21,073 research outputs found
Le sinfonie di Luigi Boccherini: contesti, fonti, analisi. Marco Mangani, Germán Labrador, Matteo Giuggioli (eds.) [reseña de libro]
No full textReseña del libro: Mangani, Marco; Labrador, Germán; Giuggioli, Matteo (eds.). Le sinfonie di Luigi Boccherini: contesti, fonti, analisi. Florencia: Leo S. Olschki Editore, 2019
I principi epistemologici della botanica di Guy de La Brosse
No full textThis paper investigates some core aspects of Guy de La Brosse’s (1586-1641) botanical work. In the first section, the focus is on the epistemological principles of La Brosse’s botany by analyzing the first and second book of the treatise De la nature, vertu et utilité des plantes (1628). In the second section, the author discusses the role of Paracelsus’s chemistry in La Brosse’s work, with a particular attention to the third book of the De la nature. The final section deals with La Brosse’s interest in the visualization of plants. Here, the author provides the transcription and first Italian translation of a short manuscript related to Abraham Bosse’s engravings for La Brosse’s unfinished book Icones posthumae
La performance teatral del juglar contemporani Matteo Belli
No full textEn aquesta dissertació he intentat recórrer els principals elements que caracteritzen el treball teatral de l'actor contemporani bolonyès Matteo Belli. La primera part se centra en les informacions bàsiques, necessàries per col·locar correctament el fenòmen tan complex com fascinant del joglar. En segona instància, he pensat en aprofundir l'aspecte de la comicitat introduint directament el treball de Belli, i relacionar-lo, per dir-ho així, amb el panorama actual del teatre contemporani. A més a més, he presentat alguns exemples relacionats amb algunes obres d'artistes moderns i contemporanis italians, d'aquesta manera prentenc comprendre millor el procés de voluntarietat que s'amaga darrere la comicitat i els seus mecanismes intrínsecs. Per concloure, he inclòs una entrevista amb ell, que em va concedir en aquests quatre anys de recerca, on es pot apreciar, no només un gran coneixement del món de l'espectacle, sinó que també una profunda espessor cultural
The asymptotic loss distribution in a fat-tailed factor model of portfolio credit risk
No full textThis paper extends the standard asymptotic results concerning the percentage loss distribution in the Vasicek uniform model to a setup where the systematic risk factor is non-normally distributed. We show that the asymptotic density in this new setup can still be obtained in closed form; in particular, we derive the return distributions, the densities and the quantile functions when the common factor follows two types of normal mixture distributions (a two-population scale mixture and a jump mixture) and the Student’s t distribution. Finally, we present a real-data application of the technique to data of the Intesa - San Paolo credit portfolio. The numerical experiments show that the asymptotic loss density is highly flexible and provides the analyst with a VaR which takes into account the event risk incorporated in the fat-tailed distribution of the common factor.Factor model, asymptotic loss, Value at Risk.
Matteo CADARIO, La corazza di Alessandro. Loricati di tipo ellenistico dal IV sec. a.C. al II d.C
No full textCavalieri Marco. Matteo CADARIO, La corazza di Alessandro. Loricati di tipo ellenistico dal IV sec. a.C. al II d.C . In: L'antiquité classique, Tome 75, 2006. pp. 626-629
Matteo CADARIO, La corazza di Alessandro. Loricati di tipo ellenistico dal IV sec. a.C. al II d.C
No full textCavalieri Marco. Matteo CADARIO, La corazza di Alessandro. Loricati di tipo ellenistico dal IV sec. a.C. al II d.C . In: L'antiquité classique, Tome 75, 2006. pp. 626-629
A Monte Carlo EM Algorithm for the Estimation of a Logistic Auto-logistic Model with Missing Data
No full textThis paper proposes an algorithm for the estimation of the parameters of a Logistic Auto-logistic Model when some values of the target variable are missing at random but the auxiliary information is known for the same areas. First, we derive a Monte Carlo EM algorithm in the setup of maximum pseudo-likelihood estimation; given the analytical intractability of the conditional expectation of the complete pseudo-likelihood function, we implement the E-step by means of Monte Carlo simulation. Second, we give an example using a simulated dataset. Finally, a comparison with the standard non-missing data case shows that the algorithm gives consistent results.Spatial Missing Data, Monte Carlo EM Algorithm, Logistic Auto-logistic Model, Pseudo-Likelihood.
Computer-Aided Design of Novel Antagonists of the EphA2 Receptor
No full textThe Eph receptors are a large family of receptor tyrosine kinases, and their activity and downstream signaling ability are stimulated by the binding of cell membrane ligands known as ephrins [1]. A growing body of evidence suggests that the pharmacological modulation of the Eph-ephrin system may lead to innovative therapies for the treatment of solid tumors and neurodegenerative disorders [2]. However, the conclusive validation of Eph receptors as a drug targets is hampered by the lack of pharmacological tools featured by PD and PK profiles suitable for in vivo administration.
The discovery of small molecules able to disrupt the Eph-ephrin interaction is a challenging task, due to the large size of the protein interacting surfaces and the lack of specialized chemical libraries to be used in HTS campaigns. Despite these shortcomings, we recently identified lithocholic acid (LCA) as a micromolar antagonist of the EphA2 receptor by means of an ELISA-based screening [2]. In the present talk, the results of our medicinal chemistry efforts devoted to the PD-optimization of LCA will be presented [3,4]. Details of the computational strategies applied to guide the synthesis of novel compounds will be discussed along with an analysis of the structure-activity relationships
Spatial models for flood risk assessment
No full textThe problem of computing risk measures associated to flood events is extremely important not only from the point of view of civil protection systems but also because of the necessity for the municipalities of insuring against the damages. In this work we propose, in the framework of an integrated strategy, an operating solution which merges in a conditional approach the information usually available in this setup. First we use a Logistic Auto-Logistic (LAM) model for the estimation of the univariate conditional probabilities of flood events. This approach has two fundamental advantages: it allows to incorporate auxiliary information and does not require the target variables to be indepen- dent. Then we simulate the joint distribution of floodings by means of the Gibbs Sampler. Finally we propose an algorithm to increase ex post the spatial autocorrelation of the simulated events. The methodology is shown to be effective by means of an application to the estimation of the flood probability of Italian hydrographic regions.Flood Risk, Conditional Approach, LAM Model, Pseudo-Maximum Likelihood Estimation, Spatial Autocorrelation, Gibbs Sampler.
A note on maximum likelihood estimation of a Pareto mixture
No full textIn this paper we study Maximum Likelihood Estimation of the parameters of a Pareto mixture. Application of standard techniques to a mixture of Pareto is problematic. For this reason we develop two alternative algorithms. The first one is the Simulated Annealing and the second one is based on Cross-Entropy minimization. The Pareto distribution is a commonly used model for heavy-tailed data. It is a two-parameter distribution whose shape parameter determines the degree of heaviness of the tail, so that it can be adapted to data with different features. This work is motivated by an application in the operational risk measurement field: we fit a Pareto mixture to operational losses recorded by a bank in two different business lines. Losses below an unknown threshold are discarded, so that the observed data are truncated. The thresholds used in the two business lines are unknown. Thus, under the assumption that each population follows a Pareto distribution, the appropriate model is a mixture of Pareto where all the parameters have to be estimated.
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