On moments of the integrated exponential Brownian motion

We present new exact expressions for a class of moments for the geometric Brownian motion, in terms of determinants, obtained using a recurrence relation and combinatorial arguments for the case of a Ito's Wiener process. We then apply the obtained exact formulas to computing averages of the solution of the logistic stochastic differential equation via a series expansion, and compare the results to the solution obtained via Monte Carlo

The rna-binding ubiquitin ligase mex3a affects glioblastoma tumorigenesis by inducing ubiquitylation and degradation of rig-i

Glioblastoma multiforme (GB) is the most malignant primary brain tumor in humans, with an overall survival of approximatively 15 months. The molecular heterogeneity of GB, as well as its rapid progression, invasiveness and the occurrence of drug-resistant cancer stem cells, limits the efficacy of the current treatments. In order to develop an innovative therapeutic strategy, it is mandatory to identify and characterize new molecular players responsible for the GB malignant phenotype. In this study, the RNA-binding ubiquitin ligase MEX3A was selected from a gene expression analysis performed on publicly available datasets, to assess its biological and still-unknown activity in GB tumorigenesis. We find that MEX3A is strongly up-regulated in GB specimens, and this correlates with very low protein levels of RIG-I, a tumor suppressor involved in differentiation, apoptosis and innate immune response. We demonstrate that MEX3A binds RIG-I and induces its ubiquitylation and proteasome-dependent degradation. Further, the genetic depletion of MEX3A leads to an increase of RIG-I protein levels and results in the suppression of GB cell growth. Our findings unveil a novel molecular mechanism involved in GB tumorigenesis and suggest MEX3A and RIG-I as promising therapeutic targets in GB

Quantum Bose-Hubbard model with an evolving graph as a toy model for emergent spacetime

We present a toy model for interacting matter and geometry that explores quantum dynamics in a spin system as a precursor to a quantum theory of gravity. The model has no a priori geometric properties; instead, locality is inferred from the more fundamental notion of interaction between the matter degrees of freedom. The interaction terms are themselves quantum degrees of freedom so that the structure of interactions and hence the resulting local and causal structures are dynamical. The system is a Hubbard model where the graph of the interactions is a set of quantum evolving variables. We show entanglement between spatial and matter degrees of freedom. We study numerically the quantum system and analyze its entanglement dynamics. We analyze the asymptotic behavior of the classical model. Finally, we discuss analogues of trapped surfaces and gravitational attraction in this simple model

Bipartite quantum states and random complex networks

We introduce a mapping between graphs and pure quantum bipartite states and show that the associated entanglement entropy conveys non-trivial information about the structure of the graph. Our primary goal is to investigate the family of random graphs known as complex networks. In the case of classical random graphs we derive an analytic expression for the averaged entanglement entropy $\bar S$ while for general complex networks we rely on numerics. For large number of nodes $n$ we find a scaling $\bar{S} \sim c \log n +g_e$ where both the prefactor $c$ and the sub-leading O(1) term $g_e$ are a characteristic of the different classes of complex networks. In particular, $g_e$ encodes topological features of the graphs and is named network topological entropy. Our results suggest that quantum entanglement may provide a powerful tool in the analysis of large complex networks with non-trivial topological properties.Comment: 4 pages, 3 figure

The suggested structure of final demand shock for sectoral labour digital skills

International data seem to confirm that countries with a relative abundancy of highly-skilled labour with digital competences grow faster than others. For this reason, digital competences and skills in general are progressively assuming a central role in labour market policies. In this article, we show the potential of the disaggregated multisectoral analysis with the macro multipliers approach as a tool of economic policy. Such analyses allow identifying a set of endogenous policies in which specific objectives do not clash with growth objectives. The identification and the quantification of the macro multipliers is based on an extended multi-industry, multi-factor and multi-sector model, which accounts for the representation of the income circular flow as in the social accounting matrix (SAM). The SAM constructed for this exercise allows for a proper disaggregation of the labour factor by formal educational attainment, digital competences and gender for the case of Italy

Politiche per l'industria: ridurre o abolire l'Irap?

L’imposta regionale sulle attività produttive (Irap) è oggetto di un ampio dibattito incentrato su alcune ipotesi di riforma relative alla riduzione o alla abolizione di questo strumento di prelievo, percepito dagli operatori come iniquo. L’argomentazione a sostegno di queste tesi si basa sul fatto che una diminuzione del prelievo potrebbe supportare ovvero stimolare il sistema produttivo, soprattutto in termini di competitività. L’analisi delle possibili riforme dell’Irap non dovrebbe trascurare gli effetti indotti dalla distribuzione del reddito, evidenziando quali potrebbero essere i percettori di reddito avvantaggiati e svantaggiati. In questo lavoro si utilizzerà un modello computazionale (CGE), implementato su una SAM (Social Accounting Matrix) che descrive il flusso circolare del reddito, per valutare l’impatto dei possibili scenari di riforma dell’Irap sulla produzione industriale, sul reddito reale, sul livello dei prezzi dei beni e dei fattori primari, sull’occupazione e sul bilancio dello Stato. Infine, in alternativa alla riforma Irap, si prenderà in considerazione l’ipotesi di destinare l’ammontare delle risorse disponibili alla riduzione delle aliquote Ire.Irap,Social Accounting Matrix,CGE,Ire

Spatially Resolved Event-Driven 24 × 24 Pixels SPAD Imager with 100% Duty Cycle for Low Optical Power Quantum Entanglement Detection

Quantum microscopy requires efficient detectors able to identify temporal correlations among photons. Photon coincidences are usually detected by postprocessing their timestamps measured by means of time-To-digital converters (TDCs), through a time and power-consuming procedure, which impairs the overall system performance. In this article, we propose an innovative single-photon sensitive imager based on single-photon avalanche diodes (SPADs), able to signal coincident photon pairs along with their position through a TDC-free, event-driven architecture. The result is a highly efficient detector (25.8%) with a 100% duty cycle and minimized data throughput. The modular architecture and the 330 ns readout time, independent of pixel number, pave the way to large format imagers based on the same paradigm. The detector enabled quantum imaging at extremely low, microwatt-level optical pump powers, four orders of magnitude lower than previous experiments with similar optical setups