The research on Virtual Plants Growth Based on DLA Model
NASA Astrophysics Data System (ADS)
Zou, YunLan; Chai, Bencheng
This article summarizes the separated Evolutionary Algorithm in fractal algorithm of Diffusion Limited Aggregation model (i.e. DLA model) and put forward the virtual plant growth realization in computer based on DLA model. The method is carried out in the VB6.0 environment to achieve and verify the plant growth based on DLA model.
Modeling solute transport by DLA in soils of northeastern Egypt.
Hamed, Yasser Ahmed; Yasuda, Hiroshi; Persson, Magnus; Berndtsson, Ronny; Wang, Xin-ping
2015-01-01
Arid soils in Egypt display large variability in solute transport properties, causing problems in soil management. To characterize this variability, dye infiltration experiments were conducted on four plots representing three main soil types in northeastern Egypt. The plots represented both cultivated and uncultivated land use. The observed dye patterns displayed a large variability and especially the clay soils indicated a high degree of preferential flow. The loamy sand and sandy soils displayed a more uniform dye distribution indicating more homogeneous soil properties. The observed dye patterns were modeled using a diffusion limited aggregation (DLA) model. The DLA is a random walk model where model parameters can be optimized using genetic algorithms (GA). The DLA model reproduced the observed dye patterns for all soils in an excellent way. The best fit was obtained with a specific combination of directional random walk probabilities Pu, Pd, Pr, and Pl for each plot (correlation 0.97-0.99). To account for soil layers with different hydraulic properties a two layer DLA model was developed. For all plots the Pu (upward random walk probability) was higher for the upper more homogeneous soil layer. The overall results showed that spatial variability resulting from solute transport for the investigated soils can be modeled using a DLA approach. PMID:25790463
Modeling Solute Transport by DLA in Soils of Northeastern Egypt
Hamed, Yasser Ahmed; Yasuda, Hiroshi; Persson, Magnus; Berndtsson, Ronny; Wang, Xin-ping
2015-01-01
Arid soils in Egypt display large variability in solute transport properties, causing problems in soil management. To characterize this variability, dye infiltration experiments were conducted on four plots representing three main soil types in northeastern Egypt. The plots represented both cultivated and uncultivated land use. The observed dye patterns displayed a large variability and especially the clay soils indicated a high degree of preferential flow. The loamy sand and sandy soils displayed a more uniform dye distribution indicating more homogeneous soil properties. The observed dye patterns were modeled using a diffusion limited aggregation (DLA) model. The DLA is a random walk model where model parameters can be optimized using genetic algorithms (GA). The DLA model reproduced the observed dye patterns for all soils in an excellent way. The best fit was obtained with a specific combination of directional random walk probabilities Pu, Pd, Pr, and Pl for each plot (correlation 0.97–0.99). To account for soil layers with different hydraulic properties a two layer DLA model was developed. For all plots the Pu (upward random walk probability) was higher for the upper more homogeneous soil layer. The overall results showed that spatial variability resulting from solute transport for the investigated soils can be modeled using a DLA approach. PMID:25790463
Conformal approach to cylindrical DLA
NASA Astrophysics Data System (ADS)
Taloni, A.; Caglioti, E.; Loreto, V.; Pietronero, L.
2006-09-01
We extend the conformal mapping approach elaborated for the radial diffusion limited aggregation model (DLA) to cylindrical geometry. We introduce in particular a complex function which allows a cylindrical cluster to be grown using as an intermediate step a radial aggregate. The aggregate grown exhibits the same self-affine features as the original cylindrical DLA. The specific choice of the transformation allows us to study the relationship between the radial and the cylindrical geometry. In particular the cylindrical aggregate can be seen as a radial aggregate with particles of size increasing with the radius. On the other hand, the radial aggregate can be seen as a cylindrical aggregate with particles of size decreasing with the height. This framework, which shifts the point of view from the geometry to the size of the particles, can open the way to more quantitative studies on the relationship between radial and cylindrical DLA.
Finite size effect of harmonic measure estimation in a DLA model: Variable size of probe particles
NASA Astrophysics Data System (ADS)
Menshutin, Anton Yu.; Shchur, Lev N.; Vinokour, Valery M.
2008-11-01
A finite size effect in the probing of the harmonic measure in simulation of diffusion-limited aggregation (DLA) growth is investigated. We introduce a variable size of probe particles, to estimate harmonic measure and extract the fractal dimension of DLA clusters taking two limits, of vanishingly small probe particle size and of infinitely large size of a DLA cluster. We generate 1000 DLA clusters consisting of 50 million particles each, using an off-lattice killing-free algorithm developed in the early work. The introduced method leads to unprecedented accuracy in the estimation of the fractal dimension. We discuss the variation of the probability distribution function with the size of probing particles.
Electrochemical Growth of Ag Junctions and Diffusion Limited Aggregate (DLA) Fractal Simulation
NASA Astrophysics Data System (ADS)
Olson, Zak; Tuppan, Sam; Kim, Woo-Joong; Seattle University Team
2015-03-01
We attempt construction of a single atom connection between two copper wires. By applying a DC voltage across the wires when immersed in a silver nitrate solution, we deposit silver until a junction is formed. The deposited silver forms a fractal structure that can be simulated with a diffusion limited aggregation model.
Diffusion Limited Aggregation: Algorithm optimization revisited
NASA Astrophysics Data System (ADS)
Braga, F. L.; Ribeiro, M. S.
2011-08-01
The Diffusion Limited Aggregation (DLA) model developed by Witten and Sander in 1978 is useful in modeling a large class of growth phenomena with local dependence. Besides its simplicity this aggregation model has a complex behavior that can be observed at the patterns generated. We propose on this work a brief review of some important proprieties of this model and present an algorithm to simulate a DLA aggregates that simpler and efficient compared to others found in the literature.
Modeling realistic breast lesions using diffusion limited aggregation
NASA Astrophysics Data System (ADS)
Rashidnasab, Alaleh; Elangovan, Premkumar; Dance, David R.; Young, Kenneth C.; Diaz, Oliver; Wells, Kevin
2012-03-01
Synthesizing the appearance of malignant masses and inserting these into digital mammograms can be used as part of a wider framework for investigating the radiological detection task in X-ray mammography. However, the randomness associated with cell division within cancerous masses and the associated complex morphology challenges the realism of the modeling process. In this paper, Diffusion Limited Aggregation (DLA), a type of fractal growth process is proposed and utilized for modeling breast lesions. Masses of different sizes, shapes and densities were grown by controlling DLA growth parameters either prior to growth, or dynamically updating these during growth. A validation study was conducted by presenting 30 real and 30 simulated masses in a random order to a team of radiologists. The results from the validation study suggest that the observers found it difficult to differentiate between the real and simulated lesions.
Scaling in the Diffusion Limited Aggregation Model
NASA Astrophysics Data System (ADS)
Menshutin, Anton
2012-01-01
We present a self-consistent picture of diffusion limited aggregation (DLA) growth based on the assumption that the probability density P(r,N) for the next particle to be attached within the distance r to the center of the cluster is expressible in the scale-invariant form P[r/Rdep(N)]. It follows from this assumption that there is no multiscaling issue in DLA and there is only a single fractal dimension D for all length scales. We check our assumption self-consistently by calculating the particle-density distribution with a measured P(r/Rdep) function on an ensemble with 1000 clusters of 5×107 particles each. We also show that a nontrivial multiscaling function D(x) can be obtained only when small clusters (N<10000) are used to calculate D(x). Hence, multiscaling is a finite-size effect and is not intrinsic to DLA.
Abnormal Stability in Growth of Diffusion-Limited Aggregation
NASA Astrophysics Data System (ADS)
Ohta, Shonosuke
2009-01-01
An abnormal and unsteady growth of an isotropic cluster in diffusion-limited aggregation (DLA) is observed in stability analyses. Macroscopic fluctuation due to the delay of transition from a dendritic tip to a tip-splitting growth induces the anisotropy of DLA. An asymptotic deformation factor \\varepsilon∞ = 0.0888 is obtained from large DLA clusters. A symmetric oval model proposed from the dual-stability growth of DLA gives an asymptotic fractal dimension of 1.7112 using \\varepsilon∞. The correspondence of this model to the box dimension is excellent.
Scaling in the diffusion limited aggregation model.
Menshutin, Anton
2012-01-01
We present a self-consistent picture of diffusion limited aggregation (DLA) growth based on the assumption that the probability density P(r,N) for the next particle to be attached within the distance r to the center of the cluster is expressible in the scale-invariant form P[r/R{dep}(N)]. It follows from this assumption that there is no multiscaling issue in DLA and there is only a single fractal dimension D for all length scales. We check our assumption self-consistently by calculating the particle-density distribution with a measured P(r/R{dep}) function on an ensemble with 1000 clusters of 5×10{7} particles each. We also show that a nontrivial multiscaling function D(x) can be obtained only when small clusters (N<10 000) are used to calculate D(x). Hence, multiscaling is a finite-size effect and is not intrinsic to DLA. PMID:22304265
Mean-field diffusion-limited aggregation: a "density" model for viscous fingering phenomena.
Bogoyavlenskiy, V A
2001-12-01
We explore a universal "density" formalism to describe nonequilibrium growth processes, specifically, the immiscible viscous fingering in Hele-Shaw cells (usually referred to as the Saffman-Taylor problem). For that we develop an alternative approach to the viscous fingering phenomena, whose basic concepts have been recently published in a Rapid Communication [Phys. Rev. E 63, 045305(R) (2001)]. This approach uses the diffusion-limited aggregation (DLA) paradigm as a core: we introduce a mean-field DLA generalization in stochastic and deterministic formulations. The stochastic model, a quasicontinuum DLA, simulates Monte Carlo patterns, which demonstrate a striking resemblance to natural Hele-Shaw fingers and, for steady-state growth regimes, follow precisely the Saffman-Taylor analytical solutions in channel and sector configurations. The relevant deterministic theory, a complete set of differential equations for a time development of density fields, is derived from that stochastic model. As a principal conclusion, we prove an asymptotic equivalency of both the stochastic and deterministic mean-field DLA formulations to the classic Saffman-Taylor hydrodynamics in terms of an interface evolution. PMID:11736272
A diffusion-limited aggregation model for the evolution of drainage networks
NASA Technical Reports Server (NTRS)
Masek, Jeffrey G.; Turcotte, Donald L.
1993-01-01
We propose a modified diffusion-limited aggregation (DLA) model for the evolution of fluvial drainage networks. Random walkers are introduced randomly on a grid, and each two-dimensional random walk proceeds until the walker finds a drainage network on which to accrete. This model for headward growth of drainage networks generates drainage patterns remarkably similar to actual drainages. The model also predicts statistical features which agree with actual networks, including the frequency-order (bifurcation) ratio (R(sub b) = 3.98) and the stream length-order (R(sub r) = 2.09). Using the definition of network fractal dimension D = log R(sub b)/log R(sub r), we find that our DLA model gives D = 1.87, near the observed range of D approximately equal to 1.80 - 1.85.
Model for amorphous aggregation processes
NASA Astrophysics Data System (ADS)
Stranks, Samuel D.; Ecroyd, Heath; van Sluyter, Steven; Waters, Elizabeth J.; Carver, John A.; von Smekal, Lorenz
2009-11-01
The amorphous aggregation of proteins is associated with many phenomena, ranging from the formation of protein wine haze to the development of cataract in the eye lens and the precipitation of recombinant proteins during their expression and purification. While much literature exists describing models for linear protein aggregation, such as amyloid fibril formation, there are few reports of models which address amorphous aggregation. Here, we propose a model to describe the amorphous aggregation of proteins which is also more widely applicable to other situations where a similar process occurs, such as in the formation of colloids and nanoclusters. As first applications of the model, we have tested it against experimental turbidimetry data of three proteins relevant to the wine industry and biochemistry, namely, thaumatin, a thaumatinlike protein, and α -lactalbumin. The model is very robust and describes amorphous experimental data to a high degree of accuracy. Details about the aggregation process, such as shape parameters of the aggregates and rate constants, can also be extracted.
Monosized aggregates -- A new model
Gopal, M.
1997-08-01
For applications requiring colloidal particles, it is desirable that they be monosized to better control the structure and the properties. In a number of systems, the monosized particles come together to form aggregates that are also monosized. A model is presented here to explain the formation of these monosized aggregates. This is of particular importance in the fields of ceramics, catalysis, pigments, pharmacy, photographic emulsions, etc.
Kinetic model for erythrocyte aggregation.
Bertoluzzo, S M; Bollini, A; Rasia, M; Raynal, A
1999-01-01
It is well known that light transmission through blood is the most widely utilized method for the study of erythrocyte aggregation. The curves obtained had been considered empirically as exponential functions. In consequence, the process becomes characterized by an only parameter that varies with all the process factors without discrimination. In the present paper a mathematical model for RBC aggregation process is deduced in accordance with von Smoluchowski's theory about the kinetics of colloidal particles agglomeration. The equation fitted the experimental pattern of the RBC suspension optical transmittance closely and contained two parameters that estimate the most important characteristics of the aggregation process separately, i.e., (1) average size of rouleaux at equilibrium and (2) aggregation rate. The evaluation of the method was assessed by some factors affecting erythrocyte aggregation, such as temperature, plasma dilutions, Dextran 500, Dextran 70 and PVP 360, at different media concentrations, cellular membrane alteration by the alkylating agent TCEA, and decrease of medium osmolarity. Results were interpreted considering the process characteristics estimated by the parameters, and there were also compared with similar studies carried out by other authors with other methods. This analysis allowed us to conclude that the equation proposed is reliable and useful to study erythrocyte aggregation. PMID:10660481
NASA Astrophysics Data System (ADS)
Braga, F. L.; Mattos, O. A.; Amorin, V. S.; Souza, A. B.
2015-07-01
Clusters formation models have been extensively studied in literature, and one of the main task of this research area is the analysis of the particle aggregation processes. Some work support that the main characteristics of this processes are strictly correlated to the cluster morphology, for example in DLA. It is expected that in the DLA clusters formation with particles containing different sizes the modification of the aggregation processes can be responsible for changes in the DLA morphology. The present article is going to analyze the formation of DLA clusters of particles with different sizes and show that the aggregates obtained by this approach generate an angle selection mechanism on dendritic growth that influences the shielding effect of the DLA edge and affect the fractal dimension of the clusters.
Average shape of transport-limited aggregates.
Davidovitch, Benny; Choi, Jaehyuk; Bazant, Martin Z
2005-08-12
We study the relation between stochastic and continuous transport-limited growth models. We derive a nonlinear integro-differential equation for the average shape of stochastic aggregates, whose mean-field approximation is the corresponding continuous equation. Focusing on the advection-diffusion-limited aggregation (ADLA) model, we show that the average shape of the stochastic growth is similar, but not identical, to the corresponding continuous dynamics. Similar results should apply to DLA, thus explaining the known discrepancies between average DLA shapes and viscous fingers in a channel geometry. PMID:16196793
Average Shape of Transport-Limited Aggregates
NASA Astrophysics Data System (ADS)
Davidovitch, Benny; Choi, Jaehyuk; Bazant, Martin Z.
2005-08-01
We study the relation between stochastic and continuous transport-limited growth models. We derive a nonlinear integro-differential equation for the average shape of stochastic aggregates, whose mean-field approximation is the corresponding continuous equation. Focusing on the advection-diffusion-limited aggregation (ADLA) model, we show that the average shape of the stochastic growth is similar, but not identical, to the corresponding continuous dynamics. Similar results should apply to DLA, thus explaining the known discrepancies between average DLA shapes and viscous fingers in a channel geometry.
Inhomogeneous diffusion-limited aggregation
NASA Technical Reports Server (NTRS)
Selinger, Robin Blumberg; Nittmann, Johann; Stanley, H. E.
1989-01-01
It is demonstrated here that inhomogeneous diffusion-limited aggregation (DLA) model can be used to simulate viscous fingering in a medium with inhomogeneous permeability and homogeneous porosity. The medium consists of a pipe-pore square-lattice network in which all pores have equal volume and the pipes have negligible volume. It is shown that fluctuations in a DLA-based growth process may be tuned by noise reduction, and that fluctuations in the velocity of the moving interface are multiplicative in form.
Model for the growth of electrodeposited ferromagnetic aggregates under an in-plane magnetic field.
Cronemberger, C; Sampaio, L C; Guimarães, A P; Molho, P
2010-02-01
The quasi-two-dimensional deposition of ferromagnetic materials by electrochemical process under the influence of a magnetic field applied in the plane of the growth leads to a surprising symmetry breaking in the dendritic structures found. The reasons for these features are still not completely understood. The original dense circular envelope becomes rectangular, as well as the sparse figures have their shapes elongated. This paper reports the results of a diffusion-limited aggregation (DLA) -like simulation. The model proposed here, a modification of the original DLA model, can deal with ferromagnetic particles under the influence of an electric field and the dipolar interactions between particles, submitted to an applied magnetic field in the plane of growth of such structures. The results were produced varying the applied magnetic field and the magnetic moment of the particles and show that the balance between these interactions is an important mechanisms that can be responsible for the changes in shape of the aggregates observed in the experiments. PMID:20365564
Model for the growth of electrodeposited ferromagnetic aggregates under an in-plane magnetic field
NASA Astrophysics Data System (ADS)
Cronemberger, C.; Sampaio, L. C.; Guimarães, A. P.; Molho, P.
2010-02-01
The quasi-two-dimensional deposition of ferromagnetic materials by electrochemical process under the influence of a magnetic field applied in the plane of the growth leads to a surprising symmetry breaking in the dendritic structures found. The reasons for these features are still not completely understood. The original dense circular envelope becomes rectangular, as well as the sparse figures have their shapes elongated. This paper reports the results of a diffusion-limited aggregation (DLA) -like simulation. The model proposed here, a modification of the original DLA model, can deal with ferromagnetic particles under the influence of an electric field and the dipolar interactions between particles, submitted to an applied magnetic field in the plane of growth of such structures. The results were produced varying the applied magnetic field and the magnetic moment of the particles and show that the balance between these interactions is an important mechanisms that can be responsible for the changes in shape of the aggregates observed in the experiments.
A Numerical Study for the Relationship between Natural Manganese Dendrites and DLA Patterns
NASA Astrophysics Data System (ADS)
Ozbey, Tugba; Bayirli, Mehmet
2016-03-01
The formation mechanisms and the origin of manganese dendrites on the magnesite ore have been under discussion. The growth process of the manganese dendrites is statistically studied by comparing them to aggregations obtained according to the diffusion limited aggregation (DLA) model via Monte Carlo simulations. In this case, ten manganese dendrite patterns changing from the least dense to the densest aggregations on the surface are separately selected to determine the relationship between real and simulated patterns. The sticking parameter is ranged from 0.05≤t≤1. The density-density correlation functions C(r) (their critical exponent A), fractal dimension Df, critical exponent α, and critical exponent β pertaining to the root mean square (rms) thickness have been computed for both the ten manganese dendrites and the simulated aggregations representing them. The results indicate that manganese dendrites may be determined with the general DLA model. Analyses of manganese dendrites, both scaling and simulations, suggest the growth mechanism for the macroscopic expression of crystalline anisotropy for the dendritic patterns. These results are in good agreement with the values in other literature and can be helpful in comparing natural and simulated aggregations (both dendritic and compact deposits).
Aggregate Models of Climate Change
NASA Astrophysics Data System (ADS)
Hooss, G.; Voss, R.; Hasselmann, K.; Maier-Reimer, E.; Joos, F.
Integrated assessment of climate change generally requires the evaluation of many transient scenario simulations of century-timescale changes in atmospheric compo- sition and climate, desirably with the accuracy of state-of-the-art three-dimensional (3D) coupled atmosphere-ocean general circulation models (GCMs). Such multi- scenario GCM computations are possible through appropriate representation of the models in aggregate forms. For this purpose, we developed Nonlinear Impulse- response projections of 3D models of the global (oceanic and terrestrial) Carbon cycle and the atmosphere-ocean Climate System (NICCS). For higher CO2 forcing, appli- cability is extended beyond the linear response domain through explicit treatment of dominant nonlinear effects. The climate change module was furthermore augmented with spatial patterns of change in some of the most impact-relevant fields. Applied to three long-term CO2 emission scenarios, the model demonstrates (a) the minor rela- tive role of the terrestrial carbon sink through CO2 fertilization, and (b) the necessity to reduce fossil carbon emissions to a very small fraction of today's rates within the next few decades if a major climate change is to be avoided.
Aggregation in ecosystem models and model stability
NASA Astrophysics Data System (ADS)
Giricheva, Evgeniya
2015-05-01
Using a multimodal approach to research ecosystems improves usage of available information on an object. This study presents several models of the Bering Sea ecosystem. The ecosystem is considered as a closed object, that is, the influence of the environment is not provided. We then add the links with the external medium in the models. The models differ in terms of the degree and method of grouping components. Our method is based on the differences in habitat and food source of groups, which allows us to determine the grouping of species with a greater effect on system dynamics. In particular, we determine whether benthic fish aggregation or pelagic fish aggregation can change the consumption structure of some groups of species, and consequently, the behavior of the entire model system.
Teaching Aggregate Demand and Supply Models
ERIC Educational Resources Information Center
Wells, Graeme
2010-01-01
The author analyzes the inflation-targeting model that underlies recent textbook expositions of the aggregate demand-aggregate supply approach used in introductory courses in macroeconomics. He shows how numerical simulations of a model with inflation inertia can be used as a tool to help students understand adjustments in response to demand and…
Exponential Clogging Time for a One Dimensional DLA
NASA Astrophysics Data System (ADS)
Benjamini, Itai; Hoffman, Christopher
2008-06-01
In this paper a simple DLA type model is analyzed. In (Benjamini and Yadin in Commun. Math. Phys. 279:187-223, [2008]) the standard DLA model from (Witten and Sander in Phys. Rev. B 27:5686-5697, [1983]) was considered on a cylinder and the arm growing phenomena was established, provided that the section of the cylinder has sufficiently fast mixing rate. When considering DLA on a cylinder it is natural to ask how many particles it takes to clog the cylinder, e.g. modeling clogging of arteries. In this note we formulate a very simple DLA clogging model and establish an exponential lower bound on the number of particles arriving before clogging appears. In particular we possibly shed some light on why it takes so long to reach the bypass operation.
A competitive aggregation model for flash nanoprecipitation.
Cheng, Janine Chungyin; Vigil, R D; Fox, R O
2010-11-15
Flash NanoPrecipitation (FNP) is a novel approach for producing functional nanoparticles stabilized by amphiphilic block copolymers. FNP involves the rapid mixing of a hydrophobic active (organic) and an amphiphilic di-block copolymer with a non-solvent (water) and subsequent co-precipitation of nanoparticles composed of both the organic and copolymer. During this process, the particle size distribution (PSD) is frozen and stabilized by the hydrophilic portion of the amphiphilic di-block copolymer residing on the particle surface. That is, the particle growth is kinetically arrested and thus a narrow PSD can be attained. To model the co-precipitation process, a bivariate population balance equation (PBE) has been formulated to account for the competitive aggregation of the organic and copolymer versus pure organic-organic or copolymer-copolymer aggregation. Aggregation rate kernels have been derived to account for the major aggregation events: free coupling, unimer insertion, and aggregate fusion. The resulting PBE is solved both by direct integration and by using the conditional quadrature method of moments (CQMOM). By solving the competitive aggregation model under well-mixed conditions, it is demonstrated that the PSD is controlled primarily by the copolymer-copolymer aggregation process and that the energy barrier to aggregate fusion plays a key role in determining the PSD. It is also shown that the characteristic aggregation times are smaller than the turbulent mixing time so that the FNP process is always mixing limited. PMID:20800847
Attracted diffusion-limited aggregation.
Rahbari, S H Ebrahimnazhad; Saberi, A A
2012-07-01
In this paper we present results of extensive Monte Carlo simulations of diffusion-limited aggregation (DLA) with a seed placed on an attractive plane as a simple model in connection with the electrical double layers. We compute the fractal dimension of the aggregated patterns as a function of the attraction strength α. For the patterns grown in both two and three dimensions, the fractal dimension shows a significant dependence on the attraction strength for small values of α and approaches that of the ordinary two-dimensional (2D) DLA in the limit of large α. For the nonattracting case with α = 1, our results in three dimensions reproduce the patterns of 3D ordinary DLA, while in two dimensions our model leads to the formation of a compact cluster with dimension 2. For intermediate α, the 3D clusters have a quasi-2D structure with a fractal dimension very close to that of the ordinary 2D DLA. This allows one to control the morphology of a growing cluster by tuning a single external parameter α. PMID:23005417
Attracted diffusion-limited aggregation
NASA Astrophysics Data System (ADS)
Rahbari, S. H. Ebrahimnazhad; Saberi, A. A.
2012-07-01
In this paper we present results of extensive Monte Carlo simulations of diffusion-limited aggregation (DLA) with a seed placed on an attractive plane as a simple model in connection with the electrical double layers. We compute the fractal dimension of the aggregated patterns as a function of the attraction strength α. For the patterns grown in both two and three dimensions, the fractal dimension shows a significant dependence on the attraction strength for small values of α and approaches that of the ordinary two-dimensional (2D) DLA in the limit of large α. For the nonattracting case with α=1, our results in three dimensions reproduce the patterns of 3D ordinary DLA, while in two dimensions our model leads to the formation of a compact cluster with dimension 2. For intermediate α, the 3D clusters have a quasi-2D structure with a fractal dimension very close to that of the ordinary 2D DLA. This allows one to control the morphology of a growing cluster by tuning a single external parameter α.
NASA Astrophysics Data System (ADS)
Kondoh, Hiroshi; Matsushita, Mitsugu
1986-10-01
Diffusion-limited aggregation (DLA) model with anisotropic sticking probability Ps is computer-simulated on two dimensional square lattice. The cluster grows from a seed particle at the origin in the positive y area with the absorption-type boundary along x-axis. The cluster is found to grow anisotropically as R//˜Nν// and R\\bot˜Nν\\bot, where R\\bot and R// are the radii of gyration of the cluster along x- and y-axes, respectively, and N is the particle number constituting the cluster. The two exponents are shown to become assymptotically ν//{=}2/3, ν\\bot{=}1/3 whenever the sticking anisotropy exists. It is also found that the present model is fairly consistent with Hack’s law of river networks, suggesting that it is a good candidate of a prototype model for the evolution of the river network.
DLA based compressed sensing for high resolution MR microscopy of neuronal tissue
NASA Astrophysics Data System (ADS)
Nguyen, Khieu-Van; Li, Jing-Rebecca; Radecki, Guillaume; Ciobanu, Luisa
2015-10-01
In this work we present the implementation of compressed sensing (CS) on a high field preclinical scanner (17.2 T) using an undersampling trajectory based on the diffusion limited aggregation (DLA) random growth model. When applied to a library of images this approach performs better than the traditional undersampling based on the polynomial probability density function. In addition, we show that the method is applicable to imaging live neuronal tissues, allowing significantly shorter acquisition times while maintaining the image quality necessary for identifying the majority of neurons via an automatic cell segmentation algorithm.
DLA based compressed sensing for high resolution MR microscopy of neuronal tissue.
Nguyen, Khieu-Van; Li, Jing-Rebecca; Radecki, Guillaume; Ciobanu, Luisa
2015-10-01
In this work we present the implementation of compressed sensing (CS) on a high field preclinical scanner (17.2 T) using an undersampling trajectory based on the diffusion limited aggregation (DLA) random growth model. When applied to a library of images this approach performs better than the traditional undersampling based on the polynomial probability density function. In addition, we show that the method is applicable to imaging live neuronal tissues, allowing significantly shorter acquisition times while maintaining the image quality necessary for identifying the majority of neurons via an automatic cell segmentation algorithm. PMID:26367320
Lacunarity and multifractal analysis of the large DLA mass distribution
NASA Astrophysics Data System (ADS)
Rodriguez-Romo, Suemi; Sosa-Herrera, Antonio
2013-08-01
We show the methodology used to analyze fractal and mass-multifractal properties of very large Diffusion-Limited Aggregation (DLA) clusters with a maximum of 109 particles for 2D aggregates and 108 particles for 3D clusters, to support our main result; the scaling behavior obtained by our experimental results corresponds to the expected performance of monofractal objects. In order to estimate lacunarity measures for large DLA clusters, we develop a variant of the gliding-box algorithm which reduces the computer time needed to obtain experimental results. We show how our mass multifractal data have a tendency to present monofractal behavior for the mass distribution of the cases presented in this paper in the limit of very large clusters. Lacunarity analysis shows, provided we study small clusters mass distributions, data which might be interpreted as two different values of fractal dimensions while the cluster grows; however, this effect tends to vanish when the cluster size increases further, in such a way that monofractality is achieved. The outcomes of this paper lead us to conclude that the previously reported mass multifractality behavior (Vicsek et al., 1990 [13]) detected for DLA clusters is a consequence of finite size effects and floating point precision limitations and not an intrinsic feature of the phenomena, since the scaling behavior of our DLA clusters space corresponds to monofractal objects, being this situation remarkably noticeable in the limit of very large clusters.
Active matter model of Myxococcus xanthus aggregation
NASA Astrophysics Data System (ADS)
Patch, Adam; Bahar, Fatmagul; Liu, Guannan; Thutupalli, Shashi; Welch, Roy; Yllanes, David; Shaevitz, Joshua; Marchetti, M. Cristina
Myxococcus xanthus is a soil-dwelling bacterium that exhibits several fascinating collective behaviors including streaming, swarming, and generation of fruiting bodies. A striking feature of M. xanthus is that it periodically reverses its motility direction. The first stage of fruiting body formation is characterized by the aggregation of cells on a surface into round mesoscopic structures. Experiments have shown that this aggregation relies heavily on regulation of the reversal rate and local mechanical interactions, suggesting motility-induced phase separation may play an important role. We have adapted self-propelled particle models to include cell reversal and motility suppression resulting from sporulation observed in aggregates. Using 2D molecular dynamics simulations, we map the phase behavior in the space of Péclet number and local density and examine the kinetics of aggregation for comparison to experiments.
Structure and aggregation in model tetramethylurea solutions
Gupta, Rini; Patey, G. N.
2014-08-14
The structure of model aqueous tetramethylurea (TMU) solutions is investigated employing large-scale (32 000, 64 000 particles) molecular dynamics simulations. Results are reported for TMU mole fractions, X{sub t}, ranging from infinite dilution up to 0.07, and for two temperatures, 300 and 330 K. Two existing force fields for TMU-water solutions are considered. These are the GROMOS 53A6 united-atom TMU model combined with SPC/E water [TMU(GROMOS-UA)/W(SPC/E)], and the more frequently employed AMBER03 all-atom force field for TMU combined with the TIP3P water model [TMU(AMBER-AA)/W(TIP3P)]. It is shown that TMU has a tendency towards aggregation for both models considered, but the tendency is significantly stronger for the [TMU(AMBER-AA)/W(TIP3P)] force field. For this model signs of aggregation are detected at X{sub t} = 0.005, aggregation is a well established feature of the solution at X{sub t} = 0.02, and the aggregates increase further in size with increasing concentration. This is in agreement with at least some experimental studies, which report signals of aggregation in the low concentration regime. The TMU aggregates exhibit little structure and are simply loosely ordered, TMU-rich regions of solution. The [TMU(GROMOS-UA)/W(SPC/E)] model shows strong signs of aggregation only at higher concentrations (X{sub t} ≳ 0.04), and the aggregates appear more loosely ordered, and less well-defined than those occurring in the [TMU(AMBER-AA)/W(TIP3P)] system. For both models, TMU aggregation increases when the temperature is increased from 300 to 330 K, consistent with an underlying entropy driven, hydrophobic interaction mechanism. At X{sub t} = 0.07, the extra-molecular correlation length expected for microheterogeneous solutions has become comparable with the size of the simulation cell for both models considered, indicating that even the systems simulated here are sufficiently large only at low concentrations.
Aggregate vehicle travel forecasting model
Greene, D.L.; Chin, Shih-Miao; Gibson, R.
1995-05-01
This report describes a model for forecasting total US highway travel by all vehicle types, and its implementation in the form of a personal computer program. The model comprises a short-run, econometrically-based module for forecasting through the year 2000, as well as a structural, scenario-based longer term module for forecasting through 2030. The short-term module is driven primarily by economic variables. It includes a detailed vehicle stock model and permits the estimation of fuel use as well as vehicle travel. The longer-tenn module depends on demographic factors to a greater extent, but also on trends in key parameters such as vehicle load factors, and the dematerialization of GNP. Both passenger and freight vehicle movements are accounted for in both modules. The model has been implemented as a compiled program in the Fox-Pro database management system operating in the Windows environment.
Probabilistic prediction models for aggregate quarry siting
Robinson, G.R., Jr.; Larkins, P.M.
2007-01-01
Weights-of-evidence (WofE) and logistic regression techniques were used in a GIS framework to predict the spatial likelihood (prospectivity) of crushed-stone aggregate quarry development. The joint conditional probability models, based on geology, transportation network, and population density variables, were defined using quarry location and time of development data for the New England States, North Carolina, and South Carolina, USA. The Quarry Operation models describe the distribution of active aggregate quarries, independent of the date of opening. The New Quarry models describe the distribution of aggregate quarries when they open. Because of the small number of new quarries developed in the study areas during the last decade, independent New Quarry models have low parameter estimate reliability. The performance of parameter estimates derived for Quarry Operation models, defined by a larger number of active quarries in the study areas, were tested and evaluated to predict the spatial likelihood of new quarry development. Population density conditions at the time of new quarry development were used to modify the population density variable in the Quarry Operation models to apply to new quarry development sites. The Quarry Operation parameters derived for the New England study area, Carolina study area, and the combined New England and Carolina study areas were all similar in magnitude and relative strength. The Quarry Operation model parameters, using the modified population density variables, were found to be a good predictor of new quarry locations. Both the aggregate industry and the land management community can use the model approach to target areas for more detailed site evaluation for quarry location. The models can be revised easily to reflect actual or anticipated changes in transportation and population features. ?? International Association for Mathematical Geology 2007.
Aggregate driver model to enable predictable behaviour
NASA Astrophysics Data System (ADS)
Chowdhury, A.; Chakravarty, T.; Banerjee, T.; Balamuralidhar, P.
2015-09-01
The categorization of driving styles, particularly in terms of aggressiveness and skill is an emerging area of interest under the broader theme of intelligent transportation. There are two possible discriminatory techniques that can be applied for such categorization; a microscale (event based) model and a macro-scale (aggregate) model. It is believed that an aggregate model will reveal many interesting aspects of human-machine interaction; for example, we may be able to understand the propensities of individuals to carry out a given task over longer periods of time. A useful driver model may include the adaptive capability of the human driver, aggregated as the individual propensity to control speed/acceleration. Towards that objective, we carried out experiments by deploying smartphone based application to be used for data collection by a group of drivers. Data is primarily being collected from GPS measurements including position & speed on a second-by-second basis, for a number of trips over a two months period. Analysing the data set, aggregate models for individual drivers were created and their natural aggressiveness were deduced. In this paper, we present the initial results for 12 drivers. It is shown that the higher order moments of the acceleration profile is an important parameter and identifier of journey quality. It is also observed that the Kurtosis of the acceleration profiles stores major information about the driving styles. Such an observation leads to two different ranking systems based on acceleration data. Such driving behaviour models can be integrated with vehicle and road model and used to generate behavioural model for real traffic scenario.
NASA Astrophysics Data System (ADS)
Menshutin, Anton Yu.; Shchur, Lev N.
2006-01-01
We test the multiscaling issue of diffusion-limited-aggregation (DLA) clusters using a modified algorithm. This algorithm eliminates killing the particles at the death circle. Instead, we return them to the birth circle at a random relative angle taken from the evaluated distribution. In addition, we use a two-level hierarchical memory model that allows using large steps in conjunction with an off-lattice realization of the model. Our algorithm still seems to stay in the framework of the original DLA model. We present an accurate estimate of the fractal dimensions based on the data for a hundred clusters with 50 million particles each. We find that multiscaling cannot be ruled out. We also find that the fractal dimension is a weak self-averaging quantity. In addition, the fractal dimension, if calculated using the harmonic measure, is a nonmonotonic function of the cluster radius. We argue that the controversies in the data interpretation can be due to the weak self-averaging and the influence of intrinsic noise.
Microwave extinction characteristics of nanoparticle aggregates
NASA Astrophysics Data System (ADS)
Wu, Y. P.; Cheng, J. X.; Liu, X. X.; Wang, H. X.; Zhao, F. T.; Wen, W. W.
2016-07-01
Structure of nanoparticle aggregates plays an important role in microwave extinction capacity. The diffusion-limited aggregation model (DLA) for fractal growth is utilized to explore the possible structures of nanoparticle aggregates by computer simulation. Based on the discrete dipole approximation (DDA) method, the microwave extinction performance by different nano-carborundum aggregates is numerically analyzed. The effects of the particle quantity, original diameter, fractal structure, as well as orientation on microwave extinction are investigated, and also the extinction characteristics of aggregates are compared with the spherical nanoparticle in the same volume. Numerical results give out that proper aggregation of nanoparticle is beneficial to microwave extinction capacity, and the microwave extinction cross section by aggregated granules is better than that of the spherical solid one in the same volume.
Aggregation kinetics in a model colloidal suspension
Bastea, S
2005-08-08
The authors present molecular dynamics simulations of aggregation kinetics in a colloidal suspension modeled as a highly asymmetric binary mixture. Starting from a configuration with largely uncorrelated colloidal particles the system relaxes by coagulation-fragmentation dynamics to a structured state of low-dimensionality clusters with an exponential size distribution. The results show that short range repulsive interactions alone can give rise to so-called cluster phases. For the present model and probably other, more common colloids, the observed clusters appear to be equilibrium phase fluctuations induced by the entropic inter-colloidal attractions.
Topological Data Analysis of Biological Aggregation Models
Topaz, Chad M.; Ziegelmeier, Lori; Halverson, Tom
2015-01-01
We apply tools from topological data analysis to two mathematical models inspired by biological aggregations such as bird flocks, fish schools, and insect swarms. Our data consists of numerical simulation output from the models of Vicsek and D'Orsogna. These models are dynamical systems describing the movement of agents who interact via alignment, attraction, and/or repulsion. Each simulation time frame is a point cloud in position-velocity space. We analyze the topological structure of these point clouds, interpreting the persistent homology by calculating the first few Betti numbers. These Betti numbers count connected components, topological circles, and trapped volumes present in the data. To interpret our results, we introduce a visualization that displays Betti numbers over simulation time and topological persistence scale. We compare our topological results to order parameters typically used to quantify the global behavior of aggregations, such as polarization and angular momentum. The topological calculations reveal events and structure not captured by the order parameters. PMID:25970184
Topological data analysis of biological aggregation models.
Topaz, Chad M; Ziegelmeier, Lori; Halverson, Tom
2015-01-01
We apply tools from topological data analysis to two mathematical models inspired by biological aggregations such as bird flocks, fish schools, and insect swarms. Our data consists of numerical simulation output from the models of Vicsek and D'Orsogna. These models are dynamical systems describing the movement of agents who interact via alignment, attraction, and/or repulsion. Each simulation time frame is a point cloud in position-velocity space. We analyze the topological structure of these point clouds, interpreting the persistent homology by calculating the first few Betti numbers. These Betti numbers count connected components, topological circles, and trapped volumes present in the data. To interpret our results, we introduce a visualization that displays Betti numbers over simulation time and topological persistence scale. We compare our topological results to order parameters typically used to quantify the global behavior of aggregations, such as polarization and angular momentum. The topological calculations reveal events and structure not captured by the order parameters. PMID:25970184
Bias-free simulation of diffusion-limited aggregation on a square lattice
NASA Astrophysics Data System (ADS)
Loh, Yen Lee
We identify sources of systematic error in traditional simulations of the Witten-Sander model of diffusion-limited aggregation (DLA) on a square lattice. Based on semi-analytic solutions of the walk-to-line and walk-to-square first-passage problems, we develop an algorithm that reduces the simulation bias to below 10-12. We grow clusters of 108 particles on 65536 × 65536 lattices. We verify that lattice DLA clusters inevitably grow into anisotropic shapes, dictated by the anisotropy of the aggregation process. We verify that the fractal dimension evolves from the continuum DLA value, D = 1 . 71 , for small disk-shaped clusters, towards Kesten's bound of D = 3 / 2 for highly anisotropic clusters with long protruding arms.
First-order aggregation models with alignment
NASA Astrophysics Data System (ADS)
Fetecau, Razvan C.; Sun, Weiran; Tan, Changhui
2016-06-01
We include alignment interactions in a well-studied first-order attractive-repulsive macroscopic model for aggregation. The distinctive feature of the extended model is that the equation that specifies the velocity in terms of the population density, becomes implicit, and can have non-unique solutions. We investigate the well-posedness of the model and show rigorously how it can be obtained as a macroscopic limit of a second-order kinetic equation. We work within the space of probability measures with compact support and use mass transportation ideas and the characteristic method as essential tools in the analysis. A discretization procedure that parallels the analysis is formulated and implemented numerically in one and two dimensions.
Simulating aggregate dynamics in ocean biogeochemical models
NASA Astrophysics Data System (ADS)
Jackson, George A.; Burd, Adrian B.
2015-04-01
The dynamics of elements in the water column is complex, depending on multiple biological and physical processes operating at very different physical scales. Coagulation of particulate material is important for transforming particles and moving them in the water column. Mechanistic models of coagulation processes provide a means to predict these processes, help interpret observations, and provide insight into the processes occurring. However, most model applications have focused on describing simple marine systems and mechanisms. We argue that further model development, in close collaboration with field and experimental scientists, is required in order to extend the models to describe the large-scale elemental distributions and interactions being studied as part of GEOTRACES. Models that provide a fundamental description of trace element-particle interactions are required as are experimental tests of the mechanisms involved and the predictions arising from models. However, a comparison between simple and complicated models of aggregation and trace metal provides a means for understanding the implications of simplifying assumptions and providing guidance as to which simplifications are needed.
On aggregation in spatial econometric modelling
NASA Astrophysics Data System (ADS)
Paelinck, Jean H. P.
The spatial aggregation problem - also termed the modifiable areal unit problem - has attracted regular attention in spatial statistics and econometrics. In this study econometric aggregation analysis is used to investigate the formal composition of meso-areal parameters given micro-areal underlying relations with spatial dependence. Impact on stochastic terms (possible meso-areal spatial autocorrelation) is also studied. Finally consequences for meso-areal estimation are derived, the general finding having been that spatial aggregation leads to meso-region specific parameter values, with the estimation problems this implies.
An extended fractal growth regime in the diffusion limited aggregation including edge diffusion
NASA Astrophysics Data System (ADS)
Ghosh, Aritra; Batabyal, R.; Das, G. P.; Dev, B. N.
2016-01-01
We have investigated on-lattice diffusion limited aggregation (DLA) involving edge diffusion and compared the results with the standard DLA model. For both cases, we observe the existence of a crossover from the fractal to the compact regime as a function of sticking coefficient. However, our modified DLA model including edge diffusion shows an extended fractal growth regime like an earlier theoretical result using realistic growth models and physical parameters [Zhang et al., Phys. Rev. Lett. 73 (1994) 1829]. While the results of Zhang et al. showed the existence of the extended fractal growth regime only on triangular but not on square lattices, we find its existence on the square lattice. There is experimental evidence of this growth regime on a square lattice. The standard DLA model cannot characterize fractal morphology as the fractal dimension (Hausdorff dimension, DH) is insensitive to morphology. It also predicts DH = DP (the perimeter dimension). For the usual fractal structures, observed in growth experiments on surfaces, the perimeter dimension can differ significantly (DH ≠ DP) depending on the morphology. Our modified DLA model shows minor sensitivity to this difference.
Duarte-Neto, P; Stošić, T; Stošić, B; Lessa, R; Milošević, M V
2014-07-01
We analyze the combined effect of three ingredients of an aggregation model--surface tension, particle flow and particle source--representing typical characteristics of many aggregation growth processes in nature. Through extensive numerical experiments and for different underlying lattice structures we demonstrate that the location of incoming particles and their preferential direction of flow can significantly affect the resulting general shape of the aggregate, while the surface tension controls the surface roughness. Combining all three ingredients increases the aggregate shape plasticity, yielding a wider spectrum of shapes as compared to earlier works that analyzed these ingredients separately. Our results indicate that the considered combination of effects is fundamental for modeling the polymorphic growth of a wide variety of structures in confined geometries and/or in the presence of external fields, such as rocks, crystals, corals, and biominerals. PMID:25122308
Modelling the structure of sludge aggregates
Smoczyński, Lech; Ratnaweera, Harsha; Kosobucka, Marta; Smoczyński, Michał; Kalinowski, Sławomir; Kvaal, Knut
2016-01-01
ABSTRACT The structure of sludge is closely associated with the process of wastewater treatment. Synthetic dyestuff wastewater and sewage were coagulated using the PAX and PIX methods, and electro-coagulated on aluminium electrodes. The processes of wastewater treatment were supported with an organic polymer. The images of surface structures of the investigated sludge were obtained using scanning electron microscopy (SEM). The software image analysis permitted obtaining plots log A vs. log P, wherein A is the surface area and P is the perimeter of the object, for individual objects comprised in the structure of the sludge. The resulting database confirmed the ‘self-similarity’ of the structural objects in the studied groups of sludge, which enabled calculating their fractal dimension and proposing models for these objects. A quantitative description of the sludge aggregates permitted proposing a mechanism of the processes responsible for their formation. In the paper, also, the impact of the structure of the investigated sludge on the process of sedimentation, and dehydration of the thickened sludge after sedimentation, was discussed. PMID:26549812
Modelling the structure of sludge aggregates.
Smoczyński, Lech; Ratnaweera, Harsha; Kosobucka, Marta; Smoczyński, Michał; Kalinowski, Sławomir; Kvaal, Knut
2016-01-01
The structure of sludge is closely associated with the process of wastewater treatment. Synthetic dyestuff wastewater and sewage were coagulated using the PAX and PIX methods, and electro-coagulated on aluminium electrodes. The processes of wastewater treatment were supported with an organic polymer. The images of surface structures of the investigated sludge were obtained using scanning electron microscopy (SEM). The software image analysis permitted obtaining plots log A vs. log P, wherein A is the surface area and P is the perimeter of the object, for individual objects comprised in the structure of the sludge. The resulting database confirmed the 'self-similarity' of the structural objects in the studied groups of sludge, which enabled calculating their fractal dimension and proposing models for these objects. A quantitative description of the sludge aggregates permitted proposing a mechanism of the processes responsible for their formation. In the paper, also, the impact of the structure of the investigated sludge on the process of sedimentation, and dehydration of the thickened sludge after sedimentation, was discussed. PMID:26549812
Modeling Protein Aggregate Assembly and Structure
NASA Astrophysics Data System (ADS)
Guo, Jun-tao; Hall, Carol K.; Xu, Ying; Wetzel, Ronald
One might say that "protein science" got its start in the domestic arts, built around the abilities of proteins to aggregate in response to environmental stresses such as heating (boiled eggs), heating and cooling (gelatin), and pH (cheese). Characterization of proteins in the late nineteenth century likewise focused on the ability of proteins to precipitate in response to certain salts and to aggregate in response to heating. Investigations by Chick and Martin (Chick and Martin, 1910) showed that the inactivating response of proteins to heat or solvent treatment is a two-step process involving separate denaturation and precipitation steps. Monitoring the coagulation and flocculation responses of proteins to heat and other stresses remained a major approach to understanding protein structure for decades, with solubility, or susceptibility to aggregation, serving as a kind of benchmark against which results of other methods, such as viscosity, chemical susceptibility, immune activity, crystallizability, and susceptibility to proteolysis, were compared (Mirsky and Pauling, 1936;Wu, 1931). Toward the middle of the last century, protein aggregation studies were largely left behind, as improved methods allowed elucidation of the primary sequence of proteins, reversible unfolding studies, and ultimately high-resolution structures. Curiously, the field of protein science, and in particular protein folding, is now gravitating back to a closer look at protein aggregation and protein aggregates. Unfortunately, the means developed during the second half of the twentieth century for studying native, globular proteins have not proved immediately amenable to the study of aggregate structures. Great progress is being made, however, to modify classical methods, including NMR and X-ray diffraction, as well as to develop newer techniques, that together should continue to expand our picture of aggregate structure (Kheterpal and Wetzel, 2006; Wetzel, 1999).
Interplay of model ingredients affecting aggregate shape plasticity in diffusion-limited aggregation
NASA Astrophysics Data System (ADS)
Duarte-Neto, P.; Stošić, T.; Stošić, B.; Lessa, R.; Milošević, M. V.
2014-07-01
We analyze the combined effect of three ingredients of an aggregation model—surface tension, particle flow and particle source—representing typical characteristics of many aggregation growth processes in nature. Through extensive numerical experiments and for different underlying lattice structures we demonstrate that the location of incoming particles and their preferential direction of flow can significantly affect the resulting general shape of the aggregate, while the surface tension controls the surface roughness. Combining all three ingredients increases the aggregate shape plasticity, yielding a wider spectrum of shapes as compared to earlier works that analyzed these ingredients separately. Our results indicate that the considered combination of effects is fundamental for modeling the polymorphic growth of a wide variety of structures in confined geometries and/or in the presence of external fields, such as rocks, crystals, corals, and biominerals.
Modeling the Microwave Single-scattering Properties of Aggregate Snowflakes
NASA Astrophysics Data System (ADS)
Nowell, H.; Honeyager, R. E.; Liu, G.
2014-12-01
A new snowflake aggregation model is developed to study single-scattering properties of aggregate snowflakes. Snowflakes are generated by random aggregation of 6-bullet rosette crystals and constrained by size-density relationships derived from previous field observations. Due to random generation, aggregates may have the same size or mass, yet differing morphology allowing for a study into how shape influences their scattering properties. Furthermore, three different aggregate shapes are created: randomly generated, oblate and prolate flakes. The single-scattering properties of the aggregates are investigated using the discrete dipole approximation (DDA) at 10 frequencies. Results are compared to those of Mie theory for solid and soft spheres (density 10% that of solid ice) and to T-matrix results for solid and soft spheroidal cases with aspect ratios of 0.8 (randomly generated) and 0.6 (oblate and prolate). Above size parameter 0.75, neither the solid nor the soft sphere and spheroidal approximations accurately represent the DDA results for the randomly generated or oblate aggregates. Asymmetry and the normalized scattering and backscattering cross-sections of the randomly generated and oblate aggregates fall between the soft and solid spherical and spheroidal approximations. This implies that evaluating snow scattering properties using realistic shapes, such as the aggregates created in this study instead of a simplified crystal shape, is of paramount importance. The dependence of the single-scattering properties on each aggregate's detailed structure seems of secondary importance. Oblate and prolate preliminary results indicate that backscattering for prolate and oblate flakes is lower than that of the randomly generated flakes. Detailed analyses are conducted to answer: (a) why aggregates of similar size yet dissimilar shape backscatter differently and (b) why prolate and oblate aggregates backscatter differently than randomly generated aggregates.
3D simulation of the Cluster-Cluster Aggregation model
NASA Astrophysics Data System (ADS)
Li, Chao; Xiong, Hailing
2014-12-01
We write a program to implement the Cluster-Cluster Aggregation (CCA) model with java programming language. By using the simulation program, the fractal aggregation growth process can be displayed dynamically in the form of a three-dimensional (3D) figure. Meanwhile, the related kinetics data of aggregation simulation can be also recorded dynamically. Compared to the traditional programs, the program has better real-time performance and is more helpful to observe the fractal growth process, which contributes to the scientific study in fractal aggregation. Besides, because of adopting java programming language, the program has very good cross-platform performance.
MODELING AGGREGATE CHLORPYRIFOS EXPOSURE AND DOSE TO CHILDREN
To help address the aggregate exposure assessment needs of the Food Quality Protection Act, a physically-based probabilistic model (SHEDS-Pesticides, version 3) has been applied to estimate aggregate chlorpyrifos exposure and dose to children. Two age groups (0-4, 5-9 years) a...
NASA Astrophysics Data System (ADS)
Deng, Yan-Hong; Ye, Chao; Yuan, Yuan; Liu, Hui-Min; Cui, Jin
2011-04-01
We investigate the effect of silicone oil viscosity on the aggregation behavior of C:F clusters deposited on silicone oil liquid substrates with viscous coefficients of 100, 350 and 500mm2/s by C4F8 dual-frequency capacitively coupled plasma. The aggregated C:F clusters all exhibit a branch-like fractal structure. However, the fractal dimension decreases from 1.67 to 1.45 with the silicone oil viscous coefficient increasing from 100mm2/s to 500 mm2/s. Owing to the fractal dimension of 1.67 and 1.45, corresponding to the diffusion-limited-aggregation (DLA) model and the cluster-cluster-aggregation (CCA) model respectively, the results show that the increase of silicone oil viscosity can lead to the change of C:F clusters aggregating on a silicone oil liquid substrate from DLA to CCA growth.
Characterization and modeling of thermal diffusion and aggregation in nanofluids.
Gharagozloo, Patricia E.; Goodson, Kenneth E.
2010-05-01
Fluids with higher thermal conductivities are sought for fluidic cooling systems in applications including microprocessors and high-power lasers. By adding high thermal conductivity nanoscale metal and metal oxide particles to a fluid the thermal conductivity of the fluid is enhanced. While particle aggregates play a central role in recent models for the thermal conductivity of nanofluids, the effect of particle diffusion in a temperature field on the aggregation and transport has yet to be studied in depth. The present work separates the effects of particle aggregation and diffusion using parallel plate experiments, infrared microscopy, light scattering, Monte Carlo simulations, and rate equations for particle and heat transport in a well dispersed nanofluid. Experimental data show non-uniform temporal increases in thermal conductivity above effective medium theory and can be well described through simulation of the combination of particle aggregation and diffusion. The simulation shows large concentration distributions due to thermal diffusion causing variations in aggregation, thermal conductivity and viscosity. Static light scattering shows aggregates form more quickly at higher concentrations and temperatures, which explains the increased enhancement with temperature reported by other research groups. The permanent aggregates in the nanofluid are found to have a fractal dimension of 2.4 and the aggregate formations that grow over time are found to have a fractal dimension of 1.8, which is consistent with diffusion limited aggregation. Calculations show as aggregates grow the viscosity increases at a faster rate than thermal conductivity making the highly aggregated nanofluids unfavorable, especially at the low fractal dimension of 1.8. An optimum nanoparticle diameter for these particular fluid properties is calculated to be 130 nm to optimize the fluid stability by reducing settling, thermal diffusion and aggregation.
Kinetic model for astaxanthin aggregation in water-methanol mixtures
NASA Astrophysics Data System (ADS)
Giovannetti, Rita; Alibabaei, Leila; Pucciarelli, Filippo
2009-07-01
The aggregation of astaxanthin in hydrated methanol was kinetically studied in the temperature range from 10 °C to 50 °C, at different astaxanthin concentrations and solvent composition. A kinetic model for the formation and transformation of astaxanthin aggregated has been proposed. Spectrophotometric studies showed that monomeric astaxanthin decayed to H-aggregates that after-wards formed J-aggregates when water content was 50% and the temperature lower than 20 °C; at higher temperatures, very stable J-aggregates were formed directly. Monomer formed very stable H-aggregates when the water content was greater than 60%; in these conditions H-aggregates decayed into J-aggregates only when the temperature was at least 50 °C. Through these findings it was possible to establish that the aggregation reactions took place through a two steps consecutive reaction with first order kinetic constants and that the values of these depended on the solvent composition and temperature.
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Measuring and modeling hemoglobin aggregation below the freezing temperature.
Rosa, Mónica; Lopes, Carlos; Melo, Eduardo P; Singh, Satish K; Geraldes, Vitor; Rodrigues, Miguel A
2013-08-01
Freezing of protein solutions is required for many applications such as storage, transport, or lyophilization; however, freezing has inherent risks for protein integrity. It is difficult to study protein stability below the freezing temperature because phase separation constrains solute concentration in solution. In this work, we developed an isochoric method to study protein aggregation in solutions at -5, -10, -15, and -20 °C. Lowering the temperature below the freezing point in a fixed volume prevents the aqueous solution from freezing, as pressure rises until equilibrium (P,T) is reached. Aggregation rates of bovine hemoglobin (BHb) increased at lower temperature (-20 °C) and higher BHb concentration. However, the addition of sucrose substantially decreased the aggregation rate and prevented aggregation when the concentration reached 300 g/L. The unfolding thermodynamics of BHb was studied using fluorescence, and the fraction of unfolded protein as a function of temperature was determined. A mathematical model was applied to describe BHb aggregation below the freezing temperature. This model was able to predict the aggregation curves for various storage temperatures and initial concentrations of BHb. The aggregation mechanism was revealed to be mediated by an unfolded state, followed by a fast growth of aggregates that readily precipitate. The aggregation kinetics increased for lower temperature because of the higher fraction of unfolded BHb closer to the cold denaturation temperature. Overall, the results obtained herein suggest that the isochoric method could provide a relatively simple approach to obtain fundamental thermodynamic information about the protein and the aggregation mechanism, thus providing a new approach to developing accelerated formulation studies below the freezing temperature. PMID:23808610
One-dimensional model of yeast prion aggregation
NASA Astrophysics Data System (ADS)
Kunes, K. C.; Cox, D. L.; Singh, R. R. P.
2005-11-01
Mammalian prion proteins (PrP) are of significant public health interest. Yeasts have proteins, which can undergo similar reconformation and aggregation processes to PrP, without posing a threat to the organism. These yeast “prions,” such as SUP35, are simpler to experimentally study and model. Recent in vitro studies of the SUP35 protein found long aggregates, pure exponential growth of the misfolded form, and a lag time which depended weakly on the monomer concentration. To explain this data, we have extended a previous model of aggregation kinetics along with a stochastic approach. We assume reconformation only upon aggregation and include aggregate fissioning and an initial nucleation barrier. We find that for sufficiently small nucleation rates or seeding by a small number of preformed nuclei, the models achieve the requisite exponential growth, long aggregates, and a lag time which depends weakly on monomer concentration. The spread in aggregate sizes is well described by the Weibull distribution. All these properties point to the preeminent role of fissioning in the growth of misfolded proteins.
SST dependence of convective aggregation in three General Circulation Models
NASA Astrophysics Data System (ADS)
Bony, Sandrine; Becker, Tobias; Coppin, David; Medeiros, Brian; Reed, Kevin; Stevens, Bjorn; Voigt, Aiko
2015-04-01
Studies using cloud-resolving models or simple models have shown that under certain conditions, the radiative-convective equilibrium state becomes unstable to large-scale overturning circulations, and leads to the phenomenon of self-aggregation of moist convection. Modeling and observational studies suggest that the degree of aggregation of moist convection can influence the large-scale atmospheric state (e.g. humidity, clouds) and its energy budget. The question thus arises as to what extent the aggregation of convection may rectify the Earth's climate, including the large-scale atmospheric circulation, hydrological sensitivity and climate feedbacks. We explore these issues by running three General Circulation Models (IPSL-CM5A-LR, ECHAM6, CAM5) in radiative-convective equilibrium, i.e. a non-rotating aqua-planet configuration forced by a globally-uniform insolation and sea surface temperature (SST). We show that in these conditions, all three models can predict the spontaneous emergence of a large-scale convective organization and overturning circulation, and that the equilibrium aggregation state depends on SST and cloud-radiative effects. We will explore the reasons why the equilibrium aggregation state depends on temperature, and the impact of convective aggregation on the global mean state. Robust behaviors will be highlighted, as well as inter-model differences. The implications of these results will be discussed.
Aggregates, broccoli and cauliflower
NASA Astrophysics Data System (ADS)
Grey, Francois; Kjems, Jørgen K.
1989-09-01
Naturally grown structures with fractal characters like broccoli and cauliflower are discussed and compared with DLA-type aggregates. It is suggested that the branching density can be used to characterize the growth process and an experimental method to determine this parameter is proposed.
An agent-based mathematical model about carp aggregation
NASA Astrophysics Data System (ADS)
Liang, Yu; Wu, Chao
2005-05-01
This work presents an agent-based mathematical model to simulate the aggregation of carp, a harmful fish in North America. The referred mathematical model is derived from the following assumptions: (1) instead of the consensus among every carps involved in the aggregation, the aggregation of carp is completely a random and spontaneous physical behavior of numerous of independent carp; (2) carp aggregation is a collective effect of inter-carp and carp-environment interaction; (3) the inter-carp interaction can be derived from the statistical analytics about large-scale observed data. The proposed mathematical model is mainly based on empirical inter-carp force field, whose effect is featured with repulsion, parallel orientation, attraction, out-of-perception zone, and blind. Based on above mathematical model, the aggregation behavior of carp is formulated and preliminary simulation results about the aggregation of small number of carps within simple environment are provided. Further experiment-based validation about the mathematical model will be made in our future work.
Scattering Computations of Snow Aggregates from Simple Geometry Models
NASA Astrophysics Data System (ADS)
Liao, L.; Meneghini, R.; Nowell, H.; Liu, G.
2012-12-01
Accurately characterizing electromagnetic scattering from snow aggregates is one of the essential components in the development of algorithms for the GPM DPR and GMI. Recently several realistic aggregate models have been developed by using randomized procedures. Using pristine ice crystal habits found in nature as the basic elements of which the aggregates are made, more complex randomly aggregated structures can be formed to replicate snowflakes. For these particles, a numerical scheme is needed to compute the scattered fields. These computations, however, are usually time consuming, and are often limited to a certain range of particle sizes and to a few frequencies. The scattering results at other frequencies and sizes are then obtained by either interpolation or extrapolation from nearby computed points (anchor points). Because of the nonlinear nature of the scattering, particularly in the particle resonance region, this sometimes leads to severe errors if the number of anchor points is not sufficiently large to cover the spectral domain and particle size range. As an alternative to these complex models, the simple geometric models, such as sphere and spheroid, are useful for radar and radiometer applications if their scattering results can be shown to closely approximate those from complex aggregate structures. A great advantage of the simple models is their computational efficiency because of existence of analytical solutions, so that the computations can be easily extended to as many frequencies and particle sizes as desired. In this study, two simple models are tested. One approach is to use a snow mass density that is defined as the ratio of the mass of the snow aggregate to the volume, where the volume is taken to be that of a sphere with a diameter equal to the maximum measured dimension of the aggregate; i.e., the diameter of the circumscribing sphere. Because of the way in which the aggregates are generated, where a size-density relation is used, the
Kinetic Model for 1D aggregation of yeast ``prions''
NASA Astrophysics Data System (ADS)
Kunes, Kay; Cox, Daniel; Singh, Rajiv
2004-03-01
Mammalian prion proteins (PrP) are of public health interest because of mad cow and chronic wasting diseases. Yeast have proteins which can undergo similar reconformation and aggregation processes to PrP; yeast forms are simpler to experimentally study and model. Recent in vitro studies of the SUP35 protein(1), showed long aggregates and pure exponential growth of the misfolded form. To explain this data, we have extended a previous model of aggregation kinetics(2). The model assumes reconformation only upon aggregation, and includes aggregate fissioning and an initial nucleation barrier. We find for sufficiently small nucleation rates or seeding by small dimer concentrations that we can achieve the requisite exponential growth and long aggregates. We will compare to a more realistic stochastic kinetics model and present prelimary attempts to describe recent experiments on SUP35 strains. *-Supported by U.S. Army Congressionally Mandated Research Fund. 1) P. Chien and J.S. Weissman, Nature 410, 223 (2001); http://online.kitp.ucsb.edu/online/bionet03/collins/. 2) J. Masel, V.A.> Jansen, M.A. Nowak, Biophys. Chem. 77, 139 (1999).
A Psychological Model for Aggregating Judgments of Magnitude
NASA Astrophysics Data System (ADS)
Merkle, Edgar C.; Steyvers, Mark
In this paper, we develop and illustrate a psychologically-motivated model for aggregating judgments of magnitude across experts. The model assumes that experts' judgments are perturbed from the truth by both systematic biases and random error, and it provides aggregated estimates that are implicitly based on the application of nonlinear weights to individual judgments. The model is also easily extended to situations where experts report multiple quantile judgments. We apply the model to expert judgments concerning flange leaks in a chemical plant, illustrating its use and comparing it to baseline measures.
Continuum modeling of deformation and aggregation of red blood cells.
Yoon, Daegeun; You, Donghyun
2016-07-26
In order to gain better understanding for rheology of an isolated red blood cell (RBC) and a group of multiple RBCs, new continuum models for describing mechanical properties of cellular structures of an RBC and inter-cellular interactions among multiple RBCs are developed. The viscous property of an RBC membrane, which characterizes dynamic behaviors of an RBC under stress loading and unloading processes, is determined using a generalized Maxwell model. The present model is capable of predicting stress relaxation and stress-strain hysteresis, of which prediction is not possible using the commonly used Kelvin-Voigt model. Nonlinear elasticity of an RBC is determined using the Yeoh hyperelastic material model in a framework of continuum mechanics using finite-element approximation. A novel method to model inter-cellular interactions among multiple adjacent RBCs is also developed. Unlike the previous modeling approaches for aggregation of RBCs, where interaction energy for aggregation is curve-fitted using a Morse-type potential function, the interaction energy is analytically determined. The present aggregation model, therefore, allows us to predict various effects of physical parameters such as the osmotic pressure, the thickness of a glycocalyx layer, the penetration depth, and the permittivity, on the depletion and electrostatic energy among RBCs. Simulations for elongation and recovery deformation of an RBC and for aggregation of multiple RBCs are conducted to evaluate the efficacy of the present continuum modeling methods. PMID:26706720
Multiscale measurement error models for aggregated small area health data.
Aregay, Mehreteab; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Carroll, Rachel; Watjou, Kevin
2016-08-01
Spatial data are often aggregated from a finer (smaller) to a coarser (larger) geographical level. The process of data aggregation induces a scaling effect which smoothes the variation in the data. To address the scaling problem, multiscale models that link the convolution models at different scale levels via the shared random effect have been proposed. One of the main goals in aggregated health data is to investigate the relationship between predictors and an outcome at different geographical levels. In this paper, we extend multiscale models to examine whether a predictor effect at a finer level hold true at a coarser level. To adjust for predictor uncertainty due to aggregation, we applied measurement error models in the framework of multiscale approach. To assess the benefit of using multiscale measurement error models, we compare the performance of multiscale models with and without measurement error in both real and simulated data. We found that ignoring the measurement error in multiscale models underestimates the regression coefficient, while it overestimates the variance of the spatially structured random effect. On the other hand, accounting for the measurement error in multiscale models provides a better model fit and unbiased parameter estimates. PMID:27566773
Aggregation of regularized solutions from multiple observation models
NASA Astrophysics Data System (ADS)
Chen, Jieyang; Pereverzyev, Sergiy, Jr.; Xu, Yuesheng
2015-07-01
Joint inversion of multiple observation models has important applications in many disciplines including geoscience, image processing and computational biology. One of the methodologies for joint inversion of ill-posed observation equations naturally leads to multi-parameter regularization, which has been intensively studied over the last several years. However, problems such as the choice of multiple regularization parameters remain unsolved. In the present study, we discuss a rather general approach to the regularization of multiple observation models, based on the idea of the linear aggregation of approximations corresponding to different values of the regularization parameters. We show how the well-known linear functional strategy can be used for such an aggregation and prove that the error of a constructive aggregator differs from the ideal error value by a quantity of an order higher than the best guaranteed accuracy from the most trustable observation model. The theoretical analysis is illustrated by numerical experiments with simulated data.
Development of Transverse Modes Damped DLA Structure
Jing, C.; Kanareykin, A.; Schoessow, P.; Gai, W.; Konecny, R.; Power, J. G.; Conde, M.
2009-01-22
As the dimensions of accelerating structures become smaller and beam intensities higher, the transverse wakefields driven by the beam become quite large with even a slight misalignment of the beam from the geometric axis. These deflection modes can cause inter-bunch beam breakup and intra-bunch head-tail instabilities along the beam path, and thus BBU control becomes a critical issue. All new metal based accelerating structures, like the accelerating structures developed at SLAC or power extractors at CLIC, have designs in which the transverse modes are heavily damped. Similarly, minimizing the transverse wakefield modes (here the HEMmn hybrid modes in Dielectric-Loaded Accelerating (DLA) structures) is also very critical for developing dielectric based high energy accelerators. In this paper, we present the design of a 7.8 GHz transverse mode damped DLA structure currently under construction, along with plans for the experimental program.
Modelling of strongly coupled particle growth and aggregation
NASA Astrophysics Data System (ADS)
Gruy, F.; Touboul, E.
2013-02-01
The mathematical modelling of the dynamics of particle suspension is based on the population balance equation (PBE). PBE is an integro-differential equation for the population density that is a function of time t, space coordinates and internal parameters. Usually, the particle is characterized by a unique parameter, e.g. the matter volume v. PBE consists of several terms: for instance, the growth rate and the aggregation rate. So, the growth rate is a function of v and t. In classical modelling, the growth and the aggregation are independently considered, i.e. they are not coupled. However, current applications occur where the growth and the aggregation are coupled, i.e. the change of the particle volume with time is depending on its initial value v0, that in turn is related to an aggregation event. As a consequence, the dynamics of the suspension does not obey the classical Von Smoluchowski equation. This paper revisits this problem by proposing a new modelling by using a bivariate PBE (with two internal variables: v and v0) and by solving the PBE by means of a numerical method and Monte Carlo simulations. This is applied to a physicochemical system with a simple growth law and a constant aggregation kernel.
Scattering and propagation of terahertz pulses in random soot aggregate systems
NASA Astrophysics Data System (ADS)
Li, Hai-Ying; Wu, Zhen-Sen; Bai, Lu; Li, Zheng-Jun
2014-05-01
Scattering and propagation of terahertz pulses in random soot aggregate systems are studied by using the generalized multi-particle Mie-solution (GMM) and the pulse propagation theory. Soot aggregates are obtained by the diffusion-limited aggregation (DLA) model. For a soot aggregate in soot aggregate systems, scattering characteristics are analyzed by using the GMM. Scattering intensities versus scattering angles are given. The effects of different positions of the aggregate on the scattering intensities, scattering cross sections, extinction cross sections, and absorption cross sections are computed and compared. Based on pulse propagation in random media, the transmission of terahertz pulses in random soot aggregate systems is determined by the two-frequency mutual coherence function. Numerical simulations and analysis are given for terahertz pulses (0.7956 THz).
Cement-aggregate compatibility and structure property relationships including modelling
Jennings, H.M.; Xi, Y.
1993-07-15
The role of aggregate, and its interface with cement paste, is discussed with a view toward establishing models that relate structure to properties. Both short (nm) and long (mm) range structure must be considered. The short range structure of the interface depends not only on the physical distribution of the various phases, but also on moisture content and reactivity of aggregate. Changes that occur on drying, i.e. shrinkage, may alter the structure which, in turn, feeds back to alter further drying and shrinkage. The interaction is dynamic, even without further hydration of cement paste, and the dynamic characteristic must be considered in order to fully understand and model its contribution to properties. Microstructure and properties are two subjects which have been pursued somewhat separately. This review discusses both disciplines with a view toward finding common research goals in the future. Finally, comment is made on possible chemical reactions which may occur between aggregate and cement paste.
Fractality à la carte: a general particle aggregation model
Nicolás-Carlock, J. R.; Carrillo-Estrada, J. L.; Dossetti, V.
2016-01-01
In nature, fractal structures emerge in a wide variety of systems as a local optimization of entropic and energetic distributions. The fractality of these systems determines many of their physical, chemical and/or biological properties. Thus, to comprehend the mechanisms that originate and control the fractality is highly relevant in many areas of science and technology. In studying clusters grown by aggregation phenomena, simple models have contributed to unveil some of the basic elements that give origin to fractality, however, the specific contribution from each of these elements to fractality has remained hidden in the complex dynamics. Here, we propose a simple and versatile model of particle aggregation that is, on the one hand, able to reveal the specific entropic and energetic contributions to the clusters’ fractality and morphology, and, on the other, capable to generate an ample assortment of rich natural-looking aggregates with any prescribed fractal dimension. PMID:26781204
Fractality à la carte: a general particle aggregation model
NASA Astrophysics Data System (ADS)
Nicolás-Carlock, J. R.; Carrillo-Estrada, J. L.; Dossetti, V.
2016-01-01
In nature, fractal structures emerge in a wide variety of systems as a local optimization of entropic and energetic distributions. The fractality of these systems determines many of their physical, chemical and/or biological properties. Thus, to comprehend the mechanisms that originate and control the fractality is highly relevant in many areas of science and technology. In studying clusters grown by aggregation phenomena, simple models have contributed to unveil some of the basic elements that give origin to fractality, however, the specific contribution from each of these elements to fractality has remained hidden in the complex dynamics. Here, we propose a simple and versatile model of particle aggregation that is, on the one hand, able to reveal the specific entropic and energetic contributions to the clusters’ fractality and morphology, and, on the other, capable to generate an ample assortment of rich natural-looking aggregates with any prescribed fractal dimension.
Fractality à la carte: a general particle aggregation model.
Nicolás-Carlock, J R; Carrillo-Estrada, J L; Dossetti, V
2016-01-01
In nature, fractal structures emerge in a wide variety of systems as a local optimization of entropic and energetic distributions. The fractality of these systems determines many of their physical, chemical and/or biological properties. Thus, to comprehend the mechanisms that originate and control the fractality is highly relevant in many areas of science and technology. In studying clusters grown by aggregation phenomena, simple models have contributed to unveil some of the basic elements that give origin to fractality, however, the specific contribution from each of these elements to fractality has remained hidden in the complex dynamics. Here, we propose a simple and versatile model of particle aggregation that is, on the one hand, able to reveal the specific entropic and energetic contributions to the clusters' fractality and morphology, and, on the other, capable to generate an ample assortment of rich natural-looking aggregates with any prescribed fractal dimension. PMID:26781204
Markov Modeling with Soft Aggregation for Safety and Decision Analysis
COOPER,J. ARLIN
1999-09-01
The methodology in this report improves on some of the limitations of many conventional safety assessment and decision analysis methods. A top-down mathematical approach is developed for decomposing systems and for expressing imprecise individual metrics as possibilistic or fuzzy numbers. A ''Markov-like'' model is developed that facilitates combining (aggregating) inputs into overall metrics and decision aids, also portraying the inherent uncertainty. A major goal of Markov modeling is to help convey the top-down system perspective. One of the constituent methodologies allows metrics to be weighted according to significance of the attribute and aggregated nonlinearly as to contribution. This aggregation is performed using exponential combination of the metrics, since the accumulating effect of such factors responds less and less to additional factors. This is termed ''soft'' mathematical aggregation. Dependence among the contributing factors is accounted for by incorporating subjective metrics on ''overlap'' of the factors as well as by correspondingly reducing the overall contribution of these combinations to the overall aggregation. Decisions corresponding to the meaningfulness of the results are facilitated in several ways. First, the results are compared to a soft threshold provided by a sigmoid function. Second, information is provided on input ''Importance'' and ''Sensitivity,'' in order to know where to place emphasis on considering new controls that may be necessary. Third, trends in inputs and outputs are tracked in order to obtain significant information% including cyclic information for the decision process. A practical example from the air transportation industry is used to demonstrate application of the methodology. Illustrations are given for developing a structure (along with recommended inputs and weights) for air transportation oversight at three different levels, for developing and using cycle information, for developing Importance and
Anisotropic diffusion limited aggregation in three dimensions: universality and nonuniversality.
Goold, Nicholas R; Somfai, Ellák; Ball, Robin C
2005-09-01
We explore the macroscopic consequences of lattice anisotropy for diffusion limited aggregation (DLA) in three dimensions. Simple cubic and bcc lattice growths are shown to approach universal asymptotic states in a coherent fashion, and the approach is accelerated by the use of noise reduction. These states are strikingly anisotropic dendrites with a rich hierarchy of structure. For growth on an fcc lattice, our data suggest at least two stable fixed points of anisotropy, one matching the bcc case. Hexagonal growths, favoring six planar and two polar directions, appear to approach a line of asymptotic states with continuously tunable polar anisotropy. The more planar of these growths visually resembles real snowflake morphologies. Our simulations use a new and dimension-independent implementation of the DLA model. The algorithm maintains a hierarchy of sphere coverings of the growth, supporting efficient random walks onto the growth by spherical moves. Anisotropy was introduced by restricting growth to certain preferred directions. PMID:16241431
Anisotropic diffusion limited aggregation in three dimensions: Universality and nonuniversality
NASA Astrophysics Data System (ADS)
Goold, Nicholas R.; Somfai, Ellák; Ball, Robin C.
2005-09-01
We explore the macroscopic consequences of lattice anisotropy for diffusion limited aggregation (DLA) in three dimensions. Simple cubic and bcc lattice growths are shown to approach universal asymptotic states in a coherent fashion, and the approach is accelerated by the use of noise reduction. These states are strikingly anisotropic dendrites with a rich hierarchy of structure. For growth on an fcc lattice, our data suggest at least two stable fixed points of anisotropy, one matching the bcc case. Hexagonal growths, favoring six planar and two polar directions, appear to approach a line of asymptotic states with continuously tunable polar anisotropy. The more planar of these growths visually resembles real snowflake morphologies. Our simulations use a new and dimension-independent implementation of the DLA model. The algorithm maintains a hierarchy of sphere coverings of the growth, supporting efficient random walks onto the growth by spherical moves. Anisotropy was introduced by restricting growth to certain preferred directions.
Multiscale modelling of nucleosome core particle aggregation
NASA Astrophysics Data System (ADS)
Lyubartsev, Alexander P.; Korolev, Nikolay; Fan, Yanping; Nordenskiöld, Lars
2015-02-01
The nucleosome core particle (NCP) is the basic building block of chromatin. Under the influence of multivalent cations, isolated mononucleosomes exhibit a rich phase behaviour forming various columnar phases with characteristic NCP-NCP stacking. NCP stacking is also a regular element of chromatin structure in vivo. Understanding the mechanism of nucleosome stacking and the conditions leading to self-assembly of NCPs is still incomplete. Due to the complexity of the system and the need to describe electrostatics properly by including the explicit mobile ions, novel modelling approaches based on coarse-grained (CG) methods at the multiscale level becomes a necessity. In this work we present a multiscale CG computer simulation approach to modelling interactions and self-assembly of solutions of NCPs induced by the presence of multivalent cations. Starting from continuum simulations including explicit three-valent cobalt(III)hexammine (CoHex3+) counterions and 20 NCPs, based on a previously developed advanced CG NCP model with one bead per amino acid and five beads per two DNA base pair unit (Fan et al 2013 PLoS One 8 e54228), we use the inverse Monte Carlo method to calculate effective interaction potentials for a ‘super-CG’ NCP model consisting of seven beads for each NCP. These interaction potentials are used in large-scale simulations of up to 5000 NCPs, modelling self-assembly induced by CoHex3+. The systems of ‘super-CG’ NCPs form a single large cluster of stacked NCPs without long-range order in agreement with experimental data for NCPs precipitated by the three-valent polyamine, spermidine3+.
Frequency Factors in a Landscape Model of Filamentous Protein Aggregation
NASA Astrophysics Data System (ADS)
Buell, Alexander K.; Jamie R. Blundell; Dobson, Christopher M.; Welland, Mark E.; Terentjev, Eugene M.; Knowles, Tuomas P. J.
2010-06-01
Using quantitative measurements of protein aggregation rates, we develop a kinetic picture of protein conversion from a soluble to a fibrillar state which shows that a single free energy barrier to aggregation controls the addition of protein molecules into amyloid fibrils, while the characteristic sublinear concentration dependence emerges as a natural consequence of finite diffusion times. These findings suggest that this reaction does not follow a simple chemical mechanism, but rather operates in a way analogous to the landscape models of protein folding defined by stochastic dynamics on a characteristic energy surface.
Modeling of alkali aggregate reaction effects in concrete dams
Capra, B.; Bournazel, J.P.; Bourdarot, E.
1995-12-31
Alkali Aggregate Reactions (AAR) are difficult to model due to the random distribution of the reactive sites and the imperfect knowledge of these chemical reactions. A new approach, using fracture mechanics and probabilities, capable to describe the anisotropic swelling of a structure is presented.
Towards a Dynamical Collision Model of Highly Porous Dust Aggregates
NASA Astrophysics Data System (ADS)
Güttler, Carsten; Krause, Maya; Geretshauser, Ralf; Speith, Roland; Blum, Jürgen
2009-06-01
In the recent years we have performed various experiments on the collision dynamics of highly porous dust aggregates and although we now have a comprehensive picture of the micromechanics of those aggregates, the macroscopic understanding is still lacking. We are therefore developing a mechanical model to describe dust aggregate collisions with macroscopic parameters like tensile strength, compressive strength and shear strength. For one well defined dust sample material, the tensile and compressive strength were measured in a static experiment and implemented in a Smoothed Particle Hydrodynamics (SPH) code. A laboratory experiment was designed to compare the laboratory results with the results of the SPH simulation. In this experiment, a mm-sized glass bead is dropped into a cm-sized dust aggregate with the previously measured strength parameters. We determine the deceleration of the glass bead by high-speed imaging and the compression of the dust aggregate by x-ray micro-tomography. The measured penetration depth, stopping time and compaction under the glass bead are utilized to calibrate and test the SPH code. We find that the statically measured compressive strength curve is only applicable if we adjust it to the dynamic situation with a ``softness'' parameter. After determining this parameter, the SPH code is capable of reproducing experimental results, which have not been used for the calibration before.
Sticky Particles: Modeling Rigid Aggregates in Dense Planetary Rings
NASA Astrophysics Data System (ADS)
Perrine, Randall P.; Richardson, D. C.; Scheeres, D. J.
2008-09-01
We present progress on our study of planetary ring dynamics. We use local N-body simulations to examine small patches of dense rings in which self-gravity and mutual collisions dominate the dynamics of the ring material. We use the numerical code pkdgrav to model the motions of 105-7 ring particles, using a sliding patch model with modified periodic boundary conditions. The exact nature of planetary ring particles is not well understood. If covered in a frost-like layer, such irregular surfaces may allow for weak cohesion between colliding particles. Thus we have recently added new functionality to our model, allowing "sticky particles” to lock into rigid aggregates while in a rotating reference frame. This capability allows particles to adhere to one another, forming irregularly shaped aggregates that move as rigid bodies. (The bonds between particles can subsequently break, given sufficient stress.) These aggregates have greater strength than gravitationally bound "rubble piles,” and are thus able to grow larger and survive longer under similar stresses. This new functionality allows us to explore planetary ring properties and dynamics in a new way, by self-consistently forming (and destroying) non-spherical aggregates and moonlets via cohesive forces, while in a rotating frame, subjected to planetary tides. (We are not aware of any similar implementations in other existing models.) These improvements allow us to study the many effects that particle aggregation may have on the rings, such as overall ring structure; wake formation; equilibrium properties of non-spherical particles, like pitch angle, orientation, shape, size distribution, and spin; and the surface properties of the ring material. We present test cases and the latest results from this new model. This work is supported by a NASA Earth and Space Science Fellowship.
Individual based and mean-field modeling of direct aggregation
Burger, Martin; Haškovec, Jan; Wolfram, Marie-Therese
2013-01-01
We introduce two models of biological aggregation, based on randomly moving particles with individual stochasticity depending on the perceived average population density in their neighborhood. In the first-order model the location of each individual is subject to a density-dependent random walk, while in the second-order model the density-dependent random walk acts on the velocity variable, together with a density-dependent damping term. The main novelty of our models is that we do not assume any explicit aggregative force acting on the individuals; instead, aggregation is obtained exclusively by reducing the individual stochasticity in response to higher perceived density. We formally derive the corresponding mean-field limits, leading to nonlocal degenerate diffusions. Then, we carry out the mathematical analysis of the first-order model, in particular, we prove the existence of weak solutions and show that it allows for measure-valued steady states. We also perform linear stability analysis and identify conditions for pattern formation. Moreover, we discuss the role of the nonlocality for well-posedness of the first-order model. Finally, we present results of numerical simulations for both the first- and second-order model on the individual-based and continuum levels of description. PMID:24926113
Balancing aggregation and smoothing errors in inverse models
Turner, A. J.; Jacob, D. J.
2015-01-13
Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a method for quantifying aggregation and smoothing errors as a function ofmore » state vector dimension, so that a suitable dimension can be selected by minimizing the combined error. Reducing the state vector within the aggregation error constraints can have the added advantage of enabling analytical solution to the inverse problem with full error characterization. We compare three methods for reducing the dimension of the state vector from its native resolution: (1) merging adjacent elements (grid coarsening), (2) clustering with principal component analysis (PCA), and (3) applying a Gaussian mixture model (GMM) with Gaussian pdfs as state vector elements on which the native-resolution state vector elements are projected using radial basis functions (RBFs). The GMM method leads to somewhat lower aggregation error than the other methods, but more importantly it retains resolution of major local features in the state vector while smoothing weak and broad features.« less
Balancing aggregation and smoothing errors in inverse models
Turner, A. J.; Jacob, D. J.
2015-06-30
Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a method for quantifying aggregation and smoothing errors as a function ofmore » state vector dimension, so that a suitable dimension can be selected by minimizing the combined error. Reducing the state vector within the aggregation error constraints can have the added advantage of enabling analytical solution to the inverse problem with full error characterization. We compare three methods for reducing the dimension of the state vector from its native resolution: (1) merging adjacent elements (grid coarsening), (2) clustering with principal component analysis (PCA), and (3) applying a Gaussian mixture model (GMM) with Gaussian pdfs as state vector elements on which the native-resolution state vector elements are projected using radial basis functions (RBFs). The GMM method leads to somewhat lower aggregation error than the other methods, but more importantly it retains resolution of major local features in the state vector while smoothing weak and broad features.« less
Aggregate Model for Heterogeneous Thermostatically Controlled Loads with Demand Response
Zhang, Wei; Kalsi, Karanjit; Fuller, Jason C.; Elizondo, Marcelo A.; Chassin, David P.
2012-07-22
Due to the potentially large number of Distributed Energy Resources (DERs) – demand response, distributed generation, distributed storage - that are expected to be deployed, it is impractical to use detailed models of these resources when integrated with the transmission system. Being able to accurately estimate the fast transients caused by demand response is especially important to analyze the stability of the system under different demand response strategies. On the other hand, a less complex model is more amenable to design feedback control strategies for the population of devices to provide ancillary services. The main contribution of this paper is to develop aggregated models for a heterogeneous population of Thermostatic Controlled Loads (TCLs) to accurately capture their collective behavior under demand response and other time varying effects of the system. The aggregated model efficiently includes statistical information of the population and accounts for a second order effect necessary to accurately capture the collective dynamic behavior. The developed aggregated models are validated against simulations of thousands of detailed building models using GridLAB-D (an open source distribution simulation software) under both steady state and severe dynamic conditions caused due to temperature set point changes.
Social Aggregation in Pea Aphids: Experiment and Random Walk Modeling
Nilsen, Christa; Paige, John; Warner, Olivia; Mayhew, Benjamin; Sutley, Ryan; Lam, Matthew; Bernoff, Andrew J.; Topaz, Chad M.
2013-01-01
From bird flocks to fish schools and ungulate herds to insect swarms, social biological aggregations are found across the natural world. An ongoing challenge in the mathematical modeling of aggregations is to strengthen the connection between models and biological data by quantifying the rules that individuals follow. We model aggregation of the pea aphid, Acyrthosiphon pisum. Specifically, we conduct experiments to track the motion of aphids walking in a featureless circular arena in order to deduce individual-level rules. We observe that each aphid transitions stochastically between a moving and a stationary state. Moving aphids follow a correlated random walk. The probabilities of motion state transitions, as well as the random walk parameters, depend strongly on distance to an aphid's nearest neighbor. For large nearest neighbor distances, when an aphid is essentially isolated, its motion is ballistic with aphids moving faster, turning less, and being less likely to stop. In contrast, for short nearest neighbor distances, aphids move more slowly, turn more, and are more likely to become stationary; this behavior constitutes an aggregation mechanism. From the experimental data, we estimate the state transition probabilities and correlated random walk parameters as a function of nearest neighbor distance. With the individual-level model established, we assess whether it reproduces the macroscopic patterns of movement at the group level. To do so, we consider three distributions, namely distance to nearest neighbor, angle to nearest neighbor, and percentage of population moving at any given time. For each of these three distributions, we compare our experimental data to the output of numerical simulations of our nearest neighbor model, and of a control model in which aphids do not interact socially. Our stochastic, social nearest neighbor model reproduces salient features of the experimental data that are not captured by the control. PMID:24376691
Social aggregation in pea aphids: experiment and random walk modeling.
Nilsen, Christa; Paige, John; Warner, Olivia; Mayhew, Benjamin; Sutley, Ryan; Lam, Matthew; Bernoff, Andrew J; Topaz, Chad M
2013-01-01
From bird flocks to fish schools and ungulate herds to insect swarms, social biological aggregations are found across the natural world. An ongoing challenge in the mathematical modeling of aggregations is to strengthen the connection between models and biological data by quantifying the rules that individuals follow. We model aggregation of the pea aphid, Acyrthosiphon pisum. Specifically, we conduct experiments to track the motion of aphids walking in a featureless circular arena in order to deduce individual-level rules. We observe that each aphid transitions stochastically between a moving and a stationary state. Moving aphids follow a correlated random walk. The probabilities of motion state transitions, as well as the random walk parameters, depend strongly on distance to an aphid's nearest neighbor. For large nearest neighbor distances, when an aphid is essentially isolated, its motion is ballistic with aphids moving faster, turning less, and being less likely to stop. In contrast, for short nearest neighbor distances, aphids move more slowly, turn more, and are more likely to become stationary; this behavior constitutes an aggregation mechanism. From the experimental data, we estimate the state transition probabilities and correlated random walk parameters as a function of nearest neighbor distance. With the individual-level model established, we assess whether it reproduces the macroscopic patterns of movement at the group level. To do so, we consider three distributions, namely distance to nearest neighbor, angle to nearest neighbor, and percentage of population moving at any given time. For each of these three distributions, we compare our experimental data to the output of numerical simulations of our nearest neighbor model, and of a control model in which aphids do not interact socially. Our stochastic, social nearest neighbor model reproduces salient features of the experimental data that are not captured by the control. PMID:24376691
Ebrahimi, Ali; Or, Dani
2016-09-01
Microbial communities inhabiting soil aggregates dynamically adjust their activity and composition in response to variations in hydration and other external conditions. These rapid dynamics shape signatures of biogeochemical activity and gas fluxes emitted from soil profiles. Recent mechanistic models of microbial processes in unsaturated aggregate-like pore networks revealed a highly dynamic interplay between oxic and anoxic microsites jointly shaped by hydration conditions and by aerobic and anaerobic microbial community abundance and self-organization. The spatial extent of anoxic niches (hotspots) flicker in time (hot moments) and support substantial anaerobic microbial activity even in aerated soil profiles. We employed an individual-based model for microbial community life in soil aggregate assemblies represented by 3D angular pore networks. Model aggregates of different sizes were subjected to variable water, carbon and oxygen contents that varied with soil depth as boundary conditions. The study integrates microbial activity within aggregates of different sizes and soil depth to obtain estimates of biogeochemical fluxes from the soil profile. The results quantify impacts of dynamic shifts in microbial community composition on CO2 and N2 O production rates in soil profiles in good agreement with experimental data. Aggregate size distribution and the shape of resource profiles in a soil determine how hydration dynamics shape denitrification and carbon utilization rates. Results from the mechanistic model for microbial activity in aggregates of different sizes were used to derive parameters for analytical representation of soil biogeochemical processes across large scales of practical interest for hydrological and climate models. PMID:27152862
Model for Aggregated Water Heater Load Using Dynamic Bayesian Networks
Vlachopoulou, Maria; Chin, George; Fuller, Jason C.; Lu, Shuai; Kalsi, Karanjit
2012-07-19
The transition to the new generation power grid, or “smart grid”, requires novel ways of using and analyzing data collected from the grid infrastructure. Fundamental functionalities like demand response (DR), that the smart grid needs, rely heavily on the ability of the energy providers and distributors to forecast the load behavior of appliances under different DR strategies. This paper presents a new model of aggregated water heater load, based on dynamic Bayesian networks (DBNs). The model has been validated against simulated data from an open source distribution simulation software (GridLAB-D). The results presented in this paper demonstrate that the DBN model accurately tracks the load profile curves of aggregated water heaters under different testing scenarios.
A probabilistic approach to aggregate induction machine modeling
Stankovic, A.M.; Lesieutre, B.C.
1996-11-01
In this paper the authors pursue probabilistic aggregate dynamical models for n identical induction machines connected to a bus, capturing the effect of different mechanical inputs to the individual machines. The authors explore model averaging and review in detail four procedures for linear models. They describe linear systems depending upon stochastic parameters, and develop a theoretical justification for a very simple and reasonably accurate averaging method. They then extend this to the nonlinear model. Finally, they use a recently introduced notion of the stochastic norm to describe a cluster of induction machines undergoing multiple simultaneous parametric variations, and obtain useful and very mildly conservative bounds on eigenstructure perturbations under multiple simultaneous parametric variations.
A new example of the diffusion-limited aggregation: Ni-Cu film patterns
NASA Astrophysics Data System (ADS)
Kockar, Hakan; Bayirli, Mehmet; Alper, Mursel
2010-02-01
The mechanism of the growth of the dendrites in the Ni-Cu films is studied by comparing them with the aggregates obtained by Monte Carlo (MC) simulations according to the diffusion-limited aggregation (DLA) model. The films were grown by electrodeposition. The structural analysis of the films carried out using the x-ray diffraction showed that the films have a face-centered cubic structure. Scanning electron microscope (SEM) was used for morphological observations and the film compositions were determined by energy dispersive x-ray spectroscopy. The observed SEM images are compared with the patterns obtained by MC simulations according to DLA model in which the sticking probability, P between the particles is used as a parameter. For all samples between the least and the densest aggregates in the films, the critical exponents of the density-density correlation functions, α were within the interval 0.160 ± 0.005-0.124 ± 0.006, and the fractal dimensions, Df, varies from 1.825 ± 0.006 to 1.809 ± 0.008 according to the method of two-point correlation function. These values are also verified by the mass-radius method. The pattern with α and Df within these intervals was obtained by MC simulations to DLA model while the sticking probability, P was within the interval from 0.35 to 0.40 obtained by varying P (1-0.001). The results showed that the DLA model in this binary system is a possible mechanism for the formation of the ramified pattern of Ni-Cu within the Ni-rich base part of the Ni-Cu films due to the diffusive characteristics of Cu.
Thermodynamically reversible generalization of diffusion limited aggregation.
D'Souza, R M; Margolus, N H
1999-07-01
We introduce a lattice gas model of cluster growth via the diffusive aggregation of particles in a closed system obeying a local, deterministic, microscopically reversible dynamics. This model roughly corresponds to placing the irreversible diffusion limited aggregation model (DLA) in contact with a heat bath. Particles release latent heat when aggregating, while singly connected cluster members can absorb heat and evaporate. The heat bath is initially empty, hence we observe the flow of entropy from the aggregating gas of particles into the heat bath, which is being populated by diffusing heat tokens. Before the population of the heat bath stabilizes, the cluster morphology (quantified by the fractal dimension) is similar to a standard DLA cluster. The cluster then gradually anneals, becoming more tenuous, until reaching configurational equilibrium when the cluster morphology resembles a quenched branched random polymer. As the microscopic dynamics is invertible, we can reverse the evolution, observe the inverse flow of heat and entropy, and recover the initial condition. This simple system provides an explicit example of how macroscopic dissipation and self-organization can result from an underlying microscopically reversible dynamics. We present a detailed description of the dynamics for the model, discuss the macroscopic limit, and give predictions for the equilibrium particle densities obtained in the mean field limit. Empirical results for the growth are then presented, including the observed equilibrium particle densities, the temperature of the system, the fractal dimension of the growth clusters, scaling behavior, finite size effects, and the approach to equilibrium. We pay particular attention to the temporal behavior of the growth process and show that the relaxation to the maximum entropy state is initially a rapid nonequilibrium process, then subsequently it is a quasistatic process with a well defined temperature. PMID:11969759
Neighborhood Supported Model Level Fuzzy Aggregation for Moving Object Segmentation.
Chiranjeevi, Pojala; Sengupta, Somnath
2014-02-01
We propose a new algorithm for moving object detection in the presence of challenging dynamic background conditions. We use a set of fuzzy aggregated multifeature similarity measures applied on multiple models corresponding to multimodal backgrounds. The algorithm is enriched with a neighborhood-supported model initialization strategy for faster convergence. A model level fuzzy aggregation measure driven background model maintenance ensures more robustness. Similarity functions are evaluated between the corresponding elements of the current feature vector and the model feature vectors. Concepts from Sugeno and Choquet integrals are incorporated in our algorithm to compute fuzzy similarities from the ordered similarity function values for each model. Model updating and the foreground/background classification decision is based on the set of fuzzy integrals. Our proposed algorithm is shown to outperform other multi-model background subtraction algorithms. The proposed approach completely avoids explicit offline training to initialize background model and can be initialized with moving objects also. The feature space uses a combination of intensity and statistical texture features for better object localization and robustness. Our qualitative and quantitative studies illustrate the mitigation of varieties of challenging situations by our approach. PMID:24235250
Simplified Exactly Solvable Model for β-Amyloid Aggregation
NASA Astrophysics Data System (ADS)
Zamparo, M.; Trovato, A.; Maritan, A.
2010-09-01
We propose an exactly solvable simplified statistical mechanical model for the thermodynamics of β-amyloid aggregation, generalizing a well-studied model for protein folding. The monomer concentration is explicitly taken into account as well as a nontrivial dependence on the microscopic degrees of freedom of the single peptide chain, both in the α-helix folded isolated state and in the fibrillar one. The phase diagram of the model is studied and compared to the outcome of fibril formation experiments which is qualitatively reproduced.
Wax crystallization and aggregation in a model crude oil
NASA Astrophysics Data System (ADS)
Vignati, Emanuele; Piazza, Roberto; Visintin, Ruben F. G.; Lapasin, Romano; D'Antona, Paolo; Lockhart, Thomas P.
2005-11-01
The high-molecular-weight paraffinic ('wax') fraction separates from crude oils at low temperatures, a process that can lead to a sol-gel transition when the mass of wax solids exceeds 1-2%. Attractive interactions between the micron-size wax solids suspended in the non-polar medium have been suggested to be responsible for gel formation. The present study reports an optically transparent model oil system, based on a mixture of linear and branched paraffins. Rheological measurements and optical microscopy show that the model system reproduces essential features of crude oil gels. Small-angle light scattering studies conducted at temperatures intermediate between the cloud point (58 °C) and sol-gel transition (39 °C) show that phase separation and wax solid aggregation are rapid processes, leading to the formation of dynamically arrested structures well above the sol-gel transition determined rheologically. Analysis of gravity settling effects has provided a rough estimate for the yield stress of the wax particle network formed (greater than 0.7 Pa at 45 °C and 0.07 Pa at 55 °C). Clusters formed by the aggregated wax solids possess a fractal dimension of about 1.8, consistent with diffusion-limited cluster-cluster aggregation.
Aggregation of model asphaltenes: a molecular dynamics study.
Costa, J L L F S; Simionesie, D; Zhang, Z J; Mulheran, P A
2016-10-01
Natural asphaltenes are defined as polyaromatic compounds whose chemical composition and structure are dependent on their geological origin and production history, hence are regarded as complex molecules with aromatic cores and aliphatic tails that occur in the heaviest fraction of crude oil. The aggregation of asphaltenes presents a range of technical challenges to the production and processing of oil. In this work we study the behaviour of the model asphaltene-like molecule hexa-tert-butylhexa-peri-hexabenzocoronene (HTBHBC) using molecular dynamics simulation. It was found that the regular arrangement of the tert-butyl side chains prevents the formation of strongly-bound dimers by severely restricting the configurational space of the aggregation pathway. In contrast, a modified molecule with only 3 side chains is readily able to form dimers. This work therefore confirms the influence of the molecular structure of polyaromatic compounds on their aggregation mechanism, and reveals the unexpected design rules required for model systems that can mimic the behavior of asphaltenes. PMID:27465036
NASA Astrophysics Data System (ADS)
Tanaka, Kie; Shima, Hiroshi
Properties of aggregate are not taken into account in current codes for drying shrinkage of concrete although the drying shrinkage is affected by the properties of aggregate. Aggregate restrains cement paste from shrinkage so that the drying shrinkage of concrete is controlled by drying shrinkage and Young's modulus of aggregate itself. The effect of the aggregate properties on drying shrinkage of concrete can be calculated by composite model in which concrete consists of cement paste and aggregate. Several different kind of coarse aggregate were used in order to verify a 3-phases composite model for drying shrinkage. Drying shrinkage and Young's modulus of cement paste, aggregate and concrete were measured. It was verified that drying shrinkage of concrete can be estimated accurately by the composite model associating with both drying shrinkage and Young's modulus of aggregate.
Aggregation-fragmentation model of robust concentration gradient formation
NASA Astrophysics Data System (ADS)
Saunders, Timothy E.
2015-02-01
Concentration gradients of signaling molecules are essential for patterning during development and they have been observed in both unicellular and multicellular systems. In subcellular systems, clustering of the signaling molecule has been observed. We develop a theoretical model of cluster-mediated concentration gradient formation based on the Becker-Döring equations of aggregation-fragmentation processes. We show that such a mechanism produces robust concentration gradients on realistic time and spatial scales so long as the process of clustering does not significantly stabilize the signaling molecule. Finally, we demonstrate that such a model is applicable to the pom1p subcellular gradient in fission yeast.
2011 Dielectric Laser Acceleration Workshop (DLA2011)
Bermel, Peter; Byer, Robert L.; Colby, Eric R.; Cowan, Benjamin M.; Dawson, Jay; England, R.Joel; Noble, Robert J.; Qi, Ming-Hao; Yoder, Rodney B.; /Manhattanville Coll., Purchase
2012-04-17
The first ICFA Mini-workshop on Dielectric Laser Accelerators was held on September 15-16, 2011 at SLAC National Accelerator Laboratory. We present the results of the Workshop, and discuss the main conclusions of the Accelerator Applications, Photonics, and Laser Technologies working groups. Over 50 participants from 4 countries participated, discussing the state of the art in photonic structures, laser science, and nanofabrication as it pertains to laser-driven particle acceleration in dielectric structures. Applications of this new and promising acceleration concept to discovery science and industrial, medical, and basic energy sciences were explored. The DLA community is presently focused on making demonstrations of high gradient acceleration and a compatible attosecond injector source - two critical steps towards realizing the potential of this technology.
Simple Statistical Model for Branched Aggregates: Application to Cooee Bitumen.
Lemarchand, Claire A; Hansen, Jesper S
2015-11-01
We propose a statistical model that can reproduce the size distribution of any branched aggregate, including amylopectin, dendrimers, molecular clusters of monoalcohols, and asphaltene nanoaggregates. It is based on the conditional probability for one molecule to form a new bond with a molecule, given that it already has bonds with others. The model is applied here to asphaltene nanoaggregates observed in molecular dynamics simulations of Cooee bitumen. The variation with temperature of the probabilities deduced from this model is discussed in terms of statistical mechanics arguments. The relevance of the statistical model in the case of asphaltene nanoaggregates is checked by comparing the predicted value of the probability for one molecule to have exactly i bonds with the same probability directly measured in the molecular dynamics simulations. The agreement is satisfactory. PMID:26458140
Influence of particle size on diffusion-limited aggregation.
Tan, Z J; Zou, X W; Zhang, W B; Jin, Z Z
1999-11-01
The influence of particle size on diffusion-limited aggregation (DLA) has been investigated by computer simulations. For DLA clusters consisting of two kinds of particles with different sizes, when large particles are in the minority, the patterns of clusters appear asymmetrical and nonuniform, and their fractal dimensions D(f) increase compared with one-component DLA. With increasing size of large particles, D(f) increases. This increase can be attributed to two reasons: one is that large particles become new growth centers; the other is the big masses of large particles. As the concentration ratio x(n) of large particles increases, D(f) will reach a maximum value D(f(m)) and then decrease. When x(n) exceeds a certain value, the morphology and D(f) of the two-component DLA clusters are similar to those of one-component DLA clusters. PMID:11970534
Aggregated Residential Load Modeling Using Dynamic Bayesian Networks
Vlachopoulou, Maria; Chin, George; Fuller, Jason C.; Lu, Shuai
2014-09-28
Abstract—It is already obvious that the future power grid will have to address higher demand for power and energy, and to incorporate renewable resources of different energy generation patterns. Demand response (DR) schemes could successfully be used to manage and balance power supply and demand under operating conditions of the future power grid. To achieve that, more advanced tools for DR management of operations and planning are necessary that can estimate the available capacity from DR resources. In this research, a Dynamic Bayesian Network (DBN) is derived, trained, and tested that can model aggregated load of Heating, Ventilation, and Air Conditioning (HVAC) systems. DBNs can provide flexible and powerful tools for both operations and planing, due to their unique analytical capabilities. The DBN model accuracy and flexibility of use is demonstrated by testing the model under different operational scenarios.
Convective aggregation in idealised models and realistic equatorial cases
NASA Astrophysics Data System (ADS)
Holloway, Chris
2015-04-01
Idealised explicit convection simulations of the Met Office Unified Model are shown to exhibit spontaneous self-aggregation in radiative-convective equilibrium, as seen previously in other models in several recent studies. This self-aggregation is linked to feedbacks between radiation, surface fluxes, and convection, and the organization is intimately related to the evolution of the column water vapour (CWV) field. To investigate the relevance of this behaviour to the real world, these idealized simulations are compared with five 15-day cases of real organized convection in the tropics, including multiple simulations of each case testing sensitivities of the convective organization and mean states to interactive radiation, interactive surface fluxes, and evaporation of rain. Despite similar large-scale forcing via lateral boundary conditions, systematic differences in mean CWV, CWV distribution shape, and the length scale of CWV features are found between the different sensitivity runs, showing that there are at least some similarities in sensitivities to these feedbacks in both idealized and realistic simulations.
Development of a Ferroelectric Based Tunable DLA Structure
Kanareykin, A.; Schoessow, P.; Jing, C.; Nenasheva, E.; Power, J. G.; Gai, W.
2009-01-22
An experimental demonstration of a tunable Dielectric Loaded Accelerating (DLA)[1] structure is planned using a nonlinear ferroelectric with temperature- or voltage-controllable permittivity. We designed and tested two prototype Ka-band double layer ferroelectric-ceramic structures (cylindrical and planar) consisting of linear ceramic layers (dielectric constant of 6.8) and BST(M) composite ferroelectric layers of 400-800 {mu}m thickness and dielectric constant of 450-550. The frequency shift by temperature variation of the cylindrical Ka-band tunable DLA of 14 MHz/ deg. K has been demonstrated leading to an overall DLA structure frequency tuning range of 140-280 MHz with 10-20 deg. K temperature variation. The Ka band prototype DLA structure demonstrated a 6 MHz frequency tuning range for a dc bias field design at 25 kV/cm field strength.
32 CFR Appendix H to Part 323 - DLA Exemption Rules
Code of Federal Regulations, 2010 CFR
2010-07-01
... PROGRAM DEFENSE LOGISTICS AGENCY PRIVACY PROGRAM Pt. 323, App. H Appendix H to Part 323—DLA Exemption Rules Exempted Records Systems. All systems of records maintained by the Defense Logistics Agency...
32 CFR Appendix H to Part 323 - DLA Exemption Rules
Code of Federal Regulations, 2011 CFR
2011-07-01
... 32 National Defense 2 2011-07-01 2011-07-01 false DLA Exemption Rules H Appendix H to Part 323... PROGRAM DEFENSE LOGISTICS AGENCY PRIVACY PROGRAM Pt. 323, App. H Appendix H to Part 323—DLA Exemption... records is exempt from the provisions of 5 U.S.C. 552a(c)(3), (d)(1) through (4), (e)(1), (e)(4)(G),...
A population balance equation model of aggregation dynamics in Taxus suspension cell cultures
Kolewe, Martin E.; Roberts, Susan C.; Henson, Michael A.
2011-01-01
The nature of plant cells to grow as multicellular aggregates in suspension culture has profound effects on bioprocess performance. Recent advances in the measurement of plant cell aggregate size allow for routine process monitoring of this property. We have exploited this capability to develop a conceptual model to describe changes in the aggregate size distribution that are observed over the course of a Taxus cell suspension batch culture. We utilized the population balance equation framework to describe plant cell aggregates as a particulate system, accounting for the relevant phenomenological processes underlying aggregation, such as growth and breakage. We compared model predictions to experimental data to select appropriate kernel functions, and found that larger aggregates had a higher breakage rate, biomass was partitioned asymmetrically following a breakage event, and aggregates grew exponentially. Our model was then validated against several data sets with different initial aggregate size distributions and was able to quantitatively predict changes in total biomass and mean aggregate size, as well as actual size distributions. We proposed a breakage mechanism where a fraction of biomass was lost upon each breakage event, and demonstrated that even though smaller aggregates have been shown to produce more paclitaxel, an optimum breakage rate was predicted for maximum paclitaxel accumulation. We believe this is the first model to use a segregated, corpuscular approach to describe changes in the size distribution of plant cell aggregates, and represents an important first step in the design of rational strategies to control aggregation and optimize process performance. PMID:21910121
A population balance equation model of aggregation dynamics in Taxus suspension cell cultures.
Kolewe, Martin E; Roberts, Susan C; Henson, Michael A
2012-02-01
The nature of plant cells to grow as multicellular aggregates in suspension culture has profound effects on bioprocess performance. Recent advances in the measurement of plant cell aggregate size allow for routine process monitoring of this property. We have exploited this capability to develop a conceptual model to describe changes in the aggregate size distribution that are observed over the course of a Taxus cell suspension batch culture. We utilized the population balance equation framework to describe plant cell aggregates as a particulate system, accounting for the relevant phenomenological processes underlying aggregation, such as growth and breakage. We compared model predictions to experimental data to select appropriate kernel functions, and found that larger aggregates had a higher breakage rate, biomass was partitioned asymmetrically following a breakage event, and aggregates grew exponentially. Our model was then validated against several datasets with different initial aggregate size distributions and was able to quantitatively predict changes in total biomass and mean aggregate size, as well as actual size distributions. We proposed a breakage mechanism where a fraction of biomass was lost upon each breakage event, and demonstrated that even though smaller aggregates have been shown to produce more paclitaxel, an optimum breakage rate was predicted for maximum paclitaxel accumulation. We believe this is the first model to use a segregated, corpuscular approach to describe changes in the size distribution of plant cell aggregates, and represents an important first step in the design of rational strategies to control aggregation and optimize process performance. PMID:21910121
Phase transition in diffusion limited aggregation with patchy particles in two dimensions
NASA Astrophysics Data System (ADS)
Kartha, Moses J.; Sayeed, Ahmed
2016-08-01
The influence of patchy interactions on diffusion-limited aggregation (DLA) has been investigated by computer simulations. In this model, the adsorption of the particle is irreversible, but the adsorption occurs only when the 'sticky patch' makes contact with the sticky patch of a previously adsorbed particle. As we vary the patch size, growth rate of the cluster decreases, and below a well-defined critical patch size, pc the steady state growth rate goes to zero. The system reaches an absorbing phase producing a non-equilibrium continuous phase transition. The order parameter close to the critical value of the patch size shows a power law behavior ρ (∞) ∼(p -pc) β, where β = 0.2840. We have found that the value of the critical exponent convincingly shows that this transition in patchy DLA belongs to the directed percolation universality class.
A model for the kinetics of homotypic cellular aggregation under static conditions
NASA Technical Reports Server (NTRS)
Neelamegham, S.; Munn, L. L.; Zygourakis, K.; McIntire, L. V. (Principal Investigator)
1997-01-01
We present the formulation and testing of a mathematical model for the kinetics of homotypic cellular aggregation. The model considers cellular aggregation under no-flow conditions as a two-step process. Individual cells and cell aggregates 1) move on the tissue culture surface and 2) collide with other cells (or aggregates). These collisions lead to the formation of intercellular bonds. The aggregation kinetics are described by a system of coupled, nonlinear ordinary differential equations, and the collision frequency kernel is derived by extending Smoluchowski's colloidal flocculation theory to cell migration and aggregation on a two-dimensional surface. Our results indicate that aggregation rates strongly depend upon the motility of cells and cell aggregates, the frequency of cell-cell collisions, and the strength of intercellular bonds. Model predictions agree well with data from homotypic lymphocyte aggregation experiments using Jurkat cells activated by 33B6, an antibody to the beta 1 integrin. Since cell migration speeds and all the other model parameters can be independently measured, the aggregation model provides a quantitative methodology by which we can accurately evaluate the adhesivity and aggregation behavior of cells.
Aggregation of Environmental Model Data for Decision Support
NASA Astrophysics Data System (ADS)
Alpert, J. C.
2013-12-01
Weather forecasts and warnings must be prepared and then delivered so as to reach their intended audience in good time to enable effective decision-making. An effort to mitigate these difficulties was studied at a Workshop, 'Sustaining National Meteorological Services - Strengthening WMO Regional and Global Centers' convened, June , 2013, by the World Bank, WMO and the US National Weather Service (NWS). The skill and accuracy of atmospheric forecasts from deterministic models have increased and there are now ensembles of such models that improve decisions to protect life, property and commerce. The NWS production of numerical weather prediction products result in model output from global and high resolution regional ensemble forecasts. Ensembles are constructed by changing the initial conditions to make a 'cloud' of forecasts that attempt to span the space of possible atmospheric realizations which can quantify not only the most likely forecast, but also the uncertainty. This has led to an unprecedented increase in data production and information content from higher resolution, multi-model output and secondary calculations. One difficulty is to obtain the needed subset of data required to estimate the probability of events, and report the information. The calibration required to reliably estimate the probability of events, and honing of threshold adjustments to reduce false alarms for decision makers is also needed. To meet the future needs of the ever-broadening user community and address these issues on a national and international basis, the weather service implemented the NOAA Operational Model Archive and Distribution System (NOMADS). NOMADS provides real-time and retrospective format independent access to climate, ocean and weather model data and delivers high availability content services as part of NOAA's official real time data dissemination at its new NCWCP web operations center. An important aspect of the server's abilities is to aggregate the matrix of
Polarimetric Models of Circumstellar Discs Including Aggregate Dust Grains
NASA Astrophysics Data System (ADS)
Mohan, Mahesh
The work conducted in this thesis examines the nature of circumstellar discs by investigating irradiance and polarization of scattered light. Two circumstellar discs are investigated. Firstly, H-band high contrast imaging data on the transitional disc of the Herbig Ae/Be star HD169142 are presented. The images were obtained through the polarimetric differential imaging (PDI) technique on the Very Large Telescope (VLT) using the adaptive optics system NACO. Our observations use longer exposure times, allowing us to examine the edges of the disc. Analysis of the observations shows distinct signs of polarization due to circumstellar material, but due to excessive saturation and adaptive optics errors further information on the disc could not be inferred. The HD169142 disc is then modelled using the 3D radiative transfer code Hyperion. Initial models were constructed using a two disc structure, however recent PDI has shown the existence of an annular gap. In addition to this the annular gap is found not to be devoid of dust. This then led to the construction of a four-component disc structure. Estimates of the mass of dust in the gap (2.10E-6 Msun) are made as well as for the planet (1.53E-5 Msun (0.016 Mjupiter)) suspected to be responsible for causing the gap. The predicted polarization was also estimated for the disc, peaking at ~14 percent. The use of realistic dust grains (ballistic aggregate particles) in Monte Carlo code is also examined. The fortran code DDSCAT is used to calculate the scattering properties for aggregates which are used to replace the spherical grain models used by the radiative transfer code Hyperion. Currently, Hyperion uses four independent elements to define the scattering matrix, therefore the use of rotational averaging and a 50/50 percent population of grains and their enantiomers were explored to reduce the number of contributing scattering elements from DDSCAT. A python script was created to extract the scattering data from the DDSCAT
A Pairwise Preferential Interaction Model for Understanding Peptide Aggregation
Kang, Myungshim
2010-01-01
A pairwise preferential interaction model (PPIM), based on Kirkwood–Buff integrals, is developed to quantify and characterize the interactions between some of the functional groups commonly observed in peptides. The existing experimental data are analyzed to determine the preferential interaction (PI) parameters for different amino acid and small peptide systems in aqueous solutions. The PIs between the different functional groups present in the peptides are then isolated and quantified by assuming simple pairwise additivity. The PPIM approach provides consistent estimates for the pair interactions between the same functional groups obtained from different solute molecules. Furthermore, these interactions appear to be chemically intuitive. It is argued that this type of approach can provide valuable information concerning specific functional group correlations which could give rise to peptide aggregation. PMID:20694045
Lattice models of peptide aggregation: evaluation of conformational search algorithms.
Oakley, Mark T; Garibaldi, Jonathan M; Hirst, Jonathan D
2005-11-30
We present a series of conformational search calculations on the aggregation of short peptide fragments that form fibrils similar to those seen in many protein mis-folding diseases. The proteins were represented by a face-centered cubic lattice model with the conformational energies calculated using the Miyazawa-Jernigan potential. The searches were performed using algorithms based on the Metropolis Monte Carlo method, including simulated annealing and replica exchange. We also present the results of searches using the tabu search method, an algorithm that has been used for many optimization problems, but has rarely been used in protein conformational searches. The replica exchange algorithm consistently found more stable structures then the other algorithms, and was particularly effective for the octamers and larger systems. PMID:16170797
Analysis of sludge aggregates produced during electrocoagulation of model wastewater.
Załęska-Chróst, B; Wardzyńska, R
2016-01-01
This paper presents the results of the study of sludge aggregates produced during electrocoagulation of model wastewater of a composition corresponding to the effluents from the cellulose and paper industry. Wastewater was electrocoagulated statically using aluminium electrodes with a current density of 31.25 A m(-2) and 62.50 A m(-2). In subsequent stages of the treatment, sludge flocs were collected, their size was studied and their floc settling velocity (30-520 μm s(-1)) and fractal dimension (D) were determined. The values of D ranged from 1.53 to 1.95 and were directly proportional to the degree of wastewater treatment. Higher values of D were determined for sludge with lower water content (after 24 hours' settling). Fractal dimension can therefore be used as an additional parameter of wastewater treatment control. PMID:26744947
Modeling aggregation of dust monomers in low gravity environments
NASA Astrophysics Data System (ADS)
Doyon, Julien; Rioux, Claude
The modeling of aggregation phenomena in microgravity is of paramount relevance to the understanding of the formation of planets. Relevant experiments have been carried out at a ground based laboratory and on aircraft providing low gravity during parabolic flight.1 Other possible environments are rockets, shuttles and the international space station. Numerical simulation of aggregation can provide us a tool to understand the formal and the-oretical background of the phenomena. The comparison between low gravity experiment and modeling prediction may confirm a theory. Also, experiments that are hard to perform can be simulated on computers allowing a vast choice of physical properties. Simulations to date have been constrained to ensembles of 100 to 1000 monomers.2 We have been able to extend such numbers to 10 000 monomers and the final goal is about 100 000 monomers, where gravitational effects become relevant yielding spheroidal systems of particles (planetesimals and planetoids). Simulations made are assumed to be diffusion processes where colliding particles will stick together with a certain probability. Future work shall include other interactions like electrostatic or magnetic forces. Recent results are to be shown at the meeting. I acknowledge the support from the ELIPS program (jointly between Canadian and European space agencies). The guidance of Prof. Slobodrian is warmly thanked. References. 1. R.J. Slobodrian, C. Rioux and J.-C. Leclerc, Microgravity Research and Aplications in Phys-ical Sciences and Biotechnology, Proceedings of the First International Symposium, Sorrento, Italy (2000) ESA SP-454, p.779-786. and Refs. therein. 2. P. Deladurantaye, C Rioux and R.J Slobodrian, Chaos, Solitons Fractals , (1997), pp. 1693-1708. Carl Robert and Eric Litvak, Software " Fractal", private communication.
Diffusion-Limited Aggregation with Polygon Particles
NASA Astrophysics Data System (ADS)
Deng, Li; Wang, Yan-Ting; Ou-Yang, Zhong-Can
2012-12-01
Diffusion-limited aggregation (DLA) assumes that particles perform pure random walk at a finite temperature and aggregate when they come close enough and stick together. Although it is well known that DLA in two dimensions results in a ramified fractal structure, how the particle shape influences the formed morphology is still unclear. In this work, we perform the off-lattice two-dimensional DLA simulations with different particle shapes of triangle, quadrangle, pentagon, hexagon, and octagon, respectively, and compare with the results for circular particles. Our results indicate that different particle shapes only change the local structure, but have no effects on the global structure of the formed fractal cluster. The local compactness decreases as the number of polygon edges increases.
A deterministic aggregate production planning model considering quality of products
NASA Astrophysics Data System (ADS)
Madadi, Najmeh; Yew Wong, Kuan
2013-06-01
Aggregate Production Planning (APP) is a medium-term planning which is concerned with the lowest-cost method of production planning to meet customers' requirements and to satisfy fluctuating demand over a planning time horizon. APP problem has been studied widely since it was introduced and formulated in 1950s. However, in several conducted studies in the APP area, most of the researchers have concentrated on some common objectives such as minimization of cost, fluctuation in the number of workers, and inventory level. Specifically, maintaining quality at the desirable level as an objective while minimizing cost has not been considered in previous studies. In this study, an attempt has been made to develop a multi-objective mixed integer linear programming model that serves those companies aiming to incur the minimum level of operational cost while maintaining quality at an acceptable level. In order to obtain the solution to the multi-objective model, the Fuzzy Goal Programming approach and max-min operator of Bellman-Zadeh were applied to the model. At the final step, IBM ILOG CPLEX Optimization Studio software was used to obtain the experimental results based on the data collected from an automotive parts manufacturing company. The results show that incorporating quality in the model imposes some costs, however a trade-off should be done between the cost resulting from producing products with higher quality and the cost that the firm may incur due to customer dissatisfaction and sale losses.
de Miguel, Gustavo; Martín-Romero, María T; Pedrosa, José M; Muñoz, Eulogia; Pérez-Morales, Marta; Richardson, Tim H; Camacho, Luis
2008-03-21
In this paper, the different aggregation modes of a water-insoluble porphyrin (EHO) mixed with an amphiphilic calix[8]arene (C8A), at the air-water interface and in Langmuir-Blodgett (LB) film form, are analyzed as a function of the mixed composition. The strategy used to control the EHO aggregation has consisted of preparing mixed thin films containing EHO and C8A, in different ratios, at the air-water interface. Therefore, the increase of the C8A molar ratio in the mixed film diminishes the aggregation of the EHO molecules, although such an effect must be exclusively related to the dilution of the porphyrin. The reflection spectra of the mixed C8A-EHO films registered at the air-water interface, show a complex Soret band exhibiting splitting, hypochromicity and broadening features. Also, during the transfer process at high surface pressure, it has been shown that the EHO molecules are ejected from the C8A monolayer and only a fraction of porphyrin is transferred to the solid support, in spite of a complete transfer for the C8A matrix. The complex structure of the reflection spectra at the air-water interface, as well as the polarization dependence of the absorption spectra for the mixed LB films, indicate the existence of four different arrangements for the EHO hosted in the C8A matrix. The aggregate formation is governed by two factors: the attraction between the porphyrin rings which minimizes their separation, and the alkyl chain interactions, that is, hydrophobic effect and/or steric hindrance which determine and restrict the possible aggregation structures. By using the extended dipole model, the assignment of the spectral peaks observed to different EHO aggregates is shown. PMID:18327313
Electromechanical properties of smart aggregate: theoretical modeling and experimental validation
NASA Astrophysics Data System (ADS)
Wang, Jianjun; Kong, Qingzhao; Shi, Zhifei; Song, Gangbing
2016-09-01
Smart aggregate (SA), as a piezoceramic-based multi-functional device, is formed by sandwiching two lead zirconate titanate (PZT) patches with copper shielding between a pair of solid-machined cylindrical marble blocks with epoxy. Previous researches have successfully demonstrated the capability and reliability of versatile SAs to monitor the structural health of concrete structures. However, the previous works concentrated mainly on the applications of SAs in structural health monitoring; no reasonable theoretical model of SAs was proposed. In this paper, electromechanical properties of SAs were investigated using a proposed theoretical model. Based on one dimensional linear theory of piezo-elasticity, the dynamic solutions of a SA subjected to an external harmonic voltage were solved. Further, the electric impedance of the SA was computed, and the resonance and anti-resonance frequencies were calculated based on derived equations. Numerical analysis was conducted to discuss the effects of the thickness of epoxy layer and the dimension of PZT patch on the fundamental resonance and anti-resonance frequencies as well as the corresponding electromechanical coupling factor. The dynamic solutions based on the proposed theoretical model were further experimentally verified with two SA samples. The fundamental resonance and anti-resonance frequencies of SAs show good agreements in both theoretical and experimental results. The presented analysis and results contribute to the overall understanding of SA properties and help to optimize the working frequencies of SAs in structural health monitoring of civil structures.
Generic Coarse-Grained Model for Protein Folding and Aggregation
NASA Astrophysics Data System (ADS)
Bereau, Tristan; Deserno, Markus
2009-03-01
The complexity involved in protein structure is not only due to the rich variety of amino acids, but also the inherent weak interactions, comparable to thermal energy, and important cooperative phenomena. This presents a challenge in atomistic simulations, as it is associated with high-dimensionality and ruggedness of the energy landscape as well as long equilibration times. We have recently developed a coarse-grained (CG) implicit solvent peptide model which has been designed to reproduce key consequences of the abovementioned weak interactions. Its intermediate level of resolution, four beads per amino acid, allows for accurate sampling of local conformations by designing a force field that relies on simple interactions. A realistic ratio of α-helix to β-sheet content is achieved by mimicking a nearest-neighbor dipole interaction. We tune the model in order to fold helical proteins while systematically comparing the structure with NMR data. Very good agreement is achieved for proteins that have simple tertiary structures. We further probe the effects of cooperativity between amino acids by looking at peptide aggregation, where hydrophobic peptide fragments cooperatively form large-scale β-sheet structures. The model is able to reproduce features from atomistic simulations on a qualitative basis.
Fatouros, Chronis; Pir, Ghulam Jeelani; Biernat, Jacek; Koushika, Sandhya Padmanabhan; Mandelkow, Eckhard; Mandelkow, Eva-Maria; Schmidt, Enrico; Baumeister, Ralf
2012-08-15
Increased Tau protein amyloidogenicity has been causatively implicated in several neurodegenerative diseases, collectively called tauopathies. In pathological conditions, Tau becomes hyperphosphorylated and forms intracellular aggregates. The deletion of K280, which is a mutation that commonly appears in patients with frontotemporal dementia with Parkinsonism linked to chromosome 17, enhances Tau aggregation propensity (pro-aggregation). In contrast, introduction of the I277P and I308P mutations prevents β-sheet formation and subsequent aggregation (anti-aggregation). In this study, we created a tauopathy model by expressing pro- or anti-aggregant Tau species in the nervous system of Caenorhabditis elegans. Animals expressing the highly amyloidogenic Tau species showed accelerated Tau aggregation and pathology manifested by severely impaired motility and evident neuronal dysfunction. In addition, we observed that the axonal transport of mitochondria was perturbed in these animals. Control animals expressing the anti-aggregant combination had rather mild phenotype. We subsequently tested several Tau aggregation inhibitor compounds and observed a mitigation of Tau proteotoxicity. In particular, a novel compound that crosses the blood-brain barrier of mammals proved effective in ameliorating the motility as well as delaying the accumulation of neuronal defects. Our study establishes a new C. elegans model of Tau aggregation-mediated toxicity and supports the emerging notion that inhibiting the nucleation of Tau aggregation can be neuroprotective. PMID:22611162
Aggregation, stability, and oscillations in different models for host-macroparasite interactions.
Rosà, Roberto; Pugliese, Andrea
2002-05-01
Aggregation is generally recognized as an important factor in the dynamics of host-macroparasite interactions and it has been found relevant in stabilizing the dynamics toward an equilibrium coexistence. In this paper we review the models of Anderson and May (1978, J. Anim. Ecol. 47, 219-247, 249-267) and compare them with some more recently developed models, which incorporate explicit mechanisms (multiple infections or host heterogeneity) for generating aggregation and different degrees of mathematical accuracy. We found that the stabilization yielded by aggregation depends strongly on the mechanism producing the aggregation: multiple infections are much less stabilizing than when aggregation is assumed to be fixed from the outside, while the opposite holds for host heterogeneity. We also give analytical estimates of the period of oscillations occurring when the equilibrium is unstable. Finally, we explore in these models the role of aggregation in host regulation and in determining a threshold value for parasite establishment. PMID:12027618
Multifractal analysis of the branch structure of diffusion-limited aggregates
NASA Astrophysics Data System (ADS)
Hanan, W. G.; Heffernan, D. M.
2012-02-01
We examine the branch structure of radial diffusion-limited aggregation (DLA) clusters for evidence of multifractality. The lacunarity of DLA clusters is measured and the generalized dimensions D(q) of their mass distribution is estimated using the sandbox method. We find that the global n-fold symmetry of the aggregates can induce anomalous scaling behavior into these measurements. However, negating the effects of this symmetry, standard scaling is recovered.
Multifractal analysis of the branch structure of diffusion-limited aggregates.
Hanan, W G; Heffernan, D M
2012-02-01
We examine the branch structure of radial diffusion-limited aggregation (DLA) clusters for evidence of multifractality. The lacunarity of DLA clusters is measured and the generalized dimensions D(q) of their mass distribution is estimated using the sandbox method. We find that the global n-fold symmetry of the aggregates can induce anomalous scaling behavior into these measurements. However, negating the effects of this symmetry, standard scaling is recovered. PMID:22463212
Kramer, Andrew M; Lyons, M Maille; Dobbs, Fred C; Drake, John M
2013-01-01
Organic aggregates provide a favorable habitat for aquatic microbes, are efficiently filtered by shellfish, and may play a major role in the dynamics of aquatic pathogens. Quantifying this role requires understanding how pathogen abundance in the water and aggregate size interact to determine the presence and abundance of pathogen cells on individual aggregates. We build upon current understanding of the dynamics of bacteria and bacterial grazers on aggregates to develop a model for the dynamics of a bacterial pathogen species. The model accounts for the importance of stochasticity and the balance between colonization and extinction. Simulation results suggest that while colonization increases linearly with background density and aggregate size, extinction rates are expected to be nonlinear on small aggregates in a low background density of the pathogen. Under these conditions, we predict lower probabilities of pathogen presence and reduced abundance on aggregates compared with predictions based solely on colonization. These results suggest that the importance of aggregates to the dynamics of aquatic bacterial pathogens may be dependent on the interaction between aggregate size and background pathogen density, and that these interactions are strongly influenced by ecological interactions and pathogen traits. The model provides testable predictions and can be a useful tool for exploring how species-specific differences in pathogen traits may alter the effect of aggregates on disease transmission. PMID:24340173
Convectively Aggregated Structures Across a Hierarchy of Models
NASA Astrophysics Data System (ADS)
Silvers, Levi; Dipankar, Anurag; Hohenegger, Cathy
2015-04-01
Convective clouds are among the most interesting and poorest understood atmospheric phenomena. This study explores the interaction between deep convection and the lower troposphere with a focus on the coupling of deep convection to the lower tropospheric clouds, water vapor, and relative humidity. We are particularly interested in the controlling factors of the cloud amount and cloud size at cloud base across various model set-ups. In particular we seek to determine how the generation of large convective structures depends on the characteristics of the lower troposphere and parameterization choices. Our experiments are analyzed by comparing the mean state, the probability distribution functions of particular quantities, and snapshots in time of the spatial distribution of cloud related fields. It is shown that the formation of aggregated convective structures depends on the different model setups. Experiments performed using an NWP model (ICON-NWP) and two cloud-resolving models (ICON-LES and UCLA-LES) are compared. The ICOsahedral Nonhydrostatic (ICON) model is used to provide a unified modeling framework in which both the NWP and CRM versions use the same dynamical core but different physics packages. This allows for a fair comparison between the GCM and CRM and leads to a better understanding of both. To check the robustness of the CRM results we also compare the ICON experiments with the UCLA-LES model. The initial analysis looks at the ICON-NWP and both CRM experiments with a uniform domain size of (1800 km)2 and doubly periodic boundary conditions to determine some of the fundamental differences between the models. The NWP experiment has an effective resolution of 13.5 km while the CRM's have resolutions in the range of 5 km. We run the NWP experiments with the full suit of physics parameterizations as well as with the convection turned off. Further sensitivity studies are then made to isolate some of the key characteristics of the convection in each model
Accurate modelling of flow induced stresses in rigid colloidal aggregates
NASA Astrophysics Data System (ADS)
Vanni, Marco
2015-07-01
A method has been developed to estimate the motion and the internal stresses induced by a fluid flow on a rigid aggregate. The approach couples Stokesian dynamics and structural mechanics in order to take into account accurately the effect of the complex geometry of the aggregates on hydrodynamic forces and the internal redistribution of stresses. The intrinsic error of the method, due to the low-order truncation of the multipole expansion of the Stokes solution, has been assessed by comparison with the analytical solution for the case of a doublet in a shear flow. In addition, it has been shown that the error becomes smaller as the number of primary particles in the aggregate increases and hence it is expected to be negligible for realistic reproductions of large aggregates. The evaluation of internal forces is performed by an adaptation of the matrix methods of structural mechanics to the geometric features of the aggregates and to the particular stress-strain relationship that occurs at intermonomer contacts. A preliminary investigation on the stress distribution in rigid aggregates and their mode of breakup has been performed by studying the response to an elongational flow of both realistic reproductions of colloidal aggregates (made of several hundreds monomers) and highly simplified structures. A very different behaviour has been evidenced between low-density aggregates with isostatic or weakly hyperstatic structures and compact aggregates with highly hyperstatic configuration. In low-density clusters breakup is caused directly by the failure of the most stressed intermonomer contact, which is typically located in the inner region of the aggregate and hence originates the birth of fragments of similar size. On the contrary, breakup of compact and highly cross-linked clusters is seldom caused by the failure of a single bond. When this happens, it proceeds through the removal of a tiny fragment from the external part of the structure. More commonly, however
Burov, S V; Shchekin, A K
2010-12-28
General thermodynamic relations for the work of polydisperse micelle formation in the model of ideal solution of molecular aggregates in nonionic surfactant solution and the model of "dressed micelles" in ionic solution have been considered. In particular, the dependence of the aggregation work on the total concentration of nonionic surfactant has been analyzed. The analogous dependence for the work of formation of ionic aggregates has been examined with regard to existence of two variables of a state of an ionic aggregate, the aggregation numbers of surface active ions and counterions. To verify the thermodynamic models, the molecular dynamics simulations of micellization in nonionic and ionic surfactant solutions at two total surfactant concentrations have been performed. It was shown that for nonionic surfactants, even at relatively high total surfactant concentrations, the shape and behavior of the work of polydisperse micelle formation found within the model of the ideal solution at different total surfactant concentrations agrees fairly well with the numerical experiment. For ionic surfactant solutions, the numerical results indicate a strong screening of ionic aggregates by the bound counterions. This fact as well as independence of the coefficient in the law of mass action for ionic aggregates on total surfactant concentration and predictable behavior of the "waterfall" lines of surfaces of the aggregation work upholds the model of "dressed" ionic aggregates. PMID:21197978
Rainfall variability effects on aggregate crop model predictions
NASA Astrophysics Data System (ADS)
Dzotsi, Kofikuma Adzewoda
Crop production operates in a highly heterogeneous environment. Space-time variability in weather and spatial heterogeneity in soil and management generate variability in crop yield. While it is practically unfeasible to thoroughly sample the variability of the crop environment, quantification of the associated uncertainties in crop performance can provide vital information for decision-making. The present study used rainfall data collected in southwestern Georgia at scales ranging from 1 km to 60 km to assess the effect of weather variability (in particular rainfall) on crop predictions aggregated over soil and management variations. The simple SALUS (System Approach to Land Use Sustainability) crop model was integrated in DSSAT (Decision Support System for Agrotechnology Transfer) then parameterized and tested for maize, peanut and cotton for use in obtaining the crop predictions. Analysis of the rainfall data indicated that variability in storm characteristics depends upon the season. Winter rainfall was more correlated at a mean distance of 54 km between locations than summer rainfall was at a mean distance of 3 km. The pairwise correlation between locations decreased with distance faster in the summer than in the winter. This rainfall variability translated into crop yield variability in the study area (about 3100 km²). It was found that weather variability explained 60% and 49% of maize yield variability respectively in 2010 and 2011 when heterogeneity in weather, soil, cultivar and planting dates were accounted for simultaneously. Uncertainties in crop predictions due to rainfall spatial uncertainty decreased as the number of sites where weather data were collected increased. Expressed in terms of maize yield coefficient of variation, this uncertainty decreased exponentially from 27% to approximately 4% at a sampling density of 20 weather locations. Based on 30 years of generated weather data, it was concluded that the general form of the relationship
Risk analysis of nuclear safeguards regulations. [Aggregated Systems Model (ASM)
Al-Ayat, R.A.; Altman, W.D.; Judd, B.R.
1982-06-01
The Aggregated Systems Model (ASM), a probabilisitic risk analysis tool for nuclear safeguards, was applied to determine benefits and costs of proposed amendments to NRC regulations governing nuclear material control and accounting systems. The objective of the amendments was to improve the ability to detect insiders attempting to steal large quantities of special nuclear material (SNM). Insider threats range from likely events with minor consequences to unlikely events with catastrophic consequences. Moreover, establishing safeguards regulations is complicated by uncertainties in threats, safeguards performance, and consequences, and by the subjective judgments and difficult trade-offs between risks and safeguards costs. The ASM systematically incorporates these factors in a comprehensive, analytical framework. The ASM was used to evaluate the effectiveness of current safeguards and to quantify the risk of SNM theft. Various modifications designed to meet the objectives of the proposed amendments to reduce that risk were analyzed. Safeguards effectiveness was judged in terms of the probability of detecting and preventing theft, the expected time to detection, and the expected quantity of SNM diverted in a year. Data were gathered in tours and interviews at NRC-licensed facilities. The assessment at each facility was begun by carefully selecting scenarios representing the range of potential insider threats. A team of analysts and facility managers assigned probabilities for detection and prevention events in each scenario. Using the ASM we computed the measures of system effectiveness and identified cost-effective safeguards modifications that met the objectives of the proposed amendments.
Yang, Yihui; Corona, Alessandro; Henson, Michael A
2012-05-15
Solid lipid nanoparticles (SLNs) have applications in drug delivery and the encapsulation of bioactive, lipophilic compounds. However, SLNs tend to aggregate when stored due to the lipid crystals undergoing a polymorphic transformation from the unstable α form to the stable β form. We developed a population balance equation (PBE) model for prediction of average polymorph content and aggregate size distribution to better understand this undesirable behavior. Experiments with SLNs stored at room temperature showed that polymorphic transformation was the rate determining step for our system, SLNs with smaller initial size distributions aggregated more rapidly, and aggregates contained particles with both α and β crystals. Using parameter values estimated from our data, the PBE model was able to capture the bimodal nature of aggregate size distributions, the α-to-β polymorph ratio, and the faster aggregation dynamics of SLNs with smaller initial size distributions. However, the model was unable to adequately capture the fast disappearance rate of primary particles, the broad size distributions of formed aggregates, and the significant α content of aggregating particles. These discrepancies suggest that a PBE model which accounts for polymorph content as an internal variable along with aggregate size may be required to better reproduce experimental observations. PMID:22405582
32 CFR Appendix A to Part 300 - Access to DLA Records
Code of Federal Regulations, 2014 CFR
2014-07-01
... stockpile that supports national defense needs. (iii) DLA Europe & Africa, Kaiserslautern, Germany—Focal point for U.S. European Command's and U.S. Africa Command's theater of operations. (iv) DLA...
Diffusion-limited aggregation on curved surfaces
NASA Astrophysics Data System (ADS)
Choi, J.; Crowdy, D.; Bazant, M. Z.
2010-08-01
We develop a general theory of transport-limited aggregation phenomena occurring on curved surfaces, based on stochastic iterated conformal maps and conformal projections to the complex plane. To illustrate the theory, we use stereographic projections to simulate diffusion-limited aggregation (DLA) on surfaces of constant Gaussian curvature, including the sphere (K>0) and the pseudo-sphere (K<0), which approximate "bumps" and "saddles" in smooth surfaces, respectively. Although the curvature affects the global morphology of the aggregates, the fractal dimension (in the curved metric) is remarkably insensitive to curvature, as long as the particle size is much smaller than the radius of curvature. We conjecture that all aggregates grown by conformally invariant transport on curved surfaces have the same fractal dimension as DLA in the plane. Our simulations suggest, however, that the multifractal dimensions increase from hyperbolic (K<0) to elliptic (K>0) geometry, which we attribute to curvature-dependent screening of tip branching.
Anisotropic diffusion-limited aggregation.
Popescu, M N; Hentschel, H G E; Family, F
2004-06-01
Using stochastic conformal mappings, we study the effects of anisotropic perturbations on diffusion-limited aggregation (DLA) in two dimensions. The harmonic measure of the growth probability for DLA can be conformally mapped onto a constant measure on a unit circle. Here we map m preferred directions for growth to a distribution on the unit circle, which is a periodic function with m peaks in [-pi,pi) such that the angular width sigma of the peak defines the "strength" of anisotropy kappa= sigma(-1) along any of the m chosen directions. The two parameters (m,kappa) map out a parameter space of perturbations that allows a continuous transition from DLA (for small enough kappa ) to m needlelike fingers as kappa--> infinity. We show that at fixed m the effective fractal dimension of the clusters D(m,kappa) obtained from mass-radius scaling decreases with increasing kappa from D(DLA) approximately 1.71 to a value bounded from below by D(min) = 3 / 2. Scaling arguments suggest a specific form for the dependence of the fractal dimension D(m,kappa) on kappa for large kappa which compares favorably with numerical results. PMID:15244564
NASA Astrophysics Data System (ADS)
Pink, David A.; Peyronel, Fernanda; Quinn, Bonnie; Singh, Pratham; Marangoni, Alejandro G.
2015-09-01
Understanding how solid fats structures come about in edible oils and quantifying their structures is of fundamental importance in developing edible oils with pre-selected characteristics. We considered the great range of fractal dimensions, from 1.91 to 2.90, reported from rheological measurements. We point out that, if the structures arise via DLA/RLA or DLCA/RLCA, as has been established using ultra small angle x-ray scattering (USAXS), we would expect fractal dimensions in the range ~1.7 to 2.1, and ~2.5 or ~3.0. We present new data for commercial fats and show that the fractal dimensions deduced lie outside these values. We have developed a model in which competition between two processes can lead to the range of fractal dimensions observed. The two processes are (i) the rate at which the solid fat particles are created as the temperature is decreased, and (ii) the rate at which these particles diffuse, thereby meeting and forming aggregates. We assumed that aggregation can take place essentially isotropically and we identified two characteristic times: a time characterizing the rate of creation of solid fats, {τ\\text{create}}(T)\\equiv 1/{{R}S}(T) , where {{R}S}(T) is the rate of solid condensation (cm3 s-1), and the diffusion time of solid fats, {τ\\text{diff}}≤ft(T,{{c}S}\\right)=< {{r}2}> /6{D}≤ft(T,{{c}S}\\right) , where {D}≤ft(T,{{c}S}\\right) is their diffusion coefficient and < {{r}2}> is the typical average distance that fats must move in order to aggregate. The intent of this model is to show that a simple process can lead to a wide range of fractal dimensions. We showed that in the limit of very fast solid creation, {τ\\text{create}}\\ll {τ\\text{diff}} the fractal dimension is predicted to be that of DLCA, ~1.7, relaxing to that of RLCA, 2.0-2.1, and that in the limit of very slow solid creation, {τ\\text{create}}\\gg {τ\\text{diff}} , the fractal dimension is predicted to be that obtained via DLA, ~2.5, relaxing to that of RLA, 3
32 CFR Appendix A to Part 1285 - Gaining Access to DLA Records
Code of Federal Regulations, 2012 CFR
2012-07-01
..., directives, and instructions. DLA is made up of a headquarters and 22 Primary Level Field Activities (PLFA's... DLA-XAM. II. Description of DLA's Central and Field Organization A. HQ Defense Logistics Agency..., Wright-Patterson AFB, OH 45433-5000....
AVAILABLE MICRO-ACTIVITY DATA AND THEIR APPLICABILITY TO AGGREGATE EXPOSURE MODELING
Several human exposure models have been developed in recent years to address children's aggregate and cumulative exposures to pesticides under the Food Quality Protection Act of 1996. These models estimate children's exposures via all significant routes and pathways including ...
Model simulations of particle aggregation effect on colloid exchange between streams and streambeds.
Areepitak, Trachu; Ren, Jianhong
2011-07-01
Colloids found in natural streams have large reactive surface areas, which makes them significant absorbents and carriers for pollutants. Stream-subsurface exchange plays a critical role in regulating the transport of colloids and contaminants in natural streams. Previous process-based multiphase exchange models were developed without consideration of colloid-colloid interaction. However, many studies have indicated that aggregation is a significant process and needs to be considered in stream process analysis. Herein, a new colloid exchange model was developed by including particle aggregation in addition to colloid settling and filtration. Self-preserving size distribution concepts and classical aggregation theory were employed to model the aggregation process. Model simulations indicate that under conditions of low filtration and high degree of particle-particle interaction, aggregation could either decrease or increase the amount of colloids retained in streambeds, depending on the initial particle size. Thus, two possible cases may occur including enhanced colloid deposition and facilitated colloid transport. Also, when the aggregation rate is high and filtration increases, more particles are retained by bed sediments due to filtration, and fewer are aggregated, which reduces the extent of aggregation effect on colloid deposition. The work presented here will contribute to a better understanding and prediction of colloid transport phenomena in natural streams. PMID:21627165
32 CFR Appendix H to Part 323 - DLA Exemption Rules
Code of Federal Regulations, 2012 CFR
2012-07-01
... PROGRAM DEFENSE LOGISTICS AGENCY PRIVACY PROGRAM Pt. 323, App. H Appendix H to Part 323—DLA Exemption Rules Exempted Records Systems. All systems of records maintained by the Defense Logistics Agency will.... b. ID: S500.20 (Specific exemption). 1. System name: Defense Logistics Agency Criminal...
Typology of Empirical Attributes: Dissimilarity Linkage Analysis (DLA).
ERIC Educational Resources Information Center
Dubin, Robert; Champoux, Joseph E.
Dissimilarity Linkage Analysis (DLA) is an extremely simple procedure for developing a typology from empirical attributes that permits the clustering of entities. First the procedure develops a taxonomy of types from empirical attributes possessed by entities in the sample. Second, the procedure assigns entities to one, and only one, type in the…
Is it really possible to grow isotropic on-lattice diffusion-limited aggregates?
NASA Astrophysics Data System (ADS)
Alves, S. G.; Ferreira, S. C., Jr.
2006-03-01
In a recent paper (Bogoyavlenskiy V A 2002 J. Phys. A: Math. Gen. 35 2533), an algorithm aiming to generate isotropic clusters of the on-lattice diffusion-limited aggregation (DLA) model was proposed. The procedure consists of aggregation probabilities proportional to the squared number of occupied sites (k2). In the present work, we analysed this algorithm using the noise reduced version of the DLA model and large-scale simulations. In the noiseless limit, instead of isotropic patterns, a 45° (30°) rotation in the anisotropy directions of the clusters grown on square (triangular) lattices was observed. A generalized algorithm, in which the aggregation probability is proportional to kν, was proposed. The exponent ν has a nonuniversal critical value νc, for which the patterns generated in the noiseless limit exhibit the original (axial) anisotropy for ν < νc and the rotated one (diagonal) for ν > νc. The values νc = 1.395 ± 0.005 and νc = 0.82 ± 0.01 were found for square and triangular lattices, respectively. Moreover, large-scale simulations show that there is a nontrivial relation between the noise reduction and anisotropy direction. The case ν = 2 (Bogoyavlenskiy's rule) is an example where the patterns exhibit the axial anisotropy for small and the diagonal one for large noise reduction.
CUMULATIVE AND AGGREGATE RISK EVALUATION SYSTEM (CARES) MODEL REVIEW
Technology Transfer Automated Retrieval System (TEKTRAN)
The 1996 Food Quality Protection Act (FQPA) changed the way the U.S. Environmental Protection Agency (USEPA) assesses risks of pesticide use. Both cumulative and aggregate exposures must now be considered. They are cumulative since consumption of residues in food and drinking water and incidental co...
Reduced-Order Modeling of Aggregated Thermostatic Loads With Demand Response
Zhang, Wei; Lian, Jianming; Chang, Chin-Yao; Kalsi, Karanjit; Sun, Yannan
2012-12-12
Demand Response is playing an increasingly important role in smart grid control strategies. Modeling the behavior of populations of appliances under demand response is especially important to evaluate the effectiveness of these demand response programs. In this paper, an aggregated model is proposed for a class of Thermostatically Controlled Loads (TCLs). The model efficiently includes statistical information of the population, systematically deals with heterogeneity, and accounts for a second-order effect necessary to accurately capture the transient dynamics in the collective response. However, an accurate characterization of the collective dynamics however requires the aggregate model to have a high state space dimension. Most of the existing model reduction techniques require the stability of the underlying system which does not hold for the proposed aggregated model. In this work, a novel model reduction approach is developed for the proposed aggregated model, which can significantly reduce its complexity with small performance loss. The original and the reducedorder aggregated models are validated against simulations of thousands of detailed building models using GridLAB-D, which is a realistic open source distribution simulation software. Index Terms – demand response, aggregated model, ancillary
Using Human iPSC-Derived Neurons to Model TAU Aggregation
Verheyen, An; Diels, Annick; Dijkmans, Joyce; Oyelami, Tutu; Meneghello, Giulia; Mertens, Liesbeth; Versweyveld, Sofie; Borgers, Marianne; Buist, Arjan; Peeters, Pieter; Cik, Miroslav
2015-01-01
Alzheimer’s disease and frontotemporal dementia are amongst the most common forms of dementia characterized by the formation and deposition of abnormal TAU in the brain. In order to develop a translational human TAU aggregation model suitable for screening, we transduced TAU harboring the pro-aggregating P301L mutation into control hiPSC-derived neural progenitor cells followed by differentiation into cortical neurons. TAU aggregation and phosphorylation was quantified using AlphaLISA technology. Although no spontaneous aggregation was observed upon expressing TAU-P301L in neurons, seeding with preformed aggregates consisting of the TAU-microtubule binding repeat domain triggered robust TAU aggregation and hyperphosphorylation already after 2 weeks, without affecting general cell health. To validate our model, activity of two autophagy inducers was tested. Both rapamycin and trehalose significantly reduced TAU aggregation levels suggesting that iPSC-derived neurons allow for the generation of a biologically relevant human Tauopathy model, highly suitable to screen for compounds that modulate TAU aggregation. PMID:26720731
Linear relationship statistics in diffusion limited aggregation
NASA Astrophysics Data System (ADS)
Saberi, Abbas Ali
2009-11-01
We show that various surface parameters in two-dimensional diffusion limited aggregation (DLA) grow linearly with the number of particles. We find the ratio of the average length of the perimeter and the accessible perimeter of a DLA cluster together with its external perimeters to the cluster size, and define a microscopic schematic procedure for attachment of an incident new particle to the cluster. We measure the fractal dimension of the red sites (i.e., the sites such that cutting each of them splits the cluster) as equal to that of the DLA cluster. It is also shown that the average number of dead sites and the average number of red sites have linear relationships with the cluster size.
Simulation of Ionic Aggregation and Ion Dynamics in Model Ionomers
NASA Astrophysics Data System (ADS)
Frischknecht, Amalie L.
2012-02-01
Ionomers, polymers containing a small fraction of covalently bound ionic groups, are of interest as possible electrolytes in batteries. A single-ion conducting polymer electrolyte would be safer and have higher efficiency than the currently-used liquid electrolytes. However, to date ionomeric materials do not have sufficiently high conductivities for practical application. This is most likely because the ions tend to form aggregates, leading to slow ion transport. A key question is therefore how molecular structure affects the ionic aggregation and ion dynamics. To probe these structure-property relationships, we have performed molecular simulations of a set of recently synthesized poly(ethylene-co-acrylic acid) copolymers and ionomers, with a focus on the morphology of the ionic aggregates. The ionomers have a precise, constant spacing of charged groups, making them ideal for direct comparisons with simulations. Ab initio calculations give insight into the expected coordination of cations with fragments of the ionomers. All-atom molecular dynamics (MD) simulations of the ionomer melt show aggregation of the ionic groups into extended string-like clusters. An extensive set of coarse-grained molecular dynamics simulations extend the results to longer times and larger length scales. The structure factors calculated from the MD simulations compare favorably with x-ray scattering data. Furthermore, the simulations give a detailed picture of the sizes, shapes, and composition of the ionic aggregates, and how they depend on polymer architecture. Implications for ion transport will be discussed. [Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.
Integrating service-life modeling and life-cycle assessment for recycled-aggregate concrete
NASA Astrophysics Data System (ADS)
Bergman, Todd Lee
The development and implementation of one-dimensional (a) analytical and (b) numerical service-life models for chloride-induced corrosion of reinforced concrete containing both recycled-aggregates and supplementary cementitious materials (SCMs) are presented in this work. Both the analytical and numerical models account for initial chloride contamination levels due to previous applications. The effects of aggregate type (e.g., virgin, recycled aggregate, recycled mortar), aggregate replacement ratio, severity of chloride contamination levels, severity of in-service chloride exposure, reinforcement cover depth, SCM type (e.g., fly ash, slag, slice fume, metakaolin), and SCM replacement ratio on the expected service life of recycled-aggregate reinforced concrete were investigated. Results illustrated trends between concrete mixes and life cycle costs, which were employed to make conclusions on the trade-offs presented by cost, sustainability, and service life.
Towards an operational implementation of particle aggregation in ash dispersion models (Invited)
NASA Astrophysics Data System (ADS)
Mastin, L. G.; Van Eaton, A. R.; Durant, A. J.; Schwaiger, H. F.; Denlinger, R. P.
2013-12-01
During volcanic unrest, ash transport models are used by volcano observatories and civil protection authorities to forecast areas at risk from tephra deposition. These models can effectively forecast areas affected due to their reliance on modern numerical wind fields. But they cannot yet accurately forecast the mass distribution in deposits, due largely to one process--particle aggregation--that is not considered in most models. Aggregation rates vary with particle concentration, size distribution, and the amount and phases of water present. Relationships between these variables are not yet well quantified. Although modeling studies have reproduced the observed distribution of tephra deposits from several key eruptions, most have done so only a posteriori, through ad-hoc adjustments in grain-size distribution or settling velocity. Here, we report early attempts to incorporate aggregation into the transport and deposition model Ash3d in a simplified form that can be implemented operationally. This project includes three steps: (1) characterizing aggregate size and abundance starting from deposit measurements at Mount St. Helens, Redoubt, and Spurr volcanoes; (2) developing a scheme to characterize aggregation using 2 or 3 parameters whose values can be ascertained for atmospheric and source conditions; and (3) incorporating the scheme into the model so that parameter values can be assigned prior to each simulation. For example, the May 18, 1980 Mount St. Helens deposit can be simulated using two aggregation parameters A (=2.8) and B (=1.9), both in phi units, where A represents the largest size class incorporated into aggregates and B represents the dominant size of aggregates (with assumed density 600 kg m-3). The mass fraction Fφ of each size class φ incorporated into aggregates is assumed to follow Fφ=1-exp(-max(0,φ-A)). We will report the success of this scheme to model several other well-characterized deposits.
Non-local models for the formation of hepatocyte-stellate cell aggregates.
Green, J E F; Waters, S L; Whiteley, J P; Edelstein-Keshet, L; Shakesheff, K M; Byrne, H M
2010-11-01
Liver cell aggregates may be grown in vitro by co-culturing hepatocytes with stellate cells. This method results in more rapid aggregation than hepatocyte-only culture, and appears to enhance cell viability and the expression of markers of liver-specific functions. We consider the early stages of aggregate formation, and develop a new mathematical model to investigate two alternative hypotheses (based on evidence in the experimental literature) for the role of stellate cells in promoting aggregate formation. Under Hypothesis 1, each population produces a chemical signal which affects the other, and enhanced aggregation is due to chemotaxis. Hypothesis 2 asserts that the interaction between the two cell types is by direct physical contact: the stellates extend long cellular processes which pull the hepatocytes into the aggregates. Under both hypotheses, hepatocytes are attracted to a chemical they themselves produce, and the cells can experience repulsive forces due to overcrowding. We formulate non-local (integro-partial differential) equations to describe the densities of cells, which are coupled to reaction-diffusion equations for the chemical concentrations. The behaviour of the model under each hypothesis is studied using a combination of linear stability analysis and numerical simulations. Our results show how the initial rate of aggregation depends upon the cell seeding ratio, and how the distribution of cells within aggregates depends on the relative strengths of attraction and repulsion between the cell types. Guided by our results, we suggest experiments which could be performed to distinguish between the two hypotheses. PMID:20709085
NUMERICAL MODELING OF THE COAGULATION AND POROSITY EVOLUTION OF DUST AGGREGATES
Okuzumi, Satoshi; Sakagami, Masa-aki; Tanaka, Hidekazu
2009-12-20
Porosity evolution of dust aggregates is crucial in understanding dust evolution in protoplanetary disks. In this study, we present useful tools to study the coagulation and porosity evolution of dust aggregates. First, we present a new numerical method for simulating dust coagulation and porosity evolution as an extension of the conventional Smoluchowski equation. This method follows the evolution of the mean porosity for each aggregate mass simultaneously with the evolution of the mass distribution function. This method reproduces the results of previous Monte Carlo simulations with much less computational expense. Second, we propose a new collision model for porous dust aggregates on the basis of our N-body experiments on aggregate collisions. As the first step, we focus on 'hit-and-stick' collisions, which involve neither compression nor fragmentation of aggregates. We first obtain empirical data on porosity changes between the classical limits of ballistic cluster-cluster and particle-cluster aggregation. Using the data, we construct a recipe for the porosity change due to general hit-and-stick collisions as well as formulae for the aerodynamical and collisional cross sections. Our collision model is thus more realistic than a previous model of Ormel et al. based on the classical aggregation limits only. Simple coagulation simulations using the extended Smoluchowski method show that our collision model explains the fractal dimensions of porous aggregates observed in a full N-body simulation and a laboratory experiment. By contrast, similar simulations using the collision model of Ormel et al. result in much less porous aggregates, meaning that this model underestimates the porosity increase upon unequal-sized collisions. Besides, we discover that aggregates at the high-mass end of the distribution can have a considerably small aerodynamical cross section per unit mass compared with aggregates of lower masses. This occurs when aggregates drift under uniform
Compression-based aggregation model for medical web services.
Al-Shammary, Dhiah; Khalil, Ibrahim
2010-01-01
Many organizations such as hospitals have adopted Cloud Web services in applying their network services to avoid investing heavily computing infrastructure. SOAP (Simple Object Access Protocol) is the basic communication protocol of Cloud Web services that is XML based protocol. Generally,Web services often suffer congestions and bottlenecks as a result of the high network traffic that is caused by the large XML overhead size. At the same time, the massive load on Cloud Web services in terms of the large demand of client requests has resulted in the same problem. In this paper, two XML-aware aggregation techniques that are based on exploiting the compression concepts are proposed in order to aggregate the medical Web messages and achieve higher message size reduction. PMID:21097152
Mucin aggregation from a rod-like meso-scale model
NASA Astrophysics Data System (ADS)
Moreno, Nicolas; Perilla, Jairo E.; Colina, Coray M.; Lísal, Martin
2015-05-01
Dissipative particle dynamics, a meso-scale particle-based model, was used to study the aggregation of mucins in aqueous solutions. Concentration, strength of the mucin-water interactions, as well as the effects of size, shape, and composition of the model molecules were studied. Model proteins were represented as rod-like objects formed by coarse-grained beads. In the first model, only one type of beads formed the mucin. It was found that all the surfaces were available to form aggregates and the conformation of the aggregates was a function of the strength of the mucin-water interaction. With this model, the number of aggregates was unaffected by the initial position of the mucins in the simulation box, except for the lowest mucin concentration. In a more refined mucin model, two kinds of beads were used in the molecule in order to represent the existence of cysteine-like terminal groups in the actual molecule. With this new scheme, aggregation took place by the interaction of the terminal groups between model molecules. The kinetic analysis of the evolution of the number of aggregates with time was also studied for both mucin models.
Dense and sparse aggregations in complex motion: Video coupled with simulation modeling
Technology Transfer Automated Retrieval System (TEKTRAN)
In censuses of aggregations composed of highly mobile animals, the link between image processing technology and simulation modeling remains relatively unexplored despite demonstrated ecological needs for abundance and density assessments. We introduce a framework that connects video censusing with ...
Size effects in models for mechanically-stressed protein crystals and aggregates
NASA Technical Reports Server (NTRS)
Noever, David A.
1992-01-01
As protein aggregates increase in size, they become easier to disrupt mechanically. Using the scaling properties of models proposed to govern protein aggregation, the effect of thermal vibrations and gravity are investigated as deforming forces. For typical protein assemblies made of 30 A proteins, the assembled diameter must remain less than 100-10,000 times the molecular radius to survive in finite thermal and gravity fields. The analysis predicts the following experimental outcomes: (1) reductions in gravitational strain should favor larger protein aggregates; (2) in comparing the aggregate stability of different proteins, the addition of peptide chains should stabilize against thermal strain, but should not affect gravitational strain; (3) critical aggregate sizes should show significant (exponential) sensitivity to cluster geometry, solution preparation and growth conditions. The analysis is extended to consider qualitative size effects in crystal damage during X-ray exposure.
Yin, Liusong; Chen, Xiaoying; Tiwari, Abhinav; Vicini, Paolo; Hickling, Timothy P.
2015-01-01
Therapeutic protein products (TPP) have been widely used to treat a variety of human diseases, including cancer, hemophilia, and autoimmune diseases. However, TPP can induce unwanted immune responses that can impact both drug efficacy and patient safety. The presence of aggregates is of particular concern as they have been implicated in inducing both T cell-independent and T cell-dependent immune responses. We used mathematical modeling to evaluate several mechanisms through which aggregates of TPP could contribute to the development of immunogenicity. Modeling interactions between aggregates and B cell receptors demonstrated that aggregates are unlikely to induce T cell-independent immune responses by cross-linking B cell receptors because the amount of signal transducing complex that can form under physiologically relevant conditions is limited. We systematically evaluate the role of aggregates in inducing T cell-dependent immune responses using a recently developed multiscale mechanistic mathematical model. Our analysis indicates that aggregates could contribute to T cell-dependent immune response by inducing high affinity epitopes which may not be present in the nonaggregated TPP and/or by enhancing danger signals to break tolerance. In summary, our computational analysis is suggestive of novel insights into the mechanisms underlying aggregate-induced immunogenicity, which could be used to develop mitigation strategies. PMID:26682236
Prigent, Stéphanie; Ballesta, Annabelle; Charles, Frédérique; Lenuzza, Natacha; Gabriel, Pierre; Tine, Léon Matar; Rezaei, Human; Doumic, Marie
2012-01-01
Protein polymerization consists in the aggregation of single monomers into polymers that may fragment. Fibrils assembly is a key process in amyloid diseases. Up to now, protein aggregation was commonly mathematically simulated by a polymer size-structured ordinary differential equations (ODE) system, which is infinite by definition and therefore leads to high computational costs. Moreover, this Ordinary Differential Equation-based modeling approach implies biological assumptions that may be difficult to justify in the general case. For example, whereas several ordinary differential equation models use the assumption that polymerization would occur at a constant rate independently of polymer size, it cannot be applied to certain protein aggregation mechanisms. Here, we propose a novel and efficient analytical method, capable of modelling and simulating amyloid aggregation processes. This alternative approach consists of an integro-Partial Differential Equation (PDE) model of coalescence-fragmentation type that was mathematically derived from the infinite differential system by asymptotic analysis. To illustrate the efficiency of our approach, we applied it to aggregation experiments on polyglutamine polymers that are involved in Huntington’s disease. Our model demonstrates the existence of a monomeric structural intermediate acting as a nucleus and deriving from a non polymerizing monomer (). Furthermore, we compared our model to previously published works carried out in different contexts and proved its accuracy to describe other amyloid aggregation processes. PMID:23152746
Simple off-lattice model to study the folding and aggregation of peptides
NASA Astrophysics Data System (ADS)
Combe, Nicolas; Frenkel, Daan
We present a numerical study of a new protein model. This off-lattice model takes into account both the hydrogen bonds and the amino-acid interactions. It reproduces the folding of a small protein (peptide): morphological analysis of the conformations at low temperature shows two well-known substructures α-helix and β-sheet depending on the chosen sequence. The folding pathway in the scope of this model is studied through a free-energy analysis. We then study the aggregation of proteins. Proteins in the aggregate are mainly bound via hydrogen bonds. Performing a free-energy analysis we show that the addition of a peptide to such an aggregate is not favourable. We qualitatively reproduce the abnormal aggregation of proteins in prion diseases.
Deeth, Lorna E; Deardon, Rob
2016-05-01
A class of complex statistical models, known as individual-level models, have been effectively used to model the spread of infectious diseases. These models are often fitted within a Bayesian Markov chain Monte Carlo framework, which can have a sig nificant computational expense due to the complex nature of the likelihood function associated with this class of models. Increases in population size or duration of the modeled epidemic can contribute to this computational burden. Here, we explore the effect of reducing this computational expense by aggregating the data into spatial clusters, and therefore reducing the overall population size. Individual-level models, reparameterized to account for this aggregation effect, may then be fitted to the spatially aggregated data. The ability of two reparameterized individual-level models, when fitted to this reduced data set, to identify a covariate effect is investigated through a simulation study. PMID:27246276
Modeling coupled nanoparticle aggregation and transport in porous media: A Lagrangian approach
NASA Astrophysics Data System (ADS)
Taghavy, Amir; Pennell, Kurt D.; Abriola, Linda M.
2015-01-01
Changes in nanoparticle size and shape due to particle-particle interactions (i.e., aggregation or agglomeration) may significantly alter particle mobility and retention in porous media. To date, however, few modeling studies have considered the coupling of transport and particle aggregation processes. The majority of particle transport models employ an Eulerian modeling framework and are, consequently, limited in the types of collisions and aggregate sizes that can be considered. In this work, a more general Lagrangian modeling framework is developed and implemented to explore coupled nanoparticle aggregation and transport processes. The model was verified through comparison of model simulations to published results of an experimental and Eulerian modeling study (Raychoudhury et al., 2012) of carboxymethyl cellulose (CMC)-modified nano-sized zero-valent iron particle (nZVI) transport and retention in water-saturated sand columns. A model sensitivity analysis reveals the influence of influent particle concentration (ca. 70 to 700 mg/L), primary particle size (10-100 nm) and pore water velocity (ca. 1-6 m/day) on particle-particle, and, consequently, particle-collector interactions. Model simulations demonstrate that, when environmental conditions promote particle-particle interactions, neglecting aggregation effects can lead to under- or over-estimation of nanoparticle mobility. Results also suggest that the extent to which higher order particle-particle collisions influence aggregation kinetics will increase with the fraction of primary particles. This work demonstrates the potential importance of time-dependent aggregation processes on nanoparticle mobility and provides a numerical model capable of capturing/describing these interactions in water-saturated porous media.
Koch, Yvonne; Helferich, Anika M; Steinacker, Petra; Oeckl, Patrick; Walther, Paul; Weishaupt, Jochen H; Danzer, Karin M; Otto, Markus
2016-08-01
Aggregation of misfolded disease-related proteins is a hallmark of neurodegenerative diseases. Aggregate propagation accompanying disease progression has been demonstrated for different proteins (eg, for α-synuclein). Additional evidence supports aggregate cross-seeding activity for α-synuclein. For mutated superoxide dismutase 1 (SOD1), which causes familial amyotrophic lateral sclerosis (ALS), self-propagation of aggregation and cell-to-cell transmission have been demonstrated in vitro. However, there is a prominent lack of in vivo data concerning aggregation and cross-aggregation processes of SOD1. We analyzed the effect of α-synuclein and SOD1 seeds in cell culture using protein fragment complementation assay and intracerebral injection of α-synuclein and SOD1 seeds into SOD1(G93A) transgenic ALS mice. Survival of injected mice was determined, and SOD1 aggregates in the facial nuclei were quantified during disease course. We found that α-synuclein preformed fibrils increased the oligomerization rate of SOD1 in vivo and in vitro, whereas aggregated SOD1 did not exert any effect in both experimental setups. Notably, survival of ALS mice was not changed after inoculation of preformed fibrils. We conclude that misfolded α-synuclein can increase SOD1 aggregation and suppose that α-synuclein seeds are transported from the temporal cortex to the facial nuclei. However, unlike other proteins, the further enhancement of a self-aggregation process by additional SOD1 could not be confirmed in our models. PMID:27322773
Singular patterns for an aggregation model with a confining potential
NASA Astrophysics Data System (ADS)
Kolokolnikov, Theodore; Huang, Yanghong; Pavlovski, Mark
2013-10-01
We consider the aggregation equation with an attractive-repulsive force law. Recent studies (Kolokolnikov et al. (2011) [22]; von Brecht et al. (2012) [23]; Balague et al. (2013) [15]) have demonstrated that this system exhibits a very rich solution structure, including steady states consisting of rings, spots, annuli, N-fold symmetries, soccer-ball patterns etc. We show that many of these patterns can be understood as singular perturbations off lower-dimensional equilibrium states. For example, an annulus is a bifurcation from a ring; soccer-ball patterns bifurcate off solutions that consist of delta-point concentrations. We apply asymptotic methods to classify the form and stability of many of these patterns. To characterize spot solutions, a class of “semi-linear” aggregation problems is derived, where the repulsion is described by a nonlinear term and the attraction is linear but non-symmetric. For a special class of perturbations that consists of a Newtonian repulsion, the spot shape is shown to be an ellipse whose precise dimensions are determined via a complex variable method. For annular shapes, their width and radial density profile are described using perturbation techniques.
NASA Astrophysics Data System (ADS)
Aravena, J. E.; Berli, M.; Tyler, S. W.
2010-12-01
The rhizosphere is the thin layer of soil that surrounds the roots. Its properties are different from the bulk, thus it is a critical environmental interface that controls water, nutrient and solute transport from the soil to the biosphere. At the aggregate scale, natural root-induced compaction may be surprisingly beneficial for the plants, as it increases contact areas between the aggregates and, contrary to traditional thinking, increases the hydraulic conductivity. We study the combined effect of compaction in a bed of multiple soil aggregates, before and after compaction for (a) a micro-balloon-induced compacted sample and (b) a natural root-induced compacted sample. Numerical models were constructed using X-ray micro-tomography (XMT) images to build the finite element meshes; the soil hydraulic properties (porosity and air-entry pressure), used to populate the models of the beds of aggregates, were estimated using XMT information, as the consolidation of the aggregates, due to the compaction results in a variable distribution of inter- and intra-aggregate porosity. The results show that root-induced compaction can be very beneficial for the plant, as it increases the hydraulic conductivity of the system. Thus, roots are able to extract more water than prior to compaction. The numerical modeling results were compared with a new theoretical hydraulic conductivity model.
Mischnik, Marcel; Gambaryan, Stepan; Subramanian, Hariharan; Geiger, Jörg; Schütz, Claudia; Timmer, Jens; Dandekar, Thomas
2014-08-01
A kinetic description of the fragile equilibrium in thrombozytes regulating blood flow would be an important basis for rational medical interventions. Challenges for such a model include regulation by a complex bistability switch that determines the transition from reversible to irreversible aggregation and sparse data on the kinetics. A so far scarcely applied technique is given by the derivation of ordinary differential equations from Boolean expressions, which are called logic ODEs. We employ a combination of light-scattering based thrombocyte aggregation data, western blot and calcium measurements to compare three different ODE approaches regarding their suitability to achieve a data-consistent model of the switch. Our analysis reveals the standardized qualitative dynamical system approach (SQUAD) to be a better choice than classical mass action formalisms. Furthermore, we analyze the dynamical properties of the platelet aggregation threshold as a basis for medical interventions such as novel platelet aggregation inhibitors. PMID:24852796
On a Competitive Model of Laplacian Growth
NASA Astrophysics Data System (ADS)
Loutsenko, Igor; Yermolayeva, Oksana; Zinsmeister, Michel
2011-11-01
We introduce a competitive model of Laplacian growth in both stochastic and deterministic versions. This defines two different aggregation laws with probabilities λ and 1- λ. The parameter λ varying from 0 to 1 is used to weight a ratio between the inner and outer harmonic measures that leads to a competition between the Eden-like process and the DLA solved with site-sticking conditions. We perform numerical and qualitative analysis of the competitive growth.
Morphological transition between diffusion-limited and ballistic aggregation growth patterns.
Ferreira, S C; Alves, S G; Brito, A Faissal; Moreira, J G
2005-05-01
In this work, the transition between diffusion-limited (DLA) and ballistic aggregation (BA) models was reconsidered using a model in which biased random walks simulate the particle trajectories. The bias is controlled by a parameter lambda, which assumes the value lambda=0 (1) for the ballistic (diffusion-limited) aggregation model. Patterns growing from a single seed were considered. In order to simulate large clusters, an efficient algorithm was developed. For lambda (not equal to) 0 , the patterns are fractal on small length scales, but homogeneous on large ones. We evaluated the mean density of particles (-)rho in the region defined by a circle of radius r centered at the initial seed. As a function of r, (-)rho reaches the asymptotic value rho(0)(lambda) following a power law (-)rho = rho(0) +Ar(-gamma) with a universal exponent gamma=0.46 (2) , independent of lambda . The asymptotic value has the behavior rho(0) approximately |1-lambda|(beta) , where beta=0.26 (1) . The characteristic crossover length that determines the transition from DLA- to BA-like scaling regimes is given by xi approximately |1-lambda|(-nu) , where nu=0.61 (1) , while the cluster mass at the crossover follows a power law M(xi) approximately |1-lambda(-alpha) , where alpha=0.97 (2) . We deduce the scaling relations beta=nugamma and beta=2nu-alpha between these exponents. PMID:16089530
Simple Model Study of Phase Transition Properties of Isolated and Aggregated Protein
NASA Astrophysics Data System (ADS)
Ji, Yong-Yun; Yi, Wei-Qi; Zhang, Lin-Xi
2011-03-01
We investigate the phase transition properties of isolated and aggregated protein by exhaustive numerical study in the confined conformation space with maximally compact lattice model. The study within the confined conformation space shows some general folding properties. Various sequences show different folding properties: two-state folding, three-state folding and prion-like folding behavior. We find that the aggregated protein holds a more evident transition than isolated one and the transition temperature is generally lower than that in isolated case.
Smina, T P; Mathew, J; Janardhanan, K K
2016-01-01
G. lucidum total triterpenes were assessed for its apoptosis-inducing and anti-tumour activities. The ability of the total triterpenes to induce apoptosis was evaluated in Dalton's lymphoma ascites (DLA) and Ehrlich's ascites carcinoma (EAC) cell lines. Total triterpenes were found to be highly cytotoxic to DLA and EAC cell lines with IC50 values 5 ± 0.32 and 7.9 ± 0.2 µg/ml respectively. Total triterpenes induced apoptosis in both cell lines which is evident from the DNA fragmentation assay. Anti-tumour activity was accessed using DLA induced solid and EAC induced ascites tumour models in Swiss albino mice. Administration of 10, 50 and 100 mg/kg b. wt. total triterpenes showed 11.86, 27.27 and 40.57% increase in life span of animals in ascites tumour model. Treatment with 10, 50 and 100 mg/kg b. wt. total triterpenes exhibited 76.86, 85.01 and 91.03% inhibition in tumour volume and 67.96, 72.38 and 77.90% inhibition in tumour weight respectively in the solid tumour model. The study reveals the significant dose-dependent anti-tumour activity of total triterpenes in both models. Total triterpenes were more active against the solid tumour than the ascites tumour. The anti-oxidant potential and ability to induce cell-specific apoptosis could be contributing to its anti-tumour activities. PMID:27188870
Impact of climate aggregation over different scales on regional NPP modelling
NASA Astrophysics Data System (ADS)
Kuhnert, Matthias
2016-04-01
Model input data aggregation methods and data aggregation across spatial scales affect various model outputs, e.g. Net Primary Productivity (NPP). The scale at which data is collected is of great importance. In ecosystem modelling studies we often see soil and climate data collected at coarse scale being used in models to predict ecosystem responses e.g. NPP in dependency of these parameters at finer scale. Outputs of these models are impacted by the way the data is aggregated or dis-aggregated to the spatial scale. Up to know there are very few studies which quantified the impact of scaling on the simulation results. In this study, we quantify the impact of climate data aggregation using five different resolutions, to simulate NPP by 11 different crop and biogeochemical models for the same study area. The aggregation effect is investigated for wheat and maize cropping systems in the state of North Rhine-Westphalia, Germany. The simulation results are analysed for NPP averaged over growing seasons of a 30 year period at different spatial resolutions as well as for annual NPP during growing season. While there is only a minor impact of input data aggregation on NPP on 30 year averages, the annual data show differences in NPP up to 9.4 % and 13.6 % between the different resolutions for wheat and maize, respectively. The scale effect differ between the models and shows higher impacts for extreme years. This is tested by selecting years with extreme dry conditions based on a drought index, which showed stronger scale effects of up to 12.8 % and 15.5 % for wheat and maize, respectively.
Marchetti, Riccardo; Taloni, Alessandro; Caglioti, Emanuele; Loreto, Vittorio; Pietronero, Luciano
2012-08-10
We prove that the harmonic measure is stationary, unique, and invariant on the interface of diffusion limited aggregation (DLA) growing on a cylinder surface. We provide a detailed theoretical analysis puzzling together multiscaling, multifractality, and conformal invariance, supported by extensive numerical simulations of clusters built using conformal mappings and on a lattice. The growth properties of the active and frozen zones are clearly elucidated. We show that the unique scaling exponent characterizing the stationary growth is the DLA fractal dimension. PMID:23006279
Stationary Growth and Unique Invariant Harmonic Measure of Cylindrical Diffusion Limited Aggregation
NASA Astrophysics Data System (ADS)
Marchetti, Riccardo; Taloni, Alessandro; Caglioti, Emanuele; Loreto, Vittorio; Pietronero, Luciano
2012-08-01
We prove that the harmonic measure is stationary, unique, and invariant on the interface of diffusion limited aggregation (DLA) growing on a cylinder surface. We provide a detailed theoretical analysis puzzling together multiscaling, multifractality, and conformal invariance, supported by extensive numerical simulations of clusters built using conformal mappings and on a lattice. The growth properties of the active and frozen zones are clearly elucidated. We show that the unique scaling exponent characterizing the stationary growth is the DLA fractal dimension.
Smyth, Erica; Solomon, Antonia; Vydyanath, Anupama; Luther, Pradeep K; Pitchford, Simon; Tetley, Teresa D; Emerson, Michael
2015-05-01
Nanoparticles (NPs) may come into contact with circulating blood elements including platelets following inhalation and translocation from the airways to the bloodstream or during proposed medical applications. Studies with model polystyrene latex nanoparticles (PLNPs) have shown that NPs are able to induce platelet aggregation in vitro suggesting a poorly defined potential mechanism of increased cardiovascular risk upon NP exposure. We aimed to provide insight into the mechanisms by which NPs may increase cardiovascular risk by determining the impact of a range of concentrations of PLNPs on platelet activation in vitro and in vivo and identifying the signaling events driving NP-induced aggregation. Model PLNPs of varying nano-size (50 and 100 nm) and surface chemistry [unmodified (uPLNP), amine-modified (aPLNP) and carboxyl-modified (cPLNP)] were therefore examined using in vitro platelet aggregometry and an established mouse model of platelet thromboembolism. Most PLNPs tested induced GPIIb/IIIa-mediated platelet aggregation with potencies that varied with both surface chemistry and nano-size. Aggregation was associated with signaling events, such as granule secretion and release of secondary agonists, indicative of conventional agonist-mediated aggregation. Platelet aggregation was associated with the physical interaction of PLNPs with the platelet membrane or internalization. 50 nm aPLNPs acted through a distinct mechanism involving the physical bridging of adjacent non-activated platelets leading to enhanced agonist-induced aggregation in vitro and in vivo. Our study suggests that should they translocate the pulmonary epithelium, or be introduced into the blood, NPs may increase the risk of platelet-driven events by inducing or enhancing platelet aggregation via mechanisms that are determined by their distinct combination of nano-size and surface chemistry. PMID:25030098
NASA Astrophysics Data System (ADS)
Boness, D. A.; Terrell-Martinez, B.
2010-12-01
As part of an ongoing undergraduate research project of light scattering calculations involving fractal carbonaceous soot aggregates relevant to current anthropogenic and natural sources in Earth's atmosphere, we have read with interest a recent paper [E.T. Wolf and O.B Toon,Science 328, 1266 (2010)] claiming that the Faint Young Sun paradox discussed four decades ago by Carl Sagan and others can be resolved without invoking heavy CO2 concentrations as a greenhouse gas warming the early Earth enough to sustain liquid water and hence allow the origin of life. Wolf and Toon report that a Titan-like Archean Earth haze, with a fractal haze aggregate nature due to nitrogen-methane photochemistry at high altitudes, should block enough UV light to protect the warming greenhouse gas NH3 while allowing enough visible light to reach the surface of the Earth. To test this hypothesis, we have employed a rigorous T-Matrix arbitrary-particle light scattering technique, to avoid the simplifications inherent in Mie-sphere scattering, on haze fractal aggregates at UV and visible wavelenths of incident light. We generate these model aggregates using diffusion-limited cluster aggregation (DLCA) algorithms, which much more closely fit actual haze fractal aggregates than do diffusion-limited aggregation (DLA) algorithms.
Percolation model for growth rates of aggregates and its application for business firm growth
NASA Astrophysics Data System (ADS)
Fu, Dongfeng; Buldyrev, Sergey V.; Salinger, Michael A.; Stanley, H. Eugene
2006-09-01
Motivated by recent empirical studies of business firm growth, we develop a dynamic percolation model which captures some of the features of the economical system—i.e., merging and splitting of business firms—represented as aggregates on a d -dimensional lattice. We find the steady-state distribution of the aggregate size and explore how this distribution depends on the model parameters. We find that at the critical threshold, the standard deviation of the aggregate growth rates, σ , increases with aggregate size S as σ˜Sβ , where β can be explained in terms of the connectedness length exponent ν and the fractal dimension df , with β=1/(2νdf)≈0.20 for d=2 and 0.125 for d→∞ . The distributions of aggregate growth rates have a sharp peak at the center and pronounced wings extending over many standard deviations, giving the distribution a tent-shape form—the Laplace distribution. The distributions for different aggregate sizes scaled by their standard deviations collapse onto the same curve.
NASA Astrophysics Data System (ADS)
Grosz, Balázs; Dechow, Rene; Ewert, Frank; Gaiser, Thomas; Hoffmann, Holger; Zhao, Gang
2015-04-01
Soil organic carbon models which have been extensively tested and calibrated for field scale applications in the past are now increasingly used for larger scale estimations. In large scale applications, recent data availability and limited computational capacity requires adequate aggregation of the model input and model initialization. Method and level of driver aggregation in up scaling studies are sources of uncertainty and might bias the aggregated model outcome. The suitability of up scaled model results using aggregated driving data depends on both the sensitivity of the model on these model drivers and the scale of interest describing the desired aggregation level of the model output. The implications of driver aggregation schemes have been examined in a scaling exercise within the joint research project MACSUR (Modelling European Agriculture with Climate Change for Food Security). In this study, meteorological driving data and data on soil properties on several aggregation levels have been used to calculate the soil organic carbon change of agricultural land use in North Rhine-Westphalia with the bio-geo-chemical model CENTURY. The model couples processes determining crop growth, soil organic matter and nutrient dynamics. In the aggregation study meteorological data and soil properties from a NUTS 2 region in Germany (North Rhine-Westphalia) from 1980 to 2010 were prepared on 6 aggregation levels corresponding to grid cells in 1x1km, 10x10km, 25x25km, 50x50km, 100x100km resolution and spatial means on federate state level. Upscaling exercises have been conducted by combining several aggregation levels of soil properties and weather data. Results show that the aggregation of meteorological data has little impact on modeled soil organic carbon changes although model uncertainty increases slightly with decreasing scale of interest from NUTS 2 (federal state) level to smaller grid cell size. Contrary, the aggregation of soil properties result in high uncertainty
NASA Astrophysics Data System (ADS)
Nowell, H.; Liu, G.
2012-12-01
With the advent of satellites, we can now observe areas of the globe that have sparse to no ground data coverage. Both active and passive satellite sensors aboard satellites including CloudSat's Cloud Profiling Radar (CPR), Aqua's Advanced Microwave Scanning Radiometer (AMSR-E) and the upcoming Global Precipitation Measurement's (GPM) Dual-Frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI) study ice and snow particles. A good retrieval algorithm for these satellite sensors can only be developed when the single scattering properties of the snowflakes are accurately calculated in radiative transfer models. This becomes crucial at frequencies at and above the W-band when aggregate ice crystals become detectable by satellite radiometers. Snowflakes are often modeled as spheres or oblate spheroids to ease the complexity of calculations, despite the fact that they are typically aggregates of crystals. For improved accuracy in satellite remote sensing, it is important to model snowflakes as close to nature as possible. Several recent studies model flakes as pristine crystal types [Liu, 2008], generate aggregate flakes as fractals [Ishimoto, 2008] or via the Monte Carlo method [Maruyama and Fujioshi, 2005]. Modeling snowflakes as pristine crystals, however, has the drawback of not accurately reflecting snowflakes as most tend to be aggregates of different crystal types. Other studies where aggregates are generated tend to overlook size-density relationships of aggregate flakes or other studied statistical parameters such as aspect ratio. In an effort to improve available single-scattering properties of aggregate flakes, we developed a new method of generating flakes. Starting out with a six-bullet rosette crystal of accurate size and density, aggregate flakes are generated with two different bullet rosette crystal sizes of 200 and/or 400 microns in maximum dimension. The flakes similarly follow size-density relationships of aggregate as determined from
Induced growth of dendrite gold nanostructure by controlling self-assembly aggregation dynamics.
Abdellatif, M H; Abdelrasoul, G N; Scarpellini, A; Marras, S; Diaspro, A
2015-11-15
Self-assembly of gold nanoparticles (AuNPs) is an important growth mode for fabricating functional materials. In this work we report a dendrite structure formed by slowing down the aggregation dynamics of AuNPs self-assembly. The obtained results show that the aggregation dynamics is dominated by the Reaction Limited Aggregation Model (RLA) more than the Diffusion Limited Aggregation Model (DLA). In which the repulsion due to electrostatic forces is dominant by the Van Der Walls attraction forces, and low sticking probability of nanoparticles. The aggregation dynamics of AuNPs can be slowed down if the water evaporation of the drop casted colloidal AuNPs on a quartz substrate is slowed. Slowing down the evaporation allows electrostatic repulsion forces to decrease gradually. At certain point, the attraction forces become higher than the electrostatic repulsion and hence cluster aggregation take place slowly. The slow aggregation dynamics allows the nanoparticles to sample all possible orientation in the sticking site, searching for the lowest energy configuration. The size distribution of the nanoparticles in liquid is confirmed using dynamic light scattering based on Stokes-Einstein equation for diffusion coefficient in water. X-ray and photoluminescence (PL) spectra of the sample after aggregation showed a shift which is related to the aggregation compared with non-aggregated colloidal nanoparticles in the solution. The study shows that dendrite self similar structure can be formed by slowing down the aggregation dynamics of nanoparticles as a result of minimizing the Helmholtz free surface energy of the system. PMID:26233557
Aggregation of asphaltene model compounds using a porphyrin tethered to a carboxylic acid.
Schulze, Matthias; Lechner, Marc P; Stryker, Jeffrey M; Tykwinski, Rik R
2015-07-01
A Ni(II) porphyrin functionalized with an alkyl carboxylic acid (3) has been synthesized to model the chemical behavior of the heaviest portion of petroleum, the asphaltenes. Specifically, porphyrin 3 is used in spectroscopic studies to probe aggregation with a second asphaltene model compound containing basic nitrogen (4), designed to mimic asphaltene behavior. NMR spectroscopy documents self-association of the porphyrin and aggregation with the second model compound in solution, and a Job's plot suggests a 1 : 2 stoichiometry for compounds 3 and 4. PMID:26024486
Determination of critical nucleation number for a single nucleation amyloid-β aggregation model
Ghosh, Preetam; Vaidya, Ashwin; Kumar, Amit; Rangachari, Vijayaraghavan
2016-01-01
Aggregates of amyloid-β (Aβ) peptide are known to be the key pathological agents in Alzheimer disease (AD). Aβ aggregates to form large, insoluble fibrils that deposit as senile plaques in AD brains. The process of aggregation is nucleation–dependent in which the formation of a nucleus is the rate–limiting step, and controls the physiochemical fate of the aggregates formed. Therefore, understanding the properties of nucleus and pre-nucleation events will be significant in reducing the existing knowledge–gap in AD pathogenesis. In this report, we have determined the plausible range of critical nucleation number (n*), the number of monomers associated within the nucleus for a homogenous aggregation model with single unique nucleation event, by two independent methods: A reduced-order stability analysis and ordinary differential equation based numerical analysis, supported by experimental biophysics. The results establish that the most likely range of n* is between 7 and 14 and within, this range, n* = 12 closely supports the experimental data. These numbers are in agreement with those previously reported, and importantly, the report establishes a new modeling framework using two independent approaches towards a convergent solution in modeling complex aggregation reactions. Our model also suggests that the formation of large protofibrils is dependent on the nature of n*, further supporting the idea that pre-nucleation events are significant in controlling the fate of larger aggregates formed. This report has re-opened an old problem with a new perspective and holds promise towards revealing the molecular events in amyloid pathologies in the future. PMID:26774039
Determination of critical nucleation number for a single nucleation amyloid-β aggregation model.
Ghosh, Preetam; Vaidya, Ashwin; Kumar, Amit; Rangachari, Vijayaraghavan
2016-03-01
Aggregates of amyloid-β (Aβ) peptide are known to be the key pathological agents in Alzheimer disease (AD). Aβ aggregates to form large, insoluble fibrils that deposit as senile plaques in AD brains. The process of aggregation is nucleation-dependent in which the formation of a nucleus is the rate-limiting step, and controls the physiochemical fate of the aggregates formed. Therefore, understanding the properties of nucleus and pre-nucleation events will be significant in reducing the existing knowledge-gap in AD pathogenesis. In this report, we have determined the plausible range of critical nucleation number (n(*)), the number of monomers associated within the nucleus for a homogenous aggregation model with single unique nucleation event, by two independent methods: A reduced-order stability analysis and ordinary differential equation based numerical analysis, supported by experimental biophysics. The results establish that the most likely range of n(*) is between 7 and 14 and within, this range, n(*) = 12 closely supports the experimental data. These numbers are in agreement with those previously reported, and importantly, the report establishes a new modeling framework using two independent approaches towards a convergent solution in modeling complex aggregation reactions. Our model also suggests that the formation of large protofibrils is dependent on the nature of n(*), further supporting the idea that pre-nucleation events are significant in controlling the fate of larger aggregates formed. This report has re-opened an old problem with a new perspective and holds promise towards revealing the molecular events in amyloid pathologies in the future. PMID:26774039
Lattuada, Marco
2012-01-12
Smoluchowski's equation for the rate of aggregation of colloidal particles under diffusion-limited conditions has set the basis for the interpretation of kinetics of aggregation phenomena. Nevertheless, its use is limited to sufficiently dilute conditions. In this work we propose a correction to Smoluchowski's equation by using a result derived by Richards ( J. Phys. Chem. 1986 , 85 , 3520 ) within the framework of trapping theory. This corrected aggregation kernel, which accounts for concentration dependence effects, has been implemented in a population-balance equations scheme and used to model the aggregation kinetics of colloidal particles undergoing diffusion-limited aggregation under concentrated conditions (up to a particle volume fraction of 30%). The predictions of population balance calculations have been validated by means of Brownian dynamic simulations. It was found that the corrected kernel can very well reproduce the results from Brownian dynamic simulations for all concentration values investigated, and is also able to accurately predict the time required by a suspension to reach the gel point. On the other hand, classical Smoluchowski's theory substantially underpredicts the rate of aggregation as well as the onset of gelation, with deviations becoming progressively more severe as the particle volume fraction increases. PMID:22148884
Owczarz, Marta; Motta, Anna C; Morbidelli, Massimo; Arosio, Paolo
2015-07-14
We apply a kinetic analysis platform to study the intermolecular interactions underlying the colloidal stability of dispersions of charged amyloid fibrils consisting of a model amphiphilic peptide (RADA 16-I). In contrast to the aggregation mechanisms observed in the large majority of proteins and peptides, where several elementary reactions involving both monomers and fibrils are present simultaneously, the system selected in this work allows the specific investigation of the fibril-fibril aggregation process. We examine the intermolecular interactions driving the aggregation reaction at pH 2.0 by changing the buffer composition in terms of salt concentration, type of ion as well as type and concentration of organic solvent. The aggregation kinetics are followed by dynamic light scattering, and the experimental data are simulated by Smoluchowski population balance equations, which allow to estimate the energy barrier between two colliding fibrils in terms of the Fuchs stability ratio (W). When normalized on a dimensionless time weighted on the Fuchs stability ratio, the aggregation profiles under a broad range of conditions collapse on a single master curve, indicating that the buffer composition modifies the aggregation kinetics without affecting the aggregation mechanism. Our results show that the aggregation process does not occur under diffusion-limited conditions. Rather, the reaction rate is limited by the presence of an activation energy barrier that is largely dominated by electrostatic repulsive interactions. Such interactions could be reduced by increasing the concentration of salt, which induces charge screening, or the concentration of organic solvent, which affects the dielectric constant. It is remarkable that the dependence of the activation energy on the ionic strength can be described quantitatively in terms of charge screening effects in the frame of the DLVO theory, although specific anion and cation effects are also observed. While anion
Three dimensional culture of pineal cell aggregates: a model of cell-cell co-operation.
Khan, N A; Shacoori, V; Havouis, R; Querné, D; Moulinoux, J P; Rault, B
1995-05-01
Three dimensional (3-D) cultures of pineal cell aggregates were obtained by constant gyratory shaking the heterogenous cell populations, obtained from the rat pineals, in the DMEM (Dulbecco's modified Eagle's medium). Within 4 days, the pineal cells became organized into a tissue like configuration appearing as a compact ball, evidenced by the scanning electron microscopy. The 3-D aggregates seemed to be mainly composed of pinealocytes (round-oval cells), glial (elongated cells) and other unknown cells. The heterogenous cells were separated by intercellular spaces. The ultrastructural characteristics revealed by transmission electron microscopy exhibited the presence of granular lysosomes, typical of pinealocytes actively involved in the secretion. These pineal cell aggregates secreted melatonin and other indole amines i.e. 5-methoxytryptamine (5-MT), indole acetic acid (IAA), 5-methoxy-3-indole acetic acid (5-MIAA), tryptophol (TOL) and 5-methoxytryptophol (5-MTL) in the culture medium, indicating the functional aspect of pinealocytes. The 3-D aggregates cultures had advantages over the pineal monolayer cultures as, after 4 days of culture, the amounts of indole amines secreted by 3-D aggregates were higher than those secreted by monolayer cultures. Besides, the 3-D aggregates remained functional till 24 days in the gyratory culture conditions. In the continuous perifusion system, the 3-D aggregates secreted melatonin while challanged with isoproterenol. This 3-D model of pineal cell aggregates might be useful, in future, to perform other kinetic studies of the release of indole amines in perifusion experiments as this system allows the maintenance of pineal cells for a long period of time. PMID:7550281
Monine, Michael; Posner, Richard; Savage, Paul; Faeder, James; Hlavacek, William S
2008-01-01
Signal transduction generally involves multivalent protein-protein interactions, which can produce various protein complexes and post-translational modifications. The reaction networks that characterize these interactions tend to be so large as to challenge conventional simulation procedures. To address this challenge, a kinetic Monte Carlo (KMC) method has been developed that can take advantage of a model specification in terms of reaction rules for molecular interactions. A set of rules implicitly defines the reactions that can occur as a result of the interactions represented by the rules. With the rule-based KMC method, explicit generation of the underlying chemical reaction network implied by rules is avoided. Here, we apply and extend this method to characterize the interactions of a trivalent ligand with a bivalent cell-surface receptor. This system is also studied experimentally. We consider the following kinetic models: an equivalent-site model, an extension of this model, which takes into account steric constraints on the configurations of receptor aggregates, and finally, a model that accounts for cyclic receptor aggregates. Simulation results for the equivalent-site model are consistent with an equilibrium continuum model. Using these models, we investigate the effects of steric constraints and the formation of cyclic aggregates on the kinetics and equilibria of small and large aggregate formation and the percolation phase transition that occurs in this system.
AN AGGREGATION AND EPISODE SELECTION SCHEME FOR EPA'S MODELS-3 CMAQ
The development of an episode selection and aggregation approach, designed to support distributional estimation for use with the Models-3 Community Multiscale Air Quality (CMAQ) model, is described. The approach utilized cluster analysis of the 700 hPa u and v wind field compo...
NASA Astrophysics Data System (ADS)
Coppin, David; Bony, Sandrine
2015-12-01
Cloud-resolving models have shown that under certain conditions, the Radiative-Convective Equilibrium (RCE) could become unstable and lead to the spontaneous organization of the atmosphere into dry and wet areas, and the aggregation of convection. In this study, we show that this "self-aggregation" behavior also occurs in nonrotating RCE simulations performed with the IPSL-CM5A-LR General Circulation Model (GCM), and that it exhibits a strong dependence on sea surface temperature (SST). We investigate the physical mechanisms that control the initiation of self-aggregation in this model, and their dependence on temperature. At low SSTs, the onset of self-aggregation is primarily controlled by the coupling between low-cloud radiative effects and shallow circulations and the formation of "radiatively driven cold pools" in areas devoid of deep convection, while at high SSTs it is primarily controlled by the coupling between surface fluxes and circulation within convective areas. At intermediate temperatures, the occurrence of self-aggregation is less spontaneous and depends on initial conditions, but it can arise through a combination of both mechanisms. Through their coupling to circulation and surface fluxes, the radiative effects of low-level clouds play a critical role in both initiation mechanisms, and the sensitivity of boundary layer clouds to surface temperature explains to a large extent the temperature dependence of convective self-aggregation. At any SST, the presence of cloud-radiative effects in the free troposphere is necessary to the initiation, growth, and maintenance of convective aggregation.
Titus, Steven A; Southall, Noel; Marugan, Juan; Austin, Christopher P; Zheng, Wei
2012-01-01
A hallmark of Huntington’s disease is the presence of a large polyglutamine expansion in the first exon of the Huntingtin protein and the propensity of protein aggregation by the mutant proteins. Aberrant protein aggregation also occurs in other polyglutamine expansion disorders, as well as in other neurodegenerative diseases including Parkinson’s, Alzheimer’s, and prion diseases. However, the pathophysiological role of these aggregates in the cell death that characterizes the diseases remains unclear. Identification of small molecule probes that modulate protein aggregation and cytotoxicity caused by aggregated proteins may greatly facilitate the studies on pathogenesis of these diseases and potentially lead to development of new therapies. Based on a detergent insoluble property of the Huntingtin protein aggregates, we have developed a homogenous assay to rapidly quantitate the levels of protein aggregates in a cellular model of Huntington’s disease. The protein aggregation assay has also been multiplexed with a protease release assay for the measurement of cytotoxicity resulting from aggregated proteins in the same cells. Through a testing screen of a compound library, we have demonstrated that this multiplexed cytotoxicity and protein aggregation assay has ability to identify active compounds that prevent cell death and/or modulate protein aggregation in cells of the Huntington’s disease model. Therefore, this multiplexed screening approach is also useful for development of high-throughput screening assays for other neurodegenerative diseases involving protein aggregation. PMID:23346268
NASA Astrophysics Data System (ADS)
Magno, Andrea; Pellarin, Riccardo; Caflisch, Amedeo
Amyloid fibrils are ordered polypeptide aggregates that have been implicated in several neurodegenerative pathologies, such as Alzheimer's, Parkinson's, Huntington's, and prion diseases, [1, 2] and, more recently, also in biological functionalities. [3, 4, 5] These findings have paved the way for a wide range of experimental and computational studies aimed at understanding the details of the fibril-formation mechanism. Computer simulations using low-resolution models, which employ a simplified representation of protein geometry and energetics, have provided insights into the basic physical principles underlying protein aggregation in general [6, 7, 8] and ordered amyloid aggregation. [9, 10, 11, 12, 13, 14, 15] For example, Dokholyan and coworkers have used the Discrete Molecular Dynamics method [16, 17] to shed light on the mechanisms of protein oligomerization [18] and the conformational changes that take place in proteins before the aggregation onset. [19, 20] One challenging observation, which is difficult to observe by computer simulations, is the wide range of aggregation scenarios emerging from a variety of biophysical measurements. [21, 22] Atomistic models have been employed to study the conformational space of amyloidogenic polypeptides in the monomeric state, [23, 24, 25] the very initial steps of amyloid formation, [26, 27, 28, 29, 30, 31, 32] and the structural stability of fibril models. [33, 34, 35) However, all-atom simulations of the kinetics of fibril formation are beyond what can be done with modern computers.
Stability of a Random Walk Model for Fruiting Body Aggregation in M. xanthus
NASA Astrophysics Data System (ADS)
McKenzie-Smith, G. C.; Schüttler, H. B.; Cotter, C.; Shimkets, L.
2015-03-01
Myxococcus xanthus exhibits the social starvation behavior of aggregation into a fruiting body containing myxospores able to survive harsh conditions. During fruiting body aggregation, individual bacteria follow random walk paths determined by randomly selected runtimes, turning angles, and speeds. We have simulated this behavior in terms of a continuous-time random walk (CTRW) model, re-formulated as a system of integral equations, describing the angle-resolved cell density, R(r, t, θ), at position r and cell orientation angle θ at time t, and angle-integrated ambient cell density ρ(r, t). By way of a linear stability analysis, we investigated whether a uniform cell density R0 will be unstable for a small non-uniform density perturbation δR(r, t, θ). Such instability indicates aggregate formation, whereas stability indicates absence of aggregation. We show that a broadening of CTRW distributions of the random speed and/or random runtimes strongly favors aggregation. We also show that, in the limit of slowly-varying (long-wavelength) density perturbations, the time-dependent linear density response can be approximated by a drift-diffusion model for which we calculate diffusion and drift coefficients as functions of the CTRW model parameters. Funded by the Fungal Genomics and Computational Biology REU at UGA.
Molecular mechanisms of protein aggregation from global fitting of kinetic models.
Meisl, Georg; Kirkegaard, Julius B; Arosio, Paolo; Michaels, Thomas C T; Vendruscolo, Michele; Dobson, Christopher M; Linse, Sara; Knowles, Tuomas P J
2016-02-01
The elucidation of the molecular mechanisms by which soluble proteins convert into their amyloid forms is a fundamental prerequisite for understanding and controlling disorders that are linked to protein aggregation, such as Alzheimer's and Parkinson's diseases. However, because of the complexity associated with aggregation reaction networks, the analysis of kinetic data of protein aggregation to obtain the underlying mechanisms represents a complex task. Here we describe a framework, using quantitative kinetic assays and global fitting, to determine and to verify a molecular mechanism for aggregation reactions that is compatible with experimental kinetic data. We implement this approach in a web-based software, AmyloFit. Our procedure starts from the results of kinetic experiments that measure the concentration of aggregate mass as a function of time. We illustrate the approach with results from the aggregation of the β-amyloid (Aβ) peptides measured using thioflavin T, but the method is suitable for data from any similar kinetic experiment measuring the accumulation of aggregate mass as a function of time; the input data are in the form of a tab-separated text file. We also outline general experimental strategies and practical considerations for obtaining kinetic data of sufficient quality to draw detailed mechanistic conclusions, and the procedure starts with instructions for extensive data quality control. For the core part of the analysis, we provide an online platform (http://www.amylofit.ch.cam.ac.uk) that enables robust global analysis of kinetic data without the need for extensive programming or detailed mathematical knowledge. The software automates repetitive tasks and guides users through the key steps of kinetic analysis: determination of constraints to be placed on the aggregation mechanism based on the concentration dependence of the aggregation reaction, choosing from several fundamental models describing assembly into linear aggregates and
Diffusion-limited aggregates grown on nonuniform substrates
NASA Astrophysics Data System (ADS)
Cornette, V.; Centres, P. M.; Ramirez-Pastor, A. J.; Nieto, F.
2013-12-01
In the present paper, patterns of diffusion-limited aggregation (DLA) grown on nonuniform substrates are investigated by means of Monte Carlo simulations. We consider a nonuniform substrate as the largest percolation cluster of dropped particles with different structures and forms that occupy more than a single site on the lattice. The aggregates are grown on such clusters, in the range the concentration, p, from the percolation threshold, pc up to the jamming coverage, pj. At the percolation threshold, the aggregates are asymmetrical and the branches are relatively few. However, for larger values of p, the patterns change gradually to a pure DLA. Tiny qualitative differences in this behavior are observed for different k sizes. Correspondingly, the fractal dimension of the aggregates increases as p raises in the same range pc≤p≤pj. This behavior is analyzed and discussed in the framework of the existing theoretical approaches.
Modeling the influence of aggregation on nanoparticle transport and retention in porous media
NASA Astrophysics Data System (ADS)
Taghavy, A.; Pennell, K. D.; Abriola, L. M.
2012-12-01
A number of experimental studies relating to nanoparticle transport have observed the influence of particle-particle interactions (i.e., aggregation) on particle-soil grain interactions (i.e., deposition) in porous media. To date, however, nanoparticle transport models have neglected such particle-particle interactions. Here, a one-dimensional Lagrangian particle transport simulator is presented which couples particle transport and retention in porous media with particle-particle interactions. A random-walk particle-tracking approach is employed to simulate the transport of nanoparticles, with Smoluchowski's second-order expression for perikinetic aggregation incorporated to represent particle-particle interactions. Aggregates are treated as fractal objects to relate cluster mass to size, and a correlation developed by Tufenkji and Elimelech (2004) for single collector contact efficiency is implemented to describe time-dependent transport behavior of growing aggregates. A maximum collector capacity-based extension of colloid filtration theory was coupled with the particle straining of Bradford et al. (2003) to describe the retention of particles in the porous medium. The developed simulator is implemented in a sensitivity study to identify the most important physicochemical factors that influence aggregation and deposition of silver nanoparticles under steady flow conditions in uniform sands. Under reaction-limited conditions (i.e. an aggregation attachment efficiency of less than 1), for aggregation of particles with a primary diameter of 12nm, particle mobility (i.e. the percent elution of particles) increased with aggregation in a ca. 15 cm sand column due to a reduction in the magnitude of Brownian forces. For a substantially longer travel distance (i.e. field scale problems) or at a slower flow velocity (i.e. typical groundwater velocities), however, aggregates may become large enough for the interception, sedimentation, and/or straining processes to dominate
A mathematical model of the dynamics of prion aggregates with chaperone-mediated fragmentation.
Davis, Jason K; Sindi, Suzanne S
2016-05-01
Prions are proteins most commonly associated with fatal neurodegenerative diseases in mammals but are also responsible for a number of harmless heritable phenotypes in yeast. These states arise when a misfolded form of a protein appears and, rather than be removed by cellular quality control mechanisms, persists. The misfolded prion protein forms aggregates and is capable of converting normally folded protein to the misfolded state through direct interaction between the two forms. The dominant mathematical model for prion aggregate dynamics has been the nucleated polymerization model (NPM) which considers the dynamics of only the normal protein and the aggregates. However, for yeast prions the molecular chaperone Hsp104 is essential for prion propagation. Further, although mammals do not express Hsp104, experimental assays have shown Hsp104 also interacts with mammalian prion aggregates. In this study, we generalize the NPM to account for molecular chaperones and develop what we call the enzyme-limited nucleated polymerization model (ELNPM). We discuss existence, uniqueness and stability of solutions to our model and demonstrate that the NPM represents a quasi-steady-state reduction of our model. We validate the ELNPM by demonstrating agreement with experimental results on the yeast prion [Formula: see text] PSI [Formula: see text] that could not be supported by the NPM. Finally, we demonstrate that, in contrast to the NPM, the ELNPM permits the coexistence of multiple prion strains. PMID:26297259
FPLUME-1.0: An integral volcanic plume model accounting for ash aggregation
NASA Astrophysics Data System (ADS)
Folch, A.; Costa, A.; Macedonio, G.
2016-02-01
Eruption source parameters (ESP) characterizing volcanic eruption plumes are crucial inputs for atmospheric tephra dispersal models, used for hazard assessment and risk mitigation. We present FPLUME-1.0, a steady-state 1-D (one-dimensional) cross-section-averaged eruption column model based on the buoyant plume theory (BPT). The model accounts for plume bending by wind, entrainment of ambient moisture, effects of water phase changes, particle fallout and re-entrainment, a new parameterization for the air entrainment coefficients and a model for wet aggregation of ash particles in the presence of liquid water or ice. In the occurrence of wet aggregation, the model predicts an effective grain size distribution depleted in fines with respect to that erupted at the vent. Given a wind profile, the model can be used to determine the column height from the eruption mass flow rate or vice versa. The ultimate goal is to improve ash cloud dispersal forecasts by better constraining the ESP (column height, eruption rate and vertical distribution of mass) and the effective particle grain size distribution resulting from eventual wet aggregation within the plume. As test cases we apply the model to the eruptive phase-B of the 4 April 1982 El Chichón volcano eruption (México) and the 6 May 2010 Eyjafjallajökull eruption phase (Iceland). The modular structure of the code facilitates the implementation in the future code versions of more quantitative ash aggregation parameterization as further observations and experiment data will be available for better constraining ash aggregation processes.
FPLUME-1.0: An integral volcanic plume model accounting for ash aggregation
NASA Astrophysics Data System (ADS)
Folch, Arnau; Costa, Antonio; Macedonio, Giovanni
2016-04-01
Eruption Source Parameters (ESP) characterizing volcanic eruption plumes are crucial inputs for atmospheric tephra dispersal models, used for hazard assessment and risk mitigation. We present FPLUME-1.0, a steady-state 1D cross-section averaged eruption column model based on the Buoyant Plume Theory (BPT). The model accounts for plume bending by wind, entrainment of ambient moisture, effects of water phase changes, particle fallout and re-entrainment, a new parameterization for the air entrainment coefficients and a model for wet aggregation of ash particles in presence of liquid water or ice. In the occurrence of wet aggregation, the model predicts an "effective" grain size distribution depleted in fines with respect to that erupted at the vent. Given a wind profile, the model can be used to determine the column height from the eruption mass flow rate or vice-versa. The ultimate goal is to improve ash cloud dispersal forecasts by better constraining the ESP (column height, eruption rate and vertical distribution of mass) and the "effective" particle grain size distribution resulting from eventual wet aggregation within the plume. As test cases we apply the model to the eruptive phase-B of the 4 April 1982 El Chichón volcano eruption (México) and the 6 May 2010 Eyjafjallajökull eruption phase (Iceland). The modular structure of the code facilitates the implementation in the future code versions of more quantitative ash aggregation parameterization as further observations and experiments data will be available for better constraining ash aggregation processes.
Minami, Takuya; Nakano, Masayoshi
2015-01-22
Electromagnetically induced transparency (EIT), which is known as an efficient control method of optical absorption property, is investigated using the polarizability spectra and population dynamics obtained by solving the quantum Liouville equation. In order to clarify the intermolecular interaction effect on EIT, we examine several molecular aggregate models composed of three-state monomers with the dipole-dipole coupling. On the basis of the present results, we discuss the applicability of EIT in molecular aggregate systems to a new type of optical switch.
Modeling capsid kinetics assembly from the steady state distribution of multi-sizes aggregates
NASA Astrophysics Data System (ADS)
Hozé, Nathanaël; Holcman, David
2014-01-01
The kinetics of aggregation for particles of various sizes depends on their diffusive arrival and fusion at a specific nucleation site. We present here a mean-field approximation and a stochastic jump model for aggregates at equilibrium. This approach is an alternative to the classical Smoluchowski equations that do not have a close form and are not solvable in general. We analyze these mean-field equations and obtain the kinetics of a cluster formation. Our approach provides a simplified theoretical framework to study the kinetics of viral capsid formation, such as HIV from the self-assembly of the structural proteins Gag.
A simple model is presented that allows the pressure difference in a subslab aggregate layer to be estimated as a function of radial distance from the central suction point of an active subslab depressurization system by knowing the average size, thickness, porosity, and permeabi...
Nanoscale insights into full-length prion protein aggregation on model lipid membranes.
Pan, Yangang; Wang, Bin; Zhang, Tong; Zhang, Yanan; Wang, Hongda; Xu, Bingqian
2016-06-30
The aggregates of the full-length human recombinant prion protein (PrP) (23-231) on model membranes were investigated by combining the atomic force microscopy (AFM) measurements and theoretical calculations at pH 5.0, showing the great effect of PrP concentration on its supramolecular assemblies on the lipid bilayer. PMID:27284592
REFINED PBPK MODEL OF AGGREGATE EXPOSURE TO METHYL TERTIARY-BUTYL ETHER
Aggregate (multiple pathway) exposures to methyl tertiary-butyl ether (MTBE) in air and water occur via dermal, inhalation, and oral routes. Previously, physiologically-based pharmacokinetic (PBPK) models have been used to quantify the kinetic behavior of MTBE and its primary met...
Female Faculty Role Models and Student Outcomes: A Caveat about Aggregation
ERIC Educational Resources Information Center
Johnson, Iryna Y.
2014-01-01
The idea that female faculty might serve as role models for female students has led to studies of the effect of female faculty on female student performance. Due to varying levels of aggregation of the measure of student exposure to female faculty--percentage of female faculty at an institution or department, percentage of classes taught by…
Studying the concentration dependence of the aggregation number of a micellar model system by SANS.
Amann, Matthias; Willner, Lutz; Stellbrink, Jörg; Radulescu, Aurel; Richter, Dieter
2015-06-01
We present a small-angle neutron scattering (SANS) structural characterization of n-alkyl-PEO polymer micelles in aqueous solution with special focus on the dependence of the micellar aggregation number on increasing concentration. The single micellar properties in the dilute region up to the overlap concentration ϕ* are determined by exploiting the well characterized unimer exchange kinetics of the model system in a freezing and diluting experiment. The micellar solutions are brought to thermodynamic equilibrium at high temperatures, where unimer exchange is fast, and are then cooled to low temperatures and diluted to concentrations in the limit of infinite dilution. At low temperatures the kinetics, and therefore the key mechanism for micellar rearrangement, is frozen on the experimental time scale, thus preserving the micellar structure in the dilution process. Information about the single micellar structure in the semidilute and concentrated region are extracted from structure factor analysis at high concentrations where the micelles order into fcc and bcc close packed lattices and the aggregation number can be calculated by geometrical arguments. This approach enables us to investigate the aggregation behavior in a wide concentration regime from dilute to 6·ϕ*, showing a constant aggregation number with concentration over a large concentration regime up to a critical concentration about three times ϕ*. When exceeding this critical concentration, the aggregation number was found to increase with increasing concentration. This behavior is compared to scaling theories for star-like polymer micelles. PMID:25892401
NASA Astrophysics Data System (ADS)
Ebrahimi, Ali; Or, Dani
2015-12-01
The constantly changing soil hydration status affects gas and nutrient diffusion through soil pores and thus the functioning of soil microbial communities. The conditions within soil aggregates are of particular interest due to limitations to oxygen diffusion into their core, and the presence of organic carbon often acting as binding agent. We developed a model for microbial life in simulated soil aggregates comprising of 3-D angular pore network model (APNM) that mimics soil hydraulic and transport properties. Within these APNM, we introduced individual motile (flagellated) microbial cells with different physiological traits that grow, disperse, and respond to local nutrients and oxygen concentrations. The model quantifies the dynamics and spatial extent of anoxic regions that vary with hydration conditions, and their role in shaping microbial community size and activity and the spatial (self) segregation of anaerobes and aerobes. Internal carbon source and opposing diffusion directions of oxygen and carbon within an aggregate were essential to emergence of stable coexistence of aerobic and anaerobic communities (anaerobes become extinct when carbon sources are external). The model illustrates a range of hydration conditions that promote or suppress denitrification or decomposition of organic matter and thus affect soil GHG emissions. Model predictions of CO2 and N2O production rates were in good agreement with limited experimental data. These limited tests support the dynamic modeling approach whereby microbial community size, composition, and spatial arrangement emerge from internal interactions within soil aggregates. The upscaling of the results to a population of aggregates of different sizes embedded in a soil profile is underway.
Traffic Flow Management Using Aggregate Flow Models and the Development of Disaggregation Methods
NASA Technical Reports Server (NTRS)
Sun, Dengfeng; Sridhar, Banavar; Grabbe, Shon
2010-01-01
A linear time-varying aggregate traffic flow model can be used to develop Traffic Flow Management (tfm) strategies based on optimization algorithms. However, there are no methods available in the literature to translate these aggregate solutions into actions involving individual aircraft. This paper describes and implements a computationally efficient disaggregation algorithm, which converts an aggregate (flow-based) solution to a flight-specific control action. Numerical results generated by the optimization method and the disaggregation algorithm are presented and illustrated by applying them to generate TFM schedules for a typical day in the U.S. National Airspace System. The results show that the disaggregation algorithm generates control actions for individual flights while keeping the air traffic behavior very close to the optimal solution.
Fader, Joseph E.; Juliano, Steven A.
2014-01-01
We investigated the aggregation model of coexistence as a potential mechanism explaining patterns of coexistence between container mosquitoes Aedes albopictus and Aedes aegypti in southern Florida. Aedes aegypti coexists with the invasive A. albopictus in many locations despite being an inferior resource competitor under most conditions. In agreement with aggregation theory we observed significant intraspecific aggregation of A. albopictus in all six field sites sampled in southern Florida in 2009. Quantitative results suggest that larval distributions of A. albopictus across containers are sufficiently aggregated to permit persistence of the inferior competitor A. aegypti. We tested whether observed levels of A. albopictus aggregation would significantly improve A. aegypti population performance in a controlled laboratory competition experiment manipulating A. albopictus aggregation while holding mean densities constant. We quantified A. aegypti’s estimated rate of population change for replicate, multi-container cohorts in response to increasing A. albopictus aggregation across the cohorts. Aedes albopictus aggregation treatments produced J statistics for aggregation that spanned the range observed in the field study. We demonstrate a positive linear relationship between intraspecific aggregation of the superior competitor A. albopictus and estimated rate of population change for cohorts of the inferior A. aegypti. Thus, aggregation of A. albopictus at levels comparable to those observed in nature appears to be sufficient to reduce significantly the competitive impact of A. albopictus on multi-container cohorts of A. aegypti, and may therefore contribute to local coexistence of these competitors. PMID:23691666
DLA-DQB1 alleles and bone marrow transplantation experiments in narcoleptic dogs.
Wagner, J L; Storb, R; Storer, B; Mignot, E
2000-09-01
Human narcolepsy is a neurological disorder known to be tightly associated with HLA-DQB1*0602. A clinically similar disorder has been described in various dog breeds. The canine form of the disease is inherited as an autosomal recessive disorder in Labrador retrievers and Doberman pinschers (canarc-1) but occurs sporadically in other breeds, most typically dachshunds and poodles. In this study, we have examined if there is a relationship between the development of narcolepsy and specific dog leukocyte antigen (DLA)-DQB1 alleles. Ninety-nine dogs were typed for DLA-DQB1-31 with narcolepsy and 68 control animals. Recent studies have linked the development of autosomal recessive canine narcolepsy to a disruption of the hypocretin receptor 2 (Hcrtr2) gene on the same chromosome as the canine MHC region (CFA12), but not close to the DLA. Four Hcrtr2-positive families (two Doberman pinscher families, one Labrador retriever family, one dachshund family) were analyzed at the DLA-DQ level. No relationship was found between narcolepsy and DLA in Hcrtr2-mediated narcolepsy but loose genetic linkage was observed (Zmax=2.3 at theta=25%, m= 40). Bone marrow transplantation between two DLA identical affected (Hcrtr2-/-) and unaffected (Hcrtr2+/-) siblings was also performed and found not to be successful neither in transmitting narcolepsy nor in relieving the symptoms in Doberman pinschers. DLA-DQB1 was next studied in 11 dogs with sporadic (non-familial) narcolepsy and in unrelated control animals of the same and different breeds. The allelic and carrier frequencies of various DLA-DQB1 alleles were analyzed. There was no strong positive or negative correlation between the development of narcolepsy and specific DLA-DQB1 alleles. These results do not support the involvement of DLA-DQ in canine narcolepsy, whether of sporadic or familial origin. PMID:11034558
Fast community detection based on sector edge aggregation metric model in hyperbolic space
NASA Astrophysics Data System (ADS)
Wang, Zuxi; Li, Qingguang; Xiong, Wei; Jin, Fengdong; Wu, Yao
2016-06-01
By studying the edge aggregation characteristic of nodes in hyperbolic space, Sector Edge Aggregation Metric (SEAM) model is proposed and theoretically proved in this paper. In hyperbolic disk SEAM model determines the minimum angular range of a sector which possesses the maximal edge aggregation of nodes. The set of nodes within such sector has dense internal links, which corresponds with the characteristic of community structure. Based on SEAM model, we propose a fast community detection algorithm called Greedy Optimization Modularity Algorithm (GOMA) which employs greedy optimization strategy and hyperbolic coordinates. GOMA firstly divides initial communities according to the quantitative results of sector edge aggregation given by SEAM and the nodes' hyperbolic coordinates, then based on greedy optimization strategy, only merges the two angular neighboring communities in hyperbolic disk to optimize the network modularity function, and consequently obtains high-quality community detection. The strategies of initial community partition and merger in hyperbolic space greatly improve the speed of searching the most optimal modularity. Experimental results indicate that GOMA is able to detect out high-quality community structure in synthetic and real networks, and performs better when applied to the large-scale and dense networks with strong clustering.
Teh, B G; Cloutier, G
2000-01-01
The present study concerns the modeling and analysis of ultrasound backscattering by red blood cell (RBC) aggregates, which under pathological conditions play a significant role in the rheology of blood within human vessels. A theoretical model based on the convolution between a tissue matrix and a point spread function, representing, respectively, the RBC aggregates and the characteristics of the ultrasound system, was used to examine the influence of the scatterer shape and size on the backscattered power. Both scatterers in the form of clumps of RBC aggregates and rouleaux were modeled. For all simulations, the hematocrit was kept constant at 10%, the ultrasound frequency was 10 MHz, the insonification angle was varied from 0 to 90 degrees , and the scatterer size (diameter for clumps and length for rouleaux) ranged from 4 mum to 120 mum. Under Rayleigh scattering by assuming a Poisson distribution of scatterers in space, the ultrasound backscattered power increased linearly with the particle volume. For non-Rayleigh scatterers, the intensity of the echoes diminished as the scatterer volume increased, with the exception of rouleaux at an angle of 90 degrees . As expected, the backscattered power was angularly dependent for anisotropic particles (rouleaux). The ultrasound backscattered power did not always increase with the size of the aggregates, especially when they were no longer Rayleigh scatterers. In the case of rouleaux, the anisotropy of the backscattered power is emphasized in the non-Rayleigh region. PMID:18238637
FPLUME-1.0: An integrated volcanic plume model accounting for ash aggregation
NASA Astrophysics Data System (ADS)
Folch, A.; Costa, A.; Macedonio, G.
2015-09-01
Eruption Source Parameters (ESP) characterizing volcanic eruption plumes are crucial inputs for atmospheric tephra dispersal models, used for hazard assessment and risk mitigation. We present FPLUME-1.0, a steady-state 1-D cross-section averaged eruption column model based on the Buoyant Plume Theory (BPT). The model accounts for plume bent over by wind, entrainment of ambient moisture, effects of water phase changes, particle fallout and re-entrainment, a new parameterization for the air entrainment coefficients and a model for wet aggregation of ash particles in presence of liquid water or ice. In the occurrence of wet aggregation, the model predicts an "effective" grain size distribution depleted in fines with respect to that erupted at the vent. Given a wind profile, the model can be used to determine the column height from the eruption mass flow rate or vice-versa. The ultimate goal is to improve ash cloud dispersal forecasts by better constraining the ESP (column height, eruption rate and vertical distribution of mass) and the "effective" particle grain size distribution resulting from eventual wet aggregation within the plume. As test cases we apply the model to the eruptive phase-B of the 4 April 1982 El Chichón volcano eruption (México) and the 6 May 2010 Eyjafjallajökull eruption phase (Iceland).
Aggregated Particle-size distributions for tephra-deposit model forecasts
NASA Astrophysics Data System (ADS)
Mastin, L. G.; Durant, A. J.; Van Eaton, A. R.
2015-12-01
The accuracy of models that forecast atmospheric transport and deposition of tephra to anticipate hazards during volcanic eruptions is limited by the fact that fine ash tends to aggregate and fall out more rapidly than the individual constituent particles. Aggregation is generally accounted for by representing fine ash as aggregates with density ρagg and a log-normal size range with median μagg and standard deviation σagg. Values of these parameters likely vary with eruption type, grain size, and atmospheric conditions. To date, no studies have examined how the values vary from one eruption or deposit to another. In this study, we used the Ash3d tephra model to simulate four deposits: 18 May 1980 Mount St. Helens, 16-17 September 1992 Crater Peak (Mount Spurr), Alaska, 17 June 1996 Ruapehu, and 23 March 2009 Mount Redoubt volcano. In 158 simulations, we systematically varied μagg (1-2.3Φ) and σagg (0.1-0.3Φ), using ellipsoidal aggregates with =600 kg m-3 and a shape factor F≡((b+c)/2a)=0.44 . We evaluated the goodness of fit using three statistical comparisons: modeled versus measured (1) mass load at individual sample locations; (2) mass load versus distance along the dispersal axis; and (3) isomass area. For all deposits, the best-fit μagg ranged narrowly between ~1.6-2.0Φ (0.33-0.25mm), despite large variations in erupted mass (0.25-50 Tg), plume height (8.5-25 km), mass fraction of fine (<0.063mm) ash (3-59%), atmospheric temperature, aggregation mechanism, and water content between these eruptions. This close agreement suggests that the aggregation process may be modeled as a discrete process that is agnostic to the eruptive style or magnitude of eruption. This result paves the way to a simple, computationally-efficient parameterization of aggregation that is suitable for use in operational deposit forecasts. Further research may indicate whether this narrow range also reflects physical constraints on processes in the evolving cloud.
Aggregation of peptides in the tube model with correlated sidechain orientations
NASA Astrophysics Data System (ADS)
Hung, Nguyen Ba; Hoang, Trinh Xuan
2015-06-01
The ability of proteins and peptides to aggregate and form toxic amyloid fibrils is associated with a range of diseases including BSE (or mad cow), Alzheimer's and Parkinson's Diseases. In this study, we investigate the the role of amino acid sequence in the aggregation propensity by using a modified tube model with a new procedure for hydrophobic interaction. In this model, the amino acid sidechains are not considered explicitly, but their orientations are taken into account in the formation of hydrophobic contact. Extensive Monte Carlo simulations for systems of short peptides are carried out with the use of parallel tempering technique. Our results show that the propensity to form and the structures of the aggregates strongly depend on the amino acid sequence and the number of peptides. Some sequences may not aggregate at all at a presumable physiological temperature while other can easily form fibril-like, β-sheet struture. Our study provides an insight into the principles of how the formation of amyloid can be governed by amino acid sequence.
A Fractal Model for the Capacitance of Lunar Dust and Lunar Dust Aggregates
NASA Technical Reports Server (NTRS)
Collier, Michael R.; Stubbs, Timothy J.; Keller, John W.; Farrell, William M.; Marshall, John; Richard, Denis Thomas
2011-01-01
Lunar dust grains and dust aggregates exhibit clumping, with an uneven mass distribution, as well as features that span many spatial scales. It has been observed that these aggregates display an almost fractal repetition of geometry with scale. Furthermore, lunar dust grains typically have sharp protrusions and jagged features that result from the lack of aeolian weathering (as opposed to space weathering) on the Moon. A perfectly spherical geometry, frequently used as a model for lunar dust grains, has none of these characteristics (although a sphere may be a reasonable proxy for the very smallest grains and some glasses). We present a fractal model for a lunar dust grain or aggregate of grains that reproduces (1) the irregular clumpy nature of lunar dust, (2) the presence of sharp points, and (3) dust features that span multiple scale lengths. We calculate the capacitance of the fractal lunar dust analytically assuming fixed dust mass (i.e. volume) for an arbitrary number of fractal levels and compare the capacitance to that of a non-fractal object with the same volume, surface area, and characteristic width. The fractal capacitance is larger than that of the equivalent non-fractal object suggesting that for a given potential, electrostatic forces on lunar dust grains and aggregates are greater than one might infer from assuming dust grains are sphericaL Consequently, electrostatic transport of lunar dust grains, for example lofting, appears more plausible than might be inferred by calculations based on less realistic assumptions about dust shape and associated capacitance.
The development of an episode selection and aggregation approach, designed to support distributional estimation of use with the Models-3 Community Multiscale Air Quality (CMAQ) model, is described. The approach utilized cluster analysis of the 700-hPa east-west and north-south...
A European model and case studies for aggregate exposure assessment of pesticides.
Kennedy, Marc C; Glass, C Richard; Bokkers, Bas; Hart, Andy D M; Hamey, Paul Y; Kruisselbrink, Johannes W; de Boer, Waldo J; van der Voet, Hilko; Garthwaite, David G; van Klaveren, Jacob D
2015-05-01
Exposures to plant protection products (PPPs) are assessed using risk analysis methods to protect public health. Traditionally, single sources, such as food or individual occupational sources, have been addressed. In reality, individuals can be exposed simultaneously to multiple sources. Improved regulation therefore requires the development of new tools for estimating the population distribution of exposures aggregated within an individual. A new aggregate model is described, which allows individual users to include as much, or as little, information as is available or relevant for their particular scenario. Depending on the inputs provided by the user, the outputs can range from simple deterministic values through to probabilistic analyses including characterisations of variability and uncertainty. Exposures can be calculated for multiple compounds, routes and sources of exposure. The aggregate model links to the cumulative dietary exposure model developed in parallel and is implemented in the web-based software tool MCRA. Case studies are presented to illustrate the potential of this model, with inputs drawn from existing European data sources and models. These cover exposures to UK arable spray operators, Italian vineyard spray operators, Netherlands users of a consumer spray and UK bystanders/residents. The model could also be adapted to handle non-PPP compounds. PMID:25280924
The Aggregate Representation of Terrestrial Land Covers Within Global Climate Models (GCM)
NASA Technical Reports Server (NTRS)
Shuttleworth, W. James; Sorooshian, Soroosh
1996-01-01
This project had four initial objectives: (1) to create a realistic coupled surface-atmosphere model to investigate the aggregate description of heterogeneous surfaces; (2) to develop a simple heuristic model of surface-atmosphere interactions; (3) using the above models, to test aggregation rules for a variety of realistic cover and meteorological conditions; and (4) to reconcile biosphere-atmosphere transfer scheme (BATS) land covers with those that can be recognized from space; Our progress in meeting these objectives can be summarized as follows. Objective 1: The first objective was achieved in the first year of the project by coupling the Biosphere-Atmosphere Transfer Scheme (BATS) with a proven two-dimensional model of the atmospheric boundary layer. The resulting model, BATS-ABL, is described in detail in a Masters thesis and reported in a paper in the Journal of Hydrology Objective 2: The potential value of the heuristic model was re-evaluated early in the project and a decision was made to focus subsequent research around modeling studies with the BATS-ABL model. The value of using such coupled surface-atmosphere models in this research area was further confirmed by the success of the Tucson Aggregation Workshop. Objective 3: There was excellent progress in using the BATS-ABL model to test aggregation rules for a variety of realistic covers. The foci of attention have been the site of the First International Satellite Land Surface Climatology Project Field Experiment (FIFE) in Kansas and one of the study sites of the Anglo-Brazilian Amazonian Climate Observational Study (ABRACOS) near the city of Manaus, Amazonas, Brazil. These two sites were selected because of the ready availability of relevant field data to validate and initiate the BATS-ABL model. The results of these tests are given in a Masters thesis, and reported in two papers. Objective 4: Progress far exceeded original expectations not only in reconciling BATS land covers with those that can be
Modeling the interplay between protein and lipid aggregation in supported membranes.
de Prado Salas, Pablo González; Encinar, Mario; Alonso, Alvaro; Vélez, Marisela; Tarazona, Pedro
2015-01-01
We present a theoretical model that deals with the complex interplay between lipid segregation and the self-aggregation of lipid-attached proteins. The model, in contrast to previous ones that consider proteins only as passive elements affecting the lipid distribution, describes the system including three terms: the dynamic interactions between protein monomers, the interactions between lipid components, and a mixed term considering protein-lipid interactions. It is used to explain experimental results performed on a well-defined system in which a self-aggregating soluble bacterial cytoskeletal protein polymerizes on a lipid bilayer containing two lipid components. All the elements considered in a previously described protein model, including torsion of the monomers within the filament, are needed to account for the observed filament shapes. The model also points out that lipid segregation can affect the length and curvature of the filaments and that the dynamic behavior of the lipids and proteins can have different time scales, giving rise to memory effects. This simple model that considers a dynamic protein assembly on a fluid and active lipid surface can be easily extended to other biologically relevant situations in which the interplay between protein and lipid aggregation is needed to fully describe the system. PMID:24968242
Aggregated Modeling and Control of Air Conditioning Loads for Demand Response
Zhang, Wei; Lian, Jianming; Chang, Chin-Yao; Kalsi, Karanjit
2013-06-21
Demand response is playing an increasingly important role in the efficient and reliable operation of the electric grid. Modeling the dynamic behavior of a large population of responsive loads is especially important to evaluate the effectiveness of various demand response strategies. In this paper, a highly-accurate aggregated model is developed for a population of air conditioning loads. The model effectively includes statistical information of the population, systematically deals with load heterogeneity, and accounts for second-order dynamics necessary to accurately capture the transient dynamics in the collective response. Based on the model, a novel aggregated control strategy is designed for the load population under realistic conditions. The proposed controller is fully responsive and achieves the control objective without sacrificing end-use performance. The proposed aggregated modeling and control strategies are validated through realistic simulations using GridLAB-D. Extensive simulation results indicate that the proposed approach can effectively manage a large number of air conditioning systems to provide various demand response services, such as frequency regulation and peak load reduction.
NASA Astrophysics Data System (ADS)
Jouandet, M.-P.; Jackson, G. A.; Carlotti, F.; Picheral, M.; Stemmann, L.; Blain, S.
2014-08-01
While production of aggregates and their subsequent sinking is known to be one pathway for the downward movement of organic matter from the euphotic zone, the rapid transition from non-aggregated to aggregated particles has not been reported previously. We made one vertical profile of particle size distributions (PSD; sizes ranging from 0.052 to several millimeters in equivalent spherical diameter) at pre-bloom stage and seven vertical profiles 3 weeks later over a 48 h period at early bloom stage using the Underwater Vision Profiler during the Kerguelen Ocean and Plateau Compared Study cruise 2 (KEOPS2, October-November 2011). In these naturally iron-fertilized waters southeast of Kerguelen Island (Southern Ocean), the total particle numerical abundance increased by more than fourfold within this time period. A massive total volume increase associated with particle size distribution changes was observed over the 48 h survey, showing the rapid formation of large particles and their accumulation at the base of the mixed layer. The results of a one-dimensional particle dynamics model support coagulation as the mechanism responsible for the rapid aggregate formation and the development of the VT subsurface maxima. The comparison of VT profiles between early bloom stage and pre-bloom stage indicates an increase of particulate export below 200 m when bloom has developed. These results highlight the role of coagulation in forming large particles and triggering carbon export at the early stage of a naturally iron-fertilized bloom, while zooplankton grazing may dominate later in the season. The rapid changes observed illustrate the critical need to measure carbon export flux with high sampling temporal resolution. Our results are the first published in situ observations of the rapid accumulation of marine aggregates and their export and the general agreement of this rapid event with a model of phytoplankton growth and coagulation.
Uptake of Aggregating Transthyretin by Fat Body in a Drosophila Model for TTR-Associated Amyloidosis
Pokrzywa, Malgorzata; Dacklin, Ingrid; Vestling, Monika; Hultmark, Dan; Lundgren, Erik; Cantera, Rafael
2010-01-01
Background A functional link has been established between the severe neurodegenerative disorder Familial amyloidotic polyneuropathy and the enhanced propensity of the plasma protein transthyretin (TTR) to form aggregates in patients with single point mutations in the TTR gene. Previous work has led to the establishment of an experimental model based on transgenic expression of normal or mutant forms of human TTR in Drosophila flies. Remarkably, the severity of the phenotype was greater in flies that expressed a single copy than with two copies of the mutated gene. Methodology/Principal Findings In this study, we analyze the distribution of normal and mutant TTR in transgenic flies, and the ultrastructure of TTR-positive tissues to clarify if aggregates and/or amyloid filaments are formed. We report the formation of intracellular aggregates of 20 nm spherules and amyloid filaments in thoracic adipose tissue and in brain glia, two tissues that do not express the transgene. The formation of aggregates of nanospherules increased with age and was more considerable in flies with two copies of mutated TTR. Treatment of human neuronal cells with protein extracts prepared from TTR flies of different age showed that the extracts from older flies were less toxic than those from younger flies. Conclusions/Significance These findings suggest that the uptake of TTR from the circulation and its subsequent segregation into cytoplasmic quasi-crystalline arrays of nanospherules is part of a mechanism that neutralizes the toxic effect of TTR. PMID:21179560
NASA Astrophysics Data System (ADS)
Dasgupta, Anushka
Many studies have suggested that oxidative stress plays an important role in the pathophysiology of both multiple sclerosis (MS) and its animal model experimental autoimmune encephalomyelitis (EAE). Yet, the mechanism by which oxidative stress leads to tissue damage in these disorders is unclear. Recent work from our laboratory has revealed that protein carbonylation, a major oxidative modification caused by severe and/or chronic oxidative stress conditions, is elevated in MS and EAE. Furthermore, protein carbonylation has been shown to alter protein structure leading to misfolding/aggregation. These findings prompted me to hypothesize that carbonylated proteins, formed as a consequence of oxidative stress and/or decreased proteasomal activity, promote protein aggregation to mediate neuronal apoptosis in vitro and in EAE. To test this novel hypothesis, I first characterized protein carbonylation, protein aggregation and apoptosis along the spinal cord during the course of myelin-oligodendrocyte glycoprotein (MOG)35-55 peptide-induced EAE in C57BL/6 mice [Chapter 2]. The results show that carbonylated proteins accumulate throughout the course of the disease, albeit by different mechanisms: increased oxidative stress in acute EAE and decreased proteasomal activity in chronic EAE. I discovered not only that there is a temporal correlation between protein carbonylation and apoptosis but also that carbonyl levels are significantly higher in apoptotic cells. A high number of juxta-nuclear and cytoplasmic protein aggregates containing the majority of the oxidized proteins are also present during the course of EAE, which seems to be due to reduced autophagy. In chapter 3, I show that when gluthathione levels are reduced to those in EAE spinal cord, both neuron-like PC12 (nPC12) cells and primary neuronal cultures accumulate carbonylated proteins and undergo cell death (both by necrosis and apoptosis). Immunocytochemical and biochemical studies also revealed a temporal
Woehl, Taylor J.; Park, Chiwoo; Evans, James E.; Arslan, Ilke; Ristenpart, William D.; Browning, Nigel D.
2014-01-08
Direct observations of solution-phase nanoparticle growth using in situ liquid transmission electron microscopy (TEM) have demonstrated the importance of “non-classical” growth mechanisms, such as aggregation and coalescence, on the growth and final morphology of nanocrystals at the atomic and single nanoparticle scales. To date, groups have quantitatively interpreted the mean growth rate of nanoparticles in terms of the Lifshitz-Slyozov-Wagner (LSW) model for Ostwald ripening, but less attention has been paid to modeling the corresponding particle size distribution. Here we use in situ fluid stage scanning TEM to demonstrate that silver nanoparticles grow by a length-scale dependent mechanism, where individual nanoparticles grow by monomer attachment but ensemble-scale growth is dominated by aggregation. Although our observed mean nanoparticle growth rate is consistent with the LSW model, we show that the corresponding particle size distribution is broader and more symmetric than predicted by LSW. Following direct observations of aggregation, we interpret the ensemble-scale growth using Smoluchowski kinetics and demonstrate that the Smoluchowski model quantitatively captures the mean growth rate and particle size distribution.
Detection, monitoring and modelling of alkali-aggregate reaction in Kouga Dam (South Africa)
Elges, H.; Lecocq, P.; Oosthuizen, C.; Geertsema, A.
1995-12-31
Kouga Dam (formerly Paul Sauer Dam) is a double curvature arch dam completed in 1969. The aggregates and the cement used for the construction have subsequently been proven to be alkali reactive. The results of the monitoring programme and the alkali-aggregate reaction (AAR) tests as well as the methodology developed to standardise the logging of cores for these investigations are presented. A brief description of the Finite Element Model used to approximate the AAR process in order to determine positions for in-situ stress measurements is also given. The aim with these tests is to refine the model for prediction of the long-term behaviour of the dam and to make an assessment of the possibility of raising the dam.
Hao, Yan; Kemper, Peter; Smith, Gregory D
2009-09-01
Mathematical models of calcium release sites derived from Markov chain models of intracellular calcium channels exhibit collective gating reminiscent of the experimentally observed phenomenon of calcium puffs and sparks. Such models often take the form of stochastic automata networks in which the transition probabilities of each channel depend on the local calcium concentration and thus the state of the other channels. In order to overcome the state-space explosion that occurs in such compositionally defined calcium release site models, we have implemented several automated procedures for model reduction using fast/slow analysis. After categorizing rate constants in the single channel model as either fast or slow, groups of states in the expanded release site model that are connected by fast transitions are lumped, and transition rates between reduced states are chosen consistent with the conditional probability distribution among states within each group. For small problems these conditional probability distributions can be numerically calculated from the full model without approximation. For large problems the conditional probability distributions can be approximated without the construction of the full model by assuming rapid mixing of states connected by fast transitions. Alternatively, iterative aggregation/disaggregation may be employed to obtain reduced calcium release site models in a memory-efficient fashion. Benchmarking of several different iterative aggregation/disaggregation-based fast/slow reduction schemes establishes the effectiveness of automated calcium release site reduction utilizing the Koury-McAllister-Stewart method. PMID:19792032
Xu, Zhijie; Meakin, Paul
2011-01-28
Two-dimensional dendritic growth due to solute precipitation was simulated using a phase-field model reported earlier [Z. Xu and P. Meakin, J. Chem. Phys. 129, 014705 (2008)]. It was shown that diffusion-limited precipitation due to the chemical reaction at the solid-liquid interface posses similarities with diffusion-limited aggregation (DLA). The diffusion-limited precipitation is attained by setting the chemical reaction rate much larger compared to the solute diffusion to eliminate the effect of the interface growth kinetics. The phase-field simulation results were in reasonable agreement with the analytical solutions. The fractal solid fingers can be formed in the diffusion-limited precipitation and have a fractal dimension measured , close to 1.64, the fractal dimensionality of large square lattice diffusion-limited aggregation (DLA) clusters.
Modeling human protein aggregation cardiomyopathy using murine induced pluripotent stem cells.
Limphong, Pattraranee; Zhang, Huali; Christians, Elisabeth; Liu, Qiang; Riedel, Michael; Ivey, Kathryn; Cheng, Paul; Mitzelfelt, Katie; Taylor, Graydon; Winge, Dennis; Srivastava, Deepak; Benjamin, Ivor
2013-03-01
Several mutations in αB-crystallin (CryAB), a heat shock protein with chaperone-like activities, are causally linked to skeletal and cardiac myopathies in humans. To better understand the underlying pathogenic mechanisms, we had previously generated transgenic (TG) mice expressing R120GCryAB, which recapitulated distinguishing features of the myopathic disorder (e.g., protein aggregates, hypertrophic cardiomyopathy). To determine whether induced pluripotent stem cell (iPSC)-derived cardiomyocytes, a new experimental approach for human disease modeling, would be relevant to aggregation-prone disorders, we decided to exploit the existing transgenic mouse model to derive iPSCs from tail tip fibroblasts. Several iPSC lines were generated from TG and non-TG mice and validated for pluripotency. TG iPSC-derived cardiomyocytes contained perinuclear aggregates positive for CryAB staining, whereas CryAB protein accumulated in both detergent-soluble and insoluble fractions. iPSC-derived cardiomyocytes identified by cardiac troponin T staining were significantly larger when expressing R120GCryAB at a high level in comparison with TG low expressor or non-TG cells. Expression of fetal genes such as atrial natriuretic factor, B-type natriuretic peptide, and α-skeletal α-actin, assessed by quantitative reverse transcription-polymerase chain reaction, were increased in TG cardiomyocytes compared with non-TG, indicating the activation of the hypertrophic genetic program in vitro. Our study demonstrates for the first time that differentiation of R120G iPSCs into cardiomyocytes causes protein aggregation and cellular hypertrophy, recapitulating in vitro key pathognomonic hallmarks found in both animal models and patients. Our findings pave the way for further studies exploiting this cell model system for mechanistic and therapeutic investigations. PMID:23430692
Zheng, Hanqiao; Tang, Mingxin; Zheng, Qingwen; Kumarapeli, Asangi R. K.; Horak, Kathleen M.; Tian, Zongwen; Wang, Xuejun
2010-01-01
Objective The goal of this preclinical study was to assess the therapeutic efficacy of doxycycline (Doxy) for desmin-related cardiomyopathy (DRC) and to elucidate the potential mechanisms involved. Background DRC, exemplifying cardiac proteinopathy, is characterized by intrasarcoplasmic protein aggregation and cardiac insufficiency. No effective treatment for DRC is presently available. Doxy was shown to attenuate aberrant intranuclear aggregation and toxicity of misfolded proteins in non-cardiac cells and animal models of other proteinopathies. Methods Mice and cultured neonatal rat cardiomyocytes with transgenic (TG) expression of a human DRC-linked missense mutant αB-crystallin (CryABR120G) were used for testing the effect of Doxy. Doxy was administered via drinking water (6 mg/ml) initiated at 8 or 16 weeks of age. Results Doxy treatment initiated at 16 weeks of age significantly delayed the premature death of CryABR120G TG mice, with a median lifespan of 30.4 weeks (placebo group 25 weeks, p<0.01). In another cohort of CryABR120G TG mice, Doxy treatment initiated at 8 weeks of age significantly attenuated cardiac hypertrophy in one month. Further investigation revealed that Doxy significantly reduced the abundance of CryAB-positive microscopic aggregates, detergent-resistant CryAB oligomers, and total ubiquitinated proteins in CryABR120G TG hearts. In cell culture, Doxy treatment dose-dependently suppressed the formation of both microscopic protein aggregates and detergent-resistant soluble CryABR120G oligomers, and reversed the upregulation of p62 protein induced by adenovirus-mediated CryABR120G expression. Conclusions Doxy suppresses CryABR120G induced aberrant protein aggregation in cardiomyocytes and prolongs CryABR120G based DRC mouse survival. PMID:20947000
Scaling structure of the growth-probability distribution in diffusion-limited aggregation processes
NASA Astrophysics Data System (ADS)
Hayakawa, Y.; Sato, S.; Matsushita, M.
1987-08-01
In nonequilibrium growth such as diffusion-limited aggregation (DLA), the growth-site probability distribution characterizes these growth processes. By solving the Laplace equation numerically, we calculate the growth probability Pg(x) at the perimeter site x of clusters for the DLA and its generalized version called the η model, and obtain the generalized dimension D(q) and the f-α spectrum proposed by Halsey et al.
NASA Astrophysics Data System (ADS)
Jokulsdottir, Tinna; Archer, David
2016-04-01
We present a new mechanistic model, stochastic, Lagrangian aggregate model of sinking particles (SLAMS) for the biological pump in the ocean, which tracks the evolution of individual particles as they aggregate, disaggregate, sink, and are altered by chemical and biological processes. SLAMS considers the impacts of ballasting by mineral phases, binding of aggregates by transparent exopolymer particles (TEP), zooplankton grazing and the fractal geometry (porosity) of the aggregates. Parameterizations for age-dependent organic carbon (orgC) degradation kinetics, and disaggregation driven by zooplankton grazing and TEP degradation, are motivated by observed particle fluxes and size spectra throughout the water column. The model is able to explain observed variations in orgC export efficiency and rain ratio from the euphotic zone and to the sea floor as driven by sea surface temperature and the primary production rate and seasonality of primary production. The model provides a new mechanistic framework with which to predict future changes on the flux attenuation of orgC in response to climate change forcing.
Adjusting particle-size distributions to account for aggregation in tephra-deposit model forecasts
NASA Astrophysics Data System (ADS)
Mastin, Larry G.; Van Eaton, Alexa R.; Durant, Adam J.
2016-07-01
Volcanic ash transport and dispersion (VATD) models are used to forecast tephra deposition during volcanic eruptions. Model accuracy is limited by the fact that fine-ash aggregates (clumps into clusters), thus altering patterns of deposition. In most models this is accounted for by ad hoc changes to model input, representing fine ash as aggregates with density ρagg, and a log-normal size distribution with median μagg and standard deviation σagg. Optimal values may vary between eruptions. To test the variance, we used the Ash3d tephra model to simulate four deposits: 18 May 1980 Mount St. Helens; 16-17 September 1992 Crater Peak (Mount Spurr); 17 June 1996 Ruapehu; and 23 March 2009 Mount Redoubt. In 192 simulations, we systematically varied μagg and σagg, holding ρagg constant at 600 kg m-3. We evaluated the fit using three indices that compare modeled versus measured (1) mass load at sample locations; (2) mass load versus distance along the dispersal axis; and (3) isomass area. For all deposits, under these inputs, the best-fit value of μagg ranged narrowly between ˜ 2.3 and 2.7φ (0.20-0.15 mm), despite large variations in erupted mass (0.25-50 Tg), plume height (8.5-25 km), mass fraction of fine ( < 0.063 mm) ash (3-59 %), atmospheric temperature, and water content between these eruptions. This close agreement suggests that aggregation may be treated as a discrete process that is insensitive to eruptive style or magnitude. This result offers the potential for a simple, computationally efficient parameterization scheme for use in operational model forecasts. Further research may indicate whether this narrow range also reflects physical constraints on processes in the evolving cloud.
Aggregation of LoD 1 building models as an optimization problem
NASA Astrophysics Data System (ADS)
Guercke, R.; Götzelmann, T.; Brenner, C.; Sester, M.
3D city models offered by digital map providers typically consist of several thousands or even millions of individual buildings. Those buildings are usually generated in an automated fashion from high resolution cadastral and remote sensing data and can be very detailed. However, not in every application such a high degree of detail is desirable. One way to remove complexity is to aggregate individual buildings, simplify the ground plan and assign an appropriate average building height. This task is computationally complex because it includes the combinatorial optimization problem of determining which subset of the original set of buildings should best be aggregated to meet the demands of an application. In this article, we introduce approaches to express different aspects of the aggregation of LoD 1 building models in the form of Mixed Integer Programming (MIP) problems. The advantage of this approach is that for linear (and some quadratic) MIP problems, sophisticated software exists to find exact solutions (global optima) with reasonable effort. We also propose two different heuristic approaches based on the region growing strategy and evaluate their potential for optimization by comparing their performance to a MIP-based approach.
NASA Astrophysics Data System (ADS)
Ilie, Ioana M.; den Otter, Wouter K.; Briels, Wim J.
2016-02-01
Particles in simulations are traditionally endowed with fixed interactions. While this is appropriate for particles representing atoms or molecules, objects with significant internal dynamics—like sequences of amino acids or even an entire protein—are poorly modelled by invariable particles. We develop a highly coarse grained polymorph patchy particle with the ultimate aim of simulating proteins as chains of particles at the secondary structure level. Conformational changes, e.g., a transition between disordered and β-sheet states, are accommodated by internal coordinates that determine the shape and interaction characteristics of the particles. The internal coordinates, as well as the particle positions and orientations, are propagated by Brownian Dynamics in response to their local environment. As an example of the potential offered by polymorph particles, we model the amyloidogenic intrinsically disordered protein α-synuclein, involved in Parkinson's disease, as a single particle with two internal states. The simulations yield oligomers of particles in the disordered state and fibrils of particles in the "misfolded" cross-β-sheet state. The aggregation dynamics is complex, as aggregates can form by a direct nucleation-and-growth mechanism and by two-step-nucleation through conversions between the two cluster types. The aggregation dynamics is complex, with fibrils formed by direct nucleation-and-growth, by two-step-nucleation through the conversion of an oligomer and by auto-catalysis of this conversion.
Allelic diversity at the DLA-88 locus in Golden Retriever and Boxer breeds is limited.
Ross, P; Buntzman, A S; Vincent, B G; Grover, E N; Gojanovich, G S; Collins, E J; Frelinger, J A; Hess, P R
2012-08-01
In the dog, previous analyses of major histocompatibility complex class I genes suggest a single polymorphic locus, dog leukocyte antigen (DLA)-88. While 51 alleles have been reported, estimates of prevalence have not been made. We hypothesized that, within a breed, DLA-88 diversity would be restricted, and one or more dominant alleles could be identified. Accordingly, we determined allele usage in 47 Golden Retrievers and 39 Boxers. In each population, 10 alleles were found; 4 were shared. Seven novel alleles were identified. DLA-88*05101 and *50801 predominated in Golden Retrievers, while most Boxers carried *03401. In these breeds, DLA-88 polymorphisms are limited and largely non-overlapping. The finding of highly prevalent alleles fulfills an important prerequisite for studying canine CD8+ T-cell responses. PMID:22571293
Allelic diversity at the DLA-88 locus in Golden Retriever and Boxer breeds is limited
Ross, Peter; Buntzman, Adam S.; Vincent, Benjamin G.; Grover, Elise N.; Gojanovich, Gregory S.; Collins, Edward J.; Frelinger, Jeffrey A.; Hess, Paul R.
2012-01-01
In the dog, previous analyses of major histocompatibility complex (MHC) class I genes suggest a single polymorphic locus, Dog Leukocyte Antigen (DLA)-88. While 51 alleles have been reported, estimates of prevalence have not been made. We hypothesized that, within a breed, DLA-88 diversity would be restricted, and one or more dominant alleles could be identified. Accordingly, we determined allele usage in 47 Golden Retrievers and 39 Boxers. In each population, 10 alleles were found; 4 were shared. Seven novel alleles were identified. DLA-88*05101 and *50801 predominated in Golden Retrievers, while most Boxers carried *03401. In these breeds DLA-88 polymorphisms are limited and largely non-overlapping. The finding of highly prevalent alleles fulfills an important prerequisite for studying canine CD8+ T-cell responses. PMID:22571293
Local-aggregate modeling for big data via distributed optimization: Applications to neuroimaging.
Hu, Yue; Allen, Genevera I
2015-12-01
Technological advances have led to a proliferation of structured big data that have matrix-valued covariates. We are specifically motivated to build predictive models for multi-subject neuroimaging data based on each subject's brain imaging scans. This is an ultra-high-dimensional problem that consists of a matrix of covariates (brain locations by time points) for each subject; few methods currently exist to fit supervised models directly to this tensor data. We propose a novel modeling and algorithmic strategy to apply generalized linear models (GLMs) to this massive tensor data in which one set of variables is associated with locations. Our method begins by fitting GLMs to each location separately, and then builds an ensemble by blending information across locations through regularization with what we term an aggregating penalty. Our so called, Local-Aggregate Model, can be fit in a completely distributed manner over the locations using an Alternating Direction Method of Multipliers (ADMM) strategy, and thus greatly reduces the computational burden. Furthermore, we propose to select the appropriate model through a novel sequence of faster algorithmic solutions that is similar to regularization paths. We will demonstrate both the computational and predictive modeling advantages of our methods via simulations and an EEG classification problem. PMID:26295449
Diepgen, T L; Blettner, M
1996-05-01
In order to determine the relative importance of genetics and the environment on the occurrence of atopic diseases, we investigated the familial aggregation of atopic eczema, allergic rhinitis, and allergic asthma in the relatives of 426 patients with atopic eczema and 628 subjects with no history of eczema (5,136 family members in total). Analyses were performed by regression models for odds ratios (OR) allowing us to estimate OR for the familial aggregation and simultaneously to adjust for other covariates. Three models were analyzed assuming that the OR i) is the same among any two members of a family, ii) depends on different familial constellations, i.e., whether the pairs are siblings, parents, or parent/sibling pairs, and iii) is not the same between the father and the children and between the mother and the children. The OR of familial aggregation for atopic eczema was 2.16 (95% confidence interval (95%-CI) 1.58-2.96) if no distinction was made between the degree of relationship. Further analyses within the members of the family showed a high OR among siblings (OR = 3.86; 95%-CI 2.10-7.09), while the OR between parents and siblings was only 1.90 (95%-CI 1.31-2.97). Only for atopic eczema was the familial aggregation between fathers and siblings (ms: OR = 2.66; fs: OR = 1.29). This can be explained by stronger maternal heritability, shared physical environment of mother and child, or environmental events that affect the fetus in utero. Since for all atopic diseases a stronger correlation was found between siblings than between siblings and parents, our study indicates that environmental factors, especially during childhood, seem to explain the recently observed increased frequencies of atopic diseases. PMID:8618061
Povlishock, J. T.; Rosenblum, W. I.; Sholley, M. M.; Wei, E. P.
1983-01-01
Those microvascular endothelial events that parallel the evolution of platelet aggregation were evaluated in a well-controlled animal model. Cat pial microvessels were observed through a cranial window while local platelet aggregation was produced by intravenous injection of sodium fluorescein and simultaneous exposure of the pial vessels to light from a filtered mercury lamp that excited the fluorescein. The vessels were fixed in situ when the in vivo observations of a preselected vessel indicated early, intermediate, or advanced aggregation in that vessel. The preselected vessel was then harvested for ultrastructural study together with adjacent vessels from the illuminated field. These vessels and appropriate controls were compared in semiserial thin sections. The onset of platelet aggregation in both venules and arterioles was accompanied by focal endothelial lucency, vacuole formation, luminal membrane rupture, and swelling of the nuclear envelope. These changes were not found in control material. With intermediate aggregation these changes were more common, while with advanced aggregation these abnormalities occurred together with focal endothelial denudation. Thus, in this model denudation occurred only with advanced aggregation and was not a prerequisite for aggregation. Images Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 PMID:6824062
Barrientos, Laura S; Zapata, Gustavo; Crespi, Julian A; Posik, Diego M; Díaz, Silvina; It, Veronica; Peral-García, Pilar; Giovambattista, Guillermo
2013-12-15
Canine chronic superficial keratitis (CSK) is an inflammatory corneal disease that primarily occurs in German shepherd dogs (GSDs). Several studies support the hypothesis that CSK is an immune-mediated disease. To investigate the genetic factors associated with CSK development, the upstream regulatory regions (URRs) of the DLA-DRB, -DQA and -DQB genes were genotyped in 60 dogs, including 32 CSK animals. LD analysis identified two blocks (r(2)≤45), with two DLA-DRB1 and five DLA-DQB1 haplotypes. Analysis of DLA-URR alleles/haplotypes showed a significant association between DQB1*-154 [C/T] (p=0.016) and CSK, suggesting that the T variant may increase the risk for developing CSK disease (OR=3, 95% CI=1.25-7.68). When haplotype associations were performed, the URR-DQB*CATT haplotype was significantly associated with CSK (p=0.016), increasing the risk of develop this disease over two-fold (OR=3, 95%, CI=1.25-7.68). These results showed that dogs homozygous at DRB1*69 [C/T] had a risk for developing CSK disease that was over four times the risk for heterozygotes. This genetic association supports the previous clinical, histological and pharmacological studies that suggest that CSK is an immune-mediated disease, and this association could potentially be used to identify susceptible animals. PMID:24238945
A look into amyloid formation by transthyretin: aggregation pathway and a novel kinetic model.
Faria, Tiago Q; Almeida, Zaida L; Cruz, Pedro F; Jesus, Catarina S H; Castanheira, Pedro; Brito, Rui M M
2015-03-21
The aggregation of proteins into insoluble amyloid fibrils is the hallmark of many, highly debilitating, human pathologies such as Alzheimer's or Parkinson's disease. Transthyretin (TTR) is a homotetrameric protein implicated in several amyloidoses like Senile Systemic Amyloidosis (SSA), Familial Amyloid Polyneuropathy (FAP), Familial Amyloid Cardiomyopathy (FAC), and the rare Central Nervous System selective Amyloidosis (CNSA). In this work, we have investigated the kinetics of TTR aggregation into amyloid fibrils produced by the addition of NaCl to acid-unfolded TTR monomers and we propose a mathematically simple kinetic mechanism to analyse the aggregation kinetics of TTR. We have conducted circular dichroism, intrinsic tryptophan fluorescence and thioflavin-T emission experiments to follow the conformational changes accompanying amyloid formation at different TTR concentrations. Kinetic traces were adjusted to a two-step model with the first step being second-order and the second being unimolecular. The molecular species present in the pathway of TTR oligomerization were characterized by size exclusion chromatography coupled to multi-angle light scattering and by transmission electron microscopy. The results show the transient accumulation of oligomers composed of 6 to 10 monomers in agreement with reports suggesting that these oligomers may be the causative agent of cell toxicity. The results obtained may prove to be useful in understanding the mode of action of different compounds in preventing fibril formation and, therefore, in designing new drugs against TTR amyloidosis. PMID:25694367
Gupta, Anju; Sender, Maximilian; Fields, Sarah; Bothun, Geoffrey D
2014-10-15
Adsorption of suspended particles to the interface of surfactant-dispersed oil droplets can alter emulsion phase and sedimentation behavior. This work examines the effects of model mineral aggregates (silica nanoparticle aggregates or SNAs) on the behavior of oil (octane)-water emulsions prepared using sodium bis(2-ethylhexyl) sulfosuccinate (DOSS). Experiments were conducted at different SNA hydrophobicities in deionized and synthetic seawater (SSW), and at 0.5mM and 2.5mM DOSS. SNAs were characterized by thermogravimetric analysis (TGA) and dynamic light scattering (DLS), and the emulsions were examined by optical and cryogenic scanning electron microscopy. In deionized water, oil-in-water emulsions were formed with DOSS and the SNAs did not adhere to the droplets or alter emulsion behavior. In SSW, water-in-oil emulsions were formed with DOSS and SNA-DOSS binding through cation bridging led to phase inversion to oil-in-water emulsions. Droplet oil-mineral aggregates (OMAs) were observed for hydrophilic SNAs, while hydrophobic SNAs yielded quickly sedimenting agglomerated OMAs. PMID:25172613
Drosophila Melanogaster as a Model System for Studies of Islet Amyloid Polypeptide Aggregation
Schultz, Sebastian Wolfgang; Nilsson, K. Peter R.; Westermark, Gunilla Torstensdotter
2011-01-01
Background Recent research supports that aggregation of islet amyloid polypeptide (IAPP) leads to cell death and this makes islet amyloid a plausible cause for the reduction of beta cell mass, demonstrated in patients with type 2 diabetes. IAPP is produced by the beta cells as a prohormone, and proIAPP is processed into IAPP by the prohormone convertases PC1/3 and PC2 in the secretory granules. Little is known about the pathogenesis for islet amyloid and which intracellular mechanisms are involved in amyloidogenesis and induction of cell death. Methodology/Principal Findings We have established expression of human proIAPP (hproIAPP), human IAPP (hIAPP) and the non-amyloidogenic mouse IAPP (mIAPP) in Drosophila melanogaster, and compared survival of flies with the expression driven to different cell populations. Only flies expressing hproIAPP in neurons driven by the Gal4 driver elavC155,Gal4 showed a reduction in lifespan whereas neither expression of hIAPP or mIAPP influenced survival. Both hIAPP and hproIAPP expression caused formation of aggregates in CNS and fat body region, and these aggregates were both stained by the dyes Congo red and pFTAA, both known to detect amyloid. Also, the morphology of the highly organized protein granules that developed in the fat body of the head in hIAPP and hproIAPP expressing flies was characterized, and determined to consist of 15.8 nm thick pentagonal rod-like structures. Conclusions/Significance These findings point to a potential for Drosophila melanogaster to serve as a model system for studies of hproIAPP and hIAPP expression with subsequent aggregation and developed pathology. PMID:21695120
Optimising Cell Aggregate Expansion in a Perfused Hollow Fibre Bioreactor via Mathematical Modelling
Chapman, Lloyd A. C.; Shipley, Rebecca J.; Whiteley, Jonathan P.; Ellis, Marianne J.; Byrne, Helen M.; Waters, Sarah L.
2014-01-01
The need for efficient and controlled expansion of cell populations is paramount in tissue engineering. Hollow fibre bioreactors (HFBs) have the potential to meet this need, but only with improved understanding of how operating conditions and cell seeding strategy affect cell proliferation in the bioreactor. This study is designed to assess the effects of two key operating parameters (the flow rate of culture medium into the fibre lumen and the fluid pressure imposed at the lumen outlet), together with the cell seeding distribution, on cell population growth in a single-fibre HFB. This is achieved using mathematical modelling and numerical methods to simulate the growth of cell aggregates along the outer surface of the fibre in response to the local oxygen concentration and fluid shear stress. The oxygen delivery to the cell aggregates and the fluid shear stress increase as the flow rate and pressure imposed at the lumen outlet are increased. Although the increased oxygen delivery promotes growth, the higher fluid shear stress can lead to cell death. For a given cell type and initial aggregate distribution, the operating parameters that give the most rapid overall growth can be identified from simulations. For example, when aggregates of rat cardiomyocytes that can tolerate shear stresses of up to are evenly distributed along the fibre, the inlet flow rate and outlet pressure that maximise the overall growth rate are predicted to be in the ranges to (equivalent to to ) and to (or 15.6 psi to 15.7 psi) respectively. The combined effects of the seeding distribution and flow on the growth are also investigated and the optimal conditions for growth found to depend on the shear tolerance and oxygen demands of the cells. PMID:25157635
Kinetic model of the aggregation of alpha-synuclein provides insights into prion-like spreading
Iljina, Marija; Garcia, Gonzalo A.; Horrocks, Mathew H.; Tosatto, Laura; Choi, Minee L.; Ganzinger, Kristina A.; Abramov, Andrey Y.; Gandhi, Sonia; Wood, Nicholas W.; Cremades, Nunilo; Dobson, Christopher M.; Knowles, Tuomas P. J.; Klenerman, David
2016-01-01
The protein alpha-synuclein (αS) self-assembles into small oligomeric species and subsequently into amyloid fibrils that accumulate and proliferate during the development of Parkinson’s disease. However, the quantitative characterization of the aggregation and spreading of αS remains challenging to achieve. Previously, we identified a conformational conversion step leading from the initially formed oligomers to more compact oligomers preceding fibril formation. Here, by a combination of single-molecule fluorescence measurements and kinetic analysis, we find that the reaction in solution involves two unimolecular structural conversion steps, from the disordered to more compact oligomers and then to fibrils, which can elongate by further monomer addition. We have obtained individual rate constants for these key microscopic steps by applying a global kinetic analysis to both the decrease in the concentration of monomeric protein molecules and the increase in oligomer concentrations over a 0.5–140-µM range of αS. The resulting explicit kinetic model of αS aggregation has been used to quantitatively explore seeding the reaction by either the compact oligomers or fibrils. Our predictions reveal that, although fibrils are more effective at seeding than oligomers, very high numbers of seeds of either type, of the order of 104, are required to achieve efficient seeding and bypass the slow generation of aggregates through primary nucleation. Complementary cellular experiments demonstrated that two orders of magnitude lower numbers of oligomers were sufficient to generate high levels of reactive oxygen species, suggesting that effective templated seeding is likely to require both the presence of template aggregates and conditions of cellular stress. PMID:26884195
Sánchez-Marín, Paula; Aierbe, Eneko; Lorenzo, J Ignacio; Mubiana, Valentine K; Beiras, Ricardo; Blust, Ronny
2016-09-01
Copper (Cu) complexation by humic acids (HA) is expected to decrease Cu bioavailability for aquatic organisms as predicted by metal bioavailability models, such as the biotic ligand model (BLM). This has been confirmed for non-feeding organisms such as marine invertebrate embryos or microalgae, but for filter-feeding organisms such as the mussel Mytilus edulis, Cu bioaccumulation was higher in the presence of HA, suggesting that part of the Cu-HA complexes were available for uptake. This study shows the dynamic modeling of Cu accumulation kinetics in the gills and rest of the soft-body of M. edulis in the absence and presence of HA. Assuming that truly dissolved Cu is taken in the body via the gills following BLM premises, and including uptake of Cu-HA aggregates via the gut into the rest compartment, this two-compartmental model could successfully explain the observed bioaccumulation data. This modeling approach gives strong evidence to the hypothesis that Cu-HA aggregates can be ingested by mussels leading to Cu absorption in the digestive system. PMID:27498364
Elenbaas, Jared S; Maitra, Dhiman; Liu, Yang; Lentz, Stephen I; Nelson, Bradley; Hoenerhoff, Mark J; Shavit, Jordan A; Omary, M Bishr
2016-05-01
Protoporphyria is a metabolic disease that causes excess production of protoporphyrin IX (PP-IX), the final biosynthetic precursor to heme. Hepatic PP-IX accumulation may lead to end-stage liver disease. We tested the hypothesis that systemic administration of porphyrin precursors to zebrafish larvae results in protoporphyrin accumulation and a reproducible nongenetic porphyria model. Retro-orbital infusion of PP-IX or the iron chelator deferoxamine mesylate (DFO), with the first committed heme precursor α-aminolevulinic acid (ALA), generates high levels of PP-IX in zebrafish larvae. Exogenously infused or endogenously produced PP-IX accumulates preferentially in the liver of zebrafish larvae and peaks 1 to 3 d after infusion. Similar to patients with protoporphyria, PP-IX is excreted through the biliary system. Porphyrin accumulation in zebrafish liver causes multiorganelle protein aggregation as determined by mass spectrometry and immunoblotting. Endoplasmic reticulum stress and induction of autophagy were noted in zebrafish larvae and corroborated in 2 mouse models of protoporphyria. Furthermore, electron microscopy of zebrafish livers from larvae administered ALA + DFO showed hepatocyte autophagosomes, nuclear membrane ruffling, and porphyrin-containing vacuoles with endoplasmic reticulum distortion. In conclusion, systemic administration of the heme precursors PP-IX or ALA + DFO into zebrafish larvae provides a new model of acute protoporphyria with consequent hepatocyte protein aggregation and proteotoxic multiorganelle alterations and stress.-Elenbaas, J. S., Maitra, D., Liu, Y., Lentz, S. I., Nelson, B., Hoenerhoff, M. J., Shavit, J. A., Omary, M. B. A precursor-inducible zebrafish model of acute protoporphyria with hepatic protein aggregation and multiorganelle stress. PMID:26839379