Reasoning with infinite stable models

This paper illustrates extensively the theoretical properties, the implementation issues, and the programming style underlying finitary programs. They are a class of normal logic programs whose consequences under the stable model semantics can be effectively computed, despite the fact that finitary programs admit function symbols (hence infinite domains) and recursion. From a theoretical point of view, finitary programs are interesting because they enjoy properties that are extremely unusual for a nonmonotonic formalism, such as compactness. From the application point of view, the theory of finitary programs shows how the existing technology for answer set programming can be extended from problem solving below the second level of the polynomial hierarchy to all semidecidable problems. Moreover, finitary programs allow a more natural encoding of recursive data structures and may increase the performance of credulous reasoners.     

How to hit scylla without avoiding charybdis: Comment on Perruchet, Tyler, Galland, and Peereman (2004).

M. Pe?a, L. L. Bonatti, M. Nespor, and J. Mehler (see record 2002-06215-001) argued that humans compute nonadjacent statistical relations among syllables in a continuous artificial speech stream to extract words, but they use other computations to determine the structural properties of words. Instead, when participants are familiarized with a segmented stream, structural generalizations about words are quickly established. P. Perruchet, M. D. Tyler, N. Galland, and R. Peereman (see record 2004-21166-008) criticized M. Pe?a et al.'s work and dismissed their results. In this article, the authors show that P. Perruchet et al.'s criticisms are groundless. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

TLS/FUS, a pro-oncogene involved in multiple chromosomal translocations, is a novel regulator of BCR/ABL-mediated leukemogenesis

The leukemogenic potential of BCR/ABL oncoproteins depends on their tyrosine kinase activity and involves the activation of several downstream effectors, some of which are essential for cell transformation. Using electrophoretic mobility shift assays and Southwestern blot analyses with a double-stranded oligonucleotide containing a zinc finger consensus sequence, we identified a 68 kDa DNA-binding protein specifically induced by BCR/ABL. The peptide sequence of the affinity-purified protein was identical to that of the RNA-binding protein FUS (also called TLS). Binding activity of FUS required a functional BCR/ABL tyrosine kinase necessary to induce PKCbetaII-dependent FUS phosphorylation. Moreover, suppression of PKCbetaII activity in BCR/ABL-expressing cells by treatment with the PKCbetaII inhibitor CGP53353, or by expression of a dominant-negative PKCbetaII, markedly impaired the ability of FUS to bind DNA. Suppression of FUS expression in myeloid precursor 32Dcl3 cells transfected with a FUS antisense construct was associated with upregulation of the granulocyte-colony stimulating factor receptor (G-CSFR) and downregulation of interleukin-3 receptor (IL-3R) beta-chain expression, and accelerated G-CSF-stimulated differentiation. Downregulation of FUS expression in BCR/ABL-expressing 32Dcl3 cells was associated with suppression of growth factor-independent colony formation, restoration of G-CSF-induced granulocytic differentiation and reduced tumorigenic potential in vivo. Together, these results suggest that FUS might function as a regulator of BCR/ABL leukemogenesis, promoting growth factor independence and preventing differentiation via modulation of cytokine receptor expression.     

Erratum to: Reasoning with infinite stable models [Artificial Intelligence 156 (1) (2004) 75-111]

Theorem 16 in [Piero A. Bonatti, Reasoning with infinite stable models, Artificial Intelligence 156 (1) (2004) 75-111] states that ground skeptical and credulous inferences under the stable model semantics are decidable when the given normal logic program is finitary. Giovanni Criscuolo and Nicola Leone independently observed in personal communications that the proof of this theorem relies on an unproved assumption that—at the best of our current knowledge—might turn out to be false. In this note we correct Theorem 16 by adding the set of odd-cyclic atoms to the inputs of the computation, and argue that this change has no impact on the current applications of the theory of finitary programs.     

A valuable tool: symbolic computation

The use of symbolic computation is proposed here as an effective tool for studying electric circuits. Using well established methods to write electric circuit equations, a student can generate a set of equations involving only state variables. With the help of symbolic computation, these equations can be rewritten in a normal form. They then can be solved for any input-output pair. Furthermore, the influence of a certain parameter can be analyzed in detail via analytic expressions     

B-ISDN economical evaluation in metropolitan areas

The economical estimation of B-ISDN development in metropolitan areas, with particular reference to the application of the asynchronous transfer mode (ATM) techniques is addressed. The results achieved by applying models and methods developed in the framework of RACE 1044-EPF Case Study E (Evolution Prospects for Metropolitan Public Networks) to an urban area of 2 million inhabitants. Equipment volumes are estimated as a function of different demand scenarios, equipment evolution, and network performances. Economical figures that verify the cost-effectiveness of alternative developments and the viability of alternative introduction policies of B-ISDN are derived. The economical impact of fulfilling service integrity requirements of specific demand segments is evaluated. Usable planning guidelines and evolutionary strategies as regards network architecture, system introduction, and growth policies are defined     

Inhibition of the Mr 70,000 S6 kinase pathway by rapamycin results in chromosome malsegregation in yeast and mammalian cells

The antifungal and immunosuppressive drug rapamycin arrests the cell cycle in G1-phase in both yeast and mammalian cells. In mammalian cells, rapamycin selectively inhibits phosphorylation and activation of p70 S6 kinase (p70(S6K)), a protein involved in the translation of a subset of mRNAs, without affecting other known kinases. We now report that rapamycin causes chromosome malsegregation in mammalian and yeast cells. Chromosome malsegregation was determined by metaphase chromosome analysis of human lymphocytes and lymphoblasts, detection of CREST-positive micronuclei in human lymphoblasts and Chinese hamster embryonic fibroblast (CHEF) cells, and selection of doubly prototrophic cells in a specially constructed yeast strain. The number of ana-telophases with displaced chromosomes and interphase and mitotic cells with an irregular number of centrosomes was also determined in CHEF cells. In quiescent mammalian cells (human lymphocytes and CHEF cells) induced with growth factor to re-enter the cell cycle, rapamycin was effective when cells were exposed at the time of p70(S6K) activation. In yeast, rapamycin was more effective when treatment was started in G1- than in G2-synchronized cells. Cells from ataxia telangiectasia (A-T) patients are characterized by chromosome instability and have recently been found to be resistant to the growth-inhibiting effect of rapamycin. We found that an A-T lymphoblastoid cell line was also resistant to the induction of chromosome malsegregation by rapamycin, but the level of spontaneous aneuploidy was higher than in normal cells. In yeast, the induction of chromosome malsegregation was dependent on the presence of a wild-type TUB2 gene, encoding the beta-subunit of tubulin. The finding that rapamycin acts in different cell types and organisms suggests that the drug affects a conserved step important for proper segregation of chromosomes. One or more proteins required for chromosome segregation could be under the control of the rapamycin-sensitive pathway.     

Sensor placement optimization applied to laminated composite plates under vibration

The location optimization of sensors is a essential problem in structural health monitoring systems. Taking the cost of sensors into account, it is uneconomical to install sensors on every part of a structure and moreover in aeronautical industry, the weight is a crucial factor. In this paper, a optimal placement optimization of sensor locations for structural health monitoring systems is studied. Several techniques of optimization of sensors are approached and applied in a shell structure. The structure, a laminate of carbon fiber, was modeled by the finite element method (FEM) and then subject to free vibration. Genetic algorithms (GAs) are then employed to locate the best sensor distribution to cover a specific number of low frequency modes. Numerical results have demonstrated the overall efficiency of sensor delivery methods. Specific problems occurred, especially regarding the method of effective independence, being less efficient and discrepant in relation to the other methods employed. In summary, the results obtained in this paper provide an optimal position for sensors in real SHM systems and experiments.