Real-time heuristic search methods are used by situated agents in applications that require the amount of planning per move to be independent of the problem size. Such agents plan only a few actions at a time in a local search space and avoid getting trapped in local minima by improving their heuristic function over time. We extend a wide class of real-time search algorithms with automatically-built state abstraction and prove completeness and convergence of the resulting family of algorithms. We then analyze the impact of abstraction in an extensive empirical study in real-time pathfinding. Abstraction is found to improve efficiency by providing better trading offs between planning time, learning speed and other negatively correlated performance measures.

An isocratic elution pressurized CEC (pCEC) system was used to separate and determine ten carbamate insecticides. It was found that introduction of the electrical field, supplementary pressure, and SDS in the proposed method greatly improved the speed, column efficiency, selectivity, and repeatability for separation and determination of carbamates. On a capillary column of 75 microm ID packed with 3 microm octadecyl silica, baseline separation and detection of ten analytes was performed by using a mobile phase consisting of 30% v/v ACN and 70% v/v of 5 mmol/L ammonium acetate (pH 6.5) containing 1 mmol/L SDS and 0.01% triethylamine (TEA). Under the optimum conditions ten carbamate insecticides could be completely separated within 20 min. For the real vegetable samples, an SPE procedure for the cleanup of matrices was carried out prior to pCEC analysis. The detection limits of 0.05-1.6 mg/kg for ten carbamates and mean recoveries of 51.3-109.2% for eight kinds of vegetable samples at different concentrations of carbamates with RSD less than 11.4% were obtained, respectively. The proposed method has been proved to be effective in the rapid analysis of carbamate residues in vegetables.

Abstract:The cataluminescence (CTL) of benzene and the benzene homologues toluene and xylene on nanosized γ-Al 2 O 3 doped with Eu 2 O 3 (γ-Al 2 O 3 /Eu 2 O 3 ) was studied and a sensor of determining these gases was designed. The proposed sensor showed high sensitivity and selectivity at an optimal temperature of 432 ºC, a wavelength of 425 nm and a flow rate of 400 mL/min. Quantitative analysis was performed at the optimal conditions. The linear ranges of CTL intensity versus concentration of the benzene homologues were as follows: benzene 2.4~5000 mL/m 3 , toluene 4.0~5000 mL/m 3 and xylene 6.8~5000 mL/m 3 , with detection limits (3σ) of 1.8 mL/m 3 , 3.0 mL/m 3 and 3.4 mL/m 3 for each one, respectively. The response time of this system was less than 3 s. The coexistence of other gases, such as SO 2, CO and NH 3, caused interference at levels around 11.7%, 5.8% and 8.9% respectively. The technique is a convenient and fast way of determining the vapors of benzene homologues in air.

We explore the task of designing an efficient multi-agent system that is capable of capturing a single moving target, assuming that every agent knows the location of all agents on a fixed known graph. Many existing approaches are suboptimal as they do not coordinate multiple pursuers and are slow as they re-plan each time the target moves, which makes them fare poorly in real-time pursuit scenarios such as video games. We address these shortcomings by developing the concept of cover set, which leads to a measure that takes advantage of information about the position and speed of each agent. We first define cover set and then present an algorithm that uses cover to coordinate multiple pursuers. We compare the effectiveness of this algorithm against several classic and state-of-the-art pursuit algorithms, along several performance measures. We also compute the optimal pursuit policy for several small grids, and use the associated optimal scores as yardsticks for our analysis.

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