Stochastic structure and individual-tree growth models

The majority of past and current individual-tree growth modelling methodologies have failed to characterise and incorporate structured stochastic components. Rather, they have relied on deterministic predictions or have added an unstructured random component to predictions. In particular, spatial stochastic structure has been neglected, despite being present in most applications of individual-tree growth models. Spatial stochastic structure (also called spatial dependence or spatial autocorrelation) eventuates when spatial influences such as competition and micro-site effects are not fully captured in models. Temporal stochastic structure (also called temporal dependence or temporal autocorrelation) eventuates when a sequence of measurements is taken on an individual-tree over time, and variables explaining temporal variation in these measurements are not included in the model. Nested stochastic structure eventuates when measurements are combined across sampling units and differences among the sampling units are not fully captured in the model. This review examines spatial, temporal, and nested stochastic structure and instances where each has been characterised in the forest biometry and statistical literature. Methodologies for incorporating stochastic structure in growth model estimation and prediction are described. Benefits from incorporation of stochastic structure include valid statistical inference, improved estimation efficiency, and more realistic and theoretically sound predictions. It is proposed in this review that individual-tree modelling methodologies need to characterise and include structured stochasticity. Possibilities for future research are discussed. (C) 2001 Elsevier Science B.V. All rights reserved.

Diffusion- and perfusion-weighted MRI response to thrombolysis in stroke

Diffusion- and perfusion-weighted magnetic resonance imaging provides important pathophysiological information in acute bra-in ischemia. We performed a prospective study in 19 sub-6-hour stroke patients using serial diffusion- and perfusion-weighted imaging before intravenous thrombolysis, with repeat studies, both subacutely and at outcome. For comparison of ischemic lesion evolution and clinical outcome, we used a historical control group of 21 sub-6-hour ischemic stroke patients studied serially with diffusion- and perfusion-weighted imaging. The two groups were well matched for the baseline National Institutes of Health Stroke Scale and magnetic resonance parameters. Perfusion-weighted imaging-diffusion-weighted imaging mismatch was present in 16 of 19 patients treated with tissue plasminogen activator, and 16 of 21 controls. Perfusion-weighted imaging-diffusion-weighted imaging mismatch patients treated with tissue plaminogen activator had higher recanalization rates and enhanced reperfusion at day 3 (81% vs 47% in controls), and a greater proportion of severely hypoperfused acute mismatch tissue not progressing to infarction (82% vs -25% in controls). Despite similar baseline diffusion-weighted imaging lesions, infarct expansion was less in the recombinant tissue plaminogen activator group (14cm(3) vs 56cm(3) in controls). The positive effect of thrombolysis on lesion growth in mismatch patients translated into a greater improvement in baseline to outcome National Institutes of Health Stroke Scale in the group treated with recombinant tissue plaminogen activator, and a significantly larger proportion of patients treated with recombinant tissue plaminogen activator having a clinically meaningful improvement in National Institutes of Health Stroke Scale of;2:7 points. The natural evolution of acute perfusion-weighted imaging-diffusion-weighted imaging mismatch tissue may be altered by thrombolysis, with improved stroke outcome. This has implications for the use of diffusion- and perfusion-weighted imaging in selecting and monitoring patients for thrombolytic therapy.

Large mitochondrial repeats multiplied during the polymerase chain reaction

The number of repeats in repetitive DNA like micro- and minisatellites is often determined by polymerase chain reaction (PCR). When we counted repeats in an array of mitochondrial repeats in the cattle tick (Boophilus microplus) we found that the number of repeats increased during PCR. Multiplication of the repeats was independent of the primers used to amplify the region, the PCR annealing temperature and the length of the PCR product. The use of PCR to determine the number of repeats in arrays needs to be reassessed. For long repeats, a subset of samples should always be analysed by Southern blot hybridization to confirm the PCR results.

General properties of cosmological models with an isotropic singularity

Much of the published work regarding the Isotropic Singularity is performed under the assumption that the matter source for the cosmological model is a barotropic perfect fluid, or even a perfect fluid with a gamma-law equation of state. There are, however, some general properties of cosmological models which admit an Isotropic Singularity, irrespective of the matter source. In particular, we show that the Isotropic Singularity is a point-like singularity and that vacuum space-times cannot admit an Isotropic Singularity. The relationships between the Isotropic Singularity, and the energy conditions, and the Hubble parameter is explored. A review of work by the authors, regarding the Isotropic Singularity, is presented.

Algebraic Bethe ansatz for integrable one-dimensional extended Hubbard models with open boundary conditions

Nine classes of integrable open boundary conditions, further extending the one-dimensional U-q (gl (212)) extended Hubbard model, have been constructed previously by means of the boundary Z(2)-graded quantum inverse scattering method. The boundary systems are now solved by using the algebraic Bethe ansatz method, and the Bethe ansatz equations are obtained for all nine cases.

Prediction of carbon monoxide in fires by conditional moment closure

Carbon monoxide is the chief killer in fires. Dangerous levels of CO can occur when reacting combustion gases are quenched by heat transfer, or by mixing of the fire plume in a cooled under- or overventilated upper layer. In this paper, carbon monoxide predictions for enclosure fires are modeled by the conditional moment closure (CMC) method and are compared with laboratory data. The modeled fire situation is a buoyant, turbulent, diffusion flame burning under a hood. The fire plume entrains fresh air, and the postflame gases are cooled considerably under the hood by conduction and radiation, emulating conditions which occur in enclosure fires and lead to the freezing of CO burnout. Predictions of CO in the cooled layer are presented in the context of a complete computational fluid dynamics solution of velocity, temperature, and major species concentrations. A range of underhood equivalence ratios, from rich to lean, are investigated. The CMC method predicts CO in very good agreement with data. In particular, CMC is able to correctly predict CO concentrations in lean cooled gases, showing its capability in conditions where reaction rates change considerably.

Discriminating between task-relevant and task-irrelevant stimuli - The effects on autonomic orienting and secondary task reaction time

The effect that the difficulty of the discrimination between task-relevant and task-irrelevant stimuli has on the relationship between skin conductance orienting and secondary task reaction time (RT) was examined. Participants (N = 72) counted the number of longer-than-usual presentations of one shape (task-relevant) and ignored presentations of another shape (task-irrelevant). The difficulty of discriminating between the two shapes varied across three groups (low, medium, and high difficulty). Simultaneous with the primary counting task, participants performed a secondary RT task to acoustic probes presented 50, 150, and 2000 ms following shape onset. Skin conductance orienting was larger, and secondary RT at the 2000 ms probe position was slower during task-relevant shapes than during task-irrelevant shapes in the low-difficulty group. This difference declined as the discrimination difficulty was increased, such that there was no difference in the high-difficulty group. Secondary RT was slower during task-irrelevant shapes than during task-relevant shapes only in the medium-difficulty group-and only at the 150 ms probe position in the first half of the experiment. The close relationship between autonomic orienting and secondary RT at the 2000 ms probe position suggests that orienting reflects the resource allocation that results from the number of matching features between a stimulus input and a mental representation primed as significant.

Oxidation of toluene in waste gas streams using mesoporous Ti-hexagonal mesoporous silica

Various mesoporous catalysts with titanium loadings between 0.5 and 4 Ti wt. % and surface areas between 600 and 1,600 m(2)/g were synthesized using the molecular designed dispersion technique. These catalysts were tested using toluene oxidation in a fixed bed reactor at temperatures between 300 and 550degreesC. The reaction products were found to be CO2 and CO with selectivity towards CO2 above 80% for all catalysts. The catalytic activity of the catalysts increases with titanium loading. The total conversion at 550degreesC was not affected by the textural porosity, but increased textural porosity did significantly reduce the ignition temperature by up to 50degreesC. The Thiele modulus was calculated to be much less than one for all these materials indicating that the reaction rate is not diffusion, limited.

A new graphic format to facilitate the understanding of technological innovation models: the seesaw of competitiveness

Many models exist in the literature to explain the success of technological innovation. However, no studies have been made regarding graphic formats representing the technological innovation models and their impact, or on the understanding of these models by non-specialists in technology management. Thus, the main objective of this paper is to propose a new graphic configuration to represent the technological innovation management. Based on the literature, the innovation model is presented in the traditional format. Next, the same model is designed in the graphic format - named `the see-saw of competitiveness` - showing the interfaces among the identified factors. The two graphic formats were compared by a group of graduate students in terms of the ease in understanding the conceptual model of innovation. The statistical analysis shows that the seesaw of competitiveness is preferred.

Ecosystem process models at multiple scales for mapping tropical forest productivity

Quantifying mass and energy exchanges within tropical forests is essential for understanding their role in the global carbon budget and how they will respond to perturbations in climate. This study reviews ecosystem process models designed to predict the growth and productivity of temperate and tropical forest ecosystems. Temperate forest models were included because of the minimal number of tropical forest models. The review provides a multiscale assessment enabling potential users to select a model suited to the scale and type of information they require in tropical forests. Process models are reviewed in relation to their input and output parameters, minimum spatial and temporal units of operation, maximum spatial extent and time period of application for each organization level of modelling. Organizational levels included leaf-tree, plot-stand, regional and ecosystem levels, with model complexity decreasing as the time-step and spatial extent of model operation increases. All ecosystem models are simplified versions of reality and are typically aspatial. Remotely sensed data sets and derived products may be used to initialize, drive and validate ecosystem process models. At the simplest level, remotely sensed data are used to delimit location, extent and changes over time of vegetation communities. At a more advanced level, remotely sensed data products have been used to estimate key structural and biophysical properties associated with ecosystem processes in tropical and temperate forests. Combining ecological models and image data enables the development of carbon accounting systems that will contribute to understanding greenhouse gas budgets at biome and global scales.

Valuing water resources in developing countries: A semiparametric approach to valuation models

Valuation of projects for the preservation of water resources provides important information to policy makers and funding institutions. Standard contingent valuation models rely on distributional assumptions to provide welfare measures. Deviations from assumed and actual distribution of benefits are important when designing policies in developing countries, where inequality is a concern. This article applies semiparametric methods to obtain estimates of the benefit from a project for the preservation of an important Brazilian river basin. These estimates lead to significant differences from those obtained using the standard parametric approach.

Use of bulk density profiles from X-radiography to examine structural crust models

Exponential and sigmoidal functions have been suggested to describe the bulk density profiles of crusts. The present work aims to evaluate these conceptual models using high resolution X-radiography. Repacked seedbeds from two soil materials, air-dried or prewetted by capillary rise, were subjected to simulated rain, which resulted in three types of structural crusts, namely, slaking, infilling, and coalescing. Bulk density distributions with depth were generated using high-resolution (70 mum), calibrated X-ray images of slices from the resin-impregnated crusted seedbeds. The bulk density decreased progressively with depth, which supports the suggestion that a crust should be considered as a nonuniform layer. For the slaking and the coalescing crusts, the exponential function underestimated the strong change in bulk density across the morphologically defined transition between the crust and the underlying material; the sigmoidal function provided a better description. Neither of these crust models effectively described the shape of the bulk density profiles through the whole seedbed. Below the infilling and slaking crusts, bulk density increased linearly with depth as a result of slumping. In the coalescing crusted seedbed, the whole seedbed uniformly collapsed and most of the bulk density change within the crust could be ascribed to slumping (0.33 g cm(-3)) rather than to crusting (0.12 g cm(-3)). Finally, (i) X-radiography appears as a unique tool to generate high resolution bulk density profiles and (ii) in structural crusts, bulk density profiles could be modeled using the existing exponential and sigmoidal crusting models, provided a slumping model would be coupled.