189 research outputs found
Effective Sampling in the Configurational Space by the Multicanonical-Multioverlap Algorithm
We propose a new generalized-ensemble algorithm, which we refer to as the
multicanonical-multioverlap algorithm. By utilizing a non-Boltzmann weight
factor, this method realizes a random walk in the multi-dimensional,
energy-overlap space and explores widely in the configurational space including
specific configurations, where the overlap of a configuration with respect to a
reference state is a measure for structural similarity. We apply the
multicanonical-multioverlap molecular dynamics method to a penta peptide,
Met-enkephalin, in vacuum as a test system. We also apply the multicanonical
and multioverlap molecular dynamics methods to this system for the purpose of
comparisons. We see that the multicanonical-multioverlap molecular dynamics
method realizes effective sampling in the configurational space including
specific configurations more than the other two methods. From the results of
the multicanonical-multioverlap molecular dynamics simulation, furthermore, we
obtain a new local-minimum state of the Met-enkephalin system.Comment: 15 pages, (Revtex4), 9 figure
Les enjeux de lâĂ©quivalence Ă©cologique pour la conception et le dimensionnement de mesures compensatoires dâimpacts sur la biodiversitĂ© et les milieux naturels,
LâĂ©volution du contexte rĂ©glementaire a renforcĂ© lâobligation de compenser " en nature " les impacts sur la biodiversitĂ© qui nâont pas pu ĂȘtre Ă©vitĂ©s ou rĂ©duits. Dans ce contexte, lâĂ©valuation de lâĂ©quivalence entre les pertes causĂ©es par ces impacts et les gains de biodiversitĂ© attendus des actions de compensation suscite des questions scientifiques et techniques quant aux concepts et connaissances Ă mobiliser et aux mĂ©thodes dâĂ©valuation Ă dĂ©velopper et mettre en Âœuvre. On y trouve en particulier l'identification des Ă©lĂ©ments de biodiversitĂ© Ă considĂ©rer, le dĂ©veloppement dâindicateurs appropriĂ©s permettant de comparer pertes et gains, la sĂ©lection dâun Ă©tat de rĂ©fĂ©rence pour le calcul des pertes et gains, et la prise en compte des dynamiques Ă©cologiques et des incertitudes dans lâĂ©valuation du devenir des sites de compensation. Par ces questions, l'Ă©quivalence Ă©cologique donne un cadre de raisonnement explicite Ă la conception et au dimensionnement de la compensation qui est appropriable par chacun des acteurs concernĂ©s. / Since 2007 France has seen a radical strengthening of its legislation concerning the mitigation of development impacts on biodiversity and ecosystems. Under pressure from the European Union and as an outcome of a national consultative process called the âGrenelle de lâEnvironnementâ, the scope of the mitigation hierarchy of avoiding, reducing and offsetting impacts of plans, programs and projects has been expanded. It now includes stronger requirements in terms of monitoring and effective implementation. These changes â which have strong financial and legal implications for developers - have revealed the lack of technical guidelines for designing and sizing offsets. Assessing the ecological equivalence between losses caused by impacts and the gains expected from offset actions raises scientific and technical issues that remain unresolved. These include the identification of relevant components of biodiversity, the development of appropriate indicators, the identification of reference states and the incorporation of ecological dynamics and uncertainties into offset design and sizing
Fixed Effect Estimation of Large T Panel Data Models
This article reviews recent advances in fixed effect estimation of panel data
models for long panels, where the number of time periods is relatively large.
We focus on semiparametric models with unobserved individual and time effects,
where the distribution of the outcome variable conditional on covariates and
unobserved effects is specified parametrically, while the distribution of the
unobserved effects is left unrestricted. Compared to existing reviews on long
panels (Arellano and Hahn 2007; a section in Arellano and Bonhomme 2011) we
discuss models with both individual and time effects, split-panel Jackknife
bias corrections, unbalanced panels, distribution and quantile effects, and
other extensions. Understanding and correcting the incidental parameter bias
caused by the estimation of many fixed effects is our main focus, and the
unifying theme is that the order of this bias is given by the simple formula
p/n for all models discussed, with p the number of estimated parameters and n
the total sample size.Comment: 40 pages, 1 tabl
Electromagnetic vertex function of the pion at T > 0
The matrix element of the electromagnetic current between pion states is
calculated in quenched lattice QCD at a temperature of . The
nonperturbatively improved Sheikholeslami-Wohlert action is used together with
the corresponding improved vector current. The electromagnetic
vertex function is extracted for pion masses down to and
momentum transfers .Comment: 17 pages, 8 figure
Loss of sea ice during winter north of Svalbard
Sea ice loss in the Arctic Ocean has up to now been strongest during summer. In contrast, the sea ice concentration north of Svalbard has experienced a larger decline during winter since 1979. The trend in winter ice area loss is close to 10% per decade, and concurrent with a 0.3°C per decade warming of the Atlantic Water entering the Arctic Ocean in this region. Simultaneously, there has been a 2°C per decade warming of winter mean surface air temperature north of Svalbard, which is 20â45% higher than observations on the west coast. Generally, the ice edge north of Svalbard has retreated towards the northeast, along the Atlantic Water pathway. By making reasonable assumptions about the Atlantic Water volume and associated heat transport, we show that the extra oceanic heat brought into the region is likely to have caused the sea ice loss. The reduced sea ice cover leads to more oceanic heat transferred to the atmosphere, suggesting that part of the atmospheric warming is driven by larger open water area. In contrast to significant trends in sea ice concentration, Atlantic Water temperature and air temperature, there is no significant temporal trend in the local winds. Thus, winds have not caused the long-term warming or sea ice loss. However, the dominant winds transport sea ice from the Arctic Ocean into the region north of Svalbard, and the local wind has influence on the year-to-year variability of the ice concentration, which correlates with surface air temperatures, ocean temperatures, as well as the local wind
Statistical modeling of ground motion relations for seismic hazard analysis
We introduce a new approach for ground motion relations (GMR) in the
probabilistic seismic hazard analysis (PSHA), being influenced by the extreme
value theory of mathematical statistics. Therein, we understand a GMR as a
random function. We derive mathematically the principle of area-equivalence;
wherein two alternative GMRs have an equivalent influence on the hazard if
these GMRs have equivalent area functions. This includes local biases. An
interpretation of the difference between these GMRs (an actual and a modeled
one) as a random component leads to a general overestimation of residual
variance and hazard. Beside this, we discuss important aspects of classical
approaches and discover discrepancies with the state of the art of stochastics
and statistics (model selection and significance, test of distribution
assumptions, extreme value statistics). We criticize especially the assumption
of logarithmic normally distributed residuals of maxima like the peak ground
acceleration (PGA). The natural distribution of its individual random component
(equivalent to exp(epsilon_0) of Joyner and Boore 1993) is the generalized
extreme value. We show by numerical researches that the actual distribution can
be hidden and a wrong distribution assumption can influence the PSHA negatively
as the negligence of area equivalence does. Finally, we suggest an estimation
concept for GMRs of PSHA with a regression-free variance estimation of the
individual random component. We demonstrate the advantages of event-specific
GMRs by analyzing data sets from the PEER strong motion database and estimate
event-specific GMRs. Therein, the majority of the best models base on an
anisotropic point source approach. The residual variance of logarithmized PGA
is significantly smaller than in previous models. We validate the estimations
for the event with the largest sample by empirical area functions. etc
Coding Efficiency of Fly Motion Processing Is Set by Firing Rate, Not Firing Precision
To comprehend the principles underlying sensory information processing, it is important to understand how the nervous system deals with various sources of perturbation. Here, we analyze how the representation of motion information in the fly's nervous system changes with temperature and luminance. Although these two environmental variables have a considerable impact on the fly's nervous system, they do not impede the fly to behave suitably over a wide range of conditions. We recorded responses from a motion-sensitive neuron, the H1-cell, to a time-varying stimulus at many different combinations of temperature and luminance. We found that the mean firing rate, but not firing precision, changes with temperature, while both were affected by mean luminance. Because we also found that information rate and coding efficiency are mainly set by the mean firing rate, our results suggest that, in the face of environmental perturbations, the coding efficiency is improved by an increase in the mean firing rate, rather than by an increased firing precision
Stability of gene contributions and identification of outliers in multivariate analysis of microarray data
BACKGROUND: Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages compared to common gene-by-gene approaches. However, due to their exploratory nature, multivariate ordination methods do not allow direct statistical testing of the stability of genes. RESULTS: In this study, we developed a computationally efficient algorithm for: i) the assessment of the significance of gene contributions and ii) the identification of sample outliers in multivariate analysis of microarray data. The approach is based on the use of resampling methods including bootstrapping and jackknifing. A statistical package of R functions was developed. This package includes tools for both inferring the statistical significance of gene contributions and identifying outliers among samples. CONCLUSION: The methodology was successfully applied to three published data sets with varying levels of signal intensities. Its relevance was compared with alternative methods. Overall, it proved to be particularly effective for the evaluation of the stability of microarray data
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