910 resultados para Event-based Model
Resumo:
Clays and claystones are used as backfill and barrier materials in the design of waste repositories, because they act as hydraulic barriers and retain contaminants. Transport through such barriers occurs mainly by molecular diffusion. There is thus an interest to relate the diffusion properties of clays to their structural properties. In previous work, we have developed a concept for up-scaling pore-scale molecular diffusion coefficients using a grid-based model for the sample pore structure. Here we present an operational algorithm which can generate such model pore structures of polymineral materials. The obtained pore maps match the rock’s mineralogical components and its macroscopic properties such as porosity, grain and pore size distributions. Representative ensembles of grains in 2D or 3D are created by a lattice Monte Carlo (MC) method, which minimizes the interfacial energy of grains starting from an initial grain distribution. Pores are generated at grain boundaries and/or within grains. The method is general and allows to generate anisotropic structures with grains of approximately predetermined shapes, or with mixtures of different grain types. A specific focus of this study was on the simulation of clay-like materials. The generated clay pore maps were then used to derive upscaled effective diffusion coefficients for non-sorbing tracers using a homogenization technique. The large number of generated maps allowed to check the relations between micro-structural features of clays and their effective transport parameters, as is required to explain and extrapolate experimental diffusion results. As examples, we present a set of 2D and 3D simulations and investigated the effects of nanopores within particles (interlayer pores) and micropores between particles. Archie’s simple power law is followed in systems with only micropores. When nanopores are present, additional parameters are required; the data reveal that effective diffusion coefficients could be described by a sum of two power functions, related to the micro- and nanoporosity. We further used the model to investigate the relationships between particle orientation and effective transport properties of the sample.
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Atmospheric concentrations of the three important greenhouse gases (GHGs) CO2, CH4 and N2O are mediated by processes in the terrestrial biosphere that are sensitive to climate and CO2. This leads to feedbacks between climate and land and has contributed to the sharp rise in atmospheric GHG concentrations since pre-industrial times. Here, we apply a process-based model to reproduce the historical atmospheric N2O and CH4 budgets within their uncertainties and apply future scenarios for climate, land-use change and reactive nitrogen (Nr) inputs to investigate future GHG emissions and their feedbacks with climate in a consistent and comprehensive framework1. Results suggest that in a business-as-usual scenario, terrestrial N2O and CH4 emissions increase by 80 and 45%, respectively, and the land becomes a net source of C by AD 2100. N2O and CH4 feedbacks imply an additional warming of 0.4–0.5 °C by AD 2300; on top of 0.8–1.0 °C caused by terrestrial carbon cycle and Albedo feedbacks. The land biosphere represents an increasingly positive feedback to anthropogenic climate change and amplifies equilibrium climate sensitivity by 22–27%. Strong mitigation limits the increase of terrestrial GHG emissions and prevents the land biosphere from acting as an increasingly strong amplifier to anthropogenic climate change.
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Most empirical studies support a decline in speciation rates through time, although evidence for constant speciation rates also exists. Declining rates have been explained by invoking pre-existing niches, whereas constant rates have been attributed to non-adaptive processes such as sexual selection and mutation. Trends in speciation rate and the processes underlying it remain unclear, representing a critical information gap in understanding patterns of global diversity. Here we show that the temporal trend in the speciation rate can also be explained by frequency-dependent selection. We construct a frequency-dependent and DNA sequence-based model of speciation. We compare our model to empirical diversity patterns observed for cichlid fish and Darwin's finches, two classic systems for which speciation rates and richness data exist. Negative frequency-dependent selection predicts well both the declining speciation rate found in cichlid fish and explains their species richness. For groups like the Darwin's finches, in which speciation rates are constant and diversity is lower, speciation rate is better explained by a model without frequency-dependent selection. Our analysis shows that differences in diversity may be driven by incipient species abundance with frequency-dependent selection. Our results demonstrate that genetic-distance-based speciation and frequency-dependent selection are sufficient to explain the high diversity observed in natural systems and, importantly, predict decay through time in speciation rate in the absence of pre-existing niches.
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Lesni Potok stream drains a forested headwater catchment in the central Czech Republic. It was artificially acidified with hydrochloric acid (HCl) for four hours to assess the role of stream substrate in acid-neutralisation and recovery. The pH was lowered from 4.7 to 3.2. Desorption of Ca and MP and desorption or solution of Al dominated acid-neutralisation; Al mobilisation was more important later. The stream substrate released 4.542 meq Ca, 1, 184 meq Mg, and 2,329 meq Al over a 45 in long and I in wide stream segment, smaller amounts of Be. Cd, Fe, and Mn were released. Adsorption of SO42- and desorption of F- occurred during the acidification phase of the experiment. The exchange reactions were rapidly reversible for Ca, Mg and SO42- but not symmetric as the substrate resorbed 1083, 790 and 0 meq Ca, Mg, and Al. respectively, in a 4-hour recovery period. Desorption of SO42- occurred during the resorption of Ca and Mg. These exchange and dissolution reactions delay acidification, diminish the pH depression and retard recovery from episodic acidification. The behaviour of the stream substrate-water interaction resembles that for soil-soil water interactions. A mathematical dynamic mass-balance based model, MASS (Modelling Acidification of Stream Sediments), was developed which simulates the adsorption and desorption of base cations during the experiment and was successfully calibrated to the experimental data.
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The aim of this study was to develop a GST-based methodology for accurately measuring the degree of transverse isotropy in trabecular bone. Using femoral sub-regions scanned in high-resolution peripheral QCT (HR-pQCT) and clinical-level-resolution QCT, trabecular orientation was evaluated using the mean intercept length (MIL) and the gradient structure tensor (GST) on the HR-pQCT and QCT data, respectively. The influence of local degree of transverse isotropy (DTI) and bone mineral density (BMD) was incorporated into the investigation. In addition, a power based model was derived, rendering a 1:1 relationship between GST and MIL eigenvalues. A specific DTI threshold (DTI thres) was found for each investigated size of region of interest (ROI), above which the estimate of major trabecular direction of the GST deviated no more than 30° from the gold standard MIL in 95% of the remaining ROIs (mean error: 16°). An inverse relationship between ROI size and DTI thres was found for discrete ranges of BMD. A novel methodology has been developed, where transversal isotropic measures of trabecular bone can be obtained from clinical QCT images for a given ROI size, DTI thres and power coefficient. Including DTI may improve future clinical QCT finite-element predictions of bone strength and diagnoses of bone disease.
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One of the current challenges in evolutionary ecology is understanding the long-term persistence of contemporary-evolving predator–prey interactions across space and time. To address this, we developed an extension of a multi-locus, multi-trait eco-evolutionary individual-based model that incorporates several interacting species in explicit landscapes. We simulated eco-evolutionary dynamics of multiple species food webs with different degrees of connectance across soil-moisture islands. A broad set of parameter combinations led to the local extinction of species, but some species persisted, and this was associated with (1) high connectance and omnivory and (2) ongoing evolution, due to multi-trait genetic variability of the embedded species. Furthermore, persistence was highest at intermediate island distances, likely because of a balance between predation-induced extinction (strongest at short island distances) and the coupling of island diversity by top predators, which by travelling among islands exert global top-down control of biodiversity. In the simulations with high genetic variation, we also found widespread trait evolutionary changes indicative of eco-evolutionary dynamics. We discuss how the ever-increasing computing power and high-resolution data availability will soon allow researchers to start bridging the in vivo–in silico gap.
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This study investigated the empirical differentiation of prospective memory, executive functions, and metacognition and their structural relationships in 119 elementary school children (M = 95 months, SD = 4.8 months). These cognitive abilities share many characteristics on the theoretical level and are all highly relevant in many everyday contexts when intentions must be executed. Nevertheless, their empirical relationships have not been examined on the latent level, although an empirical approach would contribute to our knowledge concerning the differentiation of cognitive abilities during childhood. We administered a computerized event-based prospective memory task, three executive function tasks (updating, inhibition, shifting), and a metacognitive control task in the context of spelling. Confirmatory factor analysis revealed that the three cognitive abilities are already empirically differentiable in young elementary school children. At the same time, prospective memory and executive functions were found to be strongly related, and there was also a close link between prospective memory and metacognitive control. Furthermore, executive functions and metacognitive control were marginally significantly related. The findings are discussed within a framework of developmental differentiation and conceptual similarities and differences.
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The urate transporter, GLUT9, is responsible for the basolateral transport of urate in the proximal tubule of human kidneys and in the placenta, playing a central role in uric acid homeostasis. GLUT9 shares the least homology with other members of the glucose transporter family, especially with the glucose transporting members GLUT1-4 and is the only member of the GLUT family to transport urate. The recently published high-resolution structure of XylE, a bacterial D-xylose transporting homologue, yields new insights into the structural foundation of this GLUT family of proteins. While this represents a huge milestone, it is unclear if human GLUT9 can benefit from this advancement through subsequent structural based targeting and mutagenesis. Little progress has been made toward understanding the mechanism of GLUT9 since its discovery in 2000. Before work can begin on resolving the mechanisms of urate transport we must determine methods to express, purify and analyze hGLUT9 using a model system adept in expressing human membrane proteins. Here, we describe the surface expression, purification and isolation of monomeric protein, and functional analysis of recombinant hGLUT9 using the Xenopus laevis oocyte system. In addition, we generated a new homology-based high-resolution model of hGLUT9 from the XylE crystal structure and utilized our purified protein to generate a low-resolution single particle reconstruction. Interestingly, we demonstrate that the functional protein extracted from the Xenopus system fits well with the homology-based model allowing us to generate the predicted urate-binding pocket and pave a path for subsequent mutagenesis and structure-function studies.
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While most previous research has considered public service motivation (PSM) as the only motivational factor predicting (public) job choice, the authors present a novel, rational choice-based model which includes three motivational dimensions: extrinsic, enjoyment-based intrinsic and prosocial intrinsic. Besides providing more accurate person-job fit predictions, this new approach fills a significant research gap and facilitates future theory building.
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Facilitation is a major force shaping the structure and diversity of plant communities in terrestrial ecosystems. Detecting positive plant–plant interactions relies on the combination of field experimentation and the demonstration of spatial association between neighboring plants. This has often restricted the study of facilitation to particular sites, limiting the development of systematic assessments of facilitation over regional and global scales. Here we explore whether the frequency of plant spatial associations detected from high-resolution remotely sensed images can be used to infer plant facilitation at the community level in drylands around the globe. We correlated the information from remotely sensed images freely available through Google Earth with detailed field assessments, and used a simple individual-based model to generate patch-size distributions using different assumptions about the type and strength of plant–plant interactions. Most of the patterns found from the remotely sensed images were more right skewed than the patterns from the null model simulating a random distribution. This suggests that the plants in the studied drylands show stronger spatial clustering than expected by chance. We found that positive plant co-occurrence, as measured in the field, was significantly related to the skewness of vegetation patch-size distribution measured using Google Earth images. Our findings suggest that the relative frequency of facilitation may be inferred from spatial pattern signals measured from remotely sensed images, since facilitation often determines positive co-occurrence among neighboring plants. They pave the road for a systematic global assessment of the role of facilitation in terrestrial ecosystems. Read More: http://www.esajournals.org/doi/10.1890/14-2358.1
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BACKGROUND AND AIMS Hepatitis C (HCV) is a leading cause of morbidity and mortality in people who live with HIV. In many countries, access to direct acting antiviral agents to treat HCV is restricted to individuals with advanced liver disease (METAVIR stage F3 or F4). Our goal was to estimate the long term impact of deferring HCV treatment for men who have sex with men (MSM) who are coinfected with HIV and often have multiple risk factors for liver disease progression. METHODS We developed an individual-based model of liver disease progression in HIV/HCV coinfected men who have sex with men. We estimated liver-related morbidity and mortality as well as the median time spent with replicating HCV infection when individuals were treated in liver fibrosis stages F0, F1, F2, F3 or F4 on the METAVIR scale. RESULTS The percentage of individuals who died of liver-related complications was 2% if treatment was initiated in F0 or F1. It increased to 3% if treatment was deferred until F2, 7% if it was deferred until F3 and 22% if deferred until F4. The median time individuals spent with replicating HCV increased from 5 years if treatment was initiated in F2 to almost 15 years if it was deferred until F4. CONCLUSIONS Deferring HCV therapy until advanced liver fibrosis is established could increase liver-related morbidity and mortality in HIV/HCV coinfected individuals, and substantially prolong the time individuals spend with replicating HCV infection.
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Microarray technology is a high-throughput method for genotyping and gene expression profiling. Limited sensitivity and specificity are one of the essential problems for this technology. Most of existing methods of microarray data analysis have an apparent limitation for they merely deal with the numerical part of microarray data and have made little use of gene sequence information. Because it's the gene sequences that precisely define the physical objects being measured by a microarray, it is natural to make the gene sequences an essential part of the data analysis. This dissertation focused on the development of free energy models to integrate sequence information in microarray data analysis. The models were used to characterize the mechanism of hybridization on microarrays and enhance sensitivity and specificity of microarray measurements. ^ Cross-hybridization is a major obstacle factor for the sensitivity and specificity of microarray measurements. In this dissertation, we evaluated the scope of cross-hybridization problem on short-oligo microarrays. The results showed that cross hybridization on arrays is mostly caused by oligo fragments with a run of 10 to 16 nucleotides complementary to the probes. Furthermore, a free-energy based model was proposed to quantify the amount of cross-hybridization signal on each probe. This model treats cross-hybridization as an integral effect of the interactions between a probe and various off-target oligo fragments. Using public spike-in datasets, the model showed high accuracy in predicting the cross-hybridization signals on those probes whose intended targets are absent in the sample. ^ Several prospective models were proposed to improve Positional Dependent Nearest-Neighbor (PDNN) model for better quantification of gene expression and cross-hybridization. ^ The problem addressed in this dissertation is fundamental to the microarray technology. We expect that this study will help us to understand the detailed mechanism that determines sensitivity and specificity on the microarrays. Consequently, this research will have a wide impact on how microarrays are designed and how the data are interpreted. ^
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The growth patterns of weight from birth through the first twelve months of life among rural Taiwanese infants were investigated with the following objectives: (i) compare each of the parameters of the Count model estimated for infants who were nutritionally at risk with those for a reference population from the United States; and (ii) within the Taiwanese infants, account for the variance in the growth patterns in the first and second six months of life on the basis of selected ecological factors.^ The significance between group differences were observed in the patterns of the weight growth in both linear growth and in the timing and the direction of velocity changes. A significant decline in growth velocity was observed among Taiwanese infants at about the fourth month of life. The decline is in keeping with a recent proposal made by J. C. Waterlow regarding the timing of change in growth velocity among nutritionally at risk populations in developing countries. The growth course of a nutritionally at risk infant during the first three months is apparently protected by the nurturance of the mother and innate biological properties of the infant.^ A highly significant portion of the growth variance in the second six months of life was accounted for by exogenous factors and biological factors related to the infant. Conversely, none of the growth variance in the first six months of life was accounted for by predictor variables. The most potent determinant of growth in the second six months of life was seasonality which represents a multiple environmental event.^ The model parameters estimated from the Count model represent different aspect of physical growth; yet the correlation coefficients between parameters b and c are high (r > .80). Clearly, the biological interpretation of the model parameters requires analysis of the whole function in the specific context of a given age period. ^
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Measurement of the absorbed dose from ionizing radiation in medical applications is an essential component to providing safe and reproducible patient care. There are a wide variety of tools available for measuring radiation dose; this work focuses on the characterization of two common, solid-state dosimeters in medical applications: thermoluminescent dosimeters (TLD) and optically stimulated luminescent dosimeters (OSLD). There were two main objectives to this work. The first objective was to evaluate the energy dependence of TLD and OSLD for non-reference measurement conditions in a radiotherapy environment. The second objective was to fully characterize the OSLD nanoDot in a CT environment, and to provide validated calibration procedures for CT dose measurement using OSLD. Current protocols for dose measurement using TLD and OSLD generally assume a constant photon energy spectrum within a nominal beam energy regardless of measurement location, tissue composition, or changes in beam parameters. Variations in the energy spectrum of therapeutic photon beams may impact the response of TLD and OSLD and could thereby result in an incorrect measure of dose unless these differences are accounted for. In this work, we used a Monte Carlo based model to simulate variations in the photon energy spectra of a Varian 6MV beam; then evaluated the impact of the perturbations in energy spectra on the response of both TLD and OSLD using Burlin Cavity Theory. Energy response correction factors were determined for a range of conditions and compared to measured correction factors with good agreement. When using OSLD for dose measurement in a diagnostic imaging environment, photon energy spectra are often referenced to a therapy-energy or orthovoltage photon beam – commonly 250kVp, Co-60, or even 6MV, where the spectra are substantially different. Appropriate calibration techniques specifically for the OSLD nanoDot in a CT environment have not been presented in the literature; furthermore the dependence of the energy response of the calibration energy has not been emphasized. The results of this work include detailed calibration procedures for CT dosimetry using OSLD, and a full characterization of this dosimetry system in a low-dose, low-energy setting.
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This study evaluated a modified home-based model of family preservation services, the long-term community case management model, as operationalized by a private child welfare agency that serves as the last resort for hard-to-serve families with children at severe risk of out-of-home placement. The evaluation used a One-Group Pretest-Posttest design with a modified time-series design to determine if the intervention would produce a change over time in the composite score of each family's Child Well-Being Scales (CWBS). A comparison of the mean CWBS scores of the 208 families and subsets of these families at the pretest and various posttests showed a statistically significant decrease in the CWBS scores, indicating decreased risk factors. The longer the duration of services, the greater the statistically significant risk reduction. The results support the conclusion that the families who participate in empowerment-oriented community case management, with the option to extend service duration to resolve or ameliorate chronic family problems, have experienced effective strengthening in family functioning.