A survey of parallel execution strategies for transitive closure and logic programs

An important feature of database technology of the nineties is the use of parallelism for speeding up the execution of complex queries. This technology is being tested in several experimental database architectures and a few commercial systems for conventional select-project-join queries. In particular, hash-based fragmentation is used to distribute data to disks under the control of different processors in order to perform selections and joins in parallel. With the development of new query languages, and in particular with the definition of transitive closure queries and of more general logic programming queries, the new dimension of recursion has been added to query processing. Recursive queries are complex; at the same time, their regular structure is particularly suited for parallel execution, and parallelism may give a high efficiency gain. We survey the approaches to parallel execution of recursive queries that have been presented in the recent literature. We observe that research on parallel execution of recursive queries is separated into two distinct subareas, one focused on the transitive closure of Relational Algebra expressions, the other one focused on optimization of more general Datalog queries. Though the subareas seem radically different because of the approach and formalism used, they have many common features. This is not surprising, because most typical Datalog queries can be solved by means of the transitive closure of simple algebraic expressions. We first analyze the relationship between the transitive closure of expressions in Relational Algebra and Datalog programs. We then review sequential methods for evaluating transitive closure, distinguishing iterative and direct methods. We address the parallelization of these methods, by discussing various forms of parallelization. Data fragmentation plays an important role in obtaining parallel execution; we describe hash-based and semantic fragmentation. Finally, we consider Datalog queries, and present general methods for parallel rule execution; we recognize the similarities between these methods and the methods reviewed previously, when the former are applied to linear Datalog queries. We also provide a quantitative analysis that shows the impact of the initial data distribution on the performance of methods. Recommended by: Patrick Valduriez     

Designing and prototyping data-intensive applications in the Logresand Algres programming environment

The authors present an environment and a methodology for the design and rapid prototyping of data-intensive software applications, i.e., applications which perform substantial retrieval and update activity on persistent data. In the approach, the application is formally specified using Logres, a database language which combines object-oriented data modeling and rule-based programming. These specifications are translated into Algres, an extended relational algebra, thus yielding a rapid executable prototype. Algres programs embedded into a conventional programming language interface may be converted to conventional programs operating on a commercial relational system. This methodology helps automate the conversion from declarative requirements to imperative code, performing several tasks fully automatically and reducing the probability of human errors, while integrity constraints and application specifications are expressed in a declarative language, at a very high level of abstraction     

Process optimization via confidence region: a case study from micro-injection molding

Journal of Intelligent Manufacturing - In industrial research, experiments are designed to determine the optimal factor levels of the process parameters. Typically, experimental data are used to...     

Extraction of lignans, proteins and carbohydrates from flaxseed meal with pressurized low polarity water

This study examined the application of pressurized low polarity water (PLPW) extraction of lignans, proteins and carbohydrates from defatted flaxseed meal. Key processing conditions included temperature (130, 160, 190 °C), solvent pH (4, 6.5 and 9), solvent to solid ratio (90, 150 and 210 mL/g) and introduction of co-packing material (0 and 3 g glass beads). The addition of 3 g glass beads increased the yields for all target compounds. The maximum yield of lignans (21 mg/g meal) was obtained at 170 °C with solvent to solid ratio of 100 mL/g meal at pH 9. Optimal conditions for protein extraction were pH 9, solvent to solid ratio of 210 mL/g meal and 160 °C. Total carbohydrates recovery was maximized at 215 mg/g meal (50% recovery) at pH 4 and 150 °C with solvent to solid ratio of 210 mL/g meal. The increase of temperature accelerated extraction, thus reducing solvent volume and time to reach equilibrium. For the extraction of proteins and carbohydrates, however, a temperature of 130-160 °C is recommended, as proteins and carbohydrates are vulnerable to thermal degradation.     

Stabilization of strict‐feedback nonlinear systems with input delay using closed‐loop predictors

In this paper, we consider the control problem of strict‐feedback nonlinear systems with time‐varying input and output delays. The approach is based on the usual observer/predictor/feedback approach, but the novelty is the use of the closed‐loop dynamics in the predictor. This approach allows to develop two designs, an instantaneous predictor and a delay differential equation‐based predictor, that both attain the same performance in terms of system trajectories and input signal as in the case with no delays. The design based on delay differential equations allows to build a cascade of predictors to deal with arbitrarily large delay bounds. The resulting controller is much simpler to implement than classical infinite‐dimensional predictors, and it is robust with respect to actuation and measurement disturbances. We illustrate the approach with an application to the control of a chaotic system with input delay. Copyright © 2016 John Wiley & Sons, Ltd.     

Effects of suramin-related and other clinically therapeutic polyanions on protein kinase C activity

The mechanism of the antineoplastic effects of suramin may involve interference with signal transduction, but in general is not well understood. We examined several polyanions to determine their effects on the kinase activity of the protein kinase C (PKC) beta1 and other PKC isoforms. Similar to suramin, a phosphorothioate oligodeoxynucleotide 28-mer homopolymer of cytidine (SdC28) inhibited the phosphatidylserine and Ca2+-dependent phosphorylation of an epidermal growth factor receptor octapeptide substrate. The inhibition by suramin was mixed competitive/noncompetitive with respect to ATP, but uncompetitive with respect to substrate. In contrast, the inhibition by SdC28 was competitive with respect to substrate (Ki = 5.4 microM) and not competitive with respect to ATP. The PKC alpha and beta1 isoforms were inhibited to the same extent with SdC28, while PKC epsilon was not inhibited. SdC28, in the absence of lipid cofactor, stimulated substrate phosphorylation, and in the absence of substrate induced PKC beta1 autophosphorylation. Similar behavior was seen with another polyanion, the polysulfated carbohydrate pentosan polysulfate (polyxylyl hydrogen sulfate). H4, a bis-naphthalene disulfonate tetraanion structurally related to suramin, also inhibited kinase activity but was not competitive with respect to ATP. Dianions closely related to H4 failed to inhibit PKC beta1, suggesting that multiple (>2) negative charges are required. The interactions of polyanions with PKC are complex, and are dependent on the molecular structure of the polyanion, the presence of cofactors, and the PKC isoform.     

Output transformations and separation results for feedback linearisable delay systems

The class of strict-feedback systems enjoys special properties that make it similar to linear systems. This paper proves that such a class is equivalent, under a change of coordinates, to the wider class of feedback linearisable systems with multiplicative input, when the multiplicative terms are functions of the measured variables only. We apply this result to the control problem of feedback linearisable nonlinear MIMO systems with input and/or output delays. In this way, we provide sufficient conditions under which a separation result holds for output feedback control and moreover a predictor-based controller exists. When these conditions are satisfied, we obtain that the existence of stabilising controllers for arbitrarily large delays in the input and/or the output can be proved for a wider class of systems than previously known.