5,572 research outputs found
ZRT1 harbors an excess of nonsynonymous polymorphism and shows evidence of balancing selection in Saccharomyces cerevisiae
Estimates of the fraction of nucleotide substitutions driven by positive
selection vary widely across different species. Accounting for different
estimates of positive selection has been difficult, in part because selection
on polymorphism within a species is known to obscure a signal of positive
selection between species. While methods have been developed to control for the
confounding effects of negative selection against deleterious polymorphism, the
impact of balancing selection on estimates of positive selection has not been
assessed. In Saccharomyces cerevisiae, there is no signal of positive selection
within protein coding sequences as the ratio of nonsynonymous to synonymous
polymorphism is higher than that of divergence. To investigate the impact of
balancing selection on estimates of positive selection we examined five genes
with high rates of nonsynonymous polymorphism in S. cerevisiae relative to
divergence from S. paradoxus. One of the genes, a high affinity zinc
transporter ZRT1, shows an elevated rate of synonymous polymorphism indicative
of balancing selection. The high rate of synonymous polymorphism coincides with
nonsynonymous divergence between three haplotype groups, which we find to be
functionally indistinguishable. We conclude that balancing selection is not
likely to be a common cause of genes harboring a large excess of nonsynonymous
polymorphism in yeast
Measuring and Testing the Impact of News on Volatility
This paper introduces the News Impact Curve to measure how new information is incorporated into volatility estimates. A variety of new and existing ARCH models are compared and estimated with daily Japanese stock return data to determine the shape of the News Impact Curve. New diagnostic tests are presented which emphasize the asymmetry of the volatility response to news. A partially non-parametric ARCH model is introduced to allow the data to estimate this shape. A comparison of this model with the existing models suggests that the best models are one by Glosten Jaganathan and Runkle (GJR) and Nelson's EGARCE. Similar results hold on a pre-crash sample period but are less strong.
Time-Varying Volatility and the Dynamic Behavior of the Term Structure
In this paper, we consider a framework with which the cross sectional and time series behavior of the yield curve can be studied simultaneously. We examine the relationship between the yield curve and the time-varying conditional volatility of the Treasury bill market. We demonstrate that differently shaped yield curves can result given different combinations of volatility and expectations about future spot rates. Moreover, adjusting the forward rate for the volatility related liquidity premium can improve its performance as a predictor of future spot rates at least for the period from August 1964 to August 1979.
PRIOR REGULATION AND POST LIABILITY AS COMPLEMENTS: AN APPLICATION TO PRESCRIBED BURNING LAW IN THE UNITED STATES
Prescribed burning is increasingly being recognized as a useful land management and conservation tool, but with it comes the risk of fire and smoke damage to the property of others. All but two states have codified laws specifying criminal penalties or liability rules for prescribed burning, but the laws in a number of states have changed in recent years or are under review. We develop an economic model of the incentive and welfare effects of prescribed burning and the use of prior regulation and post liability as instruments to address potential external damage from the use of prescribed fire.Resource /Energy Economics and Policy,
Fear and its implications for stock markets
The value of stocks, indices and other assets, are examples of stochastic
processes with unpredictable dynamics. In this paper, we discuss asymmetries in
short term price movements that can not be associated with a long term positive
trend. These empirical asymmetries predict that stock index drops are more
common on a relatively short time scale than the corresponding raises. We
present several empirical examples of such asymmetries. Furthermore, a simple
model featuring occasional short periods of synchronized dropping prices for
all stocks constituting the index is introduced with the aim of explaining
these facts. The collective negative price movements are imagined triggered by
external factors in our society, as well as internal to the economy, that
create fear of the future among investors. This is parameterized by a ``fear
factor'' defining the frequency of synchronized events. It is demonstrated that
such a simple fear factor model can reproduce several empirical facts
concerning index asymmetries. It is also pointed out that in its simplest form,
the model has certain shortcomings.Comment: 5 pages, 5 figures. Submitted to the Proceedings of Applications of
Physics in Financial Analysis 5, Turin 200
Entropy of generic quantum isolated horizons
We review our recent proposal of a method to extend the quantization of
spherically symmetric isolated horizons, a seminal result of loop quantum
gravity, to a phase space containing horizons of arbitrary geometry. Although
the details of the quantization remain formally unchanged, the physical
interpretation of the results can be quite different. We highlight several such
differences, with particular emphasis on the physical interpretation of black
hole entropy in loop quantum gravity.Comment: 4 pages, contribution to loops '11 conference proceedings; 2
references added, a sentence remove
Dissociable brain mechanisms for inhibitory control: Effects of interference content and working memory capacity
In this study, event-related fMRI was used to examine whether the resolution of interference arising from two different information contents activates the same or different neuronal circuitries. In addition, we examined the extent to which these inhibitory control mechanisms are modulated by individual differences in working memory capacity. Two groups of participants with high and low working memory capacity [high span (HS) and low span (LS) participants, respectively] performed two versions of an item recognition task with familiar letters and abstract objects as stimulus materials. Interference costs were examined by means of the recent negative probe technique with otherwise identical testing conditions across both tasks. While the behavioral interference costs were of similar magnitude in both tasks, the underlying brain activation pattern differed between tasks: The object task interference-effects (higher activation in interference trials than in control trials) were restricted to the anterior intraparietal sulcus (IPS). Interference effects for familiar letters were obtained in the anterior IPS, the left postero-ventral and the right dorsolateral prefrontal cortex (PFC) as well as the precuneus. As the letters were more discernible than the objects, the results suggest that the critical feature for PFC and precuneus involvement in interference resolution is the saliency of stimulus-response mappings. The interference effects in the letter task were modulated by working memory capacity: LS participants showed enhanced activation for interference trials only, whereas for HS participants, who showed better performance and also lower interference costs in the letter task, the above-mentioned neuronal circuitry was activated for interference and control trials, thereby attenuating the interference effects. The latter results support the view that HS individuals allocate more attentional resources for the maintenance of task goals in the face of interfering information from preceding trials with familiar stimulus materials
Holomorphic Factorization for a Quantum Tetrahedron
We provide a holomorphic description of the Hilbert space H(j_1,..,j_n) of
SU(2)-invariant tensors (intertwiners) and establish a holomorphically
factorized formula for the decomposition of identity in H(j_1,..,j_n).
Interestingly, the integration kernel that appears in the decomposition formula
turns out to be the n-point function of bulk/boundary dualities of string
theory. Our results provide a new interpretation for this quantity as being, in
the limit of large conformal dimensions, the exponential of the Kahler
potential of the symplectic manifold whose quantization gives H(j_1,..,j_n).
For the case n=4, the symplectic manifold in question has the interpretation of
the space of "shapes" of a geometric tetrahedron with fixed face areas, and our
results provide a description for the quantum tetrahedron in terms of
holomorphic coherent states. We describe how the holomorphic intertwiners are
related to the usual real ones by computing their overlap. The semi-classical
analysis of these overlap coefficients in the case of large spins allows us to
obtain an explicit relation between the real and holomorphic description of the
space of shapes of the tetrahedron. Our results are of direct relevance for the
subjects of loop quantum gravity and spin foams, but also add an interesting
new twist to the story of the bulk/boundary correspondence.Comment: 45 pages; published versio
Coherent states, constraint classes, and area operators in the new spin-foam models
Recently, two new spin-foam models have appeared in the literature, both
motivated by a desire to modify the Barrett-Crane model in such a way that the
imposition of certain second class constraints, called cross-simplicity
constraints, are weakened. We refer to these two models as the FKLS model, and
the flipped model. Both of these models are based on a reformulation of the
cross-simplicity constraints. This paper has two main parts. First, we clarify
the structure of the reformulated cross-simplicity constraints and the nature
of their quantum imposition in the new models. In particular we show that in
the FKLS model, quantum cross-simplicity implies no restriction on states. The
deeper reason for this is that, with the symplectic structure relevant for
FKLS, the reformulated cross-simplicity constraints, in a certain relevant
sense, are now \emph{first class}, and this causes the coherent state method of
imposing the constraints, key in the FKLS model, to fail to give any
restriction on states. Nevertheless, the cross-simplicity can still be seen as
implemented via suppression of intertwiner degrees of freedom in the dynamical
propagation. In the second part of the paper, we investigate area spectra in
the models. The results of these two investigations will highlight how, in the
flipped model, the Hilbert space of states, as well as the spectra of area
operators exactly match those of loop quantum gravity, whereas in the FKLS (and
Barrett-Crane) models, the boundary Hilbert spaces and area spectra are
different.Comment: 21 pages; statements about gamma limits made more precise, and minor
phrasing change
Unboxing Cluster Heatmaps
Background: Cluster heatmaps are commonly used in biology and related fields to reveal hierarchical clusters in data matrices. This visualization technique has high data density and reveal clusters better than unordered heatmaps alone. However, cluster heatmaps have known issues making them both time consuming to use and prone to error. We hypothesize that visualization techniques without the rigid grid constraint of cluster heatmaps will perform better at clustering-related tasks.
Results: We developed an approach to “unbox” the heatmap values and embed them directly in the hierarchical clustering results, allowing us to use standard hierarchical visualization techniques as alternatives to cluster heatmaps. We then tested our hypothesis by conducting a survey of 45 practitioners to determine how cluster heatmaps are used, prototyping alternatives to cluster heatmaps using pair analytics with a computational biologist, and evaluating those alternatives with hour-long interviews of 5 practitioners and an Amazon Mechanical Turk user study with approximately 200 participants. We found statistically significant performance differences for most clustering-related tasks, and in the number of perceived visual clusters. Visit git.io/vw0t3 for our results.
Conclusions: The optimal technique varied by task. However, gapmaps were preferred by the interviewed practitioners and outperformed or performed as well as cluster heatmaps for clustering-related tasks. Gapmaps are similar to cluster heatmaps, but relax the heatmap grid constraints by introducing gaps between rows and/or columns that are not closely clustered. Based on these results, we recommend users adopt gapmaps as an alternative to cluster heatmaps
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