Hydrothermal microwave-assisted synthesis of LaFeO3 catalyst for N2O decomposition

Lanthanum orthoferrite powders were synthesized via one-step hydrothermal reactions under mild conditions using microwave and conventional heating. The use of microwave irradiation during the synthesis allows one to obtain nanocrystalline LaFeO₃ with a higher yield and reduced crystallite and particle size within a 16 times shorter duration (3 hours) at a lower temperature of 220°C as compared to the conventional heating. The catalytic decomposition of nitrous oxide was performed over both samples, it was shown that the sample obtained under microwave conditions demonstrates enhanced activity as a catalyst: N₂O decomposes completely at 700°C over the catalyst formed at microwave conditions, while the comparative catalyst prepared by conventional heating reaches a lower conversion of only 60% at the same temperature and catalytic reaction conditions.     

On fractional faces of the metric polytope

The integrality recognition problem is considered on a sequence M _{n, k} of nested relaxations of a Boolean quadric polytope, including the rooted semimetric M _n and metric M _{n, 3} polytopes. The constraints of the metric polytope cut off all faces of the rooted semimetric polytope that contain only fractional vertices. This makes it possible to solve the integrality recognition problem on M _n in polynomial time. To solve the integrality recognition problem on the metric polytope, we consider the possibility of cutting off all fractional faces of M _{n, 3} by a certain relaxation M _{n, k} . The coordinates of points of the metric polytope are represented in homogeneous form as a three-dimensional block matrix. We show that in studying the question of cutting off the fractional faces of the metric polytope, it is sufficient to consider only constraints in the form of triangle inequalities.     

Aerobic biological treatment of thermophilically digested sludge

Aerobic biological treatment of digested sludge was studied in a continuously operated laboratory set-up. An aerated reactor was filled with thermophilically digested sludge from the Moscow wastewater treatment plant and inoculated with special activated sludge. It was then operated at the chemostat mode at different flow rates. Processes of nitrification and denitrification, as well as dephosphatation, occurred simultaneously during biological aerobic treatment of thermophilically digested sludge. Under optimal conditions, organic matter degradation was 9.6%, the concentrations of ammonium nitrogen and phosphate decreased by 89 and 83%, respectively, while COD decreased by 12%. Dewaterability of digested sludge improved significantly. The processes were found to depend on hydraulic retention time, oxygen regime, and temperature. The optimal conditions were as follows: hydraulic retention time 3-4 days, temperature 30-35 degrees C, dissolved oxygen levels 0.2-0.5 mg/L at continuous aeration or 0.7-1 mg/L at intermittent aeration. Based on these findings, we propose a new combined technology of wastewater sludge treatment. The technology combines two stages: anaerobic digestion followed by aerobic biological treatment of digested sludge. The proposed technology makes it possible to degrade the sludge with conversion of approximately 45% volatile suspended solids to biogas, to improve nitrogen and phosphorus removal in reject water from sludge treatment units, and to achieve removal of malodorous substances after 8-9 days of anaerobic-aerobic sludge treatment.     

Generating vegetation leaf area index Earth system data record from multiple sensors. Part 2: Implementation,analysis and validation

The evaluation of a new global monthly leaf area index (LAI) data set for the period July 1981 to December 2006 derived from AVHRR Normalized Difference Vegetation Index (NDVI) data is described. The physically based algorithm is detailed in the first of the two part series. Here, the implementation, production and evaluation of the data set are described. The data set is evaluated both by direct comparisons to ground data and indirectly through inter-comparisons with similar data sets. This indirect validation showed satisfactory agreement with existing LAI products, importantly MODIS, at a range of spatial scales, and significant correlations with key climate variables in areas where temperature and precipitation limit plant growth. The data set successfully reproduced well-documented spatio-temporal trends and inter-annual variations in vegetation activity in the northern latitudes and semi-arid tropics. Comparison with plot scale field measurements over homogeneous vegetation patches indicated a 7% underestimation when all major vegetation types are taken into account. The error in mean values obtained from distributions of AVHRR LAI and high-resolution field LAI maps for different biomes is within 0.5 LAI for six out of the ten selected sites. These validation exercises though limited by the amount of field data, and thus less than comprehensive, indicated satisfactory agreement between the LAI product and field measurements. Overall, the inter-comparison with short-term LAI data sets, evaluation of long term trends with known variations in climate variables, and validation with field measurements together build confidence in the utility of this new 26 year LAI record for long term vegetation monitoring and modeling studies.     

Agent-based time delay margin in consensus of multi-agent systems by an event-triggered control method: Concept and computation

This paper deals with defining the concept of agent-based time delay margin and computing its value in multi-agent systems controlled by event-triggered based controllers. The agent-based time delay margin specifying the time delay tolerance of each agent for ensuring consensus in event-triggered controlled multi-agent systems can be considered as complementary for the concept of (network) time delay margin, which has been previously introduced in some literature. In this paper, an event-triggered control method for achieving consensus in multi-agent systems with time delay is considered. It is shown that the Zeno behavior is excluded by applying this method. Then, in a multi-agent system controlled by the considered event-triggered method, the concept of agent-based time delay margin in the presence of a fixed network delay is defined. Moreover, an algorithm for computing the value of the time delay margin for each agent is proposed. Numerical simulation results are also provided to verify the obtained theoretical results.     

Reactive Stresses in Ni<Subscript>49</Subscript>Fe<Subscript>18</Subscript>Ga<Subscript>27</Subscript>Co<Subscript>6</Subscript> Shape-Memory-Alloy Single Crystals

The reactive stresses induced in Ni₄₉Fe₁₈Ga₂₇Co₆-alloy single crystals during martensitic transformations with a limited possibility of shape-memory-strain recovery have been experimentally studied. The data on these crystals are compared with the results obtained previously for Cu–Al–Ni, Ni–Ti, and Ni?Fe–Ga crystals. The potential of application of the Ni₄₉Fe₁₈Ga₂₇Co₆ single crystals in designing drives and power motors is demonstrated.     

The Effect of the Method by Which a High-Resistivity GaN Buffer Layer Is Formed on Properties of InAlN/GaN and AlGaN/GaN Heterostructures with 2D Electron Gas

AlGaN/AlN/GaN and InAlN/AlN/GaN structures with 2D electron gas have been grown on sapphire substrates by metal-organic vapor-phase epitaxy. The suppression of the parasitic conductivity of buffer GaN layers was provided either by intentionally raising the density of edge dislocations or by doping with iron (GaN:Fe). It was shown that using GaN buffer layers with a better crystal perfection and more planar surface results in the electron mobility in the 2D channel for carriers becoming 1.2–1.5 times higher.     

Automated bidding in computational markets: an application in market-based allocation of computing services

Autonomous agents are widely applied to automate interactions in robotics, e.g. for selling and purchasing goods on eBay, and in financial markets, e.g. in the form of quote machines and algorithmic traders. Current research investigates efficient economic mechanisms that fully automate the provisioning and usage processes of Grid-based services. On the one hand, consumers want to allocate resources on demand for their various applications, e.g. data sharing, stream processing, email, business applications and simulations. On the other hand, providers of Grid services want to govern business policies to meet their utilization and profit goals. The above-mentioned processes are not manually manageable, however, because decisions need to be taken within milliseconds. Therefore, such processes have to be automated to minimize human interactions. Hence, market mechanisms and strategic behavior play important roles when it comes to achieving automated and efficient allocation of Grid services. The paper begins by presenting a framework for automated bidding, providing a methodology for the design and implementation of configurable bidding strategies. Second, it presents a novel bidding strategy based on a reinforcement learning technique. This strategy is designed to automate the bid generation processes of consumers and providers in various market mechanisms. Third, the behavior and convergence of the strategy is evaluated in a centralized Continuous Double Auction and a decentralized on-line machine scheduling mechanism against selected benchmark bidding strategies. Fourth, we define a bidding language for communicating consumer and provider preferences to the market as well as report back the match of the market-based allocation process.