202 research outputs found
On the low-field Hall coefficient of graphite
We have measured the temperature and magnetic field dependence of the Hall
coefficient () in three, several micrometer long multigraphene
samples of thickness between to ~nm in the temperature range
0.1 to 200~K and up to 0.2~T field. The temperature dependence of the
longitudinal resistance of two of the samples indicates the contribution from
embedded interfaces running parallel to the graphene layers. At low enough
temperatures and fields is positive in all samples, showing a
crossover to negative values at high enough fields and/or temperatures in
samples with interfaces contribution. The overall results are compatible with
the reported superconducting behavior of embedded interfaces in the graphite
structure and indicate that the negative low magnetic field Hall coefficient is
not intrinsic of the ideal graphite structure.Comment: 10 pages with 7 figures, to be published in AIP Advances (2014
A solution to the weighted procrustes problem in which the transformation is in agreement with the loss function
This paper provides a generalization of the Procrustes problem in which the errors are weighted from the right, or the left, or both. The solution is achieved by having the orthogonality constraint on the transformation be in agreement with the norm of the least squares criterion. This general principle is discussed and illustrated by the mathematics of the weighted orthogonal Procrustes problem.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45737/1/11336_2005_Article_BF02296976.pd
Alternative measures of fit for the Schönemann-carroll matrix fitting algorithm
In connection with a least-squares solution for fitting one matrix, A , to another, B , under optimal choice of a rigid motion and a dilation, Schönemann and Carroll suggested two measures of fit: a raw measure, e , and a refined similarity measure, e s , which is symmetric. Both measures share the weakness of depending upon the norm of the target matrix, B , e.g. , e ( A , kB ) â e ( A , B ) for k â 1. Therefore, both measures are useless for answering questions of the type: âDoes A fit B better than A fits C ?â. In this note two new measures of fit are suggested which do not depend upon the norms of A and B , which are (0, 1)-bounded, and which, therefore, provide meaningful answers for comparative analyses.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45731/1/11336_2005_Article_BF02291666.pd
A direct approach to individual differences scaling using increasingly complex transformations
A family of models for the representation and assessment of individual differences for multivariate data is embodied in a hierarchically organized and sequentially applied procedure called PINDIS. The two principal models used for directly fitting individual configurations to some common or hypothesized space are the dimensional salience and perspective models. By systematically increasing the complexity of transformations one can better determine the validities of the various models and assess the patterns and commonalities of individual differences. PINDIS sheds some new light on the interpretability and general applicability of the dimension weighting approach implemented by the commonly used INDSCAL procedure.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45738/1/11336_2005_Article_BF02293810.pd
The Ernst equation and ergosurfaces
We show that analytic solutions \mcE of the Ernst equation with non-empty
zero-level-set of \Re \mcE lead to smooth ergosurfaces in space-time. In
fact, the space-time metric is smooth near a "Ernst ergosurface" if and
only if \mcE is smooth near and does not have zeros of infinite order
there.Comment: 23 pages, 4 figures; misprints correcte
Bulk fermi surface of the Weyl type-II semimetallic candidate ÎłâMoTe2
The electronic structure of WTe and orthorhombic MoTe, are
claimed to contain pairs of Weyl type-II points. A series of ARPES experiments
claim a broad agreement with these predictions. We synthesized single-crystals
of MoTe through a Te flux method to validate these predictions through
measurements of its bulk Fermi surface (FS) \emph{via} quantum oscillatory
phenomena. We find that the superconducting transition temperature of
MoTe depends on disorder as quantified by the ratio between the
room- and low-temperature resistivities, suggesting the possibility of an
unconventional superconducting pairing symmetry. Similarly to WTe, the
magnetoresistivity of MoTe does not saturate at high magnetic
fields and can easily surpass \%. Remarkably, the analysis of the de
Haas-van Alphen (dHvA) signal superimposed onto the magnetic torque, indicates
that the geometry of its FS is markedly distinct from the calculated one. The
dHvA signal also reveals that the FS is affected by the Zeeman-effect
precluding the extraction of the Berry-phase. A direct comparison between the
previous ARPES studies and density-functional-theory (DFT) calculations reveals
a disagreement in the position of the valence bands relative to the Fermi level
. Here, we show that a shift of the DFT valence bands relative
to , in order to match the ARPES observations, and of the DFT
electron bands to explain some of the observed dHvA frequencies, leads to a
good agreement between the calculations and the angular dependence of the FS
cross-sectional areas observed experimentally. However, this relative
displacement between electron- and hole-bands eliminates their crossings and,
therefore, the Weyl type-II points predicted for MoTe.Comment: 13 pages, 7 figures, supplementary file not included (in press
Factor analysis for gene regulatory networks and transcription factor activity profiles
BACKGROUND: Most existing algorithms for the inference of the structure of gene regulatory networks from gene expression data assume that the activity levels of transcription factors (TFs) are proportional to their mRNA levels. This assumption is invalid for most biological systems. However, one might be able to reconstruct unobserved activity profiles of TFs from the expression profiles of target genes. A simple model is a two-layer network with unobserved TF variables in the first layer and observed gene expression variables in the second layer. TFs are connected to regulated genes by weighted edges. The weights, known as factor loadings, indicate the strength and direction of regulation. Of particular interest are methods that produce sparse networks, networks with few edges, since it is known that most genes are regulated by only a small number of TFs, and most TFs regulate only a small number of genes. RESULTS: In this paper, we explore the performance of five factor analysis algorithms, Bayesian as well as classical, on problems with biological context using both simulated and real data. Factor analysis (FA) models are used in order to describe a larger number of observed variables by a smaller number of unobserved variables, the factors, whereby all correlation between observed variables is explained by common factors. Bayesian FA methods allow one to infer sparse networks by enforcing sparsity through priors. In contrast, in the classical FA, matrix rotation methods are used to enforce sparsity and thus to increase the interpretability of the inferred factor loadings matrix. However, we also show that Bayesian FA models that do not impose sparsity through the priors can still be used for the reconstruction of a gene regulatory network if applied in conjunction with matrix rotation methods. Finally, we show the added advantage of merging the information derived from all algorithms in order to obtain a combined result. CONCLUSION: Most of the algorithms tested are successful in reconstructing the connectivity structure as well as the TF profiles. Moreover, we demonstrate that if the underlying network is sparse it is still possible to reconstruct hidden activity profiles of TFs to some degree without prior connectivity information
Real-time monitoring shows substantial excess all-cause mortality during second wave of COVID-19 in Europe, October to December 2020.
The European monitoring of excess mortality for public health action (EuroMOMO) network monitors weekly excess all-cause mortality in 27 European countries or subnational areas. During the first wave of the coronavirus disease (COVID-19) pandemic in Europe in spring 2020, several countries experienced extraordinarily high levels of excess mortality. Europe is currently seeing another upsurge in COVID-19 cases, and EuroMOMO is again witnessing a substantial excess all-cause mortality attributable to COVID-19.Funding statement: The EuroMOMO network hub at Statens Serum Institut receives funding from European Centre for Disease Prevention and Control, Solna, Sweden, through a framework contract 2017-2020.S
The structure of subjective well-being in nine western societies
The structure of subjective well-being is analyzed by multidimensional mapping of evaluations of life concerns. For example, one finds that evaluations of Income are close to (i.e., relatively strongly related to) evaluations of Standard of living, but remote from (weakly related to) evaluations of Health. These structures show how evaluations of life components fit together and hence illuminate the psychological meaning of life quality. They can be useful for determining the breadth of coverage and degree of redundancy of social indicators of perceived well-being. Analyzed here are data from representative sample surveys in Belgium, Denmark, France, Germany, Great Britain, Ireland, Italy, Netherlands, and the United States (each Nâ1000). Eleven life concerns are considered, including Income, Housing, Job, Health, Leisure, Neighborhood, Transportation, and Relations with other people. It is found that structures in all of these countries have a basic similarity and that the European countries tend to be more similar to one another than they are to USA. These results suggest that comparative research on subjective well-being is feasible within this group of nations.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43699/1/11205_2004_Article_BF00305437.pd
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