Epatite E: ruolo del suino nella trasmissione dell'infezione all'uomo, studio di prevalenza in aree rurali della Bolivia

L’infezione da virus dell’ epatite E (HEV) nei suini e nell’uomo è stata segnalata in diversi Paesi. Nei suini, il virus causa infezioni asintomatiche, mentre nell’uomo è responsabile di epidemie di epatite ad andamento acuto nei Paesi a clima tropicale o subtropicale con condizioni igieniche scadenti, di casi sporadici in quelli sviluppati. HEV è stato isolato anche in diversi animali e l’analisi nucleotidica degli isolati virali di origine animale ha mostrato un elevato grado di omologia con i ceppi di HEV umani isolati nelle stesse aree geografiche, avvalorando l’ipotesi che l'infezione da HEV sia una zoonosi. In America del Sud HEV suino è stato isolato per la prima volta in suini argentini nel 2006, mentre solo dal 1998 esistono dati sull’ infezione da HEV nell’uomo in Bolivia. In questa indagine è stato eseguito uno studio di sieroprevalenza in due comunità rurali boliviane e i risultati sono stati confrontati con quelli dello studio di sieroprevalenza sopra menzionato condotto in altre zone rurali della Bolivia. Inoltre, mediante Nested RT-PCR, è stata verificata la presenza di HEV nella popolazione umana e suina. La sieroprevalenza per anticorpi IgG anti-HEV è risultata pari al 6,2%, molto simile a quella evidenziata nello studio precedente. La prevalenza maggiore (24%) si è osservata nei soggetti di età compresa tra 41 e 50 anni, confermando che l’ infezione da HEV è maggiore fra i giovani-adulti. La ricerca di anticorpi anti HEV di classe IgM eseguita su 52 sieri ha fornito 4 risultati positivi. Il genoma virale è stato identificato in uno dei 22 pool di feci umane e l'esame virologico di 30 campioni individuali fecali e 7 individuali di siero ha fornito rispettivamente risultati positivi in 4/30 e 1/7. La Nested RT-PCR eseguita sui 22 pool di feci suine ha dato esito positivo in 7 pool. L’analisi delle sequenze genomiche di tutti gli amplificati ha consentito di stabilire che gli isolati umani appartenevano allo stesso genotipo III di quelli suini e presentavano con questi una elevata omologia aminoacidica (92%).

Non-Markovian stochastic processes and their applications: from anomalous diffusion to time series analysis

This work provides a forward step in the study and comprehension of the relationships between stochastic processes and a certain class of integral-partial differential equation, which can be used in order to model anomalous diffusion and transport in statistical physics. In the first part, we brought the reader through the fundamental notions of probability and stochastic processes, stochastic integration and stochastic differential equations as well. In particular, within the study of H-sssi processes, we focused on fractional Brownian motion (fBm) and its discrete-time increment process, the fractional Gaussian noise (fGn), which provide examples of non-Markovian Gaussian processes. The fGn, together with stationary FARIMA processes, is widely used in the modeling and estimation of long-memory, or long-range dependence (LRD). Time series manifesting long-range dependence, are often observed in nature especially in physics, meteorology, climatology, but also in hydrology, geophysics, economy and many others. We deepely studied LRD, giving many real data examples, providing statistical analysis and introducing parametric methods of estimation. Then, we introduced the theory of fractional integrals and derivatives, which indeed turns out to be very appropriate for studying and modeling systems with long-memory properties. After having introduced the basics concepts, we provided many examples and applications. For instance, we investigated the relaxation equation with distributed order time-fractional derivatives, which describes models characterized by a strong memory component and can be used to model relaxation in complex systems, which deviates from the classical exponential Debye pattern. Then, we focused in the study of generalizations of the standard diffusion equation, by passing through the preliminary study of the fractional forward drift equation. Such generalizations have been obtained by using fractional integrals and derivatives of distributed orders. In order to find a connection between the anomalous diffusion described by these equations and the long-range dependence, we introduced and studied the generalized grey Brownian motion (ggBm), which is actually a parametric class of H-sssi processes, which have indeed marginal probability density function evolving in time according to a partial integro-differential equation of fractional type. The ggBm is of course Non-Markovian. All around the work, we have remarked many times that, starting from a master equation of a probability density function f(x,t), it is always possible to define an equivalence class of stochastic processes with the same marginal density function f(x,t). All these processes provide suitable stochastic models for the starting equation. Studying the ggBm, we just focused on a subclass made up of processes with stationary increments. The ggBm has been defined canonically in the so called grey noise space. However, we have been able to provide a characterization notwithstanding the underline probability space. We also pointed out that that the generalized grey Brownian motion is a direct generalization of a Gaussian process and in particular it generalizes Brownain motion and fractional Brownain motion as well. Finally, we introduced and analyzed a more general class of diffusion type equations related to certain non-Markovian stochastic processes. We started from the forward drift equation, which have been made non-local in time by the introduction of a suitable chosen memory kernel K(t). The resulting non-Markovian equation has been interpreted in a natural way as the evolution equation of the marginal density function of a random time process l(t). We then consider the subordinated process Y(t)=X(l(t)) where X(t) is a Markovian diffusion. The corresponding time-evolution of the marginal density function of Y(t) is governed by a non-Markovian Fokker-Planck equation which involves the same memory kernel K(t). We developed several applications and derived the exact solutions. Moreover, we considered different stochastic models for the given equations, providing path simulations.

Aumento della risoluzione spaziale per il sondaggio di temperatura e umidità da satellite geostazionario mediante radiometria ad onde millimetriche e submillimetriche

The purpose of this study is to develop and evaluate techniques that improve the spatial resolution of the channels already selected in the preliminary studies for Geostationary Observatory for Microwave Atmospheric Soundings (GOMAS). Reference high resolution multifrequency brightness temperatures scenarios have been derived by applying radiative transfer calculation to the spatially and microphysically detailed output of meteorological events simulated by the University of Wisconsin - Non-hydrostatic Model System (UW-NMS). Three approaches, Wiener filter, Super-Resolution and Image Fusion have been applied to some representative GOMAS frequency channels to enhance the resolution of antenna temperatures. The Wiener filter improved resolution of the largely oversampled images by a factor 1.5- 2.0 without introducing any penalty in the radiometric accuracy. Super-resolution, suitable for not largely oversampled images, improved resolution by a factor ~1.5 but introducing an increased radiometric noise by a factor 1.4-2.5. The image fusion allows finally to further increase the spatial frequency of the images obtained by the Wiener filter increasing the total resolution up to a factor 5.0 with an increased radiometric noise closely linked to the radiometric frequency and to the examined case study.