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PubMed2006

Phenophases alter the soil respiration-temperature relationship in an oak-dominated forest.

Soil respiration (SR) represents a major component of forest ecosystem respiration and is influenced seasonally by environmental factors such as temperature, soil moisture, root respiration, and litter fall. Changes in these environmental factors correspond with shifts in plant phenology. In this study, we examined the relationship between canopy phenophases (pre-growth, growth, pre-dormancy, and dormancy) and SR sensitivity to changes in soil temperature (T(S)). SR was measured 53 times over 550 days within an oak forest in northwest Ohio, USA. Annual estimates of SR were calculated with a Q(10) model based on T(S) on a phenological (PT), or annual timescale (AT), or T(S) and soil volumetric water content (VWC) on a phenological (PTM) or annual (ATM) timescale. We found significant (p<0.01) difference in apparent Q(10) from year 2004 (1.23) and year 2005 (2.76) during the growth phenophase. Accounting for moisture-sensitivity increased model performance compared to temperature-only models: the error was -17% for the ATM model and -6% for the PTM model. The annual models consistently underestimated SR in summer and overestimated it in winter. These biases were reduced by delineating SR by tree phenophases and accounting for variation in soil moisture. Even though the bias of annual models in winter SR was small in absolute scale, the relative error was about 91%, and may thus have significant implications for regional and continental C balance estimates.

Models, Theoretical↗

PubMed2006

Modeling the effect of temperature on growth of Salmonella in chicken.

Growth data of Salmonella in chicken were collected at several isothermal conditions (10, 15, 20, 25, 28, 32, 35, 37, 42, and 45 degrees C) and were then fitted into primary models, namely the logistic model, modified Gompertz model and Baranyi model. Measures of goodness-of-fit such as mean square error, pseudo-R(2), -2 log likelihood, Akaike's information, and Sawa's Bayesian information criteria were used for comparison for these primary models. Based on these criteria, modified Gompertz model described growth data the best, followed by the Baranyi model, and then the logistic model. The maximum growth rates obtained from each primary model were then modeled as a function of temperature using the modified Ratkowsky model. Pseudo-R(2) values for this secondary model describing growth rate obtained from Baranyi, modified Gompertz, and logistic models were 0.999, 0.980, and 0.990, respectively. Mean square error values for corresponding models were 0.0002, 0.0008, and 0.0009, respectively. Both measures clearly show that the Baranyi model performed better than the modified Gompertz model or the logistic model.

Animals↗

PubMed2005

Equally valid models gave divergent predictions for mortality in acute myocardial infarction patients in a comparison of logistic [corrected] regression models.

OBJECTIVE: Models that predict mortality after acute myocardial infarction (AMI) contain different predictors and are based on different populations. We studied the agreement and validity of predictions for individual patients. STUDY DESIGN AND SETTING: We compared predictions from five predictive logistic regression models for short-term mortality after AMI. Three models were developed previously, and two models were developed in the GUSTO-I data, where all five models were applied (n =40,830, 7.0% 30-day mortality). Agreement was studied with weighted kappa statistics of categorized predictions. Validity was assessed by comparing observed frequencies with predictions (indicating calibration) and by the area under the receiver operating characteristic curve (AUC), indicating discriminative ability. RESULTS: The predictions from the five models varied considerably for individual patients, with low agreement between most (kappa <0.6). Risk predictions from the three previously developed models were on average too high, which could be corrected by re-calibration of the model intercept. The AUC ranged from 0.76-0.78 and increased to 0.78-0.79 with re-estimated regression coefficients that were optimal for the GUSTO-I patients. The two more detailed GUSTO-I based models performed better (AUC approximately 0.82). CONCLUSION: Models with different predictors may have a similar validity while the agreement between predictions for individual patients is poor. The main concerns in the applicability of predictive models for AMI should relate to the selected predictors and average calibration.

Aged↗

PubMed2002

Growth and yield functions for irrigated plantations of Eucalyptus camaldulensis in the hot desert of India.

Eucalyptus camaldulensis forms a major portion of irrigated plantations in the hot desert of India and for effective management of these plantations, growth and yield functions are necessary. This paper describes the development of height, diameter and volume growth functions based on the analysis of the data collected from the permanent sample plots laid out in the study area. The Chapman-Richards equation could be used for the prediction of diameter growth while the Schumacher model could be considered for predicting volume growth. Some base-age variant and invariant site-index models, already reported in the literature, were compared in terms of relative accuracy and it was found that the Payandeh and Wang model performed the best among the four models tried.

Biotechnology↗

PubMed2000

Evaluation of wind fields used in Grand Canyon Visibility Transport Commission analyses.

The Grand Canyon Visibility Transport Commission (GCVTC) was established by the U.S. Congress to assess the potential impacts of projected growth on atmospheric visibility at Grand Canyon National Park and to make recommendations to the U.S. Environmental Protection Agency on what measures could be taken to avoid such adverse impacts. A critical input to the assessment tool used by the commission was three-dimensional model-derived wind fields used to transport the emissions. This paper describes the evaluation of the wind fields used at various stages in the assessment. Wind fields evaluated included those obtained from the Colorado State University Regional Atmospheric Modeling System (RAMS), the National Meteorological Center's Nested Grid Model (NGM), and the National Oceanic and Atmospheric Administration's Atmospheric Transport and Dispersion (ATAD) trajectory model. The model-derived wind fields were evaluated at multiple vertical levels at several locations in the southwestern United States by determining differences between model predicted winds and winds that were measured using radiosonde and radar wind profiler data. Model-derived winds were also evaluated by determining the percent of time that they were within acceptable differences from measured winds. All models had difficulties, generally meeting the acceptable criteria for less than 50% of the predictions. The RAMS model had a persistent bias toward southwesterly winds at the expense of other directions, especially failing to represent channeling by north-south mountain ranges in the lower levels. The NGM model exhibited a substantial bias in the summer months by extending northwesterly winds in the eastern Pacific Ocean well inland, in contrast to the observed southwesterlies at inland locations. The simpler ATAD trajectory model performed somewhat better than the other models, probably because of its use of more upper air sites. The results of the evaluation indicated that these wind fields could not be used to reliably predict source-receptor impacts on a particular day; thus, seasonally averaged impacts were used in the GCVTC assessment.

Air Pollution↗

PubMed2005

Evaluation of multisectional and two-section particulate matter photochemical grid models in the Western United States.

Version 4.10s of the comprehensive air-quality model with extensions (CAMx) photochemical grid model has been developed, which includes two options for representing particulate matter (PM) size distribution: (1) a two-section representation that consists of fine (PM2.5) and coarse (PM2.5-10) modes that has no interactions between the sections and assumes all of the secondary PM is fine; and (2) a multisectional representation that divides the PM size distribution into N sections (e.g., N = 10) and simulates the mass transfer between sections because of coagulation, accumulation, evaporation, and other processes. The model was applied to Southern California using the two-section and multisection representation of PM size distribution, and we found that allowing secondary PM to grow into the coarse mode had a substantial effect on PM concentration estimates. CAMx was then applied to the Western United States for the 1996 annual period with a 36-km grid resolution using both the two-section and multisection PM representation. The Community Multiscale Air Quality (CMAQ) and Regional Modeling for Aerosol and Deposition (REMSAD) models were also applied to the 1996 annual period. Similar model performance was exhibited by the four models across the Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network monitoring networks. All four of the models exhibited fairly low annual bias for secondary PM sulfate and nitrate but with a winter overestimation and summer underestimation bias. The CAMx multisectional model estimated that coarse mode secondary sulfate and nitrate typically contribute <10% of the total sulfate and nitrate when averaged across the more rural IMPROVE monitoring network.

Air Pollutants, Occupational↗

PubMed2006

An application of exposure modeling in exposure assessments for a university chemistry teaching laboratory.

Chemical exposures in a university teaching lab were assessed using a tiered approach to modeling. Zero ventilation and well mixed room models estimated air concentrations of ethyl ether, n-hexane, and methylene chloride during distillation and extraction exercises. A simple, zero ventilation model determined that health risks from the ethyl ether exercise were minimum. N-hexane and methylene chloride exposures were evaluated with higher tiered, well mixed room models. An assumption that all of the solvent evaporated during the lab resulted in estimated n-hexane concentrations well below the occupational exposure limit. Methylene chloride concentration estimates using this approach were only one-half the occupational exposure limit, so the model was refined using information on the actual amount of solvent that evaporated. This resulted in a concentration estimate approximately one-fifth of the occupational exposure limit. Air sampling was done to evaluate model performance. Measured concentrations were higher than modeled concentrations by up to a factor of two but were still below applicable occupational exposure limits. The exposure models selected were deemed useful in the assessment of exposure acceptability in these labs.

Air Pollution, Indoor↗

PubMed2005

Rice morphogenesis and plant architecture: measurement, specification and the reconstruction of structural development by 3D architectural modelling.

BACKGROUND AND AIMS: The morphogenesis and architecture of a rice plant, Oryza sativa, are critical factors in the yield equation, but they are not well studied because of the lack of appropriate tools for 3D measurement. The architecture of rice plants is characterized by a large number of tillers and leaves. The aims of this study were to specify rice plant architecture and to find appropriate functions to represent the 3D growth across all growth stages. METHODS: A japonica type rice, 'Namaga', was grown in pots under outdoor conditions. A 3D digitizer was used to measure the rice plant structure at intervals from the young seedling stage to maturity. The L-system formalism was applied to create '3D virtual rice' plants, incorporating models of phenological development and leaf emergence period as a function of temperature and photoperiod, which were used to determine the timing of tiller emergence. KEY RESULTS: The relationships between the nodal positions and leaf lengths, leaf angles and tiller angles were analysed and used to determine growth functions for the models. The '3D virtual rice' reproduces the structural development of isolated plants and provides a good estimation of the tillering process, and of the accumulation of leaves. CONCLUSIONS: The results indicated that the '3D virtual rice' has a possibility to demonstrate the differences in the structure and development between cultivars and under different environmental conditions. Future work, necessary to reflect both cultivar and environmental effects on the model performance, and to link with physiological models, is proposed in the discussion.

Computer Simulation↗

PubMed1990

Simulation of mechanisms of viral interference in influenza.

Biological interference among viral agents might have significant implications for disease prevention and therapy. Field data for influenza yield conflicting evidence concerning the independence of infection rates, or disease severity, for two co-circulating viruses. To examine the effects of several assumed modes of interference for influenza, simulations of a Monte Carlo micropopulation model of influenza epidemics have been performed. Model parameters were selected so that the simulated attack rates for each of two different viral strains matched actual field data. Rates of infection were compared for single agents and for two viruses with only behavioural interference. Other simulations included temporary immunity to the other virus for the duration of the infection, and/or reduced shedding of viral particles for dual infections. Simulated viral competition had little impact on epidemic severity, duration, or size distribution. Under the conditions studied, viral interference in natural populations would be difficult to infer from field observations of attack rates. Other simulations extended a partial immunity and/or reduced viral shedding during an infection with a second virus. These indicated that interference might be suggested by field data, but it could not be demonstrated conclusively. Still other simulations showed that for epidemics with much higher attack rates for both viruses, it would be relatively easy to demonstrate interference. However, in order to observe interference between influenza strains, it would be necessary to monitor on an almost daily basis, using a method of viral detection which would have to be both highly specific and also very sensitive.

Adolescent↗

PubMed2004

Infrared target detection with probability density functions of wavelet transform subbands.

We report the development of a wavelet multiresolution texture-based algorithm that uses the probability density functions (PDFs) of the subband of the wavelet decomposition of an image. The moments of these pdfs are used in a clustering algorithm to segment the targets from their background clutter. Using the tools of experimental methodology, we evaluate the performance of this algorithm on real infrared imagery under varying algorithm parameter sets as well as scene, image, and false-alarm conditions. We estimate a set of multidimensional predictive analytic performance models that relate the detection probabilities as functions of false alarm, algorithm internal parameter, target pixel number, target-to-background interference ratio, target-interference ratio, and Fechner-Weber and local entropy metrics in the scene. These models can be used to predict performance in regions were no data are available and to optimize performance by selection of the optimum parameter and constant false-alarm values in regions with known scene and metric conditions.

Journal Article↗

PubMed2001

Laparoscopic intracorporeally constructed ileal conduit after porcine cystoprostatectomy.

PURPOSE: We present our technique of laparoscopic ileal conduit creation after cystoprostatectomy in a porcine model performed in a completely intracorporeal manner. METHODS AND METHODS: After developing the technique in 5 acute animals laparoscopic cystoprostatectomy with intracorporeally performed ileal conduit urinary diversion was performed in 10 surviving male pigs. A 5-port transperitoneal technique was used. All steps of the technique applied during open surgery were duplicated intracorporeally. Specifically cystectomy, isolation of an ileal conduit, restoration of bowel continuity and mucosa-to-mucosa stented bilateral ileoureteral anastomosis formation were performed by exclusively intracorporeal laparoscopic techniques. RESULTS: Surgery was successful in all 10 study animals without intraoperative or immediate postoperative complications. Blood loss was minimal and average operative time was 200 minutes. Stenosis of the end ileal stoma specifically at the skin level was noted in 6 animals. Three deaths occurred 2 to 3 weeks postoperatively. At sacrifice renal function was normal in all surviving animals. No ileo-ureteral anastomotic strictures were noted on pre-sacrifice radiography of the loop or at autopsy examination of the anastomotic sites. CONCLUSIONS: Laparoscopic ileal conduit urinary diversion after cystoprostatectomy may be performed completely intracorporeally in the porcine model. Clinical application of this technique is imminent.

Animals↗

PubMed2005

Test equating in the presence of DIF items.

This paper proposes a multilevel measurement model that controls for DIF effects in test equating. The accuracy and stability of item and ability parameter estimates under the proposed multilevel measurement model were examined using randomly simulated data. Estimates from the proposed model were compared with those resulting from two multiple-group concurrent equating designs, including 1) a design that replaced DIF-items with items with no DIF; and 2) a design that retained DIF items with no attempt to control for DIF. In most of the investigated conditions, the results indicated that the proposed multilevel measurement model performed better than the two comparison models.

Educational Measurement↗

PubMed1991

Computer simulations of chondrocytic clone behaviour in rabbit growth plates.

The growth behaviour of chondrocytic clones in the cell columns of the proximal tibial growth plates of young rabbits was modelled in computer simulations. Simulations were performed, modelling either clones in large groups of columns or clones in one single column. The former were based on morphological data and measurements of cell columns from an earlier study while the latter utilised previous findings of cellular kinetics in rabbit growth plates. Simulation results that resembled most closely the actual observations on rabbit growth plates were those in which a distribution of values was assumed both for clone length (ranging from 1000 to 2000 microns) and for the lengths of the discontinuities between clones. When the assumption was made in the models that the disappearing (metaphyseal) end of an 'old' clone moved more rapidly than the developing (epiphyseal) end of a 'new' clone, replacing the former, the length of the discontinuity between these two clones increased with time. This assumption, which could be modelled in the simulations of clones in a single column based on cell growth behaviour, was found to provide an explanation for an earlier finding that there are more short columns at the epiphyseal side than at the metaphyseal side of a growth plate.

Animals↗

PubMed2001

Modeling functions of striatal dopamine modulation in learning and planning.

The activity of midbrain dopamine neurons is strikingly similar to the reward prediction error of temporal difference reinforcement learning models. Experimental evidence and simulation studies suggest that dopamine neuron activity serves as an effective reinforcement signal for learning of sensorimotor associations in striatal matrisomes. In the current study, we simulate dopamine neuron activity with the extended temporal difference model of Pavlovian learning and examine the influences of this signal on medium spiny neurons in striatal matrisomes. The modeled influences include transient membrane effects of dopamine D(1) receptor activation, dopamine-dependent long-term adaptations of corticostriatal transmission, and effects of dopamine on rhythmic fluctuations of the membrane potential between an elevated "up-state" and a hyperpolarized "down-state". The most dominant activity in the striatal matrisomes is assumed to elicit behaviors via projections from the basal ganglia to the thalamus and the cortex. This "standard model" performs successfully when tested for sensorimotor learning and goal-directed behavior (planning). To investigate the contributions of our model assumptions to learning and planning, we test the performance of several model variants that lack one of these mechanisms. These simulations show that the adaptation of the dopamine-like signal is necessary for sensorimotor learning and planning. Sensorimotor learning requires dopamine-dependent long-term adaptation of corticostriatal transmission. Lack of dopamine-like novelty responses decreases the number of exploratory acts, which impairs planning capabilities. The model loses its planning capabilities if the dopamine-like signal is simulated with the original temporal difference model, because the original temporal difference model does not form novel associative chains. Transient membrane effects of the dopamine-like signal on striatal firing substantially shorten the reaction time in the planning task. The capability for planning is improved by influences of dopamine on the durations of membrane potential fluctuations and by manipulations that prolong the reaction time of the model. These results suggest that responses of dopamine neurons to conditioned stimuli contribute to sensorimotor reward learning, novelty responses of dopamine neurons stimulate exploration, and transient dopamine membrane effects are important for planning.

Animals↗

PubMed2002

Coupled microstrip line transverse electromagnetic resonator model for high-field magnetic resonance imaging.

The performance modeling of RF resonators at high magnetic fields of 4.7 T and more requires a physical approach that goes beyond conventional lumped circuit concepts. The treatment of voltages and currents as variables in time and space leads to a coupled transmission line model, whereby the electric and magnetic fields are assumed static in planes orthogonal to the length of the resonator, but wave-like along its longitudinal axis. In this work a multiconductor transmission line (MTL) model is developed and successfully applied to analyze a 12-element unloaded and loaded microstrip line transverse electromagnetic (TEM) resonator coil for animal studies. The loading involves a homogeneous cylindrical dielectric insert of variable radius and length. This model formulation is capable of estimating the resonance spectrum, field distributions, and certain types of losses in the coil, while requiring only modest computational resources. The boundary element method is adopted to compute all relevant transmission line parameters needed to set up the transmission line matrices. Both the theoretical basis and its engineering implementation are discussed and the resulting model predictions are placed in context with measurements. A comparison between a conventional lumped circuit model and this distributed formulation is conducted, showing significant departures in the resonance response at higher frequencies. This MTL model is applied to simulate two small-bore animal systems: one of 7.5-cm inner diameter, tuned to 200 MHz (4.7 T for proton imaging), and one of 13.36-cm inner diameter, tuned to both 200 and 300 MHz (7 T).

Animals↗

PubMed2005

Using stochastic differential equations for PK/PD model development.

A method for PK/PD model development based on stochastic differential equation models is proposed. The new method has a number of advantages compared to conventional methods. In particular, the new method avoids the exhaustive trial-and-error based search often conducted to determine the most appropriate model structure, because it allows information about the appropriate model structure to be extracted directly from data. This is accomplished through quantification of the uncertainty of the individual parts of an initial model, by means of which tools for performing model diagnostics can be constructed and guidelines for model improvement provided. Furthermore, the new method allows time-variations in key parameters to be tracked and visualized graphically, which allows important functional relationships to be revealed. Using simulated data, the performance of the new method is demonstrated by means of two examples. The first example shows how, starting from a simple assumption of linear PK, the method can be used to determine the correct nonlinear model for describing the PK of a drug following an oral dose. The second example shows how, starting from a simple assumption of no drug effect, the method can be used to determine the correct model for the nonlinear effect of a drug with known PK in an indirect response model.

Algorithms↗

PubMed2004

Alternative methods for modeling fatigue and performance.

The use of nonparametric approaches and semiparametric approaches for modeling fatigue and performance are analyzed. Nonparametric approaches in the form of stand-alone artificial neural networks and semiparametric (hybrid) approaches that combine neural networks with prior process knowledge are explored and compared with existing parametric approaches based on the two-process model of sleep regulation. Within the context of a military application, we explore two notional semiparametric approaches for real-time prediction of cognitive performance on the basis of individualized on-line measurements of physiologic variables. Initial analysis indicates that these alternative modeling approaches may address key technological gaps and advance fatigue and performance modeling. Most notably, these approaches seem amenable to predicting individual performance and quantitatively assessing the reliability of model predictions through estimation of statistical error bounds, which have eluded researchers for the last two decades.

Fatigue↗

PubMed2006

Adding sequence context to a Markov background model improves the identification of regulatory elements.

MOTIVATION: Many computational methods for identifying regulatory elements use a likelihood ratio between motif and background models. Often, the methods use a background model of independent bases. At least two different Markov background models have been proposed with the aim of increasing the accuracy of predicting regulatory elements. Both Markov background models suffer theoretical drawbacks, so this article develops a third, context-dependent Markov background model from fundamental statistical principles. RESULTS: Datasets containing known regulatory elements in eukaryotes provided a basis for comparing the predictive accuracies of the different background models. Non-parametric statistical tests indicated that Markov models of order 3 constituted a statistically significant improvement over the background model of independent bases. Our model performed slightly better than the previous Markov background models. We also found that for discriminating between the predictive accuracies of competing background models, the correlation coefficient is a more sensitive measure than the performance coefficient. AVAILABILITY: Our C++ program is available at ftp://ftp.ncbi.nih.gov/pub/spouge/papers/archive/AGLAM/2006-07-19

Algorithms↗