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Decision and Inhibitory Trees for Decision Tables with Many-Valued Decisions(2018-06-06)Decision trees are one of the most commonly used tools in decision analysis, knowledge representation, machine learning, etc., for its simplicity and interpretability. We consider an extension of dynamic programming approach to process the whole set of decision trees for the given decision table which was previously only attainable by brute-force algorithms. We study decision tables with many-valued decisions (each row may contain multiple decisions) because they are more reasonable models of data in many cases. To address this problem in a broad sense, we consider not only decision trees but also inhibitory trees where terminal nodes are labeled with “̸= decision”. Inhibitory trees can sometimes describe more knowledge from datasets than decision trees. As for cost functions, we consider depth or average depth to minimize time complexity of trees, and the number of nodes or the number of the terminal, or nonterminal nodes to minimize the space complexity of trees. We investigate the multi-stage optimization of trees relative to some cost functions, and also the possibility to describe the whole set of strictly optimal trees. Furthermore, we study the bi-criteria optimization cost vs. cost and cost vs. uncertainty for decision trees, and cost vs. cost and cost vs. completeness for inhibitory trees. The most interesting application of the developed technique is the creation of multi-pruning and restricted multi-pruning approaches which are useful for knowledge representation and prediction. The experimental results show that decision trees constructed by these approaches can often outperform the decision trees constructed by the CART algorithm. Another application includes the comparison of 12 greedy heuristics for single- and bi-criteria optimization (cost vs. cost) of trees. We also study the three approaches (decision tables with many-valued decisions, decision tables with most common decisions, and decision tables with generalized decisions) to handle inconsistency of decision tables. We also analyze the time complexity of decision and inhibitory trees over arbitrary sets of attributes represented by information systems in the frameworks of local (when we can use in trees only attributes from problem description) and global (when we can use in trees arbitrary attributes from the information system) approaches.
Numerical Computation of Detonation Stability(2018-06-03)Detonation is a supersonic mode of combustion that is modeled by a system of conservation laws of compressible fluid mechanics coupled with the equations describing thermodynamic and chemical properties of the fluid. Mathematically, these governing equations admit steady-state travelling-wave solutions consisting of a leading shock wave followed by a reaction zone. However, such solutions are often unstable to perturbations and rarely observed in laboratory experiments. The goal of this work is to study the stability of travelling-wave solutions of detonation models by the following novel approach. We linearize the governing equations about a base travelling-wave solution and solve the resultant linearized problem using high-order numerical methods. The results of these computations are postprocessed using dynamic mode decomposition to extract growth rates and frequencies of the perturbations and predict stability of travelling-wave solutions to infinitesimal perturbations. We apply this approach to two models based on the reactive Euler equations for perfect gases. For the first model with a one-step reaction mechanism, we find agreement of our results with the results of normal-mode analysis. For the second model with a two-step mechanism, we find that both types of admissible travelling-wave solutions exhibit the same stability spectra. Then we investigate the Fickett’s detonation analogue coupled with a particular reaction-rate expression. In addition to the linear stability analysis of this model, we demonstrate that it exhibits rich nonlinear dynamics with multiple bifurcations and chaotic behavior.
Constructing robust and highly-selective hydrogel membranes by bioadhesion-inspired method for CO 2 separation(Elsevier BV, 2018-06-01)Water-swollen hydrogel membranes are good candidates for CO2 separations due to the favorable solubility of CO2 in water. However, the excessive amount of water often causes the poor mechanical property and low selectivity. Herein, we propose a bioadhesion-inspired method to construct robust and high-performance CO2 separation membranes via in situ generation of polydopamine (PDA) nanoaggregates within poly (vinyl alcohol) (PVA) matrix. PDA nanoaggregates entangled with PVA chains and formed hydrogen bonding with hydroxyl groups from PVA chains. Physical cross-linking occurred between PVA chains and PDA nanoaggregates. Compared with the PVA membrane, the PVA-PDA hybrid membrane with the dopamine content of 0.5mol% exhibited a 1.7-fold increase in tensile strength and a 2.2-fold increase in the tensile modulus. The membranes were used for CO2/CH4 separation. The physical cross-linking resulted in a PVA chain rigidification region around PDA nanoaggregates, which hindered the penetration of larger-size gas molecules and thus enhancing the CO2/CH4 selectivity. Moreover, the abundant amine groups from PDA nanoaggregates could facilitate CO2 transport. The optimized hybrid hydrogel membrane exhibited CO2/CH4 selectivity of 43.2, which was 43.85% higher than that of the PVA membrane. The bioadhesion-inspired method opens up new opportunities to exploit the potential application of hydrogel membranes.
Species delineation and hybrid identification using diagnostic nuclear markers for Plectropomus leopardus and Plectropomus maculatus(Elsevier BV, 2018-06-01)Diagnostic molecular markers are an essential tool in the study of species’ ecology and evolution, particularly in closely related and sympatric species. Furthermore, the increasing awareness of wild-hybrids has led to a renewed interest in rapid diagnostic assays. Here, we test the ability of two mitochondrial (Cytb and COI) and two nuclear markers (ETS2 and TMO-4c4) to confidently discriminate purebred P. leopardus and P. maculatus and their first-generation hybrids. A sample of 48 purebred individuals and 91 interspecific hybrids were used in this study and their delineation confirmed using a set of microsatellite markers. Our results indicate mitochondrial markers could not distinguish even between species but both nuclear markers confidently identified species and first-generation hybrids. However, later-generation hybrids could not always be confidently identified due to on-going introgression between species. Our findings provide a robust tool to distinguish purebred individuals and interspecific hybrids in a pair of species with an unexpectedly high incidence of hybridization. The quick species discrimination abilities provided by these diagnostic markers are important for stock assessment and recruitment studies of these important fishery species.
Bacterial polyextremotolerant bioemulsifiers from arid soils improve water retention capacity and humidity uptake in sandy soil(Springer Nature, 2018-05-31)Water stress is a critical issue for plant growth in arid sandy soils. Here, we aimed to select bacteria producing polyextremotolerant surface-active compounds capable of improving water retention and humidity uptake in sandy soils.From Tunisian desert and saline systems, we selected eleven isolates able to highly emulsify different organic solvents. The bioemulsifying activities were stable with 30% NaCl, at 4 and 120 °C and in a pH range 4-12. Applications to a sandy soil of the partially purified surface-active compounds improved soil water retention up to 314.3% compared to untreated soil. Similarly, after 36 h of incubation, the humidity uptake rate of treated sandy soil was up to 607.7% higher than untreated controls.Overall, results revealed that polyextremotolerant bioemulsifiers of bacteria from arid and desert soils represent potential sources to develop new natural soil-wetting agents for improving water retention in arid soils.