A longitudinal analysis of logical reasoning relationships: Conservation and transitive inference.

102 children originally assessed in 1973 were retested 1 yr later on a series of conservation and transitive inference tasks (length and weight content areas). An additional sample of matched cohort/grade Ss (1st- and 4th-grade levels) were assessed in the 2nd yr only to permit evaluation of repeated measurement biases for the longitudinal sample. Results indicate that there were no effects of presentation order, selective survival, repeated measurement, sex, or content area; these variables did not interact with each other. Analyses of the longitudinal Ss' conservation task performances over the annual interval indicated significant grade-level distinctions, Yr 1 vs Yr 2 differences, and type of conservation distinctions (identity vs equivalence). Identity conservation scores were consistently superior to equivalence conservation scores, a superiority most notable for the youngest Ss. Transitive inference tasks were significantly less difficult than equivalence conservation tasks. Most importantly, evidence for a developmental mastery sequence (transitivity-conservation) was demonstrated. Identity-equivalence conservation task distinctions were most apparent for the without verbal justification response criterion. (26 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Knowledge representation of the software architecture design process based on situation calculus

Software architecture design is an interactive, complex, decision‐making process. Such a design process involves the exploration, evaluation, and composition of design alternatives. Increasingly, new computer‐aided tools are available to help designers in these complex activities. However, these tools do not know how design is actually done, in other words, by means of which design activities the final artefact was obtained. In fact, the architectural design knowledge exclusively rests in the mind of designers, and there is an urgent need to move it, as much as possible, to a computer‐supported environment that enables the capture of this type of knowledge. This contribution addresses this need by introducing a model for capturing how products under development are generated and transformed along the software architecture design process. The proposed model follows an operational perspective, where architectural design decisions are modelled by means of sequences of operations that are applied on the design products. Situation calculus is used to formally express the existence of an object in a given state of a design process. In addition, this formalism allows us expressing without ambiguities when an operation can be performed in a specific state of the design process.     

A numerical tool to predict ice growth in lakes

Oil and gas exploration activities on the North of Slope of Alaska rely on ice roads to provide access to the exploration sites, with negligible effects on the tundra. The construction of ice roads requires a large volume of water which, in turn, poses challenges to water resource managers. A tool capable of predicting ice thickness in a given lake could certainly benefit the oil industry. This study focuses on the development and use of such a predictive tool. Using a simplified Stefan equation, the tool is based on a combination of three weather scenarios (warm, average and cold winters), current winter condition and ice thickness measurements. It was applied to four lakes located on the Arctic Coastal Plain and one lake in the foothill area. The study results indicate the model predictions are relatively accurate (7% average percentage error) for monthly time spans. The study results also reveal a temporal variation in a coefficient used in the calculations, although previous literature utilized a constant coefficient to estimate the ice thickness.     

Water and phosphoric acid uptake of poly [2,5-benzimidazole] (ABPBI) membranes prepared by low and high temperature casting

Phosphoric acid-doped membranes based in poly[2,5-benzimidazole] (ABPBI) were obtained by a new low temperature casting procedure and by the classical high temperature casting from methanesulfonic acid. These membranes, which can be suitable for application in direct methanol proton exchange membrane (PEM) fuel cells, were studied in relation with their phosphoric acid doping level by measuring the free and bonded acid. The water isotherms were also determined for the low and high temperature casted ABPBI membranes. Both, acid and water sorption properties, were compared with those determined in poly [2-2′-(m-fenylene)-5-5′ bibenzimidazole] (PBI) membranes. The water sorption of the ABPBI membranes over the range of all water activity is described by the modified BET equation, commonly known as Guggenheim–Anderson–de Boer (GAB) and a two-parameters empirical isotherm. The acid uptake behaviour of the membranes prepared by low and high temperature casting are related with differences in their supramolecular structure.     

Gamma interferon is a major suppressive factor produced by activated human peripheral blood lymphocytes that is able to inhibit foamy virus-induced cytopathic effects

The activation of human peripheral blood lymphocytes by mitogens or by triggering the T-cell receptor with anti-CD3 antibodies leads to the production of a potent soluble inhibitory activity against foamy virus-induced cytopathic effects in vitro. The inhibitory activity acts in a species-specific manner. As a consequence, the isolation of foamy viruses from blood lymphocytes of infected humans is accelerated in a heterologous coculture system. Antibodies against gamma interferon (IFN-gamma) are able to suppress most of the inhibitory activity, suggesting that IFN-gamma is the dominant component.     

An enumeration scheme to generate constrained exact checkerboard patterns

Checkerboard patterns belong to a special class of 2-stage guillotine patterns that require less machine time to be cut. In this paper we propose an enumerative algorithm to generate exact constrained checkerboard patterns. At each node of the enumeration tree a constructive procedure is used to generate a feasible pattern. In addition, an upper bound on the objective function value is calculated to decide whether further branching from the node is worth. The algorithm was implemented and computational tests were performed. The test results indicate that the proposed scheme outperforms previous methods of the literature in terms of execution times.     

A Machine Learning Approach to POS Tagging

We have applied the inductive learning of statistical decision trees and relaxation labeling to the Natural Language Processing (NLP) task of morphosyntactic disambiguation (Part Of Speech Tagging). The learning process is supervised and obtains a language model oriented to resolve POS ambiguities, consisting of a set of statistical decision trees expressing distribution of tags and words in some relevant contexts. The acquired decision trees have been directly used in a tagger that is both relatively simple and fast, and which has been tested and evaluated on the Wall Street Journal (WSJ) corpus with competitive accuracy. However, better results can be obtained by translating the trees into rules to feed a flexible relaxation labeling based tagger. In this direction we describe a tagger which is able to use information of any kind (n-grams, automatically acquired constraints, linguistically motivated manually written constraints, etc.), and in particular to incorporate the machine-learned decision trees. Simultaneously, we address the problem of tagging when only limited training material is available, which is crucial in any process of constructing, from scratch, an annotated corpus. We show that high levels of accuracy can be achieved with our system in this situation, and report some results obtained when using it to develop a 5.5 million words Spanish corpus from scratch.     

Synthesis,studies and fuel cell performance of “core–shell” electrocatalysts for oxygen reduction reaction based on a PtNix carbon nitride “shell” and a pyrolyzed polyketone nanoball “core”

This report describes a new class of “core–shell” electrocatalysts for oxygen reduction reaction (ORR) processes for application in Proton Exchange Membrane Fuel Cells (PEMFCs). The electrocatalysts are obtained by supporting a “shell” consisting of PtNi_x alloy nanoparticles embedded into a carbon nitride matrix (indicated as PtNi_x-CN) on a “core” of pyrolyzed polyketone nanoballs, labeled ‘ST_p’. ST_ps are obtained by the sulfonation and pyrolysis of a precursor consisting of XC-72R carbon nanoparticles wrapped by polyketone (PK) fibers. The ST_ps are extensively characterized in terms of the chemical composition, thermal stability, degree of graphitization and morphology. The “core–shell” ORR electrocatalysts are prepared by the pyrolysis of precursors obtained impregnating the ST_p “cores” with a zeolitic inorganic–organic polymer electrolyte (Z-IOPE) plastic material. The electrochemical performance of the electrocatalysts in the ORR is tested “in situ” by single fuel cell tests. The interplay between the chemical composition, the degree of graphitization of both PtNi_x-CN “shell” and ST_ps “cores”, the morphology of the electrocatalysts and the fuel cell performance is elucidated. The most crucial preparation parameters for the optimization of the various features affecting the fuel cell performance of this promising class of ORR electrocatalysts are identified.     

Adaptive statistical scheduling of divisible workloads in heterogeneous systems

This article presents a statistical approach to the scheduling of divisible workloads. Structured as a task farm with different scheduling modes including adaptive single and multi-round scheduling, this novel divisible load theory approach comprises two phases, calibration and execution, which dynamically adapt the installment size and number. It introduces the concept of a generic installment factor based on the statistical dispersion of the calibration times of the participating nodes, which allows automatic determination of the number and size of the workload installments. Initially, the calibration ranks processors according to their fitness and determines an installment factor based on how different their execution times are. Subsequently, the execution iteratively distributes the workload according to the processor fitness, which is continuously re-assessed throughout the program execution. Programmed as an adaptive algorithmic skeleton, our task farm has been successfully evaluated for single-round scheduling and generic multi-round scheduling using a computational biology parameter-sweep in a non-dedicated multi-cluster system.