Solving the stellar 62Ni problem with AMS

An accurate knowledge of the neutron capture cross sections of 62,63Ni is crucial since both isotopes take key positions which affect the whole reaction flow in the weak s process up to A=90. No experimental value for the 63Ni(n,gamma) cross section exists so far, and until recently the experimental values for 62Ni(n,gamma) at stellar temperatures (kT=30 keV) ranged between 12 and 37 mb. This latter discrepancy could now be solved by two activations with following AMS using the GAMS setup at the Munich tandem accelerator which are also in perfect agreement with a recent time-of-flight measurement. The resulting (preliminary) Maxwellian cross section at kT=30 keV was determined to be 30keV = 23.4 +/- 4.6 mb. Additionally, we have measured the 64Ni(gamma,n)63Ni cross section close to threshold. Photoactivations at 13.5 MeV, 11.4 MeV and 10.3 MeV were carried out with the ELBE accelerator at Forschungszentrum Dresden-Rossendorf. A first AMS measurement of the sample activated at 13.5 MeV revealed a cross section smaller by more than a factor of 2 compared to NON-SMOKER predictions.Comment: Proceedings of the 11th International Conference on Accelerator Mass Spectrometry in Rome, Sept. 14-19, 2008; to be published in Nucl. Instr. Meth.

Transfer learning for galaxy morphology from one survey to another

© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of $\sim$5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy ($\sim$ 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies ($\sim$500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.Peer reviewedFinal Accepted Versio

A new regulatory mechanism of protein phosphatase 2A activity via SET in acute myeloid leukemia

Acute myeloid leukemia (AML) is an aggressive hematologic malignancy. Although novel emerging drugs are available, the overall prognosis remains poor and new therapeutic approaches are required. PP2A phosphatase is a key regulator of cell homeostasis and is recurrently inactivated in AML. The anticancer activity of several PP2A-activating drugs (e.g., FTY720) depends on their interaction with the SET oncoprotein, an endogenous PP2A inhibitor that is overexpressed in 30% of AML cases. Elucidation of SET regulatory mechanisms may therefore provide novel targeted therapies for SET-overexpressing AMLs. Here, we show that upregulation of protein kinase p38 beta is a common event in AML. We provide evidence that p38 beta potentiates SET-mediated PP2A inactivation by two mechanisms: facilitating SET cytoplasmic translocation through CK2 phosphorylation, and directly binding to and stabilizing the SET protein. We demonstrate the importance of this new regulatory mechanism in primary AML cells from patients and in zebrafish xenograft models. Accordingly, combination of the CK2 inhibitor CX-4945, which retains SET in the nucleus, and FTY720, which disrupts the SET-PP2A binding in the cytoplasm, significantly reduces the viability and migration of AML cells. In conclusion, we show that the p38 beta/CK2/SET axis represents a new potential therapeutic pathway in AML patients with SET-dependent PP2A inactivation

Constrained Markovian dynamics of random graphs

We introduce a statistical mechanics formalism for the study of constrained graph evolution as a Markovian stochastic process, in analogy with that available for spin systems, deriving its basic properties and highlighting the role of the `mobility' (the number of allowed moves for any given graph). As an application of the general theory we analyze the properties of degree-preserving Markov chains based on elementary edge switchings. We give an exact yet simple formula for the mobility in terms of the graph's adjacency matrix and its spectrum. This formula allows us to define acceptance probabilities for edge switchings, such that the Markov chains become controlled Glauber-type detailed balance processes, designed to evolve to any required invariant measure (representing the asymptotic frequencies with which the allowed graphs are visited during the process). As a corollary we also derive a condition in terms of simple degree statistics, sufficient to guarantee that, in the limit where the number of nodes diverges, even for state-independent acceptance probabilities of proposed moves the invariant measure of the process will be uniform. We test our theory on synthetic graphs and on realistic larger graphs as studied in cellular biology.Comment: 28 pages, 6 figure