Simulated-annealing-based conditional simulation for the local-scale characterization of heterogeneous aquifers

Simulated-annealing-based conditional simulations provide a flexible means of quantitatively integrating diverse types of subsurface data. Although such techniques are being increasingly used in hydrocarbon reservoir characterization studies, their potential in environmental, engineering and hydrological investigations is still largely unexploited. Here, we introduce a novel simulated annealing (SA) algorithm geared towards the integration of high-resolution geophysical and hydrological data which, compared to more conventional approaches, provides significant advancements in the way that large-scale structural information in the geophysical data is accounted for. Model perturbations in the annealing procedure are made by drawing from a probability distribution for the target parameter conditioned to the geophysical data. This is the only place where geophysical information is utilized in our algorithm, which is in marked contrast to other approaches where model perturbations are made through the swapping of values in the simulation grid and agreement with soft data is enforced through a correlation coefficient constraint. Another major feature of our algorithm is the way in which available geostatistical information is utilized. Instead of constraining realizations to match a parametric target covariance model over a wide range of spatial lags, we constrain the realizations only at smaller lags where the available geophysical data cannot provide enough information. Thus we allow the larger-scale subsurface features resolved by the geophysical data to have much more due control on the output realizations. Further, since the only component of the SA objective function required in our approach is a covariance constraint at small lags, our method has improved convergence and computational efficiency over more traditional methods. Here, we present the results of applying our algorithm to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the local-scale porosity structure. Our procedure is first tested on a synthetic data set, and then applied to data collected at the Boise Hydrogeophysical Research Site.

Empirical study of correlated survival times for recurrent events with proportional hazards margins and the effect of correlation and censoring.

Background: In longitudinal studies where subjects experience recurrent incidents over a period of time, such as respiratory infections, fever or diarrhea, statistical methods are required to take into account the within-subject correlation. Methods: For repeated events data with censored failure, the independent increment (AG), marginal (WLW) and conditional (PWP) models are three multiple failure models that generalize Cox"s proportional hazard model. In this paper, we revise the efficiency, accuracy and robustness of all three models under simulated scenarios with varying degrees of within-subject correlation, censoring levels, maximum number of possible recurrences and sample size. We also study the methods performance on a real dataset from a cohort study with bronchial obstruction. Results: We find substantial differences between methods and there is not an optimal method. AG and PWP seem to be preferable to WLW for low correlation levels but the situation reverts for high correlations. Conclusions: All methods are stable in front of censoring, worsen with increasing recurrence levels and share a bias problem which, among other consequences, makes asymptotic normal confidence intervals not fully reliable, although they are well developed theoretically.

Chaotic systems with a null conditional Lyapunov exponent under nonlinear driving.

Control of a chaotic system by homogeneous nonlinear driving, when a conditional Lyapunov exponent is zero, may give rise to special and interesting synchronizationlike behaviors in which the response evolves in perfect correlation with the drive. Among them, there are the amplification of the drive attractor and the shift of it to a different region of phase space. In this paper, these synchronizationlike behaviors are discussed, and demonstrated by computer simulation of the Lorentz model [E. N. Lorenz, J. Atmos. Sci. 20 130 (1963)] and the double scroll [T. Matsumoto, L. O. Chua, and M. Komuro, IEEE Trans. CAS CAS-32, 798 (1985)].

Conditional maximum likelihood timing recovery: estimators and bounds

This paper is concerned with the derivation of new estimators and performance bounds for the problem of timing estimation of (linearly) digitally modulated signals. The conditional maximum likelihood (CML) method is adopted, in contrast to the classical low-SNR unconditional ML (UML) formulationthat is systematically applied in the literature for the derivationof non-data-aided (NDA) timing-error-detectors (TEDs). A new CML TED is derived and proved to be self-noise free, in contrast to the conventional low-SNR-UML TED. In addition, the paper provides a derivation of the conditional Cramér–Rao Bound (CRB ), which is higher (less optimistic) than the modified CRB (MCRB)[which is only reached by decision-directed (DD) methods]. It is shown that the CRB is a lower bound on the asymptotic statisticalaccuracy of the set of consistent estimators that are quadratic with respect to the received signal. Although the obtained boundis not general, it applies to most NDA synchronizers proposed in the literature. A closed-form expression of the conditional CRBis obtained, and numerical results confirm that the CML TED attains the new bound for moderate to high Eg/No.

Self-Organising Maps and Correlation Analysis as a Tool to Explore Patterns in Excitation-Emission Matrix Data Sets and to Discriminate Dissolved Organic Matter Fluorescence Components

Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets.

Conditional equilibrium constants in multicomponent heterogeneous adsorption: The conditional affinity spectrum

The concept of conditional stability constant is extended to the competitive binding of small molecules to heterogeneous surfaces or macromolecules via the introduction of the conditional affinity spectrum (CAS). The CAS describes the distribution of effective binding energies experienced by one complexing agent at a fixed concentration of the rest. We show that, when the multicomponent system can be described in terms of an underlying affinity spectrum [integral equation (IE) approach], the system can always be characterized by means of a CAS. The thermodynamic properties of the CAS and its dependence on the concentration of the rest of components are discussed. In the context of metal/proton competition, analytical expressions for the mean (conditional average affinity) and the variance (conditional heterogeneity) of the CAS as functions of pH are reported and their physical interpretation discussed. Furthermore, we show that the dependence of the CAS variance on pH allows for the analytical determination of the correlation coefficient between the binding energies of the metal and the proton. Nonideal competitive adsorption isotherm and Frumkin isotherms are used to illustrate the results of this work. Finally, the possibility of using CAS when the IE approach does not apply (for instance, when multidentate binding is present) is explored. © 2006 American Institute of Physics.

Targeted inactivation of hypocretin receptors in dopaminergic and noradrenergic systems alters brain activity in wakefulness

Since the discovery of hypocretins/orexins (Hcrt/Ox) in 1998, several narcoleptic mouse models, such as Hcrt-KO, Hcrtrl-KO, Hcrtr2-KO and double receptors KO mice, and orexin-ataxin transgenic mice were generated. The available Hcrt mouse models do not allow the dissection of the specific role of Hcrt in each target region. Dr. Anne Vassalli generated loxP-flanked alleles for each Hcrt receptor, which are manipulated by Cre recombinase to generate mouse lines with disrupted Hcrtrl or Hcrtr2 (or both) in cell type-specific manner. The role of noradrenaline (NA) and dopamine (OA) in ttie regulation of vigilance states is well documented. The purpose of this thesis is to explore the role of the Hcrt input into these two monoaminergic systems. Chronic loss of Hcrtrl in NA neurons consolidated paradoxical sleep (PS), and altered wakefulness brain activity in baseline, during the sleep deprivation (SD), and when mice were challenged by a novel environment, or exposed to nest-building material. The analysis of alterations in the sleep EEG delta power showed a consistent correlation with the changes in the preceding waking quality in these mice. Targeted inactivation of Hcrt input into DA neurons showed that Hcrtr2 inactivation present the strongest phenotype. The loss of Hcrtr2 in DA neurons caused modified brain activities in spontaneous wakefulness, during SD, and in novel environmental conditions. In addition to alteration of wakefulness quality and quantity, conditional inactivation of Hcrtr2 in DA neurons caused an increased in time spent in PS in baseline and a delayed and less complete PS recovery after SD. In the first 30 min of sleep recovery, single (i.e. for Hcrtrl or Hcrtr2) conditional knockout receptor mice had opposite changes in delta activity, including an increased power density in the fast delta range with specific inactivation of Hcrtr2, but a decreased power density in the same range with specific inactivation of Hcrtrl in DA cells. These studies demonstrate a complex impact of Hcrt receptors signaling in both NA and DA system, not only on quantity and quality of wakefulness, but also on PS amount regulation as well as on SWS delta power expression. -- Depuis la découverte des hypocrétines/orexines (Hcrt/Ox) en 1998, plusieurs modèles de souris, narcoleptiques telles que Hcrt-KO, Hcrtr2-KO et récepteurs doubles KO et les souris transgéniques orexine-ataxine ont été générés. Les modèles de souris Hcrt disponibles ne permettaient pas la dissection du rôle spécifique de l'Hcrt dans chaque noyau neuronal cible. Notre laboratoire a généré des allèles loxP pour chacun des 2 gènes codant pour les récepteurs Hcrtr, qui sont manipulés par recombinase Cre pour générer des lignées de souris avec Hcrtrl inactivé, ou Hcrtr2 inactivé, (ou les deux), spécifiquement dans un type cellulaire particulier. Le rôle de la noradrénaline (NA) et la dopamine (DA) dans la régulation des états de vigilance est bien documentée. Le but de cette thèse est d'étudier le rôle de l'afférence Hcrt dans ces deux systèmes monoaminergiques au niveau de l'activité cérébrale telle qu'elle apparaît dans l'électroencéphalogramme (EEG). Mon travail montre que la perte chronique de Hcrtrl dans les neurones NA consolide le sommeil paradoxal (PS), et l'activité cérébrale de l'éveil est modifiée en condition spontanée, au cours d'une experience de privation de sommeil (SD), et lorsque les souris sont présentées à un nouvel environnement, ou exposées à des matériaux de construction du nid. Ces modifications de l'éveil sont corrélées à des modifications de puissance de l'activité delta du sommeil lent qui le suit. L'inactivation ciblée des Hcrtrs dans les neurones DA a montré que l'inactivation Hcrtr2 conduit au phénotype le plus marqué. La perte de Hcrtr2 dans les neurones DA mène à des modification d'activité cérébrale en éveil spontané, pendant SD, ainsi que dans des conditions environnementales nouvelles. En plus de l'altération de la qualité de l'éveil et de la quantité, l'inactivation conditionnelle de Hcrtr2 dans les neurones DA a provoqué une augmentation du temps passé en sommeil paradoxal (PS) en condition de base, et une reprise retardée et moins complète du PS après SD. Dans les 30 premières minutes de la récupération de sommeil, les modèles inactivés pour un seul des récepteurs (ie pour Hcrtrl ou Hcrtr2 seulement) montrent des changements opposés en activité delta, en particulier une densité de puissance accrue dans le delta rapide avec l'inactivation spécifique de Hcrtr2, mais une densité de puissance diminuée dans cette même gamme chez les souris inactivées spécifiquement en Hcrtrl dans les neurones DA. Ces études démontrent un impact complexe de l'inactivation de la neurotransmission au niveau des récepteurs d'Hcrt dans les deux compartiments NA et DA, non seulement sur la quantité et la qualité de l'éveil, mais aussi sur la régulation de quantité de sommeil paradoxal, ainsi que sur l'expression de la puissance delta pendant le sommeil lent.

Self-Organising Maps and Correlation Analysis as a Tool to Explore Patterns in Excitation-Emission Matrix Data Sets and to Discriminate Dissolved Organic Matter Fluorescence Components

Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets.

Empirical study of correlated survival times for recurrent events with proportional hazards margins and the effect of correlation and censoring.

Background: In longitudinal studies where subjects experience recurrent incidents over a period of time, such as respiratory infections, fever or diarrhea, statistical methods are required to take into account the within-subject correlation. Methods: For repeated events data with censored failure, the independent increment (AG), marginal (WLW) and conditional (PWP) models are three multiple failure models that generalize Cox"s proportional hazard model. In this paper, we revise the efficiency, accuracy and robustness of all three models under simulated scenarios with varying degrees of within-subject correlation, censoring levels, maximum number of possible recurrences and sample size. We also study the methods performance on a real dataset from a cohort study with bronchial obstruction. Results: We find substantial differences between methods and there is not an optimal method. AG and PWP seem to be preferable to WLW for low correlation levels but the situation reverts for high correlations. Conclusions: All methods are stable in front of censoring, worsen with increasing recurrence levels and share a bias problem which, among other consequences, makes asymptotic normal confidence intervals not fully reliable, although they are well developed theoretically.

Self-consistent theory of current and voltage noise in multimode ballistic conductors

Electron transport in a self-consistent potential along a ballistic two-terminal conductor has been investigated. We have derived general formulas which describe the nonlinear current-voltage characteristics, differential conductance, and low-frequency current and voltage noise assuming an arbitrary distribution function and correlation properties of injected electrons. The analytical results have been obtained for a wide range of biases: from equilibrium to high values beyond the linear-response regime. The particular case of a three-dimensional Fermi-Dirac injection has been analyzed. We show that the Coulomb correlations are manifested in the negative excess voltage noise, i.e., the voltage fluctuations under high-field transport conditions can be less than in equilibrium.

Cellular and molecular studies of the effects of a selective COX-2 inhibitor celecoxib in the cardiac cell line H9c2 and their correlation with death mechanisms

Cardiovascular disease is one of the leading causes of death worldwide, and evidence indicates a correlation between the inflammatory process and cardiac dysfunction. Selective inhibitors of cyclooxygenase-2 (COX-2) enzyme are not recommended for long-term use because of potentially severe side effects to the heart. Considering this and the frequent prescribing of commercial celecoxib, the present study analyzed cellular and molecular effects of 1 and 10 µM celecoxib in a cell culture model. After a 24-h incubation, celecoxib reduced cell viability in a dose-dependent manner as also demonstrated in MTT assays. Furthermore, reverse transcription-polymerase chain reaction analysis showed that the drug modulated the expression level of genes related to death pathways, and Western blot analyses demonstrated a modulatory effect of the drug on COX-2 protein levels in cardiac cells. In addition, the results demonstrated a downregulation of prostaglandin E2 production by the cardiac cells incubated with celecoxib, in a dose-specific manner. These results are consistent with the decrease in cell viability and the presence of necrotic processes shown by Fourier transform infrared analysis, suggesting a direct correlation of prostanoids in cellular homeostasis and survival.

The application of the structural correlation method to determine the reaction coordinate for a putative ring closure reaction

The cr ystal structure of the compound 2-benzoylethylidene-3-(2,4- dibromophenyl)-2,3-dihydro-5-phenyl-l,3,4-thiadiazole* C23H16Br2NZOS (BRMEO) has been determined by using three dimensiona l x-ray diffraction data. The crys tal form is monoclinic, space group P21/c, a = 17.492(4), o -.t' 0 R 0 b =: 16.979(1), c = 14.962(1) A, "X. =o= 90 ',= 106.46(1) , z = 8, graphite-monochromatized Mo~ rad iation, Jl= 0.710J3~, D = 1.62g/cc and o D = 1.65g/cc. The data were col lected on ~ Nonius CAD-4 c diffractometer. The following atoms were made anisotropic: Br, S, N, 0, C7, and C14-C16 for each i ndependent molecu le ; the rest were left isotropic. For 3112 independent refl ec tions with F > 6G\F), R == 0.057. The compound has two independent molecules within the asymmetric unit. Two different conformers were observed which pack well together. /l The S---O interaction distances of 2.493(6) and 2 . 478(7) A were observed for molecules A and B respectively. These values are consistent with earlier findings for 2-benzoylmethylene-3-(2,4-dibromophenyl)- ~~ 2,3-dihydro-5-phenyl-l,3,4-thiadiazole C22H14Br2N20S (BRPHO) and 2-benzoylpropylidene-3-(2,4-dibromophenyl)-2,3-dihydroiii ,'r 5-phenyl-l,3,4-thiadiazole C24H18Br2N20S (BRPETO ) where S---O distances are l ess than the van der Waals (3.251\) but greater than those expected for () a single bond (1.50A). From the results and the literature it appears obvious that the energy/reaction coordinate pathway has a minimum between the end structures (the mono- and bicyclic compounds). * See reference (21) for nomenclature.

Estimating the Tobit Model with Serial Correlation: an Operational Approach

Several Authors Have Discussed Recently the Limited Dependent Variable Regression Model with Serial Correlation Between Residuals. the Pseudo-Maximum Likelihood Estimators Obtained by Ignoring Serial Correlation Altogether, Have Been Shown to Be Consistent. We Present Alternative Pseudo-Maximum Likelihood Estimators Which Are Obtained by Ignoring Serial Correlation Only Selectively. Monte Carlo Experiments on a Model with First Order Serial Correlation Suggest That Our Alternative Estimators Have Substantially Lower Mean-Squared Errors in Medium Size and Small Samples, Especially When the Serial Correlation Coefficient Is High. the Same Experiments Also Suggest That the True Level of the Confidence Intervals Established with Our Estimators by Assuming Asymptotic Normality, Is Somewhat Lower Than the Intended Level. Although the Paper Focuses on Models with Only First Order Serial Correlation, the Generalization of the Proposed Approach to Serial Correlation of Higher Order Is Also Discussed Briefly.

Ground-state self-consistent calculation of quantum dots under magnetic fields: Addition spectrum

A density-functional self-consistent calculation of the ground-state electronic density of quantum dots under an arbitrary magnetic field is performed. We consider a parabolic lateral confining potential. The addition energy, E(N+1)-E(N), where N is the number of electrons, is compared with experimental data and the different contributions to the energy are analyzed. The Hamiltonian is modeled by a density functional, which includes the exchange and correlation interactions and the local formation of Landau levels for different equilibrium spin populations. We obtain an analytical expression for the critical density under which spontaneous polarization, induced by the exchange interaction, takes place.

Self-consistent theory of current and voltage noise in multimode ballistic conductors

Electron transport in a self-consistent potential along a ballistic two-terminal conductor has been investigated. We have derived general formulas which describe the nonlinear current-voltage characteristics, differential conductance, and low-frequency current and voltage noise assuming an arbitrary distribution function and correlation properties of injected electrons. The analytical results have been obtained for a wide range of biases: from equilibrium to high values beyond the linear-response regime. The particular case of a three-dimensional Fermi-Dirac injection has been analyzed. We show that the Coulomb correlations are manifested in the negative excess voltage noise, i.e., the voltage fluctuations under high-field transport conditions can be less than in equilibrium.