Coarse-graining of proteins based on elastic network models
NASA Astrophysics Data System (ADS)
Sinitskiy, Anton V.; Voth, Gregory A.
2013-08-01
To simulate molecular processes on biologically relevant length- and timescales, coarse-grained (CG) models of biomolecular systems with tens to even hundreds of residues per CG site are required. One possible way to build such models is explored in this article: an elastic network model (ENM) is employed to define the CG variables. Free energy surfaces are approximated by Taylor series, with the coefficients found by force-matching. CG potentials are shown to undergo renormalization due to roughness of the energy landscape and smoothing of it under coarse-graining. In the case study of hen egg-white lysozyme, the entropy factor is shown to be of critical importance for maintaining the native structure, and a relationship between the proposed ENM-mode-based CG models and traditional CG-bead-based models is discussed. The proposed approach uncovers the renormalizable character of CG models and offers new opportunities for automated and computationally efficient studies of complex free energy surfaces.
Distinct Tensile Response of Model Semi-flexible Elastomer Networks
NASA Astrophysics Data System (ADS)
Aguilera-Mercado, Bernardo M.; Cohen, Claude; Escobedo, Fernando A.
2011-03-01
Through coarse-grained molecular modeling, we study how the elastic response strongly depends upon nanostructural heterogeneities in model networks made of semi-flexible chains exhibiting both regular and realistic connectivity. Idealized regular polymer networks have been shown to display a peculiar elastic response similar to that of super-tough natural materials (e.g., organic adhesives inside abalone shells). We investigate the impact of chain stiffness, and the effect of including tri-block copolymer chains, on the network's topology and elastic response. We find in some systems a dual tensile response: a liquid-like behavior at small deformations, and a distinct saw-tooth shaped stress-strain curve at moderate to large deformations. Additionally, stiffer regular networks exhibit a marked hysteresis over loading-unloading cycles that can be deleted by heating-cooling cycles or by performing deformations along different axes. Furthermore, small variations of chain stiffness may entirely change the nature of the network's tensile response from an entropic to an enthalpic elastic regime, and micro-phase separation of different blocks within elastomer networks may significantly enhance their mechanical strength. This work was supported by the American Chemical Society.
NASA Astrophysics Data System (ADS)
Orellana, Laura; Yoluk, Ozge; Carrillo, Oliver; Orozco, Modesto; Lindahl, Erik
2016-08-01
Protein conformational changes are at the heart of cell functions, from signalling to ion transport. However, the transient nature of the intermediates along transition pathways hampers their experimental detection, making the underlying mechanisms elusive. Here we retrieve dynamic information on the actual transition routes from principal component analysis (PCA) of structurally-rich ensembles and, in combination with coarse-grained simulations, explore the conformational landscapes of five well-studied proteins. Modelling them as elastic networks in a hybrid elastic-network Brownian dynamics simulation (eBDIMS), we generate trajectories connecting stable end-states that spontaneously sample the crystallographic motions, predicting the structures of known intermediates along the paths. We also show that the explored non-linear routes can delimit the lowest energy passages between end-states sampled by atomistic molecular dynamics. The integrative methodology presented here provides a powerful framework to extract and expand dynamic pathway information from the Protein Data Bank, as well as to validate sampling methods in general.
Xia, Kelin
2017-12-20
In this paper, a multiscale virtual particle based elastic network model (MVP-ENM) is proposed for the normal mode analysis of large-sized biomolecules. The multiscale virtual particle (MVP) model is proposed for the discretization of biomolecular density data. With this model, large-sized biomolecular structures can be coarse-grained into virtual particles such that a balance between model accuracy and computational cost can be achieved. An elastic network is constructed by assuming "connections" between virtual particles. The connection is described by a special harmonic potential function, which considers the influence from both the mass distributions and distance relations of the virtual particles. Two independent models, i.e., the multiscale virtual particle based Gaussian network model (MVP-GNM) and the multiscale virtual particle based anisotropic network model (MVP-ANM), are proposed. It has been found that in the Debye-Waller factor (B-factor) prediction, the results from our MVP-GNM with a high resolution are as good as the ones from GNM. Even with low resolutions, our MVP-GNM can still capture the global behavior of the B-factor very well with mismatches predominantly from the regions with large B-factor values. Further, it has been demonstrated that the low-frequency eigenmodes from our MVP-ANM are highly consistent with the ones from ANM even with very low resolutions and a coarse grid. Finally, the great advantage of MVP-ANM model for large-sized biomolecules has been demonstrated by using two poliovirus virus structures. The paper ends with a conclusion.
Hybrid continuum-coarse-grained modeling of erythrocytes
NASA Astrophysics Data System (ADS)
Lyu, Jinming; Chen, Paul G.; Boedec, Gwenn; Leonetti, Marc; Jaeger, Marc
2018-06-01
The red blood cell (RBC) membrane is a composite structure, consisting of a phospholipid bilayer and an underlying membrane-associated cytoskeleton. Both continuum and particle-based coarse-grained RBC models make use of a set of vertices connected by edges to represent the RBC membrane, which can be seen as a triangular surface mesh for the former and a spring network for the latter. Here, we present a modeling approach combining an existing continuum vesicle model with a coarse-grained model for the cytoskeleton. Compared to other two-component approaches, our method relies on only one mesh, representing the cytoskeleton, whose velocity in the tangential direction of the membrane may be different from that of the lipid bilayer. The finitely extensible nonlinear elastic (FENE) spring force law in combination with a repulsive force defined as a power function (POW), called FENE-POW, is used to describe the elastic properties of the RBC membrane. The mechanical interaction between the lipid bilayer and the cytoskeleton is explicitly computed and incorporated into the vesicle model. Our model includes the fundamental mechanical properties of the RBC membrane, namely fluidity and bending rigidity of the lipid bilayer, and shear elasticity of the cytoskeleton while maintaining surface-area and volume conservation constraint. We present three simulation examples to demonstrate the effectiveness of this hybrid continuum-coarse-grained model for the study of RBCs in fluid flows.
The Ribosome Shape Directs mRNA Translocation through Entrance and Exit Dynamics
USDA-ARS?s Scientific Manuscript database
The protein-synthesizing ribosome undergoes large motions to effect the translocation of tRNAs (transfer ribonucleic acids) and mRNA (messenger ribonucleic acid); here the domain motions of this system are explored with a coarse-grained elastic network model using normal mode analysis. Crystal struc...
Hierarchical coarse-graining strategy for protein-membrane systems to access mesoscopic scales
Ayton, Gary S.; Lyman, Edward
2014-01-01
An overall multiscale simulation strategy for large scale coarse-grain simulations of membrane protein systems is presented. The protein is modeled as a heterogeneous elastic network, while the lipids are modeled using the hybrid analytic-systematic (HAS) methodology, where in both cases atomistic level information obtained from molecular dynamics simulation is used to parameterize the model. A feature of this approach is that from the outset liposome length scales are employed in the simulation (i.e., on the order of ½ a million lipids plus protein). A route to develop highly coarse-grained models from molecular-scale information is proposed and results for N-BAR domain protein remodeling of a liposome are presented. PMID:20158037
Na, Hyuntae; Song, Guang
2015-07-01
In a recent work we developed a method for deriving accurate simplified models that capture the essentials of conventional all-atom NMA and identified two best simplified models: ssNMA and eANM, both of which have a significantly higher correlation with NMA in mean square fluctuation calculations than existing elastic network models such as ANM and ANMr2, a variant of ANM that uses the inverse of the squared separation distances as spring constants. Here, we examine closely how the performance of these elastic network models depends on various factors, namely, the presence of hydrogen atoms in the model, the quality of input structures, and the effect of crystal packing. The study reveals the strengths and limitations of these models. Our results indicate that ssNMA and eANM are the best fine-grained elastic network models but their performance is sensitive to the quality of input structures. When the quality of input structures is poor, ANMr2 is a good alternative for computing mean-square fluctuations while ANM model is a good alternative for obtaining normal modes. © 2015 Wiley Periodicals, Inc.
A mass weighted chemical elastic network model elucidates closed form domain motions in proteins
Kim, Min Hyeok; Seo, Sangjae; Jeong, Jay Il; Kim, Bum Joon; Liu, Wing Kam; Lim, Byeong Soo; Choi, Jae Boong; Kim, Moon Ki
2013-01-01
An elastic network model (ENM), usually Cα coarse-grained one, has been widely used to study protein dynamics as an alternative to classical molecular dynamics simulation. This simple approach dramatically saves the computational cost, but sometimes fails to describe a feasible conformational change due to unrealistically excessive spring connections. To overcome this limitation, we propose a mass-weighted chemical elastic network model (MWCENM) in which the total mass of each residue is assumed to be concentrated on the representative alpha carbon atom and various stiffness values are precisely assigned according to the types of chemical interactions. We test MWCENM on several well-known proteins of which both closed and open conformations are available as well as three α-helix rich proteins. Their normal mode analysis reveals that MWCENM not only generates more plausible conformational changes, especially for closed forms of proteins, but also preserves protein secondary structures thus distinguishing MWCENM from traditional ENMs. In addition, MWCENM also reduces computational burden by using a more sparse stiffness matrix. PMID:23456820
Global Motions of the Nuclear Pore Complex: Insights from Elastic Network Models
Lezon, Timothy R.; Sali, Andrej; Bahar, Ivet
2009-01-01
The nuclear pore complex (NPC) is the gate to the nucleus. Recent determination of the configuration of proteins in the yeast NPC at ∼5 nm resolution permits us to study the NPC global dynamics using coarse-grained structural models. We investigate these large-scale motions by using an extended elastic network model (ENM) formalism applied to several coarse-grained representations of the NPC. Two types of collective motions (global modes) are predicted by the ENMs to be intrinsically favored by the NPC architecture: global bending and extension/contraction from circular to elliptical shapes. These motions are shown to be robust against tested variations in the representation of the NPC, and are largely captured by a simple model of a toroid with axially varying mass density. We demonstrate that spoke multiplicity significantly affects the accessible number of symmetric low-energy modes of motion; the NPC-like toroidal structures composed of 8 spokes have access to highly cooperative symmetric motions that are inaccessible to toroids composed of 7 or 9 spokes. The analysis reveals modes of motion that may facilitate macromolecular transport through the NPC, consistent with previous experimental observations. PMID:19730674
Global motions of the nuclear pore complex: insights from elastic network models.
Lezon, Timothy R; Sali, Andrej; Bahar, Ivet
2009-09-01
The nuclear pore complex (NPC) is the gate to the nucleus. Recent determination of the configuration of proteins in the yeast NPC at approximately 5 nm resolution permits us to study the NPC global dynamics using coarse-grained structural models. We investigate these large-scale motions by using an extended elastic network model (ENM) formalism applied to several coarse-grained representations of the NPC. Two types of collective motions (global modes) are predicted by the ENMs to be intrinsically favored by the NPC architecture: global bending and extension/contraction from circular to elliptical shapes. These motions are shown to be robust against tested variations in the representation of the NPC, and are largely captured by a simple model of a toroid with axially varying mass density. We demonstrate that spoke multiplicity significantly affects the accessible number of symmetric low-energy modes of motion; the NPC-like toroidal structures composed of 8 spokes have access to highly cooperative symmetric motions that are inaccessible to toroids composed of 7 or 9 spokes. The analysis reveals modes of motion that may facilitate macromolecular transport through the NPC, consistent with previous experimental observations.
Koehl, Patrice; Poitevin, Frédéric; Navaza, Rafael; Delarue, Marc
2017-03-14
Understanding the dynamics of biomolecules is the key to understanding their biological activities. Computational methods ranging from all-atom molecular dynamics simulations to coarse-grained normal-mode analyses based on simplified elastic networks provide a general framework to studying these dynamics. Despite recent successes in studying very large systems with up to a 100,000,000 atoms, those methods are currently limited to studying small- to medium-sized molecular systems due to computational limitations. One solution to circumvent these limitations is to reduce the size of the system under study. In this paper, we argue that coarse-graining, the standard approach to such size reduction, must define a hierarchy of models of decreasing sizes that are consistent with each other, i.e., that each model contains the information of the dynamics of its predecessor. We propose a new method, Decimate, for generating such a hierarchy within the context of elastic networks for normal-mode analysis. This method is based on the concept of the renormalization group developed in statistical physics. We highlight the details of its implementation, with a special focus on its scalability to large systems of up to millions of atoms. We illustrate its application on two large systems, the capsid of a virus and the ribosome translation complex. We show that highly decimated representations of those systems, containing down to 1% of their original number of atoms, still capture qualitatively and quantitatively their dynamics. Decimate is available as an OpenSource resource.
Zheng, Wenjun
2010-01-01
Abstract Protein conformational dynamics, despite its significant anharmonicity, has been widely explored by normal mode analysis (NMA) based on atomic or coarse-grained potential functions. To account for the anharmonic aspects of protein dynamics, this study proposes, and has performed, an anharmonic NMA (ANMA) based on the Cα-only elastic network models, which assume elastic interactions between pairs of residues whose Cα atoms or heavy atoms are within a cutoff distance. The key step of ANMA is to sample an anharmonic potential function along the directions of eigenvectors of the lowest normal modes to determine the mean-squared fluctuations along these directions. ANMA was evaluated based on the modeling of anisotropic displacement parameters (ADPs) from a list of 83 high-resolution protein crystal structures. Significant improvement was found in the modeling of ADPs by ANMA compared with standard NMA. Further improvement in the modeling of ADPs is attained if the interactions between a protein and its crystalline environment are taken into account. In addition, this study has determined the optimal cutoff distances for ADP modeling based on elastic network models, and these agree well with the peaks of the statistical distributions of distances between Cα atoms or heavy atoms derived from a large set of protein crystal structures. PMID:20550915
Solvated dissipative electro-elastic network model of hydrated proteins
NASA Astrophysics Data System (ADS)
Martin, Daniel
2013-03-01
Elastic network models coarse grain proteins into a network of residue beads connected by springs. We add dissipative dynamics to this mechanical system by applying overdamped Langevin equations of motion to normal-mode vibrations of the network. In addition, the network is made heterogeneous and softened at the protein surface by accounting for hydration of the ionized residues. Solvation changes the network Hessian in two ways. Diagonal solvation terms soften the spring constants and off-diagonal dipole-dipole terms correlate displacements of the ionized residues. The model is used to formulate the response functions of the electrostatic potential and electric field appearing in theories of redox reactions and spectroscopy. We also formulate the dielectric response of the protein and find that solvation of the surface ionized residues leads to a slow relaxation peak in the dielectric loss spectrum, about two orders of magnitude slower than the main peak of protein relaxation. Finally, the solvated network is used to formulate the allosteric response of the protein to ion binding. The global thermodynamics of ion binding is not strongly affected by the network solvation, but it dramatically enhances conformational changes in response to placing a charge at the a the active site.
Solvated dissipative electro-elastic network model of hydrated proteins
NASA Astrophysics Data System (ADS)
Martin, Daniel R.; Matyushov, Dmitry V.
2012-10-01
Elastic network models coarse grain proteins into a network of residue beads connected by springs. We add dissipative dynamics to this mechanical system by applying overdamped Langevin equations of motion to normal-mode vibrations of the network. In addition, the network is made heterogeneous and softened at the protein surface by accounting for hydration of the ionized residues. Solvation changes the network Hessian in two ways. Diagonal solvation terms soften the spring constants and off-diagonal dipole-dipole terms correlate displacements of the ionized residues. The model is used to formulate the response functions of the electrostatic potential and electric field appearing in theories of redox reactions and spectroscopy. We also formulate the dielectric response of the protein and find that solvation of the surface ionized residues leads to a slow relaxation peak in the dielectric loss spectrum, about two orders of magnitude slower than the main peak of protein relaxation. Finally, the solvated network is used to formulate the allosteric response of the protein to ion binding. The global thermodynamics of ion binding is not strongly affected by the network solvation, but it dramatically enhances conformational changes in response to placing a charge at the active site of the protein.
KOSMOS: a universal morph server for nucleic acids, proteins and their complexes.
Seo, Sangjae; Kim, Moon Ki
2012-07-01
KOSMOS is the first online morph server to be able to address the structural dynamics of DNA/RNA, proteins and even their complexes, such as ribosomes. The key functions of KOSMOS are the harmonic and anharmonic analyses of macromolecules. In the harmonic analysis, normal mode analysis (NMA) based on an elastic network model (ENM) is performed, yielding vibrational modes and B-factor calculations, which provide insight into the potential biological functions of macromolecules based on their structural features. Anharmonic analysis involving elastic network interpolation (ENI) is used to generate plausible transition pathways between two given conformations by optimizing a topology-oriented cost function that guarantees a smooth transition without steric clashes. The quality of the computed pathways is evaluated based on their various facets, including topology, energy cost and compatibility with the NMA results. There are also two unique features of KOSMOS that distinguish it from other morph servers: (i) the versatility in the coarse-graining methods and (ii) the various connection rules in the ENM. The models enable us to analyze macromolecular dynamics with the maximum degrees of freedom by combining a variety of ENMs from full-atom to coarse-grained, backbone and hybrid models with one connection rule, such as distance-cutoff, number-cutoff or chemical-cutoff. KOSMOS is available at http://bioengineering.skku.ac.kr/kosmos.
Effect of pH on chitosan hydrogel polymer network structure.
Xu, Hongcheng; Matysiak, Silvina
2017-06-29
Chitosan is a molecule that can form water-filled 3D polymer networks with a wide range of applications. A new coarse-grained model for chitosan hydrogel was developed to explore its pH-dependent self-assembly behavior and mechanical properties. Our results indicate that the underlying polymer physical crosslinking pattern induced by solution pH has a significant effect on hydrogel elastic moduli. With this model, we obtain pH-dependent structural and mechanical property changes in agreement with experimental observations, and provide a molecular mechanism behind the changes in polymer crosslinking patterns.
Generalized rules for the optimization of elastic network models
NASA Astrophysics Data System (ADS)
Lezon, Timothy; Eyal, Eran; Bahar, Ivet
2009-03-01
Elastic network models (ENMs) are widely employed for approximating the coarse-grained equilibrium dynamics of proteins using only a few parameters. An area of current focus is improving the predictive accuracy of ENMs by fine-tuning their force constants to fit specific systems. Here we introduce a set of general rules for assigning ENM force constants to residue pairs. Using a novel method, we construct ENMs that optimally reproduce experimental residue covariances from NMR models of 68 proteins. We analyze the optimal interactions in terms of amino acid types, pair distances and local protein structures to identify key factors in determining the effective spring constants. When applied to several unrelated globular proteins, our method shows an improved correlation with experiment over a standard ENM. We discuss the physical interpretation of our findings as well as its implications in the fields of protein folding and dynamics.
Multiscale simulations of PS-SiO2 nanocomposites: from melt to glassy state.
Mathioudakis, I G; Vogiatzis, G G; Tzoumanekas, C; Theodorou, D N
2016-09-28
The interaction energetics, molecular packing, entanglement network properties, segmental dynamics, and elastic constants of atactic polystyrene-amorphous silica nanocomposites in the molten and the glassy state are studied via molecular simulations using two interconnected levels of representation: (a) a coarse-grained one, wherein each polystyrene repeat unit is mapped onto a single "superatom" and the silica nanoparticle is viewed as a solid sphere. Equilibration at all length scales at this level is achieved via connectivity-altering Monte Carlo simulations. (b) A united-atom (UA) level, wherein the polymer chains are represented in terms of a united-atom forcefield and the silica nanoparticle is represented in terms of a simplified, fully atomistic model. Initial configurations for UA molecular dynamics (MD) simulations are obtained by reverse mapping well-equilibrated coarse-grained configurations. By analysing microcanonical UA MD trajectories, the polymer density profile is studied and the polymer is found to exhibit layering in the vicinity of the nanoparticle surface. An estimate of the enthalpy of mixing between polymer and nanoparticles, derived from the UA simulations, compares favourably against available experimental values. The dynamical behaviour of polystyrene (in neat and filled melt systems) is characterized in terms of bond orientation and dihedral angle time autocorrelation functions. At low concentration in the molten polymer matrix, silica nanoparticles are found to cause a slight deceleration of the segmental dynamics close to their surface compared to the bulk polymer. Well-equilibrated coarse-grained long-chain configurations are reduced to entanglement networks via topological analysis with the CReTA algorithm, yielding a slightly lower density of entanglements in the filled than in the neat systems. UA melt configurations are glassified by MD cooling. The elastic moduli of the resulting glassy nanocomposites are computed through an analysis of strain fluctuations in the undeformed state and through explicit mechanical deformation by MD, showing a stiffening of the polymer in the presence of nanoparticles. UA simulation results for the elastic constants are compared to continuum micromechanical calculations invoked in homogenization models of the overall mechanical behaviour of heterogeneous materials. They can be interpreted in terms of the presence of an "interphase" of approximate thickness 2 nm around the nanoparticles, with elastic constants intermediate between those of the filler and the matrix.
KOSMOS: a universal morph server for nucleic acids, proteins and their complexes
Seo, Sangjae; Kim, Moon Ki
2012-01-01
KOSMOS is the first online morph server to be able to address the structural dynamics of DNA/RNA, proteins and even their complexes, such as ribosomes. The key functions of KOSMOS are the harmonic and anharmonic analyses of macromolecules. In the harmonic analysis, normal mode analysis (NMA) based on an elastic network model (ENM) is performed, yielding vibrational modes and B-factor calculations, which provide insight into the potential biological functions of macromolecules based on their structural features. Anharmonic analysis involving elastic network interpolation (ENI) is used to generate plausible transition pathways between two given conformations by optimizing a topology-oriented cost function that guarantees a smooth transition without steric clashes. The quality of the computed pathways is evaluated based on their various facets, including topology, energy cost and compatibility with the NMA results. There are also two unique features of KOSMOS that distinguish it from other morph servers: (i) the versatility in the coarse-graining methods and (ii) the various connection rules in the ENM. The models enable us to analyze macromolecular dynamics with the maximum degrees of freedom by combining a variety of ENMs from full-atom to coarse-grained, backbone and hybrid models with one connection rule, such as distance-cutoff, number-cutoff or chemical-cutoff. KOSMOS is available at http://bioengineering.skku.ac.kr/kosmos. PMID:22669912
NASA Astrophysics Data System (ADS)
Li, Chunhua; Lv, Dashuai; Zhang, Lei; Yang, Feng; Wang, Cunxin; Su, Jiguo; Zhang, Yang
2016-07-01
Riboswitches are noncoding mRNA segments that can regulate the gene expression via altering their structures in response to specific metabolite binding. We proposed a coarse-grained Gaussian network model (GNM) to examine the unfolding and folding dynamics of adenosine deaminase (add) A-riboswitch upon the adenine dissociation, in which the RNA is modeled by a nucleotide chain with interaction networks formed by connecting adjoining atomic contacts. It was shown that the adenine binding is critical to the folding of the add A-riboswitch while the removal of the ligand can result in drastic increase of the thermodynamic fluctuations especially in the junction regions between helix domains. Under the assumption that the native contacts with the highest thermodynamic fluctuations break first, the iterative GNM simulations showed that the unfolding process of the adenine-free add A-riboswitch starts with the denature of the terminal helix stem, followed by the loops and junctions involving ligand binding pocket, and then the central helix domains. Despite the simplified coarse-grained modeling, the unfolding dynamics and pathways are shown in close agreement with the results from atomic-level MD simulations and the NMR and single-molecule force spectroscopy experiments. Overall, the study demonstrates a new avenue to investigate the binding and folding dynamics of add A-riboswitch molecule which can be readily extended for other RNA molecules.
Frappier, Vincent; Najmanovich, Rafael J.
2014-01-01
Normal mode analysis (NMA) methods are widely used to study dynamic aspects of protein structures. Two critical components of NMA methods are coarse-graining in the level of simplification used to represent protein structures and the choice of potential energy functional form. There is a trade-off between speed and accuracy in different choices. In one extreme one finds accurate but slow molecular-dynamics based methods with all-atom representations and detailed atom potentials. On the other extreme, fast elastic network model (ENM) methods with Cα−only representations and simplified potentials that based on geometry alone, thus oblivious to protein sequence. Here we present ENCoM, an Elastic Network Contact Model that employs a potential energy function that includes a pairwise atom-type non-bonded interaction term and thus makes it possible to consider the effect of the specific nature of amino-acids on dynamics within the context of NMA. ENCoM is as fast as existing ENM methods and outperforms such methods in the generation of conformational ensembles. Here we introduce a new application for NMA methods with the use of ENCoM in the prediction of the effect of mutations on protein stability. While existing methods are based on machine learning or enthalpic considerations, the use of ENCoM, based on vibrational normal modes, is based on entropic considerations. This represents a novel area of application for NMA methods and a novel approach for the prediction of the effect of mutations. We compare ENCoM to a large number of methods in terms of accuracy and self-consistency. We show that the accuracy of ENCoM is comparable to that of the best existing methods. We show that existing methods are biased towards the prediction of destabilizing mutations and that ENCoM is less biased at predicting stabilizing mutations. PMID:24762569
Elastic Network Model of a Nuclear Transport Complex
NASA Astrophysics Data System (ADS)
Ryan, Patrick; Liu, Wing K.; Lee, Dockjin; Seo, Sangjae; Kim, Young-Jin; Kim, Moon K.
2010-05-01
The structure of Kap95p was obtained from the Protein Data Bank (www.pdb.org) and analyzed RanGTP plays an important role in both nuclear protein import and export cycles. In the nucleus, RanGTP releases macromolecular cargoes from importins and conversely facilitates cargo binding to exportins. Although the crystal structure of the nuclear import complex formed by importin Kap95p and RanGTP was recently identified, its molecular mechanism still remains unclear. To understand the relationship between structure and function of a nuclear transport complex, a structure-based mechanical model of Kap95p:RanGTP complex is introduced. In this model, a protein structure is simply modeled as an elastic network in which a set of coarse-grained point masses are connected by linear springs representing biochemical interactions at atomic level. Harmonic normal mode analysis (NMA) and anharmonic elastic network interpolation (ENI) are performed to predict the modes of vibrations and a feasible pathway between locked and unlocked conformations of Kap95p, respectively. Simulation results imply that the binding of RanGTP to Kap95p induces the release of the cargo in the nucleus as well as prevents any new cargo from attaching to the Kap95p:RanGTP complex.
Packing Regularities in Biological Structures Relate to Their Dynamics
Jernigan, Robert L.; Kloczkowski, Andrzej
2007-01-01
The high packing density inside proteins leads to certain geometric regularities and also is one of the most important contributors to the high extent of cooperativity manifested by proteins in their cohesive domain motions. The orientations between neighboring non-bonded residues in proteins substantially follow the similar geometric regularities, regardless of whether the residues are on the surface or buried - a direct result of hydrophobicity forces. These orientations are relatively fixed and correspond closely to small deformations from those of the face-centered cubic lattice, which is the way in which identical spheres pack at the highest density. Packing density also is related to the extent of conservation of residues, and we show this relationship for residue packing densities by averaging over a large sample or residue packings. There are three regimes: 1) over a broad range of packing densities the relationship between sequence entropy and inverse packing density is nearly linear, 2) over a limited range of low packing densities the sequence entropy is nearly constant, and 3) at extremely low packing densities the sequence entropy is highly variable. These packing results provide important justification for the simple elastic network models that have been shown for a large number of proteins to represent protein dynamics so successfully, even when the models are extremely coarse-grained. Elastic network models for polymeric chains are simple and could be combined with these protein elastic networks to represent partially denatured parts of proteins. Finally, we show results of applications of the elastic network model to study the functional motions of the ribosome, based on its known structure. These results indicate expected correlations among its components for the step-wise processing steps in protein synthesis, and suggest ways to use these elastic network models to develop more detailed mechanisms - an important possibility, since most experiments yield only static structures. PMID:16957327
Hammond, Nathan A; Kamm, Roger D
2008-07-01
The synthetic peptide RAD16-II has shown promise in tissue engineering and drug delivery. It has been studied as a vehicle for cell delivery and controlled release of IGF-1 to repair infarcted cardiac tissue, and as a scaffold to promote capillary formation for an in vitro model of angiogenesis. The structure of RAD16-II is hierarchical, with monomers forming long beta-sheets that pair together to form filaments; filaments form bundles approximately 30-60 nm in diameter; branching networks of filament bundles form macroscopic gels. We investigate the mechanics of shearing between the two beta-sheets constituting one filament, and between cohered filaments of RAD16-II. This shear loading is found in filament bundle bending or in tensile loading of fibers composed of partial-length filaments. Molecular dynamics simulations show that time to failure is a stochastic function of applied shear stress, and that for a given loading time behavior is elastic for sufficiently small shear loads. We propose a coarse-grained model based on Langevin dynamics that matches molecular dynamics results and facilities extending simulations in space and time. The model treats a filament as an elastic string of particles, each having potential energy that is a periodic function of its position relative to the neighboring filament. With insight from these simulations, we discuss strategies for strengthening RAD16-II and similar materials.
A comparison between elastic network interpolation and MD simulation of 16S ribosomal RNA.
Kim, Moon K; Li, Wen; Shapiro, Bruce A; Chirikjian, Gregory S
2003-12-01
In this paper a coarse-grained method called elastic network interpolation (ENI) is used to generate feasible transition pathways between two given conformations of the core central domain of 16S Ribosomal RNA (16S rRNA). The two given conformations are the extremes generated by a molecular dynamics (MD) simulation, which differ from each other by 10A in root-mean-square deviation (RMSD). It takes only several hours to build an ENI pathway on a 1.5GHz Pentium with 512 MB memory, while the MD takes several weeks on high-performance multi-processor servers such as the SGI ORIGIN 2000/2100. It is shown that multiple ENI pathways capture the essential anharmonic motions of millions of timesteps in a particular MD simulation. A coarse-grained normal mode analysis (NMA) is performed on each intermediate ENI conformation, and the lowest 1% of the normal modes (representing about 40 degrees of freedom (DOF)) are used to parameterize fluctuations. This combined ENI/NMA method captures all intermediate conformations in the MD run with 1.5A RMSD on average. In addition, if we restrict attention to the time interval of the MD run between the two extreme conformations, the RMSD between the closest ENI/NMA pathway and the MD results is about 1A. These results may serve as a paradigm for reduced-DOF dynamic simulations of large biological macromolecules as well as a method for the reduced-parameter interpretation of massive amounts of MD data.
Coarse graining for synchronization in directed networks
NASA Astrophysics Data System (ADS)
Zeng, An; Lü, Linyuan
2011-05-01
Coarse-graining model is a promising way to analyze and visualize large-scale networks. The coarse-grained networks are required to preserve statistical properties as well as the dynamic behaviors of the initial networks. Some methods have been proposed and found effective in undirected networks, while the study on coarse-graining directed networks lacks of consideration. In this paper we proposed a path-based coarse-graining (PCG) method to coarse grain the directed networks. Performing the linear stability analysis of synchronization and numerical simulation of the Kuramoto model on four kinds of directed networks, including tree networks and variants of Barabási-Albert networks, Watts-Strogatz networks, and Erdös-Rényi networks, we find our method can effectively preserve the network synchronizability.
A coarse-grained model of microtubule self-assembly
NASA Astrophysics Data System (ADS)
Regmi, Chola; Cheng, Shengfeng
Microtubules play critical roles in cell structures and functions. They also serve as a model system to stimulate the next-generation smart, dynamic materials. A deep understanding of their self-assembly process and biomechanical properties will not only help elucidate how microtubules perform biological functions, but also lead to exciting insight on how microtubule dynamics can be altered or even controlled for specific purposes such as suppressing the division of cancer cells. Combining all-atom molecular dynamics (MD) simulations and the essential dynamics coarse-graining method, we construct a coarse-grained (CG) model of the tubulin protein, which is the building block of microtubules. In the CG model a tubulin dimer is represented as an elastic network of CG sites, the locations of which are determined by examining the protein dynamics of the tubulin and identifying the essential dynamic domains. Atomistic MD modeling is employed to directly compute the tubulin bond energies in the surface lattice of a microtubule, which are used to parameterize the interactions between CG building blocks. The CG model is then used to study the self-assembly pathways, kinetics, dynamics, and nanomechanics of microtubules.
Comparative Investigation of Normal Modes and Molecular Dynamics of Hepatitis C NS5B Protein
NASA Astrophysics Data System (ADS)
Asafi, M. S.; Yildirim, A.; Tekpinar, M.
2016-04-01
Understanding dynamics of proteins has many practical implications in terms of finding a cure for many protein related diseases. Normal mode analysis and molecular dynamics methods are widely used physics-based computational methods for investigating dynamics of proteins. In this work, we studied dynamics of Hepatitis C NS5B protein with molecular dynamics and normal mode analysis. Principal components obtained from a 100 nanoseconds molecular dynamics simulation show good overlaps with normal modes calculated with a coarse-grained elastic network model. Coarse-grained normal mode analysis takes at least an order of magnitude shorter time. Encouraged by this good overlaps and short computation times, we analyzed further low frequency normal modes of Hepatitis C NS5B. Motion directions and average spatial fluctuations have been analyzed in detail. Finally, biological implications of these motions in drug design efforts against Hepatitis C infections have been elaborated.
Coarse-graining and self-dissimilarity of complex networks
NASA Astrophysics Data System (ADS)
Itzkovitz, Shalev; Levitt, Reuven; Kashtan, Nadav; Milo, Ron; Itzkovitz, Michael; Alon, Uri
2005-01-01
Can complex engineered and biological networks be coarse-grained into smaller and more understandable versions in which each node represents an entire pattern in the original network? To address this, we define coarse-graining units as connectivity patterns which can serve as the nodes of a coarse-grained network and present algorithms to detect them. We use this approach to systematically reverse-engineer electronic circuits, forming understandable high-level maps from incomprehensible transistor wiring: first, a coarse-grained version in which each node is a gate made of several transistors is established. Then the coarse-grained network is itself coarse-grained, resulting in a high-level blueprint in which each node is a circuit module made of many gates. We apply our approach also to a mammalian protein signal-transduction network, to find a simplified coarse-grained network with three main signaling channels that resemble multi-layered perceptrons made of cross-interacting MAP-kinase cascades. We find that both biological and electronic networks are “self-dissimilar,” with different network motifs at each level. The present approach may be used to simplify a variety of directed and nondirected, natural and designed networks.
NASA Astrophysics Data System (ADS)
Penta, Raimondo; Gerisch, Alf
2017-01-01
The classical asymptotic homogenization approach for linear elastic composites with discontinuous material properties is considered as a starting point. The sharp length scale separation between the fine periodic structure and the whole material formally leads to anisotropic elastic-type balance equations on the coarse scale, where the arising fourth rank operator is to be computed solving single periodic cell problems on the fine scale. After revisiting the derivation of the problem, which here explicitly points out how the discontinuity in the individual constituents' elastic coefficients translates into stress jump interface conditions for the cell problems, we prove that the gradient of the cell problem solution is minor symmetric and that its cell average is zero. This property holds for perfect interfaces only (i.e., when the elastic displacement is continuous across the composite's interface) and can be used to assess the accuracy of the computed numerical solutions. These facts are further exploited, together with the individual constituents' elastic coefficients and the specific form of the cell problems, to prove a theorem that characterizes the fourth rank operator appearing in the coarse-scale elastic-type balance equations as a composite material effective elasticity tensor. We both recover known facts, such as minor and major symmetries and positive definiteness, and establish new facts concerning the Voigt and Reuss bounds. The latter are shown for the first time without assuming any equivalence between coarse and fine-scale energies ( Hill's condition), which, in contrast to the case of representative volume elements, does not identically hold in the context of asymptotic homogenization. We conclude with instructive three-dimensional numerical simulations of a soft elastic matrix with an embedded cubic stiffer inclusion to show the profile of the physically relevant elastic moduli (Young's and shear moduli) and Poisson's ratio at increasing (up to 100 %) inclusion's volume fraction, thus providing a proxy for the design of artificial elastic composites.
NASA Astrophysics Data System (ADS)
Dykeman, Eric C.; Sankey, Otto F.
2010-02-01
We describe a technique for calculating the low-frequency mechanical modes and frequencies of a large symmetric biological molecule where the eigenvectors of the Hessian matrix are determined with full atomic detail. The method, which follows order N methods used in electronic structure theory, determines the subset of lowest-frequency modes while using group theory to reduce the complexity of the problem. We apply the method to three icosahedral viruses of various T numbers and sizes; the human viruses polio and hepatitis B, and the cowpea chlorotic mottle virus, a plant virus. From the normal-mode eigenvectors, we use a bond polarizability model to predict a low-frequency Raman scattering profile for the viruses. The full atomic detail in the displacement patterns combined with an empirical potential-energy model allows a comparison of the fully atomic normal modes with elastic network models and normal-mode analysis with only dihedral degrees of freedom. We find that coarse-graining normal-mode analysis (particularly the elastic network model) can predict the displacement patterns for the first few (˜10) low-frequency modes that are global and cooperative.
Ostermeir, Katja; Zacharias, Martin
2014-12-01
Coarse-grained elastic network models (ENM) of proteins offer a low-resolution representation of protein dynamics and directions of global mobility. A Hamiltonian-replica exchange molecular dynamics (H-REMD) approach has been developed that combines information extracted from an ENM analysis with atomistic explicit solvent MD simulations. Based on a set of centers representing rigid segments (centroids) of a protein, a distance-dependent biasing potential is constructed by means of an ENM analysis to promote and guide centroid/domain rearrangements. The biasing potentials are added with different magnitude to the force field description of the MD simulation along the replicas with one reference replica under the control of the original force field. The magnitude and the form of the biasing potentials are adapted during the simulation based on the average sampled conformation to reach a near constant biasing in each replica after equilibration. This allows for canonical sampling of conformational states in each replica. The application of the methodology to a two-domain segment of the glycoprotein 130 and to the protein cyanovirin-N indicates significantly enhanced global domain motions and improved conformational sampling compared with conventional MD simulations. © 2014 Wiley Periodicals, Inc.
Distributions of experimental protein structures on coarse-grained free energy landscapes
Liu, Jie; Jernigan, Robert L.
2015-01-01
Predicting conformational changes of proteins is needed in order to fully comprehend functional mechanisms. With the large number of available structures in sets of related proteins, it is now possible to directly visualize the clusters of conformations and their conformational transitions through the use of principal component analysis. The most striking observation about the distributions of the structures along the principal components is their highly non-uniform distributions. In this work, we use principal component analysis of experimental structures of 50 diverse proteins to extract the most important directions of their motions, sample structures along these directions, and estimate their free energy landscapes by combining knowledge-based potentials and entropy computed from elastic network models. When these resulting motions are visualized upon their coarse-grained free energy landscapes, the basis for conformational pathways becomes readily apparent. Using three well-studied proteins, T4 lysozyme, serum albumin, and sarco-endoplasmic reticular Ca2+ adenosine triphosphatase (SERCA), as examples, we show that such free energy landscapes of conformational changes provide meaningful insights into the functional dynamics and suggest transition pathways between different conformational states. As a further example, we also show that Monte Carlo simulations on the coarse-grained landscape of HIV-1 protease can directly yield pathways for force-driven conformational changes. PMID:26723638
Local elasticity map and plasticity in a model Lennard-Jones glass.
Tsamados, Michel; Tanguy, Anne; Goldenberg, Chay; Barrat, Jean-Louis
2009-08-01
In this work we calculate the local elastic moduli in a weakly polydispersed two-dimensional Lennard-Jones glass undergoing a quasistatic shear deformation at zero temperature. The numerical method uses coarse-grained microscopic expressions for the strain, displacement, and stress fields. This method allows us to calculate the local elasticity tensor and to quantify the deviation from linear elasticity (local Hooke's law) at different coarse-graining scales. From the results a clear picture emerges of an amorphous material with strongly spatially heterogeneous elastic moduli that simultaneously satisfies Hooke's law at scales larger than a characteristic length scale of the order of five interatomic distances. At this scale, the glass appears as a composite material composed of a rigid scaffolding and of soft zones. Only recently calculated in nonhomogeneous materials, the local elastic structure plays a crucial role in the elastoplastic response of the amorphous material. For a small macroscopic shear strain, the structures associated with the nonaffine displacement field appear directly related to the spatial structure of the elastic moduli. Moreover, for a larger macroscopic shear strain we show that zones of low shear modulus concentrate most of the strain in the form of plastic rearrangements. The spatiotemporal evolution of this local elasticity map and its connection with long term dynamical heterogeneity as well as with the plasticity in the material is quantified. The possibility to use this local parameter as a predictor of subsequent local plastic activity is also discussed.
Buckling of paramagnetic chains in soft gels
NASA Astrophysics Data System (ADS)
Huang, Shilin; Pessot, Giorgio; Cremer, Peet; Weeber, Rudolf; Holm, Christian; Nowak, Johannes; Odenbach, Stefan; Menzel, Andreas M.; Auernhammer, Günter K.
We study the magneto-elastic coupling behavior of paramagnetic chains in soft polymer gels exposed to external magnetic fields. To this end, a laser scanning confocal microscope is used to observe the morphology of the paramagnetic chains together with the deformation field of the surrounding gel network. The paramagnetic chains in soft polymer gels show rich morphological shape changes under oblique magnetic fields, in particular a pronounced buckling deformation. The details of the resulting morphological shapes depend on the length of the chain, the strength of the external magnetic field, and the modulus of the gel. Based on the observation that the magnetic chains are strongly coupled to the surrounding polymer network, a simplified model is developed to describe their buckling behavior. A coarse-grained molecular dynamics simulation model featuring an increased matrix stiffness on the surfaces of the particles leads to morphologies in agreement with the experimentally observed buckling effects.
Advanced Polymer Network Structures
2016-02-01
double networks in a single step was identified from coarse-grained molecular dynamics simulations of polymer solvents bearing rigid side chains dissolved...in a polymer network. Coarse-grained molecular dynamics simulations also explored the mechanical behavior of traditional double networks and...DRI), polymer networks, polymer gels, molecular dynamics simulations , double networks 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF
Coarse gaining of molecular crystals: limitations imposed by molecular flexibility
NASA Astrophysics Data System (ADS)
Picu, Catalin; Pal, Anirban
Molecular crystals include molecular electronics, energetic materials, pharmaceuticals and some food components. In many of these applications the small scale mechanical behavior of the crystal is important such as for example in energetic materials where detonation is induced by the formation of hot spots which are induced thermomechanically, and in pharmaceuticals where phase stability is critical for the biochemical activity of the drug. Accurate modeling of these processes requires resolving the atomistic scale details of the material. However, the cost of these models is very large due to the complexity of the molecules forming the crystal, and some form of coarse graning is necessary. In this study we identify the limitations imposed by the need to accurately capture molecular flexibility on the development of coarse grained models for the energetic molecular crystal RDX. We define guidelines for the definition of coarse grained models that target elastic and plastic crystal scale properties such as elastic constants, thermal expansion, compressibility, the critical stress for the motion of dislocations (Peierls stress) and the stacking fault energy This work was supported by the ARO through Grant W911NF-09-1-0330 and AFRL through Grant FA8651-16-1-0004.
Rigid-Cluster Models of Conformational Transitions in Macromolecular Machines and Assemblies
Kim, Moon K.; Jernigan, Robert L.; Chirikjian, Gregory S.
2005-01-01
We present a rigid-body-based technique (called rigid-cluster elastic network interpolation) to generate feasible transition pathways between two distinct conformations of a macromolecular assembly. Many biological molecules and assemblies consist of domains which act more or less as rigid bodies during large conformational changes. These collective motions are thought to be strongly related with the functions of a system. This fact encourages us to simply model a macromolecule or assembly as a set of rigid bodies which are interconnected with distance constraints. In previous articles, we developed coarse-grained elastic network interpolation (ENI) in which, for example, only Cα atoms are selected as representatives in each residue of a protein. We interpolate distance differences of two conformations in ENI by using a simple quadratic cost function, and the feasible conformations are generated without steric conflicts. Rigid-cluster interpolation is an extension of the ENI method with rigid-clusters replacing point masses. Now the intermediate conformations in an anharmonic pathway can be determined by the translational and rotational displacements of large clusters in such a way that distance constraints are observed. We present the derivation of the rigid-cluster model and apply it to a variety of macromolecular assemblies. Rigid-cluster ENI is then modified for a hybrid model represented by a mixture of rigid clusters and point masses. Simulation results show that both rigid-cluster and hybrid ENI methods generate sterically feasible pathways of large systems in a very short time. For example, the HK97 virus capsid is an icosahedral symmetric assembly composed of 60 identical asymmetric units. Its original Hessian matrix size for a Cα coarse-grained model is >(300,000)2. However, it reduces to (84)2 when we apply the rigid-cluster model with icosahedral symmetry constraints. The computational cost of the interpolation no longer scales heavily with the size of structures; instead, it depends strongly on the minimal number of rigid clusters into which the system can be decomposed. PMID:15833998
A unified data representation theory for network visualization, ordering and coarse-graining
Kovács, István A.; Mizsei, Réka; Csermely, Péter
2015-01-01
Representation of large data sets became a key question of many scientific disciplines in the last decade. Several approaches for network visualization, data ordering and coarse-graining accomplished this goal. However, there was no underlying theoretical framework linking these problems. Here we show an elegant, information theoretic data representation approach as a unified solution of network visualization, data ordering and coarse-graining. The optimal representation is the hardest to distinguish from the original data matrix, measured by the relative entropy. The representation of network nodes as probability distributions provides an efficient visualization method and, in one dimension, an ordering of network nodes and edges. Coarse-grained representations of the input network enable both efficient data compression and hierarchical visualization to achieve high quality representations of larger data sets. Our unified data representation theory will help the analysis of extensive data sets, by revealing the large-scale structure of complex networks in a comprehensible form. PMID:26348923
Elastic moduli of biological fibers in a coarse-grained model: crystalline cellulose and β-amyloids.
Poma, Adolfo B; Chwastyk, Mateusz; Cieplak, Marek
2017-10-25
We study the mechanical response of cellulose and β-amyloid microfibrils to three types of deformation: tensile, indentational, and shear. The cellulose microfibrils correspond to the allomorphs Iα or Iβ whereas the β-amyloid microfibrils correspond to the polymorphs of either two- or three-fold symmetry. This response can be characterized by three elastic moduli, namely, Y L , Y T , and S. We use a structure-based coarse-grained model to analyze the deformations in a unified manner. We find that each of the moduli is almost the same for the two allomorphs of cellulose but Y L is about 20 times larger than Y T (140 GPa vs. 7 GPa), indicating the existence of significant anisotropy. For cellulose we note that the anisotropy results from the involvement of covalent bonds in stretching. For β-amyloid, the sense of anisotropy is opposite to that of cellulose. In the three-fold symmetry case, Y L is about half of Y T (3 vs. 7) whereas for two-fold symmetry the anisotropy is much larger (1.6 vs. 21 GPa). The S modulus is derived to be 1.2 GPa for three-fold symmetry and one half of it for the other symmetry and 3.0 GPa for cellulose. The values of the moduli reflect deformations in the hydrogen-bond network. Unlike in our theoretical approach, no experiment can measure all three elastic moduli with the same apparatus. However, our theoretical results are consistent with various measured values: typical Y L for cellulose Iβ ranges from 133 to 155 GPa, Y T from 2 to 25 GPa, and S from 1.8 to 3.8 GPa. For β-amyloid, the experimental values of S and Y T are about 0.3 GPa and 3.3 GPa respectively, while the value of Y L has not been reported.
Systematic methods for defining coarse-grained maps in large biomolecules.
Zhang, Zhiyong
2015-01-01
Large biomolecules are involved in many important biological processes. It would be difficult to use large-scale atomistic molecular dynamics (MD) simulations to study the functional motions of these systems because of the computational expense. Therefore various coarse-grained (CG) approaches have attracted rapidly growing interest, which enable simulations of large biomolecules over longer effective timescales than all-atom MD simulations. The first issue in CG modeling is to construct CG maps from atomic structures. In this chapter, we review the recent development of a novel and systematic method for constructing CG representations of arbitrarily complex biomolecules, in order to preserve large-scale and functionally relevant essential dynamics (ED) at the CG level. In this ED-CG scheme, the essential dynamics can be characterized by principal component analysis (PCA) on a structural ensemble, or elastic network model (ENM) of a single atomic structure. Validation and applications of the method cover various biological systems, such as multi-domain proteins, protein complexes, and even biomolecular machines. The results demonstrate that the ED-CG method may serve as a very useful tool for identifying functional dynamics of large biomolecules at the CG level.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zheng, Wenjun, E-mail: wjzheng@buffalo.edu; Glenn, Paul
2015-01-21
The Bacteriophage T4 Lysozyme (T4L) is a prototype modular protein comprised of an N-terminal and a C-domain domain, which was extensively studied to understand the folding/unfolding mechanism of modular proteins. To offer detailed structural and dynamic insights to the folded-state stability and the mechanical unfolding behaviors of T4L, we have performed extensive equilibrium and steered molecular dynamics simulations of both the wild-type (WT) and a circular permutation (CP) variant of T4L using all-atom and coarse-grained force fields. Our all-atom and coarse-grained simulations of the folded state have consistently found greater stability of the C-domain than the N-domain in isolation, whichmore » is in agreement with past thermostatic studies of T4L. While the all-atom simulation cannot fully explain the mechanical unfolding behaviors of the WT and the CP variant observed in an optical tweezers study, the coarse-grained simulations based on the Go model or a modified elastic network model (mENM) are in qualitative agreement with the experimental finding of greater unfolding cooperativity in the WT than the CP variant. Interestingly, the two coarse-grained models predict different structural mechanisms for the observed change in cooperativity between the WT and the CP variant—while the Go model predicts minor modification of the unfolding pathways by circular permutation (i.e., preserving the general order that the N-domain unfolds before the C-domain), the mENM predicts a dramatic change in unfolding pathways (e.g., different order of N/C-domain unfolding in the WT and the CP variant). Based on our simulations, we have analyzed the limitations of and the key differences between these models and offered testable predictions for future experiments to resolve the structural mechanism for cooperative folding/unfolding of T4L.« less
Emergence of linear elasticity from the atomistic description of matter
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cakir, Abdullah, E-mail: acakir@ntu.edu.sg; Pica Ciamarra, Massimo; Dipartimento di Scienze Fisiche, CNR–SPIN, Università di Napoli Federico II, I-80126 Napoli
2016-08-07
We investigate the emergence of the continuum elastic limit from the atomistic description of matter at zero temperature considering how locally defined elastic quantities depend on the coarse graining length scale. Results obtained numerically investigating different model systems are rationalized in a unifying picture according to which the continuum elastic limit emerges through a process determined by two system properties, the degree of disorder, and a length scale associated to the transverse low-frequency vibrational modes. The degree of disorder controls the emergence of long-range local shear stress and shear strain correlations, while the length scale influences the amplitude of themore » fluctuations of the local elastic constants close to the jamming transition.« less
Engineering molecular machines
NASA Astrophysics Data System (ADS)
Erman, Burak
2016-04-01
Biological molecular motors use chemical energy, mostly in the form of ATP hydrolysis, and convert it to mechanical energy. Correlated thermal fluctuations are essential for the function of a molecular machine and it is the hydrolysis of ATP that modifies the correlated fluctuations of the system. Correlations are consequences of the molecular architecture of the protein. The idea that synthetic molecular machines may be constructed by designing the proper molecular architecture is challenging. In their paper, Sarkar et al (2016 New J. Phys. 18 043006) propose a synthetic molecular motor based on the coarse grained elastic network model of proteins and show by numerical simulations that motor function is realized, ranging from deterministic to thermal, depending on temperature. This work opens up a new range of possibilities of molecular architecture based engine design.
Ahmed, Aqeel; Villinger, Saskia; Gohlke, Holger
2010-12-01
A large-scale comparison of essential dynamics (ED) modes from molecular dynamic simulations and normal modes from coarse-grained normal mode methods (CGNM) was performed on a dataset of 335 proteins. As CGNM methods, the elastic network model (ENM) and the rigid cluster normal mode analysis (RCNMA) were used. Low-frequency normal modes from ENM correlate very well with ED modes in terms of directions of motions and relative amplitudes of motions. Notably, a similar performance was found if normal modes from RCNMA were used, despite a higher level of coarse graining. On average, the space spanned by the first quarter of ENM modes describes 84% of the space spanned by the five ED modes. Furthermore, no prominent differences for ED and CGNM modes among different protein structure classes (CATH classification) were found. This demonstrates the general potential of CGNM approaches for describing intrinsic motions of proteins with little computational cost. For selected cases, CGNM modes were found to be more robust among proteins that have the same topology or are of the same homologous superfamily than ED modes. In view of recent evidence regarding evolutionary conservation of vibrational dynamics, this suggests that ED modes, in some cases, might not be representative of the underlying dynamics that are characteristic of a whole family, probably due to insufficient sampling of some of the family members by MD. Copyright © 2010 Wiley-Liss, Inc.
Clusterin expression in elastofibroma dorsi.
Aigelsreiter, Ariane; Pichler, Martin; Pixner, Thomas; Janig, Elke; Schuller, Monika; Lackner, Carolin; Scheipl, Susanne; Beham, Alfred; Regauer, Sigrid
2013-05-01
Elastofibroma dorsi is a benign soft tissue lesion composed of abnormal elastic fibers. Degenerated elastic fibers in skin and liver are associated with clusterin, an apoprotein that shares functional properties with small heat shock proteins. We evaluated the staining pattern and possible role of clusterin in elastofibroma dorsi. Twenty-one subcutaneous elastofibromas from the scapular region were evaluated with Elastica van Gieson and Orcein stains, immunohistochemically with antibodies to clusterin, smooth muscle actin, S-100, vimentin and CD34 and correlated with clinical data with respect to physical trauma. Clusterin correlated with the staining pattern of Elastica van Gieson and labelled abnormal broad coarse fibrillar and globular elastic fibers in all elastofibromas. Orcein stains additionally identified fine oxytalan fibers which were not stained by clusterin. Clusterin staining was observed only on the outside of the elastin fibers, while the cores of fibers and globules were unstained. 4/21 elastofibromas showed cellular nodules with a myxoid/collagenous stroma. The round to oval cells showed cytoplasmic staining with vimentin and clusterin; CD34 labelled mostly cell membranes. The cells lacked SMA and S-100 expression. The central areas of the nodules were devoid of elastic fibers, but the periphery contained coarse fibers and globules. 9/ 11 patients, for whom clinical data were available, reported trauma to the scapular region. Many investigated ED were associated with trauma, which supports a reactive/degenerative etiology of ED. The abnormal large elastic fibers in all ED were enveloped by clusterin. Clusterin deposition may protect elastic fibers from degradation and thus contribute indirectly to the tumor-like presentation of ED.
Multi-PON access network using a coarse AWG for smooth migration from TDM to WDM PON
NASA Astrophysics Data System (ADS)
Shachaf, Y.; Chang, C.-H.; Kourtessis, P.; Senior, J. M.
2007-06-01
An interoperable access network architecture based on a coarse array waveguide grating (AWG) is described, displaying dynamic wavelength assignment to manage the network load across multiple PONs. The multi-PON architecture utilizes coarse Gaussian channels of an AWG to facilitate scalability and smooth migration path between TDM and WDM PONs. Network simulations of a cross-operational protocol platform confirmed successful routing of individual PON clusters through 7 nm-wide passband windows of the AWG. Furthermore, polarization-dependent wavelength shift and phase errors of the device proved not to impose restrain on the routing performance. Optical transmission tests at 2.5 Gbit/s for distances up to 20 km are demonstrated.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wilson, Mark A.; Baljon, Arlette R. C.
The response of associating polymers with oscillatory shear is studied through large-scale simulations. A hybrid molecular dynamics (MD), Monte Carlo (MC) algorithm is employed. Polymer chains are modeled as a coarse-grained bead-spring system. Functionalized end groups, at both ends of the polymer chains, can form reversible bonds according to MC rules. Stress-strain curves show nonlinearities indicated by a non-ellipsoidal shape. We consider two types of nonlinearities. Type I occurs at a strain amplitude much larger than one, type II at a frequency at which the elastic storage modulus dominates the viscous loss modulus. In this last case, the network topologymore » resembles that of the system at rest. The reversible bonds are broken and chains stretch when the system moves away from the zero-strain position. For type I, the chains relax and the number of reversible bonds peaks when the system is near an extreme of the motion. During the movement to the other extreme of the cycle, first a stress overshoot occurs, then a yield accompanied by shear-banding. Lastly, the network restructures. Interestingly, the system periodically restores bonds between the same associating groups. Even though major restructuring occurs, the system remembers previous network topologies.« less
NASA Astrophysics Data System (ADS)
Pouyandeh, Sima; Iubini, Stefano; Jurinovich, Sandro; Omar, Yasser; Mennucci, Benedetta; Piazza, Francesco
2017-12-01
In this paper, we work out a parameterization of environmental noise within the Haken-Strobl-Reinenker (HSR) model for the PE545 light-harvesting complex, based on atomic-level quantum mechanics/molecular mechanics (QM/MM) simulations. We use this approach to investigate the role of various auto- and cross-correlations in the HSR noise tensor, confirming that site-energy autocorrelations (pure dephasing) terms dominate the noise-induced exciton mobility enhancement, followed by site energy-coupling cross-correlations for specific triplets of pigments. Interestingly, several cross-correlations of the latter kind, together with coupling-coupling cross-correlations, display clear low-frequency signatures in their spectral densities in the 30-70 cm-1 region. These slow components lie at the limits of validity of the HSR approach, which requires that environmental fluctuations be faster than typical exciton transfer time scales. We show that a simple coarse-grained elastic-network-model (ENM) analysis of the PE545 protein naturally spotlights collective normal modes in this frequency range that represent specific concerted motions of the subnetwork of cysteines covalenty linked to the pigments. This analysis strongly suggests that protein scaffolds in light-harvesting complexes are able to express specific collective, low-frequency normal modes providing a fold-rooted blueprint of exciton transport pathways. We speculate that ENM-based mixed quantum classical methods, such as Ehrenfest dynamics, might be promising tools to disentangle the fundamental designing principles of these dynamical processes in natural and artificial light-harvesting structures.
Yang, Hui; Zhang, Jie; Zhao, Yongli; Ji, Yuefeng; Li, Hui; Lin, Yi; Li, Gang; Han, Jianrui; Lee, Young; Ma, Teng
2014-07-28
Data center interconnection with elastic optical networks is a promising scenario to meet the high burstiness and high-bandwidth requirements of data center services. We previously implemented enhanced software defined networking over elastic optical network for data center application [Opt. Express 21, 26990 (2013)]. On the basis of it, this study extends to consider the time-aware data center service scheduling with elastic service time and service bandwidth according to the various time sensitivity requirements. A novel time-aware enhanced software defined networking (TeSDN) architecture for elastic data center optical interconnection has been proposed in this paper, by introducing a time-aware resources scheduling (TaRS) scheme. The TeSDN can accommodate the data center services with required QoS considering the time dimensionality, and enhance cross stratum optimization of application and elastic optical network stratums resources based on spectrum elasticity, application elasticity and time elasticity. The overall feasibility and efficiency of the proposed architecture is experimentally verified on our OpenFlow-based testbed. The performance of TaRS scheme under heavy traffic load scenario is also quantitatively evaluated based on TeSDN architecture in terms of blocking probability and resource occupation rate.
Sapudom, Jiranuwat; Rubner, Stefan; Martin, Steve; Kurth, Tony; Riedel, Stefanie; Mierke, Claudia T; Pompe, Tilo
2015-06-01
The behavior of cancer cells is strongly influenced by the properties of extracellular microenvironments, including topology, mechanics and composition. As topological and mechanical properties of the extracellular matrix are hard to access and control for in-depth studies of underlying mechanisms in vivo, defined biomimetic in vitro models are needed. Herein we show, how pore size and fibril diameter of collagen I networks distinctively regulate cancer cell morphology and invasion. Three-dimensional collagen I matrices with a tight control of pore size, fibril diameter and stiffness were reconstituted by adjustment of concentration and pH value during matrix reconstitution. At first, a detailed analysis of topology and mechanics of matrices using confocal laser scanning microscopy, image analysis tools and force spectroscopy indicate pore size and not fibril diameter as the major determinant of matrix elasticity. Secondly, by using two different breast cancer cell lines (MDA-MB-231 and MCF-7), we demonstrate collagen fibril diameter--and not pore size--to primarily regulate cell morphology, cluster formation and invasion. Invasiveness increased and clustering decreased with increasing fibril diameter for both, the highly invasive MDA-MB-231 cells with mesenchymal migratory phenotype and the MCF-7 cells with amoeboid migratory phenotype. As this behavior was independent of overall pore size, matrix elasticity is shown to be not the major determinant of the cell characteristics. Our work emphasizes the complex relationship between structural-mechanical properties of the extracellular matrix and invasive behavior of cancer cells. It suggests a correlation of migratory and invasive phenotype of cancer cells in dependence on topological and mechanical features of the length scale of single fibrils and not on coarse-grained network properties. Copyright © 2015 Elsevier Ltd. All rights reserved.
Coarse-Grained Molecular Dynamics Simulation of Ionic Polymer Networks
2008-07-01
AFRL-RX-WP-TP-2009-4198 COARSE-GRAINED MOLECULAR DYNAMICS SIMULATION OF IONIC POLYMER NETWORKS (Postprint) T.E. Dirama, V. Varshney, K.L...GRAINED MOLECULAR DYNAMICS SIMULATION OF IONIC POLYMER NETWORKS (Postprint) 5a. CONTRACT NUMBER FA8650-05-D-5807-0052 5b. GRANT NUMBER 5c...We studied two types of networks which differ only by one containing ionic pairs that amount to 7% of the total number of bonds present. The stress
On the intrinsic flexibility of the opioid receptor through multiscale modeling approaches
NASA Astrophysics Data System (ADS)
Vercauteren, Daniel; FosséPré, Mathieu; Leherte, Laurence; Laaksonen, Aatto
Numerous releases of G protein-coupled receptors crystalline structures created the opportunity for computational methods to widely explore their dynamics. Here, we study the biological implication of the intrinsic flexibility properties of opioid receptor OR. First, one performed classical all-atom (AA) Molecular Dynamics (MD) simulations of OR in its apo-form. We highlighted that the various degrees of bendability of the α-helices present important consequences on the plasticity of the binding site. Hence, this latter adopts a wide diversity of shape and volume, explaining why OR interacts with very diverse ligands. Then, one introduces a new strategy for parameterizing purely mechanical but precise coarse-grained (CG) elastic network models (ENMs). The CG ENMs reproduced in a high accurate way the flexibility properties of OR versus the AA simulations. At last, one uses network modularization to design multi-grained (MG) models. They represent a novel type of low resolution models, different in nature versus CG models as being true multi-resolution models, i . e ., each MG grouping a different number of residues. The three parts constitute hierarchical and multiscale approach for tackling the flexibility of OR.
Coarse-Grained Clustering Dynamics of Heterogeneously Coupled Neurons.
Moon, Sung Joon; Cook, Katherine A; Rajendran, Karthikeyan; Kevrekidis, Ioannis G; Cisternas, Jaime; Laing, Carlo R
2015-12-01
The formation of oscillating phase clusters in a network of identical Hodgkin-Huxley neurons is studied, along with their dynamic behavior. The neurons are synaptically coupled in an all-to-all manner, yet the synaptic coupling characteristic time is heterogeneous across the connections. In a network of N neurons where this heterogeneity is characterized by a prescribed random variable, the oscillatory single-cluster state can transition-through [Formula: see text] (possibly perturbed) period-doubling and subsequent bifurcations-to a variety of multiple-cluster states. The clustering dynamic behavior is computationally studied both at the detailed and the coarse-grained levels, and a numerical approach that can enable studying the coarse-grained dynamics in a network of arbitrarily large size is suggested. Among a number of cluster states formed, double clusters, composed of nearly equal sub-network sizes are seen to be stable; interestingly, the heterogeneity parameter in each of the double-cluster components tends to be consistent with the random variable over the entire network: Given a double-cluster state, permuting the dynamical variables of the neurons can lead to a combinatorially large number of different, yet similar "fine" states that appear practically identical at the coarse-grained level. For weak heterogeneity we find that correlations rapidly develop, within each cluster, between the neuron's "identity" (its own value of the heterogeneity parameter) and its dynamical state. For single- and double-cluster states we demonstrate an effective coarse-graining approach that uses the Polynomial Chaos expansion to succinctly describe the dynamics by these quickly established "identity-state" correlations. This coarse-graining approach is utilized, within the equation-free framework, to perform efficient computations of the neuron ensemble dynamics.
Wavelet-based multiscale adjoint waveform-difference tomography using body and surface waves
NASA Astrophysics Data System (ADS)
Yuan, Y. O.; Simons, F. J.; Bozdag, E.
2014-12-01
We present a multi-scale scheme for full elastic waveform-difference inversion. Using a wavelet transform proves to be a key factor to mitigate cycle-skipping effects. We start with coarse representations of the seismogram to correct a large-scale background model, and subsequently explain the residuals in the fine scales of the seismogram to map the heterogeneities with great complexity. We have previously applied the multi-scale approach successfully to body waves generated in a standard model from the exploration industry: a modified two-dimensional elastic Marmousi model. With this model we explored the optimal choice of wavelet family, number of vanishing moments and decomposition depth. For this presentation we explore the sensitivity of surface waves in waveform-difference tomography. The incorporation of surface waves is rife with cycle-skipping problems compared to the inversions considering body waves only. We implemented an envelope-based objective function probed via a multi-scale wavelet analysis to measure the distance between predicted and target surface-wave waveforms in a synthetic model of heterogeneous near-surface structure. Our proposed method successfully purges the local minima present in the waveform-difference misfit surface. An elastic shallow model with 100~m in depth is used to test the surface-wave inversion scheme. We also analyzed the sensitivities of surface waves and body waves in full waveform inversions, as well as the effects of incorrect density information on elastic parameter inversions. Based on those numerical experiments, we ultimately formalized a flexible scheme to consider both body and surface waves in adjoint tomography. While our early examples are constructed from exploration-style settings, our procedure will be very valuable for the study of global network data.
Global Dynamics of Proteins: Bridging Between Structure and Function
Bahar, Ivet; Lezon, Timothy R.; Yang, Lee-Wei; Eyal, Eran
2010-01-01
Biomolecular systems possess unique, structure-encoded dynamic properties that underlie their biological functions. Recent studies indicate that these dynamic properties are determined to a large extent by the topology of native contacts. In recent years, elastic network models used in conjunction with normal mode analyses have proven to be useful for elucidating the collective dynamics intrinsically accessible under native state conditions, including in particular the global modes of motions that are robustly defined by the overall architecture. With increasing availability of structural data for well-studied proteins in different forms (liganded, complexed, or free), there is increasing evidence in support of the correspondence between functional changes in structures observed in experiments and the global motions predicted by these coarse-grained analyses. These observed correlations suggest that computational methods may be advantageously employed for assessing functional changes in structure and allosteric mechanisms intrinsically favored by the native fold. PMID:20192781
Global dynamics of proteins: bridging between structure and function.
Bahar, Ivet; Lezon, Timothy R; Yang, Lee-Wei; Eyal, Eran
2010-01-01
Biomolecular systems possess unique, structure-encoded dynamic properties that underlie their biological functions. Recent studies indicate that these dynamic properties are determined to a large extent by the topology of native contacts. In recent years, elastic network models used in conjunction with normal mode analyses have proven to be useful for elucidating the collective dynamics intrinsically accessible under native state conditions, including in particular the global modes of motions that are robustly defined by the overall architecture. With increasing availability of structural data for well-studied proteins in different forms (liganded, complexed, or free), there is increasing evidence in support of the correspondence between functional changes in structures observed in experiments and the global motions predicted by these coarse-grained analyses. These observed correlations suggest that computational methods may be advantageously employed for assessing functional changes in structure and allosteric mechanisms intrinsically favored by the native fold.
NASA Astrophysics Data System (ADS)
Morelli, Marco J.; Allen, Rosalind J.; Tǎnase-Nicola, Sorin; ten Wolde, Pieter Rein
2008-01-01
In many stochastic simulations of biochemical reaction networks, it is desirable to "coarse grain" the reaction set, removing fast reactions while retaining the correct system dynamics. Various coarse-graining methods have been proposed, but it remains unclear which methods are reliable and which reactions can safely be eliminated. We address these issues for a model gene regulatory network that is particularly sensitive to dynamical fluctuations: a bistable genetic switch. We remove protein-DNA and/or protein-protein association-dissociation reactions from the reaction set using various coarse-graining strategies. We determine the effects on the steady-state probability distribution function and on the rate of fluctuation-driven switch flipping transitions. We find that protein-protein interactions may be safely eliminated from the reaction set, but protein-DNA interactions may not. We also find that it is important to use the chemical master equation rather than macroscopic rate equations to compute effective propensity functions for the coarse-grained reactions.
Coarse-to-fine deep neural network for fast pedestrian detection
NASA Astrophysics Data System (ADS)
Li, Yaobin; Yang, Xinmei; Cao, Lijun
2017-11-01
Pedestrian detection belongs to a category of object detection is a key issue in the field of video surveillance and automatic driving. Although recent object detection methods, such as Fast/Faster RCNN, have achieved excellent performance, it is difficult to meet real-time requirements and limits the application in real scenarios. A coarse-to-fine deep neural network for fast pedestrian detection is proposed in this paper. Two-stage approach is presented to realize fine trade-off between accuracy and speed. In the coarse stage, we train a fast deep convolution neural network to generate most pedestrian candidates at the cost of a number of false positives. The detector can cover the majority of scales, sizes, and occlusions of pedestrians. After that, a classification network is introduced to refine the pedestrian candidates generated from the previous stage. Refining through classification network, most of false detections will be excluded easily and the final pedestrian predictions with bounding box and confidence score are produced. Competitive results have been achieved on INRIA dataset in terms of accuracy, especially the method can achieve real-time detection that is faster than the previous leading methods. The effectiveness of coarse-to-fine approach to detect pedestrians is verified, and the accuracy and stability are also improved.
Geometric Nonlinear Computation of Thin Rods and Shells
NASA Astrophysics Data System (ADS)
Grinspun, Eitan
2011-03-01
We develop simple, fast numerical codes for the dynamics of thin elastic rods and shells, by exploiting the connection between physics, geometry, and computation. By building a discrete mechanical picture from the ground up, mimicking the axioms, structures, and symmetries of the smooth setting, we produce numerical codes that not only are consistent in a classical sense, but also reproduce qualitative, characteristic behavior of a physical system----such as exact preservation of conservation laws----even for very coarse discretizations. As two recent examples, we present discrete computational models of elastic rods and shells, with straightforward extensions to the viscous setting. Even at coarse discretizations, the resulting simulations capture characteristic geometric instabilities. The numerical codes we describe are used in experimental mechanics, cinema, and consumer software products. This is joint work with Miklós Bergou, Basile Audoly, Max Wardetzky, and Etienne Vouga. This research is supported in part by the Sloan Foundation, the NSF, Adobe, Autodesk, Intel, the Walt Disney Company, and Weta Digital.
Multiscale Modelling for investigating single molecule effects on the mechanics of actin filaments
NASA Astrophysics Data System (ADS)
A, Deriu Marco; C, Bidone Tamara; Laura, Carbone; Cristina, Bignardi; M, Montevecchi Franco; Umberto, Morbiducci
2011-12-01
This work presents a preliminary multiscale computational investigation of the effects of nucleotides and cations on the mechanics of actin filaments (F-actin). At the molecular level, Molecular Dynamics (MD) simulations are employed to characterize the rearrangements of the actin monomers (G-actin) in terms of secondary structures evolution in physiological conditions. At the mesoscale level, a coarse grain (CG) procedure is adopted where each monomer is represented by means of Elastic Network Modeling (ENM) technique. At the macroscale level, actin filaments up to hundreds of nanometers are assumed as isotropic and elastic beams and characterized via Rotation Translation Block (RTB) analysis. F-actin bound to adenosine triphosphate (ATP) shows a persistence length around 5 μm, while actin filaments bound to adenosine diphosphate (ADP) have a persistence length of about 3 μm. With magnesium bound to the high affinity binding site of G-actin, the persistence length of F-actin decreases to about 2 μm only in the ADP-bound form of the filament, while the same ion has no effects, in terms of stiffness variation, on the ATP-bound form of F-actin. The molecular mechanisms behind these changes in flexibility are herein elucidated. Thus, this study allows to analyze how the local binding of cations and nucleotides on G-actin induce molecular rearrangements that transmit to the overall F-actin, characterizing shifts of mechanical properties, that can be related with physiological and pathological cellular phenomena, as cell migration and spreading. Further, this study provides the basis for upcoming investigating of network and cellular remodelling at higher length scales.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gao, Kai; Fu, Shubin; Gibson, Richard L.
It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both the boundaries and interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale mediummore » property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gao, Kai, E-mail: kaigao87@gmail.com; Fu, Shubin, E-mail: shubinfu89@gmail.com; Gibson, Richard L., E-mail: gibson@tamu.edu
It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both the boundaries and interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale mediummore » property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system.« less
Gao, Kai; Fu, Shubin; Gibson, Richard L.; ...
2015-04-14
It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both the boundaries and interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale mediummore » property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system.« less
Microstructural Origins of Nonlinear Response in Associating Polymers under Oscillatory Shear
Wilson, Mark A.; Baljon, Arlette R. C.
2017-10-26
The response of associating polymers with oscillatory shear is studied through large-scale simulations. A hybrid molecular dynamics (MD), Monte Carlo (MC) algorithm is employed. Polymer chains are modeled as a coarse-grained bead-spring system. Functionalized end groups, at both ends of the polymer chains, can form reversible bonds according to MC rules. Stress-strain curves show nonlinearities indicated by a non-ellipsoidal shape. We consider two types of nonlinearities. Type I occurs at a strain amplitude much larger than one, type II at a frequency at which the elastic storage modulus dominates the viscous loss modulus. In this last case, the network topologymore » resembles that of the system at rest. The reversible bonds are broken and chains stretch when the system moves away from the zero-strain position. For type I, the chains relax and the number of reversible bonds peaks when the system is near an extreme of the motion. During the movement to the other extreme of the cycle, first a stress overshoot occurs, then a yield accompanied by shear-banding. Lastly, the network restructures. Interestingly, the system periodically restores bonds between the same associating groups. Even though major restructuring occurs, the system remembers previous network topologies.« less
Surrogate modeling of deformable joint contact using artificial neural networks.
Eskinazi, Ilan; Fregly, Benjamin J
2015-09-01
Deformable joint contact models can be used to estimate loading conditions for cartilage-cartilage, implant-implant, human-orthotic, and foot-ground interactions. However, contact evaluations are often so expensive computationally that they can be prohibitive for simulations or optimizations requiring thousands or even millions of contact evaluations. To overcome this limitation, we developed a novel surrogate contact modeling method based on artificial neural networks (ANNs). The method uses special sampling techniques to gather input-output data points from an original (slow) contact model in multiple domains of input space, where each domain represents a different physical situation likely to be encountered. For each contact force and torque output by the original contact model, a multi-layer feed-forward ANN is defined, trained, and incorporated into a surrogate contact model. As an evaluation problem, we created an ANN-based surrogate contact model of an artificial tibiofemoral joint using over 75,000 evaluations of a fine-grid elastic foundation (EF) contact model. The surrogate contact model computed contact forces and torques about 1000 times faster than a less accurate coarse grid EF contact model. Furthermore, the surrogate contact model was seven times more accurate than the coarse grid EF contact model within the input domain of a walking motion. For larger input domains, the surrogate contact model showed the expected trend of increasing error with increasing domain size. In addition, the surrogate contact model was able to identify out-of-contact situations with high accuracy. Computational contact models created using our proposed ANN approach may remove an important computational bottleneck from musculoskeletal simulations or optimizations incorporating deformable joint contact models. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.
Surrogate Modeling of Deformable Joint Contact using Artificial Neural Networks
Eskinazi, Ilan; Fregly, Benjamin J.
2016-01-01
Deformable joint contact models can be used to estimate loading conditions for cartilage-cartilage, implant-implant, human-orthotic, and foot-ground interactions. However, contact evaluations are often so expensive computationally that they can be prohibitive for simulations or optimizations requiring thousands or even millions of contact evaluations. To overcome this limitation, we developed a novel surrogate contact modeling method based on artificial neural networks (ANNs). The method uses special sampling techniques to gather input-output data points from an original (slow) contact model in multiple domains of input space, where each domain represents a different physical situation likely to be encountered. For each contact force and torque output by the original contact model, a multi-layer feed-forward ANN is defined, trained, and incorporated into a surrogate contact model. As an evaluation problem, we created an ANN-based surrogate contact model of an artificial tibiofemoral joint using over 75,000 evaluations of a fine-grid elastic foundation (EF) contact model. The surrogate contact model computed contact forces and torques about 1000 times faster than a less accurate coarse grid EF contact model. Furthermore, the surrogate contact model was seven times more accurate than the coarse grid EF contact model within the input domain of a walking motion. For larger input domains, the surrogate contact model showed the expected trend of increasing error with increasing domain size. In addition, the surrogate contact model was able to identify out-of-contact situations with high accuracy. Computational contact models created using our proposed ANN approach may remove an important computational bottleneck from musculoskeletal simulations or optimizations incorporating deformable joint contact models. PMID:26220591
Star polymers as unit cells for coarse-graining cross-linked networks
NASA Astrophysics Data System (ADS)
Molotilin, Taras Y.; Maduar, Salim R.; Vinogradova, Olga I.
2018-03-01
Reducing the complexity of cross-linked polymer networks by preserving their main macroscale properties is key to understanding them, and a crucial issue is to relate individual properties of the polymer constituents to those of the reduced network. Here we study polymer networks in a good solvent, by considering star polymers as their unit elements, and first quantify the interaction between their centers of masses. We then reduce the complexity of a network by replacing sets of its bridged star polymers by equivalent effective soft particles with dense cores. Our coarse graining allows us to approximate complex polymer networks by much simpler ones, keeping their relevant mechanical properties, as illustrated in computer experiments.
Robustness Elasticity in Complex Networks
Matisziw, Timothy C.; Grubesic, Tony H.; Guo, Junyu
2012-01-01
Network robustness refers to a network’s resilience to stress or damage. Given that most networks are inherently dynamic, with changing topology, loads, and operational states, their robustness is also likely subject to change. However, in most analyses of network structure, it is assumed that interaction among nodes has no effect on robustness. To investigate the hypothesis that network robustness is not sensitive or elastic to the level of interaction (or flow) among network nodes, this paper explores the impacts of network disruption, namely arc deletion, over a temporal sequence of observed nodal interactions for a large Internet backbone system. In particular, a mathematical programming approach is used to identify exact bounds on robustness to arc deletion for each epoch of nodal interaction. Elasticity of the identified bounds relative to the magnitude of arc deletion is assessed. Results indicate that system robustness can be highly elastic to spatial and temporal variations in nodal interactions within complex systems. Further, the presence of this elasticity provides evidence that a failure to account for nodal interaction can confound characterizations of complex networked systems. PMID:22808060
Elastic and thermal expansion asymmetry in dense molecular materials.
Burg, Joseph A; Dauskardt, Reinhold H
2016-09-01
The elastic modulus and coefficient of thermal expansion are fundamental properties of elastically stiff molecular materials and are assumed to be the same (symmetric) under both tension and compression loading. We show that molecular materials can have a marked asymmetric elastic modulus and coefficient of thermal expansion that are inherently related to terminal chemical groups that limit molecular network connectivity. In compression, terminal groups sterically interact to stiffen the network, whereas in tension they interact less and disconnect the network. The existence of asymmetric elastic and thermal expansion behaviour has fundamental implications for computational approaches to molecular materials modelling and practical implications on the thermomechanical strains and associated elastic stresses. We develop a design space to control the degree of elastic asymmetry in molecular materials, a vital step towards understanding their integration into device technologies.
NASA Technical Reports Server (NTRS)
Spirkovska, Lilly; Reid, Max B.
1993-01-01
A higher-order neural network (HONN) can be designed to be invariant to changes in scale, translation, and inplane rotation. Invariances are built directly into the architecture of a HONN and do not need to be learned. Consequently, fewer training passes and a smaller training set are required to learn to distinguish between objects. The size of the input field is limited, however, because of the memory required for the large number of interconnections in a fully connected HONN. By coarse coding the input image, the input field size can be increased to allow the larger input scenes required for practical object recognition problems. We describe a coarse coding technique and present simulation results illustrating its usefulness and its limitations. Our simulations show that a third-order neural network can be trained to distinguish between two objects in a 4096 x 4096 pixel input field independent of transformations in translation, in-plane rotation, and scale in less than ten passes through the training set. Furthermore, we empirically determine the limits of the coarse coding technique in the object recognition domain.
Impact of branching on the elasticity of actin networks
Pujol, Thomas; du Roure, Olivia; Fermigier, Marc; Heuvingh, Julien
2012-01-01
Actin filaments play a fundamental role in cell mechanics: assembled into networks by a large number of partners, they ensure cell integrity, deformability, and migration. Here we focus on the mechanics of the dense branched network found at the leading edge of a crawling cell. We develop a new technique based on the dipolar attraction between magnetic colloids to measure mechanical properties of branched actin gels assembled around the colloids. This technique allows us to probe a large number of gels and, through the study of different networks, to access fundamental relationships between their microscopic structure and their mechanical properties. We show that the architecture does regulate the elasticity of the network: increasing both capping and branching concentrations strongly stiffens the networks. These effects occur at protein concentrations that can be regulated by the cell. In addition, the dependence of the elastic modulus on the filaments’ flexibility and on increasing internal stress has been studied. Our overall results point toward an elastic regime dominated by enthalpic rather than entropic deformations. This result strongly differs from the elasticity of diluted cross-linked actin networks and can be explained by the dense dendritic structure of lamellipodium-like networks. PMID:22689953
Surface Stresses and a Force Balance at a Contact Line.
Liang, Heyi; Cao, Zhen; Wang, Zilu; Dobrynin, Andrey V
2018-06-26
Results of the coarse-grained molecular dynamics simulations are used to show that the force balance analysis at the triple-phase contact line formed at an elastic substrate has to include a quartet of forces: three surface tensions (surface free energies) and an elastic force per unit length. In the case of the contact line formed by a droplet on an elastic substrate an elastic force is due to substrate deformation generated by formation of the wetting ridge. The magnitude of this force f el is proportional to the product of the ridge height h and substrate shear modulus G. Similar elastic line force should be included in the force analysis at the triple-phase contact line of a solid particle in contact with an elastic substrate. For this contact problem elastic force obtained from contact angles and surface tensions is a sum of the elastic forces acting from the side of a solid particle and an elastic substrate. By considering only three line forces acting at the triple-phase contact line, one implicitly accounts the bulk stress contribution as a part of the resultant surface stresses. This "contamination" of the surface properties by a bulk contribution could lead to unphysically large values of the surface stresses in soft materials.
Coarse-grained protein-protein stiffnesses and dynamics from all-atom simulations
NASA Astrophysics Data System (ADS)
Hicks, Stephen D.; Henley, C. L.
2010-03-01
Large protein assemblies, such as virus capsids, may be coarse-grained as a set of rigid units linked by generalized (rotational and stretching) harmonic springs. We present an ab initio method to obtain the elastic parameters and overdamped dynamics for these springs from all-atom molecular-dynamics simulations of one pair of units at a time. The computed relaxation times of this pair give a consistency check for the simulation, and we can also find the corrective force needed to null systematic drifts. As a first application we predict the stiffness of an HIV capsid layer and the relaxation time for its breathing mode.
Adiabatic coarse-graining and simulations of stochastic biochemical networks
Sinitsyn, N. A.; Hengartner, Nicolas; Nemenman, Ilya
2009-01-01
We propose a universal approach for analysis and fast simulations of stiff stochastic biochemical networks, which rests on elimination of fast chemical species without a loss of information about mesoscopic, non-Poissonian fluctuations of the slow ones. Our approach is similar to the Born–Oppenheimer approximation in quantum mechanics and follows from the stochastic path integral representation of the cumulant generating function of reaction events. In applications with a small number of chemical reactions, it produces analytical expressions for cumulants of chemical fluxes between the slow variables. This allows for a low-dimensional, interpretable representation and can be used for high-accuracy, low-complexity coarse-grained numerical simulations. As an example, we derive the coarse-grained description for a chain of biochemical reactions and show that the coarse-grained and the microscopic simulations agree, but the former is 3 orders of magnitude faster. PMID:19525397
Entropic elasticity based coarse-grained model of lipid membranes
NASA Astrophysics Data System (ADS)
Feng, Shuo; Hu, Yucai; Liang, Haiyi
2018-04-01
Various models for lipid bilayer membranes have been presented to investigate their morphologies. Among them, the aggressive coarse-grained models, where the membrane is represented by a single layer of particles, are computationally efficient and of practical importance for simulating membrane dynamics at the microscopic scale. In these models, soft potentials between particle pairs are used to maintain the fluidity of membranes, but the underlying mechanism of the softening requires further clarification. We have analyzed the membrane area decrease due to thermal fluctuations, and the results demonstrate that the intraparticle part of entropic elasticity is responsible for the softening of the potential. Based on the stretching response of the membrane, a bottom-up model is developed with an entropic effect explicitly involved. The model reproduces several essential properties of the lipid membrane, including the fluid state and a plateau in the stretching curve. In addition, the area compressibility modulus, bending rigidity, and spontaneous curvature display linear dependence on model parameters. As a demonstration, we have investigated the closure and morphology evolution of membrane systems driven by spontaneous curvature, and vesicle shapes observed experimentally are faithfully reproduced.
Experimental Observation of Two Features Unexpected from the Classical Theories of Rubber Elasticity
NASA Astrophysics Data System (ADS)
Nishi, Kengo; Fujii, Kenta; Chung, Ung-il; Shibayama, Mitsuhiro; Sakai, Takamasa
2017-12-01
Although the elastic modulus of a Gaussian chain network is thought to be successfully described by classical theories of rubber elasticity, such as the affine and phantom models, verification experiments are largely lacking owing to difficulties in precisely controlling of the network structure. We prepared well-defined model polymer networks experimentally, and measured the elastic modulus G for a broad range of polymer concentrations and connectivity probabilities, p . In our experiment, we observed two features that were distinct from those predicted by classical theories. First, we observed the critical behavior G ˜|p -pc|1.95 near the sol-gel transition. This scaling law is different from the prediction of classical theories, but can be explained by analogy between the electric conductivity of resistor networks and the elasticity of polymer networks. Here, pc is the sol-gel transition point. Furthermore, we found that the experimental G -p relations in the region above C* did not follow the affine or phantom theories. Instead, all the G /G0-p curves fell onto a single master curve when G was normalized by the elastic modulus at p =1 , G0. We show that the effective medium approximation for Gaussian chain networks explains this master curve.
Liu, Lei; Peng, Wei-Ren; Casellas, Ramon; Tsuritani, Takehiro; Morita, Itsuro; Martínez, Ricardo; Muñoz, Raül; Yoo, S J B
2014-01-13
Optical Orthogonal Frequency Division Multiplexing (O-OFDM), which transmits high speed optical signals using multiple spectrally overlapped lower-speed subcarriers, is a promising candidate for supporting future elastic optical networks. In contrast to previous works which focus on Coherent Optical OFDM (CO-OFDM), in this paper, we consider the direct-detection optical OFDM (DDO-OFDM) as the transport technique, which leads to simpler hardware and software realizations, potentially offering a low-cost solution for elastic optical networks, especially in metro networks, and short or medium distance core networks. Based on this network scenario, we design and deploy a software-defined networking (SDN) control plane enabled by extending OpenFlow, detailing the network architecture, the routing and spectrum assignment algorithm, OpenFlow protocol extensions and the experimental validation. To the best of our knowledge, it is the first time that an OpenFlow-based control plane is reported and its performance is quantitatively measured in an elastic optical network with DDO-OFDM transmission.
Summation rules for a fully nonlocal energy-based quasicontinuum method
NASA Astrophysics Data System (ADS)
Amelang, J. S.; Venturini, G. N.; Kochmann, D. M.
2015-09-01
The quasicontinuum (QC) method coarse-grains crystalline atomic ensembles in order to bridge the scales from individual atoms to the micro- and mesoscales. A crucial cornerstone of all QC techniques, summation or quadrature rules efficiently approximate the thermodynamic quantities of interest. Here, we investigate summation rules for a fully nonlocal, energy-based QC method to approximate the total Hamiltonian of a crystalline atomic ensemble by a weighted sum over a small subset of all atoms in the crystal lattice. Our formulation does not conceptually differentiate between atomistic and coarse-grained regions and thus allows for seamless bridging without domain-coupling interfaces. We review traditional summation rules and discuss their strengths and weaknesses with a focus on energy approximation errors and spurious force artifacts. Moreover, we introduce summation rules which produce no residual or spurious force artifacts in centrosymmetric crystals in the large-element limit under arbitrary affine deformations in two dimensions (and marginal force artifacts in three dimensions), while allowing us to seamlessly bridge to full atomistics. Through a comprehensive suite of examples with spatially non-uniform QC discretizations in two and three dimensions, we compare the accuracy of the new scheme to various previous ones. Our results confirm that the new summation rules exhibit significantly smaller force artifacts and energy approximation errors. Our numerical benchmark examples include the calculation of elastic constants from completely random QC meshes and the inhomogeneous deformation of aggressively coarse-grained crystals containing nano-voids. In the elastic regime, we directly compare QC results to those of full atomistics to assess global and local errors in complex QC simulations. Going beyond elasticity, we illustrate the performance of the energy-based QC method with the new second-order summation rule by the help of nanoindentation examples with automatic mesh adaptation. Overall, our findings provide guidelines for the selection of summation rules for the fully nonlocal energy-based QC method.
Coarse Scale In Situ Albedo Observations over Heterogeneous Land Surfaces and Validation Strategy
NASA Astrophysics Data System (ADS)
Xiao, Q.; Wu, X.; Wen, J.; BAI, J., Sr.
2017-12-01
To evaluate and improve the quality of coarse-pixel land surface albedo products, validation with ground measurements of albedo is crucial over the spatially and temporally heterogeneous land surface. The performance of albedo validation depends on the quality of ground-based albedo measurements at a corresponding coarse-pixel scale, which can be conceptualized as the "truth" value of albedo at coarse-pixel scale. The wireless sensor network (WSN) technology provides access to continuously observe on the large pixel scale. Taking the albedo products as an example, this paper was dedicated to the validation of coarse-scale albedo products over heterogeneous surfaces based on the WSN observed data, which is aiming at narrowing down the uncertainty of results caused by the spatial scaling mismatch between satellite and ground measurements over heterogeneous surfaces. The reference value of albedo at coarse-pixel scale can be obtained through an upscaling transform function based on all of the observations for that pixel. We will devote to further improve and develop new method that that are better able to account for the spatio-temporal characteristic of surface albedo in the future. Additionally, how to use the widely distributed single site measurements over the heterogeneous surfaces is also a question to be answered. Keywords: Remote sensing; Albedo; Validation; Wireless sensor network (WSN); Upscaling; Heterogeneous land surface; Albedo truth at coarse-pixel scale
Method and system for pattern analysis using a coarse-coded neural network
NASA Technical Reports Server (NTRS)
Spirkovska, Liljana (Inventor); Reid, Max B. (Inventor)
1994-01-01
A method and system for performing pattern analysis with a neural network coarse-coding a pattern to be analyzed so as to form a plurality of sub-patterns collectively defined by data. Each of the sub-patterns comprises sets of pattern data. The neural network includes a plurality fields, each field being associated with one of the sub-patterns so as to receive the sub-pattern data therefrom. Training and testing by the neural network then proceeds in the usual way, with one modification: the transfer function thresholds the value obtained from summing the weighted products of each field over all sub-patterns associated with each pattern being analyzed by the system.
A new paradigm for the molecular basis of rubber elasticity
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hanson, David E.; Barber, John L.
The molecular basis for rubber elasticity is arguably the oldest and one of the most important questions in the field of polymer physics. The theoretical investigation of rubber elasticity began in earnest almost a century ago with the development of analytic thermodynamic models, based on simple, highly-symmetric configurations of so-called Gaussian chains, i.e. polymer chains that obey Markov statistics. Numerous theories have been proposed over the past 90 years based on the ansatz that the elastic force for individual network chains arises from the entropy change associated with the distribution of end-to-end distances of a free polymer chain. There aremore » serious philosophical objections to this assumption and others, such as the assumption that all network nodes undergo affine motion and that all of the network chains have the same length. Recently, a new paradigm for elasticity in rubber networks has been proposed that is based on mechanisms that originate at the molecular level. Using conventional statistical mechanics analyses, quantum chemistry, and molecular dynamics simulations, the fundamental entropic and enthalpic chain extension forces for polyisoprene (natural rubber) have been determined, along with estimates for the basic force constants. Concurrently, the complex morphology of natural rubber networks (the joint probability density distributions that relate the chain end-to-end distance to its contour length) has also been captured in a numerical model. When molecular chain forces are merged with the network structure in this model, it is possible to study the mechanical response to tensile and compressive strains of a representative volume element of a polymer network. As strain is imposed on a network, pathways of connected taut chains, that completely span the network along strain axis, emerge. Although these chains represent only a few percent of the total, they account for nearly all of the elastic stress at high strain. Here we provide a brief review of previous elasticity theories and their deficiencies, and present a new paradigm with an emphasis on experimental comparisons.« less
A new paradigm for the molecular basis of rubber elasticity
Hanson, David E.; Barber, John L.
2015-02-19
The molecular basis for rubber elasticity is arguably the oldest and one of the most important questions in the field of polymer physics. The theoretical investigation of rubber elasticity began in earnest almost a century ago with the development of analytic thermodynamic models, based on simple, highly-symmetric configurations of so-called Gaussian chains, i.e. polymer chains that obey Markov statistics. Numerous theories have been proposed over the past 90 years based on the ansatz that the elastic force for individual network chains arises from the entropy change associated with the distribution of end-to-end distances of a free polymer chain. There aremore » serious philosophical objections to this assumption and others, such as the assumption that all network nodes undergo affine motion and that all of the network chains have the same length. Recently, a new paradigm for elasticity in rubber networks has been proposed that is based on mechanisms that originate at the molecular level. Using conventional statistical mechanics analyses, quantum chemistry, and molecular dynamics simulations, the fundamental entropic and enthalpic chain extension forces for polyisoprene (natural rubber) have been determined, along with estimates for the basic force constants. Concurrently, the complex morphology of natural rubber networks (the joint probability density distributions that relate the chain end-to-end distance to its contour length) has also been captured in a numerical model. When molecular chain forces are merged with the network structure in this model, it is possible to study the mechanical response to tensile and compressive strains of a representative volume element of a polymer network. As strain is imposed on a network, pathways of connected taut chains, that completely span the network along strain axis, emerge. Although these chains represent only a few percent of the total, they account for nearly all of the elastic stress at high strain. Here we provide a brief review of previous elasticity theories and their deficiencies, and present a new paradigm with an emphasis on experimental comparisons.« less
TensorCalculator: exploring the evolution of mechanical stress in the CCMV capsid
NASA Astrophysics Data System (ADS)
Kononova, Olga; Maksudov, Farkhad; Marx, Kenneth A.; Barsegov, Valeri
2018-01-01
A new computational methodology for the accurate numerical calculation of the Cauchy stress tensor, stress invariants, principal stress components, von Mises and Tresca tensors is developed. The methodology is based on the atomic stress approach which permits the calculation of stress tensors, widely used in continuum mechanics modeling of materials properties, using the output from the MD simulations of discrete atomic and C_α -based coarse-grained structural models of biological particles. The methodology mapped into the software package TensorCalculator was successfully applied to the empty cowpea chlorotic mottle virus (CCMV) shell to explore the evolution of mechanical stress in this mechanically-tested specific example of a soft virus capsid. We found an inhomogeneous stress distribution in various portions of the CCMV structure and stress transfer from one portion of the virus structure to another, which also points to the importance of entropic effects, often ignored in finite element analysis and elastic network modeling. We formulate a criterion for elastic deformation using the first principal stress components. Furthermore, we show that von Mises and Tresca stress tensors can be used to predict the onset of a viral capsid’s mechanical failure, which leads to total structural collapse. TensorCalculator can be used to study stress evolution and dynamics of defects in viral capsids and other large-size protein assemblies.
Decorated tensor network renormalization for lattice gauge theories and spin foam models
NASA Astrophysics Data System (ADS)
Dittrich, Bianca; Mizera, Sebastian; Steinhaus, Sebastian
2016-05-01
Tensor network techniques have proved to be powerful tools that can be employed to explore the large scale dynamics of lattice systems. Nonetheless, the redundancy of degrees of freedom in lattice gauge theories (and related models) poses a challenge for standard tensor network algorithms. We accommodate for such systems by introducing an additional structure decorating the tensor network. This allows to explicitly preserve the gauge symmetry of the system under coarse graining and straightforwardly interpret the fixed point tensors. We propose and test (for models with finite Abelian groups) a coarse graining algorithm for lattice gauge theories based on decorated tensor networks. We also point out that decorated tensor networks are applicable to other models as well, where they provide the advantage to give immediate access to certain expectation values and correlation functions.
NASA Astrophysics Data System (ADS)
Ortiz, Carlos Pompeyo
Rigidity emerges in a broad class of soft matter systems, relevant to many industrial and biological processes. In our experiments, we study a model soft matter system, hard-sphere Brownian suspensions of submicron particles. Brownian suspensions lack rigidity in the absence of external driving, but form flow-stabilized solid-like microsphere heaps under the influence of hydrodynamic forces. The overarching question driving my dissertation is "What is the nature of the rigidity of these microsphere heaps?" Does the rigidity of the heaps follow from mechanical stability driven by a sufficiently interconnected network of particle contacts? Or, does the rigidity of the heaps follow from a kinetic glass transition characterized by a diverging resistance to flow such that the time necessary to observe rearrangements grows prohibitively large? We expect that insights into the mechanism of rigidity of Brownian microsphere heaps are applicable to a wide class of soft matter systems. In this thesis,we have overcome the limitations of previous experimental approaches. Namely, we show that the rigidity of our heaps does not emerge from the effects of gravity, inertia, static friction, or van der Waals sticking. In Chapter 1 of thesis, we review the background literature. In Chapter 2, we present the experimental, analytical, and computational methods used in the remainder of the thesis. In Chapter 3, we investigate the onset of rigidity by characterizing the steady-state size of the heap versus the imposed flow conditions. We show that thermal fluctuations and repulsive interparticle interactions, the dominant forces at the single-particle scale, suppress the development of a rigid phase. These conditions imply that the onset of rigidity in involves many-body collective interactions. In Chapter 4, we measure the response of the heap to external perturbations, which allows us to measure their elastic modulus and compare our results to hard sphere theoretical expectations. We find bulk nonlinear elastic behavior. In Chapter 5, we study the particle displacements in response to external perturbations and quantify the local nonlinear elastic behavior.
Micromechanical model of lung parenchyma hyperelasticity
NASA Astrophysics Data System (ADS)
Concha, Felipe; Sarabia-Vallejos, Mauricio; Hurtado, Daniel E.
2018-03-01
Mechanics plays a key role in respiratory physiology, as lung tissue cyclically deforms to bring air in and out the lung, a life-long process necessary for respiration. The study of regional mechanisms of deformation in lung parenchyma has received great attention to date due to its clinical relevance, as local overstretching and stress concentration in lung tissue is currently associated to pathological conditions such as lung injury during mechanical ventilation therapy. This mechanical approach to lung physiology has motivated the development of constitutive models to better understand the relation between stress and deformation in the lung. While material models proposed to date have been key in the development of whole-lung simulations, either they do not directly relate microstructural properties of alveolar tissue with coarse-scale behavior, or they require a high computational effort when based on real alveolar geometries. Furthermore, most models proposed to date have not been thoroughly validated for anisotropic deformation states, which are commonly found in normal lungs in-vivo. In this work, we develop a novel micromechanical model of lung parenchyma hyperelasticity using the framework of finite-deformation homogenization. To this end, we consider a tetrakaidecahedron unit cell with incompressible Neo-Hookean structural elements that account for the alveolar wall tissue responsible for the elastic response, and derive expressions for its effective coarse-scale behavior that directly depend on the alveolar wall elasticity, reference porosity, and two other geometrical coefficients. To validate the proposed model, we simulate the non-linear elastic response of twelve representative volume elements (RVEs) of lung parenchyma with micrometric dimensions, whose geometry is obtained from micrometric computed-tomography reconstructions of murine lungs. We show that the proposed micromechanical model accurately captures the RVEs response not only for isotropic volumetric expansion, but also for three other anisotropic loading conditions for different levels of tissue porosity, while displaying superior computational efficiency and stability in estimating coarse-scale response when compared to direct numerical simulations of RVEs. Further, we find that the most influential microstructural parameters on the response of the micromechanical model are the reference porosity and the alveolar wall elasticity. We also show that the model can reproduce uniaxial experimental tests on lung tissue samples, and estimate the Poisson ratio to be 0.22. We envision that our model will enable predictive and efficient whole-organ simulations useful to study the normal and diseased lung.
Chen, Po-Chia; Hologne, Maggy; Walker, Olivier
2017-03-02
Rotational diffusion (D rot ) is a fundamental property of biomolecules that contains information about molecular dimensions and solute-solvent interactions. While ab initio D rot prediction can be achieved by explicit all-atom molecular dynamics simulations, this is hindered by both computational expense and limitations in water models. We propose coarse-grained force fields as a complementary solution, and show that the MARTINI force field with elastic networks is sufficient to compute D rot in >10 proteins spanning 5-157 kDa. We also adopt a quaternion-based approach that computes D rot orientation directly from autocorrelations of best-fit rotations as used in, e.g., RMSD algorithms. Over 2 μs trajectories, isotropic MARTINI+EN tumbling replicates experimental values to within 10-20%, with convergence analyses suggesting a minimum sampling of >50 × τ theor to achieve sufficient precision. Transient fluctuations in anisotropic tumbling cause decreased precision in predictions of axisymmetric anisotropy and rhombicity, the latter of which cannot be precisely evaluated within 2000 × τ theor for GB3. Thus, we encourage reporting of axial decompositions D x , D y , D z to ease comparability between experiment and simulation. Where protein disorder is absent, we observe close replication of MARTINI+EN D rot orientations versus CHARMM22*/TIP3p and experimental data. This work anticipates the ab initio prediction of NMR-relaxation by combining coarse-grained global motions with all-atom local motions.
Thermodynamically consistent coarse graining of biocatalysts beyond Michaelis–Menten
NASA Astrophysics Data System (ADS)
Wachtel, Artur; Rao, Riccardo; Esposito, Massimiliano
2018-04-01
Starting from the detailed catalytic mechanism of a biocatalyst we provide a coarse-graining procedure which, by construction, is thermodynamically consistent. This procedure provides stoichiometries, reaction fluxes (rate laws), and reaction forces (Gibbs energies of reaction) for the coarse-grained level. It can treat active transporters and molecular machines, and thus extends the applicability of ideas that originated in enzyme kinetics. Our results lay the foundations for systematic studies of the thermodynamics of large-scale biochemical reaction networks. Moreover, we identify the conditions under which a relation between one-way fluxes and forces holds at the coarse-grained level as it holds at the detailed level. In doing so, we clarify the speculations and broad claims made in the literature about such a general flux–force relation. As a further consequence we show that, in contrast to common belief, the second law of thermodynamics does not require the currents and the forces of biochemical reaction networks to be always aligned.
Algorithms for tensor network renormalization
NASA Astrophysics Data System (ADS)
Evenbly, G.
2017-01-01
We discuss in detail algorithms for implementing tensor network renormalization (TNR) for the study of classical statistical and quantum many-body systems. First, we recall established techniques for how the partition function of a 2 D classical many-body system or the Euclidean path integral of a 1 D quantum system can be represented as a network of tensors, before describing how TNR can be implemented to efficiently contract the network via a sequence of coarse-graining transformations. The efficacy of the TNR approach is then benchmarked for the 2 D classical statistical and 1 D quantum Ising models; in particular the ability of TNR to maintain a high level of accuracy over sustained coarse-graining transformations, even at a critical point, is demonstrated.
McLeish, Tom C.B.; Cann, Martin J.; Rodgers, Thomas L.
2015-01-01
We examine the contrast between mechanisms for allosteric signaling that involve structural change, and those that do not, from the perspective of allosteric pathways. In particular we treat in detail the case of fluctuation-allostery by which amplitude modulation of the thermal fluctuations of the elastic normal modes conveys the allosteric signal, and address the question of what an allosteric pathway means in this case. We find that a perturbation theory of thermal elastic solids and nonperturbative approach (by super-coarse-graining elasticity into internal bending modes) have opposite signatures in their structure of correlated pathways. We illustrate the effect from analysis of previous results from GlxR of Corynebacterium glutamicum, an example of the CRP/FNR transcription family of allosteric homodimers. We find that the visibility of both correlated pathways and disconnected sites of correlated motion in this protein suggests that mechanisms of local elastic stretch and bend are recruited for the purpose of creating and controlling allosteric cooperativity. PMID:26338443
Elastic constants from microscopic strain fluctuations
Sengupta; Nielaba; Rao; Binder
2000-02-01
Fluctuations of the instantaneous local Lagrangian strain epsilon(ij)(r,t), measured with respect to a static "reference" lattice, are used to obtain accurate estimates of the elastic constants of model solids from atomistic computer simulations. The measured strains are systematically coarse-grained by averaging them within subsystems (of size L(b)) of a system (of total size L) in the canonical ensemble. Using a simple finite size scaling theory we predict the behavior of the fluctuations
NASA Astrophysics Data System (ADS)
Haryanto, Y.; Hermanto, N. I. S.; Pamudji, G.; Wardana, K. P.
2017-11-01
One feasible solution to overcome the issue of tire disposal waste is the use of waste tire rubber to replace aggregate in concrete. We have conducted an experimental investigation on the effect of rubber tire waste aggregate in cuboid form on the compressive strength and modulus of elasticity of concrete. The test was performed on 72 cylindrical specimens with the height of 300 mm and diameter of 150 mm. We found that the workability of concrete with waste tire rubber aggregate has increased. The concrete density with waste tire rubber aggregate was decreased, and so was the compressive strength. The decrease of compressive strength is up to 64.34%. If the content of waste tire rubber aggregate is more than 40%, then the resulting concrete cannot be categorized as structural concrete. The modulus of elasticity decreased to 59.77%. The theoretical equation developed to determine the modulus of elasticity of concrete with rubber tire waste aggregate has an accuracy of 84.27%.
Recursive regularization for inferring gene networks from time-course gene expression profiles
Shimamura, Teppei; Imoto, Seiya; Yamaguchi, Rui; Fujita, André; Nagasaki, Masao; Miyano, Satoru
2009-01-01
Background Inferring gene networks from time-course microarray experiments with vector autoregressive (VAR) model is the process of identifying functional associations between genes through multivariate time series. This problem can be cast as a variable selection problem in Statistics. One of the promising methods for variable selection is the elastic net proposed by Zou and Hastie (2005). However, VAR modeling with the elastic net succeeds in increasing the number of true positives while it also results in increasing the number of false positives. Results By incorporating relative importance of the VAR coefficients into the elastic net, we propose a new class of regularization, called recursive elastic net, to increase the capability of the elastic net and estimate gene networks based on the VAR model. The recursive elastic net can reduce the number of false positives gradually by updating the importance. Numerical simulations and comparisons demonstrate that the proposed method succeeds in reducing the number of false positives drastically while keeping the high number of true positives in the network inference and achieves two or more times higher true discovery rate (the proportion of true positives among the selected edges) than the competing methods even when the number of time points is small. We also compared our method with various reverse-engineering algorithms on experimental data of MCF-7 breast cancer cells stimulated with two ErbB ligands, EGF and HRG. Conclusion The recursive elastic net is a powerful tool for inferring gene networks from time-course gene expression profiles. PMID:19386091
Elastic collapse in disordered isostatic networks
NASA Astrophysics Data System (ADS)
Moukarzel, C. F.
2012-02-01
Isostatic networks are minimally rigid and therefore have, generically, nonzero elastic moduli. Regular isostatic networks have finite moduli in the limit of large sizes. However, numerical simulations show that all elastic moduli of geometrically disordered isostatic networks go to zero with system size. This holds true for positional as well as for topological disorder. In most cases, elastic moduli decrease as inverse power laws of system size. On directed isostatic networks, however, of which the square and cubic lattices are particular cases, the decrease of the moduli is exponential with size. For these, the observed elastic weakening can be quantitatively described in terms of the multiplicative growth of stresses with system size, giving rise to bulk and shear moduli of order e-bL. The case of sphere packings, which only accept compressive contact forces, is considered separately. It is argued that these have a finite bulk modulus because of specific correlations in contact disorder, introduced by the constraint of compressivity. We discuss why their shear modulus, nevertheless, is again zero for large sizes. A quantitative model is proposed that describes the numerically measured shear modulus, both as a function of the loading angle and system size. In all cases, if a density p>0 of overconstraints is present, as when a packing is deformed by compression or when a glass is outside its isostatic composition window, all asymptotic moduli become finite. For square networks with periodic boundary conditions, these are of order \\sqrt{p} . For directed networks, elastic moduli are of order e-c/p, indicating the existence of an "isostatic length scale" of order 1/p.
NASA Astrophysics Data System (ADS)
Skripnyak, Vladimir
2011-06-01
Features of mechanical behavior of nanostructured (NS) and ultrafine grained (UFG) metal and ceramic materials under quasistatic and shock wave loadings are discussed in this report. Multilevel models developed within the approach of computational mechanics of materials were used for simulation mechanical behavior of UFG and NS metals and ceramics. Comparisons of simulation results with experimental data are presented. Models of mechanical behavior of nanostructured metal alloys takes into account a several structural factors influencing on the mechanical behavior of materials (type of a crystal lattice, density of dislocations, a size of dislocation substructures, concentration and size of phase precipitation, and distribution of grains sizes). Results show the strain rate sensitivity of the yield stress of UFG and polycrystalline alloys is various in a range from 103 up to 106 1/s. But the difference of the Hugoniot elastic limits of a UFG and coarse-grained alloys may be not considerable. The spall strength, the yield stress of UFG and NS alloys are depend not only on grains size, but a number of factors such as a distribution of grains sizes, a concentration and sizes of voids and cracks, a concentration and sizes of phase precipitation. Some titanium alloys with grain sizes from 300 to 500 nm have the quasi-static yield strength and the tensile strength twice higher than that of coarse grained counterparts. But the spall strength of the UFG titanium alloys is only 10 percents above than that of coarse grained alloys. At the same time it was found the spall strength of the bulk UFG aluminium and magnesium alloys with precipitation strengthening is essentially higher in comparison of coarse-grained counterparts. The considerable decreasing of the strain before failure of UFG alloys was predicted at high strain rates. The Hugoniot elastic limits of oxide nanoceramics depend not only on the porosity, but also on sizes and volume distribution of voids.
Tavakoli, J; Elliott, D M; Costi, J J
2017-08-01
The inter-lamellar matrix (ILM)-located between adjacent lamellae of the annulus fibrosus-consists of a complex structure of elastic fibers, while elastic fibers of the intra-lamellar region are aligned predominantly parallel to the collagen fibers. The organization of elastic fibers under low magnification, in both inter- and intra-lamellar regions, was studied by light microscopic analysis of histologically prepared samples; however, little is known about their ultrastructure. An ultrastructural visualization of elastic fibers in the inter-lamellar matrix is crucial for describing their contribution to structural integrity, as well as mechanical properties of the annulus fibrosus. The aims of this study were twofold: first, to present an ultrastructural analysis of the elastic fiber network in the ILM and intra-lamellar region, including cross section (CS) and in-plane (IP) lamellae, of the AF using Scanning Electron Microscopy (SEM) and second, to -compare the elastic fiber orientation between the ILM and intra-lamellar region. Four samples (lumbar sheep discs) from adjacent sections (30μm thickness) of anterior annulus were partially digested by a developed NaOH-sonication method for visualization of elastic fibers by SEM. Elastic fiber orientation and distribution were quantified relative to the tangential to circumferential reference axis. Visualization of the ILM under high magnification revealed a dense network of elastic fibers that has not been previously described. Within the ILM, elastic fibers form a complex network, consisting of different size and shape fibers, which differed to those located in the intra-lamellar region. For both regions, the majority of fibers were oriented near 0° with respect to tangential to circumferential (TCD) direction and two minor symmetrical orientations of approximately±45°. Statistically, the orientation of elastic fibers between the ILM and intra-lamellar region was not different (p=0.171). The present study used extracellular matrix partial digestion to address significant gaps in understanding of disc microstructure and will contribute to multidisciplinary ultrastructure-function studies. Visualization of the intra-lamellar matrix under high magnification revealed a dense network of elastic fibers that has not been previously described. The present study used extracellular matrix partial digestion to address significant gaps in understanding of disc microstructure and will contribute to multidisciplinary ultrastructure-function studies. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Skripnyak, Vladimir
2012-03-01
Features of mechanical behavior of nanostructured and ultrafine-grained metals under quasistatic and shock wave loadings are discussed. Features of mechanical behavior of nanostructured and ultrafine grained metals over a wide range of strain rates are discussed. A constitutive model for mechanical behavior of metal alloys under shock wave loading including a grain size distribution, a precipitate hardening, and physical mechanisms of shear stress relaxation is presented. Strain rate sensitivity of the yield stress of face-centered-cubic, hexagonal close-packed metal alloys depends on grain size, whereas the Hugoniot elastic limits of ultrafine-grained copper, aluminum, and titanium alloys are close to values of coarse-grained counterparts. At quasi-static loading the yield strength and the tensile strength of titanium alloys with grain size from 300 to 500 nm are twice higher than at coarse-grained counterparts. But the spall strength of the UFG titanium alloys exceeds the value of coarse-grained counterparts only for 10 percents.
Physics of soft hyaluronic acid-collagen type II double network gels
NASA Astrophysics Data System (ADS)
Morozova, Svetlana; Muthukumar, Murugappan
2015-03-01
Many biological hydrogels are made up of multiple interpenetrating, charged components. We study the swelling, elastic diffusion, mechanical, and optical behaviors of 100 mol% ionizable hyaluronic acid (HA) and collagen type II fiber networks. Dilute, 0.05-0.5 wt% hyaluronic acid networks are extremely sensitive to solution salt concentration, but are stable at pH above 2. When swelled in 0.1M NaCl, single-network hyaluronic acid gels follow scaling laws relevant to high salt semidilute solutions; the elastic shear modulus G' and diffusion constant D scale with the volume fraction ϕ as G' ~ϕ 9 / 4 and D ~ϕ 3 / 4 , respectively. With the addition of a collagen fiber network, we find that the hyaluronic acid network swells to suspend the rigid collagen fibers, providing extra strength to the hydrogel. Results on swelling equilibria, elasticity, and collective diffusion on these double network hydrogels will be presented.
Evolutionary multidimensional access architecture featuring cost-reduced components
NASA Astrophysics Data System (ADS)
Farjady, Farsheed; Parker, Michael C.; Walker, Stuart D.
1998-12-01
We describe a three-stage wavelength-routed optical access network, utilizing coarse passband-flattened arrayed- waveguide grating routers. An N-dimensional addressing strategy enables 6912 customers to be bi-directionally addressed with multi-Gb/s data using only 24 wavelengths spaced by 1.6 nm. Coarse wavelength separation allows use of increased tolerance WDM components at the exchange and customer premises. The architecture is designed to map onto standard access network topologies, allowing elegant upgradability from legacy PON infrastructures at low cost. Passband-flattening of the routers is achieved through phase apodization.
Molecular modeling of polycarbonate materials: Glass transition and mechanical properties
NASA Astrophysics Data System (ADS)
Palczynski, Karol; Wilke, Andreas; Paeschke, Manfred; Dzubiella, Joachim
2017-09-01
Linking the experimentally accessible macroscopic properties of thermoplastic polymers to their microscopic static and dynamic properties is a key requirement for targeted material design. Classical molecular dynamics simulations enable us to study the structural and dynamic behavior of molecules on microscopic scales, and statistical physics provides a framework for relating these properties to the macroscopic properties. We take a first step toward creating an automated workflow for the theoretical prediction of thermoplastic material properties by developing an expeditious method for parameterizing a simple yet surprisingly powerful coarse-grained bisphenol-A polycarbonate model which goes beyond previous coarse-grained models and successfully reproduces the thermal expansion behavior, the glass transition temperature as a function of the molecular weight, and several elastic properties.
2012-08-01
paper, we will first briefly discuss our recent results, using coarse-grained bead - spring model , on the dependence of failure stress and failure...length of the resin strands. In the coarse-grained model used here the polymer network is treated as a bead - spring system. To create highly cross...simulations of Thermosets We have used a coarse-grained bead - spring model to study the dependence of the mechanical properties of thermosets on chain
Kauffmann, Louise; Chauvin, Alan; Pichat, Cédric; Peyrin, Carole
2015-10-01
According to current models of visual perception scenes are processed in terms of spatial frequencies following a predominantly coarse-to-fine processing sequence. Low spatial frequencies (LSF) reach high-order areas rapidly in order to activate plausible interpretations of the visual input. This triggers top-down facilitation that guides subsequent processing of high spatial frequencies (HSF) in lower-level areas such as the inferotemporal and occipital cortices. However, dynamic interactions underlying top-down influences on the occipital cortex have never been systematically investigated. The present fMRI study aimed to further explore the neural bases and effective connectivity underlying coarse-to-fine processing of scenes, particularly the role of the occipital cortex. We used sequences of six filtered scenes as stimuli depicting coarse-to-fine or fine-to-coarse processing of scenes. Participants performed a categorization task on these stimuli (indoor vs. outdoor). Firstly, we showed that coarse-to-fine (compared to fine-to-coarse) sequences elicited stronger activation in the inferior frontal gyrus (in the orbitofrontal cortex), the inferotemporal cortex (in the fusiform and parahippocampal gyri), and the occipital cortex (in the cuneus). Dynamic causal modeling (DCM) was then used to infer effective connectivity between these regions. DCM results revealed that coarse-to-fine processing resulted in increased connectivity from the occipital cortex to the inferior frontal gyrus and from the inferior frontal gyrus to the inferotemporal cortex. Critically, we also observed an increase in connectivity strength from the inferior frontal gyrus to the occipital cortex, suggesting that top-down influences from frontal areas may guide processing of incoming signals. The present results support current models of visual perception and refine them by emphasizing the role of the occipital cortex as a cortical site for feedback projections in the neural network underlying coarse-to-fine processing of scenes. Copyright © 2015 Elsevier Inc. All rights reserved.
Kujala, Rainer; Glerean, Enrico; Pan, Raj Kumar; Jääskeläinen, Iiro P; Sams, Mikko; Saramäki, Jari
2016-11-01
Networks have become a standard tool for analyzing functional magnetic resonance imaging (fMRI) data. In this approach, brain areas and their functional connections are mapped to the nodes and links of a network. Even though this mapping reduces the complexity of the underlying data, it remains challenging to understand the structure of the resulting networks due to the large number of nodes and links. One solution is to partition networks into modules and then investigate the modules' composition and relationship with brain functioning. While this approach works well for single networks, understanding differences between two networks by comparing their partitions is difficult and alternative approaches are thus necessary. To this end, we present a coarse-graining framework that uses a single set of data-driven modules as a frame of reference, enabling one to zoom out from the node- and link-level details. As a result, differences in the module-level connectivity can be understood in a transparent, statistically verifiable manner. We demonstrate the feasibility of the method by applying it to networks constructed from fMRI data recorded from 13 healthy subjects during rest and movie viewing. While independently partitioning the rest and movie networks is shown to yield little insight, the coarse-graining framework enables one to pinpoint differences in the module-level structure, such as the increased number of intra-module links within the visual cortex during movie viewing. In addition to quantifying differences due to external stimuli, the approach could also be applied in clinical settings, such as comparing patients with healthy controls. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Gene regulatory networks: a coarse-grained, equation-free approach to multiscale computation.
Erban, Radek; Kevrekidis, Ioannis G; Adalsteinsson, David; Elston, Timothy C
2006-02-28
We present computer-assisted methods for analyzing stochastic models of gene regulatory networks. The main idea that underlies this equation-free analysis is the design and execution of appropriately initialized short bursts of stochastic simulations; the results of these are processed to estimate coarse-grained quantities of interest, such as mesoscopic transport coefficients. In particular, using a simple model of a genetic toggle switch, we illustrate the computation of an effective free energy Phi and of a state-dependent effective diffusion coefficient D that characterize an unavailable effective Fokker-Planck equation. Additionally we illustrate the linking of equation-free techniques with continuation methods for performing a form of stochastic "bifurcation analysis"; estimation of mean switching times in the case of a bistable switch is also implemented in this equation-free context. The accuracy of our methods is tested by direct comparison with long-time stochastic simulations. This type of equation-free analysis appears to be a promising approach to computing features of the long-time, coarse-grained behavior of certain classes of complex stochastic models of gene regulatory networks, circumventing the need for long Monte Carlo simulations.
Rubber elasticity for percolation network consisting of Gaussian chains.
Nishi, Kengo; Noguchi, Hiroshi; Sakai, Takamasa; Shibayama, Mitsuhiro
2015-11-14
A theory describing the elastic modulus for percolation networks of Gaussian chains on general lattices such as square and cubic lattices is proposed and its validity is examined with simulation and mechanical experiments on well-defined polymer networks. The theory was developed by generalizing the effective medium approximation (EMA) for Hookian spring network to Gaussian chain networks. From EMA theory, we found that the ratio of the elastic modulus at p, G to that at p = 1, G0, must be equal to G/G0 = (p - 2/f)/(1 - 2/f) if the position of sites can be determined so as to meet the force balance, where p is the degree of cross-linking reaction. However, the EMA prediction cannot be applicable near its percolation threshold because EMA is a mean field theory. Thus, we combine real-space renormalization and EMA and propose a theory called real-space renormalized EMA, i.e., REMA. The elastic modulus predicted by REMA is in excellent agreement with the results of simulations and experiments of near-ideal diamond lattice gels.
Rubber elasticity for percolation network consisting of Gaussian chains
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nishi, Kengo, E-mail: kengo.nishi@phys.uni-goettingen.de, E-mail: sakai@tetrapod.t.u-tokyo.ac.jp, E-mail: sibayama@issp.u-tokyo.ac.jp; Noguchi, Hiroshi; Shibayama, Mitsuhiro, E-mail: kengo.nishi@phys.uni-goettingen.de, E-mail: sakai@tetrapod.t.u-tokyo.ac.jp, E-mail: sibayama@issp.u-tokyo.ac.jp
2015-11-14
A theory describing the elastic modulus for percolation networks of Gaussian chains on general lattices such as square and cubic lattices is proposed and its validity is examined with simulation and mechanical experiments on well-defined polymer networks. The theory was developed by generalizing the effective medium approximation (EMA) for Hookian spring network to Gaussian chain networks. From EMA theory, we found that the ratio of the elastic modulus at p, G to that at p = 1, G{sub 0}, must be equal to G/G{sub 0} = (p − 2/f)/(1 − 2/f) if the position of sites can be determined somore » as to meet the force balance, where p is the degree of cross-linking reaction. However, the EMA prediction cannot be applicable near its percolation threshold because EMA is a mean field theory. Thus, we combine real-space renormalization and EMA and propose a theory called real-space renormalized EMA, i.e., REMA. The elastic modulus predicted by REMA is in excellent agreement with the results of simulations and experiments of near-ideal diamond lattice gels.« less
Path statistics, memory, and coarse-graining of continuous-time random walks on networks
Kion-Crosby, Willow; Morozov, Alexandre V.
2015-01-01
Continuous-time random walks (CTRWs) on discrete state spaces, ranging from regular lattices to complex networks, are ubiquitous across physics, chemistry, and biology. Models with coarse-grained states (for example, those employed in studies of molecular kinetics) or spatial disorder can give rise to memory and non-exponential distributions of waiting times and first-passage statistics. However, existing methods for analyzing CTRWs on complex energy landscapes do not address these effects. Here we use statistical mechanics of the nonequilibrium path ensemble to characterize first-passage CTRWs on networks with arbitrary connectivity, energy landscape, and waiting time distributions. Our approach can be applied to calculating higher moments (beyond the mean) of path length, time, and action, as well as statistics of any conservative or non-conservative force along a path. For homogeneous networks, we derive exact relations between length and time moments, quantifying the validity of approximating a continuous-time process with its discrete-time projection. For more general models, we obtain recursion relations, reminiscent of transfer matrix and exact enumeration techniques, to efficiently calculate path statistics numerically. We have implemented our algorithm in PathMAN (Path Matrix Algorithm for Networks), a Python script that users can apply to their model of choice. We demonstrate the algorithm on a few representative examples which underscore the importance of non-exponential distributions, memory, and coarse-graining in CTRWs. PMID:26646868
Yang, Hui; Zhang, Jie; Ji, Yuefeng; Tian, Rui; Han, Jianrui; Lee, Young
2015-11-30
Data center interconnect with elastic optical network is a promising scenario to meet the high burstiness and high-bandwidth requirements of data center services. In our previous work, we implemented multi-stratum resilience between IP and elastic optical networks that allows to accommodate data center services. In view of this, this study extends to consider the resource integration by breaking the limit of network device, which can enhance the resource utilization. We propose a novel multi-stratum resources integration (MSRI) architecture based on network function virtualization in software defined elastic data center optical interconnect. A resource integrated mapping (RIM) scheme for MSRI is introduced in the proposed architecture. The MSRI can accommodate the data center services with resources integration when the single function or resource is relatively scarce to provision the services, and enhance globally integrated optimization of optical network and application resources. The overall feasibility and efficiency of the proposed architecture are experimentally verified on the control plane of OpenFlow-based enhanced software defined networking (eSDN) testbed. The performance of RIM scheme under heavy traffic load scenario is also quantitatively evaluated based on MSRI architecture in terms of path blocking probability, provisioning latency and resource utilization, compared with other provisioning schemes.
Normal Stresses, Contraction, and Stiffening in Sheared Elastic Networks
NASA Astrophysics Data System (ADS)
Baumgarten, Karsten; Tighe, Brian P.
2018-04-01
When elastic solids are sheared, a nonlinear effect named after Poynting gives rise to normal stresses or changes in volume. We provide a novel relation between the Poynting effect and the microscopic Grüneisen parameter, which quantifies how stretching shifts vibrational modes. By applying this relation to random spring networks, a minimal model for, e.g., biopolymer gels and solid foams, we find that networks contract or develop tension because they vibrate faster when stretched. The amplitude of the Poynting effect is sensitive to the network's linear elastic moduli, which can be tuned via its preparation protocol and connectivity. Finally, we show that the Poynting effect can be used to predict the finite strain scale where the material stiffens under shear.
Inherently unstable networks collapse to a critical point
NASA Astrophysics Data System (ADS)
Sheinman, M.; Sharma, A.; Alvarado, J.; Koenderink, G. H.; MacKintosh, F. C.
2015-07-01
Nonequilibrium systems that are driven or drive themselves towards a critical point have been studied for almost three decades. Here we present a minimalist example of such a system, motivated by experiments on collapsing active elastic networks. Our model of an unstable elastic network exhibits a collapse towards a critical point from any macroscopically connected initial configuration. Taking into account steric interactions within the network, the model qualitatively and quantitatively reproduces results of the experiments on collapsing active gels.
2011-04-01
experiments was performed using an artificial neural network to try to capture the nonlinearities. The radial Gaussian artificial neural network system...Modeling Blast-Wave Propagation using Artificial Neural Network Methods‖, in International Journal of Advanced Engineering Informatics, Elsevier
An expanded role for river networks
Jonathan P. Benstead; David S. Leigh
2012-01-01
Estimates of stream and river area have relied on observations at coarse resolution. Consideration of the smallest and most dynamic streams could reveal a greater role for river networks in global biogeochemical cycling than previously thought.
iMODS: internal coordinates normal mode analysis server.
López-Blanco, José Ramón; Aliaga, José I; Quintana-Ortí, Enrique S; Chacón, Pablo
2014-07-01
Normal mode analysis (NMA) in internal (dihedral) coordinates naturally reproduces the collective functional motions of biological macromolecules. iMODS facilitates the exploration of such modes and generates feasible transition pathways between two homologous structures, even with large macromolecules. The distinctive internal coordinate formulation improves the efficiency of NMA and extends its applicability while implicitly maintaining stereochemistry. Vibrational analysis, motion animations and morphing trajectories can be easily carried out at different resolution scales almost interactively. The server is versatile; non-specialists can rapidly characterize potential conformational changes, whereas advanced users can customize the model resolution with multiple coarse-grained atomic representations and elastic network potentials. iMODS supports advanced visualization capabilities for illustrating collective motions, including an improved affine-model-based arrow representation of domain dynamics. The generated all-heavy-atoms conformations can be used to introduce flexibility for more advanced modeling or sampling strategies. The server is free and open to all users with no login requirement at http://imods.chaconlab.org. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
Hybrid services efficient provisioning over the network coding-enabled elastic optical networks
NASA Astrophysics Data System (ADS)
Wang, Xin; Gu, Rentao; Ji, Yuefeng; Kavehrad, Mohsen
2017-03-01
As a variety of services have emerged, hybrid services have become more common in real optical networks. Although the elastic spectrum resource optimizations over the elastic optical networks (EONs) have been widely investigated, little research has been carried out on the hybrid services of the routing and spectrum allocation (RSA), especially over the network coding-enabled EON. We investigated the RSA for the unicast service and network coding-based multicast service over the network coding-enabled EON with the constraints of time delay and transmission distance. To address this issue, a mathematical model was built to minimize the total spectrum consumption for the hybrid services over the network coding-enabled EON under the constraints of time delay and transmission distance. The model guarantees different routing constraints for different types of services. The immediate nodes over the network coding-enabled EON are assumed to be capable of encoding the flows for different kinds of information. We proposed an efficient heuristic algorithm of the network coding-based adaptive routing and layered graph-based spectrum allocation algorithm (NCAR-LGSA). From the simulation results, NCAR-LGSA shows highly efficient performances in terms of the spectrum resources utilization under different network scenarios compared with the benchmark algorithms.
2011-09-06
Presentation Outline A) Review of Soil Model governing equations B) Development of pedo -transfer functions (terrain database to engineering properties) C...lateral earth pressure) UNCLASSIFIED B) Development of pedo -transfer functions Engineering parameters needed by soil model - compression index - rebound...inches, RCI for fine- grained soils, CI for coarse-grained soils. UNCLASSIFIED Pedo -transfer function • Need to transfer existing terrain database
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pan, Wenxiao; Fedosov, Dmitry A.; Caswell, Bruce
In this work we compare the predictive capability of two mathematical models for red blood cells (RBCs) focusing on blood flow in capillaries and arterioles. Both RBC models as well as their corresponding blood flows are based on the dissipative particle dynamics (DPD) method, a coarse-grained molecular dynamics approach. The first model employs a multiscale description of the RBC (MS-RBC), with its membrane represented by hundreds or even thousands of DPD-particles connected by springs into a triangular network in combination with out-of-plane elastic bending resistance. Extra dissipation within the network accounts for membrane viscosity, while the characteristic biconcave RBC shapemore » is achieved by imposition of constraints for constant membrane area and constant cell volume. The second model is based on a low-dimensional description (LD-RBC) constructed as a closed torus-like ring of only 10 large DPD colloidal particles. They are connected into a ring by worm-like chain (WLC) springs combined with bending resistance. The LD-RBC model can be fitted to represent the entire range of nonlinear elastic deformations as measured by optical-tweezers for healthy and for infected RBCs in malaria. MS-RBCs suspensions model the dynamics and rheology of blood flow accurately for any size vessel but this approach is computationally expensive above 100 microns. Surprisingly, the much more economical suspensions of LD-RBCs also capture the blood flow dynamics and rheology accurately except for vessels with sizes comparable to RBC diameter. In particular, the LD-RBC suspensions are shown to properly capture the experimental data for the apparent viscosity of blood and its cell-free layer (CFL) in tube flow. Taken together, these findings suggest a hierarchical approach in modeling blood flow in the arterial tree, whereby the MS-RBC model should be employed for capillaries and arterioles below 100 microns, the LD-RBC model for arterioles, and the continuum description for arteries.« less
Simulation of the mechanical behavior of random fiber networks with different microstructure.
Hatami-Marbini, H
2018-05-24
Filamentous protein networks are broadly encountered in biological systems such as cytoskeleton and extracellular matrix. Many numerical studies have been conducted to better understand the fundamental mechanisms behind the striking mechanical properties of these networks. In most of these previous numerical models, the Mikado algorithm has been used to represent the network microstructure. Here, a different algorithm is used to create random fiber networks in order to investigate possible roles of architecture on the elastic behavior of filamentous networks. In particular, random fibrous structures are generated from the growth of individual fibers from random nucleation points. We use computer simulations to determine the mechanical behavior of these networks in terms of their model parameters. The findings are presented and discussed along with the response of Mikado fiber networks. We demonstrate that these alternative networks and Mikado networks show a qualitatively similar response. Nevertheless, the overall elasticity of Mikado networks is stiffer compared to that of the networks created using the alternative algorithm. We describe the effective elasticity of both network types as a function of their line density and of the material properties of the filaments. We also characterize the ratio of bending and axial energy and discuss the behavior of these networks in terms of their fiber density distribution and coordination number.
Differentiated optical services: a quality of optical service model for WDM networks
NASA Astrophysics Data System (ADS)
Ndousse, Thomas D.; Golmie, Nada
1999-08-01
This paper addresses the issues of guaranteed and scalable end-to-end QoS in Metropolitan DWDM networks serving as transit networks for IP access networks. DWDM offering few wavelengths have in the past been deployed in backbone networks to upgrade point-to-point transmission where sharing is based on coarse granularity. This type of DWDM backbone networks, offering few lightpaths, provides no support for QoS services traversing the network. As DWDM networks with larger numbers of wavelengths penetrate the data-centric Metro environment, specific IP service requirements such as priority restoration, scalability, dynamic provisioning of capacity and routes, and support for coarse-grain QoS capabilities will have to be addressed in the optical domain in order to support end-to-end Service- Level Agreements. In this paper, we focus on the support of QoS in the optical domain in order to achieve end-to-end QoS over a DWDM network. We propose a QoS service model in the optical domain called Differentiated Optical Services (DOS). Service classification in DOS is based on a set of optical parameters that captures the quality and reliability of the optical lightpath.
NASA Astrophysics Data System (ADS)
Orlandi, Javier G.; Casademunt, Jaume
2017-05-01
We introduce a coarse-grained stochastic model for the spontaneous activity of neuronal cultures to explain the phenomenon of noise focusing, which entails localization of the noise activity in excitable networks with metric correlations. The system is modeled as a continuum excitable medium with a state-dependent spatial coupling that accounts for the dynamics of synaptic connections. The most salient feature is the emergence at the mesoscale of a vector field V (r ) , which acts as an advective carrier of the noise. This entails an explicit symmetry breaking of isotropy and homogeneity that stems from the amplification of the quenched fluctuations of the network by the activity avalanches, concomitant with the excitable dynamics. We discuss the microscopic interpretation of V (r ) and propose an explicit construction of it. The coarse-grained model shows excellent agreement with simulations at the network level. The generic nature of the observed phenomena is discussed.
Elasticity in Physically Cross-Linked Amyloid Fibril Networks.
Cao, Yiping; Bolisetty, Sreenath; Adamcik, Jozef; Mezzenga, Raffaele
2018-04-13
We provide a constitutive model of semiflexible and rigid amyloid fibril networks by combining the affine thermal model of network elasticity with the Derjaguin-Landau-Vervey-Overbeek (DLVO) theory of electrostatically charged colloids. When compared to rheological experiments on β-lactoglobulin and lysozyme amyloid networks, this approach provides the correct scaling of elasticity versus both concentration (G∼c^{2.2} and G∼c^{2.5} for semiflexible and rigid fibrils, respectively) and ionic strength (G∼I^{4.4} and G∼I^{3.8} for β-lactoglobulin and lysozyme, independent from fibril flexibility). The pivotal role played by the screening salt is to reduce the electrostatic barrier among amyloid fibrils, converting labile physical entanglements into long-lived cross-links. This gives a power-law behavior of G with I having exponents significantly larger than in other semiflexible polymer networks (e.g., actin) and carrying DLVO traits specific to the individual amyloid fibrils.
Elasticity in Physically Cross-Linked Amyloid Fibril Networks
NASA Astrophysics Data System (ADS)
Cao, Yiping; Bolisetty, Sreenath; Adamcik, Jozef; Mezzenga, Raffaele
2018-04-01
We provide a constitutive model of semiflexible and rigid amyloid fibril networks by combining the affine thermal model of network elasticity with the Derjaguin-Landau-Vervey-Overbeek (DLVO) theory of electrostatically charged colloids. When compared to rheological experiments on β -lactoglobulin and lysozyme amyloid networks, this approach provides the correct scaling of elasticity versus both concentration (G ˜c2.2 and G ˜c2.5 for semiflexible and rigid fibrils, respectively) and ionic strength (G ˜I4.4 and G ˜I3.8 for β -lactoglobulin and lysozyme, independent from fibril flexibility). The pivotal role played by the screening salt is to reduce the electrostatic barrier among amyloid fibrils, converting labile physical entanglements into long-lived cross-links. This gives a power-law behavior of G with I having exponents significantly larger than in other semiflexible polymer networks (e.g., actin) and carrying DLVO traits specific to the individual amyloid fibrils.
Design and deployment of an elastic network test-bed in IHEP data center based on SDN
NASA Astrophysics Data System (ADS)
Zeng, Shan; Qi, Fazhi; Chen, Gang
2017-10-01
High energy physics experiments produce huge amounts of raw data, while because of the sharing characteristics of the network resources, there is no guarantee of the available bandwidth for each experiment which may cause link congestion problems. On the other side, with the development of cloud computing technologies, IHEP have established a cloud platform based on OpenStack which can ensure the flexibility of the computing and storage resources, and more and more computing applications have been deployed on virtual machines established by OpenStack. However, under the traditional network architecture, network capability can’t be required elastically, which becomes the bottleneck of restricting the flexible application of cloud computing. In order to solve the above problems, we propose an elastic cloud data center network architecture based on SDN, and we also design a high performance controller cluster based on OpenDaylight. In the end, we present our current test results.
NASA Astrophysics Data System (ADS)
Gardel, M. L.; Nakamura, F.; Hartwig, J. H.; Crocker, J. C.; Stossel, T. P.; Weitz, D. A.
2006-02-01
We show that actin filaments, shortened to physiological lengths by gelsolin and cross-linked with recombinant human filamins (FLNs), exhibit dynamic elastic properties similar to those reported for live cells. To achieve elasticity values of comparable magnitude to those of cells, the in vitro network must be subjected to external prestress, which directly controls network elasticity. A molecular requirement for the strain-related behavior at physiological conditionsis a flexible hinge found in FLNa and some FLNb molecules. Basic physical properties of the in vitro filamin-F-actin network replicate the essential mechanical properties of living cells. This physical behavior could accommodate passive deformation and internal organelle trafficking at low strains yet resist externally or internally generated high shear forces. cytoskeleton | cell mechanics | nonlinear rheology
Experimental Investigation on Damping Property of Coarse Aggregate Replaced Rubber Concrete
NASA Astrophysics Data System (ADS)
Sugapriya, P.; Ramkrishnan, R.; Keerthana, G.; Saravanamurugan, S.
2018-02-01
Rubber has good damping and vibrational characteristics and can reduce cracking significantly due to its elastic nature. This property of rubber can be incorporated in concrete to control vibrations and create better pavements. Crumb Rubber on being dumped in landfills has serious repercussions and causes soil and land pollution. An innovative use of waste tires is shredding them into small pieces and using them as a replacement for coarse aggregate. Crumb rubber is obtained by chopping scrap tires, and in this study it was added in two different sets named SET 1 - Treated Crumb Rubber and concrete, and SET 2 - Treated Crumb rubber with Ultra Fine GGBS as admixture in concrete. Coarse aggregate replaces Rubber in each of the 2 SET’s in proportions of 5, 10, 15 and 20%. Properties like Compressive Strength, Young’s Modulus, Direct and Semi direct Ultrasonic Pulse Velocity, Sorptivity, Damping ratio and Frequency were found out. Deformation and mode shape were studied with modal analysis and static analysis by applying a uniform pressure corresponding to the highest compressive strength of the slab, using ANSYS.
NASA Astrophysics Data System (ADS)
Pfeiffer, Andrew; Wohl, Ellen
2018-01-01
We used 48 reach-scale measurements of large wood and wood-associated sediment and coarse particulate organic matter (CPOM) storage within an 80 km2 catchment to examine spatial patterns of storage relative to stream order. Wood, sediment, and CPOM are not distributed uniformly across the drainage basin. Third- and fourth-order streams (23% of total stream length) disproportionately store wood and coarse and fine sediments: 55% of total wood volume, 78% of coarse sediment, and 49% of fine sediment, respectively. Fourth-order streams store 0.8 m3 of coarse sediment and 0.2 m3 of fine sediment per cubic meter of wood. CPOM storage is highest in first-order streams (60% of storage in 47% of total network stream length). First-order streams can store up to 0.3 m3 of CPOM for each cubic meter of wood. Logjams in third- and fourth-order reaches are primary sediment storage agents, whereas roots in small streams may be more important for storage of CPOM. We propose the large wood particulate storage index to quantify average volume of sediment or CPOM stored by a cubic meter of wood.
A collagen and elastic network in the wing of the bat.
Holbrook, K A; Odland, G F
1978-05-01
Bundles of collagen fibrils, elastic fibres and fibroblasts are organized into a network that lies in the plane of a large portion of the bat wing. By ultrastructural (TEM and SEM) and biochemical analyses it was found that individual bundles of the net are similar to elastic ligaments. Although elastic fibres predominate, they are integrated and aligned in parallel with small bundles of collagen. A reticulum of fibroblasts, joined by focal junctions, forms a cellular framework throughout each bundle. Because of the unique features of the fibre bundles of the bat's wing, in particular their accessibility, and the parallel alignment of the collagen fibrils and elastic fibres in each easily isolatable fibre bundle, they should prove a most valuable model for connective tissue studies, particularly for the study of collagen-elastin interactions.
Burns, K C; Zotz, G
2010-02-01
Epiphytes are an important component of many forested ecosystems, yet our understanding of epiphyte communities lags far behind that of terrestrial-based plant communities. This discrepancy is exacerbated by the lack of a theoretical context to assess patterns in epiphyte community structure. We attempt to fill this gap by developing an analytical framework to investigate epiphyte assemblages, which we then apply to a data set on epiphyte distributions in a Panamanian rain forest. On a coarse scale, interactions between epiphyte species and host tree species can be viewed as bipartite networks, similar to pollination and seed dispersal networks. On a finer scale, epiphyte communities on individual host trees can be viewed as meta-communities, or suites of local epiphyte communities connected by dispersal. Similar analytical tools are typically employed to investigate species interaction networks and meta-communities, thus providing a unified analytical framework to investigate coarse-scale (network) and fine-scale (meta-community) patterns in epiphyte distributions. Coarse-scale analysis of the Panamanian data set showed that most epiphyte species interacted with fewer host species than expected by chance. Fine-scale analyses showed that epiphyte species richness on individual trees was lower than null model expectations. Therefore, epiphyte distributions were clumped at both scales, perhaps as a result of dispersal limitations. Scale-dependent patterns in epiphyte species composition were observed. Epiphyte-host networks showed evidence of negative co-occurrence patterns, which could arise from adaptations among epiphyte species to avoid competition for host species, while most epiphyte meta-communities were distributed at random. Application of our "meta-network" analytical framework in other locales may help to identify general patterns in the structure of epiphyte assemblages and their variation in space and time.
Computational Study of Uniaxial Deformations in Silica Aerogel Using a Coarse-Grained Model.
Ferreiro-Rangel, Carlos A; Gelb, Lev D
2015-07-09
Simulations of a flexible coarse-grained model are used to study silica aerogels. This model, introduced in a previous study (J. Phys. Chem. C 2007, 111, 15792), consists of spherical particles which interact through weak nonbonded forces and strong interparticle bonds that may form and break during the simulations. Small-deformation simulations are used to determine the elastic moduli of a wide range of material models, and large-deformation simulations are used to probe structural evolution and plastic deformation. Uniaxial deformation at constant transverse pressure is simulated using two methods: a hybrid Monte Carlo approach combining molecular dynamics for the motion of individual particles and stochastic moves for transverse stress equilibration, and isothermal molecular dynamics simulations at fixed Poisson ratio. Reasonable agreement on elastic moduli is obtained except at very low densities. The model aerogels exhibit Poisson ratios between 0.17 and 0.24, with higher-density gels clustered around 0.20, and Young's moduli that vary with aerogel density according to a power-law dependence with an exponent near 3.0. These results are in agreement with reported experimental values. The models are shown to satisfy the expected homogeneous isotropic linear-elastic relationship between bulk and Young's moduli at higher densities, but there are systematic deviations at the lowest densities. Simulations of large compressive and tensile strains indicate that these materials display a ductile-to-brittle transition as the density is increased, and that the tensile strength varies with density according to a power law, with an exponent in reasonable agreement with experiment. Auxetic behavior is observed at large tensile strains in some models. Finally, at maximum tensile stress very few broken bonds are found in the materials, in accord with the theory that only a small fraction of the material structure is actually load-bearing.
Modeling the elastic energy of alloys: Potential pitfalls of continuum treatments.
Baskaran, Arvind; Ratsch, Christian; Smereka, Peter
2015-12-01
Some issues that arise when modeling elastic energy for binary alloys are discussed within the context of a Keating model and density-functional calculations. The Keating model is a simplified atomistic formulation based on modeling elastic interactions of a binary alloy with harmonic springs whose equilibrium length is species dependent. It is demonstrated that the continuum limit for the strain field are the usual equations of linear elasticity for alloys and that they correctly capture the coarse-grained behavior of the displacement field. In addition, it is established that Euler-Lagrange equation of the continuum limit of the elastic energy will yield the same strain field equation. This is the same energy functional that is often used to model elastic effects in binary alloys. However, a direct calculation of the elastic energy atomistic model reveals that the continuum expression for the elastic energy is both qualitatively and quantitatively incorrect. This is because it does not take atomistic scale compositional nonuniformity into account. Importantly, this result also shows that finely mixed alloys tend to have more elastic energy than segregated systems, which is the exact opposite of predictions made by some continuum theories. It is also shown that for strained thin films the traditionally used effective misfit for alloys systematically underestimate the strain energy. In some models, this drawback is handled by including an elastic contribution to the enthalpy of mixing, which is characterized in terms of the continuum concentration. The direct calculation of the atomistic model reveals that this approach suffers serious difficulties. It is demonstrated that elastic contribution to the enthalpy of mixing is nonisotropic and scale dependent. It is also shown that such effects are present in density-functional theory calculations for the Si-Ge system. This work demonstrates that it is critical to include the microscopic arrangements in any elastic model to achieve even qualitatively correct behavior.
Variable-free exploration of stochastic models: a gene regulatory network example.
Erban, Radek; Frewen, Thomas A; Wang, Xiao; Elston, Timothy C; Coifman, Ronald; Nadler, Boaz; Kevrekidis, Ioannis G
2007-04-21
Finding coarse-grained, low-dimensional descriptions is an important task in the analysis of complex, stochastic models of gene regulatory networks. This task involves (a) identifying observables that best describe the state of these complex systems and (b) characterizing the dynamics of the observables. In a previous paper [R. Erban et al., J. Chem. Phys. 124, 084106 (2006)] the authors assumed that good observables were known a priori, and presented an equation-free approach to approximate coarse-grained quantities (i.e., effective drift and diffusion coefficients) that characterize the long-time behavior of the observables. Here we use diffusion maps [R. Coifman et al., Proc. Natl. Acad. Sci. U.S.A. 102, 7426 (2005)] to extract appropriate observables ("reduction coordinates") in an automated fashion; these involve the leading eigenvectors of a weighted Laplacian on a graph constructed from network simulation data. We present lifting and restriction procedures for translating between physical variables and these data-based observables. These procedures allow us to perform equation-free, coarse-grained computations characterizing the long-term dynamics through the design and processing of short bursts of stochastic simulation initialized at appropriate values of the data-based observables.
Modeling the mechanical properties of DNA nanostructures.
Arbona, Jean Michel; Aimé, Jean-Pierre; Elezgaray, Juan
2012-11-01
We discuss generalizations of a previously published coarse-grained description [Mergell et al., Phys. Rev. E 68, 021911 (2003)] of double stranded DNA (dsDNA). The model is defined at the base-pair level and includes the electrostatic repulsion between neighbor helices. We show that the model reproduces mechanical and elastic properties of several DNA nanostructures (DNA origamis). We also show that electrostatic interactions are necessary to reproduce atomic force microscopy measurements on planar DNA origamis.
2014-07-01
of models for variable conditions: – Use implicit models to eliminate constraint of sequence of fast time scales: c, ve, – Price to pay: lack...collisions: – Elastic – Bragiinski terms – Inelastic – warning! Rates depend on both T and relative velocity – Multi-fluid CR model from...merge/split for particle management, efficient sampling, inelastic collisions … – Level grouping schemes of electronic states, for dynamical coarse
Effects of elasticity and geometry on the locomotion of a model bacterium
NASA Astrophysics Data System (ADS)
Nguyen, Frank; Graham, Michael
2017-11-01
The locomotion of flagellated bacteria in viscous fluid provides the blueprint for a number of micro-scale engineering applications. The elasticities of both the hook protein (connecting cell body and flagellum) and the flagella themselves play a key role in determining the stability of locomotion. We use a coarse-grained discretization of elastic flagella connected to a rigid cell body to examine trajectories and flow fields for free swimmers. We indeed find that hook and/or flagellar buckling occurs above a critical flexibility relative to the swimmer's torque input. This renders straight swimming ineffective, though not necessarily undesirable in practice. Simulations with multiple flagella show bundling may partially stabilize the buckling effect. For a single flagellum or single bundle, we define a parameter space of characteristic angles tracking the overall time-averaged shape of the swimmer while also delineating stability boundaries between different modes of buckling. Ultimately our results may provide insight on how swimmers move through complex environments and how to design microrobotic swimmers for specific applications. NHS, GERS.
Refined elasticity sampling for Monte Carlo-based identification of stabilizing network patterns.
Childs, Dorothee; Grimbs, Sergio; Selbig, Joachim
2015-06-15
Structural kinetic modelling (SKM) is a framework to analyse whether a metabolic steady state remains stable under perturbation, without requiring detailed knowledge about individual rate equations. It provides a representation of the system's Jacobian matrix that depends solely on the network structure, steady state measurements, and the elasticities at the steady state. For a measured steady state, stability criteria can be derived by generating a large number of SKMs with randomly sampled elasticities and evaluating the resulting Jacobian matrices. The elasticity space can be analysed statistically in order to detect network positions that contribute significantly to the perturbation response. Here, we extend this approach by examining the kinetic feasibility of the elasticity combinations created during Monte Carlo sampling. Using a set of small example systems, we show that the majority of sampled SKMs would yield negative kinetic parameters if they were translated back into kinetic models. To overcome this problem, a simple criterion is formulated that mitigates such infeasible models. After evaluating the small example pathways, the methodology was used to study two steady states of the neuronal TCA cycle and the intrinsic mechanisms responsible for their stability or instability. The findings of the statistical elasticity analysis confirm that several elasticities are jointly coordinated to control stability and that the main source for potential instabilities are mutations in the enzyme alpha-ketoglutarate dehydrogenase. © The Author 2015. Published by Oxford University Press.
Final Report, DE-FG01-06ER25718 Domain Decomposition and Parallel Computing
DOE Office of Scientific and Technical Information (OSTI.GOV)
Widlund, Olof B.
2015-06-09
The goal of this project is to develop and improve domain decomposition algorithms for a variety of partial differential equations such as those of linear elasticity and electro-magnetics.These iterative methods are designed for massively parallel computing systems and allow the fast solution of the very large systems of algebraic equations that arise in large scale and complicated simulations. A special emphasis is placed on problems arising from Maxwell's equation. The approximate solvers, the preconditioners, are combined with the conjugate gradient method and must always include a solver of a coarse model in order to have a performance which is independentmore » of the number of processors used in the computer simulation. A recent development allows for an adaptive construction of this coarse component of the preconditioner.« less
Emergent space-time via a geometric renormalization method
NASA Astrophysics Data System (ADS)
Rastgoo, Saeed; Requardt, Manfred
2016-12-01
We present a purely geometric renormalization scheme for metric spaces (including uncolored graphs), which consists of a coarse graining and a rescaling operation on such spaces. The coarse graining is based on the concept of quasi-isometry, which yields a sequence of discrete coarse grained spaces each having a continuum limit under the rescaling operation. We provide criteria under which such sequences do converge within a superspace of metric spaces, or may constitute the basin of attraction of a common continuum limit, which hopefully may represent our space-time continuum. We discuss some of the properties of these coarse grained spaces as well as their continuum limits, such as scale invariance and metric similarity, and show that different layers of space-time can carry different distance functions while being homeomorphic. Important tools in this analysis are the Gromov-Hausdorff distance functional for general metric spaces and the growth degree of graphs or networks. The whole construction is in the spirit of the Wilsonian renormalization group (RG). Furthermore, we introduce a physically relevant notion of dimension on the spaces of interest in our analysis, which, e.g., for regular lattices reduces to the ordinary lattice dimension. We show that this dimension is stable under the proposed coarse graining procedure as long as the latter is sufficiently local, i.e., quasi-isometric, and discuss the conditions under which this dimension is an integer. We comment on the possibility that the limit space may turn out to be fractal in case the dimension is noninteger. At the end of the paper we briefly mention the possibility that our network carries a translocal far order that leads to the concept of wormhole spaces and a scale dependent dimension if the coarse graining procedure is no longer local.
Muddy marine sediments are gels
NASA Astrophysics Data System (ADS)
Dorgan, K. M.; Clemo, W. C.; Barry, M. A.; Johnson, B.
2016-02-01
Marine sediments cover 70% of the earth's surface, are important sites of carbon burial and nutrient regeneration, and provide habitat for diverse and abundant infaunal communities. The majority of these sediments are muds, in which bioturbation affects sediment structure and geochemical gradients. How infaunal activites result in particle mixing depends on the mechanical properties of muddy sediments. At the scale of burrowing animals, muds are elastic solids. Animals move through these elastic muds by extending crack-shaped burrows by fracture. The underlying mechanism driving this elasticity, however, has not been explicitly illustrated. Here, we test the hypothesis that the elastic behavior of muddy sediments is disrupted by removal of organic material by measuring fracture toughness and stiffness of manipulated and control sediments. Our results indicate that the mechanical responses of sediments to forces are governed by the muco-polymeric matrix of organic material. Similar effects of organic material oxidation were not observed in sands, indicating a clear mechanical distinction between fine- and coarse-grained sediments. Muddy sediments are gels, not fluids or granular materials, and models of how sediments respond to forces imposed by, e.g., organisms, gases, and ambient water should explicitly consider the role of organic material.
A symplectic integration method for elastic filaments
NASA Astrophysics Data System (ADS)
Ladd, Tony; Misra, Gaurav
2009-03-01
Elastic rods are a ubiquitous coarse-grained model of semi-flexible biopolymers such as DNA, actin, and microtubules. The Worm-Like Chain (WLC) is the standard numerical model for semi-flexible polymers, but it is only a linearized approximation to the dynamics of an elastic rod, valid for small deflections; typically the torsional motion is neglected as well. In the standard finite-difference and finite-element formulations of an elastic rod, the continuum equations of motion are discretized in space and time, but it is then difficult to ensure that the Hamiltonian structure of the exact equations is preserved. Here we discretize the Hamiltonian itself, expressed as a line integral over the contour of the filament. This discrete representation of the continuum filament can then be integrated by one of the explicit symplectic integrators frequently used in molecular dynamics. The model systematically approximates the continuum partial differential equations, but has the same level of computational complexity as molecular dynamics and is constraint free. Numerical tests show that the algorithm is much more stable than a finite-difference formulation and can be used for high aspect ratio filaments, such as actin. We present numerical results for the deterministic and stochastic motion of single filaments.
NASA Astrophysics Data System (ADS)
Karimi-Fard, M.; Durlofsky, L. J.
2016-10-01
A comprehensive framework for modeling flow in porous media containing thin, discrete features, which could be high-permeability fractures or low-permeability deformation bands, is presented. The key steps of the methodology are mesh generation, fine-grid discretization, upscaling, and coarse-grid discretization. Our specialized gridding technique combines a set of intersecting triangulated surfaces by constructing approximate intersections using existing edges. This procedure creates a conforming mesh of all surfaces, which defines the internal boundaries for the volumetric mesh. The flow equations are discretized on this conforming fine mesh using an optimized two-point flux finite-volume approximation. The resulting discrete model is represented by a list of control-volumes with associated positions and pore-volumes, and a list of cell-to-cell connections with associated transmissibilities. Coarse models are then constructed by the aggregation of fine-grid cells, and the transmissibilities between adjacent coarse cells are obtained using flow-based upscaling procedures. Through appropriate computation of fracture-matrix transmissibilities, a dual-continuum representation is obtained on the coarse scale in regions with connected fracture networks. The fine and coarse discrete models generated within the framework are compatible with any connectivity-based simulator. The applicability of the methodology is illustrated for several two- and three-dimensional examples. In particular, we consider gas production from naturally fractured low-permeability formations, and transport through complex fracture networks. In all cases, highly accurate solutions are obtained with significant model reduction.
Inferring phenomenological models of Markov processes from data
NASA Astrophysics Data System (ADS)
Rivera, Catalina; Nemenman, Ilya
Microscopically accurate modeling of stochastic dynamics of biochemical networks is hard due to the extremely high dimensionality of the state space of such networks. Here we propose an algorithm for inference of phenomenological, coarse-grained models of Markov processes describing the network dynamics directly from data, without the intermediate step of microscopically accurate modeling. The approach relies on the linear nature of the Chemical Master Equation and uses Bayesian Model Selection for identification of parsimonious models that fit the data. When applied to synthetic data from the Kinetic Proofreading process (KPR), a common mechanism used by cells for increasing specificity of molecular assembly, the algorithm successfully uncovers the known coarse-grained description of the process. This phenomenological description has been notice previously, but this time it is derived in an automated manner by the algorithm. James S. McDonnell Foundation Grant No. 220020321.
NASA Astrophysics Data System (ADS)
Xin, Meiting; Li, Bing; Yan, Xiao; Chen, Lei; Wei, Xiang
2018-02-01
A robust coarse-to-fine registration method based on the backpropagation (BP) neural network and shift window technology is proposed in this study. Specifically, there are three steps: coarse alignment between the model data and measured data, data simplification based on the BP neural network and point reservation in the contour region of point clouds, and fine registration with the reweighted iterative closest point algorithm. In the process of rough alignment, the initial rotation matrix and the translation vector between the two datasets are obtained. After performing subsequent simplification operations, the number of points can be reduced greatly. Therefore, the time and space complexity of the accurate registration can be significantly reduced. The experimental results show that the proposed method improves the computational efficiency without loss of accuracy.
Efficiency gain from elastic optical networks
NASA Astrophysics Data System (ADS)
Morea, Annalisa; Rival, Olivier
2011-12-01
We compare the cost-efficiency of optical networks based on mixed datarates (10, 40, 100Gb/s) and datarateelastic technologies. A European backbone network is examined under various traffic assumptions (volume of transported data per demand and total number of demands) to better understand the impact of traffic characteristics on cost-efficiency. Network dimensioning is performed for static and restorable networks (resilient to one-link failure). In this paper we will investigate the trade-offs between price of interfaces, reach and reconfigurability, showing that elastic solutions can be more cost-efficient than mixed-rate solutions because of the better compatibility between different datarates, increased reach of channels and simplified wavelength allocation.
Coarse-Grain Bandwidth Estimation Techniques for Large-Scale Space Network
NASA Technical Reports Server (NTRS)
Cheung, Kar-Ming; Jennings, Esther
2013-01-01
In this paper, we describe a top-down analysis and simulation approach to size the bandwidths of a store-andforward network for a given network topology, a mission traffic scenario, and a set of data types with different latency requirements. We use these techniques to estimate the wide area network (WAN) bandwidths of the ground links for different architecture options of the proposed Integrated Space Communication and Navigation (SCaN) Network.
Scalable parallel communications
NASA Technical Reports Server (NTRS)
Maly, K.; Khanna, S.; Overstreet, C. M.; Mukkamala, R.; Zubair, M.; Sekhar, Y. S.; Foudriat, E. C.
1992-01-01
Coarse-grain parallelism in networking (that is, the use of multiple protocol processors running replicated software sending over several physical channels) can be used to provide gigabit communications for a single application. Since parallel network performance is highly dependent on real issues such as hardware properties (e.g., memory speeds and cache hit rates), operating system overhead (e.g., interrupt handling), and protocol performance (e.g., effect of timeouts), we have performed detailed simulations studies of both a bus-based multiprocessor workstation node (based on the Sun Galaxy MP multiprocessor) and a distributed-memory parallel computer node (based on the Touchstone DELTA) to evaluate the behavior of coarse-grain parallelism. Our results indicate: (1) coarse-grain parallelism can deliver multiple 100 Mbps with currently available hardware platforms and existing networking protocols (such as Transmission Control Protocol/Internet Protocol (TCP/IP) and parallel Fiber Distributed Data Interface (FDDI) rings); (2) scale-up is near linear in n, the number of protocol processors, and channels (for small n and up to a few hundred Mbps); and (3) since these results are based on existing hardware without specialized devices (except perhaps for some simple modifications of the FDDI boards), this is a low cost solution to providing multiple 100 Mbps on current machines. In addition, from both the performance analysis and the properties of these architectures, we conclude: (1) multiple processors providing identical services and the use of space division multiplexing for the physical channels can provide better reliability than monolithic approaches (it also provides graceful degradation and low-cost load balancing); (2) coarse-grain parallelism supports running several transport protocols in parallel to provide different types of service (for example, one TCP handles small messages for many users, other TCP's running in parallel provide high bandwidth service to a single application); and (3) coarse grain parallelism will be able to incorporate many future improvements from related work (e.g., reduced data movement, fast TCP, fine-grain parallelism) also with near linear speed-ups.
A new model linking elastic properties and ionic conductivity of mixed network former glasses.
Wang, Weimin; Christensen, Randilynn; Curtis, Brittany; Martin, Steve W; Kieffer, John
2018-01-17
Glasses are promising candidate materials for all-solid-state electrolytes for rechargeable batteries due to their outstanding mechanical stability, wide electrochemical stability range, and open structure for potentially high conductivity. Mechanical stiffness and ionic conductivity are two key parameters for solid-state electrolytes. In this study, we investigate two mixed-network former glass systems, sodium borosilicate 0.2Na 2 O + 0.8[xBO 1.5 + (1 - x)SiO 2 ] and sodium borogermanate 0.2Na 2 O + 0.8[xBO 1.5 + (1 - x)GeO 2 ] glasses. With mixed-network formers, the structure of the network changes while the network modifier mole fraction is kept constant, i.e., x = 0.2, which allows us to analyze the effect of the network structure on various properties, including ionic conductivity and elastic properties. Besides the non-linear, non-additive mixed glass former effect, we find that the longitudinal, shear and Young's moduli depend on the combined number density of tetrahedrally and octahedrally coordinated network former elements. These units provide connectivity in three dimensions, which is required for the networks to exhibit restoring forces in response to isotropic and shear deformations. Moreover, the activation energy for modifier cation, Na + , migration is strongly correlated with the bulk modulus, suggesting that the elastic strain energy associated with the passageway dilation for the sodium ions is governed by the bulk modulus of the glass. The detailed analysis provided here gives an estimate for the number of atoms in the vicinity of the migrating cation that are affected by elastic deformation during the activated process. The larger this number and the more compliant the glass network, the lower is the activation energy for the cation jump.
Dynamics Behaviors of Scale-Free Networks with Elastic Demand
NASA Astrophysics Data System (ADS)
Li, Yan-Lai; Sun, Hui-Jun; Wu, Jian-Jun
Many real-world networks, such as transportation networks and Internet, have the scale-free properties. It is important to study the bearing capacity of such networks. Considering the elastic demand condition, we analyze load distributions and bearing capacities with different parameters through artificially created scale-free networks. The simulation results show that the load distribution follows a power-law form, which means some ordered pairs, playing the dominant role in the transportation network, have higher demand than other pairs. We found that, with the decrease of perceptual error, the total and average ordered pair demand will decrease and then stay in a steady state. However, with the increase of the network size, the average demand of each ordered pair will decrease, which is particularly interesting for the network design problem.
Elastic-plastic models for multi-site damage
NASA Technical Reports Server (NTRS)
Actis, Ricardo L.; Szabo, Barna A.
1994-01-01
This paper presents recent developments in advanced analysis methods for the computation of stress site damage. The method of solution is based on the p-version of the finite element method. Its implementation was designed to permit extraction of linear stress intensity factors using a superconvergent extraction method (known as the contour integral method) and evaluation of the J-integral following an elastic-plastic analysis. Coarse meshes are adequate for obtaining accurate results supported by p-convergence data. The elastic-plastic analysis is based on the deformation theory of plasticity and the von Mises yield criterion. The model problem consists of an aluminum plate with six equally spaced holes and a crack emanating from each hole. The cracks are of different sizes. The panel is subjected to a remote tensile load. Experimental results are available for the panel. The plasticity analysis provided the same limit load as the experimentally determined load. The results of elastic-plastic analysis were compared with the results of linear elastic analysis in an effort to evaluate how plastic zone sizes influence the crack growth rates. The onset of net-section yielding was determined also. The results show that crack growth rate is accelerated by the presence of adjacent damage, and the critical crack size is shorter when the effects of plasticity are taken into consideration. This work also addresses the effects of alternative stress-strain laws: The elastic-ideally-plastic material model is compared against the Ramberg-Osgood model.
A model for compression-weakening materials and the elastic fields due to contractile cells
NASA Astrophysics Data System (ADS)
Rosakis, Phoebus; Notbohm, Jacob; Ravichandran, Guruswami
2015-12-01
We construct a homogeneous, nonlinear elastic constitutive law that models aspects of the mechanical behavior of inhomogeneous fibrin networks. Fibers in such networks buckle when in compression. We model this as a loss of stiffness in compression in the stress-strain relations of the homogeneous constitutive model. Problems that model a contracting biological cell in a finite matrix are solved. It is found that matrix displacements and stresses induced by cell contraction decay slower (with distance from the cell) in a compression weakening material than linear elasticity would predict. This points toward a mechanism for long-range cell mechanosensing. In contrast, an expanding cell would induce displacements that decay faster than in a linear elastic matrix.
Piezoresistive Sensor with High Elasticity Based on 3D Hybrid Network of Sponge@CNTs@Ag NPs.
Zhang, Hui; Liu, Nishuang; Shi, Yuling; Liu, Weijie; Yue, Yang; Wang, Siliang; Ma, Yanan; Wen, Li; Li, Luying; Long, Fei; Zou, Zhengguang; Gao, Yihua
2016-08-31
Pressure sensors with high elasticity are in great demand for the realization of intelligent sensing, but there is a need to develope a simple, inexpensive, and scalable method for the manufacture of the sensors. Here, we reported an efficient, simple, facile, and repeatable "dipping and coating" process to manufacture a piezoresistive sensor with high elasticity, based on homogeneous 3D hybrid network of carbon nanotubes@silver nanoparticles (CNTs@Ag NPs) anchored on a skeleton sponge. Highly elastic, sensitive, and wearable sensors are obtained using the porous structure of sponge and the synergy effect of CNTs/Ag NPs. Our sensor was also tested for over 2000 compression-release cycles, exhibiting excellent elasticity and cycling stability. Sensors with high performance and a simple fabrication process are promising devices for commercial production in various electronic devices, for example, sport performance monitoring and man-machine interfaces.
Correlation between elastic and plastic deformations of partially cured epoxy networks
NASA Astrophysics Data System (ADS)
Müller, Michael; Böhm, Robert; Geller, Sirko; Kupfer, Robert; Jäger, Hubert; Gude, Maik
2018-05-01
The thermo-mechanical behavior of polymer matrix materials is strongly dependent on the curing reaction as well as temperature and time. To date, investigations of epoxy resins and their composites mainly focused on the elastic domain because plastic deformation of cross-linked polymer networks was considered as irrelevant or not feasible. This paper presents a novel approach which combines both elastic and plastic domain. Based on an analytical framework describing the storage modulus, analogous parameter combinations are defined in order to reduce complexity when variations in temperature, strain rate and degree of cure are encountered.
Wilczynski, Bartek; Furlong, Eileen E M
2010-04-15
Development is regulated by dynamic patterns of gene expression, which are orchestrated through the action of complex gene regulatory networks (GRNs). Substantial progress has been made in modeling transcriptional regulation in recent years, including qualitative "coarse-grain" models operating at the gene level to very "fine-grain" quantitative models operating at the biophysical "transcription factor-DNA level". Recent advances in genome-wide studies have revealed an enormous increase in the size and complexity or GRNs. Even relatively simple developmental processes can involve hundreds of regulatory molecules, with extensive interconnectivity and cooperative regulation. This leads to an explosion in the number of regulatory functions, effectively impeding Boolean-based qualitative modeling approaches. At the same time, the lack of information on the biophysical properties for the majority of transcription factors within a global network restricts quantitative approaches. In this review, we explore the current challenges in moving from modeling medium scale well-characterized networks to more poorly characterized global networks. We suggest to integrate coarse- and find-grain approaches to model gene regulatory networks in cis. We focus on two very well-studied examples from Drosophila, which likely represent typical developmental regulatory modules across metazoans. Copyright (c) 2009 Elsevier Inc. All rights reserved.
Coarse-Grained Structural Modeling of Molecular Motors Using Multibody Dynamics
Parker, David; Bryant, Zev; Delp, Scott L.
2010-01-01
Experimental and computational approaches are needed to uncover the mechanisms by which molecular motors convert chemical energy into mechanical work. In this article, we describe methods and software to generate structurally realistic models of molecular motor conformations compatible with experimental data from different sources. Coarse-grained models of molecular structures are constructed by combining groups of atoms into a system of rigid bodies connected by joints. Contacts between rigid bodies enforce excluded volume constraints, and spring potentials model system elasticity. This simplified representation allows the conformations of complex molecular motors to be simulated interactively, providing a tool for hypothesis building and quantitative comparisons between models and experiments. In an example calculation, we have used the software to construct atomically detailed models of the myosin V molecular motor bound to its actin track. The software is available at www.simtk.org. PMID:20428469
Analog neural network control method proposed for use in a backup satellite control mode
DOE Office of Scientific and Technical Information (OSTI.GOV)
Frigo, J.R.; Tilden, M.W.
1998-03-01
The authors propose to use an analog neural network controller implemented in hardware, independent of the active control system, for use in a satellite backup control mode. The controller uses coarse sun sensor inputs. The field of view of the sensors activate the neural controller, creating an analog dead band with respect to the direction of the sun on each axis. This network controls the orientation of the vehicle toward the sunlight to ensure adequate power for the system. The attitude of the spacecraft is stabilized with respect to the ambient magnetic field on orbit. This paper develops a modelmore » of the controller using real-time coarse sun sensor data and a dynamic model of a prototype system based on a satellite system. The simulation results and the feasibility of this control method for use in a satellite backup control mode are discussed.« less
The Role of Network Architecture in Collagen Mechanics.
Jansen, Karin A; Licup, Albert J; Sharma, Abhinav; Rens, Robbie; MacKintosh, Fred C; Koenderink, Gijsje H
2018-06-05
Collagen forms fibrous networks that reinforce tissues and provide an extracellular matrix for cells. These networks exhibit remarkable strain-stiffening properties that tailor the mechanical functions of tissues and regulate cell behavior. Recent models explain this nonlinear behavior as an intrinsic feature of disordered networks of stiff fibers. Here, we experimentally validate this theoretical framework by measuring the elastic properties of collagen networks over a wide range of self-assembly conditions. We show that the model allows us to quantitatively relate both the linear and nonlinear elastic behavior of collagen networks to their underlying architecture. Specifically, we identify the local coordination number (or connectivity) 〈z〉 as a key architectural parameter that governs the elastic response of collagen. The network elastic response reveals that 〈z〉 decreases from 3.5 to 3 as the polymerization temperature is raised from 26 to 37°C while being weakly dependent on concentration. We furthermore infer a Young's modulus of 1.1 MPa for the collagen fibrils from the linear modulus. Scanning electron microscopy confirms that 〈z〉 is between three and four but is unable to detect the subtle changes in 〈z〉 with polymerization conditions that rheology is sensitive to. Finally, we show that, consistent with the model, the initial stress-stiffening response of collagen networks is controlled by the negative normal stress that builds up under shear. Our work provides a predictive framework to facilitate future studies of the regulatory effect of extracellular matrix molecules on collagen mechanics. Moreover, our findings can aid mechanobiological studies of wound healing, fibrosis, and cancer metastasis, which require collagen matrices with tunable mechanical properties. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Drainage fracture networks in elastic solids with internal fluid generation
NASA Astrophysics Data System (ADS)
Kobchenko, Maya; Hafver, Andreas; Jettestuen, Espen; Galland, Olivier; Renard, François; Meakin, Paul; Jamtveit, Bjørn; Dysthe, Dag K.
2013-06-01
Experiments in which CO2 gas was generated by the yeast fermentation of sugar in an elastic layer of gelatine gel confined between two glass plates are described and analyzed theoretically. The CO2 gas pressure causes the gel layer to fracture. The gas produced is drained on short length scales by diffusion and on long length scales by flow in a fracture network, which has topological properties that are intermediate between river networks and hierarchical-fracture networks. A simple model for the experimental system with two parameters that characterize the disorder and the intermediate (river-fracture) topology of the network was developed and the results of the model were compared with the experimental results.
Homopolyrotaxanes and Homopolyrotaxane Networks of PEO
NASA Technical Reports Server (NTRS)
Pugh, Coleen; Mattice, Wayne
2005-01-01
In order to identify the optimum size of macrocrown ether for threading, we first investigated the size and shape of simple crown ethers in the melt at 373 K, and their extent of threading with PEO in the melt using coarse-grained Monte Carlo simulations on the 2nnd (second nearest neighbor diamond) lattice, which is a high coordination lattice whose coarse-grained chains can be reverse mapped into fully atomistic models in continuous space.
Modeling of heterogeneous elastic materials by the multiscale hp-adaptive finite element method
NASA Astrophysics Data System (ADS)
Klimczak, Marek; Cecot, Witold
2018-01-01
We present an enhancement of the multiscale finite element method (MsFEM) by combining it with the hp-adaptive FEM. Such a discretization-based homogenization technique is a versatile tool for modeling heterogeneous materials with fast oscillating elasticity coefficients. No assumption on periodicity of the domain is required. In order to avoid direct, so-called overkill mesh computations, a coarse mesh with effective stiffness matrices is used and special shape functions are constructed to account for the local heterogeneities at the micro resolution. The automatic adaptivity (hp-type at the macro resolution and h-type at the micro resolution) increases efficiency of computation. In this paper details of the modified MsFEM are presented and a numerical test performed on a Fichera corner domain is presented in order to validate the proposed approach.
Elastic properties and short-range structural order in mixed network former glasses.
Wang, Weimin; Christensen, Randilynn; Curtis, Brittany; Hynek, David; Keizer, Sydney; Wang, James; Feller, Steve; Martin, Steve W; Kieffer, John
2017-06-21
Elastic properties of alkali containing glasses are of great interest not only because they provide information about overall structural integrity but also they are related to other properties such as thermal conductivity and ion mobility. In this study, we investigate two mixed-network former glass systems, sodium borosilicate 0.2Na 2 O + 0.8[xBO 1.5 + (1 - x)SiO 2 ] and sodium borogermanate 0.2Na 2 O + 0.8[xBO 1.5 + (1 - x)GeO 2 ] glasses. By mixing network formers, the network topology can be changed while keeping the network modifier concentration constant, which allows for the effect of network structure on elastic properties to be analyzed over a wide parametric range. In addition to non-linear, non-additive mixed-glass former effects, maxima are observed in longitudinal, shear and Young's moduli with increasing atomic number density. By combining results from NMR spectroscopy and Brillouin light scattering with a newly developed statistical thermodynamic reaction equilibrium model, it is possible to determine the relative proportions of all network structural units. This new analysis reveals that the structural characteristic predominantly responsible for effective mechanical load transmission in these glasses is a high density of network cations coordinated by four or more bridging oxygens, as it provides for establishing a network of covalent bonds among these cations with connectivity in three dimensions.
NASA Astrophysics Data System (ADS)
Bhatia, Parmeet S.; Reda, Fitsum; Harder, Martin; Zhan, Yiqiang; Zhou, Xiang Sean
2017-02-01
Automatically detecting anatomy orientation is an important task in medical image analysis. Specifically, the ability to automatically detect coarse orientation of structures is useful to minimize the effort of fine/accurate orientation detection algorithms, to initialize non-rigid deformable registration algorithms or to align models to target structures in model-based segmentation algorithms. In this work, we present a deep convolution neural network (DCNN)-based method for fast and robust detection of the coarse structure orientation, i.e., the hemi-sphere where the principal axis of a structure lies. That is, our algorithm predicts whether the principal orientation of a structure is in the northern hemisphere or southern hemisphere, which we will refer to as UP and DOWN, respectively, in the remainder of this manuscript. The only assumption of our method is that the entire structure is located within the scan's field-of-view (FOV). To efficiently solve the problem in 3D space, we formulated it as a multi-planar 2D deep learning problem. In the training stage, a large number coronal-sagittal slice pairs are constructed as 2-channel images to train a DCNN to classify whether a scan is UP or DOWN. During testing, we randomly sample a small number of coronal-sagittal 2-channel images and pass them through our trained network. Finally, coarse structure orientation is determined using majority voting. We tested our method on 114 Elbow MR Scans. Experimental results suggest that only five 2-channel images are sufficient to achieve a high success rate of 97.39%. Our method is also extremely fast and takes approximately 50 milliseconds per 3D MR scan. Our method is insensitive to the location of the structure in the FOV.
NASA Astrophysics Data System (ADS)
Erwin, S. O.; Jacobson, R. B.; Eric, A. B.; Jones, J. C.; Anderson, B. W.
2015-12-01
Perturbations to sediment regimes due to anthropogenic activities may have long lasting effects, especially in systems dominated by coarse sediment where travel times are relatively long. Effectively evaluating management alternatives requires understanding the future trajectory of river response at both the river network and reach scales. The Ozark Plateaus physiographic province is a montane region in the interior US composed primarily of Paleozoic sedimentary rock. Historic land-use practices around the turn of the last century accelerated delivery of coarse sediment to river channels. Effects of this legacy sediment persist in two national parks, Ozark National Scenic Riverways, MO and Buffalo National River, AR, and are of special concern for management of native mussel fauna. These species require stable habitat, yet they occupy inherently dynamic environments: alluvial rivers. At the river-network scale, analysis of historical data reveals the signature of sediment waves moving through river networks in the Ozarks. Channel planform alternates between relatively stable, straight reaches, and wider, multithread reaches which have been more dynamic over the past several decades. These alternate planform configurations route and store sediment differently, and translate into different patterns of bed stability at the reach scale, which in turn affects the distribution and availability of habitat for native biota. Geomorphic mapping and hydrodynamic modeling reveal the complex relations between planform (in)stability, flow dynamics, bed mobility, and aquatic habitat in systems responding to increased sediment supply. Reaches that have a more dynamic planform may provide more hydraulic refugia and habitat heterogeneity compared to stable, homogeneous reaches. This research provides new insights that may inform management of sediment and mussel habitat in rivers subject to coarse legacy sediment.
Stress-enhanced gelation: a dynamic nonlinearity of elasticity.
Yao, Norman Y; Broedersz, Chase P; Depken, Martin; Becker, Daniel J; Pollak, Martin R; Mackintosh, Frederick C; Weitz, David A
2013-01-04
A hallmark of biopolymer networks is their sensitivity to stress, reflected by pronounced nonlinear elastic stiffening. Here, we demonstrate a distinct dynamical nonlinearity in biopolymer networks consisting of filamentous actin cross-linked by α-actinin-4. Applied stress delays the onset of relaxation and flow, markedly enhancing gelation and extending the regime of solidlike behavior to much lower frequencies. We show that this macroscopic network response can be accounted for at the single molecule level by the increased binding affinity of the cross-linker under load, characteristic of catch-bond-like behavior.
Scale transition using dislocation dynamics and the nudged elastic band method
Sobie, Cameron; Capolungo, Laurent; McDowell, David L.; ...
2017-08-01
Microstructural features such as precipitates or irradiation-induced defects impede dislocation motion and directly influence macroscopic mechanical properties such as yield point and ductility. In dislocation-defect interactions both atomic scale and long range elastic interactions are involved. Thermally assisted dislocation bypass of obstacles occurs when thermal fluctuations and driving stresses contribute sufficient energy to overcome the energy barrier. The Nudged Elastic Band (NEB) method is typically used in the context of atomistic simulations to quantify the activation barriers for a given reaction. In this work, the NEB method is generalized to coarse-grain continuum representations of evolving microstructure states beyond the discretemore » particle descriptions of first principles and atomistics. The method we employed enables the calculation of activation energies for a View the MathML source glide dislocation bypassing a [001] self-interstitial atom loop of size in the range of 4-10 nm with a spacing larger than 150nm in α-iron for a range of applied stresses and interaction geometries. This study is complemented by a comparison between atomistic and continuum based prediction of barriers.« less
NASA Astrophysics Data System (ADS)
Roos, Wouter; Gibbons, Melissa; Klug, William; Wuite, Gijs
2009-03-01
We report nanoindentation experiments by atomic force microscopy on capsids of the Hepatitis B Virus (HBV). HBV is investigated because its capsids can form in either a smaller T=3 or a bigger T=4 configuration, making it an ideal system to test the predictive power of continuum elastic theory to describe nanometre-sized objects. It is shown that for small, consecutive indentations the particles behave reversibly linear and no material fatigue occurs. For larger indentations the particles start to deform non-linearly. The experimental force response fits very well with finite element simulations on coarse grained models of HBV capsids. Furthermore, this also fits with thin shell simulations guided by the F"oppl- von K'arm'an (FvK) number (the dimensionless ratio of stretching and bending stiffness of a thin shell). Both the T=3 and T=4 morphology are very well described by the simulations and the capsid material turns out to have the same Young's modulus, as expected. The presented results demonstrate the surprising strength of continuum elastic theory to describe indentation of viral capsids.
NASA Astrophysics Data System (ADS)
Shankar, Chandrashekar
The goal of this research was to gain a fundamental understanding of the properties of networks created by the ring opening metathesis polymerization (ROMP) of dicyclopentadiene (DCPD) used in self-healing materials. To this end we used molecular simulation methods to generate realistic structures of DCPD networks, characterize their structures, and determine their mechanical properties. Density functional theory (DFT) calculations, complemented by structural information derived from molecular dynamics simulations were used to reconstruct experimental Raman spectra and differential scanning calorimetry (DSC) data. We performed coarse-grained simulations comparing networks generated via the ROMP reaction process and compared them to those generated via a RANDOM process, which led to the fundamental realization that the polymer topology has a unique influence on the network properties. We carried out fully atomistic simulations of DCPD using a novel algorithm for recreating ROMP reactions of DCPD molecules. Mechanical properties derived from these atomistic networks are in excellent agreement with those obtained from coarse-grained simulations in which interactions between nodes are subject to angular constraints. This comparison provides self-consistent validation of our simulation results and helps to identify the level of detail necessary for the coarse-grained interaction model. Simulations suggest networks can classified into three stages: fluid-like, rubber-like or glass-like delineated by two thresholds in degree of reaction alpha: The onset of finite magnitudes for the Young's modulus, alphaY, and the departure of the Poisson ration from 0.5, alphaP. In each stage the polymer exhibits a different predominant mechanical response to deformation. At low alpha < alphaY it flows. At alpha Y < alpha < alphaP the response is entropic with no change in internal energy. At alpha > alphaP the response is enthalpic change in internal energy. We developed graph theory-based network characterizations to correlate between network topology and the simulated mechanical properties. (1) Eigenvector centrality (2) Graph fractal dimension, (3) Fiedler partitioning, and (4) Cross-link fraction (Q3+Q4). Of these quantities, the Fiedler partition is the best characteristic for the prediction of Young's Modulus. The new computational tools developed in this research are of great fundamental and practical interest.
Macroscopic and histological investigation of guanaco footpads (Lama guanicoe, Müller 1776).
König, Horst Erich; Skewes, Oscar; Helmreich, Magda; Böck, Peter
2015-03-01
The surface of guanaco footpads is characterized by hairless skin with up to 4-mm-thick stratum corneum that protects from abrasion. The horny layer is pliable and elastic, and ensures firm contact with irregular ground. It is padded with a particular structure of the subcutaneous layer, the digital cushion. The flat cushions of each of the two digits are of elongated ovate shape, each about 45-mm long, up to 20-mm wide, and 8-mm thick. The cushions are lined by a 1-2-mm-thick capsule that resembles a tunica albuginea. The capsule consists of coarse collagen fibers, with elastic fibers absent. The cushion capsule and dermis approach each other, and fuse along a line that runs parallel to the longitudinal axes of cushion and digit. Loose connective tissue rich in elastic fibers and acidic glycosaminoglycans separates dermis and cushion capsule lateral to the narrow interconnecting zone. The cushion capsule encloses cloudy yellowish, gelatinous material. Microscopy shows bundles of elastic fibers in abundant mucinous matrix. Tightly gathered elastic bundles adjoin the inner surface of the capsule. Rough cords of elastic fibers branch out from there and traverse to the opposite side. The cushion is pressed flat, and elastic fibers are stretched when bearing weight. With relief of load, elastic fibers contract and reset the cushion's shape. Contractile cells are absent. A resistant capsule and easily malleable mucinous contents establish the functioning as a gel pad. Mucinous connective tissue between elastic fiber bundles contains abundant basophilic matrix. Hyaluronan, chondroitin sulfate, and dermatan sulfate are main matrix constituents. Spindle-shaped or stellate fibroblasts contain vimentin, S100 protein, and neuron specific enolase. Moprhology, staining characteristics and synthesis activities of these cells meet the criteria to be classified as myxoid cells. The connective tissue in guanaco digital cushions represents myxoid tissue. © 2014 Wiley Periodicals, Inc.
Experimental demonstration of spectrum-sliced elastic optical path network (SLICE).
Kozicki, Bartłomiej; Takara, Hidehiko; Tsukishima, Yukio; Yoshimatsu, Toshihide; Yonenaga, Kazushige; Jinno, Masahiko
2010-10-11
We describe experimental demonstration of spectrum-sliced elastic optical path network (SLICE) architecture. We employ optical orthogonal frequency-division multiplexing (OFDM) modulation format and bandwidth-variable optical cross-connects (OXC) to generate, transmit and receive optical paths with bandwidths of up to 1 Tb/s. We experimentally demonstrate elastic optical path setup and spectrally-efficient transmission of multiple channels with bit rates ranging from 40 to 140 Gb/s between six nodes of a mesh network. We show dynamic bandwidth scalability for optical paths with bit rates of 40 to 440 Gb/s. Moreover, we demonstrate multihop transmission of a 1 Tb/s optical path over 400 km of standard single-mode fiber (SMF). Finally, we investigate the filtering properties and the required guard band width for spectrally-efficient allocation of optical paths in SLICE.
Self-organization in neural networks - Applications in structural optimization
NASA Technical Reports Server (NTRS)
Hajela, Prabhat; Fu, B.; Berke, Laszlo
1993-01-01
The present paper discusses the applicability of ART (Adaptive Resonance Theory) networks, and the Hopfield and Elastic networks, in problems of structural analysis and design. A characteristic of these network architectures is the ability to classify patterns presented as inputs into specific categories. The categories may themselves represent distinct procedural solution strategies. The paper shows how this property can be adapted in the structural analysis and design problem. A second application is the use of Hopfield and Elastic networks in optimization problems. Of particular interest are problems characterized by the presence of discrete and integer design variables. The parallel computing architecture that is typical of neural networks is shown to be effective in such problems. Results of preliminary implementations in structural design problems are also included in the paper.
NASA Astrophysics Data System (ADS)
Zhao, Yongli; Zhang, Jie; Ji, Yuefeng; Li, Hui; Wang, Huitao; Ge, Chao
2015-10-01
The end-to-end tunability is important to provision elastic channel for the burst traffic of data center optical networks. Then, how to complete the end-to-end tunability based on elastic optical networks? Software defined networking (SDN) based end-to-end tunability solution is proposed for software defined data center optical networks, and the protocol extension and implementation procedure are designed accordingly. For the first time, the flexible grid all optical networks with Tbps end-to-end tunable transport and switch system have been online demonstrated for data center interconnection, which are controlled by OpenDayLight (ODL) based controller. The performance of the end-to-end tunable transport and switch system has been evaluated with wavelength number tuning, bit rate tuning, and transmit power tuning procedure.
NASA Astrophysics Data System (ADS)
Xuan, Hejun; Wang, Yuping; Xu, Zhanqi; Hao, Shanshan; Wang, Xiaoli
2017-11-01
Virtualization technology can greatly improve the efficiency of the networks by allowing the virtual optical networks to share the resources of the physical networks. However, it will face some challenges, such as finding the efficient strategies for virtual nodes mapping, virtual links mapping and spectrum assignment. It is even more complex and challenging when the physical elastic optical networks using multi-core fibers. To tackle these challenges, we establish a constrained optimization model to determine the optimal schemes of optical network mapping, core allocation and spectrum assignment. To solve the model efficiently, tailor-made encoding scheme, crossover and mutation operators are designed. Based on these, an efficient genetic algorithm is proposed to obtain the optimal schemes of the virtual nodes mapping, virtual links mapping, core allocation. The simulation experiments are conducted on three widely used networks, and the experimental results show the effectiveness of the proposed model and algorithm.
NASA Technical Reports Server (NTRS)
Wu, H. I.; Spence, R. D.; Sharpe, P. J.; Goeschl, J. D.
1985-01-01
The traditional bulk elastic modulus approach to plant cell pressure-volume relations is inconsistent with its definition. The relationship between the bulk modulus and Young's modulus that forms the basis of their usual application to cell pressure-volume properties is demonstrated to be physically meaningless. The bulk modulus describes stress/strain relations of solid, homogeneous bodies undergoing small deformations, whereas the plant cell is best described as a thin-shelled, fluid-filled structure with a polymer base. Because cell walls possess a polymer structure, an alternative method of mechanical analysis is presented using polymer elasticity principles. This initial study presents the groundwork of polymer mechanics as would be applied to cell walls and discusses how the matrix and microfibrillar network induce nonlinear stress/strain relationships in the cell wall in response to turgor pressure. In subsequent studies, these concepts will be expanded to include anisotropic expansion as regulated by the microfibrillar network.
Actin-mediated bacterial propulsion: comet profile, velocity pulsations.
Benza, V G
2008-05-23
The propulsion of bacteria under the action of an actin gel network is examined in terms of gel concentration dynamics. The model includes the elasticity of the network, the gel-bacterium interaction, the bulk and interface polymerization. A formula for the cruise velocity is obtained where the contributions to bacterial motility arising from elasticity and polymerization are made explicit. Higher velocities correspond to lower concentration peaks and longer tails, in agreement with experimental results. The condition for the onset of motion is explicitly given. The behavior of the system is explored by varying the growth rates and the gel elasticity. At steady state two regimes are found, respectively, of constant and pulsating velocity; in the latter case, the velocity undergoes sudden accelerations and subsequent recoveries. The transition to the pulsating regime is obtained by increasing the elastic response of the gel.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tedesco, L.P.; Wanless, H.R.
Excavation of deep, open burrow networks and subsequent infilling with sediment from the surface produces an entirely new sedimentary deposit and results in obliteration to severe diagenetic transformation of precursor depositional facies. Repetitive excavation and infilling is responsible for creating the preserved depositional facies of many marine deposits. Excavating burrowers occur from intertidal to abyssal depths, and are important throughout the Phanerozoic. The repetitive coupling of deep, open burrow excavation with subsequent storm sediment infilling of open burrow networks is a gradual process that ultimately results in the loss of the original deposit and the generation of new lithologies, fabricsmore » and facies. The new lithologies are produced in the subsurface and possess fabrics, textures and skeletal assemblages that are not a direct reflection of either precursor facies or the surficial depositional conditions. Sedimentary facies generated by repetitive burrow excavation and infilling commonly are massively bedded and generally are mottled skeletal packstones. Skeletal grains usually are well-preserved and coarser components are concentrated in burrow networks, pockets and patches. The coarse skeletal components of burrow-generated facies are a mixture of coarse bioclasts from the precursor facies and both the coarse and fine skeletal material introduced from the sediment surface. Many so-called bioturbated or massive facies may, in fact, be primary depositional facies generated in the subsurface and represent severe diagenetic transformation of originally deposited sequences. In addition, mudstones and wackestones mottled with packstone patches may record storm sedimentation.« less
NASA Astrophysics Data System (ADS)
Kim, S. K.; Lee, J.; Zhang, C.; Ames, S.; Williams, D. N.
2017-12-01
Deep learning techniques have been successfully applied to solve many problems in climate and geoscience using massive-scaled observed and modeled data. For extreme climate event detections, several models based on deep neural networks have been recently proposed and attend superior performance that overshadows all previous handcrafted expert based method. The issue arising, though, is that accurate localization of events requires high quality of climate data. In this work, we propose framework capable of detecting and localizing extreme climate events in very coarse climate data. Our framework is based on two models using deep neural networks, (1) Convolutional Neural Networks (CNNs) to detect and localize extreme climate events, and (2) Pixel recursive recursive super resolution model to reconstruct high resolution climate data from low resolution climate data. Based on our preliminary work, we have presented two CNNs in our framework for different purposes, detection and localization. Our results using CNNs for extreme climate events detection shows that simple neural nets can capture the pattern of extreme climate events with high accuracy from very coarse reanalysis data. However, localization accuracy is relatively low due to the coarse resolution. To resolve this issue, the pixel recursive super resolution model reconstructs the resolution of input of localization CNNs. We present a best networks using pixel recursive super resolution model that synthesizes details of tropical cyclone in ground truth data while enhancing their resolution. Therefore, this approach not only dramat- ically reduces the human effort, but also suggests possibility to reduce computing cost required for downscaling process to increase resolution of data.
Multiscale Multiphysics and Multidomain Models I: Basic Theory
Wei, Guo-Wei
2013-01-01
This work extends our earlier two-domain formulation of a differential geometry based multiscale paradigm into a multidomain theory, which endows us the ability to simultaneously accommodate multiphysical descriptions of aqueous chemical, physical and biological systems, such as fuel cells, solar cells, nanofluidics, ion channels, viruses, RNA polymerases, molecular motors and large macromolecular complexes. The essential idea is to make use of the differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain of solvent from the microscopic domain of solute, and dynamically couple continuum and discrete descriptions. Our main strategy is to construct energy functionals to put on an equal footing of multiphysics, including polar (i.e., electrostatic) solvation, nonpolar solvation, chemical potential, quantum mechanics, fluid mechanics, molecular mechanics, coarse grained dynamics and elastic dynamics. The variational principle is applied to the energy functionals to derive desirable governing equations, such as multidomain Laplace-Beltrami (LB) equations for macromolecular morphologies, multidomain Poisson-Boltzmann (PB) equation or Poisson equation for electrostatic potential, generalized Nernst-Planck (NP) equations for the dynamics of charged solvent species, generalized Navier-Stokes (NS) equation for fluid dynamics, generalized Newton's equations for molecular dynamics (MD) or coarse-grained dynamics and equation of motion for elastic dynamics. Unlike the classical PB equation, our PB equation is an integral-differential equation due to solvent-solute interactions. To illustrate the proposed formalism, we have explicitly constructed three models, a multidomain solvation model, a multidomain charge transport model and a multidomain chemo-electro-fluid-MD-elastic model. Each solute domain is equipped with distinct surface tension, pressure, dielectric function, and charge density distribution. In addition to long-range Coulombic interactions, various non-electrostatic solvent-solute interactions are considered in the present modeling. We demonstrate the consistency between the non-equilibrium charge transport model and the equilibrium solvation model by showing the systematical reduction of the former to the latter at equilibrium. This paper also offers a brief review of the field. PMID:25382892
Multiscale Multiphysics and Multidomain Models I: Basic Theory.
Wei, Guo-Wei
2013-12-01
This work extends our earlier two-domain formulation of a differential geometry based multiscale paradigm into a multidomain theory, which endows us the ability to simultaneously accommodate multiphysical descriptions of aqueous chemical, physical and biological systems, such as fuel cells, solar cells, nanofluidics, ion channels, viruses, RNA polymerases, molecular motors and large macromolecular complexes. The essential idea is to make use of the differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain of solvent from the microscopic domain of solute, and dynamically couple continuum and discrete descriptions. Our main strategy is to construct energy functionals to put on an equal footing of multiphysics, including polar (i.e., electrostatic) solvation, nonpolar solvation, chemical potential, quantum mechanics, fluid mechanics, molecular mechanics, coarse grained dynamics and elastic dynamics. The variational principle is applied to the energy functionals to derive desirable governing equations, such as multidomain Laplace-Beltrami (LB) equations for macromolecular morphologies, multidomain Poisson-Boltzmann (PB) equation or Poisson equation for electrostatic potential, generalized Nernst-Planck (NP) equations for the dynamics of charged solvent species, generalized Navier-Stokes (NS) equation for fluid dynamics, generalized Newton's equations for molecular dynamics (MD) or coarse-grained dynamics and equation of motion for elastic dynamics. Unlike the classical PB equation, our PB equation is an integral-differential equation due to solvent-solute interactions. To illustrate the proposed formalism, we have explicitly constructed three models, a multidomain solvation model, a multidomain charge transport model and a multidomain chemo-electro-fluid-MD-elastic model. Each solute domain is equipped with distinct surface tension, pressure, dielectric function, and charge density distribution. In addition to long-range Coulombic interactions, various non-electrostatic solvent-solute interactions are considered in the present modeling. We demonstrate the consistency between the non-equilibrium charge transport model and the equilibrium solvation model by showing the systematical reduction of the former to the latter at equilibrium. This paper also offers a brief review of the field.
Domain-averaged snow depth over complex terrain from flat field measurements
NASA Astrophysics Data System (ADS)
Helbig, Nora; van Herwijnen, Alec
2017-04-01
Snow depth is an important parameter for a variety of coarse-scale models and applications, such as hydrological forecasting. Since high-resolution snow cover models are computational expensive, simplified snow models are often used. Ground measured snow depth at single stations provide a chance for snow depth data assimilation to improve coarse-scale model forecasts. Snow depth is however commonly recorded at so-called flat fields, often in large measurement networks. While these ground measurement networks provide a wealth of information, various studies questioned the representativity of such flat field snow depth measurements for the surrounding topography. We developed two parameterizations to compute domain-averaged snow depth for coarse model grid cells over complex topography using easy to derive topographic parameters. To derive the two parameterizations we performed a scale dependent analysis for domain sizes ranging from 50m to 3km using highly-resolved snow depth maps at the peak of winter from two distinct climatic regions in Switzerland and in the Spanish Pyrenees. The first, simpler parameterization uses a commonly applied linear lapse rate. For the second parameterization, we first removed the obvious elevation gradient in mean snow depth, which revealed an additional correlation with the subgrid sky view factor. We evaluated domain-averaged snow depth derived with both parameterizations using flat field measurements nearby with the domain-averaged highly-resolved snow depth. This revealed an overall improved performance for the parameterization combining a power law elevation trend scaled with the subgrid parameterized sky view factor. We therefore suggest the parameterization could be used to assimilate flat field snow depth into coarse-scale snow model frameworks in order to improve coarse-scale snow depth estimates over complex topography.
Baek, Jiwon; Hur, Nam Wook; Kim, Hyeon Chang; Youm, Yoosik
2016-07-01
Hypertension is a common chronic disease among older adults, and is associated with medical complications and mortality. This study aimed to examine the effects of social network characteristics on the prevalence, awareness, and control of hypertension among older adults. The Korean Social Life, Health, and Aging Project (KSHAP) interviewed 814 ≥ 60-year-old residents and their spouses from a rural township between December 2011 and March 2012 (response rate: 95%). We evaluated the data from 595 participants. Multivariate logistic regression models were used to assess the effects of network characteristics on hypertension. We observed strong sex-specific network effects on the prevalence, awareness, and control of hypertension. Among older women, network density was associated with hypertension awareness [odds ratio (OR): 2.63, 95% confidence interval (CI): 1.03-5.37] and control (OR: 1.72; 95% CI: 0.94-3.13). Among older men, large networks were associated with a lower prevalence of hypertension (OR: 0.75; 95% CI: 0.58-0.96). Compared to older women, older men with coarse networks exhibited better hypertension awareness (OR: 0.37; 95% CI: 0.14-0.95) and control (OR: 0.42; 95% CI: 0.19-0.91). Network size interacted with density for hypertension control (P = 0.051), with controlled hypertension being associated with large and course networks. A large network was associated with a lower risk for hypertension, and a coarse network was associated with hypertension awareness and control among older men. Older women with dense networks were most likely to exhibit hypertension awareness and control.
Amaya, N; Irfan, M; Zervas, G; Nejabati, R; Simeonidou, D; Sakaguchi, J; Klaus, W; Puttnam, B J; Miyazawa, T; Awaji, Y; Wada, N; Henning, I
2013-04-08
We present the first elastic, space division multiplexing, and multi-granular network based on two 7-core MCF links and four programmable optical nodes able to switch traffic utilising the space, frequency and time dimensions with over 6000-fold bandwidth granularity. Results show good end-to-end performance on all channels with power penalties between 0.75 dB and 3.7 dB.
Model of a Soft Robotic Actuator with Embedded Fluidic Network
NASA Astrophysics Data System (ADS)
Gamus, Benny; Or, Yizhar; Gat, Amir
2017-11-01
Soft robotics is an emerging bio-inspired concept of actuation, with promising applications for robotic locomotion and manipulation. Focusing on actuation by pressurized embedded fluidic networks, we present analytic formulation and closed-form solutions of an elastic actuator with pressurized fluidic networks. In this work we account for the effects of solid inertia and elasticity, as well as fluid viscosity, which allows modelling the system's step-response and frequency response as well as suggesting mode elimination and isolation techniques. We also present and model the application of viscous-peeling as an actuation mechanism, simplifying the fabrication process by eliminating the need for internal cavities. The theoretical results describing the viscous-elastic-inertial dynamics of the actuator are illustrated by experiments. The approach presented in this work may pave the way for the design and implementation of soft robotic legged locomotion that exploits dynamic effects.
Solvent-free, supersoft and superelastic bottlebrush melts and networks
NASA Astrophysics Data System (ADS)
Daniel, William F. M.; Burdyńska, Joanna; Vatankhah-Varnoosfaderani, Mohammad; Matyjaszewski, Krzysztof; Paturej, Jarosław; Rubinstein, Michael; Dobrynin, Andrey V.; Sheiko, Sergei S.
2016-02-01
Polymer gels are the only viable class of synthetic materials with a Young's modulus below 100 kPa conforming to biological applications, yet those gel properties require a solvent fraction. The presence of a solvent can lead to phase separation, evaporation and leakage on deformation, diminishing gel elasticity and eliciting inflammatory responses in any surrounding tissues. Here, we report solvent-free, supersoft and superelastic polymer melts and networks prepared from bottlebrush macromolecules. The brush-like architecture expands the diameter of the polymer chains, diluting their entanglements without markedly increasing stiffness. This adjustable interplay between chain diameter and stiffness makes it possible to tailor the network's elastic modulus and extensibility without the complications associated with a swollen gel. The bottlebrush melts and elastomers exhibit an unprecedented combination of low modulus (~100 Pa), high strain at break (~1,000%), and extraordinary elasticity, properties that are on par with those of designer gels.
Deformable complex network for refining low-resolution X-ray structures
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Chong; Wang, Qinghua; Ma, Jianpeng, E-mail: jpma@bcm.edu
2015-10-27
A new refinement algorithm called the deformable complex network that combines a novel angular network-based restraint with a deformable elastic network model in the target function has been developed to aid in structural refinement in macromolecular X-ray crystallography. In macromolecular X-ray crystallography, building more accurate atomic models based on lower resolution experimental diffraction data remains a great challenge. Previous studies have used a deformable elastic network (DEN) model to aid in low-resolution structural refinement. In this study, the development of a new refinement algorithm called the deformable complex network (DCN) is reported that combines a novel angular network-based restraint withmore » the DEN model in the target function. Testing of DCN on a wide range of low-resolution structures demonstrated that it constantly leads to significantly improved structural models as judged by multiple refinement criteria, thus representing a new effective refinement tool for low-resolution structural determination.« less
Brauchle, Eva; Bauer, Hannah; Fernes, Patrick; Zuk, Alexandra; Schenke-Layland, Katja; Sengle, Gerhard
2017-04-01
Fibrillin microfibrils and elastic fibers are critical determinants of elastic tissues where they define as tissue-specific architectures vital mechanical properties such as pliability and elastic recoil. Fibrillin microfibrils also facilitate elastic fiber formation and support the association of epithelial cells with the interstitial matrix. Mutations in fibrillin-1 (FBN1) are causative for the Marfan syndrome, a congenital multisystem disorder characterized by progressive deterioration of the fibrillin microfibril/ elastic fiber architecture in the cardiovascular, musculoskeletal, ocular, and dermal system. In this study, we utilized Raman microspectroscopy in combination with principal component analysis (PCA) to analyze the molecular consequences of fibrillin-1 deficiency in skin of a mouse model (GT8) of Marfan syndrome. In addition, full-thickness skin models incorporating murine wild-type and Fbn1 GT8/GT8 fibroblasts as well as human HaCaT keratinocytes were generated and analyzed. Skin models containing GT8 fibroblasts showed an altered epidermal morphology when compared to wild-type models indicating a new role for fibrillin-1 in dermal-epidermal crosstalk. Obtained Raman spectra together with PCA allowed to discriminate between healthy and deficient microfibrillar networks in murine dermis and skin models. Interestingly, results obtained from GT8 dermis and skin models showed similar alterations in molecular signatures triggered by fibrillin-1 deficiency such as amide III vibrations and decreased levels of glycan vibrations. Overall, this study indicates that Raman microspectroscopy has the potential to analyze subtle changes in fibrillin-1 microfibrils and elastic fiber networks. Therefore Raman microspectroscopy may be utilized as a non-invasive and sensitive diagnostic tool to identify connective tissue disorders and monitor their disease progression. Mutations in building blocks of the fibrillin microfibril/ elastic fiber network manifest in disease conditions such as aneurysms, emphysema or lax skin. Understanding how structural changes induced by fibrillin-1 mutation impact the architecture of fibrillin microfibrils, which then translates into an altered activation state of targeted growth factors, represents a huge challenge in elucidating the genotype-phenotype correlations in connective tissue disorders such as Marfan syndrome. This study shows that Raman microspectroscopy is able to reveal structural changes in fibrillin-1 microfibrils and elastic fiber networks and to discriminate between normal and diseased networks in vivo and in vitro. Therefore Raman microspectroscopy may be utilized as a non-invasive and sensitive diagnostic tool to identify connective tissue disorders and monitor their disease progression. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Ye, Fei
2018-04-01
With the rapid increase of electric automobiles and charging piles, the elastic expansion and online rapid upgrade were required for the vehicle networking system platform (system platform for short). At present, it is difficult to meet the operation needs due to the traditional huge rock architecture used by the system platform. This paper studied the system platform technology architecture based on "cloud platform +micro-service" to obtain a new generation of vehicle networking system platform with the combination of elastic expansion and application, thus significantly improving the service operation ability of system.
Shape memory polymer network with thermally distinct elasticity and plasticity.
Zhao, Qian; Zou, Weike; Luo, Yingwu; Xie, Tao
2016-01-01
Stimuli-responsive materials with sophisticated yet controllable shape-changing behaviors are highly desirable for real-world device applications. Among various shape-changing materials, the elastic nature of shape memory polymers allows fixation of temporary shapes that can recover on demand, whereas polymers with exchangeable bonds can undergo permanent shape change via plasticity. We integrate the elasticity and plasticity into a single polymer network. Rational molecular design allows these two opposite behaviors to be realized at different temperature ranges without any overlap. By exploring the cumulative nature of the plasticity, we demonstrate easy manipulation of highly complex shapes that is otherwise extremely challenging. The dynamic shape-changing behavior paves a new way for fabricating geometrically complex multifunctional devices.
NASA Astrophysics Data System (ADS)
Wang, Yongfu; Gao, Kaixiong; Wang, Qi; Zhang, Junyan
2018-01-01
Fullerene-like hydrogenated carbon films have outstanding mechanical and frictional properties, but their structures have never enjoyed elaboration. In this study, we investigate the relation between nano-hardness and elasticity and fullerene-like clusters by changing energy supply form (direct current and pulse) and H2 concentration in the feedstock. It is found that the films have a network of H-rich amorphous carbon and H-poor or -deficient fullerene-like carbon, and the network change can affect hardness and elastic recovery. This is due to the energy minimization process of the film growing system in a very short pulse period at low temperature.
Engineering the Mechanical Properties of Polymer Networks with Precise Doping of Primary Defects.
Chan, Doreen; Ding, Yichuan; Dauskardt, Reinhold H; Appel, Eric A
2017-12-06
Polymer networks are extensively utilized across numerous applications ranging from commodity superabsorbent polymers and coatings to high-performance microelectronics and biomaterials. For many applications, desirable properties are known; however, achieving them has been challenging. Additionally, the accurate prediction of elastic modulus has been a long-standing difficulty owing to the presence of loops. By tuning the prepolymer formulation through precise doping of monomers, specific primary network defects can be programmed into an elastomeric scaffold, without alteration of their resulting chemistry. The addition of these monomers that respond mechanically as primary defects is used both to understand their impact on the resulting mechanical properties of the materials and as a method to engineer the mechanical properties. Indeed, these materials exhibit identical bulk and surface chemistry, yet vastly different mechanical properties. Further, we have adapted the real elastic network theory (RENT) to the case of primary defects in the absence of loops, thus providing new insights into the mechanism for material strength and failure in polymer networks arising from primary network defects, and to accurately predict the elastic modulus of the polymer system. The versatility of the approach we describe and the fundamental knowledge gained from this study can lead to new advancements in the development of novel materials with precisely defined and predictable chemical, physical, and mechanical properties.
Yang, Hui; Zhang, Jie; Ji, Yuefeng; Tan, Yuanlong; Lin, Yi; Han, Jianrui; Lee, Young
2015-09-07
Data center interconnection with elastic optical network is a promising scenario to meet the high burstiness and high-bandwidth requirements of data center services. In our previous work, we implemented cross stratum optimization of optical network and application stratums resources that allows to accommodate data center services. In view of this, this study extends the data center resources to user side to enhance the end-to-end quality of service. We propose a novel data center service localization (DCSL) architecture based on virtual resource migration in software defined elastic data center optical network. A migration evaluation scheme (MES) is introduced for DCSL based on the proposed architecture. The DCSL can enhance the responsiveness to the dynamic end-to-end data center demands, and effectively reduce the blocking probability to globally optimize optical network and application resources. The overall feasibility and efficiency of the proposed architecture are experimentally verified on the control plane of our OpenFlow-based enhanced SDN testbed. The performance of MES scheme under heavy traffic load scenario is also quantitatively evaluated based on DCSL architecture in terms of path blocking probability, provisioning latency and resource utilization, compared with other provisioning scheme.
Determination of stores pointing error due to wing flexibility under flight load
NASA Technical Reports Server (NTRS)
Lokos, William A.; Bahm, Catherine M.; Heinle, Robert A.
1995-01-01
The in-flight elastic wing twist of a fighter-type aircraft was studied to provide for an improved on-board real-time computed prediction of pointing variations of three wing store stations. This is an important capability to correct sensor pod alignment variation or to establish initial conditions of iron bombs or smart weapons prior to release. The original algorithm was based upon coarse measurements. The electro-optical Flight Deflection Measurement System measured the deformed wing shape in flight under maneuver loads to provide a higher resolution database from which an improved twist prediction algorithm could be developed. The FDMS produced excellent repeatable data. In addition, a NASTRAN finite-element analysis was performed to provide additional elastic deformation data. The FDMS data combined with the NASTRAN analysis indicated that an improved prediction algorithm could be derived by using a different set of aircraft parameters, namely normal acceleration, stores configuration, Mach number, and gross weight.
Lubricated immersed boundary method in two dimensions
NASA Astrophysics Data System (ADS)
Fai, Thomas G.; Rycroft, Chris H.
2018-03-01
Many biological examples of fluid-structure interaction, including the transit of red blood cells through the narrow slits in the spleen and the intracellular trafficking of vesicles into dendritic spines, involve the near-contact of elastic structures separated by thin layers of fluid. Motivated by such problems, we introduce an immersed boundary method that uses elements of lubrication theory to resolve thin fluid layers between immersed boundaries. We demonstrate 2nd-order accurate convergence for simple two-dimensional flows with known exact solutions to showcase the increased accuracy of this method compared to the standard immersed boundary method. Motivated by the phenomenon of wall-induced migration, we apply the lubricated immersed boundary method to simulate an elastic vesicle near a wall in shear flow. We also simulate the dynamics of a vesicle traveling through a narrow channel and observe the ability of the lubricated method to capture the vesicle motion on relatively coarse fluid grids.
Coarse-grained mechanics of viral shells
NASA Astrophysics Data System (ADS)
Klug, William S.; Gibbons, Melissa M.
2008-03-01
We present an approach for creating three-dimensional finite element models of viral capsids from atomic-level structural data (X-ray or cryo-EM). The models capture heterogeneous geometric features and are used in conjunction with three-dimensional nonlinear continuum elasticity to simulate nanoindentation experiments as performed using atomic force microscopy. The method is extremely flexible; able to capture varying levels of detail in the three-dimensional structure. Nanoindentation simulations are presented for several viruses: Hepatitis B, CCMV, HK97, and φ29. In addition to purely continuum elastic models a multiscale technique is developed that combines finite-element kinematics with MD energetics such that large-scale deformations are facilitated by a reduction in degrees of freedom. Simulations of these capsid deformation experiments provide a testing ground for the techniques, as well as insight into the strength-determining mechanisms of capsid deformation. These methods can be extended as a framework for modeling other proteins and macromolecular structures in cell biology.
A neural network for controlling the configuration of frame structure with elastic members
NASA Technical Reports Server (NTRS)
Tsutsumi, Kazuyoshi
1989-01-01
A neural network for controlling the configuration of frame structure with elastic members is proposed. In the present network, the structure is modeled not by using the relative angles of the members but by using the distances between the joint locations alone. The relationship between the environment and the joints is also defined by their mutual distances. The analog neural network attains the reaching motion of the manipulator as a minimization problem of the energy constructed by the distances between the joints, the target, and the obstacles. The network can generate not only the final but also the transient configurations and the trajectory. This framework with flexibility and parallelism is very suitable for controlling the Space Telerobotic systems with many degrees of freedom.
NASA Astrophysics Data System (ADS)
Abut, Yavuz; Taner Yildirim, Salih
2017-10-01
Using recycled aggregates in the concrete offers advantages in many areas such as waste management, energy save and natural resources, conservation of ecological balance, low CO2 emissions, and users are encouraged in this regard to use these materials. In this study, the profit / loss account arising in the structural design phase was investigated when Reclaimed Asphalt Pavement (RAP), which is limited to use in Roller Compacted Concrete (RCC) pavements, was used as coarse aggregate. RAP materials were used as coarse aggregates by the levels of 0%, 15% and 20% and mechanical properties such as compressive strength, flexural strength, splitting tensile strength and modulus of elasticity were investigated. In the last stage, the mechanical properties obtained from these experimental studies were entered into KENSLABS software as input, and the slab layer thicknesses were determined according to three different subgrade conditions and a certain fatigue criterion. According to the results, it has been determined that the use of RAP at a level of 20% is a serious reducing effect on mechanical properties and and the use of RAP at a level of 15% does not bring a great economic benefit but it is reasonable to use it as coarse aggregate in RCC mixes in consideration of environmental effects.
Lee, Han-Seung; Ismail, Mohamed A.; Woo, Young-Je; Min, Tae-Beom; Choi, Hyun-Kook
2014-01-01
Structural lightweight concrete (SLWC) has superior properties that allow the optimization of super tall structure systems for the process of design. Because of the limited supply of lightweight aggregates in Korea, the development of structural lightweight concrete without lightweight aggregates is needed. The physical and mechanical properties of specimens that were cast using normal coarse aggregates and different mixing ratios of foaming agent to evaluate the possibility of creating structural lightweight concrete were investigated. The results show that the density of SLWC decreases as the dosage of foaming agent increases up to a dosage of 0.6%, as observed by SEM. It was also observed that the foaming agent induced well separated pores, and that the size of the pores ranged from 50 to 100 μm. Based on the porosity of concrete specimens with foaming agent, compressive strength values of structural lightweight foam concrete (SLWFC) were obtained. It was also found that the estimated values from proposed equations for compressive strength and modulus of elasticity of SLWFC, and values obtained by actual measurements were in good agreement. Thus, this study confirms that new structural lightweight concrete using normal coarse aggregates and foaming agent can be developed successfully. PMID:28788691
Coarse cluster enhancing collaborative recommendation for social network systems
NASA Astrophysics Data System (ADS)
Zhao, Yao-Dong; Cai, Shi-Min; Tang, Ming; Shang, Min-Sheng
2017-10-01
Traditional collaborative filtering based recommender systems for social network systems bring very high demands on time complexity due to computing similarities of all pairs of users via resource usages and annotation actions, which thus strongly suppresses recommending speed. In this paper, to overcome this drawback, we propose a novel approach, namely coarse cluster that partitions similar users and associated items at a high speed to enhance user-based collaborative filtering, and then develop a fast collaborative user model for the social tagging systems. The experimental results based on Delicious dataset show that the proposed model is able to dramatically reduce the processing time cost greater than 90 % and relatively improve the accuracy in comparison with the ordinary user-based collaborative filtering, and is robust for the initial parameter. Most importantly, the proposed model can be conveniently extended by introducing more users' information (e.g., profiles) and practically applied for the large-scale social network systems to enhance the recommending speed without accuracy loss.
Printable elastic conductors by in situ formation of silver nanoparticles from silver flakes
NASA Astrophysics Data System (ADS)
Matsuhisa, Naoji; Inoue, Daishi; Zalar, Peter; Jin, Hanbit; Matsuba, Yorishige; Itoh, Akira; Yokota, Tomoyuki; Hashizume, Daisuke; Someya, Takao
2017-08-01
Printable elastic conductors promise large-area stretchable sensor/actuator networks for healthcare, wearables and robotics. Elastomers with metal nanoparticles are one of the best approaches to achieve high performance, but large-area utilization is limited by difficulties in their processability. Here we report a printable elastic conductor containing Ag nanoparticles that are formed in situ, solely by mixing micrometre-sized Ag flakes, fluorine rubbers, and surfactant. Our printable elastic composites exhibit conductivity higher than 4,000 S cm-1 (highest value: 6,168 S cm-1) at 0% strain, and 935 S cm-1 when stretched up to 400%. Ag nanoparticle formation is influenced by the surfactant, heating processes, and elastomer molecular weight, resulting in a drastic improvement of conductivity. Fully printed sensor networks for stretchable robots are demonstrated, sensing pressure and temperature accurately, even when stretched over 250%.
The Effect of Fin Pitch on Fluid Elastic Instability of Tube Arrays Subjected to Cross Flow of Water
NASA Astrophysics Data System (ADS)
Desai, Sandeep Rangrao; Pavitran, Sampat
2018-02-01
Failure of tubes in shell and tube exchangers is attributed to flow induced vibrations of such tubes. There are different excitations mechanisms due to which flow induced vibration occurs and among such mechanisms, fluid elastic instability is the most prominent one as it causes the most violent vibrations and may lead to rapid tube failures within short time. Fluid elastic instability is the fluid-structure interaction phenomenon which occurs when energy input by the fluid force exceeds energy expended in damping. This point is referred as instability threshold and corresponding velocity is referred as critical velocity. Once flow velocity exceeds critical flow velocity, the vibration amplitude increases very rapidly with flow velocity. An experimental program is carried out to determine the critical velocity at instability for plain and finned tube arrays subjected to cross flow of water. The tube array geometry is parallel triangular with cantilever end condition and pitch ratios considered are 2.6 and 2.1. The objective of research is to determine the effect of increase in pitch ratio on instability threshold for plain tube arrays and to assess the effect of addition of fins as well as increase in fin density on instability threshold for finned tube arrays. Plain tube array with two different pitch ratios; 2.1 and 2.6 and finned tube arrays with same pitch ratio; 2.6 but with two different fin pitches; such as fine (10 fpi) and coarse (4 fpi) are considered for the experimentation. Connors' equation that relates critical velocity at instability to different parameters, on which instability depends, has been used as the basis for analysis and the concept of effective diameter is used for the present investigation. The modal parameters are first suitably modified using natural frequency reduction setup that is already designed and developed to reduce natural frequency and hence to achieve experimental simulation of fluid elastic instability within the limited flow capacity of the pump. The tests are carried out first on plain tube arrays to establish the same as the datum case and results are compared to known results of plain tube arrays and hence the quality of the test rig is also assessed. The fluid elastic vibration tests are then carried out on finned tube arrays with coarse and fine fin pitches and effects of fins and fin pitch on instability threshold are shown. The vibration response of the tube is recorded for each gradually increasing flow rates of water till instability point is reached. The parameters at the instability are then presented in terms of dimensionless parameters to compare them with published results. It is concluded that, arrays with higher pitch ratios are unstable at comparatively higher flow velocities and instability threshold for finned tube arrays is delayed due to addition of the fins. Further, it is concluded that, instability threshold for finned tube arrays with fine fin pitch is delayed compared to coarse fin pitch and hence for increased fin density, instability threshold is delayed. The experimental results in terms of critical velocities obtained for different tube arrays subjected to water cross flow will serve as the base flow rates for air-water cross flow experiments to be conducted in the next phase.
Intelligent neural network and fuzzy logic control of industrial and power systems
NASA Astrophysics Data System (ADS)
Kuljaca, Ognjen
The main role played by neural network and fuzzy logic intelligent control algorithms today is to identify and compensate unknown nonlinear system dynamics. There are a number of methods developed, but often the stability analysis of neural network and fuzzy control systems was not provided. This work will meet those problems for the several algorithms. Some more complicated control algorithms included backstepping and adaptive critics will be designed. Nonlinear fuzzy control with nonadaptive fuzzy controllers is also analyzed. An experimental method for determining describing function of SISO fuzzy controller is given. The adaptive neural network tracking controller for an autonomous underwater vehicle is analyzed. A novel stability proof is provided. The implementation of the backstepping neural network controller for the coupled motor drives is described. Analysis and synthesis of adaptive critic neural network control is also provided in the work. Novel tuning laws for the system with action generating neural network and adaptive fuzzy critic are given. Stability proofs are derived for all those control methods. It is shown how these control algorithms and approaches can be used in practical engineering control. Stability proofs are given. Adaptive fuzzy logic control is analyzed. Simulation study is conducted to analyze the behavior of the adaptive fuzzy system on the different environment changes. A novel stability proof for adaptive fuzzy logic systems is given. Also, adaptive elastic fuzzy logic control architecture is described and analyzed. A novel membership function is used for elastic fuzzy logic system. The stability proof is proffered. Adaptive elastic fuzzy logic control is compared with the adaptive nonelastic fuzzy logic control. The work described in this dissertation serves as foundation on which analysis of particular representative industrial systems will be conducted. Also, it gives a good starting point for analysis of learning abilities of adaptive and neural network control systems, as well as for the analysis of the different algorithms such as elastic fuzzy systems.
Greenland GPS network: Measurements and Models of 3D Elastic deformation
NASA Astrophysics Data System (ADS)
Khan, S. A.; van Dam, T. M.; Bevis, M. G.; Sasgen, I.; Bamber, J. L.; Helm, V.; Bjork, A. A.; Liu, L.; Kjaer, K. H.; Knudsen, P.; Kjeldsen, K. K.
2017-12-01
The Greenland GPS Network (GNET) uses the Global Positioning System (GPS) to measure the displacement of bedrock exposed near the margins of the Greenland ice sheet. The entire network is uplifting in response to past and present-day changes in ice mass. Here, we focus on present-day changes and compare measurements with models. To retrieve 3D elastic displacements from GPS time series, we correct our observations for glacial-isostatic adjustment and tectonic plate motion, and study the effect of the underlying mantle viscosity, ice load history and Euler parameters. To model 3D elastic displacements, we first estimate mass loss using 1995-2014 NASA's Airborne Topographic Mapper (ATM) flights derived altimetry, supplemented with laser altimetry observations from the Ice, Cloud, and Land Elevation Satellite (ICESat) during 2003-2009; the airborne Land, Vegetation, and Ice Sensor (LVIS) instrument during 2007-2013; radar altimetry from the CryoSat-2 satellite during 2010-2017; and European Remote-Sensing Satellite-1 (ERS-1) and ERS-2 data during 1995-2003. We converted the volume loss rate into a mass loss rate accounting for firn compaction as described by Kuipers Munneke et al. (2015). We predict the elastic displacements by convolving mass loss estimates with Green's functions for vertical and horizontal displacements. We use a variety of elastic Green's functions and mass change grid resolutions, respectively, to study the sensitivity of 3D elastic deformation on Earth model parameters different from the Preliminary Reference Earth Reference Model (PREM; Dziewonski & Anderson 1981) and the forcing ice load.
Solar elastosis in its papular form: uncommon, mistakable.
Heng, Jun Khee; Aw, Derrick Chen Wee; Tan, Kong Bing
2014-01-01
Solar elastosis is a degenerative condition of elastic tissue in the dermis due to prolonged sun exposure. There are a variety of clinical manifestations of solar elastosis. In its most common form, solar elastosis manifests as yellow, thickened, coarsely wrinkled skin. We report two uncommon cases of severe solar elastosis with a papular morphology. Its presentation can closely mimic a host of cutaneous disorders and thus, although it is helpful to be cognizant of this entity, it is still crucial to biopsy these lesions to avoid missing a more sinister condition.
NASA Astrophysics Data System (ADS)
Heili, Manon; Bielawski, Andrew; Kieffer, John
The cure kinetics of a DGEBA/DETA epoxy is investigated using concurrent Raman and Brillouin light scattering. Raman scattering allows us to monitor the in-situ reaction and quantitatively assess the degree of cure. Brillouin scattering yields the elastic properties of the system, providing a measure of network connectivity. We show that the adiabatic modulus evolves non-uniquely as a function of cure degree, depending on the cure temperature and the molar ratio of the epoxy. Two mechanisms contribute to the increase in the elastic modulus of the material during curing. First, there is the formation of covalent bonds in the network during the curing process. Second, following bond formation, the epoxy undergoes structural relaxation toward an optimally packed network configuration, enhancing non-bonded interactions. We investigate to what extent the non-bonded interaction contribution to structural rigidity in cross-linked polymers is reversible, and to what extent it corresponds to the difference between adiabatic and isothermal moduli obtained from static tensile, i.e. the so-called relaxational modulus. To this end, we simultaneously measure the adiabatic and isothermal elastic moduli as a function of applied strain and deformation rate.
A coarse-to-fine approach for pericardial effusion localization and segmentation in chest CT scans
NASA Astrophysics Data System (ADS)
Liu, Jiamin; Chellamuthu, Karthik; Lu, Le; Bagheri, Mohammadhadi; Summers, Ronald M.
2018-02-01
Pericardial effusion on CT scans demonstrates very high shape and volume variability and very low contrast to adjacent structures. This inhibits traditional automated segmentation methods from achieving high accuracies. Deep neural networks have been widely used for image segmentation in CT scans. In this work, we present a two-stage method for pericardial effusion localization and segmentation. For the first step, we localize the pericardial area from the entire CT volume, providing a reliable bounding box for the more refined segmentation step. A coarse-scaled holistically-nested convolutional networks (HNN) model is trained on entire CT volume. The resulting HNN per-pixel probability maps are then threshold to produce a bounding box covering the pericardial area. For the second step, a fine-scaled HNN model is trained only on the bounding box region for effusion segmentation to reduce the background distraction. Quantitative evaluation is performed on a dataset of 25 CT scans of patient (1206 images) with pericardial effusion. The segmentation accuracy of our two-stage method, measured by Dice Similarity Coefficient (DSC), is 75.59+/-12.04%, which is significantly better than the segmentation accuracy (62.74+/-15.20%) of only using the coarse-scaled HNN model.
Bertalan, Tom; Wu, Yan; Laing, Carlo; Gear, C. William; Kevrekidis, Ioannis G.
2017-01-01
Finding accurate reduced descriptions for large, complex, dynamically evolving networks is a crucial enabler to their simulation, analysis, and ultimately design. Here, we propose and illustrate a systematic and powerful approach to obtaining good collective coarse-grained observables—variables successfully summarizing the detailed state of such networks. Finding such variables can naturally lead to successful reduced dynamic models for the networks. The main premise enabling our approach is the assumption that the behavior of a node in the network depends (after a short initial transient) on the node identity: a set of descriptors that quantify the node properties, whether intrinsic (e.g., parameters in the node evolution equations) or structural (imparted to the node by its connectivity in the particular network structure). The approach creates a natural link with modeling and “computational enabling technology” developed in the context of Uncertainty Quantification. In our case, however, we will not focus on ensembles of different realizations of a problem, each with parameters randomly selected from a distribution. We will instead study many coupled heterogeneous units, each characterized by randomly assigned (heterogeneous) parameter value(s). One could then coin the term Heterogeneity Quantification for this approach, which we illustrate through a model dynamic network consisting of coupled oscillators with one intrinsic heterogeneity (oscillator individual frequency) and one structural heterogeneity (oscillator degree in the undirected network). The computational implementation of the approach, its shortcomings and possible extensions are also discussed. PMID:28659781
Burst Testing and Analysis of Superalloy Disks With a Dual Grain Microstructure
NASA Technical Reports Server (NTRS)
Gayda, John; Kantzos, Pete
2006-01-01
Elastic-plastic finite element analyses of room temperature burst tests on four superalloy disks were conducted and reported in this paper. Two alloys, Rene 104 (General Electric Aircraft Engines) and Alloy 10 (Honeywell Engines & Systems), were studied. For both alloys an advanced dual microstructure disk, fine grain bore and coarse grain rim, were analyzed and compared with conventional disks with uniform microstructures, coarse grain for Rene 104 and fine grain for Alloy 10. The analysis and experimental data were in good agreement up to burst. At burst, the analysis underestimated the speed and growth of the Rene 104 disks, but overestimated the speed and growth of the Alloy 10 disks. Fractography revealed that the Alloy 10 disks displayed significant surface microcracking and coalescence in comparison to Rene 104 disks. This phenomenon may help explain the differences between the Alloy 10 disks and the Rene 104 disks, as well as the observed deviations between analytical and experimental data at burst.
NASA Astrophysics Data System (ADS)
Zhao, Yongli; Zhu, Ye; Wang, Chunhui; Yu, Xiaosong; Liu, Chuan; Liu, Binglin; Zhang, Jie
2017-07-01
With the capacity increasing in optical networks enabled by spatial division multiplexing (SDM) technology, spatial division multiplexing elastic optical networks (SDM-EONs) attract much attention from both academic and industry. Super-channel is an important type of service provisioning in SDM-EONs. This paper focuses on the issue of super-channel construction in SDM-EONs. Mixed super-channel oriented routing, spectrum and core assignment (MS-RSCA) algorithm is proposed in SDM-EONs considering inter-core crosstalk. Simulation results show that MS-RSCA can improve spectrum resource utilization and reduce blocking probability significantly compared with the baseline RSCA algorithms.
Effect of pendent chains on the interfacial properties of thin polydimethylsiloxane (PDMS) networks.
Landherr, Lucas J T; Cohen, Claude; Archer, Lynden A
2011-05-17
The interfacial properties of end-linked polydimethylsiloxane (PDMS) films on silicon are examined. Thin cross-linked PDMS films (∼10 μm thick) were synthesized over a self-assembled monolayer supported on a silicon wafer. By systematically varying the concentration of monofunctional PDMS in a mixture with telechelic precursor molecules, structures ranging from near-ideal elastic networks to poorly cross-linked networks composed of a preponderance of dangling/pendent chains were synthesized. Lateral force microscopy (LFM) employing bead probes was used to quantify the effect of network structure on the interfacial friction coefficient and residual force. Indentation measurements employing an AFM in force mode were used to characterize the elastic modulus and the pull-off force for the films as a function of pendent chain content. These measurements were complemented with conventional mechanical rheometry measurements on similar thick network films to determine their bulk rheological properties. All networks studied manifested interfacial friction coefficients substantially lower than that of bare silicon. PDMS networks with the lowest pendent chain content displayed friction coefficients close to 1 order of magnitude lower than that of bare silicon, whereas networks with the highest pendent chain content manifested friction coefficients about 3 times lower than that of bare silicon. At intermediate sliding velocities, a crossover in the interfacial friction coefficient was observed, wherein cross-linked PDMS films with the least amount of pendent chains exhibit the highest friction coefficient. These observations are discussed in terms of the structure of the films and relaxation dynamics of elastic strands and dangling chains in tethered network films.
Effective-medium theory of elastic waves in random networks of rods.
Katz, J I; Hoffman, J J; Conradi, M S; Miller, J G
2012-06-01
We formulate an effective medium (mean field) theory of a material consisting of randomly distributed nodes connected by straight slender rods, hinged at the nodes. Defining wavelength-dependent effective elastic moduli, we calculate both the static moduli and the dispersion relations of ultrasonic longitudinal and transverse elastic waves. At finite wave vector k the waves are dispersive, with phase and group velocities decreasing with increasing wave vector. These results are directly applicable to networks with empty pore space. They also describe the solid matrix in two-component (Biot) theories of fluid-filled porous media. We suggest the possibility of low density materials with higher ratios of stiffness and strength to density than those of foams, aerogels, or trabecular bone.
Shape memory polymer network with thermally distinct elasticity and plasticity
Zhao, Qian; Zou, Weike; Luo, Yingwu; Xie, Tao
2016-01-01
Stimuli-responsive materials with sophisticated yet controllable shape-changing behaviors are highly desirable for real-world device applications. Among various shape-changing materials, the elastic nature of shape memory polymers allows fixation of temporary shapes that can recover on demand, whereas polymers with exchangeable bonds can undergo permanent shape change via plasticity. We integrate the elasticity and plasticity into a single polymer network. Rational molecular design allows these two opposite behaviors to be realized at different temperature ranges without any overlap. By exploring the cumulative nature of the plasticity, we demonstrate easy manipulation of highly complex shapes that is otherwise extremely challenging. The dynamic shape-changing behavior paves a new way for fabricating geometrically complex multifunctional devices. PMID:26824077
NASA Astrophysics Data System (ADS)
Lezon, Timothy R.; Shrivastava, Indira H.; Yang, Zheng; Bahar, Ivet
The following sections are included: * Introduction * Theory and Assumptions * Statistical mechanical foundations * Anisotropic network models * Gaussian network model * Rigid block models * Treatment of perturbations * Langevin dynamics * Applications * Membrane proteins * Viruses * Conclusion * References
ChinaSpec: a network of SIF observations to bridge flux measurements and remote sensing data
NASA Astrophysics Data System (ADS)
Zhang, Y.; Wang, S.; Liu, L.; Ju, W.; Zhu, X.
2017-12-01
Accurately quantifying atmosphere-biosphere interactions across multiple scale still remains a challenge. Remote sensing, especially satellite data, has been widely used as a solution to resolve the broad scale estimation of carbon flux by upscaling the point measurements of eddy covariance (EC) technique. However, critical gaps remain between the EC observations and coarse satellite data due to the scale mismatch. In this regard, it is necessary to build a network of in situ optical observations to bridge the scale-mismatch between EC measurements and satellite remote sensing data. Internationally, a few networks have already been established (e.g., SpecNet and EuroSpec), but still at its early stage. ChinaSpec is a network of linking in situ spectral measurements, especially sun-induce chlorophyll fluorescence (SIF), with point EC observations for better understanding the interactions of atmosphere-biosphere. One main focus of ChinsSpec is to conduct continuous field SIF measurements at multiple EC sites across the mainland of China. This will help us better understand the mechanics of SIF and photosynthesis, and resolve the missing gaps between recent SIF retrievals from coarse satellite data and EC observations. In this presentation, we introduce the background, current stage, and the development of ChinaSpec network.
Ye, Tao; Wang, Baocheng; Song, Ping; Li, Juan
2018-06-12
Many accidents happen under shunting mode when the speed of a train is below 45 km/h. In this mode, train attendants observe the railway condition ahead using the traditional manual method and tell the observation results to the driver in order to avoid danger. To address this problem, an automatic object detection system based on convolutional neural network (CNN) is proposed to detect objects ahead in shunting mode, which is called Feature Fusion Refine neural network (FR-Net). It consists of three connected modules, i.e., the depthwise-pointwise convolution, the coarse detection module, and the object detection module. Depth-wise-pointwise convolutions are used to improve the detection in real time. The coarse detection module coarsely refine the locations and sizes of prior anchors to provide better initialization for the subsequent module and also reduces search space for the classification, whereas the object detection module aims to regress accurate object locations and predict the class labels for the prior anchors. The experimental results on the railway traffic dataset show that FR-Net achieves 0.8953 mAP with 72.3 FPS performance on a machine with a GeForce GTX1080Ti with the input size of 320 × 320 pixels. The results imply that FR-Net takes a good tradeoff both on effectiveness and real time performance. The proposed method can meet the needs of practical application in shunting mode.
Hu, Mingyang; de Jong, Djurre H; Marrink, Siewert J; Deserno, Markus
2013-01-01
We calculate the Gaussian curvature modulus kappa of a systematically coarse-grained (CG) one-component lipid membrane by applying the method recently proposed by Hu et al. [Biophys. J., 2012, 102, 1403] to the MARTINI representation of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC). We find the value kappa/kappa = -1.04 +/- 0.03 for the elastic ratio between the Gaussian and the mean curvature modulus and deduce kappa(m)/kappa(m) = -0.98 +/- 0.09 for the monolayer elastic ratio, where the latter is based on plausible assumptions for the distance z0 of the monolayer neutral surface from the bilayer midplane and the spontaneous lipid curvature K(0m). By also analyzing the lateral stress profile sigma0(z) of our system, two other lipid types and pertinent data from the literature, we show that determining K(0m) and kappa through the first and second moment of sigma0(z) gives rise to physically implausible values for these observables. This discrepancy, which we previously observed for a much simpler CG model, suggests that the moment conditions derived from simple continuum assumptions miss the effect of physically important correlations in the lipid bilayer.
Multi scale modeling of 2450MHz electric field effects on microtubule mechanical properties.
Setayandeh, S S; Lohrasebi, A
2016-11-01
Microtubule (MT) rigidity and response to 2450MHz electric fields were investigated, via multi scale modeling approach. For this purpose, six systems were designed and simulated to consider all types of feasible interactions between α and β monomers in MT, by using all atom molecular dynamics method. Subsequently, coarse grain modeling was used to design different lengths of MT. Investigation of effects of external 2450MHz electric field on MT showed MT less rigidity in the presence of such field, which may perturb its functions. Moreover, an additional computational setup was designed to study effects of 2450MHz field on MT response to AFM tip. It was found, more tip velocity led to MT faster transformation and less time was required to change MT elastic response to plastic one, applying constant radius. Moreover it was observed smaller tip caused to increase required time to change MT elastic response to plastic one, considering constant velocity. Furthermore, exposing MT to 2450MHz field led to no significant changes in MT response to AFM tip, but quick change in MT elastic response to plastic one. Copyright © 2016 Elsevier Inc. All rights reserved.
Fiber Orientation Estimation Guided by a Deep Network.
Ye, Chuyang; Prince, Jerry L
2017-09-01
Diffusion magnetic resonance imaging (dMRI) is currently the only tool for noninvasively imaging the brain's white matter tracts. The fiber orientation (FO) is a key feature computed from dMRI for tract reconstruction. Because the number of FOs in a voxel is usually small, dictionary-based sparse reconstruction has been used to estimate FOs. However, accurate estimation of complex FO configurations in the presence of noise can still be challenging. In this work we explore the use of a deep network for FO estimation in a dictionary-based framework and propose an algorithm named Fiber Orientation Reconstruction guided by a Deep Network (FORDN). FORDN consists of two steps. First, we use a smaller dictionary encoding coarse basis FOs to represent diffusion signals. To estimate the mixture fractions of the dictionary atoms, a deep network is designed to solve the sparse reconstruction problem. Second, the coarse FOs inform the final FO estimation, where a larger dictionary encoding a dense basis of FOs is used and a weighted ℓ 1 -norm regularized least squares problem is solved to encourage FOs that are consistent with the network output. FORDN was evaluated and compared with state-of-the-art algorithms that estimate FOs using sparse reconstruction on simulated and typical clinical dMRI data. The results demonstrate the benefit of using a deep network for FO estimation.
ChainMail based neural dynamics modeling of soft tissue deformation for surgical simulation.
Zhang, Jinao; Zhong, Yongmin; Smith, Julian; Gu, Chengfan
2017-07-20
Realistic and real-time modeling and simulation of soft tissue deformation is a fundamental research issue in the field of surgical simulation. In this paper, a novel cellular neural network approach is presented for modeling and simulation of soft tissue deformation by combining neural dynamics of cellular neural network with ChainMail mechanism. The proposed method formulates the problem of elastic deformation into cellular neural network activities to avoid the complex computation of elasticity. The local position adjustments of ChainMail are incorporated into the cellular neural network as the local connectivity of cells, through which the dynamic behaviors of soft tissue deformation are transformed into the neural dynamics of cellular neural network. Experiments demonstrate that the proposed neural network approach is capable of modeling the soft tissues' nonlinear deformation and typical mechanical behaviors. The proposed method not only improves ChainMail's linear deformation with the nonlinear characteristics of neural dynamics but also enables the cellular neural network to follow the principle of continuum mechanics to simulate soft tissue deformation.
Dynamic rheology of food protein networks
USDA-ARS?s Scientific Manuscript database
Small amplitude oscillatory shear analyses of samples containing protein are useful for determining the nature of the protein matrix without damaging it. Elastic modulus, viscous modulus, and loss tangent (the ratio of viscous modulus to elastic modulus) give information on the strength of the netw...
Thermal fluctuations and elastic relaxation in the compressed exponential dynamics of colloidal gels
NASA Astrophysics Data System (ADS)
Bouzid, Mehdi; Colombo, Jader; Del Gado, Emanuela
Colloidal gels belong to the class of amorphous systems, they are disordered elastic solids that can form at very low volume fraction, via aggregation into a rich variety of networks. They exhibit a slow relaxation process in the aging regime similar to the glassy dynamics. A wide range of experiments on colloidal gels show unusual compressed exponential of the relaxation dynamical properties. We use molecular dynamics simulation to investigate how the dynamic change with the age of the system. Upon breaking and reorganization of the network structure, the system may display stretched or compressed exponential relaxation. We show that the transition between these two regimes is associated to the interplay between thermally activated rearrangements and the elastic relaxation of internal stresses. In particular, ballistic-like displacements emerge from the non local relaxation of internal stresses mediated by a series of ''micro-collapses''. When thermal fluctuations dominate, the gel restructuring involves instead more homogeneous displacements across the heterogeneous gel network, leading to a stretched exponential type of relaxation.
Hybrid finite difference/finite element immersed boundary method.
E Griffith, Boyce; Luo, Xiaoyu
2017-12-01
The immersed boundary method is an approach to fluid-structure interaction that uses a Lagrangian description of the structural deformations, stresses, and forces along with an Eulerian description of the momentum, viscosity, and incompressibility of the fluid-structure system. The original immersed boundary methods described immersed elastic structures using systems of flexible fibers, and even now, most immersed boundary methods still require Lagrangian meshes that are finer than the Eulerian grid. This work introduces a coupling scheme for the immersed boundary method to link the Lagrangian and Eulerian variables that facilitates independent spatial discretizations for the structure and background grid. This approach uses a finite element discretization of the structure while retaining a finite difference scheme for the Eulerian variables. We apply this method to benchmark problems involving elastic, rigid, and actively contracting structures, including an idealized model of the left ventricle of the heart. Our tests include cases in which, for a fixed Eulerian grid spacing, coarser Lagrangian structural meshes yield discretization errors that are as much as several orders of magnitude smaller than errors obtained using finer structural meshes. The Lagrangian-Eulerian coupling approach developed in this work enables the effective use of these coarse structural meshes with the immersed boundary method. This work also contrasts two different weak forms of the equations, one of which is demonstrated to be more effective for the coarse structural discretizations facilitated by our coupling approach. © 2017 The Authors International Journal for Numerical Methods in Biomedical Engineering Published by John Wiley & Sons Ltd.
Generalization of mixed multiscale finite element methods with applications
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lee, C S
Many science and engineering problems exhibit scale disparity and high contrast. The small scale features cannot be omitted in the physical models because they can affect the macroscopic behavior of the problems. However, resolving all the scales in these problems can be prohibitively expensive. As a consequence, some types of model reduction techniques are required to design efficient solution algorithms. For practical purpose, we are interested in mixed finite element problems as they produce solutions with certain conservative properties. Existing multiscale methods for such problems include the mixed multiscale finite element methods. We show that for complicated problems, the mixedmore » multiscale finite element methods may not be able to produce reliable approximations. This motivates the need of enrichment for coarse spaces. Two enrichment approaches are proposed, one is based on generalized multiscale finte element metthods (GMsFEM), while the other is based on spectral element-based algebraic multigrid (rAMGe). The former one, which is called mixed GMsFEM, is developed for both Darcy’s flow and linear elasticity. Application of the algorithm in two-phase flow simulations are demonstrated. For linear elasticity, the algorithm is subtly modified due to the symmetry requirement of the stress tensor. The latter enrichment approach is based on rAMGe. The algorithm differs from GMsFEM in that both of the velocity and pressure spaces are coarsened. Due the multigrid nature of the algorithm, recursive application is available, which results in an efficient multilevel construction of the coarse spaces. Stability, convergence analysis, and exhaustive numerical experiments are carried out to validate the proposed enrichment approaches. iii« less
Structural Plasticity and Conformational Transitions of HIV Envelope Glycoprotein gp120
Korkut, Anil; Hendrickson, Wayne A.
2012-01-01
HIV envelope glycoproteins undergo large-scale conformational changes as they interact with cellular receptors to cause the fusion of viral and cellular membranes that permits viral entry to infect targeted cells. Conformational dynamics in HIV gp120 are also important in masking conserved receptor epitopes from being detected for effective neutralization by the human immune system. Crystal structures of HIV gp120 and its complexes with receptors and antibody fragments provide high-resolution pictures of selected conformational states accessible to gp120. Here we describe systematic computational analyses of HIV gp120 plasticity in such complexes with CD4 binding fragments, CD4 mimetic proteins, and various antibody fragments. We used three computational approaches: an isotropic elastic network analysis of conformational plasticity, a full atomic normal mode analysis, and simulation of conformational transitions with our coarse-grained virtual atom molecular mechanics (VAMM) potential function. We observe collective sub-domain motions about hinge points that coordinate those motions, correlated local fluctuations at the interfacial cavity formed when gp120 binds to CD4, and concerted changes in structural elements that form at the CD4 interface during large-scale conformational transitions to the CD4-bound state from the deformed states of gp120 in certain antibody complexes. PMID:23300605
A cohesive-frictional force field (CFFF) for colloidal calcium-silicate-hydrates
NASA Astrophysics Data System (ADS)
Palkovic, Steven D.; Yip, Sidney; Büyüköztürk, Oral
2017-12-01
Calcium-silicate-hydrate (C-S-H) gel is a cohesive-frictional material that exhibits strength asymmetry in compression and tension and normal-stress dependency of the maximum shear strength. Experiments suggest the basic structural component of C-S-H is a colloidal particle with an internal layered structure. These colloids form heterogeneous assemblies with a complex pore network at the mesoscale. We propose a cohesive-frictional force field (CFFF) to describe the interactions in colloidal C-S-H materials that incorporates the strength anisotropy fundamental to the C-S-H molecular structure that has been omitted from recent mesoscale models. We parameterize the CFFF from reactive force field simulations of an internal interface that controls mechanical performance, describing the behavior of thousands of atoms through a single effective pair interaction. We apply the CFFF to study the mesoscale elastic and Mohr-Coulomb strength properties of C-S-H with varying polydispersity and packing density. Our results show that the consideration of cohesive-frictional interactions lead to an increase in stiffness, shear strength, and normal-stress dependency, while also changing the nature of local deformation processes. The CFFF and our coarse-graining approach provide an essential connection between nanoscale molecular interactions and macroscale continuum behavior for hydrated cementitious materials.
TALEs from a spring--superelasticity of Tal effector protein structures.
Flechsig, Holger
2014-01-01
Transcription activator-like effectors (TALEs) are DNA-related proteins that recognise and bind specific target sequences to manipulate gene expression. Recently determined crystal structures show that their common architecture reveals a superhelical overall structure that may undergo drastic conformational changes. To establish a link between structure and dynamics in TALE proteins we have employed coarse-grained elastic-network modelling of currently available structural data and implemented a force-probe setup that allowed us to investigate their mechanical behaviour in computer experiments. Based on the measured force-extension curves we conclude that TALEs exhibit superelastic dynamical properties allowing for large-scale global conformational changes along their helical axis, which represents the soft direction in such proteins. For moderate external forcing the TALE models behave like linear springs, obeying Hooke's law, and the investigated structures can be characterised and compared by a corresponding spring constant. We show that conformational flexibility underlying the large-scale motions is not homogeneously distributed over the TALE structure, but instead soft spot residues around which strain is accumulated and which turn out to represent key agents in the transmission of conformational motions are identified. They correspond to the RVD loop residues that have been experimentally determined to play an eminent role in the binding process of target DNA.
TALEs from a Spring – Superelasticity of Tal Effector Protein Structures
Flechsig, Holger
2014-01-01
Transcription activator-like effectors (TALEs) are DNA-related proteins that recognise and bind specific target sequences to manipulate gene expression. Recently determined crystal structures show that their common architecture reveals a superhelical overall structure that may undergo drastic conformational changes. To establish a link between structure and dynamics in TALE proteins we have employed coarse-grained elastic-network modelling of currently available structural data and implemented a force-probe setup that allowed us to investigate their mechanical behaviour in computer experiments. Based on the measured force-extension curves we conclude that TALEs exhibit superelastic dynamical properties allowing for large-scale global conformational changes along their helical axis, which represents the soft direction in such proteins. For moderate external forcing the TALE models behave like linear springs, obeying Hooke's law, and the investigated structures can be characterised and compared by a corresponding spring constant. We show that conformational flexibility underlying the large-scale motions is not homogeneously distributed over the TALE structure, but instead soft spot residues around which strain is accumulated and which turn out to represent key agents in the transmission of conformational motions are identified. They correspond to the RVD loop residues that have been experimentally determined to play an eminent role in the binding process of target DNA. PMID:25313859
NASA Astrophysics Data System (ADS)
Zhu, Ruijie; Zhao, Yongli; Yang, Hui; Tan, Yuanlong; Chen, Haoran; Zhang, Jie; Jue, Jason P.
2016-08-01
Network virtualization can eradicate the ossification of the infrastructure and stimulate innovation of new network architectures and applications. Elastic optical networks (EONs) are ideal substrate networks for provisioning flexible virtual optical network (VON) services. However, as network traffic continues to increase exponentially, the capacity of EONs will reach the physical limitation soon. To further increase network flexibility and capacity, the concept of EONs is extended into the spatial domain. How to map the VON onto substrate networks by thoroughly using the spectral and spatial resources is extremely important. This process is called VON embedding (VONE).Considering the two kinds of resources at the same time during the embedding process, we propose two VONE algorithms, the adjacent link embedding algorithm (ALEA) and the remote link embedding algorithm (RLEA). First, we introduce a model to solve the VONE problem. Then we design the embedding ability measurement of network elements. Based on the network elements' embedding ability, two VONE algorithms were proposed. Simulation results show that the proposed VONE algorithms could achieve better performance than the baseline algorithm in terms of blocking probability and revenue-to-cost ratio.
Katashima, Takuya; Urayama, Kenji; Chung, Ung-il; Sakai, Takamasa
2015-05-07
The pure shear deformation of the Tetra-polyethylene glycol gels reveals the presence of an explicit cross-effect of strains in the strain energy density function even for the polymer networks with nearly regular structure including no appreciable amount of structural defect such as trapped entanglement. This result is in contrast to the expectation of the classical Gaussian network model (Neo Hookean model), i.e., the vanishing of the cross effect in regular networks with no trapped entanglement. The results show that (1) the cross effect of strains is not dependent on the network-strand length; (2) the cross effect is not affected by the presence of non-network strands; (3) the cross effect is proportional to the network polymer concentration including both elastically effective and ineffective strands; (4) no cross effect is expected exclusively in zero limit of network concentration in real polymer networks. These features indicate that the real polymer networks with regular network structures have an explicit cross-effect of strains, which originates from some interaction between network strands (other than entanglement effect) such as nematic interaction, topological interaction, and excluded volume interaction.
Zheng, Wenjun
2017-02-01
In the adaptive immune systems of many bacteria and archaea, the Cas9 endonuclease forms a complex with specific guide/scaffold RNA to identify and cleave complementary target sequences in foreign DNA. This DNA targeting machinery has been exploited in numerous applications of genome editing and transcription control. However, the molecular mechanism of the Cas9 system is still obscure. Recently, high-resolution structures have been solved for Cas9 in different structural forms (e.g., unbound forms, RNA-bound binary complexes, and RNA-DNA-bound tertiary complexes, corresponding to an inactive state, a pre-target-bound state, and a cleavage-competent or product state), which offered key structural insights to the Cas9 mechanism. To further probe the structural dynamics of Cas9 interacting with RNA and DNA at the amino-acid level of details, we have performed systematic coarse-grained modeling using an elastic network model and related analyses. Our normal mode analysis predicted a few key modes of collective motions that capture the observed conformational changes featuring large domain motions triggered by binding of RNA and DNA. Our flexibility analysis identified specific regions with high or low flexibility that coincide with key functional sites (such as DNA/RNA-binding sites, nuclease cleavage sites, and key hinges). We also identified a small set of hotspot residues that control the energetics of functional motions, which overlap with known functional sites and offer promising targets for future mutagenesis efforts to improve the specificity of Cas9. Finally, we modeled the conformational transitions of Cas9 from the unbound form to the binary complex and then the tertiary complex, and predicted a distinct sequence of domain motions. In sum, our findings have offered rich structural and dynamic details relevant to the Cas9 machinery, and will guide future investigation and engineering of the Cas9 systems. Proteins 2017; 85:342-353. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
In Silico Reconstitution of Actin-Based Symmetry Breaking and Motility
Dayel, Mark J.; Akin, Orkun; Landeryou, Mark; Risca, Viviana; Mogilner, Alex; Mullins, R. Dyche
2009-01-01
Eukaryotic cells assemble viscoelastic networks of crosslinked actin filaments to control their shape, mechanical properties, and motility. One important class of actin network is nucleated by the Arp2/3 complex and drives both membrane protrusion at the leading edge of motile cells and intracellular motility of pathogens such as Listeria monocytogenes. These networks can be reconstituted in vitro from purified components to drive the motility of spherical micron-sized beads. An Elastic Gel model has been successful in explaining how these networks break symmetry, but how they produce directed motile force has been less clear. We have combined numerical simulations with in vitro experiments to reconstitute the behavior of these motile actin networks in silico using an Accumulative Particle-Spring (APS) model that builds on the Elastic Gel model, and demonstrates simple intuitive mechanisms for both symmetry breaking and sustained motility. The APS model explains observed transitions between smooth and pulsatile motion as well as subtle variations in network architecture caused by differences in geometry and conditions. Our findings also explain sideways symmetry breaking and motility of elongated beads, and show that elastic recoil, though important for symmetry breaking and pulsatile motion, is not necessary for smooth directional motility. The APS model demonstrates how a small number of viscoelastic network parameters and construction rules suffice to recapture the complex behavior of motile actin networks. The fact that the model not only mirrors our in vitro observations, but also makes novel predictions that we confirm by experiment, suggests that the model captures much of the essence of actin-based motility in this system. PMID:19771152
Lin, Pei-Feng; Lo, Men-Tzung; Tsao, Jenho; Chang, Yi-Chung; Lin, Chen; Ho, Yi-Lwun
2014-01-01
The heart begins to beat before the brain is formed. Whether conventional hierarchical central commands sent by the brain to the heart alone explain all the interplay between these two organs should be reconsidered. Here, we demonstrate correlations between the signal complexity of brain and cardiac activity. Eighty-seven geriatric outpatients with healthy hearts and varied cognitive abilities each provided a 24-hour electrocardiography (ECG) and a 19-channel eye-closed routine electroencephalography (EEG). Multiscale entropy (MSE) analysis was applied to three epochs (resting-awake state, photic stimulation of fast frequencies (fast-PS), and photic stimulation of slow frequencies (slow-PS)) of EEG in the 1–58 Hz frequency range, and three RR interval (RRI) time series (awake-state, sleep and that concomitant with the EEG) for each subject. The low-to-high frequency power (LF/HF) ratio of RRI was calculated to represent sympatho-vagal balance. With statistics after Bonferroni corrections, we found that: (a) the summed MSE value on coarse scales of the awake RRI (scales 11–20, RRI-MSE-coarse) were inversely correlated with the summed MSE value on coarse scales of the resting-awake EEG (scales 6–20, EEG-MSE-coarse) at Fp2, C4, T6 and T4; (b) the awake RRI-MSE-coarse was inversely correlated with the fast-PS EEG-MSE-coarse at O1, O2 and C4; (c) the sleep RRI-MSE-coarse was inversely correlated with the slow-PS EEG-MSE-coarse at Fp2; (d) the RRI-MSE-coarse and LF/HF ratio of the awake RRI were correlated positively to each other; (e) the EEG-MSE-coarse at F8 was proportional to the cognitive test score; (f) the results conform to the cholinergic hypothesis which states that cognitive impairment causes reduction in vagal cardiac modulation; (g) fast-PS significantly lowered the EEG-MSE-coarse globally. Whether these heart-brain correlations could be fully explained by the central autonomic network is unknown and needs further exploration. PMID:24498375
Ionic supramolecular networks fully based on chemicals coming from renewable sources.
Aboudzadeh, Ali; Fernandez, Mercedes; Muñoz, Maria Eugenia; Santamaría, Antxon; Mecerreyes, David
2014-02-01
New supramolecular ionic networks are synthesized by proton transfer reaction between a bio-based fatty diamine molecule (Priamine 1074) and a series of naturally occurring carboxylic acids such as malonic acid, citric acid, tartaric acid, and 2,5-furandicarboxylic acid. The resulting solid soft material exhibits a thermoreversible transition becoming a viscoelastic liquid at high temperatures. All the networks show an elastic behavior at low temperatures/high frequencies, with elastic modulus values ranging from 4.5 × 10(6) to 4.5 × 10(7) Pa and soft network to liquid transitions T(nl) between -10 and 60 °C. The supramolecular ionic network based on cationic Priamine 1074 and anionic citrate shows promising self-healing properties at room temperature as well as relatively high ionic conductivity values close to 10(-6) S cm(-1). © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
NASA Astrophysics Data System (ADS)
Hsu, David D.
Due to high nanointerfacial area to volume ratio, the properties of "nanoconfined" polymer thin films, blends, and composites become highly altered compared to their bulk homopolymer analogues. Understanding the structure-property mechanisms underlying this effect is an active area of research. However, despite extensive work, a fundamental framework for predicting the local and system-averaged thermomechanical properties as a function of configuration and polymer species has yet to be established. Towards bridging this gap, here, we present a novel, systematic coarse-graining (CG) method which is able to capture quantitatively, the thermomechanical properties of real polymer systems in bulk and in nanoconfined geometries. This method, which we call thermomechanically consistent coarse-graining (TCCG), is a two-bead-per-monomer CG hybrid approach through which bonded interactions are optimized to match the atomistic structure via the Iterative Boltzmann Inversion method (IBI), and nonbonded interactions are tuned to macroscopic targets through parametric studies. We validate the TCCG method by systematically developing coarse-grain models for a group of five specialized methacrylate-based polymers including poly(methyl methacrylate) (PMMA). Good correlation with bulk all-atom (AA) simulations and experiments is found for the temperature-dependent glass transition temperature (Tg) Flory-Fox scaling relationships, self-diffusion coefficients of liquid monomers, and modulus of elasticity. We apply this TCCG method also to bulk polystyrene (PS) using a comparable coarse-grain CG bead mapping strategy. The model demonstrates chain stiffness commensurate with experiments, and we utilize a density-correction term to improve the transferability of the elastic modulus over a 500 K range. Additionally, PS and PMMA models capture the unexplained, characteristically dissimilar scaling of Tg with the thickness of free-standing films as seen in experiments. Using vibrational density of states (VDOS) analysis, we discover that increasing backbone to sidechain mass ratio in CG models increases the amplitude of sidechain fluctuations associated with flexibility, and suppresses the free-surface Tg-nanoconfinement effect. This uncovers that intrinsic mass distribution and sidechain flexibility differences in the PS and PMMA chemical structure are central to explaining the dissimilarities in their free surface response. PS and PMMA models are subsequently combined in the supported bilayer film configuration to explore the local Tg-nanoconfinement effect associated with different interface types at nanometer resolution. We find that Tg gradients in the interphase regions where chain mobility deviates from the bulk are independent of the film thickness above a critical thickness and add by the principle of superposition below the critical thickness to good approximation. The analytical expressions describing the interphase regions and their interactions demonstrate geometric universality and can be used to derive accurate local and global Tg estimations for complex nanophase blends and nanocomposite configurations. Our studies ascertain the significance of molecular characteristics on nanoconfinement, and highlight the ability for chemistry-specific CG models to explore and predict thermomechanical property modification accompanying interfacial nanoconfinement.
Elastin: a representative ideal protein elastomer.
Urry, D W; Hugel, T; Seitz, M; Gaub, H E; Sheiba, L; Dea, J; Xu, J; Parker, T
2002-01-01
During the last half century, identification of an ideal (predominantly entropic) protein elastomer was generally thought to require that the ideal protein elastomer be a random chain network. Here, we report two new sets of data and review previous data. The first set of new data utilizes atomic force microscopy to report single-chain force-extension curves for (GVGVP)(251) and (GVGIP)(260), and provides evidence for single-chain ideal elasticity. The second class of new data provides a direct contrast between low-frequency sound absorption (0.1-10 kHz) exhibited by random-chain network elastomers and by elastin protein-based polymers. Earlier composition, dielectric relaxation (1-1000 MHz), thermoelasticity, molecular mechanics and dynamics calculations and thermodynamic and statistical mechanical analyses are presented, that combine with the new data to contrast with random-chain network rubbers and to detail the presence of regular non-random structural elements of the elastin-based systems that lose entropic elastomeric force upon thermal denaturation. The data and analyses affirm an earlier contrary argument that components of elastin, the elastic protein of the mammalian elastic fibre, and purified elastin fibre itself contain dynamic, non-random, regularly repeating structures that exhibit dominantly entropic elasticity by means of a damping of internal chain dynamics on extension. PMID:11911774
The interplay between mechanics and stability of viral cages
NASA Astrophysics Data System (ADS)
Hernando-Pérez, Mercedes; Pascual, Elena; Aznar, María; Ionel, Alina; Castón, José R.; Luque, Antoni; Carrascosa, José L.; Reguera, David; de Pablo, Pedro J.
2014-02-01
The stability and strength of viral nanoparticles are crucial to fulfill the functions required through the viral cycle as well as using capsids for biomedical and nanotechnological applications. The mechanical properties of viral shells obtained through Atomic Force Microscopy (AFM) and continuum elasticity theory, such as stiffness or Young's modulus, have been interpreted very often in terms of stability. However, viruses are normally subjected to chemical rather than to mechanical aggression. Thus, a correct interpretation of mechanics in terms of stability requires an adequate linkage between the ability of viral cages to support chemical and mechanical stresses. Here we study the mechanical fragility and chemical stability of bacteriophage T7 in two different maturation states: the early proheads and the final mature capsids. Using chemical stress experiments we show that proheads are less stable than final mature capsids. Still, both particles present similar anisotropic stiffness, indicating that a continuum elasticity description in terms of Young's modulus is not an adequate measure of viral stability. In combination with a computational coarse-grained model we demonstrate that mechanical anisotropy of T7 emerges out of the discrete nature of the proheads and empty capsids. Even though they present the same stiffness, proheads break earlier and have fractures ten times larger than mature capsids, in agreement with chemical stability, thus demonstrating that fragility rather than stiffness is a better indicator of viral cages' stability.The stability and strength of viral nanoparticles are crucial to fulfill the functions required through the viral cycle as well as using capsids for biomedical and nanotechnological applications. The mechanical properties of viral shells obtained through Atomic Force Microscopy (AFM) and continuum elasticity theory, such as stiffness or Young's modulus, have been interpreted very often in terms of stability. However, viruses are normally subjected to chemical rather than to mechanical aggression. Thus, a correct interpretation of mechanics in terms of stability requires an adequate linkage between the ability of viral cages to support chemical and mechanical stresses. Here we study the mechanical fragility and chemical stability of bacteriophage T7 in two different maturation states: the early proheads and the final mature capsids. Using chemical stress experiments we show that proheads are less stable than final mature capsids. Still, both particles present similar anisotropic stiffness, indicating that a continuum elasticity description in terms of Young's modulus is not an adequate measure of viral stability. In combination with a computational coarse-grained model we demonstrate that mechanical anisotropy of T7 emerges out of the discrete nature of the proheads and empty capsids. Even though they present the same stiffness, proheads break earlier and have fractures ten times larger than mature capsids, in agreement with chemical stability, thus demonstrating that fragility rather than stiffness is a better indicator of viral cages' stability. Electronic supplementary information (ESI) available: Purification of T7 proheads and capsids, coarse-grained simulations of the indentation of T7 empty capsids, Finite Element (FE) simulations, and justification of the anisotropic stiffness based on structural information. See DOI: 10.1039/c3nr05763a
Designing heavy metal oxide glasses with threshold properties from network rigidity
NASA Astrophysics Data System (ADS)
Chakraborty, Shibalik; Boolchand, P.; Malki, M.; Micoulaut, M.
2014-01-01
Here, we show that a new class of glasses composed of heavy metal oxides involving transition metals (V2O5-TeO2) can surprisingly be designed from very basic tools using topology and rigidity of their underlying molecular networks. When investigated as a function of composition, such glasses display abrupt changes in network packing and enthalpy of relaxation at Tg, underscoring presence of flexible to rigid elastic phase transitions. We find that these elastic phases are fully consistent with polaronic nature of electronic conductivity at high V2O5 content. Such observations have new implications for designing electronic glasses which differ from the traditional amorphous electrolytes having only mobile ions as charge carriers.
Designing heavy metal oxide glasses with threshold properties from network rigidity.
Chakraborty, Shibalik; Boolchand, P; Malki, M; Micoulaut, M
2014-01-07
Here, we show that a new class of glasses composed of heavy metal oxides involving transition metals (V2O5-TeO2) can surprisingly be designed from very basic tools using topology and rigidity of their underlying molecular networks. When investigated as a function of composition, such glasses display abrupt changes in network packing and enthalpy of relaxation at Tg, underscoring presence of flexible to rigid elastic phase transitions. We find that these elastic phases are fully consistent with polaronic nature of electronic conductivity at high V2O5 content. Such observations have new implications for designing electronic glasses which differ from the traditional amorphous electrolytes having only mobile ions as charge carriers.
Anisotropy of fluctuation dynamics of proteins with an elastic network model.
Atilgan, A R; Durell, S R; Jernigan, R L; Demirel, M C; Keskin, O; Bahar, I
2001-01-01
Fluctuations about the native conformation of proteins have proven to be suitably reproduced with a simple elastic network model, which has shown excellent agreement with a number of different properties for a wide variety of proteins. This scalar model simply investigates the magnitudes of motion of individual residues in the structure. To use the elastic model approach further for developing the details of protein mechanisms, it becomes essential to expand this model to include the added details of the directions of individual residue fluctuations. In this paper a new tool is presented for this purpose and applied to the retinol-binding protein, which indicates enhanced flexibility in the region of entry to the ligand binding site and for the portion of the protein binding to its carrier protein. PMID:11159421
Technologies for Elastic Optical Networking Systems in Spatial, Temporal and Spectral Domains
NASA Astrophysics Data System (ADS)
Qin, Chuan
As the demand for more data capacity keeps increasing, the need for the more efficient use of the data channel becomes more imperative. The fixed wavelength grid which has been in use for more than ten years in conventional wavelength division multiplexing (WDM) is a bottleneck that prevents the capacity from upgrading towards 400 Gb/s and above. A new elastic optical networking scheme where both transceivers and interconnects become flexible break the boundary of wavelength grids and allow a more efficient use of the limited optical bands for communication. This dissertation focuses on a few enabling technologies for elastic optical networking systems. Optical arbitrary waveform generation (OAWG) uses Fourier synthesis and generates user-defined broad-band scalable optical waveforms with high-fidelity through line-by-line full field control of a coherent optical frequency comb. OAWG finds its niche in elastic optical networking since it provides no grids, and scales to user-defined bandwidth. When elastic optical networking builds various connections to use an arbitrary number of subcarriers depending on the users' bandwidth needs, the flexibility also creates non-contiguous spectral fragmentation, much like a computer hard disk generating fragments. Spectral defragmentation aims to re-optimize and re-assign the optical spectrum to achieve more efficient use of the spectrum. One of the technologies is "hop tuning" defragmentation method with a fast auto-tracking local oscillator (LO). In the demonstrated defragmentation experiment, I used a field-programmable gate array (FPGA) to monitor the wavelength change in the signal laser and tune the front and rear current that controls the wavelength of the local oscillator laser. However, the control of the front and rear current needs a complete and accurate calibration of the LO laser and may not apply to a larger number of coherent communication links. A single-tone optical frequency shifter can shift the LO laser wavelength to track the signal wavelength, thus providing a technique for authentically automatic wavelength tracking. I also explored different materials and crystal orientations to reduce the radio-frequency (RF) power consumption required to shift the wavelengths. Based on the elastic optical networking in the temporal, spectral and spatial domains, an additional degree of freedom has been investigated recently to increase the data capacity. The exploration to use the spatial domain to carry more data is termed as spatial division multiplexing (SDM). One such SDM method is orbital angular momentum(OAM), which is a group of orthogonal light beams carrying orbital angular momentum exhibiting an azimuthal phase variation. The utilization of OAM states has the potential to significantly increase the spectral efficiency and channel capacity. The thesis also includes the demonstration to establish a connection by exploiting the elasticity steering in spatial, temporal and spectral domains. Beam steering based on optical phased array (OPA) is also a potential candidate of SDM to carry information when a different linear phase will distribute light to different spatial locations. The states are intrinsically orthogonal to one another. Using 4x4 3-D waveguides written by ultrafast laser inscription (ULI), we demonstrated 2-D optical phased array (OPA) beam steering that shows steering in both vertical and horizontal directions. Enabling technologies provide future pathways for elastic optical networking and will fundamentally impact optical communication systems in many ways.
Efficient Construction of Mesostate Networks from Molecular Dynamics Trajectories.
Vitalis, Andreas; Caflisch, Amedeo
2012-03-13
The coarse-graining of data from molecular simulations yields conformational space networks that may be used for predicting the system's long time scale behavior, to discover structural pathways connecting free energy basins in the system, or simply to represent accessible phase space regions of interest and their connectivities in a two-dimensional plot. In this contribution, we present a tree-based algorithm to partition conformations of biomolecules into sets of similar microstates, i.e., to coarse-grain trajectory data into mesostates. On account of utilizing an architecture similar to that of established tree-based algorithms, the proposed scheme operates in near-linear time with data set size. We derive expressions needed for the fast evaluation of mesostate properties and distances when employing typical choices for measures of similarity between microstates. Using both a pedagogically useful and a real-word application, the algorithm is shown to be robust with respect to tree height, which in addition to mesostate threshold size is the main adjustable parameter. It is demonstrated that the derived mesostate networks can preserve information regarding the free energy basins and barriers by which the system is characterized.
Kataoka, Toshikazu; Ishioka, Yumi; Mizuhata, Minoru; Minami, Hideto; Maruyama, Tatsuo
2015-10-21
We prepared a heterogeneous double-network (DN) ionogel containing a low-molecular-weight gelator network and a polymer network that can exhibit high ionic conductivity and high mechanical strength. An imidazolium-based ionic liquid was first gelated by the molecular self-assembly of a low-molecular-weight gelator (benzenetricarboxamide derivative), and methyl methacrylate was polymerized with a cross-linker to form a cross-linked poly(methyl methacrylate) (PMMA) network within the ionogel. Microscopic observation and calorimetric measurement revealed that the fibrous network of the low-molecular-weight gelator was maintained in the DN ionogel. The PMMA network strengthened the ionogel of the low-molecular-weight gelator and allowed us to handle the ionogel using tweezers. The orthogonal DNs produced ionogels with a broad range of storage elastic moduli. DN ionogels with low PMMA concentrations exhibited high ionic conductivity that was comparable to that of a neat ionic liquid. The present study demonstrates that the ionic conductivities of the DN and single-network, low-molecular-weight gelator or polymer ionogels strongly depended on their storage elastic moduli.
NASA Astrophysics Data System (ADS)
Chakraborty, Shibalik; Boolchand, Punit
2014-03-01
Binary GexS100-x glasses reveal elastic and chemical phase transitions driven by network topology. With increasing Ge content x, well defined rigidity (xc(1) =19.3%) and stress(xc(2) =24.85%) transitions and associated optical elasticity power-laws are observed in Raman scattering. Calorimetric measurements reveal a square-well like minimum with window walls that coincide with the two elastic phase transitions. Molar volumes show a trapezoidal-like minimum with edges that nearly coincide with the reversibility window. These results are signatures of the isostatically rigid nature of the elastic phase formed between the rigidity and stress transitions. Complex Cp measurements show melt fragility index, m(x) to also show a global minimum in the reversibility window, underscoring that melt dynamics encode the elastic behavior of the glass formed at Tg. The strong nature of melts formed in the IP has an important practical consequence; they lead to slow homogenization of non-stoichiometric batch compositions reacted at high temperatures. Homogenization of chalcogenides melts/glasses over a scale of a few microns is a pre-requisite to observe the intrinsic physical properties of these materials. Supported by NSF Grant DMR 0853957.
Song, Youyi; Zhang, Ling; Chen, Siping; Ni, Dong; Lei, Baiying; Wang, Tianfu
2015-10-01
In this paper, a multiscale convolutional network (MSCN) and graph-partitioning-based method is proposed for accurate segmentation of cervical cytoplasm and nuclei. Specifically, deep learning via the MSCN is explored to extract scale invariant features, and then, segment regions centered at each pixel. The coarse segmentation is refined by an automated graph partitioning method based on the pretrained feature. The texture, shape, and contextual information of the target objects are learned to localize the appearance of distinctive boundary, which is also explored to generate markers to split the touching nuclei. For further refinement of the segmentation, a coarse-to-fine nucleus segmentation framework is developed. The computational complexity of the segmentation is reduced by using superpixel instead of raw pixels. Extensive experimental results demonstrate that the proposed cervical nucleus cell segmentation delivers promising results and outperforms existing methods.
Coarse graining flow of spin foam intertwiners
NASA Astrophysics Data System (ADS)
Dittrich, Bianca; Schnetter, Erik; Seth, Cameron J.; Steinhaus, Sebastian
2016-12-01
Simplicity constraints play a crucial role in the construction of spin foam models, yet their effective behavior on larger scales is scarcely explored. In this article we introduce intertwiner and spin net models for the quantum group SU (2 )k×SU (2 )k, which implement the simplicity constraints analogous to four-dimensional Euclidean spin foam models, namely the Barrett-Crane (BC) and the Engle-Pereira-Rovelli-Livine/Freidel-Krasnov (EPRL/FK) model. These models are numerically coarse grained via tensor network renormalization, allowing us to trace the flow of simplicity constraints to larger scales. In order to perform these simulations we have substantially adapted tensor network algorithms, which we discuss in detail as they can be of use in other contexts. The BC and the EPRL/FK model behave very differently under coarse graining: While the unique BC intertwiner model is a fixed point and therefore constitutes a two-dimensional topological phase, BC spin net models flow away from the initial simplicity constraints and converge to several different topological phases. Most of these phases correspond to decoupling spin foam vertices; however we find also a new phase in which this is not the case, and in which a nontrivial version of the simplicity constraints holds. The coarse graining flow of the BC spin net models indicates furthermore that the transitions between these phases are not of second order. The EPRL/FK model by contrast reveals a far more intricate and complex dynamics. We observe an immediate flow away from the original simplicity constraints; however, with the truncation employed here, the models generically do not converge to a fixed point. The results show that the imposition of simplicity constraints can indeed lead to interesting and also very complex dynamics. Thus we need to further develop coarse graining tools to efficiently study the large scale behavior of spin foam models, in particular for the EPRL/FK model.
The impact of baking time and bread storage temperature on bread crumb properties.
Bosmans, Geertrui M; Lagrain, Bert; Fierens, Ellen; Delcour, Jan A
2013-12-15
Two baking times (9 and 24 min) and storage temperatures (4 and 25 °C) were used to explore the impact of heat exposure during bread baking and subsequent storage on amylopectin retrogradation, water mobility, and bread crumb firming. Shorter baking resulted in less retrogradation, a less extended starch network and smaller changes in crumb firmness and elasticity. A lower storage temperature resulted in faster retrogradation, a more rigid starch network with more water inclusion and larger changes in crumb firmness and elasticity. Crumb to crust moisture migration was lower for breads baked shorter and stored at lower temperature, resulting in better plasticized biopolymer networks in crumb. Network stiffening, therefore, contributed less to crumb firmness. A negative relation was found between proton mobilities of water and biopolymers in the crumb gel network and crumb firmness. The slope of this linear function was indicative for the strength of the starch network. Copyright © 2013 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Bai, Wei; Yang, Hui; Yu, Ao; Xiao, Hongyun; He, Linkuan; Feng, Lei; Zhang, Jie
2018-01-01
The leakage of confidential information is one of important issues in the network security area. Elastic Optical Networks (EON) as a promising technology in the optical transport network is under threat from eavesdropping attacks. It is a great demand to support confidential information service (CIS) and design efficient security strategy against the eavesdropping attacks. In this paper, we propose a solution to cope with the eavesdropping attacks in routing and spectrum allocation. Firstly, we introduce probability theory to describe eavesdropping issue and achieve awareness of eavesdropping attacks. Then we propose an eavesdropping-aware routing and spectrum allocation (ES-RSA) algorithm to guarantee information security. For further improving security and network performance, we employ multi-flow virtual concatenation (MFVC) and propose an eavesdropping-aware MFVC-based secure routing and spectrum allocation (MES-RSA) algorithm. The presented simulation results show that the proposed two RSA algorithms can both achieve greater security against the eavesdropping attacks and MES-RSA can also improve the network performance efficiently.
Modeling the polydomain-monodomain transition of liquid crystal elastomers.
Whitmer, Jonathan K; Roberts, Tyler F; Shekhar, Raj; Abbott, Nicholas L; de Pablo, Juan J
2013-02-01
We study the mechanism of the polydomain-monodomain transition in liquid crystalline elastomers at the molecular scale. A coarse-grained model is proposed in which mesogens are described as ellipsoidal particles. Molecular dynamics simulations are used to examine the transition from a polydomain state to a monodomain state in the presence of uniaxial strain. Our model demonstrates soft elasticity, similar to that exhibited by side-chain elastomers in the literature. By analyzing the growth dynamics of nematic domains during uniaxial extension, we provide direct evidence that at a molecular level the polydomain-monodomain transition proceeds through cluster rotation and domain growth.
Quantitative comparison of alternative methods for coarse-graining biological networks
Bowman, Gregory R.; Meng, Luming; Huang, Xuhui
2013-01-01
Markov models and master equations are a powerful means of modeling dynamic processes like protein conformational changes. However, these models are often difficult to understand because of the enormous number of components and connections between them. Therefore, a variety of methods have been developed to facilitate understanding by coarse-graining these complex models. Here, we employ Bayesian model comparison to determine which of these coarse-graining methods provides the models that are most faithful to the original set of states. We find that the Bayesian agglomerative clustering engine and the hierarchical Nyström expansion graph (HNEG) typically provide the best performance. Surprisingly, the original Perron cluster cluster analysis (PCCA) method often provides the next best results, outperforming the newer PCCA+ method and the most probable paths algorithm. We also show that the differences between the models are qualitatively significant, rather than being minor shifts in the boundaries between states. The performance of the methods correlates well with the entropy of the resulting coarse-grainings, suggesting that finding states with more similar populations (i.e., avoiding low population states that may just be noise) gives better results. PMID:24089717
Chylek, Lily A.; Harris, Leonard A.; Tung, Chang-Shung; Faeder, James R.; Lopez, Carlos F.
2013-01-01
Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and post-translational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). PMID:24123887
Arroyo el Mimbral, Mexico, K/T unit: Origin as debris flow/turbidite, not a tsunami deposit
NASA Technical Reports Server (NTRS)
Bohor, Bruce F.; Betterton, William J.
1993-01-01
Coarse, spherule-bearing, elastic units have been discovered at 10 marine sites that span the K/T boundary in northeastern Mexico. We examined one of the best exposed sites in Arroyo el Mimbral, northwest of Tampico. The Mimbral outcrop displays a layered elastic unit up to 3 m thick enclosed by marly limestones of the Mendez (Latest Maastrichian) and Velasco (Earliest Danian) Formations. At its thickest point, this channelized elastic unit is comprised of 3 subunits: (1) a basal, poorly-sorted, ungraded calcareous spherule bed 1 m thick containing relict impact glass and shocked mineral grains, (2) a massive set of laminated calcite-cemented sandstones up to 2 m thick with plant debris at its base, (3) capped by a thin (up to 20 cm) set of rippled sandstone layers separated by silty mudstone drapes containing a small (921 pg/g) iridium anomaly. This tripartite elastic unit is conformably overlain by marls of the Velasco Formation. We also visited the La Lajilla site east of Ciudad Victoria; its stratigraphy is similar to Mimbral's, but its elastic beds are thinner and less extensive laterally. The Mimbral elastic unit has been interpreted previously as being deposited by a megawave or tsunami produced by an asteroid impact on nearby Yucatan (Chicxulub crater). However, a presumed 400-m paleodepth of water at the Mimbral site, channeling of the spherule subunit into the underlying Mendez Formation marls, and the overtopping of the basal, spherule-bearing subunit by the laminated sandstone subunit, all suggest a combined debris flow/turbidite origin for this elastic unit similar to that proposed for Upper Pleistocene sand/silt beds occurring elsewhere in the Gulf of Mexico. In this latter model, the sediment source region for the elastic unit is the lower continental shelf and slope escarpment. For the K/T unit at Mimbral, we propose that thick ejecta blanket deposits composed mostly of spherules were rapidly loaded onto the lower shelf and slope from an impact-generated ejecta curtain.
The elastic properties of woven polymeric fabric
DOE Office of Scientific and Technical Information (OSTI.GOV)
Warren, W.E.
1989-01-01
The in-plane linear elastic constants of woven fabric are determined in terms of the specific fabric microstructure. The fabric is assumed to be a spatially periodic interlaced network of orthogonal yarns and the individual yarns are modeled as extensible elastica. These results indicate that a significant coupling of bending and stretching effects occurs during deformation. Results of this theoretical analysis compare favorable with measured in-plane elastic constants for Vincel yarn fabrics. 17 refs., 2 figs., 1 tab.
Sadeghi, Zahra
2016-09-01
In this paper, I investigate conceptual categories derived from developmental processing in a deep neural network. The similarity matrices of deep representation at each layer of neural network are computed and compared with their raw representation. While the clusters generated by raw representation stand at the basic level of abstraction, conceptual categories obtained from deep representation shows a bottom-up transition procedure. Results demonstrate a developmental course of learning from specific to general level of abstraction through learned layers of representations in a deep belief network. © The Author(s) 2016.
NASA Technical Reports Server (NTRS)
Manchiraju, Sivom; Gaydosh, Darrell; Benafan, Othmane; Noebe, Ronald; Vaidyanathan, Raj; Anderson, Peter M.
2011-01-01
A recent microstructure-based FEM model that couples crystal-based plasticity, the B2<-> MB190 phase transformation and anisotropic elasticity at the grain scale is calibrated to recent data for polycrystalline NiTi (49.9 at.% Ni). Inputs include anisotropic elastic properties, texture and differential scanning calorimetry data, as well as a subset of recent isothermal deformation and load-biased thermal cycling data. The model is assessed against additional experimental data. Several experimental trends are captured - in particular, the transformation strain during thermal cycling monotonically increases and reaches a peak with increasing bias stress. This is achieved, in part, by modifying the martensite hardening matrix proposed by Patoor et al. [Patoor E, Eberhardt A, Berveiller M. J Phys IV 1996;6:277]. Some experimental trends are underestimated - in particular, the ratcheting of macrostrain during thermal cycling. This may reflect a model limitation that transformation-plasticity coupling is captured on a coarse (grain) scale but not on a fine (martensitic plate) scale.
Fiber optic voice/data network
NASA Technical Reports Server (NTRS)
Bergman, Larry A. (Inventor)
1989-01-01
An asynchronous, high-speed, fiber optic local area network originally developed for tactical environments with additional benefits for other environments such as spacecraft, and the like. The network supports ordinary data packet traffic simultaneously with synchronous T1 voice traffic over a common token ring channel; however, the techniques and apparatus of this invention can be applied to any deterministic class of packet data networks, including multitier backbones, that must transport stream data (e.g., video, SAR, sensors) as well as data. A voice interface module parses, buffers, and resynchronizes the voice data to the packet network employing elastic buffers on both the sending and receiving ends. Voice call setup and switching functions are performed external to the network with ordinary PABX equipment. Clock information is passed across network boundaries in a token passing ring by preceeding the token with an idle period of non-transmission which allows the token to be used to re-establish a clock synchronized to the data. Provision is made to monitor and compensate the elastic receiving buffers so as to prevent them from overflowing or going empty.
An optimization method of VON mapping for energy efficiency and routing in elastic optical networks
NASA Astrophysics Data System (ADS)
Liu, Huanlin; Xiong, Cuilian; Chen, Yong; Li, Changping; Chen, Derun
2018-03-01
To improve resources utilization efficiency, network virtualization in elastic optical networks has been developed by sharing the same physical network for difference users and applications. In the process of virtual nodes mapping, longer paths between physical nodes will consume more spectrum resources and energy. To address the problem, we propose a virtual optical network mapping algorithm called genetic multi-objective optimize virtual optical network mapping algorithm (GM-OVONM-AL), which jointly optimizes the energy consumption and spectrum resources consumption in the process of virtual optical network mapping. Firstly, a vector function is proposed to balance the energy consumption and spectrum resources by optimizing population classification and crowding distance sorting. Then, an adaptive crossover operator based on hierarchical comparison is proposed to improve search ability and convergence speed. In addition, the principle of the survival of the fittest is introduced to select better individual according to the relationship of domination rank. Compared with the spectrum consecutiveness-opaque virtual optical network mapping-algorithm and baseline-opaque virtual optical network mapping algorithm, simulation results show the proposed GM-OVONM-AL can achieve the lowest bandwidth blocking probability and save the energy consumption.
Han, Biao; Chery, Daphney R; Yin, Jie; Lu, X Lucas; Lee, Daeyeon; Han, Lin
2016-01-28
This study investigates the roles of two distinct features of ionically cross-linked polyelectrolyte networks - ionic cross-links and fixed charges - in determining their nanomechanical properties. The layer-by-layer assembled poly(allylamine hydrochloride)/poly(acrylic acid) (PAH/PAA) network is used as the model material. The densities of ionic cross-links and fixed charges are modulated through solution pH and ionic strength (IS), and the swelling ratio, elastic and viscoelastic properties are quantified via an array of atomic force microscopy (AFM)-based nanomechanical tools. The roles of ionic cross-links are underscored by the distinctive elastic and viscoelastic nanomechanical characters observed here. First, as ionic cross-links are highly sensitive to solution conditions, the instantaneous modulus, E0, exhibits orders-of-magnitude changes upon pH- and IS-governed swelling, distinctive from the rubber elasticity prediction based on permanent covalent cross-links. Second, ionic cross-links can break and self-re-form, and this mechanism dominates force relaxation of PAH/PAA under a constant indentation depth. In most states, the degree of relaxation is >90%, independent of ionic cross-link density. The importance of fixed charges is highlighted by the unexpectedly more elastic nature of the network despite low ionic cross-link density at pH 2.0, IS 0.01 M. Here, the complex is a net charged, loosely cross-linked, where the degree of relaxation is attenuated to ≈50% due to increased elastic contribution arising from fixed charge-induced Donnan osmotic pressure. In addition, this study develops a new method for quantifying the thickness of highly swollen polymer hydrogel films. It also underscores important technical considerations when performing nanomechanical tests on highly rate-dependent polymer hydrogel networks. These results provide new insights into the nanomechanical characters of ionic polyelectrolyte complexes, and lay the ground for further investigation of their unique time-dependent properties.
Elastic network model of learned maintained contacts to predict protein motion
Putz, Ines
2017-01-01
We present a novel elastic network model, lmcENM, to determine protein motion even for localized functional motions that involve substantial changes in the protein’s contact topology. Existing elastic network models assume that the contact topology remains unchanged throughout the motion and are thus most appropriate to simulate highly collective function-related movements. lmcENM uses machine learning to differentiate breaking from maintained contacts. We show that lmcENM accurately captures functional transitions unexplained by the classical ENM and three reference ENM variants, while preserving the simplicity of classical ENM. We demonstrate the effectiveness of our approach on a large set of proteins covering different motion types. Our results suggest that accurately predicting a “deformation-invariant” contact topology offers a promising route to increase the general applicability of ENMs. We also find that to correctly predict this contact topology a combination of several features seems to be relevant which may vary slightly depending on the protein. Additionally, we present case studies of two biologically interesting systems, Ferric Citrate membrane transporter FecA and Arachidonate 15-Lipoxygenase. PMID:28854238
New optimization model for routing and spectrum assignment with nodes insecurity
NASA Astrophysics Data System (ADS)
Xuan, Hejun; Wang, Yuping; Xu, Zhanqi; Hao, Shanshan; Wang, Xiaoli
2017-04-01
By adopting the orthogonal frequency division multiplexing technology, elastic optical networks can provide the flexible and variable bandwidth allocation to each connection request and get higher spectrum utilization. The routing and spectrum assignment problem in elastic optical network is a well-known NP-hard problem. In addition, information security has received worldwide attention. We combine these two problems to investigate the routing and spectrum assignment problem with the guaranteed security in elastic optical network, and establish a new optimization model to minimize the maximum index of the used frequency slots, which is used to determine an optimal routing and spectrum assignment schemes. To solve the model effectively, a hybrid genetic algorithm framework integrating a heuristic algorithm into a genetic algorithm is proposed. The heuristic algorithm is first used to sort the connection requests and then the genetic algorithm is designed to look for an optimal routing and spectrum assignment scheme. In the genetic algorithm, tailor-made crossover, mutation and local search operators are designed. Moreover, simulation experiments are conducted with three heuristic strategies, and the experimental results indicate that the effectiveness of the proposed model and algorithm framework.
An Integrated Tensorial Approach for Quantifying Porous, Fractured Rocks
NASA Astrophysics Data System (ADS)
Healy, David; Rizzo, Roberto; Harland, Sophie; Farrell, Natalie; Browning, John; Meredith, Phil; Mitchell, Tom; Bubeck, Alodie; Walker, Richard
2017-04-01
The patterns of fractures in deformed rocks are rarely uniform or random. Fracture orientations, sizes, shapes and spatial distributions often exhibit some kind of order. In detail, there may be relationships among the different fracture attributes e.g. small fractures dominated by one orientation, and larger fractures by another. These relationships are important because the mechanical (e.g. strength, anisotropy) and transport (e.g. fluids, heat) properties of rock depend on these fracture patterns and fracture attributes. Based on previously published work (Oda, Cowin, Sayers & Kachanov) this presentation describes an integrated tensorial approach to quantifying fracture networks and predicting the key properties of fractured rock: permeability and elasticity (and in turn, seismic velocities). Each of these properties can be represented as tensors, and these entities capture the essential 'directionality', or anisotropy of the property. In structural geology, we are familiar with using tensors for stress and strain, where these concepts incorporate volume averaging of many forces (in the case of the stress tensor), or many displacements (for the strain tensor), to produce more tractable and more computationally efficient quantities. It is conceptually attractive to formulate both the structure (the fracture network) and the structure-dependent properties (permeability, elasticity) in a consistent way with tensors of 2nd and 4th rank, as appropriate. Examples are provided to highlight the interdependence of the property tensors with the geometry of the fracture network. The fabric tensor (or orientation tensor of Scheidegger, Woodcock) describes the orientation distribution of fractures in the network. The crack tensor combines the fabric tensor (orientation distribution) with information about the fracture density and fracture size distribution. Changes to the fracture network, manifested in the values of the fabric and crack tensors, translate into changes in predicted permeability and elasticity (seismic velocity). Conversely, this implies that measured changes in any of the in situ properties or responses in the subsurface (e.g. permeability, seismic velocity) could be used to predict, or at least constrain, the fracture network. Explicitly linking the fracture network geometry to the permeability and elasticity (seismic velocity) through a tensorial formulation provides an exciting and efficient alternative to existing approaches.
A machine learning approach for efficient uncertainty quantification using multiscale methods
NASA Astrophysics Data System (ADS)
Chan, Shing; Elsheikh, Ahmed H.
2018-02-01
Several multiscale methods account for sub-grid scale features using coarse scale basis functions. For example, in the Multiscale Finite Volume method the coarse scale basis functions are obtained by solving a set of local problems over dual-grid cells. We introduce a data-driven approach for the estimation of these coarse scale basis functions. Specifically, we employ a neural network predictor fitted using a set of solution samples from which it learns to generate subsequent basis functions at a lower computational cost than solving the local problems. The computational advantage of this approach is realized for uncertainty quantification tasks where a large number of realizations has to be evaluated. We attribute the ability to learn these basis functions to the modularity of the local problems and the redundancy of the permeability patches between samples. The proposed method is evaluated on elliptic problems yielding very promising results.
Surface-induced polymerization of actin.
Renault, A; Lenne, P F; Zakri, C; Aradian, A; Vénien-Bryan, C; Amblard, F
1999-01-01
Living cells contain a very large amount of membrane surface area, which potentially influences the direction, the kinetics, and the localization of biochemical reactions. This paper quantitatively evaluates the possibility that a lipid monolayer can adsorb actin from a nonpolymerizing solution, induce its polymerization, and form a 2D network of individual actin filaments, in conditions that forbid bulk polymerization. G- and F-actin solutions were studied beneath saturated Langmuir monolayers containing phosphatidylcholine (PC, neutral) and stearylamine (SA, a positively charged surfactant) at PC:SA = 3:1 molar ratio. Ellipsometry, tensiometry, shear elastic measurements, electron microscopy, and dark-field light microscopy were used to characterize the adsorption kinetics and the interfacial polymerization of actin. In all cases studied, actin follows a monoexponential reaction-limited adsorption with similar time constants (approximately 10(3) s). At a longer time scale the shear elasticity of the monomeric actin adsorbate increases only in the presence of lipids, to a 2D shear elastic modulus of mu approximately 30 mN/m, indicating the formation of a structure coupled to the monolayer. Electron microscopy shows the formation of a 2D network of actin filaments at the PC:SA surface, and several arguments strongly suggest that this network is indeed causing the observed elasticity. Adsorption of F-actin to PC:SA leads more quickly to a slightly more rigid interface with a modulus of mu approximately 50 mN/m. PMID:10049338
NASA Astrophysics Data System (ADS)
Skripnyak, Vladimir; Skripnyak, Evgeniya; Meyer, Lothar W.; Herzig, Norman; Skripnyak, Nataliya
2012-02-01
Researches of the last years have allowed to establish that the laws of deformation and fracture of bulk ultrafine-grained and coarse-grained materials are various both in static and in dynamic loading conditions. Development of adequate constitutive equations for the description of mechanical behavior of bulk ultrafine-grained materials at intensive dynamic influences is complicated in consequence of insufficient knowledge about general rules of inelastic deformation and nucleation and growth of cracks. Multi-scale computational model was used for the investigation of deformation and fracture of bulk structured aluminum and magnesium alloys under stress pulse loadings on mesoscale level. The increment of plastic deformation is defined by the sum of the increments caused by a nucleation and gliding of dislocations, the twinning, meso-blocks movement, and grain boundary sliding. The model takes into account the influence on mechanical properties of alloys an average grains size, grain sizes distribution of and concentration of precipitates. It was obtained the nucleation and gliding of dislocations caused the high attenuation rate of the elastic precursor of ultrafine-grained alloys than in coarse grained counterparts.
Form finding in elastic gridshells.
Baek, Changyeob; Sageman-Furnas, Andrew O; Jawed, Mohammad K; Reis, Pedro M
2018-01-02
Elastic gridshells comprise an initially planar network of elastic rods that are actuated into a shell-like structure by loading their extremities. The resulting actuated form derives from the elastic buckling of the rods subjected to inextensibility. We study elastic gridshells with a focus on the rational design of the final shapes. Our precision desktop experiments exhibit complex geometries, even from seemingly simple initial configurations and actuation processes. The numerical simulations capture this nonintuitive behavior with excellent quantitative agreement, allowing for an exploration of parameter space that reveals multistable states. We then turn to the theory of smooth Chebyshev nets to address the inverse design of hemispherical elastic gridshells. The results suggest that rod inextensibility, not elastic response, dictates the zeroth-order shape of an actuated elastic gridshell. As it turns out, this is the shape of a common household strainer. Therefore, the geometry of Chebyshev nets can be further used to understand elastic gridshells. In particular, we introduce a way to quantify the intrinsic shape of the empty, but enclosed regions, which we then use to rationalize the nonlocal deformation of elastic gridshells to point loading. This justifies the observed difficulty in form finding. Nevertheless, we close with an exploration of concatenating multiple elastic gridshell building blocks.
Form finding in elastic gridshells
NASA Astrophysics Data System (ADS)
Baek, Changyeob; Sageman-Furnas, Andrew O.; Jawed, Mohammad K.; Reis, Pedro M.
2018-01-01
Elastic gridshells comprise an initially planar network of elastic rods that are actuated into a shell-like structure by loading their extremities. The resulting actuated form derives from the elastic buckling of the rods subjected to inextensibility. We study elastic gridshells with a focus on the rational design of the final shapes. Our precision desktop experiments exhibit complex geometries, even from seemingly simple initial configurations and actuation processes. The numerical simulations capture this nonintuitive behavior with excellent quantitative agreement, allowing for an exploration of parameter space that reveals multistable states. We then turn to the theory of smooth Chebyshev nets to address the inverse design of hemispherical elastic gridshells. The results suggest that rod inextensibility, not elastic response, dictates the zeroth-order shape of an actuated elastic gridshell. As it turns out, this is the shape of a common household strainer. Therefore, the geometry of Chebyshev nets can be further used to understand elastic gridshells. In particular, we introduce a way to quantify the intrinsic shape of the empty, but enclosed regions, which we then use to rationalize the nonlocal deformation of elastic gridshells to point loading. This justifies the observed difficulty in form finding. Nevertheless, we close with an exploration of concatenating multiple elastic gridshell building blocks.
NASA Astrophysics Data System (ADS)
Beller, S.; Monteiller, V.; Combe, L.; Operto, S.; Nolet, G.
2018-02-01
Full-waveform inversion (FWI) is not yet a mature imaging technology for lithospheric imaging from teleseismic data. Therefore, its promise and pitfalls need to be assessed more accurately according to the specifications of teleseismic experiments. Three important issues are related to (1) the choice of the lithospheric parametrization for optimization and visualization, (2) the initial model and (3) the acquisition design, in particular in terms of receiver spread and sampling. These three issues are investigated with a realistic synthetic example inspired by the CIFALPS experiment in the Western Alps. Isotropic elastic FWI is implemented with an adjoint-state formalism and aims to update three parameter classes by minimization of a classical least-squares difference-based misfit function. Three different subsurface parametrizations, combining density (ρ) with P and S wave speeds (Vp and Vs) , P and S impedances (Ip and Is), or elastic moduli (λ and μ) are first discussed based on their radiation patterns before their assessment by FWI. We conclude that the (ρ, λ, μ) parametrization provides the FWI models that best correlate with the true ones after recombining a posteriori the (ρ, λ, μ) optimization parameters into Ip and Is. Owing to the low frequency content of teleseismic data, 1-D reference global models as PREM provide sufficiently accurate initial models for FWI after smoothing that is necessary to remove the imprint of the layering. Two kinds of station deployments are assessed: coarse areal geometry versus dense linear one. We unambiguously conclude that a coarse areal geometry should be favoured as it dramatically increases the penetration in depth of the imaging as well as the horizontal resolution. This results because the areal geometry significantly increases local wavenumber coverage, through a broader sampling of the scattering and dip angles, compared to a linear deployment.
Embrittlement of Intercritically Reheated Coarse Grain Heat-Affected Zone of ASTM4130 Steel
NASA Astrophysics Data System (ADS)
Li, Liying; Han, Tao; Han, Bin
2018-04-01
In this investigation, a thermal welding simulation technique was used to investigate the microstructures and mechanical properties of the intercritically reheated coarse grain heat-affected zone (IR CGHAZ) of ASTM4130 steel. The effect of post weld heat treatment (PWHT) on the toughness of IR CGHAZ was also analyzed. The toughness of IR CGHAZ was measured by means of Charpy impact, and it is found that IR CGHAZ has the lowest toughness which is much lower than that of the base metal regardless of whether PWHT is applied or not. The as-welded IR CGHAZ is mainly composed of ferrite, martensite, and many blocky M-A constituents distributing along grain boundaries and subgrain boundaries in a near-connected network. Also, the prior austenite grains are still as coarse as those in the coarse grain heat-affected zone (CGHAZ). The presence of the blocky M-A constituents and the coarsened austenite grains result in the toughness deterioration of the as-welded IR CGHAZ. Most of the blocky M-A constituents are decomposed to granular bainite due to the effect of the PWHT. However, PWHT cannot refine the prior austenite grains. Thus, the low toughness of IR CGHAZ after PWHT can be attributed to two factors, i.e., the coarsened austenite grains, and the presence of the remaining M-A constituents and granular bainite, which are located at grain boundaries and subgrain boundaries in a near-connected network. The absorbed energy of the IR CGHAZ was increased by about 3.75 times, which means that the PWHT can effectively improve the toughness but it cannot be recovered to the level of base metal.
Nguyen, Thanh-Son; Selinger, Jonathan V
2017-09-01
In liquid crystal elastomers and polymer networks, the orientational order of liquid crystals is coupled with elastic distortions of crosslinked polymers. Previous theoretical research has described these materials through two different approaches: a neoclassical theory based on the liquid crystal director and the deformation gradient tensor, and a geometric elasticity theory based on the difference between the actual metric tensor and a reference metric. Here, we connect those two approaches using a formalism based on differential geometry. Through this connection, we determine how both the director and the geometry respond to a change of temperature.
Jo, Sunhwan; Bahar, Ivet; Roux, Benoît
2014-01-01
Biomolecular conformational transitions are essential to biological functions. Most experimental methods report on the long-lived functional states of biomolecules, but information about the transition pathways between these stable states is generally scarce. Such transitions involve short-lived conformational states that are difficult to detect experimentally. For this reason, computational methods are needed to produce plausible hypothetical transition pathways that can then be probed experimentally. Here we propose a simple and computationally efficient method, called ANMPathway, for constructing a physically reasonable pathway between two endpoints of a conformational transition. We adopt a coarse-grained representation of the protein and construct a two-state potential by combining two elastic network models (ENMs) representative of the experimental structures resolved for the endpoints. The two-state potential has a cusp hypersurface in the configuration space where the energies from both the ENMs are equal. We first search for the minimum energy structure on the cusp hypersurface and then treat it as the transition state. The continuous pathway is subsequently constructed by following the steepest descent energy minimization trajectories starting from the transition state on each side of the cusp hypersurface. Application to several systems of broad biological interest such as adenylate kinase, ATP-driven calcium pump SERCA, leucine transporter and glutamate transporter shows that ANMPathway yields results in good agreement with those from other similar methods and with data obtained from all-atom molecular dynamics simulations, in support of the utility of this simple and efficient approach. Notably the method provides experimentally testable predictions, including the formation of non-native contacts during the transition which we were able to detect in two of the systems we studied. An open-access web server has been created to deliver ANMPathway results. PMID:24699246
Benefit of adaptive FEC in shared backup path protected elastic optical network.
Guo, Hong; Dai, Hua; Wang, Chao; Li, Yongcheng; Bose, Sanjay K; Shen, Gangxiang
2015-07-27
We apply an adaptive forward error correction (FEC) allocation strategy to an Elastic Optical Network (EON) operated with shared backup path protection (SBPP). To maximize the protected network capacity that can be carried, an Integer Linear Programing (ILP) model and a spectrum window plane (SWP)-based heuristic algorithm are developed. Simulation results show that the FEC coding overhead required by the adaptive FEC scheme is significantly lower than that needed by a fixed FEC allocation strategy resulting in higher network capacity for the adaptive strategy. The adaptive FEC allocation strategy can also significantly outperform the fixed FEC allocation strategy both in terms of the spare capacity redundancy and the average FEC coding overhead needed per optical channel. The proposed heuristic algorithm is efficient and not only performs closer to the ILP model but also does much better than the shortest-path algorithm.
Generalized networking engineering: optimal pricing and routing in multiservice networks
NASA Astrophysics Data System (ADS)
Mitra, Debasis; Wang, Qiong
2002-07-01
One of the functions of network engineering is to allocate resources optimally to forecasted demand. We generalize the mechanism by incorporating price-demand relationships into the problem formulation, and optimizing pricing and routing jointly to maximize total revenue. We consider a network, with fixed topology and link bandwidths, that offers multiple services, such as voice and data, each having characteristic price elasticity of demand, and quality of service and policy requirements on routing. Prices, which depend on service type and origin-destination, determine demands, that are routed, subject to their constraints, so as to maximize revenue. We study the basic properties of the optimal solution and prove that link shadow costs provide the basis for both optimal prices and optimal routing policies. We investigate the impact of input parameters, such as link capacities and price elasticities, on prices, demand growth, and routing policies. Asymptotic analyses, in which network bandwidth is scaled to grow, give results that are noteworthy for their qualitative insights. Several numerical examples illustrate the analyses.
Mechanical and structural model of fractal networks of fat crystals at low deformations.
Narine, S S; Marangoni, A G
1999-12-01
Fat-crystal networks demonstrate viscoelastic behavior at very small deformations. A structural model of these networks is described and supported by polarized light and atomic-force microscopy. A mechanical model is described which allows the shear elastic modulus (G') of the system to be correlated with forces acting within the network. The fractal arrangement of the network at certain length scales is taken into consideration. It is assumed that the forces acting are due to van der Waals forces. The final expression for G' is related to the volume fraction of solid fat (Phi) via the mass fractal dimension (D) of the network, which agrees with the experimental verification of the scaling behavior of fat-crystal networks [S. S. Narine and A. G. Marangoni, Phys. Rev. E 59, 1908 (1999)]. G' was also found to be inversely proportional to the diameter of the primary particles (sigma approximately equal to 6 microm) within the network (microstructural elements) as well as to the diameter of the microstructures (xi approximately equal to 100 microm) and inversely proportional to the cube of the intermicrostructural element distance (d(0)). This formulation of the elastic modulus agrees well with experimental observations.
Yang, Yali; Bai, Mo; Klug, William S.; Levine, Alex J.
2012-01-01
We determine the time- and force-dependent viscoelastic responses of reconstituted networks of microtubules that have been strongly crosslinked by biotin-streptavidin bonds. To measure the microscale viscoelasticity of such networks, we use a magnetic tweezers device to apply localized forces. At short time scales, the networks respond nonlinearly to applied force, with stiffening at small forces, followed by a reduction in the stiffening response at high forces, which we attribute to the force-induced unbinding of crosslinks. At long time scales, force-induced bond unbinding leads to local network rearrangement and significant bead creep. Interestingly, the network retains its elastic modulus even under conditions of significant plastic flow, suggesting that crosslinker breakage is balanced by the formation of new bonds. To better understand this effect, we developed a finite element model of such a stiff filament network with labile crosslinkers obeying force-dependent Bell model unbinding dynamics. The coexistence of dissipation, due to bond breakage, and the elastic recovery of the network is possible because each filament has many crosslinkers. Recovery can occur as long as a sufficient number of the original crosslinkers are preserved under the loading period. When these remaining original crosslinkers are broken, plastic flow results. PMID:23577042
Breaking a virus: Identifying molecular level failure modes of a viral capsid by multiscale modeling
NASA Astrophysics Data System (ADS)
Krishnamani, V.; Globisch, C.; Peter, C.; Deserno, M.
2016-10-01
We use coarse-grained (CG) simulations to study the deformation of empty Cowpea Chlorotic Mottle Virus (CCMV) capsids under uniaxial compression, from the initial elastic response up to capsid breakage. Our CG model is based on the MARTINI force field and has been amended by a stabilizing elastic network, acting only within individual proteins, that was tuned to capture the fluctuation spectrum of capsid protein dimers, obtained from all atom simulations. We have previously shown that this model predicts force-compression curves that match AFM indentation experiments on empty CCMV capsids. Here we investigate details of the actual breaking events when the CCMV capsid finally fails. We present a symmetry classification of all relevant protein contacts and show that they differ significantly in terms of stability. Specifically, we show that interfaces which break readily are precisely those which are believed to form last during assembly, even though some of them might share the same contacts as other non-breaking interfaces. In particular, the interfaces that form pentamers of dimers never break, while the virtually identical interfaces within hexamers of dimers readily do. Since these units differ in the large-scale geometry and, most noticeably, the cone-angle at the center of the 5- or 6-fold vertex, we propose that the hexameric unit fails because it is pre-stressed. This not only suggests that hexamers of dimers form less frequently during the early stages of assembly; it also offers a natural explanation for the well-known β-barrel motif at the hexameric center as a post-aggregation stabilization mechanism. Finally, we identify those amino acid contacts within all key protein interfaces that are most persistent during compressive deformation of the capsid, thereby providing potential targets for mutation studies aiming to elucidate the key contacts upon which overall stability rests.
Transient response of nonlinear polymer networks: A kinetic theory
NASA Astrophysics Data System (ADS)
Vernerey, Franck J.
2018-06-01
Dynamic networks are found in a majority of natural materials, but also in engineering materials, such as entangled polymers and physically cross-linked gels. Owing to their transient bond dynamics, these networks display a rich class of behaviors, from elasticity, rheology, self-healing, or growth. Although classical theories in rheology and mechanics have enabled us to characterize these materials, there is still a gap in our understanding on how individuals (i.e., the mechanics of each building blocks and its connection with others) affect the emerging response of the network. In this work, we introduce an alternative way to think about these networks from a statistical point of view. More specifically, a network is seen as a collection of individual polymer chains connected by weak bonds that can associate and dissociate over time. From the knowledge of these individual chains (elasticity, transient attachment, and detachment events), we construct a statistical description of the population and derive an evolution equation of their distribution based on applied deformation and their local interactions. We specifically concentrate on nonlinear elastic response that follows from the strain stiffening response of individual chains of finite size. Upon appropriate averaging operations and using a mean field approximation, we show that the distribution can be replaced by a so-called chain distribution tensor that is used to determine important macroscopic measures such as stress, energy storage and dissipation in the network. Prediction of the kinetic theory are then explored against known experimental measurement of polymer responses under uniaxial loading. It is found that even under the simplest assumptions of force-independent chain kinetics, the model is able to reproduce complex time-dependent behaviors of rubber and self-healing supramolecular polymers.
NASA Astrophysics Data System (ADS)
Franciosi, Patrick; Spagnuolo, Mario; Salman, Oguz Umut
2018-04-01
Composites comprising included phases in a continuous matrix constitute a huge class of meta-materials, whose effective properties, whether they be mechanical, physical or coupled, can be selectively optimized by using appropriate phase arrangements and architectures. An important subclass is represented by "network-reinforced matrices," say those materials in which one or more of the embedded phases are co-continuous with the matrix in one or more directions. In this article, we present a method to study effective properties of simple such structures from which more complex ones can be accessible. Effective properties are shown, in the framework of linear elasticity, estimable by using the global mean Green operator for the entire embedded fiber network which is by definition through sample spanning. This network operator is obtained from one of infinite planar alignments of infinite fibers, which the network can be seen as an interpenetrated set of, with the fiber interactions being fully accounted for in the alignments. The mean operator of such alignments is given in exact closed form for isotropic elastic-like or dielectric-like matrices. We first exemplify how these operators relevantly provide, from classic homogenization frameworks, effective properties in the case of 1D fiber bundles embedded in an isotropic elastic-like medium. It is also shown that using infinite patterns with fully interacting elements over their whole influence range at any element concentration suppresses the dilute approximation limit of these frameworks. We finally present a construction method for a global operator of fiber networks described as interpenetrated such bundles.
Cognitive-Developmental Learning for a Humanoid Robot: A Caregiver’s Gift
2004-05-01
system . We propose a real- time algorithm to infer depth and build 3-dimensional coarse maps for objects through the analysis of cues provided by an... system is well defined at the boundary of these regions (although the derivatives are not). A time domain analysis is presented for a piece-linear... Analysis of Multivariable Systems ......................... 266 D.3.1 Networks of Multiple Neural Oscillators ................. 266 D.3.2 Networks of
All-optical OXC transition strategy from WDM optical network to elastic optical network.
Chen, Xin; Li, Juhao; Guo, Bingli; Zhu, Paikun; Tang, Ruizhi; Chen, Zhangyuan; He, Yongqi
2016-02-22
Elastic optical network (EON) has been proposed recently as a spectrum-efficient optical layer to adapt to rapidly-increasing traffic demands instead of current deployed wavelength-division-multiplexing (WDM) optical network. In contrast with conventional WDM optical cross-connect (OXCs) based on wavelength selective switches (WSSs), the EON OXCs are based on spectrum selective switches (SSSs) which are much more expensive than WSSs, especially for large-scale switching architectures. So the transition cost from WDM OXCs to EON OXCs is a major obstacle to realizing EON. In this paper, we propose and experimentally demonstrate a transition OXC (TOXC) structure based on 2-stage cascading switching architectures, which make full use of available WSSs in current deployed WDM OXCs to reduce number and port count of required SSSs. Moreover, we propose a contention-aware spectrum allocation (CASA) scheme for EON built with the proposed TOXCs. We show by simulation that the TOXCs reduce the network capital expenditure transiting from WDM optical network to EON about 50%, with a minor traffic blocking performance degradation and about 10% accommodated traffic number detriment compared with all-SSS EON OXC architectures.
NASA Astrophysics Data System (ADS)
Ratnam, T. C.; Ghosh, D. P.; Negash, B. M.
2018-05-01
Conventional reservoir modeling employs variograms to predict the spatial distribution of petrophysical properties. This study aims to improve property distribution by incorporating elastic wave properties. In this study, elastic wave properties obtained from seismic inversion are used as input for an artificial neural network to predict neutron porosity in between well locations. The method employed in this study is supervised learning based on available well logs. This method converts every seismic trace into a pseudo-well log, hence reducing the uncertainty between well locations. By incorporating the seismic response, the reliance on geostatistical methods such as variograms for the distribution of petrophysical properties is reduced drastically. The results of the artificial neural network show good correlation with the neutron porosity log which gives confidence for spatial prediction in areas where well logs are not available.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Merijs-Meri, Remo; Zicans, Janis; Ivanova, Tatjana
2014-05-15
Styrene acrylate polymer (SAC) nanocomposites with various carbon nanofillers (multiwalled carbon nanotubes MWCNTs and onion like carbon OLC) are manufactured by means of latex based routes. Concentration of the carbon nanofillers is changed in a broad interval starting from 0.01 up to 10 wt. %. Elastic, dielectric and electromagnetic properties of SAC nanocomposites are investigated. Elastic modulus, electrical conductivity and electromagnetic radiation absorption of the investigated SAC nanocomposites increase along with rising nanofiller content. The effect of the addition of anisometric MWCNTs on the elastic properties of the composite is higher than in the case of the addition of OLC.more » Higher electrical conductivity of the OLC containing nanocomposites is explained with the fact that reasonable agglomeration of the nanofiller can promote the development of electrically conductive network. Efficiency of the absorption of electromagnetic radiation depends on the development of conductive network within the SAC matrix.« less
Compressed glassy carbon: An ultrastrong and elastic interpenetrating graphene network
Hu, Meng; He, Julong; Zhao, Zhisheng; Strobel, Timothy A.; Hu, Wentao; Yu, Dongli; Sun, Hao; Liu, Lingyu; Li, Zihe; Ma, Mengdong; Kono, Yoshio; Shu, Jinfu; Mao, Ho-kwang; Fei, Yingwei; Shen, Guoyin; Wang, Yanbin; Juhl, Stephen J.; Huang, Jian Yu; Liu, Zhongyuan; Xu, Bo; Tian, Yongjun
2017-01-01
Carbon’s unique ability to have both sp2 and sp3 bonding states gives rise to a range of physical attributes, including excellent mechanical and electrical properties. We show that a series of lightweight, ultrastrong, hard, elastic, and conductive carbons are recovered after compressing sp2-hybridized glassy carbon at various temperatures. Compression induces the local buckling of graphene sheets through sp3 nodes to form interpenetrating graphene networks with long-range disorder and short-range order on the nanometer scale. The compressed glassy carbons have extraordinary specific compressive strengths—more than two times that of commonly used ceramics—and simultaneously exhibit robust elastic recovery in response to local deformations. This type of carbon is an optimal ultralight, ultrastrong material for a wide range of multifunctional applications, and the synthesis methodology demonstrates potential to access entirely new metastable materials with exceptional properties. PMID:28630918
Morris, Ralph; Koo, Bonyoung; Yarwood, Greg
2005-11-01
Version 4.10s of the comprehensive air-quality model with extensions (CAMx) photochemical grid model has been developed, which includes two options for representing particulate matter (PM) size distribution: (1) a two-section representation that consists of fine (PM2.5) and coarse (PM2.5-10) modes that has no interactions between the sections and assumes all of the secondary PM is fine; and (2) a multisectional representation that divides the PM size distribution into N sections (e.g., N = 10) and simulates the mass transfer between sections because of coagulation, accumulation, evaporation, and other processes. The model was applied to Southern California using the two-section and multisection representation of PM size distribution, and we found that allowing secondary PM to grow into the coarse mode had a substantial effect on PM concentration estimates. CAMx was then applied to the Western United States for the 1996 annual period with a 36-km grid resolution using both the two-section and multisection PM representation. The Community Multiscale Air Quality (CMAQ) and Regional Modeling for Aerosol and Deposition (REMSAD) models were also applied to the 1996 annual period. Similar model performance was exhibited by the four models across the Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network monitoring networks. All four of the models exhibited fairly low annual bias for secondary PM sulfate and nitrate but with a winter overestimation and summer underestimation bias. The CAMx multisectional model estimated that coarse mode secondary sulfate and nitrate typically contribute <10% of the total sulfate and nitrate when averaged across the more rural IMPROVE monitoring network.
Badiei, N; Sowedan, A M; Curtis, D J; Brown, M R; Lawrence, M J; Campbell, A I; Sabra, A; Evans, P A; Weisel, J W; Chernysh, I N; Nagaswami, C; Williams, P R; Hawkins, K
2015-01-01
Incipient clot formation in whole blood and fibrin gels was studied by the rheometric techniques of controlled stress parallel superposition (CSPS) and small amplitude oscillatory shear (SAOS). The effects of unidirectional shear stress on incipient clot microstructure, formation kinetics and elasticity are reported in terms of the fractal dimension (df) of the fibrin network, the gel network formation time (TGP) and the shear elastic modulus, respectively. The results of this first haemorheological application of CSPS reveal the marked sensitivity of incipient clot microstructure to physiologically relevant levels of shear stress, these being an order of magnitude lower than have previously been studied by SAOS. CSPS tests revealed that exposure of forming clots to increasing levels of shear stress produces a corresponding elevation in df, consistent with the formation of tighter, more compact clot microstructures under unidirectional flow. A corresponding increase in shear elasticity was recorded. The scaling relationship established between shear elasticity and df for fibrin clots and whole blood confirms the fibrin network as the dominant microstructural component of the incipient clot in terms of its response to imposed stress. Supplementary studies of fibrin clot formation by rheometry and microscopy revealed the substantial additional network mass required to increase df and provide evidence to support the hypothesis that microstructural changes in blood clotted under unidirectional shear may be attributed to flow enhanced thrombin generation and activation. CSPS also identified a threshold value of unidirectional shear stress above which no incipient clot formation could be detected. CSPS was shown to be a valuable haemorheological tool for the study of the effects of physiological and pathological levels of shear on clot properties.
New Coarse-Grained Model and Its Implementation in Simulations of Graphene Assemblies.
Shang, Jun-Jun; Yang, Qing-Sheng; Liu, Xia
2017-08-08
Graphene is a one-atom thick layer of carbon atoms arranged in a hexagonal pattern, which makes it the strongest material in the world. The Tersoff potential is a suitable potential for simulating the mechanical behavior of the complex covalently bonded system of graphene. In this paper, we describe a new coarse-grained (CG) potential, TersoffCG, which is based on the function form of the Tersoff potential. The TersoffCG applies to a CG model of graphene that uses the same hexagonal pattern as the atomistic model. The parameters of the TersoffCG potential are determined using structural feature and potential-energy fitting between the CG model and the atomic model. The modeling process of graphene is highly simplified using the present CG model as it avoids the necessity to define bonds/angles/dihedrals connectivity. What is more, the present CG model provides a new perspective of coarse-graining scheme for crystal structures of nanomaterials. The structural changes and mechanical properties of multilayer graphene were calculated using the new potential. Furthermore, a CG model of a graphene aerogel was built in a specific form of assembly. The chemical bonding in the joints of graphene-aerogel forms automatically during the energy relaxation process. The compressive and recover test of the graphene aerogel was reproduced to study its high elasticity. Our computational examples show that the TersoffCG potential can be used for simulations of graphene and its assemblies, which have many applications in areas of environmental protection, aerospace engineering, and others.
Evaluation of the use of a singularity element in finite element analysis of center-cracked plates
NASA Technical Reports Server (NTRS)
Mendelson, A.; Gross, B.; Srawley, J., E.
1972-01-01
Two different methods are applied to the analyses of finite width linear elastic plates with central cracks. Both methods give displacements as a primary part of the solution. One method makes use of Fourier transforms. The second method employs a coarse mesh of triangular second-order finite elements in conjunction with a single singularity element subjected to appropriate additional constraints. The displacements obtained by these two methods are in very good agreement. The results suggest considerable potential for the use of a cracked element for related crack problems, particularly in connection with the extension to nonlinear material behavior.
Definition of the persistence length in the coarse-grained models of DNA elasticity.
Fathizadeh, A; Eslami-Mossallam, B; Ejtehadi, M R
2012-11-01
By considering the detailed structure of DNA in the base pair level, two possible definitions of the persistence length are compared. One definition is related to the orientation of the terminal base pairs, and the other is based on the vectors which connect two adjacent base pairs at each end of the molecule. It is shown that although these definitions approach each other for long DNA molecules, they are dramatically different on short length scales. We show analytically that the difference mostly comes from the shear flexibility of the molecule and can be used to measure the shear modulus of DNA.
Effects of the interaction range on structural phases of flexible polymers.
Gross, J; Neuhaus, T; Vogel, T; Bachmann, M
2013-02-21
We systematically investigate how the range of interaction between non-bonded monomers influences the formation of structural phases of elastic, flexible polymers. Massively parallel replica-exchange simulations of a generic, coarse-grained model, performed partly on graphics processing units and in multiple-gaussian modified ensembles, pave the way for the construction of the structural phase diagram, parametrized by interaction range and temperature. Conformational transitions between gas-like, liquid, and diverse solid (pseudo) phases are identified by microcanonical statistical inflection-point analysis. We find evidence for finite-size effects that cause the crossover of "collapse" and "freezing" transitions for very short interaction ranges.
Topology determines force distributions in one-dimensional random spring networks.
Heidemann, Knut M; Sageman-Furnas, Andrew O; Sharma, Abhinav; Rehfeldt, Florian; Schmidt, Christoph F; Wardetzky, Max
2018-02-01
Networks of elastic fibers are ubiquitous in biological systems and often provide mechanical stability to cells and tissues. Fiber-reinforced materials are also common in technology. An important characteristic of such materials is their resistance to failure under load. Rupture occurs when fibers break under excessive force and when that failure propagates. Therefore, it is crucial to understand force distributions. Force distributions within such networks are typically highly inhomogeneous and are not well understood. Here we construct a simple one-dimensional model system with periodic boundary conditions by randomly placing linear springs on a circle. We consider ensembles of such networks that consist of N nodes and have an average degree of connectivity z but vary in topology. Using a graph-theoretical approach that accounts for the full topology of each network in the ensemble, we show that, surprisingly, the force distributions can be fully characterized in terms of the parameters (N,z). Despite the universal properties of such (N,z) ensembles, our analysis further reveals that a classical mean-field approach fails to capture force distributions correctly. We demonstrate that network topology is a crucial determinant of force distributions in elastic spring networks.
Topology determines force distributions in one-dimensional random spring networks
NASA Astrophysics Data System (ADS)
Heidemann, Knut M.; Sageman-Furnas, Andrew O.; Sharma, Abhinav; Rehfeldt, Florian; Schmidt, Christoph F.; Wardetzky, Max
2018-02-01
Networks of elastic fibers are ubiquitous in biological systems and often provide mechanical stability to cells and tissues. Fiber-reinforced materials are also common in technology. An important characteristic of such materials is their resistance to failure under load. Rupture occurs when fibers break under excessive force and when that failure propagates. Therefore, it is crucial to understand force distributions. Force distributions within such networks are typically highly inhomogeneous and are not well understood. Here we construct a simple one-dimensional model system with periodic boundary conditions by randomly placing linear springs on a circle. We consider ensembles of such networks that consist of N nodes and have an average degree of connectivity z but vary in topology. Using a graph-theoretical approach that accounts for the full topology of each network in the ensemble, we show that, surprisingly, the force distributions can be fully characterized in terms of the parameters (N ,z ) . Despite the universal properties of such (N ,z ) ensembles, our analysis further reveals that a classical mean-field approach fails to capture force distributions correctly. We demonstrate that network topology is a crucial determinant of force distributions in elastic spring networks.
Reduced-Order Modeling for Flutter/LCO Using Recurrent Artificial Neural Network
NASA Technical Reports Server (NTRS)
Yao, Weigang; Liou, Meng-Sing
2012-01-01
The present study demonstrates the efficacy of a recurrent artificial neural network to provide a high fidelity time-dependent nonlinear reduced-order model (ROM) for flutter/limit-cycle oscillation (LCO) modeling. An artificial neural network is a relatively straightforward nonlinear method for modeling an input-output relationship from a set of known data, for which we use the radial basis function (RBF) with its parameters determined through a training process. The resulting RBF neural network, however, is only static and is not yet adequate for an application to problems of dynamic nature. The recurrent neural network method [1] is applied to construct a reduced order model resulting from a series of high-fidelity time-dependent data of aero-elastic simulations. Once the RBF neural network ROM is constructed properly, an accurate approximate solution can be obtained at a fraction of the cost of a full-order computation. The method derived during the study has been validated for predicting nonlinear aerodynamic forces in transonic flow and is capable of accurate flutter/LCO simulations. The obtained results indicate that the present recurrent RBF neural network is accurate and efficient for nonlinear aero-elastic system analysis
Pandey, R B; Farmer, B L
2014-11-07
Multi-scale aggregation to network formation of interacting proteins (H3.1) are examined by a knowledge-based coarse-grained Monte Carlo simulation as a function of temperature and the number of protein chains, i.e., the concentration of the protein. Self-assembly of corresponding homo-polymers of constitutive residues (Cys, Thr, and Glu) with extreme residue-residue interactions, i.e., attractive (Cys-Cys), neutral (Thr-Thr), and repulsive (Glu-Glu), are also studied for comparison with the native protein. Visual inspections show contrast and similarity in morphological evolutions of protein assembly, aggregation of small aggregates to a ramified network from low to high temperature with the aggregation of a Cys-polymer, and an entangled network of Glu and Thr polymers. Variations in mobility profiles of residues with the concentration of the protein suggest that the segmental characteristic of proteins is altered considerably by the self-assembly from that in its isolated state. The global motion of proteins and Cys polymer chains is enhanced by their interacting network at the low temperature where isolated chains remain quasi-static. Transition from globular to random coil transition, evidenced by the sharp variation in the radius of gyration, of an isolated protein is smeared due to self-assembly of interacting networks of many proteins. Scaling of the structure factor S(q) with the wave vector q provides estimates of effective dimension D of the mass distribution at multiple length scales in self-assembly. Crossover from solid aggregates (D ∼ 3) at low temperature to a ramified fibrous network (D ∼ 2) at high temperature is observed for the protein H3.1 and Cys polymers in contrast to little changes in mass distribution (D ∼ 1.6) of fibrous Glu- and Thr-chain configurations.
NASA Astrophysics Data System (ADS)
Pandey, R. B.; Farmer, B. L.
2014-11-01
Multi-scale aggregation to network formation of interacting proteins (H3.1) are examined by a knowledge-based coarse-grained Monte Carlo simulation as a function of temperature and the number of protein chains, i.e., the concentration of the protein. Self-assembly of corresponding homo-polymers of constitutive residues (Cys, Thr, and Glu) with extreme residue-residue interactions, i.e., attractive (Cys-Cys), neutral (Thr-Thr), and repulsive (Glu-Glu), are also studied for comparison with the native protein. Visual inspections show contrast and similarity in morphological evolutions of protein assembly, aggregation of small aggregates to a ramified network from low to high temperature with the aggregation of a Cys-polymer, and an entangled network of Glu and Thr polymers. Variations in mobility profiles of residues with the concentration of the protein suggest that the segmental characteristic of proteins is altered considerably by the self-assembly from that in its isolated state. The global motion of proteins and Cys polymer chains is enhanced by their interacting network at the low temperature where isolated chains remain quasi-static. Transition from globular to random coil transition, evidenced by the sharp variation in the radius of gyration, of an isolated protein is smeared due to self-assembly of interacting networks of many proteins. Scaling of the structure factor S(q) with the wave vector q provides estimates of effective dimension D of the mass distribution at multiple length scales in self-assembly. Crossover from solid aggregates (D ˜ 3) at low temperature to a ramified fibrous network (D ˜ 2) at high temperature is observed for the protein H3.1 and Cys polymers in contrast to little changes in mass distribution (D ˜ 1.6) of fibrous Glu- and Thr-chain configurations.
Towards the understanding of network information processing in biology
NASA Astrophysics Data System (ADS)
Singh, Vijay
Living organisms perform incredibly well in detecting a signal present in the environment. This information processing is achieved near optimally and quite reliably, even though the sources of signals are highly variable and complex. The work in the last few decades has given us a fair understanding of how individual signal processing units like neurons and cell receptors process signals, but the principles of collective information processing on biological networks are far from clear. Information processing in biological networks, like the brain, metabolic circuits, cellular-signaling circuits, etc., involves complex interactions among a large number of units (neurons, receptors). The combinatorially large number of states such a system can exist in makes it impossible to study these systems from the first principles, starting from the interactions between the basic units. The principles of collective information processing on such complex networks can be identified using coarse graining approaches. This could provide insights into the organization and function of complex biological networks. Here I study models of biological networks using continuum dynamics, renormalization, maximum likelihood estimation and information theory. Such coarse graining approaches identify features that are essential for certain processes performed by underlying biological networks. We find that long-range connections in the brain allow for global scale feature detection in a signal. These also suppress the noise and remove any gaps present in the signal. Hierarchical organization with long-range connections leads to large-scale connectivity at low synapse numbers. Time delays can be utilized to separate a mixture of signals with temporal scales. Our observations indicate that the rules in multivariate signal processing are quite different from traditional single unit signal processing.
Keratin sponge/hydrogel II, active agent delivery
USDA-ARS?s Scientific Manuscript database
Keratin sponge/hydrogels from oxidation and reduction hydrolysis of fine and coarse wool fibers were formed to behave as cationic hydrogels to swell and release active agents in the specific region of the gastro-intestinal (GI) tract. Their porous, interpenetrating networks (IPN) were effective for...
Novel model of a AlGaN/GaN high electron mobility transistor based on an artificial neural network
NASA Astrophysics Data System (ADS)
Cheng, Zhi-Qun; Hu, Sha; Liu, Jun; Zhang, Qi-Jun
2011-03-01
In this paper we present a novel approach to modeling AlGaN/GaN high electron mobility transistor (HEMT) with an artificial neural network (ANN). The AlGaN/GaN HEMT device structure and its fabrication process are described. The circuit-based Neuro-space mapping (neuro-SM) technique is studied in detail. The EEHEMT model is implemented according to the measurement results of the designed device, which serves as a coarse model. An ANN is proposed to model AlGaN/GaN HEMT based on the coarse model. Its optimization is performed. The simulation results from the model are compared with the measurement results. It is shown that the simulation results obtained from the ANN model of AlGaN/GaN HEMT are more accurate than those obtained from the EEHEMT model. Project supported by the National Natural Science Foundation of China (Grant No. 60776052).
The ART of representation: Memory reduction and noise tolerance in a neural network vision system
NASA Astrophysics Data System (ADS)
Langley, Christopher S.
The Feature Cerebellar Model Arithmetic Computer (FCMAC) is a multiple-input-single-output neural network that can provide three-degree-of-freedom (3-DOF) pose estimation for a robotic vision system. The FCMAC provides sufficient accuracy to enable a manipulator to grasp an object from an arbitrary pose within its workspace. The network learns an appearance-based representation of an object by storing coarsely quantized feature patterns. As all unique patterns are encoded, the network size grows uncontrollably. A new architecture is introduced herein, which combines the FCMAC with an Adaptive Resonance Theory (ART) network. The ART module categorizes patterns observed during training into a set of prototypes that are used to build the FCMAC. As a result, the network no longer grows without bound, but constrains itself to a user-specified size. Pose estimates remain accurate since the ART layer tends to discard the least relevant information first. The smaller network performs recall faster, and in some cases is better for generalization, resulting in a reduction of error at recall time. The ART-Under-Constraint (ART-C) algorithm is extended to include initial filling with randomly selected patterns (referred to as ART-F). In experiments using a real-world data set, the new network performed equally well using less than one tenth the number of coarse patterns as a regular FCMAC. The FCMAC is also extended to include real-valued input activations. As a result, the network can be tuned to reject a variety of types of noise in the image feature detection. A quantitative analysis of noise tolerance was performed using four synthetic noise algorithms, and a qualitative investigation was made using noisy real-world image data. In validation experiments, the FCMAC system outperformed Radial Basis Function (RBF) networks for the 3-DOF problem, and had accuracy comparable to that of Principal Component Analysis (PCA) and superior to that of Shape Context Matching (SCM), both of which estimate orientation only.
Barkaoui, Abdelwahed; Chamekh, Abdessalem; Merzouki, Tarek; Hambli, Ridha; Mkaddem, Ali
2014-03-01
The complexity and heterogeneity of bone tissue require a multiscale modeling to understand its mechanical behavior and its remodeling mechanisms. In this paper, a novel multiscale hierarchical approach including microfibril scale based on hybrid neural network (NN) computation and homogenization equations was developed to link nanoscopic and macroscopic scales to estimate the elastic properties of human cortical bone. The multiscale model is divided into three main phases: (i) in step 0, the elastic constants of collagen-water and mineral-water composites are calculated by averaging the upper and lower Hill bounds; (ii) in step 1, the elastic properties of the collagen microfibril are computed using a trained NN simulation. Finite element calculation is performed at nanoscopic levels to provide a database to train an in-house NN program; and (iii) in steps 2-10 from fibril to continuum cortical bone tissue, homogenization equations are used to perform the computation at the higher scales. The NN outputs (elastic properties of the microfibril) are used as inputs for the homogenization computation to determine the properties of mineralized collagen fibril. The mechanical and geometrical properties of bone constituents (mineral, collagen, and cross-links) as well as the porosity were taken in consideration. This paper aims to predict analytically the effective elastic constants of cortical bone by modeling its elastic response at these different scales, ranging from the nanostructural to mesostructural levels. Our findings of the lowest scale's output were well integrated with the other higher levels and serve as inputs for the next higher scale modeling. Good agreement was obtained between our predicted results and literature data. Copyright © 2013 John Wiley & Sons, Ltd.
NASA Astrophysics Data System (ADS)
Marín-Moreno, H.; Sahoo, S. K.; Best, A. I.
2017-03-01
The majority of presently exploitable marine methane hydrate reservoirs are likely to host hydrate in disseminated form in coarse grain sediments. For hydrate concentrations below 25-40%, disseminated or pore-filling hydrate does not increase elastic frame moduli, thus making impotent traditional seismic velocity-based methods. Here, we present a theoretical model to calculate frequency-dependent P and S wave velocity and attenuation of an effective porous medium composed of solid mineral grains, methane hydrate, methane gas, and water. The model considers elastic wave energy losses caused by local viscous flow both (i) between fluid inclusions in hydrate and pores and (ii) between different aspect ratio pores (created when hydrate grows); the inertial motion of the frame with respect to the pore fluid (Biot's type fluid flow); and gas bubble damping. The sole presence of pore-filling hydrate in the sediment reduces the available porosity and intrinsic permeability of the sediment affecting Biot's type attenuation at high frequencies. Our model shows that attenuation maxima due to fluid inclusions in hydrate are possible over the entire frequency range of interest to exploration seismology (1-106 Hz), depending on the aspect ratio of the inclusions, whereas maxima due to different aspect ratio pores occur only at sonic to ultrasound frequencies (104-106 Hz). This frequency response imposes further constraints on possible hydrate saturations able to reproduce broadband elastic measurements of velocity and attenuation. Our results provide a physical basis for detecting the presence and amount of pore-filling hydrate in seafloor sediments using conventional seismic surveys.
Game Theoretic Models of Competition and Upgrade Investments in Communication Networks
ERIC Educational Resources Information Center
Wu, Shuang
2010-01-01
In the first part of this dissertation, we study the competition among network service providers in a parallel-link network with the presence of elastic user demand that diminishes both with higher prices and congestion. First we analyze a game where providers strategically price their service for single class of traffic. Later we analyze a game…
Evolution of a fracture network in an elastic medium with internal fluid generation and expulsion
NASA Astrophysics Data System (ADS)
Kobchenko, Maya; Hafver, Andreas; Jettestuen, Espen; Renard, François; Galland, Olivier; Jamtveit, Bjørn; Meakin, Paul; Dysthe, Dag Kristian
2014-11-01
A simple and reproducible analog experiment was used to simulate fracture formation in a low-permeability elastic solid during internal fluid/gas production, with the objective of developing a better understanding of the mechanisms that control the dynamics of fracturing, fracture opening and closing, and fluid transport. In the experiment, nucleation, propagation, and coalescence of fractures within an elastic gelatin matrix, confined in a Hele-Shaw cell, occurred due to CO2 production via fermentation of sugar, and it was monitored by optical means. We first quantified how a fracture network develops, and then how intermittent fluid transport is controlled by the dynamics of opening and closing of fractures. The gas escape dynamics exhibited three characteristic behaviors: (1) Quasiperiodic release of gas with a characteristic frequency that depends on the gas production rate but not on the system size. (2) A 1 /f power spectrum for the fluctuations in the total open fracture area over an intermediate range of frequencies (f ), which we attribute to collective effects caused by interaction between fractures in the drainage network. (3) A 1 /f2 power spectrum was observed at high frequencies, which can be explained by the characteristic behavior of single fractures.
Stiffening of Red Blood Cells Induced by Cytoskeleton Disorders: A Joint Theory-Experiment Study.
Lai, Lipeng; Xu, Xiaofeng; Lim, Chwee Teck; Cao, Jianshu
2015-12-01
The functions and elasticities of the cell are largely related to the structures of the cytoskeletons underlying the lipid bilayer. Among various cell types, the red blood cell (RBC) possesses a relatively simple cytoskeletal structure. Underneath the membrane, the RBC cytoskeleton takes the form of a two-dimensional triangular network, consisting of nodes of actins (and other proteins) and edges of spectrins. Recent experiments focusing on the malaria-infected RBCs (iRBCs) show that there is a correlation between the elongation of spectrins in the cytoskeletal network and the stiffening of the iRBCs. Here we rationalize the correlation between these two observations by combining the wormlike chain model for single spectrins and the effective medium theory for the network elasticity. We specifically focus on how the disorders in the cytoskeletal network affect its macroscopic elasticity. Analytical and numerical solutions from our model reveal that the stiffness of the membrane increases with increasing end-to-end distances of spectrins, but has a nonmonotonic dependence on the variance of the end-to-end distance distributions. These predictions are verified quantitatively by our atomic force microscopy and micropipette aspiration measurements of iRBCs. The model may, from a molecular level, provide guidelines for future identification of new treatment methods for RBC-related diseases, such as malaria infection. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.
A structural study of F-actin - filamin networks
NASA Astrophysics Data System (ADS)
Ahrens-Braunstein, Ashley; Nguyen, Lam; Hirst, Linda
2010-03-01
The cell's ability to move and contract is attributed to the semi-flexible filamentous protein, F -actin, one of the three filaments in the cytoskeleton. Actin bundling can be formed by a cross-linking actin binding protein (ABP) filamin. By examining filamin's cross-linking abilities at different concentrations and molar ratios, we can study the flexibility, structure and multiple network formations created when cross-linking F-actin with this protein. We have studied the phase diagram of this protein system using fluorescence microscopy, analyzing the network structures observed in the context of a coarse grained molecular dynamics simulation carried out by our group.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Richaud, Emmanuel; Gilormini, Pierre; Verdu, Jacques
2016-05-18
Methyl methacrylate networks were synthetized and submitted to radiochemical degradation. Ageing was monitored by means of sol-gel analysis and glass transition temperature measurements. Networks were shown to undergo exclusively chain scission process leading to the degelation of network. The critical conversion degree corresponding to degelation (loss of all elastically active chains) is discussed regarding a statistical theory.
Joys of Community Ensemble Playing: The Case of the Happy Roll Elastic Ensemble in Taiwan
ERIC Educational Resources Information Center
Hsieh, Yuan-Mei; Kao, Kai-Chi
2012-01-01
The Happy Roll Elastic Ensemble (HREE) is a community music ensemble supported by Tainan Culture Centre in Taiwan. With enjoyment and friendship as its primary goals, it aims to facilitate the joys of ensemble playing and the spirit of social networking. This article highlights the key aspects of HREE's development in its first two years…
Fernando L. Dri; Louis G. Jr. Hector; Robert J. Moon; Pablo D. Zavattieri
2013-01-01
In spite of the significant potential of cellulose nanocrystals as functional nanoparticles for numerous applications, a fundamental understanding of the mechanical properties of defect-free, crystalline cellulose is still lacking. In this paper, the elasticity matrix for cellulose IÃ with hydrogen bonding network A was calculated using ab initio...
Local structure controls the nonaffine shear and bulk moduli of disordered solids
NASA Astrophysics Data System (ADS)
Schlegel, M.; Brujic, J.; Terentjev, E. M.; Zaccone, A.
2016-01-01
Paradigmatic model systems, which are used to study the mechanical response of matter, are random networks of point-atoms, random sphere packings, or simple crystal lattices; all of these models assume central-force interactions between particles/atoms. Each of these models differs in the spatial arrangement and the correlations among particles. In turn, this is reflected in the widely different behaviours of the shear (G) and compression (K) elastic moduli. The relation between the macroscopic elasticity as encoded in G, K and their ratio, and the microscopic lattice structure/order, is not understood. We provide a quantitative analytical connection between the local orientational order and the elasticity in model amorphous solids with different internal microstructure, focusing on the two opposite limits of packings (strong excluded-volume) and networks (no excluded-volume). The theory predicts that, in packings, the local orientational order due to excluded-volume causes less nonaffinity (less softness or larger stiffness) under compression than under shear. This leads to lower values of G/K, a well-documented phenomenon which was lacking a microscopic explanation. The theory also provides an excellent one-parameter description of the elasticity of compressed emulsions in comparison with experimental data over a broad range of packing fractions.
Development of New Elastomers and Elastic Nanocomposites from Plant Oils
NASA Astrophysics Data System (ADS)
Zhu, Lin; Wool, Richard
2006-03-01
Economic and environmental concerns lead to the development of new polymers from renewable resources. In this research, new elastomers were synthesized from plant oil based resins. Acrylated oleic methyl ester (AOME), synthesized from high oleic triglycerides, can readily undergo free radical polymerization and form a linear polymer. To achieve the elastic properties, different strategies have been developed to generate an elastic network and control the crosslink density. The elastomers are reinforced by nanoclays. The intercalated state has a network structure similar to thermoplastic elastomers in which the hard segments aggregate to give ordered crystalline domains. The selected organically modified clay and AOME matrix have similar solubility parameters, therefore intercalation of the monomer/polymer into the clay layers occurs and the nano-scale multilayered structure is stable. In situ intercalation and solution intercalation were used to prepare the elastic nanocomposites. Dramatic improvement in mechanical properties was observed. Changes of tensile strength, strain, Young's modulus and fracture energy were related to the clay concentration. The fracture surface was studied to further understand clay effects on the mechanical properties. Self-Healing of the intercalated nanobeams, thermal stability, biocompatibility and biodegradability of this new elastomer were also explored.
NASA Astrophysics Data System (ADS)
Zhao, Yongli; Tian, Rui; Yu, Xiaosong; Zhang, Jiawei; Zhang, Jie
2017-03-01
A proper traffic grooming strategy in dynamic optical networks can improve the utilization of bandwidth resources. An auxiliary graph (AG) is designed to solve the traffic grooming problem under a dynamic traffic scenario in spatial division multiplexing enabled elastic optical networks (SDM-EON) with multi-core fibers. Five traffic grooming policies achieved by adjusting the edge weights of an AG are proposed and evaluated through simulation: maximal electrical grooming (MEG), maximal optical grooming (MOG), maximal SDM grooming (MSG), minimize virtual hops (MVH), and minimize physical hops (MPH). Numeric results show that each traffic grooming policy has its own features. Among different traffic grooming policies, an MPH policy can achieve the lowest bandwidth blocking ratio, MEG can save the most transponders, and MSG can obtain the fewest cores for each request.
A Highly Flexible and Efficient Passive Optical Network Employing Dynamic Wavelength Allocation
NASA Astrophysics Data System (ADS)
Hsueh, Yu-Li; Rogge, Matthew S.; Yamamoto, Shu; Kazovsky, Leonid G.
2005-01-01
A novel and high-performance passive optical network (PON), the SUCCESS-DWA PON, employs dynamic wavelength allocation to provide bandwidth sharing across multiple physical PONs. In the downstream, tunable lasers, an arrayed waveguide grating, and coarse/fine filtering combine to create a flexible new optical access solution. In the upstream, several distributed and centralized schemes are proposed and investigated. The network performance is compared to conventional TDM-PONs under different traffic models, including the self-similar traffic model and the transaction-oriented model. Broadcast support and deployment issues are addressed. The network's excellent scalability can bridge the gap between conventional TDM-PONs and WDM-PONs. The powerful architecture is a promising candidate for next generation optical access networks.
Model Reduction in Biomechanics
NASA Astrophysics Data System (ADS)
Feng, Yan
The mechanical characteristic of the cell is primarily performed by the cytoskeleton. Microtubules, actin, and intermediate filaments are the three main cytoskeletal polymers. Of these, microtubules are the stiffest and have multiple functions within a cell that include: providing tracks for intracellular transport, transmitting the mechanical force necessary for cell division during mitosis, and providing sufficient stiffness for propulsion in flagella and cilia. Microtubule mechanics has been studied by a variety of methods: detailed molecular dynamics (MD), coarse-grained models, engineering type models, and elastic continuum models. In principle, atomistic MD simulations should be able to predict all desired mechanical properties of a single molecule, however, in practice the large computational resources are required to carry out a simulation of larger biomolecular system. Due to the limited accessibility using even the most ambitious all-atom models and the demand for the multiscale molecular modeling and simulation, the emergence of the reduced models is critically important to provide the capability for investigating the biomolecular dynamics that are critical to many biological processes. Then the coarse-grained models, such as elastic network models and anisotropic network models, have been shown to bequite accurate in predicting microtubule mechanical response, but still requires significant computational resources. On the other hand, the microtubule is treated as comprising materials with certain continuum material properties. Such continuum models, especially Euler-Bernoulli beam models, are often used to extract mechanical parameters from experimental results. The microtubule is treated as comprising materials with certain continuum material properties. Such continuum models, especially Euler-Bernoulli beam models in which the biomolecular system is assumed as homogeneous isotropic materials with solid cross-sections, are often used to extract mechanical parameters from experimental results. However, in real biological world, these homogeneous and isotropic assumptions are usually invalidate. Thus, instead of using hypothesized model, a specific continuum model at mesoscopic scale can be introduced based upon data reduction of the results from molecular simulations at atomistic level. Once a continuum model is established, it can provide details on the distribution of stresses and strains induced within the biomolecular system which is useful in determining the distribution and transmission of these forces to the cytoskeletal and sub-cellular components, and help us gain a better understanding in cell mechanics. A data-driven model reduction approach to the problem of microtubule mechanics as an application is present, a beam element is constructed for microtubules based upon data reduction of the results from molecular simulation of the carbon backbone chain of alphabeta-tubulin dimers. The data base of mechanical responses to various types of loads from molecular simulation is reduced to dominant modes. The dominant modes are subsequently used to construct the stiffness matrix of a beam element that captures the anisotropic behavior and deformation mode coupling that arises from a microtubule's spiral structure. In contrast to standard Euler-Bernoulli or Timoshenko beam elements, the link between forces and node displacements results not from hypothesized deformation behavior, but directly from the data obtained by molecular scale simulation. Differences between the resulting microtubule data-driven beam model (MTDDBM) and standard beam elements are presented, with a focus on coupling of bending, stretch, shear deformations. The MTDDBM is just as economical to use as a standard beam element, and allows accurate reconstruction of the mechanical behavior of structures within a cell as exemplified in a simple model of a component element of the mitotic spindle.
NASA Astrophysics Data System (ADS)
Wang, Fu; Liu, Bo; Zhang, Lijia; Zhang, Qi; Tian, Qinghua; Tian, Feng; Rao, Lan; Xin, Xiangjun
2017-07-01
Elastic software-defined optical networks greatly improve the flexibility of the optical switching network while it has brought challenges to the routing and spectrum assignment (RSA). A multilayer virtual topology model is proposed to solve RSA problems. Two RSA algorithms based on the virtual topology are proposed, which are the ant colony optimization (ACO) algorithm of minimum consecutiveness loss and the ACO algorithm of maximum spectrum consecutiveness. Due to the computing power of the control layer in the software-defined network, the routing algorithm avoids the frequent link-state information between routers. Based on the effect of the spectrum consecutiveness loss on the pheromone in the ACO, the path and spectrum of the minimal impact on the network are selected for the service request. The proposed algorithms have been compared with other algorithms. The results show that the proposed algorithms can reduce the blocking rate by at least 5% and perform better in spectrum efficiency. Moreover, the proposed algorithms can effectively decrease spectrum fragmentation and enhance available spectrum consecutiveness.
NASA Astrophysics Data System (ADS)
Li, Nan-Lin; Wu, Wen-Ping; Nie, Kai
2018-05-01
The evolution of misfit dislocation network at γ /γ‧ phase interface and tensile mechanical properties of Ni-based single crystal superalloys at various temperatures and strain rates are studied by using molecular dynamics (MD) simulations. From the simulations, it is found that with the increase of loading, the dislocation network effectively inhibits dislocations emitted in the γ matrix cutting into the γ‧ phase and absorbs the matrix dislocations to strengthen itself which increases the stability of structure. Under the influence of the temperature, the initial mosaic structure of dislocation network gradually becomes irregular, and the initial misfit stress and the elastic modulus slowly decline as temperature increasing. On the other hand, with the increase of the strain rate, it almost has no effect on the elastic modulus and the way of evolution of dislocation network, but contributes to the increases of the yield stress and tensile strength. Moreover, tension-compression asymmetry of Ni-based single crystal superalloys is also presented based on MD simulations.
NASA Astrophysics Data System (ADS)
Nayak, Kapileswar; Das, Sushanta; Nanavati, Hemant
2008-01-01
We present a framework for the development of elasticity and photoelasticity relationships for polyethylene terephthalate fiber networks, incorporating aspects of the primary molecular structure. Semicrystalline polymeric fiber networks are modeled as sequentially arranged crystalline and amorphous regions. Rotational isomeric states-Monte Carlo simulations of amorphous chains of up to 360 bonds (degree of polymerization, DP =60), confined between and bridging infinite impenetrable crystalline walls, have been characterized by Ω, the probability density of the intercrystal separation h, and Δβ, the polarizability anisotropy. lnΩ and Δβ have been modeled as functions of h, yielding the chain deformation relationships. The development has been extended to the fiber network to yield the photoelasticity relationships. We execute our framework by fitting to experimental stress-elongation data and employing the single fitted parameter to directly predict the birefringence-elongation behavior, without any further fitting. Incorporating the effect of strain-induced crystallization into the framework makes it physically more meaningful and yields accurate predictions of the birefringence-elongation behavior.
Detecting and evaluating communities in complex human and biological networks
NASA Astrophysics Data System (ADS)
Morrison, Greg; Mahadevan, L.
2012-02-01
We develop a simple method for detecting the community structure in a network can by utilizing a measure of closeness between nodes. This approach readily leads to a method of coarse graining the network, which allows the detection of the natural hierarchy (or hierarchies) of community structure without appealing to an unknown resolution parameter. The closeness measure can also be used to evaluate the robustness of an individual node's assignment to its community (rather than evaluating only the quality of the global structure). Each of these methods in community detection and evaluation are illustrated using a variety of real world networks of either biological or sociological importance and illustrate the power and flexibility of the approach.
The role of capture spiral silk properties in the diversification of orb webs.
Tarakanova, Anna; Buehler, Markus J
2012-12-07
Among a myriad of spider web geometries, the orb web presents a fascinating, exquisite example in architecture and evolution. Orb webs can be divided into two categories according to the capture silk used in construction: cribellate orb webs (composed of pseudoflagelliform silk) coated with dry cribellate threads and ecribellate orb webs (composed of flagelliform silk fibres) coated by adhesive glue droplets. Cribellate capture silk is generally stronger but less-extensible than viscid capture silk, and a body of phylogenic evidence suggests that cribellate capture silk is more closely related to the ancestral form of capture spiral silk. Here, we use a coarse-grained web model to investigate how the mechanical properties of spiral capture silk affect the behaviour of the whole web, illustrating that more elastic capture spiral silk yields a decrease in web system energy absorption, suggesting that the function of the capture spiral shifted from prey capture to other structural roles. Additionally, we observe that in webs with more extensible capture silk, the effect of thread strength on web performance is reduced, indicating that thread elasticity is a dominant driving factor in web diversification.
Szyrkowiec, Thomas; Autenrieth, Achim; Gunning, Paul; Wright, Paul; Lord, Andrew; Elbers, Jörg-Peter; Lumb, Alan
2014-02-10
For the first time, we demonstrate the orchestration of elastic datacenter and inter-datacenter transport network resources using a combination of OpenStack and OpenFlow. Programmatic control allows a datacenter operator to dynamically request optical lightpaths from a transport network operator to accommodate rapid changes of inter-datacenter workflows.
Resistance to alveolar shape change limits range of force propagation in lung parenchyma.
Ma, Baoshun; Smith, Bradford J; Bates, Jason H T
2015-06-01
We have recently shown that if the lung parenchyma is modeled in 2 dimensions as a network of springs arranged in a pattern of repeating hexagonal cells, the distortional forces around a contracting airway propagate much further from the airway wall than classic continuum theory predicts. In the present study we tested the hypothesis that this occurs because of the negligible shear modulus of a hexagonal spring network. We simulated the narrowing of an airway embedded in a hexagonal network of elastic alveolar walls when the hexagonal cells of the network offered some resistance to a change in shape. We found that as the forces resisting shape change approach about 10% of the forces resisting length change of an individual spring the range of distortional force propagation in the spring network fell of rapidly as in an elastic continuum. We repeated these investigations in a 3-dimensional spring network composed of space-filling polyhedral cells and found similar results. This suggests that force propagation away from a point of local parenchymal distortion also falls off rapidly in real lung tissue. Copyright © 2015 Elsevier B.V. All rights reserved.
Climatological Aspects of the Optical Properties of Fine/Coarse Mode Aerosol Mixtures
NASA Technical Reports Server (NTRS)
Eck, T. F.; Holben, B. N.; Sinyuk, A.; Pinker, R. T.; Goloub, P.; Chen, H.; Chatenet, B.; Li, Z.; Singh, R. P.; Tripathi, S.N.;
2010-01-01
Aerosol mixtures composed of coarse mode desert dust combined with fine mode combustion generated aerosols (from fossil fuel and biomass burning sources) were investigated at three locations that are in and/or downwind of major global aerosol emission source regions. Multiyear monitoring data at Aerosol Robotic Network sites in Beijing (central eastern China), Kanpur (Indo-Gangetic Plain, northern India), and Ilorin (Nigeria, Sudanian zone of West Africa) were utilized to study the climatological characteristics of aerosol optical properties. Multiyear climatological averages of spectral single scattering albedo (SSA) versus fine mode fraction (FMF) of aerosol optical depth at 675 nm at all three sites exhibited relatively linear trends up to 50% FMF. This suggests the possibility that external linear mixing of both fine and coarse mode components (weighted by FMF) dominates the SSA variation, where the SSA of each component remains relatively constant for this range of FMF only. However, it is likely that a combination of other factors is also involved in determining the dynamics of SSA as a function of FMF, such as fine mode particles adhering to coarse mode dust. The spectral variation of the climatological averaged aerosol absorption optical depth (AAOD) was nearly linear in logarithmic coordinates over the wavelength range of 440-870 nm for both the Kanpur and Ilorin sites. However, at two sites in China (Beijing and Xianghe), a distinct nonlinearity in spectral AAOD in logarithmic space was observed, suggesting the possibility of anomalously strong absorption in coarse mode aerosols increasing the 870 nm AAOD.
Einstein Equations from Varying Complexity
NASA Astrophysics Data System (ADS)
Czech, Bartłomiej
2018-01-01
A recent proposal equates the circuit complexity of a quantum gravity state with the gravitational action of a certain patch of spacetime. Since Einstein's equations follow from varying the action, it should be possible to derive them by varying complexity. I present such a derivation for vacuum solutions of pure Einstein gravity in three-dimensional asymptotically anti-de Sitter space. The argument relies on known facts about holography and on properties of tensor network renormalization, an algorithm for coarse-graining (and optimizing) tensor networks.
Buck, Patrick M; Chaudhri, Anuj; Kumar, Sandeep; Singh, Satish K
2015-01-05
Therapeutic monoclonal antibody (mAb) candidates that form highly viscous solutions at concentrations above 100 mg/mL can lead to challenges in bioprocessing, formulation development, and subcutaneous drug delivery. Earlier studies of mAbs with concentration-dependent high viscosity have indicated that mAbs with negatively charged Fv regions have a dipole-like quality that increases the likelihood of reversible self-association. This suggests that weak electrostatic intermolecular interactions can form transient antibody networks that participate in resistance to solution deformation under shear stress. Here this hypothesis is explored by parametrizing a coarse-grained (CG) model of an antibody using the domain charges from four different mAbs that have had their concentration-dependent viscosity behaviors previously determined. Multicopy molecular dynamics simulations were performed for these four CG mAbs at several concentrations to understand the effect of surface charge on mass diffusivity, pairwise interactions, and electrostatic network formation. Diffusion coefficients computed from simulations were in qualitative agreement with experimentally determined viscosities for all four mAbs. Contact analysis revealed an overall greater number of pairwise interactions for the two mAbs in this study with high concentration viscosity issues. Further, using equilibrated solution trajectories, the two mAbs with high concentration viscosity issues quantitatively formed more features of an electrostatic network than the other mAbs. The change in the number of these network features as a function of concentration is related to the number of pairwise interactions formed by electrostatic complementarities between antibody domains. Thus, transient antibody network formation caused by domain-domain electrostatic complementarities is the most probable origin of high concentration viscosity for mAbs in this study.
High Birefringence Liquid Crystals for Laser Hardening and IR Countermeasure
2004-09-24
A fast-switching and scattering-free phase modulator using polymer network liquid crystal ( PNLC ) is demonstrated at **=l.55 um for laser beam...steering application. The strong polymer network anchoring greatly reduces the visco-elastic coefficient of the liquid crystal. As a result, the PNLC
Filamentary structures that self-organize due to adhesion
NASA Astrophysics Data System (ADS)
Sengab, A.; Picu, R. C.
2018-03-01
We study the self-organization of random collections of elastic filaments that interact adhesively. The evolution from an initial fully random quasi-two-dimensional state is controlled by filament elasticity, adhesion and interfilament friction, and excluded volume. Three outcomes are possible: the system may remain locked in the initial state, may organize into isolated fiber bundles, or may form a stable, connected network of bundles. The range of system parameters leading to each of these states is identified. The network of bundles is subisostatic and is stabilized by prestressed triangular features forming at bundle-to-bundle nodes, similar to the situation in foams. Interfiber friction promotes locking and expands the parametric range of nonevolving systems.
New generation of elastic network models.
López-Blanco, José Ramón; Chacón, Pablo
2016-04-01
The intrinsic flexibility of proteins and nucleic acids can be grasped from remarkably simple mechanical models of particles connected by springs. In recent decades, Elastic Network Models (ENMs) combined with Normal Model Analysis widely confirmed their ability to predict biologically relevant motions of biomolecules and soon became a popular methodology to reveal large-scale dynamics in multiple structural biology scenarios. The simplicity, robustness, low computational cost, and relatively high accuracy are the reasons behind the success of ENMs. This review focuses on recent advances in the development and application of ENMs, paying particular attention to combinations with experimental data. Successful application scenarios include large macromolecular machines, structural refinement, docking, and evolutionary conservation. Copyright © 2015 Elsevier Ltd. All rights reserved.
Microstructures and rheology of a calcite-shale thrust fault
NASA Astrophysics Data System (ADS)
Wells, Rachel K.; Newman, Julie; Wojtal, Steven
2014-08-01
A thin (˜2 cm) layer of extensively sheared fault rock decorates the ˜15 km displacement Copper Creek thrust at an exposure near Knoxville, TN (USA). In these ultrafine-grained (<0.3 μm) fault rocks, interpenetrating calcite grains form an interconnected network around shale clasts. One cm below the fault rock layer, sedimentary laminations in non-penetratively deformed footwall shale are cut by calcite veins, small faults, and stylolites. A 350 μm thick calcite vein separates the fault rocks and footwall shale. The vein is composed of layers of (1) coarse calcite grains (>5 μm) that exhibit a lattice preferred orientation (LPO) with pores at twin-twin and twin-grain boundary intersections, and (2) ultrafine-grained (0.3 μm) calcite that exhibits interpenetrating grain boundaries, four-grain junctions and lacks a LPO. Coarse calcite layers crosscut ultrafine-grained layers indicating intermittent vein formation during shearing. Calcite in the fault rock layer is derived from vein calcite and grain-size reduction of calcite took place by plasticity-induced fracture. The ultrafine-grained calcite deformed primarily by diffusion-accommodated grain boundary sliding and formed an interconnected network around shale clasts within the shear zone. The interconnected network of ultrafine-grained calcite indicates that calcite, not shale, was the weak phase in this fault zone.
On neutral metacommunity patterns of river basins at different scales of aggregation
NASA Astrophysics Data System (ADS)
Convertino, Matteo; Muneepeerakul, Rachata; Azaele, Sandro; Bertuzzo, Enrico; Rinaldo, Andrea; Rodriguez-Iturbe, Ignacio
2009-08-01
Neutral metacommunity models for spatial biodiversity patterns are implemented on river networks acting as ecological corridors at different resolution. Coarse-graining elevation fields (under the constraint of preserving the basin mean elevation) produce a set of reconfigured drainage networks. The hydrologic assumption made implies uniform runoff production such that each link has the same habitat capacity. Despite the universal scaling properties shown by river basins regardless of size, climate, vegetation, or exposed lithology, we find that species richness at local and regional scales exhibits resolution-dependent behavior. In addition, we investigate species-area relationships and rank-abundance patterns. The slopes of the species-area relationships, which are consistent over coarse-graining resolutions, match those found in real landscapes in the case of long-distance dispersal. The rank-abundance patterns are independent of the resolution over a broad range of dispersal length. Our results confirm that strong interactions occur between network structure and the dispersal of species and that under the assumption of neutral dynamics, these interactions produce resolution-dependent biodiversity patterns that diverge from expectations following from universal geomorphic scaling laws. Both in theoretical and in applied ecology studying how patterns change in resolution is relevant for understanding how ecological dynamics work in fragmented landscape and for sampling and biodiversity management campaigns, especially in consideration of climate change.
Coupling Field Theory with Mesoscopic Dynamical Simulations of Multicomponent Lipid Bilayers
McWhirter, J. Liam; Ayton, Gary; Voth, Gregory A.
2004-01-01
A method for simulating a two-component lipid bilayer membrane in the mesoscopic regime is presented. The membrane is modeled as an elastic network of bonded points; the spring constants of these bonds are parameterized by the microscopic bulk modulus estimated from earlier atomistic nonequilibrium molecular dynamics simulations for several bilayer mixtures of DMPC and cholesterol. The modulus depends on the composition of a point in the elastic membrane model. The dynamics of the composition field is governed by the Cahn-Hilliard equation where a free energy functional models the coupling between the composition and curvature fields. The strength of the bonds in the elastic network are then modulated noting local changes in the composition and using a fit to the nonequilibrium molecular dynamics simulation data. Estimates for the magnitude and sign of the coupling parameter in the free energy model are made treating the bending modulus as a function of composition. A procedure for assigning the remaining parameters in the free energy model is also outlined. It is found that the square of the mean curvature averaged over the entire simulation box is enhanced if the strength of the bonds in the elastic network are modulated in response to local changes in the composition field. We suggest that this simulation method could also be used to determine if phase coexistence affects the stress response of the membrane to uniform dilations in area. This response, measured in the mesoscopic regime, is already known to be conditioned or renormalized by thermal undulations. PMID:15347594
Strength properties and structure of a submicrocrystalline Al-Mg-Mn alloy under shock compression
NASA Astrophysics Data System (ADS)
Petrova, A. N.; Brodova, I. G.; Razorenov, S. V.
2017-06-01
The results of studying the strength of a submicrocrystalline aluminum A5083 alloy (chemical composition was 4.4Mg-0.6Mn-0.11Si-0.23Fe-0.03Cr-0.02Cu-0.06Ti wt % and Al base) under shockwave compression are presented. The submicrocrystalline structure of the alloy was produced in the process of dynamic channel-angular pressing at a strain rate of 104 s-1. The average size of crystallites in the alloy was 180-460 nm. Hugoniot elastic limit σHEL, dynamic yield stress σy, and the spall strength σSP of the submicrocrystalline alloy were determined based on the free-surface velocity profiles of samples during shock compression. It has been established that upon shock compression, the σHEL and σy of the submicrocrystalline alloy are higher than those of the coarse-grained alloy and σsp does not depend on the grain size. The maximum value of σHEL reached for the submicrocrystalline alloy is 0.66 GPa, which is greater than that in the coarse-crystalline alloy by 78%. The dynamic yield stress is σy = 0.31 GPa, which is higher than that of the coarse-crystalline alloy by 63%. The spall strength is σsp = 1.49 GPa. The evolution of the submicrocrystalline structure of the alloy during shock compression was studied. It has been established that a mixed nonequilibrium grain-subgrain structure with a fragment size of about 400 nm is retained after shock compression, and the dislocation density and the hardness of the alloy are increased.
NASA Astrophysics Data System (ADS)
Søe-Knudsen, Alf; Sorokin, Sergey
2011-06-01
This rapid communication is concerned with justification of the 'rule of thumb', which is well known to the community of users of the finite element (FE) method in dynamics, for the accuracy assessment of the wave finite element (WFE) method. An explicit formula linking the size of a window in the dispersion diagram, where the WFE method is trustworthy, with the coarseness of a FE mesh employed is derived. It is obtained by the comparison of the exact Pochhammer-Chree solution for an elastic rod having the circular cross-section with its WFE approximations. It is shown that the WFE power flow predictions are also valid within this window.
Flaw tolerance promoted by dissipative deformation mechanisms between material building blocks
NASA Astrophysics Data System (ADS)
Verho, Tuukka; Buehler, Markus J.
2014-09-01
Novel high-performance composite materials often draw inspiration from natural materials such as bone or mollusc shells. A prime feature of such composites is that they are, like their natural counterparts, quasibrittle. They are tolerant to material flaws up to a certain characteristic flaw-tolerant size scale, exhibiting high strength and toughness, but start to behave in a brittle manner when sufficiently large flaws are present. Here, we establish that better flaw tolerance can be achieved by maximizing fracture toughness relative to the maximum elastic energy available in the material, and we demonstrate this concept with simple two-dimensional coarse-grained simulations where the transition from brittle to quasibrittle behaviour is examined.
Poly(Capro-Lactone) Networks as Actively Moving Polymers
NASA Astrophysics Data System (ADS)
Meng, Yuan
Shape-memory polymers (SMPs), as a subset of actively moving polymers, form an exciting class of materials that can store and recover elastic deformation energy upon application of an external stimulus. Although engineering of SMPs nowadays has lead to robust materials that can memorize multiple temporary shapes, and can be triggered by various stimuli such as heat, light, moisture, or applied magnetic fields, further commercialization of SMPs is still constrained by the material's incapability to store large elastic energy, as well as its inherent one-way shape-change nature. This thesis develops a series of model semi-crystalline shape-memory networks that exhibit ultra-high energy storage capacity, with accurately tunable triggering temperature; by introducing a second competing network, or reconfiguring the existing network under strained state, configurational chain bias can be effectively locked-in, and give rise to two-way shape-actuators that, in the absence of an external load, elongates upon cooling and reversibly contracts upon heating. We found that well-defined network architecture plays essential role on strain-induced crystallization and on the performance of cold-drawn shape-memory polymers. Model networks with uniform molecular weight between crosslinks, and specified functionality of each net-point, results in tougher, more elastic materials with a high degree of crystallinity and outstanding shape-memory properties. The thermal behavior of the model networks can be finely modified by introducing non-crystalline small molecule linkers that effectively frustrates the crystallization of the network strands. This resulted in shape-memory networks that are ultra-sensitive to heat, as deformed materials can be efficiently triggered to revert to its permanent state upon only exposure to body temperature. We also coupled the same reaction adopted to create the model network with conventional free-radical polymerization to prepare a dual-cure "double network" that behaves as a real thermal "actuator". This approach places sub-chains under different degrees of configurational bias within the network to utilize the material's propensity to undergo stress-induced crystallization. Reconfiguration of model shape-memory networks containing photo-sensitive linkages can also be employed to program two-way actuator. Chain reshuffling of a partially reconfigurable network is initiated upon exposure to light under specific strains. Interesting photo-induced creep and stress relaxation behaviors were demonstrated and understood based on a novel transient network model we derived. In summary, delicate manipulation of shape-memory network architectures addressed critical issues constraining the application of this type of functional polymer material. Strategies developed in this thesis may provide new opportunity to the field of shape-memory polymers.
pH induced contrast in viscoelasticity imaging of biopolymers
Yapp, R D; Insana, M F
2009-01-01
Understanding contrast mechanisms and identifying discriminating features is at the heart of diagnostic imaging development. This report focuses on how pH influences the viscoelastic properties of biopolymers to better understand the effects of extracellular pH on breast tumour elasticity imaging. Extracellular pH is known to decrease as much as 1 pH unit in breast tumours, thus creating a dangerous environment that increases cellular mutatation rates and therapeutic resistance. We used a gelatin hydrogel phantom to isolate the effects of pH on a polymer network with similarities to the extracellular matrix in breast stroma. Using compressive unconfined creep and stress relaxation measurements, we systematically measured the viscoelastic features sensitive to pH by way of time domain models and complex modulus analysis. These results are used to determine the sensitivity of quasi-static ultrasonic elasticity imaging to pH. We found a strong elastic response of the polymer network to pH, such that the matrix stiffness decreases as pH was reduced, however the viscous response of the medium to pH was negligible. While physiological features of breast stroma such as proteoglycans and vascular networks are not included in our hydrogel model, observations in this study provide insight into viscoelastic features specific to pH changes in the collagenous stromal network. These observations suggest that the large contrast common in breast tumours with desmoplasia may be reduced under acidic conditions, and that viscoelastic features are unlikely to improve discriminability. PMID:19174599
Towards a carrier SDN: an example for elastic inter-datacenter connectivity.
Velasco, L; Asensio, A; Berral, J L; Castro, A; López, V
2014-01-13
We propose a network-driven transfer mode for cloud operations in a step towards a carrier SDN. Inter-datacenter connectivity is requested in terms of volume of data and completion time. The SDN controller translates and forwards requests to an ABNO controller in charge of a flexgrid network.
The flow of power law fluids in elastic networks and porous media.
Sochi, Taha
2016-02-01
The flow of power law fluids, which include shear thinning and shear thickening as well as Newtonian as a special case, in networks of interconnected elastic tubes is investigated using a residual-based pore scale network modeling method with the employment of newly derived formulae. Two relations describing the mechanical interaction between the local pressure and local cross-sectional area in distensible tubes of elastic nature are considered in the derivation of these formulae. The model can be used to describe shear dependent flows of mainly viscous nature. The behavior of the proposed model is vindicated by several tests in a number of special and limiting cases where the results can be verified quantitatively or qualitatively. The model, which is the first of its kind, incorporates more than one major nonlinearity corresponding to the fluid rheology and conduit mechanical properties, that is non-Newtonian effects and tube distensibility. The formulation, implementation, and performance indicate that the model enjoys certain advantages over the existing models such as being exact within the restricting assumptions on which the model is based, easy implementation, low computational costs, reliability, and smooth convergence. The proposed model can, therefore, be used as an alternative to the existing Newtonian distensible models; moreover, it stretches the capabilities of the existing modeling approaches to reach non-Newtonian rheologies.
WDM PONs based on colorless technology
NASA Astrophysics Data System (ADS)
Saliou, Fabienne; Simon, Gael; Chanclou, Philippe; Pizzinat, Anna; Lin, Huafeng; Zhou, Enyu; Xu, Zhiguang
2015-12-01
Wavelength Division Multiplexing (WDM) Passive Optical Network (PON) is foreseen to be part of the Next Generation Passive Optical Networks. Business and mobile fronthaul networks already express the need to develop WDM PONs in the access segment. Fixed wavelength transceivers based on Coarse WDM are already available to respond to today's market needs but Dense WDM technologies will be needed and colorless technologies are essential to provide simple and cost-effective WDM PON systems. We propose in this paper to demonstrate the capabilities of a DWDM PON system prototype based on self-seeded RSOAs and designed to transmit CPRI over 60 km of fiber at 2.5 Gbit/s.
NASA Astrophysics Data System (ADS)
Wu, Jun-Zheng; Meng, Wei-Lie; Tang, Heng-Song; Zhang, Neng-Hui
2017-05-01
DNA film self-assembled or nanografted on a substrate, as a kind of soft matter, consists of fixed DNA chains endowed with negative charges and an aqueous solution full of cations, anions and water molecules. Their thermal/electrical/mechanical properties are closely related to the complex biodetection signals in nano-/micro-scale biosensors and other new genome technologies. This makes it important to properly characterize these properties. In this paper, the effect of flexible micro-scale configurations on the elastic moduli of DNA films is investigated. First, illuminated by Qiu’s sphere model, an alternative bead-chain model in terms of the Yukawa potential is presented for flexible intra-DNA configurations to describe interactions between DNA fragments. The effective charges of coarse-grained DNA beads could be derived, in which the empirical parameters are identified by curve fitting with Qiu’s experimental data. Second, the updated mesoscopic bead-chain model and the thought experiment of a continuum compression bar are used to compare the elastic moduli of double-stranded DNA (dsDNA) films prepared by self-assembling and nanografting techniques. Configurational sampling is achieved via Monte Carlo simulation. Our predictions quantitatively or qualitatively agree well with the relevant experiments on the effective charge of dsDNA from low to moderate monovalent counterion concentration, immobilization deflection of single-stranded DNA (ssDNA) or dsDNA microcantilever with the variation of salt concentration, and elastic modulus of ssDNA film in the air. The results reveal that different solution environment stimulates the diverse mechanical properties of dsDNA film on a substrate, and the end effect (i.e. terminal group effect) makes self-assembling dsDNA film stiffer in the sense of the same average packing density.
On a Possible Relationship between Linguistic Expertise and EEG Gamma Band Phase Synchrony
Reiterer, Susanne; Pereda, Ernesto; Bhattacharya, Joydeep
2011-01-01
Recent research has shown that extensive training in and exposure to a second language can modify the language organization in the brain by causing both structural and functional changes. However it is not yet known how these changes are manifested by the dynamic brain oscillations and synchronization patterns subserving the language networks. In search for synchronization correlates of proficiency and expertise in second language acquisition, multivariate EEG signals were recorded from 44 high and low proficiency bilinguals during processing of natural language in their first and second languages. Gamma band (30–45 Hz) phase synchronization (PS) was calculated mainly by two recently developed methods: coarse-graining of Markov chains (estimating global phase synchrony, measuring the degree of PS between one electrode and all other electrodes), and phase lag index (PLI; estimating bivariate phase synchrony, measuring the degree of PS between a pair of electrodes). On comparing second versus first language processing, global PS by coarse-graining Markov chains indicated that processing of the second language needs significantly higher synchronization strength than first language. On comparing the proficiency groups, bivariate PS measure (i.e., PLI) revealed that during second language processing the low proficiency group showed stronger and broader network patterns than the high proficiency group, with interconnectivities between a left fronto-parietal network. Mean phase coherence analysis also indicated that the network activity was globally stronger in the low proficiency group during second language processing. PMID:22125542
Alastruey, Jordi; Khir, Ashraf W; Matthys, Koen S; Segers, Patrick; Sherwin, Spencer J; Verdonck, Pascal R; Parker, Kim H; Peiró, Joaquim
2011-08-11
The accuracy of the nonlinear one-dimensional (1-D) equations of pressure and flow wave propagation in Voigt-type visco-elastic arteries was tested against measurements in a well-defined experimental 1:1 replica of the 37 largest conduit arteries in the human systemic circulation. The parameters required by the numerical algorithm were directly measured in the in vitro setup and no data fitting was involved. The inclusion of wall visco-elasticity in the numerical model reduced the underdamped high-frequency oscillations obtained using a purely elastic tube law, especially in peripheral vessels, which was previously reported in this paper [Matthys et al., 2007. Pulse wave propagation in a model human arterial network: Assessment of 1-D numerical simulations against in vitro measurements. J. Biomech. 40, 3476-3486]. In comparison to the purely elastic model, visco-elasticity significantly reduced the average relative root-mean-square errors between numerical and experimental waveforms over the 70 locations measured in the in vitro model: from 3.0% to 2.5% (p<0.012) for pressure and from 15.7% to 10.8% (p<0.002) for the flow rate. In the frequency domain, average relative errors between numerical and experimental amplitudes from the 5th to the 20th harmonic decreased from 0.7% to 0.5% (p<0.107) for pressure and from 7.0% to 3.3% (p<10(-6)) for the flow rate. These results provide additional support for the use of 1-D reduced modelling to accurately simulate clinically relevant problems at a reasonable computational cost. Copyright © 2011 Elsevier Ltd. All rights reserved.
Beri, A; Norton, J E; Norton, I T
2013-12-01
Water-in-oil emulsions in lipsticks could have the potential to improve moisturizing properties and deliver hydrophilic molecules to the lips. The aims of this work were (i) to investigate the effect of emulsifier type (polymer vs. monomer, and saturated vs. unsaturated chain) and concentration on droplet size and (ii) to investigate the effect of wax ratio (carnauba wax, microcrystalline wax, paraffin wax and performalene) and aqueous phase volume on material properties (Young's modulus, point of fracture, elastic modulus and viscous modulus). Emulsion formation was achieved using a high shear mixer. Results showed that the saturated nature of the emulsifier had very little effect on droplet size, neither did the use of an emulsifier with a larger head group (droplet size ~18-25 μm). Polyglycerol polyricinoleate (PGPR) resulted in emulsions with the smallest droplets (~3-5 μm), as expected from previous studies that show that it produces a thick elastic interface. The results also showed that both Young's modulus and point of fracture increase with increasing percentage of carnauba wax (following a power law dependency of 3), but decrease with increasing percentage of microcrystalline wax, suggesting that the carnauba wax is included in the overall wax network formed by the saturated components, whereas the microcrystalline wax forms irregular crystals that disrupt the overall wax crystal network. Young's modulus, elastic modulus and viscous modulus all decrease with increasing aqueous phase volume in the emulsions, although the slope of the decrease in elastic and viscous moduli is dependent on the addition of solid wax, as a result of strengthening the network. This work suggests the potential use for emulsions in lipstick applications, particularly when PGPR is used as an emulsifier, and with the addition of solid wax, as it increases network strength. © 2013 Society of Cosmetic Scientists and the Société Française de Cosmétologie.
DSGRN: Examining the Dynamics of Families of Logical Models.
Cummins, Bree; Gedeon, Tomas; Harker, Shaun; Mischaikow, Konstantin
2018-01-01
We present a computational tool DSGRN for exploring the dynamics of a network by computing summaries of the dynamics of switching models compatible with the network across all parameters. The network can arise directly from a biological problem, or indirectly as the interaction graph of a Boolean model. This tool computes a finite decomposition of parameter space such that for each region, the state transition graph that describes the coarse dynamical behavior of a network is the same. Each of these parameter regions corresponds to a different logical description of the network dynamics. The comparison of dynamics across parameters with experimental data allows the rejection of parameter regimes or entire networks as viable models for representing the underlying regulatory mechanisms. This in turn allows a search through the space of perturbations of a given network for networks that robustly fit the data. These are the first steps toward discovering a network that optimally matches the observed dynamics by searching through the space of networks.
Rajendran, V; Begum, A Nishara; Azooz, M A; el Batal, F H
2002-11-01
Bioactive glasses of the system SiO2-Na2O-CaO-P2O5 have been prepared by the normal melting and annealing technique. The elastic moduli, attenuation, Vickers hardness, fracture toughness and fracture surface energy have been obtained using the known method at room temperature. The temperature dependence of elastic moduli and attenuation measurements have been extended over a wide range of temperature from 150 to 500 K. The SiO2 content dependence of velocities, attenuation, elastic moduli, and other parameters show an interesting observation at 45 wt% of SiO2 by exhibiting an anomalous behaviour. A linear relation is developed for Tg, which explores the influence of Na2O on SiO2-Na2O-CaO-P2O5 bioactive glasses. The measured hardness, fracture toughness and fracture surface energy show a linear relation with Young's modulus. It is also interesting to note that the observed results are functions of polymerisation and the number of non-bridging oxygens (NBO) prevailing in the network with change in SiO2 content. The temperature dependence of velocities, attenuation and elastic moduli show the existence of softening in the glass network structure as temperature increases.
Towards a phase diagram for spin foams
NASA Astrophysics Data System (ADS)
Delcamp, Clement; Dittrich, Bianca
2017-11-01
One of the most pressing issues for loop quantum gravity and spin foams is the construction of the continuum limit. In this paper, we propose a systematic coarse-graining scheme for three-dimensional lattice gauge models including spin foams. This scheme is based on the concept of decorated tensor networks, which have been introduced recently. Here we develop an algorithm applicable to gauge theories with non-Abelian groups, which for the first time allows for the application of tensor network coarse-graining techniques to proper spin foams. The procedure deals efficiently with the large redundancy of degrees of freedom resulting from gauge invariance. The algorithm is applied to 3D spin foams defined on a cubical lattice which, in contrast to a proper triangulation, allows for non-trivial simplicity constraints. This mimics the construction of spin foams for 4D gravity. For lattice gauge models based on a finite group we use the algorithm to obtain phase diagrams, encoding the continuum limit of a wide range of these models. We find phase transitions for various families of models carrying non-trivial simplicity constraints.
Modification of Hazen's equation in coarse grained soils by soft computing techniques
NASA Astrophysics Data System (ADS)
Kaynar, Oguz; Yilmaz, Isik; Marschalko, Marian; Bednarik, Martin; Fojtova, Lucie
2013-04-01
Hazen first proposed a Relationship between coefficient of permeability (k) and effective grain size (d10) was first proposed by Hazen, and it was then extended by some other researchers. However many attempts were done for estimation of k, correlation coefficients (R2) of the models were generally lower than ~0.80 and whole grain size distribution curves were not included in the assessments. Soft computing techniques such as; artificial neural networks, fuzzy inference systems, genetic algorithms, etc. and their hybrids are now being successfully used as an alternative tool. In this study, use of some soft computing techniques such as Artificial Neural Networks (ANNs) (MLP, RBF, etc.) and Adaptive Neuro-Fuzzy Inference System (ANFIS) for prediction of permeability of coarse grained soils was described, and Hazen's equation was then modificated. It was found that the soft computing models exhibited high performance in prediction of permeability coefficient. However four different kinds of ANN algorithms showed similar prediction performance, results of MLP was found to be relatively more accurate than RBF models. The most reliable prediction was obtained from ANFIS model.
Altobelli, R; Salzano de Luna, M; Filippone, G
2017-09-27
The sequence of events which leads to the interfacial crowding of plate-like nanoparticles in co-continuous polymer blends is investigated through a combination of morphological and rheological analyses. Very low amounts (∼0.2 vol%) of organo-modified clay are sufficient to suppress phase coarsening in a co-continuous polystyrene/poly(methyl methacrylate) blend, while lower particle loading allows for a tuning of the characteristic size of the polymer phases at the μm-scale. In any case, an interfacial network of nanoparticles eventually forms, which is driven by the preferred polymer-polymer interface. The elastic features and stress-bearing ability of this peculiar nanoparticle assembly are studied in detail by means of a descriptive two-phase viscoelastic model, which allows isolation of the contribution of the filler network. The role of the co-continuous matrix in driving the space arrangement of the nanoparticles is emphasized by means of comparative analysis with systems based on the same polymers and nanoparticles, but in which the matrix is either a pure polymer or a blend with drop-in-matrix morphology. The relaxation dynamics of the interfacial network was found not to depend on the matrix microstructure, which instead substantially affects the assembly of the nanoplatelets. When the host medium is co-continuous, the particles align along the preferred polymer-polymer interface, percolating at a very low amount (∼0.17 vol%) and prevalently interacting edge-to-edge. The stress bearing ability of such a network is much higher than that in the case of matrix based on a homogeneous polymer or a drop-in-matrix blend, but its elasticity shows low sensitivity to the filler content.
Confocal microscopy for automatic texture analysis of elastic fibers in histologic preparations
NASA Astrophysics Data System (ADS)
Adam, R. L.; Vieira, G.; Ferro, D. P.; de Thomaz, A. A.; Cesar, C., L.; Metze, K.
2009-07-01
Elastic fibers are an important component of many organs and tissues, such as skin, lungs, arteries, ligaments, intervertebral discs and cartilage Their function is to endow tissues with elastic recoil and resilience, to act as an important adhesion template for cells, and to regulate growth factor availability (1,2). Loss or remodeling of the elastic fiber texture occurs in many diseases. Degeneration and fragmentation of elastic fibers and aging are intimately related (3). Recently, the importance of elastin for the study of malignant tumor progression has been emphasized (4,5). Elastic tissue may be a significant reservoir of angiostatic molecules and soluble elastin as well as elastin peptides, that are inhibitors of the metastatic process in experimental tumor models (4). Elastic fibers are involved in the anatomic remodeling of chronic pulmonary diseases (6) and, especially, of diseases of the arterial wall (7, 8). The study of these phenomena is important for the understanding of the pathophysiologic basis of the diseases. Recently the role of elastic fibers in small diameter vascular graft design has been emphasized (2). The possibility to regenerate or engineer elastic fibres and tissues creates an important challenge, not only to understand the molecular basis of elastic-fibre biology (1,2), but also of its spatial arrangement and remodeling in the diseased tissues. Subtle changes of the complex elastic fiber network may be involved in the pathogenesis of diseases. Therefore a precise and objective histopathologic description is necessary.
Coarse coding and discourse comprehension in adults with right hemisphere brain damage
Tompkins, Connie A.; Scharp, Victoria L.; Meigh, Kimberly M.; Fassbinder, Wiltrud
2009-01-01
Background Various investigators suggest that some discourse-level comprehension difficulties in adults with right hemisphere brain damage (RHD) have a lexical-semantic basis. As words are processed, the intact right hemisphere arouses and sustains activation of a wide-ranging network of secondary or peripheral meanings and features—a phenomenon dubbed “coarse coding”. Coarse coding impairment has been postulated to underpin some prototypical RHD comprehension deficits, such as difficulties with nonliteral language interpretation, discourse integration, some kinds of inference generation, and recovery when a reinterpretation is needed. To date, however, no studies have addressed the hypothesised link between coarse coding deficit and discourse comprehension in RHD. Aims The current investigation examined whether coarse coding was related to performance on two measures of narrative comprehension in adults with RHD. Methods & Procedures Participants were 32 adults with unilateral RHD from cerebrovascular accident, and 38 adults without brain damage. Coarse coding was operationalised as poor activation of peripheral/weakly related semantic features of words. For the coarse coding assessment, participants listened to spoken sentences that ended in a concrete noun. Each sentence was followed by a spoken target phoneme string. Targets were subordinate semantic features of the sentence-final nouns that were incompatible with their dominant mental representations (e.g., “rotten” for apple). Targets were presented at two post-noun intervals. A lexical decision task was used to gauge both early activation and maintenance of activation of these weakly related semantic features. One of the narrative tasks assessed comprehension of implied main ideas and details, while the other indexed high-level inferencing and integration. Both comprehension tasks were presented auditorily. For all tasks, accuracy of performance was the dependent measure. Correlations were computed within the RHD group between both the early and late coarse coding measures and the two discourse measures. Additionally, ANCOVA and independent t-tests were used to compare both early and sustained coarse coding in subgroups of good and poor RHD comprehenders. Outcomes & Results The group with RHD was less accurate than the control group on all measures. The finding of coarse coding impairment (difficulty activating/sustaining activation of a word’s peripheral features) may appear to contradict prior evidence of RHD suppression deficit (prolonged activation for context-inappropriate meanings of words). However, the sentence contexts in this study were unbiased and thus did not provide an appropriate test of suppression function. Correlations between coarse coding and the discourse measures were small and nonsignificant. There were no differences in coarse coding between RHD comprehension subgroups on the high-level inferencing task. There was also no distinction in early coarse coding for subgroups based on comprehension of implied main ideas and details. But for these same subgroups, there was a difference in sustained coarse coding. Poorer RHD comprehenders of implied information from discourse were also poorer at maintaining activation for semantically distant features of concrete nouns. Conclusions This study provides evidence of a variant of the postulated link between coarse coding and discourse comprehension in RHD. Specifically, adults with RHD who were particularly poor at sustaining activation for peripheral semantic features of nouns were also relatively poor comprehenders of implied information from narratives. PMID:20037670
NASA Astrophysics Data System (ADS)
Adam, L.; Sim, C. Y.; Macfarlane, J.; van Wijk, K.; Shragge, J. C.; Higgs, K.
2015-12-01
Time-lapse seismic signatures can be used to quantify fluid saturation and pressure changes in a reservoir undergoing CO2 sequestration. However, the injection of CO2 acidifies the water, which may dissolve and/or precipitate minerals. Understanding the impact on the rock frame from field seismic time-lapse changes remains an outstanding challenge. Here, we study the effects of carbonate-CO2-water reactions on the physical and elastic properties of rock samples with variable volumes of carbonate cementation. The effects of fluid substitution alone (brine to CO2) and those due to the combination of fluid substitution and mineral dissolution on time-lapse seismic signatures are studied by combining laboratory data, geophysical well-log data and 1-D seismic modeling. Nine rocks from Pohokura Field (New Zealand) are reacted with carbonic acid. The elastic properties are measured using a high-density laser-ultrasonic setup. We observe that P-wave velocity changes up to -19% and correlate with sandstone grain size. Coarse-grained sandstones show greater changes in elastic wave velocities due to dissolution than fine-grained sandstones. To put this in perspective, this velocity change is comparable to the effect of fluid substitution from brine to CO2. This can potentially create an ambiguity in the interpretation of the physical processes responsible for time-lapse signatures in a CO2injection scenario. The laboratory information is applied onto well-log data to model changes in elastic properties of sandstones at the well-log scale. Well-logs and core petrographic analyses are used to find an elastic model that best describes the observed elastic waves velocities in the cemented reservoir sandstones. The Constant-cement rock physics model is found to predict the elastic behaviour of the cemented sandstones. A possible late-time sequestration scenario is that both mineral dissolution and fluid substitution occur in the reservoir. 1-D synthetic seismograms show that seismic amplitudes can change up to 126% in such a scenario. Our work shows that it is important to consider that time-lapse seismic signatures in carbonate-cemented reservoirs can result not only from fluid and pressure changes but also potentially from chemical reaction between CO2-water mixtures and carbonate cemented sandstones.
Ben Isaac, Eyal; Manor, Uri; Kachar, Bechara; Yochelis, Arik; Gov, Nir S
2013-08-01
Reaction-diffusion models have been used to describe pattern formation on the cellular scale, and traditionally do not include feedback between cellular shape changes and biochemical reactions. We introduce here a distinct reaction-diffusion-elasticity approach: The reaction-diffusion part describes bistability between two actin orientations, coupled to the elastic energy of the cell membrane deformations. This coupling supports spatially localized patterns, even when such solutions do not exist in the uncoupled self-inhibited reaction-diffusion system. We apply this concept to describe the nonlinear (threshold driven) initiation mechanism of actin-based cellular protrusions and provide support by several experimental observations.
Rheological investigation of self-emulsification process: effect of co-surfactant.
Biradar, Shailesh V; Dhumal, Ravindra S; Paradkar, Ananat R
2009-01-01
The aim of study is to investigate role of co-surfactant in self-emulsification through rheological analysis of intermediate liquid crystalline (LC) phase formed during self-emulsification. To mixture of Captex 200P (C200) and tween 80 (T80) (SES Plain), either medium hydrocarbon chain co-surfactant (Capmul MCM (CMCM): SES C) or long hydrocarbon chain co-surfactant (Peceol (P): SES P) was added separately at different concentration levels. Self-emulsification was monitored by visual observations, turbidimetric and droplet size measurement. Mesophases were obtained by 30% v/v aqueous hydration of SES and characterized by polarizing microscopy, differential scanning calorimetry (DSC) and rheological studies. SES Plain exhibited 'bad' emulsification owing to instantaneous gel formation in aqueous media. Almost all SES C have shown 'good' emulsification with transparent appearance, very low turbidity value and nano size droplets. All SES P presented 'moderate' emulsification with milky appearance, high turbidity value and coarse droplets. Polarizing microscopy revealed formation of lamellar phase in SES Plain and in all SES P while almost all SES C exhibited formation of micellar cubic phase. In DSC studies, higher extent of LC phase formation was observed in SES C as compared to SES P. Rheological study clearly demonstrated presence of elastic and partially recoverable mesophase in SES Plain, which was transformed into a viscous and non-recovering mesophase with addition of CMCM while there was no change in rheological status of SES Plain after addition of P. The weak and viscous LC phase in SES C must have not presented any resistance to strain induced deformation. Therefore, it might have ruptured easily and quickly, releasing jet of nanosize droplets whereas elastic mesophase in SES P might have ruptured with little resistance resulting in coarse droplets. The ability of co-surfactant to promote self-emulsification was attributed to their influence on viscoelastic properties of intermediate LC phase.
Statistical physics of modulated phases in nematic liquid crystals
NASA Astrophysics Data System (ADS)
Shamid, Shaikh M.
Nematic liquid crystals are the state of the matter in which there is no positional order like crystals but it has orientational order of the constituent molecules. In the conventional nematics, the long axes of the rod-like molecules tend to align up or down uniformly along a director n. If the constituent molecules are chiral, they tend to form a modulated structure in one of the space dimensions. They are called the chiral nematics. If the chirality is strong enough we get the modulated structures in all three dimensions called the chiral blue phase. On the other hand, if the molecules are achiral, but an additional polar dipole is attached to the molecules, they also tend to form a modulated structure. In these types of materials we observe an important physical effect called flexoelectric effect, in which the polar order is linearly coupled to the director gradients. This dissertation work presents analytical and simulation studies of that modulated structures using the flexoelectric mechanism. Classic work by R. B. Meyer and further studies by I. Dozov predicted two possible structures, known as twist-bend and splay-bend. One of these predictions, the twist-bend phase, has recently been identified in experiments on bent-shaped liquid crystals. In this recently discovered twist-bend nematic phase the modulation is along one of the space dimensions. If this flexoelectric coupling is strong enough, in addition to twist-bend and splay-bend, here we predict the formation of polar analog of chiral blue phases (in both 2D and 3D) made of achiral polar liquid crystal materials by using Elastic continuum theory-based numerical calculations and computer simulations. This dissertation work also presents the coarse-grained theory of twist-bend phase. This theory predicts normal modes of fluctuation in both sides of nematic to twist-bend transition, which then compared with light scattering experiments. Macroscopic elastic and electric properties of twist-bend nematics can be realized using this coarse-grained description.
Microstructure-Property Correlations in Fiber Laser Welded Nb-Ti Microalloyed C-Mn Steel
NASA Astrophysics Data System (ADS)
Sun, Qian; Nie, Xiao-Kang; Li, Yang; Di, Hong-Shuang
2018-02-01
Mechanical Performance of traditional gas-shielded arc welded joints of 700 MPa grade microalloyed C-Mn steel cannot meet service requirements. Laser welding, with its characteristic high energy density, is known to improve the welding performance of experimental steels. In the present study, Nb-Ti microalloyed steel with a thickness of 4.5 mm was welded using a 4 kW fiber laser. The microstructure, precipitation, and mechanical properties of the welded joints were studied. The hardness and tensile strength of the welded joints were higher than those of the base metal (BM). The microstructure of the fusion zone (FZ) and coarse grain heat affected zone (CGHAZ) was lath martensite (LM), while the microstructure of the fine grain HAZ and mixed grain HAZ consisted of ferrite and martensite/austenite islands. Although LM was observed in both the FZ and CGHAZ, the hardness and calculated tensile strength of the FZ were lower than those of the CGHAZ, due to a reduction in solid solution strengthening by element loss and the dissolution of high-hardness precipitates in FZ. Most precipitates such as [(Nb,Ti)C and (Nb,Ti)(C,N)] that were present in the BM were dissolved, which led to an increase in C and N in solid solution in the FZ. Thus, the elastic modulus of the FZ was higher than that of the BM. Similarly, the elastic modulus of the CGHAZ was higher than that of the BM due to the segregation of C and N atoms during the welding process. The toughness of the FZ was superior to that of the BM, and the toughness of the HAZ approached 91% of that of the BM. The change in toughness primarily depended on the microstructural refinement, the increase in the fraction of grains with high misorientation, the residual austenite in the FZ and CGHAZ, and the dissolution of coarse precipitates.
Continuum vs. spring network models of airway-parenchymal interdependence
Ma, Baoshun
2012-01-01
The outward tethering forces exerted by the lung parenchyma on the airways embedded within it are potent modulators of the ability of the airway smooth muscle to shorten. Much of our understanding of these tethering forces is based on treating the parenchyma as an elastic continuum; yet, on a small enough scale, the lung parenchyma in two dimensions would seem to be more appropriately described as a discrete spring network. We therefore compared how the forces and displacements in the parenchyma surrounding a contracting airway are predicted to differ depending on whether the parenchyma is modeled as an elastic continuum or as a spring network. When the springs were arranged hexagonally to represent alveolar walls, the predicted parenchymal stresses and displacements propagated substantially farther away from the airway than when the springs were arranged in a triangular pattern or when the parenchyma was modeled as a continuum. Thus, to the extent that the parenchyma in vivo behaves as a hexagonal spring network, our results suggest that the range of interdependence forces due to airway contraction may have a greater influence than was previously thought. PMID:22500006
Schlötzer-Schrehardt, Ursula; Hammer, Christian M; Krysta, Anita W; Hofmann-Rummelt, Carmen; Pasutto, Francesca; Sasaki, Takako; Kruse, Friedrich E; Zenkel, Matthias
2012-09-01
To test the hypothesis that a primary disturbance in lysyl oxidase-like 1 (LOXL1) and elastin metabolism in the lamina cribrosa of eyes with pseudoexfoliation syndrome constitutes an independent risk factor for glaucoma development and progression. Observational, consecutive case series. Posterior segment tissues obtained from 37 donors with early and late stages of pseudoexfoliation syndrome without glaucoma, 37 normal age-matched control subjects, 5 eyes with pseudoexfoliation-associated open-angle glaucoma, and 5 eyes with primary open-angle glaucoma (POAG). Protein and mRNA expression of major elastic fiber components (elastin, fibrillin-1, fibulin-4), collagens (types I, III, and IV), and lysyl oxidase crosslinking enzymes (LOX, LOXL1, LOXL2) were assessed in situ by quantitative real-time polymerase chain reaction, (immuno)histochemistry, and light and electron microscopy. Lysyl oxidase-dependent elastin fiber assembly was assessed by primary optic nerve head astrocytes in vitro. Expression levels of elastic proteins, collagens, and lysyl oxidases in the lamina cribrosa. Lysyl oxidase-like 1 proved to be the major lysyl oxidase isoform in the normal lamina cribrosa in association with a complex elastic fiber network. Compared with normal and POAG specimens, lamina cribrosa tissues obtained from early and late stages of pseudoexfoliation syndrome without and with glaucoma consistently revealed a significant coordinated downregulation of LOXL1 and elastic fiber constituents on mRNA and protein level. In contrast, expression levels of collagens and other lysyl oxidase isoforms were not affected. Dysregulated expression of LOXL1 and elastic proteins was associated with pronounced (ultra)structural alterations of the elastic fiber network in the laminar beams of pseudoexfoliation syndrome eyes. Inhibition of LOXL1 interfered with elastic fiber assembly by optic nerve head astrocytes in vitro. The findings provide evidence for a pseudoexfoliation-specific elastinopathy of the lamina cribrosa resulting from a primary disturbance in LOXL1 regulation and elastic fiber homeostasis, possibly rendering pseudoexfoliation syndrome eyes more vulnerable to pressure-induced optic nerve damage and glaucoma development and progression. Copyright © 2012 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Yoon, Gwonchan; Lee, Myeongsang; Kim, Kyungwoo; In Kim, Jae; Chang, Hyun Joon; Baek, Inchul; Eom, Kilho; Na, Sungsoo
2015-12-01
Amyloid fibrils are responsible for pathogenesis of various diseases and exhibit the structural feature of an ordered, hierarchical structure such as multi-stranded helical structure. As the multi-strandedness of amyloid fibrils has recently been found to be highly correlated with their toxicity and infectivity, it is necessary to study how the hierarchical (i.e. multi-stranded) structure of amyloid fibril is formed. Moreover, although it has recently been reported that the nanomechanics of amyloid proteins plays a key role on the amyloid-induced pathogenesis, a critical role that the multi-stranded helical structure of the fibrils plays in their nanomechanical properties has not fully characterized. In this work, we characterize the morphology and mechanical properties of multi-stranded amyloid fibrils by using equilibrium molecular dynamics simulation and elastic network model. It is shown that the helical pitch of multi-stranded amyloid fibril is linearly proportional to the number of filaments comprising the amyloid fibril, and that multi-strandedness gives rise to improving the bending rigidity of the fibril. Moreover, we have also studied the morphology and mechanical properties of a single protofilament (filament) in order to understand the effect of cross-β structure and mutation on the structures and mechanical properties of amyloid fibrils. Our study sheds light on the underlying design principles showing how the multi-stranded amyloid fibril is formed and how the structure of amyloid fibrils governs their nanomechanical properties.
Renormalization group contraction of tensor networks in three dimensions
NASA Astrophysics Data System (ADS)
García-Sáez, Artur; Latorre, José I.
2013-02-01
We present a new strategy for contracting tensor networks in arbitrary geometries. This method is designed to follow as strictly as possible the renormalization group philosophy, by first contracting tensors in an exact way and, then, performing a controlled truncation of the resulting tensor. We benchmark this approximation procedure in two dimensions against an exact contraction. We then apply the same idea to a three-dimensional quantum system. The underlying rational for emphasizing the exact coarse graining renormalization group step prior to truncation is related to monogamy of entanglement.
Shi, Wei; Yun, Han; Lin, Charlie; Greenberg, Mark; Wang, Xu; Wang, Yun; Fard, Sahba Talebi; Flueckiger, Jonas; Jaeger, Nicolas A F; Chrostowski, Lukas
2013-03-25
Wavelength-division-multiplexing (WDM) networks with wide channel grids and bandwidths are promising for low-cost, low-power optical interconnects. Wide-bandwidth, single-band (i.e., no free-spectral range) add-drop filters have been developed on silicon using anti-reflection contra-directional couplers with out-of-phase Bragg gratings. Using such filter components, we demonstrate a 4-channel, coarse-WDM demultiplexer with flat passbands of up to 13 nm and an ultra-compact size of 1.2 × 10(-3) mm(2).
NASA Astrophysics Data System (ADS)
Zahouani, H.; Djaghloul, M.; Vargiolu, R.; Mezghani, S.; Mansori, M. E. L.
2014-03-01
The structuring of the dermis with a network of collagen and elastic fibres gives a three-dimensional structure to the skin network with directions perpendicular and parallel to the skin surface. This three-dimensional morphology prints on the surface of the stratum corneum a three dimensional network of lines which express the mechanical tension of the skin at rest. To evaluate the changes of skin morphology, we used a three-dimensional confocal microscopy and characterization of skin imaging of volar forearm microrelief. We have accurately characterize the role of skin line network during chronological aging with the identification of depth scales on the network of lines (z <= 60μm) and the network of lines covering Langer's lines (z > 60 microns). During aging has been highlighted lower rows for elastic fibres, the decrease weakened the tension and results in enlargement of the plates of the microrelief, which gives us a geometric pertinent indicator to quantify the loss of skin tension and assess the stage of aging. The study of 120 Caucasian women shows that ageing in the volar forearm zone results in changes in the morphology of the line network organisation. The decrease in secondary lines (z <= 60 μm) is counterbalanced by an increase in the depth of the primary lines (z > 60 μm) and an accentuation of the anisotropy index.
Biologically Derived Soft Conducting Hydrogels Using Heparin-Doped Polymer Networks
2015-01-01
The emergence of flexible and stretchable electronic components expands the range of applications of electronic devices. Flexible devices are ideally suited for electronic biointerfaces because of mechanically permissive structures that conform to curvilinear structures found in native tissue. Most electronic materials used in these applications exhibit elastic moduli on the order of 0.1–1 MPa. However, many electronically excitable tissues exhibit elasticities in the range of 1–10 kPa, several orders of magnitude smaller than existing components used in flexible devices. This work describes the use of biologically derived heparins as scaffold materials for fabricating networks with hybrid electronic/ionic conductivity and ultracompliant mechanical properties. Photo-cross-linkable heparin–methacrylate hydrogels serve as templates to control the microstructure and doping of in situ polymerized polyaniline structures. Macroscopic heparin-doped polyaniline hydrogel dual networks exhibit impedances as low as Z = 4.17 Ω at 1 kHz and storage moduli of G′ = 900 ± 100 Pa. The conductivity of heparin/polyaniline networks depends on the oxidation state and microstructure of secondary polyaniline networks. Furthermore, heparin/polyaniline networks support the attachment, proliferation, and differentiation of murine myoblasts without any surface treatments. Taken together, these results suggest that heparin/polyaniline hydrogel networks exhibit suitable physical properties as an electronically active biointerface material that can match the mechanical properties of soft tissues composed of excitable cells. PMID:24738911
Numerical methods for solving moment equations in kinetic theory of neuronal network dynamics
NASA Astrophysics Data System (ADS)
Rangan, Aaditya V.; Cai, David; Tao, Louis
2007-02-01
Recently developed kinetic theory and related closures for neuronal network dynamics have been demonstrated to be a powerful theoretical framework for investigating coarse-grained dynamical properties of neuronal networks. The moment equations arising from the kinetic theory are a system of (1 + 1)-dimensional nonlinear partial differential equations (PDE) on a bounded domain with nonlinear boundary conditions. The PDEs themselves are self-consistently specified by parameters which are functions of the boundary values of the solution. The moment equations can be stiff in space and time. Numerical methods are presented here for efficiently and accurately solving these moment equations. The essential ingredients in our numerical methods include: (i) the system is discretized in time with an implicit Euler method within a spectral deferred correction framework, therefore, the PDEs of the kinetic theory are reduced to a sequence, in time, of boundary value problems (BVPs) with nonlinear boundary conditions; (ii) a set of auxiliary parameters is introduced to recast the original BVP with nonlinear boundary conditions as BVPs with linear boundary conditions - with additional algebraic constraints on the auxiliary parameters; (iii) a careful combination of two Newton's iterates for the nonlinear BVP with linear boundary condition, interlaced with a Newton's iterate for solving the associated algebraic constraints is constructed to achieve quadratic convergence for obtaining the solutions with self-consistent parameters. It is shown that a simple fixed-point iteration can only achieve a linear convergence for the self-consistent parameters. The practicability and efficiency of our numerical methods for solving the moment equations of the kinetic theory are illustrated with numerical examples. It is further demonstrated that the moment equations derived from the kinetic theory of neuronal network dynamics can very well capture the coarse-grained dynamical properties of integrate-and-fire neuronal networks.
Simulation of Blast Loading on an Ultrastructurally-based Computational Model of the Ocular Lens
2016-12-01
organelles. Additionally, the cell membranes demonstrated the classic ball-and-socket loops . For the SEM images, they were placed in two fixatives and mounted...considered (fibrous network and matrix), both components are modelled using a hyper - elastic framework, and the resulting constitutive model is embedded in a...within the framework of hyper - elasticity). Full details on the linearization procedures that were adopted in these previous models or the convergence
Kinetic Theories for Biofilms (Preprint)
2011-01-01
2011 2. REPORT TYPE 3. DATES COVERED 00-00-2011 to 00-00-2011 4. TITLE AND SUBTITLE Kinetic Theories for Biofilms 5a. CONTRACT NUMBER 5b...binary complex fluids to develop a set of hydrodynamic models for the two-phase mixture of biofilms and solvent (water). It is aimed to model...kinetics along with the intrinsic molecular elasticity of the EPS network strand modeled as an elastic dumbbell. This theory is valid in both the biofilm
3D printing of an interpenetrating network hydrogel material with tunable viscoelastic properties.
Bootsma, Katherine; Fitzgerald, Martha M; Free, Brandon; Dimbath, Elizabeth; Conjerti, Joe; Reese, Greg; Konkolewicz, Dominik; Berberich, Jason A; Sparks, Jessica L
2017-06-01
Interpenetrating network (IPN) hydrogel materials are recognized for their unique mechanical properties. While IPN elasticity and toughness properties have been explored in previous studies, the factors that impact the time-dependent stress relaxation behavior of IPN materials are not well understood. Time-dependent (i.e. viscoelastic) mechanical behavior is a critical design parameter in the development of materials for a variety of applications, such as medical simulation devices, flexible substrate materials, cellular mechanobiology substrates, or regenerative medicine applications. This study reports a novel technique for 3D printing alginate-polyacrylamide IPN gels with tunable elastic and viscoelastic properties. The viscoelastic stress relaxation behavior of the 3D printed alginate-polyacrylamide IPN hydrogels was influenced most strongly by varying the concentration of the acrylamide cross-linker (MBAA), while the elastic modulus was affected most by varying the concentration of total monomer material. The material properties of our 3D printed IPN constructs were consistent with those reported in the biomechanics literature for soft tissues such as skeletal muscle, cardiac muscle, skin and subcutaneous tissue. Copyright © 2017 Elsevier Ltd. All rights reserved.
Combined distributed and concentrated transducer network for failure indication
NASA Astrophysics Data System (ADS)
Ostachowicz, Wieslaw; Wandowski, Tomasz; Malinowski, Pawel
2010-03-01
In this paper algorithm for discontinuities localisation in thin panels made of aluminium alloy is presented. Mentioned algorithm uses Lamb wave propagation methods for discontinuities localisation. Elastic waves were generated and received using piezoelectric transducers. They were arranged in concentrated arrays distributed on the specimen surface. In this way almost whole specimen could be monitored using this combined distributed-concentrated transducer network. Excited elastic waves propagate and reflect from panel boundaries and discontinuities existing in the panel. Wave reflection were registered through the piezoelectric transducers and used in signal processing algorithm. Proposed processing algorithm consists of two parts: signal filtering and extraction of obstacles location. The first part was used in order to enhance signals by removing noise from them. Second part allowed to extract features connected with wave reflections from discontinuities. Extracted features damage influence maps were a basis to create damage influence maps. Damage maps indicated intensity of elastic wave reflections which corresponds to obstacles coordinates. Described signal processing algorithms were implemented in the MATLAB environment. It should be underlined that in this work results based only on experimental signals were presented.
Fragmenting networks by targeting collective influencers at a mesoscopic level.
Kobayashi, Teruyoshi; Masuda, Naoki
2016-11-25
A practical approach to protecting networks against epidemic processes such as spreading of infectious diseases, malware, and harmful viral information is to remove some influential nodes beforehand to fragment the network into small components. Because determining the optimal order to remove nodes is a computationally hard problem, various approximate algorithms have been proposed to efficiently fragment networks by sequential node removal. Morone and Makse proposed an algorithm employing the non-backtracking matrix of given networks, which outperforms various existing algorithms. In fact, many empirical networks have community structure, compromising the assumption of local tree-like structure on which the original algorithm is based. We develop an immunization algorithm by synergistically combining the Morone-Makse algorithm and coarse graining of the network in which we regard a community as a supernode. In this way, we aim to identify nodes that connect different communities at a reasonable computational cost. The proposed algorithm works more efficiently than the Morone-Makse and other algorithms on networks with community structure.
Fragmenting networks by targeting collective influencers at a mesoscopic level
NASA Astrophysics Data System (ADS)
Kobayashi, Teruyoshi; Masuda, Naoki
2016-11-01
A practical approach to protecting networks against epidemic processes such as spreading of infectious diseases, malware, and harmful viral information is to remove some influential nodes beforehand to fragment the network into small components. Because determining the optimal order to remove nodes is a computationally hard problem, various approximate algorithms have been proposed to efficiently fragment networks by sequential node removal. Morone and Makse proposed an algorithm employing the non-backtracking matrix of given networks, which outperforms various existing algorithms. In fact, many empirical networks have community structure, compromising the assumption of local tree-like structure on which the original algorithm is based. We develop an immunization algorithm by synergistically combining the Morone-Makse algorithm and coarse graining of the network in which we regard a community as a supernode. In this way, we aim to identify nodes that connect different communities at a reasonable computational cost. The proposed algorithm works more efficiently than the Morone-Makse and other algorithms on networks with community structure.
Fragmenting networks by targeting collective influencers at a mesoscopic level
Kobayashi, Teruyoshi; Masuda, Naoki
2016-01-01
A practical approach to protecting networks against epidemic processes such as spreading of infectious diseases, malware, and harmful viral information is to remove some influential nodes beforehand to fragment the network into small components. Because determining the optimal order to remove nodes is a computationally hard problem, various approximate algorithms have been proposed to efficiently fragment networks by sequential node removal. Morone and Makse proposed an algorithm employing the non-backtracking matrix of given networks, which outperforms various existing algorithms. In fact, many empirical networks have community structure, compromising the assumption of local tree-like structure on which the original algorithm is based. We develop an immunization algorithm by synergistically combining the Morone-Makse algorithm and coarse graining of the network in which we regard a community as a supernode. In this way, we aim to identify nodes that connect different communities at a reasonable computational cost. The proposed algorithm works more efficiently than the Morone-Makse and other algorithms on networks with community structure. PMID:27886251
William H. McWilliams; Stanford L. Arner; Charles J. Barnett
1997-01-01
The USDA Forest Service's Forest Inventory and Analysis (FIA) program and the Forest Health Monitoring (FHM) program maintain networks of sample locations providing coarse-scale information that characterize general indicators of forest health. Tree mortality is the primary FIA variable for analyzing forest health. Recent FIA inventories of New York, Pennsylvania...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Biao
We use the NOvA near detector and the NuMI beam at Fermilab to study the neutrino- electron elastic scattering and the muon neutrino magnetic process beyond the Standard Model physics. The particle identications of neutrino on electron elastic scattering are trained by using the multi-layer neural networks. This thesis provides a general discussion of this technique and shows a good agreement between data and MC for the neutrino-electron elastic weak scattering. So that beneting from the precise cross-section of this channel, we are able to tune the neutrino beam ux simulation in the future. Giving the exposure of 3:62 1020more » POT in the NOvA near detector, we report 1:58 10« less
Non-affine deformations in polymer hydrogels
Wen, Qi; Basu, Anindita; Janmey, Paul A.; Yodh, A. G.
2012-01-01
Most theories of soft matter elasticity assume that the local strain in a sample after deformation is identical everywhere and equal to the macroscopic strain, or equivalently that the deformation is affine. We discuss the elasticity of hydrogels of crosslinked polymers with special attention to affine and non-affine theories of elasticity. Experimental procedures to measure non-affine deformations are also described. Entropic theories, which account for gel elasticity based on stretching out individual polymer chains, predict affine deformations. In contrast, simulations of network deformation that result in bending of the stiff constituent filaments generally predict non-affine behavior. Results from experiments show significant non-affine deformation in hydrogels even when they are formed by flexible polymers for which bending would appear to be negligible compared to stretching. However, this finding is not necessarily an experimental proof of the non-affine model for elasticity. We emphasize the insights gained from experiments using confocal rheoscope and show that, in addition to filament bending, sample micro-inhomogeneity can be a significant alternative source of non-affine deformation. PMID:23002395
El Nady, K; Ganghoffer, J F
2016-05-01
The asymptotic homogenization technique is involved to derive the effective elastic response of biological membranes viewed as repetitive beam networks. Thereby, a systematic methodology is established, allowing the prediction of the overall mechanical properties of biological membranes in the nonlinear regime, reflecting the influence of the geometrical and mechanical micro-parameters of the network structure on the overall response of the equivalent continuum. Biomembranes networks are classified based on nodal connectivity, so that we analyze in this work 3, 4 and 6-connectivity networks, which are representative of most biological networks. The individual filaments of the network are described as undulated beams prone to entropic elasticity, with tensile moduli determined from their persistence length. The effective micropolar continuum evaluated as a continuum substitute of the biological network has a kinematics reflecting the discrete network deformation modes, involving a nodal displacement and a microrotation. The statics involves the classical Cauchy stress and internal moments encapsulated into couple stresses, which develop internal work in duality to microcurvatures reflecting local network undulations. The relative ratio of the characteristic bending length of the effective micropolar continuum to the unit cell size determines the relevant choice of the equivalent medium. In most cases, the Cauchy continuum is sufficient to model biomembranes. The peptidoglycan network may exhibit a re-entrant hexagonal configuration due to thermal or pressure fluctuations, for which micropolar effects become important. The homogenized responses are in good agreement with FE simulations performed over the whole network. The predictive nature of the employed homogenization technique allows the identification of a strain energy density of a hyperelastic model, for the purpose of performing structural calculations of the shape evolutions of biomembranes. Copyright © 2015 Elsevier Ltd. All rights reserved.
Zhang, Jingsi; Li, Ning; Dai, Xiaohu; Tao, Wenquan; Jenkinson, Ian R; Li, Zhuo
2017-12-19
Comprehensive insights into the sludge digestate dewaterability were gained through porous network structure of sludge. We measured the evolution of digestate dewaterability, represented by the solid content of centrifugally dewatered cake, in high-solids sequencing batch digesters with and without thermal hydrolysis pretreatment (THP). The results show that the dewaterability of the sludge after digestion was improved by 3.5% (±0.5%) for unpretreated sludge and 5.1% (±0.4%) for thermally hydrolyzed sludge. Compared to the unpretreated sludge digestate, thermal hydrolysis pretreatment eventually resulted in an improvement of dewaterability by 4.6% (±0.5%). Smaller particle size and larger surface area of sludge were induced by thermal hydrolysis and anaerobic digestion treatments. The structure strength and compactness of sludge, represented by elastic modulus and fractal dimension respectively, decreased with increase of digestion time. The porous network structure was broken up by thermal hydrolysis pretreatment and was further weakened during anaerobic digestion, which correspondingly improved the dewaterability of digestates. The logarithm of elastic modulus increased linearly with fractal dimension regardless of the pretreatment. Both fractal dimension and elastic modulus showed linear relationship with dewaterability. The rheological characterization combined with the analysis of fractal dimension of sewage sludge porous network structure was found applicable in quantitative evaluation of sludge dewaterability, which depended positively on both thermal hydrolysis and anaerobic digestion. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Muir, J.; Phinn, S. R.; Armston, J.; Scarth, P.; Eyre, T.
2014-12-01
Coarse woody debris (CWD) provides important habitat for many species and plays a vital role in nutrient cycling within an ecosystem. In addition, CWD makes an important contribution to forest biomass and fuel loads. Airborne or space based remote sensing instruments typically do not detect CWD beneath the forest canopy. Terrestrial laser scanning (TLS) provides a ground based method for three-dimensional (3-D) reconstruction of surface features and CWD. This research produced a 3-D reconstruction of the ground surface and automatically classified coarse woody debris from registered TLS scans. The outputs will be used to inform the development of a site-based index for the assessment of forest condition, and quantitative assessments of biomass and fuel loads. A survey grade terrestrial laser scanner (Riegl VZ400) was used to scan 13 positions, in an open eucalypt woodland site at Karawatha Forest Park, near Brisbane, Australia. Scans were registered, and a digital surface model (DSM) produced using an intensity threshold and an iterative morphological filter. The DSMs produced from single scans were compared to the registered multi-scan point cloud using standard error metrics including: Root Mean Squared Error (RMSE), Mean Squared Error (MSE), range, absolute error and signed error. In addition the DSM was compared to a Digital Elevation Model (DEM) produced from Airborne Laser Scanning (ALS). Coarse woody debris was subsequently classified from the DSM using laser pulse properties, including: width and amplitude, as well as point spatial relationships (e.g. nearest neighbour slope vectors). Validation of the coarse woody debris classification was completed using true-colour photographs co-registered to the TLS point cloud. The volume and length of the coarse woody debris was calculated from the classified point cloud. A representative network of TLS sites will allow for up-scaling to large area assessment using airborne or space based sensors to monitor forest condition, biomass and fuel loads.
Coarse-grained Brownian ratchet model of membrane protrusion on cellular scale.
Inoue, Yasuhiro; Adachi, Taiji
2011-07-01
Membrane protrusion is a mechanochemical process of active membrane deformation driven by actin polymerization. Previously, Brownian ratchet (BR) was modeled on the basis of the underlying molecular mechanism. However, because the BR requires a priori load that cannot be determined without information of the cell shape, it cannot be effective in studies in which resultant shapes are to be solved. Other cellular-scale models describing the protrusion have also been suggested for modeling a whole cell; however, these models were not developed on the basis of coarse-grained physics representing the underlying molecular mechanism. Therefore, to express the membrane protrusion on the cellular scale, we propose a novel mathematical model, the coarse-grained BR (CBR), which is derived on the basis of nonequilibrium thermodynamics theory. The CBR can reproduce the BR within the limit of the quasistatic process of membrane protrusion and can estimate the protrusion velocity consistently with an effective elastic constant that represents the state of the energy of the membrane. Finally, to demonstrate the applicability of the CBR, we attempt to perform a cellular-scale simulation of migrating keratocyte in which the proposed CBR is used for the membrane protrusion model on the cellular scale. The results show that the experimentally observed shapes of the leading edge are well reproduced by the simulation. In addition, The trend of dependences of the protrusion velocity on the curvature of the leading edge, the temperature, and the substrate stiffness also agreed with the other experimental results. Thus, the CBR can be considered an appropriate cellular-scale model to express the membrane protrusion on the basis of its underlying molecular mechanism.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yoo, S.J.Ben; Lauer, Gregory S.
Extreme-science drives the need for distributed exascale processing and communications that are carefully, yet flexibly, managed. Exponential growth of data for scientific simulations, experimental data, collaborative data analyses, remote visualization and GRID computing requirements of scientists in fields as diverse as high energy physics, climate change, genomics, fusion, synchrotron radiation, material science, medicine, and other scientific disciplines cannot be accommodated by simply applying existing transport protocols to faster pipes. Further, scientific challenges today demand diverse research teams, heightening the need for and increasing the complexity of collaboration. To address these issues within the network layer and physical layer, we havemore » performed a number of research activities surrounding effective allocation and management of elastic optical network (EON) resources, particularly focusing on FlexGrid transponders. FlexGrid transponders support the opportunity to build Layer-1 connections at a wide range of bandwidths and to reconfigure them rapidly. The new flexibility supports complex new ways of using the physical layer that must be carefully managed and hidden from the scientist end-users. FlexGrid networks utilize flexible (or elastic) spectral bandwidths for each data link without using fixed wavelength grids. The flexibility in spectrum allocation brings many appealing features to network operations. Current networks are designed for the worst case impairments in transmission performance and the assigned spectrum is over-provisioned. In contrast, the FlexGrid networks can operate with the highest spectral efficiency and minimum bandwidth for the given traffic demand while meeting the minimum quality of transmission (QoT) requirement. Two primary focuses of our research are: (1) resource and spectrum allocation (RSA) for IP traffic over EONs, and (2) RSA for cross-domain optical networks. Previous work concentrates primarily on large file transfers within a single domain. Adding support for IP traffic changes the nature of the RSA problem: instead of choosing to accept or deny each request for network support, IP traffic is inherently elastic and thus lends itself to a bandwidth maximization formulation. We developed a number of algorithms that could be easily deployed within existing and new FlexGrid networks, leading to networks that better support scientific collaboration. Cross-domain RSA research is essential to support large-scale FlexGrid networks, since configuration information is generally not shared or coordinated across domains. The results presented here are in their early stages. They are technically feasible and practical, but still require coordination among organizations and equipment owners and a higher-layer framework for managing network requests.« less
The role of capture spiral silk properties in the diversification of orb webs
Tarakanova, Anna; Buehler, Markus J.
2012-01-01
Among a myriad of spider web geometries, the orb web presents a fascinating, exquisite example in architecture and evolution. Orb webs can be divided into two categories according to the capture silk used in construction: cribellate orb webs (composed of pseudoflagelliform silk) coated with dry cribellate threads and ecribellate orb webs (composed of flagelliform silk fibres) coated by adhesive glue droplets. Cribellate capture silk is generally stronger but less-extensible than viscid capture silk, and a body of phylogenic evidence suggests that cribellate capture silk is more closely related to the ancestral form of capture spiral silk. Here, we use a coarse-grained web model to investigate how the mechanical properties of spiral capture silk affect the behaviour of the whole web, illustrating that more elastic capture spiral silk yields a decrease in web system energy absorption, suggesting that the function of the capture spiral shifted from prey capture to other structural roles. Additionally, we observe that in webs with more extensible capture silk, the effect of thread strength on web performance is reduced, indicating that thread elasticity is a dominant driving factor in web diversification. PMID:22896566
Johnathan E. Goodsell; Robert J. Moon; Alionso Huizar; R. Byron Pipes
2014-01-01
The reinforcement potential of cellulose nanocrystal (CNC) additions on an idealized 2-dirmensional (2-D) fiber network structure consisting of micron sized fiber elements was investigated. The reinforcement mechanism considered in this study was through the stiffening of the micron sized fiber elements via a CNC-epoxy coating. A hierarchical analytical modeling...
NASA Astrophysics Data System (ADS)
Zhang, Quan-Ping; Liu, Jun-Hua; Liu, Hai-Dong; Jia, Fei; Zhou, Yuan-Lin; Zheng, Jian
2017-10-01
Adding ceramic or conductive fillers into polymers for increasing permittivity is a direct and effective approach to enhance the actuation strain of dielectric elastomer actuators (DEAs). Unfortunately, the major dielectric loss caused by weak interfaces potentially harms the electro-mechanical stability and lifetime of DEAs. Here, we construct a desired macromolecular network with a long chain length and low cross-link density to reduce the elastic modulus of silicone elastomers. Selecting a high molecular weight of polymethylvinylsiloxane and a low dose of the cross-linker leads the soft but tough networks with rich entanglements, poor cross-links, and a low amount of defects. Then, a ductile material with low elastic modulus but high elongation at break is obtained. It accounts for much more excellent actuation strain of Hl in comparison to that of the other silicone elastomers. Importantly, without other fillers, the ultralow dielectric loss, conductivity, and firm networks possibly promote the electro-mechanical stability and lifetime for the DEA application.
Hardness, elastic, and electronic properties of chromium monoboride
Han, Lei; Wang, Shanmin; Zhu, Jinlong; ...
2015-06-03
Here, we report high-pressure synthesis of chromium monoboride (CrB) at 6 GPa and 1400 K. The elastic and plastic behaviors have been investigated by hydrostatic compression experiment and micro-indentation measurement. CrB is elastically incompressible with a high bulk modulus of 269.0 (5.9) GPa and exhibits a high Vickers hardness of 19.6 (0.7) GPa under the load of 1 kg force. Based on first principles calculations, the observed mechanical properties are attributed to the polar covalent Cr-B bonds interconnected with strong zigzag B-B covalent bonding network. The presence of metallic Cr bilayers is presumably responsible for the weakest paths in shearmore » deformation.« less
Application of artificial neural networks in nonlinear analysis of trusses
NASA Technical Reports Server (NTRS)
Alam, J.; Berke, L.
1991-01-01
A method is developed to incorporate neural network model based upon the Backpropagation algorithm for material response into nonlinear elastic truss analysis using the initial stiffness method. Different network configurations are developed to assess the accuracy of neural network modeling of nonlinear material response. In addition to this, a scheme based upon linear interpolation for material data, is also implemented for comparison purposes. It is found that neural network approach can yield very accurate results if used with care. For the type of problems under consideration, it offers a viable alternative to other material modeling methods.
Multicasting based optical inverse multiplexing in elastic optical network.
Guo, Bingli; Xu, Yingying; Zhu, Paikun; Zhong, Yucheng; Chen, Yuanxiang; Li, Juhao; Chen, Zhangyuan; He, Yongqi
2014-06-16
Optical multicasting based inverse multiplexing (IM) is introduced in spectrum allocation of elastic optical network to resolve the spectrum fragmentation problem, where superchannels could be split and fit into several discrete spectrum blocks in the intermediate node. We experimentally demonstrate it with a 1-to-7 optical superchannel multicasting module and selecting/coupling components. Also, simulation results show that, comparing with several emerging spectrum defragmentation solutions (e.g., spectrum conversion, split spectrum), IM could reduce blocking performance significantly but without adding too much system complexity as split spectrum. On the other hand, service fairness for traffic with different granularity of these schemes is investigated for the first time and it shows that IM performs better than spectrum conversion and almost as well as split spectrum, especially for smaller size traffic under light traffic intensity.
Frustration in protein elastic network models
NASA Astrophysics Data System (ADS)
Lezon, Timothy; Bahar, Ivet
2010-03-01
Elastic network models (ENMs) are widely used for studying the equilibrium dynamics of proteins. The most common approach in ENM analysis is to adopt a uniform force constant or a non-specific distance dependent function to represent the force constant strength. Here we discuss the influence of sequence and structure in determining the effective force constants between residues in ENMs. Using a novel method based on entropy maximization, we optimize the force constants such that they exactly reporduce a subset of experimentally determined pair covariances for a set of proteins. We analyze the optimized force constants in terms of amino acid types, distances, contact order and secondary structure, and we demonstrate that including frustrated interactions in the ENM is essential for accurately reproducing the global modes in the middle of the frequency spectrum.
Gurdián, Hebé; García-Alcocel, Eva; Baeza-Brotons, Francisco; Garcés, Pedro; Zornoza, Emilio
2014-04-21
The main strategy to reduce the environmental impact of the concrete industry is to reuse the waste materials. This research has considered the combination of cement replacement by industrial by-products, and natural coarse aggregate substitution by recycled aggregate. The aim is to evaluate the behavior of concretes with a reduced impact on the environment by replacing a 50% of cement by industrial by-products (15% of spent fluid catalytic cracking catalyst and 35% of fly ash) and a 100% of natural coarse aggregate by recycled aggregate. The concretes prepared according to these considerations have been tested in terms of mechanical strengths and the protection offered against steel reinforcement corrosion under carbonation attack and chloride-contaminated environments. The proposed concrete combinations reduced the mechanical performance of concretes in terms of elastic modulus, compressive strength, and flexural strength. In addition, an increase in open porosity due to the presence of recycled aggregate was observed, which is coherent with the changes observed in mechanical tests. Regarding corrosion tests, no significant differences were observed in the case of the resistance of these types of concretes under a natural chloride attack. In the case of carbonation attack, although all concretes did not stand the highly aggressive conditions, those concretes with cement replacement behaved worse than Portland cement concretes.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cook, Caitlyn Christian
An evaporation barrier is required to enhance the lifetime of electrophoretic deposition (EPD) displays. As EPD functions on the basis of reversible deposition and resuspension of colloids suspended in a solvent, evaporation of the solvent ultimately leads to device failure. Incorporation of a thiol-polybutadiene elastomer into EPD displays enabled display lifetime surpassing six months in counting and catalyzed rigid display transition into a flexible package. Final flexible display transition to mass production compels an electronic-ink approach to encapsulate display suspension within an elastomer shell. Final thiol-polybutadiene photosensitive resin network microstructure was idealized to be dense, homogeneous, and expose an elasticmore » response to deformation. Research at hand details an approach to understanding microstructural change within display elastomers. Polybutadiene-based resin properties are modified via polymer chain structure, with and without added aromatic urethane methacrylate difunctionality, and in measuring network response to variation in thiol and initiator concentration. Dynamic mechanical analysis results signify that cross-linked segments within a difunctionalized polybutadiene network were on average eight times more elastically active than that of linked segments within a non-functionalized polybutadiene network. Difunctionalized polybutadiene samples also showed a 2.5 times greater maximum elastic modulus than non-functionalized samples. Hybrid polymer composed of both polybutadiene chains encompassed TE-2000 stiffness and B-1000 elasticity for use in encapsulating display suspension. Later experiments measured kinetic and rheological response due to alteration in dithiol cross-linker chain length via real time Fourier transform infrared spectroscopy and real-time dynamic rheology. Distinct differences were discovered between dithiol resin systems, as maximum thiol conversion achieved in short and long chain length dithiols was 86% and 11%, respectively. Oscillatory real-time rheological experiments confirmed a more uniform network to better dissipate applied shear in short chain length dithiol systems, as long chain length dithiols relayed a steep internal stress build-up due to less cross-links and chain entanglements. Thorough understanding of network formation aids the production of a stronger and impermeable elastomeric barrier for preservation of EPD displays.« less
1990-05-25
INCLUDING ORIENTATIONAL INTERACTIONS BETWEEN CHAIN SEGMENTS B. Deloche, E.T. Samulski (France, USA) CHAIN SEGMENT ORDERING IN STRAINED BIMODAL P-2 PDMS...theory of elastomers is difficult because it requires a detailed study of many body interactions . A theory of elasticity must address the following: (1...a Kirchhoff matrix which describes the connectivity of the network (Kc) or the linear chains (Ku). The nonbonded interactions are handled with the
Cross-Linker Unbinding and Self-Similarity in Bundled Cytoskeletal Networks
NASA Astrophysics Data System (ADS)
Lieleg, O.; Bausch, A. R.
2007-10-01
The macromechanical properties of purely bundled in vitro actin networks are not only determined by the micromechanical properties of individual bundles but also by molecular unbinding events of the actin-binding protein (ABP) fascin. Under high mechanical load the network elasticity depends on the forced unbinding of individual ABPs in a rate dependent manner. Cross-linker unbinding in combination with the structural self-similarity of the network enables the introduction of a concentration-time superposition principle—broadening the mechanically accessible frequency range over 8 orders of magnitude.
Neural networks for sign language translation
NASA Astrophysics Data System (ADS)
Wilson, Beth J.; Anspach, Gretel
1993-09-01
A neural network is used to extract relevant features of sign language from video images of a person communicating in American Sign Language or Signed English. The key features are hand motion, hand location with respect to the body, and handshape. A modular hybrid design is under way to apply various techniques, including neural networks, in the development of a translation system that will facilitate communication between deaf and hearing people. One of the neural networks described here is used to classify video images of handshapes into their linguistic counterpart in American Sign Language. The video image is preprocessed to yield Fourier descriptors that encode the shape of the hand silhouette. These descriptors are then used as inputs to a neural network that classifies their shapes. The network is trained with various examples from different signers and is tested with new images from new signers. The results have shown that for coarse handshape classes, the network is invariant to the type of camera used to film the various signers and to the segmentation technique.
Comparative analysis of two discretizations of Ricci curvature for complex networks.
Samal, Areejit; Sreejith, R P; Gu, Jiao; Liu, Shiping; Saucan, Emil; Jost, Jürgen
2018-06-05
We have performed an empirical comparison of two distinct notions of discrete Ricci curvature for graphs or networks, namely, the Forman-Ricci curvature and Ollivier-Ricci curvature. Importantly, these two discretizations of the Ricci curvature were developed based on different properties of the classical smooth notion, and thus, the two notions shed light on different aspects of network structure and behavior. Nevertheless, our extensive computational analysis in a wide range of both model and real-world networks shows that the two discretizations of Ricci curvature are highly correlated in many networks. Moreover, we show that if one considers the augmented Forman-Ricci curvature which also accounts for the two-dimensional simplicial complexes arising in graphs, the observed correlation between the two discretizations is even higher, especially, in real networks. Besides the potential theoretical implications of these observations, the close relationship between the two discretizations has practical implications whereby Forman-Ricci curvature can be employed in place of Ollivier-Ricci curvature for faster computation in larger real-world networks whenever coarse analysis suffices.
Why glass elasticity affects the thermodynamics and fragility of supercooled liquids
Yan, Le; Düring, Gustavo; Wyart, Matthieu
2013-01-01
Supercooled liquids are characterized by their fragility: The slowing down of the dynamics under cooling is more sudden and the jump of specific heat at the glass transition is generally larger in fragile liquids than in strong ones. Despite the importance of this quantity in classifying liquids, explaining what aspects of the microscopic structure controls fragility remains a challenge. Surprisingly, experiments indicate that the linear elasticity of the glass—a purely local property of the free energy landscape—is a good predictor of fragility. In particular, materials presenting a large excess of soft elastic modes, the so-called boson peak, are strong. This is also the case for network liquids near the rigidity percolation, known to affect elasticity. Here we introduce a model of the glass transition based on the assumption that particles can organize locally into distinct configurations that are coupled spatially via elasticity. The model captures the mentioned observations connecting elasticity and fragility. We find that materials presenting an abundance of soft elastic modes have little elastic frustration: Energy is insensitive to most directions in phase space, leading to a small jump of specific heat. In this framework strong liquids turn out to lie the closest to a critical point associated with a rigidity or jamming transition, and their thermodynamic properties are related to the problem of number partitioning and to Hopfield nets in the limit of small memory. PMID:23576746
Why glass elasticity affects the thermodynamics and fragility of supercooled liquids.
Yan, Le; Düring, Gustavo; Wyart, Matthieu
2013-04-16
Supercooled liquids are characterized by their fragility: The slowing down of the dynamics under cooling is more sudden and the jump of specific heat at the glass transition is generally larger in fragile liquids than in strong ones. Despite the importance of this quantity in classifying liquids, explaining what aspects of the microscopic structure controls fragility remains a challenge. Surprisingly, experiments indicate that the linear elasticity of the glass--a purely local property of the free energy landscape--is a good predictor of fragility. In particular, materials presenting a large excess of soft elastic modes, the so-called boson peak, are strong. This is also the case for network liquids near the rigidity percolation, known to affect elasticity. Here we introduce a model of the glass transition based on the assumption that particles can organize locally into distinct configurations that are coupled spatially via elasticity. The model captures the mentioned observations connecting elasticity and fragility. We find that materials presenting an abundance of soft elastic modes have little elastic frustration: Energy is insensitive to most directions in phase space, leading to a small jump of specific heat. In this framework strong liquids turn out to lie the closest to a critical point associated with a rigidity or jamming transition, and their thermodynamic properties are related to the problem of number partitioning and to Hopfield nets in the limit of small memory.
Shaping through buckling in elastic gridshells: from camping tents to architectural roofs
NASA Astrophysics Data System (ADS)
Reis, Pedro
Elastic gridshells comprise an initially planar network of elastic rods that is actuated into a 3D shell-like structure by loading its extremities. This shaping results from elastic buckling and the subsequent geometrically nonlinear deformation of the grid structure. Architectural elastic gridshells first appeared in the 1970's. However, to date, only a limited number of examples have been constructed around the world, primarily due to the challenges involved in their structural design. Yet, elastic gridshells are highly appealing: they can cover wide spans with low self-weight, they allow for aesthetically pleasing shapes and their construction is typically simple and rapid. We study the mechanics of elastic gridshells by combining precision model experiments that explore their scale invariance, together with computer simulations that employ the Discrete Elastic Rods method. Excellent agreement is found between the two. Upon validation, the numerics are then used to systematically explore parameter space and identify general design principles for specific target final shapes. Our findings are rationalized using the theory of discrete Chebyshev nets, together with the group theory for crystals. Higher buckling modes occur for some configurations due to geometric incompatibility at the boundary and result in symmetry breaking. Along with the systematic classification of the various possible modes of deformation, we provide a reduced model that rationalizes form-finding in elastic gridshells. This work was done in collaboration with Changyeob Baek, Khalid Jawed and Andrew Sageman-Furnas. We are grateful to the NSF for funding (CAREER, CMMI-1351449).
NASA Astrophysics Data System (ADS)
Wang, Fu; Liu, Bo; Zhang, Lijia; Xin, Xiangjun; Tian, Qinghua; Zhang, Qi; Rao, Lan; Tian, Feng; Luo, Biao; Liu, Yingjun; Tang, Bao
2016-10-01
Elastic Optical Networks are considered to be a promising technology for future high-speed network. In this paper, we propose a RSA algorithm based on the ant colony optimization of minimum consecutiveness loss (ACO-MCL). Based on the effect of the spectrum consecutiveness loss on the pheromone in the ant colony optimization, the path and spectrum of the minimal impact on the network are selected for the service request. When an ant arrives at the destination node from the source node along a path, we assume that this path is selected for the request. We calculate the consecutiveness loss of candidate-neighbor link pairs along this path after the routing and spectrum assignment. Then, the networks update the pheromone according to the value of the consecutiveness loss. We save the path with the smallest value. After multiple iterations of the ant colony optimization, the final selection of the path is assigned for the request. The algorithms are simulated in different networks. The results show that ACO-MCL algorithm performs better in blocking probability and spectrum efficiency than other algorithms. Moreover, the ACO-MCL algorithm can effectively decrease spectrum fragmentation and enhance available spectrum consecutiveness. Compared with other algorithms, the ACO-MCL algorithm can reduce the blocking rate by at least 5.9% in heavy load.
Modeling epidemics on adaptively evolving networks: A data-mining perspective.
Kattis, Assimakis A; Holiday, Alexander; Stoica, Ana-Andreea; Kevrekidis, Ioannis G
2016-01-01
The exploration of epidemic dynamics on dynamically evolving ("adaptive") networks poses nontrivial challenges to the modeler, such as the determination of a small number of informative statistics of the detailed network state (that is, a few "good observables") that usefully summarize the overall (macroscopic, systems-level) behavior. Obtaining reduced, small size accurate models in terms of these few statistical observables--that is, trying to coarse-grain the full network epidemic model to a small but useful macroscopic one--is even more daunting. Here we describe a data-based approach to solving the first challenge: the detection of a few informative collective observables of the detailed epidemic dynamics. This is accomplished through Diffusion Maps (DMAPS), a recently developed data-mining technique. We illustrate the approach through simulations of a simple mathematical model of epidemics on a network: a model known to exhibit complex temporal dynamics. We discuss potential extensions of the approach, as well as possible shortcomings.
Deep neural network-based domain adaptation for classification of remote sensing images
NASA Astrophysics Data System (ADS)
Ma, Li; Song, Jiazhen
2017-10-01
We investigate the effectiveness of deep neural network for cross-domain classification of remote sensing images in this paper. In the network, class centroid alignment is utilized as a domain adaptation strategy, making the network able to transfer knowledge from the source domain to target domain on a per-class basis. Since predicted labels of target data should be used to estimate the centroid of each class, we use overall centroid alignment as a coarse domain adaptation method to improve the estimation accuracy. In addition, rectified linear unit is used as the activation function to produce sparse features, which may improve the separation capability. The proposed network can provide both aligned features and an adaptive classifier, as well as obtain label-free classification of target domain data. The experimental results using Hyperion, NCALM, and WorldView-2 remote sensing images demonstrated the effectiveness of the proposed approach.
Huang, Guoliang; Song, Fei; Wang, Xiaodong
2010-01-01
Elastic waves, especially guided waves, generated by a piezoelectric actuator/sensor network, have shown great potential for on-line health monitoring of advanced aerospace, nuclear, and automotive structures in recent decades. Piezoelectric materials can function as both actuators and sensors in these applications due to wide bandwidth, quick response and low costs. One of the most fundamental issues surrounding the effective use of piezoelectric actuators is the quantitative evaluation of the resulting elastic wave propagation by considering the coupled piezo-elastodynamic behavior between the actuator and the host medium. Accurate characterization of the local interfacial stress distribution between the actuator and the host medium is the key issue for the problem. This paper presents a review of the development of analytical, numerical and hybrid approaches for modeling of the coupled piezo-elastodynamic behavior. The resulting elastic wave propagation for structural health monitoring is also summarized.
Printable elastic conductors with a high conductivity for electronic textile applications
Matsuhisa, Naoji; Kaltenbrunner, Martin; Yokota, Tomoyuki; Jinno, Hiroaki; Kuribara, Kazunori; Sekitani, Tsuyoshi; Someya, Takao
2015-01-01
The development of advanced flexible large-area electronics such as flexible displays and sensors will thrive on engineered functional ink formulations for printed electronics where the spontaneous arrangement of molecules aids the printing processes. Here we report a printable elastic conductor with a high initial conductivity of 738 S cm−1 and a record high conductivity of 182 S cm−1 when stretched to 215% strain. The elastic conductor ink is comprised of Ag flakes, a fluorine rubber and a fluorine surfactant. The fluorine surfactant constitutes a key component which directs the formation of surface-localized conductive networks in the printed elastic conductor, leading to a high conductivity and stretchability. We demonstrate the feasibility of our inks by fabricating a stretchable organic transistor active matrix on a rubbery stretchability-gradient substrate with unimpaired functionality when stretched to 110%, and a wearable electromyogram sensor printed onto a textile garment. PMID:26109453
Skin Lesion Analysis towards Melanoma Detection Using Deep Learning Network.
Li, Yuexiang; Shen, Linlin
2018-02-11
Skin lesions are a severe disease globally. Early detection of melanoma in dermoscopy images significantly increases the survival rate. However, the accurate recognition of melanoma is extremely challenging due to the following reasons: low contrast between lesions and skin, visual similarity between melanoma and non-melanoma lesions, etc. Hence, reliable automatic detection of skin tumors is very useful to increase the accuracy and efficiency of pathologists. In this paper, we proposed two deep learning methods to address three main tasks emerging in the area of skin lesion image processing, i.e., lesion segmentation (task 1), lesion dermoscopic feature extraction (task 2) and lesion classification (task 3). A deep learning framework consisting of two fully convolutional residual networks (FCRN) is proposed to simultaneously produce the segmentation result and the coarse classification result. A lesion index calculation unit (LICU) is developed to refine the coarse classification results by calculating the distance heat-map. A straight-forward CNN is proposed for the dermoscopic feature extraction task. The proposed deep learning frameworks were evaluated on the ISIC 2017 dataset. Experimental results show the promising accuracies of our frameworks, i.e., 0.753 for task 1, 0.848 for task 2 and 0.912 for task 3 were achieved.
NASA Astrophysics Data System (ADS)
Kamali, M.; Shamsi, M.; Saidi, A. R.
2018-03-01
As a first endeavor, the effect of nonlinear elastic foundation on the postbuckling behavior of smart magneto-electro-elastic (MEE) composite nanotubes is investigated. The composite nanotube is affected by a non-uniform thermal environment. A typical MEE composite nanotube consists of microtubules (MTs) and carbon nanotubes (CNTs) with a MEE cylindrical nanoshell for smart control. It is assumed that the nanoscale layers of the system are coupled by a polymer matrix or filament network depending on the application. In addition to thermal loads, magneto-electro-mechanical loads are applied to the composite nanostructure. Length scale effects are taken into account using the nonlocal elasticity theory. The principle of virtual work and von Karman's relations are used to derive the nonlinear governing differential equations of MEE CNT-MT nanotubes. Using Galerkin's method, nonlinear critical buckling loads are determined. Various types of non-uniform temperature distribution in the radial direction are considered. Finally, the effects of various parameters such as the nonlinear constant of elastic medium, thermal loading factor and small scale coefficient on the postbuckling of MEE CNT-MT nanotubes are studied.
Competing dynamic phases of active polymer networks
NASA Astrophysics Data System (ADS)
Freedman, Simon; Banerjee, Shiladitya; Dinner, Aaron R.
Recent experiments on in-vitro reconstituted assemblies of F-actin, myosin-II motors, and cross-linking proteins show that tuning local network properties can changes the fundamental biomechanical behavior of the system. For example, by varying cross-linker density and actin bundle rigidity, one can switch between contractile networks useful for reshaping cells, polarity sorted networks ideal for directed molecular transport, and frustrated networks with robust structural properties. To efficiently investigate the dynamic phases of actomyosin networks, we developed a coarse grained non-equilibrium molecular dynamics simulation of model semiflexible filaments, molecular motors, and cross-linkers with phenomenologically defined interactions. The simulation's accuracy was verified by benchmarking the mechanical properties of its individual components and collective behavior against experimental results at the molecular and network scales. By adjusting the model's parameters, we can reproduce the qualitative phases observed in experiment and predict the protein characteristics where phase crossovers could occur in collective network dynamics. Our model provides a framework for understanding cells' multiple uses of actomyosin networks and their applicability in materials research. Supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program.
Fracture Simulation of Highly Crosslinked Polymer Networks: Triglyceride-Based Adhesives
NASA Astrophysics Data System (ADS)
Lorenz, Christian; Stevens, Mark; Wool, Richard
2003-03-01
The ACRES program at the U. of Delaware has shown that triglyceride oils derived from plants are a favorable alternative to the traditional adhesives. The triglyceride networks are formed from an initial mixture of styrene monomers, free-radical initiators and triglycerides. We have performed simulations to study the effect of physical composition and physical characteristics of the triglyceride network on the strength of triglyceride network. A coarse-grained, bead-spring model of the triglyceride system is used. The average triglyceride consists of 6 beads per chain, the styrenes are represented as a single bead and the initiators are two bead chains. The polymer network is formed using an off-lattice 3D Monte Carlo simulation, in which the initiators activate the styrene and triglyceride reactive sites and then bonds are randomly formed between the styrene and active triglyceride monomers producing a highly crosslinked polymer network. Molecular dynamics simulations of the network under tensile and shear strains were performed to determine the strength as a function of the network composition. The relationship between the network structure and its strength will also be discussed.
Mechanical metamaterials at the theoretical limit of isotropic elastic stiffness
NASA Astrophysics Data System (ADS)
Berger, J. B.; Wadley, H. N. G.; McMeeking, R. M.
2017-02-01
A wide variety of high-performance applications require materials for which shape control is maintained under substantial stress, and that have minimal density. Bio-inspired hexagonal and square honeycomb structures and lattice materials based on repeating unit cells composed of webs or trusses, when made from materials of high elastic stiffness and low density, represent some of the lightest, stiffest and strongest materials available today. Recent advances in 3D printing and automated assembly have enabled such complicated material geometries to be fabricated at low (and declining) cost. These mechanical metamaterials have properties that are a function of their mesoscale geometry as well as their constituents, leading to combinations of properties that are unobtainable in solid materials; however, a material geometry that achieves the theoretical upper bounds for isotropic elasticity and strain energy storage (the Hashin-Shtrikman upper bounds) has yet to be identified. Here we evaluate the manner in which strain energy distributes under load in a representative selection of material geometries, to identify the morphological features associated with high elastic performance. Using finite-element models, supported by analytical methods, and a heuristic optimization scheme, we identify a material geometry that achieves the Hashin-Shtrikman upper bounds on isotropic elastic stiffness. Previous work has focused on truss networks and anisotropic honeycombs, neither of which can achieve this theoretical limit. We find that stiff but well distributed networks of plates are required to transfer loads efficiently between neighbouring members. The resulting low-density mechanical metamaterials have many advantageous properties: their mesoscale geometry can facilitate large crushing strains with high energy absorption, optical bandgaps and mechanically tunable acoustic bandgaps, high thermal insulation, buoyancy, and fluid storage and transport. Our relatively simple design can be manufactured using origami-like sheet folding and bonding methods.
Mechanical metamaterials at the theoretical limit of isotropic elastic stiffness.
Berger, J B; Wadley, H N G; McMeeking, R M
2017-03-23
A wide variety of high-performance applications require materials for which shape control is maintained under substantial stress, and that have minimal density. Bio-inspired hexagonal and square honeycomb structures and lattice materials based on repeating unit cells composed of webs or trusses, when made from materials of high elastic stiffness and low density, represent some of the lightest, stiffest and strongest materials available today. Recent advances in 3D printing and automated assembly have enabled such complicated material geometries to be fabricated at low (and declining) cost. These mechanical metamaterials have properties that are a function of their mesoscale geometry as well as their constituents, leading to combinations of properties that are unobtainable in solid materials; however, a material geometry that achieves the theoretical upper bounds for isotropic elasticity and strain energy storage (the Hashin-Shtrikman upper bounds) has yet to be identified. Here we evaluate the manner in which strain energy distributes under load in a representative selection of material geometries, to identify the morphological features associated with high elastic performance. Using finite-element models, supported by analytical methods, and a heuristic optimization scheme, we identify a material geometry that achieves the Hashin-Shtrikman upper bounds on isotropic elastic stiffness. Previous work has focused on truss networks and anisotropic honeycombs, neither of which can achieve this theoretical limit. We find that stiff but well distributed networks of plates are required to transfer loads efficiently between neighbouring members. The resulting low-density mechanical metamaterials have many advantageous properties: their mesoscale geometry can facilitate large crushing strains with high energy absorption, optical bandgaps and mechanically tunable acoustic bandgaps, high thermal insulation, buoyancy, and fluid storage and transport. Our relatively simple design can be manufactured using origami-like sheet folding and bonding methods.
Elastic Behavior and Platelet Retraction in Low- and High-Density Fibrin Gels
Wufsus, Adam R.; Rana, Kuldeepsinh; Brown, Andrea; Dorgan, John R.; Liberatore, Matthew W.; Neeves, Keith B.
2015-01-01
Fibrin is a biopolymer that gives thrombi the mechanical strength to withstand the forces imparted on them by blood flow. Importantly, fibrin is highly extensible, but strain hardens at low deformation rates. The density of fibrin in clots, especially arterial clots, is higher than that in gels made at plasma concentrations of fibrinogen (3–10 mg/mL), where most rheology studies have been conducted. Our objective in this study was to measure and characterize the elastic regimes of low (3–10 mg/mL) and high (30–100 mg/mL) density fibrin gels using shear and extensional rheology. Confocal microscopy of the gels shows that fiber density increases with fibrinogen concentration. At low strains, fibrin gels act as thermal networks independent of fibrinogen concentration. Within the low-strain regime, one can predict the mesh size of fibrin gels by the elastic modulus using semiflexible polymer theory. Significantly, this provides a link between gel mechanics and interstitial fluid flow. At moderate strains, we find that low-density fibrin gels act as nonaffine mechanical networks and transition to affine mechanical networks with increasing strains within the moderate regime, whereas high-density fibrin gels only act as affine mechanical networks. At high strains, the backbone of individual fibrin fibers stretches for all fibrin gels. Platelets can retract low-density gels by >80% of their initial volumes, but retraction is attenuated in high-density fibrin gels and with decreasing platelet density. Taken together, these results show that the nature of fibrin deformation is a strong function of fibrin fiber density, which has ramifications for the growth, embolization, and lysis of thrombi. PMID:25564864
NASA Astrophysics Data System (ADS)
Pastor, A.; Babault, J.; Teixell, A.; Arboleya, M. L.
2012-11-01
The Ouarzazate basin is a Cenozoic foreland basin located to the south of the High Atlas Mountains. The basin has been externally drained during the Quaternary, with fluvial dynamics dominated by erosive processes from a progressive base level drop. The current drainage network is composed of rivers draining the mountain and carrying large amounts of coarse sediments and by piedmont streams with smaller catchments eroding the soft Cenozoic rocks of the Ouarzazate basin. The coarse-grained sediments covering the channel beds of main rivers cause the steepening of the channel gradient and act as a shield inhibiting bedrock incision. Under such circumstances, piedmont streams that incise to lower gradients evolve to large, depressed pediments at lower elevations and threaten to capture rivers originating in the mountain. Much of the current surface of the Ouarzazate basin is covered by coarse sediments forming large systems of stepped fan pediments that developed by the filling of low elevation pediments after a capture event. We identified 14 capture events, and previously published geochronology support an ~ 100 ka frequency for fan pediment formation. Our study indicates that the reorganization of the fluvial network in the Ouarzazate basin during the late Pleistocene and Holocene has been controlled by the piedmont-stream piracy process, a process ultimately controlled by the cover effect. The stream capture is influenced by erosion, sediment supply and transport, and therefore may not be entirely decoupled from tectonic and climatic forcing. Indeed, we show that at least two capture events may have occurred during climate changes, and local tectonic structures control at most the spatial localization of capture events.
Loop optimization for tensor network renormalization
NASA Astrophysics Data System (ADS)
Yang, Shuo; Gu, Zheng-Cheng; Wen, Xiao-Gang
We introduce a tensor renormalization group scheme for coarse-graining a two-dimensional tensor network, which can be successfully applied to both classical and quantum systems on and off criticality. The key idea of our scheme is to deform a 2D tensor network into small loops and then optimize tensors on each loop. In this way we remove short-range entanglement at each iteration step, and significantly improve the accuracy and stability of the renormalization flow. We demonstrate our algorithm in the classical Ising model and a frustrated 2D quantum model. NSF Grant No. DMR-1005541 and NSFC 11274192, BMO Financial Group, John Templeton Foundation, Government of Canada through Industry Canada, Province of Ontario through the Ministry of Economic Development & Innovation.
NASA Astrophysics Data System (ADS)
Czarnik, Piotr; Dziarmaga, Jacek; Oleś, Andrzej M.
2017-07-01
The variational tensor network renormalization approach to two-dimensional (2D) quantum systems at finite temperature is applied to a model suffering the notorious quantum Monte Carlo sign problem—the orbital eg model with spatially highly anisotropic orbital interactions. Coarse graining of the tensor network along the inverse temperature β yields a numerically tractable 2D tensor network representing the Gibbs state. Its bond dimension D —limiting the amount of entanglement—is a natural refinement parameter. Increasing D we obtain a converged order parameter and its linear susceptibility close to the critical point. They confirm the existence of finite order parameter below the critical temperature Tc, provide a numerically exact estimate of Tc, and give the critical exponents within 1 % of the 2D Ising universality class.
Flexible wavelength de-multiplexer for elastic optical networking.
Zhou, Rui; Gutierrez Pascual, M Deseada; Anandarajah, Prince M; Shao, Tong; Smyth, Frank; Barry, Liam P
2016-05-15
We report an injection locked flexible wavelength de-multiplexer (de-mux) that shows 24-h frequency stability of 1 kHz for optical comb-based elastic optical networking applications. We demonstrate 50 GHz, 87.5 GHz equal spacing and 6.25G-25G-50 GHz, 75G-50G-100 GHz unequal spacing for the de-multiplexer outputs. We also implement an unequally spaced (75G-50G-100 GHz), mixed symbol rate (12.5 GBaud and 40 GBaud) and modulation format (polarization division multiplexed quadrature phase shift keying and on-off keying) wavelength division multiplexed transmission system using the de-multiplexer outputs. The results show 0.6 dB receiver sensitivity penalty, at 7% hard decision forward error correction coding limit, of the 100 km transmitted de-mux outputs when compared to comb source seeding laser back-to-back.
Contraction star-shaped cracks: From 90 degrees to 120 degrees crack intersections
NASA Astrophysics Data System (ADS)
Lazarus, Veronique; Gauthier, Georges
2010-05-01
Giant's Causeway, Port Arthur tessellated pavement, Bimini Road, Mars polygons, fracture networks in permafrost, septarias are some more or less known examples of self-organized crack patterns that have intrigued people through out history. These pavements are formed by constrained shrinking of the media due, for instance, to cooling or drying leading to fracture. The crack networks form in some conditions star-shaped cracks with mostly 90 or 120 degrees angles. Here, we report experiments allowing to control the transition between 90 and 120 degrees. We show that the transition is governed by the linear elastic fracture mechanics energy minimization principle, hence by two parameters: the cell size and the Griffith's length (balance between the energy needed to create cracks and to deform the material elastically). The results are used to infer new informations on tessellated pavements formation.
NASA Astrophysics Data System (ADS)
Hanson, David E.
2011-08-01
Based on recent molecular dynamics and ab initio simulations of small isoprene molecules, we propose a new ansatz for rubber elasticity. We envision a network chain as a series of independent molecular kinks, each comprised of a small number of backbone units, and the strain as being imposed along the contour of the chain. We treat chain extension in three distinct force regimes: (Ia) near zero strain, where we assume that the chain is extended within a well defined tube, with all of the kinks participating simultaneously as entropic elastic springs, (II) when the chain becomes sensibly straight, giving rise to a purely enthalpic stretching force (until bond rupture occurs) and, (Ib) a linear entropic regime, between regimes Ia and II, in which a force limit is imposed by tube deformation. In this intermediate regime, the molecular kinks are assumed to be gradually straightened until the chain becomes a series of straight segments between entanglements. We assume that there exists a tube deformation tension limit that is inversely proportional to the chain path tortuosity. Here we report the results of numerical simulations of explicit three-dimensional, periodic, polyisoprene networks, using these extension-only force models. At low strain, crosslink nodes are moved affinely, up to an arbitrary node force limit. Above this limit, non-affine motion of the nodes is allowed to relax unbalanced chain forces. Our simulation results are in good agreement with tensile stress vs. strain experiments.
Hanson, David E
2011-08-07
Based on recent molecular dynamics and ab initio simulations of small isoprene molecules, we propose a new ansatz for rubber elasticity. We envision a network chain as a series of independent molecular kinks, each comprised of a small number of backbone units, and the strain as being imposed along the contour of the chain. We treat chain extension in three distinct force regimes: (Ia) near zero strain, where we assume that the chain is extended within a well defined tube, with all of the kinks participating simultaneously as entropic elastic springs, (II) when the chain becomes sensibly straight, giving rise to a purely enthalpic stretching force (until bond rupture occurs) and, (Ib) a linear entropic regime, between regimes Ia and II, in which a force limit is imposed by tube deformation. In this intermediate regime, the molecular kinks are assumed to be gradually straightened until the chain becomes a series of straight segments between entanglements. We assume that there exists a tube deformation tension limit that is inversely proportional to the chain path tortuosity. Here we report the results of numerical simulations of explicit three-dimensional, periodic, polyisoprene networks, using these extension-only force models. At low strain, crosslink nodes are moved affinely, up to an arbitrary node force limit. Above this limit, non-affine motion of the nodes is allowed to relax unbalanced chain forces. Our simulation results are in good agreement with tensile stress vs. strain experiments.
Mechanism for longitudinal growth of rod-shaped bacteria
NASA Astrophysics Data System (ADS)
Taneja, Swadhin; Levitan, Ben; Rutenberg, Andrew
2013-03-01
The peptidoglycan (PG) cell wall along with MreB proteins are major determinants of shape in rod-shaped bacteria. However the mechanism guiding the growth of this elastic network of cross-linked PG (sacculus) that maintains the integrity and shape of the rod-shaped cell remains elusive. We propose that the known anisotropic elasticity and anisotropic loading, due to the shape and turgor pressure, of the sacculus is sufficient to direct small gaps in the sacculus to elongate around the cell, and that subsequent repair leads to longitudinal growth without radial growth. We computationally show in our anisotropically stressed anisotropic elasticity model small gaps can extend stably in the circumferential direction for the known elasticity of the sacculus. We suggest that MreB patches that normally propagate circumferentially, are associated with these gaps and are steered with this common mechanism. This basic picture is unchanged in Gram positive and Gram negative bacteria. We also show that small changes of elastic properties can in fact lead to bi-stable propagation of gaps, both longitudinal and circumferential, that can explain the bi-stability in patch movement observed in ΔmblΔmreb mutants.
Chang, Xueli; Du, Siliang; Li, Yingying; Fang, Shenghui
2018-01-01
Large size high resolution (HR) satellite image matching is a challenging task due to local distortion, repetitive structures, intensity changes and low efficiency. In this paper, a novel matching approach is proposed for the large size HR satellite image registration, which is based on coarse-to-fine strategy and geometric scale-invariant feature transform (SIFT). In the coarse matching step, a robust matching method scale restrict (SR) SIFT is implemented at low resolution level. The matching results provide geometric constraints which are then used to guide block division and geometric SIFT in the fine matching step. The block matching method can overcome the memory problem. In geometric SIFT, with area constraints, it is beneficial for validating the candidate matches and decreasing searching complexity. To further improve the matching efficiency, the proposed matching method is parallelized using OpenMP. Finally, the sensing image is rectified to the coordinate of reference image via Triangulated Irregular Network (TIN) transformation. Experiments are designed to test the performance of the proposed matching method. The experimental results show that the proposed method can decrease the matching time and increase the number of matching points while maintaining high registration accuracy. PMID:29702589
Chaimovich, Aviel; Shell, M Scott
2009-03-28
Recent efforts have attempted to understand many of liquid water's anomalous properties in terms of effective spherically-symmetric pairwise molecular interactions entailing two characteristic length scales (so-called "core-softened" potentials). In this work, we examine the extent to which such simple descriptions of water are representative of the true underlying interactions by extracting coarse-grained potential functions that are optimized to reproduce the behavior of an all-atom model. To perform this optimization, we use a novel procedure based upon minimizing the relative entropy, a quantity that measures the extent to which a coarse-grained configurational ensemble overlaps with a reference all-atom one. We show that the optimized spherically-symmetric water models exhibit notable variations with the state conditions at which they were optimized, reflecting in particular the shifting accessibility of networked hydrogen bonding interactions. Moreover, we find that water's density and diffusivity anomalies are only reproduced when the effective coarse-grained potentials are allowed to vary with state. Our results therefore suggest that no state-independent spherically-symmetric potential can fully capture the interactions responsible for water's unique behavior; rather, the particular way in which the effective interactions vary with temperature and density contributes significantly to anomalous properties.
NASA Astrophysics Data System (ADS)
Rohan, Eduard; Naili, Salah; Nguyen, Vu-Hieu
2016-08-01
We study wave propagation in an elastic porous medium saturated with a compressible Newtonian fluid. The porous network is interconnected whereby the pores are characterized by two very different characteristic sizes. At the mesoscopic scale, the medium is described using the Biot model, characterized by a high contrast in the hydraulic permeability and anisotropic elasticity, whereas the contrast in the Biot coupling coefficient is only moderate. Fluid motion is governed by the Darcy flow model extended by inertia terms and by the mass conservation equation. The homogenization method based on the asymptotic analysis is used to obtain a macroscopic model. To respect the high contrast in the material properties, they are scaled by the small parameter, which is involved in the asymptotic analysis and characterized by the size of the heterogeneities. Using the estimates of wavelengths in the double-porosity networks, it is shown that the macroscopic descriptions depend on the contrast in the static permeability associated with pores and micropores and on the frequency. Moreover, the microflow in the double porosity is responsible for fading memory effects via the macroscopic poroviscoelastic constitutive law. xml:lang="fr"
Water Holding as Determinant for the Elastically Stored Energy in Protein-Based Gels.
Pouvreau, Laurice; van Wijlen, Emke; Klok, Jan; Urbonaite, Vaida; Munialo, Claire D; de Jongh, Harmen H J
2016-04-01
To evaluate the importance of the water holding capacity for the elastically stored energy of protein gels, a range of gels were created from proteins from different origin (plant: pea and soy proteins, and animal: whey, blood plasma, egg white proteins, and ovalbumin) varying in network morphology set by the protein concentration, pH, ionic strength, or the presence of specific ions. The results showed that the observed positive and linear relation between water holding (WH) and elastically stored energy (RE) is generic for globular protein gels studied. The slopes of this relation are comparable for all globular protein gels (except for soy protein gels) whereas the intercept is close to 0 for most of the systems except for ovalbumin and egg white gels. The slope and intercept obtained allows one to predict the impact of tuning WH, by gel morphology or network stiffness, on the mechanical deformation of the protein-based gel. Addition of charged polysaccharides to a protein system leads to a deviation from the linear relation between WH and RE and this deviation coincides with a change in phase behavior. © 2016 Institute of Food Technologists®
Variational Principles for Buckling of Microtubules Modeled as Nonlocal Orthotropic Shells
2014-01-01
A variational principle for microtubules subject to a buckling load is derived by semi-inverse method. The microtubule is modeled as an orthotropic shell with the constitutive equations based on nonlocal elastic theory and the effect of filament network taken into account as an elastic surrounding. Microtubules can carry large compressive forces by virtue of the mechanical coupling between the microtubules and the surrounding elastic filament network. The equations governing the buckling of the microtubule are given by a system of three partial differential equations. The problem studied in the present work involves the derivation of the variational formulation for microtubule buckling. The Rayleigh quotient for the buckling load as well as the natural and geometric boundary conditions of the problem is obtained from this variational formulation. It is observed that the boundary conditions are coupled as a result of nonlocal formulation. It is noted that the analytic solution of the buckling problem for microtubules is usually a difficult task. The variational formulation of the problem provides the basis for a number of approximate and numerical methods of solutions and furthermore variational principles can provide physical insight into the problem. PMID:25214886
Depalle, Baptiste; Qin, Zhao; Shefelbine, Sandra J.; Buehler, Markus J.
2015-01-01
Collagen is a ubiquitous protein with remarkable mechanical properties. It is highly elastic, shows large fracture strength and enables substantial energy dissipation during deformation. Most of the connective tissue in humans consists of collagen fibrils composed of a staggered array of tropocollagen molecules, which are connected by intermolecular cross-links. In this study, we report a three-dimensional coarse-grained model of collagen and analyze the influence of enzymatic cross-links on the mechanics of collagen fibrils. Two representatives immature and mature cross-links are implemented in the mesoscale model using a bottom-up approach. By varying the number, type and mechanical properties of cross-links in the fibrils and performing tensile test on the models, we systematically investigate the deformation mechanisms of cross-linked collagen fibrils. We find that cross-linked fibrils exhibit a three phase behavior, which agrees closer with experimental results than what was obtained using previous models. The fibril mechanical response is characterized by: (i) an initial elastic deformation corresponding to the collagen molecule uncoiling, (ii) a linear regime dominated by molecule sliding and (iii) the second stiffer elastic regime related to the stretching of the backbone of the tropocollagen molecules until the fibril ruptures. Our results suggest that both cross-link density and type dictate the stiffness of large deformation regime by increasing the number of interconnected molecules while cross-links mechanical properties determine the failure strain and strength of the fibril. These findings reveal that cross-links play an essential role in creating an interconnected fibrillar material of tunable toughness and strength. PMID:25153614
Relating microstructure to rheology of a bundled and cross-linked F-actin network in vitro
NASA Astrophysics Data System (ADS)
Shin, J. H.; Gardel, M. L.; Mahadevan, L.; Matsudaira, P.; Weitz, D. A.
2004-06-01
The organization of individual actin filaments into higher-order structures is controlled by actin-binding proteins (ABPs). Although the biological significance of the ABPs is well documented, little is known about how bundling and cross-linking quantitatively affect the microstructure and mechanical properties of actin networks. Here we quantify the effect of the ABP scruin on actin networks by using imaging techniques, cosedimentation assays, multiparticle tracking, and bulk rheology. We show how the structure of the actin network is modified as the scruin concentration is varied, and we correlate these structural changes to variations in the resultant network elasticity.
The C. elegans Connectome Consists of Homogenous Circuits with Defined Functional Roles
Azulay, Aharon; Zaslaver, Alon
2016-01-01
A major goal of systems neuroscience is to decipher the structure-function relationship in neural networks. Here we study network functionality in light of the common-neighbor-rule (CNR) in which a pair of neurons is more likely to be connected the more common neighbors it shares. Focusing on the fully-mapped neural network of C. elegans worms, we establish that the CNR is an emerging property in this connectome. Moreover, sets of common neighbors form homogenous structures that appear in defined layers of the network. Simulations of signal propagation reveal their potential functional roles: signal amplification and short-term memory at the sensory/inter-neuron layer, and synchronized activity at the motoneuron layer supporting coordinated movement. A coarse-grained view of the neural network based on homogenous connected sets alone reveals a simple modular network architecture that is intuitive to understand. These findings provide a novel framework for analyzing larger, more complex, connectomes once these become available. PMID:27606684
Adaptation, Growth, and Resilience in Biological Distribution Networks
NASA Astrophysics Data System (ADS)
Ronellenfitsch, Henrik; Katifori, Eleni
Highly optimized complex transport networks serve crucial functions in many man-made and natural systems such as power grids and plant or animal vasculature. Often, the relevant optimization functional is nonconvex and characterized by many local extrema. In general, finding the global, or nearly global optimum is difficult. In biological systems, it is believed that such an optimal state is slowly achieved through natural selection. However, general coarse grained models for flow networks with local positive feedback rules for the vessel conductivity typically get trapped in low efficiency, local minima. We show how the growth of the underlying tissue, coupled to the dynamical equations for network development, can drive the system to a dramatically improved optimal state. This general model provides a surprisingly simple explanation for the appearance of highly optimized transport networks in biology such as plant and animal vasculature. In addition, we show how the incorporation of spatially collective fluctuating sources yields a minimal model of realistic reticulation in distribution networks and thus resilience against damage.
NASA Astrophysics Data System (ADS)
Stone, Howard A.
2013-03-01
Instabilities are triggered when elastic materials are subjected to compression. We explore new features of two distinct systems of this type. First, we describe a two-layer polymeric system under biaxial compressive stress, which exhibits a repetitive wrinkle-to-fold transition that subsequently generates a hierarchical network of folds during reorganization of the stress field. The folds delineate individual domains, and each domain subdivides into smaller ones over multiple generations. By modifying the boundary conditions and geometry, we demonstrate control over the final network morphology. Some analogies to the venation pattern of leaves are indicated. Second, motivated by the confined configurations common to cells, which are wrapped in lipid bilayer membranes, we study a lipid bilayer, coupled to an elastic sheet, and demonstrate that, upon straining, the confined lipid membrane is able to passively regulate its area. In particular, by stretching the elastic support, the bilayer laterally expands without rupture by fusing adhered lipid vesicles; upon compression, lipid tubes grow out of the membrane plane, thus reducing its area. These transformations are reversible, as we show using cycles of expansion and compression, and closely reproduce membrane processes found in cells during area regulation. The two distinct systems illustrate the influence of the substrate on finite amplitude shape changes, for which we describe the time-dependent shape evolution as the stress relaxes. This talk describes joint research with Manouk Abkarian, Marino Arroyo, Pilnam Kim, Mohammad Rahimi and Margarita Staykova.
Hydrodynamics of Turning Flocks.
Yang, Xingbo; Marchetti, M Cristina
2015-12-18
We present a hydrodynamic model of flocking that generalizes the familiar Toner-Tu equations to incorporate turning inertia of well-polarized flocks. The continuum equations controlled by only two dimensionless parameters, orientational inertia and alignment strength, are derived by coarse-graining the inertial spin model recently proposed by Cavagna et al. The interplay between orientational inertia and bend elasticity of the flock yields anisotropic spin waves that mediate the propagation of turning information throughout the flock. The coupling between spin-current density to the local vorticity field through a nonlinear friction gives rise to a hydrodynamic mode with angular-dependent propagation speed at long wavelengths. This mode becomes unstable as a result of the growth of bend and splay deformations augmented by the spin wave, signaling the transition to complex spatiotemporal patterns of continuously turning and swirling flocks.
A toy model that predicts the qualitative role of bar bend in a push jerk.
Santos, Aaron; Meltzer, Norman E
2009-11-01
In this work, we describe a simple coarse-grained model of a barbell that can be used to determine the qualitative role of bar bend during a jerk. In simulations of this model, we observed a narrow time window during which the lifter can leverage the elasticity of the bar in order to lift the weight to a maximal height. This time window shifted to later times as the weight was increased. In addition, we found that the optimal time to initiate the drive was strongly correlated with the time at which the bar had reached a maximum upward velocity after recoiling. By isolating the effect of the bar, we obtained a generalized strategy for lifting heavy weight in the jerk.
1998-02-24
conducting polyaniline layer . A processing technique was demonstrated for the fabrication of interpenetrating conductive polyaniline networks at the...and sihibits appreciable conductivity in the incorporated, doped polyaniline layer without deteriorating the elasticity and tensile strength of the... Layer Lee Y. Wang and Long Y. Chiang* Center for Condensed Matter Sciences, National Taiwan University, Taipei, Taiwan i Abstract: A synthetic
Structural and stereological analysis of elastic fibers in the glans penis of young men.
Andrade, F; Cardoso, G P; Bastos, Ana Luiza; Costa, W; Chagas, M; Babinski, M
2012-01-01
The extracellular matrix is an important element in penile function and pathology, although little is known about its components in human glans. This study evaluates the morphological organization and volumetric density of elastic fibers in the glans penis of young men without any evidence of urogenital disease at autopsy or medical history. Penile glans were obtained from five young men who died of causes not related to the urogenital tract, ranging in age from 18 to 30 years (mean 24 years). Samples were fixed in formalin, embedded in paraffin, and histologically processed. Tissue was analyzed by light microscopy using Weigert's resorcin-fuchsin, after previous oxidation with oxone. The point-counting method was used for morphometrical evaluation. Quantities were expressed as volumetric densities (Vv) and were determined on 25 random fields for each individual. Elastic system fibers were easily identified. These fibers had tortuous profile and surrounded sinusoids in the glans penis. An irregular elastic fibers network was identified in the mucosa, while in the corpus spongiosum the elastic fibers were longitudinally distributed. Volumetric density of elastic fibers in the glans penis is 29.4% ± 3.1. These data could provide valuable information in order to draw parallels regarding patients with erectile dysfunction. Further studies regarding extracellular matrix of the penis are necessary to better elucidate the relation between elastic fibers and erectile dysfunction.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhou, Jing; Huang, Hai; Mattson, Earl
Aimed at supporting the design of hydraulic fracturing experiments at the kISMET site, ~1500 m below ground in a deep mine, we performed pre-experimental hydraulic fracturing simulations in order to estimate the breakdown pressure, propagation pressure, fracture geometry, and the magnitude of induced seismicity using a newly developed fully coupled three-dimensional (3D) network flow and quasi-static discrete element model (DEM). The quasi-static DEM model, which is constructed by Delaunay tessellation of the rock volume, considers rock fabric heterogeneities by using the “disordered” DEM mesh and adding random perturbations to the stiffness and tensile/shear strengths of individual DEM elements and themore » elastic beams between them. A conjugate 3D flow network based on the DEM lattice is constructed to calculate the fluid flow in both the fracture and porous matrix. One distinctive advantage of the model is that fracturing is naturally described by the breakage of elastic beams between DEM elements. It is also extremely convenient to introduce mechanical anisotropy into the model by simply assigning orientation-dependent tensile/shear strengths to the elastic beams. In this paper, the 3D hydraulic fracturing model was verified against the analytic solution for a penny-shaped crack model. We applied the model to simulate fracture propagation from a vertical open borehole based on initial estimates of rock mechanical properties and in-situ stress conditions. The breakdown pressure and propagation pressure are directly obtained from the simulation. In addition, the released elastic strain energies of individual fracturing events were calculated and used as a conservative estimate for the magnitudes of the potential induced seismic activities associated with fracturing. The comparisons between model predictions and experimental results are still ongoing.« less
Least loaded and route fragmentation aware RSA strategies for elastic optical networks
NASA Astrophysics Data System (ADS)
Batham, Deepak; Yadav, Dharmendra Singh; Prakash, Shashi
2017-12-01
Elastic optical networks (EONs) provide flexibility to assign wide range of spectral resources to the connection requests. In this manuscript, we address two issues related to spectrum assignment in EONs: the non uniform spectrum assignment along different links of the route and the spectrum fragmentation in the network. To address these issues, two routing and spectrum assignment (RSA) strategies have been proposed: Least Loaded RSA (LLRSA) and Route Fragmentation Aware RSA (RFARSA). The LLRSA allocates spectrum homogeneously along different links in the network, where as RFARSA accords priority to the routes which are less fragmented. To highlight the salient features of the two strategies, two new metrics, route fragmentation index (RFI) and standard deviation (SD) are introduced. RFI is defined as the ratio of non-contiguous FSs to the total available free FSs on the route, and SD relates to the measure of non-uniformity in the allocation of resources on the links in the network. A simulation program has been developed to evaluate the performance of the proposed (LLRSA and RFARSA) strategies, and the existing strategies of shortest path RSA (SPRSA) and spectrum compactness based defragmentation (SCD) strategies, on the metric of RFI, bandwidth blocking probability (BBP), network capacity utilized, and SD. The variation in the metrics on the basis of number of requests and the bandwidth (number of FSs) requested has been studied. It has been conclusively established that the proposed strategies (LLRSA and RFARSA) outperform the existing strategies in terms of all the metrics.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cho, Hyun Woo; Kim, Jeongmin; Sung, Bong June, E-mail: jjpark@chonnam.ac.kr, E-mail: bjsung@sogang.ac.kr
We investigate how the electrical conductance of microfibers (made of polymers and conductive nanofillers) decreases upon uniaxial deformation by performing both experiments and simulations. Even though various elastic conductors have been developed due to promising applications for deformable electronic devices, the mechanism at a molecular level for electrical conductance change has remained elusive. Previous studies proposed that the decrease in electrical conductance would result from changes in either distances or contact numbers between conductive fillers. In this work, we prepare microfibers of single walled carbon nanotubes (SWCNTs)/polyvinyl alcohol composites and investigate the electrical conductance and the orientation of SWCNTs uponmore » uniaxial deformation. We also perform extensive Monte Carlo simulations, which reproduce experimental results for the relative decrease in conductance and the SWCNTs orientation. We investigate the electrical networks of SWCNTs in microfibers and find that the decrease in the electrical conductance upon uniaxial deformation should be attributed to a subtle change in the topological structure of the electrical network.« less
Mesoscopic model of actin-based propulsion.
Zhu, Jie; Mogilner, Alex
2012-01-01
Two theoretical models dominate current understanding of actin-based propulsion: microscopic polymerization ratchet model predicts that growing and writhing actin filaments generate forces and movements, while macroscopic elastic propulsion model suggests that deformation and stress of growing actin gel are responsible for the propulsion. We examine both experimentally and computationally the 2D movement of ellipsoidal beads propelled by actin tails and show that neither of the two models can explain the observed bistability of the orientation of the beads. To explain the data, we develop a 2D hybrid mesoscopic model by reconciling these two models such that individual actin filaments undergoing nucleation, elongation, attachment, detachment and capping are embedded into the boundary of a node-spring viscoelastic network representing the macroscopic actin gel. Stochastic simulations of this 'in silico' actin network show that the combined effects of the macroscopic elastic deformation and microscopic ratchets can explain the observed bistable orientation of the actin-propelled ellipsoidal beads. To test the theory further, we analyze observed distribution of the curvatures of the trajectories and show that the hybrid model's predictions fit the data. Finally, we demonstrate that the model can explain both concave-up and concave-down force-velocity relations for growing actin networks depending on the characteristic time scale and network recoil. To summarize, we propose that both microscopic polymerization ratchets and macroscopic stresses of the deformable actin network are responsible for the force and movement generation.
Energy-efficient routing, modulation and spectrum allocation in elastic optical networks
NASA Astrophysics Data System (ADS)
Tan, Yanxia; Gu, Rentao; Ji, Yuefeng
2017-07-01
With tremendous growth in bandwidth demand, energy consumption problem in elastic optical networks (EONs) becomes a hot topic with wide concern. The sliceable bandwidth-variable transponder in EON, which can transmit/receive multiple optical flows, was recently proposed to improve a transponder's flexibility and save energy. In this paper, energy-efficient routing, modulation and spectrum allocation (EE-RMSA) in EONs with sliceable bandwidth-variable transponder is studied. To decrease the energy consumption, we develop a Mixed Integer Linear Programming (MILP) model with corresponding EE-RMSA algorithm for EONs. The MILP model jointly considers the modulation format and optical grooming in the process of routing and spectrum allocation with the objective of minimizing the energy consumption. With the help of genetic operators, the EE-RMSA algorithm iteratively optimizes the feasible routing path, modulation format and spectrum resources solutions by explore the whole search space. In order to save energy, the optical-layer grooming strategy is designed to transmit the lightpath requests. Finally, simulation results verify that the proposed scheme is able to reduce the energy consumption of the network while maintaining the blocking probability (BP) performance compare with the existing First-Fit-KSP algorithm, Iterative Flipping algorithm and EAMGSP algorithm especially in large network topology. Our results also demonstrate that the proposed EE-RMSA algorithm achieves almost the same performance as MILP on an 8-node network.
NASA Astrophysics Data System (ADS)
Johnson, Stanley
An increasing adoption of digital signal processing (DSP) in optical fiber telecommunication has brought to the fore several interesting DSP enabled modulation formats. One such format is orthogonal frequency division multiplexing (OFDM), which has seen great success in wireless and wired RF applications, and is being actively investigated by several research groups for use in optical fiber telecom. In this dissertation, I present three implementations of OFDM for elastic optical networking and distributed network control. The first is a field programmable gate array (FPGA) based real-time implementation of a version of OFDM conventionally known as intensity modulation and direct detection (IMDD) OFDM. I experimentally demonstrate the ability of this transmission system to dynamically adjust bandwidth and modulation format to meet networking constraints in an automated manner. To the best of my knowledge, this is the first real-time software defined networking (SDN) based control of an OFDM system. In the second OFDM implementation, I experimentally demonstrate a novel OFDM transmission scheme that supports both direct detection and coherent detection receivers simultaneously using the same OFDM transmitter. This interchangeable receiver solution enables a trade-off between bit rate and equipment cost in network deployment and upgrades. I show that the proposed transmission scheme can provide a receiver sensitivity improvement of up to 1.73 dB as compared to IMDD OFDM. I also present two novel polarization analyzer based detection schemes, and study their performance using experiment and simulation. In the third implementation, I present an OFDM pilot-tone based scheme for distributed network control. The first instance of an SDN-based OFDM elastic optical network with pilot-tone assisted distributed control is demonstrated. An improvement in spectral efficiency and a fast reconfiguration time of 30 ms have been achieved in this experiment. Finally, I experimentally demonstrate optical re-timing of a 10.7 Gb/s data stream utilizing the property of bound soliton pairs (or "soliton molecules") to relax to an equilibrium temporal separation after propagation through a nonlinear dispersion alternating fiber span. Pulses offset up to 16 ps from bit center are successfully re-timed. The optical re-timing scheme studied here is a good example of signal processing in the optical domain and such a technique can overcome the bandwidth bottleneck present in DSP. An enhanced version of this re-timing scheme is analyzed using numerical simulations.
Stepwise Elastic Behavior in a Model Elastomer
NASA Astrophysics Data System (ADS)
Bhawe, Dhananjay M.; Cohen, Claude; Escobedo, Fernando A.
2004-12-01
MonteCarlo simulations of an entanglement-free cross-linked polymer network of semiflexible chains reveal a peculiar stepwise elastic response. For increasing stress, step jumps in strain are observed that do not correlate with changes in the number of aligned chains. We show that this unusual behavior stems from the ability of the system to form multiple ordered chain domains that exclude the cross-linking species. This novel elastomer shows a toughening behavior similar to that observed in biological structural materials, such as muscle proteins and abalone shell adhesive.
A modular (almost) automatic set-up for elastic multi-tenants cloud (micro)infrastructures
NASA Astrophysics Data System (ADS)
Amoroso, A.; Astorino, F.; Bagnasco, S.; Balashov, N. A.; Bianchi, F.; Destefanis, M.; Lusso, S.; Maggiora, M.; Pellegrino, J.; Yan, L.; Yan, T.; Zhang, X.; Zhao, X.
2017-10-01
An auto-installing tool on an usb drive can allow for a quick and easy automatic deployment of OpenNebula-based cloud infrastructures remotely managed by a central VMDIRAC instance. A single team, in the main site of an HEP Collaboration or elsewhere, can manage and run a relatively large network of federated (micro-)cloud infrastructures, making an highly dynamic and elastic use of computing resources. Exploiting such an approach can lead to modular systems of cloud-bursting infrastructures addressing complex real-life scenarios.
Uncovering the spatial structure of mobility networks
NASA Astrophysics Data System (ADS)
Louail, Thomas; Lenormand, Maxime; Picornell, Miguel; García Cantú, Oliva; Herranz, Ricardo; Frias-Martinez, Enrique; Ramasco, José J.; Barthelemy, Marc
2015-01-01
The extraction of a clear and simple footprint of the structure of large, weighted and directed networks is a general problem that has relevance for many applications. An important example is seen in origin-destination matrices, which contain the complete information on commuting flows, but are difficult to analyze and compare. We propose here a versatile method, which extracts a coarse-grained signature of mobility networks, under the form of a 2 × 2 matrix that separates the flows into four categories. We apply this method to origin-destination matrices extracted from mobile phone data recorded in 31 Spanish cities. We show that these cities essentially differ by their proportion of two types of flows: integrated (between residential and employment hotspots) and random flows, whose importance increases with city size. Finally, the method allows the determination of categories of networks, and in the mobility case, the classification of cities according to their commuting structure.
NASA Astrophysics Data System (ADS)
Natale, Joseph; Hentschel, George
Firing-rate networks offer a coarse model of signal propagation in the brain. Here we analyze sparse, 2D planar firing-rate networks with no synapses beyond a certain cutoff distance. Additionally, we impose Dale's Principle to ensure that each neuron makes only or inhibitory outgoing connections. Using spectral methods, we find that the number of neurons participating in excitations of the network becomes insignificant whenever the connectivity cutoff is tuned to a value near or below the average interneuron separation. Further, neural activations exceeding a certain threshold stay confined to a small region of space. This behavior is an instance of Anderson localization, a disorder-induced phase transition by which an information channel is rendered unable to transmit signals. We discuss several potential implications of localization for both local and long-range computation in the brain. This work was supported in part by Grants JSMF/ 220020321 and NSF/IOS/1208126.
Morphology and linear-elastic moduli of random network solids.
Nachtrab, Susan; Kapfer, Sebastian C; Arns, Christoph H; Madadi, Mahyar; Mecke, Klaus; Schröder-Turk, Gerd E
2011-06-17
The effective linear-elastic moduli of disordered network solids are analyzed by voxel-based finite element calculations. We analyze network solids given by Poisson-Voronoi processes and by the structure of collagen fiber networks imaged by confocal microscopy. The solid volume fraction ϕ is varied by adjusting the fiber radius, while keeping the structural mesh or pore size of the underlying network fixed. For intermediate ϕ, the bulk and shear modulus are approximated by empirical power-laws K(phi)proptophin and G(phi)proptophim with n≈1.4 and m≈1.7. The exponents for the collagen and the Poisson-Voronoi network solids are similar, and are close to the values n=1.22 and m=2.11 found in a previous voxel-based finite element study of Poisson-Voronoi systems with different boundary conditions. However, the exponents of these empirical power-laws are at odds with the analytic values of n=1 and m=2, valid for low-density cellular structures in the limit of thin beams. We propose a functional form for K(ϕ) that models the cross-over from a power-law at low densities to a porous solid at high densities; a fit of the data to this functional form yields the asymptotic exponent n≈1.00, as expected. Further, both the intensity of the Poisson-Voronoi process and the collagen concentration in the samples, both of which alter the typical pore or mesh size, affect the effective moduli only by the resulting change of the solid volume fraction. These findings suggest that a network solid with the structure of the collagen networks can be modeled in quantitative agreement by a Poisson-Voronoi process. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Graph partitions and cluster synchronization in networks of oscillators
Schaub, Michael T.; O’Clery, Neave; Billeh, Yazan N.; Delvenne, Jean-Charles; Lambiotte, Renaud; Barahona, Mauricio
2017-01-01
Synchronization over networks depends strongly on the structure of the coupling between the oscillators. When the coupling presents certain regularities, the dynamics can be coarse-grained into clusters by means of External Equitable Partitions of the network graph and their associated quotient graphs. We exploit this graph-theoretical concept to study the phenomenon of cluster synchronization, in which different groups of nodes converge to distinct behaviors. We derive conditions and properties of networks in which such clustered behavior emerges, and show that the ensuing dynamics is the result of the localization of the eigenvectors of the associated graph Laplacians linked to the existence of invariant subspaces. The framework is applied to both linear and non-linear models, first for the standard case of networks with positive edges, before being generalized to the case of signed networks with both positive and negative interactions. We illustrate our results with examples of both signed and unsigned graphs for consensus dynamics and for partial synchronization of oscillator networks under the master stability function as well as Kuramoto oscillators. PMID:27781454
Learning relevant features of data with multi-scale tensor networks
NASA Astrophysics Data System (ADS)
Miles Stoudenmire, E.
2018-07-01
Inspired by coarse-graining approaches used in physics, we show how similar algorithms can be adapted for data. The resulting algorithms are based on layered tree tensor networks and scale linearly with both the dimension of the input and the training set size. Computing most of the layers with an unsupervised algorithm, then optimizing just the top layer for supervised classification of the MNIST and fashion MNIST data sets gives very good results. We also discuss mixing a prior guess for supervised weights together with an unsupervised representation of the data, yielding a smaller number of features nevertheless able to give good performance.
Mechanostability of Proteins and Virus Capsids
NASA Astrophysics Data System (ADS)
Cieplak, Marek
2013-03-01
Molecular dynamics of proteins within coarse grained models have become a useful tool in studies of large scale systems. The talk will discuss two applications of such modeling. The first is a theoretical survey of proteins' resistance to constant speed stretching as performed for a set of 17134 simple and 318 multidomain proteins. The survey has uncovered new potent force clamps. They involve formation of cysteine slipknots or dragging of a cystine plug through the cystine ring and lead to characteristic forces that are significantly larger than the common shear-based clamp such as observed in titin. The second application involves studies of nanoindentation processes in virus capsids and elucidates their molecular aspects by showing deviations in behavior compared to the continuum shell model. Across the 35 capsids studied, both the collapse force and the elastic stiffness are observed to vary by a factor of 20. The changes in mechanical properties do not correlate simply with virus size or symmetry. There is a strong connection to the mean coordination number < z > , defined as the mean number of interactions to neighboring amino acids. The Young's modulus for thin shell capsids rises roughly quadratically with < z > - 6, where 6 is the minimum coordination for elastic stability in three dimensions. Supported by European Regional Development Fund, through Innovative Economy grant Nanobiom (POIG.01.01.02-00-008/08)
A neural network approach for the blind deconvolution of turbulent flows
NASA Astrophysics Data System (ADS)
Maulik, R.; San, O.
2017-11-01
We present a single-layer feedforward artificial neural network architecture trained through a supervised learning approach for the deconvolution of flow variables from their coarse grained computations such as those encountered in large eddy simulations. We stress that the deconvolution procedure proposed in this investigation is blind, i.e. the deconvolved field is computed without any pre-existing information about the filtering procedure or kernel. This may be conceptually contrasted to the celebrated approximate deconvolution approaches where a filter shape is predefined for an iterative deconvolution process. We demonstrate that the proposed blind deconvolution network performs exceptionally well in the a-priori testing of both two-dimensional Kraichnan and three-dimensional Kolmogorov turbulence and shows promise in forming the backbone of a physics-augmented data-driven closure for the Navier-Stokes equations.
Integrating Metal-Oxide-Decorated CNT Networks with a CMOS Readout in a Gas Sensor
Lee, Hyunjoong; Lee, Sanghoon; Kim, Dai-Hong; Perello, David; Park, Young June; Hong, Seong-Hyeon; Yun, Minhee; Kim, Suhwan
2012-01-01
We have implemented a tin-oxide-decorated carbon nanotube (CNT) network gas sensor system on a single die. We have also demonstrated the deposition of metallic tin on the CNT network, its subsequent oxidation in air, and the improvement of the lifetime of the sensors. The fabricated array of CNT sensors contains 128 sensor cells for added redundancy and increased accuracy. The read-out integrated circuit (ROIC) was combined with coarse and fine time-to-digital converters to extend its resolution in a power-efficient way. The ROIC is fabricated using a 0.35 μm CMOS process, and the whole sensor system consumes 30 mA at 5 V. The sensor system was successfully tested in the detection of ammonia gas at elevated temperatures. PMID:22736966
Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions
NASA Technical Reports Server (NTRS)
Spear, Ashley D.; Priest, Amanda R.; Veilleux, Michael G.; Ingraffea, Anthony R.; Hochhalter, Jacob D.
2011-01-01
A surrogate model methodology is described for predicting in real time the residual strength of flight structures with discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. A residual strength test of a metallic, integrally-stiffened panel is simulated to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data would, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high-fidelity fracture simulation framework provide useful tools for adaptive flight technology.
Epoxidized Natural Rubber/Chitosan Network Binder for Silicon Anode in Lithium-Ion Battery.
Lee, Sang Ha; Lee, Jeong Hun; Nam, Dong Ho; Cho, Misuk; Kim, Jaehoon; Chanthad, Chalathorn; Lee, Youngkwan
2018-05-16
Polymeric binder is extremely important for Si-based anode in lithium-ion batteries due to large volume variation during charging/discharging process. Here, natural rubber-incorporated chitosan networks were designed as a binder material to obtain both adhesion and elasticity. Chitosan could strongly anchor Si particles through hydrogen bonding, while the natural rubber could stretch reversibly during the volume variation of Si particles, resulting in high cyclic performance. The prepared electrode exhibited the specific capacities of 1350 mAh/g after 1600 cycles at the current density of 8 A/g and 2310 mAh/g after 500 cycles at the current density of 1 A/g. Furthermore, the cycle test with limiting lithiation capacity was conducted to study the optimal binder properties at varying degree of the volume expansion of silicon, and it was found that the elastic property of binder material was strongly required when the large volume expansion of Si occurred.
Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions
NASA Technical Reports Server (NTRS)
Spear, Ashley D.; Priest, Amanda R.; Veilleux, Michael G.; Ingraffea, Anthony R.; Hochhalter, Jacob D.
2011-01-01
A surrogate model methodology is described for predicting, during flight, the residual strength of aircraft structures that sustain discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. Two ductile fracture simulations are presented to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data does, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high fidelity fracture simulation framework provide useful tools for adaptive flight technology.
Optimizing Double-Network Hydrogel for Biomedical Soft Robots.
Banerjee, Hritwick; Ren, Hongliang
2017-09-01
Double-network hydrogel with standardized chemical parameters demonstrates a reasonable and viable alternative to silicone in soft robotic fabrication due to its biocompatibility, comparable mechanical properties, and customizability through the alterations of key variables. The most viable hydrogel sample in our article shows tensile strain of 851% and maximum tensile strength of 0.273 MPa. The elasticity and strength range of this hydrogel can be customized according to application requirements by simple alterations in the recipe. Furthermore, we incorporated Agar/PAM hydrogel into our highly constrained soft pneumatic actuator (SPA) design and eventually produced SPAs with escalated capabilities, such as larger range of motion, higher force output, and power efficiency. Incorporating SPAs made of Agar/PAM hydrogel resulted in low viscosity, thermos-reversibility, and ultralow elasticity, which we believe can help to combine with the other functions of hydrogel, tailoring a better solution for fabricating biocompatible soft robots.
Multi-scale Multi-mechanism Design of Tough Hydrogels: Building Dissipation into Stretchy Networks
Zhao, Xuanhe
2014-01-01
As swollen polymer networks in water, hydrogels are usually brittle. However, hydrogels with high toughness play critical roles in many plant and animal tissues as well as in diverse engineering applications. Here we review the intrinsic mechanisms of a wide variety of tough hydrogels developed over past few decades. We show that tough hydrogels generally possess mechanisms to dissipate substantial mechanical energy but still maintain high elasticity under deformation. The integrations and interactions of different mechanisms for dissipating energy and maintaining elasticity are essential to the design of tough hydrogels. A matrix that combines various mechanisms is constructed for the first time to guide the design of next-generation tough hydrogels. We further highlight that a particularly promising strategy for the design is to implement multiple mechanisms across multiple length scales into nano-, micro-, meso-, and macro-structures of hydrogels. PMID:24834901
Elastic modulus of tree frog adhesive toe pads.
Barnes, W Jon P; Goodwyn, Pablo J Perez; Nokhbatolfoghahai, Mohsen; Gorb, Stanislav N
2011-10-01
Previous work using an atomic force microscope in nanoindenter mode indicated that the outer, 10- to 15-μm thick, keratinised layer of tree frog toe pads has a modulus of elasticity equivalent to silicone rubber (5-15 MPa) (Scholz et al. 2009), but gave no information on the physical properties of deeper structures. In this study, micro-indentation is used to measure the stiffness of whole toe pads of the tree frog, Litoria caerulea. We show here that tree frog toe pads are amongst the softest of biological structures (effective elastic modulus 4-25 kPa), and that they exhibit a gradient of stiffness, being stiffest on the outside. This stiffness gradient results from the presence of a dense network of capillaries lying beneath the pad epidermis, which probably has a shock absorbing function. Additionally, we compare the physical properties (elastic modulus, work of adhesion, pull-off force) of the toe pads of immature and adult frogs.
Huang, Guoliang; Song, Fei; Wang, Xiaodong
2010-01-01
Elastic waves, especially guided waves, generated by a piezoelectric actuator/sensor network, have shown great potential for on-line health monitoring of advanced aerospace, nuclear, and automotive structures in recent decades. Piezoelectric materials can function as both actuators and sensors in these applications due to wide bandwidth, quick response and low costs. One of the most fundamental issues surrounding the effective use of piezoelectric actuators is the quantitative evaluation of the resulting elastic wave propagation by considering the coupled piezo-elastodynamic behavior between the actuator and the host medium. Accurate characterization of the local interfacial stress distribution between the actuator and the host medium is the key issue for the problem. This paper presents a review of the development of analytical, numerical and hybrid approaches for modeling of the coupled piezo-elastodynamic behavior. The resulting elastic wave propagation for structural health monitoring is also summarized. PMID:22319319
NASA Astrophysics Data System (ADS)
Shnawah, Dhafer Abdul-Ameer; Said, Suhana Binti Mohd; Sabri, Mohd Faizul Mohd; Badruddin, Irfan Anjum; Hoe, Teh Guan; Che, Fa Xing; Abood, Adnan Naama
2012-08-01
This work investigates the effects of 0.1 wt.% and 0.5 wt.% Al additions on bulk alloy microstructure and tensile properties as well as on the thermal behavior of Sn-1Ag-0.5Cu (SAC105) lead-free solder alloy. The addition of 0.1 wt.% Al reduces the amount of Ag3Sn intermetallic compound (IMC) particles and leads to the formation of larger ternary Sn-Ag-Al IMC particles. However, the addition of 0.5 wt.% Al suppresses the formation of Ag3Sn IMC particles and leads to a large amount of fine Al-Ag IMC particles. Moreover, both 0.1 wt.% and 0.5 wt.% Al additions suppress the formation of Cu6Sn5 IMC particles and lead to the formation of larger Al-Cu IMC particles. The 0.1 wt.% Al-added solder shows a microstructure with coarse β-Sn dendrites. However, the addition of 0.5 wt.% Al has a great effect on suppressing the undercooling and refinement of the β-Sn dendrites. In addition to coarse β-Sn dendrites, the formation of large Sn-Ag-Al and Al-Cu IMC particles significantly reduces the elastic modulus and yield strength for the SAC105 alloy containing 0.1 wt.% Al. On the other hand, the fine β-Sn dendrite and the second-phase dispersion strengthening mechanism through the formation of fine Al-Ag IMC particles significantly increases the elastic modulus and yield strength of the SAC105 alloy containing 0.5 wt.% Al. Moreover, both 0.1 wt.% and 0.5 wt.% Al additions worsen the elongation. However, the reduction in elongation is much stronger, and brittle fracture occurs instead of ductile fracture, with 0.5 wt.% Al addition. The two additions of Al increase both solidus and liquidus temperatures. With 0.5 wt.% Al addition the pasty range is significantly reduced and the differential scanning calorimetry (DSC) endotherm curve gradually shifts from a dual to a single endothermic peak.
Dependence of physical and mechanical properties on polymer architecture for model polymer networks
NASA Astrophysics Data System (ADS)
Guo, Ruilan
Effect of architecture at nanoscale on the macroscopic properties of polymer materials has long been a field of major interest, as evidenced by inhomogeneities in networks, multimodal network topologies, etc. The primary purpose of this research is to establish the architecture-property relationship of polymer networks by studying the physical and mechanical responses of a series of topologically different PTHF networks. Monodispersed allyl-tenninated PTHF precursors were synthesized through "living" cationic polymerization and functional end-capping. Model networks of various crosslink densities and inhomogeneities levels (unimodal, bimodal and clustered) were prepared by endlinking precursors via thiol-ene reaction. Thermal characteristics, i.e., glass transition, melting point, and heat of fusion, of model PTHF networks were investigated as functions of crosslink density and inhomogeneities, which showed different dependence on these two architectural parameters. Study of freezing point depression (FPD) of solvent confined in swollen networks indicated that the size of solvent microcrystals is comparable to the mesh size formed by intercrosslink chains depending on crosslink density and inhomogeneities. Relationship between crystal size and FPD provided a good reflection of the existing architecture facts in the networks. Mechanical responses of elastic chains to uniaxial strains were studied through SANS. Spatial inhomogeneities in bimodal and clustered networks gave rise to "abnormal butterfly patterns", which became more pronounced as elongation ratio increases. Radii of gyration of chains were analyzed at directions parallel and perpendicular to stretching axis. Dependence of Rg on lambda was compared to three rubber elasticity models and the molecular deformation mechanisms for unimodal, bimodal and clustered networks were explored. The thesis focused its last part on the investigation of evolution of free volume distribution of linear polymer (PE) subjected to uniaxial strain at various temperatures using a combination of MD, hard sphere probe method and Voronoi tessellation. Combined effects of temperature and strain on free volume were studied and mechanism of formation of large and ellipsoidal free volume voids was explored.
Stochastic entangled chain dynamics of dense polymer solutions.
Kivotides, Demosthenes; Wilkin, S Louise; Theofanous, Theo G
2010-10-14
We propose an adjustable-parameter-free, entangled chain dynamics model of dense polymer solutions. The model includes the self-consistent dynamics of molecular chains and solvent by describing the former via coarse-grained polymer dynamics that incorporate hydrodynamic interaction effects, and the latter via the forced Stokes equation. Real chain elasticity is modeled via the inclusion of a Pincus regime in the polymer's force-extension curve. Excluded volume effects are taken into account via the combined action of coarse-grained intermolecular potentials and explicit geometric tracking of chain entanglements. We demonstrate that entanglements are responsible for a new (compared to phantom chain dynamics), slow relaxation mode whose characteristic time scale agrees very well with experiment. Similarly good agreement between theory and experiment is also obtained for the equilibrium chain size. We develop methods for the solution of the model in periodic flow domains and apply them to the computation of entangled polymer solutions in equilibrium. We show that the number of entanglements Π agrees well with the number of entanglements expected on the basis of tube theory, satisfactorily reproducing the latter's scaling of Π with the polymer volume fraction φ. Our model predicts diminishing chain size with concentration, thus vindicating Flory's suggestion of excluded volume effects screening in dense solutions. The predicted scaling of chain size with φ is consistent with the heuristic, Flory theory based value.
Gurdián, Hebé; García-Alcocel, Eva; Baeza-Brotons, Francisco; Garcés, Pedro; Zornoza, Emilio
2014-01-01
The main strategy to reduce the environmental impact of the concrete industry is to reuse the waste materials. This research has considered the combination of cement replacement by industrial by-products, and natural coarse aggregate substitution by recycled aggregate. The aim is to evaluate the behavior of concretes with a reduced impact on the environment by replacing a 50% of cement by industrial by-products (15% of spent fluid catalytic cracking catalyst and 35% of fly ash) and a 100% of natural coarse aggregate by recycled aggregate. The concretes prepared according to these considerations have been tested in terms of mechanical strengths and the protection offered against steel reinforcement corrosion under carbonation attack and chloride-contaminated environments. The proposed concrete combinations reduced the mechanical performance of concretes in terms of elastic modulus, compressive strength, and flexural strength. In addition, an increase in open porosity due to the presence of recycled aggregate was observed, which is coherent with the changes observed in mechanical tests. Regarding corrosion tests, no significant differences were observed in the case of the resistance of these types of concretes under a natural chloride attack. In the case of carbonation attack, although all concretes did not stand the highly aggressive conditions, those concretes with cement replacement behaved worse than Portland cement concretes. PMID:28788613
Scaling of F-actin network rheology to probe single filament elasticity and dynamics.
Gardel, M L; Shin, J H; MacKintosh, F C; Mahadevan, L; Matsudaira, P A; Weitz, D A
2004-10-29
The linear and nonlinear viscoelastic response of networks of cross-linked and bundled cytoskeletal filaments demonstrates remarkable scaling with both frequency and applied prestress, which helps elucidate the origins of the viscoelasticity. The frequency dependence of the shear modulus reflects the underlying single-filament relaxation dynamics for 0.1-10 rad/sec. Moreover, the nonlinear strain stiffening of such networks exhibits a universal form as a function of prestress; this is quantitatively explained by the full force-extension relation of single semiflexible filaments.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Chunhua; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 45108; Lv, Dashuai
Riboswitches are noncoding mRNA segments that can regulate the gene expression via altering their structures in response to specific metabolite binding. We proposed a coarse-grained Gaussian network model (GNM) to examine the unfolding and folding dynamics of adenosine deaminase (add) A-riboswitch upon the adenine dissociation, in which the RNA is modeled by a nucleotide chain with interaction networks formed by connecting adjoining atomic contacts. It was shown that the adenine binding is critical to the folding of the add A-riboswitch while the removal of the ligand can result in drastic increase of the thermodynamic fluctuations especially in the junction regionsmore » between helix domains. Under the assumption that the native contacts with the highest thermodynamic fluctuations break first, the iterative GNM simulations showed that the unfolding process of the adenine-free add A-riboswitch starts with the denature of the terminal helix stem, followed by the loops and junctions involving ligand binding pocket, and then the central helix domains. Despite the simplified coarse-grained modeling, the unfolding dynamics and pathways are shown in close agreement with the results from atomic-level MD simulations and the NMR and single-molecule force spectroscopy experiments. Overall, the study demonstrates a new avenue to investigate the binding and folding dynamics of add A-riboswitch molecule which can be readily extended for other RNA molecules.« less
Skin Lesion Analysis towards Melanoma Detection Using Deep Learning Network
2018-01-01
Skin lesions are a severe disease globally. Early detection of melanoma in dermoscopy images significantly increases the survival rate. However, the accurate recognition of melanoma is extremely challenging due to the following reasons: low contrast between lesions and skin, visual similarity between melanoma and non-melanoma lesions, etc. Hence, reliable automatic detection of skin tumors is very useful to increase the accuracy and efficiency of pathologists. In this paper, we proposed two deep learning methods to address three main tasks emerging in the area of skin lesion image processing, i.e., lesion segmentation (task 1), lesion dermoscopic feature extraction (task 2) and lesion classification (task 3). A deep learning framework consisting of two fully convolutional residual networks (FCRN) is proposed to simultaneously produce the segmentation result and the coarse classification result. A lesion index calculation unit (LICU) is developed to refine the coarse classification results by calculating the distance heat-map. A straight-forward CNN is proposed for the dermoscopic feature extraction task. The proposed deep learning frameworks were evaluated on the ISIC 2017 dataset. Experimental results show the promising accuracies of our frameworks, i.e., 0.753 for task 1, 0.848 for task 2 and 0.912 for task 3 were achieved. PMID:29439500
NASA Technical Reports Server (NTRS)
Chaikovsky, A.; Dubovik, O.; Holben, Brent N.; Bril, A.; Goloub, P.; Tanre, D.; Pappalardo, G.; Wandinger, U.; Chaikovskaya, L.; Denisov, S.;
2015-01-01
This paper presents a detailed description of LIRIC (LIdar-Radiometer Inversion Code)algorithm for simultaneous processing of coincident lidar and radiometric (sun photometric) observations for the retrieval of the aerosol concentration vertical profiles. As the lidar radiometric input data we use measurements from European Aerosol Re-search Lidar Network (EARLINET) lidars and collocated sun-photometers of Aerosol Robotic Network (AERONET). The LIRIC data processing provides sequential inversion of the combined lidar and radiometric data by the estimations of column-integrated aerosol parameters from radiometric measurements followed by the retrieval of height-dependent concentrations of fine and coarse aerosols from lidar signals using integrated column characteristics of aerosol layer as a priori constraints. The use of polarized lidar observations allows us to discriminate between spherical and non-spherical particles of the coarse aerosol mode. The LIRIC software package was implemented and tested at a number of EARLINET stations. Inter-comparison of the LIRIC-based aerosol retrievals was performed for the observations by seven EARLNET lidars in Leipzig, Germany on 25 May 2009. We found close agreement between the aerosol parameters derived from different lidars that supports high robustness of the LIRIC algorithm. The sensitivity of the retrieval results to the possible reduction of the available observation data is also discussed.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Langeloth, Michael; Böhm, Michael C.; Müller-Plathe, Florian
2015-12-28
We investigate the volumetric glass transition temperature T{sub g} in epoxy thermosets by means of molecular dynamics simulations. The epoxy thermosets consist of the resin bisphenol A diglycidyl ether and the hardener diethylenetriamine. A structure based coarse-grained (CG) force field has been derived using iterative Boltzmann inversion in order to facilitate simulations of larger length scales. We observe that T{sub g} increases clearly with the degree of cross-linking for all-atomistic (AA) and CG simulations. The transition T{sub g} in CG simulations of uncured mixtures is much lower than in AA-simulations due to the soft nature of the CG potentials, butmore » increases all the more with the formation of rigid cross-links. Additional simulations of the CG mixtures in contact with a surface show the existence of an interphase region of about 3 nm thickness in which the network properties deviate significantly from the bulk. In accordance to experimental studies, we observe that T{sub g} is reduced in this interphase region and gradually increases to its bulk value with distance from the surface. The present study shows that the glass transition is a local phenomenon that depends on the network structure in the immediate environment.« less
Hybrid regulatory models: a statistically tractable approach to model regulatory network dynamics.
Ocone, Andrea; Millar, Andrew J; Sanguinetti, Guido
2013-04-01
Computational modelling of the dynamics of gene regulatory networks is a central task of systems biology. For networks of small/medium scale, the dominant paradigm is represented by systems of coupled non-linear ordinary differential equations (ODEs). ODEs afford great mechanistic detail and flexibility, but calibrating these models to data is often an extremely difficult statistical problem. Here, we develop a general statistical inference framework for stochastic transcription-translation networks. We use a coarse-grained approach, which represents the system as a network of stochastic (binary) promoter and (continuous) protein variables. We derive an exact inference algorithm and an efficient variational approximation that allows scalable inference and learning of the model parameters. We demonstrate the power of the approach on two biological case studies, showing that the method allows a high degree of flexibility and is capable of testable novel biological predictions. http://homepages.inf.ed.ac.uk/gsanguin/software.html. Supplementary data are available at Bioinformatics online.
Permeability and elastic properties of cracked glass under pressure
NASA Astrophysics Data System (ADS)
Ougier-Simonin, A.; GuéGuen, Y.; Fortin, J.; Schubnel, A.; Bouyer, F.
2011-07-01
Fluid flow in rocks is allowed through networks of cracks and fractures at all scales. In fact, cracks are of high importance in various applications ranging from rock elastic and transport properties to nuclear waste disposal. The present work aims at investigating thermomechanical cracking effects on elastic wave velocities, mechanical strength, and permeability of cracked glass under pressure. We performed the experiments on a triaxial cell at room temperature which allows for independent controls of the confining pressure, the axial stress, and pore pressure. We produced cracks in original borosilicate glass samples with a reproducible method (thermal treatment with a thermal shock of 300°C). The evolution of the elastic and transport properties have been monitored using elastic wave velocity sensors, strain gage, and flow measurements. The results obtained evidence for (1) a crack family with identified average aspect ratio and crack aperture, (2) a very small permeability which decreases as a power (exponential) function of pressure, and depends on (3) the crack aperture cube. We also show that permeability behavior of a cracked elastic brittle solid is reversible and independent of the fluid nature. Two independent methods (permeability and elastic wave velocity measurements) give these consistent results. This study provides data on the mechanical and transport properties of an almost ideal elastic brittle solid in which a crack population has been introduced. Comparisons with similar data on rocks allow for drawing interesting conclusions. Over the timescale of our experiments, our results do not provide any data on stress corrosion, which should be considered in further study.
Coarse-graining as a downward causation mechanism
NASA Astrophysics Data System (ADS)
Flack, Jessica C.
2017-11-01
Downward causation is the controversial idea that `higher' levels of organization can causally influence behaviour at `lower' levels of organization. Here I propose that we can gain traction on downward causation by being operational and examining how adaptive systems identify regularities in evolutionary or learning time and use these regularities to guide behaviour. I suggest that in many adaptive systems components collectively compute their macroscopic worlds through coarse-graining. I further suggest we move from simple feedback to downward causation when components tune behaviour in response to estimates of collectively computed macroscopic properties. I introduce a weak and strong notion of downward causation and discuss the role the strong form plays in the origins of new organizational levels. I illustrate these points with examples from the study of biological and social systems and deep neural networks. This article is part of the themed issue 'Reconceptualizing the origins of life'.
Coarse-graining as a downward causation mechanism
2017-01-01
Downward causation is the controversial idea that ‘higher’ levels of organization can causally influence behaviour at ‘lower’ levels of organization. Here I propose that we can gain traction on downward causation by being operational and examining how adaptive systems identify regularities in evolutionary or learning time and use these regularities to guide behaviour. I suggest that in many adaptive systems components collectively compute their macroscopic worlds through coarse-graining. I further suggest we move from simple feedback to downward causation when components tune behaviour in response to estimates of collectively computed macroscopic properties. I introduce a weak and strong notion of downward causation and discuss the role the strong form plays in the origins of new organizational levels. I illustrate these points with examples from the study of biological and social systems and deep neural networks. This article is part of the themed issue ‘Reconceptualizing the origins of life’. PMID:29133440
Early stages of clathrin aggregation at a membrane in coarse-grained simulations
NASA Astrophysics Data System (ADS)
Giani, M.; den Otter, W. K.; Briels, W. J.
2017-04-01
The self-assembly process of clathrin coated pits during endocytosis has been simulated by combining and extending coarse grained models of the clathrin triskelion, the adaptor protein AP2, and a flexible network membrane. The AP2's core, upon binding to membrane and cargo, releases a motif that can bind clathrin. In conditions where the core-membrane-cargo binding is weak, the binding of this motif to clathrin can result in a stable complex. We characterize the conditions and mechanisms resulting in the formation of clathrin lattices that curve the membrane, i.e., clathrin coated pits. The mechanical properties of the AP2 β linker appear crucial to the orientation of the curved clathrin lattice relative to the membrane, with wild-type short linkers giving rise to the inward curving buds enabling endocytosis while long linkers produce upside-down cages and outward curving bulges.
NASA Astrophysics Data System (ADS)
Kassianov, E.; Pekour, M. S.; Flynn, C. J.; Berg, L. K.; Beranek, J.; Zelenyuk, A.; Zhao, C.; Leung, L. R.; Ma, P. L.; Riihimaki, L.; Fast, J. D.; Barnard, J.; Hallar, G. G.; McCubbin, I.; Eloranta, E. W.; McComiskey, A. C.; Rasch, P. J.
2017-12-01
Understanding the effects of dust on the regional and global climate requires detailed information on particle size distributions and their changes with distance from the source. Awareness is now growing about the tendency of the dust coarse mode with moderate ( 3.5 µm) volume median diameter (VMD) to be rather insensitive to complex removal processes associated with long-range transport of dust from the main sources. Our study, with a focus on the transpacific transport of dust, demonstrates that the impact of coarse mode aerosol (VMD 3µm) is well defined at the high-elevation mountain-top Storm Peak Laboratory (SPL, about 3.2 km MSL) and nearby Atmospheric Radiation Measurement (ARM) Climate Research Facility Mobile Facility (AMF) during March 2011. Significant amounts of coarse mode aerosol are also found at the nearest Aerosol Robotic Network (AERONET) site. Outputs from the high-resolution Weather Research and Forecasting (WRF) Model coupled with chemistry (WRF-Chem) show that the major dust event is likely associated with transpacific transport of Asian and African plumes. Satellite data, including the Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging SpectroRadiometer (MISR) aerosol optical depth (AOD) and plume height from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar data provide the observational support of the WRF-Chem simulations. Our study complements previous findings by indicating that the quasi-static nature of the coarse mode appears to be a reasonable approximation for Asian and African dust despite expected frequent orographic precipitation over mountainous regions in the western United States.
NASA Astrophysics Data System (ADS)
Zeng, Zhihui; Liu, Menglong; Xu, Hao; Liu, Weijian; Liao, Yaozhong; Jin, Hao; Zhou, Limin; Zhang, Zhong; Su, Zhongqing
2016-06-01
Inspired by an innovative sensing philosophy, a light-weight nanocomposite sensor made of a hybrid of carbon black (CB)/polyvinylidene fluoride (PVDF) has been developed. The nanoscalar architecture and percolation characteristics of the hybrid were optimized in order to fulfil the in situ acquisition of dynamic elastic disturbance from low-frequency vibration to high-frequency ultrasonic waves. Dynamic particulate motion induced by elastic disturbance modulates the infrastructure of the CB conductive network in the sensor, with the introduction of the tunneling effect, leading to dynamic alteration in the piezoresistivity measured by the sensor. Electrical analysis, morphological characterization, and static/dynamic electromechanical response interrogation were implemented to advance our insight into the sensing mechanism of the sensor, and meanwhile facilitate understanding of the optimal percolation threshold. At the optimal threshold (˜6.5 wt%), the sensor exhibits high fidelity, a fast response, and high sensitivity to ultrafast elastic disturbance (in an ultrasonic regime up to 400 kHz), yet with an ultralow magnitude (on the order of micrometers). The performance of the sensor was evaluated against a conventional strain gauge and piezoelectric transducer, showing excellent coincidence, yet a much greater gauge factor and frequency-independent piezoresistive behavior. Coatable on a structure and deployable in a large quantity to form a dense sensor network, this nanocomposite sensor has blazed a trail for implementing in situ sensing for vibration- or ultrasonic-wave-based structural health monitoring, by striking a compromise between ‘sensing cost’ and ‘sensing effectiveness’.
Three dimensional microstructural network of elastin, collagen, and cells in Achilles tendons.
Pang, Xin; Wu, Jian-Ping; Allison, Garry T; Xu, Jiake; Rubenson, Jonas; Zheng, Ming-Hao; Lloyd, David G; Gardiner, Bruce; Wang, Allan; Kirk, Thomas Brett
2017-06-01
Similar to most biological tissues, the biomechanical, and functional characteristics of the Achilles tendon are closely related to its composition and microstructure. It is commonly reported that type I collagen is the predominant component of tendons and is mainly responsible for the tissue's function. Although elastin has been found in varying proportions in other connective tissues, previous studies report that tendons contain very small quantities of elastin. However, the morphology and the microstructural relationship among the elastic fibres, collagen, and cells in tendon tissue have not been well examined. We hypothesize the elastic fibres, as another fibrillar component in the extracellular matrix, have a unique role in mechanical function and microstructural arrangement in Achilles tendons. It has been shown that elastic fibres present a close connection with the tenocytes. The close relationship of the three components has been revealed as a distinct, integrated and complex microstructural network. Notably, a "spiral" structure within fibril bundles in Achilles tendons was observed in some samples in specialized regions. This study substantiates the hierarchical system of the spatial microstructure of tendon, including the mapping of collagen, elastin and tenocytes, with 3-dimensional confocal images. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:1203-1214, 2017. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.
Shojaee, S. A.; Qi, Y.; Wang, Y. Q.; Mehner, A.; Lucca, D. A.
2017-01-01
Ion irradiation is an alternative to heat treatment for transforming organic-inorganic thin films to a ceramic state. One major shortcoming in previous studies of ion-irradiated films is the assumption that constituent phases in ion-irradiated and heat-treated films are identical and that the ion irradiation effect is limited to changes in composition. In this study, we investigate the effects of ion irradiation on both the composition and structure of constituent phases and use the results to explain the measured elastic modulus of the films. The results indicated that the microstructure of the irradiated films consisted of carbon clusters within a silica matrix. It was found that carbon was present in a non-graphitic sp2-bonded configuration. It was also observed that ion irradiation caused a decrease in the Si-O-Si bond angle of silica, similar to the effects of applied pressure. A phase transformation from tetrahedrally bonded to octahedrally bonded silica was also observed. The results indicated the incorporation of carbon within the silica network. A combination of the decrease in Si-O-Si bond angle and an increase in the carbon incorporation within the silica network was found to be responsible for the increase in the elastic modulus of the films. PMID:28071696
Shojaee, S. A.; Qi, Y.; Wang, Y. Q.; ...
2017-01-10
Ion irradiation is an alternative to heat treatment for transforming organic-inorganic thin films to a ceramic state. One major shortcoming in previous studies of ion-irradiated films is the assumption that constituent phases in ion-irradiated and heat-treated films are identical and that the ion irradiation effect is limited to changes in composition. Here, we investigate the effects of ion irradiation on both the composition and structure of constituent phases and use the results to explain the measured elastic modulus of the films. Our results indicated that the microstructure of the irradiated films consisted of carbon clusters within a silica matrix. Itmore » was found that carbon was present in a non-graphitic sp 2-bonded configuration. It was also observed that ion irradiation caused a decrease in the Si-O-Si bond angle of silica, similar to the effects of applied pressure. A phase transformation from tetrahedrally bonded to octahedrally bonded silica was also observed. The results indicated the incorporation of carbon within the silica network. Finally, a combination of the decrease in Si-O-Si bond angle and an increase in the carbon incorporation within the silica network was found to be responsible for the increase in the elastic modulus of the films.« less
Assessing Temporal Stability for Coarse Scale Satellite Moisture Validation in the Maqu Area, Tibet
Bhatti, Haris Akram; Rientjes, Tom; Verhoef, Wouter; Yaseen, Muhammad
2013-01-01
This study evaluates if the temporal stability concept is applicable to a time series of satellite soil moisture images so to extend the common procedure of satellite image validation. The area of study is the Maqu area, which is located in the northeastern part of the Tibetan plateau. The network serves validation purposes of coarse scale (25–50 km) satellite soil moisture products and comprises 20 stations with probes installed at depths of 5, 10, 20, 40, 80 cm. The study period is 2009. The temporal stability concept is applied to all five depths of the soil moisture measuring network and to a time series of satellite-based moisture products from the Advance Microwave Scanning Radiometer (AMSR-E). The in-situ network is also assessed by Pearsons's correlation analysis. Assessments by the temporal stability concept proved to be useful and results suggest that probe measurements at 10 cm depth best match to the satellite observations. The Mean Relative Difference plot for satellite pixels shows that a RMSM pixel can be identified but in our case this pixel does not overlay any in-situ station. Also, the RMSM pixel does not overlay any of the Representative Mean Soil Moisture (RMSM) stations of the five probe depths. Pearson's correlation analysis on in-situ measurements suggests that moisture patterns over time are more persistent than over space. Since this study presents first results on the application of the temporal stability concept to a series of satellite images, we recommend further tests to become more conclusive on effectiveness to broaden the procedure of satellite validation. PMID:23959237
Depalle, Baptiste; Qin, Zhao; Shefelbine, Sandra J; Buehler, Markus J
2015-12-01
Collagen is a ubiquitous protein with remarkable mechanical properties. It is highly elastic, shows large fracture strength and enables substantial energy dissipation during deformation. Most of the connective tissue in humans consists of collagen fibrils composed of a staggered array of tropocollagen molecules, which are connected by intermolecular cross-links. In this study, we report a three-dimensional coarse-grained model of collagen and analyze the influence of enzymatic cross-links on the mechanics of collagen fibrils. Two representatives immature and mature cross-links are implemented in the mesoscale model using a bottom-up approach. By varying the number, type and mechanical properties of cross-links in the fibrils and performing tensile test on the models, we systematically investigate the deformation mechanisms of cross-linked collagen fibrils. We find that cross-linked fibrils exhibit a three phase behavior, which agrees closer with experimental results than what was obtained using previous models. The fibril mechanical response is characterized by: (i) an initial elastic deformation corresponding to the collagen molecule uncoiling, (ii) a linear regime dominated by molecule sliding and (iii) the second stiffer elastic regime related to the stretching of the backbone of the tropocollagen molecules until the fibril ruptures. Our results suggest that both cross-link density and type dictate the stiffness of large deformation regime by increasing the number of interconnected molecules while cross-links mechanical properties determine the failure strain and strength of the fibril. These findings reveal that cross-links play an essential role in creating an interconnected fibrillar material of tunable toughness and strength. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.
Tran, Truyet T.; Craven, Ashley P.; Leung, Tsz-Wing; Chat, Sandy W.; Levi, Dennis M.
2016-01-01
Neurons in the early visual cortex are finely tuned to different low-level visual features, forming a multi-channel system analysing the visual image formed on the retina in a parallel manner. However, little is known about the potential ‘cross-talk’ among these channels. Here, we systematically investigated whether stereoacuity, over a large range of target spatial frequencies, can be enhanced by perceptual learning. Using narrow-band visual stimuli, we found that practice with coarse (low spatial frequency) targets substantially improves performance, and that the improvement spreads from coarse to fine (high spatial frequency) three-dimensional perception, generalizing broadly across untrained spatial frequencies and orientations. Notably, we observed an asymmetric transfer of learning across the spatial frequency spectrum. The bandwidth of transfer was broader when training was at a high spatial frequency than at a low spatial frequency. Stereoacuity training is most beneficial when trained with fine targets. This broad transfer of stereoacuity learning contrasts with the highly specific learning reported for other basic visual functions. We also revealed strategies to boost learning outcomes ‘beyond-the-plateau’. Our investigations contribute to understanding the functional properties of the network subserving stereovision. The ability to generalize may provide a key principle for restoring impaired binocular vision in clinical situations. PMID:26909178
Coarse-Grained Molecular Monte Carlo Simulations of Liquid Crystal-Nanoparticle Mixtures
NASA Astrophysics Data System (ADS)
Neufeld, Ryan; Kimaev, Grigoriy; Fu, Fred; Abukhdeir, Nasser M.
Coarse-grained intermolecular potentials have proven capable of capturing essential details of interactions between complex molecules, while substantially reducing the number of degrees of freedom of the system under study. In the domain of liquid crystals, the Gay-Berne (GB) potential has been successfully used to model the behavior of rod-like and disk-like mesogens. However, only ellipsoid-like interaction potentials can be described with GB, making it a poor fit for many real-world mesogens. In this work, the results of Monte Carlo simulations of liquid crystal domains using the Zewdie-Corner (ZC) potential are presented. The ZC potential is constructed from an orthogonal series of basis functions, allowing for potentials of essentially arbitrary shapes to be modeled. We also present simulations of mixtures of liquid crystalline mesogens with nanoparticles. Experimentally these mixtures have been observed to exhibit microphase separation and formation of long-range networks under some conditions. This highlights the need for a coarse-grained approach which can capture salient details on the molecular scale while simulating sufficiently large domains to observe these phenomena. We compare the phase behavior of our simulations with that of a recently presented continuum theory. This work was made possible by the Natural Sciences and Engineering Research Council of Canada and Compute Ontario.
Yang, Jingqi; Huang, Jun; Zeng, Hongbo; Chen, Lingyun
2015-11-01
Protein interfacial network formation under mechanical pressure and its influence on degradation was investigated at molecular level using Langmuir-Blodgett B-hordein monolayer as a 2D model. Surface properties, such as surface pressure, dilatational and shear rheology and the surface pressure--area (π-A) isotherm, of B-hordein at air-water interface were analyzed by tensiometer, rheometer and a Langmuir-Blodgett trough respectively. B-Hordein conformation and orientation under different surface pressures were determined by polarization modulation-infrared reflection absorption spectroscopy (PM-IRRAS). The interfacial network morphology was observed by atomic force microscopy (AFM). B-Hordein could reduce the air-water surface tension rapidly to ∼ 45 mN/m and form a solid-like network with high rheological elasticity and compressibility at interface, which could be a result of interactions developed by intermolecular β-sheets. The results also revealed that B-hordein interfacial network switched from an expanded liquid phase to a solid-like film with increasing compression pressure. The orientation of B-hordein was parallel to the surface when in expended liquid phase, whereas upon compression, the hydrophobic repetitive region tilted away from water phase. When compressed to 30 mN/m, a strong elastic network was formed at the interface, and it was resistant to a harsh gastric-like environment of low pH and pepsin. This work generated fundamental knowledge, which suggested the potential to design B-hordein stabilized emulsions and encapsulations with controllable digestibility for small intestine targeted delivery of bioactive compounds. Copyright © 2015 Elsevier B.V. All rights reserved.
Topological and kinetic determinants of the modal matrices of dynamic models of metabolism
2017-01-01
Large-scale kinetic models of metabolism are becoming increasingly comprehensive and accurate. A key challenge is to understand the biochemical basis of the dynamic properties of these models. Linear analysis methods are well-established as useful tools for characterizing the dynamic response of metabolic networks. Central to linear analysis methods are two key matrices: the Jacobian matrix (J) and the modal matrix (M-1) arising from its eigendecomposition. The modal matrix M-1 contains dynamically independent motions of the kinetic model near a reference state, and it is sparse in practice for metabolic networks. However, connecting the structure of M-1 to the kinetic properties of the underlying reactions is non-trivial. In this study, we analyze the relationship between J, M-1, and the kinetic properties of the underlying network for kinetic models of metabolism. Specifically, we describe the origin of mode sparsity structure based on features of the network stoichiometric matrix S and the reaction kinetic gradient matrix G. First, we show that due to the scaling of kinetic parameters in real networks, diagonal dominance occurs in a substantial fraction of the rows of J, resulting in simple modal structures with clear biological interpretations. Then, we show that more complicated modes originate from topologically-connected reactions that have similar reaction elasticities in G. These elasticities represent dynamic equilibrium balances within reactions and are key determinants of modal structure. The work presented should prove useful towards obtaining an understanding of the dynamics of kinetic models of metabolism, which are rooted in the network structure and the kinetic properties of reactions. PMID:29267329
Analysis of blocking probability for OFDM-based variable bandwidth optical network
NASA Astrophysics Data System (ADS)
Gong, Lei; Zhang, Jie; Zhao, Yongli; Lin, Xuefeng; Wu, Yuyao; Gu, Wanyi
2011-12-01
Orthogonal Frequency Division Multiplexing (OFDM) has recently been proposed as a modulation technique. For optical networks, because of its good spectral efficiency, flexibility, and tolerance to impairments, optical OFDM is much more flexible compared to traditional WDM systems, enabling elastic bandwidth transmissions, and optical networking is the future trend of development. In OFDM-based optical network the research of blocking rate has very important significance for network assessment. Current research for WDM network is basically based on a fixed bandwidth, in order to accommodate the future business and the fast-changing development of optical network, our study is based on variable bandwidth OFDM-based optical networks. We apply the mathematical analysis and theoretical derivation, based on the existing theory and algorithms, research blocking probability of the variable bandwidth of optical network, and then we will build a model for blocking probability.
Generalization of the swelling method to measure the intrinsic curvature of lipids
NASA Astrophysics Data System (ADS)
Barragán Vidal, I. A.; Müller, M.
2017-12-01
Via computer simulation of a coarse-grained model of two-component lipid bilayers, we compare two methods of measuring the intrinsic curvatures of the constituting monolayers. The first one is a generalization of the swelling method that, in addition to the assumption that the spontaneous curvature linearly depends on the composition of the lipid mixture, incorporates contributions from its elastic energy. The second method measures the effective curvature-composition coupling between the apposing leaflets of bilayer structures (planar bilayers or cylindrical tethers) to extract the spontaneous curvature. Our findings demonstrate that both methods yield consistent results. However, we highlight that the two-leaflet structure inherent to the latter method has the advantage of allowing measurements for mixed lipid systems up to their critical point of demixing as well as in the regime of high concentration (of either species).
Electron volt spectroscopy on a pulsed neutron source
NASA Astrophysics Data System (ADS)
Newport, R. J.; Penfold, J.; Williams, W. G.
1984-07-01
The principal design aspects of a pulsed source neutron spectrometer in which the scattered neutron energy is determined by a resonance absorption filter difference method are discussed. Calculations of the accessible dynamic range, resolution and spectrum simulations are given for the spectrometer on a high intensity pulsed neutron source, such as the spallation neutron source (SNS) now being constructed at the Rutherford Appleton Laboratory. Special emphasis is made of the advantage gained by placing coarse and fixed energy-sensitive filters before and after the scatterer; these enhance the inelastic/elastic descrimination of the method. A brief description is given of a double difference filter method which gives a superior difference peak shape, as well as a better energy transfer resolution. Finally, some first results of scattering from zirconium hydride, obtained on a test spectrometer, are presented.
Mechanical Properties of Steel Fiber Reinforced all Lightweight Aggregate Concrete
NASA Astrophysics Data System (ADS)
Yang, Y. M.; Li, J. Y.; Zhen, Y.; Nie, Y. N.; Dong, W. L.
2018-05-01
In order to study the basic mechanical properties and failure characteristics of all lightweight aggregate concrete with different volume of steel fiber (0%, 1%, 2%), shale ceramsite is used as light coarse aggregate. The shale sand is made of light fine aggregate and mixed with different volume of steel fiber, and the mix proportion design of all lightweight aggregate concrete is carried out. The cubic compressive strength, axial compressive strength, flexural strength, splitting strength and modulus of elasticity of steel fiber all lightweight aggregate concrete were studied. Test results show that the incorporation of steel fiber can restrict the cracking of concrete, improve crack resistance; at the same time, it shows good plastic deformation ability and failure morphology. It lays a theoretical foundation for further research on the application of all lightweight aggregate concrete in structural systems.
BioNet Digital Communications Framework
NASA Technical Reports Server (NTRS)
Gifford, Kevin; Kuzminsky, Sebastian; Williams, Shea
2010-01-01
BioNet v2 is a peer-to-peer middleware that enables digital communication devices to talk to each other. It provides a software development framework, standardized application, network-transparent device integration services, a flexible messaging model, and network communications for distributed applications. BioNet is an implementation of the Constellation Program Command, Control, Communications and Information (C3I) Interoperability specification, given in CxP 70022-01. The system architecture provides the necessary infrastructure for the integration of heterogeneous wired and wireless sensing and control devices into a unified data system with a standardized application interface, providing plug-and-play operation for hardware and software systems. BioNet v2 features a naming schema for mobility and coarse-grained localization information, data normalization within a network-transparent device driver framework, enabling of network communications to non-IP devices, and fine-grained application control of data subscription band width usage. BioNet directly integrates Disruption Tolerant Networking (DTN) as a communications technology, enabling networked communications with assets that are only intermittently connected including orbiting relay satellites and planetary rover vehicles.
NASA Astrophysics Data System (ADS)
Basart, S.; Pay, M. T.; Jorba, O.; Pérez, C.; Jiménez-Guerrero, P.; Schulz, M.; Baldasano, J. M.
2011-07-01
The CALIOPE high-resolution air quality modelling system is developed and applied to Europe (12 km × 12 km, 1 h). The modelled daily to seasonal aerosol variability over Europe in 2004 have been evaluated and analysed. The aerosols are estimated from two models, CMAQv4.5 (AERO4) and BSC-DREAM8b. CMAQv4.5 calculates biogenic, anthropogenic and sea salt aerosol and BSC-DREAM8b provides the natural mineral dust contribution from North African deserts. For the evaluation, we use daily PM10/PM2.5 and chemical composition data from 54 stations of the EMEP/CREATE network and coarse and fine aerosol optical depth (AOD) data from 35 stations of the AERONET sun photometer network. The model achieves daily PM10 and PM2.5 correlations of 0.57 and 0.47, respectively, and total, coarse and fine AOD correlations of 0.51, 0.63, and 0.53, respectively. The higher correlations of the PM10 and the coarse mode AOD are largely due to the accurate representation of the African dust influence in the forecasting system. Overall PM and AOD levels are underestimated. The evaluation of the chemical composition highlights underestimations of the modelled fine fractions particularly for carbonaceous matter (EC and OC) and secondary inorganic aerosols (SIA; i.e. nitrates, sulphates and ammonium). The scores of the bulk parameters are significantly improved after applying a simple model bias correction based on the chemical composition observations. SIA are dominant in the fine fractions representing up to 80 % of the aerosol budget in latitudes beyond 40° N. The highest aerosol concentrations are found over the industrialized and populated areas of the Po Valley and the Benelux regions. High values in southern Europe are linked to the transport of coarse particles from the Sahara desert which contributes up to 40 % of the total aerosol mass. Close to the surface, maxima dust seasonal concentrations (>30 μg m-3) are found between spring and early autumn. We estimate that desert dust causes daily exceedances of the PM10 European air quality threshold (50 μg m-3) in large areas south of 45° N reaching up to more than 75 days per year in the southernmost regions.
Periodic buckling of constrained cylindrical elastic shells
NASA Astrophysics Data System (ADS)
Marthelot, Joel; Brun, Pierre-Thomas; Lopez Jimenez, Francisco; Reis, Pedro M.
We revisit the classic problem of buckling of a thin cylindrical elastic shell loaded either by pneumatic depressurization or axial compression. The control of the resulting dimpled pattern is achieved by using a concentric inner rigid mandrel that constrains and stabilizes the post-buckling response. Under axial compression, a regular lattice of diamond-like dimples appears sequentially on the surface of the shell to form a robust spatially extended periodic pattern. Under pressure loading, a periodic array of ridges facets the surface of the elastic cylindrical shell. The sharpness of these ridges can be readily varied and controlled through a single scalar parameter, the applied pressure. A combination of experiments, simulations and scaling analyses is used to rationalize the combined role of geometry and mechanics in the nucleation and evolution of the diamond-like dimples and ridges networks.
Brownian motion studies of viscoelastic colloidal gels by rotational single particle tracking
Liang, Mengning; Harder, Ross; Robinson, Ian K.
2014-04-14
Colloidal gels have unique properties due to a complex microstructure which forms into an extended network. Although the bulk properties of colloidal gels have been studied, there has been difficulty correlating those properties with individual colloidal dynamics on the microscale due to the very high viscosity and elasticity of the material. We utilize rotational X-ray tracking (RXT) to investigate the rotational motion of component crystalline colloidal particles in a colloidal gel of alumina and decanoic acid. Our investigation has determined that the high elasticity of the bulk is echoed by a high elasticity experienced by individual colloidal particles themselves butmore » also finds an unexpected high degree of rotational diffusion, indicating a large degree of freedom in the rotational motion of individual colloids even within a tightly bound system.« less
Synthesis of Road Networks by Data Conflation
2014-04-01
Transform requires basic trigonometric properties. Suppose we have a line oriented as shown in Figure 9 then by defining the parameters, ρ, and θ we...location. Rather than searching for the remaining three parameters, the major and minor axes and the orientation angle, the axes ratio is utilized to...axes ratio and orientation angle are searched on a coarse quantization level and then the local maxima are obtained and a finer resolution area is
Dielectric and diamagnetic susceptibilities near percolative superconductor-insulator transitions.
Loh, Yen Lee; Karki, Pragalv
2017-10-25
Coarse-grained superconductor-insulator composites exhibit a superconductor-insulator transition governed by classical percolation, which should be describable by networks of inductors and capacitors. We study several classes of random inductor-capacitor networks on square lattices. We present a unifying framework for defining electric and magnetic response functions, and we extend the Frank-Lobb bond-propagation algorithm to compute these quantities by network reduction. We confirm that the superfluid stiffness scales approximately as [Formula: see text] as the superconducting bond fraction p approaches the percolation threshold p c . We find that the diamagnetic susceptibility scales as [Formula: see text] below percolation, and as [Formula: see text] above percolation. For models lacking self-capacitances, the electric susceptibility scales as [Formula: see text]. Including a self-capacitance on each node changes the critical behavior to approximately [Formula: see text].
On system behaviour using complex networks of a compression algorithm
NASA Astrophysics Data System (ADS)
Walker, David M.; Correa, Debora C.; Small, Michael
2018-01-01
We construct complex networks of scalar time series using a data compression algorithm. The structure and statistics of the resulting networks can be used to help characterize complex systems, and one property, in particular, appears to be a useful discriminating statistic in surrogate data hypothesis tests. We demonstrate these ideas on systems with known dynamical behaviour and also show that our approach is capable of identifying behavioural transitions within electroencephalogram recordings as well as changes due to a bifurcation parameter of a chaotic system. The technique we propose is dependent on a coarse grained quantization of the original time series and therefore provides potential for a spatial scale-dependent characterization of the data. Finally the method is as computationally efficient as the underlying compression algorithm and provides a compression of the salient features of long time series.
Dynamic behavior of acrylic acid clusters as quasi-mobile nodes in a model of hydrogel network
NASA Astrophysics Data System (ADS)
Zidek, Jan; Milchev, Andrey; Vilgis, Thomas A.
2012-12-01
Using a molecular dynamics simulation, we study the thermo-mechanical behavior of a model hydrogel subject to deformation and change in temperature. The model is found to describe qualitatively poly-lactide-glycolide hydrogels in which acrylic acid (AA)-groups are believed to play the role of quasi-mobile nodes in the formation of a network. From our extensive analysis of the structure, formation, and disintegration of the AA-groups, we are able to elucidate the relationship between structure and viscous-elastic behavior of the model hydrogel. Thus, in qualitative agreement with observations, we find a softening of the mechanical response at large deformations, which is enhanced by growing temperature. Several observables as the non-affinity parameter A and the network rearrangement parameter V indicate the existence of a (temperature-dependent) threshold degree of deformation beyond which the quasi-elastic response of the model system turns over into plastic (ductile) one. The critical stretching when the affinity of the deformation is lost can be clearly located in terms of A and V as well as by analysis of the energy density of the system. The observed stress-strain relationship matches that of known experimental systems.
NASA Astrophysics Data System (ADS)
Caroli, Christiane; Ronsin, Olivier; Lemaître, Anaël
2018-02-01
The stress response of permanently crosslinked gelatin gels was recently observed to display glass-like features, namely, a stretched-exponential behavior terminated by an exponential decay, the characteristic time scales of which increase dramatically with decreasing temperature. This phenomenon is studied here using a model of flexible polymer gel network where relaxation proceeds via elementary monomer exchanges between helix and coil segments. The relaxation dynamics of a full network simulation is found to be nearly identical to that of a model of independent strands, which shows that for flexible polymer gels in the range of elastic moduli of interest, both strand contour length disorder and elastic couplings are irrelevant. We thus focus on the independent strand model and find it not only to explain the observed functional form of the stress relaxation curves but also to yield predictions that match very satisfactorily the experimental measurements of final relaxation time and total stress drop. The system under study thus constitutes a rare case where the origin of glass-like behavior can be unambiguously identified, namely, as the signature of the enhancement of helix content fluctuations when approaching from above the mean-field helix-coil transition of strands.
Elastic Coupling of Nascent apCAM Adhesions to Flowing Actin Networks
Mejean, Cecile O.; Schaefer, Andrew W.; Buck, Kenneth B.; Kress, Holger; Shundrovsky, Alla; Merrill, Jason W.; Dufresne, Eric R.; Forscher, Paul
2013-01-01
Adhesions are multi-molecular complexes that transmit forces generated by a cell’s acto-myosin networks to external substrates. While the physical properties of some of the individual components of adhesions have been carefully characterized, the mechanics of the coupling between the cytoskeleton and the adhesion site as a whole are just beginning to be revealed. We characterized the mechanics of nascent adhesions mediated by the immunoglobulin-family cell adhesion molecule apCAM, which is known to interact with actin filaments. Using simultaneous visualization of actin flow and quantification of forces transmitted to apCAM-coated beads restrained with an optical trap, we found that adhesions are dynamic structures capable of transmitting a wide range of forces. For forces in the picoNewton scale, the nascent adhesions’ mechanical properties are dominated by an elastic structure which can be reversibly deformed by up to 1 µm. Large reversible deformations rule out an interface between substrate and cytoskeleton that is dominated by a number of stiff molecular springs in parallel, and favor a compliant cross-linked network. Such a compliant structure may increase the lifetime of a nascent adhesion, facilitating signaling and reinforcement. PMID:24039928
A classification of event sequences in the influence network
NASA Astrophysics Data System (ADS)
Walsh, James Lyons; Knuth, Kevin H.
2017-06-01
We build on the classification in [1] of event sequences in the influence network as respecting collinearity or not, so as to determine in future work what phenomena arise in each case. Collinearity enables each observer to uniquely associate each particle event of influencing with one of the observer's own events, even in the case of events of influencing the other observer. We further classify events as to whether they are spacetime events that obey in the fine-grained case the coarse-grained conditions of [2], finding that Newton's First and Second Laws of motion are obeyed at spacetime events. A proof of Newton's Third Law under particular circumstances is also presented.
The power law and dynamic rheology in cheese analysis
USDA-ARS?s Scientific Manuscript database
The protein networks of food such as cheese are investigated nondestructively by small amplitude oscillatory shear analysis, which provides information on elastic modulus and viscous modulus. Relationships between frequency and viscoelastic data may be obtained from frequency sweeps by applying the...
Novel elastic protection against DDF failures in an enhanced software-defined SIEPON
NASA Astrophysics Data System (ADS)
Pakpahan, Andrew Fernando; Hwang, I.-Shyan; Yu, Yu-Ming; Hsu, Wu-Hsiao; Liem, Andrew Tanny; Nikoukar, AliAkbar
2017-07-01
Ever-increasing bandwidth demands on passive optical networks (PONs) are pushing the utilization of every fiber strand to its limit. This is mandating comprehensive protection until the end of the distribution drop fiber (DDF). Hence, it is important to provide refined protection with an advanced fault-protection architecture and recovery mechanism that is able to cope with various DDF failures. We propose a novel elastic protection against DDF failures that incorporates a software-defined networking (SDN) capability and a bus protection line to enhance the resiliency of the existing Service Interoperability in Ethernet Passive Optical Networks (SIEPON) system. We propose the addition of an integrated SDN controller and flow tables to the optical line terminal and optical network units (ONUs) in order to deliver various DDF protection scenarios. The proposed architecture enables flexible assignment of backup ONU(s) in pre/post-fault conditions depending on the PON traffic load. A transient backup ONU and multiple backup ONUs can be deployed in the pre-fault and post-fault scenarios, respectively. Our extensively discussed simulation results show that our proposed architecture provides better overall throughput and drop probability compared to the architecture with a fixed DDF protection mechanism. It does so while still maintaining overall QoS performance in terms of packet delay, mean jitter, packet loss, and throughput under various fault conditions.
Formation and rupture of Ca(2+) induced pectin biopolymer gels.
Basak, Rajib; Bandyopadhyay, Ranjini
2014-10-07
When calcium salts are added to an aqueous solution of polysaccharide pectin, ionic cross-links form between pectin chains, giving rise to a gel network in dilute solution. In this work, dynamic light scattering (DLS) is employed to study the microscopic dynamics of the fractal aggregates (flocs) that constitute the gels, while rheological measurements are carried out to study the process of gel rupture. As the calcium salt concentration is increased, DLS experiments reveal that the polydispersity of the flocs increase simultaneously with the characteristic relaxation times of the gel network. Above a critical salt concentration, the flocs become interlinked to form a reaction-limited fractal gel network. Rheological studies demonstrate that the limits of the linear rheological response and the critical stresses required to rupture these networks both decrease with the increase in salt concentration. These features indicate that the ion-mediated pectin gels studied here lie in a 'strong link' regime that is characterised by inter-floc links that are stronger than intra-floc links. A scaling analysis of the experimental data presented here demonstrates that the elasticities of the individual fractal flocs exhibit power-law dependences on the added salt concentration. We conclude that when both pectin and salt concentrations are increased, the number of fractal flocs of pectin increases simultaneously with the density of crosslinks, giving rise to very large values of the bulk elastic modulus.
Hydrophobic-Interaction-Induced Stiffening of α -Synuclein Fibril Networks
NASA Astrophysics Data System (ADS)
Semerdzhiev, Slav A.; Lindhoud, Saskia; Stefanovic, Anja; Subramaniam, Vinod; van der Schoot, Paul; Claessens, Mireille M. A. E.
2018-05-01
In water, networks of semiflexible fibrils of the protein α -synuclein stiffen significantly with increasing temperature. We make plausible that this reversible stiffening is a result of hydrophobic contacts between the fibrils that become more prominent with increasing temperature. The good agreement of our experimentally observed temperature dependence of the storage modulus of the network with a scaling theory linking network elasticity with reversible cross-linking enables us to quantify the endothermic binding enthalpy and estimate the effective size of hydrophobic patches on the fibril surface. Our findings may not only shed light on the role of amyloid deposits in disease conditions, but can also inspire new approaches for the design of thermoresponsive materials.
Hydrophobic-Interaction-Induced Stiffening of α-Synuclein Fibril Networks.
Semerdzhiev, Slav A; Lindhoud, Saskia; Stefanovic, Anja; Subramaniam, Vinod; van der Schoot, Paul; Claessens, Mireille M A E
2018-05-18
In water, networks of semiflexible fibrils of the protein α-synuclein stiffen significantly with increasing temperature. We make plausible that this reversible stiffening is a result of hydrophobic contacts between the fibrils that become more prominent with increasing temperature. The good agreement of our experimentally observed temperature dependence of the storage modulus of the network with a scaling theory linking network elasticity with reversible cross-linking enables us to quantify the endothermic binding enthalpy and estimate the effective size of hydrophobic patches on the fibril surface. Our findings may not only shed light on the role of amyloid deposits in disease conditions, but can also inspire new approaches for the design of thermoresponsive materials.
Real-time neural network earthquake profile predictor
Leach, R.R.; Dowla, F.U.
1996-02-06
A neural network has been developed that uses first-arrival energy to predict the characteristics of impending earthquake seismograph signals. The propagation of ground motion energy through the earth is a highly nonlinear function. This is due to different forms of ground motion as well as to changes in the elastic properties of the media throughout the propagation path. The neural network is trained using seismogram data from earthquakes. Presented with a previously unseen earthquake, the neural network produces a profile of the complete earthquake signal using data from the first seconds of the signal. This offers a significant advance in the real-time monitoring, warning, and subsequent hazard minimization of catastrophic ground motion. 17 figs.
Real-time neural network earthquake profile predictor
Leach, Richard R.; Dowla, Farid U.
1996-01-01
A neural network has been developed that uses first-arrival energy to predict the characteristics of impending earthquake seismograph signals. The propagation of ground motion energy through the earth is a highly nonlinear function. This is due to different forms of ground motion as well as to changes in the elastic properties of the media throughout the propagation path. The neural network is trained using seismogram data from earthquakes. Presented with a previously unseen earthquake, the neural network produces a profile of the complete earthquake signal using data from the first seconds of the signal. This offers a significant advance in the real-time monitoring, warning, and subsequent hazard minimization of catastrophic ground motion.
Scaling in Transportation Networks
Louf, Rémi; Roth, Camille; Barthelemy, Marc
2014-01-01
Subway systems span most large cities, and railway networks most countries in the world. These networks are fundamental in the development of countries and their cities, and it is therefore crucial to understand their formation and evolution. However, if the topological properties of these networks are fairly well understood, how they relate to population and socio-economical properties remains an open question. We propose here a general coarse-grained approach, based on a cost-benefit analysis that accounts for the scaling properties of the main quantities characterizing these systems (the number of stations, the total length, and the ridership) with the substrate's population, area and wealth. More precisely, we show that the length, number of stations and ridership of subways and rail networks can be estimated knowing the area, population and wealth of the underlying region. These predictions are in good agreement with data gathered for about subway systems and more than railway networks in the world. We also show that train networks and subway systems can be described within the same framework, but with a fundamental difference: while the interstation distance seems to be constant and determined by the typical walking distance for subways, the interstation distance for railways scales with the number of stations. PMID:25029528
Structure-property relations of orthorhombic [(CH3)3NCH2COO]2(CuCl2)3 · 2H2 O
NASA Astrophysics Data System (ADS)
Haussühl, Eiken; Schreuer, Jürgen; Wiehl, Leonore; Paulsen, Natalia
2014-04-01
Large single crystals of orthorhombic [(CH3)3NCH2COO]2(CuCl2)3 · 2H2 O with dimensions up to 40×40×30 mm3 were grown from aqueous solutions. The elastic and piezoelastic coefficients were derived from ultrasonic resonance frequencies and their shifts upon variation of pressure, respectively, using the plate-resonance technique. Additionally, the coefficients of thermal expansion were determined between 95 K and 305 K by dilatometry. The elastic behaviour at ambient conditions is dominated by the 2-dimensional network of strong hydrogen bonds within the (001) plane leading to a corresponding pseudo-tetragonal anisotropy of the longitudinal elastic stiffness. The variation of elastic properties with pressure, however, as well as the thermal expansion shows strong deviations from the pseudo-tetragonal symmetry. These deviations are probably correlated with tilts of the elongated tri-nuclear betaine-CuCl2-water complexes. Neither the thermal expansion nor the specific heat capacity gives any hint on a phase transition in the investigated temperature range.
Xu, Yingjie; Gao, Tian
2016-01-01
Carbon fiber-reinforced multi-layered pyrocarbon–silicon carbide matrix (C/C–SiC) composites are widely used in aerospace structures. The complicated spatial architecture and material heterogeneity of C/C–SiC composites constitute the challenge for tailoring their properties. Thus, discovering the intrinsic relations between the properties and the microstructures and sequentially optimizing the microstructures to obtain composites with the best performances becomes the key for practical applications. The objective of this work is to optimize the thermal-elastic properties of unidirectional C/C–SiC composites by controlling the multi-layered matrix thicknesses. A hybrid approach based on micromechanical modeling and back propagation (BP) neural network is proposed to predict the thermal-elastic properties of composites. Then, a particle swarm optimization (PSO) algorithm is interfaced with this hybrid model to achieve the optimal design for minimizing the coefficient of thermal expansion (CTE) of composites with the constraint of elastic modulus. Numerical examples demonstrate the effectiveness of the proposed hybrid model and optimization method. PMID:28773343
Wrinkling instability in graphene supported on nanoparticle-patterned SiO2
NASA Astrophysics Data System (ADS)
Cullen, William; Yamamoto, Mahito; Pierre-Louis, Olivier; Einstein, Theodore; Fuhrer, Michael
2012-02-01
Atomically-thin graphene is arguably the thinnest possible mechanical membrane: graphene's effective thickness (the thickness of an isotropic continuum slab which would have the same elastic and bending stiffness) is significantly less than 1 å, indicating that graphene can distort out-of-plane to conform to sub-nanometer features. Here we study the elastic response of graphene supported on a SiO2 substrate covered with SiO2 nanoparticles. At a low density of nanoparticles, graphene is largely pinned to the substrate due to adhesive interaction. However, with increasing nanoparticle density, graphene's elasticity dominates adhesion and strain is relieved by the formation of wrinkles which connect peaks introduced by the supporting nanoparticles. At a critical density, the wrinkles percolate, resulting in a wrinkle network. We develop a simple elastic model allowing for adhesion which accurately predicts the critical spacing between nanoparticles for wrinkle formation. This work has been supported by the University of Maryland NSF-MRSEC under Grant No. DMR 05-20471 with supplemental funding from NRI, and NSF-DMR 08-04976.
Efficient convex-elastic net algorithm to solve the Euclidean traveling salesman problem.
Al-Mulhem, M; Al-Maghrabi, T
1998-01-01
This paper describes a hybrid algorithm that combines an adaptive-type neural network algorithm and a nondeterministic iterative algorithm to solve the Euclidean traveling salesman problem (E-TSP). It begins with a brief introduction to the TSP and the E-TSP. Then, it presents the proposed algorithm with its two major components: the convex-elastic net (CEN) algorithm and the nondeterministic iterative improvement (NII) algorithm. These two algorithms are combined into the efficient convex-elastic net (ECEN) algorithm. The CEN algorithm integrates the convex-hull property and elastic net algorithm to generate an initial tour for the E-TSP. The NII algorithm uses two rearrangement operators to improve the initial tour given by the CEN algorithm. The paper presents simulation results for two instances of E-TSP: randomly generated tours and tours for well-known problems in the literature. Experimental results are given to show that the proposed algorithm ran find the nearly optimal solution for the E-TSP that outperform many similar algorithms reported in the literature. The paper concludes with the advantages of the new algorithm and possible extensions.
Beshel, Jennifer
2010-01-01
We previously showed that in a two-alternative choice (2AC) task, olfactory bulb (OB) gamma oscillations (∼70 Hz in rats) were enhanced during discrimination of structurally similar odorants (fine discrimination) versus discrimination of dissimilar odorants (coarse discrimination). In other studies (mostly employing go/no-go tasks) in multiple labs, beta oscillations (15–35 Hz) dominate the local field potential (LFP) signal in olfactory areas during odor sampling. Here we analyzed the beta frequency band power and pairwise coherence in the 2AC task. We show that in a task dominated by gamma in the OB, beta oscillations are also present in three interconnected olfactory areas (OB and anterior and posterior pyriform cortex). Only the beta band showed consistently elevated coherence during odor sniffing across all odor pairs, classes (alcohols and ketones), and discrimination types (fine and coarse), with stronger effects in first than in final criterion sessions (>70% correct). In the first sessions for fine discrimination odor pairs, beta power for incorrect trials was the same as that for correct trials for the other odor in the pair. This pattern was not repeated in coarse discrimination, in which beta power was elevated for correct relative to incorrect trials. This difference between fine and coarse odor discriminations may relate to different behavioral strategies for learning to differentiate similar versus dissimilar odors. Phase analysis showed that the OB led both pyriform areas in the beta frequency band during odor sniffing. We conclude that the beta band may be the means by which information is transmitted from the OB to higher order areas, even though task specifics modify dominance of one frequency band over another within the OB. PMID:20538778
Liang, Liang; Liu, Minliang; Sun, Wei
2017-11-01
Biological collagenous tissues comprised of networks of collagen fibers are suitable for a broad spectrum of medical applications owing to their attractive mechanical properties. In this study, we developed a noninvasive approach to estimate collagenous tissue elastic properties directly from microscopy images using Machine Learning (ML) techniques. Glutaraldehyde-treated bovine pericardium (GLBP) tissue, widely used in the fabrication of bioprosthetic heart valves and vascular patches, was chosen to develop a representative application. A Deep Learning model was designed and trained to process second harmonic generation (SHG) images of collagen networks in GLBP tissue samples, and directly predict the tissue elastic mechanical properties. The trained model is capable of identifying the overall tissue stiffness with a classification accuracy of 84%, and predicting the nonlinear anisotropic stress-strain curves with average regression errors of 0.021 and 0.031. Thus, this study demonstrates the feasibility and great potential of using the Deep Learning approach for fast and noninvasive assessment of collagenous tissue elastic properties from microstructural images. In this study, we developed, to our best knowledge, the first Deep Learning-based approach to estimate the elastic properties of collagenous tissues directly from noninvasive second harmonic generation images. The success of this study holds promise for the use of Machine Learning techniques to noninvasively and efficiently estimate the mechanical properties of many structure-based biological materials, and it also enables many potential applications such as serving as a quality control tool to select tissue for the manufacturing of medical devices (e.g. bioprosthetic heart valves). Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
The effect of gum tragacanth on the rheological properties of salep based ice cream mix.
Kurt, Abdullah; Cengiz, Alime; Kahyaoglu, Talip
2016-06-05
The influence of concentration (0-0.5%, w/w) of gum tragacanth (GT) on thixotropy, dynamic, and creep-recovery rheological properties of ice cream mixes prepared with milk or water based were investigated. These properties were used to evaluate the viscoelastic behavior and internal structure of ice cream network. The textural properties of ice cream were also evaluated. Thixotropy values of samples were reduced by increasing GT concentration. The dynamic and creep-recovery analyses exhibited that GT addition increased both ice cream elastic and viscous behaviors. The increasing of Burger's model parameters with GT concentration indicated higher resistance network to the stress and more elastic behavior of samples. The applying of Cox-Merz rule is possible by using shift factor (α). GT also led to an increase in Young's modulus and the stickiness of ice creams. The obtained results highlighted the possible application of GT as a valuable member to promote structural properties of ice cream. Copyright © 2016 Elsevier Ltd. All rights reserved.
Bedrock displacements in Greenland manifest ice mass variations, climate cycles and climate change
Bevis, Michael; Wahr, John; Khan, Shfaqat A.; Madsen, Finn Bo; Brown, Abel; Willis, Michael; Kendrick, Eric; Knudsen, Per; Box, Jason E.; van Dam, Tonie; Caccamise, Dana J.; Johns, Bjorn; Nylen, Thomas; Abbott, Robin; White, Seth; Miner, Jeremy; Forsberg, Rene; Zhou, Hao; Wang, Jian; Wilson, Terry; Bromwich, David; Francis, Olivier
2012-01-01
The Greenland GPS Network (GNET) uses the Global Positioning System (GPS) to measure the displacement of bedrock exposed near the margins of the Greenland ice sheet. The entire network is uplifting in response to past and present-day changes in ice mass. Crustal displacement is largely accounted for by an annual oscillation superimposed on a sustained trend. The oscillation is driven by earth’s elastic response to seasonal variations in ice mass and air mass (i.e., atmospheric pressure). Observed vertical velocities are higher and often much higher than predicted rates of postglacial rebound (PGR), implying that uplift is usually dominated by the solid earth’s instantaneous elastic response to contemporary losses in ice mass rather than PGR. Superimposed on longer-term trends, an anomalous ‘pulse’ of uplift accumulated at many GNET stations during an approximate six-month period in 2010. This anomalous uplift is spatially correlated with the 2010 melting day anomaly. PMID:22786931
The effects of rigid motions on elastic network model force constants
Lezon, Timothy R.
2012-01-01
Elastic network models provide an efficient way to quickly calculate protein global dynamics from experimentally determined structures. The model’s single parameter, its force constant, determines the physical extent of equilibrium fluctuations. The values of force constants can be calculated by fitting to experimental data, but the results depend on the type of experimental data used. Here we investigate the differences between calculated values of force constants _t to data from NMR and X-ray structures. We find that X-ray B factors carry the signature of rigid-body motions, to the extent that B factors can be almost entirely accounted for by rigid motions alone. When fitting to more refined anisotropic temperature factors, the contributions of rigid motions are significantly reduced, indicating that the large contribution of rigid motions to B factors is a result of over-fitting. No correlation is found between force constants fit to NMR data and those fit to X-ray data, possibly due to the inability of NMR data to accurately capture protein dynamics. PMID:22228562