6 resultados para Minimal Defining Set

em University of Queensland eSpace - Australia


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It is shown that in some cases it is possible to reconstruct a block design D uniquely from incomplete knowledge of a minimal defining set for D. This surprising result has implications for the use of minimal defining sets in secret sharing schemes.

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Let G be a graph that admits a perfect matching. A forcing set for a perfect matching M of G is a subset S of M, such that S is contained in no other perfect matching of G. This notion has arisen in the study of finding resonance structures of a given molecule in chemistry. Similar concepts have been studied for block designs and graph colorings under the name defining set, and for Latin squares under the name critical set. There is some study of forcing sets of hexagonal systems in the context of chemistry, but only a few other classes of graphs have been considered. For the hypercubes Q(n), it turns out to be a very interesting notion which includes many challenging problems. In this paper we study the computational complexity of finding the forcing number of graphs, and we give some results on the possible values of forcing number for different matchings of the hypercube Q(n). Also we show an application to critical sets in back circulant Latin rectangles. (C) 2003 Elsevier B.V. All rights reserved.

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The use of many conventional chemotherapeutic drugs is often severely restricted due to dose-limiting toxicities, as these drugs target the destruction of the proliferating fraction of cells, often with little specificity for tumor cells over proliferating normal body tissue. Many newer drugs attempt to overcome this shortcoming by targeting defective gene products or cellular mechanisms that are specific to the tumor, thereby minimizing the toxicity to normal tissue. Histone deacetylase inhibitors are an example of this type of tumor-directed drug, having significant toxicity for tumors but minimal effects on normal tissue. These drugs can affect the transcriptional program by modifying chromatin structure, but it is not yet clear whether specific transcriptional changes are directly responsible for their tumor-selective toxicity. Recent evidence suggests that transcriptional changes underlie their cytostatic activity, although this is not tumor-selective and affects all proliferating cells. Here we present evidence that supports an alternative mechanism for the tumor-selective cytotoxicity of histone deacetylase inhibitors. The target is still likely to be the chromatin histones, but rather than transcriptional changes due to modification of the transcriptionally active euchromatin, we propose that hyperacetylation and disruption of the transcriptionally inactive heterochromatin, particularly the centromeric heterochromatin, and the inability of tumor cells to cell cycle arrest in response to a specific checkpoint, underlies the tumor-selective cytotoxicity of these drugs.

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Minimal representations are known to have no redundant elements, and are therefore of great importance. Based on the notions of performance and size indices and measures for process systems, the paper proposes conditions for a process model being minimal in a set of functionally equivalent models with respect to a size norm. Generalized versions of known procedures to obtain minimal process models for a given modelling goal, model reduction based on sensitivity analysis and incremental model building are proposed and discussed. The notions and procedures are illustrated and compared on a simple example, that of a simple nonlinear fermentation process with different modelling goals and on a case study of a heat exchanger modelling. (C) 2004 Elsevier Ltd. All rights reserved.

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Agreement on response criteria in rheumatoid arthritis (RA) has allowed better standardization and interpretation of clinical trial reports. With recent advances in therapy, the proportion of patients achieving a satisfactory state of minimal disease activity (MDA) is becoming a more important measure with which to compare different treatment strategies. The threshold for MDA is between high disease activity and remission and, by definition, anyone in remission will also be in MDA. True remission is still rare in RA; in addition, the American College of Rheumatology definition is difficult to apply in the context of trials. Participants at OMERACT 6 in 2002 agreed on a conceptual definition of minimal disease activity (MDA): "that state of disease activity deemed a useful target of treatment by both the patient and the physician, given current treatment possibilities and limitations." To prepare for a preliminary operational definition of MDA for use in clinical trials, we asked rheumatologists to assess 60 patient profiles describing real RA patients seen in routine clinical practice. Based on their responses, several candidate definitions for MDA were designed and discussed at the OMERACT 7 in 2004. Feedback from participants and additional on-site analyses in a cross-sectional database allowed the formulation of 2 preliminary, equivalent definitions of MDA: one based on the Disease Activity Score 28 (DAS28) index, and one based on meeting cutpoints in 5 out the 7 WHO/ILAR core set measures. Researchers applying these definitions first need to choose whether to use the DAS28 or the core set definition, because although each selects a similar proportion in a population, these are not always the same patients. In both MDA definitions, an initial decision node places all patients in MDA who have a tender joint count of 0 and a swollen joint count of 0, and an erythrocyte sedimentation rate (ESR) no greater than 10 mm. If this condition is not met: center dot The DAS28 definition places patients in MDA when DAS28

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Pattern discovery in a long temporal event sequence is of great importance in many application domains. Most of the previous work focuses on identifying positive associations among time stamped event types. In this paper, we introduce the problem of defining and discovering negative associations that, as positive rules, may also serve as a source of knowledge discovery. In general, an event-oriented pattern is a pattern that associates with a selected type of event, called a target event. As a counter-part of previous research, we identify patterns that have a negative relationship with the target events. A set of criteria is defined to evaluate the interestingness of patterns associated with such negative relationships. In the process of counting the frequency of a pattern, we propose a new approach, called unique minimal occurrence, which guarantees that the Apriori property holds for all patterns in a long sequence. Based on the interestingness measures, algorithms are proposed to discover potentially interesting patterns for this negative rule problem. Finally, the experiment is made for a real application.