On the protocol dependence of plasticity in ultra-stable amorphous solids

While perfect crystals may exhibit a purely elastic response to shear all the way to yielding, the response of amorphous solids is punctuated by plastic events. The prevalence of this plasticity depends on the number of particles $N$ of the system, with the average strain interval before the first plastic event, $\overline{\Delta\gamma}$, scaling like $N^\alpha$ with $\alpha$ negative: larger samples are more susceptible to plasticity due to more numerous disorder-induced soft spots. In this paper we examine this scaling relation in ultra-stable glasses prepared with the Swap Monte Carlo algorithm, with regard to the possibility of protocol-dependent scaling exponent, which would also imply a protocol dependence in the distribution of local yield stresses in the glass. We show that, while a superficial analysis seems to corroborate this hypothesis, this is only a pre-asymptotic effect and in fact our data can be well explained by a simple model wherein such protocol dependence is absent.Comment: 7 pages, 9 figures; figures improved, implications on the issue of a static glass lengthscale are discusse

ELM regime classification by conformal prediction on an information manifold

Characterization and control of plasma instabilities known as edge-localized modes (ELMs) is crucial for the operation of fusion reactors. Recently, machine learning methods have demonstrated good potential in making useful inferences from stochastic fusion data sets. However, traditional classification methods do not offer an inherent estimate of the goodness of their prediction. In this paper, a distance-based conformal predictor classifier integrated with a geometric-probabilistic framework is presented. The first benefit of the approach lies in its comprehensive treatment of highly stochastic fusion data sets, by modeling the measurements with probability distributions in a metric space. This enables calculation of a natural distance measure between probability distributions: the Rao geodesic distance. Second, the predictions are accompanied by estimates of their accuracy and reliability. The method is applied to the classification of regimes characterized by different types of ELMs based on the measurements of global parameters and their error bars. This yields promising success rates and outperforms state-of-the-art automatic techniques for recognizing ELM signatures. The estimates of goodness of the predictions increase the confidence of classification by ELM experts, while allowing more reliable decisions regarding plasma control and at the same time increasing the robustness of the control system

Review of The Ruined Nest and Other Stories by Rabindranath Tagore, ed. and trans. by Mohammad A. Quayum.

Review of The Ruined Nest and Other Stories by Rabindranath Tagore, ed. and trans. by Mohammad A. Quayu

Reviews

Obra ressenyada: Indira Chowdhury SENGUPTA (comp.); J. Crowther (ed.). The Indian English Supplement to the Advanced Learner's Dictionary of Current English. 5th edition. Oxford: Oxford University Press, 1996

EPACs: epigenetic regulators that affect cell survival in cancer.

Cyclic adenosine monophosphate (cAMP) is a second messenger responsive to many external stimuli, playing an important role in cellular gene expression, metabolism, migration, differentiation, hypertrophy, apoptosis and secretion. All of these cellular functions are important in many diseases including cancer. Most of its effects were initially attributed to the classical protein kinase A (PKA) protein, but cellular functions such as proliferation and migration were found to be PKA independent and dependent on the newly discovered exchange proteins directly activated by cAMP (EPACs). EPACs are single polypeptides that primarily function as guanine exchange factors (GEFs) for Rap proteins that allow the replacement of guanine diphosphate (GDP) with the more abundant guanosine triphosphate (GTP), under cAMP stimulation. EPAC has been reported to promote cancer cell growth and activate phosphhatidylinositol 3-kinase (PI3K) in direct opposition to the effects of PKA. This was confirmed in the Brattain Laboratory, treating colorectal cancer (CRC) cell lines with the EPAC specific activator 8CPT (8-pCPT-2-O-Me-cAMP) induced AKT expression along with increased expression of inhibitor of apoptosis protein (IAP) survivin and X-linked IAP (XIAP); which are implicated with poor prognosis in cancer. However, there are 2 isoforms of EPAC – EPAC1 and 2 and to dissect which EPAC is pro-tumorigenic we used EPAC specific inhibitors (ESI) – ESI09 (inhibits EPAC1 and 2), ESI05 (inhibits EPAC2) and CE3F4 (inhibits EPAC1) and confirmed that EPAC1 is associated with cell survival in CRC cell line as well as in pancreatic cancer (PaCa) cell lines. Inhibition of EPACs decreased histone deacetylase (HDAC) 4 and 5 that are overexpressed in many cancers. Inhibition of HDAC4 and 5 with LMK235 decreased survivin and XIAP allowing us to hypothesize that the cell survival effects observed on EPAC inhibition must be due to the repression of HDACs 4 and 5 making EPACs epigenetic regulators