1,721,035 research outputs found
Stochastic geometry and related statistical problems in biomedicine
No full textMany processes of biomedical interest may be modelled as birth-and-growth processes (germ-grain models), which are composed of two processes, birth (nucleation, branching, etc.) and subsequent growth of spatial structures (cells, vessel networks, etc), which, in general, are both stochastic in time and space.
These structures induce a random division of the relevant spatial region, known as a random tessellation. A quantitative description of the spatial structure of the tessellation can be
given, in terms of the mean densities of interfaces (-facets).
In applications to medicine, it is very important for either prevention, or clinical treatment, to describe the relevant phenomenon in terms of a biomathematical model including all significant features (parameters ,variables) of the system.
One very significant example in this respect is the mathematical modelling of tumor growth and of tumor-induced angiogenesis.
The understanding of the principles and the dominant mechanisms underlying tumor growth is an essential prerequisite for identifying optimal control strategies, in terms of prevention and
treatment. Predictive mathematical models which are capable of producing quantitative morphological features of developing tumor
and blood vessels can contribute to this.
The difficulty arises from the strong coupling of the kinetic parameters of the relevant birth-and-growth (or branching-and-growth) process with interacting underlying fields, and the geometric spatial densities of the existing tumor, or
capillary network itself.
All these aspects induce stochastic time and space
heterogenities, thus motivating a more general analysis of the stochastic geometry of the process.
The formulation of an exhaustive evolution model which relates all the relevant
features of a real phenomenon dealing with different scales, and a stochastic domain decomposition at different Hausdorff dimensions, is a problem of high complexity, both analytical and computational.
Methods for reducing complexity include homogenization at larger scales, thus leading to hybrid models (deterministic at the larger scale, and stochastic at lower scales).
As a matter of example we present a couple of simplified stochastic geometric models, for which we discuss how to relate the geometric probability distribution to the kinetic parameters of birth and growth.
On the dual side, in order to compare numerical simulations of proposed mathematical models with existing data, we provide methods of statistical analysis for the estimation of geometric densities
that characterize the morphology of a real system
Simulation of the dynamics of an olympic rowing boat
No full textEditors: P. Wesseling, E. Oñate, J. Périau
Adaptive Tree Approximation with Finite Element Functions: A First Look
No full textWe provide an introduction to adaptive tree approximation with finite element functions over meshes that are generated by bisection. This approximation technique can be seen as a benchmark for adaptive finite element methods, but may be also used therein for the approximation of data and coarsening. Correspondingly, we focus on approximation problems related to adaptive finite element methods, the design and performance of algorithms, and the resulting convergence rates, together with the involved regularity. For simplicity and clarity, these issues are presented and discussed in detail in the univariate case. The additional technicalities and difficulties of the multivariate case are briefly outlined
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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