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.

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.

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.

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 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.

An efficient approach to the analysis of rail surface irregularities accounting for dynamic train-track interaction and inelastic deformations

NASA Astrophysics Data System (ADS)

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

2015-11-01

A two-dimensional computational model for assessment of rolling contact fatigue induced by discrete rail surface irregularities, especially in the context of so-called squats, is presented. Dynamic excitation in a wide frequency range is considered in computationally efficient time-domain simulations of high-frequency dynamic vehicle-track interaction accounting for transient non-Hertzian wheel-rail contact. Results from dynamic simulations are mapped onto a finite element model to resolve the cyclic, elastoplastic stress response in the rail. Ratcheting under multiple wheel passages is quantified. In addition, low cycle fatigue impact is quantified using the Jiang-Sehitoglu fatigue parameter. The functionality of the model is demonstrated by numerical examples.

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.

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.

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).

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.

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

Evolutionary dynamics under interactive diversity

NASA Astrophysics Data System (ADS)

Su, Qi; Li, Aming; Wang, Long

2017-10-01

As evidenced by many cases in human societies, individuals often make different behavior decisions in different interactions, and adaptively adjust their behavior in changeable interactive scenarios. However, up to now, how such diverse interactive behavior affects cooperation dynamics has still remained unknown. Here we develop a general framework of interactive diversity, which models individuals’ separated behavior against distinct opponents and their adaptive adjustment in response to opponents’ strategies, to explore the evolution of cooperation. We find that interactive diversity enables individuals to reciprocate every single opponent, and thus sustains large-scale reciprocal interactions. Our work witnesses an impressive boost of cooperation for a notably extensive range of parameters and for all pairwise games. These results are robust against well-mixed and various networked populations, and against degree-normalized and cumulative payoff patterns. From the perspective of network dynamics, distinguished from individuals competing for nodes in most previous work, in this paper, the system evolves in the form of behavior disseminating along edges. We propose a theoretical method based on evolution of edges, which predicts well both the frequency of cooperation and the compact cooperation clusters. Our thorough investigation clarifies the positive role of interactive diversity in resolving social dilemmas and highlights the significance of understanding evolutionary dynamics from the viewpoint of edge dynamics.

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.

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

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

Vehicle systems: coupled and interactive dynamics analysis

NASA Astrophysics Data System (ADS)

Vantsevich, Vladimir V.

2014-11-01

This article formulates a new direction in vehicle dynamics, described as coupled and interactive vehicle system dynamics. Formalised procedures and analysis of case studies are presented. An analytical consideration, which explains the physics of coupled system dynamics and its consequences for dynamics of a vehicle, is given for several sets of systems including: (i) driveline and suspension of a 6×6 truck, (ii) a brake mechanism and a limited slip differential of a drive axle and (iii) a 4×4 vehicle steering system and driveline system. The article introduces a formal procedure to turn coupled system dynamics into interactive dynamics of systems. A new research direction in interactive dynamics of an active steering and a hybrid-electric power transmitting unit is presented and analysed to control power distribution between the drive axles of a 4×4 vehicle. A control strategy integrates energy efficiency and lateral dynamics by decoupling dynamics of the two systems thus forming their interactive dynamics.

Introducing Co-Activation Pattern Metrics to Quantify Spontaneous Brain Network Dynamics

PubMed Central

Chen, Jingyuan E.; Chang, Catie; Greicius, Michael D.; Glover, Gary H.

2015-01-01

Recently, fMRI researchers have begun to realize that the brain's intrinsic network patterns may undergo substantial changes during a single resting state (RS) scan. However, despite the growing interest in brain dynamics, metrics that can quantify the variability of network patterns are still quite limited. Here, we first introduce various quantification metrics based on the extension of co-activation pattern (CAP) analysis, a recently proposed point-process analysis that tracks state alternations at each individual time frame and relies on very few assumptions; then apply these proposed metrics to quantify changes of brain dynamics during a sustained 2-back working memory (WM) task compared to rest. We focus on the functional connectivity of two prominent RS networks, the default-mode network (DMN) and executive control network (ECN). We first demonstrate less variability of global Pearson correlations with respect to the two chosen networks using a sliding-window approach during WM task compared to rest; then we show that the macroscopic decrease in variations in correlations during a WM task is also well characterized by the combined effect of a reduced number of dominant CAPs, increased spatial consistency across CAPs, and increased fractional contributions of a few dominant CAPs. These CAP metrics may provide alternative and more straightforward quantitative means of characterizing brain network dynamics than time-windowed correlation analyses. PMID:25662866

Using metabarcoding to reveal and quantify plant-pollinator interactions

PubMed Central

Pornon, André; Escaravage, Nathalie; Burrus, Monique; Holota, Hélène; Khimoun, Aurélie; Mariette, Jérome; Pellizzari, Charlène; Iribar, Amaia; Etienne, Roselyne; Taberlet, Pierre; Vidal, Marie; Winterton, Peter; Zinger, Lucie; Andalo, Christophe

2016-01-01

Given the ongoing decline of both pollinators and plants, it is crucial to implement effective methods to describe complex pollination networks across time and space in a comprehensive and high-throughput way. Here we tested if metabarcoding may circumvent the limits of conventional methodologies in detecting and quantifying plant-pollinator interactions. Metabarcoding experiments on pollen DNA mixtures described a positive relationship between the amounts of DNA from focal species and the number of trnL and ITS1 sequences yielded. The study of pollen loads of insects captured in plant communities revealed that as compared to the observation of visits, metabarcoding revealed 2.5 times more plant species involved in plant-pollinator interactions. We further observed a tight positive relationship between the pollen-carrying capacities of insect taxa and the number of trnL and ITS1 sequences. The number of visits received per plant species also positively correlated to the number of their ITS1 and trnL sequences in insect pollen loads. By revealing interactions hard to observe otherwise, metabarcoding significantly enlarges the spatiotemporal observation window of pollination interactions. By providing new qualitative and quantitative information, metabarcoding holds great promise for investigating diverse facets of interactions and will provide a new perception of pollination networks as a whole. PMID:27255732

Entropy of dynamical social networks

NASA Astrophysics Data System (ADS)

Zhao, Kun; Karsai, Marton; Bianconi, Ginestra

2012-02-01

Dynamical social networks are evolving rapidly and are highly adaptive. Characterizing the information encoded in social networks is essential to gain insight into the structure, evolution, adaptability and dynamics. Recently entropy measures have been used to quantify the information in email correspondence, static networks and mobility patterns. Nevertheless, we still lack methods to quantify the information encoded in time-varying dynamical social networks. In this talk we present a model to quantify the entropy of dynamical social networks and use this model to analyze the data of phone-call communication. We show evidence that the entropy of the phone-call interaction network changes according to circadian rhythms. Moreover we show that social networks are extremely adaptive and are modified by the use of technologies such as mobile phone communication. Indeed the statistics of duration of phone-call is described by a Weibull distribution and is significantly different from the distribution of duration of face-to-face interactions in a conference. Finally we investigate how much the entropy of dynamical social networks changes in realistic models of phone-call or face-to face interactions characterizing in this way different type human social behavior.

Quantifying Information Gain from Dynamic Downscaling Experiments

NASA Astrophysics Data System (ADS)

Tian, Y.; Peters-Lidard, C. D.

2015-12-01

Dynamic climate downscaling experiments are designed to produce information at higher spatial and temporal resolutions. Such additional information is generated from the low-resolution initial and boundary conditions via the predictive power of the physical laws. However, errors and uncertainties in the initial and boundary conditions can be propagated and even amplified to the downscaled simulations. Additionally, the limit of predictability in nonlinear dynamical systems will also damper the information gain, even if the initial and boundary conditions were error-free. Thus it is critical to quantitatively define and measure the amount of information increase from dynamic downscaling experiments, to better understand and appreciate their potentials and limitations. We present a scheme to objectively measure the information gain from such experiments. The scheme is based on information theory, and we argue that if a downscaling experiment is to exhibit value, it has to produce more information than what can be simply inferred from information sources already available. These information sources include the initial and boundary conditions, the coarse resolution model in which the higher-resolution models are embedded, and the same set of physical laws. These existing information sources define an "information threshold" as a function of the spatial and temporal resolution, and this threshold serves as a benchmark to quantify the information gain from the downscaling experiments, or any other approaches. For a downscaling experiment to shown any value, the information has to be above this threshold. A recent NASA-supported downscaling experiment is used as an example to illustrate the application of this scheme.

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.

Interharmonic modulation products as a means to quantify nonlinear D-region interactions

NASA Astrophysics Data System (ADS)

Moore, Robert

Experimental observations performed during dual beam ionospheric HF heating experiments at the High frequency Active Auroral Research Program (HAARP) HF transmitter in Gakona, Alaska are used to quantify the relative importance of specific nonlinear interactions that occur within the D region ionosphere. During these experiments, HAARP broadcast two amplitude modulated HF beams whose center frequencies were separated by less than 20 kHz. One beam was sinusoidally modulated at 500 Hz while the second beam was sinusoidally modulated using a 1-7 kHz linear frequency-time chirp. ELF/VLF observations performed at two different locations (3 and 98 km from HAARP) provide clear evidence of strong interactions between all field components of the two HF beams in the form of low and high order interharmonic modulation products. From a theoretical standpoint, the observed interharmonic modulation products could be produced by several different nonlinearities. The two primary nonlinearities take the form of wave-medium interactions (i.e., cross modulation), wherein the ionospheric conductivity modulation produced by one signal crosses onto the other signal via collision frequency modification, and wave-wave interactions, wherein the conduction current associated with one wave mixes with the electric field of the other wave to produce electron temperature oscillations. We are able to separate and quantify these two different nonlinearities, and we conclude that the wave-wave interactions dominate the wave-medium interactions by a factor of two. These results are of great importance for the modeling of transioinospheric radio wave propagation, in that both the wave-wave and the wave-medium interactions could be responsible for a significant amount of anomalous absorption.

Quantifying Aggregation Dynamics during Myxococcus xanthus Development▿†

PubMed Central

Zhang, Haiyang; Angus, Stuart; Tran, Michael; Xie, Chunyan; Igoshin, Oleg A.; Welch, Roy D.

2011-01-01

Under starvation conditions, a swarm of Myxococcus xanthus cells will undergo development, a multicellular process culminating in the formation of many aggregates called fruiting bodies, each of which contains up to 100,000 spores. The mechanics of symmetry breaking and the self-organization of cells into fruiting bodies is an active area of research. Here we use microcinematography and automated image processing to quantify several transient features of developmental dynamics. An analysis of experimental data indicates that aggregation reaches its steady state in a highly nonmonotonic fashion. The number of aggregates rapidly peaks at a value 2- to 3-fold higher than the final value and then decreases before reaching a steady state. The time dependence of aggregate size is also nonmonotonic, but to a lesser extent: average aggregate size increases from the onset of aggregation to between 10 and 15 h and then gradually decreases thereafter. During this process, the distribution of aggregates transitions from a nearly random state early in development to a more ordered state later in development. A comparison of experimental results to a mathematical model based on the traffic jam hypothesis indicates that the model fails to reproduce these dynamic features of aggregation, even though it accurately describes its final outcome. The dynamic features of M. xanthus aggregation uncovered in this study impose severe constraints on its underlying mechanisms. PMID:21784940

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.

Dynamic quadrupole interactions in semiconductors

NASA Astrophysics Data System (ADS)

Dang, Thien Thanh; Schell, Juliana; Lupascu, Doru C.; Vianden, Reiner

2018-04-01

The time differential perturbed angular correlation, TDPAC, technique has been used for several decades to study electric quadrupole hyperfine interactions in semiconductors such as dynamic quadrupole interactions (DQI) resulting from after-effects of the nuclear decay as well as static quadrupole interactions originating from static defects around the probe nuclei such as interstitial ions, stresses in the crystalline structure, and impurities. Nowadays, the quality of the available semiconductor materials is much better, allowing us to study purely dynamic interactions. We present TDPAC measurements on pure Si, Ge, GaAs, and InP as a function of temperature between 12 K and 110 K. The probe 111In (111Cd) was used. Implantation damage was recovered by thermal annealing. Si experienced the strongest DQI with lifetime, τg, increasing with rising temperature, followed by Ge. In contrast, InP and GaAs, which have larger band gaps and less electron concentration than Si and Ge in the same temperature range, presented no DQI. The results obtained also allow us to conclude that indirect band gap semiconductors showed the dynamic interaction, whereas the direct band gap semiconductors, restricted to GaAs and InP, did not.

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 combinatorial framework to quantify peak/pit asymmetries in complex dynamics.

PubMed

Hasson, Uri; Iacovacci, Jacopo; Davis, Ben; Flanagan, Ryan; Tagliazucchi, Enzo; Laufs, Helmut; Lacasa, Lucas

2018-02-23

We explore a combinatorial framework which efficiently quantifies the asymmetries between minima and maxima in local fluctuations of time series. We first showcase its performance by applying it to a battery of synthetic cases. We find rigorous results on some canonical dynamical models (stochastic processes with and without correlations, chaotic processes) complemented by extensive numerical simulations for a range of processes which indicate that the methodology correctly distinguishes different complex dynamics and outperforms state of the art metrics in several cases. Subsequently, we apply this methodology to real-world problems emerging across several disciplines including cases in neurobiology, finance and climate science. We conclude that differences between the statistics of local maxima and local minima in time series are highly informative of the complex underlying dynamics and a graph-theoretic extraction procedure allows to use these features for statistical learning purposes.

Quantifying Functional Group Interactions that Determine Urea Effects on Nucleic Acid Helix Formation

PubMed Central

Guinn, Emily J.; Schwinefus, Jeffrey J.; Cha, Hyo Keun; McDevitt, Joseph L.; Merker, Wolf E.; Ritzer, Ryan; Muth, Gregory W.; Engelsgjerd, Samuel W.; Mangold, Kathryn E.; Thompson, Perry J.; Kerins, Michael J.; Record, Thomas

2013-01-01

Urea destabilizes helical and folded conformations of nucleic acids and proteins, as well as protein-nucleic acid complexes. To understand these effects, extend previous characterizations of interactions of urea with protein functional groups, and thereby develop urea as a probe of conformational changes in protein and nucleic acid processes, we obtain chemical potential derivatives (μ23 = dμ2/dm3) quantifying interactions of urea (component 3) with nucleic acid bases, base analogs, nucleosides and nucleotide monophosphates (component 2) using osmometry and hexanol-water distribution assays. Dissection of these μ23 yields interaction potentials quantifying interactions of urea with unit surface areas of nucleic acid functional groups (heterocyclic aromatic ring, ring methyl, carbonyl and phosphate O, amino N, sugar (C,O)); urea interacts favorably with all these groups, relative to interactions with water. Interactions of urea with heterocyclic aromatic rings and attached methyl groups (as on thymine) are particularly favorable, as previously observed for urea-homocyclic aromatic ring interactions. Urea m-values determined for double helix formation by DNA dodecamers near 25°C are in the range 0.72 to 0.85 kcal mol−1 m−1 and exhibit little systematic dependence on nucleobase composition (17–42% GC). Interpretation of these results using the urea interaction potentials indicates that extensive (60–90%) stacking of nucleobases in the separated strands in the transition region is required to explain the m-value. Results for RNA and DNA dodecamers obtained at higher temperatures, and literature data, are consistent with this conclusion. This demonstrates the utility of urea as a quantitative probe of changes in surface area (ΔASA) in nucleic acid processes. PMID:23510511

Dynamic interactions in neural networks

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

Arbib, M.A.; Amari, S.

The study of neural networks is enjoying a great renaissance, both in computational neuroscience, the development of information processing models of living brains, and in neural computing, the use of neurally inspired concepts in the construction of intelligent machines. This volume presents models and data on the dynamic interactions occurring in the brain, and exhibits the dynamic interactions between research in computational neuroscience and in neural computing. The authors present current research, future trends and open problems.

Coevolution of dynamical states and interactions in dynamic networks

NASA Astrophysics Data System (ADS)

Zimmermann, Martín G.; Eguíluz, Víctor M.; San Miguel, Maxi

2004-06-01

We explore the coupled dynamics of the internal states of a set of interacting elements and the network of interactions among them. Interactions are modeled by a spatial game and the network of interaction links evolves adapting to the outcome of the game. As an example, we consider a model of cooperation in which the adaptation is shown to facilitate the formation of a hierarchical interaction network that sustains a highly cooperative stationary state. The resulting network has the characteristics of a small world network when a mechanism of local neighbor selection is introduced in the adaptive network dynamics. The highly connected nodes in the hierarchical structure of the network play a leading role in the stability of the network. Perturbations acting on the state of these special nodes trigger global avalanches leading to complete network reorganization.

Cross-scale interactions: Quantifying multi-scaled cause–effect relationships in macrosystems

USGS Publications Warehouse

Soranno, Patricia A.; Cheruvelil, Kendra S.; Bissell, Edward G.; Bremigan, Mary T.; Downing, John A.; Fergus, Carol E.; Filstrup, Christopher T.; Henry, Emily N.; Lottig, Noah R.; Stanley, Emily H.; Stow, Craig A.; Tan, Pang-Ning; Wagner, Tyler; Webster, Katherine E.

2014-01-01

Ecologists are increasingly discovering that ecological processes are made up of components that are multi-scaled in space and time. Some of the most complex of these processes are cross-scale interactions (CSIs), which occur when components interact across scales. When undetected, such interactions may cause errors in extrapolation from one region to another. CSIs, particularly those that include a regional scaled component, have not been systematically investigated or even reported because of the challenges of acquiring data at sufficiently broad spatial extents. We present an approach for quantifying CSIs and apply it to a case study investigating one such interaction, between local and regional scaled land-use drivers of lake phosphorus. Ultimately, our approach for investigating CSIs can serve as a basis for efforts to understand a wide variety of multi-scaled problems such as climate change, land-use/land-cover change, and invasive species.

Quantifying dynamic rheology, phase interactions and strain localisation in deforming three phase magmas using high-speed x-ray tomography

NASA Astrophysics Data System (ADS)

Dobson, Katherine; Pistone, Mattia; Fife, Julie; Cordonnier, Benoit; Blundy, Jon; Dingwell, Don; Lee, Peter

2015-04-01

bubble within a small volume cylindrical experimental charge (3mm diameter, 5mm length) undergoing shear along a single vertical plane. By qualitative and quantitative analysis of the sequential images collected over 5-15 minute deformation cycles we track the local bubble, crystal and melt concentrations on a range of spatial scales. From this we calculate a spatially heterogeneous and dynamic local viscosity [3] and assess our results against recently developed 3-phase rheological models [4]. We will present how this real time 4D information can be used to quantify the dynamics of magma motion, discuss the implications of spatially and temporally variable rheological behaviours, and show how this novel technique can be integrated with other volcanology methods to improve our understanding of volcanic and magmatic processes. [1] Fife et al. 2012. J. Synchrotron Rad. 19, 352-358 [2] Kareh et al. 2014 Nature Comm. 5 4464. [3] Giordano, et al. 2008 EPSL 271 123-134. [4] Truby et al. 2015 P.Roy.Soc.A. 2015471 20140557

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.

A field comparison of multiple techniques to quantify groundwater - surface-water interactions

USGS Publications Warehouse

González-Pinzón, Ricardo; Ward, Adam S; Hatch, Christine E; Wlostowski, Adam N; Singha, Kamini; Gooseff, Michael N.; Haggerty, Roy; Harvey, Judson; Cirpka, Olaf A; Brock, James T

2015-01-01

Groundwater–surface-water (GW-SW) interactions in streams are difficult to quantify because of heterogeneity in hydraulic and reactive processes across a range of spatial and temporal scales. The challenge of quantifying these interactions has led to the development of several techniques, from centimeter-scale probes to whole-system tracers, including chemical, thermal, and electrical methods. We co-applied conservative and smart reactive solute-tracer tests, measurement of hydraulic heads, distributed temperature sensing, vertical profiles of solute tracer and temperature in the stream bed, and electrical resistivity imaging in a 450-m reach of a 3rd-order stream. GW-SW interactions were not spatially expansive, but were high in flux through a shallow hyporheic zone surrounding the reach. NaCl and resazurin tracers suggested different surface–subsurface exchange patterns in the upper ⅔ and lower ⅓ of the reach. Subsurface sampling of tracers and vertical thermal profiles quantified relatively high fluxes through a 10- to 20-cm deep hyporheic zone with chemical reactivity of the resazurin tracer indicated at 3-, 6-, and 9-cm sampling depths. Monitoring of hydraulic gradients along transects with MINIPOINT streambed samplers starting ∼40 m from the stream indicated that groundwater discharge prevented development of a larger hyporheic zone, which progressively decreased from the stream thalweg toward the banks. Distributed temperature sensing did not detect extensive inflow of ground water to the stream, and electrical resistivity imaging showed limited large-scale hyporheic exchange. We recommend choosing technique(s) based on: 1) clear definition of the questions to be addressed (physical, biological, or chemical processes), 2) explicit identification of the spatial and temporal scales to be covered and those required to provide an appropriate context for interpretation, and 3) maximizing generation of mechanistic understanding and reducing costs of

Quantified Gamow shell model interaction for p s d -shell nuclei

NASA Astrophysics Data System (ADS)

Jaganathen, Y.; Betan, R. M. Id; Michel, N.; Nazarewicz, W.; Płoszajczak, M.

2017-11-01

and excitation spectra of light nuclei with quantified uncertainties. Conclusion: The new interaction will enable comprehensive and fully quantified studies of structure and reactions aspects of nuclei from the p s d region of the nuclear chart.

Quantified Gamow shell model interaction for p s d -shell nuclei

DOE PAGES

Jaganathen, Y.; Betan, R. M. Id; Michel, N.; ...

2017-11-20

densities and excitation spectra of light nuclei with quantified uncertainties. In conclusion: The new interaction will enable comprehensive and fully quantified studies of structure and reactions aspects of nuclei from the psd region of the nuclear chart.« less

Quantifying sleep architecture dynamics and individual differences using big data and Bayesian networks

PubMed Central

Shelton, Christian; Mednick, Sara C.

2018-01-01

The pattern of sleep stages across a night (sleep architecture) is influenced by biological, behavioral, and clinical variables. However, traditional measures of sleep architecture such as stage proportions, fail to capture sleep dynamics. Here we quantify the impact of individual differences on the dynamics of sleep architecture and determine which factors or set of factors best predict the next sleep stage from current stage information. We investigated the influence of age, sex, body mass index, time of day, and sleep time on static (e.g. minutes in stage, sleep efficiency) and dynamic measures of sleep architecture (e.g. transition probabilities and stage duration distributions) using a large dataset of 3202 nights from a non-clinical population. Multi-level regressions show that sex effects duration of all Non-Rapid Eye Movement (NREM) stages, and age has a curvilinear relationship for Wake After Sleep Onset (WASO) and slow wave sleep (SWS) minutes. Bayesian network modeling reveals sleep architecture depends on time of day, total sleep time, age and sex, but not BMI. Older adults, and particularly males, have shorter bouts (more fragmentation) of Stage 2, SWS, and they transition less frequently to these stages. Additionally, we showed that the next sleep stage and its duration can be optimally predicted by the prior 2 stages and age. Our results demonstrate the potential benefit of big data and Bayesian network approaches in quantifying static and dynamic architecture of normal sleep. PMID:29641599

Quantifying sleep architecture dynamics and individual differences using big data and Bayesian networks.

PubMed

Yetton, Benjamin D; McDevitt, Elizabeth A; Cellini, Nicola; Shelton, Christian; Mednick, Sara C

2018-01-01

The pattern of sleep stages across a night (sleep architecture) is influenced by biological, behavioral, and clinical variables. However, traditional measures of sleep architecture such as stage proportions, fail to capture sleep dynamics. Here we quantify the impact of individual differences on the dynamics of sleep architecture and determine which factors or set of factors best predict the next sleep stage from current stage information. We investigated the influence of age, sex, body mass index, time of day, and sleep time on static (e.g. minutes in stage, sleep efficiency) and dynamic measures of sleep architecture (e.g. transition probabilities and stage duration distributions) using a large dataset of 3202 nights from a non-clinical population. Multi-level regressions show that sex effects duration of all Non-Rapid Eye Movement (NREM) stages, and age has a curvilinear relationship for Wake After Sleep Onset (WASO) and slow wave sleep (SWS) minutes. Bayesian network modeling reveals sleep architecture depends on time of day, total sleep time, age and sex, but not BMI. Older adults, and particularly males, have shorter bouts (more fragmentation) of Stage 2, SWS, and they transition less frequently to these stages. Additionally, we showed that the next sleep stage and its duration can be optimally predicted by the prior 2 stages and age. Our results demonstrate the potential benefit of big data and Bayesian network approaches in quantifying static and dynamic architecture of normal sleep.

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

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.

Loschmidt echo as a robust decoherence quantifier for many-body systems

NASA Astrophysics Data System (ADS)

Zangara, Pablo R.; Dente, Axel D.; Levstein, Patricia R.; Pastawski, Horacio M.

2012-07-01

We employ the Loschmidt echo, i.e., the signal recovered after the reversal of an evolution, to identify and quantify the processes contributing to decoherence. This procedure, which has been extensively used in single-particle physics, is employed here in a spin ladder. The isolated chains have 1/2 spins with XY interaction and their excitations would sustain a one-body-like propagation. One of them constitutes the controlled system S whose reversible dynamics is degraded by the weak coupling with the uncontrolled second chain, i.e., the environment E. The perturbative SE coupling is swept through arbitrary combinations of XY and Ising-like interactions, that contain the standard Heisenberg and dipolar ones. Different time regimes are identified for the Loschmidt echo dynamics in this perturbative configuration. In particular, the exponential decay scales as a Fermi golden rule, where the contributions of the different SE terms are individually evaluated and analyzed. Comparisons with previous analytical and numerical evaluations of decoherence based on the attenuation of specific interferences show that the Loschmidt echo is an advantageous decoherence quantifier at any time, regardless of the S internal dynamics.

A comparative analysis of alternative approaches for quantifying nonlinear dynamics in cardiovascular system.

PubMed

Chen, Yun; Yang, Hui

2013-01-01

Heart rate variability (HRV) analysis has emerged as an important research topic to evaluate autonomic cardiac function. However, traditional time and frequency-domain analysis characterizes and quantify only linear and stationary phenomena. In the present investigation, we made a comparative analysis of three alternative approaches (i.e., wavelet multifractal analysis, Lyapunov exponents and multiscale entropy analysis) for quantifying nonlinear dynamics in heart rate time series. Note that these extracted nonlinear features provide information about nonlinear scaling behaviors and the complexity of cardiac systems. To evaluate the performance, we used 24-hour HRV recordings from 54 healthy subjects and 29 heart failure patients, available in PhysioNet. Three nonlinear methods are evaluated not only individually but also in combination using three classification algorithms, i.e., linear discriminate analysis, quadratic discriminate analysis and k-nearest neighbors. Experimental results show that three nonlinear methods capture nonlinear dynamics from different perspectives and the combined feature set achieves the best performance, i.e., sensitivity 97.7% and specificity 91.5%. Collectively, nonlinear HRV features are shown to have the promise to identify the disorders in autonomic cardiovascular function.

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.

Quantum dynamics modeled by interacting trajectories

NASA Astrophysics Data System (ADS)

Cruz-Rodríguez, L.; Uranga-Piña, L.; Martínez-Mesa, A.; Meier, C.

2018-03-01

We present quantum dynamical simulations based on the propagation of interacting trajectories where the effect of the quantum potential is mimicked by effective pseudo-particle interactions. The method is applied to several quantum systems, both for bound and scattering problems. For the bound systems, the quantum ground state density and zero point energy are shown to be perfectly obtained by the interacting trajectories. In the case of time-dependent quantum scattering, the Eckart barrier and uphill ramp are considered, with transmission coefficients in very good agreement with standard quantum calculations. Finally, we show that via wave function synthesis along the trajectories, correlation functions and energy spectra can be obtained based on the dynamics of interacting trajectories.

Quantifying Electrical Interactions between Cardiomyocytes and Other Cells in Micropatterned Cell Pairs

PubMed Central

Nguyen, Hung; Badie, Nima; McSpadden, Luke; Pedrotty, Dawn; Bursac, Nenad

2014-01-01

Micropatterning is a powerful technique to control cell shape and position on a culture substrate. In this chapter, we describe the method to reproducibly create large numbers of micropatterned heterotypic cell pairs with defined size, shape, and length of cell–cell contact. These cell pairs can be utilized in patch clamp recordings to quantify electrical interactions between cardiomyocytes and non-cardiomyocytes. PMID:25070342

Quantifying Temperature Effects on Snow, Plant and Streamflow Dynamics in Headwater Catchments

NASA Astrophysics Data System (ADS)

Wainwright, H. M.; Sarah, T.; Siirila-Woodburn, E. R.; Newcomer, M. E.; Williams, K. H.; Hubbard, S. S.; Enquist, B. J.; Steltzer, H.; Carroll, R. W. H.

2017-12-01

Quantifying Temperature Effects on Snow, Plant and Streamflow Dynamics in Headwater Catchments Snow-dominated headwater catchments are critical for water resource throughout the world; particularly in Western US. Under climate change, temperature increases are expected to be amplified in mountainous regions. We use a data-driven approach to better understand the coupling among inter-annual variability in temperature, snow and plant community dynamics and stream discharge. We apply data mining methods (e.g., principal component analysis, random forest) to historical spatiotemporal datasets, including the SNOTEL data, Landsat-based normalized difference vegetation index (NDVI) and airborne LiDAR-based snow distribution. Although both snow distribution and NDVI are extremely heterogeneous spatially, the inter-annual variability and temporal responses are spatially consistent, providing an opportunity to quantify the effect of temperature in the catchment-scale. We demonstrate our approach in the East River Watershed of the Upper Colorado River Basin, including Rocky Mountain Biological Laboratory, where the changes in plant communities and their dynamics have been extensively documented. Results indicate that temperature - particularly spring temperature - has a significant control not only on the timing of snowmelt, plant NDVI and peak flow but also on the magnitude of peak NDVI, peak flow and annual discharge. Monthly temperature in spring explains the variability of snowmelt by the equivalent standard deviation of 3.4-4.4 days, and total discharge by 10-11%. In addition, the high correlation among June temperature, peak NDVI and annual discharge suggests a primary role of spring evapotranspiration on plant community phenology, productivity, and streamflow volume. On the other hand, summer monsoon precipitation does not contribute significantly to annual discharge, further emphasizing the importance of snowmelt. This approach is mostly based on a set of datasets

A Dynamic Interactive Theory of Person Construal

ERIC Educational Resources Information Center

Freeman, Jonathan B.; Ambady, Nalini

2011-01-01

A dynamic interactive theory of person construal is proposed. It assumes that the perception of other people is accomplished by a dynamical system involving continuous interaction between social categories, stereotypes, high-level cognitive states, and the low-level processing of facial, vocal, and bodily cues. This system permits lower-level…

Quantifying intermolecular interactions of ionic liquids using cohesive energy densities.

PubMed

Lovelock, Kevin R J

2017-12-01

For ionic liquids (ILs), both the large number of possible cation + anion combinations and their ionic nature provide a unique challenge for understanding intermolecular interactions. Cohesive energy density, ced , is used to quantify the strength of intermolecular interactions for molecular liquids, and is determined using the enthalpy of vaporization. A critical analysis of the experimental challenges and data to obtain ced for ILs is provided. For ILs there are two methods to judge the strength of intermolecular interactions, due to the presence of multiple constituents in the vapour phase of ILs. Firstly, ced IP , where the ionic vapour constituent is neutral ion pairs, the major constituent of the IL vapour. Secondly, ced C+A , where the ionic vapour constituents are isolated ions. A ced IP dataset is presented for 64 ILs. For the first time an experimental ced C+A , a measure of the strength of the total intermolecular interaction for an IL, is presented. ced C+A is significantly larger for ILs than ced for most molecular liquids, reflecting the need to break all of the relatively strong electrostatic interactions present in ILs. However, the van der Waals interactions contribute significantly to IL volatility due to the very strong electrostatic interaction in the neutral ion pair ionic vapour. An excellent linear correlation is found between ced IP and the inverse of the molecular volume. A good linear correlation is found between IL ced IP and IL Gordon parameter (which are dependent primarily on surface tension). ced values obtained through indirect methods gave similar magnitude values to ced IP . These findings show that ced IP is very important for understanding IL intermolecular interactions, in spite of ced IP not being a measure of the total intermolecular interactions of an IL. In the outlook section, remaining challenges for understanding IL intermolecular interactions are outlined.

Quantifying intermolecular interactions of ionic liquids using cohesive energy densities

PubMed Central

2017-01-01

For ionic liquids (ILs), both the large number of possible cation + anion combinations and their ionic nature provide a unique challenge for understanding intermolecular interactions. Cohesive energy density, ced, is used to quantify the strength of intermolecular interactions for molecular liquids, and is determined using the enthalpy of vaporization. A critical analysis of the experimental challenges and data to obtain ced for ILs is provided. For ILs there are two methods to judge the strength of intermolecular interactions, due to the presence of multiple constituents in the vapour phase of ILs. Firstly, cedIP, where the ionic vapour constituent is neutral ion pairs, the major constituent of the IL vapour. Secondly, cedC+A, where the ionic vapour constituents are isolated ions. A cedIP dataset is presented for 64 ILs. For the first time an experimental cedC+A, a measure of the strength of the total intermolecular interaction for an IL, is presented. cedC+A is significantly larger for ILs than ced for most molecular liquids, reflecting the need to break all of the relatively strong electrostatic interactions present in ILs. However, the van der Waals interactions contribute significantly to IL volatility due to the very strong electrostatic interaction in the neutral ion pair ionic vapour. An excellent linear correlation is found between cedIP and the inverse of the molecular volume. A good linear correlation is found between IL cedIP and IL Gordon parameter (which are dependent primarily on surface tension). ced values obtained through indirect methods gave similar magnitude values to cedIP. These findings show that cedIP is very important for understanding IL intermolecular interactions, in spite of cedIP not being a measure of the total intermolecular interactions of an IL. In the outlook section, remaining challenges for understanding IL intermolecular interactions are outlined. PMID:29308254

Modular scanning FCS quantifies receptor-ligand interactions in living multicellular organisms.

PubMed

Ries, Jonas; Yu, Shuizi Rachel; Burkhardt, Markus; Brand, Michael; Schwille, Petra

2009-09-01

Analysis of receptor-ligand interactions in vivo is key to biology but poses a considerable challenge to quantitative microscopy. Here we combine static-volume, two-focus and dual-color scanning fluorescence correlation spectroscopy to solve this task at cellular resolution in complex biological environments. We quantified the mobility of fibroblast growth factor receptors Fgfr1 and Fgfr4 in cell membranes of living zebrafish embryos and determined their in vivo binding affinities to their ligand Fgf8.

Quantifying hyporheic exchange dynamics in a highly regulated large river reach

NASA Astrophysics Data System (ADS)

Zhou, T.; Bao, J.; Huang, M.; Hou, Z.; Arntzen, E.; Mackley, R.; Harding, S.; Crump, A.; Xu, Y.; Song, X.; Chen, X.; Stegen, J.; Hammond, G. E.; Thorne, P. D.; Zachara, J. M.

2016-12-01

Hyporheic exchange is an important mechanism taking place in riverbanks and riverbed sediments, where the river water and shallow groundwater mix and interact with each other. The direction and magnitude of hyporheic flux that penetrates the river bed and residence time of river water in the hyporheic zone are critical for biogeochemical processes such as carbon and nitrogen cycling, and biodegradation of organic contaminants. Hyporheic flux can be quantified using many direct and indirect measurements as well as analytical and numerical modeling tools. However, in a relatively large river, these methods can be limited by the accessibility, spatial constraints, complexity of geomorphologic features and subsurface properties, and computational power. In rivers regulated by hydroelectric dams, quantifying hyporheic fluxes becomes more challenging due to frequent hydropeaking events created by dam operations. In this study, we developed and validated methods that combined field measurements and numerical modeling for estimating hyporheic fluxes across the river bed in a 7-km long reach of the highly regulated Columbia River. The reach has a minimum width of about 800 meters and variations in river stage within a day could be up to two meters due to the upstream dam operations. In shallow water along the shoreline, vertical thermal profiles measured by self-recording thermistors were combined with time series of hydraulic gradient derived from river stage and water level at in-land wells to estimate the hyporheic flux rate. For the deep section, a high resolution computational fluid dynamics (CFD) modeling framework was developed to characterize the spatial distribution of flux rates at the river bed and the residence time of hyporheic flow at different river flow conditions. Our modeling results show that the rates of hyporheic exchange and residence time are controlled by (1) hydrostatic pressure induced by river stage fluctuations, and (2) hydrodynamic drivers

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.

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

DOE PAGES

Sippel, Sebastian; Lange, Holger; Mahecha, Miguel D.; ...

2016-10-20

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observedmore » and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

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

Sippel, Sebastian; Lange, Holger; Mahecha, Miguel D.

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observedmore » and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

PubMed Central

Sippel, Sebastian; Mahecha, Miguel D.; Hauhs, Michael; Bodesheim, Paul; Kaminski, Thomas; Gans, Fabian; Rosso, Osvaldo A.

2016-01-01

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observed and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. We demonstrate here that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time

Vortex dynamics during blade-vortex interactions

NASA Astrophysics Data System (ADS)

Peng, Di; Gregory, James W.

2015-05-01

Vortex dynamics during parallel blade-vortex interactions (BVIs) were investigated in a subsonic wind tunnel using particle image velocimetry (PIV). Vortices were generated by applying a rapid pitch-up motion to an airfoil through a pneumatic system, and the subsequent interactions with a downstream, unloaded target airfoil were studied. The blade-vortex interactions may be classified into three categories in terms of vortex behavior: close interaction, very close interaction, and collision. For each type of interaction, the vortex trajectory and strength variation were obtained from phase-averaged PIV data. The PIV results revealed the mechanisms of vortex decay and the effects of several key parameters on vortex dynamics, including separation distance (h/c), Reynolds number, and vortex sense. Generally, BVI has two main stages: interaction between vortex and leading edge (vortex-LE interaction) and interaction between vortex and boundary layer (vortex-BL interaction). Vortex-LE interaction, with its small separation distance, is dominated by inviscid decay of vortex strength due to pressure gradients near the leading edge. Therefore, the decay rate is determined by separation distance and vortex strength, but it is relatively insensitive to Reynolds number. Vortex-LE interaction will become a viscous-type interaction if there is enough separation distance. Vortex-BL interaction is inherently dominated by viscous effects, so the decay rate is dependent on Reynolds number. Vortex sense also has great impact on vortex-BL interaction because it changes the velocity field and shear stress near the surface.

Model-free inference of direct network interactions from nonlinear collective dynamics.

PubMed

Casadiego, Jose; Nitzan, Mor; Hallerberg, Sarah; Timme, Marc

2017-12-19

The topology of interactions in network dynamical systems fundamentally underlies their function. Accelerating technological progress creates massively available data about collective nonlinear dynamics in physical, biological, and technological systems. Detecting direct interaction patterns from those dynamics still constitutes a major open problem. In particular, current nonlinear dynamics approaches mostly require to know a priori a model of the (often high dimensional) system dynamics. Here we develop a model-independent framework for inferring direct interactions solely from recording the nonlinear collective dynamics generated. Introducing an explicit dependency matrix in combination with a block-orthogonal regression algorithm, the approach works reliably across many dynamical regimes, including transient dynamics toward steady states, periodic and non-periodic dynamics, and chaos. Together with its capabilities to reveal network (two point) as well as hypernetwork (e.g., three point) interactions, this framework may thus open up nonlinear dynamics options of inferring direct interaction patterns across systems where no model is known.

PCB Food Web Dynamics Quantify Nutrient and Energy Flow in Aquatic Ecosystems.

PubMed

McLeod, Anne M; Paterson, Gordon; Drouillard, Ken G; Haffner, G Douglas

2015-11-03

Measuring in situ nutrient and energy flows in spatially and temporally complex aquatic ecosystems represents a major ecological challenge. Food web structure, energy and nutrient budgets are difficult to measure, and it is becoming more important to quantify both energy and nutrient flow to determine how food web processes and structure are being modified by multiple stressors. We propose that polychlorinated biphenyl (PCB) congeners represent an ideal tracer to quantify in situ energy and nutrient flow between trophic levels. Here, we demonstrate how an understanding of PCB congener bioaccumulation dynamics provides multiple direct measurements of energy and nutrient flow in aquatic food webs. To demonstrate this novel approach, we quantified nitrogen (N), phosphorus (P) and caloric turnover rates for Lake Huron lake trout, and reveal how these processes are regulated by both growth rate and fish life history. Although minimal nutrient recycling was observed in young growing fish, slow growing, older lake trout (>5 yr) recycled an average of 482 Tonnes·yr(-1) of N, 45 Tonnes·yr(-1) of P and assimilated 22 TJ yr(-1) of energy. Compared to total P loading rates of 590 Tonnes·yr(-1), the recycling of primarily bioavailable nutrients by fish plays an important role regulating the nutrient states of oligotrophic lakes.

Revealing physical interaction networks from statistics of collective dynamics

PubMed Central

Nitzan, Mor; Casadiego, Jose; Timme, Marc

2017-01-01

Revealing physical interactions in complex systems from observed collective dynamics constitutes a fundamental inverse problem in science. Current reconstruction methods require access to a system’s model or dynamical data at a level of detail often not available. We exploit changes in invariant measures, in particular distributions of sampled states of the system in response to driving signals, and use compressed sensing to reveal physical interaction networks. Dynamical observations following driving suffice to infer physical connectivity even if they are temporally disordered, are acquired at large sampling intervals, and stem from different experiments. Testing various nonlinear dynamic processes emerging on artificial and real network topologies indicates high reconstruction quality for existence as well as type of interactions. These results advance our ability to reveal physical interaction networks in complex synthetic and natural systems. PMID:28246630

Communication: Polymer entanglement dynamics: Role of attractive interactions

DOE PAGES

Grest, Gary S.

2016-10-10

The coupled dynamics of entangled polymers, which span broad time and length scales, govern their unique viscoelastic properties. To follow chain mobility by numerical simulations from the intermediate Rouse and reptation regimes to the late time diffusive regime, highly coarse grained models with purely repulsive interactions between monomers are widely used since they are computationally the most efficient. In this paper, using large scale molecular dynamics simulations, the effect of including the attractive interaction between monomers on the dynamics of entangled polymer melts is explored for the first time over a wide temperature range. Attractive interactions have little effect onmore » the local packing for all temperatures T and on the chain mobility for T higher than about twice the glass transition T g. Finally, these results, across a broad range of molecular weight, show that to study the dynamics of entangled polymer melts, the interactions can be treated as pure repulsive, confirming a posteriori the validity of previous studies and opening the way to new large scale numerical simulations.« less

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

Structural Dynamics and Control Interaction of Flexible Structures

NASA Technical Reports Server (NTRS)

Ryan, Robert S. (Editor); Scofield, Harold N. (Editor)

1987-01-01

A workshop on structural dynamics and control interaction of flexible structures was held to promote technical exchange between the structural dynamics and control disciplines, foster joint technology, and provide a forum for discussing and focusing critical issues in the separate and combined areas. Issues and areas of emphasis were identified in structure-control interaction for the next generation of flexible systems.

Quantifying human-environment interactions using videography in the context of infectious disease transmission.

PubMed

Julian, Timothy R; Bustos, Carla; Kwong, Laura H; Badilla, Alejandro D; Lee, Julia; Bischel, Heather N; Canales, Robert A

2018-05-08

Quantitative data on human-environment interactions are needed to fully understand infectious disease transmission processes and conduct accurate risk assessments. Interaction events occur during an individual's movement through, and contact with, the environment, and can be quantified using diverse methodologies. Methods that utilize videography, coupled with specialized software, can provide a permanent record of events, collect detailed interactions in high resolution, be reviewed for accuracy, capture events difficult to observe in real-time, and gather multiple concurrent phenomena. In the accompanying video, the use of specialized software to capture humanenvironment interactions for human exposure and disease transmission is highlighted. Use of videography, combined with specialized software, allows for the collection of accurate quantitative representations of human-environment interactions in high resolution. Two specialized programs include the Virtual Timing Device for the Personal Computer, which collects sequential microlevel activity time series of contact events and interactions, and LiveTrak, which is optimized to facilitate annotation of events in real-time. Opportunities to annotate behaviors at high resolution using these tools are promising, permitting detailed records that can be summarized to gain information on infectious disease transmission and incorporated into more complex models of human exposure and risk.

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.

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)

Electrostatically confined nanoparticle interactions and dynamics.

PubMed

Eichmann, Shannon L; Anekal, Samartha G; Bevan, Michael A

2008-02-05

We report integrated evanescent wave and video microscopy measurements of three-dimensional trajectories of 50, 100, and 250 nm gold nanoparticles electrostatically confined between parallel planar glass surfaces separated by 350 and 600 nm silica colloid spacers. Equilibrium analyses of single and ensemble particle height distributions normal to the confining walls produce net electrostatic potentials in excellent agreement with theoretical predictions. Dynamic analyses indicate lateral particle diffusion coefficients approximately 30-50% smaller than expected from predictions including the effects of the equilibrium particle distribution within the gap and multibody hydrodynamic interactions with the confining walls. Consistent analyses of equilibrium and dynamic information in each measurement do not indicate any roles for particle heating or hydrodynamic slip at the particle or wall surfaces, which would both increase diffusivities. Instead, lower than expected diffusivities are speculated to arise from electroviscous effects enhanced by the relative extent (kappaa approximately 1-3) and overlap (kappah approximately 2-4) of electrostatic double layers on the particle and wall surfaces. These results demonstrate direct, quantitative measurements and a consistent interpretation of metal nanoparticle electrostatic interactions and dynamics in a confined geometry, which provides a basis for future similar measurements involving other colloidal forces and specific biomolecular interactions.

Interactions Dominate the Dynamics of Visual Cognition

PubMed Central

Stephen, Damian G.; Mirman, Daniel

2010-01-01

Many cognitive theories have described behavior as the summation of independent contributions from separate components. Contrasting views have emphasized the importance of multiplicative interactions and emergent structure. We describe a statistical approach to distinguishing additive and multiplicative processes and apply it to the dynamics of eye movements during classic visual cognitive tasks. The results reveal interaction-dominant dynamics in eye movements in each of the three tasks, and that fine-grained eye movements are modulated by task constraints. These findings reveal the interactive nature of cognitive processing and are consistent with theories that view cognition as an emergent property of processes that are broadly distributed over many scales of space and time rather than a componential assembly line. PMID:20070957

Interactions dominate the dynamics of visual cognition.

PubMed

Stephen, Damian G; Mirman, Daniel

2010-04-01

Many cognitive theories have described behavior as the summation of independent contributions from separate components. Contrasting views have emphasized the importance of multiplicative interactions and emergent structure. We describe a statistical approach to distinguishing additive and multiplicative processes and apply it to the dynamics of eye movements during classic visual cognitive tasks. The results reveal interaction-dominant dynamics in eye movements in each of the three tasks, and that fine-grained eye movements are modulated by task constraints. These findings reveal the interactive nature of cognitive processing and are consistent with theories that view cognition as an emergent property of processes that are broadly distributed over many scales of space and time rather than a componential assembly line. Copyright 2009 Elsevier B.V. All rights reserved.

Acoustics and dynamics of coaxial interacting vortex rings

NASA Technical Reports Server (NTRS)

Shariff, Karim; Leonard, Anthony; Zabusky, Norman J.; Ferziger, Joel H.

1988-01-01

Using a contour dynamics method for inviscid axisymmetric flow we examine the effects of core deformation on the dynamics and acoustic signatures of coaxial interacting vortex rings. Both 'passage' and 'collision' (head-on) interactions are studied for initially identical vortices. Good correspondence with experiments is obtained. A simple model which retains only the elliptic degree of freedom in the core shape is used to explain some of the calculated features.

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.

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.

Coupling functions: Universal insights into dynamical interaction mechanisms

NASA Astrophysics Data System (ADS)

Stankovski, Tomislav; Pereira, Tiago; McClintock, Peter V. E.; Stefanovska, Aneta

2017-10-01

The dynamical systems found in nature are rarely isolated. Instead they interact and influence each other. The coupling functions that connect them contain detailed information about the functional mechanisms underlying the interactions and prescribe the physical rule specifying how an interaction occurs. A coherent and comprehensive review is presented encompassing the rapid progress made recently in the analysis, understanding, and applications of coupling functions. The basic concepts and characteristics of coupling functions are presented through demonstrative examples of different domains, revealing the mechanisms and emphasizing their multivariate nature. The theory of coupling functions is discussed through gradually increasing complexity from strong and weak interactions to globally coupled systems and networks. A variety of methods that have been developed for the detection and reconstruction of coupling functions from measured data is described. These methods are based on different statistical techniques for dynamical inference. Stemming from physics, such methods are being applied in diverse areas of science and technology, including chemistry, biology, physiology, neuroscience, social sciences, mechanics, and secure communications. This breadth of application illustrates the universality of coupling functions for studying the interaction mechanisms of coupled dynamical systems.

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

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.

Dynamic neurotransmitter interactions measured with PET

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

Schiffer, W.K.; Dewey, S.L.

2001-04-02

Positron emission tomography (PET) has become a valuable interdisciplinary tool for understanding physiological, biochemical and pharmacological functions at a molecular level in living humans, whether in a healthy or diseased state. The utility of tracing chemical activity through the body transcends the fields of cardiology, oncology, neurology and psychiatry. In this, PET techniques span radiochemistry and radiopharmaceutical development to instrumentation, image analysis, anatomy and modeling. PET has made substantial contributions in each of these fields by providing a,venue for mapping dynamic functions of healthy and unhealthy human anatomy. As diverse as the disciplines it bridges, PET has provided insight intomore » an equally significant variety of psychiatric disorders. Using the unique quantitative ability of PET, researchers are now better able to non-invasively characterize normally occurring neurotransmitter interactions in the brain. With the knowledge that these interactions provide the fundamental basis for brain response, many investigators have recently focused their efforts on an examination of the communication between these chemicals in both healthy volunteers and individuals suffering from diseases classically defined as neurotransmitter specific in nature. In addition, PET can measure the biochemical dynamics of acute and sustained drug abuse. Thus, PET studies of neurotransmitter interactions enable investigators to describe a multitude of specific functional interactions in the human brain. This information can then be applied to understanding side effects that occur in response to acute and chronic drug therapy, and to designing new drugs that target multiple systems as opposed to single receptor types. Knowledge derived from PET studies can be applied to drug discovery, research and development (for review, see (Fowler et al., 1999) and (Burns et al., 1999)). Here, we will cover the most substantial contributions of PET to

Evaluation of interaction dynamics of concurrent processes

NASA Astrophysics Data System (ADS)

Sobecki, Piotr; Białasiewicz, Jan T.; Gross, Nicholas

2017-03-01

The purpose of this paper is to present the wavelet tools that enable the detection of temporal interactions of concurrent processes. In particular, the determination of interaction coherence of time-varying signals is achieved using a complex continuous wavelet transform. This paper has used electrocardiogram (ECG) and seismocardiogram (SCG) data set to show multiple continuous wavelet analysis techniques based on Morlet wavelet transform. MATLAB Graphical User Interface (GUI), developed in the reported research to assist in quick and simple data analysis, is presented. These software tools can discover the interaction dynamics of time-varying signals, hence they can reveal their correlation in phase and amplitude, as well as their non-linear interconnections. The user-friendly MATLAB GUI enables effective use of the developed software what enables to load two processes under investigation, make choice of the required processing parameters, and then perform the analysis. The software developed is a useful tool for researchers who have a need for investigation of interaction dynamics of concurrent processes.

Quantifying wetland–aquifer interactions in a humid subtropical climate region: An integrated approach

USGS Publications Warehouse

Mendoza-Sanchez, Itza; Phanikumar, Mantha S.; Niu, Jie; Masoner, Jason R.; Cozzarelli, Isabelle M.; McGuire, Jennifer T.

2013-01-01

Wetlands are widely recognized as sentinels of global climate change. Long-term monitoring data combined with process-based modeling has the potential to shed light on key processes and how they change over time. This paper reports the development and application of a simple water balance model based on long-term climate, soil, vegetation and hydrological dynamics to quantify groundwater–surface water (GW–SW) interactions at the Norman landfill research site in Oklahoma, USA. Our integrated approach involved model evaluation by means of the following independent measurements: (a) groundwater inflow calculation using stable isotopes of oxygen and hydrogen (16O, 18O, 1H, 2H); (b) seepage flux measurements in the wetland hyporheic sediment; and (c) pan evaporation measurements on land and in the wetland. The integrated approach was useful for identifying the dominant hydrological processes at the site, including recharge and subsurface flows. Simulated recharge compared well with estimates obtained using isotope methods from previous studies and allowed us to identify specific annual signatures of this important process during the period of study (1997–2007). Similarly, observations of groundwater inflow and outflow rates to and from the wetland using seepage meters and isotope methods were found to be in good agreement with simulation results. Results indicate that subsurface flow components in the system are seasonal and readily respond to rainfall events. The wetland water balance is dominated by local groundwater inputs and regional groundwater flow contributes little to the overall water balance.

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.

Dynamic Interaction of Long Suspension Bridges with Running Trains

NASA Astrophysics Data System (ADS)

XIA, H.; XU, Y. L.; CHAN, T. H. T.

2000-10-01

This paper presents an investigation of dynamic interaction of long suspension bridges with running trains. A three-dimensional finite element model is used to represent a long suspension bridge. Each 4-axle vehicle in a train is modelled by a 27-degrees-of-freedom dynamic system. The dynamic interaction between the bridge and train is realized through the contact forces between the wheels and track. By applying a mode superposition technique to the bridge only and taking the measured track irregularities as known quantities, the number of degrees of freedom (d.o.f.) the bridge-train system is significantly reduced and the coupled equations of motion are efficiently solved. The proposed formulation and the associated computer program are then applied to a real long suspension bridge carrying a railway within the bridge deck. The dynamic response of the bridge-train system and the derail and offload factors related to the running safety of the train are computed. The results show that the formulation presented in this paper can well predict dynamic behaviors of both bridge and train with reasonable computation efforts. Dynamic interaction between the long suspension bridge and train is not significant.

Modeling the dynamical interaction between epidemics on overlay networks

NASA Astrophysics Data System (ADS)

Marceau, Vincent; Noël, Pierre-André; Hébert-Dufresne, Laurent; Allard, Antoine; Dubé, Louis J.

2011-08-01

Epidemics seldom occur as isolated phenomena. Typically, two or more viral agents spread within the same host population and may interact dynamically with each other. We present a general model where two viral agents interact via an immunity mechanism as they propagate simultaneously on two networks connecting the same set of nodes. By exploiting a correspondence between the propagation dynamics and a dynamical process performing progressive network generation, we develop an analytical approach that accurately captures the dynamical interaction between epidemics on overlay networks. The formalism allows for overlay networks with arbitrary joint degree distribution and overlap. To illustrate the versatility of our approach, we consider a hypothetical delayed intervention scenario in which an immunizing agent is disseminated in a host population to hinder the propagation of an undesirable agent (e.g., the spread of preventive information in the context of an emerging infectious disease).

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.

Modular interdependency in complex dynamical systems.

PubMed

Watson, Richard A; Pollack, Jordan B

2005-01-01

Herbert A. Simon's characterization of modularity in dynamical systems describes subsystems as having dynamics that are approximately independent of those of other subsystems (in the short term). This fits with the general intuition that modules must, by definition, be approximately independent. In the evolution of complex systems, such modularity may enable subsystems to be modified and adapted independently of other subsystems, whereas in a nonmodular system, modifications to one part of the system may result in deleterious side effects elsewhere in the system. But this notion of modularity and its effect on evolvability is not well quantified and is rather simplistic. In particular, modularity need not imply that intermodule dependences are weak or unimportant. In dynamical systems this is acknowledged by Simon's suggestion that, in the long term, the dynamical behaviors of subsystems do interact with one another, albeit in an "aggregate" manner--but this kind of intermodule interaction is omitted in models of modularity for evolvability. In this brief discussion we seek to unify notions of modularity in dynamical systems with notions of how modularity affects evolvability. This leads to a quantifiable measure of modularity and a different understanding of its effect on evolvability.

Modeling Human Dynamics of Face-to-Face Interaction Networks

NASA Astrophysics Data System (ADS)

Starnini, Michele; Baronchelli, Andrea; Pastor-Satorras, Romualdo

2013-04-01

Face-to-face interaction networks describe social interactions in human gatherings, and are the substrate for processes such as epidemic spreading and gossip propagation. The bursty nature of human behavior characterizes many aspects of empirical data, such as the distribution of conversation lengths, of conversations per person, or of interconversation times. Despite several recent attempts, a general theoretical understanding of the global picture emerging from data is still lacking. Here we present a simple model that reproduces quantitatively most of the relevant features of empirical face-to-face interaction networks. The model describes agents that perform a random walk in a two-dimensional space and are characterized by an attractiveness whose effect is to slow down the motion of people around them. The proposed framework sheds light on the dynamics of human interactions and can improve the modeling of dynamical processes taking place on the ensuing dynamical social networks.

Quantifying infant physical interactions using sensorized toys in a natural play environment.

PubMed

Goyal, Vatsala; Torres, Wilson; Rai, Roshan; Shofer, Frances; Bogen, Daniel; Bryant, Phillip; Prosser, Laura; Johnson, Michelle J

2017-07-01

Infants with developmental delays must be detected early in their development to minimize the progression of motor and neurological impairments. Our objective is to quantify how sensorized toys in a natural play environment can promote infant-toy physical interactions. We created a hanging elephant toy, equipped with an inertial measurement unit (IMU), a pressure transducer, and multiple feedback sensors, to be a hand-grasping toy. We used a 3 DoF robotic model with inputs from the IMU to calculate multiple kinematic metrics and an equation to calculate haptic metrics from the pressure transducer. Six typical infants were tested in the gym set-up. Three infants interacted with the toy for more than half the trial time. The youngest infant exhibited the largest toy displacement with ΔD = 27.6 cm, while the oldest infant squeezed the toy with the largest mean pressure of 4.5 kPa. More data on on both typical and atypical infants needs to be collected. After testing atypical infants in the SmarToyGym set-up, we will be able to identify interaction metrics that differentiate atypical and typical infants.

Quantifying the effects of overgrazing on mountainous watershed vegetation dynamics under a changing climate.

PubMed

Hao, Lu; Pan, Cen; Fang, Di; Zhang, Xiaoyu; Zhou, Decheng; Liu, Peilong; Liu, Yongqiang; Sun, Ge

2018-10-15

Grazing is a major ecosystem disturbance in arid regions that are increasingly threatened by climate change. Understanding the long-term impacts of grazing on rangeland vegetation dynamics in a complex terrain in mountainous regions is important for quantifying dry land ecosystem services for integrated watershed management and climate change adaptation. However, data on the detailed long-term spatial distribution of grazing activities are rare, which prevents trend detection and environmental impact assessments of grazing. This study quantified the impacts of grazing on vegetation dynamics for the period of 1983-2010 in the Upper Heihe River basin, a complex multiple-use watershed in northwestern China. We also examined the relative contributions of grazing and climate to vegetation change using a dynamic grazing pressure method. Spatial grazing patterns and temporal dynamics were mapped at a 1 km × 1 km pixel scale using satellite-derived leaf area index (LAI) data. We found that overgrazing was a dominant driver for LAI reduction in alpine grasslands and shrubs, especially for the periods of 1985-1991 and 1997-2004. Although the recent decade-long active grazing management contributed to the improvement of LAI and partially offset the negative effects of increased livestock, overgrazing has posed significant challenges to shrub-grassland ecosystem recovery in the eastern part of the study basin. We conclude that the positive effects of a warming and wetting climate on vegetation could be underestimated if the negative long-term grazing effects are not considered. Findings from the present case study show that assessing long-term climate change impacts on watersheds must include the influences of human activities. Our study provides important guidance for ecological restoration efforts in locating vulnerable areas and designing effective management practices in the study watershed. Such information is essential for natural resource management that aims

Evolutionary dynamics of group interactions on structured populations: a review

PubMed Central

Perc, Matjaž; Gómez-Gardeñes, Jesús; Szolnoki, Attila; Floría, Luis M.; Moreno, Yamir

2013-01-01

Interactions among living organisms, from bacteria colonies to human societies, are inherently more complex than interactions among particles and non-living matter. Group interactions are a particularly important and widespread class, representative of which is the public goods game. In addition, methods of statistical physics have proved valuable for studying pattern formation, equilibrium selection and self-organization in evolutionary games. Here, we review recent advances in the study of evolutionary dynamics of group interactions on top of structured populations, including lattices, complex networks and coevolutionary models. We also compare these results with those obtained on well-mixed populations. The review particularly highlights that the study of the dynamics of group interactions, like several other important equilibrium and non-equilibrium dynamical processes in biological, economical and social sciences, benefits from the synergy between statistical physics, network science and evolutionary game theory. PMID:23303223

Quantifiers more or less quantify online: ERP evidence for partial incremental interpretation

PubMed Central

Urbach, Thomas P.; Kutas, Marta

2010-01-01

Event-related brain potentials were recorded during RSVP reading to test the hypothesis that quantifier expressions are incrementally interpreted fully and immediately. In sentences tapping general knowledge (Farmers grow crops/worms as their primary source of income), Experiment 1 found larger N400s for atypical (worms) than typical objects (crops). Experiment 2 crossed object typicality with non-logical subject-noun phrase quantifiers (most, few). Off-line plausibility ratings exhibited the crossover interaction predicted by full quantifier interpretation: Most farmers grow crops and Few farmers grow worms were rated more plausible than Most farmers grow worms and Few farmers grow crops. Object N400s, although modulated in the expected direction, did not reverse. Experiment 3 replicated these findings with adverbial quantifiers (Farmers often/rarely grow crops/worms). Interpretation of quantifier expressions thus is neither fully immediate nor fully delayed. Furthermore, object atypicality was associated with a frontal slow positivity in few-type/rarely quantifier contexts, suggesting systematic processing differences among quantifier types. PMID:20640044

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.

Dynamics of two interacting active Janus particles.

PubMed

Bayati, Parvin; Najafi, Ali

2016-04-07

Starting from a microscopic model for a spherically symmetric active Janus particle, we study the interactions between two such active motors. The ambient fluid mediates a long range hydrodynamic interaction between two motors. This interaction has both direct and indirect hydrodynamic contributions. The direct contribution is due to the propagation of fluid flow that originated from a moving motor and affects the motion of the other motor. The indirect contribution emerges from the re-distribution of the ionic concentrations in the presence of both motors. Electric force exerted on the fluid from this ionic solution enhances the flow pattern and subsequently changes the motion of both motors. By formulating a perturbation method for very far separated motors, we derive analytic results for the translation and rotational dynamics of the motors. We show that the overall interaction at the leading order modifies the translational and rotational speeds of motors which scale as O[1/D](3) and O[1/D](4) with their separation, respectively. Our findings open up the way for studying the collective dynamics of synthetic micro-motors.

Dynamics of deceptive interactions in social networks.

PubMed

Barrio, Rafael A; Govezensky, Tzipe; Dunbar, Robin; Iñiguez, Gerardo; Kaski, Kimmo

2015-11-06

In this paper, we examine the role of lies in human social relations by implementing some salient characteristics of deceptive interactions into an opinion formation model, so as to describe the dynamical behaviour of a social network more realistically. In this model, we take into account such basic properties of social networks as the dynamics of the intensity of interactions, the influence of public opinion and the fact that in every human interaction it might be convenient to deceive or withhold information depending on the instantaneous situation of each individual in the network. We find that lies shape the topology of social networks, especially the formation of tightly linked, small communities with loose connections between them. We also find that agents with a larger proportion of deceptive interactions are the ones that connect communities of different opinion, and, in this sense, they have substantial centrality in the network. We then discuss the consequences of these results for the social behaviour of humans and predict the changes that could arise due to a varying tolerance for lies in society. © 2015 The Author(s).

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

Quantifying non-ergodic dynamics of force-free granular gases.

PubMed

Bodrova, Anna; Chechkin, Aleksei V; Cherstvy, Andrey G; Metzler, Ralf

2015-09-14

Brownian motion is ergodic in the Boltzmann-Khinchin sense that long time averages of physical observables such as the mean squared displacement provide the same information as the corresponding ensemble average, even at out-of-equilibrium conditions. This property is the fundamental prerequisite for single particle tracking and its analysis in simple liquids. We study analytically and by event-driven molecular dynamics simulations the dynamics of force-free cooling granular gases and reveal a violation of ergodicity in this Boltzmann-Khinchin sense as well as distinct ageing of the system. Such granular gases comprise materials such as dilute gases of stones, sand, various types of powders, or large molecules, and their mixtures are ubiquitous in Nature and technology, in particular in Space. We treat-depending on the physical-chemical properties of the inter-particle interaction upon their pair collisions-both a constant and a velocity-dependent (viscoelastic) restitution coefficient ε. Moreover we compare the granular gas dynamics with an effective single particle stochastic model based on an underdamped Langevin equation with time dependent diffusivity. We find that both models share the same behaviour of the ensemble mean squared displacement (MSD) and the velocity correlations in the limit of weak dissipation. Qualitatively, the reported non-ergodic behaviour is generic for granular gases with any realistic dependence of ε on the impact velocity of particles.

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.

Study on Human-structure Dynamic Interaction in Civil Engineering

NASA Astrophysics Data System (ADS)

Gao, Feng; Cao, Li Lin; Li, Xing Hua

2018-06-01

The research of human-structure dynamic interaction are reviewed. Firstly, the influence of the crowd load on structural dynamic characteristics is introduced and the advantages and disadvantages of different crowd load models are analyzed. Then, discussing the influence of structural vibration on the human-induced load, especially the influence of different stiffness structures on the crowd load. Finally, questions about human-structure interaction that require further study are presented.

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

X-ray computed tomography uncovers root-root interactions: quantifying spatial relationships between interacting root systems in three dimensions.

PubMed

Paya, Alexander M; Silverberg, Jesse L; Padgett, Jennifer; Bauerle, Taryn L

2015-01-01

Research in the field of plant biology has recently demonstrated that inter- and intra-specific interactions belowground can dramatically alter root growth. Our aim was to answer questions related to the effect of inter- vs. intra-specific interactions on the growth and utilization of undisturbed space by fine roots within three dimensions (3D) using micro X-ray computed tomography. To achieve this, Populus tremuloides (quaking aspen) and Picea mariana (black spruce) seedlings were planted into containers as either solitary individuals, or inter-/intra-specific pairs, allowed to grow for 2 months, and 3D metrics developed in order to quantify their use of belowground space. In both aspen and spruce, inter-specific root interactions produced a shift in the vertical distribution of the root system volume, and deepened the average position of root tips when compared to intra-specifically growing seedlings. Inter-specific interactions also increased the minimum distance between root tips belonging to the same root system. There was no effect of belowground interactions on the radial distribution of roots, or the directionality of lateral root growth for either species. In conclusion, we found that significant differences were observed more often when comparing controls (solitary individuals) and paired seedlings (inter- or intra-specific), than when comparing inter- and intra-specifically growing seedlings. This would indicate that competition between neighboring seedlings was more responsible for shifting fine root growth in both species than was neighbor identity. However, significant inter- vs. intra-specific differences were observed, which further emphasizes the importance of biological interactions in competition studies.

A high-throughput assay for quantifying appetite and digestive dynamics.

PubMed

Jordi, Josua; Guggiana-Nilo, Drago; Soucy, Edward; Song, Erin Yue; Lei Wee, Caroline; Engert, Florian

2015-08-15

Food intake and digestion are vital functions, and their dysregulation is fundamental for many human diseases. Current methods do not support their dynamic quantification on large scales in unrestrained vertebrates. Here, we combine an infrared macroscope with fluorescently labeled food to quantify feeding behavior and intestinal nutrient metabolism with high temporal resolution, sensitivity, and throughput in naturally behaving zebrafish larvae. Using this method and rate-based modeling, we demonstrate that zebrafish larvae match nutrient intake to their bodily demand and that larvae adjust their digestion rate, according to the ingested meal size. Such adaptive feedback mechanisms make this model system amenable to identify potential chemical modulators. As proof of concept, we demonstrate that nicotine, l-lysine, ghrelin, and insulin have analogous impact on food intake as in mammals. Consequently, the method presented here will promote large-scale translational research of food intake and digestive function in a naturally behaving vertebrate. Copyright © 2015 the American Physiological Society.

A high-throughput assay for quantifying appetite and digestive dynamics

PubMed Central

Guggiana-Nilo, Drago; Soucy, Edward; Song, Erin Yue; Lei Wee, Caroline; Engert, Florian

2015-01-01

Food intake and digestion are vital functions, and their dysregulation is fundamental for many human diseases. Current methods do not support their dynamic quantification on large scales in unrestrained vertebrates. Here, we combine an infrared macroscope with fluorescently labeled food to quantify feeding behavior and intestinal nutrient metabolism with high temporal resolution, sensitivity, and throughput in naturally behaving zebrafish larvae. Using this method and rate-based modeling, we demonstrate that zebrafish larvae match nutrient intake to their bodily demand and that larvae adjust their digestion rate, according to the ingested meal size. Such adaptive feedback mechanisms make this model system amenable to identify potential chemical modulators. As proof of concept, we demonstrate that nicotine, l-lysine, ghrelin, and insulin have analogous impact on food intake as in mammals. Consequently, the method presented here will promote large-scale translational research of food intake and digestive function in a naturally behaving vertebrate. PMID:26108871

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.

Quantifying the size-resolved dynamics of indoor bioaerosol transport and control.

PubMed

Kunkel, S A; Azimi, P; Zhao, H; Stark, B C; Stephens, B

2017-09-01

Understanding the bioaerosol dynamics of droplets and droplet nuclei emitted during respiratory activities is important for understanding how infectious diseases are transmitted and potentially controlled. To this end, we conducted experiments to quantify the size-resolved dynamics of indoor bioaerosol transport and control in an unoccupied apartment unit operating under four different HVAC particle filtration conditions. Two model organisms (Escherichia coli K12 and bacteriophage T4) were aerosolized under alternating low and high flow rates to roughly represent constant breathing and periodic coughing. Size-resolved aerosol sampling and settle plate swabbing were conducted in multiple locations. Samples were analyzed by DNA extraction and quantitative polymerase chain reaction (qPCR). DNA from both organisms was detected during all test conditions in all air samples up to 7 m away from the source, but decreased in magnitude with the distance from the source. A greater fraction of T4 DNA was recovered from the aerosol size fractions smaller than 1 μm than E. coli K12 at all air sampling locations. Higher efficiency HVAC filtration also reduced the amount of DNA recovered in air samples and on settle plates located 3-7 m from the source. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Effective interactions and dynamics of small passive particles in an active bacterial medium

NASA Astrophysics Data System (ADS)

Semeraro, Enrico F.; Devos, Juliette M.; Narayanan, Theyencheri

2018-05-01

This article presents an investigation of the interparticle interactions and dynamics of submicron silica colloids suspended in a bath of motile Escherichia coli bacteria. The colloidal microstructure and dynamics were probed by ultra-small-angle x-ray scattering and multi-speckles x-ray photon correlation spectroscopy, respectively. Both static and hydrodynamic interactions were obtained for different colloid volume fractions and bacteria concentrations as well as when the interparticle interaction potential was modified by the motility buffer. Results suggest that motile bacteria reduce the effective attractive interactions between passive colloids and enhance their dynamics at high colloid volume fractions. The enhanced dynamics under different static interparticle interactions can be rationalized in terms of an effective viscosity of the medium and unified by means of an empirical effective temperature of the system. While the influence of swimming bacteria on the colloid dynamics is significantly lower for small particles, the role of motility buffer on the static and dynamic interactions becomes more pronounced.

Dark soliton dynamics and interactions in continuous-wave-induced lattices.

PubMed

Tsopelas, Ilias; Kominis, Yannis; Hizanidis, Kyriakos

2007-10-01

The dynamics of dark spatial soliton beams and their interaction under the presence of a continuous wave (CW), which dynamically induces a photonic lattice, are investigated. It is shown that appropriate selection of the characteristic parameters of the CW result in controllable steering of a single soliton as well as controllable interaction between two solitons. Depending on the CW parameters, the soliton angle of propagation can be changed drastically, while two-soliton interaction can be either enhanced or reduced, suggesting a reconfigurable soliton control mechanism. Our analytical approach, based on the variational perturbation method, provides a dynamical system for the dark soliton evolution parameters. Analytical results are shown in good agreement with direct numerical simulations.

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

Diet-Dependent Modular Dynamic Interactions of the Equine Cecal Microbiota

PubMed Central

Kristoffersen, Camilla; Jensen, Rasmus B.; Avershina, Ekaterina; Austbø, Dag; Tauson, Anne-Helene; Rudi, Knut

2016-01-01

Knowledge on dynamic interactions in microbiota is pivotal for understanding the role of bacteria in the gut. We herein present comprehensive dynamic models of the horse cecal microbiota, which include short-chained fatty acids, carbohydrate metabolic networks, and taxonomy. Dynamic models were derived from time-series data in a crossover experiment in which four cecum-cannulated horses were fed a starch-rich diet of hay supplemented with barley (starch intake 2 g kg−1 body weight per day) and a fiber-rich diet of only hay. Cecal contents were sampled via the cannula each h for 24 h for both diets. We observed marked differences in the microbial dynamic interaction patterns for Fibrobacter succinogenes, Lachnospiraceae, Streptococcus, Treponema, Anaerostipes, and Anaerovibrio between the two diet groups. Fluctuations and microbiota interactions were the most pronounced for the starch rich diet, with Streptococcus spp. and Anaerovibrio spp. showing the largest fluctuations. Shotgun metagenome sequencing revealed that diet differences may be explained by modular switches in metabolic cross-feeding between microbial consortia in which fermentation is linked to sugar alcohols and amino sugars for the starch-rich diet and monosaccharides for the fiber-rich diet. In conclusion, diet may not only affect the composition of the cecal microbiota, but also dynamic interactions and metabolic cross-feeding. PMID:27773914

Diet-Dependent Modular Dynamic Interactions of the Equine Cecal Microbiota.

PubMed

Kristoffersen, Camilla; Jensen, Rasmus B; Avershina, Ekaterina; Austbø, Dag; Tauson, Anne-Helene; Rudi, Knut

2016-12-23

Knowledge on dynamic interactions in microbiota is pivotal for understanding the role of bacteria in the gut. We herein present comprehensive dynamic models of the horse cecal microbiota, which include short-chained fatty acids, carbohydrate metabolic networks, and taxonomy. Dynamic models were derived from time-series data in a crossover experiment in which four cecum-cannulated horses were fed a starch-rich diet of hay supplemented with barley (starch intake 2 g kg -1 body weight per day) and a fiber-rich diet of only hay. Cecal contents were sampled via the cannula each h for 24 h for both diets. We observed marked differences in the microbial dynamic interaction patterns for Fibrobacter succinogenes, Lachnospiraceae, Streptococcus, Treponema, Anaerostipes, and Anaerovibrio between the two diet groups. Fluctuations and microbiota interactions were the most pronounced for the starch rich diet, with Streptococcus spp. and Anaerovibrio spp. showing the largest fluctuations. Shotgun metagenome sequencing revealed that diet differences may be explained by modular switches in metabolic cross-feeding between microbial consortia in which fermentation is linked to sugar alcohols and amino sugars for the starch-rich diet and monosaccharides for the fiber-rich diet. In conclusion, diet may not only affect the composition of the cecal microbiota, but also dynamic interactions and metabolic cross-feeding.

Interaction of DNA bases with silver nanoparticles: assembly quantified through SPRS and SERS.

PubMed

Basu, Soumen; Jana, Subhra; Pande, Surojit; Pal, Tarasankar

2008-05-15

Colloidal silver nanoparticles were prepared by reducing silver nitrate with sodium borohydride. The synthesized silver particles show an intense surface plasmon band in the visible region. The work reported here describes the interaction between nanoscale silver particles and various DNA bases (adenine, guanine, cytosine, and thymine), which are used as molecular linkers because of their biological significance. In colloidal solutions, the color of silver nanoparticles may range from red to purple to orange to blue, depending on the degree of aggregation as well as the orientation of the individual particles within the aggregates. Transmission electron microscopy (TEM), X-ray diffraction (XRD), and absorption spectroscopy were used to characterize the assemblies. DNA base-induced differential silver nanoparticle aggregation was quantified from the peak separation (relates to color) of surface plasmon resonance spectroscopy (SPRS) and the signal intensity of surface-enhanced Raman scattering (SERS), which rationalize the extent of silver-nucleobase interactions.

Multimodel inference to quantify the relative importance of abiotic factors in the population dynamics of marine zooplankton

NASA Astrophysics Data System (ADS)

Everaert, Gert; Deschutter, Yana; De Troch, Marleen; Janssen, Colin R.; De Schamphelaere, Karel

2018-05-01

The effect of multiple stressors on marine ecosystems remains poorly understood and most of the knowledge available is related to phytoplankton. To partly address this knowledge gap, we tested if combining multimodel inference with generalized additive modelling could quantify the relative contribution of environmental variables on the population dynamics of a zooplankton species in the Belgian part of the North Sea. Hence, we have quantified the relative contribution of oceanographic variables (e.g. water temperature, salinity, nutrient concentrations, and chlorophyll a concentrations) and anthropogenic chemicals (i.e. polychlorinated biphenyls) to the density of Acartia clausi. We found that models with water temperature and chlorophyll a concentration explained ca. 73% of the population density of the marine copepod. Multimodel inference in combination with regression-based models are a generic way to disentangle and quantify multiple stressor-induced changes in marine ecosystems. Future-oriented simulations of copepod densities suggested increased copepod densities under predicted environmental changes.

Vortex-Surface Interactions: Vortex Dynamics and Instabilities

DTIC Science & Technology

2015-10-16

31 May 2015 4. TITLE AND SUBTITLE VORTEX -SURFACE INTERACTIONS: VORTEX DYNAMICS AND INSTABILITIES Sa. CONTRACT NUMBER Sb. GRANT NUMBER N00014-12...new natural instabilities coming from vortex - vortex or vortex -surface interactions, but also ultimately the possibility to control these flows...design of vortex generators to modify surface pressures. We find a short wave instability of the secondary vortices that are created by the

Quantifying the impacts of vegetation changes on catchment storage-discharge dynamics using paired-catchment data

NASA Astrophysics Data System (ADS)

Cheng, Lei; Zhang, Lu; Chiew, Francis H. S.; Canadell, Josep G.; Zhao, Fangfang; Wang, Ying-Ping; Hu, Xianqun; Lin, Kairong

2017-07-01

It is widely recognized that vegetation changes can significantly affect the local water availability. Methods have been developed to predict the effects of vegetation change on water yield or total streamflow. However, it is still a challenge to predict changes in base flow following vegetation change due to limited understanding of catchment storage-discharge dynamics. In this study, the power law relationship for describing catchment storage-discharge dynamics is reformulated to quantify the changes in storage-discharge relationship resulting from vegetation changes using streamflow data from six paired-catchment experiments, of which two are deforestation catchments and four are afforestation catchments. Streamflow observations from the paired-catchment experiments clearly demonstrate that vegetation changes have led to significant changes in catchment storage-discharge relationships, accounting for about 83-128% of the changes in groundwater discharge in the treated catchments. Deforestation has led to increases in groundwater discharge (or base flow) but afforestation has resulted in decreases in groundwater discharge. Further analysis shows that the contribution of changes in groundwater discharge to the total changes in streamflow varies greatly among experimental catchments ranging from 12% to 80% with a mean of 38 ± 22% (μ ± σ). This study proposed a new method to quantify the effects of vegetation changes on groundwater discharge from catchment storage and will improve our predictability about the impacts of vegetation changes on catchment water yields.

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

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

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

Quantifying nonergodicity in nonautonomous dissipative dynamical systems: An application to climate change

NASA Astrophysics Data System (ADS)

Drótos, Gábor; Bódai, Tamás; Tél, Tamás

2016-08-01

In nonautonomous dynamical systems, like in climate dynamics, an ensemble of trajectories initiated in the remote past defines a unique probability distribution, the natural measure of a snapshot attractor, for any instant of time, but this distribution typically changes in time. In cases with an aperiodic driving, temporal averages taken along a single trajectory would differ from the corresponding ensemble averages even in the infinite-time limit: ergodicity does not hold. It is worth considering this difference, which we call the nonergodic mismatch, by taking time windows of finite length for temporal averaging. We point out that the probability distribution of the nonergodic mismatch is qualitatively different in ergodic and nonergodic cases: its average is zero and typically nonzero, respectively. A main conclusion is that the difference of the average from zero, which we call the bias, is a useful measure of nonergodicity, for any window length. In contrast, the standard deviation of the nonergodic mismatch, which characterizes the spread between different realizations, exhibits a power-law decrease with increasing window length in both ergodic and nonergodic cases, and this implies that temporal and ensemble averages differ in dynamical systems with finite window lengths. It is the average modulus of the nonergodic mismatch, which we call the ergodicity deficit, that represents the expected deviation from fulfilling the equality of temporal and ensemble averages. As an important finding, we demonstrate that the ergodicity deficit cannot be reduced arbitrarily in nonergodic systems. We illustrate via a conceptual climate model that the nonergodic framework may be useful in Earth system dynamics, within which we propose the measure of nonergodicity, i.e., the bias, as an order-parameter-like quantifier of climate change.

Man/Machine Interaction Dynamics And Performance (MMIDAP) capability

NASA Technical Reports Server (NTRS)

Frisch, Harold P.

1991-01-01

The creation of an ability to study interaction dynamics between a machine and its human operator can be approached from a myriad of directions. The Man/Machine Interaction Dynamics and Performance (MMIDAP) project seeks to create an ability to study the consequences of machine design alternatives relative to the performance of both machine and operator. The class of machines to which this study is directed includes those that require the intelligent physical exertions of a human operator. While Goddard's Flight Telerobotic's program was expected to be a major user, basic engineering design and biomedical applications reach far beyond telerobotics. Ongoing efforts are outlined of the GSFC and its University and small business collaborators to integrate both human performance and musculoskeletal data bases with analysis capabilities necessary to enable the study of dynamic actions, reactions, and performance of coupled machine/operator systems.

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.

Control dynamics of interaction quenched ultracold bosons in periodically driven lattices

NASA Astrophysics Data System (ADS)

Mistakidis, Simeon; Schmelcher, Peter; Group of Fundamental Processes in Quantum Physics Team

2016-05-01

The out-of-equilibrium dynamics of ultracold bosons following an interaction quench upon a periodically driven optical lattice is investigated. It is shown that an interaction quench triggers the inter-well tunneling dynamics, while for the intra-well dynamics breathing and cradle-like processes can be generated. In particular, the occurrence of a resonance between the cradle and tunneling modes is revealed. On the other hand, the employed periodic driving enforces the bosons in the mirror wells to oscillate out-of-phase and to exhibit a dipole mode, while in the central well the cloud experiences a breathing mode. The dynamical behaviour of the system is investigated with respect to the driving frequency revealing a resonant behaviour of the intra-well dynamics. To drive the system in a highly non-equilibrium state an interaction quench upon the driving is performed giving rise to admixtures of excitations in the outer wells, an enhanced breathing in the center and an amplification of the tunneling dynamics. As a result of the quench the system experiences multiple resonances between the inter- and intra-well dynamics at different quench amplitudes. Deutsche Forschungsgemeinschaft, SFB 925 ``Light induced dynamics and control of correlated quantum systems''.

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

Quantifying interactions between accommodation and vergence in a binocularly normal population.

PubMed

Sweeney, Laura E; Seidel, Dirk; Day, Mhairi; Gray, Lyle S

2014-12-01

Stimulation of the accommodation system results in a response in the vergence system via accommodative vergence cross-link interactions, and stimulation of the vergence system results in an accommodation response via vergence accommodation cross-link interactions. Cross-link interactions are necessary in order to ensure simultaneous responses in the accommodation and vergence systems. The crosslink interactions are represented most comprehensively by the response AC/A (accommodative vergence) and CA/C (vergence accommodation) ratios, although the stimulus AC/A ratio is measured clinically, and the stimulus CA/C ratio is seldom measured in clinical practice. The present study aims to quantify both stimulus and response AC/A and CA/C ratios in a binocularly normal population, and determine the relationship between them. 25 Subjects (mean ± SD age 21.0 ± 1.9 years) were recruited from the university population. A significant linear relationship was found between the stimulus and response ratios, for both AC/A (r² = 0.96, p < 0.001) and CA/C ratios (r² = 0.40, p < 0.05). Good agreement was found between the stimulus and response AC/A ratios (95% CI -0.06 to 0.24 MA/D). Stimulus and response CA/C ratios are linearly related. Stimulus CA/C ratios were higher than response ratios at low values, and lower than response ratios at high values (95% CI -0.46 to 0.42 D/MA). Agreement between stimulus and response CA/C ratios is poorer than that found for AC/A ratios due to increased variability in vergence responses when viewing the Gaussian blurred target. This study has shown that more work is needed to refine the methodology of CA/C ratio measurement.

The Dynamics of Interacting Swarms

DTIC Science & Technology

2018-04-04

Unlimited 16 Ira Schwartzt (202) 404-8359 Swarms are self-organized dynamical coupled agents which evolve from simple rules of communication. They are ...when delay is introduced to the communicating agents. One of our major findings is that interacting swarms are far less likely to flock cohesively if...they are coupled with delay. In addition, parameter ranges based on coupling strength, incidence angle of collision, and delay change dramatically

Interacting dark energy: Dynamical system analysis

NASA Astrophysics Data System (ADS)

Golchin, Hanif; Jamali, Sara; Ebrahimi, Esmaeil

We investigate the impacts of interaction between dark matter (DM) and dark energy (DE) in the context of two DE models, holographic (HDE) and ghost dark energy (GDE). In fact, using the dynamical system analysis, we obtain the cosmological consequence of several interactions, considering all relevant component of universe, i.e. matter (dark and luminous), radiation and DE. Studying the phase space for all interactions in detail, we show the existence of unstable matter-dominated and stable DE-dominated phases. We also show that linear interactions suffer from the absence of standard radiation-dominated epoch. Interestingly, this failure resolved by adding the nonlinear interactions to the models. We find an upper bound for the value of the coupling constant of the interaction between DM and DE as b < 0.57in the case of holographic model, and b < 0.61 in the case of GDE model, to result in a cosmological viable matter-dominated epoch. More specifically, this bound is vital to satisfy instability and deceleration of matter-dominated epoch.

Dynamics of Entangled Polymers: Role of Attractive Interactions

NASA Astrophysics Data System (ADS)

Grest, Gary S.; Koski, Jason

The coupled dynamics of entangled polymers, which span broad time and length scales, govern their unique viscoelastic properties. Numerical simulations of highly coarse grained models are often used to follow chain mobility from the intermediate Rouse and reptation regimes to the late time diffusive regime. In these models, purely repulsive interactions between monomers are typically used because it is less computationally expensive than including attractive interactions. The effect of including the attractive interaction on the local and macroscopic properties of entangled polymer melts is explored over a wide temperature range using large scale molecular dynamics simulations. Attractive interactions are shown to have little effect on the local packing for all temperatures T and chain mobility for T higher than about twice the glass transition Tg. For lower T, the attractive interactions play a significant role, reducing the chain mobility compared to the repulsive case. As T approaches Tg breakdown of time-temperature superposition for the stress autocorrelation function is observed. Sandia National Labs is a multiprogram laboratory managed and operated by Sandia Corporation, a Lockheed-Martin Company, for the U.S. Dept of Energy under Contract No. DEAC04-94AL85000.

Anomalous dynamical phase in quantum spin chains with long-range interactions

NASA Astrophysics Data System (ADS)

Homrighausen, Ingo; Abeling, Nils O.; Zauner-Stauber, Valentin; Halimeh, Jad C.

2017-09-01

The existence or absence of nonanalytic cusps in the Loschmidt-echo return rate is traditionally employed to distinguish between a regular dynamical phase (regular cusps) and a trivial phase (no cusps) in quantum spin chains after a global quench. However, numerical evidence in a recent study (J. C. Halimeh and V. Zauner-Stauber, arXiv:1610.02019) suggests that instead of the trivial phase, a distinct anomalous dynamical phase characterized by a novel type of nonanalytic cusps occurs in the one-dimensional transverse-field Ising model when interactions are sufficiently long range. Using an analytic semiclassical approach and exact diagonalization, we show that this anomalous phase also arises in the fully connected case of infinite-range interactions, and we discuss its defining signature. Our results show that the transition from the regular to the anomalous dynamical phase coincides with Z2-symmetry breaking in the infinite-time limit, thereby showing a connection between two different concepts of dynamical criticality. Our work further expands the dynamical phase diagram of long-range interacting quantum spin chains, and can be tested experimentally in ion-trap setups and ultracold atoms in optical cavities, where interactions are inherently long range.

Dynamics of the diffusive DM-DE interaction – Dynamical system approach

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

Haba, Zbigniew; Stachowski, Aleksander; Szydłowski, Marek, E-mail: zhab@ift.uni.wroc.pl, E-mail: aleksander.stachowski@uj.edu.pl, E-mail: marek.szydlowski@uj.edu.pl

We discuss dynamics of a model of an energy transfer between dark energy (DE) and dark matter (DM) . The energy transfer is determined by a non-conservation law resulting from a diffusion of dark matter in an environment of dark energy. The relativistic invariance defines the diffusion in a unique way. The system can contain baryonic matter and radiation which do not interact with the dark sector. We treat the Friedman equation and the conservation laws as a closed dynamical system. The dynamics of the model is examined using the dynamical systems methods for demonstration how solutions depend on initialmore » conditions. We also fit the model parameters using astronomical observation: SNIa, H ( z ), BAO and Alcock-Paczynski test. We show that the model with diffuse DM-DE is consistent with the data.« less

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.

Influence of the number of topologically interacting neighbors on swarm dynamics

PubMed Central

Shang, Yilun; Bouffanais, Roland

2014-01-01

Recent empirical and theoretical works on collective behaviors based on a topological interaction are beginning to offer some explanations as for the physical reasons behind the selection of a particular number of nearest neighbors locally affecting each individual's dynamics. Recently, flocking starlings have been shown to topologically interact with a very specific number of neighbors, between six to eight, while metric-free interactions were found to govern human crowd dynamics. Here, we use network- and graph-theoretic approaches combined with a dynamical model of locally interacting self-propelled particles to study how the consensus reaching process and its dynamics are influenced by the number k of topological neighbors. Specifically, we prove exactly that, in the absence of noise, consensus is always attained with a speed to consensus strictly increasing with k. The analysis of both speed and time to consensus reveals that, irrespective of the swarm size, a value of k ~ 10 speeds up the rate of convergence to consensus to levels close to the one of the optimal all-to-all interaction signaling. Furthermore, this effect is found to be more pronounced in the presence of environmental noise. PMID:24567077

Interaction dynamics of multiple mobile robots with simple navigation strategies

NASA Technical Reports Server (NTRS)

Wang, P. K. C.

1989-01-01

The global dynamic behavior of multiple interacting autonomous mobile robots with simple navigation strategies is studied. Here, the effective spatial domain of each robot is taken to be a closed ball about its mass center. It is assumed that each robot has a specified cone of visibility such that interaction with other robots takes place only when they enter its visibility cone. Based on a particle model for the robots, various simple homing and collision-avoidance navigation strategies are derived. Then, an analysis of the dynamical behavior of the interacting robots in unbounded spatial domains is made. The article concludes with the results of computer simulations studies of two or more interacting robots.

Aspergillus fumigatus morphology and dynamic host interactions.

PubMed

van de Veerdonk, Frank L; Gresnigt, Mark S; Romani, Luigina; Netea, Mihai G; Latgé, Jean-Paul

2017-11-01

Aspergillus fumigatus is an environmental filamentous fungus that can cause life-threatening disease in immunocompromised individuals. The interactions between A. fumigatus and the host environment are dynamic and complex. The host immune system needs to recognize the distinct morphological forms of A. fumigatus to control fungal growth and prevent tissue invasion, whereas the fungus requires nutrients and needs to adapt to the hostile environment by escaping immune recognition and counteracting host responses. Understanding these highly dynamic interactions is necessary to fully understand the pathogenesis of aspergillosis and to facilitate the design of new therapeutics to overcome the morbidity and mortality caused by A. fumigatus. In this Review, we describe how A. fumigatus adapts to environmental change, the mechanisms of host defence, and our current knowledge of the interplay between the host immune response and the fungus.

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

Interactive molecular dynamics

NASA Astrophysics Data System (ADS)

Schroeder, Daniel V.

2015-03-01

Physics students now have access to interactive molecular dynamics simulations that can model and animate the motions of hundreds of particles, such as noble gas atoms, that attract each other weakly at short distances but repel strongly when pressed together. Using these simulations, students can develop an understanding of forces and motions at the molecular scale, nonideal fluids, phases of matter, thermal equilibrium, nonequilibrium states, the Boltzmann distribution, the arrow of time, and much more. This article summarizes the basic features and capabilities of such a simulation, presents a variety of student exercises using it at the introductory and intermediate levels, and describes some enhancements that can further extend its uses. A working simulation code, in html5 and javascript for running within any modern Web browser, is provided as an online supplement.

Social Dynamics in Web Page through Inter-Agent Interaction

NASA Astrophysics Data System (ADS)

Takeuchi, Yugo; Katagiri, Yasuhiro

Social persuasion abounds in human-human interactions. Attitudes and behaviors of people are invariably influenced by the attitudes and behaviors of other people as well as our social roles/relationships toward them. In the pedagogic scene, the relationship between teacher and learner produces one of the most typical interactions, in which the teacher makes the learner spontaneously study what he/she teaches. This study is an attempt to elucidate the nature and effectiveness of social persuasion in human-computer interaction environments. We focus on the social dynamics of multi-party interactions that involve both human-agent and inter-agent interactions. An experiment is conducted in a virtual web-instruction setting employing two types of agents: conductor agents who accompany and guide each learner throughout his/her learning sessions, and domain-expert agents who provide explanations and instructions for each stage of the instructional materials. In this experiment, subjects are assigned two experimental conditions: the authorized condition, in which an agent respectfully interacts with another agent, and the non-authorized condition, in which an agent carelessly interacts with another agent. The results indicate performance improvements in the authorized condition of inter-agent interactions. An analysis is given from the perspective of the transfer of authority from inter-agent to human-agent interactions based on social conformity. We argue for pedagogic advantages of social dynamics created by multiple animated character agents.

Dynamic interaction between vehicles and infrastructure experiment (DIVINE) : policy implications

DOT National Transportation Integrated Search

1998-01-01

The Dynamic Interaction between Vehicles and Infrastructure Experiment (DIVINE) Project provided scientific evidence of the dynamic effects of heavy vehicles and their suspension systems on pavements and bridges. These conclusions are detailed in the...

Dynamic interaction between vehicles and infrastructure experiment (DIVINE) : technical report

DOT National Transportation Integrated Search

1998-10-27

The Dynamic Interaction between Vehicles and Infrastructure Experiment (DIVINE) Project provides scientific evidence of the dynamic effects of heavy vehicles and their suspension systems on pavements and bridges in support of transport policy decisio...

Electron-phonon interaction within classical molecular dynamics

DOE PAGES

Tamm, A.; Samolyuk, G.; Correa, A. A.; ...

2016-07-14

Here, we present a model for nonadiabatic classical molecular dynamics simulations that captures with high accuracy the wave-vector q dependence of the phonon lifetimes, in agreement with quantum mechanics calculations. It is based on a local view of the e-ph interaction where individual atom dynamics couples to electrons via a damping term that is obtained as the low-velocity limit of the stopping power of a moving ion in a host. The model is parameter free, as its components are derived from ab initio-type calculations, is readily extended to the case of alloys, and is adequate for large-scale molecular dynamics computermore » simulations. We also show how this model removes some oversimplifications of the traditional ionic damped dynamics commonly used to describe situations beyond the Born-Oppenheimer approximation.« less

Structure and Dynamics of Interacting Nanoparticles in Semidilute Polymer Solutions

DOE PAGES

Pollng-Skutvik, Ryan; Mongcopa, Katrina Irene S.; Faraone, Antonio; ...

2016-08-17

We investigate the structure and dynamics of silica nanoparticles and polymer chains in semidilute solutions of high molecular weight polystyrene in 2-butanone to determine the effect of long-range interparticle interactions on the coupling between particle and polymer dynamics. Particles at concentrations of 1–10 wt % are well dispersed in the semidilute polymer solutions and exhibit long-range electrostatic repulsions between particles. Because the particles are comparably sized to the radius of gyration of the polymer, the particle dynamics is predicted to couple to that of the polymer. We verify that the polymer structure and dynamics are not significantly affected by themore » particles, indicating that the particle–polymer coupling does not change with increasing particle loading. We find that the coupling between the dynamics of comparably sized particles and polymer results in subdiffusive particle dynamics, as expected. Over the interparticle distance, however, the particle dynamics is hindered and not fully described by the relaxation of the surrounding polymer chains. Instead, the particle dynamics is inversely related to the structure factor, suggesting that physical particle–polymer coupling on short length scales and interparticle interactions on long length scales both present energetic barriers to particle motion that lead to subdiffusive dynamics and de Gennes narrowing, respectively.« less

Cross-Modulated Amplitudes and Frequencies Characterize Interacting Components in Complex Systems

NASA Astrophysics Data System (ADS)

Gans, Fabian; Schumann, Aicko Y.; Kantelhardt, Jan W.; Penzel, Thomas; Fietze, Ingo

2009-03-01

The dynamics of complex systems is characterized by oscillatory components on many time scales. To study the interactions between these components we analyze the cross modulation of their instantaneous amplitudes and frequencies, separating synchronous and antisynchronous modulation. We apply our novel technique to brain-wave oscillations in the human electroencephalogram and show that interactions between the α wave and the δ or β wave oscillators as well as spatial interactions can be quantified and related with physiological conditions (e.g., sleep stages). Our approach overcomes the limitation to oscillations with similar frequencies and enables us to quantify directly nonlinear effects such as positive or negative frequency modulation.

Interactions Dominate the Dynamics of Visual Cognition

ERIC Educational Resources Information Center

Stephen, Damian G.; Mirman, Daniel

2010-01-01

Many cognitive theories have described behavior as the summation of independent contributions from separate components. Contrasting views have emphasized the importance of multiplicative interactions and emergent structure. We describe a statistical approach to distinguishing additive and multiplicative processes and apply it to the dynamics of…

Direction of Amygdala-Neocortex Interaction During Dynamic Facial Expression Processing.

PubMed

Sato, Wataru; Kochiyama, Takanori; Uono, Shota; Yoshikawa, Sakiko; Toichi, Motomi

2017-03-01

Dynamic facial expressions of emotion strongly elicit multifaceted emotional, perceptual, cognitive, and motor responses. Neuroimaging studies revealed that some subcortical (e.g., amygdala) and neocortical (e.g., superior temporal sulcus and inferior frontal gyrus) brain regions and their functional interaction were involved in processing dynamic facial expressions. However, the direction of the functional interaction between the amygdala and the neocortex remains unknown. To investigate this issue, we re-analyzed functional magnetic resonance imaging (fMRI) data from 2 studies and magnetoencephalography (MEG) data from 1 study. First, a psychophysiological interaction analysis of the fMRI data confirmed the functional interaction between the amygdala and neocortical regions. Then, dynamic causal modeling analysis was used to compare models with forward, backward, or bidirectional effective connectivity between the amygdala and neocortical networks in the fMRI and MEG data. The results consistently supported the model of effective connectivity from the amygdala to the neocortex. Further increasing time-window analysis of the MEG demonstrated that this model was valid after 200 ms from the stimulus onset. These data suggest that emotional processing in the amygdala rapidly modulates some neocortical processing, such as perception, recognition, and motor mimicry, when observing dynamic facial expressions of emotion. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Spatial patterns and temporal dynamics of global scale climate-groundwater interactions

NASA Astrophysics Data System (ADS)

Cuthbert, M. O.; Gleeson, T. P.; Moosdorf, N.; Schneider, A. C.; Hartmann, J.; Befus, K. M.; Lehner, B.

2017-12-01

The interactions between groundwater and climate are important to resolve in both space and time as they influence mass and energy transfers at Earth's land surface. Despite the significance of these processes, little is known about the spatio-temporal distribution of such interactions globally, and many large-scale climate, hydrological and land surface models oversimplify groundwater or exclude it completely. In this study we bring together diverse global geomatic data sets to map spatial patterns in the sensitivity and degree of connectedness between the water table and the land surface, and use the output from a global groundwater model to assess the locations where the lateral import or export of groundwater is significant. We also quantify the groundwater response time, the characteristic time for groundwater systems to respond to a change in boundary conditions, and map its distribution globally to assess the likely dynamics of groundwater's interaction with climate. We find that more than half of the global land surface significantly exports or imports groundwater laterally. Nearly 40% of Earth's landmass has water tables that are strongly coupled to topography with water tables shallow enough to enable a bi-directional exchange of moisture with the climate system. However, only a small proportion (around 12%) of such regions have groundwater response times of 100 years or less and have groundwater fluxes that would significantly respond to rapid environmental changes over this timescale. We last explore fundamental relationships between aridity, groundwater response times and groundwater turnover times. Our results have wide ranging implications for understanding and modelling changes in Earth's water and energy balance and for informing robust future water management and security decisions.

Quantified, Interactive Simulation of AMCW ToF Camera Including Multipath Effects

PubMed Central

Lambers, Martin; Kolb, Andreas

2017-01-01

In the last decade, Time-of-Flight (ToF) range cameras have gained increasing popularity in robotics, automotive industry, and home entertainment. Despite technological developments, ToF cameras still suffer from error sources such as multipath interference or motion artifacts. Thus, simulation of ToF cameras, including these artifacts, is important to improve camera and algorithm development. This paper presents a physically-based, interactive simulation technique for amplitude modulated continuous wave (AMCW) ToF cameras, which, among other error sources, includes single bounce indirect multipath interference based on an enhanced image-space approach. The simulation accounts for physical units down to the charge level accumulated in sensor pixels. Furthermore, we present the first quantified comparison for ToF camera simulators. We present bidirectional reference distribution function (BRDF) measurements for selected, purchasable materials in the near-infrared (NIR) range, craft real and synthetic scenes out of these materials and quantitatively compare the range sensor data. PMID:29271888

Quantified, Interactive Simulation of AMCW ToF Camera Including Multipath Effects.

PubMed

Bulczak, David; Lambers, Martin; Kolb, Andreas

2017-12-22

In the last decade, Time-of-Flight (ToF) range cameras have gained increasing popularity in robotics, automotive industry, and home entertainment. Despite technological developments, ToF cameras still suffer from error sources such as multipath interference or motion artifacts. Thus, simulation of ToF cameras, including these artifacts, is important to improve camera and algorithm development. This paper presents a physically-based, interactive simulation technique for amplitude modulated continuous wave (AMCW) ToF cameras, which, among other error sources, includes single bounce indirect multipath interference based on an enhanced image-space approach. The simulation accounts for physical units down to the charge level accumulated in sensor pixels. Furthermore, we present the first quantified comparison for ToF camera simulators. We present bidirectional reference distribution function (BRDF) measurements for selected, purchasable materials in the near-infrared (NIR) range, craft real and synthetic scenes out of these materials and quantitatively compare the range sensor data.

Crowding of Interacting Fluid Particles in Porous Media through Molecular Dynamics: Breakdown of Universality for Soft Interactions.

PubMed

Schnyder, Simon K; Horbach, Jürgen

2018-02-16

Molecular dynamics simulations of interacting soft disks confined in a heterogeneous quenched matrix of soft obstacles show dynamics which is fundamentally different from that of hard disks. The interactions between the disks can enhance transport when their density is increased, as disks cooperatively help each other over the finite energy barriers in the matrix. The system exhibits a transition from a diffusive to a localized state, but the transition is strongly rounded. Effective exponents in the mean-squared displacement can be observed over three decades in time but depend on the density of the disks and do not correspond to asymptotic behavior in the vicinity of a critical point, thus, showing that it is incorrect to relate them to the critical exponents in the Lorentz model scenario. The soft interactions are, therefore, responsible for a breakdown of the universality of the dynamics.

Crowding of Interacting Fluid Particles in Porous Media through Molecular Dynamics: Breakdown of Universality for Soft Interactions

NASA Astrophysics Data System (ADS)

Schnyder, Simon K.; Horbach, Jürgen

2018-02-01

Molecular dynamics simulations of interacting soft disks confined in a heterogeneous quenched matrix of soft obstacles show dynamics which is fundamentally different from that of hard disks. The interactions between the disks can enhance transport when their density is increased, as disks cooperatively help each other over the finite energy barriers in the matrix. The system exhibits a transition from a diffusive to a localized state, but the transition is strongly rounded. Effective exponents in the mean-squared displacement can be observed over three decades in time but depend on the density of the disks and do not correspond to asymptotic behavior in the vicinity of a critical point, thus, showing that it is incorrect to relate them to the critical exponents in the Lorentz model scenario. The soft interactions are, therefore, responsible for a breakdown of the universality of the dynamics.

[Brownian dynamics simulations of protein-protein interactions in photosynthetic electron transport chain].

PubMed

Khruschev, S S; Abaturova, A M; Diakonova, A N; Fedorov, V A; Ustinin, D M; Kovalenko, I B; Riznichenko, G Yu; Rubin, A B

2015-01-01

The application of Brownian dynamics for simulation of transient protein-protein interactions is reviewed. The review focuses on theoretical basics of Brownian dynamics method, its particular implementations, advantages and drawbacks of the method. The outlook for future development of Brownian dynamics-based simulation techniques is discussed. Special attention is given to analysis of Brownian dynamics trajectories. The second part of the review is dedicated to the role of Brownian dynamics simulations in studying photosynthetic electron transport. Interactions of mobile electron carriers (plastocyanin, cytochrome c6, and ferredoxin) with their reaction partners (cytochrome b6f complex, photosystem I, ferredoxin:NADP-reductase, and hydrogenase) are considered.

Dynamics of Conceptual Change in Small Group Science Interactions.

ERIC Educational Resources Information Center

Fellows, Nancy J.

This paper documents the dynamics of the social interactions within two small groups of sixth grade students as they solved problems and attempted to understand the concepts related to the nature of matter and molecular theory. Similarities and differences of social interactions between the two groups are compared, and interpretations presented…

Mechanisms and dynamics of nuclear lamina-genome interactions.

PubMed

Amendola, Mario; van Steensel, Bas

2014-06-01

The nuclear lamina (NL) interacts with the genomic DNA and is thought to influence chromosome organization and gene expression. Both DNA sequences and histone modifications are important for NL tethering of the genomic DNA. These interactions are dynamic in individual cells and can change during differentiation and development. Evidence is accumulating that the NL contributes to the repression of transcription. Advances in mapping, genome-editing and microscopy techniques are increasing our understanding of the molecular mechanisms involved in NL-genome interactions. Copyright © 2014 Elsevier Ltd. All rights reserved.

An iterative method for hydrodynamic interactions in Brownian dynamics simulations of polymer dynamics

NASA Astrophysics Data System (ADS)

Miao, Linling; Young, Charles D.; Sing, Charles E.

2017-07-01

Brownian Dynamics (BD) simulations are a standard tool for understanding the dynamics of polymers in and out of equilibrium. Quantitative comparison can be made to rheological measurements of dilute polymer solutions, as well as direct visual observations of fluorescently labeled DNA. The primary computational challenge with BD is the expensive calculation of hydrodynamic interactions (HI), which are necessary to capture physically realistic dynamics. The full HI calculation, performed via a Cholesky decomposition every time step, scales with the length of the polymer as O(N3). This limits the calculation to a few hundred simulated particles. A number of approximations in the literature can lower this scaling to O(N2 - N2.25), and explicit solvent methods scale as O(N); however both incur a significant constant per-time step computational cost. Despite this progress, there remains a need for new or alternative methods of calculating hydrodynamic interactions; large polymer chains or semidilute polymer solutions remain computationally expensive. In this paper, we introduce an alternative method for calculating approximate hydrodynamic interactions. Our method relies on an iterative scheme to establish self-consistency between a hydrodynamic matrix that is averaged over simulation and the hydrodynamic matrix used to run the simulation. Comparison to standard BD simulation and polymer theory results demonstrates that this method quantitatively captures both equilibrium and steady-state dynamics after only a few iterations. The use of an averaged hydrodynamic matrix allows the computationally expensive Brownian noise calculation to be performed infrequently, so that it is no longer the bottleneck of the simulation calculations. We also investigate limitations of this conformational averaging approach in ring polymers.

Dynamical system analysis for DBI dark energy interacting with dark matter

NASA Astrophysics Data System (ADS)

Mahata, Nilanjana; Chakraborty, Subenoy

2015-01-01

A dynamical system analysis related to Dirac-Born-Infeld (DBI) cosmological model has been investigated in this present work. For spatially flat FRW spacetime, the Einstein field equation for DBI scenario has been used to study the dynamics of DBI dark energy interacting with dark matter. The DBI dark energy model is considered as a scalar field with a nonstandard kinetic energy term. An interaction between the DBI dark energy and dark matter is considered through a phenomenological interaction between DBI scalar field and the dark matter fluid. The field equations are reduced to an autonomous dynamical system by a suitable redefinition of the basic variables. The potential of the DBI scalar field is assumed to be exponential. Finally, critical points are determined, their nature have been analyzed and corresponding cosmological scenario has been discussed.

Dynamical screening of the van der Waals interaction between graphene layers.

PubMed

Dappe, Y J; Bolcatto, P G; Ortega, J; Flores, F

2012-10-24

The interaction between graphene layers is analyzed combining local orbital DFT and second order perturbation theory. For this purpose we use the linear combination of atomic orbitals-orbital occupancy (LCAO-OO) formalism, that allows us to separate the interaction energy as the sum of a weak chemical interaction between graphene layers plus the van der Waals interaction (Dappe et al 2006 Phys. Rev. B 74 205434). In this work, the weak chemical interaction is calculated by means of corrected-LDA calculations using an atomic-like sp(3)d(5) basis set. The van der Waals interaction is calculated by means of second order perturbation theory using an atom-atom interaction approximation and the atomic-like-orbital occupancies. We also analyze the effect of dynamical screening in the van der Waals interaction using a simple model. We find that this dynamical screening reduces by 40% the van der Waals interaction. Taking this effect into account, we obtain a graphene-graphene interaction energy of 70 ± 5 meV/atom in reasonable agreement with the experimental evidence.

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.

Fluid-Solid Interaction and Multiscale Dynamic Processes: Experimental Approach

NASA Astrophysics Data System (ADS)

Arciniega-Ceballos, Alejandra; Spina, Laura; Mendo-Pérez, Gerardo M.; Guzmán-Vázquez, Enrique; Scheu, Bettina; Sánchez-Sesma, Francisco J.; Dingwell, Donald B.

2017-04-01

The speed and the style of a pressure drop in fluid-filled conduits determines the dynamics of multiscale processes and the elastic interaction between the fluid and the confining solid. To observe this dynamics we performed experiments using fluid-filled transparent tubes (15-50 cm long, 2-4 cm diameter and 0.3-1 cm thickness) instrumented with high-dynamic piezoelectric sensors and filmed the evolution of these processes with a high speed camera. We analyzed the response of Newtonian fluids to slow and sudden pressure drops from 3 bar-10 MPa to ambient pressure. We used fluids with viscosities of mafic to intermediate silicate melts of 1 to 1000 Pa s and water. The processes observed are fluid mass expansion, fluid flow, jets, bubbles nucleation, growth, coalescence and collapse, degassing, foam building at the surface and vertical wagging. All these processes (in fine and coarse scales) are triggered by the pressure drop and are sequentially coupled in time while interacting with the solid. During slow decompression, the multiscale processes are recognized occurring within specific pressure intervals, and exhibit a localized distribution along the conduit. In this, degassing predominates near the surface and may present piston-like oscillations. In contrast, during sudden decompression the fluid-flow reaches higher velocities, the dynamics is dominated by a sequence of gas-packet pulses driving jets of the gas-fluid mixture. The evolution of this multiscale phenomenon generates complex non-stationary microseismic signals recorded along the conduit. We discuss distinctive characteristics of these signals depending on the decompression style and compare them with synthetics. These synthetics are obtained numerically under an averaging modeling scheme, that accounted for the stress-strain of the cyclic dynamic interaction between the fluid and the solid wall, assuming an incompressible and viscous fluid that flows while the elastic solid responds oscillating

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.

Visual Design Guidelines for Improving Learning from Dynamic and Interactive Digital Text

ERIC Educational Resources Information Center

Jin, Sung-Hee

2013-01-01

Despite the dynamic and interactive features of digital text, the visual design guidelines for digital text are similar to those for printed text. The purpose of this study was to develop visual design guidelines for improving learning from dynamic and interactive digital text and to validate them by controlled testing. Two structure design…

Dynamics of relaxation to a stationary state for interacting molecular motors

NASA Astrophysics Data System (ADS)

Gomes, Luiza V. F.; Kolomeisky, Anatoly B.

2018-01-01

Motor proteins are active enzymatic molecules that drive a variety of biological processes, including transfer of genetic information, cellular transport, cell motility and muscle contraction. It is known that these biological molecular motors usually perform their cellular tasks by acting collectively, and there are interactions between individual motors that specify the overall collective behavior. One of the fundamental issues related to the collective dynamics of motor proteins is the question if they function at stationary-state conditions. To investigate this problem, we analyze a relaxation to the stationary state for the system of interacting molecular motors. Our approach utilizes a recently developed theoretical framework, which views the collective dynamics of motor proteins as a totally asymmetric simple exclusion process of interacting particles, where interactions are taken into account via a thermodynamically consistent approach. The dynamics of relaxation to the stationary state is analyzed using a domain-wall method that relies on a mean-field description, which takes into account some correlations. It is found that the system quickly relaxes for repulsive interactions, while attractive interactions always slow down reaching the stationary state. It is also predicted that for some range of parameters the fastest relaxation might be achieved for a weak repulsive interaction. Our theoretical predictions are tested with Monte Carlo computer simulations. The implications of our findings for biological systems are briefly discussed.

Quantifying Additive Interactions of the Osmolyte Proline with Individual Functional Groups of Proteins: Comparisons with Urea and Glycine Betaine, Interpretation of m-Values

PubMed Central

Diehl, Roger C.; Guinn, Emily J.; Capp, Michael W.; Tsodikov, Oleg V.; Record, M. Thomas

2013-01-01

To quantify interactions of the osmolyte L-proline with protein functional groups and predict its effects on protein processes, we use vapor pressure osmometry to determine chemical potential derivatives dµ2/dm3 = µ23 quantifying preferential interactions of proline (component 3) with 21 solutes (component 2) selected to display different combinations of aliphatic or aromatic C, amide, carboxylate, phosphate or hydroxyl O, and/or amide or cationic N surface. Solubility data yield µ23 values for 4 less-soluble solutes. Values of µ23 are dissected using an ASA-based analysis to test the hypothesis of additivity and obtain α-values (proline interaction potentials) for these eight surface types and three inorganic ions. Values of µ23 predicted from these α-values agree with experiment, demonstrating additivity. Molecular interpretation of α-values using the solute partitioning model yields partition coefficients (Kp) quantifying the local accumulation or exclusion of proline in the hydration water of each functional group. Interactions of proline with native protein surface and effects of proline on protein unfolding are predicted from α-values and ASA information and compared with experimental data, with results for glycine betaine and urea, and with predictions from transfer free energy analysis. We conclude that proline stabilizes proteins because of its unfavorable interactions with (exclusion from) amide oxygens and aliphatic hydrocarbon surface exposed in unfolding, and that proline is an effective in vivo osmolyte because of the osmolality increase resulting from its unfavorable interactions with anionic (carboxylate and phosphate) and amide oxygens and aliphatic hydrocarbon groups on the surface of cytoplasmic proteins and nucleic acids. PMID:23909383

Crop rotations and poultry litter impact dynamic soil chemical properties and soil biota long-term

USDA-ARS?s Scientific Manuscript database

Dynamic soil physiochemical interactions with conservation agricultural practices and soil biota are largely unknown. Therefore, this study aims to quantify long-term (12-yr) impacts of cover crops, poultry litter, crop rotations, and conservation tillage and their interactions on soil physiochemica...

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.

Low latitude ionospheric TEC responses to dynamical complexity quantifiers during transient events over Nigeria

NASA Astrophysics Data System (ADS)

Ogunsua, Babalola

2018-04-01

In this study, the values of chaoticity and dynamical complexity parameters for some selected storm periods in the year 2011 and 2012 have been computed. This was done using detrended TEC data sets measured from Birnin-Kebbi, Torro and Enugu global positioning system (GPS) receiver stations in Nigeria. It was observed that the significance of difference (SD) values were mostly greater than 1.96 but surprisingly lower than 1.96 in September 29, 2011. The values of the computed SD were also found to be reduced in most cases just after the geomagnetic storm with immediate recovery a day after the main phase of the storm while the values of Lyapunov exponent and Tsallis entropy remains reduced due to the influence of geomagnetic storms. It was also observed that the value of Lyapunov exponent and Tsallis entropy reveals similar variation pattern during storm period in most cases. Also recorded surprisingly were lower values of these dynamical quantifiers during the solar flare event of August 8th and 9th of the year 2011. The possible mechanisms responsible for these observations were further discussed in this work. However, our observations show that the ionospheric effects of some other possible transient events other than geomagnetic storms can also be revealed by the variation of chaoticity and dynamical complexity.

Interactive Dynamic Volume Illumination with Refraction and Caustics.

PubMed

Magnus, Jens G; Bruckner, Stefan

2018-01-01

In recent years, significant progress has been made in developing high-quality interactive methods for realistic volume illumination. However, refraction - despite being an important aspect of light propagation in participating media - has so far only received little attention. In this paper, we present a novel approach for refractive volume illumination including caustics capable of interactive frame rates. By interleaving light and viewing ray propagation, our technique avoids memory-intensive storage of illumination information and does not require any precomputation. It is fully dynamic and all parameters such as light position and transfer function can be modified interactively without a performance penalty.

The human dynamic clamp as a paradigm for social interaction

PubMed Central

Dumas, Guillaume; de Guzman, Gonzalo C.; Tognoli, Emmanuelle; Kelso, J. A. Scott

2014-01-01

Social neuroscience has called for new experimental paradigms aimed toward real-time interactions. A distinctive feature of interactions is mutual information exchange: One member of a pair changes in response to the other while simultaneously producing actions that alter the other. Combining mathematical and neurophysiological methods, we introduce a paradigm called the human dynamic clamp (HDC), to directly manipulate the interaction or coupling between a human and a surrogate constructed to behave like a human. Inspired by the dynamic clamp used so productively in cellular neuroscience, the HDC allows a person to interact in real time with a virtual partner itself driven by well-established models of coordination dynamics. People coordinate hand movements with the visually observed movements of a virtual hand, the parameters of which depend on input from the subject’s own movements. We demonstrate that HDC can be extended to cover a broad repertoire of human behavior, including rhythmic and discrete movements, adaptation to changes of pacing, and behavioral skill learning as specified by a virtual “teacher.” We propose HDC as a general paradigm, best implemented when empirically verified theoretical or mathematical models have been developed in a particular scientific field. The HDC paradigm is powerful because it provides an opportunity to explore parameter ranges and perturbations that are not easily accessible in ordinary human interactions. The HDC not only enables to test the veracity of theoretical models, it also illuminates features that are not always apparent in real-time human social interactions and the brain correlates thereof. PMID:25114256

The human dynamic clamp as a paradigm for social interaction.

PubMed

Dumas, Guillaume; de Guzman, Gonzalo C; Tognoli, Emmanuelle; Kelso, J A Scott

2014-09-02

Social neuroscience has called for new experimental paradigms aimed toward real-time interactions. A distinctive feature of interactions is mutual information exchange: One member of a pair changes in response to the other while simultaneously producing actions that alter the other. Combining mathematical and neurophysiological methods, we introduce a paradigm called the human dynamic clamp (HDC), to directly manipulate the interaction or coupling between a human and a surrogate constructed to behave like a human. Inspired by the dynamic clamp used so productively in cellular neuroscience, the HDC allows a person to interact in real time with a virtual partner itself driven by well-established models of coordination dynamics. People coordinate hand movements with the visually observed movements of a virtual hand, the parameters of which depend on input from the subject's own movements. We demonstrate that HDC can be extended to cover a broad repertoire of human behavior, including rhythmic and discrete movements, adaptation to changes of pacing, and behavioral skill learning as specified by a virtual "teacher." We propose HDC as a general paradigm, best implemented when empirically verified theoretical or mathematical models have been developed in a particular scientific field. The HDC paradigm is powerful because it provides an opportunity to explore parameter ranges and perturbations that are not easily accessible in ordinary human interactions. The HDC not only enables to test the veracity of theoretical models, it also illuminates features that are not always apparent in real-time human social interactions and the brain correlates thereof.

Non-interacting surface solvation and dynamics in protein-protein interactions.

PubMed

Visscher, Koen M; Kastritis, Panagiotis L; Bonvin, Alexandre M J J

2015-03-01

Protein-protein interactions control a plethora of cellular processes, including cell proliferation, differentiation, apoptosis, and signal transduction. Understanding how and why proteins interact will inevitably lead to novel structure-based drug design methods, as well as design of de novo binders with preferred interaction properties. At a structural and molecular level, interface and rim regions are not enough to fully account for the energetics of protein-protein binding, even for simple lock-and-key rigid binders. As we have recently shown, properties of the global surface might also play a role in protein-protein interactions. Here, we report on molecular dynamics simulations performed to understand solvent effects on protein-protein surfaces. We compare properties of the interface, rim, and non-interacting surface regions for five different complexes and their free components. Interface and rim residues become, as expected, less mobile upon complexation. However, non-interacting surface appears more flexible in the complex. Fluctuations of polar residues are always lower compared with charged ones, independent of the protein state. Further, stable water molecules are often observed around polar residues, in contrast to charged ones. Our analysis reveals that (a) upon complexation, the non-interacting surface can have a direct entropic compensation for the lower interface and rim entropy and (b) the mobility of the first hydration layer, which is linked to the stability of the protein-protein complex, is influenced by the local chemical properties of the surface. These findings corroborate previous hypotheses on the role of the hydration layer in shielding protein-protein complexes from unintended protein-protein interactions. © 2014 Wiley Periodicals, Inc.

Metabolic interactions and dynamics in microbial communities

NASA Astrophysics Data System (ADS)

Segre', Daniel

Metabolism, in addition to being the engine of every living cell, plays a major role in the cell-cell and cell-environment relations that shape the dynamics and evolution of microbial communities, e.g. by mediating competition and cross-feeding interactions between different species. Despite the increasing availability of metagenomic sequencing data for numerous microbial ecosystems, fundamental aspects of these communities, such as the unculturability of many isolates, and the conditions necessary for taxonomic or functional stability, are still poorly understood. We are developing mechanistic computational approaches for studying the interactions between different organisms based on the knowledge of their entire metabolic networks. In particular, we have recently built an open source platform for the Computation of Microbial Ecosystems in Time and Space (COMETS), which combines metabolic models with convection-diffusion equations to simulate the spatio-temporal dynamics of metabolism in microbial communities. COMETS has been experimentally tested on small artificial communities, and is scalable to hundreds of species in complex environments. I will discuss recent developments and challenges towards the implementation of models for microbiomes and synthetic microbial communities.

New activity pattern in human interactive dynamics

NASA Astrophysics Data System (ADS)

Formentin, Marco; Lovison, Alberto; Maritan, Amos; Zanzotto, Giovanni

2015-09-01

We investigate the response function of human agents as demonstrated by written correspondence, uncovering a new pattern for how the reactive dynamics of individuals is distributed across the set of each agent’s contacts. In long-term empirical data on email, we find that the set of response times considered separately for the messages to each different correspondent of a given writer, generate a family of heavy-tailed distributions, which have largely the same features for all agents, and whose characteristic times grow exponentially with the rank of each correspondent. We furthermore show that this new behavioral pattern emerges robustly by considering weighted moving averages of the priority-conditioned response-time probabilities generated by a basic prioritization model. Our findings clarify how the range of priorities in the inputs from one’s environment underpin and shape the dynamics of agents embedded in a net of reactive relations. These newly revealed activity patterns might be universal, being present in other general interactive environments, and constrain future models of communication and interaction networks, affecting their architecture and evolution.

Evolutionary dynamics of general group interactions in structured populations

NASA Astrophysics Data System (ADS)

Li, Aming; Broom, Mark; Du, Jinming; Wang, Long

2016-02-01

The evolution of populations is influenced by many factors, and the simple classical models have been developed in a number of important ways. Both population structure and multiplayer interactions have been shown to significantly affect the evolution of important properties, such as the level of cooperation or of aggressive behavior. Here we combine these two key factors and develop the evolutionary dynamics of general group interactions in structured populations represented by regular graphs. The traditional linear and threshold public goods games are adopted as models to address the dynamics. We show that for linear group interactions, population structure can favor the evolution of cooperation compared to the well-mixed case, and we see that the more neighbors there are, the harder it is for cooperators to persist in structured populations. We further show that threshold group interactions could lead to the emergence of cooperation even in well-mixed populations. Here population structure sometimes inhibits cooperation for the threshold public goods game, where depending on the benefit to cost ratio, the outcomes are bistability or a monomorphic population of defectors or cooperators. Our results suggest, counterintuitively, that structured populations are not always beneficial for the evolution of cooperation for nonlinear group interactions.

Dynamic near-field optical interaction between oscillating nanomechanical structures

DOE PAGES

Ahn, Phillip; Chen, Xiang; Zhang, Zhen; ...

2015-05-27

Near-field optical techniques exploit light-matter interactions at small length scales for mechanical sensing and actuation of nanomechanical structures. Here, we study the optical interaction between two mechanical oscillators—a plasmonic nanofocusing probe-tip supported by a low frequency cantilever, and a high frequency nanomechanical resonator—and leverage their interaction for local detection of mechanical vibrations. The plasmonic nanofocusing probe provides a confined optical source to enhance the interaction between the two oscillators. Dynamic perturbation of the optical cavity between the probe-tip and the resonator leads to nonlinear modulation of the scattered light intensity at the sum and difference of their frequencies. This double-frequencymore » demodulation scheme is explored to suppress unwanted background and to detect mechanical vibrations with a minimum detectable displacement sensitivity of 0.45pm/Hz 1/2, which is limited by shot noise and electrical noise. We explore the demodulation scheme for imaging the bending vibration mode shape of the resonator with a lateral spatial resolution of 20nm. We also demonstrate the time-resolved aspect of the local optical interaction by recording the ring-down vibrations of the resonator at frequencies of up to 129MHz. The near-field optical technique is promising for studying dynamic mechanical processes in individual nanostructures.« less

Description of the ventriculoarterial interaction dynamics using recurrence plot strategies.

PubMed

Schulz, S; Bauernschmitt, R; Schwarzhaupt, A; Vahl, C F; Kiencke, U

1997-01-01

The classical description of ventriculoarterial coupling by calculating the ratio between the effective arterial elastance Ea to the end-systolic elastance Ees does not give insight into the underlying dynamics of the interaction between left-ventricular pressure (LVP) and aortic pressure (AOP) and flow (AOF). The aim of this study was to introduce a state space representation for the ventriculoarterial coupling and to quantify changes of the coupling state. A ventriculoarterial state space orbit VAO was defined to be dependent on three variables: VAO = [LVP(t), AOP(t + delta t), AOF(t + delta t)]. Changes in the coupling effect directly or indirectly on the time series of these parameters. They reflect the actual state of the cardiovascular system. The time delay delta t between the LVP and the aortic signals takes respect to the short delay between the heart action and the resulting waves in the arterial tree. The recurrence map of the VAO(i) (i = 1 .. N, N = number of points) is constructed by plotting the index i of every single point on the orbit (x-axis) against the indices of his 10 nearest neighbors (y-axis) in distance. The data were recorded in 9 anaesthetized pigs with a sample frequency of 512 Hz over a period of 6 seconds using piezoelectric pressure sensors and a Doppler flowmeter. A control condition was compared to a total occlusion of the descending aorta as a strong artificial disturbance of ventriculoarterial interaction. The nonlinear parameters percent recurrence, percent determinism and the entropy were calculated from the plot. Periodic crossing points and forbidden zones in all plots identify the nonlinear character of the chosen variables. The recurrent patterns are less rigid for control conditions than for total occlusion. Entropy (2.3% rise) and determinism (24% rise) are significantly (p < 0.003) increased. Total aortic occlusion leads to more complex time correlation patterns. These results may reflect the loss of an ideal coupling

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.

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.

Rethinking the logistic approach for population dynamics of mutualistic interactions.

PubMed

García-Algarra, Javier; Galeano, Javier; Pastor, Juan Manuel; Iriondo, José María; Ramasco, José J

2014-12-21

Mutualistic communities have an internal structure that makes them resilient to external perturbations. Late research has focused on their stability and the topology of the relations between the different organisms to explain the reasons of the system robustness. Much less attention has been invested in analyzing the systems dynamics. The main population models in use are modifications of the r-K formulation of logistic equation with additional terms to account for the benefits produced by the interspecific interactions. These models have shortcomings as the so-called r-K formulation diverges under some conditions. In this work, we introduce a model for population dynamics under mutualism that preserves the original logistic formulation. It is mathematically simpler than the widely used type II models, although it shows similar complexity in terms of fixed points and stability of the dynamics. We perform an analytical stability analysis and numerical simulations to study the model behavior in general interaction scenarios including tests of the resilience of its dynamics under external perturbations. Despite its simplicity, our results indicate that the model dynamics shows an important richness that can be used to gain further insights in the dynamics of mutualistic communities. Copyright © 2014 Elsevier Ltd. All rights reserved.

Single-cell dynamics of genome-nuclear lamina interactions.

PubMed

Kind, Jop; Pagie, Ludo; Ortabozkoyun, Havva; Boyle, Shelagh; de Vries, Sandra S; Janssen, Hans; Amendola, Mario; Nolen, Leisha D; Bickmore, Wendy A; van Steensel, Bas

2013-03-28

The nuclear lamina (NL) interacts with hundreds of large genomic regions termed lamina associated domains (LADs). The dynamics of these interactions and the relation to epigenetic modifications are poorly understood. We visualized the fate of LADs in single cells using a "molecular contact memory" approach. In each nucleus, only ~30% of LADs are positioned at the periphery; these LADs are in intermittent molecular contact with the NL but remain constrained to the periphery. Upon mitosis, LAD positioning is not detectably inherited but instead is stochastically reshuffled. Contact of individual LADs with the NL is linked to transcriptional repression and H3K9 dimethylation in single cells. Furthermore, we identify the H3K9 methyltransferase G9a as a regulator of NL contacts. Collectively, these results highlight principles of the dynamic spatial architecture of chromosomes in relation to gene regulation. Copyright © 2013 Elsevier Inc. All rights reserved.

Phase Space Approach to Dynamics of Interacting Fermions

NASA Astrophysics Data System (ADS)

Davidson, Shainen; Sels, Dries; Kasper, Valentin; Polkovnikov, Anatoli

Understanding the behavior of interacting fermions is of fundamental interest in many fields ranging from condensed matter to high energy physics. Developing numerically efficient and accurate simulation methods is an indispensable part of this. Already in equilibrium, fermions are notoriously hard to handle due to the sign problem. Out of equilibrium, an important outstanding problem is the efficient numerical simulation of the dynamics of these systems. In this work we develop a new semiclassical phase-space approach (a.k.a. the truncated Wigner approximation) for simulating the dynamics of interacting lattice fermions in arbitrary dimensions. We demonstrate the strength of the method by comparing the results to exact diagonalization (ED) on small 1D and 2D systems. We furthermore present results on Many-Body Localized (MBL) systems in 1D and 2D, and demonstrate how the method can be used to determine the MBL transition.

Spin and orbital exchange interactions from Dynamical Mean Field Theory

NASA Astrophysics Data System (ADS)

Secchi, A.; Lichtenstein, A. I.; Katsnelson, M. I.

2016-02-01

We derive a set of equations expressing the parameters of the magnetic interactions characterizing a strongly correlated electronic system in terms of single-electron Green's functions and self-energies. This allows to establish a mapping between the initial electronic system and a spin model including up to quadratic interactions between the effective spins, with a general interaction (exchange) tensor that accounts for anisotropic exchange, Dzyaloshinskii-Moriya interaction and other symmetric terms such as dipole-dipole interaction. We present the formulas in a format that can be used for computations via Dynamical Mean Field Theory algorithms.

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.

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.

Dynamic density functional theory with hydrodynamic interactions and fluctuations

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

Donev, Aleksandar, E-mail: donev@courant.nyu.edu; Vanden-Eijnden, Eric, E-mail: eve2@courant.nyu.edu

2014-06-21

We derive a closed equation for the empirical concentration of colloidal particles in the presence of both hydrodynamic and direct interactions. The ensemble average of our functional Langevin equation reproduces known deterministic Dynamic Density Functional Theory (DDFT) [M. Rex and H. Löwen, “Dynamical density functional theory with hydrodynamic interactions and colloids in unstable traps,” Phys. Rev. Lett. 101(14), 148302 (2008)], and, at the same time, it also describes the microscopic fluctuations around the mean behavior. We suggest separating the ideal (non-interacting) contribution from additional corrections due to pairwise interactions. We find that, for an incompressible fluid and in the absencemore » of direct interactions, the mean concentration follows Fick's law just as for uncorrelated walkers. At the same time, the nature of the stochastic terms in fluctuating DDFT is shown to be distinctly different for hydrodynamically-correlated and uncorrelated walkers. This leads to striking differences in the behavior of the fluctuations around Fick's law, even in the absence of pairwise interactions. We connect our own prior work [A. Donev, T. G. Fai, and E. Vanden-Eijnden, “A reversible mesoscopic model of diffusion in liquids: from giant fluctuations to Fick's law,” J. Stat. Mech.: Theory Exp. (2014) P04004] on fluctuating hydrodynamics of diffusion in liquids to the DDFT literature, and demonstrate that the fluid cannot easily be eliminated from consideration if one wants to describe the collective diffusion in colloidal suspensions.« less

Fluid Dynamic Mechanisms and Interactions within Separated Flows.

DTIC Science & Technology

1986-07-01

Vol. 42, Series E, No., pp. 197, pp. 387-39S. b5-bD, March N95, 18. Warpinski , N. R., and Chow, W. L., "Base Pres- 27. Chow, W. L., "Base Pressure of a...lied Rocket/Plume Fluid Dynamic Interactions, Vol. Mechanics, Vol. 46, No. 3, Sept. 197. 1, Base Flows, Fluid Dynamic Lab Report 63-101, 19. Warpinski ...34Surface Pressure Measurements ’" Warpinski , N. R. and Chow, W. L., "Base Pressure Associated on a Boattailed Projectile Shape at Transonic Speeds," ARBRL

Bioluminescence Resonance Energy Transfer System for Measuring Dynamic Protein-Protein Interactions in Bacteria

PubMed Central

Cui, Boyu; Wang, Yao; Song, Yunhong; Wang, Tietao; Li, Changfu; Wei, Yahong

2014-01-01

ABSTRACT Protein-protein interactions are important for virtually every biological process, and a number of elegant approaches have been designed to detect and evaluate such interactions. However, few of these methods allow the detection of dynamic and real-time protein-protein interactions in bacteria. Here we describe a bioluminescence resonance energy transfer (BRET) system based on the bacterial luciferase LuxAB. We found that enhanced yellow fluorescent protein (eYFP) accepts the emission from LuxAB and emits yellow fluorescence. Importantly, BRET occurred when LuxAB and eYFP were fused, respectively, to the interacting protein pair FlgM and FliA. Furthermore, we observed sirolimus (i.e., rapamycin)-inducible interactions between FRB and FKBP12 and a dose-dependent abolishment of such interactions by FK506, the ligand of FKBP12. Using this system, we showed that osmotic stress or low pH efficiently induced multimerization of the regulatory protein OmpR and that the multimerization induced by low pH can be reversed by a neutralizing agent, further indicating the usefulness of this system in the measurement of dynamic interactions. This method can be adapted to analyze dynamic protein-protein interactions and the importance of such interactions in bacterial processes such as development and pathogenicity. PMID:24846380

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.

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.

Quantum many-body dynamics of strongly interacting atom arrays

NASA Astrophysics Data System (ADS)

Bernien, Hannes; Keesling, Alexander; Levine, Harry; Schwartz, Sylvain; Omran, Ahmed; Anschuetz, Eric; Endres, Manuel; Vuletic, Vladan; Greiner, Markus; Lukin, Mikhail

2017-04-01

The coherent interaction between large numbers of particles gives rise to fascinating quantum many-body effects and lies at the center of quantum simulations and quantum information processing. The development of systems consisting of many, well-controlled particles with tunable interactions is an outstanding challenge. Here we present a new platform based on large, reconfigurable arrays of individually trapped atoms. Strong interactions between these atoms are enabled by exciting them to Rydberg states. This flexible approach allows access to vastly different regimes with interactions tunable over several orders of magnitude. We study the coherent many-body dynamics in varying array geometries and observe the formation of Rydberg crystals.

Agreement dynamics on interaction networks with diverse topologies

NASA Astrophysics Data System (ADS)

Barrat, Alain; Baronchelli, Andrea; Dall'Asta, Luca; Loreto, Vittorio

2007-06-01

We review the behavior of a recently introduced model of agreement dynamics, called the "Naming Game." This model describes the self-organized emergence of linguistic conventions and the establishment of simple communication systems in a population of agents with pairwise local interactions. The mechanisms of convergence towards agreement strongly depend on the network of possible interactions between the agents. In particular, the mean-field case in which all agents communicate with all the others is not efficient, since a large temporary memory is requested for the agents. On the other hand, regular lattice topologies lead to a fast local convergence but to a slow global dynamics similar to coarsening phenomena. The embedding of the agents in a small-world network represents an interesting tradeoff: a local consensus is easily reached, while the long-range links allow to bypass coarsening-like convergence. We also consider alternative adaptive strategies which can lead to faster global convergence.

Pluto-Charon solar wind interaction dynamics

NASA Astrophysics Data System (ADS)

Hale, J. P. M.; Paty, C. S.

2017-05-01

This work studies Charon's effects on the Pluto-solar wind interaction using a multifluid MHD model which simulates the interactions of Pluto and Charon with the solar wind as well as with each other. Specifically, it investigates the ionospheric dynamics of a two body system in which either one or both bodies possess an ionosphere. Configurations in which Charon is directly upstream and directly downstream of Pluto are considered. Depending on ionospheric and solar wind conditions, Charon could periodically pass into the solar wind flow upstream of Pluto. The results of this study demonstrate that in these circumstances Charon modifies the upstream flow, both in the case in which Charon possesses an ionosphere, and in the case in which Charon is without an ionosphere. This modification amounts to a change in the gross structure of the interaction region when Charon possesses an ionosphere but is more localized when Charon lacks an ionosphere. Furthermore, evidence is shown that supports Charon acting to partially shield Pluto from the solar wind when it is upstream of Pluto, resulting in a decrease in ionospheric loss by Pluto.

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.

Inference of Time-Evolving Coupled Dynamical Systems in the Presence of Noise

NASA Astrophysics Data System (ADS)

Stankovski, Tomislav; Duggento, Andrea; McClintock, Peter V. E.; Stefanovska, Aneta

2012-07-01

A new method is introduced for analysis of interactions between time-dependent coupled oscillators, based on the signals they generate. It distinguishes unsynchronized dynamics from noise-induced phase slips and enables the evolution of the coupling functions and other parameters to be followed. It is based on phase dynamics, with Bayesian inference of the time-evolving parameters achieved by shaping the prior densities to incorporate knowledge of previous samples. The method is tested numerically and applied to reveal and quantify the time-varying nature of cardiorespiratory interactions.

MDANSE: An Interactive Analysis Environment for Molecular Dynamics Simulations.

PubMed

Goret, G; Aoun, B; Pellegrini, E

2017-01-23

The MDANSE software-Molecular Dynamics Analysis of Neutron Scattering Experiments-is presented. It is an interactive application for postprocessing molecular dynamics (MD) simulations. Given the widespread use of MD simulations in material and biomolecular sciences to get a better insight for experimental techniques such as thermal neutron scattering (TNS), the development of MDANSE has focused on providing a user-friendly, interactive, graphical user interface for analyzing many trajectories in the same session and running several analyses simultaneously independently of the interface. This first version of MDANSE already proposes a broad range of analyses, and the application has been designed to facilitate the introduction of new analyses in the framework. All this makes MDANSE a valuable tool for extracting useful information from trajectories resulting from a wide range of MD codes.

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

Dynamic gesture recognition using neural networks: a fundament for advanced interaction construction

NASA Astrophysics Data System (ADS)

Boehm, Klaus; Broll, Wolfgang; Sokolewicz, Michael A.

1994-04-01

Interaction in virtual reality environments is still a challenging task. Static hand posture recognition is currently the most common and widely used method for interaction using glove input devices. In order to improve the naturalness of interaction, and thereby decrease the user-interface learning time, there is a need to be able to recognize dynamic gestures. In this paper we describe our approach to overcoming the difficulties of dynamic gesture recognition (DGR) using neural networks. Backpropagation neural networks have already proven themselves to be appropriate and efficient for posture recognition. However, the extensive amount of data involved in DGR requires a different approach. Because of features such as topology preservation and automatic-learning, Kohonen Feature Maps are particularly suitable for the reduction of the high dimensional data space that is the result of a dynamic gesture, and are thus implemented for this task.

Quantifying predictability variations in a low-order ocean-atmosphere model - A dynamical systems approach

NASA Technical Reports Server (NTRS)

Nese, Jon M.; Dutton, John A.

1993-01-01

The predictability of the weather and climatic states of a low-order moist general circulation model is quantified using a dynamic systems approach, and the effect of incorporating a simple oceanic circulation on predictability is evaluated. The predictability and the structure of the model attractors are compared using Liapunov exponents, local divergence rates, and the correlation and Liapunov dimensions. It was found that the activation of oceanic circulation increases the average error doubling time of the atmosphere and the coupled ocean-atmosphere system by 10 percent and decreases the variance of the largest local divergence rate by 20 percent. When an oceanic circulation develops, the average predictability of annually averaged states is improved by 25 percent and the variance of the largest local divergence rate decreases by 25 percent.

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…

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

Quantifying temporal trends in fisheries abundance using Bayesian dynamic linear models: A case study of riverine Smallmouth Bass populations

USGS Publications Warehouse

Schall, Megan K.; Blazer, Vicki S.; Lorantas, Robert M.; Smith, Geoffrey; Mullican, John E.; Keplinger, Brandon J.; Wagner, Tyler

2018-01-01

Detecting temporal changes in fish abundance is an essential component of fisheries management. Because of the need to understand short‐term and nonlinear changes in fish abundance, traditional linear models may not provide adequate information for management decisions. This study highlights the utility of Bayesian dynamic linear models (DLMs) as a tool for quantifying temporal dynamics in fish abundance. To achieve this goal, we quantified temporal trends of Smallmouth Bass Micropterus dolomieu catch per effort (CPE) from rivers in the mid‐Atlantic states, and we calculated annual probabilities of decline from the posterior distributions of annual rates of change in CPE. We were interested in annual declines because of recent concerns about fish health in portions of the study area. In general, periods of decline were greatest within the Susquehanna River basin, Pennsylvania. The declines in CPE began in the late 1990s—prior to observations of fish health problems—and began to stabilize toward the end of the time series (2011). In contrast, many of the other rivers investigated did not have the same magnitude or duration of decline in CPE. Bayesian DLMs provide information about annual changes in abundance that can inform management and are easily communicated with managers and stakeholders.

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.

Current-Current Interactions, Dynamical Symmetry - and Quantum Chromodynamics.

NASA Astrophysics Data System (ADS)

Neuenschwander, Dwight Edward, Jr.

Quantum Chromodynamics with massive gluons (gluon mass (TBOND) xm(,p)) in a contact-interaction limit called CQCD (strong coupling g (--->) (INFIN); x (--->) (INFIN)), despite its non-renormalizability and lack of hope of confinement, is nevertheless interesting for at least two reasons. (1) Some authors have suggested a relation between 4-Fermi and Yang-Mills theories. If g/x('2) << 1, then CQCD is not merely a 4-Fermi interaction, but includes 4, 6, 8, ...-Fermi non-Abelian contact interactions. (2) With the possibility of infrared slavery, perturbative evaluation of QCD in the infrared is a dubious practice. However, if g('2)/x('2) << 1 in CQCD, then the simplest 4-Fermi interaction is dominant, and CQCD admits perturbative treatment, but only in the infrared. With the dominant interaction, a dynamical Nambu-Goldstone realization of chiral symmetry -breaking (XSB) is found. Although in QCD the relation between confinement and XSB is controversial, XSB occurs in CQCD provided confinement is sacrificed.

A dynamics based view of atmosphere-fire interactions

Treesearch

Brian E. Potter

2002-01-01

Current research on severe fire interactions with the atmosphere focuses largely on examination of correlations between fire growth and various atmospheric properties, and on the development of indices based on these correlations. The author proposes that progress requires understanding the physics and atmospheric dynamics behind the correlations. A conceptual 3-stage...

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 of Francisella tularensis bacterial cells with dynamic speckles

NASA Astrophysics Data System (ADS)

Ulianova, Onega V.; Ulyanov, Sergey S.; Sazanova, Elena V.; Zudina, Irina; Zhang, Zhihong; Sibo, Zhou; Luo, Qingming

2006-08-01

Influence of low-coherent speckles on the colonies grows is investigated. It has been demonstrated that effects of light on the inhibition of cells (Francisella Tularensis) are caused by speckle dynamics. The regimes of illumination of cell suspension with purpose of devitalization of hazard bacteria, caused very dangerous infections, such as tularemia, are found. Mathematical model of interaction of low-coherent laser radiation with bacteria suspension has been proposed. Computer simulations of the processes of laser-cells interaction have been carried out. Role of coherence of light in the processes of laser-cell interaction is analyzed.

Deciphering the Dynamic Interaction Profile of an Intrinsically Disordered Protein by NMR Exchange Spectroscopy.

PubMed

Delaforge, Elise; Kragelj, Jaka; Tengo, Laura; Palencia, Andrés; Milles, Sigrid; Bouvignies, Guillaume; Salvi, Nicola; Blackledge, Martin; Jensen, Malene Ringkjøbing

2018-01-24

Intrinsically disordered proteins (IDPs) display a large number of interaction modes including folding-upon-binding, binding without major structural transitions, or binding through highly dynamic, so-called fuzzy, complexes. The vast majority of experimental information about IDP binding modes have been inferred from crystal structures of proteins in complex with short peptides of IDPs. However, crystal structures provide a mainly static view of the complexes and do not give information about the conformational dynamics experienced by the IDP in the bound state. Knowledge of the dynamics of IDP complexes is of fundamental importance to understand how IDPs engage in highly specific interactions without concomitantly high binding affinity. Here, we combine rotating-frame R 1ρ , Carr-Purcell-Meiboom Gill relaxation dispersion as well as chemical exchange saturation transfer to decipher the dynamic interaction profile of an IDP in complex with its partner. We apply the approach to the dynamic signaling complex formed between the mitogen-activated protein kinase (MAPK) p38α and the intrinsically disordered regulatory domain of the MAPK kinase MKK4. Our study demonstrates that MKK4 employs a subtle combination of interaction modes in order to bind to p38α, leading to a complex displaying significantly different dynamics across the bound regions.

Modeling the within-host dynamics of cholera: bacterial-viral interaction.

PubMed

Wang, Xueying; Wang, Jin

2017-08-01

Novel deterministic and stochastic models are proposed in this paper for the within-host dynamics of cholera, with a focus on the bacterial-viral interaction. The deterministic model is a system of differential equations describing the interaction among the two types of vibrios and the viruses. The stochastic model is a system of Markov jump processes that is derived based on the dynamics of the deterministic model. The multitype branching process approximation is applied to estimate the extinction probability of bacteria and viruses within a human host during the early stage of the bacterial-viral infection. Accordingly, a closed-form expression is derived for the disease extinction probability, and analytic estimates are validated with numerical simulations. The local and global dynamics of the bacterial-viral interaction are analysed using the deterministic model, and the result indicates that there is a sharp disease threshold characterized by the basic reproduction number [Formula: see text]: if [Formula: see text], vibrios ingested from the environment into human body will not cause cholera infection; if [Formula: see text], vibrios will grow with increased toxicity and persist within the host, leading to human cholera. In contrast, the stochastic model indicates, more realistically, that there is always a positive probability of disease extinction within the human host.

Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, Upper Yangtze, China from 1975 to 2000

USGS Publications Warehouse

Zhao, Shuqing; Liu, Shuguang; Yin, Runsheng; Li, Zhengpeng; Deng, Yulin; Tan, Kun; Deng, Xiangzheng; Rothstein, David; Qi, Jiaguo

2010-01-01

Quantifying the spatial and temporal dynamics of carbon stocks in terrestrial ecosystems and carbon fluxes between the terrestrial biosphere and the atmosphere is critical to our understanding of regional patterns of carbon budgets. Here we use the General Ensemble biogeochemical Modeling System to simulate the terrestrial ecosystem carbon dynamics in the Jinsha watershed of China’s upper Yangtze basin from 1975 to 2000, based on unique combinations of spatial and temporal dynamics of major driving forces, such as climate, soil properties, nitrogen deposition, and land use and land cover changes. Our analysis demonstrates that the Jinsha watershed ecosystems acted as a carbon sink during the period of 1975–2000, with an average rate of 0.36 Mg/ha/yr, primarily resulting from regional climate variation and local land use and land cover change. Vegetation biomass accumulation accounted for 90.6% of the sink, while soil organic carbon loss before 1992 led to a lower net gain of carbon in the watershed, and after that soils became a small sink. Ecosystem carbon sink/source patterns showed a high degree of spatial heterogeneity. Carbon sinks were associated with forest areas without disturbances, whereas carbon sources were primarily caused by stand-replacing disturbances. It is critical to adequately represent the detailed fast-changing dynamics of land use activities in regional biogeochemical models to determine the spatial and temporal evolution of regional carbon sink/source patterns.

Exploring Classroom Interaction with Dynamic Social Network Analysis

ERIC Educational Resources Information Center

Bokhove, Christian

2018-01-01

This article reports on an exploratory project in which technology and dynamic social network analysis (SNA) are used for modelling classroom interaction. SNA focuses on the links between social actors, draws on graphic imagery to reveal and display the patterning of those links, and develops mathematical and computational models to describe and…

Simulating market dynamics: interactions between consumer psychology and social networks.

PubMed

Janssen, Marco A; Jager, Wander

2003-01-01

Markets can show different types of dynamics, from quiet markets dominated by one or a few products, to markets with continual penetration of new and reintroduced products. In a previous article we explored the dynamics of markets from a psychological perspective using a multi-agent simulation model. The main results indicated that the behavioral rules dominating the artificial consumer's decision making determine the resulting market dynamics, such as fashions, lock-in, and unstable renewal. Results also show the importance of psychological variables like social networks, preferences, and the need for identity to explain the dynamics of markets. In this article we extend this work in two directions. First, we will focus on a more systematic investigation of the effects of different network structures. The previous article was based on Watts and Strogatz's approach, which describes the small-world and clustering characteristics in networks. More recent research demonstrated that many large networks display a scale-free power-law distribution for node connectivity. In terms of market dynamics this may imply that a small proportion of consumers may have an exceptional influence on the consumptive behavior of others (hubs, or early adapters). We show that market dynamics is a self-organized property depending on the interaction between the agents' decision-making process (heuristics), the product characteristics (degree of satisfaction of unit of consumption, visibility), and the structure of interactions between agents (size of network and hubs in a social network).

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

Temporal dynamics and impact of event interactions in cyber-social populations

NASA Astrophysics Data System (ADS)

Zhang, Yi-Qing; Li, Xiang

2013-03-01

The advance of information technologies provides powerful measures to digitize social interactions and facilitate quantitative investigations. To explore large-scale indoor interactions of a social population, we analyze 18 715 users' Wi-Fi access logs recorded in a Chinese university campus during 3 months, and define event interaction (EI) to characterize the concurrent interactions of multiple users inferred by their geographic coincidences—co-locating in the same small region at the same time. We propose three rules to construct a transmission graph, which depicts the topological and temporal features of event interactions. The vertex dynamics of transmission graph tells that the active durations of EIs fall into the truncated power-law distributions, which is independent on the number of involved individuals. The edge dynamics of transmission graph reports that the transmission durations present a truncated power-law pattern independent on the daily and weekly periodicities. Besides, in the aggregated transmission graph, low-degree vertices previously neglected in the aggregated static networks may participate in the large-degree EIs, which is verified by three data sets covering different sizes of social populations with various rendezvouses. This work highlights the temporal significance of event interactions in cyber-social populations.

Dynamic interactions between cells and their extracellular matrix mediate embryonic development.

PubMed

Goody, Michelle F; Henry, Clarissa A

2010-06-01

Cells and their surrounding extracellular matrix microenvironment interact throughout all stages of life. Understanding the continuously changing scope of cell-matrix interactions in vivo is crucial to garner insights into both congenital birth defects and disease progression. A current challenge in the field of developmental biology is to adapt in vitro tools and rapidly evolving imaging technology to study cell-matrix interactions in a complex 4-D environment. In this review, we highlight the dynamic modulation of cell-matrix interactions during development. We propose that individual cell-matrix adhesion proteins are best considered as complex proteins that can play multiple, often seemingly contradictory roles, depending upon the context of the microenvironment. In addition, cell-matrix proteins can also exert different short versus long term effects. It is thus important to consider cell behavior in light of the microenvironment because of the constant and dynamic reciprocal interactions occurring between them. Finally, we suggest that analysis of cell-matrix interactions at multiple levels (molecules, cells, tissues) in vivo is critical for an integrated understanding because different information can be acquired from all size scales. Copyright 2010 Wiley-Liss, Inc.

Molecular dynamics simulations of β2-microglobulin interaction with hydrophobic surfaces.

PubMed

Dongmo Foumthuim, Cedrix J; Corazza, Alessandra; Esposito, Gennaro; Fogolari, Federico

2017-11-21

Hydrophobic surfaces are known to adsorb and unfold proteins, a process that has been studied only for a few proteins. Here we address the interaction of β2-microglobulin, a paradigmatic protein for the study of amyloidogenesis, with hydrophobic surfaces. A system with 27 copies of the protein surrounded by a model cubic hydrophobic box is studied by implicit solvent molecular dynamics simulations. Most proteins adsorb on the walls of the box without major distortions in local geometry, whereas free molecules maintain proper structures and fluctuations as observed in explicit solvent molecular dynamics simulations. The major conclusions from the simulations are as follows: (i) the adopted implicit solvent model is adequate to describe protein dynamics and thermodynamics; (ii) adsorption occurs readily and is irreversible on the simulated timescale; (iii) the regions most involved in molecular encounters and stable interactions with the walls are the same as those that are important in protein-protein and protein-nanoparticle interactions; (iv) unfolding following adsorption occurs at regions found to be flexible by both experiments and simulations; (v) thermodynamic analysis suggests a very large contribution from van der Waals interactions, whereas unfavorable electrostatic interactions are not found to contribute much to adsorption energy. Surfaces with different degrees of hydrophobicity may occur in vivo. Our simulations show that adsorption is a fast and irreversible process which is accompanied by partial unfolding. The results and the thermodynamic analysis presented here are consistent with and rationalize previous experimental work.

Dynamic ion-ion and water-ion interactions in ion channels.

PubMed Central

Wu, J V

1992-01-01

The dynamic interactions among ions and water molecules in ion channels are treated based on an assumption that ions at binding sites can be knocked off by both transient entering ions and local water molecules. The theory, when applied to a single-site model K+ channel, provides solutions for super- and subsaturations, flux-ratio exponent (n') greater than 1, osmotic streaming current, activity-dependent reversal potentials, and anomalous mole-fraction behavior. The analysis predicts that: (a) the saturation may but, in general, does not follow the Michaelis-Menten relation; (b) streaming current results from imbalanced water-ion knock-off interactions; (c) n' greater than 1 even for single-site channels, but it is unlikely to exceed 1.4 unless the pore is occupied by one or more ion(s); (d) in the calculation involving two permeant ion species with similar radii, the heavier ions show higher affinity; the ion-ion knock-off dissociation from the site is more effective when two interacting ions are identical. Therefore, the "multi-ion behaviors" found in most ion channels are the consequences of dynamic ion-ion and water-ion interactions. The presence of these interactions does not require two or more binding sites in channels. PMID:1376158

Dynamic dual-tracer MRI-guided fluorescence tomography to quantify receptor density in vivo

PubMed Central

Davis, Scott C.; Samkoe, Kimberley S.; Tichauer, Kenneth M.; Sexton, Kristian J.; Gunn, Jason R.; Deharvengt, Sophie J.; Hasan, Tayyaba; Pogue, Brian W.

2013-01-01

The up-regulation of cell surface receptors has become a central focus in personalized cancer treatment; however, because of the complex nature of contrast agent pharmacokinetics in tumor tissue, methods to quantify receptor binding in vivo remain elusive. Here, we present a dual-tracer optical technique for noninvasive estimation of specific receptor binding in cancer. A multispectral MRI-coupled fluorescence molecular tomography system was used to image the uptake kinetics of two fluorescent tracers injected simultaneously, one tracer targeted to the receptor of interest and the other tracer a nontargeted reference. These dynamic tracer data were then fit to a dual-tracer compartmental model to estimate the density of receptors available for binding in the tissue. Applying this approach to mice with deep-seated gliomas that overexpress the EGF receptor produced an estimate of available receptor density of 2.3 ± 0.5 nM (n = 5), consistent with values estimated in comparative invasive imaging and ex vivo studies. PMID:23671066

Quantifying changes in spatial patterns of surface air temperature dynamics over several decades

NASA Astrophysics Data System (ADS)

Zappalà, Dario A.; Barreiro, Marcelo; Masoller, Cristina

2018-04-01

We study daily surface air temperature (SAT) reanalysis in a grid over the Earth's surface to identify and quantify changes in SAT dynamics during the period 1979-2016. By analysing the Hilbert amplitude and frequency we identify the regions where relative variations are most pronounced (larger than ±50 % for the amplitude and ±100 % for the frequency). Amplitude variations are interpreted as due to changes in precipitation or ice melting, while frequency variations are interpreted as due to a northward shift of the inter-tropical convergence zone (ITCZ) and to a widening of the rainfall band in the western Pacific Ocean. The ITCZ is the ascending branch of the Hadley cell, and thus by affecting the tropical atmospheric circulation, ITCZ migration has far-reaching climatic consequences. As the methodology proposed here can be applied to many other geophysical time series, our work will stimulate new research that will advance the understanding of climate change impacts.

Quantum Spin Dynamics with Pairwise-Tunable, Long-Range Interactions

DTIC Science & Technology

2016-08-05

rection of the arrows. Dashed (dotted) lines mark the NNN hopping terms (coefficients ±t2). NNNN long -range hopping along curved lines are included to...Quantum spin dynamics with pairwise-tunable, long -range interactions C.-L. Hunga,b,1,2, Alejandro González-Tudelac,1,2, J. Ignacio Ciracc, and H. J...atoms) that interact by way of a variety of processes, such as atomic collisions. Such pro- cesses typically lead to short -range, nearest-neighbor

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.

Adequacy of damped dynamics to represent the electron-phonon interaction in solids

DOE PAGES

Caro, A.; Correa, A. A.; Tamm, A.; ...

2015-10-16

Time-dependent density functional theory and Ehrenfest dynamics are used to calculate the electronic excitations produced by a moving Ni ion in a Ni crystal in the case of energetic MeV range (electronic stopping power regime), as well as thermal energy meV range (electron-phonon interaction regime). Results at high energy compare well to experimental databases of stopping power, and at low energy the electron-phonon interaction strength determined in this way is very similar to the linear response calculation and experimental measurements. This approach to electron-phonon interaction as an electronic stopping process provides the basis for a unified framework to perform classicalmore » molecular dynamics of ion-solid interaction with ab initio type nonadiabatic terms in a wide range of energies.« less

Analysis Of Dynamic Interactions Between Solar Array Simulators And Spacecraft Power Conditioning And Distribution Units

NASA Astrophysics Data System (ADS)

Valdivia, V.; Barrado, A.; Lazaro, A.; Rueda, P.; Tonicello, F.; Fernandez, A.; Mourra, O.

2011-10-01

Solar array simulators (SASs) are hardware devices, commonly applied instead of actual solar arrays (SAs) during the design process of spacecrafts power conditioning and distribution units (PCDUs), and during spacecrafts assembly integration and tests. However, the dynamic responses between SASs and actual SAs are usually different. This fact plays an important role, since the dynamic response of the SAS may influence significantly the dynamic behaviour of the PCDU under certain conditions, even leading to instability. This paper deals with the dynamic interactions between SASs and PCDUs. Several methods for dynamic characterization of the SASs are discussed, and the response of commercial SASs widely applied in the space industry is compared to that of actual SAs. After that, the interactions are experimentally analyzed by using a boost converter connected to the aforementioned SASs, thus demonstrating their critical importance. The interactions are first tackled analytically by means of small-signal models, and finally a black-box modelling method of SASs is proposed as a useful tool to analyze the interactions by means of simulation. The capabilities of both the analytical method and the black- box model to predict the interactions are demonstrated.

Pho dynamically interacts with Spt5 to facilitate transcriptional switches at the hsp70 locus.

PubMed

Pereira, Allwyn; Paro, Renato

2017-12-06

Numerous target genes of the Polycomb group (PcG) are transiently activated by a stimulus and subsequently repressed. However, mechanisms by which PcG proteins regulate such target genes remain elusive. We employed the heat shock-responsive hsp70 locus in Drosophila to study the chromatin dynamics of PRC1 and its interplay with known regulators of the locus before, during and after heat shock. We detected mutually exclusive binding patterns for HSF and PRC1 at the hsp70 locus. We found that Pleiohomeotic (Pho), a DNA-binding PcG member, dynamically interacts with Spt5, an elongation factor. The dynamic interaction switch between Pho and Spt5 is triggered by the recruitment of HSF to chromatin. Mutation in the protein-protein interaction domain (REPO domain) of Pho interferes with the dynamics of its interaction with Spt5. The transcriptional kinetics of the heat shock response is negatively affected by a mutation in the REPO domain of Pho. We propose that a dynamic interaction switch between PcG proteins and an elongation factor enables stress-inducible genes to efficiently switch between ON/OFF states in the presence/absence of the activating stimulus.

Dynamic reciprocity in cell-scaffold interactions.

PubMed

Mauney, Joshua R; Adam, Rosalyn M

2015-03-01

Tissue engineering in urology has shown considerable promise. However, there is still much to understand, particularly regarding the interactions between scaffolds and their host environment, how these interactions regulate regeneration and how they may be enhanced for optimal tissue repair. In this review, we discuss the concept of dynamic reciprocity as applied to tissue engineering, i.e. how bi-directional signaling between implanted scaffolds and host tissues such as the bladder drives the process of constructive remodeling to ensure successful graft integration and tissue repair. The impact of scaffold content and configuration, the contribution of endogenous and exogenous bioactive factors, the influence of the host immune response and the functional interaction with mechanical stimulation are all considered. In addition, the temporal relationships of host tissue ingrowth, bioactive factor mobilization, scaffold degradation and immune cell infiltration, as well as the reciprocal signaling between discrete cell types and scaffolds are discussed. Improved understanding of these aspects of tissue repair will identify opportunities for optimization of repair that could be exploited to enhance regenerative medicine strategies for urology in future studies. Copyright © 2014 Elsevier B.V. All rights reserved.

Collective Phenomena Emerging from the Interactions between Dynamical Processes in Multiplex Networks

NASA Astrophysics Data System (ADS)

Nicosia, Vincenzo; Skardal, Per Sebastian; Arenas, Alex; Latora, Vito

2017-03-01

We introduce a framework to intertwine dynamical processes of different nature, each with its own distinct network topology, using a multilayer network approach. As an example of collective phenomena emerging from the interactions of multiple dynamical processes, we study a model where neural dynamics and nutrient transport are bidirectionally coupled in such a way that the allocation of the transport process at one layer depends on the degree of synchronization at the other layer, and vice versa. We show numerically, and we prove analytically, that the multilayer coupling induces a spontaneous explosive synchronization and a heterogeneous distribution of allocations, otherwise not present in the two systems considered separately. Our framework can find application to other cases where two or more dynamical processes such as synchronization, opinion formation, information diffusion, or disease spreading, are interacting with each other.

Molecular Dynamics of "Fuzzy" Transcriptional Activator-Coactivator Interactions

PubMed Central

Scholes, Natalie S.; Weinzierl, Robert O. J.

2016-01-01

Transcriptional activation domains (ADs) are generally thought to be intrinsically unstructured, but capable of adopting limited secondary structure upon interaction with a coactivator surface. The indeterminate nature of this interface made it hitherto difficult to study structure/function relationships of such contacts. Here we used atomistic accelerated molecular dynamics (aMD) simulations to study the conformational changes of the GCN4 AD and variants thereof, either free in solution, or bound to the GAL11 coactivator surface. We show that the AD-coactivator interactions are highly dynamic while obeying distinct rules. The data provide insights into the constant and variable aspects of orientation of ADs relative to the coactivator, changes in secondary structure and energetic contributions stabilizing the various conformers at different time points. We also demonstrate that a prediction of α-helical propensity correlates directly with the experimentally measured transactivation potential of a large set of mutagenized ADs. The link between α-helical propensity and the stimulatory activity of ADs has fundamental practical and theoretical implications concerning the recruitment of ADs to coactivators. PMID:27175900

Effective Dynamics of Microorganisms That Interact with Their Own Trail

NASA Astrophysics Data System (ADS)

Kranz, W. Till; Gelimson, Anatolij; Zhao, Kun; Wong, Gerard C. L.; Golestanian, Ramin

2016-07-01

Like ants, some microorganisms are known to leave trails on surfaces to communicate. We explore how trail-mediated self-interaction could affect the behavior of individual microorganisms when diffusive spreading of the trail is negligible on the time scale of the microorganism using a simple phenomenological model for an actively moving particle and a finite-width trail. The effective dynamics of each microorganism takes on the form of a stochastic integral equation with the trail interaction appearing in the form of short-term memory. For a moderate coupling strength below an emergent critical value, the dynamics exhibits effective diffusion in both orientation and position after a phase of superdiffusive reorientation. We report experimental verification of a seemingly counterintuitive perpendicular alignment mechanism that emerges from the model.

Quantifying ubiquitin signaling.

PubMed

Ordureau, Alban; Münch, Christian; Harper, J Wade

2015-05-21

Ubiquitin (UB)-driven signaling systems permeate biology, and are often integrated with other types of post-translational modifications (PTMs), including phosphorylation. Flux through such pathways is dictated by the fractional stoichiometry of distinct modifications and protein assemblies as well as the spatial organization of pathway components. Yet, we rarely understand the dynamics and stoichiometry of rate-limiting intermediates along a reaction trajectory. Here, we review how quantitative proteomic tools and enrichment strategies are being used to quantify UB-dependent signaling systems, and to integrate UB signaling with regulatory phosphorylation events, illustrated with the PINK1/PARKIN pathway. A key feature of ubiquitylation is that the identity of UB chain linkage types can control downstream processes. We also describe how proteomic and enzymological tools can be used to identify and quantify UB chain synthesis and linkage preferences. The emergence of sophisticated quantitative proteomic approaches will set a new standard for elucidating biochemical mechanisms of UB-driven signaling systems. Copyright © 2015 Elsevier Inc. All rights reserved.

Quantifying Ubiquitin Signaling

PubMed Central

Ordureau, Alban; Münch, Christian; Harper, J. Wade

2015-01-01

Ubiquitin (UB)-driven signaling systems permeate biology, and are often integrated with other types of post-translational modifications (PTMs), most notably phosphorylation. Flux through such pathways is typically dictated by the fractional stoichiometry of distinct regulatory modifications and protein assemblies as well as the spatial organization of pathway components. Yet, we rarely understand the dynamics and stoichiometry of rate-limiting intermediates along a reaction trajectory. Here, we review how quantitative proteomic tools and enrichment strategies are being used to quantify UB-dependent signaling systems, and to integrate UB signaling with regulatory phosphorylation events. A key regulatory feature of ubiquitylation is that the identity of UB chain linkage types can control downstream processes. We also describe how proteomic and enzymological tools can be used to identify and quantify UB chain synthesis and linkage preferences. The emergence of sophisticated quantitative proteomic approaches will set a new standard for elucidating biochemical mechanisms of UB-driven signaling systems. PMID:26000850

Self-healing multiphase polymers via dynamic metal-ligand interactions.

PubMed

Mozhdehi, Davoud; Ayala, Sergio; Cromwell, Olivia R; Guan, Zhibin

2014-11-19

A new self-healing multiphase polymer is developed in which a pervasive network of dynamic metal-ligand (zinc-imidazole) interactions are programmed in the soft matrix of a hard/soft two-phase brush copolymer system. The mechanical and dynamic properties of the materials can be tuned by varying a number of molecular parameters (e.g., backbone/brush degree of polymerization and brush density) as well as the ligand/metal ratio. Following mechanical damage, these thermoplastic elastomers show excellent self-healing ability under ambient conditions without any intervention.

Explaining Dynamic Interactions in Wiki-Based Collaborative Writing

ERIC Educational Resources Information Center

Li, Mimi; Zhu, Wei

2017-01-01

This article reports a case study that examined dynamic patterns of interaction that two small groups (Group A and Group B) of ESL students exemplified when they performed two writing tasks: a research proposal (Task 1) and an annotated bibliography (Task 2) in a wiki site. Group A demonstrated a collective pattern in Task 1, but switched to an…

Fluid Dynamic - Structural Interactions of Labyrinth Seals.

DTIC Science & Technology

1986-08-01

A., "The Leakage of Steam Through Labyrinth Seals ", Trans. ASME, Vol. 57, 1935, pp 115-122. 21. Komotori, K., "A Consideration on the Labyrinth ...October 1980. 17. Vermes, G., "A fluid-Mechanics Approach to the Labyrinth Seal Leakage Problem", Journal of Basic Engineering, Tr. ASME, Series D...INTERACTIONS OF LABYRINTH SEALS Manuel Martinez-Sanchez John Dugundji Gas Turbine and Plasma Dynamics Laboratory D T IC Department of Aeronautics and

Probing and quantifying DNA-protein interactions with asymmetrical flow field-flow fractionation.

PubMed

Ashby, Jonathan; Schachermeyer, Samantha; Duan, Yaokai; Jimenez, Luis A; Zhong, Wenwan

2014-09-05

Tools capable of measuring binding affinities as well as amenable to downstream sequencing analysis are needed for study of DNA-protein interaction, particularly in discovery of new DNA sequences with affinity to diverse targets. Asymmetrical flow field-flow fractionation (AF4) is an open-channel separation technique that eliminates interference from column packing to the non-covalently bound complex and could potentially be applied for study of macromolecular interaction. The recovery and elution behaviors of the poly(dA)n strand and aptamers in AF4 were investigated. Good recovery of ssDNAs was achieved by judicious selection of the channel membrane with consideration of the membrane pore diameter and the radius of gyration (Rg) of the ssDNA, which was obtained with the aid of a Molecular Dynamics tool. The Rg values were also used to assess the folding situation of aptamers based on their migration times in AF4. The interactions between two ssDNA aptamers and their respective protein components were investigated. Using AF4, near-baseline resolution between the free and protein-bound aptamer fractions could be obtained. With this information, dissociation constants of ∼16nM and ∼57nM were obtained for an IgE aptamer and a streptavidin aptamer, respectively. In addition, free and protein-bound IgE aptamer was extracted from the AF4 eluate and amplified, illustrating the potential of AF4 in screening ssDNAs with high affinity to targets. Our results demonstrate that AF4 is an effective tool holding several advantages over the existing techniques and should be useful for study of diverse macromolecular interaction systems. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

LETTER TO THE EDITOR: Dynamics of interacting neural networks

NASA Astrophysics Data System (ADS)

Kinzel, W.; Metzler, R.; Kanter, I.

2000-04-01

The dynamics of interacting perceptrons is solved analytically. For a directed flow of information the system runs into a state which has a higher symmetry than the topology of the model. A symmetry-breaking phase transition is found with increasing learning rate. In addition, it is shown that a system of interacting perceptrons which is trained on the history of its minority decisions develops a good strategy for the problem of adaptive competition known as the bar problem or minority game.

Exploring GPCR-Lipid Interactions by Molecular Dynamics Simulations: Excitements, Challenges, and the Way Forward.

PubMed

Sengupta, Durba; Prasanna, Xavier; Mohole, Madhura; Chattopadhyay, Amitabha

2018-06-07

Gprotein-coupled receptors (GPCRs) are seven transmembrane receptors that mediate a large number of cellular responses and are important drug targets. One of the current challenges in GPCR biology is to analyze the molecular signatures of receptor-lipid interactions and their subsequent effects on GPCR structure, organization, and function. Molecular dynamics simulation studies have been successful in predicting molecular determinants of receptor-lipid interactions. In particular, predicted cholesterol interaction sites appear to correspond well with experimentally determined binding sites and estimated time scales of association. In spite of several success stories, the methodologies in molecular dynamics simulations are still emerging. In this Feature Article, we provide a comprehensive overview of coarse-grain and atomistic molecular dynamics simulations of GPCR-lipid interaction in the context of experimental observations. In addition, we discuss the effect of secondary and tertiary structural constraints in coarse-grain simulations in the context of functional dynamics and structural plasticity of GPCRs. We envision that this comprehensive overview will help resolve differences in computational studies and provide a way forward.

Dynamic Creative Interaction Networks and Team Creativity Evolution: A Longitudinal Study

ERIC Educational Resources Information Center

Jiang, Hui; Zhang, Qing-Pu; Zhou, Yang

2018-01-01

To assess the dynamical effects of creative interaction networks on team creativity evolution, this paper elaborates a theoretical framework that links the key elements of creative interaction networks, including node, edge and network structure, to creativity in teams. The process of team creativity evolution is divided into four phases,…

Nonlinear evolution dynamics of holographic superconductor model with scalar self-interaction

NASA Astrophysics Data System (ADS)

Li, Ran; Zi, Tieguang; Zhang, Hongbao

2018-04-01

We investigate the holographic superconductor model that is described by the Einstein-Maxwell theory with the self-interaction term λ |Ψ |4 of complex scalar field in asymptotic anti-de Sitter (AdS) spacetime. Below critical temperature Tc, the planar Reissner-Nordström-AdS black hole is unstable due to the near-horizon scalar condensation instability. We study the full nonlinear development of this instability by numerically solving the gravitational dynamics in the asymptotic AdS spacetime, and observe a dynamical process from the perturbed Reissner-Nordström-AdS black hole to a hairy black hole when the initial black hole temperature T dynamical process is then holographically dual to the dynamical superconducting phase transition process in the boundary theory. Furthermore, we also study the effect of the scalar self-interaction on time evolution of superconducting condensate operator, event and apparent horizon areas of the final hairy black hole.

Dynamic Optical Tuning of Interlayer Interactions in the Transition Metal Dichalcogenides

DOE PAGES

Mannebach, Ehren M.; Nyby, Clara; Ernst, Friederike; ...

2017-11-09

Modulation of weak interlayer interactions between quasi-two-dimensional atomic planes in the transition metal dichalcogenides (TMDCs) provides avenues for tuning their functional properties. Here we show that above-gap optical excitation in the TMDCs leads to an unexpected large-amplitude, ultrafast compressive force between the two-dimensional layers, as probed by in situ measurements of the atomic layer spacing at femtosecond time resolution. We show that this compressive response arises from a dynamic modulation of the interlayer van der Waals interaction and that this represents the dominant light-induced stress at low excitation densities. A simple analytic model predicts the magnitude and carrier density dependencemore » of the measured strains. Furthermore, this work establishes a new method for dynamic, nonequilibrium tuning of correlation-driven dispersive interactions and of the optomechanical functionality of TMDC quasi-two-dimensional materials.« less

Modeled interactive effects of precipitation, temperature, and [CO2] on ecosystem carbon and water dynamics in different climatic zones

Treesearch

Yiqi Luo; Dieter Gerten; Guerric Le Maire; William J. Parton; Ensheng Weng; Xuhui Zhou; Cindy Keough; Claus Beier; Philippe Ciais; Wolfgang Cramer; Jeffrey S. Dukes; Bridget Emmett; Paul J. Hanson; Alan Knapp; Sune Linder; Dan Nepstad; Lindsey. Rustad

2008-01-01

Interactive effects of multiple global change factors on ecosystem processes are complex. It is relatively expensive to explore those interactions in manipulative experiments. We conducted a modeling analysis to identify potentially important interactions and to stimulate hypothesis formulation for experimental research. Four models were used to quantify interactive...

Brain-to-Brain Synchrony Tracks Real-World Dynamic Group Interactions in the Classroom.

PubMed

Dikker, Suzanne; Wan, Lu; Davidesco, Ido; Kaggen, Lisa; Oostrik, Matthias; McClintock, James; Rowland, Jess; Michalareas, Georgios; Van Bavel, Jay J; Ding, Mingzhou; Poeppel, David

2017-05-08

The human brain has evolved for group living [1]. Yet we know so little about how it supports dynamic group interactions that the study of real-world social exchanges has been dubbed the "dark matter of social neuroscience" [2]. Recently, various studies have begun to approach this question by comparing brain responses of multiple individuals during a variety of (semi-naturalistic) tasks [3-15]. These experiments reveal how stimulus properties [13], individual differences [14], and contextual factors [15] may underpin similarities and differences in neural activity across people. However, most studies to date suffer from various limitations: they often lack direct face-to-face interaction between participants, are typically limited to dyads, do not investigate social dynamics across time, and, crucially, they rarely study social behavior under naturalistic circumstances. Here we extend such experimentation drastically, beyond dyads and beyond laboratory walls, to identify neural markers of group engagement during dynamic real-world group interactions. We used portable electroencephalogram (EEG) to simultaneously record brain activity from a class of 12 high school students over the course of a semester (11 classes) during regular classroom activities (Figures 1A-1C; Supplemental Experimental Procedures, section S1). A novel analysis technique to assess group-based neural coherence demonstrates that the extent to which brain activity is synchronized across students predicts both student class engagement and social dynamics. This suggests that brain-to-brain synchrony is a possible neural marker for dynamic social interactions, likely driven by shared attention mechanisms. This study validates a promising new method to investigate the neuroscience of group interactions in ecologically natural settings. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Dynamic characterization of contact interactions of micro-robotic leg structures

NASA Astrophysics Data System (ADS)

Ryou, Jeong Hoon; Oldham, Kenn Richard

2014-05-01

Contact dynamics of microelectromechanical systems (MEMS) are typically complicated and it is consequently difficult to model all dynamic characteristics observed in time-domain responses involving impact. This issue becomes worse when a device, such as a mobile micro-robot, is not clamped to a substrate and has a complex mechanical structure. To characterize such a contact interaction situation, two walking micro-robot prototypes are tested having intentionally simple structures with different dimensions (21.2 mm × 16.3 mm × 0.75 mm and 32 mm × 25.4 mm × 4.1 mm) and weights (0.16 and 2.7 g). Contact interaction behaviors are characterized by analyzing experimental data under various excitation signals. A numerical approach was used to derive a novel contact model consisting of a coefficient of restitution matrix that uses modal vibration information. Experimental validation of the simulation model shows that it captures various dynamic features of the contact interaction when simulating leg behavior more accurately than previous contact models, such as single-point coefficient of restitution or compliant ground models. In addition, this paper shows that small-scale forces can be added to the simulation to improve model accuracy, resulting in average errors across driving conditions on the order of 2-6% for bounce frequency, maximum foot height, and average foot height, although there is substantial variation from case to case.

Dynamical control of electron-phonon interactions with high-frequency light

NASA Astrophysics Data System (ADS)

Dutreix, C.; Katsnelson, M. I.

2017-01-01

This work addresses the one-dimensional problem of Bloch electrons when they are rapidly driven by a homogeneous time-periodic light and linearly coupled to vibrational modes. Starting from a generic time-periodic electron-phonon Hamiltonian, we derive a time-independent effective Hamiltonian that describes the stroboscopic dynamics up to the third order in the high-frequency limit. This yields nonequilibrium corrections to the electron-phonon coupling that are controllable dynamically via the driving strength. This shows in particular that local Holstein interactions in equilibrium are corrected by antisymmetric Peierls interactions out of equilibrium, as well as by phonon-assisted hopping processes that make the dynamical Wannier-Stark localization of Bloch electrons impossible. Subsequently, we revisit the Holstein polaron problem out of equilibrium in terms of effective Green's functions, and specify explicitly how the binding energy and effective mass of the polaron can be controlled dynamically. These tunable properties are reported within the weak- and strong-coupling regimes since both can be visited within the same material when varying the driving strength. This work provides some insight into controllable microscopic mechanisms that may be involved during the multicycle laser irradiations of organic molecular crystals in ultrafast pump-probe experiments, although it should also be suitable for realizations in shaken optical lattices of ultracold atoms.

Dynamic nuclear protein interactions investigated using fluorescence lifetime and fluorescence fluctuation spectroscopy

NASA Astrophysics Data System (ADS)

Siegel, Amanda P.; Hays, Nicole M.; Day, Richard N.

2012-03-01

The discovery and engineering of novel fluorescent proteins (FPs) from diverse organisms is yielding fluorophores with exceptional characteristics for live-cell imaging. In particular, the development of FPs for Förster resonance energy transfer (FRET) microscopy and fluorescence fluctuation spectroscopy (FFS) provide important tools for monitoring dynamic protein interactions inside living cells. Fluorescence lifetime imaging microscopy (FLIM) quantitatively maps changes in the spatial distribution of donor FP lifetimes that result from FRET with acceptor FPs. FFS probes dynamic protein associations through its capacity to monitor localized protein diffusion. Here, we use FRET-FLIM combined with FFS in living cells to investigate changes in protein mobility due to protein-protein interactions involving transcription factors and chromatin modifying proteins that function in anterior pituitary gene regulation. The heterochromatin protein 1 alpha (HP1α) plays a key role in the establishment and maintenance of heterochromatin through its interactions with histone methyltransferases. Recent studies, however, also highlight the importance of HP1α as a positive regulator of active transcription in euchromatin. Intriguingly, we observed that the transcription factor CCAAT/enhancer-binding protein alpha (C/EBPα) interacts with HP1α in regions of pericentromeric heterochromatin in mouse pituitary cells. These observations prompted us to investigate the relationship between HP1α dynamic interactions in pituitary specific gene regulation.

Specific Non-Local Interactions Are Not Necessary for Recovering Native Protein Dynamics

PubMed Central

Dasgupta, Bhaskar; Kasahara, Kota; Kamiya, Narutoshi; Nakamura, Haruki; Kinjo, Akira R.

2014-01-01

The elastic network model (ENM) is a widely used method to study native protein dynamics by normal mode analysis (NMA). In ENM we need information about all pairwise distances, and the distance between contacting atoms is restrained to the native value. Therefore ENM requires O(N2) information to realize its dynamics for a protein consisting of N amino acid residues. To see if (or to what extent) such a large amount of specific structural information is required to realize native protein dynamics, here we introduce a novel model based on only O(N) restraints. This model, named the ‘contact number diffusion’ model (CND), includes specific distance restraints for only local (along the amino acid sequence) atom pairs, and semi-specific non-local restraints imposed on each atom, rather than atom pairs. The semi-specific non-local restraints are defined in terms of the non-local contact numbers of atoms. The CND model exhibits the dynamic characteristics comparable to ENM and more correlated with the explicit-solvent molecular dynamics simulation than ENM. Moreover, unrealistic surface fluctuations often observed in ENM were suppressed in CND. On the other hand, in some ligand-bound structures CND showed larger fluctuations of buried protein atoms interacting with the ligand compared to ENM. In addition, fluctuations from CND and ENM show comparable correlations with the experimental B-factor. Although there are some indications of the importance of some specific non-local interactions, the semi-specific non-local interactions are mostly sufficient for reproducing the native protein dynamics. PMID:24625758

Quantifying Wheat Sensitivities to Environmental Constraints to Dissect Genotype × Environment Interactions in the Field.

PubMed

Parent, Boris; Bonneau, Julien; Maphosa, Lance; Kovalchuk, Alex; Langridge, Peter; Fleury, Delphine

2017-07-01

Yield is subject to strong genotype-by-environment (G × E) interactions in the field, especially under abiotic constraints such as soil water deficit (drought [D]) and high temperature (heat [H]). Since environmental conditions show strong fluctuations during the whole crop cycle, geneticists usually do not consider environmental measures as quantitative variables but rather as factors in multienvironment analyses. Based on 11 experiments in a field platform with contrasting temperature and soil water deficit, we determined the periods of sensitivity to drought and heat constraints in wheat ( Triticum aestivum ) and determined the average sensitivities for major yield components. G × E interactions were separated into their underlying components, constitutive genotypic effect (G), G × D, G × H, and G × H × D, and were analyzed for two genotypes, highlighting contrasting responses to heat and drought constraints. We then tested the constitutive and responsive behaviors of two strong quantitative trait loci (QTLs) associated previously with yield components. This analysis confirmed the constitutive effect of the chromosome 1B QTL and explained the G × E interaction of the chromosome 3B QTL by a benefit of one allele when temperature rises. In addition to the method itself, which can be applied to other data sets and populations, this study will support the cloning of a major yield QTL on chromosome 3B that is highly dependent on environmental conditions and for which the climatic interaction is now quantified. © 2017 American Society of Plant Biologists. All Rights Reserved.

Dynamical analysis of yeast protein interaction network during the sake brewing process.

PubMed

Mirzarezaee, Mitra; Sadeghi, Mehdi; Araabi, Babak N

2011-12-01

Proteins interact with each other for performing essential functions of an organism. They change partners to get involved in various processes at different times or locations. Studying variations of protein interactions within a specific process would help better understand the dynamic features of the protein interactions and their functions. We studied the protein interaction network of Saccharomyces cerevisiae (yeast) during the brewing of Japanese sake. In this process, yeast cells are exposed to several stresses. Analysis of protein interaction networks of yeast during this process helps to understand how protein interactions of yeast change during the sake brewing process. We used gene expression profiles of yeast cells for this purpose. Results of our experiments revealed some characteristics and behaviors of yeast hubs and non-hubs and their dynamical changes during the brewing process. We found that just a small portion of the proteins (12.8 to 21.6%) is responsible for the functional changes of the proteins in the sake brewing process. The changes in the number of edges and hubs of the yeast protein interaction networks increase in the first stages of the process and it then decreases at the final stages.

Influence of the Location of Attractive Polymer-Pore Interactions on Translocation Dynamics.

PubMed

Ghosh, Bappa; Chaudhury, Srabanti

2018-01-11

We probe the influence of polymer-pore interactions on the translocation dynamics using Langevin dynamics simulations. We investigate the effect of the strength and location of the polymer-pore interaction using nanopores that are partially charged either at the entry or the exit or on both sides of the pore. We study the change in the translocation time as a function of the strength of the polymer-pore interaction for a given chain length and under the effect of an externally applied field. Under a moderate driving force and a chain length longer than the length of the pore, the translocation time shows a nonmonotonic increase with an increase in the attractive interaction. Also, an interaction on the cis side of the pore can increase the translocation probability. In the presence of an external field and a strong attractive force, the translocation time for shorter chains is independent of the polymer-pore interaction at the entry side of the pore, whereas an interaction on the trans side dominates the translocation process. Our simulation results are rationalized by a qualitative analysis of the free energy landscape for polymer translocation.

The Oort cloud and the Galaxy - Dynamical interactions

NASA Technical Reports Server (NTRS)

Weissman, Paul R.

1986-01-01

The results of recent dynamical studies of the Oort cloud and its interaction with the Galaxy are discussed. Various studies which used Monte Carlo simulations to investigate the evolution of comets in the Oort cloud and the manner in which they are injected into the planetary region are reviewed. Work done on perturbation of cometary orbits by stars, interstellar clouds, and the Galaxy is examined. The growing consensus that there is a massive inner Oort cloud with a population up to 100 times that of the dynamically active outer cloud is addressed. Variations on the Oort hypothesis are discussed. It is argued that speculations about the existence of a small unseen solar companion star or a tenth planet causing periodic comet showers from the inner Oort cloud are not supported by dynamical studies or analyses of the terrestrial and lunar cratering record. Evidence for Oort clouds around other stars is summarized.

Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, Upper Yangtze, China from 1975 to 2000

USGS Publications Warehouse

Zhao, Shuqing; Liu, Shuguang; Yin, Runsheng; Li, Zhengpeng; Deng, Yulin; Tan, Kun; Deng, Xiangzheng; Rothstein, David; Qi, Jiaguo; Yin, Runsheng

2009-01-01

Quantifying the spatial and temporal dynamics of carbon stocks in terrestrial ecosystems and carbon fluxes between the terrestrial biosphere and the atmosphere is critical to our understanding of regional patterns of carbon storage and loss. Here we use the General Ensemble Biogeochemical Modeling System to simulate the terrestrial ecosystem carbon dynamics in the Jinsha watershed of China's upper Yangtze basin from 1975 to 2000, based on unique combinations of spatial and temporal dynamics of major driving forces, such as climate, soil properties, nitrogen deposition, and land use and land cover changes. Our analysis demonstrates that the Jinsha watershed ecosystems acted as a carbon sink during the period of 1975–2000, with an average rate of 0.36 Mg/ha/yr, primarily resulting from regional climate variation and local land use and land cover change. Vegetation biomass accumulation accounted for 90.6% of the sink, while soil organic carbon loss before 1992 led to lower net gain of carbon in the watershed, and after that soils became a small sink. Ecosystem carbon sinks/source pattern showed a high degree of spatial heterogeneity, Carbon sinks were associated with forest areas without disturbances, whereas carbon Sources were primarily caused by stand-replacing disturbances. This highlights the importance of land-use history in determining the regional carbon sinks/source pattern.

Evolution of scalar and velocity dynamics in planar shock-turbulence interaction

NASA Astrophysics Data System (ADS)

Boukharfane, R.; Bouali, Z.; Mura, A.

2018-01-01

Due to the short residence time of air in supersonic combustors, achieving efficient mixing in compressible turbulent reactive flows is crucial for the design of supersonic ramjet (Scramjet) engines. In this respect, improving the understanding of shock-scalar mixing interactions is of fundamental importance for such supersonic combustion applications. In these compressible flows, the interaction between the turbulence and the shock wave is reciprocal, and the coupling between them is very strong. A basic understanding of the physics of such complex interactions has already been obtained through the analysis of relevant simplified flow configurations, including propagation of the shock wave in density-stratified media, shock-wave-mixing-layer interaction, and shock-wave-vortex interaction. Amplification of velocity fluctuations and substantial changes in turbulence characteristic length scales are the most well-known outcomes of shock-turbulence interaction, which may also deeply influence scalar mixing between fuel and oxidizer. The effects of the shock wave on the turbulence have been widely characterized through the use of so-called amplification factors, and similar quantities are introduced herein to characterize the influence of the shock wave on scalar mixing. One of the primary goals of the present study is indeed to extend previous analyses to the case of shock-scalar mixing interaction, which is directly relevant to supersonic combustion applications. It is expected that the shock wave will affect the scalar dissipation rate (SDR) dynamics. Special emphasis is placed on the modification of the so-called turbulence-scalar interaction as a leading-order contribution to the production of mean SDR, i.e., a quantity that defines the mixing rate and efficiency. To the best of the authors' knowledge, this issue has never been addressed in detail in the literature, and the objective of the present study is to scrutinize this influence. The turbulent mixing of a

Three-wave resonant interactions: Multi-dark-dark-dark solitons, breathers, rogue waves, and their interactions and dynamics

NASA Astrophysics Data System (ADS)

Zhang, Guoqiang; Yan, Zhenya; Wen, Xiao-Yong

2018-03-01

We investigate three-wave resonant interactions through both the generalized Darboux transformation method and numerical simulations. Firstly, we derive a simple multi-dark-dark-dark-soliton formula through the generalized Darboux transformation. Secondly, we use the matrix analysis method to avoid the singularity of transformed potential functions and to find the general nonsingular breather solutions. Moreover, through a limit process, we deduce the general rogue wave solutions and give a classification by their dynamics including bright, dark, four-petals, and two-peaks rogue waves. Ever since the coexistence of dark soliton and rogue wave in non-zero background, their interactions naturally become a quite appealing topic. Based on the N-fold Darboux transformation, we can derive the explicit solutions to depict their interactions. Finally, by performing extensive numerical simulations we can predict whether these dark solitons and rogue waves are stable enough to propagate. These results can be available for several physical subjects such as fluid dynamics, nonlinear optics, solid state physics, and plasma physics.

Merging Disparate Data and Numerical Model Results for Dynamically Constrained Nowcasts

DTIC Science & Technology

1999-09-30

of Delaware Newark, DE 19716 phone: (302) 831-6836 fax: (302) 831-6838 email: brucel @udel.edu Award #: N000149910052 http://newark.cms.udel.edu... brucel /hrd.html LONG-TERM GOALS The long term goal of our research is to quantify submesoscale dynamical processes and understand their interactions

Species interactions may help explain the erratic periodicity of whooping cough dynamics.

PubMed

Bhattacharyya, Samit; Ferrari, Matthew J; Bjørnstad, Ottar N

2017-12-14

Incidence of whooping cough exhibits variable dynamics across time and space. The periodicity of this disease varies from annual to five years in different geographic regions in both developing and developed countries. Many hypotheses have been put forward to explain this variability such as nonlinearity and seasonality, stochasticity, variable recruitment of susceptible individuals via birth, immunization, and immune boosting. We propose an alternative hypothesis to describe the variability in periodicity - the intricate dynamical variability of whooping cough may arise from interactions between its dominant etiological agents of Bordetella pertussis and Bordetella parapertussis. We develop a two-species age-structured model, where two pathogens are allowed to interact by age-dependent convalescence of individuals with severe illness from infections. With moderate strength of interactions, the model exhibits multi-annual coexisting attractors that depend on the R 0 of the two pathogens. We also examine how perturbation from case importation and noise in transmission may push the system from one dynamical regime to another. The coexistence of multi-annual cycles and the behavior of switching between attractors suggest that variable dynamics of whopping cough could be an emergent property of its multi-agent etiology. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Plasma Interaction and Energetic Particle Dynamics near Callisto

NASA Astrophysics Data System (ADS)

Liuzzo, L.; Simon, S.; Feyerabend, M.; Motschmann, U. M.

2017-12-01

Callisto's magnetic environment is characterized by a complex admixture of induction signals from its conducting subsurface ocean, the interaction of corotating Jovian magnetospheric plasma with the moon's ionosphere and induced dipole, and the non-linear coupling between the effects. In contrast to other Galilean moons, ion gyroradii near Callisto are comparable to its size, requiring a kinetic treatment of the interaction region near the moon. Thus, we apply the hybrid simulation code AIKEF to constrain the competing effects of plasma interaction and induction. We determine their influence on the magnetic field signatures measured by Galileo during various Callisto flybys. We use the magnetic field calculated by the model to investigate energetic particle dynamics and their effect on Callisto's environment. From this, we provide a map of global energetic particle precipitation onto Callisto's surface, which may contribute to the generation of its atmosphere.

Nonlinear dynamics of resonant electrons interacting with coherent Langmuir waves

NASA Astrophysics Data System (ADS)

Tobita, Miwa; Omura, Yoshiharu

2018-03-01

We study the nonlinear dynamics of resonant particles interacting with coherent waves in space plasmas. Magnetospheric plasma waves such as whistler-mode chorus, electromagnetic ion cyclotron waves, and hiss emissions contain coherent wave structures with various discrete frequencies. Although these waves are electromagnetic, their interaction with resonant particles can be approximated by equations of motion for a charged particle in a one-dimensional electrostatic wave. The equations are expressed in the form of nonlinear pendulum equations. We perform test particle simulations of electrons in an electrostatic model with Langmuir waves and a non-oscillatory electric field. We solve equations of motion and study the dynamics of particles with different values of inhomogeneity factor S defined as a ratio of the non-oscillatory electric field intensity to the wave amplitude. The simulation results demonstrate deceleration/acceleration, thermalization, and trapping of particles through resonance with a single wave, two waves, and multiple waves. For two-wave and multiple-wave cases, we describe the wave-particle interaction as either coherent or incoherent based on the probability of nonlinear trapping.

Dynamic interactions of proteins in complex networks

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

Appella, E.; Anderson, C.

2009-10-01

Recent advances in techniques such as NMR and EPR spectroscopy have enabled the elucidation of how proteins undergo structural changes to act in concert in complex networks. The three minireviews in this series highlight current findings and the capabilities of new methodologies for unraveling the dynamic changes controlling diverse cellular functions. They represent a sampling of the cutting-edge research presented at the 17th Meeting of Methods in Protein Structure Analysis, MPSA2008, in Sapporo, Japan, 26-29 August, 2008 (http://www.iapsap.bnl.gov). The first minireview, by Christensen and Klevit, reports on a structure-based yeast two-hybrid method for identifying E2 ubiquitin-conjugating enzymes that interact withmore » the E3 BRCA1/BARD1 heterodimer ligase to generate either mono- or polyubiquitinated products. This method demonstrated for the first time that the BRCA1/BARD1 E3 can interact with 10 different E2 enzymes. Interestingly, the interaction with multiple E2 enzymes displayed unique ubiquitin-transfer properties, a feature expected to be common among other RING and U-box E3s. Further characterization of new E3 ligases and the E2 enzymes that interact with them will greatly enhance our understanding of ubiquitin transfer and facilitate studies of roles of ubiquitin and ubiquitin-like proteins in protein processing and trafficking. Stein et al., in the second minireview, describe recent progress in defining the binding specificity of different peptide-binding domains. The authors clearly point out that transient peptide interactions mediated by both post-translational modifications and disordered regions ensure a high level of specificity. They postulate that a regulatory code may dictate the number of combinations of domains and post-translational modifications needed to achieve the required level of interaction specificity. Moreover, recognition alone is not enough to obtain a stable complex, especially in a complex cellular environment. Increasing

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

Orientational dynamics and dye-DNA interactions in a dye-labeled DNA aptamer.

PubMed

Unruh, Jay R; Gokulrangan, Giridharan; Lushington, G H; Johnson, Carey K; Wilson, George S

2005-05-01

We report the picosecond and nanosecond timescale rotational dynamics of a dye-labeled DNA oligonucleotide or "aptamer" designed to bind specifically to immunoglobulin E. Rotational dynamics in combination with fluorescence lifetime measurements provide information about dye-DNA interactions. Comparison of Texas Red (TR), fluorescein, and tetramethylrhodamine (TAMRA)-labeled aptamers reveals surprising differences with significant implications for biophysical studies employing such conjugates. Time-resolved anisotropy studies demonstrate that the TR- and TAMRA-aptamer anisotropy decays are dominated by the overall rotation of the aptamer, whereas the fluorescein-aptamer anisotropy decay displays a subnanosecond rotational correlation time much shorter than that expected for the overall rotation of the aptamer. Docking and molecular dynamics simulations suggest that the low mobility of TR is a result of binding in the groove of the DNA helix. Additionally, associated anisotropy analysis of the TAMRA-aptamer reveals both quenched and unquenched states that experience significant coupling to the DNA motion. Therefore, quenching of TAMRA by guanosine must depend on the configuration of the dye bound to the DNA. The strong coupling of TR to the rotational dynamics of the DNA aptamer, together with the absence of quenching of its fluorescence by DNA, makes it a good probe of DNA orientational dynamics. The understanding of the nature of dye-DNA interactions provides the basis for the development of bioconjugates optimized for specific biophysical measurements and is important for the sensitivity of anisotropy-based DNA-protein interaction studies employing such conjugates.

Orientational Dynamics and Dye-DNA Interactions in a Dye-Labeled DNA Aptamer

PubMed Central

Unruh, Jay R.; Gokulrangan, Giridharan; Lushington, G. H.; Johnson, Carey K.; Wilson, George S.

2005-01-01

We report the picosecond and nanosecond timescale rotational dynamics of a dye-labeled DNA oligonucleotide or “aptamer” designed to bind specifically to immunoglobulin E. Rotational dynamics in combination with fluorescence lifetime measurements provide information about dye-DNA interactions. Comparison of Texas Red (TR), fluorescein, and tetramethylrhodamine (TAMRA)-labeled aptamers reveals surprising differences with significant implications for biophysical studies employing such conjugates. Time-resolved anisotropy studies demonstrate that the TR- and TAMRA-aptamer anisotropy decays are dominated by the overall rotation of the aptamer, whereas the fluorescein-aptamer anisotropy decay displays a subnanosecond rotational correlation time much shorter than that expected for the overall rotation of the aptamer. Docking and molecular dynamics simulations suggest that the low mobility of TR is a result of binding in the groove of the DNA helix. Additionally, associated anisotropy analysis of the TAMRA-aptamer reveals both quenched and unquenched states that experience significant coupling to the DNA motion. Therefore, quenching of TAMRA by guanosine must depend on the configuration of the dye bound to the DNA. The strong coupling of TR to the rotational dynamics of the DNA aptamer, together with the absence of quenching of its fluorescence by DNA, makes it a good probe of DNA orientational dynamics. The understanding of the nature of dye-DNA interactions provides the basis for the development of bioconjugates optimized for specific biophysical measurements and is important for the sensitivity of anisotropy-based DNA-protein interaction studies employing such conjugates. PMID:15731389

Observation of Water-Protein Interaction Dynamics with Broadband Two-Dimensional Infrared Spectroscopy

NASA Astrophysics Data System (ADS)

De Marco, Luigi; Haky, Andrew; Tokmakoff, Andrei

Two-dimensional infrared (2D IR) spectroscopy has proven itself an indispensable tool for studying molecular dynamics and intermolecular interactions on ultrafast timescales. Using a novel source of broadband mid-IR pulses, we have collected 2D IR spectra of protein films at varying levels of hydration. With 2D IR, we can directly observe coupling between water's motions and the protein's. Protein films provide us with the ability to discriminate hydration waters from bulk water and thus give us access to studying water dynamics along the protein backbone, fluctuations in the protein structure, and the interplay between the molecular dynamics of the two. We present two representative protein films: poly-L-proline (PLP) and hen egg-white lysozyme (HEWL). Having no N-H groups, PLP allows us to look at water dynamics without interference from resonant energy transfer between the protein N-H stretch and the water O-H stretch. We conclude that at low hydration levels water-protein interactions dominate, and the water's dynamics are tied to those of the protein. In HEWL films, we take advantage of the robust secondary structure to partially deuterate the film, allowing us to spectrally distinguish the protein core from the exterior. From this, we show that resonant energy transfer to water provides an effective means of dissipating excess energy within the protein, while maintaining the structure. These methods are general and can easily be extended to studying specific protein-water interactions.

The Dynamics of Social Interaction in Telecollaborative Tandem Exchanges

ERIC Educational Resources Information Center

Janssen Sanchez, Brianna

2015-01-01

Using both quantitative and qualitative methods of inquiry, this dissertation study undertakes an exploration of the dynamics of the social interaction in discourse co-constructed by pairs of college students in telecollaborative tandem exchanges. Two groups of participants, Mexican learners of English as a foreign language and American learners…

Dynamics of tandem bubble interaction in a microfluidic channel

PubMed Central

Yuan, Fang; Sankin, Georgy; Zhong, Pei

2011-01-01

The dynamics of tandem bubble interaction in a microfluidic channel (800 × 21 μm, W × H) have been investigated using high-speed photography, with resultant fluid motion characterized by particle imaging velocimetry. A single or tandem bubble is produced reliably via laser absorption by micron-sized gold dots (6 μm in diameter with 40 μm in separation distance) coated on a glass surface of the microfluidic channel. Using two pulsed Nd:YAG lasers at λ = 1064 nm and ∼10 μJ/pulse, the dynamics of tandem bubble interaction (individual maximum bubble diameter of 50 μm with a corresponding collapse time of 5.7 μs) are examined at different phase delays. In close proximity (i.e., interbubble distance = 40 μm or γ = 0.8), the tandem bubbles interact strongly with each other, leading to asymmetric deformation of the bubble walls and jet formation, as well as the production of two pairs of vortices in the surrounding fluid rotating in opposite directions. The direction and speed of the jet (up to 95 m/s), as well as the orientation and strength of the vortices can be varied by adjusting the phase delay. PMID:22088007

Dynamics of tandem bubble interaction in a microfluidic channel.

PubMed

Yuan, Fang; Sankin, Georgy; Zhong, Pei

2011-11-01

The dynamics of tandem bubble interaction in a microfluidic channel (800  ×  21 μm, W × H) have been investigated using high-speed photography, with resultant fluid motion characterized by particle imaging velocimetry. A single or tandem bubble is produced reliably via laser absorption by micron-sized gold dots (6 μm in diameter with 40 μm in separation distance) coated on a glass surface of the microfluidic channel. Using two pulsed Nd:YAG lasers at λ = 1064 nm and ∼10 μJ/pulse, the dynamics of tandem bubble interaction (individual maximum bubble diameter of 50 μm with a corresponding collapse time of 5.7 μs) are examined at different phase delays. In close proximity (i.e., interbubble distance = 40 μm or γ = 0.8), the tandem bubbles interact strongly with each other, leading to asymmetric deformation of the bubble walls and jet formation, as well as the production of two pairs of vortices in the surrounding fluid rotating in opposite directions. The direction and speed of the jet (up to 95 m/s), as well as the orientation and strength of the vortices can be varied by adjusting the phase delay.

Mirroring and beyond: coupled dynamics as a generalized framework for modelling social interactions

PubMed Central

Hasson, Uri; Frith, Chris D.

2016-01-01

When people observe one another, behavioural alignment can be detected at many levels, from the physical to the mental. Likewise, when people process the same highly complex stimulus sequences, such as films and stories, alignment is detected in the elicited brain activity. In early sensory areas, shared neural patterns are coupled to the low-level properties of the stimulus (shape, motion, volume, etc.), while in high-order brain areas, shared neural patterns are coupled to high-levels aspects of the stimulus, such as meaning. Successful social interactions require such alignments (both behavioural and neural), as communication cannot occur without shared understanding. However, we need to go beyond simple, symmetric (mirror) alignment once we start interacting. Interactions are dynamic processes, which involve continuous mutual adaptation, development of complementary behaviour and division of labour such as leader–follower roles. Here, we argue that interacting individuals are dynamically coupled rather than simply aligned. This broader framework for understanding interactions can encompass both processes by which behaviour and brain activity mirror each other (neural alignment), and situations in which behaviour and brain activity in one participant are coupled (but not mirrored) to the dynamics in the other participant. To apply these more sophisticated accounts of social interactions to the study of the underlying neural processes we need to develop new experimental paradigms and novel methods of data analysis PMID:27069044

Quantifying suspended sediment dynamics in mega deltas using remote sensing data: A case study of the Mekong floodplains

NASA Astrophysics Data System (ADS)

Dang, Thanh Duc; Cochrane, Thomas A.; Arias, Mauricio E.

2018-06-01

Temporal and spatial concentrations of suspended sediment in floodplains are difficult to quantify because in situ measurements can be logistically complex, time consuming and costly. In this research, satellite imagery with long temporal and large spatial coverage (Landsat TM/ETM+) was used to complement in situ suspended sediment measurements to reflect sediment dynamics in a large (70,000 km2) floodplain. Instead of using a single spectral band from Landsat, a Principal Component Analysis was applied to obtain uncorrelated reflectance values for five bands of Landsat TM/ETM+. Significant correlations between the scores of the 1st principal component and the values of continuously gauged suspended sediment concentration, shown via high coefficients of determination of sediment rating curves (R2 ranging from 0.66 to 0.92), permit the application of satellite images to quantify spatial and temporal sediment variation in the Mekong floodplains. Estimated suspended sediment maps show that hydraulic regimes at Chaktomuk (Cambodia), where the Mekong, Bassac, and Tonle Sap rivers diverge, determine the amount of seasonal sediment supplies to the Mekong Delta. The development of flood prevention systems to allow for three rice crops a year in the Vietnam Mekong Delta significantly reduces localized flooding, but also prevents sediment (source of nutrients) from entering fields. A direct consequence of this is the need to apply more artificial fertilizers to boost agricultural productivity, which may trigger environmental problems. Overall, remote sensing is shown to be an effective tool to understand temporal and spatial sediment dynamics in large floodplains.

Spin dynamics in helical molecules with nonlinear interactions

NASA Astrophysics Data System (ADS)

Díaz, E.; Albares, P.; Estévez, P. G.; Cerveró, J. M.; Gaul, C.; Diez, E.; Domínguez-Adame, F.

2018-04-01

It is widely admitted that the helical conformation of certain chiral molecules may induce a sizable spin selectivity observed in experiments. Spin selectivity arises as a result of the interplay between a helicity-induced spin–orbit coupling (SOC) and electric dipole fields in the molecule. From the theoretical point of view, different phenomena might affect the spin dynamics in helical molecules, such as quantum dephasing, dissipation and the role of metallic contacts. With a few exceptions, previous studies usually neglect the local deformation of the molecule about the carrier, but this assumption seems unrealistic to describe charge transport in molecular systems. We introduce an effective model describing the electron spin dynamics in a deformable helical molecule with weak SOC. We find that the electron–lattice interaction allows the formation of stable solitons such as bright solitons with well defined spin projection onto the molecule axis. We present a thorough study of these bright solitons and analyze their possible impact on the spin dynamics in deformable helical molecules.

Quantified Facial Soft-tissue Strain in Animation Measured by Real-time Dynamic 3-Dimensional Imaging.

PubMed

Hsu, Vivian M; Wes, Ari M; Tahiri, Youssef; Cornman-Homonoff, Joshua; Percec, Ivona

2014-09-01

The aim of this study is to evaluate and quantify dynamic soft-tissue strain in the human face using real-time 3-dimensional imaging technology. Thirteen subjects (8 women, 5 men) between the ages of 18 and 70 were imaged using a dual-camera system and 3-dimensional optical analysis (ARAMIS, Trilion Quality Systems, Pa.). Each subject was imaged at rest and with the following facial expressions: (1) smile, (2) laughter, (3) surprise, (4) anger, (5) grimace, and (6) pursed lips. The facial strains defining stretch and compression were computed for each subject and compared. The areas of greatest strain were localized to the midface and lower face for all expressions. Subjects over the age of 40 had a statistically significant increase in stretch in the perioral region while lip pursing compared with subjects under the age of 40 (58.4% vs 33.8%, P = 0.015). When specific components of lip pursing were analyzed, there was a significantly greater degree of stretch in the nasolabial fold region in subjects over 40 compared with those under 40 (61.6% vs 32.9%, P = 0.007). Furthermore, we observed a greater degree of asymmetry of strain in the nasolabial fold region in the older age group (18.4% vs 5.4%, P = 0.03). This pilot study illustrates that the face can be objectively and quantitatively evaluated using dynamic major strain analysis. The technology of 3-dimensional optical imaging can be used to advance our understanding of facial soft-tissue dynamics and the effects of animation on facial strain over time.

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

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

Breath-by-breath analysis of cardiorespiratory interaction for quantifying developmental maturity in premature infants

PubMed Central

Rusin, Craig G.; Hudson, John L.; Lee, Hoshik; Delos, John B.; Guin, Lauren E.; Vergales, Brooke D.; Paget-Brown, Alix; Kattwinkel, John; Lake, Douglas E.; Moorman, J. Randall

2012-01-01

In healthy neonates, connections between the heart and lungs through brain stem chemosensory pathways and the autonomic nervous system result in cardiorespiratory synchronization. This interdependence between cardiac and respiratory dynamics can be difficult to measure because of intermittent signal quality in intensive care settings and variability of heart and breathing rates. We employed a phase-based measure suggested by Schäfer and coworkers (Schäfer C, Rosenblum MG, Kurths J, Abel HH. Nature 392: 239–240, 1998) to obtain a breath-by-breath analysis of cardiorespiratory interaction. This measure of cardiorespiratory interaction does not distinguish between cardiac control of respiration associated with cardioventilatory coupling and respiratory influences on the heart rate associated with respiratory sinus arrhythmia. We calculated, in sliding 4-min windows, the probability density of heartbeats as a function of the concurrent phase of the respiratory cycle. Probability density functions whose Shannon entropy had a <0.1% chance of occurring from random numbers were classified as exhibiting interaction. In this way, we analyzed 18 infant-years of data from 1,202 patients in the Neonatal Intensive Care Unit at University of Virginia. We found evidence of interaction in 3.3 patient-years of data (18%). Cardiorespiratory interaction increased several-fold with postnatal development, but, surprisingly, the rate of increase was not affected by gestational age at birth. We find evidence for moderate correspondence between this measure of cardiorespiratory interaction and cardioventilatory coupling and no evidence for respiratory sinus arrhythmia, leading to the need for further investigation of the underlying mechanism. Such continuous measures of physiological interaction may serve to gauge developmental maturity in neonatal intensive care patients and prove useful in decisions about incipient illness and about hospital discharge. PMID:22174403

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.

Dynamic interaction of monowheel inclined vehicle-vibration platform coupled system with quadratic and cubic nonlinearities

NASA Astrophysics Data System (ADS)

Zhou, Shihua; Song, Guiqiu; Sun, Maojun; Ren, Zhaohui; Wen, Bangchun

2018-01-01

In order to analyze the nonlinear dynamics and stability of a novel design for the monowheel inclined vehicle-vibration platform coupled system (MIV-VPCS) with intermediate nonlinearity support subjected to a harmonic excitation, a multi-degree of freedom lumped parameter dynamic model taking into account the dynamic interaction of the MIV-VPCS with quadratic and cubic nonlinearities is presented. The dynamical equations of the coupled system are derived by applying the displacement relationship, interaction force relationship at the contact position and Lagrange's equation, which are further discretized into a set of nonlinear ordinary differential equations with coupled terms by Galerkin's truncation. Based on the mathematical model, the coupled multi-body nonlinear dynamics of the vibration system is investigated by numerical method, and the parameters influences of excitation amplitude, mass ratio and inclined angle on the dynamic characteristics are precisely analyzed and discussed by bifurcation diagram, Largest Lyapunov exponent and 3-D frequency spectrum. Depending on different ranges of system parameters, the results show that the different motions and jump discontinuity appear, and the coupled system enters into chaotic behavior through different routes (period-doubling bifurcation, inverse period-doubling bifurcation, saddle-node bifurcation and Hopf bifurcation), which are strongly attributed to the dynamic interaction of the MIV-VPCS. The decreasing excitation amplitude and inclined angle could reduce the higher order bifurcations, and effectively control the complicated nonlinear dynamic behaviors under the perturbation of low rotational speed. The first bifurcation and chaotic motion occur at lower value of inclined angle, and the chaotic behavior lasts for larger intervals with higher rotational speed. The investigation results could provide a better understanding of the nonlinear dynamic behaviors for the dynamic interaction of the MIV-VPCS.

The structure and dynamics of interactive documents

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

Rocha, J.T.

1999-04-01

Advances in information technology continue to accelerate as the new millennium approaches. With these advances, electronic information management is becoming increasingly important and is now supported by a seemingly bewildering array of hardware and software whose sole purpose is the design and implementation of interactive documents employing multimedia applications. Multimedia memory and storage applications such as Compact Disk-Read Only Memory (CD-ROMs) are already a familiar interactive tool in both the entertainment and business sectors. Even home enthusiasts now have the means at their disposal to design and produce CD-ROMs. More recently, Digital Video Disk (DVD) technology is carving its ownmore » niche in these markets and may (once application bugs are corrected and prices are lowered) eventually supplant CD-ROM technology. CD-ROM and DVD are not the only memory and storage applications capable of supporting interactive media. External, high-capacity drives and disks such as the Iomega{copyright} zip{reg_sign} and jaz{reg_sign} are also useful platforms for launching interactive documents without the need for additional hardware such as CD-ROM burners and copiers. The main drawback here, however, is the relatively high unit price per disk when compared to the unit cost of CD-ROMs. Regardless of the application chosen, there are fundamental structural characteristics that must be considered before effective interactive documents can be created. Additionally, the dynamics of interactive documents employing hypertext links are unique and bear only slight resemblance to those of their traditional hard-copy counterparts. These two considerations form the essential content of this paper.« less

QUANTIFYING LOAD-INDUCED SOLUTE TRANSPORT AND SOLUTE-MATRIX INTERACTIONS WITHIN THE OSTEOCYTE LACUNAR-CANALICULAR SYSTEM

PubMed Central

Wang, Bin; Zhou, Xiaozhou; Price, Christopher; Li, Wen; Pan, Jun; Wang, Liyun

2012-01-01

Osteocytes, the most abundant cells in bone, are critical in maintaining tissue homeostasis and orchestrating bone’s mechanical adaptation. Osteocytes depend upon load-induced convection within the lacunar-canalicular system (LCS) to maintain viability and to sense their mechanical environment. Using the fluorescence recovery after photobleaching (FRAP) imaging approach, we previously quantified the convection of a small tracer (sodium fluorescein, 376Da) in the murine tibial LCS for an intermittent cyclic loading (Price et al., 2011. JBMR 26:277-85). In the present study we first expanded the investigation of solute transport using a larger tracer (parvalbumin, 12.3kDa), which is comparable in size to some signaling proteins secreted by osteocytes. Murine tibiae were subjected to sequential FRAP tests under rest-inserted cyclic loading while the loading magnitude (0, 2.8, or 4.8N) and frequency (0.5, 1, or 2 Hz) were varied. The characteristic transport rate k and the transport enhancement relative to diffusion (k/k0) were measured under each loading condition, from which the peak solute velocity in the LCS was derived using our LCS transport model. Both the transport enhancement and solute velocity increased with loading magnitude and decreased with loading frequency. Furthermore, the solute-matrix interactions, quantified in terms of the reflection coefficient through the osteocytic pericellular matrix (PCM), were measured and theoretically modeled. The reflection coefficient of parvalbumin (σ=0.084) was derived from the differential fluid and solute velocities within loaded bone. Using a newly developed PCM sieving model, the PCM’s fiber configurations accounting for the measured interactions were obtained for the first time. The present study provided not only new data on the micro-fluidic environment experienced by osteocytes in situ, but also a powerful quantitative tool for future study of the PCM, the critical interface that controls both outside

Dynamic Modularity of Host Protein Interaction Networks in Salmonella Typhi Infection

PubMed Central

Dhal, Paltu Kumar; Barman, Ranjan Kumar; Saha, Sudipto; Das, Santasabuj

2014-01-01

Background Salmonella Typhi is a human-restricted pathogen, which causes typhoid fever and remains a global health problem in the developing countries. Although previously reported host expression datasets had identified putative biomarkers and therapeutic targets of typhoid fever, the underlying molecular mechanism of pathogenesis remains incompletely understood. Methods We used five gene expression datasets of human peripheral blood from patients suffering from S. Typhi or other bacteremic infections or non-infectious disease like leukemia. The expression datasets were merged into human protein interaction network (PIN) and the expression correlation between the hubs and their interacting proteins was measured by calculating Pearson Correlation Coefficient (PCC) values. The differences in the average PCC for each hub between the disease states and their respective controls were calculated for studied datasets. The individual hubs and their interactors with expression, PCC and average PCC values were treated as dynamic subnetworks. The hubs that showed unique trends of alterations specific to S. Typhi infection were identified. Results We identified S. Typhi infection-specific dynamic subnetworks of the host, which involve 81 hubs and 1343 interactions. The major enriched GO biological process terms in the identified subnetworks were regulation of apoptosis and biological adhesions, while the enriched pathways include cytokine signalling in the immune system and downstream TCR signalling. The dynamic nature of the hubs CCR1, IRS2 and PRKCA with their interactors was studied in detail. The difference in the dynamics of the subnetworks specific to S. Typhi infection suggests a potential molecular model of typhoid fever. Conclusions Hubs and their interactors of the S. Typhi infection-specific dynamic subnetworks carrying distinct PCC values compared with the non-typhoid and other disease conditions reveal new insight into the pathogenesis of S. Typhi. PMID:25144185

Practical technique to quantify small, dense low-density lipoprotein cholesterol using dynamic light scattering

NASA Astrophysics Data System (ADS)

Trirongjitmoah, Suchin; Iinaga, Kazuya; Sakurai, Toshihiro; Chiba, Hitoshi; Sriyudthsak, Mana; Shimizu, Koichi

2016-04-01

Quantification of small, dense low-density lipoprotein (sdLDL) cholesterol is clinically significant. We propose a practical technique to estimate the amount of sdLDL cholesterol using dynamic light scattering (DLS). An analytical solution in a closed form has newly been obtained to estimate the weight fraction of one species of scatterers in the DLS measurement of two species of scatterers. Using this solution, we can quantify the sdLDL cholesterol amount from the amounts of the low-density lipoprotein cholesterol and the high-density lipoprotein (HDL) cholesterol, which are commonly obtained through clinical tests. The accuracy of the proposed technique was confirmed experimentally using latex spheres with known size distributions. The applicability of the proposed technique was examined using samples of human blood serum. The possibility of estimating the sdLDL amount using the HDL data was demonstrated. These results suggest that the quantitative estimation of sdLDL amounts using DLS is feasible for point-of-care testing in clinical practice.

Dynamics and interactions of particles in a thermophoretic trap

NASA Astrophysics Data System (ADS)

Foster, Benjamin; Fung, Frankie; Fieweger, Connor; Usatyuk, Mykhaylo; Gaj, Anita; DeSalvo, B. J.; Chin, Cheng

2017-08-01

We investigate dynamics and interactions of particles levitated and trapped by the thermophoretic force in a vacuum cell. Our analysis is based on footage taken by orthogonal cameras that are able to capture the three dimensional trajectories of the particles. In contrast to spherical particles, which remain stationary at the center of the cell, here we report new qualitative features of the motion of particles with non-spherical geometry. Singly levitated particles exhibit steady spinning around their body axis and rotation around the symmetry axis of the cell. When two levitated particles approach each other, repulsive or attractive interactions between the particles are observed. Our levitation system offers a wonderful platform to study interaction between particles in a microgravity environment.

A dynamical system for interacting flapping swimmers

NASA Astrophysics Data System (ADS)

Oza, Anand; Ramananarivo, Sophie; Ristroph, Leif; Shelley, Michael

2015-11-01

We present the results of a theoretical investigation into the dynamics of interacting flapping swimmers. Our study is motivated by the recent experiments of Becker et al., who studied a one-dimensional array of self-propelled flapping wings that swim within each other's wakes in a water tank. They discovered that the system adopts certain ``schooling modes'' characterized by specific spatial phase relationships between swimmers. To rationalize these phenomena, we develop a discrete dynamical system in which the swimmers are modeled as heaving airfoils that shed point vortices during each flapping cycle. We then apply our model to recent experiments in the Applied Math Lab, in which two tandem flapping airfoils are free to choose both their speed and relative positions. We expect that our model may be used to understand how schooling behavior is influenced by hydrodynamics in more general contexts. Thanks to the NSF for its support.

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

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.

Quantifying Proportional Variability

PubMed Central

Heath, Joel P.; Borowski, Peter

2013-01-01

Real quantities can undergo such a wide variety of dynamics that the mean is often a meaningless reference point for measuring variability. Despite their widespread application, techniques like the Coefficient of Variation are not truly proportional and exhibit pathological properties. The non-parametric measure Proportional Variability (PV) [1] resolves these issues and provides a robust way to summarize and compare variation in quantities exhibiting diverse dynamical behaviour. Instead of being based on deviation from an average value, variation is simply quantified by comparing the numbers to each other, requiring no assumptions about central tendency or underlying statistical distributions. While PV has been introduced before and has already been applied in various contexts to population dynamics, here we present a deeper analysis of this new measure, derive analytical expressions for the PV of several general distributions and present new comparisons with the Coefficient of Variation, demonstrating cases in which PV is the more favorable measure. We show that PV provides an easily interpretable approach for measuring and comparing variation that can be generally applied throughout the sciences, from contexts ranging from stock market stability to climate variation. PMID:24386334

Dynamic Fluctuations of Protein-Carbohydrate Interactions Promote Protein Aggregation

PubMed Central

Voynov, Vladimir; Chennamsetty, Naresh; Kayser, Veysel; Helk, Bernhard; Forrer, Kurt; Zhang, Heidi; Fritsch, Cornelius; Heine, Holger; Trout, Bernhardt L.

2009-01-01

Protein-carbohydrate interactions are important for glycoprotein structure and function. Antibodies of the IgG class, with increasing significance as therapeutics, are glycosylated at a conserved site in the constant Fc region. We hypothesized that disruption of protein-carbohydrate interactions in the glycosylated domain of antibodies leads to the exposure of aggregation-prone motifs. Aggregation is one of the main problems in protein-based therapeutics because of immunogenicity concerns and decreased efficacy. To explore the significance of intramolecular interactions between aromatic amino acids and carbohydrates in the IgG glycosylated domain, we utilized computer simulations, fluorescence analysis, and site-directed mutagenesis. We find that the surface exposure of one aromatic amino acid increases due to dynamic fluctuations. Moreover, protein-carbohydrate interactions decrease upon stress, while protein-protein and carbohydrate-carbohydrate interactions increase. Substitution of the carbohydrate-interacting aromatic amino acids with non-aromatic residues leads to a significantly lower stability than wild type, and to compromised binding to Fc receptors. Our results support a mechanism for antibody aggregation via decreased protein-carbohydrate interactions, leading to the exposure of aggregation-prone regions, and to aggregation. PMID:20037630

Quantifying Trophic Interactions and Carbon Flow in Louisiana Salt Marshes Using Multiple Biomarkers

NASA Astrophysics Data System (ADS)

Polito, M. J.; Lopez-Duarte, P. C.; Olin, J.; Johnson, J. J.; Able, K.; Martin, C. W.; Fodrie, J.; Hooper-Bui, L. M.; Taylor, S.; Stouffer, P.; Roberts, B. J.; Rabalais, N. N.; Jensen, O.

2017-12-01

Salt marshes are critical habitats for many species in the northern Gulf of Mexico. However, given their complex nature, quantifying trophic linkages and the flow of carbon through salt marsh food webs is challenging. This gap in our understanding of food web structure and function limits our ability to evaluate the impacts of natural and anthropogenic stressors on salt marsh ecosystems. For example, 2010 Deepwater Horizon (DWH) oil spill had the potential to alter trophic and energy pathways. Even so, our ability to evaluate its effects on Louisiana salt marsh food webs was limited by a poor basis for comparison of the pre-spill baseline food web. To be better equipped to measure significant alterations in salt marsh ecosystems in the future, we quantified trophic interactions at two marsh sites in Barataria Bay, LA in May and October of 2015. Trophic structure and carbon flow across 52 species of saltmarsh primary producers and consumers were examined through a combination of three approaches: bulk tissue stable isotope analysis (δ13C, δ15N, δ34S), dietary fatty acid analysis (FAA), and compound-specific stable isotope analysis of essential amino acids (δ13C EAA). Bulk stable isotope analysis indicated similar trophic diversity between sites and seasons with the use of aquatic resources increasing concomitantly with trophic level. FAA and δ13C EAA biomarkers revealed that marsh organisms were largely divided into two groups: those that primarily derive carbon from terrestrial C4 grasses, and those that predominately derive carbon from a combination of phytoplankton and benthic microalgal sources. Differences in trophic structure and carbon flow were minimal between seasons and sites that were variably impacted by the DWH spill. These data on salt marsh ecosystem structure will be useful to inform future injury assessments and restoration initiatives.

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.

Spatial structure favors cooperative behavior in the snowdrift game with multiple interactive dynamics

NASA Astrophysics Data System (ADS)

Su, Qi; Li, Aming; Wang, Long

2017-02-01

Spatial reciprocity is generally regarded as a positive rule facilitating the evolution of cooperation. However, a few recent studies show that, in the snowdrift game, spatial structure still could be detrimental to cooperation. Here we propose a model of multiple interactive dynamics, where each individual can cooperate and defect simultaneously against different neighbors. We realize individuals' multiple interactions simply by endowing them with strategies relevant to probabilities, and every one decides to cooperate or defect with a probability. With multiple interactive dynamics, the cooperation level in square lattices is higher than that in the well-mixed case for a wide range of cost-to-benefit ratio r, implying that spatial structure favors cooperative behavior in the snowdrift game. Moreover, in square lattices, the most favorable strategy follows a simple relation of r, which confers theoretically the average evolutionary frequency of cooperative behavior. We further extend our study to various homogeneous and heterogeneous networks, which demonstrates the robustness of our results. Here multiple interactive dynamics stabilizes the positive role of spatial structure on the evolution of cooperation and individuals' distinct reactions to different neighbors can be a new line in understanding the emergence of cooperation.

Dynamics of barite growth in porous media quantified by in situ synchrotron X-ray tomography

NASA Astrophysics Data System (ADS)

Godinho, jose; Gerke, kirill

2016-04-01

Current models used to formulate mineral sequestration strategies of dissolved contaminants in the bedrock often neglect the effect of confinement and the variation of reactive surface area with time. In this work, in situ synchrotron X-ray micro-tomography is used to quantify barite growth rates in a micro-porous structure as a function of time during 13.5 hours with a resolution of 1 μm. Additionally, the 3D porous network at different time frames are used to simulate the flow velocities and calculate the permeability evolution during the experiment. The kinetics of barite growth under porous confinement is compared with the kinetics of barite growth on free surfaces in the same fluid composition. Results are discussed in terms of surface area normalization and the evolution of flow velocities as crystals fill the porous structure. During the initial hours the growth rate measured in porous media is similar to the growth rate on free surfaces. However, as the thinner flow paths clog the growth rate progressively decreases, which is correlated to a decrease of local flow velocity. The largest pores remain open, enabling growth to continue throughout the structure. Quantifying the dynamics of mineral precipitation kinetics in situ in 4D, has revealed the importance of using a time dependent reactive surface area and accounting for the local properties of the porous network, when formulating predictive models of mineral precipitation in porous media.

Multilevel summation with B-spline interpolation for pairwise interactions in molecular dynamics simulations.

PubMed

Hardy, David J; Wolff, Matthew A; Xia, Jianlin; Schulten, Klaus; Skeel, Robert D

2016-03-21

The multilevel summation method for calculating electrostatic interactions in molecular dynamics simulations constructs an approximation to a pairwise interaction kernel and its gradient, which can be evaluated at a cost that scales linearly with the number of atoms. The method smoothly splits the kernel into a sum of partial kernels of increasing range and decreasing variability with the longer-range parts interpolated from grids of increasing coarseness. Multilevel summation is especially appropriate in the context of dynamics and minimization, because it can produce continuous gradients. This article explores the use of B-splines to increase the accuracy of the multilevel summation method (for nonperiodic boundaries) without incurring additional computation other than a preprocessing step (whose cost also scales linearly). To obtain accurate results efficiently involves technical difficulties, which are overcome by a novel preprocessing algorithm. Numerical experiments demonstrate that the resulting method offers substantial improvements in accuracy and that its performance is competitive with an implementation of the fast multipole method in general and markedly better for Hamiltonian formulations of molecular dynamics. The improvement is great enough to establish multilevel summation as a serious contender for calculating pairwise interactions in molecular dynamics simulations. In particular, the method appears to be uniquely capable for molecular dynamics in two situations, nonperiodic boundary conditions and massively parallel computation, where the fast Fourier transform employed in the particle-mesh Ewald method falls short.

Multilevel summation with B-spline interpolation for pairwise interactions in molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Hardy, David J.; Wolff, Matthew A.; Xia, Jianlin; Schulten, Klaus; Skeel, Robert D.

2016-03-01

The multilevel summation method for calculating electrostatic interactions in molecular dynamics simulations constructs an approximation to a pairwise interaction kernel and its gradient, which can be evaluated at a cost that scales linearly with the number of atoms. The method smoothly splits the kernel into a sum of partial kernels of increasing range and decreasing variability with the longer-range parts interpolated from grids of increasing coarseness. Multilevel summation is especially appropriate in the context of dynamics and minimization, because it can produce continuous gradients. This article explores the use of B-splines to increase the accuracy of the multilevel summation method (for nonperiodic boundaries) without incurring additional computation other than a preprocessing step (whose cost also scales linearly). To obtain accurate results efficiently involves technical difficulties, which are overcome by a novel preprocessing algorithm. Numerical experiments demonstrate that the resulting method offers substantial improvements in accuracy and that its performance is competitive with an implementation of the fast multipole method in general and markedly better for Hamiltonian formulations of molecular dynamics. The improvement is great enough to establish multilevel summation as a serious contender for calculating pairwise interactions in molecular dynamics simulations. In particular, the method appears to be uniquely capable for molecular dynamics in two situations, nonperiodic boundary conditions and massively parallel computation, where the fast Fourier transform employed in the particle-mesh Ewald method falls short.

Classifying and quantifying basins of attraction

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

Sprott, J. C.; Xiong, Anda

2015-08-15

A scheme is proposed to classify the basins for attractors of dynamical systems in arbitrary dimensions. There are four basic classes depending on their size and extent, and each class can be further quantified to facilitate comparisons. The calculation uses a Monte Carlo method and is applied to numerous common dissipative chaotic maps and flows in various dimensions.

Local interactions lead to pathogen-driven change to host population dynamics.

PubMed

Boots, Michael; Childs, Dylan; Reuman, Daniel C; Mealor, Michael

2009-10-13

Individuals tend to interact more strongly with nearby individuals or within particular social groups. Recent theoretical advances have demonstrated that these within-population relationships can have fundamental implications for ecological and evolutionary dynamics. In particular, contact networks are crucial to the spread and evolution of disease. However, the theory remains largely untested experimentally. Here, we manipulate habitat viscosity and thereby the frequency of local interactions in an insect-pathogen model system in which the virus had previously been shown to have little effect on host population dynamics. At high viscosity, the pathogen caused the collapse of dominant and otherwise stable host generation cycles. Modeling shows that this collapse can be explained by an increase in the frequency of intracohort interactions relative to intercohort interactions, leading to more disease transmission. Our work emphasizes that spatial structure can subtly mediate intraspecific competition and the effects of natural enemies. A decrease in dispersal in a population may actually (sometimes rather counterintuitively) intensify the effects of parasites. Broadly, because anthropological and environmental change often cause changes in population mixing, our work highlights the potential for dramatic changes in the effects of parasites on host populations.

General two-species interacting Lotka-Volterra system: Population dynamics and wave propagation

NASA Astrophysics Data System (ADS)

Zhu, Haoqi; Wang, Mao-Xiang; Lai, Pik-Yin

2018-05-01

The population dynamics of two interacting species modeled by the Lotka-Volterra (LV) model with general parameters that can promote or suppress the other species is studied. It is found that the properties of the two species' isoclines determine the interaction of species, leading to six regimes in the phase diagram of interspecies interaction; i.e., there are six different interspecific relationships described by the LV model. Four regimes allow for nontrivial species coexistence, among which it is found that three of them are stable, namely, weak competition, mutualism, and predator-prey scenarios can lead to win-win coexistence situations. The Lyapunov function for general nontrivial two-species coexistence is also constructed. Furthermore, in the presence of spatial diffusion of the species, the dynamics can lead to steady wavefront propagation and can alter the population map. Propagating wavefront solutions in one dimension are investigated analytically and by numerical solutions. The steady wavefront speeds are obtained analytically via nonlinear dynamics analysis and verified by numerical solutions. In addition to the inter- and intraspecific interaction parameters, the intrinsic speed parameters of each species play a decisive role in species populations and wave properties. In some regimes, both species can copropagate with the same wave speeds in a finite range of parameters. Our results are further discussed in the light of possible biological relevance and ecological implications.

Vector-virus interactions and transmission dynamics of West Nile virus.

PubMed

Ciota, Alexander T; Kramer, Laura D

2013-12-09

West Nile virus (WNV; Flavivirus; Flaviviridae) is the cause of the most widespread arthropod-borne viral disease in the world and the largest outbreak of neuroinvasive disease ever observed. Mosquito-borne outbreaks are influenced by intrinsic (e.g., vector and viral genetics, vector and host competence, vector life-history traits) and extrinsic (e.g., temperature, rainfall, human land use) factors that affect virus activity and mosquito biology in complex ways. The concept of vectorial capacity integrates these factors to address interactions of the virus with the arthropod host, leading to a clearer understanding of their complex interrelationships, how they affect transmission of vector-borne disease, and how they impact human health. Vertebrate factors including host competence, population dynamics, and immune status also affect transmission dynamics. The complexity of these interactions are further exacerbated by the fact that not only can divergent hosts differentially alter the virus, but the virus also can affect both vertebrate and invertebrate hosts in ways that significantly alter patterns of virus transmission. This chapter concentrates on selected components of the virus-vector-vertebrate interrelationship, focusing specifically on how interactions between vector, virus, and environment shape the patterns and intensity of WNV transmission.

Vector-Virus Interactions and Transmission Dynamics of West Nile Virus

PubMed Central

Ciota, Alexander T.; Kramer, Laura D.

2013-01-01

West Nile virus (WNV; Flavivirus; Flaviviridae) is the cause of the most widespread arthropod-borne viral disease in the world and the largest outbreak of neuroinvasive disease ever observed. Mosquito-borne outbreaks are influenced by intrinsic (e.g., vector and viral genetics, vector and host competence, vector life-history traits) and extrinsic (e.g., temperature, rainfall, human land use) factors that affect virus activity and mosquito biology in complex ways. The concept of vectorial capacity integrates these factors to address interactions of the virus with the arthropod host, leading to a clearer understanding of their complex interrelationships, how they affect transmission of vector-borne disease, and how they impact human health. Vertebrate factors including host competence, population dynamics, and immune status also affect transmission dynamics. The complexity of these interactions are further exacerbated by the fact that not only can divergent hosts differentially alter the virus, but the virus also can affect both vertebrate and invertebrate hosts in ways that significantly alter patterns of virus transmission. This chapter concentrates on selected components of the virus-vector-vertebrate interrelationship, focusing specifically on how interactions between vector, virus, and environment shape the patterns and intensity of WNV transmission. PMID:24351794

Quantifiers are incrementally interpreted in context, more than less

PubMed Central

Urbach, Thomas P.; DeLong, Katherine A.; Kutas, Marta

2015-01-01

Language interpretation is often assumed to be incremental. However, our studies of quantifier expressions in isolated sentences found N400 event-related brain potential (ERP) evidence for partial but not full immediate quantifier interpretation (Urbach & Kutas, 2010). Here we tested similar quantifier expressions in pragmatically supporting discourse contexts (Alex was an unusual toddler. Most/Few kids prefer sweets/vegetables…) while participants made plausibility judgments (Experiment 1) or read for comprehension (Experiment 2). Control Experiments 3A (plausibility) and 3B (comprehension) removed the discourse contexts. Quantifiers always modulated typical and/or atypical word N400 amplitudes. However, only the real-time N400 effects only in Experiment 2 mirrored offline quantifier and typicality crossover interaction effects for plausibility ratings and cloze probabilities. We conclude that quantifier expressions can be interpreted fully and immediately, though pragmatic and task variables appear to impact the speed and/or depth of quantifier interpretation. PMID:26005285

On the decomposition of a dynamical system into non-interacting subsystems.

NASA Technical Reports Server (NTRS)

Rosen, R.

1972-01-01

It is shown that, under rather general conditions, it is possible to formally decompose the dynamics of an n-dimensional dynamical system into a number of non-interacting subsystems. It is shown that these decompositions are in general not simply related to the kinds of observational procedures in terms of which the original state variables of the system are defined. Some consequences of this construction for reductionism in biology are discussed.

Interactions among energy consumption, economic development and greenhouse gas emissions in Japan after World War II

EPA Science Inventory

The long-term dynamic changes in the triad, energy consumption, economic development, and Greenhouse gas (GHG) emissions, in Japan after World War II were quantified, and the interactions among them were analyzed based on an integrated suite of energy, emergy and economic indices...

Structure and Dynamics of Antifreeze Protein--Model Membrane Interactions: A Combined Spectroscopic and Molecular Dynamics Study.

PubMed

Kar, Rajiv K; Mroue, Kamal H; Kumar, Dinesh; Tejo, Bimo A; Bhunia, Anirban

2016-02-11

Antifreeze proteins (AFPs) are the key biomolecules that enable species to survive under subzero temperature conditions. The physiologically relevant activities of AFPs are based on the adsorption to ice crystals, followed by the inhibition of subsequent crystal layer growth of ice, routed with depression in freezing point in a noncolligative manner. The functional attributes governing the mechanism by which AFPs inhibit freezing of body fluids in bacteria, fungi, plants, and fishes are mainly attributed to their adsorption onto the surface of ice within the physiological system. Importantly, AFPs are also known for their application in cryopreservation of biological samples that might be related to membrane interaction. To date, there is a paucity of information detailing the interaction of AFPs with membrane structures. Here, we focus on elucidating the biophysical properties of the interactions between AFPs and micelle models that mimic the membrane system. Micelle model systems of zwitterionic DPC and negatively charged SDS were utilized in this study, against which a significant interaction is experienced by two AFP molecules, namely, Peptide 1m and wfAFP (the popular AFP sourced from winter flounder). Using low- and high-resolution biophysical characterization techniques, such as circular dichroism (CD) and NMR spectroscopy, a strong evidence for the interactions of these AFPs with the membrane models is revealed in detail and is corroborated by in-depth residue-specific information derived from molecular dynamics simulation. Altogether, these results not only strengthen the fact that AFPs interact actively with membrane systems, but also demonstrate that membrane-associated AFPs are dynamic and capable of adopting a number of conformations rendering fluidity to the system.

Brownian dynamics simulations of lipid bilayer membrane with hydrodynamic interactions in LAMMPS

NASA Astrophysics Data System (ADS)

Fu, Szu-Pei; Young, Yuan-Nan; Peng, Zhangli; Yuan, Hongyan

2016-11-01

Lipid bilayer membranes have been extensively studied by coarse-grained molecular dynamics simulations. Numerical efficiencies have been reported in the cases of aggressive coarse-graining, where several lipids are coarse-grained into a particle of size 4 6 nm so that there is only one particle in the thickness direction. Yuan et al. proposed a pair-potential between these one-particle-thick coarse-grained lipid particles to capture the mechanical properties of a lipid bilayer membrane (such as gel-fluid-gas phase transitions of lipids, diffusion, and bending rigidity). In this work we implement such interaction potential in LAMMPS to simulate large-scale lipid systems such as vesicles and red blood cells (RBCs). We also consider the effect of cytoskeleton on the lipid membrane dynamics as a model for red blood cell (RBC) dynamics, and incorporate coarse-grained water molecules to account for hydrodynamic interactions. The interaction between the coarse-grained water molecules (explicit solvent molecules) is modeled as a Lennard-Jones (L-J) potential. We focus on two sets of LAMMPS simulations: 1. Vesicle shape transitions with varying enclosed volume; 2. RBC shape transitions with different enclosed volume. This work is funded by NSF under Grant DMS-1222550.

Brownian dynamics simulations of lipid bilayer membrane with hydrodynamic interactions in LAMMPS

NASA Astrophysics Data System (ADS)

Fu, Szu-Pei; Young, Yuan-Nan; Peng, Zhangli; Yuan, Hongyan

Lipid bilayer membranes have been extensively studied by coarse-grained molecular dynamics simulations. Numerical efficiency has been reported in the cases of aggressive coarse-graining, where several lipids are coarse-grained into a particle of size 4 6 nm so that there is only one particle in the thickness direction. Yuan et al. proposed a pair-potential between these one-particle-thick coarse-grained lipid particles to capture the mechanical properties of a lipid bilayer membrane (such as gel-fluid-gas phase transitions of lipids, diffusion, and bending rigidity). In this work we implement such interaction potential in LAMMPS to simulate large-scale lipid systems such as vesicles and red blood cells (RBCs). We also consider the effect of cytoskeleton on the lipid membrane dynamics as a model for red blood cell (RBC) dynamics, and incorporate coarse-grained water molecules to account for hydrodynamic interactions. The interaction between the coarse-grained water molecules (explicit solvent molecules) is modeled as a Lennard-Jones (L-J) potential. We focus on two sets of LAMMPS simulations: 1. Vesicle shape transitions with varying enclosed volume; 2. RBC shape transitions with different enclosed volume.

Dynamic interactions between prophages induce lysis in Propionibacterium acnes.

PubMed

L Brown, Teagan; Tucci, Joseph; Dyson, Zoe A; Lock, Peter; Adda, Christopher G; Petrovski, Steve

Progress in next-generation sequencing technologies has facilitated investigations into microbial dynamics. An important bacterium in the dairy industry is Propionibacterium freudenreichii, which is exploited to manufacture Swiss cheeses. A healthy culture of these bacteria ensures a consistent cheese with formed 'eyes' and pleasant flavour profile, and the investigation of prophages and their interactions with these bacteria could assist in the maintenance of the standard of this food product. Two bacteriophages, termed PFR1 and PFR2, were chemically induced using mitomycin C from two different dairy strains of P. freudenreichii. Both phages have identical genomes; however, PFR2 was found to contain an insertion sequence, IS204. Host range characterisation showed that PFR1 was able to form plaques on a wild type Propionibacterium acnes strain, whereas PFR2 could not. The lytic plaques observed on P. acnes were a result of PFR1 inducing the lytic cycle of a pseudolysogenic phage in P. acnes. Further investigation revealed that both PFR1 and PFR2 could infect P. acnes but not replicate. This study demonstrates the dynamic interactions between phages, which may alter their lytic capacity under certain conditions. To our knowledge, this is the first report of two phages interacting to kill their host. Copyright © 2016 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

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.

A system dynamics model of human-water interaction in anthropogenic droughts

NASA Astrophysics Data System (ADS)

Blair, Peter; Buytaert, Wouter

2016-04-01

Modelling is set to be a key part of socio-hydrology's quest to understand the dynamics and long-term consequences of human-water interactions. As a subject in its infancy, still learning the questions to ask, conceptual models are of particular use in trying to understand the general nature of human-water systems. The conceptual model of Di Baldassarre et al. (2013), which investigates human-flood interactions, has been widely discussed, prompting great steps forward in understanding and coverage of socio-hydrology. The development of further conceptual models could generate further discussion and understanding. Flooding is one archetypal example of a system of human-water interaction; another is the case of water stress and drought. There has been a call to recognise and understand anthropogenic drought (Aghakouchak et al. 2015), and so this study investigates the nature of the socio-hydrological dynamics involved in these situations. Here we present a system dynamics model to simulate human-water interactions in the context of water-stressed areas, where drought is induced via a combination of lower than usual water availability and relatively high water use. It is designed based on an analysis of several case-studies where recent droughts have occurred, or where the prospect of drought looms. The locations investigated are Spain, Southeast Brazil, Northeast China and California. The numerical system dynamics model is based on causal loop, and stocks and flows diagrams, which are in turn developed from the qualitative analysis of the different cases studied. The study uses a comparative approach, which has the advantage of eliciting general system characteristics from the similarities between cases, while using the differences to determine the important factors which lead to different system behaviours. References: Aghakouchak, A., Feldman, D., Hoerling, M., Huxman, T., Lund, J., 2015. Recognize anthropogenic drought. Nature, 524, pp.409-411. Di Baldassarre, G

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.

Atomic detail brownian dynamics simulations of concentrated protein solutions with a mean field treatment of hydrodynamic interactions.

PubMed

Mereghetti, Paolo; Wade, Rebecca C

2012-07-26

High macromolecular concentrations are a distinguishing feature of living organisms. Understanding how the high concentration of solutes affects the dynamic properties of biological macromolecules is fundamental for the comprehension of biological processes in living systems. In this paper, we describe the implementation of mean field models of translational and rotational hydrodynamic interactions into an atomically detailed many-protein brownian dynamics simulation method. Concentrated solutions (30-40% volume fraction) of myoglobin, hemoglobin A, and sickle cell hemoglobin S were simulated, and static structure factors, oligomer formation, and translational and rotational self-diffusion coefficients were computed. Good agreement of computed properties with available experimental data was obtained. The results show the importance of both solvent mediated interactions and weak protein-protein interactions for accurately describing the dynamics and the association properties of concentrated protein solutions. Specifically, they show a qualitative difference in the translational and rotational dynamics of the systems studied. Although the translational diffusion coefficient is controlled by macromolecular shape and hydrodynamic interactions, the rotational diffusion coefficient is affected by macromolecular shape, direct intermolecular interactions, and both translational and rotational hydrodynamic interactions.

Mutation-induced protein interaction kinetics changes affect apoptotic network dynamic properties and facilitate oncogenesis

PubMed Central

Zhao, Linjie; Sun, Tanlin; Pei, Jianfeng; Ouyang, Qi

2015-01-01

It has been a consensus in cancer research that cancer is a disease caused primarily by genomic alterations, especially somatic mutations. However, the mechanism of mutation-induced oncogenesis is not fully understood. Here, we used the mitochondrial apoptotic pathway as a case study and performed a systematic analysis of integrating pathway dynamics with protein interaction kinetics to quantitatively investigate the causal molecular mechanism of mutation-induced oncogenesis. A mathematical model of the regulatory network was constructed to establish the functional role of dynamic bifurcation in the apoptotic process. The oncogenic mutation enrichment of each of the protein functional domains involved was found strongly correlated with the parameter sensitivity of the bifurcation point. We further dissected the causal mechanism underlying this correlation by evaluating the mutational influence on protein interaction kinetics using molecular dynamics simulation. We analyzed 29 matched mutant–wild-type and 16 matched SNP—wild-type protein systems. We found that the binding kinetics changes reflected by the changes of free energy changes induced by protein interaction mutations, which induce variations in the sensitive parameters of the bifurcation point, were a major cause of apoptosis pathway dysfunction, and mutations involved in sensitive interaction domains show high oncogenic potential. Our analysis provided a molecular basis for connecting protein mutations, protein interaction kinetics, network dynamics properties, and physiological function of a regulatory network. These insights provide a framework for coupling mutation genotype to tumorigenesis phenotype and help elucidate the logic of cancer initiation. PMID:26170328

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

Photonic-plasmonic hybrid single-molecule nanosensor measures the effect of fluorescent labels on DNA-protein dynamics

PubMed Central

Liang, Feng; Guo, Yuzheng; Hou, Shaocong; Quan, Qimin

2017-01-01

Current methods to study molecular interactions require labeling the subject molecules with fluorescent reporters. However, the effect of the fluorescent reporters on molecular dynamics has not been quantified because of a lack of alternative methods. We develop a hybrid photonic-plasmonic antenna-in-a-nanocavity single-molecule biosensor to study DNA-protein dynamics without using fluorescent labels. Our results indicate that the fluorescein and fluorescent protein labels decrease the interaction between a single DNA and a protein due to weakened electrostatic interaction. Although the study is performed on the DNA-XPA system, the conclusion has a general implication that the traditional fluorescent labeling methods might be misestimating the molecular interactions. PMID:28560341

Bioluminescence resonance energy transfer system for measuring dynamic protein-protein interactions in bacteria.

PubMed

Cui, Boyu; Wang, Yao; Song, Yunhong; Wang, Tietao; Li, Changfu; Wei, Yahong; Luo, Zhao-Qing; Shen, Xihui

2014-05-20

Protein-protein interactions are important for virtually every biological process, and a number of elegant approaches have been designed to detect and evaluate such interactions. However, few of these methods allow the detection of dynamic and real-time protein-protein interactions in bacteria. Here we describe a bioluminescence resonance energy transfer (BRET) system based on the bacterial luciferase LuxAB. We found that enhanced yellow fluorescent protein (eYFP) accepts the emission from LuxAB and emits yellow fluorescence. Importantly, BRET occurred when LuxAB and eYFP were fused, respectively, to the interacting protein pair FlgM and FliA. Furthermore, we observed sirolimus (i.e., rapamycin)-inducible interactions between FRB and FKBP12 and a dose-dependent abolishment of such interactions by FK506, the ligand of FKBP12. Using this system, we showed that osmotic stress or low pH efficiently induced multimerization of the regulatory protein OmpR and that the multimerization induced by low pH can be reversed by a neutralizing agent, further indicating the usefulness of this system in the measurement of dynamic interactions. This method can be adapted to analyze dynamic protein-protein interactions and the importance of such interactions in bacterial processes such as development and pathogenicity. Real-time measurement of protein-protein interactions in prokaryotes is highly desirable for determining the roles of protein complex in the development or virulence of bacteria, but methods that allow such measurement are not available. Here we describe the development of a bioluminescence resonance energy transfer (BRET) technology that meets this need. The use of endogenous excitation light in this strategy circumvents the requirement for the sophisticated instrument demanded by standard fluorescence resonance energy transfer (FRET). Furthermore, because the LuxAB substrate decanal is membrane permeable, the assay can be performed without lysing the bacterial cells

Quantified Facial Soft-tissue Strain in Animation Measured by Real-time Dynamic 3-Dimensional Imaging

PubMed Central

Hsu, Vivian M.; Wes, Ari M.; Tahiri, Youssef; Cornman-Homonoff, Joshua

2014-01-01

Background: The aim of this study is to evaluate and quantify dynamic soft-tissue strain in the human face using real-time 3-dimensional imaging technology. Methods: Thirteen subjects (8 women, 5 men) between the ages of 18 and 70 were imaged using a dual-camera system and 3-dimensional optical analysis (ARAMIS, Trilion Quality Systems, Pa.). Each subject was imaged at rest and with the following facial expressions: (1) smile, (2) laughter, (3) surprise, (4) anger, (5) grimace, and (6) pursed lips. The facial strains defining stretch and compression were computed for each subject and compared. Results: The areas of greatest strain were localized to the midface and lower face for all expressions. Subjects over the age of 40 had a statistically significant increase in stretch in the perioral region while lip pursing compared with subjects under the age of 40 (58.4% vs 33.8%, P = 0.015). When specific components of lip pursing were analyzed, there was a significantly greater degree of stretch in the nasolabial fold region in subjects over 40 compared with those under 40 (61.6% vs 32.9%, P = 0.007). Furthermore, we observed a greater degree of asymmetry of strain in the nasolabial fold region in the older age group (18.4% vs 5.4%, P = 0.03). Conclusions: This pilot study illustrates that the face can be objectively and quantitatively evaluated using dynamic major strain analysis. The technology of 3-dimensional optical imaging can be used to advance our understanding of facial soft-tissue dynamics and the effects of animation on facial strain over time. PMID:25426394

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).

On the Interactions Between Planetary and Mesoscale Dynamics in the Oceans

NASA Astrophysics Data System (ADS)

Grooms, I.; Julien, K. A.; Fox-Kemper, B.

2011-12-01

Multiple-scales asymptotic methods are used to investigate the interaction of planetary and mesoscale dynamics in the oceans. We find three regimes. In the first, the slow, large-scale planetary flow sets up a baroclinically unstable background which leads to vigorous mesoscale eddy generation, but the eddy dynamics do not affect the planetary dynamics. In the second, the planetary flow feels the effects of the eddies, but appears to be unable to generate them. The first two regimes rely on horizontally isotropic large-scale dynamics. In the third regime, large-scale anisotropy, as exists for example in the Antarctic Circumpolar Current and in western boundary currents, allows the large-scale dynamics to both generate and respond to mesoscale eddies. We also discuss how the investigation may be brought to bear on the problem of parameterization of unresolved mesoscale dynamics in ocean general circulation models.

Current-current interactions, dynamical symmetry-breaking, and quantum chromodynamics

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

Neuenschwander, D.E. Jr.

1983-01-01

Quantum Chromodynamics with massive gluons (gluon mass triple bond xm/sub p/) in a contact-interaction limit called CQCD (strong coupling g..-->..infinity; x..-->..infinity), despite its non-renormalizability and lack of hope of confinement, is nevertheless interesting for at least two reasons. Some authors have suggested a relation between 4-Fermi and Yang-Mills theories. If g/x/sup 2/ much less than 1, then CQCD is not merely a 4-Fermi interaction, but includes 4,6,8 etc-Fermi non-Abelian contact interactions. With possibility of infrared slavery, perturbative evaluation of QCD in the infrared is a dubious practice. However, if g/sup 2//x/sup 2/ much less than 1 in CQCD, then themore » simplest 4-Fermi interaction is dominant, and CQCD admits perturbative treatment, but only in the infrared. With the dominant interaction, a dynamical Nambu-Goldstone realization of chiral symmetry-breaking (XSB) is found. Although in QCD the relation between confinement and XSB is controversial, XSB occurs in CQCD provided confinement is sacrificed.« less

Krylov subspace methods for computing hydrodynamic interactions in Brownian dynamics simulations

PubMed Central

Ando, Tadashi; Chow, Edmond; Saad, Yousef; Skolnick, Jeffrey

2012-01-01

Hydrodynamic interactions play an important role in the dynamics of macromolecules. The most common way to take into account hydrodynamic effects in molecular simulations is in the context of a Brownian dynamics simulation. However, the calculation of correlated Brownian noise vectors in these simulations is computationally very demanding and alternative methods are desirable. This paper studies methods based on Krylov subspaces for computing Brownian noise vectors. These methods are related to Chebyshev polynomial approximations, but do not require eigenvalue estimates. We show that only low accuracy is required in the Brownian noise vectors to accurately compute values of dynamic and static properties of polymer and monodisperse suspension models. With this level of accuracy, the computational time of Krylov subspace methods scales very nearly as O(N2) for the number of particles N up to 10 000, which was the limit tested. The performance of the Krylov subspace methods, especially the “block” version, is slightly better than that of the Chebyshev method, even without taking into account the additional cost of eigenvalue estimates required by the latter. Furthermore, at N = 10 000, the Krylov subspace method is 13 times faster than the exact Cholesky method. Thus, Krylov subspace methods are recommended for performing large-scale Brownian dynamics simulations with hydrodynamic interactions. PMID:22897254

Modelling social interaction as perceptual crossing: an investigation into the dynamics of the interaction process

NASA Astrophysics Data System (ADS)

Froese, Tom; Di Paolo, Ezequiel A.

2010-03-01

This paper continues efforts to establish a mutually informative dialogue between psychology and evolutionary robotics in order to investigate the dynamics of social interaction. We replicate a recent simulation model of a minimalist experiment in perceptual crossing and confirm the results with significantly simpler artificial agents. A series of psycho-physical tests of their behaviour informs a hypothetical circuit model of their internal operation. However, a detailed study of the actual internal dynamics reveals this circuit model to be unfounded, thereby offering a tale of caution for those hypothesising about sub-personal processes in terms of behavioural observations. In particular, it is shown that the behaviour of the agents largely emerges out of the interaction process itself rather than being an individual achievement alone. We also extend the original simulation model in two novel directions in order to test further the extent to which perceptual crossing between agents can self-organise in a robust manner. These modelling results suggest new hypotheses that can become the basis for further psychological experiments.

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.

Fluid dynamic mechanisms and interactions within separated flows

NASA Astrophysics Data System (ADS)

Dutton, J. C.; Addy, A. L.

1990-02-01

The significant results of a joint research effort investigating the fundamental fluid dynamic mechanisms and interactions within high-speed separated flows are presented in detail. The results have obtained through analytical and numerical approaches, but with primary emphasis on experimental investigations of missile and projectile base flow-related configurations. The objectives of the research program focus on understanding the component mechanisms and interactions which establish and maintain high-speed separated flow regions. The analytical and numerical efforts have centered on unsteady plume-wall interactions in rocket launch tubes and on predictions of the effects of base bleed on transonic and supersonic base flowfields. The experimental efforts have considered the development and use of a state-of-the-art two component laser Doppler velocimeter (LDV) system for experiments with planar, two-dimensional, small-scale models in supersonic flows. The LDV experiments have yielded high quality, well documented mean and turbulence velocity data for a variety of high-speed separated flows including initial shear layer development, recompression/reattachment processes for two supersonic shear layers, oblique shock wave/turbulent boundary layer interactions in a compression corner, and two-stream, supersonic, near-wake flow behind a finite-thickness base.

Multilevel summation with B-spline interpolation for pairwise interactions in molecular dynamics simulations

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

Hardy, David J., E-mail: dhardy@illinois.edu; Schulten, Klaus; Wolff, Matthew A.

2016-03-21

The multilevel summation method for calculating electrostatic interactions in molecular dynamics simulations constructs an approximation to a pairwise interaction kernel and its gradient, which can be evaluated at a cost that scales linearly with the number of atoms. The method smoothly splits the kernel into a sum of partial kernels of increasing range and decreasing variability with the longer-range parts interpolated from grids of increasing coarseness. Multilevel summation is especially appropriate in the context of dynamics and minimization, because it can produce continuous gradients. This article explores the use of B-splines to increase the accuracy of the multilevel summation methodmore » (for nonperiodic boundaries) without incurring additional computation other than a preprocessing step (whose cost also scales linearly). To obtain accurate results efficiently involves technical difficulties, which are overcome by a novel preprocessing algorithm. Numerical experiments demonstrate that the resulting method offers substantial improvements in accuracy and that its performance is competitive with an implementation of the fast multipole method in general and markedly better for Hamiltonian formulations of molecular dynamics. The improvement is great enough to establish multilevel summation as a serious contender for calculating pairwise interactions in molecular dynamics simulations. In particular, the method appears to be uniquely capable for molecular dynamics in two situations, nonperiodic boundary conditions and massively parallel computation, where the fast Fourier transform employed in the particle–mesh Ewald method falls short.« less

A Method for Predicting Protein Complexes from Dynamic Weighted Protein-Protein Interaction Networks.

PubMed

Liu, Lizhen; Sun, Xiaowu; Song, Wei; Du, Chao

2018-06-01

Predicting protein complexes from protein-protein interaction (PPI) network is of great significance to recognize the structure and function of cells. A protein may interact with different proteins under different time or conditions. Existing approaches only utilize static PPI network data that may lose much temporal biological information. First, this article proposed a novel method that combines gene expression data at different time points with traditional static PPI network to construct different dynamic subnetworks. Second, to further filter out the data noise, the semantic similarity based on gene ontology is regarded as the network weight together with the principal component analysis, which is introduced to deal with the weight computing by three traditional methods. Third, after building a dynamic PPI network, a predicting protein complexes algorithm based on "core-attachment" structural feature is applied to detect complexes from each dynamic subnetworks. Finally, it is revealed from the experimental results that our method proposed in this article performs well on detecting protein complexes from dynamic weighted PPI networks.

Single-molecule dynamic force spectroscopy of the fibronectin-heparin interaction

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

Mitchell, Gabriel; Lamontagne, Charles-Antoine; Lebel, Rejean

2007-12-21

The integrity of cohesive tissues strongly depends on the presence of the extracellular matrix, which provides support and anchorage for cells. The fibronectin protein and the heparin-like glycosaminoglycans are key components of this dynamic structural network. In this report, atomic force spectroscopy was used to gain insight into the compliance and the resistance of the fibronectin-heparin interaction. We found that this interaction can be described by an energetic barrier width of 3.1 {+-} 0.2 A and an off-rate of 0.2 {+-} 0.1 s{sup -1}. These dissociation parameters are similar to those of other carbohydrate-protein interactions and to off-rate values reportedmore » for more complex interactions between cells and extracellular matrix components. Our results indicate that the function of the fibronectin-heparin interaction is supported by its capacity to sustain significant deformations and considerable external mechanical forces.« less

A GPU-accelerated immersive audio-visual framework for interaction with molecular dynamics using consumer depth sensors.

PubMed

Glowacki, David R; O'Connor, Michael; Calabró, Gaetano; Price, James; Tew, Philip; Mitchell, Thomas; Hyde, Joseph; Tew, David P; Coughtrie, David J; McIntosh-Smith, Simon

2014-01-01

With advances in computational power, the rapidly growing role of computational/simulation methodologies in the physical sciences, and the development of new human-computer interaction technologies, the field of interactive molecular dynamics seems destined to expand. In this paper, we describe and benchmark the software algorithms and hardware setup for carrying out interactive molecular dynamics utilizing an array of consumer depth sensors. The system works by interpreting the human form as an energy landscape, and superimposing this landscape on a molecular dynamics simulation to chaperone the motion of the simulated atoms, affecting both graphics and sonified simulation data. GPU acceleration has been key to achieving our target of 60 frames per second (FPS), giving an extremely fluid interactive experience. GPU acceleration has also allowed us to scale the system for use in immersive 360° spaces with an array of up to ten depth sensors, allowing several users to simultaneously chaperone the dynamics. The flexibility of our platform for carrying out molecular dynamics simulations has been considerably enhanced by wrappers that facilitate fast communication with a portable selection of GPU-accelerated molecular force evaluation routines. In this paper, we describe a 360° atmospheric molecular dynamics simulation we have run in a chemistry/physics education context. We also describe initial tests in which users have been able to chaperone the dynamics of 10-alanine peptide embedded in an explicit water solvent. Using this system, both expert and novice users have been able to accelerate peptide rare event dynamics by 3-4 orders of magnitude.

Interspecies interactions are an integral determinant of microbial community dynamics

PubMed Central

Aziz, Fatma A. A.; Suzuki, Kenshi; Ohtaki, Akihiro; Sagegami, Keita; Hirai, Hidetaka; Seno, Jun; Mizuno, Naoko; Inuzuka, Yuma; Saito, Yasuhisa; Tashiro, Yosuke; Hiraishi, Akira; Futamata, Hiroyuki

2015-01-01

This study investigated the factors that determine the dynamics of bacterial communities in a complex system using multidisciplinary methods. Since natural and engineered microbial ecosystems are too complex to study, six types of synthetic microbial ecosystems (SMEs) were constructed under chemostat conditions with phenol as the sole carbon and energy source. Two to four phenol-degrading, phylogenetically and physiologically different bacterial strains were used in each SME. Phylogeny was based on the nucleotide sequence of 16S rRNA genes, while physiologic traits were based on kinetic and growth parameters on phenol. Two indices, J parameter and “interspecies interaction,” were compared to predict which strain would become dominant in an SME. The J parameter was calculated from kinetic and growth parameters. On the other hand, “interspecies interaction,” a new index proposed in this study, was evaluated by measuring the specific growth activity, which was determined on the basis of relative growth of a strain with or without the supernatant prepared from other bacterial cultures. Population densities of strains used in SMEs were enumerated by real-time quantitative PCR (qPCR) targeting the gene encoding the large subunit of phenol hydroxylase and were compared to predictions made from J parameter and interspecies interaction calculations. In 4 of 6 SEMs tested the final dominant strain shown by real-time qPCR analyses coincided with the strain predicted by both the J parameter and the interspecies interaction. However, in SMEII-2 and SMEII-3 the final dominant Variovorax strains coincided with prediction of the interspecies interaction but not the J parameter. These results demonstrate that the effects of interspecies interactions within microbial communities contribute to determining the dynamics of the microbial ecosystem. PMID:26539177

Dynamic train-track interaction at high vehicle speeds—Modelling of wheelset dynamics and wheel rotation

NASA Astrophysics Data System (ADS)

Torstensson, P. T.; Nielsen, J. C. O.; Baeza, L.

2011-10-01

Vertical dynamic train-track interaction at high vehicle speeds is investigated in a frequency range from about 20 Hz to 2.5 kHz. The inertial effects due to wheel rotation are accounted for in the vehicle model by implementing a structural dynamics model of a rotating wheelset. Calculated wheel-rail contact forces using the flexible, rotating wheelset model are compared with contact forces based on rigid, non-rotating models. For a validation of the train-track interaction model, calculated contact forces are compared with contact forces measured using an instrumented wheelset. When the system is excited at a frequency where two different wheelset mode shapes, due to the wheel rotation, have coinciding resonance frequencies, significant differences are found in the contact forces calculated with the rotating and non-rotating wheelset models. Further, the use of a flexible, rotating wheelset model is recommended for load cases leading to large magnitude contact force components in the high-frequency range (above 1.5 kHz). In particular, the influence of the radial wheel eigenmodes with two or three nodal diameters is significant.

Remote Sensing of Aerosols from Satellites: Why Has It Been Do Difficult to Quantify Aerosol-Cloud Interactions for Climate Assessment, and How Can We Make Progress?

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.

2015-01-01

The organizers of the National Academy of Sciences Arthur M. Sackler Colloquia Series on Improving Our Fundamental Understanding of the Role of Aerosol-Cloud Interactions in the Climate System would like to post Ralph Kahn's presentation entitled Remote Sensing of Aerosols from Satellites: Why has it been so difficult to quantify aerosol-cloud interactions for climate assessment, and how can we make progress? to their public website.

Effects of Lipid Composition on Bilayer Membranes Quantified by All-Atom Molecular Dynamics.

PubMed

Ding, Wei; Palaiokostas, Michail; Wang, Wen; Orsi, Mario

2015-12-10

Biological bilayer membranes typically contain varying amounts of lamellar and nonlamellar lipids. Lamellar lipids, such as dioleoylphosphatidylcholine (DOPC), are defined by their tendency to form the lamellar phase, ubiquitous in biology. Nonlamellar lipids, such as dioleoylphosphatidylethanolamine (DOPE), prefer instead to form nonlamellar phases, which are mostly nonbiological. However, nonlamellar lipids mix with lamellar lipids in biomembrane structures that remain overall lamellar. Importantly, changes in the lamellar vs nonlamellar lipid composition are believed to affect membrane function and modulate membrane proteins. In this work, we employ atomistic molecular dynamics simulations to quantify how a range of bilayer properties are altered by variations in the lamellar vs nonlamellar lipid composition. Specifically, we simulate five DOPC/DOPE bilayers at mixing ratios of 1/0, 3/1, 1/1, 1/3, and 0/1. We examine properties including lipid area and bilayer thickness, as well as the transmembrane profiles of electron density, lateral pressure, electric field, and dipole potential. While the bilayer structure is only marginally altered by lipid composition changes, dramatic effects are observed for the lateral pressure, electric field, and dipole potential profiles. Possible implications for membrane function are discussed.

Molecular dynamics simulations of membrane proteins and their interactions: from nanoscale to mesoscale.

PubMed

Chavent, Matthieu; Duncan, Anna L; Sansom, Mark Sp

2016-10-01

Molecular dynamics simulations provide a computational tool to probe membrane proteins and systems at length scales ranging from nanometers to close to a micrometer, and on microsecond timescales. All atom and coarse-grained simulations may be used to explore in detail the interactions of membrane proteins and specific lipids, yielding predictions of lipid binding sites in good agreement with available structural data. Building on the success of protein-lipid interaction simulations, larger scale simulations reveal crowding and clustering of proteins, resulting in slow and anomalous diffusional dynamics, within realistic models of cell membranes. Current methods allow near atomic resolution simulations of small membrane organelles, and of enveloped viruses to be performed, revealing key aspects of their structure and functionally important dynamics. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Characterization of Hydrophobic Interactions of Polymers with Water and Phospholipid Membranes Using Molecular Dynamics Simulations

NASA Astrophysics Data System (ADS)

Drenscko, Mihaela

Polymers and lipid membranes are both essential soft materials. The structure and hydrophobicity/hydrophilicity of polymers, as well as the solvent they are embedded in, ultimately determines their size and shape. Understating the variation of shape of the polymer as well as its interactions with model biological membranes can assist in understanding the biocompatibility of the polymer itself. Computer simulations, in particular molecular dynamics, can aid in characterization of the interaction of polymers with solvent, as well as polymers with model membranes. In this thesis, molecular dynamics serve to describe polymer interactions with a solvent (water) and with a lipid membrane. To begin with, we characterize the hydrophobic collapse of single polystyrene chains in water using molecular dynamics simulations. Specifically, we calculate the potential of mean force for the collapse of a single polystyrene chain in water using metadynamics, comparing the results between all atomistic with coarse-grained molecular simulation. We next explore the scaling behavior of the collapsed globular shape at the minimum energy configuration, characterized by the radius of gyration, as a function of chain length. The exponent is close to one third, consistent with that predicted for a polymer chain in bad solvent. We also explore the scaling behavior of the Solvent Accessible Surface Area (SASA) as a function of chain length, finding a similar exponent for both all-atomistic and coarse-grained simulations. Furthermore, calculation of the local water density as a function of chain length near the minimum energy configuration suggests that intermediate chain lengths are more likely to form dewetted states, as compared to shorter or longer chain lengths. Next, in order to investigate the molecular interactions between single hydrophobic polymer chains and lipids in biological membranes and at lipid membrane/solvent interface, we perform a series of molecular dynamics simulations of

Predicted Bacterial Interactions Affect in Vivo Microbial Colonization Dynamics in Nematostella

PubMed Central

Domin, Hanna; Zurita-Gutiérrez, Yazmín H.; Scotti, Marco; Buttlar, Jann; Hentschel Humeida, Ute; Fraune, Sebastian

2018-01-01

The maintenance and resilience of host-associated microbiota during development is a fundamental process influencing the fitness of many organisms. Several host properties were identified as influencing factors on bacterial colonization, including the innate immune system, mucus composition, and diet. In contrast, the importance of bacteria–bacteria interactions on host colonization is less understood. Here, we use bacterial abundance data of the marine model organism Nematostella vectensis to reconstruct potential bacteria–bacteria interactions through co-occurrence networks. The analysis indicates that bacteria–bacteria interactions are dynamic during host colonization and change according to the host’s developmental stage. To assess the predictive power of inferred interactions, we tested bacterial isolates with predicted cooperative or competitive behavior for their ability to influence bacterial recolonization dynamics. Within 3 days of recolonization, all tested bacterial isolates affected bacterial community structure, while only competitive bacteria increased bacterial diversity. Only 1 week after recolonization, almost no differences in bacterial community structure could be observed between control and treatments. These results show that predicted competitive bacteria can influence community structure for a short period of time, verifying the in silico predictions. However, within 1 week, the effects of the bacterial isolates are neutralized, indicating a high degree of resilience of the bacterial community. PMID:29740401

Probing Polyoxometalate-Protein Interactions Using Molecular Dynamics Simulations.

PubMed

Solé-Daura, Albert; Goovaerts, Vincent; Stroobants, Karen; Absillis, Gregory; Jiménez-Lozano, Pablo; Poblet, Josep M; Hirst, Jonathan D; Parac-Vogt, Tatjana N; Carbó, Jorge J

2016-10-17

The molecular interactions between the Ce IV -substituted Keggin anion [PW 11 O 39 Ce(OH 2 ) 4 ] 3- (CeK) and hen egg-white lysozyme (HEWL) were investigated by molecular dynamics simulations. The analysis of CeK was compared with the Ce IV -substituted Keggin dimer [(PW 11 O 39 ) 2 Ce] 10- (CeK 2 ) and the Zr IV -substituted Lindqvist anion [W 5 O 18 Zr(OH 2 )(OH)] 3- (ZrL) to understand how POM features such as shape, size, charge, or type of incorporated metal ion influence the POM⋅⋅⋅protein interactions. Simulations revealed two regions of the protein in which the CeK anion interacts strongly: cationic sites formed by Arg21 and by Arg45 and Arg68. The POMs chiefly interact with the side chains of the positively charged (arginines, lysines) and the polar uncharged residues (tyrosines, serines, aspargines) via electrostatic attraction and hydrogen bonding with the oxygen atoms of the POM framework. The CeK anion shows higher protein affinity than the CeK 2 and ZrL anions, because it is less hydrophilic and it has the right size and shape for establishing interactions with several residues simultaneously. The larger, more negatively charged CeK 2 anion has a high solvent-accessible surface, which is sub-optimal for the interaction, while the smaller ZrL anion is highly hydrophilic and cannot efficiently interact with several residues simultaneously. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multiscale modeling of dislocation-precipitate interactions in Fe: From molecular dynamics to discrete dislocations.

PubMed

Lehtinen, Arttu; Granberg, Fredric; Laurson, Lasse; Nordlund, Kai; Alava, Mikko J

2016-01-01

The stress-driven motion of dislocations in crystalline solids, and thus the ensuing plastic deformation process, is greatly influenced by the presence or absence of various pointlike defects such as precipitates or solute atoms. These defects act as obstacles for dislocation motion and hence affect the mechanical properties of the material. Here we combine molecular dynamics studies with three-dimensional discrete dislocation dynamics simulations in order to model the interaction between different kinds of precipitates and a 1/2〈111〉{110} edge dislocation in BCC iron. We have implemented immobile spherical precipitates into the ParaDis discrete dislocation dynamics code, with the dislocations interacting with the precipitates via a Gaussian potential, generating a normal force acting on the dislocation segments. The parameters used in the discrete dislocation dynamics simulations for the precipitate potential, the dislocation mobility, shear modulus, and dislocation core energy are obtained from molecular dynamics simulations. We compare the critical stresses needed to unpin the dislocation from the precipitate in molecular dynamics and discrete dislocation dynamics simulations in order to fit the two methods together and discuss the variety of the relevant pinning and depinning mechanisms.

Quantifying Wheat Sensitivities to Environmental Constraints to Dissect Genotype × Environment Interactions in the Field1[OPEN

PubMed Central

Maphosa, Lance; Kovalchuk, Alex

2017-01-01

Yield is subject to strong genotype-by-environment (G × E) interactions in the field, especially under abiotic constraints such as soil water deficit (drought [D]) and high temperature (heat [H]). Since environmental conditions show strong fluctuations during the whole crop cycle, geneticists usually do not consider environmental measures as quantitative variables but rather as factors in multienvironment analyses. Based on 11 experiments in a field platform with contrasting temperature and soil water deficit, we determined the periods of sensitivity to drought and heat constraints in wheat (Triticum aestivum) and determined the average sensitivities for major yield components. G × E interactions were separated into their underlying components, constitutive genotypic effect (G), G × D, G × H, and G × H × D, and were analyzed for two genotypes, highlighting contrasting responses to heat and drought constraints. We then tested the constitutive and responsive behaviors of two strong quantitative trait loci (QTLs) associated previously with yield components. This analysis confirmed the constitutive effect of the chromosome 1B QTL and explained the G × E interaction of the chromosome 3B QTL by a benefit of one allele when temperature rises. In addition to the method itself, which can be applied to other data sets and populations, this study will support the cloning of a major yield QTL on chromosome 3B that is highly dependent on environmental conditions and for which the climatic interaction is now quantified. PMID:28546436

Dynamical network interactions in distributed control of robots

NASA Astrophysics Data System (ADS)

Buscarino, Arturo; Fortuna, Luigi; Frasca, Mattia; Rizzo, Alessandro

2006-03-01

In this paper the dynamical network model of the interactions within a group of mobile robots is investigated and proposed as a possible strategy for controlling the robots without central coordination. Motivated by the results of the analysis of our simple model, we show that the system performance in the presence of noise can be improved by including long-range connections between the robots. Finally, a suitable strategy based on this model to control exploration and transport is introduced.

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).

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.

Effect of solvation-related interaction on the low-temperature dynamics of proteins

NASA Astrophysics Data System (ADS)

Zuo, Guanghong; Wang, Jun; Qin, Meng; Xue, Bin; Wang, Wei

2010-03-01

The effect of solvation-related interaction on the low-temperature dynamics of proteins is studied by taking into account the desolvation barriers in the interactions of native contacts. It is found out that about the folding transition temperature, the protein folds in a cooperative manner, and the water molecules are expelled from the hydrophobic core at the final stage in the folding process. At low temperature, however, the protein would generally be trapped in many metastable conformations with some water molecules frozen inside the protein. The desolvation takes an important role in these processes. The number of frozen water molecules and that of frozen states of proteins are further analyzed with the methods based on principal component analysis (PCA) and the clustering of conformations. It is found out that both the numbers of frozen water molecules and the frozen states of the protein increase quickly below a certain temperature. Especially, the number of frozen states of the protein increases exponentially following the decrease in the temperature, which resembles the basic features of glassy dynamics. Interestingly, it is observed that the freezing of water molecules and that of protein conformations happen at almost the same temperature. This suggests that the solvation-related interaction performs an important role for the low-temperature dynamics of the model protein.

Optimal bipedal interactions with dynamic terrain: synthesis and analysis via nonlinear programming

NASA Astrophysics Data System (ADS)

Hubicki, Christian; Goldman, Daniel; Ames, Aaron

In terrestrial locomotion, gait dynamics and motor control behaviors are tuned to interact efficiently and stably with the dynamics of the terrain (i.e. terradynamics). This controlled interaction must be particularly thoughtful in bipeds, as their reduced contact points render them highly susceptible to falls. While bipedalism under rigid terrain assumptions is well-studied, insights for two-legged locomotion on soft terrain, such as sand and dirt, are comparatively sparse. We seek an understanding of how biological bipeds stably and economically negotiate granular media, with an eye toward imbuing those abilities in bipedal robots. We present a trajectory optimization method for controlled systems subject to granular intrusion. By formulating a large-scale nonlinear program (NLP) with reduced-order resistive force theory (RFT) models and jamming cone dynamics, the optimized motions are informed and shaped by the dynamics of the terrain. Using a variant of direct collocation methods, we can express all optimization objectives and constraints in closed-form, resulting in rapid solving by standard NLP solvers, such as IPOPT. We employ this tool to analyze emergent features of bipedal locomotion in granular media, with an eye toward robotic implementation.

Effects of ecological interactions and environmental conditions on community dynamics in an estuarine ecosystem

NASA Astrophysics Data System (ADS)

Liu, H.; Minello, T.; Sutton, G.

2016-02-01

Coastal marine ecosystems are both productive and vulnerable to human and natural stressors. Examining the relative importance of fishing, environmental variability, and habitat alteration on ecosystem dynamics is challenging. Intensive harvest and habitat loss have resulted in widespread concerns related to declines in fisheries production, but causal mechanisms are rarely clear. In this study, we modeled trophic dynamics in Galveston Bay, Texas, using fishery-independent catch data for blue crab, shrimp, red drum, Atlantic croaker and spotted seatrout along with habitat information collected by the Texas Parks and Wildlife Department during 1984 - 2014. We developed a multispecies state-space model to examine ecological interactions and partition the relative effects of trophic interactions and environmental conditions on the community dynamics. Preliminary results showed the importance of salinity, density-dependence, and trophic interactions. We are continuing to explore these results from a perspective of fish community compensatory responses to exploitation, reflecting both direct and indirect effects of harvesting under the influence of climate variability.

Quantifying heterogeneity of lesion uptake in dynamic contrast enhanced MRI for breast cancer diagnosis

NASA Astrophysics Data System (ADS)

Karahaliou, A.; Vassiou, K.; Skiadopoulos, S.; Kanavou, T.; Yiakoumelos, A.; Costaridou, L.

2009-07-01

The current study investigates whether texture features extracted from lesion kinetics feature maps can be used for breast cancer diagnosis. Fifty five women with 57 breast lesions (27 benign, 30 malignant) were subjected to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) on 1.5T system. A linear-slope model was fitted pixel-wise to a representative lesion slice time series and fitted parameters were used to create three kinetic maps (wash out, time to peak enhancement and peak enhancement). 28 grey level co-occurrence matrices features were extracted from each lesion kinetic map. The ability of texture features per map in discriminating malignant from benign lesions was investigated using a Probabilistic Neural Network classifier. Additional classification was performed by combining classification outputs of most discriminating feature subsets from the three maps, via majority voting. The combined scheme outperformed classification based on individual maps achieving area under Receiver Operating Characteristics curve 0.960±0.029. Results suggest that heterogeneity of breast lesion kinetics, as quantified by texture analysis, may contribute to computer assisted tissue characterization in DCE-MRI.

Teacher Guidance to Mediate Student Inquiry through Interactive Dynamic Visualizations

ERIC Educational Resources Information Center

Chang, Hsin-Yi

2013-01-01

The purpose of this study is to investigate how three teachers guided their students to learn science using interactive dynamic visualizations incorporated in an inquiry digital unit. The results show that the teachers' guidance varied in frequency, occasion, and content type. Each teacher demonstrated a different instructional approach in…

Novel fine-scale aerial mapping approach quantifies grassland weed cover dynamics and response to management.

PubMed

Malmstrom, Carolyn M; Butterfield, H Scott; Planck, Laura; Long, Christopher W; Eviner, Valerie T

2017-01-01

Invasive weeds threaten the biodiversity and forage productivity of grasslands worldwide. However, management of these weeds is constrained by the practical difficulty of detecting small-scale infestations across large landscapes and by limits in understanding of landscape-scale invasion dynamics, including mechanisms that enable patches to expand, contract, or remain stable. While high-end hyperspectral remote sensing systems can effectively map vegetation cover, these systems are currently too costly and limited in availability for most land managers. We demonstrate application of a more accessible and cost-effective remote sensing approach, based on simple aerial imagery, for quantifying weed cover dynamics over time. In California annual grasslands, the target communities of interest include invasive weedy grasses (Aegilops triuncialis and Elymus caput-medusae) and desirable forage grass species (primarily Avena spp. and Bromus spp.). Detecting invasion of annual grasses into an annual-dominated community is particularly challenging, but we were able to consistently characterize these two communities based on their phenological differences in peak growth and senescence using maximum likelihood supervised classification of imagery acquired twice per year (in mid- and end-of season). This approach permitted us to map weed-dominated cover at a 1-m scale (correctly detecting 93% of weed patches across the landscape) and to evaluate weed cover change over time. We found that weed cover was more pervasive and persistent in management units that had no significant grazing for several years than in those that were grazed, whereas forage cover was more abundant and stable in the grazed units. This application demonstrates the power of this method for assessing fine-scale vegetation transitions across heterogeneous landscapes. It thus provides means for small-scale early detection of invasive species and for testing fundamental questions about landscape dynamics.

Novel fine-scale aerial mapping approach quantifies grassland weed cover dynamics and response to management

PubMed Central

Butterfield, H. Scott; Planck, Laura; Long, Christopher W.; Eviner, Valerie T.

2017-01-01

Invasive weeds threaten the biodiversity and forage productivity of grasslands worldwide. However, management of these weeds is constrained by the practical difficulty of detecting small-scale infestations across large landscapes and by limits in understanding of landscape-scale invasion dynamics, including mechanisms that enable patches to expand, contract, or remain stable. While high-end hyperspectral remote sensing systems can effectively map vegetation cover, these systems are currently too costly and limited in availability for most land managers. We demonstrate application of a more accessible and cost-effective remote sensing approach, based on simple aerial imagery, for quantifying weed cover dynamics over time. In California annual grasslands, the target communities of interest include invasive weedy grasses (Aegilops triuncialis and Elymus caput-medusae) and desirable forage grass species (primarily Avena spp. and Bromus spp.). Detecting invasion of annual grasses into an annual-dominated community is particularly challenging, but we were able to consistently characterize these two communities based on their phenological differences in peak growth and senescence using maximum likelihood supervised classification of imagery acquired twice per year (in mid- and end-of season). This approach permitted us to map weed-dominated cover at a 1-m scale (correctly detecting 93% of weed patches across the landscape) and to evaluate weed cover change over time. We found that weed cover was more pervasive and persistent in management units that had no significant grazing for several years than in those that were grazed, whereas forage cover was more abundant and stable in the grazed units. This application demonstrates the power of this method for assessing fine-scale vegetation transitions across heterogeneous landscapes. It thus provides means for small-scale early detection of invasive species and for testing fundamental questions about landscape dynamics. PMID

Focus: Structure and dynamics of the interfacial layer in polymer nanocomposites with attractive interactions

DOE PAGES

Cheng, Shiwang; Carroll, Bobby; Bocharova, Vera; ...

2017-03-30

In recent years it has become clear that the interfacial layer formed around nanoparticles in polymer nanocomposites (PNCs) is critical for controlling their macroscopic properties. The interfacial layer occupies a significant volume fraction of the polymer matrix in PNCs and creates strong intrinsic heterogeneity in their structure and dynamics. In this paper, we focus on analysis of the structure and dynamics of the interfacial region in model PNCs with well-dispersed, spherical nanoparticles with attractive interactions. First, we discuss several experimental techniques that provide structural and dynamic information on the interfacial region in PNCs. Then, we discuss the role of variousmore » microscopic parameters in controlling structure and dynamics of the interfacial layer. The analysis presented emphasizes the importance of the polymer-nanoparticle interactions for the slowing down dynamics in the interfacial region, while the thickness of the interfacial layer appears to be dependent on chain rigidity, and has been shown to increase with cooling upon approaching the glass transition. Aside from chain rigidity and polymer-nanoparticle interactions, the interfacial layer properties are also affected by the molecular weight of the polymer and the size of the nanoparticles. Finally, in the last part of this focus article, we emphasize the important challenges in the field of polymer nanocomposites and a potential analogy with the behavior observed in thin films.« less

Interaction between telencephalic signals and respiratory dynamics in songbirds

PubMed Central

Méndez, Jorge M.; Mindlin, Gabriel B.

2012-01-01

The mechanisms by which telencephalic areas affect motor activities are largely unknown. They could either take over motor control from downstream motor circuits or interact with the intrinsic dynamics of these circuits. Both models have been proposed for telencephalic control of respiration during learned vocal behavior in birds. The interactive model postulates that simple signals from the telencephalic song control areas are sufficient to drive the nonlinear respiratory network into producing complex temporal sequences. We tested this basic assumption by electrically stimulating telencephalic song control areas and analyzing the resulting respiratory patterns in zebra finches and in canaries. We found strong evidence for interaction between the rhythm of stimulation and the intrinsic respiratory rhythm, including naturally emerging subharmonic behavior and integration of lateralized telencephalic input. The evidence for clear interaction in our experimental paradigm suggests that telencephalic vocal control also uses a similar mechanism. Furthermore, species differences in the response of the respiratory system to stimulation show parallels to differences in the respiratory patterns of song, suggesting that the interactive production of respiratory rhythms is manifested in species-specific specialization of the involved circuitry. PMID:22402649

Quantifying microstructural dynamics and electrochemical activity of graphite and silicon-graphite lithium ion battery anodes

NASA Astrophysics Data System (ADS)

Pietsch, Patrick; Westhoff, Daniel; Feinauer, Julian; Eller, Jens; Marone, Federica; Stampanoni, Marco; Schmidt, Volker; Wood, Vanessa

2016-09-01

Despite numerous studies presenting advances in tomographic imaging and analysis of lithium ion batteries, graphite-based anodes have received little attention. Weak X-ray attenuation of graphite and, as a result, poor contrast between graphite and the other carbon-based components in an electrode pore space renders data analysis challenging. Here we demonstrate operando tomography of weakly attenuating electrodes during electrochemical (de)lithiation. We use propagation-based phase contrast tomography to facilitate the differentiation between weakly attenuating materials and apply digital volume correlation to capture the dynamics of the electrodes during operation. After validating that we can quantify the local electrochemical activity and microstructural changes throughout graphite electrodes, we apply our technique to graphite-silicon composite electrodes. We show that microstructural changes that occur during (de)lithiation of a pure graphite electrode are of the same order of magnitude as spatial inhomogeneities within it, while strain in composite electrodes is locally pronounced and introduces significant microstructural changes.

Quantifying and tuning entanglement for quantum systems

NASA Astrophysics Data System (ADS)

Xu, Qing

A 2D Ising model with transverse field on a triangular lattice is studied using exact diagonalization. The quantum entanglement of the system is quantified by the entanglement of formation. The ground state property of the system is studied and the quantified entanglement is shown to be closely related to the ground state wavefunction while the singularity in the entanglement as a function of the transverse field is a reasonable indicator of the quantum phase transition. In order to tune the entanglement, one can either include an impurity in the otherwise homogeneous system whose strength is tunable, or one can vary the external transverse field as a tuner. The latter kind of tuning involves complicated dynamical properties of the system. From the study of the dynamics on a comparatively smaller system, we provide ways to tune the entanglement without triggering any decoherence. The finite temperature effect is also discussed. Besides showing above physical results, the realization of the trace-minimization method in our system is provided; the scalability of such method to larger systems is argued.

Quantifying Thin Mat Floating Marsh Strength and Interaction with Hydrodynamic Conditions

NASA Astrophysics Data System (ADS)

Collins, J. H., III; Sasser, C.; Willson, C. S.

2016-12-01

Louisiana possesses over 350,000 acres of unique floating vegetated systems known as floating marshes or flotants. Floating marshes make up 70% of the Terrebonne and Barataria basin wetlands and exist in several forms, mainly thick mat or thin mat. Salt-water intrusion, nutria grazing, and high-energy wave events are believed to be some contributing factors to the degradation of floating marshes; however, there has been little investigation into the hydrodynamic effects on their structural integrity. Due to their unique nature, floating marshes could be susceptible to changes in the hydrodynamic environment that may result from proposed river freshwater and sediment diversion projects introducing flow to areas that are typically somewhat isolated. This study aims to improve the understanding of how thin mat floating marshes respond to increased hydrodynamic stresses and, more specifically, how higher water velocities might increase the washout probability of this vegetation type. There are two major components of this research: 1) A thorough measurement of the material properties of the vegetative mats as a root-soil matrix composite material; and 2) An accurate numerical simulation of the hydrodynamics and forces imposed on the floating marsh mats by the flow. To achieve these goals, laboratory and field experiments were conducted using a customized device to measure the bulk properties of typical floating marshes. Additionally, Delft-3D FLOW and ANSYS FLUENT were used to simulate the flow around a series of simplified mat structures in order to estimate the hydrodynamic forcings on the mats. The hydrodynamic forcings are coupled with a material analysis, allowing for a thorough analysis of their interaction under various conditions. The 2-way Fluid Structure Interaction (F.S.I.) between the flow and the mat is achieved by coupling a Finite Element Analysis (F.E.A.) solver in ANSYS with FLUENT. The flow conditions necessary for the structural failure of the

Dynamic interactions between a membrane binding protein and lipids induce fluctuating diffusivity

PubMed Central

Yamamoto, Eiji; Akimoto, Takuma; Kalli, Antreas C.; Yasuoka, Kenji; Sansom, Mark S. P.

2017-01-01

Pleckstrin homology (PH) domains are membrane-binding lipid recognition proteins that interact with phosphatidylinositol phosphate (PIP) molecules in eukaryotic cell membranes. Diffusion of PH domains plays a critical role in biological reactions on membrane surfaces. Although diffusivity can be estimated by long-time measurements, it lacks information on the short-time diffusive nature. We reveal two diffusive properties of a PH domain bound to the surface of a PIP-containing membrane using molecular dynamics simulations. One is fractional Brownian motion, attributed to the motion of the lipids with which the PH domain interacts. The other is temporally fluctuating diffusivity; that is, the short-time diffusivity of the bound protein changes substantially with time. Moreover, the diffusivity for short-time measurements is intrinsically different from that for long-time measurements. This fluctuating diffusivity results from dynamic changes in interactions between the PH domain and PIP molecules. Our results provide evidence that the complexity of protein-lipid interactions plays a crucial role in the diffusion of proteins on biological membrane surfaces. Changes in the diffusivity of PH domains and related membrane-bound proteins may in turn contribute to the formation/dissolution of protein complexes in membranes. PMID:28116358

New Frontiers in Analyzing Dynamic Group Interactions: Bridging Social and Computer Science.

PubMed

Lehmann-Willenbrock, Nale; Hung, Hayley; Keyton, Joann

2017-10-01

This special issue on advancing interdisciplinary collaboration between computer scientists and social scientists documents the joint results of the international Lorentz workshop, "Interdisciplinary Insights into Group and Team Dynamics," which took place in Leiden, The Netherlands, July 2016. An equal number of scholars from social and computer science participated in the workshop and contributed to the papers included in this special issue. In this introduction, we first identify interaction dynamics as the core of group and team models and review how scholars in social and computer science have typically approached behavioral interactions in groups and teams. Next, we identify key challenges for interdisciplinary collaboration between social and computer scientists, and we provide an overview of the different articles in this special issue aimed at addressing these challenges.

Effect of Dynamical Phase on the Resonant Interaction Among Tsunami Edge Wave Modes

NASA Astrophysics Data System (ADS)

Geist, Eric L.

2018-02-01

Different modes of tsunami edge waves can interact through nonlinear resonance. During this process, edge waves that have very small initial amplitude can grow to be as large or larger than the initially dominant edge wave modes. In this study, the effects of dynamical phase are established for a single triad of edge waves that participate in resonant interactions. In previous studies, Jacobi elliptic functions were used to describe the slow variation in amplitude associated with the interaction. This analytical approach assumes that one of the edge waves in the triad has zero initial amplitude and that the combined phase of the three waves φ = θ 1 + θ 2 - θ 3 is constant at the value for maximum energy exchange (φ = 0). To obtain a more general solution, dynamical phase effects and non-zero initial amplitudes for all three waves are incorporated using numerical methods for the governing differential equations. Results were obtained using initial conditions calculated from a subduction zone, inter-plate thrust fault geometry and a stochastic earthquake slip model. The effect of dynamical phase is most apparent when the initial amplitudes and frequencies of the three waves are within an order of magnitude. In this case, non-zero initial phase results in a marked decrease in energy exchange and a slight decrease in the period of the interaction. When there are large differences in frequency and/or initial amplitude, dynamical phase has less of an effect and typically one wave of the triad has very little energy exchange with the other two waves. Results from this study help elucidate under what conditions edge waves might be implicated in late, large-amplitude arrivals.

Effect of Dynamical Phase on the Resonant Interaction Among Tsunami Edge Wave Modes

NASA Astrophysics Data System (ADS)

Geist, Eric L.

2018-04-01

Different modes of tsunami edge waves can interact through nonlinear resonance. During this process, edge waves that have very small initial amplitude can grow to be as large or larger than the initially dominant edge wave modes. In this study, the effects of dynamical phase are established for a single triad of edge waves that participate in resonant interactions. In previous studies, Jacobi elliptic functions were used to describe the slow variation in amplitude associated with the interaction. This analytical approach assumes that one of the edge waves in the triad has zero initial amplitude and that the combined phase of the three waves φ = θ 1 + θ 2 - θ 3 is constant at the value for maximum energy exchange ( φ = 0). To obtain a more general solution, dynamical phase effects and non-zero initial amplitudes for all three waves are incorporated using numerical methods for the governing differential equations. Results were obtained using initial conditions calculated from a subduction zone, inter-plate thrust fault geometry and a stochastic earthquake slip model. The effect of dynamical phase is most apparent when the initial amplitudes and frequencies of the three waves are within an order of magnitude. In this case, non-zero initial phase results in a marked decrease in energy exchange and a slight decrease in the period of the interaction. When there are large differences in frequency and/or initial amplitude, dynamical phase has less of an effect and typically one wave of the triad has very little energy exchange with the other two waves. Results from this study help elucidate under what conditions edge waves might be implicated in late, large-amplitude arrivals.

Interacting opinion and disease dynamics in multiplex networks: Discontinuous phase transition and nonmonotonic consensus times

NASA Astrophysics Data System (ADS)

Velásquez-Rojas, Fátima; Vazquez, Federico

2017-05-01

Opinion formation and disease spreading are among the most studied dynamical processes on complex networks. In real societies, it is expected that these two processes depend on and affect each other. However, little is known about the effects of opinion dynamics over disease dynamics and vice versa, since most studies treat them separately. In this work we study the dynamics of the voter model for opinion formation intertwined with that of the contact process for disease spreading, in a population of agents that interact via two types of connections, social and contact. These two interacting dynamics take place on two layers of networks, coupled through a fraction q of links present in both networks. The probability that an agent updates its state depends on both the opinion and disease states of the interacting partner. We find that the opinion dynamics has striking consequences on the statistical properties of disease spreading. The most important is that the smooth (continuous) transition from a healthy to an endemic phase observed in the contact process, as the infection probability increases beyond a threshold, becomes abrupt (discontinuous) in the two-layer system. Therefore, disregarding the effects of social dynamics on epidemics propagation may lead to a misestimation of the real magnitude of the spreading. Also, an endemic-healthy discontinuous transition is found when the coupling q overcomes a threshold value. Furthermore, we show that the disease dynamics delays the opinion consensus, leading to a consensus time that varies nonmonotonically with q in a large range of the model's parameters. A mean-field approach reveals that the coupled dynamics of opinions and disease can be approximately described by the dynamics of the voter model decoupled from that of the contact process, with effective probabilities of opinion and disease transmission.

The Dynamic Reactance Interaction - How Vested Interests Affect People's Experience, Behavior, and Cognition in Social Interactions.

PubMed

Steindl, Christina; Jonas, Eva

2015-01-01

In social interactions, individuals may sometimes pursue their own interests at the expense of their interaction partner. Such self-interested behaviors impose a threat to the interaction partner's freedom to act. The current article investigates this threat in the context of interdependence and reactance theory. We explore how vested interests influence reactance process stages of an advisor-client interaction. We aim to explore the interactional process that evolves. In two studies, participants took the perspective of a doctor (advisor) or a patient (client). In both studies we incorporated a vested interest. In Study 1 (N = 82) we found that in response to a vested interest of their interaction partner, patients indicated a stronger experience of reactance, more aggressive behavioral intentions, and more biased cognitions than doctors. A serial multiple mediation revealed that a vested interest engendered mistrust toward the interaction partner and this mistrust led to an emerging reactance process. Study 2 (N = 207) further demonstrated that doctors expressed their reactance in a subtle way: they revealed a classic confirmation bias when searching for additional information on their preliminary decision preference, indicating stronger defense motivation. We discuss how these findings can help us to understand how social interactions develop dynamically.

Brownian dynamics simulations of a flexible polymer chain which includes continuous resistance and multibody hydrodynamic interactions

NASA Astrophysics Data System (ADS)

Butler, Jason E.; Shaqfeh, Eric S. G.

2005-01-01

Using methods adapted from the simulation of suspension dynamics, we have developed a Brownian dynamics algorithm with multibody hydrodynamic interactions for simulating the dynamics of polymer molecules. The polymer molecule is modeled as a chain composed of a series of inextensible, rigid rods with constraints at each joint to ensure continuity of the chain. The linear and rotational velocities of each segment of the polymer chain are described by the slender-body theory of Batchelor [J. Fluid Mech. 44, 419 (1970)]. To include hydrodynamic interactions between the segments of the chain, the line distribution of forces on each segment is approximated by making a Legendre polynomial expansion of the disturbance velocity on the segment, where the first two terms of the expansion are retained in the calculation. Thus, the resulting linear force distribution is specified by a center of mass force, couple, and stresslet on each segment. This method for calculating the hydrodynamic interactions has been successfully used to simulate the dynamics of noncolloidal suspensions of rigid fibers [O. G. Harlen, R. R. Sundararajakumar, and D. L. Koch, J. Fluid Mech. 388, 355 (1999); J. E. Butler and E. S. G. Shaqfeh, J. Fluid Mech. 468, 204 (2002)]. The longest relaxation time and center of mass diffusivity are among the quantities calculated with the simulation technique. Comparisons are made for different levels of approximation of the hydrodynamic interactions, including multibody interactions, two-body interactions, and the "freely draining" case with no interactions. For the short polymer chains studied in this paper, the results indicate a difference in the apparent scaling of diffusivity with polymer length for the multibody versus two-body level of approximation for the hydrodynamic interactions.

Phonon-magnon interaction in low dimensional quantum magnets observed by dynamic heat transport measurements.

PubMed

Montagnese, Matteo; Otter, Marian; Zotos, Xenophon; Fishman, Dmitry A; Hlubek, Nikolai; Mityashkin, Oleg; Hess, Christian; Saint-Martin, Romuald; Singh, Surjeet; Revcolevschi, Alexandre; van Loosdrecht, Paul H M

2013-04-05

Thirty-five years ago, Sanders and Walton [Phys. Rev. B 15, 1489 (1977)] proposed a method to measure the phonon-magnon interaction in antiferromagnets through thermal transport which so far has not been verified experimentally. We show that a dynamical variant of this approach allows direct extraction of the phonon-magnon equilibration time, yielding 400 μs for the cuprate spin-ladder system Ca(9)La(5)Cu(24)O(41). The present work provides a general method to directly address the spin-phonon interaction by means of dynamical transport experiments.

The effect of side motion in the dynamics of interacting molecular motors

NASA Astrophysics Data System (ADS)

Midha, Tripti; Gupta, Arvind Kumar; Kolomeisky, Anatoly B.

2017-07-01

To mimic the collective motion of interacting molecular motors, we propose and discuss an open two-lane symmetrically coupled interactive TASEP model that incorporates interaction in the thermodynamically consistent fashion. We study the effect of both repulsive and attractive interaction on the system’s dynamical properties using various cluster mean field analysis and extensive Monte Carlo simulations. The interactions bring correlations into the system, which were found to be reduced due to the side motion of particles. We produce the steady-state phase diagrams for symmetrically split interaction strength. The behavior of the maximal particle current with respect to the interaction energy E is analyzed for different coupling rates and interaction splittings. The results suggest that for strong coupling and large splittings, the maximal flow of the motors occurs at a weak attractive interaction strength which matches with the known experimental results on kinesin motor protein.

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.

Laplace-SGBEM analysis of the dynamic stress intensity factors and the dynamic T-stress for the interaction between a crack and auxetic inclusions

NASA Astrophysics Data System (ADS)

Kwon, Kibum

A dynamic analysis of the interaction between a crack and an auxetic (negative Poisson ratio)/non-auxetic inclusion is presented. The two most important fracture parameters, namely the stress intensity factors and the T-stress are analyzed by using the symmetric Galerkin boundary element method in the Laplace domain for three different models of crack-inclusion interaction. To investigate the effects of auxetic inclusions on the fracture behavior of composites reinforced by this new type of material, comparisons of the dynamic stress intensity factors and the dynamic T-stress are made between the use of auxetic inclusions as opposed to the use of traditional inclusions. Furthermore, the technique presented in this research can be employed to analyze for the interaction between a crack and a cluster of auxetic/non-auxetic inclusions. Results from the latter models can be employed in crack growth analysis in auxetic-fiber-reinforced composites.

Neotropical fish-fruit interactions: eco-evolutionary dynamics and conservation.

PubMed

Correa, Sandra Bibiana; Costa-Pereira, Raul; Fleming, Theodore; Goulding, Michael; Anderson, Jill T

2015-11-01

Frugivorous fish play a prominent role in seed dispersal and reproductive dynamics of plant communities in riparian and floodplain habitats of tropical regions worldwide. In Neotropical wetlands, many plant species have fleshy fruits and synchronize their fruiting with the flood season, when fruit-eating fish forage in forest and savannahs for periods of up to 7 months. We conducted a comprehensive analysis to examine the evolutionary origin of fish-fruit interactions, describe fruit traits associated with seed dispersal and seed predation, and assess the influence of fish size on the effectiveness of seed dispersal by fish (ichthyochory). To date, 62 studies have documented 566 species of fruits and seeds from 82 plant families in the diets of 69 Neotropical fish species. Fish interactions with flowering plants are likely to be as old as 70 million years in the Neotropics, pre-dating most modern bird-fruit and mammal-fruit interactions, and contributing to long-distance seed dispersal and possibly the radiation of early angiosperms. Ichthyochory occurs across the angiosperm phylogeny, and is more frequent among advanced eudicots. Numerous fish species are capable of dispersing small seeds, but only a limited number of species can disperse large seeds. The size of dispersed seeds and the probability of seed dispersal both increase with fish size. Large-bodied species are the most effective seed dispersal agents and remain the primary target of fishing activities in the Neotropics. Thus, conservation efforts should focus on these species to ensure continuity of plant recruitment dynamics and maintenance of plant diversity in riparian and floodplain ecosystems. © 2015 Cambridge Philosophical Society.

A Qualitative Model of Human Interaction with Complex Dynamic Systems

NASA Technical Reports Server (NTRS)

Hess, Ronald A.

1987-01-01

A qualitative model describing human interaction with complex dynamic systems is developed. The model is hierarchical in nature and consists of three parts: a behavior generator, an internal model, and a sensory information processor. The behavior generator is responsible for action decomposition, turning higher level goals or missions into physical action at the human-machine interface. The internal model is an internal representation of the environment which the human is assumed to possess and is divided into four submodel categories. The sensory information processor is responsible for sensory composition. All three parts of the model act in consort to allow anticipatory behavior on the part of the human in goal-directed interaction with dynamic systems. Human workload and error are interpreted in this framework, and the familiar example of an automobile commute is used to illustrate the nature of the activity in the three model elements. Finally, with the qualitative model as a guide, verbal protocols from a manned simulation study of a helicopter instrument landing task are analyzed with particular emphasis on the effect of automation on human-machine performance.

A qualitative model of human interaction with complex dynamic systems

NASA Technical Reports Server (NTRS)

Hess, Ronald A.

1987-01-01

A qualitative model describing human interaction with complex dynamic systems is developed. The model is hierarchical in nature and consists of three parts: a behavior generator, an internal model, and a sensory information processor. The behavior generator is responsible for action decomposition, turning higher level goals or missions into physical action at the human-machine interface. The internal model is an internal representation of the environment which the human is assumed to possess and is divided into four submodel categories. The sensory information processor is responsible for sensory composition. All three parts of the model act in consort to allow anticipatory behavior on the part of the human in goal-directed interaction with dynamic systems. Human workload and error are interpreted in this framework, and the familiar example of an automobile commute is used to illustrate the nature of the activity in the three model elements. Finally, with the qualitative model as a guide, verbal protocols from a manned simulation study of a helicopter instrument landing task are analyzed with particular emphasis on the effect of automation on human-machine performance.

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.

Modeling the Effect of Fluid-Structure Interaction on the Impact Dynamics of Pressurized Tank Cars

DOT National Transportation Integrated Search

2009-11-13

This paper presents a computational framework that : analyzes the effect of fluid-structure interaction (FSI) on the : impact dynamics of pressurized commodity tank cars using the : nonlinear dynamic finite element code ABAQUS/Explicit. : There exist...

Joint symbolic dynamic analysis of cardiorespiratory interactions in patients on weaning trials.

PubMed

Caminal, P; Giraldo, B; Zabaleta, H; Vallverdu, M; Benito, S; Ballesteros, D; Lopez-Rodriguez, L; Esteban, A; Baumert, M; Voss, A

2005-01-01

Assessing autonomic control provides information about patho-physiological imbalances. Measures of variability of the cardiac interbeat duration RR(n) and the variability of the breath duration TTot(n) are sensitive to those changes. The interactions between RR(n) and TTot(n) are complex and strongly non-linear. A study of joint symbolic dynamics is presented as a new short-term non-linear analysis method to investigate these interactions in patients on weaning trials. 78 patients from mechanical ventilation are studied: Group A (patients that failed to maintain spontaneous breathing and were reconnected) and Group B (patients with successful trials). Using the concept of joint symbolic dynamics, cardiac and respiratory changes were transformed into a word series, and the probability of occurrence of each word type was calculated and compared between both groups. Significant differences were found in 13 words, and the most significant pn(Wc010, r010): 0.0041 ± 0.0036 (group A) against 0.0012 ± 0.0024 (group B), p-value = 0.00001. The number of seldom occurring word types (forbidden words) also presents significant differences fwcr: 6.9 ± 6.6 against 13.5 ± 5.3, p-value = 0.00004. Joint symbolic dynamics provides an efficient non-linear representation of cardiorespiratory interactions that offers simple physiological interpretations.

An Empirical Validation of a Dynamic Systems Model of Interaction: Do Children of Different Sociometric Statuses Differ in Their Dyadic Play?

ERIC Educational Resources Information Center

Steenbeek, Henderien; van Geert, Paul

2008-01-01

Studying short-term dynamic processes and change mechanisms in interaction yields important knowledge that contributes to understanding long-term social development of children. In order to get a grip on this short-term dynamics of interaction processes, the authors made a dynamic systems model of dyadic interaction of children during one play…

Quantifying covalent interactions with resonant inelastic soft X-ray scattering: Case study of Ni 2+ aqua complex

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

Kunnus, K.; Josefsson, I.; Schreck, S.

We analyze the effects of covalent interactions in Ni 2p3d resonant inelastic X-ray scattering (RIXS) spectra from aqueous Ni 2+ ions and find that the relative RIXS intensities of ligand-to-metal charge-transfer final states with respect to the ligand-field final states reflect the covalent mixing between Ni 3d and water orbitals. Specifically, the experimental intensity ratio at the Ni L 3-edge allows to determine that the Ni 3d orbitals have on average 5.5% of water character. Here, we propose that 2p3d RIXS at the Ni L 3-edge can be utilized to quantify covalency in Ni complexes without the use of externalmore » references or simulations.« less

Quantifying covalent interactions with resonant inelastic soft X-ray scattering: Case study of Ni 2+ aqua complex

DOE PAGES

Kunnus, K.; Josefsson, I.; Schreck, S.; ...

2016-12-23

We analyze the effects of covalent interactions in Ni 2p3d resonant inelastic X-ray scattering (RIXS) spectra from aqueous Ni 2+ ions and find that the relative RIXS intensities of ligand-to-metal charge-transfer final states with respect to the ligand-field final states reflect the covalent mixing between Ni 3d and water orbitals. Specifically, the experimental intensity ratio at the Ni L 3-edge allows to determine that the Ni 3d orbitals have on average 5.5% of water character. Here, we propose that 2p3d RIXS at the Ni L 3-edge can be utilized to quantify covalency in Ni complexes without the use of externalmore » references or simulations.« less

A hierarchical dislocation-grain boundary interaction model based on 3D discrete dislocation dynamics and molecular dynamics

NASA Astrophysics Data System (ADS)

Gao, Yuan; Zhuang, Zhuo; You, XiaoChuan

2011-04-01

We develop a new hierarchical dislocation-grain boundary (GB) interaction model to predict the mechanical behavior of polycrystalline metals at micro and submicro scales by coupling 3D Discrete Dislocation Dynamics (DDD) simulation with the Molecular Dynamics (MD) simulation. At the microscales, the DDD simulations are responsible for capturing the evolution of dislocation structures; at the nanoscales, the MD simulations are responsible for obtaining the GB energy and ISF energy which are then transferred hierarchically to the DDD level. In the present model, four kinds of dislocation-GB interactions, i.e. transmission, absorption, re-emission and reflection, are all considered. By this methodology, the compression of a Cu micro-sized bi-crystal pillar is studied. We investigate the characteristic mechanical behavior of the bi-crystal compared with that of the single-crystal. Moreover, the comparison between the present penetrable model of GB and the conventional impenetrable model also shows the accuracy and efficiency of the present model.

Flocking dynamics with voter-like interactions

NASA Astrophysics Data System (ADS)

Baglietto, Gabriel; Vazquez, Federico

2018-03-01

We study the collective motion of a large set of self-propelled particles subject to voter-like interactions. Each particle moves on a 2D space at a constant speed in a direction that is randomly assigned initially. Then, at every step of the dynamics, each particle adopts the direction of motion of a randomly chosen neighboring particle. We investigate the time evolution of the global alignment of particles measured by the order parameter φ, until complete order \\varphi=1.0 is reached (polar consensus). We find that φ increases as t 1/2 for short times and approaches 1.0 exponentially fast for longer times. Also, the mean time to consensus τ varies non-monotonically with the density of particles ρ, reaching a minimum at some intermediate density ρmin . At ρmin , the mean consensus time scales with the system size N as τmin ∼ N0.765 , and thus the consensus is faster than in the case of all-to-all interactions (large ρ) where τ=2N . We show that the fast consensus, also observed at intermediate and high densities, is a consequence of the segregation of the system into clusters of equally-oriented particles which breaks the balance of transitions between directional states in well mixed systems.

Dynamic Ice-Water Interactions Form Europa's Chaos Terrains

NASA Astrophysics Data System (ADS)

Blankenship, D. D.; Schmidt, B. E.; Patterson, G. W.; Schenk, P.

2011-12-01

Unique to the surface of Europa, chaos terrain is diagnostic of the properties and dynamics of its icy shell. We present a new model that suggests large melt lenses form within the shell and that water-ice interactions above and within these lenses drive the production of chaos. This model is consistent with key observations of chaos, predicts observables for future missions, and indicates that the surface is likely still active today[1]. We apply lessons from ice-water interaction in the terrestrial cryosphere to hypothesize a dynamic lense-collapse model to for Europa's chaos terrain. Chaos terrain morphology, like that of Conamara chaos and Thera Macula, suggests a four-phase formation [1]: 1) Surface deflection occurs as ice melts over ascending thermal plumes, as regularly occurs on Earth as subglacial volcanoes activate. The same process can occur at Europa if thermal plumes cause pressure melt as they cross ice-impurity eutectics. 2) Resulting hydraulic gradients and driving forces produce a sealed, pressurized melt lense, akin to the hydraulic sealing of subglacial caldera lakes. On Europa, the water cannot escape the lense due to the horizontally continuous ice shell. 3) Extension of the brittle ice lid above the lense opens cracks, allowing for the ice to be hydrofractured by pressurized water. Fracture, brine injection and percolation within the ice and possible iceberg toppling produces ice-melange-like granular matrix material. 4) Refreezing of the melt lense and brine-filled pores and cracks within the matrix results in raised chaos. Brine soaking and injection concentrates the ice in brines and adds water volume to the shell. As this englacial water freezes, the now water-filled ice will expand, not unlike the process of forming pingos and other "expansion ice" phenomena on Earth. The refreezing can raise the surface and create the oft-observed matrix "domes" In this presentation, we describe how catastrophic ice-water interactions on Earth have

Hierarchical organization of eglin c native state dynamics is shaped by competing direct and water-mediated interactions.

PubMed

Materese, Christopher Kroboth; Goldmon, Christa Charisse; Papoian, Garegin A

2008-08-05

The native state dynamics of the small globular serine protease inhibitor eglin c has been studied in a long 336 ns computer simulation in explicit solvent. We have elucidated the energy landscape explored during the course of the simulation by using Principal Component Analysis. We observe several basins in the energy landscape in which the system lingers for extended periods. Through an iterative process we have generated a tree-like hierarchy of states describing the observed dynamics. We observe a range of divergent contact types including salt bridges, hydrogen bonds, hydrophilic interactions, and hydrophobic interactions, pointing to the frustration between competing interactions. Additionally, we find evidence of competing water-mediated interactions. Divergence in water-mediated interactions may be found to supplement existing direct contacts, but they are also found to be independent of such changes. Water-mediated contacts facilitate interactions between residues of like charge as observed in the simulation. Our results provide insight into the complexity of the dynamic native state of a globular protein and directly probe the residual frustration in the native state.

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.

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.

COMPLEX FLARE DYNAMICS INITIATED BY A FILAMENT–FILAMENT INTERACTION

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

Zhu, Chunming; McAteer, R. T. James; Liu, Rui

2015-11-01

We report on an eruption involving a relatively rare filament–filament interaction on 2013 June 21, observed by SDO and STEREO-B. The two filaments were separated in height with a “double-decker” configuration. The eruption of the lower filament began simultaneously with a descent of the upper filament, resulting in a convergence and direct interaction of the two filaments. The interaction was accompanied by the heating of surrounding plasma and an apparent crossing of a loop-like structure through the upper filament. The subsequent coalescence of the filaments drove a bright front ahead of the erupting structures. The whole process was associated withmore » a C3.0 flare followed immediately by an M2.9 flare. Shrinking loops and descending dark voids were observed during the M2.9 flare at different locations above a C-shaped flare arcade as part of the energy release, giving us unique insight into the flare dynamics.« less

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.

Dynamic Plant-Plant-Herbivore Interactions Govern Plant Growth-Defence Integration.

PubMed

de Vries, Jorad; Evers, Jochem B; Poelman, Erik H

2017-04-01

Plants downregulate their defences against insect herbivores upon impending competition for light. This has long been considered a resource trade-off, but recent advances in plant physiology and ecology suggest this mechanism is more complex. Here we propose that to understand why plants regulate and balance growth and defence, the complex dynamics in plant-plant competition and plant-herbivore interactions needs to be considered. Induced growth-defence responses affect plant competition and herbivore colonisation in space and time, which has consequences for the adaptive value of these responses. Assessing these complex interactions strongly benefits from advanced modelling tools that can model multitrophic interactions in space and time. Such an exercise will allow a critical re-evaluation why and how plants integrate defence and competition for light. Copyright © 2016 Elsevier Ltd. All rights reserved.

Parameterization of Ca+2-protein interactions for molecular dynamics simulations.

PubMed

Project, Elad; Nachliel, Esther; Gutman, Menachem

2008-05-01

Molecular dynamics simulations of Ca+2 ions near protein were performed with three force fields: GROMOS96, OPLS-AA, and CHARMM22. The simulations reveal major, force-field dependent, inconsistencies in the interaction between the Ca+2 ions with the protein. The variations are attributed to the nonbonded parameterizations of the Ca+2-carboxylates interactions. The simulations results were compared to experimental data, using the Ca+2-HCOO- equilibrium as a model. The OPLS-AA force field grossly overestimates the binding affinity of the Ca+2 ions to the carboxylate whereas the GROMOS96 and CHARMM22 force fields underestimate the stability of the complex. Optimization of the Lennard-Jones parameters for the Ca+2-carboxylate interactions were carried out, yielding new parameters which reproduce experimental data. Copyright 2007 Wiley Periodicals, Inc.

Quantifying Interactions of Nucleobase Atoms with Model Compounds for the Peptide Backbone and Glutamine and Asparagine Side Chains in Water.

PubMed

Cheng, Xian; Shkel, Irina A; Molzahn, Cristen; Lambert, David; Karim, Rezwana; Record, M Thomas

2018-04-17

Alkylureas display hydrocarbon and amide groups, the primary functional groups of proteins. To obtain the thermodynamic information that is needed to analyze interactions of amides and proteins with nucleobases and nucleic acids, we quantify preferential interactions of alkylureas with nucleobases differing in the amount and composition of water-accessible surface area (ASA) by solubility assays. Using an established additive ASA-based analysis, we interpret these thermodynamic results to determine interactions of each alkylurea with five types of nucleobase unified atoms (carbonyl sp 2 O, amino sp 3 N, ring sp 2 N, methyl sp 3 C, and ring sp 2 C). All alkylureas interact favorably with nucleobase sp 2 C and sp 3 C atoms; these interactions become more favorable with an increasing level of alkylation of urea. Interactions with nucleobase sp 2 O are most favorable for urea, less favorable for methylurea and ethylurea, and unfavorable for dialkylated ureas. Contributions to overall alkylurea-nucleobase interactions from interactions with each nucleobase atom type are proportional to the ASA of that atom type with proportionality constant (interaction strength) α, as observed previously for urea. Trends in α-values for interactions of alkylureas with nucleobase atom types parallel those for corresponding amide compound atom types, offset because nucleobase α-values are more favorable. Comparisons between ethylated and methylated ureas show interactions of amide compound sp 3 C with nucleobase sp 2 C, sp 3 C, sp 2 N, and sp 3 N atoms are favorable while amide sp 3 C-nucleobase sp 2 O interactions are unfavorable. Strongly favorable interactions of urea with nucleobase sp 2 O but weakly favorable interactions with nucleobase sp 3 N indicate that amide sp 2 N-nucleobase sp 2 O and nucleobase sp 3 N-amide sp 2 O hydrogen bonding (NH···O═C) interactions are favorable while amide sp 2 N-nucleobase sp 3 N interactions are unfavorable. These favorable amide

Dynamics of a suspension of interacting yolk-shell particles

DOE PAGES

Sánchez Díaz, L. E.; Cortes-Morales, E. C.; Li, X.; ...

2014-12-01

In this work we study the self-diusion properties of a liquid of hollow spherical particles (shells) bearing a smaller solid sphere in their interior (yolks). We model this system using purely repulsive hard-body interactions between all (shell and yolk) particles, but assume the presence of a background ideal solvent such that all the particles execute free Brownian motion between collisions, characterized by short-time self-diusion coecients D0 s for the shells and D0 y for the yolks. Using a softened version of these interparticle potentials we perform Brownian dynamics simulations to determine the mean squared displacement and intermediate scattering function ofmore » the yolk-shell complex. These results can be understood in terms of a set of eective Langevin equations for the N interacting shell particles, pre-averaged over the yolks' degrees of freedom, from which an approximate self-consistent description of the simulated self-diusion properties can be derived. Here we compare the theoretical and simulated results between them, and with the results for the same system in the absence of yolks. We nd that the yolks, which have no eect on the shell-shell static structure, in uence the dynamic properties in a predictable manner, fully captured by the theory.« less

Reconsideration of dynamic force spectroscopy analysis of streptavidin-biotin interactions.

PubMed

Taninaka, Atsushi; Takeuchi, Osamu; Shigekawa, Hidemi

2010-05-13

To understand and design molecular functions on the basis of molecular recognition processes, the microscopic probing of the energy landscapes of individual interactions in a molecular complex and their dependence on the surrounding conditions is of great importance. Dynamic force spectroscopy (DFS) is a technique that enables us to study the interaction between molecules at the single-molecule level. However, the obtained results differ among previous studies, which is considered to be caused by the differences in the measurement conditions. We have developed an atomic force microscopy technique that enables the precise analysis of molecular interactions on the basis of DFS. After verifying the performance of this technique, we carried out measurements to determine the landscapes of streptavidin-biotin interactions. The obtained results showed good agreement with theoretical predictions. Lifetimes were also well analyzed. Using a combination of cross-linkers and the atomic force microscope that we developed, site-selective measurement was carried out, and the steps involved in bonding due to microscopic interactions are discussed using the results obtained by site-selective analysis.

New Frontiers in Analyzing Dynamic Group Interactions: Bridging Social and Computer Science

PubMed Central

Lehmann-Willenbrock, Nale; Hung, Hayley; Keyton, Joann

2017-01-01

This special issue on advancing interdisciplinary collaboration between computer scientists and social scientists documents the joint results of the international Lorentz workshop, “Interdisciplinary Insights into Group and Team Dynamics,” which took place in Leiden, The Netherlands, July 2016. An equal number of scholars from social and computer science participated in the workshop and contributed to the papers included in this special issue. In this introduction, we first identify interaction dynamics as the core of group and team models and review how scholars in social and computer science have typically approached behavioral interactions in groups and teams. Next, we identify key challenges for interdisciplinary collaboration between social and computer scientists, and we provide an overview of the different articles in this special issue aimed at addressing these challenges. PMID:29249891

Effect of dynamical phase on the resonant interaction among tsunami edge wave modes

USGS Publications Warehouse

Geist, Eric L.

2018-01-01

Different modes of tsunami edge waves can interact through nonlinear resonance. During this process, edge waves that have very small initial amplitude can grow to be as large or larger than the initially dominant edge wave modes. In this study, the effects of dynamical phase are established for a single triad of edge waves that participate in resonant interactions. In previous studies, Jacobi elliptic functions were used to describe the slow variation in amplitude associated with the interaction. This analytical approach assumes that one of the edge waves in the triad has zero initial amplitude and that the combined phase of the three waves φ = θ1 + θ2 − θ3 is constant at the value for maximum energy exchange (φ = 0). To obtain a more general solution, dynamical phase effects and non-zero initial amplitudes for all three waves are incorporated using numerical methods for the governing differential equations. Results were obtained using initial conditions calculated from a subduction zone, inter-plate thrust fault geometry and a stochastic earthquake slip model. The effect of dynamical phase is most apparent when the initial amplitudes and frequencies of the three waves are within an order of magnitude. In this case, non-zero initial phase results in a marked decrease in energy exchange and a slight decrease in the period of the interaction. When there are large differences in frequency and/or initial amplitude, dynamical phase has less of an effect and typically one wave of the triad has very little energy exchange with the other two waves. Results from this study help elucidate under what conditions edge waves might be implicated in late, large-amplitude arrivals.

Brownian dynamics simulations of a flexible polymer chain which includes continuous resistance and multibody hydrodynamic interactions.

PubMed

Butler, Jason E; Shaqfeh, Eric S G

2005-01-01

Using methods adapted from the simulation of suspension dynamics, we have developed a Brownian dynamics algorithm with multibody hydrodynamic interactions for simulating the dynamics of polymer molecules. The polymer molecule is modeled as a chain composed of a series of inextensible, rigid rods with constraints at each joint to ensure continuity of the chain. The linear and rotational velocities of each segment of the polymer chain are described by the slender-body theory of Batchelor [J. Fluid Mech. 44, 419 (1970)]. To include hydrodynamic interactions between the segments of the chain, the line distribution of forces on each segment is approximated by making a Legendre polynomial expansion of the disturbance velocity on the segment, where the first two terms of the expansion are retained in the calculation. Thus, the resulting linear force distribution is specified by a center of mass force, couple, and stresslet on each segment. This method for calculating the hydrodynamic interactions has been successfully used to simulate the dynamics of noncolloidal suspensions of rigid fibers [O. G. Harlen, R. R. Sundararajakumar, and D. L. Koch, J. Fluid Mech. 388, 355 (1999); J. E. Butler and E. S. G. Shaqfeh, J. Fluid Mech. 468, 204 (2002)]. The longest relaxation time and center of mass diffusivity are among the quantities calculated with the simulation technique. Comparisons are made for different levels of approximation of the hydrodynamic interactions, including multibody interactions, two-body interactions, and the "freely draining" case with no interactions. For the short polymer chains studied in this paper, the results indicate a difference in the apparent scaling of diffusivity with polymer length for the multibody versus two-body level of approximation for the hydrodynamic interactions. (c) 2005 American Institute of Physics.

Three-dimensional interactive Molecular Dynamics program for the study of defect dynamics in crystals

NASA Astrophysics Data System (ADS)

Patriarca, M.; Kuronen, A.; Robles, M.; Kaski, K.

2007-01-01

The study of crystal defects and the complex processes underlying their formation and time evolution has motivated the development of the program ALINE for interactive molecular dynamics experiments. This program couples a molecular dynamics code to a Graphical User Interface and runs on a UNIX-X11 Window System platform with the MOTIF library, which is contained in many standard Linux releases. ALINE is written in C, thus giving the user the possibility to modify the source code, and, at the same time, provides an effective and user-friendly framework for numerical experiments, in which the main parameters can be interactively varied and the system visualized in various ways. We illustrate the main features of the program through some examples of detection and dynamical tracking of point-defects, linear defects, and planar defects, such as stacking faults in lattice-mismatched heterostructures. Program summaryTitle of program:ALINE Catalogue identifier:ADYJ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADYJ_v1_0 Program obtainable from: CPC Program Library, Queen University of Belfast, N. Ireland Computer for which the program is designed and others on which it has been tested: Computers:DEC ALPHA 300, Intel i386 compatible computers, G4 Apple Computers Installations:Laboratory of Computational Engineering, Helsinki University of Technology, Helsinki, Finland Operating systems under which the program has been tested:True64 UNIX, Linux-i386, Mac OS X 10.3 and 10.4 Programming language used:Standard C and MOTIF libraries Memory required to execute with typical data:6 Mbytes but may be larger depending on the system size No. of lines in distributed program, including test data, etc.:16 901 No. of bytes in distributed program, including test data, etc.:449 559 Distribution format:tar.gz Nature of physical problem:Some phenomena involving defects take place inside three-dimensional crystals at times which can be hardly predicted. For this reason they are

Investigation of the heparin-thrombin interaction by dynamic force spectroscopy.

PubMed

Wang, Congzhou; Jin, Yingzi; Desai, Umesh R; Yadavalli, Vamsi K

2015-06-01

The interaction between heparin and thrombin is a vital step in the blood (anti)coagulation process. Unraveling the molecular basis of the interactions is therefore extremely important in understanding the mechanisms of this complex biological process. In this study, we use a combination of an efficient thiolation chemistry of heparin, a self-assembled monolayer-based single molecule platform, and a dynamic force spectroscopy to provide new insights into the heparin-thrombin interaction from an energy viewpoint at the molecular scale. Well-separated single molecules of heparin covalently attached to mixed self-assembled monolayers are demonstrated, whereby interaction forces with thrombin can be measured via atomic force microscopy-based spectroscopy. Further these interactions are studied at different loading rates and salt concentrations to directly obtain kinetic parameters. An increase in the loading rate shows a higher interaction force between the heparin and thrombin, which can be directly linked to the kinetic dissociation rate constant (koff). The stability of the heparin/thrombin complex decreased with increasing NaCl concentration such that the off-rate was found to be driven primarily by non-ionic forces. These results contribute to understanding the role of specific and nonspecific forces that drive heparin-thrombin interactions under applied force or flow conditions. Copyright © 2015 Elsevier B.V. All rights reserved.

Interactions in Undersaturated and Supersaturated Lysozyme Solutions: Static and Dynamic Light Scattering Results

NASA Technical Reports Server (NTRS)

Muschol, Martin; Rosenberger, Franz

1995-01-01

We have performed multiangle static and dynamic light scattering studies of lysozyme solutions at pH=4.7. The Rayleigh ratio R(sub g) and the collective diffusion coefficient D(sub c) were determined as function of both protein concentration c(sub p) and salt concentration c(sub s) with two different salts. At low salt concentrations, the scattering ratio K(sub c)(sub p)/R(sub theta) and diffusivity increased with protein concentration above the values for a monomeric, ideal solution. With increasing salt concentration this trend was eventually reversed. The hydrodynamic interactions of lysozyme in solution, extracted from the combination of static and dynamic scattering data, decreased significantly with increasing salt concentration. These observations reflect changes in protein interactions, in response to increased salt screening, from net repulsion to net attraction. Both salts had the same qualitative effect, but the quantitative behavior did not scale with the ionic strength of the solution. This indicates the presence of salt specific effects. At low protein concentrations, the slopes of K(sub c)(sub p)/R(sub theta) and D(sub c) vs c(sub p) were obtained. The dependence of the slopes on ionic strength was modeled using a DLVO potential for colloidal interactions of two spheres, with the net protein charge Z(sub e) and Hamaker constant A(sub H) as fitting parameters. The model reproduces the observed variations with ionic strength quite well. Independent fits to the static and dynamic data, however, led to different values of the fitting parameters. These and other shortcomings suggest that colloidal interaction models alone are insufficient to explain protein interactions in solutions.

Inverting dynamic force microscopy: From signals to time-resolved interaction forces

PubMed Central

Stark, Martin; Stark, Robert W.; Heckl, Wolfgang M.; Guckenberger, Reinhard

2002-01-01

Transient forces between nanoscale objects on surfaces govern friction, viscous flow, and plastic deformation, occur during manipulation of matter, or mediate the local wetting behavior of thin films. To resolve transient forces on the (sub) microsecond time and nanometer length scale, dynamic atomic force microscopy (AFM) offers largely unexploited potential. Full spectral analysis of the AFM signal completes dynamic AFM. Inverting the signal formation process, we measure the time course of the force effective at the sensing tip. This approach yields rich insight into processes at the tip and dispenses with a priori assumptions about the interaction, as it relies solely on measured data. Force measurements on silicon under ambient conditions demonstrate the distinct signature of the interaction and reveal that peak forces exceeding 200 nN are applied to the sample in a typical imaging situation. These forces are 2 orders of magnitude higher than those in covalent bonds. PMID:12070341

Environmental variability uncovers disruptive effects of species' interactions on population dynamics.

PubMed

Gudmundson, Sara; Eklöf, Anna; Wennergren, Uno

2015-08-07

How species respond to changes in environmental variability has been shown for single species, but the question remains whether these results are transferable to species when incorporated in ecological communities. Here, we address this issue by analysing the same species exposed to a range of environmental variabilities when (i) isolated or (ii) embedded in a food web. We find that all species in food webs exposed to temporally uncorrelated environments (white noise) show the same type of dynamics as isolated species, whereas species in food webs exposed to positively autocorrelated environments (red noise) can respond completely differently compared with isolated species. This is owing to species following their equilibrium densities in a positively autocorrelated environment that in turn enables species-species interactions to come into play. Our results give new insights into species' response to environmental variation. They especially highlight the importance of considering both species' interactions and environmental autocorrelation when studying population dynamics in a fluctuating environment. © 2015 The Author(s).

Environmental variability uncovers disruptive effects of species' interactions on population dynamics

PubMed Central

Gudmundson, Sara; Eklöf, Anna; Wennergren, Uno

2015-01-01

How species respond to changes in environmental variability has been shown for single species, but the question remains whether these results are transferable to species when incorporated in ecological communities. Here, we address this issue by analysing the same species exposed to a range of environmental variabilities when (i) isolated or (ii) embedded in a food web. We find that all species in food webs exposed to temporally uncorrelated environments (white noise) show the same type of dynamics as isolated species, whereas species in food webs exposed to positively autocorrelated environments (red noise) can respond completely differently compared with isolated species. This is owing to species following their equilibrium densities in a positively autocorrelated environment that in turn enables species–species interactions to come into play. Our results give new insights into species' response to environmental variation. They especially highlight the importance of considering both species' interactions and environmental autocorrelation when studying population dynamics in a fluctuating environment. PMID:26224705

Lipid Interaction Sites on Channels, Transporters and Receptors: Recent Insights from Molecular Dynamics Simulations

PubMed Central

Hedger, George; Sansom, Mark S. P.

2017-01-01

Lipid molecules are able to selectively interact with specific sites on integral membrane proteins, and modulate their structure and function. Identification and characterisation of these sites is of importance for our understanding of the molecular basis of membrane protein function and stability, and may facilitate the design of lipid-like drug molecules. Molecular dynamics simulations provide a powerful tool for the identification of these sites, complementing advances in membrane protein structural biology and biophysics. We describe recent notable biomolecular simulation studies which have identified lipid interaction sites on a range of different membrane proteins. The sites identified in these simulation studies agree well with those identified by complementary experimental techniques. This demonstrates the power of the molecular dynamics approach in the prediction and characterization of lipid interaction sites on integral membrane proteins. PMID:26946244

Perceptions of the Effectiveness of System Dynamics-Based Interactive Learning Environments: An Empirical Study

ERIC Educational Resources Information Center

Qudrat-Ullah, Hassan

2010-01-01

The use of simulations in general and of system dynamics simulation based interactive learning environments (SDILEs) in particular is well recognized as an effective way of improving users' decision making and learning in complex, dynamic tasks. However, the effectiveness of SDILEs in classrooms has rarely been evaluated. This article describes…

Ab Initio Molecular Dynamics Study on the Interactions between Carboxylate Ions and Metal Ions in Water.

PubMed

Mehandzhiyski, Aleksandar Y; Riccardi, Enrico; van Erp, Titus S; Trinh, Thuat T; Grimes, Brian A

2015-08-20

The interaction between a carboxylate anion (deprotonated propanoic acid) and the divalent Mg(2+), Ca(2+), Sr(2+), Ba(2+) metal ions is studied via ab initio molecular dynamics. The main focus of the study is the selectivity of the carboxylate-metal ion interaction in aqueous solution. The interaction is modeled by explicitly accounting for the solvent molecules on a DFT level. The hydration energies of the metal ions along with their diffusion and mobility coefficients are determined and a trend correlated with their ionic radius is found. Subsequently, a series of 16 constrained molecular dynamics simulations for every ion is performed, and the interaction free energy is obtained from thermodynamic integration of the forces between the metal ion and the carboxylate ion. The results indicate that the magnesium ion interacts most strongly with the carboxylate, followed by calcium, strontium, and barium. Because the interaction free energy is not enough to explain the selectivity of the reaction observed experimentally, more detailed analysis is performed on the simulation trajectories to understand the steric changes in the reaction complex during dissociation. The solvent dynamics appear to play an important role during the dissociation of the complex and also in the observed selectivity behavior of the divalent ions.

The interaction of cannibalism and omnivory: consequences for community dynamics.

PubMed

Rudolf, Volker H W

2007-11-01

Although cannibalism is ubiquitous in food webs and frequent in systems where a predator and its prey also share a common resource (intraguild predation, IGP), its impacts on species interactions and the dynamics and structure of communities are still poorly understood. In addition, the few existing studies on cannibalism have generally focused on cannibalism in the top-predator, ignoring that it is frequent at intermediate trophic levels. A set of structured models shows that cannibalism can completely alter the dynamics and structure of three-species IGP systems depending on the trophic position where cannibalism occurs. Contrary to the expectations of simple models, the IG predator can exploit the resources more efficiently when it is cannibalistic, enabling the predator to persist at lower resource densities than the IG prey. Cannibalism in the IG predator can also alter the effect of enrichment, preventing predator-mediated extinction of the IG prey at high productivities predicted by simple models. Cannibalism in the IG prey can reverse the effect of top-down cascades, leading to an increase in the resource with decreasing IG predator density. These predictions are consistent with current data. Overall, cannibalism promotes the coexistence of the IG predator and IG prey. These results indicate that including cannibalism in current models can overcome the discrepancy between theory and empirical data. Thus, we need to measure and account for cannibalistic interactions to reliably predict the structure and dynamics of communities.

Contact processes with competitive dynamics in bipartite lattices: effects of distinct interactions

NASA Astrophysics Data System (ADS)

Pianegonda, Salete; Fiore, Carlos E.

2014-05-01

The two-dimensional contact process (CP) with a competitive dynamics proposed by Martins et al (2011 Phys. Rev. E 84 011125) leads to the appearance of an unusual active-asymmetric phase, in which the system sublattices are unequally populated. It differs from the usual CP only by the fact that particles also interact with their next-nearest neighbor sites via a distinct strength creation rate, and for the inclusion of an inhibition effect, proportional to the local density. Aimed at investigating the robustness of such an asymmetric phase, in this paper we study the influence of distinct interactions for two bidimensional CPs. In the first model, the interaction between first neighbors requires a minimal neighborhood of adjacent particles for creating new offspring, whereas second neighbors interact as usual (e.g. at least one neighboring particle is required). The second model takes the opposite situation, in which the restrictive dynamics is in the interaction between next-nearest neighbor sites. Both models are investigated under mean field theory (MFT) and Monte Carlo simulations. In similarity with results by Martins et al, the inclusion of distinct sublattice interactions maintains the occurrence of an asymmetric active phase and re-entrant transition lines. In contrast, remarkable differences are presented, such as discontinuous phase transitions (even between the active phases), the appearance of tricritical points and the stabilization of active phases under larger values of control parameters. Finally, we have shown that the critical behaviors are not altered due to the change of interactions, in which the absorbing transitions belong to the directed percolation (DP) universality class, whereas second-order active phase transitions belong to the Ising universality class.

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.

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.

Investigating the Role of Large-Scale Domain Dynamics in Protein-Protein Interactions.

PubMed

Delaforge, Elise; Milles, Sigrid; Huang, Jie-Rong; Bouvier, Denis; Jensen, Malene Ringkjøbing; Sattler, Michael; Hart, Darren J; Blackledge, Martin

2016-01-01

Intrinsically disordered linkers provide multi-domain proteins with degrees of conformational freedom that are often essential for function. These highly dynamic assemblies represent a significant fraction of all proteomes, and deciphering the physical basis of their interactions represents a considerable challenge. Here we describe the difficulties associated with mapping the large-scale domain dynamics and describe two recent examples where solution state methods, in particular NMR spectroscopy, are used to investigate conformational exchange on very different timescales.

Investigating the Role of Large-Scale Domain Dynamics in Protein-Protein Interactions

PubMed Central

Delaforge, Elise; Milles, Sigrid; Huang, Jie-rong; Bouvier, Denis; Jensen, Malene Ringkjøbing; Sattler, Michael; Hart, Darren J.; Blackledge, Martin

2016-01-01

Intrinsically disordered linkers provide multi-domain proteins with degrees of conformational freedom that are often essential for function. These highly dynamic assemblies represent a significant fraction of all proteomes, and deciphering the physical basis of their interactions represents a considerable challenge. Here we describe the difficulties associated with mapping the large-scale domain dynamics and describe two recent examples where solution state methods, in particular NMR spectroscopy, are used to investigate conformational exchange on very different timescales. PMID:27679800

Focus on out-of-equilibrium dynamics in strongly interacting one-dimensional systems

NASA Astrophysics Data System (ADS)

Daley, A. J.; Rigol, M.; Weiss, D. S.

2014-09-01

In the past few years, there have been significant advances in understanding out-of-equilibrium dynamics in strongly interacting many-particle quantum systems. This is the case for 1D dynamics, where experimental advances—both with ultracold atomic gases and with solid state systems—have been accompanied by advances in theoretical methods, both analytical and numerical. This ‘focus on’ collection brings together 17 new papers, which together give a representative overview of the recent advances.

Direct Observation of Dynamical Quantum Phase Transitions in an Interacting Many-Body System

NASA Astrophysics Data System (ADS)

Jurcevic, P.; Shen, H.; Hauke, P.; Maier, C.; Brydges, T.; Hempel, C.; Lanyon, B. P.; Heyl, M.; Blatt, R.; Roos, C. F.

2017-08-01

The theory of phase transitions represents a central concept for the characterization of equilibrium matter. In this work we study experimentally an extension of this theory to the nonequilibrium dynamical regime termed dynamical quantum phase transitions (DQPTs). We investigate and measure DQPTs in a string of ions simulating interacting transverse-field Ising models. During the nonequilibrium dynamics induced by a quantum quench we show for strings of up to 10 ions the direct detection of DQPTs by revealing nonanalytic behavior in time. Moreover, we provide a link between DQPTs and the dynamics of other quantities such as the magnetization, and we establish a connection between DQPTs and entanglement production.

Direct Observation of Dynamical Quantum Phase Transitions in an Interacting Many-Body System.

PubMed

Jurcevic, P; Shen, H; Hauke, P; Maier, C; Brydges, T; Hempel, C; Lanyon, B P; Heyl, M; Blatt, R; Roos, C F

2017-08-25

The theory of phase transitions represents a central concept for the characterization of equilibrium matter. In this work we study experimentally an extension of this theory to the nonequilibrium dynamical regime termed dynamical quantum phase transitions (DQPTs). We investigate and measure DQPTs in a string of ions simulating interacting transverse-field Ising models. During the nonequilibrium dynamics induced by a quantum quench we show for strings of up to 10 ions the direct detection of DQPTs by revealing nonanalytic behavior in time. Moreover, we provide a link between DQPTs and the dynamics of other quantities such as the magnetization, and we establish a connection between DQPTs and entanglement production.

Alleles versus genotypes: Genetic interactions and the dynamics of selection in sexual populations

NASA Astrophysics Data System (ADS)

Neher, Richard

2010-03-01

Physical interactions between amino-acids are essential for protein structure and activity, while protein-protein interactions and regulatory interactions are central to cellular function. As a consequence of these interactions, the combined effect of two mutations can differ from the sum of the individual effects of the mutations. This phenomenon of genetic interaction is known as epistasis. However, the importance of epistasis and its effects on evolutionary dynamics are poorly understood, especially in sexual populations where recombination breaks up existing combinations of alleles to produce new ones. Here, we present a computational model of selection dynamics involving many epistatic loci in a recombining population. We demonstrate that a large number of polymorphic interacting loci can, despite frequent recombination, exhibit cooperative behavior that locks alleles into favorable genotypes leading to a population consisting of a set of competing clones. As the recombination rate exceeds a certain critical value this ``genotype selection'' phase disappears in an abrupt transition giving way to ``allele selection'' - the phase where different loci are only weakly correlated as expected in sexually reproducing populations. Clustering of interacting sets of genes on a chromosome leads to the emergence of an intermediate regime, where localized blocks of cooperating alleles lock into genetic modules. Large populations attain highest fitness at a recombination rate just below critical, suggesting that natural selection might tune recombination rates to balance the beneficial aspect of exploration of genotype space with the breaking up of synergistic allele combinations.

Interaction-Dominant Dynamics in Human Cognition: Beyond 1/f[superscript [alpha

ERIC Educational Resources Information Center

Ihlen, Espen A. F.; Vereijken, Beatrix

2010-01-01

It has been suggested that human behavior in general and cognitive performance in particular emerge from coordination between multiple temporal scales. In this article, we provide quantitative support for such a theory of interaction-dominant dynamics in human cognition by using wavelet-based multifractal analysis and accompanying multiplicative…

Molecular Dynamic Simulations of Interaction of an AFM Probe with the Surface of an SCN Sample

NASA Technical Reports Server (NTRS)

Bune, Adris; Kaukler, William; Rose, M. Franklin (Technical Monitor)

2001-01-01

Molecular dynamic (MD) simulations is conducted in order to estimate forces of probe-substrate interaction in the Atomic Force Microscope (AFM). First a review of available molecular dynamic techniques is given. Implementation of MD simulation is based on an object-oriented code developed at the University of Delft. Modeling of the sample material - succinonitrile (SCN) - is based on the Lennard-Jones potentials. For the polystyrene probe an atomic interaction potential is used. Due to object-oriented structure of the code modification of an atomic interaction potential is straight forward. Calculation of melting temperature is used for validation of the code and of the interaction potentials. Various fitting parameters of the probe-substrate interaction potentials are considered, as potentials fitted to certain properties and temperature ranges may not be reliable for the others. This research provides theoretical foundation for an interpretation of actual measurements of an interaction forces using AFM.

A benchmark study for the crown-type splashing dynamics of one- and two-component droplet wall-film interactions

NASA Astrophysics Data System (ADS)

Geppert, A.; Terzis, A.; Lamanna, G.; Marengo, M.; Weigand, B.

2017-12-01

The present paper investigates experimentally the impact dynamics of crown-type splashing for miscible two- and one-component droplet wall-film interactions over a range of Weber numbers and dimensionless film thicknesses. The splashing outcome is parametrised in terms of a set of quantifiable parameters, such as crown height, top and base diameter, wall inclination, number of fingers, and secondary droplet properties. The results show that the outcome of a splashing event is not affected by the choice of similar or dissimilar fluids, provided the dimensionless film thickness is larger than 0.1. Below this threshold, distinctive features of two-component interactions appear, such as hole formation and crown bottom breakdown. The observation of different crown shapes (e.g. V-shaped, cylindrical, and truncated-cone) confirms that vorticity production induces changes in the crown wall inclination, thus affecting the evolution of the crown height and top diameter. The evolution of the crown base diameter, instead, is mainly dependent on the relative importance of liquid inertia and viscous losses in the wall-film. The maximum number of liquid fingers decreases with increasing wall, film thickness, due to the enhanced attenuation of the effect of surface properties on the fingering process. The formation of secondary droplets is also affected by changes in the crown wall inclination. In particular, for truncated-cone shapes the occurrence of crown rim contraction induces a large scatter in the secondary droplet properties. Consequently, empirical models for the maximum number and mean diameter of the secondary droplets are derived for V-shaped crowns, as observed for the hexadecane-Hyspin interactions.