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Catalytic upgrading of anisole and guaiacol in an atmospheric dielectric barrier discharge (DBD) plasma reactor was studied. Compared to thermal upgrading in a fixed bed, the DBD plasma method can convert the model compound to benzene and toluene with high selectivity under relatively low temperature. The synergistic effect between H2 plasma and Ni-Mo/SiO2 catalyst is crucial to the high deoxygenation rate. The primary reactions occurring during the DBD upgrading process include demethylation, methyl transfer, and hydrogenolysis. XRD spectra indicate that phase change should not be the primary reason for catalyst deactivation; GC–MS, NH3-TPD, and regeneration experiments show that carbon deposition is the cause for deactivation. NH3-TPD analysis reveals that a combination of medium and strong acid sites plays an important role in the hydrogenolysis of phenols to benzenes. The present work shows DBD catalytic upgrading as a promising route for the C O bond hydrogenolysis reaction.

Individual-based computational environment provides an effective solution to study complex social events by reconstructing scenarios. Challenges remain in reconstructing the virtual scenarios and reproducing the complex evolution. In this paper, we propose a framework to reconstruct a synthetic computational environment, reproduce the epidemic outbreak, and evaluate management interventions in a virtual university. The reconstructed computational environment includes 4 fundamental components: the synthetic population, behavior algorithms, multiple social networks, and geographic campus environment. In the virtual university, influenza H1N1 transmission experiments are conducted, and gradually enhanced interventions are evaluated and compared quantitatively. The experiment results indicate that the reconstructed virtual environment provides a solution to reproduce complex emergencies and evaluate policies to be executed in the real world.

A very active Ni-Mo bimetallic catalyst supported on SiO2 was prepared for the hydrodeoxygenation (HDO) reaction of anisole and guaiacol under a H2 partial pressure of 83 kPa. Generally, transition metal and their oxides were thought to have less HDO activity than others, such as sulfides, carbides, phosphides. However, this work achieved a novel deoxygenation result, where a high conversion (98.7%) at 673–693 °C and atmospheric pressure for the model compounds and high selectivity (> 96%) to aromatic hydrocarbons (BTX) were obtained. Furthermore, the methyl transfer reaction is greatly promoted by abundant acid sites of the catalyst, leading to a low carbon-loss. The present work provides a promising way and new insight for an economic and efficient HDO process for the lignin-derived thermal degradation products.

Emergencies, which are very difficult to be forecasted, would always bring about huge harm to people. Therefore, to find ways to reduce such devastating effects, researches on emergency management have turned to be paramount. Nowadays, the rapid development of computer technology has supplied a new and effective idea for the researches of emergency management, namely that the researches can be done in computers by performing simulation experiments according to the artificial societies, computational experiments, parallel execution (ACP) approach. Guided by this approach, this paper has proposed one agent-based prototype simulation system to research emergency management. Firstly, structure of the simulation system oriented to emergency management was analyzed and designed. Then a simulation system oriented to public health emergency management was constructed to study the transmission of infectious diseases. Finally, several experiments were carried out based on the system, with several significant conclusions having also been obtained.

Computational social science plays an important role in emergency management from a quantitative perspective. Reconstructing an individual-based social computing environment is crucial for both accurate computational experiments and determining optimal decisions. Here, the authors propose a formalization method to define basic componential models in the artificial society and the inner logic in these models. A detailed generation process is presented, and multisource statistical data, social interactive behavior, and multilayer social networks are integrated together. As an evaluation of the proposed framework, a virtual city of Beijing is reconstructed. Each citizen is endowed with demographic attributes, including age, gender, social role, correlated geographic locations, and multiple social relations. The generated synthetic population is statistically equivalent to the real population. Transmission experiments of influenza are performed in the reconstructed computational environment, and individual daily interacting behavior is tracked and analyzed. The results indicate that the framework can provide an effective methodology to reconstruct the computing environment in high resolution by using low-resolution statistical data, leading to better prediction and management of emergencies.

Organically modified silicate (Ormosil) coatings have been synthesized through the sol–gel method for corrosion protection of aluminum alloy. Silica-based unmodified coatings were also designed to investigate the effect of tetraethoxysilane (TEOS) content on the properties of the coatings. The surface morphology of the coatings was characterized by scanning electron microscopy. The corrosion resistance was evaluated by immersion test, electrochemical impedance spectroscopy and potentiodynamic polarization measurements. In addition, the surface potential differences of the coated samples were determined by scanning Kelvin probe. The results showed that a better corrosion resistance of unmodified coating was prepared by controlling the TEOS/EtOH/H2O molar ratio of 0.109/1/1.52. Ormosil coatings provided excellent barrier properties and corrosion resistance in comparison with the unmodified sol–gel coatings. The Ormosil coating modified with triethoxyoctylsilane exhibited corrosion resistance properties superior to the other Ormosil coatings after exposure to 3.5 wt% NaCl solution for 10 days.

Increasing computing capability and high-resolution digital tracing of human behavior make large-scale computational models for individual-based realistic simulation available. Reconstructing a virtual computational environment is crucial for designing and implementing individual interactions in an artificial society as human beings behave in the real world. In this paper, we propose a methodology to recreate a virtual city by utilizing statistical data and geographic information. The synthetic population and physical environment are baseline components of the virtual city. Individual-based modeling is used to specify individuals’ demographic characteristics, and each individual is endowed with heterogeneous social attributes. Various physical environments are generated with geographic locations and mapped with individuals to support daily mobility, migration, and interaction. A series of algorithms are proposed to bridge the gap between macroscopic data and microscopic models, and guarantee equivalence between them. Based on the methodology, we reconstructed a virtual city of Beijing, and presented the statistical analysis of population structure, spatial distribution of physical environments, human travel characteristics, and spatial topologies of social networks. Our synthetic population can represent individual actors in the form of households and household members, and the synthetic population is statistically equivalent to a real population. The proposed methodology is efficient to recreate a synthetic virtual city and can serve as a base for computational experiments.

Ni–Ce three-dimensional material with macropore diameter of 146.6 ± 8.4 nm was synthesized and used as a methanation catalyst. Firstly, H 2 reduction of the catalyst was conducted in the thermal fixed bed and plasma reactor, respectively, then X-ray diffraction (XRD) and CO 2 temperature programmed desorption experiments on the two reduced samples were carried out to reveal the plasma effect on the catalyst's physico-chemical properties. It was found that plasma reduction created more abundant basic sites for CO 2 adsorption, in particular the medium basic sites were even doubled compared with the thermal-reduced catalysts. The plasma-reduced catalyst exhibited excellent low-temperature activity, ca 50–60°C lower than the thermal catalyst (the maximum CO 2 conversion point). Based on the optimum reduced catalyst, plasma effect in the reactor level was further investigated under high gas hour space velocity of approximately 50 000 h −1 . The plasma reactor showed higher CO 2 conversion capacity and efficiency than the thermal reactor.

Social contact networks exhibit overlapping qualities of communities, hierarchical structure and spatial-correlated nature. We propose a mixing pattern of modular and growing hierarchical structures to reconstruct social contact networks by using an individual’s geospatial distribution information in the real world. The hierarchical structure of social contact networks is defined based on the spatial distance between individuals, and edges among individuals are added in turn from the modular layer to the highest layer. It is a gradual process to construct the hierarchical structure: from the basic modular model up to the global network. The proposed model not only shows hierarchically increasing degree distribution and large clustering coefficients in communities, but also exhibits spatial clustering features of individual distributions. As an evaluation of the method, we reconstruct a hierarchical contact network based on the investigation data of a university. Transmission experiments of influenza H1N1 are carried out on the generated social contact networks, and results show that the constructed network is efficient to reproduce the dynamic process of an outbreak and evaluate interventions. The reproduced spread process exhibits that the spatial clustering of infection is accordant with the clustering of network topology. Moreover, the effect of individual topological character on the spread of influenza is analyzed, and the experiment results indicate that the spread is limited by individual daily contact patterns and local clustering topology rather than individual degree.

Agent-based modeling and simulation play an important role in sociological analysis for complex phenomena. The social communication behaviors can be reproduced by interactive agents, who can behave like human beings. In this paper, we propose a simulation framework of multilayer social networks to model high-resolution interaction between agents. The agent model contains three components: social networks, a demographic-based population and a schedule-based behavior. A common description of multilayer heterogeneous networks is presented. To evaluate the performance of the proposed framework, we reproduce the transmission of influenza H1N1 in an artificial classroom, and compare the simulation results with a real outbreak of influenza H1N1 at one university in Langfang, 2009. The simulation results show high correlation between social networks and the transmission of influenza, and demonstrate that individual-based social network models can well reproduce and analyze complex interacting behavior. Furthermore, experiments under controlled conditions are carried out to analyze the sensitivity of alternative parameters. The framework is able to model high-resolution, social communications from multiple aspects.

The centrality of a node is a crucial indicator to understand how important this node is in a network, and several measures of centrality have been used to realize the identification. In this paper, we propose a new one named load centrality based on the betweenness changes caused by the removal of some nodes in the network. This measure of centrality combines the ideas: more important node is closer to others and more important node stands between more node pairs. By comparing with the other point centrality measures, the load centrality is validated further.

Social contact between individuals is the chief factor for airborne epidemic transmission among the crowd. Social contact networks, which describe the contact relationships among individuals, always exhibit overlapping qualities of communities, hierarchical structure and spatial-correlated. We find that traditional global targeted immunization strategy would lose its superiority in controlling the epidemic propagation in the social contact networks with modular and hierarchical structure. Therefore, we propose a hierarchical targeted immunization strategy to settle this problem. In this novel strategy, importance of the hierarchical structure is considered. Transmission control experiments of influenza H1N1 are carried out based on a modular and hierarchical network model. Results obtained indicate that hierarchical structure of the network is more critical than the degrees of the immunized targets and the modular network layer is the most important for the epidemic propagation control. Finally, the efficacy and stability of this novel immunization strategy have been validated as well., Highlights • We pointed out the disadvantage of traditional targeted immunization. • We proposed a hierarchical targeted immunization strategy to improve the disease control better. • We analyzed the importance of hierarchical structure in a network in controlling epidemic propagation. • We validated the efficiency and stability of the hierarchical targeted immunization strategy.

Emergency management is crucial to finding effective ways to minimize or even eliminate the damage of emergent events, but there still exists no quantified method to study the events by computation. Statistical algorithms, such as susceptible-infected-recovered (SIR) models on epidemic transmission, ignore many details, thus always influencing the spread of emergent events. In this paper, we first propose an agent-based modeling and experiment framework to model the real world with the emergent events. The model of the real world is called artificial society, which is composed of agent model, agent activity model, and environment model, and it employs finite state automata (FSA) as its modeling paradigm. An artificial campus, on which a series of experiments are done to analyze the key factors of the acute hemorrhagic conjunctivitis (AHC) transmission, is then constructed to illustrate how our method works on the emergency management. Intervention measures and optional configurations (such as the isolation period) of them for the emergency management are also given through the evaluations in these experiments.

Emergencies always bring about lots of huge harm to people and are very difficult to be forecasted. Therefore, researches on emergency management have been hot to find the ways to reduce their devastating effect on human beings. This paper proposed one method using agent-based simulation to research emergency management according to ACP (Artificial Societies, Computational Experiments, Parallel Execution) approach. Firstly, the structure of a simulation system oriented to emergency management was analyzed and designed. Then a simulation system oriented to public health emergency management was constructed to study the transmission of infectious diseases. Finally, two experiments were carried out based on the system.

Multi-agent generation within a special scene is a basic problem for the research on artificial society. In the context of public health emergency, the multi-agent model of an artificial campus is built; based on the deep analysis of the problem, we consider that a special scene in artificial society is approximate to a polygon determined by some key points (border points). Therefore the problem of multi-agent generation is converted to inner-point generation in the polygon. The grid-based method is proposed to divide the scene polygon reasonably consistent to the density. The filtering mechanism of grids generated is proposed. Finally, the experiment shows that the method could be used to generate some agents with some properties in a special scene randomly, and has certain reference value.

According to the outbreak of H1N1 influenza on campus in Langfang city, Hebei province, at north of China in 2009, this paper constructed an artificial society model of the school, and simulated the spread of H1N1 influenza at the fifth floor in dormitory building. Firstly, it built the geographic environment model in accordance with the real dormitory building and a social relationship network model, including classmates, roommates and playmates. Secondly, it designed the behaviors and activities of students during a day, and built role based agent models of student. Each agent student had three roles, which were susceptible, infectious and recovered student. Finally, it conducted simulation experiments to compare the emergency measures of segregating nonclassmates and segregating non-roommates.

Network centric warfare (NCW) need to be supported by modeling and simulation systems, and the interoperability between different simulation systems is an important aspect to realize cooperation of varied military simulation systems and establish common simulation environment. However, complexities of the NCW and individual military simulation systems make the interoperability difficult to achieve. A large body of work shows that interoperability of NCW simulation is not only a technical problem, but also involves factors like human being's behavior, modeling mechanism, and application environment of the simulation systems which raises the interoperability complexity rapidly. We believe that modeling is the root where interoperability gaps and complexity problems come from, build a layered interoperability model of NCW simulation with the theory of levels of conceptual interoperability model (LCIM), and put forwards some challenges about how to achieve NCW simulation interoperability.

Agent based computational modeling and simulation can capture human behaviors, emergency events, and complex social networks from the bottom up. The construction of artificial society is system engineering that the bottom simulation platform needs to be designed for multi regions’ experiments and engineering realization. Influenza H1N1 that outbreak in 2009 is modeled and simulated in the platform. Based on statistic cases, an artificial classroom with agent student and agent teacher has been constructed in an artificial campus. The artificial classroom is described from three parts: agent, environment, and emergency model. Role based agent demographic catalog, “time-location-behavior” social behaviors mode, and group based social networks have been characterized and built up. Computational experiments are carried on in the artificial classroom, and results indicate that the spread of influenza H1N1 among high density of population is related to demographic attributes, behaviors, and social networks.