Statistical analysis and simulation techniques in wall-bounded turbulence

The present work is devoted to the assessment of the energy fluxes physics in the space of scales and physical space of wall-turbulent flows. The generalized Kolmogorov equation will be applied to DNS data of a turbulent channel flow in order to describe the energy fluxes paths from production to dissipation in the augmented space of wall-turbulent flows. This multidimensional description will be shown to be crucial to understand the formation and sustainment of the turbulent fluctuations fed by the energy fluxes coming from the near-wall production region. An unexpected behavior of the energy fluxes comes out from this analysis consisting of spiral-like paths in the combined physical/scale space where the controversial reverse energy cascade plays a central role. The observed behavior conflicts with the classical notion of the Richardson/Kolmogorov energy cascade and may have strong repercussions on both theoretical and modeling approaches to wall-turbulence. To this aim a new relation stating the leading physical processes governing the energy transfer in wall-turbulence is suggested and shown able to capture most of the rich dynamics of the shear dominated region of the flow. Two dynamical processes are identified as driving mechanisms for the fluxes, one in the near wall region and a second one further away from the wall. The former, stronger one is related to the dynamics involved in the near-wall turbulence regeneration cycle. The second suggests an outer self-sustaining mechanism which is asymptotically expected to take place in the log-layer and could explain the debated mixed inner/outer scaling of the near-wall statistics. The same approach is applied for the first time to a filtered velocity field. A generalized Kolmogorov equation specialized for filtered velocity field is derived and discussed. The results will show what effects the subgrid scales have on the resolved motion in both physical and scale space, singling out the prominent role of the filter length compared to the cross-over scale between production dominated scales and inertial range, lc, and the reverse energy cascade region lb. The systematic characterization of the resolved and subgrid physics as function of the filter scale and of the wall-distance will be shown instrumental for a correct use of LES models in the simulation of wall turbulent flows. Taking inspiration from the new relation for the energy transfer in wall turbulence, a new class of LES models will be also proposed. Finally, the generalized Kolmogorov equation specialized for filtered velocity fields will be shown to be an helpful statistical tool for the assessment of LES models and for the development of new ones. As example, some classical purely dissipative eddy viscosity models are analyzed via an a priori procedure.

Investigating within-canopy variation of functional traits and cellular structure of sugar maple (Acer saccharum) leaves

Patterns of increasing leaf mass per area (LMA), area-based leaf nitrogen (Narea), and carbon isotope composition (δ13C) with increasing height in the canopy have been attributed to light gradients or hydraulic limitation in tall trees. Theoretical optimal distributions of LMA and Narea that scale with light maximize canopy photosynthesis; however, sub-optimal distributions are often observed due to hydraulic constraints on leaf development. Using observational, experimental, and modeling approaches, we investigated the response of leaf functional traits (LMA, density, thickness, and leaf nitrogen), leaf carbon isotope composition (δ13C), and cellular structure to light availability, height, and leaf water potential (Ψl) in an Acer saccharum forest to tease apart the influence of light and hydraulic limitations. LMA, leaf and palisade layer thickness, and leaf density were greater at greater light availability but similar heights, highlighting the strong control of light on leaf morphology and cellular structure. Experimental shading decreased both LMA and area-based leaf nitrogen (Narea) and revealed that LMA and Narea were more strongly correlated with height earlier in the growing season and with light later in the growing season. The supply of CO2 to leaves at higher heights appeared to be constrained by stomatal sensitivity to vapor pressure deficit (VPD) or midday leaf water potential, as indicated by increasing δ13C and VPD and decreasing midday Ψl with height. Model simulations showed that daily canopy photosynthesis was biased during the early growing season when seasonality was not accounted for, and was biased throughout the growing season when vertical gradients in LMA and Narea were not accounted for. Overall, our results suggest that leaves acclimate to light soon after leaf expansion, through an accumulation of leaf carbon, thickening of palisade layers and increased LMA, and reduction in stomatal sensitivity to Ψl or VPD. This period of light acclimation in leaves appears to optimize leaf function over time, despite height-related constraints early in the growing season. Our results imply that vertical gradients in leaf functional traits and leaf acclimation to light should be incorporated in canopy function models in order to refine estimates of canopy photosynthesis.

Arctic patterned-ground ecosystems: A synthesis of field studies and models along a North American Arctic Transect

Arctic landscapes have visually striking patterns of small polygons, circles, and hummocks. The linkages between the geophysical and biological components of these systems and their responses to climate changes are not well understood. The "Biocomplexity of Patterned Ground Ecosystems" project examined patterned-ground features (PGFs) in all five Arctic bioclimate subzones along an 1800-km trans-Arctic temperature gradient in northern Alaska and northwestern Canada. This paper provides an overview of the transect to illustrate the trends in climate, PGFs, vegetation, n-factors, soils, active-layer depth, and frost heave along the climate gradient. We emphasize the thermal effects of the vegetation and snow on the heat and water fluxes within patterned-ground systems. Four new modeling approaches build on the theme that vegetation controls microscale soil temperature differences between the centers and margins of the PGFs, and these in turn drive the movement of water, affect the formation of aggradation ice, promote differential soil heave, and regulate a host of system propel-ties that affect the ability of plants to colonize the centers of these features. We conclude with an examination of the possible effects of a climate wan-ning on patterned-ground ecosystems.

An Early-Warning System for Hypo-/Hyperglycemic Events Based on Fusion of Adaptive Prediction Models

Introduction: Early warning of future hypoglycemic and hyperglycemic events can improve the safety of type 1 diabetes mellitus (T1DM) patients. The aim of this study is to design and evaluate a hypoglycemia / hyperglycemia early warning system (EWS) for T1DM patients under sensor-augmented pump (SAP) therapy. Methods: The EWS is based on the combination of data-driven online adaptive prediction models and a warning algorithm. Three modeling approaches have been investigated: (i) autoregressive (ARX) models, (ii) auto-regressive with an output correction module (cARX) models, and (iii) recurrent neural network (RNN) models. The warning algorithm performs postprocessing of the models′ outputs and issues alerts if upcoming hypoglycemic/hyperglycemic events are detected. Fusion of the cARX and RNN models, due to their complementary prediction performances, resulted in the hybrid autoregressive with an output correction module/recurrent neural network (cARN)-based EWS. Results: The EWS was evaluated on 23 T1DM patients under SAP therapy. The ARX-based system achieved hypoglycemic (hyperglycemic) event prediction with median values of accuracy of 100.0% (100.0%), detection time of 10.0 (8.0) min, and daily false alarms of 0.7 (0.5). The respective values for the cARX-based system were 100.0% (100.0%), 17.5 (14.8) min, and 1.5 (1.3) and, for the RNN-based system, were 100.0% (92.0%), 8.4 (7.0) min, and 0.1 (0.2). The hybrid cARN-based EWS presented outperforming results with 100.0% (100.0%) prediction accuracy, detection 16.7 (14.7) min in advance, and 0.8 (0.8) daily false alarms. Conclusion: Combined use of cARX and RNN models for the development of an EWS outperformed the single use of each model, achieving accurate and prompt event prediction with few false alarms, thus providing increased safety and comfort.

Experimental validation of a mean field model of mineralized collagen fiber arrays at two levels of hierarchy

In the course of this study, stiffness of a fibril array of mineralized collagen fibrils modeled with a mean field method was validated experimentally at site-matched two levels of tissue hierarchy using mineralized turkey leg tendons (MTLT). The applied modeling approaches allowed to model the properties of this unidirectional tissue from nanoscale (mineralized collagen fibrils) to macroscale (mineralized tendon). At the microlevel, the indentation moduli obtained with a mean field homogenization scheme were compared to the experimental ones obtained with microindentation. At the macrolevel, the macroscopic stiffness predicted with micro finite element (μFE) models was compared to the experimental stiffness measured with uniaxial tensile tests. Elastic properties of the elements in μFE models were injected from the mean field model or two-directional microindentations. Quantitatively, the indentation moduli can be properly predicted with the mean-field models. Local stiffness trends within specific tissue morphologies are very weak, suggesting additional factors responsible for the stiffness variations. At macrolevel, the μFE models underestimate the macroscopic stiffness, as compared to tensile tests, but the correlations are strong.

Internal Models, Vestibular Cognition, and Mental Imagery: Conceptual Considerations

Vestibular cognition has recently gained attention. Despite numerous experimental and clinical demonstrations, it is not yet clear what vestibular cognition really is. For future research in vestibular cognition, adopting a computational approach will make it easier to explore the underlying mech- anisms. Indeed, most modeling approaches in vestibular science include a top-down or a priori component. We review recent Bayesian optimal observer models, and discuss in detail the conceptual value of prior assumptions, likelihood and posterior estimates for research in vestibular cognition. We then consider forward models in vestibular processing, which are required in order to distinguish between sensory input that is induced by active self-motion, and sensory input that is due to passive self-motion. We suggest that forward models are used not only in the service of estimating sensory states but they can also be drawn upon in an offline mode (e.g., spatial perspective transformations), in which interaction with sensory input is not desired. A computational approach to vestibular cogni- tion will help to discover connections across studies, and it will provide a more coherent framework for investigating vestibular cognition.

The Impact of Thermal Coupling on Catalyst Behavior in Wall-Coated Heat-Exchanger Microreactors

This thesis presents a numerical study of reaction and diffusion phenomena in wall-coated heat-exchanger microreactors. Specifically, the interactions between an endothermic and exothermic catalyst layer separated by an impermeable wall is studied to understand the inherent behavior of the system. Two modeling approaches are presented, the first under the assumption of a constant thermal gradient and neglecting heat of reaction and the second considering both catalyst layers and reaction heat. Both studies found that thicker, more thermally insulating catalyst layers increase the effectiveness of the exothermic reaction by allowing for accumulation of reaction heat while thinner catalyst layers for the endothermic catalyst allow for direct access of the reactant to higher wall temperatures.

A full pedigree based method for the statistical assessment of genetic anticipation

Genetic anticipation is defined as a decrease in age of onset or increase in severity as the disorder is transmitted through subsequent generations. Anticipation has been noted in the literature for over a century. Recently, anticipation in several diseases including Huntington's Disease, Myotonic Dystrophy and Fragile X Syndrome were shown to be caused by expansion of triplet repeats. Anticipation effects have also been observed in numerous mental disorders (e.g. Schizophrenia, Bipolar Disorder), cancers (Li-Fraumeni Syndrome, Leukemia) and other complex diseases. ^ Several statistical methods have been applied to determine whether anticipation is a true phenomenon in a particular disorder, including standard statistical tests and newly developed affected parent/affected child pair methods. These methods have been shown to be inappropriate for assessing anticipation for a variety of reasons, including familial correlation and low power. Therefore, we have developed family-based likelihood modeling approaches to model the underlying transmission of the disease gene and penetrance function and hence detect anticipation. These methods can be applied in extended families, thus improving the power to detect anticipation compared with existing methods based only upon parents and children. The first method we have proposed is based on the regressive logistic hazard model. This approach models anticipation by a generational covariate. The second method allows alleles to mutate as they are transmitted from parents to offspring and is appropriate for modeling the known triplet repeat diseases in which the disease alleles can become more deleterious as they are transmitted across generations. ^ To evaluate the new methods, we performed extensive simulation studies for data simulated under different conditions to evaluate the effectiveness of the algorithms to detect genetic anticipation. Results from analysis by the first method yielded empirical power greater than 87% based on the 5% type I error critical value identified in each simulation depending on the method of data generation and current age criteria. Analysis by the second method was not possible due to the current formulation of the software. The application of this method to Huntington's Disease and Li-Fraumeni Syndrome data sets revealed evidence for a generation effect in both cases. ^

Thorium and radiocarbon measurements on sediment cores from the Northseast Atlantic

Radiocarbon and 230Thexcess data from six NE Atlantic box cores are considered. The cores form a transect from the Porcupine Abyssal Plain over the East Thulean Rise to the southern end of Feni Drift. The chronology for the cores is established from bulk sediment carbonate radiocarbon data and reveals that sections exhibiting constant accumulation rates can be identified in all the cores, with rates of 3.0-3.5 cm/kyr on the plain through the Holocene and late Holocene rates of 4.3-6.6 cm/kyr elsewhere. Five out of the six cores show accumulations of more 230Thexcess than is produced in the overlying water column, with the greatest inventories (up to 225% of production) in the cores from the rise and drift. A size fraction comparison between two cores from the plain and rise reveals that the higher overall accumulation rates and 230Thexcess inventories in the off-plain cores are due to an increased fine (<5 µm) component fraction, whereas the flux of coarser material is similar to that received on the plain. This suggests that the higher fluxes of materials observed are physically (rather than biogeochemically) driven and also that drift formation has been continuously active in the late Holocene. Sections of all the cores where regular accumulation is defined by the radiocarbon data are modeled first by a linear radiocarbon age/depth model and second by a constant rain (230Thexcess)0 model prorated for the observed core inventories. These modeling approaches yield historical mass accumulation rate estimates which are generally in reasonable agreement (±30%), but the differences observed appear to be well organized in time rather than random.

Analysis of house prices to assess economic impacts of new public transport infrastructure: Madrid metro line 12.

Transportation infrastructure is known to affect the value of real estate property by virtue of changes in accessibility. The impact of transportation facilities is highly localized as well, and it is possible that spillover effects result from the capitalization of accessibility. The objective of this study was to review the theoretical background related to spatial hedonic models and the opportunities that they provided to evaluate the effect of new transportation infrastructure. An empirical case study is presented: the Madrid Metro Line 12, known as Metrosur, in the region of Madrid, Spain. The effect of proximity to metro stations on housing prices was evaluated. The analysis took into account a host of variables, including structure, location, and neighborhood and made use of three modeling approaches: linear regression estimation with ordinary least squares, spatial error, and spatial lag. The results indicated that better accessibility to Metrosur stations had a positive impact on real estate values and that the effect was marked in cases in which a house was for sale. The results also showed the presence of submarkets, which were well defined by geographic boundaries, and transport fares, which implied that the economic benefits differed across municipalities.

A model of the spatially dependent mechanical properties of the axon during its growth

Neuronal growth is a complex process involving many intra- and extracellular mechanisms which are collaborating conjointly to participate to the development of the nervous system. More particularly, the early neocortical development involves the creation of a multilayered structure constituted by neuronal growth (driven by axonal or dendritic guidance cues) as well as cell migration. The underlying mechanisms of such structural lamination not only implies important biochemical changes at the intracellular level through axonal microtubule (de)polymerization and growth cone advance, but also through the directly dependent stress/stretch coupling mechanisms driving them. Efforts have recently focused on modeling approaches aimed at accounting for the effect of mechanical tension or compression on the axonal growth and subsequent soma migration. However, the reciprocal influence of the biochemical structural evolution on the mechanical properties has been mostly disregarded. We thus propose a new model aimed at providing the spatially dependent mechanical properties of the axon during its growth. Our in-house finite difference solver Neurite is used to describe the guanosine triphosphate (GTP) transport through the axon, its dephosphorylation in guanosine diphosphate (GDP), and thus the microtubules polymerization. The model is calibrated against experimental results and the tensile and bending mechanical stiffnesses are ultimately inferred from the spatially dependent microtubule occupancy. Such additional information is believed to be of drastic relevance in the growth cone vicinity, where biomechanical mechanisms are driving axonal growth and pathfinding. More specifically, the confirmation of a lower stiffness in the distal axon ultimately participates in explaining the controversy associated to the tensile role of the growth cone.

Evaluation of air quality impacts with an integrated assessment model for Spain

The present paper describes the advancement and evaluation of air quality-related impacts with the Atmospheric Evaluation and Research Integrated system for Spain (AERIS). In its current version, AERIS is able to provide estimates on the impacts of air quality over human health (PM2.5 and O3), crops and vegetation (O3). The modules that allow quantifying the before mentioned impacts were modeled by applying different approaches (mostly for the European context) present in scientific literature to the conditions of the Iberian Peninsula. This application was supported by reliable data sources, as well as by the good predictive capacity of AERIS for ambient concentrations. For validation purposes, the estimates of AERIS for impacts on human health (change in the statistical life expectancy-PM2.5) and vegetation (loss of wheat crops-O3) were compared against results from the SERCA project and GAINS estimates for two emission scenarios. In general, good results evidenced by reasonable correlation coefficients were obtained, therefore confirming the adequateness of the followed modeling approaches and the quality of AERIS predictions.

Incorporação do espalhamento Compton no modelo de TBC modificado

No último século, houve grande avanço no entendimento das interações das radiações com a matéria. Essa compreensão se faz necessária para diversas aplicações, entre elas o uso de raios X no diagnóstico por imagens. Neste caso, imagens são formadas pelo contraste resultante da diferença na atenuação dos raios X pelos diferentes tecidos do corpo. Entretanto, algumas das interações dos raios X com a matéria podem levar à redução da qualidade destas imagens, como é o caso dos fenômenos de espalhamento. Muitas abordagens foram propostas para estimar a distribuição espectral de fótons espalhados por uma barreira, ou seja, como no caso de um feixe de campo largo, ao atingir um plano detector, tais como modelos que utilizam métodos de Monte Carlo e modelos que utilizam aproximações analíticas. Supondo-se um espectro de um feixe primário que não interage com nenhum objeto após sua emissão pelo tubo de raios X, este espectro é, essencialmente representado pelos modelos propostos anteriormente. Contudo, considerando-se um feixe largo de radiação X, interagindo com um objeto, a radiação a ser detectada por um espectrômetro, passa a ser composta pelo feixe primário, atenuado pelo material adicionado, e uma fração de radiação espalhada. A soma destas duas contribuições passa a compor o feixe resultante. Esta soma do feixe primário atenuado, com o feixe de radiação espalhada, é o que se mede em um detector real na condição de feixe largo. O modelo proposto neste trabalho visa calcular o espectro de um tubo de raios X, em situação de feixe largo, o mais fidedigno possível ao que se medem em condições reais. Neste trabalho se propõe a discretização do volume de interação em pequenos elementos de volume, nos quais se calcula o espalhamento Compton, fazendo uso de um espectro de fótons gerado pelo Modelo de TBC, a equação de Klein-Nishina e considerações geométricas. Por fim, o espectro de fótons espalhados em cada elemento de volume é somado ao espalhamento dos demais elementos de volume, resultando no espectro total espalhado. O modelo proposto foi implementado em ambiente computacional MATLAB® e comparado com medições experimentais para sua validação. O modelo proposto foi capaz de produzir espectros espalhados em diferentes condições, apresentando boa conformidade com os valores medidos, tanto em termos quantitativos, nas quais a diferença entre kerma no ar calculado e kerma no ar medido é menor que 10%, quanto qualitativos, com fatores de mérito superiores a 90%.

On systems thinking, systems biology and the in Silico Plant

The recent summary report of a Department of Energy Workshop on Plant Systems Biology (P.V. Minorsky [2003] Plant Physiol 132: 404-409) offered a welcomed advocacy for systems analysis as essential in understanding plant development, growth, and production. The goal of the Workshop was to consider methods for relating the results of molecular research to real-world challenges in plant production for increased food supplies, alternative energy sources, and environmental improvement. The rather surprising feature of this report, however, was that the Workshop largely overlooked the rich history of plant systems analysis extending over nearly 40 years (Sinclair and Seligman, 1996) that has considered exactly those challenges targeted by the Workshop. Past systems research has explored and incorporated biochemical and physiological knowledge into plant simulation models from a number of perspectives. The research has resulted in considerable understanding and insight about how to simulate plant systems and the relative contribution of various factors in influencing plant production. These past activities have contributed directly to research focused on solving the problems of increasing biomass production and crop yields. These modeling approaches are also now providing an avenue to enhance integration of molecular genetic technologies in plant improvement (Hammer et al., 2002).

On the optimal ratio of heavy to light chain genes for efficient recombinant antibody production by CHO cells

Monoclonal antibodies (Mab) are heterotetramers consisting of an equimolar ratio of heavy chain (HC) and light chain (LC) polypeptides. Accordingly, most recombinant Mab expression systems utilize an equimolar ratio of heavy chain (he) to light chain (lc) genes encoded on either one or two plasmids. However, there is no evidence to suggest that this gene ratio is optimal for stable or transient production of recombinant Mab. In this study we have determined the optimal ratio of hc:lc genes for production of a recombinant IgG(4) Mab, cB72.3, by Chinese hamster ovary (CHO) cells using both empirical and mathematical modeling approaches. Polyethyleneimine-mediated transient expression of cB72.3 at varying ratios of hc:lc genes encoded on separate plasmids yielded an optimal Mab titer at a hc:lc gene ratio of 3:2; a conclusion confirmed by separate mathematical modeling of the Mab folding and assembly process using transient expression data. On the basis of this information, we hypothesized that utilization of he genes at low hc:lc gene ratios is more efficient. To confirm this, cB72.3 Mab was transiently produced by CHO cells at constant he and varying lc gene dose. Under these conditions, Mab yield was increased with a concomitant increase in lc gene dose. To determine if the above findings also apply to stably transfected CHO cells producing recombinant Mab, we compared the intra- and extracellular ratios of HC and LC polypeptides for three GS-CHO cells lines transfected with a 1:1 ratio of hc:lc genes and selected for stable expression of the same recombinant Mab, cB72.3. Intra- and extracellular HC:LC polypeptide ratios ranged from 1:2 to 1:5, less than that observed on transient expression of the same Mab in parental CHO cells using the same vector. In conclusion, our data suggest that the optimal ratio of hc:lc genes used for transient and stable expression of Mab differ. In the case of the latter, we infer that optimal Mab production by stably transfected cells represents a compromise between HC abundance limiting productivity and the requirement for excess LC to render Mab folding and assembly more efficient.