Monte Carlo studies of helicity modulus and heat capacity of a coupled XY model in two dimensions.
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Journal Article↗
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Results for “Coupled model”
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A predictive model of fatigue in human skeletal muscles.
Fatigue is a major limitation to the clinical application of functional electrical stimulation. The activation pattern used during electrical stimulation affects force and fatigue. Identifying the activation pattern that produces the greatest force and least fatigue for each patient is, therefore, of great importance. Mathematical models that predict muscle forces and fatigue produced by a wide range of stimulation patterns would facilitate the search for optimal patterns. Previously, we developed a mathematical isometric force model that successfully identified the stimulation patterns that produced the greatest forces from healthy subjects under nonfatigue and fatigue conditions. The present study introduces a four-parameter fatigue model, coupled with the force model that predicts the fatigue induced by different stimulation patterns on different days during isometric contractions. This fatigue model accounted for 90% of the variability in forces produced by different fatigue tests. The predicted forces at the end of fatigue testing differed from those observed by only 9%. This model demonstrates the potential for predicting muscle fatigue in response to a wide range of stimulation patterns.
Electric Stimulation↗
[Coupling cardiovascular models for analysis of frequency-adaptive cardiac pacemaker systems].
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Computer Simulation↗
Alpha rhythm emerges from large-scale networks of realistically coupled multicompartmental model cortical neurons.
Conical pyramidal and stellate neurons were simulated using the GENESIS simulation package. Model neurons were leaky integrate-and-fire and consisted of from four to nine passive compartments. Neurophysiological measurements, based on single-cell recordings and patch-clamp experiments, provided estimations for the simulation of cortical neurons: transmitter-activated conductances, passive membrane time constants and axonal delays. Network connectivity was generated using a previously described probabilistic scheme based on known cortical histology, in which the probability of connections forming between one neuron and another fell off monotonically with increasing inter-cellular separation. Simulations of up to 6400 cortical neurons, approaching the scale of an individual cortical column, confirmed previous findings with smaller networks. Limit-cycle behaviour emerged in the network, in the frequency in the range of the mammalian alpha and beta rhythms (8-20 Hz). Contrary to expectation, near-linear relationships were found between the mean soma membrane potential and and neuronal firing probability. Some of the implications for cortical information processing, in particular the dynamical interactions between the neuronal and larger scales, are discussed.
Alpha Rhythm↗
Intervenability: another measure of health risk. By coupling predictive modeling with evidence-based medicine, health plans can identify patients who will benefit the most from care management intervention.
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Decision Support Systems, Clinical↗
The magnetic susceptibility of cytochrome oxidase in the 4.2-1.5 K range.
Sixteen low temperature measurements on eight independent cytochrome oxidase samples from two separate laboratories have yielded magnetic susceptibility data compatible with a model of spin-coupled iron and copper ions, as presented in the preceding paper (Tweedle, M.F., Wilson, L.J., García-Iñiguez, L., Babcock, G. T., and Palmer, G. (1978) J. Biol. Chem. 253, 8065-8071). The data in the 1.5-77 K range match those attained at higher temperatures and the predictions of the spin-coupled model. Measurements on reduced samples confirm the high spin nature of one iron atom. No obvious uncoupling of the antiferromagnetic Fe-Cu interaction is detected in partly reduced samples.
Copper↗
Impacts of lindane usage in the Canadian prairies on the Great Lakes ecosystem. 1. Coupled atmospheric transport model and modeled concentrations in air and soil.
A coupled atmospheric transport, soil-air, water-air exchange model was developed to investigate the impacts of gamma-hexachlorocyclohexane (gamma-HCH or lindane) usage in the Canadian prairies over the Great Lakes region. The fate of gamma-HCH in air and soil is governed by atmospheric dynamics and physical and chemical processes that are described by the coupled model. These processes include transport and turbulent diffusion in the atmosphere, dry and wet deposition, exchange at the interfacial boundaries of air-water and soil-air, and removal processes from the soil such as diffusion, leaching, and degradation. Numerical experiments were conducted for the period of May 1, 1998-April 30, 1999, starting with application of lindane in the spring. The coupled model was executed with two lindane emission (usage) inventories in the model domain. The first scenario contained all known fresh emission sources in Canada-98% was usage in the prairies; the second excluded emission sources from Ontario and Quebec. The model showed that, in the absence of the reemission from past application of lindane, usage of lindane in Ontario and Quebec has a negligible impact on air concentrations in these regions and that the lindane budget in the Great Lakes ecosystem is mostly attributed to applications of lindane in the canola fields in Canadian prairie provinces. Model-predicted air concentrations and seasonal trends agreed well with measured data over the same time period for several background sites operated under the Integrated Atmospheric Deposition Network. Air temperature was shown to play a key role on surface-air exchange dynamics of gamma-HCH. A future paper will assess loadings to the Great Lakes based on these validated model results.
Air Movements↗
Inspiratory timing during anaesthesia: a model of cardioventilatory coupling.
We describe a simple model of cardioventilatory coupling in which a hypothetical inspiratory pacemaker is stimulated by a signal related to cardiac action. At suitable values for the control variables (cardiac signal magnitude, heart rate, inspiratory pacemaker rate and inspiratory rate variability), the model was found to: (1) replicate all clinically described patterns of coupling; (2) predict variations in these described patterns and new patterns which were subsequently found in clinical time series; (3) simulate variations in clinically observed breathing frequency variations associated with each coupling pattern; (4) simulate the clinically observed distribution of coupling patterns between heart rate and breathing frequency; (5) explain the invariability of coupling below a critical heart rate/breathing frequency ratio; and (6) simulate the changes in breathing frequency and transitions between coupling patterns from the heart rate time series of human subjects. Although cardioventilatory coupling causes complex breathing rate irregularities during anaesthesia, these are readily explained by three variables, heart rate, intrinsic breathing frequency, and the strength of their interaction. This simple model, along with clinical observations of cardioventilatory coupling may provide a useful non-invasive method to study the respiratory central pattern generator.
Anesthesia, General↗
Rhythmogenic effects of weak electrotonic coupling in neuronal models.
Strong gap-junctional coupling can synchronize the electrical oscillations of cells, but we show, in a theoretical model, that weak coupling can phase lock two cells 180 degrees out-of-phase. Antiphase oscillations can exist in parameter regimens where in-phase oscillations break down. Some consequences are (i) coupling two excitable cells leads to pacemaking, (ii) coupling two pacemaker cells leads to bursting, and (iii) coupling two bursters increases burst period. The latter shows that details of the fast spikes can affect macroscopic properties of the slow bursts. These effects hold in other models for bursting and may play a role in the collective behavior of cellular ensembles.
Animals↗
A naive Bayes model to predict coupling between seven transmembrane domain receptors and G-proteins.
MOTIVATION: An understanding of the coupling between a G-protein coupled receptor (GPCR) and a specific class of heterotrimeric GTP-binding proteins (G-proteins) is vital for further comprehending the function of the receptor within a cell. However, predicting G-protein coupling based on the amino acid sequence of a receptor has been a daunting task. While experimental data for G-protein coupling exist, published models that rely on sequence based prediction are few. In this study, we have developed a Naive Bayes model to successfully predict G-protein coupling specificity by training over 80 GPCRs with known coupling. Each intracellular domain of GPCRs was treated as a discrete random variable, conditionally independent of one another. In order to determine the conditional probability distributions of these variables, ClustalW-generated phylogenetic trees were used as an approximation for the clustering of the intracellular domain sequences. The sampling of an intracellular domain sequence was achieved by identifying the cluster containing the homologue with the highest sequence similarity. RESULTS: Out of 55 GPCRs validated, the model yielded a correct classification rate of 72%. Our model also predicted multiple G-protein coupling for most of the GPCRs in the validation set. The Bayesian approach in this work offers an alternative to the experimental approach in order to answer the biological problem of GPCR/G-protein coupling selectivity. AVAILABILITY: Academic users should send their request for the perl program for calculating likelihood probabilities at jack.cao@astrazeneca.com. SUPPLEMENTARY INFORMATION: The materials can be viewed at http://www.astrazeneca-montreal.com/AZRDM_info/supporting_info.pdf.
Algorithms↗
Dications of bis-triarylamino-[2.2]paracyclophanes: Evaluation of excited state couplings by GMH analysis.
In this paper, we present the absorption properties of a series of bis-triarylamino-[2.2]paracyclophane diradical dications. The localized pi-pi and the charge-transfer (CT) transitions of these dications are explained and analyzed by an exciton coupling model that also considers the photophysical properties of the "monomeric" triarylamine radical cations. Together with AM1-CISD-calculated transition moments, experimental transition moments and transition energies of the bis-triarylamine dications were used to calculate electronic couplings by a generalized Mulliken-Hush (GMH) approach. These couplings are a measure for interactions of the excited mixed-valence CT states. The modification of the diabatic states reveals similarities of the GMH three-level model and the exciton coupling model. Comparison of the two models shows that the transition moment between the excited mixed-valence states mu(ab) of the dimer equals the dipole moment difference Delta of the ground and the excited bridge state of the corresponding monomer.
Journal Article↗
Pulsed electron-electron double resonance on multinuclear metal clusters: assignment of spin projection factors based on the dipolar interaction.
The interaction between two paramagnetic metal centers, a [3Fe-4S](+) cluster and a [NiFe] center, is investigated in the hydrogenase from Desulfovibrio vulgaris Miyazaki F by pulsed ELDOR (electron-electron double resonance). The distance between the metal centers is known from X-ray crystallography. The experimental dipolar spin-spin interaction deviates from the value expected for two point-dipoles located at the centers of the metal clusters. An extended spin-coupling model accounting for the spin coupling in the [3Fe-4S](+) cluster yields the observed interaction under the assumption of a particular magnetic coupling scheme for the three Fe ions. These results demonstrate that pulsed ELDOR can be used to gain insight into the inner structure of a multinuclear metal cluster.
Computer Simulation↗
Trimeric G alpha beta gamma protein coupling to a 3D model of G protein-coupled receptors confirming a new molecular mechanism for activation.
The present-day model for G protein activation and the associated theory on how a G protein-coupled receptor may activate the G protein are summarized. Experimental data are outlined which seem not to be in accordance with this present-day model. An alternative molecular mechanism for ternary complex activation is presented together with a three-dimensional model for a receptor coupled to the appropriate trimeric G protein. This 3D structure confirms our new molecular mechanism of activation.
GTP-Binding Proteins↗
Dynamic analysis and geometry models for the design of bi-leaflet prosthetic mechanical heart valves.
This paper provides new geometry definitions for the axi-symmetric stiffening (or sewing) ring, as part of a bi-leaflet prosthetic heart valve, and presents a dynamic behaviour analysis of the leaflet. An optimal stiffening ring geometry may be constructed by considering the point of flow separation on the stiffening ring (measured in the downstream coordinate), the effective orifice area of the stiffening ring and the associated dynamic behaviour of the leaflet. The dynamic model is accomplished by utilizing a second-order rotating system to simulate the opening and closing characteristics of the leaflet. The moments due to the aerodynamic loads are evaluated from an irrotational inviscid flow model, coupled with boundary layer theory, modelling the internal flow phenomena of the bi-leaflet heart valve implanted in the aortic root. It has been shown that this internal flow model provides the correct evaluation of lift and induced drag and the subsequent dynamic characteristics.
Algorithms↗
A 3D hydrodynamic fate and transport model for herbicides in Sacca di Goro coastal lagoon (Northern Adriatic).
Sacca di Goro is a shallow coastal microtidal lagoon with a surface area of 26 km2, and an average depth of about 1.5m. Fresh water pollutant loads from Po River branches and several drainage canals lead to anthropogenic eutrophication, frequent summer anoxia crises and chemical contamination. Such events not only affect the lagoon ecosystem but also cause serious economic losses, the lagoon being the second largest producer of clams in Italy. The present work aims at using a fate model coupled with COHERENS 3D hydrodynamic model to simulate and to explain the spatial distribution and temporal variations of s-triazines herbicides in the Sacca di Goro lagoon. The simulation results of spatial and temporal dynamic behaviour of atrazine, simazine and terbuthylazine have been compared with experimental data obtained during an annual monitoring programme.
Animals↗
Use of temporal/seasonal- and size-dependent bioaerosol data to characterize the contribution of outdoor fungi to residential exposures.
With the use of published temporal/seasonal and particle size distribution of outdoor bioaerosol data and meteorological information in the subtropical climate, we characterized the airborne fungal concentration indoor/outdoor/personal exposure relationships in a wind-induced naturally ventilated residence. We applied a size-dependent indoor/outdoor ratio model coupled with a compartmental lung model based on a hygroscopic growth factor as a function of relative humidity on aerodynamic diameter and concentration of fungal spores. The higher indoor airborne fungal concentrations occurred in early morning and late afternoon in which median values were 699.29 and 626.20 CFU m(-3) in summer as well as 138.71 and 99.01 CFU m(-3) in winter, respectively, at 2 am and 8 pm. In the absence of indoor sources, summer has higher mean indoor/outdoor ratios of airborne fungal concentration (0.29-0.58) than that in winter (0.12-0.16). Lung region of extrathoracic (ET) has higher fungal concentration lung/indoor ratios (0.7-0.8) than that in bronchial (BB; 0.41-0.60), bronchiolar (bb; 0.12-0.40), and alveolar-interstitial (AI); 0.01-0.24) regions. The highest airborne fungal deposition dose (95th-percentile is 4600 CFU) occurred in 11 pm-5 am in region AI in that the 95th-percentile fungal deposition rate was 0.22 CFU s(-1).
Aerosols↗
Membrane rejection of nitrogen compounds.
Rejection characteristics of nitrogen compounds were examined for reverse osmosis, nanofiltration, and low-pressure reverse osmosis membranes. The rejection of nitrogen compounds is explained by integrating experimental results with calculations using the extended Nernst-Planck model coupled with a steric hindrance model. The molecular weight and chemical structure of nitrogen compounds appear to be less important in determining rejection than electrostatic properties. The rejection is greatest when the Donnan potential exceeds 0.05 V or when the ratio of the solute radius to the pore radius is greater than 0.8. The transport of solute in the pore is dominated by diffusion, although convective transport is significant for organic nitrogen compounds. Electromigration contributes negligibly to the overall solute transport in the membrane. Urea, a small organic compound, has lower rejection than ionic compounds such as ammonium, nitrate, and nitrite, indicating the critical role of electrostatic interaction in rejection. This suggests that better treatment efficiency for organic nitrogen compounds can be obtained after ammonification of urea.
Membranes, Artificial↗
Thermal physics in carbon nanotube growth kinetics.
The growth of single wall carbon nanotubes (SWNTs) mediated by metal nanoparticles is considered within (i) the surface diffusion growth kinetics model coupled with (ii) a thermal model taking into account heat release of carbon adsorption-desorption on nanotube surface and carbon incorporation into the nanotube wall and (iii) carbon nanotube-inert gas collisional heat exchange. Numerical simulations performed together with analytical estimates reveal various temperature regimes occurring during SWNT growth. During the initial stage, which is characterized by SWNT lengths that are shorter than the surface diffusion length of carbon atoms adsorbed on the SWNT wall, the SWNT temperature remains constant and is significantly higher than that of the ambient gas. After this stage the SWNT temperature decreases towards that of gas and becomes nonuniformly distributed over the length of the SWNT. The rate of SWNT cooling depends on the SWNT-gas collisional energy transfer that, from molecular dynamics simulations, is seen to be efficient only in the SWNT radial direction. The decreasing SWNT temperature may lead to solidification of the catalytic metal nanoparticle terminating SWNT growth or triggering nucleation of a new carbon layer and growth of multiwall carbon nanotubes.
Journal Article↗