10,474 research outputs found
Classifying pairs with trees for supervised biological network inference
Networks are ubiquitous in biology and computational approaches have been
largely investigated for their inference. In particular, supervised machine
learning methods can be used to complete a partially known network by
integrating various measurements. Two main supervised frameworks have been
proposed: the local approach, which trains a separate model for each network
node, and the global approach, which trains a single model over pairs of nodes.
Here, we systematically investigate, theoretically and empirically, the
exploitation of tree-based ensemble methods in the context of these two
approaches for biological network inference. We first formalize the problem of
network inference as classification of pairs, unifying in the process
homogeneous and bipartite graphs and discussing two main sampling schemes. We
then present the global and the local approaches, extending the later for the
prediction of interactions between two unseen network nodes, and discuss their
specializations to tree-based ensemble methods, highlighting their
interpretability and drawing links with clustering techniques. Extensive
computational experiments are carried out with these methods on various
biological networks that clearly highlight that these methods are competitive
with existing methods.Comment: 22 page
The role of phonemic awareness in the development of emergent literacy
Phonemic awareness is discussed as one possible prerequisite and predictor of later reading ability. The role of phonemic awareness in the development of emergent literacy is investigated through a thorough review of relevant literature. The usefulness of phonemic awareness as a predictor of later reading and spelling achievement is discussed. In addition, the effectiveness of phonemic awareness intervention is discussed. Suggestion for future research are presented
The effects of decisional guidance on the forecast performance in judgmentally adjusting forecasts
Three regularization models of the Navier-Stokes equations
We determine how the differences in the treatment of the subfilter-scale
physics affect the properties of the flow for three closely related
regularizations of Navier-Stokes. The consequences on the applicability of the
regularizations as SGS models are also shown by examining their effects on
superfilter-scale properties. Numerical solutions of the Clark-alpha model are
compared to two previously employed regularizations, LANS-alpha and Leray-alpha
(at Re ~ 3300, Taylor Re ~ 790) and to a DNS. We derive the Karman-Howarth
equation for both the Clark-alpha and Leray-alpha models. We confirm one of two
possible scalings resulting from this equation for Clark as well as its
associated k^(-1) energy spectrum. At sub-filter scales, Clark-alpha possesses
similar total dissipation and characteristic time to reach a statistical
turbulent steady-state as Navier-Stokes, but exhibits greater intermittency. As
a SGS model, Clark reproduces the energy spectrum and intermittency properties
of the DNS. For the Leray model, increasing the filter width decreases the
nonlinearity and the effective Re is substantially decreased. Even for the
smallest value of alpha studied, Leray-alpha was inadequate as a SGS model. The
LANS energy spectrum k^1, consistent with its so-called "rigid bodies,"
precludes a reproduction of the large-scale energy spectrum of the DNS at high
Re while achieving a large reduction in resolution. However, that this same
feature reduces its intermittency compared to Clark-alpha (which shares a
similar Karman-Howarth equation). Clark is found to be the best approximation
for reproducing the total dissipation rate and the energy spectrum at scales
larger than alpha, whereas high-order intermittency properties for larger
values of alpha are best reproduced by LANS-alpha.Comment: 21 pages, 8 figure
PremiÚres données a l'étude paplynologique des dépÎts calcareux quaternaires en Catalogne
Los primeros anĂĄlisis polĂnicos de los depĂłsitos del cuaternario catalĂĄn permiten diferenciar 76 taxones y cuatro conjuntos florĂsticos que se sitĂșan entre el pleistoceno antiguo y el subactual
Somatosensory and nociceptive changes in chronic post-stroke shoulder pain
Preliminary results from a cross-sectional study that investigated the relation between the presence of post-stroke shoulder pain and somatosensory and nociceptive changes are presented. The main finding is that both abnormal somatosensation and nociception are more frequently observed in stroke patients with pain as compared to pain-free stroke patients and healthy controls
Cortical processing of electrocutaneous stimuli in chronic stroke patients: a relationship with post-stroke shoulder pain.
Cerebral stroke is often associated with changes in cognitive-evaluative and somatosensory functions which may play a role in the development and maintenance of post-stroke pain
Leray and LANS- modeling of turbulent mixing
Mathematical regularisation of the nonlinear terms in the Navier-Stokes
equations provides a systematic approach to deriving subgrid closures for
numerical simulations of turbulent flow. By construction, these subgrid
closures imply existence and uniqueness of strong solutions to the
corresponding modelled system of equations. We will consider the large eddy
interpretation of two such mathematical regularisation principles, i.e., Leray
and LANS regularisation. The Leray principle introduces a {\bfi
smoothed transport velocity} as part of the regularised convective
nonlinearity. The LANS principle extends the Leray formulation in a
natural way in which a {\bfi filtered Kelvin circulation theorem},
incorporating the smoothed transport velocity, is explicitly satisfied. These
regularisation principles give rise to implied subgrid closures which will be
applied in large eddy simulation of turbulent mixing. Comparison with filtered
direct numerical simulation data, and with predictions obtained from popular
dynamic eddy-viscosity modelling, shows that these mathematical regularisation
models are considerably more accurate, at a lower computational cost.Comment: 42 pages, 12 figure
Distribution of the Timing, Trigger and Control Signals in the Endcap Cathode Strip Chamber System at CMS
This paper presents the implementation of the Timing, Trigger and Control (TTC) signal distribution tree in the Cathode Strip Chamber (CSC) sub-detector of the CMS Experiment at CERN. The key electronic component, the Clock and Control Board (CCB) is described in detail, as well as the transmission of TTC signals from the top of the system down to the front-end boards
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