A model for space-time threshold exceedances with an application to extreme rainfall

In extreme value studies models for observations exceeding a fixed high threshold have the advantage of exploiting the available extremal information, while avoiding bias from low values. In the context of space-time data, the challenge is to develop models for threshold exceedances that account for both spatial and temporal dependence. We address this issue through a modelling approach that embeds spatial dependence within a time series formulation. The model allows for different forms of limiting dependence in the spatial and temporal domains as the threshold level increases. In particular, temporal asymptotic independence is assumed, as this is often supported by empirical evidence, especially in environmental applications, while both asymptotic dependence and asymptotic independence are considered for the spatial domain. Inference from the observed exceedances is carried out through a combination of pairwise likelihood and a censoring mechanism. For those model specifications for which direct maximization of the censored pairwise likelihood is unfeasible, we propose an indirect inference procedure which leads to satisfactory results in a simulation study. The approach is applied to a dataset of rainfall amounts recorded over a set of weather stations in the North Brabant province of the Netherlands. The application shows that the range of extremal patterns that the model can cover is wide and that it has a competitive performance with respect to an alternative existing model for space-time threshold exceedances

Clinical usefulness of oral supplementation with alpha-lipoic acid, curcumin phytosome, and B-group vitamins in patients with carpal tunnel syndrome undergoing surgical treatment

We investigated the clinical usefulness of oral supplementation with a combination product containing alpha-lipoic acid, curcumin phytosome, and B-group vitamins in 180 patients with carpal tunnel syndrome (CTS), scheduled to undergo surgical decompression of the median nerve. Patients in Group A (n = 60) served as controls and did not receive any treatment either before or after surgery. Patients in Group B (n = 60) received oral supplementation twice a day for 3 months both before and after surgery (totaling 6 months of supplementation). Patients in Group C (n = 60) received oral supplementation twice a day for 3 months before surgery only. Patients in Group B showed significantly lower nocturnal symptoms scores compared with Group A subjects at both 40 days and 3 months after surgery (both P values < 0.05). Moreover, patients in Group B had a significantly lower number of positive Phalen's tests at 3 months compared with the other study groups (P < 0.05). We conclude that oral supplementation with alpha-lipoic acid, curcumin phytosome, and B-group vitamins twice a day both before and after surgery is safe and effective in CTS patients scheduled to undergo surgical decompression of the median nerve

Characterization of a Be(p,xn) neutron source for fission yields measurements

We report on measurements performed at The Svedberg Laboratory (TSL) to characterize a proton-neutron converter for independent fission yield studies at the IGISOL-JYFLTRAP facility (Jyv\"askyl\"a, Finland). A 30 MeV proton beam impinged on a 5 mm water-cooled Beryllium target. Two independent experimental techniques have been used to measure the neutron spectrum: a Time of Flight (TOF) system used to estimate the high-energy contribution, and a Bonner Sphere Spectrometer able to provide precise results from thermal energies up to 20 MeV. An overlap between the energy regions covered by the two systems will permit a cross-check of the results from the different techniques. In this paper, the measurement and analysis techniques will be presented together with some preliminary results.Comment: 3 pages, 3 figures, also submitted as proceedings of the International Conference on Nuclear Data for Science and Technology 201

Non-linear regression models for Approximate Bayesian Computation

Approximate Bayesian inference on the basis of summary statistics is well-suited to complex problems for which the likelihood is either mathematically or computationally intractable. However the methods that use rejection suffer from the curse of dimensionality when the number of summary statistics is increased. Here we propose a machine-learning approach to the estimation of the posterior density by introducing two innovations. The new method fits a nonlinear conditional heteroscedastic regression of the parameter on the summary statistics, and then adaptively improves estimation using importance sampling. The new algorithm is compared to the state-of-the-art approximate Bayesian methods, and achieves considerable reduction of the computational burden in two examples of inference in statistical genetics and in a queueing model.Comment: 4 figures; version 3 minor changes; to appear in Statistics and Computin

Microdosimetry on nanometric scale with a new low-pressure avalanche-confinement TEPC

The tissue equivalent proportional counter (TEPC) is the most accurate device for measuring the microdosimetric properties of a particle beam, nevertheless no detailed information on the track structure of the impinging particles can be obtained, since the lower operation limit of common TEPCs is about 0.3 μm. On the other hand, the pattern of particle interactions is measured by track-nanodosimetry, which derives the single-event distribution of ionization cluster size at the nanometric scale. Anyway, only three nanodosimeters are available worldwide. A feasibility study for extending the performances of TEPC down to the nanometric region was performed and a novel avalanche-confinement TEPC was designed and constructed. This detector is constituted by a cylindrical chamber, based on a three-electrode structure, connected to a vacuum and gas flow system to ensure a continuous replacement of the tissue equivalent gas, thus allowing to simulate different biological site sizes in the range 300-25 nm. This TEPC can be calibrated by exploiting a built-in alpha source and a miniaturized solid-state detector as a trigger. Irradiations with photons, fast neutrons and two hadron beams demonstrated the good performances of the device. A satisfactory agreement with FLUKA simulations was obtained

Monocyte-to-lymphocye ratio (MLR) and LDH level in metastatic colorectal cancer (mCRC) patients (pts)

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Geometries of Light and Shadows, from Piero della Francesca to James Turrell

This chapter addresses the problem of representing light and shadow in the artistic culture, from its uncertain beginnings, related to the studies on conical linear perspective in the Fifteenth Century, to the applications of light projection in the installations of contemporary art. Here are examined in particular two works by two artists, representing two different conceptual approaches to the perception and symbolism of light and shadow. The first is the so-called Brera Madonna by Piero della Francesca, where the image projected from a luminous radiation is employed with a narrative purpose, supporting the apparently hidden script of the painting and according to the artist\u2019s own speculations about perspective as a means to clarify the phenomenal world. The second is one of James Turrell\u2019s Dark Spaces installations, where quantum electrodynamics interpretation of light is taken into account: for Turrell, light is physical and thus can shape spaces where the visitors, or viewers, can \u201csee themselves seeing.\u201d In his body of work, perceptual deceptions are carefullyproduced by the interaction of the senses with his phenomenal staging of light and darkness, but a strong symbolic component is always present, often related to his own speculative interests. In both cases, light and shadow, through their geometries, emphasize both phenomenal and spiritual contents of the work of art, intended as a device to expand the perception and the knowledge of the viewer

ESTUDO DO ENVELHECIMENTO ACELERADO DE UM NOVO ÓLEO VEGETAL ISOLANTE, À BASE DE PINHÃO-MANSO, PARA USO EM TRANSFORMADORES ELÉTRICOS

O presente trabalho foca na avaliação de um novo fluido isolante vegetal para transformadores elétricos de potência à base do óleo de Jatropha curcas. Foi proposta uma metodologia para ensaios de envelhecimento acelerado do óleo, a fim de verificar o comportamento deste em condições extremas, comparando-o com fluido comercial BIOTEMP®. Utilizou-se óleo de Jatropha curcas extraído e processado neste estudo, cujas propriedades preencheram todas as especificações das normas ASTM D6871 e ABNT NBR 15422 para óleos vegetais isolantes novos para transformador. Os ensaios de envelhecimento acelerado foram realizados utilizando os dois óleos em diferentes condições: sem aditivos; com a adição de fio de cobre e papel Kraft; e com a adição destes dois componentes mais  antioxidantes. Os antioxidantes utilizados foram o ácido ascórbico, BHT (di-terc-butil-metilfenol) e TBHQ (terc-butil hidroquinona). O melhor resultado para o óleo de Jatropha curcas (menor viscosidade e menor variação do índice de acidez) foi obtido na presença de TBHQ 2 %m/m óleo, fio de cobre e papel kraft. No entanto, o BIOTEMP® foi mais estável do que o óleo de Jatropha curcas. Este estudo indicou que o óleo de Jatropha curcas tem potencial para ser usado em transformadores de potência. No entanto, os testes de envelhecimento acelerado precisam ser refinados

ABCtoolbox: a versatile toolkit for approximate Bayesian computations

BACKGROUND: The estimation of demographic parameters from genetic data often requires the computation of likelihoods. However, the likelihood function is computationally intractable for many realistic evolutionary models, and the use of Bayesian inference has therefore been limited to very simple models. The situation changed recently with the advent of Approximate Bayesian Computation (ABC) algorithms allowing one to obtain parameter posterior distributions based on simulations not requiring likelihood computations. RESULTS: Here we present ABCtoolbox, a series of open source programs to perform Approximate Bayesian Computations (ABC). It implements various ABC algorithms including rejection sampling, MCMC without likelihood, a Particle-based sampler and ABC-GLM. ABCtoolbox is bundled with, but not limited to, a program that allows parameter inference in a population genetics context and the simultaneous use of different types of markers with different ploidy levels. In addition, ABCtoolbox can also interact with most simulation and summary statistics computation programs. The usability of the ABCtoolbox is demonstrated by inferring the evolutionary history of two evolutionary lineages of Microtus arvalis. Using nuclear microsatellites and mitochondrial sequence data in the same estimation procedure enabled us to infer sex-specific population sizes and migration rates and to find that males show smaller population sizes but much higher levels of migration than females. CONCLUSION: ABCtoolbox allows a user to perform all the necessary steps of a full ABC analysis, from parameter sampling from prior distributions, data simulations, computation of summary statistics, estimation of posterior distributions, model choice, validation of the estimation procedure, and visualization of the results