Modelo integrado de cuantificación del nivel de significación y de asignación del error tolerable en procesos de auditoría de estados contables

El objetivo que persigue un proceso de auditoría de estados contables es la comunicación por parte del auditor de una conclusión en relación al grado de razonabilidad con que tales estados reflejan la situación patrimonial, económica y financiera del ente de acuerdo a los criterios plasmados en las normas contables de referencia a ser utilizadas. El hecho que un auditor emita una conclusión errónea como consecuencia de su labor puede implicar la asunción de responsabilidades profesionales, civiles y penales como consecuencia de reclamos de usuarios de los estados contables que pudieran haberse visto perjudicados como consecuencia de la emisión de la conclusión errónea. Las normas contables a nivel nacional e internacional admiten la existencia de errores u omisiones en la información contenida en los estados contables, en la medida que tales desvíos no provoquen en los usuarios interesados en tales estados una decisión distinta a la que tomarían en caso de no existir los errores u omisiones aludidos. De lo expuesto en el párrafo anterior surge la cabal importancia que la determinación del nivel de significación total (nivel de desvíos admitidos por los usuarios de los estados contables en la información por ellos contenida) adquiere en los procesos de auditoría, como así también la asignación de tal nivel entre los distintos componentes de los estados contables (asignación del error tolerable) a los efectos de que los auditores eviten asumir responsabilidades de índole profesional, civil y/o penal. Hasta el momento no se conoce la existencia de modelos matemáticos que respalden de modo objetivo y verificable el cálculo del nivel de significación total y la asignación del error tolerable entre los distintos elementos conformantes de los estados contables. Entendemos que el desarrollo e integración de un modelo de cuantificación del nivel de significación total y de asignación del error tolerable tiene las siguientes repercusiones: 1 – Representaría para el auditor un elemento que respalde el modo de cuantificación del nivel de significación y la asignación del error tolerable entre los componentes de los estados contables. 2 – Permitiría que los auditores reduzcan las posibilidades de asumir responsabilidades de carácter profesional, civil y/o penales como consecuencia de su labor. 3 – Representaría un principio de avance a los efectos de que los organismos emisores de normas de auditoría a nivel nacional e internacional recepten elementos a los efectos de fijar directrices en relación al cálculo del nivel de significación y de asignación del error tolerable. 4 - Eliminaría al cálculo del nivel de significación como una barrera que afecte la comparabilidad de los estados contables.

Non-classical error bounds in the central limit theorem

The classical central limit theorem states the uniform convergence of the distribution functions of the standardized sums of independent and identically distributed square integrable real-valued random variables to the standard normal distribution function. While first versions of the central limit theorem are already due to Moivre (1730) and Laplace (1812), a systematic study of this topic started at the beginning of the last century with the fundamental work of Lyapunov (1900, 1901). Meanwhile, extensions of the central limit theorem are available for a multitude of settings. This includes, e.g., Banach space valued random variables as well as substantial relaxations of the assumptions of independence and identical distributions. Furthermore, explicit error bounds are established and asymptotic expansions are employed to obtain better approximations. Classical error estimates like the famous bound of Berry and Esseen are stated in terms of absolute moments of the random summands and therefore do not reflect a potential closeness of the distributions of the single random summands to a normal distribution. Non-classical approaches take this issue into account by providing error estimates based on, e.g., pseudomoments. The latter field of investigation was initiated by work of Zolotarev in the 1960's and is still in its infancy compared to the development of the classical theory. For example, non-classical error bounds for asymptotic expansions seem not to be available up to now ...

A comparative analysis of Cobb-Douglas model with additive and multiplicative error

This paper dis cusses the fitting of a Cobb-Doug las response curve Yi = αXβi, with additive error, Yi = αXβi + e i, instead of the usual multiplicative error Yi = αXβi (1 + e i). The estimation of the parameters A and B is discussed. An example is given with use of both types of error.

Stability and error analysis for a numerical scheme to approximate elastic flow

Otto-von-Guericke-Universität Magdeburg, Fakultät für Mathematik, Univ., Dissertation, 2015

Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference.

Restriction site-associated DNA sequencing (RADseq) provides researchers with the ability to record genetic polymorphism across thousands of loci for nonmodel organisms, potentially revolutionizing the field of molecular ecology. However, as with other genotyping methods, RADseq is prone to a number of sources of error that may have consequential effects for population genetic inferences, and these have received only limited attention in terms of the estimation and reporting of genotyping error rates. Here we use individual sample replicates, under the expectation of identical genotypes, to quantify genotyping error in the absence of a reference genome. We then use sample replicates to (i) optimize de novo assembly parameters within the program Stacks, by minimizing error and maximizing the retrieval of informative loci; and (ii) quantify error rates for loci, alleles and single-nucleotide polymorphisms. As an empirical example, we use a double-digest RAD data set of a nonmodel plant species, Berberis alpina, collected from high-altitude mountains in Mexico.

Compartmentalized Cerebral Metabolism of [1,6-(13)C]Glucose Determined by in vivo (13)C NMR Spectroscopy at 14.1 T.

Cerebral metabolism is compartmentalized between neurons and glia. Although glial glycolysis is thought to largely sustain the energetic requirements of neurotransmission while oxidative metabolism takes place mainly in neurons, this hypothesis is matter of debate. The compartmentalization of cerebral metabolic fluxes can be determined by (13)C nuclear magnetic resonance (NMR) spectroscopy upon infusion of (13)C-enriched compounds, especially glucose. Rats under light α-chloralose anesthesia were infused with [1,6-(13)C]glucose and (13)C enrichment in the brain metabolites was measured by (13)C NMR spectroscopy with high sensitivity and spectral resolution at 14.1 T. This allowed determining (13)C enrichment curves of amino acid carbons with high reproducibility and to reliably estimate cerebral metabolic fluxes (mean error of 8%). We further found that TCA cycle intermediates are not required for flux determination in mathematical models of brain metabolism. Neuronal tricarboxylic acid cycle rate (V(TCA)) and neurotransmission rate (V(NT)) were 0.45̴1;±̴1;0.01 and 0.11̴1;±̴1;0.01̴1;μmol/g/min, respectively. Glial V(TCA) was found to be 38̴1;±̴1;3% of total cerebral oxidative metabolism, accounting for more than half of neuronal oxidative metabolism. Furthermore, glial anaplerotic pyruvate carboxylation rate (V(PC)) was 0.069̴1;±̴1;0.004̴1;μmol/g/min, i.e., 25̴1;±̴1;1% of the glial TCA cycle rate. These results support a role of glial cells as active partners of neurons during synaptic transmission beyond glycolytic metabolism.

Role of the stress sigma factor RpoS in GacA/RsmA-controlled secondary metabolism and resistance to oxidative stress in Pseudomonas fluorescens CHA0.

In Pseudomonas fluorescens biocontrol strain CHA0, the two-component system GacS/GacA positively controls the synthesis of extracellular products such as hydrogen cyanide, protease, and 2,4-diacetylphloroglucinol, by upregulating the transcription of small regulatory RNAs which relieve RsmA-mediated translational repression of target genes. The expression of the stress sigma factor sigmaS (RpoS) was controlled positively by GacA and negatively by RsmA. By comparison with the wild-type CHA0, both a gacS and an rpoS null mutant were more sensitive to H2O2 in stationary phase. Overexpression of rpoS or of rsmZ, encoding a small RNA antagonistic to RsmA, restored peroxide resistance to a gacS mutant. By contrast, the rpoS mutant showed a slight increase in the expression of the hcnA (HCN synthase subunit) gene and of the aprA (major exoprotease) gene, whereas overexpression of sigmaS strongly reduced the expression of these genes. These results suggest that in strain CHA0, regulation of exoproduct synthesis does not involve sigmaS as an intermediate in the Gac/Rsm signal transduction pathway whereas sigmaS participates in Gac/Rsm-mediated resistance to oxidative stress.

Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference.

Restriction site-associated DNA sequencing (RADseq) provides researchers with the ability to record genetic polymorphism across thousands of loci for nonmodel organisms, potentially revolutionizing the field of molecular ecology. However, as with other genotyping methods, RADseq is prone to a number of sources of error that may have consequential effects for population genetic inferences, and these have received only limited attention in terms of the estimation and reporting of genotyping error rates. Here we use individual sample replicates, under the expectation of identical genotypes, to quantify genotyping error in the absence of a reference genome. We then use sample replicates to (i) optimize de novo assembly parameters within the program Stacks, by minimizing error and maximizing the retrieval of informative loci; and (ii) quantify error rates for loci, alleles and single-nucleotide polymorphisms. As an empirical example, we use a double-digest RAD data set of a nonmodel plant species, Berberis alpina, collected from high-altitude mountains in Mexico.

Error estimate and control in the MSFV method for multiphase flow in porous media

n this paper the iterative MSFV method is extended to include the sequential implicit simulation of time dependent problems involving the solution of a system of pressure-saturation equations. To control numerical errors in simulation results, an error estimate, based on the residual of the MSFV approximate pressure field, is introduced. In the initial time steps in simulation iterations are employed until a specified accuracy in pressure is achieved. This initial solution is then used to improve the localization assumption at later time steps. Additional iterations in pressure solution are employed only when the pressure residual becomes larger than a specified threshold value. Efficiency of the strategy and the error control criteria are numerically investigated. This paper also shows that it is possible to derive an a-priori estimate and control based on the allowed pressure-equation residual to guarantee the desired accuracy in saturation calculation.

Comparison of T1 relaxation times of the neurochemical profile in rat brain at 9.4 tesla and 14.1 tesla.

Knowledge of T(1) relaxation times can be important for accurate relative and absolute quantification of brain metabolites, for sensitivity optimizations, for characterizing molecular dynamics, and for studying changes induced by various pathological conditions. (1)H T(1) relaxation times of a series of brain metabolites, including J-coupled ones, were determined using a progressive saturation (PS) technique that was validated with an adiabatic inversion-recovery (IR) method. The (1)H T(1) relaxation times of 16 functional groups of the neurochemical profile were measured at 14.1T and 9.4T. Overall, the T(1) relaxation times found at 14.1T were, within the experimental error, identical to those at 9.4T. The T(1)s of some coupled spin resonances of the neurochemical profile were measured for the first time (e.g., those of gamma-aminobutyrate [GABA], aspartate [Asp], alanine [Ala], phosphoethanolamine [PE], glutathione [GSH], N-acetylaspartylglutamate [NAAG], and glutamine [Gln]). Our results suggest that T(1) does not increase substantially beyond 9.4T. Furthermore, the similarity of T(1) among the metabolites (approximately 1.5 s) suggests that T(1) relaxation time corrections for metabolite quantification are likely to be similar when using rapid pulsing conditions. We therefore conclude that the putative T(1) increase of metabolites has a minimal impact on sensitivity when increasing B(0) beyond 9.4T.

Selected configuration interaction with truncation energy error and application to the Ne atom

Selected configuration interaction (SCI) for atomic and molecular electronic structure calculations is reformulated in a general framework encompassing all CI methods. The linked cluster expansion is used as an intermediate device to approximate CI coefficients BK of disconnected configurations (those that can be expressed as products of combinations of singly and doubly excited ones) in terms of CI coefficients of lower-excited configurations where each K is a linear combination of configuration-state-functions (CSFs) over all degenerate elements of K. Disconnected configurations up to sextuply excited ones are selected by Brown's energy formula, ΔEK=(E-HKK)BK2/(1-BK2), with BK determined from coefficients of singly and doubly excited configurations. The truncation energy error from disconnected configurations, Δdis, is approximated by the sum of ΔEKS of all discarded Ks. The remaining (connected) configurations are selected by thresholds based on natural orbital concepts. Given a model CI space M, a usual upper bound ES is computed by CI in a selected space S, and EM=E S+ΔEdis+δE, where δE is a residual error which can be calculated by well-defined sensitivity analyses. An SCI calculation on Ne ground state featuring 1077 orbitals is presented. Convergence to within near spectroscopic accuracy (0.5 cm-1) is achieved in a model space M of 1.4× 109 CSFs (1.1 × 1012 determinants) containing up to quadruply excited CSFs. Accurate energy contributions of quintuples and sextuples in a model space of 6.5 × 1012 CSFs are obtained. The impact of SCI on various orbital methods is discussed. Since ΔEdis can readily be calculated for very large basis sets without the need of a CI calculation, it can be used to estimate the orbital basis incompleteness error. A method for precise and efficient evaluation of ES is taken up in a companion paper

Basis set superposition error-counterpoise corrected potential energy surfaces : application to hydrogen peroxide ... X (X=F-, Cl-, Br-, Li+, Na+) complexes

Møller-Plesset (MP2) and Becke-3-Lee-Yang-Parr (B3LYP) calculations have been used to compare the geometrical parameters, hydrogen-bonding properties, vibrational frequencies and relative energies for several X- and X+ hydrogen peroxide complexes. The geometries and interaction energies were corrected for the basis set superposition error (BSSE) in all the complexes (1-5), using the full counterpoise method, yielding small BSSE values for the 6-311 + G(3df,2p) basis set used. The interaction energies calculated ranged from medium to strong hydrogen-bonding systems (1-3) and strong electrostatic interactions (4 and 5). The molecular interactions have been characterized using the atoms in molecules theory (AIM), and by the analysis of the vibrational frequencies. The minima on the BSSE-counterpoise corrected potential-energy surface (PES) have been determined as described by S. Simón, M. Duran, and J. J. Dannenberg, and the results were compared with the uncorrected PES

Fusion of the human gene for the polyubiquitination co-effector UEV-1 with Kua, a newly identified gene

UEV proteins are enzymatically inactive variants of the E2 ubiquitin-conjugating enzymes that regulate noncanonical elongation of ubiquitin chains. In Saccharomyces cerevisiae, UEV is part of the RAD6-mediated error-free DNA repair pathway. In mammalian cells, UEV proteins can modulate c-FOS transcription and the G2-M transition of the cell cycle. Here we show that the UEV genes from phylogenetically distant organisms present a remarkable conservation in their exon–intron structure. We also show that the human UEV1 gene is fused with the previously unknown gene Kua. In Caenorhabditis elegans and Drosophila melanogaster, Kua and UEV are in separated loci, and are expressed as independent transcripts and proteins. In humans, Kua and UEV1 are adjacent genes, expressed either as separate transcripts encoding independent Kua and UEV1 proteins, or as a hybrid Kua–UEV transcript, encoding a two-domain protein. Kua proteins represent a novel class of conserved proteins with juxtamembrane histidine-rich motifs. Experiments with epitope-tagged proteins show that UEV1A is a nuclear protein, whereas both Kua and Kua–UEV localize to cytoplasmic structures, indicating that the Kua domain determines the cytoplasmic localization of Kua–UEV. Therefore, the addition of a Kua domain to UEV in the fused Kua–UEV protein confers new biological properties to this regulator of variant polyubiquitination.[Kua cDNAs isolated by RT-PCR and described in this paper have been deposited in the GenBank data library under accession nos. AF1155120 (H. sapiens) and AF152361 (D. melanogaster). Genomic clones containing UEV genes: S. cerevisiae, YGL087c (accession no. Z72609); S. pombe, c338 (accession no. AL023781); P. falciparum, MAL3P2 (accession no. AL034558); A. thaliana, F26F24 (accession no. AC005292); C. elegans, F39B2 (accession no. Z92834); D. melanogaster, AC014908; and H. sapiens, 1185N5 (accession no. AL034423). Accession numbers for Kua cDNAs in GenBank dbEST: M. musculus, AA7853; T. cruzi, AI612534. Other Kua-containing sequences: A. thaliana genomic clones F10M23 (accession no. AL035440), F19K23 (accession no. AC000375), and T20K9 (accession no. AC004786).