Theoretical insight into diagnosing observation error correlations using observation-minus-background and observation-minus-analysis statistics

To improve the quantity and impact of observations used in data assimilation it is necessary to take into account the full, potentially correlated, observation error statistics. A number of methods for estimating correlated observation errors exist, but a popular method is a diagnostic that makes use of statistical averages of observation-minus-background and observation-minus-analysis residuals. The accuracy of the results it yields is unknown as the diagnostic is sensitive to the difference between the exact background and exact observation error covariances and those that are chosen for use within the assimilation. It has often been stated in the literature that the results using this diagnostic are only valid when the background and observation error correlation length scales are well separated. Here we develop new theory relating to the diagnostic. For observations on a 1D periodic domain we are able to the show the effect of changes in the assumed error statistics used in the assimilation on the estimated observation error covariance matrix. We also provide bounds for the estimated observation error variance and eigenvalues of the estimated observation error correlation matrix. We demonstrate that it is still possible to obtain useful results from the diagnostic when the background and observation error length scales are similar. In general, our results suggest that when correlated observation errors are treated as uncorrelated in the assimilation, the diagnostic will underestimate the correlation length scale. We support our theoretical results with simple illustrative examples. These results have potential use for interpreting the derived covariances estimated using an operational system.

A new calibrated sunspot group series since 1749: statistics of active day fractions

Although the sunspot-number series have existed since the mid-19th century, they are still the subject of intense debate, with the largest uncertainty being related to the "calibration" of the visual acuity of individual observers in the past. Daisy-chain regression methods are applied to inter-calibrate the observers which may lead to significant bias and error accumulation. Here we present a novel method to calibrate the visual acuity of the key observers to the reference data set of Royal Greenwich Observatory sunspot groups for the period 1900-1976, using the statistics of the active-day fraction. For each observer we independently evaluate their observational thresholds [S_S] defined such that the observer is assumed to miss all of the groups with an area smaller than S_S and report all the groups larger than S_S. Next, using a Monte-Carlo method we construct, from the reference data set, a correction matrix for each observer. The correction matrices are significantly non-linear and cannot be approximated by a linear regression or proportionality. We emphasize that corrections based on a linear proportionality between annually averaged data lead to serious biases and distortions of the data. The correction matrices are applied to the original sunspot group records for each day, and finally the composite corrected series is produced for the period since 1748. The corrected series displays secular minima around 1800 (Dalton minimum) and 1900 (Gleissberg minimum), as well as the Modern grand maximum of activity in the second half of the 20th century. The uniqueness of the grand maximum is confirmed for the last 250 years. It is shown that the adoption of a linear relationship between the data of Wolf and Wolfer results in grossly inflated group numbers in the 18th and 19th centuries in some reconstructions.

Data Assimilation and Inverse Methods in Terms of a Probabilistic Formulation

The weak-constraint inverse for nonlinear dynamical models is discussed and derived in terms of a probabilistic formulation. The well-known result that for Gaussian error statistics the minimum of the weak-constraint inverse is equal to the maximum-likelihood estimate is rederived. Then several methods based on ensemble statistics that can be used to find the smoother (as opposed to the filter) solution are introduced and compared to traditional methods. A strong point of the new methods is that they avoid the integration of adjoint equations, which is a complex task for real oceanographic or atmospheric applications. they also avoid iterative searches in a Hilbert space, and error estimates can be obtained without much additional computational effort. the feasibility of the new methods is illustrated in a two-layer quasigeostrophic model.

Diagnosing observation error correlations for Doppler radar radial winds in the Met Office UKV model using observation-minus-background and observation-minus-analysis statistics

With the development of convection-permitting numerical weather prediction the efficient use of high resolution observations in data assimilation is becoming increasingly important. The operational assimilation of these observations, such as Dopplerradar radial winds, is now common, though to avoid violating the assumption of un- correlated observation errors the observation density is severely reduced. To improve the quantity of observations used and the impact that they have on the forecast will require the introduction of the full, potentially correlated, error statistics. In this work, observation error statistics are calculated for the Doppler radar radial winds that are assimilated into the Met Office high resolution UK model using a diagnostic that makes use of statistical averages of observation-minus-background and observation-minus-analysis residuals. This is the first in-depth study using the diagnostic to estimate both horizontal and along-beam correlated observation errors. By considering the new results obtained it is found that the Doppler radar radial wind error standard deviations are similar to those used operationally and increase as the observation height increases. Surprisingly the estimated observation error correlation length scales are longer than the operational thinning distance. They are dependent on both the height of the observation and on the distance of the observation away from the radar. Further tests show that the long correlations cannot be attributed to the use of superobservations or the background error covariance matrix used in the assimilation. The large horizontal correlation length scales are, however, in part, a result of using a simplified observation operator.

Conservative force fields in non-Gaussian statistics

In this Letter, we determine the kappa-distribution function for a gas in the presence of an external field of force described by a potential U(r). In the case of a dilute gas, we show that the kappa-power law distribution including the potential energy factor term can rigorously be deduced in the framework of kinetic theory with basis on the Vlasov equation. Such a result is significant as a preliminary to the discussion on the role of long range interactions in the Kaniadakis thermostatistics and the underlying kinetic theory. (C) 2008 Elsevier B.V. All rights reserved.

Population and Computational Analysis of the MGEA6 P521A Variation as a Risk Factor for Familial Idiopathic Basal Ganglia Calcification (Fahr`s Disease)

Familial idiopathic basal ganglia calcification, also known as ""Fahr`s disease"" (FD), is a neuropsychiatric disorder with autosomal dominant pattern of inheritance and characterized by symmetric basal ganglia calcifications and, occasionally, other brain regions. Currently, there are three loci linked to this devastating disease. The first one (IBGC1) is located in 14q11.2-21.3 and the other two have been identified in 2q37 (IBGC2) and 8p21.1-q11.13 (IBGC3). Further studies identified a heterozygous variation (rs36060072) which consists in the change of the cytosine to guanine located at MGEA6/CTAGE5 gene, present in all of the affected large American family linked to IBGC1. This missense substitution, which induces changes of a proline to alanine at the 521 position (P521A), in a proline-rich and highly conserved protein domain was considered a rare variation, with a minor allele frequency (MAF) of 0.0058 at the US population. Considering that the population frequency of a given variation is an indirect indicative of potential pathogenicity, we screened 200 chromosomes in a random control set of Brazilian samples and in two nuclear families, comparing with our previous analysis in a US population. In addition, we accomplished analyses through bioinformatics programs to predict the pathogenicity of such variation. Our genetic screen found no P521A carriers. Polling these data together with the previous study in the USA, we have now a MAF of 0.0036, showing that this mutation is very rare. On the other hand, the bioinformatics analysis provided conflicting findings. There are currently various candidate genes and loci that could be involved with the underlying molecular basis of FD etiology, and other groups suggested the possible role played by genes in 2q37, related to calcium metabolism, and at chromosome 8 (NRG1 and SNTG1). Additional mutagenesis and in vivo studies are necessary to confirm the pathogenicity for variation in the P521A MGEA6.

A psychophysical and computational analysis of the spatio-temporal mechanisms underlying the flash-lag effect

Several accounts put forth to explain the flash-lag effect (FLE) rely mainly on either spatial or temporal mechanisms. Here we investigated the relationship between these mechanisms by psychophysical and theoretical approaches. In a first experiment we assessed the magnitudes of the FLE and temporal-order judgments performed under identical visual stimulation. The results were interpreted by means of simulations of an artificial neural network, that wits also employed to make predictions concerning the F LE. The model predicted that a spatio-temporal mislocalisation would emerge from two, continuous and abrupt-onset, moving stimuli. Additionally, a straightforward prediction of the model revealed that the magnitude of this mislocalisation should be task-dependent, increasing when the use of the abrupt-onset moving stimulus switches from a temporal marker only to both temporal and spatial markers. Our findings confirmed the model`s predictions and point to an indissoluble interplay between spatial facilitation and processing delays in the FLE.

Sequence-specific reconstruction from fragmentary databases using seed sequences: implementation and validation on SAGE, proteome and generic sequencing data

Motivation: DNA assembly programs classically perform an all-against-all comparison of reads to identify overlaps, followed by a multiple sequence alignment and generation of a consensus sequence. If the aim is to assemble a particular segment, instead of a whole genome or transcriptome, a target-specific assembly is a more sensible approach. GenSeed is a Perl program that implements a seed-driven recursive assembly consisting of cycles comprising a similarity search, read selection and assembly. The iterative process results in a progressive extension of the original seed sequence. GenSeed was tested and validated on many applications, including the reconstruction of nuclear genes or segments, full-length transcripts, and extrachromosomal genomes. The robustness of the method was confirmed through the use of a variety of DNA and protein seeds, including short sequences derived from SAGE and proteome projects.

Black-box decomposition approach for computational hemodynamics: One-dimensional models

Increasing efforts exist in integrating different levels of detail in models of the cardiovascular system. For instance, one-dimensional representations are employed to model the systemic circulation. In this context, effective and black-box-type decomposition strategies for one-dimensional networks are needed, so as to: (i) employ domain decomposition strategies for large systemic models (1D-1D coupling) and (ii) provide the conceptual basis for dimensionally-heterogeneous representations (1D-3D coupling, among various possibilities). The strategy proposed in this article works for both of these two scenarios, though the several applications shown to illustrate its performance focus on the 1D-1D coupling case. A one-dimensional network is decomposed in such a way that each coupling point connects two (and not more) of the sub-networks. At each of the M connection points two unknowns are defined: the flow rate and pressure. These 2M unknowns are determined by 2M equations, since each sub-network provides one (non-linear) equation per coupling point. It is shown how to build the 2M x 2M non-linear system with arbitrary and independent choice of boundary conditions for each of the sub-networks. The idea is then to solve this non-linear system until convergence, which guarantees strong coupling of the complete network. In other words, if the non-linear solver converges at each time step, the solution coincides with what would be obtained by monolithically modeling the whole network. The decomposition thus imposes no stability restriction on the choice of the time step size. Effective iterative strategies for the non-linear system that preserve the black-box character of the decomposition are then explored. Several variants of matrix-free Broyden`s and Newton-GMRES algorithms are assessed as numerical solvers by comparing their performance on sub-critical wave propagation problems which range from academic test cases to realistic cardiovascular applications. A specific variant of Broyden`s algorithm is identified and recommended on the basis of its computer cost and reliability. (C) 2010 Elsevier B.V. All rights reserved.

A computational study of some rheological influences on the ""splashing experiment""

In various attempts to relate the behaviour of highly-elastic liquids in complex flows to their rheometrical behaviour, obvious candidates for study have been the variation of shear viscosity with shear rate, the two normal stress differences N(1) and N(2), especially N(1), the extensional viscosity, and the dynamic moduli G` and G ``. In this paper, we shall confine attention to `constant-viscosity` Boger fluids, and, accordingly, we shall limit attention to N(1), eta(E), G` and G ``. We shall concentrate on the ""splashing"" problem (particularly that which arises when a liquid drop falls onto the free surface of the same liquid). Modern numerical techniques are employed to provide the theoretical predictions. We show that high eta(E) can certainly reduce the height of the so-called Worthington jet, thus confirming earlier suggestions, but other rheometrical influences (steady and transient) can also have a role to play and the overall picture may not be as clear as it was once envisaged. We argue that this is due in the main to the fact that splashing is a manifestly unsteady flow. To confirm this proposition, we obtain numerical simulations for the linear Jeffreys model. (C) 2010 Elsevier B.V. All rights reserved.

A Bayesian Long-term Survival Model Parametrized in the Cured Fraction

The main goal of this paper is to investigate a cure rate model that comprehends some well-known proposals found in the literature. In our work the number of competing causes of the event of interest follows the negative binomial distribution. The model is conveniently reparametrized through the cured fraction, which is then linked to covariates by means of the logistic link. We explore the use of Markov chain Monte Carlo methods to develop a Bayesian analysis in the proposed model. The procedure is illustrated with a numerical example.

PK/DB: database for pharmacokinetic properties and predictive in silico ADME models

The study of pharmacokinetic properties (PK) is of great importance in drug discovery and development. In the present work, PK/DB (a new freely available database for PK) was designed with the aim of creating robust databases for pharmacokinetic studies and in silico absorption, distribution, metabolism and excretion (ADME) prediction. Comprehensive, web-based and easy to access, PK/DB manages 1203 compounds which represent 2973 pharmacokinetic measurements, including five models for in silico ADME prediction (human intestinal absorption, human oral bioavailability, plasma protein binding, bloodbrain barrier and water solubility).

Study of the phenanthroline-Mn-imidazole bonding in Mn(I) triscarbonyl complex: A X-ray and DFT computational analysis

355 nm light irradiation of fac-[Mn(CO)(3)(phen)(imH)](+) (fac-1) produces the mer-1 isomer and a long lived radical which can be efficiently trapped by electron acceptor molecules. EPR experiments shows that when excited, the manganese(I) complex can be readily oxidized by one-electron process to produce Mn(II) and phen(.-). In the present study, DFT calculations have been used to investigated the photochemical isomerization of the parent Mn(I) complex and to characterize the electronic structures of the long lived radical. The theoretical calculations have been performed on both the fac-1 and mer-1 species as well as on their one electron oxidized species fac-1+ and mer-1+ for the lowest spin configurations (S = 1/2) and fac-6 and mer-6 (S = 5/2) for the highest one to characterize these complexes. In particular, we used a charge decomposition analysis (CDA) and a natural bonding orbital (NBO) to have a better understanding of the chemical bonding in terms of the nature of electronic interactions. The observed variations in geometry and bond energies with an increasing oxidation state in the central metal ion are interpreted in terms of changes in the nature of metal-ligand bonding interactions. The X-ray structure of fac-1 is also described. (C) 2011 Elsevier B.V. All rights reserved.