Dynamic Models with Additive Specific Effects

The transport of dust particles in tokamak fusion devices is studied using computer simulations with the dust transport code, DUSTT. Recent developments in modelling with the DUSTT code are reported. The improved model of dust dynamics in edge plasmas takes into account several additional effects, including thermionic and secondary electron emission which affects dust charging and heating, dust grain size effect on thermal radiation, and the presence of impurities in the plasma. It is shown that thermionic emission leads to enhanced dust heating by the plasma that boosts destruction of dust particles. The zone structure of tokamak plasmas is introduced for a qualitative analysis of dust survivability conditions. It is shown that a dust particle can experience net deposition in relatively cold carbon-contaminated plasma regions. Trajectories of sample dust particles in the DIII-D tokamak are simulated and analysed using the zone plasma description. Statistical averaging over an ensemble of particle trajectories is used to obtain spatial distributions of dust characteristics in the edge plasma of tokamaks. It is shown that transport of dust in tokamaks can significantly enhance penetration of carbon impurities towards the core plasma.

The purpose of this study is to analyze the combined effects of storm surge and inland rainfall on the floodplain of a coastal bayou in the Houston area by using dynamic hydraulic modeling. Most existing floodplains in the Houston area are defined using only rainfall as an input into steady-state hydraulic models and do not consider the impact of hurricane-induced storm surge on the floodplain. HEC-RAS, a one-dimensional flow model, was run for both steady- and unsteady-states to analyze the additional effect storm surge has on the coastal floodplain. Storm surge and rainfall data from Hurricane Ike were utilized to run an unsteady hydraulic model on Horsepen Bayou near Galveston Bay. The dynamic model generated a good match between the modeled hydrograph and measured data in the watershed. Additionally, a timing sensitivity analysis was completed by shifting the timing of the storm surge both earlier and later in time. The dynamic model revealed that the timing of both rainfall and storm surge play a significant role in the magnitude of inland flooding.

An important challenge for conservation is a quantitative understanding of how multiple human stressors will interact to mitigate or exacerbate global environmental change at a community or ecosystem level. We explored the interaction effects of fishing, ocean warming, and ocean acidification over time on 60 functional groups of species in the southeastern Australian marine ecosystem. We tracked changes in relative biomass within a coupled dynamic whole-ecosystem modeling framework that included the biophysical system, human effects, socioeconomics, and management evaluation. We estimated the individual, additive, and interactive effects on the ecosystem and for five community groups (top predators, fishes, benthic invertebrates, plankton, and primary producers). We calculated the size and direction of interaction effects with an additive null model and interpreted results as synergistic (amplified stress), additive (no additional stress), or antagonistic (reduced stress). Individually, only ocean acidification had a negative effect on total biomass. Fishing and ocean warming and ocean warming with ocean acidification had an additive effect on biomass. Adding fishing to ocean warming and ocean acidification significantly changed the direction and magnitude of the interaction effect to a synergistic response on biomass. The interaction effect depended on the response level examined (ecosystem vs. community). For communities, the size, direction, and type of interaction effect varied depending on the combination of stressors. Top predator and fish biomass had a synergistic response to the interaction of all three stressors, whereas biomass of benthic invertebrates responded antagonistically. With our approach, we were able to identify the regional effects of fishing on the size and direction of the interacting effects of ocean warming and ocean acidification.

This paper presents a dynamic core loss model for active loss control of permanent magnet synchronous machines. Deadbeat-direct torque and flux control (DB-DTFC) enables direct control of torque and stator flux linkage over each switching period. Total machine loss can be minimized by selecting the optimal flux level in every sampled time instant. Reliable models for dynamic copper and core loss are an essential requirement for this optimizing task. This paper presents an analytical dynamic core loss model in switching period time-domain, using stator flux linkage as the manipulated input variable. Combining numerical and analytical calculation methods is used to create an easy and practical approach to estimate core loss components based on stator flux linkage without running FEA calculations for every time instant. Additional effects like high frequency eddy current loss in electrically conducting permanent magnets as well as spatial harmonic content are taken into account.

The ‘Dynamic’ Marriage Between Varicella and Zoster

Accurate models for clusters of interacting bubbles are sought for both biomedical and underwater applications. Multiple bubble models have been developed by treating the bubbles as a system of interacting oscillators. The models are obtained initially for bubbles in an incompressible, irrotational, and inviscid liquid; additional effects are included in an ad hoc fashion. The existing oscillator models for the dynamics of interacting bubbles are improved by including the effect of liquid compressibility. In particular, while existing models have been improved by including propagation delays in the bubble interactions, the effect of bubble interaction on radiation damping has not been considered. The current work develops corrections for the radiation damping of coupled bubbles in both linear and nonlinear models of bubble dynamics. These corrections eliminate certain instabilities that have been observed in delay differential equation models of coupled-bubble dynamics. Additionally, an increase in the coupling strength between bubbles undergoing high-amplitude radial motion is predicted when coupled radiation damping is included; this increase in coupling strength strongly affects the predicted motion of the system and the resultant pressure in the surrounding medium. [Work supported by the ARL:UT McKinney Fellowship in Acoustics and NIH DK070618.]

The interactive effects of length and stimulus frequency on rise and fall times and on sag were investigated in fast-twitch feline caudofemoralis at normal body temperature. The length and stimulus frequency ranges studied were 0.8 1.2 L0 and 15 60 pps. Isometric rise times were shortest under two sets of conditions: short lengths + low stimulus frequencies and long lengths + high stimulus frequencies. In contrast the isometric fall time relationship showed a single minimum at short lengths + low stimulus frequencies. Velocity was shown to have an additional effect on fall time, but only at higher stimulus frequencies (40 60 pps): fall times were shorter during movement in either direction as compared to isometric. The effects of sag were greatest at shorter lengths and lower stimulus frequencies during isometric stimulus trains. Potential mechanisms underlying this last effect were investigated by comparing isometric twitches elicited prior to and immediately following a sag-inducing stimulus train. Post-sag twitches produced less force, reached peak force earlier and initially decayed more quickly compared to pre-sag twitches. However, the final rate of force decay and the initial rate of force rise (during the first 15 ms) were unaffected by sag. We construct a logical argument based on these findings to hypothesize that the predominant mechanism underlying sag is an increase in the rate of sarcoplasmic calcium ion removal. All of the above findings were used to construct a model of activation dynamics for fast-twitch muscle, which was then extrapolated to slow-twitch muscle. When coupled with a previous model of kinematic dynamics, the complete model produced accurate predictions of the forces actually recorded during experiments in which we applied concurrent dynamic changes in length. velocity and stimulus frequency.

Abstract. This study investigates the impacts of land cover change, as simulated by a dynamic vegetation model, on the summertime climatology over Asia. The climate model used in this study has systematic biases of underestimated rainfall around Korea and overestimation over the South China Sea. When coupled to a dynamic vegetation model, the resulting change in land cover is accompanied by an additional direct radiative effect over dust-producing regions. Both the change in land surface conditions directly and the effect of increased bare-soil fraction on dust loading affect the climate in the region and are examined separately in this study. The direct radiative effect of the additional dust contributes to increasing the rainfall biases, while the land surface physical processes are related to local temperature biases such as warm biases over North China. In time slice runs for future climate, as the dust loading changes, anomalous anticyclonic flows are simulated over South China Sea, resulting in reduced rainfall over the South China Sea and more rainfall near Korea and south China. In contrast with the rainfall changes, the influence of land cover change and the associated dust radiative effects are very small for a future projection of temperature, which is dominated by atmospheric CO2 increase. The results in this study suggest that the land cover simulated by a dynamic vegetation model can affect, and be affected by, model systematic biases on regional scales over dust emission source regions such as Asia. In particular, the analysis of the radiative effects of dust changes associated with land cover change is important in order to understand future changes in regional precipitation in global warming.

Risky business: The combined effects of fishing and changes in primary productivity on fish communities

This contribution focuses on a dynamic energy model of a refrigerated warehouse, which is used in conjunction with a counterpart model of a liquid-air energy storage (LAES) system. These coupled models represent a newly designed LAES pilot plant, which is to be integrated with an existing refrigerated warehouse in Belgium. The designed pilot plant stores excess renewable energy in periods of high availability and generates electricity in periods of high demand. Evaporating liquid air employed for power generation is also utilized to directly refrigerate the warehouse. Along with the usual energy storage benefits, the additional effect is reduced refrigeration demand of the warehouse and improved round-trip efficiency of the LAES system. The developed model serves to predict the temperature of the refrigerating air in the warehouse, as an important control variable for the integrated LAES-warehouse system.

A set of analyses using a multiple-trait model (model 1) and dynamic models for the evaluation of beef cattle growth is presented. All models contained additive direct and maternal environmental effects, as well as contemporary groups as nuisance parameters. The predictive ability of models at different parts of the growth trajectory was compared. Body weight records of 6,856 Nelore animals taken at 6 different ages (birth to 540 d) were used. Different models embedding a Kalman filter (KF) into a mixed model representation were fitted. Model 2 assumed that additive, maternal, and residual effects changed over time according to a linear autoregressive process. Model 3 was similar to model 2, but all regression coefficients were set to 1. In model 4, KF was applied only to direct genetic and maternal environmental effects. A leave-one-out cross-validation check was used to assess the predictive ability of models. Estimates of additive variance were similar in the analysis with models 1, 3, and 4 for all ages. Posterior means of maternal components increased slightly after birth and decreased after 135 d of age. Posterior means of additive rates of change were close to 1 at almost all time points, irrespective of the model. The posterior means of residual rates of change, which varied from 0.096 to 0.529, did not support the restrictions that regression coefficients were equal to 1 imposed by model 3. Estimates of additive and maternal correlations obtained with dynamic models were larger than those from a multivariate model. Model 3 produced different phenotypic correlations. Models 2 and 4 had better predictive ability than the multivariate specification. Model 3 predicted the data very poorly, and errors increased markedly with age. The KF can be a useful tool for structuring (co)variance matrices without reducing dimensionality. This model provided accurate predictions and plausible estimates of (co)variance components. Moreover, KF is a flexible specification, because a multivariate structure can be used for some random effects, whereas a dynamic feature can be incorporated for others.

Graph drawing is one of the imperative techniques for understanding biological regulations in a cell or among cells at the pathway level. Dynamic modeling and simulation of signaling pathways is a fundamental issue in systems biology and has growing attention from researchers with experimental or theoretical background. Here is an attempt to develop a reliable method for the analysis and modeling of specific signaling pathways contributing for the endotoxin clearance. Here, integration of proteins in signaling pathways was analyzed, which enables the understanding of complex cellular processes. In pathway drawing, location information is essential for its comprehension. However, complex shapes need to be taken into account when torus-shaped location information such as nuclear inner membrane, nuclear outer membrane, and plasma membrane is considered. Schwartz introduced the notion of crosstalk, referring to the case that two inputs work through distinct signaling pathways but cooperate to regulate cell signaling. In disquiet to that current study hypothesized at adopting electronic circuit block diagrams for the analysis of pathways contribute for endotoxin neutralization, by developing a logical circuit models and simulate using Very High Speed Integrated Circuit Hardware Description Language (VHDL), here mathematical models are developed as a viaduct between pathway model and circuit model. This method is reliable since it helps calculating the flux at each node. The method establishes that the multiple signaling pathways do not have the additive effect but the signals will cancel at the converging points. The established method can be applied for any network modeling and calculation of signal flux from different nodes to nucleus, degree of error depends on pathway modeling since it is a manual process errors in modeling can reflect on method reliability.

Intensive loblolly pine (Pinus taeda L.) plantation management in the southeastern United States includes mid-rotation silvicultural practices (MRSP) like thinning, fertilization, competitive vegetation control, and their combinations. Consistent and well-designed long-term studies considering interactions of MRSP are required to produce accurate projections and evaluate management decisions. Here we use longitudinal data from the regional Mid-Rotation Treatment study established by the Plantation Management Research Cooperative (PMRC) at the University of Georgia across the southeast U.S. to fit and validate a new dynamic model system rooted in theoretical and biological principles. A Weibull pdf was used as a modifier function coupled with the basal area growth model. The growth model system and error projection functions were estimated simultaneously. The new formulation results in a compatible and consistent growth and yield system and provides temporal responses to treatment. The results indicated that the model projections reproduce the observed behavior of stand characteristics. The model has high predictive accuracy (the cross-validation variance explained was 96.2%, 99.7%, and 98.6%; and the prediction root mean square distance was 0.704 m, 19.1 trees ha−1, and 1.03 m2ha−1 for dominant height (DH), trees per hectare (N), and basal area (BA), respectively), and can be used to project the current stand attributes following combinations of MRSP and with different thinning intensities. Simulations across southern physiographic regions allow us to conclude that the most overall ranking of MRSP after thinning is fertilization + competitive vegetation control (Fert + CVC) > fertilization only (Fert) > competitive vegetation control only (CVC), and Fert + CVC show less than additive effect. Because of the model structure, the response to treatment changes with location, age of application, and dominant height growth as indicators of site quality. Therefore, the proposed model adequately represents regional growth conditions.

Low phosphorus availability regulates root hair growth in Arabidopsis by (1) increasing root hair length, (2) increasing root hair density, (3) decreasing the distance between the root tip and the point at which root hairs begin to emerge, and (4) increasing the number of epidermal cell files that bear hairs (trichoblasts). The coordinated regulation of these traits by phosphorus availability prompted us to speculate that they are synergistic, that is, that they have greater adaptive value in combination than they do in isolation. In this study, we explored this concept using a geometric model to evaluate the effect of varying root hair length (short, medium, and long), density (0, 24, 48, 72, 96, and 120 root hairs per mm of root length), tip to first root hair distance (0.5, 1, 2, and 4 mm), and number of trichoblast files (8 vs. 12) on phosphorus acquisition efficiency (PAE) in Arabidopsis. SimRoot, a dynamic threedimensional geometric model of root growth and architecture, was used to simulate the growth of Arabidopsis roots with contrasting root hair parameters at three values of phosphorus diffusion coefficient (De=1×10 −7 ,1 ×10 −8 , and 1×10 −9 cm 2 s −1 ) over time (20, 40, and 60 h). Depzone, a program that dynamically models nutrient diffusion to roots, was employed to estimate PAE and competition among root hairs. As De decreased from 1×10 −7 to 1×10 −9 cm 2 s −1 , roots with longer root hairs and higher root hair densities had greater PAE than those with shorter and less dense root hairs. At De=1×10 −9 cm 2 s −1 , the PAE of root hairs at any given density was in the order of long hairs > medium length hairs > short hairs, and the maximum PAE occurred at density = 96 hairs mm −1 for both long and medium length hairs. This was due to greater competition among root hairs when they were short and dense. Competition over time decreased differences in PAE due to density, but the effect of length was maintained, as there was less competition among long hairs than short hairs. At high De(1×10 −7 cm 2 s −1 ), competition among root hairs was greatest among long hairs and lowest among short hairs, and competition increased with increasing root hair densities. This led to a decrease in PAE as root hair length and density increased. PAE was also affected by the tip to first root hair distance. At low De values, decreasing tip to first root hair distance increased PAE of long hairs more than that of short hairs, whereas at high De values, decreasing tip to first root hair distance increased PAE of root hairs at low density but decreased PAE of long hairs at very high density. Our models confirmed the benefits of increasing root hair density by increasing the number of trichoblast files rather than decreasing the trichoblast length. The combined effects of all four root hair traits on phosphorus acquisition was 371% greater than their additive effects, demonstrating substantial morphological synergy. In conclusion, our data support the hypothesis that the responses of root hairs to low phosphorus availability are synergistic, which may account for their coordinated regulation.

We present a new dynamic dominant height growth model based on Cieszewski’s generalized algebraic difference approach (GADA) advanced dynamic site equation strengthened by the use of explicit climate and soil variables (i.e., H = f(H0,T0, T, site conditions)). The results suggest that the inclusion of climatic variables would improve the applicability of the inter-regional model in regions in which climate and soil type lead to intra-regional variability. The new model reduces the bias present in a previous dynamic model that did not include climatic attributes and improves the model efficiency across the different age classes. Climate has a multiplicative effect on dominant tree growth in the early development stages (<20 years) and an additive effect in older stands.