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Revisiting the Gini Correction in L-Moments Estimation of the Weibull Shape Parameter

Il presente lavoro riesamina il ruolo del fattore di correzione dell’indice di Gini nella stima, mediante L-momenti, del parametro di forma della distribuzione di Weibull monoparametrica. Precedenti indagini numeriche hanno suggerito che il fattore di correzione tradizionale potrebbe non risultare ottimale nel caso di campioni di piccole dimensioni. Al fine di valutare il valore atteso e la distorsione dello stimatore, viene sviluppata un’espansione di Taylor del secondo ordine dello stimator...

On the work function dependency on molecular oxygen coverage for cesiated molybdenum surfaces

DFT-D method aimed at describing the pathways of surface mechanisms of reaction toward stable chemical systems and correlating the resulting structures of the adsorbates to the effects on the work function of the cesiated surface in presence of impurities, i.e. when ultra-high vacuum conditions aren’t met. We set up a computational procedure to mimic the O2 chemical reaction over the cesiated surface, at increasing concentrations of the impinging gas species, and to calculate the work functio...

Verifying Smart Contracts in Yul via Transformation to CHC by Interpreter Specialization

Yul is an intermediate representation that lies in between the (high-level) source code and the (low-level) bytecode languages for Ethereum smart contracts. Although it was proposed to favour the development of verification and optimization techniques, there exists no verifier that can be applied on Yul code directly yet. In this paper, we present a transformational approach to verifying Yul code by transforming it into an equivalent set of Constrained Horn Claus...

A DNABERT based deep learning framework for predicting transcription factor binding sites

Transcription factors are proteins that regulate the expression of genes by binding to specific genomic regions known as Transcription Factor Binding Sites (TFBSs), typically located in the promoter regions of those genes. Accurate prediction of these binding sites is essential for understanding the complex gene regulatory networks underlying various cellular functions. In this regard, many deep learning models have been developed for such prediction, but there is still scope of improvement. ...

Probing spin-electric transitions in a molecular exchange qubit

Electric fields represent an ideal means for controlling spins at the nanoscale and, more specifically, for manipulating protected degrees of freedom in multispin systems. Here we perform low-temperature magnetic far-IR spectroscopy on a molecular spin triangle (Fe3) and provide initial experimental evidence suggesting spin-electric transitions in polynuclear complexes. The co-presence of electric- and magnetic-dipole transitions, allows us to estimate the spin-electric coupling. Based on spi...

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  • DRIOLI, ENRICO1668
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