1,836 research outputs found

    Between Treewidth and Clique-width

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    Many hard graph problems can be solved efficiently when restricted to graphs of bounded treewidth, and more generally to graphs of bounded clique-width. But there is a price to be paid for this generality, exemplified by the four problems MaxCut, Graph Coloring, Hamiltonian Cycle and Edge Dominating Set that are all FPT parameterized by treewidth but none of which can be FPT parameterized by clique-width unless FPT = W[1], as shown by Fomin et al [7, 8]. We therefore seek a structural graph parameter that shares some of the generality of clique-width without paying this price. Based on splits, branch decompositions and the work of Vatshelle [18] on Maximum Matching-width, we consider the graph parameter sm-width which lies between treewidth and clique-width. Some graph classes of unbounded treewidth, like distance-hereditary graphs, have bounded sm-width. We show that MaxCut, Graph Coloring, Hamiltonian Cycle and Edge Dominating Set are all FPT parameterized by sm-width

    Probabilistic abstract interpretation: From trace semantics to DTMC’s and linear regression

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    In order to perform probabilistic program analysis we need to consider probabilistic languages or languages with a probabilistic semantics, as well as a corresponding framework for the analysis which is able to accommodate probabilistic properties and properties of probabilistic computations. To this purpose we investigate the relationship between three different types of probabilistic semantics for a core imperative language, namely Kozen’s Fixpoint Semantics, our Linear Operator Semantics and probabilistic versions of Maximal Trace Semantics. We also discuss the relationship between Probabilistic Abstract Interpretation (PAI) and statistical or linear regression analysis. While classical Abstract Interpretation, based on Galois connection, allows only for worst-case analyses, the use of the Moore-Penrose pseudo inverse in PAI opens the possibility of exploiting statistical and noisy observations in order to analyse and identify various system properties

    The Goldbeter-Koshland switch in the first-order region and its response to dynamic disorder

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    In their classical work (Proc. Natl. Acad. Sci. USA, 1981, 78:6840-6844), Goldbeter and Koshland mathematically analyzed a reversible covalent modification system which is highly sensitive to the concentration of effectors. Its signal-response curve appears sigmoidal, constituting a biochemical switch. However, the switch behavior only emerges in the "zero-order region", i.e. when the signal molecule concentration is much lower than that of the substrate it modifies. In this work we showed that the switching behavior can also occur under comparable concentrations of signals and substrates, provided that the signal molecules catalyze the modification reaction in cooperation. We also studied the effect of dynamic disorders on the proposed biochemical switch, in which the enzymatic reaction rates, instead of constant, appear as stochastic functions of time. We showed that the system is robust to dynamic disorder at bulk concentration. But if the dynamic disorder is quasi-static, large fluctuations of the switch response behavior may be observed at low concentrations. Such fluctuation is relevant to many biological functions. It can be reduced by either increasing the conformation interconversion rate of the protein, or correlating the enzymatic reaction rates in the network.Comment: 23 pages, 4 figures, accepted by PLOS ON

    Solitary splenic metastasis from ovarian carcinosarcoma: a case report

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    <p>Abstract</p> <p>Introduction</p> <p>Metastatic tumors to the spleen are rare but are usually found in conjunction with metastasis to other organs. The most common sources of splenic metastasis are breast, lung and colorectal cancers as well as melanoma and ovarian carcinoma. A solitary carcinosarcoma metastasis to the spleen of any origin is very rare. To the best of our knowledge, there are fewer than 30 reported cases of ovarian primary tumors with solitary metastasis to the spleen, and only three solitary primary carcinosarcomas to the spleen have been reported, of which one is female. We present what is, to the best of our knowledge, the first case of a solitary metastatic carcinosarcoma to the spleen arising from a primary ovarian carcinsarcoma.</p> <p>Case presentation</p> <p>A 72-year-old Hispanic woman status post-total abdominal hysterectomy for ovarian carcinosarcoma presented with complaints of early satiety and abdominal pain for the past two months with a 30-lb unintentional weight loss. An initial computed tomographic scan of her abdomen and pelvis revealed a 30 cm × 27 cm splenic mass with displacement of the left kidney, stomach and liver. The patient was found to have a solitary metastatic carcinosarcoma of the spleen with biphasic epithelial (carcinomatous) and mesenchymal (sarcomatous) elements consistent with carcinosarcoma.</p> <p>Conclusion</p> <p>Carcinosarcoma of the spleen is a rare tumor. Carcinosarcomas are a biphasic neoplasm comprising malignant epithelial and mesenchymal components arising from a stem cell capable of differentiation. They can arise anywhere in the female genital tract, most commonly from the endometrium. Even though it is rare, carcinosarcomas can metastasize to the spleen. This unique case of a solitary splenic metastasis from ovarian carcinosarcoma has particular interest in medicine, especially for the specialties of surgical oncology, pathology and hematology/oncology.</p

    Proximity curves for potential-based clustering

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    YesThe concept of proximity curve and a new algorithm are proposed for obtaining clusters in a finite set of data points in the finite dimensional Euclidean space. Each point is endowed with a potential constructed by means of a multi-dimensional Cauchy density, contributing to an overall anisotropic potential function. Guided by the steepest descent algorithm, the data points are successively visited and removed one by one, and at each stage the overall potential is updated and the magnitude of its local gradient is calculated. The result is a finite sequence of tuples, the proximity curve, whose pattern is analysed to give rise to a deterministic clustering. The finite set of all such proximity curves in conjunction with a simulation study of their distribution results in a probabilistic clustering represented by a distribution on the set of dendrograms. A two-dimensional synthetic data set is used to illustrate the proposed potential-based clustering idea. It is shown that the results achieved are plausible since both the ‘geographic distribution’ of data points as well as the ‘topographic features’ imposed by the potential function are well reflected in the suggested clustering. Experiments using the Iris data set are conducted for validation purposes on classification and clustering benchmark data. The results are consistent with the proposed theoretical framework and data properties, and open new approaches and applications to consider data processing from different perspectives and interpret data attributes contribution to patterns

    Use of the bootstrap in analysing cost data from cluster randomised trials: some simulation results

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    BACKGROUND: This work has investigated under what conditions confidence intervals around the differences in mean costs from a cluster RCT are suitable for estimation using a commonly used cluster-adjusted bootstrap in preference to methods that utilise the Huber-White robust estimator of variance. The bootstrap's main advantage is in dealing with skewed data, which often characterise patient costs. However, it is insufficiently well recognised that one method of adjusting the bootstrap to deal with clustered data is only valid in large samples. In particular, the requirement that the number of clusters randomised should be large would not be satisfied in many cluster RCTs performed to date. METHODS: The performances of confidence intervals for simple differences in mean costs utilising a robust (cluster-adjusted) standard error and from two cluster-adjusted bootstrap procedures were compared in terms of confidence interval coverage in a large number of simulations. Parameters varied included the intracluster correlation coefficient, the sample size and the distributions used to generate the data. RESULTS: The bootstrap's advantage in dealing with skewed data was found to be outweighed by its poor confidence interval coverage when the number of clusters was at the level frequently found in cluster RCTs in practice. Simulations showed that confidence intervals based on robust methods of standard error estimation achieved coverage rates between 93.5% and 94.8% for a 95% nominal level whereas those for the bootstrap ranged between 86.4% and 93.8%. CONCLUSION: In general, 24 clusters per treatment arm is probably the minimum number for which one would even begin to consider the bootstrap in preference to traditional robust methods, for the parameter combinations investigated here. At least this number of clusters and extremely skewed data would be necessary for the bootstrap to be considered in favour of the robust method. There is a need for further investigation of more complex bootstrap procedures if economic data from cluster RCTs are to be analysed appropriately

    A Neural Correlate of the Processing of Multi-Second Time Intervals in Primate Prefrontal Cortex

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    Several areas of the brain are known to participate in temporal processing. Neurons in the prefrontal cortex (PFC) are thought to contribute to perception of time intervals. However, it remains unclear whether the PFC itself can generate time intervals independently of external stimuli. Here we describe a group of PFC neurons in area 9 that became active when monkeys recognized a particular elapsed time within the range of 1–7 seconds. Another group of area 9 neurons became active only when subjects reproduced a specific interval without external cues. Both types of neurons were individually tuned to recognize or reproduce particular intervals. Moreover, the injection of muscimol, a GABA agonist, into this area bilaterally resulted in an increase in the error rate during time interval reproduction. These results suggest that area 9 may process multi-second intervals not only in perceptual recognition, but also in internal generation of time intervals

    Cytoplasmic p53 couples oncogene-driven glucose metabolism to apoptosis and is a therapeutic target in glioblastoma.

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    Cross-talk among oncogenic signaling and metabolic pathways may create opportunities for new therapeutic strategies in cancer. Here we show that although acute inhibition of EGFR-driven glucose metabolism induces only minimal cell death, it lowers the apoptotic threshold in a subset of patient-derived glioblastoma (GBM) cells. Mechanistic studies revealed that after attenuated glucose consumption, Bcl-xL blocks cytoplasmic p53 from triggering intrinsic apoptosis. Consequently, targeting of EGFR-driven glucose metabolism in combination with pharmacological stabilization of p53 with the brain-penetrant small molecule idasanutlin resulted in synthetic lethality in orthotopic glioblastoma xenograft models. Notably, neither the degree of EGFR-signaling inhibition nor genetic analysis of EGFR was sufficient to predict sensitivity to this therapeutic combination. However, detection of rapid inhibitory effects on [18F]fluorodeoxyglucose uptake, assessed through noninvasive positron emission tomography, was an effective predictive biomarker of response in vivo. Together, these studies identify a crucial link among oncogene signaling, glucose metabolism, and cytoplasmic p53, which may potentially be exploited for combination therapy in GBM and possibly other malignancies

    Entrepreneurial sons, patriarchy and the Colonels' experiment in Thessaly, rural Greece

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    Existing studies within the field of institutional entrepreneurship explore how entrepreneurs influence change in economic institutions. This paper turns the attention of scholarly inquiry on the antecedents of deinstitutionalization and more specifically, the influence of entrepreneurship in shaping social institutions such as patriarchy. The paper draws from the findings of ethnographic work in two Greek lowland village communities during the military Dictatorship (1967–1974). Paradoxically this era associated with the spread of mechanization, cheap credit, revaluation of labour and clear means-ends relations, signalled entrepreneurial sons’ individuated dissent and activism who were now able to question the Patriarch’s authority, recognize opportunities and act as unintentional agents of deinstitutionalization. A ‘different’ model of institutional change is presented here, where politics intersects with entrepreneurs, in changing social institutions. This model discusses the external drivers of institutional atrophy and how handling dissensus (and its varieties over historical time) is instrumental in enabling institutional entrepreneurship
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