146 resultados para Strong Fuzzy Negations


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The oncogenic role of WNT is well characterized. Wntless (WLS) (also known as GPR177, or Evi), a key modulator of WNT protein secretion, was recently found to be highly overexpressed in malignant astrocytomas. We hypothesized that this molecule may be aberrantly expressed in other cancers known to possess aberrant WNT signaling such as ovarian, gastric, and breast cancers. Immunohistochemical analysis using a TMA platform revealed WLS overexpression in a subset of ovarian, gastric, and breast tumors; this overexpression was associated with poorer clinical outcomes in gastric cancer (P=0.025). In addition, a strong correlation was observed between WLS expression and human epidermal growth factor receptor 2 (HER2) overexpression. Indeed, 100% of HER2-positive intestinal gastric carcinomas, 100% of HER2-positive serous ovarian carcinomas, and 64% of HER2-positive breast carcinomas coexpressed WLS protein. Although HER2 protein expression or gene amplification is an established predictive biomarker for trastuzumab response in breast and gastric cancers, a significant proportion of HER2-positive tumors display resistance to trastuzumab, which may be in part explainable by a possible mechanistic link between WLS and HER2.

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We test current numerical implementations of laser-matter interactions by comparison with exact analytical results. Focusing on photon emission processes, it is found that the numerics accurately reproduce analytical emission spectra in all considered regimes, except for the harmonic structures often singled out as the most significant high-intensity (multiphoton) effects. We find that this discrepancy originates in the use of the locally constant field approximation.

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We present ab initio studies of photoelectron spectra for above threshold detachment (ATD) of F- anions in short, 1300 nm and 1800 nm laser pulses. We identify and assess the importance of electron rescattering in strong-field photodetachment of a negative ion through comparison with an analytic, Keldysh-type approach, demonstrating the capability of ab-initio computation in the challenging near-IR regime. We further assess the influence of the strong electron correlation on the photodetachment.

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Credal networks are graph-based statistical models whose parameters take values on a set, instead of being sharply specified as in traditional statistical models (e.g., Bayesian networks). The result of inferences with such models depends on the irrelevance/independence concept adopted. In this paper, we study the computational complexity of inferences under the concepts of epistemic irrelevance and strong independence. We strengthen complexity results by showing that inferences with strong independence are NP-hard even in credal trees with ternary variables, which indicates that tractable algorithms, including the existing one for epistemic trees, cannot be used for strong independence. We prove that the polynomial time of inferences in credal trees under epistemic irrelevance is not likely to extend to more general models, because the problem becomes NP-hard even in simple polytrees. These results draw a definite line between networks with efficient inferences and those where inferences are hard, and close several open questions regarding the computational complexity of such models.

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Contact zones between divergent forms of the same species are often characterised by high levels of phenotypic diversity over small geographic distances. What processes are involved in generating such high phenotypic diversity? One possibility is that introgression and recombination between divergent forms in contact zones results in greater phenotypic and genetic polymorphism. Alternatively, strong reproductive isolation between forms may maintain distinct phenotypes, preventing homogenisation by gene flow. Contact zones between divergent freshwater-resident and anadromous stickleback (Gasterosteus aculeatus L.) forms are numerous and common throughout the species distribution, offering an opportunity to examine these contrasting hypotheses in greater detail. This study reports on an interesting new contact zone located in a tidally influenced lake catchment in western Ireland, characterised by high polymorphism for lateral plate phenotypes. Using neutral and QTL-linked microsatellite markers, we tested whether the high diversity observed in this contact zone arose as a result of introgression or reproductive isolation between divergent forms: we found strong support for the latter hypothesis. Three phenotypic and genetic clusters were identified, consistent with two divergent resident forms and a distinct anadromous completely plated population that migrates in and out of the system. Given the strong neutral differentiation detected between all three morphotypes (mean FST = 0.12), we hypothesised that divergent selection between forms maintains reproductive isolation. We found a correlation between neutral genetic and adaptive genetic differentiation that support this. While strong associations between QTL linked markers and phenotypes were also observed in this wild population, our results support the suggestion that such associations may be more complex in some Atlantic populations compared to those in the Pacific. These findings provide an important foundation for future work investigating the dynamics of gene flow and adaptive divergence in this newly discovered stickleback contact zone.

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This paper proposes an efficient learning mechanism to build fuzzy rule-based systems through the construction of sparse least-squares support vector machines (LS-SVMs). In addition to the significantly reduced computational complexity in model training, the resultant LS-SVM-based fuzzy system is sparser while offers satisfactory generalization capability over unseen data. It is well known that the LS-SVMs have their computational advantage over conventional SVMs in the model training process; however, the model sparseness is lost, which is the main drawback of LS-SVMs. This is an open problem for the LS-SVMs. To tackle the nonsparseness issue, a new regression alternative to the Lagrangian solution for the LS-SVM is first presented. A novel efficient learning mechanism is then proposed in this paper to extract a sparse set of support vectors for generating fuzzy IF-THEN rules. This novel mechanism works in a stepwise subset selection manner, including a forward expansion phase and a backward exclusion phase in each selection step. The implementation of the algorithm is computationally very efficient due to the introduction of a few key techniques to avoid the matrix inverse operations to accelerate the training process. The computational efficiency is also confirmed by detailed computational complexity analysis. As a result, the proposed approach is not only able to achieve the sparseness of the resultant LS-SVM-based fuzzy systems but significantly reduces the amount of computational effort in model training as well. Three experimental examples are presented to demonstrate the effectiveness and efficiency of the proposed learning mechanism and the sparseness of the obtained LS-SVM-based fuzzy systems, in comparison with other SVM-based learning techniques.

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Although Chronic Myeloid Leukaemia (CML) can be treated successfully with allogeneic bone marrow transplantation (BMT), leukaemia relapse remains a significant clinical problem. Molecular monitoring of the post transplant marrow can be useful in predicting relapse particularly in CML patients where the Philadelphia chromosome or its molecular counterpart, the BCR-ABL fusion messenger RNA can be used as a leukaemia specific marker of minimal residual disease (MRD). We have investigated chimaerism (using polymerase chain reaction of short tandem repeat sequences (STR-PCR)) and MRD status (using reverse transcriptase PCR of the BCR-ABL fusion mRNA) in a serial fashion in 18 patients who were in clinical and haematological remission post allogeneic BMT for chronic phase CML. Eleven patients exhibited complete donor chimaerism with no evidence of minimal residual disease. Five patients had transient or low level stable MC. Late MC and MRD was observed in two patients who relapsed > 6 years after T cell depleted BMT for CML. Thus STR-PCR is an appropriate screening test in the post transplant setting for CML patients, but those patients exhibiting mixed haemopoietic chimaerism should also be monitored using a leukaemia specific sensitive molecular assay.