Geobacteracea are distinct for their ability to reduce insoluble oxidants including minerals and electrodes without apparent reliance on soluble extracellular electron transfer (ET) mediators. This ...property makes them important anode catalysts in new generation microbial fuel cells (MFCs) because it obviates the need to replenish ET mediators otherwise necessary to sustain power. Here we report cyclic voltammetry (CV) of biofilms of wild type (WT) and mutant G. sulfurreducens strains grown on graphite cloth anodes acting as electron acceptors with acetate as the electron donor. Our analysis indicates that WT biofilms contain a conductive network of bound ET mediators in which OmcZ (outer membrane c-type cytochrome Z) participates in homogeneous ET (through the biofilm bulk) while OmcB mediates heterogeneous ET (across the biofilm/electrode interface); that type IV pili are important in both reactions; that OmcS plays a secondary role in homogenous ET; that OmcE, important in Fe(iii) oxide reduction, is not involved in either reaction; that catalytic current is limited overall by the rate of microbial uptake of acetate; that protons generated from acetate oxidation act as charge compensating ions in homogenous ET; and that homogenous ET, when accelerated by fast voltammetric scan rates, is limited by diffusion of protons within the biofilm. These results provide the first direct electrochemical evidence substantiating utilization of bound ET mediators by Geobacter biofilms and the distinct roles of OmcB and OmcZ in the extracellular ET properties of anode-reducing G. sulfurreducens.
Using tracking data obtained from the smartphone and Internet survey, a data-driven machine learning method is proposed to identify trip ends. In previous literature, this is usually done based on ...some predefined rules, which have been confirmed to be valid. Nonetheless, these rule-based methods largely depend on researchers' own knowledge, which is inevitably subjective and arbitrary. Moreover, they are not effective enough to process the huge amount of data in the era of big data. In this paper, millions of smartphone-based GPS tracking data are targeted. A group of attributes, such as travel speed, distance, and heading, are derived to characterize the smartphone holders' travel status. In other words, the tracking points could be identified as being at the state of traveling or non-traveling, based on which the trip ends are easily detected. In contrast to those rule-based methods, a random forest is utilized in this paper as the classification model, with no subjective rules predefined for classification. This data-driven model is automatically built. The results show that after training the GPS tracking data of 1393 days and the prompted recall (PR) survey data using the random forest, the accuracy of trip ends identification on tracking data of 697 days is 96.17%. The current analysis is free from personal experiences, which is expected to be useful for the smartphone-based survey data in the era of big data.
Abstract
The efficiency of sunlight-driven reduction of carbon dioxide (CO
2
), a process mimicking the photosynthesis in nature that integrates the light harvester and electrolysis cell to convert ...CO
2
into valuable chemicals, is greatly limited by the sluggish kinetics of oxygen evolution in pH-neutral conditions. Current non-noble metal oxide catalysts developed to drive oxygen evolution in alkaline solution have poor performance in neutral solutions. Here we report a highly active and stable oxygen evolution catalyst in neutral pH, Brownmillerite Sr
2
GaCoO
5
, with the specific activity about one order of magnitude higher than that of widely used iridium oxide catalyst. Using Sr
2
GaCoO
5
to catalyze oxygen evolution, the integrated CO
2
reduction achieves the average solar-to-CO efficiency of 13.9% with no appreciable performance degradation in 19 h of operation. Our results not only set a record for the efficiency in sunlight-driven CO
2
reduction, but open new opportunities towards the realization of practical CO
2
reduction systems.
Deciding an optimal location of a transportation facility and automotive service enterprise is an interesting and important issue in the area of facility location allocation (FLA). In practice, some ...factors, i.e., customer demands, allocations, and locations of customers and facilities, are changing, and thus, it features with uncertainty. To account for this uncertainty, some researchers have addressed the stochastic time and cost issues of FLA. A new FLA research issue arises when decision makers want to minimize the transportation time of customers and their transportation cost while ensuring customers to arrive at their desired destination within some specific time and cost. By taking the vehicle inspection station as a typical automotive service enterprise example, this paper presents a novel stochastic multiobjective optimization to address it. This work builds two practical stochastic multiobjective programs subject to stochastic demand, varying velocity, and regional constraints. A hybrid intelligent algorithm integrating stochastic simulation and multiobjective teaching-learning-based optimization algorithm is proposed to solve the proposed programs. This approach is applied to a real-world location problem of a vehicle inspection station in Fushun, China. The results show that this is able to produce satisfactory Pareto solutions for an actual vehicle inspection station location problem.
In this perspective, we highlight results of a research consortium devoted to advancing understanding of oxygen reduction reaction (ORR) catalysis as a means to inform fuel cell science. We ...demonstrate how targeted collaborations between different institutions from academic, national lab, and industry backgrounds and different scientific disciplines like theory, experiment, and characterization can yield unique insights into fuel cell catalysts. We comment on such insights into material designs for platinum-group-metal alloys, transition metal oxides, and non-traditional materials including metal-organic frameworks; systems that have served as the foundational building blocks for our consortium. We also motivate a renewed focus on catalyst durability in light of emerging technological requirements and paths forward in understanding
in situ
and
operando
electrochemical stability. Finally, we describe new frontiers ORR research can take and how emerging artificial intelligence tools can assist researchers in capturing data, selecting new experiments, and guiding characterization to accelerate the design and discovery of fuel cell catalysts. A main goal of sharing this perspective is to discuss the rationale for our future research plans based on our consortium work. However, we also hope to illustrate both the potential impact of a collaborative strategy with the hopes of inspiring a higher degree of Industry-Academia-National Laboratory collaboration and encourage other centers and consortiums to distill and share their findings in a similar perspective-type article. Together we hope to enable the fuel cell research community to engage in a discussion of strategies for research and accelerated development of catalysts with improved activity and stability.
In this perspective, we highlight results of a research consortium devoted to advancing understanding of oxygen reduction reaction (ORR) catalysis as a means to inform fuel cell science.
Based on relevant complex network theory, this paper analyzes the characterization parameters of traffic network complexity, such as the causes of traffic congestion and evacuation models. From the ...perspective of the traffic capacity of traffic network nodes, combined with the transit time of each road, model is proposed for selecting the weights of congestion evacuation nodes. According to the evacuation target, combined with characteristic parameters, such as node degree, node strength, clustering coefficient and closeness, the grey system evaluation method and the analytic hierarchy process (AHP)are combined. Based on the grey relational analysis model, a model is established for determining the priority connectivity evaluation value of each node. The complex characteristics of the actual traffic network in the Chaoyang District of Changchun City are analyzed, then the selection weights of each node of the traffic network are obtained. Having defined the distance between complex network nodes, a congestion evacuation path selection model is proposed, and an evacuation path scheme is given for specified start and end points.
A bypassing behavior model was proposed, in which the local optimal decision behavior in the strategy level was modeled in velocity–time domain, to describe how pedestrians bypass the local obstacles ...considering the relative speed.
The model contains (1) pedestrian visual and contact information acquisition; (2) motion state prediction of the local obstacles based on the visual and contact information; (3) pedestrian bypass strategy modeling in the velocity–time domain; (4) moving and overlapping solution. In the numerical solution, velocity domain was divided into n equal angle, the value of n ranges from 2 to infinity, the Manhattan space was refined gradually to Euclid Space accordingly, in which the movement of pedestrians was described.
The model was applied to the analysis of pedestrian arching at the bottleneck in the emergent evacuation situation. (1) The results showed that the formation of the pedestrian arching at the bottleneck was deformation pressure, because many pedestrians try to pass through the bottleneck simultaneously, even in the absence of friction, the pedestrian arching still occurs; (2) In the emergent situation, we are more concerned about the bottleneck attribution of resistance to form the arching, the calculation and simulation results showed that the probability of an arching and the bottleneck width is an exponential function relationship, so when the stampede occurs in the middle of the bottleneck, the probability of arching will increase exponentially.
•Velocity–time domain was constructed for modeling behavior decision.•Bypassing strategy of pedestrian behavior was modeled in the velocity–time domain.•The expectation time of the pedestrian arching at the bottleneck is depending on the width of the exit exponentially.
Harvesting electricity from the environment, organic wastes, or renewable biomass with microbial fuel cells (MFCs) is an appealing strategy, but the destructive sampling required to investigate the ...anode-associated biofilms has hampered research designed to better understand and optimize microbe-anode interactions. Therefore, a MFC that permits real-time imaging of the anode biofilm with confocal scanning laser microscopy was developed. In this new MFC Geobacter sulfurreducens, an organism closely related to those often found on MFC anodes and capable of high current densities, produced current comparable to that previously reported with other MFC designs. G. sulfurreducens engineered to produce the fluorescent protein mcherry to facilitate real-time imaging produced current comparable to wild-type cells. Introducing C-SNARF-4, a pH-sensitive fluoroprobe, into the anode chamber revealed strong pH gradients within the anode biofilms. The pH decreased with increased proximity to the anode surface and from the exterior to the interior of biofilm pillars. Near the anode surface pH levels were as low as 6.1 compared to ca. 7 in the external medium. Various controls demonstrated that the proton accumulation was associated with current production. Dropping the pH of culture medium from 7 to 6 severely limited the growth of G. sulfurreducens. These results demonstrate that it is feasible to non-destructively monitor the activity of anode biofilms in real time and suggest that the accumulation of protons that are released from organic matter oxidation within anode biofilms can limit current production.
To support urban sustainable development, cities need innovative green logistics solutions to meet the needs of economic development. Crowdshipping is regarded as a promising sustainable freight ...solution. This article aims to assess the feasibility of implementing intercity express crowdshipping using private vehicle traveling. The crowdshipping carrier, who drives his or her private vehicle and travels on the intercity route, carries out the express delivery task between the regional cargo center and the dispatch center along the route. The feasibility assessment covers three parts. First, face-to-face interview and stated preference survey are used to investigate the willingness and preferences of express companies and car owners to participate in crowdshipping activities, respectively. Then, it calculates the environmental benefit and economic benefit brought by the crowdshipping mode in comparison with the traditional mode. The results show that the express companies are willing to pay 30 yuan for each car participating in the crowdshipping activities, and there are considerable numbers of car owners to support this crowdshipping activity, and this crowdshipping activity could bring positive impacts on environment as well as corporate economics. It is hoped that the research could enrich the knowledge of the development of green logistics.
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