Quantification of Interactions between Dynamic Cellular Network Functionalities by Cascaded Layering

PubMed Central

Prescott, Thomas P.; Lang, Moritz; Papachristodoulou, Antonis

2015-01-01

Large, naturally evolved biomolecular networks typically fulfil multiple functions. When modelling or redesigning such systems, functional subsystems are often analysed independently first, before subsequent integration into larger-scale computational models. In the design and analysis process, it is therefore important to quantitatively analyse and predict the dynamics of the interactions between integrated subsystems; in particular, how the incremental effect of integrating a subsystem into a network depends on the existing dynamics of that network. In this paper we present a framework for simulating the contribution of any given functional subsystem when integrated together with one or more other subsystems. This is achieved through a cascaded layering of a network into functional subsystems, where each layer is defined by an appropriate subset of the reactions. We exploit symmetries in our formulation to exhaustively quantify each subsystem’s incremental effects with minimal computational effort. When combining subsystems, their isolated behaviour may be amplified, attenuated, or be subject to more complicated effects. We propose the concept of mutual dynamics to quantify such nonlinear phenomena, thereby defining the incompatibility and cooperativity between all pairs of subsystems when integrated into any larger network. We exemplify our theoretical framework by analysing diverse behaviours in three dynamic models of signalling and metabolic pathways: the effect of crosstalk mechanisms on the dynamics of parallel signal transduction pathways; reciprocal side-effects between several integral feedback mechanisms and the subsystems they stabilise; and consequences of nonlinear interactions between elementary flux modes in glycolysis for metabolic engineering strategies. Our analysis shows that it is not sufficient to just specify subsystems and analyse their pairwise interactions; the environment in which the interaction takes place must also be explicitly defined. Our framework provides a natural representation of nonlinear interaction phenomena, and will therefore be an important tool for modelling large-scale evolved or synthetic biomolecular networks. PMID:25933116

Critical Zone Co-dynamics: Quantifying Interactions between Subsurface, Land Surface, and Vegetation Properties Using UAV and Geophysical Approaches

NASA Astrophysics Data System (ADS)

Dafflon, B.; Leger, E.; Peterson, J.; Falco, N.; Wainwright, H. M.; Wu, Y.; Tran, A. P.; Brodie, E.; Williams, K. H.; Versteeg, R.; Hubbard, S. S.

2017-12-01

Improving understanding and modelling of terrestrial systems requires advances in measuring and quantifying interactions among subsurface, land surface and vegetation processes over relevant spatiotemporal scales. Such advances are important to quantify natural and managed ecosystem behaviors, as well as to predict how watershed systems respond to increasingly frequent hydrological perturbations, such as droughts, floods and early snowmelt. Our study focuses on the joint use of UAV-based multi-spectral aerial imaging, ground-based geophysical tomographic monitoring (incl., electrical and electromagnetic imaging) and point-scale sensing (soil moisture sensors and soil sampling) to quantify interactions between above and below ground compartments of the East River Watershed in the Upper Colorado River Basin. We evaluate linkages between physical properties (incl. soil composition, soil electrical conductivity, soil water content), metrics extracted from digital surface and terrain elevation models (incl., slope, wetness index) and vegetation properties (incl., greenness, plant type) in a 500 x 500 m hillslope-floodplain subsystem of the watershed. Data integration and analysis is supported by numerical approaches that simulate the control of soil and geomorphic characteristic on hydrological processes. Results provide an unprecedented window into critical zone interactions, revealing significant below- and above-ground co-dynamics. Baseline geophysical datasets provide lithological structure along the hillslope, which includes a surface soil horizon, underlain by a saprolite layer and the fractured Mancos shale. Time-lapse geophysical data show very different moisture dynamics in various compartments and locations during the winter and growing season. Integration with aerial imaging reveals a significant linkage between plant growth and the subsurface wetness, soil characteristics and the topographic gradient. The obtained information about the organization and connectivity of the landscape is being transferred to larger regions using aerial imaging and will be used to constrain multi-scale, multi-physics hydro-biogeochemical simulations of the East River watershed response to hydrological perturbations.

Speed Limits: Orientation and Semantic Context Interactions Constrain Natural Scene Discrimination Dynamics

ERIC Educational Resources Information Center

Rieger, Jochem W.; Kochy, Nick; Schalk, Franziska; Gruschow, Marcus; Heinze, Hans-Jochen

2008-01-01

The visual system rapidly extracts information about objects from the cluttered natural environment. In 5 experiments, the authors quantified the influence of orientation and semantics on the classification speed of objects in natural scenes, particularly with regard to object-context interactions. Natural scene photographs were presented in an…

Optimal Objective-Based Experimental Design for Uncertain Dynamical Gene Networks with Experimental Error.

PubMed

Mohsenizadeh, Daniel N; Dehghannasiri, Roozbeh; Dougherty, Edward R

2018-01-01

In systems biology, network models are often used to study interactions among cellular components, a salient aim being to develop drugs and therapeutic mechanisms to change the dynamical behavior of the network to avoid undesirable phenotypes. Owing to limited knowledge, model uncertainty is commonplace and network dynamics can be updated in different ways, thereby giving multiple dynamic trajectories, that is, dynamics uncertainty. In this manuscript, we propose an experimental design method that can effectively reduce the dynamics uncertainty and improve performance in an interaction-based network. Both dynamics uncertainty and experimental error are quantified with respect to the modeling objective, herein, therapeutic intervention. The aim of experimental design is to select among a set of candidate experiments the experiment whose outcome, when applied to the network model, maximally reduces the dynamics uncertainty pertinent to the intervention objective.

Analysis of airframe/engine interactions - An integrated control perspective

NASA Technical Reports Server (NTRS)

Schmidt, David K.; Schierman, John D.; Garg, Sanjay

1990-01-01

Techniques for the analysis of the dynamic interactions between airframe/engine dynamical systems are presented. Critical coupling terms are developed that determine the significance of these interactions with regard to the closed loop stability and performance of the feedback systems. A conceptual model is first used to indicate the potential sources of the coupling, how the coupling manifests itself, and how the magnitudes of these critical coupling terms are used to quantify the effects of the airframe/engine interactions. A case study is also presented involving an unstable airframe with thrust vectoring for attitude control. It is shown for this system with classical, decentralized control laws that there is little airframe/engine interaction, and the stability and performance with those control laws is not affected. Implications of parameter uncertainty in the coupling dynamics is also discussed, and effects of these parameter variations are also demonstrated to be small for this vehicle configuration.

Diffusion and interactions of interstitials in hard-sphere interstitial solid solutions

NASA Astrophysics Data System (ADS)

van der Meer, Berend; Lathouwers, Emma; Smallenburg, Frank; Filion, Laura

2017-12-01

Using computer simulations, we study the dynamics and interactions of interstitial particles in hard-sphere interstitial solid solutions. We calculate the free-energy barriers associated with their diffusion for a range of size ratios and densities. By applying classical transition state theory to these free-energy barriers, we predict the diffusion coefficients, which we find to be in good agreement with diffusion coefficients as measured using event-driven molecular dynamics simulations. These results highlight that transition state theory can capture the interstitial dynamics in the hard-sphere model system. Additionally, we quantify the interactions between the interstitials. We find that, apart from excluded volume interactions, the interstitial-interstitial interactions are almost ideal in our system. Lastly, we show that the interstitial diffusivity can be inferred from the large-particle fluctuations alone, thus providing an empirical relationship between the large-particle fluctuations and the interstitial diffusivity.

Characterization of Relatively Large Track Geometry Variations

DOT National Transportation Integrated Search

1982-03-01

An analysis of existing track geometry data is described from which the signatures of key track geometry variations related to severe track-train dynamic interaction are identified and quantified. Mathematical representations of these signatures are ...

The relationship between structure and function in locally observed complex networks

NASA Astrophysics Data System (ADS)

Comin, Cesar H.; Viana, Matheus P.; Costa, Luciano da F.

2013-01-01

Recently, studies looking at the small scale interactions taking place in complex networks have started to unveil the wealth of interactions that occur between groups of nodes. Such findings make the claim for a new systematic methodology to quantify, at node level, how dynamics are influenced (or differentiated) by the structure of the underlying system. Here we define a new measure that, based on the dynamical characteristics obtained for a large set of initial conditions, compares the dynamical behavior of the nodes present in the system. Through this measure, we find that the geographic and Barabási-Albert models have a high capacity for generating networks that exhibit groups of nodes with distinct dynamics compared to the rest of the network. The application of our methodology is illustrated with respect to two real systems. In the first we use the neuronal network of the nematode Caenorhabditis elegans to show that the interneurons of the ventral cord of the nematode present a very large dynamical differentiation when compared to the rest of the network. The second application concerns the SIS epidemic model on an airport network, where we quantify how different the distribution of infection times of high and low degree nodes can be, when compared to the expected value for the network.

The dynamics of meaningful social interactions and the emergence of collective knowledge

PubMed Central

Dankulov, Marija Mitrović; Melnik, Roderick; Tadić, Bosiljka

2015-01-01

Collective knowledge as a social value may arise in cooperation among actors whose individual expertise is limited. The process of knowledge creation requires meaningful, logically coordinated interactions, which represents a challenging problem to physics and social dynamics modeling. By combining two-scale dynamics model with empirical data analysis from a well-known Questions & Answers system Mathematics, we show that this process occurs as a collective phenomenon in an enlarged network (of actors and their artifacts) where the cognitive recognition interactions are properly encoded. The emergent behavior is quantified by the information divergence and innovation advancing of knowledge over time and the signatures of self-organization and knowledge sharing communities. These measures elucidate the impact of each cognitive element and the individual actor’s expertise in the collective dynamics. The results are relevant to stochastic processes involving smart components and to collaborative social endeavors, for instance, crowdsourcing scientific knowledge production with online games. PMID:26174482

The classical and quantum dynamics of molecular spins on graphene.

PubMed

Cervetti, Christian; Rettori, Angelo; Pini, Maria Gloria; Cornia, Andrea; Repollés, Ana; Luis, Fernando; Dressel, Martin; Rauschenbach, Stephan; Kern, Klaus; Burghard, Marko; Bogani, Lapo

2016-02-01

Controlling the dynamics of spins on surfaces is pivotal to the design of spintronic and quantum computing devices. Proposed schemes involve the interaction of spins with graphene to enable surface-state spintronics and electrical spin manipulation. However, the influence of the graphene environment on the spin systems has yet to be unravelled. Here we explore the spin-graphene interaction by studying the classical and quantum dynamics of molecular magnets on graphene. Whereas the static spin response remains unaltered, the quantum spin dynamics and associated selection rules are profoundly modulated. The couplings to graphene phonons, to other spins, and to Dirac fermions are quantified using a newly developed model. Coupling to Dirac electrons introduces a dominant quantum relaxation channel that, by driving the spins over Villain's threshold, gives rise to fully coherent, resonant spin tunnelling. Our findings provide fundamental insight into the interaction between spins and graphene, establishing the basis for electrical spin manipulation in graphene nanodevices.

The classical and quantum dynamics of molecular spins on graphene

NASA Astrophysics Data System (ADS)

Cervetti, Christian; Rettori, Angelo; Pini, Maria Gloria; Cornia, Andrea; Repollés, Ana; Luis, Fernando; Dressel, Martin; Rauschenbach, Stephan; Kern, Klaus; Burghard, Marko; Bogani, Lapo

2016-02-01

Controlling the dynamics of spins on surfaces is pivotal to the design of spintronic and quantum computing devices. Proposed schemes involve the interaction of spins with graphene to enable surface-state spintronics and electrical spin manipulation. However, the influence of the graphene environment on the spin systems has yet to be unravelled. Here we explore the spin-graphene interaction by studying the classical and quantum dynamics of molecular magnets on graphene. Whereas the static spin response remains unaltered, the quantum spin dynamics and associated selection rules are profoundly modulated. The couplings to graphene phonons, to other spins, and to Dirac fermions are quantified using a newly developed model. Coupling to Dirac electrons introduces a dominant quantum relaxation channel that, by driving the spins over Villain’s threshold, gives rise to fully coherent, resonant spin tunnelling. Our findings provide fundamental insight into the interaction between spins and graphene, establishing the basis for electrical spin manipulation in graphene nanodevices.

The dynamics of meaningful social interactions and the emergence of collective knowledge

NASA Astrophysics Data System (ADS)

Dankulov, Marija Mitrović; Melnik, Roderick; Tadić, Bosiljka

2015-07-01

Collective knowledge as a social value may arise in cooperation among actors whose individual expertise is limited. The process of knowledge creation requires meaningful, logically coordinated interactions, which represents a challenging problem to physics and social dynamics modeling. By combining two-scale dynamics model with empirical data analysis from a well-known Questions & Answers system Mathematics, we show that this process occurs as a collective phenomenon in an enlarged network (of actors and their artifacts) where the cognitive recognition interactions are properly encoded. The emergent behavior is quantified by the information divergence and innovation advancing of knowledge over time and the signatures of self-organization and knowledge sharing communities. These measures elucidate the impact of each cognitive element and the individual actor’s expertise in the collective dynamics. The results are relevant to stochastic processes involving smart components and to collaborative social endeavors, for instance, crowdsourcing scientific knowledge production with online games.

The dynamics of meaningful social interactions and the emergence of collective knowledge.

PubMed

Dankulov, Marija Mitrović; Melnik, Roderick; Tadić, Bosiljka

2015-07-15

Collective knowledge as a social value may arise in cooperation among actors whose individual expertise is limited. The process of knowledge creation requires meaningful, logically coordinated interactions, which represents a challenging problem to physics and social dynamics modeling. By combining two-scale dynamics model with empirical data analysis from a well-known Questions &Answers system Mathematics, we show that this process occurs as a collective phenomenon in an enlarged network (of actors and their artifacts) where the cognitive recognition interactions are properly encoded. The emergent behavior is quantified by the information divergence and innovation advancing of knowledge over time and the signatures of self-organization and knowledge sharing communities. These measures elucidate the impact of each cognitive element and the individual actor's expertise in the collective dynamics. The results are relevant to stochastic processes involving smart components and to collaborative social endeavors, for instance, crowdsourcing scientific knowledge production with online games.

Predictability and Robustness in the Manipulation of Dynamically Complex Objects

PubMed Central

Hasson, Christopher J.

2017-01-01

Manipulation of complex objects and tools is a hallmark of many activities of daily living, but how the human neuromotor control system interacts with such objects is not well understood. Even the seemingly simple task of transporting a cup of coffee without spilling creates complex interaction forces that humans need to compensate for. Predicting the behavior of an underactuated object with nonlinear fluid dynamics based on an internal model appears daunting. Hence, this research tests the hypothesis that humans learn strategies that make interactions predictable and robust to inaccuracies in neural representations of object dynamics. The task of moving a cup of coffee is modeled with a cart-and-pendulum system that is rendered in a virtual environment, where subjects interact with a virtual cup with a rolling ball inside using a robotic manipulandum. To gain insight into human control strategies, we operationalize predictability and robustness to permit quantitative theory-based assessment. Predictability is quantified by the mutual information between the applied force and the object dynamics; robustness is quantified by the energy margin away from failure. Three studies are reviewed that show how with practice subjects develop movement strategies that are predictable and robust. Alternative criteria, common for free movement, such as maximization of smoothness and minimization of force, do not account for the observed data. As manual dexterity is compromised in many individuals with neurological disorders, the experimental paradigm and its analyses are a promising platform to gain insights into neurological diseases, such as dystonia and multiple sclerosis, as well as healthy aging. PMID:28035560

Modeling dynamic interactions and coherence between marine zooplankton and fishes linked to environmental variability

NASA Astrophysics Data System (ADS)

Liu, Hui; Fogarty, Michael J.; Hare, Jonathan A.; Hsieh, Chih-hao; Glaser, Sarah M.; Ye, Hao; Deyle, Ethan; Sugihara, George

2014-03-01

The dynamics of marine fishes are closely related to lower trophic levels and the environment. Quantitatively understanding ecosystem dynamics linking environmental variability and prey resources to exploited fishes is crucial for ecosystem-based management of marine living resources. However, standard statistical models typically grounded in the concept of linear system may fail to capture the complexity of ecological processes. We have attempted to model ecosystem dynamics using a flexible, nonparametric class of nonlinear forecasting models. We analyzed annual time series of four environmental indices, 22 marine copepod taxa, and four ecologically and commercially important fish species during 1977 to 2009 on Georges Bank, a highly productive and intensively studied area of the northeast U.S. continental shelf ecosystem. We examined the underlying dynamic features of environmental indices and copepods, quantified the dynamic interactions and coherence with fishes, and explored the potential control mechanisms of ecosystem dynamics from a nonlinear perspective. We found: (1) the dynamics of marine copepods and environmental indices exhibiting clear nonlinearity; (2) little evidence of complex dynamics across taxonomic levels of copepods; (3) strong dynamic interactions and coherence between copepods and fishes; and (4) the bottom-up forcing of fishes and top-down control of copepods coexisting as target trophic levels vary. These findings highlight the nonlinear interactions among ecosystem components and the importance of marine zooplankton to fish populations which point to two forcing mechanisms likely interactively regulating the ecosystem dynamics on Georges Bank under a changing environment.

A fractal approach to dynamic inference and distribution analysis

PubMed Central

van Rooij, Marieke M. J. W.; Nash, Bertha A.; Rajaraman, Srinivasan; Holden, John G.

2013-01-01

Event-distributions inform scientists about the variability and dispersion of repeated measurements. This dispersion can be understood from a complex systems perspective, and quantified in terms of fractal geometry. The key premise is that a distribution's shape reveals information about the governing dynamics of the system that gave rise to the distribution. Two categories of characteristic dynamics are distinguished: additive systems governed by component-dominant dynamics and multiplicative or interdependent systems governed by interaction-dominant dynamics. A logic by which systems governed by interaction-dominant dynamics are expected to yield mixtures of lognormal and inverse power-law samples is discussed. These mixtures are described by a so-called cocktail model of response times derived from human cognitive performances. The overarching goals of this article are twofold: First, to offer readers an introduction to this theoretical perspective and second, to offer an overview of the related statistical methods. PMID:23372552

Interaction rewiring and the rapid turnover of plant-pollinator networks.

PubMed

CaraDonna, Paul J; Petry, William K; Brennan, Ross M; Cunningham, James L; Bronstein, Judith L; Waser, Nickolas M; Sanders, Nathan J

2017-03-01

Whether species interactions are static or change over time has wide-reaching ecological and evolutionary consequences. However, species interaction networks are typically constructed from temporally aggregated interaction data, thereby implicitly assuming that interactions are fixed. This approach has advanced our understanding of communities, but it obscures the timescale at which interactions form (or dissolve) and the drivers and consequences of such dynamics. We address this knowledge gap by quantifying the within-season turnover of plant-pollinator interactions from weekly censuses across 3 years in a subalpine ecosystem. Week-to-week turnover of interactions (1) was high, (2) followed a consistent seasonal progression in all years of study and (3) was dominated by interaction rewiring (the reassembly of interactions among species). Simulation models revealed that species' phenologies and relative abundances constrained both total interaction turnover and rewiring. Our findings reveal the diversity of species interactions that may be missed when the temporal dynamics of networks are ignored. © 2017 John Wiley & Sons Ltd/CNRS.

Detection of time delays and directional interactions based on time series from complex dynamical systems

NASA Astrophysics Data System (ADS)

Ma, Huanfei; Leng, Siyang; Tao, Chenyang; Ying, Xiong; Kurths, Jürgen; Lai, Ying-Cheng; Lin, Wei

2017-07-01

Data-based and model-free accurate identification of intrinsic time delays and directional interactions is an extremely challenging problem in complex dynamical systems and their networks reconstruction. A model-free method with new scores is proposed to be generally capable of detecting single, multiple, and distributed time delays. The method is applicable not only to mutually interacting dynamical variables but also to self-interacting variables in a time-delayed feedback loop. Validation of the method is carried out using physical, biological, and ecological models and real data sets. Especially, applying the method to air pollution data and hospital admission records of cardiovascular diseases in Hong Kong reveals the major air pollutants as a cause of the diseases and, more importantly, it uncovers a hidden time delay (about 30-40 days) in the causal influence that previous studies failed to detect. The proposed method is expected to be universally applicable to ascertaining and quantifying subtle interactions (e.g., causation) in complex systems arising from a broad range of disciplines.

Capacitive Sensing of Intercalated H2O Molecules Using Graphene.

PubMed

Olson, Eric J; Ma, Rui; Sun, Tao; Ebrish, Mona A; Haratipour, Nazila; Min, Kyoungmin; Aluru, Narayana R; Koester, Steven J

2015-11-25

Understanding the interactions of ambient molecules with graphene and adjacent dielectrics is of fundamental importance for a range of graphene-based devices, particularly sensors, where such interactions could influence the operation of the device. It is well-known that water can be trapped underneath graphene and its host substrate; however, the electrical effect of water beneath graphene and the dynamics of how the interfacial water changes with different ambient conditions has not been quantified. Here, using a metal-oxide-graphene variable-capacitor (varactor) structure, we show that graphene can be used to capacitively sense the intercalation of water between graphene and HfO2 and that this process is reversible on a fast time scale. Atomic force microscopy is used to confirm the intercalation and quantify the displacement of graphene as a function of humidity. Density functional theory simulations are used to quantify the displacement of graphene induced by intercalated water and also explain the observed Dirac point shifts as being due to the combined effect of water and oxygen on the carrier concentration in the graphene. Finally, molecular dynamics simulations indicate that a likely mechanism for the intercalation involves adsorption and lateral diffusion of water molecules beneath the graphene.

Delay-correlation landscape reveals characteristic time delays of brain rhythms and heart interactions

PubMed Central

Lin, Aijing; Liu, Kang K. L.; Bartsch, Ronny P.; Ivanov, Plamen Ch.

2016-01-01

Within the framework of ‘Network Physiology’, we ask a fundamental question of how modulations in cardiac dynamics emerge from networked brain–heart interactions. We propose a generalized time-delay approach to identify and quantify dynamical interactions between physiologically relevant brain rhythms and the heart rate. We perform empirical analysis of synchronized continuous EEG and ECG recordings from 34 healthy subjects during night-time sleep. For each pair of brain rhythm and heart interaction, we construct a delay-correlation landscape (DCL) that characterizes how individual brain rhythms are coupled to the heart rate, and how modulations in brain and cardiac dynamics are coordinated in time. We uncover characteristic time delays and an ensemble of specific profiles for the probability distribution of time delays that underly brain–heart interactions. These profiles are consistently observed in all subjects, indicating a universal pattern. Tracking the evolution of DCL across different sleep stages, we find that the ensemble of time-delay profiles changes from one physiologic state to another, indicating a strong association with physiologic state and function. The reported observations provide new insights on neurophysiological regulation of cardiac dynamics, with potential for broad clinical applications. The presented approach allows one to simultaneously capture key elements of dynamic interactions, including characteristic time delays and their time evolution, and can be applied to a range of coupled dynamical systems. PMID:27044991

Delay-correlation landscape reveals characteristic time delays of brain rhythms and heart interactions

NASA Astrophysics Data System (ADS)

Lin, Aijing; Liu, Kang K. L.; Bartsch, Ronny P.; Ivanov, Plamen Ch.

2016-05-01

Within the framework of `Network Physiology', we ask a fundamental question of how modulations in cardiac dynamics emerge from networked brain-heart interactions. We propose a generalized time-delay approach to identify and quantify dynamical interactions between physiologically relevant brain rhythms and the heart rate. We perform empirical analysis of synchronized continuous EEG and ECG recordings from 34 healthy subjects during night-time sleep. For each pair of brain rhythm and heart interaction, we construct a delay-correlation landscape (DCL) that characterizes how individual brain rhythms are coupled to the heart rate, and how modulations in brain and cardiac dynamics are coordinated in time. We uncover characteristic time delays and an ensemble of specific profiles for the probability distribution of time delays that underly brain-heart interactions. These profiles are consistently observed in all subjects, indicating a universal pattern. Tracking the evolution of DCL across different sleep stages, we find that the ensemble of time-delay profiles changes from one physiologic state to another, indicating a strong association with physiologic state and function. The reported observations provide new insights on neurophysiological regulation of cardiac dynamics, with potential for broad clinical applications. The presented approach allows one to simultaneously capture key elements of dynamic interactions, including characteristic time delays and their time evolution, and can be applied to a range of coupled dynamical systems.

BRIDGING SCALES IN THE EVOLUTION OF INFECTIOUS DISEASE LIFE HISTORIES: APPLICATION

PubMed Central

Mideo, Nicole; Nelson, William A.; Reece, Sarah E.; Bell, Andrew S.; Read, Andrew F.; Day, Troy

2014-01-01

Within- and between-host disease processes occur on the same timescales, therefore changes in the within-host dynamics of parasites, resources, and immunity can interact with changes in the epidemiological dynamics to affect evolutionary outcomes. Consequently, studies of the evolution of disease life histories, that is, infection-age-specific patterns of transmission and virulence, have been constrained by the need for a mechanistic understanding of within-host disease dynamics. In a companion paper (Day et al. 2011), we develop a novel approach that quantifies the relevant within-host aspects of disease through genetic covariance functions. Here, we demonstrate how to apply this theory to data. Using two previously published datasets from rodent malaria infections, we show how to translate experimental measures into disease life-history traits, and how to quantify the covariance in these traits. Our results show how patterns of covariance can interact with epidemiological dynamics to affect evolutionary predictions for disease life history. We also find that the selective constraints on disease life-history evolution can vary qualitatively, and that “simple” virulence-transmission trade-offs that are often the subject of experimental investigation can be obscured by trade-offs within one trait alone. Finally, we highlight the type and quality of data required for future applications. PMID:22023593

Dual redundant arm system operational quality measures and their applications - Dynamic measures

NASA Technical Reports Server (NTRS)

Lee, Sukhan; Kim, Sungbok

1990-01-01

Dual-arm dynamic operation quality measures are presented which quantify the efficiency and capability of generating Cartesian accelerations by two cooperative arms based on the analysis of dual-arm dynamic interactions. Dual-arm dynamic manipulability is defined as the efficiency of generating Cartesian accelerations under the dynamic and kinematic interactions between individual arms and an object under manipulation. The analysis of dual-arm dynamic interactions is based on the so-called Cartesian space agent model of an arm, which represents an individual arm as a force source acting upon a point mass with the effective Cartesian space arm dynamics and an environment or an object under manipulation. The Cartesian space agent model of an arm makes it possible to derive the dynamic and kinematic constraints involved in the transport, assembly and grasping modes of dual-arm cooperation. A task-oriented operational quality measure, (TOQd) is defined by evaluating dual-arm dynamic manipulability in terms of given task requirements. TOQd is used in dual-arm joint configuration optimization. Simulation results are shown. A complete set of forward dynamic equations for a dual-arm system is derived, and dual-arm dynamic operational quality measures for various modes of dual-arm cooperation allowing sliding contacts are established.

The classical and quantum dynamics of molecular spins on graphene

PubMed Central

Cervetti, Christian; Rettori, Angelo; Pini, Maria Gloria; Cornia, Andrea; Repollés, Ana; Luis, Fernando; Dressel, Martin; Rauschenbach, Stephan; Kern, Klaus; Burghard, Marko; Bogani, Lapo

2015-01-01

Controlling the dynamics of spins on surfaces is pivotal to the design of spintronic1 and quantum computing2 devices. Proposed schemes involve the interaction of spins with graphene to enable surface-state spintronics3,4, and electrical spin-manipulation4-11. However, the influence of the graphene environment on the spin systems has yet to be unraveled12. Here we explore the spin-graphene interaction by studying the classical and quantum dynamics of molecular magnets13 on graphene. While the static spin response remains unaltered, the quantum spin dynamics and associated selection rules are profoundly modulated. The couplings to graphene phonons, to other spins, and to Dirac fermions are quantified using a newly-developed model. Coupling to Dirac electrons introduces a dominant quantum-relaxation channel that, by driving the spins over Villain’s threshold, gives rise to fully-coherent, resonant spin tunneling. Our findings provide fundamental insight into the interaction between spins and graphene, establishing the basis for electrical spin-manipulation in graphene nanodevices. PMID:26641019

Determination of ¹⁵N-incorporation into plant proteins and their absolute quantitation: a new tool to study nitrogen flux dynamics and protein pool sizes elicited by plant-herbivore interactions.

PubMed

Ullmann-Zeunert, Lynn; Muck, Alexander; Wielsch, Natalie; Hufsky, Franziska; Stanton, Mariana A; Bartram, Stefan; Böcker, Sebastian; Baldwin, Ian T; Groten, Karin; Svatoš, Aleš

2012-10-05

Herbivory leads to changes in the allocation of nitrogen among different pools and tissues; however, a detailed quantitative analysis of these changes has been lacking. Here, we demonstrate that a mass spectrometric data-independent acquisition approach known as LC-MS(E), combined with a novel algorithm to quantify heavy atom enrichment in peptides, is able to quantify elicited changes in protein amounts and (15)N flux in a high throughput manner. The reliable identification/quantitation of rabbit phosphorylase b protein spiked into leaf protein extract was achieved. The linear dynamic range, reproducibility of technical and biological replicates, and differences between measured and expected (15)N-incorporation into the small (SSU) and large (LSU) subunits of ribulose-1,5-bisphosphate-carboxylase/oxygenase (RuBisCO) and RuBisCO activase 2 (RCA2) of Nicotiana attenuata plants grown in hydroponic culture at different known concentrations of (15)N-labeled nitrate were used to further evaluate the procedure. The utility of the method for whole-plant studies in ecologically realistic contexts was demonstrated by using (15)N-pulse protocols on plants growing in soil under unknown (15)N-incorporation levels. Additionally, we quantified the amounts of lipoxygenase 2 (LOX2) protein, an enzyme important in antiherbivore defense responses, demonstrating that the approach allows for in-depth quantitative proteomics and (15)N flux analyses of the metabolic dynamics elicited during plant-herbivore interactions.

Enhancing Analytical Separations Using Super-Resolution Microscopy

NASA Astrophysics Data System (ADS)

Moringo, Nicholas A.; Shen, Hao; Bishop, Logan D. C.; Wang, Wenxiao; Landes, Christy F.

2018-04-01

Super-resolution microscopy is becoming an invaluable tool to investigate structure and dynamics driving protein interactions at interfaces. In this review, we highlight the applications of super-resolution microscopy for quantifying the physics and chemistry that occur between target proteins and stationary-phase supports during chromatographic separations. Our discussion concentrates on the newfound ability of super-resolved single-protein spectroscopy to inform theoretical parameters via quantification of adsorption-desorption dynamics, protein unfolding, and nanoconfined transport.

Rapid and Specific Method for Evaluating Streptomyces Competitive Dynamics in Complex Soil Communities

USDA-ARS?s Scientific Manuscript database

Quantifying target microbial populations in complex communities remains a barrier to studying species interactions in soil environments. Quantitative real-time PCR (qPCR) offers a rapid and specific means to assess populations of target microorganisms. SYBR Green and TaqMan-based qPCR assays were de...

Bridging scales in the evolution of infectious disease life histories: application.

PubMed

Mideo, Nicole; Nelson, William A; Reece, Sarah E; Bell, Andrew S; Read, Andrew F; Day, Troy

2011-11-01

Within- and between-host disease processes occur on the same timescales, therefore changes in the within-host dynamics of parasites, resources, and immunity can interact with changes in the epidemiological dynamics to affect evolutionary outcomes. Consequently, studies of the evolution of disease life histories, that is, infection-age-specific patterns of transmission and virulence, have been constrained by the need for a mechanistic understanding of within-host disease dynamics. In a companion paper (Day et al. 2011), we develop a novel approach that quantifies the relevant within-host aspects of disease through genetic covariance functions. Here, we demonstrate how to apply this theory to data. Using two previously published datasets from rodent malaria infections, we show how to translate experimental measures into disease life-history traits, and how to quantify the covariance in these traits. Our results show how patterns of covariance can interact with epidemiological dynamics to affect evolutionary predictions for disease life history. We also find that the selective constraints on disease life-history evolution can vary qualitatively, and that "simple" virulence-transmission trade-offs that are often the subject of experimental investigation can be obscured by trade-offs within one trait alone. Finally, we highlight the type and quality of data required for future applications. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Universal quantum uncertainty relations between nonergodicity and loss of information

NASA Astrophysics Data System (ADS)

Awasthi, Natasha; Bhattacharya, Samyadeb; SenDe, Aditi; Sen, Ujjwal

2018-03-01

We establish uncertainty relations between information loss in general open quantum systems and the amount of nonergodicity of the corresponding dynamics. The relations hold for arbitrary quantum systems interacting with an arbitrary quantum environment. The elements of the uncertainty relations are quantified via distance measures on the space of quantum density matrices. The relations hold for arbitrary distance measures satisfying a set of intuitively satisfactory axioms. The relations show that as the nonergodicity of the dynamics increases, the lower bound on information loss decreases, which validates the belief that nonergodicity plays an important role in preserving information of quantum states undergoing lossy evolution. We also consider a model of a central qubit interacting with a fermionic thermal bath and derive its reduced dynamics to subsequently investigate the information loss and nonergodicity in such dynamics. We comment on the "minimal" situations that saturate the uncertainty relations.

Decay of interspecific avian flock networks along a disturbance gradient in Amazonia.

PubMed

Mokross, Karl; Ryder, Thomas B; Côrtes, Marina Corrêa; Wolfe, Jared D; Stouffer, Philip C

2014-02-07

Our understanding of how anthropogenic habitat change shapes species interactions is in its infancy. This is in large part because analytical approaches such as network theory have only recently been applied to characterize complex community dynamics. Network models are a powerful tool for quantifying how ecological interactions are affected by habitat modification because they provide metrics that quantify community structure and function. Here, we examine how large-scale habitat alteration has affected ecological interactions among mixed-species flocking birds in Amazonian rainforest. These flocks provide a model system for investigating how habitat heterogeneity influences non-trophic interactions and the subsequent social structure of forest-dependent mixed-species bird flocks. We analyse 21 flock interaction networks throughout a mosaic of primary forest, fragments of varying sizes and secondary forest (SF) at the Biological Dynamics of Forest Fragments Project in central Amazonian Brazil. Habitat type had a strong effect on network structure at the levels of both species and flock. Frequency of associations among species, as summarized by weighted degree, declined with increasing levels of forest fragmentation and SF. At the flock level, clustering coefficients and overall attendance positively correlated with mean vegetation height, indicating a strong effect of habitat structure on flock cohesion and stability. Prior research has shown that trophic interactions are often resilient to large-scale changes in habitat structure because species are ecologically redundant. By contrast, our results suggest that behavioural interactions and the structure of non-trophic networks are highly sensitive to environmental change. Thus, a more nuanced, system-by-system approach may be needed when thinking about the resiliency of ecological networks.

Major component analysis of dynamic networks of physiologic organ interactions

NASA Astrophysics Data System (ADS)

Liu, Kang K. L.; Bartsch, Ronny P.; Ma, Qianli D. Y.; Ivanov, Plamen Ch

2015-09-01

The human organism is a complex network of interconnected organ systems, where the behavior of one system affects the dynamics of other systems. Identifying and quantifying dynamical networks of diverse physiologic systems under varied conditions is a challenge due to the complexity in the output dynamics of the individual systems and the transient and nonlinear characteristics of their coupling. We introduce a novel computational method based on the concept of time delay stability and major component analysis to investigate how organ systems interact as a network to coordinate their functions. We analyze a large database of continuously recorded multi-channel physiologic signals from healthy young subjects during night-time sleep. We identify a network of dynamic interactions between key physiologic systems in the human organism. Further, we find that each physiologic state is characterized by a distinct network structure with different relative contribution from individual organ systems to the global network dynamics. Specifically, we observe a gradual decrease in the strength of coupling of heart and respiration to the rest of the network with transition from wake to deep sleep, and in contrast, an increased relative contribution to network dynamics from chin and leg muscle tone and eye movement, demonstrating a robust association between network topology and physiologic function.

MuTE: a MATLAB toolbox to compare established and novel estimators of the multivariate transfer entropy.

PubMed

Montalto, Alessandro; Faes, Luca; Marinazzo, Daniele

2014-01-01

A challenge for physiologists and neuroscientists is to map information transfer between components of the systems that they study at different scales, in order to derive important knowledge on structure and function from the analysis of the recorded dynamics. The components of physiological networks often interact in a nonlinear way and through mechanisms which are in general not completely known. It is then safer that the method of choice for analyzing these interactions does not rely on any model or assumption on the nature of the data and their interactions. Transfer entropy has emerged as a powerful tool to quantify directed dynamical interactions. In this paper we compare different approaches to evaluate transfer entropy, some of them already proposed, some novel, and present their implementation in a freeware MATLAB toolbox. Applications to simulated and real data are presented.

MuTE: A MATLAB Toolbox to Compare Established and Novel Estimators of the Multivariate Transfer Entropy

PubMed Central

Montalto, Alessandro; Faes, Luca; Marinazzo, Daniele

2014-01-01

A challenge for physiologists and neuroscientists is to map information transfer between components of the systems that they study at different scales, in order to derive important knowledge on structure and function from the analysis of the recorded dynamics. The components of physiological networks often interact in a nonlinear way and through mechanisms which are in general not completely known. It is then safer that the method of choice for analyzing these interactions does not rely on any model or assumption on the nature of the data and their interactions. Transfer entropy has emerged as a powerful tool to quantify directed dynamical interactions. In this paper we compare different approaches to evaluate transfer entropy, some of them already proposed, some novel, and present their implementation in a freeware MATLAB toolbox. Applications to simulated and real data are presented. PMID:25314003

Attomole quantitation of protein separations with accelerator mass spectrometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vogel, J S; Grant, P G; Buccholz, B A

2000-12-15

Quantification of specific proteins depends on separation by chromatography or electrophoresis followed by chemical detection schemes such as staining and fluorophore adhesion. Chemical exchange of short-lived isotopes, particularly sulfur, is also prevalent despite the inconveniences of counting radioactivity. Physical methods based on isotopic and elemental analyses offer highly sensitive protein quantitation that has linear response over wide dynamic ranges and is independent of protein conformation. Accelerator mass spectrometry quantifies long-lived isotopes such as 14C to sub-attomole sensitivity. We quantified protein interactions with small molecules such as toxins, vitamins, and natural biochemicals at precisions of 1-5% . Micro-proton-induced-xray-emission quantifies elemental abundancesmore » in separated metalloprotein samples to nanogram amounts and is capable of quantifying phosphorylated loci in gels. Accelerator-based quantitation is a possible tool for quantifying the genome translation into proteome.« less

Protein stability and dynamics influenced by ligands in extremophilic complexes - a molecular dynamics investigation.

PubMed

Khan, Sara; Farooq, Umar; Kurnikova, Maria

2017-08-22

In this study, we explore the structural and dynamic adaptations of the Tryptophan synthase α-subunit in a ligand bound state in psychrophilic, mesophilic and hyperthermophilic organisms at different temperatures by MD simulations. We quantify the global and local fluctuations in the 40 ns time scale by analyzing the root mean square deviation/fluctuations. The distinct behavior of the active site and loop 6 is observed with the elevation of temperature. Protein stability relies more on electrostatic interactions, and these interactions might be responsible for the stability of varying temperature evolved proteins. The paper also focuses on the effect of temperature on protein dynamics and stability governed by the distinct behavior of the ligand associated with its retention, binding and dissociation over the course of time. The integration of principle component analysis and a free energy landscape was useful in identifying the conformational space accessible to ligand bound homologues and how the presence of the ligand alters the conformational and dynamic properties of the protein.

Vocalization Subsystem Responses to a Temporarily Induced Unilateral Vocal Fold Paralysis

ERIC Educational Resources Information Center

Croake, Daniel J.; Andreatta, Richard D.; Stemple, Joseph C.

2018-01-01

Purpose: The purpose of this study is to quantify the interactions of the 3 vocalization subsystems of respiration, phonation, and resonance before, during, and after a perturbation to the larynx (temporarily induced unilateral vocal fold paralysis) in 10 vocally healthy participants. Using dynamic systems theory as a guide, we hypothesized that…

A dynamic model of the radiation-belt electron phase-space density based on POLAR/HIST measurements

NASA Astrophysics Data System (ADS)

Vassiliadis, D.; Green, J. C.

2007-12-01

The response of the energetic-electron phase-space density (PSD) in the radiation belts is subject to a delicate combination of acceleration and loss processes which are strongly determined by the magnetospheric configuration and field disturbance level. We quantify the response of the density to stormtime fields as observed by the HIST detector on board POLAR. Several distinct modes are identified, characterized by peak second- and third- adiabatic invariants and peak delay time. The modes represent quasiadiabatic transport due to ring current activity; high L* (~6), day-long acceleration linked to ULF wave-particle interaction; and low-L* (~3), minute- to hour-long acceleration interpreted to be due to transient inductive fields or VLF wave-particle interaction. The net transport due to these responses is not always or everywhere diffusive, therefore we quantify the degree of departure from diffusive transport for specific storm intervals and radial ranges. Taken together the response modes comprise a dynamic, nonlinear model which allows us to better understand the historic variability of the high-energy tail of the electron distribution in the inner magnetosphere.

Anatomical connectivity influences both intra- and inter-brain synchronizations.

PubMed

Dumas, Guillaume; Chavez, Mario; Nadel, Jacqueline; Martinerie, Jacques

2012-01-01

Recent development in diffusion spectrum brain imaging combined to functional simulation has the potential to further our understanding of how structure and dynamics are intertwined in the human brain. At the intra-individual scale, neurocomputational models have already started to uncover how the human connectome constrains the coordination of brain activity across distributed brain regions. In parallel, at the inter-individual scale, nascent social neuroscience provides a new dynamical vista of the coupling between two embodied cognitive agents. Using EEG hyperscanning to record simultaneously the brain activities of subjects during their ongoing interaction, we have previously demonstrated that behavioral synchrony correlates with the emergence of inter-brain synchronization. However, the functional meaning of such synchronization remains to be specified. Here, we use a biophysical model to quantify to what extent inter-brain synchronizations are related to the anatomical and functional similarity of the two brains in interaction. Pairs of interacting brains were numerically simulated and compared to real data. Results show a potential dynamical property of the human connectome to facilitate inter-individual synchronizations and thus may partly account for our propensity to generate dynamical couplings with others.

Towards understanding the behavior of physical systems using information theory

NASA Astrophysics Data System (ADS)

Quax, Rick; Apolloni, Andrea; Sloot, Peter M. A.

2013-09-01

One of the goals of complex network analysis is to identify the most influential nodes, i.e., the nodes that dictate the dynamics of other nodes. In the case of autonomous systems or transportation networks, highly connected hubs play a preeminent role in diffusing the flow of information and viruses; in contrast, in language evolution most linguistic norms come from the peripheral nodes who have only few contacts. Clearly a topological analysis of the interactions alone is not sufficient to identify the nodes that drive the state of the network. Here we show how information theory can be used to quantify how the dynamics of individual nodes propagate through a system. We interpret the state of a node as a storage of information about the state of other nodes, which is quantified in terms of Shannon information. This information is transferred through interactions and lost due to noise, and we calculate how far it can travel through a network. We apply this concept to a model of opinion formation in a complex social network to calculate the impact of each node by measuring how long its opinion is remembered by the network. Counter-intuitively we find that the dynamics of opinions are not determined by the hubs or peripheral nodes, but rather by nodes with an intermediate connectivity.

Pacific Decadal Variability and Central Pacific Warming El Niño in a Changing Climate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Di Lorenzo, Emanuele

This research aimed at understanding the dynamics controlling decadal variability in the Pacific Ocean and its interactions with global-scale climate change. The first goal was to assess how the dynamics and statistics of the El Niño Southern Oscillation and the modes of Pacific decadal variability are represented in global climate models used in the IPCC. The second goal was to quantify how decadal dynamics are projected to change under continued greenhouse forcing, and determine their significance in the context of paleo-proxy reconstruction of long-term climate.

Decadal-scale ecosystem memory reveals interactive effects of drought and insect defoliation on boreal forest productivity

NASA Astrophysics Data System (ADS)

Itter, M.; D'Orangeville, L.; Dawson, A.; Kneeshaw, D.; Finley, A. O.

2017-12-01

Drought and insect defoliation have lasting impacts on the dynamics of the boreal forest. Impacts are expected to worsen under global climate change as hotter, drier conditions forecast for much of the boreal increase the frequency and severity of drought and defoliation events. Contemporary ecological theory predicts physiological feedbacks in tree responses to drought and defoliation amplify impacts potentially causing large-scale productivity losses and forest mortality. Quantifying the interactive impacts of drought and insect defoliation on regional forest health is difficult given delayed and persistent responses to disturbance events. We developed a Bayesian hierarchical model to estimate forest growth responses to interactions between drought and insect defoliation by species and size class. Delayed and persistent responses to past drought and defoliation were quantified using empirical memory functions allowing for improved detection of interactions. The model was applied to tree-ring data from stands in Western (Alberta) and Eastern (Québec) regions of the Canadian boreal forest with different species compositions, disturbance regimes, and regional climates. Western stands experience chronic water deficit and forest tent caterpillar (FTC) defoliation; Eastern stands experience irregular water deficit and spruce budworm (SBW) defoliation. Ecosystem memory to past water deficit peaked in the year previous to growth and decayed to zero within 5 (West) to 8 (East) years; memory to past defoliation ranged from 8 (West) to 12 (East) years. The drier regional climate and faster FTC defoliation dynamics (compared to SBW) likely contribute to shorter ecosystem memory in the West. Drought and defoliation had the largest negative impact on large-diameter, host tree growth. Surprisingly, a positive interaction was observed between drought and defoliation for large-diameter, non-host trees likely due to reduced stand-level competition for water. Results highlight the temporal persistence of drought and defoliation stress on boreal forest growth dynamics and provide an empirical estimate of their interactive effects with explicit uncertainty.

Quantification of dynamic soil - vegetation feedbacks following an isotopically labelled precipitation pulse

NASA Astrophysics Data System (ADS)

Piayda, Arndt; Dubbert, Maren; Siegwolf, Rolf; Cuntz, Matthias; Werner, Christiane

2017-04-01

The presence of vegetation alters hydrological cycles of ecosystems. Complex plant-soil interactions govern the fate of precipitation input and water transitions through ecosystem compartments. Disentangling these interactions is a major challenge in the field of ecohydrology and pivotal foundation for understanding the carbon cycle of semi-arid ecosystems. Stable water isotopes can be used in this context as tracer to quantify water movement through soil-vegetation-atmosphere interfaces. The aim of this study is to disentangle vegetation effects on soil water infiltration and distribution as well as dynamics of soil evaporation and grassland water-use in a Mediterranean cork-oak woodland during dry conditions. An irrigation experiment using δ18O-labeled water was carried out in order to quantify distinct effects of tree and herbaceous vegetation on infiltration and distribution of event water in the soil profile. Dynamic responses of soil and herbaceous vegetation fluxes to precipitation regarding event water-use, water uptake depth plasticity and contribution to ecosystem evapotranspiration were quantified. Total water loss to the atmosphere from bare soil was as high as from vegetated soil, utilizing large amounts of unproductive water loss for biomass production, carbon sequestration and nitrogen fixation. During the experiment no adjustments of main root water uptake depth to changes of water availability could be observed, rendering light to medium precipitation events under dry conditions useless. This forces understory plants to compete with adjacent trees for soil water in deeper soil layers. Thus understory plants are faster subject to chronic drought, leading to premature senescence at the onset of drought. Despite this water competition, the presence of Cork oak trees fosters infiltration to large degrees. That reduces drought stress, caused by evapotranspiration, due to favourable micro climatic conditions under tree crown shading. This study highlights complex soil-plant-atmosphere and inter-species interactions in both space and time controlling the fate of rain pulse transitions through a typical Mediterranean savannah ecosystem, disentangled by the use of stable water isotopes.

Quantification of dynamic soil-vegetation feedbacks following an isotopically labelled precipitation pulse

NASA Astrophysics Data System (ADS)

Piayda, Arndt; Dubbert, Maren; Siegwolf, Rolf; Cuntz, Matthias; Werner, Christiane

2017-05-01

The presence of vegetation alters hydrological cycles of ecosystems. Complex plant-soil interactions govern the fate of precipitation input and water transitions through ecosystem compartments. Disentangling these interactions is a major challenge in the field of ecohydrology and a pivotal foundation for understanding the carbon cycle of semi-arid ecosystems. Stable water isotopes can be used in this context as tracer to quantify water movement through soil-vegetation-atmosphere interfaces. The aim of this study is to disentangle vegetation effects on soil water infiltration and distribution as well as dynamics of soil evaporation and grassland water use in a Mediterranean cork oak woodland during dry conditions. An irrigation experiment using δ18O labelled water was carried out in order to quantify distinct effects of tree and herbaceous vegetation on the infiltration and distribution of event water in the soil profile. Dynamic responses of soil and herbaceous vegetation fluxes to precipitation regarding event water use, water uptake depth plasticity, and contribution to ecosystem soil evaporation and transpiration were quantified. Total water loss to the atmosphere from bare soil was as high as from vegetated soil, utilizing large amounts of unproductive evaporation for transpiration, but infiltration rates decreased. No adjustments of main root water uptake depth to changes in water availability could be observed during the experiment. This forces understorey plants to compete with adjacent trees for water in deeper soil layers at the onset of summer. Thus, understorey plants are subjected to chronic water deficits faster, leading to premature senescence at the onset of drought. Despite this water competition, the presence of cork oak trees fosters infiltration and reduces evapotranspirative water losses from the understorey and the soil, both due to altered microclimatic conditions under crown shading. This study highlights complex soil-plant-atmosphere and inter-species interactions controlling rain pulse transitions through a typical Mediterranean savannah ecosystem, disentangled by the use of stable water isotopes.

Quantifying long-term evolution of intra-urban spatial interactions

PubMed Central

Sun, Lijun; Jin, Jian Gang; Axhausen, Kay W.; Lee, Der-Horng; Cebrian, Manuel

2015-01-01

Understanding the long-term impact that changes in a city's transportation infrastructure have on its spatial interactions remains a challenge. The difficulty arises from the fact that the real impact may not be revealed in static or aggregated mobility measures, as these are remarkably robust to perturbations. More generally, the lack of longitudinal, cross-sectional data demonstrating the evolution of spatial interactions at a meaningful urban scale also hinders us from evaluating the sensitivity of movement indicators, limiting our capacity to understand the evolution of urban mobility in depth. Using very large mobility records distributed over 3 years, we quantify the impact of the completion of a metro line extension: the Circle Line (CCL) in Singapore. We find that the commonly used movement indicators are almost identical before and after the project was completed. However, in comparing the temporal community structure across years, we do observe significant differences in the spatial reorganization of the affected geographical areas. The completion of CCL enables travellers to re-identify their desired destinations collectively with lower transport cost, making the community structure more consistent. These changes in locality are dynamic and characterized over short timescales, offering us a different approach to identify and analyse the long-term impact of new infrastructures on cities and their evolution dynamics. PMID:25551142

An immunological approach to quantifying the saprotrophic growth dynamics of Trichoderma species during antagonistic interactions with Rhizoctonia solani in a soil-less mix.

PubMed

Thornton, Christopher R

2004-04-01

Studies of the saprotrophic growth dynamics of Trichoderma species and their fungal hosts during antagonistic interactions are severely hampered by the absence of methods that allow the unambiguous identification and quantification of individual genera in complex environments such as soil or compost containing mixed populations of fungi. Furthermore, methods are required that allow discrimination between active hyphal growth and other components of fungal biomass such as quiescent spores that are produced in large numbers by Trichoderma species. This study details the use of monoclonal antibodies to quantify the saprotrophic growth dynamics of the soil-borne plant pathogen Rhizoctonia solani and biological control strains of Trichoderma asperellum and Trichoderma harzianum during antagonistic interactions in peat-based microcosms. Quantification was based on the immunological detection of constitutive, extracellular antigens that are secreted from the growing tip of Rhizoctonia and Trichoderma mycelium and, in the case of Trichoderma harzianum, from quiescent phialoconidia also. The Trichoderma-specific monoclonal antibody (MF2) binds to a protein epitope of the enzyme glucoamylase, which was shown by immunofluorescence and immunogold electron gold microscopy studies of Trichoderma virens in vitro to be produced at the origin of germ tube emergence in phialoconidia and from the growing tip of germ tubes. In addition, a non-destructive immunoblotting technique showed that the enzyme was secreted during active growth of Trichoderma asperellum mycelium in peat. The Rhizoctonia solani-specific monoclonal antibody (EH2) similarly binds to a protein epitope of a glycoprotein that is secreted during active mycelial growth. Extracts derived from lyophilized mycelium were used as a quantifiable and repeatable source of antigens for construction of calibration curves. These curves were used to convert the absorbance values obtained in ELISA tests of peat extracts to biomass equivalents, which allowed comparisons of the saprotrophic growth dynamics of the pathogen and antagonists to be made in single or mixed species microcosms. Trichoderma species were able to compete successfully with R. solani for nutrients and to prevent saprotrophic growth of the pathogen. Specificity of the Trichoderma quantitative assay was tested in non-sterile soil-based microcosms artificially inoculated with T. asperellum. The assay was highly specific and only detected T. asperellum population dynamics. No cross-reactivity was found with extracts from soil samples containing contaminant fungi.

Two-soliton interaction as an elementary act of soliton turbulence in integrable systems

NASA Astrophysics Data System (ADS)

Pelinovsky, E. N.; Shurgalina, E. G.; Sergeeva, A. V.; Talipova, T. G.; El, G. A.; Grimshaw, R. H. J.

2013-01-01

Two-soliton interactions play a definitive role in the formation of the structure of soliton turbulence in integrable systems. To quantify the contribution of these interactions to the dynamical and statistical characteristics of the nonlinear wave field of soliton turbulence we study properties of the spatial moments of the two-soliton solution of the Korteweg-de Vries (KdV) equation. While the first two moments are integrals of the KdV evolution, the 3rd and 4th moments undergo significant variations in the dominant interaction region, which could have strong effect on the values of the skewness and kurtosis in soliton turbulence.

Density Scaling of Glassy Dynamics and Dynamic Heterogeneities in Glass-forming Liquids.

NASA Astrophysics Data System (ADS)

Hu, Yuan-Chao; Yang, Yong; Wang, Wei-Hua

The discovery of density scaling in strongly correlating systems is an important progress for understanding the dynamic behaviors of supercooled liquids. Here we found for a ternary metallic glass-forming liquid, it is not strongly correlating thermodynamically, but its average dynamics, dynamic heterogeneities and static structure are still well described by density scaling with the same scaling exponent γ. As an intrinsic material constant stemming from the fundamental interatomic interactions, γ is theoretically predicted from the thermodynamic fluctuations of potential energy and the virial. Although γ is conventionally understood merely from the repulsive part of the inter-particle potentials, the strong correlation between γ and the Grüneisen parameter up to the accuracy of the Dulong-Petit approximation demonstrates the important roles of anharmonicity and attractive force of the interatomic potential in governing glass transition of metallic glass-formers. The supercooled dynamics and density scaling behaviors will also be discussed in model glass-forming liquids with tunable attractive potentials to further quantify the nonperturbative roles of attractive interactions. We acknowledge the support from ''Peter Ho Conference Scholarships'' of City University of Hong Kong.

Quantifying why urea is a protein denaturant, whereas glycine betaine is a protein stabilizer

PubMed Central

Guinn, Emily J.; Pegram, Laurel M.; Capp, Michael W.; Pollock, Michelle N.; Record, M. Thomas

2011-01-01

To explain the large, opposite effects of urea and glycine betaine (GB) on stability of folded proteins and protein complexes, we quantify and interpret preferential interactions of urea with 45 model compounds displaying protein functional groups and compare with a previous analysis of GB. This information is needed to use urea as a probe of coupled folding in protein processes and to tune molecular dynamics force fields. Preferential interactions between urea and model compounds relative to their interactions with water are determined by osmometry or solubility and dissected using a unique coarse-grained analysis to obtain interaction potentials quantifying the interaction of urea with each significant type of protein surface (aliphatic, aromatic hydrocarbon (C); polar and charged N and O). Microscopic local-bulk partition coefficients Kp for the accumulation or exclusion of urea in the water of hydration of these surfaces relative to bulk water are obtained. Kp values reveal that urea accumulates moderately at amide O and weakly at aliphatic C, whereas GB is excluded from both. These results provide both thermodynamic and molecular explanations for the opposite effects of urea and glycine betaine on protein stability, as well as deductions about strengths of amide NH—amide O and amide NH—amide N hydrogen bonds relative to hydrogen bonds to water. Interestingly, urea, like GB, is moderately accumulated at aromatic C surface. Urea m-values for protein folding and other protein processes are quantitatively interpreted and predicted using these urea interaction potentials or Kp values. PMID:21930943

Quantifying why urea is a protein denaturant, whereas glycine betaine is a protein stabilizer.

PubMed

Guinn, Emily J; Pegram, Laurel M; Capp, Michael W; Pollock, Michelle N; Record, M Thomas

2011-10-11

To explain the large, opposite effects of urea and glycine betaine (GB) on stability of folded proteins and protein complexes, we quantify and interpret preferential interactions of urea with 45 model compounds displaying protein functional groups and compare with a previous analysis of GB. This information is needed to use urea as a probe of coupled folding in protein processes and to tune molecular dynamics force fields. Preferential interactions between urea and model compounds relative to their interactions with water are determined by osmometry or solubility and dissected using a unique coarse-grained analysis to obtain interaction potentials quantifying the interaction of urea with each significant type of protein surface (aliphatic, aromatic hydrocarbon (C); polar and charged N and O). Microscopic local-bulk partition coefficients K(p) for the accumulation or exclusion of urea in the water of hydration of these surfaces relative to bulk water are obtained. K(p) values reveal that urea accumulates moderately at amide O and weakly at aliphatic C, whereas GB is excluded from both. These results provide both thermodynamic and molecular explanations for the opposite effects of urea and glycine betaine on protein stability, as well as deductions about strengths of amide NH--amide O and amide NH--amide N hydrogen bonds relative to hydrogen bonds to water. Interestingly, urea, like GB, is moderately accumulated at aromatic C surface. Urea m-values for protein folding and other protein processes are quantitatively interpreted and predicted using these urea interaction potentials or K(p) values.

Protonation-induced stereoisomerism in nicotine: Conformational studies using classical (AMBER) and ab initio (Car Parrinello) molecular dynamics

NASA Astrophysics Data System (ADS)

Hammond, Philip S.; Wu, Yudong; Harris, Rebecca; Minehardt, Todd J.; Car, Roberto; Schmitt, Jeffrey D.

2005-01-01

A variety of biologically active small molecules contain prochiral tertiary amines, which become chiral centers upon protonation. S-nicotine, the prototypical nicotinic acetylcholine receptor agonist, produces two diastereomers on protonation. Results, using both classical (AMBER) and ab initio (Car-Parrinello) molecular dynamical studies, illustrate the significant differences in conformational space explored by each diastereomer. As is expected, this phenomenon has an appreciable effect on nicotine's energy hypersurface and leads to differentiation in molecular shape and divergent sampling. Thus, protonation induced isomerism can produce dynamic effects that may influence the behavior of a molecule in its interaction with a target protein. We also examine differences in the conformational dynamics for each diastereomer as quantified by both molecular dynamics methods.

Preface: Impacts of extreme climate events and disturbances on carbon dynamics

USGS Publications Warehouse

Xiao, Jingfeng; Liu, Shuguang; Stoy, Paul C.

2016-01-01

The impacts of extreme climate events and disturbances (ECE&D) on the carbon cycle have received growing attention in recent years. This special issue showcases a collection of recent advances in understanding the impacts of ECE&D on carbon cycling. Notable advances include quantifying how harvesting activities impact forest structure, carbon pool dynamics, and recovery processes; observed drastic increases of the concentrations of dissolved organic carbon and dissolved methane in thermokarst lakes in western Siberia during a summer warming event; disentangling the roles of herbivores and fire on forest carbon dioxide flux; direct and indirect impacts of fire on the global carbon balance; and improved atmospheric inversion of regional carbon sources and sinks by incorporating disturbances. Combined, studies herein indicate several major research needs. First, disturbances and extreme events can interact with one another, and it is important to understand their overall impacts and also disentangle their effects on the carbon cycle. Second, current ecosystem models are not skillful enough to correctly simulate the underlying processes and impacts of ECE&D (e.g., tree mortality and carbon consequences). Third, benchmark data characterizing the timing, location, type, and magnitude of disturbances must be systematically created to improve our ability to quantify carbon dynamics over large areas. Finally, improving the representation of ECE&D in regional climate/earth system models and accounting for the resulting feedbacks to climate are essential for understanding the interactions between climate and ecosystem dynamics.

Local Competition and Metapopulation Processes Drive Long-Term Seagrass-Epiphyte Population Dynamics

PubMed Central

Lobelle, Delphine; Kenyon, Emma J.; Cook, Kevan J.; Bull, James C.

2013-01-01

It is well known that ecological processes such as population regulation and natural enemy interactions potentially occur over a range of spatial scales, and there is a substantial body of literature developing theoretical understanding of the interplay between these processes. However, there are comparatively few studies quantifying the long-term effects of spatial scaling in natural ecosystems. A key challenge is that trophic complexity in real-world biological communities quickly obscures the signal from a focal process. Seagrass meadows provide an excellent opportunity in this respect: in many instances, seagrasses effectively form extensive natural monocultures, in which hypotheses about endogenous dynamics can be formulated and tested. We present amongst the longest unbroken, spatially explict time series of seagrass abundance published to date. Data include annual measures of shoot density, total above-ground abundance, and associated epiphyte cover from five Zostera marina meadows distributed around the Isles of Scilly, UK, from 1996 to 2011. We explore empirical patterns at the local and metapopulation scale using standard time series analysis and develop a simple population dynamic model, testing the hypothesis that both local and metapopulation scale feedback processes are important. We find little evidence of an interaction between scales in seagrass dynamics but that both scales contribute approximately equally to observed local epiphyte abundance. By quantifying the long-term dynamics of seagrass-epiphyte interactions we show how measures of density and extent are both important in establishing baseline information relevant to predicting responses to environmental change and developing management plans. We hope that this study complements existing mechanistic studies of physiology, genetics and productivity in seagrass, whilst highlighting the potential of seagrass as a model ecosystem. More generally, this study provides a rare opportunity to test some of the predictions of ecological theory in a natural ecosystem of global conservation and economic value. PMID:23437313

Local competition and metapopulation processes drive long-term seagrass-epiphyte population dynamics.

PubMed

Lobelle, Delphine; Kenyon, Emma J; Cook, Kevan J; Bull, James C

2013-01-01

It is well known that ecological processes such as population regulation and natural enemy interactions potentially occur over a range of spatial scales, and there is a substantial body of literature developing theoretical understanding of the interplay between these processes. However, there are comparatively few studies quantifying the long-term effects of spatial scaling in natural ecosystems. A key challenge is that trophic complexity in real-world biological communities quickly obscures the signal from a focal process. Seagrass meadows provide an excellent opportunity in this respect: in many instances, seagrasses effectively form extensive natural monocultures, in which hypotheses about endogenous dynamics can be formulated and tested. We present amongst the longest unbroken, spatially explict time series of seagrass abundance published to date. Data include annual measures of shoot density, total above-ground abundance, and associated epiphyte cover from five Zostera marina meadows distributed around the Isles of Scilly, UK, from 1996 to 2011. We explore empirical patterns at the local and metapopulation scale using standard time series analysis and develop a simple population dynamic model, testing the hypothesis that both local and metapopulation scale feedback processes are important. We find little evidence of an interaction between scales in seagrass dynamics but that both scales contribute approximately equally to observed local epiphyte abundance. By quantifying the long-term dynamics of seagrass-epiphyte interactions we show how measures of density and extent are both important in establishing baseline information relevant to predicting responses to environmental change and developing management plans. We hope that this study complements existing mechanistic studies of physiology, genetics and productivity in seagrass, whilst highlighting the potential of seagrass as a model ecosystem. More generally, this study provides a rare opportunity to test some of the predictions of ecological theory in a natural ecosystem of global conservation and economic value.

Aggrecan nanoscale solid-fluid interactions are a primary determinant of cartilage dynamic mechanical properties.

PubMed

Nia, Hadi Tavakoli; Han, Lin; Bozchalooi, Iman Soltani; Roughley, Peter; Youcef-Toumi, Kamal; Grodzinsky, Alan J; Ortiz, Christine

2015-03-24

Poroelastic interactions between interstitial fluid and the extracellular matrix of connective tissues are critical to biological and pathophysiological functions involving solute transport, energy dissipation, self-stiffening and lubrication. However, the molecular origins of poroelasticity at the nanoscale are largely unknown. Here, the broad-spectrum dynamic nanomechanical behavior of cartilage aggrecan monolayer is revealed for the first time, including the equilibrium and instantaneous moduli and the peak in the phase angle of the complex modulus. By performing a length scale study and comparing the experimental results to theoretical predictions, we confirm that the mechanism underlying the observed dynamic nanomechanics is due to solid-fluid interactions (poroelasticity) at the molecular scale. Utilizing finite element modeling, the molecular-scale hydraulic permeability of the aggrecan assembly was quantified (kaggrecan = (4.8 ± 2.8) × 10(-15) m(4)/N·s) and found to be similar to the nanoscale hydraulic permeability of intact normal cartilage tissue but much lower than that of early diseased tissue. The mechanisms underlying aggrecan poroelasticity were further investigated by altering electrostatic interactions between the molecule's constituent glycosaminoglycan chains: electrostatic interactions dominated steric interactions in governing molecular behavior. While the hydraulic permeability of aggrecan layers does not change across species and age, aggrecan from adult human cartilage is stiffer than the aggrecan from newborn human tissue.

Quantitative mass imaging of single biological macromolecules.

PubMed

Young, Gavin; Hundt, Nikolas; Cole, Daniel; Fineberg, Adam; Andrecka, Joanna; Tyler, Andrew; Olerinyova, Anna; Ansari, Ayla; Marklund, Erik G; Collier, Miranda P; Chandler, Shane A; Tkachenko, Olga; Allen, Joel; Crispin, Max; Billington, Neil; Takagi, Yasuharu; Sellers, James R; Eichmann, Cédric; Selenko, Philipp; Frey, Lukas; Riek, Roland; Galpin, Martin R; Struwe, Weston B; Benesch, Justin L P; Kukura, Philipp

2018-04-27

The cellular processes underpinning life are orchestrated by proteins and their interactions. The associated structural and dynamic heterogeneity, despite being key to function, poses a fundamental challenge to existing analytical and structural methodologies. We used interferometric scattering microscopy to quantify the mass of single biomolecules in solution with 2% sequence mass accuracy, up to 19-kilodalton resolution, and 1-kilodalton precision. We resolved oligomeric distributions at high dynamic range, detected small-molecule binding, and mass-imaged proteins with associated lipids and sugars. These capabilities enabled us to characterize the molecular dynamics of processes as diverse as glycoprotein cross-linking, amyloidogenic protein aggregation, and actin polymerization. Interferometric scattering mass spectrometry allows spatiotemporally resolved measurement of a broad range of biomolecular interactions, one molecule at a time. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Multiloop Manual Control of Dynamic Systems

NASA Technical Reports Server (NTRS)

Hess, R. A.; Mcnally, B. D.

1984-01-01

Human interaction with a simple, multiloop dynamic system in which the human's activity was systematically varied by changing the levels of automation was studied. The control loop structure resulting from the task definition parallels that for any multiloop manual control system, is considered a sterotype. Simple models of the human in the task, and upon extending a technique for describing the manner in which the human subjectively quantifies his opinion of task difficulty were developed. A man in the loop simulation which provides data to support and direct the analytical effort is presented.

Quantum simulation of dissipative processes without reservoir engineering

DOE PAGES

Di Candia, R.; Pedernales, J. S.; del Campo, A.; ...

2015-05-29

We present a quantum algorithm to simulate general finite dimensional Lindblad master equations without the requirement of engineering the system-environment interactions. The proposed method is able to simulate both Markovian and non-Markovian quantum dynamics. It consists in the quantum computation of the dissipative corrections to the unitary evolution of the system of interest, via the reconstruction of the response functions associated with the Lindblad operators. Our approach is equally applicable to dynamics generated by effectively non-Hermitian Hamiltonians. We confirm the quality of our method providing specific error bounds that quantify its accuracy.

Quantifying the abnormal hemodynamics of sickle cell anemia

NASA Astrophysics Data System (ADS)

Lei, Huan; Karniadakis, George

2012-02-01

Sickle red blood cells (SS-RBC) exhibit heterogeneous morphologies and abnormal hemodynamics in deoxygenated states. A multi-scale model for SS-RBC is developed based on the Dissipative Particle Dynamics (DPD) method. Different cell morphologies (sickle, granular, elongated shapes) typically observed in deoxygenated states are constructed and quantified by the Asphericity and Elliptical shape factors. The hemodynamics of SS-RBC suspensions is studied in both shear and pipe flow systems. The flow resistance obtained from both systems exhibits a larger value than the healthy blood flow due to the abnormal cell properties. Moreover, SS-RBCs exhibit abnormal adhesive interactions with both the vessel endothelium cells and the leukocytes. The effect of the abnormal adhesive interactions on the hemodynamics of sickle blood is investigated using the current model. It is found that both the SS-RBC - endothelium and the SS-RBC - leukocytes interactions, can potentially trigger the vicious ``sickling and entrapment'' cycles, resulting in vaso-occlusion phenomena widely observed in micro-circulation experiments.

Application of Dynamic Mode Decomposition: Temporal Evolution of Flow Structures in an Aneurysm

NASA Astrophysics Data System (ADS)

Conlin, William; Yu, Paulo; Durgesh, Vibhav

2017-11-01

An aneurysm is an enlargement of a weakened arterial wall that can be fatal or debilitating on rupture. Aneurysm hemodynamics is integral to developing an understanding of aneurysm formation, growth, and rupture. The flow in an aneurysm exhibits complex fluid dynamics behavior due to an inherent unsteady inflow condition and its interactions with large-scale flow structures present in the aneurysm. The objective of this study is to identify the large-scale structures in the aneurysm, study temporal behavior, and quantify their interaction with the inflow condition. For this purpose, detailed Particle Image Velocimetry (PIV) measurements were performed at the center plane of an idealized aneurysm model for a range of inflow conditions. Inflow conditions were precisely controlled using a ViVitro SuperPump system. Dynamic Modal Decomposition (DMD) of the velocity field was used to identify coherent structures and their temporal behavior. DMD was successful in capturing the large-scale flow structures and their temporal behavior. A low dimensional approximation to the flow field was obtained with the most relevant dynamic modes and was used to obtain temporal information about the coherent structures and their interaction with the inflow, formation, evolution, and growth.

Unraveling Hydrophobic Interactions at the Molecular Scale Using Force Spectroscopy and Molecular Dynamics Simulations.

PubMed

Stock, Philipp; Monroe, Jacob I; Utzig, Thomas; Smith, David J; Shell, M Scott; Valtiner, Markus

2017-03-28

Interactions between hydrophobic moieties steer ubiquitous processes in aqueous media, including the self-organization of biologic matter. Recent decades have seen tremendous progress in understanding these for macroscopic hydrophobic interfaces. Yet, it is still a challenge to experimentally measure hydrophobic interactions (HIs) at the single-molecule scale and thus to compare with theory. Here, we present a combined experimental-simulation approach to directly measure and quantify the sequence dependence and additivity of HIs in peptide systems at the single-molecule scale. We combine dynamic single-molecule force spectroscopy on model peptides with fully atomistic, both equilibrium and nonequilibrium, molecular dynamics (MD) simulations of the same systems. Specifically, we mutate a flexible (GS) 5 peptide scaffold with increasing numbers of hydrophobic leucine monomers and measure the peptides' desorption from hydrophobic self-assembled monolayer surfaces. Based on the analysis of nonequilibrium work-trajectories, we measure an interaction free energy that scales linearly with 3.0-3.4 k B T per leucine. In good agreement, simulations indicate a similar trend with 2.1 k B T per leucine, while also providing a detailed molecular view into HIs. This approach potentially provides a roadmap for directly extracting qualitative and quantitative single-molecule interactions at solid/liquid interfaces in a wide range of fields, including interactions at biointerfaces and adhesive interactions in industrial applications.

Tracking transcription factor mobility and interaction in Arabidopsis roots with fluorescence correlation spectroscopy

PubMed Central

Clark, Natalie M; Hinde, Elizabeth; Winter, Cara M; Fisher, Adam P; Crosti, Giuseppe; Blilou, Ikram; Gratton, Enrico; Benfey, Philip N; Sozzani, Rosangela

2016-01-01

To understand complex regulatory processes in multicellular organisms, it is critical to be able to quantitatively analyze protein movement and protein-protein interactions in time and space. During Arabidopsis development, the intercellular movement of SHORTROOT (SHR) and subsequent interaction with its downstream target SCARECROW (SCR) control root patterning and cell fate specification. However, quantitative information about the spatio-temporal dynamics of SHR movement and SHR-SCR interaction is currently unavailable. Here, we quantify parameters including SHR mobility, oligomeric state, and association with SCR using a combination of Fluorescent Correlation Spectroscopy (FCS) techniques. We then incorporate these parameters into a mathematical model of SHR and SCR, which shows that SHR reaches a steady state in minutes, while SCR and the SHR-SCR complex reach a steady-state between 18 and 24 hr. Our model reveals the timing of SHR and SCR dynamics and allows us to understand how protein movement and protein-protein stoichiometry contribute to development. DOI: http://dx.doi.org/10.7554/eLife.14770.001 PMID:27288545

Error correction in multi-fidelity molecular dynamics simulations using functional uncertainty quantification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reeve, Samuel Temple; Strachan, Alejandro, E-mail: strachan@purdue.edu

We use functional, Fréchet, derivatives to quantify how thermodynamic outputs of a molecular dynamics (MD) simulation depend on the potential used to compute atomic interactions. Our approach quantifies the sensitivity of the quantities of interest with respect to the input functions as opposed to its parameters as is done in typical uncertainty quantification methods. We show that the functional sensitivity of the average potential energy and pressure in isothermal, isochoric MD simulations using Lennard–Jones two-body interactions can be used to accurately predict those properties for other interatomic potentials (with different functional forms) without re-running the simulations. This is demonstrated undermore » three different thermodynamic conditions, namely a crystal at room temperature, a liquid at ambient pressure, and a high pressure liquid. The method provides accurate predictions as long as the change in potential can be reasonably described to first order and does not significantly affect the region in phase space explored by the simulation. The functional uncertainty quantification approach can be used to estimate the uncertainties associated with constitutive models used in the simulation and to correct predictions if a more accurate representation becomes available.« less

Spin-phase-space-entropy production

NASA Astrophysics Data System (ADS)

Santos, Jader P.; Céleri, Lucas C.; Brito, Frederico; Landi, Gabriel T.; Paternostro, Mauro

2018-05-01

Quantifying the degree of irreversibility of an open system dynamics represents a problem of both fundamental and applied relevance. Even though a well-known framework exists for thermal baths, the results give diverging results in the limit of zero temperature and are also not readily extended to nonequilibrium reservoirs, such as dephasing baths. Aimed at filling this gap, in this paper we introduce a phase-space-entropy production framework for quantifying the irreversibility of spin systems undergoing Lindblad dynamics. The theory is based on the spin Husimi-Q function and its corresponding phase-space entropy, known as Wehrl entropy. Unlike the von Neumann entropy production rate, we show that in our framework, the Wehrl entropy production rate remains valid at any temperature and is also readily extended to arbitrary nonequilibrium baths. As an application, we discuss the irreversibility associated with the interaction of a two-level system with a single-photon pulse, a problem which cannot be treated using the conventional approach.

Luciferase Protein Complementation Assays for Bioluminescence Imaging of Cells and Mice

PubMed Central

Luker, Gary D.; Luker, Kathryn E.

2015-01-01

Summary Protein fragment complementation assays (PCAs) with luciferase reporters currently are the preferred method for detecting and quantifying protein-protein interactions in living animals. At the most basic level, PCAs involve fusion of two proteins of interest to enzymatically inactive fragments of luciferase. Upon association of the proteins of interest, the luciferase fragments are capable of reconstituting enzymatic activity to generate luminescence in vivo. In addition to bi-molecular luciferase PCAs, unimolecular biosensors for hormones, kinases, and proteases also have been developed using target peptides inserted between inactive luciferase fragments. Luciferase PCAs offer unprecedented opportunities to quantify dynamics of protein-protein interactions in intact cells and living animals, but successful use of luciferase PCAs in cells and mice involves careful consideration of many technical factors. This chapter discusses the design of luciferase PCAs appropriate for animal imaging, including construction of reporters, incorporation of reporters into cells and mice, imaging techniques, and data analysis. PMID:21153371

Defining Early Markers of Neurodevelopmental Disorders in Infants With TSC

DTIC Science & Technology

2013-10-01

in (1) children with autism and tuberous sclerosis complex and (2) children with temporal lobe tubers. This study is the first to quantify atypical...Furthermore, we hypothesize that it is the dynamic interplay between aberrant functional connectivity and physiological stressors, such as epilepsy ...neurodevelopmental disorders in children with TSC, particularly the interaction between clinical factors (such as epilepsy or tuber burden) and cognitive and

SST Control by Subsurface Mixing During Indian Ocean Monsoons

DTIC Science & Technology

2015-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. SST Control by Subsurface Mixing during Indian Ocean ...quantify the variability in upper ocean mixing associated with changes in barrier layer thickness and strength across the BoB and under different...These objectives directly target the fundamental role that upper ocean dynamics play in the complex air-sea interactions of the northern Indian Ocean

Predictability, Force and (Anti-)Resonance in Complex Object Control.

PubMed

Maurice, Pauline; Hogan, Neville; Sternad, Dagmar

2018-04-18

Manipulation of complex objects as in tool use is ubiquitous and has given humans an evolutionary advantage. This study examined the strategies humans choose when manipulating an object with underactuated internal dynamics, such as a cup of coffee. The object's dynamics renders the temporal evolution complex, possibly even chaotic, and difficult to predict. A cart-and-pendulum model, loosely mimicking coffee sloshing in a cup, was implemented in a virtual environment with a haptic interface. Participants rhythmically manipulated the virtual cup containing a rolling ball; they could choose the oscillation frequency, while the amplitude was prescribed. Three hypotheses were tested: 1) humans decrease interaction forces between hand and object; 2) humans increase the predictability of the object dynamics; 3) humans exploit the resonances of the coupled object-hand system. Analysis revealed that humans chose either a high-frequency strategy with anti-phase cup-and-ball movements or a low-frequency strategy with in-phase cup-and-ball movements. Counter Hypothesis 1, they did not decrease interaction force; instead, they increased the predictability of the interaction dynamics, quantified by mutual information, supporting Hypothesis 2. To address Hypothesis 3, frequency analysis of the coupled hand-object system revealed two resonance frequencies separated by an anti-resonance frequency. The low-frequency strategy exploited one resonance, while the high-frequency strategy afforded more choice, consistent with the frequency response of the coupled system; both strategies avoided the anti-resonance. Hence, humans did not prioritize interaction force, but rather strategies that rendered interactions predictable. These findings highlight that physical interactions with complex objects pose control challenges not present in unconstrained movements.

A molecular dynamics study of freezing in a confined geometry

NASA Technical Reports Server (NTRS)

Ma, Wen-Jong; Banavar, Jayanth R.; Koplik, Joel

1992-01-01

The dynamics of freezing of a Lennard-Jones liquid in narrow channels bounded by molecular walls is studied by computer simulation. The time development of ordering is quantified and a novel freezing mechanism is observed. The liquid forms layers and subsequent in-plane ordering within a layer is accompanied by a sharpening of the layer in the transverse direction. The effects of channel size, the methods of quench, the liquid-wall interaction and the roughness of walls on the freezing mechanism are elucidated. Comparison with recent experiments on freezing in confined geometries is presented.

Closing loop base pairs in RNA loop-loop complexes: structural behavior, interaction energy and solvation analysis through molecular dynamics simulations.

PubMed

Golebiowski, Jérôme; Antonczak, Serge; Fernandez-Carmona, Juan; Condom, Roger; Cabrol-Bass, Daniel

2004-12-01

Nanosecond molecular dynamics using the Ewald summation method have been performed to elucidate the structural and energetic role of the closing base pair in loop-loop RNA duplexes neutralized by Mg2+ counterions in aqueous phases. Mismatches GA, CU and Watson-Crick GC base pairs have been considered for closing the loop of an RNA in complementary interaction with HIV-1 TAR. The simulations reveal that the mismatch GA base, mediated by a water molecule, leads to a complex that presents the best compromise between flexibility and energetic contributions. The mismatch CU base pair, in spite of the presence of an inserted water molecule, is too short to achieve a tight interaction at the closing-loop junction and seems to force TAR to reorganize upon binding. An energetic analysis has allowed us to quantify the strength of the interactions of the closing and the loop-loop pairs throughout the simulations. Although the water-mediated GA closing base pair presents an interaction energy similar to that found on fully geometry-optimized structure, the water-mediated CU closing base pair energy interaction reaches less than half the optimal value.

Quantifying the effect of hydrogen on dislocation dynamics: A three-dimensional discrete dislocation dynamics framework

NASA Astrophysics Data System (ADS)

Gu, Yejun; El-Awady, Jaafar A.

2018-03-01

We present a new framework to quantify the effect of hydrogen on dislocations using large scale three-dimensional (3D) discrete dislocation dynamics (DDD) simulations. In this model, the first order elastic interaction energy associated with the hydrogen-induced volume change is accounted for. The three-dimensional stress tensor induced by hydrogen concentration, which is in equilibrium with respect to the dislocation stress field, is derived using the Eshelby inclusion model, while the hydrogen bulk diffusion is treated as a continuum process. This newly developed framework is utilized to quantify the effect of different hydrogen concentrations on the dynamics of a glide dislocation in the absence of an applied stress field as well as on the spacing between dislocations in an array of parallel edge dislocations. A shielding effect is observed for materials having a large hydrogen diffusion coefficient, with the shield effect leading to the homogenization of the shrinkage process leading to the glide loop maintaining its circular shape, as well as resulting in a decrease in dislocation separation distances in the array of parallel edge dislocations. On the other hand, for materials having a small hydrogen diffusion coefficient, the high hydrogen concentrations around the edge characters of the dislocations act to pin them. Higher stresses are required to be able to unpin the dislocations from the hydrogen clouds surrounding them. Finally, this new framework can open the door for further large scale studies on the effect of hydrogen on the different aspects of dislocation-mediated plasticity in metals. With minor modifications of the current formulations, the framework can also be extended to account for general inclusion-induced stress field in discrete dislocation dynamics simulations.

Communication Dynamics in Finite Capacity Social Networks

NASA Astrophysics Data System (ADS)

Haerter, Jan O.; Jamtveit, Bjørn; Mathiesen, Joachim

2012-10-01

In communication networks, structure and dynamics are tightly coupled. The structure controls the flow of information and is itself shaped by the dynamical process of information exchanged between nodes. In order to reconcile structure and dynamics, a generic model, based on the local interaction between nodes, is considered for the communication in large social networks. In agreement with data from a large human organization, we show that the flow is non-Markovian and controlled by the temporal limitations of individuals. We confirm the versatility of our model by predicting simultaneously the degree-dependent node activity, the balance between information input and output of nodes, and the degree distribution. Finally, we quantify the limitations to network analysis when it is based on data sampled over a finite period of time.

Hypersonic Magneto-Fluid-Dynamic Compression in Cylindrical Inlet

NASA Technical Reports Server (NTRS)

Shang, Joseph S.; Chang, Chau-Lyan

2007-01-01

Hypersonic magneto-fluid-dynamic interaction has been successfully performed as a virtual leading-edge strake and a virtual cowl of a cylindrical inlet. In a side-by-side experimental and computational study, the magnitude of the induced compression was found to be depended on configuration and electrode placement. To better understand the interacting phenomenon the present investigation is focused on a direct current discharge at the leading edge of a cylindrical inlet for which validating experimental data is available. The present computational result is obtained by solving the magneto-fluid-dynamics equations at the low magnetic Reynolds number limit and using a nonequilibrium weakly ionized gas model based on the drift-diffusion theory. The numerical simulation provides a detailed description of the intriguing physics. After validation with experimental measurements, the computed results further quantify the effectiveness of a magnet-fluid-dynamic compression for a hypersonic cylindrical inlet. At a minuscule power input to a direct current surface discharge of 8.14 watts per square centimeter of electrode area produces an additional compression of 6.7 percent for a constant cross-section cylindrical inlet.

Quantifying gaze and mouse interactions on spatial visual interfaces with a new movement analytics methodology

PubMed Central

2017-01-01

Eye movements provide insights into what people pay attention to, and therefore are commonly included in a variety of human-computer interaction studies. Eye movement recording devices (eye trackers) produce gaze trajectories, that is, sequences of gaze location on the screen. Despite recent technological developments that enabled more affordable hardware, gaze data are still costly and time consuming to collect, therefore some propose using mouse movements instead. These are easy to collect automatically and on a large scale. If and how these two movement types are linked, however, is less clear and highly debated. We address this problem in two ways. First, we introduce a new movement analytics methodology to quantify the level of dynamic interaction between the gaze and the mouse pointer on the screen. Our method uses volumetric representation of movement, the space-time densities, which allows us to calculate interaction levels between two physically different types of movement. We describe the method and compare the results with existing dynamic interaction methods from movement ecology. The sensitivity to method parameters is evaluated on simulated trajectories where we can control interaction levels. Second, we perform an experiment with eye and mouse tracking to generate real data with real levels of interaction, to apply and test our new methodology on a real case. Further, as our experiment tasks mimics route-tracing when using a map, it is more than a data collection exercise and it simultaneously allows us to investigate the actual connection between the eye and the mouse. We find that there seem to be natural coupling when eyes are not under conscious control, but that this coupling breaks down when instructed to move them intentionally. Based on these observations, we tentatively suggest that for natural tracing tasks, mouse tracking could potentially provide similar information as eye-tracking and therefore be used as a proxy for attention. However, more research is needed to confirm this. PMID:28777822

Quantifying gaze and mouse interactions on spatial visual interfaces with a new movement analytics methodology.

PubMed

Demšar, Urška; Çöltekin, Arzu

2017-01-01

Eye movements provide insights into what people pay attention to, and therefore are commonly included in a variety of human-computer interaction studies. Eye movement recording devices (eye trackers) produce gaze trajectories, that is, sequences of gaze location on the screen. Despite recent technological developments that enabled more affordable hardware, gaze data are still costly and time consuming to collect, therefore some propose using mouse movements instead. These are easy to collect automatically and on a large scale. If and how these two movement types are linked, however, is less clear and highly debated. We address this problem in two ways. First, we introduce a new movement analytics methodology to quantify the level of dynamic interaction between the gaze and the mouse pointer on the screen. Our method uses volumetric representation of movement, the space-time densities, which allows us to calculate interaction levels between two physically different types of movement. We describe the method and compare the results with existing dynamic interaction methods from movement ecology. The sensitivity to method parameters is evaluated on simulated trajectories where we can control interaction levels. Second, we perform an experiment with eye and mouse tracking to generate real data with real levels of interaction, to apply and test our new methodology on a real case. Further, as our experiment tasks mimics route-tracing when using a map, it is more than a data collection exercise and it simultaneously allows us to investigate the actual connection between the eye and the mouse. We find that there seem to be natural coupling when eyes are not under conscious control, but that this coupling breaks down when instructed to move them intentionally. Based on these observations, we tentatively suggest that for natural tracing tasks, mouse tracking could potentially provide similar information as eye-tracking and therefore be used as a proxy for attention. However, more research is needed to confirm this.

Coupled range dynamics of brood parasites and their hosts responding to climate and vegetation changes.

PubMed

Péron, Guillaume; Altwegg, Res; Jamie, Gabriel A; Spottiswoode, Claire N

2016-09-01

As populations shift their ranges in response to global change, local species assemblages can change, setting the stage for new ecological interactions, community equilibria and evolutionary responses. Here, we focus on the range dynamics of four avian brood parasite species and their hosts in southern Africa, in a context of bush encroachment (increase in woody vegetation density in places previously occupied by savanna-grassland mosaics) favouring some species at the expense of others. We first tested whether hosts and parasites constrained each other's ability to expand or maintain their ranges. Secondly, we investigated whether range shifts represented an opportunity for new host-parasite and parasite-parasite interactions. We used multispecies dynamic occupancy models with interactions, fitted to citizen science data, to estimate the contribution of interspecific interactions to range shifts and to quantify the change in species co-occurrence probability over a 25-year period. Parasites were able to track their hosts' range shifts. We detected no deleterious effect of the parasites' presence on either the local population viability of host species or the hosts' ability to colonize newly suitable areas. In the recently diversified indigobird radiation (Vidua spp.), following bush encroachment, the new assemblages presented more potential opportunities for speciation via host switch, but also more potential for hybridization between extant lineages, also via host switch. Multispecies dynamic occupancy models with interactions brought new insights into the feedbacks between range shifts, biotic interactions and local demography: brood parasitism had little detected impact on extinction or colonization processes, but inversely the latter processes affected biotic interactions via the modification of co-occurrence patterns. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

Quantifying long-range correlations and 1/f patterns in a minimal experiment of social interaction

PubMed Central

Bedia, Manuel G.; Aguilera, Miguel; Gómez, Tomás; Larrode, David G.; Seron, Francisco

2014-01-01

In recent years, researchers in social cognition have found the “perceptual crossing paradigm” to be both a theoretical and practical advance toward meeting particular challenges. This paradigm has been used to analyze the type of interactive processes that emerge in minimal interactions and it has allowed progress toward understanding of the principles of social cognition processes. In this paper, we analyze whether some critical aspects of these interactions could not have been observed by previous studies. We consider alternative indicators that could complete, or even lead us to rethink, the current interpretation of the results obtained from both experimental and simulated modeling in the fields of social interactions and minimal perceptual crossing. In particular, we discuss the possibility that previous experiments have been analytically constrained to a short-term dynamic type of player response. Additionally, we propose the possibility of considering these experiments from a more suitable framework based on the use and analysis of long-range correlations and fractal dynamics. We will also reveal evidence supporting the idea that social interactions are deployed along many scales of activity. Specifically, we propose that the fractal structure of the interactions could be a more adequate framework to understand the type of social interaction patterns generated in a social engagement. PMID:25429277

Dynamics of prebiotic RNA reproduction illuminated by chemical game theory

PubMed Central

Yeates, Jessica A. M.; Hilbe, Christian; Zwick, Martin; Nowak, Martin A.; Lehman, Niles

2016-01-01

Many origins-of-life scenarios depict a situation in which there are common and potentially scarce resources needed by molecules that compete for survival and reproduction. The dynamics of RNA assembly in a complex mixture of sequences is a frequency-dependent process and mimics such scenarios. By synthesizing Azoarcus ribozyme genotypes that differ in their single-nucleotide interactions with other genotypes, we can create molecules that interact among each other to reproduce. Pairwise interplays between RNAs involve both cooperation and selfishness, quantifiable in a 2 × 2 payoff matrix. We show that a simple model of differential equations based on chemical kinetics accurately predicts the outcomes of these molecular competitions using simple rate inputs into these matrices. In some cases, we find that mixtures of different RNAs reproduce much better than each RNA type alone, reflecting a molecular form of reciprocal cooperation. We also demonstrate that three RNA genotypes can stably coexist in a rock–paper–scissors analog. Our experiments suggest a new type of evolutionary game dynamics, called prelife game dynamics or chemical game dynamics. These operate without template-directed replication, illustrating how small networks of RNAs could have developed and evolved in an RNA world. PMID:27091972

Dynamics of prebiotic RNA reproduction illuminated by chemical game theory.

PubMed

Yeates, Jessica A M; Hilbe, Christian; Zwick, Martin; Nowak, Martin A; Lehman, Niles

2016-05-03

Many origins-of-life scenarios depict a situation in which there are common and potentially scarce resources needed by molecules that compete for survival and reproduction. The dynamics of RNA assembly in a complex mixture of sequences is a frequency-dependent process and mimics such scenarios. By synthesizing Azoarcus ribozyme genotypes that differ in their single-nucleotide interactions with other genotypes, we can create molecules that interact among each other to reproduce. Pairwise interplays between RNAs involve both cooperation and selfishness, quantifiable in a 2 × 2 payoff matrix. We show that a simple model of differential equations based on chemical kinetics accurately predicts the outcomes of these molecular competitions using simple rate inputs into these matrices. In some cases, we find that mixtures of different RNAs reproduce much better than each RNA type alone, reflecting a molecular form of reciprocal cooperation. We also demonstrate that three RNA genotypes can stably coexist in a rock-paper-scissors analog. Our experiments suggest a new type of evolutionary game dynamics, called prelife game dynamics or chemical game dynamics. These operate without template-directed replication, illustrating how small networks of RNAs could have developed and evolved in an RNA world.

Instantaneous Transfer Entropy for the Study of Cardiovascular and Cardiorespiratory Nonstationary Dynamics.

PubMed

Valenza, Gaetano; Faes, Luca; Citi, Luca; Orini, Michele; Barbieri, Riccardo

2018-05-01

Measures of transfer entropy (TE) quantify the direction and strength of coupling between two complex systems. Standard approaches assume stationarity of the observations, and therefore are unable to track time-varying changes in nonlinear information transfer with high temporal resolution. In this study, we aim to define and validate novel instantaneous measures of TE to provide an improved assessment of complex nonstationary cardiorespiratory interactions. We here propose a novel instantaneous point-process TE (ipTE) and validate its assessment as applied to cardiovascular and cardiorespiratory dynamics. In particular, heartbeat and respiratory dynamics are characterized through discrete time series, and modeled with probability density functions predicting the time of the next physiological event as a function of the past history. Likewise, nonstationary interactions between heartbeat and blood pressure dynamics are characterized as well. Furthermore, we propose a new measure of information transfer, the instantaneous point-process information transfer (ipInfTr), which is directly derived from point-process-based definitions of the Kolmogorov-Smirnov distance. Analysis on synthetic data, as well as on experimental data gathered from healthy subjects undergoing postural changes confirms that ipTE, as well as ipInfTr measures are able to dynamically track changes in physiological systems coupling. This novel approach opens new avenues in the study of hidden, transient, nonstationary physiological states involving multivariate autonomic dynamics in cardiovascular health and disease. The proposed method can also be tailored for the study of complex multisystem physiology (e.g., brain-heart or, more in general, brain-body interactions).

From structure to function, via dynamics

NASA Astrophysics Data System (ADS)

Stetter, O.; Soriano, J.; Geisel, T.; Battaglia, D.

2013-01-01

Neurons in the brain are wired into a synaptic network that spans multiple scales, from local circuits within cortical columns to fiber tracts interconnecting distant areas. However, brain function require the dynamic control of inter-circuit interactions on time-scales faster than synaptic changes. In particular, strength and direction of causal influences between neural populations (described by the so-called directed functional connectivity) must be reconfigurable even when the underlying structural connectivity is fixed. Such directed functional influences can be quantified resorting to causal analysis of time-series based on tools like Granger Causality or Transfer Entropy. The ability to quickly reorganize inter-areal interactions is a chief requirement for performance in a changing natural environment. But how can manifold functional networks stem "on demand" from an essentially fixed structure? We explore the hypothesis that the self-organization of neuronal synchronous activity underlies the control of brain functional connectivity. Based on simulated and real recordings of critical neuronal cultures in vitro, as well as on mean-field and spiking network models of interacting brain areas, we have found that "function follows dynamics", rather than structure. Different dynamic states of a same structural network, characterized by different synchronization properties, are indeed associated to different functional digraphs (functional multiplicity). We also highlight the crucial role of dynamics in establishing a structure-to-function link, by showing that whenever different structural topologies lead to similar dynamical states, than the associated functional connectivities are also very similar (structural degeneracy).

Current induced vortex wall dynamics in helical magnetic systems

NASA Astrophysics Data System (ADS)

Roostaei, Bahman

2015-03-01

Nontrivial topology of interfaces separating phases with opposite chirality in helical magnetic metals result in new effects as they interact with spin polarized current. These interfaces or vortex walls consist of a one dimensional array of vortex lines. We predict that adiabatic transfer of angular momentum between vortex array and spin polarized current will result in topological Hall effect in multi-domain samples. Also we predict that the motion of the vortex array will result in a new damping mechanism for magnetic moments based on Lenz's law. We study the dynamics of these walls interacting with electric current and use fundamental electromagnetic laws to quantify those predictions. On the other hand discrete nature of vortex walls affects their pinning and results in low depinning current density. We predict the value of this current using collective pinning theory.

Entropy gives rise to topologically associating domains

PubMed Central

Vasquez, Paula A.; Hult, Caitlin; Adalsteinsson, David; Lawrimore, Josh; Forest, Mark G.; Bloom, Kerry

2016-01-01

We investigate chromosome organization within the nucleus using polymer models whose formulation is closely guided by experiments in live yeast cells. We employ bead-spring chromosome models together with loop formation within the chains and the presence of nuclear bodies to quantify the extent to which these mechanisms shape the topological landscape in the interphase nucleus. By investigating the genome as a dynamical system, we show that domains of high chromosomal interactions can arise solely from the polymeric nature of the chromosome arms due to entropic interactions and nuclear confinement. In this view, the role of bio-chemical related processes is to modulate and extend the duration of the interacting domains. PMID:27257057

Stochasticity and Spatial Interaction Govern Stem Cell Differentiation Dynamics

NASA Astrophysics Data System (ADS)

Smith, Quinton; Stukalin, Evgeny; Kusuma, Sravanti; Gerecht, Sharon; Sun, Sean X.

2015-07-01

Stem cell differentiation underlies many fundamental processes such as development, tissue growth and regeneration, as well as disease progression. Understanding how stem cell differentiation is controlled in mixed cell populations is an important step in developing quantitative models of cell population dynamics. Here we focus on quantifying the role of cell-cell interactions in determining stem cell fate. Toward this, we monitor stem cell differentiation in adherent cultures on micropatterns and collect statistical cell fate data. Results show high cell fate variability and a bimodal probability distribution of stem cell fraction on small (80-140 μm diameter) micropatterns. On larger (225-500 μm diameter) micropatterns, the variability is also high but the distribution of the stem cell fraction becomes unimodal. Using a stochastic model, we analyze the differentiation dynamics and quantitatively determine the differentiation probability as a function of stem cell fraction. Results indicate that stem cells can interact and sense cellular composition in their immediate neighborhood and adjust their differentiation probability accordingly. Blocking epithelial cadherin (E-cadherin) can diminish this cell-cell contact mediated sensing. For larger micropatterns, cell motility adds a spatial dimension to the picture. Taken together, we find stochasticity and cell-cell interactions are important factors in determining cell fate in mixed cell populations.

Recurrence quantification analysis to characterize cyclical components of environmental elemental exposures during fetal and postnatal development

PubMed Central

Austin, Christine; Gennings, Chris; Tammimies, Kristiina; Bölte, Sven; Arora, Manish

2017-01-01

Environmental exposures to essential and toxic elements may alter health trajectories, depending on the timing, intensity, and mixture of exposures. In epidemiologic studies, these factors are typically analyzed as a function of elemental concentrations in biological matrices measured at one or more points in time. Such an approach, however, fails to account for the temporal cyclicity in the metabolism of environmental chemicals, which if perturbed may lead to adverse health outcomes. Here, we conceptualize and apply a non-linear method–recurrence quantification analysis (RQA)–to quantify cyclical components of prenatal and early postnatal exposure profiles for elements essential to normal development, including Zn, Mn, Mg, and Ca, and elements associated with deleterious health effects or narrow tolerance ranges, including Pb, As, and Cr. We found robust evidence of cyclical patterns in the metabolic profiles of nutrient elements, which we validated against randomized twin-surrogate time-series, and further found that nutrient dynamical properties differ from those of Cr, As, and Pb. Furthermore, we extended this approach to provide a novel method of quantifying dynamic interactions between two environmental exposures. To achieve this, we used cross-recurrence quantification analysis (CRQA), and found that elemental nutrient-nutrient interactions differed from those involving toxicants. These rhythmic regulatory interactions, which we characterize in two geographically distinct cohorts, have not previously been uncovered using traditional regression-based approaches, and may provide a critical unit of analysis for environmental and dietary exposures in epidemiological studies. PMID:29112980

Plant-pollinator interactions in a biodiverse meadow are rather stable and tight for 3 consecutive years.

PubMed

Fang, Qiang; Huang, Shuangquan

2016-05-01

Plant-pollinator interactions can be highly variable across years in natural communities. Although variation in the species composition and its basic structure has been investigated to understand the dynamic nature of pollination networks, little is known about the temporal dynamic of interaction strength between the same plant and pollinator species in any natural community. Pollinator-mediated selection on the evolution of floral traits could be diminished if plant-pollinator interactions vary temporally. To quantify the temporal variation in plant-pollinator interactions and the interaction strength (observed visits), we compared weighted networks between plants and pollinators in a biodiverse alpine meadow in Shangri-La, southwest China for 3 consecutive years. Although plant-pollinator interactions were highly dynamic such that identical interactions only accounted for 10.7% of the total between pair years, the diversity of interactions was stable. These identical interactions contributed 41.2% of total visits and were similar in strength and weighted nestedness. For plant species, 72.6% of species were visited by identical pollinator species between pair years, accounting for over half of the total visits and three-quarters at the functional group level. More generalized pollinators contributed more connectiveness and were more central in networks across years. However, there was no similar or even opposite trend for plant species, which suggested that specialized plant species may also be central in pollinator networks. The variation in pollinator composition decreased as pollinator species numbers increased, suggesting that generalized plants experienced stable pollinator partition. The stable, tight interactions between generalized pollinators and specialized plants represent cornerstones of the studied community. © 2016 International Society of Zoological Sciences, Institute of Zoology/Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

Quantification of correlations in quantum many-particle systems.

PubMed

Byczuk, Krzysztof; Kuneš, Jan; Hofstetter, Walter; Vollhardt, Dieter

2012-02-24

We introduce a well-defined and unbiased measure of the strength of correlations in quantum many-particle systems which is based on the relative von Neumann entropy computed from the density operator of correlated and uncorrelated states. The usefulness of this general concept is demonstrated by quantifying correlations of interacting electrons in the Hubbard model and in a series of transition-metal oxides using dynamical mean-field theory.

The complex nature of calcium cation interactions with phospholipid bilayers

PubMed Central

Melcrová, Adéla; Pokorna, Sarka; Pullanchery, Saranya; Kohagen, Miriam; Jurkiewicz, Piotr; Hof, Martin; Jungwirth, Pavel; Cremer, Paul S.; Cwiklik, Lukasz

2016-01-01

Understanding interactions of calcium with lipid membranes at the molecular level is of great importance in light of their involvement in calcium signaling, association of proteins with cellular membranes, and membrane fusion. We quantify these interactions in detail by employing a combination of spectroscopic methods with atomistic molecular dynamics simulations. Namely, time-resolved fluorescent spectroscopy of lipid vesicles and vibrational sum frequency spectroscopy of lipid monolayers are used to characterize local binding sites of calcium in zwitterionic and anionic model lipid assemblies, while dynamic light scattering and zeta potential measurements are employed for macroscopic characterization of lipid vesicles in calcium-containing environments. To gain additional atomic-level information, the experiments are complemented by molecular simulations that utilize an accurate force field for calcium ions with scaled charges effectively accounting for electronic polarization effects. We demonstrate that lipid membranes have substantial calcium-binding capacity, with several types of binding sites present. Significantly, the binding mode depends on calcium concentration with important implications for calcium buffering, synaptic plasticity, and protein-membrane association. PMID:27905555

Predictive power of food web models based on body size decreases with trophic complexity.

PubMed

Jonsson, Tomas; Kaartinen, Riikka; Jonsson, Mattias; Bommarco, Riccardo

2018-05-01

Food web models parameterised using body size show promise to predict trophic interaction strengths (IS) and abundance dynamics. However, this remains to be rigorously tested in food webs beyond simple trophic modules, where indirect and intraguild interactions could be important and driven by traits other than body size. We systematically varied predator body size, guild composition and richness in microcosm insect webs and compared experimental outcomes with predictions of IS from models with allometrically scaled parameters. Body size was a strong predictor of IS in simple modules (r 2  = 0.92), but with increasing complexity the predictive power decreased, with model IS being consistently overestimated. We quantify the strength of observed trophic interaction modifications, partition this into density-mediated vs. behaviour-mediated indirect effects and show that model shortcomings in predicting IS is related to the size of behaviour-mediated effects. Our findings encourage development of dynamical food web models explicitly including and exploring indirect mechanisms. © 2018 John Wiley & Sons Ltd/CNRS.

The dominant interaction between peptide and urea is electrostatic in nature: a molecular dynamics simulation study.

PubMed

Tobi, Dror; Elber, Ron; Thirumalai, Devarajan

2003-03-01

The conformational equilibrium of a blocked valine peptide in water and aqueous urea solution is studied using molecular dynamics simulations. Pair correlation functions indicate enhanced concentration of urea near the peptide. Stronger hydrogen bonding of urea-peptide compared to water-peptide is observed with preference for helical conformation. The potential of mean force, computed using umbrella sampling, shows only small differences between urea and water solvation that are difficult to quantify. The changes in solvent structure around the peptide are explained by favorable electrostatic interactions (hydrogen bonds) of urea with the peptide backbone. There is no evidence for significant changes in hydrophobic interactions in the two conformations of the peptide in urea solution. Our simulations suggest that urea denatures proteins by preferentially forming hydrogen bonds to the peptide backbone, reducing the barrier for exposing protein residues to the solvent, and reaching the unfolded state. Copyright 2003 Wiley Periodicals, Inc. Biopolymers: 359-369, 2003

The complex nature of calcium cation interactions with phospholipid bilayers

NASA Astrophysics Data System (ADS)

Melcrová, Adéla; Pokorna, Sarka; Pullanchery, Saranya; Kohagen, Miriam; Jurkiewicz, Piotr; Hof, Martin; Jungwirth, Pavel; Cremer, Paul S.; Cwiklik, Lukasz

2016-12-01

Understanding interactions of calcium with lipid membranes at the molecular level is of great importance in light of their involvement in calcium signaling, association of proteins with cellular membranes, and membrane fusion. We quantify these interactions in detail by employing a combination of spectroscopic methods with atomistic molecular dynamics simulations. Namely, time-resolved fluorescent spectroscopy of lipid vesicles and vibrational sum frequency spectroscopy of lipid monolayers are used to characterize local binding sites of calcium in zwitterionic and anionic model lipid assemblies, while dynamic light scattering and zeta potential measurements are employed for macroscopic characterization of lipid vesicles in calcium-containing environments. To gain additional atomic-level information, the experiments are complemented by molecular simulations that utilize an accurate force field for calcium ions with scaled charges effectively accounting for electronic polarization effects. We demonstrate that lipid membranes have substantial calcium-binding capacity, with several types of binding sites present. Significantly, the binding mode depends on calcium concentration with important implications for calcium buffering, synaptic plasticity, and protein-membrane association.

Quantifying climate feedbacks in polar regions.

PubMed

Goosse, Hugues; Kay, Jennifer E; Armour, Kyle C; Bodas-Salcedo, Alejandro; Chepfer, Helene; Docquier, David; Jonko, Alexandra; Kushner, Paul J; Lecomte, Olivier; Massonnet, François; Park, Hyo-Seok; Pithan, Felix; Svensson, Gunilla; Vancoppenolle, Martin

2018-05-15

The concept of feedback is key in assessing whether a perturbation to a system is amplified or damped by mechanisms internal to the system. In polar regions, climate dynamics are controlled by both radiative and non-radiative interactions between the atmosphere, ocean, sea ice, ice sheets and land surfaces. Precisely quantifying polar feedbacks is required for a process-oriented evaluation of climate models, a clear understanding of the processes responsible for polar climate changes, and a reduction in uncertainty associated with model projections. This quantification can be performed using a simple and consistent approach that is valid for a wide range of feedbacks, offering the opportunity for more systematic feedback analyses and a better understanding of polar climate changes.

Quantification of cardiorespiratory interactions based on joint symbolic dynamics.

PubMed

Kabir, Muammar M; Saint, David A; Nalivaiko, Eugene; Abbott, Derek; Voss, Andreas; Baumert, Mathias

2011-10-01

Cardiac and respiratory rhythms are highly nonlinear and nonstationary. As a result traditional time-domain techniques are often inadequate to characterize their complex dynamics. In this article, we introduce a novel technique to investigate the interactions between R-R intervals and respiratory phases based on their joint symbolic dynamics. To evaluate the technique, electrocardiograms (ECG) and respiratory signals were recorded in 13 healthy subjects in different body postures during spontaneous and controlled breathing. Herein, the R-R time series were extracted from ECG and respiratory phases were obtained from abdomen impedance belts using the Hilbert transform. Both time series were transformed into ternary symbol vectors based on the changes between two successive R-R intervals or respiratory phases. Subsequently, words of different symbol lengths were formed and the correspondence between the two series of words was determined to quantify the interaction between cardiac and respiratory cycles. To validate our results, respiratory sinus arrhythmia (RSA) was further studied using the phase-averaged characterization of the RSA pattern. The percentage of similarity of the sequence of symbols, between the respective words of the two series determined by joint symbolic dynamics, was significantly reduced in the upright position compared to the supine position (26.4 ± 4.7 vs. 20.5 ± 5.4%, p < 0.01). Similarly, RSA was also reduced during upright posture, but the difference was less significant (0.11 ± 0.02 vs. 0.08 ± 0.01 s, p < 0.05). In conclusion, joint symbolic dynamics provides a new efficient technique for the analysis of cardiorespiratory interaction that is highly sensitive to the effects of orthostatic challenge.

Controlling the influence of elastic eigenmodes on nanomagnet dynamics through pattern geometry

NASA Astrophysics Data System (ADS)

Berk, C.; Yahagi, Y.; Dhuey, S.; Cabrini, S.; Schmidt, H.

2017-03-01

The effect of the nanoscale array geometry on the interaction between optically generated surface acoustic waves (SAWs) and nanomagnet dynamics is investigated using Time-Resolved Magneto-Optical Kerr Effect Microscopy (TR-MOKE). It is demonstrated that altering the nanomagnet geometry from a periodic to a randomized aperiodic pattern effectively removes the magneto-elastic effect of SAWs on the magnetization dynamics. The efficiency of this method depends on the extent of any residual spatial correlations and is quantified by spatial Fourier analysis of the two structures. Randomization allows observation and extraction of intrinsic magnetic parameters such as spin wave frequencies and damping to be resolvable using all-optical methods, enabling the conclusion that the fabrication process does not affect the damping.

Dynamics of microtubules: highlights of recent computational and experimental investigations

NASA Astrophysics Data System (ADS)

Barsegov, Valeri; Ross, Jennifer L.; Dima, Ruxandra I.

2017-11-01

Microtubules are found in most eukaryotic cells, with homologs in eubacteria and archea, and they have functional roles in mitosis, cell motility, intracellular transport, and the maintenance of cell shape. Numerous efforts have been expended over the last two decades to characterize the interactions between microtubules and the wide variety of microtubule associated proteins that control their dynamic behavior in cells resulting in microtubules being assembled and disassembled where and when they are required by the cell. We present the main findings regarding microtubule polymerization and depolymerization and review recent work about the molecular motors that modulate microtubule dynamics by inducing either microtubule depolymerization or severing. We also discuss the main experimental and computational approaches used to quantify the thermodynamics and mechanics of microtubule filaments.

Direct Numerical Simulations of Small-Scale Gravity Wave Instability Dynamics in Variable Stratification and Shear

NASA Astrophysics Data System (ADS)

Mixa, T.; Fritts, D. C.; Laughman, B.; Wang, L.; Kantha, L. H.

2015-12-01

Multiple observations provide compelling evidence that gravity wave dissipation events often occur in multi-scale environments having highly-structured wind and stability profiles extending from the stable boundary layer into the mesosphere and lower thermosphere. Such events tend to be highly localized and thus yield local energy and momentum deposition and efficient secondary gravity wave generation expected to have strong influences at higher altitudes [e.g., Fritts et al., 2013; Baumgarten and Fritts, 2014]. Lidars, radars, and airglow imagers typically cannot achieve the spatial resolution needed to fully quantify these small-scale instability dynamics. Hence, we employ high-resolution modeling to explore these dynamics in representative environments. Specifically, we describe numerical studies of gravity wave packets impinging on a sheet of high stratification and shear and the resulting instabilities and impacts on the gravity wave amplitude and momentum flux for various flow and gravity wave parameters. References: Baumgarten, Gerd, and David C. Fritts (2014). Quantifying Kelvin-Helmholtz instability dynamics observed in noctilucent clouds: 1. Methods and observations. Journal of Geophysical Research: Atmospheres, 119.15, 9324-9337. Fritts, D. C., Wang, L., & Werne, J. A. (2013). Gravity wave-fine structure interactions. Part I: Influences of fine structure form and orientation on flow evolution and instability. Journal of the Atmospheric Sciences, 70(12), 3710-3734.

Cooperativity of self-organized Brownian motors pulling on soft cargoes.

PubMed

Orlandi, Javier G; Blanch-Mercader, Carles; Brugués, Jan; Casademunt, Jaume

2010-12-01

We study the cooperative dynamics of Brownian motors moving along a one-dimensional track when an external load is applied to the leading motor, mimicking molecular motors pulling on membrane-bound cargoes in intracellular traffic. Due to the asymmetric loading, self-organized motor clusters form spontaneously. We model the motors with a two-state noise-driven ratchet formulation and study analytically and numerically the collective velocity-force and efficiency-force curves resulting from mutual interactions, mostly hard-core repulsion and weak (nonbinding) attraction. We analyze different parameter regimes including the limits of weak noise, mean-field behavior, rigid coupling, and large numbers of motors, for the different interactions. We present a general framework to classify and quantify cooperativity. We show that asymmetric loading leads generically to enhanced cooperativity beyond the simple superposition of the effects of individual motors. For weakly attracting interactions, the cooperativity is mostly enhanced, including highly coordinated motion of motors and complex nonmonotonic velocity-force curves, leading to self-regulated clusters. The dynamical scenario is enriched by resonances associated to commensurability of different length scales. Large clusters exhibit synchronized dynamics and bidirectional motion. Biological implications are discussed.

Cooperativity of self-organized Brownian motors pulling on soft cargoes

NASA Astrophysics Data System (ADS)

Orlandi, Javier G.; Blanch-Mercader, Carles; Brugués, Jan; Casademunt, Jaume

2010-12-01

We study the cooperative dynamics of Brownian motors moving along a one-dimensional track when an external load is applied to the leading motor, mimicking molecular motors pulling on membrane-bound cargoes in intracellular traffic. Due to the asymmetric loading, self-organized motor clusters form spontaneously. We model the motors with a two-state noise-driven ratchet formulation and study analytically and numerically the collective velocity-force and efficiency-force curves resulting from mutual interactions, mostly hard-core repulsion and weak (nonbinding) attraction. We analyze different parameter regimes including the limits of weak noise, mean-field behavior, rigid coupling, and large numbers of motors, for the different interactions. We present a general framework to classify and quantify cooperativity. We show that asymmetric loading leads generically to enhanced cooperativity beyond the simple superposition of the effects of individual motors. For weakly attracting interactions, the cooperativity is mostly enhanced, including highly coordinated motion of motors and complex nonmonotonic velocity-force curves, leading to self-regulated clusters. The dynamical scenario is enriched by resonances associated to commensurability of different length scales. Large clusters exhibit synchronized dynamics and bidirectional motion. Biological implications are discussed.

A Statistical Physics Characterization of the Complex Systems Dynamics: Quantifying Complexity from Spatio-Temporal Interactions

PubMed Central

Koorehdavoudi, Hana; Bogdan, Paul

2016-01-01

Biological systems are frequently categorized as complex systems due to their capabilities of generating spatio-temporal structures from apparent random decisions. In spite of research on analyzing biological systems, we lack a quantifiable framework for measuring their complexity. To fill this gap, in this paper, we develop a new paradigm to study a collective group of N agents moving and interacting in a three-dimensional space. Our paradigm helps to identify the spatio-temporal states of the motion of the group and their associated transition probabilities. This framework enables the estimation of the free energy landscape corresponding to the identified states. Based on the energy landscape, we quantify missing information, emergence, self-organization and complexity for a collective motion. We show that the collective motion of the group of agents evolves to reach the most probable state with relatively lowest energy level and lowest missing information compared to other possible states. Our analysis demonstrates that the natural group of animals exhibit a higher degree of emergence, self-organization and complexity over time. Consequently, this algorithm can be integrated into new frameworks to engineer collective motions to achieve certain degrees of emergence, self-organization and complexity. PMID:27297496

A Statistical Physics Characterization of the Complex Systems Dynamics: Quantifying Complexity from Spatio-Temporal Interactions

NASA Astrophysics Data System (ADS)

Koorehdavoudi, Hana; Bogdan, Paul

2016-06-01

Biological systems are frequently categorized as complex systems due to their capabilities of generating spatio-temporal structures from apparent random decisions. In spite of research on analyzing biological systems, we lack a quantifiable framework for measuring their complexity. To fill this gap, in this paper, we develop a new paradigm to study a collective group of N agents moving and interacting in a three-dimensional space. Our paradigm helps to identify the spatio-temporal states of the motion of the group and their associated transition probabilities. This framework enables the estimation of the free energy landscape corresponding to the identified states. Based on the energy landscape, we quantify missing information, emergence, self-organization and complexity for a collective motion. We show that the collective motion of the group of agents evolves to reach the most probable state with relatively lowest energy level and lowest missing information compared to other possible states. Our analysis demonstrates that the natural group of animals exhibit a higher degree of emergence, self-organization and complexity over time. Consequently, this algorithm can be integrated into new frameworks to engineer collective motions to achieve certain degrees of emergence, self-organization and complexity.

Noise Response Data Reveal Novel Controllability Gramian for Nonlinear Network Dynamics

PubMed Central

Kashima, Kenji

2016-01-01

Control of nonlinear large-scale dynamical networks, e.g., collective behavior of agents interacting via a scale-free connection topology, is a central problem in many scientific and engineering fields. For the linear version of this problem, the so-called controllability Gramian has played an important role to quantify how effectively the dynamical states are reachable by a suitable driving input. In this paper, we first extend the notion of the controllability Gramian to nonlinear dynamics in terms of the Gibbs distribution. Next, we show that, when the networks are open to environmental noise, the newly defined Gramian is equal to the covariance matrix associated with randomly excited, but uncontrolled, dynamical state trajectories. This fact theoretically justifies a simple Monte Carlo simulation that can extract effectively controllable subdynamics in nonlinear complex networks. In addition, the result provides a novel insight into the relationship between controllability and statistical mechanics. PMID:27264780

Dynamic behaviour of a rolling tyre: Experimental and numerical analyses

NASA Astrophysics Data System (ADS)

Gonzalez Diaz, Cristobal; Kindt, Peter; Middelberg, Jason; Vercammen, Stijn; Thiry, Christophe; Close, Roland; Leyssens, Jan

2016-03-01

Based on the results of experimental and numerical analyses, the effect of rotation on the tyre dynamic behaviour is investigated. Better understanding of these effects will further improve the ability to control and optimize the noise and vibrations that result from the interaction between the road surface and the rolling tyre. Therefore, more understanding in the complex tyre dynamic properties will contribute to develop tyre design strategies to lower the tyre/road noise while less affecting other tyre performances. The presented work is performed in the framework of the European industry-academia project TIRE-DYN, with partners Goodyear, Katholieke Universiteit Leuven and LMS International. The effect of rotation on the tyre dynamic behaviour is quantified for different operating conditions of the tyre, such as load, air pressure and rotation speed. By means of experimental and numerical analyses, the effects of rotation on the tyre dynamic behaviour are studied.

Quantifying Hydro-biogeochemical Model Sensitivity in Assessment of Climate Change Effect on Hyporheic Zone Processes

NASA Astrophysics Data System (ADS)

Song, X.; Chen, X.; Dai, H.; Hammond, G. E.; Song, H. S.; Stegen, J.

2016-12-01

The hyporheic zone is an active region for biogeochemical processes such as carbon and nitrogen cycling, where the groundwater and surface water mix and interact with each other with distinct biogeochemical and thermal properties. The biogeochemical dynamics within the hyporheic zone are driven by both river water and groundwater hydraulic dynamics, which are directly affected by climate change scenarios. Besides that, the hydraulic and thermal properties of local sediments and microbial and chemical processes also play important roles in biogeochemical dynamics. Thus for a comprehensive understanding of the biogeochemical processes in the hyporheic zone, a coupled thermo-hydro-biogeochemical model is needed. As multiple uncertainty sources are involved in the integrated model, it is important to identify its key modules/parameters through sensitivity analysis. In this study, we develop a 2D cross-section model in the hyporheic zone at the DOE Hanford site adjacent to Columbia River and use this model to quantify module and parametric sensitivity on assessment of climate change. To achieve this purpose, We 1) develop a facies-based groundwater flow and heat transfer model that incorporates facies geometry and heterogeneity characterized from a field data set, 2) derive multiple reaction networks/pathways from batch experiments with in-situ samples and integrate temperate dependent reactive transport modules to the flow model, 3) assign multiple climate change scenarios to the coupled model by analyzing historical river stage data, 4) apply a variance-based global sensitivity analysis to quantify scenario/module/parameter uncertainty in hierarchy level. The objectives of the research include: 1) identifing the key control factors of the coupled thermo-hydro-biogeochemical model in the assessment of climate change, and 2) quantify the carbon consumption in different climate change scenarios in the hyporheic zone.

Multidimensional Modeling of Coronal Rain Dynamics

NASA Astrophysics Data System (ADS)

Fang, X.; Xia, C.; Keppens, R.

2013-07-01

We present the first multidimensional, magnetohydrodynamic simulations that capture the initial formation and long-term sustainment of the enigmatic coronal rain phenomenon. We demonstrate how thermal instability can induce a spectacular display of in situ forming blob-like condensations which then start their intimate ballet on top of initially linear force-free arcades. Our magnetic arcades host a chromospheric, transition region, and coronal plasma. Following coronal rain dynamics for over 80 minutes of physical time, we collect enough statistics to quantify blob widths, lengths, velocity distributions, and other characteristics which directly match modern observational knowledge. Our virtual coronal rain displays the deformation of blobs into V-shaped features, interactions of blobs due to mostly pressure-mediated levitations, and gives the first views of blobs that evaporate in situ or are siphoned over the apex of the background arcade. Our simulations pave the way for systematic surveys of coronal rain showers in true multidimensional settings to connect parameterized heating prescriptions with rain statistics, ultimately allowing us to quantify the coronal heating input.

Lipid packing determines protein-membrane interactions: challenges for apolipoprotein A–I and High Density Lipoproteins

PubMed Central

Sánchez, Susana A.; Tricerri, M. Alejandra; Ossato, Giulia; Gratton, Enrico

2010-01-01

Summary Protein and protein-lipid interactions, with and within specific areas in the cell membrane, are critical in order to modulate the cell signaling events required to maintain cell functions and viability. Biological bilayers are complex, dynamic platforms, and thus in vivo observations usually need to be preceded by studies on model systems that simplify and discriminate the different factors involved in lipid-protein interactions. Fluorescence microscopy studies using giant unilamellar vesicles (GUVs) as membrane model systems provide a unique methodology to quantify protein binding, interaction and lipid solubilization in artificial bilayers. The large size of lipid domains obtainable on GUVs, together with fluorescence microscopy techniques, provides the possibility to localize and quantify molecular interactions. FCS (Fluorescence Correlation Spectroscopy) can be performed using the GUV model to extract information on mobility and concentration. Two-photon Laurdan GP (Generalized Polarization) reports on local changes in membrane water content (related to membrane fluidity) due to protein binding or lipid removal from a given lipid domain. In this review, we summarize the experimental microscopy methods used to study the interaction of human apolipoprotein A–I (apoA-I) in lipid-free and lipid-bound conformations with bilayers and natural membranes. Results described here help us to understand cholesterol homeostasis, and offer a methodological design suited to different biological systems. PMID:20347719

Mass Spectrometry Analysis of Spatial Protein Networks by Colocalization Analysis (COLA).

PubMed

Mardakheh, Faraz K

2017-01-01

A major challenge in systems biology is comprehensive mapping of protein interaction networks. Crucially, such interactions are often dynamic in nature, necessitating methods that can rapidly mine the interactome across varied conditions and treatments to reveal change in the interaction networks. Recently, we described a fast mass spectrometry-based method to reveal functional interactions in mammalian cells on a global scale, by revealing spatial colocalizations between proteins (COLA) (Mardakheh et al., Mol Biosyst 13:92-105, 2017). As protein localization and function are inherently linked, significant colocalization between two proteins is a strong indication for their functional interaction. COLA uses rapid complete subcellular fractionation, coupled with quantitative proteomics to generate a subcellular localization profile for each protein quantified by the mass spectrometer. Robust clustering is then applied to reveal significant similarities in protein localization profiles, indicative of colocalization.

Multiscale contact mechanics model for RF-MEMS switches with quantified uncertainties

NASA Astrophysics Data System (ADS)

Kim, Hojin; Huda Shaik, Nurul; Xu, Xin; Raman, Arvind; Strachan, Alejandro

2013-12-01

We introduce a multiscale model for contact mechanics between rough surfaces and apply it to characterize the force-displacement relationship for a metal-dielectric contact relevant for radio frequency micro-electromechanicl system (MEMS) switches. We propose a mesoscale model to describe the history-dependent force-displacement relationships in terms of the surface roughness, the long-range attractive interaction between the two surfaces, and the repulsive interaction between contacting asperities (including elastic and plastic deformation). The inputs to this model are the experimentally determined surface topography and the Hamaker constant as well as the mechanical response of individual asperities obtained from density functional theory calculations and large-scale molecular dynamics simulations. The model captures non-trivial processes including the hysteresis during loading and unloading due to plastic deformation, yet it is computationally efficient enough to enable extensive uncertainty quantification and sensitivity analysis. We quantify how uncertainties and variability in the input parameters, both experimental and theoretical, affect the force-displacement curves during approach and retraction. In addition, a sensitivity analysis quantifies the relative importance of the various input quantities for the prediction of force-displacement during contact closing and opening. The resulting force-displacement curves with quantified uncertainties can be directly used in device-level simulations of micro-switches and enable the incorporation of atomic and mesoscale phenomena in predictive device-scale simulations.

Capturing multi-stage fuzzy uncertainties in hybrid system dynamics and agent-based models for enhancing policy implementation in health systems research.

PubMed

Liu, Shiyong; Triantis, Konstantinos P; Zhao, Li; Wang, Youfa

2018-01-01

In practical research, it was found that most people made health-related decisions not based on numerical data but on perceptions. Examples include the perceptions and their corresponding linguistic values of health risks such as, smoking, syringe sharing, eating energy-dense food, drinking sugar-sweetened beverages etc. For the sake of understanding the mechanisms that affect the implementations of health-related interventions, we employ fuzzy variables to quantify linguistic variable in healthcare modeling where we employ an integrated system dynamics and agent-based model. In a nonlinear causal-driven simulation environment driven by feedback loops, we mathematically demonstrate how interventions at an aggregate level affect the dynamics of linguistic variables that are captured by fuzzy agents and how interactions among fuzzy agents, at the same time, affect the formation of different clusters(groups) that are targeted by specific interventions. In this paper, we provide an innovative framework to capture multi-stage fuzzy uncertainties manifested among interacting heterogeneous agents (individuals) and intervention decisions that affect homogeneous agents (groups of individuals) in a hybrid model that combines an agent-based simulation model (ABM) and a system dynamics models (SDM). Having built the platform to incorporate high-dimension data in a hybrid ABM/SDM model, this paper demonstrates how one can obtain the state variable behaviors in the SDM and the corresponding values of linguistic variables in the ABM. This research provides a way to incorporate high-dimension data in a hybrid ABM/SDM model. This research not only enriches the application of fuzzy set theory by capturing the dynamics of variables associated with interacting fuzzy agents that lead to aggregate behaviors but also informs implementation research by enabling the incorporation of linguistic variables at both individual and institutional levels, which makes unstructured linguistic data meaningful and quantifiable in a simulation environment. This research can help practitioners and decision makers to gain better understanding on the dynamics and complexities of precision intervention in healthcare. It can aid the improvement of the optimal allocation of resources for targeted group (s) and the achievement of maximum utility. As this technology becomes more mature, one can design policy flight simulators by which policy/intervention designers can test a variety of assumptions when they evaluate different alternatives interventions.

Modeling Forest Composition and Carbon Dynamics Under Projected Climate-Fire Interactions in the Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Liang, S.; Hurteau, M. D.; Westerling, A. L.

2014-12-01

The Sierra Nevada Mountains are occupied by a diversity of forest types that sort by elevation. The interaction of changing climate and altered disturbance regimes (e.g. fire) has the potential to drive changes in forest distribution as a function of species-specific response. Quantifying the effects of these drivers on species distributions and productivity under future climate-fire interactions is necessary for informing mitigation and adaptation efforts. In this study, we assimilated forest inventory and soil survey data and species life history traits into a landscape model, LANDIS-II, to quantify the response of forest dynamics to the interaction of climate change and large wildfire frequency in the Sierra Nevada. We ran 100-year simulations forced with historical climate and climate projections from three models (GFDL, CNRM and CCSM3) driven by the A2 emission scenario. We found that non-growing season NPP is greatly enhanced by 15%-150%, depending on the specific climate projection. The greatest increase occurs in subalpine forests. Species-specific response varied as a function of life history characteristics. The distribution of drought and fire-tolerant species, such as ponderosa pine, expanded by 7.3-9.6% from initial conditions, while drought and fire-intolerant species, such as white fir, showed little change in the absence of fire. Changes in wildfire size and frequency influence species distributions by altering the successional stage of burned patches. The range of responses to different climate models demonstrates the sensitivity of these forests to climate variability. The scale of climate projections relative to the scale of forest simulations presents a source of uncertainty, particularly at the ecotone between forest types and for identifying topographically mediated climate refugia. Improving simulations will likely require higher resolution climate projections.

A family of interaction-adjusted indices of community similarity.

PubMed

Schmidt, Thomas Sebastian Benedikt; Matias Rodrigues, João Frederico; von Mering, Christian

2017-03-01

Interactions between taxa are essential drivers of ecological community structure and dynamics, but they are not taken into account by traditional indices of β diversity. In this study, we propose a novel family of indices that quantify community similarity in the context of taxa interaction networks. Using publicly available datasets, we assessed the performance of two specific indices that are Taxa INteraction-Adjusted (TINA, based on taxa co-occurrence networks), and Phylogenetic INteraction-Adjusted (PINA, based on phylogenetic similarities). TINA and PINA outperformed traditional indices when partitioning human-associated microbial communities according to habitat, even for extremely downsampled datasets, and when organising ocean micro-eukaryotic plankton diversity according to geographical and physicochemical gradients. We argue that interaction-adjusted indices capture novel aspects of diversity outside the scope of traditional approaches, highlighting the biological significance of ecological association networks in the interpretation of community similarity.

A family of interaction-adjusted indices of community similarity

PubMed Central

Schmidt, Thomas Sebastian Benedikt; Matias Rodrigues, João Frederico; von Mering, Christian

2017-01-01

Interactions between taxa are essential drivers of ecological community structure and dynamics, but they are not taken into account by traditional indices of β diversity. In this study, we propose a novel family of indices that quantify community similarity in the context of taxa interaction networks. Using publicly available datasets, we assessed the performance of two specific indices that are Taxa INteraction-Adjusted (TINA, based on taxa co-occurrence networks), and Phylogenetic INteraction-Adjusted (PINA, based on phylogenetic similarities). TINA and PINA outperformed traditional indices when partitioning human-associated microbial communities according to habitat, even for extremely downsampled datasets, and when organising ocean micro-eukaryotic plankton diversity according to geographical and physicochemical gradients. We argue that interaction-adjusted indices capture novel aspects of diversity outside the scope of traditional approaches, highlighting the biological significance of ecological association networks in the interpretation of community similarity. PMID:27935587

Dynamics differentiate between active and inactive inteins

PubMed Central

Cronin, Melissa; Coolbaugh, Michael J; Nellis, David; Zhu, Jianwei; Wood, David W.; Nussinov, Ruth; Ma, Buyong

2014-01-01

The balance between stability and dynamics for active enzymes can be somewhat quantified by studies of intein splicing and cleaving reactions. Inteins catalyze the ligation of flanking host exteins while excising themselves. The potential for applications led to engineering of a mini-intein splicing domain, where the homing endonuclease domain of the Mycobacterium tuberculosis RecA (Mtu recA) intein was removed. The remaining domains were linked by several short peptides, but splicing activity in all was substantially lower than the full-length intein. Native splicing activity was restored in some cases by a V67L mutation. Using computations and experiments, we examine the impact of this mutation on the stability and conformational dynamics of the mini-intein splicing domain. Molecular dynamics simulations were used to delineate the factors that determine the active state, including the V67L mini-intein mutant, and peptide linker. We found that (1) the V67L mutation lowers the global fluctuations in all modeled mini-inteins, stabilizing the mini-intein constructs; (2) the connecting linker length affects intein dynamics; and (3) the flexibilities of the linker and intein core are higher in the active structure. We have observed that the interaction of the linker region and a turn region around residues 35-41 provides the pathway for the allostery interaction. Our experiments reveal that intein catalysis is characterized by non-linear Arrhenius plot, confirming the significant contribution of protein conformational dynamics to intein function. We conclude that while the V67L mutation stabilizes the global structure, cooperative dynamics of all intein regions appear more important for intein function than high stability. Our studies suggest that effectively quenching the conformational dynamics of an intein through engineered allosteric interactions could deactivate intein splicing or cleaving. PMID:25087201

Effects of communication burstiness on consensus formation and tipping points in social dynamics

NASA Astrophysics Data System (ADS)

Doyle, C.; Szymanski, B. K.; Korniss, G.

2017-06-01

Current models for opinion dynamics typically utilize a Poisson process for speaker selection, making the waiting time between events exponentially distributed. Human interaction tends to be bursty though, having higher probabilities of either extremely short waiting times or long periods of silence. To quantify the burstiness effects on the dynamics of social models, we place in competition two groups exhibiting different speakers' waiting-time distributions. These competitions are implemented in the binary naming game and show that the relevant aspect of the waiting-time distribution is the density of the head rather than that of the tail. We show that even with identical mean waiting times, a group with a higher density of short waiting times is favored in competition over the other group. This effect remains in the presence of nodes holding a single opinion that never changes, as the fraction of such committed individuals necessary for achieving consensus decreases dramatically when they have a higher head density than the holders of the competing opinion. Finally, to quantify differences in burstiness, we introduce the expected number of small-time activations and use it to characterize the early-time regime of the system.

Modeling Multi-Agent Self-Organization through the Lens of Higher Order Attractor Dynamics.

PubMed

Butner, Jonathan E; Wiltshire, Travis J; Munion, A K

2017-01-01

Social interaction occurs across many time scales and varying numbers of agents; from one-on-one to large-scale coordination in organizations, crowds, cities, and colonies. These contexts, are characterized by emergent self-organization that implies higher order coordinated patterns occurring over time that are not due to the actions of any particular agents, but rather due to the collective ordering that occurs from the interactions of the agents. Extant research to understand these social coordination dynamics (SCD) has primarily examined dyadic contexts performing rhythmic tasks. To advance this area of study, we elaborate on attractor dynamics, our ability to depict them visually, and quantitatively model them. Primarily, we combine difference/differential equation modeling with mixture modeling as a way to infer the underlying topological features of the data, which can be described in terms of attractor dynamic patterns. The advantage of this approach is that we are able to quantify the self-organized dynamics that agents exhibit, link these dynamics back to activity from individual agents, and relate it to other variables central to understanding the coordinative functionality of a system's behavior. We present four examples that differ in the number of variables used to depict the attractor dynamics (1, 2, and 6) and range from simulated to non-simulated data sources. We demonstrate that this is a flexible method that advances scientific study of SCD in a variety of multi-agent systems.

Genomic investigations of evolutionary dynamics and epistasis in microbial evolution experiments.

PubMed

Jerison, Elizabeth R; Desai, Michael M

2015-12-01

Microbial evolution experiments enable us to watch adaptation in real time, and to quantify the repeatability and predictability of evolution by comparing identical replicate populations. Further, we can resurrect ancestral types to examine changes over evolutionary time. Until recently, experimental evolution has been limited to measuring phenotypic changes, or to tracking a few genetic markers over time. However, recent advances in sequencing technology now make it possible to extensively sequence clones or whole-population samples from microbial evolution experiments. Here, we review recent work exploiting these techniques to understand the genomic basis of evolutionary change in experimental systems. We first focus on studies that analyze the dynamics of genome evolution in microbial systems. We then survey work that uses observations of sequence evolution to infer aspects of the underlying fitness landscape, concentrating on the epistatic interactions between mutations and the constraints these interactions impose on adaptation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Pattern Selection and Super-Patterns in Opinion Dynamics

NASA Astrophysics Data System (ADS)

Ben-Naim, Eli; Scheel, Arnd

We study pattern formation in the bounded confidence model of opinion dynamics. In this random process, opinion is quantified by a single variable. Two agents may interact and reach a fair compromise, but only if their difference of opinion falls below a fixed threshold. Starting from a uniform distribution of opinions with compact support, a traveling wave forms and it propagates from the domain boundary into the unstable uniform state. Consequently, the system reaches a steady state with isolated clusters that are separated by distance larger than the interaction range. These clusters form a quasi-periodic pattern where the sizes of the clusters and the separations between them are nearly constant. We obtain analytically the average separation between clusters L. Interestingly, there are also very small quasi-periodic modulations in the size of the clusters. The spatial periods of these modulations are a series of integers that follow from the continued-fraction representation of the irrational average separation L.

Phase dynamics of coupled oscillators reconstructed from data

NASA Astrophysics Data System (ADS)

Rosenblum, Michael; Kralemann, Bjoern; Pikovsky, Arkady

2013-03-01

We present a technique for invariant reconstruction of the phase dynamics equations for coupled oscillators from data. The invariant description is achieved by means of a transformation of phase estimates (protophases) obtained from general scalar observables to genuine phases. Staring from the bivariate data, we obtain the coupling functions in terms of these phases. We discuss the importance of the protophase-to-phase transformation for characterization of strength and directionality of interaction. To illustrate the technique we analyse the cardio-respiratory interaction on healthy humans. Our invariant approach is confirmed by high similarity of the coupling functions obtained from different observables of the cardiac system. Next, we generalize the technique to cover the case of small networks of coupled periodic units. We use the partial norms of the reconstructed coupling functions to quantify directed coupling between the oscillators. We illustrate the method by different network motifs for three coupled oscillators. We also discuss nonlinear effects in coupling.

Diagnosis of middle atmosphere chemistry-dynamics interactions

NASA Astrophysics Data System (ADS)

Zhu, X.; Swartz, W. H.; Garcia, R. R.; Chartier, A.; Yee, J. H.; Yue, J.

2017-12-01

We apply the recently developed middle atmosphere climate feedback-response analysis method (MCFRAM) to diagnosing the temperature variations associated with chemistry-dynamics interactions in the middle atmosphere. By using output fields from the Whole Atmosphere Community Climate Model (WACCM) coupled with the measurements, we identify and isolate the distinctive characteristics of different components in the observed temperature variations. Both the temperature trends associated with the anthropogenic forcing and temperature changes associated with natural and internal feedback processes are quantified based on MCFRAM defined partial temperature changes corresponding to localized radiative heating, non-localized chemical heating, eddy transport, and transport by the mean meridional circulation of energy and chemical species. In addition, the temperature responses to variations of CO2, O3, and solar flux have distinctly different spatial structures that can be systematically categorized by the eigenmodes of the generalized damping matrix derived from MCFRAM.

Complexity of cardiac signals for predicting changes in alpha-waves after stress in patients undergoing cardiac catheterization

NASA Astrophysics Data System (ADS)

Chiu, Hung-Chih; Lin, Yen-Hung; Lo, Men-Tzung; Tang, Sung-Chun; Wang, Tzung-Dau; Lu, Hung-Chun; Ho, Yi-Lwun; Ma, Hsi-Pin; Peng, Chung-Kang

2015-08-01

The hierarchical interaction between electrical signals of the brain and heart is not fully understood. We hypothesized that the complexity of cardiac electrical activity can be used to predict changes in encephalic electricity after stress. Most methods for analyzing the interaction between the heart rate variability (HRV) and electroencephalography (EEG) require a computation-intensive mathematical model. To overcome these limitations and increase the predictive accuracy of human relaxing states, we developed a method to test our hypothesis. In addition to routine linear analysis, multiscale entropy and detrended fluctuation analysis of the HRV were used to quantify nonstationary and nonlinear dynamic changes in the heart rate time series. Short-time Fourier transform was applied to quantify the power of EEG. The clinical, HRV, and EEG parameters of postcatheterization EEG alpha waves were analyzed using change-score analysis and generalized additive models. In conclusion, the complexity of cardiac electrical signals can be used to predict EEG changes after stress.

General Method to Determine the Flux of Charged Molecules through Nanopores Applied to β-Lactamase Inhibitors and OmpF.

PubMed

Ghai, Ishan; Pira, Alessandro; Scorciapino, Mariano Andrea; Bodrenko, Igor; Benier, Lorraine; Ceccarelli, Matteo; Winterhalter, Mathias; Wagner, Richard

2017-03-16

A major challenge in the discovery of the new antibiotics against Gram-negative bacteria is to achieve sufficiently fast permeation in order to avoid high doses causing toxic side effects. So far, suitable assays for quantifying the uptake of charged antibiotics into bacteria are lacking. We apply an electrophysiological zero-current assay using concentration gradients of β-lactamase inhibitors combined with single-channel conductance to quantify their flux rates through OmpF. Molecular dynamic simulations provide in addition details on the interactions between the nanopore wall and the charged solutes. In particular, the interaction barrier for three β-lactamase inhibitors is surprisingly as low as 3-5 kcal/mol and only slightly above the diffusion barrier of ions such as chloride. Within our macroscopic constant field model, we determine that at a zero-membrane potential a concentration gradient of 10 μM of avibactam, sulbactam, or tazobactam can create flux rates of roughly 620 molecules/s per OmpF trimer.

Complexity of cardiac signals for predicting changes in alpha-waves after stress in patients undergoing cardiac catheterization

PubMed Central

Chiu, Hung-Chih; Lin, Yen-Hung; Lo, Men-Tzung; Tang, Sung-Chun; Wang, Tzung-Dau; Lu, Hung-Chun; Ho, Yi-Lwun; Ma, Hsi-Pin; Peng, Chung-Kang

2015-01-01

The hierarchical interaction between electrical signals of the brain and heart is not fully understood. We hypothesized that the complexity of cardiac electrical activity can be used to predict changes in encephalic electricity after stress. Most methods for analyzing the interaction between the heart rate variability (HRV) and electroencephalography (EEG) require a computation-intensive mathematical model. To overcome these limitations and increase the predictive accuracy of human relaxing states, we developed a method to test our hypothesis. In addition to routine linear analysis, multiscale entropy and detrended fluctuation analysis of the HRV were used to quantify nonstationary and nonlinear dynamic changes in the heart rate time series. Short-time Fourier transform was applied to quantify the power of EEG. The clinical, HRV, and EEG parameters of postcatheterization EEG alpha waves were analyzed using change-score analysis and generalized additive models. In conclusion, the complexity of cardiac electrical signals can be used to predict EEG changes after stress. PMID:26286628

Simultaneously measuring multiple protein interactions and their correlations in a cell by Protein-interactome Footprinting

PubMed Central

Luo, Si-Wei; Liang, Zhi; Wu, Jia-Rui

2017-01-01

Quantitatively detecting correlations of multiple protein-protein interactions (PPIs) in vivo is a big challenge. Here we introduce a novel method, termed Protein-interactome Footprinting (PiF), to simultaneously measure multiple PPIs in one cell. The principle of PiF is that each target physical PPI in the interactome is simultaneously transcoded into a specific DNA sequence based on dimerization of the target proteins fused with DNA-binding domains. The interaction intensity of each target protein is quantified as the copy number of the specific DNA sequences bound by each fusion protein dimers. Using PiF, we quantitatively reveal dynamic patterns of PPIs and their correlation network in E. coli two-component systems. PMID:28338015

Individual-Based Model of Microbial Life on Hydrated Rough Soil Surfaces

PubMed Central

Kim, Minsu; Or, Dani

2016-01-01

Microbial life in soil is perceived as one of the most interesting ecological systems, with microbial communities exhibiting remarkable adaptability to vast dynamic environmental conditions. At the same time, it is a notoriously challenging system to understand due to its complexity including physical, chemical, and biological factors in synchrony. This study presents a spatially-resolved model of microbial dynamics on idealised rough soil surfaces represented as patches with different (roughness) properties that preserve the salient hydration physics of real surfaces. Cell level microbial interactions are considered within an individual-based formulation including dispersion and various forms of trophic dependencies (competition, mutualism). The model provides new insights into mechanisms affecting microbial community dynamics and gives rise to spontaneous formation of microbial community spatial patterns. The framework is capable of representing many interacting species and provides diversity metrics reflecting surface conditions and their evolution over time. A key feature of the model is its spatial scalability that permits representation of microbial processes from cell-level (micro-metric scales) to soil representative volumes at sub-metre scales. Several illustrative examples of microbial trophic interactions and population dynamics highlight the potential of the proposed modelling framework to quantitatively study soil microbial processes. The model is highly applicable in a wide range spanning from quantifying spatial organisation of multiple species under various hydration conditions to predicting microbial diversity residing in different soils. PMID:26807803

The dynamics of emotions in online interaction

PubMed Central

Kappas, Arvid; Küster, Dennis

2016-01-01

We study the changes in emotional states induced by reading and participating in online discussions, empirically testing a computational model of online emotional interaction. Using principles of dynamical systems, we quantify changes in valence and arousal through subjective reports, as recorded in three independent studies including 207 participants (110 female). In the context of online discussions, the dynamics of valence and arousal is composed of two forces: an internal relaxation towards baseline values independent of the emotional charge of the discussion and a driving force of emotional states that depends on the content of the discussion. The dynamics of valence show the existence of positive and negative tendencies, while arousal increases when reading emotional content regardless of its polarity. The tendency of participants to take part in the discussion increases with positive arousal. When participating in an online discussion, the content of participants' expression depends on their valence, and their arousal significantly decreases afterwards as a regulation mechanism. We illustrate how these results allow the design of agent-based models to reproduce and analyse emotions in online communities. Our work empirically validates the microdynamics of a model of online collective emotions, bridging online data analysis with research in the laboratory. PMID:27853586

In-situ neutron imaging of hydrogenous fuels in combustion generated porous carbons under dynamic and steady state pressure conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ossler, Frederik; Santodonato, Louis J.; Bilheux, Hassina Z.

Here, we report results from experiments where we characterize the surface properties of soot particles interacting with high-pressure methane. We also found considerable differences in behavior of the soot material between static and dynamic pressure conditions that can be explained by multiscale correlations in the dynamics, from the micro to macro of the porous fractal-like carbon matrix. The measurements were possible utilizing cold neutron imaging of methane mixed with combustion generated carbon (soot) inside steel cells. The studies were performed under static and dynamic pressure conditions in the range 10-90 bar, and are of interest for applications of energy storagemore » of hydrogenous fuels. The very high cross sections for neutrons compared to hard X-ray photons, enabled us to find considerable amounts of native hydrogen in the soot and to see and quantify the presence of hydrogen atoms in the carbon soot matrix under different pressure conditions. Our work lays the base for more detailed in-situ investigations on the interaction of porous carbon materials with hydrogen in practical environments for hydrogen and methane storage.« less

In-situ neutron imaging of hydrogenous fuels in combustion generated porous carbons under dynamic and steady state pressure conditions

DOE PAGES

Ossler, Frederik; Santodonato, Louis J.; Bilheux, Hassina Z.

2017-02-12

Here, we report results from experiments where we characterize the surface properties of soot particles interacting with high-pressure methane. We also found considerable differences in behavior of the soot material between static and dynamic pressure conditions that can be explained by multiscale correlations in the dynamics, from the micro to macro of the porous fractal-like carbon matrix. The measurements were possible utilizing cold neutron imaging of methane mixed with combustion generated carbon (soot) inside steel cells. The studies were performed under static and dynamic pressure conditions in the range 10-90 bar, and are of interest for applications of energy storagemore » of hydrogenous fuels. The very high cross sections for neutrons compared to hard X-ray photons, enabled us to find considerable amounts of native hydrogen in the soot and to see and quantify the presence of hydrogen atoms in the carbon soot matrix under different pressure conditions. Our work lays the base for more detailed in-situ investigations on the interaction of porous carbon materials with hydrogen in practical environments for hydrogen and methane storage.« less

Inertial collapse of bubble pairs near a solid surface

NASA Astrophysics Data System (ADS)

Alahyari Beig, Shahaboddin; Johnsen, Eric

2017-11-01

Cavitation occurs in a variety of applications ranging from naval structures to biomedical ultrasound. One important consequence is structural damage to neighboring surfaces following repeated inertial collapse of vapor bubbles. Although the mechanical loading produced by the collapse of a single bubble has been widely investigated, less is known about the detailed dynamics of the collapse of multiple bubbles. In such a problem, the bubble-bubble interactions typically affect the dynamics, e.g., by increasing the non-sphericity of the bubbles and amplifying/hindering the collapse intensity depending on the flow parameters. Here, we quantify the effects of bubble-bubble interactions on the bubble dynamics, as well as the pressures/temperatures produced by the collapse of a pair of gas bubbles near a rigid surface. We perform high-resolution simulations of this problem by solving the three-dimensional compressible Navier-Stokes equations for gas/liquid flows. The results are used to investigate the non-spherical bubble dynamics and characterize the pressure and temperature fields based on the relevant parameters entering the problem: stand-off distance, geometrical configuration (angle, relative size, distance), collapse strength. This research was supported in part by ONR Grant N00014-12-1-0751 and NSF Grant CBET 1253157.

Quantifying climate feedbacks in polar regions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goosse, Hugues; Kay, Jennifer E.; Armour, Kyle C.

The concept of feedback is key in assessing whether a perturbation to a system is amplified or damped by mechanisms internal to the system. In polar regions, climate dynamics are controlled by both radiative and non-radiative interactions between the atmosphere, ocean, sea ice, ice sheets and land surfaces. Precisely quantifying polar feedbacks is required for a process-oriented evaluation of climate models, a clear understanding of the processes responsible for polar climate changes, and a reduction in uncertainty associated with model projections. This quantification can be performed using a simple and consistent approach that is valid for a wide range ofmore » feedbacks, thus offering the opportunity for more systematic feedback analyses and a better understanding of polar climate changes.« less

Quantifying climate feedbacks in polar regions

DOE PAGES

Goosse, Hugues; Kay, Jennifer E.; Armour, Kyle C.; ...

2018-05-15

The concept of feedback is key in assessing whether a perturbation to a system is amplified or damped by mechanisms internal to the system. In polar regions, climate dynamics are controlled by both radiative and non-radiative interactions between the atmosphere, ocean, sea ice, ice sheets and land surfaces. Precisely quantifying polar feedbacks is required for a process-oriented evaluation of climate models, a clear understanding of the processes responsible for polar climate changes, and a reduction in uncertainty associated with model projections. This quantification can be performed using a simple and consistent approach that is valid for a wide range ofmore » feedbacks, thus offering the opportunity for more systematic feedback analyses and a better understanding of polar climate changes.« less

Quantifying protein microstructure and electrostatic effects on the change in Gibbs free energy of binding in immobilized metal affinity chromatography.

PubMed

Pathange, Lakshmi P; Bevan, David R; Zhang, Chenming

2008-03-01

Electrostatic forces play a major role in maintaining both structural and functional properties of proteins. A major component of protein electrostatics is the interactions between the charged or titratable amino acid residues (e.g., Glu, Lys, and His), whose pK(a) (or the change of the pK(a)) value could be used to study protein electrostatics. Here, we report the study of electrostatic forces through experiments using a well-controlled model protein (T4 lysozyme) and its variants. We generated 10 T4 lysozyme variants, in which the electrostatic environment of the histidine residue was perturbed by altering charged and neutral amino acid residues at various distances from the histidine (probe) residue. The electrostatic perturbations were theoretically quantified by calculating the change in free energy (DeltaDeltaG(E)) using Coulomb's law. On the other hand, immobilized metal affinity chromatography (IMAC) was used to quantify these perturbations in terms of protein binding strength or change in free energy of binding (DeltaDeltaG(B)), which varies from -0.53 to 0.99 kcal/mol. For most of the variants, there is a good correlation (R(2) = 0.97) between the theoretical DeltaDeltaG(E) and experimental DeltaDeltaG(B) values. However, there are three deviant variants, whose histidine residue was found to be involved in site-specific interactions (e.g., ion pair and steric hindrance), which were further investigated by molecular dynamics simulation. This report demonstrates that the electrostatic (DeltaDeltaG(Elec)) and microstructural effects (DeltaDeltaG(Micro)) in a protein can be quantified by IMAC through surface histidine mediated protein-metal ion interaction and that the unique microstructure around a histidine residue can be identified by identifying the abnormal binding behaviors during IMAC.

Spectral Analysis: From Additive Perspective to Multiplicative Perspective

NASA Astrophysics Data System (ADS)

Wu, Z.

2017-12-01

The early usage of trigonometric functions can be traced back to at least 17th century BC. It was Bhaskara II of the 12th century CE who first proved the mathematical equivalence between the sum of two trigonometric functions of any given angles and the product of two trigonometric functions of related angles, which has been taught these days in middle school classroom. The additive perspective of trigonometric functions led to the development of the Fourier transform that is used to express any functions as the sum of a set of trigonometric functions and opened a new mathematical field called harmonic analysis. Unfortunately, Fourier's sum cannot directly express nonlinear interactions between trigonometric components of different periods, and thereby lacking the capability of quantifying nonlinear interactions in dynamical systems. In this talk, the speaker will introduce the Huang transform and Holo-spectrum which were pioneered by Norden Huang and emphasizes the multiplicative perspective of trigonometric functions in expressing any function. Holo-spectrum is a multi-dimensional spectral expression of a time series that explicitly identifies the interactions among different scales and quantifies nonlinear interactions hidden in a time series. Along with this introduction, the developing concepts of physical, rather than mathematical, analysis of data will be explained. Various enlightening applications of Holo-spectrum analysis in atmospheric and climate studies will also be presented.

Scaling properties in time-varying networks with memory

NASA Astrophysics Data System (ADS)

Kim, Hyewon; Ha, Meesoon; Jeong, Hawoong

2015-12-01

The formation of network structure is mainly influenced by an individual node's activity and its memory, where activity can usually be interpreted as the individual inherent property and memory can be represented by the interaction strength between nodes. In our study, we define the activity through the appearance pattern in the time-aggregated network representation, and quantify the memory through the contact pattern of empirical temporal networks. To address the role of activity and memory in epidemics on time-varying networks, we propose temporal-pattern coarsening of activity-driven growing networks with memory. In particular, we focus on the relation between time-scale coarsening and spreading dynamics in the context of dynamic scaling and finite-size scaling. Finally, we discuss the universality issue of spreading dynamics on time-varying networks for various memory-causality tests.

Dynamic absorption and scattering of water and hydrogel during high-repetition-rate (>100 MHz) burst-mode ultrafast-pulse laser ablation.

PubMed

Qian, Zuoming; Covarrubias, Andrés; Grindal, Alexander W; Akens, Margarete K; Lilge, Lothar; Marjoribanks, Robin S

2016-06-01

High-repetition-rate burst-mode ultrafast-laser ablation and disruption of biological tissues depends on interaction of each pulse with the sample, but under those particular conditions which persist from previous pulses. This work characterizes and compares the dynamics of absorption and scattering of a 133-MHz repetition-rate, burst-mode ultrafast-pulse laser, in agar hydrogel targets and distilled water. The differences in energy partition are quantified, pulse-by-pulse, using a time-resolving integrating-sphere-based device. These measurements reveal that high-repetition-rate burst-mode ultrafast-laser ablation is a highly dynamical process affected by the persistence of ionization, dissipation of plasma plume, neutral material flow, tissue tensile strength, and the hydrodynamic oscillation of cavitation bubbles.

Water's Interfacial Hydrogen Bonding Structure Reveals the Effective Strength of Surface-Water Interactions.

PubMed

Shin, Sucheol; Willard, Adam P

2018-06-05

We combine all-atom molecular dynamics simulations with a mean field model of interfacial hydrogen bonding to analyze the effect of surface-water interactions on the structural and energetic properties of the liquid water interface. We show that the molecular structure of water at a weakly interacting ( i.e., hydrophobic) surface is resistant to change unless the strength of surface-water interactions are above a certain threshold. We find that below this threshold water's interfacial structure is homogeneous and insensitive to the details of the disordered surface, however, above this threshold water's interfacial structure is heterogeneous. Despite this heterogeneity, we demonstrate that the equilibrium distribution of molecular orientations can be used to quantify the energetic component of the surface-water interactions that contribute specifically to modifying the interfacial hydrogen bonding network. We identify this specific energetic component as a new measure of hydrophilicity, which we refer to as the intrinsic hydropathy.

Impact of aeroelasticity on propulsion and longitudinal flight dynamics of an air-breathing hypersonic vehicle

NASA Technical Reports Server (NTRS)

Raney, David L.; Mcminn, John D.; Pototzky, Anthony S.; Wooley, Christine L.

1993-01-01

Many air-breathing hypersonic aerospacecraft design concepts incorporate an elongated fuselage forebody acting as the aerodynamic compression surface for a hypersonic combustion module, or scram jet. This highly integrated design approach creates the potential for an unprecedented form of aero-propulsive-elastic interaction in which deflections of the vehicle fuselage give rise to propulsion transients, producing force and moment variations that may adversely impact the rigid body flight dynamics and/or further excite the fuselage bending modes. To investigate the potential for such interactions, a math model was developed which included the longitudinal flight dynamics, propulsion system, and first seven elastic modes of a hypersonic air-breathing vehicle. Perturbation time histories from a simulation incorporating this math model are presented that quantify the propulsive force and moment variations resulting from aeroelastic vehicle deflections. Root locus plots are presented to illustrate the effect of feeding the propulsive perturbations back into the aeroelastic model. A concluding section summarizes the implications of the observed effects for highly integrated hypersonic air-breathing vehicle concepts.

Dynamics of Magnetopause Reconnection in Response to Variable Solar Wind Conditions

NASA Astrophysics Data System (ADS)

Berchem, J.; Richard, R. L.; Escoubet, C. P.; Pitout, F.

2017-12-01

Quantifying the dynamics of magnetopause reconnection in response to variable solar wind driving is essential to advancing our predictive understanding of the interaction of the solar wind/IMF with the magnetosphere. To this end we have carried out numerical studies that combine global magnetohydrodynamic (MHD) and Large-Scale Kinetic (LSK) simulations to identify and understand the effects of solar wind/IMF variations. The use of the low dissipation, high resolution UCLA MHD code incorporating a non-linear local resistivity allows the representation of the global configuration of the dayside magnetosphere while the use of LSK ion test particle codes with distributed particle detectors allows us to compare the simulation results with spacecraft observations such as ion dispersion signatures observed by the Cluster spacecraft. We present the results of simulations that focus on the impacts of relatively simple solar wind discontinuities on the magnetopause and examine how the recent history of the interaction of the magnetospheric boundary with solar wind discontinuities can modify the dynamics of magnetopause reconnection in response to the solar wind input.

Impact of aeroelasticity on propulsion and longitudinal flight dynamics of an air-breathing hypersonic vehicle

NASA Astrophysics Data System (ADS)

Raney, David L.; McMinn, John D.; Pototzky, Anthony S.; Wooley, Christine L.

1993-04-01

Many air-breathing hypersonic aerospacecraft design concepts incorporate an elongated fuselage forebody acting as the aerodynamic compression surface for a hypersonic combustion module, or scram jet. This highly integrated design approach creates the potential for an unprecedented form of aero-propulsive-elastic interaction in which deflections of the vehicle fuselage give rise to propulsion transients, producing force and moment variations that may adversely impact the rigid body flight dynamics and/or further excite the fuselage bending modes. To investigate the potential for such interactions, a math model was developed which included the longitudinal flight dynamics, propulsion system, and first seven elastic modes of a hypersonic air-breathing vehicle. Perturbation time histories from a simulation incorporating this math model are presented that quantify the propulsive force and moment variations resulting from aeroelastic vehicle deflections. Root locus plots are presented to illustrate the effect of feeding the propulsive perturbations back into the aeroelastic model. A concluding section summarizes the implications of the observed effects for highly integrated hypersonic air-breathing vehicle concepts.

The quantum-mechanical approach to construction of quantitative assessments of some documentary information properties (on example of nuclear knowledge)

NASA Astrophysics Data System (ADS)

Lebedev, A. A.; Maksimov, N. V.; Smirnova, E. V.

2017-01-01

The paper presents a model of information interactions, based on a probabilistic concept of meanings. The proposed hypothesis about the wave nature of information and use of quantum mechanics mathematical apparatus allow to consider the phenomena of interference and diffraction with respect to the linguistic variables, and to quantify dynamics of terms in subject areas. Retrospective database INIS IAEA was used as an experimental base.

Dynamics of the Yellowstone hydrothermal system

USGS Publications Warehouse

Hurwitz, Shaul; Lowenstern, Jacob B.

2014-01-01

The Yellowstone Plateau Volcanic Field is characterized by extensive seismicity, episodes of uplift and subsidence, and a hydrothermal system that comprises more than 10,000 thermal features, including geysers, fumaroles, mud pots, thermal springs, and hydrothermal explosion craters. The diverse chemical and isotopic compositions of waters and gases derive from mantle, crustal, and meteoric sources and extensive water-gas-rock interaction at variable pressures and temperatures. The thermal features are host to all domains of life that utilize diverse inorganic sources of energy for metabolism. The unique and exceptional features of the hydrothermal system have attracted numerous researchers to Yellowstone beginning with the Washburn and Hayden expeditions in the 1870s. Since a seminal review published a quarter of a century ago, research in many fields has greatly advanced our understanding of the many coupled processes operating in and on the hydrothermal system. Specific advances include more refined geophysical images of the magmatic system, better constraints on the time scale of magmatic processes, characterization of fluid sources and water-rock interactions, quantitative estimates of heat and magmatic volatile fluxes, discovering and quantifying the role of thermophile microorganisms in the geochemical cycle, defining the chronology of hydrothermal explosions and their relation to glacial cycles, defining possible links between hydrothermal activity, deformation, and seismicity; quantifying geyser dynamics; and the discovery of extensive hydrothermal activity in Yellowstone Lake. Discussion of these many advances forms the basis of this review.

Weakly Nonergodic Dynamics in the Gross-Pitaevskii Lattice

NASA Astrophysics Data System (ADS)

Mithun, Thudiyangal; Kati, Yagmur; Danieli, Carlo; Flach, Sergej

2018-05-01

The microcanonical Gross-Pitaevskii (also known as the semiclassical Bose-Hubbard) lattice model dynamics is characterized by a pair of energy and norm densities. The grand canonical Gibbs distribution fails to describe a part of the density space, due to the boundedness of its kinetic energy spectrum. We define Poincaré equilibrium manifolds and compute the statistics of microcanonical excursion times off them. The tails of the distribution functions quantify the proximity of the many-body dynamics to a weakly nonergodic phase, which occurs when the average excursion time is infinite. We find that a crossover to weakly nonergodic dynamics takes place inside the non-Gibbs phase, being unnoticed by the largest Lyapunov exponent. In the ergodic part of the non-Gibbs phase, the Gibbs distribution should be replaced by an unknown modified one. We relate our findings to the corresponding integrable limit, close to which the actions are interacting through a short range coupling network.

Electrical control of spin dynamics in finite one-dimensional systems

NASA Astrophysics Data System (ADS)

Pertsova, A.; Stamenova, M.; Sanvito, S.

2011-10-01

We investigate the possibility of the electrical control of spin transfer in monoatomic chains incorporating spin impurities. Our theoretical framework is the mixed quantum-classical (Ehrenfest) description of the spin dynamics, in the spirit of the s-d model, where the itinerant electrons are described by a tight-binding model while localized spins are treated classically. Our main focus is on the dynamical exchange interaction between two well-separated spins. This can be quantified by the transfer of excitations in the form of transverse spin oscillations. We systematically study the effect of an electrostatic gate bias Vg on the interconnecting channel and we map out the long-range dynamical spin transfer as a function of Vg. We identify regions of Vg giving rise to significant amplification of the spin transmission at low frequencies and relate this to the electronic structure of the channel.

FDNS CFD Code Benchmark for RBCC Ejector Mode Operation

NASA Technical Reports Server (NTRS)

Holt, James B.; Ruf, Joe

1999-01-01

Computational Fluid Dynamics (CFD) analysis results are compared with benchmark quality test data from the Propulsion Engineering Research Center's (PERC) Rocket Based Combined Cycle (RBCC) experiments to verify fluid dynamic code and application procedures. RBCC engine flowpath development will rely on CFD applications to capture the multi-dimensional fluid dynamic interactions and to quantify their effect on the RBCC system performance. Therefore, the accuracy of these CFD codes must be determined through detailed comparisons with test data. The PERC experiments build upon the well-known 1968 rocket-ejector experiments of Odegaard and Stroup by employing advanced optical and laser based diagnostics to evaluate mixing and secondary combustion. The Finite Difference Navier Stokes (FDNS) code was used to model the fluid dynamics of the PERC RBCC ejector mode configuration. Analyses were performed for both Diffusion and Afterburning (DAB) and Simultaneous Mixing and Combustion (SMC) test conditions. Results from both the 2D and the 3D models are presented.

Unraveling dynamics of human physical activity patterns in chronic pain conditions

NASA Astrophysics Data System (ADS)

Paraschiv-Ionescu, Anisoara; Buchser, Eric; Aminian, Kamiar

2013-06-01

Chronic pain is a complex disabling experience that negatively affects the cognitive, affective and physical functions as well as behavior. Although the interaction between chronic pain and physical functioning is a well-accepted paradigm in clinical research, the understanding of how pain affects individuals' daily life behavior remains a challenging task. Here we develop a methodological framework allowing to objectively document disruptive pain related interferences on real-life physical activity. The results reveal that meaningful information is contained in the temporal dynamics of activity patterns and an analytical model based on the theory of bivariate point processes can be used to describe physical activity behavior. The model parameters capture the dynamic interdependence between periods and events and determine a `signature' of activity pattern. The study is likely to contribute to the clinical understanding of complex pain/disease-related behaviors and establish a unified mathematical framework to quantify the complex dynamics of various human activities.

Quantifying uncertainty due to fission-fusion dynamics as a component of social complexity.

PubMed

Ramos-Fernandez, Gabriel; King, Andrew J; Beehner, Jacinta C; Bergman, Thore J; Crofoot, Margaret C; Di Fiore, Anthony; Lehmann, Julia; Schaffner, Colleen M; Snyder-Mackler, Noah; Zuberbühler, Klaus; Aureli, Filippo; Boyer, Denis

2018-05-30

Groups of animals (including humans) may show flexible grouping patterns, in which temporary aggregations or subgroups come together and split, changing composition over short temporal scales, (i.e. fission and fusion). A high degree of fission-fusion dynamics may constrain the regulation of social relationships, introducing uncertainty in interactions between group members. Here we use Shannon's entropy to quantify the predictability of subgroup composition for three species known to differ in the way their subgroups come together and split over time: spider monkeys ( Ateles geoffroyi ), chimpanzees ( Pan troglodytes ) and geladas ( Theropithecus gelada ). We formulate a random expectation of entropy that considers subgroup size variation and sample size, against which the observed entropy in subgroup composition can be compared. Using the theory of set partitioning, we also develop a method to estimate the number of subgroups that the group is likely to be divided into, based on the composition and size of single focal subgroups. Our results indicate that Shannon's entropy and the estimated number of subgroups present at a given time provide quantitative metrics of uncertainty in the social environment (within which social relationships must be regulated) for groups with different degrees of fission-fusion dynamics. These metrics also represent an indirect quantification of the cognitive challenges posed by socially dynamic environments. Overall, our novel methodological approach provides new insight for understanding the evolution of social complexity and the mechanisms to cope with the uncertainty that results from fission-fusion dynamics. © 2017 The Author(s).

Unifying dynamical and structural stability of equilibria

NASA Astrophysics Data System (ADS)

Arnoldi, Jean-François; Haegeman, Bart

2016-09-01

We exhibit a fundamental relationship between measures of dynamical and structural stability of linear dynamical systems-e.g. linearized models in the vicinity of equilibria. We show that dynamical stability, quantified via the response to external perturbations (i.e. perturbation of dynamical variables), coincides with the minimal internal perturbation (i.e. perturbations of interactions between variables) able to render the system unstable. First, by reformulating a result of control theory, we explain that harmonic external perturbations reflect the spectral sensitivity of the Jacobian matrix at the equilibrium, with respect to constant changes of its coefficients. However, for this equivalence to hold, imaginary changes of the Jacobian's coefficients have to be allowed. The connection with dynamical stability is thus lost for real dynamical systems. We show that this issue can be avoided, thus recovering the fundamental link between dynamical and structural stability, by considering stochastic noise as external and internal perturbations. More precisely, we demonstrate that a linear system's response to white-noise perturbations directly reflects the intensity of internal white-noise disturbance that it can accommodate before becoming stochastically unstable.

Unifying dynamical and structural stability of equilibria.

PubMed

Arnoldi, Jean-François; Haegeman, Bart

2016-09-01

We exhibit a fundamental relationship between measures of dynamical and structural stability of linear dynamical systems-e.g. linearized models in the vicinity of equilibria. We show that dynamical stability, quantified via the response to external perturbations (i.e. perturbation of dynamical variables), coincides with the minimal internal perturbation (i.e. perturbations of interactions between variables) able to render the system unstable. First, by reformulating a result of control theory, we explain that harmonic external perturbations reflect the spectral sensitivity of the Jacobian matrix at the equilibrium, with respect to constant changes of its coefficients. However, for this equivalence to hold, imaginary changes of the Jacobian's coefficients have to be allowed. The connection with dynamical stability is thus lost for real dynamical systems. We show that this issue can be avoided, thus recovering the fundamental link between dynamical and structural stability, by considering stochastic noise as external and internal perturbations. More precisely, we demonstrate that a linear system's response to white-noise perturbations directly reflects the intensity of internal white-noise disturbance that it can accommodate before becoming stochastically unstable.

Multimodal Pressure Flow Analysis: Application of Hilbert Huang Transform in Cerebral Blood Flow Regulation

PubMed Central

Lo, Men-Tzung; Hu, Kun; Liu, Yanhui; Peng, C.-K.; Novak, Vera

2008-01-01

Quantification of nonlinear interactions between two nonstationary signals presents a computational challenge in different research fields, especially for assessments of physiological systems. Traditional approaches that are based on theories of stationary signals cannot resolve nonstationarity-related issues and, thus, cannot reliably assess nonlinear interactions in physiological systems. In this review we discuss a new technique “Multi-Modal Pressure Flow method (MMPF)” that utilizes Hilbert-Huang transformation to quantify dynamic cerebral autoregulation (CA) by studying interaction between nonstationary cerebral blood flow velocity (BFV) and blood pressure (BP). CA is an important mechanism responsible for controlling cerebral blood flow in responses to fluctuations in systemic BP within a few heart-beats. The influence of CA is traditionally assessed from the relationship between the well-pronounced systemic BP and BFV oscillations induced by clinical tests. Reliable noninvasive assessment of dynamic CA, however, remains a challenge in clinical and diagnostic medicine. In this brief review we: 1) present an overview of transfer function analysis (TFA) that is traditionally used to quantify CA; 2) describe the a MMPF method and its modifications; 3) introduce a newly developed automatic algorithm and engineering aspects of the improved MMPF method; and 4) review clinical applications of MMPF and its sensitivity for detection of CA abnormalities in clinical studies. The MMPF analysis decomposes complex nonstationary BP and BFV signals into multiple empirical modes adaptively so that the fluctuations caused by a specific physiologic process can be represented in a corresponding empirical mode. Using this technique, we recently showed that dynamic CA can be characterized by specific phase delays between the decomposed BP and BFV oscillations, and that the phase shifts are significantly reduced in hypertensive, diabetics and stroke subjects with impaired CA. In addition, the new technique enables reliable assessment of CA using both data collected during clinical test and spontaneous BP/BFV fluctuations during baseline resting conditions. PMID:18725996

Seasonal species interactions minimize the impact of species turnover on the likelihood of community persistence.

PubMed

Saavedra, Serguei; Rohr, Rudolf P; Fortuna, Miguel A; Selva, Nuria; Bascompte, Jordi

2016-04-01

Many of the observed species interactions embedded in ecological communities are not permanent, but are characterized by temporal changes that are observed along with abiotic and biotic variations. While work has been done describing and quantifying these changes, little is known about their consequences for species coexistence. Here, we investigate the extent to which changes of species composition impact the likelihood of persistence of the predator-prey community in the highly seasonal Białowieza Primeval Forest (northeast Poland), and the extent to which seasonal changes of species interactions (predator diet) modulate the expected impact. This likelihood is estimated extending recent developments on the study of structural stability in ecological communities. We find that the observed species turnover strongly varies the likelihood of community persistence between summer and winter. Importantly, we demonstrate that the observed seasonal interaction changes minimize the variation in the likelihood of persistence associated with species turnover across the year. We find that these community dynamics can be explained as the coupling of individual species to their environment by minimizing both the variation in persistence conditions and the interaction changes between seasons. Our results provide a homeostatic explanation for seasonal species interactions and suggest that monitoring the association of interactions changes with the level of variation in community dynamics can provide a good indicator of the response of species to environmental pressures.

Probing the communication of deoxythymidine triphosphate in HIV-1 reverse transcriptase by communication maps and interaction energy studies.

PubMed

Gnanasekaran, Ramachandran

2017-11-08

We calculate communication maps for HIV-1 Reverse Transcriptase (RT) to elucidate energy transfer pathways between deoxythymidine triphosphate (dTTP) and other parts of the protein. This approach locates energy transport channels from the dTTP to remote regions of the protein via residues and water molecules. We examine the water dynamics near the catalytic site of HIV-1 RT by molecular dynamics (MD) simulations. We find that, within the catalytic site, the relaxation of water molecules is similar to that of the hydration water molecules present in other proteins and the relaxation time scale is fast enough to transport energy and helps in communication between dTTP and other residues in the system. To quantify energy transfer, we also calculate the interaction energies of dTTP, 2Mg 2+ , doxy-guanosine nucleotide (DG22) with their surrounding residues by using the B3LYP-D3 method. The results, from classical vibrational energy diffusivity and QM interaction energy, are complementary to identify the important residues involved in the process of polymerization. The positive and negative interactions by dTTP with different types of residues in the catalytic region make the residues transfer energy through vibrational communication.

Memory and obesity affect the population dynamics of asexual freshwater planarians

NASA Astrophysics Data System (ADS)

Dunkel, Jörn; Talbot, Jared; Schötz, Eva-Maria

2011-04-01

Asexual reproduction in multicellular organisms is a complex biophysical process that is not yet well understood quantitatively. Here, we report a detailed population study for the asexual freshwater planarian Schmidtea mediterranea, which can reproduce via transverse fission due to a large stem cell contingent. Our long-term observations of isolated non-interacting planarian populations reveal that the characteristic fission waiting time distributions for head and tail fragments differ significantly from each other. The stochastic fission dynamics of tail fragments exhibits non-negligible memory effects, implying that an accurate mathematical description of future data should be based on non-Markovian tree models. By comparing the effective growth of non-interacting planarian populations with those of self-interacting populations, we are able to quantify the influence of interactions between flatworms and physical conditions on the population growth. A surprising result is the non-monotonic relationship between effective population growth rate and nutrient supply: planarians exhibit a tendency to become 'obese' if the feeding frequency exceeds a critical level, resulting in a decreased reproduction activity. This suggests that these flatworms, which possess many genes homologous to those of humans, could become a new model system for studying dietary effects on reproduction and regeneration in multicellular organisms.

Nitrogen feedbacks increase future terrestrial ecosystem carbon uptake in an individual-based dynamic vegetation model

NASA Astrophysics Data System (ADS)

Wårlind, D.; Smith, B.; Hickler, T.; Arneth, A.

2014-01-01

Recently a considerable amount of effort has been put into quantifying how interactions of the carbon and nitrogen cycle affect future terrestrial carbon sinks. Dynamic vegetation models, representing the nitrogen cycle with varying degree of complexity, have shown diverging constraints of nitrogen dynamics on future carbon sequestration. In this study, we use the dynamic vegetation model LPJ-GUESS to evaluate how population dynamics and resource competition between plant functional types, combined with nitrogen dynamics, have influenced the terrestrial carbon storage in the past and to investigate how terrestrial carbon and nitrogen dynamics might change in the future (1850 to 2100; one exemplary "business-as-usual" climate scenario). Single factor model experiments of CO2 fertilisation and climate change show generally similar directions of the responses of C-N interactions, compared to the C-only version of the model, as documented in previous studies. Under a RCP 8.5 scenario, nitrogen limitation suppresses potential CO2 fertilisation, reducing the cumulative net ecosystem carbon uptake between 1850 and 2100 by 61%, and soil warming-induced increase in nitrogen mineralisation reduces terrestrial carbon loss by 31%. When environmental changes are considered conjointly, carbon sequestration is limited by nitrogen dynamics until present. However, during the 21st century nitrogen dynamics induce a net increase in carbon sequestration, resulting in an overall larger carbon uptake of 17% over the full period. This contradicts earlier model results that showed an 8 to 37% decrease in carbon uptake, questioning the often stated assumption that projections of future terrestrial C dynamics from C-only models are too optimistic.

Analyzing complex networks evolution through Information Theory quantifiers

NASA Astrophysics Data System (ADS)

Carpi, Laura C.; Rosso, Osvaldo A.; Saco, Patricia M.; Ravetti, Martín Gómez

2011-01-01

A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts-Strogatz model, a gene network during the progression of Alzheimer's disease and a climate network for the Tropical Pacific region to study the El Niño/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution.

The potential and flux landscape theory of evolution.

PubMed

Zhang, Feng; Xu, Li; Zhang, Kun; Wang, Erkang; Wang, Jin

2012-08-14

We established the potential and flux landscape theory for evolution. We found explicitly the conventional Wright's gradient adaptive landscape based on the mean fitness is inadequate to describe the general evolutionary dynamics. We show the intrinsic potential as being Lyapunov function(monotonically decreasing in time) does exist and can define the adaptive landscape for general evolution dynamics for studying global stability. The driving force determining the dynamics can be decomposed into gradient of potential landscape and curl probability flux. Non-zero flux causes detailed balance breaking and measures how far the evolution from equilibrium state. The gradient of intrinsic potential and curl flux are perpendicular to each other in zero fluctuation limit resembling electric and magnetic forces on electrons. We quantified intrinsic energy, entropy and free energy of evolution and constructed non-equilibrium thermodynamics. The intrinsic non-equilibrium free energy is a Lyapunov function. Both intrinsic potential and free energy can be used to quantify the global stability and robustness of evolution. We investigated an example of three allele evolutionary dynamics with frequency dependent selection (detailed balance broken). We uncovered the underlying single, triple, and limit cycle attractor landscapes. We found quantitative criterions for stability through landscape topography. We also quantified evolution pathways and found paths do not follow potential gradient and are irreversible due to non-zero flux. We generalized the original Fisher's fundamental theorem to the general (i.e., frequency dependent selection) regime of evolution by linking the adaptive rate with not only genetic variance related to the potential but also the flux. We show there is an optimum potential where curl flux resulting from biotic interactions of individuals within a species or between species can sustain an endless evolution even if the physical environment is unchanged. We offer a theoretical basis for explaining the corresponding Red Queen hypothesis proposed by Van Valen. Our work provides a theoretical foundation for evolutionary dynamics.

Information-theoretic decomposition of embodied and situated systems.

PubMed

Da Rold, Federico

2018-07-01

The embodied and situated view of cognition stresses the importance of real-time and nonlinear bodily interaction with the environment for developing concepts and structuring knowledge. In this article, populations of robots controlled by an artificial neural network learn a wall-following task through artificial evolution. At the end of the evolutionary process, time series are recorded from perceptual and motor neurons of selected robots. Information-theoretic measures are estimated on pairings of variables to unveil nonlinear interactions that structure the agent-environment system. Specifically, the mutual information is utilized to quantify the degree of dependence and the transfer entropy to detect the direction of the information flow. Furthermore, the system is analyzed with the local form of such measures, thus capturing the underlying dynamics of information. Results show that different measures are interdependent and complementary in uncovering aspects of the robots' interaction with the environment, as well as characteristics of the functional neural structure. Therefore, the set of information-theoretic measures provides a decomposition of the system, capturing the intricacy of nonlinear relationships that characterize robots' behavior and neural dynamics. Copyright © 2018 Elsevier Ltd. All rights reserved.

Identification of Object Dynamics Using Hand Worn Motion and Force Sensors

PubMed Central

Kortier, Henk G.; Schepers, H. Martin; Veltink, Peter H.

2016-01-01

Emerging microelectromechanical system (MEMS)-based sensors become much more applicable for on-body measurement purposes lately. Especially, the development of a finger tip-sized tri-axial force sensor gives the opportunity to measure interaction forces between the human hand and environmental objects. We have developed a new prototype device that allows simultaneous 3D force and movement measurements at the finger and thumb tips. The combination of interaction forces and movements makes it possible to identify the dynamical characteristics of the object being handled by the hand. With this device attached to the hand, a subject manipulated mass and spring objects under varying conditions. We were able to identify and estimate the weight of two physical mass objects (0.44 kg: 29.3%±18.9% and 0.28 kg: 19.7%±10.6%) and the spring constant of a physical spring object (16.3%±12.6%). The system is a first attempt to quantify the interactions of the hand with the environment and has many potential applications in rehabilitation, ergonomics and sports. PMID:27898040

An artificial network model for estimating the network structure underlying partially observed neuronal signals.

PubMed

Komatsu, Misako; Namikawa, Jun; Chao, Zenas C; Nagasaka, Yasuo; Fujii, Naotaka; Nakamura, Kiyohiko; Tani, Jun

2014-01-01

Many previous studies have proposed methods for quantifying neuronal interactions. However, these methods evaluated the interactions between recorded signals in an isolated network. In this study, we present a novel approach for estimating interactions between observed neuronal signals by theorizing that those signals are observed from only a part of the network that also includes unobserved structures. We propose a variant of the recurrent network model that consists of both observable and unobservable units. The observable units represent recorded neuronal activity, and the unobservable units are introduced to represent activity from unobserved structures in the network. The network structures are characterized by connective weights, i.e., the interaction intensities between individual units, which are estimated from recorded signals. We applied this model to multi-channel brain signals recorded from monkeys, and obtained robust network structures with physiological relevance. Furthermore, the network exhibited common features that portrayed cortical dynamics as inversely correlated interactions between excitatory and inhibitory populations of neurons, which are consistent with the previous view of cortical local circuits. Our results suggest that the novel concept of incorporating an unobserved structure into network estimations has theoretical advantages and could provide insights into brain dynamics beyond what can be directly observed. Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Quantification of brain macrostates using dynamical nonstationarity of physiological time series.

PubMed

Latchoumane, Charles-Francois Vincent; Jeong, Jaeseung

2011-04-01

The brain shows complex, nonstationarity temporal dynamics, with abrupt micro- and macrostate transitions during its information processing. Detecting and characterizing these transitions in dynamical states of the brain is a critical issue in the field of neuroscience and psychiatry. In the current study, a novel method is proposed to quantify brain macrostates (e.g., sleep stages or cognitive states) from shifts of dynamical microstates or dynamical nonstationarity. A ``dynamical microstate'' is a temporal unit of the information processing in the brain with fixed dynamical parameters and specific spatial distribution. In this proposed approach, a phase-space-based dynamical dissimilarity map (DDM) is used to detect transitions between dynamically stationary microstates in the time series, and Tsallis time-dependent entropy is applied to quantify dynamical patterns of transitions in the DDM. We demonstrate that the DDM successfully detects transitions between microstates of different temporal dynamics in the simulated physiological time series against high levels of noise. Based on the assumption of nonlinear, deterministic brain dynamics, we also demonstrate that dynamical nonstationarity analysis is useful to quantify brain macrostates (sleep stages I, II, III, IV, and rapid eye movement (REM) sleep) from sleep EEGs with an overall accuracy of 77%. We suggest that dynamical nonstationarity is a useful tool to quantify macroscopic mental states (statistical integration) of the brain using dynamical transitions at the microscopic scale in physiological data.

Non-linear unsteady wing theory, part 1. Quasi two-dimensional behavior: Airfoils and slender wings

NASA Technical Reports Server (NTRS)

Mccune, J. E.

1987-01-01

The initial phases of a study of the large-amplitude unsteady aerodynamics of wings in severe maneuver are reported. The research centers on vortex flows, their initiation at wing surfaces, their subsequent convection, and interaction dynamically with wings and control surfaces. The focus is on 2D and quasi-2D aspects of the problem and features the development of an exact nonlinear unsteady airfoil theory as well as an approach to the crossflow problem for slender wing applications including leading-edge separation. The effective use of interactive on-line computing in quantifying and visualizing the nonsteady effects of severe maneuver is demonstrated. Interactive computational work is now possible, in which a maneuver can be initiated and its effects observed and analyzed immediately.

Macroscopic description of complex adaptive networks coevolving with dynamic node states

NASA Astrophysics Data System (ADS)

Wiedermann, Marc; Donges, Jonathan F.; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

2015-05-01

In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

Development of a New Method to Investigate the Dynamic Friction Behavior of Interfaces Using a Kolsky Tension Bar

DOE PAGES

Sanborn, B.; Song, B.; Nishida, E.

2017-11-02

In order to understand interfacial interaction of a bi-material during an impact loading event, the dynamic friction coefficient is one of the key parameters that must be characterized and quantified. In this study, a new experimental method to determine the dynamic friction coefficient between two metals was developed by using a Kolsky tension bar and a custom-designed friction fixture. Polyvinylidene fluoride (PVDF) force sensors were used to measure the normal force applied to the friction tribo pairs and the friction force was measured with conventional Kolsky tension bar method. To evaluate the technique, the dynamic friction coefficient between 4340 steelmore » and 7075-T6 aluminum was investigated at an impact speed of approximately 8 m/s. Additionally, the dynamic friction coefficient of the tribo pairs with varied surface roughness was also investigated. The data suggest that higher surface roughness leads to higher friction coefficients at the same speed of 8 m/s.« less

Macroscopic description of complex adaptive networks coevolving with dynamic node states.

PubMed

Wiedermann, Marc; Donges, Jonathan F; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

2015-05-01

In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

Using time reversal to detect entanglement and spreading of quantum information

NASA Astrophysics Data System (ADS)

Gaerttner, Martin

2017-04-01

Characterizing and understanding the states of interacting quantum systems and their non-equilibrium dynamics is the goal of quantum simulation. For this it is crucial to find experimentally feasible means for quantifying how entanglement and correlation build up and spread. The ability of analog quantum simulators to reverse the unitary dynamics of quantum many-body systems provides new tools in this quest. One such tool is the multiple-quantum coherence (MQC) spectrum previously used in NMR spectroscopy which can now be studied in so far inaccessible parameter regimes near zero temperature in highly controllable environments. I present recent progress in relating the MQC spectrum to established entanglement witnesses such as quantum Fisher information. Recognizing the MQC as out-of-time-order correlation functions, which quantify the spreading, or scrambling, of quantum information, allows us to establish a connection between these quantities and multi-partite entanglement. I will show recent experimental results obtained with a trapped ion quantum simulator and a spinor BEC illustrating the power of time reversal protocols. Supported by: JILA-NSF-PFC-1125844, NSF-PHY-1521080, ARO, AFOSR, AFOSR-MURI, DARPA, NIST.

Correlating Nitrile IR Frequencies to Local Electrostatics Quantifies Noncovalent Interactions of Peptides and Proteins.

PubMed

Deb, Pranab; Haldar, Tapas; Kashid, Somnath M; Banerjee, Subhrashis; Chakrabarty, Suman; Bagchi, Sayan

2016-05-05

Noncovalent interactions, in particular the hydrogen bonds and nonspecific long-range electrostatic interactions are fundamental to biomolecular functions. A molecular understanding of the local electrostatic environment, consistently for both specific (hydrogen-bonding) and nonspecific electrostatic (local polarity) interactions, is essential for a detailed understanding of these processes. Vibrational Stark Effect (VSE) has proven to be an extremely useful method to measure the local electric field using infrared spectroscopy of carbonyl and nitrile based probes. The nitrile chemical group would be an ideal choice because of its absorption in an infrared spectral window transparent to biomolecules, ease of site-specific incorporation into proteins, and common occurrence as a substituent in various drug molecules. However, the inability of VSE to describe the dependence of IR frequency on electric field for hydrogen-bonded nitriles to date has severely limited nitrile's utility to probe the noncovalent interactions. In this work, using infrared spectroscopy and atomistic molecular dynamics simulations, we have reported for the first time a linear correlation between nitrile frequencies and electric fields in a wide range of hydrogen-bonding environments that may bridge the existing gap between VSE and H-bonding interactions. We have demonstrated the robustness of this field-frequency correlation for both aromatic nitriles and sulfur-based nitriles in a wide range of molecules of varying size and compactness, including small molecules in complex solvation environments, an amino acid, disordered peptides, and structured proteins. This correlation, when coupled to VSE, can be used to quantify noncovalent interactions, specific or nonspecific, in a consistent manner.

Coexistence and survival in conservative Lotka-Volterra networks.

PubMed

Knebel, Johannes; Krüger, Torben; Weber, Markus F; Frey, Erwin

2013-04-19

Analyzing coexistence and survival scenarios of Lotka-Volterra (LV) networks in which the total biomass is conserved is of vital importance for the characterization of long-term dynamics of ecological communities. Here, we introduce a classification scheme for coexistence scenarios in these conservative LV models and quantify the extinction process by employing the Pfaffian of the network's interaction matrix. We illustrate our findings on global stability properties for general systems of four and five species and find a generalized scaling law for the extinction time.

Coexistence and Survival in Conservative Lotka-Volterra Networks

NASA Astrophysics Data System (ADS)

Knebel, Johannes; Krüger, Torben; Weber, Markus F.; Frey, Erwin

2013-04-01

Analyzing coexistence and survival scenarios of Lotka-Volterra (LV) networks in which the total biomass is conserved is of vital importance for the characterization of long-term dynamics of ecological communities. Here, we introduce a classification scheme for coexistence scenarios in these conservative LV models and quantify the extinction process by employing the Pfaffian of the network’s interaction matrix. We illustrate our findings on global stability properties for general systems of four and five species and find a generalized scaling law for the extinction time.

Quantifying Grassland-to-Woodland Transitions and the Implications for Carbon and Nitrogen Dynamics in the Southwest United States

NASA Technical Reports Server (NTRS)

Wessman, Carol A.; Archer, Steven R.; Asner, Gregory P.; Bateson, C. Ann

2004-01-01

Replacement of grasslands and savannas by shrublands and woodlands has been widely reported in tropical, temperate and high-latitude rangelands worldwide (Archer 1994). These changes in vegetation structure may reflect historical shifts in climate and land use; and are likely to influence biodiversity, productivity, above- and below ground carbon and nitrogen sequestration and biophysical aspects of land surface-atmosphere interactions. The goal of our proposed research is to investigate how changes in the relative abundance of herbaceous and woody vegetation affect carbon and nitrogen dynamics across heterogeneous savannas and shrub/woodlands. By linking actual land-cover composition (derived through spectral mixture analysis of AVIRIS, TM, and AVHRR imagery) with a process-based ecosystem model, we will generate explicit predictions of the C and N storage in plants and soils resulting from changes in vegetation structure. Our specific objectives will be to (1) continue development and test applications of spectral mixture analysis across grassland-to-woodland transitions; (2) quantify temporal changes in plant and soil C and N storage and turnover for remote sensing and process model parameterization and verification; and (3) couple landscape fraction maps to an ecosystem simulation model to observe biogeochemical dynamics under changing landscape structure and climatological forcings.

Effect of skin hydration on the dynamics of fingertip gripping contact.

PubMed

André, T; Lévesque, V; Hayward, V; Lefèvre, P; Thonnard, J-L

2011-11-07

The dynamics of fingertip contact manifest themselves in the complex skin movements observed during the transition from a stuck state to a fully developed slip. While investigating this transition, we found that it depended on skin hydration. To quantify this dependency, we asked subjects to slide their index fingertip on a glass surface while keeping the normal component of the interaction force constant with the help of visual feedback. Skin deformation inside the contact region was imaged with an optical apparatus that allowed us to quantify the relative sizes of the slipping and sticking regions. The ratio of the stuck skin area to the total contact area decreased linearly from 1 to 0 when the tangential force component increased from 0 to a maximum. The slope of this relationship was inversely correlated to the normal force component. The skin hydration level dramatically affected the dynamics of the contact encapsulated in the course of evolution from sticking to slipping. The specific effect was to reduce the tendency of a contact to slip, regardless of the variations of the coefficient of friction. Since grips were more unstable under dry skin conditions, our results suggest that the nervous system responds to dry skin by exaggerated grip forces that cannot be simply explained by a change in the coefficient of friction.

Effect of skin hydration on the dynamics of fingertip gripping contact

PubMed Central

André, T.; Lévesque, V.; Hayward, V.; Lefèvre, P.; Thonnard, J.-L.

2011-01-01

The dynamics of fingertip contact manifest themselves in the complex skin movements observed during the transition from a stuck state to a fully developed slip. While investigating this transition, we found that it depended on skin hydration. To quantify this dependency, we asked subjects to slide their index fingertip on a glass surface while keeping the normal component of the interaction force constant with the help of visual feedback. Skin deformation inside the contact region was imaged with an optical apparatus that allowed us to quantify the relative sizes of the slipping and sticking regions. The ratio of the stuck skin area to the total contact area decreased linearly from 1 to 0 when the tangential force component increased from 0 to a maximum. The slope of this relationship was inversely correlated to the normal force component. The skin hydration level dramatically affected the dynamics of the contact encapsulated in the course of evolution from sticking to slipping. The specific effect was to reduce the tendency of a contact to slip, regardless of the variations of the coefficient of friction. Since grips were more unstable under dry skin conditions, our results suggest that the nervous system responds to dry skin by exaggerated grip forces that cannot be simply explained by a change in the coefficient of friction. PMID:21490002

Middle-Down and Chemical Proteomic Approaches to Reveal Histone H4 Modification Dynamics in Cell Cycle: Label-Free Semi-Quantification of Histone Tail Peptide Modifications Including Phosphorylation and Highly Sensitive Capture of Histone PTM Binding Proteins Using Photo-Reactive Crosslinkers

PubMed Central

Yamamoto, Kazuki; Chikaoka, Yoko; Hayashi, Gosuke; Sakamoto, Ryosuke; Yamamoto, Ryuji; Sugiyama, Akira; Kodama, Tatsuhiko; Okamoto, Akimitsu; Kawamura, Takeshi

2015-01-01

Mass spectrometric proteomics is an effective approach for identifying and quantifying histone post-translational modifications (PTMs) and their binding proteins, especially in the cases of methylation and acetylation. However, another vital PTM, phosphorylation, tends to be poorly quantified because it is easily lost and inefficiently ionized. In addition, PTM binding proteins for phosphorylation are sometimes resistant to identification because of their variable binding affinities. Here, we present our efforts to improve the sensitivity of detection of histone H4 tail peptide phosphorylated at serine 1 (H4S1ph) and our successful identification of an H4S1ph binder candidate by means of a chemical proteomics approach. Our nanoLC-MS/MS system permitted semi-quantitative label-free analysis of histone H4 PTM dynamics of cell cycle-synchronized HeLa S3 cells, including phosphorylation, methylation, and acetylation. We show that H4S1ph abundance on nascent histone H4 unmethylated at lysine 20 (H4K20me0) peaks from late S-phase to M-phase. We also attempted to characterize effects of phosphorylation at H4S1 on protein–protein interactions. Specially synthesized photoaffinity bait peptides specifically captured 14-3-3 proteins as novel H4S1ph binding partners, whose interaction was otherwise undetectable by conventional peptide pull-down experiments. This is the first report that analyzes dynamics of PTM pattern on the whole histone H4 tail during cell cycle and enables the identification of PTM binders with low affinities using high-resolution mass spectrometry and photo-affinity bait peptides. PMID:26819910

Quantifying hyporheic exchange dynamics in a highly regulated large river reach.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hammond, Glenn Edward; Zhou, T; Huang, M

Hyporheic exchange is an important mechanism taking place in riverbanks and riverbed sediments, where river water and shallow groundwater mix and interact with each other. The direction, magnitude, and residence time of the hyporheic flux that penetrates the river bed are critical for biogeochemical processes such as carbon and nitrogen cycling, and biodegradation of organic contaminants. Many approaches including field measurements and numerical methods have been developed to quantify the hyporheic exchanges in relatively small rivers. However, the spatial and temporal distributions of hyporheic exchanges in a large, regulated river reach remain less explored due to the large spatial domains,more » complexity of geomorphologic features and subsurface properties, and the great pressure gradient variations at the riverbed created by dam operations.« less

Nitrogen feedbacks increase future terrestrial ecosystem carbon uptake in an individual-based dynamic vegetation model

NASA Astrophysics Data System (ADS)

Wårlind, D.; Smith, B.; Hickler, T.; Arneth, A.

2014-11-01

Recently a considerable amount of effort has been put into quantifying how interactions of the carbon and nitrogen cycle affect future terrestrial carbon sinks. Dynamic vegetation models, representing the nitrogen cycle with varying degree of complexity, have shown diverging constraints of nitrogen dynamics on future carbon sequestration. In this study, we use LPJ-GUESS, a dynamic vegetation model employing a detailed individual- and patch-based representation of vegetation dynamics, to evaluate how population dynamics and resource competition between plant functional types, combined with nitrogen dynamics, have influenced the terrestrial carbon storage in the past and to investigate how terrestrial carbon and nitrogen dynamics might change in the future (1850 to 2100; one representative "business-as-usual" climate scenario). Single-factor model experiments of CO2 fertilisation and climate change show generally similar directions of the responses of C-N interactions, compared to the C-only version of the model as documented in previous studies using other global models. Under an RCP 8.5 scenario, nitrogen limitation suppresses potential CO2 fertilisation, reducing the cumulative net ecosystem carbon uptake between 1850 and 2100 by 61%, and soil warming-induced increase in nitrogen mineralisation reduces terrestrial carbon loss by 31%. When environmental changes are considered conjointly, carbon sequestration is limited by nitrogen dynamics up to the present. However, during the 21st century, nitrogen dynamics induce a net increase in carbon sequestration, resulting in an overall larger carbon uptake of 17% over the full period. This contrasts with previous results with other global models that have shown an 8 to 37% decrease in carbon uptake relative to modern baseline conditions. Implications for the plausibility of earlier projections of future terrestrial C dynamics based on C-only models are discussed.

Molecular Mechanistic Insights into the Endothelial Receptor Mediated Cytoadherence of Plasmodium falciparum-Infected Erythrocytes

PubMed Central

Li, Ang; Lim, Tong Seng; Shi, Hui; Yin, Jing; Tan, Swee Jin; Li, Zhengjun; Low, Boon Chuan; Tan, Kevin Shyong Wei; Lim, Chwee Teck

2011-01-01

Cytoadherence or sequestration is essential for the pathogenesis of the most virulent human malaria species, Plasmodium falciparum (P. falciparum). Similar to leukocyte-endothelium interaction in response to inflammation, cytoadherence of P. falciparum infected red blood cells (IRBCs) to endothelium occurs under physiological shear stresses in blood vessels and involves an array of molecule complexes which cooperate to form stable binding. Here, we applied single-molecule force spectroscopy technique to quantify the dynamic force spectra and characterize the intrinsic kinetic parameters for specific ligand-receptor interactions involving two endothelial receptor proteins: thrombospondin (TSP) and CD36. It was shown that CD36 mediated interaction was much more stable than that mediated by TSP at single molecule level, although TSP-IRBC interaction appeared stronger than CD36-IRBC interaction in the high pulling rate regime. This suggests that TSP-mediated interaction may initiate cell adhesion by capturing the fast flowing IRBCs whereas CD36 functions as the ‘holder’ for providing stable binding. PMID:21437286

Advances in global sensitivity analyses of demographic-based species distribution models to address uncertainties in dynamic landscapes.

PubMed

Naujokaitis-Lewis, Ilona; Curtis, Janelle M R

2016-01-01

Developing a rigorous understanding of multiple global threats to species persistence requires the use of integrated modeling methods that capture processes which influence species distributions. Species distribution models (SDMs) coupled with population dynamics models can incorporate relationships between changing environments and demographics and are increasingly used to quantify relative extinction risks associated with climate and land-use changes. Despite their appeal, uncertainties associated with complex models can undermine their usefulness for advancing predictive ecology and informing conservation management decisions. We developed a computationally-efficient and freely available tool (GRIP 2.0) that implements and automates a global sensitivity analysis of coupled SDM-population dynamics models for comparing the relative influence of demographic parameters and habitat attributes on predicted extinction risk. Advances over previous global sensitivity analyses include the ability to vary habitat suitability across gradients, as well as habitat amount and configuration of spatially-explicit suitability maps of real and simulated landscapes. Using GRIP 2.0, we carried out a multi-model global sensitivity analysis of a coupled SDM-population dynamics model of whitebark pine (Pinus albicaulis) in Mount Rainier National Park as a case study and quantified the relative influence of input parameters and their interactions on model predictions. Our results differed from the one-at-time analyses used in the original study, and we found that the most influential parameters included the total amount of suitable habitat within the landscape, survival rates, and effects of a prevalent disease, white pine blister rust. Strong interactions between habitat amount and survival rates of older trees suggests the importance of habitat in mediating the negative influences of white pine blister rust. Our results underscore the importance of considering habitat attributes along with demographic parameters in sensitivity routines. GRIP 2.0 is an important decision-support tool that can be used to prioritize research, identify habitat-based thresholds and management intervention points to improve probability of species persistence, and evaluate trade-offs of alternative management options.

Advances in global sensitivity analyses of demographic-based species distribution models to address uncertainties in dynamic landscapes

PubMed Central

Curtis, Janelle M.R.

2016-01-01

Developing a rigorous understanding of multiple global threats to species persistence requires the use of integrated modeling methods that capture processes which influence species distributions. Species distribution models (SDMs) coupled with population dynamics models can incorporate relationships between changing environments and demographics and are increasingly used to quantify relative extinction risks associated with climate and land-use changes. Despite their appeal, uncertainties associated with complex models can undermine their usefulness for advancing predictive ecology and informing conservation management decisions. We developed a computationally-efficient and freely available tool (GRIP 2.0) that implements and automates a global sensitivity analysis of coupled SDM-population dynamics models for comparing the relative influence of demographic parameters and habitat attributes on predicted extinction risk. Advances over previous global sensitivity analyses include the ability to vary habitat suitability across gradients, as well as habitat amount and configuration of spatially-explicit suitability maps of real and simulated landscapes. Using GRIP 2.0, we carried out a multi-model global sensitivity analysis of a coupled SDM-population dynamics model of whitebark pine (Pinus albicaulis) in Mount Rainier National Park as a case study and quantified the relative influence of input parameters and their interactions on model predictions. Our results differed from the one-at-time analyses used in the original study, and we found that the most influential parameters included the total amount of suitable habitat within the landscape, survival rates, and effects of a prevalent disease, white pine blister rust. Strong interactions between habitat amount and survival rates of older trees suggests the importance of habitat in mediating the negative influences of white pine blister rust. Our results underscore the importance of considering habitat attributes along with demographic parameters in sensitivity routines. GRIP 2.0 is an important decision-support tool that can be used to prioritize research, identify habitat-based thresholds and management intervention points to improve probability of species persistence, and evaluate trade-offs of alternative management options. PMID:27547529

Piezoelectric tuning fork biosensors for the quantitative measurement of biomolecular interactions

NASA Astrophysics Data System (ADS)

Gonzalez, Laura; Rodrigues, Mafalda; Benito, Angel Maria; Pérez-García, Lluïsa; Puig-Vidal, Manel; Otero, Jorge

2015-12-01

The quantitative measurement of biomolecular interactions is of great interest in molecular biology. Atomic force microscopy (AFM) has proved its capacity to act as a biosensor and determine the affinity between biomolecules of interest. Nevertheless, the detection scheme presents certain limitations when it comes to developing a compact biosensor. Recently, piezoelectric quartz tuning forks (QTFs) have been used as laser-free detection sensors for AFM. However, only a few studies along these lines have considered soft biological samples, and even fewer constitute quantified molecular recognition experiments. Here, we demonstrate the capacity of QTF probes to perform specific interaction measurements between biotin-streptavidin complexes in buffer solution. We propose in this paper a variant of dynamic force spectroscopy based on representing adhesion energies E (aJ) against pulling rates v (nm s-1). Our results are compared with conventional AFM measurements and show the great potential of these sensors in molecular interaction studies.

Exhaust Nozzle Plume and Shock Wave Interaction

NASA Technical Reports Server (NTRS)

Castner, Raymond S.; Elmiligui, Alaa; Cliff, Susan

2013-01-01

Fundamental research for sonic boom reduction is needed to quantify the interaction of shock waves generated from the aircraft wing or tail surfaces with the exhaust plume. Both the nozzle exhaust plume shape and the tail shock shape may be affected by an interaction that may alter the vehicle sonic boom signature. The plume and shock interaction was studied using Computational Fluid Dynamics simulation on two types of convergent-divergent nozzles and a simple wedge shock generator. The nozzle plume effects on the lower wedge compression region are evaluated for two- and three-dimensional nozzle plumes. Results show that the compression from the wedge deflects the nozzle plume and shocks form on the deflected lower plume boundary. The sonic boom pressure signature of the wedge is modified by the presence of the plume, and the computational predictions show significant (8 to 15 percent) changes in shock amplitude.

Wedge Shock and Nozzle Exhaust Plume Interaction in a Supersonic Jet Flow

NASA Technical Reports Server (NTRS)

Castner, Raymond; Zaman, Khairul; Fagan, Amy; Heath, Christopher

2014-01-01

Fundamental research for sonic boom reduction is needed to quantify the interaction of shock waves generated from the aircraft wing or tail surfaces with the nozzle exhaust plume. Aft body shock waves that interact with the exhaust plume contribute to the near-field pressure signature of a vehicle. The plume and shock interaction was studied using computational fluid dynamics and compared with experimental data from a coaxial convergent-divergent nozzle flow in an open jet facility. A simple diamond-shaped wedge was used to generate the shock in the outer flow to study its impact on the inner jet flow. Results show that the compression from the wedge deflects the nozzle plume and shocks form on the opposite plume boundary. The sonic boom pressure signature of the nozzle exhaust plume was modified by the presence of the wedge. Both the experimental results and computational predictions show changes in plume deflection.

Molecular dynamics simulations of pea (Pisum sativum) lectin structure with octyl glucoside detergents: the ligand interactions and dynamics.

PubMed

Konidala, Praveen; Niemeyer, Bernd

2007-07-01

The mitogenic pea (Pisum sativum) lectin is a legume protein of non-immunoglobulin nature capable of specific recognition of glucose derivatives without altering its structure. Molecular dynamics simulations were performed in a realistic environment to investigate the structure and interaction properties of pea lectin with various concentrations of n-octyl-beta-d-glucopyranoside (OG) detergent monomers distributed inside explicit solvent cell. In addition, the diffusion coefficients of the ligands (OG, Ca2+, Mn2+, and Cl-) and the water molecules were also reported. The structural flexibility of the lectin was conserved in all simulations. The self-assembly of OG monomers into a small micelle at the hydrophobic site of the lectin was noticed in the simulation with 20 OG monomers. The interaction energy analysis concludes that the lectin was appropriately termed an adaptive structure. One or rarely two binding sites were observed at an instant in each simulation that were electrostatically favoured for the OG to interact with the surface amino acid residues. Enhanced binding of OG to the pea lectin was quantified in the system containing only Ca2+ divalent ions. Interestingly, no binding was observed in the simulation without divalent ions. Furthermore, the lectin-ligand complex was stabilized by multiple hydrogen bonds and at least one water bridge. Finally, the work was also in accordance with the published work elsewhere that the simulations performed with different initial conditions and using higher nonbonded cutoffs for the van der Waals and electrostatic interactions provide more accurate information and clues than the single large simulation of the biomolecular system of interest.

Simulating Fiber Ordering and Aggregation In Shear Flow Using Dissipative Particle Dynamics

NASA Astrophysics Data System (ADS)

Stimatze, Justin T.

We have developed a mesoscale simulation of fiber aggregation in shear flow using LAMMPS and its implementation of dissipative particle dynamics. Understanding fiber aggregation in shear flow and flow-induced microstructural fiber networks is critical to our interest in high-performance composite materials. Dissipative particle dynamics enables the consideration of hydrodynamic interactions between fibers through the coarse-grained simulation of the matrix fluid. Correctly simulating hydrodynamic interactions and accounting for fluid forces on the microstructure is required to correctly model the shear-induced aggregation process. We are able to determine stresses, viscosity, and fiber forces while simulating the evolution of a model fiber system undergoing shear flow. Fiber-fiber contact interactions are approximated by combinations of common pairwise forces, allowing the exploration of interaction-influenced fiber behaviors such as aggregation and bundling. We are then able to quantify aggregate structure and effective volume fraction for a range of relevant system and fiber-fiber interaction parameters. Our simulations have demonstrated several aggregate types dependent on system parameters such as shear rate, short-range attractive forces, and a resistance to relative rotation while in contact. A resistance to relative rotation at fiber-fiber contact points has been found to strongly contribute to an increased angle between neighboring aggregated fibers and therefore an increase in average aggregate volume fraction. This increase in aggregate volume fraction is strongly correlated with a significant enhancement of system viscosity, leading us to hypothesize that controlling the resistance to relative rotation during manufacturing processes is important when optimizing for desired composite material characteristics.

Construction and analysis of gene-gene dynamics influence networks based on a Boolean model.

PubMed

Mazaya, Maulida; Trinh, Hung-Cuong; Kwon, Yung-Keun

2017-12-21

Identification of novel gene-gene relations is a crucial issue to understand system-level biological phenomena. To this end, many methods based on a correlation analysis of gene expressions or structural analysis of molecular interaction networks have been proposed. They have a limitation in identifying more complicated gene-gene dynamical relations, though. To overcome this limitation, we proposed a measure to quantify a gene-gene dynamical influence (GDI) using a Boolean network model and constructed a GDI network to indicate existence of a dynamical influence for every ordered pair of genes. It represents how much a state trajectory of a target gene is changed by a knockout mutation subject to a source gene in a gene-gene molecular interaction (GMI) network. Through a topological comparison between GDI and GMI networks, we observed that the former network is denser than the latter network, which implies that there exist many gene pairs of dynamically influencing but molecularly non-interacting relations. In addition, a larger number of hub genes were generated in the GDI network. On the other hand, there was a correlation between these networks such that the degree value of a node was positively correlated to each other. We further investigated the relationships of the GDI value with structural properties and found that there are negative and positive correlations with the length of a shortest path and the number of paths, respectively. In addition, a GDI network could predict a set of genes whose steady-state expression is affected in E. coli gene-knockout experiments. More interestingly, we found that the drug-targets with side-effects have a larger number of outgoing links than the other genes in the GDI network, which implies that they are more likely to influence the dynamics of other genes. Finally, we found biological evidences showing that the gene pairs which are not molecularly interacting but dynamically influential can be considered for novel gene-gene relationships. Taken together, construction and analysis of the GDI network can be a useful approach to identify novel gene-gene relationships in terms of the dynamical influence.

Quantifying the topography of the intrinsic energy landscape of flexible biomolecular recognition

PubMed Central

Chu, Xiakun; Gan, Linfeng; Wang, Erkang; Wang, Jin

2013-01-01

Biomolecular functions are determined by their interactions with other molecules. Biomolecular recognition is often flexible and associated with large conformational changes involving both binding and folding. However, the global and physical understanding for the process is still challenging. Here, we quantified the intrinsic energy landscapes of flexible biomolecular recognition in terms of binding–folding dynamics for 15 homodimers by exploring the underlying density of states, using a structure-based model both with and without considering energetic roughness. By quantifying three individual effective intrinsic energy landscapes (one for interfacial binding, two for monomeric folding), the association mechanisms for flexible recognition of 15 homodimers can be classified into two-state cooperative “coupled binding–folding” and three-state noncooperative “folding prior to binding” scenarios. We found that the association mechanism of flexible biomolecular recognition relies on the interplay between the underlying effective intrinsic binding and folding energy landscapes. By quantifying the whole global intrinsic binding–folding energy landscapes, we found strong correlations between the landscape topography measure Λ (dimensionless ratio of energy gap versus roughness modulated by the configurational entropy) and the ratio of the thermodynamic stable temperature versus trapping temperature, as well as between Λ and binding kinetics. Therefore, the global energy landscape topography determines the binding–folding thermodynamics and kinetics, crucial for the feasibility and efficiency of realizing biomolecular function. We also found “U-shape” temperature-dependent kinetic behavior and a dynamical cross-over temperature for dividing exponential and nonexponential kinetics for two-state homodimers. Our study provides a unique way to bridge the gap between theory and experiments. PMID:23754431

Subgrid-scale effects in compressible variable-density decaying turbulence

DOE PAGES

GS, Sidharth; Candler, Graham V.

2018-05-08

We present that many turbulent flows are characterized by complex scale interactions and vorticity generation caused by compressibility and variable-density effects. In the large-eddy simulation of variable-density flows, these processes manifest themselves as subgrid-scale (SGS) terms that interact with the resolved-scale flow. This paper studies the effect of the variable-density SGS terms and quantifies their relative importance. We consider the SGS terms appearing in the density-weighted Favre-filtered equations and in the unweighted Reynolds-filtered equations. The conventional form of the Reynolds-filtered momentum equation is complicated by a temporal SGS term; therefore, we derive a new form of the Reynolds-filtered governing equationsmore » that does not contain this term and has only double-correlation SGS terms. The new form of the filtered equations has terms that represent the SGS mass flux, pressure-gradient acceleration and velocity-dilatation correlation. To evaluate the dynamical significance of the variable-density SGS effects, we carry out direct numerical simulations of compressible decaying turbulence at a turbulent Mach number of 0.3. Two different initial thermodynamic conditions are investigated: homentropic and a thermally inhomogeneous gas with regions of differing densities. The simulated flow fields are explicitly filtered to evaluate the SGS terms. The importance of the variable-density SGS terms is quantified relative to the SGS specific stress, which is the only SGS term active in incompressible constant-density turbulence. It is found that while the variable-density SGS terms in the homentropic case are negligible, they are dynamically significant in the thermally inhomogeneous flows. Investigation of the variable-density SGS terms is therefore important, not only to develop variable-density closures but also to improve the understanding of scale interactions in variable-density flows.« less

Subgrid-scale effects in compressible variable-density decaying turbulence

DOE Office of Scientific and Technical Information (OSTI.GOV)

GS, Sidharth; Candler, Graham V.

We present that many turbulent flows are characterized by complex scale interactions and vorticity generation caused by compressibility and variable-density effects. In the large-eddy simulation of variable-density flows, these processes manifest themselves as subgrid-scale (SGS) terms that interact with the resolved-scale flow. This paper studies the effect of the variable-density SGS terms and quantifies their relative importance. We consider the SGS terms appearing in the density-weighted Favre-filtered equations and in the unweighted Reynolds-filtered equations. The conventional form of the Reynolds-filtered momentum equation is complicated by a temporal SGS term; therefore, we derive a new form of the Reynolds-filtered governing equationsmore » that does not contain this term and has only double-correlation SGS terms. The new form of the filtered equations has terms that represent the SGS mass flux, pressure-gradient acceleration and velocity-dilatation correlation. To evaluate the dynamical significance of the variable-density SGS effects, we carry out direct numerical simulations of compressible decaying turbulence at a turbulent Mach number of 0.3. Two different initial thermodynamic conditions are investigated: homentropic and a thermally inhomogeneous gas with regions of differing densities. The simulated flow fields are explicitly filtered to evaluate the SGS terms. The importance of the variable-density SGS terms is quantified relative to the SGS specific stress, which is the only SGS term active in incompressible constant-density turbulence. It is found that while the variable-density SGS terms in the homentropic case are negligible, they are dynamically significant in the thermally inhomogeneous flows. Investigation of the variable-density SGS terms is therefore important, not only to develop variable-density closures but also to improve the understanding of scale interactions in variable-density flows.« less

Stigmergic construction and topochemical information shape ant nest architecture

PubMed Central

Khuong, Anaïs; Gautrais, Jacques; Perna, Andrea; Sbaï, Chaker; Combe, Maud; Kuntz, Pascale; Jost, Christian; Theraulaz, Guy

2016-01-01

The nests of social insects are not only impressive because of their sheer complexity but also because they are built from individuals whose work is not centrally coordinated. A key question is how groups of insects coordinate their building actions. Here, we use a combination of experimental and modeling approaches to investigate nest construction in the ant Lasius niger. We quantify the construction dynamics and the 3D structures built by ants. Then, we characterize individual behaviors and the interactions of ants with the structures they build. We show that two main interactions are involved in the coordination of building actions: (i) a stigmergic-based interaction that controls the amplification of depositions at some locations and is attributable to a pheromone added by ants to the building material; and (ii) a template-based interaction in which ants use their body size as a cue to control the height at which they start to build a roof from existing pillars. We then develop a 3D stochastic model based on these individual behaviors to analyze the effect of pheromone presence and strength on construction dynamics. We show that the model can quantitatively reproduce key features of construction dynamics, including a large-scale pattern of regularly spaced pillars, the formation and merging of caps over the pillars, and the remodeling of built structures. Finally, our model suggests that the lifetime of the pheromone is a highly influential parameter that controls the growth and form of nest architecture. PMID:26787857

Stigmergic construction and topochemical information shape ant nest architecture.

PubMed

Khuong, Anaïs; Gautrais, Jacques; Perna, Andrea; Sbaï, Chaker; Combe, Maud; Kuntz, Pascale; Jost, Christian; Theraulaz, Guy

2016-02-02

The nests of social insects are not only impressive because of their sheer complexity but also because they are built from individuals whose work is not centrally coordinated. A key question is how groups of insects coordinate their building actions. Here, we use a combination of experimental and modeling approaches to investigate nest construction in the ant Lasius niger. We quantify the construction dynamics and the 3D structures built by ants. Then, we characterize individual behaviors and the interactions of ants with the structures they build. We show that two main interactions are involved in the coordination of building actions: (i) a stigmergic-based interaction that controls the amplification of depositions at some locations and is attributable to a pheromone added by ants to the building material; and (ii) a template-based interaction in which ants use their body size as a cue to control the height at which they start to build a roof from existing pillars. We then develop a 3D stochastic model based on these individual behaviors to analyze the effect of pheromone presence and strength on construction dynamics. We show that the model can quantitatively reproduce key features of construction dynamics, including a large-scale pattern of regularly spaced pillars, the formation and merging of caps over the pillars, and the remodeling of built structures. Finally, our model suggests that the lifetime of the pheromone is a highly influential parameter that controls the growth and form of nest architecture.

Near-field electromagnetic holography for high-resolution analysis of network interactions in neuronal tissue

PubMed Central

Kjeldsen, Henrik D.; Kaiser, Marcus; Whittington, Miles A.

2015-01-01

Background Brain function is dependent upon the concerted, dynamical interactions between a great many neurons distributed over many cortical subregions. Current methods of quantifying such interactions are limited by consideration only of single direct or indirect measures of a subsample of all neuronal population activity. New method Here we present a new derivation of the electromagnetic analogy to near-field acoustic holography allowing high-resolution, vectored estimates of interactions between sources of electromagnetic activity that significantly improves this situation. In vitro voltage potential recordings were used to estimate pseudo-electromagnetic energy flow vector fields, current and energy source densities and energy dissipation in reconstruction planes at depth into the neural tissue parallel to the recording plane of the microelectrode array. Results The properties of the reconstructed near-field estimate allowed both the utilization of super-resolution techniques to increase the imaging resolution beyond that of the microelectrode array, and facilitated a novel approach to estimating causal relationships between activity in neocortical subregions. Comparison with existing methods The holographic nature of the reconstruction method allowed significantly better estimation of the fine spatiotemporal detail of neuronal population activity, compared with interpolation alone, beyond the spatial resolution of the electrode arrays used. Pseudo-energy flow vector mapping was possible with high temporal precision, allowing a near-realtime estimate of causal interaction dynamics. Conclusions Basic near-field electromagnetic holography provides a powerful means to increase spatial resolution from electrode array data with careful choice of spatial filters and distance to reconstruction plane. More detailed approaches may provide the ability to volumetrically reconstruct activity patterns on neuronal tissue, but the ability to extract vectored data with the method presented already permits the study of dynamic causal interactions without bias from any prior assumptions on anatomical connectivity. PMID:26026581

Near-field electromagnetic holography for high-resolution analysis of network interactions in neuronal tissue.

PubMed

Kjeldsen, Henrik D; Kaiser, Marcus; Whittington, Miles A

2015-09-30

Brain function is dependent upon the concerted, dynamical interactions between a great many neurons distributed over many cortical subregions. Current methods of quantifying such interactions are limited by consideration only of single direct or indirect measures of a subsample of all neuronal population activity. Here we present a new derivation of the electromagnetic analogy to near-field acoustic holography allowing high-resolution, vectored estimates of interactions between sources of electromagnetic activity that significantly improves this situation. In vitro voltage potential recordings were used to estimate pseudo-electromagnetic energy flow vector fields, current and energy source densities and energy dissipation in reconstruction planes at depth into the neural tissue parallel to the recording plane of the microelectrode array. The properties of the reconstructed near-field estimate allowed both the utilization of super-resolution techniques to increase the imaging resolution beyond that of the microelectrode array, and facilitated a novel approach to estimating causal relationships between activity in neocortical subregions. The holographic nature of the reconstruction method allowed significantly better estimation of the fine spatiotemporal detail of neuronal population activity, compared with interpolation alone, beyond the spatial resolution of the electrode arrays used. Pseudo-energy flow vector mapping was possible with high temporal precision, allowing a near-realtime estimate of causal interaction dynamics. Basic near-field electromagnetic holography provides a powerful means to increase spatial resolution from electrode array data with careful choice of spatial filters and distance to reconstruction plane. More detailed approaches may provide the ability to volumetrically reconstruct activity patterns on neuronal tissue, but the ability to extract vectored data with the method presented already permits the study of dynamic causal interactions without bias from any prior assumptions on anatomical connectivity. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Adsorption behavior of proteins on temperature-responsive resins.

PubMed

Poplewska, Izabela; Muca, Renata; Strachota, Adam; Piątkowski, Wojciech; Antos, Dorota

2014-01-10

The adsorption behavior of proteins on thermo-responsible resins based on poly(N-isopropylacrylamide) and its copolymer containing an anionic co-monomer has been investigated. The influence of the polymer composition, i.e., the content of the co-monomer and crosslinker on the thermo-sensitivity of the protein adsorption has been quantified. The properties of ungrafted polymer as well grafted onto the agarose matrix have been analyzed and compared. Batch and dynamic (column) experiments have been performed to measure the adsorption equilibrium of proteins and to quantify the phase transition process. As model proteins lysozyme, lactoferrin, α-chymotrypsinogen A and ovalbumin have been used. The adsorption process was found to be governed by ionic interactions between the negatively charged surface of resin and the protein, which enabled separation of proteins differing in electrostatic charge. The interactions enhanced with increase of temperature. Decrease of temperature facilitated desorption of proteins and reduced the salt usage in the desorption buffer. Grafted polymers exhibited markedly higher mechanical stability and, however, weaker temperature response compared to the ungrafted ones. Copyright © 2013 Elsevier B.V. All rights reserved.

Ultrafast Fabry-Perot fiber-optic pressure sensors for multimedia blast event measurements.

PubMed

Zou, Xiaotian; Wu, Nan; Tian, Ye; Zhang, Yang; Fitek, John; Maffeo, Michael; Niezrecki, Christopher; Chen, Julie; Wang, Xingwei

2013-02-20

A shock wave (SW) is characterized as a large pressure fluctuation that typically lasts only a few milliseconds. On the battlefield, SWs pose a serious threat to soldiers who are exposed to explosions, which may lead to blast-induced traumatic brain injuries. SWs can also be used beneficially and have been applied to a variety of medical treatments due to their unique interaction with tissues and cells. Consequently, it is important to have sensors that can quantify SW dynamics in order to better understand the physical interaction between body tissue and the incident acoustic wave. In this paper, the ultrafast fiber-optic sensor based on the Fabry-Perot interferometric principle was designed and four such sensors were fabricated to quantify a blast event within different media, simultaneously. The compact design of the fiber-optic sensor allows for a high degree of spatial resolution when capturing the wavefront of the traveling SW. Several blast event experiments were conducted within different media (e.g., air, rubber membrane, and water) to evaluate the sensor's performance. This research revealed valuable knowledge for further study of SW behavior and SW-related applications.

Quantifying surface water–groundwater interactions using time series analysis of streambed thermal records: Method development

USGS Publications Warehouse

Hatch, Christine E; Fisher, Andrew T.; Revenaugh, Justin S.; Constantz, Jim; Ruehl, Chris

2006-01-01

We present a method for determining streambed seepage rates using time series thermal data. The new method is based on quantifying changes in phase and amplitude of temperature variations between pairs of subsurface sensors. For a reasonable range of streambed thermal properties and sensor spacings the time series method should allow reliable estimation of seepage rates for a range of at least ±10 m d−1 (±1.2 × 10−2 m s−1), with amplitude variations being most sensitive at low flow rates and phase variations retaining sensitivity out to much higher rates. Compared to forward modeling, the new method requires less observational data and less setup and data handling and is faster, particularly when interpreting many long data sets. The time series method is insensitive to streambed scour and sedimentation, which allows for application under a wide range of flow conditions and allows time series estimation of variable streambed hydraulic conductivity. This new approach should facilitate wider use of thermal methods and improve understanding of the complex spatial and temporal dynamics of surface water–groundwater interactions.

Time and dose-dependent risk of pneumococcal pneumonia following influenza: a model for within-host interaction between influenza and Streptococcus pneumoniae

PubMed Central

Shrestha, Sourya; Foxman, Betsy; Dawid, Suzanne; Aiello, Allison E.; Davis, Brian M.; Berus, Joshua; Rohani, Pejman

2013-01-01

A significant fraction of seasonal and in particular pandemic influenza deaths are attributed to secondary bacterial infections. In animal models, influenza virus predisposes hosts to severe infection with both Streptococcus pneumoniae and Staphylococcus aureus. Despite its importance, the mechanistic nature of the interaction between influenza and pneumococci, its dependence on the timing and sequence of infections as well as the clinical and epidemiological consequences remain unclear. We explore an immune-mediated model of the viral–bacterial interaction that quantifies the timing and the intensity of the interaction. Taking advantage of the wealth of knowledge gained from animal models, and the quantitative understanding of the kinetics of pathogen-specific immunological dynamics, we formulate a mathematical model for immune-mediated interaction between influenza virus and S. pneumoniae in the lungs. We use the model to examine the pathogenic effect of inoculum size and timing of pneumococcal invasion relative to influenza infection, as well as the efficacy of antivirals in preventing severe pneumococcal disease. We find that our model is able to capture the key features of the interaction observed in animal experiments. The model predicts that introduction of pneumococcal bacteria during a 4–6 day window following influenza infection results in invasive pneumonia at significantly lower inoculum size than in hosts not infected with influenza. Furthermore, we find that antiviral treatment administered later than 4 days after influenza infection was not able to prevent invasive pneumococcal disease. This work provides a quantitative framework to study interactions between influenza and pneumococci and has the potential to accurately quantify the interactions. Such quantitative understanding can form a basis for effective clinical care, public health policies and pandemic preparedness. PMID:23825111

Ecological modeling from time-series inference: insight into dynamics and stability of intestinal microbiota.

PubMed

Stein, Richard R; Bucci, Vanni; Toussaint, Nora C; Buffie, Charlie G; Rätsch, Gunnar; Pamer, Eric G; Sander, Chris; Xavier, João B

2013-01-01

The intestinal microbiota is a microbial ecosystem of crucial importance to human health. Understanding how the microbiota confers resistance against enteric pathogens and how antibiotics disrupt that resistance is key to the prevention and cure of intestinal infections. We present a novel method to infer microbial community ecology directly from time-resolved metagenomics. This method extends generalized Lotka-Volterra dynamics to account for external perturbations. Data from recent experiments on antibiotic-mediated Clostridium difficile infection is analyzed to quantify microbial interactions, commensal-pathogen interactions, and the effect of the antibiotic on the community. Stability analysis reveals that the microbiota is intrinsically stable, explaining how antibiotic perturbations and C. difficile inoculation can produce catastrophic shifts that persist even after removal of the perturbations. Importantly, the analysis suggests a subnetwork of bacterial groups implicated in protection against C. difficile. Due to its generality, our method can be applied to any high-resolution ecological time-series data to infer community structure and response to external stimuli.

Modeling birds on wires.

PubMed

Aydoğdu, A; Frasca, P; D'Apice, C; Manzo, R; Thornton, J M; Gachomo, B; Wilson, T; Cheung, B; Tariq, U; Saidel, W; Piccoli, B

2017-02-21

In this paper we introduce a mathematical model to study the group dynamics of birds resting on wires. The model is agent-based and postulates attraction-repulsion forces between the interacting birds: the interactions are "topological", in the sense that they involve a given number of neighbors irrespective of their distance. The model is first mathematically analyzed and then simulated to study its main properties: we observe that the model predicts birds to be more widely spaced near the borders of each group. We compare the results from the model with experimental data, derived from the analysis of pictures of pigeons and starlings taken in New Jersey: two different image elaboration protocols allow us to establish a good agreement with the model and to quantify its main parameters. We also discuss the potential handedness of the birds, by analyzing the group organization features and the group dynamics at the arrival of new birds. Finally, we propose a more refined mathematical model that describes landing and departing birds by suitable stochastic processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Blood flow and blood cell interactions and migration in microvessels

NASA Astrophysics Data System (ADS)

Fedosov, Dmitry; Fornleitner, Julia; Gompper, Gerhard

2011-11-01

Blood flow in microcirculation plays a fundamental role in a wide range of physiological processes and pathologies in the organism. To understand and, if necessary, manipulate the course of these processes it is essential to investigate blood flow under realistic conditions including deformability of blood cells, their interactions, and behavior in the complex microvascular network which is characteristic for the microcirculation. We employ the Dissipative Particle Dynamics method to model blood as a suspension of deformable cells represented by a viscoelastic spring-network which incorporates appropriate mechanical and rheological cell-membrane properties. Blood flow is investigated in idealized geometries. In particular, migration of blood cells and their distribution in blood flow are studied with respect to various conditions such as hematocrit, flow rate, red blood cell aggregation. Physical mechanisms which govern cell migration in microcirculation and, in particular, margination of white blood cells towards the vessel wall, will be discussed. In addition, we characterize blood flow dynamics and quantify hemodynamic resistance. D.F. acknowledges the Humboldt Foundation for financial support.

Simulation of blood flow in deformable vessels using subject-specific geometry and spatially varying wall properties

PubMed Central

Xiong, Guanglei; Figueroa, C. Alberto; Xiao, Nan; Taylor, Charles A.

2011-01-01

SUMMARY Simulation of blood flow using image-based models and computational fluid dynamics has found widespread application to quantifying hemodynamic factors relevant to the initiation and progression of cardiovascular diseases and for planning interventions. Methods for creating subject-specific geometric models from medical imaging data have improved substantially in the last decade but for many problems, still require significant user interaction. In addition, while fluid–structure interaction methods are being employed to model blood flow and vessel wall dynamics, tissue properties are often assumed to be uniform. In this paper, we propose a novel workflow for simulating blood flow using subject-specific geometry and spatially varying wall properties. The geometric model construction is based on 3D segmentation and geometric processing. Variable wall properties are assigned to the model based on combining centerline-based and surface-based methods. We finally demonstrate these new methods using an idealized cylindrical model and two subject-specific vascular models with thoracic and cerebral aneurysms. PMID:21765984

Ecological Modeling from Time-Series Inference: Insight into Dynamics and Stability of Intestinal Microbiota

PubMed Central

Toussaint, Nora C.; Buffie, Charlie G.; Rätsch, Gunnar; Pamer, Eric G.; Sander, Chris; Xavier, João B.

2013-01-01

The intestinal microbiota is a microbial ecosystem of crucial importance to human health. Understanding how the microbiota confers resistance against enteric pathogens and how antibiotics disrupt that resistance is key to the prevention and cure of intestinal infections. We present a novel method to infer microbial community ecology directly from time-resolved metagenomics. This method extends generalized Lotka–Volterra dynamics to account for external perturbations. Data from recent experiments on antibiotic-mediated Clostridium difficile infection is analyzed to quantify microbial interactions, commensal-pathogen interactions, and the effect of the antibiotic on the community. Stability analysis reveals that the microbiota is intrinsically stable, explaining how antibiotic perturbations and C. difficile inoculation can produce catastrophic shifts that persist even after removal of the perturbations. Importantly, the analysis suggests a subnetwork of bacterial groups implicated in protection against C. difficile. Due to its generality, our method can be applied to any high-resolution ecological time-series data to infer community structure and response to external stimuli. PMID:24348232

All-Electrical Measurement of Interfacial Dzyaloshinskii-Moriya Interaction Using Collective Spin-Wave Dynamics.

PubMed

Lee, Jong Min; Jang, Chaun; Min, Byoung-Chul; Lee, Seo-Won; Lee, Kyung-Jin; Chang, Joonyeon

2016-01-13

Dzyaloshinskii-Moriya interaction (DMI), which arises from the broken inversion symmetry and spin-orbit coupling, is of prime interest as it leads to a stabilization of chiral magnetic order and provides an efficient manipulation of magnetic nanostructures. Here, we report all-electrical measurement of DMI using propagating spin wave spectroscopy based on the collective spin wave with a well-defined wave vector. We observe a substantial frequency shift of spin waves depending on the spin chirality in Pt/Co/MgO structures. After subtracting the contribution from other sources to the frequency shift, it is possible to quantify the DMI energy in Pt/Co/MgO systems. The result reveals that the DMI in Pt/Co/MgO originates from the interfaces, and the sign of DMI corresponds to the inversion asymmetry of the film structures. The electrical excitation and detection of spin waves and the influence of interfacial DMI on the collective spin-wave dynamics will pave the way to the emerging field of spin-wave logic devices.

Empirical and Theoretical Aspects of Generation and Transfer of Information in a Neuromagnetic Source Network

PubMed Central

Vakorin, Vasily A.; Mišić, Bratislav; Krakovska, Olga; McIntosh, Anthony Randal

2011-01-01

Variability in source dynamics across the sources in an activated network may be indicative of how the information is processed within a network. Information-theoretic tools allow one not only to characterize local brain dynamics but also to describe interactions between distributed brain activity. This study follows such a framework and explores the relations between signal variability and asymmetry in mutual interdependencies in a data-driven pipeline of non-linear analysis of neuromagnetic sources reconstructed from human magnetoencephalographic (MEG) data collected as a reaction to a face recognition task. Asymmetry in non-linear interdependencies in the network was analyzed using transfer entropy, which quantifies predictive information transfer between the sources. Variability of the source activity was estimated using multi-scale entropy, quantifying the rate of which information is generated. The empirical results are supported by an analysis of synthetic data based on the dynamics of coupled systems with time delay in coupling. We found that the amount of information transferred from one source to another was correlated with the difference in variability between the dynamics of these two sources, with the directionality of net information transfer depending on the time scale at which the sample entropy was computed. The results based on synthetic data suggest that both time delay and strength of coupling can contribute to the relations between variability of brain signals and information transfer between them. Our findings support the previous attempts to characterize functional organization of the activated brain, based on a combination of non-linear dynamics and temporal features of brain connectivity, such as time delay. PMID:22131968

Boldness by habituation and social interactions: a model.

PubMed

Oosten, Johanneke E; Magnhagen, Carin; Hemelrijk, Charlotte K

2010-04-01

Most studies of animal personality attribute personality to genetic traits. But a recent study by Magnhagen and Staffan (Behav Ecol Sociobiol 57:295-303, 2005) on young perch in small groups showed that boldness, a central personality trait, is also shaped by social interactions and by previous experience. The authors measured boldness by recording the duration that an individual spent near a predator and the speed with which it fed there. They found that duration near the predator increased over time and was higher the higher the average boldness of other group members. In addition, the feeding rate of shy individuals was reduced if other members of the same group were bold. The authors supposed that these behavioral dynamics were caused by genetic differences, social interactions, and habituation to the predator. However, they did not quantify exactly how this could happen. In the present study, we therefore use an agent-based model to investigate whether these three factors may explain the empirical findings. We choose an agent-based model because this type of model is especially suited to study the relation between behavior at an individual level and behavioral dynamics at a group level. In our model, individuals were either hiding in vegetation or feeding near a predator, whereby their behavior was affected by habituation and by two social mechanisms: social facilitation to approach the predator and competition over food. We show that even if we start the model with identical individuals, these three mechanisms were sufficient to reproduce the behavioral dynamics of the empirical study, including the consistent differences among individuals. Moreover, if we start the model with individuals that already differ in boldness, the behavioral dynamics produced remained the same. Our results indicate the importance of previous experience and social interactions when studying animal personality empirically.

Quantifying Parameter Sensitivity, Interaction and Transferability in Hydrologically Enhanced Versions of Noah-LSM over Transition Zones

NASA Technical Reports Server (NTRS)

Rosero, Enrique; Yang, Zong-Liang; Wagener, Thorsten; Gulden, Lindsey E.; Yatheendradas, Soni; Niu, Guo-Yue

2009-01-01

We use sensitivity analysis to identify the parameters that are most responsible for shaping land surface model (LSM) simulations and to understand the complex interactions in three versions of the Noah LSM: the standard version (STD), a version enhanced with a simple groundwater module (GW), and version augmented by a dynamic phenology module (DV). We use warm season, high-frequency, near-surface states and turbulent fluxes collected over nine sites in the US Southern Great Plains. We quantify changes in the pattern of sensitive parameters, the amount and nature of the interaction between parameters, and the covariance structure of the distribution of behavioral parameter sets. Using Sobol s total and first-order sensitivity indexes, we show that very few parameters directly control the variance of the model output. Significant parameter interaction occurs so that not only the optimal parameter values differ between models, but the relationships between parameters change. GW decreases parameter interaction and appears to improve model realism, especially at wetter sites. DV increases parameter interaction and decreases identifiability, implying it is overparameterized and/or underconstrained. A case study at a wet site shows GW has two functional modes: one that mimics STD and a second in which GW improves model function by decoupling direct evaporation and baseflow. Unsupervised classification of the posterior distributions of behavioral parameter sets cannot group similar sites based solely on soil or vegetation type, helping to explain why transferability between sites and models is not straightforward. This evidence suggests a priori assignment of parameters should also consider climatic differences.

Multi-event capture–recapture modeling of host–pathogen dynamics among European rabbit populations exposed to myxoma and Rabbit Hemorrhagic Disease Viruses: common and heterogeneous patterns

PubMed Central

2014-01-01

Host–pathogen epidemiological processes are often unclear due both to their complexity and over-simplistic approaches used to quantify them. We applied a multi-event capture–recapture procedure on two years of data from three rabbit populations to test hypotheses about the effects on survival of, and the dynamics of host immunity to, both myxoma virus and Rabbit Hemorrhagic Disease Virus (MV and RHDV). Although the populations shared the same climatic and management conditions, MV and RHDV dynamics varied greatly among them; MV and RHDV seroprevalences were positively related to density in one population, but RHDV seroprevalence was negatively related to density in another. In addition, (i) juvenile survival was most often negatively related to seropositivity, (ii) RHDV seropositives never had considerably higher survival, and (iii) seroconversion to seropositivity was more likely than the reverse. We suggest seropositivity affects survival depending on trade-offs among antibody protection, immunosuppression and virus lethality. Negative effects of seropositivity might be greater on juveniles due to their immature immune system. Also, while RHDV directly affects survival through the hemorrhagic syndrome, MV lack of direct lethal effects means that interactions influencing survival are likely to be more complex. Multi-event modeling allowed us to quantify patterns of host–pathogen dynamics otherwise difficult to discern. Such an approach offers a promising tool to shed light on causative mechanisms. PMID:24708296

Quantifying Factors That Impact Riverbed Dynamic Permeability at a Riverbank Filtration Facility

NASA Astrophysics Data System (ADS)

Ulrich, C.; Hubbard, S. S.; Florsheim, J. L.; Rosenberry, D. O.; Borglin, S. E.; Zhang, Y.; Seymour, D.; Trotta, M.

2012-12-01

Previous modeling studies of the Wohler riverbank filtration system on the Russian River, California suggested that riverbed and aquifer permeability both influence the development of a pumping-induced unsaturated zone below the riverbed, which affects water produced through large radial water-supply collector wells that extend beneath and adjacent to the river. In particular, previous work suggests that riverbed permeability is influenced by interaction between pumping and river stage that is controlled by a downstream temporary inflatable dam during the summer low flow period. We hypothesize that raising the dam may instead lead to deposition of fine-grained sediment and/or accumulation of biota, both of which decrease riverbed permeability in the vicinity of the collector wells. To test this hypothesis, we are monitoring streambed permeability and seepage as a function of river stage and dam operation. We are using multiple methods to monitor the hydrological, sedimentological and geomorphic dynamics, including: seepage meters, sediment traps, cryogenic coring, ground penetrating radar, electrical resistance tomography, riverbed topography, piezometers, and thermistors. Here we discuss the use of this novel suite of methods to quantify dynamic riverbed permeability, how it relates to dam operation, and determine the key controls on permeability (i.e., biotic or abiotic). These results are expected to improve the overall understanding of riverbed permeability dynamics associated with Riverbank filtration. The results are also expected to be transferable to the project sponsors, the Sonoma County Water Agency, toward the development of an optimal pumping and dam operation schedule.

Graph distance for complex networks

NASA Astrophysics Data System (ADS)

Shimada, Yutaka; Hirata, Yoshito; Ikeguchi, Tohru; Aihara, Kazuyuki

2016-10-01

Networks are widely used as a tool for describing diverse real complex systems and have been successfully applied to many fields. The distance between networks is one of the most fundamental concepts for properly classifying real networks, detecting temporal changes in network structures, and effectively predicting their temporal evolution. However, this distance has rarely been discussed in the theory of complex networks. Here, we propose a graph distance between networks based on a Laplacian matrix that reflects the structural and dynamical properties of networked dynamical systems. Our results indicate that the Laplacian-based graph distance effectively quantifies the structural difference between complex networks. We further show that our approach successfully elucidates the temporal properties underlying temporal networks observed in the context of face-to-face human interactions.

Multiscale modeling of sickle anemia blood blow by Dissipative Partice Dynamics

NASA Astrophysics Data System (ADS)

Lei, Huan; Caswell, Bruce; Karniadakis, George

2011-11-01

A multi-scale model for sickle red blood cell is developed based on Dissipative Particle Dynamics (DPD). Different cell morphologies (sickle, granular, elongated shapes) typically observed in in vitro and in vivo are constructed and the deviations from the biconcave shape is quantified by the Asphericity and Elliptical shape factors. The rheology of sickle blood is studied in both shear and pipe flow systems. The flow resistance obtained from both systems exhibits a larger value than the healthy blood flow due to the abnormal cell properties. However, the vaso-occulusion phenomenon, reported in a recent microfluid experiment, is not observed in the pipe flow system unless the adhesive interactions between sickle blood cells and endothelium properly introduced into the model.

The influence of rail surface irregularities on contact forces and local stresses

NASA Astrophysics Data System (ADS)

Andersson, Robin; Torstensson, Peter T.; Kabo, Elena; Larsson, Fredrik

2015-01-01

The effect of initial rail surface irregularities on promoting further surface degradation is investigated. The study concerns rolling contact fatigue formation, in particular in the form of the so-called squats. The impact of surface irregularities in the form of dimples is quantified by peak magnitudes of dynamic contact stresses and contact forces. To this end simulations of two-dimensional (later extended to three-dimensional) vertical dynamic vehicle-track interaction are employed. The most influencing parameters are identified. It is shown that even very shallow dimples might have a large impact on local contact stresses. Peak magnitudes of contact forces and stresses due to the influence of rail dimples are shown to exceed those due to rail corrugation.

Flow-induced Flutter of Heart Valves: Experiments with Canonical Models

NASA Astrophysics Data System (ADS)

Dou, Zhongwang; Seo, Jung-Hee; Mittal, Rajat

2017-11-01

For the better understanding of hemodynamics associated with valvular function in health and disease, the flow-induced flutter of heart valve leaflets is studied using benchtop experiments with canonical valve models. A simple experimental model with flexible leaflets is constructed and a pulsatile pump drives the flow through the leaflets. We quantify the leaflet dynamics using digital image analysis and also characterize the dynamics of the flow around the leaflets using particle imaging velocimetry. Experiments are conducted over a wide range of flow and leaflet parameters and data curated for use as a benchmark for validation of computational fluid-structure interaction models. The authors would like to acknowledge Supported from NSF Grants IIS-1344772, CBET-1511200 and NSF XSEDE Grant TG-CTS100002.

Tropical Storm Kyle (2002) and cold-air damming: their interactions and impacts on heavy rainfall in the Carolinas

NASA Astrophysics Data System (ADS)

Garcia-Rivera, Jose M.; Lin, Yuh-Lang; Rastigejev, Yevgenii

2016-06-01

The interactions between an Appalachian cold-air damming event and the near passage of Tropical Storm Kyle (2002) along the coastal Carolinas are assessed by using a numerical weather prediction model. As the storm moved along the coastline, it began extra-tropical transition, bringing heavy rains to both the coastal region and inland towards the Piedmont of North Carolina. Our goal is to quantify the effects of both interacting weather systems on heavy precipitation to improve the dynamical understanding of such effects, as well as precipitation forecasts in the study region. A series of sensitivity tests were performed to isolate and quantify the effects of both systems on the total accumulated precipitation. It was found that (a) for this type of along-coast track, the pre-existing cold-air damming played only a minor role on the total accumulated precipitation, (b) the outer circulation of Kyle weakened the cold-air damming due to a redirection of the mean flow away from the east side of the Appalachian Mountains, and (c) the combination of Kyle with a shortwave mid- to upper-level trough and a surface coastal front were responsible for the heavy precipitation experienced in the study area through the advection of moisture, vorticity, and the forcing of upward motion.

Challenges and opportunities for quantifying roots and rhizosphere interactions through imaging and image analysis.

PubMed

Downie, H F; Adu, M O; Schmidt, S; Otten, W; Dupuy, L X; White, P J; Valentine, T A

2015-07-01

The morphology of roots and root systems influences the efficiency by which plants acquire nutrients and water, anchor themselves and provide stability to the surrounding soil. Plant genotype and the biotic and abiotic environment significantly influence root morphology, growth and ultimately crop yield. The challenge for researchers interested in phenotyping root systems is, therefore, not just to measure roots and link their phenotype to the plant genotype, but also to understand how the growth of roots is influenced by their environment. This review discusses progress in quantifying root system parameters (e.g. in terms of size, shape and dynamics) using imaging and image analysis technologies and also discusses their potential for providing a better understanding of root:soil interactions. Significant progress has been made in image acquisition techniques, however trade-offs exist between sample throughput, sample size, image resolution and information gained. All of these factors impact on downstream image analysis processes. While there have been significant advances in computation power, limitations still exist in statistical processes involved in image analysis. Utilizing and combining different imaging systems, integrating measurements and image analysis where possible, and amalgamating data will allow researchers to gain a better understanding of root:soil interactions. © 2014 John Wiley & Sons Ltd.

A fluorescence study of the molecular interactions of harmane with the nucleobases, their nucleosides and mononucleotides.

PubMed

Balón, M; Muñoz, M A; Carmona, C; Guardado, P; Galán, M

1999-07-19

Fluorescence binding studies of harmane to the elemental components of the nucleic acids were undertaken to investigate the origin of the interaction between the drug and DNA. Most of the tested substrates have been found to induce hypochromism in the absorption spectrum of harmane and to quench its fluorescence. The quenching process induced by the nucleobases and their nucleosides is mainly due to the formation of ground state 1:1 complexes. However, in the case of the mononucleotides a dynamic quenching component is also observed. This quenching component is likely due to the excited state interaction of harmane with the phosphate group of the nucleotides. UV-vis spectral changes and quenching measurements have been used to quantify the ground state association constants of the complexes and the quenching rate constants.

Live-cell imaging reveals the dynamics of PRC2 and recruitment to chromatin by SUZ12-associated subunits.

PubMed

Youmans, Daniel T; Schmidt, Jens C; Cech, Thomas R

2018-06-01

Polycomb-repressive complex 2 (PRC2) is a histone methyltransferase that promotes epigenetic gene silencing, but the dynamics of its interactions with chromatin are largely unknown. Here we quantitatively measured the binding of PRC2 to chromatin in human cancer cells. Genome editing of a HaloTag into the endogenous EZH2 and SUZ12 loci and single-particle tracking revealed that ∼80% of PRC2 rapidly diffuses through the nucleus, while ∼20% is chromatin-bound. Short-term treatment with a small molecule inhibitor of the EED-H3K27me3 interaction had no immediate effect on the chromatin residence time of PRC2. In contrast, separation-of-function mutants of SUZ12, which still form the core PRC2 complex but cannot bind accessory proteins, revealed a major contribution of AEBP2 and PCL homolog proteins to chromatin binding. We therefore quantified the dynamics of this chromatin-modifying complex in living cells and separated the contributions of H3K27me3 histone marks and various PRC2 subunits to recruitment of PRC2 to chromatin. © 2018 Youmans et al.; Published by Cold Spring Harbor Laboratory Press.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rameau, J. D.; Freutel, S.; Kemper, A. F.

We report that in complex materials various interactions have important roles in determining electronic properties. Angle-resolved photoelectron spectroscopy (ARPES) is used to study these processes by resolving the complex single-particle self-energy and quantifying how quantum interactions modify bare electronic states. However, ambiguities in the measurement of the real part of the self-energy and an intrinsic inability to disentangle various contributions to the imaginary part of the self-energy can leave the implications of such measurements open to debate. Here we employ a combined theoretical and experimental treatment of femtosecond time-resolved ARPES (tr-ARPES) show how population dynamics measured using tr-ARPES can bemore » used to separate electron–boson interactions from electron–electron interactions. In conclusion, we demonstrate a quantitative analysis of a well-defined electron–boson interaction in the unoccupied spectrum of the cuprate Bi 2Sr 2CaCu 2O 8+x characterized by an excited population decay time that maps directly to a discrete component of the equilibrium self-energy not readily isolated by static ARPES experiments.« less

Synchronous dynamics of zooplankton competitors prevail in temperate lake ecosystems.

PubMed

Vasseur, David A; Fox, Jeremy W; Gonzalez, Andrew; Adrian, Rita; Beisner, Beatrix E; Helmus, Matthew R; Johnson, Catherine; Kratina, Pavel; Kremer, Colin; de Mazancourt, Claire; Miller, Elizabeth; Nelson, William A; Paterson, Michael; Rusak, James A; Shurin, Jonathan B; Steiner, Christopher F

2014-08-07

Although competing species are expected to exhibit compensatory dynamics (negative temporal covariation), empirical work has demonstrated that competitive communities often exhibit synchronous dynamics (positive temporal covariation). This has led to the suggestion that environmental forcing dominates species dynamics; however, synchronous and compensatory dynamics may appear at different length scales and/or at different times, making it challenging to identify their relative importance. We compiled 58 long-term datasets of zooplankton abundance in north-temperate and sub-tropical lakes and used wavelet analysis to quantify general patterns in the times and scales at which synchronous/compensatory dynamics dominated zooplankton communities in different regions and across the entire dataset. Synchronous dynamics were far more prevalent at all scales and times and were ubiquitous at the annual scale. Although we found compensatory dynamics in approximately 14% of all combinations of time period/scale/lake, there were no consistent scales or time periods during which compensatory dynamics were apparent across different regions. Our results suggest that the processes driving compensatory dynamics may be local in their extent, while those generating synchronous dynamics operate at much larger scales. This highlights an important gap in our understanding of the interaction between environmental and biotic forces that structure communities. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Understanding neuromotor strategy during functional upper extremity tasks using symbolic dynamics.

PubMed

Nathan, Dominic E; Guastello, Stephen J; Prost, Robert W; Jeutter, Dean C

2012-01-01

The ability to model and quantify brain activation patterns that pertain to natural neuromotor strategy of the upper extremities during functional task performance is critical to the development of therapeutic interventions such as neuroprosthetic devices. The mechanisms of information flow, activation sequence and patterns, and the interaction between anatomical regions of the brain that are specific to movement planning, intention and execution of voluntary upper extremity motor tasks were investigated here. This paper presents a novel method using symbolic dynamics (orbital decomposition) and nonlinear dynamic tools of entropy, self-organization and chaos to describe the underlying structure of activation shifts in regions of the brain that are involved with the cognitive aspects of functional upper extremity task performance. Several questions were addressed: (a) How is it possible to distinguish deterministic or causal patterns of activity in brain fMRI from those that are really random or non-contributory to the neuromotor control process? (b) Can the complexity of activation patterns over time be quantified? (c) What are the optimal ways of organizing fMRI data to preserve patterns of activation, activation levels, and extract meaningful temporal patterns as they evolve over time? Analysis was performed using data from a custom developed time resolved fMRI paradigm involving human subjects (N=18) who performed functional upper extremity motor tasks with varying time delays between the onset of intention and onset of actual movements. The results indicate that there is structure in the data that can be quantified through entropy and dimensional complexity metrics and statistical inference, and furthermore, orbital decomposition is sensitive in capturing the transition of states that correlate with the cognitive aspects of functional task performance.

Capturing change: the duality of time-lapse imagery to acquire data and depict ecological dynamics

USGS Publications Warehouse

Brinley Buckley, Emma M.; Allen, Craig R.; Forsberg, Michael; Farrell, Michael; Caven, Andrew J.

2017-01-01

We investigate the scientific and communicative value of time-lapse imagery by exploring applications for data collection and visualization. Time-lapse imagery has a myriad of possible applications to study and depict ecosystems and can operate at unique temporal and spatial scales to bridge the gap between large-scale satellite imagery projects and observational field research. Time-lapse data sequences, linking time-lapse imagery with data visualization, have the ability to make data come alive for a wider audience by connecting abstract numbers to images that root data in time and place. Utilizing imagery from the Platte Basin Timelapse Project, water inundation and vegetation phenology metrics are quantified via image analysis and then paired with passive monitoring data, including streamflow and water chemistry. Dynamic and interactive time-lapse data sequences elucidate the visible and invisible ecological dynamics of a significantly altered yet internationally important river system in central Nebraska.

Four-time 7Li stimulated-echo spectroscopy for the study of dynamic heterogeneities: Application to lithium borate glass.

PubMed

Storek, M; Tilly, J F; Jeffrey, K R; Böhmer, R

2017-09-01

To study the nature of the nonexponential ionic hopping in solids a pulse sequence was developed that yields four-time stimulated-echo functions of previously inaccessible spin-3/2-nuclei such as 7 Li. It exploits combined Zeeman and octupolar order as longitudinal carrier state. Higher-order correlation functions were successfully generated for natural-abundance and isotopically-enriched lithium diborate glasses. Four-time 7 Li measurements are presented and compared with two-time correlation functions. The results are discussed with reference to approaches devised to quantify the degree of nonexponentiality in glass forming systems and evidence for the occurrence of dynamic heterogeneities and dynamic exchange were found. Additional experiments using the 6 Li species illustrate the challenge posed by subensemble selection when the dipolar interactions are not very much smaller than the quadrupolar ones. Copyright © 2017 Elsevier Inc. All rights reserved.

Modelling tooth–prey interactions in sharks: the importance of dynamic testing

PubMed Central

Farina, Stacy C.; Brash, Jeffrey; Summers, Adam P.

2016-01-01

The shape of shark teeth varies among species, but traditional testing protocols have revealed no predictive relationship between shark tooth morphology and performance. We developed a dynamic testing device to quantify cutting performance of teeth. We mimicked head-shaking behaviour in feeding large sharks by attaching teeth to the blade of a reciprocating power saw fixed in a custom-built frame. We tested three tooth types at biologically relevant speeds and found differences in tooth cutting ability and wear. Teeth from the bluntnose sixgill (Hexanchus griseus) showed poor cutting ability compared with tiger (Galeocerdo cuvier), sandbar (Carcharhinus plumbeus) and silky (C. falciformis) sharks, but they also showed no wear with repeated use. Some shark teeth are very sharp at the expense of quickly dulling, while others are less sharp but dull more slowly. This demonstrates that dynamic testing is vital to understanding the performance of shark teeth. PMID:27853592

The impact of future forest dynamics on climate: interactive effects of changing vegetation and disturbance regimes.

PubMed

Thom, Dominik; Rammer, Werner; Seidl, Rupert

2017-11-01

Currently, the temperate forest biome cools the earth's climate and dampens anthropogenic climate change. However, climate change will substantially alter forest dynamics in the future, affecting the climate regulation function of forests. Increasing natural disturbances can reduce carbon uptake and evaporative cooling, but at the same time increase the albedo of a landscape. Simultaneous changes in vegetation composition can mitigate disturbance impacts, but also influence climate regulation directly (e.g., via albedo changes). As a result of a number of interactive drivers (changes in climate, vegetation, and disturbance) and their simultaneous effects on climate-relevant processes (carbon exchange, albedo, latent heat flux) the future climate regulation function of forests remains highly uncertain. Here we address these complex interactions to assess the effect of future forest dynamics on the climate system. Our specific objectives were (1) to investigate the long-term interactions between changing vegetation composition and disturbance regimes under climate change, (2) to quantify the response of climate regulation to changes in forest dynamics, and (3) to identify the main drivers of the future influence of forests on the climate system. We investigated these issues using the individual-based forest landscape and disturbance model (iLand). Simulations were run over 200 yr for Kalkalpen National Park (Austria), assuming different future climate projections, and incorporating dynamically responding wind and bark beetle disturbances. To consistently assess the net effect on climate the simulated responses of carbon exchange, albedo, and latent heat flux were expressed as contributions to radiative forcing. We found that climate change increased disturbances (+27.7% over 200 yr) and specifically bark beetle activity during the 21st century. However, negative feedbacks from a simultaneously changing tree species composition (+28.0% broadleaved species) decreased disturbance activity in the long run (-10.1%), mainly by reducing the host trees available for bark beetles. Climate change and the resulting future forest dynamics significantly reduced the climate regulation function of the landscape, increasing radiative forcing by up to +10.2% on average over 200 yr. Overall, radiative forcing was most strongly driven by carbon exchange. We conclude that future changes in forest dynamics can cause amplifying climate feedbacks from temperate forest ecosystems.

FDNS CFD Code Benchmark for RBCC Ejector Mode Operation: Continuing Toward Dual Rocket Effects

NASA Technical Reports Server (NTRS)

West, Jeff; Ruf, Joseph H.; Turner, James E. (Technical Monitor)

2000-01-01

Computational Fluid Dynamics (CFD) analysis results are compared with benchmark quality test data from the Propulsion Engineering Research Center's (PERC) Rocket Based Combined Cycle (RBCC) experiments to verify fluid dynamic code and application procedures. RBCC engine flowpath development will rely on CFD applications to capture the multi -dimensional fluid dynamic interactions and to quantify their effect on the RBCC system performance. Therefore, the accuracy of these CFD codes must be determined through detailed comparisons with test data. The PERC experiments build upon the well-known 1968 rocket-ejector experiments of Odegaard and Stroup by employing advanced optical and laser based diagnostics to evaluate mixing and secondary combustion. The Finite Difference Navier Stokes (FDNS) code [2] was used to model the fluid dynamics of the PERC RBCC ejector mode configuration. Analyses were performed for the Diffusion and Afterburning (DAB) test conditions at the 200-psia thruster operation point, Results with and without downstream fuel injection are presented.

Modulator Dynamics Shape the Design Space for Stepwise-Elution Simulated Moving Bed Chromatographic Separations.

PubMed

Wayne, Chris J; Velayudhan, Ajoy

2018-03-31

For proteins and other biological macromolecules, SMB chromatography is best operated non-isocratically. However, traditional modes of non-isocratic SMB operation generate significant mobile-phase modulator dynamics. The mechanisms by which these modulator dynamics affect a separation's success, and thus frame the design space, have yet to be explained quantitatively. Here, the dynamics of the modulator (e.g., salts in ion exchange and hydrophobic interaction chromatography) are explicitly accounted for. This leads to the elucidation of two new design constraints, presented as dimensionless numbers, which quantify the effects of the modulator phenomena and thus predict the success of a non-isocratic SMB separation. Consequently, these two new design constraints re-define the SMB design space. Computational and experimental studies at the boundaries of this design space corroborate the theoretical predictions. The design of efficient and robust operating conditions through use of the new design space is also demonstrated. © 2018 The Authors. Biotechnology Journal Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cycle-expansion method for the Lyapunov exponent, susceptibility, and higher moments.

PubMed

Charbonneau, Patrick; Li, Yue Cathy; Pfister, Henry D; Yaida, Sho

2017-09-01

Lyapunov exponents characterize the chaotic nature of dynamical systems by quantifying the growth rate of uncertainty associated with the imperfect measurement of initial conditions. Finite-time estimates of the exponent, however, experience fluctuations due to both the initial condition and the stochastic nature of the dynamical path. The scale of these fluctuations is governed by the Lyapunov susceptibility, the finiteness of which typically provides a sufficient condition for the law of large numbers to apply. Here, we obtain a formally exact expression for this susceptibility in terms of the Ruelle dynamical ζ function for one-dimensional systems. We further show that, for systems governed by sequences of random matrices, the cycle expansion of the ζ function enables systematic computations of the Lyapunov susceptibility and of its higher-moment generalizations. The method is here applied to a class of dynamical models that maps to static disordered spin chains with interactions stretching over a varying distance and is tested against Monte Carlo simulations.

Quantifying Subsurface Water and Heat Distribution and its Linkage with Landscape Properties in Terrestrial Environment using Hydro-Thermal-Geophysical Monitoring and Coupled Inverse Modeling

NASA Astrophysics Data System (ADS)

Dafflon, B.; Tran, A. P.; Wainwright, H. M.; Hubbard, S. S.; Peterson, J.; Ulrich, C.; Williams, K. H.

2015-12-01

Quantifying water and heat fluxes in the subsurface is crucial for managing water resources and for understanding the terrestrial ecosystem where hydrological properties drive a variety of biogeochemical processes across a large range of spatial and temporal scales. Here, we present the development of an advanced monitoring strategy where hydro-thermal-geophysical datasets are continuously acquired and further involved in a novel inverse modeling framework to estimate the hydraulic and thermal parameter that control heat and water dynamics in the subsurface and further influence surface processes such as evapotranspiration and vegetation growth. The measured and estimated soil properties are also used to investigate co-interaction between subsurface and surface dynamics by using above-ground aerial imaging. The value of this approach is demonstrated at two different sites, one in the polygonal shaped Arctic tundra where water and heat dynamics have a strong impact on freeze-thaw processes, vegetation and biogeochemical processes, and one in a floodplain along the Colorado River where hydrological fluxes between compartments of the system (surface, vadose zone and groundwater) drive biogeochemical transformations. Results show that the developed strategy using geophysical, point-scale and aerial measurements is successful to delineate the spatial distribution of hydrostratigraphic units having distinct physicochemical properties, to monitor and quantify in high resolution water and heat distribution and its linkage with vegetation, geomorphology and weather conditions, and to estimate hydraulic and thermal parameters for enhanced predictions of water and heat fluxes as well as evapotranspiration. Further, in the Colorado floodplain, results document the potential presence of only periodic infiltration pulses as a key hot moment controlling soil hydro and biogeochemical functioning. In the arctic, results show the strong linkage between soil water content, thermal parameters, thaw layer thickness and vegetation distribution. Overall, results of these efforts demonstrate the value of coupling various datasets at high spatial and temporal resolution to improve predictive understanding of subsurface and surface dynamics.

Multiparametric Imaging of Organ System Interfaces

PubMed Central

Vandoorne, Katrien; Nahrendorf, Matthias

2017-01-01

Cardiovascular diseases are a consequence of genetic and environmental risk factors that together generate arterial wall and cardiac pathologies. Blood vessels connect multiple systems throughout the entire body and allow organs to interact via circulating messengers. These same interactions facilitate nervous and metabolic system influence on cardiovascular health. Multiparametric imaging offers the opportunity to study these interfacing systems’ distinct processes, to quantify their interactions and to explore how these contribute to cardiovascular disease. Noninvasive multiparametric imaging techniques are emerging tools that can further our understanding of this complex and dynamic interplay. PET/MRI and multichannel optical imaging are particularly promising because they can simultaneously sample multiple biomarkers. Preclinical multiparametric diagnostics could help discover clinically relevant biomarker combinations pivotal for understanding cardiovascular disease. Interfacing systems important to cardiovascular disease include the immune, nervous and hematopoietic systems. These systems connect with ‘classical’ cardiovascular organs, like the heart and vasculature, and with the brain. The dynamic interplay between these systems and organs enables processes such as hemostasis, inflammation, angiogenesis, matrix remodeling, metabolism and fibrosis. As the opportunities provided by imaging expand, mapping interconnected systems will help us decipher the complexity of cardiovascular disease and monitor novel therapeutic strategies. PMID:28360260

Networks of energetic and metabolic interactions define dynamics in microbial communities.

PubMed

Embree, Mallory; Liu, Joanne K; Al-Bassam, Mahmoud M; Zengler, Karsten

2015-12-15

Microorganisms form diverse communities that have a profound impact on the environment and human health. Recent technological advances have enabled elucidation of community diversity at high resolution. Investigation of microbial communities has revealed that they often contain multiple members with complementing and seemingly redundant metabolic capabilities. An understanding of the communal impacts of redundant metabolic capabilities is currently lacking; specifically, it is not known whether metabolic redundancy will foster competition or motivate cooperation. By investigating methanogenic populations, we identified the multidimensional interspecies interactions that define composition and dynamics within syntrophic communities that play a key role in the global carbon cycle. Species-specific genomes were extracted from metagenomic data using differential coverage binning. We used metabolic modeling leveraging metatranscriptomic information to reveal and quantify a complex intertwined system of syntrophic relationships. Our results show that amino acid auxotrophies create additional interdependencies that define community composition and control carbon and energy flux through the system while simultaneously contributing to overall community robustness. Strategic use of antimicrobials further reinforces this intricate interspecies network. Collectively, our study reveals the multidimensional interactions in syntrophic communities that promote high species richness and bolster community stability during environmental perturbations.

An optimal control framework for dynamic induction control of wind farms and their interaction with the atmospheric boundary layer.

PubMed

Munters, W; Meyers, J

2017-04-13

Complex turbine wake interactions play an important role in overall energy extraction in large wind farms. Current control strategies optimize individual turbine power, and lead to significant energy losses in wind farms compared with lone-standing wind turbines. In recent work, an optimal coordinated control framework was introduced (Goit & Meyers 2015 J. Fluid Mech. 768 , 5-50 (doi:10.1017/jfm.2015.70)). Here, we further elaborate on this framework, quantify the influence of optimization parameters and introduce new simulation results for which gains in power production of up to 21% are observed.This article is part of the themed issue 'Wind energy in complex terrains'. © 2017 The Authors.

An optimal control framework for dynamic induction control of wind farms and their interaction with the atmospheric boundary layer

PubMed Central

Munters, W.

2017-01-01

Complex turbine wake interactions play an important role in overall energy extraction in large wind farms. Current control strategies optimize individual turbine power, and lead to significant energy losses in wind farms compared with lone-standing wind turbines. In recent work, an optimal coordinated control framework was introduced (Goit & Meyers 2015 J. Fluid Mech. 768, 5–50 (doi:10.1017/jfm.2015.70)). Here, we further elaborate on this framework, quantify the influence of optimization parameters and introduce new simulation results for which gains in power production of up to 21% are observed. This article is part of the themed issue ‘Wind energy in complex terrains’. PMID:28265024

Entrainment-Zone Restratification and Flow Structures in Stratified Shear Turbulence

NASA Technical Reports Server (NTRS)

Reif, B. Anders Pettersson; Werne, Joseph; Andreassen, Oyvind; Meyer, Christian; Davis-Mansour, Melissa

2002-01-01

Late-time dynamics and morphology of a stratified turbulent shear layer are examined using 1) Reynolds-stress and heat-flux budgets, 2) the single-point structure tensors introduced by Kassinos et al. (2001), and 3) flow visualization via 3D volume rendering. Flux reversal is observed during restratification in the edges of the turbulent layer. We present a first attempt to quantify the turbulence-mean-flow interaction and to characterize the predominant flow structures. Future work will extend this analysis to earlier times and different values of the Reynolds and Richardson numbers.

Quantitative Boltzmann-Gibbs Principles via Orthogonal Polynomial Duality

NASA Astrophysics Data System (ADS)

Ayala, Mario; Carinci, Gioia; Redig, Frank

2018-06-01

We study fluctuation fields of orthogonal polynomials in the context of particle systems with duality. We thereby obtain a systematic orthogonal decomposition of the fluctuation fields of local functions, where the order of every term can be quantified. This implies a quantitative generalization of the Boltzmann-Gibbs principle. In the context of independent random walkers, we complete this program, including also fluctuation fields in non-stationary context (local equilibrium). For other interacting particle systems with duality such as the symmetric exclusion process, similar results can be obtained, under precise conditions on the n particle dynamics.

Analysis and prediction of pest dynamics in an agroforestry context using Tiko'n, a generic tool to develop food web models

NASA Astrophysics Data System (ADS)

Rojas, Marcela; Malard, Julien; Adamowski, Jan; Carrera, Jaime Luis; Maas, Raúl

2017-04-01

While it is known that climate change will impact future plant-pest population dynamics, potentially affecting crop damage, agroforestry with its enhanced biodiversity is said to reduce the outbreaks of pest insects by providing natural enemies for the control of pest populations. This premise is known in the literature as the natural enemy hypothesis and has been widely studied qualitatively. However, disagreement still exists on whether biodiversity enhancement reduces pest outbreaks, showing the need of quantitatively understanding the mechanisms behind the interactions between pests and natural enemies, also known as trophic interactions. Crop pest models that study insect population dynamics in agroforestry contexts are very rare, and pest models that take trophic interactions into account are even rarer. This may be due to the difficulty of representing complex food webs in a quantifiable model. There is therefore a need for validated food web models that allow users to predict the response of these webs to changes in climate in agroforestry systems. In this study we present Tiko'n, a Python-based software whose API allows users to rapidly build and validate trophic web models; the program uses a Bayesian inference approach to calibrate the models according to field data, allowing for the reuse of literature data from various sources and reducing the need for extensive field data collection. Tiko'n was run using coffee leaf miner (Leucoptera coffeella) and associated parasitoid data from a shaded coffee plantation, showing the mechanisms of insect population dynamics within a tri-trophic food web in an agroforestry system.

Transport induced by mean-eddy interaction: I. Theory, and relation to Lagrangian lobe dynamics

NASA Astrophysics Data System (ADS)

Ide, Kayo; Wiggins, Stephen

2015-02-01

In this paper we develop a method for the estimation of Transport Induced by the Mean-Eddy interaction (TIME) in two-dimensional unsteady flows. The method is based on the dynamical systems approach to fluid transport and can be viewed as a hybrid combination of Lagrangian and Eulerian methods. The (Eulerian) boundaries across which we consider (Lagrangian) transport are kinematically defined by appropriately chosen streamlines of the mean flow. By evaluating the impact of the mean-eddy interaction on transport, the TIME method can be used as a diagnostic tool for transport processes that occur during a specified time interval along a specified boundary segment. We introduce two types of TIME functions: one that quantifies the accumulation of flow properties and another that measures the displacement of the transport geometry. The spatial geometry of transport is described by the so-called pseudo-lobes, and temporal evolution of transport by their dynamics. In the case where the TIME functions are evaluated along a separatrix, the pseudo-lobes have a relationship to the lobes of Lagrangian transport theory. In fact, one of the TIME functions is identical to the Melnikov function that is used to measure the distance, at leading order in a small parameter, between the two invariant manifolds that define the Lagrangian lobes. We contrast the similarities and differences between the TIME and Lagrangian lobe dynamics in detail. An application of the TIME method is carried out for inter-gyre transport in the wind-driven oceanic circulation model and a comparison with the Lagrangian transport theory is made.

Carbon Nanotubes in Water: MD Simulations of Internal and External Flow, Self Organization

NASA Technical Reports Server (NTRS)

Jaffe, Richard L.; Halicioglu, Timur; Werder, Thomas; Walther, Jens; Koumoutsakos, Petros; Arnold, James (Technical Monitor)

2001-01-01

We have developed computational tools, based on particle codes, for molecular dynamics (MD) simulation of carbon nanotubes (CNT) in aqueous environments. The interaction of CNTs with water is envisioned as a prototype for the design of engineering nano-devices, such as artificial sterocillia and molecular biosensors. Large scale simulations involving thousands of water molecules are possible due to our efficient parallel MD code that takes long range electrostatic interactions into account. Since CNTs can be considered as rolled up sheets of graphite, we expect the CNT-water interaction to be similar to the interaction of graphite with water. However, there are fundamental differences between considering graphite and CNTs, since the curvature of CNTs affects their chemical activity and also since capillary effects play an important role for both dynamic and static behaviour of materials inside CNTs. In recent studies Gordillo and Marti described the hydrogen bond structure as well as time dependent properties of water confined in CNTs. We are presenting results from the development of force fields describing the interaction of CNTs and water based on ab-initio quantum mechanical calculations. Furthermore, our results include both water flows external to CNTs and the behaviour of water nanodroplets inside heated CNTs. In the first case (external flows) the hydrophobic behaviour of CNTs is quantified and we analyze structural properties of water in the vicinity of CNTs with diagnostics such as hydrogen bond distribution, water dipole orientation and radial distribution functions. The presence of water leads to attractive forces between CNTs as a result of their hydrophobicity. Through extensive simulations we quantify these attractive forces in terms of the number and separation of the CNT. Results of our simulations involving arrays of CNTs indicate that these exhibit a hydrophobic behaviour that leads to self-organising structures capable of trapping water clusters. In the second case (internal flows) we study the behaviour of water droplets confined inside CNTs. Constant temperature simulations allow us to capture structural properties such as the contact angles and density profiles of the equilibrated drops. By heating and subsequently cooling of the CNT, we are able to measure the evaporation and the condensation rate of the entrapped water.

The Role of Water in the Stability of Wild Type and Mutant Insulin Dimers.

PubMed

Raghunathan, Shampa; El Hage, Krystel; Desmond, Jasmine; Zhang, Lixian; Meuwly, Markus

2018-06-19

Insulin dimerization and aggregation play important roles in the endogenous delivery of the hormone. One of the important residues at the insulin dimer interface is Phe B24 which is an invariant aromatic anchor that packs towards its own monomer inside a hydrophobic cavity formed by Val B12 , Leu B15 , Tyr B16 , Cys B19 and Tyr B26 . Using molecular dynamics and free energy simulations in explicit solvent, the structural and dynamical consequences of mutations of Phe at position B24 to Gly, Ala, and d-Ala and the des-PheB25 variant are quantified. Consistent with experiments it is found that the Gly and Ala modifications lead to insulin dimers with reduced stability by 4 and 5 kcal/mol from thermodynamic integration and 4 and 8 kcal/mol from results using MM-GBSA, respectively. Given the experimental difficulties to quantify the thermodynamic stability of modified insulin dimers, such computations provide a valuable complement. Interestingly, the Gly-mutant exists as a strongly and a weakly interacting dimer. Analysis of the molecular dynamics simulations shows that this can be explained by water molecules that replace direct monomer-monomer H-bonding contacts at the dimerization interface involving residues B24 to B26. It is concluded that such solvent molecules play an essential role and must be included in future insulin dimerization studies.

Oceanic biogeochemical controls on global dynamics of persistent organic pollutants.

PubMed

Dachs, Jordi; Lohmann, Rainer; Ockenden, Wendy A; Méjanelle, Laurence; Eisenreich, Steven J; Jones, Kevin C

2002-10-15

Understanding and quantifying the global dynamics and sinks of persistent organic pollutants (POPs) is important to assess their environmental impact and fate. Air-surface exchange processes, where temperature plays a central role in controlling volatilization and deposition, are of key importance in controlling global POP dynamics. The present study is an assessment of the role of oceanic biogeochemical processes, notably phytoplankton uptake and vertical fluxes of particles, on the global dynamics of POPs. Field measurements of atmospheric polychlorinated biphenyls (PCBs), polychlorinated dibenzodioxins (PCDDs), and furans (PCDFs) are combined with remote sensing estimations of oceanic temperature, wind speed, and chlorophyll, to model the interactions between air-water exchange, phytoplankton uptake, and export of organic matter and POPs out of the mixed surface ocean layer. Deposition is enhanced in the mid-high latitudes and is driven by sinking marine particulate matter, rather than by a cold condensation effect. However, the relative contribution of the biological pump is a function of the physical-chemical properties of POPs. It is concluded that oceanic biogeochemical processes play a critical role in controlling the global dynamics and the ultimate sink of POPs.

Rotation of Guanine Amino Groups in G-Quadruplexes: A Probe for Local Structure and Ligand Binding.

PubMed

Adrian, Michael; Winnerdy, Fernaldo Richtia; Heddi, Brahim; Phan, Anh Tuân

2017-08-22

Nucleic acids are dynamic molecules whose functions may depend on their conformational fluctuations and local motions. In particular, amino groups are dynamic components of nucleic acids that participate in the formation of various secondary structures such as G-quadruplexes. Here, we present a cost-efficient NMR method to quantify the rotational dynamics of guanine amino groups in G-quadruplex nucleic acids. An isolated spectrum of amino protons from a specific tetrad-bound guanine can be extracted from the nuclear Overhauser effect spectroscopy spectrum based on the close proximity between the intra-residue imino and amino protons. We apply the method in different structural contexts of G-quadruplexes and their complexes. Our results highlight the role of stacking and hydrogen-bond interactions in restraining amino-group rotation. The measurement of the rotation rate of individual amino groups could give insight into the dynamic processes occurring at specific locations within G-quadruplex nucleic acids, providing valuable probes for local structure, dynamics, and ligand binding. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Non-invasive measurement of instantaneous forces during aquatic locomotion: a case study of the bluegill sunfish pectoral fin.

PubMed

Peng, Jifeng; Dabiri, John O; Madden, Peter G; Lauder, George V

2007-02-01

Swimming and flying animals generate unsteady locomotive forces by delivering net momentum into the fluid wake. Hence, swimming and flying forces can be quantified by measuring the momentum of animal wakes. A recently developed model provides an approach to empirically deduce swimming and flying forces based on the measurement of velocity and vortex added-mass in the animal wake. The model is contingent on the identification of the vortex boundary in the wake. This paper demonstrates the application of that method to a case study quantifying the instantaneous locomotive forces generated by the pectoral fins of the bluegill sunfish (Lepomis macrochirus Rafinesque), measured using digital particle image velocimetry (DPIV). The finite-time Lyapunov exponent (FTLE) field calculated from the DPIV data was used to determine the wake vortex boundary, according to recently developed fluid dynamics theory. Momentum of the vortex wake and its added-mass were determined and the corresponding instantaneous locomotive forces were quantified at discrete time points during the fin stroke. The instantaneous forces estimated in this study agree in magnitude with the time-averaged forces quantified for the pectoral fin of the same species swimming in similar conditions and are consistent with the observed global motion of the animals. A key result of this study is its suggestion that the dynamical effect of the vortex wake on locomotion is to replace the real animal fin with an ;effective appendage', whose geometry is dictated by the FTLE field and whose interaction with the surrounding fluid is wholly dictated by inviscid concepts from potential flow theory. Benefits and limitations of this new framework for non-invasive instantaneous force measurement are discussed, and its application to comparative biomechanics and engineering studies is suggested.

Dynamics of Marine Microbial Metabolism and Physiology at Station ALOHA

NASA Astrophysics Data System (ADS)

Casey, John R.

Marine microbial communities influence global biogeochemical cycles by coupling the transduction of free energy to the transformation of Earth's essential bio-elements: H, C, N, O, P, and S. The web of interactions between these processes is extraordinarily complex, though fundamental physical and thermodynamic principles should describe its dynamics. In this collection of 5 studies, aspects of the complexity of marine microbial metabolism and physiology were investigated as they interact with biogeochemical cycles and direct the flow of energy within the Station ALOHA surface layer microbial community. In Chapter 1, and at the broadest level of complexity discussed, a method to relate cell size to metabolic activity was developed to evaluate allometric power laws at fine scales within picoplankton populations. Although size was predictive of metabolic rates, within-population power laws deviated from the broader size spectrum, suggesting metabolic diversity as a key determinant of microbial activity. In Chapter 2, a set of guidelines was proposed by which organic substrates are selected and utilized by the heterotrophic community based on their nitrogen content, carbon content, and energy content. A hierarchical experimental design suggested that the heterotrophic microbial community prefers high nitrogen content but low energy density substrates, while carbon content was not important. In Chapter 3, a closer look at the light-dependent dynamics of growth on a single organic substrate, glycolate, suggested that growth yields were improved by photoheterotrophy. The remaining chapters were based on the development of a genome-scale metabolic network reconstruction of the cyanobacterium Prochlorococcus to probe its metabolic capabilities and quantify metabolic fluxes. Findings described in Chapter 4 pointed to evolution of the Prochlorococcus metabolic network to optimize growth at low phosphate concentrations. Finally, in Chapter 5 and at the finest scale of complexity, a method was developed to predict hourly changes in both physiology and metabolic fluxes in Prochlorococcus by incorporating gene expression time-series data within the metabolic network model. Growth rates predicted by this method more closely matched experimental data, and diel changes in elemental composition and the energy content of biomass were predicted. Collectively, these studies identify and quantify the potential impact of variations in metabolic and physiological traits on the melee of microbial community interactions.

How spatio-temporal habitat connectivity affects amphibian genetic structure.

PubMed

Watts, Alexander G; Schlichting, Peter E; Billerman, Shawn M; Jesmer, Brett R; Micheletti, Steven; Fortin, Marie-Josée; Funk, W Chris; Hapeman, Paul; Muths, Erin; Murphy, Melanie A

2015-01-01

Heterogeneous landscapes and fluctuating environmental conditions can affect species dispersal, population genetics, and genetic structure, yet understanding how biotic and abiotic factors affect population dynamics in a fluctuating environment is critical for species management. We evaluated how spatio-temporal habitat connectivity influences dispersal and genetic structure in a population of boreal chorus frogs (Pseudacris maculata) using a landscape genetics approach. We developed gravity models to assess the contribution of various factors to the observed genetic distance as a measure of functional connectivity. We selected (a) wetland (within-site) and (b) landscape matrix (between-site) characteristics; and (c) wetland connectivity metrics using a unique methodology. Specifically, we developed three networks that quantify wetland connectivity based on: (i) P. maculata dispersal ability, (ii) temporal variation in wetland quality, and (iii) contribution of wetland stepping-stones to frog dispersal. We examined 18 wetlands in Colorado, and quantified 12 microsatellite loci from 322 individual frogs. We found that genetic connectivity was related to topographic complexity, within- and between-wetland differences in moisture, and wetland functional connectivity as contributed by stepping-stone wetlands. Our results highlight the role that dynamic environmental factors have on dispersal-limited species and illustrate how complex asynchronous interactions contribute to the structure of spatially-explicit metapopulations.

Quantifying the dilution effect for models in ecological epidemiology.

PubMed

Roberts, M G; Heesterbeek, J A P

2018-03-01

The dilution effect , where an increase in biodiversity results in a reduction in the prevalence of an infectious disease, has been the subject of speculation and controversy. Conversely, an amplification effect occurs when increased biodiversity is related to an increase in prevalence. We explore the conditions under which these effects arise, using multi species compartmental models that integrate ecological and epidemiological interactions. We introduce three potential metrics for quantifying dilution and amplification, one based on infection prevalence in a focal host species, one based on the size of the infected subpopulation of that species and one based on the basic reproduction number. We introduce our approach in the simplest epidemiological setting with two species, and show that the existence and strength of a dilution effect is influenced strongly by the choices made to describe the system and the metric used to gauge the effect. We show that our method can be generalized to any number of species and to more complicated ecological and epidemiological dynamics. Our method allows a rigorous analysis of ecological systems where dilution effects have been postulated, and contributes to future progress in understanding the phenomenon of dilution in the context of infectious disease dynamics and infection risk. © 2018 The Author(s).

Characterizing hydrophobicity at the nanoscale: a molecular dynamics simulation study.

PubMed

Bandyopadhyay, Dibyendu; Choudhury, Niharendu

2012-06-14

We use molecular dynamics (MD) simulations of water near nanoscopic surfaces to characterize hydrophobic solute-water interfaces. By using nanoscopic paraffin like plates as model solutes, MD simulations in isothermal-isobaric ensemble have been employed to identify characteristic features of such an interface. Enhanced water correlation, density fluctuations, and position dependent compressibility apart from surface specific hydrogen bond distribution and molecular orientations have been identified as characteristic features of such interfaces. Tetrahedral order parameter that quantifies the degree of tetrahedrality in the water structure and an orientational order parameter, which quantifies the orientational preferences of the second solvation shell water around a central water molecule, have also been calculated as a function of distance from the plate surface. In the vicinity of the surface these two order parameters too show considerable sensitivity to the surface hydrophobicity. The potential of mean force (PMF) between water and the surface as a function of the distance from the surface has also been analyzed in terms of direct interaction and induced contribution, which shows unusual effect of plate hydrophobicity on the solvent induced PMF. In order to investigate hydrophobic nature of these plates, we have also investigated interplate dewetting when two such plates are immersed in water.

Predicting community responses to perturbations in the face of imperfect knowledge and network complexity

USGS Publications Warehouse

Novak, Mark; Wootton, J. Timothy; Doak, Daniel F.; Emmerson, Mark; Estes, James A.; Tinker, M. Timothy

2011-01-01

How best to predict the effects of perturbations to ecological communities has been a long-standing goal for both applied and basic ecology. This quest has recently been revived by new empirical data, new analysis methods, and increased computing speed, with the promise that ecologically important insights may be obtainable from a limited knowledge of community interactions. We use empirically based and simulated networks of varying size and connectance to assess two limitations to predicting perturbation responses in multispecies communities: (1) the inaccuracy by which species interaction strengths are empirically quantified and (2) the indeterminacy of species responses due to indirect effects associated with network size and structure. We find that even modest levels of species richness and connectance (∼25 pairwise interactions) impose high requirements for interaction strength estimates because system indeterminacy rapidly overwhelms predictive insights. Nevertheless, even poorly estimated interaction strengths provide greater average predictive certainty than an approach that uses only the sign of each interaction. Our simulations provide guidance in dealing with the trade-offs involved in maximizing the utility of network approaches for predicting dynamics in multispecies communities.

Kinetic Measurements Reveal Enhanced Protein-Protein Interactions at Intercellular Junctions

PubMed Central

Shashikanth, Nitesh; Kisting, Meridith A.; Leckband, Deborah E.

2016-01-01

The binding properties of adhesion proteins are typically quantified from measurements with soluble fragments, under conditions that differ radically from the confined microenvironment of membrane bound proteins in adhesion zones. Using classical cadherin as a model adhesion protein, we tested the postulate that confinement within quasi two-dimensional intercellular gaps exposes weak protein interactions that are not detected in solution binding assays. Micropipette-based measurements of cadherin-mediated, cell-cell binding kinetics identified a unique kinetic signature that reflects both adhesive (trans) bonds between cadherins on opposing cells and lateral (cis) interactions between cadherins on the same cell. In solution, proposed lateral interactions were not detected, even at high cadherin concentrations. Mutations postulated to disrupt lateral cadherin association altered the kinetic signatures, but did not affect the adhesive (trans) binding affinity. Perturbed kinetics further coincided with altered cadherin distributions at junctions, wound healing dynamics, and paracellular permeability. Intercellular binding kinetics thus revealed cadherin interactions that occur within confined, intermembrane gaps but not in solution. Findings further demonstrate the impact of these revealed interactions on the organization and function of intercellular junctions. PMID:27009566

A Functional Cartography of Cognitive Systems

PubMed Central

Mattar, Marcelo G.; Cole, Michael W.; Thompson-Schill, Sharon L.; Bassett, Danielle S.

2015-01-01

One of the most remarkable features of the human brain is its ability to adapt rapidly and efficiently to external task demands. Novel and non-routine tasks, for example, are implemented faster than structural connections can be formed. The neural underpinnings of these dynamics are far from understood. Here we develop and apply novel methods in network science to quantify how patterns of functional connectivity between brain regions reconfigure as human subjects perform 64 different tasks. By applying dynamic community detection algorithms, we identify groups of brain regions that form putative functional communities, and we uncover changes in these groups across the 64-task battery. We summarize these reconfiguration patterns by quantifying the probability that two brain regions engage in the same network community (or putative functional module) across tasks. These tools enable us to demonstrate that classically defined cognitive systems—including visual, sensorimotor, auditory, default mode, fronto-parietal, cingulo-opercular and salience systems—engage dynamically in cohesive network communities across tasks. We define the network role that a cognitive system plays in these dynamics along the following two dimensions: (i) stability vs. flexibility and (ii) connected vs. isolated. The role of each system is therefore summarized by how stably that system is recruited over the 64 tasks, and how consistently that system interacts with other systems. Using this cartography, classically defined cognitive systems can be categorized as ephemeral integrators, stable loners, and anything in between. Our results provide a new conceptual framework for understanding the dynamic integration and recruitment of cognitive systems in enabling behavioral adaptability across both task and rest conditions. This work has important implications for understanding cognitive network reconfiguration during different task sets and its relationship to cognitive effort, individual variation in cognitive performance, and fatigue. PMID:26629847

Quantifying Variations In Multi-parameter Models With The Photon Clean Method (PCM) And Bootstrap Methods

NASA Astrophysics Data System (ADS)

Carpenter, Matthew H.; Jernigan, J. G.

2007-05-01

We present examples of an analysis progression consisting of a synthesis of the Photon Clean Method (Carpenter, Jernigan, Brown, Beiersdorfer 2007) and bootstrap methods to quantify errors and variations in many-parameter models. The Photon Clean Method (PCM) works well for model spaces with large numbers of parameters proportional to the number of photons, therefore a Monte Carlo paradigm is a natural numerical approach. Consequently, PCM, an "inverse Monte-Carlo" method, requires a new approach for quantifying errors as compared to common analysis methods for fitting models of low dimensionality. This presentation will explore the methodology and presentation of analysis results derived from a variety of public data sets, including observations with XMM-Newton, Chandra, and other NASA missions. Special attention is given to the visualization of both data and models including dynamic interactive presentations. This work was performed under the auspices of the Department of Energy under contract No. W-7405-Eng-48. We thank Peter Beiersdorfer and Greg Brown for their support of this technical portion of a larger program related to science with the LLNL EBIT program.

Driftcretions: The legacy impacts of driftwood on shoreline morphology

NASA Astrophysics Data System (ADS)

Kramer, Natalie; Wohl, Ellen

2015-07-01

This research demonstrates how vegetation interacts with physical processes to govern landscape development. We quantify and describe interactions among driftwood, sedimentation, and vegetation for Great Slave Lake, which is used as proxy for shoreline dynamics and landforms before deforestation and wood removal along major waterways. We introduce driftcretion to describe large, persistent concentrations of driftwood that interact with vegetation and sedimentation to influence shoreline evolution. We report the volume and distribution of driftwood along shorelines, the morphological impacts of driftwood delivery throughout the Holocene, and rates of driftwood accretion. Driftcretions facilitate the formation of complex, diverse morphologies that increase biological productivity and organic carbon capture and buffer against erosion. Driftcretions should be common on shorelines receiving a large wood supply and with processes which store wood permanently. We encourage others to work in these depositional zones to understand the physical and biological impacts of large wood export from river basins.

Long-range correlations improve understanding of the influence of network structure on contact dynamics.

PubMed

Peyrard, N; Dieckmann, U; Franc, A

2008-05-01

Models of infectious diseases are characterized by a phase transition between extinction and persistence. A challenge in contemporary epidemiology is to understand how the geometry of a host's interaction network influences disease dynamics close to the critical point of such a transition. Here we address this challenge with the help of moment closures. Traditional moment closures, however, do not provide satisfactory predictions close to such critical points. We therefore introduce a new method for incorporating longer-range correlations into existing closures. Our method is technically simple, remains computationally tractable and significantly improves the approximation's performance. Our extended closures thus provide an innovative tool for quantifying the influence of interaction networks on spatially or socially structured disease dynamics. In particular, we examine the effects of a network's clustering coefficient, as well as of new geometrical measures, such as a network's square clustering coefficients. We compare the relative performance of different closures from the literature, with or without our long-range extension. In this way, we demonstrate that the normalized version of the Bethe approximation-extended to incorporate long-range correlations according to our method-is an especially good candidate for studying influences of network structure. Our numerical results highlight the importance of the clustering coefficient and the square clustering coefficient for predicting disease dynamics at low and intermediate values of transmission rate, and demonstrate the significance of path redundancy for disease persistence.

Factors Influencing Occupant-To-Seat Belt Interaction in Far-Side Crashes

PubMed Central

Douglas, C.A.; Fildes, B.N.; Gibson, T.J.; Boström, O.; Pintar, F.A.

2007-01-01

Seat belt interaction with a far-side occupant’s shoulder and thorax is critical to governing excursion towards the struck-side of the vehicle in side impact. In this study, occupant-to-belt interaction was simulated using a modified MADYMO human model and finite element belts. Quasi-static tests with volunteers and dynamic sled tests with PMHS and WorldSID were used for model validation and comparison. Parameter studies were then undertaken to quantify the effect of impact direction, seat belt geometry and pretension on occupant-to-seat belt interaction. Results suggest that lowering the D-ring and increasing pretension reduces the likelihood of the belt slipping off the shoulder. Anthropometry was also shown to influence restraint provided by the shoulder belt. Furthermore, the belt may slip off the occupant’s shoulder at impact angles greater than 40 degrees from frontal when no pretension is used. However, the addition of pretension allowed the shoulder to engage the belt in all impacts from 30 to 90 degrees. PMID:18184500

Entropy Production in Field Theories without Time-Reversal Symmetry: Quantifying the Non-Equilibrium Character of Active Matter

NASA Astrophysics Data System (ADS)

Nardini, Cesare; Fodor, Étienne; Tjhung, Elsen; van Wijland, Frédéric; Tailleur, Julien; Cates, Michael E.

2017-04-01

Active-matter systems operate far from equilibrium because of the continuous energy injection at the scale of constituent particles. At larger scales, described by coarse-grained models, the global entropy production rate S quantifies the probability ratio of forward and reversed dynamics and hence the importance of irreversibility at such scales: It vanishes whenever the coarse-grained dynamics of the active system reduces to that of an effective equilibrium model. We evaluate S for a class of scalar stochastic field theories describing the coarse-grained density of self-propelled particles without alignment interactions, capturing such key phenomena as motility-induced phase separation. We show how the entropy production can be decomposed locally (in real space) or spectrally (in Fourier space), allowing detailed examination of the spatial structure and correlations that underly departures from equilibrium. For phase-separated systems, the local entropy production is concentrated mainly on interfaces, with a bulk contribution that tends to zero in the weak-noise limit. In homogeneous states, we find a generalized Harada-Sasa relation that directly expresses the entropy production in terms of the wave-vector-dependent deviation from the fluctuation-dissipation relation between response functions and correlators. We discuss extensions to the case where the particle density is coupled to a momentum-conserving solvent and to situations where the particle current, rather than the density, should be chosen as the dynamical field. We expect the new conceptual tools developed here to be broadly useful in the context of active matter, allowing one to distinguish when and where activity plays an essential role in the dynamics.

Graph Theory Approach for Studying Food Webs

NASA Astrophysics Data System (ADS)

Longjas, A.; Tejedor, A.; Foufoula-Georgiou, E.

2017-12-01

Food webs are complex networks of feeding interactions among species in ecological communities. Metrics describing food web structure have been proposed to compare and classify food webs ranging from food chain length, connectance, degree distribution, centrality measures, to the presence of motifs (distinct compartments), among others. However, formal methodologies for studying both food web topology and the dynamic processes operating on them are still lacking. Here, we utilize a quantitative framework using graph theory within which a food web is represented by a directed graph, i.e., a collection of vertices (species or trophic species defined as sets of species sharing the same predators and prey) and directed edges (predation links). This framework allows us to identify apex (environmental "source" node) to outlet (top predators) subnetworks and compute the steady-state flux (e.g., carbon, nutrients, energy etc.) in the food web. We use this framework to (1) construct vulnerability maps that quantify the relative change of flux delivery to the top predators in response to perturbations in prey species (2) identify keystone species, whose loss would precipitate further species extinction, and (3) introduce a suite of graph-theoretic metrics to quantify the topologic (imposed by food web connectivity) and dynamic (dictated by the flux partitioning and distribution) components of a food web's complexity. By projecting food webs into a 2D Topodynamic Complexity Space whose coordinates are given by Number of alternative paths (topologic) and Leakage Index (dynamic), we show that this space provides a basis for food web comparison and provide physical insights into their dynamic behavior.

Dynamical diagnostics of the SST annual cycle in the eastern equatorial Pacific: part I a linear coupled framework

NASA Astrophysics Data System (ADS)

Chen, Ying-Ying; Jin, Fei-Fei

2018-03-01

The eastern equatorial Pacific has a pronounced westward propagating SST annual cycle resulting from ocean-atmosphere interactions with equatorial semiannual solar forcing and off-equatorial annual solar forcing conveyed to the equator. In this two-part paper, a simple linear coupled framework is proposed to quantify the internal dynamics and external forcing for a better understanding of the linear part of the dynamics annual cycle. It is shown that an essential internal dynamical factor is the SST damping rate which measures the coupled stability in a similar way as the Bjerknes instability index for the El Niño-Southern Oscillation. It comprises three major negative terms (dynamic damping due to the Ekman pumping feedback, mean circulation advection, and thermodynamic feedback) and two positive terms (thermocline feedback and zonal advection). Another dynamical factor is the westward-propagation speed that is mainly determined by the thermodynamic feedback, the Ekman pumping feedback, and the mean circulation. The external forcing is measured by the annual and semiannual forcing factors. These linear internal and external factors, which can be estimated from data, determine the amplitude of the annual cycle.

Mental workload during n-back task-quantified in the prefrontal cortex using fNIRS.

PubMed

Herff, Christian; Heger, Dominic; Fortmann, Ole; Hennrich, Johannes; Putze, Felix; Schultz, Tanja

2013-01-01

When interacting with technical systems, users experience mental workload. Particularly in multitasking scenarios (e.g., interacting with the car navigation system while driving) it is desired to not distract the users from their primary task. For such purposes, human-machine interfaces (HCIs) are desirable which continuously monitor the users' workload and dynamically adapt the behavior of the interface to the measured workload. While memory tasks have been shown to elicit hemodynamic responses in the brain when averaging over multiple trials, a robust single trial classification is a crucial prerequisite for the purpose of dynamically adapting HCIs to the workload of its user. The prefrontal cortex (PFC) plays an important role in the processing of memory and the associated workload. In this study of 10 subjects, we used functional Near-Infrared Spectroscopy (fNIRS), a non-invasive imaging modality, to sample workload activity in the PFC. The results show up to 78% accuracy for single-trial discrimination of three levels of workload from each other. We use an n-back task (n ∈ {1, 2, 3}) to induce different levels of workload, forcing subjects to continuously remember the last one, two, or three of rapidly changing items. Our experimental results show that measuring hemodynamic responses in the PFC with fNIRS, can be used to robustly quantify and classify mental workload. Single trial analysis is still a young field that suffers from a general lack of standards. To increase comparability of fNIRS methods and results, the data corpus for this study is made available online.

Physiological condition of bank voles (Myodes glareolus) during the increase and decline phases of the population cycle.

PubMed

Nieminen, Petteri; Huitu, Otso; Henttonen, Heikki; Finnilä, Mikko A J; Voutilainen, Liina; Itämies, Juhani; Kärjä, Vesa; Saarela, Seppo; Halonen, Toivo; Aho, Jari; Mustonen, Anne-Mari

2015-09-01

The dynamics of animal populations are greatly influenced by interactions with their natural enemies and food resources. However, quantifying the relative effects of these factors on demographic rates remains a perpetual challenge for animal population ecology. Food scarcity is assumed to limit the growth and to initiate the decline of cyclic herbivore populations, but this has not been verified with physiological health indices. We hypothesized that individuals in declining populations would exhibit signs of malnutrition-induced deterioration of physiological condition. We evaluated the association of body condition with population cycle phase in bank voles (Myodes glareolus) during the increase and decline phases of a population cycle. The bank voles had lower body masses, condition indices and absolute masses of particular organs during the decline. Simultaneously, they had lower femoral masses, mineral contents and densities. Hemoglobin and hematocrit values and several parameters known to respond to food deprivation were unaffected by the population phase. There were no signs of lymphopenia, eosinophilia, granulocytosis or monocytosis. Erythrocyte counts were higher and plasma total protein levels and tissue proportions of essential polyunsaturated fatty acids lower in the population decline. Ectoparasite load was lower and adrenal gland masses or catecholamine concentrations did not suggest higher stress levels. Food availability seems to limit the size of voles during the decline but they can adapt to the prevailing conditions without clear deleterious health effects. This highlights the importance of quantifying individual health state when evaluating the effects of complex trophic interactions on the dynamics of wild animal populations. Copyright © 2015 Elsevier Inc. All rights reserved.

Mental workload during n-back task—quantified in the prefrontal cortex using fNIRS

PubMed Central

Herff, Christian; Heger, Dominic; Fortmann, Ole; Hennrich, Johannes; Putze, Felix; Schultz, Tanja

2014-01-01

When interacting with technical systems, users experience mental workload. Particularly in multitasking scenarios (e.g., interacting with the car navigation system while driving) it is desired to not distract the users from their primary task. For such purposes, human-machine interfaces (HCIs) are desirable which continuously monitor the users' workload and dynamically adapt the behavior of the interface to the measured workload. While memory tasks have been shown to elicit hemodynamic responses in the brain when averaging over multiple trials, a robust single trial classification is a crucial prerequisite for the purpose of dynamically adapting HCIs to the workload of its user. The prefrontal cortex (PFC) plays an important role in the processing of memory and the associated workload. In this study of 10 subjects, we used functional Near-Infrared Spectroscopy (fNIRS), a non-invasive imaging modality, to sample workload activity in the PFC. The results show up to 78% accuracy for single-trial discrimination of three levels of workload from each other. We use an n-back task (n ∈ {1, 2, 3}) to induce different levels of workload, forcing subjects to continuously remember the last one, two, or three of rapidly changing items. Our experimental results show that measuring hemodynamic responses in the PFC with fNIRS, can be used to robustly quantify and classify mental workload. Single trial analysis is still a young field that suffers from a general lack of standards. To increase comparability of fNIRS methods and results, the data corpus for this study is made available online. PMID:24474913

Incorporating human-water dynamics in a hyper-resolution land surface model

NASA Astrophysics Data System (ADS)

Vergopolan, N.; Chaney, N.; Wanders, N.; Sheffield, J.; Wood, E. F.

2017-12-01

The increasing demand for water, energy, and food is leading to unsustainable groundwater and surface water exploitation. As a result, the human interactions with the environment, through alteration of land and water resources dynamics, need to be reflected in hydrologic and land surface models (LSMs). Advancements in representing human-water dynamics still leave challenges related to the lack of water use data, water allocation algorithms, and modeling scales. This leads to an over-simplistic representation of human water use in large-scale models; this is in turn leads to an inability to capture extreme events signatures and to provide reliable information at stakeholder-level spatial scales. The emergence of hyper-resolution models allows one to address these challenges by simulating the hydrological processes and interactions with the human impacts at field scales. We integrated human-water dynamics into HydroBlocks - a hyper-resolution, field-scale resolving LSM. HydroBlocks explicitly solves the field-scale spatial heterogeneity of land surface processes through interacting hydrologic response units (HRUs); and its HRU-based model parallelization allows computationally efficient long-term simulations as well as ensemble predictions. The implemented human-water dynamics include groundwater and surface water abstraction to meet agricultural, domestic and industrial water demands. Furthermore, a supply-demand water allocation scheme based on relative costs helps to determine sectoral water use requirements and tradeoffs. A set of HydroBlocks simulations over the Midwest United States (daily, at 30-m spatial resolution for 30 years) are used to quantify the irrigation impacts on water availability. The model captures large reductions in total soil moisture and water table levels, as well as spatiotemporal changes in evapotranspiration and runoff peaks, with their intensity related to the adopted water management strategy. By incorporating human-water dynamics in a hyper-resolution LSM this work allows for progress on hydrological monitoring and predictions, as well as drought preparedness and water impact assessments at relevant decision-making scales.

Teleconnection Paths via Climate Network Direct Link Detection.

PubMed

Zhou, Dong; Gozolchiani, Avi; Ashkenazy, Yosef; Havlin, Shlomo

2015-12-31

Teleconnections describe remote connections (typically thousands of kilometers) of the climate system. These are of great importance in climate dynamics as they reflect the transportation of energy and climate change on global scales (like the El Niño phenomenon). Yet, the path of influence propagation between such remote regions, and weighting associated with different paths, are only partially known. Here we propose a systematic climate network approach to find and quantify the optimal paths between remotely distant interacting locations. Specifically, we separate the correlations between two grid points into direct and indirect components, where the optimal path is found based on a minimal total cost function of the direct links. We demonstrate our method using near surface air temperature reanalysis data, on identifying cross-latitude teleconnections and their corresponding optimal paths. The proposed method may be used to quantify and improve our understanding regarding the emergence of climate patterns on global scales.

Direct Observation of Domain-Wall Surface Tension by Deflating or Inflating a Magnetic Bubble

NASA Astrophysics Data System (ADS)

Zhang, Xueying; Vernier, Nicolas; Zhao, Weisheng; Yu, Haiming; Vila, Laurent; Zhang, Yue; Ravelosona, Dafiné

2018-02-01

The surface energy of a magnetic domain wall (DW) strongly affects its static and dynamic behaviors. However, this effect is seldom directly observed, and some of the related phenomena are not well understood. Moreover, a reliable method to quantify the DW surface energy is still absent. Here, we report a series of experiments in which the DW surface energy becomes a dominant parameter. We observe that a semicircular magnetic domain bubble can spontaneously collapse under the Laplace pressure induced by DW surface energy. We further demonstrate that the surface energy can lead to a geometrically induced pinning when the DW propagates in a Hall cross or from a nanowire into a nucleation pad. Based on these observations, we develop two methods to quantify the DW surface energy, which can be very helpful in the estimation of intrinsic parameters such as Dzyaloshinskii-Moriya interactions or exchange stiffness in magnetic ultrathin films.

Segmentation and Tracking of Cytoskeletal Filaments Using Open Active Contours

PubMed Central

Smith, Matthew B.; Li, Hongsheng; Shen, Tian; Huang, Xiaolei; Yusuf, Eddy; Vavylonis, Dimitrios

2010-01-01

We use open active contours to quantify cytoskeletal structures imaged by fluorescence microscopy in two and three dimensions. We developed an interactive software tool for segmentation, tracking, and visualization of individual fibers. Open active contours are parametric curves that deform to minimize the sum of an external energy derived from the image and an internal bending and stretching energy. The external energy generates (i) forces that attract the contour toward the central bright line of a filament in the image, and (ii) forces that stretch the active contour toward the ends of bright ridges. Images of simulated semiflexible polymers with known bending and torsional rigidity are analyzed to validate the method. We apply our methods to quantify the conformations and dynamics of actin in two examples: actin filaments imaged by TIRF microscopy in vitro, and actin cables in fission yeast imaged by spinning disk confocal microscopy. PMID:20814909

Crystal Plasticity Model of Reactor Pressure Vessel Embrittlement in GRIZZLY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chakraborty, Pritam; Biner, Suleyman Bulent; Zhang, Yongfeng

2015-07-01

The integrity of reactor pressure vessels (RPVs) is of utmost importance to ensure safe operation of nuclear reactors under extended lifetime. Microstructure-scale models at various length and time scales, coupled concurrently or through homogenization methods, can play a crucial role in understanding and quantifying irradiation-induced defect production, growth and their influence on mechanical behavior of RPV steels. A multi-scale approach, involving atomistic, meso- and engineering-scale models, is currently being pursued within the GRIZZLY project to understand and quantify irradiation-induced embrittlement of RPV steels. Within this framework, a dislocation-density based crystal plasticity model has been developed in GRIZZLY that captures themore » effect of irradiation-induced defects on the flow stress behavior and is presented in this report. The present formulation accounts for the interaction between self-interstitial loops and matrix dislocations. The model predictions have been validated with experiments and dislocation dynamics simulation.« less

Bicuspid aortic valve hemodynamics: a fluid-structure interaction study

NASA Astrophysics Data System (ADS)

Chandra, Santanu; Seaman, Clara; Sucosky, Philippe

2011-11-01

The bicuspid aortic valve (BAV) is a congenital defect in which the aortic valve forms with two leaflets instead of three. While calcific aortic valve disease (CAVD) also develops in the normal tricuspid aortic valve (TAV), its progression in the BAV is more rapid. Although studies have suggested a mechano-potential root for the disease, the native BAV hemodynamics remains largely unknown. This study aimed at characterizing BAV hemodynamics and quantifying the degree of wall-shear stress (WSS) abnormality on BAV leaflets. Fluid-structure interaction models validated with particle-image velocimetry were designed to predict the flow and leaflet dynamics in idealized TAV and BAV anatomies. Valvular function was quantified in terms of the effective orifice area. The regional leaflet WSS was characterized in terms of oscillatory shear index, temporal shear magnitude and temporal shear gradient. The predictions indicate the intrinsic degree of stenosis of the BAV anatomy, reveal drastic differences in shear stress magnitude and pulsatility on BAV and TAV leaflets and confirm the side- and site-specificity of the leaflet WSS. Given the ability of abnormal fluid shear stress to trigger valvular inflammation, these results support the existence of a mechano-etiology of CAVD in the BAV.

Social niche specialization under constraints: personality, social interactions and environmental heterogeneity

PubMed Central

Montiglio, Pierre-Olivier; Ferrari, Caterina; Réale, Denis

2013-01-01

Several personality traits are mainly expressed in a social context, and others, which are not restricted to a social context, can be affected by the social interactions with conspecifics. In this paper, we focus on the recently proposed hypothesis that social niche specialization (i.e. individuals in a population occupy different social roles) can explain the maintenance of individual differences in personality. We first present ecological and social niche specialization hypotheses. In particular, we show how niche specialization can be quantified and highlight the link between personality differences and social niche specialization. We then review some ecological factors (e.g. competition and environmental heterogeneity) and the social mechanisms (e.g. frequency-dependent, state-dependent and social awareness) that may be associated with the evolution of social niche specialization and personality differences. Finally, we present a conceptual model and methods to quantify the contribution of ecological factors and social mechanisms to the dynamics between personality and social roles. In doing so, we suggest a series of research objectives to help empirical advances in this research area. Throughout this paper, we highlight empirical studies of social niche specialization in mammals, where available. PMID:23569291

Oman Drilling Project GT3 site survey: dynamics at the roof of an oceanic magma chamber

NASA Astrophysics Data System (ADS)

France, L.; Nicollet, C.; Debret, B.; Lombard, M.; Berthod, C.; Ildefonse, B.; Koepke, J.

2017-12-01

Oman Drilling Project (OmanDP) aims at bringing new constraints on oceanic crust accretion and evolution by drilling Holes in the whole ophiolite section (mantle and crust). Among those, operations at GT3 in the Sumail massif drilled 400 m to sample the dike - gabbro transition that corresponds to the top (gabbros) and roof (dikes) of the axial magma chamber, an interface where hydrothermal and magmatic system interacts. Previous studies based on oceanic crust formed at present day fast-spreading ridges and preserved in ophiolites have highlighted that this interface is a dynamic horizon where the axial melt lens that top the main magma chamber can intrude, reheat, and partially assimilate previously hydrothermally altered roof rocks. Here we present the preliminary results obtained in GT3 area that have allowed the community to choose the drilling site. We provide a geological and structural map of the area, together with new petrographic and chemical constraints on the dynamics of the dike - gabbro transition. Our new results allow us to quantify the dynamic processes, and to propose that 1/ the intrusive contact of the varitextured gabbro within the dikes highlights the intrusion of the melt lens top in the dike rooting zone, 2/ both dikes and previously crystallized gabbros are reheated, and recrystallized by underlying melt lens dynamics (up to 1050°C, largely above the hydrous solidus temperature of altered dikes and gabbros), 3/ the reheating range can be > 200°C, 4/ the melt lens depth variations for a given ridge position is > 200m, 5/ the reheating stage and associated recrystallization within the dikes occurred under hydrous conditions, 6/ the reheating stage is recorded at the root zone of the sheeted dike complex by one of the highest stable conductive thermal gradient ever recorded on Earth ( 3°C/m), 7/ local chemical variations in recrystallized dikes and gabbros are highlighted and used to quantify crystallization and anatectic processes, and the presence of trapped melt, 8/ melt lens cannibalism is attested by numerous assimilation figures close its roof. Besides providing a general context for future studies at OmanDP GT3 site, those new results allow us to quantify the dynamic processes that govern the layer 2 - layer 3 transition in ocean lithosphere.

Controlling Interfacial Dynamics: Covalent Bonding versus Physical Adsorption in Polymer Nanocomposites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Holt, Adam P.; Bocharova, Vera; Cheng, Shiwang

It is generally believed that the strength of the polymer nanoparticle interaction controls the modification of near-interface segmental mobility in polymer nanocomposites (PNCs). However, little is known about the effect of covalent bonding on the segmental dynamics and glass transition of matrix-free polymer-grafted nanoparticles (PGNs), especially when compared to PNCs. In this article, we directly compare the static and dynamic properties of poly(2-vinylpyridine)/silica-based nanocomposites with polymer chains either physically adsorbed (PNCs) or covalently bonded (PGNs) to identical silica nanoparticles (RNP = 12.5 nm) for three different molecular weight (MW) systems. Interestingly, when the MW of the matrix is as lowmore » as 6 kg/mol (RNP/Rg = 5.4) or as high as 140 kg/mol (RNP/Rg= 1.13), both small-angle X-ray scattering and broadband dielectric spectroscopy show similar static and dynamic properties for PNCs and PGNs. However, for the intermediate MW of 18 kg/mol (RNP/Rg = 3.16), the difference between physical adsorption and covalent bonding can be clearly identified in the static and dynamic properties of the interfacial layer. We ascribe the differences in the interfacial properties of PNCs and PGNs to changes in chain stretching, as quantified by self-consistent field theory calculations. These results demonstrate that the dynamic suppression at the interface is affected by the chain stretching; that is, it depends on the anisotropy of the segmental conformations, more so than the strength of the interaction, which suggests that the interfacial dynamics can be effectively tuned by the degree of stretching a parameter accessible from the MW or grafting density.« less

Controlling Interfacial Dynamics: Covalent Bonding versus Physical Adsorption in Polymer Nanocomposites

DOE PAGES

Holt, Adam P.; Bocharova, Vera; Cheng, Shiwang; ...

2016-06-23

It is generally believed that the strength of the polymer nanoparticle interaction controls the modification of near-interface segmental mobility in polymer nanocomposites (PNCs). However, little is known about the effect of covalent bonding on the segmental dynamics and glass transition of matrix-free polymer-grafted nanoparticles (PGNs), especially when compared to PNCs. In this article, we directly compare the static and dynamic properties of poly(2-vinylpyridine)/silica-based nanocomposites with polymer chains either physically adsorbed (PNCs) or covalently bonded (PGNs) to identical silica nanoparticles (RNP = 12.5 nm) for three different molecular weight (MW) systems. Interestingly, when the MW of the matrix is as lowmore » as 6 kg/mol (RNP/Rg = 5.4) or as high as 140 kg/mol (RNP/Rg= 1.13), both small-angle X-ray scattering and broadband dielectric spectroscopy show similar static and dynamic properties for PNCs and PGNs. However, for the intermediate MW of 18 kg/mol (RNP/Rg = 3.16), the difference between physical adsorption and covalent bonding can be clearly identified in the static and dynamic properties of the interfacial layer. We ascribe the differences in the interfacial properties of PNCs and PGNs to changes in chain stretching, as quantified by self-consistent field theory calculations. These results demonstrate that the dynamic suppression at the interface is affected by the chain stretching; that is, it depends on the anisotropy of the segmental conformations, more so than the strength of the interaction, which suggests that the interfacial dynamics can be effectively tuned by the degree of stretching a parameter accessible from the MW or grafting density.« less

Differential Modulation of Functional Dynamics and Allosteric Interactions in the Hsp90-Cochaperone Complexes with p23 and Aha1: A Computational Study

PubMed Central

Blacklock, Kristin; Verkhivker, Gennady M.

2013-01-01

Allosteric interactions of the molecular chaperone Hsp90 with a large cohort of cochaperones and client proteins allow for molecular communication and event coupling in signal transduction networks. The integration of cochaperones into the Hsp90 system is driven by the regulatory mechanisms that modulate the progression of the ATPase cycle and control the recruitment of the Hsp90 clientele. In this work, we report the results of computational modeling of allosteric regulation in the Hsp90 complexes with the cochaperones p23 and Aha1. By integrating protein docking, biophysical simulations, modeling of allosteric communications, protein structure network analysis and the energy landscape theory we have investigated dynamics and stability of the Hsp90-p23 and Hsp90-Aha1 interactions in direct comparison with the extensive body of structural and functional experiments. The results have revealed that functional dynamics and allosteric interactions of Hsp90 can be selectively modulated by these cochaperones via specific targeting of the regulatory hinge regions that could restrict collective motions and stabilize specific chaperone conformations. The protein structure network parameters have quantified the effects of cochaperones on conformational stability of the Hsp90 complexes and identified dynamically stable communities of residues that can contribute to the strengthening of allosteric interactions. According to our results, p23-mediated changes in the Hsp90 interactions may provide “molecular brakes” that could slow down an efficient transmission of the inter-domain allosteric signals, consistent with the functional role of p23 in partially inhibiting the ATPase cycle. Unlike p23, Aha1-mediated acceleration of the Hsp90-ATPase cycle may be achieved via modulation of the equilibrium motions that facilitate allosteric changes favoring a closed dimerized form of Hsp90. The results of our study have shown that Aha1 and p23 can modulate the Hsp90-ATPase activity and direct the chaperone cycle by exerting the precise control over structural stability, global movements and allosteric communications in Hsp90. PMID:23977182

Observation of electron cloud instabilities and emittance dilution at the Cornell electron-positron Storage ring Test Accelerator

DOE PAGES

Holtzapple, R. L.; Billing, M. G.; Campbell, R. C.; ...

2016-04-11

Electron cloud related emittance dilution and instabilities of bunch trains limit the performance of high intensity circular colliders. One of the key goals of the Cornell electron-positron storage ring Test Accelerator (CesrTA) research program is to improve our understanding of how the electron cloud alters the dynamics of bunches within the train. Single bunch beam diagnostics have been developed to measure the beam spectra, vertical beam size, two important dynamical effects of beams interacting with the electron cloud, for bunch trains on a turn-by-turn basis. Experiments have been performed at CesrTA to probe the interaction of the electron cloud withmore » stored positron bunch trains. The purpose of these experiments was to characterize the dependence of beam-electron cloud interactions on the machine parameters such as bunch spacing, vertical chromaticity, and bunch current. The beam dynamics of the stored beam, in the presence of the electron cloud, was quantified using: 1) a gated beam position monitor (BPM) and spectrum analyzer to measure the bunch-by-bunch frequency spectrum of the bunch trains, 2) an x-ray beam size monitor to record the bunch-by-bunch, turn-by-turn vertical size of each bunch within the trains. In this study we report on the observations from these experiments and analyze the effects of the electron cloud on the stability of bunches in a train under many different operational conditions.« less

Interaction of arginine, lysine, and guanidine with surface residues of lysozyme: implication to protein stability.

PubMed

Shah, Dhawal; Shaikh, Abdul Rajjak

2016-01-01

Additives are widely used to suppress aggregation of therapeutic proteins. However, the molecular mechanisms of effect of additives to stabilize proteins are still unclear. To understand this, we herein perform molecular dynamics simulations of lysozyme in the presence of three commonly used additives: arginine, lysine, and guanidine. These additives have different effects on stability of proteins and have different structures with some similarities; arginine and lysine have aliphatic side chain, while arginine has a guanidinium group. We analyze atomic contact frequencies to study the interactions of the additives with individual residues of lysozyme. Contact coefficient, quantified from contact frequencies, is helpful in analyzing the interactions with the guanidine groups as well as aliphatic side chains of arginine and lysine. Strong preference for contacts to the additives (over water) is seen for the acidic followed by polar and the aromatic residues. Further analysis suggests that the hydration layer around the protein surface is depleted more in the presence of arginine, followed by lysine and guanidine. Molecular dynamics simulations also reveal that the internal dynamics of protein, as indicated by the lifetimes of the hydrogen bonds within the protein, changes depending on the additives. Particularly, we note that the side-chain hydrogen-bonding patterns within the protein differ with the additives, with several side-chain hydrogen bonds missing in the presence of guanidine. These results collectively indicate that the aliphatic chain of arginine and lysine plays a critical role in the stabilization of the protein.

Observation of Electron Cloud Instabilities and Emittance Dilution at the Cornell Electron-Positron Storage Ring Test Accelerator

NASA Astrophysics Data System (ADS)

Holtzapple, R. L.; Billing, M. G.; Campbell, R. C.; Dugan, G. F.; Flanagan, J.; McArdle, K. E.; Miller, M. I.; Palmer, M. A.; Ramirez, G. A.; Sonnad, K. G.; Totten, M. M.; Tucker, S. L.; Williams, H. A.

2016-04-01

Electron cloud related emittance dilution and instabilities of bunch trains limit the performance of high intensity circular colliders. One of the key goals of the Cornell electron-positron storage ring Test Accelerator (CesrTA) research program is to improve our understanding of how the electron cloud alters the dynamics of bunches within the train. Single bunch beam diagnotics have been developed to measure the beam spectra, vertical beam size, two important dynamical effects of beams interacting with the electron cloud, for bunch trains on a turn-by-turn basis. Experiments have been performed at CesrTA to probe the interaction of the electron cloud with stored positron bunch trains. The purpose of these experiments was to characterize the dependence of beam-electron cloud interactions on the machine parameters such as bunch spacing, vertical chromaticity, and bunch current. The beam dynamics of the stored beam, in the presence of the electron cloud, was quantified using: 1) a gated beam position monitor (BPM) and spectrum analyzer to measure the bunch-by-bunch frequency spectrum of the bunch trains; 2) an x-ray beam size monitor to record the bunch-by-bunch, turn-by-turn vertical size of each bunch within the trains. In this paper we report on the observations from these experiments and analyze the effects of the electron cloud on the stability of bunches in a train under many different operational conditions.

Quantifying protein-protein interactions in high throughput using protein domain microarrays.

PubMed

Kaushansky, Alexis; Allen, John E; Gordus, Andrew; Stiffler, Michael A; Karp, Ethan S; Chang, Bryan H; MacBeath, Gavin

2010-04-01

Protein microarrays provide an efficient way to identify and quantify protein-protein interactions in high throughput. One drawback of this technique is that proteins show a broad range of physicochemical properties and are often difficult to produce recombinantly. To circumvent these problems, we have focused on families of protein interaction domains. Here we provide protocols for constructing microarrays of protein interaction domains in individual wells of 96-well microtiter plates, and for quantifying domain-peptide interactions in high throughput using fluorescently labeled synthetic peptides. As specific examples, we will describe the construction of microarrays of virtually every human Src homology 2 (SH2) and phosphotyrosine binding (PTB) domain, as well as microarrays of mouse PDZ domains, all produced recombinantly in Escherichia coli. For domains that mediate high-affinity interactions, such as SH2 and PTB domains, equilibrium dissociation constants (K(D)s) for their peptide ligands can be measured directly on arrays by obtaining saturation binding curves. For weaker binding domains, such as PDZ domains, arrays are best used to identify candidate interactions, which are then retested and quantified by fluorescence polarization. Overall, protein domain microarrays provide the ability to rapidly identify and quantify protein-ligand interactions with minimal sample consumption. Because entire domain families can be interrogated simultaneously, they provide a powerful way to assess binding selectivity on a proteome-wide scale and provide an unbiased perspective on the connectivity of protein-protein interaction networks.

Monogenean parasites from fishes of the Vaal Dam, Gauteng Province, South Africa. I. Winter survey versus summer survey comparison from Labeo capensis (Smith, 1841) and Labeo umbratus (Smith, 1841) hosts.

PubMed

Crafford, Dionne; Luus-Powell, Wilmien; Avenant-Oldewage, Annemariè

2014-03-01

Indigenous South African Labeo spp. show promise with regard to development of semi-intensive aquaculture, yet little research on their monogenean fauna has been conducted. Ecological aspects of monogenean fauna of the moggel Labeo umbratus (Smith 1841) and the Orange River mudfish Labeo capensis (Smith 1841), as recorded during both winter and summer sampling surveys, are reported here. Fish were collected using gill nets, euthanized and gills removed and examined to both quantify parasite numbers and distribution on the gills. Results obtained support the hypothesis that gill site preference is not due to active choice for a particular attachment site, but rather a result of water flow over gills during respiration in conjunction with fish behaviour and habitat use. Interaction between individual elements investigated (temperature effects, parasite population dynamics and host population dynamics) may be largely responsible for seasonal differences in infection statistics of monogenean parasites. Such interactions should be investigated in future large scale ecological studies, in combination with experimental studies, to further elucidate these effects.

New approach of financial volatility duration dynamics by stochastic finite-range interacting voter system.

PubMed

Wang, Guochao; Wang, Jun

2017-01-01

We make an approach on investigating the fluctuation behaviors of financial volatility duration dynamics. A new concept of volatility two-component range intensity (VTRI) is developed, which constitutes the maximal variation range of volatility intensity and shortest passage time of duration, and can quantify the investment risk in financial markets. In an attempt to study and describe the nonlinear complex properties of VTRI, a random agent-based financial price model is developed by the finite-range interacting biased voter system. The autocorrelation behaviors and the power-law scaling behaviors of return time series and VTRI series are investigated. Then, the complexity of VTRI series of the real markets and the proposed model is analyzed by Fuzzy entropy (FuzzyEn) and Lempel-Ziv complexity. In this process, we apply the cross-Fuzzy entropy (C-FuzzyEn) to study the asynchrony of pairs of VTRI series. The empirical results reveal that the proposed model has the similar complex behaviors with the actual markets and indicate that the proposed stock VTRI series analysis and the financial model are meaningful and feasible to some extent.

New approach of financial volatility duration dynamics by stochastic finite-range interacting voter system

NASA Astrophysics Data System (ADS)

Wang, Guochao; Wang, Jun

2017-01-01

We make an approach on investigating the fluctuation behaviors of financial volatility duration dynamics. A new concept of volatility two-component range intensity (VTRI) is developed, which constitutes the maximal variation range of volatility intensity and shortest passage time of duration, and can quantify the investment risk in financial markets. In an attempt to study and describe the nonlinear complex properties of VTRI, a random agent-based financial price model is developed by the finite-range interacting biased voter system. The autocorrelation behaviors and the power-law scaling behaviors of return time series and VTRI series are investigated. Then, the complexity of VTRI series of the real markets and the proposed model is analyzed by Fuzzy entropy (FuzzyEn) and Lempel-Ziv complexity. In this process, we apply the cross-Fuzzy entropy (C-FuzzyEn) to study the asynchrony of pairs of VTRI series. The empirical results reveal that the proposed model has the similar complex behaviors with the actual markets and indicate that the proposed stock VTRI series analysis and the financial model are meaningful and feasible to some extent.

The dynamic still-face effect: do infants decrease bidding over time when parents are not responsive?

PubMed

Ekas, Naomi V; Haltigan, John D; Messinger, Daniel S

2013-06-01

The still-face paradigm (SFP) was designed to assess infant expectations that parents will respond to infant communicative signals. During the still-face (SF) episode, the parent ceases interaction and maintains a neutral expression. Original, qualitative descriptions of infant behavior suggested changes within the SF episode: infants decrease bidding and disengage from their impassive parent. Research has documented changes in mean levels of infant behavior between episodes of the SFP. The hypothesis that infant behavior changes within the SF episode has not been empirically tested. In this study, hierarchical linear modeling indicated that infant gazing at the parent, smiling, and social bidding (smiling while gazing at the parent) decreased with time in the SF episode, while infant cry-face expressions increased. Changes in infant behaviors within the SF episode were associated with infant attachment and infant internalizing problems. The dynamic still-face effect quantifies infant initiation of interaction in the face of parental unresponsiveness and is a potential predictor of individual differences in development. PsycINFO Database Record (c) 2013 APA, all rights reserved

Remote Control of Tissue Interactions via Engineered Photo-switchable Cell Surfaces

NASA Astrophysics Data System (ADS)

Luo, Wei; Pulsipher, Abigail; Dutta, Debjit; Lamb, Brian M.; Yousaf, Muhammad N.

2014-09-01

We report a general cell surface molecular engineering strategy via liposome fusion delivery to create a dual photo-active and bio-orthogonal cell surface for remote controlled spatial and temporal manipulation of microtissue assembly and disassembly. Cell surface tailoring of chemoselective functional groups was achieved by a liposome fusion delivery method and quantified by flow cytometry and characterized by a new cell surface lipid pull down mass spectrometry strategy. Dynamic co-culture spheroid tissue assembly in solution and co-culture tissue multilayer assembly on materials was demonstrated by an intercellular photo-oxime ligation that could be remotely cleaved and disassembled on demand. Spatial and temporal control of microtissue structures containing multiple cell types was demonstrated by the generation of patterned multilayers for controlling stem cell differentiation. Remote control of cell interactions via cell surface engineering that allows for real-time manipulation of tissue dynamics may provide tools with the scope to answer fundamental questions of cell communication and initiate new biotechnologies ranging from imaging probes to drug delivery vehicles to regenerative medicine, inexpensive bioreactor technology and tissue engineering therapies.

The origin of and conditions for clustering in fluids with competing interactions

NASA Astrophysics Data System (ADS)

Jadrich, Ryan; Bollinger, Jonathan; Truskett, Thomas

2015-03-01

Fluids with competing short-range attractions and long-range repulsions exhibit a rich phase behavior characterized by intermediate range order (IRO), as quantified via the static structure factor. This phase behavior includes cluster formation depending upon density-controlled packing effects and the magnitude and range of the attractive and repulsive interactions. Such model systems mimic (to zeroth order) screened, charge-stabilized, aqueous colloidal dispersions of, e.g., proteins. We employ molecular dynamics simulations and integral equation theory to elucidate a more fundamental microscopic explanation for IRO-driven clustering. A simple criterion is identified that indicates when dynamic, amorphous clustering emerges in a polydisperse system, namely when the Ornstein-Zernike thermal correlation length in the system exceeds the repulsive potential tail range. Remarkably, this criterion also appears tightly correlated to crystalline cluster formation in a monodisperse system. Our new gauge is compared to another phenomenological condition for clustering which is when the IRO peak magnitude exceeds ~ 2.7. Ramifications of crystalline versus amorphous clustering are discussed and potential ways of using our new measure in experiment are put forward.

Molecular dynamics simulations of acoustic absorption by a carbon nanotube

NASA Astrophysics Data System (ADS)

Ayub, M.; Zander, A. C.; Huang, D. M.; Howard, C. Q.; Cazzolato, B. S.

2018-06-01

Acoustic absorption by a carbon nanotube (CNT) was studied using molecular dynamics (MD) simulations in a molecular domain containing a monatomic gas driven by a time-varying periodic force to simulate acoustic wave propagation. Attenuation of the sound wave and the characteristics of the sound field due to interactions with the CNT were studied by evaluating the behavior of various acoustic parameters and comparing the behavior with that of the domain without the CNT present. A standing wave model was developed for the CNT-containing system to predict sound attenuation by the CNT and the results were verified against estimates of attenuation using the thermodynamic concept of exergy. This study demonstrates acoustic absorption effects of a CNT in a thermostatted MD simulation, quantifies the acoustic losses induced by the CNT, and illustrates their effects on the CNT. Overall, a platform was developed for MD simulations that can model acoustic damping induced by nanostructured materials such as CNTs, which can be used for further understanding of nanoscale acoustic loss mechanisms associated with molecular interactions between acoustic waves and nanomaterials.

Entropy Transfer between Residue Pairs and Allostery in Proteins: Quantifying Allosteric Communication in Ubiquitin.

PubMed

Hacisuleyman, Aysima; Erman, Burak

2017-01-01

It has recently been proposed by Gunasakaran et al. that allostery may be an intrinsic property of all proteins. Here, we develop a computational method that can determine and quantify allosteric activity in any given protein. Based on Schreiber's transfer entropy formulation, our approach leads to an information transfer landscape for the protein that shows the presence of entropy sinks and sources and explains how pairs of residues communicate with each other using entropy transfer. The model can identify the residues that drive the fluctuations of others. We apply the model to Ubiquitin, whose allosteric activity has not been emphasized until recently, and show that there are indeed systematic pathways of entropy and information transfer between residues that correlate well with the activities of the protein. We use 600 nanosecond molecular dynamics trajectories for Ubiquitin and its complex with human polymerase iota and evaluate entropy transfer between all pairs of residues of Ubiquitin and quantify the binding susceptibility changes upon complex formation. We explain the complex formation propensities of Ubiquitin in terms of entropy transfer. Important residues taking part in allosteric communication in Ubiquitin predicted by our approach are in agreement with results of NMR relaxation dispersion experiments. Finally, we show that time delayed correlation of fluctuations of two interacting residues possesses an intrinsic causality that tells which residue controls the interaction and which one is controlled. Our work shows that time delayed correlations, entropy transfer and causality are the required new concepts for explaining allosteric communication in proteins.

Hydrodynamics of confined active fluids.

PubMed

Brotto, Tommaso; Caussin, Jean-Baptiste; Lauga, Eric; Bartolo, Denis

2013-01-18

We theoretically describe the dynamics of swimmer populations in rigidly confined thin liquid films. We first demonstrate that hydrodynamic interactions between confined swimmers depend solely on their shape and are independent of their specific swimming mechanism. We also show that, due to friction with the nearby rigid walls, confined swimmers do not just reorient in flow gradients but also in uniform flows. We then quantify the consequences of these microscopic interaction rules on the large-scale hydrodynamics of isotropic populations. We investigate in detail their stability and the resulting phase behavior, highlighting the differences with conventional active, three-dimensional suspensions. Two classes of polar swimmers are distinguished depending on their geometrical polarity. The first class gives rise to coherent directed motion at all scales, whereas for the second class we predict the spontaneous formation of coherent clusters (swarms).

Quantifying the Molecular Origins of Opposite Solvent Effects on Protein-Protein Interactions

PubMed Central

Vagenende, Vincent; Han, Alvin X.; Pek, Han B.; Loo, Bernard L. W.

2013-01-01

Although the nature of solvent-protein interactions is generally weak and non-specific, addition of cosolvents such as denaturants and osmolytes strengthens protein-protein interactions for some proteins, whereas it weakens protein-protein interactions for others. This is exemplified by the puzzling observation that addition of glycerol oppositely affects the association constants of two antibodies, D1.3 and D44.1, with lysozyme. To resolve this conundrum, we develop a methodology based on the thermodynamic principles of preferential interaction theory and the quantitative characterization of local protein solvation from molecular dynamics simulations. We find that changes of preferential solvent interactions at the protein-protein interface quantitatively account for the opposite effects of glycerol on the antibody-antigen association constants. Detailed characterization of local protein solvation in the free and associated protein states reveals how opposite solvent effects on protein-protein interactions depend on the extent of dewetting of the protein-protein contact region and on structural changes that alter cooperative solvent-protein interactions at the periphery of the protein-protein interface. These results demonstrate the direct relationship between macroscopic solvent effects on protein-protein interactions and atom-scale solvent-protein interactions, and establish a general methodology for predicting and understanding solvent effects on protein-protein interactions in diverse biological environments. PMID:23696727

Quantifying the molecular origins of opposite solvent effects on protein-protein interactions.

PubMed

Vagenende, Vincent; Han, Alvin X; Pek, Han B; Loo, Bernard L W

2013-01-01

Although the nature of solvent-protein interactions is generally weak and non-specific, addition of cosolvents such as denaturants and osmolytes strengthens protein-protein interactions for some proteins, whereas it weakens protein-protein interactions for others. This is exemplified by the puzzling observation that addition of glycerol oppositely affects the association constants of two antibodies, D1.3 and D44.1, with lysozyme. To resolve this conundrum, we develop a methodology based on the thermodynamic principles of preferential interaction theory and the quantitative characterization of local protein solvation from molecular dynamics simulations. We find that changes of preferential solvent interactions at the protein-protein interface quantitatively account for the opposite effects of glycerol on the antibody-antigen association constants. Detailed characterization of local protein solvation in the free and associated protein states reveals how opposite solvent effects on protein-protein interactions depend on the extent of dewetting of the protein-protein contact region and on structural changes that alter cooperative solvent-protein interactions at the periphery of the protein-protein interface. These results demonstrate the direct relationship between macroscopic solvent effects on protein-protein interactions and atom-scale solvent-protein interactions, and establish a general methodology for predicting and understanding solvent effects on protein-protein interactions in diverse biological environments.

Atomic-scale dynamics of a model glass-forming metallic liquid: Dynamical crossover, dynamical decoupling, and dynamical clustering

DOE PAGES

Jaiswal, Abhishek; Egami, Takeshi; Zhang, Yang

2015-04-01

The phase behavior of multi-component metallic liquids is exceedingly complex because of the convoluted many-body and many-elemental interactions. Herein, we present systematic studies of the dynamic aspects of such a model ternary metallic liquid Cu 40Zr 51Al 9 using molecular dynamics simulation with embedded atom method. We observed a dynamical crossover from Arrhenius to super-Arrhenius behavior in the transport properties (diffusion coefficient, relaxation times, and shear viscosity) bordered at T x ~1300K. Unlike in many molecular and macromolecular liquids, this crossover phenomenon occurs in the equilibrium liquid state well above the melting temperature of the system (T m ~ 900K),more » and the crossover temperature is roughly twice of the glass-transition temperature (T g). Below T x, we found the elemental dynamics decoupled and the Stokes-Einstein relation broke down, indicating the onset of heterogeneous spatially correlated dynamics in the system mediated by dynamic communications among local configurational excitations. To directly characterize and visualize the correlated dynamics, we employed a non-parametric, unsupervised machine learning technique and identified dynamical clusters of atoms with similar atomic mobility. The revealed average dynamical cluster size shows an accelerated increase below T x and mimics the trend observed in other ensemble averaged quantities that are commonly used to quantify the spatially heterogeneous dynamics such as the non-Gaussian parameter and the four-point correlation function.« less

Energy dissipation from a correlated system driven out of equilibrium

DOE PAGES

Rameau, J. D.; Freutel, S.; Kemper, A. F.; ...

2016-12-20

We report that in complex materials various interactions have important roles in determining electronic properties. Angle-resolved photoelectron spectroscopy (ARPES) is used to study these processes by resolving the complex single-particle self-energy and quantifying how quantum interactions modify bare electronic states. However, ambiguities in the measurement of the real part of the self-energy and an intrinsic inability to disentangle various contributions to the imaginary part of the self-energy can leave the implications of such measurements open to debate. Here we employ a combined theoretical and experimental treatment of femtosecond time-resolved ARPES (tr-ARPES) show how population dynamics measured using tr-ARPES can bemore » used to separate electron–boson interactions from electron–electron interactions. In conclusion, we demonstrate a quantitative analysis of a well-defined electron–boson interaction in the unoccupied spectrum of the cuprate Bi 2Sr 2CaCu 2O 8+x characterized by an excited population decay time that maps directly to a discrete component of the equilibrium self-energy not readily isolated by static ARPES experiments.« less

Sex differences in leg dexterity are not present in elite athletes.

PubMed

Lawrence, Emily L; Peppoloni, Lorenzo; Valero-Cuevas, Francisco J

2017-10-03

We studied whether the time-varying forces that control unstable foot-ground interactions provide insight into the neural control of dynamic leg function. Twenty elite (10F, 26.4±3.5yrs) and 20 recreational (10F, 24.8±2.4yrs) athletes used an isolated leg to maximally compress a slender spring designed to buckle at low forces while seated. The foot forces during the compression at the edge of instability quantify the maximal sensorimotor ability to control dynamic foot-ground interactions. Using the nonlinear analysis technique of attractor reconstruction, we characterized the spatial (interquartile range IQR) and geometric (trajectory length TL, volume V, and sum of edge lengths SE) features of the dynamical behavior of those force time series. ANOVA confirmed the already published effect of sex, and a new effect of athletic ability, respectively, in TL (p=0.014 and p<0.001), IQR (p=0.008 and p<0.001), V (p=0.034 and p=0.002), and SE (p=0.033 and p<0.001). Further analysis revealed that, for recreational athletes, females exhibited weaker corrective actions and greater stochasticity than males as per their greater mean values of TL (p=0.003), IQR (p=0.018), V (p=0.017), and SE (p=0.025). Importantly, sex differences disappeared in elite athletes. These results provide an empirical link between sex, athletic ability, and nonlinear dynamical control. This is a first step in understanding the sensorimotor mechanisms for control of unstable foot-ground interactions. Given that females suffer a greater incidence of non-contact knee ligament injuries, these non-invasive and practical metrics of leg dexterity may be both indicators of athletic ability, and predictors of risk of injury. Copyright © 2017 Elsevier Ltd. All rights reserved.

How plants connect pollination and herbivory networks and their contribution to community stability.

PubMed

Sauve, Alix M C; Thébault, Elisa; Pocock, Michael J O; Fontaine, Colin

2016-04-01

Pollination and herbivory networks have mainly been studied separately, highlighting their distinct structural characteristics and the related processes and dynamics. However, most plants interact with both pollinators and herbivores, and there is evidence that both types of interaction affect each other. Here we investigated the way plants connect these mutualistic and antagonistic networks together, and the consequences for community stability. Using an empirical data set, we show that the way plants connect pollination and herbivory networks is not random and promotes community stability. Analyses of the structure of binary and quantitative networks show different results: the plants' generalism with regard to pollinators is positively correlated to their generalism with regard to herbivores when considering binary interactions, but not when considering quantitative interactions. We also show that plants that share the same pollinators do not share the same herbivores. However, the way plants connect pollination and herbivory networks promotes stability for both binary and quantitative networks. Our results highlight the relevance of considering the diversity of interaction types in ecological communities, and stress the need to better quantify the costs and benefits of interactions, as well as to develop new metrics characterizing the way different interaction types are combined within ecological networks.

Effect of interaction strength on robustness of controlling edge dynamics in complex networks

NASA Astrophysics Data System (ADS)

Pang, Shao-Peng; Hao, Fei

2018-05-01

Robustness plays a critical role in the controllability of complex networks to withstand failures and perturbations. Recent advances in the edge controllability show that the interaction strength among edges plays a more important role than network structure. Therefore, we focus on the effect of interaction strength on the robustness of edge controllability. Using three categories of all edges to quantify the robustness, we develop a universal framework to evaluate and analyze the robustness in complex networks with arbitrary structures and interaction strengths. Applying our framework to a large number of model and real-world networks, we find that the interaction strength is a dominant factor for the robustness in undirected networks. Meanwhile, the strongest robustness and the optimal edge controllability in undirected networks can be achieved simultaneously. Different from the case of undirected networks, the robustness in directed networks is determined jointly by the interaction strength and the network's degree distribution. Moreover, a stronger robustness is usually associated with a larger number of driver nodes required to maintain full control in directed networks. This prompts us to provide an optimization method by adjusting the interaction strength to optimize the robustness of edge controllability.

Divergent evapotranspiration partition dynamics between shrubs and grasses in a shrub-encroached steppe ecosystem.

PubMed

Wang, Pei; Li, Xiao-Yan; Wang, Lixin; Wu, Xiuchen; Hu, Xia; Fan, Ying; Tong, Yaqin

2018-06-04

Previous evapotranspiration (ET) partitioning studies have usually neglected competitions and interactions between antagonistic plant functional types. This study investigated whether shrubs and grasses have divergent ET partition dynamics impacted by different water-use patterns, canopy structures, and physiological properties in a shrub-encroached steppe ecosystem in Inner Mongolia, China. The soil water-use patterns of shrubs and grasses have been quantified by an isotopic tracing approach and coupled into an improved multisource energy balance model to partition ET fluxes into soil evaporation, grass transpiration, and shrub transpiration. The mean fractional contributions to total ET were 24 ± 13%, 20 ± 4%, and 56 ± 16% for shrub transpiration, grass transpiration, and soil evaporation respectively during the growing season. Difference in ecohydrological connectivity and leaf development both contributed to divergent transpiration partitioning between shrubs and grasses. Shrub-encroachment processes result in larger changes in the ET components than in total ET flux, which could be well explained by changes in canopy resistance, an ecosystem function dominated by the interaction of soil water-use patterns and ecosystem structure. The analyses presented here highlight the crucial effects of vegetation structural changes on the processes of land-atmosphere interaction and climate feedback. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

Quantifying the Dynamic Interactions Between a Clathrin-Coated Pit and Cargo Molecules

NASA Astrophysics Data System (ADS)

Weigel, Aubrey; Tamkun, Michael; Krapf, Diego

2014-03-01

Clathrin-mediated endocytosis is a major pathway of internalization of cargo in eukaryotic cells. This process involves the recruitment of cargo molecules into a growing clathrin-coated pit (CCP). However, cargo-CCP interactions are difficult to study because CCPs display a large degree of lifetime heterogeneity and the interactions with cargo molecules evolve over time. We use single-molecule total internal reflection fluorescence (TIRF) microscopy, in combination with automatic detection and tracking algorithms, to directly visualize the recruitment of individual voltage-gated potassium channels into forming CCPs in living cells. Contrary to widespread ideas, cargo often escapes from a pit before abortive CCP termination or endocytic vesicle production. By measuring tens of thousands of capturing events, we build the distribution of capture times and the times that cargo remains confined to a CCP. An analytical stochastic model is developed and compared to the measured distributions. Due to the dynamic nature of the pit, the model is non-Markovian and it displays long-tail power law statistics. Our findings identify one source of the large heterogeneities observed in CCP maturation and provide a mechanism for the anomalous diffusion of proteins in the plasma membrane. This work was supported by National Science Foundation Grant PHY-0956714.

Multimodal Pressure-Flow Analysis: Application of Hilbert Huang Transform in Cerebral Blood Flow Regulation

NASA Astrophysics Data System (ADS)

Lo, Men-Tzung; Hu, Kun; Liu, Yanhui; Peng, C.-K.; Novak, Vera

2008-12-01

Quantification of nonlinear interactions between two nonstationary signals presents a computational challenge in different research fields, especially for assessments of physiological systems. Traditional approaches that are based on theories of stationary signals cannot resolve nonstationarity-related issues and, thus, cannot reliably assess nonlinear interactions in physiological systems. In this review we discuss a new technique called multimodal pressure flow (MMPF) method that utilizes Hilbert-Huang transformation to quantify interaction between nonstationary cerebral blood flow velocity (BFV) and blood pressure (BP) for the assessment of dynamic cerebral autoregulation (CA). CA is an important mechanism responsible for controlling cerebral blood flow in responses to fluctuations in systemic BP within a few heart-beats. The MMPF analysis decomposes BP and BFV signals into multiple empirical modes adaptively so that the fluctuations caused by a specific physiologic process can be represented in a corresponding empirical mode. Using this technique, we showed that dynamic CA can be characterized by specific phase delays between the decomposed BP and BFV oscillations, and that the phase shifts are significantly reduced in hypertensive, diabetics and stroke subjects with impaired CA. Additionally, the new technique can reliably assess CA using both induced BP/BFV oscillations during clinical tests and spontaneous BP/BFV fluctuations during resting conditions.

Spatially Nonlinear Interdependence of Alpha-Oscillatory Neural Networks under Chan Meditation

PubMed Central

Chang, Chih-Hao

2013-01-01

This paper reports the results of our investigation of the effects of Chan meditation on brain electrophysiological behaviors from the viewpoint of spatially nonlinear interdependence among regional neural networks. Particular emphasis is laid on the alpha-dominated EEG (electroencephalograph). Continuous-time wavelet transform was adopted to detect the epochs containing substantial alpha activities. Nonlinear interdependence quantified by similarity index S(X∣Y), the influence of source signal Y on sink signal X, was applied to the nonlinear dynamical model in phase space reconstructed from multichannel EEG. Experimental group involved ten experienced Chan-Meditation practitioners, while control group included ten healthy subjects within the same age range, yet, without any meditation experience. Nonlinear interdependence among various cortical regions was explored for five local neural-network regions, frontal, posterior, right-temporal, left-temporal, and central regions. In the experimental group, the inter-regional interaction was evaluated for the brain dynamics under three different stages, at rest (stage R, pre-meditation background recording), in Chan meditation (stage M), and the unique Chakra-focusing practice (stage C). Experimental group exhibits stronger interactions among various local neural networks at stages M and C compared with those at stage R. The intergroup comparison demonstrates that Chan-meditation brain possesses better cortical inter-regional interactions than the resting brain of control group. PMID:24489583

Understanding SO2 Capture by Ionic Liquids.

PubMed

Mondal, Anirban; Balasubramanian, Sundaram

2016-05-19

Ionic liquids have generated interest for efficient SO2 absorption due to their low vapor pressure and versatility. In this work, a systematic investigation of the structure, thermodynamics, and dynamics of SO2 absorption by ionic liquids has been carried out through quantum chemical calculations and molecular dynamics (MD) simulations. MP2 level calculations of several ion pairs complexed with SO2 reveal its preferential interaction with the anion. Results of condensed phase MD simulations of SO2-IL mixtures manifested the essential role of both cations and anions in the solvation of SO2, where the solute is surrounded by the "cage" formed by the cations (primarily its alkyl tail) through dispersion interactions. These structural effects of gas absorption are substantiated by calculated Gibbs free energy of solvation; the dissolution is demonstrated to be enthalpy driven. The entropic loss of SO2 absorption in ionic liquids with a larger anion such as [NTf2](-) has been quantified and has been attributed to the conformational restriction of the anion imposed by its interaction with SO2. SO2 loading IL decreases its shear viscosity and enhances the electrical conductivity. This systematic study provides a molecular level understanding which can aid the design of task-specific ILs as electrolytes for efficient SO2 absorption.

Higher-order kinetic expansion of quantum dissipative dynamics: mapping quantum networks to kinetic networks.

PubMed

Wu, Jianlan; Cao, Jianshu

2013-07-28

We apply a new formalism to derive the higher-order quantum kinetic expansion (QKE) for studying dissipative dynamics in a general quantum network coupled with an arbitrary thermal bath. The dynamics of system population is described by a time-convoluted kinetic equation, where the time-nonlocal rate kernel is systematically expanded of the order of off-diagonal elements of the system Hamiltonian. In the second order, the rate kernel recovers the expression of the noninteracting-blip approximation method. The higher-order corrections in the rate kernel account for the effects of the multi-site quantum coherence and the bath relaxation. In a quantum harmonic bath, the rate kernels of different orders are analytically derived. As demonstrated by four examples, the higher-order QKE can reliably predict quantum dissipative dynamics, comparing well with the hierarchic equation approach. More importantly, the higher-order rate kernels can distinguish and quantify distinct nontrivial quantum coherent effects, such as long-range energy transfer from quantum tunneling and quantum interference arising from the phase accumulation of interactions.

The impact of future forest dynamics on climate: interactive effects of changing vegetation and disturbance regimes

PubMed Central

Thom, Dominik; Rammer, Werner; Seidl, Rupert

2018-01-01

Currently, the temperate forest biome cools the earth’s climate and dampens anthropogenic climate change. However, climate change will substantially alter forest dynamics in the future, affecting the climate regulation function of forests. Increasing natural disturbances can reduce carbon uptake and evaporative cooling, but at the same time increase the albedo of a landscape. Simultaneous changes in vegetation composition can mitigate disturbance impacts, but also influence climate regulation directly (e.g., via albedo changes). As a result of a number of interactive drivers (changes in climate, vegetation, and disturbance) and their simultaneous effects on climate-relevant processes (carbon exchange, albedo, latent heat flux) the future climate regulation function of forests remains highly uncertain. Here we address these complex interactions to assess the effect of future forest dynamics on the climate system. Our specific objectives were (1) to investigate the long-term interactions between changing vegetation composition and disturbance regimes under climate change, (2) to quantify the response of climate regulation to changes in forest dynamics, and (3) to identify the main drivers of the future influence of forests on the climate system. We investigated these issues using the individual-based forest landscape and disturbance model (iLand). Simulations were run over 200 yr for Kalkalpen National Park (Austria), assuming different future climate projections, and incorporating dynamically responding wind and bark beetle disturbances. To consistently assess the net effect on climate the simulated responses of carbon exchange, albedo, and latent heat flux were expressed as contributions to radiative forcing. We found that climate change increased disturbances (+27.7% over 200 yr) and specifically bark beetle activity during the 21st century. However, negative feedbacks from a simultaneously changing tree species composition (+28.0% broadleaved species) decreased disturbance activity in the long run (−10.1%), mainly by reducing the host trees available for bark beetles. Climate change and the resulting future forest dynamics significantly reduced the climate regulation function of the landscape, increasing radiative forcing by up to +10.2% on average over 200 yr. Overall, radiative forcing was most strongly driven by carbon exchange. We conclude that future changes in forest dynamics can cause amplifying climate feedbacks from temperate forest ecosystems. PMID:29628526

Infrared thermography of evaporative fluxes and dynamics of salt deposition on heterogeneous porous surfaces

NASA Astrophysics Data System (ADS)

Nachshon, Uri; Shahraeeni, Ebrahim; Or, Dani; Dragila, Maria; Weisbrod, Noam

2011-12-01

Evaporation of saline solutions from porous media, common in arid areas, involves complex interactions between mass transport, energy exchange and phase transitions. We quantified evaporation of saline solutions from heterogeneous sand columns under constant hydraulic boundary conditions to focus on effects of salt precipitation on evaporation dynamics. Mass loss measurements and infrared thermography were used to quantify evaporation rates. The latter method enables quantification of spatial and temporal variability of salt precipitation to identify its dynamic effects on evaporation. Evaporation from columns filled with texturally-contrasting sand using different salt solutions revealed preferential salt precipitation within the fine textured domains. Salt precipitation reduced evaporation rates from the fine textured regions by nearly an order of magnitude. In contrast, low evaporation rates from coarse-textured regions (due to low capillary drive) exhibited less salt precipitation and consequently less evaporation rate suppression. Experiments provided insights into two new phenomena: (1) a distinct increase in evaporation rate at the onset of evaporation; and (2) a vapor pumping mechanism related to the presence of a salt crust over semidry media. Both phenomena are related to local vapor pressure gradients established between pore water and the surface salt crust. Comparison of two salts: NaCl and NaI, which tend to precipitate above the matrix surface and within matrix pores, respectively, shows a much stronger influence of NaCl on evaporation rate suppression. This disparity reflects the limited effect of NaI precipitation on matrix resistivity for solution and vapor flows.

Protein analysis by time-resolved measurements with an electro-switchable DNA chip

PubMed Central

Langer, Andreas; Hampel, Paul A.; Kaiser, Wolfgang; Knezevic, Jelena; Welte, Thomas; Villa, Valentina; Maruyama, Makiko; Svejda, Matej; Jähner, Simone; Fischer, Frank; Strasser, Ralf; Rant, Ulrich

2013-01-01

Measurements in stationary or mobile phases are fundamental principles in protein analysis. Although the immobilization of molecules on solid supports allows for the parallel analysis of interactions, properties like size or shape are usually inferred from the molecular mobility under the influence of external forces. However, as these principles are mutually exclusive, a comprehensive characterization of proteins usually involves a multi-step workflow. Here we show how these measurement modalities can be reconciled by tethering proteins to a surface via dynamically actuated nanolevers. Short DNA strands, which are switched by alternating electric fields, are employed as capture probes to bind target proteins. By swaying the proteins over nanometre amplitudes and comparing their motional dynamics to a theoretical model, the protein diameter can be quantified with Angström accuracy. Alterations in the tertiary protein structure (folding) and conformational changes are readily detected, and even post-translational modifications are revealed by time-resolved molecular dynamics measurements. PMID:23839273

Understanding social forces involved in diabetes outcomes: a systems science approach to quality-of-life research.

PubMed

Lounsbury, David W; Hirsch, Gary B; Vega, Chawntel; Schwartz, Carolyn E

2014-04-01

The field of quality-of-life (QOL) research would benefit from learning about and integrating systems science approaches that model how social forces interact dynamically with health and affect the course of chronic illnesses. Our purpose is to describe the systems science mindset and to illustrate the utility of a system dynamics approach to promoting QOL research in chronic disease, using diabetes as an example. We build a series of causal loop diagrams incrementally, introducing new variables and their dynamic relationships at each stage. These causal loop diagrams demonstrate how a common set of relationships among these variables can generate different disease and QOL trajectories for people with diabetes and also lead to a consideration of non-clinical (psychosocial and behavioral) factors that can have implications for program design and policy formulation. The policy implications of the causal loop diagrams are discussed, and empirical next steps to validate the diagrams and quantify the relationships are described.

Simulations for designing and interpreting intervention trials in infectious diseases.

PubMed

Halloran, M Elizabeth; Auranen, Kari; Baird, Sarah; Basta, Nicole E; Bellan, Steven E; Brookmeyer, Ron; Cooper, Ben S; DeGruttola, Victor; Hughes, James P; Lessler, Justin; Lofgren, Eric T; Longini, Ira M; Onnela, Jukka-Pekka; Özler, Berk; Seage, George R; Smith, Thomas A; Vespignani, Alessandro; Vynnycky, Emilia; Lipsitch, Marc

2017-12-29

Interventions in infectious diseases can have both direct effects on individuals who receive the intervention as well as indirect effects in the population. In addition, intervention combinations can have complex interactions at the population level, which are often difficult to adequately assess with standard study designs and analytical methods. Herein, we urge the adoption of a new paradigm for the design and interpretation of intervention trials in infectious diseases, particularly with regard to emerging infectious diseases, one that more accurately reflects the dynamics of the transmission process. In an increasingly complex world, simulations can explicitly represent transmission dynamics, which are critical for proper trial design and interpretation. Certain ethical aspects of a trial can also be quantified using simulations. Further, after a trial has been conducted, simulations can be used to explore the possible explanations for the observed effects. Much is to be gained through a multidisciplinary approach that builds collaborations among experts in infectious disease dynamics, epidemiology, statistical science, economics, simulation methods, and the conduct of clinical trials.

Real-time intravital microscopy of individual nanoparticle dynamics in liver and tumors of live mice

PubMed Central

van de Ven, Anne L; Kim, Pilhan; Ferrari, Mauro; Yun, Seok Hyun

2013-01-01

Intravital microscopy is emerging as an important experimental tool for the research and development of multi-functional therapeutic nanoconstructs. The direct visualization of nanoparticle dynamics within live animals provides invaluable insights into the mechanisms that regulate nanotherapeutics transport and cell-particle interactions. Here we present a protocol to image the dynamics of nanoparticles within the liver and tumors of live mice immediately following systemic injection using a high-speed (30-400 fps) confocal or multi-photon laser-scanning fluorescence microscope. Techniques for quantifying the real-time accumulation and cellular association of individual particles with a size ranging from several tens of nanometers to micrometers are described, as well as an experimental strategy for labeling Kupffer cells in the liver in vivo. Experimental design considerations and controls are provided, as well as minimum equipment requirements. The entire protocol takes approximately 4-8 hours and yields quantitative information. These techniques can serve to study a wide range of kinetic parameters that drive nanotherapeutics delivery, uptake, and treatment response. PMID:25383179

Dynamic correlations at different time-scales with empirical mode decomposition

NASA Astrophysics Data System (ADS)

Nava, Noemi; Di Matteo, T.; Aste, Tomaso

2018-07-01

We introduce a simple approach which combines Empirical Mode Decomposition (EMD) and Pearson's cross-correlations over rolling windows to quantify dynamic dependency at different time scales. The EMD is a tool to separate time series into implicit components which oscillate at different time-scales. We apply this decomposition to intraday time series of the following three financial indices: the S&P 500 (USA), the IPC (Mexico) and the VIX (volatility index USA), obtaining time-varying multidimensional cross-correlations at different time-scales. The correlations computed over a rolling window are compared across the three indices, across the components at different time-scales and across different time lags. We uncover a rich heterogeneity of interactions, which depends on the time-scale and has important lead-lag relations that could have practical use for portfolio management, risk estimation and investment decisions.

Coupled rotor/airframe vibration analysis

NASA Technical Reports Server (NTRS)

Sopher, R.; Studwell, R. E.; Cassarino, S.; Kottapalli, S. B. R.

1982-01-01

A coupled rotor/airframe vibration analysis developed as a design tool for predicting helicopter vibrations and a research tool to quantify the effects of structural properties, aerodynamic interactions, and vibration reduction devices on vehicle vibration levels is described. The analysis consists of a base program utilizing an impedance matching technique to represent the coupled rotor/airframe dynamics of the system supported by inputs from several external programs supplying sophisticated rotor and airframe aerodynamic and structural dynamic representation. The theoretical background, computer program capabilities and limited correlation results are presented in this report. Correlation results using scale model wind tunnel results show that the analysis can adequately predict trends of vibration variations with airspeed and higher harmonic control effects. Predictions of absolute values of vibration levels were found to be very sensitive to modal characteristics and results were not representative of measured values.

Human mobility in an emerging epidemic: a key aspect for response planning

NASA Astrophysics Data System (ADS)

Poletto, Chiara; Bajardi, Paolo; Colizza, Vittoria; Ramasco, Jose J.; Tizzoni, Michele; Vespignani, Alessandro

2010-03-01

Human mobility and interactions represent key ingredients in the spreading dynamics of an infectious disease. The flows of traveling people form a network characterized by complex features, such as strong topological and traffic heterogeneities, that unfolds at different temporal and spatial scales, from short ranges to the global scale. Computational models can be developed that integrate detailed network structures based on demographic and mobility data, in order to simulate the spatial evolution of an epidemic. Focusing on the recent A(H1N1) influenza pandemic as a paradigmatic example, these approaches allow the assessment of the interplay between individual mobility and epidemic dynamics, quantifying the effects of travel restrictions in delaying the epidemic spread and the role of mobility as an additional source of information for the understanding of the early outbreak.

Structure of the first- and second-neighbor shells of simulated water: Quantitative relation to translational and orientational order

NASA Astrophysics Data System (ADS)

Yan, Zhenyu; Buldyrev, Sergey V.; Kumar, Pradeep; Giovambattista, Nicolas; Debenedetti, Pablo G.; Stanley, H. Eugene

2007-11-01

We perform molecular dynamics simulations of water using the five-site transferable interaction potential (TIP5P) model to quantify structural order in both the first shell (defined by four nearest neighbors) and second shell (defined by twelve next-nearest neighbors) of a central water molecule. We find that the anomalous decrease of orientational order upon compression occurs in both shells, but the anomalous decrease of translational order upon compression occurs mainly in the second shell. The decreases of translational order and orientational order upon compression (called the “structural anomaly”) are thus correlated only in the second shell. Our findings quantitatively confirm the qualitative idea that the thermodynamic, structural, and hence dynamic anomalies of water are related to changes upon compression in the second shell.

An involuntary stereotypical grasp tendency pervades voluntary dynamic multifinger manipulation

PubMed Central

Rácz, Kornelius; Brown, Daniel

2012-01-01

We used a novel apparatus with three hinged finger pads to characterize collaborative multifinger interactions during dynamic manipulation requiring individuated control of fingertip motions and forces. Subjects placed the thumb, index, and middle fingertips on each hinged finger pad and held it—unsupported—with constant total grasp force while voluntarily oscillating the thumb's pad. This task combines the need to 1) hold the object against gravity while 2) dynamically reconfiguring the grasp. Fingertip force variability in this combined motion and force task exhibited strong synchrony among normal (i.e., grasp) forces. Mechanical analysis and simulation show that such synchronous variability is unnecessary and cannot be explained solely by signal-dependent noise. Surprisingly, such variability also pervaded control tasks requiring different individuated fingertip motions and forces, but not tasks without finger individuation such as static grasp. These results critically extend notions of finger force variability by exposing and quantifying a pervasive challenge to dynamic multifinger manipulation: the need for the neural controller to carefully and continuously overlay individuated finger actions over mechanically unnecessary synchronous interactions. This is compatible with—and may explain—the phenomenology of strong coupling of hand muscles when this delicate balance is not yet developed, as in early childhood, or when disrupted, as in brain injury. We conclude that the control of healthy multifinger dynamic manipulation has barely enough neuromechanical degrees of freedom to meet the multiple demands of ecological tasks and critically depends on the continuous inhibition of synchronous grasp tendencies, which we speculate may be of vestigial evolutionary origin. PMID:22956798

Ultrafast non-radiative dynamics of atomically thin MoSe 2

DOE PAGES

Lin, Ming -Fu; Kochat, Vidya; Krishnamoorthy, Aravind; ...

2017-10-17

Non-radiative energy dissipation in photoexcited materials and resulting atomic dynamics provide a promising pathway to induce structural phase transitions in two-dimensional materials. However, these dynamics have not been explored in detail thus far because of incomplete understanding of interaction between the electronic and atomic degrees of freedom, and a lack of direct experimental methods to quantify real-time atomic motion and lattice temperature. Here, we explore the ultrafast conversion of photoenergy to lattice vibrations in a model bi-layered semiconductor, molybdenum diselenide, MoSe 2. Specifically, we characterize sub-picosecond lattice dynamics initiated by the optical excitation of electronic charge carriers in the highmore » electron-hole plasma density regime. Our results focuses on the first ten picosecond dynamics subsequent to photoexcitation before the onset of heat transfer to the substrate, which occurs on a ~100 picosecond time scale. Photoinduced atomic motion is probed by measuring the time dependent Bragg diffraction of a delayed mega-electronvolt femtosecond electron beam. Transient lattice temperatures are characterized through measurement of Bragg peak intensities and calculation of the Debye-Waller factor (DWF). These measurements show a sub-picosecond decay of Bragg diffraction and a correspondingly rapid rise in lattice temperatures. We estimate a high quantum yield for the conversion of excited charge carrier energy to lattice motion under our experimental conditions, indicative of a strong electron-phonon interaction. First principles nonadiabatic quantum molecular dynamics simulations (NAQMD) on electronically excited MoSe 2 bilayers reproduce the observed picosecond-scale increase in lattice temperature and ultrafast conversion of photoenergy to lattice vibrations. Calculation of excited-state phonon dispersion curves suggests that softened vibrational modes in the excited state are involved in efficient and rapid energy transfer between the electronic system and the lattice.« less

Ultrafast non-radiative dynamics of atomically thin MoSe 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Ming -Fu; Kochat, Vidya; Krishnamoorthy, Aravind

Non-radiative energy dissipation in photoexcited materials and resulting atomic dynamics provide a promising pathway to induce structural phase transitions in two-dimensional materials. However, these dynamics have not been explored in detail thus far because of incomplete understanding of interaction between the electronic and atomic degrees of freedom, and a lack of direct experimental methods to quantify real-time atomic motion and lattice temperature. Here, we explore the ultrafast conversion of photoenergy to lattice vibrations in a model bi-layered semiconductor, molybdenum diselenide, MoSe 2. Specifically, we characterize sub-picosecond lattice dynamics initiated by the optical excitation of electronic charge carriers in the highmore » electron-hole plasma density regime. Our results focuses on the first ten picosecond dynamics subsequent to photoexcitation before the onset of heat transfer to the substrate, which occurs on a ~100 picosecond time scale. Photoinduced atomic motion is probed by measuring the time dependent Bragg diffraction of a delayed mega-electronvolt femtosecond electron beam. Transient lattice temperatures are characterized through measurement of Bragg peak intensities and calculation of the Debye-Waller factor (DWF). These measurements show a sub-picosecond decay of Bragg diffraction and a correspondingly rapid rise in lattice temperatures. We estimate a high quantum yield for the conversion of excited charge carrier energy to lattice motion under our experimental conditions, indicative of a strong electron-phonon interaction. First principles nonadiabatic quantum molecular dynamics simulations (NAQMD) on electronically excited MoSe 2 bilayers reproduce the observed picosecond-scale increase in lattice temperature and ultrafast conversion of photoenergy to lattice vibrations. Calculation of excited-state phonon dispersion curves suggests that softened vibrational modes in the excited state are involved in efficient and rapid energy transfer between the electronic system and the lattice.« less

A probabilistic approach to quantifying hydrologic thresholds regulating migration of adult Atlantic salmon into spawning streams

NASA Astrophysics Data System (ADS)

Lazzaro, G.; Soulsby, C.; Tetzlaff, D.; Botter, G.

2017-03-01

Atlantic salmon is an economically and ecologically important fish species, whose survival is dependent on successful spawning in headwater rivers. Streamflow dynamics often have a strong control on spawning because fish require sufficiently high discharges to move upriver and enter spawning streams. However, these streamflow effects are modulated by biological factors such as the number and the timing of returning fish in relation to the annual spawning window in the fall/winter. In this paper, we develop and apply a novel probabilistic approach to quantify these interactions using a parsimonious outflux-influx model linking the number of female salmon emigrating (i.e., outflux) and returning (i.e., influx) to a spawning stream in Scotland. The model explicitly accounts for the interannual variability of the hydrologic regime and the hydrological connectivity of spawning streams to main rivers. Model results are evaluated against a detailed long-term (40 years) hydroecological data set that includes annual fluxes of salmon, allowing us to explicitly assess the role of discharge variability. The satisfactory model results show quantitatively that hydrologic variability contributes to the observed dynamics of salmon returns, with a good correlation between the positive (negative) peaks in the immigration data set and the exceedance (nonexceedance) probability of a threshold flow (0.3 m3/s). Importantly, model performance deteriorates when the interannual variability of flow regime is disregarded. The analysis suggests that flow thresholds and hydrological connectivity for spawning return represent a quantifiable and predictable feature of salmon rivers, which may be helpful in decision making where flow regimes are altered by water abstractions.

Numerical simulations (2D) on the influence of pre-existing local structures and seismic source characteristics in earthquake-volcano interactions

NASA Astrophysics Data System (ADS)

Farías, Cristian; Galván, Boris; Miller, Stephen A.

2017-09-01

Earthquake triggering of hydrothermal and volcanic systems is ubiquitous, but the underlying processes driving these systems are not well-understood. We numerically investigate the influence of seismic wave interaction with volcanic systems simulated as a trapped, high-pressure fluid reservoir connected to a fluid-filled fault system in a 2-D poroelastic medium. Different orientations and earthquake magnitudes are studied to quantify dynamic and static stress, and pore pressure changes induced by a seismic event. Results show that although the response of the system is mainly dominated by characteristics of the radiated seismic waves, local structures can also play an important role on the system dynamics. The fluid reservoir affects the seismic wave front, distorts the static overpressure pattern induced by the earthquake, and concentrates the kinetic energy of the incoming wave on its boundaries. The static volumetric stress pattern inside the fault system is also affected by the local structures. Our results show that local faults play an important role in earthquake-volcanic systems dynamics by concentrating kinetic energy inside and acting as wave-guides that have a breakwater-like behavior. This generates sudden changes in pore pressure, volumetric expansion, and stress gradients. Local structures also influence the regional Coulomb yield function. Our results show that local structures affect the dynamics of volcanic and hydrothermal systems, and should be taken into account when investigating triggering of these systems from nearby or distant earthquakes.

How spatio-temporal habitat connectivity affects amphibian genetic structure

PubMed Central

Watts, Alexander G.; Schlichting, Peter E.; Billerman, Shawn M.; Jesmer, Brett R.; Micheletti, Steven; Fortin, Marie-Josée; Funk, W. Chris; Hapeman, Paul; Muths, Erin; Murphy, Melanie A.

2015-01-01

Heterogeneous landscapes and fluctuating environmental conditions can affect species dispersal, population genetics, and genetic structure, yet understanding how biotic and abiotic factors affect population dynamics in a fluctuating environment is critical for species management. We evaluated how spatio-temporal habitat connectivity influences dispersal and genetic structure in a population of boreal chorus frogs (Pseudacris maculata) using a landscape genetics approach. We developed gravity models to assess the contribution of various factors to the observed genetic distance as a measure of functional connectivity. We selected (a) wetland (within-site) and (b) landscape matrix (between-site) characteristics; and (c) wetland connectivity metrics using a unique methodology. Specifically, we developed three networks that quantify wetland connectivity based on: (i) P. maculata dispersal ability, (ii) temporal variation in wetland quality, and (iii) contribution of wetland stepping-stones to frog dispersal. We examined 18 wetlands in Colorado, and quantified 12 microsatellite loci from 322 individual frogs. We found that genetic connectivity was related to topographic complexity, within- and between-wetland differences in moisture, and wetland functional connectivity as contributed by stepping-stone wetlands. Our results highlight the role that dynamic environmental factors have on dispersal-limited species and illustrate how complex asynchronous interactions contribute to the structure of spatially-explicit metapopulations. PMID:26442094

Multicolor Three-Dimensional Tracking for Single-Molecule Fluorescence Resonance Energy Transfer Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keller, Aaron M.; DeVore, Matthew S.; Stich, Dominik G.

Single-molecule fluorescence resonance energy transfer (smFRET) remains a widely utilized and powerful tool for quantifying heterogeneous interactions and conformational dynamics of biomolecules. However, traditional smFRET experiments either are limited to short observation times (typically less than 1 ms) in the case of “burst” confocal measurements or require surface immobilization which usually has a temporal resolution limited by the camera framing rate. We developed a smFRET 3D tracking microscope that is capable of observing single particles for extended periods of time with high temporal resolution. The confocal tracking microscope utilizes closed-loop feedback to follow the particle in solution by recentering itmore » within two overlapping tetrahedral detection elements, corresponding to donor and acceptor channels. We demonstrated the microscope’s multicolor tracking capability via random walk simulations and experimental tracking of 200 nm fluorescent beads in water with a range of apparent smFRET efficiency values, 0.45-0.69. We also demonstrated the microscope’s capability to track and quantify double-stranded DNA undergoing intramolecular smFRET in a viscous glycerol solution. In future experiments, the smFRET 3D tracking system will be used to study protein conformational dynamics while diffusing in solution and native biological environments with high temporal resolution.« less

Dynamic organization of myristoylated Src in the live cell plasma membrane

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Adam W.; Huang, Hector H.; Endres, Nicholas F.

The spatial organization of lipid-anchored proteins in the plasma membrane directly influences cell signaling, but measuring such organization in situ is experimentally challenging. The canonical oncogene, c-Src, is a lipid anchored protein that plays a key role in integrin-mediated signal transduction within focal adhesions and cell–cell junctions. Because of its activity in specific plasma membrane regions, structural motifs within the protein have been hypothesized to play an important role in its subcellular localization. This study used a combination of time-resolved fluorescence fluctuation spectroscopy and super-resolution microscopy to quantify the dynamic organization of c-Src in live cell membranes. Pulsed-interleaved excitation fluorescencemore » cross-correlation spectroscopy (PIE–FCCS) showed that a small fraction of c-Src transiently sorts into membrane clusters that are several times larger than the monomers. Photoactivated localization microscopy (PALM) confirmed that c-Src partitions into clusters with low probability and showed that the characteristic size of the clusters is 10–80 nm. Finally, time-resolved fluorescence anisotropy measurements were used to quantify the rotational mobility of c-Src to determine how it interacts with its local environment. Altogether, these results build a quantitative description of the mobility and clustering behavior of the c-Src nonreceptor tyrosine kinase in the live cell plasma membrane.« less

Dynamic organization of myristoylated Src in the live cell plasma membrane

DOE PAGES

Smith, Adam W.; Huang, Hector H.; Endres, Nicholas F.; ...

2016-01-15

The spatial organization of lipid-anchored proteins in the plasma membrane directly influences cell signaling, but measuring such organization in situ is experimentally challenging. The canonical oncogene, c-Src, is a lipid anchored protein that plays a key role in integrin-mediated signal transduction within focal adhesions and cell–cell junctions. Because of its activity in specific plasma membrane regions, structural motifs within the protein have been hypothesized to play an important role in its subcellular localization. This study used a combination of time-resolved fluorescence fluctuation spectroscopy and super-resolution microscopy to quantify the dynamic organization of c-Src in live cell membranes. Pulsed-interleaved excitation fluorescencemore » cross-correlation spectroscopy (PIE–FCCS) showed that a small fraction of c-Src transiently sorts into membrane clusters that are several times larger than the monomers. Photoactivated localization microscopy (PALM) confirmed that c-Src partitions into clusters with low probability and showed that the characteristic size of the clusters is 10–80 nm. Finally, time-resolved fluorescence anisotropy measurements were used to quantify the rotational mobility of c-Src to determine how it interacts with its local environment. Altogether, these results build a quantitative description of the mobility and clustering behavior of the c-Src nonreceptor tyrosine kinase in the live cell plasma membrane.« less

Multicolor Three-Dimensional Tracking for Single-Molecule Fluorescence Resonance Energy Transfer Measurements

DOE PAGES

Keller, Aaron M.; DeVore, Matthew S.; Stich, Dominik G.; ...

2018-04-19

Single-molecule fluorescence resonance energy transfer (smFRET) remains a widely utilized and powerful tool for quantifying heterogeneous interactions and conformational dynamics of biomolecules. However, traditional smFRET experiments either are limited to short observation times (typically less than 1 ms) in the case of “burst” confocal measurements or require surface immobilization which usually has a temporal resolution limited by the camera framing rate. We developed a smFRET 3D tracking microscope that is capable of observing single particles for extended periods of time with high temporal resolution. The confocal tracking microscope utilizes closed-loop feedback to follow the particle in solution by recentering itmore » within two overlapping tetrahedral detection elements, corresponding to donor and acceptor channels. We demonstrated the microscope’s multicolor tracking capability via random walk simulations and experimental tracking of 200 nm fluorescent beads in water with a range of apparent smFRET efficiency values, 0.45-0.69. We also demonstrated the microscope’s capability to track and quantify double-stranded DNA undergoing intramolecular smFRET in a viscous glycerol solution. In future experiments, the smFRET 3D tracking system will be used to study protein conformational dynamics while diffusing in solution and native biological environments with high temporal resolution.« less

Spatial distribution of tree species governs the spatio-temporal interaction of leaf area index and soil moisture across a forested landscape.

PubMed

Naithani, Kusum J; Baldwin, Doug C; Gaines, Katie P; Lin, Henry; Eissenstat, David M

2013-01-01

Quantifying coupled spatio-temporal dynamics of phenology and hydrology and understanding underlying processes is a fundamental challenge in ecohydrology. While variation in phenology and factors influencing it have attracted the attention of ecologists for a long time, the influence of biodiversity on coupled dynamics of phenology and hydrology across a landscape is largely untested. We measured leaf area index (L) and volumetric soil water content (θ) on a co-located spatial grid to characterize forest phenology and hydrology across a forested catchment in central Pennsylvania during 2010. We used hierarchical Bayesian modeling to quantify spatio-temporal patterns of L and θ. Our results suggest that the spatial distribution of tree species across the landscape created unique spatio-temporal patterns of L, which created patterns of water demand reflected in variable soil moisture across space and time. We found a lag of about 11 days between increase in L and decline in θ. Vegetation and soil moisture become increasingly homogenized and coupled from leaf-onset to maturity but heterogeneous and uncoupled from leaf maturity to senescence. Our results provide insight into spatio-temporal coupling between biodiversity and soil hydrology that is useful to enhance ecohydrological modeling in humid temperate forests.

How spatio-temporal habitat connectivity affects amphibian genetic structure

USGS Publications Warehouse

Watts, Alexander G.; Schlichting, P; Billerman, S; Jesmer, B; Micheletti, S; Fortin, M.-J.; Funk, W.C.; Hapeman, P; Muths, Erin L.; Murphy, M.A.

2015-01-01

Heterogeneous landscapes and fluctuating environmental conditions can affect species dispersal, population genetics, and genetic structure, yet understanding how biotic and abiotic factors affect population dynamics in a fluctuating environment is critical for species management. We evaluated how spatio-temporal habitat connectivity influences dispersal and genetic structure in a population of boreal chorus frogs (Pseudacris maculata) using a landscape genetics approach. We developed gravity models to assess the contribution of various factors to the observed genetic distance as a measure of functional connectivity. We selected (a) wetland (within-site) and (b) landscape matrix (between-site) characteristics; and (c) wetland connectivity metrics using a unique methodology. Specifically, we developed three networks that quantify wetland connectivity based on: (i) P. maculata dispersal ability, (ii) temporal variation in wetland quality, and (iii) contribution of wetland stepping-stones to frog dispersal. We examined 18 wetlands in Colorado, and quantified 12 microsatellite loci from 322 individual frogs. We found that genetic connectivity was related to topographic complexity, within- and between-wetland differences in moisture, and wetland functional connectivity as contributed by stepping-stone wetlands. Our results highlight the role that dynamic environmental factors have on dispersal-limited species and illustrate how complex asynchronous interactions contribute to the structure of spatially-explicit metapopulations.

Poissonian steady states: from stationary densities to stationary intensities.

PubMed

Eliazar, Iddo

2012-10-01

Markov dynamics are the most elemental and omnipresent form of stochastic dynamics in the sciences, with applications ranging from physics to chemistry, from biology to evolution, and from economics to finance. Markov dynamics can be either stationary or nonstationary. Stationary Markov dynamics represent statistical steady states and are quantified by stationary densities. In this paper, we generalize the notion of steady state to the case of general Markov dynamics. Considering an ensemble of independent motions governed by common Markov dynamics, we establish that the entire ensemble attains Poissonian steady states which are quantified by stationary Poissonian intensities and which hold valid also in the case of nonstationary Markov dynamics. The methodology is applied to a host of Markov dynamics, including Brownian motion, birth-death processes, random walks, geometric random walks, renewal processes, growth-collapse dynamics, decay-surge dynamics, Ito diffusions, and Langevin dynamics.

Poissonian steady states: From stationary densities to stationary intensities

NASA Astrophysics Data System (ADS)

Eliazar, Iddo

2012-10-01

Markov dynamics are the most elemental and omnipresent form of stochastic dynamics in the sciences, with applications ranging from physics to chemistry, from biology to evolution, and from economics to finance. Markov dynamics can be either stationary or nonstationary. Stationary Markov dynamics represent statistical steady states and are quantified by stationary densities. In this paper, we generalize the notion of steady state to the case of general Markov dynamics. Considering an ensemble of independent motions governed by common Markov dynamics, we establish that the entire ensemble attains Poissonian steady states which are quantified by stationary Poissonian intensities and which hold valid also in the case of nonstationary Markov dynamics. The methodology is applied to a host of Markov dynamics, including Brownian motion, birth-death processes, random walks, geometric random walks, renewal processes, growth-collapse dynamics, decay-surge dynamics, Ito diffusions, and Langevin dynamics.

Predicting community responses to perturbations in the face of imperfect knowledge and network complexity

USGS Publications Warehouse

Novak, M.; Wootton, J.T.; Doak, D.F.; Emmerson, M.; Estes, J.A.; Tinker, M.T.

2011-01-01

How best to predict the effects of perturbations to ecological communities has been a long-standing goal for both applied and basic ecology. This quest has recently been revived by new empirical data, new analysis methods, and increased computing speed, with the promise that ecologically important insights may be obtainable from a limited knowledge of community interactions. We use empirically based and simulated networks of varying size and connectance to assess two limitations to predicting perturbation responses in multispecies communities: (1) the inaccuracy by which species interaction strengths are empirically quantified and (2) the indeterminacy of species responses due to indirect effects associated with network size and structure. We find that even modest levels of species richness and connectance (??25 pairwise interactions) impose high requirements for interaction strength estimates because system indeterminacy rapidly overwhelms predictive insights. Nevertheless, even poorly estimated interaction strengths provide greater average predictive certainty than an approach that uses only the sign of each interaction. Our simulations provide guidance in dealing with the trade-offs involved in maximizing the utility of network approaches for predicting dynamics in multispecies communities. ?? 2011 by the Ecological Society of America.

Global coherence of quantum evolutions based on decoherent histories: Theory and application to photosynthetic quantum energy transport

NASA Astrophysics Data System (ADS)

Allegra, Michele; Giorda, Paolo; Lloyd, Seth

2016-04-01

Assessing the role of interference in natural and artificial quantum dynamical processes is a crucial task in quantum information theory. To this aim, an appropriate formalism is provided by the decoherent histories framework. While this approach has been deeply explored from different theoretical perspectives, it still lacks of a comprehensive set of tools able to concisely quantify the amount of coherence developed by a given dynamics. In this paper, we introduce and test different measures of the (average) coherence present in dissipative (Markovian) quantum evolutions, at various time scales and for different levels of environmentally induced decoherence. In order to show the effectiveness of the introduced tools, we apply them to a paradigmatic quantum process where the role of coherence is being hotly debated: exciton transport in photosynthetic complexes. To spot out the essential features that may determine the performance of the transport, we focus on a relevant trimeric subunit of the Fenna-Matthews-Olson complex and we use a simplified (Haken-Strobl) model for the system-bath interaction. Our analysis illustrates how the high efficiency of environmentally assisted transport can be traced back to a quantum recoil avoiding effect on the exciton dynamics, that preserves and sustains the benefits of the initial fast quantum delocalization of the exciton over the network. Indeed, for intermediate levels of decoherence, the bath is seen to selectively kill the negative interference between different exciton pathways, while retaining the initial positive one. The concepts and tools here developed show how the decoherent histories approach can be used to quantify the relation between coherence and efficiency in quantum dynamical processes.

Mechanistic modeling of thermo-hydrological processes and microbial interactions at pore to profile scales resolve methane emission dynamics from permafrost soil

NASA Astrophysics Data System (ADS)

Ebrahimi, Ali; Or, Dani

2017-04-01

The sensitivity of the Earth's polar regions to raising global temperatures is reflected in rapidly changing hydrological processes with pronounced seasonal thawing of permafrost soil and increased biological activity. Of particular concern is the potential release of large amounts of soil carbon and the stimulation of other soil-borne GHG emissions such as methane. Soil methanotrophic and methanogenic microbial communities rapidly adjust their activity and spatial organization in response to permafrost thawing and a host of other environmental factors. Soil structural elements such as aggregates and layering and hydration status affect oxygen and nutrient diffusion processes thereby contributing to methanogenic activity within temporal anoxic niches (hotspots or hot-layers). We developed a mechanistic individual based model to quantify microbial activity dynamics within soil pore networks considering, hydration, temperature, transport processes and enzymatic activity associated with methane production in soil. The model was the upscaled from single aggregates (or hotspots) to quantifying emissions from soil profiles in which freezing/thawing processes provide macroscopic boundary conditions for microbial activity at different soil depths. The model distinguishes microbial activity in aerate bulk soil from aggregates (or submerged parts of the profile) for resolving methane production and oxidation rates. Methane transport pathways through soil by diffusion and ebullition of bubbles vary with hydration dynamics and affect emission patterns. The model links seasonal thermal and hydrologic dynamics with evolution of microbial community composition and function affecting net methane emissions in good agreement with experimental data. The mechanistic model enables systematic evaluation of key controlling factors in thawing permafrost and microbial response (e.g., nutrient availability, enzyme activity, PH) on long term methane emissions and carbon decomposition rates in the rapidly changing polar regions.

Cryptic herbivores mediate the strength and form of ungulate impacts on a long-lived savanna tree.

PubMed

Maclean, Janet E; Goheen, Jacob R; Doak, Daniel F; Palmer, Todd M; Young, Truman P

2011-08-01

Plant populations are regulated by a diverse array of herbivores that impose demographic filters throughout their life cycle. Few studies, however, simultaneously quantify the impacts of multiple herbivore guilds on the lifetime performance or population growth rate of plants. In African savannas, large ungulates (such as elephants) are widely regarded as important drivers of woody plant population dynamics, while the potential impacts of smaller, more cryptic herbivores (such as rodents) have largely been ignored. We combined a large-scale ungulate exclusion experiment with a five-year manipulation of rodent densities to quantify the impacts of three herbivore guilds (wild ungulates, domestic cattle, and rodents) on all life stages of a widespread savanna tree. We utilized demographic modeling to reveal the overall role of each guild in regulating tree population dynamics, and to elucidate the importance of different demographic hurdles in driving population growth under contrasting consumer communities. We found that wild ungulates dramatically reduced population growth, shifting the population trajectory from increase to decline, but that the mechanisms driving these effects were strongly mediated by rodents. The impact of wild ungulates on population growth was predominantly driven by their negative effect on tree reproduction when rodents were excluded, and on adult tree survival when rodents were present. By limiting seedling survival, rodents also reduced population growth; however, this effect was strongly dampened where wild ungulates were present. We suggest that these complex interactions between disparate consumer guilds can have important consequences for the population demography of long-lived species, and that the effects of a single consumer group are often likely to vary dramatically depending on the larger community in which interactions are embedded.

Quantifying the propagation of distress and mental disorders in social networks.

PubMed

Scatà, Marialisa; Di Stefano, Alessandro; La Corte, Aurelio; Liò, Pietro

2018-03-22

Heterogeneity of human beings leads to think and react differently to social phenomena. Awareness and homophily drive people to weigh interactions in social multiplex networks, influencing a potential contagion effect. To quantify the impact of heterogeneity on spreading dynamics, we propose a model of coevolution of social contagion and awareness, through the introduction of statistical estimators, in a weighted multiplex network. Multiplexity of networked individuals may trigger propagation enough to produce effects among vulnerable subjects experiencing distress, mental disorder, which represent some of the strongest predictors of suicidal behaviours. The exposure to suicide is emotionally harmful, since talking about it may give support or inadvertently promote it. To disclose the complex effect of the overlapping awareness on suicidal ideation spreading among disordered people, we also introduce a data-driven approach by integrating different types of data. Our modelling approach unveils the relationship between distress and mental disorders propagation and suicidal ideation spreading, shedding light on the role of awareness in a social network for suicide prevention. The proposed model is able to quantify the impact of overlapping awareness on suicidal ideation spreading and our findings demonstrate that it plays a dual role on contagion, either reinforcing or delaying the contagion outbreak.

A force-based, parallel assay for the quantification of protein-DNA interactions.

PubMed

Limmer, Katja; Pippig, Diana A; Aschenbrenner, Daniela; Gaub, Hermann E

2014-01-01

Analysis of transcription factor binding to DNA sequences is of utmost importance to understand the intricate regulatory mechanisms that underlie gene expression. Several techniques exist that quantify DNA-protein affinity, but they are either very time-consuming or suffer from possible misinterpretation due to complicated algorithms or approximations like many high-throughput techniques. We present a more direct method to quantify DNA-protein interaction in a force-based assay. In contrast to single-molecule force spectroscopy, our technique, the Molecular Force Assay (MFA), parallelizes force measurements so that it can test one or multiple proteins against several DNA sequences in a single experiment. The interaction strength is quantified by comparison to the well-defined rupture stability of different DNA duplexes. As a proof-of-principle, we measured the interaction of the zinc finger construct Zif268/NRE against six different DNA constructs. We could show the specificity of our approach and quantify the strength of the protein-DNA interaction.

Fire, flow and dynamic equilibrium in stream macroinvertebrate communities

USGS Publications Warehouse

Arkle, R.S.; Pilliod, D.S.; Strickler, K.

2010-01-01

The complex effects of disturbances on ecological communities can be further complicated by subsequent perturbations within an ecosystem. We investigated how wildfire interacts with annual variations in peak streamflow to affect the stability of stream macroinvertebrate communities in a central Idaho wilderness, USA. We conducted a 4-year retrospective analysis of unburned (n = 7) and burned (n = 6) catchments, using changes in reflectance values (??NBR) from satellite imagery to quantify the percentage of each catchment's riparian and upland vegetation that burned at high and low severity. For this wildland fire complex, increasing riparian burn severity and extent were associated with greater year-to-year variation, rather than a perennial increase, in sediment loads, organic debris, large woody debris (LWD) and undercut bank structure. Temporal changes in these variables were correlated with yearly peak flow in burned catchments but not in unburned reference catchments, indicating that an interaction between fire and flow can result in decreased habitat stability in burned catchments. Streams in more severely burned catchments exhibited increasingly dynamic macroinvertebrate communities and did not show increased similarity to reference streams over time. Annual variability in macroinvertebrates was attributed, predominantly, to the changing influence of sediment, LWD, riparian cover and organic debris, as quantities of these habitat components fluctuated annually depending on burn severity and annual peak streamflows. These analyses suggest that interactions among fire, flow and stream habitat may increase inter-annual habitat variability and macroinvertebrate community dynamics for a duration approaching the length of the historic fire return interval of the study area. ?? 2009 Blackwell Publishing Ltd.

Quantitative Proteomics Reveals Dynamic Interactions of the Minichromosome Maintenance Complex (MCM) in the Cellular Response to Etoposide Induced DNA Damage.

PubMed

Drissi, Romain; Dubois, Marie-Line; Douziech, Mélanie; Boisvert, François-Michel

2015-07-01

The minichromosome maintenance complex (MCM) proteins are required for processive DNA replication and are a target of S-phase checkpoints. The eukaryotic MCM complex consists of six proteins (MCM2-7) that form a heterohexameric ring with DNA helicase activity, which is loaded on chromatin to form the pre-replication complex. Upon entry in S phase, the helicase is activated and opens the DNA duplex to recruit DNA polymerases at the replication fork. The MCM complex thus plays a crucial role during DNA replication, but recent work suggests that MCM proteins could also be involved in DNA repair. Here, we employed a combination of stable isotope labeling with amino acids in cell culture (SILAC)-based quantitative proteomics with immunoprecipitation of green fluorescent protein-tagged fusion proteins to identify proteins interacting with the MCM complex, and quantify changes in interactions in response to DNA damage. Interestingly, the MCM complex showed very dynamic changes in interaction with proteins such as Importin7, the histone chaperone ASF1, and the Chromodomain helicase DNA binding protein 3 (CHD3) following DNA damage. These changes in interactions were accompanied by an increase in phosphorylation and ubiquitination on specific sites on the MCM proteins and an increase in the co-localization of the MCM complex with γ-H2AX, confirming the recruitment of these proteins to sites of DNA damage. In summary, our data indicate that the MCM proteins is involved in chromatin remodeling in response to DNA damage. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

What drives interaction strengths in complex food webs? A test with feeding rates of a generalist stream predator.

PubMed

Preston, Daniel L; Henderson, Jeremy S; Falke, Landon P; Segui, Leah M; Layden, Tamara J; Novak, Mark

2018-05-08

Describing the mechanisms that drive variation in species interaction strengths is central to understanding, predicting, and managing community dynamics. Multiple factors have been linked to trophic interaction strength variation, including species densities, species traits, and abiotic factors. Yet most empirical tests of the relative roles of multiple mechanisms that drive variation have been limited to simplified experiments that may diverge from the dynamics of natural food webs. Here, we used a field-based observational approach to quantify the roles of prey density, predator density, predator-prey body-mass ratios, prey identity, and abiotic factors in driving variation in feeding rates of reticulate sculpin (Cottus perplexus). We combined data on over 6,000 predator-prey observations with prey identification time functions to estimate 289 prey-specific feeding rates at nine stream sites in Oregon. Feeding rates on 57 prey types showed an approximately log-normal distribution, with few strong and many weak interactions. Model selection indicated that prey density, followed by prey identity, were the two most important predictors of prey-specific sculpin feeding rates. Feeding rates showed a positive relationship with prey taxon densities that was inconsistent with predator saturation predicted by current functional response models. Feeding rates also exhibited four orders-of-magnitude in variation across prey taxonomic orders, with the lowest feeding rates observed on prey with significant anti-predator defenses. Body-mass ratios were the third most important predictor variable, showing a hump-shaped relationship with the highest feeding rates at intermediate ratios. Sculpin density was negatively correlated with feeding rates, consistent with the presence of intraspecific predator interference. Our results highlight how multiple co-occurring drivers shape trophic interactions in nature and underscore ways in which simplified experiments or reliance on scaling laws alone may lead to biased inferences about the structure and dynamics of species-rich food webs. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Entropy Transfer between Residue Pairs and Allostery in Proteins: Quantifying Allosteric Communication in Ubiquitin

PubMed Central

2017-01-01

It has recently been proposed by Gunasakaran et al. that allostery may be an intrinsic property of all proteins. Here, we develop a computational method that can determine and quantify allosteric activity in any given protein. Based on Schreiber's transfer entropy formulation, our approach leads to an information transfer landscape for the protein that shows the presence of entropy sinks and sources and explains how pairs of residues communicate with each other using entropy transfer. The model can identify the residues that drive the fluctuations of others. We apply the model to Ubiquitin, whose allosteric activity has not been emphasized until recently, and show that there are indeed systematic pathways of entropy and information transfer between residues that correlate well with the activities of the protein. We use 600 nanosecond molecular dynamics trajectories for Ubiquitin and its complex with human polymerase iota and evaluate entropy transfer between all pairs of residues of Ubiquitin and quantify the binding susceptibility changes upon complex formation. We explain the complex formation propensities of Ubiquitin in terms of entropy transfer. Important residues taking part in allosteric communication in Ubiquitin predicted by our approach are in agreement with results of NMR relaxation dispersion experiments. Finally, we show that time delayed correlation of fluctuations of two interacting residues possesses an intrinsic causality that tells which residue controls the interaction and which one is controlled. Our work shows that time delayed correlations, entropy transfer and causality are the required new concepts for explaining allosteric communication in proteins. PMID:28095404

An Investigation of Land-Atmosphere Coupling from Local to Regional Scales

NASA Astrophysics Data System (ADS)

Brunsell, N. A.; Van Vleck, E.; Rahn, D. A.

2017-12-01

The exchanges of mass and energy between the surface and atmosphere have been shown to depend upon both local and regional climatic influences. However, the degree of control exerted by the land surface on the coupling metrics is not well understood. In particular, we lack an understanding of the relationship between the local microclimate of a site and the regional forces responsible for land-atmosphere coupling. To address this, we investigate a series of metrics calculated from eddy covariance data and ceilometer data, land surface modeling and remotely sensed observations in the central United States to diagnose these interactions and predict the change from one coupling regime (e.g. wet/dry coupling) to another state. The stability of the coupling is quantified using a Lyapunov exponent based methodology. Through the use of a wavelet information theoretic approach, we isolate the roles local energy partitioning, as well as the temperature and moisture gradients on controlling and changing the coupling regime. Taking a multi-scale observational approach, we first examine the relationship at the tower scale. Using land surface models, we quantify to what extent current models are capable of properly diagnosing the dynamics of the coupling regime. In particular, we focus on the role of the surface moisture and vegetation to initiate and maintain precipitation feedbacks. We extend this analysis to the regional scale by utilizing reanalysis and remotely sensed observations. Thus, we are able to quantify the changes in observed coupling patterns with linkages to local interactions to address the question of the local control that the surface exerts over the maintenance of land-atmosphere coupling.

An attempt to quantify aerosol-cloud effects in fields of precipitating trade wind cumuli

NASA Astrophysics Data System (ADS)

Seifert, Axel; Heus, Thijs

2015-04-01

Aerosol indirect effects are notoriously difficult to understand and quantify. Using large-eddy simulations (LES) we attempt to quantify the impact of aerosols on the albedo and the precipitation formation in trade wind cumulus clouds. Having performed a set of large-domain Giga-LES runs we are able to capture the mesoscale self-organization of the cloud field. Our simulations show that self-organization is intrinsically tied to precipitation formation in this cloud regime making previous studies that did not consider cloud organization questionable. We find that aerosols, here modeled just as a perturbation in cloud droplet number concentration, have a significant impact on the transient behavior, i.e., how fast rain is formed and self-organization of the cloud field takes place. Though, for longer integration times, all simulations approach the same radiative-convective equilibrium and aerosol effects become small. The sensitivity to aerosols becomes even smaller when we include explicit cloud-radiation interaction as this leads to a much faster and more vigorous response of the cloud layer. Overall we find that aerosol-cloud interactions, like cloud lifetime effects etc., are small or even negative when the cloud field is close to equilibrium. Consequently, the Twomey effect does already provide an upper bound on the albedo effects of aerosol perturbations. Our analysis also highlights that current parameterizations that predict only the grid-box mean of the cloud field and do not take into account cloud organization are not able to describe aerosol indirect effects correctly, but overestimate them due to that lack of cloud dynamical and mesoscale buffering.

A separate role for ICAM-1 and fluid shear in regulating leukocyte interactions with straight regions of venular wall and venular convergences

PubMed Central

Sumagin, Ronen; Lamkin-Kennard, Kathleen A.; Sarelius, Ingrid H

2011-01-01

Objective Variation in expression of adhesion molecules plays a key role in regulating leukocyte behavior, but the contribution of fluid shear to these interactions cannot be ignored. Here we dissected the effects of each of these factors on leukocyte behavior in different venular regions. Methods Leukocyte behavior was quantified in blood perfused microvascular networks in anesthetized mouse cremaster muscle using intravital confocal microscopy. ICAM-1 expression and fluid shear rate were quantified using ICAM-1 fluorescent labeling, fluorescent particle tracking, and computational fluid dynamics. Results TNFα-induced an increase in ICAM-1 expression, and abolished the differences observed among control venules of different sizes. Consequently, leukocyte adhesion was increased to a similar level across all vessel sizes (5.1±0.46 leukocytes/100μm vs. 2.1±0.47 [control]), but remained significantly higher in venular convergences (7.8±0.4). Leukocyte transmigration occurred primarily in the smallest venules and venular convergences (23.9±5.1 and 31.9±2.7 leukocytes/10,000μm2 tissue, respectively). In venular convergences the two inlet vessels are predicted to create a region of low velocity, increasing leukocyte adhesion probability. Conclusions In straight regions of different sized venules the variability in ICAM-1 expression accounts for the differences in leukocyte behavior; in converging regions, fluid shear potentially has a greater effect on leukocyte-EC interactions. PMID:19468960

Parental and Infant Gender Factors in Parent-Infant Interaction: State-Space Dynamic Analysis.

PubMed

Cerezo, M Angeles; Sierra-García, Purificación; Pons-Salvador, Gemma; Trenado, Rosa M

2017-01-01

This study aimed to investigate the influence of parental gender on their interaction with their infants, considering, as well, the role of the infant's gender. The State Space Grid (SSG) method, a graphical tool based on the non-linear dynamic system (NDS) approach was used to analyze the interaction, in Free-Play setting, of 52 infants, aged 6 to 10 months, divided into two groups: half of the infants interacted with their fathers and half with their mothers. There were 50% boys in each group. MANOVA results showed no differential parenting of boys and girls. Additionally, mothers and fathers showed no differences in the Diversity of behavioral dyadic states nor in Predictability. However, differences associated with parent's gender were found in that the paternal dyads were more "active" than the maternal dyads: they were faster in the rates per second of behavioral events and transitions or change of state. In contrast, maternal dyads were more repetitive because, once they visited a certain dyadic state, they tend to be involved in more events. Results showed a significant discriminant function on the parental groups, fathers and mothers. Specifically, the content analyses carried out for the three NDS variables, that previously showed differences between groups, showed particular dyadic behavioral states associated with the rate of Transitions and the Events per Visit ratio. Thus, the transitions involving 'in-out' of 'Child Social Approach neutral - Sensitive Approach neutral' state and the repetitions of events in the dyadic state 'Child Play-Sensitive Approach neutral' distinguished fathers from mothers. The classification of dyads (with fathers and mothers) based on this discriminant function identified 73.10% (19/26) of the father-infant dyads and 88.5% (23/26) of the mother-infant dyads. The study of father-infant interaction using the SSG approach offers interesting possibilities because it characterizes and quantifies the actual moment-to-moment flow of parent-infant interactive dynamics. Our findings showed how observational methods applied to natural contexts offer new facets in father vs. mother interactive behavior with their infants that can inform further developments in this field.

Parallel Force Assay for Protein-Protein Interactions

PubMed Central

Aschenbrenner, Daniela; Pippig, Diana A.; Klamecka, Kamila; Limmer, Katja; Leonhardt, Heinrich; Gaub, Hermann E.

2014-01-01

Quantitative proteome research is greatly promoted by high-resolution parallel format assays. A characterization of protein complexes based on binding forces offers an unparalleled dynamic range and allows for the effective discrimination of non-specific interactions. Here we present a DNA-based Molecular Force Assay to quantify protein-protein interactions, namely the bond between different variants of GFP and GFP-binding nanobodies. We present different strategies to adjust the maximum sensitivity window of the assay by influencing the binding strength of the DNA reference duplexes. The binding of the nanobody Enhancer to the different GFP constructs is compared at high sensitivity of the assay. Whereas the binding strength to wild type and enhanced GFP are equal within experimental error, stronger binding to superfolder GFP is observed. This difference in binding strength is attributed to alterations in the amino acids that form contacts according to the crystal structure of the initial wild type GFP-Enhancer complex. Moreover, we outline the potential for large-scale parallelization of the assay. PMID:25546146

Parallel force assay for protein-protein interactions.

PubMed

Aschenbrenner, Daniela; Pippig, Diana A; Klamecka, Kamila; Limmer, Katja; Leonhardt, Heinrich; Gaub, Hermann E

2014-01-01

Quantitative proteome research is greatly promoted by high-resolution parallel format assays. A characterization of protein complexes based on binding forces offers an unparalleled dynamic range and allows for the effective discrimination of non-specific interactions. Here we present a DNA-based Molecular Force Assay to quantify protein-protein interactions, namely the bond between different variants of GFP and GFP-binding nanobodies. We present different strategies to adjust the maximum sensitivity window of the assay by influencing the binding strength of the DNA reference duplexes. The binding of the nanobody Enhancer to the different GFP constructs is compared at high sensitivity of the assay. Whereas the binding strength to wild type and enhanced GFP are equal within experimental error, stronger binding to superfolder GFP is observed. This difference in binding strength is attributed to alterations in the amino acids that form contacts according to the crystal structure of the initial wild type GFP-Enhancer complex. Moreover, we outline the potential for large-scale parallelization of the assay.

Scaling and self-organized criticality in proteins: Lysozyme c

NASA Astrophysics Data System (ADS)

Phillips, J. C.

2009-11-01

Proteins appear to be the most dramatic natural example of self-organized criticality (SOC), a concept that explains many otherwise apparently unlikely phenomena. Protein functionality is often dominated by long-range hydro(phobic/philic) interactions, which both drive protein compaction and mediate protein-protein interactions. In contrast to previous reductionist short-range hydrophobicity scales, the holistic Moret-Zebende hydrophobicity scale [Phys. Rev. E 75, 011920 (2007)] represents a hydroanalytic tool that bioinformatically quantifies SOC in a way fully compatible with evolution. Hydroprofiling identifies chemical trends in the activities and substrate binding abilities of model enzymes and antibiotic animal lysozymes c , as well as defensins, which have been the subject of tens of thousands of experimental studies. The analysis is simple and easily performed and immediately yields insights not obtainable by traditional methods based on short-range real-space interactions, as described either by classical force fields used in molecular-dynamics simulations, or hydrophobicity scales based on transference energies from water to organic solvents or solvent-accessible areas.

Effect of Culverts on Predator-Prey Interactions in a Tropical Stream.

NASA Astrophysics Data System (ADS)

Hein, C. L.; Kikkert, D. A.; Crowl, T. A.

2005-05-01

As part of a biocomplexity project in Puerto Rico, we use river and road networks as a platform to understand the interactions between stream biota, the physical environment, and human activity. Specifically, we ask if humans affect aquatic organisms through road building and recreational activities. Culverts have been documented to impede or slow migration of aquatic biota. This is especially important in these streams because all of the freshwater, stream species have diadramous life cycles. If culverts do act as bottlenecks to shrimp migrations, we expect altered predator-prey interactions downstream through density-dependent predation dynamics. In order to determine how roads may affect predation rates on upstream migrating shrimp, we parameterized functional response curves for mountain mullet (Agonostomus monticola) consuming shrimp (Xiphocaris sp.) using artificial mesocosm experiments. We then used data obtained from underwater videography to determine how culverts decrease the rate and number of shrimp moving upstream. These data were combined in a predator-prey model to quantify the effects of culverts on localized shrimp densities and fish predation.

Conserved conformational selection mechanism of Hsp70 chaperone-substrate interactions

PubMed Central

Velyvis, Algirdas; Zoltsman, Guy; Rosenzweig, Rina; Bouvignies, Guillaume

2018-01-01

Molecular recognition is integral to biological function and frequently involves preferred binding of a molecule to one of several exchanging ligand conformations in solution. In such a process the bound structure can be selected from the ensemble of interconverting ligands a priori (conformational selection, CS) or may form once the ligand is bound (induced fit, IF). Here we focus on the ubiquitous and conserved Hsp70 chaperone which oversees the integrity of the cellular proteome through its ATP-dependent interaction with client proteins. We directly quantify the flux along CS and IF pathways using solution NMR spectroscopy that exploits a methyl TROSY effect and selective isotope-labeling methodologies. Our measurements establish that both bacterial and human Hsp70 chaperones interact with clients by selecting the unfolded state from a pre-existing array of interconverting structures, suggesting a conserved mode of client recognition among Hsp70s and highlighting the importance of molecular dynamics in this recognition event. PMID:29460778

Dynamic and label-free high-throughput detection of biomolecular interactions based on phase-shift interferometry

NASA Astrophysics Data System (ADS)

Li, Qiang; Huang, Guoliang; Gan, Wupeng; Chen, Shengyi

2009-08-01

Biomolecular interactions can be detected by many established technologies such as fluorescence imaging, surface plasmon resonance (SPR)[1-4], interferometry and radioactive labeling of the analyte. In this study, we have designed and constructed a label-free, real-time sensing platform and its operating imaging instrument that detects interactions using optical phase differences from the accumulation of biological material on solid substrates. This system allows us to monitor biomolecular interactions in real time and quantify concentration changes during micro-mixing processes by measuring the changes of the optical path length (OPD). This simple interferometric technology monitors the optical phase difference resulting from accumulated biomolecular mass. A label-free protein chip that forms a 4×4 probe array was designed and fabricated using a commercial microarray robot spotter on solid substrates. Two positive control probe lines of BSA (Bovine Serum Albumin) and two experimental human IgG and goat IgG was used. The binding of multiple protein targets was performed and continuously detected by using this label-free and real-time sensing platform.

Energetics and Dynamics Across the Bcl-2-Regulated Apoptotic Pathway Reveal Distinct Evolutionary Determinants of Specificity and Affinity.

PubMed

Ivanov, Stefan M; Huber, Roland G; Warwicker, Jim; Bond, Peter J

2016-11-01

Critical regulatory pathways are replete with instances of intra- and interfamily protein-protein interactions due to the pervasiveness of gene duplication throughout evolution. Discerning the specificity determinants within these systems has proven a challenging task. Here, we present an energetic analysis of the specificity determinants within the Bcl-2 family of proteins (key regulators of the intrinsic apoptotic pathway) via a total of ∼20 μs of simulation of 60 distinct protein-protein complexes. We demonstrate where affinity and specificity of protein-protein interactions arise across the family, and corroborate our conclusions with extensive experimental evidence. We identify energy and specificity hotspots that may offer valuable guidance in the design of targeted therapeutics for manipulating the protein-protein interactions within the apoptosis-regulating pathway. Moreover, we propose a conceptual framework that allows us to quantify the relationship between sequence, structure, and binding energetics. This approach may represent a general methodology for investigating other paralogous protein-protein interaction sites. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quantification of the memory effect of steady-state currents from interaction-induced transport in quantum systems

NASA Astrophysics Data System (ADS)

Lai, Chen-Yen; Chien, Chih-Chun

2017-09-01

Dynamics of a system in general depends on its initial state and how the system is driven, but in many-body systems the memory is usually averaged out during evolution. Here, interacting quantum systems without external relaxations are shown to retain long-time memory effects in steady states. To identify memory effects, we first show quasi-steady-state currents form in finite, isolated Bose- and Fermi-Hubbard models driven by interaction imbalance and they become steady-state currents in the thermodynamic limit. By comparing the steady-state currents from different initial states or ramping rates of the imbalance, long-time memory effects can be quantified. While the memory effects of initial states are more ubiquitous, the memory effects of switching protocols are mostly visible in interaction-induced transport in lattices. Our simulations suggest that the systems enter a regime governed by a generalized Fick's law and memory effects lead to initial-state-dependent diffusion coefficients. We also identify conditions for enhancing memory effects and discuss possible experimental implications.

DeepPIV: Particle image velocimetry measurements using deep-sea, remotely operated vehicles

NASA Astrophysics Data System (ADS)

Katija, Kakani; Sherman, Alana; Graves, Dale; Klimov, Denis; Kecy, Chad; Robison, Bruce

2015-11-01

The midwater region of the ocean (below the euphotic zone and above the benthos) is one of the largest ecosystems on our planet, yet remains one of the least explored. Little-known marine organisms that inhabit midwater have developed life strategies that contribute to their evolutionary success, and may inspire engineering solutions for societally relevant challenges. Although significant advances in underwater vehicle technologies have improved access to midwater, small-scale, in situ fluid mechanics measurement methods that seek to quantify the interactions that midwater organisms have with their physical environment are lacking. Here we present DeepPIV, an instrumentation package affixed to remotely operated vehicles that quantifies fluid motions from the surface of the ocean down to 4000 m depths. Utilizing ambient suspended particulate, fluid-structure interactions are evaluated on a range of marine organisms in midwater. Initial science targets include larvaceans, biological equivalents of flapping flexible foils, that create mucus houses to filter food. Little is known about the structure of these mucus houses and the function they play in selectively filtering particles, and these dynamics can serve as particle-mucus models for human health. Using DeepPIV, we reveal the complex structures and flows generated within larvacean mucus houses, and elucidate how these structures function. Funding is gratefully acknowledged from the Packard Foundation.

A conceptual model for quantifying connectivity using graph theory and cellular (per-pixel) approach

NASA Astrophysics Data System (ADS)

Singh, Manudeo; Sinha, Rajiv; Tandon, Sampat K.

2016-04-01

The concept of connectivity is being increasingly used for understanding hydro-geomorphic processes at all spatio-temporal scales. Connectivity is defined as the potential for energy and material flux (water, sediments, nutrients, heat, etc.) to navigate within or between the landscape systems and has two components, structural connectivity and dynamic connectivity. Structural connectivity is defined by the spatially connected features (physical linkages) through which energy and materials flow. Dynamic connectivity is a process defined connectivity component. These two connectivity components also interact with each other by forming a feedback system. This study attempts to explore a method to quantify structural and dynamic connectivity. In fluvial transport systems, sediment and water can flow in either a diffused manner or in a channelized way. At all the scales, hydrological and sediment fluxes can be tracked using a cellular (per-pixel) approach and can be quantified using graphical approach. The material flux, slope and LULC (Land Use Land Cover) weightage factors of a pixel together determine if it will contribute towards connectivity of the landscape/system. In a graphical approach, all the contributing pixels will form a node at their centroid and this node will be connected to the next 'down-node' via a directed edge with 'least cost path'. The length of the edge will depend on the desired spatial scale and its path direction will depend on the traversed pixel's slope and the LULC (weightage) factors. The weightage factors will lie in-between 0 to 1. This value approaches 1 for the LULC factors which promote connectivity. For example, in terms of sediment connectivity, the weightage could be RUSLE (Revised Universal Soil Loss Equation) C-factors with bare unconsolidated surfaces having values close to 1. This method is best suited for areas with low slopes, where LULC can be a deciding as well as dominating factor. The degree of connectivity and its pathways will show changes under different LULC conditions even if the slope remains the same. The graphical approach provides the statistics of connected and disconnected graph elements (edges, nodes) and graph components, thereby allowing the quantification of structural connectivity. This approach also quantifies the dynamic connectivity by allowing the measurement of the fluxes (e.g. via hydrographs or sedimentographs) at any node as well as at any system outlet. The contribution of any sub-system can be understood by removing the remaining sub-systems which can be conveniently achieved by masking associated graph elements.

Propagation of hydroclimatic variability through the critical zone

NASA Astrophysics Data System (ADS)

Porporato, A. M.; Calabrese, S.; Parolari, A.

2016-12-01

The interaction between soil moisture dynamics and mineral-weathering reactions (e.g., ion exchange, precipitation-dissolution) affects the availability of nutrients to plants, composition of soils, soil acidification, as well as CO2 sequestration. Across the critical zone (CZ), this interaction is responsible for propagating hydroclimatic fluctuations to deeper soil layers, controlling weathering rates via leaching events which intermittently alter the alkalinity levels. In this contribution, we analyze these dynamics using a stochastic modeling approach based on spatially lumped description of soil hydrology and chemical weathering reactions forced by multi-scale temporal hydrologic variability. We quantify the role of soil moisture dynamics in filtering the rainfall fluctuations through its impacts on soil water chemistry, described by a system of ordinary differential equations (and algebraic equations, for the equilibrium reactions), driving the evolution of alkalinity, pH, the chemical species of the soil solution, and the mineral-weathering rate. A probabilistic description of the evolution of the critical zone is thus obtained, allowing us to describe the CZ response to long-term climate fluctuations, ecosystem and land-use conditions, in terms of key variables groups. The model is applied to the weathering rate of albite in the Calhoun CZ observatory and then extended to explore similarities and differences across other CZs. Typical time scales of response and degrees of sensitivities of CZ to hydroclimatic fluctuations and human forcing are also explored.

Information dynamics of brain-heart physiological networks during sleep

NASA Astrophysics Data System (ADS)

Faes, L.; Nollo, G.; Jurysta, F.; Marinazzo, D.

2014-10-01

This study proposes an integrated approach, framed in the emerging fields of network physiology and information dynamics, for the quantitative analysis of brain-heart interaction networks during sleep. With this approach, the time series of cardiac vagal autonomic activity and brain wave activities measured respectively as the normalized high frequency component of heart rate variability and the EEG power in the δ, θ, α, σ, and β bands, are considered as realizations of the stochastic processes describing the dynamics of the heart system and of different brain sub-systems. Entropy-based measures are exploited to quantify the predictive information carried by each (sub)system, and to dissect this information into a part actively stored in the system and a part transferred to it from the other connected systems. The application of this approach to polysomnographic recordings of ten healthy subjects led us to identify a structured network of sleep brain-brain and brain-heart interactions, with the node described by the β EEG power acting as a hub which conveys the largest amount of information flowing between the heart and brain nodes. This network was found to be sustained mostly by the transitions across different sleep stages, as the information transfer was weaker during specific stages than during the whole night, and vanished progressively when moving from light sleep to deep sleep and to REM sleep.

Investigation of electric charge on inertial particle dynamics in turbulence

NASA Astrophysics Data System (ADS)

Lu, Jiang; Shaw, Raymond

2014-11-01

The behavior of electrically charged, inertial particles in homogeneous, isotropic turbulence is investigated. Both like-charged and oppositely-charged particle interactions are considered. Direct numerical simulations (DNS) of turbulence in a periodic box using the pseudospectral numerical method are performed, with Lagrangian tracking of the particles. We study effects of mutual electrostatic repulsion and attraction on the particle dynamics, as quantified by the radial distribution function (RDF) and the radial relative velocity. For the like-charged particle case, the Coulomb force leads to a short range repulsion behavior and an RDF reminiscent of that for a dilute gas. For the oppositely-charged particle case, the Coulomb force increases the RDF beyond that already occurring for neutral inertial particles. For both cases, the relative velocities are calculated as a function of particle separation distance and show distinct deviations from the expected scaling within the dissipation range. This research was supported by NASA Grant NNX113AF90G.

Variance decomposition in stochastic simulators.

PubMed

Le Maître, O P; Knio, O M; Moraes, A

2015-06-28

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Reputation drives cooperative behaviour and network formation in human groups.

PubMed

Cuesta, Jose A; Gracia-Lázaro, Carlos; Ferrer, Alfredo; Moreno, Yamir; Sánchez, Angel

2015-01-19

Cooperativeness is a defining feature of human nature. Theoreticians have suggested several mechanisms to explain this ubiquitous phenomenon, including reciprocity, reputation, and punishment, but the problem is still unsolved. Here we show, through experiments conducted with groups of people playing an iterated Prisoner's Dilemma on a dynamic network, that it is reputation what really fosters cooperation. While this mechanism has already been observed in unstructured populations, we find that it acts equally when interactions are given by a network that players can reconfigure dynamically. Furthermore, our observations reveal that memory also drives the network formation process, and cooperators assort more, with longer link lifetimes, the longer the past actions record. Our analysis demonstrates, for the first time, that reputation can be very well quantified as a weighted mean of the fractions of past cooperative acts and the last action performed. This finding has potential applications in collaborative systems and e-commerce.

Model structures amplify uncertainty in predicted soil carbon responses to climate change.

PubMed

Shi, Zheng; Crowell, Sean; Luo, Yiqi; Moore, Berrien

2018-06-04

Large model uncertainty in projected future soil carbon (C) dynamics has been well documented. However, our understanding of the sources of this uncertainty is limited. Here we quantify the uncertainties arising from model parameters, structures and their interactions, and how those uncertainties propagate through different models to projections of future soil carbon stocks. Both the vertically resolved model and the microbial explicit model project much greater uncertainties to climate change than the conventional soil C model, with both positive and negative C-climate feedbacks, whereas the conventional model consistently predicts positive soil C-climate feedback. Our findings suggest that diverse model structures are necessary to increase confidence in soil C projection. However, the larger uncertainty in the complex models also suggests that we need to strike a balance between model complexity and the need to include diverse model structures in order to forecast soil C dynamics with high confidence and low uncertainty.

Evolution of Secondary Software Businesses: Understanding Industry Dynamics

NASA Astrophysics Data System (ADS)

Tyrväinen, Pasi; Warsta, Juhani; Seppänen, Veikko

Primary software industry originates from IBM's decision to unbundle software-related computer system development activities to external partners. This kind of outsourcing from an enterprise internal software development activity is a common means to start a new software business serving a vertical software market. It combines knowledge of the vertical market process with competence in software development. In this research, we present and analyze the key figures of the Finnish secondary software industry, in order to quantify its interaction with the primary software industry during the period of 2000-2003. On the basis of the empirical data, we present a model for evolution of a secondary software business, which makes explicit the industry dynamics. It represents the shift from internal software developed for competitive advantage to development of products supporting standard business processes on top of standardized technologies. We also discuss the implications for software business strategies in each phase.

Reputation drives cooperative behaviour and network formation in human groups

PubMed Central

Cuesta, Jose A.; Gracia-Lázaro, Carlos; Ferrer, Alfredo; Moreno, Yamir; Sánchez, Angel

2015-01-01

Cooperativeness is a defining feature of human nature. Theoreticians have suggested several mechanisms to explain this ubiquitous phenomenon, including reciprocity, reputation, and punishment, but the problem is still unsolved. Here we show, through experiments conducted with groups of people playing an iterated Prisoner's Dilemma on a dynamic network, that it is reputation what really fosters cooperation. While this mechanism has already been observed in unstructured populations, we find that it acts equally when interactions are given by a network that players can reconfigure dynamically. Furthermore, our observations reveal that memory also drives the network formation process, and cooperators assort more, with longer link lifetimes, the longer the past actions record. Our analysis demonstrates, for the first time, that reputation can be very well quantified as a weighted mean of the fractions of past cooperative acts and the last action performed. This finding has potential applications in collaborative systems and e-commerce. PMID:25598347

Topographic Cues Reveal Two Distinct Spreading Mechanisms in Blood Platelets

PubMed Central

Sandmann, Rabea; Köster, Sarah

2016-01-01

Blood platelets are instrumental in blood clotting and are thus heavily involved in early wound closure. After adhering to a substrate they spread by forming protrusions like lamellipodia and filopodia. However, the interaction of these protrusions with the physical environment of platelets while spreading is not fully understood. Here we dynamically image platelets during this spreading process and compare their behavior on smooth and on structured substrates. In particular we analyze the temporal evolution of the spread area, the cell morphology and the dynamics of individual filopodia. Interestingly, the topographic cues enable us to distinguish two spreading mechanisms, one that is based on numerous persistent filopodia and one that rather involves lamellipodia. Filopodia-driven spreading coincides with a strong response of platelet morphology to the substrate topography during spreading, whereas lamellipodia-driven spreading does not. Thus, we quantify different degrees of filopodia formation in platelets and the influence of filopodia in spreading on structured substrates. PMID:26934830

Perturbations for transient acceleration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vargas, Cristofher Zuñiga; Zimdahl, Winfried; Hipólito-Ricaldi, Wiliam S., E-mail: win_unac@hotmail.com, E-mail: hipolito@ceunes.ufes.br, E-mail: winfried.zimdahl@pq.cnpq.br

2012-04-01

According to the standard ΛCDM model, the accelerated expansion of the Universe will go on forever. Motivated by recent observational results, we explore the possibility of a finite phase of acceleration which asymptotically approaches another period of decelerated expansion. Extending an earlier study on a corresponding homogeneous and isotropic dynamics, in which interactions between dark matter and dark energy are crucial, the present paper also investigates the dynamics of the matter perturbations both on the Newtonian and General Relativistic (GR) levels and quantifies the potential relevance of perturbations of the dark-energy component. In the background, the model is tested againstmore » the Supernova type Ia (SNIa) data of the Constitution set and on the perturbative level against growth rate data, among them those of the WiggleZ survey, and the data of the 2dFGRS project. Our results indicate that a transient phase of accelerated expansion is not excluded by current observations.« less

Static Aeroelastic Predictions for a Transonic Transport Model Using an Unstructured-Grid Flow Solver Coupled With a Structural Plate Technique

NASA Technical Reports Server (NTRS)

Allison, Dennis O.; Cavallo, Peter A.

2003-01-01

An equivalent-plate structural deformation technique was coupled with a steady-state unstructured-grid three-dimensional Euler flow solver and a two-dimensional strip interactive boundary-layer technique. The objective of the research was to assess the extent to which a simple accounting for static model deformations could improve correlations with measured wing pressure distributions and lift coefficients at transonic speeds. Results were computed and compared to test data for a wing-fuselage model of a generic low-wing transonic transport at a transonic cruise condition over a range of Reynolds numbers and dynamic pressures. The deformations significantly improved correlations with measured wing pressure distributions and lift coefficients. This method provided a means of quantifying the role of dynamic pressure in wind-tunnel studies of Reynolds number effects for transonic transport models.

Variance decomposition in stochastic simulators

NASA Astrophysics Data System (ADS)

Le Maître, O. P.; Knio, O. M.; Moraes, A.

2015-06-01

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Towards Quantification of Glacier Dynamic Ice Loss through Passive Seismic Monitoring

NASA Astrophysics Data System (ADS)

Köhler, A.; Nuth, C.; Weidle, C.; Schweitzer, J.; Kohler, J.; Buscaino, G.

2015-12-01

Global glaciers and ice caps loose mass through calving, while existing models are currently not equipped to realistically predict dynamic ice loss. This is mainly because long-term continuous calving records, that would help to better understand fine scale processes and key climatic-dynamic feedbacks between calving, climate, terminus evolution and marine conditions, do not exist. Combined passive seismic/acoustic strategies are the only technique able to capture rapid calving events continuously, independent of daylight or meteorological conditions. We have produced such a continuous calving record for Kronebreen, a tidewater glacier in Svalbard, using data from permanent seismic stations between 2001 and 2014. However, currently no method has been established in cryo-seismology to quantify the calving ice loss directly from seismic data. Independent calibration data is required to derive 1) a realistic estimation of the dynamic ice loss unobserved due to seismic noise and 2) a robust scaling of seismic calving signals to ice volumes. Here, we analyze the seismic calving record at Kronebreen and independent calving data in a first attempt to quantify ice loss directly from seismic records. We make use of a) calving flux data with weekly to monthly resolution obtained from satellite remote sensing and GPS data between 2007 and 2013, and b) direct, visual calving observations in two weeks in 2009 and 2010. Furthermore, the magnitude-scaling property of seismic calving events is analyzed. We derive and discuss an empirical relation between seismic calving events and calving flux which for the first time allows to estimate a time series of calving volumes more than one decade back in time. Improving our model requires to incorporate more precise, high-resolution calibration data. A new field campaign will combine innovative, multi-disciplinary monitoring techniques to measure calving ice volumes and dynamic ice-ocean interactions simultaneously with terrestrial laser scanning and a temporary seismic/underwater-acoustic network.

Molecular dynamics simulation of the partitioning of benzocaine and phenytoin into a lipid bilayer.

PubMed

Martin, Lewis J; Chao, Rebecca; Corry, Ben

2014-01-01

Molecular dynamics simulations were used to examine the partitioning behaviour of the local anaesthetic benzocaine and the anti-epileptic phenytoin into lipid bilayers, a factor that is critical to their mode of action. Free energy methods are used to quantify the thermodynamics of drug movement between water and octanol as well as for permeation across a POPC membrane. Both drugs are shown to favourably partition into the lipid bilayer from water and are likely to accumulate just inside the lipid headgroups where they may alter bilayer properties or interact with target proteins. Phenytoin experiences a large barrier to cross the centre of the bilayer due to less favourable energetic interactions in this less dense region of the bilayer. Remarkably, in our simulations both drugs are able to pull water into the bilayer, creating water chains that extend back to bulk, and which may modify the local bilayer properties. We find that the choice of atomic partial charges can have a significant impact on the quantitative results, meaning that careful validation of parameters for new drugs, such as performed here, should be performed prior to their use in biomolecular simulations. Copyright © 2013 Elsevier B.V. All rights reserved.

Filtering Meteoroid Flights Using Multiple Unscented Kalman Filters

NASA Astrophysics Data System (ADS)

Sansom, E. K.; Bland, P. A.; Rutten, M. G.; Paxman, J.; Towner, M. C.

2016-11-01

Estimator algorithms are immensely versatile and powerful tools that can be applied to any problem where a dynamic system can be modeled by a set of equations and where observations are available. A well designed estimator enables system states to be optimally predicted and errors to be rigorously quantified. Unscented Kalman filters (UKFs) and interactive multiple models can be found in methods from satellite tracking to self-driving cars. The luminous trajectory of the Bunburra Rockhole fireball was observed by the Desert Fireball Network in mid-2007. The recorded data set is used in this paper to examine the application of these two techniques as a viable approach to characterizing fireball dynamics. The nonlinear, single-body system of equations, used to model meteoroid entry through the atmosphere, is challenged by gross fragmentation events that may occur. The incorporation of the UKF within an interactive multiple model smoother provides a likely solution for when fragmentation events may occur as well as providing a statistical analysis of the state uncertainties. In addition to these benefits, another advantage of this approach is its automatability for use within an image processing pipeline to facilitate large fireball data analyses and meteorite recoveries.

Metabolomic Modularity Analysis (MMA) to Quantify Human Liver Perfusion Dynamics.

PubMed

Sridharan, Gautham Vivek; Bruinsma, Bote Gosse; Bale, Shyam Sundhar; Swaminathan, Anandh; Saeidi, Nima; Yarmush, Martin L; Uygun, Korkut

2017-11-13

Large-scale -omics data are now ubiquitously utilized to capture and interpret global responses to perturbations in biological systems, such as the impact of disease states on cells, tissues, and whole organs. Metabolomics data, in particular, are difficult to interpret for providing physiological insight because predefined biochemical pathways used for analysis are inherently biased and fail to capture more complex network interactions that span multiple canonical pathways. In this study, we introduce a nov-el approach coined Metabolomic Modularity Analysis (MMA) as a graph-based algorithm to systematically identify metabolic modules of reactions enriched with metabolites flagged to be statistically significant. A defining feature of the algorithm is its ability to determine modularity that highlights interactions between reactions mediated by the production and consumption of cofactors and other hub metabolites. As a case study, we evaluated the metabolic dynamics of discarded human livers using time-course metabolomics data and MMA to identify modules that explain the observed physiological changes leading to liver recovery during subnormothermic machine perfusion (SNMP). MMA was performed on a large scale liver-specific human metabolic network that was weighted based on metabolomics data and identified cofactor-mediated modules that would not have been discovered by traditional metabolic pathway analyses.

System dynamics-based evaluation of interventions to promote appropriate waste disposal behaviors in low-income urban areas: A Baltimore case study.

PubMed

Guo, Huaqing; Hobbs, Benjamin F; Lasater, Molly E; Parker, Cindy L; Winch, Peter J

2016-10-01

Inappropriate waste disposal is a serious issue in many urban neighborhoods, exacerbating environmental, rodent, and public health problems. Governments all over the world have been developing interventions to reduce inappropriate waste disposal. A system dynamics model is proposed to quantify the impacts of interventions on residential waste related behavior. In contrast to other models of municipal solid waste management, the structure of our model is based on sociological and economic studies on how incentives and social norms interactively affect waste disposal behavior, and its parameterization is informed by field work. A case study of low-income urban neighborhoods in Baltimore, MD, USA is presented. The simulation results show the effects of individual interventions, and also identify positive interactions among some potential interventions, especially information and incentive-based policies, as well as their limitations. The model can help policy analysts identify the most promising intervention packages, and then field test those few, rather than having to pilot test all combinations. Sensitivity analyses demonstrate large uncertainties about behavioral responses to some interventions, showing where information from survey research and social experiments would improve policy making. Copyright © 2016 Elsevier Ltd. All rights reserved.

Nonlinear shear wave interaction at a frictional interface: energy dissipation and generation of harmonics.

PubMed

Meziane, A; Norris, A N; Shuvalov, A L

2011-10-01

Analytical and numerical modeling of the nonlinear interaction of shear wave with a frictional interface is presented. The system studied is composed of two homogeneous and isotropic elastic solids, brought into frictional contact by remote normal compression. A shear wave, either time harmonic or a narrow band pulse, is incident normal to the interface and propagates through the contact. Two friction laws are considered and the influence on interface behavior is investigated: Coulomb's law with a constant friction coefficient and a slip-weakening friction law which involves static and dynamic friction coefficients. The relationship between the nonlinear harmonics and the dissipated energy, and the dependence on the contact dynamics (friction law, sliding, and tangential stress) and on the normal contact stress are examined in detail. The analytical and numerical results indicate universal type laws for the amplitude of the higher harmonics and for the dissipated energy, properly non-dimensionalized in terms of the pre-stress, the friction coefficient and the incident amplitude. The results suggest that measurements of higher harmonics can be used to quantify friction and dissipation effects of a sliding interface. © 2011 Acoustical Society of America

Epistasis × environment interactions among Arabidopsis thaliana glucosinolate genes impact complex traits and fitness in the field.

PubMed

Kerwin, Rachel E; Feusier, Julie; Muok, Alise; Lin, Catherine; Larson, Brandon; Copeland, Daniel; Corwin, Jason A; Rubin, Matthew J; Francisco, Marta; Li, Baohua; Joseph, Bindu; Weinig, Cynthia; Kliebenstein, Daniel J

2017-08-01

Despite the growing number of studies showing that genotype × environment and epistatic interactions control fitness, the influences of epistasis × environment interactions on adaptive trait evolution remain largely uncharacterized. Across three field trials, we quantified aliphatic glucosinolate (GSL) defense chemistry, leaf damage, and relative fitness using mutant lines of Arabidopsis thaliana varying at pairs of causal aliphatic GSL defense genes to test the impact of epistatic and epistasis × environment interactions on adaptive trait variation. We found that aliphatic GSL accumulation was primarily influenced by additive and epistatic genetic variation, leaf damage was primarily influenced by environmental variation and relative fitness was primarily influenced by epistasis and epistasis × environment interactions. Epistasis × environment interactions accounted for up to 48% of the relative fitness variation in the field. At a single field site, the impact of epistasis on relative fitness varied significantly over 2 yr, showing that epistasis × environment interactions within a location can be temporally dynamic. These results suggest that the environmental dependency of epistasis can profoundly influence the response to selection, shaping the adaptive trajectories of natural populations in complex ways, and deserves further consideration in future evolutionary studies. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Thermodynamic fingerprints of non-Markovianity in a system of coupled superconducting qubits

NASA Astrophysics Data System (ADS)

Hamedani Raja, Sina; Borrelli, Massimo; Schmidt, Rebecca; Pekola, Jukka P.; Maniscalco, Sabrina

2018-03-01

The exploitation and characterization of memory effects arising from the interaction between system and environment is a key prerequisite for quantum reservoir engineering beyond the standard Markovian limit. In this paper we investigate a prototype of non-Markovian dynamics experimentally implementable with superconducting qubits. We rigorously quantify non-Markovianity, highlighting the effects of the environmental temperature on the Markovian to non-Markovian crossover. We investigate how memory effects influence, and specifically suppress, the ability to perform work on the driven qubit. We show that the average work performed on the qubit can be used as a diagnostic tool to detect the presence or absence of memory effects.

Heterogeneity and Self-Organization of Complex Systems Through an Application to Financial Market with Multiagent Systems

NASA Astrophysics Data System (ADS)

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

2017-12-01

Multiagent systems (MAS) provide a useful tool for exploring the complex dynamics and behavior of financial markets and now MAS approach has been widely implemented and documented in the empirical literature. This paper introduces the implementation of an innovative multi-scale mathematical model for a computational agent-based financial market. The paper develops a method to quantify the degree of self-organization which emerges in the system and shows that the capacity of self-organization is maximized when the agent behaviors are heterogeneous. Numerical results are presented and analyzed, showing how the global market behavior emerges from specific individual behavior interactions.

SEASAT economic assessment

NASA Technical Reports Server (NTRS)

Hicks, K.; Steele, W.

1974-01-01

The SEASAT program will provide scientific and economic benefits from global remote sensing of the ocean's dynamic and physical characteristics. The program as presently envisioned consists of: (1) SEASAT A; (2) SEASAT B; and (3) Operational SEASAT. This economic assessment was to identify, rationalize, quantify and validate the economic benefits evolving from SEASAT. These benefits will arise from improvements in the operating efficiency of systems that interface with the ocean. SEASAT data will be combined with data from other ocean and atmospheric sampling systems and then processed through analytical models of the interaction between oceans and atmosphere to yield accurate global measurements and global long range forecasts of ocean conditions and weather.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fang, X.; Xia, C.; Keppens, R.

We present the first multidimensional, magnetohydrodynamic simulations that capture the initial formation and long-term sustainment of the enigmatic coronal rain phenomenon. We demonstrate how thermal instability can induce a spectacular display of in situ forming blob-like condensations which then start their intimate ballet on top of initially linear force-free arcades. Our magnetic arcades host a chromospheric, transition region, and coronal plasma. Following coronal rain dynamics for over 80 minutes of physical time, we collect enough statistics to quantify blob widths, lengths, velocity distributions, and other characteristics which directly match modern observational knowledge. Our virtual coronal rain displays the deformation ofmore » blobs into V-shaped features, interactions of blobs due to mostly pressure-mediated levitations, and gives the first views of blobs that evaporate in situ or are siphoned over the apex of the background arcade. Our simulations pave the way for systematic surveys of coronal rain showers in true multidimensional settings to connect parameterized heating prescriptions with rain statistics, ultimately allowing us to quantify the coronal heating input.« less

Binary dislocation junction formation and strength in hexagonal close-packed crystals

DOE PAGES

Wu, Chi -Chin; Aubry, Sylvie; Arsenlis, Athanasios; ...

2015-12-17

This work examines binary dislocation interactions, junction formation and junction strengths in hexagonal close-packed ( hcp ) crystals. Through a line-tension model and dislocation dynamics (DD) simulations, the interaction and dissociation of different sets of binary junctions are investigated involving one dislocation on the (011¯0) prismatic plane and a second dislocation on one of the following planes: (0001) basal, (11¯00) prismatic, (11¯01) primary pyramidal, or (2¯112) secondary pyramidal. Varying pairs of Burgers vectors are chosen from among the common types the basal type < a > 1/3 < 112¯0 >, prismatic type < c > <0001>, and pyramidal type 1/3 < 112¯3¯ >. For binary interaction due to dislocation intersection, both the analytical results and DD-simulations indicate a relationship between symmetry of interaction maps and the relative magnitude of the Burgers vectors that constitute the junction. Using analytical formulae, a simple regressive model is also developed to represent the junction yield surface. The equation is treated as a degenerated super elliptical equation to quantify the aspect ratio and tilting angle. Lastly, the results provide analytical insights on binary dislocation interactions that may occur in general hcp metals.« less

Predator–prey interactions mediated by prey personality and predator hunting mode

PubMed Central

Belgrad, Benjamin A.; Griffen, Blaine D.

2016-01-01

Predator–prey interactions are important drivers in structuring ecological communities. However, despite widespread acknowledgement that individual behaviours and predator species regulate ecological processes, studies have yet to incorporate individual behavioural variations in a multipredator system. We quantified a prevalent predator avoidance behaviour to examine the simultaneous roles of prey personality and predator hunting mode in governing predator–prey interactions. Mud crabs, Panopeus herbstii, reduce their activity levels and increase their refuge use in the presence of predator cues. We measured mud crab mortality and consistent individual variations in the strength of this predator avoidance behaviour in the presence of predatory blue crabs, Callinectes sapidus, and toadfish, Opsanus tau. We found that prey personality and predator species significantly interacted to affect mortality with blue crabs primarily consuming bold mud crabs and toadfish preferentially selecting shy crabs. Additionally, the strength of the predator avoidance behaviour depended upon the predation risk from the predator species. Consequently, the personality composition of populations and predator hunting mode may be valuable predictors of both direct and indirect predator–prey interaction strength. These findings support theories postulating mechanisms for maintaining intraspecies diversity and have broad implications for community dynamics. PMID:27075257

Predator-prey interactions mediated by prey personality and predator hunting mode.

PubMed

Belgrad, Benjamin A; Griffen, Blaine D

2016-04-13

Predator-prey interactions are important drivers in structuring ecological communities. However, despite widespread acknowledgement that individual behaviours and predator species regulate ecological processes, studies have yet to incorporate individual behavioural variations in a multipredator system. We quantified a prevalent predator avoidance behaviour to examine the simultaneous roles of prey personality and predator hunting mode in governing predator-prey interactions. Mud crabs, Panopeus herbstii, reduce their activity levels and increase their refuge use in the presence of predator cues. We measured mud crab mortality and consistent individual variations in the strength of this predator avoidance behaviour in the presence of predatory blue crabs, Callinectes sapidus, and toadfish, Opsanus tau We found that prey personality and predator species significantly interacted to affect mortality with blue crabs primarily consuming bold mud crabs and toadfish preferentially selecting shy crabs. Additionally, the strength of the predator avoidance behaviour depended upon the predation risk from the predator species. Consequently, the personality composition of populations and predator hunting mode may be valuable predictors of both direct and indirect predator-prey interaction strength. These findings support theories postulating mechanisms for maintaining intraspecies diversity and have broad implications for community dynamics. © 2016 The Author(s).

Stratification Pattern of Static and Scale-Invariant Dynamic Measures of Heartbeat Fluctuations Across Sleep Stages in Young and Elderly

PubMed Central

Schmitt, Daniel T.; Stein, Phyllis K.; Ivanov, Plamen Ch.

2010-01-01

Cardiac dynamics exhibit complex variability characterized by scale-invariant and nonlinear temporal organization related to the mechanism of neuroautonomic control, which changes with physiologic states and pathologic conditions. Changes in sleep regulation during sleep stages are also related to fluctuations in autonomic nervous activity. However, the interaction between sleep regulation and cardiac autonomic control remains not well understood. Even less is known how this interaction changes with age, as aspects of both cardiac dynamics and sleep regulation differ in healthy elderly compared to young subjects. We hypothesize that because of the neuroautonomic responsiveness in young subjects, fractal and nonlinear features of cardiac dynamics exhibit a pronounced stratification pattern across sleep stages, while in elderly these features will remain unchanged due to age-related loss of cardiac variability and decline of neuroautonomic responsiveness. We analyze the variability and the temporal fractal organization of heartbeat fluctuations across sleep stages in both young and elderly. We find that independent linear and nonlinear measures of cardiac control consistently exhibit the same ordering in their values across sleep stages, forming a robust stratification pattern. Despite changes in sleep architecture and reduced heart rate variability in elderly subjects, this stratification surprisingly does not break down with advanced age. Moreover, the difference between sleep stages for some linear, fractal, and nonlinear measures exceeds the difference between young and elderly, suggesting that the effect of sleep regulation on cardiac dynamics is significantly stronger than the effect of healthy aging. Quantifying changes in this stratification pattern may provide insights into how alterations in sleep regulation contribute to increased cardiac risk. PMID:19203874

To Which Extent can Aerosols Affect Alpine Mixed-Phase Clouds?

NASA Astrophysics Data System (ADS)

Henneberg, O.; Lohmann, U.

2017-12-01

Aerosol-cloud interactions constitute a high uncertainty in regional climate and changing weather patterns. Such uncertainties are due to the multiple processes that can be triggered by aerosol especially in mixed-phase clouds. Mixed-phase clouds most likely result in precipitation due to the formation of ice crystals, which can grow to precipitation size. Ice nucleating particles (INPs) determine how fast these clouds glaciate and form precipitation. The potential for INP to transfer supercooled liquid clouds to precipitating clouds depends on the available humidity and supercooled liquid. Those conditions are determined by dynamics. Moderately high updraft velocities result in persistent mixed-phase clouds in the Swiss Alps [1], which provide an ideal testbed to investigate the effect of aerosol on precipitation in mixed-phase clouds. To address the effect of aerosols in orographic winter clouds under different dynamic conditions, we run a number of real case ensembles with the regional climate model COSMO on a horizontal resolution of 1.1 km. Simulations with different INP concentrations within the range observed at the GAW research station Jungfraujoch in the Swiss Alps are conducted and repeated within the ensemble. Microphysical processes are described with a two-moment scheme. Enhanced INP concentrations enhance the precipitation rate of a single precipitation event up to 20%. Other precipitation events of similar strength are less affected by the INP concentration. The effect of CCNs is negligible for precipitation from orographic winter clouds in our case study. There is evidence for INP to change precipitation rate and location more effectively in stronger dynamic regimes due to the enhanced potential to transfer supercooled liquid to ice. The classification of the ensemble members according to their dynamics will quantify the interaction of aerosol effects and dynamics. Reference [1] Lohmann et al, 2016: Persistence of orographic mixed-phase clouds, GRL

The Effect of Stem- and Canopy-Scale Turbulence on Sediment Dynamics within Submerged Vegetation.

NASA Astrophysics Data System (ADS)

Tinoco, R. O.; San Juan Blanco, J. E.; Prada, A. F.

2017-12-01

Stem- and canopy-scale turbulence generated by submerged patches of vegetation plays a paramount role on sediment transport within aquatic ecosystems such as wetlands, marshes, mangrove forests, and coastal regions, as dense patches dampen velocities and mean bed stresses within the plants, while also increasing turbulence intensity through stem-scale wakes and canopy-scale eddies. To explore the interactions between such processes, laboratory experiments are conducted using rigid cylinders placed in a staggered configuration as vegetation elements, embedded on a non-cohesive sediment bed in a racetrack flume. Quantitative imaging is used to characterize the flow field and the associated suspended sediment concentration throughout the water column at different submergence ratios, defined as the ratio between water depth, H, and plant height, h, to investigate the role of canopy-scale eddies formed at the top of the canopy, and their interaction with near-bed flow structures, on sediment dynamics. Turbulent kinetic energy, turbulent intensity, and Reynolds stresses are quantified within and above the array to clearly identify the contributions from bed generated turbulence and vegetation generated turbulence, at both stem- and canopy-scale, as submergence ratio increases from emergent, H/h=1, to fully submerged, H/h=5, conditions. The experimental results are compared with transport models to highlight the need for a multi-scale approach to represent flow-vegetation-sediment interactions.

The Molecular Structure of a Phosphatidylserine Bilayer Determined by Scattering and Molecular Dynamics Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pan, Jianjun; Cheng, Xiaolin; Monticelli, Luca

2014-01-01

Phosphatidylserine (PS) lipids play essential roles in biological processes, including enzyme activation and apoptosis. We report on the molecular structure and atomic scale interactions of a fluid bilayer composed of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylserine (POPS). A scattering density profile model, aided by molecular dynamics (MD) simulations, was developed to jointly refine different contrast small-angle neutron and X-ray scattering data, which yielded a lipid area of 62.7 A2 at 25 C. MD simulations with POPS lipid area constrained at different values were also performed using all-atom and aliphatic united-atom models. The optimal simulated bilayer was obtained using a model-free comparison approach. Examination of themore » simulated bilayer, which agrees best with the experimental scattering data, reveals a preferential interaction between Na+ ions and the terminal serine and phosphate moieties. Long-range inter-lipid interactions were identified, primarily between the positively charged ammonium, and the negatively charged carboxylic and phosphate oxygens. The area compressibility modulus KA of the POPS bilayer was derived by quantifying lipid area as a function of surface tension from area-constrained MD simulations. It was found that POPS bilayers possess a much larger KA than that of neutral phosphatidylcholine lipid bilayers. We propose that the unique molecular features of POPS bilayers may play an important role in certain physiological functions.« less

On the Mediterranean Sea inter-basin exchanges and nutrient dynamics

NASA Astrophysics Data System (ADS)

Rupolo, V.; Ribera D'Alcalà, M.; Iudicone, D.; Artale, V.

2009-04-01

The Mediterranean Sea is an evaporative basin in which the deficit of water is supplied by the inflow from the Gibraltar Strait of Atlantic Water. The net result of the air sea interactions in the entire basin is an outflow at Gibraltar of a salty water that is mainly constituted by the Levantin Intermediate Water, formed in the eastern part of the basin. Despite this simplified pattern, the circulation in the Mediterranean is rather complex. Most of the Mediterranean sub-basins are characterized by water mass formation processes and the presence of sills and straits strongly influence both the spreading and the mixing of intermediate and deep waters. In this context a Lagrangian diagnostics applied to numerical results was used to quantify mass transport in the main pathways of the upper and lower cells of the Mediterranean thermohaline circulation as they results from OGCM simulations. Lagrangian diagnostics reveals to be very useful to quantify both transports between different regions and the associated spectrum of transit times by means of pdf distribution of particles transit times between the different regions of the basin. This method is very effective to estimate the contribution of different water masses in isopycnal and diapycnal transformation processes and in reconstructing the fate of tracers. We use here these previous results on the basin circulation for better understanding the nutrient dynamics within the basin where the inputs from the different sources (atmosphere, runoff and open ocean) have similar order of magnitude. This, to the aim of building scenarios on the impact of climate driven changes in elemental fluxes to the basin on the internal nutrient dynamics.

A Generalized Framework for Reduced-Order Modeling of a Wind Turbine Wake

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamilton, Nicholas; Viggiano, Bianca; Calaf, Marc

A reduced-order model for a wind turbine wake is sought from large eddy simulation data. Fluctuating velocity fields are combined in the correlation tensor to form the kernel of the proper orthogonal decomposition (POD). Proper orthogonal decomposition modes resulting from the decomposition represent the spatially coherent turbulence structures in the wind turbine wake; eigenvalues delineate the relative amount of turbulent kinetic energy associated with each mode. Back-projecting the POD modes onto the velocity snapshots produces dynamic coefficients that express the amplitude of each mode in time. A reduced-order model of the wind turbine wake (wakeROM) is defined through a seriesmore » of polynomial parameters that quantify mode interaction and the evolution of each POD mode coefficients. The resulting system of ordinary differential equations models the wind turbine wake composed only of the large-scale turbulent dynamics identified by the POD. Tikhonov regularization is used to recalibrate the dynamical system by adding additional constraints to the minimization seeking polynomial parameters, reducing error in the modeled mode coefficients. The wakeROM is periodically reinitialized with new initial conditions found by relating the incoming turbulent velocity to the POD mode coefficients through a series of open-loop transfer functions. The wakeROM reproduces mode coefficients to within 25.2%, quantified through the normalized root-mean-square error. A high-level view of the modeling approach is provided as a platform to discuss promising research directions, alternate processes that could benefit stability and efficiency, and desired extensions of the wakeROM.« less

Plasmonic imaging of protein interactions with single bacterial cells.

PubMed

Syal, Karan; Wang, Wei; Shan, Xiaonan; Wang, Shaopeng; Chen, Hong-Yuan; Tao, Nongjian

2015-01-15

Quantifying the interactions of bacteria with external ligands is fundamental to the understanding of pathogenesis, antibiotic resistance, immune evasion, and mechanism of antimicrobial action. Due to inherent cell-to-cell heterogeneity in a microbial population, each bacterium interacts differently with its environment. This large variability is washed out in bulk assays, and there is a need of techniques that can quantify interactions of bacteria with ligands at the single bacterium level. In this work, we present a label-free and real-time plasmonic imaging technique to measure the binding kinetics of ligand interactions with single bacteria, and perform statistical analysis of the heterogeneity. Using the technique, we have studied interactions of antibodies with single Escherichia coli O157:H7 cells and demonstrated a capability of determining the binding kinetic constants of single live bacteria with ligands, and quantify heterogeneity in a microbial population. Copyright © 2014 Elsevier B.V. All rights reserved.

Detection of rhodopsin dimerization in situ by PIE-FCCS, a time-resolved fluorescence spectroscopy.

PubMed

Smith, Adam W

2015-01-01

Rhodopsin self-associates in the plasma membrane. At low concentrations, the interactions are consistent with a monomer-dimer equilibrium (Comar et al., J Am Chem Soc 136(23):8342-8349, 2014). At high concentrations in native tissue, higher-order clusters have been observed (Fotiadis et al., Nature 421:127-128, 2003). The physiological role of rhodopsin dimerization is still being investigated, but it is clear that a quantitative assessment is essential to determining the function of rhodopsin clusters in vision. To quantify rhodopsin interactions, I will outline the theory and methodology of a specialized time-resolved fluorescence spectroscopy for measuring membrane protein-protein interactions called pulsed-interleaved excitation fluorescence cross-correlation spectroscopy (PIE-FCCS). The strength of this technique is its ability to quantify rhodopsin interactions in situ (i.e., a live cell plasma membrane). There are two reasons for restricting the scope to live cell membranes. First, the compositional heterogeneity of the plasma membrane creates a complex milieu with thousands of lipid, protein, and carbohydrate species. This makes it difficult to infer quaternary interactions from detergent solubilized samples or construct a model phospholipid bilayer that recapitulates all of the interactions present in native membranes. Second, organizational structure and dynamics is a key feature of the plasma membrane, and fixation techniques like formaldehyde cross-linking and vitrification will modulate the interactions. PIE-FCCS is based on two-color fluorescence imaging with time-correlated single-photon counting (TCSPC) (Becker et al., Rev Sci Instrum 70:1835-1841, 1999). By time-tagging every detected photon, the data can be analyzed as a fluorescence intensity distribution, fluorescence lifetime histogram, or fluorescence (cross-)correlation spectra (FCS/FCCS) (Becker, Advanced time-correlated single-photon counting techniques, Springer, Berlin, 2005). These analysis tools can then be used to quantify protein concentration, mobility, clustering, and Förster resonance energy transfer (FRET). In this paper I will focus on PIE-FCCS, which interleaves two wavelength excitation events in time so that the effects of spectral cross-talk and FRET can be isolated. In this way it is possible to characterize monomer-dimer-oligomer equilibria with high accuracy (Müller et al., Biophys J 89:3508-3522, 2005). Currently, PIE-FCCS requires a customized equipment configuration that will be described below. There is an excellent protocol that outlines traditional FCCS on a commercially available instrument (Bacia and Schwille, Nat Protoc 2:2842-2856, 2007). The PIE-FCCS approach is a relatively recent advance in FCCS that has been used in live cell assays to quantify lipid-anchored protein clustering (Triffo et al., J Am Chem Soc 134:10833-10842, 2012), epidermal growth factor receptor dimerization (Endres et al., Cell 152:543-556, 2013), and recently the dimerization of opsin (Comar et al., J Am Chem Soc 136(23):8342-8349, 2014). This paper will outline the theory and instrumentation requirements for PIE-FCCS, as well as the data collection and analysis process.

Quantitative Modeling of Human-Environment Interactions in Preindustrial Time

NASA Astrophysics Data System (ADS)

Sommer, Philipp S.; Kaplan, Jed O.

2017-04-01

Quantifying human-environment interactions and anthropogenic influences on the environment prior to the Industrial revolution is essential for understanding the current state of the earth system. This is particularly true for the terrestrial biosphere, but marine ecosystems and even climate were likely modified by human activities centuries to millennia ago. Direct observations are however very sparse in space and time, especially as one considers prehistory. Numerical models are therefore essential to produce a continuous picture of human-environment interactions in the past. Agent-based approaches, while widely applied to quantifying human influence on the environment in localized studies, are unsuitable for global spatial domains and Holocene timescales because of computational demands and large parameter uncertainty. Here we outline a new paradigm for the quantitative modeling of human-environment interactions in preindustrial time that is adapted to the global Holocene. Rather than attempting to simulate agency directly, the model is informed by a suite of characteristics describing those things about society that cannot be predicted on the basis of environment, e.g., diet, presence of agriculture, or range of animals exploited. These categorical data are combined with the properties of the physical environment in coupled human-environment model. The model is, at its core, a dynamic global vegetation model with a module for simulating crop growth that is adapted for preindustrial agriculture. This allows us to simulate yield and calories for feeding both humans and their domesticated animals. We couple this basic caloric availability with a simple demographic model to calculate potential population, and, constrained by labor requirements and land limitations, we create scenarios of land use and land cover on a moderate-resolution grid. We further implement a feedback loop where anthropogenic activities lead to changes in the properties of the physical environment, e.g., through soil erosion.

Developments in dynamic MR elastography for in vitro biomechanical assessment of hyaline cartilage under high-frequency cyclical shear.

PubMed

Lopez, Orlando; Amrami, Kimberly K; Manduca, Armando; Rossman, Phillip J; Ehman, Richard L

2007-02-01

The design, construction, and evaluation of a customized dynamic magnetic resonance elastography (MRE) technique for biomechanical assessment of hyaline cartilage in vitro are described. For quantification of the dynamic shear properties of hyaline cartilage by dynamic MRE, mechanical excitation and motion sensitization were performed at frequencies in the kilohertz range. A custom electromechanical actuator and a z-axis gradient coil were used to generate and image shear waves throughout cartilage at 1000-10,000 Hz. A radiofrequency (RF) coil was also constructed for high-resolution imaging. The technique was validated at 4000 and 6000 Hz by quantifying differences in shear stiffness between soft ( approximately 200 kPa) and stiff ( approximately 300 kPa) layers of 5-mm-thick bilayered phantoms. The technique was then used to quantify the dynamic shear properties of bovine and shark hyaline cartilage samples at frequencies up to 9000 Hz. The results demonstrate that one can obtain high-resolution shear stiffness measurements of hyaline cartilage and small, stiff, multilayered phantoms at high frequencies by generating robust mechanical excitations and using large magnetic field gradients. Dynamic MRE can potentially be used to directly quantify the dynamic shear properties of hyaline and articular cartilage, as well as other cartilaginous materials and engineered constructs. (c) 2007 Wiley-Liss, Inc.

Path Similarity Analysis: A Method for Quantifying Macromolecular Pathways

PubMed Central

Seyler, Sean L.; Kumar, Avishek; Thorpe, M. F.; Beckstein, Oliver

2015-01-01

Diverse classes of proteins function through large-scale conformational changes and various sophisticated computational algorithms have been proposed to enhance sampling of these macromolecular transition paths. Because such paths are curves in a high-dimensional space, it has been difficult to quantitatively compare multiple paths, a necessary prerequisite to, for instance, assess the quality of different algorithms. We introduce a method named Path Similarity Analysis (PSA) that enables us to quantify the similarity between two arbitrary paths and extract the atomic-scale determinants responsible for their differences. PSA utilizes the full information available in 3N-dimensional configuration space trajectories by employing the Hausdorff or Fréchet metrics (adopted from computational geometry) to quantify the degree of similarity between piecewise-linear curves. It thus completely avoids relying on projections into low dimensional spaces, as used in traditional approaches. To elucidate the principles of PSA, we quantified the effect of path roughness induced by thermal fluctuations using a toy model system. Using, as an example, the closed-to-open transitions of the enzyme adenylate kinase (AdK) in its substrate-free form, we compared a range of protein transition path-generating algorithms. Molecular dynamics-based dynamic importance sampling (DIMS) MD and targeted MD (TMD) and the purely geometric FRODA (Framework Rigidity Optimized Dynamics Algorithm) were tested along with seven other methods publicly available on servers, including several based on the popular elastic network model (ENM). PSA with clustering revealed that paths produced by a given method are more similar to each other than to those from another method and, for instance, that the ENM-based methods produced relatively similar paths. PSA applied to ensembles of DIMS MD and FRODA trajectories of the conformational transition of diphtheria toxin, a particularly challenging example, showed that the geometry-based FRODA occasionally sampled the pathway space of force field-based DIMS MD. For the AdK transition, the new concept of a Hausdorff-pair map enabled us to extract the molecular structural determinants responsible for differences in pathways, namely a set of conserved salt bridges whose charge-charge interactions are fully modelled in DIMS MD but not in FRODA. PSA has the potential to enhance our understanding of transition path sampling methods, validate them, and to provide a new approach to analyzing conformational transitions. PMID:26488417

Modeling the Dynamics of Soil Structure and Water in Agricultural Soil

NASA Astrophysics Data System (ADS)

Weller, U.; Lang, B.; Rabot, E.; Stössel, B.; Urbanski, L.; Vogel, H. J.; Wiesmeier, M.; Wollschlaeger, U.

2017-12-01

The impact of agricultural management on soil functions is manifold and severe. It has both positive and adverse influence. Our goal is to develop model tools quantifying the agricultural impact on soil functions based on a mechanistic understanding of soil processes to support farmers and decision makers. The modeling approach is based on defining relevant soil components, i.e. soil matrix, macropores, organisms, roots and organic matter. They interact and form the soil's macroscopic properties and functions including water and gas dynamics, and biochemical cycles. Based on existing literature information we derive functional interaction processes and combine them in a network of dynamic soil components. In agricultural soils, a major issue is linked to changes in soil structure and their influence on water dynamics. Compaction processes are well studied in literature, but for the resilience due to root growth and activity of soil organisms the information is scarcer. We implement structural dynamics into soil water and gas simulations using a lumped model that is both coarse enough to allow extensive model runs while still preserving some important, yet rarely modeled phenomenons like preferential flow, hysteretic and dynamic behavior. For simulating water dynamics, at each depth, the model assumes water at different binding energies depending on soil structure, i.e. the pore size distribution. Non-equilibrium is postulated, meaning that free water may occur even if the soil is not fully saturated. All energy levels are interconnected allowing water to move, both within a spatial node, and between neighboring nodes (adding gravity). Structure dynamics alters the capacity of this water compartments, and the conductance of its connections. Connections are switched on and off depending on whether their sources contain water or their targets have free capacity. This leads to piecewise linear system behavior that allows fast calculation for extended time steps. Based on this concept, the dynamics of soil structure can be directly linked to soil water dynamics as a main driver for other soil processes. Further steps will include integration of temperature and solute leaching as well as defining the feedback of the water regime on the structure forming processes.

Future Carbon Dynamics of the Northern Rockies Ecoregion due to Climate Impacts and Fire Effects

NASA Astrophysics Data System (ADS)

Weller, U.; Lang, B.; Rabot, E.; Stössel, B.; Urbanski, L.; Vogel, H. J.; Wiesmeier, M.; Wollschlaeger, U.

2016-12-01

The impact of agricultural management on soil functions is manifold and severe. It has both positive and adverse influence. Our goal is to develop model tools quantifying the agricultural impact on soil functions based on a mechanistic understanding of soil processes to support farmers and decision makers. The modeling approach is based on defining relevant soil components, i.e. soil matrix, macropores, organisms, roots and organic matter. They interact and form the soil's macroscopic properties and functions including water and gas dynamics, and biochemical cycles. Based on existing literature information we derive functional interaction processes and combine them in a network of dynamic soil components. In agricultural soils, a major issue is linked to changes in soil structure and their influence on water dynamics. Compaction processes are well studied in literature, but for the resilience due to root growth and activity of soil organisms the information is scarcer. We implement structural dynamics into soil water and gas simulations using a lumped model that is both coarse enough to allow extensive model runs while still preserving some important, yet rarely modeled phenomenons like preferential flow, hysteretic and dynamic behavior. For simulating water dynamics, at each depth, the model assumes water at different binding energies depending on soil structure, i.e. the pore size distribution. Non-equilibrium is postulated, meaning that free water may occur even if the soil is not fully saturated. All energy levels are interconnected allowing water to move, both within a spatial node, and between neighboring nodes (adding gravity). Structure dynamics alters the capacity of this water compartments, and the conductance of its connections. Connections are switched on and off depending on whether their sources contain water or their targets have free capacity. This leads to piecewise linear system behavior that allows fast calculation for extended time steps. Based on this concept, the dynamics of soil structure can be directly linked to soil water dynamics as a main driver for other soil processes. Further steps will include integration of temperature and solute leaching as well as defining the feedback of the water regime on the structure forming processes.

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling

PubMed Central

Wisz, Mary Susanne; Pottier, Julien; Kissling, W Daniel; Pellissier, Loïc; Lenoir, Jonathan; Damgaard, Christian F; Dormann, Carsten F; Forchhammer, Mads C; Grytnes, John-Arvid; Guisan, Antoine; Heikkinen, Risto K; Høye, Toke T; Kühn, Ingolf; Luoto, Miska; Maiorano, Luigi; Nilsson, Marie-Charlotte; Normand, Signe; Öckinger, Erik; Schmidt, Niels M; Termansen, Mette; Timmermann, Allan; Wardle, David A; Aastrup, Peter; Svenning, Jens-Christian

2013-01-01

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km2 to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere. PMID:22686347

Ion specific effects: decoupling ion-ion and ion-water interactions

PubMed Central

Song, Jinsuk; Kang, Tae Hui; Kim, Mahn Won; Han, Songi

2015-01-01

Ion-specific effects in aqueous solution, known as the Hofmeister effect is prevalent in diverse systems ranging from pure ionic to complex protein solutions. The objective of this paper is to explicitly demonstrate how complex ion-ion and ion-water interactions manifest themselves in the Hofmeister effects, based on a series of recent experimental observation. These effects are not considered in the classical description of ion effects, such as the Deryaguin-Landau-Verwey-Overbeek (DLVO) theory that, likely for that reason, fail to describe the origin of the phenomenological Hofmeister effect. However, given that models considering the basic forces of electrostatic and van der Waals interactions can offer rationalization for the core experimental observations, a universal interaction model stands a chance to be developed. In this perspective, we separately derive the contribution from ion-ion electrostatic interaction and ion-water interaction from second harmonic generation (SHG) data at the air-ion solution interface, which yields an estimate of ion-water interactions in solution. Hofmeister ion effects observed on biological solutes in solution should be similarly influenced by contributions from ion-ion and ion-water interactions, where the same ion-water interaction parameters derived from SHG data at the air-ion solution interface could be applicable. A key experimental data set available from solution systems to probe ion-water interaction is the modulation of water diffusion dynamics near ions in bulk ion solution, as well as near biological liposome surfaces. It is obtained from Overhauser dynamic nuclear polarization (ODNP), a nuclear magnetic resonance (NMR) relaxometry technique. The surface water diffusivity is influenced by the contribution from ion-water interactions, both from localized surface charges and adsorbed ions, although the relative contribution of the former is larger on liposome surfaces. In this perspective, ion-water interaction energy values derived from experimental data for various ions are compared with theoretical values in the literature. Ultimately, quantifying ion-induced changes in surface energy for the purpose of developing valid theoretical models for ion-water interaction, will be critical to rationalizing the Hofmeister effect. PMID:25761273

A biplanar X-ray approach for studying the 3D dynamics of human track formation.

PubMed

Hatala, Kevin G; Perry, David A; Gatesy, Stephen M

2018-05-09

Recent discoveries have made hominin tracks an increasingly prevalent component of the human fossil record, and these data have the capacity to inform long-standing debates regarding the biomechanics of hominin locomotion. However, there is currently no consensus on how to decipher biomechanical variables from hominin tracks. These debates can be linked to our generally limited understanding of the complex interactions between anatomy, motion, and substrate that give rise to track morphology. These interactions are difficult to study because direct visualization of the track formation process is impeded by foot and substrate opacity. To address these obstacles, we developed biplanar X-ray and computer animation methods, derived from X-ray Reconstruction of Moving Morphology (XROMM), to analyze the 3D dynamics of three human subjects' feet as they walked across four substrates (three deformable muds and rigid composite panel). By imaging and reconstructing 3D positions of external markers, we quantified the 3D dynamics at the foot-substrate interface. Foot shape, specifically heel and medial longitudinal arch deformation, was significantly affected by substrate rigidity. In deformable muds, we found that depths measured across tracks did not directly reflect the motions of the corresponding regions of the foot, and that track outlines were not perfectly representative of foot size. These results highlight the complex, dynamic nature of track formation, and the experimental methods presented here offer a promising avenue for developing and refining methods for accurately inferring foot anatomy and gait biomechanics from fossil hominin tracks. Copyright © 2018 Elsevier Ltd. All rights reserved.

Observation and quantification of the quantum dynamics of a strong-field excited multi-level system.

PubMed

Liu, Zuoye; Wang, Quanjun; Ding, Jingjie; Cavaletto, Stefano M; Pfeifer, Thomas; Hu, Bitao

2017-01-04

The quantum dynamics of a V-type three-level system, whose two resonances are first excited by a weak probe pulse and subsequently modified by another strong one, is studied. The quantum dynamics of the multi-level system is closely related to the absorption spectrum of the transmitted probe pulse and its modification manifests itself as a modulation of the absorption line shape. Applying the dipole-control model, the modulation induced by the second strong pulse to the system's dynamics is quantified by eight intensity-dependent parameters, describing the self and inter-state contributions. The present study opens the route to control the quantum dynamics of multi-level systems and to quantify the quantum-control process.

Quantifying chaos for ecological stoichiometry.

PubMed

Duarte, Jorge; Januário, Cristina; Martins, Nuno; Sardanyés, Josep

2010-09-01

The theory of ecological stoichiometry considers ecological interactions among species with different chemical compositions. Both experimental and theoretical investigations have shown the importance of species composition in the outcome of the population dynamics. A recent study of a theoretical three-species food chain model considering stoichiometry [B. Deng and I. Loladze, Chaos 17, 033108 (2007)] shows that coexistence between two consumers predating on the same prey is possible via chaos. In this work we study the topological and dynamical measures of the chaotic attractors found in such a model under ecological relevant parameters. By using the theory of symbolic dynamics, we first compute the topological entropy associated with unimodal Poincaré return maps obtained by Deng and Loladze from a dimension reduction. With this measure we numerically prove chaotic competitive coexistence, which is characterized by positive topological entropy and positive Lyapunov exponents, achieved when the first predator reduces its maximum growth rate, as happens at increasing δ1. However, for higher values of δ1 the dynamics become again stable due to an asymmetric bubble-like bifurcation scenario. We also show that a decrease in the efficiency of the predator sensitive to prey's quality (increasing parameter ζ) stabilizes the dynamics. Finally, we estimate the fractal dimension of the chaotic attractors for the stoichiometric ecological model.

Microfluidic platform for single cell analysis under dynamic spatial and temporal stimulation.

PubMed

Song, Jiyoung; Ryu, Hyunryul; Chung, Minhwan; Kim, Youngtaek; Blum, Yannick; Lee, Sung Sik; Pertz, Olivier; Jeon, Noo Li

2018-05-01

Recent research on cellular responses is shifting from static observations recorded under static stimuli to real-time monitoring in a dynamic environment. Since cells sense and interact with their surrounding microenvironment, an experimental platform where dynamically changing cellular microenvironments should be recreated in vitro. There has been a lack of microfluidic devices to support spatial and temporal stimulations in a simple and robust manner. Here, we describe a microfluidic device that generates dynamic chemical gradients and pulses in both space and time using a single device. This microfluidic device provides at least 12h of continuous stimulations that can be used to observe responses from mammalian cells. Combination of the microfluidic de-vice with live-cell imaging facilitates real-time observation of dynamic cellular response at single cell level. Using stable HEK cells with biosensors, ERK (Extracellular signal-Regulated Kinase) activities were observed un-der the pulsatile and ramping stimulations of EGF (Epidermal Growth Factor). We quantified ERK activation even at extremely low EGF concentration (0.0625µg/ml), which can not be observed using conventional techniques such as western blot. Cytoskeleton re-arrangement of the 3T3 fibroblast (stable transfection with Lifeact-GFP) was compared under abrupt and gradually changing gradient of PDGF. Copyright © 2017 Elsevier B.V. All rights reserved.

Signatures of ecological processes in microbial community time series.

PubMed

Faust, Karoline; Bauchinger, Franziska; Laroche, Béatrice; de Buyl, Sophie; Lahti, Leo; Washburne, Alex D; Gonze, Didier; Widder, Stefanie

2018-06-28

Growth rates, interactions between community members, stochasticity, and immigration are important drivers of microbial community dynamics. In sequencing data analysis, such as network construction and community model parameterization, we make implicit assumptions about the nature of these drivers and thereby restrict model outcome. Despite apparent risk of methodological bias, the validity of the assumptions is rarely tested, as comprehensive procedures are lacking. Here, we propose a classification scheme to determine the processes that gave rise to the observed time series and to enable better model selection. We implemented a three-step classification scheme in R that first determines whether dependence between successive time steps (temporal structure) is present in the time series and then assesses with a recently developed neutrality test whether interactions between species are required for the dynamics. If the first and second tests confirm the presence of temporal structure and interactions, then parameters for interaction models are estimated. To quantify the importance of temporal structure, we compute the noise-type profile of the community, which ranges from black in case of strong dependency to white in the absence of any dependency. We applied this scheme to simulated time series generated with the Dirichlet-multinomial (DM) distribution, Hubbell's neutral model, the generalized Lotka-Volterra model and its discrete variant (the Ricker model), and a self-organized instability model, as well as to human stool microbiota time series. The noise-type profiles for all but DM data clearly indicated distinctive structures. The neutrality test correctly classified all but DM and neutral time series as non-neutral. The procedure reliably identified time series for which interaction inference was suitable. Both tests were required, as we demonstrated that all structured time series, including those generated with the neutral model, achieved a moderate to high goodness of fit to the Ricker model. We present a fast and robust scheme to classify community structure and to assess the prevalence of interactions directly from microbial time series data. The procedure not only serves to determine ecological drivers of microbial dynamics, but also to guide selection of appropriate community models for prediction and follow-up analysis.

Cooperation dynamics of generalized reciprocity in state-based social dilemmas

NASA Astrophysics Data System (ADS)

Stojkoski, Viktor; Utkovski, Zoran; Basnarkov, Lasko; Kocarev, Ljupco

2018-05-01

We introduce a framework for studying social dilemmas in networked societies where individuals follow a simple state-based behavioral mechanism based on generalized reciprocity, which is rooted in the principle "help anyone if helped by someone." Within this general framework, which applies to a wide range of social dilemmas including, among others, public goods, donation, and snowdrift games, we study the cooperation dynamics on a variety of complex network examples. By interpreting the studied model through the lenses of nonlinear dynamical systems, we show that cooperation through generalized reciprocity always emerges as the unique attractor in which the overall level of cooperation is maximized, while simultaneously exploitation of the participating individuals is prevented. The analysis elucidates the role of the network structure, here captured by a local centrality measure which uniquely quantifies the propensity of the network structure to cooperation by dictating the degree of cooperation displayed both at the microscopic and macroscopic level. We demonstrate the applicability of the analysis on a practical example by considering an interaction structure that couples a donation process with a public goods game.

Ambulatory Healthcare Utilization in the United States: A System Dynamics Approach

NASA Technical Reports Server (NTRS)

Diaz, Rafael; Behr, Joshua G.; Tulpule, Mandar

2011-01-01

Ambulatory health care needs within the United States are served by a wide range of hospitals, clinics, and private practices. The Emergency Department (ED) functions as an important point of supply for ambulatory healthcare services. Growth in our aging populations as well as changes stemming from broader healthcare reform are expected to continue trend in congestion and increasing demand for ED services. While congestion is, in part, a manifestation of unmatched demand, the state of the alignment between the demand for, and supply of, emergency department services affects quality of care and profitability. The central focus of this research is to provide an explanation of the salient factors at play within the dynamic demand-supply tensions within which ambulatory care is provided within an Emergency Department. A System Dynamics (SO) simulation model is used to capture the complexities among the intricate balance and conditional effects at play within the demand-supply emergency department environment. Conceptual clarification of the forces driving the elements within the system , quantifying these elements, and empirically capturing the interaction among these elements provides actionable knowledge for operational and strategic decision-making.

Systematic Validation of Protein Force Fields against Experimental Data

PubMed Central

Eastwood, Michael P.; Dror, Ron O.; Shaw, David E.

2012-01-01

Molecular dynamics simulations provide a vehicle for capturing the structures, motions, and interactions of biological macromolecules in full atomic detail. The accuracy of such simulations, however, is critically dependent on the force field—the mathematical model used to approximate the atomic-level forces acting on the simulated molecular system. Here we present a systematic and extensive evaluation of eight different protein force fields based on comparisons of experimental data with molecular dynamics simulations that reach a previously inaccessible timescale. First, through extensive comparisons with experimental NMR data, we examined the force fields' abilities to describe the structure and fluctuations of folded proteins. Second, we quantified potential biases towards different secondary structure types by comparing experimental and simulation data for small peptides that preferentially populate either helical or sheet-like structures. Third, we tested the force fields' abilities to fold two small proteins—one α-helical, the other with β-sheet structure. The results suggest that force fields have improved over time, and that the most recent versions, while not perfect, provide an accurate description of many structural and dynamical properties of proteins. PMID:22384157

Mapping dynamic social networks in real life using participants' own smartphones.

PubMed

Boonstra, Tjeerd W; E Larsen, Mark; Christensen, Helen

2015-11-01

Interpersonal relationships are vital for our daily functioning and wellbeing. Social networks may form the primary means by which environmental influences determine individual traits. Several studies have shown the influence of social networks on decision-making, behaviors and wellbeing. Smartphones have great potential for measuring social networks in a real world setting. Here we tested the feasibility of using people's own smartphones as a data collection platform for face-to-face interactions. We developed an application for iOS and Android to collect Bluetooth data and acquired one week of data from 14 participants in our organization. The Bluetooth scanning statistics were used to quantify the time-resolved connection strength between participants and define the weights of a dynamic social network. We used network metrics to quantify changes in network topology over time and non-negative matrix factorization to identify cliques or subgroups that reoccurred during the week. The scanning rate varied considerably between smartphones running Android and iOS and egocentric networks metrics were correlated with the scanning rate. The time courses of two identified subgroups matched with two meetings that took place that week. These findings demonstrate the feasibility of using participants' own smartphones to map social network, whilst identifying current limitations of using generic smartphones. The bias introduced by variations in scanning rate and missing data is an important limitation that needs to be addressed in future studies.

A computer analysis of reflex eyelid motion in normal subjects and in facial neuropathy.

PubMed

Somia, N N; Rash, G S; Epstein, E E; Wachowiak, M; Sundine, M J; Stremel, R W; Barker, J H; Gossman, D

2000-12-01

To demonstrate how computerized eyelid motion analysis can quantify the human reflex blink. Seventeen normal subjects and 10 patients with unilateral facial nerve paralysis were analyzed. Eyelid closure is currently evaluated by systems primarily designed to assess lower/midfacial movements. The methods are subjective, difficult to reproduce, and measure only volitional closure. Reflex closure is responsible for eye hydration, and its evaluation demands dynamic analysis. A 60Hz video camera incorporated into a helmet was used to analyze blinking. Reflective markers on the forehead and eyelids allowed for the dynamic measurement of the reflex blink. Eyelid displacement, velocity and acceleration were calculated. The degree of synchrony between bilateral blinks was also determined. This study demonstrates that video motion analysis can describe normal and altered eyelid motions in a quantifiable manner. To our knowledge, this is the first study to measure dynamic reflex blinks. Eyelid closure may now be evaluated in kinematic terms. This technique could increase understanding of eyelid motion and permit more accurate evaluation of eyelid function. Dynamic eyelid evaluation has immediate applications in the treatment of facial palsy affecting the reflex blink. Relevance No method has been developed that objectively quantifies dynamic eyelid closure. Methods currently in use evaluate only volitional eyelid closure, and are based on direct and indirect observer assessments. These methods are subjective and are incapable of analyzing dynamic eyelid movements, which are critical to maintenance of corneal hydration and comfort. A system that quantifies eyelid kinematics can provide a functional analysis of blink disorders and an objective evaluation of their treatment(s).

Facilitative-Competitive Interactions in an Old-Growth Forest: The Importance of Large-Diameter Trees as Benefactors and Stimulators for Forest Community Assembly

PubMed Central

Fichtner, Andreas; Forrester, David I.; Härdtle, Werner; Sturm, Knut; von Oheimb, Goddert

2015-01-01

The role of competition in tree communities is increasingly well understood, while little is known about the patterns and mechanisms of the interplay between above- and belowground competition in tree communities. This knowledge, however, is crucial for a better understanding of community dynamics and developing adaptive near-natural management strategies. We assessed neighbourhood interactions in an unmanaged old-growth European beech (Fagus sylvatica) forest by quantifying variation in the intensity of above- (shading) and belowground competition (crowding) among dominant and co-dominant canopy beech trees during tree maturation. Shading had on average a much larger impact on radial growth than crowding and the sensitivity to changes in competitive conditions was lowest for crowding effects. We found that each mode of competition reduced the effect of the other. Increasing crowding reduced the negative effect of shading, and at high levels of shading, crowding actually had a facilitative effect and increased growth. Our study demonstrates that complementarity in above- and belowground processes enable F. sylvatica to alter resource acquisition strategies, thus optimising tree radial growth. As a result, competition seemed to become less important in stands with a high growing stock and tree communities with a long continuity of anthropogenic undisturbed population dynamics. We suggest that growth rates do not exclusively depend on the density of potential competitors at the intraspecific level, but on the conspecific aggregation of large-diameter trees and their functional role for regulating biotic filtering processes. This finding highlights the potential importance of the rarely examined relationship between the spatial aggregation pattern of large-diameter trees and the outcome of neighbourhood interactions, which may be central to community dynamics and the related forest ecosystem services. PMID:25803035

Facilitative-competitive interactions in an old-growth forest: the importance of large-diameter trees as benefactors and stimulators for forest community assembly.

PubMed

Fichtner, Andreas; Forrester, David I; Härdtle, Werner; Sturm, Knut; von Oheimb, Goddert

2015-01-01

The role of competition in tree communities is increasingly well understood, while little is known about the patterns and mechanisms of the interplay between above- and belowground competition in tree communities. This knowledge, however, is crucial for a better understanding of community dynamics and developing adaptive near-natural management strategies. We assessed neighbourhood interactions in an unmanaged old-growth European beech (Fagus sylvatica) forest by quantifying variation in the intensity of above- (shading) and belowground competition (crowding) among dominant and co-dominant canopy beech trees during tree maturation. Shading had on average a much larger impact on radial growth than crowding and the sensitivity to changes in competitive conditions was lowest for crowding effects. We found that each mode of competition reduced the effect of the other. Increasing crowding reduced the negative effect of shading, and at high levels of shading, crowding actually had a facilitative effect and increased growth. Our study demonstrates that complementarity in above- and belowground processes enable F. sylvatica to alter resource acquisition strategies, thus optimising tree radial growth. As a result, competition seemed to become less important in stands with a high growing stock and tree communities with a long continuity of anthropogenic undisturbed population dynamics. We suggest that growth rates do not exclusively depend on the density of potential competitors at the intraspecific level, but on the conspecific aggregation of large-diameter trees and their functional role for regulating biotic filtering processes. This finding highlights the potential importance of the rarely examined relationship between the spatial aggregation pattern of large-diameter trees and the outcome of neighbourhood interactions, which may be central to community dynamics and the related forest ecosystem services.

Functional Connectivity’s Degenerate View of Brain Computation

PubMed Central

Giron, Alain; Rudrauf, David

2016-01-01

Brain computation relies on effective interactions between ensembles of neurons. In neuroimaging, measures of functional connectivity (FC) aim at statistically quantifying such interactions, often to study normal or pathological cognition. Their capacity to reflect a meaningful variety of patterns as expected from neural computation in relation to cognitive processes remains debated. The relative weights of time-varying local neurophysiological dynamics versus static structural connectivity (SC) in the generation of FC as measured remains unsettled. Empirical evidence features mixed results: from little to significant FC variability and correlation with cognitive functions, within and between participants. We used a unified approach combining multivariate analysis, bootstrap and computational modeling to characterize the potential variety of patterns of FC and SC both qualitatively and quantitatively. Empirical data and simulations from generative models with different dynamical behaviors demonstrated, largely irrespective of FC metrics, that a linear subspace with dimension one or two could explain much of the variability across patterns of FC. On the contrary, the variability across BOLD time-courses could not be reduced to such a small subspace. FC appeared to strongly reflect SC and to be partly governed by a Gaussian process. The main differences between simulated and empirical data related to limitations of DWI-based SC estimation (and SC itself could then be estimated from FC). Above and beyond the limited dynamical range of the BOLD signal itself, measures of FC may offer a degenerate representation of brain interactions, with limited access to the underlying complexity. They feature an invariant common core, reflecting the channel capacity of the network as conditioned by SC, with a limited, though perhaps meaningful residual variability. PMID:27736900

Elucidating the interaction between light competition and herbivore feeding patterns using functional–structural plant modelling

PubMed Central

de Vries, Jorad; Poelman, Erik H; Anten, Niels; Evers, Jochem B

2018-01-01

Abstract Background and Aims Plants usually compete with neighbouring plants for resources such as light as well as defend themselves against herbivorous insects. This requires investment of limiting resources, resulting in optimal resource distribution patterns and trade-offs between growth- and defence-related traits. A plant’s competitive success is determined by the spatial distribution of its resources in the canopy. The spatial distribution of herbivory in the canopy in turn differs between herbivore species as the level of herbivore specialization determines their response to the distribution of resources and defences in the canopy. Here, we investigated to what extent competition for light affects plant susceptibility to herbivores with different feeding preferences. Methods To quantify interactions between herbivory and competition, we developed and evaluated a 3-D spatially explicit functional–structural plant model for Brassica nigra that mechanistically simulates competition in a dynamic light environment, and also explicitly models leaf area removal by herbivores with different feeding preferences. With this novel approach, we can quantitatively explore the extent to which herbivore feeding location and light competition interact in their effect on plant performance. Key Results Our results indicate that there is indeed a strong interaction between levels of plant–plant competition and herbivore feeding preference. When plants did not compete, herbivory had relatively small effects irrespective of feeding preference. Conversely, when plants competed, herbivores with a preference for young leaves had a strong negative effect on the competitiveness and subsequent performance of the plant, whereas herbivores with a preference for old leaves did not. Conclusions Our study predicts how plant susceptibility to herbivory depends on the composition of the herbivore community and the level of plant competition, and highlights the importance of considering the full range of dynamics in plant–plant–herbivore interactions. PMID:29373660

Information theoretic measures of network coordination in high-frequency scalp EEG reveal dynamic patterns associated with seizure termination

PubMed Central

Stamoulis, Catherine; Schomer, Donald L.; Chang, Bernard S.

2013-01-01

How a seizure terminates is still under-studied and, despite its clinical importance, remains an obscure phase of seizure evolution. Recent studies of seizure-related scalp EEGs at frequencies >100 Hz suggest that neural activity, in the form of oscillations and/or neuronal network interactions, may play an important role in preictal/ictal seizure evolution [2, 31]. However, the role of high-frequency activity in seizure termination, is unknown, if it exists at all. Using information theoretic measures of network coordination, this study investigated ictal and immediate postictal neurodynamic interactions encoded in scalp EEGs from a relatively small sample of 8 patients with focal epilepsy and multiple seizures originating in temporal and/or frontal brain regions, at frequencies ≤100 Hz and >100 Hz, respectively. Despite some heterogeneity in the dynamics of these interactions, consistent patterns were also estimated. Specifically, in several seizures, linear or non-linear increase in high-frequency neuronal coordination during ictal intervals, coincided with a corresponding decrease in coordination at frequencies <100 Hz, suggesting a potential interference role of high-frequency activity, to disrupt abnormal ictal synchrony at lower frequencies. These changes in network synchrony started at least 20–30 sec prior to seizure offset, depending on the seizure duration. Opposite patterns were estimated at frequencies ≤100 Hz in several seizures. These results raise the possibility that high-frequency interference may occur in the form of progressive network coordination during the ictal interval, which continues during the postictal interval. This may be one of several possible mechanisms that facilitate seizure termination. In fact, inhibition of pairwise interactions between EEGs by other signals in their spatial neighborhood, quantified by negative interaction information, was estimated at frequencies ≤100 Hz, at least in some seizures. PMID:23608198

Collective dynamics of cell migration and cell rearrangements

NASA Astrophysics Data System (ADS)

Kabla, Alexandre

Understanding multicellular processes such as embryo development or cancer metastasis requires to decipher the contributions of local cell autonomous behaviours and long range interactions with the tissue environment. A key question in this context concerns the emergence of large scale coordination in cell behaviours, a requirement for collective cell migration or convergent extension. I will present a few examples where physical and mechanical aspects play a significant role in driving tissue scale dynamics.

Physical interface dynamics alter how robotic exosuits augment human movement: implications for optimizing wearable assistive devices.

PubMed

Yandell, Matthew B; Quinlivan, Brendan T; Popov, Dmitry; Walsh, Conor; Zelik, Karl E

2017-05-18

Wearable assistive devices have demonstrated the potential to improve mobility outcomes for individuals with disabilities, and to augment healthy human performance; however, these benefits depend on how effectively power is transmitted from the device to the human user. Quantifying and understanding this power transmission is challenging due to complex human-device interface dynamics that occur as biological tissues and physical interface materials deform and displace under load, absorbing and returning power. Here we introduce a new methodology for quickly estimating interface power dynamics during movement tasks using common motion capture and force measurements, and then apply this method to quantify how a soft robotic ankle exosuit interacts with and transfers power to the human body during walking. We partition exosuit end-effector power (i.e., power output from the device) into power that augments ankle plantarflexion (termed augmentation power) vs. power that goes into deformation and motion of interface materials and underlying soft tissues (termed interface power). We provide empirical evidence of how human-exosuit interfaces absorb and return energy, reshaping exosuit-to-human power flow and resulting in three key consequences: (i) During exosuit loading (as applied forces increased), about 55% of exosuit end-effector power was absorbed into the interfaces. (ii) However, during subsequent exosuit unloading (as applied forces decreased) most of the absorbed interface power was returned viscoelastically. Consequently, the majority (about 75%) of exosuit end-effector work over each stride contributed to augmenting ankle plantarflexion. (iii) Ankle augmentation power (and work) was delayed relative to exosuit end-effector power, due to these interface energy absorption and return dynamics. Our findings elucidate the complexities of human-exosuit interface dynamics during transmission of power from assistive devices to the human body, and provide insight into improving the design and control of wearable robots. We conclude that in order to optimize the performance of wearable assistive devices it is important, throughout design and evaluation phases, to account for human-device interface dynamics that affect power transmission and thus human augmentation benefits.

Cloudy with a Chance of Solar Flares: The Sun as a Natural Hazard

NASA Technical Reports Server (NTRS)

Pellish, Jonathan

2017-01-01

Space weather is a naturally occurring phenomenon that represents a quantifiable risk to space- and ground-based infrastructure as well as society at large. Space weather hazards include permanent and correctable faults in computer systems, Global Positioning System (GPS) and high-frequency communication disturbances, increased airline passenger and astronaut radiation exposure, and electric grid disruption. From the National Space Weather Strategy, published by the Office of Science and Technology Policy in October 2015, space weather refers to the dynamic conditions of the space environment that arise from emissions from the Sun, which include solar flares, solar energetic particles, and coronal mass ejections. These emissions can interact with Earth and its surrounding space, including the Earth's magnetic field, potentially disrupting technologies and infrastructures. Space weather is measured using a range of space- and ground-based platforms that directly monitor the Sun, the Earth's magnetic field, the conditions in interplanetary space and impacts at Earth's surface, like neutron ground-level enhancement. The NASA Goddard Space Flight Center's Space Weather Research Center and their international collaborators in government, industry, and academia are working towards improved techniques for predicting space weather as part of the strategy and action plan to better quantify and mitigate space weather hazards. In addition to accurately measuring and predicting space weather, we also need to continue developing more advanced techniques for evaluating space weather impacts on space- and ground-based infrastructure. Within the Earth's atmosphere, elevated neutron flux driven by atmosphere-particle interactions from space weather is a primary risk source. Ground-based neutron sources form an essential foundation for quantifying space weather impacts in a variety of systems.

Using the relational event model (REM) to investigate the temporal dynamics of animal social networks.

PubMed

Tranmer, Mark; Marcum, Christopher Steven; Morton, F Blake; Croft, Darren P; de Kort, Selvino R

2015-03-01

Social dynamics are of fundamental importance in animal societies. Studies on nonhuman animal social systems often aggregate social interaction event data into a single network within a particular time frame. Analysis of the resulting network can provide a useful insight into the overall extent of interaction. However, through aggregation, information is lost about the order in which interactions occurred, and hence the sequences of actions over time. Many research hypotheses relate directly to the sequence of actions, such as the recency or rate of action, rather than to their overall volume or presence. Here, we demonstrate how the temporal structure of social interaction sequences can be quantified from disaggregated event data using the relational event model (REM). We first outline the REM, explaining why it is different from other models for longitudinal data, and how it can be used to model sequences of events unfolding in a network. We then discuss a case study on the European jackdaw, Corvus monedula , in which temporal patterns of persistence and reciprocity of action are of interest, and present and discuss the results of a REM analysis of these data. One of the strengths of a REM analysis is its ability to take into account different ways in which data are collected. Having explained how to take into account the way in which the data were collected for the jackdaw study, we briefly discuss the application of the model to other studies. We provide details of how the models may be fitted in the R statistical software environment and outline some recent extensions to the REM framework.

Prediction of the solubility of cucurbitacin drugs in self-associating poly(ethylene oxide)-b-poly(alpha-benzyl carboxylate epsilon-caprolactone) block copolymer with different tacticities using molecular dynamics simulation.

PubMed

Patel, Sarthak K; Lavasanifar, Afsaneh; Choi, Phillip

2010-01-01

Molecular dynamics (MD) simulation was used to investigate the solubility of two hydrophobic drugs Cucurbitacin B (CuB) and Cucurbitacin I (CuI) in poly(ethylene oxide)-b-poly(alpha-benzyl carboxylate epsilon-caprolactone) (PEO-b-PBCL) block copolymers with different tacticities. In particular, di-block copolymer with three different tacticities viz. PEO-b-iPBCL, PEO-b-sPBCL, and PEO-b-aPBCL were used. The solubility was quantified by calculating the corresponding Flory-Huggins interaction parameters (chi) using random binary mixture models with 10wt% of drug. The tacticity of the di-block copolymer was found to influence significantly the solubility of two drugs in it. In particular, based on MD simulation results, only PEO-b-sPBCL exhibited solubility while the other two did not. Given the fact that the drugs were shown to be soluble in PEO-b-PBCL experimentally, it is predicted that the tacticity of the di-block copolymer synthesized in experiment is syndiotactic. This predication matches well with the dominant ring opening polymerization of cyclic lactones to syndiotactic polymers by stannous octoate as catalyst used to prepare PEO-b-PBCL block copolymers in our previous experiments. The simulation results showed that the solubility of the drugs in PEO-b-sPBCL is attributed to the favorable intra-molecular interaction of the di-block copolymer and favorable intermolecular interaction between the di-block copolymer and the drugs. Radial distribution function analysis provides useful insights into the nature and type of the intermolecular interactions.

Feedback Controlled Colloidal Assembly at Fluid Interfaces

NASA Astrophysics Data System (ADS)

Bevan, Michael

The autonomous and reversible assembly of colloidal nano- and micro- scale components into ordered configurations is often suggested as a scalable process capable of manufacturing meta-materials with exotic electromagnetic properties. As a result, there is strong interest in understanding how thermal motion, particle interactions, patterned surfaces, and external fields can be optimally coupled to robustly control the assembly of colloidal components into hierarchically structured functional meta-materials. We approach this problem by directly relating equilibrium and dynamic colloidal microstructures to kT-scale energy landscapes mediated by colloidal forces, physically and chemically patterned surfaces, multiphase fluid interfaces, and electromagnetic fields. 3D colloidal trajectories are measured in real-space and real-time with nanometer resolution using an integrated suite of evanescent wave, video, and confocal microscopy methods. Equilibrium structures are connected to energy landscapes via statistical mechanical models. The dynamic evolution of initially disordered colloidal fluid configurations into colloidal crystals in the presence of tunable interactions (electromagnetic field mediated interactions, particle-interface interactions) is modeled using a novel approach based on fitting the Fokker-Planck equation to experimental microscopy and computer simulated assembly trajectories. This approach is based on the use of reaction coordinates that capture important microstructural features of crystallization processes and quantify both statistical mechanical (free energy) and fluid mechanical (hydrodynamic) contributions. Ultimately, we demonstrate real-time control of assembly, disassembly, and repair of colloidal crystals using both open loop and closed loop control to produce perfectly ordered colloidal microstructures. This approach is demonstrated for close packed colloidal crystals of spherical particles at fluid-solid interfaces and is being extended to anisotropic particles and multiphase fluid interfaces.

Quantifying pollen-vegetation relationships to reconstruct ancient forests using 19th-century forest composition and pollen data

USGS Publications Warehouse

Dawson, Andria; Paciorek, Christopher J.; McLachlan, Jason S.; Goring, Simon; Williams, John W.; Jackson, Stephen T.

2016-01-01

Mitigation of climate change and adaptation to its effects relies partly on how effectively land-atmosphere interactions can be quantified. Quantifying composition of past forest ecosystems can help understand processes governing forest dynamics in a changing world. Fossil pollen data provide information about past forest composition, but rigorous interpretation requires development of pollen-vegetation models (PVMs) that account for interspecific differences in pollen production and dispersal. Widespread and intensified land-use over the 19th and 20th centuries may have altered pollen-vegetation relationships. Here we use STEPPS, a Bayesian hierarchical spatial PVM, to estimate key process parameters and associated uncertainties in the pollen-vegetation relationship. We apply alternate dispersal kernels, and calibrate STEPPS using a newly developed Euro-American settlement-era calibration data set constructed from Public Land Survey data and fossil pollen samples matched to the settlement-era using expert elicitation. Models based on the inverse power-law dispersal kernel outperformed those based on the Gaussian dispersal kernel, indicating that pollen dispersal kernels are fat tailed. Pine and birch have the highest pollen productivities. Pollen productivity and dispersal estimates are generally consistent with previous understanding from modern data sets, although source area estimates are larger. Tests of model predictions demonstrate the ability of STEPPS to predict regional compositional patterns.

Quantifying pollen-vegetation relationships to reconstruct ancient forests using 19th-century forest composition and pollen data

NASA Astrophysics Data System (ADS)

Dawson, Andria; Paciorek, Christopher J.; McLachlan, Jason S.; Goring, Simon; Williams, John W.; Jackson, Stephen T.

2016-04-01

Mitigation of climate change and adaptation to its effects relies partly on how effectively land-atmosphere interactions can be quantified. Quantifying composition of past forest ecosystems can help understand processes governing forest dynamics in a changing world. Fossil pollen data provide information about past forest composition, but rigorous interpretation requires development of pollen-vegetation models (PVMs) that account for interspecific differences in pollen production and dispersal. Widespread and intensified land-use over the 19th and 20th centuries may have altered pollen-vegetation relationships. Here we use STEPPS, a Bayesian hierarchical spatial PVM, to estimate key process parameters and associated uncertainties in the pollen-vegetation relationship. We apply alternate dispersal kernels, and calibrate STEPPS using a newly developed Euro-American settlement-era calibration data set constructed from Public Land Survey data and fossil pollen samples matched to the settlement-era using expert elicitation. Models based on the inverse power-law dispersal kernel outperformed those based on the Gaussian dispersal kernel, indicating that pollen dispersal kernels are fat tailed. Pine and birch have the highest pollen productivities. Pollen productivity and dispersal estimates are generally consistent with previous understanding from modern data sets, although source area estimates are larger. Tests of model predictions demonstrate the ability of STEPPS to predict regional compositional patterns.

Pharmacodynamic Modeling of Cell Cycle Effects for Gemcitabine and Trabectedin Combinations in Pancreatic Cancer Cells

PubMed Central

Miao, Xin; Koch, Gilbert; Ait-Oudhia, Sihem; Straubinger, Robert M.; Jusko, William J.

2016-01-01

Combinations of gemcitabine and trabectedin exert modest synergistic cytotoxic effects on two pancreatic cancer cell lines. Here, systems pharmacodynamic (PD) models that integrate cellular response data and extend a prototype model framework were developed to characterize dynamic changes in cell cycle phases of cancer cell subpopulations in response to gemcitabine and trabectedin as single agents and in combination. Extensive experimental data were obtained for two pancreatic cancer cell lines (MiaPaCa-2 and BxPC-3), including cell proliferation rates over 0–120 h of drug exposure, and the fraction of cells in different cell cycle phases or apoptosis. Cell cycle analysis demonstrated that gemcitabine induced cell cycle arrest in S phase, and trabectedin induced transient cell cycle arrest in S phase that progressed to G2/M phase. Over time, cells in the control group accumulated in G0/G1 phase. Systems cell cycle models were developed based on observed mechanisms and were used to characterize both cell proliferation and cell numbers in the sub G1, G0/G1, S, and G2/M phases in the control and drug-treated groups. The proposed mathematical models captured well both single and joint effects of gemcitabine and trabectedin. Interaction parameters were applied to quantify unexplainable drug-drug interaction effects on cell cycle arrest in S phase and in inducing apoptosis. The developed models were able to identify and quantify the different underlying interactions between gemcitabine and trabectedin, and captured well our large datasets in the dimensions of time, drug concentrations, and cellular subpopulations. PMID:27895579

Quantifying stochasticity in the dynamics of delay-coupled semiconductor lasers via forbidden patterns.

PubMed

Tiana-Alsina, Jordi; Buldú, Javier M; Torrent, M C; García-Ojalvo, Jordi

2010-01-28

We quantify the level of stochasticity in the dynamics of two mutually coupled semiconductor lasers. Specifically, we concentrate on a regime in which the lasers synchronize their dynamics with a non-zero lag time, and the leader and laggard roles alternate irregularly between the lasers. We analyse this switching dynamics in terms of the number of forbidden patterns of the alternate time series. The results reveal that the system operates in a stochastic regime, with the level of stochasticity decreasing as the lasers are pumped further away from their lasing threshold. This behaviour is similar to that exhibited by a single semiconductor laser subject to external optical feedback, as its dynamics shifts from the regime of low-frequency fluctuations to coherence collapse. This journal is © 2010 The Royal Society

A multiplexed microfluidic system for evaluation of dynamics of immune-tumor interactions.

PubMed

Moore, N; Doty, D; Zielstorff, M; Kariv, I; Moy, L Y; Gimbel, A; Chevillet, J R; Lowry, N; Santos, J; Mott, V; Kratchman, L; Lau, T; Addona, G; Chen, H; Borenstein, J T

2018-05-25

Recapitulation of the tumor microenvironment is critical for probing mechanisms involved in cancer, and for evaluating the tumor-killing potential of chemotherapeutic agents, targeted therapies and immunotherapies. Microfluidic devices have emerged as valuable tools for both mechanistic studies and for preclinical evaluation of therapeutic agents, due to their ability to precisely control drug concentrations and gradients of oxygen and other species in a scalable and potentially high throughput manner. Most existing in vitro microfluidic cancer models are comprised of cultured cancer cells embedded in a physiologically relevant matrix, collocated with vascular-like structures. However, the recent emergence of immune checkpoint inhibitors (ICI) as a powerful therapeutic modality against many cancers has created a need for preclinical in vitro models that accommodate interactions between tumors and immune cells, particularly for assessment of unprocessed tumor fragments harvested directly from patient biopsies. Here we report on a microfluidic model, termed EVIDENT (ex vivo immuno-oncology dynamic environment for tumor biopsies), that accommodates up to 12 separate tumor biopsy fragments interacting with flowing tumor-infiltrating lymphocytes (TILs) in a dynamic microenvironment. Flow control is achieved with a single pump in a simple and scalable configuration, and the entire system is constructed using low-sorption materials, addressing two principal concerns with existing microfluidic cancer models. The system sustains tumor fragments for multiple days, and permits real-time, high-resolution imaging of the interaction between autologous TILs and tumor fragments, enabling mapping of TIL-mediated tumor killing and testing of various ICI treatments versus tumor response. Custom image analytic algorithms based on machine learning reported here provide automated and quantitative assessment of experimental results. Initial studies indicate that the system is capable of quantifying temporal levels of TIL infiltration and tumor death, and that the EVIDENT model mimics the known in vivo tumor response to anti-PD-1 ICI treatment of flowing TILs relative to isotype control treatments for syngeneic mouse MC38 tumors.

Pair bond characteristics and maintenance in free-flying jackdaws Corvus monedula: effects of social context and season

PubMed Central

Kubitza, Robin J.; Bugnyar, Thomas; Schwab, Christine

2015-01-01

Most birds rely on cooperation between pair partners for breeding. In long-term monogamous species, pair bonds are considered the basic units of social organization, albeit these birds often form foraging, roosting or breeding groups in which they repeatedly interact with numerous conspecifics. Focusing on jackdaws Corvus monedula, we here investigated 1) the interplay between pair bond and group dynamics in several social contexts and 2) how pair partners differ in individual effort of pair bond maintenance. Based on long-term data on free-flying birds, we quantified social interactions between group members within three positive contexts (spatial proximity, feeding and sociopositive interactions) for different periods of the year (non-breeding, pre-breeding, parental care). On the group level, we found that the number of interaction partners was highest in the spatial proximity context while in the feeding and sociopositive contexts the number of interaction partners was low and moderately low, respectively. Interactions were reciprocated within almost all contexts and periods. Investigating subgrouping within the flock, results showed that interactions were preferentially directed towards the respective pair partner compared to unmated adults. When determining pair partner effort, both sexes similarly invested most into mutual proximity during late winter, thereby refreshing their bond before the onset of breeding. Paired males fed their mates over the entire year at similar rates while paired females hardly fed their mates at all but engaged in sociopositive behaviors instead. We conclude that jackdaws actively seek out positive social ties to flock members (close proximity, sociopositive behavior), at certain times of the year. Thus, the group functions as a dynamic social unit, nested within are highly cooperative pair bonds. Both sexes invested into the bond with different social behaviors and different levels of effort, yet these are likely male and female proximate mechanisms aimed at maintaining and perpetuating the pair bond. PMID:25892848

Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time-to-event in presence of censoring and competing risks.

PubMed

Blanche, Paul; Proust-Lima, Cécile; Loubère, Lucie; Berr, Claudine; Dartigues, Jean-François; Jacqmin-Gadda, Hélène

2015-03-01

Thanks to the growing interest in personalized medicine, joint modeling of longitudinal marker and time-to-event data has recently started to be used to derive dynamic individual risk predictions. Individual predictions are called dynamic because they are updated when information on the subject's health profile grows with time. We focus in this work on statistical methods for quantifying and comparing dynamic predictive accuracy of this kind of prognostic models, accounting for right censoring and possibly competing events. Dynamic area under the ROC curve (AUC) and Brier Score (BS) are used to quantify predictive accuracy. Nonparametric inverse probability of censoring weighting is used to estimate dynamic curves of AUC and BS as functions of the time at which predictions are made. Asymptotic results are established and both pointwise confidence intervals and simultaneous confidence bands are derived. Tests are also proposed to compare the dynamic prediction accuracy curves of two prognostic models. The finite sample behavior of the inference procedures is assessed via simulations. We apply the proposed methodology to compare various prediction models using repeated measures of two psychometric tests to predict dementia in the elderly, accounting for the competing risk of death. Models are estimated on the French Paquid cohort and predictive accuracies are evaluated and compared on the French Three-City cohort. © 2014, The International Biometric Society.

Simulating Food Web Dynamics along a Gradient: Quantifying Human Influence

PubMed Central

Jordán, Ferenc; Gjata, Nerta; Mei, Shu; Yule, Catherine M.

2012-01-01

Realistically parameterized and dynamically simulated food-webs are useful tool to explore the importance of the functional diversity of ecosystems, and in particular relations between the dynamics of species and the whole community. We present a stochastic dynamical food web simulation for the Kelian River (Borneo). The food web was constructed for six different locations, arrayed along a gradient of increasing human perturbation (mostly resulting from gold mining activities) along the river. Along the river, the relative importance of grazers, filterers and shredders decreases with increasing disturbance downstream, while predators become more dominant in governing eco-dynamics. Human activity led to increased turbidity and sedimentation which adversely impacts primary productivity. Since the main difference between the study sites was not the composition of the food webs (structure is quite similar) but the strengths of interactions and the abundance of the trophic groups, a dynamical simulation approach seemed to be useful to better explain human influence. In the pristine river (study site 1), when comparing a structural version of our model with the dynamical model we found that structurally central groups such as omnivores and carnivores were not the most important ones dynamically. Instead, primary consumers such as invertebrate grazers and shredders generated a greater dynamical response. Based on the dynamically most important groups, bottom-up control is replaced by the predominant top-down control regime as distance downstream and human disturbance increased. An important finding, potentially explaining the poor structure to dynamics relationship, is that indirect effects are at least as important as direct ones during the simulations. We suggest that our approach and this simulation framework could serve systems-based conservation efforts. Quantitative indicators on the relative importance of trophic groups and the mechanistic modeling of eco-dynamics could greatly contribute to understanding various aspects of functional diversity. PMID:22768346

Globally conditioned Granger causality in brain–brain and brain–heart interactions: a combined heart rate variability/ultra-high-field (7 T) functional magnetic resonance imaging study

PubMed Central

Passamonti, Luca; Wald, Lawrence L.; Barbieri, Riccardo

2016-01-01

The causal, directed interactions between brain regions at rest (brain–brain networks) and between resting-state brain activity and autonomic nervous system (ANS) outflow (brain–heart links) have not been completely elucidated. We collected 7 T resting-state functional magnetic resonance imaging (fMRI) data with simultaneous respiration and heartbeat recordings in nine healthy volunteers to investigate (i) the causal interactions between cortical and subcortical brain regions at rest and (ii) the causal interactions between resting-state brain activity and the ANS as quantified through a probabilistic, point-process-based heartbeat model which generates dynamical estimates for sympathetic and parasympathetic activity as well as sympathovagal balance. Given the high amount of information shared between brain-derived signals, we compared the results of traditional bivariate Granger causality (GC) with a globally conditioned approach which evaluated the additional influence of each brain region on the causal target while factoring out effects concomitantly mediated by other brain regions. The bivariate approach resulted in a large number of possibly spurious causal brain–brain links, while, using the globally conditioned approach, we demonstrated the existence of significant selective causal links between cortical/subcortical brain regions and sympathetic and parasympathetic modulation as well as sympathovagal balance. In particular, we demonstrated a causal role of the amygdala, hypothalamus, brainstem and, among others, medial, middle and superior frontal gyri, superior temporal pole, paracentral lobule and cerebellar regions in modulating the so-called central autonomic network (CAN). In summary, we show that, provided proper conditioning is employed to eliminate spurious causalities, ultra-high-field functional imaging coupled with physiological signal acquisition and GC analysis is able to quantify directed brain–brain and brain–heart interactions reflecting central modulation of ANS outflow. PMID:27044985

Synergistic effects of plasma-catalyst interactions for CH4 activation.

PubMed

Kim, Jongsik; Go, David B; Hicks, Jason C

2017-05-24

The elucidation of catalyst surface-plasma interactions is a challenging endeavor and therefore requires thorough and rigorous assessment of the reaction dynamics on the catalyst in the plasma environment. The first step in quantifying and defining catalyst-plasma interactions is a detailed kinetic study that can be used to verify appropriate reaction conditions for comparison and to discover any unexpected behavior of plasma-assisted reactions that might prevent direct comparison. In this paper, we provide a kinetic evaluation of CH 4 activation in a dielectric barrier discharge plasma in order to quantify plasma-catalyst interactions via kinetic parameters. The dry reforming of CH 4 with CO 2 was studied as a model reaction using Ni supported on γ-Al 2 O 3 at temperatures of 790-890 K under atmospheric pressure, where the partial pressures of CH 4 (or CO 2 ) were varied over a range of ≤25.3 kPa. Reaction performance was monitored by varying gas hourly space velocity, plasma power, bulk gas temperature, and reactant concentration. After correcting for gas-phase plasma reactions, a linear relationship was observed in the log of the measured rate constant with respect to reciprocal power (1/power). Although thermal catalysis displays typical Arrhenius behavior for this reaction, plasma-assisted catalysis occurs from a complex mixture of sources and shows non-Arrhenius behavior. However, an energy barrier was obtained from the relationship between the reaction rate constant and input power to exhibit ≤∼20 kJ mol -1 (compared to ∼70 kJ mol -1 for thermal catalysis). Of additional importance, the energy barriers measured during plasma-assisted catalysis were relatively consistent with respect to variations in total flow rates, types of diluent, or bulk reaction temperature. These experimental results suggest that plasma-generated vibrationally-excited CH 4 favorably interacts with Ni sites at elevated temperatures, which helps reduce the energy barrier required to activate CH 4 and enhance CH 4 reforming rates.

A transported probability density function/photon Monte Carlo method for high-temperature oxy-natural gas combustion with spectral gas and wall radiation

NASA Astrophysics Data System (ADS)

Zhao, X. Y.; Haworth, D. C.; Ren, T.; Modest, M. F.

2013-04-01

A computational fluid dynamics model for high-temperature oxy-natural gas combustion is developed and exercised. The model features detailed gas-phase chemistry and radiation treatments (a photon Monte Carlo method with line-by-line spectral resolution for gas and wall radiation - PMC/LBL) and a transported probability density function (PDF) method to account for turbulent fluctuations in composition and temperature. The model is first validated for a 0.8 MW oxy-natural gas furnace, and the level of agreement between model and experiment is found to be at least as good as any that has been published earlier. Next, simulations are performed with systematic model variations to provide insight into the roles of individual physical processes and their interplay in high-temperature oxy-fuel combustion. This includes variations in the chemical mechanism and the radiation model, and comparisons of results obtained with versus without the PDF method to isolate and quantify the effects of turbulence-chemistry interactions and turbulence-radiation interactions. In this combustion environment, it is found to be important to account for the interconversion of CO and CO2, and radiation plays a dominant role. The PMC/LBL model allows the effects of molecular gas radiation and wall radiation to be clearly separated and quantified. Radiation and chemistry are tightly coupled through the temperature, and correct temperature prediction is required for correct prediction of the CO/CO2 ratio. Turbulence-chemistry interactions influence the computed flame structure and mean CO levels. Strong local effects of turbulence-radiation interactions are found in the flame, but the net influence of TRI on computed mean temperature and species profiles is small. The ultimate goal of this research is to simulate high-temperature oxy-coal combustion, where accurate treatments of chemistry, radiation and turbulence-chemistry-particle-radiation interactions will be even more important.

Imaging Large Cohorts of Single Ion Channels and Their Activity

PubMed Central

Hiersemenzel, Katia; Brown, Euan R.; Duncan, Rory R.

2013-01-01

As calcium is the most important signaling molecule in neurons and secretory cells, amongst many other cell types, it follows that an understanding of calcium channels and their regulation of exocytosis is of vital importance. Calcium imaging using calcium dyes such as Fluo3, or FRET-based dyes that have been used widely has provided invaluable information, which combined with modeling has estimated the subtypes of channels responsible for triggering the exocytotic machinery as well as inferences about the relative distances away from vesicle fusion sites these molecules adopt. Importantly, new super-resolution microscopy techniques, combined with novel Ca2+ indicators and imaginative imaging approaches can now define directly the nano-scale locations of very large cohorts of single channel molecules in relation to single vesicles. With combinations of these techniques the activity of individual channels can be visualized and quantified using novel Ca2+ indicators. Fluorescently labeled specific channel toxins can also be used to localize endogenous assembled channel tetramers. Fluorescence lifetime imaging microscopy and other single-photon-resolution spectroscopic approaches offer the possibility to quantify protein–protein interactions between populations of channels and the SNARE protein machinery for the first time. Together with simultaneous electrophysiology, this battery of quantitative imaging techniques has the potential to provide unprecedented detail describing the locations, dynamic behaviors, interactions, and conductance activities of many thousands of channel molecules and vesicles in living cells. PMID:24027557

The role of turbulence-flow interactions in L- to H-mode transition dynamics: recent progress

NASA Astrophysics Data System (ADS)

Schmitz, L.

2017-02-01

Recent experimental and simulation work has substantially advanced the understanding of L-mode plasma edge turbulence and plasma flows and their mutual interaction across the L-H transition. Flow acceleration and E   ×   B shear flow amplification via the turbulent Reynolds stress have been directly observed in multiple devices, using multi-tip probe arrays, Doppler backscattering, beam emission spectroscopy, and gas puff imaging diagnostics. L-H transitions characterized by limit-cycle oscillations (LCO) allow probing of the trigger dynamics and the synergy of turbulence-driven and pressure-gradient-driven flows with high spatio-temporal resolution. L-mode turbulent structures exhibit characteristic changes in topology (tilting) and temporal and radial correlation preceding the L-H transition. Long-range toroidal flow correlations increase preceding edge-transport-barrier formation. The energy transfer from the turbulence spectrum to large-scale axisymmetric flows has been quantified in L-LCO and fast L-H transitions in several devices. After formation of a transient barrier, the increasing ion pressure gradient (via the E   ×   B flow shear associated with diamagnetic flow) sustains fluctuation suppression and secures the transition to H-mode. Heuristic models of the L-H trigger dynamics have progressed from 0D predator-prey models to 1D extended models, including neoclassical ion flow-damping and pressure-gradient evolution. Initial results from 2D and 3D reduced fluid models have been obtained for high-collisionality regimes.

Differential influences of local subpopulations on regional diversity and differentiation for greater sage-grouse (Centrocercus urophasianus)

USGS Publications Warehouse

Row, Jeffery R.; Oyler-McCance, Sara J.; Fedy, Brad C.

2016-01-01

The distribution of spatial genetic variation across a region can shape evolutionary dynamics and impact population persistence. Local population dynamics and among-population dispersal rates are strong drivers of this spatial genetic variation, yet for many species we lack a clear understanding of how these population processes interact in space to shape within-species genetic variation. Here, we used extensive genetic and demographic data from 10 subpopulations of greater sage-grouse to parameterize a simulated approximate Bayesian computation (ABC) model and (i) test for regional differences in population density and dispersal rates for greater sage-grouse subpopulations in Wyoming, and (ii) quantify how these differences impact subpopulation regional influence on genetic variation. We found a close match between observed and simulated data under our parameterized model and strong variation in density and dispersal rates across Wyoming. Sensitivity analyses suggested that changes in dispersal (via landscape resistance) had a greater influence on regional differentiation, whereas changes in density had a greater influence on mean diversity across all subpopulations. Local subpopulations, however, varied in their regional influence on genetic variation. Decreases in the size and dispersal rates of central populations with low overall and net immigration (i.e. population sources) had the greatest negative impact on genetic variation. Overall, our results provide insight into the interactions among demography, dispersal and genetic variation and highlight the potential of ABC to disentangle the complexity of regional population dynamics and project the genetic impact of changing conditions.

Modelling fungal growth in heterogeneous soil: analyses of the effect of soil physical structure on fungal community dynamics

NASA Astrophysics Data System (ADS)

Falconer, R.; Radoslow, P.; Grinev, D.; Otten, W.

2009-04-01

Fungi play a pivital role in soil ecosystems contributing to plant productivity. The underlying soil physical and biological processes responsible for community dynamics are interrelated and, at present, poorly understood. If these complex processes can be understood then this knowledge can be managed with an aim to providing more sustainable agriculture. Our understanding of microbial dynamics in soil has long been hampered by a lack of a theoretical framework and difficulties in observation and quantification. We will demonstrate how the spatial and temporal dynamics of fungi in soil can be understood by linking mathematical modelling with novel techniques that visualise the complex structure of the soil. The combination of these techniques and mathematical models opens up new possibilities to understand how the physical structure of soil affects fungal colony dynamics and also how fungal dynamics affect soil structure. We will quantify, using X ray tomography, soil structure for a range of artificially prepared microcosms. We characterise the soil structures using soil metrics such as porosity, fractal dimension, and the connectivity of the pore volume. Furthermore we will use the individual based fungal colony growth model of Falconer et al. 2005, which is based on the physiological processes of fungi, to assess the effect of soil structure on microbial dynamics by qualifying biomass abundances and distributions. We demonstrate how soil structure can critically affect fungal species interactions with consequences for biological control and fungal biodiversity.

Computational studies of sequence-specific driving forces in peptide self-assembly

NASA Astrophysics Data System (ADS)

Jeon, Joohyun

Peptides are biopolymers made from various sequences of twenty different types of amino acids, connected by peptide bonds. There are practically an infinite number of possible sequences and tremendous possible combinations of peptide-peptide interactions. Recently, an increasing number of studies have shown a stark variety of peptide self-assembled nanomaterials whose detailed structures depend on their sequences and environmental factors; these have end uses in medical and bio-electronic applications, for example. To understand the underlying physics of complex peptide self-assembly processes and to delineate sequence specific effects, in this study, I use various simulation tools spanning all-atom molecular dynamics to simple lattice models and quantify the balance of interactions in the peptide self-assembly processes. In contrast to the existing view that peptides' aggregation propensities are proportional to the net sequence hydrophobicity and inversely proportional to the net charge, I show the more nuanced effects of electrostatic interactions, including the cooperative effects between hydrophobic and electrostatic interactions. Notably, I suggest rather unexpected, yet important roles of entropies in the small scale oligomerization processes. Overall, this study broadens our understanding of the role of thermodynamic driving forces in peptide self-assembly.

A network-base analysis of CMIP5 "historical" experiments

NASA Astrophysics Data System (ADS)

Bracco, A.; Foudalis, I.; Dovrolis, C.

2012-12-01

In computer science, "complex network analysis" refers to a set of metrics, modeling tools and algorithms commonly used in the study of complex nonlinear dynamical systems. Its main premise is that the underlying topology or network structure of a system has a strong impact on its dynamics and evolution. By allowing to investigate local and non-local statistical interaction, network analysis provides a powerful, but only marginally explored, framework to validate climate models and investigate teleconnections, assessing their strength, range, and impacts on the climate system. In this work we propose a new, fast, robust and scalable methodology to examine, quantify, and visualize climate sensitivity, while constraining general circulation models (GCMs) outputs with observations. The goal of our novel approach is to uncover relations in the climate system that are not (or not fully) captured by more traditional methodologies used in climate science and often adopted from nonlinear dynamical systems analysis, and to explain known climate phenomena in terms of the network structure or its metrics. Our methodology is based on a solid theoretical framework and employs mathematical and statistical tools, exploited only tentatively in climate research so far. Suitably adapted to the climate problem, these tools can assist in visualizing the trade-offs in representing global links and teleconnections among different data sets. Here we present the methodology, and compare network properties for different reanalysis data sets and a suite of CMIP5 coupled GCM outputs. With an extensive model intercomparison in terms of the climate network that each model leads to, we quantify how each model reproduces major teleconnections, rank model performances, and identify common or specific errors in comparing model outputs and observations.

Weight of fitness deviation governs strict physical chaos in replicator dynamics.

PubMed

Pandit, Varun; Mukhopadhyay, Archan; Chakraborty, Sagar

2018-03-01

Replicator equation-a paradigm equation in evolutionary game dynamics-mathematizes the frequency dependent selection of competing strategies vying to enhance their fitness (quantified by the average payoffs) with respect to the average fitnesses of the evolving population under consideration. In this paper, we deal with two discrete versions of the replicator equation employed to study evolution in a population where any two players' interaction is modelled by a two-strategy symmetric normal-form game. There are twelve distinct classes of such games, each typified by a particular ordinal relationship among the elements of the corresponding payoff matrix. Here, we find the sufficient conditions for the existence of asymptotic solutions of the replicator equations such that the solutions-fixed points, periodic orbits, and chaotic trajectories-are all strictly physical, meaning that the frequency of any strategy lies inside the closed interval zero to one at all times. Thus, we elaborate on which of the twelve types of games are capable of showing meaningful physical solutions and for which of the two types of replicator equation. Subsequently, we introduce the concept of the weight of fitness deviation that is the scaling factor in a positive affine transformation connecting two payoff matrices such that the corresponding one-shot games have exactly same Nash equilibria and evolutionary stable states. The weight also quantifies how much the excess of fitness of a strategy over the average fitness of the population affects the per capita change in the frequency of the strategy. Intriguingly, the weight's variation is capable of making the Nash equilibria and the evolutionary stable states, useless by introducing strict physical chaos in the replicator dynamics based on the normal-form game.

Toward an integrated monitoring framework to assess the effects of tropical forest degradation and recovery on carbon stocks and biodiversity.

PubMed

Bustamante, Mercedes M C; Roitman, Iris; Aide, T Mitchell; Alencar, Ane; Anderson, Liana O; Aragão, Luiz; Asner, Gregory P; Barlow, Jos; Berenguer, Erika; Chambers, Jeffrey; Costa, Marcos H; Fanin, Thierry; Ferreira, Laerte G; Ferreira, Joice; Keller, Michael; Magnusson, William E; Morales-Barquero, Lucia; Morton, Douglas; Ometto, Jean P H B; Palace, Michael; Peres, Carlos A; Silvério, Divino; Trumbore, Susan; Vieira, Ima C G

2016-01-01

Tropical forests harbor a significant portion of global biodiversity and are a critical component of the climate system. Reducing deforestation and forest degradation contributes to global climate-change mitigation efforts, yet emissions and removals from forest dynamics are still poorly quantified. We reviewed the main challenges to estimate changes in carbon stocks and biodiversity due to degradation and recovery of tropical forests, focusing on three main areas: (1) the combination of field surveys and remote sensing; (2) evaluation of biodiversity and carbon values under a unified strategy; and (3) research efforts needed to understand and quantify forest degradation and recovery. The improvement of models and estimates of changes of forest carbon can foster process-oriented monitoring of forest dynamics, including different variables and using spatially explicit algorithms that account for regional and local differences, such as variation in climate, soil, nutrient content, topography, biodiversity, disturbance history, recovery pathways, and socioeconomic factors. Generating the data for these models requires affordable large-scale remote-sensing tools associated with a robust network of field plots that can generate spatially explicit information on a range of variables through time. By combining ecosystem models, multiscale remote sensing, and networks of field plots, we will be able to evaluate forest degradation and recovery and their interactions with biodiversity and carbon cycling. Improving monitoring strategies will allow a better understanding of the role of forest dynamics in climate-change mitigation, adaptation, and carbon cycle feedbacks, thereby reducing uncertainties in models of the key processes in the carbon cycle, including their impacts on biodiversity, which are fundamental to support forest governance policies, such as Reducing Emissions from Deforestation and Forest Degradation. © 2015 John Wiley & Sons Ltd.

Scale transition using dislocation dynamics and the nudged elastic band method

DOE PAGES

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

Groundwater-surface water interactions across scales in a boreal landscape investigated using a numerical modelling approach

NASA Astrophysics Data System (ADS)

Jutebring Sterte, Elin; Johansson, Emma; Sjöberg, Ylva; Huseby Karlsen, Reinert; Laudon, Hjalmar

2018-05-01

Groundwater and surface-water interactions are regulated by catchment characteristics and complex inter- and intra-annual variations in climatic conditions that are not yet fully understood. Our objective was to investigate the influence of catchment characteristics and freeze-thaw processes on surface and groundwater interactions in a boreal landscape, the Krycklan catchment in Sweden. We used a numerical modelling approach and sub-catchment evaluation method to identify and evaluate fundamental catchment characteristics and processes. The model reproduced observed stream discharge patterns of the 14 sub-catchments and the dynamics of the 15 groundwater wells with an average accumulated discharge error of 1% (15% standard deviation) and an average groundwater-level mean error of 0.1 m (0.23 m standard deviation). We show how peatland characteristics dampen the effect of intense rain, and how soil freeze-thaw processes regulate surface and groundwater partitioning during snowmelt. With these results, we demonstrate the importance of defining, understanding and quantifying the role of landscape heterogeneity and sub-catchment characteristics for accurately representing catchment hydrological functioning.

Molecular Simulation Evaluation of Macromolecular Transport through Nanofiltration Membranes

NASA Astrophysics Data System (ADS)

Almodovar Arbelo, Noelia; Boudouris, Bryan; Corti, David

A hybrid Monte Carlo and Molecular Dynamics simulation technique was implemented to elucidate the equilibrium behavior and transport properties of a model macromolecule as it navigated across a nanoporous polymer thin film (i.e., a nanofiltration membrane). The model linear homopolymer chosen was one that had interactions that were representative of poly(ethylene oxide) (PEO) due to the known interactions of PEO with solution molecules when a PEO chain is dissolved in an aqueous environment. The structural rearrangements of the PEO chain as it passes through the nanopore under an imposed chemical potential gradient was quantified as a function of solvent quality, polymer chain length, nanopore diameter and shape, and PEO-nanopore wall interactions. Thus, these computational studies provide a more detailed picture of the underlying physical mechanisms that drive macromolecular transport through nanopores, and, in particular, how dimensionally-large macromolecules (i.e., with large radii of gyration) enter and move through dimensionally-small pores (i.e., small radii nanopores). The insights gained from these studies will aid in the development of more cost-effective water purification systems in separation technologies for myriad industrial applications.

Learning from real and tissue-engineered jellyfish: How to design and build a muscle-powered pump at intermediate Reynolds numbers

NASA Astrophysics Data System (ADS)

Nawroth, Janna; Lee, Hyungsuk; Feinberg, Adam; Ripplinger, Crystal; McCain, Megan; Grosberg, Anna; Dabiri, John; Parker, Kit

2012-11-01

Tissue-engineered devices promise to advance medical implants, aquatic robots and experimental platforms for tissue-fluid interactions. The design, fabrication and systematic improvement of tissue constructs, however, is challenging because of the complex interactions of living cell, synthetic materials and their fluid environments. In a proof of concept study we have tissue-engineered a construct that mimics the swimming of a juvenile jellyfish, a simple model system for muscle-powered pumps at intermediate Reynolds numbers with quantifiable fluid dynamics and morphological properties. Optimally designed constructs achieved jellyfish-like swimming and generated biomimetic propulsion and feeding currents. Focusing on the fluid interactions, we discuss failed and successful designs and the lessons learned in the process. The main challenges were (1) to derive a body shape and deformation suitable for effective fluid transport under physiological fluid conditions, (2) to understand the mechanical properties of muscle and bell matrix and device a design capable of the desired deformation, (3) to establish adequate 3D kinematics of power and recovery stroke, and (4) to evaluate the performance of the design.

Pattern Formation and Strong Nonlinear Interactions in Exciton-Polariton Condensates

NASA Astrophysics Data System (ADS)

Ge, Li; Nersisyan, Ani; Oztop, Baris; Tureci, Hakan

2014-03-01

Exciton-polaritons generated by light-induced potentials can spontaneously condense into macroscopic quantum states that display nontrivial spatial and temporal density modulation. While these patterns and their dynamics can be reproduced through the solution of the generalized Gross-Pitaevskii equation, a predictive theory of their thresholds, oscillation frequencies, and multi-pattern interactions has so far been lacking. Here we represent such an approach based on current-carrying quasi-modes of the non-Hermitian potential induced by the pump. The presented theory allows us to capture the patterns formed in the steady-state directly and account for nonlinearities exactly. We find a simple but powerful expression for thresholds of condensation and the associated frequencies of oscillations, quantifying the contribution of particle formation, leakage, and interactions. We also show that the evolution of the condensate with increasing pump strength is strongly geometry dependent and can display contrasting features such as enhancement or reduction of the spatial localization of the condensate. We acknowledge support by DARPA under Grant No. N66001-11-1-4162 and NSF under CAREER Grant No. DMR-1151810.

Quantifying chaotic dynamics from integrate-and-fire processes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pavlov, A. N.; Saratov State Technical University, Politehnicheskaya Str. 77, 410054 Saratov; Pavlova, O. N.

2015-01-15

Characterizing chaotic dynamics from integrate-and-fire (IF) interspike intervals (ISIs) is relatively easy performed at high firing rates. When the firing rate is low, a correct estimation of Lyapunov exponents (LEs) describing dynamical features of complex oscillations reflected in the IF ISI sequences becomes more complicated. In this work we discuss peculiarities and limitations of quantifying chaotic dynamics from IF point processes. We consider main factors leading to underestimated LEs and demonstrate a way of improving numerical determining of LEs from IF ISI sequences. We show that estimations of the two largest LEs can be performed using around 400 mean periodsmore » of chaotic oscillations in the regime of phase-coherent chaos. Application to real data is discussed.« less

WatAA: Atlas of Protein Hydration. Exploring synergies between data mining and ab initio calculations.

PubMed

Černý, Jiří; Schneider, Bohdan; Biedermannová, Lada

2017-07-14

Water molecules represent an integral part of proteins and a key determinant of protein structure, dynamics and function. WatAA is a newly developed, web-based atlas of amino-acid hydration in proteins. The atlas provides information about the ordered first hydration shell of the most populated amino-acid conformers in proteins. The data presented in the atlas are drawn from two sources: experimental data and ab initio quantum-mechanics calculations. The experimental part is based on a data-mining study of a large set of high-resolution protein crystal structures. The crystal-derived data include 3D maps of water distribution around amino-acids and probability of occurrence of each of the identified hydration sites. The quantum mechanics calculations validate and extend this primary description by optimizing the water position for each hydration site, by providing hydrogen atom positions and by quantifying the interaction energy that stabilizes the water molecule at the particular hydration site position. The calculations show that the majority of experimentally derived hydration sites are positioned near local energy minima for water, and the calculated interaction energies help to assess the preference of water for the individual hydration sites. We propose that the atlas can be used to validate water placement in electron density maps in crystallographic refinement, to locate water molecules mediating protein-ligand interactions in drug design, and to prepare and evaluate molecular dynamics simulations. WatAA: Atlas of Protein Hydration is freely available without login at .

Identification of influential spreaders in online social networks using interaction weighted K-core decomposition method

NASA Astrophysics Data System (ADS)

Al-garadi, Mohammed Ali; Varathan, Kasturi Dewi; Ravana, Sri Devi

2017-02-01

Online social networks (OSNs) have become a vital part of everyday living. OSNs provide researchers and scientists with unique prospects to comprehend individuals on a scale and to analyze human behavioral patterns. Influential spreaders identification is an important subject in understanding the dynamics of information diffusion in OSNs. Targeting these influential spreaders is significant in planning the techniques for accelerating the propagation of information that is useful for various applications, such as viral marketing applications or blocking the diffusion of annoying information (spreading of viruses, rumors, online negative behaviors, and cyberbullying). Existing K-core decomposition methods consider links equally when calculating the influential spreaders for unweighted networks. Alternatively, the proposed link weights are based only on the degree of nodes. Thus, if a node is linked to high-degree nodes, then this node will receive high weight and is treated as an important node. Conversely, the degree of nodes in OSN context does not always provide accurate influence of users. In the present study, we improve the K-core method for OSNs by proposing a novel link-weighting method based on the interaction among users. The proposed method is based on the observation that the interaction of users is a significant factor in quantifying the spreading capability of user in OSNs. The tracking of diffusion links in the real spreading dynamics of information verifies the effectiveness of our proposed method for identifying influential spreaders in OSNs as compared with degree centrality, PageRank, and original K-core.

An interactive tool for visualization of spike train synchronization.

PubMed

Terry, Kevin

2010-08-15

A number of studies have examined the synchronization of central and peripheral spike trains by applying signal analysis techniques in the time and frequency domains. These analyses can reveal the presence of one or more common neural inputs that produce synchronization. However, synchronization measurements can fluctuate significantly due to the inherent variability of neural discharges and a finite data record length. Moreover, the effect of these natural variations is further compounded by the number of parameters available for calculating coherence in the frequency domain and the number of indices used to quantify short-term synchronization (STS) in the time domain. The computational tool presented here provides the user with an interactive environment that dynamically calculates and displays spike train properties along with STS and coherence indices to show how these factors interact. It is intended for a broad range of users, from those who are new to synchronization to experienced researchers who want to develop more meaningful and effective computational and experimental studies. To ensure this freely available tool meets the needs of all users, there are two versions. The first is a stand-alone version for educational use that can run on any computer. The second version can be modified and expanded by researchers who want to explore more in-depth questions about synchronization. Therefore, the distribution and use of this tool should both improve the understanding of fundamental spike train synchronization dynamics and produce more efficient and meaningful synchronization studies. (c) 2010 Elsevier B.V. All rights reserved.

Water Quality and Herbivory Interactively Drive Coral-Reef Recovery Patterns in American Samoa

PubMed Central

Houk, Peter; Musburger, Craig; Wiles, Phil

2010-01-01

Background Compared with a wealth of information regarding coral-reef recovery patterns following major disturbances, less insight exists to explain the cause(s) of spatial variation in the recovery process. Methodology/Principal Findings This study quantifies the influence of herbivory and water quality upon coral reef assemblages through space and time in Tutuila, American Samoa, a Pacific high island. Widespread declines in dominant corals (Acropora and Montipora) resulted from cyclone Heta at the end of 2003, shortly after the study began. Four sites that initially had similar coral reef assemblages but differential temporal dynamics four years following the disturbance event were classified by standardized measures of ‘recovery status’, defined by rates of change in ecological measures that are known to be sensitive to localized stressors. Status was best predicted, interactively, by water quality and herbivory. Expanding upon temporal trends, this study examined if similar dependencies existed through space; building multiple regression models to identify linkages between similar status measures and local stressors for 17 localities around Tutuila. The results highlighted consistent, interactive interdependencies for coral reef assemblages residing upon two unique geological reef types. Finally, the predictive regression models produced at the island scale were graphically interpreted with respect to hypothesized site-specific recovery thresholds. Conclusions/Significance Cumulatively, our study purports that moving away from describing relatively well-known patterns behind recovery, and focusing upon understanding causes, improves our foundation to predict future ecological dynamics, and thus improves coral reef management. PMID:21085715

Water quality and herbivory interactively drive coral-reef recovery patterns in American Samoa.

PubMed

Houk, Peter; Musburger, Craig; Wiles, Phil

2010-11-10

Compared with a wealth of information regarding coral-reef recovery patterns following major disturbances, less insight exists to explain the cause(s) of spatial variation in the recovery process. This study quantifies the influence of herbivory and water quality upon coral reef assemblages through space and time in Tutuila, American Samoa, a Pacific high island. Widespread declines in dominant corals (Acropora and Montipora) resulted from cyclone Heta at the end of 2003, shortly after the study began. Four sites that initially had similar coral reef assemblages but differential temporal dynamics four years following the disturbance event were classified by standardized measures of 'recovery status', defined by rates of change in ecological measures that are known to be sensitive to localized stressors. Status was best predicted, interactively, by water quality and herbivory. Expanding upon temporal trends, this study examined if similar dependencies existed through space; building multiple regression models to identify linkages between similar status measures and local stressors for 17 localities around Tutuila. The results highlighted consistent, interactive interdependencies for coral reef assemblages residing upon two unique geological reef types. Finally, the predictive regression models produced at the island scale were graphically interpreted with respect to hypothesized site-specific recovery thresholds. Cumulatively, our study purports that moving away from describing relatively well-known patterns behind recovery, and focusing upon understanding causes, improves our foundation to predict future ecological dynamics, and thus improves coral reef management.

Investigation of formaldehyde interaction with carbon nanotubes and quartz sand

NASA Astrophysics Data System (ADS)

Georgopoulou, Maria P.; Chrysikopoulos, Constantinos V.

2017-04-01

Assessment of the potential impact of synthetic carbon nanotubes on the fate and transport of common chemical contaminants (pesticides, pharmaceuticals, etc.) in groundwater systems is considered to be an increasingly important aspect of environmental research. This study investigates the interaction of formaldehyde with multi-walled carbon nanotubes (MWCNTs) and quartz sand under static and dynamic conditions. Due to polarity, formaldehyde, is expected to develop strong adsorptive interactions with carbon nanotubes. Several batch adsorption experiments were conducted in test tubes, under controlled conditions. Various initial formaldehyde solution concentration (2, 5, 8 ppm), contact times, and temperatures (8, 18, 25 °C) were considered. Supernatant liquid samples were collected at regular intervals, and centrifuged. Subsequently, the formaldehyde concentration in the supernatant was quantified indirectly, by derivatization with Nash reagent and subsequent measurement of the resulting complex using spectrophotometry in the visible spectral range. Experimental results suggested that formaldehyde has a low affinity for quartz sand, but an enhanced potential for adsorption onto carbon nanotubes. Formaldehyde adsorption onto both absorbents (quartz sand and MWCNTs) was more pronounced under dynamic than static conditions, probably, because agitation improves the mixing of the absorbent within the solution. Also, it was shown that the adsorption data were adequately described by the pseudo-second order kinetic model, suggesting that the primary adsorption mechanism was chemisorption, where two or more (sequential or parallel) processes (e.g. surface chemisorption, intraparticle diffusion) were taking place. Therefore, MWCNTs could be promising adsorbent materials for groundwater remediation.

Directionality of coupling of physiological subsystems: age-related changes of cardiorespiratory interaction during different sleep stages in babies.

PubMed

Mrowka, Ralf; Cimponeriu, Laura; Patzak, Andreas; Rosenblum, Michael G

2003-12-01

Activity of many physiological subsystems has a well-expressed rhythmic character. Often, a dependency between physiological rhythms is established due to interaction between the corresponding subsystems. Traditional methods of data analysis allow one to quantify the strength of interaction but not the causal interrelation that is indispensable for understanding the mechanisms of interaction. Here we present a recently developed method for quantification of coupling direction and apply it to an important problem. Namely, we study the mutual influence of respiratory and cardiovascular rhythms in healthy newborns within the first 6 mo of life in quiet and active sleep. We find an age-related change of the coupling direction: the interaction is nearly symmetric during the first days and becomes practically unidirectional (from respiration to heart rhythm) at the age of 6 mo. Next, we show that the direction of interaction is mainly determined by respiratory frequency. If the latter is less than approximately 0.6 Hz, the interaction occurs dominantly from respiration to heart. With higher respiratory frequencies that only occur at very young ages, the dominating direction is less pronounced or even abolished. The observed dependencies are not related to sleep stage, suggesting that the coupling direction is determined by system-inherent dynamical processes, rather than by functional modulations. The directional analysis may be applied to other interacting narrow band oscillatory systems, e.g., in the central nervous system. Thus it is an important step forward in revealing and understanding causal mechanisms of interactions.

Diesel Emissions Quantifier (DEQ)

EPA Pesticide Factsheets

.The Diesel Emissions Quantifier (Quantifier) is an interactive tool to estimate emission reductions and cost effectiveness. Publications EPA-420-F-13-008a (420f13008a), EPA-420-B-10-035 (420b10023), EPA-420-B-10-034 (420b10034)

Modeling the resilience of urban water supply using the capital portfolio approach

NASA Astrophysics Data System (ADS)

Krueger, E. H.; Klammler, H.; Borchardt, D.; Frank, K.; Jawitz, J. W.; Rao, P. S.

2017-12-01

The dynamics of global change challenge the resilience of cities in a multitude of ways, including pressures resulting from population and consumption changes, production patterns, climate and landuse change, as well as environmental hazards. Responses to these challenges aim to improve urban resilience, but lack an adequate understanding of 1) the elements and processes that lead to the resilience of coupled natural-human-engineered systems, 2) the complex dynamics emerging from the interaction of these elements, including the availability of natural resources, infrastructure, and social capital, which may lead to 3) unintended consequences resulting from management responses. We propose a new model that simulates the coupled dynamics of five types of capitals (water resources, infrastructure, finances, political capital /management, and social adaptive capacity) that are necessary for the provision of water supply to urban residents. We parameterize the model based on data for a case study city, which is limited by constraints in water availability, financial resources, and faced with degrading infrastructure, as well as population increase, which challenge the urban management institutions. Our model analyzes the stability of the coupled system, and produces time series of the capital dynamics to quantify its resilience as a result of the portfolio of capitals available to usher adaptive capacity and to secure water supply subjected to multiple recurring shocks. We apply our model to one real urban water supply system located in an arid environment, as well as a wide range of hypothetical case studies, which demonstrates its applicability to various types of cities, and its ability to quantify and compare water supply resilience. The analysis of a range of urban water systems provides valuable insights into guiding more sustainable responses for maintaining the resilience of urban water supply around the globe, by showing how unsustainable responses risk the loss of resilience. We suggest that the same model can be generalized to represent other types of urban infrastructure service systems with different parameterizations.

Turbulence sources, character, and effects in the stable boundary layer: Insights from multi-scale direct numerical simulations and new, high-resolution measurements

NASA Astrophysics Data System (ADS)

Fritts, Dave; Wang, Ling; Balsley, Ben; Lawrence, Dale

2013-04-01

A number of sources contribute to intermittent small-scale turbulence in the stable boundary layer (SBL). These include Kelvin-Helmholtz instability (KHI), gravity wave (GW) breaking, and fluid intrusions, among others. Indeed, such sources arise naturally in response to even very simple "multi-scale" superpositions of larger-scale GWs and smaller-scale GWs, mean flows, or fine structure (FS) throughout the atmosphere and the oceans. We describe here results of two direct numerical simulations (DNS) of these GW-FS interactions performed at high resolution and high Reynolds number that allow exploration of these turbulence sources and the character and effects of the turbulence that arises in these flows. Results include episodic turbulence generation, a broad range of turbulence scales and intensities, PDFs of dissipation fields exhibiting quasi-log-normal and more complex behavior, local turbulent mixing, and "sheet and layer" structures in potential temperature that closely resemble high-resolution measurements. Importantly, such multi-scale dynamics differ from their larger-scale, quasi-monochromatic gravity wave or quasi-horizontally homogeneous shear flow instabilities in significant ways. The ability to quantify such multi-scale dynamics with new, very high-resolution measurements is also advancing rapidly. New in-situ sensors on small, unmanned aerial vehicles (UAVs), balloons, or tethered systems are enabling definition of SBL (and deeper) environments and turbulence structure and dissipation fields with high spatial and temporal resolution and precision. These new measurement and modeling capabilities promise significant advances in understanding small-scale instability and turbulence dynamics, in quantifying their roles in mixing, transport, and evolution of the SBL environment, and in contributing to improved parameterizations of these dynamics in mesoscale, numerical weather prediction, climate, and general circulation models. We expect such measurement and modeling capabilities to also aid in the design of new and more comprehensive future SBL measurement programs.

Classifying acoustic signals into phoneme categories: average and dyslexic readers make use of complex dynamical patterns and multifractal scaling properties of the speech signal

PubMed Central

2015-01-01

Several competing aetiologies of developmental dyslexia suggest that the problems with acquiring literacy skills are causally entailed by low-level auditory and/or speech perception processes. The purpose of this study is to evaluate the diverging claims about the specific deficient peceptual processes under conditions of strong inference. Theoretically relevant acoustic features were extracted from a set of artificial speech stimuli that lie on a /bAk/-/dAk/ continuum. The features were tested on their ability to enable a simple classifier (Quadratic Discriminant Analysis) to reproduce the observed classification performance of average and dyslexic readers in a speech perception experiment. The ‘classical’ features examined were based on component process accounts of developmental dyslexia such as the supposed deficit in Envelope Rise Time detection and the deficit in the detection of rapid changes in the distribution of energy in the frequency spectrum (formant transitions). Studies examining these temporal processing deficit hypotheses do not employ measures that quantify the temporal dynamics of stimuli. It is shown that measures based on quantification of the dynamics of complex, interaction-dominant systems (Recurrence Quantification Analysis and the multifractal spectrum) enable QDA to classify the stimuli almost identically as observed in dyslexic and average reading participants. It seems unlikely that participants used any of the features that are traditionally associated with accounts of (impaired) speech perception. The nature of the variables quantifying the temporal dynamics of the speech stimuli imply that the classification of speech stimuli cannot be regarded as a linear aggregate of component processes that each parse the acoustic signal independent of one another, as is assumed by the ‘classical’ aetiologies of developmental dyslexia. It is suggested that the results imply that the differences in speech perception performance between average and dyslexic readers represent a scaled continuum rather than being caused by a specific deficient component. PMID:25834769

Spillover modes in multiplex games: double-edged effects on cooperation and their coevolution.

PubMed

Khoo, Tommy; Fu, Feng; Pauls, Scott

2018-05-02

In recent years, there has been growing interest in studying games on multiplex networks that account for interactions across linked social contexts. However, little is known about how potential cross-context interference, or spillover, of individual behavioural strategy impact overall cooperation. We consider three plausible spillover modes, quantifying and comparing their effects on the evolution of cooperation. In our model, social interactions take place on two network layers: repeated interactions with close neighbours in a lattice, and one-shot interactions with random individuals. Spillover can occur during the learning process with accidental cross-layer strategy transfer, or during social interactions with errors in implementation. Our analytical results, using extended pair approximation, are in good agreement with extensive simulations. We find double-edged effects of spillover: increasing the intensity of spillover can promote cooperation provided cooperation is favoured in one layer, but too much spillover is detrimental. We also discover a bistability phenomenon: spillover hinders or promotes cooperation depending on initial frequencies of cooperation in each layer. Furthermore, comparing strategy combinations emerging in each spillover mode provides good indication of their co-evolutionary dynamics with cooperation. Our results make testable predictions that inspire future research, and sheds light on human cooperation across social domains.

C-terminal interactions mediate the quaternary dynamics of αB-crystallin

PubMed Central

Hilton, Gillian R.; Hochberg, Georg K. A.; Laganowsky, Arthur; McGinnigle, Scott I.; Baldwin, Andrew J.; Benesch, Justin L. P.

2013-01-01

αB-crystallin is a highly dynamic, polydisperse small heat-shock protein that can form oligomers ranging in mass from 200 to 800 kDa. Here we use a multifaceted mass spectrometry approach to assess the role of the C-terminal tail in the self-assembly of αB-crystallin. Titration experiments allow us to monitor the binding of peptides representing the C-terminus to the αB-crystallin core domain, and observe individual affinities to both monomeric and dimeric forms. Notably, we find that binding the second peptide equivalent to the core domain dimer is considerably more difficult than the first, suggesting a role of the C-terminus in regulating assembly. This finding motivates us to examine the effect of point mutations in the C-terminus in the full-length protein, by quantifying the changes in oligomeric distribution and corresponding subunit exchange rates. Our results combine to demonstrate that alterations in the C-terminal tail have a significant impact on the thermodynamics and kinetics of αB-crystallin. Remarkably, we find that there is energy compensation between the inter- and intra-dimer interfaces: when one interaction is weakened, the other is strengthened. This allosteric communication between binding sites on αB-crystallin is likely important for its role in binding target proteins. PMID:23530258

Eigenvalue Attraction

NASA Astrophysics Data System (ADS)

Movassagh, Ramis

2016-02-01

We prove that the complex conjugate (c.c.) eigenvalues of a smoothly varying real matrix attract (Eq. 15). We offer a dynamical perspective on the motion and interaction of the eigenvalues in the complex plane, derive their governing equations and discuss applications. C.c. pairs closest to the real axis, or those that are ill-conditioned, attract most strongly and can collide to become exactly real. As an application we consider random perturbations of a fixed matrix M. If M is Normal, the total expected force on any eigenvalue is shown to be only the attraction of its c.c. (Eq. 24) and when M is circulant the strength of interaction can be related to the power spectrum of white noise. We extend this by calculating the expected force (Eq. 41) for real stochastic processes with zero-mean and independent intervals. To quantify the dominance of the c.c. attraction, we calculate the variance of other forces. We apply the results to the Hatano-Nelson model and provide other numerical illustrations. It is our hope that the simple dynamical perspective herein might help better understanding of the aggregation and low density of the eigenvalues of real random matrices on and near the real line respectively. In the appendix we provide a Matlab code for plotting the trajectories of the eigenvalues.

Multiscale Granger causality

NASA Astrophysics Data System (ADS)

Faes, Luca; Nollo, Giandomenico; Stramaglia, Sebastiano; Marinazzo, Daniele

2017-10-01

In the study of complex physical and biological systems represented by multivariate stochastic processes, an issue of great relevance is the description of the system dynamics spanning multiple temporal scales. While methods to assess the dynamic complexity of individual processes at different time scales are well established, multiscale analysis of directed interactions has never been formalized theoretically, and empirical evaluations are complicated by practical issues such as filtering and downsampling. Here we extend the very popular measure of Granger causality (GC), a prominent tool for assessing directed lagged interactions between joint processes, to quantify information transfer across multiple time scales. We show that the multiscale processing of a vector autoregressive (AR) process introduces a moving average (MA) component, and describe how to represent the resulting ARMA process using state space (SS) models and to combine the SS model parameters for computing exact GC values at arbitrarily large time scales. We exploit the theoretical formulation to identify peculiar features of multiscale GC in basic AR processes, and demonstrate with numerical simulations the much larger estimation accuracy of the SS approach compared to pure AR modeling of filtered and downsampled data. The improved computational reliability is exploited to disclose meaningful multiscale patterns of information transfer between global temperature and carbon dioxide concentration time series, both in paleoclimate and in recent years.

Exploring Entrainment Patterns of Human Emotion in Social Media

PubMed Central

Luo, Chuan; Zhang, Zhu

2016-01-01

Emotion entrainment, which is generally defined as the synchronous convergence of human emotions, performs many important social functions. However, what the specific mechanisms of emotion entrainment are beyond in-person interactions, and how human emotions evolve under different entrainment patterns in large-scale social communities, are still unknown. In this paper, we aim to examine the massive emotion entrainment patterns and understand the underlying mechanisms in the context of social media. As modeling emotion dynamics on a large scale is often challenging, we elaborate a pragmatic framework to characterize and quantify the entrainment phenomenon. By applying this framework on the datasets from two large-scale social media platforms, we find that the emotions of online users entrain through social networks. We further uncover that online users often form their relations via dual entrainment, while maintain it through single entrainment. Remarkably, the emotions of online users are more convergent in nonreciprocal entrainment. Building on these findings, we develop an entrainment augmented model for emotion prediction. Experimental results suggest that entrainment patterns inform emotion proximity in dyads, and encoding their associations promotes emotion prediction. This work can further help us to understand the underlying dynamic process of large-scale online interactions and make more reasonable decisions regarding emergency situations, epidemic diseases, and political campaigns in cyberspace. PMID:26953692

Model of rhythmic ball bouncing using a visually controlled neural oscillator.

PubMed

Avrin, Guillaume; Siegler, Isabelle A; Makarov, Maria; Rodriguez-Ayerbe, Pedro

2017-10-01

The present paper investigates the sensory-driven modulations of central pattern generator dynamics that can be expected to reproduce human behavior during rhythmic hybrid tasks. We propose a theoretical model of human sensorimotor behavior able to account for the observed data from the ball-bouncing task. The novel control architecture is composed of a Matsuoka neural oscillator coupled with the environment through visual sensory feedback. The architecture's ability to reproduce human-like performance during the ball-bouncing task in the presence of perturbations is quantified by comparison of simulated and recorded trials. The results suggest that human visual control of the task is achieved online. The adaptive behavior is made possible by a parametric and state control of the limit cycle emerging from the interaction of the rhythmic pattern generator, the musculoskeletal system, and the environment. NEW & NOTEWORTHY The study demonstrates that a behavioral model based on a neural oscillator controlled by visual information is able to accurately reproduce human modulations in a motor action with respect to sensory information during the rhythmic ball-bouncing task. The model attractor dynamics emerging from the interaction between the neuromusculoskeletal system and the environment met task requirements, environmental constraints, and human behavioral choices without relying on movement planning and explicit internal models of the environment. Copyright © 2017 the American Physiological Society.

Exploring Entrainment Patterns of Human Emotion in Social Media.

PubMed

He, Saike; Zheng, Xiaolong; Zeng, Daniel; Luo, Chuan; Zhang, Zhu

2016-01-01

Emotion entrainment, which is generally defined as the synchronous convergence of human emotions, performs many important social functions. However, what the specific mechanisms of emotion entrainment are beyond in-person interactions, and how human emotions evolve under different entrainment patterns in large-scale social communities, are still unknown. In this paper, we aim to examine the massive emotion entrainment patterns and understand the underlying mechanisms in the context of social media. As modeling emotion dynamics on a large scale is often challenging, we elaborate a pragmatic framework to characterize and quantify the entrainment phenomenon. By applying this framework on the datasets from two large-scale social media platforms, we find that the emotions of online users entrain through social networks. We further uncover that online users often form their relations via dual entrainment, while maintain it through single entrainment. Remarkably, the emotions of online users are more convergent in nonreciprocal entrainment. Building on these findings, we develop an entrainment augmented model for emotion prediction. Experimental results suggest that entrainment patterns inform emotion proximity in dyads, and encoding their associations promotes emotion prediction. This work can further help us to understand the underlying dynamic process of large-scale online interactions and make more reasonable decisions regarding emergency situations, epidemic diseases, and political campaigns in cyberspace.

Methodology for Uncertainty Analysis of Dynamic Computational Toxicology Models

EPA Science Inventory

The task of quantifying the uncertainty in both parameter estimates and model predictions has become more important with the increased use of dynamic computational toxicology models by the EPA. Dynamic toxicological models include physiologically-based pharmacokinetic (PBPK) mode...

Plasticity of brain wave network interactions and evolution across physiologic states

PubMed Central

Liu, Kang K. L.; Bartsch, Ronny P.; Lin, Aijing; Mantegna, Rosario N.; Ivanov, Plamen Ch.

2015-01-01

Neural plasticity transcends a range of spatio-temporal scales and serves as the basis of various brain activities and physiologic functions. At the microscopic level, it enables the emergence of brain waves with complex temporal dynamics. At the macroscopic level, presence and dominance of specific brain waves is associated with important brain functions. The role of neural plasticity at different levels in generating distinct brain rhythms and how brain rhythms communicate with each other across brain areas to generate physiologic states and functions remains not understood. Here we perform an empirical exploration of neural plasticity at the level of brain wave network interactions representing dynamical communications within and between different brain areas in the frequency domain. We introduce the concept of time delay stability (TDS) to quantify coordinated bursts in the activity of brain waves, and we employ a system-wide Network Physiology integrative approach to probe the network of coordinated brain wave activations and its evolution across physiologic states. We find an association between network structure and physiologic states. We uncover a hierarchical reorganization in the brain wave networks in response to changes in physiologic state, indicating new aspects of neural plasticity at the integrated level. Globally, we find that the entire brain network undergoes a pronounced transition from low connectivity in Deep Sleep and REM to high connectivity in Light Sleep and Wake. In contrast, we find that locally, different brain areas exhibit different network dynamics of brain wave interactions to achieve differentiation in function during different sleep stages. Moreover, our analyses indicate that plasticity also emerges in frequency-specific networks, which represent interactions across brain locations mediated through a specific frequency band. Comparing frequency-specific networks within the same physiologic state we find very different degree of network connectivity and link strength, while at the same time each frequency-specific network is characterized by a different signature pattern of sleep-stage stratification, reflecting a remarkable flexibility in response to change in physiologic state. These new aspects of neural plasticity demonstrate that in addition to dominant brain waves, the network of brain wave interactions is a previously unrecognized hallmark of physiologic state and function. PMID:26578891

Effects of temperature on consumer-resource interactions.

PubMed

Amarasekare, Priyanga

2015-05-01

Understanding how temperature variation influences the negative (e.g. self-limitation) and positive (e.g. saturating functional responses) feedback processes that characterize consumer-resource interactions is an important research priority. Previous work on this topic has yielded conflicting outcomes with some studies predicting that warming should increase consumer-resource oscillations and others predicting that warming should decrease consumer-resource oscillations. Here, I develop a consumer-resource model that both synthesizes previous findings in a common framework and yields novel insights about temperature effects on consumer-resource dynamics. I report three key findings. First, when the resource species' birth rate exhibits a unimodal temperature response, as demonstrated by a large number of empirical studies, the temperature range over which the consumer-resource interaction can persist is determined by the lower and upper temperature limits to the resource species' reproduction. This contrasts with the predictions of previous studies, which assume that the birth rate exhibits a monotonic temperature response, that consumer extinction is determined by temperature effects on consumer species' traits, rather than the resource species' traits. Secondly, the comparative analysis I have conducted shows that whether warming leads to an increase or decrease in consumer-resource oscillations depends on the manner in which temperature affects intraspecific competition. When the strength of self-limitation increases monotonically with temperature, warming causes a decrease in consumer-resource oscillations. However, if self-limitation is strongest at temperatures physiologically optimal for reproduction, a scenario previously unanalysed by theory but amply substantiated by empirical data, warming can cause an increase in consumer-resource oscillations. Thirdly, the model yields testable comparative predictions about consumer-resource dynamics under alternative hypotheses for how temperature affects competitive and resource acquisition traits. Importantly, it does so through empirically quantifiable metrics for predicting temperature effects on consumer viability and consumer-resource oscillations, which obviates the need for parameterizing complex dynamical models. Tests of these metrics with empirical data on a host-parasitoid interaction yield realistic estimates of temperature limits for consumer persistence and the propensity for consumer-resource oscillations, highlighting their utility in predicting temperature effects, particularly warming, on consumer-resource interactions in both natural and agricultural settings. © 2014 The Author. Journal of Animal Ecology © 2014 British Ecological Society.

Hydrological and dynamical characterization of Meddies in the Azores region: A paradigm for baroclinic vortex dynamics

NASA Astrophysics Data System (ADS)

Tychensky, A.; Carton, X.

1998-10-01

The Structure des Echanges Mer-Atmosphere, Proprietes des Heterogeneites Oceaniques: Recherche Expérimentale (SEMAPHORE) oceanographic experiment surveyed a 500 × 500 km2 domain south of the Azores from June to November 1993 and collected hydrological data, float trajectories, and current meter recordings. This data exhibited three intrathermocline eddies of Mediterranean water (Meddies), two of them being repeatedly sampled. Their hydrological and dynamical properties are quantified here by an isopycnic analysis. For the three Meddies, intense temperature and salinity anomalies (up to 4°C and 1.1 practical salinity units (psu)) are observed extending vertically over up to 1000 m and centered around 1000 m. Horizontally, these anomalies spread out to radii of 50-60 km, while the maximum azimuthal velocities (30 cm s-1, as computed by geostrophy) lie only at 35-40 km from the central axis. These Meddies followed curved trajectories, with drift velocities up to 7.5 cm s-1, under the influence of the neighboring mesoscale features (cyclonic vortices or Azores Current meanders). The three-dimensional structure of potential vorticity in and around these features evidences their complex interactions. Northwest of the domain, a Meddy was coupled to a subsurface anticyclone, forming an "aligned" vortex. It later interacted with the Azores Current, creating a large-amplitude northward meander by vertical alignment of vorticity. In the southeastern part of the domain, another Meddy was vertically aligned with an anticyclonic meander of the Azores Current and horizontally coupled with a cyclone of large vertical extent. These two features, as well as a small warm and salty fragment in their vicinity, seem to result from the southward crossing of the Meddy under the Azores Current. These observations illustrate previous theoretical studies of baroclinic vortex dynamics.

Multijoint kinetic chain analysis of knee extension during the soccer instep kick.

PubMed

Naito, Kozo; Fukui, Yosuke; Maruyama, Takeo

2010-04-01

Although previous studies have shown that motion-dependent interactions between adjacent segments play an important role in producing knee extension during the soccer instep kick, detailed knowledge about the mechanisms underlying those interactions is lacking. The present study aimed to develop a 3-D dynamical model for the multijoint kinetic chain of the instep kick in order to quantify the contributions of the causal dynamical factors to the production of maximum angular velocity during knee extension. Nine collegiate soccer players volunteered to participate in the experiment and performed instep kicking movements while 3-D positional data and the ground reaction force were measured. A dynamical model was developed in the form of a linked system containing 8 segments and 18 joint rotations, and the knee extension/flexion motion was decomposed into causal factors related to muscular moment, gyroscopic moment, centrifugal force, Coriolis force, gravity, proximal endpoint linear acceleration, and external force-dependent terms. The rapid knee extension during instep kicking was found to result almost entirely from kicking leg centrifugal force, trunk rotation muscular moment, kicking leg Coriolis force, and trunk rotation gyroscopic-dependent components. Based on the finding that rapid knee extension during instep kicking stems from multiple dynamical factors, it is suggested that the multijoint kinetic chain analysis used in the present study is more useful for achieving a detailed understanding of the cause of rapid kicking leg movement than the previously used 2-D, two-segment kinetic chain model. The present results also indicated that the centrifugal effect due to the kicking hip flexion angular velocity contributed substantially to the generation of a rapid knee extension, suggesting that the adjustment between the kicking hip flexion angular velocity and the leg configuration (knee flexion angle) is more important for effective instep kicking than other joint kinematics.

Sediment-stabilizing and Destabilizing Ecoengineering Species from River to Estuary: the Case of the Scheldt System

NASA Astrophysics Data System (ADS)

Selakovic, S.; Cozzoli, F.; Leuven, J.; Van Braeckel, A.; Speybroeck, J.; Kleinhans, M. G.; Bouma, T.

2017-12-01

Interactions between organisms and landscape forming processes play an important role in evolution of coastal landscapes. In particular, biota has a strong potential to interact with important geomorphological processes such as sediment dynamics. Although many studies worked towards quantifying the impact of different species groups on sediment dynamics, information has been gathered on an ad hoc base. Depending on species' traits and distribution, functional groups of ecoengineering species may have differential effects on sediment deposition and erosion. We hypothesize that the spatial distributions of sediment-stabilizing and destabilizing species across the channel and along the whole salinity gradient of an estuary partly determine the planform shape and channel-shoal morphology of estuaries. To test this hypothesis, we analyze vegetation and macrobenthic data taking the Scheldt river-estuarine continuum as model ecosystem. We identify species traits with important effects on sediment dynamics and use them to form functional groups. By using linearized mixed modelling, we are able to accurately describe the distributions of the different functional groups. We observe a clear distinction of dominant ecosystem engineering functional groups and their potential effects on the sediment in the river-estuarine continuum. The first results of longitudinal cross section show the highest effects of stabilizing plant species in riverine and sediment bioturbators in weak polyhaline part of continuum. The distribution of functional groups in transverse cross sections shows dominant stabilizing effect in supratidal zone compared to dominant destabilizing effect in the lower intertidal zone. This analysis offers a new and more general conceptualization of distributions of sediment stabilizing and destabilizing functional groups and their potential impacts on sediment dynamics, shoal patterns, and planform shapes in river-estuarine continuum. We intend to test this in future modelling and experiments.

Climate, invasive species and land use drive population dynamics of a cold-water specialist

USGS Publications Warehouse

Kovach, Ryan P.; Al-Chokhachy, Robert K.; Whited, Diane C.; Schmetterling, David A.; Dux, Andrew M; Muhlfeld, Clint C.

2017-01-01

Climate change is an additional stressor in a complex suite of threats facing freshwater biodiversity, particularly for cold-water fishes. Research addressing the consequences of climate change on cold-water fish has generally focused on temperature limits defining spatial distributions, largely ignoring how climatic variation influences population dynamics in the context of other existing stressors.We used long-term data from 92 populations of bull trout Salvelinus confluentus – one of North America's most cold-adapted fishes – to quantify additive and interactive effects of climate, invasive species and land use on population dynamics (abundance, variability and growth rate).Populations were generally depressed, more variable and declining where spawning and rearing stream habitat was limited, invasive species and land use were prevalent and stream temperatures were highest. Increasing stream temperature acted additively and independently, whereas land use and invasive species had additive and interactive effects (i.e. the impact of one stressor depended on exposure to the other stressor).Most (58%–78%) of the explained variation in population dynamics was attributed to the presence of invasive species, differences in life history and management actions in foraging habitats in rivers, lakes and reservoirs. Although invasive fishes had strong negative effects on populations in foraging habitats, proactive control programmes appeared to effectively temper their negative impact.Synthesis and applications. Long-term demographic data emphasize that climate warming will exacerbate imperilment of cold-water specialists like bull trout, yet other stressors – especially invasive fishes – are immediate threats that can be addressed by proactive management actions. Therefore, climate-adaptation strategies for freshwater biodiversity should consider existing abiotic and biotic stressors, some of which provide potential and realized opportunity for conservation of freshwater biodiversity in a warming world.

Compensatory dynamics stabilize aggregate community properties in response to multiple types of perturbations.

PubMed

Brown, Bryan L; Downing, Amy L; Leibold, Mathew A

2016-08-01

Compensatory dynamics are an important suite of mechanisms that can stabilize community and ecosystem attributes in systems subject to environmental fluctuations. However, few experimental investigations of compensatory dynamics have addressed these mechanisms in systems of real-world complexity, and existing evidence relies heavily on correlative analyses, retrospective examination, and experiments in simple systems. We investigated the potential for compensatory dynamics to stabilize plankton communities in plankton mesocosm systems of real-world complexity. We employed four types of perturbations including two types of nutrient pulses, shading, and acidification. To quantify how communities responded to these perturbations, we used a measure of community-wide synchrony combined with spectral analysis that allowed us to assess timescale-specific community dynamics, for example, whether dynamics were synchronous at some timescales but compensatory at others. The 150-d experiment produced 32-point time series of all zooplankton taxa in the mesocosms. We then used those time series to evaluate total zooplankton biomass as an aggregate property and to evaluate community dynamics. For three of our four perturbation types, total zooplankton biomass was significantly less variable in systems with environmental variation than in constant environments. For the same three perturbation types, community-wide synchrony was much lower in fluctuating environments than in the constant environment, particularly at longer timescales (periods ≈ 60 d). Additionally, there were strong negative correlations between population temporal variances and the level of community-wide synchrony. Taken together, these results strongly imply that compensatory interactions between species stabilized total biomass in response to perturbations. Diversity did not differ significantly across either treatments or perturbation types, thus ruling out several classes of mechanisms driven by changes in diversity. We also used several pieces of secondary evidence to evaluate the particular mechanism behind compensatory responses since a wide variety of mechanisms are hypothesized to produce compensatory dynamics. We concluded that fluctuation dependent endogenous cycles that occur as a consequence of consumer-resource interactions in competitive communities were the most likely explanation for the compensatory dynamics observed in our experiment. As with our previous work, scale-dependent dynamics were also a key to understanding compensatory dynamics in these experimental communities. © 2016 by the Ecological Society of America.

A Dynamic Nutrient Budget of Subsystem Interactions in a Salt Marsh Estuary

NASA Astrophysics Data System (ADS)

Childers, Daniel L.; McKellar, Henry N.; Dame, Richard F.; Sklar, Fred H.; Blood, Elizabeth R.

1993-02-01

In tidal salt marsh estuaries, the different habitats of the ecosystem interact primarily through the tidal creek water column. These interactions include nutrient and materials exchanges with the salt marsh, oyster reefs, creek bottoms, and adjacent uplands. Nutrient budgets are often used to synthesize these kinds of subsystem exchange data, and are usually based on annual totals without accounting for nutrient variability at finer temporal resolutions. In this paper, we present a dynamic budget of carbon (C), nitrogen (N), and phosphorus (P) for the North Inlet estuary, South Carolina that synthesizes subsystem flux data in a new way. We have developed a dynamic budget that uses a tidal hydrology model to generate daily areas of inundated intertidal habitat (i.e. vegetated marsh and oyster reef) from tidal heights calculated hourly and combines them with flux data to determine a net daily input to, or removal from, the water column. Daily surpluses or deficits of each nutrient were compared with daily rates of change in observed tidally-averaged nutrient concentrations. Particular emphasis was placed on evaluating budget output from the intertidal subsystems. We compared our total annual budgets to values from syntheses of two North Inlet flux studies. Although areas of marsh inundated were 150-200 times greater than areas of oyster reef inundated, interactions per unit volume of estuarine water column were comparable in magnitude for soluble reactive P (SRP), particulate organic C (POC), and dissolved organic C (DOC). The marsh dominated the ammonium (NH +4) and nitrate + nitrite (NN) exchanges in the summer but the NH +4 and POC output were particularly sensitive to changes in oyster reef area. Winter and spring DOC release by the marsh coincided closely (in timing and magnitude) with the peak in DOC concentrations observed in the North Inlet estuary, suggesting that forest stream inputs of DOC are not nearly as important as has been hypothesized. Comparison of our budget predictions to a previous synthesis of the same subsytem flux data confirmed the power of using tidal hydrology to estimate subsystem interactions between sampling times. These comparisons also emphasized the importance of (1) water column processes to NH +4 dynamics (2) subtidal benthic fluxes to DOC dynamics, and (3) external inputs to NN dynamics. By incorporating our best current knowledge of estuary-wide subsystem areas, the dynamic budget also allowed us to link subsystem flux data to the results of a study quantifying exchanges between the estuary and the coastal ocean. That comparison indicated the shortcomings of any site-specific extrapolation to whole-system conclusions where a homogeneous ecosystem must be assumed. We used the differences between our total annual C, N, and P budgets and reported exports of those constituents from the system to generate hypotheses and suggest future research efforts both at North Inlet and southeastern salt marsh estuaries in general.

Assessment of the dynamics of human glymphatic system by near-infrared spectroscopy.

PubMed

Myllylä, Teemu; Harju, Markus; Korhonen, Vesa; Bykov, Alexander; Kiviniemi, Vesa; Meglinski, Igor

2017-08-12

Fluctuations in brain water content has attracted increasing interest, particularly as regards studies of the glymphatic system, which is connected with the complex organization of dural lymphatic vessels, responsible for cleaning tissue. Disturbances of glymphatic circulation are associated with several brain disorders, including dementia. This article introduces an approach to noninvasive measurement of water dynamics in the human brain utilizing near-infrared spectroscopy (NIRS). We demonstrate the possibility to sense dynamic variations of water content between the skull and grey matter, for instance, in the subarachnoid space. Measured fluctuations in water content, especially in the cerebrospinal fluid (CSF), are assumed to be correlated with the dynamics of glymphatic circulation. The sampling volume for the NIRS optode was estimated by Monte Carlo modelling for the wavelengths of 660, 740, 830 and 980 nm. In addition, using combinations of these wavelengths, this article presents the calculation models for quantifying water and haemodynamics. The presented NIRS technique allows long-term functional brain monitoring, including sleeping time. Furthermore, it is used in combination with different magnetic neuroimaging techniques, particularly magnetic resonance encephalography. Using the combined setup, we report the preliminary results on the interaction between CSF and blood oxygen level-dependent fluctuations. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dynamic and impact contact mechanics of geologic materials: Grain-scale experiments and modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cole, David M.; Hopkins, Mark A.; Ketcham, Stephen A.

2013-06-18

High fidelity treatments of the generation and propagation of seismic waves in naturally occurring granular materials is becoming more practical given recent advancements in our ability to model complex particle shapes and their mechanical interaction. Of particular interest are the grain-scale processes that are activated by impact events and the characteristics of force transmission through grain contacts. To address this issue, we have developed a physics based approach that involves laboratory experiments to quantify the dynamic contact and impact behavior of granular materials and incorporation of the observed behavior indiscrete element models. The dynamic experiments do not involve particle damagemore » and emphasis is placed on measured values of contact stiffness and frictional loss. The normal stiffness observed in dynamic contact experiments at low frequencies (e.g., 10 Hz) are shown to be in good agreement with quasistatic experiments on quartz sand. The results of impact experiments - which involve moderate to extensive levels of particle damage - are presented for several types of naturally occurring granular materials (several quartz sands, magnesite and calcium carbonate ooids). Implementation of the experimental findings in discrete element models is discussed and the results of impact simulations involving up to 5 Multiplication-Sign 105 grains are presented.« less

Real-time modulated nanoparticle separation with an ultra-large dynamic range.

PubMed

Zeming, Kerwin Kwek; Thakor, Nitish V; Zhang, Yong; Chen, Chia-Hung

2016-01-07

Nanoparticles exhibit size-dependent properties which make size-selective purification of proteins, DNA or synthetic nanoparticles essential for bio-analytics, clinical medicine, nano-plasmonics and nano-material sciences. Current purification methods of centrifugation, column chromatography and continuous-flow techniques suffer from particle aggregation, multi-stage process, complex setups and necessary nanofabrication. These increase process costs and time, reduce efficiency and limit dynamic range. Here, we achieve an unprecedented real-time nanoparticle separation (51-1500 nm) using a large-pore (2 μm) deterministic lateral displacement (DLD) device. No external force fields or nanofabrication are required. Instead, we investigated innate long-range electrostatic influences on nanoparticles within a fluid medium at different NaCl ionic concentrations. In this study we account for the electrostatic forces beyond Debye length and showed that they cannot be assumed as negligible especially for precise nanoparticle separation methods such as DLD. Our findings have enabled us to develop a model to simultaneously quantify and modulate the electrostatic force interactions between nanoparticle and micropore. By simply controlling buffer solutions, we achieve dynamic nanoparticle size separation on a single device with a rapid response time (<20 s) and an enlarged dynamic range (>1200%), outperforming standard benchtop centrifuge systems. This novel method and model combines device simplicity, isolation precision and dynamic flexibility, opening opportunities for high-throughput applications in nano-separation for industrial and biological applications.

Quantifying internal friction in unfolded and intrinsically disordered proteins with single-molecule spectroscopy

PubMed Central

Soranno, Andrea; Buchli, Brigitte; Nettels, Daniel; Cheng, Ryan R.; Müller-Späth, Sonja; Pfeil, Shawn H.; Hoffmann, Armin; Lipman, Everett A.; Makarov, Dmitrii E.; Schuler, Benjamin

2012-01-01

Internal friction, which reflects the “roughness” of the energy landscape, plays an important role for proteins by modulating the dynamics of their folding and other conformational changes. However, the experimental quantification of internal friction and its contribution to folding dynamics has remained challenging. Here we use the combination of single-molecule Förster resonance energy transfer, nanosecond fluorescence correlation spectroscopy, and microfluidic mixing to determine the reconfiguration times of unfolded proteins and investigate the mechanisms of internal friction contributing to their dynamics. Using concepts from polymer dynamics, we determine internal friction with three complementary, largely independent, and consistent approaches as an additive contribution to the reconfiguration time of the unfolded state. We find that the magnitude of internal friction correlates with the compactness of the unfolded protein: its contribution dominates the reconfiguration time of approximately 100 ns of the compact unfolded state of a small cold shock protein under native conditions, but decreases for more expanded chains, and approaches zero both at high denaturant concentrations and in intrinsically disordered proteins that are expanded due to intramolecular charge repulsion. Our results suggest that internal friction in the unfolded state will be particularly relevant for the kinetics of proteins that fold in the microsecond range or faster. The low internal friction in expanded intrinsically disordered proteins may have implications for the dynamics of their interactions with cellular binding partners. PMID:22492978

Quantifying internal friction in unfolded and intrinsically disordered proteins with single-molecule spectroscopy.

PubMed

Soranno, Andrea; Buchli, Brigitte; Nettels, Daniel; Cheng, Ryan R; Müller-Späth, Sonja; Pfeil, Shawn H; Hoffmann, Armin; Lipman, Everett A; Makarov, Dmitrii E; Schuler, Benjamin

2012-10-30

Internal friction, which reflects the "roughness" of the energy landscape, plays an important role for proteins by modulating the dynamics of their folding and other conformational changes. However, the experimental quantification of internal friction and its contribution to folding dynamics has remained challenging. Here we use the combination of single-molecule Förster resonance energy transfer, nanosecond fluorescence correlation spectroscopy, and microfluidic mixing to determine the reconfiguration times of unfolded proteins and investigate the mechanisms of internal friction contributing to their dynamics. Using concepts from polymer dynamics, we determine internal friction with three complementary, largely independent, and consistent approaches as an additive contribution to the reconfiguration time of the unfolded state. We find that the magnitude of internal friction correlates with the compactness of the unfolded protein: its contribution dominates the reconfiguration time of approximately 100 ns of the compact unfolded state of a small cold shock protein under native conditions, but decreases for more expanded chains, and approaches zero both at high denaturant concentrations and in intrinsically disordered proteins that are expanded due to intramolecular charge repulsion. Our results suggest that internal friction in the unfolded state will be particularly relevant for the kinetics of proteins that fold in the microsecond range or faster. The low internal friction in expanded intrinsically disordered proteins may have implications for the dynamics of their interactions with cellular binding partners.

Epigenetic information in gametes: Gaming from before fertilization. Comment on ;Epigenetic game theory: How to compute the epigenetic control of maternal-to-zygotic transition; by Qian Wang et al.

NASA Astrophysics Data System (ADS)

Shi, Junchao; Zhang, Xudong; Liu, Ying; Chen, Qi

2017-03-01

In their interesting article [1] Wang et al. proposed a mathematical model based on evolutionary game theory [2] to tackle the fundamental question in embryo development, that how sperm and egg interact with each other, through epigenetic processes, to form a zygote and direct successful embryo development. This work is based on the premise that epigenetic reprogramming (referring to the erasure and reconstruction of epigenetic marks, such as DNA methylation and histone modifications) after fertilization might be of paramount importance to maintain the normal development of embryos, a premise we fully agree, given the compelling experimental evidence reported [3]. Wang et al. have specifically chosen to employ the well-studied DNA methylation reprogramming process during mammalian early embryo development, as a basis to develop their mathematical model, namely epigenetic game theory (epiGame). They concluded that the DNA methylation pattern in mammalian early embryo could be formulated and quantified, and their model can be further used to quantify the interactions, such as competition and/or cooperation of expressed genes that maximize the fitness of embryos. The efforts by Wang et al. in quantitatively and systematically analyzing the beginning of life apparently hold value and represent a novel direction for future embryo development research from both theoretical and experimental biologists. On the other hand, we see their theory still at its infancy, because there are plenty more parameters to consider and there are spaces for debates, such as the cases of haploid embryo development [4]. Here, we briefly comment on the dynamic process of epigenetic reprogramming that goes beyond DNA methylation, a dynamic interplay that involves histone modifications, non-coding RNAs, transposable elements et al., as well as the potential input of the various types of 'hereditary' epigenetic information in the gametes - a game that has started before the fertilization.

Super-resolution microscopy reveals structural diversity in molecular exchange among peptide amphiphile nanofibres

DOE PAGES

da Silva, Ricardo M. P.; van der Zwaag, Daan; Albertazzi, Lorenzo; ...

2016-05-19

The dynamic behaviour of supramolecular systems is an important dimension of their potential functions. Here, we report on the use of stochastic optical reconstruction microscopy to study the molecular exchange of peptide amphiphile nanofibres, supramolecular systems known to have important biomedical functions. Solutions of nanofibres labelled with different dyes (Cy3 and Cy5) were mixed, and the distribution of dyes inserting into initially single-colour nanofibres was quantified using correlative image analysis. Our observations are consistent with an exchange mechanism involving monomers or small clusters of molecules inserting randomly into a fibre. Different exchange rates are observed within the same fibre, suggestingmore » that local cohesive structures exist on the basis of beta-sheet discontinuous domains. The results reported here show that peptide amphiphile supramolecular systems can be dynamic and that their intermolecular interactions affect exchange patterns. Lastly, this information can be used to generate useful aggregate morphologies for improved biomedical function.« less

Visualizing viral transport and host infection

NASA Astrophysics Data System (ADS)

Son, Kwangmin; Guasto, Jeffrey; Cubillos-Ruiz, Andres; Sullivan, Matthew; Stocker, Roman; MIT Team

2013-11-01

A virus is a non-motile infectious agent that can only replicate inside a living host. They consist of a <100 nm diameter capsid which houses their DNA, and a <20 nm diameter tail used to inject DNA to the host, which are classified into three different morphologies by the tail type: short tail (~ 10 nm, podovirus), rigid contractile tail (~ 100 nm, myovirus), or flexible noncontractile tail (~ 300 nm, siphovirus). Combining microfluidics with epifluorescent microscopy, we studied the simultaneous diffusive transport governing the initial encounter and ultimately the infection of a non-motile cyanobacteria host (~ 1 μm prochlorococcus) and their viral (phage) counterparts in real time. This methodology allows us to quantify the virus-host encounter/adsorption dynamics and subsequently the effectiveness of various tail morphologies for viral infection. Viral transport and the role of viral morphology in host-virus interactions are critical to our understanding of both ecosystem dynamics and human health, as well as to the evolution of virus morphology.

A Study of Particle Beam Spin Dynamics for High Precision Experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fiedler, Andrew J.

In the search for physics beyond the Standard Model, high precision experiments to measure fundamental properties of particles are an important frontier. One group of such measurements involves magnetic dipole moment (MDM) values as well as searching for an electric dipole moment (EDM), both of which could provide insights about how particles interact with their environment at the quantum level and if there are undiscovered new particles. For these types of high precision experiments, minimizing statistical uncertainties in the measurements plays a critical role. \\\\ \\indent This work leverages computer simulations to quantify the effects of statistical uncertainty for experimentsmore » investigating spin dynamics. In it, analysis of beam properties and lattice design effects on the polarization of the beam is performed. As a case study, the beam lines that will provide polarized muon beams to the Fermilab Muon \\emph{g}-2 experiment are analyzed to determine the effects of correlations between the phase space variables and the overall polarization of the muon beam.« less

Defects and spatiotemporal disorder in a pattern of falling liquid columns

NASA Astrophysics Data System (ADS)

Brunet, Philippe; Limat, Laurent

2004-10-01

Disordered regimes of a one-dimensional pattern of liquid columns hanging below an overflowing circular dish are investigated experimentally. The interaction of two basic dynamical modes (oscillations and drift) combined with the occurrence of defects (birth of new columns, disappearances by coalescences of two columns) leads to spatiotemporal chaos. When the flow rate is progressively increased, a continuous transition between transient and permanent chaos is pointed into evidence. We introduce the rate of defects as the sole relevant quantity to quantify this “turbulence” without ambiguity. Statistics on both transient and endlessly chaotic regimes enable to define a critical flow rate around which exponents are extracted. Comparisons are drawn with other interfacial pattern-forming systems, where transition towards chaos follows similar steps. Qualitatively, careful examinations of the global dynamics show that the contamination processes are nonlocal and involve the propagation of blocks of elementary laminar states (such as propagative domains or local oscillations), emitted near the defects, which turn out to be essential ingredients of this self-sustained disorder.

Variance decomposition in stochastic simulators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Le Maître, O. P., E-mail: olm@limsi.fr; Knio, O. M., E-mail: knio@duke.edu; Moraes, A., E-mail: alvaro.moraesgutierrez@kaust.edu.sa

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance.more » Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.« less

Multiscale Analysis of a Collapsible Respiratory Airway

NASA Astrophysics Data System (ADS)

Ghadiali, Samir; Bell, E. David; Swarts, J. Douglas

2006-11-01

The Eustachian tube (ET) is a collapsible respiratory airway that connects the nasopharynx with the middle ear (ME). The ET normally exists in a collapsed state and must be periodically opened to maintain a healthy and sterile ME. Although the inability to open the ET (i.e. ET dysfunction) is the primary etiology responsible for several common ME diseases (i.e. Otitis Media), the mechanisms responsible for ET dysfunction are not well established. To investigate these mechanisms, we developed a multi-scale model of airflow in the ET and correlated model results with experimental data obtained in healthy and diseased subjects. The computational models utilized finite-element methods to simulate fluid-structure interactions and molecular dynamics techniques to quantify the adhesive properties of mucus glycoproteins. Results indicate that airflow in the ET is highly sensitive to both the dynamics of muscle contraction and molecular adhesion forces within the ET lumen. In addition, correlation of model results with experimental data obtained in diseased subjects was used to identify the biomechanical mechanisms responsible for ET dysfunction.

Effects of surface nanostructuring and impurity doping on ultrafast carrier dynamics of silicon photovoltaic cells: a pump-probe study

NASA Astrophysics Data System (ADS)

Chen, Tianyu; Nam, Yoon-Ho; Wang, Xinke; Han, Peng; Sun, Wenfeng; Feng, Shengfei; Ye, Jiasheng; Song, Jae-Won; Lee, Jung-Ho; Zhang, Chao; Zhang, Yan

2018-01-01

We present femtosecond optical pump-terahertz probe studies on the ultrafast dynamical processes of photo-generated charge carriers in silicon photovoltaic cells with various nanostructured surfaces and doping densities. The pump-probe measurements provide direct insight on the lifetime of photo-generated carriers, frequency-dependent complex dielectric response along with photoconductivity of silicon photovoltaic cells excited by optical pump pulses. A lifetime of photo-generated carriers of tens of nanosecond is identified from the time-dependent pump-induced attenuation of the terahertz transmission. In addition, we find a large value of the imaginary part of the dielectric function and of the real part of the photoconductivity in silicon photovoltaic cells with micron length nanowires. We attribute these findings to the result of defect-enhanced electron-photon interactions. Moreover, doping densities of phosphorous impurities in silicon photovoltaic cells are also quantified using the Drude-Smith model with our measured frequency-dependent complex photoconductivities.

Dynamic Coupling Between Respiratory and Cardiovascular System

NASA Astrophysics Data System (ADS)

Censi, Federica; Calcagnini, Giovanni; Cerutti, Sergio

The analysis of non-linear dynamics of the coupling among interacting quantities can be very useful for understanding the cardiorespiratory and cardiovascular control mechanisms. In this chapter RP is used to detect and quantify the degree of non-linear coupling between respiration and spontaneous rhythms of both heart rate and blood pressure variability signals. RQA turned out to be suitable for a quantitative evaluation of the observed coupling patterns among rhythms, both in simulated and real data, providing different degrees of coupling. The results from the simulated data showed that the increased degree of coupling between the signals was marked by the increase of PR and PD, and by the decrease of ER. When the RQA was applied to experimental data, PD and ER turned out to be the most significant variables, compared to PR. A remarkable finding is the detection of transient 1:2 PL episodes between respiration and cardiovascular variability signals. This phenomenon can be associated to a sub-harmonic synchronization between the two main rhythms of HR and BP variability series.

Deciphering the Minimal Algorithm for Development and Information-genesis

NASA Astrophysics Data System (ADS)

Li, Zhiyuan; Tang, Chao; Li, Hao

During development, cells with identical genomes acquires different fates in a highly organized manner. In order to decipher the principles underlining development, we used C.elegans as the model organism. Based on a large set of microscopy imaging, we first constructed a ``standard worm'' in silico: from the single zygotic cell to about 500 cell stage, the lineage, position, cell-cell contact and gene expression dynamics are quantified for each cell in order to investigate principles underlining these intensive data. Next, we reverse-engineered the possible gene-gene/cell-cell interaction rules that are capable of running a dynamic model recapitulating the early fate decisions during C.elegans development. we further formulized the C.elegans embryogenesis in the language of information genesis. Analysis towards data and model uncovered the global landscape of development in the cell fate space, suggested possible gene regulatory architectures and cell signaling processes, revealed diversity and robustness as the essential trade-offs in development, and demonstrated general strategies in building multicellular organisms.

The vacuole system is a significant intracellular pathway for longitudinal solute transport in basidiomycete fungi.

PubMed

Darrah, P R; Tlalka, M; Ashford, A; Watkinson, S C; Fricker, M D

2006-07-01

Mycelial fungi have a growth form which is unique among multicellular organisms. The data presented here suggest that they have developed a unique solution to internal solute translocation involving a complex, extended vacuole. In all filamentous fungi examined, this extended vacuole forms an interconnected network, dynamically linked by tubules, which has been hypothesized to act as an internal distribution system. We have tested this hypothesis directly by quantifying solute movement within the organelle by photobleaching a fluorescent vacuolar marker. Predictive simulation models were then used to determine the transport characteristics over extended length scales. This modeling showed that the vacuolar organelle forms a functionally important, bidirectional diffusive transport pathway over distances of millimeters to centimeters. Flux through the pathway is regulated by the dynamic tubular connections involving homotypic fusion and fission. There is also a strongly predicted interaction among vacuolar organization, predicted diffusion transport distances, and the architecture of the branching colony margin.

Collective chemotaxis and segregation of active bacterial colonies

NASA Astrophysics Data System (ADS)

Amar, M. Ben

2016-02-01

Still recently, bacterial fluid suspensions have motivated a lot of works, both experimental and theoretical, with the objective to understand their collective dynamics from universal and simple rules. Since some species are active, most of these works concern the strong interactions that these bacteria exert on a forced flow leading to instabilities, chaos and turbulence. Here, we investigate the self-organization of expanding bacterial colonies under chemotaxis, proliferation and eventually active-reaction. We propose a simple model to understand and quantify the physical properties of these living organisms which either give cohesion or on the contrary dispersion to the colony. Taking into account the diffusion and capture of morphogens complicates the model since it induces a bacterial density gradient coupled to bacterial density fluctuations and dynamics. Nevertheless under some specific conditions, it is possible to investigate the pattern formation as a usual viscous fingering instability. This explains the similarity and differences of patterns according to the physical bacterial suspension properties and explain the factors which favor compactness or branching.

The influence of Unruh effect on quantum steering for accelerated two-level detectors with different measurements

NASA Astrophysics Data System (ADS)

Liu, Tonghua; Wang, Jieci; Jing, Jiliang; Fan, Heng

2018-03-01

We propose a tight measure of quantum steering and study the dynamics of steering in a relativistic setting via different quantifiers. We present the dynamics of steering between two correlated Unruh-Dewitt detectors when one of them locally interacts with external scalar field. We find that the quantum steering, either measured by the entropic steering inequality or the Cavalcanti-Jones-Wiseman-Reid inequality, is fragile under the influence of Unruh thermal noise. The quantum steering is found always asymmetric and the asymmetry is extremely sensitive to the initial state parameter. In addition, the steering-type quantum correlations experience "sudden death" for some accelerations, which are quite different from the behaviors of other quantum correlations in the same system. It is worth noting that the domination value of the tight quantum steering exists a transformation point with increasing acceleration. We also find that the robustness of quantum steerability under the Unruh thermal noise can be realized by choosing the smallest energy gap in the detectors.

Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) Study of Mass-Transfer Mechanisms in Riser Flow.

PubMed

Carlos Varas, Álvaro E; Peters, E A J F; Kuipers, J A M

2017-05-17

We report a computational fluid dynamics-discrete element method (CFD-DEM) simulation study on the interplay between mass transfer and a heterogeneous catalyzed chemical reaction in cocurrent gas-particle flows as encountered in risers. Slip velocity, axial gas dispersion, gas bypassing, and particle mixing phenomena have been evaluated under riser flow conditions to study the complex system behavior in detail. The most important factors are found to be directly related to particle cluster formation. Low air-to-solids flux ratios lead to more heterogeneous systems, where the cluster formation is more pronounced and mass transfer more influenced. Falling clusters can be partially circumvented by the gas phase, which therefore does not fully interact with the cluster particles, leading to poor gas-solid contact efficiencies. Cluster gas-solid contact efficiencies are quantified at several gas superficial velocities, reaction rates, and dilution factors in order to gain more insight regarding the influence of clustering phenomena on the performance of riser reactors.

Quantitative Understanding of SHAPE Mechanism from RNA Structure and Dynamics Analysis.

PubMed

Hurst, Travis; Xu, Xiaojun; Zhao, Peinan; Chen, Shi-Jie

2018-05-10

The selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) method probes RNA local structural and dynamic information at single nucleotide resolution. To gain quantitative insights into the relationship between nucleotide flexibility, RNA 3D structure, and SHAPE reactivity, we develop a 3D Structure-SHAPE Relationship model (3DSSR) to rebuild SHAPE profiles from 3D structures. The model starts from RNA structures and combines nucleotide interaction strength and conformational propensity, ligand (SHAPE reagent) accessibility, and base-pairing pattern through a composite function to quantify the correlation between SHAPE reactivity and nucleotide conformational stability. The 3DSSR model shows the relationship between SHAPE reactivity and RNA structure and energetics. Comparisons between the 3DSSR-predicted SHAPE profile and the experimental SHAPE data show correlation, suggesting that the extracted analytical function may have captured the key factors that determine the SHAPE reactivity profile. Furthermore, the theory offers an effective method to sieve RNA 3D models and exclude models that are incompatible with experimental SHAPE data.

An unsupervised method for quantifying the behavior of paired animals

NASA Astrophysics Data System (ADS)

Klibaite, Ugne; Berman, Gordon J.; Cande, Jessica; Stern, David L.; Shaevitz, Joshua W.

2017-02-01

Behaviors involving the interaction of multiple individuals are complex and frequently crucial for an animal’s survival. These interactions, ranging across sensory modalities, length scales, and time scales, are often subtle and difficult to characterize. Contextual effects on the frequency of behaviors become even more difficult to quantify when physical interaction between animals interferes with conventional data analysis, e.g. due to visual occlusion. We introduce a method for quantifying behavior in fruit fly interaction that combines high-throughput video acquisition and tracking of individuals with recent unsupervised methods for capturing an animal’s entire behavioral repertoire. We find behavioral differences between solitary flies and those paired with an individual of the opposite sex, identifying specific behaviors that are affected by social and spatial context. Our pipeline allows for a comprehensive description of the interaction between two individuals using unsupervised machine learning methods, and will be used to answer questions about the depth of complexity and variance in fruit fly courtship.

Physical Forces between Humans and How Humans Attract and Repel Each Other Based on Their Social Interactions in an Online World

PubMed Central

Thurner, Stefan; Fuchs, Benedikt

2015-01-01

Physical interactions between particles are the result of the exchange of gauge bosons. Human interactions are mediated by the exchange of messages, goods, money, promises, hostilities, etc. While in the physical world interactions and their associated forces have immediate dynamical consequences (Newton’s laws) the situation is not clear for human interactions. Here we quantify the relative acceleration between humans who interact through the exchange of messages, goods and hostilities in a massive multiplayer online game. For this game we have complete information about all interactions (exchange events) between about 430,000 players, and about their trajectories (movements) in the metric space of the game universe at any point in time. We use this information to derive “interaction potentials" for communication, trade and attacks and show that they are harmonic in nature. Individuals who exchange messages and trade goods generally attract each other and start to separate immediately after exchange events end. The form of the interaction potential for attacks mirrors the usual “hit-and-run" tactics of aggressive players. By measuring interaction intensities as a function of distance, velocity and acceleration, we show that “forces" between players are directly related to the number of exchange events. We find an approximate power-law decay of the likelihood for interactions as a function of distance, which is in accordance with previous real world empirical work. We show that the obtained potentials can be understood with a simple model assuming an exchange-driven force in combination with a distance-dependent exchange rate. PMID:26196505

Physical Forces between Humans and How Humans Attract and Repel Each Other Based on Their Social Interactions in an Online World.

PubMed

Thurner, Stefan; Fuchs, Benedikt

2015-01-01

Physical interactions between particles are the result of the exchange of gauge bosons. Human interactions are mediated by the exchange of messages, goods, money, promises, hostilities, etc. While in the physical world interactions and their associated forces have immediate dynamical consequences (Newton's laws) the situation is not clear for human interactions. Here we quantify the relative acceleration between humans who interact through the exchange of messages, goods and hostilities in a massive multiplayer online game. For this game we have complete information about all interactions (exchange events) between about 430,000 players, and about their trajectories (movements) in the metric space of the game universe at any point in time. We use this information to derive "interaction potentials" for communication, trade and attacks and show that they are harmonic in nature. Individuals who exchange messages and trade goods generally attract each other and start to separate immediately after exchange events end. The form of the interaction potential for attacks mirrors the usual "hit-and-run" tactics of aggressive players. By measuring interaction intensities as a function of distance, velocity and acceleration, we show that "forces" between players are directly related to the number of exchange events. We find an approximate power-law decay of the likelihood for interactions as a function of distance, which is in accordance with previous real world empirical work. We show that the obtained potentials can be understood with a simple model assuming an exchange-driven force in combination with a distance-dependent exchange rate.

Characterization of mRNA-Cytoskeleton Interactions In Situ Using FMTRIP and Proximity Ligation

PubMed Central

Jung, Jeenah; Lifland, Aaron W.; Alonas, Eric J.; Zurla, Chiara; Santangelo, Philip J.

2013-01-01

Many studies have demonstrated an association between the cytoskeleton and mRNA, as well as the asymmetric distribution of mRNA granules within the cell in response to various signaling events. It is likely that the extensive cytoskeletal network directs mRNA transport and localization, with different cytoskeletal elements having their own specific roles. In order to understand the spatiotemporal changes in the interactions between the mRNA and the cytoskeleton as a response to a stimulus, a technique that can visualize and quantify these changes across a population of cells while capturing cell-to-cell variations is required. Here, we demonstrate a method for imaging and quantifying mRNA-cytoskeleton interactions on a per cell basis with single-interaction sensitivity. Using a proximity ligation assay with flag-tagged multiply-labeled tetravalent RNA imaging probes (FMTRIP), we quantified interactions between mRNAs and β-tubulin, vimentin, or filamentous actin (F-actin) for two different mRNAs, poly(A) + and β-actin mRNA, in two different cell types, A549 cells and human dermal fibroblasts (HDF). We found that the mRNAs interacted predominantly with F-actin (>50% in HDF, >20% in A549 cells), compared to β-tubulin (<5%) and vimentin (11-13%). This likely reflects differences in mRNA management by the two cell types. We then quantified changes in these interactions in response to two perturbations, F-actin depolymerization and arsenite-induced oxidative stress, both of which alter either the cytoskeleton itself and mRNA localization. Both perturbations led to a decrease in poly(A) + mRNA interactions with F-actin and an increase in the interactions with microtubules, in a time dependent manner. PMID:24040294

A CONTINUUM HARD-SPHERE MODEL OF PROTEIN ADSORPTION

PubMed Central

Finch, Craig; Clarke, Thomas; Hickman, James J.

2012-01-01

Protein adsorption plays a significant role in biological phenomena such as cell-surface interactions and the coagulation of blood. Two-dimensional random sequential adsorption (RSA) models are widely used to model the adsorption of proteins on solid surfaces. Continuum equations have been developed so that the results of RSA simulations can be used to predict the kinetics of adsorption. Recently, Brownian dynamics simulations have become popular for modeling protein adsorption. In this work a continuum model was developed to allow the results from a Brownian dynamics simulation to be used as the boundary condition in a computational fluid dynamics (CFD) simulation. Brownian dynamics simulations were used to model the diffusive transport of hard-sphere particles in a liquid and the adsorption of the particles onto a solid surface. The configuration of the adsorbed particles was analyzed to quantify the chemical potential near the surface, which was found to be a function of the distance from the surface and the fractional surface coverage. The near-surface chemical potential was used to derive a continuum model of adsorption that incorporates the results from the Brownian dynamics simulations. The equations of the continuum model were discretized and coupled to a CFD simulation of diffusive transport to the surface. The kinetics of adsorption predicted by the continuum model closely matched the results from the Brownian dynamics simulation. This new model allows the results from mesoscale simulations to be incorporated into micro- or macro-scale CFD transport simulations of protein adsorption in practical devices. PMID:23729843

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling.

PubMed

Wisz, Mary Susanne; Pottier, Julien; Kissling, W Daniel; Pellissier, Loïc; Lenoir, Jonathan; Damgaard, Christian F; Dormann, Carsten F; Forchhammer, Mads C; Grytnes, John-Arvid; Guisan, Antoine; Heikkinen, Risto K; Høye, Toke T; Kühn, Ingolf; Luoto, Miska; Maiorano, Luigi; Nilsson, Marie-Charlotte; Normand, Signe; Öckinger, Erik; Schmidt, Niels M; Termansen, Mette; Timmermann, Allan; Wardle, David A; Aastrup, Peter; Svenning, Jens-Christian

2013-02-01

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere. © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society.

Use of Mobile Device Data To Better Estimate Dynamic Population Size for Wastewater-Based Epidemiology.

PubMed

Thomas, Kevin V; Amador, Arturo; Baz-Lomba, Jose Antonio; Reid, Malcolm

2017-10-03

Wastewater-based epidemiology is an established approach for quantifying community drug use and has recently been applied to estimate population exposure to contaminants such as pesticides and phthalate plasticizers. A major source of uncertainty in the population weighted biomarker loads generated is related to estimating the number of people present in a sewer catchment at the time of sample collection. Here, the population quantified from mobile device-based population activity patterns was used to provide dynamic population normalized loads of illicit drugs and pharmaceuticals during a known period of high net fluctuation in the catchment population. Mobile device-based population activity patterns have for the first time quantified the high degree of intraday, week, and month variability within a specific sewer catchment. Dynamic population normalization showed that per capita pharmaceutical use remained unchanged during the period when static normalization would have indicated an average reduction of up to 31%. Per capita illicit drug use increased significantly during the monitoring period, an observation that was only possible to measure using dynamic population normalization. The study quantitatively confirms previous assessments that population estimates can account for uncertainties of up to 55% in static normalized data. Mobile device-based population activity patterns allow for dynamic normalization that yields much improved temporal and spatial trend analysis.

Quantifying dynamic characteristics of human walking for comprehensive gait cycle.

PubMed

Mummolo, Carlotta; Mangialardi, Luigi; Kim, Joo H

2013-09-01

Normal human walking typically consists of phases during which the body is statically unbalanced while maintaining dynamic stability. Quantifying the dynamic characteristics of human walking can provide better understanding of gait principles. We introduce a novel quantitative index, the dynamic gait measure (DGM), for comprehensive gait cycle. The DGM quantifies the effects of inertia and the static balance instability in terms of zero-moment point and ground projection of center of mass and incorporates the time-varying foot support region (FSR) and the threshold between static and dynamic walking. Also, a framework of determining the DGM from experimental data is introduced, in which the gait cycle segmentation is further refined. A multisegmental foot model is integrated into a biped system to reconstruct the walking motion from experiments, which demonstrates the time-varying FSR for different subphases. The proof-of-concept results of the DGM from a gait experiment are demonstrated. The DGM results are analyzed along with other established features and indices of normal human walking. The DGM provides a measure of static balance instability of biped walking during each (sub)phase as well as the entire gait cycle. The DGM of normal human walking has the potential to provide some scientific insights in understanding biped walking principles, which can also be useful for their engineering and clinical applications.

Quantifying Ciliary Dynamics during Assembly Reveals Step-wise Waveform Maturation in Airway Cells.

PubMed

Oltean, Alina; Schaffer, Andrew J; Bayly, Philip V; Brody, Steven L

2018-05-31

Motile cilia are essential for clearance of particulates and pathogens from airways. For effective transport, ciliary motor proteins and axonemal structures interact to generate the rhythmic, propulsive bending, but the mechanisms that produce a dynamic waveform remain incompletely understood. Biomechanical measures of human cilia motion and their relationships to cilia assembly are needed to illuminate the biophysics of normal cilia function, and to quantify dysfunction in ciliopathies. To these ends, we analyzed cilia motion from high-speed video microscopy of ciliated cells sampled from human lung airways compared to primary-culture cells that undergo ciliogenesis in vitro. Quantitative assessment of waveform parameters showed variations in waveform shape between individual cilia; however, general trends in waveform parameters emerged, associated with progression of cilia length and stage of differentiation. When cilia emerged from cultured cells, beat frequency was initially elevated, then fell and remained stable as cilia lengthened. In contrast, the average bending amplitude and the ability to generate force gradually increased and eventually approached values observed in ex vivo samples. Dynein arm motor proteins DNAH5, DNAH9, DNAH11, and DNAH6 were localized within specific regions of the axoneme in the ex vivo cells; however distinct stages of in vitro waveform development identified by biomechanical features were associated with the progressive movement of dyneins to the appropriate proximal or distal sections of the cilium. These observations suggest that the step-wise variation in waveform development during ciliogenesis is dependent on cilia length and potentially outer dynein arm assembly.

Measurement of energy landscape roughness of folded and unfolded proteins

PubMed Central

Milanesi, Lilia; Waltho, Jonathan P.; Hunter, Christopher A.; Shaw, Daniel J.; Beddard, Godfrey S.; Reid, Gavin D.; Dev, Sagarika; Volk, Martin

2012-01-01

The dynamics of protein conformational changes, from protein folding to smaller changes, such as those involved in ligand binding, are governed by the properties of the conformational energy landscape. Different techniques have been used to follow the motion of a protein over this landscape and thus quantify its properties. However, these techniques often are limited to short timescales and low-energy conformations. Here, we describe a general approach that overcomes these limitations. Starting from a nonnative conformation held by an aromatic disulfide bond, we use time-resolved spectroscopy to observe nonequilibrium backbone dynamics over nine orders of magnitude in time, from picoseconds to milliseconds, after photolysis of the disulfide bond. We find that the reencounter probability of residues that initially are in close contact decreases with time following an unusual power law that persists over the full time range and is independent of the primary sequence. Model simulations show that this power law arises from subdiffusional motion, indicating a wide distribution of trapping times in local minima of the energy landscape, and enable us to quantify the roughness of the energy landscape (4–5 kBT). Surprisingly, even under denaturing conditions, the energy landscape remains highly rugged with deep traps (>20 kBT) that result from multiple nonnative interactions and are sufficient for trapping on the millisecond timescale. Finally, we suggest that the subdiffusional motion of the protein backbone found here may promote rapid folding of proteins with low contact order by enhancing contact formation between nearby residues. PMID:23150572

Distinctly Different Glass Transition Behaviors of Trehalose Mixed with Na2HPO 4 or NaH 2PO 4: Evidence for its Molecular Origin.

PubMed

Weng, Lindong; Elliott, Gloria D

2015-07-01

The present study is aimed at understanding how the interactions between sugar molecules and phosphate ions affect the glass transition temperature of their mixtures, and the implications for pharmaceutical formulations. The glass transition temperature (Tg) and the α-relaxation temperature (Tα) of dehydrated trehalose/sodium phosphate mixtures (monobasic or dibasic) were determined by differential scanning calorimetry and dynamic mechanical analysis, respectively. Molecular dynamics simulations were also conducted to investigate the microscopic interactions between sugar molecules and phosphate ions. The hydrogen-bonding characteristics and the self-aggregation features of these mixtures were quantified and compared. Thermal analysis measurements demonstrated that the addition of NaH2PO4 decreased both the glass transition temperature and the α-relaxation temperature of the dehydrated trehalose/NaH2PO4 mixture compared to trehalose alone while both Tg and Tα were increased by adding Na2HPO4 to pure trehalose. The hydrogen-bonding interactions between trehalose and HPO4(2-) were found to be stronger than both the trehalose-trehalose hydrogen bonds and those formed between trehalose and H2PO4(-). The HPO4(2-) ions also aggregated into smaller clusters than H2PO4(-) ions. The trehalose/Na2HPO4 mixture yielded a higher T g than pure trehalose because marginally self-aggregated HPO4(2-) ions established a strengthened hydrogen-bonding network with trehalose molecules. In contrast H2PO4(-) ions served only as plasticizers, resulting in a lower Tg of the mixtures than trehalose alone, creating large-sized ionic pockets, weakening interactions, and disrupting the original hydrogen-bonding network amongst trehalose molecules.