Parallel best-first search algorithms for planning problems on multi-core processors

The Journal of Supercomputing - The multiplication of computing cores in modern processor units permits revisiting the design of classical algorithms to improve computational performance in complex...     

Competition between isomerization and addition in the Sonication of Vinyl Sulfones in the presence of bromotrichloromethane

(E)- and (Z)-vinyl sulfones isomerise under ultrasound irradiation in carbon tetrachloride in the presence of bromoform or bromotrichloromethane to give an E/Z equilibrium mixture via bromine radicals. Furthermore, the bromine radicals formed add to the CC double bond (presumably of the Z isomer) to form vic-dibromo compounds. In pure CBrCl₃ this addition reaction reaches a 99% yield. In tetrahydrofurane/CBr₄ (or CBrCl₃) no isomerization is observed since the bromine radicals react probably with the THF. The addition is also favoured by highly efficient energy transmission.     

Phase Equilibria and Reactive Chemical Vapor Deposition (RCVD) of Ti<Subscript>3</Subscript>SiC<Subscript>2</Subscript>

The present article addresses the issue of properly modelling the thermodynamic aspect of chemical reactions proceeding at the solid/gas interface in a multi-component system. Attention is more especially paid to the formation of Ti₃SiC₂ by reactive chemical vapor deposition (RCVD) on a silicon carbide substrate heated at 1100 °C. A deposition diagram has been calculated by Gibbs free energy minimization in the C-Cl-H-Si-Ti quinary system. It is shown that this deposition diagram can account for experimental results obtained by RCVD only for the short period of time during which the reaction layer is thin and discontinuous. For thick, dense and continuous reaction layers, the deposition diagram is no longer appropriate and reaction-diffusion models developed for solid-state diffusion couples have to be used in place of it.     

Reactive chemical vapor deposition of Ti3SiC2 with and without pressure pulses: Effect on the ternary carbide texture

Ti₃SiC₂ layers were grown by reactive chemical vapor deposition (RCVD) of a H₂/TiCl₄ gaseous mixture on previously deposited SiC layers. A comparison was made between classical RCVD in which the gases continuously flow at a constant low pressure during several minutes in the reactor and pressure-pulsed RCVD (P-RCVD) in which the reactor is (periodically) (re)filled with the H₂/TiCl₄ gas and (re)emptied every few seconds. Long duration single treatments resulted in similar thick multi-phased coatings growing by solid state diffusion with both RCVD and P-RCVD methods. Conversely, in relation with the steps of nucleation and growth by surface reaction, the repetition of short duration SiC deposition/RCVD sequences with or without pressure pulses gave rise to Ti₃SiC₂ coatings with different textures.     

Metabolomic approach for understanding phenolic compounds and melanoidin roles on antioxidant activity of Indonesia robusta and arabica coffee extracts

Our experiments investigated roles of phenolic compounds and melanoidins on antioxidant activity of Indonesia robusta and arabica coffee extracts. The 2,2,-diphenyl-1-picrylhydrazyl (DPPH) assay and a ferric reducing antioxidant power (FRAP) method were used to determine the antioxidant activity. An increase in the roasting degree (green, light, medium, and dark) reduced phenolic compounds and the antioxidant activity of coffee extracts, but enhanced melanoidin content. Principle component analysis (PCA) demonstrated that phenolic compounds showed stronger effects on antioxidant activity of coffee extracts in comparison with melanoidins. This finding was supported by the results of metabolomic fingerprint by partial least square (PLS), which describes the correlation of functional groups of coffee extracts on antioxidant activity. Based on the PLS analysis, hydroxyl groups (O–H) were observed to show a positive correlation, but carbonyl (C=O) and amine (N–H) groups were attributed to a negative correlation on antioxidant activity of coffee extracts.     

Studying the separability relation between finite state machines

Several authors have studied the relationships between non‐deterministic finite state machines (FSMs). These relationships can be used, for example, for deriving conformance tests from specifications represented by FSMs. In this paper, the separability relation between FSMs is studied. In particular, an algorithm is presented that derives a shortest separating sequence of two non‐deterministic FSMs. Given FSMs S with n states and T with m states, it is shown that the upper bound on the length of a shortest separating sequence is 2^mn−1. Moreover, the upper bound is shown to be reachable. However, according to the conducted experiments, on average, the length of a shortest separating sequence of FSMs S and T states is less than mn and the existence of a separating sequence significantly depends on the number of non‐deterministic transitions in these FSMs. The proposed algorithm can also be used for deriving a separating sequence of two different states of a single FSM or for deriving a separating sequence of three or more FSMs. Copyright © 2007 John Wiley & Sons, Ltd.     

LEAD: a methodology for learning efficient approaches to medical diagnosis.

Determining the most efficient use of diagnostic tests is one of the complex issues facing medical practitioners. With the soaring cost of healthcare, particularly in the US, there is a critical need for cutting costs of diagnostic tests, while achieving a higher level of diagnostic accuracy. This paper develops a learning based methodology that, based on patient information, recommends test(s) that optimize a suitable measure of diagnostic performance. A comprehensive performance measure is developed that accounts for the costs of testing, morbidity, and mortality associated with the tests, and time taken to reach diagnosis. The performance measure also accounts for the diagnostic ability of the tests. The methodology combines tools from the fields of data mining (rough set theory, in particular), utility theory, Markov decision processes (MDP), and reinforcement learning (RL). The rough set theory is used in extracting diagnostic information in the form of rules from the medical databases. Utility theory is used in bringing various nonhomogenous performance measures into one cost based measure. An MDP model together with an RL algorithm facilitates obtaining efficient testing strategies. The methodology is implemented on a sample problem of diagnosing solitary pulmonary nodule (SPN). The results obtained are compared with those from four alternative testing strategies. Our methodology holds significant promise to improve the process of medical diagnosis.