonal antibodies that recognize HBV pol and subsequently evaluate their diagnostic and therapeutic value. Four antibodies (P3, P5, P12, P20) against HBV pol were obtained. Among them, the P20 antibody indicated optimal binding with HBV pol as demonstrated by Western blotting (WB) in a cell model transfected with the HBV genome. We also expressed P5 and P12 antibodies in mouse liver cells by transfection and the results indicated significant antiviral effects caused by these two antibodies especially P12. In summary, the present study established an antibody which was denoted P20. This antibody can be used to detect HBV pol expression by four HBV genomes via WB analysis. In addition, the antibody denoted P12 could exert antiviral effects via intracellular expression, which may provide a promising approach for the treatment of chronic hepatitis B. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the safety and efficacy of the IOPTx™ system – a novel wearable, electroceutical treatment to lower intraocular pressure. Methods: Patients wear the customized contact lens and spectacles of the IOPTx™ system and undergo three 15-minute randomized stimulation trials at different stimulus amplitudes with 15 minutes of rest in between. The parameters for the stimulation trials include a frequency of 50 Hz, a pulse width of 100 µs, and current amplitudes between 90–150 µA. The optometrist measures the intraocular pressure (IOP) before, immediately after, and 15 minutes after the trial, and performs topography, a slit eye examination, and specular microscopy before and after the entire study to check the health of the eye and confirm the safety of the system. Results: The IOPTx™ system successfully modulates a patient's IOP. By testing various currents, we create individual tuning curves examining the effect of the stimulation amplitude on the change in IOP. Each patient may have an optimal dose-response curve and by normalizing to this value, the IOPTx™ system decreased IOP by an average of 17.7% with fifteen minutes of therapy. No Adverse Events or Adverse Device Effects occurred.Conclusions: The results of this clinical case series provide preliminary evidence of efficacy and safety of the IOPTx™ system and its potential usefulness to lower IOP in glaucoma and ocular hypertension. [ABSTRACT FROM AUTHOR]

Plant fiber-reinforced polypropylene composites are low-cost, good-performance and resource-saving, so has wide application prospect in automotive components. While the density of composites increases with the increase in the plant fiber content, the chemical foaming injection process was used to prepare straw fiber/PP foamed composites with exothermic foaming agent azodicarbonamide, in order to reduce the density of composite products and meet the requirements for lightweight automotive trim parts. The effects of temperature and fiber content on the mechanical properties and microstructures of the composites were investigated. Research results show that the microporous straw fiber/PP composites have close bond with the core layer fibers, the matrix, and the cells. The cells evenly distributed around the fibers to form a 'sea island' phase structure of the fiber microporous matrix, and the toughness of microporous sample is better than solid composites. Within a certain range, the cell density and the impact resistance of the microporous composites increases first and then decreases as the molding temperature increases, and maximize at 185 °C. Straw fiber plays a role of nucleation and toughening in the microporous straw fiber/PP composite system. And as its content increases, the cell density increases, similarly the toughness of the composites increases. [ABSTRACT FROM AUTHOR]

In massive open online courses (MOOCs), learners have diverse types of motivation. Learners with different motivations have different interaction behaviours, presence, and learning outcomes. However, scant research has investigated the moderating role of learner motivations in the associations between presence and learning outcomes. This study examined MOOC learner motivation and its moderating role by surveying 646 MOOC learners. By exploratory factor analysis, this study identified four types of motivation: interest in knowledge, curiosity and expansion, connection and recognition, and professional relevance. Based on motivation, the study clustered learners into high-motivation, low-motivation, and asocial learners. Both high-motivation and asocial learners reported strong interest in knowledge and professional relevance, but asocial learners reported the lowest level of connection and recognition among the three groups of learners. Despite the low social presence, the asocial learners still had high levels of cognitive and teaching presence and learning outcomes. In addition, learners with higher presence generally perceived higher cognitive learning, but asocial learners with higher social presence were less satisfied. The results highlight the impacts of specific types of motivation to enrol in MOOCs and suggest designing different environments for learners with different motivation types. [ABSTRACT FROM AUTHOR]

Oncolytic viruses represent a promising therapeutic modality, but they have yet to live up to their therapeutic potential. Safety and efficacy concerns impel us to identify least toxic oncolytic agents that would generate durable and multifaceted anti-tumor immune responses to disrupt the tumors. Here we describe a rational engineered oncolytic herpes virus (OVH) that is a selective killer for targeting tumors, has strong safety records, induces complete regression of tumors in multiple tumor models, and elicits potent antitumor immunity. By far, the potential of OVs in promoting the tumor antigen-specific humoral immune responses remains obscure. In this study, we found that effective treatment by OVH induced immunogenic cell death, which facilitates to elicit humoral immune responses. Depletion experiments revealed that B cells were required for maximal antitumor efficacy of oncolytic immunotherapy. Both serum transfer and antibody treatment experiments revealed that endogenous oncolysis-induced antigen-targeting therapeutic antibodies can lead to systemic tumor regression. Our data demonstrate that tumor-targeting immune modulatory properties confer oncolytic OVH virotherapy as potent immunotherapeutic cancer vaccines that can generate specific and efficacious antitumor humoral responses by eliciting endogenous tumor antigen-targeting therapeutic antibodies in situ, resulting in an efficacious and tumor-specific therapeutic effect. [ABSTRACT FROM AUTHOR]

Interaction is central to any learning experience. Currently, Massive Open Online Courses (MOOCs) rely on discussion forums as a primary means of interaction among learners and instructors. Threaded discussions of such forums help learners to hold an ongoing and recursive discussion over an extended period, but the lack of temporal and spatial contiguity makes it insufficient to deliver a smooth interaction experience. To facilitate such interaction, this study designed DanMOOC, a commenting tool that facilitates timeline-anchored discussion among MOOC learners and instructors. DanMOOC was the first to combine threaded discussions with Danmaku commenting, a video commenting feature that allows viewers of the same video to share comments at the top of the video screen. The design process followed an iterative process of user-centered design. The impact of the new design on learning was assessed empirically through a laboratory experiment comparing DanMOOC with the current MOOC system (video-based learning + forum). The results show that DanMOOC increases learners' perceptions of social, teaching, and cognitive presence, engages learners more in discussion, and improves learners' satisfaction with both the course and the platform. [ABSTRACT FROM AUTHOR]

Problem, research strategy, and findings: Recent research reveals growing spatial disparities in warehousing-related environmental externalities, including air pollution and traffic safety concerns, across municipalities. The existing research, however, fails to present how institutional factors contribute to spatial variations. In this study, I explore how variations in planning practices contribute to the different trajectories of warehousing development. I interviewed planners, local residents, warehousing developers, and regional agency staff to identify local planning practices and policy elements that affect the location choice of warehousing facilities. My results show land use policies (land use permission, industrial zoning, and land parcel division schemes), job-related policies (job creation initiatives and job density requirements), financial incentives (tax rates and financial incentives), and environmental regulations (building design, land use buffering, and landscaping) are the major planning elements that affect warehousing development. Relative to brownfield redevelopment in the municipalities close to the urban core of a metropolitan area, developing greenfield warehousing facilities in suburban cities is likely to cause more environmental concerns in the near future. However, unmeasured factors could be responsible for some of the warehousing development patterns I find in the data. Takeaway for practice: Knowledge, communication, and collaboration are needed to cope with the rapid growth and, in particular, the disproportionate concentration of warehousing-related environmental externalities in certain municipalities. In this study I also provide planning strategies to regulate excessive warehousing development, including land use- and job-related policies, financial incentives, and environmental regulations. With these strategies, planners in warehousing-intensive cities can determine the best way to reduce the impacts of environmental externalities on local communities in the long term. [ABSTRACT FROM AUTHOR]

Objective: E-commerce has increased freight volumes and shifted freight vehicles to local streets and arterials. These changes have caused increasing concern over traffic safety in urban areas, but there has been limited investigation of road safety impacts. To advance understanding of this issue, we examined recent trends in urban freight-related safety in the United States and characteristics of these crashes. Methods: We estimated annual rates of fatal and nonfatal urban freight-related injuries from 2005 through 2015 using data from the NHTSA's Fatal Analysis Reporting System and National Automotive Sampling System General Estimates System. We compared trends in fatal and nonfatal urban freight-related injuries, stratified by road type (interstate vs. not), to overall crash injury trends. We used piecewise linear regression models to test trend changes. We examined and compared specific crash and injury characteristics associated with urban freight-involved crashes, compared to other types of crashes, for the most recent year of data analyzed. Results: Though freight and overall crash fatality rates per vehicle mile traveled declined between 2005 and 2009, increases were observed between 2009 and 2015. Fatality rates increased 3% for all vehicle crashes, 17% for urban freight-involved crashes, and 15% for urban freight-involved crashes not occurring on interstates. Nonfatal injury rates for urban freight-involved crashes rose even more rapidly between 2009 and 2015. Nonfatal injury rates for urban freight-involved crashes increased 45%, rates for urban freight-involved crashes not occurring on interstates increased 40%, and overall nonfatal injury rates for all vehicle crashes increased 3% during this time. Of all urban freight-related crashes resulting in nonfatal injury, the proportion occurring on non-interstate roads increased from 17% to 25% between 2005 and 2015, and these crashes were more likely to occur on weekdays between 6 a.m. and 4 p.m., when freight demand is high, than weekends or evenings. Conclusions: Freight-involved injury and fatality rates are rising more rapidly than overall road traffic-related rates, both in all areas and in urban areas. These crashes are also increasingly occurring on local roads and arterials as opposed to interstates. These findings can help policymakers better understand the changing patterns of freight-related safety issues. As freight volumes increase in commercial and residential areas, planners must increasingly consider freight needs and ensure that space is allocated to this function. Additionally, changes to surveillance systems are necessary to better track burden and risk factors associated with these crashes and inform crash prevention efforts. [ABSTRACT FROM AUTHOR]

Vehicle to vulnerable road user (VRU) crash is a large portion of traffic crashes in China Crash data from Beijing, China from the year 2009 to 2012 are used to identify the factors associated with the likelihood of vehicle to VRU crashes. 180 passenger-vehicles to VRU crashes are collected including 60 vehicle to pedestrian, 60 vehicle to bicycle and 60 vehicle to electric-bicycle cases. Then the statistics of the crash data are carried out, and the variables of human, vehicle, road, environment are investigated. Further, a logic regression model is established to analyse the significance of main contributing factors of these crashes. This paper describes the sample data, which includes time of incident, road user's age and gender, impact speed, crash pattern and VRU's head impact position. Also a comparative research among the three crash types is performed. According to the results, some characteristics of three crash types are different, such as the occurrence time, road position, impact speed and the impact position of VRU's head on the passenger-car. Moreover, chi-square test reveals that night-time travelling, crash type involving pedestrian and speeding of vehicle are significant related to non-fatal/fatal crashes. The logic regression model shows that night-time, intersection, older age of VRU and higher speed of vehicle increased the crash severity. [ABSTRACT FROM PUBLISHER]

Single-vehicle collision is a typical traffic collision, which usually causes heavy casualties and property losses. This study uses crash data during the last five years to obtain the characteristics of injury severity and contributing factors, and further provides some important insights for crash prevention and vehicle safety. Based on the investigation and in-depth data analysis of traffic collisions, 100 serious single-passenger vehicle collisions in Beijing, China, from 2009 to 2013 are collected. Main characteristics of occupant, vehicle, fixed objects, road, environment and their correlations with severity are analysed, respectively. The results demonstrate that time of occurrence, type of date, number of occupants and speed of vehicles are the significant factors related to the severity. And for the total crashes, chi-square test reveals that night time travelling, common weekday, single occupant in vehicle and over 80 km/h vehicle speed are significant related to nonfatal/fatal crashes. A logic regression model shows that driving solo and impacting trees increased the crash severity. Further, this paper discusses the main causation and related safety countermeasures on the serious single-vehicle collisions. [ABSTRACT FROM PUBLISHER]

Accumulation of lipid-laden macrophage foam cells in arterial wall is the hallmark of atherosclerosis, the underlying cause of cardiovascular disease (CVD). Increased uptake of cholesteryl ester-rich modified low-density lipoprotein (LDL) is thought to be responsible for lipid accumulation and strong inverse correlation exists between plasma LDL and CVD. However, despite reaching the target LDL levels significant residual risk for CVD remains. Furthermore, current therapeutic strategies do not lead to regression of existing plaques. This review discusses a change in paradigm emphasizing the importance of removal of cholesterol from macrophage foam cells and final elimination of cholesterol from the body. Intracellular processes involved in this process are described to provide insight into the development of new therapies for CVD. [ABSTRACT FROM AUTHOR]

The bacterial morphology and diversity in the reactors of a combined autotrophic nitritation and sulfur-carbon three-dimensional-electrode denitrification (CANSCTED) process operating under steady-state conditions were investigated by scanning electron microscopy and partial 16S rDNA cloning and sequencing. The CANSCTED process consisted of two parts, i.e., the nitritation membrane bioreactor (NMBR) and the sulfur-carbon three-dimensional-electrode denitrification reactor (SCTED). When the influent NH+4concentration of NMBR ranged from 854 to 1086 mg N L−1, with about 50% NH+4removal efficiency and NO−2accumulation rate, the spherical and spheroidal ammonia-oxidizing bacteria were predominant, with community successions ofβ-Proteobacteria(60.0%),Bacteroidetes(28.3%) andChloroflexi(11.7%). The NMBR effluent with 429∼543 mg N L−1NH+4and 519∼578 mg N L−1NO−2was continuously supplied to SCTED for sulfur denitrification, bioelectrochemical hydrogen denitrification, and anaerobic ammonium oxidation. The predominant bacterial community successions wereβ-Proteobacteria(78.3%) andϵ-Proteobacteria(21.7%). When the SCTED influent was supplied with only NO−2(412–525 mg N L−1) as nitrogen substrate, the predominant bacteria in SCTED were short-bacilliform and spheroidal denitrification bacteria,β-Proteobacteria(82.0%),ϵ-Proteobacteria(16.4%) andγ-Proteobacteria(1.6%). Although the predominant bacterial communities were bothβ-Proteobacteriaandϵ-Proteobacteriain SCTED, the species and quantity of each community varied with the change of SCTED influent composition, which indicated that the composition influence the bacterial morphology and diversity in SCTED. [ABSTRACT FROM AUTHOR]