1,721,105 research outputs found
Replication technic in scanning electron microscopy: possibilities for use in the field of biology. Comparative study of various materials and methods [La tecnica della replica in microscopia elettronica a scansione: possibilita applicative in campo biologico. Studio comparativo di differenti materiali e metodologie.]
No full textLe tecniche di preparazione dei tessuti dentari per lo studio al microscopio elettronico a scansione
No full textFour-dimensional ensemble variational data assimilation and the unstable subspace
No full textThe performance of (ensemble) Kalman filters used for data assimilation in the geosciences critically depends on the dynamical properties of the evolutionmodel.Akey aspect is that the error covariance matrix is asymptotically supported by the unstable-neutral subspace only, i.e. it is spanned by the backward Lyapunov vectors with non-negative exponents. The analytic proof of such a property for the Kalman filter error covariance has been recently given, and in particular that of its confinement to the unstable-neutral subspace. In this paper, we first generalize those results to the case of the Kalman smoother in a linear, Gaussian and perfect model scenario. We also provide square-root formulae for the filter and smoother that make the connection with ensemble formulations of the Kalman filter and smoother, where the span of the error covariance is described in terms of the ensemble deviations from the mean.We then discuss how this neat picture is modified when the dynamics are nonlinear and chaotic, and for which analytic results are precluded or difficult to obtain. A numerical investigation is carried out to study the approximate confinement of the anomalies for both a deterministic ensemble Kalman filter (EnKF) and a four-dimensional ensemble variational method, the iterative ensemble Kalman smoother (IEnKS), in a perfect model scenario. The confinement is characterized using geometrical angles that determine the relative position of the anomalies with respect to the unstable-neutral subspace. The alignment of the anomalies and of the unstable-neutral subspace is more pronounced when observation precision or frequency, as well as the data assimilation window length for the IEnKS, are increased. These results also suggest that the IEnKS and the deterministic EnKF realize in practice (albeit implicitly) the paradigm behind the approach of Anna Trevisan and co-authors known as the assimilation in the unstable subspace
Introduction to scanning electron microscopy | [Nozioni introduttive di microscopia elettronica a scansione.]
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Riqualificazione del quartiere Carrassi a Bari
No full textL'oggetto della mia Tesi è un progetto per la riqualificazione del quartiere Carrassi a Bari.
Lo sviluppo del progetto è stato preceduto da un lavoro di analisi. Partendo dall'analisi storica della città con particolare attenzione allo sviluppo del quartiere Carrassi sono state poi effettuate delle analisi dello spazio pubblico, dell'edificato e della relazione tra essi. Queste analisi hanno evidenziato una carenza nel rione Carrassi di spazi pubblici e di aggregazione, una estrema saturazione e disomogeneità dell'edificato con scarse possibilità di costruzione ex novo. Per dare una risposta a queste problematiche ho sviluppato un progetto che si articola su tre livelli di intervento, la riqualificazione della strada, la riqualificazione delle corti interne agli isolati e la creazione di una nuova sede di quartiere
Attività di un servizio di diagnosi e terapia delle affezioni delle mucose orali negli anni 1981-1988
No full textInferring the instability of a dynamical system from the skill of data assimilation exercises
Full text linkData assimilation (DA) aims at optimally merging observational data and model outputs to create a coherent statistical and dynamical picture of the system under investigation. Indeed, DA aims at minimizing the effect of observational and model error and at distilling the correct ingredients of its dynamics. DA is of critical importance for the analysis of systems featuring sensitive dependence on the initial conditions, as chaos wins over any finitely accurate knowledge of the state of the system, even in absence of model error. Clearly, the skill of DA is guided by the properties of dynamical system under investigation, as merging optimally observational data and model outputs is harder when strong instabilities are present. In this paper we reverse the usual angle on the problem and show that it is indeed possible to use the skill of DA to infer some basic properties of the tangent space of the system, which may be hard to compute in very high-dimensional systems. Here, we focus our attention on the first Lyapunov exponent and the Kolmogorov-Sinai entropy and perform numerical experiments on the Vissio-Lucarini 2020 model, a recently proposed generalization of the Lorenz 1996 model that is able to describe in a simple yet meaningful way the interplay between dynamical and thermodynamical variables
On the numerical integration of the Lorenz-96 model, with scalar additive noise, for benchmark twin experiments
Full text linkRelatively little attention has been given to the impact of discretization error on twin experiments in the stochastic form of the Lorenz-96 equations when the dynamics are fully resolved but random. We study a simple form of the stochastically forced Lorenz-96 equations that is amenable to higher-order time-discretization schemes in order to investigate these effects. We provide numerical benchmarks for the overall discretization error, in the strong and weak sense, for several commonly used integration schemes and compare these methods for biases introduced into ensemble-based statistics and filtering performance. The distinction between strong and weak convergence of the numerical schemes is focused on, highlighting which of the two concepts is relevant based on the problem at hand. Using the above analysis, we suggest a mathematically consistent framework for the treatment of these discretization errors in ensemble forecasting and data assimilation twin experiments for unbiased and computationally efficient benchmark studies. Pursuant to this, we provide a novel derivation of the order 2.0 strong Taylor scheme for numerically generating the truth twin in the stochastically perturbed Lorenz-96 equations
Data assimilation by delay-coordinate nudging
No full textA new nudging method for data assimilation, delay-coordinate nudging, is presented. Delay-coordinate nudging makes explicit use of present and past observations in the formulation of the forcing driving the model evolution at each time step. Numerical experiments with a low-order chaotic system show that the new method systematically outperforms standard nudging in different model and observational scenarios, also when using an unoptimized formulation of the delay-nudging coefficients. A connection between the optimal delay and the dominant Lyapunov exponent of the dynamics is found based on heuristic arguments and is confirmed by the numerical results, providing a guideline for the practical implementation of the algorithm. Delay-coordinate nudging preserves the easiness of implementation, the intuitive functioning and the reduced computational cost of the standard nudging, making it a potential alternative especially in the field of seasonal-to-decadal predictions with large Earth system models that limit the use of more sophisticated data assimilation procedures
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